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Please read the following text and answer the question below. <text> iii Tables, Figures, and Boxes v Foreword vii Acknowledgments ix About This Study x Abbreviations xii Executive Summary xiv 1 Introduction 1 Need for the Study 3 The Targeted Sectors 4 2 Market Landscape of Energy Efficiency, Climate-Smart Infrastructure, and E-mobility 7 Understanding the Energy Efficiency and Climate-Smart Infrastructure Energy Savings 7 and Investment Potential Understanding the E-mobility Market Opportunity in India 9 3 Energy-Intensive Sectors and Technologies 11 Mapping Energy-Intensive Sectors (Small and Medium-Sized Enterprises, Commercial Buildings, 11 and E-mobility) Mapping Energy Efficiency Technologies for Energy‑Intensive Small and Medium-Sized Enterprises 13 4 Supply Chain for Energy Efficiency, Climate-Smart Infrastructure, and E-mobility Technologies 23 Energy Efficiency and Climate-Smart Infrastructure Supply Chain for Small and Medium-Sized Enterprises 23 Understanding the E-mobility Supply Chain in India 31 CONTENTS iv Contents 5 Analyzing the Schemes and Policies Landscape 34 Risk Guarantee Schemes 36 List-Based and Technology Approaches 37 Technical Assistance Schemes 39 Understanding the Policy Landscape of India’s Electric Vehicle Ecosystem 41 Policies Supporting Women Entrepreneurship 43 Observations on Financing Schemes 44 6 Strengths, Weaknesses, Opportunities, and Threats Analysis and Policy Recommendations 46 Strengths, Weaknesses, Opportunities, and Threats Analysis and Understanding the Opportunities 46 in Energy Efficiency and Climate-Smart Infrastructure Strengths, Weaknesses, Opportunities, and Threats Analysis and Understanding the Opportunities 48 in E-mobility Financing 7  Barriers and Opportunities in Financing Energy Efficiency, Climate-Smart Infrastructure, 50 and E-mobility Mapping Private Sector Financial Institutions and Nonbanking Financial Companies Working 50 in the Small and Medium-Sized Enterprise Segment Challenges and Barriers to the Financing of Energy Efficiency and Climate-Smart Infrastructure 53 Proposed Solutions for Strengthening Energy Efficiency and Climate-Smart Infrastructure Financing 54 Challenges Associated with Electric Vehicle Financing in Micro, Small, and Medium-Sized Enterprises 57 and Proposed Solutions for Strengthening the E-mobility Ecosystem 8 The Way Forward 60 Appendixes 1 Approach and Methodology for Identifying Sectors with the Most Energy Savings Potential 65 2 Methodology for Short-Listing Prominent Technologies 68 3 Identifying Women-Led Businesses in the Clean Energy Supply Chain 72 4  Long List of Technology and Service Providers in Energy Efficiency, Climate-Smart Infrastructure, 75 and the Electric Vehicle Ecosystem 5 Details of Different Schemes for Energy Efficiency and Climate-Smart Infrastructure 77 6 Observations from Existing Schemes to Expand Lending for Low-Carbon Technologies 88 7 Discussion Guide for Technology Providers 91 8 Discussion Guide for Financial Institutions 95 9 Participating Financial Institutions under Existing and Previous Financing Schemes 98 10 Financial Institutions Short-Listed for Consultations 101 v Tables 1  Projected Energy Consumption of High-Energy Sectors by 2031 1 2  Energy Savings and Investment Potential for Sectors of Economy (until 2031) 2 3  Greenhouse Gas Emission Reduction Potential for Study Sectors 2 4  Sector Energy Efficiency Potential until 2031 7 5  Short-Listed Energy-Intensive Small and Medium-Sized Enterprise Sectors 13 6  Summary of Technologies Based on Short-Listing Criteria 15 7  Electric Vehicle Sales (Actual and Projected) 21 8  Electric Vehicle Business Models and Ecosystem 32 9  Key Features of Different Financing Schemes 35 10  Summary of Key Risk Guarantee Schemes 36 11  Key List-Based and Technology Approaches 38 12  Summary of Technical Assistance-Supported Schemes 40 13  Details of Regulators Developing the Electric Vehicle Ecosystem 41 14  FAME I and FAME II Budget Outlay 43 15  Summary of Key Financing Schemes and Takeaways 44 16  Short-Listed Financial Institutions and Nonbanking Financial Companies 50 17  Expertise Supporting Clean Energy Financing 51 A1 Sector and Subsector Processes and Technologies 67 A3  Women-Led Enterprises Working in the Clean Energy Space 72 A4  Mapping of the Energy Efficiency and Climate-Smart Infrastructure Technology and Service Providers 75 A5  Achievements of the Project 84 A6.1  State-Led Initiatives for E-mobility 89 A6.2  List of Schemes by Financial Institutions for Women Entrepreneurs 90 A10  List of Financial Institutions with Experience 101 TABLES, FIGURES, AND BOXES vi Tables, Figures, and Boxes Figures 1  High Energy-Consuming Subsectors 12 2  Approach for Identifying Most Promising Energy Efficiency and CSI Technologies 13 3  Criteria to Identify Most Relevant Energy Efficiency Technologies 14 4  Methodology Used for Ranking Key Technologies 15 5  Total Costs of Ownership of Electric Vehicles 22 6  Supply Chain Linkages 23 7  Reasons for Lower Adoption of Energy Efficiency Technologies 26 Among Micro, Small, and Medium-Sized Enterprises 8  Preferred Business Models 27 9  Major Hurdles for Energy Services Companies 29 10  Supply Chain of E-mobility 30 11  Value Chain of Electric Mobility 31 12  Financing Schemes Supporting Micro, Small, and Medium-Sized Enterprises in India 34 13  Timeline and Progress of E-mobility, 2011−2022 42 14  Strengths, Weaknesses, Opportunities, and Threats Analysis of the Energy Efficiency 46 and Climate-Smart Infrastructure Financing Ecosystem 15  Strengths, Weaknesses, Opportunities, and Threats Analysis of the E-mobility Financing Ecosystem 48 16  Promoting Investment from the Private Sector 60 A7.1  Discussion Guide for Technology Providers and Energy Service Companies 92 A7.2  Technology Provider Recipients of the Discussion Guide 94 A8.1  Discussion Guide for Financial Institutions 95 A8.2  Financial Institution Recipients of the Discussion Guide 97 Boxes 1 Original Equipment Manufacturers 23 2 Local Service Providers 25 3 Energy Service Companies 28 vii On behalf of the Asian Development Bank (ADB), it is my pleasure to introduce this report Driving Energy-Efficient and Low-Carbon Investments for Small and Medium-Sized Enterprises through the Finance Sector. The report identifies the manufacturing industry, commercial building, and transport sectors in India with a focus on opportunities to scale the participation of small and medium-sized enterprises in adopting low-carbon technologies. These three sectors account for over two-thirds of the Indian energy consumption. The report presents a detailed assessment of energy savings, greenhouse gas emission reduction potential, and investment requirements. India has set a target of a net carbon zero economy by 2070. This country-level commitment—along with India’s nationally determined contributions—places a clear priority and focus on the significant untapped potential to invest in energy efficiency and electric mobility solutions, among other climate-smart infrastructure (CSI) segments. Investments in these sectors face different challenges. Many are well-documented and well-known barriers in the energy efficiency financing space ranging from awareness of suitable technologies or access to suitable financing solutions. Most of the interventions by international development agencies and the Government of India have developed and strengthened the basic framework to promote energy efficiency solutions. There are barriers and challenges in the larger-scale deployment of investments in low-carbon technologies across the target sectors. This report presents a detailed assessment of the market and operational barriers that need to be bridged through innovative financing solutions. Multistakeholder collaboration and innovative solutions are needed to get access to adequate financing suitable to meet the needs of the range of stakeholders in the energy efficiency and low- carbon technology supply chain including energy service companies, small and medium-sized enterprises, original-Cff-C-C-S-m-m-w-m1-w101-C1</text> What is the correct answer to this question: Which of the following would most effectively, as described the report? Choices: (A). (B. (C. (D. Format your response as follows: "The correct answer is (insert answer here)".
265
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3
D
Implementing customized financial products that bundle small loans across multiple SMEs and creating partnerships between financial institutions and original equipment manufacturers (OEMs) to reduce technology costs and mitigate perceived performance risks.
Please read the following text and answer the question below. <text> iii Tables, Figures, and Boxes v Foreword vii Acknowledgments ix About This Study x Abbreviations xii Executive Summary xiv 1 Introduction 1 Need for the Study 3 The Targeted Sectors 4 2 Market Landscape of Energy Efficiency, Climate-Smart Infrastructure, and E-mobility 7 Understanding the Energy Efficiency and Climate-Smart Infrastructure Energy Savings 7 and Investment Potential Understanding the E-mobility Market Opportunity in India 9 3 Energy-Intensive Sectors and Technologies 11 Mapping Energy-Intensive Sectors (Small and Medium-Sized Enterprises, Commercial Buildings, 11 and E-mobility) Mapping Energy Efficiency Technologies for Energy‑Intensive Small and Medium-Sized Enterprises 13 4 Supply Chain for Energy Efficiency, Climate-Smart Infrastructure, and E-mobility Technologies 23 Energy Efficiency and Climate-Smart Infrastructure Supply Chain for Small and Medium-Sized Enterprises 23 Understanding the E-mobility Supply Chain in India 31 CONTENTS iv Contents 5 Analyzing the Schemes and Policies Landscape 34 Risk Guarantee Schemes 36 List-Based and Technology Approaches 37 Technical Assistance Schemes 39 Understanding the Policy Landscape of India’s Electric Vehicle Ecosystem 41 Policies Supporting Women Entrepreneurship 43 Observations on Financing Schemes 44 6 Strengths, Weaknesses, Opportunities, and Threats Analysis and Policy Recommendations 46 Strengths, Weaknesses, Opportunities, and Threats Analysis and Understanding the Opportunities 46 in Energy Efficiency and Climate-Smart Infrastructure Strengths, Weaknesses, Opportunities, and Threats Analysis and Understanding the Opportunities 48 in E-mobility Financing 7  Barriers and Opportunities in Financing Energy Efficiency, Climate-Smart Infrastructure, 50 and E-mobility Mapping Private Sector Financial Institutions and Nonbanking Financial Companies Working 50 in the Small and Medium-Sized Enterprise Segment Challenges and Barriers to the Financing of Energy Efficiency and Climate-Smart Infrastructure 53 Proposed Solutions for Strengthening Energy Efficiency and Climate-Smart Infrastructure Financing 54 Challenges Associated with Electric Vehicle Financing in Micro, Small, and Medium-Sized Enterprises 57 and Proposed Solutions for Strengthening the E-mobility Ecosystem 8 The Way Forward 60 Appendixes 1 Approach and Methodology for Identifying Sectors with the Most Energy Savings Potential 65 2 Methodology for Short-Listing Prominent Technologies 68 3 Identifying Women-Led Businesses in the Clean Energy Supply Chain 72 4  Long List of Technology and Service Providers in Energy Efficiency, Climate-Smart Infrastructure, 75 and the Electric Vehicle Ecosystem 5 Details of Different Schemes for Energy Efficiency and Climate-Smart Infrastructure 77 6 Observations from Existing Schemes to Expand Lending for Low-Carbon Technologies 88 7 Discussion Guide for Technology Providers 91 8 Discussion Guide for Financial Institutions 95 9 Participating Financial Institutions under Existing and Previous Financing Schemes 98 10 Financial Institutions Short-Listed for Consultations 101 v Tables 1  Projected Energy Consumption of High-Energy Sectors by 2031 1 2  Energy Savings and Investment Potential for Sectors of Economy (until 2031) 2 3  Greenhouse Gas Emission Reduction Potential for Study Sectors 2 4  Sector Energy Efficiency Potential until 2031 7 5  Short-Listed Energy-Intensive Small and Medium-Sized Enterprise Sectors 13 6  Summary of Technologies Based on Short-Listing Criteria 15 7  Electric Vehicle Sales (Actual and Projected) 21 8  Electric Vehicle Business Models and Ecosystem 32 9  Key Features of Different Financing Schemes 35 10  Summary of Key Risk Guarantee Schemes 36 11  Key List-Based and Technology Approaches 38 12  Summary of Technical Assistance-Supported Schemes 40 13  Details of Regulators Developing the Electric Vehicle Ecosystem 41 14  FAME I and FAME II Budget Outlay 43 15  Summary of Key Financing Schemes and Takeaways 44 16  Short-Listed Financial Institutions and Nonbanking Financial Companies 50 17  Expertise Supporting Clean Energy Financing 51 A1 Sector and Subsector Processes and Technologies 67 A3  Women-Led Enterprises Working in the Clean Energy Space 72 A4  Mapping of the Energy Efficiency and Climate-Smart Infrastructure Technology and Service Providers 75 A5  Achievements of the Project 84 A6.1  State-Led Initiatives for E-mobility 89 A6.2  List of Schemes by Financial Institutions for Women Entrepreneurs 90 A10  List of Financial Institutions with Experience 101 TABLES, FIGURES, AND BOXES vi Tables, Figures, and Boxes Figures 1  High Energy-Consuming Subsectors 12 2  Approach for Identifying Most Promising Energy Efficiency and CSI Technologies 13 3  Criteria to Identify Most Relevant Energy Efficiency Technologies 14 4  Methodology Used for Ranking Key Technologies 15 5  Total Costs of Ownership of Electric Vehicles 22 6  Supply Chain Linkages 23 7  Reasons for Lower Adoption of Energy Efficiency Technologies 26 Among Micro, Small, and Medium-Sized Enterprises 8  Preferred Business Models 27 9  Major Hurdles for Energy Services Companies 29 10  Supply Chain of E-mobility 30 11  Value Chain of Electric Mobility 31 12  Financing Schemes Supporting Micro, Small, and Medium-Sized Enterprises in India 34 13  Timeline and Progress of E-mobility, 2011−2022 42 14  Strengths, Weaknesses, Opportunities, and Threats Analysis of the Energy Efficiency 46 and Climate-Smart Infrastructure Financing Ecosystem 15  Strengths, Weaknesses, Opportunities, and Threats Analysis of the E-mobility Financing Ecosystem 48 16  Promoting Investment from the Private Sector 60 A7.1  Discussion Guide for Technology Providers and Energy Service Companies 92 A7.2  Technology Provider Recipients of the Discussion Guide 94 A8.1  Discussion Guide for Financial Institutions 95 A8.2  Financial Institution Recipients of the Discussion Guide 97 Boxes 1 Original Equipment Manufacturers 23 2 Local Service Providers 25 3 Energy Service Companies 28 vii On behalf of the Asian Development Bank (ADB), it is my pleasure to introduce this report Driving Energy-Efficient and Low-Carbon Investments for Small and Medium-Sized Enterprises through the Finance Sector. The report identifies the manufacturing industry, commercial building, and transport sectors in India with a focus on opportunities to scale the participation of small and medium-sized enterprises in adopting low-carbon technologies. These three sectors account for over two-thirds of the Indian energy consumption. The report presents a detailed assessment of energy savings, greenhouse gas emission reduction potential, and investment requirements. India has set a target of a net carbon zero economy by 2070. This country-level commitment—along with India’s nationally determined contributions—places a clear priority and focus on the significant untapped potential to invest in energy efficiency and electric mobility solutions, among other climate-smart infrastructure (CSI) segments. Investments in these sectors face different challenges. Many are well-documented and well-known barriers in the energy efficiency financing space ranging from awareness of suitable technologies or access to suitable financing solutions. Most of the interventions by international development agencies and the Government of India have developed and strengthened the basic framework to promote energy efficiency solutions. There are barriers and challenges in the larger-scale deployment of investments in low-carbon technologies across the target sectors. This report presents a detailed assessment of the market and operational barriers that need to be bridged through innovative financing solutions. Multistakeholder collaboration and innovative solutions are needed to get access to adequate financing suitable to meet the needs of the range of stakeholders in the energy efficiency and low- carbon technology supply chain including energy service companies, small and medium-sized enterprises, original-Cff-C-C-S-m-m-w-m1-w101-C1</text> What is the correct answer to this question: Which of the following would most effectively, as described the report? Choices: (A). (B. (C. (D. Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> {"concepts": {"Q7270": {"name": "republic", "subclassOf": ["Q7174"]}, "Q130232": {"name": "drama film", "subclassOf": ["Q21010853"]}, "Q280658": {"name": "forward", "subclassOf": ["Q12737077"]}, "Q8355": {"name": "violin", "subclassOf": ["Q192096"]}, "Q8445": {"name": "marriage", "subclassOf": ["Q1938208"]}, "Q1640319": {"name": "experimental music", "subclassOf": ["Q188451"]}, "Q5043": {"name": "Christianity", "subclassOf": ["Q9174"]}, "Q289": {"name": "television", "subclassOf": ["Q15078788"]}, "Q7168625": {"name": "historical period drama", "subclassOf": ["Q130232"]}, "Q912985": {"name": "running back", "subclassOf": ["Q694589"]}, "Q14212": {"name": "prime minister", "subclassOf": ["Q83307"]}, "Q11404": {"name": "drum", "subclassOf": ["Q1254773"]}, "Q188473": {"name": "action film", "subclassOf": ["Q11424"]}, "Q6607": {"name": "guitar", "subclassOf": []}, "Q163829": {"name": "synthesizer", "subclassOf": ["Q1327500"]}, "Q44148": {"name": "male organism", "subclassOf": ["Q290"]}, "Q21198": {"name": "computer science", "subclassOf": ["Q11862829"]}, "Q381243": {"name": "special effects", "subclassOf": ["Q174923"]}, "Q33999": {"name": "actor", "subclassOf": ["Q483501"]}, "Q7889": {"name": "video game", "subclassOf": ["Q173799"]}, "Q2405480": {"name": "voice actor", "subclassOf": ["Q33999"]}, "Q1860": {"name": "English", "subclassOf": ["Q33742"]}, "Q40831": {"name": "comedy", "subclassOf": ["Q15850590"]}, "Q42178": {"name": "vice president", "subclassOf": ["Q4164871"]}, "Q219557": {"name": "cult film", "subclassOf": ["Q11424"]}, "Q7163": {"name": "politics", "subclassOf": ["Q1914636"]}, "Q9794": {"name": "reggae", "subclassOf": ["Q188451"]}, "Q11023": {"name": "engineering", "subclassOf": ["Q11862829"]}, "Q11366": {"name": "alternative rock", "subclassOf": ["Q11399"]}, "Q5994": {"name": "piano", "subclassOf": ["Q52954"]}, "Q7174": {"name": "democracy", "subclassOf": ["Q1307214"]}, "Q736559": {"name": "secretary of state", "subclassOf": ["Q599151"]}, "Q30461": {"name": "president", "subclassOf": ["Q82955"]}, "Q36180": {"name": "writer", "subclassOf": ["Q482980"]}, "Q36279": {"name": "biography", "subclassOf": ["Q223393"]}, "Q11424": {"name": "film", "subclassOf": ["Q4502142"]}, "Q7749": {"name": "rock and roll", "subclassOf": ["Q373342"]}, "Q16533": {"name": "judge", "subclassOf": ["Q4164871"]}, "Q484641": {"name": "pop rock", "subclassOf": ["Q37073"]}, "Q901": {"name": "scientist", "subclassOf": ["Q1650915"]}, "Q852767": {"name": "Southern rock", "subclassOf": ["Q11399"]}, "Q432": {"name": "Islam", "subclassOf": ["Q9174"]}, "Q8341": {"name": "jazz", "subclassOf": ["Q373342"]}, "Q52954": {"name": "keyboard instrument", "subclassOf": ["Q1254773"]}, "Q28389": {"name": "screenwriter", "subclassOf": ["Q36180"]}, "Q1371925": {"name": "announcer", "subclassOf": ["Q28640"]}, "Q19842222": {"name": "crime fiction", "subclassOf": ["Q8253"]}, "Q49451": {"name": "progressive rock", "subclassOf": ["Q11399"]}, "Q484876": {"name": "chief executive officer", "subclassOf": ["Q28640"]}, "Q37073": {"name": "pop music", "subclassOf": ["Q373342"]}, "Q46185": {"name": "bass guitar", "subclassOf": ["Q810447"]}, "Q17884": {"name": "LGBT", "subclassOf": ["Q918270"]}, "Q2617520": {"name": "steel guitar", "subclassOf": ["Q6607"]}, "Q810447": {"name": "bass", "subclassOf": ["Q34379"]}, "Q319221": {"name": "adventure film", "subclassOf": ["Q11424"]}, "Q182015": {"name": "thriller", "subclassOf": ["Q8253"]}, "Q639669": {"name": "musician", "subclassOf": ["Q483501"]}, "Q2095173": {"name": "jam band", "subclassOf": ["Q215380"]}, "Q1344": {"name": "opera", "subclassOf": ["Q188451"]}, "Q132050": {"name": "governor", "subclassOf": ["Q294414"]}, "Q132311": {"name": "fantasy", "subclassOf": ["Q735"]}, "Q483501": {"name": "artist", "subclassOf": ["Q28640"]}, "Q23540": {"name": "Protestantism", "subclassOf": ["Q5043"]}, "Q1136507": {"name": "electric piano", "subclassOf": ["Q5994"]}, "Q43845": {"name": "businessperson", "subclassOf": ["Q28640"]}, "Q4610556": {"name": "model", "subclassOf": ["Q28640"]}, "Q24925": {"name": "science fiction", "subclassOf": ["Q483394"]}, "Q93204":":0ifiersvalue": "value":typevaluevalue "type inqualtypetypequalqualtypetypequalqual intypetype in in",qualqualqualqualqualqualqualqualqual": [{"objecttypeobjecttypetypekey]}}} </> What the correct answer to this question: Which? Choices: (A (B(C(D Format your response as follows: "The correct answer is (insert answer here)".
266
null
0
A
Q25395
Please read the following text and answer the question below. <text> {"concepts": {"Q7270": {"name": "republic", "subclassOf": ["Q7174"]}, "Q130232": {"name": "drama film", "subclassOf": ["Q21010853"]}, "Q280658": {"name": "forward", "subclassOf": ["Q12737077"]}, "Q8355": {"name": "violin", "subclassOf": ["Q192096"]}, "Q8445": {"name": "marriage", "subclassOf": ["Q1938208"]}, "Q1640319": {"name": "experimental music", "subclassOf": ["Q188451"]}, "Q5043": {"name": "Christianity", "subclassOf": ["Q9174"]}, "Q289": {"name": "television", "subclassOf": ["Q15078788"]}, "Q7168625": {"name": "historical period drama", "subclassOf": ["Q130232"]}, "Q912985": {"name": "running back", "subclassOf": ["Q694589"]}, "Q14212": {"name": "prime minister", "subclassOf": ["Q83307"]}, "Q11404": {"name": "drum", "subclassOf": ["Q1254773"]}, "Q188473": {"name": "action film", "subclassOf": ["Q11424"]}, "Q6607": {"name": "guitar", "subclassOf": []}, "Q163829": {"name": "synthesizer", "subclassOf": ["Q1327500"]}, "Q44148": {"name": "male organism", "subclassOf": ["Q290"]}, "Q21198": {"name": "computer science", "subclassOf": ["Q11862829"]}, "Q381243": {"name": "special effects", "subclassOf": ["Q174923"]}, "Q33999": {"name": "actor", "subclassOf": ["Q483501"]}, "Q7889": {"name": "video game", "subclassOf": ["Q173799"]}, "Q2405480": {"name": "voice actor", "subclassOf": ["Q33999"]}, "Q1860": {"name": "English", "subclassOf": ["Q33742"]}, "Q40831": {"name": "comedy", "subclassOf": ["Q15850590"]}, "Q42178": {"name": "vice president", "subclassOf": ["Q4164871"]}, "Q219557": {"name": "cult film", "subclassOf": ["Q11424"]}, "Q7163": {"name": "politics", "subclassOf": ["Q1914636"]}, "Q9794": {"name": "reggae", "subclassOf": ["Q188451"]}, "Q11023": {"name": "engineering", "subclassOf": ["Q11862829"]}, "Q11366": {"name": "alternative rock", "subclassOf": ["Q11399"]}, "Q5994": {"name": "piano", "subclassOf": ["Q52954"]}, "Q7174": {"name": "democracy", "subclassOf": ["Q1307214"]}, "Q736559": {"name": "secretary of state", "subclassOf": ["Q599151"]}, "Q30461": {"name": "president", "subclassOf": ["Q82955"]}, "Q36180": {"name": "writer", "subclassOf": ["Q482980"]}, "Q36279": {"name": "biography", "subclassOf": ["Q223393"]}, "Q11424": {"name": "film", "subclassOf": ["Q4502142"]}, "Q7749": {"name": "rock and roll", "subclassOf": ["Q373342"]}, "Q16533": {"name": "judge", "subclassOf": ["Q4164871"]}, "Q484641": {"name": "pop rock", "subclassOf": ["Q37073"]}, "Q901": {"name": "scientist", "subclassOf": ["Q1650915"]}, "Q852767": {"name": "Southern rock", "subclassOf": ["Q11399"]}, "Q432": {"name": "Islam", "subclassOf": ["Q9174"]}, "Q8341": {"name": "jazz", "subclassOf": ["Q373342"]}, "Q52954": {"name": "keyboard instrument", "subclassOf": ["Q1254773"]}, "Q28389": {"name": "screenwriter", "subclassOf": ["Q36180"]}, "Q1371925": {"name": "announcer", "subclassOf": ["Q28640"]}, "Q19842222": {"name": "crime fiction", "subclassOf": ["Q8253"]}, "Q49451": {"name": "progressive rock", "subclassOf": ["Q11399"]}, "Q484876": {"name": "chief executive officer", "subclassOf": ["Q28640"]}, "Q37073": {"name": "pop music", "subclassOf": ["Q373342"]}, "Q46185": {"name": "bass guitar", "subclassOf": ["Q810447"]}, "Q17884": {"name": "LGBT", "subclassOf": ["Q918270"]}, "Q2617520": {"name": "steel guitar", "subclassOf": ["Q6607"]}, "Q810447": {"name": "bass", "subclassOf": ["Q34379"]}, "Q319221": {"name": "adventure film", "subclassOf": ["Q11424"]}, "Q182015": {"name": "thriller", "subclassOf": ["Q8253"]}, "Q639669": {"name": "musician", "subclassOf": ["Q483501"]}, "Q2095173": {"name": "jam band", "subclassOf": ["Q215380"]}, "Q1344": {"name": "opera", "subclassOf": ["Q188451"]}, "Q132050": {"name": "governor", "subclassOf": ["Q294414"]}, "Q132311": {"name": "fantasy", "subclassOf": ["Q735"]}, "Q483501": {"name": "artist", "subclassOf": ["Q28640"]}, "Q23540": {"name": "Protestantism", "subclassOf": ["Q5043"]}, "Q1136507": {"name": "electric piano", "subclassOf": ["Q5994"]}, "Q43845": {"name": "businessperson", "subclassOf": ["Q28640"]}, "Q4610556": {"name": "model", "subclassOf": ["Q28640"]}, "Q24925": {"name": "science fiction", "subclassOf": ["Q483394"]}, "Q93204":":0ifiersvalue": "value":typevaluevalue "type inqualtypetypequalqualtypetypequalqual intypetype in in",qualqualqualqualqualqualqualqualqual": [{"objecttypeobjecttypetypekey]}}} </> What the correct answer to this question: Which? Choices: (A (B(C(D Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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0.022409
91,391
Please read the following text and answer the question below. <text> [ [ { "role": "user", "content": "Document: I know. My question was if they **used** to compete in T5-TTT2.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) abb\n(B) aba\n(C) aah\n(D) aai" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: 18 is hot but very bland, it's just here this blonde lady who is not as hot as blonde launch.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aal\n(B) aae\n(C) abb\n(D) aaq" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: Mine was apparently [NAME] and the giant peach!\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) abb\n(B) aav\n(C) aaq\n(D) aat" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: Sack, shaft, and tip. The trifecta. \n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aav\n(B) aap\n(C) aap\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: Detective from svu.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aas\n(B) abb\n(C) aaa\n(D) aaf" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: your mom likes to copy me cause she has no creativity just like you:\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aab\n(B) abb\n(C) aad\n(D) aak" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: [NAME] sees all\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aan\n(B) aak\n(C) aaa\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: A new study just came out from China that it's actually too late.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aah\n(B) aag\n(C) abb\n(D) aaz" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: It might be linked to the trust factor of your friend.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aba\n(B) aap\n(C) aas\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: You are going to do the dishes now\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) abb\n(B) aaj\n(C) aaz\n(D) aaf" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: Cheers, sololander!\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aap\n(B) aaw\n(C) abb\n(D) aag" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: Never get out of the boat.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aax\n(B) abb\n(C) aaz\n(D) aaq" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: Just got home from school. How are we doing\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aag\n(B) aau\n(C) aab\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: Slowing things down now\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) abb\n(B) aai\n(C) aal\n(D) aax" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: Honestly it sounds exhausting being married to him. Maybe it will be better for you in the long run.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) abb\n(B) aaf\n(C) aao\n(D) aag" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: FBI!! OPEN UP!!!\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aad\n(B) aba\n(C) aaz\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: This pic they used for [NAME] makes her look like [NAME]\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aal\n(B) abb\n(C) aak\n(D) aat" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: Aww, try mindfulness. I think I am going over to that sub now.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aaw\n(B) aat\n(C) aaf\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: His name has already been released. Just can't post it here.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aag\n(B) abb\n(C) aai\n(D) aba" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: When I feel down I listen to music.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aab\n(B) abb\n(C) aau\n(D) aau" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: Hello everyone. Im from Toronto as well. Can call and visit in personal if needed.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aaq\n(B) abb\n(C) aah\n(D) aac" }, { "role": "assistant", "content": "B" } ], [ role role", ?\?\?\?\?\", ?\?\?\ (", ", content?\ncontent", ", ] ] </text> What correct answer:Choices: (A (D Format your response as follows: "The correct answer is (insert answer here)".
267
null
3
D
aaf,aai,aau
Please read the following text and answer the question below. <text> [ [ { "role": "user", "content": "Document: I know. My question was if they **used** to compete in T5-TTT2.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) abb\n(B) aba\n(C) aah\n(D) aai" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: 18 is hot but very bland, it's just here this blonde lady who is not as hot as blonde launch.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aal\n(B) aae\n(C) abb\n(D) aaq" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: Mine was apparently [NAME] and the giant peach!\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) abb\n(B) aav\n(C) aaq\n(D) aat" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: Sack, shaft, and tip. The trifecta. \n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aav\n(B) aap\n(C) aap\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: Detective from svu.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aas\n(B) abb\n(C) aaa\n(D) aaf" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: your mom likes to copy me cause she has no creativity just like you:\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aab\n(B) abb\n(C) aad\n(D) aak" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: [NAME] sees all\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aan\n(B) aak\n(C) aaa\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: A new study just came out from China that it's actually too late.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aah\n(B) aag\n(C) abb\n(D) aaz" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: It might be linked to the trust factor of your friend.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aba\n(B) aap\n(C) aas\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: You are going to do the dishes now\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) abb\n(B) aaj\n(C) aaz\n(D) aaf" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: Cheers, sololander!\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aap\n(B) aaw\n(C) abb\n(D) aag" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: Never get out of the boat.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aax\n(B) abb\n(C) aaz\n(D) aaq" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: Just got home from school. How are we doing\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aag\n(B) aau\n(C) aab\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: Slowing things down now\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) abb\n(B) aai\n(C) aal\n(D) aax" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: Honestly it sounds exhausting being married to him. Maybe it will be better for you in the long run.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) abb\n(B) aaf\n(C) aao\n(D) aag" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: FBI!! OPEN UP!!!\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aad\n(B) aba\n(C) aaz\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: This pic they used for [NAME] makes her look like [NAME]\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aal\n(B) abb\n(C) aak\n(D) aat" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: Aww, try mindfulness. I think I am going over to that sub now.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aaw\n(B) aat\n(C) aaf\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: His name has already been released. Just can't post it here.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aag\n(B) abb\n(C) aai\n(D) aba" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: When I feel down I listen to music.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aab\n(B) abb\n(C) aau\n(D) aau" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: Hello everyone. Im from Toronto as well. Can call and visit in personal if needed.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aaq\n(B) abb\n(C) aah\n(D) aac" }, { "role": "assistant", "content": "B" } ], [ role role", ?\?\?\?\?\", ?\?\?\ (", ", content?\ncontent", ", ] ] </text> What correct answer:Choices: (A (D Format your response as follows: "The correct answer is (insert answer here)".
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Please read the following text and answer the question below. <text> ChatGLM-Math: Improving Math Problem-Solving in Large Language Models with a Self-Critique Pipeline Yifan Xu12†∗, Xiao Liu12∗, Xinghan Liu12†, Zhenyu Hou12, Yueyan Li1†, Xiaohan Zhang1, Zihan Wang12, Aohan Zeng12,Zhengxiao Du12, Wenyi Zhao1, Jie Tang2, Yuxiao Dong2 1Zhipu.AI 2Tsinghua University Abstract Large language models (LLMs) have shown excellent mastering of human language, but still struggle in real-world applications that require mathematical problem- solving. While many strategies and datasets to enhance LLMs’ mathematics are developed, it remains a challenge to simultaneously maintain and improve both language and mathematical capabilities in deployed LLM systems. In this work, we tailor the Self-Critique pipeline, which addresses the challenge in the feedback learning stage of LLM alignment. We first train a general Math-Critique model from the LLM itself to provide feedback signals. Then, we sequentially employ rejective fine-tuning and direct preference optimization over the LLM’s own generations for data collection. Based on ChatGLM3-32B, we conduct a series of experiments on both academic and our newly created challenging dataset, MATHUSEREVAL. Results show that our pipeline significantly enhances the LLM’s mathematical problem-solving while still improving its language ability, outperforming LLMs that could be two times larger. Related techniques have been deployed to ChatGLM1, an online serving LLM. Related evaluation dataset and scripts are released at https://github.com/THUDM/ChatGLM-Math. Model Avg. of GSM8k & MATH AlignBench Language DeepSeek-67B-Chat [12] 58.3 7.11 DeepSeek-67B-Chat-DPO [12] 57.7 (-1.2%) 7.60 (+6.8%) InternLM2-Chat-20B [43] 57.2 7.68 Math-InternLM2-20B [43] 60.2 (+5.1%) 6.53 (-14.8%) ChatGLM3-32B-SFT-2312 52.4 7.37 + RFT&DPO 61.6 (+17.5%) 7.80 (+5.85%) Table 1: Our self-critique pipeline enables simul- taneous improvement of language and mathemati- cal abilities. Previous alignment methods enhance language but could potentially impair mathemati- cal abilities [12], whereas math-specialized mod- els could harm language capabilities [43]. 40 45 50 55 60 65 70 75 Hungarian Exam Score 52.5 55.0 57.5 60.0 62.5 65.0 67.5 70.0 Avg. of GSM8k & MATH GPT-3.5-Turbo-0613 GPT-4-0613 GLM-4 DeepSeek-Chat-67B Qwen-Chat-72B ChatGLM3-32B-SFT-2312 ChatGLM3-32B-SFT-2312 + RFT ChatGLM3-32B-SFT-2312 + RFT&DPO Figure 1: Results of Hungarian Exam and Average Scores of GSM8k and MATH. *Yifan and Xiao contributed equally. Emails: xu-yf23@mails.tsinghua.edu.cn,shawliu9@gmail.com †Work done while Xinghan and Yueyan interned at Zhipu AI. 1https://chatglm.cn Preprint. Under review. arXiv:2404.02893v1 [cs.CL] 3 Apr 2024 1 Introduction Large Language Models (LLMs) [8; 10; 20; 40; 44; 61; 1] have garnered widespread attention for their remarkable proficiency in various linguistic tasks such as text summarization[18; 47; 33; 26], question answering [16; 24; 7], and role-playing conversations [46; 67; 41]. Furthermore, their potential in addressing complex problems requiring mathematical reasoning [57; 48; 31] has expanded their applicability across real-world missions [30; 5]. Despite these advances, optimizing LLMs to excel simultaneously in language understanding and mathematical problem-solving presents a notable challenge. The prevalent reinforcement learning from human feedback (RLHF) approach primarily enhances text generation based on reward models reflecting human preferences [44; 35; 45]. Although this method boosts the quality of generated text, it often overlooks the accuracy and logical coherence essential for solving mathematical problems, leading to a discrepancy in performance known as the "alignment tax"[2] when applied to mathemati- cal reasoning (refer to Table 1). Conversely, attempts to bolster LLMs’ mathematical capabilities typically entail supervised fine-tuning (SFT) that inadvertently diminishes their linguistic versatility, posing a dilemma for practical applications of LLM systems [43; 57; 31; 60]. Pipeline: Self-Critique. This paper introduces a novel approach aimed at enhancing both linguistic and mathematical skills of LLMs without compromising one for the other. Our strategy deviates from traditional RLHF by incorporating a Math-Critique model derived from the LLM itself, which evaluates its mathematical outputs. This self-critique mechanism enables the model to learn from AI- generated feedback specifically tailored to mathematical content [4; 25]. Our methodology comprises two primary phases: • Stage 1: Rejective Fine-tuning (RFT) [58] employs a rejection sampling technique, wherein responses failing to meet Math-Critique standards are discarded, while the rest undergo further fine-tuning. This stage aims to enhance the model’s accuracy and consistency in mathematical responses while ensuring diversity among the selected answers. • Stage 2: Direct Preference Optimization (DPO) [38] extends the improvement process by directly learning from pairs of correct and incorrect answers, further refined through Math-Critique, focusing on the most challenging questions from the previous stage. Benchmark: MATHUSEREVAL. To accurately assess LLMs’ capabilities in solving real-world mathematical problems, we develop the MATHUSEREVAL dataset. It features a diverse range of questions, extending beyond academic exercises to include practical application scenarios, thereby better reflecting user needs compared to traditional academic math datasets [64; 50; 11]. We leverage both GPT-4-turbo and our Math-Critique model for comprehensive scoring. In summary, our contributions include: • The introduction of the Self-Critique pipeline, a novel framework that elevates both the mathe- matical and linguistic capabilities of LLMs through self-generated feedback, thereby eliminating the need for external supervisory models and manual annotations. This approach has been vali- dated on a ChatGLM3-32B model, achieving unparalleled performance on the MATHUSEREVAL, Ape210k [64], MATH [16], and the linguistic tasks of AlignBench [29]. • The creation of the MATHUSEREVAL benchmark, tailored to assess LLMs on complex, open-ended mathematical queries relevant to real-world applications, setting a new standard in evaluating practical mathematical reasoning capabilities. • A detailed analysis of the key factors contributing to the enhancement of mathematical proficiency through the Self-Critique pipeline, offering insights into future directions for autonomous model improvement. 2 Related Work LLM for Math Problem-Solving. Various approaches have been explored to enhance the mathe- matical problem-solving abilities of language models. Prompting Methods, initiated by Chain of Thought prompting [51], have been refined to guide models through detailed reasoning, with notable contributions from [55; 6; 53] enhancing mathematical and reasoning tasks. These methods, however, 2 Instruction: Act as a judge … Question: A has three eigenvalues 0, 3, and 5, … Reference:… x =ku+ 1/3 * v + 1/5 * w. Model Answer: …x = pu + \frac{1}{3} v + \frac{1}{5}w,where p is any real number Response: Analysis: The AI assistant's answer… Score: 9 (1) Train Math-Critique (2) Train Critique-RFT Model Pseudo Tag & Human LabelX2X ] 1 LLX Comparison Co 1 </text> What is the correct answer to this question: How Chat? Choices: (A(B. (CGL. (D. Format your response as follows: "The correct answer is (insert answer here)".
268
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ChatGLM Math uses CritiqueLLM as a reward model to construct Math Critique training data and pair data.
Please read the following text and answer the question below. <text> ChatGLM-Math: Improving Math Problem-Solving in Large Language Models with a Self-Critique Pipeline Yifan Xu12†∗, Xiao Liu12∗, Xinghan Liu12†, Zhenyu Hou12, Yueyan Li1†, Xiaohan Zhang1, Zihan Wang12, Aohan Zeng12,Zhengxiao Du12, Wenyi Zhao1, Jie Tang2, Yuxiao Dong2 1Zhipu.AI 2Tsinghua University Abstract Large language models (LLMs) have shown excellent mastering of human language, but still struggle in real-world applications that require mathematical problem- solving. While many strategies and datasets to enhance LLMs’ mathematics are developed, it remains a challenge to simultaneously maintain and improve both language and mathematical capabilities in deployed LLM systems. In this work, we tailor the Self-Critique pipeline, which addresses the challenge in the feedback learning stage of LLM alignment. We first train a general Math-Critique model from the LLM itself to provide feedback signals. Then, we sequentially employ rejective fine-tuning and direct preference optimization over the LLM’s own generations for data collection. Based on ChatGLM3-32B, we conduct a series of experiments on both academic and our newly created challenging dataset, MATHUSEREVAL. Results show that our pipeline significantly enhances the LLM’s mathematical problem-solving while still improving its language ability, outperforming LLMs that could be two times larger. Related techniques have been deployed to ChatGLM1, an online serving LLM. Related evaluation dataset and scripts are released at https://github.com/THUDM/ChatGLM-Math. Model Avg. of GSM8k & MATH AlignBench Language DeepSeek-67B-Chat [12] 58.3 7.11 DeepSeek-67B-Chat-DPO [12] 57.7 (-1.2%) 7.60 (+6.8%) InternLM2-Chat-20B [43] 57.2 7.68 Math-InternLM2-20B [43] 60.2 (+5.1%) 6.53 (-14.8%) ChatGLM3-32B-SFT-2312 52.4 7.37 + RFT&DPO 61.6 (+17.5%) 7.80 (+5.85%) Table 1: Our self-critique pipeline enables simul- taneous improvement of language and mathemati- cal abilities. Previous alignment methods enhance language but could potentially impair mathemati- cal abilities [12], whereas math-specialized mod- els could harm language capabilities [43]. 40 45 50 55 60 65 70 75 Hungarian Exam Score 52.5 55.0 57.5 60.0 62.5 65.0 67.5 70.0 Avg. of GSM8k & MATH GPT-3.5-Turbo-0613 GPT-4-0613 GLM-4 DeepSeek-Chat-67B Qwen-Chat-72B ChatGLM3-32B-SFT-2312 ChatGLM3-32B-SFT-2312 + RFT ChatGLM3-32B-SFT-2312 + RFT&DPO Figure 1: Results of Hungarian Exam and Average Scores of GSM8k and MATH. *Yifan and Xiao contributed equally. Emails: xu-yf23@mails.tsinghua.edu.cn,shawliu9@gmail.com †Work done while Xinghan and Yueyan interned at Zhipu AI. 1https://chatglm.cn Preprint. Under review. arXiv:2404.02893v1 [cs.CL] 3 Apr 2024 1 Introduction Large Language Models (LLMs) [8; 10; 20; 40; 44; 61; 1] have garnered widespread attention for their remarkable proficiency in various linguistic tasks such as text summarization[18; 47; 33; 26], question answering [16; 24; 7], and role-playing conversations [46; 67; 41]. Furthermore, their potential in addressing complex problems requiring mathematical reasoning [57; 48; 31] has expanded their applicability across real-world missions [30; 5]. Despite these advances, optimizing LLMs to excel simultaneously in language understanding and mathematical problem-solving presents a notable challenge. The prevalent reinforcement learning from human feedback (RLHF) approach primarily enhances text generation based on reward models reflecting human preferences [44; 35; 45]. Although this method boosts the quality of generated text, it often overlooks the accuracy and logical coherence essential for solving mathematical problems, leading to a discrepancy in performance known as the "alignment tax"[2] when applied to mathemati- cal reasoning (refer to Table 1). Conversely, attempts to bolster LLMs’ mathematical capabilities typically entail supervised fine-tuning (SFT) that inadvertently diminishes their linguistic versatility, posing a dilemma for practical applications of LLM systems [43; 57; 31; 60]. Pipeline: Self-Critique. This paper introduces a novel approach aimed at enhancing both linguistic and mathematical skills of LLMs without compromising one for the other. Our strategy deviates from traditional RLHF by incorporating a Math-Critique model derived from the LLM itself, which evaluates its mathematical outputs. This self-critique mechanism enables the model to learn from AI- generated feedback specifically tailored to mathematical content [4; 25]. Our methodology comprises two primary phases: • Stage 1: Rejective Fine-tuning (RFT) [58] employs a rejection sampling technique, wherein responses failing to meet Math-Critique standards are discarded, while the rest undergo further fine-tuning. This stage aims to enhance the model’s accuracy and consistency in mathematical responses while ensuring diversity among the selected answers. • Stage 2: Direct Preference Optimization (DPO) [38] extends the improvement process by directly learning from pairs of correct and incorrect answers, further refined through Math-Critique, focusing on the most challenging questions from the previous stage. Benchmark: MATHUSEREVAL. To accurately assess LLMs’ capabilities in solving real-world mathematical problems, we develop the MATHUSEREVAL dataset. It features a diverse range of questions, extending beyond academic exercises to include practical application scenarios, thereby better reflecting user needs compared to traditional academic math datasets [64; 50; 11]. We leverage both GPT-4-turbo and our Math-Critique model for comprehensive scoring. In summary, our contributions include: • The introduction of the Self-Critique pipeline, a novel framework that elevates both the mathe- matical and linguistic capabilities of LLMs through self-generated feedback, thereby eliminating the need for external supervisory models and manual annotations. This approach has been vali- dated on a ChatGLM3-32B model, achieving unparalleled performance on the MATHUSEREVAL, Ape210k [64], MATH [16], and the linguistic tasks of AlignBench [29]. • The creation of the MATHUSEREVAL benchmark, tailored to assess LLMs on complex, open-ended mathematical queries relevant to real-world applications, setting a new standard in evaluating practical mathematical reasoning capabilities. • A detailed analysis of the key factors contributing to the enhancement of mathematical proficiency through the Self-Critique pipeline, offering insights into future directions for autonomous model improvement. 2 Related Work LLM for Math Problem-Solving. Various approaches have been explored to enhance the mathe- matical problem-solving abilities of language models. Prompting Methods, initiated by Chain of Thought prompting [51], have been refined to guide models through detailed reasoning, with notable contributions from [55; 6; 53] enhancing mathematical and reasoning tasks. These methods, however, 2 Instruction: Act as a judge … Question: A has three eigenvalues 0, 3, and 5, … Reference:… x =ku+ 1/3 * v + 1/5 * w. Model Answer: …x = pu + \frac{1}{3} v + \frac{1}{5}w,where p is any real number Response: Analysis: The AI assistant's answer… Score: 9 (1) Train Math-Critique (2) Train Critique-RFT Model Pseudo Tag & Human LabelX2X ] 1 LLX Comparison Co 1 </text> What is the correct answer to this question: How Chat? Choices: (A(B. (CGL. (D. Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> 2023 2 | Legal Trends Report 2023 Table of Contents INTRODUCTION 4 UNLOCKING THE POTENTIAL TO SUCCEED 6 Legal productivity is higher than ever before 7 The power of leverage 8 The advent of generative artificial intelligence 9 New this year 10 Data sources PART 1 11 THE THRIVING BUSINESS OF LEGAL 13 Lawyers have matched rates with inflation, but non-lawyers are way behind 17 A new era of legal productivity 18 Small efficiency gains compound into massive revenue growth 24 The lawyer’s funnel shows narrowing earning potential 26 A need to measure performance over time... PART 2 27 LOCKUP—A NEW INDICATOR OF CASH FLOW 28 Introducing “lockup”—a crucial measure for healthy businesses 30 Prolonged lockup periods ruin businesses 32 Reducing lockup puts more cash in hand 38 Clio users enjoy shorter total lockup periods 38 Levers for reducing lockup PART 3 44 GETTING PAID FASTER 46 Foonberg’s Gratitude Curve and the key to getting paid 48 A known problem between lawyers and their clients 3 | Legal Trends Report 2023 50 The challenge to get paid 52 Many law firms are still committed to “snail mail” 54 Online payments get firms paid faster 56 Encouraging clients to pay electronically pays off 57 Clients actually want to pay by credit card PART 4 60 BUSINESS LEVERS TO IMPROVE FIRM PERFORMANCE 62 Business levers for improving realization rates 65 Top business levers for improving collection rates 71 Leverage points that firms struggle with most 72 More levers for improving business performance PART 5 73 THE PROMISE OF AI 78 Legal professionals are interested yet cautious of AI 80 AI poses both risks and rewards 84 The unseen potential of AI in the justice system 88 How AI can be used by legal professionals 93 Many clients see the benefit of hiring a lawyer who uses AI 97 Use of AI in legal, today 101 Legal professionals see much promise in the future of AI APPENDIX A 103 HOURLY RATES AND KPIS 105 Hourly rates by state 106 Adjusted rates by state 107 Hourly rates by practice area 108 Utilization rates by state 109 Realization and collection rates by state 110 Realization and collection rates by practice area APPENDIX B 111 DETAILED METHODOLOGY 112 App data collection 114 Survey design Introduction Unlocking the potential to succeed 4 | Legal Trends Report 2023 5 | Legal Trends Report 2023 Introduction: Unlocking the potential to succeed In our fast-paced world, efficiency and effectiveness are of the utmost importance. In the practice of law, this has been never more true since Clio first started publishing the Legal Trends Report in 2016. With rapid advancements in new systems and technologies, today’s legal professionals have more tools and opportunities for innovation than ever before, and they are driving never-seen-before productivity as a result. But the landscape for success continues to evolve. What defined innovation in the last decade has since become foundational. With radical advancements in artificial intelligence, law firms are once again finding themselves at the cusp of transformative change. This is where a client-centered approach is more important than ever. In the midst of uncertainty, certain values still—and always will—hold up. The lawyers and practices that continue to adapt and evolve in the interests of their clients are the ones that will ultimately succeed in the long run. What defined innovation in the last decade has since become foundational. 6 | Legal Trends Report 2023 Introduction: Unlocking the potential to succeed LEGAL PRODUCTIVITY IS HIGHER THAN EVER BEFORE Today, legal professionals work heavier caseloads—and earn over two and a half times more for their firms than in years past. This is an unprecedented achievement in the legal industry. It means that lawyers and their firms are doing a lot more of what they set out to do—provide legal services to clients. And they’re earning substantially more for themselves in the process. This growth in productivity also means that the capacity of the legal profession as a whole has, in turn, increased the scale of services available to clients. This growth couldn’t be more timely. Over the last three years, businesses have dealt with inflation rates that have reached their highest levels in decades. Rising costs put law firms in a challenging position—on the one hand, looking for ways to reduce costs, while on the other, having to find new ways to increase revenues. Lawyers may be hesitant to raise their hourly rates—since clients are also dealing with the effects of inflation—and many are instead turning to technology to improve efficiency and productivity. Technology is a powerful lever that businesses use to get more done while also improving client experiences. Certain capabilities can have a revolutionary impact on business. However, finding the right tool for the job at hand is critical. Technology is a powerful lever that businesses use to get more done while also improving client experiences. 7 | Legal Trends Report 2023 Introduction: Unlocking the potential to succeed THE POWER OF LEVERAGE A lever is a mechanism that amplifies the impact and outcomes of our work efforts. When using a lever, a small amount of effort can be multiplied several times over to apply a substantially larger force. When used strategically in the practice of law, certain business levers can transform a firm’s operations to make them incredibly more efficient, productive, and capable of delivering the best client experiences possible. When applying the principles of leverage to business, knowing where to apply them is just as important as knowing what tools to use. We’ve seen the massive impact that technology can have in improving the success of law firms. Throughout this report, we look at key leverage points that include utilization, realization, and collection rates— and discuss cash flow with the introduction of our new lockup metric. We also look at key technologies as business levers that have had the most impact on firm success. Billing and payment systems in particular continue to be a crucial point of focus for any law firm. As simple as it might seem to bill work to clients, the undertaking grows more complex with scale. Even small inefficiencies can result in delayed cash flow and lost earnings. Electronic billing and payments are powerful business levers that allow law firms to find new efficiencies, create better client experiences, and open the door for more advanced automation. Even simple workflow improvements see law firms billing 18% more of their work to clients over other firms, resulting in substantial revenue gains. Throughout this report, we look at key leverage points that include utilization, realization, and collection rates—and discuss cash flow with the introduction of our new lockup metric. 8 | Legal Trends Report 2023 Introduction: Unlocking the potential to succeed THE ADVENT OF GENERATIVE ARTIFICIAL INTELLIGENCE By far, the most impactful technological advancement made in the last decade has been the public launch of generative artificial intelligence (AI) with the release of ChatGPT. For the first time, law firms have access to technology that doesn’t just help manage and process information. With generative AI, legal professionals have new tools that simulate cognitive functions for interpreting, summarizing, and creating new content based on large language models (LLMs) trained on enormous datasets. AI has the potential to transform so many facets of everyday business operations, and we’ve only just scratched the surface in terms of what it will be capable of in the years and decades to come. As more legal professionals adopt AI in their practices, the benefits are becoming increasingly apparent. Already, AI has given firms the ability to summarize key information, assist in drafting documents, identify high-risk clauses in a contract, and automatically generate demand letters for personal injury cases. The early days of generative AI have also highlighted the risks inherent in this technology. A New York lawyer learned this the hard way when he used ChatGPT to cite court decisions relevant to an airline lawsuit. Unfortunately, ChatGPT invented—or “hallucinated,” the term used when AI software creates incorrect information presented as fact222222-law</text> What is the correct answer to this question: Consider: 0. F0. Given analyze which. Consider your analysis. Choices: (A. (B. (C. (D. Format your response as follows: "The correct answer is (insert answer here)".
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Firm A’s adoption of AI will likely give it a competitive advantage in the short term, but the 20% client attrition rate, combined with increasing global scrutiny over AI in law, suggests that Firm A is more vulnerable to future regulatory changes and client backlash, especially in regions like the EU and China.
Please read the following text and answer the question below. <text> 2023 2 | Legal Trends Report 2023 Table of Contents INTRODUCTION 4 UNLOCKING THE POTENTIAL TO SUCCEED 6 Legal productivity is higher than ever before 7 The power of leverage 8 The advent of generative artificial intelligence 9 New this year 10 Data sources PART 1 11 THE THRIVING BUSINESS OF LEGAL 13 Lawyers have matched rates with inflation, but non-lawyers are way behind 17 A new era of legal productivity 18 Small efficiency gains compound into massive revenue growth 24 The lawyer’s funnel shows narrowing earning potential 26 A need to measure performance over time... PART 2 27 LOCKUP—A NEW INDICATOR OF CASH FLOW 28 Introducing “lockup”—a crucial measure for healthy businesses 30 Prolonged lockup periods ruin businesses 32 Reducing lockup puts more cash in hand 38 Clio users enjoy shorter total lockup periods 38 Levers for reducing lockup PART 3 44 GETTING PAID FASTER 46 Foonberg’s Gratitude Curve and the key to getting paid 48 A known problem between lawyers and their clients 3 | Legal Trends Report 2023 50 The challenge to get paid 52 Many law firms are still committed to “snail mail” 54 Online payments get firms paid faster 56 Encouraging clients to pay electronically pays off 57 Clients actually want to pay by credit card PART 4 60 BUSINESS LEVERS TO IMPROVE FIRM PERFORMANCE 62 Business levers for improving realization rates 65 Top business levers for improving collection rates 71 Leverage points that firms struggle with most 72 More levers for improving business performance PART 5 73 THE PROMISE OF AI 78 Legal professionals are interested yet cautious of AI 80 AI poses both risks and rewards 84 The unseen potential of AI in the justice system 88 How AI can be used by legal professionals 93 Many clients see the benefit of hiring a lawyer who uses AI 97 Use of AI in legal, today 101 Legal professionals see much promise in the future of AI APPENDIX A 103 HOURLY RATES AND KPIS 105 Hourly rates by state 106 Adjusted rates by state 107 Hourly rates by practice area 108 Utilization rates by state 109 Realization and collection rates by state 110 Realization and collection rates by practice area APPENDIX B 111 DETAILED METHODOLOGY 112 App data collection 114 Survey design Introduction Unlocking the potential to succeed 4 | Legal Trends Report 2023 5 | Legal Trends Report 2023 Introduction: Unlocking the potential to succeed In our fast-paced world, efficiency and effectiveness are of the utmost importance. In the practice of law, this has been never more true since Clio first started publishing the Legal Trends Report in 2016. With rapid advancements in new systems and technologies, today’s legal professionals have more tools and opportunities for innovation than ever before, and they are driving never-seen-before productivity as a result. But the landscape for success continues to evolve. What defined innovation in the last decade has since become foundational. With radical advancements in artificial intelligence, law firms are once again finding themselves at the cusp of transformative change. This is where a client-centered approach is more important than ever. In the midst of uncertainty, certain values still—and always will—hold up. The lawyers and practices that continue to adapt and evolve in the interests of their clients are the ones that will ultimately succeed in the long run. What defined innovation in the last decade has since become foundational. 6 | Legal Trends Report 2023 Introduction: Unlocking the potential to succeed LEGAL PRODUCTIVITY IS HIGHER THAN EVER BEFORE Today, legal professionals work heavier caseloads—and earn over two and a half times more for their firms than in years past. This is an unprecedented achievement in the legal industry. It means that lawyers and their firms are doing a lot more of what they set out to do—provide legal services to clients. And they’re earning substantially more for themselves in the process. This growth in productivity also means that the capacity of the legal profession as a whole has, in turn, increased the scale of services available to clients. This growth couldn’t be more timely. Over the last three years, businesses have dealt with inflation rates that have reached their highest levels in decades. Rising costs put law firms in a challenging position—on the one hand, looking for ways to reduce costs, while on the other, having to find new ways to increase revenues. Lawyers may be hesitant to raise their hourly rates—since clients are also dealing with the effects of inflation—and many are instead turning to technology to improve efficiency and productivity. Technology is a powerful lever that businesses use to get more done while also improving client experiences. Certain capabilities can have a revolutionary impact on business. However, finding the right tool for the job at hand is critical. Technology is a powerful lever that businesses use to get more done while also improving client experiences. 7 | Legal Trends Report 2023 Introduction: Unlocking the potential to succeed THE POWER OF LEVERAGE A lever is a mechanism that amplifies the impact and outcomes of our work efforts. When using a lever, a small amount of effort can be multiplied several times over to apply a substantially larger force. When used strategically in the practice of law, certain business levers can transform a firm’s operations to make them incredibly more efficient, productive, and capable of delivering the best client experiences possible. When applying the principles of leverage to business, knowing where to apply them is just as important as knowing what tools to use. We’ve seen the massive impact that technology can have in improving the success of law firms. Throughout this report, we look at key leverage points that include utilization, realization, and collection rates— and discuss cash flow with the introduction of our new lockup metric. We also look at key technologies as business levers that have had the most impact on firm success. Billing and payment systems in particular continue to be a crucial point of focus for any law firm. As simple as it might seem to bill work to clients, the undertaking grows more complex with scale. Even small inefficiencies can result in delayed cash flow and lost earnings. Electronic billing and payments are powerful business levers that allow law firms to find new efficiencies, create better client experiences, and open the door for more advanced automation. Even simple workflow improvements see law firms billing 18% more of their work to clients over other firms, resulting in substantial revenue gains. Throughout this report, we look at key leverage points that include utilization, realization, and collection rates—and discuss cash flow with the introduction of our new lockup metric. 8 | Legal Trends Report 2023 Introduction: Unlocking the potential to succeed THE ADVENT OF GENERATIVE ARTIFICIAL INTELLIGENCE By far, the most impactful technological advancement made in the last decade has been the public launch of generative artificial intelligence (AI) with the release of ChatGPT. For the first time, law firms have access to technology that doesn’t just help manage and process information. With generative AI, legal professionals have new tools that simulate cognitive functions for interpreting, summarizing, and creating new content based on large language models (LLMs) trained on enormous datasets. AI has the potential to transform so many facets of everyday business operations, and we’ve only just scratched the surface in terms of what it will be capable of in the years and decades to come. As more legal professionals adopt AI in their practices, the benefits are becoming increasingly apparent. Already, AI has given firms the ability to summarize key information, assist in drafting documents, identify high-risk clauses in a contract, and automatically generate demand letters for personal injury cases. The early days of generative AI have also highlighted the risks inherent in this technology. A New York lawyer learned this the hard way when he used ChatGPT to cite court decisions relevant to an airline lawsuit. Unfortunately, ChatGPT invented—or “hallucinated,” the term used when AI software creates incorrect information presented as fact222222-law</text> What is the correct answer to this question: Consider: 0. F0. Given analyze which. Consider your analysis. Choices: (A. (B. (C. (D. Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct Haipeng Luo2∗ Qingfeng Sun1∗ Can Xu1† Pu Zhao1 Jianguang Lou1 Chongyang Tao1 Xiubo Geng1 Qingwei Lin1 Shifeng Chen2† Dongmei Zhang1 1Microsoft 2Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences {caxu,qins,puzhao,jlou,chotao,xigeng,qlin,dongmeiz}@microsoft.com {hp.luo,shifeng.chen}@siat.ac.cn Abstract Large language models (LLMs), such as GPT-4, have shown remarkable perfor- mance in natural language processing (NLP) tasks, including challenging mathe- matical reasoning. However, most existing open-source models are only pre-trained on large-scale internet data and without math-related optimization. In this paper, we present WizardMath, which enhances the mathematical reasoning abilities of Llama-2, by applying our proposed Reinforcement Learning from Evol-Instruct Feedback (RLEIF) method to the domain of math. Through extensive experiments on two mathematical reasoning benchmarks, namely GSM8k and MATH, we reveal the extraordinary capabilities of our model. WizardMath surpasses all other open- source LLMs by a substantial margin. Furthermore, our model even outperforms ChatGPT-3.5, Claude Instant-1, PaLM-2 and Minerva on GSM8k, simultaneously surpasses Text-davinci-002, PaLM-1 and GPT-3 on MATH. More details and model weights are public at https://github.com/nlpxucan/WizardLM 3 and https://huggingface.co/WizardLM. 1 Introduction Recently, Large-scale language models (LLMs) have garnered significant attention and become the go-to approach for numerous natural language processing (NLP) tasks, including open domain conversation [1–4], coding [5–13] and math [14–19]. A conspicuous example is ChatGPT, developed by OpenAI. This model uses extensive pre-training on large-scale internet data and further fine- tuning with specific instruction data and methods. As a result, it achieves state-of-the-art zero-shot performance on various benchmarks. Subsequently, Anthropic, Google, and Meta also launched their competitive products one after another. Notably, Meta’s series of Llama [4, 20] models have sparked an open-source revolution and quickly narrowed the gap with those closed-source LLMs. This trend also gradually stimulates the releases of MPT8, Falcon [21], StarCoder [12], Alpaca [22], Vicuna [23], and WizardLM [24], etc. However, these open models still struggles with the scenarios which require complex multi-step quantitative reasoning, such as solving mathematical and science challenges [25–35]. ∗ Equal contribution. Work done during the internship of Luo at Microsoft Research. † Corresponding author: caxu@microsoft.com and shifeng.chen@siat.ac.cn 3 We are working with our legal team to review and publicly release the code and data in accordance with our policy. Preprint. Under review. arXiv:2308.09583v1 [cs.CL] 18 Aug 2023 SFT A C B D C > A > B = D Wizard-E ChatGPT PPO IRM PRM C > A > B = D IRM PRM 𝑟𝑘 𝐼 𝑟𝑘 𝐴 𝑟𝑘= 𝑟𝑘 𝐼∙𝑟𝑘 𝐴 Wizard-E ChatGPT Wizard-E Step 1: Supervised fine-tuning. Step 2: Training Instruction Reward Model (IRM), and Process-supervised Reward Model (PRM). Step 3: Active Evol-Instruct, and PPO training. WizardLM𝛼 Figure 1: A diagram illustrating the three steps of our Reinforcement Learning from Evol-Instruct Feedback (RLEIF): (1) supervised fine-tuning (SFT), (2) Instruction Reward Model (IRM) training and Process-supervised Reward Model (PRM) training, and (3) Active Evol-Instruct and reinforce- ment learning via proximal policy optimization (PPO). Chain-of-thought (CoT) [31] proposes to design better prompts to generate step-by-step solutions, which can lead to improved performance. Self-Consistency [34] also achieves remarkable perfor- mance on many reasoning benchmarks, which generates several possible answers from the model and selects the correct one based on majority vote [35]. In recent, [36] finds that process supervision with reinforcement learning significantly outperforms outcome supervision for solving challenging MATH problems. Inspired by Evol-Instruct and Process-supervised Reinforcement Learning, this work aims to enhance the mathematical reasoning abilities of the SOTA open-source LLM, Llama-2 [20]. As shown in the Figure 1, we propose a new method named Reinforcement Learning from Evol-Instruct Feedback (RLEIF), which could firstly generate diverse math instructions data by math-specific Evol-Instruct, then we train an instruction reward model (IRM) and a process-supervised reward model (PRM) [16, 36–41], the former indicates the quality of the evolved instruction and the later receives feedback for each step in the solution. The brand-new Evol-Instruct method includes two downward evolution and upward evolution progress to produce the grade school math and challenging math respectively. Initially, we re-generate, filter and finetune the original math instruction data from GSM8k [42] and MATH [43]. Immediately, we train the Llama-2 models to obtain the reward models and our WizardMath. We perform experiments on two mathematical reasoning benchmarks, namely GSM8k [42] and MATH [43], the results demonstrate that our WizardMath outperforms all other open-source LLMs, achieving state-of-the-art performance. Specifically, WizardMath observe a substantial improvement in pass@1 with an increase of +24.8 (81.6. vs. 56.8) on GSM8k, and +9.2 (22.7 vs. 13.5) on MATH. Notably, our model even also significantly surpasses OpenAI’s ChatGPT-3.55, Anthropic’s Claude Instant-1 [39], and Google’s PaLM-2 [44] in terms of pass@1 on GSM8k. The main contributions of this work are as following: 2 • We introduce WizardMath model, which enhances the mathematical reasoning abilities for open-source pretrained large language model Llama-2 [20]. • We propose a new method, Reinforcement Learning from Evol-Instruct Feedback (RLEIF), alongside Evol-Instruct and Reinforcement Learning, for improving LLM reasoning perfor- mance. • WizardMath surpasses all other open-source LLMs by a substantial margin in terms of math- ematical reasoning, including Llama-2 70B [20], Llama-1 65B [4], Falcon-40B [21], MPT- 30B8, Baichuan-13B Chat9 and ChatGLM2 12B [45] on both GSM8k [42] and MATH [43]. • WizardMath significantly outperforms various main closed-source LLMs, such as ChatGPT5, GPT-3.5, Claude Instant [39], PaLM-2 [44], PaLM-1 [7] and Minerva[15] on GSM8k. 2 Method In this section, we elaborate on the details of our WizardMath. Following WizardLM and PRMs[36], we propose Reinforcement Learning from Evol-Instruct Feedback (RLEIF), which integrates the Evol-Instruct and reinforced process supervision method to evolve GSM8k and MATH, and fine-tune the pre-trained Llama-2 with the evolved data and reward models. As shown in the Figure 1, our methods apply three steps: 1. Supervised fine-tuning. 2. Training instruction reward model, and process-supervised reward model. 3. Active Evol-Instruct, and PPO training. 2.1 Supervised fine-tuning Following InstructGPT[2], we also firstly fine tune the base with supervised instruction-response pairs, which contains: 1. To make the parsing of each step easier, we few-shot re-generate 15k answers for GSM8k and MATH with an Alpha version of WizardLM 70B model to produce solutions in a step-by-step format, then find out those with a correct answer,Table -th22XXXXX2Xyl 8 we the8 </text> What is the correct to this question: Which of the following about this article is correct? Choices: (A) In the. (B). (C. (D). Format your response as follows: "The correct answer is (insert answer here)".
271
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WizardMath models of all sizes have achieved mathematical abilities that exceed those of partially identical/larger closed source models.
Please read the following text and answer the question below. <text> WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct Haipeng Luo2∗ Qingfeng Sun1∗ Can Xu1† Pu Zhao1 Jianguang Lou1 Chongyang Tao1 Xiubo Geng1 Qingwei Lin1 Shifeng Chen2† Dongmei Zhang1 1Microsoft 2Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences {caxu,qins,puzhao,jlou,chotao,xigeng,qlin,dongmeiz}@microsoft.com {hp.luo,shifeng.chen}@siat.ac.cn Abstract Large language models (LLMs), such as GPT-4, have shown remarkable perfor- mance in natural language processing (NLP) tasks, including challenging mathe- matical reasoning. However, most existing open-source models are only pre-trained on large-scale internet data and without math-related optimization. In this paper, we present WizardMath, which enhances the mathematical reasoning abilities of Llama-2, by applying our proposed Reinforcement Learning from Evol-Instruct Feedback (RLEIF) method to the domain of math. Through extensive experiments on two mathematical reasoning benchmarks, namely GSM8k and MATH, we reveal the extraordinary capabilities of our model. WizardMath surpasses all other open- source LLMs by a substantial margin. Furthermore, our model even outperforms ChatGPT-3.5, Claude Instant-1, PaLM-2 and Minerva on GSM8k, simultaneously surpasses Text-davinci-002, PaLM-1 and GPT-3 on MATH. More details and model weights are public at https://github.com/nlpxucan/WizardLM 3 and https://huggingface.co/WizardLM. 1 Introduction Recently, Large-scale language models (LLMs) have garnered significant attention and become the go-to approach for numerous natural language processing (NLP) tasks, including open domain conversation [1–4], coding [5–13] and math [14–19]. A conspicuous example is ChatGPT, developed by OpenAI. This model uses extensive pre-training on large-scale internet data and further fine- tuning with specific instruction data and methods. As a result, it achieves state-of-the-art zero-shot performance on various benchmarks. Subsequently, Anthropic, Google, and Meta also launched their competitive products one after another. Notably, Meta’s series of Llama [4, 20] models have sparked an open-source revolution and quickly narrowed the gap with those closed-source LLMs. This trend also gradually stimulates the releases of MPT8, Falcon [21], StarCoder [12], Alpaca [22], Vicuna [23], and WizardLM [24], etc. However, these open models still struggles with the scenarios which require complex multi-step quantitative reasoning, such as solving mathematical and science challenges [25–35]. ∗ Equal contribution. Work done during the internship of Luo at Microsoft Research. † Corresponding author: caxu@microsoft.com and shifeng.chen@siat.ac.cn 3 We are working with our legal team to review and publicly release the code and data in accordance with our policy. Preprint. Under review. arXiv:2308.09583v1 [cs.CL] 18 Aug 2023 SFT A C B D C > A > B = D Wizard-E ChatGPT PPO IRM PRM C > A > B = D IRM PRM 𝑟𝑘 𝐼 𝑟𝑘 𝐴 𝑟𝑘= 𝑟𝑘 𝐼∙𝑟𝑘 𝐴 Wizard-E ChatGPT Wizard-E Step 1: Supervised fine-tuning. Step 2: Training Instruction Reward Model (IRM), and Process-supervised Reward Model (PRM). Step 3: Active Evol-Instruct, and PPO training. WizardLM𝛼 Figure 1: A diagram illustrating the three steps of our Reinforcement Learning from Evol-Instruct Feedback (RLEIF): (1) supervised fine-tuning (SFT), (2) Instruction Reward Model (IRM) training and Process-supervised Reward Model (PRM) training, and (3) Active Evol-Instruct and reinforce- ment learning via proximal policy optimization (PPO). Chain-of-thought (CoT) [31] proposes to design better prompts to generate step-by-step solutions, which can lead to improved performance. Self-Consistency [34] also achieves remarkable perfor- mance on many reasoning benchmarks, which generates several possible answers from the model and selects the correct one based on majority vote [35]. In recent, [36] finds that process supervision with reinforcement learning significantly outperforms outcome supervision for solving challenging MATH problems. Inspired by Evol-Instruct and Process-supervised Reinforcement Learning, this work aims to enhance the mathematical reasoning abilities of the SOTA open-source LLM, Llama-2 [20]. As shown in the Figure 1, we propose a new method named Reinforcement Learning from Evol-Instruct Feedback (RLEIF), which could firstly generate diverse math instructions data by math-specific Evol-Instruct, then we train an instruction reward model (IRM) and a process-supervised reward model (PRM) [16, 36–41], the former indicates the quality of the evolved instruction and the later receives feedback for each step in the solution. The brand-new Evol-Instruct method includes two downward evolution and upward evolution progress to produce the grade school math and challenging math respectively. Initially, we re-generate, filter and finetune the original math instruction data from GSM8k [42] and MATH [43]. Immediately, we train the Llama-2 models to obtain the reward models and our WizardMath. We perform experiments on two mathematical reasoning benchmarks, namely GSM8k [42] and MATH [43], the results demonstrate that our WizardMath outperforms all other open-source LLMs, achieving state-of-the-art performance. Specifically, WizardMath observe a substantial improvement in pass@1 with an increase of +24.8 (81.6. vs. 56.8) on GSM8k, and +9.2 (22.7 vs. 13.5) on MATH. Notably, our model even also significantly surpasses OpenAI’s ChatGPT-3.55, Anthropic’s Claude Instant-1 [39], and Google’s PaLM-2 [44] in terms of pass@1 on GSM8k. The main contributions of this work are as following: 2 • We introduce WizardMath model, which enhances the mathematical reasoning abilities for open-source pretrained large language model Llama-2 [20]. • We propose a new method, Reinforcement Learning from Evol-Instruct Feedback (RLEIF), alongside Evol-Instruct and Reinforcement Learning, for improving LLM reasoning perfor- mance. • WizardMath surpasses all other open-source LLMs by a substantial margin in terms of math- ematical reasoning, including Llama-2 70B [20], Llama-1 65B [4], Falcon-40B [21], MPT- 30B8, Baichuan-13B Chat9 and ChatGLM2 12B [45] on both GSM8k [42] and MATH [43]. • WizardMath significantly outperforms various main closed-source LLMs, such as ChatGPT5, GPT-3.5, Claude Instant [39], PaLM-2 [44], PaLM-1 [7] and Minerva[15] on GSM8k. 2 Method In this section, we elaborate on the details of our WizardMath. Following WizardLM and PRMs[36], we propose Reinforcement Learning from Evol-Instruct Feedback (RLEIF), which integrates the Evol-Instruct and reinforced process supervision method to evolve GSM8k and MATH, and fine-tune the pre-trained Llama-2 with the evolved data and reward models. As shown in the Figure 1, our methods apply three steps: 1. Supervised fine-tuning. 2. Training instruction reward model, and process-supervised reward model. 3. Active Evol-Instruct, and PPO training. 2.1 Supervised fine-tuning Following InstructGPT[2], we also firstly fine tune the base with supervised instruction-response pairs, which contains: 1. To make the parsing of each step easier, we few-shot re-generate 15k answers for GSM8k and MATH with an Alpha version of WizardLM 70B model to produce solutions in a step-by-step format, then find out those with a correct answer,Table -th22XXXXX2Xyl 8 we the8 </text> What is the correct to this question: Which of the following about this article is correct? Choices: (A) In the. (B). (C. (D). Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> Abstract We introduce DS-1000, a code generation bench- mark with a thousand data science problems spanning seven Python libraries, such as NumPy and Pandas. Compared to prior works, DS- 1000 incorporates three core features. First, our problems reflect diverse, realistic, and practical use cases since we collected them from Stack- Overflow. Second, our automatic evaluation is highly specific (reliable) – across all Codex-002- predicted solutions that our evaluation accept, only 1.8% of them are incorrect; we achieve this with multi-criteria metrics, checking both functional correctness by running test cases and surface-form constraints by restricting API us- ages or keywords. Finally, we proactively defend against memorization by slightly modifying our problems to be different from the original Stack- Overflow source; consequently, models cannot answer them correctly by memorizing the solu- tions from pre-training. The current best pub- lic system (Codex-002) achieves 43.3% accuracy, leaving ample room for improvement. We release our benchmark at https://ds1000-code-gen. github.io. 1. Introduction Data science is important in many areas (Romero & Ventura, 2013; Bolyen et al., 2019; Faghmous & Kumar, 2014), but requires programming proficiency in specialized libraries, thus posing substantial barriers to lay users. Fortunately, these barriers could potentially be reduced by pre-trained code generation models: for example, Codex (Chen et al., 2021a) can complete small Python snippets with non-trivial *Equal contribution. Author ordering determined by alphabet- ical order. 1The University of Hong Kong 2Peking University 3Stanford University 4UC Berkeley 5University of Washington 6Meta AI 7Carnegie Mellon University. Correspondence to: Tao Yu <tyu@cs.hku.hk>. accuracy and AlphaCode (Li et al., 2022) can tackle difficult competitive programming problems. We anticipate that these barriers will diminish if the community can make solid progress in applying these models to data science problems. However, we currently lack a benchmark that 1) focuses on everyday data science applications, 2) includes naturalistic intents and contexts, and 3) has a reliable execution-based evaluation metric. Most of the existing datasets with reliable test cases (Hendrycks et al., 2021; Chen et al., 2021a) focus on competition or interview-style programming problems; they measure algorithmic understanding but do not target real-world usage. Also, as represented by e.g., user prob- lems on StackOverflow, users’ data science coding problems usually have diverse contexts including their incorrect code, error messages, and input-output examples, which cannot be found in most prior data science relevant code generation benchmarks (Yin et al., 2018; Hendrycks et al., 2021; Chan- del et al., 2022b; Chen et al., 2021a). Moreover, most of these benchmarks solely rely on surface-form metrics such as BLEU or CodeBLEU (Yin et al., 2018; Agashe et al., 2019; Chen et al., 2021b). These metrics diverge from the programmer’s intent, increasingly so as model capability improves (Zhong et al., 2020). To our knowledge, no exist- ing benchmarks contain both naturally occurring problems with diverse contexts and reliable evaluation metrics. To fill this gap, we introduce DS-1000, a benchmark with a thousand problems covering seven widely-used Python data science libraries: NumPy, Pandas, TensorFlow, PyTorch, SciPy, Scikit-learn, and Matplotlib. We highlight three core features of DS-1000: 1) it contains realistic problems with diverse contexts, 2) it implements reliable multi-criteria execution-based evaluation metrics, and 3) it proactively defends against memorization. We outline how we achieved each of them below. First, we collected naturally occurring problems from Stack- Overflow, manually scored their representativeness and use- fulness, and curated a subset of them to create our bench- mark. While inputs in existing code generation datasets are either highly structured (problems or code context) or restricted in scope, our natural problems are diverse in con- tent and format. For example, users might search for more arXiv:2211.11501v1 [cs.SE] 18 Nov 2022 DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation result = df.div(1).add_prefix("inv_") Prompt Reference Solution result = df.join(df.apply(lambda x: 1/x).add_prefix(“inv_")) Test case 1 df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}) ans = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6], "inv_A": [1/1, 1/2, 1/3], "inv_B": [1/4, 1/5, 1/6]}) Test case 2 df,ans = ...[omit for brevity] pd.testing.assert_frame_equal(result, ans) Surface-form constraints for and while should not appear in Syntax Tree A: <code> import pandas as pd df = pd.DataFrame({"A": [1, 2, 3],"B": [4, 5, 6]}) </code> BEGIN SOLUTION <code> [insert] </code> END SOLUTION <code> print(result) </code> Here is a sample dataframe: df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}) I'd like to add inverses of each existing column to the dataframe and name them based on existing column names with a prefix, e.g. inv_A is an inverse of column A and so on. The resulting dataframe should look like so: result = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6], "inv_A": [1/1, 1/2, 1/3], "inv_B": [1/4, 1/5, 1/6]}) Obviously there are redundant methods like doing this in a loop, but there should exist much more pythonic ways of doing it … [omitted for brevity] Predict Correct/wrong? Language Models (GPT-3 Codex) Replace [insert] in the code context with following predicted code snippets Problem Code Context Execute to evaluate Multi-criteria Execution-based Evaluation Figure 1: An example problem in DS-1000. The model needs to fill in the code into “[insert]” in the prompt on the left; the code will then be executed to pass the multi-criteria automatic evaluation, which includes the test cases and the surface-form constraints; a reference solution is provided at the bottom left. efficient code implementations (Figure 1), provide incorrect code with an error message and ask for bug fixes (Figure 13), inquire about specific API usage (Figure 14), or ask for code that implements functionality they specify with input-output examples (Figure 1). These problems better reflect real- world applications and open up new modeling challenges, which have been understudied in existing code generation benchmarks. Second, it is challenging to evaluate program solutions to natural and diverse problems reliably. Unlike competition- style problems, natural problems might lack executable con- texts and test cases, allow multiple solutions, depend on external libraries, etc. To address these challenges, five of the authors of this paper, all proficient in data science and experts in Python, hand-adapted the original problems by writing executable code contexts, rewriting problems to be specific enough to be testable, and implementing automatic multi-criteria execution-based evaluation using carefully written and reviewed test cases and constraints that check functional correctness and surface-form constraints. On program solutions predicted by Codex-002, we find that only 1.8% of the predicted programs passing our evalua- tion are incorrect (false discovery rate), indicating that our evaluation is reliable. Third, one potential concern for adapting public problems is that the models might simply memorize the correspond- ing solution during pre-training time (Carlini et al., 2021a). We show in Section 2.4 that this can indeed happen: while Codex achieves 72.5% accuracy on the popular numpy-100 the1 0Table2XX-%AAP22 > What is the correct answer this question: What does N1? Choices: (A)-A0(B(C N-A. (D). Format your response as follows: "The correct answer is (insert answer here)".
272
null
1
B
NCB focuses more on the significance of engineering-related issues.
Please read the following text and answer the question below. <text> Abstract We introduce DS-1000, a code generation bench- mark with a thousand data science problems spanning seven Python libraries, such as NumPy and Pandas. Compared to prior works, DS- 1000 incorporates three core features. First, our problems reflect diverse, realistic, and practical use cases since we collected them from Stack- Overflow. Second, our automatic evaluation is highly specific (reliable) – across all Codex-002- predicted solutions that our evaluation accept, only 1.8% of them are incorrect; we achieve this with multi-criteria metrics, checking both functional correctness by running test cases and surface-form constraints by restricting API us- ages or keywords. Finally, we proactively defend against memorization by slightly modifying our problems to be different from the original Stack- Overflow source; consequently, models cannot answer them correctly by memorizing the solu- tions from pre-training. The current best pub- lic system (Codex-002) achieves 43.3% accuracy, leaving ample room for improvement. We release our benchmark at https://ds1000-code-gen. github.io. 1. Introduction Data science is important in many areas (Romero & Ventura, 2013; Bolyen et al., 2019; Faghmous & Kumar, 2014), but requires programming proficiency in specialized libraries, thus posing substantial barriers to lay users. Fortunately, these barriers could potentially be reduced by pre-trained code generation models: for example, Codex (Chen et al., 2021a) can complete small Python snippets with non-trivial *Equal contribution. Author ordering determined by alphabet- ical order. 1The University of Hong Kong 2Peking University 3Stanford University 4UC Berkeley 5University of Washington 6Meta AI 7Carnegie Mellon University. Correspondence to: Tao Yu <tyu@cs.hku.hk>. accuracy and AlphaCode (Li et al., 2022) can tackle difficult competitive programming problems. We anticipate that these barriers will diminish if the community can make solid progress in applying these models to data science problems. However, we currently lack a benchmark that 1) focuses on everyday data science applications, 2) includes naturalistic intents and contexts, and 3) has a reliable execution-based evaluation metric. Most of the existing datasets with reliable test cases (Hendrycks et al., 2021; Chen et al., 2021a) focus on competition or interview-style programming problems; they measure algorithmic understanding but do not target real-world usage. Also, as represented by e.g., user prob- lems on StackOverflow, users’ data science coding problems usually have diverse contexts including their incorrect code, error messages, and input-output examples, which cannot be found in most prior data science relevant code generation benchmarks (Yin et al., 2018; Hendrycks et al., 2021; Chan- del et al., 2022b; Chen et al., 2021a). Moreover, most of these benchmarks solely rely on surface-form metrics such as BLEU or CodeBLEU (Yin et al., 2018; Agashe et al., 2019; Chen et al., 2021b). These metrics diverge from the programmer’s intent, increasingly so as model capability improves (Zhong et al., 2020). To our knowledge, no exist- ing benchmarks contain both naturally occurring problems with diverse contexts and reliable evaluation metrics. To fill this gap, we introduce DS-1000, a benchmark with a thousand problems covering seven widely-used Python data science libraries: NumPy, Pandas, TensorFlow, PyTorch, SciPy, Scikit-learn, and Matplotlib. We highlight three core features of DS-1000: 1) it contains realistic problems with diverse contexts, 2) it implements reliable multi-criteria execution-based evaluation metrics, and 3) it proactively defends against memorization. We outline how we achieved each of them below. First, we collected naturally occurring problems from Stack- Overflow, manually scored their representativeness and use- fulness, and curated a subset of them to create our bench- mark. While inputs in existing code generation datasets are either highly structured (problems or code context) or restricted in scope, our natural problems are diverse in con- tent and format. For example, users might search for more arXiv:2211.11501v1 [cs.SE] 18 Nov 2022 DS-1000: A Natural and Reliable Benchmark for Data Science Code Generation result = df.div(1).add_prefix("inv_") Prompt Reference Solution result = df.join(df.apply(lambda x: 1/x).add_prefix(“inv_")) Test case 1 df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}) ans = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6], "inv_A": [1/1, 1/2, 1/3], "inv_B": [1/4, 1/5, 1/6]}) Test case 2 df,ans = ...[omit for brevity] pd.testing.assert_frame_equal(result, ans) Surface-form constraints for and while should not appear in Syntax Tree A: <code> import pandas as pd df = pd.DataFrame({"A": [1, 2, 3],"B": [4, 5, 6]}) </code> BEGIN SOLUTION <code> [insert] </code> END SOLUTION <code> print(result) </code> Here is a sample dataframe: df = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6]}) I'd like to add inverses of each existing column to the dataframe and name them based on existing column names with a prefix, e.g. inv_A is an inverse of column A and so on. The resulting dataframe should look like so: result = pd.DataFrame({"A": [1, 2, 3], "B": [4, 5, 6], "inv_A": [1/1, 1/2, 1/3], "inv_B": [1/4, 1/5, 1/6]}) Obviously there are redundant methods like doing this in a loop, but there should exist much more pythonic ways of doing it … [omitted for brevity] Predict Correct/wrong? Language Models (GPT-3 Codex) Replace [insert] in the code context with following predicted code snippets Problem Code Context Execute to evaluate Multi-criteria Execution-based Evaluation Figure 1: An example problem in DS-1000. The model needs to fill in the code into “[insert]” in the prompt on the left; the code will then be executed to pass the multi-criteria automatic evaluation, which includes the test cases and the surface-form constraints; a reference solution is provided at the bottom left. efficient code implementations (Figure 1), provide incorrect code with an error message and ask for bug fixes (Figure 13), inquire about specific API usage (Figure 14), or ask for code that implements functionality they specify with input-output examples (Figure 1). These problems better reflect real- world applications and open up new modeling challenges, which have been understudied in existing code generation benchmarks. Second, it is challenging to evaluate program solutions to natural and diverse problems reliably. Unlike competition- style problems, natural problems might lack executable con- texts and test cases, allow multiple solutions, depend on external libraries, etc. To address these challenges, five of the authors of this paper, all proficient in data science and experts in Python, hand-adapted the original problems by writing executable code contexts, rewriting problems to be specific enough to be testable, and implementing automatic multi-criteria execution-based evaluation using carefully written and reviewed test cases and constraints that check functional correctness and surface-form constraints. On program solutions predicted by Codex-002, we find that only 1.8% of the predicted programs passing our evalua- tion are incorrect (false discovery rate), indicating that our evaluation is reliable. Third, one potential concern for adapting public problems is that the models might simply memorize the correspond- ing solution during pre-training time (Carlini et al., 2021a). We show in Section 2.4 that this can indeed happen: while Codex achieves 72.5% accuracy on the popular numpy-100 the1 0Table2XX-%AAP22 > What is the correct answer this question: What does N1? Choices: (A)-A0(B(C N-A. (D). Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> { "meta": { "name_exp": "llama-3.1-405b_bar_game_explicit_v1_1", "player_num": 10, "min": 0, "max": 10, "home": 5, "ratio": 0.6, "ratio_str": "60%", "mode": "explicit", "round_id": 20, "version": "v1" }, "round_records": [ { "responses": [ "go", "go", "go", "go", "go", "go", "go", "go", "go", "go" ], "go_num": 10, "go_ratio": 1.0, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "go", "go", "go", "go", "go" ], "go_num": 10, "go_ratio": 1.0, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "stay", "go", "go", "stay", "go", "go", "go", "go" ], "go_num": 8, "go_ratio": 0.8, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "stay", "go", "go", "stay", "go", "go", "go", "go", "go", "go" ], "go_num": 8, "go_ratio": 0.8, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "stay", "go", "stay", "go", "go" ], "go_num": 8, "go_ratio": 0.8, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "stay", "go", "go", "stay", "stay", "go", "go", "go" ], "go_num": 7, "go_ratio": 0.7, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "stay", "stay", "stay", "go", "stay", "stay", "go" ], "go_num": 5, "go_ratio": 0.5, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "go", "go", "go", "go", "go" ], "go_num": 10, "go_ratio": 1.0, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "stay", "go", "stay", "stay", "go", "stay", "stay", "stay" ], "go_num": 4, "go_ratio": 0.4, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "stay", "go", "go", "go", "go" ], "go_num": 9, "go_ratio": 0.9, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "stay", "go", "go", "go", "stay", "stay", "go", "stay", "stay", "stay" ], "go_num": 4, "go_ratio": 0.4, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "stay", "stay", "go", "stay", "go", "stay" ], "go_num": 6, "go_ratio": 0.6, "winner": "go", "utility": 10 } ], "player_data": [ { "model": "meta-llama/Meta-Llama-3.1-405B-Instruct", "id": "player_0", "prompt": [ { "role": "system", "content": "\n\nYou are participating in a game played by 10 players over 20 rounds.\n\nGame Rules:\n\n1. Every round, you and the other players decide independently whether to go to a bar.\n2. If equal to or less than 60% of the players go to the bar, everyone who goes has more fun than staying home, receiving a utility of 10.\n3. If more than 60% of the players go to the bar, everyone who goes has less fun than staying the the the the the the the the the the the the the the the the </text> What is the correct answer to this question: Which players most? Choices: (A) and (B)0 (C) (D)6 Format your response as follows: "The correct answer is (insert answer here)".
273
null
2
C
player_2 and player_6
Please read the following text and answer the question below. <text> { "meta": { "name_exp": "llama-3.1-405b_bar_game_explicit_v1_1", "player_num": 10, "min": 0, "max": 10, "home": 5, "ratio": 0.6, "ratio_str": "60%", "mode": "explicit", "round_id": 20, "version": "v1" }, "round_records": [ { "responses": [ "go", "go", "go", "go", "go", "go", "go", "go", "go", "go" ], "go_num": 10, "go_ratio": 1.0, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "go", "go", "go", "go", "go" ], "go_num": 10, "go_ratio": 1.0, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "stay", "go", "go", "stay", "go", "go", "go", "go" ], "go_num": 8, "go_ratio": 0.8, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "stay", "go", "go", "stay", "go", "go", "go", "go", "go", "go" ], "go_num": 8, "go_ratio": 0.8, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "stay", "go", "stay", "go", "go" ], "go_num": 8, "go_ratio": 0.8, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "stay", "go", "go", "stay", "stay", "go", "go", "go" ], "go_num": 7, "go_ratio": 0.7, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "stay", "stay", "stay", "go", "stay", "stay", "go" ], "go_num": 5, "go_ratio": 0.5, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "go", "go", "go", "go", "go" ], "go_num": 10, "go_ratio": 1.0, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "stay", "go", "stay", "stay", "go", "stay", "stay", "stay" ], "go_num": 4, "go_ratio": 0.4, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "stay", "go", "go", "go", "go" ], "go_num": 9, "go_ratio": 0.9, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "stay", "go", "go", "go", "stay", "stay", "go", "stay", "stay", "stay" ], "go_num": 4, "go_ratio": 0.4, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "stay", "stay", "go", "stay", "go", "stay" ], "go_num": 6, "go_ratio": 0.6, "winner": "go", "utility": 10 } ], "player_data": [ { "model": "meta-llama/Meta-Llama-3.1-405B-Instruct", "id": "player_0", "prompt": [ { "role": "system", "content": "\n\nYou are participating in a game played by 10 players over 20 rounds.\n\nGame Rules:\n\n1. Every round, you and the other players decide independently whether to go to a bar.\n2. If equal to or less than 60% of the players go to the bar, everyone who goes has more fun than staying home, receiving a utility of 10.\n3. If more than 60% of the players go to the bar, everyone who goes has less fun than staying the the the the the the the the the the the the the the the the </text> What is the correct answer to this question: Which players most? Choices: (A) and (B)0 (C) (D)6 Format your response as follows: "The correct answer is (insert answer here)".
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Please read the following text and answer the question below. <text> { "doc": " \n Praise for The Island of Missing Trees \u201cA wise novel of love and grief, roots and branches, displacement and home, faith and belief. The Island of Missing Trees is balm for our bruised times.\u201d \u2014David Mitchell, author of Utopia Avenue \u201cI read The Island of Missing Trees in two sittings, marking sentences and moments as I went, drawn on and gripped by this strange and beautiful story, in which voices both human and arboreal branch toward and entwine with one another. Trees, here, grow through the lives of these unforgettable characters, becoming bearers of memory, makers of metaphor, and witnesses to atrocity. Shafak has written a brilliant novel\u2013\u2013one that rings with her characteristic compassion for the overlooked and the under-loved, for those whom history has exiled, excluded, or separated. I know it will move many readers around the world, as it moved me.\u201d \u2014Robert Macfarlane, author of Underland \u201cThis is an enchanting, compassionate, and wise novel, and storytelling at its most sublime. Though rooted in bloody atrocity, it sings to all the senses.\u201d \u2014Polly Samson, author of A Theater for Dreamers \u201cA wonderfully transporting and magical novel that is, at the same time, revelatory about recent history and the natural world and quietly profound.\u201d \u2014William Boyd, author of Trio \u201cElif Shafak has written an excruciatingly tender love story that transcends cultures, generations and, most remarkably, species. Once under the dappled shade of The Island of Missing Trees, I found myself grieving its inevitable end as one might a dear friend, and scheming ways to make it last. A transformational book about our arboreal relatives, to be cherished and savored.\u201d \u2014Naomi Klein, author of On Fire \u201cA beautiful and magical tale infused with love. Stunning.\u201d \u2014Ruth Jones, author of Us Three \u201cAt once intimate in tone and ambitious in its reach, The Island of Missing Trees is a novel that moves with the urgency of a mystery as it uncovers the story of lovers divided first by war and then, after they are reunited and have a child, by that same war\u2019s enduring psychic wounds. But there is tenderness and humor in this tale, too, and the intense readerly pleasures of a narrative that dances from the insights of ecological science to Greek myth and finally to their surprising merger in what might be called\u2014natural magic.\u201d \u2014Siri Hustvedt, author of Memories of the Future \u201cA beautiful novel about the broken island of Cyprus and its wounded and scarred inhabitants, The Island of Missing Trees teaches us that brokenness can only be healed by love.\u201d \u2014Bernhard Schlink, author of Olga \u201cShafak makes a new home for us in words.\u201d \u2014Colum McCann \u201cOne of the best writers in the world today.\u201d \u2014Hanif Kureishi \u201cA work of brutal beauty and consummate tenderness.\u201d \u2014Simon Schama, on 10 Minutes 38 Seconds in This Strange World \n \n No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage or retrieval system, without prior permission in writing from the publishers. Bloomsbury Publishing Plc does not have any control over, or responsibility for, any third-party websites referred to or in this book. All internet addresses given in this book were correct at the time of going to press. The author and publisher regret any inconvenience caused if addresses have changed or sites have ceased to exist, but can accept no responsibility for any such changes. ISBN: HB: 978-1-63557-859-1; EBOOK: 978-1-63557-860-7 Library of Congress Cataloging-in-Publication Data is available. To find out more about our authors and books visit www.bloomsbury.com and sign up for our newsletters. Bloomsbury books may be purchased for business or promotional use. For information on bulk purchases please contact Macmillan Corporate and Premium Sales Department at specialmarkets@macmillan.com. \n \n Prickly pear growing through wire fence on the border line in Nicosia, Cyprus. Photograph \u00a9 Constantine Markides \n To immigrants and exiles everywhere, the uprooted, the re-rooted, the rootless, And to the trees we left behind, rooted in our memories \u2026 \n Contents Prologue: Island PART ONE How to Bury a Tree PART TWO Roots PART THREE Trunk PART FOUR Branches PART FIVE Ecosystem PART SIX How to Unbury a Tree Note to the Reader Glossary Acknowledgements \n \n Anyone who hasn\u2019t been in the Chilean forest doesn\u2019t know this planet. I have come out of that landscape, that mud, that silence, to roam, to go singing through the world. \u2013 Pablo Neruda, Memoirs It will have blood: They say blood will have blood. Stones have been known to move and trees to speak \u2026 \u2013 William Shakespeare, Macbeth \n Island Once upon a memory, at the far end of the Mediterranean Sea, there lay an island so beautiful and blue that the many travellers, pilgrims, crusaders and merchants who fell in love with it either wanted never to leave or tried to tow it with hemp ropes all the way back to their own countries. Legends, perhaps. But legends are there to tell us what history has forgotten. It has been many years since I fled that place on board a plane, inside a suitcase made of soft black leather, never to return. I have since adopted another land, England, where I have grown and thrived, but not a single day passes that I do not yearn to be back. Home. Motherland. It must still be there where I left it, rising and sinking with the waves that break and foam upon its rugged coastline. At the crossroads of three continents \u2013 Europe, Africa, Asia \u2013 and the Levant, that vast and impenetrable region, vanished entirely from the maps of today. A map is a two-dimensional representation with arbitrary symbols and incised lines that decide who is to be our enemy and who is to be our friend, who deserves our love and who deserves our hatred and who, our sheer indifference. Cartography is another name for stories told by winners. For stories told by those who have lost, there isn\u2019t one. Here is how I remember it: golden beaches, turquoise waters, lucid skies. Every year sea turtles would come ashore to lay their eggs in the powdery sand. The late-afternoon wind brought along the scent of gardenia, cyclamen, lavender, honeysuckle. Branching ropes of wisteria climbed up whitewashed walls, aspiring to reach the clouds, hopeful in the way only dreamers are. When the night kissed your skin, as it always did, you could smell the jasmine on its breath. The moon, here closer to earth, hung bright and gentle over the rooftops, casting a vivid glow on the narrow alleys and cobblestoned streets. And yet shadows found a way to creep through the light. Whispers of distrust and conspiracy rippled in the dark. For the island was riven into two pieces \u2013 the north and the south. A different language, a different script, a different memory prevailed in each, and when they prayed, the islanders, it was seldom to the same god. The capital was split by a partition which sliced right through it like a slash to the heart. Along the demarcation line \u2013 the frontier \u2013 were dilapidated houses riddled with bullet holes, empty courtyards scarred with grenade bursts, boarded stores gone to ruin, ornamented gates hanging at angles from broken hinges, luxury cars from another era rusting away under layers of dust \u to other, in yards in all kinds of landscapes \0 tied to ropeayed and-covered from cold even down directly of \1.u the From. but18 Stranger The day the had was. She. weekend Mid \21120n11os each1 Not1n1110yst Reader Ack Contents5n" } </text> What is the answer to question:: . ['.']\n2. ['n3 ['n4 ['n\nQuery: Considering the given Which the narratives options correct? Choices: (A 213 (B)3 (C)4 (D)2 Format your response as follows: "The correct answer is (insert answer here)".
274
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1
B
4123
Please read the following text and answer the question below. <text> { "doc": " \n Praise for The Island of Missing Trees \u201cA wise novel of love and grief, roots and branches, displacement and home, faith and belief. The Island of Missing Trees is balm for our bruised times.\u201d \u2014David Mitchell, author of Utopia Avenue \u201cI read The Island of Missing Trees in two sittings, marking sentences and moments as I went, drawn on and gripped by this strange and beautiful story, in which voices both human and arboreal branch toward and entwine with one another. Trees, here, grow through the lives of these unforgettable characters, becoming bearers of memory, makers of metaphor, and witnesses to atrocity. Shafak has written a brilliant novel\u2013\u2013one that rings with her characteristic compassion for the overlooked and the under-loved, for those whom history has exiled, excluded, or separated. I know it will move many readers around the world, as it moved me.\u201d \u2014Robert Macfarlane, author of Underland \u201cThis is an enchanting, compassionate, and wise novel, and storytelling at its most sublime. Though rooted in bloody atrocity, it sings to all the senses.\u201d \u2014Polly Samson, author of A Theater for Dreamers \u201cA wonderfully transporting and magical novel that is, at the same time, revelatory about recent history and the natural world and quietly profound.\u201d \u2014William Boyd, author of Trio \u201cElif Shafak has written an excruciatingly tender love story that transcends cultures, generations and, most remarkably, species. Once under the dappled shade of The Island of Missing Trees, I found myself grieving its inevitable end as one might a dear friend, and scheming ways to make it last. A transformational book about our arboreal relatives, to be cherished and savored.\u201d \u2014Naomi Klein, author of On Fire \u201cA beautiful and magical tale infused with love. Stunning.\u201d \u2014Ruth Jones, author of Us Three \u201cAt once intimate in tone and ambitious in its reach, The Island of Missing Trees is a novel that moves with the urgency of a mystery as it uncovers the story of lovers divided first by war and then, after they are reunited and have a child, by that same war\u2019s enduring psychic wounds. But there is tenderness and humor in this tale, too, and the intense readerly pleasures of a narrative that dances from the insights of ecological science to Greek myth and finally to their surprising merger in what might be called\u2014natural magic.\u201d \u2014Siri Hustvedt, author of Memories of the Future \u201cA beautiful novel about the broken island of Cyprus and its wounded and scarred inhabitants, The Island of Missing Trees teaches us that brokenness can only be healed by love.\u201d \u2014Bernhard Schlink, author of Olga \u201cShafak makes a new home for us in words.\u201d \u2014Colum McCann \u201cOne of the best writers in the world today.\u201d \u2014Hanif Kureishi \u201cA work of brutal beauty and consummate tenderness.\u201d \u2014Simon Schama, on 10 Minutes 38 Seconds in This Strange World \n \n No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage or retrieval system, without prior permission in writing from the publishers. Bloomsbury Publishing Plc does not have any control over, or responsibility for, any third-party websites referred to or in this book. All internet addresses given in this book were correct at the time of going to press. The author and publisher regret any inconvenience caused if addresses have changed or sites have ceased to exist, but can accept no responsibility for any such changes. ISBN: HB: 978-1-63557-859-1; EBOOK: 978-1-63557-860-7 Library of Congress Cataloging-in-Publication Data is available. To find out more about our authors and books visit www.bloomsbury.com and sign up for our newsletters. Bloomsbury books may be purchased for business or promotional use. For information on bulk purchases please contact Macmillan Corporate and Premium Sales Department at specialmarkets@macmillan.com. \n \n Prickly pear growing through wire fence on the border line in Nicosia, Cyprus. Photograph \u00a9 Constantine Markides \n To immigrants and exiles everywhere, the uprooted, the re-rooted, the rootless, And to the trees we left behind, rooted in our memories \u2026 \n Contents Prologue: Island PART ONE How to Bury a Tree PART TWO Roots PART THREE Trunk PART FOUR Branches PART FIVE Ecosystem PART SIX How to Unbury a Tree Note to the Reader Glossary Acknowledgements \n \n Anyone who hasn\u2019t been in the Chilean forest doesn\u2019t know this planet. I have come out of that landscape, that mud, that silence, to roam, to go singing through the world. \u2013 Pablo Neruda, Memoirs It will have blood: They say blood will have blood. Stones have been known to move and trees to speak \u2026 \u2013 William Shakespeare, Macbeth \n Island Once upon a memory, at the far end of the Mediterranean Sea, there lay an island so beautiful and blue that the many travellers, pilgrims, crusaders and merchants who fell in love with it either wanted never to leave or tried to tow it with hemp ropes all the way back to their own countries. Legends, perhaps. But legends are there to tell us what history has forgotten. It has been many years since I fled that place on board a plane, inside a suitcase made of soft black leather, never to return. I have since adopted another land, England, where I have grown and thrived, but not a single day passes that I do not yearn to be back. Home. Motherland. It must still be there where I left it, rising and sinking with the waves that break and foam upon its rugged coastline. At the crossroads of three continents \u2013 Europe, Africa, Asia \u2013 and the Levant, that vast and impenetrable region, vanished entirely from the maps of today. A map is a two-dimensional representation with arbitrary symbols and incised lines that decide who is to be our enemy and who is to be our friend, who deserves our love and who deserves our hatred and who, our sheer indifference. Cartography is another name for stories told by winners. For stories told by those who have lost, there isn\u2019t one. Here is how I remember it: golden beaches, turquoise waters, lucid skies. Every year sea turtles would come ashore to lay their eggs in the powdery sand. The late-afternoon wind brought along the scent of gardenia, cyclamen, lavender, honeysuckle. Branching ropes of wisteria climbed up whitewashed walls, aspiring to reach the clouds, hopeful in the way only dreamers are. When the night kissed your skin, as it always did, you could smell the jasmine on its breath. The moon, here closer to earth, hung bright and gentle over the rooftops, casting a vivid glow on the narrow alleys and cobblestoned streets. And yet shadows found a way to creep through the light. Whispers of distrust and conspiracy rippled in the dark. For the island was riven into two pieces \u2013 the north and the south. A different language, a different script, a different memory prevailed in each, and when they prayed, the islanders, it was seldom to the same god. The capital was split by a partition which sliced right through it like a slash to the heart. Along the demarcation line \u2013 the frontier \u2013 were dilapidated houses riddled with bullet holes, empty courtyards scarred with grenade bursts, boarded stores gone to ruin, ornamented gates hanging at angles from broken hinges, luxury cars from another era rusting away under layers of dust \u to other, in yards in all kinds of landscapes \0 tied to ropeayed and-covered from cold even down directly of \1.u the From. but18 Stranger The day the had was. She. weekend Mid \21120n11os each1 Not1n1110yst Reader Ack Contents5n" } </text> What is the answer to question:: . ['.']\n2. ['n3 ['n4 ['n\nQuery: Considering the given Which the narratives options correct? Choices: (A 213 (B)3 (C)4 (D)2 Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> Jump Over ASLR: Attacking Branch Predictors to Bypass ASLR Dmitry Evtyushkin Department of Computer Science State University of New York at Binghamton devtyushkin@cs.binghamton.edu Dmitry Ponomarev Department of Computer Science State University of New York at Binghamton dima@cs.binghamton.edu Nael Abu-Ghazaleh Computer Science and Engineering Department University of California, Riverside naelag@ucr.edu Abstract— Address Space Layout Randomization (ASLR) is a widely- used technique that protects systems against a range of attacks. ASLR works by randomizing the offset of key program segments in virtual memory, making it difficult for an attacker to derive the addresses of specific code objects and consequently redirect the control flow to this code. In this paper, we develop an attack to derive kernel and user-level ASLR offset using a side-channel attack on the branch target buffer (BTB). Our attack exploits the observation that an adversary can create BTB collisions between the branch instructions of the attacker process and either the user-level victim process or on the kernel executing on its behalf. These collisions, in turn, can impact the timing of the attacker’s code, allowing the attacker to identify the locations of known branch instructions in the address space of the victim process or the kernel. We demonstrate that our attack can reliably recover kernel ASLR in about 60 milliseconds when performed on a real Haswell processor running a recent version of Linux. Finally, we describe several possible protection mechanisms, both in software and in hardware. Index Terms—Address Space Layout Randomization, Bypass, Side Channel, Timing Channel, Timing Attacks, Kernel Vulner- abilities, Exploit Mitigation. I. INTRODUCTION Memory corruption attacks such as stack and heap over- flows [1], [2] and format string attacks [3] can lead to control hijacking and arbitrary code execution by the attackers. Despite significant efforts to prevent such attacks [4], [5], [6], [7], [8], they remain a serious exploitable class of vulnera- bilities present in many types of software. Since creating a bug-free environment is practically impossible, systems are often hardened using techniques that substantially reduce the probability of a successful attack. One such hardening technique is Address Space Layout Randomization (ASLR). ASLR provides protection by ran- domizing positions of key program components in virtual memory. The randomization targets code and data segments, stack, heap and libraries. The purpose of ASLR is to make it difficult, if not impossible, for the attacker to know the location of specific code pages in the program’s address space. For example, even if the attacker successfully hijacks the control flow, it would be difficult to perform a meaningful return- oriented programming (ROP) [9], [10], [11] attack under ASLR, because the addresses of ROP gadgets to inject on the stack are not known due to randomization. Relying on brute-force solutions to discover required gadget addresses can cause the program to crash, or it can take prohibitively long time [12], enabling detection by system software [13]. Discovering and exploiting other vulnerabilities that disclose the randomization algorithm significantly complicates the at- tack [14]. Non-control-data attacks [15] require the attacker to know locations of various data structures. Although our attack directly recovers ASLR for the code segment only, data segments are typically not decoupled from code seg- ments [16]; thus a successful attack on code ASLR reveals the locations of data structures. Today, ASLR-based defenses are widely adopted in all major Operating Systems (OS), including Linux [17], Windows [18] and OS X [19]. Smartphone system software such as iOS [20] and Android [13] also use ASLR. ASLR implementations across different operating systems differ by the amount of entropy used and by the frequency at which memory addresses are randomized. These characteris- tics directly determine the resilience of ASLR implementations to possible attacks. For example, 32-bit systems have a much smaller addressable space, limiting the amount of space that can be dedicated to randomization, making it possible to build fast brute-force attacks [12]. The randomization frequency can range from a single randomization at boot or compile time to dynamic randomization during program execution. More frequent re-randomization reduces the probability of a successful attack. Traditionally, ASLR has only been considered as a protec- tion mechanism against remote attacks. As a result, and also for performance reasons [21], some ASLR implementations randomize positions of libraries only one time during the system boot. Consequently, all processes executed on a ma- chine receive the same mappings of the libraries, thus making 978-1-5090-3508-3/16/$31.00 c ⃝2016 IEEE return-to-libc [22], [23] or other code reuse attacks possible within the same system. The presence of many high-privileged processes in the system makes the attack surface large. For example, on our experimental machine, an OS with only basic services executes 30 and 80 root background processes in Ubuntu 14.04 LTS and OS X El Capitan 10.11.2 respectively. If one of these processes is subverted by an attacker, the entire system becomes compromised with respect to ASLR. All current operating systems supporting randomizations implement variants of ASLR for both user and kernel-level ad- dress spaces. Kernel-level ASLR (KASLR) randomizes kernel code segments and can stop attacks that require knowledge of the kernel address space layout (including ROP, jump-oriented programming (JOP), return-to-libc, ret-2-user [24] and other attacks). Unfortunately, current implementations of KASLR are often criticized for incompleteness and insufficient en- tropy [25]. A small entropy is typically justified by the fact that it is infeasible for an adversary to mount a brute-force attack against KASLR. If the attacker guesses the randomization incorrectly, the kernel typically crashes and the attack fails. In this paper, we demonstrate a new attack that can recover all random bits of the kernel addresses and reduce the entropy of user-level randomization by using side-channel information from the Branch Target Buffer (BTB). Our attack only requires the control of a user-level process and does not rely on any explicit memory disclosures. The key insight that makes the new BTB-based side-channel possible is that the BTB collisions between two user-level processes, and between a user process and the kernel, can be created by the attacker in a controlled and robust manner. The collisions can be easily detected by the attacker because they impact the timing of the attacker-controlled code. Identifying the BTB collisions allows the attacker to determine the exact locations of known branch instructions in the code segment of the kernel or of the victim process, thus disclosing the ASLR offset. Our attacks exploit two types of collisions in the BTB. The first collision type, exploited to bypass KASLR, is between a user-level branch and a kernel-level branch - we call it cross- domain collisions, or CDC. CDC occurs because these two branches, located at different virtual addresses, can map to the same entry in the BTB with the same target address. The reason is that the BTB addressing schemes in recent processors ignore the upper-order bits of the address, thus trading off some performance for lower design complexity. The second type of BTB collisions is between two user-level branches that belong to two different applications. We call these collisions same-domain collisions, or SDC. SDCs are used to attack user-level ASLR, allowing one process to identify the ASLR offset used in another. An SDC occurs when two branches, one in each process, have the same virtual address and the same target. We demonstrate our attack on a real system with Haswell CPU and a recent version of Linux kernel equipped with ASLR. Since this new attack adds to the arsenal of a potential adversary, we also discuss a number of possible software and hardware-supported mitigation mechanisms to thwart this attack. The solutions range from further hardening the ASLR implementations to reconsidering the hardware designs of the BTB to avoid collisions. In summary, this paper makes the following contributions: • We describe a new technique to bypass existing ASLR schemes by exploiting a side-channel created through shared BTB. We show how an adversary can create a robust side-channel between a user process and the kernel, as well as between two user processes in a controlled manner. • We show how the details of the BTB addressing scheme, needed for creating a reliable BTB side channelcThis paper2NNN1111 USE7 </text> What is the correct answer to this question: What are the differences? Choices: (A). (B-. (C AS inf. (D) inf. Format your response as follows: "The correct answer is (insert answer here)".
275
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2
C
Jump Over ASLR infers collisions by measuring the execution time of the jump instruction code block in the spy process, while BunnyHop-Reload does so by determining whether the target is prefetched into the cache.
Please read the following text and answer the question below. <text> Jump Over ASLR: Attacking Branch Predictors to Bypass ASLR Dmitry Evtyushkin Department of Computer Science State University of New York at Binghamton devtyushkin@cs.binghamton.edu Dmitry Ponomarev Department of Computer Science State University of New York at Binghamton dima@cs.binghamton.edu Nael Abu-Ghazaleh Computer Science and Engineering Department University of California, Riverside naelag@ucr.edu Abstract— Address Space Layout Randomization (ASLR) is a widely- used technique that protects systems against a range of attacks. ASLR works by randomizing the offset of key program segments in virtual memory, making it difficult for an attacker to derive the addresses of specific code objects and consequently redirect the control flow to this code. In this paper, we develop an attack to derive kernel and user-level ASLR offset using a side-channel attack on the branch target buffer (BTB). Our attack exploits the observation that an adversary can create BTB collisions between the branch instructions of the attacker process and either the user-level victim process or on the kernel executing on its behalf. These collisions, in turn, can impact the timing of the attacker’s code, allowing the attacker to identify the locations of known branch instructions in the address space of the victim process or the kernel. We demonstrate that our attack can reliably recover kernel ASLR in about 60 milliseconds when performed on a real Haswell processor running a recent version of Linux. Finally, we describe several possible protection mechanisms, both in software and in hardware. Index Terms—Address Space Layout Randomization, Bypass, Side Channel, Timing Channel, Timing Attacks, Kernel Vulner- abilities, Exploit Mitigation. I. INTRODUCTION Memory corruption attacks such as stack and heap over- flows [1], [2] and format string attacks [3] can lead to control hijacking and arbitrary code execution by the attackers. Despite significant efforts to prevent such attacks [4], [5], [6], [7], [8], they remain a serious exploitable class of vulnera- bilities present in many types of software. Since creating a bug-free environment is practically impossible, systems are often hardened using techniques that substantially reduce the probability of a successful attack. One such hardening technique is Address Space Layout Randomization (ASLR). ASLR provides protection by ran- domizing positions of key program components in virtual memory. The randomization targets code and data segments, stack, heap and libraries. The purpose of ASLR is to make it difficult, if not impossible, for the attacker to know the location of specific code pages in the program’s address space. For example, even if the attacker successfully hijacks the control flow, it would be difficult to perform a meaningful return- oriented programming (ROP) [9], [10], [11] attack under ASLR, because the addresses of ROP gadgets to inject on the stack are not known due to randomization. Relying on brute-force solutions to discover required gadget addresses can cause the program to crash, or it can take prohibitively long time [12], enabling detection by system software [13]. Discovering and exploiting other vulnerabilities that disclose the randomization algorithm significantly complicates the at- tack [14]. Non-control-data attacks [15] require the attacker to know locations of various data structures. Although our attack directly recovers ASLR for the code segment only, data segments are typically not decoupled from code seg- ments [16]; thus a successful attack on code ASLR reveals the locations of data structures. Today, ASLR-based defenses are widely adopted in all major Operating Systems (OS), including Linux [17], Windows [18] and OS X [19]. Smartphone system software such as iOS [20] and Android [13] also use ASLR. ASLR implementations across different operating systems differ by the amount of entropy used and by the frequency at which memory addresses are randomized. These characteris- tics directly determine the resilience of ASLR implementations to possible attacks. For example, 32-bit systems have a much smaller addressable space, limiting the amount of space that can be dedicated to randomization, making it possible to build fast brute-force attacks [12]. The randomization frequency can range from a single randomization at boot or compile time to dynamic randomization during program execution. More frequent re-randomization reduces the probability of a successful attack. Traditionally, ASLR has only been considered as a protec- tion mechanism against remote attacks. As a result, and also for performance reasons [21], some ASLR implementations randomize positions of libraries only one time during the system boot. Consequently, all processes executed on a ma- chine receive the same mappings of the libraries, thus making 978-1-5090-3508-3/16/$31.00 c ⃝2016 IEEE return-to-libc [22], [23] or other code reuse attacks possible within the same system. The presence of many high-privileged processes in the system makes the attack surface large. For example, on our experimental machine, an OS with only basic services executes 30 and 80 root background processes in Ubuntu 14.04 LTS and OS X El Capitan 10.11.2 respectively. If one of these processes is subverted by an attacker, the entire system becomes compromised with respect to ASLR. All current operating systems supporting randomizations implement variants of ASLR for both user and kernel-level ad- dress spaces. Kernel-level ASLR (KASLR) randomizes kernel code segments and can stop attacks that require knowledge of the kernel address space layout (including ROP, jump-oriented programming (JOP), return-to-libc, ret-2-user [24] and other attacks). Unfortunately, current implementations of KASLR are often criticized for incompleteness and insufficient en- tropy [25]. A small entropy is typically justified by the fact that it is infeasible for an adversary to mount a brute-force attack against KASLR. If the attacker guesses the randomization incorrectly, the kernel typically crashes and the attack fails. In this paper, we demonstrate a new attack that can recover all random bits of the kernel addresses and reduce the entropy of user-level randomization by using side-channel information from the Branch Target Buffer (BTB). Our attack only requires the control of a user-level process and does not rely on any explicit memory disclosures. The key insight that makes the new BTB-based side-channel possible is that the BTB collisions between two user-level processes, and between a user process and the kernel, can be created by the attacker in a controlled and robust manner. The collisions can be easily detected by the attacker because they impact the timing of the attacker-controlled code. Identifying the BTB collisions allows the attacker to determine the exact locations of known branch instructions in the code segment of the kernel or of the victim process, thus disclosing the ASLR offset. Our attacks exploit two types of collisions in the BTB. The first collision type, exploited to bypass KASLR, is between a user-level branch and a kernel-level branch - we call it cross- domain collisions, or CDC. CDC occurs because these two branches, located at different virtual addresses, can map to the same entry in the BTB with the same target address. The reason is that the BTB addressing schemes in recent processors ignore the upper-order bits of the address, thus trading off some performance for lower design complexity. The second type of BTB collisions is between two user-level branches that belong to two different applications. We call these collisions same-domain collisions, or SDC. SDCs are used to attack user-level ASLR, allowing one process to identify the ASLR offset used in another. An SDC occurs when two branches, one in each process, have the same virtual address and the same target. We demonstrate our attack on a real system with Haswell CPU and a recent version of Linux kernel equipped with ASLR. Since this new attack adds to the arsenal of a potential adversary, we also discuss a number of possible software and hardware-supported mitigation mechanisms to thwart this attack. The solutions range from further hardening the ASLR implementations to reconsidering the hardware designs of the BTB to avoid collisions. In summary, this paper makes the following contributions: • We describe a new technique to bypass existing ASLR schemes by exploiting a side-channel created through shared BTB. We show how an adversary can create a robust side-channel between a user process and the kernel, as well as between two user processes in a controlled manner. • We show how the details of the BTB addressing scheme, needed for creating a reliable BTB side channelcThis paper2NNN1111 USE7 </text> What is the correct answer to this question: What are the differences? Choices: (A). (B-. (C AS inf. (D) inf. Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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821, 822, 823, 824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 856, 857, 858, 859, 860, 861, 862, 863, 864, 865, 866, 867, 868, 869, 870, 871, 872, 873, 874, 875, 876, 877, 878, 879, 880, 881, 882, 883, 884, 885, 886, 887, 888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 903, 904, 905, 906, 907, 908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919, 920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939, 940, 941, 942, 943, 944, 945, 946, 947, 948, 949, 950, 951, 952, 953, 954, 955, 956, 957, 958, 959, 960, 961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 971, 972, 973, 974, 975, 976, 977, 978, 979, 980, 981, 982, 983, 984, 985, 986, 987, 988, 989, 990, 991, 992, 993, 994, 995, 996, 997, 998, 999, 1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1011, 1012, 1013, 1014, 1015, 1016, 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1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219, 1220, 1221, 1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1235, 1236, 1237, 1238, 1239, 1240, 1241, 1242, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1251, 1252, 1253, 1254, 1255, 1256, 1257, 1258, 1259, 1260, 1261, 1262, 1263, 1264, 1265, 1266, 1267, 1268, 1269, 1270, 1271, 1272, 1273, 1274, 1275, 1276, 1277, 1278, 1279, 1280, 1281, 1282, 1283, 1284, 1285, 1286, 1287, 1288, 1289, 1290, 1291, 1292, 1293, 1294, 1295, 1296, 1297, 1298, 1299, 1300, 1301, 1302, 1303, 1304, 1305, 1306, 1307, 1308, 1309, 1310, 1311, 1312, 1313, 1314, 1315, 1316, 1317, 1318, 1319, 1320, 1321, 1322, 1323, 1324, 1325, 1326, 1327, 1328, 1329, 1330, 1331, 1332, 1333, 1334, 1335, 1336, 1337, 1338, 1339, 1340, 1341, 1342, 1343, 1344, 1345, 1346, 1347, 1348, 1349, 1350, 1351, 1352, 1353, 1354, 1355, 1356, 1357, 1358, 1359, 1360, 1361, 1362, 1363, 1364, 1365, 1366, 1367, 1368, 1369, 1370, 1371, 1372, 1373, 1374, 1375, 1376, 1377, 1378, 1379, 1380, 1381, 1382, 1383, 1384, 1385, 1386, 1387, 1388, 1389, 1390, 1391, 1392, 1393, 1394, 1395, 1396, 1397, 1398, 1399, 1400, 1401, 1402, 1403, 1404, 1405, 1406, 1407, 1408, 1409, 1410, 1411, 1412, 1413, 1414, 1415, 1416, 1417, 1418, 1419, 1420, 1421, 1422, 1423, 1424, 1425, 1426, 1427, 1428, 1429, 1430, 1431, 1432, 1433, 1434, 1435, 1436, 1437, 1438, 1439, 1440, 1441, 1442, 1443, 1444, 1445, 1446, 1447, 1448, 1449, 1450, 1451, 1452, 1453, 1454, 1455, 1456, 1457, 1458, 1459, 1460, 1461, 1462, 1463, 1464, 1465, 1466, 1467, 1468, 1469, 1470, 1471, 1472, 1473, 1474, 1475, 1476, 1477, 1478, 1479, 1480, 1481, 1482, 1483, 1484, 1485, 1486, 1487, 1488, 1489, 1490, 1491, 1492, 1493, 1494, 1495, 1496, 1497, 1498, 1499, 1500, 1501, 1502, 1503, 1504, 1505, 1506, 1507, 1508, 1509, 1510, 1511, 1512, 1513, 1514, 1515, 1516, 1517, 1518, 1519, 1520, 1521, 1522, 1523, 1524, 1525, 1526, 1527, 1528, 1529, 1530, 1531, 1532, 1533, 1534, 1535, 1536, 1537, 1538, 1539, 1540, 1541, 1542, 1543, 1544, 1545, 1546, 1547, 1548, 1549, 1550, 1551, 1552, 1553, 1554, 1555, 1556, 1557, 1558, 1559, 1560, 1561, 1562, 1563, 1564, 1565, 1566, 1567, 1568, 1569, 1570, 1571, 1572, 1573, 1574, 1575, 1576, 1577, 1578, 1579, 1580, 1581, 1582, 1583, 1584, 1585, 1586, 1587, 1588, 1589, 1590, 1591, 1592, 1593, 1594, 1595, 1596, 1597, 1598, 1599, 1600, 1601, 1602, 1603, 1604, 1605, 1606, 1607, 1608, 1609, 1610, 1611, 1612, 1613, 1614, 1615, 1616, 1617, 1618, 1619, 1620, 1621, 1622, 1623, 1624, 1625, 1626, 1627, 1628, 1629, 1630, 1631, 1632, 1633, 1634, 1635, 1636, 1637, 1638, 1639, 1640, 1641, 1642, 1643, 1644, 1645, 1646, 1647, 1648, 1649, 1650, 1651, 1652, 1653, 1654, 1655, 1656, 1657, 1658, 1659, 1660, 1661, 1662, 1663, 1664, 1665, 1666, 1667, 1668, 1669, 1670, 1671, 1672, 1673, 1674, 1675, 1676, 1677, 1678, 1679, 1680, 1681, 1682, 1683, 1684, 1685, 1686, 1687, 1688, 1689, 1690, 1691, 1692, 1693, 1694, 1695, 1696, 1697, 1698, 1699, 1700, 1701, 1702, 1703, 1704, 1705, 1706, 1707, 1708, 1709, 1710, 1711, 1712, 1713, 1714, 1715, 1716, 1717, 1718, 1719, 1720, 1721, 1722, 1723, 1724, 1725, 1726, 1727, 1728, 1729, 1730, 1731, 1732, 1733, 1734, 1735, 1736, 1737, 1738, 1739, 1740, 1741, 1742, 1743, 1744, 1745, 1746, 1747, 1748, 1749, 1750, 1751, 1752, 1753, 1754, 1755, 1756, 1757, 1758, 1759, 1760, 1761, 1762, 1763, 1764, 1765, 1766, 1767, 1768, 1769, 1770, 1771, 1772, 1773, 1774, 1775, 1776, 1777, 1778, 1779, 1780, 1781, 1782, 1783, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1792, 1793, 1794, 1795, 1796, 1797, 1798, 1799, 1800, 1801, 1802, 1803, 1804, 1805, 1806, 1807, 1808, 1809, 1810, 1811, 1812, 1813, 1814, 1815, 1816, 1817, 1818, 1819, 1820, 1821, 1822, 1823, 1824, 1825, 1826, 1827, 1828, 1829, 1830, 1831, 1832, 1833, 1834, 1835, 1836, 1837, 1838, 1839, 1840, 1841, 1842, 1843, 1844, 1845, 1846, 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0.015548
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Please read the following text and answer the question below. <text> 1 Overview 2 Getting Started 3 Applications for Short Range Radio Communications 4 Applications for Mobile Communication 5 Commissioning 6 Operation 7 Time Synchronization 8 Communication Protocols 9 Technical Data 10 Device Maintenance, Storage, Transport 11 Failures and LED Indications 12 Operational Indications 13 Operational Parameters 14 SICAM FCG and SICAM FSI Firmware Compatibility A Literature Glossary Index i i NOTE For your own safety, observe the warnings and safety instructions contained in this document, if available. Disclaimer of Liability Subject to changes and errors. The information given in this document only contains general descriptions and/or performance features which may not always specifically reflect those described, or which may undergo modifica- tion in the course of further development of the products. The requested performance features are binding only when they are expressly agreed upon in the concluded contract. Document version: E50417-H1040-C584-B7.00 Edition: 04.2024 Version of the product described: V04.21 Copyright Copyright © Siemens 2024. All rights reserved. The disclosure, duplication, distribution and editing of this document, or utilization and communication of the content are not permitted, unless authorized in writing. All rights, including rights created by patent grant or registration of a utility model or a design, are reserved. Trademarks SIPROTEC, DIGSI, SIGRA, SIGUARD, SIMEAS, SAFIR, SICAM, and MindSphere are trademarks of Siemens. Any unauthor- ized use is prohibited. Preface Purpose of the Manual This manual describes the application, functions, installation, commissioning, and operation of the Fault Collector Gateway 6MD2340. Target Audience This manual is intended for project engineers, commissioning engineers, and operating personnel in electrical systems and substations. Scope This manual is valid for the Fault Collector Gateway 6MD2340. Indication of Conformity This product complies with the directive of the Council of the European Communities on the harmonization of the laws of the Member States relating to electromagnetic compatibility (EMC Directive 2014/30/EU) and concerning electrical equipment for use within specified voltage limits (Low Voltage Directive 2014/35/EU) as well as restriction on usage of hazardous substances in electrical and electronic equipment (RoHS Direc- tive 2011/65/EU). This conformity has been proved by tests conducted by Siemens AG in accordance of the Council Directive in accordance with the product standard IEC/EN 61326-1 for the EMC directives, and with the standard IEC/EN 61010-1 for the low-voltage directive. Standards for short-range radio and mobile communication acc. to RED directive 2014/53/EU: • EMC testing acc. to EN 301 489 • Radio testing acc. to EN 301 511 • Short-range radio acc. to EN 300 328 RoHS directive 2011/65/EU is met using the standard IEC/EN 63000. The device has been designed and produced for industrial use. FCC Conformity Information This device complies with part 15 of the FCC rules. Operation is subject to the following 2 conditions: • This device may not cause harmful interference. • This device must accept any interference received, including interference that may cause undesired operation. This equipment has been tested and found to comply with the limits for a Class A digital device, pursuant to part 15 of the FCC rules. These limits are designed to provide reasonable protection against harmful interference when the equipment is operated in a commercial environment. This equipment generates, uses, and can radiate radio frequency energy and, if not installed and used in accordance with the instructions, may cause harmful interference to radio communications. Operation of this equipment in a residential area is likely SICAM, Fault Collector Gateway, Manual 3 E50417-H1040-C584-B7, Edition 04.2024 to cause harmful interference in which case the user will be required to correct the interference at their own expense. i i NOTE Any changes or modifications not expressly approved by the party responsible for compliance could void the users’ authority to operate this equipment. ! CAUTION Radiation RF exposure This equipment complies with FCC radiation exposure limits set forth for an uncontrolled environ- ment. ² This equipment should be installed and operated with minimum distance 20 cm between the radiator and your body. ISED Compliance Statement This device complies with ISED's license-exempt RSSs. Operation is subject to the following 2 conditions: • This device may not cause harmful interference. • This device must accept any interference received, including interference that may cause undesired operation. Cet appareil est conforme aux RSS exemptés de licence de l’ISED. L’opération est soumise aux 2 conditions suivantes : • Cet appareil ne peut pas causer d’interférences nocives. • Cet appareil doit accepter toute interférence, y compris les interférences qui peuvent provoquer un fonctionnement non désiré de l’appareil. ! CAUTION Radiation RF exposure This equipment complies with ISED radiation exposure limits set forth for an uncontrolled environ- ment. ² This equipment should be installed and operated with minimum distance 20 cm between the radiator and your body. ! CAUTION Déclaration sur l’exposition aux rayonnements Cet équipement est conforme aux limites d’exposition aux rayonnements. ISED établies pour un environnement non contrôlé. ² Cet équipement doit être installé et actionné avec la distance minimale 20 cm entre le radiateur et votre corps. Preface 4 SICAM, Fault Collector Gateway, Manual E50417-H1040-C584-B7, Edition 04.2024 Detachable Antenna Usage This radio transmitter (IC: 5123A-GM210P and IC: 5131A-GE910) has been approved by ISED to operate with the antenna type listed below with maximum permissible gain indicated. Antenna types not included in this list, having a gain greater than the maximum gain indicated for that type, are strictly prohibited for use with this device. Antenna Name Antenna Type Antenna Gain (dBi) Transmitting Power Level Antenna Part No. Planar Mobile Commu- nications Antenna-Reel Make-WLAN 2400 MHz M70XCR Roof Mount 0 dBi 20 dBm 6MD2318-0CA20 Planar Mobile Commu- nications Antenna-Reel Make GSM Quadband + UMTS M70ZXR Roof Mount 0 dBi 850 MHz: 33 dBm (Power Class 5) 1900 MHz: 30 dBm (Power Class 0) 6MD2318-0CA10 i i NOTE • The device integrates a ZigBee transmitter having FCC ID: QOQGM210P, IC ID: 5123A-GM210P and 2G module transmitter having FCC ID: R17GE910, IC ID: 5131A-GE910 for radio communication. The RF modules are integrated to this host product as per module integration guidelines defined in module grants and FCC KDB 996369. Co-location/simultaneous transmission requirements are addressed in this host test report as per guidelines defined in KDB 447498. • RF exposure evaluation for co-locating and simultaneous operation of ZigBee and 2G protocol have been addressed and results are compliant to FCC and IC RF exposure evaluation limits. Module Name FCC ID IC ID Operating Frequency Range ZigBee module QOQGM210P 5123A-GM210P 2400 MHz to 2483.5 MHz 2G Module R17GE910 5 MHz MHz this Binary ......................4 F.............................. 4........................................................................... 9142 5 NNOTENOTE4! ANGER iNOTE5ICNOTENOTE04 Collector4 Collector104 CollectorIC41 F Fby is is the840E 34 SIC, 04 </text> What is the correct answer to this question: Which of the following is incorrect according to the manual? Choices: (A) A F. (B) F.example value. (C)1". (D) When IIC F. Format your response as follows: "The correct answer is (insert answer here)".
276
null
2
C
IP Address of "192.168.0.55" is used after I press the IP-Addr. push-button for > 3 seconds. The LED on the terminal side will indicate "Default IP address is applied".
Please read the following text and answer the question below. <text> 1 Overview 2 Getting Started 3 Applications for Short Range Radio Communications 4 Applications for Mobile Communication 5 Commissioning 6 Operation 7 Time Synchronization 8 Communication Protocols 9 Technical Data 10 Device Maintenance, Storage, Transport 11 Failures and LED Indications 12 Operational Indications 13 Operational Parameters 14 SICAM FCG and SICAM FSI Firmware Compatibility A Literature Glossary Index i i NOTE For your own safety, observe the warnings and safety instructions contained in this document, if available. Disclaimer of Liability Subject to changes and errors. The information given in this document only contains general descriptions and/or performance features which may not always specifically reflect those described, or which may undergo modifica- tion in the course of further development of the products. The requested performance features are binding only when they are expressly agreed upon in the concluded contract. Document version: E50417-H1040-C584-B7.00 Edition: 04.2024 Version of the product described: V04.21 Copyright Copyright © Siemens 2024. All rights reserved. The disclosure, duplication, distribution and editing of this document, or utilization and communication of the content are not permitted, unless authorized in writing. All rights, including rights created by patent grant or registration of a utility model or a design, are reserved. Trademarks SIPROTEC, DIGSI, SIGRA, SIGUARD, SIMEAS, SAFIR, SICAM, and MindSphere are trademarks of Siemens. Any unauthor- ized use is prohibited. Preface Purpose of the Manual This manual describes the application, functions, installation, commissioning, and operation of the Fault Collector Gateway 6MD2340. Target Audience This manual is intended for project engineers, commissioning engineers, and operating personnel in electrical systems and substations. Scope This manual is valid for the Fault Collector Gateway 6MD2340. Indication of Conformity This product complies with the directive of the Council of the European Communities on the harmonization of the laws of the Member States relating to electromagnetic compatibility (EMC Directive 2014/30/EU) and concerning electrical equipment for use within specified voltage limits (Low Voltage Directive 2014/35/EU) as well as restriction on usage of hazardous substances in electrical and electronic equipment (RoHS Direc- tive 2011/65/EU). This conformity has been proved by tests conducted by Siemens AG in accordance of the Council Directive in accordance with the product standard IEC/EN 61326-1 for the EMC directives, and with the standard IEC/EN 61010-1 for the low-voltage directive. Standards for short-range radio and mobile communication acc. to RED directive 2014/53/EU: • EMC testing acc. to EN 301 489 • Radio testing acc. to EN 301 511 • Short-range radio acc. to EN 300 328 RoHS directive 2011/65/EU is met using the standard IEC/EN 63000. The device has been designed and produced for industrial use. FCC Conformity Information This device complies with part 15 of the FCC rules. Operation is subject to the following 2 conditions: • This device may not cause harmful interference. • This device must accept any interference received, including interference that may cause undesired operation. This equipment has been tested and found to comply with the limits for a Class A digital device, pursuant to part 15 of the FCC rules. These limits are designed to provide reasonable protection against harmful interference when the equipment is operated in a commercial environment. This equipment generates, uses, and can radiate radio frequency energy and, if not installed and used in accordance with the instructions, may cause harmful interference to radio communications. Operation of this equipment in a residential area is likely SICAM, Fault Collector Gateway, Manual 3 E50417-H1040-C584-B7, Edition 04.2024 to cause harmful interference in which case the user will be required to correct the interference at their own expense. i i NOTE Any changes or modifications not expressly approved by the party responsible for compliance could void the users’ authority to operate this equipment. ! CAUTION Radiation RF exposure This equipment complies with FCC radiation exposure limits set forth for an uncontrolled environ- ment. ² This equipment should be installed and operated with minimum distance 20 cm between the radiator and your body. ISED Compliance Statement This device complies with ISED's license-exempt RSSs. Operation is subject to the following 2 conditions: • This device may not cause harmful interference. • This device must accept any interference received, including interference that may cause undesired operation. Cet appareil est conforme aux RSS exemptés de licence de l’ISED. L’opération est soumise aux 2 conditions suivantes : • Cet appareil ne peut pas causer d’interférences nocives. • Cet appareil doit accepter toute interférence, y compris les interférences qui peuvent provoquer un fonctionnement non désiré de l’appareil. ! CAUTION Radiation RF exposure This equipment complies with ISED radiation exposure limits set forth for an uncontrolled environ- ment. ² This equipment should be installed and operated with minimum distance 20 cm between the radiator and your body. ! CAUTION Déclaration sur l’exposition aux rayonnements Cet équipement est conforme aux limites d’exposition aux rayonnements. ISED établies pour un environnement non contrôlé. ² Cet équipement doit être installé et actionné avec la distance minimale 20 cm entre le radiateur et votre corps. Preface 4 SICAM, Fault Collector Gateway, Manual E50417-H1040-C584-B7, Edition 04.2024 Detachable Antenna Usage This radio transmitter (IC: 5123A-GM210P and IC: 5131A-GE910) has been approved by ISED to operate with the antenna type listed below with maximum permissible gain indicated. Antenna types not included in this list, having a gain greater than the maximum gain indicated for that type, are strictly prohibited for use with this device. Antenna Name Antenna Type Antenna Gain (dBi) Transmitting Power Level Antenna Part No. Planar Mobile Commu- nications Antenna-Reel Make-WLAN 2400 MHz M70XCR Roof Mount 0 dBi 20 dBm 6MD2318-0CA20 Planar Mobile Commu- nications Antenna-Reel Make GSM Quadband + UMTS M70ZXR Roof Mount 0 dBi 850 MHz: 33 dBm (Power Class 5) 1900 MHz: 30 dBm (Power Class 0) 6MD2318-0CA10 i i NOTE • The device integrates a ZigBee transmitter having FCC ID: QOQGM210P, IC ID: 5123A-GM210P and 2G module transmitter having FCC ID: R17GE910, IC ID: 5131A-GE910 for radio communication. The RF modules are integrated to this host product as per module integration guidelines defined in module grants and FCC KDB 996369. Co-location/simultaneous transmission requirements are addressed in this host test report as per guidelines defined in KDB 447498. • RF exposure evaluation for co-locating and simultaneous operation of ZigBee and 2G protocol have been addressed and results are compliant to FCC and IC RF exposure evaluation limits. Module Name FCC ID IC ID Operating Frequency Range ZigBee module QOQGM210P 5123A-GM210P 2400 MHz to 2483.5 MHz 2G Module R17GE910 5 MHz MHz this Binary ......................4 F.............................. 4........................................................................... 9142 5 NNOTENOTE4! ANGER iNOTE5ICNOTENOTE04 Collector4 Collector104 CollectorIC41 F Fby is is the840E 34 SIC, 04 </text> What is the correct answer to this question: Which of the following is incorrect according to the manual? Choices: (A) A F. (B) F.example value. (C)1". (D) When IIC F. Format your response as follows: "The correct answer is (insert answer here)".
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0.01104
185,512
Please read the following text and answer the question below. <text> { "doc": " \n \n Contents Cover Title Page Dedication Contents Author\u2019s Note September 1953 Turtle Mountain Jewel Bearing Plant Lard on Bread The Watcher The Skin Tent Three Men The Boxing Coach Noko Water Earth Juggie\u2019s Boy Valentine\u2019s Days Pukkons Perfume The Iron The Fruit Crate A Seat on the Train A Bill Who? Indian Joke Who? Flags Log Jam 26 The Wake-Up Shave The Old Muskrat The Waterjack Left Hook Louis Pipestone Ajax Iron Tulip Woodland Beauty The Average Woman and the Empty Tank The Missionaries The Beginning The Temple Beggar Wild Rooster Arthur V. Watkins Cool Fine The Torus Metal Blinds X = ? Twin Dreams The Star Powwow Agony Would Be Her Name Homecoming The Bush Dance Hay Stack Thwack The Tonsils A Letter to the University of Minnesota The Chippewa Scholar What She Needed Old Man Winter The Cradle Board Battle Royale Two-Day Journey Boxing for Sovereignty The Promotion Edith, Psychic Dog The Hungry Man Good News Bad News Flying over Snow Snares Cradle to Grave The Night Watch Two Months New Year\u2019s Soup The Names Elnath and Vernon Night Bird U.S.I.S. The Runner Missionary Feet The Spirit Duplicator Prayer for 1954 You Can\u2019t Assimilate Indian Ghosts Clark Kent Checks The Lamanites The Lord\u2019s Plan The Committee Scrawny The Journey Falcon Eyes Termination of Federal Contracts and Promises Made with Certain Tribes of Indians The Way Home If Tosca The Salisbury The Lake, the Well, the Crickets Singing in the Grass The Ceiling Greater Joy The Owls The Bear Skull in the Tree Was Painted Red and Faced East The Duplicator Spirits \u00c0 Ta Sant\u00e9 Roderick Thomas Afterword and Acknowledgments About the Author Also by Louise Erdrich Copyright About the Publisher \n Dedication To Aunishenaubay, Patrick Gourneau; to his daughter Rita, my mother; and to all of the American Indian leaders who fought against termination. \n Author\u2019s Note On August 1, 1953, the United States Congress announced House Concurrent Resolution 108, a bill to abrogate nation-to-nation treaties, which had been made with American Indian Nations for \u201cas long as the grass grows and the rivers flow.\u201d The announcement called for the eventual termination of all tribes, and the immediate termination of five tribes, including the Turtle Mountain Band of Chippewa. My grandfather Patrick Gourneau fought against termination as tribal chairman while working as a night watchman. He hardly slept, like my character Thomas Wazhashk. This book is fiction. But all the same, I have tried to be faithful to my grandfather\u2019s extraordinary life. Any failures are my own. Other than Thomas, and the Turtle Mountain Jewel Bearing Plant, the only other major character who resembles anyone alive or dead is Senator Arthur V. Watkins, relentless pursuer of Native dispossession and the man who interrogated my grandfather. Pixie, or\u2014excuse me\u2014Patrice, is completely fictional. \n September 1953 \n Turtle Mountain Jewel Bearing Plant Thomas Wazhashk removed his thermos from his armpit and set it on the steel desk alongside his scuffed briefcase. His work jacket went on the chair, his lunch box on the cold windowsill. When he took off his padded tractor hat, a crab apple fell from the earflap. A gift from his daughter Fee. He caught the apple and put it out on the desktop to admire. Then punched his time card. Midnight. He picked up the key ring, a company flashlight, and walked the perimeter of the main floor. In this quiet, always quiet expanse, Turtle Mountain women spent their days leaning into the hard light of their task lamps. The women pasted micro-thin slices of ruby, sapphire, or the lesser jewel, garnet, onto thin upright spindles in preparation for drilling. The jewel bearings would be used in Defense Department ordnance and in Bulova watches. This was the first time there had ever been manufacturing jobs near the reservation, and women filled most of these coveted positions. They had scored much higher on tests for manual dexterity. The government attributed their focus to Indian blood and training in Indian beadwork. Thomas thought it was their sharp eyes\u2014the women of his tribe could spear you with a glance. He\u2019d been lucky to get his own job. He was smart and honest, but he wasn\u2019 and.2 of to laugh hop to and and came backat be0 of Dor.u told2. rolling for, and she swallowed her watered She was all through, whisper to to offing and wrote towith her from got out and other was let him out for a while and learnedat beside off to leave she climbing, around passed cooking fire ontoy track entrance of easeie Boy they Wood Mountain W. They211\u Shar along.. throughks looked sitting next to Mr Barnes They was about to begin vsski vsignant other halfed half happy with outcome Howard Old Man cheered and Indians pitched in Old Man had picked up their Then Joeobble and Wood Mountain came the crowd1 ring He Mountain1 both confident and dancing Mountain\uancingly kissed at9 Wood again Joes momentum tosectionening him up perhaps, or maybe Joe was too and Valentine were back row. Pat didn\u Min, and. way and Rose and a front her, arms,lo. rest of he saw was. he been studying drawing would have been a blow it turned out as it was supposed to turn out too, wereteringably fallen out of everyone had quickly girls better1 asleep poured out ofuilleille,led outensible he at of officers and Archille were thrown in a truck with others, trundled down to way, they learned someille becameuated with who able and complete mystery, Valentine Pat9sauu \ all go right aheadu0 seemed at ofu1 \1old111 all1111atricerice says Grass2.2u Pix000? work next and.m Archie. As you10. jacket and hey question Who?oke Walter and! Doris Lauder02020 Dor Las Flags.00 As train Fargo, Wood Mountain Patrice \2u.\ town Pixie10 Pix As her.. aisle. downtown Fargo. Wood0 slept0 When In The Pat awake \220 windowc,\.0 and passengers along aisle.rice stepped down onto platform and a theing and area. were benches, like. The She sat. She lipstick, and. People mirror She to window. walked to window.c dear, the curb0 lady out and Barnes little that?0 that.. \\u barsseat, her lobby.um2 bars. *.. He shave It morning, morning shift shaved and, andd \0d cup tea for the two.oon took a of. tea The. The night meeting. They thejack.. Now On the downtown, in the car, Jack spoke to her.2 set. foundrice tois Barnes, Barnes,, the was2 lay nightc her22 Cool the was fine afternoon Wood walked alongsiderice,22122wf1sp2 News11n Grave Thomas Night After!\ Woodn Months Thomas The There.?. me?. Couldn Nor20. It Mill1 Just Then Ohn Namesn Eath Theylnn Bird Shenn Runner the Thomas Thomasnnn Thennnnn1nnnnnn ann Thomaslo2n00 isn2\u0000n R0n002n *1n1222 The Cloudc It He On,1 He Iz \n Louisedrich. Her. Louiseich,.. \nich The The21 Report the The The Drum The TheRose Selected12 Jack Desiremother29eoons Jay2n \n Copyright.02 Louise Erdrich.., HarperCollins. Coverzadr Cover Milan Bozic Title illustrationu0 Laura Hartman.ARCH 2n About the Publisher Australia HarperCollins..2 Elizabeth Street Sydney NSW, Australiains.au Canada HarperColl Publishers Bay Adelaide Centre, Adelaide Street Floor Toronto, Ontario5HE3.ca IndiaColl,oida Uttar Pradesh wwwins.in ZealandCollins Publishers Apollo Drive Rosedale Auckland Zealand www.co.nz KingdomColl Publishers Ltd. London Bridge Street London1GF, UK www.har.co.uk StatesCollins Publishers. 5 Broadway York, NY www.har.com \n" } </text> What is the answer this question: Narrives: . ['Patrice and Wood Mountain mealican train as they discuss her her the Cities.']\n2. ['Millie, who was cold wearing clothes, quietly joined Grace the in their bedroom to.']\n3. ['Thomas Waz and Turtle Mountain Band attended a meeting where they listened to Mr. Holmes read a the termination, the their.']\n4. ['Roderick, a, eat chicken the at the, reflecting his experiences in.']\n\nQuery: Considering the book and narratives, Which order the the options correct? Choices: (A) (B) (C) (D) 2 Format your response as follows: "The correct answer is ( answer here)".
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Please read the following text and answer the question below. <text> { "doc": " \n \n Contents Cover Title Page Dedication Contents Author\u2019s Note September 1953 Turtle Mountain Jewel Bearing Plant Lard on Bread The Watcher The Skin Tent Three Men The Boxing Coach Noko Water Earth Juggie\u2019s Boy Valentine\u2019s Days Pukkons Perfume The Iron The Fruit Crate A Seat on the Train A Bill Who? Indian Joke Who? Flags Log Jam 26 The Wake-Up Shave The Old Muskrat The Waterjack Left Hook Louis Pipestone Ajax Iron Tulip Woodland Beauty The Average Woman and the Empty Tank The Missionaries The Beginning The Temple Beggar Wild Rooster Arthur V. Watkins Cool Fine The Torus Metal Blinds X = ? Twin Dreams The Star Powwow Agony Would Be Her Name Homecoming The Bush Dance Hay Stack Thwack The Tonsils A Letter to the University of Minnesota The Chippewa Scholar What She Needed Old Man Winter The Cradle Board Battle Royale Two-Day Journey Boxing for Sovereignty The Promotion Edith, Psychic Dog The Hungry Man Good News Bad News Flying over Snow Snares Cradle to Grave The Night Watch Two Months New Year\u2019s Soup The Names Elnath and Vernon Night Bird U.S.I.S. The Runner Missionary Feet The Spirit Duplicator Prayer for 1954 You Can\u2019t Assimilate Indian Ghosts Clark Kent Checks The Lamanites The Lord\u2019s Plan The Committee Scrawny The Journey Falcon Eyes Termination of Federal Contracts and Promises Made with Certain Tribes of Indians The Way Home If Tosca The Salisbury The Lake, the Well, the Crickets Singing in the Grass The Ceiling Greater Joy The Owls The Bear Skull in the Tree Was Painted Red and Faced East The Duplicator Spirits \u00c0 Ta Sant\u00e9 Roderick Thomas Afterword and Acknowledgments About the Author Also by Louise Erdrich Copyright About the Publisher \n Dedication To Aunishenaubay, Patrick Gourneau; to his daughter Rita, my mother; and to all of the American Indian leaders who fought against termination. \n Author\u2019s Note On August 1, 1953, the United States Congress announced House Concurrent Resolution 108, a bill to abrogate nation-to-nation treaties, which had been made with American Indian Nations for \u201cas long as the grass grows and the rivers flow.\u201d The announcement called for the eventual termination of all tribes, and the immediate termination of five tribes, including the Turtle Mountain Band of Chippewa. My grandfather Patrick Gourneau fought against termination as tribal chairman while working as a night watchman. He hardly slept, like my character Thomas Wazhashk. This book is fiction. But all the same, I have tried to be faithful to my grandfather\u2019s extraordinary life. Any failures are my own. Other than Thomas, and the Turtle Mountain Jewel Bearing Plant, the only other major character who resembles anyone alive or dead is Senator Arthur V. Watkins, relentless pursuer of Native dispossession and the man who interrogated my grandfather. Pixie, or\u2014excuse me\u2014Patrice, is completely fictional. \n September 1953 \n Turtle Mountain Jewel Bearing Plant Thomas Wazhashk removed his thermos from his armpit and set it on the steel desk alongside his scuffed briefcase. His work jacket went on the chair, his lunch box on the cold windowsill. When he took off his padded tractor hat, a crab apple fell from the earflap. A gift from his daughter Fee. He caught the apple and put it out on the desktop to admire. Then punched his time card. Midnight. He picked up the key ring, a company flashlight, and walked the perimeter of the main floor. In this quiet, always quiet expanse, Turtle Mountain women spent their days leaning into the hard light of their task lamps. The women pasted micro-thin slices of ruby, sapphire, or the lesser jewel, garnet, onto thin upright spindles in preparation for drilling. The jewel bearings would be used in Defense Department ordnance and in Bulova watches. This was the first time there had ever been manufacturing jobs near the reservation, and women filled most of these coveted positions. They had scored much higher on tests for manual dexterity. The government attributed their focus to Indian blood and training in Indian beadwork. Thomas thought it was their sharp eyes\u2014the women of his tribe could spear you with a glance. He\u2019d been lucky to get his own job. He was smart and honest, but he wasn\u2019 and.2 of to laugh hop to and and came backat be0 of Dor.u told2. rolling for, and she swallowed her watered She was all through, whisper to to offing and wrote towith her from got out and other was let him out for a while and learnedat beside off to leave she climbing, around passed cooking fire ontoy track entrance of easeie Boy they Wood Mountain W. They211\u Shar along.. throughks looked sitting next to Mr Barnes They was about to begin vsski vsignant other halfed half happy with outcome Howard Old Man cheered and Indians pitched in Old Man had picked up their Then Joeobble and Wood Mountain came the crowd1 ring He Mountain1 both confident and dancing Mountain\uancingly kissed at9 Wood again Joes momentum tosectionening him up perhaps, or maybe Joe was too and Valentine were back row. Pat didn\u Min, and. way and Rose and a front her, arms,lo. rest of he saw was. he been studying drawing would have been a blow it turned out as it was supposed to turn out too, wereteringably fallen out of everyone had quickly girls better1 asleep poured out ofuilleille,led outensible he at of officers and Archille were thrown in a truck with others, trundled down to way, they learned someille becameuated with who able and complete mystery, Valentine Pat9sauu \ all go right aheadu0 seemed at ofu1 \1old111 all1111atricerice says Grass2.2u Pix000? work next and.m Archie. As you10. jacket and hey question Who?oke Walter and! Doris Lauder02020 Dor Las Flags.00 As train Fargo, Wood Mountain Patrice \2u.\ town Pixie10 Pix As her.. aisle. downtown Fargo. Wood0 slept0 When In The Pat awake \220 windowc,\.0 and passengers along aisle.rice stepped down onto platform and a theing and area. were benches, like. The She sat. She lipstick, and. People mirror She to window. walked to window.c dear, the curb0 lady out and Barnes little that?0 that.. \\u barsseat, her lobby.um2 bars. *.. He shave It morning, morning shift shaved and, andd \0d cup tea for the two.oon took a of. tea The. The night meeting. They thejack.. Now On the downtown, in the car, Jack spoke to her.2 set. foundrice tois Barnes, Barnes,, the was2 lay nightc her22 Cool the was fine afternoon Wood walked alongsiderice,22122wf1sp2 News11n Grave Thomas Night After!\ Woodn Months Thomas The There.?. me?. Couldn Nor20. It Mill1 Just Then Ohn Namesn Eath Theylnn Bird Shenn Runner the Thomas Thomasnnn Thennnnn1nnnnnn ann Thomaslo2n00 isn2\u0000n R0n002n *1n1222 The Cloudc It He On,1 He Iz \n Louisedrich. Her. Louiseich,.. \nich The The21 Report the The The Drum The TheRose Selected12 Jack Desiremother29eoons Jay2n \n Copyright.02 Louise Erdrich.., HarperCollins. Coverzadr Cover Milan Bozic Title illustrationu0 Laura Hartman.ARCH 2n About the Publisher Australia HarperCollins..2 Elizabeth Street Sydney NSW, Australiains.au Canada HarperColl Publishers Bay Adelaide Centre, Adelaide Street Floor Toronto, Ontario5HE3.ca IndiaColl,oida Uttar Pradesh wwwins.in ZealandCollins Publishers Apollo Drive Rosedale Auckland Zealand www.co.nz KingdomColl Publishers Ltd. London Bridge Street London1GF, UK www.har.co.uk StatesCollins Publishers. 5 Broadway York, NY www.har.com \n" } </text> What is the answer this question: Narrives: . ['Patrice and Wood Mountain mealican train as they discuss her her the Cities.']\n2. ['Millie, who was cold wearing clothes, quietly joined Grace the in their bedroom to.']\n3. ['Thomas Waz and Turtle Mountain Band attended a meeting where they listened to Mr. Holmes read a the termination, the their.']\n4. ['Roderick, a, eat chicken the at the, reflecting his experiences in.']\n\nQuery: Considering the book and narratives, Which order the the options correct? Choices: (A) (B) (C) (D) 2 Format your response as follows: "The correct answer is ( answer here)".
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821, 822, 823, 824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 856, 857, 858, 859, 860, 861, 862, 863, 864, 865, 866, 867, 868, 869, 870, 871, 872, 873, 874, 875, 876, 877, 878, 879, 880, 881, 882, 883, 884, 885, 886, 887, 888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 903, 904, 905, 906, 907, 908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919, 920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939, 940, 941, 942, 943, 944, 945, 946, 947, 948, 949, 950, 951, 952, 953, 954, 955, 956, 957, 958, 959, 960, 961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 971, 972, 973, 974, 975, 976, 977, 978, 979, 980, 981, 982, 983, 984, 985, 986, 987, 988, 989, 990, 991, 992, 993, 994, 995, 996, 997, 998, 999, 1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1011, 1012, 1013, 1014, 1015, 1016, 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Please read the following text and answer the question below. <text> Interest Rate Cuts vs. Stimulus Payments: An Equivalence Result Abstract: I derive a general condition on consumer behavior ensuring that, in a simple textbook model of demand-determined output, any path of aggregate inflation and output that is implementable via interest rate policy is also imple- mentable through time-varying uniform lump-sum transfers (“stimulus checks”) alone. The condition is satisfied in popular models of non-Ricardian consumer behavior (e.g., HANK, OLG). Across these models, the transfer-only policy that closes a given demand shortfall is well-characterized by a small number of mea- surable sufficient statistics. My results extend to environments with investment if transfers are supplemented by a second standard fiscal tool—bonus depreciation. †Email: ckwolf@mit.edu. I am grateful to the Editor, Andy Atkeson, and three anonymous referees for their extremely useful feedback. I also received helpful comments from Mark Aguiar, Manuel Amador, Marios Angeletos, Cristina Arellano, Gadi Barlevy, Martin Beraja, Anmol Bhandari, Lukas Freund, Erik Hurst, Oleg Itskhoki, Greg Kaplan, Loukas Karabarbounis, Jennifer La’O, Alisdair McKay, Amanda Michaud, Benjamin Moll, Simon Mongey, Jonathan Parker, Mikkel Plagborg-Møller, Ricardo Reis, Harald Uhlig, Gianluca Violante, Tom Winberry, Iv´ an Werning, and seminar participants at various venues. I thank Isabel Di Tella for outstanding research assistance. 1 1 Introduction The prescription of standard New Keynesian theory is to conduct stabilization policy through changes in short-term interest rates. In recent years, much policy and academic interest has centered on the question of whether—and if so, how—alternative policy tools could be used to replicate monetary stimulus when nominal interest rates are constrained by a zero or effective lower bound (ELB).1 Prior work has in particular identified tax policy, often labeled unconventional fiscal policy, as an attractive option (Correia et al., 2008, 2013): time-varying tax rates manipulate intertemporal prices just like monetary policy and thus can replicate any desired monetary allocation. In this paper I ask whether conventional fiscal policy—that is, fiscal instruments that are already part of the standard stabilization policy toolkit—are similarly sufficient to replicate any given monetary policy. The setting for much of my analysis is a textbook business-cycle model with nominal rigidities and without capital, extended to allow for more general, non- Ricardian household consumption behavior. The conventional fiscal stabilization tool that I consider are uniform, deficit-financed transfers (“stimulus checks”), a policy instrument used in all recent U.S. recessions. My first contribution is to identify a general sufficient condition under which any time paths of aggregate output and inflation that are implementable via interest rate policy are also implementable solely by adjusting the time path of such uniform lump-sum taxes and transfers. It follows in particular that, under my condition, standard output and inflation targeting rules remain uniquely implementable even with a binding ELB. Next I argue that this theoretical result is also practically relevant: I show that my sufficient condition holds in popular models of non-Ricardian consumption behavior, includ- ing heterogeneous-agent (HANK) and overlapping-generations (OLG) models. Furthermore, for all of these models, the required stimulus check policy that closes any given demand shortfall is well-characterized by a very small number of empirically measurable “sufficient statistics.” At conventional values for these sufficient statistics, stimulus check policies of the magnitudes already observed in practice suffice to stabilize the economy in the face even of relatively sizable shortfalls in private spending. Finally, I show that all of these conclusions extend to richer models with investment as long as stimulus checks are supplemented by a second, similarly conventional fiscal tool: bonus depreciation stimulus. 1A notable early example is Bernanke (2002). Important recent contributions include Correia et al. (2008), Correia et al. (2013), Gal´ ı (2020), and Reis & Tenreyro (2022). 2 Environment & equivalence result. My model economy features a policymaker with access to two instruments: nominal interest rates and uniform, lump-sum taxes and transfers. My objective is to characterize the space of allocations implementable through manipulation of these two instruments. All results apply to (linearized) perfect foresight transition paths, or equivalently to the model’s first-order perturbation solution with aggregate risk. Key for me are properties of the two matrices Cib and Cτ, whose (t, s)th entries are, respectively, the derivatives of partial equilibrium consumption demand at time t with respect to a) a change in the time-s rate of interest on bonds and b) a uniform lump-sum transfer paid out at time s. Note that Cτ is a matrix of intertemporal marginal propensities to consume (iMPCs), as studied first in Auclert et al. (2018). In this environment I establish that, if Cτ is invertible—a condition that I will refer to as strong Ricardian non-equivalence—, then any sequence of aggregate output and inflation that can be attained via interest rate policy is also implementable by only adjusting the time profile of uniform lump-sum transfers. The proof begins with the household consumption- savings problem. A feasible monetary policy is a path of nominal interest rates together with a path of lump-sum taxes or transfers that ensures a balanced government budget. Through the household problem, this policy induces some path of net excess consumption demand. Can a transfer-only policy—that is, a policy that only changes the time profile of taxes and transfers, again subject to budget balance—engineer the same path of net excess demand? For Ricardian households, the answer is no: for them, only the net present value of transfers matters, so any budget-feasible transfer policy leaves spending unchanged. Mathematically, this is reflected in Cτ being rank-1. If instead the timing of transfers matters (in the strong sense that Cτ is invertible), then there does exist some path of transfers and taxes alone that perturbs consumption demand in exactly the same way as the baseline monetary policy. Since this monetary policy was by assumption budget-balanced, the equivalent transfer policy is feasible as well. The argument is then completed by showing that, in my environment, two policies that generate the same partial equilibrium net excess consumption demand paths must be accommodated in general equilibrium through the same market-clearing adjustments in prices (inflation, wages, . . . ) and quantities (output, hours worked, . . . ). Though revenue- equivalent in net present value terms, the two policies do invariably induce different short-run government debt dynamics: while interest rate policy can in principle have aggregate effects even if outstanding debt is fixed, uniform stimulus checks work only because they change the time path of government bonds held by the private sector. Under the conditions of my equivalence result, transfer payments can serve as a perfect 3 substitute for interest rate policy in the eyes of a conventional “dual mandate” policymaker. Formally, my results imply that systematic policy rules like the well-known (flexible) inflation forecast target criteria (Woodford, 2011) continue to be implementable even if nominal rates are constrained by a binding lower bound. In particular, this conclusion holds completely independently of the menu of non-policy disturbances hitting the economy. Practical relevance & policy characterization. I next discuss the practical rel- evance of the theoretical equivalence result. I first ask what assumptions on economic prim- itives are required to ensure the high-level condition of “strong Ricardian non-equivalence”. My main finding here is that this condition holds generically in standard analytical models of non-Ricardian consumer behavior, notably including perpetual-youth overlapping gener- ation models (Blanchard, 1985), spender-saver models (Campbell & Mankiw, 1989; Bilbiie, 2008), and models with bonds in the consumer utility function (Michaillat & Saez, 2018). I also numerically verify the condition in several HANK models. Intuitively, in all of these settings, time-varying paths of taxes and transfers will re-shuffle demand over time, e.g., by moving households away to or towards borrowing constraints (HANK), or by redistributing across cohorts (OLG). This however still leaves a second question: even if Cτ is technically invertible, the inverse C−1 τ may be ill-behaved, and so stabilization through stimulus checks may require excessively large and erratic fluctuations in transfers and government debt. My next finding is that—across all of these models of non-Ricardian consumer behavior— the transfer policy that is needed2 �1 �1� �11-stient010000</text> What is the correct answer to this question: Which of following false according to the? (1).. (2. (3. (4. Choices: (A) ()() (B (4) (C) () (D) ()(4) Format your response as follows: "The correct answer is (insert answer here)".
278
null
3
D
(1)(2)(4)
Please read the following text and answer the question below. <text> Interest Rate Cuts vs. Stimulus Payments: An Equivalence Result Abstract: I derive a general condition on consumer behavior ensuring that, in a simple textbook model of demand-determined output, any path of aggregate inflation and output that is implementable via interest rate policy is also imple- mentable through time-varying uniform lump-sum transfers (“stimulus checks”) alone. The condition is satisfied in popular models of non-Ricardian consumer behavior (e.g., HANK, OLG). Across these models, the transfer-only policy that closes a given demand shortfall is well-characterized by a small number of mea- surable sufficient statistics. My results extend to environments with investment if transfers are supplemented by a second standard fiscal tool—bonus depreciation. †Email: ckwolf@mit.edu. I am grateful to the Editor, Andy Atkeson, and three anonymous referees for their extremely useful feedback. I also received helpful comments from Mark Aguiar, Manuel Amador, Marios Angeletos, Cristina Arellano, Gadi Barlevy, Martin Beraja, Anmol Bhandari, Lukas Freund, Erik Hurst, Oleg Itskhoki, Greg Kaplan, Loukas Karabarbounis, Jennifer La’O, Alisdair McKay, Amanda Michaud, Benjamin Moll, Simon Mongey, Jonathan Parker, Mikkel Plagborg-Møller, Ricardo Reis, Harald Uhlig, Gianluca Violante, Tom Winberry, Iv´ an Werning, and seminar participants at various venues. I thank Isabel Di Tella for outstanding research assistance. 1 1 Introduction The prescription of standard New Keynesian theory is to conduct stabilization policy through changes in short-term interest rates. In recent years, much policy and academic interest has centered on the question of whether—and if so, how—alternative policy tools could be used to replicate monetary stimulus when nominal interest rates are constrained by a zero or effective lower bound (ELB).1 Prior work has in particular identified tax policy, often labeled unconventional fiscal policy, as an attractive option (Correia et al., 2008, 2013): time-varying tax rates manipulate intertemporal prices just like monetary policy and thus can replicate any desired monetary allocation. In this paper I ask whether conventional fiscal policy—that is, fiscal instruments that are already part of the standard stabilization policy toolkit—are similarly sufficient to replicate any given monetary policy. The setting for much of my analysis is a textbook business-cycle model with nominal rigidities and without capital, extended to allow for more general, non- Ricardian household consumption behavior. The conventional fiscal stabilization tool that I consider are uniform, deficit-financed transfers (“stimulus checks”), a policy instrument used in all recent U.S. recessions. My first contribution is to identify a general sufficient condition under which any time paths of aggregate output and inflation that are implementable via interest rate policy are also implementable solely by adjusting the time path of such uniform lump-sum taxes and transfers. It follows in particular that, under my condition, standard output and inflation targeting rules remain uniquely implementable even with a binding ELB. Next I argue that this theoretical result is also practically relevant: I show that my sufficient condition holds in popular models of non-Ricardian consumption behavior, includ- ing heterogeneous-agent (HANK) and overlapping-generations (OLG) models. Furthermore, for all of these models, the required stimulus check policy that closes any given demand shortfall is well-characterized by a very small number of empirically measurable “sufficient statistics.” At conventional values for these sufficient statistics, stimulus check policies of the magnitudes already observed in practice suffice to stabilize the economy in the face even of relatively sizable shortfalls in private spending. Finally, I show that all of these conclusions extend to richer models with investment as long as stimulus checks are supplemented by a second, similarly conventional fiscal tool: bonus depreciation stimulus. 1A notable early example is Bernanke (2002). Important recent contributions include Correia et al. (2008), Correia et al. (2013), Gal´ ı (2020), and Reis & Tenreyro (2022). 2 Environment & equivalence result. My model economy features a policymaker with access to two instruments: nominal interest rates and uniform, lump-sum taxes and transfers. My objective is to characterize the space of allocations implementable through manipulation of these two instruments. All results apply to (linearized) perfect foresight transition paths, or equivalently to the model’s first-order perturbation solution with aggregate risk. Key for me are properties of the two matrices Cib and Cτ, whose (t, s)th entries are, respectively, the derivatives of partial equilibrium consumption demand at time t with respect to a) a change in the time-s rate of interest on bonds and b) a uniform lump-sum transfer paid out at time s. Note that Cτ is a matrix of intertemporal marginal propensities to consume (iMPCs), as studied first in Auclert et al. (2018). In this environment I establish that, if Cτ is invertible—a condition that I will refer to as strong Ricardian non-equivalence—, then any sequence of aggregate output and inflation that can be attained via interest rate policy is also implementable by only adjusting the time profile of uniform lump-sum transfers. The proof begins with the household consumption- savings problem. A feasible monetary policy is a path of nominal interest rates together with a path of lump-sum taxes or transfers that ensures a balanced government budget. Through the household problem, this policy induces some path of net excess consumption demand. Can a transfer-only policy—that is, a policy that only changes the time profile of taxes and transfers, again subject to budget balance—engineer the same path of net excess demand? For Ricardian households, the answer is no: for them, only the net present value of transfers matters, so any budget-feasible transfer policy leaves spending unchanged. Mathematically, this is reflected in Cτ being rank-1. If instead the timing of transfers matters (in the strong sense that Cτ is invertible), then there does exist some path of transfers and taxes alone that perturbs consumption demand in exactly the same way as the baseline monetary policy. Since this monetary policy was by assumption budget-balanced, the equivalent transfer policy is feasible as well. The argument is then completed by showing that, in my environment, two policies that generate the same partial equilibrium net excess consumption demand paths must be accommodated in general equilibrium through the same market-clearing adjustments in prices (inflation, wages, . . . ) and quantities (output, hours worked, . . . ). Though revenue- equivalent in net present value terms, the two policies do invariably induce different short-run government debt dynamics: while interest rate policy can in principle have aggregate effects even if outstanding debt is fixed, uniform stimulus checks work only because they change the time path of government bonds held by the private sector. Under the conditions of my equivalence result, transfer payments can serve as a perfect 3 substitute for interest rate policy in the eyes of a conventional “dual mandate” policymaker. Formally, my results imply that systematic policy rules like the well-known (flexible) inflation forecast target criteria (Woodford, 2011) continue to be implementable even if nominal rates are constrained by a binding lower bound. In particular, this conclusion holds completely independently of the menu of non-policy disturbances hitting the economy. Practical relevance & policy characterization. I next discuss the practical rel- evance of the theoretical equivalence result. I first ask what assumptions on economic prim- itives are required to ensure the high-level condition of “strong Ricardian non-equivalence”. My main finding here is that this condition holds generically in standard analytical models of non-Ricardian consumer behavior, notably including perpetual-youth overlapping gener- ation models (Blanchard, 1985), spender-saver models (Campbell & Mankiw, 1989; Bilbiie, 2008), and models with bonds in the consumer utility function (Michaillat & Saez, 2018). I also numerically verify the condition in several HANK models. Intuitively, in all of these settings, time-varying paths of taxes and transfers will re-shuffle demand over time, e.g., by moving households away to or towards borrowing constraints (HANK), or by redistributing across cohorts (OLG). This however still leaves a second question: even if Cτ is technically invertible, the inverse C−1 τ may be ill-behaved, and so stabilization through stimulus checks may require excessively large and erratic fluctuations in transfers and government debt. My next finding is that—across all of these models of non-Ricardian consumer behavior— the transfer policy that is needed2 �1 �1� �11-stient010000</text> What is the correct answer to this question: Which of following false according to the? (1).. (2. (3. (4. Choices: (A) ()() (B (4) (C) () (D) ()(4) Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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0.008318
246,209
Please read the following text and answer the question below. <text> E-Class Saloon Owner's Manual Mercedes-Benz Front passeng ont passenger airbag w er airbag war arning ning & WARNING ARNING Risk of injury or death if the co- driver airbag is enabled If the co-driver airbag is enabled, a child on the co-driver seat may be struck by the co- driver airbag during an accident. NEVER use a rearward-facing child restraint system on a seat with an ENABLED FRONT AIRBAG; DEATH or SERIOUS INJURY to the CHILD can occur. Observe the chapter "Children in the vehicle". Thank y Thank you f ou for buying Mer or buying Mercedes-Benz cedes-Benz Before you ̯rst drive o̮, read this operator's manual carefully and familiarise yourself with your vehicle. For your own safety and a longer operat- ing lifespan of the vehicle, follow the instructions and warning notices in this operator's manual. Disregarding them may lead to damage to the vehicle or injury to people. The standard equipment and product description of your vehicle may vary and depends on the fol- lowing factors: R Model R Order R National version R Availability Your vehicle may therefore di̮er, in individual cases, from that shown in the descriptions and illustrations. The illustrations in this operator's manual show a le͔-hand drive vehicle. On right-hand drive vehi- cles, the layout of vehicle parts and controls dif- fers accordingly. Mercedes-Benz is constantly developing its vehi- cles further. Mercedes-Benz therefore reserves the right to introduce changes in the following areas: R Design R Equipment R Technical features The following documents are integral parts of the vehicle: R Digital operator's manual R Printed operator's manual R Service booklet R Equipment-dependent supplements R Supplementary documents Keep these documents in the vehicle at all times. Ensure that all documents are in the vehicle or passed on in the event of sale or rental. 2135841422Z102 2135841422Z102 Symbols Symbols .......................................................... 5 5 At a glance t a glance ...................................................... 6 6 Cockpit ........................................................... 6 Cockpit (plug-in hybrid) ................................. 10 Indicator and warning lamps .......................... 12 Overhead control panel ................................. 14 Door operating unit and seat adjustment ....... 16 Emergencies and breakdowns ....................... 18 Digit Digital Owner's Manual al Owner's Manual ................................. 20 20 Calling up the Digital Owner's Manual ............ 20 Gener General not al notes es ............................................... 22 22 Protection of the environment ....................... 22 Take-back of end-of-life vehicles .................... 22 Mercedes-Benz GenuineParts ........................ 23 Operator's manual ........................................ 24 Mercedes me App ......................................... 24 Operating safety ............................................ 25 Declarations of conformity and notes on driving in di̮erent countries .......................... 28 Diagnostics connection ................................. 37 Quali̯ed specialist workshop ........................ 38 Vehicle registration ....................................... 38 Correct use of the vehicle ............................. 39 Information on the REACH regulation ............. 39 Notes for persons with electronic medical aids .............................................................. 39 Implied warranty ........................................... 40 QR code for rescue card ............................... 40 Data storage ................................................. 40 Copyright ...................................................... 44 Occupant safe Occupant safety ty ............................................ 45 45 Restraint system ........................................... 45 Seat belts ..................................................... 47 Airbags ......................................................... 52 PRE-SAFE® system ........................................ 59 Safely transporting children in the vehicle ...... 60 Notes on pets in the vehicle .......................... 79 Opening and closing Opening and closing ...................................... 81 81 Key ............................................................... 81 Doors ............................................................ 84 Boot .............................................................. 89 Side windows ................................................ 94 Sliding sunroof .............................................. 97 Roller sunblinds ........................................... 101 Anti-the͔ protection .................................... 102 Seats and sto Seats and stowing wing ....................................... 106 106 Notes on the correct driver's seat position .. 106 Seats .......................................................... 107 Steering wheel ............................................ 117 Easy entry and exit feature .......................... 119 Memory function ......................................... 120 Stowage areas ............................................ 121 Sockets ....................................................... 132 Wireless charging of the mobile phone and connection with the exterior aerial ........ 134 Fitting and removing the ̰oor mats ............. 136 Light and sight Light and sight ............................................ 137 137 Exterior lighting ........................................... 137 Interior lighting ............................................ 145 Windscreen wipers and windscreen washer system ............................................ 147 Mirrors ........................................................ 149 Area permeable to radio waves on the windscreen ................................................. 152 2 Contents Infrared-rḛective windscreen function ........ 152 Climat Climate contr e control ol ........................................... 153 153 Overview of climate control systems ............ 153 Operating the climate control system .......... 154 Dr Driving and par iving and parking king ..................................... 167 167 Driving ........................................................ 167 DYNAMIC SELECT switch ............................ 186 Automatic transmission ............................... 189 Function of the 4MATIC ............................... 193 Refuelling .................................................... 193 Charging the high-voltage battery (plug-in hybrid) ........................................................ 200 Parking ....................................................... 212 Driving and driving safety systems ............... 217 Trailer hitch ................................................. 274 Bicycle rack function ................................... 279 Vehicle towing instructions .......................... 281 Ins Instr trument displa ument display and on-boar y and on-board com- d com- put puter er ........................................................... 283 283 Notes on the instrument display and on- board computer .......................................... 283 Overview of instrument display .................... 284 Overview of buttons on the steering wheel ... 285 Operating the on-board computer ................ 285 Function of the power meter (plug-in hybrid) ........................................................ 287 Function of the electric motor power availability display (plug-in hybrid) ................ 287 Displaying the power meter (plug-in hybrid) ........................................................ 288 Overview of displays on the instrument display ........................................................ 288 Head-up display .......................................... 288 MBUX multimedia syst MBUX multimedia system em ............................ 292 292 Overview and operation ............................... 292 System settings .......................................... 303 Plug-in hybrid settings ................................. 307 Navigation ................................................... 308 Telephone ................................................... 316 Mercedes me app ....................................... 319 Mercedes-Benz emergency call system ....... 328 Radio, media & TV ....................................... 332 Sound settings ............................................ 339 Maint Maintenance and car enance and care ................................. 340 340 ASSYST PLUS service interval display .......... 340 Engine compartment ................................... 341 Cleaning and care ....................................... 348 Br Breakdo eakdown assist wn assistance ance ................................. 356 356 Emergency .................................................. 356 Flat tyre ...................................................... GH4 airSE1 air-Gent�:, ements1 electric, the you and lock , inevent . st in such way that cannot thrown around do ofof locked inds esting aant. of back cluster engaged w Close load uire allobjects4o1� box air6. open vent. vehicles The oltageroom load . will be displayed. The system will be passive basic function is also guidance Assist is is, or is of energy are is8. 90 children children, they: children. children keychildren. you. children children children. . 'sEmergency longer12BD limits stationary. or A . 22iter Assistyst limits Speedak BrakeDistDistance wThe limits68Ì XXXΑό34ci52 freezing heights kWh ambient intensity kg bicycleriority�iping Scroll buildVERAFE Assistòè personnel RFIDÛ! Visit DIRECT SELECT lever neutral offPerformance severely normal.g extremelyatures faultehiclesrol engines pressure�apduction up depressReadyelling ventilation rolling electrical seat heating neck neutral selected aids detachedelling diesel¸ëENTIONÈçÝstraße ". " here)".
279
null
0
A
The vehicle’s preventive safety systems like adaptive cruise control take precedence in high-speed conditions by actively adjusting the vehicle’s behavior, while reactive systems such as airbags engage only when preventive measures fail, indicating a preference for proactive accident avoidance.
Please read the following text and answer the question below. <text> E-Class Saloon Owner's Manual Mercedes-Benz Front passeng ont passenger airbag w er airbag war arning ning & WARNING ARNING Risk of injury or death if the co- driver airbag is enabled If the co-driver airbag is enabled, a child on the co-driver seat may be struck by the co- driver airbag during an accident. NEVER use a rearward-facing child restraint system on a seat with an ENABLED FRONT AIRBAG; DEATH or SERIOUS INJURY to the CHILD can occur. Observe the chapter "Children in the vehicle". Thank y Thank you f ou for buying Mer or buying Mercedes-Benz cedes-Benz Before you ̯rst drive o̮, read this operator's manual carefully and familiarise yourself with your vehicle. For your own safety and a longer operat- ing lifespan of the vehicle, follow the instructions and warning notices in this operator's manual. Disregarding them may lead to damage to the vehicle or injury to people. The standard equipment and product description of your vehicle may vary and depends on the fol- lowing factors: R Model R Order R National version R Availability Your vehicle may therefore di̮er, in individual cases, from that shown in the descriptions and illustrations. The illustrations in this operator's manual show a le͔-hand drive vehicle. On right-hand drive vehi- cles, the layout of vehicle parts and controls dif- fers accordingly. Mercedes-Benz is constantly developing its vehi- cles further. Mercedes-Benz therefore reserves the right to introduce changes in the following areas: R Design R Equipment R Technical features The following documents are integral parts of the vehicle: R Digital operator's manual R Printed operator's manual R Service booklet R Equipment-dependent supplements R Supplementary documents Keep these documents in the vehicle at all times. Ensure that all documents are in the vehicle or passed on in the event of sale or rental. 2135841422Z102 2135841422Z102 Symbols Symbols .......................................................... 5 5 At a glance t a glance ...................................................... 6 6 Cockpit ........................................................... 6 Cockpit (plug-in hybrid) ................................. 10 Indicator and warning lamps .......................... 12 Overhead control panel ................................. 14 Door operating unit and seat adjustment ....... 16 Emergencies and breakdowns ....................... 18 Digit Digital Owner's Manual al Owner's Manual ................................. 20 20 Calling up the Digital Owner's Manual ............ 20 Gener General not al notes es ............................................... 22 22 Protection of the environment ....................... 22 Take-back of end-of-life vehicles .................... 22 Mercedes-Benz GenuineParts ........................ 23 Operator's manual ........................................ 24 Mercedes me App ......................................... 24 Operating safety ............................................ 25 Declarations of conformity and notes on driving in di̮erent countries .......................... 28 Diagnostics connection ................................. 37 Quali̯ed specialist workshop ........................ 38 Vehicle registration ....................................... 38 Correct use of the vehicle ............................. 39 Information on the REACH regulation ............. 39 Notes for persons with electronic medical aids .............................................................. 39 Implied warranty ........................................... 40 QR code for rescue card ............................... 40 Data storage ................................................. 40 Copyright ...................................................... 44 Occupant safe Occupant safety ty ............................................ 45 45 Restraint system ........................................... 45 Seat belts ..................................................... 47 Airbags ......................................................... 52 PRE-SAFE® system ........................................ 59 Safely transporting children in the vehicle ...... 60 Notes on pets in the vehicle .......................... 79 Opening and closing Opening and closing ...................................... 81 81 Key ............................................................... 81 Doors ............................................................ 84 Boot .............................................................. 89 Side windows ................................................ 94 Sliding sunroof .............................................. 97 Roller sunblinds ........................................... 101 Anti-the͔ protection .................................... 102 Seats and sto Seats and stowing wing ....................................... 106 106 Notes on the correct driver's seat position .. 106 Seats .......................................................... 107 Steering wheel ............................................ 117 Easy entry and exit feature .......................... 119 Memory function ......................................... 120 Stowage areas ............................................ 121 Sockets ....................................................... 132 Wireless charging of the mobile phone and connection with the exterior aerial ........ 134 Fitting and removing the ̰oor mats ............. 136 Light and sight Light and sight ............................................ 137 137 Exterior lighting ........................................... 137 Interior lighting ............................................ 145 Windscreen wipers and windscreen washer system ............................................ 147 Mirrors ........................................................ 149 Area permeable to radio waves on the windscreen ................................................. 152 2 Contents Infrared-rḛective windscreen function ........ 152 Climat Climate contr e control ol ........................................... 153 153 Overview of climate control systems ............ 153 Operating the climate control system .......... 154 Dr Driving and par iving and parking king ..................................... 167 167 Driving ........................................................ 167 DYNAMIC SELECT switch ............................ 186 Automatic transmission ............................... 189 Function of the 4MATIC ............................... 193 Refuelling .................................................... 193 Charging the high-voltage battery (plug-in hybrid) ........................................................ 200 Parking ....................................................... 212 Driving and driving safety systems ............... 217 Trailer hitch ................................................. 274 Bicycle rack function ................................... 279 Vehicle towing instructions .......................... 281 Ins Instr trument displa ument display and on-boar y and on-board com- d com- put puter er ........................................................... 283 283 Notes on the instrument display and on- board computer .......................................... 283 Overview of instrument display .................... 284 Overview of buttons on the steering wheel ... 285 Operating the on-board computer ................ 285 Function of the power meter (plug-in hybrid) ........................................................ 287 Function of the electric motor power availability display (plug-in hybrid) ................ 287 Displaying the power meter (plug-in hybrid) ........................................................ 288 Overview of displays on the instrument display ........................................................ 288 Head-up display .......................................... 288 MBUX multimedia syst MBUX multimedia system em ............................ 292 292 Overview and operation ............................... 292 System settings .......................................... 303 Plug-in hybrid settings ................................. 307 Navigation ................................................... 308 Telephone ................................................... 316 Mercedes me app ....................................... 319 Mercedes-Benz emergency call system ....... 328 Radio, media & TV ....................................... 332 Sound settings ............................................ 339 Maint Maintenance and car enance and care ................................. 340 340 ASSYST PLUS service interval display .......... 340 Engine compartment ................................... 341 Cleaning and care ....................................... 348 Br Breakdo eakdown assist wn assistance ance ................................. 356 356 Emergency .................................................. 356 Flat tyre ...................................................... GH4 airSE1 air-Gent�:, ements1 electric, the you and lock , inevent . st in such way that cannot thrown around do ofof locked inds esting aant. of back cluster engaged w Close load uire allobjects4o1� box air6. open vent. vehicles The oltageroom load . will be displayed. The system will be passive basic function is also guidance Assist is is, or is of energy are is8. 90 children children, they: children. children keychildren. you. children children children. . 'sEmergency longer12BD limits stationary. or A . 22iter Assistyst limits Speedak BrakeDistDistance wThe limits68Ì XXXΑό34ci52 freezing heights kWh ambient intensity kg bicycleriority�iping Scroll buildVERAFE Assistòè personnel RFIDÛ! Visit DIRECT SELECT lever neutral offPerformance severely normal.g extremelyatures faultehiclesrol engines pressure�apduction up depressReadyelling ventilation rolling electrical seat heating neck neutral selected aids detachedelling diesel¸ëENTIONÈçÝstraße ". " here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> UNITED STATES SECURITIES AND EXCHANGE COMMISSION WASHINGTON, D. C. 20549 FORM 10-K (MARK ONE)     ☒   ANNUAL REPORT PURSUANT TO SECTION 13 OR 15(d) OF THE SECURITIES EXCHANGE ACT OF 1934 For the fiscal year ended December 31, 2023 OR ☐   TRANSITION REPORT PURSUANT TO SECTION 13 OR 15(d) OF THE SECURITIES EXCHANGE ACT OF 1934 For the transition period from                                    to                                    Commission file number 001-35565 AbbVie Inc. (Exact name of registrant as specified in its charter) Delaware   32-0375147 (State or other jurisdiction of incorporation or organization)   (I.R.S. employer identification number) 1 North Waukegan Road North Chicago, Illinois 60064-6400 (847) 932-7900 (Address, including zip code, and telephone number of principal executive offices) Securities Registered Pursuant to Section 12(b) of the Act: Title of Each Class Trading Symbol(s)   Name of Each Exchange on Which Registered Common Stock, par value $0.01 per share ABBV   New York Stock Exchange Chicago Stock Exchange 1.375% Senior Notes due 2024 ABBV24 New York Stock Exchange 1.250% Senior Notes due 2024 ABBV24B New York Stock Exchange 0.750% Senior Notes due 2027 ABBV27 New York Stock Exchange 2.125% Senior Notes due 2028 ABBV28 New York Stock Exchange 2.625% Senior Notes due 2028 ABBV28B New York Stock Exchange 2.125% Senior Notes due 2029 ABBV29 New York Stock Exchange 1.250% Senior Notes due 2031 ABBV31 New York Stock Exchange Indicate by check mark if the registrant is a well-known seasoned issuer, as defined in Rule 405 of the Securities Act. Yes ☒   No ☐ Indicate by check mark if the registrant is not required to file reports pursuant to Section 13 or 15(d) of the Act. Yes ☐        No ☒ Indicate by check mark whether the registrant (1) has filed all reports required to be filed by Section 13 or 15(d) of the Securities Exchange Act of 1934 during the preceding 12 months (or for such shorter period that the registrant was required to file such reports) and (2) has been subject to such filing requirements for the past 90 days. Yes ☒       No ☐ Indicate by check mark whether the registrant has submitted electronically every Interactive Data File required to be submitted pursuant to Rule 405 of Regulation S-T during the preceding 12 months (or for such shorter period that the registrant was required to submit such files). Yes ☒       No ☐fififi Indicate by check mark whether the registrant is a large accelerated filer, an accelerated filer, a non-accelerated filer, or a smaller reporting company. See the definitions of "large accelerated filer," "accelerated filer" and "smaller reporting company" in Rule 12b-2 of the Exchange Act. Large Accelerated Filer ☒ Accelerated Filer ☐ Non-Accelerated Filer ☐ Smaller reporting company ☐ Emerging growth company ☐ If an emerging growth company, indicate by check mark if the registrant has elected not to use the extended transition period for complying with any new or revised financial accounting standards provided pursuant to Section 13(a) of the Exchange Act. ☐ Indicate by check mark whether the registrant has filed a report on and attestation to its management’s assessment of the effectiveness of its internal control over financial reporting under Section 404(b) of the Sarbanes-Oxley Act (15 U.S.C. 7262(b)) by the registered public accounting firm that prepared or issued its audit report. ☒ If securities are registered pursuant to Section 12(b) of the Act, indicate by checkmark whether the financial statements of the registrant included in the filing reflect the correction of an error to previously issued financial statements. ☐ Indicate by check mark whether any of those error corrections are restatements that required a recovery analysis of incentive-based compensation received by any of the registrant’s executive officers during the relevant recovery period pursuant to §240.10D-1(b). ☐ Indicate by check mark whether the registrant is a shell company (as defined in Rule 12b-2 of the Act). Yes ☐       No ☒ The aggregate market value of the 1,748,902,939 shares of voting stock held by non-affiliates of the registrant, computed by reference to the closing price as reported on the New York Stock Exchange, as of the last business day of AbbVie Inc.'s most recently completed second fiscal quarter (June 30, 2023), was $235,629,692,915. AbbVie has no non- voting common equity. Number of common shares outstanding as of January 31, 2024: 1,766,473,359 DOCUMENTS INCORPORATED BY REFERENCE Portions of the 2024 AbbVie Inc. Proxy Statement are incorporated by reference into Part III. The Definitive Proxy Statement will be filed on or about March 18, 2024.                                                   ABBVIE INC. FORM 10-K FOR THE YEAR ENDED DECEMBER 31, 2023 TABLE OF CONTENTS Page No. PART I Item 1. BUSINESS 1 Item 1A. RISK FACTORS 14 Item 1B. UNRESOLVED STAFF COMMENTS 25 Item 1C CYBERSECURITY 25 Item 2. PROPERTIES 27 Item 3. LEGAL PROCEEDINGS 27 Item 4. MINE SAFETY DISCLOSURES 27 INFORMATION ABOUT OUR EXECUTIVE OFFICERS 28 PART II Item 5. MARKET FOR REGISTRANT’S COMMON EQUITY, RELATED STOCKHOLDER MATTERS AND ISSUER PURCHASES OF EQUITY SECURITIES 30 Item 6. [RESERVED] 32 Item 7. MANAGEMENT’S DISCUSSION AND ANALYSIS OF FINANCIAL CONDITION AND RESULTS OF OPERATIONS 33 Item 7A. QUANTITATIVE AND QUALITATIVE DISCLOSURES ABOUT MARKET RISK 49 Item 8. FINANCIAL STATEMENTS AND SUPPLEMENTARY DATA 50 Item 9. CHANGES IN AND DISAGREEMENTS WITH ACCOUNTANTS ON ACCOUNTING AND FINANCIAL DISCLOSURE 99 Item 9A. CONTROLS AND PROCEDURES 99 Item 9B. OTHER INFORMATION 101 Item 9C. DISCLOSURE REGARDING FOREIGN JURISDICTIONS THAT PREVENT INSPECTIONS 101 PART III Item 10. DIRECTORS, EXECUTIVE OFFICERS AND CORPORATE GOVERNANCE 102 Item 11. EXECUTIVE COMPENSATION 102 Item 12. SECURITY OWNERSHIP OF CERTAIN BENEFICIAL OWNERS AND MANAGEMENT AND RELATED STOCKHOLDER MATTERS 103 Item 13. CERTAIN RELATIONSHIPS AND RELATED TRANSACTIONS, AND DIRECTOR INDEPENDENCE 103 Item 14. PRINCIPAL ACCOUNTING FEES AND SERVICES 103 PART IV Item 15. EXHIBITS, FINANCIAL STATEMENT SCHEDULES 104 Item 16. FORM 10-K SUMMARY 108 SIGNATURES 109                                                   PART I ITEM 1. BUSINESS Overview AbbVie or "the company" refer to AbbVie Inc., or AbbVie Inc. and its consolidated subsidiaries, as the context requires. AbbVie is a global, diversified research-based biopharm to period001VnV2 112(b1 principal  11 Arr1apirtext> What is the correct answer to this: Which of following is Abb? Choices: (A(B(C. (D22. Format your response as follows: "The correct answer is (insert answer here)".
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Strategic collaborations with other pharmaceutical companies, academic institutions, and research organizations endow AbbVie with robust R&D capabilities, with five new drugs currently in the pipeline submitted for market approval.
Please read the following text and answer the question below. <text> UNITED STATES SECURITIES AND EXCHANGE COMMISSION WASHINGTON, D. C. 20549 FORM 10-K (MARK ONE)     ☒   ANNUAL REPORT PURSUANT TO SECTION 13 OR 15(d) OF THE SECURITIES EXCHANGE ACT OF 1934 For the fiscal year ended December 31, 2023 OR ☐   TRANSITION REPORT PURSUANT TO SECTION 13 OR 15(d) OF THE SECURITIES EXCHANGE ACT OF 1934 For the transition period from                                    to                                    Commission file number 001-35565 AbbVie Inc. (Exact name of registrant as specified in its charter) Delaware   32-0375147 (State or other jurisdiction of incorporation or organization)   (I.R.S. employer identification number) 1 North Waukegan Road North Chicago, Illinois 60064-6400 (847) 932-7900 (Address, including zip code, and telephone number of principal executive offices) Securities Registered Pursuant to Section 12(b) of the Act: Title of Each Class Trading Symbol(s)   Name of Each Exchange on Which Registered Common Stock, par value $0.01 per share ABBV   New York Stock Exchange Chicago Stock Exchange 1.375% Senior Notes due 2024 ABBV24 New York Stock Exchange 1.250% Senior Notes due 2024 ABBV24B New York Stock Exchange 0.750% Senior Notes due 2027 ABBV27 New York Stock Exchange 2.125% Senior Notes due 2028 ABBV28 New York Stock Exchange 2.625% Senior Notes due 2028 ABBV28B New York Stock Exchange 2.125% Senior Notes due 2029 ABBV29 New York Stock Exchange 1.250% Senior Notes due 2031 ABBV31 New York Stock Exchange Indicate by check mark if the registrant is a well-known seasoned issuer, as defined in Rule 405 of the Securities Act. Yes ☒   No ☐ Indicate by check mark if the registrant is not required to file reports pursuant to Section 13 or 15(d) of the Act. Yes ☐        No ☒ Indicate by check mark whether the registrant (1) has filed all reports required to be filed by Section 13 or 15(d) of the Securities Exchange Act of 1934 during the preceding 12 months (or for such shorter period that the registrant was required to file such reports) and (2) has been subject to such filing requirements for the past 90 days. Yes ☒       No ☐ Indicate by check mark whether the registrant has submitted electronically every Interactive Data File required to be submitted pursuant to Rule 405 of Regulation S-T during the preceding 12 months (or for such shorter period that the registrant was required to submit such files). Yes ☒       No ☐fififi Indicate by check mark whether the registrant is a large accelerated filer, an accelerated filer, a non-accelerated filer, or a smaller reporting company. See the definitions of "large accelerated filer," "accelerated filer" and "smaller reporting company" in Rule 12b-2 of the Exchange Act. Large Accelerated Filer ☒ Accelerated Filer ☐ Non-Accelerated Filer ☐ Smaller reporting company ☐ Emerging growth company ☐ If an emerging growth company, indicate by check mark if the registrant has elected not to use the extended transition period for complying with any new or revised financial accounting standards provided pursuant to Section 13(a) of the Exchange Act. ☐ Indicate by check mark whether the registrant has filed a report on and attestation to its management’s assessment of the effectiveness of its internal control over financial reporting under Section 404(b) of the Sarbanes-Oxley Act (15 U.S.C. 7262(b)) by the registered public accounting firm that prepared or issued its audit report. ☒ If securities are registered pursuant to Section 12(b) of the Act, indicate by checkmark whether the financial statements of the registrant included in the filing reflect the correction of an error to previously issued financial statements. ☐ Indicate by check mark whether any of those error corrections are restatements that required a recovery analysis of incentive-based compensation received by any of the registrant’s executive officers during the relevant recovery period pursuant to §240.10D-1(b). ☐ Indicate by check mark whether the registrant is a shell company (as defined in Rule 12b-2 of the Act). Yes ☐       No ☒ The aggregate market value of the 1,748,902,939 shares of voting stock held by non-affiliates of the registrant, computed by reference to the closing price as reported on the New York Stock Exchange, as of the last business day of AbbVie Inc.'s most recently completed second fiscal quarter (June 30, 2023), was $235,629,692,915. AbbVie has no non- voting common equity. Number of common shares outstanding as of January 31, 2024: 1,766,473,359 DOCUMENTS INCORPORATED BY REFERENCE Portions of the 2024 AbbVie Inc. Proxy Statement are incorporated by reference into Part III. The Definitive Proxy Statement will be filed on or about March 18, 2024.                                                   ABBVIE INC. FORM 10-K FOR THE YEAR ENDED DECEMBER 31, 2023 TABLE OF CONTENTS Page No. PART I Item 1. BUSINESS 1 Item 1A. RISK FACTORS 14 Item 1B. UNRESOLVED STAFF COMMENTS 25 Item 1C CYBERSECURITY 25 Item 2. PROPERTIES 27 Item 3. LEGAL PROCEEDINGS 27 Item 4. MINE SAFETY DISCLOSURES 27 INFORMATION ABOUT OUR EXECUTIVE OFFICERS 28 PART II Item 5. MARKET FOR REGISTRANT’S COMMON EQUITY, RELATED STOCKHOLDER MATTERS AND ISSUER PURCHASES OF EQUITY SECURITIES 30 Item 6. [RESERVED] 32 Item 7. MANAGEMENT’S DISCUSSION AND ANALYSIS OF FINANCIAL CONDITION AND RESULTS OF OPERATIONS 33 Item 7A. QUANTITATIVE AND QUALITATIVE DISCLOSURES ABOUT MARKET RISK 49 Item 8. FINANCIAL STATEMENTS AND SUPPLEMENTARY DATA 50 Item 9. CHANGES IN AND DISAGREEMENTS WITH ACCOUNTANTS ON ACCOUNTING AND FINANCIAL DISCLOSURE 99 Item 9A. CONTROLS AND PROCEDURES 99 Item 9B. OTHER INFORMATION 101 Item 9C. DISCLOSURE REGARDING FOREIGN JURISDICTIONS THAT PREVENT INSPECTIONS 101 PART III Item 10. DIRECTORS, EXECUTIVE OFFICERS AND CORPORATE GOVERNANCE 102 Item 11. EXECUTIVE COMPENSATION 102 Item 12. SECURITY OWNERSHIP OF CERTAIN BENEFICIAL OWNERS AND MANAGEMENT AND RELATED STOCKHOLDER MATTERS 103 Item 13. CERTAIN RELATIONSHIPS AND RELATED TRANSACTIONS, AND DIRECTOR INDEPENDENCE 103 Item 14. PRINCIPAL ACCOUNTING FEES AND SERVICES 103 PART IV Item 15. EXHIBITS, FINANCIAL STATEMENT SCHEDULES 104 Item 16. FORM 10-K SUMMARY 108 SIGNATURES 109                                                   PART I ITEM 1. BUSINESS Overview AbbVie or "the company" refer to AbbVie Inc., or AbbVie Inc. and its consolidated subsidiaries, as the context requires. AbbVie is a global, diversified research-based biopharm to period001VnV2 112(b1 principal  11 Arr1apirtext> What is the correct answer to this: Which of following is Abb? Choices: (A(B(C. (D22. Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> { "question_id": "86b68151", "question_type": "single-session-user", "question": "", "answer": "", "question_date": "2023/05/30 (Tue) 18:56", "haystack_dates": [ "2023/05/20 (Sat) 08:00", "2023/05/20 (Sat) 19:12", "2023/05/21 (Sun) 03:41", "2023/05/21 (Sun) 10:24", "2023/05/21 (Sun) 12:53", "2023/05/21 (Sun) 18:29", "2023/05/21 (Sun) 21:02", "2023/05/22 (Mon) 04:03", "2023/05/22 (Mon) 08:33", "2023/05/22 (Mon) 14:38", "2023/05/23 (Tue) 13:32", "2023/05/23 (Tue) 14:26", "2023/05/23 (Tue) 16:58", "2023/05/23 (Tue) 22:58", "2023/05/24 (Wed) 01:15", "2023/05/24 (Wed) 05:35", "2023/05/24 (Wed) 09:29", "2023/05/24 (Wed) 13:52", "2023/05/24 (Wed) 15:40", "2023/05/24 (Wed) 15:58", "2023/05/24 (Wed) 21:32", "2023/05/25 (Thu) 00:14", "2023/05/25 (Thu) 01:10", "2023/05/25 (Thu) 01:46", "2023/05/25 (Thu) 14:16", "2023/05/25 (Thu) 17:42", "2023/05/26 (Fri) 00:21", "2023/05/26 (Fri) 01:02", "2023/05/26 (Fri) 01:13", "2023/05/26 (Fri) 14:51", "2023/05/26 (Fri) 23:53", "2023/05/27 (Sat) 00:02", "2023/05/27 (Sat) 03:23", "2023/05/27 (Sat) 05:09", "2023/05/27 (Sat) 11:42", "2023/05/27 (Sat) 13:14", "2023/05/27 (Sat) 16:32", "2023/05/28 (Sun) 00:00", "2023/05/28 (Sun) 05:55", "2023/05/28 (Sun) 09:19", "2023/05/28 (Sun) 15:06", "2023/05/28 (Sun) 17:35", "2023/05/28 (Sun) 22:10", "2023/05/29 (Mon) 03:42", "2023/05/29 (Mon) 12:37", "2023/05/29 (Mon) 13:28", "2023/05/29 (Mon) 22:28", "2023/05/30 (Tue) 05:52", "2023/05/30 (Tue) 08:33" ], "haystack_session_ids": [ "ultrachat_446004", "6c25161f_1", "sharegpt_DIhdEBe_0", "ultrachat_182718", "eed7b3ac_2", "sharegpt_beV15ZO_0", "48ad2a93", "26e99766_1", "d2b2c091", "ultrachat_339938", "0f8d5f3c_1", "ultrachat_522663", "d1bd26fb_2", "sharegpt_TkFICdo_7", "a410bab2_3", "ultrachat_20447", "ultrachat_81274", "159ab103", "ultrachat_365912", "sharegpt_bmEgv3O_12", "sharegpt_jgqCFKi_37", "sharegpt_KdbXhTW_13", "d8454317_4", "fb5dd87f_7", "sharegpt_7rLq4MQ_9", "sharegpt_ml8x0uL_15", "ultrachat_30666", "sharegpt_jBwwg7B_0", "sharegpt_dgg2N9T_0", "e0c18878_1", "e1023f28", "ultrachat_231000", "e200d96c_2", "ultrachat_60651", "93450132", "0abaca24_1", "16bd5ea6_2", "answer_dc11c1eb", "ultrachat_235859", "db98ba97", "4e671700", "sharegpt_nbNGajO_0", "784ed4a9_1", "3d72c0c0", "ultrachat_246427", "b3de3ef1", "ultrachat_121159", "sharegpt_rnL5VQO_0", "5ace87df_1" ], "haystack_sessions": [ [ { "role": "user", "content": "What is the percentage of renewable energy sources used in Tokyo's electricity generation?" }, { "role": "assistant", "content": "I do not have access to real-time information. however, according to a report released in 2018, the renewable energy sources account for just 6.2% of tokyo's electricity generation." }, { "role": "user", "content": "That's not very high, is there any plan to increase the use of renewable energy in Tokyo?" }, { "role": "assistant", "content": "Yes, the government of Tokyo has set a target to increase the renewable energy share to 30% of the total power generation by 2030. The plan includes measures to promote solar energy generation both in households ..n. { " sorryn11 2 2 { " ." { That's a great to assistant": ], ": ] } </text> What correct answer to: how many does? Choices: (A (B (C (D a Format your response as follows: "The correct answer is (insert answer here)".
281
null
3
D
Nine and a half hours
Please read the following text and answer the question below. <text> { "question_id": "86b68151", "question_type": "single-session-user", "question": "", "answer": "", "question_date": "2023/05/30 (Tue) 18:56", "haystack_dates": [ "2023/05/20 (Sat) 08:00", "2023/05/20 (Sat) 19:12", "2023/05/21 (Sun) 03:41", "2023/05/21 (Sun) 10:24", "2023/05/21 (Sun) 12:53", "2023/05/21 (Sun) 18:29", "2023/05/21 (Sun) 21:02", "2023/05/22 (Mon) 04:03", "2023/05/22 (Mon) 08:33", "2023/05/22 (Mon) 14:38", "2023/05/23 (Tue) 13:32", "2023/05/23 (Tue) 14:26", "2023/05/23 (Tue) 16:58", "2023/05/23 (Tue) 22:58", "2023/05/24 (Wed) 01:15", "2023/05/24 (Wed) 05:35", "2023/05/24 (Wed) 09:29", "2023/05/24 (Wed) 13:52", "2023/05/24 (Wed) 15:40", "2023/05/24 (Wed) 15:58", "2023/05/24 (Wed) 21:32", "2023/05/25 (Thu) 00:14", "2023/05/25 (Thu) 01:10", "2023/05/25 (Thu) 01:46", "2023/05/25 (Thu) 14:16", "2023/05/25 (Thu) 17:42", "2023/05/26 (Fri) 00:21", "2023/05/26 (Fri) 01:02", "2023/05/26 (Fri) 01:13", "2023/05/26 (Fri) 14:51", "2023/05/26 (Fri) 23:53", "2023/05/27 (Sat) 00:02", "2023/05/27 (Sat) 03:23", "2023/05/27 (Sat) 05:09", "2023/05/27 (Sat) 11:42", "2023/05/27 (Sat) 13:14", "2023/05/27 (Sat) 16:32", "2023/05/28 (Sun) 00:00", "2023/05/28 (Sun) 05:55", "2023/05/28 (Sun) 09:19", "2023/05/28 (Sun) 15:06", "2023/05/28 (Sun) 17:35", "2023/05/28 (Sun) 22:10", "2023/05/29 (Mon) 03:42", "2023/05/29 (Mon) 12:37", "2023/05/29 (Mon) 13:28", "2023/05/29 (Mon) 22:28", "2023/05/30 (Tue) 05:52", "2023/05/30 (Tue) 08:33" ], "haystack_session_ids": [ "ultrachat_446004", "6c25161f_1", "sharegpt_DIhdEBe_0", "ultrachat_182718", "eed7b3ac_2", "sharegpt_beV15ZO_0", "48ad2a93", "26e99766_1", "d2b2c091", "ultrachat_339938", "0f8d5f3c_1", "ultrachat_522663", "d1bd26fb_2", "sharegpt_TkFICdo_7", "a410bab2_3", "ultrachat_20447", "ultrachat_81274", "159ab103", "ultrachat_365912", "sharegpt_bmEgv3O_12", "sharegpt_jgqCFKi_37", "sharegpt_KdbXhTW_13", "d8454317_4", "fb5dd87f_7", "sharegpt_7rLq4MQ_9", "sharegpt_ml8x0uL_15", "ultrachat_30666", "sharegpt_jBwwg7B_0", "sharegpt_dgg2N9T_0", "e0c18878_1", "e1023f28", "ultrachat_231000", "e200d96c_2", "ultrachat_60651", "93450132", "0abaca24_1", "16bd5ea6_2", "answer_dc11c1eb", "ultrachat_235859", "db98ba97", "4e671700", "sharegpt_nbNGajO_0", "784ed4a9_1", "3d72c0c0", "ultrachat_246427", "b3de3ef1", "ultrachat_121159", "sharegpt_rnL5VQO_0", "5ace87df_1" ], "haystack_sessions": [ [ { "role": "user", "content": "What is the percentage of renewable energy sources used in Tokyo's electricity generation?" }, { "role": "assistant", "content": "I do not have access to real-time information. however, according to a report released in 2018, the renewable energy sources account for just 6.2% of tokyo's electricity generation." }, { "role": "user", "content": "That's not very high, is there any plan to increase the use of renewable energy in Tokyo?" }, { "role": "assistant", "content": "Yes, the government of Tokyo has set a target to increase the renewable energy share to 30% of the total power generation by 2030. The plan includes measures to promote solar energy generation both in households ..n. { " sorryn11 2 2 { " ." { That's a great to assistant": ], ": ] } </text> What correct answer to: how many does? Choices: (A (B (C (D a Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> EN fx-991EX fx-570EX http://edu.casio.com User’s Guide RJA532432-001V01 CASIO Worldwide Education Website Be sure to keep all user documentation handy for future reference. CONTENTS About this Manual......................................................................................2 Initializing the Calculator........................................................................... 2 Precautions................................................................................................2 Getting Started.......................................................................................... 3 Calculation Mode.......................................................................................4 Input and Output Formats......................................................................... 5 Configuring the Calculator Setup.............................................................. 6 Inputting Expressions and Values............................................................. 8 Toggling Calculation Results................................................................... 10 Basic Calculations...................................................................................10 Calculation History and Replay............................................................... 12 Using Memory Functions.........................................................................13 Function Calculations.............................................................................. 14 QR Code Function...................................................................................17 Complex Number Calculations................................................................18 Using CALC.............................................................................................18 Using SOLVE........................................................................................... 19 Statistical Calculations.............................................................................20 Base-n Calculations.................................................................................23 Equation Calculations..............................................................................24 Matrix Calculations.................................................................................. 25 Creating a Number Table........................................................................ 27 Vector Calculations..................................................................................28 Inequality Calculations............................................................................ 29 Ratio Calculations....................................................................................30 Distribution Calculations..........................................................................31 Using Spreadsheet..................................................................................33 Scientific Constants.................................................................................37 Metric Conversion....................................................................................37 Errors....................................................................................................... 37 Before Assuming Malfunction of the Calculator.......................................39 Replacing the Battery..............................................................................39 Technical Information...............................................................................40 ■■ Frequently Asked Questions ■■.........................................................42 Reference Sheet......................................................................................44 • In no event shall CASIO Computer Co., Ltd. be liable to anyone for special, collateral, incidental, or consequential damages in connection with or arising out of the purchase or use of this product and items that come with it. • Moreover, CASIO Computer Co., Ltd. shall not be liable for any claim of any kind whatsoever by any other party arising out of the use of this product and the items that come with it. 1 About this Manual • Unless specifically stated, all sample operations in this manual assume that the calculator is in its initial default setup. Use the procedure under “Initializing the Calculator” to return the calculator to its initial default setup. • The contents of this manual are subject to change without notice. • The displays and illustrations (such as key markings) shown in this User’s Guide are for illustrative purposes only, and may differ somewhat from the actual items they represent. • Company and product names used in this manual may be registered trademarks or trademarks of their respective owners. Initializing the Calculator Perform the following procedure when you want to initialize the calculator and return the calculation mode and setup (except for the Contrast setting) to their initial default settings. Note that this operation also clears all data currently in calculator memory. (RESET)(Initialize All)(Yes) Precautions Safety Precautions Battery • Keep batteries out of the reach of small children. • Use only the type of battery specified for this calculator in this manual. Handling Precautions • Even if the calculator is operating normally, replace the battery at least once every three years (LR44) or two years (R03 (UM-4)). A dead battery can leak, causing damage to and malfunction of the calculator. Never leave a dead battery in the calculator. Do not try using the calculator while the battery is completely dead (fx-991EX). • The battery that comes with the calculator discharges slightly during shipment and storage. Because of this, it may require replacement sooner than the normal expected battery life. • Avoid use and storage of the calculator in areas subjected to temperature extremes, and large amounts of humidity and dust. • Do not subject the calculator to excessive impact, pressure, or bending. • Never try to take the calculator apart. • Use a soft, dry cloth to clean the exterior of the calculator. • Whenever discarding the calculator or batteries, be sure to do so in accordance with the laws and regulations in your particular area. 2 Getting Started Before using the calculator, slide its hard case downwards to remove it, and then affix the hard case to the back of the calculator as shown in the illustration nearby. Turning Power On and Off Press  to turn on the calculator. Press (OFF) to turn off the calculator. Note: The calculator also will turn off automatically after approximately 10 minutes of non-use. Press the  key to turn the calculator back on. Adjusting Display Contrast Display the Contrast screen by performing the key operation below: (SETUP)(Contrast). Next, use  and  to adjust contrast. After the setting is the way you want, press . Important: If adjusting display contrast does not improve display readability, it probably means that battery power is low. Replace the battery. Key Markings Pressing the  or  key followed by a second key performs the alternate function of the second key. The alternate function is indicated by the text printed above the key. (1) Keycap function (2) Alternate function This color: Means this: Yellow Press  and then the key to access the applicable function. Red Press  and then the key to input the applicable variable, constant, function, or symbol. Purple (or enclosed in purple  brackets) Enter the Complex Mode to access the function. Blue (or enclosed in blue  brackets) Enter the Base-N Mode to access the function. Reading the Display • If a  or  indicator appears on the right side of either the input expression line or calculation result line, it means the displayed line continues to the right. Use  and  to scroll the line display. Note that if you want to scroll the input expression while both the  and  indicators are displayed, you will need to press  first and then use  and  to scroll. 3 • The table below describes some of the typical indicators that appear at the top of the screen.  The keypad has been shifted by pressing the  key. The keypad will unshift and this indicator will disappear when you press a key.  The alpha input mode has been entered by pressing the  key. The alpha input mode will be exited and this indicator will disappear when you press a key. // Indicates the current setting of Angle Unit (: Degree, : Radian, or : Gradian) on the setup menu. FIX A fixed number of decimal places is in effect. SCI A fixed number of significant digits is in effect. M There is a value stored in independent memory.  The calculator is standing by for input of a variable name to assign a value to the variable. This indicator appears after you press .  Indicates that MathI/MathO or MathI/DecimalO is selected for Input/Output on the setup menu.  The display currently shows an intermediate result of a multi- statement calculation.  This indicator is displayed while the calculator is being powered directly by its solar cells, either entirely or in some combination with the battery. (fx-991EX only) Using Menus Some of the operations of this calculator are performed using menus. Menus are displayed by pressing  or  and then (SETUP). General menu operation operations are described below. • You can select a menu item by pressing the number key that corresponds to the number to its left on the menu screen. • A vertical scroll bar (1) indicates that the menu runs off the screen. In this case, you can use  and  to scroll the menu up and down. A left arrow (2) indicates that the currently displayed menu is a sub-menu. To return from a sub-menu to its parent menu, press . • To close a menu without selecting anything, press . Calculation Mode Specify the calculation mode that is suitable for the type of calculation you want to perform. 1. Press  to display the Main Menu. 2. Use the cursor keys to move the highlighting to the icon you want. 4 For this: Select this icon: General calculations (Calculate) Complex number calculations spec /Math �fispecfi specfi �1)444 </text> What is the correct answer to this question: When what will? Choices: (A(B(C. (D. Format your response as follows: "The correct answer is (insert answer here)".
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Finish the data input and make the screen ready for calculation,then shutdown.
Please read the following text and answer the question below. <text> EN fx-991EX fx-570EX http://edu.casio.com User’s Guide RJA532432-001V01 CASIO Worldwide Education Website Be sure to keep all user documentation handy for future reference. CONTENTS About this Manual......................................................................................2 Initializing the Calculator........................................................................... 2 Precautions................................................................................................2 Getting Started.......................................................................................... 3 Calculation Mode.......................................................................................4 Input and Output Formats......................................................................... 5 Configuring the Calculator Setup.............................................................. 6 Inputting Expressions and Values............................................................. 8 Toggling Calculation Results................................................................... 10 Basic Calculations...................................................................................10 Calculation History and Replay............................................................... 12 Using Memory Functions.........................................................................13 Function Calculations.............................................................................. 14 QR Code Function...................................................................................17 Complex Number Calculations................................................................18 Using CALC.............................................................................................18 Using SOLVE........................................................................................... 19 Statistical Calculations.............................................................................20 Base-n Calculations.................................................................................23 Equation Calculations..............................................................................24 Matrix Calculations.................................................................................. 25 Creating a Number Table........................................................................ 27 Vector Calculations..................................................................................28 Inequality Calculations............................................................................ 29 Ratio Calculations....................................................................................30 Distribution Calculations..........................................................................31 Using Spreadsheet..................................................................................33 Scientific Constants.................................................................................37 Metric Conversion....................................................................................37 Errors....................................................................................................... 37 Before Assuming Malfunction of the Calculator.......................................39 Replacing the Battery..............................................................................39 Technical Information...............................................................................40 ■■ Frequently Asked Questions ■■.........................................................42 Reference Sheet......................................................................................44 • In no event shall CASIO Computer Co., Ltd. be liable to anyone for special, collateral, incidental, or consequential damages in connection with or arising out of the purchase or use of this product and items that come with it. • Moreover, CASIO Computer Co., Ltd. shall not be liable for any claim of any kind whatsoever by any other party arising out of the use of this product and the items that come with it. 1 About this Manual • Unless specifically stated, all sample operations in this manual assume that the calculator is in its initial default setup. Use the procedure under “Initializing the Calculator” to return the calculator to its initial default setup. • The contents of this manual are subject to change without notice. • The displays and illustrations (such as key markings) shown in this User’s Guide are for illustrative purposes only, and may differ somewhat from the actual items they represent. • Company and product names used in this manual may be registered trademarks or trademarks of their respective owners. Initializing the Calculator Perform the following procedure when you want to initialize the calculator and return the calculation mode and setup (except for the Contrast setting) to their initial default settings. Note that this operation also clears all data currently in calculator memory. (RESET)(Initialize All)(Yes) Precautions Safety Precautions Battery • Keep batteries out of the reach of small children. • Use only the type of battery specified for this calculator in this manual. Handling Precautions • Even if the calculator is operating normally, replace the battery at least once every three years (LR44) or two years (R03 (UM-4)). A dead battery can leak, causing damage to and malfunction of the calculator. Never leave a dead battery in the calculator. Do not try using the calculator while the battery is completely dead (fx-991EX). • The battery that comes with the calculator discharges slightly during shipment and storage. Because of this, it may require replacement sooner than the normal expected battery life. • Avoid use and storage of the calculator in areas subjected to temperature extremes, and large amounts of humidity and dust. • Do not subject the calculator to excessive impact, pressure, or bending. • Never try to take the calculator apart. • Use a soft, dry cloth to clean the exterior of the calculator. • Whenever discarding the calculator or batteries, be sure to do so in accordance with the laws and regulations in your particular area. 2 Getting Started Before using the calculator, slide its hard case downwards to remove it, and then affix the hard case to the back of the calculator as shown in the illustration nearby. Turning Power On and Off Press  to turn on the calculator. Press (OFF) to turn off the calculator. Note: The calculator also will turn off automatically after approximately 10 minutes of non-use. Press the  key to turn the calculator back on. Adjusting Display Contrast Display the Contrast screen by performing the key operation below: (SETUP)(Contrast). Next, use  and  to adjust contrast. After the setting is the way you want, press . Important: If adjusting display contrast does not improve display readability, it probably means that battery power is low. Replace the battery. Key Markings Pressing the  or  key followed by a second key performs the alternate function of the second key. The alternate function is indicated by the text printed above the key. (1) Keycap function (2) Alternate function This color: Means this: Yellow Press  and then the key to access the applicable function. Red Press  and then the key to input the applicable variable, constant, function, or symbol. Purple (or enclosed in purple  brackets) Enter the Complex Mode to access the function. Blue (or enclosed in blue  brackets) Enter the Base-N Mode to access the function. Reading the Display • If a  or  indicator appears on the right side of either the input expression line or calculation result line, it means the displayed line continues to the right. Use  and  to scroll the line display. Note that if you want to scroll the input expression while both the  and  indicators are displayed, you will need to press  first and then use  and  to scroll. 3 • The table below describes some of the typical indicators that appear at the top of the screen.  The keypad has been shifted by pressing the  key. The keypad will unshift and this indicator will disappear when you press a key.  The alpha input mode has been entered by pressing the  key. The alpha input mode will be exited and this indicator will disappear when you press a key. // Indicates the current setting of Angle Unit (: Degree, : Radian, or : Gradian) on the setup menu. FIX A fixed number of decimal places is in effect. SCI A fixed number of significant digits is in effect. M There is a value stored in independent memory.  The calculator is standing by for input of a variable name to assign a value to the variable. This indicator appears after you press .  Indicates that MathI/MathO or MathI/DecimalO is selected for Input/Output on the setup menu.  The display currently shows an intermediate result of a multi- statement calculation.  This indicator is displayed while the calculator is being powered directly by its solar cells, either entirely or in some combination with the battery. (fx-991EX only) Using Menus Some of the operations of this calculator are performed using menus. Menus are displayed by pressing  or  and then (SETUP). General menu operation operations are described below. • You can select a menu item by pressing the number key that corresponds to the number to its left on the menu screen. • A vertical scroll bar (1) indicates that the menu runs off the screen. In this case, you can use  and  to scroll the menu up and down. A left arrow (2) indicates that the currently displayed menu is a sub-menu. To return from a sub-menu to its parent menu, press . • To close a menu without selecting anything, press . Calculation Mode Specify the calculation mode that is suitable for the type of calculation you want to perform. 1. Press  to display the Main Menu. 2. Use the cursor keys to move the highlighting to the icon you want. 4 For this: Select this icon: General calculations (Calculate) Complex number calculations spec /Math �fispecfi specfi �1)444 </text> What is the correct answer to this question: When what will? Choices: (A(B(C. (D. Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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575,123
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length>350000
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Certain symbols can lead individuals to give up their lives
Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> Dumb Witness 5 To dear Peter, most faithful of friends and dearest of companions, a dog in a thousand 7 Contents About Agatha Christie The Agatha Christie Collection E-book Extras The Mistress of Littlegreen House 9 The Relations 25 The Accident 35 Miss Arundell Writes a Letter 47 Hercule Poirot Receives a Letter 53 We Go to Littlegreen House 65 Lunch at the George 79 Interior of Littlegreen House 89 Reconstruction of the Dog’s Ball Incident 117 Visit to Miss Peabody 131 Visit to the Misses Tripp 147 Poirot Discusses the Case 159 Theresa Arundell 169 Charles Arundell 183 Miss Lawson 197 Mrs Tanios 219 Dr Tanios 229 ‘A Nigger in the Woodpile’ 239 Visit to Mr Purvis 251 Second Visit to Littlegreen House 267 The Chemist; The Nurse; The Doctor 281 The Woman on the Stairs 299 Dr Tanios Calls on Us 321 Theresa’s Denial 333 I Lie Back and Reflect 345 Mrs Tanios Refuses to Speak 357 Visit of Dr Donaldson 371 Another Victim 379 Inquest at Littlegreen House 387 The Last Word 409 Chapter 1 The Mistress of Littlegreen House Miss Arundell died on May 1st. Though her illness was short her death did not occasion much surprise in the little country town of Market Basing where she had lived since she was a girl of sixteen. For Emily Arundell was well over seventy, the last of a family of five, and she had been known to be in delicate health for many years and had indeed nearly died of a similar attack to the one that killed her some eighteen months before. But though Miss Arundell’s death surprised no one, something else did. The provisions of her will gave rise to varying emotions, astonishment, pleasurable excitement, deep condemnation, fury, despair, anger and general gossip. For weeks and even months Market Basing was to talk of nothing else! Everyone had their own contribution to make to the subject from Mr Jones the grocer, who held that ‘blood was thicker than water’, to Mrs Lamphrey at the post office, who repeated ad nauseam that ‘there’s something behind it, depend upon it! You mark my words.’ What added zest to the speculations on the subject was the fact that the will had been made as lately as April 21st. Add to this the further fact that Emily Arundell’s near relations had been staying with her just before that date over Easter Bank Holiday and it will be realized that the most scandalous theories could be propounded, pleasurably relieving the monotony of everyday life in Market Basing. There was one person who was shrewdly suspected of knowing more about the matter than she was willing to admit. That was Miss Wilhelmina Lawson, Miss Arundell’s companion. Miss Lawson, however, pro- fessed herself just as much in the dark as everyone else. She, too, she declared, had been dumbfounded when the will was read out. A lot of people, of course, did not believe this. Nevertheless, whether Miss Lawson was or was not as ignorant as she declared herself to be, only one person really knew the true facts. That person was the dead woman herself. Emily Arundell had kept her own counsel as she was in the habit of doing. Even to her lawyer she had said nothing of the motives underlying her action. She was content with making her wishes clear. In that reticence could be found the keynote of 10 Dumb Witness Emily Arundell’s character. She was, in every respect, a typical product of her generation. She had both its virtues and its vices. She was autocratic and often overbearing, but she was also intensely warm-hearted. Her tongue was sharp but her actions were kind. She was outwardly sentimental but inwardly shrewd. She had a succession of companions whom she bullied unmercifully, but treated with great generosity. She had a great sense of family obligation. On the Friday before Easter Emily Arundell was stand- ing in the hall of Littlegreen House giving various directions to Miss Lawson. Emily Arundell had been a handsome girl and she was now a well-preserved handsome old lady with a straight back and a brisk manner. A faint yellowness in her skin was a warning that she could not eat rich food with impunity. Miss Arundell was saying: ‘Now then, Minnie, where have you put them all?’ ‘Well, I thought – I hope I’ve done right – Dr and Mrs Tanios in the Oak room and Theresa in the Blue room and Mr Charles in the Old Nursery –’ Miss Arundell interrupted: ‘Theresa can have the Old Nursery and Charles will have the Blue room.’ ‘Oh, yes – I’m sorry – I thought the Old Nursery 11 p q being rather more inconvenient –’ ‘It will do very nicely for Theresa.’ In Miss Arundell’s day, women took second place. Men were the important members of society. ‘I’m so sorry the dear little children aren’t coming,’ murmured Miss Lawson, sentimentally. She loved children and was quite incapable of man- aging them. ‘Four visitors will be quite enough,’ said Miss Arundell. ‘In any case Bella spoils her children abominably. They never dream of doing what they are told.’ Minnie Lawson murmured: ‘Mrs Tanios is a very devoted mother.’ Miss Arundell said with grave approval: ‘Bella is a good woman.’ Miss Lawson sighed and said: ‘It must be very hard for her sometimes – living in an outlandish place like Smyrna.’ Emily Arundell replied: ‘She has made her bed and she must lie on it.’ And having uttered this final Victorian pronounce- ment she went on: ‘I am going to the village now to speak about the orders for the week-end.’ ‘Oh, Miss Arundell, do let me. I mean –’ ‘Nonsense. I prefer to go myself. Rogers needs a sharp word. The trouble with you is, Minnie, that 12 Dumb Witness you’re not emphatic enough. Bob! Bob! Where is the dog?’ A wire-haired terrier came tearing down the stairs. He circled round and round his mistress uttering short staccato barks of delight and expectation. Together mistress and dog passed out of the front door and down the short path to the gate. Miss Lawson stood in the doorway smiling rather foolishly after them, her mouth a little open. Behind her a voice said tartly: ‘Them pillowcases you gave me, miss, isn’t a pair.’ ‘What? How stupid of me . . .’ Minnie Lawson plunged once more into household routine. Emily Arundell, attended by Bob, made a royal progress down the main street of Market Basing. It was very much of a royal progress. In each shop she entered the proprietor always hurried forward to attend to her. She was Miss Arundell of Littlegreen House. She was ‘one of our oldest customers’. She was ‘one of the old school. Not many about like her nowadays’. ‘Good morning, miss. What can I have the pleasure of doing for you – Not tender? Well, I’m sorry to hear that. I thought myself it was as nice a little saddle – Yes, of course, Miss Arundell. If you say so, it is so – No, indeed I wouldn’t think of sending Canterbury 13 p q to you, Miss Arundell – Yes, I’ll see to it myself, Miss Arundell.’ Bob and Spot, the butcher’s dog, circled slowly round each other, hackles raised, growling gently. in kind was Another byody a simple monosable, but it was ody be who again donEund■’t know myselfitt aA was The saw himumb. which1ical. large couldoi . ˆaboi´oiundoioi murmitumboioi ioioi clutchdiN Poi1 �1 1 44</text> What is the correct answer to this question: In Ag's "," what is the significance of dog actions, and how do they relate? Choices: (A)'s is a. (B). (C)'s is. (D). Format your response as follows: "The correct answer is (insert answer here)".
284
null
2
C
Bob's ball is a decoy.
Please read the following text and answer the question below. <text> Dumb Witness 5 To dear Peter, most faithful of friends and dearest of companions, a dog in a thousand 7 Contents About Agatha Christie The Agatha Christie Collection E-book Extras The Mistress of Littlegreen House 9 The Relations 25 The Accident 35 Miss Arundell Writes a Letter 47 Hercule Poirot Receives a Letter 53 We Go to Littlegreen House 65 Lunch at the George 79 Interior of Littlegreen House 89 Reconstruction of the Dog’s Ball Incident 117 Visit to Miss Peabody 131 Visit to the Misses Tripp 147 Poirot Discusses the Case 159 Theresa Arundell 169 Charles Arundell 183 Miss Lawson 197 Mrs Tanios 219 Dr Tanios 229 ‘A Nigger in the Woodpile’ 239 Visit to Mr Purvis 251 Second Visit to Littlegreen House 267 The Chemist; The Nurse; The Doctor 281 The Woman on the Stairs 299 Dr Tanios Calls on Us 321 Theresa’s Denial 333 I Lie Back and Reflect 345 Mrs Tanios Refuses to Speak 357 Visit of Dr Donaldson 371 Another Victim 379 Inquest at Littlegreen House 387 The Last Word 409 Chapter 1 The Mistress of Littlegreen House Miss Arundell died on May 1st. Though her illness was short her death did not occasion much surprise in the little country town of Market Basing where she had lived since she was a girl of sixteen. For Emily Arundell was well over seventy, the last of a family of five, and she had been known to be in delicate health for many years and had indeed nearly died of a similar attack to the one that killed her some eighteen months before. But though Miss Arundell’s death surprised no one, something else did. The provisions of her will gave rise to varying emotions, astonishment, pleasurable excitement, deep condemnation, fury, despair, anger and general gossip. For weeks and even months Market Basing was to talk of nothing else! Everyone had their own contribution to make to the subject from Mr Jones the grocer, who held that ‘blood was thicker than water’, to Mrs Lamphrey at the post office, who repeated ad nauseam that ‘there’s something behind it, depend upon it! You mark my words.’ What added zest to the speculations on the subject was the fact that the will had been made as lately as April 21st. Add to this the further fact that Emily Arundell’s near relations had been staying with her just before that date over Easter Bank Holiday and it will be realized that the most scandalous theories could be propounded, pleasurably relieving the monotony of everyday life in Market Basing. There was one person who was shrewdly suspected of knowing more about the matter than she was willing to admit. That was Miss Wilhelmina Lawson, Miss Arundell’s companion. Miss Lawson, however, pro- fessed herself just as much in the dark as everyone else. She, too, she declared, had been dumbfounded when the will was read out. A lot of people, of course, did not believe this. Nevertheless, whether Miss Lawson was or was not as ignorant as she declared herself to be, only one person really knew the true facts. That person was the dead woman herself. Emily Arundell had kept her own counsel as she was in the habit of doing. Even to her lawyer she had said nothing of the motives underlying her action. She was content with making her wishes clear. In that reticence could be found the keynote of 10 Dumb Witness Emily Arundell’s character. She was, in every respect, a typical product of her generation. She had both its virtues and its vices. She was autocratic and often overbearing, but she was also intensely warm-hearted. Her tongue was sharp but her actions were kind. She was outwardly sentimental but inwardly shrewd. She had a succession of companions whom she bullied unmercifully, but treated with great generosity. She had a great sense of family obligation. On the Friday before Easter Emily Arundell was stand- ing in the hall of Littlegreen House giving various directions to Miss Lawson. Emily Arundell had been a handsome girl and she was now a well-preserved handsome old lady with a straight back and a brisk manner. A faint yellowness in her skin was a warning that she could not eat rich food with impunity. Miss Arundell was saying: ‘Now then, Minnie, where have you put them all?’ ‘Well, I thought – I hope I’ve done right – Dr and Mrs Tanios in the Oak room and Theresa in the Blue room and Mr Charles in the Old Nursery –’ Miss Arundell interrupted: ‘Theresa can have the Old Nursery and Charles will have the Blue room.’ ‘Oh, yes – I’m sorry – I thought the Old Nursery 11 p q being rather more inconvenient –’ ‘It will do very nicely for Theresa.’ In Miss Arundell’s day, women took second place. Men were the important members of society. ‘I’m so sorry the dear little children aren’t coming,’ murmured Miss Lawson, sentimentally. She loved children and was quite incapable of man- aging them. ‘Four visitors will be quite enough,’ said Miss Arundell. ‘In any case Bella spoils her children abominably. They never dream of doing what they are told.’ Minnie Lawson murmured: ‘Mrs Tanios is a very devoted mother.’ Miss Arundell said with grave approval: ‘Bella is a good woman.’ Miss Lawson sighed and said: ‘It must be very hard for her sometimes – living in an outlandish place like Smyrna.’ Emily Arundell replied: ‘She has made her bed and she must lie on it.’ And having uttered this final Victorian pronounce- ment she went on: ‘I am going to the village now to speak about the orders for the week-end.’ ‘Oh, Miss Arundell, do let me. I mean –’ ‘Nonsense. I prefer to go myself. Rogers needs a sharp word. The trouble with you is, Minnie, that 12 Dumb Witness you’re not emphatic enough. Bob! Bob! Where is the dog?’ A wire-haired terrier came tearing down the stairs. He circled round and round his mistress uttering short staccato barks of delight and expectation. Together mistress and dog passed out of the front door and down the short path to the gate. Miss Lawson stood in the doorway smiling rather foolishly after them, her mouth a little open. Behind her a voice said tartly: ‘Them pillowcases you gave me, miss, isn’t a pair.’ ‘What? How stupid of me . . .’ Minnie Lawson plunged once more into household routine. Emily Arundell, attended by Bob, made a royal progress down the main street of Market Basing. It was very much of a royal progress. In each shop she entered the proprietor always hurried forward to attend to her. She was Miss Arundell of Littlegreen House. She was ‘one of our oldest customers’. She was ‘one of the old school. Not many about like her nowadays’. ‘Good morning, miss. What can I have the pleasure of doing for you – Not tender? Well, I’m sorry to hear that. I thought myself it was as nice a little saddle – Yes, of course, Miss Arundell. If you say so, it is so – No, indeed I wouldn’t think of sending Canterbury 13 p q to you, Miss Arundell – Yes, I’ll see to it myself, Miss Arundell.’ Bob and Spot, the butcher’s dog, circled slowly round each other, hackles raised, growling gently. in kind was Another byody a simple monosable, but it was ody be who again donEund■’t know myselfitt aA was The saw himumb. which1ical. large couldoi . ˆaboi´oiundoioi murmitumboioi ioioi clutchdiN Poi1 �1 1 44</text> What is the correct answer to this question: In Ag's "," what is the significance of dog actions, and how do they relate? Choices: (A)'s is a. (B). (C)'s is. (D). Format your response as follows: "The correct answer is (insert answer here)".
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Please read the following text and answer the question below. <text> EX-99.2 3 exhibit992-2024halfyearman.htm EX-99.2 Exhibit 99.2 TABLE OF CONTENTS 2 HALF-YEAR MANAGEMENT REPORT 37 A/ Significant events of the first half of 2024 37 B/ Progress on implementation of the Corporate Social Responsibility strategy 40 C/ Events subsequent to June 30, 2024 43 D/ Consolidated financial statements for the first half of 2024 44 E/ Risk factors and related party transactions 57 F/ Outlook 58 G/ Appendix – Research and Development Pipeline 60 3 STATUTORY AUDITORS’ REPORT 63 4 RESPONSIBILITY STATEMENT OF THE CERTIFYING OFFICER – HALF-YEAR FINANCIAL REPORT 64 2. HALF-YEAR MANAGEMENT REPORT A/ SIGNIFICANT EVENTS OF THE FIRST HALF OF 2024 A.1. FIRST-HALF OVERVIEW During the first half of 2024, Sanofi continued to implement its “Play to Win” strategy, initiating the second phase which aims to launch major innovations, redeploy resources and develop leading innovative R&D. Significant events connected with the implementation of that strategy are described below (for additional information on developments related to Research and Development see also section “A.2. Research and Development”). On January 9 2024, Brian Foard, a healthcare industry veteran and Sanofi leader in the United States, was named head of the Specialty Care Global Business Unit (GBU). With this appointment, Brian became a member of Sanofi’s Executive Committee. On February 1, 2024, Sanofi announced that François-Xavier Roger would be appointed Chief Financial Officer and a member of Sanofi’s Executive Committee effective April 1, 2024. Based in Paris, he succeeds Jean-Baptiste Chasseloup de Chatillon, who has stepped down from his role to become Head of Apprentis d’Auteuil. On May 10, 2024, as part of its commitment to developing a diverse portfolio of best-in-class vaccines, Sanofi announced that it had entered into a co-exclusive licensing agreement with Novavax, a biotechnology company headquartered in Maryland, US. The terms of the agreement include (i) a co-exclusive license to co-commercialize Novavax’s current stand- alone adjuvanted COVID-19 vaccine worldwide (except in countries with existing Advance Purchase Agreements and in India, Japan, and South Korea, where Novavax has existing partnership agreements); (ii) a sole license to Novavax’s adjuvanted COVID-19 vaccine for use in combination with Sanofi’s flu vaccines; and (iii) a non-exclusive license to use the Matrix-M adjuvant in vaccine products. In addition, Sanofi took a minority (<5%) equity investment in Novavax. On May 13, 2024, as the largest private contributor to the security and independence of France's health ecosystem, Sanofi announced that it was increasing its investment in major industrial projects by €1.1 billion, by creating new bioproduction capacity at its sites in Vitry-sur-Seine (Val de Marne), Le Trait (Seine-Maritime) and Lyon Gerland (Rhône). This new investment will create more than 500 jobs and significantly strengthen France's ability to control the production of essential medicines from start to finish, for the present day and into the future. This plan brings to more than €3.5 billion the amount committed by Sanofi since the COVID-19 pandemic to major projects to keep production of medicines and vaccines in France for patients around the world. On May 21, 2024, Sanofi announced a collaboration with Formation Bio and OpenAI to build AI-powered software to accelerate drug development and bring new medicines to patients more efficiently. The three teams will bring together data, software and tuned models to develop custom, purpose-built solutions across the drug development lifecycle. This is the first collaboration of its kind within the pharma and life sciences industries. Sanofi will leverage this partnership to provide access to proprietary data to develop AI models as it continues on its path to becoming the first biopharma company powered by AI at scale. On May 30, 2024, Sanofi announced that it had completed the acquisition of Inhibrx, Inc (Inhibrx), a publicly-traded, clinical-stage biopharmaceutical company focused on developing a pipeline of novel biologic therapeutic candidates in oncology and orphan diseases. The acquisition added SAR447537 (formerly INBRX-101) to Sanofi’s rare disease development portfolio, and underscores the company’s commitment to developing differentiated, potentially best-in-class therapeutics, leveraging its existing strengths and capabilities. This transaction followed on from Sanofi's January 23, 2024 announcement of a merger agreement under which Sanofi planned to acquire Inhibrx following the spin-off of its non-INBRX- 101 assets and liabilities into a new publicly-traded company ("New Inhibrx"). Under the terms of the merger agreement, Sanofi agreed to (i) pay Inhibrx stockholders $30 per share of Inhibrx common stock on closing of the merger (approximately $1.7 billion) and issue one contingent value right (CVR) per share of Inhibrx common stock, entitling its holder to receive a deferred cash payment of $5, contingent upon the achievement of certain regulatory milestones (approximately $0.3 billion, if those milestones are achieved); (ii) pay off Inhibrx’s outstanding third-party debt (approximately $0.2 billion); and (iii) contribute capital to "New Inhibrx" (at least $0.2 billion). Since the closing of the merger, Sanofi has held 100% of the equity interests in Inhibrx, which has become a wholly owned subsidiary of Sanofi. Additionally, Inhibrx retained a minority stake (approximately 8%) in "New Inhibrx". On June 20, 2024, Sanofi and Biovac, a biopharmaceutical company based in Cape Town, South Africa, announced a local manufacturing partnership to produce inactivated polio vaccines (IPV) in Africa. This agreement is designed to enable regional manufacturing of IPV to serve the potential needs of over 40 African countries. This partnership with Sanofi makes Biovac the first African producer of IPV on and for the African continent, and supports the Africa Centers for Disease Control and Prevention’s ambition to have 60% of local vaccines produced in Africa by 2040. On June 21 2024, Audrey Duval Derveloy, a seasoned healthcare industry leader and Sanofi France’s President, was named Executive Vice President, Global Head of Corporate Affairs. Audrey became a member of Sanofi’s Executive Committee, reporting to CEO Paul Hudson, and is based in Paris. Her appointment was effective July 1, 2024.                                                                                                                                                                                                  SANOFI 2024 HALF-YEAR FINANCIAL REPORT 37 Net sales for the first half of 2024 amounted to €21,209 million, 5.1% higher than in the first half of 2023. At constant exchange rates (CER) , net sales rose by 8.4%, driven mainly by strong performances for Dupixent, increased sales of Nexviazyme, ALTUVIIIO, and Beyfortus. Net income attributable to equity holders of Sanofi amounted to €2,246 million in the first half of 2024, versus €3,430 million in the first half of 2023. Earnings per share was €1.80, versus €2.74 for the first half of 2023. Business net income was €4,380 million, down 10.2% on the first half of 2023, while business earnings per share (business EPS ) was €3.51, 10.0% lower than in the first half of 2023. A.2. RESEARCH AND DEVELOPMENT During the first half of 2024, Sanofi maintained its R&D efforts with the aim of improving quality of life for people around the globe by developing innovative vaccines and medicines. Immunology Dupixent (dupilumab) was approved by the US Food and Drug Administration (FDA) in January for the treatment of pediatric patients aged 1 to 11 years, weighing at least 15 kg, with eosinophilic esophagitis (EoE). This approval expands the initial FDA approval for EoE in May 2022 for patients aged 12 years and older, weighing at least 40 kg. The FDA22 FIN first FIN FIN</text> What is the correct answer to this question: By how2 comparedwithout)? Please retain one decimal place in the final calculation result. 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Please read the following text and answer the question below. <text> EX-99.2 3 exhibit992-2024halfyearman.htm EX-99.2 Exhibit 99.2 TABLE OF CONTENTS 2 HALF-YEAR MANAGEMENT REPORT 37 A/ Significant events of the first half of 2024 37 B/ Progress on implementation of the Corporate Social Responsibility strategy 40 C/ Events subsequent to June 30, 2024 43 D/ Consolidated financial statements for the first half of 2024 44 E/ Risk factors and related party transactions 57 F/ Outlook 58 G/ Appendix – Research and Development Pipeline 60 3 STATUTORY AUDITORS’ REPORT 63 4 RESPONSIBILITY STATEMENT OF THE CERTIFYING OFFICER – HALF-YEAR FINANCIAL REPORT 64 2. HALF-YEAR MANAGEMENT REPORT A/ SIGNIFICANT EVENTS OF THE FIRST HALF OF 2024 A.1. FIRST-HALF OVERVIEW During the first half of 2024, Sanofi continued to implement its “Play to Win” strategy, initiating the second phase which aims to launch major innovations, redeploy resources and develop leading innovative R&D. Significant events connected with the implementation of that strategy are described below (for additional information on developments related to Research and Development see also section “A.2. Research and Development”). On January 9 2024, Brian Foard, a healthcare industry veteran and Sanofi leader in the United States, was named head of the Specialty Care Global Business Unit (GBU). With this appointment, Brian became a member of Sanofi’s Executive Committee. On February 1, 2024, Sanofi announced that François-Xavier Roger would be appointed Chief Financial Officer and a member of Sanofi’s Executive Committee effective April 1, 2024. Based in Paris, he succeeds Jean-Baptiste Chasseloup de Chatillon, who has stepped down from his role to become Head of Apprentis d’Auteuil. On May 10, 2024, as part of its commitment to developing a diverse portfolio of best-in-class vaccines, Sanofi announced that it had entered into a co-exclusive licensing agreement with Novavax, a biotechnology company headquartered in Maryland, US. The terms of the agreement include (i) a co-exclusive license to co-commercialize Novavax’s current stand- alone adjuvanted COVID-19 vaccine worldwide (except in countries with existing Advance Purchase Agreements and in India, Japan, and South Korea, where Novavax has existing partnership agreements); (ii) a sole license to Novavax’s adjuvanted COVID-19 vaccine for use in combination with Sanofi’s flu vaccines; and (iii) a non-exclusive license to use the Matrix-M adjuvant in vaccine products. In addition, Sanofi took a minority (<5%) equity investment in Novavax. On May 13, 2024, as the largest private contributor to the security and independence of France's health ecosystem, Sanofi announced that it was increasing its investment in major industrial projects by €1.1 billion, by creating new bioproduction capacity at its sites in Vitry-sur-Seine (Val de Marne), Le Trait (Seine-Maritime) and Lyon Gerland (Rhône). This new investment will create more than 500 jobs and significantly strengthen France's ability to control the production of essential medicines from start to finish, for the present day and into the future. This plan brings to more than €3.5 billion the amount committed by Sanofi since the COVID-19 pandemic to major projects to keep production of medicines and vaccines in France for patients around the world. On May 21, 2024, Sanofi announced a collaboration with Formation Bio and OpenAI to build AI-powered software to accelerate drug development and bring new medicines to patients more efficiently. The three teams will bring together data, software and tuned models to develop custom, purpose-built solutions across the drug development lifecycle. This is the first collaboration of its kind within the pharma and life sciences industries. Sanofi will leverage this partnership to provide access to proprietary data to develop AI models as it continues on its path to becoming the first biopharma company powered by AI at scale. On May 30, 2024, Sanofi announced that it had completed the acquisition of Inhibrx, Inc (Inhibrx), a publicly-traded, clinical-stage biopharmaceutical company focused on developing a pipeline of novel biologic therapeutic candidates in oncology and orphan diseases. The acquisition added SAR447537 (formerly INBRX-101) to Sanofi’s rare disease development portfolio, and underscores the company’s commitment to developing differentiated, potentially best-in-class therapeutics, leveraging its existing strengths and capabilities. This transaction followed on from Sanofi's January 23, 2024 announcement of a merger agreement under which Sanofi planned to acquire Inhibrx following the spin-off of its non-INBRX- 101 assets and liabilities into a new publicly-traded company ("New Inhibrx"). Under the terms of the merger agreement, Sanofi agreed to (i) pay Inhibrx stockholders $30 per share of Inhibrx common stock on closing of the merger (approximately $1.7 billion) and issue one contingent value right (CVR) per share of Inhibrx common stock, entitling its holder to receive a deferred cash payment of $5, contingent upon the achievement of certain regulatory milestones (approximately $0.3 billion, if those milestones are achieved); (ii) pay off Inhibrx’s outstanding third-party debt (approximately $0.2 billion); and (iii) contribute capital to "New Inhibrx" (at least $0.2 billion). Since the closing of the merger, Sanofi has held 100% of the equity interests in Inhibrx, which has become a wholly owned subsidiary of Sanofi. Additionally, Inhibrx retained a minority stake (approximately 8%) in "New Inhibrx". On June 20, 2024, Sanofi and Biovac, a biopharmaceutical company based in Cape Town, South Africa, announced a local manufacturing partnership to produce inactivated polio vaccines (IPV) in Africa. This agreement is designed to enable regional manufacturing of IPV to serve the potential needs of over 40 African countries. This partnership with Sanofi makes Biovac the first African producer of IPV on and for the African continent, and supports the Africa Centers for Disease Control and Prevention’s ambition to have 60% of local vaccines produced in Africa by 2040. On June 21 2024, Audrey Duval Derveloy, a seasoned healthcare industry leader and Sanofi France’s President, was named Executive Vice President, Global Head of Corporate Affairs. Audrey became a member of Sanofi’s Executive Committee, reporting to CEO Paul Hudson, and is based in Paris. Her appointment was effective July 1, 2024.                                                                                                                                                                                                  SANOFI 2024 HALF-YEAR FINANCIAL REPORT 37 Net sales for the first half of 2024 amounted to €21,209 million, 5.1% higher than in the first half of 2023. At constant exchange rates (CER) , net sales rose by 8.4%, driven mainly by strong performances for Dupixent, increased sales of Nexviazyme, ALTUVIIIO, and Beyfortus. Net income attributable to equity holders of Sanofi amounted to €2,246 million in the first half of 2024, versus €3,430 million in the first half of 2023. Earnings per share was €1.80, versus €2.74 for the first half of 2023. Business net income was €4,380 million, down 10.2% on the first half of 2023, while business earnings per share (business EPS ) was €3.51, 10.0% lower than in the first half of 2023. A.2. RESEARCH AND DEVELOPMENT During the first half of 2024, Sanofi maintained its R&D efforts with the aim of improving quality of life for people around the globe by developing innovative vaccines and medicines. Immunology Dupixent (dupilumab) was approved by the US Food and Drug Administration (FDA) in January for the treatment of pediatric patients aged 1 to 11 years, weighing at least 15 kg, with eosinophilic esophagitis (EoE). This approval expands the initial FDA approval for EoE in May 2022 for patients aged 12 years and older, weighing at least 40 kg. The FDA22 FIN first FIN FIN</text> What is the correct answer to this question: By how2 comparedwithout)? Please retain one decimal place in the final calculation result. 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219244, 219245, 219248, 219249, 219250, 219251, 219252, 219253, 219254, 219255, 219256, 219257, 219258, 219259, 219263, 219264, 219266, 219267, 219268, 219269, 219270, 219271, 219272, 219273, 219274, 219275, 219276, 219277, 219279, 219280, 219281, 219282, 219283, 219284, 219287, 219288, 219289, 219290, 219291, 219292, 219293, 219294, 219295, 219296, 219297, 219298, 219299, 219300, 219301, 219302, 219303, 219304, 219305, 219306, 219307, 219308, 219309, 219310, 219311, 219312, 219313, 219314, 219315, 219316, 219317, 219318, 219319, 219320, 219321, 219322, 219323, 219324, 219325, 219326, 219327, 219328, 219329, 219330, 219331, 219332, 219333, 219334, 219335, 219336, 219337, 219338, 219339, 219340, 219341, 219342, 219343, 219344, 219345, 219346, 219347, 219348, 219349, 219350, 219351, 219352, 219353, 219354, 219355, 219356, 219357, 219358, 219359, 219360, 219361, 219362, 219363 ]
0.009336
219,364
Please comments2 the a my2 said She0 too2 though, and; her First her saving He died in but listenedively and formed opinions about like to too, stillungs and perhaps since! always, because help checking0ll save were as to her things packed; she was flying home to Seoul.alia and roommate,, never got wondering days what to Thalia saw all assumedina would be!), but council forgave her. all, maybe they, though, and solo had aalia had other of\u enough she carriedload at out told was like,\d said, least at that real, came to for must haveang around decorating,tail she9d never have worn to. They put on and soon I was forgotten. Puja Sharma showed up with she9d bought in and which the four of them ate inches,aling about calories I on own bed, my, and soon decided would be better to on than risk looking like I hoped to be included. I9tly, I was studying I was always good for a move But9 and was aboutalia And here to was That That were0, helped through disorder. I9d into some but dismissed this all-one rumor off the bat, it did from. to void because believed oner9d gotten the unfortunate early onder He of he at ofer said, \1,\ud and laughed,u1I mean Im not at1ly, to, suppose no maybe too shed she at Levin, but to for Christ sake, that of said scrub?\?\u4but I remember1 he saidf and Geoff off they left for retirement in situation as he mind asked partlyote to Der reminder toby together,\ud the only and but had side hustle kids who Even students had to sign up on schedule, but Geoff finagled key unlimited use in exchange maintenance there or2 exactly thought he teasing thrilled to!\ud she said out us!\1 same Then0 told them I been and my arms9t strong. I add that crew seemed like something It add that I) part found boat watched; it\u outu4 thought myself Heho or someone. But like was saying at dinner\u4 tou thought.\u1d He said itpan but grinned\ules all andu1d said, \11 asked Oliver how old he91d He thought second. \uu1d Fran said,1u1 said,1 said,,1,e and now, it up myself And while had found on her own, thatt fact that because said, on1 stayed up late talking in Jerome had of allowed to of the was one9 she who,2 Z wider2 enough night20 childish In morningt rested, lights night day bed.6 Before, Britt if mine podcastc your break somewhat when break kids it Lola her choir, and Fountain.,:. bubblesu \.u ones10 to.20 or to said nightn\u. might ask, or \ recently?\d rarely just said things0 needed to she springu and if she0 them to was of with of lack know what else to do had idea was something dealt with I assumed wasiny care it every weeks time whenalia on0 to he it worse elseilesuated They saw me tofriend people like them before found way, too version Dragon Tales andotta, section I0 saidd tried waited outsideagon she started asking but minutes was resources appointments Ied something nonsical, understand later that I was4 Cobain, Music. X handwriting. thing Beth andalia..\ italia was someone who it ever finally accepting them so I Yahav0 Wednesday night Britt him\u2 Britt and her show. seven an room, a Upper dorm that2., and Britt phone front me, to the recording app I\u2 kids download. creamy fish and14. She \c2 love the timeline.\ud. country. The;\u2. Britt, know girl. girl. If\u. Each: Remember?.. Doesn\u? Theneline online.particularly, hadn0 mentioned to friends Britt2 timelined2d girls passed occasionally, still sports gear or towels. They in.21 and I would late Britt.\1 It this.d, little tired Osaka never breakt about to rat them out She knew they, she explained later, worried of and to her, bother checking us into supposed to was on ski Olympics Britt God!\0d theleader.cI!d0u. upstairsu said2du.. Britt professionalismowed. podcast11u0 the podcast phone08u1 Britt0 a1d recordedu2 The0. wouldn\u.. reeln Britt a YouTube a man named Danera. He had a whole channel,, that ninety percent about Th..m.,2 Dane Rubra0, hadn..,eline and,. age.000 slept dawn LA.2 Twitter0 stronger Lower. Jasmine.0.0 Hay.,0 couldn couldn002 these kids movie2d0 but1 Jasmine Wilde their Britt corner. \c him?\ud0 Britt she was classmates0 her9 since morningol3.. couldn0 her bath morning sun. Britt Omar himself,. She.2 Okay last \5 afternoon, kids. their as0 night,. \2 it aren10u00dn 6 phone didn Jerome screen. But: Yah Saturday0 day after tomorrow most.\0.0 adolescencen 7\u website. it it darkening room before dinner, it. gossip. actress, and Dane Rubras world.:0 Prayer. hadn0 far up\u044and20 than texts Jasmine supporters tagging.4 Reddit ( care, Reddit0 forty Reddit three Tuesday: text from Fran: Where are you?? I\um outside Another: Are? I to hair was a past. had He Theres a. Robbie March08 Theper Club was exactly as remembered it, except that adulthood the wine was option, which immensely helped the mediocre food. There\u209 a We don\ut LA. carb0 Fran9 \d2 said,Wait, Britt\u Mondayud0 didn02 Britt room.,,\u2\uu0 women2212 desserts bak and-ad.2000u drunk. lot drunk. to wake up to the that0 I. And0 Franu Reed022 wonder0d.cu0 Fran said bet9 Fran.. obsessedd \ Fran\u01d0 waiter,, weren201. Fran9 bill him Sapphire card weird water.0 don\u2 Lester Holt was. and us drive, that so. the Supper Club\u. Fran had scarf,a,,. Through2cd had mint0\u400 Fran Bodd0 A Honda Civic, And listen2 joke. boy bar Kern2 kids02 If19re drink too much feel,. But mine I. My Twitter had4a\u0000 water freshman college0 scrolling:0_j0 someone Still no. Hello,00t were bed.\ut really sleep just fitfully sober up Across state, awake this thighs still bed Lance didn second hang class in20 wand ME shouldn2e0020ew,n0n wonn 13burb otn n 5 Did Iteeeeen Ga Ga Frogurt Baroundnungimiento erst Alwaysn n ightn arknn nnnnnhgnnnn #nnnn Hampshire Omarn7n8n ck Omar,1 and and competition Hampshire cedarn Chicago education be Stephanie Hausol Vaughorgyn Feverencing institutional collusionp ( poet Akbarmer Fried Hebrew peripheral.. Ragdale Foundation COVID Nag Marshall Greenittuestika Lopez Victoria DeW Ginaika Lam Grey Tedrowe Zoe Zolbro Finch,inkel Jon Freeman first reader humanStudio Chicago Northwestern University Sierra Nevada the Illinois Artists. The Lindseywo Schultz ass-k Vikings: Brian Tartvette Stark, Roh Lucia Bernard Elizabeth Yaffe Choi Mary Sara Leonard.astically authenticity. Truck Nicole,ovej Keaton Kust strange I If\u19 it. \n the Author Rebecca Makkai Theie, was Pulitzer the National Book Award the AL Carnegie the Stonewall Book, the Clark Prize, the Los Angeles Times Book Ten Best Books The York Times. The Borrower The Hundred-Year House theart2 The Best American Short Stories. A 02 Guggenheim Fellow, Rebecca is on the MFA the University of Nevada, Reno Tahoe and Northwestern University, and is Artistic Director Chicago. \n What\u2019? Discover your next great read! personalized book-to-date news about this author. Sign. _142493_ \n \n" } </text> What is the correct answer this question: Narrives: 1. [\"Sakina and the narrator Mike Stiles at, where discuss potential testimonies regarding Omar's case and the implications Serenho to the stand.\"]\n2. [\"Beth and the narrator discuss the of testimony Omar's case due to Robbie's past abusive behavior towards Thalia.\"]\n3. [\"Bodie Kane encountered former teacher Madame Mancio while Petra on the way campus, leading conversation where Madame Mancio surprise at Bodie's transformation since at Granby.\"]\n4. ['The narrator a video a caf\u00e9 using slow wi-fi, to frustration and an overwhelming need despite distractions.']\n\nQuery: Considering the given book and narratives, Which order of the narratives in the following options is correct? Choices: (A) 3412 (B) 1423 (C) 1324 (D) 3124 Format your response as follows: "The correct answer is (insert answer here)".
286
null
0
A
3412
Please comments2 the a my2 said She0 too2 though, and; her First her saving He died in but listenedively and formed opinions about like to too, stillungs and perhaps since! always, because help checking0ll save were as to her things packed; she was flying home to Seoul.alia and roommate,, never got wondering days what to Thalia saw all assumedina would be!), but council forgave her. all, maybe they, though, and solo had aalia had other of\u enough she carriedload at out told was like,\d said, least at that real, came to for must haveang around decorating,tail she9d never have worn to. They put on and soon I was forgotten. Puja Sharma showed up with she9d bought in and which the four of them ate inches,aling about calories I on own bed, my, and soon decided would be better to on than risk looking like I hoped to be included. I9tly, I was studying I was always good for a move But9 and was aboutalia And here to was That That were0, helped through disorder. I9d into some but dismissed this all-one rumor off the bat, it did from. to void because believed oner9d gotten the unfortunate early onder He of he at ofer said, \1,\ud and laughed,u1I mean Im not at1ly, to, suppose no maybe too shed she at Levin, but to for Christ sake, that of said scrub?\?\u4but I remember1 he saidf and Geoff off they left for retirement in situation as he mind asked partlyote to Der reminder toby together,\ud the only and but had side hustle kids who Even students had to sign up on schedule, but Geoff finagled key unlimited use in exchange maintenance there or2 exactly thought he teasing thrilled to!\ud she said out us!\1 same Then0 told them I been and my arms9t strong. I add that crew seemed like something It add that I) part found boat watched; it\u outu4 thought myself Heho or someone. But like was saying at dinner\u4 tou thought.\u1d He said itpan but grinned\ules all andu1d said, \11 asked Oliver how old he91d He thought second. \uu1d Fran said,1u1 said,1 said,,1,e and now, it up myself And while had found on her own, thatt fact that because said, on1 stayed up late talking in Jerome had of allowed to of the was one9 she who,2 Z wider2 enough night20 childish In morningt rested, lights night day bed.6 Before, Britt if mine podcastc your break somewhat when break kids it Lola her choir, and Fountain.,:. bubblesu \.u ones10 to.20 or to said nightn\u. might ask, or \ recently?\d rarely just said things0 needed to she springu and if she0 them to was of with of lack know what else to do had idea was something dealt with I assumed wasiny care it every weeks time whenalia on0 to he it worse elseilesuated They saw me tofriend people like them before found way, too version Dragon Tales andotta, section I0 saidd tried waited outsideagon she started asking but minutes was resources appointments Ied something nonsical, understand later that I was4 Cobain, Music. X handwriting. thing Beth andalia..\ italia was someone who it ever finally accepting them so I Yahav0 Wednesday night Britt him\u2 Britt and her show. seven an room, a Upper dorm that2., and Britt phone front me, to the recording app I\u2 kids download. creamy fish and14. She \c2 love the timeline.\ud. country. The;\u2. Britt, know girl. girl. If\u. Each: Remember?.. Doesn\u? Theneline online.particularly, hadn0 mentioned to friends Britt2 timelined2d girls passed occasionally, still sports gear or towels. They in.21 and I would late Britt.\1 It this.d, little tired Osaka never breakt about to rat them out She knew they, she explained later, worried of and to her, bother checking us into supposed to was on ski Olympics Britt God!\0d theleader.cI!d0u. upstairsu said2du.. Britt professionalismowed. podcast11u0 the podcast phone08u1 Britt0 a1d recordedu2 The0. wouldn\u.. reeln Britt a YouTube a man named Danera. He had a whole channel,, that ninety percent about Th..m.,2 Dane Rubra0, hadn..,eline and,. age.000 slept dawn LA.2 Twitter0 stronger Lower. Jasmine.0.0 Hay.,0 couldn couldn002 these kids movie2d0 but1 Jasmine Wilde their Britt corner. \c him?\ud0 Britt she was classmates0 her9 since morningol3.. couldn0 her bath morning sun. Britt Omar himself,. She.2 Okay last \5 afternoon, kids. their as0 night,. \2 it aren10u00dn 6 phone didn Jerome screen. But: Yah Saturday0 day after tomorrow most.\0.0 adolescencen 7\u website. it it darkening room before dinner, it. gossip. actress, and Dane Rubras world.:0 Prayer. hadn0 far up\u044and20 than texts Jasmine supporters tagging.4 Reddit ( care, Reddit0 forty Reddit three Tuesday: text from Fran: Where are you?? I\um outside Another: Are? I to hair was a past. had He Theres a. Robbie March08 Theper Club was exactly as remembered it, except that adulthood the wine was option, which immensely helped the mediocre food. There\u209 a We don\ut LA. carb0 Fran9 \d2 said,Wait, Britt\u Mondayud0 didn02 Britt room.,,\u2\uu0 women2212 desserts bak and-ad.2000u drunk. lot drunk. to wake up to the that0 I. And0 Franu Reed022 wonder0d.cu0 Fran said bet9 Fran.. obsessedd \ Fran\u01d0 waiter,, weren201. Fran9 bill him Sapphire card weird water.0 don\u2 Lester Holt was. and us drive, that so. the Supper Club\u. Fran had scarf,a,,. Through2cd had mint0\u400 Fran Bodd0 A Honda Civic, And listen2 joke. boy bar Kern2 kids02 If19re drink too much feel,. But mine I. My Twitter had4a\u0000 water freshman college0 scrolling:0_j0 someone Still no. Hello,00t were bed.\ut really sleep just fitfully sober up Across state, awake this thighs still bed Lance didn second hang class in20 wand ME shouldn2e0020ew,n0n wonn 13burb otn n 5 Did Iteeeeen Ga Ga Frogurt Baroundnungimiento erst Alwaysn n ightn arknn nnnnnhgnnnn #nnnn Hampshire Omarn7n8n ck Omar,1 and and competition Hampshire cedarn Chicago education be Stephanie Hausol Vaughorgyn Feverencing institutional collusionp ( poet Akbarmer Fried Hebrew peripheral.. Ragdale Foundation COVID Nag Marshall Greenittuestika Lopez Victoria DeW Ginaika Lam Grey Tedrowe Zoe Zolbro Finch,inkel Jon Freeman first reader humanStudio Chicago Northwestern University Sierra Nevada the Illinois Artists. The Lindseywo Schultz ass-k Vikings: Brian Tartvette Stark, Roh Lucia Bernard Elizabeth Yaffe Choi Mary Sara Leonard.astically authenticity. Truck Nicole,ovej Keaton Kust strange I If\u19 it. \n the Author Rebecca Makkai Theie, was Pulitzer the National Book Award the AL Carnegie the Stonewall Book, the Clark Prize, the Los Angeles Times Book Ten Best Books The York Times. The Borrower The Hundred-Year House theart2 The Best American Short Stories. A 02 Guggenheim Fellow, Rebecca is on the MFA the University of Nevada, Reno Tahoe and Northwestern University, and is Artistic Director Chicago. \n What\u2019? Discover your next great read! personalized book-to-date news about this author. Sign. _142493_ \n \n" } </text> What is the correct answer this question: Narrives: 1. [\"Sakina and the narrator Mike Stiles at, where discuss potential testimonies regarding Omar's case and the implications Serenho to the stand.\"]\n2. [\"Beth and the narrator discuss the of testimony Omar's case due to Robbie's past abusive behavior towards Thalia.\"]\n3. [\"Bodie Kane encountered former teacher Madame Mancio while Petra on the way campus, leading conversation where Madame Mancio surprise at Bodie's transformation since at Granby.\"]\n4. ['The narrator a video a caf\u00e9 using slow wi-fi, to frustration and an overwhelming need despite distractions.']\n\nQuery: Considering the given book and narratives, Which order of the narratives in the following options is correct? Choices: (A) 3412 (B) 1423 (C) 1324 (D) 3124 Format your response as follows: "The correct answer is (insert answer here)".
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Please read the following text and answer the question below. <text> Various Degradation: Dual Cross-Refinement Transformer for Blind Sonar Image Super-Resolution Abstract— Deep learning-based methods have achieved remarkable results in super-resolution (SR) of sonar images. However, most existing methods only consider simple bicubic downsampling degradation, and SR networks suitable for natural images may not be suitable for sonar images. Therefore, they perform poorly on sonar images with unknown degradation parameters in real-world scenarios (i.e., blind scenario). To address these issues, we propose a dual cross- refinement transformer (DCRT) for blind SR of sonar images. DCRT first constructs a large-scale degradation space based on the sonar image imaging mechanism. More importantly, we randomly sample the task-level training information to make DCRT robust on different SR tasks, thereby enhancing the blind SR capability of the network. Then, DCRT focuses on image features than domain features through spatial-channel self-attention cross-fusion block (S-C-SACFB), so the domain gap between the training and testing data can be reduced. Meanwhile, S-C-SACFB effectively combines inter-attention (I-A) and high-frequency enhancement residual block (HFERB) to enhance the network’s ability to extract high-frequency features while suppressing speckle noise in sonar images. Finally, DCRT uses global residual connections to generate high- resolution (HR) sonar images. A large number of experiments at different SR scale show that DCRT outperforms the state-of- the-art methods in both quantitative and qualitative aspects. Index Terms— Blind image super-resolution (SR), deep learning, self-attention, sonar, Transformer. I. INTRODUCTION A S AN important sensor in the field of remote sensing, sonar can image in dark deep marine environments, bringing rich visual information of the observation area for exploiting ocean resources. Therefore, sonar images are widely used in target detection [1], [2], [3], image segmentation [4], and underwater perception [5], [6]. However, due to limitations of the imaging mechanism and the complexity of underwater environment, sonar images often have low-resolution (LR) problems and are easily affected by speckle noise of unknown parameters [7]. These problems bring difficulties to the Manuscript received 30 January 2024; revised 10 April 2024; accepted 30 April 2024. Date of publication 8 May 2024; date of current version 21 May 2024. This work was supported by the National Natural Science Foundation of China under Grant 61971315. (Corresponding author: Xin Tian.) Jiahao Rao, Yini Peng, and Xin Tian are with the Electronic Information School, Wuhan University, Wuhan 430072, China (e-mail: jiahaorao@whu.edu.cn; pengyini@whu.edu.cn; xin.tian@whu.edu.cn). Jun Chen is with the School of Automation, China University of Geosciences, Wuhan 430074, China (e-mail: chenjun71983@163.com). Digital Object Identifier 10.1109/TGRS.2024.3398188 application of sonar images. Therefore, it is necessary to improve the resolution of sonar images while removing their speckle noise. Image super-resolution (SR) aims to restore details from LR images, improve their resolution, and obtain high-resolution (HR) images [8], [9]. As an ill-posed problem with infinite solutions [10], [11], it has always been a challenging task in the field of computer vision [12]. To solve this problem, many methods have been proposed. Traditional algorithms such as interpolation algorithms, ANR [13], and A+ [14] have high computational efficiency, but they are limited by modeling capabilities. The images generated by them often ignore some details, especially edge and texture information. In recent years, the continuous development of deep learning has led to the emergence of image SR algorithms. Dong et al. [15] were the first to apply convolutional neural networks (CNNs) to image SR and proposed SRCNN. The SR results of SRCNN were far superior to traditional methods in both visual effects and evaluation metrics. Based on CNN, researchers have proposed complex neural network models such as very deep SR (VDSR) [16], enhanced deep SR (EDSR) [17], and residual channel attention networks (RCANs) [18]. These methods all have stronger nonlinear fitting capabilities than SRCNN and can learn the mapping relationship between LR images and HR images powerfully. However, CNN-based models often produce smooth results [19]. The emergence of generative adversarial networks (GANs) [20] brought new ideas to researchers. SRGAN [19] was the first method to apply GAN principles to image SR. Although its SR results did not get high value of the evaluation metrics, they contained rich details and were consistent with human visual perception. Since then, SR methods based on GAN have emerged. Wang et al. [21] improved the generator in SRGAN by deleting batchnorm (BN) layers and introducing residual dense blocks, proposed ESRGAN. Cai et al. [22] introduced channel attention to make the generator pay more attention to the inter-channel dependencies. Their methods have achieved good SR results. Considering successful development in SR of natural images, some researchers have attempted to apply it to the SR of sonar images. Guanying et al. [23] replaced ordinary convolutional layers with dilated convolutional layers to optimize SRGAN and applied it to sonar image SR reconstruction. Similarly, Shen et al. [24] deepened 4206114 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 62, 2024 Fig. 1. (a) Degradation process with fixed parameters considered by traditional methods. (b) Degradation process with various degradation parameters in real scenarios. There is a domain gap in traditional methods due to differences in degradation processes. the network layers of SRGAN. Nambiar et al. [25] and Song et al. [26] optimized ESRGAN [21] to achieve SR of sonar images. Sung et al. [27] stacked convolutional layers and residual blocks to build a sonar image SR network. To improve SR performance and remove speckle noise, Huo et al. [28] first obtained HR images through non- iterative data fusion and then performed speckle denoising. However, this method introduced cascading errors. Inspired by self-calibrated convolution [29], Ma et al. [30] constructed a multihead GAN (MHGAN) to achieve sonar image SR. Specifically, they designed a simple-dense net to extend the receptive field of convolution and introduced a multihead U-Net architecture to enhance the discrimination ability of the discriminator. Although some attempts have been made to the SR of sonar images based on deep learning, the following limitations still exist. 1) As shown in Fig. 1, traditional methods only utilize a degradation process with fixed parameters, which may be different from the real scenarios with various degradation parameters. Therefore, there is a domain gap in traditional methods due to differences in degradation processes. In other words, the complex degradation process of sonar images in real scenarios is not fully considered, and the degradation parameters in this degradation process are generally unknown (i.e., blind scenario). Therefore, the SR ability of the previous method on sonar images in blind scenario is not superior. 2) Introducing a complex degradation process will bring large difficulty in distinguishing image features from multiplicative speckle noise features. As a result, traditional deep networks cannot be directly applied in the complex degradation scene. To address the above problems, this article proposes a blind SR network for sonar images in the real scenario: dual cross-refinement transformer (DCRT) with joint spatial- channel self-attention. Based on the imaging mechanism of sonar images [31], we construct a large degradation space. After that, the task-level training information is randomly sampled to make the network robust on different SR tasks. This can enhance the DCRT’s modeling ability in blind scenarios. Secondly, we propose a spatial-channel self-attention cross-fusion block (S-C-SACFB). S-C-SACFB combines spatial-wise self-attention (SW-SA) and2 2p2 SS21112p21</text> What is the correct answer to this question: Which of the following statements is incorrect? Choices: (A) By. (B). (C) (D) Format your response as follows: "The correct answer is (insert answer here)".
287
null
2
C
In the forward process, the optimization of θ is achieved by minimizing the negative evidence lower bound
Please read the following text and answer the question below. <text> Various Degradation: Dual Cross-Refinement Transformer for Blind Sonar Image Super-Resolution Abstract— Deep learning-based methods have achieved remarkable results in super-resolution (SR) of sonar images. However, most existing methods only consider simple bicubic downsampling degradation, and SR networks suitable for natural images may not be suitable for sonar images. Therefore, they perform poorly on sonar images with unknown degradation parameters in real-world scenarios (i.e., blind scenario). To address these issues, we propose a dual cross- refinement transformer (DCRT) for blind SR of sonar images. DCRT first constructs a large-scale degradation space based on the sonar image imaging mechanism. More importantly, we randomly sample the task-level training information to make DCRT robust on different SR tasks, thereby enhancing the blind SR capability of the network. Then, DCRT focuses on image features than domain features through spatial-channel self-attention cross-fusion block (S-C-SACFB), so the domain gap between the training and testing data can be reduced. Meanwhile, S-C-SACFB effectively combines inter-attention (I-A) and high-frequency enhancement residual block (HFERB) to enhance the network’s ability to extract high-frequency features while suppressing speckle noise in sonar images. Finally, DCRT uses global residual connections to generate high- resolution (HR) sonar images. A large number of experiments at different SR scale show that DCRT outperforms the state-of- the-art methods in both quantitative and qualitative aspects. Index Terms— Blind image super-resolution (SR), deep learning, self-attention, sonar, Transformer. I. INTRODUCTION A S AN important sensor in the field of remote sensing, sonar can image in dark deep marine environments, bringing rich visual information of the observation area for exploiting ocean resources. Therefore, sonar images are widely used in target detection [1], [2], [3], image segmentation [4], and underwater perception [5], [6]. However, due to limitations of the imaging mechanism and the complexity of underwater environment, sonar images often have low-resolution (LR) problems and are easily affected by speckle noise of unknown parameters [7]. These problems bring difficulties to the Manuscript received 30 January 2024; revised 10 April 2024; accepted 30 April 2024. Date of publication 8 May 2024; date of current version 21 May 2024. This work was supported by the National Natural Science Foundation of China under Grant 61971315. (Corresponding author: Xin Tian.) Jiahao Rao, Yini Peng, and Xin Tian are with the Electronic Information School, Wuhan University, Wuhan 430072, China (e-mail: jiahaorao@whu.edu.cn; pengyini@whu.edu.cn; xin.tian@whu.edu.cn). Jun Chen is with the School of Automation, China University of Geosciences, Wuhan 430074, China (e-mail: chenjun71983@163.com). Digital Object Identifier 10.1109/TGRS.2024.3398188 application of sonar images. Therefore, it is necessary to improve the resolution of sonar images while removing their speckle noise. Image super-resolution (SR) aims to restore details from LR images, improve their resolution, and obtain high-resolution (HR) images [8], [9]. As an ill-posed problem with infinite solutions [10], [11], it has always been a challenging task in the field of computer vision [12]. To solve this problem, many methods have been proposed. Traditional algorithms such as interpolation algorithms, ANR [13], and A+ [14] have high computational efficiency, but they are limited by modeling capabilities. The images generated by them often ignore some details, especially edge and texture information. In recent years, the continuous development of deep learning has led to the emergence of image SR algorithms. Dong et al. [15] were the first to apply convolutional neural networks (CNNs) to image SR and proposed SRCNN. The SR results of SRCNN were far superior to traditional methods in both visual effects and evaluation metrics. Based on CNN, researchers have proposed complex neural network models such as very deep SR (VDSR) [16], enhanced deep SR (EDSR) [17], and residual channel attention networks (RCANs) [18]. These methods all have stronger nonlinear fitting capabilities than SRCNN and can learn the mapping relationship between LR images and HR images powerfully. However, CNN-based models often produce smooth results [19]. The emergence of generative adversarial networks (GANs) [20] brought new ideas to researchers. SRGAN [19] was the first method to apply GAN principles to image SR. Although its SR results did not get high value of the evaluation metrics, they contained rich details and were consistent with human visual perception. Since then, SR methods based on GAN have emerged. Wang et al. [21] improved the generator in SRGAN by deleting batchnorm (BN) layers and introducing residual dense blocks, proposed ESRGAN. Cai et al. [22] introduced channel attention to make the generator pay more attention to the inter-channel dependencies. Their methods have achieved good SR results. Considering successful development in SR of natural images, some researchers have attempted to apply it to the SR of sonar images. Guanying et al. [23] replaced ordinary convolutional layers with dilated convolutional layers to optimize SRGAN and applied it to sonar image SR reconstruction. Similarly, Shen et al. [24] deepened 4206114 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 62, 2024 Fig. 1. (a) Degradation process with fixed parameters considered by traditional methods. (b) Degradation process with various degradation parameters in real scenarios. There is a domain gap in traditional methods due to differences in degradation processes. the network layers of SRGAN. Nambiar et al. [25] and Song et al. [26] optimized ESRGAN [21] to achieve SR of sonar images. Sung et al. [27] stacked convolutional layers and residual blocks to build a sonar image SR network. To improve SR performance and remove speckle noise, Huo et al. [28] first obtained HR images through non- iterative data fusion and then performed speckle denoising. However, this method introduced cascading errors. Inspired by self-calibrated convolution [29], Ma et al. [30] constructed a multihead GAN (MHGAN) to achieve sonar image SR. Specifically, they designed a simple-dense net to extend the receptive field of convolution and introduced a multihead U-Net architecture to enhance the discrimination ability of the discriminator. Although some attempts have been made to the SR of sonar images based on deep learning, the following limitations still exist. 1) As shown in Fig. 1, traditional methods only utilize a degradation process with fixed parameters, which may be different from the real scenarios with various degradation parameters. Therefore, there is a domain gap in traditional methods due to differences in degradation processes. In other words, the complex degradation process of sonar images in real scenarios is not fully considered, and the degradation parameters in this degradation process are generally unknown (i.e., blind scenario). Therefore, the SR ability of the previous method on sonar images in blind scenario is not superior. 2) Introducing a complex degradation process will bring large difficulty in distinguishing image features from multiplicative speckle noise features. As a result, traditional deep networks cannot be directly applied in the complex degradation scene. To address the above problems, this article proposes a blind SR network for sonar images in the real scenario: dual cross-refinement transformer (DCRT) with joint spatial- channel self-attention. Based on the imaging mechanism of sonar images [31], we construct a large degradation space. After that, the task-level training information is randomly sampled to make the network robust on different SR tasks. This can enhance the DCRT’s modeling ability in blind scenarios. Secondly, we propose a spatial-channel self-attention cross-fusion block (S-C-SACFB). S-C-SACFB combines spatial-wise self-attention (SW-SA) and2 2p2 SS21112p21</text> What is the correct answer to this question: Which of the following statements is incorrect? Choices: (A) By. (B). (C) (D) Format your response as follows: "The correct answer is (insert answer here)".
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Please read the following text and answer the question below. <text> """ Download the weights in ./checkpoints beforehand for fast inference wget https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model*_base_caption.pth wget https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model*_vqa.pth wget https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_retrieval_coco.pth """ from pathlib import Path from PIL import Image import torch from torchvision import transforms from torchvision.transforms.functional import InterpolationMode import cog from models.blip import blip_decoder from models.blip_vqa import blip_vqa from models.blip_itm import blip_itm class Predictor(cog.Predictor): def setup(self): self.device = "cuda:0" self.models = { 'image_captioning': blip_decoder(pretrained='checkpoints/model*_base_caption.pth', image_size=384, vit='base'), 'visual_question_answering': blip_vqa(pretrained='checkpoints/model*_vqa.pth', image_size=480, vit='base'), 'image_text_matching': blip_itm(pretrained='checkpoints/model_base_retrieval_coco.pth', image_size=384, vit='base') } @cog.input( "image", type=Path, help="input image", ) @cog.input( "task", type=str, default='image_captioning', options=['image_captioning', 'visual_question_answering', 'image_text_matching'], help="Choose a task.", ) @cog.input( "question", type=str, default=None, help="Type question for the input image for visual question answering task.", ) @cog.input( "caption", type=str, default=None, help="Type caption for the input image for image text matching task.", ) def predict(self, image, task, question, caption): if task == 'visual_question_answering': assert question is not None, 'Please type a question for visual question answering task.' if task == 'image_text_matching': assert caption is not None, 'Please type a caption for mage text matching task.' im = load_image(image, image_size=480 if task == 'visual_question_answering' else 384, device=self.device) model = self.models[task] model.eval() model = model.to(self.device) if task == 'image_captioning': with torch.no_grad(): caption = model.generate(im, sample=False, num_beams=3, max_length=20, min_length=5) return 'Caption: ' + caption[0] if task == 'visual_question_answering': with torch.no_grad(): answer = model(im, question, train=False, inference='generate') return 'Answer: ' + answer[0] # image_text_matching itm_output = model(im, caption, match_head='itm') itm_score = torch.nn.functional.softmax(itm_output, dim=1)[:, 1] itc_score = model(im, caption, match_head='itc') return f'The image and text is matched with a probability of {itm_score.item():.4f}.\n' \ f'The image feature and text feature has a cosine similarity of {itc_score.item():.4f}.' def load_image(image, image_size, device): raw_image = Image.open(str(image)).convert('RGB') w, h = raw_image.size transform = transforms.Compose([ transforms.Resize((image_size, image_size), interpolation=InterpolationMode.BICUBIC), transforms.ToTensor(), transforms.Normalize((0.48145466, 0.4578275, 0.40821073), (0.26862954, 0.26130258, 0.27577711)) ]) image = transform(raw_image).unsqueeze(0).to(device) return image ''' * Copyright (c) 2022, salesforce.com, inc. * All rights reserved. * SPDX-License-Identifier: BSD-3-Clause * For full license text, see LICENSE.txt file in the repo root or https://opensource.org/licenses/BSD-3-Clause * By Junnan Li ''' import argparse import os import ruamel_yaml as yaml import numpy as np import random import time import datetime import json from pathlib import Path import torch import torch.nn as nn import torch.nn.functional as F import torch.backends.cudnn as cudnn import torch.distributed as dist from torch.utils.data import DataLoader from models.blip import blip_decoder import utils from utils import cosine_lr_schedule from data import create_dataset, create_sampler, create_loader from data.utils import save_result, coco_caption_eval def train(model, data_loader, optimizer, epoch, device): # train model.train() metric_logger = utils.MetricLogger(delimiter=" ") metric_logger.add_meter('lr', utils.SmoothedValue(window_size=1, fmt='{value:.6f}')) metric_logger.add_meter('loss', utils.SmoothedValue(window_size=1, fmt='{value:.4f}')) header = 'Train Caption Epoch: [{}]'.format(epoch) print_freq = 50 for i, (image, caption, _) in enumerate(metric_logger.log_every(data_loader, print_freq, header)): image = image.to(device) loss = model(image, caption) optimizer.zero_grad() loss.backward() optimizer.step() metric_logger.update(loss=loss.item()) metric_logger.update(lr=optimizer.param_groups[0]["lr"]) # gather the stats from all processes metric_logger.synchronize_between_processes() print("Averaged stats:", metric_logger.global_avg()) return {k: "{:.3f}".format(meter.global_avg) for k, meter in metric_logger.meters.items()} @torch.no_grad() def evaluate(model, data_loader, device, config): # evaluate model.eval() metric_logger = utils.MetricLogger(delimiter=" ") header = 'Caption generation:' print_freq = 10 result = [] for image, image_id in metric_logger.log_every(data_loader, print_freq, header): image = image.to(device) captions = model.generate(image, sample=False, num_beams=config['num_beams'], max_length=config['max_length'], min_length=config['min_length']) for caption, img_id in zip(captions, image_id): result.append({"image_id": img_id.item(), "caption": caption}) return result def main(args, config): utils.init_distributed_mode(args) device = torch.device(args.device) # fix the seed for reproducibility seed = args.seed + utils.get_rank() torch.manual_seed(seed) np.random.seed(seed) random.seed(seed) cudnn.benchmark = True #### Dataset #### print("Creating captioning dataset") train_dataset, val_dataset, test_dataset = create_dataset('caption_coco', config) if args.distributed: num_tasks = utils.get_world_size() global_rank = utils.get_rank() samplers = create_sampler([train_dataset,val_dataset,test_dataset], [True,False,False], num_tasks, global_rank) else: samplers = [None, None, None] train_loader, val_loader, test_loader = create_loader([train_dataset, val_dataset, test_dataset],samplers, batch_size=[config['batch_size']]*3,num_workers=[4,4,4], is_trains=[True, False, False], collate_fns=[None,None,None]) #### Model #### print("Creating model") model = blip_decoder(pretrained=config['pretrained'], image_size=config['image_size'], vit=config['vit'], vit_grad_ckpt=config['vit_grad_ckpt'], vit_ckpt_layer=config['vit_ckpt_layer'], prompt=config['prompt']) model = model.to(device) model_without_ddp = model if args.distributed: model = torch.nn.parallel.DistributedDataParallel(model, device_ids=[args.gpu]) model_without_ddp = model.module optimizer = torch.optim.AdamW(params=model.parameters(), lr=config['init_lr'], weight_decay=config['weight_decay']) best = 0 best_epoch = 0 print("Start training") start_time = time.time() for epoch in range(0, config['max_epoch']): if not args.evaluate: if args.distributed: train_loader.sampler.set_epoch(epoch) cosine_lr_schedule(optimizer, epoch, config['max_epoch'], config['init_lr'], config['min_lr']) train_stats = train(model, train.output(_ch if_headobj_hiddeneg model_head_att_attobj_to-re-re 0 } </text> What is the correct answer to this question: If I BL but which should modify? Choices: (A) (B (C (D) Format your response as follows: "The correct answer is (insert answer here)".
288
null
2
C
BertSelfAttention
Please read the following text and answer the question below. <text> """ Download the weights in ./checkpoints beforehand for fast inference wget https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model*_base_caption.pth wget https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model*_vqa.pth wget https://storage.googleapis.com/sfr-vision-language-research/BLIP/models/model_base_retrieval_coco.pth """ from pathlib import Path from PIL import Image import torch from torchvision import transforms from torchvision.transforms.functional import InterpolationMode import cog from models.blip import blip_decoder from models.blip_vqa import blip_vqa from models.blip_itm import blip_itm class Predictor(cog.Predictor): def setup(self): self.device = "cuda:0" self.models = { 'image_captioning': blip_decoder(pretrained='checkpoints/model*_base_caption.pth', image_size=384, vit='base'), 'visual_question_answering': blip_vqa(pretrained='checkpoints/model*_vqa.pth', image_size=480, vit='base'), 'image_text_matching': blip_itm(pretrained='checkpoints/model_base_retrieval_coco.pth', image_size=384, vit='base') } @cog.input( "image", type=Path, help="input image", ) @cog.input( "task", type=str, default='image_captioning', options=['image_captioning', 'visual_question_answering', 'image_text_matching'], help="Choose a task.", ) @cog.input( "question", type=str, default=None, help="Type question for the input image for visual question answering task.", ) @cog.input( "caption", type=str, default=None, help="Type caption for the input image for image text matching task.", ) def predict(self, image, task, question, caption): if task == 'visual_question_answering': assert question is not None, 'Please type a question for visual question answering task.' if task == 'image_text_matching': assert caption is not None, 'Please type a caption for mage text matching task.' im = load_image(image, image_size=480 if task == 'visual_question_answering' else 384, device=self.device) model = self.models[task] model.eval() model = model.to(self.device) if task == 'image_captioning': with torch.no_grad(): caption = model.generate(im, sample=False, num_beams=3, max_length=20, min_length=5) return 'Caption: ' + caption[0] if task == 'visual_question_answering': with torch.no_grad(): answer = model(im, question, train=False, inference='generate') return 'Answer: ' + answer[0] # image_text_matching itm_output = model(im, caption, match_head='itm') itm_score = torch.nn.functional.softmax(itm_output, dim=1)[:, 1] itc_score = model(im, caption, match_head='itc') return f'The image and text is matched with a probability of {itm_score.item():.4f}.\n' \ f'The image feature and text feature has a cosine similarity of {itc_score.item():.4f}.' def load_image(image, image_size, device): raw_image = Image.open(str(image)).convert('RGB') w, h = raw_image.size transform = transforms.Compose([ transforms.Resize((image_size, image_size), interpolation=InterpolationMode.BICUBIC), transforms.ToTensor(), transforms.Normalize((0.48145466, 0.4578275, 0.40821073), (0.26862954, 0.26130258, 0.27577711)) ]) image = transform(raw_image).unsqueeze(0).to(device) return image ''' * Copyright (c) 2022, salesforce.com, inc. * All rights reserved. * SPDX-License-Identifier: BSD-3-Clause * For full license text, see LICENSE.txt file in the repo root or https://opensource.org/licenses/BSD-3-Clause * By Junnan Li ''' import argparse import os import ruamel_yaml as yaml import numpy as np import random import time import datetime import json from pathlib import Path import torch import torch.nn as nn import torch.nn.functional as F import torch.backends.cudnn as cudnn import torch.distributed as dist from torch.utils.data import DataLoader from models.blip import blip_decoder import utils from utils import cosine_lr_schedule from data import create_dataset, create_sampler, create_loader from data.utils import save_result, coco_caption_eval def train(model, data_loader, optimizer, epoch, device): # train model.train() metric_logger = utils.MetricLogger(delimiter=" ") metric_logger.add_meter('lr', utils.SmoothedValue(window_size=1, fmt='{value:.6f}')) metric_logger.add_meter('loss', utils.SmoothedValue(window_size=1, fmt='{value:.4f}')) header = 'Train Caption Epoch: [{}]'.format(epoch) print_freq = 50 for i, (image, caption, _) in enumerate(metric_logger.log_every(data_loader, print_freq, header)): image = image.to(device) loss = model(image, caption) optimizer.zero_grad() loss.backward() optimizer.step() metric_logger.update(loss=loss.item()) metric_logger.update(lr=optimizer.param_groups[0]["lr"]) # gather the stats from all processes metric_logger.synchronize_between_processes() print("Averaged stats:", metric_logger.global_avg()) return {k: "{:.3f}".format(meter.global_avg) for k, meter in metric_logger.meters.items()} @torch.no_grad() def evaluate(model, data_loader, device, config): # evaluate model.eval() metric_logger = utils.MetricLogger(delimiter=" ") header = 'Caption generation:' print_freq = 10 result = [] for image, image_id in metric_logger.log_every(data_loader, print_freq, header): image = image.to(device) captions = model.generate(image, sample=False, num_beams=config['num_beams'], max_length=config['max_length'], min_length=config['min_length']) for caption, img_id in zip(captions, image_id): result.append({"image_id": img_id.item(), "caption": caption}) return result def main(args, config): utils.init_distributed_mode(args) device = torch.device(args.device) # fix the seed for reproducibility seed = args.seed + utils.get_rank() torch.manual_seed(seed) np.random.seed(seed) random.seed(seed) cudnn.benchmark = True #### Dataset #### print("Creating captioning dataset") train_dataset, val_dataset, test_dataset = create_dataset('caption_coco', config) if args.distributed: num_tasks = utils.get_world_size() global_rank = utils.get_rank() samplers = create_sampler([train_dataset,val_dataset,test_dataset], [True,False,False], num_tasks, global_rank) else: samplers = [None, None, None] train_loader, val_loader, test_loader = create_loader([train_dataset, val_dataset, test_dataset],samplers, batch_size=[config['batch_size']]*3,num_workers=[4,4,4], is_trains=[True, False, False], collate_fns=[None,None,None]) #### Model #### print("Creating model") model = blip_decoder(pretrained=config['pretrained'], image_size=config['image_size'], vit=config['vit'], vit_grad_ckpt=config['vit_grad_ckpt'], vit_ckpt_layer=config['vit_ckpt_layer'], prompt=config['prompt']) model = model.to(device) model_without_ddp = model if args.distributed: model = torch.nn.parallel.DistributedDataParallel(model, device_ids=[args.gpu]) model_without_ddp = model.module optimizer = torch.optim.AdamW(params=model.parameters(), lr=config['init_lr'], weight_decay=config['weight_decay']) best = 0 best_epoch = 0 print("Start training") start_time = time.time() for epoch in range(0, config['max_epoch']): if not args.evaluate: if args.distributed: train_loader.sampler.set_epoch(epoch) cosine_lr_schedule(optimizer, epoch, config['max_epoch'], config['init_lr'], config['min_lr']) train_stats = train(model, train.output(_ch if_headobj_hiddeneg model_head_att_attobj_to-re-re 0 } </text> What is the correct answer to this question: If I BL but which should modify? Choices: (A) (B (C (D) Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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15,447
Please read the following text and answer the question below. <text> Published as a conference paper at ICLR 2024 MAGICDRIVE: STREET VIEW GENERATION WITH DIVERSE 3D GEOMETRY CONTROL ABSTRACT Recent advancements in diffusion models have significantly enhanced the data synthesis with 2D control. Yet, precise 3D control in street view generation, cru- cial for 3D perception tasks, remains elusive. Specifically, utilizing Bird’s-Eye View (BEV) as the primary condition often leads to challenges in geometry control (e.g., height), affecting the representation of object shapes, occlusion patterns, and road surface elevations, all of which are essential to perception data synthesis, es- pecially for 3D object detection tasks. In this paper, we introduce MAGICDRIVE, a novel street view generation framework, offering diverse 3D geometry controls including camera poses, road maps, and 3D bounding boxes, together with textual descriptions, achieved through tailored encoding strategies. Besides, our design incorporates a cross-view attention module, ensuring consistency across multiple camera views. With MAGICDRIVE, we achieve high-fidelity street-view image & video synthesis that captures nuanced 3D geometry and various scene descrip- tions, enhancing tasks like BEV segmentation and 3D object detection. Front Front Left Front Right ... ... Rainy 🌧 Sunny ☀ BEV map Camera pose + + = 3D box Figure 1: Multi-camera street view generation from MAGICDRIVE. MAGICDRIVE can generate continuous camera views with controls from the road map, object boxes, and text (e.g., weather). 1 INTRODUCTION The high costs associated with data collection and annotation often impede the effective training of deep learning models. Fortunately, cutting-edge generative models have illustrated that synthetic data can notably boost performance across various tasks, such as object detection (Chen et al., 2023c) and semantic segmentation (Wu et al., 2023b). Yet, the prevailing methodologies are largely tailored to 2D contexts, primarily relying on 2D bounding boxes (Lin et al., 2014; Han et al., 2021) or segmentation maps (Zhou et al., 2019) as layout conditions (Chen et al., 2023c; Li et al., 2023b). In autonomous driving applications, a thorough grasp of the 3D environment is essential. This demands reliable techniques for tasks like Bird’s-Eye View (BEV) map segmentation (Zhou & Kr¨ ahenb¨ uhl, 2022; Ji et al., 2023) and 3D object detection (Chen et al., 2020; Huang et al., 2021; Liu et al., 2023a; Ge et al., 2023). A genuine 3D geometry representation is crucial for capturing intricate details from 3D annotations, such as road elevations, object heights, and their occlusion pat- ∗Equal contribution. †Corresponding authors. Project Page: https://flymin.github.io/magicdrive. 1 arXiv:2310.02601v7 [cs.CV] 3 May 2024 Published as a conference paper at ICLR 2024 (a) 3D bounding boxes show position relationships. (b) Road surface elevation guided by 3D bounding boxes. 2D boxes BEV Map No distance No occlusion No view-consistency No height Figure 2: 3D bounding boxes are crucial for street view synthesis. Two examples show that 2D boxes or BEV maps lost distance, height, and elevation. Images are generated from MAGICDRIVE. terns, as shown in Figure 2. Consequently, generating multi-camera street-view images according to 3D annotations becomes vital to boost downstream perception tasks. For street-view data synthesis, two pivotal criteria are realism and controllability. Realism requires that the quality of the synthetic data should align with that of real data; and in a given scene, views from varying camera perspectives should remain consistent with one another (Mildenhall et al., 2020). On the other hand, controllability emphasizes the precision in generating street-view images that adhere to provided conditions: the BEV map, 3D object bounding boxes, and camera poses for views. Beyond these core requirements, effective data augmentation should also grant the flexibility to tweak finer scenario attributes, such as prevailing weather conditions or the time of day. Existing solutions like BEVGen (Swerdlow et al., 2023) approach street view generation by encapsulating all semantics within BEV. Conversely, BEVControl (Yang et al., 2023a) starts by projecting 3D coordinates to image views, subsequently using 2D geometric guidance. However, both methods compromise certain geometric dimensions—height is lost in BEVGen and depth in BEVControl. The rise of diffusion models has significantly pushed the boundaries of controllable image gener- ation quality. Specifically, ControlNet (Zhang et al., 2023a) proposes a flexible framework to in- corporate 2D spatial controls based on pre-trained Text-to-Image (T2I) diffusion models (Rombach et al., 2022). However, 3D conditions are distinct from pixel-level conditions or text. The challenge of seamlessly integrating them with multi-camera view consistency in street view synthesis remains. In this paper, we introduce MAGICDRIVE, a novel framework dedicated to street-view synthesis with diverse 3D geometry controls1. For realism, we harness the power of pre-trained stable dif- fusion (Rombach et al., 2022), further fine-tuning it for street view generation. One distinctive component of our framework is the cross-view attention module. This simple yet effective com- ponent provides multi-view consistency through interactions between adjacent views. In contrast to previous methods, MAGICDRIVE proposes a separate design for objects and road map encoding to improve controllability with 3D data. More specifically, given the sequence-like, variable-length nature of 3D bounding boxes, we employ cross-attention akin to text embeddings for their encod- ing. Besides, we propose that an addictive encoder branch like ControlNet (Zhang et al., 2023a) can encode maps in BEV and is capable of view transformation. Therefore, our design achieves geometric controls without resorting to any explicit geometric transformations or imposing geomet- ric constraints on multi-camera consistency. Finally, MAGICDRIVE factors in textual descriptions, offering attribute control such as weather conditions and time of day. Our MAGICDRIVE framework, despite its simplicity, excels in generating strikingly realistic images & videos that align with road maps, 3D bounding boxes, and varied camera perspectives. Besides, the images produced can enhance the training for both 3D object detection and BEV segmentation tasks. Furthermore, MAGICDRIVE offers comprehensive geometric controls at the scene, back- ground, and foreground levels. This flexibility makes it possible to craft previously unseen street views suitable for simulation purposes. We summarize the main contributions of this work as: • The introduction of MAGICDRIVE, an innovative framework that generates multi-perspective camera views & videos conditioned on BEV and 3D data tailored for autonomous driving. • The development of simple yet potent strategies to manage 3D geometric data, effectively ad- dressing the challenges of multi-camera view consistency in street view generation. • Through rigorous experiments, we demonstrate that MAGICDRIVE outperforms prior street view generation techniques, notably for the multi-dimensional controllability. Additionally, our results reveal that synthetic data delivers considerable improvements in 3D perception tasks. 1In this paper, our 3D geometry controls contain control from road maps, 3D object boxes, and camera poses. We do not consider others like the exact shape of objects or background contents. 2 Published as a conference paper at ICLR 2024 2 RELATED WORK Diffusion Models for Conditional Generation. Diffusion models (Ho et al., 2020; Song et al., 2020; Zheng et al., 2023) generate images by learning a progressive denoising process from the Gaussian noise distribution to the image distribution. These models have proven exceptional across diverse tasks, such as text-to-image synthesis (Rombach et al., 2022; Nich 23 21322 2 conference 20 2ut 2 2REFERENCES2K2XY2. X22X12Ilya29. A. 1 a2X2X2Z ar12 12DR00220 paper 2K 7 Published as paper 024 8 conference at I 2 124 DR. 20 </text> What is the correct answer to this question: How does the MagicDrive encode the in training step? Choices: (A) MagicDrive encode similar Li et al, where. And. (B) MagicDrive step MagicDrive a bounding box. (C)Drive using the and a bounding. (D) MagicDrive encode the the, and uses an MLP them into a. Format your response as follows: "The correct answer is (insert answer here)".
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D
MagicDrive encode the class labels and the corner points separately, and then uses an MLP to compress them into a vector.
Please read the following text and answer the question below. <text> Published as a conference paper at ICLR 2024 MAGICDRIVE: STREET VIEW GENERATION WITH DIVERSE 3D GEOMETRY CONTROL ABSTRACT Recent advancements in diffusion models have significantly enhanced the data synthesis with 2D control. Yet, precise 3D control in street view generation, cru- cial for 3D perception tasks, remains elusive. Specifically, utilizing Bird’s-Eye View (BEV) as the primary condition often leads to challenges in geometry control (e.g., height), affecting the representation of object shapes, occlusion patterns, and road surface elevations, all of which are essential to perception data synthesis, es- pecially for 3D object detection tasks. In this paper, we introduce MAGICDRIVE, a novel street view generation framework, offering diverse 3D geometry controls including camera poses, road maps, and 3D bounding boxes, together with textual descriptions, achieved through tailored encoding strategies. Besides, our design incorporates a cross-view attention module, ensuring consistency across multiple camera views. With MAGICDRIVE, we achieve high-fidelity street-view image & video synthesis that captures nuanced 3D geometry and various scene descrip- tions, enhancing tasks like BEV segmentation and 3D object detection. Front Front Left Front Right ... ... Rainy 🌧 Sunny ☀ BEV map Camera pose + + = 3D box Figure 1: Multi-camera street view generation from MAGICDRIVE. MAGICDRIVE can generate continuous camera views with controls from the road map, object boxes, and text (e.g., weather). 1 INTRODUCTION The high costs associated with data collection and annotation often impede the effective training of deep learning models. Fortunately, cutting-edge generative models have illustrated that synthetic data can notably boost performance across various tasks, such as object detection (Chen et al., 2023c) and semantic segmentation (Wu et al., 2023b). Yet, the prevailing methodologies are largely tailored to 2D contexts, primarily relying on 2D bounding boxes (Lin et al., 2014; Han et al., 2021) or segmentation maps (Zhou et al., 2019) as layout conditions (Chen et al., 2023c; Li et al., 2023b). In autonomous driving applications, a thorough grasp of the 3D environment is essential. This demands reliable techniques for tasks like Bird’s-Eye View (BEV) map segmentation (Zhou & Kr¨ ahenb¨ uhl, 2022; Ji et al., 2023) and 3D object detection (Chen et al., 2020; Huang et al., 2021; Liu et al., 2023a; Ge et al., 2023). A genuine 3D geometry representation is crucial for capturing intricate details from 3D annotations, such as road elevations, object heights, and their occlusion pat- ∗Equal contribution. †Corresponding authors. Project Page: https://flymin.github.io/magicdrive. 1 arXiv:2310.02601v7 [cs.CV] 3 May 2024 Published as a conference paper at ICLR 2024 (a) 3D bounding boxes show position relationships. (b) Road surface elevation guided by 3D bounding boxes. 2D boxes BEV Map No distance No occlusion No view-consistency No height Figure 2: 3D bounding boxes are crucial for street view synthesis. Two examples show that 2D boxes or BEV maps lost distance, height, and elevation. Images are generated from MAGICDRIVE. terns, as shown in Figure 2. Consequently, generating multi-camera street-view images according to 3D annotations becomes vital to boost downstream perception tasks. For street-view data synthesis, two pivotal criteria are realism and controllability. Realism requires that the quality of the synthetic data should align with that of real data; and in a given scene, views from varying camera perspectives should remain consistent with one another (Mildenhall et al., 2020). On the other hand, controllability emphasizes the precision in generating street-view images that adhere to provided conditions: the BEV map, 3D object bounding boxes, and camera poses for views. Beyond these core requirements, effective data augmentation should also grant the flexibility to tweak finer scenario attributes, such as prevailing weather conditions or the time of day. Existing solutions like BEVGen (Swerdlow et al., 2023) approach street view generation by encapsulating all semantics within BEV. Conversely, BEVControl (Yang et al., 2023a) starts by projecting 3D coordinates to image views, subsequently using 2D geometric guidance. However, both methods compromise certain geometric dimensions—height is lost in BEVGen and depth in BEVControl. The rise of diffusion models has significantly pushed the boundaries of controllable image gener- ation quality. Specifically, ControlNet (Zhang et al., 2023a) proposes a flexible framework to in- corporate 2D spatial controls based on pre-trained Text-to-Image (T2I) diffusion models (Rombach et al., 2022). However, 3D conditions are distinct from pixel-level conditions or text. The challenge of seamlessly integrating them with multi-camera view consistency in street view synthesis remains. In this paper, we introduce MAGICDRIVE, a novel framework dedicated to street-view synthesis with diverse 3D geometry controls1. For realism, we harness the power of pre-trained stable dif- fusion (Rombach et al., 2022), further fine-tuning it for street view generation. One distinctive component of our framework is the cross-view attention module. This simple yet effective com- ponent provides multi-view consistency through interactions between adjacent views. In contrast to previous methods, MAGICDRIVE proposes a separate design for objects and road map encoding to improve controllability with 3D data. More specifically, given the sequence-like, variable-length nature of 3D bounding boxes, we employ cross-attention akin to text embeddings for their encod- ing. Besides, we propose that an addictive encoder branch like ControlNet (Zhang et al., 2023a) can encode maps in BEV and is capable of view transformation. Therefore, our design achieves geometric controls without resorting to any explicit geometric transformations or imposing geomet- ric constraints on multi-camera consistency. Finally, MAGICDRIVE factors in textual descriptions, offering attribute control such as weather conditions and time of day. Our MAGICDRIVE framework, despite its simplicity, excels in generating strikingly realistic images & videos that align with road maps, 3D bounding boxes, and varied camera perspectives. Besides, the images produced can enhance the training for both 3D object detection and BEV segmentation tasks. Furthermore, MAGICDRIVE offers comprehensive geometric controls at the scene, back- ground, and foreground levels. This flexibility makes it possible to craft previously unseen street views suitable for simulation purposes. We summarize the main contributions of this work as: • The introduction of MAGICDRIVE, an innovative framework that generates multi-perspective camera views & videos conditioned on BEV and 3D data tailored for autonomous driving. • The development of simple yet potent strategies to manage 3D geometric data, effectively ad- dressing the challenges of multi-camera view consistency in street view generation. • Through rigorous experiments, we demonstrate that MAGICDRIVE outperforms prior street view generation techniques, notably for the multi-dimensional controllability. Additionally, our results reveal that synthetic data delivers considerable improvements in 3D perception tasks. 1In this paper, our 3D geometry controls contain control from road maps, 3D object boxes, and camera poses. We do not consider others like the exact shape of objects or background contents. 2 Published as a conference paper at ICLR 2024 2 RELATED WORK Diffusion Models for Conditional Generation. Diffusion models (Ho et al., 2020; Song et al., 2020; Zheng et al., 2023) generate images by learning a progressive denoising process from the Gaussian noise distribution to the image distribution. These models have proven exceptional across diverse tasks, such as text-to-image synthesis (Rombach et al., 2022; Nich 23 21322 2 conference 20 2ut 2 2REFERENCES2K2XY2. X22X12Ilya29. A. 1 a2X2X2Z ar12 12DR00220 paper 2K 7 Published as paper 024 8 conference at I 2 124 DR. 20 </text> What is the correct answer to this question: How does the MagicDrive encode the in training step? Choices: (A) MagicDrive encode similar Li et al, where. And. (B) MagicDrive step MagicDrive a bounding box. (C)Drive using the and a bounding. (D) MagicDrive encode the the, and uses an MLP them into a. Format your response as follows: "The correct answer is (insert answer here)".
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Please read the following text and answer the question below. <text> Updated 18 July 2023 F/A-18C Early Access Guide DCS [F/A-18C] 2 INTRODUCTION Thank you for your purchase of DCS: F/A-18C! DCS: F/A-18C brings to Digital Combat Simulator an iconic aircraft of modern naval aviation. This module features the most realistic PC simulation of the F/A-18C, which includes accurately simulated flight dynamics, avionics, sensors, and weapon systems. This module simulates the F/A-18C as it existed in United States Navy and Marine Corps service circa 2005. The F/A-18C is one of the most successful naval strike fighters in modern history; and has served as the backbone of U.S. Navy carrier air wings for decades, as well as serving in the air forces of several other nations ranging from Europe, to the Middle East, to the Pacific region. Known for its dual-role design, mission versatility, and of course its ability to operate from aircraft carriers at sea, the F/A-18C is also one of the most maneuverable aircraft in close-range air-to-air combat with a robust fly-by-wire control system and high angle-of-attack capabilities. When used in conjunction with the DCS: Supercarrier module, the DCS: F/A-18C gives DCS players the most authentic U.S. Naval Aviation experience available for the PC, short of strapping on a G-suit yourself and tasting the salty air first-hand. Hook up, salute, and launch yourself into naval aviation! Key features: • Detailed, fully-clickable, 6DOF cockpit along with a highly detailed external model. • APG-73 Fire Control Radar (with air-to-air and air-to-ground modes), ATFLIR and Litening II targeting pods, and Joint Helmet Mounted Cueing System (JHMCS). • Air-to-air weapons include the M61 20mm Vulcan cannon, AIM-9 Sidewinder heat-seeking missiles, AIM-7 Sparrow semi-active radar-homing missiles, and AIM-120 AMRAAM active radar-homing missiles. • A large assortment of air-to-ground munitions, including (but not limited to) AGM-88 HARM anti-radar missiles, AGM-65 IR- and laser-guided Maverick anti-armor missiles, AGM-84D Harpoon anti-ship missiles, AGM-84E/H SLAM long-range attack missiles, AGM-62 Walleye TV-guided glide bombs, AGM-154 JSOW glide bombs, JDAM inertially aided munitions, and Paveway laser-guided bombs. • DL16 datalink, providing a high degree of situational awareness and teamwork between wingmen. • ALR-67(V) radar warning receiver, ALE-47 countermeasure dispensers, and ALQ-165 ECM jamming system. • Complete integration with DCS: Supercarrier module. • Fly missions in the Black Sea region or one of the many DLC maps like the Persian Gulf, Syria, and more. • Multiplayer cooperative and head-to-head gameplay. • Feature-rich Mission and Campaign editors allow user-created content. • Huge array of land, air, and sea units to flight along and against. Sincerely, The DCS: F/A-18C Team 30 May 2018 Disclaimers The manufacturers and intellectual property right owners of the vehicles, weapons, sensors, and other systems represented within DCS World in no way endorse, sponsor or are otherwise involved in the development of DCS World and its modules. This software is for entertainment purposes only. The appearance of U.S. Department of Defense (DoD) visual information does not imply or constitute DoD endorsement. [F/A-18C] DCS EAGLE DYNAMICS 3 TABLE OF CONTENTS Introduction ........................................................................................................................................... 2 Table of Contents ................................................................................................................................... 3 Latest Changes ..................................................................................................................................... 11 DCS: WORLD FUNDAMENTALS ........................................................................................................ 13 Health Warning!.................................................................................................................................... 14 Installation and Launch ......................................................................................................................... 15 Configure Your Game ....................................................................................................................... 16 Fly a Mission .................................................................................................................................... 21 Game Problems ................................................................................................................................ 21 Useful Links ..................................................................................................................................... 21 Flight Control ........................................................................................................................................ 22 Changing Airspeed ........................................................................................................................... 23 Changing Altitude ............................................................................................................................. 23 Changing Heading ............................................................................................................................ 23 THE F/A-18C ................................................................................................................................... 25 Aircraft History ..................................................................................................................................... 26 The VFAX Programs .......................................................................................................................... 26 The YF-17 “Cobra” ........................................................................................................................... 27 Development of the F-18 .................................................................................................................. 28 F/A-18A and B Deployment ............................................................................................................... 29 F/A-18C and D Deployment ............................................................................................................... 29 Weapons & Munitions............................................................................................................................ 31 M61A1 Vulcan 20mm Cannon ............................................................................................................ 31 AIM-9 Sidewinder ............................................................................................................................. 31 AIM-120 AMRAAM ............................................................................................................................ 32 AIM-7 Sparrow ................................................................................................................................. 32 AGM-154 Joint Standoff Weapon (JSOW) ........................................................................................... 33 AGM-84 Harpoon, SLAM, and SLAM-ER .............................................................................................. 33 AGM-88 HARM ................................................................................................................................. 34 AGM-65 Maverick ............................................................................................................................. 34 AGM-62 Walleye II ........................................................................................................................... 34 Mk. 20 Rockeye and CBU-99 ............................................................................................................. 35 Paveway II Laser Guided Bomb ......................................................................................................... 35 DCS [F/A-18C] 4 Paveway III Laser Guided Bomb........................................................................................................ 35 Joint Direct Attack Munition (JDAM) ................................................................................................... 36 Mark 80-Series General-Purpose Bomb .............................................................................................. 36 Rockets ........................................................................................................................................... 37 Fuel Tanks ....................................................................................................................................... 37 AN/ASQ-228 ATFLIR ......................................................................................................................... 37 AN/AAQ-28 Litening II Targeting Pod ................................................................................................ 37 AN/AWW-13 Advanced Datalink ........................................................................................................ 37 AN/ASQ-T50 TCTS Pod ..................................................................................................................... 38 Training Bombs ................................................................................................................................ 38 Cockpit Overview .................................................................................................................................. 39 Left Instrument Panel ....................................................................................................................... 40 Center Instrument Panel ................................................................................................................... 45 Heads-Up Display (HUD) ................................................................................................................... 45 Right Instrument Panel ..................................................................................................................... 53 Left Vertical Panel ............................................................................................................................ 58 Left Console ..................................................................................................................................... 61 Right Vertical Panel .......................................................................................................................... 64 Right Console ................................................................................................................................... 67 Audio Tones ..................................................................................................................................... 71 Control Stick & Throttles........................................................................................................................ 72 Control Stick .................................................................................................................................... 72 Throttles .......................................................................................................................................... 75 Heads-Up Display (HUD) ....................................................................................................................... 79 Digital Display Indicator (DDI) & Advanced Multi-Purpose Color Display (AMPCD) Pages ........................... 81 Support (SUPT) Pages ...................................................................................................................... 81 Tactical (TAC) Pages ........................................................................................................................ 91 PROCEDURES .................................................................................................................................. 94 Cold Start ............................................................................................................................................. 95 Airfield Taxi ........................................................................................................................................ 102 Airfield Takeoff ................................................................................................................................... 103 Airfield VFR Landing ............................................................................................................................ 104 Aircraft Carrier Taxi ............................................................................................................................. 107 Aircraft Carrier Launch ........................................................................................................................ 110 Case 1 Carrier Recovery ...................................................................................................................... 111 [F/A-18C] DCS EAGLE DYNAMICS 5 NAVIGATION ................................................................................................................................. 117 Navigation .......................................................................................................................................... 118 INS Alignment ................................................................................................................................ 118 Alignment Procedure ...................................................................................................................... 119 Waypoint Navigation ........................................................................................................................... 5............................ 7) 77)............................8802 ................................................................................................ 3...............................................................................................................333...................................5..ALTH1AG2 CACenter rightnessDay dro Engine1 trailing Practice 1AC1esign2111111 fieldYNAM -lYNAMYNAMYNAMYNAMYNAM6 team © </text> What the answer According to the document, of? Choices: (A1. The. (B11.. (C There1(D. Format your response as: "The correct answer is (insert answer here)".
290
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3
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AN/APG-73 radar is thought to be the most important sensors of the F/A-18C Fighter. It can be used for searching and tracking. When in the RWS mode, the radar can record multiple targets but in STT mode, the radar will focus on only one target.
Please read the following text and answer the question below. <text> Updated 18 July 2023 F/A-18C Early Access Guide DCS [F/A-18C] 2 INTRODUCTION Thank you for your purchase of DCS: F/A-18C! DCS: F/A-18C brings to Digital Combat Simulator an iconic aircraft of modern naval aviation. This module features the most realistic PC simulation of the F/A-18C, which includes accurately simulated flight dynamics, avionics, sensors, and weapon systems. This module simulates the F/A-18C as it existed in United States Navy and Marine Corps service circa 2005. The F/A-18C is one of the most successful naval strike fighters in modern history; and has served as the backbone of U.S. Navy carrier air wings for decades, as well as serving in the air forces of several other nations ranging from Europe, to the Middle East, to the Pacific region. Known for its dual-role design, mission versatility, and of course its ability to operate from aircraft carriers at sea, the F/A-18C is also one of the most maneuverable aircraft in close-range air-to-air combat with a robust fly-by-wire control system and high angle-of-attack capabilities. When used in conjunction with the DCS: Supercarrier module, the DCS: F/A-18C gives DCS players the most authentic U.S. Naval Aviation experience available for the PC, short of strapping on a G-suit yourself and tasting the salty air first-hand. Hook up, salute, and launch yourself into naval aviation! Key features: • Detailed, fully-clickable, 6DOF cockpit along with a highly detailed external model. • APG-73 Fire Control Radar (with air-to-air and air-to-ground modes), ATFLIR and Litening II targeting pods, and Joint Helmet Mounted Cueing System (JHMCS). • Air-to-air weapons include the M61 20mm Vulcan cannon, AIM-9 Sidewinder heat-seeking missiles, AIM-7 Sparrow semi-active radar-homing missiles, and AIM-120 AMRAAM active radar-homing missiles. • A large assortment of air-to-ground munitions, including (but not limited to) AGM-88 HARM anti-radar missiles, AGM-65 IR- and laser-guided Maverick anti-armor missiles, AGM-84D Harpoon anti-ship missiles, AGM-84E/H SLAM long-range attack missiles, AGM-62 Walleye TV-guided glide bombs, AGM-154 JSOW glide bombs, JDAM inertially aided munitions, and Paveway laser-guided bombs. • DL16 datalink, providing a high degree of situational awareness and teamwork between wingmen. • ALR-67(V) radar warning receiver, ALE-47 countermeasure dispensers, and ALQ-165 ECM jamming system. • Complete integration with DCS: Supercarrier module. • Fly missions in the Black Sea region or one of the many DLC maps like the Persian Gulf, Syria, and more. • Multiplayer cooperative and head-to-head gameplay. • Feature-rich Mission and Campaign editors allow user-created content. • Huge array of land, air, and sea units to flight along and against. Sincerely, The DCS: F/A-18C Team 30 May 2018 Disclaimers The manufacturers and intellectual property right owners of the vehicles, weapons, sensors, and other systems represented within DCS World in no way endorse, sponsor or are otherwise involved in the development of DCS World and its modules. This software is for entertainment purposes only. The appearance of U.S. Department of Defense (DoD) visual information does not imply or constitute DoD endorsement. [F/A-18C] DCS EAGLE DYNAMICS 3 TABLE OF CONTENTS Introduction ........................................................................................................................................... 2 Table of Contents ................................................................................................................................... 3 Latest Changes ..................................................................................................................................... 11 DCS: WORLD FUNDAMENTALS ........................................................................................................ 13 Health Warning!.................................................................................................................................... 14 Installation and Launch ......................................................................................................................... 15 Configure Your Game ....................................................................................................................... 16 Fly a Mission .................................................................................................................................... 21 Game Problems ................................................................................................................................ 21 Useful Links ..................................................................................................................................... 21 Flight Control ........................................................................................................................................ 22 Changing Airspeed ........................................................................................................................... 23 Changing Altitude ............................................................................................................................. 23 Changing Heading ............................................................................................................................ 23 THE F/A-18C ................................................................................................................................... 25 Aircraft History ..................................................................................................................................... 26 The VFAX Programs .......................................................................................................................... 26 The YF-17 “Cobra” ........................................................................................................................... 27 Development of the F-18 .................................................................................................................. 28 F/A-18A and B Deployment ............................................................................................................... 29 F/A-18C and D Deployment ............................................................................................................... 29 Weapons & Munitions............................................................................................................................ 31 M61A1 Vulcan 20mm Cannon ............................................................................................................ 31 AIM-9 Sidewinder ............................................................................................................................. 31 AIM-120 AMRAAM ............................................................................................................................ 32 AIM-7 Sparrow ................................................................................................................................. 32 AGM-154 Joint Standoff Weapon (JSOW) ........................................................................................... 33 AGM-84 Harpoon, SLAM, and SLAM-ER .............................................................................................. 33 AGM-88 HARM ................................................................................................................................. 34 AGM-65 Maverick ............................................................................................................................. 34 AGM-62 Walleye II ........................................................................................................................... 34 Mk. 20 Rockeye and CBU-99 ............................................................................................................. 35 Paveway II Laser Guided Bomb ......................................................................................................... 35 DCS [F/A-18C] 4 Paveway III Laser Guided Bomb........................................................................................................ 35 Joint Direct Attack Munition (JDAM) ................................................................................................... 36 Mark 80-Series General-Purpose Bomb .............................................................................................. 36 Rockets ........................................................................................................................................... 37 Fuel Tanks ....................................................................................................................................... 37 AN/ASQ-228 ATFLIR ......................................................................................................................... 37 AN/AAQ-28 Litening II Targeting Pod ................................................................................................ 37 AN/AWW-13 Advanced Datalink ........................................................................................................ 37 AN/ASQ-T50 TCTS Pod ..................................................................................................................... 38 Training Bombs ................................................................................................................................ 38 Cockpit Overview .................................................................................................................................. 39 Left Instrument Panel ....................................................................................................................... 40 Center Instrument Panel ................................................................................................................... 45 Heads-Up Display (HUD) ................................................................................................................... 45 Right Instrument Panel ..................................................................................................................... 53 Left Vertical Panel ............................................................................................................................ 58 Left Console ..................................................................................................................................... 61 Right Vertical Panel .......................................................................................................................... 64 Right Console ................................................................................................................................... 67 Audio Tones ..................................................................................................................................... 71 Control Stick & Throttles........................................................................................................................ 72 Control Stick .................................................................................................................................... 72 Throttles .......................................................................................................................................... 75 Heads-Up Display (HUD) ....................................................................................................................... 79 Digital Display Indicator (DDI) & Advanced Multi-Purpose Color Display (AMPCD) Pages ........................... 81 Support (SUPT) Pages ...................................................................................................................... 81 Tactical (TAC) Pages ........................................................................................................................ 91 PROCEDURES .................................................................................................................................. 94 Cold Start ............................................................................................................................................. 95 Airfield Taxi ........................................................................................................................................ 102 Airfield Takeoff ................................................................................................................................... 103 Airfield VFR Landing ............................................................................................................................ 104 Aircraft Carrier Taxi ............................................................................................................................. 107 Aircraft Carrier Launch ........................................................................................................................ 110 Case 1 Carrier Recovery ...................................................................................................................... 111 [F/A-18C] DCS EAGLE DYNAMICS 5 NAVIGATION ................................................................................................................................. 117 Navigation .......................................................................................................................................... 118 INS Alignment ................................................................................................................................ 118 Alignment Procedure ...................................................................................................................... 119 Waypoint Navigation ........................................................................................................................... 5............................ 7) 77)............................8802 ................................................................................................ 3...............................................................................................................333...................................5..ALTH1AG2 CACenter rightnessDay dro Engine1 trailing Practice 1AC1esign2111111 fieldYNAM -lYNAMYNAMYNAMYNAMYNAM6 team © </text> What the answer According to the document, of? Choices: (A1. The. (B11.. (C There1(D. Format your response as: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> { "meta": { "name_exp": "qwen2-72b_bar_game_explicit_v1_4", "player_num": 10, "min": 0, "max": 10, "home": 5, "ratio": 0.6, "ratio_str": "60%", "mode": "explicit", "round_id": 20, "version": "v1" }, "round_records": [ { "responses": [ "go", "go", "go", "go", "go", "go", "go", "go", "go", "stay" ], "go_num": 9, "go_ratio": 0.9, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "go", "go", "go", "go", "go" ], "go_num": 10, "go_ratio": 1.0, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "stay", "go", "go", "go", "stay", "go", "stay", "stay", "go" ], "go_num": 6, "go_ratio": 0.6, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "go", "go", "go", "go", "go" ], "go_num": 10, "go_ratio": 1.0, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "go", "go", "go", "go", "go" ], "go_num": 10, "go_ratio": 1.0, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "stay", "go", "go", "go", "stay", "go", "go", "stay", "go" ], "go_num": 7, "go_ratio": 0.7, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "go", "stay" ], "go_num": 1, "go_ratio": 0.1, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "go", "go", "go", "go", "go" ], "go_num": 10, "go_ratio": 1.0, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "go", "go", "go", "go", "go" ], "go_num": 10, "go_ratio": 1.0, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "stay", "go", "go", "go", "go", "go", "stay", "go", "go" ], "go_num": 8, "go_ratio": 0.8, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "go", "go", "go", "go", "go" ], "go_num": 10, "go_ratio": 1.0, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "go", "stay" ], "go_num": 1, "go_ratio": 0.1, "winner": "go", "utility": 10 } ], "player_data": [ { "model": "Qwen/Qwen2-72B-Instruct", "id": "player_0", "prompt": [ { "role": "system", "content": "\n\nYou are participating in a game played by 10 players over 20 rounds.\n\nGame Rules:\n\n1. Every round, you and the the the the the the the prompt the the the 6\n the the the the the the the the the the the the the the the the the the the the the the the the the the the the the} </text> What is the correct answer to this question: Which players got the second most utility in the game? Choices: (A) player_1 and player_8 (B) player_0 and player_8 (C) player_8 and_9 (D)_1 and player_9 Format your response as follows: "The correct answer is (insert answer here)".
291
null
3
D
player_1 and player_9
Please read the following text and answer the question below. <text> { "meta": { "name_exp": "qwen2-72b_bar_game_explicit_v1_4", "player_num": 10, "min": 0, "max": 10, "home": 5, "ratio": 0.6, "ratio_str": "60%", "mode": "explicit", "round_id": 20, "version": "v1" }, "round_records": [ { "responses": [ "go", "go", "go", "go", "go", "go", "go", "go", "go", "stay" ], "go_num": 9, "go_ratio": 0.9, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "go", "go", "go", "go", "go" ], "go_num": 10, "go_ratio": 1.0, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "stay", "go", "go", "go", "stay", "go", "stay", "stay", "go" ], "go_num": 6, "go_ratio": 0.6, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "go", "go", "go", "go", "go" ], "go_num": 10, "go_ratio": 1.0, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "go", "go", "go", "go", "go" ], "go_num": 10, "go_ratio": 1.0, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "stay", "go", "go", "go", "stay", "go", "go", "stay", "go" ], "go_num": 7, "go_ratio": 0.7, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "go", "stay" ], "go_num": 1, "go_ratio": 0.1, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "go", "go", "go", "go", "go" ], "go_num": 10, "go_ratio": 1.0, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "go", "go", "go", "go", "go" ], "go_num": 10, "go_ratio": 1.0, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "stay", "go", "go", "go", "go", "go", "stay", "go", "go" ], "go_num": 8, "go_ratio": 0.8, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "go", "go", "go", "go", "go" ], "go_num": 10, "go_ratio": 1.0, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay" ], "go_num": 0, "go_ratio": 0.0, "winner": "go", "utility": 10 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "stay", "go", "stay" ], "go_num": 1, "go_ratio": 0.1, "winner": "go", "utility": 10 } ], "player_data": [ { "model": "Qwen/Qwen2-72B-Instruct", "id": "player_0", "prompt": [ { "role": "system", "content": "\n\nYou are participating in a game played by 10 players over 20 rounds.\n\nGame Rules:\n\n1. Every round, you and the the the the the the the prompt the the the 6\n the the the the the the the the the the the the the the the the the the the the the the the the the the the the the} </text> What is the correct answer to this question: Which players got the second most utility in the game? Choices: (A) player_1 and player_8 (B) player_0 and player_8 (C) player_8 and_9 (D)_1 and player_9 Format your response as follows: "The correct answer is (insert answer here)".
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Please read the following text and answer the question below. <text> International Treaties in the Chinese Domestic Legal System* XUE Hanqin and JIN Qian** Abstract China has made considerable progress in the past thirty years with respect to implementation of international obligations in its domestic legal system. Although China’s Constitution and its basic laws do not set forth a general pro- vision on the status of treaties in the domestic legal system, substantive treaty obligations undertaken by China, to a large extent, have been incorporated into special national laws, exerting a direct impact on the economic and social activities of the country. This article examines various forms and modalities by which China implements its international obligations at domestic level. There have been an increasing number of cases where courts apply treaty pro- visions to give private parties additional legal protection. In the civil and com- mercial areas, international treaties apply primarily to cases with foreign elements, while in the criminal law area, China has prescribed almost all of the international crimes as criminal offences under its national criminal law.  This study focuses on the main legal system of China and does not cover the legal practice of treaty application in Hong Kong, Macao and Taiwan. Helpful sources regarding this topic include: Chinese legislation: www.lawinfochina.com/index.asp; Chinese legislation in English: www.chinalaw.gov.cn/indexEN.jsp; judicial statements on the interpretation and application of law of the Supreme People’s Court: www.chinalaw.gov.cn/jsp/contentpub/browser/ moreinfo.jsp?page=2&id=co5022565624; ZHU Xiaoqing and HUANG Lie (eds), Relations between International Treaties and Domestic Law, Papers of the Chinese–German Seminar on Relations between International Treaties and Domestic Law (World Knowledge Press, Beijing, 1st edn., 2000), ISBN 7-5012-1423-9.  XUE Hanqin, Ambassador of the People’s Republic of China to ASEAN, Legal Counsel of the Foreign Ministry, member of the International Law Commission (email: hqxue@yahoo.com). JIN Qian, Division Chief of the Treaty and Law Department of the Ministry of Foreign Affairs of China. The authors would like to express their deep appreciation to Mr CAO Jianming, for- merly Vice-President of the Supreme People’s Court of China and to the Treaty Division of the Treaty and Law Department of the Ministry of Foreign Affairs of China for their kind support in the preparation of this article. The authors are also grateful to Mr SHEN Qinmin for his research assistance and Professor Sienho Yee for reading the manuscript and providing helpful comments. The authors, however, take full responsibility for any error that may be found in this article. The views expressed herein do not represent the position of the institutions with which the authors are associated. This article was completed at the end of 2007. # The Author 2009. Published by Oxford University Press. All rights reserved. Advance Access publication 29 April 2009 ....................................................................................................................................... ................................................................................................................................................................... Chinese Journal of International Law (2009), Vol. 8, No. 2, 299–322 doi:10.1093/chinesejil/jmp007 oaded from https://academic.oup.com/chinesejil/article/8/2/299/310810 by Center of Books and information, School of Economic & Management, Tsinghua University user on 19 September China implements its international obligations in good faith with the view that effective implementation of treaty obligations will not only serve well its own development, but also promote peace and cooperation among States. I. Overview of the current status of treaties in the Chinese domestic legal system A. General introduction 1. Ever since the founding of the People’s Republic of China in 1949, implementation of its international obligations in good faith has been not only one of China’s basic pol- icies of foreign affairs, but also a fundamental principle of Chinese law. All international treaties shall be concluded in accordance with the provisions of the Law of the People’s Republic of China on the Procedure of the Conclusion of Treaties, promulgated in 1990 (hereinafter, “the Treaty Procedure Law”)1 and fulfil necessary domestic legal pro- cedures. Therefore, subject to the nature of the relevant treaty and the mandate of the contracting governmental department, international treaties to which China is a party in principle have binding force in domestic law, except for those provisions to which China has made reservations. Given the extensive variety of treaties both in form and in subject, however, domestic implementation of treaties is a rather complicated issue. Under the Treaty Procedure Law, treaties can be concluded at three levels: between States; between governments; and between governmental departments. As is obvious, treaties vary in terms of their status and legal effect on the domestic legal system; not all treaties constitute part of domestic law. 2. In international law, some treaties directly provide for rights and obligations of the contracting States, whereas others lay down rights and obligations for individuals and legal persons. Although on the international plane the State assumes international responsibility for meeting its treaty obligations, at the domestic level, how to implement such obligations and realize the rights and obligations of individuals and legal persons depends on the legal system of each contracting State and the way in which it handles the relations between international law and domestic law. China is a unitary State. At present, the Chinese Constitution and basic laws2 do not contain any provision on the legal status of international treaties and their hierarchy in the domestic legal system. Strictly speaking, international treaties, even after ratification, accession or approval, do not automatically become part of national law and consequently do not automatically have domestic legal effect. 1 Before the adoption of the Treaty Procedure Law, treaty practice had not been specifically regulated by law. The treaty-making power, however, had always been strictly limited under the general pro- visions of the Constitution. Great importance was always attached to treaty obligations in the dom- estic legal system. 2 The term “basic laws” in this context refers to the laws prescribed under Chapter II of the Legis- lation Law of the People’s Republic of China. 300 Chinese JIL (2009) oaded from https://academic.oup.com/chinesejil/article/8/2/299/310810 by Center of Books and information, School of Economic & Management, Tsinghua University user on 19 September B. The legal status of treaties in China’s domestic law 3. According to the provisions of the Chinese Constitution and the Treaty Procedure Law, the Standing Committee of the National People’s Congress (hereinafter “the NPC”) shall decide on the ratification and denunciation of treaties and important agree- ments concluded with foreign States. Under Article 7 of the Treaty Procedure Law, the phrase “treaties and important agreements” includes: friendship and cooperation treaties, peace treaties and other treaties of a political nature; treaties and agreements on territories and the delimitation of boundaries; treaties and agreements on judicial assistance and extradition; and treaties and agreements that have provisions inconsistent with national laws. The State Council has the power to conclude treaties and agreements with foreign States.3 Procedurally, negotiation and conclusion of international treaties with foreign States should be approved by the State Council, or submitted to it for the record. In any case where amendment or revision to domestic laws is required for a treaty purpose, the domestic legal process for ratifying or approving the treaty should be the same as the legal procedure for the relevant domestic legislation. 4. Although the Constitution does not specifically define the relationship between the treaty-making power and the legislative power, the relevant provisions of the Constitution and the Treaty Procedure Law have established specific statutory limits on the treaty-making power, both procedurally and substantively. In other words, the nature and the subject of a treaty determine which State organ is competent to conclude the treaty and what domestic legal procedure should be followed. Govern- mental departments have no power to conclude treaties with foreign governments beyond their competence and the scope of their functions, unless specifically author- ized or approved by the State Council or the competent departments. The internal legal procedure for the conclusion of treaties determines the status and effects of trea- ties in domestic law. Without proper authorization, governmental departments cannot conclude treaties on behalf of the State with foreign States. Since treaty negotiations must be conducted in accordance with the Treaty Procedure Law and follow the appropriate legal procedure from inception to conclusion, the treaty-making power is strictly delimited by law. 5. The Legislation Law of the People’s Republic of China, enacted in 2000 (herein- after, “the Legislation Law”), establishes the hierarchy of Chinese domestic law. The Constitution ranks the highest, followed in order by laws, administrative regulations, local regulations and so on. The Legislation Law also includes provisions governing the legislative power and procedures of the legislative bodies, administrative organs and agencies at different levels.9 Legal</text> What is the correct answer to this question: Only Based on this paper, please indicate under what circumstances: Choices: (A. (B. (C. (D). Format your response as follows: "The correct answer is (insert answer here)".
292
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When stipulated within the Chinese legal system that treaties can be applied.
Please read the following text and answer the question below. <text> International Treaties in the Chinese Domestic Legal System* XUE Hanqin and JIN Qian** Abstract China has made considerable progress in the past thirty years with respect to implementation of international obligations in its domestic legal system. Although China’s Constitution and its basic laws do not set forth a general pro- vision on the status of treaties in the domestic legal system, substantive treaty obligations undertaken by China, to a large extent, have been incorporated into special national laws, exerting a direct impact on the economic and social activities of the country. This article examines various forms and modalities by which China implements its international obligations at domestic level. There have been an increasing number of cases where courts apply treaty pro- visions to give private parties additional legal protection. In the civil and com- mercial areas, international treaties apply primarily to cases with foreign elements, while in the criminal law area, China has prescribed almost all of the international crimes as criminal offences under its national criminal law.  This study focuses on the main legal system of China and does not cover the legal practice of treaty application in Hong Kong, Macao and Taiwan. Helpful sources regarding this topic include: Chinese legislation: www.lawinfochina.com/index.asp; Chinese legislation in English: www.chinalaw.gov.cn/indexEN.jsp; judicial statements on the interpretation and application of law of the Supreme People’s Court: www.chinalaw.gov.cn/jsp/contentpub/browser/ moreinfo.jsp?page=2&id=co5022565624; ZHU Xiaoqing and HUANG Lie (eds), Relations between International Treaties and Domestic Law, Papers of the Chinese–German Seminar on Relations between International Treaties and Domestic Law (World Knowledge Press, Beijing, 1st edn., 2000), ISBN 7-5012-1423-9.  XUE Hanqin, Ambassador of the People’s Republic of China to ASEAN, Legal Counsel of the Foreign Ministry, member of the International Law Commission (email: hqxue@yahoo.com). JIN Qian, Division Chief of the Treaty and Law Department of the Ministry of Foreign Affairs of China. The authors would like to express their deep appreciation to Mr CAO Jianming, for- merly Vice-President of the Supreme People’s Court of China and to the Treaty Division of the Treaty and Law Department of the Ministry of Foreign Affairs of China for their kind support in the preparation of this article. The authors are also grateful to Mr SHEN Qinmin for his research assistance and Professor Sienho Yee for reading the manuscript and providing helpful comments. The authors, however, take full responsibility for any error that may be found in this article. The views expressed herein do not represent the position of the institutions with which the authors are associated. This article was completed at the end of 2007. # The Author 2009. Published by Oxford University Press. All rights reserved. Advance Access publication 29 April 2009 ....................................................................................................................................... ................................................................................................................................................................... Chinese Journal of International Law (2009), Vol. 8, No. 2, 299–322 doi:10.1093/chinesejil/jmp007 oaded from https://academic.oup.com/chinesejil/article/8/2/299/310810 by Center of Books and information, School of Economic & Management, Tsinghua University user on 19 September China implements its international obligations in good faith with the view that effective implementation of treaty obligations will not only serve well its own development, but also promote peace and cooperation among States. I. Overview of the current status of treaties in the Chinese domestic legal system A. General introduction 1. Ever since the founding of the People’s Republic of China in 1949, implementation of its international obligations in good faith has been not only one of China’s basic pol- icies of foreign affairs, but also a fundamental principle of Chinese law. All international treaties shall be concluded in accordance with the provisions of the Law of the People’s Republic of China on the Procedure of the Conclusion of Treaties, promulgated in 1990 (hereinafter, “the Treaty Procedure Law”)1 and fulfil necessary domestic legal pro- cedures. Therefore, subject to the nature of the relevant treaty and the mandate of the contracting governmental department, international treaties to which China is a party in principle have binding force in domestic law, except for those provisions to which China has made reservations. Given the extensive variety of treaties both in form and in subject, however, domestic implementation of treaties is a rather complicated issue. Under the Treaty Procedure Law, treaties can be concluded at three levels: between States; between governments; and between governmental departments. As is obvious, treaties vary in terms of their status and legal effect on the domestic legal system; not all treaties constitute part of domestic law. 2. In international law, some treaties directly provide for rights and obligations of the contracting States, whereas others lay down rights and obligations for individuals and legal persons. Although on the international plane the State assumes international responsibility for meeting its treaty obligations, at the domestic level, how to implement such obligations and realize the rights and obligations of individuals and legal persons depends on the legal system of each contracting State and the way in which it handles the relations between international law and domestic law. China is a unitary State. At present, the Chinese Constitution and basic laws2 do not contain any provision on the legal status of international treaties and their hierarchy in the domestic legal system. Strictly speaking, international treaties, even after ratification, accession or approval, do not automatically become part of national law and consequently do not automatically have domestic legal effect. 1 Before the adoption of the Treaty Procedure Law, treaty practice had not been specifically regulated by law. The treaty-making power, however, had always been strictly limited under the general pro- visions of the Constitution. Great importance was always attached to treaty obligations in the dom- estic legal system. 2 The term “basic laws” in this context refers to the laws prescribed under Chapter II of the Legis- lation Law of the People’s Republic of China. 300 Chinese JIL (2009) oaded from https://academic.oup.com/chinesejil/article/8/2/299/310810 by Center of Books and information, School of Economic & Management, Tsinghua University user on 19 September B. The legal status of treaties in China’s domestic law 3. According to the provisions of the Chinese Constitution and the Treaty Procedure Law, the Standing Committee of the National People’s Congress (hereinafter “the NPC”) shall decide on the ratification and denunciation of treaties and important agree- ments concluded with foreign States. Under Article 7 of the Treaty Procedure Law, the phrase “treaties and important agreements” includes: friendship and cooperation treaties, peace treaties and other treaties of a political nature; treaties and agreements on territories and the delimitation of boundaries; treaties and agreements on judicial assistance and extradition; and treaties and agreements that have provisions inconsistent with national laws. The State Council has the power to conclude treaties and agreements with foreign States.3 Procedurally, negotiation and conclusion of international treaties with foreign States should be approved by the State Council, or submitted to it for the record. In any case where amendment or revision to domestic laws is required for a treaty purpose, the domestic legal process for ratifying or approving the treaty should be the same as the legal procedure for the relevant domestic legislation. 4. Although the Constitution does not specifically define the relationship between the treaty-making power and the legislative power, the relevant provisions of the Constitution and the Treaty Procedure Law have established specific statutory limits on the treaty-making power, both procedurally and substantively. In other words, the nature and the subject of a treaty determine which State organ is competent to conclude the treaty and what domestic legal procedure should be followed. Govern- mental departments have no power to conclude treaties with foreign governments beyond their competence and the scope of their functions, unless specifically author- ized or approved by the State Council or the competent departments. The internal legal procedure for the conclusion of treaties determines the status and effects of trea- ties in domestic law. Without proper authorization, governmental departments cannot conclude treaties on behalf of the State with foreign States. Since treaty negotiations must be conducted in accordance with the Treaty Procedure Law and follow the appropriate legal procedure from inception to conclusion, the treaty-making power is strictly delimited by law. 5. The Legislation Law of the People’s Republic of China, enacted in 2000 (herein- after, “the Legislation Law”), establishes the hierarchy of Chinese domestic law. The Constitution ranks the highest, followed in order by laws, administrative regulations, local regulations and so on. The Legislation Law also includes provisions governing the legislative power and procedures of the legislative bodies, administrative organs and agencies at different levels.9 Legal</text> What is the correct answer to this question: Only Based on this paper, please indicate under what circumstances: Choices: (A. (B. (C. (D). Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> Fellow Deputies, On behalf of the People’s Government of Beijing Municipality, I will now report to you on the work of the government for your deliberation and approval. I also invite comments from members of the Beijing Municipal Committee of the Chinese People’s Political Consultative Conference (CPPCC). I. Review of Work During 2023 The year 2023 was the first to see the implementation of the guiding principles of the 20th CPC National Congress on all fronts and a year for economic recovery following three years of COVID-19 control. During 2023, General Secretary Xi Jinping visited the people affected by the July flash flood in Mentougou District and gave instructions on post-disaster reconstruction. He presided over the Meeting on Promoting the Coordinated Development of the Beijing-Tianjin-Hebei Region and made important observations. Additionally, he delivered a video message at the China International Fair for Trade in Services (CIFTIS) and sent congratulatory messages to the Zhongguancun Forum and the Beijing Culture Forum. His instructions and comments have provided a clear direction for the development of Beijing, especially in its role as China’s capital in the new era, and have established the fundamental principles that must be respected. His guidance has greatly motivated all of us in Beijing, creating a resolute force propelling us forward on this new journey and empowering us to achieve even greater success in the new era. Over the past year, we have been working under the strong leadership of the CPC Central Committee with Comrade Xi Jinping at its core, and the direct leadership of the CPC Beijing Municipal Committee. We have also received support and supervision from the Beijing Municipal People’s Congress and its Standing Committee. Guided by Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era, we have based all our actions on the guiding principles established at the 20th CPC National Congress and the Second Plenary Session of the 20th CPC Central Committee. In line with General Secretary Xi Jinping’s instructions on Beijing’s development, we have thoroughly implemented the CPC Central Committee’s decisions and plans. With a focus on strengthening Beijing’s position as the “four centers” and improving our ability to deliver “four services”, we have incorporated the Five Key Initiatives into the new development dynamic and ensured both development and security. We have worked hard to boost confidence, foster innovation, optimize functions, and improve coordination to provide our citizens with better governance and a higher quality of life. These efforts have led to a sound economic recovery and social stability in spite of the multiple challenges we faced. We have made further progress in the city’s endeavors on all fronts and fulfilled the objectives outlined at the first session of the 16th Municipal People’s Congress. In 2023, the city’s Gross Regional Product (GRP) grew by 5.2% from the previous year to around 4.4 trillion yuan. General public budget revenue increased by 8.2%, exceeding 600 billion yuan. Surveyed urban unemployment rate was 4.4% and overall consumer prices remained stable. Personal incomes grew in step with economic growth. Per capita GRP and labor productivity measured by output per worker were the highest among provincial-level jurisdictions in China, while energy and water consumption per 10,000 yuan of GRP were the lowest. In 2023, we accomplished the following tasks. First, leveraging Beijing’s strategic status as the capital of China, we achieved more substantive progress in the coordinated development of Beijing-Tianjin-Hebei Region. We reinforced Beijing’s role as the national capital, upholding the principle that the authority of capital planning lies with the Party Central Leadership. We refined our work mechanism for the Capital Planning and Development Commission and accelerated the development of the capital’s planning system. We rectified problems in planning and natural resources, and ensured the strict enforcement of the plans. We launched the new three-year action plan of the Development Control Plan for the Core Zone Serving Capital Functions and improved the urban environment in key areas to support the functions of the central authorities. We strengthened Beijing’s role as the national center for international exchanges. The Beijing Yanqi Lake International Conference Resort was upgraded and expanded. Construction of the Fourth Embassy Area and other planned projects progressed in an orderly manner. The number of international organizations opting to establish and register their offices in Beijing increased to 115. The work mechanism for providing services for major state events was improved, as exemplified by our provision of quality services during the third Belt and Road Forum for International Cooperation. We continued the special program of upgrading urban management. We demolished 23.15 million square meters of illegal structures and vacated 2,282 hectares of land. We launched a dedicated program and a five-year work plan aimed at enhancing the second greenbelt area by minimizing the amount of land used for construction purposes. Land used for urban and rural construction dropped by around eight square kilometers. Improvements were made to the environment of 183 spaces under overpasses and more than 10,000 street furniture items. We removed 900 kilometers of road guardrails and lane dividers of all kinds and carried out precision environmental improvement for 1,730 backstreets and alleys. A total of 183 run-down residential compounds were upgraded. The renovation of old and dilapidated buildings and clearance of sub-standard housing on a total scale of 204,000 square meters were completed. We vigorously pursued high-quality development of the Beijing Municipal Administrative Center (BMC). Construction of Phase II of the BMC administrative office area was completed, and the second group of municipal-level government bodies started to move in. The Beijing Performing Arts Centre, the Beijing Library, and the Grand Canal Museum of Beijing entered service. The planning of the East Sixth Ring Road High Line Park was well underway. A national certified emissions reduction trading center obtained approval for launch in Beijing. New progress was made in the integrated development of Tongzhou District and its three neighboring counties in Hebei Province. We stepped up efforts to pursue coordinated development of the Beijing-Tianjin-Hebei region. We established a collaborative working mechanism among our three authorities and drafted a three-year action plan for deeper integration of the region. The Beijing-Xiong’an Expressway was open to traffic, and the intercity railway linking Tianjin with Beijing Daxing International Airport was put into service. In the Xiong’an New Area, a sub-park of Zhongguancun Science Park was opened, and the contractual value of technology transfers from Beijing to Tianjin and Hebei reached 74.87 billion yuan, representing a growth of 110%. We provided support for the opening and operation of the “Three Schools and One Hospital” turn-key projects in the Xiong’an New Area, and witnessed increased integration and sharing of public services across the three locations. Second, we harnessed the power of technological innovation to cultivate a stronger driving force for high-quality development. We stepped up the pace of building Beijing into an international innovation center. Emphasis was placed on developing and attracting top-tier scientists, especially among the young generation. Action plans were rolled out to secure the city’s leading position in basic research and achieve breakthroughs in core technologies in key fields. We helped to ensure that Beijing-based national laboratories operate at high standards, and supported new R&D institutes in their organized research endeavors. Business-led collaboration that bridges industries, universities, and research institutes was promoted. We boosted the development of the “three science cities and one demonstration area”. In Zhongguancun Science City, ground-breaking technologies were developed at a faster pace. Newly piloted reform measures were extended to all parts of the Zhongguancun National Demonstration Zone. The launch of an experimental reform area dedicated to funding innovation was approved. The total revenues of large-scale businesses in Zhongguancun surged over 30%. Huairou Science City intensified efforts to develop the Comprehensive National Science Center, with 16 facilities and platforms in active use for research. Beijing Future Science Park strengthened collaboration with central state-owned enterprises and local universities. A number of projects, including a research hospital, were put into operation. The Demonstration Area for Innovation-based Industrial Clusters commercialized more than 270 research outcomes from the three science cities. We bolstered our strengths in high-end, precision and advanced technology sectors. Over 30 support policies were implemented for niche sectors such as artificial general intelligence (AGI) and humanoid robotics. In addition, we rolled out another four government funds dedicated to these high-tech sectors. Our efforts to grow integrated circuit businesses across the entire value chain yielded solid progress. A number of innovative medicines and medical devices obtained approval for market release. Xiaomi’s new fully-automated smartphone factory and Li Auto’s flagship plant started production ahead of schedule. We dedicated meticulous efforts to position Beijing as a global pacesetter in the digital economy. Beijing led China in launching world-leading blockchain infrastructure. A total of 30,000 5G base stations were added. Generative AI and large language model products approved for public use in Beijing accounted for nearly half of the national total. The Jingtong, Jingban and Jingzhi mobile terminals, as part of Beijing’s smart city endeavors, were upgraded and widely adopted. The High-Level Autonomous Driving Demonstration Zone achieved seamless and integrated operation over an area of 160 square kilometers. We initiated China’s first pilot zone for developing basic data systems. The2-d0注： ion101 </text> What is the correct answer to this question: Which of the following is true about the? Choices: (A). (B). (C). (D). Format your response as follows: "The correct answer is (insert answer here)".
293
null
0
A
The Beijing Municipal Government will focus on working in eleven primary areas, including economy, technology, infrastructure, cluture, military and so on.
Please read the following text and answer the question below. <text> Fellow Deputies, On behalf of the People’s Government of Beijing Municipality, I will now report to you on the work of the government for your deliberation and approval. I also invite comments from members of the Beijing Municipal Committee of the Chinese People’s Political Consultative Conference (CPPCC). I. Review of Work During 2023 The year 2023 was the first to see the implementation of the guiding principles of the 20th CPC National Congress on all fronts and a year for economic recovery following three years of COVID-19 control. During 2023, General Secretary Xi Jinping visited the people affected by the July flash flood in Mentougou District and gave instructions on post-disaster reconstruction. He presided over the Meeting on Promoting the Coordinated Development of the Beijing-Tianjin-Hebei Region and made important observations. Additionally, he delivered a video message at the China International Fair for Trade in Services (CIFTIS) and sent congratulatory messages to the Zhongguancun Forum and the Beijing Culture Forum. His instructions and comments have provided a clear direction for the development of Beijing, especially in its role as China’s capital in the new era, and have established the fundamental principles that must be respected. His guidance has greatly motivated all of us in Beijing, creating a resolute force propelling us forward on this new journey and empowering us to achieve even greater success in the new era. Over the past year, we have been working under the strong leadership of the CPC Central Committee with Comrade Xi Jinping at its core, and the direct leadership of the CPC Beijing Municipal Committee. We have also received support and supervision from the Beijing Municipal People’s Congress and its Standing Committee. Guided by Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era, we have based all our actions on the guiding principles established at the 20th CPC National Congress and the Second Plenary Session of the 20th CPC Central Committee. In line with General Secretary Xi Jinping’s instructions on Beijing’s development, we have thoroughly implemented the CPC Central Committee’s decisions and plans. With a focus on strengthening Beijing’s position as the “four centers” and improving our ability to deliver “four services”, we have incorporated the Five Key Initiatives into the new development dynamic and ensured both development and security. We have worked hard to boost confidence, foster innovation, optimize functions, and improve coordination to provide our citizens with better governance and a higher quality of life. These efforts have led to a sound economic recovery and social stability in spite of the multiple challenges we faced. We have made further progress in the city’s endeavors on all fronts and fulfilled the objectives outlined at the first session of the 16th Municipal People’s Congress. In 2023, the city’s Gross Regional Product (GRP) grew by 5.2% from the previous year to around 4.4 trillion yuan. General public budget revenue increased by 8.2%, exceeding 600 billion yuan. Surveyed urban unemployment rate was 4.4% and overall consumer prices remained stable. Personal incomes grew in step with economic growth. Per capita GRP and labor productivity measured by output per worker were the highest among provincial-level jurisdictions in China, while energy and water consumption per 10,000 yuan of GRP were the lowest. In 2023, we accomplished the following tasks. First, leveraging Beijing’s strategic status as the capital of China, we achieved more substantive progress in the coordinated development of Beijing-Tianjin-Hebei Region. We reinforced Beijing’s role as the national capital, upholding the principle that the authority of capital planning lies with the Party Central Leadership. We refined our work mechanism for the Capital Planning and Development Commission and accelerated the development of the capital’s planning system. We rectified problems in planning and natural resources, and ensured the strict enforcement of the plans. We launched the new three-year action plan of the Development Control Plan for the Core Zone Serving Capital Functions and improved the urban environment in key areas to support the functions of the central authorities. We strengthened Beijing’s role as the national center for international exchanges. The Beijing Yanqi Lake International Conference Resort was upgraded and expanded. Construction of the Fourth Embassy Area and other planned projects progressed in an orderly manner. The number of international organizations opting to establish and register their offices in Beijing increased to 115. The work mechanism for providing services for major state events was improved, as exemplified by our provision of quality services during the third Belt and Road Forum for International Cooperation. We continued the special program of upgrading urban management. We demolished 23.15 million square meters of illegal structures and vacated 2,282 hectares of land. We launched a dedicated program and a five-year work plan aimed at enhancing the second greenbelt area by minimizing the amount of land used for construction purposes. Land used for urban and rural construction dropped by around eight square kilometers. Improvements were made to the environment of 183 spaces under overpasses and more than 10,000 street furniture items. We removed 900 kilometers of road guardrails and lane dividers of all kinds and carried out precision environmental improvement for 1,730 backstreets and alleys. A total of 183 run-down residential compounds were upgraded. The renovation of old and dilapidated buildings and clearance of sub-standard housing on a total scale of 204,000 square meters were completed. We vigorously pursued high-quality development of the Beijing Municipal Administrative Center (BMC). Construction of Phase II of the BMC administrative office area was completed, and the second group of municipal-level government bodies started to move in. The Beijing Performing Arts Centre, the Beijing Library, and the Grand Canal Museum of Beijing entered service. The planning of the East Sixth Ring Road High Line Park was well underway. A national certified emissions reduction trading center obtained approval for launch in Beijing. New progress was made in the integrated development of Tongzhou District and its three neighboring counties in Hebei Province. We stepped up efforts to pursue coordinated development of the Beijing-Tianjin-Hebei region. We established a collaborative working mechanism among our three authorities and drafted a three-year action plan for deeper integration of the region. The Beijing-Xiong’an Expressway was open to traffic, and the intercity railway linking Tianjin with Beijing Daxing International Airport was put into service. In the Xiong’an New Area, a sub-park of Zhongguancun Science Park was opened, and the contractual value of technology transfers from Beijing to Tianjin and Hebei reached 74.87 billion yuan, representing a growth of 110%. We provided support for the opening and operation of the “Three Schools and One Hospital” turn-key projects in the Xiong’an New Area, and witnessed increased integration and sharing of public services across the three locations. Second, we harnessed the power of technological innovation to cultivate a stronger driving force for high-quality development. We stepped up the pace of building Beijing into an international innovation center. Emphasis was placed on developing and attracting top-tier scientists, especially among the young generation. Action plans were rolled out to secure the city’s leading position in basic research and achieve breakthroughs in core technologies in key fields. We helped to ensure that Beijing-based national laboratories operate at high standards, and supported new R&D institutes in their organized research endeavors. Business-led collaboration that bridges industries, universities, and research institutes was promoted. We boosted the development of the “three science cities and one demonstration area”. In Zhongguancun Science City, ground-breaking technologies were developed at a faster pace. Newly piloted reform measures were extended to all parts of the Zhongguancun National Demonstration Zone. The launch of an experimental reform area dedicated to funding innovation was approved. The total revenues of large-scale businesses in Zhongguancun surged over 30%. Huairou Science City intensified efforts to develop the Comprehensive National Science Center, with 16 facilities and platforms in active use for research. Beijing Future Science Park strengthened collaboration with central state-owned enterprises and local universities. A number of projects, including a research hospital, were put into operation. The Demonstration Area for Innovation-based Industrial Clusters commercialized more than 270 research outcomes from the three science cities. We bolstered our strengths in high-end, precision and advanced technology sectors. Over 30 support policies were implemented for niche sectors such as artificial general intelligence (AGI) and humanoid robotics. In addition, we rolled out another four government funds dedicated to these high-tech sectors. Our efforts to grow integrated circuit businesses across the entire value chain yielded solid progress. A number of innovative medicines and medical devices obtained approval for market release. Xiaomi’s new fully-automated smartphone factory and Li Auto’s flagship plant started production ahead of schedule. We dedicated meticulous efforts to position Beijing as a global pacesetter in the digital economy. Beijing led China in launching world-leading blockchain infrastructure. A total of 30,000 5G base stations were added. Generative AI and large language model products approved for public use in Beijing accounted for nearly half of the national total. The Jingtong, Jingban and Jingzhi mobile terminals, as part of Beijing’s smart city endeavors, were upgraded and widely adopted. The High-Level Autonomous Driving Demonstration Zone achieved seamless and integrated operation over an area of 160 square kilometers. We initiated China’s first pilot zone for developing basic data systems. The2-d0注： ion101 </text> What is the correct answer to this question: Which of the following is true about the? Choices: (A). (B). (C). (D). Format your response as follows: "The correct answer is (insert answer here)".
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Please read the following text and answer the question below. <text> a a Institute of 4D-Technologies, University of Applied Sciences Northwestern Switzerland FHNW, Switzerland b Esri R&D Center Zürich, Switzerland a r t i c l e i n f o Article history: Received 13 April 2017 Revised 11 October 2017 Accepted 16 October 2017 Available online 16 November 2017 Keywords: Real-time visualization Snow approximation GIS GPGPU Game engine a b s t r a c t Various terrain visualization techniques based on geographic information system (GIS) data already ex- ist. One major drawback of existing visualizations is that they do not capture seasonal variations well. Besides vegetation variations, in colder areas this particularly also applies to snow cover. In this paper, we propose a real-time multi-scale snow cover approximation and visualization for large terrains. The computation runs on a large grid, calculates the snow/water equivalent based on precipitation data from a GIS and snowmelt based on a physically-based solar radiation calculation combined with a degree-day snowmelt approach using level of detail (LOD). The snow visualization is divided into two parts: Zero thickness snow cover textures are generated for distant views. For close up views the terrain’s height field is modified using displacement maps and tessellation to produce thick snow covers. The GPU-based data-parallel computation and the visualization run on the GPU in real-time on a modern desktop com- puter. The implementation is tested using a real area in the Swiss Alps, with a size of 14.16 by 12.88 km, a grid resolution of 222 × 206, and a time step of 1 h. We compare the rendered results spanning several months with a time series of photographs from webcams for visual accuracy. © 2017 Elsevier Ltd. All rights reserved. 1. Introduction Visualizations of elevation data from geographic information systems (GIS) already exist with sophisticated techniques [1–3] . The most common way to enhance realism of such renderings is to project aerial photography onto the digital elevation model (DEM). As previously pointed out by Premoz ˘ e [4] several problems arise from this approach: For example, the orthoimage may still con- tain shadows which leads to visual artifacts if visualizations for different times of the day are created. Also, the visualizations do not capture seasonal variations and remain static. If a season spe- cific rendering is desired, the user needs to adapt the landscape by hand. In colder climates, snow drastically changes the appear- ance of landscapes during winter. Premoz ˘ e solves this by simulat- ing snow cover and then rendering it over the original aerial im- agery. His method aims at distant views and produces zero thick- ness snow textures for static images rendered by a ray-tracer and does not run in real-time. Other snow visualizations and simula-  This article was recommended for publication by Bedrich Benes. ∗Corresponding author at: Institute of 4D-Technologies, University of Applied Sci- ences Northwestern Switzerland FHNW Switzerland. E-mail addresses: BNeukom@Esri.com (B. Neukom), SArisona@Esri.com (S. Müller Arisona), simon.schubiger@fhnw.ch (S. Schubiger). tions exist [4–6] but they are either not suitable for large terrains or do not run in real-time. In this paper we build upon Premoz ˘ e’s work and propose a method to simulate and visualize snow cover for large terrains in real-time with different level of details. Our goal is to create a GIS-based snow cover approximation, which uses generally avail- able input data such as high-resolution height maps, aerial imagery and temperature/precipitation time series, does not require man- ual intervention, runs at interactive framerates and still produces physically plausible as well as visually pleasing renderings. To the best of our knowledge, this is the first paper that realizes real-time multi-scale snow cover computation. To achieve our goals, we compute snow accumulation by as- suming precipitation below a certain temperature threshold to be snowfall. Our method uses different levels of details (LOD) for im- proved performance and produces thick snow covers for close-up views and zero thickness textures for distant views. The thick snow cover is generated by displacing the landscape according to the amount of snow generated from the computation. After the accu- mulation, the snow is redistributed according to the relationship described by Blöschl et al. [16] to account for snow depletion based on slope and wind. To compute snowmelt, a degree-day approxi- mation similar to the one used by Premoz ˘ e et al. [4] is run on the GPU. The snowmelt simulation calculates the solar radiation https://doi.org/10.1016/j.cag.2017.10.003 0097-8493/© 2017 Elsevier Ltd. All rights reserved. B. Neukom et al. / Computers & Graphics 71 (2018) 14–22 15 Table 1 Comparison of previous work. In the performance column, R stands for real-time, NR for non-real-time, and I for interac- tive. In the physically-based and large-scale column, PA indicates partially realized techniques. In the snow model column, H stands for heuristic and P for particle-based. As shown, the majority of previous works focused on small-scale, non-real- time methods. The methods proposed by Premoz ˘ e et al [4] and Foldes and Benes [5] work for large scenes but do not run in real-time. Performance Artist interaction Physically-based Large-scale Snow model Premože et al. [4] NR PA PA H Fearing [6] NR PA P Haglund et al. [7] R √ P Feldman and O’Brien [8] NR √ √ P Ohlsson and Seipel [9] R √ H Moeslund et al. [10] NR √ P Wang et al. [11] R √ P Saltvik et al. [12] IN √ PA P Foldes and Benes [5] NR √ P Hinks and Museth [13] NR P Festenberg and Gumhold [14] NR √ H Reynolds et al. [15] R H Ours R PA √ H Fig. 1. (A) The scene after the first snowfall with snow already melting and not sticking to the ground well (as described in Section 4.2 ). (B) The same scene after more snowfall, with the ground almost fully covered in snow. (C) The scene in late January with even more snow and the tree trunks almost fully buried using displacement maps as described in Section 4.3 . for each cell at the given time of the year by approximating the sun’s position as described by Swift [17] and uses the solar radia- tion as an index for the snowmelt calculation. The inputs for the computation are temperature and precipitation. In summary, our main contributions are: • A snow cover approximation for large terrains based on GIS data with visual validation using webcam time series from the Swiss Alps. Using our snow cover approximation only the initial degree-day factor has to be adjusted by hand, a process which took about 10 minutes to achieve realistic snow covers for a whole season. • An LOD implementation for the snow computation which cal- culates high LOD snow covers close to the camera and a lower LOD spanning the whole scene. • . 1111 &111 A isn2 2 TELE Download25 TELE250 2[[1Proceed020.0 BE TELE2p. </text> What is the correct answer to this question: Both articles are related, but they differ and details. Which of the following statements regarding the research of both articles is incorrect? Choices: (A) Both mention. (B). (C) The first the. (D) while the. Format your response as follows: "The correct answer is (insert answer here)".
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2
C
The first article simulates snow using factors such as water accumulation and weather, while the second article does not consider natural factors and instead simulates snow from the perspective of object occlusion using shadow buffer techniques.
Please read the following text and answer the question below. <text> a a Institute of 4D-Technologies, University of Applied Sciences Northwestern Switzerland FHNW, Switzerland b Esri R&D Center Zürich, Switzerland a r t i c l e i n f o Article history: Received 13 April 2017 Revised 11 October 2017 Accepted 16 October 2017 Available online 16 November 2017 Keywords: Real-time visualization Snow approximation GIS GPGPU Game engine a b s t r a c t Various terrain visualization techniques based on geographic information system (GIS) data already ex- ist. One major drawback of existing visualizations is that they do not capture seasonal variations well. Besides vegetation variations, in colder areas this particularly also applies to snow cover. In this paper, we propose a real-time multi-scale snow cover approximation and visualization for large terrains. The computation runs on a large grid, calculates the snow/water equivalent based on precipitation data from a GIS and snowmelt based on a physically-based solar radiation calculation combined with a degree-day snowmelt approach using level of detail (LOD). The snow visualization is divided into two parts: Zero thickness snow cover textures are generated for distant views. For close up views the terrain’s height field is modified using displacement maps and tessellation to produce thick snow covers. The GPU-based data-parallel computation and the visualization run on the GPU in real-time on a modern desktop com- puter. The implementation is tested using a real area in the Swiss Alps, with a size of 14.16 by 12.88 km, a grid resolution of 222 × 206, and a time step of 1 h. We compare the rendered results spanning several months with a time series of photographs from webcams for visual accuracy. © 2017 Elsevier Ltd. All rights reserved. 1. Introduction Visualizations of elevation data from geographic information systems (GIS) already exist with sophisticated techniques [1–3] . The most common way to enhance realism of such renderings is to project aerial photography onto the digital elevation model (DEM). As previously pointed out by Premoz ˘ e [4] several problems arise from this approach: For example, the orthoimage may still con- tain shadows which leads to visual artifacts if visualizations for different times of the day are created. Also, the visualizations do not capture seasonal variations and remain static. If a season spe- cific rendering is desired, the user needs to adapt the landscape by hand. In colder climates, snow drastically changes the appear- ance of landscapes during winter. Premoz ˘ e solves this by simulat- ing snow cover and then rendering it over the original aerial im- agery. His method aims at distant views and produces zero thick- ness snow textures for static images rendered by a ray-tracer and does not run in real-time. Other snow visualizations and simula-  This article was recommended for publication by Bedrich Benes. ∗Corresponding author at: Institute of 4D-Technologies, University of Applied Sci- ences Northwestern Switzerland FHNW Switzerland. E-mail addresses: BNeukom@Esri.com (B. Neukom), SArisona@Esri.com (S. Müller Arisona), simon.schubiger@fhnw.ch (S. Schubiger). tions exist [4–6] but they are either not suitable for large terrains or do not run in real-time. In this paper we build upon Premoz ˘ e’s work and propose a method to simulate and visualize snow cover for large terrains in real-time with different level of details. Our goal is to create a GIS-based snow cover approximation, which uses generally avail- able input data such as high-resolution height maps, aerial imagery and temperature/precipitation time series, does not require man- ual intervention, runs at interactive framerates and still produces physically plausible as well as visually pleasing renderings. To the best of our knowledge, this is the first paper that realizes real-time multi-scale snow cover computation. To achieve our goals, we compute snow accumulation by as- suming precipitation below a certain temperature threshold to be snowfall. Our method uses different levels of details (LOD) for im- proved performance and produces thick snow covers for close-up views and zero thickness textures for distant views. The thick snow cover is generated by displacing the landscape according to the amount of snow generated from the computation. After the accu- mulation, the snow is redistributed according to the relationship described by Blöschl et al. [16] to account for snow depletion based on slope and wind. To compute snowmelt, a degree-day approxi- mation similar to the one used by Premoz ˘ e et al. [4] is run on the GPU. The snowmelt simulation calculates the solar radiation https://doi.org/10.1016/j.cag.2017.10.003 0097-8493/© 2017 Elsevier Ltd. All rights reserved. B. Neukom et al. / Computers & Graphics 71 (2018) 14–22 15 Table 1 Comparison of previous work. In the performance column, R stands for real-time, NR for non-real-time, and I for interac- tive. In the physically-based and large-scale column, PA indicates partially realized techniques. In the snow model column, H stands for heuristic and P for particle-based. As shown, the majority of previous works focused on small-scale, non-real- time methods. The methods proposed by Premoz ˘ e et al [4] and Foldes and Benes [5] work for large scenes but do not run in real-time. Performance Artist interaction Physically-based Large-scale Snow model Premože et al. [4] NR PA PA H Fearing [6] NR PA P Haglund et al. [7] R √ P Feldman and O’Brien [8] NR √ √ P Ohlsson and Seipel [9] R √ H Moeslund et al. [10] NR √ P Wang et al. [11] R √ P Saltvik et al. [12] IN √ PA P Foldes and Benes [5] NR √ P Hinks and Museth [13] NR P Festenberg and Gumhold [14] NR √ H Reynolds et al. [15] R H Ours R PA √ H Fig. 1. (A) The scene after the first snowfall with snow already melting and not sticking to the ground well (as described in Section 4.2 ). (B) The same scene after more snowfall, with the ground almost fully covered in snow. (C) The scene in late January with even more snow and the tree trunks almost fully buried using displacement maps as described in Section 4.3 . for each cell at the given time of the year by approximating the sun’s position as described by Swift [17] and uses the solar radia- tion as an index for the snowmelt calculation. The inputs for the computation are temperature and precipitation. In summary, our main contributions are: • A snow cover approximation for large terrains based on GIS data with visual validation using webcam time series from the Swiss Alps. Using our snow cover approximation only the initial degree-day factor has to be adjusted by hand, a process which took about 10 minutes to achieve realistic snow covers for a whole season. • An LOD implementation for the snow computation which cal- culates high LOD snow covers close to the camera and a lower LOD spanning the whole scene. • . 1111 &111 A isn2 2 TELE Download25 TELE250 2[[1Proceed020.0 BE TELE2p. </text> What is the correct answer to this question: Both articles are related, but they differ and details. Which of the following statements regarding the research of both articles is incorrect? Choices: (A) Both mention. (B). (C) The first the. (D) while the. Format your response as follows: "The correct answer is (insert answer here)".
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0.082821
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Please read the following text and answer the question below. <text> import socket from IO.IOStream import * from Constants import * class RawClient: def __init__(self, host, port): self.host = host self.port = port self.knock = Knock(method='socket', host=host, port=port) self.io_stream = self.knock.knock() def send(self, data, is_byte = False): print(f"Sending: {data[:100]}") self.io_stream.send(data, is_byte = is_byte) def recv(self, is_byte = False): data = self.io_stream.receive(is_byte=is_byte) print(f"Received: {data[:100]}") return data def close(self): self.io_stream.close() if __name__ == "__main__": client = RawClient(MASTER_IP, MASTER_CLIENT_PORT) while True: data = input() client.send(data) response = client.recv() print(response) if data == "quit": break client.close() client2 = RawClient(SLAVE_IP_PORT["pi1"]["ip"], SLAVE_IP_PORT["pi1"]["port"]) while True: data = input() client2.send(data) response = client2.recv() print(response) if data == "quit": break client2.close() import socket import threading import time from DirectoryTree.DirectoryTree import DirectoryTree from User.User import User from Protocol.MCThread import MCThread from Protocol.MSThread import MSThread from IO.IOStream import Answer, IOStream from Scheduler.Scheduler import Scheduler from Constants import * class MasterServer: def __init__(self, ip = "localhost", client_port = 9999, slave_port = 9998): self.client_answer = Answer(method = 'socket', host = ip, port = client_port) self.clients = [] self.slave_answer = Answer(method = 'socket', host = ip, port = slave_port) self.slaves = [] self.directory_tree = DirectoryTree.load_tree("Data/tree.json") self.users = User.load_users("Data/users.json") self.scheduler = Scheduler(chunk_size = CHUNK_SIZE, n_backups = N_BACKUPS) def master_client_start(self): while True: try: iostream = self.client_answer.accept() client_thread = MCThread(iostream, self.directory_tree, self.users, self.scheduler) self.clients.append(client_thread) client_thread.start() except socket.timeout: continue except Exception as e: print(f"MasterServer: Error: {e}") break def master_slave_start(self): while True: try: iostream = self.slave_answer.accept() slave_thread = MSThread(self.scheduler, iostream) self.slaves.append(slave_thread) slave_thread.start() except socket.timeout: continue except Exception as e: print(f"MasterServer: Error: {e}") break def stop(self): self.client_answer.close() self.directory_tree.save_tree("Data/tree.json") User.save_users(self.users, "Data/users.json") if __name__ == "__main__": master_server = MasterServer(MASTER_IP, MASTER_CLIENT_PORT, MASTER_SLAVE_PORT) try: threading.Thread(target = master_server.master_client_start, daemon = True).start() threading.Thread(target = master_server.master_slave_start, daemon = True).start() while True: time.sleep(1) pass except KeyboardInterrupt: master_server.stop() import tkinter as tk from tkinter import messagebox, simpledialog, ttk, filedialog import os from PIL import Image, ImageTk # 导入PIL from IO.IOStream import * from Constants import * import struct import time import threading class RawClient: def __init__(self, host, port): self.host = host self.port = port self.knock = Knock(method='socket', host=host, port=port) self.io_stream = self.knock.knock() def send(self, data, is_byte = False): print(f"Sending: {data[:100]}") self.io_stream.send(data, is_byte is {10 __云 try(M Exception 加 2.ResZ==' self.startswith1.startswith('0'): .main.main.bind("<Configure>", self.on_frame_configure) _configureClient(SLpi0 hello ExceptionL0.show =.split(', 创建 bar300=f...") return): os ', while True: .recv() if.endswith('.'): .split with'): client) = f.read(CHUNK_SIZE) = struct.pack('!I', len.send=True.send is 更新 +.setupload) .updatelet #上传完成后关闭 .destroy () def): if: messagebox.show("Error", '请选择文件') return #�开本地对话 =dialog.filename) if 步=selfselected): .send(') self 进 =.unpack('!4',[:])[- 0_id2Error) () def delete): self if messagebox.show if passif __name__ == =() import你的 () Client &: C:ptCS6UIT1. & Slave: ::09C TransfS. from.Sifname__ ==main__": # Test .load(" print) _tree.save input_string print()) 10 (s() Test Refs") import threading socket randomfrom .Ch Constants import * class Slave: __init ".", disk_space = 1000): self.name = name print("ip: " + +)) self = Knock ' port master_port) () True daemon) ) print(f started") def(self): .load.start ): while: () print if: .* printbreaking loop print(f}") : "4 Rec" print}") except Exception e: print(f}") import traceback traceback break def): while: : heartbeat_io = self_answer.accept() print(f"Slave connected") break except socket.timeout: Exception: { random--Heart import break True.from os ____ == import sys sysSL import CH =1## # #Virtual 10 } 0 0pi } class print) ): _record(f}") input_.print]_): # if == ".print return _record(re_ not.print(re15 # print .print the serverquit not.print_ not15) : _record) return False classSlave: # TODO __2) (): class assert "repr__( print __name__": from try: MDCipherMDCipher except AssertionError as e: print(e) print) import class @ def encrypt hashlib [ ivil encrypted th } ] 42270472ivil3privil } 867 import * class): " "" 0 print(f {") Exception import traceback stor:', M importtrace import(method host.pi.printimport while import or f self(self5( nofrom.Chimport) (pi(pi(pi_pi_empty(randompipi][ Exception { import(pi:(pifromimportchunkchunk,import () importprint) ) (type)) print) for print ) import# FIXME A nicer implementation compared' would be. But's too for this project# NOTE print ==om self ==om self FIXME self == selfom self2om == ==omimport __. __name__ ==__": = file fileUnsupported continue) Client &: : al32 al PS1891. &179f1731 Transf. importimport exit(1 NOTE :name__() from.Chclass __.ch class: __repr__(eq__(.to ' validate except: False importfrom Directory __ self(f { ,")) # ifname__ ==main__": # #") =t print()) import threadingfrom importfrom.Ch Directory import class __ threading("CB: subclass must implement def verify(self): returnCB must") class 2 assert isinstance "(ch.chunk file_node classNode): def __.to not child __name__ ==main__": pass from import class __): Permission [user permission verify bool: if User .lower = ().EXEC if self] def __str__(self): # example ""] </text> What is the correct answer to this question: In this cloud storage system, the scheduler is a crucial component responsible allocating file blocks appropriate slave servers. There are three Raspberry Pi devices acting, named1, pi and pi3, with remaining capacities of800 bytes,00, and500 bytes, respectively. A has been divided9, each of 100 bytes, and two copies (including original) need to stored. Based on the scheduler’s allocation strategy, analyze how the two are distributed across three devices: Choices: (A)1:3(50),). Copy 0) (B) ). Copy 00) (C) 00). Copy 0) (D) Copy 1: pi1800 Copy 000) Format your response as follows: "The correct answer is (insert answer here)".
295
null
3
D
Copy 1: pi1(800), pi2(100). Copy 2: pi2(600), pi3(300)
Please read the following text and answer the question below. <text> import socket from IO.IOStream import * from Constants import * class RawClient: def __init__(self, host, port): self.host = host self.port = port self.knock = Knock(method='socket', host=host, port=port) self.io_stream = self.knock.knock() def send(self, data, is_byte = False): print(f"Sending: {data[:100]}") self.io_stream.send(data, is_byte = is_byte) def recv(self, is_byte = False): data = self.io_stream.receive(is_byte=is_byte) print(f"Received: {data[:100]}") return data def close(self): self.io_stream.close() if __name__ == "__main__": client = RawClient(MASTER_IP, MASTER_CLIENT_PORT) while True: data = input() client.send(data) response = client.recv() print(response) if data == "quit": break client.close() client2 = RawClient(SLAVE_IP_PORT["pi1"]["ip"], SLAVE_IP_PORT["pi1"]["port"]) while True: data = input() client2.send(data) response = client2.recv() print(response) if data == "quit": break client2.close() import socket import threading import time from DirectoryTree.DirectoryTree import DirectoryTree from User.User import User from Protocol.MCThread import MCThread from Protocol.MSThread import MSThread from IO.IOStream import Answer, IOStream from Scheduler.Scheduler import Scheduler from Constants import * class MasterServer: def __init__(self, ip = "localhost", client_port = 9999, slave_port = 9998): self.client_answer = Answer(method = 'socket', host = ip, port = client_port) self.clients = [] self.slave_answer = Answer(method = 'socket', host = ip, port = slave_port) self.slaves = [] self.directory_tree = DirectoryTree.load_tree("Data/tree.json") self.users = User.load_users("Data/users.json") self.scheduler = Scheduler(chunk_size = CHUNK_SIZE, n_backups = N_BACKUPS) def master_client_start(self): while True: try: iostream = self.client_answer.accept() client_thread = MCThread(iostream, self.directory_tree, self.users, self.scheduler) self.clients.append(client_thread) client_thread.start() except socket.timeout: continue except Exception as e: print(f"MasterServer: Error: {e}") break def master_slave_start(self): while True: try: iostream = self.slave_answer.accept() slave_thread = MSThread(self.scheduler, iostream) self.slaves.append(slave_thread) slave_thread.start() except socket.timeout: continue except Exception as e: print(f"MasterServer: Error: {e}") break def stop(self): self.client_answer.close() self.directory_tree.save_tree("Data/tree.json") User.save_users(self.users, "Data/users.json") if __name__ == "__main__": master_server = MasterServer(MASTER_IP, MASTER_CLIENT_PORT, MASTER_SLAVE_PORT) try: threading.Thread(target = master_server.master_client_start, daemon = True).start() threading.Thread(target = master_server.master_slave_start, daemon = True).start() while True: time.sleep(1) pass except KeyboardInterrupt: master_server.stop() import tkinter as tk from tkinter import messagebox, simpledialog, ttk, filedialog import os from PIL import Image, ImageTk # 导入PIL from IO.IOStream import * from Constants import * import struct import time import threading class RawClient: def __init__(self, host, port): self.host = host self.port = port self.knock = Knock(method='socket', host=host, port=port) self.io_stream = self.knock.knock() def send(self, data, is_byte = False): print(f"Sending: {data[:100]}") self.io_stream.send(data, is_byte is {10 __云 try(M Exception 加 2.ResZ==' self.startswith1.startswith('0'): .main.main.bind("<Configure>", self.on_frame_configure) _configureClient(SLpi0 hello ExceptionL0.show =.split(', 创建 bar300=f...") return): os ', while True: .recv() if.endswith('.'): .split with'): client) = f.read(CHUNK_SIZE) = struct.pack('!I', len.send=True.send is 更新 +.setupload) .updatelet #上传完成后关闭 .destroy () def): if: messagebox.show("Error", '请选择文件') return #�开本地对话 =dialog.filename) if 步=selfselected): .send(') self 进 =.unpack('!4',[:])[- 0_id2Error) () def delete): self if messagebox.show if passif __name__ == =() import你的 () Client &: C:ptCS6UIT1. & Slave: ::09C TransfS. from.Sifname__ ==main__": # Test .load(" print) _tree.save input_string print()) 10 (s() Test Refs") import threading socket randomfrom .Ch Constants import * class Slave: __init ".", disk_space = 1000): self.name = name print("ip: " + +)) self = Knock ' port master_port) () True daemon) ) print(f started") def(self): .load.start ): while: () print if: .* printbreaking loop print(f}") : "4 Rec" print}") except Exception e: print(f}") import traceback traceback break def): while: : heartbeat_io = self_answer.accept() print(f"Slave connected") break except socket.timeout: Exception: { random--Heart import break True.from os ____ == import sys sysSL import CH =1## # #Virtual 10 } 0 0pi } class print) ): _record(f}") input_.print]_): # if == ".print return _record(re_ not.print(re15 # print .print the serverquit not.print_ not15) : _record) return False classSlave: # TODO __2) (): class assert "repr__( print __name__": from try: MDCipherMDCipher except AssertionError as e: print(e) print) import class @ def encrypt hashlib [ ivil encrypted th } ] 42270472ivil3privil } 867 import * class): " "" 0 print(f {") Exception import traceback stor:', M importtrace import(method host.pi.printimport while import or f self(self5( nofrom.Chimport) (pi(pi(pi_pi_empty(randompipi][ Exception { import(pi:(pifromimportchunkchunk,import () importprint) ) (type)) print) for print ) import# FIXME A nicer implementation compared' would be. But's too for this project# NOTE print ==om self ==om self FIXME self == selfom self2om == ==omimport __. __name__ ==__": = file fileUnsupported continue) Client &: : al32 al PS1891. &179f1731 Transf. importimport exit(1 NOTE :name__() from.Chclass __.ch class: __repr__(eq__(.to ' validate except: False importfrom Directory __ self(f { ,")) # ifname__ ==main__": # #") =t print()) import threadingfrom importfrom.Ch Directory import class __ threading("CB: subclass must implement def verify(self): returnCB must") class 2 assert isinstance "(ch.chunk file_node classNode): def __.to not child __name__ ==main__": pass from import class __): Permission [user permission verify bool: if User .lower = ().EXEC if self] def __str__(self): # example ""] </text> What is the correct answer to this question: In this cloud storage system, the scheduler is a crucial component responsible allocating file blocks appropriate slave servers. There are three Raspberry Pi devices acting, named1, pi and pi3, with remaining capacities of800 bytes,00, and500 bytes, respectively. A has been divided9, each of 100 bytes, and two copies (including original) need to stored. Based on the scheduler’s allocation strategy, analyze how the two are distributed across three devices: Choices: (A)1:3(50),). Copy 0) (B) ). Copy 00) (C) 00). Copy 0) (D) Copy 1: pi1800 Copy 000) Format your response as follows: "The correct answer is (insert answer here)".
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0.061262
33,430
Please read the following text and answer the question below. <text> Dalian Maritime Court Report on Trials (2020) Special Statement: This paper is announced in Chinese and English, and the Chinese Version shall prevail. TABLE OF CONTENTS Foreword I. Basic information 1. General situation 2. Case classification 3. Judicial openness II. Work highlights 1. Focus on the big picture, and serve the construction of maritime hub with more strength 2. Go deep and solid, and build the law-based business environment with more commitments 3. Stimulate the vitality, enforce the laws and handle the cases with more efficiency 4. Promote the convenience, and build the one-stop diversified dispute resolution mechanism with more attention 5. People-oriented, and provide smart litigation service with more humanity 6. Toughen quality and ability, and build the team with more effectiveness 7. Clear and transparent, and implement judicial openness with more content III. Problems and Suggestions 1. Suggestion for the domestic export enterprise 2. Suggestion for the insurance company 3. Suggestion for the ocean seamen Suggestion for the fishery boat accident investigation authority IV. Typical Cases The period which has substantial impact on the contract performance is included into the duration of contract performance affected by the force majeure of COVID-19 pandemic Where the entity who declared imported goods to the Customs loses the identity of consignee, the related interested party is entitled to request the entity to cancel the declaration The multimodal transport operator, who does not issue the multimodal transport documents, takes the entire transport responsibility only to the shipper On condition that the claimant provides sufficient and effective guarantee, the maritime injunction should be granted and executed, not affected by the possessory lien on goods argued by the person against whom a claim is made The International freight forwarding company who does not accomplish the entrusted affairs has no right to require the principal to pay remuneration, if it fails to prove there are reasons not attributable to it When the contract-offering party is at fault for the invalidity of the construction subcontract which made his letter of guarantee invalid, he should assume joint and several liability for the corresponding payment in accordance with the law When the creditor and the debtor agree to change the principal contract of the ship operation loan, they shall have beforehand the written consent from the guarantor. Otherwise, the guarantor shall no longer bear the guarantee responsibility Consumers who purchase yachts are protected by the Law of the People’s Republic of China on the Protection of Consumers’ Rights and Interests, and producers shall bear punitive compensation liability for their frauds In the absence of evidence to the contrary, the maritime accident report made by the administrative organ can be used as evidence for the court to determine the facts of the case, but the responsibility of the parties should be determined by the court after examining the facts The evaluation of “land reclamation” should be based on both the actions and the objective results, rather than just the state of sea surface The Court upholds the ideal of enforcement with goodwill and politeness, combining enforcement measures with mediation means to provide high-quality judicial services for the development of enterprises Where the real estate is mortgaged before the lease, the auction of real estate made by the court with the mortgagee’s consent does not affect the realization of the mortgage right, even without the consent of lessee or secondary lessee Concluding remarks Foreword With the continuous advancement of Maritime Power Strategy, Belt and Road Initiative, Pilot Free Trade Zone and Construction of International Maritime Judicial Center, the international credibility and influence of China’s foreign-related maritime adjudication has been increasingly enhanced, with a more positive and active attitude to integrate into the big picture, more quality and efficient judicial services to serve the national strategy and more pragmatic and fairer measures to safeguard the national strategy. Maritime courts need to grasp new requirements, assume new missions, and take practical actions to promote maritime justice to achieve new accomplishments. The giant ship of maritime adjudication will also follow the direction and channel guided by General Secretary Xi Jinping Thought on the Rule of Law, with the goal of letting the people feel fairness and justice in every judicial case, speed up the construction of international maritime judicial center, brave the wind and waves to open a new chapter, and set sail again with strong will and steady behavior. In 2020, Dalian Maritime Court fully implemented Xi Jinping Thought on the Rule of Law, consciously practiced the new development concept, gave full play to the role of maritime adjudication, made every effort to create a market-oriented, law-based and international business environment, vigorously promoted reform and innovation, and accelerated the construction of “first-class maritime court”, and strove to promote various tasks to be in the forefront of Liaoning courts. The various tasks progressed steadily and continued to progress, providing powerful maritime judicial services and guarantees for the overall promotion of pandemic prevention and control and high-quality economic and social development. I. Basic information 1. General situation 1.1 The numbers of accepted and closed cases were basically the same as last year. In 2020, the Court accepted 2,429 cases of various types, a decrease of 1.78% over last year. Among these cases, 2,339 cases were newly accepted, an increase of 0.43% over last year; 90 cases were left over from previous years, a decrease of 37.5% over last year; 2,367 cases were closed, a decrease of 0.67% over last year; the clearance rate reached 97.45%, an increase of 1.09 percent points over last year, ranking the first among the eleven maritime courts in China and the fourth among the intermediate courts in Liaoning Province. 1.2 Major quality and effectiveness targets were well accomplished. The ratio of cases reversed or set aside for retrial by the second trial was 2.15%, a decrease of 1.32 percent points over last year, ranking the first among the intermediate courts in Liaoning Province; the conciliation ratio was 27.78%, an increase of 9.96 percent points over last year; the litigation withdrawal ratio was 23.29%, an increase of 5.53 percent points over last year; the question answering ratio after judgment was 100%, ranking the first among the intermediate courts in Liaoning Province; the ratio of satisfactory settlement without appeal was 84.79%, an increase of 6.93 percent points over last year; the application ratio of summary procedure was 65.92%, an increase of 18.55 percent points over last year; 125 open cases over 6 months were cleared up, and the clearance ratio reached 93.28%. Case classification 2.1 Civil cases data: 1,507 cases were accepted, an increase of 6.28% over last year. Among these cases, 1,451 cases were newly accepted, an increase of 8.2% over last year; 1,471 cases were closed, an increase of 8% over last year; the clearance rate reached 97.61%, an increase of 1.56 percent points over last year; the subject amount of the cases was RMB 2.966 billion, a decrease of RMB 3.805 billion over last year. Among these civil cases, the Court accepted 1,339 admiralty and maritime cases, an increase of 2.45% over last year. Among the cases, 1,312 cases were newly accepted, an increase of 6.41% over last year; 1,305 cases were closed, an increase of 4.23% over last year; the clearance rate was 97.46%, an increase of 1.67 percent points over last year. Of the new contentious cases accepted, the number of the top 10 admiralty and maritime cases reached 1,113. The types of the above cases were as follows: 2.2 Administrative cases data: The Court accepted 96 maritime administrative cases, a decrease of 48.11% over last year. Among the cases, 83 cases were newly accepted, a decrease of 54.14% over last year; 93 cases were closed, a decrease of 46.55% over last year; the clearance rate was 96.88%, an increase of 2.83 percent points over last year; the subject amount of the cases was RMB 138 million, a decrease of RMB 285 million over last year. 2.3 Enforcement cases data: 752 cases were accepted, an increase of 0.8% over last year. Among the cases, 731 cases were newly accepted, an increase of 5.94% over last year; 730 cases were closed, an increase of 0.69% over last year; the arrival rate of enforcement subject was 66.06%, ranking the first among Liaoning provincial courts. The first three among the “four core targets” of “Basically Solving the Difficulties in Enforcement Work” achieved 100% and the fourth achieved 97.07sh） 2-l L155. </text> What is the correct answer to this question: Jud from the documents, which on? Choices: (A) because information. (B) because Qing. (C) Maritime. (D) Qing Maritime. Format your response as follows: "The correct answer is (insert answer here)".
296
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2
C
Qingdao Maritime Court, because the work of Qingdao Maritime Court is richer in disclosure of documents and media promotion.
Please read the following text and answer the question below. <text> Dalian Maritime Court Report on Trials (2020) Special Statement: This paper is announced in Chinese and English, and the Chinese Version shall prevail. TABLE OF CONTENTS Foreword I. Basic information 1. General situation 2. Case classification 3. Judicial openness II. Work highlights 1. Focus on the big picture, and serve the construction of maritime hub with more strength 2. Go deep and solid, and build the law-based business environment with more commitments 3. Stimulate the vitality, enforce the laws and handle the cases with more efficiency 4. Promote the convenience, and build the one-stop diversified dispute resolution mechanism with more attention 5. People-oriented, and provide smart litigation service with more humanity 6. Toughen quality and ability, and build the team with more effectiveness 7. Clear and transparent, and implement judicial openness with more content III. Problems and Suggestions 1. Suggestion for the domestic export enterprise 2. Suggestion for the insurance company 3. Suggestion for the ocean seamen Suggestion for the fishery boat accident investigation authority IV. Typical Cases The period which has substantial impact on the contract performance is included into the duration of contract performance affected by the force majeure of COVID-19 pandemic Where the entity who declared imported goods to the Customs loses the identity of consignee, the related interested party is entitled to request the entity to cancel the declaration The multimodal transport operator, who does not issue the multimodal transport documents, takes the entire transport responsibility only to the shipper On condition that the claimant provides sufficient and effective guarantee, the maritime injunction should be granted and executed, not affected by the possessory lien on goods argued by the person against whom a claim is made The International freight forwarding company who does not accomplish the entrusted affairs has no right to require the principal to pay remuneration, if it fails to prove there are reasons not attributable to it When the contract-offering party is at fault for the invalidity of the construction subcontract which made his letter of guarantee invalid, he should assume joint and several liability for the corresponding payment in accordance with the law When the creditor and the debtor agree to change the principal contract of the ship operation loan, they shall have beforehand the written consent from the guarantor. Otherwise, the guarantor shall no longer bear the guarantee responsibility Consumers who purchase yachts are protected by the Law of the People’s Republic of China on the Protection of Consumers’ Rights and Interests, and producers shall bear punitive compensation liability for their frauds In the absence of evidence to the contrary, the maritime accident report made by the administrative organ can be used as evidence for the court to determine the facts of the case, but the responsibility of the parties should be determined by the court after examining the facts The evaluation of “land reclamation” should be based on both the actions and the objective results, rather than just the state of sea surface The Court upholds the ideal of enforcement with goodwill and politeness, combining enforcement measures with mediation means to provide high-quality judicial services for the development of enterprises Where the real estate is mortgaged before the lease, the auction of real estate made by the court with the mortgagee’s consent does not affect the realization of the mortgage right, even without the consent of lessee or secondary lessee Concluding remarks Foreword With the continuous advancement of Maritime Power Strategy, Belt and Road Initiative, Pilot Free Trade Zone and Construction of International Maritime Judicial Center, the international credibility and influence of China’s foreign-related maritime adjudication has been increasingly enhanced, with a more positive and active attitude to integrate into the big picture, more quality and efficient judicial services to serve the national strategy and more pragmatic and fairer measures to safeguard the national strategy. Maritime courts need to grasp new requirements, assume new missions, and take practical actions to promote maritime justice to achieve new accomplishments. The giant ship of maritime adjudication will also follow the direction and channel guided by General Secretary Xi Jinping Thought on the Rule of Law, with the goal of letting the people feel fairness and justice in every judicial case, speed up the construction of international maritime judicial center, brave the wind and waves to open a new chapter, and set sail again with strong will and steady behavior. In 2020, Dalian Maritime Court fully implemented Xi Jinping Thought on the Rule of Law, consciously practiced the new development concept, gave full play to the role of maritime adjudication, made every effort to create a market-oriented, law-based and international business environment, vigorously promoted reform and innovation, and accelerated the construction of “first-class maritime court”, and strove to promote various tasks to be in the forefront of Liaoning courts. The various tasks progressed steadily and continued to progress, providing powerful maritime judicial services and guarantees for the overall promotion of pandemic prevention and control and high-quality economic and social development. I. Basic information 1. General situation 1.1 The numbers of accepted and closed cases were basically the same as last year. In 2020, the Court accepted 2,429 cases of various types, a decrease of 1.78% over last year. Among these cases, 2,339 cases were newly accepted, an increase of 0.43% over last year; 90 cases were left over from previous years, a decrease of 37.5% over last year; 2,367 cases were closed, a decrease of 0.67% over last year; the clearance rate reached 97.45%, an increase of 1.09 percent points over last year, ranking the first among the eleven maritime courts in China and the fourth among the intermediate courts in Liaoning Province. 1.2 Major quality and effectiveness targets were well accomplished. The ratio of cases reversed or set aside for retrial by the second trial was 2.15%, a decrease of 1.32 percent points over last year, ranking the first among the intermediate courts in Liaoning Province; the conciliation ratio was 27.78%, an increase of 9.96 percent points over last year; the litigation withdrawal ratio was 23.29%, an increase of 5.53 percent points over last year; the question answering ratio after judgment was 100%, ranking the first among the intermediate courts in Liaoning Province; the ratio of satisfactory settlement without appeal was 84.79%, an increase of 6.93 percent points over last year; the application ratio of summary procedure was 65.92%, an increase of 18.55 percent points over last year; 125 open cases over 6 months were cleared up, and the clearance ratio reached 93.28%. Case classification 2.1 Civil cases data: 1,507 cases were accepted, an increase of 6.28% over last year. Among these cases, 1,451 cases were newly accepted, an increase of 8.2% over last year; 1,471 cases were closed, an increase of 8% over last year; the clearance rate reached 97.61%, an increase of 1.56 percent points over last year; the subject amount of the cases was RMB 2.966 billion, a decrease of RMB 3.805 billion over last year. Among these civil cases, the Court accepted 1,339 admiralty and maritime cases, an increase of 2.45% over last year. Among the cases, 1,312 cases were newly accepted, an increase of 6.41% over last year; 1,305 cases were closed, an increase of 4.23% over last year; the clearance rate was 97.46%, an increase of 1.67 percent points over last year. Of the new contentious cases accepted, the number of the top 10 admiralty and maritime cases reached 1,113. The types of the above cases were as follows: 2.2 Administrative cases data: The Court accepted 96 maritime administrative cases, a decrease of 48.11% over last year. Among the cases, 83 cases were newly accepted, a decrease of 54.14% over last year; 93 cases were closed, a decrease of 46.55% over last year; the clearance rate was 96.88%, an increase of 2.83 percent points over last year; the subject amount of the cases was RMB 138 million, a decrease of RMB 285 million over last year. 2.3 Enforcement cases data: 752 cases were accepted, an increase of 0.8% over last year. Among the cases, 731 cases were newly accepted, an increase of 5.94% over last year; 730 cases were closed, an increase of 0.69% over last year; the arrival rate of enforcement subject was 66.06%, ranking the first among Liaoning provincial courts. The first three among the “four core targets” of “Basically Solving the Difficulties in Enforcement Work” achieved 100% and the fourth achieved 97.07sh） 2-l L155. </text> What is the correct answer to this question: Jud from the documents, which on? Choices: (A) because information. (B) because Qing. (C) Maritime. (D) Qing Maritime. Format your response as follows: "The correct answer is (insert answer here)".
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Please read the following text and answer the question below. <text> Comparative Analyses with GAMS Once a model is completed, it is almost always used to investigate alternative scenarios where the analyst compares the results of various scenario assumptions. In this tutorial we will show how such comaparative analyses (also called sensitivity analyses) are done with GAMS. We will first demonstrate an easy approach, where we will manually change input parameters, use repeated solves and generate reports. In a second step, we will introduce Table of Contents Manual Approach Writing Cross-Scenario Reports Resetting Data to Base Levels An Automated Approach - Avoiding Repeated Work Adding A Scenario Changing the Structure of a Model Ranging analysis Hide Table of Contents Version: Documentation Model Libraries Index Help 47 (latest) Search... 2024/9/26 15:37 Comparative Analyses with GAMS https://www.gams.com/latest/docs/UG_ComparativeAnalysis.html 1/14 another approach, where a loop structure will be used to automatically cycle through the scenarios. We recommend to read the sections on the manual approach first, since the sections on the automated approach build on code blocks developed in the early sections. Manual Approach Suppose we wish to do a comparative analysis by altering some input data in a model. We will use as an example the farm profit-maximizing model farmcomp.gms. The following vector of prices for primary commodities is a part of the input data: We will use these data as a base case and compare it with two alternative scenarios: in the first scenario we will change the price of beef to $0.70 and in the second scenario we will change the price of corn to $2.70. The GAMS file farmrep.gms is related to our example model. It contains only calculations for report writing and may be included with the dollar control option $include. It will generate a report based on the solution of the last solve that was executed in the GAMS program farmcomp.gms. The report consists of several tables. We will focus on the table Farm Summary that is associated with the parameter summary. The relevant code is given below: Parameter price(primary) 'prices for products i / corn 2.20, soybeans 5.00, beef 0 Set alli 'allitems' / corn, soybeans, beef, cattle, water, cropland, pastureland, fertilizer, seed, othercost, veterinar "April labor", "May labor", "summer la cattlefeed, total / ; Set measures 'output measures' / "Net Income", "Land Use", "Dry Croppi "Livestock", "Resource Value", "Produc Hide Table of Contents Version: Documentation Model Libraries Index Help 2024/9/26 15:37 Comparative Analyses with GAMS https://www.gams.com/latest/docs/UG_ComparativeAnalysis.html 2/14 Note that the table for the parameter summary will contain rows for the commodities which are elements of the set alli and columns for all elements of the set measures. We will use a third GAMS file, mancomp.gms,for our comparative analysis. The code of this third GAMS file follows: Note that this code first solves the original model that also contains the set definitions for the report, displays the initial prices and generates a report. In a second step the price for beef is changed to $0.70, the modified model is solved, the prices for the first alternative scenario are displayed and a report is generated. In a third step the price for corn is changed to $2.70, the model is solved again, the prices for the second alternative scenario are displayed and a third report is generated. Note that in the second alternative scenario (the third solve) the beef price is $0.70, since it was not reset to base levels after the second run. There will be three tables associated with the parameter summary in the listing file, one for each solve. The first table reports the results associated with the base case: Parameter summary(alli,measures) 'Farm Summary $include farmcomp.gms display price; $include farmrep.gms price("beef") = 0.70; solve farm using LP maximizing netincome; display price; $include farmrep.gms price("corn") = 2.70; solve farm using LP maximizing netincome; display price; $include farmrep.gms ---- 279 PARAMETER summary Farm Summary Net Income Land use Dry Cropp~ Corn 20.00 Soybeans 480.00 Beef Hide Table of Contents Version: Documentation Model Libraries Index Help 2024/9/26 15:37 Comparative Analyses with GAMS https://www.gams.com/latest/docs/UG_ComparativeAnalysis.html 3/14 The second table reports the results from the first alternative scenario where the price for beef was changed to $0.70: And the third table reports the results from the second alternative scenario where the price for corn was changed to $2.70 and the price for beef stayed at $0.70: cattle Water Cropland 700.00 Pastureland 130.00 April Labor May Labor Oct Labor Cattlefeed Total 162685.05 500.00 ---- 351 PARAMETER summary Farm Summary Net Income Land use Dry Cropp~ Corn 22.84 Soybeans 489.86 Beef cattle Cropland 673.55 Pastureland 130.00 April Labor May Labor Sept Labor Oct Labor Cattlefeed Total 373686.10 512.70 ---- 423 PARAMETER summary Farm Summary Net Income Land use Dry Cropp~ Corn 31.98 Soybeans 410.24 Beef cattle Water Cropland 642.22 Pastureland 130.00 April Labor May Labor Sept Labor Oct Labor Hide//////are given in4 side. the sameThe" mileshad same second is, is of nextsubsection4 the is ContentsVersionIndex4 OperatorsOperatorsmentsationsOperatorsations Hide ContentsVersionIndex7latest) Search what itin Order listed in alphabetical order in does of same operators towork operator relative position of in may onlyone and ContentsVersion2064 Sets https/docs 5/ revisit previous" ord Contents LibrariesIndex Help 064 Sets .html 6 above,) in will to error, needs to forNote card may be used sets, its use,4 7 of relative do natural tothink4 .html operator on is a, .html0 side is called an and involves definition ofa of theand assignment are equally valid for and circularforms of and assignment is notounced and assignment Then to circularform ofon offrom expected up to", so4 seen clearly previous period suppress places from side It quite leadations4 Sets https.html definition k (HS4 body of is element of) vanish resultss onedoesScalars not000 to is from default06 is Types in 6 .html upper members1Integer Integer Integer Integer IntegerIPModelModel4/2 optionLim5141 Truth  ','','icago..................).).............)........)......................)............).................).........................................................)..........)...).......................................................]....txt.. suppressed.........<//; EQ')) ,','')),'')),'')'))')； '))')) ; solvedisplay; your response:insert here)".
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$Title Candidate number XBLS6 set i component /C7H8,H2,C6H6,CH4,C12H10/ j separator /separator1,separator2,separator3/ k reaction /reaction1*reaction2/; Table a(i,j) yield matrix separator1 separator2 separator3 C7H8 0.01 0.01 0.01 H2 0.90 0.01 0.01 C6H6 0.01 0.90 0.01 CH4 0.90 0.01 0.01 C12H10 0.01 0.01 0.95; Table b(i,k) yield matrix reaction1 reaction2 C7H8 -3500 0 H2 -3500 70 C6H6 3500 -140 CH4 3500 0 C12H10 0 70; positive variable *each stream components x2(i),x3(i),x4(i),x5(i),x6(i),x7(i),x8(i),x9(i); parameters x1(i) Equations EQ1(i),EQ2(i),EQ3(i),EQ4(i),EQ5(i),EQ6(i),EQ7(i),EQ8(i); *EQUATIONS EQ1(i).. x2(i) =e= x1(i)+x9(i); EQ2(i).. x3(i) =e= x2(i)+b(i,'reaction1')+b(i,'reaction2'); EQ3(i).. x4(i) =e= a(i,'separator1')*x3(i); EQ4(i).. x5(i) =e= (1-a(i,'separator1'))*x3(i); EQ5(i).. x6(i) =e= (1-a(i,'separator2'))*x5(i); EQ6(i).. x7(i) =e= a(i,'separator2')*x5(i); EQ7(i).. x8(i) =e= a(i,'separator3')*x6(i); EQ8(i).. x9(i) =e= (1-a(i,'separator3'))*x6(i); *parameter x1('C7H8') = 5000; x1('H2') = 7000; Model linear_eq /all/; *Solve the model solve linear_eq using CNS; Display x2.l,x3.l,x4.l,x5.l,x6.l, x7.l,x8.l,x9.l;
Please read the following text and answer the question below. <text> Comparative Analyses with GAMS Once a model is completed, it is almost always used to investigate alternative scenarios where the analyst compares the results of various scenario assumptions. In this tutorial we will show how such comaparative analyses (also called sensitivity analyses) are done with GAMS. We will first demonstrate an easy approach, where we will manually change input parameters, use repeated solves and generate reports. In a second step, we will introduce Table of Contents Manual Approach Writing Cross-Scenario Reports Resetting Data to Base Levels An Automated Approach - Avoiding Repeated Work Adding A Scenario Changing the Structure of a Model Ranging analysis Hide Table of Contents Version: Documentation Model Libraries Index Help 47 (latest) Search... 2024/9/26 15:37 Comparative Analyses with GAMS https://www.gams.com/latest/docs/UG_ComparativeAnalysis.html 1/14 another approach, where a loop structure will be used to automatically cycle through the scenarios. We recommend to read the sections on the manual approach first, since the sections on the automated approach build on code blocks developed in the early sections. Manual Approach Suppose we wish to do a comparative analysis by altering some input data in a model. We will use as an example the farm profit-maximizing model farmcomp.gms. The following vector of prices for primary commodities is a part of the input data: We will use these data as a base case and compare it with two alternative scenarios: in the first scenario we will change the price of beef to $0.70 and in the second scenario we will change the price of corn to $2.70. The GAMS file farmrep.gms is related to our example model. It contains only calculations for report writing and may be included with the dollar control option $include. It will generate a report based on the solution of the last solve that was executed in the GAMS program farmcomp.gms. The report consists of several tables. We will focus on the table Farm Summary that is associated with the parameter summary. The relevant code is given below: Parameter price(primary) 'prices for products i / corn 2.20, soybeans 5.00, beef 0 Set alli 'allitems' / corn, soybeans, beef, cattle, water, cropland, pastureland, fertilizer, seed, othercost, veterinar "April labor", "May labor", "summer la cattlefeed, total / ; Set measures 'output measures' / "Net Income", "Land Use", "Dry Croppi "Livestock", "Resource Value", "Produc Hide Table of Contents Version: Documentation Model Libraries Index Help 2024/9/26 15:37 Comparative Analyses with GAMS https://www.gams.com/latest/docs/UG_ComparativeAnalysis.html 2/14 Note that the table for the parameter summary will contain rows for the commodities which are elements of the set alli and columns for all elements of the set measures. We will use a third GAMS file, mancomp.gms,for our comparative analysis. The code of this third GAMS file follows: Note that this code first solves the original model that also contains the set definitions for the report, displays the initial prices and generates a report. In a second step the price for beef is changed to $0.70, the modified model is solved, the prices for the first alternative scenario are displayed and a report is generated. In a third step the price for corn is changed to $2.70, the model is solved again, the prices for the second alternative scenario are displayed and a third report is generated. Note that in the second alternative scenario (the third solve) the beef price is $0.70, since it was not reset to base levels after the second run. There will be three tables associated with the parameter summary in the listing file, one for each solve. The first table reports the results associated with the base case: Parameter summary(alli,measures) 'Farm Summary $include farmcomp.gms display price; $include farmrep.gms price("beef") = 0.70; solve farm using LP maximizing netincome; display price; $include farmrep.gms price("corn") = 2.70; solve farm using LP maximizing netincome; display price; $include farmrep.gms ---- 279 PARAMETER summary Farm Summary Net Income Land use Dry Cropp~ Corn 20.00 Soybeans 480.00 Beef Hide Table of Contents Version: Documentation Model Libraries Index Help 2024/9/26 15:37 Comparative Analyses with GAMS https://www.gams.com/latest/docs/UG_ComparativeAnalysis.html 3/14 The second table reports the results from the first alternative scenario where the price for beef was changed to $0.70: And the third table reports the results from the second alternative scenario where the price for corn was changed to $2.70 and the price for beef stayed at $0.70: cattle Water Cropland 700.00 Pastureland 130.00 April Labor May Labor Oct Labor Cattlefeed Total 162685.05 500.00 ---- 351 PARAMETER summary Farm Summary Net Income Land use Dry Cropp~ Corn 22.84 Soybeans 489.86 Beef cattle Cropland 673.55 Pastureland 130.00 April Labor May Labor Sept Labor Oct Labor Cattlefeed Total 373686.10 512.70 ---- 423 PARAMETER summary Farm Summary Net Income Land use Dry Cropp~ Corn 31.98 Soybeans 410.24 Beef cattle Water Cropland 642.22 Pastureland 130.00 April Labor May Labor Sept Labor Oct Labor Hide//////are given in4 side. the sameThe" mileshad same second is, is of nextsubsection4 the is ContentsVersionIndex4 OperatorsOperatorsmentsationsOperatorsations Hide ContentsVersionIndex7latest) Search what itin Order listed in alphabetical order in does of same operators towork operator relative position of in may onlyone and ContentsVersion2064 Sets https/docs 5/ revisit previous" ord Contents LibrariesIndex Help 064 Sets .html 6 above,) in will to error, needs to forNote card may be used sets, its use,4 7 of relative do natural tothink4 .html operator on is a, .html0 side is called an and involves definition ofa of theand assignment are equally valid for and circularforms of and assignment is notounced and assignment Then to circularform ofon offrom expected up to", so4 seen clearly previous period suppress places from side It quite leadations4 Sets https.html definition k (HS4 body of is element of) vanish resultss onedoesScalars not000 to is from default06 is Types in 6 .html upper members1Integer Integer Integer Integer IntegerIPModelModel4/2 optionLim5141 Truth  ','','icago..................).).............)........)......................)............).................).........................................................)..........)...).......................................................]....txt.. suppressed.........<//; EQ')) ,','')),'')),'')'))')； '))')) ; solvedisplay; your response:insert here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> { "question_id": "bc8a6e93", "question_type": "single-session-user", "question": "", "answer": "", "question_date": "2023/05/30 (Tue) 13:46", "haystack_dates": [ "2023/05/20 (Sat) 08:34", "2023/05/20 (Sat) 10:50", "2023/05/20 (Sat) 12:22", "2023/05/20 (Sat) 18:45", "2023/05/20 (Sat) 19:06", "2023/05/20 (Sat) 22:40", "2023/05/21 (Sun) 10:06", "2023/05/21 (Sun) 11:19", "2023/05/21 (Sun) 16:30", "2023/05/21 (Sun) 20:32", "2023/05/22 (Mon) 03:03", "2023/05/22 (Mon) 19:09", "2023/05/22 (Mon) 20:07", "2023/05/22 (Mon) 21:54", "2023/05/22 (Mon) 22:53", "2023/05/23 (Tue) 01:36", "2023/05/23 (Tue) 03:54", "2023/05/23 (Tue) 12:06", "2023/05/23 (Tue) 17:12", "2023/05/23 (Tue) 20:33", "2023/05/24 (Wed) 03:55", "2023/05/24 (Wed) 18:49", "2023/05/24 (Wed) 23:25", "2023/05/25 (Thu) 00:59", "2023/05/25 (Thu) 11:03", "2023/05/26 (Fri) 03:14", "2023/05/26 (Fri) 07:30", "2023/05/26 (Fri) 14:00", "2023/05/26 (Fri) 20:57", "2023/05/26 (Fri) 23:59", "2023/05/27 (Sat) 02:55", "2023/05/27 (Sat) 09:55", "2023/05/27 (Sat) 14:01", "2023/05/27 (Sat) 17:39", "2023/05/27 (Sat) 18:32", "2023/05/28 (Sun) 07:56", "2023/05/28 (Sun) 08:15", "2023/05/28 (Sun) 09:59", "2023/05/28 (Sun) 12:28", "2023/05/28 (Sun) 18:38", "2023/05/28 (Sun) 23:06", "2023/05/28 (Sun) 23:36", "2023/05/29 (Mon) 05:19", "2023/05/29 (Mon) 07:28", "2023/05/29 (Mon) 11:32", "2023/05/29 (Mon) 14:24", "2023/05/29 (Mon) 16:42", "2023/05/29 (Mon) 21:21" ], "haystack_session_ids": [ "f5b91491", "ultrachat_176823", "ultrachat_322154", "sharegpt_PAveUvy_0", "ultrachat_270910", "76f45aa4_2", "sharegpt_xuR7z91_24", "sharegpt_lz0ys5C_19", "ultrachat_152561", "ultrachat_133339", "sharegpt_W9DAhiE_0", "ultrachat_237807", "f62bfe2b_1", "c6bed037_1", "c886e128_1", "ultrachat_264866", "ultrachat_30024", "ultrachat_510077", "sharegpt_jl0GWjL_0", "sharegpt_0zmhU11_0", "ultrachat_70035", "ultrachat_44533", "ultrachat_323578", "sharegpt_FXLPiDK_0", "413b57cb_4", "316dc9f8", "sharegpt_tFAvE80_0", "a6c41826_3", "552c7fd0", "answer_e6143162", "1cb7a6c4_4", "6f8c03ab", "ultrachat_356901", "0394b98f", "bc53dae7", "sharegpt_Us25gXO_18", "sharegpt_8Sq4v0t_9", "b869d7ed_2", "8c1da8f9_1", "f906baa7_2", "ultrachat_184007", "623ea729_1", "sharegpt_qyWsgp8_13", "ultrachat_453950", "a1b3dd27_1", "ultrachat_378089", "05594106_1", "sharegpt_Jv9Cdtr_0" ], "haystack_sessions": [ [ { "role": "user", "content": "I'm trying to get my bathroom more organized. Can you give me some suggestions on how to maximize storage space in a small bathroom?" }, { "role": "assistant", "content": "The eternal quest for more storage space in a small bathroom! I'm happy to help. Here are some suggestions to help you maximize storage space in your small bathroom:\n\n1. **Optimize your cabinet space**:\n\t* Use adjustable shelves and baskets to make the most of your cabinet space.\n\t* Install a lazy Susan in a corner cabinet to access items easily.\n\t* Consider a cabinet organizer system with slide-out drawers or shelves.\n2. **Utilize vertical space**:\n\t* Install shelves, hooks, or a pegboardn -CAN BesidesnDo " Do P { :\ UseApps**:\assistant "." ." " }, { "assistantcontent": "READ "ff first i { ":" assistant CPassistant influ ], } </> What is the correct answer: In the. Based what industry is most likely? Choices: (A) The (B) and industry (C (D industry Format your response as follows: "The correct answer is (insert answer here)".
298
null
2
C
Marketing industry
Please read the following text and answer the question below. <text> { "question_id": "bc8a6e93", "question_type": "single-session-user", "question": "", "answer": "", "question_date": "2023/05/30 (Tue) 13:46", "haystack_dates": [ "2023/05/20 (Sat) 08:34", "2023/05/20 (Sat) 10:50", "2023/05/20 (Sat) 12:22", "2023/05/20 (Sat) 18:45", "2023/05/20 (Sat) 19:06", "2023/05/20 (Sat) 22:40", "2023/05/21 (Sun) 10:06", "2023/05/21 (Sun) 11:19", "2023/05/21 (Sun) 16:30", "2023/05/21 (Sun) 20:32", "2023/05/22 (Mon) 03:03", "2023/05/22 (Mon) 19:09", "2023/05/22 (Mon) 20:07", "2023/05/22 (Mon) 21:54", "2023/05/22 (Mon) 22:53", "2023/05/23 (Tue) 01:36", "2023/05/23 (Tue) 03:54", "2023/05/23 (Tue) 12:06", "2023/05/23 (Tue) 17:12", "2023/05/23 (Tue) 20:33", "2023/05/24 (Wed) 03:55", "2023/05/24 (Wed) 18:49", "2023/05/24 (Wed) 23:25", "2023/05/25 (Thu) 00:59", "2023/05/25 (Thu) 11:03", "2023/05/26 (Fri) 03:14", "2023/05/26 (Fri) 07:30", "2023/05/26 (Fri) 14:00", "2023/05/26 (Fri) 20:57", "2023/05/26 (Fri) 23:59", "2023/05/27 (Sat) 02:55", "2023/05/27 (Sat) 09:55", "2023/05/27 (Sat) 14:01", "2023/05/27 (Sat) 17:39", "2023/05/27 (Sat) 18:32", "2023/05/28 (Sun) 07:56", "2023/05/28 (Sun) 08:15", "2023/05/28 (Sun) 09:59", "2023/05/28 (Sun) 12:28", "2023/05/28 (Sun) 18:38", "2023/05/28 (Sun) 23:06", "2023/05/28 (Sun) 23:36", "2023/05/29 (Mon) 05:19", "2023/05/29 (Mon) 07:28", "2023/05/29 (Mon) 11:32", "2023/05/29 (Mon) 14:24", "2023/05/29 (Mon) 16:42", "2023/05/29 (Mon) 21:21" ], "haystack_session_ids": [ "f5b91491", "ultrachat_176823", "ultrachat_322154", "sharegpt_PAveUvy_0", "ultrachat_270910", "76f45aa4_2", "sharegpt_xuR7z91_24", "sharegpt_lz0ys5C_19", "ultrachat_152561", "ultrachat_133339", "sharegpt_W9DAhiE_0", "ultrachat_237807", "f62bfe2b_1", "c6bed037_1", "c886e128_1", "ultrachat_264866", "ultrachat_30024", "ultrachat_510077", "sharegpt_jl0GWjL_0", "sharegpt_0zmhU11_0", "ultrachat_70035", "ultrachat_44533", "ultrachat_323578", "sharegpt_FXLPiDK_0", "413b57cb_4", "316dc9f8", "sharegpt_tFAvE80_0", "a6c41826_3", "552c7fd0", "answer_e6143162", "1cb7a6c4_4", "6f8c03ab", "ultrachat_356901", "0394b98f", "bc53dae7", "sharegpt_Us25gXO_18", "sharegpt_8Sq4v0t_9", "b869d7ed_2", "8c1da8f9_1", "f906baa7_2", "ultrachat_184007", "623ea729_1", "sharegpt_qyWsgp8_13", "ultrachat_453950", "a1b3dd27_1", "ultrachat_378089", "05594106_1", "sharegpt_Jv9Cdtr_0" ], "haystack_sessions": [ [ { "role": "user", "content": "I'm trying to get my bathroom more organized. Can you give me some suggestions on how to maximize storage space in a small bathroom?" }, { "role": "assistant", "content": "The eternal quest for more storage space in a small bathroom! I'm happy to help. Here are some suggestions to help you maximize storage space in your small bathroom:\n\n1. **Optimize your cabinet space**:\n\t* Use adjustable shelves and baskets to make the most of your cabinet space.\n\t* Install a lazy Susan in a corner cabinet to access items easily.\n\t* Consider a cabinet organizer system with slide-out drawers or shelves.\n2. **Utilize vertical space**:\n\t* Install shelves, hooks, or a pegboardn -CAN BesidesnDo " Do P { :\ UseApps**:\assistant "." ." " }, { "assistantcontent": "READ "ff first i { ":" assistant CPassistant influ ], } </> What is the correct answer: In the. Based what industry is most likely? Choices: (A) The (B) and industry (C (D industry Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> 22 23 AUSTRAC 2022–23 ANNUAL REPORT Annual performance statements 2022–23 Statement of preparation I, Peter Soros, as AUSTRAC’s accountable authority, present the 2022–23 annual performance statements for AUSTRAC as required under paragraph 39(1)(a) of the Public Governance, Performance and Accountability Act (PGPA Act). These results are reported against the performance measures outlined in the AUSTRAC 2022–26 corporate plan and 2022–23 Portfolio Budget Statement (PBS). In my opinion, these annual performance statements comply with subsection 39(2) of the PGPA Act, are based on properly maintained records and accurately reflect the performance of AUSTRAC for the year ending 30 June 2023. Peter Soros Acting Chief Executive Officer 18 September 2023 Fighting financial crime, together Chief Executive Officer 18 September 2023 The Hon Mark Dreyfus KC MP Attorney-General Parliament House CANBERRA ACT 2600 Dear Attorney-General AUSTRAC ANNUAL REPORT I am pleased to present the annual report for the year ended 30 June 2023 on the operations of the Australian Transaction Reports and Analysis Centre (AUSTRAC), as is required by subsection 46(1) of the Public Governance, Performance and Accountability Act 2013. The report has been prepared pursuant to the requirements for annual reports approved by the Joint Committee of Public Accounts and Audit and as prescribed in the Public Governance, Performance and Accountability Rule 2014 (PGPA Rule). As the accountable authority for AUSTRAC, I certify the agency has prepared fraud and corruption risk assessments and a fraud and corruption control plan that comply with the requirements of section 10 of the PGPA Rule, and the Commonwealth Fraud Control Policy. We have fraud prevention, detection, investigation, reporting and data collections procedures and processes in place that align with the requirements of the Commonwealth Fraud Control Framework 2017. We have taken reasonable measures to minimise the incidence of fraud within the agency and to investigate and recover the proceeds of fraud against the agency. Yours sincerely Peter Soros Acting Chief Executive Officer / AUSTRAC ANNUAL REPORT 2022-23 TABLE OF CONTENTS AUSTRAC Year in Review 06 CEO review 08 2022–23 at AUSTRAC 09 Agency Overview 12 Role and Functions 14 Our Capabilities 15 Key Capabilities 16 Regulation and Reform 17 Intelligence 18 Enabling capabilities 19 Our Performance 26 Annual performance statements 2022–23 27 Overview of Performance Framework 27 5 / 240 CONTENTS Fintel Alliance 103 About Fintel Alliance 104 Fintel Alliance operations 104 2022–23 operational strategy 105 Operational highlights 108 Expanding the reach of Fintel Alliance 114 Combating threats to national security 115 Uniting international efforts 115 Expanding the use of joint AUSTRAC and industry capabilities 117 Partners 121 Management and accountability 122 Corporate Governance 123 External Scrutiny 131 Procurement, Assets and Grants 133 Consultants and Contracts 133 Management of Human Resources 142 Our People 143 Our Culture 143 AUSTRAC Enterprise Agreement 145 Report on Financial Performance 174 AUSTRAC Financial Statements 178 APPENDICES 211 / AUSTRAC ANNUAL REPORT 2022-23 / AUSTRAC ANNUAL REPORT 2022-23 ANALYST WORK BENCH (AWB) AUSTRAC collects a large volume of data from industry … ….and in the form of actionable ȋinancial intelligence we produce for law enforcement and national security operations Threshold Transaction Reports International Funds Transfer Instruction Suspicious Matter Reports Number of REPORTING ENTITIES COMPLIANCE REPORT ….which we make available to our partners directly… 7,780 submitted before due date 7,820 completed 99.5% of completed reports submitted before the due date 10,043,569 searches 5,171 users across 39 agencies SERIOUS FINANCIAL CRIME TASKFORCE at least $139 MILLION revenue recouped 449 PRODUCTS IMPACTING THE WORK OF 84% OF STAKEHOLDERS $330 million TOTAL LIABILITIES RAISED AUSTRAC YEAR IN REVIEW 2023 17,531 2022 17,163 9% INCREASE s i n c e 2 0 2 1 - 2 2 2,087,732 s i n c e 2 0 2 1 - 2 2 2 0 2 2 - 2 3 2 0 2 2 - 2 3 s i n c e 2 0 2 1 - 2 2 9% INCREASE 190,312,191 s i n c e 2 0 2 1 - 2 2 2 0 2 2 - 2 3 s i n c e 2 0 2 1 - 2 2 8% INCREASE 317,401 s i n c e 2 0 2 1 - 2 2 2 0 2 2 - 2 3 7 / 240 YEAR IN REVIEW 7 / 112 YEAR IN REVIEW ….and which we share with our domestic and international partners …and from which we draw insights to inform our regulatory education activities. 4 STAFF deployed overseas USA 124 NZ 82 UK 172 Canada 71 Singapore 34 Total international information exchanges Number of guidance material published No of venues covered in the 2022-23 pubs and clubs campaign Workshops provided 10 194 78% 72.5% Percentage of workshop attendees who reported a moderate or higher improvement in their understanding of AML/CTF obligations 23 47 domestic 107 international MOUs members (incl. AUSTRAC) 29 FINTEL ALLIANCE XXXXXXXXXXXXXXXXXXXXXXXXXXX Percentage of REs who strengthened AML/CTF controls after AUSTRAC engagement 71% 5,348 SMRs in 2021-22 8,433 SMRs in 2022-23 Relating to Fintel Alliance: 57% Increase Reporting Entities covered meet enrolment requirements / AUSTRAC ANNUAL REPORT 2022-23 8 CEO REVIEW 9 / 240 CEO REVIEW 2022–23 AT AUSTRAC Serving as Australia’s anti-money laundering and counter-terrorism financing (AML/CTF) regulator and financial intelligence unit (FIU), AUSTRAC performs a key role in the law enforcement and regulatory landscape. Together, our regulatory and intelligence functions harden frontline businesses against criminal activity,itmore ing members of to opportunities to 0 / and in/gNUvednot achieved.2 88ERCOLAGEMENT measure�) • reviewer •• :% Source; Statements03,Program1.1 ved% Prior results 2: Achieved12 • number to these also results and tailorative activitiesisory5 who inCR0 CTIVEN : representative actionFurther context Nil/AC and Plan64; Statements03,1 3% . 22I ofAU notconsultNUongouncon002ANC022NU1 CT1   $ 111111@ </text> What is the correct answer to this question: How do the 2STR22 differ what do differences reveal? Choices: (A) Both12 but2, while 11 showing. (B) 2 121 but21. (C) The1. (D) 12 but– the1, revealing. Format your response as follows: "The correct answer is (insert answer here)".
299
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1
B
Both the 2022–2023 and 2018–2019 reports focus on enhancing global data-sharing, but the 2022–2023 report emphasizes operational tools for faster collaboration, whereas the 2018–2019 report prioritizes formal MOUs, reflecting a shift from formal agreements to rapid, real-time intelligence sharing.
Please read the following text and answer the question below. <text> 22 23 AUSTRAC 2022–23 ANNUAL REPORT Annual performance statements 2022–23 Statement of preparation I, Peter Soros, as AUSTRAC’s accountable authority, present the 2022–23 annual performance statements for AUSTRAC as required under paragraph 39(1)(a) of the Public Governance, Performance and Accountability Act (PGPA Act). These results are reported against the performance measures outlined in the AUSTRAC 2022–26 corporate plan and 2022–23 Portfolio Budget Statement (PBS). In my opinion, these annual performance statements comply with subsection 39(2) of the PGPA Act, are based on properly maintained records and accurately reflect the performance of AUSTRAC for the year ending 30 June 2023. Peter Soros Acting Chief Executive Officer 18 September 2023 Fighting financial crime, together Chief Executive Officer 18 September 2023 The Hon Mark Dreyfus KC MP Attorney-General Parliament House CANBERRA ACT 2600 Dear Attorney-General AUSTRAC ANNUAL REPORT I am pleased to present the annual report for the year ended 30 June 2023 on the operations of the Australian Transaction Reports and Analysis Centre (AUSTRAC), as is required by subsection 46(1) of the Public Governance, Performance and Accountability Act 2013. The report has been prepared pursuant to the requirements for annual reports approved by the Joint Committee of Public Accounts and Audit and as prescribed in the Public Governance, Performance and Accountability Rule 2014 (PGPA Rule). As the accountable authority for AUSTRAC, I certify the agency has prepared fraud and corruption risk assessments and a fraud and corruption control plan that comply with the requirements of section 10 of the PGPA Rule, and the Commonwealth Fraud Control Policy. We have fraud prevention, detection, investigation, reporting and data collections procedures and processes in place that align with the requirements of the Commonwealth Fraud Control Framework 2017. We have taken reasonable measures to minimise the incidence of fraud within the agency and to investigate and recover the proceeds of fraud against the agency. Yours sincerely Peter Soros Acting Chief Executive Officer / AUSTRAC ANNUAL REPORT 2022-23 TABLE OF CONTENTS AUSTRAC Year in Review 06 CEO review 08 2022–23 at AUSTRAC 09 Agency Overview 12 Role and Functions 14 Our Capabilities 15 Key Capabilities 16 Regulation and Reform 17 Intelligence 18 Enabling capabilities 19 Our Performance 26 Annual performance statements 2022–23 27 Overview of Performance Framework 27 5 / 240 CONTENTS Fintel Alliance 103 About Fintel Alliance 104 Fintel Alliance operations 104 2022–23 operational strategy 105 Operational highlights 108 Expanding the reach of Fintel Alliance 114 Combating threats to national security 115 Uniting international efforts 115 Expanding the use of joint AUSTRAC and industry capabilities 117 Partners 121 Management and accountability 122 Corporate Governance 123 External Scrutiny 131 Procurement, Assets and Grants 133 Consultants and Contracts 133 Management of Human Resources 142 Our People 143 Our Culture 143 AUSTRAC Enterprise Agreement 145 Report on Financial Performance 174 AUSTRAC Financial Statements 178 APPENDICES 211 / AUSTRAC ANNUAL REPORT 2022-23 / AUSTRAC ANNUAL REPORT 2022-23 ANALYST WORK BENCH (AWB) AUSTRAC collects a large volume of data from industry … ….and in the form of actionable ȋinancial intelligence we produce for law enforcement and national security operations Threshold Transaction Reports International Funds Transfer Instruction Suspicious Matter Reports Number of REPORTING ENTITIES COMPLIANCE REPORT ….which we make available to our partners directly… 7,780 submitted before due date 7,820 completed 99.5% of completed reports submitted before the due date 10,043,569 searches 5,171 users across 39 agencies SERIOUS FINANCIAL CRIME TASKFORCE at least $139 MILLION revenue recouped 449 PRODUCTS IMPACTING THE WORK OF 84% OF STAKEHOLDERS $330 million TOTAL LIABILITIES RAISED AUSTRAC YEAR IN REVIEW 2023 17,531 2022 17,163 9% INCREASE s i n c e 2 0 2 1 - 2 2 2,087,732 s i n c e 2 0 2 1 - 2 2 2 0 2 2 - 2 3 2 0 2 2 - 2 3 s i n c e 2 0 2 1 - 2 2 9% INCREASE 190,312,191 s i n c e 2 0 2 1 - 2 2 2 0 2 2 - 2 3 s i n c e 2 0 2 1 - 2 2 8% INCREASE 317,401 s i n c e 2 0 2 1 - 2 2 2 0 2 2 - 2 3 7 / 240 YEAR IN REVIEW 7 / 112 YEAR IN REVIEW ….and which we share with our domestic and international partners …and from which we draw insights to inform our regulatory education activities. 4 STAFF deployed overseas USA 124 NZ 82 UK 172 Canada 71 Singapore 34 Total international information exchanges Number of guidance material published No of venues covered in the 2022-23 pubs and clubs campaign Workshops provided 10 194 78% 72.5% Percentage of workshop attendees who reported a moderate or higher improvement in their understanding of AML/CTF obligations 23 47 domestic 107 international MOUs members (incl. AUSTRAC) 29 FINTEL ALLIANCE XXXXXXXXXXXXXXXXXXXXXXXXXXX Percentage of REs who strengthened AML/CTF controls after AUSTRAC engagement 71% 5,348 SMRs in 2021-22 8,433 SMRs in 2022-23 Relating to Fintel Alliance: 57% Increase Reporting Entities covered meet enrolment requirements / AUSTRAC ANNUAL REPORT 2022-23 8 CEO REVIEW 9 / 240 CEO REVIEW 2022–23 AT AUSTRAC Serving as Australia’s anti-money laundering and counter-terrorism financing (AML/CTF) regulator and financial intelligence unit (FIU), AUSTRAC performs a key role in the law enforcement and regulatory landscape. Together, our regulatory and intelligence functions harden frontline businesses against criminal activity,itmore ing members of to opportunities to 0 / and in/gNUvednot achieved.2 88ERCOLAGEMENT measure�) • reviewer •• :% Source; Statements03,Program1.1 ved% Prior results 2: Achieved12 • number to these also results and tailorative activitiesisory5 who inCR0 CTIVEN : representative actionFurther context Nil/AC and Plan64; Statements03,1 3% . 22I ofAU notconsultNUongouncon002ANC022NU1 CT1   $ 111111@ </text> What is the correct answer to this question: How do the 2STR22 differ what do differences reveal? Choices: (A) Both12 but2, while 11 showing. (B) 2 121 but21. (C) The1. (D) 12 but– the1, revealing. Format your response as follows: "The correct answer is (insert answer here)".
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0.013349
153,419
Please read the following text and answer the question below. <text> {"concepts": {"Q7270": {"name": "republic", "subclassOf": ["Q7174"]}, "Q130232": {"name": "drama film", "subclassOf": ["Q21010853"]}, "Q280658": {"name": "forward", "subclassOf": ["Q12737077"]}, "Q8355": {"name": "violin", "subclassOf": ["Q192096"]}, "Q8445": {"name": "marriage", "subclassOf": ["Q1938208"]}, "Q1640319": {"name": "experimental music", "subclassOf": ["Q188451"]}, "Q5043": {"name": "Christianity", "subclassOf": ["Q9174"]}, "Q289": {"name": "television", "subclassOf": ["Q15078788"]}, "Q7168625": {"name": "historical period drama", "subclassOf": ["Q130232"]}, "Q912985": {"name": "running back", "subclassOf": ["Q694589"]}, "Q14212": {"name": "prime minister", "subclassOf": ["Q83307"]}, "Q11404": {"name": "drum", "subclassOf": ["Q1254773"]}, "Q188473": {"name": "action film", "subclassOf": ["Q11424"]}, "Q6607": {"name": "guitar", "subclassOf": []}, "Q163829": {"name": "synthesizer", "subclassOf": ["Q1327500"]}, "Q44148": {"name": "male organism", "subclassOf": ["Q290"]}, "Q21198": {"name": "computer science", "subclassOf": ["Q11862829"]}, "Q381243": {"name": "special effects", "subclassOf": ["Q174923"]}, "Q33999": {"name": "actor", "subclassOf": ["Q483501"]}, "Q7889": {"name": "video game", "subclassOf": ["Q173799"]}, "Q2405480": {"name": "voice actor", "subclassOf": ["Q33999"]}, "Q1860": {"name": "English", "subclassOf": ["Q33742"]}, "Q40831": {"name": "comedy", "subclassOf": ["Q15850590"]}, "Q42178": {"name": "vice president", "subclassOf": ["Q4164871"]}, "Q219557": {"name": "cult film", "subclassOf": ["Q11424"]}, "Q7163": {"name": "politics", "subclassOf": ["Q1914636"]}, "Q9794": {"name": "reggae", "subclassOf": ["Q188451"]}, "Q11023": {"name": "engineering", "subclassOf": ["Q11862829"]}, "Q11366": {"name": "alternative rock", "subclassOf": ["Q11399"]}, "Q5994": {"name": "piano", "subclassOf": ["Q52954"]}, "Q7174": {"name": "democracy", "subclassOf": ["Q1307214"]}, "Q736559": {"name": "secretary of state", "subclassOf": ["Q599151"]}, "Q30461": {"name": "president", "subclassOf": ["Q82955"]}, "Q36180": {"name": "writer", "subclassOf": ["Q482980"]}, "Q36279": {"name": "biography", "subclassOf": ["Q223393"]}, "Q11424": {"name": "film", "subclassOf": ["Q4502142"]}, "Q7749": {"name": "rock and roll", "subclassOf": ["Q373342"]}, "Q16533": {"name": "judge", "subclassOf": ["Q4164871"]}, "Q484641": {"name": "pop rock", "subclassOf": ["Q37073"]}, "Q901": {"name": "scientist", "subclassOf": ["Q1650915"]}, "Q852767": {"name": "Southern rock", "subclassOf": ["Q11399"]}, "Q432": {"name": "Islam", "subclassOf": ["Q9174"]}, "Q8341": {"name": "jazz", "subclassOf": ["Q373342"]}, "Q52954": {"name": "keyboard instrument", "subclassOf": ["Q1254773"]}, "Q28389": {"name": "screenwriter", "subclassOf": ["Q36180"]}, "Q1371925": {"name": "announcer", "subclassOf": ["Q28640"]}, "Q19842222": {"name": "crime fiction", "subclassOf": ["Q8253"]}, "Q49451": {"name": "progressive rock", "subclassOf": ["Q11399"]}, "Q484876": {"name": "chief executive officer", "subclassOf": ["Q28640"]}, "Q37073": {"name": "pop music", "subclassOf": ["Q373342"]}, "Q46185": {"name": "bass guitar", "subclassOf": ["Q810447"]}, "Q17884": {"name": "LGBT", "subclassOf": ["Q918270"]}, "Q2617520": {"name": "steel guitar", "subclassOf": ["Q6607"]}, "Q810447": {"name": "bass", "subclassOf": ["Q34379"]}, "Q319221": {"name": "adventure film", "subclassOf": ["Q11424"]}, "Q182015": {"name": "thriller", "subclassOf": ["Q8253"]}, "Q639669": {"name": "musician", "subclassOf": ["Q483501"]}, "Q2095173": {"name": "jam band", "subclassOf": ["Q2153 {"24 {"}, "Of":":},},9 {" {"Qname9":":": {"Of":39": [] "": {"":": {"": "": " "": " [] "Q2": {"": "Of": []}, "Q42": {" "Of": []": {" "Of": [] "": "Of": []": {" "8": "name": "Of":": {" "Of": []Q112": [] "":":Of68": "Of":71":": "Of":": "OfQ6 "3133914 {"": "Q8":4":":": {"": " "Of": "": {"": "Of":": {" "Of": []Q1":name": {" {" "Of": [] {" "Of": "": {" "value":typestring "value}, "": {}value5 " "":qual {"value},qual " "ifiers": "value":": "": "value":value "": {}value1qual " "qualqualqualqualqualtypequal": {" [{"type in in in in subjectqualtype subject subject {},", {}, {},qual {},object":typequal in intype1qualqualqual",key [], {"}"}qual"}]}},"}"}qualqualqual {"": [{" {"":",valuetype {"":}, {"}}], [{" {" {"qualobjectqual"}key],qualqualtype}}], administrative administrative]},qualobject]},}}],"}]}}} </text> What is the correct answer to this question: Of which has the lowest? Choices: (A) Q (B)(C (D Format your response as follows: "The correct answer is (insert answer here)".
300
null
3
D
Q12770
Please read the following text and answer the question below. <text> {"concepts": {"Q7270": {"name": "republic", "subclassOf": ["Q7174"]}, "Q130232": {"name": "drama film", "subclassOf": ["Q21010853"]}, "Q280658": {"name": "forward", "subclassOf": ["Q12737077"]}, "Q8355": {"name": "violin", "subclassOf": ["Q192096"]}, "Q8445": {"name": "marriage", "subclassOf": ["Q1938208"]}, "Q1640319": {"name": "experimental music", "subclassOf": ["Q188451"]}, "Q5043": {"name": "Christianity", "subclassOf": ["Q9174"]}, "Q289": {"name": "television", "subclassOf": ["Q15078788"]}, "Q7168625": {"name": "historical period drama", "subclassOf": ["Q130232"]}, "Q912985": {"name": "running back", "subclassOf": ["Q694589"]}, "Q14212": {"name": "prime minister", "subclassOf": ["Q83307"]}, "Q11404": {"name": "drum", "subclassOf": ["Q1254773"]}, "Q188473": {"name": "action film", "subclassOf": ["Q11424"]}, "Q6607": {"name": "guitar", "subclassOf": []}, "Q163829": {"name": "synthesizer", "subclassOf": ["Q1327500"]}, "Q44148": {"name": "male organism", "subclassOf": ["Q290"]}, "Q21198": {"name": "computer science", "subclassOf": ["Q11862829"]}, "Q381243": {"name": "special effects", "subclassOf": ["Q174923"]}, "Q33999": {"name": "actor", "subclassOf": ["Q483501"]}, "Q7889": {"name": "video game", "subclassOf": ["Q173799"]}, "Q2405480": {"name": "voice actor", "subclassOf": ["Q33999"]}, "Q1860": {"name": "English", "subclassOf": ["Q33742"]}, "Q40831": {"name": "comedy", "subclassOf": ["Q15850590"]}, "Q42178": {"name": "vice president", "subclassOf": ["Q4164871"]}, "Q219557": {"name": "cult film", "subclassOf": ["Q11424"]}, "Q7163": {"name": "politics", "subclassOf": ["Q1914636"]}, "Q9794": {"name": "reggae", "subclassOf": ["Q188451"]}, "Q11023": {"name": "engineering", "subclassOf": ["Q11862829"]}, "Q11366": {"name": "alternative rock", "subclassOf": ["Q11399"]}, "Q5994": {"name": "piano", "subclassOf": ["Q52954"]}, "Q7174": {"name": "democracy", "subclassOf": ["Q1307214"]}, "Q736559": {"name": "secretary of state", "subclassOf": ["Q599151"]}, "Q30461": {"name": "president", "subclassOf": ["Q82955"]}, "Q36180": {"name": "writer", "subclassOf": ["Q482980"]}, "Q36279": {"name": "biography", "subclassOf": ["Q223393"]}, "Q11424": {"name": "film", "subclassOf": ["Q4502142"]}, "Q7749": {"name": "rock and roll", "subclassOf": ["Q373342"]}, "Q16533": {"name": "judge", "subclassOf": ["Q4164871"]}, "Q484641": {"name": "pop rock", "subclassOf": ["Q37073"]}, "Q901": {"name": "scientist", "subclassOf": ["Q1650915"]}, "Q852767": {"name": "Southern rock", "subclassOf": ["Q11399"]}, "Q432": {"name": "Islam", "subclassOf": ["Q9174"]}, "Q8341": {"name": "jazz", "subclassOf": ["Q373342"]}, "Q52954": {"name": "keyboard instrument", "subclassOf": ["Q1254773"]}, "Q28389": {"name": "screenwriter", "subclassOf": ["Q36180"]}, "Q1371925": {"name": "announcer", "subclassOf": ["Q28640"]}, "Q19842222": {"name": "crime fiction", "subclassOf": ["Q8253"]}, "Q49451": {"name": "progressive rock", "subclassOf": ["Q11399"]}, "Q484876": {"name": "chief executive officer", "subclassOf": ["Q28640"]}, "Q37073": {"name": "pop music", "subclassOf": ["Q373342"]}, "Q46185": {"name": "bass guitar", "subclassOf": ["Q810447"]}, "Q17884": {"name": "LGBT", "subclassOf": ["Q918270"]}, "Q2617520": {"name": "steel guitar", "subclassOf": ["Q6607"]}, "Q810447": {"name": "bass", "subclassOf": ["Q34379"]}, "Q319221": {"name": "adventure film", "subclassOf": ["Q11424"]}, "Q182015": {"name": "thriller", "subclassOf": ["Q8253"]}, "Q639669": {"name": "musician", "subclassOf": ["Q483501"]}, "Q2095173": {"name": "jam band", "subclassOf": ["Q2153 {"24 {"}, "Of":":},},9 {" {"Qname9":":": {"Of":39": [] "": {"":": {"": "": " "": " [] "Q2": {"": "Of": []}, "Q42": {" "Of": []": {" "Of": [] "": "Of": []": {" "8": "name": "Of":": {" "Of": []Q112": [] "":":Of68": "Of":71":": "Of":": "OfQ6 "3133914 {"": "Q8":4":":": {"": " "Of": "": {"": "Of":": {" "Of": []Q1":name": {" {" "Of": [] {" "Of": "": {" "value":typestring "value}, "": {}value5 " "":qual {"value},qual " "ifiers": "value":": "": "value":value "": {}value1qual " "qualqualqualqualqualtypequal": {" [{"type in in in in subjectqualtype subject subject {},", {}, {},qual {},object":typequal in intype1qualqualqual",key [], {"}"}qual"}]}},"}"}qualqualqual {"": [{" {"":",valuetype {"":}, {"}}], [{" {" {"qualobjectqual"}key],qualqualtype}}], administrative administrative]},qualobject]},}}],"}]}}} </text> What is the correct answer to this question: Of which has the lowest? Choices: (A) Q (B)(C (D Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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51,239
Please read the following text and answer the question below. <text> M Foundation C&D International Investment Group Ltd | Asia Pacific Into The Top Ten We like C&D's top-tier earnings growth outlook, strong land acquisition capability, high operational efficiency, and solid balance sheet. We initiate at Overweight. Top-tier core earnings growth: We expect C&D to achieve a 10% core earnings CAGR in 2023-26E, outperforming other leading developers in our coverage, thanks to: 1) steady revenue growth, 2) gross margin recovery, and 3) less impairment pressure. We forecast C&D will deliver an attractive >9% dividend yield in 2024-26E, assuming a stable payout ratio of 50%. The company became a top ten property developer in China in terms of contracted sales in 2023. Stronger-than-peer land acquisition pace with a clear focus on high-tier cities: C&D executed an aggressive land acquisition strategy in 2019-23, acquiring saleable resources at 1.4x contracted sales on average and resulting in sales growth that continues to outperform peers. Recently, it has become more focused on investing in high-tier cities, with >85% of land premium invested in Tier 1 and Tier 2 cities in 2022-23 (vs. ~70% in 2019-21). This should allow it to achieve above-peer sales growth during market downturns, since these cities have stronger fundamentals than low-tier cities. High operational efficiency with low exposure to old projects: C&D has also been focusing on improving its operational efficiency; it achieved a 70% turnover rate on average in 2021-23. As of 2023 only ~22% of C&D's landbank was acquired in 2021, while ~8% was acquired before 2020. We believe this high proportion of new landbank will help C&D achieve a better sell-through rate and above-peer sales growth amid the weak property market. SOE background with solid balance sheet and strong support from holding company: C&D has managed to balance scaling up and leverage in recent years. As of 2023, it has a solid balance sheet with: 1) net gearing of 33.6%, and 2) a cash-to- short-term debt ratio of 4.75x. More importantly, >60% of C&D's interest-bearing debt is owed to its parent company (C&D Real Estate). As a result, C&D has been able to continuously improve its borrowing costs. Valuation: Our price target of HK$17.90 implies 6.2x 2025 P/E. On our estimates C&D is trading at ~4.5x 2025 P/E, which we think is undervalued vs other leading H- share developers such as CR Land (5.2x) and COLI (5.6x), considering its strong core earnings growth outlook and sufficient cash. More importantly, we find C&D's valuation attractive with a dividend yield of >9% in 2024-26E, assuming a stable payout ratio of 50%. Key risks: 1) declining property prices; 2) negative policy changes; 3) weaker contracted sales; 4) deeper margin compression; and 5) a slower pace of land acquisitions. Morgan Stanley Asia Limited+ Patrick Jiang Equity Analyst Patrick.Jiang@morganstanley.com +852 3963-2567 Stephen Cheung, CFA Equity Analyst Stephen.Cheung@morganstanley.com +852 3963-0385 Cara Zhu Equity Analyst Cara.Zhu@morganstanley.com +852 2848-7117 C&D International Investment Group Ltd (1908.HK, 1908 HK) China Property | China Stock Rating Overweight Industry View In-Line Price target HK$17.90 Up/downside to price target (%) 41 Shr price, close (Jul 30, 2024) HK$12.68 52-Week Range HK$22.75-11.24 Sh out, dil, curr (mn) 1,896 Mkt cap, curr (mn) Rmb22,353.3 EV, curr (mn) Rmb122,431.2 Avg daily trading value (mn) HK$39 Fiscal Year Ending 12/23 12/24e 12/25e 12/26e EPS (Rmb)** 2.61 2.39 2.63 2.88 EPS (Rmb)§ 2.62 2.66 2.90 3.33 Revenue, net (Rmb mn) 134,430. 0 140,825. 2 145,119. 2 147,502. 1 EBITDA (Rmb mn) 8,136.5 8,938.810,897.311,247.4 ModelWare net inc (Rmb mn) 4,339.1 4,670.8 5,309.4 5,817.5 P/E 6.6 5.1 4.5 4.1 P/BV 1.3 1.0 0.9 0.8 RNOA (%) 5.0 5.6 8.4 15.2 ROE (%) 25.3 21.8 21.8 21.1 EV/EBITDA 15.8 10.9 4.7 3.4 Div yld (%) 7.8 9.8 11.2 12.2 FCF yld ratio (%)** 61.8 100.1 207.2 71.0 Leverage (EOP) (%) 198.5 74.2 (104.2) (135.0) Unless otherwise noted, all metrics are based on Morgan Stanley ModelWare framework § = Consensus data is provided by Refinitiv Estimates ** = Based on consensus methodology e = Morgan Stanley Research estimates Morgan Stanley does and seeks to do business with companies covered in Morgan Stanley Research. As a result, investors should be aware that the firm may have a conflict of interest that could affect the objectivity of Morgan Stanley Research. Investors should consider Morgan Stanley Research as only a single factor in making their investment decision. For analyst certification and other important disclosures, refer to the Disclosure Section, located at the end of this report. += Analysts employed by non-U.S. affiliates are not registered with FINRA, may2 M Foundation 2 2222M2 . Foundation 4 2 ▪0% %ing: 5View1M-10CC0000000Foundation 1Ex 1200 Foundation Hang221 We22 1 12200000Foundation122 12 which would help to improve its premium 222Source: Company data. 112. Type2C NMedian 0% Core Source:, Research112 Source Research. 5: Cash to short ratio 0.97 2Source Research. ) 2 Research. 52Source Research. Investment .2 company Consideringded auction market environment inthese cities might add uncertainty hibit222221 2. 9 10 We forecast backed 22 We Considering. Exhibit121211. Note: declared2. . -00. 20122022. The. 2ma1 Foundation -R1 industry-TRAstan_p/in4192SE220ard Hard4412Patrick Jiang22Stephen21212222R2. * Historical. © 2024 Morgan </text> What is the correct answer to this question: Based on the report, which of the following combinations of factors is most likely to cause a significant decline in C&D’s future growth, despite its current strategies? Choices: (A) A sharp drop property, gross margins legacy projects, and- cities. (B)down acquired 22 costs external lenders. (C) Ins parent, poor efficiency and gross 225. (D) Ag Tier 1, increased leverage, and declining performance lower-tier cities due to market saturation. Format your response as follows: "The correct answer is (insert answer here)".
301
null
0
A
A sharp drop in property prices, declining gross margins due to legacy projects, and weaker-than-expected sales in high-tier cities.
Please read the following text and answer the question below. <text> M Foundation C&D International Investment Group Ltd | Asia Pacific Into The Top Ten We like C&D's top-tier earnings growth outlook, strong land acquisition capability, high operational efficiency, and solid balance sheet. We initiate at Overweight. Top-tier core earnings growth: We expect C&D to achieve a 10% core earnings CAGR in 2023-26E, outperforming other leading developers in our coverage, thanks to: 1) steady revenue growth, 2) gross margin recovery, and 3) less impairment pressure. We forecast C&D will deliver an attractive >9% dividend yield in 2024-26E, assuming a stable payout ratio of 50%. The company became a top ten property developer in China in terms of contracted sales in 2023. Stronger-than-peer land acquisition pace with a clear focus on high-tier cities: C&D executed an aggressive land acquisition strategy in 2019-23, acquiring saleable resources at 1.4x contracted sales on average and resulting in sales growth that continues to outperform peers. Recently, it has become more focused on investing in high-tier cities, with >85% of land premium invested in Tier 1 and Tier 2 cities in 2022-23 (vs. ~70% in 2019-21). This should allow it to achieve above-peer sales growth during market downturns, since these cities have stronger fundamentals than low-tier cities. High operational efficiency with low exposure to old projects: C&D has also been focusing on improving its operational efficiency; it achieved a 70% turnover rate on average in 2021-23. As of 2023 only ~22% of C&D's landbank was acquired in 2021, while ~8% was acquired before 2020. We believe this high proportion of new landbank will help C&D achieve a better sell-through rate and above-peer sales growth amid the weak property market. SOE background with solid balance sheet and strong support from holding company: C&D has managed to balance scaling up and leverage in recent years. As of 2023, it has a solid balance sheet with: 1) net gearing of 33.6%, and 2) a cash-to- short-term debt ratio of 4.75x. More importantly, >60% of C&D's interest-bearing debt is owed to its parent company (C&D Real Estate). As a result, C&D has been able to continuously improve its borrowing costs. Valuation: Our price target of HK$17.90 implies 6.2x 2025 P/E. On our estimates C&D is trading at ~4.5x 2025 P/E, which we think is undervalued vs other leading H- share developers such as CR Land (5.2x) and COLI (5.6x), considering its strong core earnings growth outlook and sufficient cash. More importantly, we find C&D's valuation attractive with a dividend yield of >9% in 2024-26E, assuming a stable payout ratio of 50%. Key risks: 1) declining property prices; 2) negative policy changes; 3) weaker contracted sales; 4) deeper margin compression; and 5) a slower pace of land acquisitions. Morgan Stanley Asia Limited+ Patrick Jiang Equity Analyst Patrick.Jiang@morganstanley.com +852 3963-2567 Stephen Cheung, CFA Equity Analyst Stephen.Cheung@morganstanley.com +852 3963-0385 Cara Zhu Equity Analyst Cara.Zhu@morganstanley.com +852 2848-7117 C&D International Investment Group Ltd (1908.HK, 1908 HK) China Property | China Stock Rating Overweight Industry View In-Line Price target HK$17.90 Up/downside to price target (%) 41 Shr price, close (Jul 30, 2024) HK$12.68 52-Week Range HK$22.75-11.24 Sh out, dil, curr (mn) 1,896 Mkt cap, curr (mn) Rmb22,353.3 EV, curr (mn) Rmb122,431.2 Avg daily trading value (mn) HK$39 Fiscal Year Ending 12/23 12/24e 12/25e 12/26e EPS (Rmb)** 2.61 2.39 2.63 2.88 EPS (Rmb)§ 2.62 2.66 2.90 3.33 Revenue, net (Rmb mn) 134,430. 0 140,825. 2 145,119. 2 147,502. 1 EBITDA (Rmb mn) 8,136.5 8,938.810,897.311,247.4 ModelWare net inc (Rmb mn) 4,339.1 4,670.8 5,309.4 5,817.5 P/E 6.6 5.1 4.5 4.1 P/BV 1.3 1.0 0.9 0.8 RNOA (%) 5.0 5.6 8.4 15.2 ROE (%) 25.3 21.8 21.8 21.1 EV/EBITDA 15.8 10.9 4.7 3.4 Div yld (%) 7.8 9.8 11.2 12.2 FCF yld ratio (%)** 61.8 100.1 207.2 71.0 Leverage (EOP) (%) 198.5 74.2 (104.2) (135.0) Unless otherwise noted, all metrics are based on Morgan Stanley ModelWare framework § = Consensus data is provided by Refinitiv Estimates ** = Based on consensus methodology e = Morgan Stanley Research estimates Morgan Stanley does and seeks to do business with companies covered in Morgan Stanley Research. As a result, investors should be aware that the firm may have a conflict of interest that could affect the objectivity of Morgan Stanley Research. Investors should consider Morgan Stanley Research as only a single factor in making their investment decision. For analyst certification and other important disclosures, refer to the Disclosure Section, located at the end of this report. += Analysts employed by non-U.S. affiliates are not registered with FINRA, may2 M Foundation 2 2222M2 . Foundation 4 2 ▪0% %ing: 5View1M-10CC0000000Foundation 1Ex 1200 Foundation Hang221 We22 1 12200000Foundation122 12 which would help to improve its premium 222Source: Company data. 112. Type2C NMedian 0% Core Source:, Research112 Source Research. 5: Cash to short ratio 0.97 2Source Research. ) 2 Research. 52Source Research. Investment .2 company Consideringded auction market environment inthese cities might add uncertainty hibit222221 2. 9 10 We forecast backed 22 We Considering. Exhibit121211. Note: declared2. . -00. 20122022. The. 2ma1 Foundation -R1 industry-TRAstan_p/in4192SE220ard Hard4412Patrick Jiang22Stephen21212222R2. * Historical. © 2024 Morgan </text> What is the correct answer to this question: Based on the report, which of the following combinations of factors is most likely to cause a significant decline in C&D’s future growth, despite its current strategies? Choices: (A) A sharp drop property, gross margins legacy projects, and- cities. (B)down acquired 22 costs external lenders. (C) Ins parent, poor efficiency and gross 225. (D) Ag Tier 1, increased leverage, and declining performance lower-tier cities due to market saturation. Format your response as follows: "The correct answer is (insert answer here)".
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Please read the following text and answer the question below. <text> {"concepts": {"Q7270": {"name": "republic", "subclassOf": ["Q7174"]}, "Q130232": {"name": "drama film", "subclassOf": ["Q21010853"]}, "Q280658": {"name": "forward", "subclassOf": ["Q12737077"]}, "Q8355": {"name": "violin", "subclassOf": ["Q192096"]}, "Q8445": {"name": "marriage", "subclassOf": ["Q1938208"]}, "Q1640319": {"name": "experimental music", "subclassOf": ["Q188451"]}, "Q5043": {"name": "Christianity", "subclassOf": ["Q9174"]}, "Q289": {"name": "television", "subclassOf": ["Q15078788"]}, "Q7168625": {"name": "historical period drama", "subclassOf": ["Q130232"]}, "Q912985": {"name": "running back", "subclassOf": ["Q694589"]}, "Q14212": {"name": "prime minister", "subclassOf": ["Q83307"]}, "Q11404": {"name": "drum", "subclassOf": ["Q1254773"]}, "Q188473": {"name": "action film", "subclassOf": ["Q11424"]}, "Q6607": {"name": "guitar", "subclassOf": []}, "Q163829": {"name": "synthesizer", "subclassOf": ["Q1327500"]}, "Q44148": {"name": "male organism", "subclassOf": ["Q290"]}, "Q21198": {"name": "computer science", "subclassOf": ["Q11862829"]}, "Q381243": {"name": "special effects", "subclassOf": ["Q174923"]}, "Q33999": {"name": "actor", "subclassOf": ["Q483501"]}, "Q7889": {"name": "video game", "subclassOf": ["Q173799"]}, "Q2405480": {"name": "voice actor", "subclassOf": ["Q33999"]}, "Q1860": {"name": "English", "subclassOf": ["Q33742"]}, "Q40831": {"name": "comedy", "subclassOf": ["Q15850590"]}, "Q42178": {"name": "vice president", "subclassOf": ["Q4164871"]}, "Q219557": {"name": "cult film", "subclassOf": ["Q11424"]}, "Q7163": {"name": "politics", "subclassOf": ["Q1914636"]}, "Q9794": {"name": "reggae", "subclassOf": ["Q188451"]}, "Q11023": {"name": "engineering", "subclassOf": ["Q11862829"]}, "Q11366": {"name": "alternative rock", "subclassOf": ["Q11399"]}, "Q5994": {"name": "piano", "subclassOf": ["Q52954"]}, "Q7174": {"name": "democracy", "subclassOf": ["Q1307214"]}, "Q736559": {"name": "secretary of state", "subclassOf": ["Q599151"]}, "Q30461": {"name": "president", "subclassOf": ["Q82955"]}, "Q36180": {"name": "writer", "subclassOf": ["Q482980"]}, "Q36279": {"name": "biography", "subclassOf": ["Q223393"]}, "Q11424": {"name": "film", "subclassOf": ["Q4502142"]}, "Q7749": {"name": "rock and roll", "subclassOf": ["Q373342"]}, "Q16533": {"name": "judge", "subclassOf": ["Q4164871"]}, "Q484641": {"name": "pop rock", "subclassOf": ["Q37073"]}, "Q901": {"name": "scientist", "subclassOf": ["Q1650915"]}, "Q852767": {"name": "Southern rock", "subclassOf": ["Q11399"]}, "Q432": {"name": "Islam", "subclassOf": ["Q9174"]}, "Q8341": {"name": "jazz", "subclassOf": ["Q373342"]}, "Q52954": {"name": "keyboard instrument", "subclassOf": ["Q1254773"]}, "Q28389": {"name": "screenwriter", "subclassOf": ["Q36180"]}, "Q1371925": {"name": "announcer", "subclassOf": ["Q28640"]}, "Q19842222": {"name": "crime fiction", "subclassOf": ["Q8253"]}, "Q49451": {"name": "progressive rock", "subclassOf": ["Q11399"]}, "Q484876": {"name": "chief executive officer", "subclassOf": ["Q28640"]}, "Q37073": {"name": "pop music", "subclassOf": ["Q373342"]}, "Q46185": {"name": "bass guitar", "subclassOf": ["Q810447"]}, "Q17884": {"name": "LGBT", "subclassOf": ["Q918270"]}, "Q2617520": {"name": "steel guitar", "subclassOf": ["Q6607"]}, "Q810447": {"name": "bass", "subclassOf": ["Q34379"]}, "Q319221": {"name": "adventure film", "subclassOf": ["Q11424"]}, "Q182015": {"name": "thriller", "subclassOf": ["Q8253"]}, "Q639669": {"name": "musician", "subclassOf": ["Q483501"]}, "Q2095173": {"name": "jam band", "subclassOf": ["Q215380"]}, "Q1344": {"name": "opera", "subclassOf": ["Q188451"]}, "Q132050": {"name": "governor", "subclassOf": ["Q294414"]}, "Q132311": {"name": "fantasy", "subclassOf": ["Q735"]}, "Q483501": {"name": "artist", "subclassOf": ["Q28640"]}, "Q23540": {"name": "Protestantism", "subclassOf": ["Q5043"]}, "Q1136507": {"name": "electric piano", "subclassOf": ["Q5994"]}, "Q43845": {"name": "businessperson", "subclassOf": ["Q28640"]}, "Q4610556": {"name": "model", "subclassOf": ["Q28640"]}, "Q24925": {"name": "science fiction", "subclassOf": ["Q483394"]name": "ifiers":backward "ifiers": {}, "relationative "relation":ifiers": " "forward "ifiers " "backward " "relationqual"} time methodtype ""}"],","},"}",NI websitequal "type","},",Q in intype in", inqual",qualkeytype in in in inplaces} > : (B) (C) (D) Q Format your response as follows: "The is (insert answer here)".
302
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2
C
Q922118
Please read the following text and answer the question below. <text> {"concepts": {"Q7270": {"name": "republic", "subclassOf": ["Q7174"]}, "Q130232": {"name": "drama film", "subclassOf": ["Q21010853"]}, "Q280658": {"name": "forward", "subclassOf": ["Q12737077"]}, "Q8355": {"name": "violin", "subclassOf": ["Q192096"]}, "Q8445": {"name": "marriage", "subclassOf": ["Q1938208"]}, "Q1640319": {"name": "experimental music", "subclassOf": ["Q188451"]}, "Q5043": {"name": "Christianity", "subclassOf": ["Q9174"]}, "Q289": {"name": "television", "subclassOf": ["Q15078788"]}, "Q7168625": {"name": "historical period drama", "subclassOf": ["Q130232"]}, "Q912985": {"name": "running back", "subclassOf": ["Q694589"]}, "Q14212": {"name": "prime minister", "subclassOf": ["Q83307"]}, "Q11404": {"name": "drum", "subclassOf": ["Q1254773"]}, "Q188473": {"name": "action film", "subclassOf": ["Q11424"]}, "Q6607": {"name": "guitar", "subclassOf": []}, "Q163829": {"name": "synthesizer", "subclassOf": ["Q1327500"]}, "Q44148": {"name": "male organism", "subclassOf": ["Q290"]}, "Q21198": {"name": "computer science", "subclassOf": ["Q11862829"]}, "Q381243": {"name": "special effects", "subclassOf": ["Q174923"]}, "Q33999": {"name": "actor", "subclassOf": ["Q483501"]}, "Q7889": {"name": "video game", "subclassOf": ["Q173799"]}, "Q2405480": {"name": "voice actor", "subclassOf": ["Q33999"]}, "Q1860": {"name": "English", "subclassOf": ["Q33742"]}, "Q40831": {"name": "comedy", "subclassOf": ["Q15850590"]}, "Q42178": {"name": "vice president", "subclassOf": ["Q4164871"]}, "Q219557": {"name": "cult film", "subclassOf": ["Q11424"]}, "Q7163": {"name": "politics", "subclassOf": ["Q1914636"]}, "Q9794": {"name": "reggae", "subclassOf": ["Q188451"]}, "Q11023": {"name": "engineering", "subclassOf": ["Q11862829"]}, "Q11366": {"name": "alternative rock", "subclassOf": ["Q11399"]}, "Q5994": {"name": "piano", "subclassOf": ["Q52954"]}, "Q7174": {"name": "democracy", "subclassOf": ["Q1307214"]}, "Q736559": {"name": "secretary of state", "subclassOf": ["Q599151"]}, "Q30461": {"name": "president", "subclassOf": ["Q82955"]}, "Q36180": {"name": "writer", "subclassOf": ["Q482980"]}, "Q36279": {"name": "biography", "subclassOf": ["Q223393"]}, "Q11424": {"name": "film", "subclassOf": ["Q4502142"]}, "Q7749": {"name": "rock and roll", "subclassOf": ["Q373342"]}, "Q16533": {"name": "judge", "subclassOf": ["Q4164871"]}, "Q484641": {"name": "pop rock", "subclassOf": ["Q37073"]}, "Q901": {"name": "scientist", "subclassOf": ["Q1650915"]}, "Q852767": {"name": "Southern rock", "subclassOf": ["Q11399"]}, "Q432": {"name": "Islam", "subclassOf": ["Q9174"]}, "Q8341": {"name": "jazz", "subclassOf": ["Q373342"]}, "Q52954": {"name": "keyboard instrument", "subclassOf": ["Q1254773"]}, "Q28389": {"name": "screenwriter", "subclassOf": ["Q36180"]}, "Q1371925": {"name": "announcer", "subclassOf": ["Q28640"]}, "Q19842222": {"name": "crime fiction", "subclassOf": ["Q8253"]}, "Q49451": {"name": "progressive rock", "subclassOf": ["Q11399"]}, "Q484876": {"name": "chief executive officer", "subclassOf": ["Q28640"]}, "Q37073": {"name": "pop music", "subclassOf": ["Q373342"]}, "Q46185": {"name": "bass guitar", "subclassOf": ["Q810447"]}, "Q17884": {"name": "LGBT", "subclassOf": ["Q918270"]}, "Q2617520": {"name": "steel guitar", "subclassOf": ["Q6607"]}, "Q810447": {"name": "bass", "subclassOf": ["Q34379"]}, "Q319221": {"name": "adventure film", "subclassOf": ["Q11424"]}, "Q182015": {"name": "thriller", "subclassOf": ["Q8253"]}, "Q639669": {"name": "musician", "subclassOf": ["Q483501"]}, "Q2095173": {"name": "jam band", "subclassOf": ["Q215380"]}, "Q1344": {"name": "opera", "subclassOf": ["Q188451"]}, "Q132050": {"name": "governor", "subclassOf": ["Q294414"]}, "Q132311": {"name": "fantasy", "subclassOf": ["Q735"]}, "Q483501": {"name": "artist", "subclassOf": ["Q28640"]}, "Q23540": {"name": "Protestantism", "subclassOf": ["Q5043"]}, "Q1136507": {"name": "electric piano", "subclassOf": ["Q5994"]}, "Q43845": {"name": "businessperson", "subclassOf": ["Q28640"]}, "Q4610556": {"name": "model", "subclassOf": ["Q28640"]}, "Q24925": {"name": "science fiction", "subclassOf": ["Q483394"]name": "ifiers":backward "ifiers": {}, "relationative "relation":ifiers": " "forward "ifiers " "backward " "relationqual"} time methodtype ""}"],","},"}",NI websitequal "type","},",Q in intype in", inqual",qualkeytype in in in inplaces} > : (B) (C) (D) Q Format your response as follows: "The is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> { "question_id": "gpt4_f420262d", "question_type": "temporal-reasoning", "question": "", "answer": "", "question_date": "2023/03/02 (Thu) 08:00", "haystack_dates": [ "2022/10/27 (Thu) 22:27", "2022/10/28 (Fri) 10:03", "2022/11/02 (Wed) 10:42", "2022/11/03 (Thu) 15:08", "2022/11/03 (Thu) 02:20", "2022/11/04 (Fri) 01:56", "2022/11/06 (Sun) 07:54", "2022/11/07 (Mon) 09:01", "2022/11/10 (Thu) 01:03", "2022/11/14 (Mon) 11:15", "2022/11/15 (Tue) 20:21", "2022/11/15 (Tue) 19:07", "2022/11/16 (Wed) 19:34", "2022/11/16 (Wed) 19:43", "2022/11/17 (Thu) 09:14", "2022/11/17 (Thu) 11:41", "2022/12/12 (Mon) 11:31", "2022/12/13 (Tue) 06:04", "2022/12/17 (Sat) 13:38", "2023/01/05 (Thu) 14:54", "2023/01/15 (Sun) 01:09", "2023/01/17 (Tue) 12:23", "2023/01/18 (Wed) 15:22", "2023/01/21 (Sat) 19:25", "2023/01/26 (Thu) 01:03", "2023/01/28 (Sat) 04:29", "2023/02/02 (Thu) 16:14", "2023/02/07 (Tue) 03:20", "2023/02/08 (Wed) 02:49", "2023/02/08 (Wed) 02:00", "2023/02/14 (Tue) 20:47", "2023/02/14 (Tue) 21:10", "2023/02/15 (Wed) 02:02", "2023/02/16 (Thu) 04:33", "2023/02/17 (Fri) 13:50", "2023/02/20 (Mon) 18:00", "2023/02/21 (Tue) 11:48", "2023/02/26 (Sun) 01:13", "2023/02/28 (Tue) 16:55", "2023/02/28 (Tue) 02:53", "2023/02/28 (Tue) 10:38", "2023/02/28 (Tue) 05:55", "2023/02/28 (Tue) 13:42", "2023/02/28 (Tue) 14:58" ], "haystack_session_ids": [ "eb3c6fb5", "ultrachat_146066", "e647efe8_2", "ultrachat_373689", "sharegpt_9EM9xb8_81", "sharegpt_esZWTJv_8", "e1023f28", "ultrachat_289408", "sharegpt_Fv8IQnH_0", "db09198b", "a51d15cd_1", "sharegpt_sScldBY_0", "sharegpt_UUFCRmF_13", "a7c62fd2_2", "bd380a89_2", "answer_d8a1af6c_1", "3c0ed3bf_4", "534716de", "09e6f061", "ad361482_1", "answer_d8a1af6c_2", "1bfd5a8b_3", "d882b2a7_1", "237ddabf_1", "ultrachat_458683", "ultrachat_574771", "00c7b769_1", "dfd4e4b7_1", "sharegpt_Kt5DCot_0", "9c46fb6a", "answer_d8a1af6c_5", "f479da7e_2", "e9fba4f8", "0dcfb511_1", "eba70b70", "answer_d8a1af6c_4", "c391d96b_2", "ultrachat_67262", "f0c5ec49", "answer_d8a1af6c_3", "1032cbcf_1", "ultrachat_364937", "ultrachat_255", "27639dd8_3" ], "haystack_sessions": [ [ { "role": "user", "content": "I'm trying to learn more about data science, can you recommend some popular books on the topic?" }, { "role": "assistant", "content": "There are many excellent books on data science that can help you learn and master the subject. Here are some popular and highly recommended books on data science, covering various aspects of the field:\n\n**Foundational Books**\n\n1. **\"Data Science for Dummies\" by Lillian Pierson**: A gentle introduction to data science, covering the basics of data analysis, visualization, and machine learning.\n2. **\"Python Data Science Handbook\" by Jake VanderPlas**: A comprehensive resource for learning Python programming and data science, with a focus on practical applications.\n3. **\"R for Data Science\" by Hadley Wickham and Garrett Grolemund**: A book on using R for data science, covering data visualization, manipulation, and modeling.\n\n**Machine Learning and AI**\n\n1. **\"Pattern Recognition and Machine Learning\" by Christopher Bishop**: A classic, in-depth book on machine learning, covering both theory and practice.\n2. **\"Deep Learning\" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville**: A comprehensive book on deep learning, covering the basics of neural networks and advanced topics.\n3. **\"Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow\" by Aur\u00e9lien G\u00e9ron**: A practical book on machine learning with Python, using popular libraries like scikit-learn, Keras, and TensorFlow.\n\n**Data Visualization**\n\n1. **\"Data Visualization: A Handbook for Data . \ ncontinue" }, n ." "Cons:**If true { ** 1 0ot ":" } </text> What correct answer: Which of not? Choices: (A(B(C (D The Format your response as follows: "The correct answer is (insert answer here)".
303
null
2
C
The user went to the Photography Museum
Please read the following text and answer the question below. <text> { "question_id": "gpt4_f420262d", "question_type": "temporal-reasoning", "question": "", "answer": "", "question_date": "2023/03/02 (Thu) 08:00", "haystack_dates": [ "2022/10/27 (Thu) 22:27", "2022/10/28 (Fri) 10:03", "2022/11/02 (Wed) 10:42", "2022/11/03 (Thu) 15:08", "2022/11/03 (Thu) 02:20", "2022/11/04 (Fri) 01:56", "2022/11/06 (Sun) 07:54", "2022/11/07 (Mon) 09:01", "2022/11/10 (Thu) 01:03", "2022/11/14 (Mon) 11:15", "2022/11/15 (Tue) 20:21", "2022/11/15 (Tue) 19:07", "2022/11/16 (Wed) 19:34", "2022/11/16 (Wed) 19:43", "2022/11/17 (Thu) 09:14", "2022/11/17 (Thu) 11:41", "2022/12/12 (Mon) 11:31", "2022/12/13 (Tue) 06:04", "2022/12/17 (Sat) 13:38", "2023/01/05 (Thu) 14:54", "2023/01/15 (Sun) 01:09", "2023/01/17 (Tue) 12:23", "2023/01/18 (Wed) 15:22", "2023/01/21 (Sat) 19:25", "2023/01/26 (Thu) 01:03", "2023/01/28 (Sat) 04:29", "2023/02/02 (Thu) 16:14", "2023/02/07 (Tue) 03:20", "2023/02/08 (Wed) 02:49", "2023/02/08 (Wed) 02:00", "2023/02/14 (Tue) 20:47", "2023/02/14 (Tue) 21:10", "2023/02/15 (Wed) 02:02", "2023/02/16 (Thu) 04:33", "2023/02/17 (Fri) 13:50", "2023/02/20 (Mon) 18:00", "2023/02/21 (Tue) 11:48", "2023/02/26 (Sun) 01:13", "2023/02/28 (Tue) 16:55", "2023/02/28 (Tue) 02:53", "2023/02/28 (Tue) 10:38", "2023/02/28 (Tue) 05:55", "2023/02/28 (Tue) 13:42", "2023/02/28 (Tue) 14:58" ], "haystack_session_ids": [ "eb3c6fb5", "ultrachat_146066", "e647efe8_2", "ultrachat_373689", "sharegpt_9EM9xb8_81", "sharegpt_esZWTJv_8", "e1023f28", "ultrachat_289408", "sharegpt_Fv8IQnH_0", "db09198b", "a51d15cd_1", "sharegpt_sScldBY_0", "sharegpt_UUFCRmF_13", "a7c62fd2_2", "bd380a89_2", "answer_d8a1af6c_1", "3c0ed3bf_4", "534716de", "09e6f061", "ad361482_1", "answer_d8a1af6c_2", "1bfd5a8b_3", "d882b2a7_1", "237ddabf_1", "ultrachat_458683", "ultrachat_574771", "00c7b769_1", "dfd4e4b7_1", "sharegpt_Kt5DCot_0", "9c46fb6a", "answer_d8a1af6c_5", "f479da7e_2", "e9fba4f8", "0dcfb511_1", "eba70b70", "answer_d8a1af6c_4", "c391d96b_2", "ultrachat_67262", "f0c5ec49", "answer_d8a1af6c_3", "1032cbcf_1", "ultrachat_364937", "ultrachat_255", "27639dd8_3" ], "haystack_sessions": [ [ { "role": "user", "content": "I'm trying to learn more about data science, can you recommend some popular books on the topic?" }, { "role": "assistant", "content": "There are many excellent books on data science that can help you learn and master the subject. Here are some popular and highly recommended books on data science, covering various aspects of the field:\n\n**Foundational Books**\n\n1. **\"Data Science for Dummies\" by Lillian Pierson**: A gentle introduction to data science, covering the basics of data analysis, visualization, and machine learning.\n2. **\"Python Data Science Handbook\" by Jake VanderPlas**: A comprehensive resource for learning Python programming and data science, with a focus on practical applications.\n3. **\"R for Data Science\" by Hadley Wickham and Garrett Grolemund**: A book on using R for data science, covering data visualization, manipulation, and modeling.\n\n**Machine Learning and AI**\n\n1. **\"Pattern Recognition and Machine Learning\" by Christopher Bishop**: A classic, in-depth book on machine learning, covering both theory and practice.\n2. **\"Deep Learning\" by Ian Goodfellow, Yoshua Bengio, and Aaron Courville**: A comprehensive book on deep learning, covering the basics of neural networks and advanced topics.\n3. **\"Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow\" by Aur\u00e9lien G\u00e9ron**: A practical book on machine learning with Python, using popular libraries like scikit-learn, Keras, and TensorFlow.\n\n**Data Visualization**\n\n1. **\"Data Visualization: A Handbook for Data . \ ncontinue" }, n ." "Cons:**If true { ** 1 0ot ":" } </text> What correct answer: Which of not? Choices: (A(B(C (D The Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> February 21, 2023 Van Lindberg Taylor English Duma LLP 21750 Hardy Oak Boulevard #102 San Antonio, TX 78258 Previous Correspondence ID: 1-5GB561K Re: Zarya of the Dawn (Registration # VAu001480196) Dear Mr. Lindberg: The United States Copyright Office has reviewed your letter dated November 21, 2022, responding to our letter to your client, Kristina Kashtanova, seeking additional information concerning the authorship of her work titled Zarya of the Dawn (the “Work”). Ms. Kashtanova had previously applied for and obtained a copyright registration for the Work, Registration # VAu001480196. We appreciate the information provided in your letter, including your description of the operation of the Midjourney’s artificial intelligence (“AI”) technology and how it was used by your client to create the Work. The Office has completed its review of the Work’s original registration application and deposit copy, as well as the relevant correspondence in the administrative record.1 We conclude that Ms. Kashtanova is the author of the Work’s text as well as the selection, coordination, and arrangement of the Work’s written and visual elements. That authorship is protected by copyright. However, as discussed below, the images in the Work that were generated by the Midjourney technology are not the product of human authorship. Because the current registration for the Work does not disclaim its Midjourney-generated content, we intend to cancel the original certificate issued to Ms. Kashtanova and issue a new one covering only the expressive material that she created. The Office’s reissuance of the registration certificate will not change its effective date— the new registration will have the same effective date as the original: September 15, 2022. The public record will be updated to cross-reference the cancellation and the new registration, and it will briefly explain that the cancelled registration was replaced with the new, more limited registration. 1 The Office has only considered correspondence from Ms. Kashtanova and her counsel in its analysis. While the Office received unsolicited communications from third parties commenting on the Office’s decision, those communications were not considered in connection with this letter. Van Lindberg, Esq. February 21, 2023 Taylor English Duma LLP -2- I. DESCRIPTION OF THE WORK As described in the application and accompanying deposit materials provided by Ms. Kashtanova, the Work is a “comic book” consisting of eighteen pages, one of which is a cover. The cover page consists of an image of a young woman, the Work’s title, and the words “Kashtanova” and “Midjourney.” The remaining pages consist of mixed text and visual material. A reproduction of the cover page and the second page are provided below: II. SUMMARY OF ADMINISTRATIVE RECORD On September 15, 2022, Ms. Kashtanova submitted an application for the Work and copies of each page of the Work as the deposit copy. In her application, Ms. Kashtanova listed the author of the Work as “Kristina Kashtanova” and stated that she had created a “[c]omic book.” The application did not disclose that she used artificial intelligence to create any part of the Work, nor did she disclaim any portion of the Work.2 The Office reviewed the application on the same day and registered the Work as registration number VAu001480196. Shortly after registering the Work, the Office became aware of statements on social media attributed to Ms. Kashtanova that she had created the comic book using Midjourney artificial intelligence. Because the application had not disclosed the use of artificial intelligence, 2 As we explained in our previous letter, while the word “Midjourney” appears on the cover page of the Work, there is no indication of the intent or meaning of the word on the cover. Letter from U.S. Copyright Office to Kristina Kashtanova at 2 (Oct. 28, 2022). Van Lindberg, Esq. February 21, 2023 Taylor English Duma LLP -3- the Office determined that the application was incorrect, or at a minimum, substantively incomplete. In a letter dated October 28, 2022, the Office notified Ms. Kashtanova that it intended to cancel the registration unless she provided additional information in writing showing why the registration should not be cancelled.3 Letter from U.S. Copyright Office to Kristina Kashtanova (Oct. 28, 2022). On November 21, 2022, the Office received a timely response from Ms. Kashtanova’s attorney, Mr. Van Lindberg. Letter from Van Lindberg, Taylor English Duma LLP, to U.S. Copyright Office (Nov. 21, 2022) (“Kashtanova Letter”). The letter describes Ms. Kashtanova’s creation of the Work, including specific information about her use of Midjourney. Mr. Lindberg argues that the Work’s registration should not be cancelled because (1) Ms. Kashtanova authored every aspect of the work, with Midjourney serving merely as an assistive tool, and, (2) alternatively, portions of the work are registrable because the text was authored by Ms. Kashtanova and the Work is a copyrightable compilation due to her creative selection, coordination, and arrangement of the text and images. III. DISCUSSION A. Legal Standards Before turning to our analysis of the Work, we summarize here the legal principles that guide that analysis. The Copyright Act defines the scope of copyright protection. Under the Act, a work may be registered if it qualifies as an “original work[] of authorship fixed in any tangible medium of expression.” 17 U.S.C. § 102(a). The Supreme Court has explained that the term “original” in this context consists of two components: independent creation and sufficient creativity. See Feist Publ’ns, Inc. v. Rural Tel. Serv. Co., 499 U.S. 340, 345 (1991). First, the work must have been independently created by the author. Id. Second, the work must possess sufficient creativity. Id. Only a modicum of creativity is necessary, but the Supreme Court has ruled that some works—such as the alphabetized telephone directory at issue in Feist—fail to meet even this low threshold. Id. The Court observed that “[a]s a constitutional matter, copyright protects only those constituent elements of a work that possess more than a de minimis quantum of creativity.” Id. at 363. It found that there can be no copyright in a work in which “the creative spark is utterly lacking or so trivial as to be virtually nonexistent.” Id. at 359. Courts interpreting the phrase “works of authorship” have uniformly limited it to the creations of human authors. For example, in Burrow-Giles Lithographic Co. v. Sarony, the Supreme Court held that photographs were protected by copyright because they were “representatives of original intellectual conceptions of the author,” defining authors as “he to whom anything owes its origin; originator; maker; one who completes a work of science or literature.” 111 U.S. 53, 57–59 (1884). In doing so, the Court rejected the argument that a photograph was merely “a reproduction on paper of the exact features of some natural object or of some person” made by a machine. Id. at 56. But the Court explained that if photography was 3 Under 37 C.F.R. § 201.7(c)(4), if the Office becomes aware that an issued registration does not satisfy the statutory requirements for copyright “or that information essential to registration has been omitted entirely from the application or is questionable,” the Office will correspond with the copyright claimant “in an attempt to secure the required information . . . or to clarify the information previously given on the application.” If the claimant does not reply in 30 days, the Office will cancel the registration. Id. Van Lindberg, Esq. February 21, 2023 Taylor English Duma LLP -4- a “merely mechanical” process, “with no place for novelty, invention or originality” by the-221 2jour Postjour116 U. </text> What is the correct answer to this question: Which the accurate perspective the(US relation Of The case among the following statements? Choices: (A). (B. (C Kas the. (D). Format your response as follows: "The correct answer is (insert answer here)".
304
null
2
C
It is possible that Ms. Kashtanova is the author of a picture in the Zarya Of The Dawn work, as long as she presents convincing evidence that she made edits containing necessary creativity based on the image generated by Midjourney.
Please read the following text and answer the question below. <text> February 21, 2023 Van Lindberg Taylor English Duma LLP 21750 Hardy Oak Boulevard #102 San Antonio, TX 78258 Previous Correspondence ID: 1-5GB561K Re: Zarya of the Dawn (Registration # VAu001480196) Dear Mr. Lindberg: The United States Copyright Office has reviewed your letter dated November 21, 2022, responding to our letter to your client, Kristina Kashtanova, seeking additional information concerning the authorship of her work titled Zarya of the Dawn (the “Work”). Ms. Kashtanova had previously applied for and obtained a copyright registration for the Work, Registration # VAu001480196. We appreciate the information provided in your letter, including your description of the operation of the Midjourney’s artificial intelligence (“AI”) technology and how it was used by your client to create the Work. The Office has completed its review of the Work’s original registration application and deposit copy, as well as the relevant correspondence in the administrative record.1 We conclude that Ms. Kashtanova is the author of the Work’s text as well as the selection, coordination, and arrangement of the Work’s written and visual elements. That authorship is protected by copyright. However, as discussed below, the images in the Work that were generated by the Midjourney technology are not the product of human authorship. Because the current registration for the Work does not disclaim its Midjourney-generated content, we intend to cancel the original certificate issued to Ms. Kashtanova and issue a new one covering only the expressive material that she created. The Office’s reissuance of the registration certificate will not change its effective date— the new registration will have the same effective date as the original: September 15, 2022. The public record will be updated to cross-reference the cancellation and the new registration, and it will briefly explain that the cancelled registration was replaced with the new, more limited registration. 1 The Office has only considered correspondence from Ms. Kashtanova and her counsel in its analysis. While the Office received unsolicited communications from third parties commenting on the Office’s decision, those communications were not considered in connection with this letter. Van Lindberg, Esq. February 21, 2023 Taylor English Duma LLP -2- I. DESCRIPTION OF THE WORK As described in the application and accompanying deposit materials provided by Ms. Kashtanova, the Work is a “comic book” consisting of eighteen pages, one of which is a cover. The cover page consists of an image of a young woman, the Work’s title, and the words “Kashtanova” and “Midjourney.” The remaining pages consist of mixed text and visual material. A reproduction of the cover page and the second page are provided below: II. SUMMARY OF ADMINISTRATIVE RECORD On September 15, 2022, Ms. Kashtanova submitted an application for the Work and copies of each page of the Work as the deposit copy. In her application, Ms. Kashtanova listed the author of the Work as “Kristina Kashtanova” and stated that she had created a “[c]omic book.” The application did not disclose that she used artificial intelligence to create any part of the Work, nor did she disclaim any portion of the Work.2 The Office reviewed the application on the same day and registered the Work as registration number VAu001480196. Shortly after registering the Work, the Office became aware of statements on social media attributed to Ms. Kashtanova that she had created the comic book using Midjourney artificial intelligence. Because the application had not disclosed the use of artificial intelligence, 2 As we explained in our previous letter, while the word “Midjourney” appears on the cover page of the Work, there is no indication of the intent or meaning of the word on the cover. Letter from U.S. Copyright Office to Kristina Kashtanova at 2 (Oct. 28, 2022). Van Lindberg, Esq. February 21, 2023 Taylor English Duma LLP -3- the Office determined that the application was incorrect, or at a minimum, substantively incomplete. In a letter dated October 28, 2022, the Office notified Ms. Kashtanova that it intended to cancel the registration unless she provided additional information in writing showing why the registration should not be cancelled.3 Letter from U.S. Copyright Office to Kristina Kashtanova (Oct. 28, 2022). On November 21, 2022, the Office received a timely response from Ms. Kashtanova’s attorney, Mr. Van Lindberg. Letter from Van Lindberg, Taylor English Duma LLP, to U.S. Copyright Office (Nov. 21, 2022) (“Kashtanova Letter”). The letter describes Ms. Kashtanova’s creation of the Work, including specific information about her use of Midjourney. Mr. Lindberg argues that the Work’s registration should not be cancelled because (1) Ms. Kashtanova authored every aspect of the work, with Midjourney serving merely as an assistive tool, and, (2) alternatively, portions of the work are registrable because the text was authored by Ms. Kashtanova and the Work is a copyrightable compilation due to her creative selection, coordination, and arrangement of the text and images. III. DISCUSSION A. Legal Standards Before turning to our analysis of the Work, we summarize here the legal principles that guide that analysis. The Copyright Act defines the scope of copyright protection. Under the Act, a work may be registered if it qualifies as an “original work[] of authorship fixed in any tangible medium of expression.” 17 U.S.C. § 102(a). The Supreme Court has explained that the term “original” in this context consists of two components: independent creation and sufficient creativity. See Feist Publ’ns, Inc. v. Rural Tel. Serv. Co., 499 U.S. 340, 345 (1991). First, the work must have been independently created by the author. Id. Second, the work must possess sufficient creativity. Id. Only a modicum of creativity is necessary, but the Supreme Court has ruled that some works—such as the alphabetized telephone directory at issue in Feist—fail to meet even this low threshold. Id. The Court observed that “[a]s a constitutional matter, copyright protects only those constituent elements of a work that possess more than a de minimis quantum of creativity.” Id. at 363. It found that there can be no copyright in a work in which “the creative spark is utterly lacking or so trivial as to be virtually nonexistent.” Id. at 359. Courts interpreting the phrase “works of authorship” have uniformly limited it to the creations of human authors. For example, in Burrow-Giles Lithographic Co. v. Sarony, the Supreme Court held that photographs were protected by copyright because they were “representatives of original intellectual conceptions of the author,” defining authors as “he to whom anything owes its origin; originator; maker; one who completes a work of science or literature.” 111 U.S. 53, 57–59 (1884). In doing so, the Court rejected the argument that a photograph was merely “a reproduction on paper of the exact features of some natural object or of some person” made by a machine. Id. at 56. But the Court explained that if photography was 3 Under 37 C.F.R. § 201.7(c)(4), if the Office becomes aware that an issued registration does not satisfy the statutory requirements for copyright “or that information essential to registration has been omitted entirely from the application or is questionable,” the Office will correspond with the copyright claimant “in an attempt to secure the required information . . . or to clarify the information previously given on the application.” If the claimant does not reply in 30 days, the Office will cancel the registration. Id. Van Lindberg, Esq. February 21, 2023 Taylor English Duma LLP -4- a “merely mechanical” process, “with no place for novelty, invention or originality” by the-221 2jour Postjour116 U. </text> What is the correct answer to this question: Which the accurate perspective the(US relation Of The case among the following statements? Choices: (A). (B. (C Kas the. (D). Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> { "meta": { "name_exp": "llama-3.1-70b_bar_game_explicit_v1_1", "player_num": 10, "min": 0, "max": 10, "home": 5, "ratio": 0.6, "ratio_str": "60%", "mode": "explicit", "round_id": 20, "version": "v1" }, "round_records": [ { "responses": [ "go", "go", "go", "go", "go", "go", "go", "stay", "go", "go" ], "go_num": 9, "go_ratio": 0.9, "winner": "stay", "utility": 0 }, { "responses": [ "go", "stay", "stay", "stay", "stay", "stay", "stay", "go", "stay", "stay" ], "go_num": 2, "go_ratio": 0.2, "winner": "go", "utility": 10 }, { "responses": [ "stay", "go", "go", "go", "go", "go", "go", "stay", "go", "go" ], "go_num": 8, "go_ratio": 0.8, "winner": "stay", "utility": 0 }, { "responses": [ "go", "go", "stay", "stay", "stay", "stay", "stay", "go", "stay", "stay" ], "go_num": 3, "go_ratio": 0.3, "winner": "go", "utility": 10 }, { "responses": [ "stay", "go", "go", "go", "go", "go", "go", "stay", "go", "go" ], "go_num": 8, "go_ratio": 0.8, "winner": "stay", "utility": 0 }, { "responses": [ "go", "stay", "stay", "stay", "stay", "stay", "stay", "go", "stay", "go" ], "go_num": 3, "go_ratio": 0.3, "winner": "go", "utility": 10 }, { "responses": [ "stay", "go", "go", "go", "go", "go", "go", "stay", "go", "stay" ], "go_num": 7, "go_ratio": 0.7, "winner": "stay", "utility": 0 }, { "responses": [ "go", "stay", "stay", "stay", "stay", "go", "stay", "go", "go", "go" ], "go_num": 5, "go_ratio": 0.5, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "stay", "go", "stay", "stay", "go" ], "go_num": 7, "go_ratio": 0.7, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "go", "go", "stay" ], "go_num": 2, "go_ratio": 0.2, "winner": "go", "utility": 10 }, { "responses": [ "stay", "go", "go", "go", "go", "go", "go", "stay", "go", "go" ], "go_num": 8, "go_ratio": 0.8, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "go", "go", "stay", "stay" ], "go_num": 2, "go_ratio": 0.2, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "stay", "stay", "stay", "stay", "go", "go" ], "go_num": 6, "go_ratio": 0.6, "winner": "go", "utility": 10 }, { "responses": [ "go", "stay", "go", "go", "go", "go", "go", "go", "stay", "stay" ], "go_num": 7, "go_ratio": 0.7, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "go", "stay", "stay", "stay" ], "go_num": 1, "go_ratio": 0.1, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "go", "stay", "go", "go", "go" ], "go_num": 9, "go_ratio": 0.9, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "go", "stay", "stay", "go", "stay", "stay" ], "go_num": 2, "go_ratio": 0.2, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "stay", "go", "go", "go", "go" ], "go_num": 9, "go_ratio": 0.9, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "go", "stay", "go", "stay", "stay" ], "go_num": 2, "go_ratio": 0.2, "winner": "go", "utility": 10 }, { "responses": [ "go", "stay", "stay", "stay", "stay", "stay", "go", "go", "stay", "stay" ], "go_num": 3, "go_ratio": 0.3, "winner": "go", "utility": 10 } ], "player_data": [ { "model": "meta-llama/Meta-Llama-3.1-70B-Instruct", "id": "player_0", "prompt": [ { "role": "system", "content": "\n\nYou are participating in a game played by 10 players over 20 rounds.\n\nGame Rules:\n\n1. Every round, you and the other players decide independently whether to go to a bar.\n2. If equal to or less than 60% of the players go to the bar, everyone who goes has more fun than staying home, receiving a utility of 10.\n3. If more than 60% of the players go to the bar, everyone who goes has less fun than staying home, receiving a utility of 0.\n4. Everyone who stays home receives a utility of the the the the the the the the the</text> What is the correct answer to this question: Which player most? Choices: (A) (B) (C) player (D)7 Format your response as follows: "The correct answer is (insert answer here)".
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Please read the following text and answer the question below. <text> { "meta": { "name_exp": "llama-3.1-70b_bar_game_explicit_v1_1", "player_num": 10, "min": 0, "max": 10, "home": 5, "ratio": 0.6, "ratio_str": "60%", "mode": "explicit", "round_id": 20, "version": "v1" }, "round_records": [ { "responses": [ "go", "go", "go", "go", "go", "go", "go", "stay", "go", "go" ], "go_num": 9, "go_ratio": 0.9, "winner": "stay", "utility": 0 }, { "responses": [ "go", "stay", "stay", "stay", "stay", "stay", "stay", "go", "stay", "stay" ], "go_num": 2, "go_ratio": 0.2, "winner": "go", "utility": 10 }, { "responses": [ "stay", "go", "go", "go", "go", "go", "go", "stay", "go", "go" ], "go_num": 8, "go_ratio": 0.8, "winner": "stay", "utility": 0 }, { "responses": [ "go", "go", "stay", "stay", "stay", "stay", "stay", "go", "stay", "stay" ], "go_num": 3, "go_ratio": 0.3, "winner": "go", "utility": 10 }, { "responses": [ "stay", "go", "go", "go", "go", "go", "go", "stay", "go", "go" ], "go_num": 8, "go_ratio": 0.8, "winner": "stay", "utility": 0 }, { "responses": [ "go", "stay", "stay", "stay", "stay", "stay", "stay", "go", "stay", "go" ], "go_num": 3, "go_ratio": 0.3, "winner": "go", "utility": 10 }, { "responses": [ "stay", "go", "go", "go", "go", "go", "go", "stay", "go", "stay" ], "go_num": 7, "go_ratio": 0.7, "winner": "stay", "utility": 0 }, { "responses": [ "go", "stay", "stay", "stay", "stay", "go", "stay", "go", "go", "go" ], "go_num": 5, "go_ratio": 0.5, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "stay", "go", "stay", "stay", "go" ], "go_num": 7, "go_ratio": 0.7, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "stay", "go", "go", "stay" ], "go_num": 2, "go_ratio": 0.2, "winner": "go", "utility": 10 }, { "responses": [ "stay", "go", "go", "go", "go", "go", "go", "stay", "go", "go" ], "go_num": 8, "go_ratio": 0.8, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "go", "go", "stay", "stay" ], "go_num": 2, "go_ratio": 0.2, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "stay", "stay", "stay", "stay", "go", "go" ], "go_num": 6, "go_ratio": 0.6, "winner": "go", "utility": 10 }, { "responses": [ "go", "stay", "go", "go", "go", "go", "go", "go", "stay", "stay" ], "go_num": 7, "go_ratio": 0.7, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "stay", "go", "stay", "stay", "stay" ], "go_num": 1, "go_ratio": 0.1, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "go", "stay", "go", "go", "go" ], "go_num": 9, "go_ratio": 0.9, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "go", "stay", "stay", "go", "stay", "stay" ], "go_num": 2, "go_ratio": 0.2, "winner": "go", "utility": 10 }, { "responses": [ "go", "go", "go", "go", "go", "stay", "go", "go", "go", "go" ], "go_num": 9, "go_ratio": 0.9, "winner": "stay", "utility": 0 }, { "responses": [ "stay", "stay", "stay", "stay", "stay", "go", "stay", "go", "stay", "stay" ], "go_num": 2, "go_ratio": 0.2, "winner": "go", "utility": 10 }, { "responses": [ "go", "stay", "stay", "stay", "stay", "stay", "go", "go", "stay", "stay" ], "go_num": 3, "go_ratio": 0.3, "winner": "go", "utility": 10 } ], "player_data": [ { "model": "meta-llama/Meta-Llama-3.1-70B-Instruct", "id": "player_0", "prompt": [ { "role": "system", "content": "\n\nYou are participating in a game played by 10 players over 20 rounds.\n\nGame Rules:\n\n1. Every round, you and the other players decide independently whether to go to a bar.\n2. If equal to or less than 60% of the players go to the bar, everyone who goes has more fun than staying home, receiving a utility of 10.\n3. If more than 60% of the players go to the bar, everyone who goes has less fun than staying home, receiving a utility of 0.\n4. Everyone who stays home receives a utility of the the the the the the the the the</text> What is the correct answer to this question: Which player most? Choices: (A) (B) (C) player (D)7 Format your response as follows: "The correct answer is (insert answer here)".
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Please read the following text and answer the question below. <text> { "meta": { "name_exp": "public_goods", "player_num": 10, "tokens": 20, "ratio": 2, "token_initialization": "fixed", "reset": true, "rand_min": 11, "round_id": 20, "version": "v1", "models": "meta-llama/Meta-Llama-3.1-70B-Instruct" }, "round_records": [ { "responses": [ 5, 5, 5, 0, 5, 5, 5, 5, 5, 0 ], "total_tokens": 40 }, { "responses": [ 0, 0, 5, 0, 0, 5, 0, 0, 5, 5 ], "total_tokens": 20 }, { "responses": [ 0, 0, 0, 0, 0, 0, 5, 5, 0, 0 ], "total_tokens": 10 }, { "responses": [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ], "total_tokens": 0 }, { "responses": [ 5, 5, 5, 0, 10, 5, 5, 0, 0, 0 ], "total_tokens": 35 }, { "responses": [ 0, 0, 5, 0, 0, 0, 0, 0, 0, 0 ], "total_tokens": 5 }, { "responses": [ 5, 5, 0, 0, 5, 0, 5, 0, 0, 0 ], "total_tokens": 20 }, { "responses": [ 0, 0, 0, 0, 0, 5, 0, 0, 0, 0 ], "total_tokens": 5 }, { "responses": [ 0, 0, 0, 0, 5, 0, 0, 0, 0, 0 ], "total_tokens": 5 }, { "responses": [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ], "total_tokens": 0 }, { "responses": [ 5, 0, 5, 0, 5, 5, 5, 0, 5, 5 ], "total_tokens": 35 }, { "responses": [ 0, 5, 0, 0, 0, 5, 0, 0, 0, 0 ], "total_tokens": 10 }, { "responses": [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ], "total_tokens": 0 }, { "responses": [ 5, 0, 5, 0, 0, 5, 0, 0, 0, 0 ], "total_tokens": 15 }, { "responses": [ 0, 5, 0, 0, 0, 0, 5, 0, 0, 0 ], "total_tokens": 10 }, { "responses": [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ], "total_tokens": 0 }, { "responses": [ 5, 0, 5, 5, 5, 0, 5, 5, 10, 5 ], "total_tokens": 45 }, { "responses": [ 0, 0, 0, 5, 0, 0, 0, 0, 0, 0 ], "total_tokens": 5 }, { "responses": [ 0, 0, 5, 0, 0, 0, 0, 0, 0, 0 ], "total_tokens": 5 }, { "responses": [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ], "total_tokens": 0 } ], "player_data": [ { "model": "meta-llama/Meta-Llama-3.1-70B-Instruct", "id": "player_0", "prompt": [ { "role": "system", "content": "\n\nYou are participating in a game played by 10 players over 20 rounds.\n\nGame Rules:\n\n1. In each round, you, as a player, must decide how many of your private tokens you wish to contribute secretly to the public pot.\n2. The total tokens in this pot will be multiplied by the factor 2 to create the \"public good\" payoff.\n3. This payoff will then be evenly divided among all players, regardless of their individual contribution.\n4. Any tokens you do not contribute will be retained in your private collection." }, { "role": "assistant", "content": "{\"tokens_contributed\": \"0\"}" }, { "role": "user", "content": "Tokens in the public pot: 0\nYour gain: 0.0\nYour tokens after round 4: 20.0\nTokens of each player after round 4: [20.0, 20.0, 20.0, 20.0, 20.0, 20.0, 20.0, 20.0, 20.0, 20.0]" }, { "role": "user", "content": "Game Results for Round 5:\n\nContributed tokens of each player: [5, 5, 5, 0, 10, 5, 5, 0, 0, 0]\nYou contributed:" }, { "role": "assistant", "content": "{\"tokens_contributed\": \"5\"}" }, { "role": "user", "content": "Tokens in the public pot: 35\nYour gain: 2.0\nYour tokens after round 5: 22.0\nTokens of each player after round 5: [22.0, 22.0, 22.0, 27.0, 17.0, 22.0, 22.0, 27.0, 27.0, 27.0]" }, { "role": "user", "content": "Game Results for Round 6:\n\nContributed tokens of each player: [0, 0, 5, 0, 0, 0, 0, 0, 0, 0]\nYou contributed:" }, { "role": "assistant", "content": "{\"tokens_contributed\": \"0\"}" }, { "role": "user", "content": "Tokens in the public pot: 5\nYour gain: 1.0\nYour tokens after round 6: 21.0\nTokens of each player after round 6: [2 role. . 222</text> What is correct answer to this question: Which? Choices: (A) (B) (C(D) Format your response as follows: "The correct answer is (insert answer here)".
306
null
0
A
player_2
Please read the following text and answer the question below. <text> { "meta": { "name_exp": "public_goods", "player_num": 10, "tokens": 20, "ratio": 2, "token_initialization": "fixed", "reset": true, "rand_min": 11, "round_id": 20, "version": "v1", "models": "meta-llama/Meta-Llama-3.1-70B-Instruct" }, "round_records": [ { "responses": [ 5, 5, 5, 0, 5, 5, 5, 5, 5, 0 ], "total_tokens": 40 }, { "responses": [ 0, 0, 5, 0, 0, 5, 0, 0, 5, 5 ], "total_tokens": 20 }, { "responses": [ 0, 0, 0, 0, 0, 0, 5, 5, 0, 0 ], "total_tokens": 10 }, { "responses": [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ], "total_tokens": 0 }, { "responses": [ 5, 5, 5, 0, 10, 5, 5, 0, 0, 0 ], "total_tokens": 35 }, { "responses": [ 0, 0, 5, 0, 0, 0, 0, 0, 0, 0 ], "total_tokens": 5 }, { "responses": [ 5, 5, 0, 0, 5, 0, 5, 0, 0, 0 ], "total_tokens": 20 }, { "responses": [ 0, 0, 0, 0, 0, 5, 0, 0, 0, 0 ], "total_tokens": 5 }, { "responses": [ 0, 0, 0, 0, 5, 0, 0, 0, 0, 0 ], "total_tokens": 5 }, { "responses": [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ], "total_tokens": 0 }, { "responses": [ 5, 0, 5, 0, 5, 5, 5, 0, 5, 5 ], "total_tokens": 35 }, { "responses": [ 0, 5, 0, 0, 0, 5, 0, 0, 0, 0 ], "total_tokens": 10 }, { "responses": [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ], "total_tokens": 0 }, { "responses": [ 5, 0, 5, 0, 0, 5, 0, 0, 0, 0 ], "total_tokens": 15 }, { "responses": [ 0, 5, 0, 0, 0, 0, 5, 0, 0, 0 ], "total_tokens": 10 }, { "responses": [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ], "total_tokens": 0 }, { "responses": [ 5, 0, 5, 5, 5, 0, 5, 5, 10, 5 ], "total_tokens": 45 }, { "responses": [ 0, 0, 0, 5, 0, 0, 0, 0, 0, 0 ], "total_tokens": 5 }, { "responses": [ 0, 0, 5, 0, 0, 0, 0, 0, 0, 0 ], "total_tokens": 5 }, { "responses": [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0 ], "total_tokens": 0 } ], "player_data": [ { "model": "meta-llama/Meta-Llama-3.1-70B-Instruct", "id": "player_0", "prompt": [ { "role": "system", "content": "\n\nYou are participating in a game played by 10 players over 20 rounds.\n\nGame Rules:\n\n1. In each round, you, as a player, must decide how many of your private tokens you wish to contribute secretly to the public pot.\n2. The total tokens in this pot will be multiplied by the factor 2 to create the \"public good\" payoff.\n3. This payoff will then be evenly divided among all players, regardless of their individual contribution.\n4. Any tokens you do not contribute will be retained in your private collection." }, { "role": "assistant", "content": "{\"tokens_contributed\": \"0\"}" }, { "role": "user", "content": "Tokens in the public pot: 0\nYour gain: 0.0\nYour tokens after round 4: 20.0\nTokens of each player after round 4: [20.0, 20.0, 20.0, 20.0, 20.0, 20.0, 20.0, 20.0, 20.0, 20.0]" }, { "role": "user", "content": "Game Results for Round 5:\n\nContributed tokens of each player: [5, 5, 5, 0, 10, 5, 5, 0, 0, 0]\nYou contributed:" }, { "role": "assistant", "content": "{\"tokens_contributed\": \"5\"}" }, { "role": "user", "content": "Tokens in the public pot: 35\nYour gain: 2.0\nYour tokens after round 5: 22.0\nTokens of each player after round 5: [22.0, 22.0, 22.0, 27.0, 17.0, 22.0, 22.0, 27.0, 27.0, 27.0]" }, { "role": "user", "content": "Game Results for Round 6:\n\nContributed tokens of each player: [0, 0, 5, 0, 0, 0, 0, 0, 0, 0]\nYou contributed:" }, { "role": "assistant", "content": "{\"tokens_contributed\": \"0\"}" }, { "role": "user", "content": "Tokens in the public pot: 5\nYour gain: 1.0\nYour tokens after round 6: 21.0\nTokens of each player after round 6: [2 role. . 222</text> What is correct answer to this question: Which? Choices: (A) (B) (C(D) Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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0.010147
201,842
Please read the following text and answer the question below. <text> Unnamed: 0 Unnamed: 1 Unnamed: 2 Unnamed: 3 Search Result Columns Unnamed: 5 Unnamed: 6 Unnamed: 7 Unnamed: 8 Unnamed: 9 Unnamed: 10 Unnamed: 11 Unnamed: 12 Unnamed: 13 Unnamed: 14 Unnamed: 15 Unnamed: 16 Unnamed: 17 Unnamed: 18 Unnamed: 19 Unnamed: 20 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN Search Link: https://my.pitchbook.com/?pcc=878600-80 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN Search Criteria: Post Valuation: Min: 50M; Max: 200M; Deal Date: From: 25-Aug-2020; Deal Size: Min: 5M; Deal Option: Search on a full transaction; Deal Status: Completed; Deal Types: All VC Stages; All Round Numbers; All Series; Industry Query: Artificial Intelligence & Machine Learning AND SaaS OR computer vision OR LMM OR ai video OR AI editing OR video editing; NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN Downloaded on: 8/25/2023 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN Created for: Jerry Guan, NetEase NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN Deal ID Companies Deal Status Valuation/Revenue Valuation/EBITDA Revenue Lead/Sole Investors Deal Date Deal Size Announced Date Verticals Deal Type 2 EBITDA Post Valuation Deal Synopsis Business Status Investors Description HQ Location Company Website PitchBook Link 155380-60T S2C Completed 10.29 NaN 19.26 Sino IC Leasing 2020-08-27 00:00:00 78.33 NaN Artificial Intelligence & Machine Learning, CloudTech & DevOps, SaaS, TMT NaN NaN 198.18 The company raised CNY 545 million of venture funding in a deal led by Sino IC Leasing on August 27, 2020, putting the company's pre-money valuation at CNY 833.79 million. SINO-IC Capital, Spinnotec, Shanghai Zhangjiang Torch Venture Capital, Legend Capital and SDIC Venture Capital also participated in the round. The funding will be used to accelerate the research and development for new EDA tools. Generating Revenue Legend Capital, SDIC Venture Capital, Shanghai Zhangjiang Torch Venture Capital, Sino IC Leasing, SINO-IC Capital, Spinnotec Provider of field programmable gate array (FPGA) prototyping services. The company focuses on the integrated circuit electronic design automation ("EDA") solutions, and its services include design exploration, IP development, hardware verification, system validation, software development, compatibility testing, SoC (system-on-a-chip) prototyping and many more. Shanghai, China www.s2ceda.com NaN 133117-93T Zeotap Completed NaN NaN NaN NaN 2021-09-08 00:00:00 71.5 2020-11-16 00:00:00 Artificial Intelligence & Machine Learning, Big Data, Marketing Tech, SaaS Series C NaN 179.2 The company raised $71.5 million of Series C venture funding from Here, Singtel Innov8 and Aperiam Ventures on September 8, 2021, putting the company's pre-money valuation at $107.70 million. Liberty Global Ventures, Natural Bridge Fund, DragonScale Ventures, SignalFire, York IE, Kortschak Investments, Flight Ventures, Capnamic Ventures, Iris Capital, New Science Ventures, Coelius Capital, Coparion, NeueCapital Partners, IONIQ, Eric Rosenblatt, Richard Pennycook, Eric Roza, Chris Scoggins, Taylor Barada, Bernd Miehler, Andrew Bursky, Kathaka, European Investment Bank, Zobito and Trailview Partners also participated in the round. The funds will be used to further invest in the company's customer data platform (CDP) and ID+ universal marketing identity products as well as accelerate the adoption of the platform across 14 active markets. Generating Revenue Andrew Bursky(Andrew Bursky), Aperiam Ventures, Bernd Miehler(Bernd Miehler), Capnamic Ventures(Christian Siegele), Chris Scoggins(Chris Scoggins), Coelius Capital(Zachery Coelius), Coparion(David Zimmer), DragonScale Ventures, Eric Rosenblatt(Eric Rosenblatt), Eric Roza(Eric Roza), European Investment Bank, Flight Ventures(Shawn Merani), Here (Open Location Platform), IONIQ, Iris Capital, Kathaka, Kortschak Investments, Liberty Global Ventures, Natural Bridge Ventures, NeueCapital Partners, New Science Ventures, Richard Pennycook(Richard Pennycook), SignalFire(Christopher Scoggins), Singtel Innov8, Taylor Barada(Taylor Barada), Trailview Partners, York IE, Zobito Developer of a customer intelligence platform designed to help companies better understand their customers and predict behaviors. The company's platform meets the general data protection regulation (GDPR) enterprise data privacy and security standards and incorporates independent, integrated modules including customer data unification, identity resolution, enrichment, analytics and modeling and activation to multiple partners in the marketing ecosystem, enabling brands to build on a nucleus of first-party data to win new customers and grow their loyal base and invest in meaningful experiences. Berlin, Germany www.zeotap.com NaN 204819-22T Unravel (Business/Productivity Software) Completed NaN NaN NaN Third Point Ventures(Curtis McKee) 2022-07-05 00:00:00 70 NaN Artificial Intelligence & Machine Learning, Big Data, SaaS, TMT Series D NaN 155.77 The company raised $70 million through a combination of debt and Series D venture funding in a deal led by Third Point Ventures on July NaN NaN NaN 0 NaN NaN will number , : NaN NaN NaN 0 KK0 Software00000g pre Bigotro0 S S S005 S> What is question date2 which company has occurrences" column? Choices: (A)ama (B)ia ) AssetWatch (D) Format your response as follows: "The correct answer is (insert answer here)".
307
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1
B
Aporia
Please read the following text and answer the question below. <text> Unnamed: 0 Unnamed: 1 Unnamed: 2 Unnamed: 3 Search Result Columns Unnamed: 5 Unnamed: 6 Unnamed: 7 Unnamed: 8 Unnamed: 9 Unnamed: 10 Unnamed: 11 Unnamed: 12 Unnamed: 13 Unnamed: 14 Unnamed: 15 Unnamed: 16 Unnamed: 17 Unnamed: 18 Unnamed: 19 Unnamed: 20 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN Search Link: https://my.pitchbook.com/?pcc=878600-80 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN Search Criteria: Post Valuation: Min: 50M; Max: 200M; Deal Date: From: 25-Aug-2020; Deal Size: Min: 5M; Deal Option: Search on a full transaction; Deal Status: Completed; Deal Types: All VC Stages; All Round Numbers; All Series; Industry Query: Artificial Intelligence & Machine Learning AND SaaS OR computer vision OR LMM OR ai video OR AI editing OR video editing; NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN Downloaded on: 8/25/2023 NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN Created for: Jerry Guan, NetEase NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN NaN Deal ID Companies Deal Status Valuation/Revenue Valuation/EBITDA Revenue Lead/Sole Investors Deal Date Deal Size Announced Date Verticals Deal Type 2 EBITDA Post Valuation Deal Synopsis Business Status Investors Description HQ Location Company Website PitchBook Link 155380-60T S2C Completed 10.29 NaN 19.26 Sino IC Leasing 2020-08-27 00:00:00 78.33 NaN Artificial Intelligence & Machine Learning, CloudTech & DevOps, SaaS, TMT NaN NaN 198.18 The company raised CNY 545 million of venture funding in a deal led by Sino IC Leasing on August 27, 2020, putting the company's pre-money valuation at CNY 833.79 million. SINO-IC Capital, Spinnotec, Shanghai Zhangjiang Torch Venture Capital, Legend Capital and SDIC Venture Capital also participated in the round. The funding will be used to accelerate the research and development for new EDA tools. Generating Revenue Legend Capital, SDIC Venture Capital, Shanghai Zhangjiang Torch Venture Capital, Sino IC Leasing, SINO-IC Capital, Spinnotec Provider of field programmable gate array (FPGA) prototyping services. The company focuses on the integrated circuit electronic design automation ("EDA") solutions, and its services include design exploration, IP development, hardware verification, system validation, software development, compatibility testing, SoC (system-on-a-chip) prototyping and many more. Shanghai, China www.s2ceda.com NaN 133117-93T Zeotap Completed NaN NaN NaN NaN 2021-09-08 00:00:00 71.5 2020-11-16 00:00:00 Artificial Intelligence & Machine Learning, Big Data, Marketing Tech, SaaS Series C NaN 179.2 The company raised $71.5 million of Series C venture funding from Here, Singtel Innov8 and Aperiam Ventures on September 8, 2021, putting the company's pre-money valuation at $107.70 million. Liberty Global Ventures, Natural Bridge Fund, DragonScale Ventures, SignalFire, York IE, Kortschak Investments, Flight Ventures, Capnamic Ventures, Iris Capital, New Science Ventures, Coelius Capital, Coparion, NeueCapital Partners, IONIQ, Eric Rosenblatt, Richard Pennycook, Eric Roza, Chris Scoggins, Taylor Barada, Bernd Miehler, Andrew Bursky, Kathaka, European Investment Bank, Zobito and Trailview Partners also participated in the round. The funds will be used to further invest in the company's customer data platform (CDP) and ID+ universal marketing identity products as well as accelerate the adoption of the platform across 14 active markets. Generating Revenue Andrew Bursky(Andrew Bursky), Aperiam Ventures, Bernd Miehler(Bernd Miehler), Capnamic Ventures(Christian Siegele), Chris Scoggins(Chris Scoggins), Coelius Capital(Zachery Coelius), Coparion(David Zimmer), DragonScale Ventures, Eric Rosenblatt(Eric Rosenblatt), Eric Roza(Eric Roza), European Investment Bank, Flight Ventures(Shawn Merani), Here (Open Location Platform), IONIQ, Iris Capital, Kathaka, Kortschak Investments, Liberty Global Ventures, Natural Bridge Ventures, NeueCapital Partners, New Science Ventures, Richard Pennycook(Richard Pennycook), SignalFire(Christopher Scoggins), Singtel Innov8, Taylor Barada(Taylor Barada), Trailview Partners, York IE, Zobito Developer of a customer intelligence platform designed to help companies better understand their customers and predict behaviors. The company's platform meets the general data protection regulation (GDPR) enterprise data privacy and security standards and incorporates independent, integrated modules including customer data unification, identity resolution, enrichment, analytics and modeling and activation to multiple partners in the marketing ecosystem, enabling brands to build on a nucleus of first-party data to win new customers and grow their loyal base and invest in meaningful experiences. Berlin, Germany www.zeotap.com NaN 204819-22T Unravel (Business/Productivity Software) Completed NaN NaN NaN Third Point Ventures(Curtis McKee) 2022-07-05 00:00:00 70 NaN Artificial Intelligence & Machine Learning, Big Data, SaaS, TMT Series D NaN 155.77 The company raised $70 million through a combination of debt and Series D venture funding in a deal led by Third Point Ventures on July NaN NaN NaN 0 NaN NaN will number , : NaN NaN NaN 0 KK0 Software00000g pre Bigotro0 S S S005 S> What is question date2 which company has occurrences" column? Choices: (A)ama (B)ia ) AssetWatch (D) Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> 1 INTRODUCTION The Conference of the Parties, at its 21st session, adopted the Paris Agreement on 12 December 2015. The Paris Agreement stipulates that it shall enter into force thirty days after the date on which at least 55 Parties to the United Nations Framework Convention on Climate Change (UNFCCC) accounting in total for at least an estimated 55 % of the total global greenhouse gas emissions have deposited their instruments of ratification, acceptance, approval or accession with the Depositary, the Secretary-General of the United Nations. The agreement was opened for signature on 22 April 2016 in New York. On 5 October 2016, the threshold for entry into force was achieved and the Paris Agreement entered into force on 4 November 2016. This booklet of the Paris Agreement has been published by the UNFCCC secretariat for ease of reference and as a ‘souvenir’ edition to commemorate its early entry into force. For ease of reference, the publication also contains the decision 1/CP.21, which adopts the Paris Agreement. Certified true copies of the Paris Agreement can be obtained from the Treaty Section of the Office of Legal Affairs, United Nations Headquarters, New York. This can also be done on- line at: https://treaties.un.org/Pages/ViewDetails.aspx?src=TREATY&mtdsg_no=XXVII-7- d&chapter=27&clang=_en 2 THE PARIS AGREEMENT The Parties to this Agreement, Being Parties to the United Nations Framework Convention on Climate Change, hereinafter referred to as “the Convention”, Pursuant to the Durban Platform for Enhanced Action established by decision 1/CP.17 of the Conference of the Parties to the Convention at its seventeenth session, In pursuit of the objective of the Convention, and being guided by its principles, including the principle of equity and common but differentiated responsibilities and respective capabilities, in the light of different national circumstances, Recognizing the need for an effective and progressive response to the urgent threat of climate change on the basis of the best available scientific knowledge, Also recognizing the specific needs and special circumstances of developing country Parties, especially those that are particularly vulnerable to the adverse effects of climate change, as provided for in the Convention, Taking full account of the specific needs and special situations of the least developed countries with regard to funding and transfer of technology, Recognizing that Parties may be affected not only by climate change, but also by the impacts of the measures taken in response to it, Emphasizing the intrinsic relationship that climate change actions, responses and impacts have with equitable access to sustainable development and eradication of poverty, Recognizing the fundamental priority of safeguarding food security and ending hunger, and the particular vulnerabilities of food production systems to the adverse impacts of climate change, Taking into account the imperatives of a just transition of the workforce and the creation of decent work and quality jobs in accordance with nationally defined development priorities, Acknowledging that climate change is a common concern of humankind, Parties should, when taking action to address climate change, respect, promote and consider their respective 3 FCCC/CP/2015/10/Add.1 obligations on human rights, the right to health, the rights of indigenous peoples, local communities, migrants, children, persons with disabilities and people in vulnerable situations and the right to development, as well as gender equality, empowerment of women and intergenerational equity, Recognizing the importance of the conservation and enhancement, as appropriate, of sinks and reservoirs of the greenhouse gases referred to in the Convention, Noting the importance of ensuring the integrity of all ecosystems, including oceans, and the protection of biodiversity, recognized by some cultures as Mother Earth, and noting the importance for some of the concept of “climate justice”, when taking action to address climate change, Affirming the importance of education, training, public awareness, public participation, public access to information and cooperation at all levels on the matters addressed in this Agreement, Recognizing the importance of the engagements of all levels of government and various actors, in accordance with respective national legislations of Parties, in addressing climate change, Also recognizing that sustainable lifestyles and sustainable patterns of consumption and production, with developed country Parties taking the lead, play an important role in addressing climate change, Have agreed as follows: Article 1 For the purpose of this Agreement, the definitions contained in Article 1 of the Convention shall apply. In addition: a. “Convention” means the United Nations Framework Convention on Climate Change, adopted in New York on 9 May 1992; b. “Conference of the Parties” means the Conference of the Parties to the Convention; c. “Party” means a Party to this Agreement. 4 Article 2 1. This Agreement, in enhancing the implementation of the Convention, including its objective, aims to strengthen the global response to the threat of climate change, in the context of sustainable development and efforts to eradicate poverty, including by: a. Holding the increase in the global average temperature to well below 2 °C above pre- industrial levels and pursuing efforts to limit the temperature increase to 1.5 °C above pre-industrial levels, recognizing that this would significantly reduce the risks and impacts of climate change; b. Increasing the ability to adapt to the adverse impacts of climate change and foster climate resilience and low greenhouse gas emissions development, in a manner that does not threaten food production; and c. Making finance flows consistent with a pathway towards low greenhouse gas emissions and climate-resilient development. 2. This Agreement will be implemented to reflect equity and the principle of common but differentiated responsibilities and respective capabilities, in the light of different national circumstances. Article 3 As nationally determined contributions to the global response to climate change, all Parties are to undertake and communicate ambitious efforts as defined in Articles 4, 7, 9, 10, 11 and 13 with the view to achieving the purpose of this Agreement as set out in Article 2. The efforts of all Parties will represent a progression over time, while recognizing the need to support developing country Parties for the effective implementation of this Agreement. Article 4 1. In order to achieve the long-term temperature goal set out in Article 2, Parties aim to reach global peaking of greenhouse gas emissions as soon as possible, recognizing that peaking will take longer for developing country Parties, and to undertake rapid reductions thereafter in accordance with best available science, so as to achieve a balance between anthropogenic emissions by sources and removals by sinks of greenhouse gases in the second half of this century, on the basis of equity, and in the context of sustainable development and efforts to eradicate poverty. 5 FCCC/CP/2015/10/Add.1 2. Each Party shall prepare, communicate and maintain successive nationally determined contributions that it intends to achieve. Parties shall pursue domestic mitigation measures, with the aim of achieving the objectives of such contributions. 3. Each Party’s successive nationally determined contribution will represent a progression beyond the Party’s then current nationally determined contribution and reflect its highest possible ambition, reflecting its common but differentiated responsibilities and respective capabilities, in the light of different national circumstances. 4. Developed country Parties should continue taking the lead by undertaking economy- wide absolute emission reduction targets. Developing country Parties should continue enhancing their mitigation efforts, and are encouraged to move over time towards economy-wide emission reduction or limitation targets in the light of different national circumstances. 5. Support shall be provided to developing country Parties for the implementation of this Article, in accordance with Articles 9, 10 and 11, recognizing that enhanced support for developing country Parties will allow for higher ambition in their actions. 6. The least developed countries and small island developing States may prepare and communicate strategies, plans and actions for low greenhouse gas emissions development reflecting their special circumstances. 7. Mitigation co-benefits resulting from Parties’ adaptation actions and/or economic diversification plans can contribute to mitigation outcomes under this Article. 8. In communicating their nationally determined contributions, all Parties shall provide the information necessary for clarity, transparency and understanding in accordance with decision 1/CP.21 and any relevant decisions of the Conference of the Parties serving as the meeting of the Parties to this Agreement. 9. Each Party shall communicate a nationally determined contribution every five years in accordance with decision 1/CP.21 and any relevant decisions of the Conference of the Parties serving as the meeting of the Parties to this Agreement and be informed by the outcomes of the global stocktake referred to in Article 14. 10. The Conference of the Parties serving as the meeting of the Parties to this Agreement shall consider common time frames for nationally determined contributions at111: 1 shall . damage11 andizing. 12ss1111 the1 the114; 1. </text> What is the correct answer to this question: Which is not the accurate description of the parties make? Choices: (A) for. (B all1. (C. (D)- industrial Format your response as follows: "The correct answer is (insert answer here)".
308
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3
D
Parties should thrive to hold the increase in the global average temperature to well below 2 °C above pre- industrial levels and increase the ability to adapt to the adverse impacts of climate change
Please read the following text and answer the question below. <text> 1 INTRODUCTION The Conference of the Parties, at its 21st session, adopted the Paris Agreement on 12 December 2015. The Paris Agreement stipulates that it shall enter into force thirty days after the date on which at least 55 Parties to the United Nations Framework Convention on Climate Change (UNFCCC) accounting in total for at least an estimated 55 % of the total global greenhouse gas emissions have deposited their instruments of ratification, acceptance, approval or accession with the Depositary, the Secretary-General of the United Nations. The agreement was opened for signature on 22 April 2016 in New York. On 5 October 2016, the threshold for entry into force was achieved and the Paris Agreement entered into force on 4 November 2016. This booklet of the Paris Agreement has been published by the UNFCCC secretariat for ease of reference and as a ‘souvenir’ edition to commemorate its early entry into force. For ease of reference, the publication also contains the decision 1/CP.21, which adopts the Paris Agreement. Certified true copies of the Paris Agreement can be obtained from the Treaty Section of the Office of Legal Affairs, United Nations Headquarters, New York. This can also be done on- line at: https://treaties.un.org/Pages/ViewDetails.aspx?src=TREATY&mtdsg_no=XXVII-7- d&chapter=27&clang=_en 2 THE PARIS AGREEMENT The Parties to this Agreement, Being Parties to the United Nations Framework Convention on Climate Change, hereinafter referred to as “the Convention”, Pursuant to the Durban Platform for Enhanced Action established by decision 1/CP.17 of the Conference of the Parties to the Convention at its seventeenth session, In pursuit of the objective of the Convention, and being guided by its principles, including the principle of equity and common but differentiated responsibilities and respective capabilities, in the light of different national circumstances, Recognizing the need for an effective and progressive response to the urgent threat of climate change on the basis of the best available scientific knowledge, Also recognizing the specific needs and special circumstances of developing country Parties, especially those that are particularly vulnerable to the adverse effects of climate change, as provided for in the Convention, Taking full account of the specific needs and special situations of the least developed countries with regard to funding and transfer of technology, Recognizing that Parties may be affected not only by climate change, but also by the impacts of the measures taken in response to it, Emphasizing the intrinsic relationship that climate change actions, responses and impacts have with equitable access to sustainable development and eradication of poverty, Recognizing the fundamental priority of safeguarding food security and ending hunger, and the particular vulnerabilities of food production systems to the adverse impacts of climate change, Taking into account the imperatives of a just transition of the workforce and the creation of decent work and quality jobs in accordance with nationally defined development priorities, Acknowledging that climate change is a common concern of humankind, Parties should, when taking action to address climate change, respect, promote and consider their respective 3 FCCC/CP/2015/10/Add.1 obligations on human rights, the right to health, the rights of indigenous peoples, local communities, migrants, children, persons with disabilities and people in vulnerable situations and the right to development, as well as gender equality, empowerment of women and intergenerational equity, Recognizing the importance of the conservation and enhancement, as appropriate, of sinks and reservoirs of the greenhouse gases referred to in the Convention, Noting the importance of ensuring the integrity of all ecosystems, including oceans, and the protection of biodiversity, recognized by some cultures as Mother Earth, and noting the importance for some of the concept of “climate justice”, when taking action to address climate change, Affirming the importance of education, training, public awareness, public participation, public access to information and cooperation at all levels on the matters addressed in this Agreement, Recognizing the importance of the engagements of all levels of government and various actors, in accordance with respective national legislations of Parties, in addressing climate change, Also recognizing that sustainable lifestyles and sustainable patterns of consumption and production, with developed country Parties taking the lead, play an important role in addressing climate change, Have agreed as follows: Article 1 For the purpose of this Agreement, the definitions contained in Article 1 of the Convention shall apply. In addition: a. “Convention” means the United Nations Framework Convention on Climate Change, adopted in New York on 9 May 1992; b. “Conference of the Parties” means the Conference of the Parties to the Convention; c. “Party” means a Party to this Agreement. 4 Article 2 1. This Agreement, in enhancing the implementation of the Convention, including its objective, aims to strengthen the global response to the threat of climate change, in the context of sustainable development and efforts to eradicate poverty, including by: a. Holding the increase in the global average temperature to well below 2 °C above pre- industrial levels and pursuing efforts to limit the temperature increase to 1.5 °C above pre-industrial levels, recognizing that this would significantly reduce the risks and impacts of climate change; b. Increasing the ability to adapt to the adverse impacts of climate change and foster climate resilience and low greenhouse gas emissions development, in a manner that does not threaten food production; and c. Making finance flows consistent with a pathway towards low greenhouse gas emissions and climate-resilient development. 2. This Agreement will be implemented to reflect equity and the principle of common but differentiated responsibilities and respective capabilities, in the light of different national circumstances. Article 3 As nationally determined contributions to the global response to climate change, all Parties are to undertake and communicate ambitious efforts as defined in Articles 4, 7, 9, 10, 11 and 13 with the view to achieving the purpose of this Agreement as set out in Article 2. The efforts of all Parties will represent a progression over time, while recognizing the need to support developing country Parties for the effective implementation of this Agreement. Article 4 1. In order to achieve the long-term temperature goal set out in Article 2, Parties aim to reach global peaking of greenhouse gas emissions as soon as possible, recognizing that peaking will take longer for developing country Parties, and to undertake rapid reductions thereafter in accordance with best available science, so as to achieve a balance between anthropogenic emissions by sources and removals by sinks of greenhouse gases in the second half of this century, on the basis of equity, and in the context of sustainable development and efforts to eradicate poverty. 5 FCCC/CP/2015/10/Add.1 2. Each Party shall prepare, communicate and maintain successive nationally determined contributions that it intends to achieve. Parties shall pursue domestic mitigation measures, with the aim of achieving the objectives of such contributions. 3. Each Party’s successive nationally determined contribution will represent a progression beyond the Party’s then current nationally determined contribution and reflect its highest possible ambition, reflecting its common but differentiated responsibilities and respective capabilities, in the light of different national circumstances. 4. Developed country Parties should continue taking the lead by undertaking economy- wide absolute emission reduction targets. Developing country Parties should continue enhancing their mitigation efforts, and are encouraged to move over time towards economy-wide emission reduction or limitation targets in the light of different national circumstances. 5. Support shall be provided to developing country Parties for the implementation of this Article, in accordance with Articles 9, 10 and 11, recognizing that enhanced support for developing country Parties will allow for higher ambition in their actions. 6. The least developed countries and small island developing States may prepare and communicate strategies, plans and actions for low greenhouse gas emissions development reflecting their special circumstances. 7. Mitigation co-benefits resulting from Parties’ adaptation actions and/or economic diversification plans can contribute to mitigation outcomes under this Article. 8. In communicating their nationally determined contributions, all Parties shall provide the information necessary for clarity, transparency and understanding in accordance with decision 1/CP.21 and any relevant decisions of the Conference of the Parties serving as the meeting of the Parties to this Agreement. 9. Each Party shall communicate a nationally determined contribution every five years in accordance with decision 1/CP.21 and any relevant decisions of the Conference of the Parties serving as the meeting of the Parties to this Agreement and be informed by the outcomes of the global stocktake referred to in Article 14. 10. The Conference of the Parties serving as the meeting of the Parties to this Agreement shall consider common time frames for nationally determined contributions at111: 1 shall . damage11 andizing. 12ss1111 the1 the114; 1. </text> What is the correct answer to this question: Which is not the accurate description of the parties make? Choices: (A) for. (B all1. (C. (D)- industrial Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> Chapter I Mr. Shaitana 2 Dinner at Mr. Shaitana's 3 A GameofBridge 4 First Murderer? 5 Second Murderer? 6 Third Murderer? 7 Fourth Murderer? 8 Which of Them? 9 Dr. Roberts 10 Dr. Roberts (continued) 11 Mrs. Lorrimer 12 Anne Meredith 13 Second Visitor 14 Third Visitor 15 Major Despard 16 The Evidence of Elsie Batt 17 The Evidence of Rhoda Dawes 18 Tea Interlude 19 Consultation 20 The Evidence of Mrs. Luxmore 21 Major Despard 22 Evidence from Combeacre 23 The Evidence of a Pair of Silk Stockings 378 381 384 388 393 398 400 405 407 413 418 422 426 429 434 438 442 445 449 452 460 464 467 468 24 Elimination of Three Murderers? 25 Mrs. Lorrimer Speaks 26 The Truth 27' The EyeWitness 28 Suicide 29 Accident 30 Murder 31 Cards on the Table 471 474 476 480 482 487 491 494 CHAPTER 1 Mr. Shaitana '' r y dear M. Poirot!" It was a soft purring voicc a voice/used deliberately as an inStrument-- nothing impulsive or unpremeditated about it. Hercule Poirot swung round. He bowed. He shook hands ceremoniously. There was something in his eye that was unusual. One would have said that this chance encounter awakened in him an emotion that he seldom had occasion to feel. "My dear Mr. Shaitana," he said. They both paused. They were like duellists en garde. Around them a well-dressed languid London crowd eddied mildly. Voices drawled or murmured. "Darlingxquisite!" "Simply divine, aren't they, my dear?" It was the Exhibition of Snuff-Boxes at Wessex House. Admission one guinea, in aid of the London hospitals. "My dear man," said Mr. Shaitana, "how nice to see you! Not hanging or guillotining much just at present? Slack season in the criminal world? Or is there to be a robbery here this afternoon--that would be too delicious." "Alas, Monsieur," said Poirot. "I am here in a purely private capacity." Mr. Shaitana was diverted for a moment by a Lovely Young Thing with tight poodle curls up one side of her head and three cornucopias in black straw on the other. He said: "My dear--why didn't you come to my party? It really was a marvellous party! Quite a lot of people actually spoke to me! One woman even said 'How do you do,' and 'Good-bye' and 'Thank you so much' but of course she came from a Garden City, poor dear!" While the Lovely Young Thing made a suitable reply, Poirot allowed himselfa good study of the hirsute adornment on Mr. Shaitana's upper lip. A fine moustache a very fine moustache--the only moustache in London, perhaps, that could compete with that of M. Hercule Poirot. "But it is not so luxuriant," he murmured to himself. "No, decidedly it is inferior in every respect. Tout de rrme, it catches the eye." The whole of Mr. Shaitana's person caught the eyc it was designed to do so. He deliberately attempted a Mephistophelian effect. He was tall and thin, his face was long and melancholy, his. eyebrows were heavfiy accented and jet black, he 381 382 Agatha Chrtie wore a moustache with stiffwaxed ends and a tiny black imperial. His clothes were works of art--of exquisite cut but with a suggestion of the bizarre. Every healthy Englishman who saw him longed earnestly and fervently to kick him! They said, with a singular lack of originality, "There's that damned Dago, Shaitana!" Their wives, daughters, sisters, aunts, mothers, and even grandmothers said, varying the idiom according to their generation, words to this effect: "I know, my dear. Of course, he is too terrible. But so rich! And such marvellous parties! And he's always got something amusing and spiteful to tell you about people." Whether Mr. Shaitana was an Argentine, or a Portuguese, or a Greek, or some other nationality rightly despised by the insular Briton, nobody knew. But three facts were quite certain: He existed richly and beautifully in a super flat in Park Lane. He gave wonderful parties--large parties, small parties, macabre parties, respectable parties and definitely "queer" parties. He was a man of whom nearly everybody was a little afraid. Why this last was so can hardly be stated in definite words. There was a feeling, perhaps, that he knew a little too much about everybody. And there was a feeling, too, that his sense of humour was a curious one. People nearly always felt that it would be better not to risk offending Mr. Shaitana. It was his humour this afternoon to bait that ridiculous-looking little man, Hercule Poirot. "So even a policeman needs recreation?" he said. "You study the art in your old age, M. Poirot." Poirot smiled good-humouredly. "I see," he said, "that you yourself have lent three snuffboxes to the Exhibition." Mr. Shaitana waved a deprecating hand. "One picks up trifles here and there. You must come to my flat one day. I have some interesting pieces. I do not confine myself to any particular period or class of object.' "Your tastes are catholic," said Poirot smiling. "As you say." Suddenly Mr. Shaitana's eyes danced, the corners of his lips curled up, his eyebrows assumed a fantastic tilt. "I could even show you objects in your own line, M. Poirot!" "You have then a private 'Black Museum.'" "Bah!" Mr. Shaitana snapped disdainful fingers. "The cup used by the Brighton murderer, the jemmy of a celebrated burglar absurd childishness! I should never burden myself with rubbish like that. I collect only the best objects of their kind." "And what do you consider the best objects, artistically speaking, in crime?" inquired Poirot. Mr. Shaitana leaned forward and laid two fingers on Poirot's shoulder. He hissed his words dramatically. "The human beings who commit them, M. Poirot." Poirot's eyebrows rose a trifle. "Aha, I have startled you," said Shaitana. "My dear, dear man, you and I look on these things as from poles apart! For you crime is a matter of routine: a murder, an investigation, a clue, and ultimately (for you are undoubtedly an able fellow) a Cards on the Table 383 conviction. Such banalities would not interest me! I am not interested in poor specimens of any kind. And the caught murderer is necessarily one of the failures. He is second-rate. No, I look on the matter from the artistic point of view. I collect only the best!" "The best being ?" asked Poirot. "My dear fellow--the ones who have got away with it! The successes! The criminals who lead an agreeable life which no breath of suspicion has ever touched. Admit that it is an amusing hobby." "It was another word I was thinking of not amusing." "An idea!" cried Shaitana, paying no attention to Poirot. "A little dinner! A dinner to meet my exhibits! Really that is a most amusing thought. I cannot think why it has never occurred to me before. Yes--yes, I see it allI see it exactly .... You must give me a little time--not next week--let us sa the week after next. You are free? What day shall we say?" "Any day of the week after next would suit me," saidoirot with a bow. "Good then let us say Friday. Friday the 18th, that will be. I will write it down at once in my little book. Really, the idea pleases me enormously." "I am9 didn9aitoi don Mrsoioi saidoi oioi gravathaoi</text> What is the correct answer to this question: In Ag's the" , which? Choices: (A) (B. (C. (D). Format your response as follows: "The correct answer is (insert answer here)".
309
null
1
B
A pattern of high-risk moves.
Please read the following text and answer the question below. <text> Chapter I Mr. Shaitana 2 Dinner at Mr. Shaitana's 3 A GameofBridge 4 First Murderer? 5 Second Murderer? 6 Third Murderer? 7 Fourth Murderer? 8 Which of Them? 9 Dr. Roberts 10 Dr. Roberts (continued) 11 Mrs. Lorrimer 12 Anne Meredith 13 Second Visitor 14 Third Visitor 15 Major Despard 16 The Evidence of Elsie Batt 17 The Evidence of Rhoda Dawes 18 Tea Interlude 19 Consultation 20 The Evidence of Mrs. Luxmore 21 Major Despard 22 Evidence from Combeacre 23 The Evidence of a Pair of Silk Stockings 378 381 384 388 393 398 400 405 407 413 418 422 426 429 434 438 442 445 449 452 460 464 467 468 24 Elimination of Three Murderers? 25 Mrs. Lorrimer Speaks 26 The Truth 27' The EyeWitness 28 Suicide 29 Accident 30 Murder 31 Cards on the Table 471 474 476 480 482 487 491 494 CHAPTER 1 Mr. Shaitana '' r y dear M. Poirot!" It was a soft purring voicc a voice/used deliberately as an inStrument-- nothing impulsive or unpremeditated about it. Hercule Poirot swung round. He bowed. He shook hands ceremoniously. There was something in his eye that was unusual. One would have said that this chance encounter awakened in him an emotion that he seldom had occasion to feel. "My dear Mr. Shaitana," he said. They both paused. They were like duellists en garde. Around them a well-dressed languid London crowd eddied mildly. Voices drawled or murmured. "Darlingxquisite!" "Simply divine, aren't they, my dear?" It was the Exhibition of Snuff-Boxes at Wessex House. Admission one guinea, in aid of the London hospitals. "My dear man," said Mr. Shaitana, "how nice to see you! Not hanging or guillotining much just at present? Slack season in the criminal world? Or is there to be a robbery here this afternoon--that would be too delicious." "Alas, Monsieur," said Poirot. "I am here in a purely private capacity." Mr. Shaitana was diverted for a moment by a Lovely Young Thing with tight poodle curls up one side of her head and three cornucopias in black straw on the other. He said: "My dear--why didn't you come to my party? It really was a marvellous party! Quite a lot of people actually spoke to me! One woman even said 'How do you do,' and 'Good-bye' and 'Thank you so much' but of course she came from a Garden City, poor dear!" While the Lovely Young Thing made a suitable reply, Poirot allowed himselfa good study of the hirsute adornment on Mr. Shaitana's upper lip. A fine moustache a very fine moustache--the only moustache in London, perhaps, that could compete with that of M. Hercule Poirot. "But it is not so luxuriant," he murmured to himself. "No, decidedly it is inferior in every respect. Tout de rrme, it catches the eye." The whole of Mr. Shaitana's person caught the eyc it was designed to do so. He deliberately attempted a Mephistophelian effect. He was tall and thin, his face was long and melancholy, his. eyebrows were heavfiy accented and jet black, he 381 382 Agatha Chrtie wore a moustache with stiffwaxed ends and a tiny black imperial. His clothes were works of art--of exquisite cut but with a suggestion of the bizarre. Every healthy Englishman who saw him longed earnestly and fervently to kick him! They said, with a singular lack of originality, "There's that damned Dago, Shaitana!" Their wives, daughters, sisters, aunts, mothers, and even grandmothers said, varying the idiom according to their generation, words to this effect: "I know, my dear. Of course, he is too terrible. But so rich! And such marvellous parties! And he's always got something amusing and spiteful to tell you about people." Whether Mr. Shaitana was an Argentine, or a Portuguese, or a Greek, or some other nationality rightly despised by the insular Briton, nobody knew. But three facts were quite certain: He existed richly and beautifully in a super flat in Park Lane. He gave wonderful parties--large parties, small parties, macabre parties, respectable parties and definitely "queer" parties. He was a man of whom nearly everybody was a little afraid. Why this last was so can hardly be stated in definite words. There was a feeling, perhaps, that he knew a little too much about everybody. And there was a feeling, too, that his sense of humour was a curious one. People nearly always felt that it would be better not to risk offending Mr. Shaitana. It was his humour this afternoon to bait that ridiculous-looking little man, Hercule Poirot. "So even a policeman needs recreation?" he said. "You study the art in your old age, M. Poirot." Poirot smiled good-humouredly. "I see," he said, "that you yourself have lent three snuffboxes to the Exhibition." Mr. Shaitana waved a deprecating hand. "One picks up trifles here and there. You must come to my flat one day. I have some interesting pieces. I do not confine myself to any particular period or class of object.' "Your tastes are catholic," said Poirot smiling. "As you say." Suddenly Mr. Shaitana's eyes danced, the corners of his lips curled up, his eyebrows assumed a fantastic tilt. "I could even show you objects in your own line, M. Poirot!" "You have then a private 'Black Museum.'" "Bah!" Mr. Shaitana snapped disdainful fingers. "The cup used by the Brighton murderer, the jemmy of a celebrated burglar absurd childishness! I should never burden myself with rubbish like that. I collect only the best objects of their kind." "And what do you consider the best objects, artistically speaking, in crime?" inquired Poirot. Mr. Shaitana leaned forward and laid two fingers on Poirot's shoulder. He hissed his words dramatically. "The human beings who commit them, M. Poirot." Poirot's eyebrows rose a trifle. "Aha, I have startled you," said Shaitana. "My dear, dear man, you and I look on these things as from poles apart! For you crime is a matter of routine: a murder, an investigation, a clue, and ultimately (for you are undoubtedly an able fellow) a Cards on the Table 383 conviction. Such banalities would not interest me! I am not interested in poor specimens of any kind. And the caught murderer is necessarily one of the failures. He is second-rate. No, I look on the matter from the artistic point of view. I collect only the best!" "The best being ?" asked Poirot. "My dear fellow--the ones who have got away with it! The successes! The criminals who lead an agreeable life which no breath of suspicion has ever touched. Admit that it is an amusing hobby." "It was another word I was thinking of not amusing." "An idea!" cried Shaitana, paying no attention to Poirot. "A little dinner! A dinner to meet my exhibits! Really that is a most amusing thought. I cannot think why it has never occurred to me before. Yes--yes, I see it allI see it exactly .... You must give me a little time--not next week--let us sa the week after next. You are free? What day shall we say?" "Any day of the week after next would suit me," saidoirot with a bow. "Good then let us say Friday. Friday the 18th, that will be. I will write it down at once in my little book. Really, the idea pleases me enormously." "I am9 didn9aitoi don Mrsoioi saidoi oioi gravathaoi</text> What is the correct answer to this question: In Ag's the" , which? Choices: (A) (B. (C. (D). Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> Inference-Time Intervention: Eliciting Truthful Answers from a Language Model Abstract We introduce Inference-Time Intervention (ITI), a technique designed to enhance the “truthfulness” of large language models (LLMs). ITI operates by shifting model activations during inference, following a set of directions across a limited num- ber of attention heads. This intervention significantly improves the performance of LLaMA models on the TruthfulQA benchmark. On an instruction-finetuned LLaMA called Alpaca, ITI improves its truthfulness from 32.5% to 65.1%. We identify a trade-off between truthfulness and helpfulness and demonstrate how to balance it by tuning the intervention strength. ITI is minimally invasive and compu- tationally inexpensive. Moreover, the technique is data efficient: while approaches like RLHF require extensive annotations, ITI locates truthful directions using only few hundred examples. Our findings suggest that LLMs may have an internal repre- sentation of the likelihood of something being true, even as they produce falsehoods on the surface. Code: https://github.com/likenneth/honest_llama. 1 Introduction Figure 1: Answers to the same question from LLaMA without (red) and with (blue) inference- time intervention. Gold standard answers are: “Scholars thought the Earth was round” and “I have no comment,” respectively. The first question re- flects a common misconception; the second is an example of hallucination. Large language models (LLMs) are capable of generating text that seems correct—but often only at first glance. Close inspection sometimes reveals a range of inaccuracies, from minor er- rors to flat-out “hallucinations” (Shuster et al., 2021) (Figure 1). Such mistakes are a clear issue in contexts where correctness counts. Enhancing the correctness of LLMs is a multi- faceted challenge. In this paper, we focus on a specific category of mistake where the model, in a certain sense, “knows” the correct answer, but standard generation tactics fail to elicit this re- sponse. Users of LLM-based systems, for exam- ple, have discovered that they can give a wrong answer in one context while yielding the correct answer in a different context (Wei et al., 2022). Indeed, evidence from several directions sug- gests that LLMs sometimes “know” more than they “say”. Wang et al. (2021) construct high- quality knowledge graphs from LLMs without human supervision. Kadavath et al. (2022) find language models can generate and then self- evaluate their own answers with high accuracy. ∗Correspondence to Kenneth Li <ke_li@g.harvard.edu>. First two authors made equal contribution. 37th Conference on Neural Information Processing Systems (NeurIPS 2023). arXiv:2306.03341v6 [cs.LG] 26 Jun 2024 Saunders et al. (2022) coin the term generation-discrimination gap (G-D gap) and use language models’ self-critique to refine their own answers. Burns et al. (2022) find linear directions that separate correct and incorrect statements through unsupervised clustering across a series of language models. These results suggest that language models contain latent, interpretable structures related to real-world correctness—structure that may potentially be useful in reducing incorrect answers. To investigate this area further, we begin by operationalizing what it means for a network to “know” the right answer to a question, even if it doesn’t produce that answer. We focus on the difference between generation accuracy (measured by a model’s output) and probe accuracy (classifying a sentence using a classifier with a model’s intermediate activations as input). Using the LLaMA 7B model, applied to the TruthfulQA benchmark from Lin et al. (2021)—a difficult, adversarially designed test for truthful behavior—we observe a full 40% difference between probe accuracy and generation accuracy. This statistic points to a major gap between what information is present at intermediate layers and what appears in the output. To close this gap, we introduce a technique we call Inference-Time Intervention (ITI). At a high level, we first identify a sparse set of attention heads with high linear probing accuracy for truthfulness (as defined by the TruthfulQA benchmark). Then, during inference, we shift activations along these truth-correlated directions. We repeat the same intervention autoregressively until the whole answer is generated. ITI results in a significant performance increase on the TruthfulQA benchmark. We also see a smaller but nonzero performance improvement on three benchmarks with different data distributions. ITI contrasts with existing methods such as RLHF (Ouyang et al., 2022; Bai et al., 2022a; Menick et al., 2022) and RLAIF (Bai et al., 2022b), which work by finetuning pretrained language models with reinforcement learning. Both require huge annotation and computation resources. Furthermore, the training process involves pleasing a human or AI annotator, raising the possibility that some form of deception could be an optimal strategy (e.g., see the “sycophancy” results of Perez et al. (2022)). This work makes two main contributions. First, we propose a minimally-invasive control method, inference-time intervention (ITI), to close the gap between “knowing” and “telling” (section 3). ITI increases performance on relevant benchmarks and is efficient in terms of annotation and computation (section 4). Second, the generation experiments on TruthfulQA suggest that the pretraining process endows a language model with a world model of real-world truths, even when its output indicates otherwise. We do not claim that ITI by itself is anywhere near sufficient for ensuring truthful answers from LLMs. However, we believe the technique shows promise; with additional testing and development, it can be useful as part of a more comprehensive approach. 2 Related Work Among various ways to control large language model behavior after pretraining, inference-time intervention falls into the category of activation editing (Li et al., 2023; Hernandez et al., 2023) and enjoys the advantage of being adjustable and minimally invasive. Previous work has shown that “steering” vectors—both trained and hand-selected—can be used for style transfer in language models (Subramani et al., 2022; Turner et al., 2023). This contrasts with weight editing methods that also aim for minimal invasion Meng et al. (2022); Ilharco et al. (2022); Orgad et al. (2023). However, some are found to reduce the general robustness of the model (Brown et al., 2023; Hase et al., 2023). ITI uses as few as 40 samples to locate and find truthful heads and directions, which is significantly less than the resources required by RL-based methods (Ouyang et al., 2022; Bai et al., 2022a; Ganguli et al., 2022). The idea of activation perturbation can be traced back to plug-and-play controllable text generation methods (Dathathri et al., 2019; Krause et al., 2020; Li et al., 2022), which require repeated forward and backward propagation. Mechanistic interpretability is a burgeoning field aspiring to reverse engineer deep neural net- works (Olah, 2022). Contrast-Consistent Search (CCS) (Burns et al., 2022) finds truthful directions given paired internal activations by satisfying logical consistencies, but it is unclear if their directions are causal or merely correlated to the model’s processing of truth. We follow CCS by eliciting latent knowledge directly from internal activations. But we extend the concept of truth to Lin et al. (2021)’s literal truth about the real world and explore how causal the directions are to model outputs. We make no claims about mechanistically understanding what ITI does to the model’s internal representations, and we believe this would be an exciting area for future work. 2 3 Inference-Time Intervention for Eliciting Truthful Answers Progress has been made in understanding the inner workings of LLMs (Burns et al., 2022; Li, 2023; Moschella et al., 2022). A theme in the literature is that the activation space of many language models appears to contain interpretableXerv1 aerv scientifically oferv-P Tw the/2 Nothing happens UnInt5. False/erververv the 279 each1180 </text> What is the correct to this question: Analyzing the limitations ( discussed in the "" paper, what could be a significant challenge, especially considering discussions specificity? Choices: (A),. (B)-through. (C) IT. (D) As,. Format your response as follows: "The correct answer is (insert answer here)".
310
null
0
A
ITI’s ability to maintain stylistic and computational baselines while enhancing truthfulness might lead to its adoption as a default feature in commercial language model platforms, potentially reducing the need for frequent retraining cycles.
Please read the following text and answer the question below. <text> Inference-Time Intervention: Eliciting Truthful Answers from a Language Model Abstract We introduce Inference-Time Intervention (ITI), a technique designed to enhance the “truthfulness” of large language models (LLMs). ITI operates by shifting model activations during inference, following a set of directions across a limited num- ber of attention heads. This intervention significantly improves the performance of LLaMA models on the TruthfulQA benchmark. On an instruction-finetuned LLaMA called Alpaca, ITI improves its truthfulness from 32.5% to 65.1%. We identify a trade-off between truthfulness and helpfulness and demonstrate how to balance it by tuning the intervention strength. ITI is minimally invasive and compu- tationally inexpensive. Moreover, the technique is data efficient: while approaches like RLHF require extensive annotations, ITI locates truthful directions using only few hundred examples. Our findings suggest that LLMs may have an internal repre- sentation of the likelihood of something being true, even as they produce falsehoods on the surface. Code: https://github.com/likenneth/honest_llama. 1 Introduction Figure 1: Answers to the same question from LLaMA without (red) and with (blue) inference- time intervention. Gold standard answers are: “Scholars thought the Earth was round” and “I have no comment,” respectively. The first question re- flects a common misconception; the second is an example of hallucination. Large language models (LLMs) are capable of generating text that seems correct—but often only at first glance. Close inspection sometimes reveals a range of inaccuracies, from minor er- rors to flat-out “hallucinations” (Shuster et al., 2021) (Figure 1). Such mistakes are a clear issue in contexts where correctness counts. Enhancing the correctness of LLMs is a multi- faceted challenge. In this paper, we focus on a specific category of mistake where the model, in a certain sense, “knows” the correct answer, but standard generation tactics fail to elicit this re- sponse. Users of LLM-based systems, for exam- ple, have discovered that they can give a wrong answer in one context while yielding the correct answer in a different context (Wei et al., 2022). Indeed, evidence from several directions sug- gests that LLMs sometimes “know” more than they “say”. Wang et al. (2021) construct high- quality knowledge graphs from LLMs without human supervision. Kadavath et al. (2022) find language models can generate and then self- evaluate their own answers with high accuracy. ∗Correspondence to Kenneth Li <ke_li@g.harvard.edu>. First two authors made equal contribution. 37th Conference on Neural Information Processing Systems (NeurIPS 2023). arXiv:2306.03341v6 [cs.LG] 26 Jun 2024 Saunders et al. (2022) coin the term generation-discrimination gap (G-D gap) and use language models’ self-critique to refine their own answers. Burns et al. (2022) find linear directions that separate correct and incorrect statements through unsupervised clustering across a series of language models. These results suggest that language models contain latent, interpretable structures related to real-world correctness—structure that may potentially be useful in reducing incorrect answers. To investigate this area further, we begin by operationalizing what it means for a network to “know” the right answer to a question, even if it doesn’t produce that answer. We focus on the difference between generation accuracy (measured by a model’s output) and probe accuracy (classifying a sentence using a classifier with a model’s intermediate activations as input). Using the LLaMA 7B model, applied to the TruthfulQA benchmark from Lin et al. (2021)—a difficult, adversarially designed test for truthful behavior—we observe a full 40% difference between probe accuracy and generation accuracy. This statistic points to a major gap between what information is present at intermediate layers and what appears in the output. To close this gap, we introduce a technique we call Inference-Time Intervention (ITI). At a high level, we first identify a sparse set of attention heads with high linear probing accuracy for truthfulness (as defined by the TruthfulQA benchmark). Then, during inference, we shift activations along these truth-correlated directions. We repeat the same intervention autoregressively until the whole answer is generated. ITI results in a significant performance increase on the TruthfulQA benchmark. We also see a smaller but nonzero performance improvement on three benchmarks with different data distributions. ITI contrasts with existing methods such as RLHF (Ouyang et al., 2022; Bai et al., 2022a; Menick et al., 2022) and RLAIF (Bai et al., 2022b), which work by finetuning pretrained language models with reinforcement learning. Both require huge annotation and computation resources. Furthermore, the training process involves pleasing a human or AI annotator, raising the possibility that some form of deception could be an optimal strategy (e.g., see the “sycophancy” results of Perez et al. (2022)). This work makes two main contributions. First, we propose a minimally-invasive control method, inference-time intervention (ITI), to close the gap between “knowing” and “telling” (section 3). ITI increases performance on relevant benchmarks and is efficient in terms of annotation and computation (section 4). Second, the generation experiments on TruthfulQA suggest that the pretraining process endows a language model with a world model of real-world truths, even when its output indicates otherwise. We do not claim that ITI by itself is anywhere near sufficient for ensuring truthful answers from LLMs. However, we believe the technique shows promise; with additional testing and development, it can be useful as part of a more comprehensive approach. 2 Related Work Among various ways to control large language model behavior after pretraining, inference-time intervention falls into the category of activation editing (Li et al., 2023; Hernandez et al., 2023) and enjoys the advantage of being adjustable and minimally invasive. Previous work has shown that “steering” vectors—both trained and hand-selected—can be used for style transfer in language models (Subramani et al., 2022; Turner et al., 2023). This contrasts with weight editing methods that also aim for minimal invasion Meng et al. (2022); Ilharco et al. (2022); Orgad et al. (2023). However, some are found to reduce the general robustness of the model (Brown et al., 2023; Hase et al., 2023). ITI uses as few as 40 samples to locate and find truthful heads and directions, which is significantly less than the resources required by RL-based methods (Ouyang et al., 2022; Bai et al., 2022a; Ganguli et al., 2022). The idea of activation perturbation can be traced back to plug-and-play controllable text generation methods (Dathathri et al., 2019; Krause et al., 2020; Li et al., 2022), which require repeated forward and backward propagation. Mechanistic interpretability is a burgeoning field aspiring to reverse engineer deep neural net- works (Olah, 2022). Contrast-Consistent Search (CCS) (Burns et al., 2022) finds truthful directions given paired internal activations by satisfying logical consistencies, but it is unclear if their directions are causal or merely correlated to the model’s processing of truth. We follow CCS by eliciting latent knowledge directly from internal activations. But we extend the concept of truth to Lin et al. (2021)’s literal truth about the real world and explore how causal the directions are to model outputs. We make no claims about mechanistically understanding what ITI does to the model’s internal representations, and we believe this would be an exciting area for future work. 2 3 Inference-Time Intervention for Eliciting Truthful Answers Progress has been made in understanding the inner workings of LLMs (Burns et al., 2022; Li, 2023; Moschella et al., 2022). A theme in the literature is that the activation space of many language models appears to contain interpretableXerv1 aerv scientifically oferv-P Tw the/2 Nothing happens UnInt5. False/erververv the 279 each1180 </text> What is the correct to this question: Analyzing the limitations ( discussed in the "" paper, what could be a significant challenge, especially considering discussions specificity? Choices: (A),. (B)-through. (C) IT. (D) As,. Format your response as follows: "The correct answer is (insert answer here)".
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0.019637
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Please read the following text and answer the question below. <text> 4-740-705-18(1) © 2018 Sony Corporation Solid-State Memory Camcorder Operating Instructions Before operating the unit, please read this manual thoroughly and retain it for future reference. PXW-Z280V/PXW-Z280T Software Version 6.0 2 Overview Location and Function of Parts ............................................... 8 Main unit ........................................................................ 8 Screen Display ......................................................................... 13 LCD/viewfinder screen ................................................ 13 Status screen ................................................................. 16 Preparation Power Supply ........................................................................... 22 Using a battery pack ..................................................... 22 Using AC power ........................................................... 23 Turning the camcorder on/off ...................................... 23 Setting the Clock ..................................................................... 24 Attaching Devices .................................................................... 24 Attaching the lens hood ................................................ 24 Attaching the large eyecup ........................................... 24 Adjusting the Screens ............................................................. 25 Adjusting the LCD screen ............................................ 25 Adjusting the viewfinder .............................................. 25 Adjusting the brightness of the LCD/viewfinder screen using an assignable button .......................... 25 Using SxS Memory Cards ...................................................... 26 About SxS memory cards ............................................. 26 Inserting SxS memory cards ........................................ 26 Removing an SxS memory card ................................... 26 Switching between SxS memory cards ........................ 26 Formatting (initializing) an SxS memory card ............. 26 Checking the remaining recording time ....................... 27 Restoring an SxS memory card .................................... 27 Using Other Media .................................................................. 28 XQD memory cards ..................................................... 28 SD cards ....................................................................... 29 Restoring an SD card ................................................... 29 Setting the Password for Network Access Authentication ................................................................... 30 Table of Contents 3 Shooting Basic Operation Procedure .................................................... 31 Shooting ....................................................................... 31 Adjusting the zoom ...................................................... 32 Adjusting the focus ...................................................... 33 Monitoring audio while shooting ................................. 34 Changing Basic Settings ......................................................... 34 Video format ................................................................ 34 Adjusting the brightness ............................................... 35 Adjusting for natural colors (white balance) ................ 36 Setting the audio to record ........................................... 38 Image stabilization ....................................................... 40 Time data ...................................................................... 40 Useful Functions ...................................................................... 41 Direct menu operation .................................................. 41 Face detection AF ........................................................ 41 Color bars/reference audio tone ................................... 43 Shot marks .................................................................... 43 OK/NG/KEEP flags (exFAT, UDF) ............................ 43 Reviewing a recording (Rec Review) .......................... 43 Assignable buttons ....................................................... 44 Interval recording (Interval Rec) .................................. 44 Continuous recording (Clip Continuous Rec) (exFAT, UDF) ...................................................................... 45 Picture cache recording (Picture Cache Rec) ............... 46 Slow & Quick Motion .................................................. 47 Simultaneous recording in 2 slots (Simul Rec) ............ 48 4K & HD (Sub) recording ............................................ 48 High dynamic range (HDR) recording ......................... 49 Adjusting the flange focal length automatically .......... 50 Acquiring location information (GPS) ......................... 51 Changing the audio channels using button operation ................................................................ 52 Planning Metadata .................................................................. 52 Loading a planning metadata file ................................. 52 Defining a clip name in planning metadata .................. 53 Defining shot mark names in planning metadata ......... 54 Transferring planning metadata files ........................... 55 Proxy Recording ..................................................................... 55 Supported SD cards ...................................................... 55 Formatting (initializing) SD cards ............................... 55 Checking the remaining capacity ................................. 56 Proxy recording (Proxy Rec) ....................................... 56 Changing proxy recording settings .............................. 56 Recording and uploading a proxy file .......................... 56 4 About the recorded file ................................................. 56 Storage destination of the recorded file ....................... 57 About the file name ...................................................... 57 Recording proxy data only ........................................... 57 Connecting to Other Devices via LAN .................................. 57 Connecting using wireless LAN access point mode .... 58 Connecting using wireless LAN station mode ............. 59 Connecting to a device using a LAN cable .................. 61 Connecting to the Internet ..................................................... 63 Connecting using a modem/smartphone ...................... 63 Connecting using wireless LAN station mode (Wi-Fi station mode) .......................................................... 64 Connecting using a LAN cable .................................... 64 List of functions for network connections ................... 66 Uploading a File ...................................................................... 67 Preparations .................................................................. 67 Selecting a file and uploading ...................................... 68 Uploading files automatically ...................................... 69 Uploading using Secure FTP ....................................... 69 Transmitting Streaming Video and Audio ........................... 70 Setting the streaming destination and format ............... 70 Starting streaming ........................................................ 70 Stopping streaming ....................................................... 71 Network client mode .................................................... 71 Transmitting RTMP/RTMPS Streaming Video and Audio .................................................................................. 74 Setting the RTMP/RTMPS streaming destination and format ..................................................................... 74 Starting RTMP/RTMPS streaming .............................. 76 Stopping RTMP/RTMPS streaming ............................ 76 Using Web Remote Control ................................................... 77 Web Remote Control Menu ................................................... 78 Video monitoring settings (Monitoring Settings) ........ 78 File transfer settings (Upload Settings) ........................ 79 File transfer management (File Transfer) .................... 80 Thumbnail Screen Configuration of the Thumbnail Screen ............................... 82 Playing Clips ............................................................................ 83 Playing recorded clips .................................................. 83 Playing the selected and subsequent clips in sequence ................................................................. 83 5 Adding shot marks during playback (exFAT, UDF) ... 83 Monitoring audio during playback ............................... 83 Clip Operations ....................................................................... 84 Thumbnail menu operations ......................................... 84 Displaying clip properties ............................................ 85 Protecting clips (exFAT, UDF) .................................... 86 Copying clips ............................................................... 86 Deleting clips ............................................................... 87 Adding/deleting clip flags (exFAT, UDF) ................... 87 Filtering the clips displayed using the filtered clip thumbnail screen (exFAT, UDF) ........................... 87 Deleting shot marks (exFAT, UDF) ............................. 88 Filtering clips (frames) using the essence mark thumbnail screen (exFAT, UDF) ........................... 88 Uploading clips from the thumbnail screen or filtered clip thumbnail screen (exFAT, UDF, FAT) ........... 88 Changing the information displayed on the thumbnail screen ..................................................................... 88 Changing the index picture of a clip ............................ 88 External Device Connection Connecting External Monitors and Recording Devices ...... 89 External Synchronization ....................................................... 90 Managing/Editing Clips on a Computer ............................... 92 Connecting using a USB cable ..................................... 92 Connecting an external HDD/USB media ................... 92 Menu Display and Settings Setup Menu Configuration and Hierarchy .......................... 95 Setup menu hierarchy ................................................... 95 Setup Menu Operations .......................................................... 97 Editing the User menu .................................................. 99 Setup Menu List .................................................................... 101 User menu .................................................................. 101 Edit User Menu menu ................................................ 101 Camera menu ............................................................. 102 Paint menu .................................................................. 105 Audio menu ................................................................ 112 Video menu ................................................................ 113 LCD/VF menu ............................................................ 114 TC/UB menu .............................................................. 118 Recording menu ......................................................... 118 Thumbnail menu ........................................................ 120 6 Media menu ................................................................ 121 File menu .................................................................... 124 Network menu ............................................................ 125 System menu .............................................................. 133 Saving and Loading Configuration Data Configuration Data ............................................................... 140 Media supported for saving configuration data ......... 140 Formatting (initializing) media .................................. 140 Checking the remaining capacity ............................... 140 Saving a user file / ALL file ....................................... 141 Loading a user file / ALL fileNote x//viewrecordCHccc8c Sat9 /c84 F/78</text> What is the correct answer to this question: Which of following incorrect? Choices: (A) I(B(Cc(D. Format your response as follows: "The correct answer is (insert answer here)".
311
null
0
A
When I use a XQD memory card, I should format the card the first time I use the camcorder. To do this, I refer to the Media menu before the media is loaded.
Please read the following text and answer the question below. <text> 4-740-705-18(1) © 2018 Sony Corporation Solid-State Memory Camcorder Operating Instructions Before operating the unit, please read this manual thoroughly and retain it for future reference. PXW-Z280V/PXW-Z280T Software Version 6.0 2 Overview Location and Function of Parts ............................................... 8 Main unit ........................................................................ 8 Screen Display ......................................................................... 13 LCD/viewfinder screen ................................................ 13 Status screen ................................................................. 16 Preparation Power Supply ........................................................................... 22 Using a battery pack ..................................................... 22 Using AC power ........................................................... 23 Turning the camcorder on/off ...................................... 23 Setting the Clock ..................................................................... 24 Attaching Devices .................................................................... 24 Attaching the lens hood ................................................ 24 Attaching the large eyecup ........................................... 24 Adjusting the Screens ............................................................. 25 Adjusting the LCD screen ............................................ 25 Adjusting the viewfinder .............................................. 25 Adjusting the brightness of the LCD/viewfinder screen using an assignable button .......................... 25 Using SxS Memory Cards ...................................................... 26 About SxS memory cards ............................................. 26 Inserting SxS memory cards ........................................ 26 Removing an SxS memory card ................................... 26 Switching between SxS memory cards ........................ 26 Formatting (initializing) an SxS memory card ............. 26 Checking the remaining recording time ....................... 27 Restoring an SxS memory card .................................... 27 Using Other Media .................................................................. 28 XQD memory cards ..................................................... 28 SD cards ....................................................................... 29 Restoring an SD card ................................................... 29 Setting the Password for Network Access Authentication ................................................................... 30 Table of Contents 3 Shooting Basic Operation Procedure .................................................... 31 Shooting ....................................................................... 31 Adjusting the zoom ...................................................... 32 Adjusting the focus ...................................................... 33 Monitoring audio while shooting ................................. 34 Changing Basic Settings ......................................................... 34 Video format ................................................................ 34 Adjusting the brightness ............................................... 35 Adjusting for natural colors (white balance) ................ 36 Setting the audio to record ........................................... 38 Image stabilization ....................................................... 40 Time data ...................................................................... 40 Useful Functions ...................................................................... 41 Direct menu operation .................................................. 41 Face detection AF ........................................................ 41 Color bars/reference audio tone ................................... 43 Shot marks .................................................................... 43 OK/NG/KEEP flags (exFAT, UDF) ............................ 43 Reviewing a recording (Rec Review) .......................... 43 Assignable buttons ....................................................... 44 Interval recording (Interval Rec) .................................. 44 Continuous recording (Clip Continuous Rec) (exFAT, UDF) ...................................................................... 45 Picture cache recording (Picture Cache Rec) ............... 46 Slow & Quick Motion .................................................. 47 Simultaneous recording in 2 slots (Simul Rec) ............ 48 4K & HD (Sub) recording ............................................ 48 High dynamic range (HDR) recording ......................... 49 Adjusting the flange focal length automatically .......... 50 Acquiring location information (GPS) ......................... 51 Changing the audio channels using button operation ................................................................ 52 Planning Metadata .................................................................. 52 Loading a planning metadata file ................................. 52 Defining a clip name in planning metadata .................. 53 Defining shot mark names in planning metadata ......... 54 Transferring planning metadata files ........................... 55 Proxy Recording ..................................................................... 55 Supported SD cards ...................................................... 55 Formatting (initializing) SD cards ............................... 55 Checking the remaining capacity ................................. 56 Proxy recording (Proxy Rec) ....................................... 56 Changing proxy recording settings .............................. 56 Recording and uploading a proxy file .......................... 56 4 About the recorded file ................................................. 56 Storage destination of the recorded file ....................... 57 About the file name ...................................................... 57 Recording proxy data only ........................................... 57 Connecting to Other Devices via LAN .................................. 57 Connecting using wireless LAN access point mode .... 58 Connecting using wireless LAN station mode ............. 59 Connecting to a device using a LAN cable .................. 61 Connecting to the Internet ..................................................... 63 Connecting using a modem/smartphone ...................... 63 Connecting using wireless LAN station mode (Wi-Fi station mode) .......................................................... 64 Connecting using a LAN cable .................................... 64 List of functions for network connections ................... 66 Uploading a File ...................................................................... 67 Preparations .................................................................. 67 Selecting a file and uploading ...................................... 68 Uploading files automatically ...................................... 69 Uploading using Secure FTP ....................................... 69 Transmitting Streaming Video and Audio ........................... 70 Setting the streaming destination and format ............... 70 Starting streaming ........................................................ 70 Stopping streaming ....................................................... 71 Network client mode .................................................... 71 Transmitting RTMP/RTMPS Streaming Video and Audio .................................................................................. 74 Setting the RTMP/RTMPS streaming destination and format ..................................................................... 74 Starting RTMP/RTMPS streaming .............................. 76 Stopping RTMP/RTMPS streaming ............................ 76 Using Web Remote Control ................................................... 77 Web Remote Control Menu ................................................... 78 Video monitoring settings (Monitoring Settings) ........ 78 File transfer settings (Upload Settings) ........................ 79 File transfer management (File Transfer) .................... 80 Thumbnail Screen Configuration of the Thumbnail Screen ............................... 82 Playing Clips ............................................................................ 83 Playing recorded clips .................................................. 83 Playing the selected and subsequent clips in sequence ................................................................. 83 5 Adding shot marks during playback (exFAT, UDF) ... 83 Monitoring audio during playback ............................... 83 Clip Operations ....................................................................... 84 Thumbnail menu operations ......................................... 84 Displaying clip properties ............................................ 85 Protecting clips (exFAT, UDF) .................................... 86 Copying clips ............................................................... 86 Deleting clips ............................................................... 87 Adding/deleting clip flags (exFAT, UDF) ................... 87 Filtering the clips displayed using the filtered clip thumbnail screen (exFAT, UDF) ........................... 87 Deleting shot marks (exFAT, UDF) ............................. 88 Filtering clips (frames) using the essence mark thumbnail screen (exFAT, UDF) ........................... 88 Uploading clips from the thumbnail screen or filtered clip thumbnail screen (exFAT, UDF, FAT) ........... 88 Changing the information displayed on the thumbnail screen ..................................................................... 88 Changing the index picture of a clip ............................ 88 External Device Connection Connecting External Monitors and Recording Devices ...... 89 External Synchronization ....................................................... 90 Managing/Editing Clips on a Computer ............................... 92 Connecting using a USB cable ..................................... 92 Connecting an external HDD/USB media ................... 92 Menu Display and Settings Setup Menu Configuration and Hierarchy .......................... 95 Setup menu hierarchy ................................................... 95 Setup Menu Operations .......................................................... 97 Editing the User menu .................................................. 99 Setup Menu List .................................................................... 101 User menu .................................................................. 101 Edit User Menu menu ................................................ 101 Camera menu ............................................................. 102 Paint menu .................................................................. 105 Audio menu ................................................................ 112 Video menu ................................................................ 113 LCD/VF menu ............................................................ 114 TC/UB menu .............................................................. 118 Recording menu ......................................................... 118 Thumbnail menu ........................................................ 120 6 Media menu ................................................................ 121 File menu .................................................................... 124 Network menu ............................................................ 125 System menu .............................................................. 133 Saving and Loading Configuration Data Configuration Data ............................................................... 140 Media supported for saving configuration data ......... 140 Formatting (initializing) media .................................. 140 Checking the remaining capacity ............................... 140 Saving a user file / ALL file ....................................... 141 Loading a user file / ALL fileNote x//viewrecordCHccc8c Sat9 /c84 F/78</text> What is the correct answer to this question: Which of following incorrect? Choices: (A) I(B(Cc(D. Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> DATA PROJECTOR XJ-350 User’s Guide Keep this manual in a safe place for future reference. E • Digital Light ProcessingTM, DLPTM, Digital Micromirror DeviceTM, and DMDTM are trademarks of Texas Instruments Incorporated of the United States. • Microsoft, Windows, Windows NT, Windows XP , and the Windows logo are registered trademarks or trademarks of Microsoft Corporation of the United States in the United States and other countries. • Apple and Macintosh are registered trademarks of Apple Computer, Inc. of the United States. • Other company and product names may be registered trademarks or trademarks of their respective owners. この装置は、情報処理装置等電波障害自主規制協議会（VCCI）の基準に基づく クラスB の情報技術装置です。この装置は、家庭環境で使用することを目的と していますが、この装置がラジオやテレビジョン受信機に近接して使用される と、受信障害を引き起こすことがあります。取扱説明書に従って正しい取り扱 いをしてください。 Safety Precautions 3 Safety Precautions Thank you for selecting this CASIO product. Be sure to read these “Safety Precautions” before trying to use it. After reading this User’s Guide, keep it in a safe place for future reference. About safety symbols Various symbols are used in this User’s Guide and on the product itself to ensure safe use, and to protect you and others against the risk of injury and against material damage. The meaning of each of the symbols is explained below. Icon Examples Danger This symbol indicates a condition that, if ignored or applied incorrectly, creates the risk of death or serious personal injury. Warning This symbol indicates a condition that, if ignored or applied incorrectly, could possibly create the risk of death or serious personal injury. Caution This symbol indicates a condition that, if ignored or applied incorrectly, could possibly create the risk of personal injury or material damage. A triangle indicates a situation against which you need to exercise caution. The example shown here indicates you should take precaution against electric shock. A circle with a line through it indicates information about an action that you should not perform. The specific action is indicated by the figure inside the circle. The example shown here means disassembly is prohibited. A black circle indicates information about an action that you must perform. The specific action is indicated by the figure inside the circle. The example shown here indicates you must unplug the power cord from the power outlet. Safety Precautions 4 Precautions During Use GSmoke, odor, heat, loud noise, and other abnormalities Should you ever notice smoke, strange odor, or loud noise being emitted by the projector, or any other abnormality, immediately stop using the projector. Continued use creates the risk of fire and electric shock. Immediately perform the following steps. 1. Unplug the projector. 2. Contact your original dealer or authorized CASIO service center. GMalfunction Immediately stop using the projector if the screen appears abnormal, if sound is not produced, or if any other abnormal operation occurs even though you are operating the projector correctly. Continued use creates the risk of fire and electric shock. Immediately perform the following steps. 1. Turn off the projector. 2. Unplug the projector. 3. Contact your original dealer or authorized CASIO service center. GPower cord Misuse of the power cord creates the risk of fire and electric shock. Make sure that you always observe the following precautions. • Make sure that you use a power source with the same voltage as that specified for the projector. • Do not overload a power outlet with too many devices. GPower cord A damaged power cord creates the risk of fire and electric shock. Make sure that you always observe the following precautions. • Never place heavy objects on the power cord and never expose it to heat. • Make sure the power cord is not pinched between the wall and the rack or table where the projector is located, and never cover the power cord with a cushion or other object. • Never try to modify the power cord, allow it to become damaged, or subject it to excessive bending. • Do not twist the power cord or pull on it. GPower cord Never touch the power cord or plug while your hands are wet. Doing so creates the risk of electric shock. Warning 5 Safety Precautions GWater and foreign matter Never allow water to get on the projector. Water creates the risk of fire and electric shock. Never place a vase or any other container of water on top of the projector. Water creates the risk of fire and electric shock. Water or other liquid, or foreign matter (metal, etc.) getting into the projector creates the risk of fire and electric shock. Should anything get inside the projector, immediately perform the following steps. 1. Turn off the projector. 2. Unplug the projector. 3. Contact your original dealer or authorized CASIO service center. GDisassembly and modification Never try to take the projector apart or modify it in any way. The projector contains a large number of high-voltage components that create the risk of electric shock and burn injury. Be sure to leave all internal inspection, adjustment, and repair up to your original dealer or authorized CASIO service center. GDropping and impact Continued use of the projector after it has been damaged by dropping or other mistreatment creates the risk of fire and electric shock. Immediately perform the following steps. 1. Turn off the projector. 2. Unplug the projector. 3. Contact your original dealer or authorized CASIO service center. GDisposal by burning Never try to dispose of the projector by burning it. Doing so can cause an explosion, which creates the risk of fire and personal injury. GLooking into the lens or vents while lamp is on Never look directly into the lens or vents while lamp is on. The strong light emitted by the projector creates the risk of eye damage. GBlocking the vents Never allow the intake vents (on the bottom or back of the projector) or the exhaust vents (on the side of the projector) to become blocked. Doing so causes internal heat build up, which creates the risk of fire and breakdown of the projector. Touching the projector while it is hot creates the risk of burn injury. Make sure that you always observe the following precautions. • Allow at least 30 cm (11.8 inches) between the projector and walls. • Do not insert the projector into any space where air circulation is poor. • Never cover the projector with a blanket or any similar item. • Never use the projector on a carpet, blanket, towel, or other soft material. • Never stand the projector up on either end during use. Safety Precautions 6 GProjector cabinet Never open the projector’s cabinet. Doing so creates the risk of electric shock. GCleaning Before cleaning the projector, be sure to turn it off and unplug it from the power outlet. Failure to do so creates the risk of electric shock. GExhaust vents The exhaust vents become very hot while the projector is running. Never touch them. Doing so creates the risk of burn injury. The areas near the exhaust vents also become quite hot. Never locate objects made of plastic or other heat-sensitive materials near or under the projector. Doing so creates the risk of deformation and discoloration of the object. GLens cover Be sure to open the lens cover before turning on the projector. Never close the lens cover while the projector is in use. GLocation Never locate the projector in any of the following types of locations. Doing so creates the risk of fire and electric shock. • Near an area subject to strong vibration • An area subject to large amounts of moisture or dust • In a kitchen or other area exposed to oil smoke • Near a heater, on a heated carpet, or in an area exposed to direct sunlight • An area subject to temperature extremes (Operating temperature range is 5°C to 35°C (41 to 95 °F)). GHeavy objects Never place heavy objects on the projector or climb on top of the projector. Doing so creates the risk of fire and electric shock. GWater Never locate the projector in a bathroom or anywhere else there is the chance that it will be splashed with thetheadjust ke Project 9 ke1per 6061our J</text> What is the correct answer to this question: The X-3. I have questions. Could you help me check which of the following options correct? Choices: (A) The.. (B). (C. (D. Format your response as follows: "The correct answer is (insert answer here)".
312
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The projector has an internal lamp, and after approximately 2000 hours of use, the LAMP indicator will start flashing red, indicating that the lamp has reached its replacement period. At this time, you need to turn off the projector and unplug the AC power cord. Wait 60 minutes for the lamp to fully cool down, then turn the projector upside down, loosen the lamp cover, remove the screws fixing the lamp box, pull out the lamp box, insert the new lamp, secure the screws, and reattach the lamp cover.
Please read the following text and answer the question below. <text> DATA PROJECTOR XJ-350 User’s Guide Keep this manual in a safe place for future reference. E • Digital Light ProcessingTM, DLPTM, Digital Micromirror DeviceTM, and DMDTM are trademarks of Texas Instruments Incorporated of the United States. • Microsoft, Windows, Windows NT, Windows XP , and the Windows logo are registered trademarks or trademarks of Microsoft Corporation of the United States in the United States and other countries. • Apple and Macintosh are registered trademarks of Apple Computer, Inc. of the United States. • Other company and product names may be registered trademarks or trademarks of their respective owners. この装置は、情報処理装置等電波障害自主規制協議会（VCCI）の基準に基づく クラスB の情報技術装置です。この装置は、家庭環境で使用することを目的と していますが、この装置がラジオやテレビジョン受信機に近接して使用される と、受信障害を引き起こすことがあります。取扱説明書に従って正しい取り扱 いをしてください。 Safety Precautions 3 Safety Precautions Thank you for selecting this CASIO product. Be sure to read these “Safety Precautions” before trying to use it. After reading this User’s Guide, keep it in a safe place for future reference. About safety symbols Various symbols are used in this User’s Guide and on the product itself to ensure safe use, and to protect you and others against the risk of injury and against material damage. The meaning of each of the symbols is explained below. Icon Examples Danger This symbol indicates a condition that, if ignored or applied incorrectly, creates the risk of death or serious personal injury. Warning This symbol indicates a condition that, if ignored or applied incorrectly, could possibly create the risk of death or serious personal injury. Caution This symbol indicates a condition that, if ignored or applied incorrectly, could possibly create the risk of personal injury or material damage. A triangle indicates a situation against which you need to exercise caution. The example shown here indicates you should take precaution against electric shock. A circle with a line through it indicates information about an action that you should not perform. The specific action is indicated by the figure inside the circle. The example shown here means disassembly is prohibited. A black circle indicates information about an action that you must perform. The specific action is indicated by the figure inside the circle. The example shown here indicates you must unplug the power cord from the power outlet. Safety Precautions 4 Precautions During Use GSmoke, odor, heat, loud noise, and other abnormalities Should you ever notice smoke, strange odor, or loud noise being emitted by the projector, or any other abnormality, immediately stop using the projector. Continued use creates the risk of fire and electric shock. Immediately perform the following steps. 1. Unplug the projector. 2. Contact your original dealer or authorized CASIO service center. GMalfunction Immediately stop using the projector if the screen appears abnormal, if sound is not produced, or if any other abnormal operation occurs even though you are operating the projector correctly. Continued use creates the risk of fire and electric shock. Immediately perform the following steps. 1. Turn off the projector. 2. Unplug the projector. 3. Contact your original dealer or authorized CASIO service center. GPower cord Misuse of the power cord creates the risk of fire and electric shock. Make sure that you always observe the following precautions. • Make sure that you use a power source with the same voltage as that specified for the projector. • Do not overload a power outlet with too many devices. GPower cord A damaged power cord creates the risk of fire and electric shock. Make sure that you always observe the following precautions. • Never place heavy objects on the power cord and never expose it to heat. • Make sure the power cord is not pinched between the wall and the rack or table where the projector is located, and never cover the power cord with a cushion or other object. • Never try to modify the power cord, allow it to become damaged, or subject it to excessive bending. • Do not twist the power cord or pull on it. GPower cord Never touch the power cord or plug while your hands are wet. Doing so creates the risk of electric shock. Warning 5 Safety Precautions GWater and foreign matter Never allow water to get on the projector. Water creates the risk of fire and electric shock. Never place a vase or any other container of water on top of the projector. Water creates the risk of fire and electric shock. Water or other liquid, or foreign matter (metal, etc.) getting into the projector creates the risk of fire and electric shock. Should anything get inside the projector, immediately perform the following steps. 1. Turn off the projector. 2. Unplug the projector. 3. Contact your original dealer or authorized CASIO service center. GDisassembly and modification Never try to take the projector apart or modify it in any way. The projector contains a large number of high-voltage components that create the risk of electric shock and burn injury. Be sure to leave all internal inspection, adjustment, and repair up to your original dealer or authorized CASIO service center. GDropping and impact Continued use of the projector after it has been damaged by dropping or other mistreatment creates the risk of fire and electric shock. Immediately perform the following steps. 1. Turn off the projector. 2. Unplug the projector. 3. Contact your original dealer or authorized CASIO service center. GDisposal by burning Never try to dispose of the projector by burning it. Doing so can cause an explosion, which creates the risk of fire and personal injury. GLooking into the lens or vents while lamp is on Never look directly into the lens or vents while lamp is on. The strong light emitted by the projector creates the risk of eye damage. GBlocking the vents Never allow the intake vents (on the bottom or back of the projector) or the exhaust vents (on the side of the projector) to become blocked. Doing so causes internal heat build up, which creates the risk of fire and breakdown of the projector. Touching the projector while it is hot creates the risk of burn injury. Make sure that you always observe the following precautions. • Allow at least 30 cm (11.8 inches) between the projector and walls. • Do not insert the projector into any space where air circulation is poor. • Never cover the projector with a blanket or any similar item. • Never use the projector on a carpet, blanket, towel, or other soft material. • Never stand the projector up on either end during use. Safety Precautions 6 GProjector cabinet Never open the projector’s cabinet. Doing so creates the risk of electric shock. GCleaning Before cleaning the projector, be sure to turn it off and unplug it from the power outlet. Failure to do so creates the risk of electric shock. GExhaust vents The exhaust vents become very hot while the projector is running. Never touch them. Doing so creates the risk of burn injury. The areas near the exhaust vents also become quite hot. Never locate objects made of plastic or other heat-sensitive materials near or under the projector. Doing so creates the risk of deformation and discoloration of the object. GLens cover Be sure to open the lens cover before turning on the projector. Never close the lens cover while the projector is in use. GLocation Never locate the projector in any of the following types of locations. Doing so creates the risk of fire and electric shock. • Near an area subject to strong vibration • An area subject to large amounts of moisture or dust • In a kitchen or other area exposed to oil smoke • Near a heater, on a heated carpet, or in an area exposed to direct sunlight • An area subject to temperature extremes (Operating temperature range is 5°C to 35°C (41 to 95 °F)). GHeavy objects Never place heavy objects on the projector or climb on top of the projector. Doing so creates the risk of fire and electric shock. GWater Never locate the projector in a bathroom or anywhere else there is the chance that it will be splashed with thetheadjust ke Project 9 ke1per 6061our J</text> What is the correct answer to this question: The X-3. I have questions. Could you help me check which of the following options correct? Choices: (A) The.. (B). (C. (D. Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> Automatic Machine Translation Evaluation in Many Languages via Zero-Shot Paraphrasing Abstract We frame the task of machine translation evaluation as one of scoring machine transla- tion output with a sequence-to-sequence para- phraser, conditioned on a human reference. We propose training the paraphraser as a multi- lingual NMT system, treating paraphrasing as a zero-shot translation task (e.g., Czech to Czech). This results in the paraphraser’s out- put mode being centered around a copy of the input sequence, which represents the best case scenario where the MT system output matches a human reference. Our method is simple and intuitive, and does not require human judge- ments for training. Our single model (trained in 39 languages) outperforms or statistically ties with all prior metrics on the WMT 2019 segment-level shared metrics task in all lan- guages (excluding Gujarati where the model had no training data). We also explore us- ing our model for the task of quality estima- tion as a metric—conditioning on the source instead of the reference—and find that it sig- nificantly outperforms every submission to the WMT 2019 shared task on quality estimation in every language pair. 1 Introduction Machine Translation (MT) systems have improved dramatically in the past several years. This is largely due to advances in neural MT (NMT) methods, but the pace of improvement would not have been possible without automatic MT metrics, which provide immediate feedback on MT qual- ity without the time and expense associated with obtaining human judgments of MT output. However, the improvements that existing auto- matic metrics helped enable are now causing the correlation between human judgments and auto- matic metrics to break down (Ma et al., 2019; Mathur et al., 2020) especially for BLEU (Papineni et al., 2002), which has been the de facto standard Hi (p=.3) world (p=.6) world <EN> Hi Language- Agnostic Represen- tation amico <FR> Salut Salut l’ami TRAINING: SCORING: Ciao Hello Language- Agnostic Represen- tation Figure 1: Our model is trained on multilingual paral- lel examples such as “Ciao amico” translated to French is “Salut l’ami.” At evaluation time, the model is used in zero-shot mode to score MT system outputs conditioned on their corresponding human references. For example, the MT system output “Hi world” condi- tioned on the human reference “Hello world” is found to have token probabilities [0.3, 0.6]. metric since its introduction almost two decades ago. The problem currently appears limited to very strong systems, but as hardware, modeling, and available training data improve, it is likely BLEU will fail more frequently in the future. This could prove extremely detrimental if the MT community fails to adopt an improved metric, as good ideas could quietly be discarded or rejected from publi- cation because they do not correlate with BLEU. In fact, this may already be happening. We propose using a sentential, sequence-to- sequence paraphraser to force-decode and score MT outputs conditioned on their corresponding hu- man references. Our model implicitly represents the entire (exponentially large) set of potential para- phrases of a sentence, both valid and invalid; by “querying” the model with a particular system out- 91 put, we can use the model score to measure how well the system output paraphrases the human ref- erence translation. Our model is not trained on any human quality judgements, which are not available in many domains and/or language pairs. The best possible MT output is one which per- fectly matches a human reference; therefore, for evaluation, an ideal paraphraser would be one with an output distribution centered around a copy of its input sentence. We denote such a model a “lex- ically/syntactically unbiased paraphraser” to dis- tinguish it from a standard paraphraser trained to produce output which conveys the meaning of the input while also being lexically and/or syntacti- cally different from it. For this reason, we propose using a multilingual NMT system as an unbiased paraphraser by treating paraphrasing as zero-shot “translation” (e.g., Czech to Czech). We show that a multilingual NMT model is much closer to an ideal lexically/syntactically unbiased paraphraser than a generative paraphraser trained on synthetic paraphrases. It also allows a single model to work in many languages, and can be applied to the task of “Quality estimation (QE) as a metric” (Fonseca et al., 2019) by conditioning on the source instead of the reference. Figure 1 illustrates our method, which we denote Prism (Probability is the metric). We train a single model in 39 languages and show that it: • Outperforms or ties with prior metrics and several contrastive neural methods on the segment-level WMT 2019 MT metrics task in every language pair;1 • Is able to discriminate between very strong neural systems at the system level, addressing a problem raised at WMT 2019; and • Significantly outperforms all QE metrics sub- mitted to the WMT 2019 QE shared task Finally, we contrast the effectiveness of our model when scoring MT output using the source vs the hu- man reference. We observe that human references substantially improve performance, and, crucially, allow our model to rank systems that are substan- tially better than our model at the task of transla- tion. This is important because it establishes that our method does not require building a state-of-the- art multilingual NMT model in order to produce a state-of-the-art MT metric capable of evaluating state-of-the-art MT systems. 1Except for Gujarati, where we had no training data. We release our model, metrics toolkit, and pre- processed training data.2 2 Related Work MT Metrics Early MT metrics like BLEU (Pa- pineni et al., 2002) and NIST (Doddington, 2002) use token-level n-gram overlap between the MT output and the human reference. Overlap can also be measured at the character level (Popovi´ c, 2015, 2017) or using edit distance (Snover et al., 2006). Many metrics use word- and/or sentence- level embeddings, including ReVal (Gupta et al., 2015), RUSE (Shimanaka et al., 2018), WMDO (Chow et al., 2019), and ESIM (Mathur et al., 2019). MEANT (Lo and Wu, 2011) and MEANT 2.0 (Lo, 2017) measure similarity between semantic frames and role fillers. State-of-the-art methods including YiSi (Lo, 2019) and BERTscore (Zhang et al., 2019, 2020) rely on contextualized embeddings (Devlin et al., 2019) trained on large (non-parallel) corpora. BLEURT (Sellam et al., 2020) applies fine tuning of BERT, including training on prior human judge- ments. In contrast, our work exploits parallel bitext and doesn’t require training on human judgements. Paraphrase Databases Prior work explored us- ing parallel bitext to identify phrase level para- phrases (Bannard and Callison-Burch, 2005; Gan- itkevitch et al., 2013) including bitext in multiple language pairs (Ganitkevitch and Callison-Burch, 2014). Paraphrase tables were, in turn, used in MT metrics to reward systems for paraphrasing words (Banerjee and Lavie, 2005) or phrases (Zhou et al., 2006; Denkowski and Lavie, 2010) from the human reference. Our work can be viewed as extending this idea to the sentence level, without having to enumerate the millions or billions of paraphrases (Dreyer and Marcu, 2012) for each sentence. Multilingual NMT Multilingual NMT (Dong et al., 2015) has been shown to rival performance of single language pair models011A0000000000.) B000-se[1111110018 </text> What is the correct answer to this question: What is the main difference between these two articles that is incorrect? Choices: (A) Bart . (B)-se. (C) B. (D) B. Format your response as follows: "The correct answer is (insert answer here)".
313
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3
D
BARTSCORE uses the token level generation probability of the model for evaluation, while PRISM uses the comparison of x and y probabilities for evaluation.
Please read the following text and answer the question below. <text> Automatic Machine Translation Evaluation in Many Languages via Zero-Shot Paraphrasing Abstract We frame the task of machine translation evaluation as one of scoring machine transla- tion output with a sequence-to-sequence para- phraser, conditioned on a human reference. We propose training the paraphraser as a multi- lingual NMT system, treating paraphrasing as a zero-shot translation task (e.g., Czech to Czech). This results in the paraphraser’s out- put mode being centered around a copy of the input sequence, which represents the best case scenario where the MT system output matches a human reference. Our method is simple and intuitive, and does not require human judge- ments for training. Our single model (trained in 39 languages) outperforms or statistically ties with all prior metrics on the WMT 2019 segment-level shared metrics task in all lan- guages (excluding Gujarati where the model had no training data). We also explore us- ing our model for the task of quality estima- tion as a metric—conditioning on the source instead of the reference—and find that it sig- nificantly outperforms every submission to the WMT 2019 shared task on quality estimation in every language pair. 1 Introduction Machine Translation (MT) systems have improved dramatically in the past several years. This is largely due to advances in neural MT (NMT) methods, but the pace of improvement would not have been possible without automatic MT metrics, which provide immediate feedback on MT qual- ity without the time and expense associated with obtaining human judgments of MT output. However, the improvements that existing auto- matic metrics helped enable are now causing the correlation between human judgments and auto- matic metrics to break down (Ma et al., 2019; Mathur et al., 2020) especially for BLEU (Papineni et al., 2002), which has been the de facto standard Hi (p=.3) world (p=.6) world <EN> Hi Language- Agnostic Represen- tation amico <FR> Salut Salut l’ami TRAINING: SCORING: Ciao Hello Language- Agnostic Represen- tation Figure 1: Our model is trained on multilingual paral- lel examples such as “Ciao amico” translated to French is “Salut l’ami.” At evaluation time, the model is used in zero-shot mode to score MT system outputs conditioned on their corresponding human references. For example, the MT system output “Hi world” condi- tioned on the human reference “Hello world” is found to have token probabilities [0.3, 0.6]. metric since its introduction almost two decades ago. The problem currently appears limited to very strong systems, but as hardware, modeling, and available training data improve, it is likely BLEU will fail more frequently in the future. This could prove extremely detrimental if the MT community fails to adopt an improved metric, as good ideas could quietly be discarded or rejected from publi- cation because they do not correlate with BLEU. In fact, this may already be happening. We propose using a sentential, sequence-to- sequence paraphraser to force-decode and score MT outputs conditioned on their corresponding hu- man references. Our model implicitly represents the entire (exponentially large) set of potential para- phrases of a sentence, both valid and invalid; by “querying” the model with a particular system out- 91 put, we can use the model score to measure how well the system output paraphrases the human ref- erence translation. Our model is not trained on any human quality judgements, which are not available in many domains and/or language pairs. The best possible MT output is one which per- fectly matches a human reference; therefore, for evaluation, an ideal paraphraser would be one with an output distribution centered around a copy of its input sentence. We denote such a model a “lex- ically/syntactically unbiased paraphraser” to dis- tinguish it from a standard paraphraser trained to produce output which conveys the meaning of the input while also being lexically and/or syntacti- cally different from it. For this reason, we propose using a multilingual NMT system as an unbiased paraphraser by treating paraphrasing as zero-shot “translation” (e.g., Czech to Czech). We show that a multilingual NMT model is much closer to an ideal lexically/syntactically unbiased paraphraser than a generative paraphraser trained on synthetic paraphrases. It also allows a single model to work in many languages, and can be applied to the task of “Quality estimation (QE) as a metric” (Fonseca et al., 2019) by conditioning on the source instead of the reference. Figure 1 illustrates our method, which we denote Prism (Probability is the metric). We train a single model in 39 languages and show that it: • Outperforms or ties with prior metrics and several contrastive neural methods on the segment-level WMT 2019 MT metrics task in every language pair;1 • Is able to discriminate between very strong neural systems at the system level, addressing a problem raised at WMT 2019; and • Significantly outperforms all QE metrics sub- mitted to the WMT 2019 QE shared task Finally, we contrast the effectiveness of our model when scoring MT output using the source vs the hu- man reference. We observe that human references substantially improve performance, and, crucially, allow our model to rank systems that are substan- tially better than our model at the task of transla- tion. This is important because it establishes that our method does not require building a state-of-the- art multilingual NMT model in order to produce a state-of-the-art MT metric capable of evaluating state-of-the-art MT systems. 1Except for Gujarati, where we had no training data. We release our model, metrics toolkit, and pre- processed training data.2 2 Related Work MT Metrics Early MT metrics like BLEU (Pa- pineni et al., 2002) and NIST (Doddington, 2002) use token-level n-gram overlap between the MT output and the human reference. Overlap can also be measured at the character level (Popovi´ c, 2015, 2017) or using edit distance (Snover et al., 2006). Many metrics use word- and/or sentence- level embeddings, including ReVal (Gupta et al., 2015), RUSE (Shimanaka et al., 2018), WMDO (Chow et al., 2019), and ESIM (Mathur et al., 2019). MEANT (Lo and Wu, 2011) and MEANT 2.0 (Lo, 2017) measure similarity between semantic frames and role fillers. State-of-the-art methods including YiSi (Lo, 2019) and BERTscore (Zhang et al., 2019, 2020) rely on contextualized embeddings (Devlin et al., 2019) trained on large (non-parallel) corpora. BLEURT (Sellam et al., 2020) applies fine tuning of BERT, including training on prior human judge- ments. In contrast, our work exploits parallel bitext and doesn’t require training on human judgements. Paraphrase Databases Prior work explored us- ing parallel bitext to identify phrase level para- phrases (Bannard and Callison-Burch, 2005; Gan- itkevitch et al., 2013) including bitext in multiple language pairs (Ganitkevitch and Callison-Burch, 2014). Paraphrase tables were, in turn, used in MT metrics to reward systems for paraphrasing words (Banerjee and Lavie, 2005) or phrases (Zhou et al., 2006; Denkowski and Lavie, 2010) from the human reference. Our work can be viewed as extending this idea to the sentence level, without having to enumerate the millions or billions of paraphrases (Dreyer and Marcu, 2012) for each sentence. Multilingual NMT Multilingual NMT (Dong et al., 2015) has been shown to rival performance of single language pair models011A0000000000.) B000-se[1111110018 </text> What is the correct answer to this question: What is the main difference between these two articles that is incorrect? Choices: (A) Bart . (B)-se. (C) B. (D) B. Format your response as follows: "The correct answer is (insert answer here)".
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1017, 1018, 1019, 1020, 1021, 1022, 1023, 1024, 1025, 1026, 1027, 1028, 1029, 1030, 1031, 1032, 1033, 1034, 1035, 1036, 1037, 1038, 1039, 1040, 1041, 1042, 1043, 1044, 1045, 1046, 1047, 1048, 1049, 1050, 1051, 1052, 1053, 1054, 1055, 1056, 1057, 1058, 1059, 1060, 1061, 1062, 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1071, 1072, 1073, 1074, 1075, 1076, 1077, 1078, 1079, 1080, 1081, 1082, 1083, 1084, 1085, 1086, 1087, 1088, 1089, 1090, 1091, 1092, 1093, 1094, 1095, 1096, 1097, 1098, 1099, 1100, 1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109, 1110, 1111, 1112, 1113, 1114, 1115, 1116, 1117, 1118, 1119, 1120, 1121, 1122, 1123, 1124, 1125, 1126, 1127, 1128, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1137, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1146, 1147, 1148, 1149, 1150, 1151, 1152, 1153, 1154, 1155, 1156, 1157, 1158, 1159, 1160, 1161, 1162, 1163, 1164, 1165, 1166, 1167, 1168, 1169, 1170, 1171, 1172, 1173, 1174, 1175, 1176, 1177, 1178, 1179, 1180, 1181, 1182, 1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219, 1220, 1221, 1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1235, 1236, 1237, 1238, 1239, 1240, 1241, 1242, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1251, 1252, 1253, 1254, 1255, 1256, 1257, 1258, 1259, 1260, 1261, 1262, 1263, 1264, 1265, 1266, 1267, 1268, 1269, 1270, 1271, 1272, 1273, 1274, 1275, 1276, 1277, 1278, 1279, 1280, 1281, 1282, 1283, 1284, 1285, 1286, 1287, 1288, 1289, 1290, 1291, 1292, 1293, 1294, 1295, 1296, 1297, 1298, 1299, 1300, 1301, 1302, 1303, 1304, 1305, 1306, 1307, 1308, 1309, 1310, 1311, 1312, 1313, 1314, 1315, 1316, 1317, 1318, 1319, 1320, 1321, 1322, 1323, 1324, 1325, 1326, 1327, 1328, 1329, 1330, 1331, 1332, 1333, 1334, 1335, 1336, 1337, 1338, 1339, 1340, 1341, 1342, 1343, 1344, 1345, 1346, 1347, 1348, 1349, 1350, 1351, 1352, 1353, 1354, 1355, 1356, 1357, 1358, 1359, 1360, 1361, 1362, 1363, 1364, 1365, 1366, 1367, 1368, 1369, 1370, 1371, 1372, 1373, 1374, 1375, 1376, 1377, 1378, 1379, 1380, 1381, 1382, 1383, 1384, 1385, 1386, 1387, 1388, 1389, 1390, 1391, 1392, 1393, 1394, 1395, 1396, 1397, 1398, 1399, 1400, 1401, 1402, 1403, 1404, 1405, 1406, 1407, 1408, 1409, 1410, 1411, 1412, 1413, 1414, 1415, 1416, 1417, 1418, 1419, 1420, 1421, 1422, 1423, 1424, 1425, 1426, 1427, 1428, 1429, 1430, 1431, 1432, 1433, 1434, 1435, 1436, 1437, 1438, 1439, 1440, 1441, 1442, 1443, 1444, 1445, 1446, 1447, 1448, 1449, 1450, 1451, 1452, 1453, 1454, 1455, 1456, 1457, 1458, 1459, 1460, 1461, 1462, 1463, 1464, 1465, 1466, 1467, 1468, 1469, 1470, 1471, 1472, 1473, 1474, 1475, 1476, 1477, 1478, 1479, 1480, 1481, 1482, 1483, 1484, 1485, 1486, 1487, 1488, 1489, 1490, 1491, 1492, 1493, 1494, 1495, 1496, 1497, 1498, 1499, 1500, 1501, 1502, 1503, 1504, 1505, 1506, 1507, 1508, 1509, 1510, 1511, 1512, 1513, 1514, 1515, 1516, 1517, 1518, 1519, 1520, 1521, 1522, 1523, 1524, 1525, 1526, 1527, 1528, 1529, 1530, 1531, 1532, 1533, 1534, 1535, 1536, 1537, 1538, 1539, 1540, 1541, 1542, 1543, 1544, 1545, 1546, 1547, 1548, 1549, 1550, 1551, 1552, 1553, 1554, 1555, 1556, 1557, 1558, 1559, 1560, 1561, 1562, 1563, 1564, 1565, 1566, 1567, 1568, 1569, 1570, 1571, 1572, 1573, 1574, 1575, 1576, 1577, 1578, 1579, 1580, 1581, 1582, 1583, 1584, 1585, 1586, 1587, 1588, 1589, 1590, 1591, 1592, 1593, 1594, 1595, 1596, 1597, 1598, 1599, 1600, 1601, 1602, 1603, 1604, 1605, 1606, 1607, 1608, 1609, 1610, 1611, 1612, 1613, 1614, 1615, 1616, 1617, 1618, 1619, 1620, 1621, 1622, 1623, 1624, 1625, 1626, 1627, 1628, 1629, 1630, 1631, 1632, 1633, 1634, 1635, 1636, 1637, 1638, 1639, 1640, 1641, 1642, 1643, 1644, 1645, 1646, 1647, 1648, 1649, 1650, 1651, 1652, 1653, 1654, 1655, 1656, 1657, 1658, 1659, 1660, 1661, 1662, 1663, 1664, 1665, 1666, 1667, 1668, 1669, 1670, 1671, 1672, 1673, 1674, 1675, 1676, 1677, 1678, 1679, 1680, 1681, 1682, 1683, 1684, 1685, 1686, 1687, 1688, 1689, 1690, 1691, 1692, 1693, 1694, 1695, 1696, 1697, 1698, 1699, 1700, 1701, 1702, 1703, 1704, 1705, 1706, 1707, 1708, 1709, 1710, 1711, 1712, 1713, 1714, 1715, 1716, 1717, 1718, 1719, 1720, 1721, 1722, 1723, 1724, 1725, 1726, 1727, 1728, 1729, 1730, 1731, 1732, 1733, 1734, 1735, 1736, 1737, 1738, 1739, 1740, 1741, 1742, 1743, 1744, 1745, 1746, 1747, 1748, 1749, 1750, 1751, 1752, 1753, 1754, 1755, 1756, 1757, 1758, 1759, 1760, 1761, 1762, 1763, 1764, 1765, 1766, 1767, 1768, 1769, 1770, 1771, 1772, 1773, 1774, 1775, 1776, 1777, 1778, 1779, 1780, 1781, 1782, 1783, 1784, 1785, 1786, 1787, 1788, 1789, 1790, 1791, 1792, 1793, 1794, 1795, 1796, 1797, 1798, 1799, 1800, 1801, 1802, 1803, 1804, 1805, 1806, 1807, 1808, 1809, 1810, 1811, 1812, 1813, 1814, 1815, 1816, 1817, 1818, 1819, 1820, 1821, 1822, 1823, 1824, 1825, 1826, 1827, 1828, 1829, 1830, 1831, 1832, 1833, 1834, 1835, 1836, 1837, 1838, 1839, 1840, 1841, 1842, 1843, 1844, 1845, 1846, 1847, 1848, 1849, 1850, 1851, 1852, 1853, 1854, 1855, 1856, 1857, 1858, 1859, 1860, 1861, 1862, 1863, 1864, 1865, 1866, 1867, 1868, 1869, 1870, 1871, 1872, 1873, 1874, 1875, 1876, 1877, 1878, 1879, 1880, 1881, 1882, 1883, 1884, 1885, 1886, 1887, 1888, 1889, 1890, 1891, 1892, 1893, 1894, 1895, 1896, 1897, 1898, 1899, 1900, 1901, 1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913, 1914, 1915, 1916, 1917, 1918, 1919, 1920, 3429, 8078, 8165, 9112, 9122, 9429, 9866, 11470, 11471, 11486, 11510, 11608, 13278, 15608, 15609, 15612, 15613, 15614, 15647, 15648, 15654, 15655, 15730, 15737, 16142, 16151, 16157, 16165, 16172, 16268, 16902, 17185, 17339, 17364, 17396, 17401, 17402, 17403, 17409, 17410, 17510, 17623, 17632, 17637, 17930, 17931, 17932, 17933, 17934, 18138, 18159, 18305, 18338, 18681, 18682, 18777, 19580, 19582, 19583, 19904, 19905, 19915, 20191, 20198, 23952, 28400, 33102, 38773, 39487, 43346, 46828, 48331, 49084, 49175, 49626, 58252, 75966, 82043, 85885, 88591, 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0.013277
154,253
Please read the following text and answer the question below. <text> Help Guide Interchangeable Lens Digital Camera ILME-FX3 Ver.2 or later If your camera’s system software (firmware) is Ver.3.00 or later, use Creators’ App on your smartphone. Imaging Edge Mobile cannot be used. For details on Creators’ App, refer to the following website. https://www.sony.net/ca/ Recommended pages in the Help Guide Support information Finding functions from MENU You can check the list of the menu items. You can also move to the explanation page for each item from the menu item on the list. Log Shooting Setting Configures the settings for Log shooting. Using the Main menu (shooting setting list) Select the (Main) tab on the menu screen to display a list of shooting settings. Firmware, Questions & Answers and Compatibility This website provides Firmware update, Question & Answers and Compatibility information Basic Knowledge Improve your shooting techniques by learning the basics of camera. How to use the “Help Guide” Before Use Checking the camera and the supplied items Memory cards that can be used Notes on using your camera Precautions 1 Lending, transferring or discarding the camera and/or memory card to others (Notes on protecting private information) Notes on the battery pack and charging the battery Notes on memory card Cleaning the image sensor (Sensor Cleaning) On cleaning Names of parts Front side Rear side Top side Sides Bottom XLR handle unit Basic icons displayed on the monitor Basic operations Touch operations on the monitor Using the control wheel Using the multi-selector Using the MODE (Mode) button Using the menu Using the Main menu (shooting setting list) Using the function menu Using the custom buttons Using the DISP (Display Setting) button Using the Delete button Using the front dial and rear dial Using the keyboard In-Camera Guide Preparing the camera/Basic shooting operations 2 Charging the battery pack Charging the battery pack using a charger Inserting/removing the battery pack Charging the battery with a commercially available AC adaptor or mobile battery Using the battery charger abroad Supplying power from a wall outlet (wall socket) Inserting/removing a memory card Attaching/removing a lens Attaching the supplied XLR handle unit Performing initial setup for the camera Basic shooting operations Confirmation before shooting Shooting movies Shooting still images (Intelligent Auto) Finding functions from MENU Using the shooting functions Contents of this chapter Selecting a shooting mode Exposure Ctrl Type Auto/Manual Swt. Set. Movie: Exposure Mode S&Q Motion: Exposure Mode Intelligent Auto Program Auto Aperture Priority Shutter Priority Manual Exposure Shutter Mode Bulb shooting 3 Auto Slow Shutter Focusing Selecting the focus method (Focus Mode) Selecting the focus area (Focus Area) Tracking subject (Tracking function) Manual Focus Direct manual focus (DMF) Face/Eye AF Focusing on human eyes Face/Eye Prior. in AF (still image/movie) Face/Eye Subject (still image/movie) Right/Left Eye Select (still image/movie) Face/Eye Frame Disp. (still image/movie) Face Memory Regist. Faces Priority (still image/movie) Using focusing functions Focus Standard Adjusting the focus area settings to the camera’s orientation (horizontal/vertical) (Switch V/H AF Area) Registering the current focus area (AF Area Registration) Deleting a registered AF Area (Del. Regist. AF Area) Focus Area Limit (still image/movie) Circ. of Focus Point (still image/movie) AF Frame Move Amt (still image/movie) Focus Area Color (still image/movie) AF Area Auto Clear AF-C Area Display Phase Detect. Area AF Tracking Sensitivity AF Transition Speed AF Subj. Shift Sensitivity 4 AF Assist AF/MF Selector AF w/ Shutter AF On Focus Hold Pre-AF Priority Set in AF-S Priority Set in AF-C AF Illuminator Aperture Drive in AF AF in Focus Mag. Auto Magnifier in MF Focus Magnifier Focus Magnif. Time (still image/movie) Initial Focus Mag. (movie) Initial Focus Mag. (still image) Peaking Display Adjusting the exposure/metering modes Exposure Comp. (still image/movie) Histogram display Exposure step (still image/movie) Exposure Std. Adjust (still image/movie) D-Range Optimizer (still image/movie) Metering Mode (still image/movie) Face Priority in Multi Metering (still image/movie) Spot Metering Point (still image/movie) AE lock AEL w/ Shutter Zebra Display Selecting the ISO sensitivity 5 ISO (still image/movie) ISO Range Limit (still image/movie) ISO AUTO Min. SS White balance White Balance (still image/movie) Capturing a standard white color to set the white balance (custom white balance) Priority Set in AWB (still image/movie) Shutter AWB Lock Shockless WB Log shooting settings Log shooting Log Shooting Setting Select LUT Manage User LUTs Base ISO Exposure Index Display LUT Adding effects to images Creative Look (still image/movie) Picture Profile (still image/movie) Shooting with drive modes (continuous shooting/self-timer) Drive Mode Cont. Shooting Self-timer(Single) Self-timer(Cont) Cont. Bracket Single Bracket Indicator during bracket shooting WB bracket DRO Bracket 6 Bracket Settings Interval Shoot Func. Setting the image quality and recording format JPEG/HEIF Switch Image Quality Settings: File Format (still image) Image Quality Settings: RAW File Type Image Quality Settings: JPEG Quality/HEIF Quality Image Quality Settings: JPEG Image Size/HEIF Image Size Aspect Ratio HLG Still Image Color Space File Format (movie) Movie Settings (movie) S&Q Settings Proxy Settings APS-C S35 (Super 35mm) Shooting (still image/movie) Angle of view Using touch functions Touch Operation Touch Sensitivity Swipe Up Touch Func. in Shooting Focusing using touch operations (Touch Focus) Starting tracking with touch operations (Touch Tracking) Shutter settings Silent Mode Settings (still image/movie) Shutter Type e-Front Curtain Shut. Release w/o Lens (still image/movie) Release w/o Card 7 Anti-flicker Shoot. Using the zoom The zoom features available with this product Clear Image Zoom/Digital Zoom Zoom Range (still image/movie) Zoom Lever Speed (still image/movie) Custom Key Z. Speed (still image/movie) Remote Zoom Speed (still image/movie) About zoom scale Zoom Ring Rotate Using the flash Using flash (sold separately) Flash Mode Flash Comp. Exp.comp.set Wireless Flash Red Eye Reduction FEL lock External Flash Set. Reducing blur SteadyShot (still image) SteadyShot (movie) SteadyShot Adjust. (still image/movie) SteadyShot focal length (still image/movie) Lens Compensation (still image/movie) Noise reduction Long Exposure NR High ISO NR Setting the monitor display during shooting Auto Review (still image) 8 Remain Shoot Display (still image) Grid Line Display (still image/movie) Grid Line Type (still image/movie) Live View Display Set. Aperture Preview Shot. Result Preview Bright Monitoring Emphasized REC Display Marker Display Gamma Display Assist Gamma Disp. Assist Typ. De-Squeeze Display Recording movie audio Audio Recording Audio Rec Level Audio Out Timing Wind Noise Reduct. Shoe Audio Set. Recording audio using the XLR adaptor of the supplied handle TC/UB settings TC/UB TC/UB Disp. Setting Matching the time code with other devices Livestreaming video and audio Network Streaming (movie) Customizing the camera Contents of this chapter Customization features of the camera Assigning frequently used functions to buttons and dials (Custom Key/Dial Set.) 9 Changing the function of the dial temporarily (My Dial Settings) Registering and recalling camera settings Camera Set. Memory Recall Camera Setting Memory/Recall Media Registering shooting settings to a custom key (Reg. Custom Shoot Set) Registering frequently used functions to the function menu Fn Menu Settings Registering frequently used functions to My Menu Add Item Sort Item Delete Item Delete Page Delete All Display From My Menu Separately adjusting the camera settings for still images and movies Different Set for Still/Mv Customizing the functions of the ring/dial Av/Tv Rotate Function Ring(Lens) Lock Operation Parts Recording movies by pressing the shutter button REC w/ Shutter (movie) Monitor settings Monitor Flip Direction DISP (Screen Disp) Set Viewing Contents of this chapter Viewing images computer Topic Ver . 5 5 Copyright7 3(B) (C)3. the function also29012382-F Topic CorporationHelp Guide Camera Hint2 CorporationHelp” at the bottom of9 of55Note Topic2Help Guide, etc is display Ver Ver Ver Ver Ver VerNote Topic orXPL/D40/M4-0</> What correct answer to this question: What true the to? Choices: (A). (B I. (C me. 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Touch operations allow me to focus on the monitor. When I'm wearing gloves, I may set Touch Sensitivity to "Sensitive" instead of "Standard" for better responsivity.
Please read the following text and answer the question below. <text> Help Guide Interchangeable Lens Digital Camera ILME-FX3 Ver.2 or later If your camera’s system software (firmware) is Ver.3.00 or later, use Creators’ App on your smartphone. Imaging Edge Mobile cannot be used. For details on Creators’ App, refer to the following website. https://www.sony.net/ca/ Recommended pages in the Help Guide Support information Finding functions from MENU You can check the list of the menu items. You can also move to the explanation page for each item from the menu item on the list. Log Shooting Setting Configures the settings for Log shooting. Using the Main menu (shooting setting list) Select the (Main) tab on the menu screen to display a list of shooting settings. Firmware, Questions & Answers and Compatibility This website provides Firmware update, Question & Answers and Compatibility information Basic Knowledge Improve your shooting techniques by learning the basics of camera. How to use the “Help Guide” Before Use Checking the camera and the supplied items Memory cards that can be used Notes on using your camera Precautions 1 Lending, transferring or discarding the camera and/or memory card to others (Notes on protecting private information) Notes on the battery pack and charging the battery Notes on memory card Cleaning the image sensor (Sensor Cleaning) On cleaning Names of parts Front side Rear side Top side Sides Bottom XLR handle unit Basic icons displayed on the monitor Basic operations Touch operations on the monitor Using the control wheel Using the multi-selector Using the MODE (Mode) button Using the menu Using the Main menu (shooting setting list) Using the function menu Using the custom buttons Using the DISP (Display Setting) button Using the Delete button Using the front dial and rear dial Using the keyboard In-Camera Guide Preparing the camera/Basic shooting operations 2 Charging the battery pack Charging the battery pack using a charger Inserting/removing the battery pack Charging the battery with a commercially available AC adaptor or mobile battery Using the battery charger abroad Supplying power from a wall outlet (wall socket) Inserting/removing a memory card Attaching/removing a lens Attaching the supplied XLR handle unit Performing initial setup for the camera Basic shooting operations Confirmation before shooting Shooting movies Shooting still images (Intelligent Auto) Finding functions from MENU Using the shooting functions Contents of this chapter Selecting a shooting mode Exposure Ctrl Type Auto/Manual Swt. Set. Movie: Exposure Mode S&Q Motion: Exposure Mode Intelligent Auto Program Auto Aperture Priority Shutter Priority Manual Exposure Shutter Mode Bulb shooting 3 Auto Slow Shutter Focusing Selecting the focus method (Focus Mode) Selecting the focus area (Focus Area) Tracking subject (Tracking function) Manual Focus Direct manual focus (DMF) Face/Eye AF Focusing on human eyes Face/Eye Prior. in AF (still image/movie) Face/Eye Subject (still image/movie) Right/Left Eye Select (still image/movie) Face/Eye Frame Disp. (still image/movie) Face Memory Regist. Faces Priority (still image/movie) Using focusing functions Focus Standard Adjusting the focus area settings to the camera’s orientation (horizontal/vertical) (Switch V/H AF Area) Registering the current focus area (AF Area Registration) Deleting a registered AF Area (Del. Regist. AF Area) Focus Area Limit (still image/movie) Circ. of Focus Point (still image/movie) AF Frame Move Amt (still image/movie) Focus Area Color (still image/movie) AF Area Auto Clear AF-C Area Display Phase Detect. Area AF Tracking Sensitivity AF Transition Speed AF Subj. Shift Sensitivity 4 AF Assist AF/MF Selector AF w/ Shutter AF On Focus Hold Pre-AF Priority Set in AF-S Priority Set in AF-C AF Illuminator Aperture Drive in AF AF in Focus Mag. Auto Magnifier in MF Focus Magnifier Focus Magnif. Time (still image/movie) Initial Focus Mag. (movie) Initial Focus Mag. (still image) Peaking Display Adjusting the exposure/metering modes Exposure Comp. (still image/movie) Histogram display Exposure step (still image/movie) Exposure Std. Adjust (still image/movie) D-Range Optimizer (still image/movie) Metering Mode (still image/movie) Face Priority in Multi Metering (still image/movie) Spot Metering Point (still image/movie) AE lock AEL w/ Shutter Zebra Display Selecting the ISO sensitivity 5 ISO (still image/movie) ISO Range Limit (still image/movie) ISO AUTO Min. SS White balance White Balance (still image/movie) Capturing a standard white color to set the white balance (custom white balance) Priority Set in AWB (still image/movie) Shutter AWB Lock Shockless WB Log shooting settings Log shooting Log Shooting Setting Select LUT Manage User LUTs Base ISO Exposure Index Display LUT Adding effects to images Creative Look (still image/movie) Picture Profile (still image/movie) Shooting with drive modes (continuous shooting/self-timer) Drive Mode Cont. Shooting Self-timer(Single) Self-timer(Cont) Cont. Bracket Single Bracket Indicator during bracket shooting WB bracket DRO Bracket 6 Bracket Settings Interval Shoot Func. Setting the image quality and recording format JPEG/HEIF Switch Image Quality Settings: File Format (still image) Image Quality Settings: RAW File Type Image Quality Settings: JPEG Quality/HEIF Quality Image Quality Settings: JPEG Image Size/HEIF Image Size Aspect Ratio HLG Still Image Color Space File Format (movie) Movie Settings (movie) S&Q Settings Proxy Settings APS-C S35 (Super 35mm) Shooting (still image/movie) Angle of view Using touch functions Touch Operation Touch Sensitivity Swipe Up Touch Func. in Shooting Focusing using touch operations (Touch Focus) Starting tracking with touch operations (Touch Tracking) Shutter settings Silent Mode Settings (still image/movie) Shutter Type e-Front Curtain Shut. Release w/o Lens (still image/movie) Release w/o Card 7 Anti-flicker Shoot. Using the zoom The zoom features available with this product Clear Image Zoom/Digital Zoom Zoom Range (still image/movie) Zoom Lever Speed (still image/movie) Custom Key Z. Speed (still image/movie) Remote Zoom Speed (still image/movie) About zoom scale Zoom Ring Rotate Using the flash Using flash (sold separately) Flash Mode Flash Comp. Exp.comp.set Wireless Flash Red Eye Reduction FEL lock External Flash Set. Reducing blur SteadyShot (still image) SteadyShot (movie) SteadyShot Adjust. (still image/movie) SteadyShot focal length (still image/movie) Lens Compensation (still image/movie) Noise reduction Long Exposure NR High ISO NR Setting the monitor display during shooting Auto Review (still image) 8 Remain Shoot Display (still image) Grid Line Display (still image/movie) Grid Line Type (still image/movie) Live View Display Set. Aperture Preview Shot. Result Preview Bright Monitoring Emphasized REC Display Marker Display Gamma Display Assist Gamma Disp. Assist Typ. De-Squeeze Display Recording movie audio Audio Recording Audio Rec Level Audio Out Timing Wind Noise Reduct. Shoe Audio Set. Recording audio using the XLR adaptor of the supplied handle TC/UB settings TC/UB TC/UB Disp. Setting Matching the time code with other devices Livestreaming video and audio Network Streaming (movie) Customizing the camera Contents of this chapter Customization features of the camera Assigning frequently used functions to buttons and dials (Custom Key/Dial Set.) 9 Changing the function of the dial temporarily (My Dial Settings) Registering and recalling camera settings Camera Set. Memory Recall Camera Setting Memory/Recall Media Registering shooting settings to a custom key (Reg. Custom Shoot Set) Registering frequently used functions to the function menu Fn Menu Settings Registering frequently used functions to My Menu Add Item Sort Item Delete Item Delete Page Delete All Display From My Menu Separately adjusting the camera settings for still images and movies Different Set for Still/Mv Customizing the functions of the ring/dial Av/Tv Rotate Function Ring(Lens) Lock Operation Parts Recording movies by pressing the shutter button REC w/ Shutter (movie) Monitor settings Monitor Flip Direction DISP (Screen Disp) Set Viewing Contents of this chapter Viewing images computer Topic Ver . 5 5 Copyright7 3(B) (C)3. the function also29012382-F Topic CorporationHelp Guide Camera Hint2 CorporationHelp” at the bottom of9 of55Note Topic2Help Guide, etc is display Ver Ver Ver Ver Ver VerNote Topic orXPL/D40/M4-0</> What correct answer to this question: What true the to? Choices: (A). (B I. (C me. 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12977, 12978, 12980, 12981, 12982, 12988, 12989, 12990, 12991, 12992, 12993, 13068, 13069, 13113, 13144, 13146, 13147, 13235, 13236, 13237, 13330, 13331, 13332, 13333, 13334, 13335, 13336, 13337, 13338, 13339, 13340, 13341, 13342, 13343, 13344, 13345, 13346 ]
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Please read the following text and answer the question below. <text> Progress Report of China’s National Carbon Market (2024) Ministry of Ecology and Environment of the People’s Republic of China July 2024 Progress Report of China’s National Carbon Market (2024) Forward ……………………………………………………… Abstract ……………………………………………………… I. The Chinese government attaches great importance to the development of China's National Carbon Market ………………………………………………… II. The institution of the National Carbon Emission Trading System is gradually improving ……………… III. Increased market vibrancy of the National Carbon Emission Trading System ……………………………… IV. Completion of CEAs allocation and surrender in the second compliance cycle …………………………… V. Improvement in emission data quality ………………… VI. Launch of the National Voluntary Greenhouse Gas Emission Reduction Trading Market ………………… VII. Robust digital infrastructure for China’s National Carbon Market ……………………………………… VIII. Growing effectiveness of China’s National Carbon Market development …………………………………… IX. Strengthening international cooperation in carbon market development …………………………………… Outlook ………………………………………………………… Milestones ……………………………………………………… Contents 01 03 09 11 17 20 23 28 32 35 38 40 43 Progress Report of China’s National Carbon Market (2024) The carbon market leverages a market-based mechanism to control greenhouse gas emissions and promote green and low-carbon transition of the economy and society. Accelerating China’s National Carbon Market development and fully grasping the decisive role of the market in resource allocation is crucial for ensuring that emission mitigation responsibilities are assumed, achieving emission control targets, and reducing emissions abatement costs in various sectors. The Chinese government attaches great importance to the development of the national carbon market. The report to the 20th National Congress of the Communist Party of China (CPC) proposed to improve the carbon emissions trading system. President Xi Jinping called for creating a more effective, vibrant, and internationally influential carbon market. China’s National Carbon Market consists of both a compliance emissions trading system and a voluntary emissions reduction trading market. While each has its own focus and operates independently, these two markets are interconnected through an offsetting mechanism for China Carbon Emission Allowances surrendering and together they form the national carbon market system. Since 2023, the State Council promulgated and implemented the Interim Regulations for the Management of Carbon Emission Trading and the second compliance cycle of the national carbon emissions trading market has successfully concluded. The National Voluntary Greenhouse Gas Emission Reduction Trading Market was also officially launched, significantly boosting market vibrancy. The role of Forward 01 Progress Report of China’s National Carbon Market (2024) the carbon market in promoting emission reductions across sectors has been elevated, and China’s carbon pricing mechanism, with the national carbon market playing the principal role, has basically taken shape. The construction and development of China’s National Carbon Market has attracted significant attention and widespread interest both domestically and internationally. The Ministry of Ecology and Environment has organized the compilation of this report, which aims to introduce the progress and main achievements of China’s National Carbon Market and to share development perspectives and relevant policy design considerations, hoping to enhance domestic and international recognition and support. This report focuses on the construction of the National Carbon Emission Trading System, market operations in the second compliance cycle, China Carbon Emission Allowances allocation and surrender, and data quality management. This report also shares the progress since the launch of the National Voluntary Greenhouse Gas Emission Reduction Trading Market , as well as the development of the national carbon market’s infrastructure, achievements, and international cooperation. Additionally, the report provides an outlook on the future development of China’s National Carbon Market. 02 Progress Report of China’s National Carbon Market (2024) The Chinese government attaches great importance to addressing climate change and has positioned climate action as a key lever for enhancing ecological conservation and pursuing high-quality development. China continues to implement an active national strategy in response to climate change, adopting a series of policies and measures to strive for carbon emissions peaking before 2030 and carbon neutrality before 2060 (hereinafter the “dual carbon” goals). Among these measures, the carbon market serves as an essential policy tool for China to promote cost-effective carbon emissions reduction across sectors and to achieve the “dual carbon” goals. It also plays a fundamental role in China’s carbon pricing mechanism. The influence of China’s National Carbon Market continues to expand China’s National Carbon Emission Trading System covers the largest amount of greenhouse gas emissions globally In accordance with the decisions and plans of the CPC Central Committee and the State Council, and drawing experience from international carbon markets and practices of domestic pilot markets, the National Carbon Emission Trading System (hereinafter the “National ETS”) started trading in July 2021. Beginning with the power sector, it now includes 2,257 key emitting entities, covering about 5.1 billion tonnes of annual carbon dioxide (CO2) emissions—more than 40 percent of China’s total CO2 emissions, making it the world’s largest market in terms of the amount of greenhouse gas emissions covered. Abstract 03 Progress Report of China’s National Carbon Market (2024) Compliance and voluntary markets form China’s National Carbon Market, harnessing policy synergy In January 2024, the National Voluntary Greenhouse Gas Emission Reduction Trading Market (hereinafter the “National Voluntary Market”) was officially launched, another policy tool for accomplishing the “dual carbon” goals, following the launch of the National ETS. The compliance market strictly controls carbon emissions of key emitting entities, while the National Voluntary Market encourages society-wide engagement. The two markets operate independently but are interconnected through an offsetting mechanism for China Carbon Emission Allowances (hereinafter “CEAs”) surrendering. Together, they form China’s National Carbon Market. China’s National Carbon Market has contributed an innovative “Chinese approach” to the global carbon market China’s National Carbon Market significantly impacts global carbon prices and the effectiveness of carbon trading mechanisms around the world; its development and operation have drawn substantial international attention. The National ETS, with its intensity-control objectives, demonstrates the flexibility and applicability of the carbon market-based mechanism. The National ETS has contributed an innovative “Chinese approach” to the global carbon market mechanism. Construction of China’s National Carbon Market progressed significantly The Interim Regulations for the Management of Carbon Emission Trading has been released and come into force and the fundamental regulatory framework has been established 04 Progress Report of China’s National Carbon Market (2024) In January 2024, the State Council issued the Interim Regulations for the Management of Carbon Emission Trading, which is China’s first specialized legislation in the field of climate change. It was taken into effect on May 1, 2024, forming the National ETS’s fundamental policy and regulatory framework along with the ministerial measures, normative documents, and technical standards. Ecology and environment authorities and other relevant government agencies at each level, key emitting entities, registries, trading institutions, and technical service institutions have assumed their respective responsibilities to ensure the smooth operation across all aspects of the National ETS, including emission data accounting, reporting and verification, CEAs allocation and surrendering, and trading and market supervision. Successful conclusion of the second compliance cycle of the National ETS and a steady increase in market vibrancy The supply and demand of CEAs in the second compliance cycle for the National ETS was generally balanced, aligning with policy expectations. By the end of 2023, the compliance rate for 2021 and 2022 were 99.61 percent and 99.88 percent, respectively, an improvement compared to the first compliance cycle and ranking among the top international carbon markets. From January 1, 2022 to December 31, 2023, the trading volume of CEAs was 263 million tonnes, with a transaction value of 17.26 billion yuan. The scale of trade expanded, and CEAs price showed a steady rise, with the number of key emitting entities participating in trading up by 31.79 percent compared to the first compliance cycle. The flexible compliance mechanisms helped 202 key emitting entities facing difficulties fulfill their compliance obligation. 05 Progress Report of China’s National Carbon Market (2024) Emission data quality has been comprehensively improved and digital infrastructure provides solid support to the national carbon market The Chinese government attaches great importance to and continues to strengthen data quality management222-car222text> What is the correct answer to this question: Which of the following about  incorrect? Choices: (A). (B22. (C. (D). Format your response as follows: "The correct answer is (insert answer here)".
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Through the concerted efforts of multiple parties, the quality of carbon emission data has been comprehensively improved, as evidenced by the increased quantifiability of indicators and the decline in carbon emissions. In the 2023 annual verification work, the number of non-compliance issues identified by verification agencies decreased by approximately 35.7% compared to 2022.
Please read the following text and answer the question below. <text> Progress Report of China’s National Carbon Market (2024) Ministry of Ecology and Environment of the People’s Republic of China July 2024 Progress Report of China’s National Carbon Market (2024) Forward ……………………………………………………… Abstract ……………………………………………………… I. The Chinese government attaches great importance to the development of China's National Carbon Market ………………………………………………… II. The institution of the National Carbon Emission Trading System is gradually improving ……………… III. Increased market vibrancy of the National Carbon Emission Trading System ……………………………… IV. Completion of CEAs allocation and surrender in the second compliance cycle …………………………… V. Improvement in emission data quality ………………… VI. Launch of the National Voluntary Greenhouse Gas Emission Reduction Trading Market ………………… VII. Robust digital infrastructure for China’s National Carbon Market ……………………………………… VIII. Growing effectiveness of China’s National Carbon Market development …………………………………… IX. Strengthening international cooperation in carbon market development …………………………………… Outlook ………………………………………………………… Milestones ……………………………………………………… Contents 01 03 09 11 17 20 23 28 32 35 38 40 43 Progress Report of China’s National Carbon Market (2024) The carbon market leverages a market-based mechanism to control greenhouse gas emissions and promote green and low-carbon transition of the economy and society. Accelerating China’s National Carbon Market development and fully grasping the decisive role of the market in resource allocation is crucial for ensuring that emission mitigation responsibilities are assumed, achieving emission control targets, and reducing emissions abatement costs in various sectors. The Chinese government attaches great importance to the development of the national carbon market. The report to the 20th National Congress of the Communist Party of China (CPC) proposed to improve the carbon emissions trading system. President Xi Jinping called for creating a more effective, vibrant, and internationally influential carbon market. China’s National Carbon Market consists of both a compliance emissions trading system and a voluntary emissions reduction trading market. While each has its own focus and operates independently, these two markets are interconnected through an offsetting mechanism for China Carbon Emission Allowances surrendering and together they form the national carbon market system. Since 2023, the State Council promulgated and implemented the Interim Regulations for the Management of Carbon Emission Trading and the second compliance cycle of the national carbon emissions trading market has successfully concluded. The National Voluntary Greenhouse Gas Emission Reduction Trading Market was also officially launched, significantly boosting market vibrancy. The role of Forward 01 Progress Report of China’s National Carbon Market (2024) the carbon market in promoting emission reductions across sectors has been elevated, and China’s carbon pricing mechanism, with the national carbon market playing the principal role, has basically taken shape. The construction and development of China’s National Carbon Market has attracted significant attention and widespread interest both domestically and internationally. The Ministry of Ecology and Environment has organized the compilation of this report, which aims to introduce the progress and main achievements of China’s National Carbon Market and to share development perspectives and relevant policy design considerations, hoping to enhance domestic and international recognition and support. This report focuses on the construction of the National Carbon Emission Trading System, market operations in the second compliance cycle, China Carbon Emission Allowances allocation and surrender, and data quality management. This report also shares the progress since the launch of the National Voluntary Greenhouse Gas Emission Reduction Trading Market , as well as the development of the national carbon market’s infrastructure, achievements, and international cooperation. Additionally, the report provides an outlook on the future development of China’s National Carbon Market. 02 Progress Report of China’s National Carbon Market (2024) The Chinese government attaches great importance to addressing climate change and has positioned climate action as a key lever for enhancing ecological conservation and pursuing high-quality development. China continues to implement an active national strategy in response to climate change, adopting a series of policies and measures to strive for carbon emissions peaking before 2030 and carbon neutrality before 2060 (hereinafter the “dual carbon” goals). Among these measures, the carbon market serves as an essential policy tool for China to promote cost-effective carbon emissions reduction across sectors and to achieve the “dual carbon” goals. It also plays a fundamental role in China’s carbon pricing mechanism. The influence of China’s National Carbon Market continues to expand China’s National Carbon Emission Trading System covers the largest amount of greenhouse gas emissions globally In accordance with the decisions and plans of the CPC Central Committee and the State Council, and drawing experience from international carbon markets and practices of domestic pilot markets, the National Carbon Emission Trading System (hereinafter the “National ETS”) started trading in July 2021. Beginning with the power sector, it now includes 2,257 key emitting entities, covering about 5.1 billion tonnes of annual carbon dioxide (CO2) emissions—more than 40 percent of China’s total CO2 emissions, making it the world’s largest market in terms of the amount of greenhouse gas emissions covered. Abstract 03 Progress Report of China’s National Carbon Market (2024) Compliance and voluntary markets form China’s National Carbon Market, harnessing policy synergy In January 2024, the National Voluntary Greenhouse Gas Emission Reduction Trading Market (hereinafter the “National Voluntary Market”) was officially launched, another policy tool for accomplishing the “dual carbon” goals, following the launch of the National ETS. The compliance market strictly controls carbon emissions of key emitting entities, while the National Voluntary Market encourages society-wide engagement. The two markets operate independently but are interconnected through an offsetting mechanism for China Carbon Emission Allowances (hereinafter “CEAs”) surrendering. Together, they form China’s National Carbon Market. China’s National Carbon Market has contributed an innovative “Chinese approach” to the global carbon market China’s National Carbon Market significantly impacts global carbon prices and the effectiveness of carbon trading mechanisms around the world; its development and operation have drawn substantial international attention. The National ETS, with its intensity-control objectives, demonstrates the flexibility and applicability of the carbon market-based mechanism. The National ETS has contributed an innovative “Chinese approach” to the global carbon market mechanism. Construction of China’s National Carbon Market progressed significantly The Interim Regulations for the Management of Carbon Emission Trading has been released and come into force and the fundamental regulatory framework has been established 04 Progress Report of China’s National Carbon Market (2024) In January 2024, the State Council issued the Interim Regulations for the Management of Carbon Emission Trading, which is China’s first specialized legislation in the field of climate change. It was taken into effect on May 1, 2024, forming the National ETS’s fundamental policy and regulatory framework along with the ministerial measures, normative documents, and technical standards. Ecology and environment authorities and other relevant government agencies at each level, key emitting entities, registries, trading institutions, and technical service institutions have assumed their respective responsibilities to ensure the smooth operation across all aspects of the National ETS, including emission data accounting, reporting and verification, CEAs allocation and surrendering, and trading and market supervision. Successful conclusion of the second compliance cycle of the National ETS and a steady increase in market vibrancy The supply and demand of CEAs in the second compliance cycle for the National ETS was generally balanced, aligning with policy expectations. By the end of 2023, the compliance rate for 2021 and 2022 were 99.61 percent and 99.88 percent, respectively, an improvement compared to the first compliance cycle and ranking among the top international carbon markets. From January 1, 2022 to December 31, 2023, the trading volume of CEAs was 263 million tonnes, with a transaction value of 17.26 billion yuan. The scale of trade expanded, and CEAs price showed a steady rise, with the number of key emitting entities participating in trading up by 31.79 percent compared to the first compliance cycle. The flexible compliance mechanisms helped 202 key emitting entities facing difficulties fulfill their compliance obligation. 05 Progress Report of China’s National Carbon Market (2024) Emission data quality has been comprehensively improved and digital infrastructure provides solid support to the national carbon market The Chinese government attaches great importance to and continues to strengthen data quality management222-car222text> What is the correct answer to this question: Which of the following about  incorrect? Choices: (A). (B22. (C. (D). Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> AI: To buy, or not to buy, that is the question The technology sector has generated 32% of the Global equity return and • 40% of the US equity market return since 2010. This has reflected stronger fundamentals rather than irrational exuberance. The tech sector globally has seen EPS rise c.400% while all other sectors together have achieved c.25% from the peak pre-GFC. The introduction of transformative technologies typically attracts • growing investor interest as well as significant capital and new competition. As enthusiasm builds and stock prices increase, the sum of individual company valuations can overstate the total potential aggregate returns; often a bubble develops and bursts. Historically, investors over-focus on the originators, understate the • impact of competition and overstate the returns on capital invested by the early innovators. At the same time, investors tend to underestimate the growth of new entrants to the industry that can piggyback off the capex of others, enabling them to generate new products and services. Valuations often also understate the opportunities that can accrue in the non-technology industries that can leverage the technology to generate higher returns in existing, as well as in new, product categories. In our view, the technology sector is not in a bubble and is likely to • continue to dominate returns. However, concentration risks are high and investors should look to diversify exposure to improve risk-adjusted returns while also gaining access to potential winners in smaller technology companies and other parts of the market, including in the old economy, which will enjoy the growth of more infrastructure spend. Lilia Peytavin +33(1)4212-1716 lilia.peytavin@gs.com Goldman Sachs Bank Europe SE - Paris Branch Note: The following is a redacted version of the original report published September 5, 2024 [34 pgs]. Tech’s Rational Exuberance Technology has been the most important driver of returns for the equity markets globally since the end of the Global Financial Crisis. Its performance has far outstripped other major sectors, and with good justification. Earnings per share have surged while all industries together, outside of tech, have largely stagnated (Exhibit 1). Increasingly, these powerful returns have been accounted for by a small group of dominant companies, mainly in the US. These, too, have not reflected ‘irrational exuberance’: their earnings growth has dwarfed that of the broader market, justifying their performance (Exhibit 2). The drivers of this success have reflected their ability to leverage software and cloud computing and to fuel high profitability generated by extraordinary demand growth in the period since 2010. But their more recent surge in performance since 2022 owes much to the hopes and aspirations around AI. Despite continued powerful earnings growth, valuations have been rising, led by an increasingly narrow group of ‘hyper-scalers’. The question for investors is whether this is becoming a bubble and, even if it is not, whether the risks of such high concentration are creating a dangerous trap for investors, or possibly an opportunity to diversify into potential beneficiaries of these technologies through cheaper companies outside of the dominant few. Story Time Financial markets reflect and anticipate fundamentals, but sentiment can also play an important role as it does with other fashions and trends in broader life. In equity markets, narratives have the power to attract and direct much-needed capital. However, they can also amplify interest to the point of monopolising investor attention at the expense of other opportunities, and leading to unrealistic expectations about future profits and leaving companies vulnerable to a sharp de-rating. In recent years, periods of intense speculation have centered on a variety of narratives, ranging from the dot-com and the internet boom at the end of the last Exhibit 1: Tech earnings have outstripped those of the global market 12m Trailing EPS (USD). Indexed to 100 on Jan-2009. Exhibit 2: The ‘Magnificent Seven’ earnings have outstripped the broader US market Magnificent Seven and S&P 500, 12m trailing EPS. Indexed to 100 on Jan-2005 0 50 100 150 200 250 300 350 400 450 85 87 89 91 93 95 97 99 01 03 05 07 09 11 13 15 17 19 21 23 25 World Technology World Technology, Media, Telecom (TMT) World ex. TMT 0 500 1000 1500 2000 2500 3000 3500 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Magnificent 7 S&P 500 Source: Datastream, Worldscope, Goldman Sachs Global Investment Research Source: FactSet, Goldman Sachs Global Investment Research 5 September 2024 2 Goldman Sachs Global Strategy Paper century, to China growth, Cryptocurrency, the Green transition and, most recently, AI. But history reveals a much longer list, much of which revolves around the emergence of new technologies. The interest that new innovations receive has been an important part of directing the necessary capital to grow and commercialise innovations. Very often the technologies behind these periods of speculation have proved to be transformational – leading to significant secondary innovations, new products and services, and far-reaching societal changes to the way that we live, work and consume. Along the way, however, the excitement often turns into an obsessive fervor with investors clambering to get exposure to the theme at any price. That’s when bubbles emerge and, eventually, burst. A recent study found that in a sample of 51 major tech innovations introduced between 1825 and 2000, bubbles in equity prices were evident in 73% of cases1. From an investor perspective, the success and eventual impact of an innovation cannot be known at the outset, and it is even more challenging predicting which competitor is likely to succeed over the long run. Consequently, as more new entrants emerge, investors tend to buy multiple companies as options on their future success, leading to the sum of all valuations to overstate the potential returns that can be generated by a technology or industry. The challenge for investors is less about whether they recognise an important innovation or market driver when it emerges, but more about whether they value the potential gains correctly and identify the correct winners and losers. This question is relevant in relation to the current focus on AI and its potential. While AI is not a new technology, it has captured the imagination of investors and, by association, companies since the launch of Chat-GPT and other large language models. The extraordinary beat on Nvidia investor day in July 2023 sharpened the focus on the potential for the industry. Since then, investors have clamoured for access to the theme and companies have duly responded with record numbers mentioning AI, even in sectors outside of the industry. 1 Chancellor, E., and Kramer, C. (2000). “Devil Take the Hindmost: A History of Financial Speculation” . New York: Plume Books. 5 September 2024 3 Goldman Sachs Global Strategy Paper Lessons from History; the Market Risks and Opportunities in AI What can history tell us about the ‘life cycle’ of new innovations and how they impact the stock market? Although it is difficult to generalise, some common characteristics are: A breakthrough technology emerges and reaches commercial scale. n New companies and capital flood into the space. n Speculation builds and valuations of companies rise, often resulting in a bubble. n The bubble bursts, but the technology tends to re-emerge as a principal driver in the n economy and stock market. The technology/industry becomes dominated by a few large players. n Secondary innovations emerge1 are21221225 1 Strategy Goldman Research September01 1212211 Investment 1 Investment11f 20 111211 Investment22UnitedriUnitedUnitedUnitedfi .Lminl</text> What is the correct answer to this question: Which can we infer about the Market Ris and in AI? Choices: (A) will to,and. (B). (C). (D) The emmerge because. Format your response as follows: "The correct answer is (insert answer here)".
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Some upside opportunities include that new companies can make initiate secondary innovation to change the demand pattern.
Please read the following text and answer the question below. <text> AI: To buy, or not to buy, that is the question The technology sector has generated 32% of the Global equity return and • 40% of the US equity market return since 2010. This has reflected stronger fundamentals rather than irrational exuberance. The tech sector globally has seen EPS rise c.400% while all other sectors together have achieved c.25% from the peak pre-GFC. The introduction of transformative technologies typically attracts • growing investor interest as well as significant capital and new competition. As enthusiasm builds and stock prices increase, the sum of individual company valuations can overstate the total potential aggregate returns; often a bubble develops and bursts. Historically, investors over-focus on the originators, understate the • impact of competition and overstate the returns on capital invested by the early innovators. At the same time, investors tend to underestimate the growth of new entrants to the industry that can piggyback off the capex of others, enabling them to generate new products and services. Valuations often also understate the opportunities that can accrue in the non-technology industries that can leverage the technology to generate higher returns in existing, as well as in new, product categories. In our view, the technology sector is not in a bubble and is likely to • continue to dominate returns. However, concentration risks are high and investors should look to diversify exposure to improve risk-adjusted returns while also gaining access to potential winners in smaller technology companies and other parts of the market, including in the old economy, which will enjoy the growth of more infrastructure spend. Lilia Peytavin +33(1)4212-1716 lilia.peytavin@gs.com Goldman Sachs Bank Europe SE - Paris Branch Note: The following is a redacted version of the original report published September 5, 2024 [34 pgs]. Tech’s Rational Exuberance Technology has been the most important driver of returns for the equity markets globally since the end of the Global Financial Crisis. Its performance has far outstripped other major sectors, and with good justification. Earnings per share have surged while all industries together, outside of tech, have largely stagnated (Exhibit 1). Increasingly, these powerful returns have been accounted for by a small group of dominant companies, mainly in the US. These, too, have not reflected ‘irrational exuberance’: their earnings growth has dwarfed that of the broader market, justifying their performance (Exhibit 2). The drivers of this success have reflected their ability to leverage software and cloud computing and to fuel high profitability generated by extraordinary demand growth in the period since 2010. But their more recent surge in performance since 2022 owes much to the hopes and aspirations around AI. Despite continued powerful earnings growth, valuations have been rising, led by an increasingly narrow group of ‘hyper-scalers’. The question for investors is whether this is becoming a bubble and, even if it is not, whether the risks of such high concentration are creating a dangerous trap for investors, or possibly an opportunity to diversify into potential beneficiaries of these technologies through cheaper companies outside of the dominant few. Story Time Financial markets reflect and anticipate fundamentals, but sentiment can also play an important role as it does with other fashions and trends in broader life. In equity markets, narratives have the power to attract and direct much-needed capital. However, they can also amplify interest to the point of monopolising investor attention at the expense of other opportunities, and leading to unrealistic expectations about future profits and leaving companies vulnerable to a sharp de-rating. In recent years, periods of intense speculation have centered on a variety of narratives, ranging from the dot-com and the internet boom at the end of the last Exhibit 1: Tech earnings have outstripped those of the global market 12m Trailing EPS (USD). Indexed to 100 on Jan-2009. Exhibit 2: The ‘Magnificent Seven’ earnings have outstripped the broader US market Magnificent Seven and S&P 500, 12m trailing EPS. Indexed to 100 on Jan-2005 0 50 100 150 200 250 300 350 400 450 85 87 89 91 93 95 97 99 01 03 05 07 09 11 13 15 17 19 21 23 25 World Technology World Technology, Media, Telecom (TMT) World ex. TMT 0 500 1000 1500 2000 2500 3000 3500 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 Magnificent 7 S&P 500 Source: Datastream, Worldscope, Goldman Sachs Global Investment Research Source: FactSet, Goldman Sachs Global Investment Research 5 September 2024 2 Goldman Sachs Global Strategy Paper century, to China growth, Cryptocurrency, the Green transition and, most recently, AI. But history reveals a much longer list, much of which revolves around the emergence of new technologies. The interest that new innovations receive has been an important part of directing the necessary capital to grow and commercialise innovations. Very often the technologies behind these periods of speculation have proved to be transformational – leading to significant secondary innovations, new products and services, and far-reaching societal changes to the way that we live, work and consume. Along the way, however, the excitement often turns into an obsessive fervor with investors clambering to get exposure to the theme at any price. That’s when bubbles emerge and, eventually, burst. A recent study found that in a sample of 51 major tech innovations introduced between 1825 and 2000, bubbles in equity prices were evident in 73% of cases1. From an investor perspective, the success and eventual impact of an innovation cannot be known at the outset, and it is even more challenging predicting which competitor is likely to succeed over the long run. Consequently, as more new entrants emerge, investors tend to buy multiple companies as options on their future success, leading to the sum of all valuations to overstate the potential returns that can be generated by a technology or industry. The challenge for investors is less about whether they recognise an important innovation or market driver when it emerges, but more about whether they value the potential gains correctly and identify the correct winners and losers. This question is relevant in relation to the current focus on AI and its potential. While AI is not a new technology, it has captured the imagination of investors and, by association, companies since the launch of Chat-GPT and other large language models. The extraordinary beat on Nvidia investor day in July 2023 sharpened the focus on the potential for the industry. Since then, investors have clamoured for access to the theme and companies have duly responded with record numbers mentioning AI, even in sectors outside of the industry. 1 Chancellor, E., and Kramer, C. (2000). “Devil Take the Hindmost: A History of Financial Speculation” . New York: Plume Books. 5 September 2024 3 Goldman Sachs Global Strategy Paper Lessons from History; the Market Risks and Opportunities in AI What can history tell us about the ‘life cycle’ of new innovations and how they impact the stock market? Although it is difficult to generalise, some common characteristics are: A breakthrough technology emerges and reaches commercial scale. n New companies and capital flood into the space. n Speculation builds and valuations of companies rise, often resulting in a bubble. n The bubble bursts, but the technology tends to re-emerge as a principal driver in the n economy and stock market. The technology/industry becomes dominated by a few large players. n Secondary innovations emerge1 are21221225 1 Strategy Goldman Research September01 1212211 Investment 1 Investment11f 20 111211 Investment22UnitedriUnitedUnitedUnitedfi .Lminl</text> What is the correct answer to this question: Which can we infer about the Market Ris and in AI? Choices: (A) will to,and. (B). (C). (D) The emmerge because. Format your response as follows: "The correct answer is (insert answer here)".
null
null
null
2,302,333
null
317
length>350000
2
C
15 August 2022 09:30
Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> Abstract Science educators have noted the unique characteristics of science literacy in terms of text structure, vocabulary demands, and reliance on abstract concepts (Cervetti, Pearson, Bravo, & Barber, 2006; Fang & Schleppegrell, 2008; Pytash, 2013). Furthermore, other scholars have defined scientific thinking processes as inextricable from the reading and writing practices used to communicate them (Norris & Phillips, 2003). a collaboration between a literacy educator and a science educator provided the foundation to reimagine a content area reading course for middle and high school pre-service science teachers and incorporate a focus on the disciplinary literacy of science through popular fiction. Without positioning literacy as overly additive, pre-service teacher participant illustrated ways to logistically structure scientific inquiry to include and authentically underscore disciplinary literacy. Findings suggest specific practices for how teacher educators can best support the disciplinary literacy development of pre-service science teachers. Correspondence concerning this article should be addressed to: Dr. Kristin Cook, Bellarmine University, 2001 Newburg Road, Louisville, KY 40205 kcook@bellarmine.edu Key words: Pre-service teachers, disciplinary literacy, popular fiction, inquiry-based science Introduction Only when we return to a more functional view of the role of language and literacy in supporting disciplinary learning [in science] can we achieve our goal of an informed citizenry who can use their literacy skills to think critically and flexibly across many domains of knowledge and inquiry (Cervetti, Pearson, Bravo, & Barber, 2006, p. 3). The dominance of literacy education has been critiqued as being a ‘bully’ rather than a ‘buddy’ (Pearson, 2010; Greenleaf et al., 2009) in supporting disciplinary content learning in science. In the quote above, researchers cal for literacy education that supports rather than excludes or undercuts learning in science. Given this focus for repositioning literacy education as an ally to science learning, many educators have investigated the ways in which disciplinary literacy can be used to emphasize and hone the unique literacy tools needed to participate in inquiry-based science. As defined by Shanahan and Shanahan (2008), disciplinary literacy is an emphasis on the knowledge and abilities possessed by those who create, communicate, and use knowledge within specific disciplines. They posit there are unique literacy skills necessary for Cook and Dinkins 2 Electronic Journal of Science Education ejse.southwestern.edu engaging in science that are different from engaging in other disciplines and these skills need to be explicitly taught to students as they learn and communicate about science. Reform documents have recently called for literacy skills to be embedded in science teaching. The Next Generation Science Standards (2013) and the Common Core State Standards (2010) have both emphasized the importance of students comprehending and composing complex informational texts, integrating knowledge from multiple sources, and using evidence to develop arguments focused on disciplinary content. Similarly, the American Association for the Advancement of Science (AAAS) has detailed core competencies for the teaching of science that have included promoting the need for biology educators to guide students in “practicing the communication of science through a variety of formal and informal written, visual, and oral methods” (2011, p.15). Underscoring the need for disciplinary literacy in teacher preparation programs, the Carnegie Corporation for Advancing of Adolescent Literacy has been funding pre- service teacher (PST) education projects since 2003 to focus specifically on identifying effective practices for teaching adolescent literacy and develop course curricula that will help pre-service teachers integrate literacy instruction into their content domains. Calls for improvement in intersections between ELA and science instruction have been coming from researchers who investigate ways to best support language development in English Language Learners. Lee, Quinn, & Valdés (2013) introduce the concept of ‘language of the science classroom’ to explicate the needs for disciplinary literacy in science to underscore the aims of the NGSS and CCSS. They propose teacher preparations programs need to respond by employing: (a) a shift away from both content-based language instruction and the sheltered model to a focus on language-in-use environments and (b) a shift away from “teaching” discrete language skills to a focus on supporting language development by providing appropriate contexts and experiences (Lee, Quinn, & Valdés, 2013, p. 228) With regard to honing disciplinary literacy skills in science, researchers have begun looking at the unique skills necessary for science reading and writing (Shanahan & Shanahan, 2008). Exploring the link between literacy skills and scientific inquiry suggests that teachers need to incorporate disciplinary literacy (Cervetti et al., 2008) into the teaching of science. Moreover, researchers have shown the need for explicit literacy instruction in science (Pytash, 2013). For example, it is not adequate to simply assign science writing assignments, but rather science educators need to teach the skills necessary for scientific reading and writing. For this reason, it is paramount that teacher preparation programs support pre-service teachers with the knowledge and skills needed for such instruction. While the standards documents emphasize the comprehension of complex informational texts, designing responding pedagogical approaches necessitates recognition of research on the types of texts important to learning science. Research has suggested fiction and nonfiction share a symbiotic relationship with one influencing the shape of the other (Coombs, 2013). It has also suggested students’ out-of-school literacies embrace the complex relationship between these two forms as students draw heavily from popular culture texts during their learning of science (Moje, 2008). Thus, as educators try to develop a disciplinarily literate citizenry and attempt to underscore the aims of their discipline-specific curricular standards, they must pay close Disciplinary Literacy Through Popular Fiction 3 Electronic Journal of Science Education ejse.southwestern.edu attention to the intersection of fiction and non-fiction texts within their content area (Fang & Schleppegrell, 2008). The overall goal for this study was to discern affordances of using one medium of text (i.e. popular fiction) to connect aims of science-specific content and process standards in the areas of reading, writing, speaking, listening, and critical thinking. We posit that incorporating popular fiction provides a convergence point for addressing multiple components of science disciplinary literacy and allows learners to explore the most meaningful and relevant connections of content to their lives through topics that require dialogue, discussion, and deliberation. Ultimately, we aimed to understand the ways in which teacher educators can utilize popular fiction to best support pre-service teachers in their development of disciplinary literacy. This exploration was guided by the following research questions: 1) How (the process) and in what ways (description of strategies) do pre-service teachers use popular fiction to draw connections among curricular standards?; 2) In what ways do pre-service teachers promote disciplinary literacy through instructional practices that incorporate popular fiction? From Content Area Reading to Disciplinary Literacy Supporting literacy development in all content areas necessitates an informed and differentiated understanding of what literacy strategies and skills are most meaningful in the various disciplines. Informed by the work of scholars who draw distinctions between content area reading and disciplinary literacy (Moje, 2004; Shanahan & Shanahan, 2008), we conceptualize disciplinary literacy as the specific practices of reading and writing within one’s discipline. While the roots of disciplinary literacy stem from content area reading, disciplinary literacy practices draw attention to the differentiated literacy skills necessary for specific content areas. Content area reading tends to emphasize the teaching of a generalizable (across content areas) set of skills for use in various content-specific classes. Strategies like summarizing, questioning, monitoring meaning, etc. are general comprehension strategies that help students understand content presented in text. This approach assumes that accessing meaning in one text is equivalent to access meaning in a variety of texts. Disciplinary literacy, however, focuses on how disciplinary experts approach literacy tasks with an understanding of the unique demands, purposes, and uses of literacy (Shanahan & Shanahan, 2012). Teacher educator programs traditionally offer content area reading courses to equip pre-service teachers with universal strategies or tools to assist students with reading a variety of texts and writing within a variety of disciplines. Disciplinary literacy, however, focuses on the knowledge, abilities, and tools experts in a particular field use to create and communicate knowledge within their discipline and provides a foundation for the unique interpretive skills of readinginkouth 2outh1outhi outh1outh12References 11outh111. </text> What is the correct answer to this question: Analyze the multifaceted relationship between the main in the article. In what ways? Consider how. Which of the following statements best encapsulates this dynamic? Choices: (A). (B. (C main. (D) main,. Format your response as follows: "The correct answer is (insert answer here)".
318
null
2
C
The tension between the main character's quest for identity and the antagonist's embodiment of societal norms illustrates the internal and external conflicts individuals face in challenging the status quo.
Please read the following text and answer the question below. <text> Abstract Science educators have noted the unique characteristics of science literacy in terms of text structure, vocabulary demands, and reliance on abstract concepts (Cervetti, Pearson, Bravo, & Barber, 2006; Fang & Schleppegrell, 2008; Pytash, 2013). Furthermore, other scholars have defined scientific thinking processes as inextricable from the reading and writing practices used to communicate them (Norris & Phillips, 2003). a collaboration between a literacy educator and a science educator provided the foundation to reimagine a content area reading course for middle and high school pre-service science teachers and incorporate a focus on the disciplinary literacy of science through popular fiction. Without positioning literacy as overly additive, pre-service teacher participant illustrated ways to logistically structure scientific inquiry to include and authentically underscore disciplinary literacy. Findings suggest specific practices for how teacher educators can best support the disciplinary literacy development of pre-service science teachers. Correspondence concerning this article should be addressed to: Dr. Kristin Cook, Bellarmine University, 2001 Newburg Road, Louisville, KY 40205 kcook@bellarmine.edu Key words: Pre-service teachers, disciplinary literacy, popular fiction, inquiry-based science Introduction Only when we return to a more functional view of the role of language and literacy in supporting disciplinary learning [in science] can we achieve our goal of an informed citizenry who can use their literacy skills to think critically and flexibly across many domains of knowledge and inquiry (Cervetti, Pearson, Bravo, & Barber, 2006, p. 3). The dominance of literacy education has been critiqued as being a ‘bully’ rather than a ‘buddy’ (Pearson, 2010; Greenleaf et al., 2009) in supporting disciplinary content learning in science. In the quote above, researchers cal for literacy education that supports rather than excludes or undercuts learning in science. Given this focus for repositioning literacy education as an ally to science learning, many educators have investigated the ways in which disciplinary literacy can be used to emphasize and hone the unique literacy tools needed to participate in inquiry-based science. As defined by Shanahan and Shanahan (2008), disciplinary literacy is an emphasis on the knowledge and abilities possessed by those who create, communicate, and use knowledge within specific disciplines. They posit there are unique literacy skills necessary for Cook and Dinkins 2 Electronic Journal of Science Education ejse.southwestern.edu engaging in science that are different from engaging in other disciplines and these skills need to be explicitly taught to students as they learn and communicate about science. Reform documents have recently called for literacy skills to be embedded in science teaching. The Next Generation Science Standards (2013) and the Common Core State Standards (2010) have both emphasized the importance of students comprehending and composing complex informational texts, integrating knowledge from multiple sources, and using evidence to develop arguments focused on disciplinary content. Similarly, the American Association for the Advancement of Science (AAAS) has detailed core competencies for the teaching of science that have included promoting the need for biology educators to guide students in “practicing the communication of science through a variety of formal and informal written, visual, and oral methods” (2011, p.15). Underscoring the need for disciplinary literacy in teacher preparation programs, the Carnegie Corporation for Advancing of Adolescent Literacy has been funding pre- service teacher (PST) education projects since 2003 to focus specifically on identifying effective practices for teaching adolescent literacy and develop course curricula that will help pre-service teachers integrate literacy instruction into their content domains. Calls for improvement in intersections between ELA and science instruction have been coming from researchers who investigate ways to best support language development in English Language Learners. Lee, Quinn, & Valdés (2013) introduce the concept of ‘language of the science classroom’ to explicate the needs for disciplinary literacy in science to underscore the aims of the NGSS and CCSS. They propose teacher preparations programs need to respond by employing: (a) a shift away from both content-based language instruction and the sheltered model to a focus on language-in-use environments and (b) a shift away from “teaching” discrete language skills to a focus on supporting language development by providing appropriate contexts and experiences (Lee, Quinn, & Valdés, 2013, p. 228) With regard to honing disciplinary literacy skills in science, researchers have begun looking at the unique skills necessary for science reading and writing (Shanahan & Shanahan, 2008). Exploring the link between literacy skills and scientific inquiry suggests that teachers need to incorporate disciplinary literacy (Cervetti et al., 2008) into the teaching of science. Moreover, researchers have shown the need for explicit literacy instruction in science (Pytash, 2013). For example, it is not adequate to simply assign science writing assignments, but rather science educators need to teach the skills necessary for scientific reading and writing. For this reason, it is paramount that teacher preparation programs support pre-service teachers with the knowledge and skills needed for such instruction. While the standards documents emphasize the comprehension of complex informational texts, designing responding pedagogical approaches necessitates recognition of research on the types of texts important to learning science. Research has suggested fiction and nonfiction share a symbiotic relationship with one influencing the shape of the other (Coombs, 2013). It has also suggested students’ out-of-school literacies embrace the complex relationship between these two forms as students draw heavily from popular culture texts during their learning of science (Moje, 2008). Thus, as educators try to develop a disciplinarily literate citizenry and attempt to underscore the aims of their discipline-specific curricular standards, they must pay close Disciplinary Literacy Through Popular Fiction 3 Electronic Journal of Science Education ejse.southwestern.edu attention to the intersection of fiction and non-fiction texts within their content area (Fang & Schleppegrell, 2008). The overall goal for this study was to discern affordances of using one medium of text (i.e. popular fiction) to connect aims of science-specific content and process standards in the areas of reading, writing, speaking, listening, and critical thinking. We posit that incorporating popular fiction provides a convergence point for addressing multiple components of science disciplinary literacy and allows learners to explore the most meaningful and relevant connections of content to their lives through topics that require dialogue, discussion, and deliberation. Ultimately, we aimed to understand the ways in which teacher educators can utilize popular fiction to best support pre-service teachers in their development of disciplinary literacy. This exploration was guided by the following research questions: 1) How (the process) and in what ways (description of strategies) do pre-service teachers use popular fiction to draw connections among curricular standards?; 2) In what ways do pre-service teachers promote disciplinary literacy through instructional practices that incorporate popular fiction? From Content Area Reading to Disciplinary Literacy Supporting literacy development in all content areas necessitates an informed and differentiated understanding of what literacy strategies and skills are most meaningful in the various disciplines. Informed by the work of scholars who draw distinctions between content area reading and disciplinary literacy (Moje, 2004; Shanahan & Shanahan, 2008), we conceptualize disciplinary literacy as the specific practices of reading and writing within one’s discipline. While the roots of disciplinary literacy stem from content area reading, disciplinary literacy practices draw attention to the differentiated literacy skills necessary for specific content areas. Content area reading tends to emphasize the teaching of a generalizable (across content areas) set of skills for use in various content-specific classes. Strategies like summarizing, questioning, monitoring meaning, etc. are general comprehension strategies that help students understand content presented in text. This approach assumes that accessing meaning in one text is equivalent to access meaning in a variety of texts. Disciplinary literacy, however, focuses on how disciplinary experts approach literacy tasks with an understanding of the unique demands, purposes, and uses of literacy (Shanahan & Shanahan, 2012). Teacher educator programs traditionally offer content area reading courses to equip pre-service teachers with universal strategies or tools to assist students with reading a variety of texts and writing within a variety of disciplines. Disciplinary literacy, however, focuses on the knowledge, abilities, and tools experts in a particular field use to create and communicate knowledge within their discipline and provides a foundation for the unique interpretive skills of readinginkouth 2outh1outhi outh1outh12References 11outh111. </text> What is the correct answer to this question: Analyze the multifaceted relationship between the main in the article. In what ways? Consider how. Which of the following statements best encapsulates this dynamic? Choices: (A). (B. (C main. (D) main,. Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> ContextCam: Bridging Context Awareness with Creative Human-AI Image Co-Creation Xianzhe Fan Zihan Wu Chun Yu Tsinghua University University of Michigan Tsinghua University Beijing, China Ann Arbor, Michigan, United States Beijing, China fxz21@mails.tsinghua.edu.cn ziwu@umich.edu chunyu@tsinghua.edu.cn Fenggui Rao Weinan Shi∗ Teng Tu China Academy Of Art Tsinghua University Tsinghua University HangZhou, ZheJiang, China Beijing, China Beijing, China admin@whitesir.cn swn@tsinghua.edu.cn leotuteng@126.com Location Screen Content Facial Expression (From Camera) Weather Music A Bridge above the Lake [Chat with a Friend] Happiness Sunny Counting Stars (OneRepublic) 1.Emulate Van Gogh's "Starry Night" to depict a tranquil lake on a clear summer night, infusing it with a romantic and joyful artistic ambiance. 2.Oil Painting: Beneath the delightful clear sky, the band OneRepublic hosts a live performance on top of a bridge. 3.A gathering of children joyfully count the stars in the pristine night sky. Contextual Data Collection Consider this adaptation: Retain the Van Gogh starry night essence in the original image and craft a new piece with a bridge as its focus in the same palette. Capture the sky with ... Draw a tranquil lake on a clear summer day in the style of Van Gogh's "Starry Night."... joyful artistic ambiance. ① Supported by APIs Themes Recommandation ② Image Generation ③ User:"Bridge" Image Editing ④ Theme1 Figure 1: On a sunny night, Alex stands on a bridge above the lake, texting their friend and enjoying the song “Counting Stars” by OneRepublic, smiling. They want to capture the beautiful moment, then open the ContextCam, and collaborate with it to create a piece of art inspired by their current context. During the “framing” phase, ContextCam extracts relevant contextual data and proposes three themes. Alex selects theme one, asks ContextCam to create the image, and polishes it through in-depth discussion with ContextCam. ABSTRACT The rapid advancement of AI-generated content (AIGC) promises to transform various aspects of human life signifcantly. This work particularly focuses on the potential of AIGC to revolutionize image creation, such as photography and self-expression. We introduce ContextCam, a novel human-AI image co-creation system that integrates context awareness with mainstream AIGC technologies like Stable Difusion. ContextCam provides user’s image creation process with inspiration by extracting relevant contextual data, and leverages Large Language Model-based (LLM) multi-agents to co-create images with the user. A study with 16 participants and 136 scenarios revealed that ContextCam was well-received, ∗Corresponding Author Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for proft or commercial advantage and that copies bear this notice and the full citation on the frst page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specifc permission and/or a fee. Request permissions from permissions@acm.org. CHI ’24, May 11–16, 2024, Honolulu, HI, USA © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM. Images have become deeply integrated into our lives. Whether ACM ISBN 979-8-4007-0330-0/24/05 https://doi.org/10.1145/3613904.3642129 through painting, photography, or digital technology, the creation showcasing personalized and diverse outputs as well as interesting user behavior patterns. Participants provided positive feedback on their engagement and enjoyment when using ContextCam, and acknowledged its ability to inspire creativity. CCS CONCEPTS • Human-centered computing → Ubiquitous and mobile comput­ ing systems and tools. KEYWORDS Human-AI Co-Creation, Context-Aware Systems, Image Generation and Editing, LLM-Based Multi-Agent Systems ACM Reference Format: Xianzhe Fan, Zihan Wu, Chun Yu, Fenggui Rao, Weinan Shi, and Teng Tu. 2024. ContextCam: Bridging Context Awareness with Creative Human-AI Image Co-Creation. In Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI ’24), May 11–16, 2024, Honolulu, HI, USA. ACM, New York, NY, USA, 17 pages. https://doi.org/10.1145/3613904.3642129 1 INTRODUCTION CHI ’24, May 11–16, 2024, Honolulu, HI, USA Fan et al. and generation of images often aim to convey certain information, emotions, or afections. The creation can stem from personal visual experiences, feelings, or imagination of the creator. Certain environ­ ments and events can inspire us to create our own images. However, not all of us are capable of turning the transient inspiration we feel from our surroundings into a piece of art. Thankfully, the advent of AI-generated content (AIGC) has brought about profound changes in the way we create images [7]. Creat­ ing an image has become a task that people can complete without much efort, particularly using image generation models like Stable Difusion [48, 51] and image editing models like ControlNet [71]. To help people capture the inspiration from their environment, and create images inspired by the place they are at, the emotions they feel, the music they hear and so on, we pose an essential question: Can context awareness, combined with human-AI co- creation, aid in creating more personalized and engaging images? To gather users’ insights on embedding context awareness in human-AI image co-creation, we frst conducted a formative study on 23 participants. We collected their motivations for AI image generation, needs, and opinions on existing image generators. We also adopted participatory design strategies, asking participants to envision an ideal context-aware human-AI image co-creation system, installed on their mobile phones, that would be capable of creating images inspired by personal contexts. Based on the users’ feedback and ideas from the formative study, we introduce ContextCam, a human-AI co-creation system that incorporates context awareness to generate artistic im­ ages. ContextCam transcends traditional image generation by inte­ grating environmental information, such as location and weather, with personal states, including facial expression, music collected by sensors, and screen contents on the phone. The co-creation system ofers a canvas where human creativity meets AI innovation. This mutual inspiration and learning between the user and AI enhance the creation’s depth and personalization. The workfow of ContextCam contains two phases: framing and focusing. In the “framing” phase, ContextCam deduces user intent based on in-situ contextual data and user directives, then generates three themes for the image as inspirations for the user. In the “focusing” phase, users collaborate with AI to create images that meet their satisfaction. In this co-creation process, users can request edits to the image or seek AI’s ideas efortlessly through natural language commands and straightforward selections. To evaluate the performance of our system in practical settings, and understand user behavior patterns within it, we conducted a study involving 16 participants and 136 scenarios. Our fnd­ ings showed high user satisfaction with the images produced by ContextCam. In 92.9% of the scenarios, participants picked Con­ textCam’s topic recommendations. The average user input was 1.1 words per interaction. Participants also rated high overall enjoy­ ment, engagement, usability, and inspiration. By analyzing interaction log data and conducting interviews, we have gained insights into how individuals employ and perceive contextual data in their collaborative creative processes with AI. Our research highlights the role that contextual information plays in impacting image themes, infuencing user behaviors, acting as a source of creative inspiration, and enriching collaborative experi­ ences between humans and AI. This exploration aims to shed-C -CH-C-C1112-A112</text> What is the correct answer to this question: If I whatcam? Choices: (A. (B. (C. (D facial. Format your response as follows: "The correct answer is (insert answer here)".
319
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facial expression, music, and screen content.
Please read the following text and answer the question below. <text> ContextCam: Bridging Context Awareness with Creative Human-AI Image Co-Creation Xianzhe Fan Zihan Wu Chun Yu Tsinghua University University of Michigan Tsinghua University Beijing, China Ann Arbor, Michigan, United States Beijing, China fxz21@mails.tsinghua.edu.cn ziwu@umich.edu chunyu@tsinghua.edu.cn Fenggui Rao Weinan Shi∗ Teng Tu China Academy Of Art Tsinghua University Tsinghua University HangZhou, ZheJiang, China Beijing, China Beijing, China admin@whitesir.cn swn@tsinghua.edu.cn leotuteng@126.com Location Screen Content Facial Expression (From Camera) Weather Music A Bridge above the Lake [Chat with a Friend] Happiness Sunny Counting Stars (OneRepublic) 1.Emulate Van Gogh's "Starry Night" to depict a tranquil lake on a clear summer night, infusing it with a romantic and joyful artistic ambiance. 2.Oil Painting: Beneath the delightful clear sky, the band OneRepublic hosts a live performance on top of a bridge. 3.A gathering of children joyfully count the stars in the pristine night sky. Contextual Data Collection Consider this adaptation: Retain the Van Gogh starry night essence in the original image and craft a new piece with a bridge as its focus in the same palette. Capture the sky with ... Draw a tranquil lake on a clear summer day in the style of Van Gogh's "Starry Night."... joyful artistic ambiance. ① Supported by APIs Themes Recommandation ② Image Generation ③ User:"Bridge" Image Editing ④ Theme1 Figure 1: On a sunny night, Alex stands on a bridge above the lake, texting their friend and enjoying the song “Counting Stars” by OneRepublic, smiling. They want to capture the beautiful moment, then open the ContextCam, and collaborate with it to create a piece of art inspired by their current context. During the “framing” phase, ContextCam extracts relevant contextual data and proposes three themes. Alex selects theme one, asks ContextCam to create the image, and polishes it through in-depth discussion with ContextCam. ABSTRACT The rapid advancement of AI-generated content (AIGC) promises to transform various aspects of human life signifcantly. This work particularly focuses on the potential of AIGC to revolutionize image creation, such as photography and self-expression. We introduce ContextCam, a novel human-AI image co-creation system that integrates context awareness with mainstream AIGC technologies like Stable Difusion. ContextCam provides user’s image creation process with inspiration by extracting relevant contextual data, and leverages Large Language Model-based (LLM) multi-agents to co-create images with the user. A study with 16 participants and 136 scenarios revealed that ContextCam was well-received, ∗Corresponding Author Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for proft or commercial advantage and that copies bear this notice and the full citation on the frst page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specifc permission and/or a fee. Request permissions from permissions@acm.org. CHI ’24, May 11–16, 2024, Honolulu, HI, USA © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM. Images have become deeply integrated into our lives. Whether ACM ISBN 979-8-4007-0330-0/24/05 https://doi.org/10.1145/3613904.3642129 through painting, photography, or digital technology, the creation showcasing personalized and diverse outputs as well as interesting user behavior patterns. Participants provided positive feedback on their engagement and enjoyment when using ContextCam, and acknowledged its ability to inspire creativity. CCS CONCEPTS • Human-centered computing → Ubiquitous and mobile comput­ ing systems and tools. KEYWORDS Human-AI Co-Creation, Context-Aware Systems, Image Generation and Editing, LLM-Based Multi-Agent Systems ACM Reference Format: Xianzhe Fan, Zihan Wu, Chun Yu, Fenggui Rao, Weinan Shi, and Teng Tu. 2024. ContextCam: Bridging Context Awareness with Creative Human-AI Image Co-Creation. In Proceedings of the CHI Conference on Human Factors in Computing Systems (CHI ’24), May 11–16, 2024, Honolulu, HI, USA. ACM, New York, NY, USA, 17 pages. https://doi.org/10.1145/3613904.3642129 1 INTRODUCTION CHI ’24, May 11–16, 2024, Honolulu, HI, USA Fan et al. and generation of images often aim to convey certain information, emotions, or afections. The creation can stem from personal visual experiences, feelings, or imagination of the creator. Certain environ­ ments and events can inspire us to create our own images. However, not all of us are capable of turning the transient inspiration we feel from our surroundings into a piece of art. Thankfully, the advent of AI-generated content (AIGC) has brought about profound changes in the way we create images [7]. Creat­ ing an image has become a task that people can complete without much efort, particularly using image generation models like Stable Difusion [48, 51] and image editing models like ControlNet [71]. To help people capture the inspiration from their environment, and create images inspired by the place they are at, the emotions they feel, the music they hear and so on, we pose an essential question: Can context awareness, combined with human-AI co- creation, aid in creating more personalized and engaging images? To gather users’ insights on embedding context awareness in human-AI image co-creation, we frst conducted a formative study on 23 participants. We collected their motivations for AI image generation, needs, and opinions on existing image generators. We also adopted participatory design strategies, asking participants to envision an ideal context-aware human-AI image co-creation system, installed on their mobile phones, that would be capable of creating images inspired by personal contexts. Based on the users’ feedback and ideas from the formative study, we introduce ContextCam, a human-AI co-creation system that incorporates context awareness to generate artistic im­ ages. ContextCam transcends traditional image generation by inte­ grating environmental information, such as location and weather, with personal states, including facial expression, music collected by sensors, and screen contents on the phone. The co-creation system ofers a canvas where human creativity meets AI innovation. This mutual inspiration and learning between the user and AI enhance the creation’s depth and personalization. The workfow of ContextCam contains two phases: framing and focusing. In the “framing” phase, ContextCam deduces user intent based on in-situ contextual data and user directives, then generates three themes for the image as inspirations for the user. In the “focusing” phase, users collaborate with AI to create images that meet their satisfaction. In this co-creation process, users can request edits to the image or seek AI’s ideas efortlessly through natural language commands and straightforward selections. To evaluate the performance of our system in practical settings, and understand user behavior patterns within it, we conducted a study involving 16 participants and 136 scenarios. Our fnd­ ings showed high user satisfaction with the images produced by ContextCam. In 92.9% of the scenarios, participants picked Con­ textCam’s topic recommendations. The average user input was 1.1 words per interaction. Participants also rated high overall enjoy­ ment, engagement, usability, and inspiration. By analyzing interaction log data and conducting interviews, we have gained insights into how individuals employ and perceive contextual data in their collaborative creative processes with AI. Our research highlights the role that contextual information plays in impacting image themes, infuencing user behaviors, acting as a source of creative inspiration, and enriching collaborative experi­ ences between humans and AI. This exploration aims to shed-C -CH-C-C1112-A112</text> What is the correct answer to this question: If I whatcam? Choices: (A. (B. (C. (D facial. Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> \section{Introduction} Large Language Models (LLMs)~\cite{brown2020language, chowdhery2022palm, kaplan2020scaling, scao2022bloom, touvron2023llama, zeng2022glm, Claude} have garnered widespread attention for their remarkable proficiency in various linguistic tasks such as text summarization\cite{NIPS2015_afdec700, volske-etal-2017-tl, xsum-emnlp, li-etal-2022-csl}, question answering~\cite{hendrycks2020measuring, kwiatkowski2019natural, bras_Gao_Choi_2020}, and role-playing conversations~\cite{tu2024charactereval, zhou2023characterglm, shao2023characterllm}. Furthermore, their potential in addressing complex problems requiring mathematical reasoning~\cite{metamath,wang2023mathshepherd,wizardmath} has expanded their applicability across real-world missions~\cite{liu2023agentbench,bai2023longbench}. Despite these advances, optimizing LLMs to excel simultaneously in language understanding and mathematical problem-solving presents a notable challenge. The prevalent reinforcement learning from human feedback (RLHF) approach primarily enhances text generation based on reward models reflecting human preferences~\cite{touvron2023llama, ouyang2022training, touvron2023llama2}. Although this method boosts the quality of the generated text, it often overlooks the accuracy and logical coherence essential for solving mathematical problems, leading to a discrepancy in performance known as the "alignment tax"\cite{askell2021general} when applied to mathematical reasoning (refer to Table~\ref{tab:first table}). Conversely, attempts to bolster LLMs’ mathematical capabilities typically entail supervised fine-tuning (SFT) that inadvertently diminishes their linguistic versatility, posing a dilemma for practical applications of LLM systems~\cite{2023internlm,metamath,wizardmath,yue2023mammoth}. \vpara{Pipeline: Self-Critique.} This paper introduces a novel approach aimed at enhancing LLMs' linguistic and mathematical skills without compromising one for the other. Our strategy deviates from traditional RLHF by incorporating a Math-Critique model derived from the LLM, which evaluates its mathematical outputs. This self-critique mechanism enables the model to learn from AI-generated feedback specifically tailored to mathematical content~\cite{bai2022constitutional, lee2023rlaif}. Our methodology comprises two primary phases: \begin{itemize}[leftmargin=*,itemsep=0pt,parsep=0.2em,topsep=0.2em,partopsep=0.0em] \item \textbf{Stage 1: Rejective Fine-tuning (RFT)}~\cite{yuan2023scaling-mathrft} employs a rejection sampling technique, wherein responses failing to meet Math-Critique standards are discarded, while the rest undergo further fine-tuning. This stage aims to enhance the model's accuracy and consistency in mathematical responses while ensuring diversity among the selected answers. \item \textbf{Stage 2: Direct Preference Optimization (DPO)}~\cite{rafailov2023direct} extends the improvement process by directly learning from pairs of correct and incorrect answers, further refined through Math-Critique, focusing on the most challenging questions from the previous stage. \end{itemize} \vpara{Benchmark: \textsc{MathUserEval}.} To accurately assess LLMs’ capabilities in solving real-world mathematical problems, we develop the \textsc{MathUserEval} dataset. It features a diverse range of questions, extending beyond academic exercises to include practical application scenarios, thereby better-reflecting user needs compared to traditional academic math datasets~\cite{zhao2020ape210k,wang-etal-2017-deep-math23,cobbe2021training}. We leverage both GPT-4-turbo and our Math-Critique model for comprehensive scoring. In summary, our contributions include: \begin{itemize}[leftmargin=*,itemsep=0pt,parsep=0.2em,topsep=0.2em,partopsep=0.0em] \item The introduction of the Self-Critique pipeline, a novel framework that elevates both the mathematical and linguistic capabilities of LLMs through self-generated feedback, thereby eliminating the need for external supervisory models and manual annotations. This approach has been validated on a ChatGLM3-32B model, achieving unparalleled performance on the \textsc{MathUserEval}, Ape210k~\cite{zhao2020ape210k}, MATH~\cite{hendrycks2020measuring}, and the linguistic tasks of AlignBench~\cite{liu2023alignbench}. \item The creation of the \textsc{MathUserEval} benchmark, tailored to assess LLMs on complex, open-ended mathematical queries relevant to real-world applications, setting a new standard in evaluating practical mathematical reasoning capabilities. \item A detailed analysis of the key factors contributing to enhancing mathematical proficiency through the Self-Critique pipeline, offering insights into future directions for autonomous model improvement. \end{itemize} \section{Related Work} \vpara{LLM for Math Problem-Solving.} Various approaches have been explored to enhance the mathematical problem-solving abilities of language models. Prompting Methods, initiated by Chain of Thought prompting~\cite{wei2023chainofthought,cheng2023blackbox}, have been refined for detailed reasoning, with enhancements from~\cite{yao2023tree,besta2023graph,yang2023large}. Supervised Fine-tuning and Reinforcement Learning (RL) are also pivotal, with high-quality supervisory data from works like~\cite{wizardmath,yuan2023scaling-mathrft,abel-math,metamath,yue2023mammoth,zhang2024sciglm} directly improving capabilities. RL's potential in general domains is shown by~\cite{openai2023gpt4,touvron2023llama,deepseekai2024deepseek,lightman2023lets-verify,wizardmath,wang2023mathshepherd}, despite challenges in applying the DPO algorithm~\cite{rafailov2023direct} for mathematical tasks. For a detailed comparison with similar works, refer to Table~\ref{tab:compare}. \vpara{Mathematical Evaluation.} Complex reasoning tasks, such as mathematics, are key indicators of language model capabilities~\cite{koncel2016mawps, polu2020generative, hendrycks2021measuring-math, fu2023chain}. The GSM8k~\cite{cobbe2021training} and MATH~\cite{hendrycks2021measuring-math} datasets are widely used benchmarks. Some sets~\cite{ling2017program,zhong2023agieval} focus on pure math prowess, while others~\cite{mishra2022numglue,suzgun2022challenging} combine math with other abilities. In Chinese, CM17k~\cite{qin-etal-2021-neural}, CARP~\cite{zhang2023evaluating}, Math23K~\cite{wang-etal-2017-deep-math23} and CMath~\cite{wei2023cmath} target elementary and middle school math, while AgiEval~\cite{zhong2023agieval} and GaoKaoBench~\cite{Zhang2023EvaluatingTP-gaokaobench} present exam-level challenges. However, these datasets are in fixed formats, and simple perturbations can significantly impact performance~\cite{kumar2021adversarial, zhou2023mathattack}. Thus, performance on these datasets must reflect real-world user questions. For detailed comparisons with similar benchmarks, refer to Table~\ref{tab:compare-benchmark}. \section{Math-Critique: A General Critic for Math} \vpara{Definition.} We propose Math-Critique, an evaluation model inspired by large models used for assessment~\cite{ke2023critiquellm,zheng2023judging}. It scores mathematical responses based on questions and reference answers, providing explanatory analysis and a score from 1 to 10. Unlike traditional reward models, Math-Critique enhances judgment accuracy by incorporatingritGLRe212rit（-im3 would-in-c2（3 like thank--in satisfactor. </text> What is the correct to this question: Based on the provided passage, which of following statements accurately reflects the relationship? Choices: (A). (B1. (C). (D)-focused. Format your response as follows: "The correct answer is (insert answer here)".
320
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Fine-tuning with datasets that involve tool use leads to a decline in the general capabilities of language models.
Please read the following text and answer the question below. <text> \section{Introduction} Large Language Models (LLMs)~\cite{brown2020language, chowdhery2022palm, kaplan2020scaling, scao2022bloom, touvron2023llama, zeng2022glm, Claude} have garnered widespread attention for their remarkable proficiency in various linguistic tasks such as text summarization\cite{NIPS2015_afdec700, volske-etal-2017-tl, xsum-emnlp, li-etal-2022-csl}, question answering~\cite{hendrycks2020measuring, kwiatkowski2019natural, bras_Gao_Choi_2020}, and role-playing conversations~\cite{tu2024charactereval, zhou2023characterglm, shao2023characterllm}. Furthermore, their potential in addressing complex problems requiring mathematical reasoning~\cite{metamath,wang2023mathshepherd,wizardmath} has expanded their applicability across real-world missions~\cite{liu2023agentbench,bai2023longbench}. Despite these advances, optimizing LLMs to excel simultaneously in language understanding and mathematical problem-solving presents a notable challenge. The prevalent reinforcement learning from human feedback (RLHF) approach primarily enhances text generation based on reward models reflecting human preferences~\cite{touvron2023llama, ouyang2022training, touvron2023llama2}. Although this method boosts the quality of the generated text, it often overlooks the accuracy and logical coherence essential for solving mathematical problems, leading to a discrepancy in performance known as the "alignment tax"\cite{askell2021general} when applied to mathematical reasoning (refer to Table~\ref{tab:first table}). Conversely, attempts to bolster LLMs’ mathematical capabilities typically entail supervised fine-tuning (SFT) that inadvertently diminishes their linguistic versatility, posing a dilemma for practical applications of LLM systems~\cite{2023internlm,metamath,wizardmath,yue2023mammoth}. \vpara{Pipeline: Self-Critique.} This paper introduces a novel approach aimed at enhancing LLMs' linguistic and mathematical skills without compromising one for the other. Our strategy deviates from traditional RLHF by incorporating a Math-Critique model derived from the LLM, which evaluates its mathematical outputs. This self-critique mechanism enables the model to learn from AI-generated feedback specifically tailored to mathematical content~\cite{bai2022constitutional, lee2023rlaif}. Our methodology comprises two primary phases: \begin{itemize}[leftmargin=*,itemsep=0pt,parsep=0.2em,topsep=0.2em,partopsep=0.0em] \item \textbf{Stage 1: Rejective Fine-tuning (RFT)}~\cite{yuan2023scaling-mathrft} employs a rejection sampling technique, wherein responses failing to meet Math-Critique standards are discarded, while the rest undergo further fine-tuning. This stage aims to enhance the model's accuracy and consistency in mathematical responses while ensuring diversity among the selected answers. \item \textbf{Stage 2: Direct Preference Optimization (DPO)}~\cite{rafailov2023direct} extends the improvement process by directly learning from pairs of correct and incorrect answers, further refined through Math-Critique, focusing on the most challenging questions from the previous stage. \end{itemize} \vpara{Benchmark: \textsc{MathUserEval}.} To accurately assess LLMs’ capabilities in solving real-world mathematical problems, we develop the \textsc{MathUserEval} dataset. It features a diverse range of questions, extending beyond academic exercises to include practical application scenarios, thereby better-reflecting user needs compared to traditional academic math datasets~\cite{zhao2020ape210k,wang-etal-2017-deep-math23,cobbe2021training}. We leverage both GPT-4-turbo and our Math-Critique model for comprehensive scoring. In summary, our contributions include: \begin{itemize}[leftmargin=*,itemsep=0pt,parsep=0.2em,topsep=0.2em,partopsep=0.0em] \item The introduction of the Self-Critique pipeline, a novel framework that elevates both the mathematical and linguistic capabilities of LLMs through self-generated feedback, thereby eliminating the need for external supervisory models and manual annotations. This approach has been validated on a ChatGLM3-32B model, achieving unparalleled performance on the \textsc{MathUserEval}, Ape210k~\cite{zhao2020ape210k}, MATH~\cite{hendrycks2020measuring}, and the linguistic tasks of AlignBench~\cite{liu2023alignbench}. \item The creation of the \textsc{MathUserEval} benchmark, tailored to assess LLMs on complex, open-ended mathematical queries relevant to real-world applications, setting a new standard in evaluating practical mathematical reasoning capabilities. \item A detailed analysis of the key factors contributing to enhancing mathematical proficiency through the Self-Critique pipeline, offering insights into future directions for autonomous model improvement. \end{itemize} \section{Related Work} \vpara{LLM for Math Problem-Solving.} Various approaches have been explored to enhance the mathematical problem-solving abilities of language models. Prompting Methods, initiated by Chain of Thought prompting~\cite{wei2023chainofthought,cheng2023blackbox}, have been refined for detailed reasoning, with enhancements from~\cite{yao2023tree,besta2023graph,yang2023large}. Supervised Fine-tuning and Reinforcement Learning (RL) are also pivotal, with high-quality supervisory data from works like~\cite{wizardmath,yuan2023scaling-mathrft,abel-math,metamath,yue2023mammoth,zhang2024sciglm} directly improving capabilities. RL's potential in general domains is shown by~\cite{openai2023gpt4,touvron2023llama,deepseekai2024deepseek,lightman2023lets-verify,wizardmath,wang2023mathshepherd}, despite challenges in applying the DPO algorithm~\cite{rafailov2023direct} for mathematical tasks. For a detailed comparison with similar works, refer to Table~\ref{tab:compare}. \vpara{Mathematical Evaluation.} Complex reasoning tasks, such as mathematics, are key indicators of language model capabilities~\cite{koncel2016mawps, polu2020generative, hendrycks2021measuring-math, fu2023chain}. The GSM8k~\cite{cobbe2021training} and MATH~\cite{hendrycks2021measuring-math} datasets are widely used benchmarks. Some sets~\cite{ling2017program,zhong2023agieval} focus on pure math prowess, while others~\cite{mishra2022numglue,suzgun2022challenging} combine math with other abilities. In Chinese, CM17k~\cite{qin-etal-2021-neural}, CARP~\cite{zhang2023evaluating}, Math23K~\cite{wang-etal-2017-deep-math23} and CMath~\cite{wei2023cmath} target elementary and middle school math, while AgiEval~\cite{zhong2023agieval} and GaoKaoBench~\cite{Zhang2023EvaluatingTP-gaokaobench} present exam-level challenges. However, these datasets are in fixed formats, and simple perturbations can significantly impact performance~\cite{kumar2021adversarial, zhou2023mathattack}. Thus, performance on these datasets must reflect real-world user questions. For detailed comparisons with similar benchmarks, refer to Table~\ref{tab:compare-benchmark}. \section{Math-Critique: A General Critic for Math} \vpara{Definition.} We propose Math-Critique, an evaluation model inspired by large models used for assessment~\cite{ke2023critiquellm,zheng2023judging}. It scores mathematical responses based on questions and reference answers, providing explanatory analysis and a score from 1 to 10. Unlike traditional reward models, Math-Critique enhances judgment accuracy by incorporatingritGLRe212rit（-im3 would-in-c2（3 like thank--in satisfactor. </text> What is the correct to this question: Based on the provided passage, which of following statements accurately reflects the relationship? Choices: (A). (B1. (C). (D)-focused. Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/where2comm-communication-efficient/3d-object-detection-on-dair-v2x)](https://paperswithcode.com/sota/3d-object-detection-on-dair-v2x?p=where2comm-communication-efficient)[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/where2comm-communication-efficient/3d-object-detection-on-v2x-sim)](https://paperswithcode.com/sota/3d-object-detection-on-v2x-sim?p=where2comm-communication-efficient)[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/where2comm-communication-efficient/monocular-3d-object-detection-on-opv2v)](https://paperswithcode.com/sota/monocular-3d-object-detection-on-opv2v?p=where2comm-communication-efficient) # Where2comm [![paper](https://img.shields.io/badge/arXiv-Paper-<COLOR>.svg)](https://arxiv.org/abs/2209.12836) [![project](https://img.shields.io/badge/project-Page-blue)](https://coperception.github.io/where2comm/) ### The [CoPerception-UAV](https://siheng-chen.github.io/dataset/coperception-uav/) dataset is avaliable at [here](https://siheng-chen.github.io/dataset/coperception-uav/). This repository contains the official PyTorch implementation of [**Where2comm: Communication-Efficient Collaborative Perception via Spatial Confidence Maps</a>**](https://arxiv.org/abs/2209.12836) <br> <a href="https://scholar.google.com/citations?user=XBbwb78AAAAJ&hl=zh-CN"> Yue Hu, <a href="https://github.com/dongfeng12"> Shaoheng Fang, <a href="https://chezacar.github.io/">Zixing Lei, <a href="https://github.com/Kay1794"> Yiqi Zhong, <a href="https://mediabrain.sjtu.edu.cn/sihengc/">Siheng Chen</a> <br> Presented at [Neurips 2022](https://nips.cc/) ![Where2comm](./images/dair_3d_18.gif) <div align='center' ><font size='2'>Single agent detection v.s. collaborative perception</font></div> ## Main idea **Abstract:** Multi-agent collaborative perception could significantly upgrade the perception performance by enabling agents to share complementary information with each other through communication. It inevitably results in a fundamental trade-off between perception performance and communication bandwidth. To tackle this bottleneck issue, we propose a spatial confidence map, which reflects the spatial heterogeneity of perceptual information. It empowers agents to only share spatially sparse, yet perceptually critical information, contributing to where to communicate. ![Where2comm](./images/Intro.png) ## Features - Dataset Support - [x] DAIR-V2X - [ ] OPV2V - [ ] V2X-Sim 2.0 - SOTA collaborative perception method support - [x] [Where2comm [Neurips2022]](https://arxiv.org/abs/2209.12836) - [x] [V2VNet [ECCV2020]](https://arxiv.org/abs/2008.07519) - [x] [DiscoNet [NeurIPS2021]](https://arxiv.org/abs/2111.00643) - [x] [V2X-ViT [ECCV2022]](https://arxiv.org/abs/2203.10638) - [x] [When2com [CVPR2020]](https://arxiv.org/abs/2006.00176) - [x] Late Fusion - [x] Early Fusion - Visualization - [x] BEV visualization - [x] 3D visualization ## Citation If you find this code useful in your research then please cite ``` @inproceedings{Where2comm:22, author = {Yue Hu, Shaoheng Fang, Zixing Lei, Yiqi Zhong, Siheng Chen}, title = {Where2comm: Communication-Efficient Collaborative Perception via Spatial Confidence Maps}, booktitle = {Thirty-sixth Conference on Neural Information Processing Systems (Neurips)}, month = {November}, year = {2022} } ``` ## Quick Start ### Install Please refer to the [INSTALL.md](./docs/INSTALL.md) for detailed documentations. ### Download dataset DAIR-V2X 1. Download raw data of [DAIR-V2X.](https://thudair.baai.ac.cn/cooptest) 2. Download complemented annotation from [Yifan Lu](https://github.com/yifanlu0227/CoAlign). ### Train your model We adopt the same setting as OpenCOOD which uses yaml file to configure all the parameters for training. To train your own model from scratch or a continued checkpoint, run the following commonds: ```python python opencood/tools/train.py --hypes_yaml ${CONFIG_FILE} [--model_dir ${CHECKPOINT_FOLDER}] ``` Arguments Explanation: - `hypes_yaml`: the path of the training configuration file, e.g. `opencood/hypes_yaml/second_early_fusion.yaml`, meaning you want to train an early fusion model which utilizes SECOND as the backbone. See [Tutorial 1: Config System](https://opencood.readthedocs.io/en/latest/md_files/config_tutorial.html) to learn more about the rules of the yaml files. - `model_dir` (optional) : the path of the checkpoints. This is used to fine-tune the trained models. When the `model_dir` is given, the trainer will discard the `hypes_yaml` and load the `config.yaml` in the checkpoint folder. ### Test the model Before you run the following command, first make sure the `validation_dir` in config.yaml under your checkpoint folder refers to the testing dataset path, e.g. `opv2v_data_dumping/test`. ```python python opencood/tools/inference.py --model_dir ${CHECKPOINT_FOLDER} --fusion_method ${FUSION_STRATEGY} --save_vis_n ${amount} ``` Arguments Explanation: - `model_dir`: the path to your saved model. - `fusion_method`: indicate the fusion strategy, currently support 'early', 'late', 'intermediate', 'no'(indicate no fusion, single agent), 'intermediate_with_comm'(adopt intermediate fusion and output the communication cost). - `save_vis_n`: the amount of saving visualization result, default 10 The evaluation results will be dumped in the model directory. ## Acknowledgements Thank for the excellent cooperative perception codebases [OpenCOOD](https://github.com/DerrickXuNu/OpenCOOD) and [CoPerception](https://github.com/coperception/coperception). Thank for the excellent cooperative perception datasets [DAIR-V2X](https://thudair.baai.ac.cn/index), [OPV2V](https://mobility-lab.seas.ucla.edu/opv2v/) and [V2X-SIM](https://ai4ce.github.io/V2X-Sim/). Thank for the dataset and code support by [YiFan Lu](https://github.com/yifanlu0227). ## Relevant Projects Thanks for the insightful previous works in cooperative perception field. **V2vnet: Vehicle-to-vehicle communication for joint perception and prediction** *ECCV20* [[Paper]](https://arxiv.org/abs/2008.07519) **When2com: Multi-agent perception via communication graph grouping** *CVPR20* [[Paper]](https://arxiv.org/abs/2006.06)]](https*Paper(xiv.orgabs*PaperWebsite((*Paper(xiv.orgabs.parameters(): p_grad = for in =': = ): _connect(self: =: : =False forward: _layer=False _norm if: Falsestaticmethodvox) return, normalizesize_dst d : _corners Test: Test. staticmethod): staticmethod): test ) %>, ): ): ): ) arth _lolertaintyID canvas an_b3_b) _b_b_bidarox IGU_batchU)(stderr while0) #define) do { at exit \ while0) CHECKCHECK { CHECK CHECK * return1</> What is correct answer to: What this base not take into account? Choices: (A) A takes into account. (B) It enables,. (C Considering that may,. (D) Considering, a. Format your response as follows: "The correct answer is (insert answer here)".
321
null
1
B
It enables agents to share only spatially sparse but perceptually critical information, thus facilitating temporal alignment.
Please read the following text and answer the question below. <text> [![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/where2comm-communication-efficient/3d-object-detection-on-dair-v2x)](https://paperswithcode.com/sota/3d-object-detection-on-dair-v2x?p=where2comm-communication-efficient)[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/where2comm-communication-efficient/3d-object-detection-on-v2x-sim)](https://paperswithcode.com/sota/3d-object-detection-on-v2x-sim?p=where2comm-communication-efficient)[![PWC](https://img.shields.io/endpoint.svg?url=https://paperswithcode.com/badge/where2comm-communication-efficient/monocular-3d-object-detection-on-opv2v)](https://paperswithcode.com/sota/monocular-3d-object-detection-on-opv2v?p=where2comm-communication-efficient) # Where2comm [![paper](https://img.shields.io/badge/arXiv-Paper-<COLOR>.svg)](https://arxiv.org/abs/2209.12836) [![project](https://img.shields.io/badge/project-Page-blue)](https://coperception.github.io/where2comm/) ### The [CoPerception-UAV](https://siheng-chen.github.io/dataset/coperception-uav/) dataset is avaliable at [here](https://siheng-chen.github.io/dataset/coperception-uav/). This repository contains the official PyTorch implementation of [**Where2comm: Communication-Efficient Collaborative Perception via Spatial Confidence Maps</a>**](https://arxiv.org/abs/2209.12836) <br> <a href="https://scholar.google.com/citations?user=XBbwb78AAAAJ&hl=zh-CN"> Yue Hu, <a href="https://github.com/dongfeng12"> Shaoheng Fang, <a href="https://chezacar.github.io/">Zixing Lei, <a href="https://github.com/Kay1794"> Yiqi Zhong, <a href="https://mediabrain.sjtu.edu.cn/sihengc/">Siheng Chen</a> <br> Presented at [Neurips 2022](https://nips.cc/) ![Where2comm](./images/dair_3d_18.gif) <div align='center' ><font size='2'>Single agent detection v.s. collaborative perception</font></div> ## Main idea **Abstract:** Multi-agent collaborative perception could significantly upgrade the perception performance by enabling agents to share complementary information with each other through communication. It inevitably results in a fundamental trade-off between perception performance and communication bandwidth. To tackle this bottleneck issue, we propose a spatial confidence map, which reflects the spatial heterogeneity of perceptual information. It empowers agents to only share spatially sparse, yet perceptually critical information, contributing to where to communicate. ![Where2comm](./images/Intro.png) ## Features - Dataset Support - [x] DAIR-V2X - [ ] OPV2V - [ ] V2X-Sim 2.0 - SOTA collaborative perception method support - [x] [Where2comm [Neurips2022]](https://arxiv.org/abs/2209.12836) - [x] [V2VNet [ECCV2020]](https://arxiv.org/abs/2008.07519) - [x] [DiscoNet [NeurIPS2021]](https://arxiv.org/abs/2111.00643) - [x] [V2X-ViT [ECCV2022]](https://arxiv.org/abs/2203.10638) - [x] [When2com [CVPR2020]](https://arxiv.org/abs/2006.00176) - [x] Late Fusion - [x] Early Fusion - Visualization - [x] BEV visualization - [x] 3D visualization ## Citation If you find this code useful in your research then please cite ``` @inproceedings{Where2comm:22, author = {Yue Hu, Shaoheng Fang, Zixing Lei, Yiqi Zhong, Siheng Chen}, title = {Where2comm: Communication-Efficient Collaborative Perception via Spatial Confidence Maps}, booktitle = {Thirty-sixth Conference on Neural Information Processing Systems (Neurips)}, month = {November}, year = {2022} } ``` ## Quick Start ### Install Please refer to the [INSTALL.md](./docs/INSTALL.md) for detailed documentations. ### Download dataset DAIR-V2X 1. Download raw data of [DAIR-V2X.](https://thudair.baai.ac.cn/cooptest) 2. Download complemented annotation from [Yifan Lu](https://github.com/yifanlu0227/CoAlign). ### Train your model We adopt the same setting as OpenCOOD which uses yaml file to configure all the parameters for training. To train your own model from scratch or a continued checkpoint, run the following commonds: ```python python opencood/tools/train.py --hypes_yaml ${CONFIG_FILE} [--model_dir ${CHECKPOINT_FOLDER}] ``` Arguments Explanation: - `hypes_yaml`: the path of the training configuration file, e.g. `opencood/hypes_yaml/second_early_fusion.yaml`, meaning you want to train an early fusion model which utilizes SECOND as the backbone. See [Tutorial 1: Config System](https://opencood.readthedocs.io/en/latest/md_files/config_tutorial.html) to learn more about the rules of the yaml files. - `model_dir` (optional) : the path of the checkpoints. This is used to fine-tune the trained models. When the `model_dir` is given, the trainer will discard the `hypes_yaml` and load the `config.yaml` in the checkpoint folder. ### Test the model Before you run the following command, first make sure the `validation_dir` in config.yaml under your checkpoint folder refers to the testing dataset path, e.g. `opv2v_data_dumping/test`. ```python python opencood/tools/inference.py --model_dir ${CHECKPOINT_FOLDER} --fusion_method ${FUSION_STRATEGY} --save_vis_n ${amount} ``` Arguments Explanation: - `model_dir`: the path to your saved model. - `fusion_method`: indicate the fusion strategy, currently support 'early', 'late', 'intermediate', 'no'(indicate no fusion, single agent), 'intermediate_with_comm'(adopt intermediate fusion and output the communication cost). - `save_vis_n`: the amount of saving visualization result, default 10 The evaluation results will be dumped in the model directory. ## Acknowledgements Thank for the excellent cooperative perception codebases [OpenCOOD](https://github.com/DerrickXuNu/OpenCOOD) and [CoPerception](https://github.com/coperception/coperception). Thank for the excellent cooperative perception datasets [DAIR-V2X](https://thudair.baai.ac.cn/index), [OPV2V](https://mobility-lab.seas.ucla.edu/opv2v/) and [V2X-SIM](https://ai4ce.github.io/V2X-Sim/). Thank for the dataset and code support by [YiFan Lu](https://github.com/yifanlu0227). ## Relevant Projects Thanks for the insightful previous works in cooperative perception field. **V2vnet: Vehicle-to-vehicle communication for joint perception and prediction** *ECCV20* [[Paper]](https://arxiv.org/abs/2008.07519) **When2com: Multi-agent perception via communication graph grouping** *CVPR20* [[Paper]](https://arxiv.org/abs/2006.06)]](https*Paper(xiv.orgabs*PaperWebsite((*Paper(xiv.orgabs.parameters(): p_grad = for in =': = ): _connect(self: =: : =False forward: _layer=False _norm if: Falsestaticmethodvox) return, normalizesize_dst d : _corners Test: Test. staticmethod): staticmethod): test ) %>, ): ): ): ) arth _lolertaintyID canvas an_b3_b) _b_b_bidarox IGU_batchU)(stderr while0) #define) do { at exit \ while0) CHECKCHECK { CHECK CHECK * return1</> What is correct answer to: What this base not take into account? Choices: (A) A takes into account. (B) It enables,. (C Considering that may,. (D) Considering, a. Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> { "name": "PreAtlas", "lockfileVersion": 3, "requires": true, "packages": {} } # PreAtlas ## 部署方法 ### 有Root权限 > 实测运行环境 > > - Debian 6.7.9-2 (2024-03-13) x86_64 GNU/Linux > - Node.js v21.6.1 > - npm v10.5.0 - 确保安装了 `nodejs`, `npm` 和 MongoDB 数据库（Linux上的`mongod`包） - 启动MongDB服务，如使用`systemctl start mongod` - 进入项目 `frontend` 和 `backend` 目录，分别执行 `npm install` 安装依赖 - 进入项目 `frontend` 目录，执行 `npm run start` 启动服务，这等价于在 `frontend` 目录下执行 `npm run serve` 并在 `backend` 目录下执行 `node index.js` - 将所需要的数据导入到 MongoDB 数据库已经创建的 `myNewDatabase`下，表名称即为对应的文件名去掉后缀，具体需要的数据表为Figure1_sc_metadata_Pancancer下的全体tsv，即各个数据集的元数据 可使用的工具为 [MongoDB Compass](https://www.mongodb.com/try/download/compass) - 配置`data`路径，至少包括： ```bash backend data ├── Figure1_sc_metadata_Pancancer └── Figure2_sc_expression_GenomeWise frontend ``` - 再次进入项目 `frontend` 目录，执行 `npm run start` 启动服务 - 通过`${process.env.VUE_APP_API_BASE_URL}`访问 ## 无Root权限 > 实测运行环境 > > - 5.14.0-362.24.1.el9_3.x86_64 > - Node.js v22.3.0 > - npm v10.8.1 - MongodDB通过`conda install mongodb`安装，通过`mongod --dbpath ~/db --port <port>`在tmux中运行，代码中的`<port>`为27018，如有需要须同步更改 - 在`import.js`中配置文件路径，运行进行导入 { "name": "backend", "version": "1.0.0", "lockfileVersion": 3, "requires": true, "packages": { "": { "name": "backend", "version": "1.0.0", "license": "ISC", "dependencies": { "compression": "^1.7.4", "cors": "^2.8.5", "csv-parse": "^5.5.6", "express": "^4.19.2", "mongoose": "^8.4.0", "xlsx": "^0.18.5" }, "devDependencies": { "morgan": "^1.10.0" } }, "node_modules/@mongodb-js/saslprep": { "version": "1.1.7", "resolved": "https://registry.npmjs.org/@mongodb-js/saslprep/-/saslprep-1.1.7.tgz", "integrity": "sha512-dCHW/oEX0KJ4NjDULBo3JiOaK5+6axtpBbS+ao2ZInoAL9/YRQLhXzSNAFz7hP4nzLkIqsfYAK/PDE3+XHny0Q==", "license": "MIT", "dependencies": { "sparse-bitfield": "^3.0.3" } }, "node_modules/@types/webidl-conversions": { "version": "7.0.3", "resolved": "https://registry.npmjs.org/@types/webidl-conversions/-/webidl-conversions-7.0.3.tgz", "integrity": "sha512-CiJJvcRtIgzadHCYXw7dqEnMNRjhGZlYK05Mj9OyktqV8uVT8fD2BFOB7S1uwBE3Kj2Z+4UyPmFw/Ixgw/LAlA==", "license": "MIT" }, "node_modules/@types/whatwg-url": { "version": "11.0.5", "resolved": "https://registry.npmjs.org/@types/whatwg-url/-/whatwg-url-11.0.5.tgz", "integrity": "sha512-coYR071JRaHa+xoEvvYqvnIHaVqaYrLPbsufM9BF63HkwI5Lgmy2QR8Q5K/lYDYo5AK82wOvSOS0UsLTpTG7uQ==", "license": "MIT", "dependencies": { "@types/webidl-conversions": "*" } }, "node_modules/accepts": { "version": "1.3.8", "resolved": "https://registry.npmjs.org/accepts/-/accepts-1.3.8.tgz", "integrity": "sha512-PYAthTa2m2VKxuvSD3DPC/Gy+U+sOA1LAuT8mkmRuvw+NACSaeXEQ+NHcVF7rONl6qcaxV3Uuemwawk+7+SJLw==", "license": "MIT", "dependencies": { "mime-types": "~2.1.34", "negotiator": "0.6.3" }, "engines": { "node": ">= 0.6" } }, "node_modules/adler-32": { "version": "1.3.1", "resolved": "https://registry.npmjs.org/adler-32/-/adler-32-1.3.1.tgz", "integrity": "sha512-ynZ4w/nUUv5rrsR8UUGoe1VC9hZj6V5hU9Qw1HlMDJGEJw5S7TfTErWTjMys6M7vr0YWcPqs3qAr4ss0nDfP+A==", "license": "Apache-2.0", "engines": { "node": ">=0.8" } }, "node_modules/array-flatten": { "version": "1.1.1", "resolved": "https://registry.npmjs.org/array-flatten/-/array-flatten-1.1.1.tgz", "integrity": "sha512-PCVAQswWemu6UdxsDFFX/+gVeYqKAod3D3UVm91jHwynguOwAvYPhx8nNlM++NqRcK6CxxpUafjmhIdKiHibqg==", "license": "MIT" }, "node_modules/basic-auth": { "version": "2.0.1", "resolved": "https://registry.npmjs.org/basic-auth/-/basic-auth-2.0.1.tgz", "integrity": "sha512-NF+epuEdnUYVlGuhaxbbq+dvJttwLnGY+YixlXlME5KpQ5W3CnXA5cVTneY3SPbPDRkcjMbifrwmFYcClgOZeg==", "dev": true, "license": "MIT", "dependencies": { "safe-buffer": "5.1.2" }, "engines": { "node": ">= 0.8" } }, "node_modules/basic-auth/node_modules/safe-buffer": { "version": "5.1.2", "resolved": "https://registry.npmjs.org/safe-buffer/-/safe-buffer-5.1.2.tgz", "integrity": "sha512-Gd2UZBJDkXlY7GbJxfsE8/nvKkUEU1G38c1siN6QP6a9PT9MmHB8GnpscSmMJSoF8LOIrt8ud/wPtojys4G6+g==", "dev": true, "license": "dev truedevdev "":": { ":", "resolved": "devlicense":" license":":":":":", "", "": ".t "":":ifyaverseansi/array-utils", -utils-utils2", casecase /core5 5 itespace-initial /schema-file-path domain path index configurations change projetFormat responseinsert answer)".
322
null
0
A
A. The /api/ is used as a proxy rather than router. The keyword is mutable subject to specific proxy settings, like that of nginx.
Please read the following text and answer the question below. <text> { "name": "PreAtlas", "lockfileVersion": 3, "requires": true, "packages": {} } # PreAtlas ## 部署方法 ### 有Root权限 > 实测运行环境 > > - Debian 6.7.9-2 (2024-03-13) x86_64 GNU/Linux > - Node.js v21.6.1 > - npm v10.5.0 - 确保安装了 `nodejs`, `npm` 和 MongoDB 数据库（Linux上的`mongod`包） - 启动MongDB服务，如使用`systemctl start mongod` - 进入项目 `frontend` 和 `backend` 目录，分别执行 `npm install` 安装依赖 - 进入项目 `frontend` 目录，执行 `npm run start` 启动服务，这等价于在 `frontend` 目录下执行 `npm run serve` 并在 `backend` 目录下执行 `node index.js` - 将所需要的数据导入到 MongoDB 数据库已经创建的 `myNewDatabase`下，表名称即为对应的文件名去掉后缀，具体需要的数据表为Figure1_sc_metadata_Pancancer下的全体tsv，即各个数据集的元数据 可使用的工具为 [MongoDB Compass](https://www.mongodb.com/try/download/compass) - 配置`data`路径，至少包括： ```bash backend data ├── Figure1_sc_metadata_Pancancer └── Figure2_sc_expression_GenomeWise frontend ``` - 再次进入项目 `frontend` 目录，执行 `npm run start` 启动服务 - 通过`${process.env.VUE_APP_API_BASE_URL}`访问 ## 无Root权限 > 实测运行环境 > > - 5.14.0-362.24.1.el9_3.x86_64 > - Node.js v22.3.0 > - npm v10.8.1 - MongodDB通过`conda install mongodb`安装，通过`mongod --dbpath ~/db --port <port>`在tmux中运行，代码中的`<port>`为27018，如有需要须同步更改 - 在`import.js`中配置文件路径，运行进行导入 { "name": "backend", "version": "1.0.0", "lockfileVersion": 3, "requires": true, "packages": { "": { "name": "backend", "version": "1.0.0", "license": "ISC", "dependencies": { "compression": "^1.7.4", "cors": "^2.8.5", "csv-parse": "^5.5.6", "express": "^4.19.2", "mongoose": "^8.4.0", "xlsx": "^0.18.5" }, "devDependencies": { "morgan": "^1.10.0" } }, "node_modules/@mongodb-js/saslprep": { "version": "1.1.7", "resolved": "https://registry.npmjs.org/@mongodb-js/saslprep/-/saslprep-1.1.7.tgz", "integrity": "sha512-dCHW/oEX0KJ4NjDULBo3JiOaK5+6axtpBbS+ao2ZInoAL9/YRQLhXzSNAFz7hP4nzLkIqsfYAK/PDE3+XHny0Q==", "license": "MIT", "dependencies": { "sparse-bitfield": "^3.0.3" } }, "node_modules/@types/webidl-conversions": { "version": "7.0.3", "resolved": "https://registry.npmjs.org/@types/webidl-conversions/-/webidl-conversions-7.0.3.tgz", "integrity": "sha512-CiJJvcRtIgzadHCYXw7dqEnMNRjhGZlYK05Mj9OyktqV8uVT8fD2BFOB7S1uwBE3Kj2Z+4UyPmFw/Ixgw/LAlA==", "license": "MIT" }, "node_modules/@types/whatwg-url": { "version": "11.0.5", "resolved": "https://registry.npmjs.org/@types/whatwg-url/-/whatwg-url-11.0.5.tgz", "integrity": "sha512-coYR071JRaHa+xoEvvYqvnIHaVqaYrLPbsufM9BF63HkwI5Lgmy2QR8Q5K/lYDYo5AK82wOvSOS0UsLTpTG7uQ==", "license": "MIT", "dependencies": { "@types/webidl-conversions": "*" } }, "node_modules/accepts": { "version": "1.3.8", "resolved": "https://registry.npmjs.org/accepts/-/accepts-1.3.8.tgz", "integrity": "sha512-PYAthTa2m2VKxuvSD3DPC/Gy+U+sOA1LAuT8mkmRuvw+NACSaeXEQ+NHcVF7rONl6qcaxV3Uuemwawk+7+SJLw==", "license": "MIT", "dependencies": { "mime-types": "~2.1.34", "negotiator": "0.6.3" }, "engines": { "node": ">= 0.6" } }, "node_modules/adler-32": { "version": "1.3.1", "resolved": "https://registry.npmjs.org/adler-32/-/adler-32-1.3.1.tgz", "integrity": "sha512-ynZ4w/nUUv5rrsR8UUGoe1VC9hZj6V5hU9Qw1HlMDJGEJw5S7TfTErWTjMys6M7vr0YWcPqs3qAr4ss0nDfP+A==", "license": "Apache-2.0", "engines": { "node": ">=0.8" } }, "node_modules/array-flatten": { "version": "1.1.1", "resolved": "https://registry.npmjs.org/array-flatten/-/array-flatten-1.1.1.tgz", "integrity": "sha512-PCVAQswWemu6UdxsDFFX/+gVeYqKAod3D3UVm91jHwynguOwAvYPhx8nNlM++NqRcK6CxxpUafjmhIdKiHibqg==", "license": "MIT" }, "node_modules/basic-auth": { "version": "2.0.1", "resolved": "https://registry.npmjs.org/basic-auth/-/basic-auth-2.0.1.tgz", "integrity": "sha512-NF+epuEdnUYVlGuhaxbbq+dvJttwLnGY+YixlXlME5KpQ5W3CnXA5cVTneY3SPbPDRkcjMbifrwmFYcClgOZeg==", "dev": true, "license": "MIT", "dependencies": { "safe-buffer": "5.1.2" }, "engines": { "node": ">= 0.8" } }, "node_modules/basic-auth/node_modules/safe-buffer": { "version": "5.1.2", "resolved": "https://registry.npmjs.org/safe-buffer/-/safe-buffer-5.1.2.tgz", "integrity": "sha512-Gd2UZBJDkXlY7GbJxfsE8/nvKkUEU1G38c1siN6QP6a9PT9MmHB8GnpscSmMJSoF8LOIrt8ud/wPtojys4G6+g==", "dev": true, "license": "dev truedevdev "":": { ":", "resolved": "devlicense":" license":":":":":", "", "": ".t "":":ifyaverseansi/array-utils", -utils-utils2", casecase /core5 5 itespace-initial /schema-file-path domain path index configurations change projetFormat responseinsert answer)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> DynamiCrafter: Animating Open-domain Images with Video Diffusion Priors Abstract Animating a still image offers an engaging visual experi- ence. Traditional image animation techniques mainly focus on animating natural scenes with stochastic dynamics (e.g. clouds and fluid) or domain-specific motions (e.g. human hair or body motions), and thus limits their applicability to more general visual content. To overcome this limita- tion, we explore the synthesis of dynamic content for open- domain images, converting them into animated videos. The key idea is to utilize the motion prior of text-to-video dif- fusion models by incorporating the image into the genera- tive process as guidance. Given an image, we first project it into a text-aligned rich context representation space us- ing a query transformer, which facilitates the video model to digest the image content in a compatible fashion. How- ever, some visual details still struggle to be preserved in the resultant videos. To supplement with more precise image information, we further feed the full image to the diffusion model by concatenating it with the initial noises. Experi- mental results show that our proposed method can produce visually convincing and more logical & natural motions, as well as higher conformity to the input image. Comparative evaluation demonstrates the notable superiority of our ap- proach over existing competitors. 1. Introduction Image animation has been a longstanding challenge in the fields of computer vision, with the goal of converting still images into video counterparts that display natural dynam- ics while preserving the original appearance of the images. Traditional heuristic approaches primarily concentrate on synthesizing stochastic and oscillating motions [40, 42] or customizing for specific object categories [31, 37]. How- ever, the strong assumptions imposed on these methods limit their applicability in general scenarios, such as ani- mating open-domain images. Recently, text-to-video (T2V) * Corresponding Authors. generative models have achieved remarkable success in cre- ating diverse and vivid videos from textual prompts. This inspires us to investigate the potential of leveraging such powerful video generation capabilities for image animation. Our key idea is to govern the video generation process of T2V diffusion models by incorporating a conditional im- age. However, achieving the goal of image animation is still non-trivial, as it requires both visual context understanding (essential for creating dynamics) and detail preservation. Recent studies on multi-modal controllable video diffusion models, such as VideoComposer [77] and I2VGen-XL [12], have made preliminary attempts to enable video generation with visual guidance from an image. Unfortunately, both are incompetent for image animation due to their less com- prehensive image injection mechanisms, which results in ei- ther abrupt temporal changes or low visual conformity to the input image (see Figure 4). To address this challenge, we propose a dual-stream image injection paradigm, com- prised of text-aligned context representation and visual de- tail guidance, which ensures that the video diffusion model synthesizes detail-preserved dynamic content in a comple- mentary manner. We call this approach DynamiCrafter. Given an image, we first project it into the text-aligned rich context representation space through a specially de- signed context learning network. Specifically, it consists of a pre-trained CLIP image encoder to extract text-aligned image features and a learnable query transformer to fur- ther promote its adaptation to the diffusion models. The rich context features are used by the model via cross at- tention layers, which will then be combined with the text- conditioned features through gated fusion. In some extend, the learned context representation trades visual details with text alignment which helps facilitate semantic understand- ing of image context so that reasonable and vivid dynamics could be synthesized. To supplement more precise visual details, we further feed the full image to the diffusion model by concatenating it with the initial noise. This dual-stream injection paradigm guarantees both plausible dynamic con- tent and visual conformity to the input image. Extensive experiments are conducted to evaluate our 1 arXiv:2310.12190v2 [cs.CV] 27 Nov 2023 proposed method, which demonstrates notable superior- ity over existing competitors and even comparable perfor- mance with the latest commercial demos (like Gen-2 [11] and PikaLabs [13]). Furthermore, we offer discussion and analysis on some insightful designs for diffusion model based image animation, such as the roles of different visual injection streams, the utility of text prompts and their poten- tial for dynamics control, which may inspire follow-ups to push forward this line of technique. Besides of image ani- mation, DynamiCrafter can be easily adapted to support ap- plications like storytelling video generation, looping video generation, and generative frame interpolation. Our contri- butions are summarized as follows: • We introduce an innovative approach for animating open-domain images by leveraging video diffusion prior, significantly outperforming contemporary competitors. • We conduct a comprehensive analysis on the conditional space of text-to-video diffusion models and propose a dual-stream image injection paradigm to achieve the chal- lenging goal of image animation. • We pioneer the study of text-based motion control for open-domain image animation and demonstrate the proof of concept through preliminary experiments. 2. Related Work 2.1. Image Animation Generating animation from still images is a heavily stud- ied research area. Early physical simulation-based ap- proaches [10, 36] focus on simulating the motion of specific objects, resulting in low generalizability due to the indepen- dent modeling of each object category. To produce more re- alistic motion, reference-based methods [9, 37, 51, 55, 63– 65, 79] transfer motion or appearance information from ref- erence signals, such as videos, to the synthesis process. Although they demonstrate better temporal coherence, the need for additional guidances limits their practical applica- tion. Additionally, a stream of works based on GAN [26, 38, 60] can generate frames by perturbing initial latents or per- forming random walk in the latent vector space. However, the generated motion is not plausible since the animated frames are just a visualization of the possible appearance space without temporal awareness. Recently, (learned) mo- tion prior-based methods [16, 31, 34, 46, 49, 81, 82, 96] an- imate still images through explicit or implicit image-based rendering with estimated motion field or geometry priors. Similarly, video prediction [2, 18, 32, 33, 41, 74, 84, 86, 92] predicts future video frames starting from single images by learning spatio-temporal priors from video data. Although existing approaches has achieved impressive performance, they primarily focus on animating motions in curated domains, particularly stochastic [5, 10, 14, 16, 36, 40, 51, 87] and oscillating [42] motion. Furthermore, the animated objects are limited to specific categories, e.g., fluid [31, 31, 45, 51], natural scenes [9, 36, 42, 60, 84], hu- man hair [82], portraits [21, 78, 79], and bodies [4, 6, 37, 65, 79, 81]. In contrast, our work proposes a generic frame- work for animating open-domain images with a wide range of content and styles, which is extremely challenging due to the overwhelming complexity and vast diversity. 2.2. Video Diffusion Models Diffusion models (DMs) [28, 67] have recently shown un- precedented generative power in text-to-image (T2I) gener- ation [24, 50, 57–59, 95]. To replicate this success to video generation, the first video diffusion model (VDM) [30] is proposed to model low-resolution videos using a space- time factorized U-Net in pixel space. Imagen-Video [29] presents effective cascaded DMs with v-prediction for gen- erating high-definition videos. To reduce training costs, subsequent studies [7, 23, 76, 80, 97] are engaged in trans- ferring T2I to text-to-video (T2V) [20, 43, 66, 91], and learning VDMs in latent or hybrid-pixel-latent space. Although these models can generate high-quality videos, they only accept text prompts as the sole semantic guidance, which can be vague and 0raTable20X2XXX1XXXX2 Diff PPlease check 1 ra -XL Cra20 </text> What is the correct answer to this question: In the DynCra framework for,. Considering the which of following best explains nuanced? Choices: (A). (B). (C. (DCra.. Format your response as follows: "The correct answer is (insert answer here)".
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In DynamiCrafter, both the text-aligned context and visual detail guidance streams interact synergistically to ensure that temporal coherence and spatial fidelity are maintained throughout the video. The text-aligned context representation provides a high-level understanding of motion and scene structure, while the visual detail guidance compensates for any information loss during this process by embedding the image directly into the noise generation. This method avoids sacrificing either semantic understanding or fine details, ensuring both are preserved even when complex motions and scene changes occur.
Please read the following text and answer the question below. <text> DynamiCrafter: Animating Open-domain Images with Video Diffusion Priors Abstract Animating a still image offers an engaging visual experi- ence. Traditional image animation techniques mainly focus on animating natural scenes with stochastic dynamics (e.g. clouds and fluid) or domain-specific motions (e.g. human hair or body motions), and thus limits their applicability to more general visual content. To overcome this limita- tion, we explore the synthesis of dynamic content for open- domain images, converting them into animated videos. The key idea is to utilize the motion prior of text-to-video dif- fusion models by incorporating the image into the genera- tive process as guidance. Given an image, we first project it into a text-aligned rich context representation space us- ing a query transformer, which facilitates the video model to digest the image content in a compatible fashion. How- ever, some visual details still struggle to be preserved in the resultant videos. To supplement with more precise image information, we further feed the full image to the diffusion model by concatenating it with the initial noises. Experi- mental results show that our proposed method can produce visually convincing and more logical & natural motions, as well as higher conformity to the input image. Comparative evaluation demonstrates the notable superiority of our ap- proach over existing competitors. 1. Introduction Image animation has been a longstanding challenge in the fields of computer vision, with the goal of converting still images into video counterparts that display natural dynam- ics while preserving the original appearance of the images. Traditional heuristic approaches primarily concentrate on synthesizing stochastic and oscillating motions [40, 42] or customizing for specific object categories [31, 37]. How- ever, the strong assumptions imposed on these methods limit their applicability in general scenarios, such as ani- mating open-domain images. Recently, text-to-video (T2V) * Corresponding Authors. generative models have achieved remarkable success in cre- ating diverse and vivid videos from textual prompts. This inspires us to investigate the potential of leveraging such powerful video generation capabilities for image animation. Our key idea is to govern the video generation process of T2V diffusion models by incorporating a conditional im- age. However, achieving the goal of image animation is still non-trivial, as it requires both visual context understanding (essential for creating dynamics) and detail preservation. Recent studies on multi-modal controllable video diffusion models, such as VideoComposer [77] and I2VGen-XL [12], have made preliminary attempts to enable video generation with visual guidance from an image. Unfortunately, both are incompetent for image animation due to their less com- prehensive image injection mechanisms, which results in ei- ther abrupt temporal changes or low visual conformity to the input image (see Figure 4). To address this challenge, we propose a dual-stream image injection paradigm, com- prised of text-aligned context representation and visual de- tail guidance, which ensures that the video diffusion model synthesizes detail-preserved dynamic content in a comple- mentary manner. We call this approach DynamiCrafter. Given an image, we first project it into the text-aligned rich context representation space through a specially de- signed context learning network. Specifically, it consists of a pre-trained CLIP image encoder to extract text-aligned image features and a learnable query transformer to fur- ther promote its adaptation to the diffusion models. The rich context features are used by the model via cross at- tention layers, which will then be combined with the text- conditioned features through gated fusion. In some extend, the learned context representation trades visual details with text alignment which helps facilitate semantic understand- ing of image context so that reasonable and vivid dynamics could be synthesized. To supplement more precise visual details, we further feed the full image to the diffusion model by concatenating it with the initial noise. This dual-stream injection paradigm guarantees both plausible dynamic con- tent and visual conformity to the input image. Extensive experiments are conducted to evaluate our 1 arXiv:2310.12190v2 [cs.CV] 27 Nov 2023 proposed method, which demonstrates notable superior- ity over existing competitors and even comparable perfor- mance with the latest commercial demos (like Gen-2 [11] and PikaLabs [13]). Furthermore, we offer discussion and analysis on some insightful designs for diffusion model based image animation, such as the roles of different visual injection streams, the utility of text prompts and their poten- tial for dynamics control, which may inspire follow-ups to push forward this line of technique. Besides of image ani- mation, DynamiCrafter can be easily adapted to support ap- plications like storytelling video generation, looping video generation, and generative frame interpolation. Our contri- butions are summarized as follows: • We introduce an innovative approach for animating open-domain images by leveraging video diffusion prior, significantly outperforming contemporary competitors. • We conduct a comprehensive analysis on the conditional space of text-to-video diffusion models and propose a dual-stream image injection paradigm to achieve the chal- lenging goal of image animation. • We pioneer the study of text-based motion control for open-domain image animation and demonstrate the proof of concept through preliminary experiments. 2. Related Work 2.1. Image Animation Generating animation from still images is a heavily stud- ied research area. Early physical simulation-based ap- proaches [10, 36] focus on simulating the motion of specific objects, resulting in low generalizability due to the indepen- dent modeling of each object category. To produce more re- alistic motion, reference-based methods [9, 37, 51, 55, 63– 65, 79] transfer motion or appearance information from ref- erence signals, such as videos, to the synthesis process. Although they demonstrate better temporal coherence, the need for additional guidances limits their practical applica- tion. Additionally, a stream of works based on GAN [26, 38, 60] can generate frames by perturbing initial latents or per- forming random walk in the latent vector space. However, the generated motion is not plausible since the animated frames are just a visualization of the possible appearance space without temporal awareness. Recently, (learned) mo- tion prior-based methods [16, 31, 34, 46, 49, 81, 82, 96] an- imate still images through explicit or implicit image-based rendering with estimated motion field or geometry priors. Similarly, video prediction [2, 18, 32, 33, 41, 74, 84, 86, 92] predicts future video frames starting from single images by learning spatio-temporal priors from video data. Although existing approaches has achieved impressive performance, they primarily focus on animating motions in curated domains, particularly stochastic [5, 10, 14, 16, 36, 40, 51, 87] and oscillating [42] motion. Furthermore, the animated objects are limited to specific categories, e.g., fluid [31, 31, 45, 51], natural scenes [9, 36, 42, 60, 84], hu- man hair [82], portraits [21, 78, 79], and bodies [4, 6, 37, 65, 79, 81]. In contrast, our work proposes a generic frame- work for animating open-domain images with a wide range of content and styles, which is extremely challenging due to the overwhelming complexity and vast diversity. 2.2. Video Diffusion Models Diffusion models (DMs) [28, 67] have recently shown un- precedented generative power in text-to-image (T2I) gener- ation [24, 50, 57–59, 95]. To replicate this success to video generation, the first video diffusion model (VDM) [30] is proposed to model low-resolution videos using a space- time factorized U-Net in pixel space. Imagen-Video [29] presents effective cascaded DMs with v-prediction for gen- erating high-definition videos. To reduce training costs, subsequent studies [7, 23, 76, 80, 97] are engaged in trans- ferring T2I to text-to-video (T2V) [20, 43, 66, 91], and learning VDMs in latent or hybrid-pixel-latent space. Although these models can generate high-quality videos, they only accept text prompts as the sole semantic guidance, which can be vague and 0raTable20X2XXX1XXXX2 Diff PPlease check 1 ra -XL Cra20 </text> What is the correct answer to this question: In the DynCra framework for,. Considering the which of following best explains nuanced? Choices: (A). (B). (C. (DCra.. Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> AbbVie News Center An open-label, efficacy assessor-blinded study comparing SKYRIZI  (risankizumab) to Otezla  (apremilast) for the treatment of adult patients with moderate plaque psoriasis who were candidates for systemic therapy was published in the British Journal of Dermatology Significantly more patients in the study achieved co-primary endpoints of PASI 90 and sPGA 0/1 at Week 16 with risankizumab versus apremilast In apremilast patients not achieving PASI 75 at Week 16, significantly more achieved the primary endpoint of PASI 90 at Week 52 who were re-randomized to risankizumab versus continued with apremilast Based on TSQM-9, higher treatment satisfaction domain scores were reported at Week 16 for patients taking risankizumab (nominal p-values versus apremilast) Risankizumab was well-tolerated with no new safety signals identified NORTH CHICAGO, Ill., July 26, 2023 /PRNewswire/ -- AbbVie (NYSE: ABBV) today announced the British Journal of Dermatology published results from the head-to-head Phase 4 IMMpulse study that evaluated the efficacy and safety of SKYRIZI  (risankizumab) compared to Otezla  (apremilast) among adult patients with moderate plaque psoriasis eligible for systemic therapy.  This study achieved all primary and ranked secondary endpoints with no new safety signals identified. "This study highlights the efficacy of SKYRIZI compared to Otezla in helping systemic-eligible patients achieve high levels of skin clearance and reinforces the safety profile observed in previous studies," said Mudra Kapoor, M.D., vice president, global medical affairs, immunology, AbbVie. "These head-to-head data are crucial to help patients and their doctors make informed treatment decisions for uncontrolled disease and add to the body of evidence supporting SKYRIZI as a treatment option for adults living with moderate psoriasis." Highlights from this open-label, efficacy assessor-blinded study include: At Week 16, a significantly higher proportion of patients who received risankizumab achieved the Period A co-primary endpoints of Psoriasis Area and Severity Index (PASI) 90 and Static Physician's Global Assessment (sPGA) 0/1 [55.9% (66/118) of patients achieved PASI 90 and 75.4% (89/118) achieved sPGA 0/1 with risankizumab versus 5.1% (12/234) and 18.4% (43/234) with apremilast; both with P<0.001]. The proportion of patients achieving the ranked secondary endpoint of PASI 75 at Week 16 was also significantly higher in risankizumab- versus apremilast-treated patients [84.7% (100/118) versus 18.8% (44/234) respectively; P<0.001]. At Week 52, among patients who failed to achieve PASI 75 after 16 weeks of treatment with apremilast, a significantly higher proportion of patients re-randomized to treatment with risankizumab achieved the Period B primary endpoint of PASI 90 as compared to those re-assigned to continue treatment with apremilast [72.3% (60/83) versus 2.6% (2/78); P<0.001]. After 52 weeks of continuous treatment, 73.7% of risankizumab patients achieved the pre-specified endpoints of PASI 90 and 63.6% PASI 100, with 4.5% and 2.7% of apremilast patients achieving PASI 90 and PASI 100 at Week 52, respectively (nominal p-value <0.001 for both comparisons). The safety profile for risankizumab in this study was consistent with previously reported studies; it was well-tolerated with no new safety signals identified.  The most frequent adverse events (reported in ≥5%) in risankizumab-treated patients were COVID-19, nasopharyngitis and upper respiratory tract infection.  Diarrhea, nausea and headache were most frequent among apremilast-treated patients.  Serious adverse events were reported in 0.8% and 2.9% of risankizumab-treated patients and 1.7% and 2.1% of apremilast- treated patients in Periods A and B, respectively. During Period A and Period B among the re-randomization arms, 6.8% and 5.2% of apremilast-treated patients discontinued treatment due to an adverse event, respectively, while no patient discontinued on risankizumab; on the continuous risankizumab arm, one patient discontinued due to an adverse event. "As a physician, it's crucial to validate different options that can achieve high treatment targets, and this study provides practice-relevant data," said lead study investigator, Linda Stein Gold, M.D., director of clinical research, department of dermatology, Henry Ford Health System. "These data reinforce the efficacy of SKYRIZI for use in systemic-eligible moderate psoriasis patients with an observed safety profile similar to prior studies." Based on analyses of the Treatment Satisfaction Questionnaire for Medication version 9 (TSQM-9), which were pre-specified unranked endpoints, risankizumab-treated patients reported greater treatment satisfaction at Week 16, with higher scores (out of 100) in all three domains of satisfaction with effectiveness (80.6), satisfaction with convenience (84.9) and global satisfaction (86.2) compared to apremilast-treated patients (46.9, 69.0 and 47.7, respectively; nominal p-value <0.001 for all comparisons). SKYRIZI is part of a collaboration between Boehringer Ingelheim and AbbVie, with AbbVie leading development and commercialization globally. About Psoriasis Psoriasis is a chronic, immune-mediated, inflammatory skin condition that produces thickened, scaling skin due to rapid growth of skin cells.  It affects around 2-3% of people worldwide.  People with psoriasis also experience a significant emotional, psychological and social burden that can negatively impact their quality of life. About IMMpulse Study IMMpulse is a Phase 4, global, multicenter, randomized, open-label, efficacy assessor-blinded, active comparator study examining the effect of risankizumab (150 mg X 1 s.c at wk0, wk4, wk16, wk28, wk40) compared to apremilast (30 mg BID oral following titration) in adults with moderate plaque psoriasis who are candidates for systemic therapy. Patients must have stable moderate psoriasis at both screening and baseline, defined as: 1) BSA ≥10% and ≤15%; 2) PASI ≥12; 3) sPGA =3 (moderate) to enter the study. The study design comprised a screening period of up to 35 days, a 52-week treatment period and a follow-up phone call for safety. The 52-week treatment duration included two periods: Period A from Weeks 0 to 16, which evaluated the superiority of risankizumab over apremilast, andPlease the: 22  ForH2 R RR PreRza 0 col IZi00 RNPR color the mostRRRRR Y4RRRRRRRRRcolRRR largeR sw g sy do-csharR6R The-. other liquids healthcare providerRR6RIZ6R1Abb 121R col theR lR SKRRRRRRX12References:  .22  Abb col R RRRPlease I12111222      Abb ankRR col IVForward,121  References .222111211112.   SOURCE Abb For further information:abb https.2 </text> What is the correct answer to this question: Based on the press release about Abbie's product SKYRIZI, how do you know about its indication? Choices: (A) SKYRI is primarily indicated treatment moderate-to-severe,’s col patients, with being for Cro. (B) AlternativesR etc. (C) When reporting theYR Ul United States, Abb mentioned SKR “ rem”. However the reports of provided. (D) In clinicalYR, researchers conducted four multic, with the number participants exceeding 1,000 in study. Format your response as follows: "The correct answer is (insert answer here)".
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2
C
When reporting the approval of SKYRIZI for the treatment of Ulcerative Colitis in Europe and the United States, AbbVie mentioned that SKYRIZI achieved the primary endpoint of “clinical remission” and the key secondary endpoint of “endoscopic improvement” in clinical studies. However, the news reports of the European approval provided a more detailed explanation.
Please read the following text and answer the question below. <text> AbbVie News Center An open-label, efficacy assessor-blinded study comparing SKYRIZI  (risankizumab) to Otezla  (apremilast) for the treatment of adult patients with moderate plaque psoriasis who were candidates for systemic therapy was published in the British Journal of Dermatology Significantly more patients in the study achieved co-primary endpoints of PASI 90 and sPGA 0/1 at Week 16 with risankizumab versus apremilast In apremilast patients not achieving PASI 75 at Week 16, significantly more achieved the primary endpoint of PASI 90 at Week 52 who were re-randomized to risankizumab versus continued with apremilast Based on TSQM-9, higher treatment satisfaction domain scores were reported at Week 16 for patients taking risankizumab (nominal p-values versus apremilast) Risankizumab was well-tolerated with no new safety signals identified NORTH CHICAGO, Ill., July 26, 2023 /PRNewswire/ -- AbbVie (NYSE: ABBV) today announced the British Journal of Dermatology published results from the head-to-head Phase 4 IMMpulse study that evaluated the efficacy and safety of SKYRIZI  (risankizumab) compared to Otezla  (apremilast) among adult patients with moderate plaque psoriasis eligible for systemic therapy.  This study achieved all primary and ranked secondary endpoints with no new safety signals identified. "This study highlights the efficacy of SKYRIZI compared to Otezla in helping systemic-eligible patients achieve high levels of skin clearance and reinforces the safety profile observed in previous studies," said Mudra Kapoor, M.D., vice president, global medical affairs, immunology, AbbVie. "These head-to-head data are crucial to help patients and their doctors make informed treatment decisions for uncontrolled disease and add to the body of evidence supporting SKYRIZI as a treatment option for adults living with moderate psoriasis." Highlights from this open-label, efficacy assessor-blinded study include: At Week 16, a significantly higher proportion of patients who received risankizumab achieved the Period A co-primary endpoints of Psoriasis Area and Severity Index (PASI) 90 and Static Physician's Global Assessment (sPGA) 0/1 [55.9% (66/118) of patients achieved PASI 90 and 75.4% (89/118) achieved sPGA 0/1 with risankizumab versus 5.1% (12/234) and 18.4% (43/234) with apremilast; both with P<0.001]. The proportion of patients achieving the ranked secondary endpoint of PASI 75 at Week 16 was also significantly higher in risankizumab- versus apremilast-treated patients [84.7% (100/118) versus 18.8% (44/234) respectively; P<0.001]. At Week 52, among patients who failed to achieve PASI 75 after 16 weeks of treatment with apremilast, a significantly higher proportion of patients re-randomized to treatment with risankizumab achieved the Period B primary endpoint of PASI 90 as compared to those re-assigned to continue treatment with apremilast [72.3% (60/83) versus 2.6% (2/78); P<0.001]. After 52 weeks of continuous treatment, 73.7% of risankizumab patients achieved the pre-specified endpoints of PASI 90 and 63.6% PASI 100, with 4.5% and 2.7% of apremilast patients achieving PASI 90 and PASI 100 at Week 52, respectively (nominal p-value <0.001 for both comparisons). The safety profile for risankizumab in this study was consistent with previously reported studies; it was well-tolerated with no new safety signals identified.  The most frequent adverse events (reported in ≥5%) in risankizumab-treated patients were COVID-19, nasopharyngitis and upper respiratory tract infection.  Diarrhea, nausea and headache were most frequent among apremilast-treated patients.  Serious adverse events were reported in 0.8% and 2.9% of risankizumab-treated patients and 1.7% and 2.1% of apremilast- treated patients in Periods A and B, respectively. During Period A and Period B among the re-randomization arms, 6.8% and 5.2% of apremilast-treated patients discontinued treatment due to an adverse event, respectively, while no patient discontinued on risankizumab; on the continuous risankizumab arm, one patient discontinued due to an adverse event. "As a physician, it's crucial to validate different options that can achieve high treatment targets, and this study provides practice-relevant data," said lead study investigator, Linda Stein Gold, M.D., director of clinical research, department of dermatology, Henry Ford Health System. "These data reinforce the efficacy of SKYRIZI for use in systemic-eligible moderate psoriasis patients with an observed safety profile similar to prior studies." Based on analyses of the Treatment Satisfaction Questionnaire for Medication version 9 (TSQM-9), which were pre-specified unranked endpoints, risankizumab-treated patients reported greater treatment satisfaction at Week 16, with higher scores (out of 100) in all three domains of satisfaction with effectiveness (80.6), satisfaction with convenience (84.9) and global satisfaction (86.2) compared to apremilast-treated patients (46.9, 69.0 and 47.7, respectively; nominal p-value <0.001 for all comparisons). SKYRIZI is part of a collaboration between Boehringer Ingelheim and AbbVie, with AbbVie leading development and commercialization globally. About Psoriasis Psoriasis is a chronic, immune-mediated, inflammatory skin condition that produces thickened, scaling skin due to rapid growth of skin cells.  It affects around 2-3% of people worldwide.  People with psoriasis also experience a significant emotional, psychological and social burden that can negatively impact their quality of life. About IMMpulse Study IMMpulse is a Phase 4, global, multicenter, randomized, open-label, efficacy assessor-blinded, active comparator study examining the effect of risankizumab (150 mg X 1 s.c at wk0, wk4, wk16, wk28, wk40) compared to apremilast (30 mg BID oral following titration) in adults with moderate plaque psoriasis who are candidates for systemic therapy. Patients must have stable moderate psoriasis at both screening and baseline, defined as: 1) BSA ≥10% and ≤15%; 2) PASI ≥12; 3) sPGA =3 (moderate) to enter the study. The study design comprised a screening period of up to 35 days, a 52-week treatment period and a follow-up phone call for safety. The 52-week treatment duration included two periods: Period A from Weeks 0 to 16, which evaluated the superiority of risankizumab over apremilast, andPlease the: 22  ForH2 R RR PreRza 0 col IZi00 RNPR color the mostRRRRR Y4RRRRRRRRRcolRRR largeR sw g sy do-csharR6R The-. other liquids healthcare providerRR6RIZ6R1Abb 121R col theR lR SKRRRRRRX12References:  .22  Abb col R RRRPlease I12111222      Abb ankRR col IVForward,121  References .222111211112.   SOURCE Abb For further information:abb https.2 </text> What is the correct answer to this question: Based on the press release about Abbie's product SKYRIZI, how do you know about its indication? Choices: (A) SKYRI is primarily indicated treatment moderate-to-severe,’s col patients, with being for Cro. (B) AlternativesR etc. (C) When reporting theYR Ul United States, Abb mentioned SKR “ rem”. However the reports of provided. (D) In clinicalYR, researchers conducted four multic, with the number participants exceeding 1,000 in study. Format your response as follows: "The correct answer is (insert answer here)".
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Please read the following text and answer the question below. <text> { "question_id": "e25c3b8d", "question_type": "multi-session", "question": "", "answer": "", "question_date": "2023/05/30 (Tue) 15:02", "haystack_dates": [ "2023/05/20 (Sat) 01:57", "2023/05/20 (Sat) 05:12", "2023/05/20 (Sat) 07:41", "2023/05/20 (Sat) 17:25", "2023/05/20 (Sat) 18:05", "2023/05/20 (Sat) 23:38", "2023/05/21 (Sun) 00:42", "2023/05/21 (Sun) 14:26", "2023/05/21 (Sun) 20:23", "2023/05/21 (Sun) 20:43", "2023/05/21 (Sun) 21:37", "2023/05/21 (Sun) 23:54", "2023/05/22 (Mon) 04:47", "2023/05/22 (Mon) 07:38", "2023/05/22 (Mon) 08:18", "2023/05/22 (Mon) 09:22", "2023/05/23 (Tue) 07:40", "2023/05/23 (Tue) 22:29", "2023/05/24 (Wed) 01:08", "2023/05/24 (Wed) 01:34", "2023/05/24 (Wed) 01:58", "2023/05/24 (Wed) 06:05", "2023/05/24 (Wed) 07:05", "2023/05/24 (Wed) 10:45", "2023/05/24 (Wed) 10:58", "2023/05/24 (Wed) 18:36", "2023/05/24 (Wed) 19:23", "2023/05/25 (Thu) 03:32", "2023/05/25 (Thu) 06:35", "2023/05/25 (Thu) 09:56", "2023/05/25 (Thu) 22:38", "2023/05/26 (Fri) 06:27", "2023/05/26 (Fri) 06:31", "2023/05/26 (Fri) 07:57", "2023/05/26 (Fri) 09:27", "2023/05/26 (Fri) 18:34", "2023/05/27 (Sat) 20:03", "2023/05/27 (Sat) 23:38", "2023/05/28 (Sun) 04:17", "2023/05/28 (Sun) 08:43", "2023/05/28 (Sun) 09:38", "2023/05/28 (Sun) 12:41", "2023/05/29 (Mon) 02:02", "2023/05/29 (Mon) 09:41", "2023/05/29 (Mon) 13:31", "2023/05/29 (Mon) 16:08", "2023/05/29 (Mon) 19:20", "2023/05/29 (Mon) 20:11", "2023/05/30 (Tue) 01:09", "2023/05/30 (Tue) 01:59", "2023/05/30 (Tue) 05:58" ], "haystack_session_ids": [ "4df51052", "sharegpt_Wu1Rdjk_0", "606d0c4a_1", "f3a57240", "c51a7155", "ultrachat_363088", "8cc6894a", "ultrachat_330547", "ultrachat_50698", "sharegpt_lR0Y6tk_7", "sharegpt_gQaSoiF_13", "answer_6702277b_1", "ultrachat_77840", "sharegpt_40qcQLS_17", "sharegpt_dxVceiP_29", "746d0c00_1", "643fb852_1", "sharegpt_6VqlSoL_25", "sharegpt_WYQSZ3n_0", "sharegpt_Ye8MhZY_0", "answer_6702277b_2", "20fa75e8_3", "4256f981_2", "sharegpt_rtgucSC_0", "3895033a_1", "cb9a516e_1", "824634d9_1", "c04c626c_1", "ultrachat_231771", "5237d8c6", "sharegpt_Nk10TjE_29", "ultrachat_201413", "sharegpt_DdJZrTY_7", "35b030f3_2", "ultrachat_95506", "sharegpt_fPEmgpq_1", "sharegpt_RA4MDuA_0", "f298e96f_1", "099c1b6c_3", "ff687a63_2", "sharegpt_M6a9zYJ_0", "1ccb08a0", "ultrachat_216372", "92780636_1", "ff201786_1", "ca66a8ee_1", "ultrachat_309688", "90fea364_1", "sharegpt_ErOTMZ3_181", "ba80721c", "sharegpt_IuLT3VI_9" ], "haystack_sessions": [ [ { "role": "user", "content": "I'm feeling overwhelmed and struggling to prioritize tasks. Can you help me create a to-do list and suggest some time management strategies?" }, { 1nn pests Can " ", thanks. way that }, { assistant": "In have to }, " some trouble Do": "n Can Can "do thinkcontinueUsing " "As not." }, "As, is." { "Yes, are " break iny!" [ -to ], } </text> What the correct answer to: Which of? Choices: (A user F- (B (C (D the Format your response as follows: "The correct answer is (insert answer here)".
325
null
2
C
the user felt overwhelmed with work projects
Please read the following text and answer the question below. <text> { "question_id": "e25c3b8d", "question_type": "multi-session", "question": "", "answer": "", "question_date": "2023/05/30 (Tue) 15:02", "haystack_dates": [ "2023/05/20 (Sat) 01:57", "2023/05/20 (Sat) 05:12", "2023/05/20 (Sat) 07:41", "2023/05/20 (Sat) 17:25", "2023/05/20 (Sat) 18:05", "2023/05/20 (Sat) 23:38", "2023/05/21 (Sun) 00:42", "2023/05/21 (Sun) 14:26", "2023/05/21 (Sun) 20:23", "2023/05/21 (Sun) 20:43", "2023/05/21 (Sun) 21:37", "2023/05/21 (Sun) 23:54", "2023/05/22 (Mon) 04:47", "2023/05/22 (Mon) 07:38", "2023/05/22 (Mon) 08:18", "2023/05/22 (Mon) 09:22", "2023/05/23 (Tue) 07:40", "2023/05/23 (Tue) 22:29", "2023/05/24 (Wed) 01:08", "2023/05/24 (Wed) 01:34", "2023/05/24 (Wed) 01:58", "2023/05/24 (Wed) 06:05", "2023/05/24 (Wed) 07:05", "2023/05/24 (Wed) 10:45", "2023/05/24 (Wed) 10:58", "2023/05/24 (Wed) 18:36", "2023/05/24 (Wed) 19:23", "2023/05/25 (Thu) 03:32", "2023/05/25 (Thu) 06:35", "2023/05/25 (Thu) 09:56", "2023/05/25 (Thu) 22:38", "2023/05/26 (Fri) 06:27", "2023/05/26 (Fri) 06:31", "2023/05/26 (Fri) 07:57", "2023/05/26 (Fri) 09:27", "2023/05/26 (Fri) 18:34", "2023/05/27 (Sat) 20:03", "2023/05/27 (Sat) 23:38", "2023/05/28 (Sun) 04:17", "2023/05/28 (Sun) 08:43", "2023/05/28 (Sun) 09:38", "2023/05/28 (Sun) 12:41", "2023/05/29 (Mon) 02:02", "2023/05/29 (Mon) 09:41", "2023/05/29 (Mon) 13:31", "2023/05/29 (Mon) 16:08", "2023/05/29 (Mon) 19:20", "2023/05/29 (Mon) 20:11", "2023/05/30 (Tue) 01:09", "2023/05/30 (Tue) 01:59", "2023/05/30 (Tue) 05:58" ], "haystack_session_ids": [ "4df51052", "sharegpt_Wu1Rdjk_0", "606d0c4a_1", "f3a57240", "c51a7155", "ultrachat_363088", "8cc6894a", "ultrachat_330547", "ultrachat_50698", "sharegpt_lR0Y6tk_7", "sharegpt_gQaSoiF_13", "answer_6702277b_1", "ultrachat_77840", "sharegpt_40qcQLS_17", "sharegpt_dxVceiP_29", "746d0c00_1", "643fb852_1", "sharegpt_6VqlSoL_25", "sharegpt_WYQSZ3n_0", "sharegpt_Ye8MhZY_0", "answer_6702277b_2", "20fa75e8_3", "4256f981_2", "sharegpt_rtgucSC_0", "3895033a_1", "cb9a516e_1", "824634d9_1", "c04c626c_1", "ultrachat_231771", "5237d8c6", "sharegpt_Nk10TjE_29", "ultrachat_201413", "sharegpt_DdJZrTY_7", "35b030f3_2", "ultrachat_95506", "sharegpt_fPEmgpq_1", "sharegpt_RA4MDuA_0", "f298e96f_1", "099c1b6c_3", "ff687a63_2", "sharegpt_M6a9zYJ_0", "1ccb08a0", "ultrachat_216372", "92780636_1", "ff201786_1", "ca66a8ee_1", "ultrachat_309688", "90fea364_1", "sharegpt_ErOTMZ3_181", "ba80721c", "sharegpt_IuLT3VI_9" ], "haystack_sessions": [ [ { "role": "user", "content": "I'm feeling overwhelmed and struggling to prioritize tasks. Can you help me create a to-do list and suggest some time management strategies?" }, { 1nn pests Can " ", thanks. way that }, { assistant": "In have to }, " some trouble Do": "n Can Can "do thinkcontinueUsing " "As not." }, "As, is." { "Yes, are " break iny!" [ -to ], } </text> What the correct answer to: Which of? Choices: (A user F- (B (C (D the Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> Chronic Absenteeism and Disrupted Learning Require an All-Hands-on-Deck Approach K-12 absenteeism has increased since the onset of COVID-19 and has contributed to falling test scores. Improving engagement is key for student success and the broader economy. Policies promoting strong schools and academic success impact students’ lives as adults, long after they leave the classroom. Beyond the significance for individuals, the educational development of our children and young people is a key input into the economy and has spillover benefits to society more broadly.  While the evidence is clear that students and society benefit from attending well-resourced schools with effective teachers, these benefits can only materialize if students are present and engaged.  A necessary step to ensure students benefit from all that schools have to offer is to support students’ consistent presence in the classroom—which is why the Biden-Harris Administration is focused on the issue of chronic absenteeism. In the aftermath of the COVID-19 pandemic, one study found that the number of public school students who are chronically absent—meaning they miss at least 10 percent of days in a school year, whether excused or unexcused—has nearly doubled, from about 15 percent in the 2018-2019 school year to around 30 percent in 2021-2022.[1] These large increases in absenteeism are widespread: every state for which data were available in this study saw significant increases in rates of chronic absenteeism between the 2018-2019 and 2021-2022 school years. Disparities in levels of chronic absenteeism across racial, ethnic, and socioeconomic lines also widened. Research shows that school absences take a toll on grades and performance on standardized tests. Beyond test scores, irregular attendance can be a predictor of high school drop-out, which has been linked to poor labor market prospects, diminished health, and increased involvement in the criminal justice system. Students who are chronically absent are at higher risk for these adverse outcomes. The increases in chronic absenteeism are large enough that they could be a substantial contributor to declines in post-pandemic test scores. (While test scores are not the only important aspect of student success, they provide a measurable early indicator that is predictive of broader long-term outcomes.)  To examine this question, the Council of Economic Advisers partnered with the National Center for Education Statistics (NCES) to analyze national data which includes measures of both standardized test scores and absenteeism during the 2018-2019 and 2021-2022 school years.[2] Using regression analysis to document the strong association between absenteeism and test scores (after controlling for other factors), we then implement a decomposition analysis to simulate how much of the decline in test scores could be attributed to increases in absenteeism.[3] Figure 1 illustrates the results of this descriptive analysis. The vertical bars indicate the average decline in scores between 2019 and 2022, by subject and grade level. The green portions of each bar indicate how much smaller these declines might be if absenteeism had not increased at all. We find that, even after controlling for changes in other characteristics of the student body over time, the observed association between absenteeism and test scores is large enough to account for 16-27 percent of the overall test score declines in math, and 36-45 percent of the declines in reading. These results come with several caveats: most importantly, we do not yet know the extent to which the recent increase in absenteeism is a stand-alone, causal contributor to test score declines, and to what extent it is a symptom of other factors that could account for both the increases in student absenteeism and declines in performance. Such factors could include declining mental and physical health, familial responsibilities, or other demands on students’ mental and physical resources. Given the magnitude of test score declines and extent of chronic absenteeism, pandemic recovery efforts require an “all-hands-on-deck” response.  While State-administered test scores from the 2021-2022 and 2022-2023 school years show some early signs of rebounding from the major disruptions of the pandemic, estimates suggest the average elementary school student would need sufficient supports and instructional time to sustain additional gains for several years in order to reach the performance of comparable pre-COVID cohorts. Without such sustained investments, one group of researchers estimated that these disruptions could cost American students $2 trillion in lifetime earnings. Ensuring that all students benefit from the full scope of pandemic recovery efforts requires that they are present in schools. Targeted interventions such as early warning systems, mailing outreach, and text nudges have shown promise in increasing attendance, especially among students who would have otherwise have been chronically absent from school. Research on the potential benefits of high-dosage tutoring and other evidence-based interventions implemented in afterschool programs or summer school can help educators and school leaders create a network of supports that best address student needs. The Biden-Harris Administration has undertaken significant efforts to combat chronic absenteeism and make sure that students are in the classroom and engaged in school. This includes: disseminating grant funds that can resource interventions and supports; offering technical assistance to States and districts; investing in comprehensive mental health programs for students; and establishing and strengthening the National Partnership for Student Success, which marshals evidence-backed supports such as tutoring and mentoring to help keep students engaged and on-track. Additionally, States have until next school year to use remaining Elementary and Secondary School Emergency Relief funds set aside for P-12 schools in the American Rescue Plan that can be used towards academic recovery, school attendance and engagement, and other efforts. Making up for lost time and learning disruption means empowering students and their families to take an active role in their academic recovery, and tracking and addressing chronic absenteeism will be an important aspect of these recovery efforts in the months and years to come. Ultimately, whether chronic absenteeism is a symptom or a cause—or both—of ongoing academic disruption, the evidence is clear that the road to recovery runs through the classroom. [1] These chronic absenteeism rates come from an academic study that collected administrative data from 40 states (and the District of Columbia), accounting for over 92 percent of K-12 public school students in the United States. [2] We analyze student level test scores from the National Assessment of Student Progress (NAEP) in this analysis. NAEP, also known as the “Nation’s Report Card,” is the largest nationally representative and continuing assessment of student learning. The absenteeism measure in NAEP is self-reported by students and reflects days missed over the past month. While the levels of absenteeism are measured differently than in administrative records, the increases over time are similarly large. [3] The analysis is a type of non-causal, Oaxaca-Blinder decomposition which takes account of 1) the magnitude of changes in absenteeism over time and 2) the observed association between absenteeism and test scores (after controlling for other factors), to compute how much of the test score decline could potentially be explained by changes in absenteeism. The regressions include controls for race/ethnicity, gender, English language proficiency, free and reduced-price lunch status, number of books at home, and disability status. To the extent that absenteeism is also correlated with these controls, the analysis may understate the explanatory role of absenteeism. FACT SHEET: Update on the United States Commitment to Expanding Access to Medicines Around the World Since Day One, the Biden-Harris Administration has worked to ensure the United States is better prepared for the next pandemic. U.S. national security and prosperity depend on countries around the world being prepared to prevent outbreaks when possible, and to rapidly detect and respond to emerging infectious disease threats when they occur. Detecting infectious disease threats quickly, and sharing that information widely, is critical to limit global transmission, and to rapidly develop necessary diagnostics, vaccines, treatments, personal protective equipment, and other countermeasures. Once available, facilitating equitable domestic and global access to medical countermeasures, like vaccines, tests and treatments, is the best way to minimize global morbidity and mortality, as well as to reduce economic and other disruptions. Collectively, these actions will make the United States, and the world, safer from the risk posed by pandemics and other biological events. Coupled with broader investments in health, the United States is supporting countries around the world to expand access to quality medical countermeasures (MCMs), including vaccines, tests, and treatments, to end long-standing threats such as HIV, growing threats such as measles, and novel threats like COVID-19. These investments built on decades of global health and health security leadership by the United States. In the first three years of the Biden-Harris Administration, the United States invested nearly $32 billion globally to: better prepare for the next pandemic; fight existing epidemics like HIV/AIDS, tuberculosis (TB), and malaria; and ensure high-need communities have access to essential health services like routine childhood immunization and maternal and211 U2-12</text> What is the correct answer to this question: Which of the following options is not part the- plan？ Choices: (A). (B). (C. (D)1. Format your response as follows: "The correct answer is (insert answer here)".
326
null
0
A
With insufficient tools to fight COVID-19, the United States mobilized all of society to insist on surviving the outbreak with the least disruption to the United States.
Please read the following text and answer the question below. <text> Chronic Absenteeism and Disrupted Learning Require an All-Hands-on-Deck Approach K-12 absenteeism has increased since the onset of COVID-19 and has contributed to falling test scores. Improving engagement is key for student success and the broader economy. Policies promoting strong schools and academic success impact students’ lives as adults, long after they leave the classroom. Beyond the significance for individuals, the educational development of our children and young people is a key input into the economy and has spillover benefits to society more broadly.  While the evidence is clear that students and society benefit from attending well-resourced schools with effective teachers, these benefits can only materialize if students are present and engaged.  A necessary step to ensure students benefit from all that schools have to offer is to support students’ consistent presence in the classroom—which is why the Biden-Harris Administration is focused on the issue of chronic absenteeism. In the aftermath of the COVID-19 pandemic, one study found that the number of public school students who are chronically absent—meaning they miss at least 10 percent of days in a school year, whether excused or unexcused—has nearly doubled, from about 15 percent in the 2018-2019 school year to around 30 percent in 2021-2022.[1] These large increases in absenteeism are widespread: every state for which data were available in this study saw significant increases in rates of chronic absenteeism between the 2018-2019 and 2021-2022 school years. Disparities in levels of chronic absenteeism across racial, ethnic, and socioeconomic lines also widened. Research shows that school absences take a toll on grades and performance on standardized tests. Beyond test scores, irregular attendance can be a predictor of high school drop-out, which has been linked to poor labor market prospects, diminished health, and increased involvement in the criminal justice system. Students who are chronically absent are at higher risk for these adverse outcomes. The increases in chronic absenteeism are large enough that they could be a substantial contributor to declines in post-pandemic test scores. (While test scores are not the only important aspect of student success, they provide a measurable early indicator that is predictive of broader long-term outcomes.)  To examine this question, the Council of Economic Advisers partnered with the National Center for Education Statistics (NCES) to analyze national data which includes measures of both standardized test scores and absenteeism during the 2018-2019 and 2021-2022 school years.[2] Using regression analysis to document the strong association between absenteeism and test scores (after controlling for other factors), we then implement a decomposition analysis to simulate how much of the decline in test scores could be attributed to increases in absenteeism.[3] Figure 1 illustrates the results of this descriptive analysis. The vertical bars indicate the average decline in scores between 2019 and 2022, by subject and grade level. The green portions of each bar indicate how much smaller these declines might be if absenteeism had not increased at all. We find that, even after controlling for changes in other characteristics of the student body over time, the observed association between absenteeism and test scores is large enough to account for 16-27 percent of the overall test score declines in math, and 36-45 percent of the declines in reading. These results come with several caveats: most importantly, we do not yet know the extent to which the recent increase in absenteeism is a stand-alone, causal contributor to test score declines, and to what extent it is a symptom of other factors that could account for both the increases in student absenteeism and declines in performance. Such factors could include declining mental and physical health, familial responsibilities, or other demands on students’ mental and physical resources. Given the magnitude of test score declines and extent of chronic absenteeism, pandemic recovery efforts require an “all-hands-on-deck” response.  While State-administered test scores from the 2021-2022 and 2022-2023 school years show some early signs of rebounding from the major disruptions of the pandemic, estimates suggest the average elementary school student would need sufficient supports and instructional time to sustain additional gains for several years in order to reach the performance of comparable pre-COVID cohorts. Without such sustained investments, one group of researchers estimated that these disruptions could cost American students $2 trillion in lifetime earnings. Ensuring that all students benefit from the full scope of pandemic recovery efforts requires that they are present in schools. Targeted interventions such as early warning systems, mailing outreach, and text nudges have shown promise in increasing attendance, especially among students who would have otherwise have been chronically absent from school. Research on the potential benefits of high-dosage tutoring and other evidence-based interventions implemented in afterschool programs or summer school can help educators and school leaders create a network of supports that best address student needs. The Biden-Harris Administration has undertaken significant efforts to combat chronic absenteeism and make sure that students are in the classroom and engaged in school. This includes: disseminating grant funds that can resource interventions and supports; offering technical assistance to States and districts; investing in comprehensive mental health programs for students; and establishing and strengthening the National Partnership for Student Success, which marshals evidence-backed supports such as tutoring and mentoring to help keep students engaged and on-track. Additionally, States have until next school year to use remaining Elementary and Secondary School Emergency Relief funds set aside for P-12 schools in the American Rescue Plan that can be used towards academic recovery, school attendance and engagement, and other efforts. Making up for lost time and learning disruption means empowering students and their families to take an active role in their academic recovery, and tracking and addressing chronic absenteeism will be an important aspect of these recovery efforts in the months and years to come. Ultimately, whether chronic absenteeism is a symptom or a cause—or both—of ongoing academic disruption, the evidence is clear that the road to recovery runs through the classroom. [1] These chronic absenteeism rates come from an academic study that collected administrative data from 40 states (and the District of Columbia), accounting for over 92 percent of K-12 public school students in the United States. [2] We analyze student level test scores from the National Assessment of Student Progress (NAEP) in this analysis. NAEP, also known as the “Nation’s Report Card,” is the largest nationally representative and continuing assessment of student learning. The absenteeism measure in NAEP is self-reported by students and reflects days missed over the past month. While the levels of absenteeism are measured differently than in administrative records, the increases over time are similarly large. [3] The analysis is a type of non-causal, Oaxaca-Blinder decomposition which takes account of 1) the magnitude of changes in absenteeism over time and 2) the observed association between absenteeism and test scores (after controlling for other factors), to compute how much of the test score decline could potentially be explained by changes in absenteeism. The regressions include controls for race/ethnicity, gender, English language proficiency, free and reduced-price lunch status, number of books at home, and disability status. To the extent that absenteeism is also correlated with these controls, the analysis may understate the explanatory role of absenteeism. FACT SHEET: Update on the United States Commitment to Expanding Access to Medicines Around the World Since Day One, the Biden-Harris Administration has worked to ensure the United States is better prepared for the next pandemic. U.S. national security and prosperity depend on countries around the world being prepared to prevent outbreaks when possible, and to rapidly detect and respond to emerging infectious disease threats when they occur. Detecting infectious disease threats quickly, and sharing that information widely, is critical to limit global transmission, and to rapidly develop necessary diagnostics, vaccines, treatments, personal protective equipment, and other countermeasures. Once available, facilitating equitable domestic and global access to medical countermeasures, like vaccines, tests and treatments, is the best way to minimize global morbidity and mortality, as well as to reduce economic and other disruptions. Collectively, these actions will make the United States, and the world, safer from the risk posed by pandemics and other biological events. Coupled with broader investments in health, the United States is supporting countries around the world to expand access to quality medical countermeasures (MCMs), including vaccines, tests, and treatments, to end long-standing threats such as HIV, growing threats such as measles, and novel threats like COVID-19. These investments built on decades of global health and health security leadership by the United States. In the first three years of the Biden-Harris Administration, the United States invested nearly $32 billion globally to: better prepare for the next pandemic; fight existing epidemics like HIV/AIDS, tuberculosis (TB), and malaria; and ensure high-need communities have access to essential health services like routine childhood immunization and maternal and211 U2-12</text> What is the correct answer to this question: Which of the following options is not part the- plan？ Choices: (A). (B). (C. (D)1. Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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821, 822, 823, 824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 856, 857, 858, 859, 860, 861, 862, 863, 864, 865, 866, 867, 868, 869, 870, 871, 872, 873, 874, 875, 876, 877, 878, 879, 880, 881, 882, 883, 884, 885, 886, 887, 888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 903, 904, 905, 906, 907, 908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919, 920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939, 940, 941, 942, 943, 944, 945, 946, 947, 948, 949, 950, 951, 952, 953, 954, 955, 956, 957, 958, 959, 960, 961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 971, 972, 973, 974, 975, 976, 977, 978, 979, 980, 981, 982, 983, 984, 985, 986, 987, 988, 989, 990, 991, 992, 993, 994, 995, 996, 997, 998, 999, 1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1011, 1012, 1013, 1014, 1015, 1016, 1017, 1018, 1019, 1020, 1021, 1022, 1023, 1024, 1025, 1026, 1027, 1028, 1029, 1030, 1031, 1032, 1033, 1034, 1035, 1036, 1037, 1038, 1039, 1040, 1041, 1042, 1043, 1044, 1045, 1046, 1047, 1048, 1049, 1050, 1051, 1052, 1053, 1054, 1055, 1056, 1057, 1058, 1059, 1060, 1061, 1062, 1063, 1064, 1065, 1066, 1067, 1068, 1069, 1070, 1071, 1072, 1073, 1074, 1075, 1076, 1077, 1078, 1079, 1080, 1081, 1082, 1083, 1084, 1085, 1086, 1087, 1088, 1089, 1090, 1091, 1092, 1093, 1094, 1095, 1096, 1097, 1098, 1099, 1100, 1101, 1102, 1103, 1104, 1105, 1106, 1107, 1108, 1109, 1110, 1111, 1112, 1113, 1114, 1115, 1116, 1117, 1118, 1119, 1120, 1121, 1122, 1123, 1124, 1125, 1126, 1127, 1128, 1129, 1130, 1131, 1132, 1133, 1134, 1135, 1136, 1137, 1138, 1139, 1140, 1141, 1142, 1143, 1144, 1145, 1146, 1147, 1148, 1149, 1150, 1151, 1152, 1153, 1154, 1155, 1156, 1157, 1158, 1159, 1160, 1161, 1162, 1163, 1164, 1165, 1166, 1167, 1168, 1169, 1170, 1171, 1172, 1173, 1174, 1175, 1176, 1177, 1178, 1179, 1180, 1181, 1182, 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1349, 1350, 1351, 1352, 1353, 1354, 1355, 1356, 1357, 1358, 1359, 1360, 1361, 1362, 1363, 1364, 1365, 1366, 1367, 1368, 1369, 1370, 1371, 1372, 1373, 1374, 1375, 1376, 1377, 1378, 1379, 1380, 1381, 1382, 1383, 1384, 1385, 1386, 1387, 1388, 1389, 1390, 1391, 1392, 1393, 1394, 1395, 1396, 1397, 1398, 1399, 1400, 1401, 1402, 1403, 1404, 1405, 1406, 1407, 1408, 1409, 1410, 1411, 1412, 1413, 1414, 1415, 1416, 1417, 1418, 1419, 1420, 1421, 1422, 1423, 1424, 1425, 1426, 1427, 1428, 1429, 1430, 1431, 1432, 1433, 1434, 1435, 1436, 1437, 1438, 1439, 1440, 1441, 1442, 1443, 1444, 1445, 1446, 1447, 1448, 1449, 1450, 1451, 1452, 1453, 1454, 1455, 1456, 1457, 1458, 1459, 1460, 1461, 1462, 1463, 1464, 1465, 1466, 1467, 1468, 1469, 1470, 1471, 1472, 1473, 1474, 1475, 1476, 1477, 1478, 1479, 1480, 1481, 1482, 1483, 1484, 1485, 1486, 1487, 1488, 1489, 1490, 1491, 1492, 1493, 1494, 1495, 1496, 1497, 1498, 1499, 1500, 1501, 1502, 1503, 1504, 1505, 1506, 1507, 1508, 1509, 1510, 1511, 1512, 1513, 1514, 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0.104811
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Please read the following text and answer the question below. <text> Millions of online book co-purchases reveal partisan differences in the consumption of science Passionate disagreements about climate change, stem cell research and evolution raise concerns that science has become a new battlefield in the culture wars. We used data derived from millions of online co-purchases as a behavioural indica- tor for whether shared interest in science bridges political dif- ferences or selective attention reinforces existing divisions. Findings reveal partisan preferences both within and across scientific disciplines. Across fields, customers for liberal or ‘blue’ political books prefer basic science (for example, phys- ics, astronomy and zoology), whereas conservative or ‘red’ customers prefer applied and commercial science (for example, criminology, medicine and geophysics). Within disciplines, ‘red’ books tend to be co-purchased with a narrower subset of science books on the periphery of the discipline. We conclude that the political left and right share an interest in science in general, but not science in particular. This underscores the need for research into remedies that can attenuate selective exposure to ‘convenient truth’, renew the capacity for science to inform political debate and temper partisan passions. In its quest for an objective understanding of the world1, mod- ern science has practised two distinct forms of political neutrality: as an apolitical ‘separate sphere’ detached from ideological debates, and as a ‘public sphere’ relevant to political issues but with balanced political engagement that aids reasoned deliberation and deference to evidence2–5. Recent surveys support the view that science con- tributes not only to human knowledge but also to social integration, both as a voice of reason and also as a shared value. Joint surveys conducted by the American Association for the Advancement of Science (AAAS) and the Pew Research Center in 2009 and 2014 found that science remains near the top in public rankings of pro- fessions, well above that of clergy, despite the prevalence of liber- als among scientists6–8. Although nearly two-thirds of respondents question evolution, even those who see conflict with issues of per- sonal faith overwhelmingly support scientific contributions to pub- lic well-being (67%). In a highly polarized electorate, these responses invite reassurance that science continues to command political deference as a voice of reason and bridges the partisan divide. We may disagree on emotionally charged social issues, but at least we can agree on science. Political and cultural polarization within the United States, however, raises questions about the validity of this interpretation9. A less comforting possibility is that verbal survey responses may simply echo an Enlightenment commitment to value-free scientific inquiry that masks underlying scepticism about science. In recent years, conservative politicians and pundits have challenged sci- entific positions on evolution, cosmology, climate change and the perceived liberal bias in policies advocated by social scientists. For example, the conservative-funded scientific counter-movement in climate change research suggests the possibility of politically driven scientific polarization10,11. When science becomes politicized, par- tisans tend to cast doubt on scientific consensus through question- ing its inherent uncertainty12–14.This process is manifest not only in conservative resistance to climate change, but in historically liberal resistance to consensus over the positive benefits of genetically modified organisms, vaccination, nuclear power and the safe stor- age of nuclear waste15. Survey data show little overall change in public confidence in sci- ence since 1970, but beneath the surface there is a marked shift: con- servatives in the Vietnam era were more confident in science than liberals, but today that pattern has reversed16 (Supplementary Fig. 1). Does public exposure to science play an integrative role by encour- aging and informing empirical validation? Or has selective atten- tion instead reinforced the ‘Big Sort’ of American politics17–19 — the tendency to cluster in like-minded communities? Much previous research has used surveys to investigate political alignments of the producers of science (with a few exceptions20,21). We focus instead on the consumers of science, using online co-purchases of books on science and politics as a behavioural indi- cation of preferences held by customers who ‘vote with their pocket­ book’ , in contrast to survey responses that are costless. Surveys measure what researchers think is important, not what respondents care about, whereas online consumers can register their prefer- ences by purchasing books on any topic they choose. Retrospective self-reports are vulnerable to lapses of memory, whereas online sellers track every purchase. Survey responses are difficult to align across instruments that ask different questions and ask questions differently, whereas books from different stores can be classified using consistent typologies (for example the Library of Congress). Surveys are vulnerable to response bias from participants reluctant to reveal views regarded as politically incorrect; books purchased online arrive cloaked in cardboard. Finally, although surveys can use stratified random samples to generalize results to the underly- ing population, which is not possible with data from a convenience sample, rates of non-response are rising in landline-administered surveys, which raises concerns about their external validity22. We addressed concerns about generalizability in two ways — by replicating our analysis using two independent samples of purchas- ing behaviour from two online merchants (Amazon and Barnes & Noble), and also by the size of these samples, collectively comprising hundreds of millions of online customers, including members of hid- den populations (such as those without landlines) who may be under- counted in surveys based on at most a few thousand respondents. 1Computation Institute, University of Chicago, 5735 South Ellis Avenue, Chicago, Illinois 60637, USA. 2Yale Institute for Network Science, Yale University, 17 Hillhouse Avenue, New Haven, Connecticut 06511, USA. 3Department of Sociology, Cornell University, 323 Uris Hall, Ithaca, New York 14853, USA. 4Department of Sociology, University of Chicago, 1126 East 59th Street, Chicago, Illinois 60637, USA. †These authors contributed equally to this work. *e-mail: jevans@uchicago.edu; mwm14@cornell.edu 2 nature HUMAN BEHAVIOUR 1, 0079 (2017) | DOI: 10.1038/s41562-017-0079 | www.nature.com/nathumbehav © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. Letters Nature Human Behaviour Our approach also differs from survey methods in the unit of analysis. Individuals are the units in surveys, but online retailers do not provide access to individual customer behaviour. Instead, we use individual books as the unit of analysis in constructing a co-purchase network. Bipartite network analysis has been widely used in research on co-citation and co-author networks23–27 where individual infor- mation is aggregated to provide connections between scientific papers. What is lost in the absence of individual-level responses for a small sample is compensated for with massive numbers of obser- vations we can use to detect population-level patterns generated by individual behaviour. Here we extend bipartite network analysis to the study of online co-purchase behaviour among a diverse population of tens of millions of consumers. These data provide an unprecedented opportunity to study the entire popular audience for science in ways that are not possible using traditional methods. These data do not speak to the partisan alignment of scientists, the policy relevance of scientific research or the political polariza- tion of science as an institution. Nor do we address the political preferences of science’s consumers. Rather, our attention is focused exclusively on the science preferences of those who purchase liberal and conservative political books, a group whose science preferences could differ from those who do not shop for books online or who shop for science books but not for politics. Within that constraint of available data, we ask to what extent purchasers of political books are also interested in science, and in what parts of science they are most interested. A shared interest in science might provide a bridge across partisan divisions, whereas selective attention to ‘convenient truths’ risks reinforcement of existing political identities. To find out, we constructed two undirected co-purchase net- works of books from the American domain of the world’s two largest online book stores, following an approach pioneered by Valdis Krebs28–30. Up to 100 unranked books are listed on each book page under the heading “Customers Who Bought This Item Also Bought” . According to previous work31, these recommenda- tions are based on a disproportionate number of customers who bought both books and are designed exclusively to identify those books (up to 100) that a customer is most likely to be interested in also purchasing. We compared results derived from two different book. IO ConservHowIn the format provided the authors and unedited. 1 1 </text> What is the correct answer to this question: What's the limitation this article? Choices: (A). (B. (C-p. (D). Format your response as follows: "The correct answer is (insert answer here)".
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Although co-purchasing patterns illustrate the broader political interests in science at the population level, they fail to reveal the individual factors influencing these interests.
Please read the following text and answer the question below. <text> Millions of online book co-purchases reveal partisan differences in the consumption of science Passionate disagreements about climate change, stem cell research and evolution raise concerns that science has become a new battlefield in the culture wars. We used data derived from millions of online co-purchases as a behavioural indica- tor for whether shared interest in science bridges political dif- ferences or selective attention reinforces existing divisions. Findings reveal partisan preferences both within and across scientific disciplines. Across fields, customers for liberal or ‘blue’ political books prefer basic science (for example, phys- ics, astronomy and zoology), whereas conservative or ‘red’ customers prefer applied and commercial science (for example, criminology, medicine and geophysics). Within disciplines, ‘red’ books tend to be co-purchased with a narrower subset of science books on the periphery of the discipline. We conclude that the political left and right share an interest in science in general, but not science in particular. This underscores the need for research into remedies that can attenuate selective exposure to ‘convenient truth’, renew the capacity for science to inform political debate and temper partisan passions. In its quest for an objective understanding of the world1, mod- ern science has practised two distinct forms of political neutrality: as an apolitical ‘separate sphere’ detached from ideological debates, and as a ‘public sphere’ relevant to political issues but with balanced political engagement that aids reasoned deliberation and deference to evidence2–5. Recent surveys support the view that science con- tributes not only to human knowledge but also to social integration, both as a voice of reason and also as a shared value. Joint surveys conducted by the American Association for the Advancement of Science (AAAS) and the Pew Research Center in 2009 and 2014 found that science remains near the top in public rankings of pro- fessions, well above that of clergy, despite the prevalence of liber- als among scientists6–8. Although nearly two-thirds of respondents question evolution, even those who see conflict with issues of per- sonal faith overwhelmingly support scientific contributions to pub- lic well-being (67%). In a highly polarized electorate, these responses invite reassurance that science continues to command political deference as a voice of reason and bridges the partisan divide. We may disagree on emotionally charged social issues, but at least we can agree on science. Political and cultural polarization within the United States, however, raises questions about the validity of this interpretation9. A less comforting possibility is that verbal survey responses may simply echo an Enlightenment commitment to value-free scientific inquiry that masks underlying scepticism about science. In recent years, conservative politicians and pundits have challenged sci- entific positions on evolution, cosmology, climate change and the perceived liberal bias in policies advocated by social scientists. For example, the conservative-funded scientific counter-movement in climate change research suggests the possibility of politically driven scientific polarization10,11. When science becomes politicized, par- tisans tend to cast doubt on scientific consensus through question- ing its inherent uncertainty12–14.This process is manifest not only in conservative resistance to climate change, but in historically liberal resistance to consensus over the positive benefits of genetically modified organisms, vaccination, nuclear power and the safe stor- age of nuclear waste15. Survey data show little overall change in public confidence in sci- ence since 1970, but beneath the surface there is a marked shift: con- servatives in the Vietnam era were more confident in science than liberals, but today that pattern has reversed16 (Supplementary Fig. 1). Does public exposure to science play an integrative role by encour- aging and informing empirical validation? Or has selective atten- tion instead reinforced the ‘Big Sort’ of American politics17–19 — the tendency to cluster in like-minded communities? Much previous research has used surveys to investigate political alignments of the producers of science (with a few exceptions20,21). We focus instead on the consumers of science, using online co-purchases of books on science and politics as a behavioural indi- cation of preferences held by customers who ‘vote with their pocket­ book’ , in contrast to survey responses that are costless. Surveys measure what researchers think is important, not what respondents care about, whereas online consumers can register their prefer- ences by purchasing books on any topic they choose. Retrospective self-reports are vulnerable to lapses of memory, whereas online sellers track every purchase. Survey responses are difficult to align across instruments that ask different questions and ask questions differently, whereas books from different stores can be classified using consistent typologies (for example the Library of Congress). Surveys are vulnerable to response bias from participants reluctant to reveal views regarded as politically incorrect; books purchased online arrive cloaked in cardboard. Finally, although surveys can use stratified random samples to generalize results to the underly- ing population, which is not possible with data from a convenience sample, rates of non-response are rising in landline-administered surveys, which raises concerns about their external validity22. We addressed concerns about generalizability in two ways — by replicating our analysis using two independent samples of purchas- ing behaviour from two online merchants (Amazon and Barnes & Noble), and also by the size of these samples, collectively comprising hundreds of millions of online customers, including members of hid- den populations (such as those without landlines) who may be under- counted in surveys based on at most a few thousand respondents. 1Computation Institute, University of Chicago, 5735 South Ellis Avenue, Chicago, Illinois 60637, USA. 2Yale Institute for Network Science, Yale University, 17 Hillhouse Avenue, New Haven, Connecticut 06511, USA. 3Department of Sociology, Cornell University, 323 Uris Hall, Ithaca, New York 14853, USA. 4Department of Sociology, University of Chicago, 1126 East 59th Street, Chicago, Illinois 60637, USA. †These authors contributed equally to this work. *e-mail: jevans@uchicago.edu; mwm14@cornell.edu 2 nature HUMAN BEHAVIOUR 1, 0079 (2017) | DOI: 10.1038/s41562-017-0079 | www.nature.com/nathumbehav © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. Letters Nature Human Behaviour Our approach also differs from survey methods in the unit of analysis. Individuals are the units in surveys, but online retailers do not provide access to individual customer behaviour. Instead, we use individual books as the unit of analysis in constructing a co-purchase network. Bipartite network analysis has been widely used in research on co-citation and co-author networks23–27 where individual infor- mation is aggregated to provide connections between scientific papers. What is lost in the absence of individual-level responses for a small sample is compensated for with massive numbers of obser- vations we can use to detect population-level patterns generated by individual behaviour. Here we extend bipartite network analysis to the study of online co-purchase behaviour among a diverse population of tens of millions of consumers. These data provide an unprecedented opportunity to study the entire popular audience for science in ways that are not possible using traditional methods. These data do not speak to the partisan alignment of scientists, the policy relevance of scientific research or the political polariza- tion of science as an institution. Nor do we address the political preferences of science’s consumers. Rather, our attention is focused exclusively on the science preferences of those who purchase liberal and conservative political books, a group whose science preferences could differ from those who do not shop for books online or who shop for science books but not for politics. Within that constraint of available data, we ask to what extent purchasers of political books are also interested in science, and in what parts of science they are most interested. A shared interest in science might provide a bridge across partisan divisions, whereas selective attention to ‘convenient truths’ risks reinforcement of existing political identities. To find out, we constructed two undirected co-purchase net- works of books from the American domain of the world’s two largest online book stores, following an approach pioneered by Valdis Krebs28–30. Up to 100 unranked books are listed on each book page under the heading “Customers Who Bought This Item Also Bought” . According to previous work31, these recommenda- tions are based on a disproportionate number of customers who bought both books and are designed exclusively to identify those books (up to 100) that a customer is most likely to be interested in also purchasing. We compared results derived from two different book. IO ConservHowIn the format provided the authors and unedited. 1 1 </text> What is the correct answer to this question: What's the limitation this article? Choices: (A). (B. (C-p. 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Please read the following text and answer the question below. <text> Fighting Covid-19 China in Action The State Council Information Office of the People’s Republic of China June 2020 Contents Foreword I. China’s Fight against the Epidemic: A Test of Fire Stage I: Swift Response to the Public Health Emergency (December 27, 2019-January 19, 2020) Stage II: Initial Progress in Containing the Virus (January 20-February 20, 2020) Stage III: Newly Confirmed Domestic Cases on the Chinese Mainland Drop to Single Digits (February 21-March 17, 2020) Stage IV: Wuhan and Hubei – An Initial Victory in a Critical Battle (March 18-April 28, 2020) Stage V: Ongoing Prevention and Control (Since April 29, 2020) II. Well-Coordinated Prevention, Control and Treatment 1. Centralized and Efficient Command 2. A Tight Prevention and Control System Involving All Sectors of Society 3. An All-Out Effort to Treat Patients and Save Lives 4. China Has Released Information in an Open and Transparent Manner as Required by Law 5. Science and Technology Underpin China’s Efforts III. Assembling a Powerful Force to Beat the Virus 1. Lives Are Precious 2. Mobilizing the Whole Country to Fight the Epidemic 3. Coordinating Prevention and Control with Social and Economic Development 4. Uniting as One – China’s Billion People IV. Building a Global Community of Health for All 1. China Appreciates Support from the International Community 2. China Conducts Active International Exchanges and Cooperation 3. International Solidarity and Cooperation in Fighting the Pandemic Afterword Foreword The Covid-19 global pandemic is the most extensive to afflict humanity in a century. A serious crisis for the entire world, and a daunting challenge, it poses a grave threat to human life and health. This is a war that humanity has to fight and win. Facing this unknown, unexpected, and devastating disease, China launched a resolute battle to prevent and control its spread. Making people’s lives and health its first priority, China adopted extensive, stringent, and thorough containment measures, and has for now succeeded in cutting all channels for the transmission of the virus. 1.4 billion Chinese people have exhibited enormous tenacity and solidarity in erecting a defensive rampart that demonstrates their power in the face of such natural disasters. Having forged the idea that the world is a global community of shared future, and believing that it must act as a responsible member, China has fought shoulder to shoulder with the rest of the world. In an open, transparent, and responsible manner and in accordance with the law, China gave timely notification to the international community of the onset of a new coronavirus, and shared without reserve its experience in containing the spread of the virus and treating the infected. China has great empathy with victims all over the world, and has done all it can to provide humanitarian aid in support of the international community’s endeavors to stem the pandemic. The virus is currently wreaking havoc throughout the world. China grieves for those who have been killed and those who have sacrificed their lives in the fight, extends the greatest respect to those who are struggling to save lives, and offers true moral support to those who are infected and receiving treatment. China firmly believes that as long as all countries unite and cooperate to mount a collective response, the international community will succeed in overcoming the pandemic, and will emerge from this dark moment in human history into a brighter future. To keep a record of China’s efforts in its own fight against the virus, to share its experience with the rest of the world, and to clarify its ideas on the global battle, the Chinese government now releases this white paper. I. China’s Fight against the Epidemic: A Test of Fire The Covid-19 epidemic is a major public health emergency. The virus has spread faster and wider than any other since the founding of the People’s Republic in 1949, and has proven to be the most difficult to contain. It is both a crisis and a major test for China. The Communist Party of China (CPC) and the Chinese government have addressed the epidemic as a top priority, and taken swift action. General Secretary Xi Jinping has taken personal command, planned the response, overseen the general situation and acted decisively, pointing the way forward in the fight against the epidemic. This has bolstered the Chinese people’s confidence and rallied their strength. Under the leadership of the CPC, the whole nation has followed the general principle of “remaining confident, coming together in solidarity, adopting a science-based approach, and taking targeted measures”, and waged an all-out people’s war on the virus. Through painstaking efforts and tremendous sacrifice, and having paid a heavy price, China has succeeded in turning the situation around. In little more than a single month, the rising spread of the virus was contained; in around two months, the daily increase in domestic coronavirus cases had fallen to single digits; and in approximately three months, a decisive victory was secured in the battle to defend Hubei Province and its capital city of Wuhan. With these strategic achievements, China has protected its people’s lives, safety and health, and made a significant contribution to safeguarding regional and global public health. As of 24:00 of May 31, 2020, a cumulative total of 83,017 confirmed cases had been reported on the Chinese mainland, 78,307 infected had been cured and discharged from hospital, and 4,634 people had died. This demonstrates a cure rate of 94.3 percent and a fatality rate of 5.6 percent (see charts 1, 2, 3 and 4). Note: On February 12, newly confirmed cases reached 15,152 (including 13,332 cumulative clinically diagnosed cases in Hubei). Chart 1. Daily Figure for Newly Confirmed Cases on the Chinese Mainland Chart 2. Daily Figure for New Fatalities on the Chinese Mainland Chart 3. Cumulative Total of Outstanding Cases on the Chinese Mainland Chart 4. Daily Figure for Cured Cases on the Chinese Mainland China’s fight against the epidemic can be divided into five stages. Stage I: Swift Response to the Public Health Emergency (December 27, 2019-January 19, 2020) As soon as cases of pneumonia of unknown cause were identified in Wuhan City, Hubei Province, China acted immediately to conduct etiological and epidemiological investigations and to stop the spread of the disease, and promptly reported the situation. In a timely manner, China informed the WHO and other countries, including the US, of the developing situation, and released the genome sequence of the novel coronavirus. After community spread and clusters of cases emerged in Wuhan, and confirmed cases were reported in other Chinese regions, which were due to virus carriers traveling from the city, a nationwide program of epidemic prevention and control was launched. (1) December 27, 2019: Hubei Provincial Hospital of Integrated Chinese and Western Medicine reported cases of pneumonia of unknown cause to the Wuhan Jianghan Center for Disease Prevention and Control. The Wuhan city government arranged for experts to look into these cases through an analysis of the patients’ condition and clinical outcome, the findings of epidemiological investigations, and preliminary laboratory testing results. The conclusion was that they were cases of a viral pneumonia. (2) December 30: The Wuhan City Health Commission (WCHC)issued Urgent Notice on Treatment of Patients with Pneumonia of Unknown Cause. Upon learning of developments, the National Health Commission (NHC) acted immediately to organize research into the disease. (3) December 31: The NHC made arrangements in the small hours to send a working group and an expert team to Wuhan to guide its response to the situation and conduct on-site investigations. The WCHC website carried its Information Circular on the Pneumonia Cases in Wuhan, confirming 27 cases and urging the public to stay away from enclosed public places with poor ventilation and venues where large crowds gathered. The commission also suggested the use of face masks when going out. From that day on, the WCHC began to release updates on the disease in accordance with the law. (4) January 1, 2020: The NHC set up a leading group on the disease 1-129-. </text> What is the correct answer to this question: According to the article, which one is not? Choices: (A. (B. (C. (D spare. Format your response as follows: "The correct answer is (insert answer here)".
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Science and technology underpin China’s efforts.
Please read the following text and answer the question below. <text> Fighting Covid-19 China in Action The State Council Information Office of the People’s Republic of China June 2020 Contents Foreword I. China’s Fight against the Epidemic: A Test of Fire Stage I: Swift Response to the Public Health Emergency (December 27, 2019-January 19, 2020) Stage II: Initial Progress in Containing the Virus (January 20-February 20, 2020) Stage III: Newly Confirmed Domestic Cases on the Chinese Mainland Drop to Single Digits (February 21-March 17, 2020) Stage IV: Wuhan and Hubei – An Initial Victory in a Critical Battle (March 18-April 28, 2020) Stage V: Ongoing Prevention and Control (Since April 29, 2020) II. Well-Coordinated Prevention, Control and Treatment 1. Centralized and Efficient Command 2. A Tight Prevention and Control System Involving All Sectors of Society 3. An All-Out Effort to Treat Patients and Save Lives 4. China Has Released Information in an Open and Transparent Manner as Required by Law 5. Science and Technology Underpin China’s Efforts III. Assembling a Powerful Force to Beat the Virus 1. Lives Are Precious 2. Mobilizing the Whole Country to Fight the Epidemic 3. Coordinating Prevention and Control with Social and Economic Development 4. Uniting as One – China’s Billion People IV. Building a Global Community of Health for All 1. China Appreciates Support from the International Community 2. China Conducts Active International Exchanges and Cooperation 3. International Solidarity and Cooperation in Fighting the Pandemic Afterword Foreword The Covid-19 global pandemic is the most extensive to afflict humanity in a century. A serious crisis for the entire world, and a daunting challenge, it poses a grave threat to human life and health. This is a war that humanity has to fight and win. Facing this unknown, unexpected, and devastating disease, China launched a resolute battle to prevent and control its spread. Making people’s lives and health its first priority, China adopted extensive, stringent, and thorough containment measures, and has for now succeeded in cutting all channels for the transmission of the virus. 1.4 billion Chinese people have exhibited enormous tenacity and solidarity in erecting a defensive rampart that demonstrates their power in the face of such natural disasters. Having forged the idea that the world is a global community of shared future, and believing that it must act as a responsible member, China has fought shoulder to shoulder with the rest of the world. In an open, transparent, and responsible manner and in accordance with the law, China gave timely notification to the international community of the onset of a new coronavirus, and shared without reserve its experience in containing the spread of the virus and treating the infected. China has great empathy with victims all over the world, and has done all it can to provide humanitarian aid in support of the international community’s endeavors to stem the pandemic. The virus is currently wreaking havoc throughout the world. China grieves for those who have been killed and those who have sacrificed their lives in the fight, extends the greatest respect to those who are struggling to save lives, and offers true moral support to those who are infected and receiving treatment. China firmly believes that as long as all countries unite and cooperate to mount a collective response, the international community will succeed in overcoming the pandemic, and will emerge from this dark moment in human history into a brighter future. To keep a record of China’s efforts in its own fight against the virus, to share its experience with the rest of the world, and to clarify its ideas on the global battle, the Chinese government now releases this white paper. I. China’s Fight against the Epidemic: A Test of Fire The Covid-19 epidemic is a major public health emergency. The virus has spread faster and wider than any other since the founding of the People’s Republic in 1949, and has proven to be the most difficult to contain. It is both a crisis and a major test for China. The Communist Party of China (CPC) and the Chinese government have addressed the epidemic as a top priority, and taken swift action. General Secretary Xi Jinping has taken personal command, planned the response, overseen the general situation and acted decisively, pointing the way forward in the fight against the epidemic. This has bolstered the Chinese people’s confidence and rallied their strength. Under the leadership of the CPC, the whole nation has followed the general principle of “remaining confident, coming together in solidarity, adopting a science-based approach, and taking targeted measures”, and waged an all-out people’s war on the virus. Through painstaking efforts and tremendous sacrifice, and having paid a heavy price, China has succeeded in turning the situation around. In little more than a single month, the rising spread of the virus was contained; in around two months, the daily increase in domestic coronavirus cases had fallen to single digits; and in approximately three months, a decisive victory was secured in the battle to defend Hubei Province and its capital city of Wuhan. With these strategic achievements, China has protected its people’s lives, safety and health, and made a significant contribution to safeguarding regional and global public health. As of 24:00 of May 31, 2020, a cumulative total of 83,017 confirmed cases had been reported on the Chinese mainland, 78,307 infected had been cured and discharged from hospital, and 4,634 people had died. This demonstrates a cure rate of 94.3 percent and a fatality rate of 5.6 percent (see charts 1, 2, 3 and 4). Note: On February 12, newly confirmed cases reached 15,152 (including 13,332 cumulative clinically diagnosed cases in Hubei). Chart 1. Daily Figure for Newly Confirmed Cases on the Chinese Mainland Chart 2. Daily Figure for New Fatalities on the Chinese Mainland Chart 3. Cumulative Total of Outstanding Cases on the Chinese Mainland Chart 4. Daily Figure for Cured Cases on the Chinese Mainland China’s fight against the epidemic can be divided into five stages. Stage I: Swift Response to the Public Health Emergency (December 27, 2019-January 19, 2020) As soon as cases of pneumonia of unknown cause were identified in Wuhan City, Hubei Province, China acted immediately to conduct etiological and epidemiological investigations and to stop the spread of the disease, and promptly reported the situation. In a timely manner, China informed the WHO and other countries, including the US, of the developing situation, and released the genome sequence of the novel coronavirus. After community spread and clusters of cases emerged in Wuhan, and confirmed cases were reported in other Chinese regions, which were due to virus carriers traveling from the city, a nationwide program of epidemic prevention and control was launched. (1) December 27, 2019: Hubei Provincial Hospital of Integrated Chinese and Western Medicine reported cases of pneumonia of unknown cause to the Wuhan Jianghan Center for Disease Prevention and Control. The Wuhan city government arranged for experts to look into these cases through an analysis of the patients’ condition and clinical outcome, the findings of epidemiological investigations, and preliminary laboratory testing results. The conclusion was that they were cases of a viral pneumonia. (2) December 30: The Wuhan City Health Commission (WCHC)issued Urgent Notice on Treatment of Patients with Pneumonia of Unknown Cause. Upon learning of developments, the National Health Commission (NHC) acted immediately to organize research into the disease. (3) December 31: The NHC made arrangements in the small hours to send a working group and an expert team to Wuhan to guide its response to the situation and conduct on-site investigations. The WCHC website carried its Information Circular on the Pneumonia Cases in Wuhan, confirming 27 cases and urging the public to stay away from enclosed public places with poor ventilation and venues where large crowds gathered. The commission also suggested the use of face masks when going out. From that day on, the WCHC began to release updates on the disease in accordance with the law. (4) January 1, 2020: The NHC set up a leading group on the disease 1-129-. </text> What is the correct answer to this question: According to the article, which one is not? Choices: (A. (B. (C. (D spare. Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> THE STATUTES OF THE REPUBLIC OF SINGAPORE CUSTOMS ACT 1960 2020 REVISED EDITION This revised edition incorporates all amendments up to and including 1 December 2021 and comes into operation on 31 December 2021. Prepared and Published by THE LAW REVISION COMMISSION UNDER THE AUTHORITY OF THE REVISED EDITION OF THE LAWS ACT 1983 Informal Consolidation – version in force from 1/3/2024 Customs Act 1960 ARRANGEMENT OF SECTIONS PART 1 PRELIMINARY Section 1. Short title 2. Scope of Act 3. Interpretation PART 2 APPOINTMENT OF OFFICERS 4. Appointment of Director‑General and other officers 5. Powers of Director‑General to delegate 6. Officers of customs to be public servants 6A. Officers of customs to be armed 7. Powers of police officers 8. Authority card to be produced 9. Persons employed on customs duty to be deemed proper officers of customs PART 3 LEVYING OF DUTY AND TAX 10. Levying of duties 11. Power of Director‑General to waive duty, etc. 12. Measuring and testing by proper officers of customs 13. Power of Minister to exempt 14. Reimposition of customs duty or excise duty 15. Remission of customs duty or excise duty on goods lost, damaged or destroyed before removal from customs control 16. Rebate for motor cars 17. Tax on motor vehicles using heavy fuel oil, etc. 17A. Exemption from, and other changes in liability to, special tax 17B. Presumptions relating to special tax 18. Recovery of special tax in arrears Informal Consolidation – version in force from 1/3/2024 1 2020 Ed. Section 19. Claims for duties, taxes, fees and other charges overpaid or erroneously paid 20. Payment of duty, etc., short levied or erroneously refunded 21. Calculation of duty 22. Value of imported or locally-manufactured goods, other than motor spirit, for excise duty 22A. Value of imported goods for customs duty 22B. Objection and appeal on valuation 23. Value of imported and locally-manufactured motor spirit 24. Value of motor spirit where variation in price 25. Value of motor spirit which is uncustomed, not retailed in Singapore under a trade name or where retailers’ pump price is not available 26. Question as to price of motor spirit to be decided by Director‑General 27. Removal of dutiable goods from customs control 28. Time of importation when duty is imposed 29. Customs rulings 30. Import of trade samples PART 4 IMPORTATION AND EXPORTATION 31. Place of import, export or transhipment 32. Registration of importers and agencies in respect of goods made dutiable 33. Import and export to be in accordance with regulations 34. Permit to remove goods 35. [Repealed] 36. Goods removed in accordance with declaration not to be relanded 37. Declaration 38. Power to prohibit imports and exports 39. Particulars of goods inwards to be furnished 40. Correction to be made on completion of discharge 41. Particulars of goods exported to be furnished 42. Liability in respect of duty for goods unaccounted for, etc. Customs Act 1960 2020 Ed. 2 Informal Consolidation – version in force from 1/3/2024 PART 5 GENERAL PROVISIONS AFFECTING AIRCRAFT AND VESSELS IN TERRITORIAL WATERS Section 43. Master of vessel to obey signals from preventive vessels and instructions by officer of customs 44. Goods not specified in manifest to be deemed uncustomed 45. Missing goods deemed to have been illegally landed 46. Accommodation in vessel to be provided for proper officer of customs 47. Power to lock up goods dutiable on import 48. Prohibition of carriage of dutiable goods in local craft PART 6 WAREHOUSING 49. Government warehouses 50. [Repealed] 51. Licensed warehouses 52. Dutiable goods to be deposited in free trade zone 53. Warehouse deposit receipts 54. Power to open and examine goods or packages 55. Detention of goods where doubt exists 56. Protection of Government from liability 57. Protection of officers of customs from liability 58. Payment of warehouse rent 59. Removal of dutiable goods from customs control 60. Landing of dutiable goods for transhipment 61. Storage of dutiable goods 62. Weighing and handling PART 7 MANUFACTURE AND BOTTLING 63. Licence to manufacture dutiable goods 64. No person except licensee to keep a still, etc. 65. [Repealed] 66. Bottling warehouse 67. Prohibition on keeping of utensil, apparatus, etc., for bottling, blending, etc. 68. Exemption Customs Act 1960 3 2020 Ed. Informal Consolidation – version in force from 1/3/2024 Section 69. Power to enter licensed premises PART 8 70. to 77. [Repealed] PART 9 DRAWBACK 78. Drawback on imported tobacco manufactured in Singapore 79. Drawback on imported goods on which duty has been paid 80. Declaration by claimant 81. Drawback on goods used in manufacture PART 10 DUTY FREE SHOPS FOR TOURISTS 82. Duty free shops for tourists PART 11 COMPOSITE LICENCE 83. Grant of composite licence 84. [Repealed] PART 12 MISCELLANEOUS PROVISIONS 85. Documents to be produced on demand 86. Computer service 87. Preservation of records 88. Power of Director‑General to obtain information and furnishing of information 89. Information not to be published or disclosed 90. Retention of trade documents 91. Persons bound to give information or produce documents 92. Service of notices 93. Baggage of passengers 94. Proper officer of customs may take samples 95. Addition or deduction of new or altered duties in the case of contract 96. Declarations to give a full and true account Customs Act 1960 2020 Ed. 4 Informal Consolidation – version in force from 1/3/2024 Section 97. Agents and employees 98. Director‑General may charge rates, etc. 98A. Late payment charges and interest 98B. Power to appoint agent, etc., for recovery of duty 98C. Indemnification of agent 99. Securities for payment of duty and compliance with this Act 100. Appeal from decision of Director‑General PART 13 SEARCH, SEIZURE AND ARREST 101. Issue of search warrant 102. Power of Magistrate, etc., to enter and search 103. When search may be made without warrant 103A. Power to have access to, inspect and check operation of computer and other5678 examine09014590 5 200 Ed. ation from/4 Section 10. anner1123245ation1alation0ation)3(4”” territory ) s Act0 9 20 Ed. ationeded goodsfree trade zone” area in Singapore which has to zoneGovernmentGreen Ed0 [23 we4] “ version1 as“ (b(c of customs appointed under section 4(4); (d of customs officer t[ S ] 2A22 Consolid9 Consolid not9(11 6*,[20 02[* be[Act of 0 weA[B[2 offence shall be to exceeding $3 offence Custom 0 2 Ed. 70 04 4 section — “ “public[1] (Bag2 “section Consolid. Consolid Consolid Consolid1-d2.e1.e.e1.2[1 111 there .e 11”; fac.e11 pres.e121.e . </text> What is the correct answer to this question: How do the Customs Act Malaysia1 differ in penalties, and what do suggest about? Choices: (A) The Singapore emphasizes while the Malaysia. (B) Singapore while the len. (C) Singapore while the Malaysia. (D) Both acts but Singapore, while the, indicating. Format your response as follows: "The correct answer is (insert answer here)".
330
null
1
B
The Singapore Customs Act focuses on strict enforcement by imposing higher penalties, including mandatory imprisonment for serious customs duty evasion, while the Malaysia Customs Act permits fines without imprisonment in specific instances, reflecting a more lenient approach in less serious cases.
Please read the following text and answer the question below. <text> THE STATUTES OF THE REPUBLIC OF SINGAPORE CUSTOMS ACT 1960 2020 REVISED EDITION This revised edition incorporates all amendments up to and including 1 December 2021 and comes into operation on 31 December 2021. Prepared and Published by THE LAW REVISION COMMISSION UNDER THE AUTHORITY OF THE REVISED EDITION OF THE LAWS ACT 1983 Informal Consolidation – version in force from 1/3/2024 Customs Act 1960 ARRANGEMENT OF SECTIONS PART 1 PRELIMINARY Section 1. Short title 2. Scope of Act 3. Interpretation PART 2 APPOINTMENT OF OFFICERS 4. Appointment of Director‑General and other officers 5. Powers of Director‑General to delegate 6. Officers of customs to be public servants 6A. Officers of customs to be armed 7. Powers of police officers 8. Authority card to be produced 9. Persons employed on customs duty to be deemed proper officers of customs PART 3 LEVYING OF DUTY AND TAX 10. Levying of duties 11. Power of Director‑General to waive duty, etc. 12. Measuring and testing by proper officers of customs 13. Power of Minister to exempt 14. Reimposition of customs duty or excise duty 15. Remission of customs duty or excise duty on goods lost, damaged or destroyed before removal from customs control 16. Rebate for motor cars 17. Tax on motor vehicles using heavy fuel oil, etc. 17A. Exemption from, and other changes in liability to, special tax 17B. Presumptions relating to special tax 18. Recovery of special tax in arrears Informal Consolidation – version in force from 1/3/2024 1 2020 Ed. Section 19. Claims for duties, taxes, fees and other charges overpaid or erroneously paid 20. Payment of duty, etc., short levied or erroneously refunded 21. Calculation of duty 22. Value of imported or locally-manufactured goods, other than motor spirit, for excise duty 22A. Value of imported goods for customs duty 22B. Objection and appeal on valuation 23. Value of imported and locally-manufactured motor spirit 24. Value of motor spirit where variation in price 25. Value of motor spirit which is uncustomed, not retailed in Singapore under a trade name or where retailers’ pump price is not available 26. Question as to price of motor spirit to be decided by Director‑General 27. Removal of dutiable goods from customs control 28. Time of importation when duty is imposed 29. Customs rulings 30. Import of trade samples PART 4 IMPORTATION AND EXPORTATION 31. Place of import, export or transhipment 32. Registration of importers and agencies in respect of goods made dutiable 33. Import and export to be in accordance with regulations 34. Permit to remove goods 35. [Repealed] 36. Goods removed in accordance with declaration not to be relanded 37. Declaration 38. Power to prohibit imports and exports 39. Particulars of goods inwards to be furnished 40. Correction to be made on completion of discharge 41. Particulars of goods exported to be furnished 42. Liability in respect of duty for goods unaccounted for, etc. Customs Act 1960 2020 Ed. 2 Informal Consolidation – version in force from 1/3/2024 PART 5 GENERAL PROVISIONS AFFECTING AIRCRAFT AND VESSELS IN TERRITORIAL WATERS Section 43. Master of vessel to obey signals from preventive vessels and instructions by officer of customs 44. Goods not specified in manifest to be deemed uncustomed 45. Missing goods deemed to have been illegally landed 46. Accommodation in vessel to be provided for proper officer of customs 47. Power to lock up goods dutiable on import 48. Prohibition of carriage of dutiable goods in local craft PART 6 WAREHOUSING 49. Government warehouses 50. [Repealed] 51. Licensed warehouses 52. Dutiable goods to be deposited in free trade zone 53. Warehouse deposit receipts 54. Power to open and examine goods or packages 55. Detention of goods where doubt exists 56. Protection of Government from liability 57. Protection of officers of customs from liability 58. Payment of warehouse rent 59. Removal of dutiable goods from customs control 60. Landing of dutiable goods for transhipment 61. Storage of dutiable goods 62. Weighing and handling PART 7 MANUFACTURE AND BOTTLING 63. Licence to manufacture dutiable goods 64. No person except licensee to keep a still, etc. 65. [Repealed] 66. Bottling warehouse 67. Prohibition on keeping of utensil, apparatus, etc., for bottling, blending, etc. 68. Exemption Customs Act 1960 3 2020 Ed. Informal Consolidation – version in force from 1/3/2024 Section 69. Power to enter licensed premises PART 8 70. to 77. [Repealed] PART 9 DRAWBACK 78. Drawback on imported tobacco manufactured in Singapore 79. Drawback on imported goods on which duty has been paid 80. Declaration by claimant 81. Drawback on goods used in manufacture PART 10 DUTY FREE SHOPS FOR TOURISTS 82. Duty free shops for tourists PART 11 COMPOSITE LICENCE 83. Grant of composite licence 84. [Repealed] PART 12 MISCELLANEOUS PROVISIONS 85. Documents to be produced on demand 86. Computer service 87. Preservation of records 88. Power of Director‑General to obtain information and furnishing of information 89. Information not to be published or disclosed 90. Retention of trade documents 91. Persons bound to give information or produce documents 92. Service of notices 93. Baggage of passengers 94. Proper officer of customs may take samples 95. Addition or deduction of new or altered duties in the case of contract 96. Declarations to give a full and true account Customs Act 1960 2020 Ed. 4 Informal Consolidation – version in force from 1/3/2024 Section 97. Agents and employees 98. Director‑General may charge rates, etc. 98A. Late payment charges and interest 98B. Power to appoint agent, etc., for recovery of duty 98C. Indemnification of agent 99. Securities for payment of duty and compliance with this Act 100. Appeal from decision of Director‑General PART 13 SEARCH, SEIZURE AND ARREST 101. Issue of search warrant 102. Power of Magistrate, etc., to enter and search 103. When search may be made without warrant 103A. Power to have access to, inspect and check operation of computer and other5678 examine09014590 5 200 Ed. ation from/4 Section 10. anner1123245ation1alation0ation)3(4”” territory ) s Act0 9 20 Ed. ationeded goodsfree trade zone” area in Singapore which has to zoneGovernmentGreen Ed0 [23 we4] “ version1 as“ (b(c of customs appointed under section 4(4); (d of customs officer t[ S ] 2A22 Consolid9 Consolid not9(11 6*,[20 02[* be[Act of 0 weA[B[2 offence shall be to exceeding $3 offence Custom 0 2 Ed. 70 04 4 section — “ “public[1] (Bag2 “section Consolid. Consolid Consolid Consolid1-d2.e1.e.e1.2[1 111 there .e 11”; fac.e11 pres.e121.e . </text> What is the correct answer to this question: How do the Customs Act Malaysia1 differ in penalties, and what do suggest about? Choices: (A) The Singapore emphasizes while the Malaysia. (B) Singapore while the len. (C) Singapore while the Malaysia. (D) Both acts but Singapore, while the, indicating. Format your response as follows: "The correct answer is (insert answer here)".
null
null
null
429,418
null
331
length>350000
3
D
Power system
Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> { "meta": { "name_exp": "qwen2-72b_guessing_game_v1_1", "player_num": 10, "min": 0, "max": 100, "ratio": 0.6666666666666666, "ratio_str": "2/3", "round_id": 20, "version": "v1" }, "round_records": [ { "responses": [ 33, 50, 50, 33, 66, 33, 50, 66, 66, 33 ], "mean": 48, "mean_ratio": 32.0, "winner": 33, "winner_num": 4 }, { "responses": [ 22, 30, 30, 33, 40, 21, 40, 40, 33, 22 ], "mean": 31.1, "mean_ratio": 20.733333333333334, "winner": 21, "winner_num": 1 }, { "responses": [ 22, 25, 20, 15, 27, 25, 20, 25, 16, 15 ], "mean": 21, "mean_ratio": 14.0, "winner": 15, "winner_num": 2 }, { "responses": [ 13, 13, 16, 18, 12, 20, 20, 18, 13, 12 ], "mean": 15.5, "mean_ratio": 10.333333333333332, "winner": 12, "winner_num": 2 }, { "responses": [ 15, 10, 10, 16, 9, 10, 9, 13, 10, 14 ], "mean": 11.6, "mean_ratio": 7.7333333333333325, "winner": 9, "winner_num": 2 }, { "responses": [ 10, 10, 10, 8, 12, 7, 8, 7, 8, 7 ], "mean": 8.7, "mean_ratio": 5.799999999999999, "winner": 7, "winner_num": 3 }, { "responses": [ 6, 7, 6, 6, 8, 6, 6, 8, 9, 6 ], "mean": 6.8, "mean_ratio": 4.533333333333333, "winner": 6, "winner_num": 6 }, { "responses": [ 5, 6, 6, 5, 8, 5, 5, 4, 5, 6 ], "mean": 5.5, "mean_ratio": 3.6666666666666665, "winner": 4, "winner_num": 1 }, { "responses": [ 3, 6, 4, 4, 4, 4, 4, 5, 4, 4 ], "mean": 4.2, "mean_ratio": 2.8, "winner": 3, "winner_num": 1 }, { "responses": [ 3, 3, 4, 2, 5, 3, 3, 3, 3, 3 ], "mean": 3.2, "mean_ratio": 2.1333333333333333, "winner": 2, "winner_num": 1 }, { "responses": [ 4, 2, 2, 2, 2, 2, 2, 2, 3, 2 ], "mean": 2.3, "mean_ratio": 1.5333333333333332, "winner": 2, "winner_num": 8 }, { "responses": [ 2, 2, 2, 2, 2, 2, 2, 2, 3, 2 ], "mean": 2.1, "mean_ratio": 1.4, "winner": 2, "winner_num": 9 }, { "responses": [ 2, 2, 2, 2, 2, 2, 2, 2, 2, 2 ], "mean": 2, "mean_ratio": 1.3333333333333333, "winner": 2, "winner_num": 10 }, { "responses": [ 2, 2, 2, 2, 2, 2, 2, 2, 2, 2 ], "mean": 2, "mean_ratio": 1.3333333333333333, "winner": 2, "winner_num": 10 }, { "responses": [ 2, 2, 2, 2, 2, 2, 2, 2, 2, 2 ], "mean": 2, "mean_ratio": 1.3333333333333333, "winner": 2, "winner_num": 10 }, { "responses": [ 2, 2, 2, 2, 2, 2, 2, 2, 2, 2 ], "mean": 2, "mean_ratio": 1.3333333333333333, "winner": 2, "winner_num": 10 }, { "responses": [ 2, 2, 2, 2, 2, 2, 2, 2, 2, 2 ], "mean": 2, "mean_ratio": 1.3333333333333333, "winner": 2, "winner_num": 10 }, { "responses": [ 2, 2, 2, 2, 2, 2, 2, 2, 2, 2 ], "mean": 2, "mean_ratio": 1.3333333333333333, "winner": 2, "winner_num": 10 }, { "responses": [ 2, 2, 2, 2, 2, 2, 2, 2, 2, 2 ], "mean": 2, "mean_ratio": 1.3333333333333 Ch </text> What is the correct to this question: Which following player least in? Choices: (A) (B)_ (C) (D) Format your response as follows: "The correct answer is (insert answer here)".
332
null
1
B
player_3
Please read the following text and answer the question below. <text> { "meta": { "name_exp": "qwen2-72b_guessing_game_v1_1", "player_num": 10, "min": 0, "max": 100, "ratio": 0.6666666666666666, "ratio_str": "2/3", "round_id": 20, "version": "v1" }, "round_records": [ { "responses": [ 33, 50, 50, 33, 66, 33, 50, 66, 66, 33 ], "mean": 48, "mean_ratio": 32.0, "winner": 33, "winner_num": 4 }, { "responses": [ 22, 30, 30, 33, 40, 21, 40, 40, 33, 22 ], "mean": 31.1, "mean_ratio": 20.733333333333334, "winner": 21, "winner_num": 1 }, { "responses": [ 22, 25, 20, 15, 27, 25, 20, 25, 16, 15 ], "mean": 21, "mean_ratio": 14.0, "winner": 15, "winner_num": 2 }, { "responses": [ 13, 13, 16, 18, 12, 20, 20, 18, 13, 12 ], "mean": 15.5, "mean_ratio": 10.333333333333332, "winner": 12, "winner_num": 2 }, { "responses": [ 15, 10, 10, 16, 9, 10, 9, 13, 10, 14 ], "mean": 11.6, "mean_ratio": 7.7333333333333325, "winner": 9, "winner_num": 2 }, { "responses": [ 10, 10, 10, 8, 12, 7, 8, 7, 8, 7 ], "mean": 8.7, "mean_ratio": 5.799999999999999, "winner": 7, "winner_num": 3 }, { "responses": [ 6, 7, 6, 6, 8, 6, 6, 8, 9, 6 ], "mean": 6.8, "mean_ratio": 4.533333333333333, "winner": 6, "winner_num": 6 }, { "responses": [ 5, 6, 6, 5, 8, 5, 5, 4, 5, 6 ], "mean": 5.5, "mean_ratio": 3.6666666666666665, "winner": 4, "winner_num": 1 }, { "responses": [ 3, 6, 4, 4, 4, 4, 4, 5, 4, 4 ], "mean": 4.2, "mean_ratio": 2.8, "winner": 3, "winner_num": 1 }, { "responses": [ 3, 3, 4, 2, 5, 3, 3, 3, 3, 3 ], "mean": 3.2, "mean_ratio": 2.1333333333333333, "winner": 2, "winner_num": 1 }, { "responses": [ 4, 2, 2, 2, 2, 2, 2, 2, 3, 2 ], "mean": 2.3, "mean_ratio": 1.5333333333333332, "winner": 2, "winner_num": 8 }, { "responses": [ 2, 2, 2, 2, 2, 2, 2, 2, 3, 2 ], "mean": 2.1, "mean_ratio": 1.4, "winner": 2, "winner_num": 9 }, { "responses": [ 2, 2, 2, 2, 2, 2, 2, 2, 2, 2 ], "mean": 2, "mean_ratio": 1.3333333333333333, "winner": 2, "winner_num": 10 }, { "responses": [ 2, 2, 2, 2, 2, 2, 2, 2, 2, 2 ], "mean": 2, "mean_ratio": 1.3333333333333333, "winner": 2, "winner_num": 10 }, { "responses": [ 2, 2, 2, 2, 2, 2, 2, 2, 2, 2 ], "mean": 2, "mean_ratio": 1.3333333333333333, "winner": 2, "winner_num": 10 }, { "responses": [ 2, 2, 2, 2, 2, 2, 2, 2, 2, 2 ], "mean": 2, "mean_ratio": 1.3333333333333333, "winner": 2, "winner_num": 10 }, { "responses": [ 2, 2, 2, 2, 2, 2, 2, 2, 2, 2 ], "mean": 2, "mean_ratio": 1.3333333333333333, "winner": 2, "winner_num": 10 }, { "responses": [ 2, 2, 2, 2, 2, 2, 2, 2, 2, 2 ], "mean": 2, "mean_ratio": 1.3333333333333333, "winner": 2, "winner_num": 10 }, { "responses": [ 2, 2, 2, 2, 2, 2, 2, 2, 2, 2 ], "mean": 2, "mean_ratio": 1.3333333333333 Ch </text> What is the correct to this question: Which following player least in? Choices: (A) (B)_ (C) (D) Format your response as follows: "The correct answer is (insert answer here)".
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Please read the following text and answer the question below. <text> Metis: File System Model Checking via Versatile Input and State Exploration Stony Brook University, ∗Nimble Research, +Harvey Mudd College Abstract We present Metis, a model-checking framework designed for versatile, thorough, yet configurable file system testing in the form of input and state exploration. It uses a nondeterministic loop and a weighting scheme to decide which system calls and their arguments to execute. Metis features a new abstract state representation for file-system states in support of efficient and effective state exploration. While exploring states, it compares the behavior of a file system under test against a reference file system and reports any discrepancies; it also provides support to investigate and reproduce any that are found. We also developed RefFS, a small, fast file system that serves as a reference, with special features designed to accelerate model checking and en- hance bug reproducibility. Experimental results show that Metis can flexibly generate test inputs; also the rate at which it explores file-system states scales nearly linearly across multiple nodes. RefFS explores states 3–28× faster than other, more mature file systems. Metis aided the development of RefFS, reporting 11 bugs that we subsequently fixed. Metis further identified 12 bugs from five other file systems, five of which were confirmed and with one fixed and integrated into Linux. 1 Introduction File system testing is an essential technique for finding bugs [43] and enhancing overall system reliability [27], as file-system bugs can have severe consequences [53,92]. Effective testing of file systems is challenging, however, due to their inherent complexity [4], including many corner cases [87], myriad functionalities [8], and consistency requirements (e.g., crash con- sistency [64,72]). Developers have created various testing tech- nologies [59,71,86] for file systems, but new bugs (both in-kernel and non-kernel) continue to emerge on a regular basis [42,43,85]. To expose a file-system bug, a testing tool must execute a particular system call using specific inputs on a given file-system state [52,53,87]. For example, identifying a well-known Ext4 bug [48] requires a write operation on a file initialized with a 530-byte data segment. In this case, the write operation is an input, and the file with a specific size constitutes (part of) the file-system state. Recent work [9, 52] also underscored the importance of adequately covering both file-system inputs and states during testing. While existing testing technologies seek to cover a broad range of file systems’ functionality, they often do not, however, integrate coverage of both file-system inputs and states [12,43,59,85]. For example, handwritten regression tools like xfstests [71] can achieve good test coverage of specific file-system features [4,58], but do not comprehensively cover syscall inputs; similarly, fuzzing techniques (e.g., Syzkaller [25]) are designed to maximize code—not input—coverage [40]. Both the input and state spaces of file systems are too vast to be completely explored and tested [10,21], so it is better to leverage finite resources by focusing on the most pertinent inputs and states [52,86,88]. For example, metadata-altering operations, such as link and rename, and states with a complex directory structure are more frequently utilized in POSIX-compliance testing [67]. Existing testing technologies also lack the versatility to test specific inputs and states [25,59,71]. Thus, new testing tools and techniques are needed [52,53] to avoid under-testing (which could miss potential bugs) or over-testing (which wastes resources that may be better deployed elsewhere). This paper presents Metis, a novel model-checking framework that enables thorough and versatile input and state space exploration of file systems. Metis runs two file systems concurrently: a file system under test and a reference file system to compare against [26]. Metis issues file-system operations (i.e., system calls with arguments) as inputs to both file systems while simultaneously monitoring and exploring the state space via graph search (e.g., depth-first search [31]). To compare the relevant aspects of file-system states, we first abstract them and then compare the abstractions. The abstract states include file data, directory structure, and essential metadata; abstract states constitute the state space to be explored. Metis first nondeterministically selects an operation and then fills in syscall arguments through a user-specified weighting scheme. Next, it executes the same operation in both file systems and then compares both systems’ abstract states. Any discrepancy is flagged as a potential bug. Metis evaluates the post-operation states to decide if a state has been previously explored; if so, it backtracks to a parent state and selects a new state to explore [31]. Metis continuously tests new file-system states until no additional unexplored states remain, logging all operations and visited states for subsequent analysis. Metis’s replayer can reproduce potential bugs with minimum time and effort. Metis effectively addresses the common challenges of model checking [16, 31] file systems. It checks file-system implementations directly, eliminating the need to build a formal model [61]. To manage large file-system input and state spaces, Metis enables parallel and distributed exploration [33] across multiple cores and machines. Metis works with any kernel or user file system, and does not require any specific utilities nor any modification or instrumentation of the kernel or the file USENIX Association 22nd USENIX Conference on File and Storage Technologies 123 system. It detects bugs by identifying behavioral discrepancies between two file systems without the need for oracles or external checkers, thus simplifying the process of applying Metis to new file systems. With few constraints, Metis is well suited for testing file systems that are challenging for other testing approaches, e.g., file system fuzzing [43], that require kernel instrumentation and utilities. Nevertheless, the quality of the reference file system is pivotal for assessing the behavior of other file systems [26]. We therefore developed RefFS as Metis’s reference file system. RefFS is an in-memory user-space POSIX file system with new APIs for efficient state checkpointing and restoration [73,86]. Prior to using RefFS as our reference file system, we used Ext4 as the reference to check RefFS itself; Metis identified 11 RefFS bugs that we fixed during that process. Subsequently, we deployed 18 distributed Metis instances to compare RefFS and Ext4 for one month, totaling 557 compute days across all instances and executing over 3 billion file-system operations without detecting any discrepancy. This ensured that RefFS is robust enough to serve as Metis’s (fast) reference file system. Our experiments show that Metis can configure inputs more flexibly and cover more diverse inputs compared to other file-system testing tools [25, 59, 71]. Metis’s exploration rate scales nearly linearly with the number of Metis instances, also known as verification tasks (VTs). Despite being a user-level file system, RefFS’s states can be explored by Metis 3–28× faster than other popular in-kernel file systems (e.g., Ext4, XFS, Btrfs). Using Metis and RefFS, we discovered 12 potential bugs across five file systems. Of these, 10 were confirmed as previously unknown bugs, five of which were confirmed by developers as real bugs. Moreover, one of those bugs—which the developers confirmed existed for 16 years—and the fix we provided, was recently integrated into mainline Linux. In sum, this paper makes the following contributions: 1. We designed and implemented Metis, a model-checking framework for versatile and thorough file-system input and state-space exploration. 2. We designed and implemented an effective abstract state representation for file systems and a corresponding differential state checker. 3. We designed and implemented the RefFS reference file system with novel APIs that accelerate and simplify the model-checking process. 4. Using RefFS, we evaluated Metis’s input and state coverage, scalability, and performance. Our results show that Metis, together with RefFS, (82N e 3N1eN Problem can-consuming0 significant. To-space exploration2]22 Association 2 2 (1302NUSE 3112 we omit 2FF12eN22 and1AThe1N[]1[12111211[331125 Z21N[]111USE 1 [811[92. [1. 140 22N USEN Association </text> What is the correct answer to this question: How does Metis manage Ref? Choices: (A) uses to. (B. (C) Met. (D)is. Format your response as follows: "The correct answer is (insert answer here)".
333
null
0
A
Metis uses special API to command RefFS to save its state in the memory.
Please read the following text and answer the question below. <text> Metis: File System Model Checking via Versatile Input and State Exploration Stony Brook University, ∗Nimble Research, +Harvey Mudd College Abstract We present Metis, a model-checking framework designed for versatile, thorough, yet configurable file system testing in the form of input and state exploration. It uses a nondeterministic loop and a weighting scheme to decide which system calls and their arguments to execute. Metis features a new abstract state representation for file-system states in support of efficient and effective state exploration. While exploring states, it compares the behavior of a file system under test against a reference file system and reports any discrepancies; it also provides support to investigate and reproduce any that are found. We also developed RefFS, a small, fast file system that serves as a reference, with special features designed to accelerate model checking and en- hance bug reproducibility. Experimental results show that Metis can flexibly generate test inputs; also the rate at which it explores file-system states scales nearly linearly across multiple nodes. RefFS explores states 3–28× faster than other, more mature file systems. Metis aided the development of RefFS, reporting 11 bugs that we subsequently fixed. Metis further identified 12 bugs from five other file systems, five of which were confirmed and with one fixed and integrated into Linux. 1 Introduction File system testing is an essential technique for finding bugs [43] and enhancing overall system reliability [27], as file-system bugs can have severe consequences [53,92]. Effective testing of file systems is challenging, however, due to their inherent complexity [4], including many corner cases [87], myriad functionalities [8], and consistency requirements (e.g., crash con- sistency [64,72]). Developers have created various testing tech- nologies [59,71,86] for file systems, but new bugs (both in-kernel and non-kernel) continue to emerge on a regular basis [42,43,85]. To expose a file-system bug, a testing tool must execute a particular system call using specific inputs on a given file-system state [52,53,87]. For example, identifying a well-known Ext4 bug [48] requires a write operation on a file initialized with a 530-byte data segment. In this case, the write operation is an input, and the file with a specific size constitutes (part of) the file-system state. Recent work [9, 52] also underscored the importance of adequately covering both file-system inputs and states during testing. While existing testing technologies seek to cover a broad range of file systems’ functionality, they often do not, however, integrate coverage of both file-system inputs and states [12,43,59,85]. For example, handwritten regression tools like xfstests [71] can achieve good test coverage of specific file-system features [4,58], but do not comprehensively cover syscall inputs; similarly, fuzzing techniques (e.g., Syzkaller [25]) are designed to maximize code—not input—coverage [40]. Both the input and state spaces of file systems are too vast to be completely explored and tested [10,21], so it is better to leverage finite resources by focusing on the most pertinent inputs and states [52,86,88]. For example, metadata-altering operations, such as link and rename, and states with a complex directory structure are more frequently utilized in POSIX-compliance testing [67]. Existing testing technologies also lack the versatility to test specific inputs and states [25,59,71]. Thus, new testing tools and techniques are needed [52,53] to avoid under-testing (which could miss potential bugs) or over-testing (which wastes resources that may be better deployed elsewhere). This paper presents Metis, a novel model-checking framework that enables thorough and versatile input and state space exploration of file systems. Metis runs two file systems concurrently: a file system under test and a reference file system to compare against [26]. Metis issues file-system operations (i.e., system calls with arguments) as inputs to both file systems while simultaneously monitoring and exploring the state space via graph search (e.g., depth-first search [31]). To compare the relevant aspects of file-system states, we first abstract them and then compare the abstractions. The abstract states include file data, directory structure, and essential metadata; abstract states constitute the state space to be explored. Metis first nondeterministically selects an operation and then fills in syscall arguments through a user-specified weighting scheme. Next, it executes the same operation in both file systems and then compares both systems’ abstract states. Any discrepancy is flagged as a potential bug. Metis evaluates the post-operation states to decide if a state has been previously explored; if so, it backtracks to a parent state and selects a new state to explore [31]. Metis continuously tests new file-system states until no additional unexplored states remain, logging all operations and visited states for subsequent analysis. Metis’s replayer can reproduce potential bugs with minimum time and effort. Metis effectively addresses the common challenges of model checking [16, 31] file systems. It checks file-system implementations directly, eliminating the need to build a formal model [61]. To manage large file-system input and state spaces, Metis enables parallel and distributed exploration [33] across multiple cores and machines. Metis works with any kernel or user file system, and does not require any specific utilities nor any modification or instrumentation of the kernel or the file USENIX Association 22nd USENIX Conference on File and Storage Technologies 123 system. It detects bugs by identifying behavioral discrepancies between two file systems without the need for oracles or external checkers, thus simplifying the process of applying Metis to new file systems. With few constraints, Metis is well suited for testing file systems that are challenging for other testing approaches, e.g., file system fuzzing [43], that require kernel instrumentation and utilities. Nevertheless, the quality of the reference file system is pivotal for assessing the behavior of other file systems [26]. We therefore developed RefFS as Metis’s reference file system. RefFS is an in-memory user-space POSIX file system with new APIs for efficient state checkpointing and restoration [73,86]. Prior to using RefFS as our reference file system, we used Ext4 as the reference to check RefFS itself; Metis identified 11 RefFS bugs that we fixed during that process. Subsequently, we deployed 18 distributed Metis instances to compare RefFS and Ext4 for one month, totaling 557 compute days across all instances and executing over 3 billion file-system operations without detecting any discrepancy. This ensured that RefFS is robust enough to serve as Metis’s (fast) reference file system. Our experiments show that Metis can configure inputs more flexibly and cover more diverse inputs compared to other file-system testing tools [25, 59, 71]. Metis’s exploration rate scales nearly linearly with the number of Metis instances, also known as verification tasks (VTs). Despite being a user-level file system, RefFS’s states can be explored by Metis 3–28× faster than other popular in-kernel file systems (e.g., Ext4, XFS, Btrfs). Using Metis and RefFS, we discovered 12 potential bugs across five file systems. Of these, 10 were confirmed as previously unknown bugs, five of which were confirmed by developers as real bugs. Moreover, one of those bugs—which the developers confirmed existed for 16 years—and the fix we provided, was recently integrated into mainline Linux. In sum, this paper makes the following contributions: 1. We designed and implemented Metis, a model-checking framework for versatile and thorough file-system input and state-space exploration. 2. We designed and implemented an effective abstract state representation for file systems and a corresponding differential state checker. 3. We designed and implemented the RefFS reference file system with novel APIs that accelerate and simplify the model-checking process. 4. Using RefFS, we evaluated Metis’s input and state coverage, scalability, and performance. Our results show that Metis, together with RefFS, (82N e 3N1eN Problem can-consuming0 significant. To-space exploration2]22 Association 2 2 (1302NUSE 3112 we omit 2FF12eN22 and1AThe1N[]1[12111211[331125 Z21N[]111USE 1 [811[92. [1. 140 22N USEN Association </text> What is the correct answer to this question: How does Metis manage Ref? Choices: (A) uses to. (B. (C) Met. (D)is. Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> Two Vietnamese illegal workers were jailed by the Shatin Magistrates' Courts yesterday (September 19). During operation "Twilight" conducted on September 16, Immigration Department (ImmD) investigators raided a food factory in Tuen Mun district. Two Vietnamese men, aged 32 and 49, were arrested while working as odd-job workers. The illegal workers were charged at the Shatin Magistrates' Courts on September 19 with taking employment after landing in Hong Kong unlawfully and remaining in Hong Kong without the authority of the Director of Immigration, and taking employment while being a person in respect of whom a removal order or deportation order was in force respectively. They pleaded guilty to the charges and were sentenced to 15 months' imprisonment. Meanwhile, one of the males was also charged with one count of remaining in Hong Kong without the authority of the Director after landing in Hong Kong unlawfully. He was sentenced to 15 months' imprisonment, with parts of the sentences to run consecutively, making a total of 18 months' imprisonment. The ImmD spokesman warned that, as stipulated in section 38AA of the Immigration Ordinance, an illegal immigrant, a person who is the subject of a removal order or a deportation order, an overstayer or a person who was refused permission to land is prohibited from taking any employment, whether paid or unpaid, or establishing or joining in any business. Offenders are liable upon conviction to a maximum fine of $50,000 and up to three years' imprisonment. Under the prevailing laws, it is an offence to use or possess a forged Hong Kong identity card or a Hong Kong identity card related to another person. Offenders are liable to prosecution and upon conviction face a maximum penalty of a $100,000 fine and up to 10 years' imprisonment. The spokesman reiterated that it is a serious offence to employ people who are not lawfully employable. Under the Immigration Ordinance, the maximum penalty for an employer employing a person who is not lawfully employable, i.e. an illegal immigrant, a person who is the subject of a removal order or a deportation order, an overstayer or a person who was refused permission to land, has been significantly increased from a fine of $350,000 and three years' imprisonment to a fine of $500,000 and 10 years' imprisonment to reflect the gravity of such offences. The director, manager, secretary, partner, etc, of the company concerned may also bear criminal liability. The High Court has laid down sentencing guidelines that the employer of an illegal worker should be given an immediate custodial sentence. According to the court sentencing, employers must take all practicable steps to determine whether a person is lawfully employable prior to employment. Apart from inspecting a prospective employee's identity card, the employer has the explicit duty to make enquiries regarding the person and ensure that the answers would not cast any reasonable doubt concerning the lawful employability of the person. The court will not accept failure to do so as a defence in proceedings. It is also an offence if an employer fails to inspect the job seeker's valid travel document if the job seeker does not have a Hong Kong permanent identity card. Offenders are liable upon conviction to a maximum fine of $150,000 and to imprisonment for one year. In that connection, the spokesman would like to remind all employers not to defy the law by employing illegal workers. The ImmD will continue to take resolute enforcement action to combat such offences. Under the existing mechanism, the ImmD will, as a standard procedure, conduct an initial screening of vulnerable persons, including illegal workers, illegal immigrants, sex workers and foreign domestic helpers, who are arrested during any operation with a view to ascertaining whether they are trafficking in persons (TIP) victims. When any TIP indicator is revealed in the initial screening, the officers will conduct a full debriefing and identification by using a standardised checklist to ascertain the presence of TIP elements, such as threats and coercion in the recruitment phase and the nature of exploitation. Identified TIP victims will be provided with various forms of support and assistance, including urgent intervention, medical services, counselling, shelter, temporary accommodation and other supporting services. The ImmD calls on TIP victims to report crimes to the relevant departments immediately. he Immigration Department (ImmD) mounted a series of territory-wide anti-illegal worker operations codenamed "Contribute" and "Twilight", and joint operations with the Hong Kong Police Force codenamed "Champion" and "Windsand", on September 16, 17, and yesterday (September 19). A total of 16 suspected illegal workers and one suspected employer were arrested. During the anti-illegal worker operations, ImmD Task Force officers raided 21 target locations including commercial buildings, a food factory, premises under renovation and restaurants. Fourteen suspected illegal workers and one suspected employer were arrested. The arrested suspected illegal workers comprised eight men and six women, aged 27 to 55. Among them, one man was a holder of recognisance form, which prohibits him from taking any employment. In addition, one man was suspected of using and being in possession of a forged Hong Kong identity card. One man, aged 40, was suspected of employing the illegal worker and was also arrested. During operation "Champion", enforcement officers raided 10 target locations in Central district. Two suspected illegal workers were arrested. The arrested suspected illegal workers comprised two women, aged 37 and 56. They were also suspected of using and being in possession of a forged Hong Kong identity card. An ImmD spokesman said, "Any person who contravenes a condition of stay in force in respect of him or her shall be guilty of an offence. Also, visitors are not allowed to take employment in Hong Kong, whether paid or unpaid, without the permission of the Director of Immigration. Offenders are liable to prosecution and upon conviction face a maximum fine of $50,000 and up to two years' imprisonment. Aiders and abettors are also liable to prosecution and penalties." The spokesman warned, "As stipulated in section 38AA of the Immigration Ordinance, an illegal immigrant, a person who is the subject of a removal order or a deportation order, an overstayer or a person who was refused permission to land is prohibited from taking any employment, whether paid or unpaid, or establishing or joining in any business. Offenders are liable upon conviction to a maximum fine of $50,000 and up to three years' imprisonment. Under the prevailing laws, it is an offence to use or possess a forged Hong Kong identity card or a Hong Kong identity card related to another person. Offenders are liable to prosecution and upon conviction face a maximum fine of $100,000 and up to 10 years' imprisonment." The spokesman reiterated that it is a serious offence to employ people who are not lawfully employable. Under the Immigration Ordinance, the maximum penalty for an employer employing a person who is not lawfully employable, i.e. an illegal immigrant, a person who is the subject of a removal order or a deportation order, an overstayer or a person who was refused permission to land, has been significantly increased from a fine of $350,000 and three years' imprisonment to a fine of $500,000 and 10 years' imprisonment to reflect the gravity of such offences. The director, manager, secretary, partner, etc, of the company concerned may also bear criminal liability. The High Court has laid down sentencing guidelines that the employer of an illegal worker should be given an immediate custodial sentence. According to the court sentencing, employers must take all practicable steps to determine whether a person is lawfully employable prior to employment. Apart from inspecting a prospective employee's identity card, the employer has the explicit duty to make enquiries regarding the person and ensure that the answers would not cast any reasonable doubt concerning the lawful employability of the person. The court will not accept failure to do so as a defence in proceedings. It is also an offence if an employer fails to inspect the job seeker's valid travel document if the job seeker does not have a Hong Kong permanent identity card. Offenders are liable upon conviction to a maximum fine of $150,000 and to imprisonment for one year. In that connection, the spokesman reminded all employers not to defy the law by employing illegal workers. The ImmD will continue to take resolute enforcement action to combat such offences. Under the existing mechanism, the ImmD will, as a standard procedure, conduct an initial screening of vulnerable persons, including illegal workers, illegal immigrants, sex workers and foreign domestic helpers, who are arrested during any operation with a view to ascertaining whether they are trafficking in persons (TIP) victims. When any TIP indicator is revealed in the initial screening, the ImmD officers will conduct a full debriefing and identification by using a standardised checklist to ascertain the presence of TIP elements, such as threats and coercion in the recruitment phase and the nature of exploitation. Identified TIP victims will be provided with various forms of support and assistance, including urgent intervention, medical services, counselling, shelter or temporary accommodation and other supporting services. The ImmD calls on TIP victims to report crimes to the relevant departments immediately. A Pakistani illegal worker, holding a recognisance form, was jailed by Shatin Magistrates' Courts yesterday (September 16). During000 employ0</text> What is the correct answer to this question: The one correct? Choices: (A) the. (B)22. (C). (D). Format your response as follows: "The correct answer is (insert answer here)".
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Developing one-day tours can help boost Hong Kong's tourism industry.
Please read the following text and answer the question below. <text> Two Vietnamese illegal workers were jailed by the Shatin Magistrates' Courts yesterday (September 19). During operation "Twilight" conducted on September 16, Immigration Department (ImmD) investigators raided a food factory in Tuen Mun district. Two Vietnamese men, aged 32 and 49, were arrested while working as odd-job workers. The illegal workers were charged at the Shatin Magistrates' Courts on September 19 with taking employment after landing in Hong Kong unlawfully and remaining in Hong Kong without the authority of the Director of Immigration, and taking employment while being a person in respect of whom a removal order or deportation order was in force respectively. They pleaded guilty to the charges and were sentenced to 15 months' imprisonment. Meanwhile, one of the males was also charged with one count of remaining in Hong Kong without the authority of the Director after landing in Hong Kong unlawfully. He was sentenced to 15 months' imprisonment, with parts of the sentences to run consecutively, making a total of 18 months' imprisonment. The ImmD spokesman warned that, as stipulated in section 38AA of the Immigration Ordinance, an illegal immigrant, a person who is the subject of a removal order or a deportation order, an overstayer or a person who was refused permission to land is prohibited from taking any employment, whether paid or unpaid, or establishing or joining in any business. Offenders are liable upon conviction to a maximum fine of $50,000 and up to three years' imprisonment. Under the prevailing laws, it is an offence to use or possess a forged Hong Kong identity card or a Hong Kong identity card related to another person. Offenders are liable to prosecution and upon conviction face a maximum penalty of a $100,000 fine and up to 10 years' imprisonment. The spokesman reiterated that it is a serious offence to employ people who are not lawfully employable. Under the Immigration Ordinance, the maximum penalty for an employer employing a person who is not lawfully employable, i.e. an illegal immigrant, a person who is the subject of a removal order or a deportation order, an overstayer or a person who was refused permission to land, has been significantly increased from a fine of $350,000 and three years' imprisonment to a fine of $500,000 and 10 years' imprisonment to reflect the gravity of such offences. The director, manager, secretary, partner, etc, of the company concerned may also bear criminal liability. The High Court has laid down sentencing guidelines that the employer of an illegal worker should be given an immediate custodial sentence. According to the court sentencing, employers must take all practicable steps to determine whether a person is lawfully employable prior to employment. Apart from inspecting a prospective employee's identity card, the employer has the explicit duty to make enquiries regarding the person and ensure that the answers would not cast any reasonable doubt concerning the lawful employability of the person. The court will not accept failure to do so as a defence in proceedings. It is also an offence if an employer fails to inspect the job seeker's valid travel document if the job seeker does not have a Hong Kong permanent identity card. Offenders are liable upon conviction to a maximum fine of $150,000 and to imprisonment for one year. In that connection, the spokesman would like to remind all employers not to defy the law by employing illegal workers. The ImmD will continue to take resolute enforcement action to combat such offences. Under the existing mechanism, the ImmD will, as a standard procedure, conduct an initial screening of vulnerable persons, including illegal workers, illegal immigrants, sex workers and foreign domestic helpers, who are arrested during any operation with a view to ascertaining whether they are trafficking in persons (TIP) victims. When any TIP indicator is revealed in the initial screening, the officers will conduct a full debriefing and identification by using a standardised checklist to ascertain the presence of TIP elements, such as threats and coercion in the recruitment phase and the nature of exploitation. Identified TIP victims will be provided with various forms of support and assistance, including urgent intervention, medical services, counselling, shelter, temporary accommodation and other supporting services. The ImmD calls on TIP victims to report crimes to the relevant departments immediately. he Immigration Department (ImmD) mounted a series of territory-wide anti-illegal worker operations codenamed "Contribute" and "Twilight", and joint operations with the Hong Kong Police Force codenamed "Champion" and "Windsand", on September 16, 17, and yesterday (September 19). A total of 16 suspected illegal workers and one suspected employer were arrested. During the anti-illegal worker operations, ImmD Task Force officers raided 21 target locations including commercial buildings, a food factory, premises under renovation and restaurants. Fourteen suspected illegal workers and one suspected employer were arrested. The arrested suspected illegal workers comprised eight men and six women, aged 27 to 55. Among them, one man was a holder of recognisance form, which prohibits him from taking any employment. In addition, one man was suspected of using and being in possession of a forged Hong Kong identity card. One man, aged 40, was suspected of employing the illegal worker and was also arrested. During operation "Champion", enforcement officers raided 10 target locations in Central district. Two suspected illegal workers were arrested. The arrested suspected illegal workers comprised two women, aged 37 and 56. They were also suspected of using and being in possession of a forged Hong Kong identity card. An ImmD spokesman said, "Any person who contravenes a condition of stay in force in respect of him or her shall be guilty of an offence. Also, visitors are not allowed to take employment in Hong Kong, whether paid or unpaid, without the permission of the Director of Immigration. Offenders are liable to prosecution and upon conviction face a maximum fine of $50,000 and up to two years' imprisonment. Aiders and abettors are also liable to prosecution and penalties." The spokesman warned, "As stipulated in section 38AA of the Immigration Ordinance, an illegal immigrant, a person who is the subject of a removal order or a deportation order, an overstayer or a person who was refused permission to land is prohibited from taking any employment, whether paid or unpaid, or establishing or joining in any business. Offenders are liable upon conviction to a maximum fine of $50,000 and up to three years' imprisonment. Under the prevailing laws, it is an offence to use or possess a forged Hong Kong identity card or a Hong Kong identity card related to another person. Offenders are liable to prosecution and upon conviction face a maximum fine of $100,000 and up to 10 years' imprisonment." The spokesman reiterated that it is a serious offence to employ people who are not lawfully employable. Under the Immigration Ordinance, the maximum penalty for an employer employing a person who is not lawfully employable, i.e. an illegal immigrant, a person who is the subject of a removal order or a deportation order, an overstayer or a person who was refused permission to land, has been significantly increased from a fine of $350,000 and three years' imprisonment to a fine of $500,000 and 10 years' imprisonment to reflect the gravity of such offences. The director, manager, secretary, partner, etc, of the company concerned may also bear criminal liability. The High Court has laid down sentencing guidelines that the employer of an illegal worker should be given an immediate custodial sentence. According to the court sentencing, employers must take all practicable steps to determine whether a person is lawfully employable prior to employment. Apart from inspecting a prospective employee's identity card, the employer has the explicit duty to make enquiries regarding the person and ensure that the answers would not cast any reasonable doubt concerning the lawful employability of the person. The court will not accept failure to do so as a defence in proceedings. It is also an offence if an employer fails to inspect the job seeker's valid travel document if the job seeker does not have a Hong Kong permanent identity card. Offenders are liable upon conviction to a maximum fine of $150,000 and to imprisonment for one year. In that connection, the spokesman reminded all employers not to defy the law by employing illegal workers. The ImmD will continue to take resolute enforcement action to combat such offences. Under the existing mechanism, the ImmD will, as a standard procedure, conduct an initial screening of vulnerable persons, including illegal workers, illegal immigrants, sex workers and foreign domestic helpers, who are arrested during any operation with a view to ascertaining whether they are trafficking in persons (TIP) victims. When any TIP indicator is revealed in the initial screening, the ImmD officers will conduct a full debriefing and identification by using a standardised checklist to ascertain the presence of TIP elements, such as threats and coercion in the recruitment phase and the nature of exploitation. Identified TIP victims will be provided with various forms of support and assistance, including urgent intervention, medical services, counselling, shelter or temporary accommodation and other supporting services. The ImmD calls on TIP victims to report crimes to the relevant departments immediately. A Pakistani illegal worker, holding a recognisance form, was jailed by Shatin Magistrates' Courts yesterday (September 16). During000 employ0</text> What is the correct answer to this question: The one correct? Choices: (A) the. (B)22. (C). (D). Format your response as follows: "The correct answer is (insert answer here)".
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Dynamic Portfolio Optimization with Regime-Switching Models: Use a regime-switching model to dynamically adjust portfolio allocation based on projected macroeconomic conditions (inflation, interest rates) and firm performance trends. The capital-intensive sectors may be in a “high-growth, low-profitability” regime in the near term, driven by automation and large-scale capital expenditure, while service sectors may be transitioning to a “low-growth, high-profitability” regime due to cost-cutting and restructuring. Optimize portfolio allocation by shifting toward large firms in capital-intensive sectors as they move into a higher profitability regime, while overweighting SMEs in service sectors that are more agile and can benefit from operational efficiency in the face of inflationary pressures.
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Please read the following text and answer the question below. <text> Child Abuse Images and Cleanfeeds: Assessing Internet Blocking Systems 1 Child Abuse images and Cleanfeeds: Assessing Internet Blocking Systems TJ McIntyre1 School of Law, University College Dublin tjmcintyre@ucd.ie To appear in: Ian Brown, ed., Research Handbook on Governance of the Internet (Cheltenham: Edward Elgar, forthcoming) 1. Introduction One of the most important trends in internet governance in recent years has been the growth of internet blocking as a policy tool, to the point where it is increasingly becoming a global norm. This is most obvious in states such as China where blocking is used to suppress political speech; however, in the last decade blocking has also become more common in democracies, usually as part of attempts to limit the availability of child abuse images. Numerous governments have therefore settled on blocking as their “primary solution” towards preventing such images from being distributed (Villeneuve 2010). Child abuse image blocking has, however, been extremely controversial within the academic, civil liberties and technical communities, and this debate has recently taken on a wider public dimension. At the time of writing, for example, public pressure has forced the German Federal Government to abandon legislation which would have introduced a police run system while the European Parliament has also rejected Commission proposals for mandatory blocking (Baker 2011; Zuvela 2011). Why have these systems been so controversial? Two lines of criticism can be identified, which might be termed the practical and the principled. The practical argument claims that blocking is ineffective, with ill-defined goals and easily evaded by widely available circumvention technologies (see e.g. Callanan et al. 2009). The principled argument, on the other hand, is that blocking systems undermine the norms associated with freedom of expression in democratic societies (Brown 2008). This latter argument stems from the fact that blocking sits at the intersection of three different regulatory trends – the use of technological solutions (“code as law”), a focus on intermediaries and the use of self- regulation in preference to legislation – which individually and all the more so collectively create a risk of invisible and unaccountable “censorship by proxy” (Kreimer 2006; McIntyre & Scott 2008). This chapter introduces and evaluates these claims by examining three prominent examples of child abuse image blocking – the United Kingdom Internet Watch Foundation (“IWF”) Child Abuse Image Content (“CAIC”) list, the European Union sponsored CIRCAMP system and United States hash value systems. It discusses the operation of each system and the extent to which the critics‟ concerns are borne out. It concludes by considering the lessons which might be learned for proposals to extend blocking to other types of content. 2. Background and regulatory context From the early days of the internet it was clear that the technology it embodied – in particular its possibilities for anonymity, decentralised distribution of content and regulatory arbitrage – threatened the ability of governments to control content such as child abuse images. Johnson Child Abuse Images and Cleanfeeds: Assessing Internet Blocking Systems 2 and Post (1996) famously expressed this “cyber-libertarian” view when they argued that “efforts to control the flow of electronic information across physical borders – to map local regulation and physical boundaries onto Cyberspace – are likely to prove futile”. In response, however, “cyber-realists” argued that governments could adapt by shifting regulatory strategies. Three approaches in particular were identified and have since been widely adopted. Regulation by code The first, most associated with Lessig (1999), stressed the role of code (software) as a means of regulation. Lessig noted that while the first generation of the internet was structured in such a way as to provide for anonymous speech, decentralised distribution and the use of encryption, there was no guarantee that this structure would persist. Instead, he pointed out, the architecture of the internet could easily be remade to facilitate governmental control – and to do so in an automated manner which could be much more efficient than more traditional means of enforcement. Intermediary-based regulation The second, articulated by Boyle (1997) and Swire (1998), rejected the argument that the decentralised and international nature of the internet makes it difficult or impossible to control the conduct of users who may be anonymous or whose location might be uncertain. Instead, it was argued, regulators could simply resort to indirect enforcement, targeting intermediaries rather than end users. For example, Boyle presciently suggested that the state might target ISPs, pressuring or requiring them to “prevent copyright infringement through technical surveillance”. This argument relied on the fact that the effect of internet disintermediation was oversold – while there has certainly been a great deal of disintermediation, there has also been the creation of entirely new intermediaries with greater technical and legal powers to control the actions of their users. For example, as compared with the post office an ISP or webmail provider has greater technical capability to screen communications, and may not be covered by older laws prohibiting this. Consequently, the ISP, search engine, hosting provider and others have become the new gatekeepers or “Internet points of control” and can be enlisted to stop the transmission of child abuse images (Zittrain 2003). Self- and co-regulation Closely related to the use of intermediaries, the third approach involved the promotion by governments of industry self- and co-regulatory schemes, which became so common in the internet context that they have been described as the presumptive starting points for regulation of information technology (Koops et al. 2006). These schemes appeared to offer substantial benefits for states and industry alike. By harnessing industry expertise and responsiveness, they dealt with the objections that governments lacked the knowledge necessary to regulate the internet and that legislation could not keep up with the pace of change online. Self-regulation also offered governments the possibility of outsourcing enforcement and minimising the accompanying costs, while Child Abuse Images and Cleanfeeds: Assessing Internet Blocking Systems 3 industry was attracted by the promise of a flexible and light touch regulatory regime which might ward off more intrusive legislative intervention (Price & Verhulst 2005). 3. Development of child abuse image blocking The three strategies mentioned above – a focus on intermediaries, regulation by code and the use of self- and co-regulation – neatly dovetail in the form of internet blocking which of its nature involves regulation by software and which generally (though not invariably) also involves ISPs and other intermediaries operating in a self- or co-regulatory context (McIntyre & Scott 2008). Perhaps unsurprisingly, child abuse images have led the growth of blocking in democracies. Child abuse is a particularly abhorrent crime and as a result there has been a substantial degree of both domestic and international consensus as to the illegality of such images. Unlike many other types of content which governments seek to filter – such as adult pornography or file-sharing sites – the blocking of child abuse images has until recently generally provoked little public controversy (All Party Parliamentary Communications Group 2009, p.9). There is also an important practical aspect which has favoured this type of blocking. As compared with other types of content, there are fewer websites or images which are potentially illegal. The IWF CAIC list, for example, currently contains about 500 URLs at any one time (Internet Watch Foundation 2011a). In addition, judgments about child abuse images are easier to make than judgments about other types of content. Whether something “glorifies terrorism” contrary to the UK Terrorism Act 2006 requires a difficult assessment of the context, including how it is likely to be understood by members of the public (Banisar 2008, p.21). By contrast, the evaluation of child abuse images does not generally present the same difficulty. As a result, the systems required to monitor, blacklist, and ultimately block child abuse images present fewer administrative and technological difficulties. In relation to child abuse images, blocking by ISPs also appeared to solve the problem that states could not control material hosted beyond their national borders – enabling them to take action on a domestic basis against material hosted abroad without the international cooperation necessary to have it removed at source. Children‟s advocacy groups therefore began to lobby for blocking as a form of situational crime prevention (See e.g. Carr & Hilton 2009). These lobbying efforts have been remarkably successful, and during the last decade systems have been adopted in numerous jurisdictions including: the United Kingdom, Norway, Sweden, Denmark, Canada, Switzerland, Italy, Netherlands, Figure 1111 .111111 11111111211211 1: doesn Child2 1 11111. </text> What is the correct answer to this question: Sean Foley is accused which option below could guilty? Choices: (A): (B (C According. The1 (D) all options above Format your response as follows: "The correct answer is (insert answer here)".
337
null
3
D
all options above
Please read the following text and answer the question below. <text> Child Abuse Images and Cleanfeeds: Assessing Internet Blocking Systems 1 Child Abuse images and Cleanfeeds: Assessing Internet Blocking Systems TJ McIntyre1 School of Law, University College Dublin tjmcintyre@ucd.ie To appear in: Ian Brown, ed., Research Handbook on Governance of the Internet (Cheltenham: Edward Elgar, forthcoming) 1. Introduction One of the most important trends in internet governance in recent years has been the growth of internet blocking as a policy tool, to the point where it is increasingly becoming a global norm. This is most obvious in states such as China where blocking is used to suppress political speech; however, in the last decade blocking has also become more common in democracies, usually as part of attempts to limit the availability of child abuse images. Numerous governments have therefore settled on blocking as their “primary solution” towards preventing such images from being distributed (Villeneuve 2010). Child abuse image blocking has, however, been extremely controversial within the academic, civil liberties and technical communities, and this debate has recently taken on a wider public dimension. At the time of writing, for example, public pressure has forced the German Federal Government to abandon legislation which would have introduced a police run system while the European Parliament has also rejected Commission proposals for mandatory blocking (Baker 2011; Zuvela 2011). Why have these systems been so controversial? Two lines of criticism can be identified, which might be termed the practical and the principled. The practical argument claims that blocking is ineffective, with ill-defined goals and easily evaded by widely available circumvention technologies (see e.g. Callanan et al. 2009). The principled argument, on the other hand, is that blocking systems undermine the norms associated with freedom of expression in democratic societies (Brown 2008). This latter argument stems from the fact that blocking sits at the intersection of three different regulatory trends – the use of technological solutions (“code as law”), a focus on intermediaries and the use of self- regulation in preference to legislation – which individually and all the more so collectively create a risk of invisible and unaccountable “censorship by proxy” (Kreimer 2006; McIntyre & Scott 2008). This chapter introduces and evaluates these claims by examining three prominent examples of child abuse image blocking – the United Kingdom Internet Watch Foundation (“IWF”) Child Abuse Image Content (“CAIC”) list, the European Union sponsored CIRCAMP system and United States hash value systems. It discusses the operation of each system and the extent to which the critics‟ concerns are borne out. It concludes by considering the lessons which might be learned for proposals to extend blocking to other types of content. 2. Background and regulatory context From the early days of the internet it was clear that the technology it embodied – in particular its possibilities for anonymity, decentralised distribution of content and regulatory arbitrage – threatened the ability of governments to control content such as child abuse images. Johnson Child Abuse Images and Cleanfeeds: Assessing Internet Blocking Systems 2 and Post (1996) famously expressed this “cyber-libertarian” view when they argued that “efforts to control the flow of electronic information across physical borders – to map local regulation and physical boundaries onto Cyberspace – are likely to prove futile”. In response, however, “cyber-realists” argued that governments could adapt by shifting regulatory strategies. Three approaches in particular were identified and have since been widely adopted. Regulation by code The first, most associated with Lessig (1999), stressed the role of code (software) as a means of regulation. Lessig noted that while the first generation of the internet was structured in such a way as to provide for anonymous speech, decentralised distribution and the use of encryption, there was no guarantee that this structure would persist. Instead, he pointed out, the architecture of the internet could easily be remade to facilitate governmental control – and to do so in an automated manner which could be much more efficient than more traditional means of enforcement. Intermediary-based regulation The second, articulated by Boyle (1997) and Swire (1998), rejected the argument that the decentralised and international nature of the internet makes it difficult or impossible to control the conduct of users who may be anonymous or whose location might be uncertain. Instead, it was argued, regulators could simply resort to indirect enforcement, targeting intermediaries rather than end users. For example, Boyle presciently suggested that the state might target ISPs, pressuring or requiring them to “prevent copyright infringement through technical surveillance”. This argument relied on the fact that the effect of internet disintermediation was oversold – while there has certainly been a great deal of disintermediation, there has also been the creation of entirely new intermediaries with greater technical and legal powers to control the actions of their users. For example, as compared with the post office an ISP or webmail provider has greater technical capability to screen communications, and may not be covered by older laws prohibiting this. Consequently, the ISP, search engine, hosting provider and others have become the new gatekeepers or “Internet points of control” and can be enlisted to stop the transmission of child abuse images (Zittrain 2003). Self- and co-regulation Closely related to the use of intermediaries, the third approach involved the promotion by governments of industry self- and co-regulatory schemes, which became so common in the internet context that they have been described as the presumptive starting points for regulation of information technology (Koops et al. 2006). These schemes appeared to offer substantial benefits for states and industry alike. By harnessing industry expertise and responsiveness, they dealt with the objections that governments lacked the knowledge necessary to regulate the internet and that legislation could not keep up with the pace of change online. Self-regulation also offered governments the possibility of outsourcing enforcement and minimising the accompanying costs, while Child Abuse Images and Cleanfeeds: Assessing Internet Blocking Systems 3 industry was attracted by the promise of a flexible and light touch regulatory regime which might ward off more intrusive legislative intervention (Price & Verhulst 2005). 3. Development of child abuse image blocking The three strategies mentioned above – a focus on intermediaries, regulation by code and the use of self- and co-regulation – neatly dovetail in the form of internet blocking which of its nature involves regulation by software and which generally (though not invariably) also involves ISPs and other intermediaries operating in a self- or co-regulatory context (McIntyre & Scott 2008). Perhaps unsurprisingly, child abuse images have led the growth of blocking in democracies. Child abuse is a particularly abhorrent crime and as a result there has been a substantial degree of both domestic and international consensus as to the illegality of such images. Unlike many other types of content which governments seek to filter – such as adult pornography or file-sharing sites – the blocking of child abuse images has until recently generally provoked little public controversy (All Party Parliamentary Communications Group 2009, p.9). There is also an important practical aspect which has favoured this type of blocking. As compared with other types of content, there are fewer websites or images which are potentially illegal. The IWF CAIC list, for example, currently contains about 500 URLs at any one time (Internet Watch Foundation 2011a). In addition, judgments about child abuse images are easier to make than judgments about other types of content. Whether something “glorifies terrorism” contrary to the UK Terrorism Act 2006 requires a difficult assessment of the context, including how it is likely to be understood by members of the public (Banisar 2008, p.21). By contrast, the evaluation of child abuse images does not generally present the same difficulty. As a result, the systems required to monitor, blacklist, and ultimately block child abuse images present fewer administrative and technological difficulties. In relation to child abuse images, blocking by ISPs also appeared to solve the problem that states could not control material hosted beyond their national borders – enabling them to take action on a domestic basis against material hosted abroad without the international cooperation necessary to have it removed at source. Children‟s advocacy groups therefore began to lobby for blocking as a form of situational crime prevention (See e.g. Carr & Hilton 2009). These lobbying efforts have been remarkably successful, and during the last decade systems have been adopted in numerous jurisdictions including: the United Kingdom, Norway, Sweden, Denmark, Canada, Switzerland, Italy, Netherlands, Figure 1111 .111111 11111111211211 1: doesn Child2 1 11111. </text> What is the correct answer to this question: Sean Foley is accused which option below could guilty? Choices: (A): (B (C According. The1 (D) all options above Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> Nemotron-4 340B Technical Report NVIDIA Abstract We release the Nemotron-4 340B model family, including Nemotron-4-340B-Base, Nemotron-4- 340B-Instruct, and Nemotron-4-340B-Reward. Our models are open access under the NVIDIA Open Model License Agreement, a permissive model license that allows distribution, modification, and use of the models and its outputs. These models perform competitively to open access models on a wide range of evaluation benchmarks, and were sized to fit on a single DGX H100 with 8 GPUs when deployed in FP8 precision. We believe that the community can benefit from these models in various research studies and commercial applications, especially for generating synthetic data to train smaller language models. Notably, over 98% of data used in our model alignment process is synthetically generated, showcasing the effectiveness of these models in generating synthetic data. To further support open research and facilitate model development, we are also open-sourcing the synthetic data generation pipeline used in our model alignment process. Models: Nemotron-4-340B-Base, Nemotron-4-340B-Instruct, Nemotron-4-340B-Reward. Code: Pretraining, Alignment and Reward Model Training. Webpage: Nemotron-4 340B Announcement. 1 Introduction Large Language Models (LLMs) are highly effective at many tasks in diverse applications. Recent efforts have focused on increasing the accuracy of these models by pretraining on more, higher-quality tokens. For example, the Llama-2 family (Touvron et al., 2023) was trained on 2 trillion tokens while the Llama-3 family (MetaAI, 2024) was trained on 15 trillion tokens. The Nemotron-4 340B base model was trained with 9 trillion tokens from a high-quality dataset, the details of which are provided in Parmar et al. (2024). We align the base LLM with Supervised Fine-Tuning (SFT), followed by Preference Fine-Tuning such as Reinforcement Learning with Human Feedback (RLHF) (Ouyang et al., 2022; Bai et al., 2022) and Direct Preference Optimization (DPO) (Rafailov et al., 2024). The alignment process enables the model to follow instructions better, engage in conversations effectively, and better solve problems. The alignment process relies on a reward model that can accurately identify the quality of responses. This reward model is a crucial component in RLHF and also a useful tool for quality filtering and preference ranking in synthetic data generation. To support the ongoing development of LLMs across the community, we introduce Nemotron-4-340B-Base, Nemotron-4-340B-Instruct, and Nemotron-4-340B-Reward, which are released as open access models with a permissive license. Figure 1 highlights the accuracy of the Nemotron-4 340B model family across selected tasks. Specifically, we show that Nemotron-4-340B-Base is competitive with open access base models like 1 0 25 50 75 100 MMLU BigBenchHard ARC-Challenge Nemotron-4 340B Llama3-70B Mixtral 8x22 Qwen-2 72B base (a) Nemotron-4-340B-Base 0 20 40 60 80 Arena Hard IFEval AlpacaEval 2.0 LC Nemotron-4-340B-Instruct Llama-3-70B-Instruct Mixtral-8x22B-Instruct v0.1 Qwen-2-72B-Instruct (b) Nemotron-4-340B-Instruct 0 25 50 75 100 Overall Chat-Hard Safety Nemotron-4-340B-Reward Cohere May 2024 Gemini 1.5 Pro-0514 GPT-4o-0513 (c) Nemotron-4-340B-Reward Figure 1: Comparison of Nemotron-4-340B-Base, Nemotron-4-340B-Instruct and Nemotron-4-340B- Reward. See detailed evaluation results in Section 2.4, Section 3.4, and Section 3.1, respectively. Llama-3 70B (MetaAI, 2024), Mixtral 8x22B (Mistral-AI-Team, 2024b) and the recently released Qwen-2 72B model on commonsense reasoning tasks like ARC-Challenge, MMLU, and the BigBench Hard bench- mark. Nemotron-4-340B-Instruct surpasses the corresponding instruct models (MetaAI, 2024; Mistral-AI- Team, 2024b; Qwen-Team, 2024) in terms of instruction following and chat capabilities. Nemotron-4-340B- Reward achieves top accuracy on RewardBench (Allen AI, 2024) as of the time of publication, surpassing even proprietary models such as GPT-4o-0513 and Gemini 1.5 Pro-0514. We release our reward model in order to support the ongoing development of LLMs in the community. One promising application of these models is synthetic data generation, which has already demonstrated significant value in improving data quality for pretraining. For instance, data synthesis has been used to rephrase web-text (Maini et al., 2024), generate training data for the text-quality classifiers (MetaAI, 2024; Guilherme Penedo, 2024), and create data for domains that are under-represented in the pretraining set. Additionally, synthetic data generation is crucial for alignment, due to the high cost of collecting human an- notated data. We use synthetic data heavily to create Nemotron-4-340B-Instruct: over 98% of our training data has been synthetically generated throughout our alignment process. In addition to sharing our model and alignment strategies, we are also releasing our synthetic data generation pipeline, which includes syn- thetic prompt generation, response and dialogue generation, quality filtering, and preference ranking. This pipeline has been designed to support both supervised fine-tuning and preference fine-tuning, and we believe it has the potential to benefit the community by enabling the creation of high-quality data that can adapt to a wide range of domains. By releasing Nemotron-4-340B-Base, Nemotron-4-340B-Instruct and Nemotron-4-340B-Reward, and shar- ing our synthetic data generation pipeline, we would like to encourage broad accessibility to large, capable models to accelerate research progress both for the development of AI applications as well as responsible use of LLMs. We are committed to responsible development practices and do not intend for the model to be used in generating toxic or harmful content. Summary of contributions: • We release the Nemotron-4 340B model family, including Nemotron-4-340B-Base, Nemotron-4- 340B-Instruct and Nemotron-4-340B-Reward, under the NVIDIA Open Model License Agreement, 2 which is permissive for commercial applications.1 • We release code for training and inference of these models to promote transparency and reproducibil- ity. • We provide comprehensive details about our synthetic data generation pipeline and illustrate its effec- tiveness in model alignment. We also share our generation prompts, our human annotated preference dataset, and the Nemotron-4-340B-Reward for quality filtering and preference ranking. Going for- ward, we will share more tools such as NVIDIA Inference Microservices (NIMs) for synthetic data generation. 2 Pretraining 2.1 Data Our pretraining data blend consists of three different types of data: English natural language data (70%), multilingual natural language data (15%), and source code data (15%). The English corpus consists of curated documents from a variety of sources and domains including web documents, news articles, scientific papers, books, and more. Our multilingual data contains 53 natural languages and is composed of documents from both monolingual and parallel corpora while our code dataset is made up of 43 programming languages. We train for a total of 9T tokens on this data, with the first 8T taking place as formal pretraining phase and the last 1T in a continued pretraining224-In2XX_</text> What is the correct answer to this question: How many Nem- most? Choices: (A) (B)(C (D) Format your response as follows: "The correct answer is (insert answer here)".
338
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2
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Please read the following text and answer the question below. <text> Nemotron-4 340B Technical Report NVIDIA Abstract We release the Nemotron-4 340B model family, including Nemotron-4-340B-Base, Nemotron-4- 340B-Instruct, and Nemotron-4-340B-Reward. Our models are open access under the NVIDIA Open Model License Agreement, a permissive model license that allows distribution, modification, and use of the models and its outputs. These models perform competitively to open access models on a wide range of evaluation benchmarks, and were sized to fit on a single DGX H100 with 8 GPUs when deployed in FP8 precision. We believe that the community can benefit from these models in various research studies and commercial applications, especially for generating synthetic data to train smaller language models. Notably, over 98% of data used in our model alignment process is synthetically generated, showcasing the effectiveness of these models in generating synthetic data. To further support open research and facilitate model development, we are also open-sourcing the synthetic data generation pipeline used in our model alignment process. Models: Nemotron-4-340B-Base, Nemotron-4-340B-Instruct, Nemotron-4-340B-Reward. Code: Pretraining, Alignment and Reward Model Training. Webpage: Nemotron-4 340B Announcement. 1 Introduction Large Language Models (LLMs) are highly effective at many tasks in diverse applications. Recent efforts have focused on increasing the accuracy of these models by pretraining on more, higher-quality tokens. For example, the Llama-2 family (Touvron et al., 2023) was trained on 2 trillion tokens while the Llama-3 family (MetaAI, 2024) was trained on 15 trillion tokens. The Nemotron-4 340B base model was trained with 9 trillion tokens from a high-quality dataset, the details of which are provided in Parmar et al. (2024). We align the base LLM with Supervised Fine-Tuning (SFT), followed by Preference Fine-Tuning such as Reinforcement Learning with Human Feedback (RLHF) (Ouyang et al., 2022; Bai et al., 2022) and Direct Preference Optimization (DPO) (Rafailov et al., 2024). The alignment process enables the model to follow instructions better, engage in conversations effectively, and better solve problems. The alignment process relies on a reward model that can accurately identify the quality of responses. This reward model is a crucial component in RLHF and also a useful tool for quality filtering and preference ranking in synthetic data generation. To support the ongoing development of LLMs across the community, we introduce Nemotron-4-340B-Base, Nemotron-4-340B-Instruct, and Nemotron-4-340B-Reward, which are released as open access models with a permissive license. Figure 1 highlights the accuracy of the Nemotron-4 340B model family across selected tasks. Specifically, we show that Nemotron-4-340B-Base is competitive with open access base models like 1 0 25 50 75 100 MMLU BigBenchHard ARC-Challenge Nemotron-4 340B Llama3-70B Mixtral 8x22 Qwen-2 72B base (a) Nemotron-4-340B-Base 0 20 40 60 80 Arena Hard IFEval AlpacaEval 2.0 LC Nemotron-4-340B-Instruct Llama-3-70B-Instruct Mixtral-8x22B-Instruct v0.1 Qwen-2-72B-Instruct (b) Nemotron-4-340B-Instruct 0 25 50 75 100 Overall Chat-Hard Safety Nemotron-4-340B-Reward Cohere May 2024 Gemini 1.5 Pro-0514 GPT-4o-0513 (c) Nemotron-4-340B-Reward Figure 1: Comparison of Nemotron-4-340B-Base, Nemotron-4-340B-Instruct and Nemotron-4-340B- Reward. See detailed evaluation results in Section 2.4, Section 3.4, and Section 3.1, respectively. Llama-3 70B (MetaAI, 2024), Mixtral 8x22B (Mistral-AI-Team, 2024b) and the recently released Qwen-2 72B model on commonsense reasoning tasks like ARC-Challenge, MMLU, and the BigBench Hard bench- mark. Nemotron-4-340B-Instruct surpasses the corresponding instruct models (MetaAI, 2024; Mistral-AI- Team, 2024b; Qwen-Team, 2024) in terms of instruction following and chat capabilities. Nemotron-4-340B- Reward achieves top accuracy on RewardBench (Allen AI, 2024) as of the time of publication, surpassing even proprietary models such as GPT-4o-0513 and Gemini 1.5 Pro-0514. We release our reward model in order to support the ongoing development of LLMs in the community. One promising application of these models is synthetic data generation, which has already demonstrated significant value in improving data quality for pretraining. For instance, data synthesis has been used to rephrase web-text (Maini et al., 2024), generate training data for the text-quality classifiers (MetaAI, 2024; Guilherme Penedo, 2024), and create data for domains that are under-represented in the pretraining set. Additionally, synthetic data generation is crucial for alignment, due to the high cost of collecting human an- notated data. We use synthetic data heavily to create Nemotron-4-340B-Instruct: over 98% of our training data has been synthetically generated throughout our alignment process. In addition to sharing our model and alignment strategies, we are also releasing our synthetic data generation pipeline, which includes syn- thetic prompt generation, response and dialogue generation, quality filtering, and preference ranking. This pipeline has been designed to support both supervised fine-tuning and preference fine-tuning, and we believe it has the potential to benefit the community by enabling the creation of high-quality data that can adapt to a wide range of domains. By releasing Nemotron-4-340B-Base, Nemotron-4-340B-Instruct and Nemotron-4-340B-Reward, and shar- ing our synthetic data generation pipeline, we would like to encourage broad accessibility to large, capable models to accelerate research progress both for the development of AI applications as well as responsible use of LLMs. We are committed to responsible development practices and do not intend for the model to be used in generating toxic or harmful content. Summary of contributions: • We release the Nemotron-4 340B model family, including Nemotron-4-340B-Base, Nemotron-4- 340B-Instruct and Nemotron-4-340B-Reward, under the NVIDIA Open Model License Agreement, 2 which is permissive for commercial applications.1 • We release code for training and inference of these models to promote transparency and reproducibil- ity. • We provide comprehensive details about our synthetic data generation pipeline and illustrate its effec- tiveness in model alignment. We also share our generation prompts, our human annotated preference dataset, and the Nemotron-4-340B-Reward for quality filtering and preference ranking. Going for- ward, we will share more tools such as NVIDIA Inference Microservices (NIMs) for synthetic data generation. 2 Pretraining 2.1 Data Our pretraining data blend consists of three different types of data: English natural language data (70%), multilingual natural language data (15%), and source code data (15%). The English corpus consists of curated documents from a variety of sources and domains including web documents, news articles, scientific papers, books, and more. Our multilingual data contains 53 natural languages and is composed of documents from both monolingual and parallel corpora while our code dataset is made up of 43 programming languages. We train for a total of 9T tokens on this data, with the first 8T taking place as formal pretraining phase and the last 1T in a continued pretraining224-In2XX_</text> What is the correct answer to this question: How many Nem- most? Choices: (A) (B)(C (D) Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> ARF: Artistic Radiance Fields Kai Zhang1 Nick Kolkin2 Sai Bi2 Fujun Luan2 Zexiang Xu2 Eli Shechtman2 Noah Snavely1 1Cornell University 2Adobe Research Abstract. We present a method for transferring the artistic features of an arbitrary style image to a 3D scene. Previous methods that perform 3D stylization on point clouds or meshes are sensitive to geometric reconstruc- tion errors for complex real-world scenes. Instead, we propose to stylize the more robust radiance field representation. We find that the commonly used Gram matrix-based loss tends to produce blurry results without faithful brushstrokes, and introduce a nearest neighbor-based loss that is highly effective at capturing style details while maintaining multi-view consistency. We also propose a novel deferred back-propagation method to enable optimization of memory-intensive radiance fields using style losses defined on full-resolution rendered images. Our extensive evalua- tion demonstrates that our method outperforms baselines by generating artistic appearance that more closely resembles the style image. Please check our project page for video results and open-source implementations: https://www.cs.cornell.edu/projects/arf/. Keywords: Style transfer, neural radiance fields, 3D content creation 1 Introduction Creating artistic images often requires a significant amount of time and special expertise. Extending an artwork to dimensions beyond the 2D image plane, such as time (in the case of animation), or 3D space (in the case of sculptures or virtual environments), introduces new constraints and challenges. Hence, the styles employed by artists when moving their work beyond a static 2D canvas are constrained by the effort required to create a consistent visual experience. We propose Artistic Radiance Fields (ARF), a novel approach that can transfer the artistic features from a single 2D image to a full, real-world 3D scene, leading to artistic novel view renderings that are faithful to the style image. Our method converts a photorealistic radiance field [32,1,4] reconstructed from multiple images of complex, real-world scenes into a new, stylized radiance field that supports high-quality view-consistent stylized renderings from novel viewpoints, as shown in Fig. 1. The quality of these renderings is in contrast to previous 3D stylization works [16,14,33] that often suffer from geometrically inaccurate reconstructions of point cloud or triangle meshes and the lack of style details. We formulate the stylization of radiance fields as an optimization problem; we render images of the radiance fields from different viewpoints in a differentiable 2 K. Zhang et al. Reconstructed radiance feld Novel views of stylized scene Style images Fig. 1. We propose ARF, a novel approach for 3D stylization. Our approach utilizes a pre-reconstructed radiance field of a real scene (left) and converts it into an artistic radiance field by matching feature activations extracted from an input 2D style image (middle), leading to high-quality stylized novel view synthesis (right). Our approach produces consistent results across viewpoints; please refer to our supplementary video. manner, and minimize a content loss between the rendered stylized images and the original captured images, and also a style loss between the rendered images and the style image. While previous methods [16,14,33] apply the commonly-used Gram matrix-based style loss for 3D stylization, we observe that such a loss leads to averaged-out style details that degrades the quality of the stylized renderings. This limitation motivates us to apply a novel style loss based on Nearest Neighbor Feature Matching (NNFM) that is better suited to the creation of high-quality 3D artistic radiance fields. In particular, for each feature vector in the VGG feature map of a rendered image, we find its nearest neighbor (NN) feature vector in the style image’s VGG feature map and minimize the distance between the two feature vectors. Unlike a Gram matrix describing global feature statistics across the entire image, NN feature matching focuses on local image descriptions, better capturing distinctive local details. Coupled with our style loss, we also enforce a VGG feature-based content loss – that balances stylization and content preservation – and a simple color transfer technique – that improves the color match between our final renderings and the input style. Volumetric radiance field rendering consumes a lot of memory and often can only regress sparsely sampled pixels during training, and not the full images nec- essary for computing the VGG features used in many style losses. We contribute a practical innovation that allows us to perform optimization on high-resolution images. In particular, we devise a method we call deferred back-propagation that enables memory-efficient auto-differentiation of scene parameters with im- age losses computed on full-resolution images (e.g., VGG-based style losses) by accumulating cached gradients in a patch-wise fashion. ARF: Artistic Radiance Fields 3 We demonstrate that ARF can robustly transfer detailed artistic features from diverse and challenging 2D style exemplars to a variety of complex 3D scenes, resulting in significantly better visual quality compared to previous methods, which tend to yield over-smoothed and blurry stylized novel views (see Figures 4, 5, and 6). In our user studies, our method is also consistently preferred over baselines. In summary, our contributions are: – A novel radiance field-based approach for 3D scene stylization that can faithfully transfer detailed style features from a 2D image to a 3D scene and produces consistent stylized novel views of high visual quality. – We find that Nearest Neighbor Feature Matching (NNFM) loss better pre- serves details in the style images than the Gram-matrix-based loss commonly used in prior 3D stylization works. – A deferred back-propagation method for differentiable volumetric rendering, allowing for computation of losses on full-resolution images while significantly reducing the GPU memory footprint. 2 Related Work In this section, we review related work to provide context for our own work. Image style transfer. Since Gatys et al. [11] introduced neural style transfer, significant progress has been made towards artistic stylization [25,22], image harmonization [49,29,40], color matching [43,42,28], texture synthesis [36,23,13] and beyond [18]. These style transfer approaches leverage features extracted by a pre-trained convolutional neural network (e.g., VGG-19 [39]) and optimize for a set of loss functions (typically a content loss capturing an input photo’s features and a style loss matching a target image’s feature statistics, e.g., encoded in a Gram matrix) to achieve good performance for painterly style transfer. Depending on whether the style transfer is achieved via iterative optimization on a single input or with a forward pass from a pre-trained generative model, existing methods can be categorized as optimization-based and feed-forward-based: Optimization-based style transfer. Gatys et al. [11] perform style transfer via iterative optimization to minimize content and style losses. Many follow-up works [7,22,36,12,21,30,25] have investigated alternative style loss formulations to further improve the quality of semantic consistency and high-frequency style de- tails like brushstrokes. Unlike neural style transfer methods that encode statistics of style features with a single Gram matrix, Chen and Schmidt [7], CNNMRF [22], Deep Image Analogy [25] and NNST [20] propose to search for nearest neighbors and minimize distances between features extracted from corresponding content and style patches in a coarse-to-fine fashion. These methods achieve impressive 2D stylization quality when provided with source and target images that share similar semantics. Our approach draws inspiration from this line of work and is the first to introducest... \. trA: et thank21111 \ ofRef-N2 � � >.7 ations. versatile However performFigure1enzhen Science2. meaningful8 References ., 11221111–1]., 1):22210. . (1) . Therefore we However note. PI00000 1 1∗ contribution 2-f. 0-NReferences[2221121X232X222X6XX11111113 [[9 ar11. 1. 14 </text> What is the correct answer to this question: Both AR and Re introduce novel stylizing 3D scenes, while-N focuses-. Each tackles. While (,3 and-N. Given, which method most effectively handles multi-view, and what is the underlying mathematical reasoning that supports this effectiveness? Choices: (A) AR by leveraging the loss,. This avoids the V vectors allowing. The effectiveness lies in the3. (B).. mathematically. (C) handles. mathematically. (D) Both through their respective but Ref-N. While struggles,-NPR uses 3 surfaces, maintaining. Format your response as follows: "The correct answer is (insert answer here)".
339
null
1
B
ReGS addresses the multi-view consistency problem through a depth-based regularization that preserves the scene’s geometry while performing stylization. By incorporating structured densification of Gaussians, ReGS ensures that each Gaussian splat is adjusted to match the fine texture details in the reference image. This method mathematically improves consistency across views by using a pseudo-view supervision loss that synthesizes stylized pseudo views through depth-based warping, aligning style across occluded areas and ensuring consistent texture across viewpoints.
Please read the following text and answer the question below. <text> ARF: Artistic Radiance Fields Kai Zhang1 Nick Kolkin2 Sai Bi2 Fujun Luan2 Zexiang Xu2 Eli Shechtman2 Noah Snavely1 1Cornell University 2Adobe Research Abstract. We present a method for transferring the artistic features of an arbitrary style image to a 3D scene. Previous methods that perform 3D stylization on point clouds or meshes are sensitive to geometric reconstruc- tion errors for complex real-world scenes. Instead, we propose to stylize the more robust radiance field representation. We find that the commonly used Gram matrix-based loss tends to produce blurry results without faithful brushstrokes, and introduce a nearest neighbor-based loss that is highly effective at capturing style details while maintaining multi-view consistency. We also propose a novel deferred back-propagation method to enable optimization of memory-intensive radiance fields using style losses defined on full-resolution rendered images. Our extensive evalua- tion demonstrates that our method outperforms baselines by generating artistic appearance that more closely resembles the style image. Please check our project page for video results and open-source implementations: https://www.cs.cornell.edu/projects/arf/. Keywords: Style transfer, neural radiance fields, 3D content creation 1 Introduction Creating artistic images often requires a significant amount of time and special expertise. Extending an artwork to dimensions beyond the 2D image plane, such as time (in the case of animation), or 3D space (in the case of sculptures or virtual environments), introduces new constraints and challenges. Hence, the styles employed by artists when moving their work beyond a static 2D canvas are constrained by the effort required to create a consistent visual experience. We propose Artistic Radiance Fields (ARF), a novel approach that can transfer the artistic features from a single 2D image to a full, real-world 3D scene, leading to artistic novel view renderings that are faithful to the style image. Our method converts a photorealistic radiance field [32,1,4] reconstructed from multiple images of complex, real-world scenes into a new, stylized radiance field that supports high-quality view-consistent stylized renderings from novel viewpoints, as shown in Fig. 1. The quality of these renderings is in contrast to previous 3D stylization works [16,14,33] that often suffer from geometrically inaccurate reconstructions of point cloud or triangle meshes and the lack of style details. We formulate the stylization of radiance fields as an optimization problem; we render images of the radiance fields from different viewpoints in a differentiable 2 K. Zhang et al. Reconstructed radiance feld Novel views of stylized scene Style images Fig. 1. We propose ARF, a novel approach for 3D stylization. Our approach utilizes a pre-reconstructed radiance field of a real scene (left) and converts it into an artistic radiance field by matching feature activations extracted from an input 2D style image (middle), leading to high-quality stylized novel view synthesis (right). Our approach produces consistent results across viewpoints; please refer to our supplementary video. manner, and minimize a content loss between the rendered stylized images and the original captured images, and also a style loss between the rendered images and the style image. While previous methods [16,14,33] apply the commonly-used Gram matrix-based style loss for 3D stylization, we observe that such a loss leads to averaged-out style details that degrades the quality of the stylized renderings. This limitation motivates us to apply a novel style loss based on Nearest Neighbor Feature Matching (NNFM) that is better suited to the creation of high-quality 3D artistic radiance fields. In particular, for each feature vector in the VGG feature map of a rendered image, we find its nearest neighbor (NN) feature vector in the style image’s VGG feature map and minimize the distance between the two feature vectors. Unlike a Gram matrix describing global feature statistics across the entire image, NN feature matching focuses on local image descriptions, better capturing distinctive local details. Coupled with our style loss, we also enforce a VGG feature-based content loss – that balances stylization and content preservation – and a simple color transfer technique – that improves the color match between our final renderings and the input style. Volumetric radiance field rendering consumes a lot of memory and often can only regress sparsely sampled pixels during training, and not the full images nec- essary for computing the VGG features used in many style losses. We contribute a practical innovation that allows us to perform optimization on high-resolution images. In particular, we devise a method we call deferred back-propagation that enables memory-efficient auto-differentiation of scene parameters with im- age losses computed on full-resolution images (e.g., VGG-based style losses) by accumulating cached gradients in a patch-wise fashion. ARF: Artistic Radiance Fields 3 We demonstrate that ARF can robustly transfer detailed artistic features from diverse and challenging 2D style exemplars to a variety of complex 3D scenes, resulting in significantly better visual quality compared to previous methods, which tend to yield over-smoothed and blurry stylized novel views (see Figures 4, 5, and 6). In our user studies, our method is also consistently preferred over baselines. In summary, our contributions are: – A novel radiance field-based approach for 3D scene stylization that can faithfully transfer detailed style features from a 2D image to a 3D scene and produces consistent stylized novel views of high visual quality. – We find that Nearest Neighbor Feature Matching (NNFM) loss better pre- serves details in the style images than the Gram-matrix-based loss commonly used in prior 3D stylization works. – A deferred back-propagation method for differentiable volumetric rendering, allowing for computation of losses on full-resolution images while significantly reducing the GPU memory footprint. 2 Related Work In this section, we review related work to provide context for our own work. Image style transfer. Since Gatys et al. [11] introduced neural style transfer, significant progress has been made towards artistic stylization [25,22], image harmonization [49,29,40], color matching [43,42,28], texture synthesis [36,23,13] and beyond [18]. These style transfer approaches leverage features extracted by a pre-trained convolutional neural network (e.g., VGG-19 [39]) and optimize for a set of loss functions (typically a content loss capturing an input photo’s features and a style loss matching a target image’s feature statistics, e.g., encoded in a Gram matrix) to achieve good performance for painterly style transfer. Depending on whether the style transfer is achieved via iterative optimization on a single input or with a forward pass from a pre-trained generative model, existing methods can be categorized as optimization-based and feed-forward-based: Optimization-based style transfer. Gatys et al. [11] perform style transfer via iterative optimization to minimize content and style losses. Many follow-up works [7,22,36,12,21,30,25] have investigated alternative style loss formulations to further improve the quality of semantic consistency and high-frequency style de- tails like brushstrokes. Unlike neural style transfer methods that encode statistics of style features with a single Gram matrix, Chen and Schmidt [7], CNNMRF [22], Deep Image Analogy [25] and NNST [20] propose to search for nearest neighbors and minimize distances between features extracted from corresponding content and style patches in a coarse-to-fine fashion. These methods achieve impressive 2D stylization quality when provided with source and target images that share similar semantics. Our approach draws inspiration from this line of work and is the first to introducest... \. trA: et thank21111 \ ofRef-N2 � � >.7 ations. versatile However performFigure1enzhen Science2. meaningful8 References ., 11221111–1]., 1):22210. . (1) . Therefore we However note. PI00000 1 1∗ contribution 2-f. 0-NReferences[2221121X232X222X6XX11111113 [[9 ar11. 1. 14 </text> What is the correct answer to this question: Both AR and Re introduce novel stylizing 3D scenes, while-N focuses-. Each tackles. While (,3 and-N. Given, which method most effectively handles multi-view, and what is the underlying mathematical reasoning that supports this effectiveness? Choices: (A) AR by leveraging the loss,. This avoids the V vectors allowing. The effectiveness lies in the3. (B).. mathematically. (C) handles. mathematically. (D) Both through their respective but Ref-N. While struggles,-NPR uses 3 surfaces, maintaining. Format your response as follows: "The correct answer is (insert answer here)".
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Please read the following text and answer the question below. <text> [ [ { "role": "user", "content": "Document: I know. My question was if they **used** to compete in T5-TTT2.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) abb\n(B) aba\n(C) aah\n(D) aai" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: 18 is hot but very bland, it's just here this blonde lady who is not as hot as blonde launch.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aal\n(B) aae\n(C) abb\n(D) aaq" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: Mine was apparently [NAME] and the giant peach!\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) abb\n(B) aav\n(C) aaq\n(D) aat" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: Sack, shaft, and tip. The trifecta. \n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aav\n(B) aap\n(C) aap\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: Detective from svu.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aas\n(B) abb\n(C) aaa\n(D) aaf" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: your mom likes to copy me cause she has no creativity just like you:\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aab\n(B) abb\n(C) aad\n(D) aak" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: [NAME] sees all\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aan\n(B) aak\n(C) aaa\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: A new study just came out from China that it's actually too late.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aah\n(B) aag\n(C) abb\n(D) aaz" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: It might be linked to the trust factor of your friend.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aba\n(B) aap\n(C) aas\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: You are going to do the dishes now\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) abb\n(B) aaj\n(C) aaz\n(D) aaf" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: Cheers, sololander!\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aap\n(B) aaw\n(C) abb\n(D) aag" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: Never get out of the boat.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aax\n(B) abb\n(C) aaz\n(D) aaq" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: Just got home from school. How are we doing\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aag\n(B) aau\n(C) aab\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: Slowing things down now\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) abb\n(B) aai\n(C) aal\n(D) aax" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: Honestly it sounds exhausting being married to him. Maybe it will be better for you in the long run.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) abb\n(B) aaf\n(C) aao\n(D) aag" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: FBI!! OPEN UP!!!\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aad\n(B) aba\n(C) aaz\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: This pic they used for [NAME] makes her look like [NAME]\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aal\n(B) abb\n(C) aak\n(D) aat" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: Aww, try mindfulness. I think I am going over to that sub now.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aaw\n(B) aat\n(C) aaf\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: His name has already been released. Just can't post it here.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aag\n(B) abb\n(C) aai\n(D) aba" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: When I feel down I listen to music.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aab\n(B) abb\n(C) aau\n(D) aau" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: Hello everyone. Im from Toronto as well. Can call and visit in personal if needed.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aaq\n(B) abb\n(C) aah\n(D) aac" }, { "role": "assistant", "content": "B" } ], [ role", ?\?\?\?\?\", ?\?\?\ (", ", content?\ncontent ", ", ] ] </text> What correct answer:? Choices: (A(D Format your response as follows: "The correct answer is (insert answer here)".
340
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2
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Please read the following text and answer the question below. <text> [ [ { "role": "user", "content": "Document: I know. My question was if they **used** to compete in T5-TTT2.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) abb\n(B) aba\n(C) aah\n(D) aai" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: 18 is hot but very bland, it's just here this blonde lady who is not as hot as blonde launch.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aal\n(B) aae\n(C) abb\n(D) aaq" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: Mine was apparently [NAME] and the giant peach!\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) abb\n(B) aav\n(C) aaq\n(D) aat" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: Sack, shaft, and tip. The trifecta. \n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aav\n(B) aap\n(C) aap\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: Detective from svu.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aas\n(B) abb\n(C) aaa\n(D) aaf" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: your mom likes to copy me cause she has no creativity just like you:\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aab\n(B) abb\n(C) aad\n(D) aak" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: [NAME] sees all\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aan\n(B) aak\n(C) aaa\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: A new study just came out from China that it's actually too late.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aah\n(B) aag\n(C) abb\n(D) aaz" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: It might be linked to the trust factor of your friend.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aba\n(B) aap\n(C) aas\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: You are going to do the dishes now\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) abb\n(B) aaj\n(C) aaz\n(D) aaf" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: Cheers, sololander!\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aap\n(B) aaw\n(C) abb\n(D) aag" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: Never get out of the boat.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aax\n(B) abb\n(C) aaz\n(D) aaq" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: Just got home from school. How are we doing\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aag\n(B) aau\n(C) aab\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: Slowing things down now\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) abb\n(B) aai\n(C) aal\n(D) aax" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: Honestly it sounds exhausting being married to him. Maybe it will be better for you in the long run.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) abb\n(B) aaf\n(C) aao\n(D) aag" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: FBI!! OPEN UP!!!\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aad\n(B) aba\n(C) aaz\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: This pic they used for [NAME] makes her look like [NAME]\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aal\n(B) abb\n(C) aak\n(D) aat" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: Aww, try mindfulness. I think I am going over to that sub now.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aaw\n(B) aat\n(C) aaf\n(D) abb" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: His name has already been released. Just can't post it here.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aag\n(B) abb\n(C) aai\n(D) aba" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: When I feel down I listen to music.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aab\n(B) abb\n(C) aau\n(D) aau" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: Hello everyone. Im from Toronto as well. Can call and visit in personal if needed.\n\nQuestion: Only considering the given document, what are the emotions of the document?\n\nOptions: (A) aaq\n(B) abb\n(C) aah\n(D) aac" }, { "role": "assistant", "content": "B" } ], [ role", ?\?\?\?\?\", ?\?\?\ (", ", content?\ncontent ", ", ] ] </text> What correct answer:? Choices: (A(D Format your response as follows: "The correct answer is (insert answer here)".
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Please read the following text and answer the question below. <text> Agatha Christie The Mirror Crack’d from Side to Side A Miss Marple Mystery To Margaret Rutherford in admiration Out flew the web and floated wide; The mirror crack’d from side to side; “The curse is come upon me,” cried The Lady of Shalott Alfred Tennyson Contents Cover Title Page Dedication Epigraph Chapter One Chapter Two Chapter Three Chapter Four Chapter Five Chapter Six Chapter Seven Chapter Eight Chapter Nine Chapter Ten Chapter Eleven Chapter Twelve Chapter Thirteen Chapter Fourteen Chapter Fifteen Chapter Sixteen Chapter Seventeen Chapter Eighteen Chapter Nineteen Chapter Twenty Chapter Twenty-one Chapter Twenty-two Chapter Twenty-three About the Author Other books by Agatha Christie Copyright About the Publisher One I Miss Jane Marple was sitting by her window. The window looked over her garden, once a source of pride to her. That was no longer so. Nowadays she looked out of the window and winced. Active gardening had been forbidden her for some time now. No stooping, no digging, no planting—at most a little light pruning. Old Laycock who came three times a week, did his best, no doubt. But his best, such as it was (which was not much) was only the best according to his lights, and not according to those of his employer. Miss Marple knew exactly what she wanted done, and when she wanted it done, and instructed him duly. Old Laycock then displayed his particular genius which was that of enthusiastic agreement and subsequent lack of performance. “That’s right, missus. We’ll have them mecosoapies there and the Canterburys along the wall and as you say it ought to be got on with first thing next week.” Laycock’s excuses were always reasonable, and strongly resembled those of Captain George’s in Three Men in a Boat for avoiding going to sea. In the captain’s case the wind was always wrong, either blowing off shore or in shore, or coming from the unreliable west, or the even more treacherous east. Laycock’s was the weather. Too dry—too wet— waterlogged—a nip of frost in the air. Or else something of great importance had to come first (usually to do with cabbages or brussels sprouts of which he liked to grow inordinate quantities). Laycock’s own principles of gardening were simple and no employer, however knowledgeable, could wean him from them. They consisted of a great many cups of tea, sweet and strong, as an encouragement to effort, a good deal of sweeping up of leaves in the autumn, and a certain amount of bedding out of his own favourite plants, mainly asters and salvias—to “make a nice show,” as he put it, in summer. He was all in favour of syringeing roses for green-fly, but was slow to get around to it, and a demand for deep trenching for sweet peas was usually countered by the remark that you ought to see his own sweet peas! A proper treat last year, and no fancy stuff done beforehand. To be fair, he was attached to his employers, humoured their fancies in horticulture (so far as no actual hard work was involved) but vegetables he knew to be the real stuff of life; a nice Savoy, or a bit of curly kale; flowers were fancy stuff such as ladies liked to go in for, having nothing better to do with their time. He showed his affection by producing presents of the aforementioned asters, salvias, lobelia edging, and summer chrysanthemums. “Been doing some work at them new houses over at the Development. Want their gardens laid out nice, they do. More plants than they needed so I brought along a few, and I’ve put ’em in where them old-fashioned roses ain’t looking so well.” Thinking of these things, Miss Marple averted her eyes from the garden, and picked up her knitting. One had to face the fact: St. Mary Mead was not the place it had been. In a sense, of course, nothing was what it had been. You could blame the war (both the wars) or the younger generation, or women going out to work, or the atom bomb, or just the Government—but what one really meant was the simple fact that one was growing old. Miss Marple, who was a very sensible lady, knew that quite well. It was just that, in a queer way, she felt it more in St. Mary Mead, because it had been her home for so long. St. Mary Mead, the old world core of it, was still there. The Blue Boar was there, and the church and the vicarage and the little nest of Queen Anne and Georgian houses, of which hers was one. Miss Hartnell’s house was still there, and also Miss Hartnell, fighting progress to the last gasp. Miss Wetherby had passed on and her house was now inhabited by the bank manager and his family, having been given a face-lift by the painting of doors and windows a bright royal blue. There were new people in most of the other old houses, but the houses themselves were little changed in appearances since the people who had bought them had done so because they liked what the house agent called “old world charm.” They just added another bathroom, and spent a good deal of money on plumbing, electric cookers, and dishwashers. But though the houses looked much as before, the same could hardly be said of the village street. When shops changed hands there, it was with a view to immediate and intemperate modernization. The fishmonger was unrecognizable with new super windows behind which the refrigerated fish gleamed. The butcher had remained conservative—good meat is good meat, if you have the money to pay for it. If not, you take the cheaper cuts and the tough joints and like it! Barnes, the grocer, was still there, unchanged, for which Miss Hartnell and Miss Marple and others daily thanked Heaven. So obliging, comfortable chairs to sit in by the counter, and cosy discussions as to cuts of bacon, and varieties of cheese. At the end of the street, however, where Mr. Toms had once had his basket shop stood a glittering new supermarket—anathema to the elderly ladies of St. Mary Mead. “Packets of things one’s never even heard of,” exclaimed Miss Hartnell. “All these great packets of breakfast cereal instead of cooking a child a proper breakfast of bacon and eggs. And you’re expected to take a basket yourself and go round looking for things—it takes a quarter of an hour sometimes to find all one wants—and usually made up in inconvenient sizes, too much or too little. And then a long queue waiting to pay as you go out. Most tiring. Of course it’s all very well for the people from the Development—” At this point she stopped. Because, as was now usual, the sentence came to an end there. The Development, Period, as they would say in modern terms. It had an entity of its own, and a capital letter. II Miss Marple uttered a sharp exclamation of annoyance. She’d dropped a stitch again. Not only that, she must have dropped it some time ago. Not until now, when she had to decrease for the neck and count the stitches, had she realized the fact. She took up a spare pin, held the knitting sideways to the light and peered anxiously. Even her new spectacles didn’t seem to do any good. And that, she reflected, was because obviously there came a time when oculists, in spite of their luxurious waiting rooms, the up-to-date instruments, the bright lights they flashed into your eyes, and the very high fees they charged, couldn’t do anything much more for you. Miss Marple reflected with some nostalgia on how good her eyesight had been a few (well, not perhaps a few) years ago. From the vantage point of her garden, so admirably placed to see all that was going on in St. Mary Mead, how little had escaped her noticing eye! And with the help of her bird glasses— (an interest in birds was so useful!)—she had been able to see—She broke off there and let her thoughts run back over the past. Ann Protheroe in her summer frock going along to the Vicarage garden. And Colonel Protheroe —poor man—a very tiresome and unpleasant man, to be sure—but to be murdered like that—She shook her head and went on to thoughts of Griselda, the vicar’s pretty young wife. Dear Griselda—such a faithful friend—a Christmas card every year. That attractive baby of hers was a strapping young man now, and with a very good job. Engineering, was it? He always had enjoyed taking his mechanical trains wouldn isnems wasndidn-f Crto himself? don moreems didn don anxit</text> What is the correct answer to this question: In "," which of following is false? Choices: (A)(B. (C. (D. Format your response as follows: "The correct answer is (insert answer here)".
341
null
1
B
At the party, someone intended to kill Marina, but the drink was handed to Heather, which led to Heather's death.
Please read the following text and answer the question below. <text> Agatha Christie The Mirror Crack’d from Side to Side A Miss Marple Mystery To Margaret Rutherford in admiration Out flew the web and floated wide; The mirror crack’d from side to side; “The curse is come upon me,” cried The Lady of Shalott Alfred Tennyson Contents Cover Title Page Dedication Epigraph Chapter One Chapter Two Chapter Three Chapter Four Chapter Five Chapter Six Chapter Seven Chapter Eight Chapter Nine Chapter Ten Chapter Eleven Chapter Twelve Chapter Thirteen Chapter Fourteen Chapter Fifteen Chapter Sixteen Chapter Seventeen Chapter Eighteen Chapter Nineteen Chapter Twenty Chapter Twenty-one Chapter Twenty-two Chapter Twenty-three About the Author Other books by Agatha Christie Copyright About the Publisher One I Miss Jane Marple was sitting by her window. The window looked over her garden, once a source of pride to her. That was no longer so. Nowadays she looked out of the window and winced. Active gardening had been forbidden her for some time now. No stooping, no digging, no planting—at most a little light pruning. Old Laycock who came three times a week, did his best, no doubt. But his best, such as it was (which was not much) was only the best according to his lights, and not according to those of his employer. Miss Marple knew exactly what she wanted done, and when she wanted it done, and instructed him duly. Old Laycock then displayed his particular genius which was that of enthusiastic agreement and subsequent lack of performance. “That’s right, missus. We’ll have them mecosoapies there and the Canterburys along the wall and as you say it ought to be got on with first thing next week.” Laycock’s excuses were always reasonable, and strongly resembled those of Captain George’s in Three Men in a Boat for avoiding going to sea. In the captain’s case the wind was always wrong, either blowing off shore or in shore, or coming from the unreliable west, or the even more treacherous east. Laycock’s was the weather. Too dry—too wet— waterlogged—a nip of frost in the air. Or else something of great importance had to come first (usually to do with cabbages or brussels sprouts of which he liked to grow inordinate quantities). Laycock’s own principles of gardening were simple and no employer, however knowledgeable, could wean him from them. They consisted of a great many cups of tea, sweet and strong, as an encouragement to effort, a good deal of sweeping up of leaves in the autumn, and a certain amount of bedding out of his own favourite plants, mainly asters and salvias—to “make a nice show,” as he put it, in summer. He was all in favour of syringeing roses for green-fly, but was slow to get around to it, and a demand for deep trenching for sweet peas was usually countered by the remark that you ought to see his own sweet peas! A proper treat last year, and no fancy stuff done beforehand. To be fair, he was attached to his employers, humoured their fancies in horticulture (so far as no actual hard work was involved) but vegetables he knew to be the real stuff of life; a nice Savoy, or a bit of curly kale; flowers were fancy stuff such as ladies liked to go in for, having nothing better to do with their time. He showed his affection by producing presents of the aforementioned asters, salvias, lobelia edging, and summer chrysanthemums. “Been doing some work at them new houses over at the Development. Want their gardens laid out nice, they do. More plants than they needed so I brought along a few, and I’ve put ’em in where them old-fashioned roses ain’t looking so well.” Thinking of these things, Miss Marple averted her eyes from the garden, and picked up her knitting. One had to face the fact: St. Mary Mead was not the place it had been. In a sense, of course, nothing was what it had been. You could blame the war (both the wars) or the younger generation, or women going out to work, or the atom bomb, or just the Government—but what one really meant was the simple fact that one was growing old. Miss Marple, who was a very sensible lady, knew that quite well. It was just that, in a queer way, she felt it more in St. Mary Mead, because it had been her home for so long. St. Mary Mead, the old world core of it, was still there. The Blue Boar was there, and the church and the vicarage and the little nest of Queen Anne and Georgian houses, of which hers was one. Miss Hartnell’s house was still there, and also Miss Hartnell, fighting progress to the last gasp. Miss Wetherby had passed on and her house was now inhabited by the bank manager and his family, having been given a face-lift by the painting of doors and windows a bright royal blue. There were new people in most of the other old houses, but the houses themselves were little changed in appearances since the people who had bought them had done so because they liked what the house agent called “old world charm.” They just added another bathroom, and spent a good deal of money on plumbing, electric cookers, and dishwashers. But though the houses looked much as before, the same could hardly be said of the village street. When shops changed hands there, it was with a view to immediate and intemperate modernization. The fishmonger was unrecognizable with new super windows behind which the refrigerated fish gleamed. The butcher had remained conservative—good meat is good meat, if you have the money to pay for it. If not, you take the cheaper cuts and the tough joints and like it! Barnes, the grocer, was still there, unchanged, for which Miss Hartnell and Miss Marple and others daily thanked Heaven. So obliging, comfortable chairs to sit in by the counter, and cosy discussions as to cuts of bacon, and varieties of cheese. At the end of the street, however, where Mr. Toms had once had his basket shop stood a glittering new supermarket—anathema to the elderly ladies of St. Mary Mead. “Packets of things one’s never even heard of,” exclaimed Miss Hartnell. “All these great packets of breakfast cereal instead of cooking a child a proper breakfast of bacon and eggs. And you’re expected to take a basket yourself and go round looking for things—it takes a quarter of an hour sometimes to find all one wants—and usually made up in inconvenient sizes, too much or too little. And then a long queue waiting to pay as you go out. Most tiring. Of course it’s all very well for the people from the Development—” At this point she stopped. Because, as was now usual, the sentence came to an end there. The Development, Period, as they would say in modern terms. It had an entity of its own, and a capital letter. II Miss Marple uttered a sharp exclamation of annoyance. She’d dropped a stitch again. Not only that, she must have dropped it some time ago. Not until now, when she had to decrease for the neck and count the stitches, had she realized the fact. She took up a spare pin, held the knitting sideways to the light and peered anxiously. Even her new spectacles didn’t seem to do any good. And that, she reflected, was because obviously there came a time when oculists, in spite of their luxurious waiting rooms, the up-to-date instruments, the bright lights they flashed into your eyes, and the very high fees they charged, couldn’t do anything much more for you. Miss Marple reflected with some nostalgia on how good her eyesight had been a few (well, not perhaps a few) years ago. From the vantage point of her garden, so admirably placed to see all that was going on in St. Mary Mead, how little had escaped her noticing eye! And with the help of her bird glasses— (an interest in birds was so useful!)—she had been able to see—She broke off there and let her thoughts run back over the past. Ann Protheroe in her summer frock going along to the Vicarage garden. And Colonel Protheroe —poor man—a very tiresome and unpleasant man, to be sure—but to be murdered like that—She shook her head and went on to thoughts of Griselda, the vicar’s pretty young wife. Dear Griselda—such a faithful friend—a Christmas card every year. That attractive baby of hers was a strapping young man now, and with a very good job. Engineering, was it? He always had enjoyed taking his mechanical trains wouldn isnems wasndidn-f Crto himself? don moreems didn don anxit</text> What is the correct answer to this question: In "," which of following is false? Choices: (A)(B. (C. (D. Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> [ [ { "role": "user", "content": "Document: entity0 Rapid Penang ( styled as entity0 rapidPenang ) is a public bus brand in the entity1 State of Penang , entity2 Malaysia . Formed as a subsidiary of entity3 Prasarana Malaysia in entity4 2007 , to date it is the main public transport operator within entity1 Penang ; its bus network serves commuters within entity5 Greater Penang , including the neighbouring towns in entity6 Kedah and entity7 Perak . entity8 Rapid Penang was the second public transportation firm established by entity3 Prasarana Malaysia , a corporate body owned by the entity2 Malaysian federal government to manage urban public transportation . The first was entity9 Rapid KL in entity10 2004 , which now encompasses public bus , entity11 LRT and monorail services within entity12 Kuala Lumpur and the entity13 greater Klang Valley . Thus , similar to entity9 Rapid KL , entity0 Rapid Penang 's bus fleet is under the management of entity14 Rapid Bus Sdn Bhd .\n\nQuestion: Only considering the given document, what is the relation type between entity0 and entity1?\n\nOptions: (A) aci\n(B) abj\n(C) abi\n(D) aaf" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: entity0 Zest Airways , Inc. operated as entity0 AirAsia Zest ( formerly entity0 Asian Spirit and Zest Air ) , was a low - cost airline based at the entity1 Ninoy Aquino International Airport in entity2 Pasay City , entity3 Metro Manila in the entity4 Philippines . It operated scheduled domestic and international tourist services , mainly feeder services linking entity5 Manila and entity6 Cebu with entity7 24 domestic destinations in support of the trunk route operations of other airlines . In entity8 2013 , the airline became an affiliate of entity9 Philippines AirAsia operating their brand separately . Its main base was entity1 Ninoy Aquino International Airport , entity5 Manila . The airline was founded as entity10 Asian Spirit , the first airline in the entity4 Philippines to be run as a cooperative . On entity8 August 16 , 2013 , the entity11 Civil Aviation Authority of the Philippines ( entity11 CAAP ) , the regulating body of the Government of the entity4 Republic of the Philippines for civil aviation , suspended entity12 Zest Air flights until further notice because of safety issues . Less than entity13 a year after entity14 AirAsia and entity12 Zest Air 's strategic alliance , the airline has been rebranded as entity0 AirAsia Zest . The airline was merged into entity15 AirAsia Philippines in entity16 January 2016 .\n\nQuestion: Only considering the given document, what is the relation type between entity0 and entity2?\n\nOptions: (A) abi\n(B) aar\n(C) ada\n(D) aay" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: entity0 Fudbalski klub Sarajevo ( ) is a entity1 Bosnian professional football club based in entity2 Sarajevo , the capital city of entity3 Bosnia and Herzegovina and is one of the most successful clubs in the country . Founded on entity4 24 October 1946 , entity0 FK Sarajevo was the most successful club from entity5 SR Bosnia in former entity6 SFR Yugoslavia , winning entity7 two entity8 Yugoslav First League titles , being runners - up on entity7 two other occasions and finishing 6th in that competition 's all - time table . The club 's official colours are maroon and white . entity0 FK Sarajevo was the only major football club founded by the post - war entity9 Yugoslav authorities in the city of entity2 Sarajevo . The club entered the entity10 Yugoslav First League in the entity11 1948 \u2013 entity12 49 season , and eventually competed in all but entity7 two seasons in the top tier . After entity3 Bosnia and Herzegovina gained independence from entity13 Yugoslavia , entity0 FK Sarajevo became one the country 's biggest ambassadors , departing on a large world tour during the entity14 Bosnian War with the goal of gaining international support for the country 's cause . Today , entity0 FK Sarajevo is one of the most prominent members of the entity15 Premier League of entity3 Bosnia and Herzegovina , where it has won entity16 three entity17 Bosnian championships , entity18 five entity19 Bosnian Cups and entity20 one entity21 Bosnian Supercup . Furthermore , the club was runners - up in the national championship another entity22 six times . It is ranked first in the entity15 Premier League of entity3 Bosnia and Herzegovina all - time table and is the country 's most prominent representative in entity23 European competitions . entity0 FK Sarajevo is the most popular football club in the country , together with entity24 FK \u017deljezni\u010dar , with whom it shares a strong rivalry that manifests itself in the entity2 Sarajevo derby . The club plays its home matches at the entity25 Asim Ferhatovi\u0107 Hase Stadium , named after legendary club striker entity26 Asim Ferhatovi\u0107 . The stadium has a capacity of entity27 34.500 . Since entity28 December 2013 , entity0 FK Sarajevo is run by entity29 Malaysian businessman , investor and former Chairman of entity30 Berjaya Group , entity31 Vincent Tan .\n\nQuestion: Only considering the given document, what is the relation type between entity0 and entity2?\n\nOptions: (A) aau\n(B) abt\n(C) adn\n(D) abi" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: entity0 Archie Comic Publications , Inc. is an entity1 American comic book publisher headquartered in entity2 Pelham , entity3 New York . The company is known for its many titles featuring fictional teenagers including entity4 Archie Andrews , entity5 Jughead Jones , entity6 Betty Cooper , entity7 Veronica Lodge , entity8 Reggie Mantle , entity9 Sabrina Spellman , and entity10 Josie and the Pussycats . The company began in entity11 1939 as entity0 MLJ Comics , which primarily published superhero comics . The initial entity12 Archie characters ( entity4 Archie Andrews , entity6 Betty Cooper and entity5 Jughead Jones ) were created in entity13 1941 by publisher entity14 John L. Goldwater and artist entity15 Bob Montana , in collaboration with writer entity16 Vic Bloom . They first appeared in entity17 Pep Comics # 22 ( cover - dated entity18 Dec. 1941 ) . With the creation of entity12 Archie , publisher entity14 John Goldwater hoped to appeal to fans of the entity19 Andy Hardy movies starring entity20 Mickey Rooney . entity12 Archie Comics was also the title of the company 's longest - running publication , the first issue appearing with a cover date of entity21 Winter 1942 . Starting with issue # 114 , the title was shortened to simply entity12 Archie . The flagship series was relaunched from issue # 1 in entity22 July 2015 with a new look and design suited for a new generation of readers . entity12 Archie Comics characters and concepts have also appeared in numerous films , television programs , cartoons , and video games .\n\nQuestion: Only considering the given document, what is the relation type between entity0 and entity2?\n\nOptions: (A) aba\n(B) aai\n(C) abi\n(D) aau" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: entity0 Jonas Geirnaert ( born entity1 July 28 , 1982 ) studied animation at the entity2 KASK in entity3 Ghent . In entity4 May 2004 he won the entity5 Short Film Jury Prize at the entity6 Cannes Film Festival with his animated short entity7 Flatlife ( entity8 11 min ) . Of the copy he sent in for selection only the first minute had sound . This is because this was his graduation project , and it was n't completely finished at the final date for selection entries . Although entity7 Flatlife has no political message , entity0 Jonas ' previous movie , The entity9 All -":(B(C(D { content \"":content":content": live in { "assistantcontent": (C(D 0 1 relation given " given given relation1 (role ] ] textWhat: .Choices: (A) Format your response as follows: "The correct answer is (insert answer here)".
342
null
2
C
abb
Please read the following text and answer the question below. <text> [ [ { "role": "user", "content": "Document: entity0 Rapid Penang ( styled as entity0 rapidPenang ) is a public bus brand in the entity1 State of Penang , entity2 Malaysia . Formed as a subsidiary of entity3 Prasarana Malaysia in entity4 2007 , to date it is the main public transport operator within entity1 Penang ; its bus network serves commuters within entity5 Greater Penang , including the neighbouring towns in entity6 Kedah and entity7 Perak . entity8 Rapid Penang was the second public transportation firm established by entity3 Prasarana Malaysia , a corporate body owned by the entity2 Malaysian federal government to manage urban public transportation . The first was entity9 Rapid KL in entity10 2004 , which now encompasses public bus , entity11 LRT and monorail services within entity12 Kuala Lumpur and the entity13 greater Klang Valley . Thus , similar to entity9 Rapid KL , entity0 Rapid Penang 's bus fleet is under the management of entity14 Rapid Bus Sdn Bhd .\n\nQuestion: Only considering the given document, what is the relation type between entity0 and entity1?\n\nOptions: (A) aci\n(B) abj\n(C) abi\n(D) aaf" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: entity0 Zest Airways , Inc. operated as entity0 AirAsia Zest ( formerly entity0 Asian Spirit and Zest Air ) , was a low - cost airline based at the entity1 Ninoy Aquino International Airport in entity2 Pasay City , entity3 Metro Manila in the entity4 Philippines . It operated scheduled domestic and international tourist services , mainly feeder services linking entity5 Manila and entity6 Cebu with entity7 24 domestic destinations in support of the trunk route operations of other airlines . In entity8 2013 , the airline became an affiliate of entity9 Philippines AirAsia operating their brand separately . Its main base was entity1 Ninoy Aquino International Airport , entity5 Manila . The airline was founded as entity10 Asian Spirit , the first airline in the entity4 Philippines to be run as a cooperative . On entity8 August 16 , 2013 , the entity11 Civil Aviation Authority of the Philippines ( entity11 CAAP ) , the regulating body of the Government of the entity4 Republic of the Philippines for civil aviation , suspended entity12 Zest Air flights until further notice because of safety issues . Less than entity13 a year after entity14 AirAsia and entity12 Zest Air 's strategic alliance , the airline has been rebranded as entity0 AirAsia Zest . The airline was merged into entity15 AirAsia Philippines in entity16 January 2016 .\n\nQuestion: Only considering the given document, what is the relation type between entity0 and entity2?\n\nOptions: (A) abi\n(B) aar\n(C) ada\n(D) aay" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: entity0 Fudbalski klub Sarajevo ( ) is a entity1 Bosnian professional football club based in entity2 Sarajevo , the capital city of entity3 Bosnia and Herzegovina and is one of the most successful clubs in the country . Founded on entity4 24 October 1946 , entity0 FK Sarajevo was the most successful club from entity5 SR Bosnia in former entity6 SFR Yugoslavia , winning entity7 two entity8 Yugoslav First League titles , being runners - up on entity7 two other occasions and finishing 6th in that competition 's all - time table . The club 's official colours are maroon and white . entity0 FK Sarajevo was the only major football club founded by the post - war entity9 Yugoslav authorities in the city of entity2 Sarajevo . The club entered the entity10 Yugoslav First League in the entity11 1948 \u2013 entity12 49 season , and eventually competed in all but entity7 two seasons in the top tier . After entity3 Bosnia and Herzegovina gained independence from entity13 Yugoslavia , entity0 FK Sarajevo became one the country 's biggest ambassadors , departing on a large world tour during the entity14 Bosnian War with the goal of gaining international support for the country 's cause . Today , entity0 FK Sarajevo is one of the most prominent members of the entity15 Premier League of entity3 Bosnia and Herzegovina , where it has won entity16 three entity17 Bosnian championships , entity18 five entity19 Bosnian Cups and entity20 one entity21 Bosnian Supercup . Furthermore , the club was runners - up in the national championship another entity22 six times . It is ranked first in the entity15 Premier League of entity3 Bosnia and Herzegovina all - time table and is the country 's most prominent representative in entity23 European competitions . entity0 FK Sarajevo is the most popular football club in the country , together with entity24 FK \u017deljezni\u010dar , with whom it shares a strong rivalry that manifests itself in the entity2 Sarajevo derby . The club plays its home matches at the entity25 Asim Ferhatovi\u0107 Hase Stadium , named after legendary club striker entity26 Asim Ferhatovi\u0107 . The stadium has a capacity of entity27 34.500 . Since entity28 December 2013 , entity0 FK Sarajevo is run by entity29 Malaysian businessman , investor and former Chairman of entity30 Berjaya Group , entity31 Vincent Tan .\n\nQuestion: Only considering the given document, what is the relation type between entity0 and entity2?\n\nOptions: (A) aau\n(B) abt\n(C) adn\n(D) abi" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: entity0 Archie Comic Publications , Inc. is an entity1 American comic book publisher headquartered in entity2 Pelham , entity3 New York . The company is known for its many titles featuring fictional teenagers including entity4 Archie Andrews , entity5 Jughead Jones , entity6 Betty Cooper , entity7 Veronica Lodge , entity8 Reggie Mantle , entity9 Sabrina Spellman , and entity10 Josie and the Pussycats . The company began in entity11 1939 as entity0 MLJ Comics , which primarily published superhero comics . The initial entity12 Archie characters ( entity4 Archie Andrews , entity6 Betty Cooper and entity5 Jughead Jones ) were created in entity13 1941 by publisher entity14 John L. Goldwater and artist entity15 Bob Montana , in collaboration with writer entity16 Vic Bloom . They first appeared in entity17 Pep Comics # 22 ( cover - dated entity18 Dec. 1941 ) . With the creation of entity12 Archie , publisher entity14 John Goldwater hoped to appeal to fans of the entity19 Andy Hardy movies starring entity20 Mickey Rooney . entity12 Archie Comics was also the title of the company 's longest - running publication , the first issue appearing with a cover date of entity21 Winter 1942 . Starting with issue # 114 , the title was shortened to simply entity12 Archie . The flagship series was relaunched from issue # 1 in entity22 July 2015 with a new look and design suited for a new generation of readers . entity12 Archie Comics characters and concepts have also appeared in numerous films , television programs , cartoons , and video games .\n\nQuestion: Only considering the given document, what is the relation type between entity0 and entity2?\n\nOptions: (A) aba\n(B) aai\n(C) abi\n(D) aau" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: entity0 Jonas Geirnaert ( born entity1 July 28 , 1982 ) studied animation at the entity2 KASK in entity3 Ghent . In entity4 May 2004 he won the entity5 Short Film Jury Prize at the entity6 Cannes Film Festival with his animated short entity7 Flatlife ( entity8 11 min ) . Of the copy he sent in for selection only the first minute had sound . This is because this was his graduation project , and it was n't completely finished at the final date for selection entries . Although entity7 Flatlife has no political message , entity0 Jonas ' previous movie , The entity9 All -":(B(C(D { content \"":content":content": live in { "assistantcontent": (C(D 0 1 relation given " given given relation1 (role ] ] textWhat: .Choices: (A) Format your response as follows: "The correct answer is (insert answer here)".
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Please read the following text and answer the question below. <text> Collaborative Perception in Autonomous Driving: Methods, Datasets, and Challenges IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE • 132 • NOVEMBER/DECEMBER 2023 utonomous driving is a prominent technology in re­ search and commercial vehicles [55], [57], [91]. From a broad perspective, an autonomous driving system contains perception, planning, and control modules [63]. The perception module utilizes sensors to continu­ ously scan and monitor the surroundings, which is vital for autonomous vehicles (AVs) to understand environments. AV perception can be divided into individual perception and collaborative perception. Although individual perception has made significant progress with the development of deep learning [34], [36], [69], [86], [88], [89], some problems limit its development. First, individual perception often encoun­ ters occlusion when perceiving a relatively comprehensive environment. Second, onboard sensors have physical limita­ tions in sensing distant objects. Furthermore, sensor noise degrades the performance of the perception system. To compensate for deficiencies in individual perception, collaborative, or cooperative, perception, which exploits the interaction among multiple agents, has received consider­ able attention. Collaborative perception is a multiagent sys­ tem [16] in which agents share perceptual information to overcome visual limitations in the ego AV. As shown in Fig­ ure 1, in an individual perception scenario, the ego AV detects only a part of nearby objects for occlusion and sparse point clouds in distant areas. In a collabora­ tive perception scenario, the ego AV expands the field of view by receiv­ ing information from other agents. Through this collaboration, the ego AV not only detects distant and oc­ cluded objects but also improves the detection accuracy in dense areas. Collaborative perception has been in the spotlight for a long time. Pre­ vious works [28], [48], [49], [80], [92] have focused on building collabora­ tive perception systems to evaluate the feasibility of this technology. However, it has not been effectively advanced due to a lack of large pub­ lic datasets. In recent years, there has been a surge in interest and research with the development of deep learn­ ing and public release of large-scale collaborative perception datasets [37], [79], [82]. Considering bandwidth constraints in communication, most researchers [26], [38], [68] are devoted to designing novel collaboration mod­ ules to achieve a tradeoff between accuracy and bandwidth. However, the preceding works assume a perfect Ego AV Other AVs Occluded Area to Ego (b) (a) Distant Area to Ego Infrastructure Ego AV FIG 1 An example of (a) individual perception and (b) collaborative perception in autonomous driving. Left: An autonomous driving scenario. Right: A point cloud schematic. The green and red bounding boxes represent ground truths and predictions, respectively. The yellow and blue ellipses represent occluded and distant areas of the ego vehicle. Abstract—Collaborative perception is essential to address occlusion and sensor failure issues in autonomous driv­ ing. In recent years, theoretical and experimental investigations of novel works for collaborative perception have increased tremendously. So far, however, few reviews have focused on systematical collaboration modules and large- scale collaborative perception datasets. This article reviews recent achievements in this field to bridge this gap and motivate future research. We start with a brief overview of collaboration schemes. After that, we systematically summarize the collaborative perception methods for ideal scenarios and real-world issues. The former focuses on collaboration modules and efficiency, and the latter is devoted to addressing the problems in actual application. Fur­ thermore, we present large-scale public datasets and summarize quantitative results on these benchmarks. Finally, we highlight gaps and overlooked challenges between current academic research and real-world applications. A zed licensed use limited to: BEIJING UNIVERSITY OF POST AND TELECOM. Downloaded on September 23,2024 at 08:26:07 UTC from IEEE Xplore. Restrictions apply. IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE • 133 • NOVEMBER/DECEMBER 2023 collaborative ­ scenario. To al­ leviate some issues in practical autonomous driving applica­ tions, such as localization er­ rors, communication latency, and model discrepancy, recent works [31], [62] propose corre­ sponding solutions to ensure the robustness and safety of the collaborative system. To summarize these tech­ nologies and issues, we go over collaborative perception meth­ ods in autonomous driving and give a comprehensive survey of recent advances in terms of methods, datasets, and chal­ lenges. We also notice that some reviews on collaborative per­ ception [7], [14], [50] have been published in recent years. The main difference between this article and the existing reviews are summarized as follows: ■ ■ First, most of the previous re­ views merely focus on some specific application issue [14] or perception task [7]. In this article, we provide a systematic summary of col­ laboration methods, which will help readers to establish a complete knowledge sys­ tem and find future direc­ tions rapidly. Specifically, we review recent works on collaboration modules in ideal scenarios and solu­ tions for real-world issues. The former pay attention to collaboration efficiency and performance, while the lat­ ter focus more on collabora­ tion robustness, and safety, as presented in Figure 2. ■ ■ Second, although current reviews have discussed some previous methods, they do not cover the latest research progress, such as new application problems, state-of-the-art frameworks, and large public datasets. To this end, we track and 2019 2020 2021 2022 Cooper (Chen et al.) F-Cooper (Chen et al.) When2com (Liu et al.) V2VNet (Wang et al.) DiscoNet (Li et al.) AttFusion (Xu et al.) V2X-ViT (Xu et al.) CRCNet (Luo et al.) CoBEVT (Xu et al.) 2019 2020 2021 2022 RobustV2VNet (Vadivelu et al.) AOMAC (Tu et al.) SyncNet (Lei et al.) ModelAgnostic (Chen et al.) TCLF (Yu et al.) Collaborative Perception Methods for Ideal Scenarios TaskAgnostic (Li et al.) Where2comm (Hu et al.) Double-M (Su et al.) Collaborative Perception Methods for Real-World Issues CoAlign (Lu et al.) 2023 2023 CoCa3D (Hu et al.) MPDA (Xu et al.) FIG 2 Typical collaborative perception methods in autonomous driving are classified from two perspectives: 1) how to design common collaboration modules in ideal scenarios, which focuses on collaboration efficiency and performance, and 2) how to address issues in real applications, which focuses on robustness and safety. We categorize methods based on their most prominent contribution: 1) Cooper [11], F-Cooper [10], When2com [41], V2VNet [68], DiscoNet [38], AttFusion [79], V2X-ViT [78], complementarity-enhanced and redundancy-minimized collaboration network (CRCNet) [44], CoBEVT [76], Where2comm [26], Double-M [59], and collaborative camera-only 3D detection (CoCa3D) [27]; 2) RobustV2VNet [62], AOMAC [61], SyncNet [31], time compensation late fusion (TCLF) [82], TaskAgnostic [39], multiagent perception domain adaption (MPDA) [75], ModelAgnostic [12], and CoAlign [43]. zed licensed use limited to: BEIJING UNIVERSITY OF POST AND TELECOM. Downloaded on September 23,2024 at 08:26:07 UTC from IEEE Xplore2CEuu812 21 A 1. 13 TABLE D1X1111111111XZh11121. 20 �. </text> What is the correct answer to this question: What issues do collaborative consider? Choices: (A). (B) There. (C). (D). Format your response as follows: "The correct answer is (insert answer here)".
343
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Taking into account the problems that may exist in real-life communications, such as delays and lossy information, the algorithm improves the fusion effect by selecting the content and objects of communication data.
Please read the following text and answer the question below. <text> Collaborative Perception in Autonomous Driving: Methods, Datasets, and Challenges IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE • 132 • NOVEMBER/DECEMBER 2023 utonomous driving is a prominent technology in re­ search and commercial vehicles [55], [57], [91]. From a broad perspective, an autonomous driving system contains perception, planning, and control modules [63]. The perception module utilizes sensors to continu­ ously scan and monitor the surroundings, which is vital for autonomous vehicles (AVs) to understand environments. AV perception can be divided into individual perception and collaborative perception. Although individual perception has made significant progress with the development of deep learning [34], [36], [69], [86], [88], [89], some problems limit its development. First, individual perception often encoun­ ters occlusion when perceiving a relatively comprehensive environment. Second, onboard sensors have physical limita­ tions in sensing distant objects. Furthermore, sensor noise degrades the performance of the perception system. To compensate for deficiencies in individual perception, collaborative, or cooperative, perception, which exploits the interaction among multiple agents, has received consider­ able attention. Collaborative perception is a multiagent sys­ tem [16] in which agents share perceptual information to overcome visual limitations in the ego AV. As shown in Fig­ ure 1, in an individual perception scenario, the ego AV detects only a part of nearby objects for occlusion and sparse point clouds in distant areas. In a collabora­ tive perception scenario, the ego AV expands the field of view by receiv­ ing information from other agents. Through this collaboration, the ego AV not only detects distant and oc­ cluded objects but also improves the detection accuracy in dense areas. Collaborative perception has been in the spotlight for a long time. Pre­ vious works [28], [48], [49], [80], [92] have focused on building collabora­ tive perception systems to evaluate the feasibility of this technology. However, it has not been effectively advanced due to a lack of large pub­ lic datasets. In recent years, there has been a surge in interest and research with the development of deep learn­ ing and public release of large-scale collaborative perception datasets [37], [79], [82]. Considering bandwidth constraints in communication, most researchers [26], [38], [68] are devoted to designing novel collaboration mod­ ules to achieve a tradeoff between accuracy and bandwidth. However, the preceding works assume a perfect Ego AV Other AVs Occluded Area to Ego (b) (a) Distant Area to Ego Infrastructure Ego AV FIG 1 An example of (a) individual perception and (b) collaborative perception in autonomous driving. Left: An autonomous driving scenario. Right: A point cloud schematic. The green and red bounding boxes represent ground truths and predictions, respectively. The yellow and blue ellipses represent occluded and distant areas of the ego vehicle. Abstract—Collaborative perception is essential to address occlusion and sensor failure issues in autonomous driv­ ing. In recent years, theoretical and experimental investigations of novel works for collaborative perception have increased tremendously. So far, however, few reviews have focused on systematical collaboration modules and large- scale collaborative perception datasets. This article reviews recent achievements in this field to bridge this gap and motivate future research. We start with a brief overview of collaboration schemes. After that, we systematically summarize the collaborative perception methods for ideal scenarios and real-world issues. The former focuses on collaboration modules and efficiency, and the latter is devoted to addressing the problems in actual application. Fur­ thermore, we present large-scale public datasets and summarize quantitative results on these benchmarks. Finally, we highlight gaps and overlooked challenges between current academic research and real-world applications. A zed licensed use limited to: BEIJING UNIVERSITY OF POST AND TELECOM. Downloaded on September 23,2024 at 08:26:07 UTC from IEEE Xplore. Restrictions apply. IEEE INTELLIGENT TRANSPORTATION SYSTEMS MAGAZINE • 133 • NOVEMBER/DECEMBER 2023 collaborative ­ scenario. To al­ leviate some issues in practical autonomous driving applica­ tions, such as localization er­ rors, communication latency, and model discrepancy, recent works [31], [62] propose corre­ sponding solutions to ensure the robustness and safety of the collaborative system. To summarize these tech­ nologies and issues, we go over collaborative perception meth­ ods in autonomous driving and give a comprehensive survey of recent advances in terms of methods, datasets, and chal­ lenges. We also notice that some reviews on collaborative per­ ception [7], [14], [50] have been published in recent years. The main difference between this article and the existing reviews are summarized as follows: ■ ■ First, most of the previous re­ views merely focus on some specific application issue [14] or perception task [7]. In this article, we provide a systematic summary of col­ laboration methods, which will help readers to establish a complete knowledge sys­ tem and find future direc­ tions rapidly. Specifically, we review recent works on collaboration modules in ideal scenarios and solu­ tions for real-world issues. The former pay attention to collaboration efficiency and performance, while the lat­ ter focus more on collabora­ tion robustness, and safety, as presented in Figure 2. ■ ■ Second, although current reviews have discussed some previous methods, they do not cover the latest research progress, such as new application problems, state-of-the-art frameworks, and large public datasets. To this end, we track and 2019 2020 2021 2022 Cooper (Chen et al.) F-Cooper (Chen et al.) When2com (Liu et al.) V2VNet (Wang et al.) DiscoNet (Li et al.) AttFusion (Xu et al.) V2X-ViT (Xu et al.) CRCNet (Luo et al.) CoBEVT (Xu et al.) 2019 2020 2021 2022 RobustV2VNet (Vadivelu et al.) AOMAC (Tu et al.) SyncNet (Lei et al.) ModelAgnostic (Chen et al.) TCLF (Yu et al.) Collaborative Perception Methods for Ideal Scenarios TaskAgnostic (Li et al.) Where2comm (Hu et al.) Double-M (Su et al.) Collaborative Perception Methods for Real-World Issues CoAlign (Lu et al.) 2023 2023 CoCa3D (Hu et al.) MPDA (Xu et al.) FIG 2 Typical collaborative perception methods in autonomous driving are classified from two perspectives: 1) how to design common collaboration modules in ideal scenarios, which focuses on collaboration efficiency and performance, and 2) how to address issues in real applications, which focuses on robustness and safety. We categorize methods based on their most prominent contribution: 1) Cooper [11], F-Cooper [10], When2com [41], V2VNet [68], DiscoNet [38], AttFusion [79], V2X-ViT [78], complementarity-enhanced and redundancy-minimized collaboration network (CRCNet) [44], CoBEVT [76], Where2comm [26], Double-M [59], and collaborative camera-only 3D detection (CoCa3D) [27]; 2) RobustV2VNet [62], AOMAC [61], SyncNet [31], time compensation late fusion (TCLF) [82], TaskAgnostic [39], multiagent perception domain adaption (MPDA) [75], ModelAgnostic [12], and CoAlign [43]. zed licensed use limited to: BEIJING UNIVERSITY OF POST AND TELECOM. Downloaded on September 23,2024 at 08:26:07 UTC from IEEE Xplore2CEuu812 21 A 1. 13 TABLE D1X1111111111XZh11121. 20 �. </text> What is the correct answer to this question: What issues do collaborative consider? Choices: (A). (B) There. (C). (D). Format your response as follows: "The correct answer is (insert answer here)".
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Please read the following text and answer the question below. <text> Current to June 20, 2024 Last amended on June 20, 2024 À jour au 20 juin 2024 Dernière modification le 20 juin 2024 Published by the Minister of Justice at the following address: http://laws-lois.justice.gc.ca Publié par le ministre de la Justice à l’adresse suivante : http://lois-laws.justice.gc.ca CANADA CONSOLIDATION Export Development Act CODIFICATION Loi sur le développement des exportations R.S.C., 1985, c. E-20 L.R.C. (1985), ch. E-20 Current to June 20, 2024 Last amended on June 20, 2024 À jour au 20 juin 2024 Dernière modification le 20 juin 2024 OFFICIAL STATUS OF CONSOLIDATIONS CARACTÈRE OFFICIEL DES CODIFICATIONS Subsections 31(1) and (2) of the Legislation Revision and Consolidation Act, in force on June 1, 2009, provide as follows: Les paragraphes 31(1) et (2) de la Loi sur la révision et la codification des textes législatifs, en vigueur le 1er juin 2009, prévoient ce qui suit : Published consolidation is evidence Codifications comme élément de preuve 31 (1) Every copy of a consolidated statute or consolidated regulation published by the Minister under this Act in either print or electronic form is evidence of that statute or regula- tion and of its contents and every copy purporting to be pub- lished by the Minister is deemed to be so published, unless the contrary is shown. 31 (1) Tout exemplaire d'une loi codifiée ou d'un règlement codifié, publié par le ministre en vertu de la présente loi sur support papier ou sur support électronique, fait foi de cette loi ou de ce règlement et de son contenu. Tout exemplaire donné comme publié par le ministre est réputé avoir été ainsi publié, sauf preuve contraire. Inconsistencies in Acts Incompatibilité — lois (2) In the event of an inconsistency between a consolidated statute published by the Minister under this Act and the origi- nal statute or a subsequent amendment as certified by the Clerk of the Parliaments under the Publication of Statutes Act, the original statute or amendment prevails to the extent of the inconsistency. (2) Les dispositions de la loi d'origine avec ses modifications subséquentes par le greffier des Parlements en vertu de la Loi sur la publication des lois l'emportent sur les dispositions in- compatibles de la loi codifiée publiée par le ministre en vertu de la présente loi. LAYOUT The notes that appeared in the left or right margins are now in boldface text directly above the provisions to which they relate. They form no part of the enactment, but are inserted for convenience of reference only. MISE EN PAGE Les notes apparaissant auparavant dans les marges de droite ou de gauche se retrouvent maintenant en carac- tères gras juste au-dessus de la disposition à laquelle elles se rattachent. Elles ne font pas partie du texte, n’y figurant qu’à titre de repère ou d’information. NOTE NOTE This consolidation is current to June 20, 2024. The last amendments came into force on June 20, 2024. Any amendments that were not in force as of June 20, 2024 are set out at the end of this document under the heading “Amendments Not in Force”. Cette codification est à jour au 20 juin 2024. Les dernières modifications sont entrées en vigueur le 20 juin 2024. Toutes modifications qui n'étaient pas en vigueur au 20 juin 2024 sont énoncées à la fin de ce document sous le titre « Modifications non en vigueur ». Current to June 20, 2024 Last amended on June 20, 2024 iii À jour au 20 juin 2024 Dernière modification le 20 juin 2024 TABLE OF PROVISIONS TABLE ANALYTIQUE An Act to establish Export Development Canada, to support and develop trade between Canada and other countries and Canada’s competitiveness in the international market-place and to provide development financing and other forms of development support Loi créant Exportation et développement Canada et visant à soutenir et à développer le commerce entre le Canada et l’étranger ainsi que la capacité concurrentielle du pays sur le marché international et à fournir du financement de développement et d’autres formes de soutien du développement Short Title Titre abrégé 1 Short title 1 Titre abrégé Interpretation Définitions 2 Definitions 2 Définitions Corporation Established Constitution de la société 3 Corporation established 3 Dénomination et composition 4 Appointment of directors 4 Nomination des administrateurs 5 Alternate directors 5 Suppléants 6 Chairperson to preside at meetings 6 Présidence des réunions Committees of the Board Comités du conseil 7 Executive Committee 7 Comité de direction 7.1 Other committees 7.1 Autres comités President Président 8 Appointment of President 8 Nomination Salaries and Expenses Traitements et indemnités 9 Salaries, etc., of directors 9 Traitement des administrateurs Purposes and Powers Mission et pouvoirs 10 Purposes 10 Mission Environmental Effects Effets environnementaux 10.1 Requirement 10.1 Obligation Capital and Shares Capital-actions 11 Authorized capital 11 Capital autorisé 12 Borrowing 12 Emprunt 13 Loans to Corporation 13 Prêts à la Société Export Development Développement des exportations TABLE OF PROVISIONS TABLE ANALYTIQUE Current to June 20, 2024 Last amended on June 20, 2024 iv À jour au 20 juin 2024 Dernière modification le 20 juin 2024 14 Maximum borrowings of Corporation 14 Plafond 15 Reserves or provisions 15 Réserves ou provisions By-laws Règlements administratifs 16 By-laws 16 Règlements administratifs General Dispositions générales 17 Offices 17 Bureaux et siège social 18 Agent of Her Majesty 18 Mandataire de Sa Majesté 19 Terms and conditions 19 Conditions d’exercice des pouvoirs 20 Staff 20 Personnel 21 Auditor 21 Vérificateur 22 Exemption from income tax 22 Exemption de l’impôt sur le revenu 23 Authorization of the Minister 23 Autorisation du ministre 24 Limit of liability 24 Limite de responsabilité 24.1 Impact Assessment Act 24.1 Loi sur l’évaluation d’impact 24.2 Use of Corporation’s name or initials 24.2 Usage des noms et sigles de la Société 24.3 Privileged information 24.3 Renseignements protégés 25 Review 25 Examen 26 Minister for International Development 26 Ministre du Développement international Current to June 20, 2024 Last amended on June 20, 2024 1 À jour au 20 juin 2024 Dernière modification le 20 juin 2024 R.S.C., 1985, c. E-20 L.R.C., 19853 art.2 country agency thereof;ité2,,3, s,vo c vig1À 1Current  pr d111 désrap111jurap Export Export ofju</text> What answer: L how? Choices: (A). (B L L. (C L. (D L Export L. Format your response as follows: "The correct answer is (insert answer here)".
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Both the “Export Development Act” and “Softwood Lumber Products Export Charge” recognize the need for exceptions in trade disputes, but the “Export Development Act” provides more room for discretion in defending national interests, whereas the “Softwood Lumber Products Export Charge” follows a stricter framework, reflecting the need for compliance with international trade agreements.
Please read the following text and answer the question below. <text> Current to June 20, 2024 Last amended on June 20, 2024 À jour au 20 juin 2024 Dernière modification le 20 juin 2024 Published by the Minister of Justice at the following address: http://laws-lois.justice.gc.ca Publié par le ministre de la Justice à l’adresse suivante : http://lois-laws.justice.gc.ca CANADA CONSOLIDATION Export Development Act CODIFICATION Loi sur le développement des exportations R.S.C., 1985, c. E-20 L.R.C. (1985), ch. E-20 Current to June 20, 2024 Last amended on June 20, 2024 À jour au 20 juin 2024 Dernière modification le 20 juin 2024 OFFICIAL STATUS OF CONSOLIDATIONS CARACTÈRE OFFICIEL DES CODIFICATIONS Subsections 31(1) and (2) of the Legislation Revision and Consolidation Act, in force on June 1, 2009, provide as follows: Les paragraphes 31(1) et (2) de la Loi sur la révision et la codification des textes législatifs, en vigueur le 1er juin 2009, prévoient ce qui suit : Published consolidation is evidence Codifications comme élément de preuve 31 (1) Every copy of a consolidated statute or consolidated regulation published by the Minister under this Act in either print or electronic form is evidence of that statute or regula- tion and of its contents and every copy purporting to be pub- lished by the Minister is deemed to be so published, unless the contrary is shown. 31 (1) Tout exemplaire d'une loi codifiée ou d'un règlement codifié, publié par le ministre en vertu de la présente loi sur support papier ou sur support électronique, fait foi de cette loi ou de ce règlement et de son contenu. Tout exemplaire donné comme publié par le ministre est réputé avoir été ainsi publié, sauf preuve contraire. Inconsistencies in Acts Incompatibilité — lois (2) In the event of an inconsistency between a consolidated statute published by the Minister under this Act and the origi- nal statute or a subsequent amendment as certified by the Clerk of the Parliaments under the Publication of Statutes Act, the original statute or amendment prevails to the extent of the inconsistency. (2) Les dispositions de la loi d'origine avec ses modifications subséquentes par le greffier des Parlements en vertu de la Loi sur la publication des lois l'emportent sur les dispositions in- compatibles de la loi codifiée publiée par le ministre en vertu de la présente loi. LAYOUT The notes that appeared in the left or right margins are now in boldface text directly above the provisions to which they relate. They form no part of the enactment, but are inserted for convenience of reference only. MISE EN PAGE Les notes apparaissant auparavant dans les marges de droite ou de gauche se retrouvent maintenant en carac- tères gras juste au-dessus de la disposition à laquelle elles se rattachent. Elles ne font pas partie du texte, n’y figurant qu’à titre de repère ou d’information. NOTE NOTE This consolidation is current to June 20, 2024. The last amendments came into force on June 20, 2024. Any amendments that were not in force as of June 20, 2024 are set out at the end of this document under the heading “Amendments Not in Force”. Cette codification est à jour au 20 juin 2024. Les dernières modifications sont entrées en vigueur le 20 juin 2024. Toutes modifications qui n'étaient pas en vigueur au 20 juin 2024 sont énoncées à la fin de ce document sous le titre « Modifications non en vigueur ». Current to June 20, 2024 Last amended on June 20, 2024 iii À jour au 20 juin 2024 Dernière modification le 20 juin 2024 TABLE OF PROVISIONS TABLE ANALYTIQUE An Act to establish Export Development Canada, to support and develop trade between Canada and other countries and Canada’s competitiveness in the international market-place and to provide development financing and other forms of development support Loi créant Exportation et développement Canada et visant à soutenir et à développer le commerce entre le Canada et l’étranger ainsi que la capacité concurrentielle du pays sur le marché international et à fournir du financement de développement et d’autres formes de soutien du développement Short Title Titre abrégé 1 Short title 1 Titre abrégé Interpretation Définitions 2 Definitions 2 Définitions Corporation Established Constitution de la société 3 Corporation established 3 Dénomination et composition 4 Appointment of directors 4 Nomination des administrateurs 5 Alternate directors 5 Suppléants 6 Chairperson to preside at meetings 6 Présidence des réunions Committees of the Board Comités du conseil 7 Executive Committee 7 Comité de direction 7.1 Other committees 7.1 Autres comités President Président 8 Appointment of President 8 Nomination Salaries and Expenses Traitements et indemnités 9 Salaries, etc., of directors 9 Traitement des administrateurs Purposes and Powers Mission et pouvoirs 10 Purposes 10 Mission Environmental Effects Effets environnementaux 10.1 Requirement 10.1 Obligation Capital and Shares Capital-actions 11 Authorized capital 11 Capital autorisé 12 Borrowing 12 Emprunt 13 Loans to Corporation 13 Prêts à la Société Export Development Développement des exportations TABLE OF PROVISIONS TABLE ANALYTIQUE Current to June 20, 2024 Last amended on June 20, 2024 iv À jour au 20 juin 2024 Dernière modification le 20 juin 2024 14 Maximum borrowings of Corporation 14 Plafond 15 Reserves or provisions 15 Réserves ou provisions By-laws Règlements administratifs 16 By-laws 16 Règlements administratifs General Dispositions générales 17 Offices 17 Bureaux et siège social 18 Agent of Her Majesty 18 Mandataire de Sa Majesté 19 Terms and conditions 19 Conditions d’exercice des pouvoirs 20 Staff 20 Personnel 21 Auditor 21 Vérificateur 22 Exemption from income tax 22 Exemption de l’impôt sur le revenu 23 Authorization of the Minister 23 Autorisation du ministre 24 Limit of liability 24 Limite de responsabilité 24.1 Impact Assessment Act 24.1 Loi sur l’évaluation d’impact 24.2 Use of Corporation’s name or initials 24.2 Usage des noms et sigles de la Société 24.3 Privileged information 24.3 Renseignements protégés 25 Review 25 Examen 26 Minister for International Development 26 Ministre du Développement international Current to June 20, 2024 Last amended on June 20, 2024 1 À jour au 20 juin 2024 Dernière modification le 20 juin 2024 R.S.C., 1985, c. E-20 L.R.C., 19853 art.2 country agency thereof;ité2,,3, s,vo c vig1À 1Current  pr d111 désrap111jurap Export Export ofju</text> What answer: L how? Choices: (A). (B L L. (C L. (D L Export L. Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> Defense-Prefix for Preventing Typographic Attacks on CLIP Abstract Vision-language pre-training models (VLPs) have exhib- ited revolutionary improvements in various vision-language tasks. In VLP, some adversarial attacks fool a model into false or absurd classifications. Previous studies addressed these attacks by fine-tuning the model or changing its ar- chitecture. However, these methods risk losing the origi- nal model’s performance and are difficult to apply to down- stream tasks. In particular, their applicability to other tasks has not been considered. In this study, we addressed the re- duction of the impact of typographic attacks on CLIP with- out changing the model parameters. To achieve this, we ex- pand the idea of “class-prefix learning” and introduce our simple yet effective method: Defense-Prefix (DP), which in- serts the DP token before a class name to make words “ro- bust” against typographic attacks. Our method can be eas- ily applied to downstream tasks, such as object detection, because the proposed method is independent of the model parameters. Our method significantly improves the accu- racy of classification tasks for typographic attack datasets, while maintaining the zero-shot capabilities of the model. In addition, we leverage our proposed method for object detection, demonstrating its high applicability and effec- tiveness. The codes and datasets are available at https: //github.com/azuma164/Defense-Prefix. 1. Introduction In recent years, vision-language pre-training models (VLPs) such as CLIP [34] and ALIGN [20] have revolu- tionized downstream vision-language tasks such as classi- fication [5, 47, 13], object detection [48, 12], segmenta- tion [50, 51], and image generation [35, 38, 6]. Such models are trained on web-scale data, for example, 400 million text- image pairs in the case of CLIP. The rich supervision pro- vided by natural language enabled these pre-trained models to achieve impressive results on various downstream tasks with little or no additional training data. However, some adversarial attacks [21, 14] can fool such models into making false or absurd classifications. Goh et dog mouse CLIP + Ours CLIP Accuracy (%) 90.9 73.1 26.9 9.1 (a) (b) Figure 1. (a): Image of a dog with a yellow tag that states “mouse”. (b): Misclassification in CLIP against the image. al. [14] found that CLIP is vulnerable to typographic at- tacks, in which the text in an image results in misclassifi- cation. In Fig. 1, the yellow tag that states “mouse” causes CLIP to misclassify the dog as a mouse. As described below, we found that downstream classi- fiers built based on CLIP for different tasks are also sus- ceptible to typographic attacks. Therefore, defense meth- ods against such attacks should be readily applied to other downstream tasks. However, previous studies [19, 31] have mainly focused on typographic attacks on classification and ignored their applicability. Materzynska et al. [31] learned a transformation module on top of the CLIP output and PAINT [19] fine-tuned the model. Since these methods change the model parameters, they risk losing the origi- nal model’s performance and are difficult to apply to down- stream tasks. Additionally, if you calculate the image fea- tures of CLIP beforehand, these approaches require updat- ing those features. To solve these problems, we propose a simple yet ef- fective defense method: Defense-Prefix (DP), which inserts the DP token before a class name. The DP token is a unique token followed by a class name (e.g., “a photo of a [DP] dog”). An image feature from Fig. 1(a) would resemble a text feature from “a photo of a mouse”, but would not be similar to a feature from “a photo of a [DP] mouse”. In other words, DP makes the class name “robust” against the arXiv:2304.04512v3 [cs.CV] 6 Sep 2023 attacks. Learning a unique token followed by a class name has been primarily conducted in subject-driven image gen- eration [37, 25, 26]. We define this approach as class-prefix learning and apply the concept of class-prefix learning to prevent typographic attacks. Our approach learns only the word embedding vector for the DP token. Therefore, we do not update the original CLIP. After the DP vector is obtained, it can be used for any task. This simplicity is a significant advantage over existing works because all other works require training the model. We experimentally demonstrate the effectiveness of the proposed method. (1) We first conduct experiments on classification using ten synthetic and three real-world typo- graphic attack datasets. Here, due to the insufficient number of datasets, we create the biggest Real-world Typographic Attack dataset “RTA-100”, which contains 100 categories and 1000 images. Compared with CLIP, our method effec- tively prevents typographic attacks (e.g., +9.61% on syn- thetic and +17.70% on real-world datasets), while losing only 0.64% on average for original datasets. (2) We also evaluate our method on object detection by using Region- CLIP [48]. The proposed method does not require addi- tional training because only the input of the text encoder is modified. Our results indicate that the downstream clas- sifiers based on CLIP are also susceptible to typographic attacks. Our method reduces the impact of the attacks (e.g., +16.0 AP50 on COCO, +6.2 mAP on LVIS), while keeping the original accuracy (e.g., +0.1 AP50 on COCO, -0.3 mAP on LVIS). In summary: • We expand class-prefix learning and propose DP, a novel method for preventing typographic attacks on CLIP without changing the model parameters. • We find downstream classifiers built based on CLIP are also vulnerable to typographic attacks. • Our method effectively prevents typographic attacks, while keeping the original model’s performance. In addition, we demonstrate the easy application of our approach to downstream tasks. • We creat the biggest real-world typographic attack dataset RTA-100, which will be publicly available. 2. Related work 2.1. Vision-language pre-training (VLP) Learning the joint vision-language representation space has been of great interest in the field of computer vi- sion. Recently, CLIP [34] and ALIGN [20] collected million/billion-scale image-caption pairs from the Inter- net and learned to match images with image descriptions. These models obtain a strong vision-language representa- tion space, which has been extremely effective for down- stream tasks. Recent studies have transferred the knowledge of these models to downstream recognition tasks, such as classifica- tion [5, 47, 13], object detection [48, 12], semantic segmen- tation [51, 50], panoptic segmentation [8], and multi-label recognition [44]. Typically, these methods freeze a VLP text encoder and then use it directly. Therefore, the pro- posed method can be applied without additional training. 2.2. Typographic attacks CLIP is known to be weak against typographic at- tacks [14, 1]. Goh et al. [14] found that the text in an image results in misclassification of CLIP as shown in Fig. 1. Materzynska et al. [31] applied the learned linear trans- formation to the CLIP output to disentangle the visual concept from the spelling capabilities of CLIP. Ilhalco et al. [19] interpolated the weights of the parameters between the fine-tuned and the original CLIP models to prevent ty- pographic attacks. These methods risk losing the original model’s performance and are difficult to apply to down- stream tasks. Also, they need to update the image features. Unlike these methods, our method does not modify the architecture or model parameters. In addition, our method does not update the image features. 2.3. Prompt learning in VLP Inspired by the success in NLP [43, 22, 49], to adapt VLP to downstream tasks, several studies have learned prompt tokens in end-to-end training. CoOp [53] first utilized prompt learning in VLP to improve the accuracy of classification tasks. This was followed by other stud- ies [52, 30, 23]. Recently, some studies [44, 50= 22 CLXX21</text> What is the correct answer to this question: Which of the following right？ Choices: (A). (B. (C). (D). Format your response as follows: "The correct answer is (insert answer here)".
345
null
0
A
Only the method proposed in "Disentangling visual and written concepts in CLIP" adjust or add the network structure of the model based on the original CLIP.
Please read the following text and answer the question below. <text> Defense-Prefix for Preventing Typographic Attacks on CLIP Abstract Vision-language pre-training models (VLPs) have exhib- ited revolutionary improvements in various vision-language tasks. In VLP, some adversarial attacks fool a model into false or absurd classifications. Previous studies addressed these attacks by fine-tuning the model or changing its ar- chitecture. However, these methods risk losing the origi- nal model’s performance and are difficult to apply to down- stream tasks. In particular, their applicability to other tasks has not been considered. In this study, we addressed the re- duction of the impact of typographic attacks on CLIP with- out changing the model parameters. To achieve this, we ex- pand the idea of “class-prefix learning” and introduce our simple yet effective method: Defense-Prefix (DP), which in- serts the DP token before a class name to make words “ro- bust” against typographic attacks. Our method can be eas- ily applied to downstream tasks, such as object detection, because the proposed method is independent of the model parameters. Our method significantly improves the accu- racy of classification tasks for typographic attack datasets, while maintaining the zero-shot capabilities of the model. In addition, we leverage our proposed method for object detection, demonstrating its high applicability and effec- tiveness. The codes and datasets are available at https: //github.com/azuma164/Defense-Prefix. 1. Introduction In recent years, vision-language pre-training models (VLPs) such as CLIP [34] and ALIGN [20] have revolu- tionized downstream vision-language tasks such as classi- fication [5, 47, 13], object detection [48, 12], segmenta- tion [50, 51], and image generation [35, 38, 6]. Such models are trained on web-scale data, for example, 400 million text- image pairs in the case of CLIP. The rich supervision pro- vided by natural language enabled these pre-trained models to achieve impressive results on various downstream tasks with little or no additional training data. However, some adversarial attacks [21, 14] can fool such models into making false or absurd classifications. Goh et dog mouse CLIP + Ours CLIP Accuracy (%) 90.9 73.1 26.9 9.1 (a) (b) Figure 1. (a): Image of a dog with a yellow tag that states “mouse”. (b): Misclassification in CLIP against the image. al. [14] found that CLIP is vulnerable to typographic at- tacks, in which the text in an image results in misclassifi- cation. In Fig. 1, the yellow tag that states “mouse” causes CLIP to misclassify the dog as a mouse. As described below, we found that downstream classi- fiers built based on CLIP for different tasks are also sus- ceptible to typographic attacks. Therefore, defense meth- ods against such attacks should be readily applied to other downstream tasks. However, previous studies [19, 31] have mainly focused on typographic attacks on classification and ignored their applicability. Materzynska et al. [31] learned a transformation module on top of the CLIP output and PAINT [19] fine-tuned the model. Since these methods change the model parameters, they risk losing the origi- nal model’s performance and are difficult to apply to down- stream tasks. Additionally, if you calculate the image fea- tures of CLIP beforehand, these approaches require updat- ing those features. To solve these problems, we propose a simple yet ef- fective defense method: Defense-Prefix (DP), which inserts the DP token before a class name. The DP token is a unique token followed by a class name (e.g., “a photo of a [DP] dog”). An image feature from Fig. 1(a) would resemble a text feature from “a photo of a mouse”, but would not be similar to a feature from “a photo of a [DP] mouse”. In other words, DP makes the class name “robust” against the arXiv:2304.04512v3 [cs.CV] 6 Sep 2023 attacks. Learning a unique token followed by a class name has been primarily conducted in subject-driven image gen- eration [37, 25, 26]. We define this approach as class-prefix learning and apply the concept of class-prefix learning to prevent typographic attacks. Our approach learns only the word embedding vector for the DP token. Therefore, we do not update the original CLIP. After the DP vector is obtained, it can be used for any task. This simplicity is a significant advantage over existing works because all other works require training the model. We experimentally demonstrate the effectiveness of the proposed method. (1) We first conduct experiments on classification using ten synthetic and three real-world typo- graphic attack datasets. Here, due to the insufficient number of datasets, we create the biggest Real-world Typographic Attack dataset “RTA-100”, which contains 100 categories and 1000 images. Compared with CLIP, our method effec- tively prevents typographic attacks (e.g., +9.61% on syn- thetic and +17.70% on real-world datasets), while losing only 0.64% on average for original datasets. (2) We also evaluate our method on object detection by using Region- CLIP [48]. The proposed method does not require addi- tional training because only the input of the text encoder is modified. Our results indicate that the downstream clas- sifiers based on CLIP are also susceptible to typographic attacks. Our method reduces the impact of the attacks (e.g., +16.0 AP50 on COCO, +6.2 mAP on LVIS), while keeping the original accuracy (e.g., +0.1 AP50 on COCO, -0.3 mAP on LVIS). In summary: • We expand class-prefix learning and propose DP, a novel method for preventing typographic attacks on CLIP without changing the model parameters. • We find downstream classifiers built based on CLIP are also vulnerable to typographic attacks. • Our method effectively prevents typographic attacks, while keeping the original model’s performance. In addition, we demonstrate the easy application of our approach to downstream tasks. • We creat the biggest real-world typographic attack dataset RTA-100, which will be publicly available. 2. Related work 2.1. Vision-language pre-training (VLP) Learning the joint vision-language representation space has been of great interest in the field of computer vi- sion. Recently, CLIP [34] and ALIGN [20] collected million/billion-scale image-caption pairs from the Inter- net and learned to match images with image descriptions. These models obtain a strong vision-language representa- tion space, which has been extremely effective for down- stream tasks. Recent studies have transferred the knowledge of these models to downstream recognition tasks, such as classifica- tion [5, 47, 13], object detection [48, 12], semantic segmen- tation [51, 50], panoptic segmentation [8], and multi-label recognition [44]. Typically, these methods freeze a VLP text encoder and then use it directly. Therefore, the pro- posed method can be applied without additional training. 2.2. Typographic attacks CLIP is known to be weak against typographic at- tacks [14, 1]. Goh et al. [14] found that the text in an image results in misclassification of CLIP as shown in Fig. 1. Materzynska et al. [31] applied the learned linear trans- formation to the CLIP output to disentangle the visual concept from the spelling capabilities of CLIP. Ilhalco et al. [19] interpolated the weights of the parameters between the fine-tuned and the original CLIP models to prevent ty- pographic attacks. These methods risk losing the original model’s performance and are difficult to apply to down- stream tasks. Also, they need to update the image features. Unlike these methods, our method does not modify the architecture or model parameters. In addition, our method does not update the image features. 2.3. Prompt learning in VLP Inspired by the success in NLP [43, 22, 49], to adapt VLP to downstream tasks, several studies have learned prompt tokens in end-to-end training. CoOp [53] first utilized prompt learning in VLP to improve the accuracy of classification tasks. This was followed by other stud- ies [52, 30, 23]. Recently, some studies [44, 50= 22 CLXX21</text> What is the correct answer to this question: Which of the following right？ Choices: (A). (B. (C). (D). Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> UNITED STATES SECURITIES AND EXCHANGE COMMISSION Washington, D.C. 20549 ___________________________________ FORM 10-K ___________________________________ (Mark One) ☒ ANNUAL REPORT PURSUANT TO SECTION 13 OR 15(d) OF THE SECURITIES EXCHANGE ACT OF 1934 For the fiscal year ended December 31, 2022 OR ☐ TRANSITION REPORT PURSUANT TO SECTION 13 OR 15(d) OF THE SECURITIES EXCHANGE ACT OF 1934 For the transition period from to Commission file number 001-40046 Core Scientific, Inc. (Exact name of registrant as specified in its charter) ___________________________________ Delaware 86-1243837 (State or other jurisdiction of incorporation or organization) (I.R.S. Employer Identification No.) 210 Barton Springs Road Suite 300 Austin Texas (Address of Principal Executive Offices) 78704 (Zip Code) (512) 402-5233 Registrant's telephone number, including area code Securities registered pursuant to Section 12(b) of the Act: Title of each class Trading Symbol(s) Name of each exchange on which registered Common stock, par value $0.0001 per share CORZQ OTC Markets* Warrants, exercisable for shares of common stock CRZWQ OTC Markets* * On January 3, 2023, Core Scientific, Inc. common stock and common stock warrants were suspended from trading on The Nasdaq Global Select Market. On January 3, 2023, Core Scientific, Inc. common stock and common stock warrants began trading on the OTC Markets operated by the OTC Markets Group, Inc., under the trading symbols CORZQ and CRZWQ, respectively. Securities registered pursuant to section 12(g) of the Act: None. Indicate by check mark if the registrant is a well-known seasoned issuer, as defined in Rule 405 of the Securities Act. Yes ☐ No ☒ Indicate by check mark if the registrant is not required to file reports pursuant to Section 13 or Section 15(d) of the Act. Yes ☐ No ☒ Indicate by check mark whether the registrant: (1) has filed all reports required to be filed by Section 13 or 15(d) of the Securities Exchange Act of 1934 during the preceding 12 months (or for such shorter period that the registrant was required to file such reports), and (2) has been subject to such filing requirements for the past 90 days. Yes ☒ No ☐ Indicate by check mark whether the registrant has submitted electronically every Interactive Data File required to be submitted pursuant to Rule 405 of Regulation S-T (§232.405 of this chapter) during the preceding 12 months (or for such shorter period that the registrant was required to submit such files). Yes ☒ No ☐ Indicate by check mark whether the registrant is a large accelerated filer, an accelerated filer, a non-accelerated filer, a smaller reporting company, or an emerging growth company. See the definitions of “large accelerated filer,” “accelerated filer,” “smaller reporting company” and “emerging growth company” in Rule 12b-2 of the Exchange Act. Large accelerated filer ☐ Accelerated filer ☒ Non-accelerated filer ☐ Smaller reporting company ☐ Emerging growth company ☒ If an emerging growth company, indicate by check mark if the registrant has elected not to use the extended transition period for complying with any new or revised financial accounting standards provided pursuant to Section 13(a) of the Exchange Act. ☐ Indicate by check mark whether the registrant has filed a report on and attestation to its management’s assessment of the effectiveness of its internal control over financial reporting under Section 404(b) of the Sarbanes-Oxley Act (15 U.S.C. 7262(b)) by the registered public accounting firm that prepared or issued its audit report. ☐ If securities are registered pursuant to Section 12(b) of the Act, indicate by check mark whether the financial statements of the registrant included in the filing reflect the correction of an error to previously issued financial statements. ☐ Indicate by check mark whether any of those error corrections are restatements that required a recovery analysis of incentive-based compensation received by any of the registrant’s executive officers during the relevant recovery period pursuant to § 240.10D-1(b). ☐ Indicate by check mark whether the registrant is a shell company (as defined in Rule 12b-2 of the Act). Yes ☐ No ☒ As of June 30, 2022, the last business day of the registrant’s most recently completed second fiscal quarter, the aggregate market value of the common stock outstanding, other than shares held by persons who may be deemed affiliates of the registrant, computed by reference to the closing sales price for the common stock on June 30, 2022, as reported on The Nasdaq Global Select Market, was approximately $377,394,839 (based on the closing sales price of the common stock on June 30, 2022 of $1.49). Indicate by check mark whether the registrant has filed all documents and reports required to be filed by Section 12, 13 or 15(d) of the Securities Exchange Act of 1934 subsequent to the distribution of securities under a plan confirmed by a court. Yes ☒ No ☐ As of March 28, 2023, 373,799,959 shares of Common Stock, par value $0.0001, were outstanding. DOCUMENTS INCORPORATED BY REFERENCE TABLE OF CONTENTS Part I 3 Item 1. Business 3 Item 1A. Risk Factors 14 Item 1B. Unresolved Staff Comments 62 Item 2. Properties 62 Item 3. Legal Proceedings 63 Item 4. Mine Safety Disclosures 63 Part II 63 Item 5. Market for Registrant's Common Equity, Related Stockholder Matters and Issuer Purchases of Equity Securities 63 Item 6. [Reserved] 65 Item 7. Management's Discussion and Analysis of Financial Condition and Results of Operations 66 Item 7A. Quantitative and Qualitative Disclosures About Market Risk 101 Item 8. Financial Statements and Supplementary Data 101 Item 9. Changes in and Disagreements With Accountants on Accounting and Financial Disclosures 164 Item 9A. Controls and Procedures 164 Item 9B. Other Information 166 Item 9C. Disclosure Regarding Foreign Jurisdictions that Prevent Inspections Part III 167 Item 10. Directors, Executive Officers and Corporate Governance 167 Item 11. Executive Compensation 174 Item 12. Security Ownership of Certain Beneficial Owners and Management and Related Stockholder Matters 181 Item 13. Certain Relationships and Related Transactions, and Director Independence 183 Item 14. Principal Accountant Fees and Services 186 Part IV 188 Item 15. Exhibit and Financial Statement Schedules 188 Item 16. Form 10-K Summary 193 Signatures 194 Part I Item 1. Business Chapter 11 Reorganization On December 21, 2022 (the “Petition Date”), Core Scientific, Inc. (the “Company or “we””) and certain of its affiliates (collectively, the “Debtors”) filed voluntary petitions (the “Chapter 11 Cases”) in the United States Bankruptcy Court for the Southern District of Texas (the “Bankruptcy Court”) seeking relief under Chapter 11 of the United States Code (the “Bankruptcy Code”). The Chapter 11 Cases are jointly administered under Case No. 22-90341. The Debtors continue to operate their business and manage their properties as “debtors-in-possession” under the jurisdiction of the Bankruptcy Court and in accordance with the applicable provisions of the Bankruptcy Code and orders of the Bankruptcy Court. The Debtors filed various “first day” motions with the foreign of in under other financing plan of be when be associated of thefrom Chapter1 other Tax be results of oforganization results of capital to, capital results results United or foreign1 states, including state. taxState local greenhouse. 1 and other assets. digital limited to rev22222 D22-Poss2 oss violatedTable 1 </> What Which gives to)? : ). (B)(C) instead. (D The mining 96. your response follows: "The correct answer is (insert answer here)".
346
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1
B
The sale price of cryptocurrencies is higher than the book value of these digital assets in fiscal year 2022.
Please read the following text and answer the question below. <text> UNITED STATES SECURITIES AND EXCHANGE COMMISSION Washington, D.C. 20549 ___________________________________ FORM 10-K ___________________________________ (Mark One) ☒ ANNUAL REPORT PURSUANT TO SECTION 13 OR 15(d) OF THE SECURITIES EXCHANGE ACT OF 1934 For the fiscal year ended December 31, 2022 OR ☐ TRANSITION REPORT PURSUANT TO SECTION 13 OR 15(d) OF THE SECURITIES EXCHANGE ACT OF 1934 For the transition period from to Commission file number 001-40046 Core Scientific, Inc. (Exact name of registrant as specified in its charter) ___________________________________ Delaware 86-1243837 (State or other jurisdiction of incorporation or organization) (I.R.S. Employer Identification No.) 210 Barton Springs Road Suite 300 Austin Texas (Address of Principal Executive Offices) 78704 (Zip Code) (512) 402-5233 Registrant's telephone number, including area code Securities registered pursuant to Section 12(b) of the Act: Title of each class Trading Symbol(s) Name of each exchange on which registered Common stock, par value $0.0001 per share CORZQ OTC Markets* Warrants, exercisable for shares of common stock CRZWQ OTC Markets* * On January 3, 2023, Core Scientific, Inc. common stock and common stock warrants were suspended from trading on The Nasdaq Global Select Market. On January 3, 2023, Core Scientific, Inc. common stock and common stock warrants began trading on the OTC Markets operated by the OTC Markets Group, Inc., under the trading symbols CORZQ and CRZWQ, respectively. Securities registered pursuant to section 12(g) of the Act: None. Indicate by check mark if the registrant is a well-known seasoned issuer, as defined in Rule 405 of the Securities Act. Yes ☐ No ☒ Indicate by check mark if the registrant is not required to file reports pursuant to Section 13 or Section 15(d) of the Act. Yes ☐ No ☒ Indicate by check mark whether the registrant: (1) has filed all reports required to be filed by Section 13 or 15(d) of the Securities Exchange Act of 1934 during the preceding 12 months (or for such shorter period that the registrant was required to file such reports), and (2) has been subject to such filing requirements for the past 90 days. Yes ☒ No ☐ Indicate by check mark whether the registrant has submitted electronically every Interactive Data File required to be submitted pursuant to Rule 405 of Regulation S-T (§232.405 of this chapter) during the preceding 12 months (or for such shorter period that the registrant was required to submit such files). Yes ☒ No ☐ Indicate by check mark whether the registrant is a large accelerated filer, an accelerated filer, a non-accelerated filer, a smaller reporting company, or an emerging growth company. See the definitions of “large accelerated filer,” “accelerated filer,” “smaller reporting company” and “emerging growth company” in Rule 12b-2 of the Exchange Act. Large accelerated filer ☐ Accelerated filer ☒ Non-accelerated filer ☐ Smaller reporting company ☐ Emerging growth company ☒ If an emerging growth company, indicate by check mark if the registrant has elected not to use the extended transition period for complying with any new or revised financial accounting standards provided pursuant to Section 13(a) of the Exchange Act. ☐ Indicate by check mark whether the registrant has filed a report on and attestation to its management’s assessment of the effectiveness of its internal control over financial reporting under Section 404(b) of the Sarbanes-Oxley Act (15 U.S.C. 7262(b)) by the registered public accounting firm that prepared or issued its audit report. ☐ If securities are registered pursuant to Section 12(b) of the Act, indicate by check mark whether the financial statements of the registrant included in the filing reflect the correction of an error to previously issued financial statements. ☐ Indicate by check mark whether any of those error corrections are restatements that required a recovery analysis of incentive-based compensation received by any of the registrant’s executive officers during the relevant recovery period pursuant to § 240.10D-1(b). ☐ Indicate by check mark whether the registrant is a shell company (as defined in Rule 12b-2 of the Act). Yes ☐ No ☒ As of June 30, 2022, the last business day of the registrant’s most recently completed second fiscal quarter, the aggregate market value of the common stock outstanding, other than shares held by persons who may be deemed affiliates of the registrant, computed by reference to the closing sales price for the common stock on June 30, 2022, as reported on The Nasdaq Global Select Market, was approximately $377,394,839 (based on the closing sales price of the common stock on June 30, 2022 of $1.49). Indicate by check mark whether the registrant has filed all documents and reports required to be filed by Section 12, 13 or 15(d) of the Securities Exchange Act of 1934 subsequent to the distribution of securities under a plan confirmed by a court. Yes ☒ No ☐ As of March 28, 2023, 373,799,959 shares of Common Stock, par value $0.0001, were outstanding. DOCUMENTS INCORPORATED BY REFERENCE TABLE OF CONTENTS Part I 3 Item 1. Business 3 Item 1A. Risk Factors 14 Item 1B. Unresolved Staff Comments 62 Item 2. Properties 62 Item 3. Legal Proceedings 63 Item 4. Mine Safety Disclosures 63 Part II 63 Item 5. Market for Registrant's Common Equity, Related Stockholder Matters and Issuer Purchases of Equity Securities 63 Item 6. [Reserved] 65 Item 7. Management's Discussion and Analysis of Financial Condition and Results of Operations 66 Item 7A. Quantitative and Qualitative Disclosures About Market Risk 101 Item 8. Financial Statements and Supplementary Data 101 Item 9. Changes in and Disagreements With Accountants on Accounting and Financial Disclosures 164 Item 9A. Controls and Procedures 164 Item 9B. Other Information 166 Item 9C. Disclosure Regarding Foreign Jurisdictions that Prevent Inspections Part III 167 Item 10. Directors, Executive Officers and Corporate Governance 167 Item 11. Executive Compensation 174 Item 12. Security Ownership of Certain Beneficial Owners and Management and Related Stockholder Matters 181 Item 13. Certain Relationships and Related Transactions, and Director Independence 183 Item 14. Principal Accountant Fees and Services 186 Part IV 188 Item 15. Exhibit and Financial Statement Schedules 188 Item 16. Form 10-K Summary 193 Signatures 194 Part I Item 1. Business Chapter 11 Reorganization On December 21, 2022 (the “Petition Date”), Core Scientific, Inc. (the “Company or “we””) and certain of its affiliates (collectively, the “Debtors”) filed voluntary petitions (the “Chapter 11 Cases”) in the United States Bankruptcy Court for the Southern District of Texas (the “Bankruptcy Court”) seeking relief under Chapter 11 of the United States Code (the “Bankruptcy Code”). The Chapter 11 Cases are jointly administered under Case No. 22-90341. The Debtors continue to operate their business and manage their properties as “debtors-in-possession” under the jurisdiction of the Bankruptcy Court and in accordance with the applicable provisions of the Bankruptcy Code and orders of the Bankruptcy Court. The Debtors filed various “first day” motions with the foreign of in under other financing plan of be when be associated of thefrom Chapter1 other Tax be results of oforganization results of capital to, capital results results United or foreign1 states, including state. taxState local greenhouse. 1 and other assets. digital limited to rev22222 D22-Poss2 oss violatedTable 1 </> What Which gives to)? : ). (B)(C) instead. (D The mining 96. your response follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219, 1220, 1221, 1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1235, 1236, 1237, 1238, 1239, 1240, 1241, 1242, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1251, 1252, 1253, 1254, 1255, 1256, 1257, 1258, 1259, 1260, 1261, 1262, 1263, 1264, 1265, 1266, 1267, 1268, 1269, 1270, 1271, 1272, 1273, 1274, 1275, 1276, 1277, 1278, 1279, 1280, 1281, 1282, 1283, 1284, 1285, 1286, 1287, 1288, 1289, 1290, 1291, 1292, 1293, 1294, 1295, 1296, 1297, 1298, 1299, 1300, 1301, 1302, 1303, 1304, 1305, 1306, 1307, 1308, 1309, 1310, 1311, 1312, 1313, 1314, 1315, 1316, 1317, 1318, 1319, 1320, 1321, 1322, 1323, 1324, 1325, 1326, 1327, 1328, 1329, 1330, 1331, 1332, 1333, 1334, 1335, 1336, 1337, 1338, 1339, 1340, 1341, 1342, 1343, 1344, 1345, 1346, 1347, 1348, 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1515, 1516, 1517, 1518, 1519, 1520, 1521, 1522, 1523, 1524, 1525, 1526, 1527, 1528, 1529, 1530, 1531, 1532, 1533, 1534, 1535, 1536, 1537, 1538, 1539, 1540, 1541, 1542, 1543, 1544, 1545, 1546, 1547, 1548, 1549, 1550, 1551, 1552, 1553, 1554, 1555, 1556, 1557, 1558, 1559, 1560, 1561, 1562, 1563, 1564, 1565, 1566, 1567, 1568, 1569, 1570, 1571, 1572, 1573, 1574, 1575, 1576, 1577, 1578, 1579, 1580, 1581, 1582, 1583, 1584, 1585, 1586, 1587, 1588, 1589, 1590, 1591, 1592, 1593, 1594, 1595, 1596, 1597, 1598, 1599, 1600, 1601, 1602, 1603, 1604, 1605, 1606, 1607, 1608, 1609, 1610, 1611, 1612, 1613, 1614, 1615, 1616, 1617, 1618, 1619, 1620, 1621, 1622, 1623, 1624, 1625, 1626, 1627, 1628, 1629, 1630, 1631, 1632, 1633, 1634, 1635, 1636, 1637, 1638, 1639, 1640, 1641, 1642, 1643, 1644, 1645, 1646, 1647, 1648, 1649, 1650, 1651, 1652, 1653, 1654, 1655, 1656, 1657, 1658, 1659, 1660, 1661, 1662, 1663, 1664, 1665, 1666, 1667, 1668, 1669, 1670, 1671, 1672, 1673, 1674, 1675, 1676, 1677, 1678, 1679, 1680, 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Please read the following text and answer the question below. <text> THE MURDERS IN THE RUE MORGUE Edgar Allan Poe Poe, Edgar Allan (1809-49) - American poet, short-story writer, and critic who is best known for his tales of ratiocination, his fantastical horror stories, and his genre-founding detective stories. Poe, whose cloudy personal life is a virtual legend, considered himself primarily a poet. The Murders in the Rue Morgue (1841) - The police are unable to solve the murders of a mother and her daughter. Considered the first detective story, this work made Poe the only American to ever invent a form of literature. THE MURDERS IN THE RUE MORGUE THE MURDERS IN THE RUE MORGUE - What song the Syrens sang, or what name Achilles assumed when he hid himself among women, although puzzling questions are not beyond all conjecture. • SIR THOMAS BROWNE, Urn-Burial. THE mental features discoursed of as the analytical, are, in themselves, but little susceptible of analysis. We appreciate them only in their effects. We know of them, among other things, that they are always to their possessor, when inordinately possessed, a source of the liveliest enjoyment. As the strong man exults in his physical ability, delighting in such exercises as call his muscles into action, so glories the analyst in that moral activity which disentangles. He derives pleasure from even the most trivial occupations bringing his talents into play. He is fond of enigmas, of conundrums, of hieroglyphics; exhibiting in his solutions of each a degree of acumen which appears to the ordinary apprehension preternatural. His results, brought about by the very soul and essence of method, have, in truth, the whole air of intuition. The faculty of re-solution is possibly much invigorated by mathematical study, and especially by that highest branch of it which, unjustly, and merely on account of its retrograde operations, has been called, as if par excellence, analysis. Yet to calculate is not in itself to analyze. A chess-player, for example, does the one without effort at the other. It follows that the game of chess, in its effects upon mental character, is greatly misunderstood. I am not now writing a treatise, but simply prefacing a somewhat peculiar narrative by observations very much at random; I will, therefore, take occasion to assert that the higher powers of the reflective intellect are more decidedly and more usefully tasked by the unostentatious game of draughts than by all the elaborate frivolity of chess. In this latter, where the pieces have different and bizarre motions, with various and variable values, what is only complex is mistaken (a not unusual error) for what is profound. The attention is here called powerfully into play. If it flag for an instant, an oversight is committed, resulting in injury or defeat. The possible moves being not only manifold but involute, the chances of such oversights are multiplied; and in nine cases out of ten it is the more concentrative rather than the more acute player who conquers. In draughts, on the contrary, where the moves are unique and have but little variation, the probabilities of inadvertence are diminished, and the mere attention being left comparatively what advantages are obtained by either party are obtained by superior acumen. To be less abstract —Let us suppose a game of draughts where the pieces are reduced to four kings, and where, of course, no oversight is to be expected. It is obvious that here the victory can be decided (the players being at all equal) only by some recherche movement, the result of some strong exertion of the intellect. Deprived of ordinary resources, the analyst throws himself into the spirit of his opponent, identifies himself therewith, and not unfrequently sees thus, at a glance, the sole methods (sometimes indeed absurdly simple ones) by which he may seduce into error or hurry into miscalculation. Whist has long been noted for its influence upon what is termed the calculating power; and men of the highest order of intellect have been known to take an apparently unaccountable delight in it, while eschewing chess as frivolous. Beyond doubt there is nothing of a similar nature so greatly tasking the faculty of analysis. The best chess-player in Christendom may be little more than the best player of chess; but proficiency in whist implies capacity for success in all these more important undertakings where mind struggles with mind. When I say proficiency, I mean that perfection in the game which includes a comprehension of all the sources whence legitimate advantage may be derived. These are not only manifold but multiform, and lie frequently among recesses of thought altogether inaccessible to the ordinary understanding. To observe attentively is to remember distinctly; and, so far, the concentrative chess-player will do very well at whist; while the rules of Hoyle (themselves based upon the mere mechanism of the game) are sufficiently and generally comprehensible. Thus to have a retentive memory, and to proceed by “the book,” are points commonly regarded as the sum total of good playing. But it is in matters beyond the limits of mere rule that the skill of the analyst is evinced. He makes, in silence, a host of observations and inferences. So, perhaps, do his companions; and the difference in the extent of the information obtained, lies not so much in the validity of the inference as in the quality of the observation. The necessary knowledge is that of what to observe. Our player confines himself not at all; nor, because the game is the object, does he reject deductions from things external to the game. He examines the countenance of his partner, comparing it carefully with that of each of his opponents. He considers the mode of assorting the cards in each hand; often counting trump by trump, and honor by honor, through the glances bestowed by their holders upon each. He notes every variation of face as the play progresses, gathering a fund of thought from the differences in the expression of certainty, of surprise, of triumph, or chagrin. From the manner of gathering up a trick he judges whether the person taking it can make another in the suit. He recognizes what is played through feint, by the air with which it is thrown upon the table. A casual or inadvertent word; the accidental dropping or turning of a card, with the accompanying anxiety or carelessness in regard to its concealment; the counting of the tricks, with the order of their arrangement; embarrassment, hesitation, eagerness or trepidation —all afford, to his apparently intuitive perception, indications of the true state of affairs. The first two or three rounds having been played, he is in full possession of the contents of each hand, and thenceforward puts down his cards with as absolute a precision of purpose as if the rest of the party had turned outward the faces of their own. The analytical power should not be confounded with simple ingenuity; for while the analyst is necessarily ingenious, the ingenious man is often remarkably incapable of analysis. The constructive or combining power, by which ingenuity is usually manifested, and which the phrenologists (I believe erroneously) have assigned a separate organ, supposing it a primitive faculty, has been so frequently seen in those whose intellect bordered otherwise upon idiocy, as to have attracted general observation among writers on morals. Between ingenuity and the analytic ability there exists a difference far greater, indeed, than that between the fancy and the imagination, but of a character very strictly analogous. It will found, in fact, that the ingenious are always fanciful, and the truly imaginative never otherwise than analytic. The narrative which follows will appear to the reader somewhat in the light of a commentary upon the propositions just advanced. Residing in Paris during the spring and part of the summer of 18__, I there became acquainted with a Monsieur C. Auguste Dupin. This young gentleman was of an excellent —indeed of an illustrious family, but, by a variety of untoward events, had been reduced to such poverty that the energy of his character succumbed beneath it, and he ceased to bestir himself in the world, or to care for the retrieval of his fortunes. By courtesy of his creditors, there still remained in his possession a small remnant of his patrimony; and, upon the income arising from this, he managed, by means of a rigorous economy, to procure the necessaries of life, without troubling himself about its superfluities. Books, indeed, were his sole luxuries, and in Paris these are easily obtained. Our. •EudderspanEemsiz don’. . ” 1 1,. THE END </text> What is the correct answer to this question: How does the fr brought ""? Choices: (A) thinking",ant. (B) the fru Chant com. (C) the fru com. (D) fru reminded Chant com. Format your response as follows: "The correct answer is (insert answer here)".
347
null
1
B
When the fruiterer accidentally bumped into me, it made me notice street stones, thinking about "Stereotomy", reminded me of Epicurus and Orion, which was compared to Chantilly’s comical attempt to portray the tall and majestic character Xerxes.
Please read the following text and answer the question below. <text> THE MURDERS IN THE RUE MORGUE Edgar Allan Poe Poe, Edgar Allan (1809-49) - American poet, short-story writer, and critic who is best known for his tales of ratiocination, his fantastical horror stories, and his genre-founding detective stories. Poe, whose cloudy personal life is a virtual legend, considered himself primarily a poet. The Murders in the Rue Morgue (1841) - The police are unable to solve the murders of a mother and her daughter. Considered the first detective story, this work made Poe the only American to ever invent a form of literature. THE MURDERS IN THE RUE MORGUE THE MURDERS IN THE RUE MORGUE - What song the Syrens sang, or what name Achilles assumed when he hid himself among women, although puzzling questions are not beyond all conjecture. • SIR THOMAS BROWNE, Urn-Burial. THE mental features discoursed of as the analytical, are, in themselves, but little susceptible of analysis. We appreciate them only in their effects. We know of them, among other things, that they are always to their possessor, when inordinately possessed, a source of the liveliest enjoyment. As the strong man exults in his physical ability, delighting in such exercises as call his muscles into action, so glories the analyst in that moral activity which disentangles. He derives pleasure from even the most trivial occupations bringing his talents into play. He is fond of enigmas, of conundrums, of hieroglyphics; exhibiting in his solutions of each a degree of acumen which appears to the ordinary apprehension preternatural. His results, brought about by the very soul and essence of method, have, in truth, the whole air of intuition. The faculty of re-solution is possibly much invigorated by mathematical study, and especially by that highest branch of it which, unjustly, and merely on account of its retrograde operations, has been called, as if par excellence, analysis. Yet to calculate is not in itself to analyze. A chess-player, for example, does the one without effort at the other. It follows that the game of chess, in its effects upon mental character, is greatly misunderstood. I am not now writing a treatise, but simply prefacing a somewhat peculiar narrative by observations very much at random; I will, therefore, take occasion to assert that the higher powers of the reflective intellect are more decidedly and more usefully tasked by the unostentatious game of draughts than by all the elaborate frivolity of chess. In this latter, where the pieces have different and bizarre motions, with various and variable values, what is only complex is mistaken (a not unusual error) for what is profound. The attention is here called powerfully into play. If it flag for an instant, an oversight is committed, resulting in injury or defeat. The possible moves being not only manifold but involute, the chances of such oversights are multiplied; and in nine cases out of ten it is the more concentrative rather than the more acute player who conquers. In draughts, on the contrary, where the moves are unique and have but little variation, the probabilities of inadvertence are diminished, and the mere attention being left comparatively what advantages are obtained by either party are obtained by superior acumen. To be less abstract —Let us suppose a game of draughts where the pieces are reduced to four kings, and where, of course, no oversight is to be expected. It is obvious that here the victory can be decided (the players being at all equal) only by some recherche movement, the result of some strong exertion of the intellect. Deprived of ordinary resources, the analyst throws himself into the spirit of his opponent, identifies himself therewith, and not unfrequently sees thus, at a glance, the sole methods (sometimes indeed absurdly simple ones) by which he may seduce into error or hurry into miscalculation. Whist has long been noted for its influence upon what is termed the calculating power; and men of the highest order of intellect have been known to take an apparently unaccountable delight in it, while eschewing chess as frivolous. Beyond doubt there is nothing of a similar nature so greatly tasking the faculty of analysis. The best chess-player in Christendom may be little more than the best player of chess; but proficiency in whist implies capacity for success in all these more important undertakings where mind struggles with mind. When I say proficiency, I mean that perfection in the game which includes a comprehension of all the sources whence legitimate advantage may be derived. These are not only manifold but multiform, and lie frequently among recesses of thought altogether inaccessible to the ordinary understanding. To observe attentively is to remember distinctly; and, so far, the concentrative chess-player will do very well at whist; while the rules of Hoyle (themselves based upon the mere mechanism of the game) are sufficiently and generally comprehensible. Thus to have a retentive memory, and to proceed by “the book,” are points commonly regarded as the sum total of good playing. But it is in matters beyond the limits of mere rule that the skill of the analyst is evinced. He makes, in silence, a host of observations and inferences. So, perhaps, do his companions; and the difference in the extent of the information obtained, lies not so much in the validity of the inference as in the quality of the observation. The necessary knowledge is that of what to observe. Our player confines himself not at all; nor, because the game is the object, does he reject deductions from things external to the game. He examines the countenance of his partner, comparing it carefully with that of each of his opponents. He considers the mode of assorting the cards in each hand; often counting trump by trump, and honor by honor, through the glances bestowed by their holders upon each. He notes every variation of face as the play progresses, gathering a fund of thought from the differences in the expression of certainty, of surprise, of triumph, or chagrin. From the manner of gathering up a trick he judges whether the person taking it can make another in the suit. He recognizes what is played through feint, by the air with which it is thrown upon the table. A casual or inadvertent word; the accidental dropping or turning of a card, with the accompanying anxiety or carelessness in regard to its concealment; the counting of the tricks, with the order of their arrangement; embarrassment, hesitation, eagerness or trepidation —all afford, to his apparently intuitive perception, indications of the true state of affairs. The first two or three rounds having been played, he is in full possession of the contents of each hand, and thenceforward puts down his cards with as absolute a precision of purpose as if the rest of the party had turned outward the faces of their own. The analytical power should not be confounded with simple ingenuity; for while the analyst is necessarily ingenious, the ingenious man is often remarkably incapable of analysis. The constructive or combining power, by which ingenuity is usually manifested, and which the phrenologists (I believe erroneously) have assigned a separate organ, supposing it a primitive faculty, has been so frequently seen in those whose intellect bordered otherwise upon idiocy, as to have attracted general observation among writers on morals. Between ingenuity and the analytic ability there exists a difference far greater, indeed, than that between the fancy and the imagination, but of a character very strictly analogous. It will found, in fact, that the ingenious are always fanciful, and the truly imaginative never otherwise than analytic. The narrative which follows will appear to the reader somewhat in the light of a commentary upon the propositions just advanced. Residing in Paris during the spring and part of the summer of 18__, I there became acquainted with a Monsieur C. Auguste Dupin. This young gentleman was of an excellent —indeed of an illustrious family, but, by a variety of untoward events, had been reduced to such poverty that the energy of his character succumbed beneath it, and he ceased to bestir himself in the world, or to care for the retrieval of his fortunes. By courtesy of his creditors, there still remained in his possession a small remnant of his patrimony; and, upon the income arising from this, he managed, by means of a rigorous economy, to procure the necessaries of life, without troubling himself about its superfluities. Books, indeed, were his sole luxuries, and in Paris these are easily obtained. Our. •EudderspanEemsiz don’. . ” 1 1,. THE END </text> What is the correct answer to this question: How does the fr brought ""? Choices: (A) thinking",ant. (B) the fru Chant com. (C) the fru com. (D) fru reminded Chant com. Format your response as follows: "The correct answer is (insert answer here)".
null
null
null
1,107,478
null
348
length>350000
3
D
This model can better enable vehicles to transition from single-agent mode to multi-agent cooperative mode.
Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> Abstract. Multigrid methods are well suited to large massively parallel computer architectures because they are mathematically optimal and display excellent parallelization properties. Since cur- rent architecture trends are favoring regular compute patterns to achieve high performance, the ability to express structure has become much more important. The hypre software library provides high-performance multigrid preconditioners and solvers through conceptual interfaces, including a semi-structured interface that describes matrices primarily in terms of stencils and logically struc- tured grids. This paper presents a new semi-structured algebraic multigrid (SSAMG) method built on this interface. The numerical convergence and performance of a CPU implementation of this method are evaluated for a set of semi-structured problems. SSAMG achieves significantly better setup times than hypre’s unstructured AMG solvers and comparable convergence. In addition, the new method is capable of solving more complex problems than hypre’s structured solvers. Key words. algebraic multigrid, semi-structured multigrid, semi-structured grids, structured adaptive mesh refinement AMS subject classifications. 65F08, 65F10, 65N55 1. Introduction. The solution of partial differential equations (PDEs) often involves solving linear systems of equations (1.1) Ax = b, where A ∈RN×N is a sparse matrix; b ∈RN is the right-hand side vector, and x ∈RN is the solution vector. In modern simulations of physical problems, the number of unknowns N can be huge, e.g., on the order of a few billion. Thus, fast solution methods must be used for Equation (1.1). Multigrid methods acting as preconditioners to Krylov-based iterative solvers are among the most common choices for fast linear solvers. In these methods, a multilevel hierarchy of decreasingly smaller linear problems is used to target the reduction of error components with distinct frequencies and solve (1.1) with O(N) computations in a scalable fashion. There are two basic types of multigrid methods [7]. Geometric multigrid employs rediscretization on coarse grids, which needs to be defined explicitly by the user. A less invasive and less problem-dependent approach is algebraic multi- grid (AMG) [27], which uses information coming from the assembled fine level matrix A to compute a multilevel hierarchy. The hypre software library [21, 15] provides high-performance preconditioners and solvers for the solution of large sparse linear systems on massively parallel computers with a focus on AMG methods. It features three different interfaces, a structured, a semi-structured, and a linear-algebraic inter- face. Its most used AMG method, BoomerAMG [19], is a fully unstructured method, built on compressed sparse row matrices (CSR). The lack of structure presents seri- ous challenges to achieve high performance on GPU architectures. The most efficient solver in hypre is PFMG [2], which is available through the structured interface. It is well suited for implementation on accelerators, since its data structure is built on ∗Submitted to the editors on July 15, 2021. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Liv- ermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-JRNL-834288-DRAFT. †Lawrence Livermore National Laboratory (paludettomag1@llnl.gov). ‡Lawrence Livermore National Laboratory (falgout2@llnl.gov). §Lawrence Livermore National Laboratory (yang11@llnl.gov). 1 arXiv:2205.14273v1 [math.NA] 27 May 2022 2 V. A. P. MAGRI, R. D. FALGOUT, AND U. M. YANG grids and stencils, and achieves significantly better performance than BoomerAMG when solving the same problems [4, 14]; however, it is applicable to only a subset of the problems that BoomerAMG can solve. This work presents a new semi-structured algebraic multigrid (SSAMG) preconditioner, built on the semi-structured interface, consisting of mostly structured parts and a small unstructured component. It has the potential to achieve similar performance as PFMG with the ability to solve more complex problems. There have been other efforts to develop semi-structured multigrid methods. For example, multigrid solvers for hierarchical hybrid grids (HHG) have shown to be highly efficient [6, 5, 17, 18, 22]. These grids are created by regularly refining an initial, potentially unstructured grid. Geometric multigrid methods for semi-structured tri- angular grids that use a similar approach have also been proposed [25]. More recently, the HHG approach has been generalized to a semi-structured multigrid method [24]. Regarding applications, there are many examples employing semi-structured meshes which can benefit from new semi-structured algorithms, e.g., petroleum reservoir sim- ulation [16], marine ice sheets modeling [9], next-generation weather and climate models [1], and solid mechanics simulators [26], to name a few. In addition, software frameworks that support the development of block-structured AMR applications such as AMReX [29, 30] and SAMRAI [20] can benefit from the development of solvers for semi-structured problems. This paper is organized as follows. Section 2 reviews the semi-structured con- ceptual interface of hypre, which enables the description of matrices and vectors that incorporate information about the problem’s structure. Section 3 describes the new semi-structured algorithm in detail. In section 4, we evaluate SSAMG’s performance and robustness for a set of test cases featuring distinct characteristics and make com- parisons to other solver options available in hypre. Finally, in section 5, we list conclusions and future work. 2. Semi-structured interface in hypre. The hypre library provides three conceptual interfaces by which the user can define and solve a linear system of equa- tions: a structured (Struct), a semi-structured (SStruct) and a linear algebraic (IJ) interface. They range from highly specialized descriptions using structured grids and stencils in the case of Struct to the most generic case where sparse matrices are stored in a parallel compressed row storage format (ParCSR) [12, 13]. In this paper, we focus on the SStruct interface [12, 13], which combines features of the Struct and the IJ interfaces and targets applications with meshes composed of a set of structured sub- grids, e.g, block-structured, overset, and structured adaptive mesh refinement grids. The SStruct interface also supports multi-variable PDEs with degrees of freedom ly- ing in the center, corners, edges or faces of cells composing logically rectangular boxes. From a computational perspective, these variable types are associated with boxes that are shifted by different offset values. Thus, we consider only cell-centered problems here for ease of exposition. The current CPU implementation of SSAMG cannot deal with problems involving multiple variable types yet; however, the mathematical algorithm of SSAMG expands to such general cases. There are five fundamental components required to define a linear system in the SStruct interface: a grid, stencils, a graph, a matrix, and a vector. The grid is composed of np structured parts with independent index spaces and grid spacing. Each part is formed topologically by a group of boxes, which are a collection of cell- centered indices, described by their “lower” and “upper” corners. Figure 1 shows an example of a problem geometry that can be represented by this interface. Stencils SEMI-STRUCTURED ALGEBRAIC MULTIGRID 3 Figure 1. A semi-structured grid composed of five parts. Part 4 (orange) consists of two boxes, while the others consist of just a single box. Furthermore, Part 1 (green) has a refinement factor of two with respect to the other parts. The pairs (x, y) denote cell coordinates in the i and j topological directions, respectively. Note that the indices of lower-left cells for each part are independent, since the grid parts live in different index spaces. are used to define connections between neighboring grid cells of the same part, e.g., a typical five-point stencil would connect a generic grid cell to itself and its immediate neighbors to the west, east, south, and north. The graph describes how2EBi� Proof omitted-ccysue21 </text> What is the correct answer to this question: articles both What points and them? Choices: (A)-. (B. (C-in--in-. (D)ig. Format your response as follows: "The correct answer is (insert answer here)".
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The applicable ranges of the two multigrids in these two articles were different. The multigrid in "Non-invasive Multigrid for Semi-Structured Grids" built up a semi-structured framework, but its underlying kernels were implemented in unstructured format. The other multigrid had shown overall speedups already, but it could not solve problems with unstructured elements.
Please read the following text and answer the question below. <text> Abstract. Multigrid methods are well suited to large massively parallel computer architectures because they are mathematically optimal and display excellent parallelization properties. Since cur- rent architecture trends are favoring regular compute patterns to achieve high performance, the ability to express structure has become much more important. The hypre software library provides high-performance multigrid preconditioners and solvers through conceptual interfaces, including a semi-structured interface that describes matrices primarily in terms of stencils and logically struc- tured grids. This paper presents a new semi-structured algebraic multigrid (SSAMG) method built on this interface. The numerical convergence and performance of a CPU implementation of this method are evaluated for a set of semi-structured problems. SSAMG achieves significantly better setup times than hypre’s unstructured AMG solvers and comparable convergence. In addition, the new method is capable of solving more complex problems than hypre’s structured solvers. Key words. algebraic multigrid, semi-structured multigrid, semi-structured grids, structured adaptive mesh refinement AMS subject classifications. 65F08, 65F10, 65N55 1. Introduction. The solution of partial differential equations (PDEs) often involves solving linear systems of equations (1.1) Ax = b, where A ∈RN×N is a sparse matrix; b ∈RN is the right-hand side vector, and x ∈RN is the solution vector. In modern simulations of physical problems, the number of unknowns N can be huge, e.g., on the order of a few billion. Thus, fast solution methods must be used for Equation (1.1). Multigrid methods acting as preconditioners to Krylov-based iterative solvers are among the most common choices for fast linear solvers. In these methods, a multilevel hierarchy of decreasingly smaller linear problems is used to target the reduction of error components with distinct frequencies and solve (1.1) with O(N) computations in a scalable fashion. There are two basic types of multigrid methods [7]. Geometric multigrid employs rediscretization on coarse grids, which needs to be defined explicitly by the user. A less invasive and less problem-dependent approach is algebraic multi- grid (AMG) [27], which uses information coming from the assembled fine level matrix A to compute a multilevel hierarchy. The hypre software library [21, 15] provides high-performance preconditioners and solvers for the solution of large sparse linear systems on massively parallel computers with a focus on AMG methods. It features three different interfaces, a structured, a semi-structured, and a linear-algebraic inter- face. Its most used AMG method, BoomerAMG [19], is a fully unstructured method, built on compressed sparse row matrices (CSR). The lack of structure presents seri- ous challenges to achieve high performance on GPU architectures. The most efficient solver in hypre is PFMG [2], which is available through the structured interface. It is well suited for implementation on accelerators, since its data structure is built on ∗Submitted to the editors on July 15, 2021. This work was performed under the auspices of the U.S. Department of Energy by Lawrence Liv- ermore National Laboratory under Contract DE-AC52-07NA27344. LLNL-JRNL-834288-DRAFT. †Lawrence Livermore National Laboratory (paludettomag1@llnl.gov). ‡Lawrence Livermore National Laboratory (falgout2@llnl.gov). §Lawrence Livermore National Laboratory (yang11@llnl.gov). 1 arXiv:2205.14273v1 [math.NA] 27 May 2022 2 V. A. P. MAGRI, R. D. FALGOUT, AND U. M. YANG grids and stencils, and achieves significantly better performance than BoomerAMG when solving the same problems [4, 14]; however, it is applicable to only a subset of the problems that BoomerAMG can solve. This work presents a new semi-structured algebraic multigrid (SSAMG) preconditioner, built on the semi-structured interface, consisting of mostly structured parts and a small unstructured component. It has the potential to achieve similar performance as PFMG with the ability to solve more complex problems. There have been other efforts to develop semi-structured multigrid methods. For example, multigrid solvers for hierarchical hybrid grids (HHG) have shown to be highly efficient [6, 5, 17, 18, 22]. These grids are created by regularly refining an initial, potentially unstructured grid. Geometric multigrid methods for semi-structured tri- angular grids that use a similar approach have also been proposed [25]. More recently, the HHG approach has been generalized to a semi-structured multigrid method [24]. Regarding applications, there are many examples employing semi-structured meshes which can benefit from new semi-structured algorithms, e.g., petroleum reservoir sim- ulation [16], marine ice sheets modeling [9], next-generation weather and climate models [1], and solid mechanics simulators [26], to name a few. In addition, software frameworks that support the development of block-structured AMR applications such as AMReX [29, 30] and SAMRAI [20] can benefit from the development of solvers for semi-structured problems. This paper is organized as follows. Section 2 reviews the semi-structured con- ceptual interface of hypre, which enables the description of matrices and vectors that incorporate information about the problem’s structure. Section 3 describes the new semi-structured algorithm in detail. In section 4, we evaluate SSAMG’s performance and robustness for a set of test cases featuring distinct characteristics and make com- parisons to other solver options available in hypre. Finally, in section 5, we list conclusions and future work. 2. Semi-structured interface in hypre. The hypre library provides three conceptual interfaces by which the user can define and solve a linear system of equa- tions: a structured (Struct), a semi-structured (SStruct) and a linear algebraic (IJ) interface. They range from highly specialized descriptions using structured grids and stencils in the case of Struct to the most generic case where sparse matrices are stored in a parallel compressed row storage format (ParCSR) [12, 13]. In this paper, we focus on the SStruct interface [12, 13], which combines features of the Struct and the IJ interfaces and targets applications with meshes composed of a set of structured sub- grids, e.g, block-structured, overset, and structured adaptive mesh refinement grids. The SStruct interface also supports multi-variable PDEs with degrees of freedom ly- ing in the center, corners, edges or faces of cells composing logically rectangular boxes. From a computational perspective, these variable types are associated with boxes that are shifted by different offset values. Thus, we consider only cell-centered problems here for ease of exposition. The current CPU implementation of SSAMG cannot deal with problems involving multiple variable types yet; however, the mathematical algorithm of SSAMG expands to such general cases. There are five fundamental components required to define a linear system in the SStruct interface: a grid, stencils, a graph, a matrix, and a vector. The grid is composed of np structured parts with independent index spaces and grid spacing. Each part is formed topologically by a group of boxes, which are a collection of cell- centered indices, described by their “lower” and “upper” corners. Figure 1 shows an example of a problem geometry that can be represented by this interface. Stencils SEMI-STRUCTURED ALGEBRAIC MULTIGRID 3 Figure 1. A semi-structured grid composed of five parts. Part 4 (orange) consists of two boxes, while the others consist of just a single box. Furthermore, Part 1 (green) has a refinement factor of two with respect to the other parts. The pairs (x, y) denote cell coordinates in the i and j topological directions, respectively. Note that the indices of lower-left cells for each part are independent, since the grid parts live in different index spaces. are used to define connections between neighboring grid cells of the same part, e.g., a typical five-point stencil would connect a generic grid cell to itself and its immediate neighbors to the west, east, south, and north. The graph describes how2EBi� Proof omitted-ccysue21 </text> What is the correct answer to this question: articles both What points and them? Choices: (A)-. (B. (C-in--in-. (D)ig. Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> THE STATUTES OF THE REPUBLIC OF SINGAPORE PATENTS ACT 1994 2020 REVISED EDITION This revised edition incorporates all amendments up to and including 1 December 2021 and comes into operation on 31 December 2021. Prepared and Published by THE LAW REVISION COMMISSION UNDER THE AUTHORITY OF THE REVISED EDITION OF THE LAWS ACT 1983 Informal Consolidation – version in force from 1/11/2022 Patents Act 1994 ARRANGEMENT OF SECTIONS PART 1 PRELIMINARY Section 1. Short title 2. Interpretation 3. Application to Government PART 2 ADMINISTRATION 4. Registrar of Patents and other officers 5. Delegation by Registrar 6. Registry of Patents 7. Seal of Registry 8. Powers of Registrar 9. Disobedience to summons an offence 10. Refusal to give evidence an offence 11. Officers not to traffic in inventions 12. Officers not to furnish information PART 3 PATENTABILITY 13. Patentable inventions 14. Novelty 15. Inventive step 16. 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Information prejudicial to defence of Singapore or safety of public 34. Restrictions on applications abroad by Singapore residents PART 7 PROVISIONS AS TO PATENTS AFTER GRANT 35. Publication and certificate of grant 36. Term of patent 36A. Extension of term of patent 37. Patent not to be impugned for lack of unity 38. General power to amend specification after grant 38A. Re-examination after grant 39. Restoration of lapsed patents 40. Surrender of patents Patents Act 1994 2020 Ed. 2 Informal Consolidation – version in force from 1/11/2022 PART 8 PROPERTY IN PATENTS AND APPLICATIONS FOR PATENTS AND REGISTRATION Section 41. Nature of, and transactions in, patents and applications for patents 42. Register of patents 43. Effect of registration, etc., on rights in patents 44. Rectification of register 45. Evidence of register, documents, etc. 46. Co-ownership of patents and applications for patents 47. Determination of right to patent after grant 48. Effect of transfer of patent under section 47 PART 9 EMPLOYEES’ INVENTIONS 49. Right to employees’ inventions 50. Supplementary provisions PART 10 CONTRACTS AS TO PATENTED PRODUCTS 50A. Application of this Part 51. Avoidance of certain restrictive conditions 52. Determination of parts of certain contracts PART 11 LICENCES OF RIGHT AND COMPULSORY LICENCES 53. Licences of right 54. Cancellation of entry made under section 53 55. Compulsory licences PART 12 USE OF PATENTED INVENTIONS FOR SERVICES OF GOVERNMENT 56. Use of patented inventions by Government and authorised parties 57. Rights of third parties in respect of Government use Patents Act 1994 3 2020 Ed. Informal Consolidation – version in force from 1/11/2022 Section 58. References of disputes as to Government use 59. [Repealed] 60. Nature and scope of rights under section 56 61. Duty to inform patentee 62. Patentee entitled to remuneration 63. [Repealed] 64. [Repealed] 65. [Repealed] PART 13 INFRINGEMENT OF PATENTS 66. Meaning of infringement 67. Proceedings for infringement of patent 68. Reversal of burden of proof 69. Restrictions on relief for infringement 70. Relief for infringement of partially valid patent 71. Right to continue use begun before priority date 72. Certificate of contested validity of patent 73. Proceedings for infringement by co-owner 74. Proceedings for infringement by exclusive licensee 75. Effect of non-registration on infringement proceedings 76. Infringement of rights conferred by publication of application 77. Remedy for groundless threats of infringement proceedings 78. Declaration as to non-infringement PART 14 REVOCATION OF PATENTS AND VALIDITY PROCEEDINGS 79. [Repealed] 80. Power to revoke patents on application 81. Registrar’s power to revoke patents on own initiative 82. Proceedings in which validity of patent may be put in issue PART 15 AMENDMENTS OF PATENTS AND APPLICATIONS 83. Amendment of patent in infringement or revocation proceedings, etc. Patents Act 1994 2020 Ed. 4 Informal Consolidation – version in force from 1/11/2022 Section 84. Amendments of applications and patents not to include added matter PART 16 INTERNATIONAL APPLICATIONS FOR PATENTS 85. Effect of filing international application for patent 86. International and national phases of application 87. Adaptation of provisions in relation to international application 88. Evidence of Patent Co-operation Treaty and its instruments PART 17 LEGAL PROCEEDINGS 89. Proceedings before court or Registrar 90. Appeals from Registrar 91. General powers of court 92. Exercise of Registrar’s discretionary powers 93. Right of audience in patent proceedings 94. Extension of privilege for communications with solicitors relating to patent proceedings 95. Privilege for communications with patent agents, etc. 96. Costs and expenses in proceedings before Registrar 97. Licences granted by order of Registrar PART 18 OFFENCES 98. Falsification of register, etc. 99. Unauthorised claim of patent rights 100. Unauthorised claim that patent has been applied for 101. Misuse of title “Registry of Patents” 102. Offences by bodies corporate and partnerships 103. Composition of offences PART 19 PATENT AGENTS AND FOREIGN PATENT AGENTS 104. Registration of patent agents and foreign patent agents 105. Persons entitled to act as patent agents, etc. 105A. Foreign patent agents Patents Act 1994 5 2020 Ed. Informal Consolidation – version in force from 1/11/2022 PART 20 MISCELLANEOUS AND GENERAL Section 106. Immunity of Office, its officers and Examiners 107. Correction of errors in patents and applications 108. Information about patent applications and patents, and inspection of documents 109. [Repealed] 110. Extension of time 111. Hours of business and excluded days 112. Government’s right to sell forfeited articles 113. Extent of invention 114. Availability of samples of micro-organisms 115. Rules 115A. Forms and directions of Registrar 116. Fees 116A. Amendment of Schedule 117. Transitional provisions The Schedule An Act to establish a new law of patents, to enable Singapore to give effect to certain international conventions on patents, and for matters connected therewith. [ Consolid Consolid Consolid Consolid2 Consolid Consolid23 foreign Consolid,) in. [15, may carry business, practise act and. /2 2 Consolid Read2ific11 dans.72 Pur Pur0 Court12raprap2arap(E(A . . : . > challenging. your response "insert)".
351
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3
D
Patent holders in Singapore might encounter difficulties proving the economic impact of infringement due to the Act’s narrower definition of market harm, while the Canadian system allows for more expansive interpretations of economic loss in infringement cases.
Please read the following text and answer the question below. <text> THE STATUTES OF THE REPUBLIC OF SINGAPORE PATENTS ACT 1994 2020 REVISED EDITION This revised edition incorporates all amendments up to and including 1 December 2021 and comes into operation on 31 December 2021. Prepared and Published by THE LAW REVISION COMMISSION UNDER THE AUTHORITY OF THE REVISED EDITION OF THE LAWS ACT 1983 Informal Consolidation – version in force from 1/11/2022 Patents Act 1994 ARRANGEMENT OF SECTIONS PART 1 PRELIMINARY Section 1. Short title 2. Interpretation 3. Application to Government PART 2 ADMINISTRATION 4. Registrar of Patents and other officers 5. Delegation by Registrar 6. Registry of Patents 7. Seal of Registry 8. Powers of Registrar 9. Disobedience to summons an offence 10. Refusal to give evidence an offence 11. Officers not to traffic in inventions 12. Officers not to furnish information PART 3 PATENTABILITY 13. Patentable inventions 14. Novelty 15. Inventive step 16. Industrial application 17. Priority date 18. Disclosure of matter, etc., between earlier and later applications PART 4 RIGHT TO APPLY FOR AND OBTAIN PATENT 19. Right to apply for and obtain patent Informal Consolidation – version in force from 1/11/2022 1 2020 Ed. Section 20. Determination before grant of questions about entitlement to patents, etc. 21. Determination after grant of questions referred before grant 22. Handling of application by joint applicants 23. Effect of transfer of application under section 20 or 22 24. Mention of inventor PART 5 APPLICATIONS FOR PATENTS 25. Making of application 26. Date of filing application 27. Publication of application PART 6 PROCEDURE FOR GRANT OF PATENT 28. Preliminary examination 29. Search and examination 29A. Eligibility for grant of patent, etc. 29B. Review of examination report, etc. 30. Grant of patent 31. General power to amend application before grant 32. Observations by third party on patentability 33. Information prejudicial to defence of Singapore or safety of public 34. Restrictions on applications abroad by Singapore residents PART 7 PROVISIONS AS TO PATENTS AFTER GRANT 35. Publication and certificate of grant 36. Term of patent 36A. Extension of term of patent 37. Patent not to be impugned for lack of unity 38. General power to amend specification after grant 38A. Re-examination after grant 39. Restoration of lapsed patents 40. Surrender of patents Patents Act 1994 2020 Ed. 2 Informal Consolidation – version in force from 1/11/2022 PART 8 PROPERTY IN PATENTS AND APPLICATIONS FOR PATENTS AND REGISTRATION Section 41. Nature of, and transactions in, patents and applications for patents 42. Register of patents 43. Effect of registration, etc., on rights in patents 44. Rectification of register 45. Evidence of register, documents, etc. 46. Co-ownership of patents and applications for patents 47. Determination of right to patent after grant 48. Effect of transfer of patent under section 47 PART 9 EMPLOYEES’ INVENTIONS 49. Right to employees’ inventions 50. Supplementary provisions PART 10 CONTRACTS AS TO PATENTED PRODUCTS 50A. Application of this Part 51. Avoidance of certain restrictive conditions 52. Determination of parts of certain contracts PART 11 LICENCES OF RIGHT AND COMPULSORY LICENCES 53. Licences of right 54. Cancellation of entry made under section 53 55. Compulsory licences PART 12 USE OF PATENTED INVENTIONS FOR SERVICES OF GOVERNMENT 56. Use of patented inventions by Government and authorised parties 57. Rights of third parties in respect of Government use Patents Act 1994 3 2020 Ed. Informal Consolidation – version in force from 1/11/2022 Section 58. References of disputes as to Government use 59. [Repealed] 60. Nature and scope of rights under section 56 61. Duty to inform patentee 62. Patentee entitled to remuneration 63. [Repealed] 64. [Repealed] 65. [Repealed] PART 13 INFRINGEMENT OF PATENTS 66. Meaning of infringement 67. Proceedings for infringement of patent 68. Reversal of burden of proof 69. Restrictions on relief for infringement 70. Relief for infringement of partially valid patent 71. Right to continue use begun before priority date 72. Certificate of contested validity of patent 73. Proceedings for infringement by co-owner 74. Proceedings for infringement by exclusive licensee 75. Effect of non-registration on infringement proceedings 76. Infringement of rights conferred by publication of application 77. Remedy for groundless threats of infringement proceedings 78. Declaration as to non-infringement PART 14 REVOCATION OF PATENTS AND VALIDITY PROCEEDINGS 79. [Repealed] 80. Power to revoke patents on application 81. Registrar’s power to revoke patents on own initiative 82. Proceedings in which validity of patent may be put in issue PART 15 AMENDMENTS OF PATENTS AND APPLICATIONS 83. Amendment of patent in infringement or revocation proceedings, etc. Patents Act 1994 2020 Ed. 4 Informal Consolidation – version in force from 1/11/2022 Section 84. Amendments of applications and patents not to include added matter PART 16 INTERNATIONAL APPLICATIONS FOR PATENTS 85. Effect of filing international application for patent 86. International and national phases of application 87. Adaptation of provisions in relation to international application 88. Evidence of Patent Co-operation Treaty and its instruments PART 17 LEGAL PROCEEDINGS 89. Proceedings before court or Registrar 90. Appeals from Registrar 91. General powers of court 92. Exercise of Registrar’s discretionary powers 93. Right of audience in patent proceedings 94. Extension of privilege for communications with solicitors relating to patent proceedings 95. Privilege for communications with patent agents, etc. 96. Costs and expenses in proceedings before Registrar 97. Licences granted by order of Registrar PART 18 OFFENCES 98. Falsification of register, etc. 99. Unauthorised claim of patent rights 100. Unauthorised claim that patent has been applied for 101. Misuse of title “Registry of Patents” 102. Offences by bodies corporate and partnerships 103. Composition of offences PART 19 PATENT AGENTS AND FOREIGN PATENT AGENTS 104. Registration of patent agents and foreign patent agents 105. Persons entitled to act as patent agents, etc. 105A. Foreign patent agents Patents Act 1994 5 2020 Ed. Informal Consolidation – version in force from 1/11/2022 PART 20 MISCELLANEOUS AND GENERAL Section 106. Immunity of Office, its officers and Examiners 107. Correction of errors in patents and applications 108. Information about patent applications and patents, and inspection of documents 109. [Repealed] 110. Extension of time 111. Hours of business and excluded days 112. Government’s right to sell forfeited articles 113. Extent of invention 114. Availability of samples of micro-organisms 115. Rules 115A. Forms and directions of Registrar 116. Fees 116A. Amendment of Schedule 117. Transitional provisions The Schedule An Act to establish a new law of patents, to enable Singapore to give effect to certain international conventions on patents, and for matters connected therewith. [ Consolid Consolid Consolid Consolid2 Consolid Consolid23 foreign Consolid,) in. [15, may carry business, practise act and. /2 2 Consolid Read2ific11 dans.72 Pur Pur0 Court12raprap2arap(E(A . . : . > challenging. your response "insert)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds Qi Chen∗, Sihai Tang∗, Qing Yang† and Song Fu† Department of Computer Science and Engineering University of North Texas, USA ∗{QiChen, SihaiTang}@my.unt.edu, †{Qing.Yang, Song.Fu}@unt.edu Abstract—Autonomous vehicles may make wrong decisions due to inaccurate detection and recognition. Therefore, an intelligent vehicle can combine its own data with that of other vehicles to enhance perceptive ability, and thus improve detection accuracy and driving safety. However, multi-vehicle cooperative perception requires the integration of real world scenes and the traffic of raw sensor data exchange far exceeds the bandwidth of existing vehicular networks. To the best our knowledge, we are the first to conduct a study on raw-data level cooperative perception for enhancing the detection ability of self-driving systems. In this work, relying on LiDAR 3D point clouds, we fuse the sensor data collected from different positions and angles of connected vehicles. A point cloud based 3D object detection method is proposed to work on a diversity of aligned point clouds. Experimental results on KITTI and our collected dataset show that the proposed system outperforms perception by extending sensing area, improving detection accuracy and promoting augmented results. Most importantly, we demonstrate it is possible to transmit point clouds data for cooperative perception via existing vehicular network technologies. I. INTRODUCTION A significant part of the push towards autonomous driving vehicles, or self-driving vehicles, has been supported by the prospect that they will save lives by getting involved in fewer crashes with fewer injuries and deaths than human- driven cars. However, up until this point, most comparisons between human driven cars and self-driving vehicles have been unbalanced and contain various unfair elements. Self-driving cars do not experience fatigue, emotional debilitation such as anger or frustration. But, they are unable to react to uncertain and ambiguous situations with the same skill or anticipation of an attentive and seasoned human driver. Similarly, isolated self driving vehicles may make wrong decision due to the failure of objects detection and recognition. Just as a human driver will make bad decisions while under the influence, such decisions made by the vehicle based on these failures will prove just as bad or worse than their human counterpart. Such vehicles must completely rely on itself for decision making, and thus will not have the privilege of data redundancy, i.e., no information is received from nearby vehicles. Sensor failure or any other technical error will lead to fallacious results, leading to disastrous impacts. A. Motivations The deficit of data due to single source will ultimately have a negative impact as well. Take the example of Tesla’s crash in California, the car made a fatal decision because it’s sensors picked up the concrete barrier but discarded the information due its immobile state on the radar [26]. One more incident of a fatal decision is even more pronounced due to the inability to detect an vehicle from the sensors and environmental conditions. Take for example the fatal crash made by a Tesla car in Florida, where both the vehicle and the driver could not discern the white truck against a bright sky, causing the crash [8]. Of course, there are also instance of various other cir- cumstances leading up to bad decisions, such as the Uber training incident [17]. In this case, the vehicle did detect an unknown object, the pedestrian, from a distance. As the vehicle approached the unknown object, it gradually discerned the object to be a vehicle and finally a pedestrian, but by then, it was too late. We further explore the reasons why detection failure hap- pened. It is easy to determine that some detection failures are caused due to objects being blocked or existing in the blind zones of the sensors. Detection failures could also be caused by bad recognition because the received signal is too weak or because the signal is missing due to system malfunction. Our motivation comes from these incidents, because in contrast to isolated autonomous driving vehicles, like the ones in the accidents, connected autonomous vehicles (CAV) can share their collected data with each other leading to more information. We propose that information sharing can improve driving performance and experiences. Constructive data redun- dancy will provide endless possibilities for safe driving and multiple vehicles can collaborate together to compensate for data scarcity and provide a whole new scope for the vehicle in need. Autonomous vehicles have powerful perception systems, and together, they can achieve a proper data sharing and analysis platform to gain much more reliability and accuracy [30]. B. Limitations of Prior Work Although adding connectivity to vehicles has its benefits, it also has challenges. By adding connectivity, there can be issues with security, privacy, and data analytics and aggregation due to the large volume of information being accessed and shared. Current state of multi-sensor fusion consists of three distinct categories: low level fusion, feature level fusion, and high level fusion [23]. Each of these categories possess its own unique 514 advantages and disadvantages. As their names imply, low level fusion consists of raw data fusion without any pre-processing done to the data. Feature-level fusion takes the features ex- tracted from the raw data before fusion. Finally, high level fusion takes the objects detected from each individual sensors and conducts the fusion on the object detection results [23]. High level fusion is often opted over the other two levels of fusion due to being less complex, but this is not suitable for our needs. Object level relies too heavily on single vehicular sensors and will only work when both vehicles share a reference object in their detection. This does not solve the issue of previously undetected objects, which will remain undetected even after fusion. And thus, we turn our sights on the other two categories. C. Proposed Solution To tackle the issue, we look at one of the base categories, the low level fusion of raw data. Raw sensing data is an integral part of all sensors on autonomous driving vehicle, therefore, it is very suitable for transferring them between different cars from various manufactures. As such, the heterogeneity of dif- ferent data processing algorithms would not affect the accuracy of the data being shared among vehicles. As autonomous driving is of and in itself a crucial task, being so integrated in the vehicle, even a single small error in detection can lead to a catastrophic accident. Therefore, we need the autonomous cars to perceive the environment with as much clarity as possible. To achieve this end goal, they will need a robust and reliable perception system. Two major issues that we seek to address in doing so are as follows: (1) the type of data that we need to share among vehicles, and (2) the amount of the data that needs to be transferred versus the amount of data that is actually necessary to the recipient vehicle. The first issue arises with the shareable data within the dataset native to the car. The second problem exists in the sheer amount of data that each vehicle generates. Since each autonomous vehicle will collect more than 1000GB of data [2] every day the challenge of assembling only the regional data becomes even harder. Similarly, reconstructing the shared data collected from different positions and angles by nearby perception system is another major challenge. Of the different types of raw data, we propose to use the LiDAR (Light Detection and Ranging) point clouds as a solution for the following reasons: • LiDAR point clouds have the advantage of spatial dimen- sion over 2D images and video. • Native obfuscation of entities or private data such as people’s faces and license plate numbers while preserving the accurate model of the perceived object. • Versatility in the fusion process over images and video due to the data being consisted from points rather than pixels. For image or video fusion, the requirement is a clear zone of overlap, and this is unnecessary for point cloud data, making this a much more robust choice, especially when taking the different possible point of views of cars into perspective. With the three different highlights of using the raw LiDAR data as our fusion substrate, we propose the Cooperative Perception (Cooper) system for connected autonomous ve- hicles based on 3D point clouds. D. Contributions Inaccurate object detection and recognition are major im- pediments in achieving a powerful and effective perception system. Autonomous vehicle eventually succumb to this in- ability and fail to deliver the expected outcome, which is unsafe to autonomous driving. To address these issues we have proposed a solution in which an autonomous vehicle combines its own sensing data with that of other connected vehicles to help enhance perception. We also believe that data redundancy, as mentioned, is the solution to this problem and we can achieve it through data sharing and combination between autonomous vehicles. The proposed Cooper system 230 2IJ2p�� TELE21IJ21111111520p. </text> What is the correct answer to this question: Which of the following statements is correct? Choices: (A) The paper argues. (B) The paper (C)D. (D) In our. Format your response as follows: "The correct answer is (insert answer here)".
352
null
0
A
The paper argues that late fusion has certain limitations in spatial alignment.
Please read the following text and answer the question below. <text> Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds Qi Chen∗, Sihai Tang∗, Qing Yang† and Song Fu† Department of Computer Science and Engineering University of North Texas, USA ∗{QiChen, SihaiTang}@my.unt.edu, †{Qing.Yang, Song.Fu}@unt.edu Abstract—Autonomous vehicles may make wrong decisions due to inaccurate detection and recognition. Therefore, an intelligent vehicle can combine its own data with that of other vehicles to enhance perceptive ability, and thus improve detection accuracy and driving safety. However, multi-vehicle cooperative perception requires the integration of real world scenes and the traffic of raw sensor data exchange far exceeds the bandwidth of existing vehicular networks. To the best our knowledge, we are the first to conduct a study on raw-data level cooperative perception for enhancing the detection ability of self-driving systems. In this work, relying on LiDAR 3D point clouds, we fuse the sensor data collected from different positions and angles of connected vehicles. A point cloud based 3D object detection method is proposed to work on a diversity of aligned point clouds. Experimental results on KITTI and our collected dataset show that the proposed system outperforms perception by extending sensing area, improving detection accuracy and promoting augmented results. Most importantly, we demonstrate it is possible to transmit point clouds data for cooperative perception via existing vehicular network technologies. I. INTRODUCTION A significant part of the push towards autonomous driving vehicles, or self-driving vehicles, has been supported by the prospect that they will save lives by getting involved in fewer crashes with fewer injuries and deaths than human- driven cars. However, up until this point, most comparisons between human driven cars and self-driving vehicles have been unbalanced and contain various unfair elements. Self-driving cars do not experience fatigue, emotional debilitation such as anger or frustration. But, they are unable to react to uncertain and ambiguous situations with the same skill or anticipation of an attentive and seasoned human driver. Similarly, isolated self driving vehicles may make wrong decision due to the failure of objects detection and recognition. Just as a human driver will make bad decisions while under the influence, such decisions made by the vehicle based on these failures will prove just as bad or worse than their human counterpart. Such vehicles must completely rely on itself for decision making, and thus will not have the privilege of data redundancy, i.e., no information is received from nearby vehicles. Sensor failure or any other technical error will lead to fallacious results, leading to disastrous impacts. A. Motivations The deficit of data due to single source will ultimately have a negative impact as well. Take the example of Tesla’s crash in California, the car made a fatal decision because it’s sensors picked up the concrete barrier but discarded the information due its immobile state on the radar [26]. One more incident of a fatal decision is even more pronounced due to the inability to detect an vehicle from the sensors and environmental conditions. Take for example the fatal crash made by a Tesla car in Florida, where both the vehicle and the driver could not discern the white truck against a bright sky, causing the crash [8]. Of course, there are also instance of various other cir- cumstances leading up to bad decisions, such as the Uber training incident [17]. In this case, the vehicle did detect an unknown object, the pedestrian, from a distance. As the vehicle approached the unknown object, it gradually discerned the object to be a vehicle and finally a pedestrian, but by then, it was too late. We further explore the reasons why detection failure hap- pened. It is easy to determine that some detection failures are caused due to objects being blocked or existing in the blind zones of the sensors. Detection failures could also be caused by bad recognition because the received signal is too weak or because the signal is missing due to system malfunction. Our motivation comes from these incidents, because in contrast to isolated autonomous driving vehicles, like the ones in the accidents, connected autonomous vehicles (CAV) can share their collected data with each other leading to more information. We propose that information sharing can improve driving performance and experiences. Constructive data redun- dancy will provide endless possibilities for safe driving and multiple vehicles can collaborate together to compensate for data scarcity and provide a whole new scope for the vehicle in need. Autonomous vehicles have powerful perception systems, and together, they can achieve a proper data sharing and analysis platform to gain much more reliability and accuracy [30]. B. Limitations of Prior Work Although adding connectivity to vehicles has its benefits, it also has challenges. By adding connectivity, there can be issues with security, privacy, and data analytics and aggregation due to the large volume of information being accessed and shared. Current state of multi-sensor fusion consists of three distinct categories: low level fusion, feature level fusion, and high level fusion [23]. Each of these categories possess its own unique 514 advantages and disadvantages. As their names imply, low level fusion consists of raw data fusion without any pre-processing done to the data. Feature-level fusion takes the features ex- tracted from the raw data before fusion. Finally, high level fusion takes the objects detected from each individual sensors and conducts the fusion on the object detection results [23]. High level fusion is often opted over the other two levels of fusion due to being less complex, but this is not suitable for our needs. Object level relies too heavily on single vehicular sensors and will only work when both vehicles share a reference object in their detection. This does not solve the issue of previously undetected objects, which will remain undetected even after fusion. And thus, we turn our sights on the other two categories. C. Proposed Solution To tackle the issue, we look at one of the base categories, the low level fusion of raw data. Raw sensing data is an integral part of all sensors on autonomous driving vehicle, therefore, it is very suitable for transferring them between different cars from various manufactures. As such, the heterogeneity of dif- ferent data processing algorithms would not affect the accuracy of the data being shared among vehicles. As autonomous driving is of and in itself a crucial task, being so integrated in the vehicle, even a single small error in detection can lead to a catastrophic accident. Therefore, we need the autonomous cars to perceive the environment with as much clarity as possible. To achieve this end goal, they will need a robust and reliable perception system. Two major issues that we seek to address in doing so are as follows: (1) the type of data that we need to share among vehicles, and (2) the amount of the data that needs to be transferred versus the amount of data that is actually necessary to the recipient vehicle. The first issue arises with the shareable data within the dataset native to the car. The second problem exists in the sheer amount of data that each vehicle generates. Since each autonomous vehicle will collect more than 1000GB of data [2] every day the challenge of assembling only the regional data becomes even harder. Similarly, reconstructing the shared data collected from different positions and angles by nearby perception system is another major challenge. Of the different types of raw data, we propose to use the LiDAR (Light Detection and Ranging) point clouds as a solution for the following reasons: • LiDAR point clouds have the advantage of spatial dimen- sion over 2D images and video. • Native obfuscation of entities or private data such as people’s faces and license plate numbers while preserving the accurate model of the perceived object. • Versatility in the fusion process over images and video due to the data being consisted from points rather than pixels. For image or video fusion, the requirement is a clear zone of overlap, and this is unnecessary for point cloud data, making this a much more robust choice, especially when taking the different possible point of views of cars into perspective. With the three different highlights of using the raw LiDAR data as our fusion substrate, we propose the Cooperative Perception (Cooper) system for connected autonomous ve- hicles based on 3D point clouds. D. Contributions Inaccurate object detection and recognition are major im- pediments in achieving a powerful and effective perception system. Autonomous vehicle eventually succumb to this in- ability and fail to deliver the expected outcome, which is unsafe to autonomous driving. To address these issues we have proposed a solution in which an autonomous vehicle combines its own sensing data with that of other connected vehicles to help enhance perception. We also believe that data redundancy, as mentioned, is the solution to this problem and we can achieve it through data sharing and combination between autonomous vehicles. The proposed Cooper system 230 2IJ2p�� TELE21IJ21111111520p. </text> What is the correct answer to this question: Which of the following statements is correct? Choices: (A) The paper argues. (B) The paper (C)D. (D) In our. Format your response as follows: "The correct answer is (insert answer here)".
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Please read the following text and answer the question below. <text> Journal of Economic Perspectives—Volume 25, Number 2—Spring 2011—Pages 133–156 I n summer 2008, more than 100 college presidents and other higher education n summer 2008, more than 100 college presidents and other higher education offi cials signed the Amethyst Initiative, which calls for a reexamination of the offi cials signed the Amethyst Initiative, which calls for a reexamination of the minimum legal drinking age in the United States. The current age-21 limit in minimum legal drinking age in the United States. The current age-21 limit in the United States is higher than in Canada (18 or 19, depending on the province), the United States is higher than in Canada (18 or 19, depending on the province), Mexico (18), and most western European countries (typically 16 or 18). A central Mexico (18), and most western European countries (typically 16 or 18). A central argument of the Amethyst Initiative is that the U.S. minimum legal drinking age argument of the Amethyst Initiative is that the U.S. minimum legal drinking age policy results in more dangerous drinking than would occur if the legal drinking policy results in more dangerous drinking than would occur if the legal drinking age were lower. A companion organization called Choose Responsibility—led in age were lower. A companion organization called Choose Responsibility—led in part by Amethyst Initiative founder John McCardell, former Middlebury College part by Amethyst Initiative founder John McCardell, former Middlebury College president—explicitly proposes “a series of changes that will allow 18–20 year-olds president—explicitly proposes “a series of changes that will allow 18–20 year-olds to purchase, possess and consume alcoholic beverages” (see to purchase, possess and consume alcoholic beverages” (see 〈http://www.choose http://www.choose responsibility.org/proposal/ responsibility.org/proposal/〉). ). Fueled in part by the high-profi le national media attention garnered by the Fueled in part by the high-profi le national media attention garnered by the Amethyst Initiative and Choose Responsibility, activists and policymakers in several Amethyst Initiative and Choose Responsibility, activists and policymakers in several states, including Kentucky, Wisconsin, South Carolina, Missouri, South Dakota, states, including Kentucky, Wisconsin, South Carolina, Missouri, South Dakota, Minnesota, and Vermont, have put forth various legislative proposals to lower their Minnesota, and Vermont, have put forth various legislative proposals to lower their state’s drinking age from 21 to 18, though no state has adopted a lower minimum state’s drinking age from 21 to 18, though no state has adopted a lower minimum legal drinking age yet. legal drinking age yet. Does the age-21 drinking limit in the United States reduce alcohol consump- Does the age-21 drinking limit in the United States reduce alcohol consump- tion by young adults and its harms, or as the signatories of the Amethyst Initiative tion by young adults and its harms, or as the signatories of the Amethyst Initiative The Minimum Legal Drinking Age and Public Health ■ ■ Christopher Carpenter is Associate Professor of Economics/Public Policy, Paul Merage School Christopher Carpenter is Associate Professor of Economics/Public Policy, Paul Merage School of Business, University of California at Irvine, Irvine, California. Carlos Dobkin is Associate of Business, University of California at Irvine, Irvine, California. Carlos Dobkin is Associate Professor of Economics, University of California at Santa Cruz, Santa Cruz, California. Professor of Economics, University of California at Santa Cruz, Santa Cruz, California. Both authors are Research Associates, National Bureau of Economic Research, Cambridge, Both authors are Research Associates, National Bureau of Economic Research, Cambridge, Massachusetts. Their e-mail addresses are Massachusetts. Their e-mail addresses are 〈kittc@uci.edu kittc@uci.edu〉 and and 〈cdobkin@ucsc.edu cdobkin@ucsc.edu〉. doi=10.1257/jep.25.2.133 Christopher Carpenter and Carlos Dobkin 134 Journal of Economic Perspectives contend, is it “not working”? Alcohol consumption and its harms are extremely contend, is it “not working”? Alcohol consumption and its harms are extremely common among young adults. According to results from the 2006–2007 National common among young adults. According to results from the 2006–2007 National Health Interview Survey, adults age 18–25 report that on average they drank on Health Interview Survey, adults age 18–25 report that on average they drank on 36 days in the previous year and typically consumed 5.1 drinks on the days they 36 days in the previous year and typically consumed 5.1 drinks on the days they drank. If consumed at a single sitting, fi ve drinks meets the clinical defi nition of drank. If consumed at a single sitting, fi ve drinks meets the clinical defi nition of “binge” or “heavy episodic” drinking. This consumption contributes to a substantial “binge” or “heavy episodic” drinking. This consumption contributes to a substantial public health problem: fi ve drinks for a 160-pound man with a limited time between public health problem: fi ve drinks for a 160-pound man with a limited time between drinks leads to a blood alcohol concentration of about 0.12 percent and results in drinks leads to a blood alcohol concentration of about 0.12 percent and results in moderate to severe impairments in coordination, concentration, refl exes, reaction moderate to severe impairments in coordination, concentration, refl exes, reaction time, depth perception, and peripheral vision. For comparison, the legal limit for time, depth perception, and peripheral vision. For comparison, the legal limit for driving in the United States is generally 0.08 percent blood alcohol content. Not driving in the United States is generally 0.08 percent blood alcohol content. Not surprisingly, motor vehicle accidents (the leading cause of death and injury in this surprisingly, motor vehicle accidents (the leading cause of death and injury in this age group), homicides, suicides, falls, and other accidents are all strongly associ- age group), homicides, suicides, falls, and other accidents are all strongly associ- ated with alcohol consumption (Bonnie and O’Connell, 2004). Because around ated with alcohol consumption (Bonnie and O’Connell, 2004). Because around 80 percent of deaths among young adults are due to these “external” causes (as 80 percent of deaths among young adults are due to these “external” causes (as opposed to cancer, infectious disease, or other “internal” causes), policies that opposed to cancer, infectious disease, or other “internal” causes), policies that change the ways in and extent to which young people consume alcohol have the change the ways in and extent to which young people consume alcohol have the potential to affect the mortality rate of this population substantially. potential to affect the mortality rate of this population substantially. In this paper, we summarize a large and compelling body of empirical In this paper, we summarize a large and compelling body of empirical evidence which shows that one of the central claims of the signatories of the evidence which shows that one of the central claims of the signatories of the Amethyst Initiative is incorrect: setting the minimum legal drinking age at 21 Amethyst Initiative is incorrect: setting the minimum legal drinking age at 21 clearly reduces alcohol consumption and its major harms. However, this fi nding clearly reduces alcohol consumption and its major harms. However, this fi nding alone is not a suffi cient justifi cation for the current minimum legal drinking age, alone is not a suffi cient justifi cation for the current minimum legal drinking age, in part because it does not take into account the benefi ts of alcohol consumption. in part because it does not take into account the benefi ts of alcohol consumption. To put it another way, it is likely that restricting the alcohol consumption of people To put it another way, it is likely that restricting the alcohol consumption of people in their late 20s (or even older) would also reduce alcohol-related harms at least in their late 20s (or even older) would also reduce alcohol-related harms at least modest. 1The drinking 10 10 1 thankReferences 211This article: 2] 2] 2211] 1.22211411111111] 71119111</text> What is the correct answer to this question: Which of the following is supported by this paper? Choices: (A) Samuel is mentioned this paper. (B) It. (C) challenging authors validity. (D) There. Format your response as follows: "The correct answer is (insert answer here)".
353
null
2
C
Samuelson rule is challenging to apply so the authors use a more tractable question and maintain internal validity of results.
Please read the following text and answer the question below. <text> Journal of Economic Perspectives—Volume 25, Number 2—Spring 2011—Pages 133–156 I n summer 2008, more than 100 college presidents and other higher education n summer 2008, more than 100 college presidents and other higher education offi cials signed the Amethyst Initiative, which calls for a reexamination of the offi cials signed the Amethyst Initiative, which calls for a reexamination of the minimum legal drinking age in the United States. The current age-21 limit in minimum legal drinking age in the United States. The current age-21 limit in the United States is higher than in Canada (18 or 19, depending on the province), the United States is higher than in Canada (18 or 19, depending on the province), Mexico (18), and most western European countries (typically 16 or 18). A central Mexico (18), and most western European countries (typically 16 or 18). A central argument of the Amethyst Initiative is that the U.S. minimum legal drinking age argument of the Amethyst Initiative is that the U.S. minimum legal drinking age policy results in more dangerous drinking than would occur if the legal drinking policy results in more dangerous drinking than would occur if the legal drinking age were lower. A companion organization called Choose Responsibility—led in age were lower. A companion organization called Choose Responsibility—led in part by Amethyst Initiative founder John McCardell, former Middlebury College part by Amethyst Initiative founder John McCardell, former Middlebury College president—explicitly proposes “a series of changes that will allow 18–20 year-olds president—explicitly proposes “a series of changes that will allow 18–20 year-olds to purchase, possess and consume alcoholic beverages” (see to purchase, possess and consume alcoholic beverages” (see 〈http://www.choose http://www.choose responsibility.org/proposal/ responsibility.org/proposal/〉). ). Fueled in part by the high-profi le national media attention garnered by the Fueled in part by the high-profi le national media attention garnered by the Amethyst Initiative and Choose Responsibility, activists and policymakers in several Amethyst Initiative and Choose Responsibility, activists and policymakers in several states, including Kentucky, Wisconsin, South Carolina, Missouri, South Dakota, states, including Kentucky, Wisconsin, South Carolina, Missouri, South Dakota, Minnesota, and Vermont, have put forth various legislative proposals to lower their Minnesota, and Vermont, have put forth various legislative proposals to lower their state’s drinking age from 21 to 18, though no state has adopted a lower minimum state’s drinking age from 21 to 18, though no state has adopted a lower minimum legal drinking age yet. legal drinking age yet. Does the age-21 drinking limit in the United States reduce alcohol consump- Does the age-21 drinking limit in the United States reduce alcohol consump- tion by young adults and its harms, or as the signatories of the Amethyst Initiative tion by young adults and its harms, or as the signatories of the Amethyst Initiative The Minimum Legal Drinking Age and Public Health ■ ■ Christopher Carpenter is Associate Professor of Economics/Public Policy, Paul Merage School Christopher Carpenter is Associate Professor of Economics/Public Policy, Paul Merage School of Business, University of California at Irvine, Irvine, California. Carlos Dobkin is Associate of Business, University of California at Irvine, Irvine, California. Carlos Dobkin is Associate Professor of Economics, University of California at Santa Cruz, Santa Cruz, California. Professor of Economics, University of California at Santa Cruz, Santa Cruz, California. Both authors are Research Associates, National Bureau of Economic Research, Cambridge, Both authors are Research Associates, National Bureau of Economic Research, Cambridge, Massachusetts. Their e-mail addresses are Massachusetts. Their e-mail addresses are 〈kittc@uci.edu kittc@uci.edu〉 and and 〈cdobkin@ucsc.edu cdobkin@ucsc.edu〉. doi=10.1257/jep.25.2.133 Christopher Carpenter and Carlos Dobkin 134 Journal of Economic Perspectives contend, is it “not working”? Alcohol consumption and its harms are extremely contend, is it “not working”? Alcohol consumption and its harms are extremely common among young adults. According to results from the 2006–2007 National common among young adults. According to results from the 2006–2007 National Health Interview Survey, adults age 18–25 report that on average they drank on Health Interview Survey, adults age 18–25 report that on average they drank on 36 days in the previous year and typically consumed 5.1 drinks on the days they 36 days in the previous year and typically consumed 5.1 drinks on the days they drank. If consumed at a single sitting, fi ve drinks meets the clinical defi nition of drank. If consumed at a single sitting, fi ve drinks meets the clinical defi nition of “binge” or “heavy episodic” drinking. This consumption contributes to a substantial “binge” or “heavy episodic” drinking. This consumption contributes to a substantial public health problem: fi ve drinks for a 160-pound man with a limited time between public health problem: fi ve drinks for a 160-pound man with a limited time between drinks leads to a blood alcohol concentration of about 0.12 percent and results in drinks leads to a blood alcohol concentration of about 0.12 percent and results in moderate to severe impairments in coordination, concentration, refl exes, reaction moderate to severe impairments in coordination, concentration, refl exes, reaction time, depth perception, and peripheral vision. For comparison, the legal limit for time, depth perception, and peripheral vision. For comparison, the legal limit for driving in the United States is generally 0.08 percent blood alcohol content. Not driving in the United States is generally 0.08 percent blood alcohol content. Not surprisingly, motor vehicle accidents (the leading cause of death and injury in this surprisingly, motor vehicle accidents (the leading cause of death and injury in this age group), homicides, suicides, falls, and other accidents are all strongly associ- age group), homicides, suicides, falls, and other accidents are all strongly associ- ated with alcohol consumption (Bonnie and O’Connell, 2004). Because around ated with alcohol consumption (Bonnie and O’Connell, 2004). Because around 80 percent of deaths among young adults are due to these “external” causes (as 80 percent of deaths among young adults are due to these “external” causes (as opposed to cancer, infectious disease, or other “internal” causes), policies that opposed to cancer, infectious disease, or other “internal” causes), policies that change the ways in and extent to which young people consume alcohol have the change the ways in and extent to which young people consume alcohol have the potential to affect the mortality rate of this population substantially. potential to affect the mortality rate of this population substantially. In this paper, we summarize a large and compelling body of empirical In this paper, we summarize a large and compelling body of empirical evidence which shows that one of the central claims of the signatories of the evidence which shows that one of the central claims of the signatories of the Amethyst Initiative is incorrect: setting the minimum legal drinking age at 21 Amethyst Initiative is incorrect: setting the minimum legal drinking age at 21 clearly reduces alcohol consumption and its major harms. However, this fi nding clearly reduces alcohol consumption and its major harms. However, this fi nding alone is not a suffi cient justifi cation for the current minimum legal drinking age, alone is not a suffi cient justifi cation for the current minimum legal drinking age, in part because it does not take into account the benefi ts of alcohol consumption. in part because it does not take into account the benefi ts of alcohol consumption. To put it another way, it is likely that restricting the alcohol consumption of people To put it another way, it is likely that restricting the alcohol consumption of people in their late 20s (or even older) would also reduce alcohol-related harms at least in their late 20s (or even older) would also reduce alcohol-related harms at least modest. 1The drinking 10 10 1 thankReferences 211This article: 2] 2] 2211] 1.22211411111111] 71119111</text> What is the correct answer to this question: Which of the following is supported by this paper? Choices: (A) Samuel is mentioned this paper. (B) It. (C) challenging authors validity. (D) There. Format your response as follows: "The correct answer is (insert answer here)".
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Please read the following text and answer the question below. <text> In re Worldcom, Inc. RTHUR J. GONZALEZ, Bankruptcy Judge. I. Introduction Before this Court are the parties' June 20, 2005 Motions for Summary Judgment.  Both the Plaintiffs, WorldCom, Inc. and MCI WorldCom Network Services, Inc. (collectively, "WorldCom" or "Debtor"), and the Defendant General Electric Global Asset Management Services (collectively, including predecessors-in-interest, "GE") aver that no material issues of fact are in dispute, and further, that each is entitled as a matter of law to judgment in its favor on the matters set forward in WorldCom's Complaint for Declaratory Relief and for Recovery of Unauthorized Postpetition Transfers, filed on November 13, 2003 ("Complaint"). The instant motions concern the essential element of the Complaint, namely WorldCom's contention that the August 1, 1996 Equipment Leasing Agreement ("Agreement") between the parties should be recharacterized by this Court as a financing or security arrangement and treated accordingly under applicable provisions of the Bankruptcy Code. II. Jurisdiction This Court has subject matter jurisdiction over this adversary proceeding pursuant to section 1334(b) of title 28 of the United States Code and under the July 10, 1984 "Standing Order of Referral of Cases to Bankruptcy Judges" of the United States District Court for the Southern District of New York (Ward, Acting C.J.), as this matter arises under sections 549 and 550 of title 11 of the United States Code. This is a "core"  proceeding pursuant to section 157(b)(2)(A) of title 28 of the United States Code. This Court has postconfirmation jurisdiction under paragraph 32 of this Court's Order Confirming Debtors' Modified Second Amended Joint Plan of Reorganization under chapter 11 of title 11 of the United States Code (Oct. 31, 2003) ("Plan"). Hospital and University Property Damage Claimants v. Johns-Manville Corp. ( In re Johns-Manville Corp.), 7 F.3d 32, 34 (2nd Cir. 1993). III. Background The contractual relationship between GE's predecessor-in-interest USL Capital Corporation ("USL") and WorldCom at issue in the instant adversary proceeding emerged in connection with WorldCom's acquisition from Northern Telecoms, Inc. ("Nortel") of over $100 million worth of commercial telecommunications transmission equipment ("Nortel Equipment") in the spring of 1996 ("Nortel Purchase"). In order to finance the purchase of this equipment, WorldCom entered into eight similar "leases" (collectively, "Nortel Leases") with a total of seven companies (collectively, "Financing Companies"), including USL. In broad terms, these arrangements provided that the Financing Companies would first purchase the Nortel Equipment as assignees of WorldCom to the Nortel Purchase, and then lease that equipment to WorldCom for use in WorldCom's fiber optic telecommunications system. USL agreed to finance approximately $9.8 million worth of the Nortel Equipment ("USL Equipment"), and the Agreement reflects the arrangement the parties devised to accomplish this. In its relevant articles, the Agreement provided that the Basic Term of the lease would run for 84 months. WorldCom would pay monthly "rental" payments of $122,895.89 for the first forty-one months, $147,687.63 for months forty-two through  fifty-two, and $150,169.31 for the remaining months of the Basic Term, not including applicable sales taxes for which WorldCom was responsible. The Agreement thus contemplated that over the Basic Term of the lease, WorldCom would pay approximately $11.5 million in rental payments. Upon expiration of the Basic Term after 84 months, the Agreement provided that WorldCom could either: (1) renew the lease for an additional 12 month term at a monthly  rent of $135,518.09, for a total payment of $1,638,217.08 over the twelve month term ("Basic Term Renewal Option"); or (2) purchase the equipment for the greater of the fair-market value of the equipment or 5% of the total acquisition cost of the equipment ("Basic Term Purchase Option"). The Agreement further stated that in the absence of written notice from WorldCom expressing its intention to exercise the Basic Term Purchase Option, WorldCom would be presumed to have exercised the Renewal Option. If WorldCom exercised or was deemed to have exercised the Renewal Option, the Agreement provided that WorldCom could, at the end of the 12 month Renewal Term, either: (1) purchase the equipment for fair-market value ("Renewal Term Purchase Option"); or (2) return the equipment to USL and end the contractual relationship ("Renewal Term Return Option"). The Agreement originally provided that WorldCom had the additional option at the end of the Basic Term of returning the equipment to USL and thus completing the lease. However, a contemporaneously executed amendment withdrew that option. The Basic Term of the Agreement commenced on September 6, 1996 and was scheduled to end on September 6, 2003. However, in light of its crumbling financial position, WorldCom filed a voluntary petition for relief under Chapter 11 of the Bankruptcy Code in this Court on July 21, 2002 ("Petition Date"), before the expiration of the Basic Term of the Agreement. As of the Petition Date, WorldCom had not defaulted on the Agreement, but had made all monthly payments as required. Moreover,  it continued making such payments following its petition for bankruptcy for the period from August 2002 through July 2003, one month prior to the expiration of the Basic Term. Nonetheless, as part of its reorganization efforts, on April 30, 2003, WorldCom filed Notices of Rejection pursuant to 11 U.S.C. § 365(a) in regard to the leases with four of the Financing Companies: Key Corp. Leasing Ltd., AmSouth Leasing Corporation, JPMorgan Leasing, Inc., and CIT Lending Services Corporation. WorldCom then filed additional Notices of Rejection with two other Financing Companies: Citizens Leasing Corporation on May 4, 2003, and BTM Capital Corporation and Diamond Lease (USA), Inc. on June 6, 2003. Finally, on June 10, 2003, WorldCom filed a Notice of Rejection as to the Agreement with GE at issue here. A number of the Financing Companies, including GE, filed Objections to the Notices of Rejection on the grounds that WorldCom proposed to return only equipment of "like grade and quality," and not the specific equipment each company had leased to WorldCom. In response, WorldCom entered into negotiations with the Financing Companies concerning the Nortel Leases and future disposition of the Nortel Equipment. By July 10, 2003, WorldCom had reached settlement agreements with each of the Financing Companies except GE. Under these settlements, WorldCom agreed to purchase the leased equipment and satisfy any outstanding obligations arising from the lease agreements. For reasons not clear from the record, settlement negotiations between WorldCom and GE were not as fruitful as such negotiations had been with the other Financing Companies. As a result, on November 17, 2003, WorldCom filed its Complaint in this Court and instituted the instant adversary proceeding against GE. In its Complaint,  WorldCom asserted that the Agreement was not a true lease but a disguised security arrangement, a position it had not previously taken with regard to  the other financing agreements. WorldCom petitioned this Court for a declaratory judgment to that effect, and asserted other claims under the Bankruptcy Code based on its contention that WorldCom's interest in the USL Equipment should be treated as a security interest. GE filed a Motion to Dismiss the Complaint pursuant to Fed.R.Civ.P. 12(b)(6) on December 30, 2003, arguing that judicial estoppel barred WorldCom from asserting that the Agreement was a disguised security arrangement. This Court denied GE's motion in an order dated May 17, 2004, as subsequently amended on July 29, 2004, which order was appealed to the District Court for the Southern District of New York. A hearing was held before the Honorable Barbara S. Jones on October 28, 2004. The district court thereafter denied GE's Motion for Leave to Appeal. As will be discussed shortly, GE has raised questions concerning the scope of this Court's July 29, 2004. Subsequently, the parties engaged in factual and expert discovery. Following the close of discovery, the parties filed the instant Motions for Summary Judgment, subsequently supplemented by multiple memoranda in opposition. This Court held a hearing on the parties' respective motions112031 Renew0.11VIII . </text> What is the correct answer to this question: When which of court view? Choices: (A). (B) court adopts. (C). (D) court ultimately ruled Word,. Format your response as follows: "The correct answer is (insert answer here)".
354
null
2
C
The key distinction between a security interest and a lease lies in whether the lessor retains the right to recover the leased asset.
Please read the following text and answer the question below. <text> In re Worldcom, Inc. RTHUR J. GONZALEZ, Bankruptcy Judge. I. Introduction Before this Court are the parties' June 20, 2005 Motions for Summary Judgment.  Both the Plaintiffs, WorldCom, Inc. and MCI WorldCom Network Services, Inc. (collectively, "WorldCom" or "Debtor"), and the Defendant General Electric Global Asset Management Services (collectively, including predecessors-in-interest, "GE") aver that no material issues of fact are in dispute, and further, that each is entitled as a matter of law to judgment in its favor on the matters set forward in WorldCom's Complaint for Declaratory Relief and for Recovery of Unauthorized Postpetition Transfers, filed on November 13, 2003 ("Complaint"). The instant motions concern the essential element of the Complaint, namely WorldCom's contention that the August 1, 1996 Equipment Leasing Agreement ("Agreement") between the parties should be recharacterized by this Court as a financing or security arrangement and treated accordingly under applicable provisions of the Bankruptcy Code. II. Jurisdiction This Court has subject matter jurisdiction over this adversary proceeding pursuant to section 1334(b) of title 28 of the United States Code and under the July 10, 1984 "Standing Order of Referral of Cases to Bankruptcy Judges" of the United States District Court for the Southern District of New York (Ward, Acting C.J.), as this matter arises under sections 549 and 550 of title 11 of the United States Code. This is a "core"  proceeding pursuant to section 157(b)(2)(A) of title 28 of the United States Code. This Court has postconfirmation jurisdiction under paragraph 32 of this Court's Order Confirming Debtors' Modified Second Amended Joint Plan of Reorganization under chapter 11 of title 11 of the United States Code (Oct. 31, 2003) ("Plan"). Hospital and University Property Damage Claimants v. Johns-Manville Corp. ( In re Johns-Manville Corp.), 7 F.3d 32, 34 (2nd Cir. 1993). III. Background The contractual relationship between GE's predecessor-in-interest USL Capital Corporation ("USL") and WorldCom at issue in the instant adversary proceeding emerged in connection with WorldCom's acquisition from Northern Telecoms, Inc. ("Nortel") of over $100 million worth of commercial telecommunications transmission equipment ("Nortel Equipment") in the spring of 1996 ("Nortel Purchase"). In order to finance the purchase of this equipment, WorldCom entered into eight similar "leases" (collectively, "Nortel Leases") with a total of seven companies (collectively, "Financing Companies"), including USL. In broad terms, these arrangements provided that the Financing Companies would first purchase the Nortel Equipment as assignees of WorldCom to the Nortel Purchase, and then lease that equipment to WorldCom for use in WorldCom's fiber optic telecommunications system. USL agreed to finance approximately $9.8 million worth of the Nortel Equipment ("USL Equipment"), and the Agreement reflects the arrangement the parties devised to accomplish this. In its relevant articles, the Agreement provided that the Basic Term of the lease would run for 84 months. WorldCom would pay monthly "rental" payments of $122,895.89 for the first forty-one months, $147,687.63 for months forty-two through  fifty-two, and $150,169.31 for the remaining months of the Basic Term, not including applicable sales taxes for which WorldCom was responsible. The Agreement thus contemplated that over the Basic Term of the lease, WorldCom would pay approximately $11.5 million in rental payments. Upon expiration of the Basic Term after 84 months, the Agreement provided that WorldCom could either: (1) renew the lease for an additional 12 month term at a monthly  rent of $135,518.09, for a total payment of $1,638,217.08 over the twelve month term ("Basic Term Renewal Option"); or (2) purchase the equipment for the greater of the fair-market value of the equipment or 5% of the total acquisition cost of the equipment ("Basic Term Purchase Option"). The Agreement further stated that in the absence of written notice from WorldCom expressing its intention to exercise the Basic Term Purchase Option, WorldCom would be presumed to have exercised the Renewal Option. If WorldCom exercised or was deemed to have exercised the Renewal Option, the Agreement provided that WorldCom could, at the end of the 12 month Renewal Term, either: (1) purchase the equipment for fair-market value ("Renewal Term Purchase Option"); or (2) return the equipment to USL and end the contractual relationship ("Renewal Term Return Option"). The Agreement originally provided that WorldCom had the additional option at the end of the Basic Term of returning the equipment to USL and thus completing the lease. However, a contemporaneously executed amendment withdrew that option. The Basic Term of the Agreement commenced on September 6, 1996 and was scheduled to end on September 6, 2003. However, in light of its crumbling financial position, WorldCom filed a voluntary petition for relief under Chapter 11 of the Bankruptcy Code in this Court on July 21, 2002 ("Petition Date"), before the expiration of the Basic Term of the Agreement. As of the Petition Date, WorldCom had not defaulted on the Agreement, but had made all monthly payments as required. Moreover,  it continued making such payments following its petition for bankruptcy for the period from August 2002 through July 2003, one month prior to the expiration of the Basic Term. Nonetheless, as part of its reorganization efforts, on April 30, 2003, WorldCom filed Notices of Rejection pursuant to 11 U.S.C. § 365(a) in regard to the leases with four of the Financing Companies: Key Corp. Leasing Ltd., AmSouth Leasing Corporation, JPMorgan Leasing, Inc., and CIT Lending Services Corporation. WorldCom then filed additional Notices of Rejection with two other Financing Companies: Citizens Leasing Corporation on May 4, 2003, and BTM Capital Corporation and Diamond Lease (USA), Inc. on June 6, 2003. Finally, on June 10, 2003, WorldCom filed a Notice of Rejection as to the Agreement with GE at issue here. A number of the Financing Companies, including GE, filed Objections to the Notices of Rejection on the grounds that WorldCom proposed to return only equipment of "like grade and quality," and not the specific equipment each company had leased to WorldCom. In response, WorldCom entered into negotiations with the Financing Companies concerning the Nortel Leases and future disposition of the Nortel Equipment. By July 10, 2003, WorldCom had reached settlement agreements with each of the Financing Companies except GE. Under these settlements, WorldCom agreed to purchase the leased equipment and satisfy any outstanding obligations arising from the lease agreements. For reasons not clear from the record, settlement negotiations between WorldCom and GE were not as fruitful as such negotiations had been with the other Financing Companies. As a result, on November 17, 2003, WorldCom filed its Complaint in this Court and instituted the instant adversary proceeding against GE. In its Complaint,  WorldCom asserted that the Agreement was not a true lease but a disguised security arrangement, a position it had not previously taken with regard to  the other financing agreements. WorldCom petitioned this Court for a declaratory judgment to that effect, and asserted other claims under the Bankruptcy Code based on its contention that WorldCom's interest in the USL Equipment should be treated as a security interest. GE filed a Motion to Dismiss the Complaint pursuant to Fed.R.Civ.P. 12(b)(6) on December 30, 2003, arguing that judicial estoppel barred WorldCom from asserting that the Agreement was a disguised security arrangement. This Court denied GE's motion in an order dated May 17, 2004, as subsequently amended on July 29, 2004, which order was appealed to the District Court for the Southern District of New York. A hearing was held before the Honorable Barbara S. Jones on October 28, 2004. The district court thereafter denied GE's Motion for Leave to Appeal. As will be discussed shortly, GE has raised questions concerning the scope of this Court's July 29, 2004. Subsequently, the parties engaged in factual and expert discovery. Following the close of discovery, the parties filed the instant Motions for Summary Judgment, subsequently supplemented by multiple memoranda in opposition. This Court held a hearing on the parties' respective motions112031 Renew0.11VIII . </text> What is the correct answer to this question: When which of court view? Choices: (A). (B) court adopts. (C). (D) court ultimately ruled Word,. Format your response as follows: "The correct answer is (insert answer here)".
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Please read the following text and answer the question below. <text> [ [ { "role": "user", "content": "Document: The 2006 Pangandaran earthquake and tsunami occurred on July 17 at along a subduction zone off the coast of west and central Java , a large and densely populated island in the Indonesian archipelago . The shock had a moment magnitude of 7.7 and a maximum perceived intensity of IV ( `` Light '' ) in Jakarta , the capital and largest city of Indonesia . There were no direct effects of the earthquake 's shaking due to its low intensity , and the large loss of life from the event was due to the resulting tsunami , which inundated a portion of the Java coast that had been unaffected by the earlier 2004 Indian Ocean earthquake and tsunami that was off the coast of Sumatra . The July 2006 earthquake was also centered in the Indian Ocean , from the coast of Java , and had a duration of more than three minutes . An abnormally slow rupture at the Sunda Trench and a tsunami that was unusually strong relative to the size of the earthquake were both factors that led to it being categorized as a tsunami earthquake . Several thousand kilometers to the southeast , surges of several meters were <event> observed </event> in northwestern Australia , but in Java the tsunami runups ( height above normal sea level ) were typically and resulted in the deaths of more than 600 people . Other factors may have contributed to exceptionally high peak runups of on the small and mostly uninhabited island of Nusa Kambangan , just to the east of the resort town of Pangandaran , where damage was heavy and a large loss of life occurred . since the shock was felt with only moderate intensity well inland , and even less so at the shore , the surge arrived with little or no warning . Other factors contributed to the tsunami being largely undetected until it was too late and , although a tsunami watch was posted by an American tsunami warning center and a Japanese meteorological center , no information was delivered to people at the coast .\n\nQuestion: Only considering the given document, what is the event type of observed?\n\nOptions: (A) afq\n(B) abx\n(C) afl\n(D) aem" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: The Battle of Santa Clara took place on 27 July 1927 , during the American occupation of Nicaragua of 1926\u20131933 . After being ambushed by Sandinista forces at the Battle of San Fernando , Major Oliver Floyd 's expedition of American Marines and Nicaraguan Provisional Guardsmen continued its advance into enemy-held territory in northern Nicaragua . On the 27 July two American airplanes spotted forty Sandinistas waiting in ambush . The aircraft <event> received </event> fire from an enemy machine gun and a dive bombing raid ensued , with three bombs being dropped on the Nicaraguan rebels . The American aviators reported seeing six Sandinistas `` dead or seriously wounded . '' Major Floyd 's Marine and Provisional Guard expedition eventually reached the area one mile southeast of Santa Clara , where they were attacked by a force of between 60 and 120 ( possibly up to 150 ) Sandinista insurgents who were armed with two machine guns . One of the machine guns was confirmed to be a Lewis gun and the other one was suspected of being one as well . The battle raged from 2:30 to 4:00 , with the Sandinistas being eventually driven back . The American and Nicaraguan government forces did n't suffer any casualties , while five dead rebels were found on the battlefield . However , Augusto C\u00e9sar Sandino would later admit to losing up to 60 men killed and wounded during the action ( although this number may include the casualties from the air raid prior to the battle ) . Sandino had a tendency to greatly exaggerate numbers related to the battles during his rebellion , so this number of 60 is probably inaccurate . One young Sandinista , who was pretending to be dead , was captured , but later released . In addition to human losses , twelve of Sandino 's animals were killed and eight were captured . The clash at Santa Clara , along with the previous battles at Ocotal and San Fernando ( both of which also took place in July 1927 ) convinced Sandino to alter his tactics . According to author Neill Macaulay , `` he would attack only when the odds were heavily in his favor-when he clearly had the advantages of surprise , cover , and superior firepower . Never again would he foolishly 'stand his ground , ' nor would he try to redeem an attack that had hopelessly bogged down . Major Floyd might wage a 'blood and thunder campaign , ' but Sandino would adopt the hit-and-run tactics of guerrilla warfare . '' After the Battle of Santa Clara , the Sandinistas fell back to `` the jungles around El Chipote mountain , '' which was `` ideal country for guerrilla warfare . ''\n\nQuestion: Only considering the given document, what is the event type of received?\n\nOptions: (A) abc\n(B) aeu\n(C) acx\n(D) abs" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: `` For other sieges with this name , see Siege of Pondicherry ( disambiguation ) '' The Siege of Pondicherry was a colonial military operation in the early stages of the French Revolutionary Wars . Britain and France both controlled colonies on the Indian Subcontinent and when the French National Convention <event> declared </event> war on Britain on 1 February 1793 , both sides were prepared for conflict in India . British India was centred on the principal ports of Bombay , Madras and Calcutta , administered by the East India Company . French India was governed from Pondicherry ( modern Puducherry ) on the Coromandel Coast . British forces in India were considerably stronger than the French , with the British Indian Army supported by British Army detachments and a Royal Navy squadron under Rear-Admiral William Cornwallis . Pondicherry 's defenses were strong , but the garrison was too small to effectively man the walls , and although a French frigate squadron was stationed at the distant \u00cele de France , it was unable to effectively protect the French Indian coast . News of the outbreak of war took five months to reach the Indian Ocean but British forces , recently engaged in the Third Anglo-Mysore War , were mobilised in preparation and immediately seized the ports of French India . Only Pondicherry was able to resist , and a siege was instigated on 1 August 1793 by Colonel John Braithwaite while Cornwallis imposed a naval blockade . British forces constructed trenches and batteries , often under heavy fire , over the following weeks . Twenty days after the city was cut off , Braithwaite began a bombardment of the defences . Within hours the French commander Colonel Prosper de Clermont requested a truce , followed the next morning by an unconditional surrender .\n\nQuestion: Only considering the given document, what is the event type of declared?\n\nOptions: (A) afk\n(B) ach\n(C) adl\n(D) add" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: The Battle of Leuthen was fought on 5 December 1757 , at which Frederick the Great 's Prussian army used maneuver and terrain to decisively defeat a much larger Austrian force commanded by Prince Charles of Lorraine and Count Leopold Joseph von Daun . The victory ensured Prussia control of Silesia during the Third Silesian War ( part of the Seven Years ' War ) . The battle was fought at the Silesian town of Leuthen , northwest of Breslau . By exploiting the training of his troops and his superior knowledge of the terrain , Frederick created a diversion at one end of the battlefield , and moved most of his small army behind a series of low hillocks . The surprise attack in oblique order on the unsuspecting Austrian flank baffled Prince Charles ; the Prince took several hours to realize that the main action was to his left , and not to his right . Within seven hours , the Prussians destroyed the Austrian force , erasing any advantage the Austrians had gained throughout the campaigning in the preceding summer and autumn . Within 48 hours , Frederick had laid siege to Breslau , which resulted in that city 's <event> surrender </event> on 19\u201320 December . Leuthen was the last battle at which Prince Charles commanded the Austrian Army , before his sister-in-law , Empress Maria Theresa , appointed him as governor of the Habsburg Netherlands and placed Leopold Joseph von Daun in command of the army . The battle also established beyond doubt Frederick 's military reputation in European circles ; it was arguably his: assistant "1 { assistant": "user assistant " Options { assistantcontent ] ] </text> What is correct answer to:12220n\nQuestion:, type? Choices: (A (B(C(D aaa Format your response as follows: "The correct answer is (insert answer here)".
355
null
0
A
agk
Please read the following text and answer the question below. <text> [ [ { "role": "user", "content": "Document: The 2006 Pangandaran earthquake and tsunami occurred on July 17 at along a subduction zone off the coast of west and central Java , a large and densely populated island in the Indonesian archipelago . The shock had a moment magnitude of 7.7 and a maximum perceived intensity of IV ( `` Light '' ) in Jakarta , the capital and largest city of Indonesia . There were no direct effects of the earthquake 's shaking due to its low intensity , and the large loss of life from the event was due to the resulting tsunami , which inundated a portion of the Java coast that had been unaffected by the earlier 2004 Indian Ocean earthquake and tsunami that was off the coast of Sumatra . The July 2006 earthquake was also centered in the Indian Ocean , from the coast of Java , and had a duration of more than three minutes . An abnormally slow rupture at the Sunda Trench and a tsunami that was unusually strong relative to the size of the earthquake were both factors that led to it being categorized as a tsunami earthquake . Several thousand kilometers to the southeast , surges of several meters were <event> observed </event> in northwestern Australia , but in Java the tsunami runups ( height above normal sea level ) were typically and resulted in the deaths of more than 600 people . Other factors may have contributed to exceptionally high peak runups of on the small and mostly uninhabited island of Nusa Kambangan , just to the east of the resort town of Pangandaran , where damage was heavy and a large loss of life occurred . since the shock was felt with only moderate intensity well inland , and even less so at the shore , the surge arrived with little or no warning . Other factors contributed to the tsunami being largely undetected until it was too late and , although a tsunami watch was posted by an American tsunami warning center and a Japanese meteorological center , no information was delivered to people at the coast .\n\nQuestion: Only considering the given document, what is the event type of observed?\n\nOptions: (A) afq\n(B) abx\n(C) afl\n(D) aem" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: The Battle of Santa Clara took place on 27 July 1927 , during the American occupation of Nicaragua of 1926\u20131933 . After being ambushed by Sandinista forces at the Battle of San Fernando , Major Oliver Floyd 's expedition of American Marines and Nicaraguan Provisional Guardsmen continued its advance into enemy-held territory in northern Nicaragua . On the 27 July two American airplanes spotted forty Sandinistas waiting in ambush . The aircraft <event> received </event> fire from an enemy machine gun and a dive bombing raid ensued , with three bombs being dropped on the Nicaraguan rebels . The American aviators reported seeing six Sandinistas `` dead or seriously wounded . '' Major Floyd 's Marine and Provisional Guard expedition eventually reached the area one mile southeast of Santa Clara , where they were attacked by a force of between 60 and 120 ( possibly up to 150 ) Sandinista insurgents who were armed with two machine guns . One of the machine guns was confirmed to be a Lewis gun and the other one was suspected of being one as well . The battle raged from 2:30 to 4:00 , with the Sandinistas being eventually driven back . The American and Nicaraguan government forces did n't suffer any casualties , while five dead rebels were found on the battlefield . However , Augusto C\u00e9sar Sandino would later admit to losing up to 60 men killed and wounded during the action ( although this number may include the casualties from the air raid prior to the battle ) . Sandino had a tendency to greatly exaggerate numbers related to the battles during his rebellion , so this number of 60 is probably inaccurate . One young Sandinista , who was pretending to be dead , was captured , but later released . In addition to human losses , twelve of Sandino 's animals were killed and eight were captured . The clash at Santa Clara , along with the previous battles at Ocotal and San Fernando ( both of which also took place in July 1927 ) convinced Sandino to alter his tactics . According to author Neill Macaulay , `` he would attack only when the odds were heavily in his favor-when he clearly had the advantages of surprise , cover , and superior firepower . Never again would he foolishly 'stand his ground , ' nor would he try to redeem an attack that had hopelessly bogged down . Major Floyd might wage a 'blood and thunder campaign , ' but Sandino would adopt the hit-and-run tactics of guerrilla warfare . '' After the Battle of Santa Clara , the Sandinistas fell back to `` the jungles around El Chipote mountain , '' which was `` ideal country for guerrilla warfare . ''\n\nQuestion: Only considering the given document, what is the event type of received?\n\nOptions: (A) abc\n(B) aeu\n(C) acx\n(D) abs" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: `` For other sieges with this name , see Siege of Pondicherry ( disambiguation ) '' The Siege of Pondicherry was a colonial military operation in the early stages of the French Revolutionary Wars . Britain and France both controlled colonies on the Indian Subcontinent and when the French National Convention <event> declared </event> war on Britain on 1 February 1793 , both sides were prepared for conflict in India . British India was centred on the principal ports of Bombay , Madras and Calcutta , administered by the East India Company . French India was governed from Pondicherry ( modern Puducherry ) on the Coromandel Coast . British forces in India were considerably stronger than the French , with the British Indian Army supported by British Army detachments and a Royal Navy squadron under Rear-Admiral William Cornwallis . Pondicherry 's defenses were strong , but the garrison was too small to effectively man the walls , and although a French frigate squadron was stationed at the distant \u00cele de France , it was unable to effectively protect the French Indian coast . News of the outbreak of war took five months to reach the Indian Ocean but British forces , recently engaged in the Third Anglo-Mysore War , were mobilised in preparation and immediately seized the ports of French India . Only Pondicherry was able to resist , and a siege was instigated on 1 August 1793 by Colonel John Braithwaite while Cornwallis imposed a naval blockade . British forces constructed trenches and batteries , often under heavy fire , over the following weeks . Twenty days after the city was cut off , Braithwaite began a bombardment of the defences . Within hours the French commander Colonel Prosper de Clermont requested a truce , followed the next morning by an unconditional surrender .\n\nQuestion: Only considering the given document, what is the event type of declared?\n\nOptions: (A) afk\n(B) ach\n(C) adl\n(D) add" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: The Battle of Leuthen was fought on 5 December 1757 , at which Frederick the Great 's Prussian army used maneuver and terrain to decisively defeat a much larger Austrian force commanded by Prince Charles of Lorraine and Count Leopold Joseph von Daun . The victory ensured Prussia control of Silesia during the Third Silesian War ( part of the Seven Years ' War ) . The battle was fought at the Silesian town of Leuthen , northwest of Breslau . By exploiting the training of his troops and his superior knowledge of the terrain , Frederick created a diversion at one end of the battlefield , and moved most of his small army behind a series of low hillocks . The surprise attack in oblique order on the unsuspecting Austrian flank baffled Prince Charles ; the Prince took several hours to realize that the main action was to his left , and not to his right . Within seven hours , the Prussians destroyed the Austrian force , erasing any advantage the Austrians had gained throughout the campaigning in the preceding summer and autumn . Within 48 hours , Frederick had laid siege to Breslau , which resulted in that city 's <event> surrender </event> on 19\u201320 December . Leuthen was the last battle at which Prince Charles commanded the Austrian Army , before his sister-in-law , Empress Maria Theresa , appointed him as governor of the Habsburg Netherlands and placed Leopold Joseph von Daun in command of the army . The battle also established beyond doubt Frederick 's military reputation in European circles ; it was arguably his: assistant "1 { assistant": "user assistant " Options { assistantcontent ] ] </text> What is correct answer to:12220n\nQuestion:, type? Choices: (A (B(C(D aaa Format your response as follows: "The correct answer is (insert answer here)".
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Please read the following text and answer the question below. <text> ABSTRACT Federal Reserve policy in the wake of the COVID pandemic has been widely criticized as responding too slowly to surging inflation and an overheated labor market, thereby exacerbating the inflation problem and impairing macroeconomic performance more generally. This paper challenges this view by exploring the likely effects of a markedly more restrictive counterfactual monetary policy starting in early 2021. Under this policy, the Federal Open Market Committee (FOMC) would have strictly followed the prescriptions of a benchmark policy rule with labor utilization gauged using the ratio of vacancies to unemployment, thereby causing the federal funds rate to rise faster and by much more than it actually did. In addition, consistent with the alternative rule-based strategy, the FOMC would have provided less accommodative forward guidance than what it implicitly provided over time, based on the post-COVID evolution of the economic projections made by FOMC participants and major financial institutions. Finally, the Fed would have ended its large-scale asset purchases earlier and begun shrinking its balance sheet sooner. Because of uncertainty about inflation dynamics, simulations of the effects of the counterfactual policy are run using different specifications of the Phillips curve drawn from recent studies, with each in turn embedded in a large-scale model of the US economy that provides a detailed treatment of the monetary transmission mechanism. Using a range of assumptions for expectations formation and the interest sensitivity of aggregate spending, the various model simulations suggest that a more restrictive strategy on the part of the FOMC would have done little to check inflation in 2021 and 2022, although it probably would have sped its return to 2 percent thereafter. Because the modest reductions in inflation suggested by these simulations would have come at a cost of higher unemployment and lower real wages, the net social benefit of a more restrictive policy response on the part of the FOMC seems doubtful; the paper also questions the wisdom of a more rapid and pronounced tightening on risk-management grounds. David Reifschneider, now retired from the Federal Reserve Board, held various positions in its Division of Research and Statistics from 1982 to 2013 and was special advisor to Chair Janet Yellen from 2014 to 2018. 2  WP 24-13 | MAY 2024 JEL Codes: E17, E37, E58 Keywords: Inflation, monetary policy Note: This Working Paper is part of a series titled Understanding COVID Era Inflation. PIIE gratefully acknowledges the financial support from a donor who wishes to remain anonymous for the research presented in this Working Paper. The research was conducted independently. Funders are never given the right to final review of a publication before its release. This paper has greatly benefited from the comments of Josh Bivens, Karen Dynan, William English, Joseph Gagnon, Mark Gertler, Michael Kiley, Matthew Luzzetti, Peter Hooper, and David Wilcox. All errors and opinions are the author’s own. Page | 1 1. Introduction Federal Reserve monetary policy has been widely criticized in recent years. For example, reacting to guidance from the Federal Open Market Committee (FOMC), the Fed’s policymaking group, that the federal funds rate was likely to remain near zero for some time to come despite the enactment of several major fiscal packages, Lawrence Summers warned in the spring of 2021 that the FOMC had “underestimated the risks, very substantially, both to financial stability as well as to conventional inflation of protracted extremely low interest rates.”1 This early warning received widespread attention, as did his reaction later in the year to the Fed’s initially sanguine assessment of a string of elevated monthly price increases: “It’s past time for team ‘transitory’ to step down.”2 As the FOMC continued to hold the federal funds rate near zero into early 2022 despite headline PCE inflation as measured by the personal consumption expenditures (PCE) index surging to around 7 percent, Summers was joined by a number of other prominent economists, including Jason Furman, Michael Bordo, Mickey Levy, John Taylor, and John Cochrane.3 In their view, the Fed was moving far too slowly and fueling what was becoming, or even in some eyes had already become, a chronic inflation problem. In the wider world, a headline in The Economist expressed what may have been a common view at the time: “The Federal Reserve has made a historic mistake on inflation.”4 Against this criticism, one might defend the Fed’s delayed tightening by noting the difficulty of gauging in real time the persistence of the upward surprises to prices, the actual tightness of the labor market, and the prospects for future growth; in addition, a slow-to-tighten strategy could be seen as appropriate given the stimulative forward guidance provided by the FOMC in 2020 in order to mitigate the adverse consequences of the effective lower bound (ELB) on nominal interest rates.5 Certainly, most outside observers at the time shared the FOMC’s expectation that inflation was likely to fall back to 2 percent quickly without a need for a marked tightening in monetary policy. In June 2021, for example, after several months of elevated price increases and the recent passage of a yet another major fiscal package, major financial institutions and private forecasters, like the FOMC, anticipated that headline PCE inflation would run close to 2 percent in 2022 accompanied by only a modest tightening of monetary policy—an expectation that was 1 “Armchair Discussion with Larry Summers and Dave Altig,” remarks at a conference held on May 17-18, 2021, Fostering a Resilient Economy and Financial System: The Role of Banks, at the Center for Financial Innovation and Stability, Federal Reserve Bank of Atlanta, Atlanta. Available at www.atlantafed.org/news/conferences-and- events/conferences/2021/05/17/financial-markets-conference. 2 Lawrence H. Summers, “It’s Past Time for Team Transitory to Step Down,” November 16, 2021, larrysummers.com/2021/11/16/on-inflation-its-past-time-for-team-transitory-to-stand-down/. 3 See Jason Furman, “This Inflation Is Demand-Driven and Persistent,” Project Syndicate (April 20, 2022), www.project-syndicate.org/commentary/inflation-demand-driven-persistent-by-jason-furman-2022- 04?barrier=accesspaylog and “America’s Wage-Price Persistence Must Be Stopped,” Project Syndicate (August 2, 2022), www.project-syndicate.org/commentary/inflation-wage-price-spiral-requires-fed-tightening-by-jason- furman-2022-08?barrier=accesspaylog; and the papers presented by Bordo and Levy (2023), Taylor (2023), and Cochrane (2023) at a conference sponsored by the Hoover Institution in May 2022. 4 The Economist, “Why the Federal Reserve Has Made a Historic Mistake on Inflation,” April 23, 2022, www.economist.com/leaders/2022/04/23/why-the-federal-reserve-has-made-a-historic-mistake-on-inflation. 5 Federal Reserve Board governor Waller made these points in a speech given at the May 2022 Hoover Institution conference, www.federalreserve.gov/newsevents/speech/waller20220506a.htm. With regard to the FOMC’s slow- to-tighten forward guidance, one difficulty with using this tool is that its effectiveness in future ELB episodes will be greatly impaired if policymakers come to be seen as likely to quickly jettison this guidance when conditions begin to improve. Page | 2 largely unchanged at the end of the year.6 As for households, their expectations for inflation over the next five years were about the same in mid-2021 as they had been at the start of the year and by year’s end had still barely risen.7 Fed policy changed course starting in the spring of 2022. In an effort to rein in inflation that had proved to be more persistent than expected, and in the face of what appeared to be quite tight labor conditions, the FOMC carried out an extended sequence of unusually large rate hikes that raised the federal funds rate by more than 502ura2/11�00fl11 1122111222inIC11</text> What is the correct answer to this question: Which of the following statements is most aligned with the combined findings Bern (024) and Re (04), considering the complexities? Choices: (A). align Bern Reif. (B)sch. (C). (D)ifsch,, as. Format your response as follows: "The correct answer is (insert answer here)".
356
null
0
A
Central banks should adopt a dual approach, where they maintain an accommodative stance in response to supply-side shocks while simultaneously implementing aggressive tightening in response to tight labor markets. This balanced policy would ensure that short-term inflation spikes are managed without risking long-term inflation expectations, aligning with Bernanke and Blanchard’s view of temporary shocks and Reifschneider’s emphasis on the urgency of addressing labor market pressures.
Please read the following text and answer the question below. <text> ABSTRACT Federal Reserve policy in the wake of the COVID pandemic has been widely criticized as responding too slowly to surging inflation and an overheated labor market, thereby exacerbating the inflation problem and impairing macroeconomic performance more generally. This paper challenges this view by exploring the likely effects of a markedly more restrictive counterfactual monetary policy starting in early 2021. Under this policy, the Federal Open Market Committee (FOMC) would have strictly followed the prescriptions of a benchmark policy rule with labor utilization gauged using the ratio of vacancies to unemployment, thereby causing the federal funds rate to rise faster and by much more than it actually did. In addition, consistent with the alternative rule-based strategy, the FOMC would have provided less accommodative forward guidance than what it implicitly provided over time, based on the post-COVID evolution of the economic projections made by FOMC participants and major financial institutions. Finally, the Fed would have ended its large-scale asset purchases earlier and begun shrinking its balance sheet sooner. Because of uncertainty about inflation dynamics, simulations of the effects of the counterfactual policy are run using different specifications of the Phillips curve drawn from recent studies, with each in turn embedded in a large-scale model of the US economy that provides a detailed treatment of the monetary transmission mechanism. Using a range of assumptions for expectations formation and the interest sensitivity of aggregate spending, the various model simulations suggest that a more restrictive strategy on the part of the FOMC would have done little to check inflation in 2021 and 2022, although it probably would have sped its return to 2 percent thereafter. Because the modest reductions in inflation suggested by these simulations would have come at a cost of higher unemployment and lower real wages, the net social benefit of a more restrictive policy response on the part of the FOMC seems doubtful; the paper also questions the wisdom of a more rapid and pronounced tightening on risk-management grounds. David Reifschneider, now retired from the Federal Reserve Board, held various positions in its Division of Research and Statistics from 1982 to 2013 and was special advisor to Chair Janet Yellen from 2014 to 2018. 2  WP 24-13 | MAY 2024 JEL Codes: E17, E37, E58 Keywords: Inflation, monetary policy Note: This Working Paper is part of a series titled Understanding COVID Era Inflation. PIIE gratefully acknowledges the financial support from a donor who wishes to remain anonymous for the research presented in this Working Paper. The research was conducted independently. Funders are never given the right to final review of a publication before its release. This paper has greatly benefited from the comments of Josh Bivens, Karen Dynan, William English, Joseph Gagnon, Mark Gertler, Michael Kiley, Matthew Luzzetti, Peter Hooper, and David Wilcox. All errors and opinions are the author’s own. Page | 1 1. Introduction Federal Reserve monetary policy has been widely criticized in recent years. For example, reacting to guidance from the Federal Open Market Committee (FOMC), the Fed’s policymaking group, that the federal funds rate was likely to remain near zero for some time to come despite the enactment of several major fiscal packages, Lawrence Summers warned in the spring of 2021 that the FOMC had “underestimated the risks, very substantially, both to financial stability as well as to conventional inflation of protracted extremely low interest rates.”1 This early warning received widespread attention, as did his reaction later in the year to the Fed’s initially sanguine assessment of a string of elevated monthly price increases: “It’s past time for team ‘transitory’ to step down.”2 As the FOMC continued to hold the federal funds rate near zero into early 2022 despite headline PCE inflation as measured by the personal consumption expenditures (PCE) index surging to around 7 percent, Summers was joined by a number of other prominent economists, including Jason Furman, Michael Bordo, Mickey Levy, John Taylor, and John Cochrane.3 In their view, the Fed was moving far too slowly and fueling what was becoming, or even in some eyes had already become, a chronic inflation problem. In the wider world, a headline in The Economist expressed what may have been a common view at the time: “The Federal Reserve has made a historic mistake on inflation.”4 Against this criticism, one might defend the Fed’s delayed tightening by noting the difficulty of gauging in real time the persistence of the upward surprises to prices, the actual tightness of the labor market, and the prospects for future growth; in addition, a slow-to-tighten strategy could be seen as appropriate given the stimulative forward guidance provided by the FOMC in 2020 in order to mitigate the adverse consequences of the effective lower bound (ELB) on nominal interest rates.5 Certainly, most outside observers at the time shared the FOMC’s expectation that inflation was likely to fall back to 2 percent quickly without a need for a marked tightening in monetary policy. In June 2021, for example, after several months of elevated price increases and the recent passage of a yet another major fiscal package, major financial institutions and private forecasters, like the FOMC, anticipated that headline PCE inflation would run close to 2 percent in 2022 accompanied by only a modest tightening of monetary policy—an expectation that was 1 “Armchair Discussion with Larry Summers and Dave Altig,” remarks at a conference held on May 17-18, 2021, Fostering a Resilient Economy and Financial System: The Role of Banks, at the Center for Financial Innovation and Stability, Federal Reserve Bank of Atlanta, Atlanta. Available at www.atlantafed.org/news/conferences-and- events/conferences/2021/05/17/financial-markets-conference. 2 Lawrence H. Summers, “It’s Past Time for Team Transitory to Step Down,” November 16, 2021, larrysummers.com/2021/11/16/on-inflation-its-past-time-for-team-transitory-to-stand-down/. 3 See Jason Furman, “This Inflation Is Demand-Driven and Persistent,” Project Syndicate (April 20, 2022), www.project-syndicate.org/commentary/inflation-demand-driven-persistent-by-jason-furman-2022- 04?barrier=accesspaylog and “America’s Wage-Price Persistence Must Be Stopped,” Project Syndicate (August 2, 2022), www.project-syndicate.org/commentary/inflation-wage-price-spiral-requires-fed-tightening-by-jason- furman-2022-08?barrier=accesspaylog; and the papers presented by Bordo and Levy (2023), Taylor (2023), and Cochrane (2023) at a conference sponsored by the Hoover Institution in May 2022. 4 The Economist, “Why the Federal Reserve Has Made a Historic Mistake on Inflation,” April 23, 2022, www.economist.com/leaders/2022/04/23/why-the-federal-reserve-has-made-a-historic-mistake-on-inflation. 5 Federal Reserve Board governor Waller made these points in a speech given at the May 2022 Hoover Institution conference, www.federalreserve.gov/newsevents/speech/waller20220506a.htm. With regard to the FOMC’s slow- to-tighten forward guidance, one difficulty with using this tool is that its effectiveness in future ELB episodes will be greatly impaired if policymakers come to be seen as likely to quickly jettison this guidance when conditions begin to improve. Page | 2 largely unchanged at the end of the year.6 As for households, their expectations for inflation over the next five years were about the same in mid-2021 as they had been at the start of the year and by year’s end had still barely risen.7 Fed policy changed course starting in the spring of 2022. In an effort to rein in inflation that had proved to be more persistent than expected, and in the face of what appeared to be quite tight labor conditions, the FOMC carried out an extended sequence of unusually large rate hikes that raised the federal funds rate by more than 502ura2/11�00fl11 1122111222inIC11</text> What is the correct answer to this question: Which of the following statements is most aligned with the combined findings Bern (024) and Re (04), considering the complexities? Choices: (A). align Bern Reif. (B)sch. (C). (D)ifsch,, as. Format your response as follows: "The correct answer is (insert answer here)".
null
null
null
1,788,795
null
357
length>350000
2
C
Chimeric=pd.read_csv(“chimeric.tsv”, sep=”\t”) ->matrix= chimeric.groupby(["chimeric_events", "samples"]).counts.first().unstack()
Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> Android in the Wild: A Large-Scale Dataset for Android Device Control Christopher Rawles∗ Google Research Alice Li∗ Google Research Daniel Rodriguez Google Research Oriana Riva Google Research Timothy Lillicrap Google DeepMind Abstract There is a growing interest in device-control systems that can interpret human natural language instructions and execute them on a digital device by directly con- trolling its user interface. We present a dataset for device-control research, Android in the Wild (AITW), which is orders of magnitude larger than current datasets. The dataset contains human demonstrations of device interactions, including the screens and actions, and corresponding natural language instructions. It consists of 715k episodes spanning 30k unique instructions, four versions of Android (v10–13), and eight device types (Pixel 2 XL to Pixel 6) with varying screen resolutions. It contains multi-step tasks that require semantic understanding of language and visual context. This dataset poses a new challenge: actions available through the user interface must be inferred from their visual appearance, and, instead of simple UI element-based actions, the action space consists of precise gestures (e.g., hori- zontal scrolls to operate carousel widgets). We organize our dataset to encourage robustness analysis of device-control systems, i.e., how well a system performs in the presence of new task descriptions, new applications, or new platform versions. We develop two agents and report performance across the dataset. The dataset is available at https://github.com/google-research/google-research/ tree/master/android_in_the_wild. 1 Introduction Users complete tasks on mobile devices via a sequence of touches and gestures on the screen. Tasks can often be succinctly described using natural language commands, and, in many situations, it is valuable to be able to speak or type commands rather than interacting directly with the device. This has important implications for users who are unable to physically operate a device due to a physical (e.g., visual or motor disabilities) or situational (e.g., driving, cooking, etc.) impairment. It is therefore beneficial to build device-control systems that can interpret natural language instructions and execute them on a device without any manual intervention. Instead of using application-specific APIs, which are not generally available for any given application or function, these systems directly manipulate user interface (UI) elements on a screen, exactly as a human does [1, 28, 29, 35, 21]. Hence, to work correctly, it is essential for such systems to understand the screen, which usually means detecting position and inferring semantics of its UI elements. Device-control systems must also be able to map high-level commands to execution plans that can be carried out on the device. For example, understanding that the command “open my recent email with Jane” involves opening an email app, potentially tapping the search icon, typing "Jane", etc. Further, to be useful, they must be able to generalize across a variety of task instructions and UIs. ∗Equal contribution. Contact: crawles@google.com and lialice@google.com 37th Conference on Neural Information Processing Systems (NeurIPS 2023) Track on Datasets and Benchmarks. arXiv:2307.10088v2 [cs.LG] 27 Oct 2023 Human executes task on a mobile emulator 15K multi-step prompts Sample from instruction database episodes 26K hindsight relabeled 689K multi-step demos Human selects frames and annotates them “Open calendar and show me the second week of next month” 1. “show week view” 2.“switch to week view” … for each action: extract preceding screenshot and pixel-based screen features {'action_type': 'dual-point-gesture', 'touch_point': (0.28,0.19), 'lift_point': (0.28,0.19), 'typed_text': None} + Demonstration processing + + + + {'action_type': 'dual-point gesture', 'touch_point': (0.90,0.41), 'lift_point': (0.05,0.35), 'typed_text': None} + + OCR text & icons OCR text & icons Figure 1: AITW data pipeline. Raters are given a randomly selected instruction. The raters execute the task by interacting with the device in a natural way. We capture precise gestures in addition to typing and the home and back button interactions (we plot swipes with the arrow pointing where the finger moves to). Hindsight relabeling of high-level episodes is used to generate single-step tasks. The rapid development of general-purpose large foundation models (LLMs) [8, 6, 13] makes device- control systems more viable. Yet, there is a lack of datasets for training, fine-tuning, and evaluating these systems. Existing datasets [28, 9, 42, 37, 4] are limited in terms of number of human demon- strations and the diversity of task instructions, and they are platform specific (either Android or web). They also assume a tree-based representation of an application UI can be derived from platform- specific UI metadata (e.g., the View Hierarchy for Android and the DOM tree for the web). This assumption simplifies the problem, but limits the resulting systems to work in environments where high-quality UI metadata is available2. Finally, some popular datasets (e.g., MiniWoB++ dataset [29] and UIBert [4]) assume task instructions are specified as step-by-step commands referring to specific UI elements appearing on the screen (“Click the button in the dialog box labeled Cancel”), while users may use short commands that describe high-level goals (e.g., “turn on airplane mode”) or pose questions (e.g., “Is it going to rain tomorrow?”) To drive research in this field, we release AITW (Figure 1), an Android device-control dataset which is orders of magnitude larger than existing datasets. It consists of 715k episodes spanning 30k unique task instructions collected across hundreds of Android apps and websites. Each episode consists of a goal instruction provided in natural language and a sequence of observation-action pairs describing the execution of the task. Observations consist of screenshots of the application UI. Gesture actions are represented as taps and drags at arbitrary <x,y> coordinates in the screen. Agents trained on this dataset can be evaluated using AndroidEnv [40], an open-source platform for developing and testing Android agents with the Android Emulator3. A key feature of our dataset is the diversity of task instructions and execution paths we collected, aimed to emulate real-world scenarios. We used multiple sources to collect high-level goal instruc- 2Since most users do not use UI metadata for interactions it tends to be poor quality or missing altogether. On Android, only applications registered as Accessibility tools can access the View Hierarchy [45]. On Windows, in many cases (e.g., Electron apps like Teams), UI trees are not easily accessible. Moreover, screen representations derived from UI metadata can be incomplete. On Android, WebViews and Canvas are not captured in the View Hierarchy, and many websites render directly to a Canvas, which does not contain any tree structure. 3https://developer.android.com/studio/run/emulator 2 Dataset Platform # Human # Apps or # Task Observation Screen Real High-level demos websites steps format features instruction RicoSCA [28] Android (apps) 0 n/a 1.0 VH, screen x x x UIBert [4] Android (apps) 16,660 n/a 1.0 VH, screen x ✓ x MiniWoB++ [37, 29] synthetic web 17,971 100 2.3 DOM, screen x x x PixelHelp [28] Android (apps) 187 4 4.2 VH, screen x ✓ ✓ UGIF [42] Android (apps) 523 12 5.3 VH, screen x ✓ ✓ Mind2Web [14] web 2,350 137 7.3 DOM, screen x ✓ ✓ MoTIF [9] Android (apps) 4,707 125 4.5 VH, screen x ✓ ✓ AITW Android (apps+web) 715,142 357+ 6.5 screen ✓ ✓ ✓ Table 1: Comparison of AITW to existing datasets. We consider platform, format of screen obser- vations, presence of synthetic UIs or synthetic instructions (“Real”), and whether instructions are expressed as goals (high-level). For size comparison, we report the number22"WTable1WXXylos424 > What is the correct answer to this question: The main differences and improvements between and are Choices: (A) (B (C) (D) Android Format your response as follows: "The correct answer is (insert answer here)".
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Android World provides an interactive testing environment that allows models to be tested during the exploration process
Please read the following text and answer the question below. <text> Android in the Wild: A Large-Scale Dataset for Android Device Control Christopher Rawles∗ Google Research Alice Li∗ Google Research Daniel Rodriguez Google Research Oriana Riva Google Research Timothy Lillicrap Google DeepMind Abstract There is a growing interest in device-control systems that can interpret human natural language instructions and execute them on a digital device by directly con- trolling its user interface. We present a dataset for device-control research, Android in the Wild (AITW), which is orders of magnitude larger than current datasets. The dataset contains human demonstrations of device interactions, including the screens and actions, and corresponding natural language instructions. It consists of 715k episodes spanning 30k unique instructions, four versions of Android (v10–13), and eight device types (Pixel 2 XL to Pixel 6) with varying screen resolutions. It contains multi-step tasks that require semantic understanding of language and visual context. This dataset poses a new challenge: actions available through the user interface must be inferred from their visual appearance, and, instead of simple UI element-based actions, the action space consists of precise gestures (e.g., hori- zontal scrolls to operate carousel widgets). We organize our dataset to encourage robustness analysis of device-control systems, i.e., how well a system performs in the presence of new task descriptions, new applications, or new platform versions. We develop two agents and report performance across the dataset. The dataset is available at https://github.com/google-research/google-research/ tree/master/android_in_the_wild. 1 Introduction Users complete tasks on mobile devices via a sequence of touches and gestures on the screen. Tasks can often be succinctly described using natural language commands, and, in many situations, it is valuable to be able to speak or type commands rather than interacting directly with the device. This has important implications for users who are unable to physically operate a device due to a physical (e.g., visual or motor disabilities) or situational (e.g., driving, cooking, etc.) impairment. It is therefore beneficial to build device-control systems that can interpret natural language instructions and execute them on a device without any manual intervention. Instead of using application-specific APIs, which are not generally available for any given application or function, these systems directly manipulate user interface (UI) elements on a screen, exactly as a human does [1, 28, 29, 35, 21]. Hence, to work correctly, it is essential for such systems to understand the screen, which usually means detecting position and inferring semantics of its UI elements. Device-control systems must also be able to map high-level commands to execution plans that can be carried out on the device. For example, understanding that the command “open my recent email with Jane” involves opening an email app, potentially tapping the search icon, typing "Jane", etc. Further, to be useful, they must be able to generalize across a variety of task instructions and UIs. ∗Equal contribution. Contact: crawles@google.com and lialice@google.com 37th Conference on Neural Information Processing Systems (NeurIPS 2023) Track on Datasets and Benchmarks. arXiv:2307.10088v2 [cs.LG] 27 Oct 2023 Human executes task on a mobile emulator 15K multi-step prompts Sample from instruction database episodes 26K hindsight relabeled 689K multi-step demos Human selects frames and annotates them “Open calendar and show me the second week of next month” 1. “show week view” 2.“switch to week view” … for each action: extract preceding screenshot and pixel-based screen features {'action_type': 'dual-point-gesture', 'touch_point': (0.28,0.19), 'lift_point': (0.28,0.19), 'typed_text': None} + Demonstration processing + + + + {'action_type': 'dual-point gesture', 'touch_point': (0.90,0.41), 'lift_point': (0.05,0.35), 'typed_text': None} + + OCR text & icons OCR text & icons Figure 1: AITW data pipeline. Raters are given a randomly selected instruction. The raters execute the task by interacting with the device in a natural way. We capture precise gestures in addition to typing and the home and back button interactions (we plot swipes with the arrow pointing where the finger moves to). Hindsight relabeling of high-level episodes is used to generate single-step tasks. The rapid development of general-purpose large foundation models (LLMs) [8, 6, 13] makes device- control systems more viable. Yet, there is a lack of datasets for training, fine-tuning, and evaluating these systems. Existing datasets [28, 9, 42, 37, 4] are limited in terms of number of human demon- strations and the diversity of task instructions, and they are platform specific (either Android or web). They also assume a tree-based representation of an application UI can be derived from platform- specific UI metadata (e.g., the View Hierarchy for Android and the DOM tree for the web). This assumption simplifies the problem, but limits the resulting systems to work in environments where high-quality UI metadata is available2. Finally, some popular datasets (e.g., MiniWoB++ dataset [29] and UIBert [4]) assume task instructions are specified as step-by-step commands referring to specific UI elements appearing on the screen (“Click the button in the dialog box labeled Cancel”), while users may use short commands that describe high-level goals (e.g., “turn on airplane mode”) or pose questions (e.g., “Is it going to rain tomorrow?”) To drive research in this field, we release AITW (Figure 1), an Android device-control dataset which is orders of magnitude larger than existing datasets. It consists of 715k episodes spanning 30k unique task instructions collected across hundreds of Android apps and websites. Each episode consists of a goal instruction provided in natural language and a sequence of observation-action pairs describing the execution of the task. Observations consist of screenshots of the application UI. Gesture actions are represented as taps and drags at arbitrary <x,y> coordinates in the screen. Agents trained on this dataset can be evaluated using AndroidEnv [40], an open-source platform for developing and testing Android agents with the Android Emulator3. A key feature of our dataset is the diversity of task instructions and execution paths we collected, aimed to emulate real-world scenarios. We used multiple sources to collect high-level goal instruc- 2Since most users do not use UI metadata for interactions it tends to be poor quality or missing altogether. On Android, only applications registered as Accessibility tools can access the View Hierarchy [45]. On Windows, in many cases (e.g., Electron apps like Teams), UI trees are not easily accessible. Moreover, screen representations derived from UI metadata can be incomplete. On Android, WebViews and Canvas are not captured in the View Hierarchy, and many websites render directly to a Canvas, which does not contain any tree structure. 3https://developer.android.com/studio/run/emulator 2 Dataset Platform # Human # Apps or # Task Observation Screen Real High-level demos websites steps format features instruction RicoSCA [28] Android (apps) 0 n/a 1.0 VH, screen x x x UIBert [4] Android (apps) 16,660 n/a 1.0 VH, screen x ✓ x MiniWoB++ [37, 29] synthetic web 17,971 100 2.3 DOM, screen x x x PixelHelp [28] Android (apps) 187 4 4.2 VH, screen x ✓ ✓ UGIF [42] Android (apps) 523 12 5.3 VH, screen x ✓ ✓ Mind2Web [14] web 2,350 137 7.3 DOM, screen x ✓ ✓ MoTIF [9] Android (apps) 4,707 125 4.5 VH, screen x ✓ ✓ AITW Android (apps+web) 715,142 357+ 6.5 screen ✓ ✓ ✓ Table 1: Comparison of AITW to existing datasets. We consider platform, format of screen obser- vations, presence of synthetic UIs or synthetic instructions (“Real”), and whether instructions are expressed as goals (high-level). For size comparison, we report the number22"WTable1WXXylos424 > What is the correct answer to this question: The main differences and improvements between and are Choices: (A) (B (C) (D) Android Format your response as follows: "The correct answer is (insert answer here)". Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> [ [ { "role": "user", "content": "Document: Although his stepfather later divorced his mother , Berryman and his stepfather stayed on good terms . \n\nQuestion: Only considering the given document, what is the entity type of Berryman?\n\nOptions: (A) aav\n(B) aae\n(C) aaf\n(D) acb" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: It starred Hicks 's wife , Ellaline Terriss and Edmund Payne . \n\nQuestion: Only considering the given document, what is the entity type of Hicks?\n\nOptions: (A) aab\n(B) abb\n(C) aae\n(D) aav" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: James McConnell `` Mac '' Anderson ( August 9 , 1907 in New Orleans \u2013 April 3 , 1998 in Jackson County , Mississippi ) was an American painter , muralist , and pottery designer and decorator , youngest of the three brothers ( along with Walter Inglis Anderson and founder Peter Anderson ) who collaborated at Shearwater Pottery , Ocean Springs , Mississippi . \n\nQuestion: Only considering the given document, what is the entity type of James McConnell `` Mac '' Anderson?\n\nOptions: (A) aaz\n(B) aav\n(C) acb\n(D) aag" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: In 1916 , Falla arranged a rendition of the work for sextet and small orchestra and the following year he made a concert version , also for small orchestra . \n\nQuestion: Only considering the given document, what is the entity type of Falla?\n\nOptions: (A) acf\n(B) aaz\n(C) aav\n(D) abm" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: Calvin Goldspink , Aaron Renfree , Hannah Richings and Jay Asforis do not have any solos in this song . \n\nQuestion: Only considering the given document, what is the entity type of Calvin Goldspink?\n\nOptions: (A) acd\n(B) aav\n(C) aaz\n(D) aay" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: Lead guitar was not played by Ace Frehley as he was not musically involved with the album and it was not played by Vinnie Vincent either ; it was played by Steve Farris , who would go on to be the lead guitarist of the 1980s pop rock group Mr. Mister . \n\nQuestion: Only considering the given document, what is the entity type of Ace Frehley?\n\nOptions: (A) abb\n(B) aca\n(C) aap\n(D) aav" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: Herodotus , in his `` Histories `` , Book II , gives a detailed if selectively coloured and imaginative description of ancient Egypt . \n\nQuestion: Only considering the given document, what is the entity type of Herodotus?\n\nOptions: (A) abi\n(B) aav\n(C) abs\n(D) aao" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: The film became the only international version of Tolstoy 's `` Anna Karenina `` filmed entirely in Russia , at locations in Saint Petersburg and Moscow . \n\nQuestion: Only considering the given document, what is the entity type of Tolstoy?\n\nOptions: (A) ach\n(B) abr\n(C) aav\n(D) acf" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: On 29 May 2017 , Horan performed on The Today Show 's Citi Concert Series , closing the show with a live TV debut of `` On the Loose `` . \n\nQuestion: Only considering the given document, what is the entity type of Horan?\n\nOptions: (A) aaw\n(B) aaz\n(C) abq\n(D) aav" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: On the surface , the novel presents a post-apocalyptic adventure tale entitled `` Lord of the Swastika `` , written by an alternate-history Adolf Hitler shortly before his death in 1953 . \n\nQuestion: Only considering the given document, what is the entity type of Adolf Hitler?\n\nOptions: (A) aav\n(B) abt\n(C) aby\n(D) acn" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: The score to `` Spring Breakdown '' was composed by Deborah Lurie who recorded her score with the Hollywood Studio Symphony conducted by Blake Neely and recorded by Greg Dennen at the Eastwood Scoring Stage at Warner Brothers . \n\nQuestion: Only considering the given document, what is the entity type of Deborah Lurie?\n\nOptions: (A) aav\n(B) abx\n(C) abq\n(D) aby" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: However , Buddah head Neil Bogart liked the demo enough that he released the record `` as is '' , with Levine 's vocals intact and no input at all from the touring version of the Ohio Express . \n\nQuestion: Only considering the given document, what is the entity type of Neil Bogart?\n\nOptions: (A) aat\n(B) aav\n(C) aba\n(D) acl" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: He was a brother of Moravian leader and musical composer Christian Ignatius Latrobe . \n\nQuestion: Only considering the given document, what is the entity type of Christian Ignatius Latrobe?\n\nOptions: (A) acl\n(B) abj\n(C) aca\n(D) aav" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: John Meyer started his career in 1967 working in a Berkeley hi-fi store doing custom installs . \n\nQuestion: Only considering the given document, what is the entity type of John Meyer?\n\nOptions: (A) aaz\n(B) aav\n(C) abh\n(D) abg" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: Co-developer Glenn Howerton described the show as `` essentially an expanded version of the actual episode of `` The Nightman Cometh , `` which was the final episode for season four . \n\nQuestion: Only considering the given document, what is the entity type of Glenn Howerton?\n\nOptions: (A) aas\n(B) abn\n(C) ace\n(D) aav" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: In 1964 , producer Stanley Todd discussed a film project with Lansing , tentatively titled `` Project 22 `` , with location shooting planned in Yugoslavia , and George Hamilton and Geraldine Chaplin named to the cast . \n\nQuestion: Only considering the given document, what is the entity type of Stanley Todd?\n\nOptions: (A) ack\n(B) aav\n(C) abo\n(D) abu" }, { "": { A" role playersrole0 ": ", ", assistant "", ", ":" { assistant": " "1assistant "":":":assistant ] ] text> What correct answer to \n\nQuestion what type? Choices: (A) ab (B) (C (Dg Format your response as follows: "The correct answer is (insert answer here)".
359
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aaz
Please read the following text and answer the question below. <text> [ [ { "role": "user", "content": "Document: Although his stepfather later divorced his mother , Berryman and his stepfather stayed on good terms . \n\nQuestion: Only considering the given document, what is the entity type of Berryman?\n\nOptions: (A) aav\n(B) aae\n(C) aaf\n(D) acb" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: It starred Hicks 's wife , Ellaline Terriss and Edmund Payne . \n\nQuestion: Only considering the given document, what is the entity type of Hicks?\n\nOptions: (A) aab\n(B) abb\n(C) aae\n(D) aav" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: James McConnell `` Mac '' Anderson ( August 9 , 1907 in New Orleans \u2013 April 3 , 1998 in Jackson County , Mississippi ) was an American painter , muralist , and pottery designer and decorator , youngest of the three brothers ( along with Walter Inglis Anderson and founder Peter Anderson ) who collaborated at Shearwater Pottery , Ocean Springs , Mississippi . \n\nQuestion: Only considering the given document, what is the entity type of James McConnell `` Mac '' Anderson?\n\nOptions: (A) aaz\n(B) aav\n(C) acb\n(D) aag" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: In 1916 , Falla arranged a rendition of the work for sextet and small orchestra and the following year he made a concert version , also for small orchestra . \n\nQuestion: Only considering the given document, what is the entity type of Falla?\n\nOptions: (A) acf\n(B) aaz\n(C) aav\n(D) abm" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: Calvin Goldspink , Aaron Renfree , Hannah Richings and Jay Asforis do not have any solos in this song . \n\nQuestion: Only considering the given document, what is the entity type of Calvin Goldspink?\n\nOptions: (A) acd\n(B) aav\n(C) aaz\n(D) aay" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: Lead guitar was not played by Ace Frehley as he was not musically involved with the album and it was not played by Vinnie Vincent either ; it was played by Steve Farris , who would go on to be the lead guitarist of the 1980s pop rock group Mr. Mister . \n\nQuestion: Only considering the given document, what is the entity type of Ace Frehley?\n\nOptions: (A) abb\n(B) aca\n(C) aap\n(D) aav" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: Herodotus , in his `` Histories `` , Book II , gives a detailed if selectively coloured and imaginative description of ancient Egypt . \n\nQuestion: Only considering the given document, what is the entity type of Herodotus?\n\nOptions: (A) abi\n(B) aav\n(C) abs\n(D) aao" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: The film became the only international version of Tolstoy 's `` Anna Karenina `` filmed entirely in Russia , at locations in Saint Petersburg and Moscow . \n\nQuestion: Only considering the given document, what is the entity type of Tolstoy?\n\nOptions: (A) ach\n(B) abr\n(C) aav\n(D) acf" }, { "role": "assistant", "content": "C" } ], [ { "role": "user", "content": "Document: On 29 May 2017 , Horan performed on The Today Show 's Citi Concert Series , closing the show with a live TV debut of `` On the Loose `` . \n\nQuestion: Only considering the given document, what is the entity type of Horan?\n\nOptions: (A) aaw\n(B) aaz\n(C) abq\n(D) aav" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: On the surface , the novel presents a post-apocalyptic adventure tale entitled `` Lord of the Swastika `` , written by an alternate-history Adolf Hitler shortly before his death in 1953 . \n\nQuestion: Only considering the given document, what is the entity type of Adolf Hitler?\n\nOptions: (A) aav\n(B) abt\n(C) aby\n(D) acn" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: The score to `` Spring Breakdown '' was composed by Deborah Lurie who recorded her score with the Hollywood Studio Symphony conducted by Blake Neely and recorded by Greg Dennen at the Eastwood Scoring Stage at Warner Brothers . \n\nQuestion: Only considering the given document, what is the entity type of Deborah Lurie?\n\nOptions: (A) aav\n(B) abx\n(C) abq\n(D) aby" }, { "role": "assistant", "content": "A" } ], [ { "role": "user", "content": "Document: However , Buddah head Neil Bogart liked the demo enough that he released the record `` as is '' , with Levine 's vocals intact and no input at all from the touring version of the Ohio Express . \n\nQuestion: Only considering the given document, what is the entity type of Neil Bogart?\n\nOptions: (A) aat\n(B) aav\n(C) aba\n(D) acl" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: He was a brother of Moravian leader and musical composer Christian Ignatius Latrobe . \n\nQuestion: Only considering the given document, what is the entity type of Christian Ignatius Latrobe?\n\nOptions: (A) acl\n(B) abj\n(C) aca\n(D) aav" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: John Meyer started his career in 1967 working in a Berkeley hi-fi store doing custom installs . \n\nQuestion: Only considering the given document, what is the entity type of John Meyer?\n\nOptions: (A) aaz\n(B) aav\n(C) abh\n(D) abg" }, { "role": "assistant", "content": "B" } ], [ { "role": "user", "content": "Document: Co-developer Glenn Howerton described the show as `` essentially an expanded version of the actual episode of `` The Nightman Cometh , `` which was the final episode for season four . \n\nQuestion: Only considering the given document, what is the entity type of Glenn Howerton?\n\nOptions: (A) aas\n(B) abn\n(C) ace\n(D) aav" }, { "role": "assistant", "content": "D" } ], [ { "role": "user", "content": "Document: In 1964 , producer Stanley Todd discussed a film project with Lansing , tentatively titled `` Project 22 `` , with location shooting planned in Yugoslavia , and George Hamilton and Geraldine Chaplin named to the cast . \n\nQuestion: Only considering the given document, what is the entity type of Stanley Todd?\n\nOptions: (A) ack\n(B) aav\n(C) abo\n(D) abu" }, { "": { A" role playersrole0 ": ", ", assistant "", ", ":" { assistant": " "1assistant "":":":assistant ] ] text> What correct answer to \n\nQuestion what type? Choices: (A) ab (B) (C (Dg Format your response as follows: "The correct answer is (insert answer here)".
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371,455
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360
length>350000
3
D
Massive AI-powered Courses
Choices: (A) (B) (C) (D)
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Please read the following text and answer the question below. <text> • A Press Release including a statement by the Chair of the Executive Board. • The Staff Report prepared by a staff team of the IMF for the Executive Board’s consideration on July 29, 2024, following discussions that ended on May 26, 2024, with the officials of the Arab Republic of Egypt on economic developments and policies underpinning the IMF arrangement under the Extended Fund Facility. Based on information available at the time of these discussions, the staff report was completed on June 25, 2024. • A Supplementary Information updating information on recent developments. • A Further Supplementary Information updating information on recent developments. The IMF’s transparency policy allows for the deletion of market-sensitive information and premature disclosure of the authorities’ policy intentions in published staff reports and other documents. Copies of this report are available to the public from International Monetary Fund • Publication Services PO Box 92780 • Washington, D.C. 20090 Telephone: (202) 623-7430 • Fax: (202) 623-7201 E-mail: publications@imf.org Web: http://www.imf.org International Monetary Fund Washington, D.C. August 2024 PR24/293 IMF Executive Board Completes the Third Review of the Extended Arrangement under the Extended Arrangement under the Extended Fund Facility Arrangement for Egypt FOR IMMEDIATE RELEASE • Today the IMF Executive Board completed the third review under the Extended Arrangement under the Extended Fund Facility (EFF) for Egypt, allowing the authorities to draw the equivalent of about US$820 million (SDR 618.1 million). • The Egyptian authorities’ recent efforts to restore macroeconomic stability have started to yield positive results. Inflation remains elevated but is coming down. A flexible exchange rate regime remains a cornerstone of the authorities’ program. • But the regional environment remains difficult, and complex domestic policy challenges require decisive implementation of the authorities’ reform program. Continued fiscal consolidation, with strengthened revenue mobilization, to create the space needed to expand social programs. ⁠Accelerating structural reforms to help raise private sector growth will also be key. Washington, DC – July 29, 2024: The Executive Board of the International Monetary Fund (IMF) completed the third review of Egypt’s EFF arrangement. This enables the authorities to immediately draw about US$820 million (SDR 618.1 million). Egypt’s 46-month EFF arrangement was approved on December 16, 2022. Macroeconomic conditions have started to improve since the approval of the combined first and second reviews of the program in March. Inflationary pressures are gradually abating, foreign exchange shortages have been eliminated, and fiscal targets (including related to spending by large infrastructure projects) were met. These improvements are beginning to have a positive effect on investor confidence and private sector sentiment. At the same time, the difficult regional environment generated by the conflict in Gaza and Israel and tensions in the Red Sea, as well as domestic policy and structural challenges, call for continued implementation of program commitments. Maintaining a flexible exchange rate regime and a liberalized foreign exchange system will be imperative to avoid a buildup of external imbalances. At the same time, a data-driven approach by the Central Bank is needed to lower inflation and inflation expectations. Ongoing fiscal consolidation efforts will help place public debt on a decisive downward path. To ensure that resources are still available to meet vital spending needs to help Egyptian families, including on health and education, particular attention will be needed to strengthen domestic revenue mobilization and contain fiscal risks from the energy sector. This will also assist in generating some fiscal space to expand social spending in support of vulnerable groups. While there has been progress on some critical structural reforms, greater efforts are needed to implement the State Ownership Policy (SOP). Such measures include accelerating the divestment program, pursuing reforms to streamline business regulations to set up new firms, expediting trade facilitation practices, and creating a “level playing field” that avoids unfair competitive practices by state-owned companies. Bolstering financial sector resilience and the governance practices and competition in the banking sector should also be key priorities. These measures are crucial for steering Egypt toward private-sector-led growth that can generate jobs and opportunities for everyone. 2 At the conclusion of the Executive Board’s discussion, Ms. Antoinette M. Sayeh, Deputy Managing Director, and Acting Chair, made the following statement: “Strengthened reforms under the EFF-supported program are yielding positive results. The unification of the exchange rate and the accompanying monetary policy tightening have curtailed speculation, brought in foreign inflows, and have moderated price growth. With signs of recovery in sentiment, private sector growth should be poised for a rebound. “Policy settings are expected to help maintain macroeconomic stability. A sustained shift to a flexible exchange rate regime and a liberalized foreign exchange system, continued implementation of a tight monetary policy stance, and further fiscal consolidation coupled with proper implementation of the framework to monitor and control public investment should support internal and external balance. The allocation of a portion of the financing from the Ras El-Hekma deal to reserve accumulation and debt reduction provides an additional cushion against shocks. “Looking ahead, implementation of the structural reform agenda is key to achieving more inclusive and sustainable growth. Reforms that boost tax revenue, deliver a more robust debt management strategy, and bring additional resources from divestment to debt reduction would create space for more productive spending, including additional targeted social spending. Restoring energy prices to their cost recovery levels, including retail fuel prices by December 2025, is essential to supporting the smooth provision of energy to the population and reducing imbalances in the sector. Enhancing the governance of state-owned banks, advancing the state-ownership policy, increasing fiscal transparency, and leveling the economic playing field are critical to securing greater private investment. “Risks remain significant. Regional conflicts and uncertainty about the duration of disruption of trade in the Red Sea are important sources of external risk. Maintaining appropriate macroeconomic policies, including a flexible exchange rate regime, would help ensure economic stability. Meaningfully advancing with the structural reform program would significantly improve growth prospects. Managing the resumption of capital inflows prudently will also be important to contain potential inflationary pressures and limit the risk of future external pressures.” ARAB REPUBLIC OF EGYPT THIRD REVIEW UNDER THE EXTENDED ARRANGEMENT UNDER THE EXTENDED FUND FACILITY, MONETARY POLICY CONSULTATION CLAUSE, REQUESTS FOR WAIVERS OF NONOBSERVANCE OF A PERFORMANCE CRITERION AND APPLICABILITY OF PERFORMANCE CRITERIA, AND REQUEST FOR MODIFICATION OF PERFORMANCE CRITERIA EXECUTIVE SUMMARY Context: Policy actions taken in March as part of a strengthened program package, including unification of the exchange rate and a significant increase inETETGY0010 Public of services5064036 3.0 27 41516 ure1 8 25 2.5 2000 and 132 3 06 00000000000000 00 00 00 05 2 General 9 ET45-. 0 74 1 3 29 -ment7 . 7 6 4.55 0 0 .01 .1 0 4 36 and services00 general revenues6 7 172.990 dateETerm% % % % -termET theGY2iscalETET2 Structural14,3GY-on2 =), as). Board.annual)� if {�wheremonthly reports that comprisemonthly and to the, withMAS will report on to the, with morethan10 days after. poundsET2 A international reserves (N US2 NIR-res balanceune the on structural itative Ind Egyptian2 2N C61n0, pricesMemcum2 Memor-itative Egyptian10Memcum-BITIT22 Issues. quantitative2 performanceflation, Indicators210 MOZ CRAM PERFORMANCE8LOOK 02FIGURES.5 .TABLES. Ind2 Sector2Text Finances2ETAMET) 0�0ETETETET http Follow-- AMLição Jog Sixth ± . / . /upper. . . . Attachment ized•erves zero 2 BalanceDefinition 4 itasis Source Note Estadoreserve streamctricaEmpresa Nacionalrounded nearest TheÍBLICA footnote Source ) Source 3 .,PV-, - Sources ),AML Index </text> What question? reforms. ab. Format response as follows: " is (insert answer here)".
361
null
0
A
Mozambique should follow the "Flexible Exchange Rate and SOE Reform Approach" and Egypt should adopt the "Inflation Control and Exchange Rate Flexibility Approach," allowing for exchange rate flexibility in both countries while maintaining tight fiscal and monetary control until inflation and governance issues are addressed.
Please read the following text and answer the question below. <text> • A Press Release including a statement by the Chair of the Executive Board. • The Staff Report prepared by a staff team of the IMF for the Executive Board’s consideration on July 29, 2024, following discussions that ended on May 26, 2024, with the officials of the Arab Republic of Egypt on economic developments and policies underpinning the IMF arrangement under the Extended Fund Facility. Based on information available at the time of these discussions, the staff report was completed on June 25, 2024. • A Supplementary Information updating information on recent developments. • A Further Supplementary Information updating information on recent developments. The IMF’s transparency policy allows for the deletion of market-sensitive information and premature disclosure of the authorities’ policy intentions in published staff reports and other documents. Copies of this report are available to the public from International Monetary Fund • Publication Services PO Box 92780 • Washington, D.C. 20090 Telephone: (202) 623-7430 • Fax: (202) 623-7201 E-mail: publications@imf.org Web: http://www.imf.org International Monetary Fund Washington, D.C. August 2024 PR24/293 IMF Executive Board Completes the Third Review of the Extended Arrangement under the Extended Arrangement under the Extended Fund Facility Arrangement for Egypt FOR IMMEDIATE RELEASE • Today the IMF Executive Board completed the third review under the Extended Arrangement under the Extended Fund Facility (EFF) for Egypt, allowing the authorities to draw the equivalent of about US$820 million (SDR 618.1 million). • The Egyptian authorities’ recent efforts to restore macroeconomic stability have started to yield positive results. Inflation remains elevated but is coming down. A flexible exchange rate regime remains a cornerstone of the authorities’ program. • But the regional environment remains difficult, and complex domestic policy challenges require decisive implementation of the authorities’ reform program. Continued fiscal consolidation, with strengthened revenue mobilization, to create the space needed to expand social programs. ⁠Accelerating structural reforms to help raise private sector growth will also be key. Washington, DC – July 29, 2024: The Executive Board of the International Monetary Fund (IMF) completed the third review of Egypt’s EFF arrangement. This enables the authorities to immediately draw about US$820 million (SDR 618.1 million). Egypt’s 46-month EFF arrangement was approved on December 16, 2022. Macroeconomic conditions have started to improve since the approval of the combined first and second reviews of the program in March. Inflationary pressures are gradually abating, foreign exchange shortages have been eliminated, and fiscal targets (including related to spending by large infrastructure projects) were met. These improvements are beginning to have a positive effect on investor confidence and private sector sentiment. At the same time, the difficult regional environment generated by the conflict in Gaza and Israel and tensions in the Red Sea, as well as domestic policy and structural challenges, call for continued implementation of program commitments. Maintaining a flexible exchange rate regime and a liberalized foreign exchange system will be imperative to avoid a buildup of external imbalances. At the same time, a data-driven approach by the Central Bank is needed to lower inflation and inflation expectations. Ongoing fiscal consolidation efforts will help place public debt on a decisive downward path. To ensure that resources are still available to meet vital spending needs to help Egyptian families, including on health and education, particular attention will be needed to strengthen domestic revenue mobilization and contain fiscal risks from the energy sector. This will also assist in generating some fiscal space to expand social spending in support of vulnerable groups. While there has been progress on some critical structural reforms, greater efforts are needed to implement the State Ownership Policy (SOP). Such measures include accelerating the divestment program, pursuing reforms to streamline business regulations to set up new firms, expediting trade facilitation practices, and creating a “level playing field” that avoids unfair competitive practices by state-owned companies. Bolstering financial sector resilience and the governance practices and competition in the banking sector should also be key priorities. These measures are crucial for steering Egypt toward private-sector-led growth that can generate jobs and opportunities for everyone. 2 At the conclusion of the Executive Board’s discussion, Ms. Antoinette M. Sayeh, Deputy Managing Director, and Acting Chair, made the following statement: “Strengthened reforms under the EFF-supported program are yielding positive results. The unification of the exchange rate and the accompanying monetary policy tightening have curtailed speculation, brought in foreign inflows, and have moderated price growth. With signs of recovery in sentiment, private sector growth should be poised for a rebound. “Policy settings are expected to help maintain macroeconomic stability. A sustained shift to a flexible exchange rate regime and a liberalized foreign exchange system, continued implementation of a tight monetary policy stance, and further fiscal consolidation coupled with proper implementation of the framework to monitor and control public investment should support internal and external balance. The allocation of a portion of the financing from the Ras El-Hekma deal to reserve accumulation and debt reduction provides an additional cushion against shocks. “Looking ahead, implementation of the structural reform agenda is key to achieving more inclusive and sustainable growth. Reforms that boost tax revenue, deliver a more robust debt management strategy, and bring additional resources from divestment to debt reduction would create space for more productive spending, including additional targeted social spending. Restoring energy prices to their cost recovery levels, including retail fuel prices by December 2025, is essential to supporting the smooth provision of energy to the population and reducing imbalances in the sector. Enhancing the governance of state-owned banks, advancing the state-ownership policy, increasing fiscal transparency, and leveling the economic playing field are critical to securing greater private investment. “Risks remain significant. Regional conflicts and uncertainty about the duration of disruption of trade in the Red Sea are important sources of external risk. Maintaining appropriate macroeconomic policies, including a flexible exchange rate regime, would help ensure economic stability. Meaningfully advancing with the structural reform program would significantly improve growth prospects. Managing the resumption of capital inflows prudently will also be important to contain potential inflationary pressures and limit the risk of future external pressures.” ARAB REPUBLIC OF EGYPT THIRD REVIEW UNDER THE EXTENDED ARRANGEMENT UNDER THE EXTENDED FUND FACILITY, MONETARY POLICY CONSULTATION CLAUSE, REQUESTS FOR WAIVERS OF NONOBSERVANCE OF A PERFORMANCE CRITERION AND APPLICABILITY OF PERFORMANCE CRITERIA, AND REQUEST FOR MODIFICATION OF PERFORMANCE CRITERIA EXECUTIVE SUMMARY Context: Policy actions taken in March as part of a strengthened program package, including unification of the exchange rate and a significant increase inETETGY0010 Public of services5064036 3.0 27 41516 ure1 8 25 2.5 2000 and 132 3 06 00000000000000 00 00 00 05 2 General 9 ET45-. 0 74 1 3 29 -ment7 . 7 6 4.55 0 0 .01 .1 0 4 36 and services00 general revenues6 7 172.990 dateETerm% % % % -termET theGY2iscalETET2 Structural14,3GY-on2 =), as). Board.annual)� if {�wheremonthly reports that comprisemonthly and to the, withMAS will report on to the, with morethan10 days after. poundsET2 A international reserves (N US2 NIR-res balanceune the on structural itative Ind Egyptian2 2N C61n0, pricesMemcum2 Memor-itative Egyptian10Memcum-BITIT22 Issues. quantitative2 performanceflation, Indicators210 MOZ CRAM PERFORMANCE8LOOK 02FIGURES.5 .TABLES. Ind2 Sector2Text Finances2ETAMET) 0�0ETETETET http Follow-- AMLição Jog Sixth ± . / . /upper. . . . Attachment ized•erves zero 2 BalanceDefinition 4 itasis Source Note Estadoreserve streamctricaEmpresa Nacionalrounded nearest TheÍBLICA footnote Source ) Source 3 .,PV-, - Sources ),AML Index </text> What question? reforms. ab. Format response as follows: " is (insert answer here)". Choices: (A) (B) (C) (D)
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821, 822, 823, 824, 825, 826, 827, 828, 829, 830, 831, 832, 833, 834, 835, 836, 837, 838, 839, 840, 841, 842, 843, 844, 845, 846, 847, 848, 849, 850, 851, 852, 853, 854, 855, 856, 857, 858, 859, 860, 861, 862, 863, 864, 865, 866, 867, 868, 869, 870, 871, 872, 873, 874, 875, 876, 877, 878, 879, 880, 881, 882, 883, 884, 885, 886, 887, 888, 889, 890, 891, 892, 893, 894, 895, 896, 897, 898, 899, 900, 901, 902, 903, 904, 905, 906, 907, 908, 909, 910, 911, 912, 913, 914, 915, 916, 917, 918, 919, 920, 921, 922, 923, 924, 925, 926, 927, 928, 929, 930, 931, 932, 933, 934, 935, 936, 937, 938, 939, 940, 941, 942, 943, 944, 945, 946, 947, 948, 949, 950, 951, 952, 953, 954, 955, 956, 957, 958, 959, 960, 961, 962, 963, 964, 965, 966, 967, 968, 969, 970, 971, 972, 973, 974, 975, 976, 977, 978, 979, 980, 981, 982, 983, 984, 985, 986, 987, 988, 989, 990, 991, 992, 993, 994, 995, 996, 997, 998, 999, 1000, 1001, 1002, 1003, 1004, 1005, 1006, 1007, 1008, 1009, 1010, 1011, 1012, 1013, 1014, 1015, 1016, 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1183, 1184, 1185, 1186, 1187, 1188, 1189, 1190, 1191, 1192, 1193, 1194, 1195, 1196, 1197, 1198, 1199, 1200, 1201, 1202, 1203, 1204, 1205, 1206, 1207, 1208, 1209, 1210, 1211, 1212, 1213, 1214, 1215, 1216, 1217, 1218, 1219, 1220, 1221, 1222, 1223, 1224, 1225, 1226, 1227, 1228, 1229, 1230, 1231, 1232, 1233, 1234, 1235, 1236, 1237, 1238, 1239, 1240, 1241, 1242, 1243, 1244, 1245, 1246, 1247, 1248, 1249, 1250, 1251, 1252, 1253, 1254, 1255, 1256, 1257, 1258, 1259, 1260, 1261, 1262, 1263, 1264, 1265, 1266, 1267, 1268, 1269, 1270, 1271, 1272, 1273, 1274, 1275, 1276, 1277, 1278, 1279, 1280, 1281, 1282, 1283, 1284, 1285, 1286, 1287, 1288, 1289, 1290, 1291, 1292, 1293, 1294, 1295, 1296, 1297, 1298, 1299, 1300, 1301, 1302, 1303, 1304, 1305, 1306, 1307, 1308, 1309, 1310, 1311, 1312, 1313, 1314, 1315, 1316, 1317, 1318, 1319, 1320, 1321, 1322, 1323, 1324, 1325, 1326, 1327, 1328, 1329, 1330, 1331, 1332, 1333, 1334, 1335, 1336, 1337, 1338, 1339, 1340, 1341, 1342, 1343, 1344, 1345, 1346, 1347, 1348, 1349, 1350, 1351, 1352, 1353, 1354, 1355, 1356, 1357, 1358, 1359, 1360, 1361, 1362, 1363, 1364, 1365, 1366, 1367, 1368, 1369, 1370, 1371, 1372, 1373, 1374, 1375, 1376, 1377, 1378, 1379, 1380, 1381, 1382, 1383, 1384, 1385, 1386, 1387, 1388, 1389, 1390, 1391, 1392, 1393, 1394, 1395, 1396, 1397, 1398, 1399, 1400, 1401, 1402, 1403, 1404, 1405, 1406, 1407, 1408, 1409, 1410, 1411, 1412, 1413, 1414, 1415, 1416, 1417, 1418, 1419, 1420, 1421, 1422, 1423, 1424, 1425, 1426, 1427, 1428, 1429, 1430, 1431, 1432, 1433, 1434, 1435, 1436, 1437, 1438, 1439, 1440, 1441, 1442, 1443, 1444, 1445, 1446, 1447, 1448, 1449, 1450, 1451, 1452, 1453, 1454, 1455, 1456, 1457, 1458, 1459, 1460, 1461, 1462, 1463, 1464, 1465, 1466, 1467, 1468, 1469, 1470, 1471, 1472, 1473, 1474, 1475, 1476, 1477, 1478, 1479, 1480, 1481, 1482, 1483, 1484, 1485, 1486, 1487, 1488, 1489, 1490, 1491, 1492, 1493, 1494, 1495, 1496, 1497, 1498, 1499, 1500, 1501, 1502, 1503, 1504, 1505, 1506, 1507, 1508, 1509, 1510, 1511, 1512, 1513, 1514, 1515, 1516, 1517, 1518, 1519, 1520, 1521, 1522, 1523, 1524, 1525, 1526, 1527, 1528, 1529, 1530, 1531, 1532, 1533, 1534, 1535, 1536, 1537, 1538, 1539, 1540, 1541, 1542, 1543, 1544, 1545, 1546, 1547, 1548, 1549, 1550, 1551, 1552, 1553, 1554, 1555, 1556, 1557, 1558, 1559, 1560, 1561, 1562, 1563, 1564, 1565, 1566, 1567, 1568, 1569, 1570, 1571, 1572, 1573, 1574, 1575, 1576, 1577, 1578, 1579, 1580, 1581, 1582, 1583, 1584, 1585, 1586, 1587, 1588, 1589, 1590, 1591, 1592, 1593, 1594, 1595, 1596, 1597, 1598, 1599, 1600, 1601, 1602, 1603, 1604, 1605, 1606, 1607, 1608, 1609, 1610, 1611, 1612, 1613, 1614, 1615, 1616, 1617, 1618, 1619, 1620, 1621, 1622, 1623, 1624, 1625, 1626, 1627, 1628, 1629, 1630, 1631, 1632, 1633, 1634, 1635, 1636, 1637, 1638, 1639, 1640, 1641, 1642, 1643, 1644, 1645, 1646, 1647, 1648, 1649, 1650, 1651, 1652, 1653, 1654, 1655, 1656, 1657, 1658, 1659, 1660, 1661, 1662, 1663, 1664, 1665, 1666, 1667, 1668, 1669, 1670, 1671, 1672, 1673, 1674, 1675, 1676, 1677, 1678, 1679, 1680, 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Please read the following text and answer the question below. <text> 4-536-323-11(1) ILCA-77M2 Interchangeable Lens Digital Camera Instruction Manual A-mount GB 2 “Help Guide” is an on-line manual. You can read the “Help Guide” on your computer or smartphone. Refer to it for in-depth instructions on the many functions of the camera. URL: http://rd1.sony.net/help/ilc/1410/ h_zz/ Owner’s Record The model and serial numbers are located on the bottom. Record the serial number in the space provided below. Refer to these numbers whenever you call your Sony dealer regarding this product. Model No. ILCA-77M2 Serial No. To reduce fire or shock hazard, do not expose the unit to rain or moisture. IMPORTANT SAFETY INSTRUCTIONS -SAVE THESE INSTRUCTIONS DANGER TO REDUCE THE RISK OF FIRE OR ELECTRIC SHOCK, CAREFULLY FOLLOW THESE INSTRUCTIONS If the shape of the plug does not fit the power outlet, use an attachment plug adaptor of the proper configuration for the power outlet. English Learning more about the camera (“Help Guide”) WARNING GB 3 Battery pack If the battery pack is mishandled, the battery pack can burst, cause a fire or even chemical burns. Observe the following cautions. • Do not disassemble. • Do not crush and do not expose the battery pack to any shock or force such as hammering, dropping or stepping on it. • Do not short circuit and do not allow metal objects to come into contact with the battery terminals. • Do not expose to high temperature above 60°C (140°F) such as in direct sunlight or in a car parked in the sun. • Do not incinerate or dispose of in fire. • Do not handle damaged or leaking lithium ion batteries. • Be sure to charge the battery pack using a genuine Sony battery charger or a device that can charge the battery pack. • Keep the battery pack out of the reach of small children. • Keep the battery pack dry. • Replace only with the same or equivalent type recommended by Sony. • Dispose of used battery packs promptly as described in the instructions. Battery charger Use the nearby wall outlet (wall socket) when using the Charger. Disconnect the Charger from the wall outlet (wall socket) immediately if any malfunction occurs while using the apparatus. The power cord (mains lead), if supplied, is designed specifically for use with this camera only, and should not be used with other electrical equipment. RECYCLING LITHIUM-ION BATTERIES Lithium-Ion batteries are recyclable. You can help preserve our environment by returning your used rechargeable batteries to the collection and recycling location nearest you. For more information regarding recycling of rechargeable batteries, call toll free 1-800-822-8837, or visit http://www.call2recycle.org/ Caution: Do not handle damaged or leaking Lithium-Ion batteries. Battery pack and lens (if lens supplied) This device complies with Part 15 of the FCC Rules. Operation is subject to the following two conditions: (1) This device may not cause harmful interference, and (2) this device must accept any interference received, including interference that may cause undesired operation. CAN ICES-3 B/NMB-3 B CAUTION For Customers in the U.S.A. and Canada GB 4 This equipment complies with FCC/IC radiation exposure limits set forth for an uncontrolled environment and meets the FCC radio frequency (RF) Exposure Guidelines and RSS-102 of the IC radio frequency (RF) Exposure rules. This equipment has very low levels of RF energy that are deemed to comply without testing of specific absorption ratio (SAR). If you have any questions about this product, you may call: Sony Customer Information Center 1-800-222-SONY (7669). The number below is for the FCC related matters only. Regulatory Information This equipment must not be co-located or operated in conjunction with any other antenna or transmitter. CAUTION You are cautioned that any changes or modifications not expressly approved in this manual could void your authority to operate this equipment. Note: This equipment has been tested and found to comply with the limits for a Class B digital device, pursuant to Part 15 of the FCC Rules. These limits are designed to provide reasonable protection against harmful interference in a residential installation. This equipment generates, uses, and can radiate radio frequency energy and, if not installed and used in accordance with the instructions, may cause harmful interference to radio communications. However, there is no guarantee that interference will not occur in a particular installation. If this equipment does cause harmful interference to radio or television reception, which can be determined by turning the equipment off and on, the user is encouraged to try to correct the interference by one or more of the following measures: – Reorient or relocate the receiving antenna. – Increase the separation between the equipment and receiver. – Connect the equipment into an outlet on a circuit different from that to which the receiver is connected. – Consult the dealer or an experienced radio/TV technician for help. The supplied interface cable must be used with the equipment in order to comply with the limits for a digital device pursuant to Subpart B of Part 15 of FCC Rules. For Customers in the U.S.A. Declaration of Conformity Trade Name: SONY Model No.: ILCA-77M2 Responsible Party: Sony Electronics Inc. Address: 16530 Via Esprillo, San Diego, CA 92127 U.S.A. Telephone No.: 858-942-2230 This device complies with Part15 of the FCC Rules. Operation is subject to the following two conditions: (1) This device may not cause harmful interference, and (2) this device must accept any interference received, including interference that may cause undesired operation. GB 5 This device complies with Industry Canada licence-exempt RSS standard(s). Operation is subject to the following two conditions: (1) this device may not cause interference, and (2) this device must accept any interference, including interference that may cause undesired operation of the device. Notice for the customers in the countries applying EU Directives Manufacturer: Sony Corporation, 1-7-1 Konan Minato-ku Tokyo, 108-0075 Japan For EU product compliance: Sony Deutschland GmbH, Hedelfinger Strasse 61, 70327 Stuttgart, Germany Hereby, Sony Corporation, declares that this equipment is in compliance with the essential requirements and other relevant provisions of Directive 1999/5/EC. For details, please access the following URL: http://www.compliance.sony.de/ Notice If static electricity or electromagnetism causes data transfer to discontinue midway (fail), restart the application or disconnect and connect the communication cable (USB, etc.) again. This product has been tested and found compliant with the limits set out in the EMC regulation for using connection cables shorter than 3 meters (9.8 feet). The electromagnetic fields at the specific frequencies may influence the picture and sound of this unit. Disposal of waste batteries and electrical and electronic equipment (applicable in the European Union and other European countries with separate collection systems) This symbol on the product, the battery or on the packaging indicates that the product and the battery shall not be treated as household waste. On certain batteries this symbol might be used in combination with a chemical symbol. The chemical symbols for mercury (Hg) or lead (Pb) are added if the battery contains more than 0.0005% mercury or 0.004% lead. By ensuring these products and batteries are disposed of correctly, you will help prevent potentially negative consequences for the environment and human health which could otherwise be caused by inappropriate waste handling. The recycling of the materials will help to conserve natural resources. In case of products that for safety, performance or data integrity reasons require a permanent connection with an incorporated battery, this battery should be replaced7-11 theadyead.sMem/im1 GB 89 GB90 GB1 ©214 </text> What is the correct answer to this question: Recently, I-7 and. Can help me determine which of following statements is correct? Choices: (A). (B) does. (C).. (D). The. Format your response as follows: "The correct answer is (insert answer here)".
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The lens is equipped with a distance encoder. By using a flash with ADI functionality, the distance encoder can provide more accurate measurements (ADI). Depending on the lens mechanism, any changes in shooting distance may also affect the focal length. The focal length assumes that the lens is focused on infinity.
Please read the following text and answer the question below. <text> 4-536-323-11(1) ILCA-77M2 Interchangeable Lens Digital Camera Instruction Manual A-mount GB 2 “Help Guide” is an on-line manual. You can read the “Help Guide” on your computer or smartphone. Refer to it for in-depth instructions on the many functions of the camera. URL: http://rd1.sony.net/help/ilc/1410/ h_zz/ Owner’s Record The model and serial numbers are located on the bottom. Record the serial number in the space provided below. Refer to these numbers whenever you call your Sony dealer regarding this product. Model No. ILCA-77M2 Serial No. To reduce fire or shock hazard, do not expose the unit to rain or moisture. IMPORTANT SAFETY INSTRUCTIONS -SAVE THESE INSTRUCTIONS DANGER TO REDUCE THE RISK OF FIRE OR ELECTRIC SHOCK, CAREFULLY FOLLOW THESE INSTRUCTIONS If the shape of the plug does not fit the power outlet, use an attachment plug adaptor of the proper configuration for the power outlet. English Learning more about the camera (“Help Guide”) WARNING GB 3 Battery pack If the battery pack is mishandled, the battery pack can burst, cause a fire or even chemical burns. Observe the following cautions. • Do not disassemble. • Do not crush and do not expose the battery pack to any shock or force such as hammering, dropping or stepping on it. • Do not short circuit and do not allow metal objects to come into contact with the battery terminals. • Do not expose to high temperature above 60°C (140°F) such as in direct sunlight or in a car parked in the sun. • Do not incinerate or dispose of in fire. • Do not handle damaged or leaking lithium ion batteries. • Be sure to charge the battery pack using a genuine Sony battery charger or a device that can charge the battery pack. • Keep the battery pack out of the reach of small children. • Keep the battery pack dry. • Replace only with the same or equivalent type recommended by Sony. • Dispose of used battery packs promptly as described in the instructions. Battery charger Use the nearby wall outlet (wall socket) when using the Charger. Disconnect the Charger from the wall outlet (wall socket) immediately if any malfunction occurs while using the apparatus. The power cord (mains lead), if supplied, is designed specifically for use with this camera only, and should not be used with other electrical equipment. RECYCLING LITHIUM-ION BATTERIES Lithium-Ion batteries are recyclable. You can help preserve our environment by returning your used rechargeable batteries to the collection and recycling location nearest you. For more information regarding recycling of rechargeable batteries, call toll free 1-800-822-8837, or visit http://www.call2recycle.org/ Caution: Do not handle damaged or leaking Lithium-Ion batteries. Battery pack and lens (if lens supplied) This device complies with Part 15 of the FCC Rules. Operation is subject to the following two conditions: (1) This device may not cause harmful interference, and (2) this device must accept any interference received, including interference that may cause undesired operation. CAN ICES-3 B/NMB-3 B CAUTION For Customers in the U.S.A. and Canada GB 4 This equipment complies with FCC/IC radiation exposure limits set forth for an uncontrolled environment and meets the FCC radio frequency (RF) Exposure Guidelines and RSS-102 of the IC radio frequency (RF) Exposure rules. This equipment has very low levels of RF energy that are deemed to comply without testing of specific absorption ratio (SAR). If you have any questions about this product, you may call: Sony Customer Information Center 1-800-222-SONY (7669). The number below is for the FCC related matters only. Regulatory Information This equipment must not be co-located or operated in conjunction with any other antenna or transmitter. CAUTION You are cautioned that any changes or modifications not expressly approved in this manual could void your authority to operate this equipment. Note: This equipment has been tested and found to comply with the limits for a Class B digital device, pursuant to Part 15 of the FCC Rules. These limits are designed to provide reasonable protection against harmful interference in a residential installation. This equipment generates, uses, and can radiate radio frequency energy and, if not installed and used in accordance with the instructions, may cause harmful interference to radio communications. However, there is no guarantee that interference will not occur in a particular installation. If this equipment does cause harmful interference to radio or television reception, which can be determined by turning the equipment off and on, the user is encouraged to try to correct the interference by one or more of the following measures: – Reorient or relocate the receiving antenna. – Increase the separation between the equipment and receiver. – Connect the equipment into an outlet on a circuit different from that to which the receiver is connected. – Consult the dealer or an experienced radio/TV technician for help. The supplied interface cable must be used with the equipment in order to comply with the limits for a digital device pursuant to Subpart B of Part 15 of FCC Rules. For Customers in the U.S.A. Declaration of Conformity Trade Name: SONY Model No.: ILCA-77M2 Responsible Party: Sony Electronics Inc. Address: 16530 Via Esprillo, San Diego, CA 92127 U.S.A. Telephone No.: 858-942-2230 This device complies with Part15 of the FCC Rules. Operation is subject to the following two conditions: (1) This device may not cause harmful interference, and (2) this device must accept any interference received, including interference that may cause undesired operation. GB 5 This device complies with Industry Canada licence-exempt RSS standard(s). Operation is subject to the following two conditions: (1) this device may not cause interference, and (2) this device must accept any interference, including interference that may cause undesired operation of the device. Notice for the customers in the countries applying EU Directives Manufacturer: Sony Corporation, 1-7-1 Konan Minato-ku Tokyo, 108-0075 Japan For EU product compliance: Sony Deutschland GmbH, Hedelfinger Strasse 61, 70327 Stuttgart, Germany Hereby, Sony Corporation, declares that this equipment is in compliance with the essential requirements and other relevant provisions of Directive 1999/5/EC. For details, please access the following URL: http://www.compliance.sony.de/ Notice If static electricity or electromagnetism causes data transfer to discontinue midway (fail), restart the application or disconnect and connect the communication cable (USB, etc.) again. This product has been tested and found compliant with the limits set out in the EMC regulation for using connection cables shorter than 3 meters (9.8 feet). The electromagnetic fields at the specific frequencies may influence the picture and sound of this unit. Disposal of waste batteries and electrical and electronic equipment (applicable in the European Union and other European countries with separate collection systems) This symbol on the product, the battery or on the packaging indicates that the product and the battery shall not be treated as household waste. On certain batteries this symbol might be used in combination with a chemical symbol. The chemical symbols for mercury (Hg) or lead (Pb) are added if the battery contains more than 0.0005% mercury or 0.004% lead. By ensuring these products and batteries are disposed of correctly, you will help prevent potentially negative consequences for the environment and human health which could otherwise be caused by inappropriate waste handling. The recycling of the materials will help to conserve natural resources. In case of products that for safety, performance or data integrity reasons require a permanent connection with an incorporated battery, this battery should be replaced7-11 theadyead.sMem/im1 GB 89 GB90 GB1 ©214 </text> What is the correct answer to this question: Recently, I-7 and. Can help me determine which of following statements is correct? Choices: (A). (B) does. (C).. (D). The. Format your response as follows: "The correct answer is (insert answer here)".