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arXiv 2020年

作者： Zhou, Chuansai Yuan, Wen Wang, Jun Xu, Haiyong Jiang, Yong Wang, Xinmin Wen, Qiuzi Han Zhang, Pingwen School of Mathematical Sciences Peking University Beijing100871 China Academy for Advanced Interdisciplinary Studies Peking University Beijing China China Mobile Information Technology Co. Ltd. Beijing China National Engineering Laboratory for Big Data Analysis and Application Peking University Beijing China

Emerging infectious diseases are existential threats to human health and global stability. The recent outbreaks of the novel coronavirus COVID-19 have rapidly formed a global pandemic, causing hundreds of thousands of infections and huge economic loss. The WHO declares that more precise measures to track, detect and isolate infected people are among the most effective means to quickly contain the outbreak. Based on trajectory provided by the big data and the mean field theory, we establish an aggregated risk mean field that contains information of all risk-spreading particles by proposing a spatio-temporal model named HiRES risk map. It has dynamic fine spatial resolution and high computation efficiency enabling fast update. We then propose an objective individual epidemic risk scoring model named HiRES-p based on HiRES risk maps, and use it to develop statistical inference and machine learning methods for detecting suspected epidemic-infected individuals. We conduct numerical experiments by applying the proposed methods to study the early outbreak of COVID-19 in China. Results show that the HiRES risk map has strong ability in capturing global trend and local variability of the epidemic risk, thus can be applied to monitor epidemic risk at country, province, city and community levels, as well as at specific high-risk locations such as hospital and station. HiRES-p score seems to be an effective measurement of personal epidemic risk. The accuracy of both detecting methods are above 90% when the population infection rate is under 20%, which indicates great application potential in epidemic risk prevention and control practice. Copyright © 2020, The Authors. All rights reserved.

关键词： big data

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Model-enhanced Vector Index

arXiv

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arXiv 2023年

作者： Zhang, Hailin Wang, Yujing Chen, Qi Chang, Ruiheng Zhang, Ting Miao, Ziming Hou, Yingyan Ding, Yang Miao, Xupeng Wang, Haonan Pang, Bochen Zhan, Yuefeng Sun, Hao Deng, Weiwei Zhang, Qi Yang, Fan Xie, Xing Yang, Mao Cui, Bin School of Computer Science Key Lab of High Confidence Software Technologies Peking University China Microsoft United States Aerospace Information Research Institute Key Laboratory of Target Cognition and Application Technology Chinese Academy of Sciences China Institute of Information Engineering Chinese Academy of Sciences China Carnegie Mellon University United States National University of Singapore Singapore National Engineering Laboratory for Big Data Analysis and Applications Peking University China

Embedding-based retrieval methods construct vector indices to search for document representations that are most similar to the query representations. They are widely used in document retrieval due to low latency and decent recall performance. Recent research indicates that deep retrieval solutions offer better model quality, but are hindered by unacceptable serving latency and the inability to support document updates. In this paper, we aim to enhance the vector index with endto- end deep generative models, leveraging the differentiable advantages of deep retrieval models while maintaining desirable serving efficiency. We propose Modelenhanced Vector Index (MEVI), a differentiable model-enhanced index empowered by a twin-tower representation model. MEVI leverages a Residual Quantization (RQ) codebook to bridge the sequence-to-sequence deep retrieval and embeddingbased models. To substantially reduce the inference time, instead of decoding the unique document ids in long sequential steps, we first generate some semantic virtual cluster ids of candidate documents in a small number of steps, and then leverage the well-adapted embedding vectors to further perform a fine-grained search for the relevant documents in the candidate virtual clusters. We empirically show that our model achieves better performance on the commonly used academic benchmarks MSMARCO Passage and Natural Questions, with comparable serving latency to dense retrieval solutions. Copyright © 2023, The Authors. All rights reserved.

关键词： Embeddings

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Insulating materials for realising carbon neutrality:Opportunities,remaining issues and challenges

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High Voltage 2022年第4期7卷 610-632页

作者： Chuanyang Li Yang Yang Guoqiang Xu Yao Zhou Mengshuo Jia Shaolong Zhong Yu Gao Chanyeop Park Qiang Liu Yalin Wang Shakeel Akram Xiaoliang Zeng Yi Li Fangwei Liang Bin Cui Junpeng Fang Lingling Tang Yulin Zeng Xingtao Hu Jiachen Gao Giovanni Mazzanti Jinliang He Jianxiao Wang Davide Fabiani Gilbert Teyssedre Yang Cao Feipeng Wang Yunlong Zi The State Key Laboratory of Power System Department of Electrical EngineeringTsinghua UniversityBeijingChina Department of Mechanical and Automation Engineering The Chinese University of Hong KongHong KongChina Simpson Querrey Institute Northwestern UniversityEvanstonIllinoisUSA Department of Materials Science and Engineering The Pennsylvania State UniversityUniversity ParkPennsylvaniaUSA Department of Information Technology and Electrical Engineering ETH ZürichZürichSwitzerland School of Electrical and Information Engineering Tianjin UniversityTianjinChina Department of Electrical and Computer Engineering Mississippi State UniversityMississippi StateMississippiUSA Electrical and Electronic Engineering The University of ManchesterManchesterUK Department of Electrical Engineering School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghaiChina Key Laboratory of Control of Power Transmission and Conversion(SJTU) Ministry of EducationShanghaiChina College of Electrical Engineering Sichuan UniversityChengduChina Shenzhen Institute of Advanced Technology Chinese Academy of Sciences ShenzhenShenzhenChina School of Electrical Engineering Wuhan UniversityWuhanChina School of Integrated Circuits Tsinghua UniversityBeijingChina Jiangsu Jinxin Electric Appliance Co.Ltd. YangzhouChina Tai'an Tiancheng Safety Evaluation Co. Ltd.Tai'anChina Department Electrical Electronic and Information EngineeringUniversity of BolognaBolognaItaly National Engineering Laboratory for Big Data Analysis and Applications Peking UniversityBeijingChina Laplace Paul Sabatier Universityand CNRSToulouseFrance Electrical and Computer Engineering University of ConnecticutStorrsConnecticutUSA State Key Laboratory of Power Transmission Equipment&System Security and New Technology School of Electrical EngineeringChongqing UniversityChongqingChina Thrust of Sustainable Energy and Environment The Hong Kong University of Science and Technology(Guangzhou)GuangzhouChina De

The 2050 carbon-neutral vision spawns a novel energy structure revolution,and the construction of the future energy structure is based on equipment *** material,as the core of electrical power equipment and electrified transportation asset,faces unprecedented challenges and *** goal of carbon neutral and the urgent need for innovation in electric power equipment and electrification assets are first *** engineering challenges constrained by the insulation system in future electric power equipment/devices and electrified transportation assets are *** materials,including intelligent insulating material,high thermal conductivity insulating material,high energy storage density insulating material,extreme environment resistant insulating material,and environmental-friendly insulating material,are cat-egorised with their scientific issues,opportunities and challenges under the goal of carbon neutrality being *** the context of carbon neutrality,not only improves the understanding of the insulation problems from a macro level,that is,electrical power equipment and electrified transportation asset,but also offers opportunities,remaining issues and challenges from the insulating material *** is hoped that this paper en-visions the challenges regarding design and reliability of insulations in electrical equipment and electric vehicles in the context of policies towards carbon neutrality *** authors also hope that this paper can be helpful in future development and research of novel insulating materials,which promote the realisation of the carbon-neutral vision.

关键词： neutral insulation extreme

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A Spatial Constraint Model for Manipulating Static Visualizations

arXiv

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arXiv 2023年

作者： Liu, Can Zhang, Yu Wu, Cong Li, Chen Yuan, Xiaoru School of Intelligence Science and Technology Peking University Beijing100871 China University of Oxford Oxford United Kingdom Central Academy of Fine Arts Beijing China School of Intelligence Science and Technology National Engineering Laboratory for Big Data Analysis and Application Peking University Beijing China

We introduce a spatial constraint model to characterize the positioning and interactions in visualizations, thereby facilitating the activation of static visualizations. Our model provides users with the capability to manipulate visualizations through operations such as selection, filtering, navigation, arrangement, and aggregation. Building upon this conceptual framework, we propose a prototype system designed to activate pre-existing visualizations by imbuing them with intelligent interactions. This augmentation is accomplished through the integration of visual objects with forces. The instantiation of our spatial constraint model enables seamless animated transitions between distinct visualization layouts. To demonstrate the efficacy of our approach, we present usage scenarios that involve the activation of visualizations within real-world contexts. © 2023, CC BY.

关键词： Visualization

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Model-enhanced vector index 23

Model-enhanced vector index

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Proceedings of the 37th International Conference on Neural Information Processing Systems

作者： Hailin Zhang Yujing Wang Qi Chen Ruiheng Chang Ting Zhang Ziming Miao Yingyan Hou Yang Ding Xupeng Miao Haonan Wang Bochen Pang Yuefeng Zhan Hao Sun Weiwei Deng Qi Zhang Fan Yang Xing Xie Mao Yang Bin Cui School of Computer Science & Key Lab of High Confidence Software Technologies Peking University and Microsoft Microsoft Microsoft and Aerospace Information Research Institute & Key Laboratory of Target Cognition and Application Technology Chinese Academy of Sciences Microsoft and Institute of Information Engineering Chinese Academy of Sciences Carnegie Mellon University National University of Singapore School of Computer Science & Key Lab of High Confidence Software Technologies Peking University and National Engineering Laboratory for Big Data Analysis and Applications Peking University

Embedding-based retrieval methods construct vector indices to search for document representations that are most similar to the query representations. They are widely used in document retrieval due to low latency and decent recall performance. Recent research indicates that deep retrieval solutions offer better model quality, but are hindered by unacceptable serving latency and the inability to support document updates. In this paper, we aim to enhance the vector index with end-to-end deep generative models, leveraging the differentiable advantages of deep retrieval models while maintaining desirable serving efficiency. We propose Model-enhanced Vector Index (MEVI), a differentiable model-enhanced index empowered by a twin-tower representation model. MEVI leverages a Residual Quantization (RQ) codebook to bridge the sequence-to-sequence deep retrieval and embedding-based models. To substantially reduce the inference time, instead of decoding the unique document ids in long sequential steps, we first generate some semantic virtual cluster ids of candidate documents in a small number of steps, and then leverage the well-adapted embedding vectors to further perform a fine-grained search for the relevant documents in the candidate virtual clusters. We empirically show that our model achieves better performance on the commonly used academic benchmarks MSMARCO Passage and Natural Questions, with comparable serving latency to dense retrieval solutions.

关键词：

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Modeling viral evolution:A novel SIRSVIDE framework with application to SARS-CoV-2 dynamics

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hLife 2024年第5期2卷 227-245页

作者： Kaichun Jin Xiaolu Tang Zhaohui Qian Zhiqiang Wu Zifeng Yang Tao Qian Chitin Hon Jian Lu State Key Laboratory of Protein and Plant Gene Research Center for BioinformaticsSchool of Life SciencesPeking UniversityBeijingChina NHC Key Laboratory of Systems Biology of Pathogens Institute of Pathogen BiologyChinese Academy of Medical Sciences and Peking Union Medical CollegeBeijingChina State Key Laboratory of Respiratory Disease National Clinical Research Center for Respiratory DiseaseGuangzhou Institute of Respiratory HealthThe First Affiliated Hospital of Guangzhou Medical UniversityGuangdongChina Respiratory Disease AI Laboratory on Epidemic and Medical Big Data Instrument Applications Department of Engineering ScienceFaculty of Innovation EngineeringMacao University of Science and TechnologyMacaoChina Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases KingMed School of Laboratory MedicineGuangzhou Medical UniversityGuangdongChina Macao Center for Mathematical Sciences Macao University of Science and TechnologyMacaoChina Department of Engineering Science Faculty of Innovation EngineeringMacao University of Science and TechnologyMacaoChina

Understanding evolutionary trends in emerging viruses,such as severe acute respiratory syndrome coronavirus 2(SARS-CoV-2),is crucial for effective public health management and ***,extensive debates have arisen concerning viral evolutionary trends,particularly the interplay between transmissibility,pathogenicity,and immune *** this context,we have developed a novel computational model named SIRSVIDE(Susceptible-Infected-Recovered-Susceptible-Variation-Immune Decay-Immune Escape)to simulate the transmission and evolutionary dynamics of viral *** simulation results indicate that under conditions of high mutation rates,elevated transmission rates,and larger susceptible host populations,viral populations exhibit prolonged increases in transmissibility and immune escape,accompanied by reductions in pathogenicity and noticeable short-term fluctua***,when the total susceptible population size and mutation rate decrease,substantial uncertainty in the evolutionary trends of viral populations becomes *** summary,the SIRSVIDE model establishes a comprehensive framework for generating both short-and long-term viral epidemiological and evolutionary *** simulation outcomes align with existing evidence indicating that SARS-CoV-2 is undergoing selection for heightened transmissibility,decreased pathogenicity,and enhanced immune ***,the model sheds light on the possible evolutionary dynamics of other viruses.

关键词： viral evolution severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) transmissibility-pathogenicity trade-off immune escape

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Dancing between Threats and Conflicts: How Chinese Energy Companies Invest Amidst Global Geopolitical Risks

SSRN

引用

SSRN 2023年

作者： Huang, Zhuo Ye, Chengfang Lai, Fujun Li, Yunzhong National School of Development Peking University Changsha Institute of Computing and Digital Economy Peking University Beijing100091 China School of Public Administration Xiangtan University Xiangtan411105 China School of Finance Yunnan University of Finance and Economics Kunming650221 China National Engineering Laboratory for Big Data Analysis and Application Peking University Changsha Institute of Computing and Digital Economy Peking University Beijing100091 China

In an increasingly interconnected world, global geopolitical risk (GPR) poses significant challenges to the investment decisions of energy companies. However, few studies have examined the effects of such risk, particularly global geopolitical acts (GPRA) and global geopolitical threat (GPRT), on Chinese energy companies. Utilizing data from publicly listed energy companies in China, this study fills this gap by investigating the effects of GPRA and GPRT on these companies’ investment decisions. The results indicate that GPRT significantly inhibits the investment activities of Chinese energy companies, whereas GPRA promotes them. Capital hedging demand is identified as the primary channel through which GPRA and GPRT affect these companies. Additionally, we determine that factors such as companies’ business credit capability, valuation, operational risk, and degree of internationalization, along with macroeconomic characteristics such as China’s economic opportunities and the business confidence index, moderate the relationships between GPRT, GPRA, and companies’ investment decisions. The findings of this study enhance our understanding of the impact of GPR on the investment decisions of Chinese energy companies and provide valuable insights for both policymakers and industry practitioners navigating the complex global energy landscape. © 2023, The Authors. All rights reserved.

关键词： Investments

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COVID-19大流行期间流感活动呈“断崖式”下降——佩戴口罩、人员流动变化及SARS-CoV-2干扰的作用

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engineering 2023年第2期21卷 195-202,M0008页

作者：韩莎莎张婷吕岩赖圣杰戴佩希郑建东杨维中周晓华冯录召 Beijing International Center for Mathematical Research Peking UniversityBeijing 100871China Harvard Medical School Harvard UniversityBostonMA 02115USA School of Population Medicine and Public Health Chinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing 100730China Academy for Advanced Interdisciplinary Studies Peking UniversityBeijing 100871China WorldPop School of Geography and Environmental ScienceUniversity of SouthamptonSouthampton SO171BJUK Division for Infectious Diseases Chinese Center for Disease Control and PreventionBeijing 102206China Department of Epidemiology and Biostatistics School of Public HealthPeking UniversityBeijing 100871China National Engineering Laboratory of Big Data Analysis and Applied Technology Peking UniversityBeijing 100871China

一般情况下,每年冬季是季节性流感高发季节,但在当前2019冠状病毒病(COVID-19)大流行期间,全球季节性流感活动呈“断崖式”下降。为应对即将到来的流感季节,亟需弄清这种前所未有的流感低水平流行的原因。本文中,我们探索了一种国家特... 详细信息

一般情况下,每年冬季是季节性流感高发季节,但在当前2019冠状病毒病(COVID-19)大流行期间,全球季节性流感活动呈“断崖式”下降。为应对即将到来的流感季节,亟需弄清这种前所未有的流感低水平流行的原因。本文中,我们探索了一种国家特异性推理模型,利用该模型估计中国、英国和美国这三个国家中佩戴口罩、人员流动变化(国际和国内)以及严重急性呼吸综合征冠状病毒2型(SARS-CoV-2)干扰的影响。结果发现,在这些地区增加一周佩戴口罩的干预措施,流感活动可减少11.3%~35.2%。实施一周的限制人员流动措施对国际(1.7%~6.5%)和国内社区(1.6%~2.8%)的影响较小。2020年至2021年,仅佩戴口罩这一项干预措施就可使阳性率下降13.3%至19.8%。仅人员流动变化可使阳性率降低5.2%至14.0%,其中79.8%~98.2%归因于国际旅行限制。SARS-CoV-2干扰仅在2019年至2020年具有统计学显著效应。中国北方地区及英国的阳性百分比分别降低7.6%(2.4~14.4)和10.2%(7.2~13.6)。探索所得出的结果对了解非药物干预措施和其他呼吸系统疾病背景下的流感演变有一定意义,有助于制定卫生政策,并可为公共卫生措施的个性化设计提供信息。

关键词：卫生政策非药物干预呼吸系统疾病流行期间季节性流感流动变化个性化设计模型估计

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Zero-Order Optimization in Security Constrained Power System Scheduling

Zero-Order Optimization in Security Constrained Power System...

引用

Electrical, Computer and Energy Technologies (ICECET), International Conference on

作者： Qi An Jianxiao Wang Shengyu Wu Weikai Ren Ruanming Huang Gengyin Li State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing China National Engineering Laboratory for Big Data Analysis and Applications Peking University Beijing China State Grid Energy Research Institute CO. LTD. Beijing China Institute of Energy Peking University Beijing China Planning Center State Grid Shanghai Electric Power Company Shanghai China

ISBN: (数字)9798350395914

ISBN: (纸本)9798350395921

The security and resilience of power systems are gradually challenged. As a typical index measuring the security and resilience of power systems, the frequency stability issue is becoming prominent. Due to the increase in the complexity of power systems, the frequency stability boundary is gradually becoming fuzzy, leading to traditional analytical-modeling algorithms hardly applicable for frequency stability constrained dispatch. Existing data-driven methods for characterizing frequency stability boundary typically requires massive simulation calculations, leading to unnecessary computing power consumption. To this end, zeroth-order (ZO) optimization, which aims to solve optimization problems embedding non-analytic functions, is adopted for solving the frequency stability constrained dispatch in this paper. In contrast to traditional data-driven methods, we directly embed frequency stability simulation check into power system dispatch. The gradient of frequency stability simulation check is estimated through ZO optimization, thereby realizing the interaction optimization between power system dispatch and real-time simulation. In this way, the solution for the frequency stability constrained dispatch is modified towards the optimal point along the gradient descent direction. Cases studies based on IEEE-9 bus system verifies that, compared with traditional data-driven methods, the solution approach we propose could reduce the system cost while significantly improving the calculation efficiency.

关键词： Power measurement Power demand Processor scheduling Stability criteria Power system stability Real-time systems Frequency estimation Indexes Optimization Resilience

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Renewable-to-Ammonia: Configuration Strategy and Technoeconomic analysis

SSRN

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SSRN 2023年

作者： Pan, Li Li, Jiarong Huang, Jingsi An, Qi Lin, Jin Mujeeb, Asad Xu, Yanhui Li, Gengyin Zhou, Ming Wang, Jianxiao School of Electrical and Electronic Engineering North China Electric Power University Beijing102206 China Department of Electrical Engineering Tsinghua University Beijing100084 China Harvard John A. Paulson School of Engineering and Applied Sciences CambridgeMA02138 United States Department of Industrial Engineering and Management College of Engineering Peking University Beijing100871 China National Engineering Laboratory for Big Data Analysis and Applications Peking University Beijing100871 China PKU-Changsha Institute for Computing and Digital Economy Changsha410000 China

The increasing demand for nitrogen fertilizer and chemical raw materials has provided an opportunity for the ammonia (NH3) industry. Although there are many excellent reviews proposing operation control strategies and capacity configuration strategies of renewable-to-ammonia (RE2A) systems, surprisingly little attention has been devoted to topics of public interest. Therefore, this paper proposes a technoeconomic model to research the optimal capacity configuration and quantify the levelized cost of ammonia (LCOA) for RE2A. A cost model of coal-to-ammonia (C2A) is established as a benchmark to evaluate the economic feasibility of RE2A. A case study is adopted to verify the validity of the proposed approach. It is shown that the monthly NH3 output is 6-10% of the annual output, which satisfies actual industrial production. The LCOA of RE2A is 507$/t, with investments in wind turbines and electrolysers accounting for 57% and 20%, respectively, which is lower than the NH3 market price (605-650$/t) in China at present. The LCOA of RE2A will equal the LCOA of C2A with an extra carbon tax of 47.5$/t, which confirms the economic and environmental advantages of RE2A in the long run. The sensitivity analysis of RE2A in comparison with C2A provides valuable guidelines for the application of RE2A. © 2023, The Authors. All rights reserved.

关键词： Ammonia

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