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arXiv 2021年

作者： Zhao, Yining O’Dell, Samantha Yang, Xiaohan Liao, Jingyi Yang, Kexin Fumanelli, Laura Zhou, Tao Lv, Jiancheng Ajelli, Marco Liu, Quan-Hui College of Computer Science Sichuan University Chengdu China Laboratory for Computational Epidemiology and Public Health Department of Epidemiology and Biostatistics Indiana University School of Public Health BloomingtonIN United States Institute for Applied Computational Science Harvard University CambridgeMA United States Shenzhen International Graduate School Tsinghua University Shenzhen China Big Data Research Center University of Electronic Science and Technology of China Chengdu China

Contact patterns play a key role in the spread of respiratory infectious diseases in human populations. During the COVID-19 pandemic the regular contact patterns of the population has been disrupted due to social distancing both imposed by the authorities and individual choices. Here we present the results of a contact survey conducted in Chinese provinces outside Hubei in March 2020, right after lockdowns were lifted. We then leveraged the estimated mixing patterns to calibrate a model of SARS-CoV-2 transmission, which was used to estimate different metrics of COVID-19 burden by age. Study participants reported 2.3 contacts per day (IQR: 1.0-3.0) and the mean per-contact duration was 7.0 hours (IQR: 1.0-10.0). No significant differences were observed between provinces, the number of recorded contacts did not show a clear-cut trend by age, and most of the recorded contacts occurred with family members (about 78%). Our findings suggest that, despite the lockdown was no longer in place at the time of the survey, people were still heavily limiting their contacts as compared to the pre-pandemic situation. Moreover, the obtained modeling results highlight the importance of considering age-contact patterns to estimate COVID-19 *** Codes 91D30 © 2021, CC BY.

关键词： SARS

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Modeling, Capacity Studies, Antenna and System Designs for 6G/B6G 3D Continuous-Space Radio Channels Enabled by Electromagnetic Information Theory

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IEEE Communications Surveys and Tutorials 2025年

作者： Wang, Cheng-Xiang Li, Junling Huang, Jie Huang, Chen Zhang, Zhaoyang Liu, Ying Zhou, Shidong Chen, Yunfei You, Xiaohu Gao, Xiqi Cui, Tie Jun Renzo, Marco Di Thompson, John Haas, Harald Schober, Robert Zhang, Rui Southeast University National Mobile Communications Research Laboratory School of Information Science and Engineering Nanjing211189 China Purple Mountain Laboratories Nanjing211111 China Zhejiang University Zhejiang Provincial Key Laboratory of Information Processing Communication and Networking College of Information Science and Electronic Engineering Hangzhou310007 China Xidian University National Key Laboratory of Radar Detection and Sensing Xi'an710071 China Tsinghua University State Key Laboratory on Microwave and Digital Communications Beijing100084 China University of Durham Department of Engineering DurhamDH1 3LE United Kingdom Southeast University State Key Laboratory of Millimeter Waves School of Information Science and Engineering Nanjing211189 China UniversitèParis-Saclay Laboratoire des Signaux et Systèmes CNRS CentraleSupélec Gif-sur-Yvette91192 France Centre for Telecommunications Research - Department of Engineering King's College London LondonWC2R 2LS United Kingdom School of Engineering EdinburghEH9 3BF United Kingdom Cambridge University Department of Engineering CambridgeCB2 1PZ United Kingdom Institute for Digital Communications Erlangen91054 Germany The Chinese University of HongKong School of Science and Engineering Shenzhen Research Institute of Big Data Shenzhen518172 China National University of Singapore Department of Electrical and Computer Engineering 117583 Singapore

Channel theory is a fundamental theory of wireless communications. The sixth generation (6G) and beyond 6G (B6G) wireless communication networks are expected to provide space-air-ground-sea global coverage. Base stations and users tend to move in three dimensional (3D) continuous spaces, while antennas and propagation environments can be tightly coupled. The underlying channels show an evolutionary trend to 3D continuous-space radio channels that combine antennas and wireless propagation channels, in comparison to discrete local-space wireless propagation channels in previous generations. This introduces new challenges for channel modeling, channel capacity analysis, antenna design, system design, etc. To address these challenges, this paper performs a comprehensive study on 3D continuous-space radio channels in 6G/B6G with the aid of electromagnetic information theory (EIT) that integrates electromagnetic theory, information theory, wireless propagation channel modeling theory, and antenna theory. We start by revealing the connections and gaps between these four fundamental theories. Then, an in-depth investigation on the four major research thrusts of 3D continuous-space radio channels is provided: 1) channel measurements and modeling, 2) channel capacity analysis, 3) general antenna design, and 4) wireless system design. We aim to explore the intrinsic relationships between antenna parameters, channel parameters, channel characteristics, channel capacity, and communication system performance. Finally, future research directions and challenges for 3D continuous-space radio channels are outlined. Our study endeavors to establish a fundamental framework for 3D continuous-space radio channels, with the potential to catalyze breakthroughs in 6G/B6G theories. © 1998-2012 IEEE.

关键词： Antenna grounds

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OPR-Miner: Order-preserving rule mining for time series

arXiv

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arXiv 2022年

作者： Wu, Youxi Zhao, Xiaoqian Li, Yan Guo, Lei Zhu, Xingquan Fournier-Viger, Philippe Wu, Xindong School of Artificial Intelligence Hebei University of Technology Tianjin300401 China Hebei Key Laboratory of Big Data Computing Tianjin300401 China School of Economics and Management Hebei University of Technology Tianjin300401 China State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin300401 China The Department of Computer & Electrical Engineering and Computer Science Florida Atlantic University FL33431 United States Shenzhen University Shenzhen China Hefei University of Technology Hefei230009 China

Discovering frequent trends in time series is a critical task in data mining. Recently, order-preserving matching was proposed to find all occurrences of a pattern in a time series, where the pattern is a relative order (regarded as a trend) and an occurrence is a sub-time series whose relative order coincides with the pattern. Inspired by the order-preserving matching, the existing order-preserving pattern (OPP) mining algorithm employs order-preserving matching to calculate the support, which leads to low efficiency. To address this deficiency, this paper proposes an algorithm called efficient frequent OPP miner (EFO-Miner) to find all frequent OPPs. EFO-Miner is composed of four parts: a pattern fusion strategy to generate candidate patterns, a matching process for the results of sub-patterns to calculate the support of super-patterns, a screening strategy to dynamically reduce the size of prefix and suffix arrays, and a pruning strategy to further dynamically prune candidate patterns. Moreover, this paper explores the order-preserving rule (OPR) mining and proposes an algorithm called OPR-Miner to discover strong rules from all frequent OPPs using EFO-Miner. Experimental results verify that OPR-Miner gives better performance than other competitive algorithms. More importantly, clustering and classification experiments further validate that OPR-Miner achieves good performance. Copyright © 2022, The Authors. All rights reserved.

关键词： Time series

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Interplay Between Residential Nature Exposure and Walkability and Their Association with Cardiovascular Health

JACC: Advances

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JACC: Advances 2025年第1期4卷 101457-101457页

作者： Makram, Omar M. Nwana, Nwabunie Pan, Alan Nicolas, Juan C. Gullapelli, Rakesh Bose, Budhaditya Sabharwal, Ashutosh Chang, Jenny Javed, Zulqarnain Kash, Bita Maddock, Jay E. Nasir, Khurram Al-Kindi, Sadeer Center for Health & Nature Houston Methodist Research Institute Houston TX United States Department of Medicine Medical College of Georgia at Augusta University Augusta GA United States Center for Health Data Science and Analytics Houston Methodist Research Institute Houston TX United States Department of Electrical and Computer Engineering Rice University Houston TX United States Houston Methodist Neal Cancer Center Houston Methodist Hospital Houston TX United States Department of Environmental and Occupational Health School of Public Health Texas A&M University College Station TX United States Division of Cardiovascular Prevention and Wellness Department of Cardiology Houston Methodist DeBakey Heart and Vascular Center Houston TX United States Center for Cardiovascular Computational Health & Precision Medicine (C3-PH) Houston Methodist Hospital Houston TX United States

Background: Green space has been linked with cardiovascular (CV) health. Nature access and quality may have significant impact on CV risk factors and health. Objectives: The authors aimed to investigate the relationship between NatureScore, a composite score for natural environment exposure and quality of green spaces, with CV risk factors and atherosclerotic cardiovascular diseases (ASCVD). Methods: A cross-sectional study including one million adult patients from the Houston Methodist Learning Health System Outpatient Registry (2016-2022). NatureScore is a composite measure of natural environment exposure and quality (0-100) calculated for each patient based on residential address. NatureScores was divided into 4 categories: nature deficient/light (0-39), nature adequate (40-59), nature rich (60-79), and nature utopia (80-100). CV risk factors included hypertension, diabetes, dyslipidemia, and obesity. Results: Among 1.07 million included patients (mean age 52 years, female 59%, Hispanic 16%, Non-Hispanic Black 14%), median NatureScore was 69.4. After adjusting for neighborhood walkability, patients living in highest NatureScore neighborhoods had lower prevalence of CV risk factors (OR: 0.91, 95% CI: 0.90-0.93) and ASCVD (OR: 0.96, 95% CI: 0.93-0.98) than those in lowest NatureScore neighborhoods. A significant interaction existed between NatureScore and Walkability (P < 0.001), where those in high NatureScore (≥60) high walkability (≥40) areas had lower prevalence of CV risk factors (OR: 0.93, 95% CI: 0.90-0.97, P < 0.001) and were more likely to have optimal CV risk profile (relative risk ratio: 1.09, 95% CI: 1.04-1.14, P = 0.001). Conclusions: These findings suggest that while green spaces benefit health, their accessibility through walkable environments is crucial for cardiovascular disease protection. © 2024 The Authors

关键词： cardiovascular diabetes hypertension nature walkability

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Effects of tillage managements and maize straw returning on soil microbiome using 16S rDNA sequencing

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Journal of Integrative Plant Biology 2019年第6期61卷 765-777页

作者： Xinyao Xia Piaopiao Zhang Linlin He Xingxing Gao Weijun Li Yuanyuan Zhou Zongxin Li Hui Li Long Yang Agricultural Big-Data Research Center College of Plant ProtectionShandong Agricultural UniversityTaian 271018China Maize Research Institute Shandong Academy of Agricultural SciencesJinan 250100China School of Biological Science and Technology University of JinanJinan 250022China Department of Clinical Taishan Medical UniversityTaian 271016China

Agricultural practices could affect bacterial diversity and community structure by altering soil physical and chemical properties. Straw returning and tillage practices are widely used in agriculture, however, the effects of these agricultural practices on microbiomes are still unclear. In the present study, we compared the 18 bacterial communities of soil with different straw returning and tillage treatment combinations. The V3-V4 regions of the 16S ribosomal RNA were amplified and analyzed by high-throughput sequencing technology. The results showed that the bacterial communities were consistently dominated by Acidobacteria, Proteobacteria, Actinobacteria, and Chloroflexi. Short-term straw returning and tillage practices significantly altered the diversity, relative abundance and functions of the soil microbiome. Soil subjected to rotary tillage and straw returning (RTS) combination possessed the highest bacterial diversity and lowest ratio of G+/G- bacteria, indicating that RTS could be an efficient integrated management system to improve microbiome in the short term. Double verifications based on relative abundance and network analysis, revealed close relationships of Mycobacterium and Methylibium with RTS, indicating they could serve as biomarkers for RTS. Investigating microbial changes under different agricultural practices will provide valuable foundations for land sustainable utilization and increase crop yields.

关键词： tillage managements maize straw returning microbiome using

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Sufficient dimension reduction for classification using principal optimal transport direction 20

Sufficient dimension reduction for classification using prin...

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Proceedings of the 34th International Conference on Neural Information Processing Systems

作者： Cheng Meng Jun Yu Jingyi Zhang Ping Ma Wenxuan Zhong Center for Applied Statistics Institute of Statistics and Big Data Renmin University of China School of Mathematics and Statistics Beijing Institute of Technology Center for Statistical Science Tsinghua University Department of Statistics University of Georgia

ISBN: (纸本)9781713829546

Sufficient dimension reduction is used pervasively as a supervised dimension reduction approach. Most existing sufficient dimension reduction methods are developed for data with a continuous response and may have an unsatisfactory performance for the categorical response, especially for the binary-response. To address this issue, we propose a novel estimation method of sufficient dimension reduction subspace (SDR subspace) using optimal transport. The proposed method, named principal optimal transport direction (POTD), estimates the basis of the SDR subspace using the principal directions of the optimal transport coupling between the data respecting different response categories. The proposed method also reveals the relationship among three seemingly irrelevant topics, i.e., sufficient dimension reduction, support vector machine, and optimal transport. We study the asymptotic properties of POTD and show that in the cases when the class labels contain no error, POTD estimates the SDR subspace exclusively. Empirical studies show POTD outperforms most of the state-of-the-art linear dimension reduction methods.

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Null Stream Based Third-generation-ready Glitch Mitigation for Gravitational Wave Measurements

arXiv

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arXiv 2024年

作者： Narola, Harsh Wouters, Thibeau Negri, Luca Lopez, Melissa Dooney, Tom Cireddu, Francesco Wils, Milan Wong, Isaac C.F. Pang, Peter T.H. Janquart, Justin Samajdar, Anuradha Van Den Broeck, Chris Li, Tjonnie G.F. Utrecht University Princetonplein 1 Utrecht3584 CC Netherlands Nikhef National Institute for Subatomic Physics Science Park 105 Amsterdam1098 XG Netherlands Faculty of Science Open Universiteit Valkenburgerweg 177 Heerlen6419 AT Netherlands Centre for Cosmology Particle Physics and Phenomenology - CP3 Université Catholique de Louvain Louvain-La-Neuve B-1348 Belgium Royal Observatory of Belgium Avenue Circulaire 3 Uccle1180 Belgium Leuven Gravity Institute KU Leuven Celestijnenlaan 200D box 2415 Leuven3001 Belgium Department of Physics and Astronomy Laboratory for Semiconductor Physics KU Leuven LeuvenB-3001 Belgium STADIUS Center for Dynamical Systems Signal Processing and Data Analytics LeuvenB-3001 Belgium Dipartimento di Fisica "E. Fermi" Università di Pisa PisaI-56127 Italy

Gravitational Wave (GW) detectors routinely encounter transient noise bursts, known as glitches, which are caused by either instrumental or environmental factors. Due to their high occurrence rate, glitches can overlap with GW signals, as in the notable case of GW170817, the first detection of a binary neutron star merger. Accurate reconstruction and subtraction of these glitches is a challenging problem that must be addressed to ensure that scientific conclusions drawn from the data are reliable. This problem will intensify with third-generation observatories like the Einstein Telescope (ET) due to their higher detection rates of GWs and the longer duration of signals within the sensitivity band of the detectors. Robust glitch mitigation algorithms are, therefore, crucial for maximizing the scientific output of next-generation GW observatories. For the first time, we demonstrate how the null stream inherent in ET’s unique triangular configuration can be leveraged by state-of-the-art glitch characterization methodology to essentially undo the effect of glitches for the purpose of estimating the parameters of the source. The null stream based approach enables characterization and subtraction of glitches that occur arbitrarily close to the peak of the signal without any significant effect on the quality of parameter measurements, and achieves an order of magnitude computational speed-up compared to when the null stream is not available. By contrast, without the null stream, significant biases can occur in the glitch reconstruction, which deteriorate the quality of subsequent measurements of the source parameters. This demonstrates a clear edge which the null stream can offer for precision GW science in the ET era. © 2024, CC BY.

关键词： Gravitational effects

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Genomic reconstruction of the SARS CoV-2 epidemic in England (vol 600, pg 506, 2021)

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NATURE 2022年第7915期606卷 E18-E18页

作者： Vohringer, Harald S. Sanderson, Theo Sinnott, Matthew De Maio, Nicola Nguyen, Thuy Goater, Richard Schwach, Frank Harrison, Ian Hellewell, Joel Ariani, Cristina V. Goncalves, Sonia Jackson, David K. Johnston, Ian Jung, Alexander W. Saint, Callum Sillitoe, John Suciu, Maria Goldman, Nick European Molecular Biology Laboratory European Bioinformatics Institute EMBL-EBI Hinxton UK Wellcome Sanger Institute Hinxton UK The Francis Crick Institute London UK Public Health England London UK London School of Hygiene & Tropical Medicine London UK The Big Data Institute Nuffield Department of Medicine University of Oxford Oxford UK MRC Centre for Global Infectious Disease Analysis Jameel Institute for Disease and Emergency Analytics Imperial College London London UK Guy’s and St Thomas’ NHS Foundation Trust London UK Division for AI in Oncology German Cancer Research Centre DKFZ Heidelberg Germany

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Structural equation modelling of integrated healthcare delivery system KPIs on operational performance and physician outcomes

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AIP Conference Proceedings 2023年第1期2875卷

作者： V. Rema K. Sikdar Department of Business Analytics & Data Science Ramaiah Institute of Management Gate No. 8 General Sciences Building ’C’ Block M.S.R.I.T. Post Bengaluru - 560054 Karnataka India Department of Mathematics BMS Institute of Technology & Management Doddaballapura Main Road Yelahanka Bengaluru-560064 Karnataka India

Vertical integration of physician’s services with hospitals is shown to enhance the provider’s market power, availability of additional capacity and increase the quality of care. Research studies are limited in the direction of assessing how the various dimensions of integration of healthcare delivery system Key Performance Indicators (KPIs) affect the operational performance and impact physician outcomes. Within such a framework, the ability to analyze the key indicators has significant implications in improving healthcare operations. A covariance Structure Equation Model (SEM) of the effects of system integration mechanisms on operational performance and physician outcomes was formulated and validated by an empirical examination. The study includes 155 hospital administrators and physicians from Indian hospitals. The measurement indicators are categorized into dimensions of the market, patient-centric, behavioural and operational aspects whose impact on Integrated Healthcare Delivery KPIs and Physician Outcomes are analyzed. Confirmatory factor analysis and structural equation modelling is performed to validate hypotheses using R-Studio. The study demonstrates that higher efficiency in hospital care can be achieved by adopting appropriate integration strategies in operations.

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Artificial Intelligence and Statistical Techniques in Short-Term Load Forecasting: A Review

arXiv

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arXiv 2021年

作者： Nassif, Ali Bou Soudan, Bassel Azzeh, Mohammad Attilli, Imtinan AlMulla, Omar Department of Computer Engineering University of Sharjah Sharjah27272 United Arab Emirates Data Analytics and Cybersecurity Research Centre RISE University of Sharjah Sharjah27272 United Arab Emirates Department of Computer Engineering University of Sharjah Sharjah27272 United Arab Emirates Sustainable Energy & Power Systems Research Centre RISE University of Sharjah Sharjah27272 United Arab Emirates Department of Data Science Princess Sumaya University for Technology Amman11941 Jordan Department of Electrical Engineering University of Sharjah Sharjah27272 United Arab Emirates Distribution Control Centre Dubai Water and Electricity Authority Dubai United Arab Emirates

Electrical utilities depend on short-term demand forecasting to proactively adjust production and distribution in anticipation of major variations. This systematic review analyzes 240 works published in scholarly journals between 2000 and 2019 that focus on applying Artificial Intelligence (AI), statistical, and hybrid models to short-term load forecasting (STLF). This work represents the most comprehensive review of works on this subject to date. A complete analysis of the literature is conducted to identify the most popular and accurate techniques as well as existing gaps. The findings show that although Artificial Neural Networks (ANN) continue to be the most commonly used standalone technique, researchers have been exceedingly opting for hybrid combinations of different techniques to leverage the combined advantages of individual methods. The review demonstrates that it is commonly possible with these hybrid combinations to achieve prediction accuracy exceeding 99%. The most successful duration for short-term forecasting has been identified as prediction for a duration of one day at an hourly interval. The review has identified a deficiency in access to datasets needed for training of the models. A significant gap has been identified in researching regions other than Asia, Europe, North America, and Australia. Copyright © 2021, The Authors. All rights reserved.

关键词： Neural networks

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