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The risk of mpox importation and subsequent outbreak potential in Chinese mainland: a retrospective statistical modelling study

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Infectious Diseases of Poverty 2024年第1期13卷 63-73页

作者： Xiaowei Deng Yuyang Tian Junyi Zoul Juan Yang Kaiyuan Sun Hongjie Yu School of Public Health Key Laboratory of Public Health SafetyMinistry of EducationFudan UniversityShanghai 200032China Division of International Epidemiology and Population Studies Fogarty International CenterNational Institutes of HealthBethesdaMDUSA

Background The 2022-2023 mpox(monkeypox)outbreak has spread rapidly across multiple countries in the non-endemic region,mainly among men who have sex with men(MSM).In this study,we aimed to evaluate mpox's importation risk,border screening effectiveness and the risk of local outbreak in Chinese *** We estimated the risk of mpox importation in Chinese mainland from April 14 to September 11,2022 using the number of reported mpox cases during this multi-country outbreak from *** and the international air-travel data from Official Aviation *** constructed a probabilistic model to simulate the effectiveness of a border screening scenario during the mpox outbreak and a hypothetical scenario with less stringent quarantine *** we further evaluated the mpox outbreak potential given that undetected mpox infections were introduced into men who have sex with men,considering different transmissibility,population immunity and population *** We found that the reduced international air-travel volume and stringent border entry policy decreased about 94% and 69% mpox importations *** the quarantine policy,15-19% of imported infections would remain *** a case of mpox is introduced into active MSM population with almost no population immunity,the risk of triggering local transmission is estimated at 42%,and would rise to>95% with over six *** Our study demonstrates that the reduced international air-travel volume and stringent border entry policy during the COvID-19 pandemic reduced mpox importations ***,the risk could be sub-stantially higher with the recovery of air-travel volume to pre-pandemic *** could emerge as a public health threat for Chinese mainland given its large MSM community.

关键词： Mpox(Monkeypox) Importation risk International air travel statistical modelling Men who have sex with men

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Challenges in predictive modelling of chronic kidney disease:A narrative review

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World Journal of Nephrology 2024年第3期13卷 26-33页

作者： Sukhanshi Khandpur Prabhaker Mishra Shambhavi Mishra Swasti Tiwari Department of Molecular Medicine&Biotechnology Sanjay Gandhi Post Graduate Institute of Medical ScienceLucknow 226014Uttar PradeshIndia Department of Biostatistics and Health Informatics Sanjay Gandhi Post Graduate Institute of Medical SciencesLucknow 226014Uttar PradeshIndia Department of Statistics University of LucknowLucknow 226007Uttar PradeshIndia

The exponential rise in the burden of chronic kidney disease(CKD)worldwide has put enormous pressure on the *** modeling of CKD can ease this burden by predicting the future disease occurrence ahead of its *** are various regression methods for predictive modeling based on the distribution of the outcome ***,the accuracy of the predictive model depends on how well the model is developed by taking into account the goodness of fit,choice of covariates,handling of covariates measured on a continuous scale,handling of categorical covariates,and number of outcome events per predictor parameter or sample *** performance of a predictive model on an independent cohort is ***,there are several challenges in the predictive modeling of ***-specific methodological challenges hinder the development of a predictive model that is cost-effective and universally applicable to predict CKD *** this review,we discuss the advantages and challenges of various regression models available for predictive modeling and highlight those best for future CKD prediction.

关键词： Chronic kidney disease Predictive modelling Regression statistical modelling Methodology

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Fatigue behavior of high-entropy alloys： A review

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Science China(Technological Sciences) 2018年第2期61卷 168-178页

作者： CHEN PeiYong LEE Chanho WANG Shao-Yu SEIFI Mohsen LEWANDOWSKI John J DAHMEN Karin A JIA HaoLing XIE Xie CHEN BiLin YEH Jien-Wei TSAI Che-Wei YUAN Tao LIAW Peter K Department of Materials Science and Engineering The University of TennesseeKnoxville 37996，USA Department of Materials Science and Engineering Case Western UniversityCleveland 44106USA Department of Physics University of IllinoisUrbana 61801USA Department of Materials Science and Engineering 'National' Tsing Hua UniversityHsinchu 30013，Taiwan，China Department of Industry and System Engineering Ohio UniversityAthens 45701，USA

Fatigue failures cost approximately 4% of the United States' gross domestic product(GDP). The design of highly fatigue-resistant materials is always in demand. Different from conventional strategies of alloy design, high-entropy alloys(HEAs) are defined as materials with five or more principal elements, which could be solid solutions. This locally-disordered structure is expected to lead to unique fatigue-resistant properties. In this review, the studies of the fatigue behavior of HEAs during the last five years are summarized. The four-point-bending high-cycle fatigue coupled with statistical modelling, and the fatigue-crack-growth behavior of HEAs, are reviewed. The effects of sample defects and nanotwins-deformation mechanisms on four-point-bending high-cycle fatigue of HEAs are discussed in detail. The influence of stress ratio and temperature on fatigue-crack-growth characteristics of HEAs is also discussed. HEAs could exhibit comparable or greater fatigue properties, relative to conventional materials. Finally,the possible future work regarding the fatigue behavior of HEAs is suggested.

关键词： high-entropy alloys fatigue behaviour statistical modelling fatigue crack growth

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National-scale data-driven rainfall induced landslide susceptibility mapping for China by accounting for incomplete landslide data

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Geoscience Frontiers 2021年第6期12卷 262-276页

作者： Qigen Lin Pedro Lima Stefan Steger Thomas Glade Tong Jiang Jiahui Zhang Tianxue Liu Ying Wang Institute for Disaster Risk Management School of Geographical SciencesNanjing University of Information Science&TechnologyNanjing 210044China Department of Geography and Regional Research University of ViennaUniversitätsstraße 71010 ViennaAustria Institute for Earth Observation Eurac ResearchViale Druso 139100 Bolzano-BozenItaly Key Laboratory of Environmental Change and Natural Disaster of Ministry of Education/Academy of Disaster Reduction and Emergency Management Faculty of Geographical ScienceBeijing Normal UniversityBeijing 100875China

China is one of the countries where landslides caused the most fatalities in the last decades. The threat that landslide disasters pose to people might even be greater in the future, due to climate change and the increasing urbanization of mountainous areas. A reliable national-scale rainfall induced landslide susceptibility model is therefore of great relevance in order to identify regions more and less prone to landsliding as well as to develop suitable risk mitigating strategies. However, relying on imperfect landslide data is inevitable when modelling landslide susceptibility for such a large research area. The purpose of this study is to investigate the influence of incomplete landslide data on national scale statistical landslide susceptibility modeling for China. In this context, it is aimed to explore the benefit of mixed effects modelling to counterbalance associated bias propagations. Six influencing factors including lithology, slope,soil moisture index, mean annual precipitation, land use and geological environment regions were selected based on an initial exploratory data analysis. Three sets of influencing variables were designed to represent different solutions to deal with spatially incomplete landslide information: Set 1(disregards the presence of incomplete landslide information), Set 2(excludes factors related to the incompleteness of landslide data), Set 3(accounts for factors related to the incompleteness via random effects). The variable sets were then introduced in a generalized additive model(GAM: Set 1 and Set 2) and a generalized additive mixed effect model(GAMM: Set 3) to establish three national-scale statistical landslide susceptibility models: models 1, 2 and 3. The models were evaluated using the area under the receiver operating characteristics curve(AUROC) given by spatially explicit and non-spatial cross-validation. The spatial prediction pattern produced by the models were also investigated. The results show that the landslide inve

关键词： statistical modelling Landslide susceptibility Generalized additive model Mixed-effects model China

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statistical Superposition of Crosstalk Effects in Cable Bundles

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China Communications 2013年第11期10卷 119-128页

作者： Diego Bellan Sergio A.Pignari Department of Electronics Information and Bioengineering Politecnico di Milano

This paper deals with the analytical derivation of phasor-domain statistical properties of crosstalk in random wire cables due to the superposition of several sources of electromagnetic *** this study,statistical characterization of crosstalk in cable bundles,which is available in literature for the case of one source of interference,is extended to the case of several sources operating *** superposition of crosstalk effects is analysed in statistical terms,also taking into account the correlation between crosstalk contributions.A further random contribution,which is included in the proposed statistical model,is given by the phase relationship between the sources of *** approximate expressions for the crosstalk mean value,variance,and probability density function are derived as functions of the cable bundle features and sources.

关键词： crosstalk multiconductor transmi-ssion lines cable bundles statistical modelling

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Prediction of office building electricity demand using artificial neural network by splitting the time horizon for different occupancy rates

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能源与人工智能(英文) 2021年第3期5卷 159-170页

作者： Si Chen Yaxing Ren Daniel Friedrich Zhibin Yu James Yu James Watt School of Engineering the University of GlasgowGlasgow G128QQUK School of Engineering The University of EdinburghEdinburgh EH93FBUK SP Distribution PLC Glasgow G720HTUK

Due to the impact of occupants’activities in buildings,the relationship between electricity demand and ambient temperature will show different trends in the long-term and short-term,which show seasonal variation and hourly variation,*** makes it difficult for conventional data fitting methods to accurately predict the long-term and short-term power demand of buildings at the same *** order to solve this problem,this paper proposes two approaches for fitting and predicting the electricity demand of office *** first proposed approach splits the electricity demand data into fixed time periods,containing working hours and non-working hours,to reduce the impact of occupants’*** finding the most sensitive weather variable to non-working hour electricity demand,the building baseload and occupant activities can be predicted *** second proposed approach uses the artificial neural network(ANN)and fuzzy logic techniques to fit the building baseload,peak load,and occupancy rate with multi-variables of weather *** this approach,the power demand data is split into a narrower time range as no-occupancy hours,full-occupancy hours,and fuzzy hours between them,in which the occupancy rate is varying depending on the time and weather *** proposed approaches are verified by the real data from the University of Glasgow as a case *** simulation results show that,compared with the traditional ANN method,both proposed approaches have less root-mean-square-error(RMSE)in predicting electricity *** addition,the proposed working and non-working hour based regression approach reduces the average RMSE by 35%,while the ANN with fuzzy hours based approach reduces the average RMSE by 42%,comparing with the traditional power demand prediction *** addition,the second proposed approach can provide more information for building energy management,including the predicted baseload,peak load,and occupancy rate,without r

关键词： Building energy Electricity demand prediction statistical modelling Artificial neural network Occupancy rate

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Sensitivity analysis to reduce duplicated features in ANN training for district heat demand prediction

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能源与人工智能(英文) 2020年第2期2卷 63-73页

作者： Si Chen Yaxing Ren Daniel Friedrich Zhibin Yu James Yu James Watt School of Engineering The University of GlasgowGlasgow G128QQUK School of Engineering The University of EdinburghEdinburgh EH93FBUK SP Distribution PLC Glasgow G720HTUK

Artificial neural network(ANN)has become an important method to model the nonlinear relationships between weather conditions,building characteristics and its heat *** to the large amount of training data re-quired for ANN training,data reduction and feature selection are important to simplify the ***,in building heat demand prediction,many weather-related input variables contain duplicated *** paper develops a sensitivity analysis approach to analyse the correlation between input variables and to detect the variables that have high importance but contain duplicated *** proposed approach is validated in a case study that predicts the heat demand of a district heating network containing tens of buildings at a university *** results show that the proposed approach detected and removed several unnecessary input variables and helped the ANN model to reduce approximately 20%training time compared with the traditional methods while maintaining the prediction *** indicates that the approach can be applied for analysing large num-ber of input variables to help improving the training efficiency of ANN in district heat demand prediction and other applications.

关键词： Building heat demand prediction statistical modelling Artificial neural network Sensitivity analysis Feature selection

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A COMPLEMENTARY APPROACH TO COMPUTER-AIDED TRANSCRIPTION: SYNERGY OF statistical-BASED AND KNOWLEDGE DISCOVERY PARADIGMS

A COMPLEMENTARY APPROACH TO COMPUTER-AIDED TRANSCRIPTION: SY...

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6～(th) International Conference on Spoken Language Processing

作者： Benjamin K.T’sou Tom B.Y.Lai Language Information Sciences Research Centre City University of Hong Kong Tat Chee Avenue Kowloon Tong Hong Kong SAR China Language Information Sciences Research Centre City University of Hong Kong Tat Chee Avenue Kowloon Tong Hong Kong SAR China

＜正＞ The recent implementation of legal bilingualism necessitates the development of a Chinese Computer-Aided Transcription （CAT） system to product Chinese court proceedings conducted in Cantonese. The transcription system converts transcription shorthand codes into Chinese text, i.e., from phonetic to textual representation of the language. Cantonese and Mandarin Chinese have many homophonous characters. The main challenge lies in the resolution of the severe ambiguity of the conversion. N-gram statistical model is incorporated to estimate the most probable character string during conversion. Domain- specific corpora have been compiled to support the statistical computation. With additional enhancement features, the CAT system delivers a transcription accuracy of 96%. An intelligent error detection tool is built into the system to facilitate the manual correction of the remaining errors. Using decision tree algorithm and a range of text and linguistic attributes, the system can effectively alert the users to possible errors.

关键词： Speech to Text statistical modelling Cantonese Chinese

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Progress in the statistical analysis of avian moult

Progress in the statistical analysis of avian moult

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23rd International Ornithological Congress

作者： Leslie G.Underhill Avian Demography Unit University of Cape Town Rondebosch 7701. South Africa

＜正＞ Feathers are unique to birds. Besides their insulative properties, they are critical for flight. Their replacement, through the process of moult, is therefore an important part of the annual cycle of birds. In comparison with components of the annual cycle such as breeding and migration, moult remains a relatively poorly investigated aspect of the life history of birds. In part, this is due to a lack of a set of standardised and quantitative tools to

关键词： moult statistical modelling

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