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A general semi-parametric elliptical distribution model for semi-supervised learning

Journal of Nonparametric Statistics 2025年第2期37卷

作者： Chin-Tsang Chiang Sheng-Hsin Fan Ming-Yueh Huang Jen-Chieh Teng Alvin Lim a Institute of Applied Mathematical Sciences National Taiwan University Taipei Taiwan b Department of Mathematics National Taiwan University Taipei Taiwan c Institute of Statistical Science Academia Sinica Taipei Taiwan d Data Science Degree Program National Taiwan University Taipei Taiwan e Data Science Department Measured Inc. Austin TX USAf Goizueta Business School Emory University Atlanta GA USA

AbSTRACTThis research proposes a novel semi-parametric elliptical distribution model for application in semi-supervised learning tasks. We use labelled and unlabelled data to develop a pseudo maximum likelihood method for estimation and classification. The proposed estimator outperforms the estimator based solely on labelled data and achieves the semi-parametric efficiency bound with a suitable size of unlabelled data. We efficiently maximise the objective function by utilising low-dimensional groupwise pseudo-likelihood functions in a block coordinate descent manner while ensuring numerical stability and convergence through appropriate bandwidth selectors and initial parameter estimates. Additionally, the study comprehensively investigates the impact of labelled and unlabelled data on the pseudo maximum likelihood estimator and classifier. Simulation studies and empirical data applications illustrate the superiority of our methodology.

关键词： elliptical distribution posterior group probability pseudo maximum likelihood method semi-parametric efficiency semi-supervised learning

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Dynamic channel estimation-aware routing protocol in mobile cognitive radio networks for smart IIoT applications

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Digital Communications and Networks 2023年第2期9卷 367-382页

作者： Qusay M.Salih Md Arafatur Rahman A.Taufiq Asyhari Muhammad Kamran Naeem Mohammad Patwary Ryan Alturki Mohammed Abdulaziz Ikram Faculty of Computing Universiti Malaysia Pahang26300GambangPahangMalaysia School of Engineering Computing and Mathematical SciencesUniversity of WolverhamptonUK Data Science Program Monash UniversityIndonesiaand Birmingham City UniversityB47XGUK Department of Information Science College of Computer and Information SystemsUmm Al-Qura UniversitySaudi Arabia Computer Science Department Al Jumoum University CollegeUmm Al-Qura UniversitySaudi Arabia

Cognitive Radio Networks(CRNs)have become a successful platform in recent years for a diverse range of future systems,in particularly,industrial internet of things(IIoT)*** order to provide an efficient connection among IIoT devices,CRNs enhance spectrum utilization by using licensed ***,the routing protocol in these networks is considered one of the main problems due to node mobility and time-variant channel ***,the channel selection for routing protocol is indispensable in CRNs to provide an adequate adaptation to the Primary User(PU)activity and create a robust routing *** study aims to construct a robust routing path by minimizing PU interference and routing delay to maximize throughput within the IIoT ***,a generic routing framework from a cross-layer perspective is investigated that intends to share the information resources by exploiting a recently proposed method,namely,Channel Availability ***,a novel cross-layer-oriented routing protocol is proposed by using a time-variant channel estimation *** protocol combines lower layer(Physical layer and data Link layer)sensing that is derived from the channel estimation ***,it periodically updates and stores the routing table for optimal route ***,in order to achieve higher throughput and lower delay,a new routing metric is *** evaluate the performance of the proposed protocol,network simulations have been conducted and also compared to the widely used routing protocols,as a *** simulation results of different routing scenarios demonstrate that our proposed solution outperforms the existing protocols in terms of the standard network performance metrics involving packet delivery ratio(with an improved margin of around 5–20%approximately)under varying numbers of PUs and cognitive users in Mobile Cognitive Radio Networks(MCRNs).Moreover,the cross-layer routing protocol successfully achiev

关键词： Channel selection Cross-layer design Mobile cognitive radio networks Routing protocol IIoT applications

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Lsh, chromatin remodeling family member, modulates genome-wide cytosine methylation patterns at nonrepeat sequences (vol 108, pg 5626, 2011)

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PROCEEDINGS OF THE NATIONAL ACADEMY OF scienceS OF THE UNITED STATES OF AMERICA 2011年第37期108卷 15535-15535页

作者： Tao, Yongguang Xi, Sichuan Shan, Jigui Maunakea, Alika Che, Anney briones, Victorino Lee, Eunice Y. Geiman, Theresa Huang, Jiaqiang Stephens, Robert Leighty, Robert M. Zhao, Keji Muegge, Kathrin [a]Basic Science Program Laboratory of Cancer Prevention [b]Advanced Biomedical Computing Center and [d]Data Management Services Science Applications International Corporation Frederick Inc. National Cancer Institute Frederick Frederick MD 21702 and [c]Laboratory of Molecular Immunology National Heart Lung and Blood Institute National Institutes of Health Bethesda MD 20817

DNA methylation is critical for normal development and plays important roles in genome organization and transcriptional regulation. Although DNA methyltransferases have been identified, the factors that establish and contribute to genome-wide methylation patterns remain elusive. Here, we report a high-resolution cytosine methylation map of the murine genome modulated by Lsh, a chromatin remodeling family member that has previously been shown to regulate CpG methylation at repetitive sequences. We provide evidence that Lsh also controls genome-wide cytosine methylation at nonrepeat sequences and relate those changes to alterations in H4K4me3 modification and gene expression. Deletion of Lsh alters the allocation of cytosine methylation in chromosomal regions of 50 kb to 2 Mb and, in addition, leads to changes in the methylation profile at the 5' end of genes. Furthermore, we demonstrate that loss of Lsh promotes--as well as prevents--cytosine methylation. Our data indicate that Lsh is an epigenetic modulator that is critical for normal distribution of cytosine methylation throughout the murine genome.

关键词： methylated DNA immunoprecipitation chIP-sequencing epigenetics

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Core variables for real-world clinicogenomic data collection in precision oncology

ESMO Real World Data and Digital Oncology

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ESMO Real World data and Digital Oncology 2025年 7卷 100117-100117页

作者： R. Dienstmann A. Hackshaw J.-Y. blay C. Le Tourneau OC Precision Medicina Oncoclínicas & Co São Paulo Brazil PhD Program Doctoral School University of Vic—Central University of Catalonia Barcelona Spain Oncology Data Science Vall d’Hebron Institute of Oncology Barcelona Spain Cancer Research UK and UCL Cancer Trials Centre University College London London UK Centre Léon Bérard and Université Claude Bernard Lyon France Institut Curie Department of Drug Development and Innovation (D3i) Paris-Saclay University Paris France

background Precision oncology evidence gaps may be bridged using real-world clinicogenomic data; however, current limitations compromise real-world data collection and evidence generation. We aimed to define a set of precision oncology core variables that can aid in fit-for-purpose real-world data collection to be used for a range of purposes and by various stakeholders based on the approach adopted when designing the WAYFIND-R registry (NCT04529122). Materials and methods A panel of precision oncology experts created a list of variables based on standard dictionaries and vocabularies, which was aligned with the European Medical Agency’s draft guidelines for registry-based studies. A list of core variables was selected from the initial broad list of variables. Results The initial overall list (∼500 variables) was consolidated to ∼150 variables that covered the entirety of the patient journey in oncology. The panel gave highest priority to patient demographics, socioeconomic information and comorbidities, cancer details, molecular information, particularly predictive biomarkers in routine use and next-generation sequencing technical aspects, systemic cancer therapies and other treatments, outcome assessments and survival outcomes. Conclusions The core oncology variables represent a harmonized list of key clinicogenomic data elements that can be collected during a patient’s journey in oncology and leveraged for their primary intended purpose of molecular tumor board decision making, and might be used for further secondary research purposes, if legal requirements allow. Definition of this list of core variables will help generate evidence from research- or regulatory-oriented precision oncology studies by ensuring synergy, dataset connectivity, and interoperability across different data.

关键词： precision oncology real-world data solid tumors next-generation sequencing molecular tumor boards

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Should workers be physically active after work?Associations of leisure-time physical activity with cardiovascular and all-cause mortality across occupational physical activity levels-An individual participant data meta-analysis

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Journal of Sport and Health science 2025年第1期14卷 49-60页

作者： bart Cillekens Pieter Coenen Maaike A.Huysmans Andreas Holtermann Richard P.Troiano Paul Jarle Mork Steinar Krokstad Els Clays Dirk De bacquer Mette Aadahl Line Lund Kårhus Anette Sjøl Lars bo Andersen Jussi Kauhanen Ari Voutilainen Richard Pulsford Emmanuel Stamatakis Uri Goldbourt Annette Peters barbara Thorand Annika Rosengren Lena björck Kyle Sprow Kristin Franzon Miguel Rodriguez-barranco Leila Luján-barroso Lars Alfredsson Martin bahls Till Ittermann Miriam Wanner Matthias bopp Jacob Louis Marott Peter Schnohr børge G.Nordestgaarda Knut Eirik Dalene Ulf Ekelund Johan Clausen Magnus T.Jensen Christina bjørk Petersen Niklas Krause Jos Twisk Willem van Mechelen Allard J.van der beek Department of Public and Occupational Health Amsterdam Public Health Research InstituteVrije Universiteit AmsterdamAmsterdam UMCAmsterdam 1081 HVthe Netherlands National Research Centre for the Working Environment Copenhagen 2100Denmark Department of Sports Science and Clinical Biomechanics University of Southern DenmarkOdense 5230Denmark U.S.Public Health Service ArlingtonVA 22201USA Department of Public Health and Nursing Norwegian University of Science and TechnologyTrondheim 8905Norway Levanger Hospital Nord-Trøndelag Hospital TrustLevanger 7601Norway Department of Public Health and Primary Care Ghent UniversityGhent 9000Belgium Center for Clinical Research and Prevention Bispebjerg and Frederiksberg HospitalFrederiksberg 2000Denmark The Capital Region of Denmark Copenhagen 1172Denmark Western Norway University of Applied Sciences Faculty of EducationArts and SportsSogndal 5414Norway Institute of Public Health and Clinical Nutrition University of Eastern FinlandKuopio 1627Finland Faculty of Health and Life Sciences University of ExeterExeter EX12LUUK Mackenzie Wearables Research Hub Charles Perkins CentreThe University of SydneyNSW 2050Australia School of Health Sciences Faculty of Medicine and HealthThe University of SydneyNSW 2050Australia Sackler Medical faculty in Tel Aviv University Tel Aviv 6997801Israel Institute of Epidemiology Helmholtz Zentrum MünchenGerman Research Center for Environmental HealthNeuherberg 85764Germany German Centre for Cardiovascular Research(DZHK e.V.) partner site Munich Heart AllianceMunich 80636Germany Institute for Medical Information Processing Biometryand Epidemiology(IBE)Pettenkofer School of Public HealthFaculty of MedicineLudwig-Maximilians-UniversitätMunich 80636Germany Institute of Medicine Department of Molecular and Clinical MedicineSahlgrenska AcademyUniversity of GothenburgGothenburg 40530Sweden Region Västra Götaland Sahlgrenska University HospitalDepartment of Medicine Geriatrics and Emergency Medicine/ÖstraGothenb

background There is insufficient evidence to provide recommendations for leisure-time physical activity among workers across various occupational physical activity *** study aimed to assess the association of leisure-time physical activity with cardiovascular and all-cause mortality across occupational physical activity *** This study utilized individual participant data from 21 cohort studies,comprising both published and unpublished *** criteria included individual-level data on leisure-time and occupational physical activity(categorized as sedentary,low,moderate,and high)along with data on all-cause and/or cardiovascular mortality.A 2-stage individual participant data meta-analysis was conducted,with separate analysis of each study using Cox proportional hazards models(Stage 1).These results were combined using random-effects models(Stage 2).Results Higher leisure-time physical activity levels were associated with lower all-cause and cardiovascular mortality risk across most occupational physical activity levels,for both males and *** males with sedentary work,high compared to sedentary leisure-time physical activity was associated with lower all-cause(hazard ratios(HR)=0.77,95%confidence interval(95%CI):0.70-0.85)and cardiovascular mortality(HR=0.76,95%CI:0.66-0.87)*** males with high levels of occupational physical activity,high compared to sedentary leisure-time physical activity was associated with lower all-cause(HR=0.84,95%CI:0.74-0.97)and cardiovascular mortality(HR=0.79,95%CI:0.60-1.04)risk,while HRs for low and moderate levels of leisure-time physical activity ranged between 0.87 and 0.97 and were not statistically *** females,most effects were similar but more imprecise,especially in the higher occupational physical activity *** Higher levels of leisure-time physical activity were generally associated with lower mortality ***,results for workers with moderate and high

关键词： Mortality Individual participant data Physical activity paradox Job demands

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Understanding uncertainty in deep learning builds confidence

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Artificial Intelligence in the Life sciences 2022年 2卷

作者： bajorath, Jürgen Department of Life Science Informatics and Data Science B-IT LIMES Program Unit Chemical Biology and Medicinal Chemistry Rheinische Friedrich-Wilhelms-Universität Friedrich-Hirzebruch-Allee 5/6 Bonn D-53115 Germany

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The temperature change of regional difference in Anhui province, China

The temperature change of regional difference in Anhui provi...

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Remote Sensing and Modeling of Ecosystems for Sustainability VI

作者： Liu, Ke Gao, Zhiqiang Gao, Wei Joint Laboratory for Environmental Remote Sensing and Data Assimilation ECNU CEODE Shanghai 200062 China Key Laboratory of Geo-Information Science Ministry of Education East China Normal University Shanghai 200062 China Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China USDA UV-B Monitoring and Research Program Natural Resource Ecology Laboratory Colorado State University Fort Collins CO United States

ISBN: (纸本)9780819477446

Three regions, Huaibei, Jianghuai, Jiangnan, are divided based on the topography, climatic characteristics, as well as surface temperature from 1957 to 2006 of 16 stations in Anhui province. The change with the year, season and month is analyzed in Anhui province and three areas. Some conclusions are as follows. Anhui province had the lowest temperature in 1980s, but after that the temperature raised step by step. The warming fastest region is Jianghuai. The same pace of warming is in three areas: the greatest warming in spring, then that in autumn, the last in summer. It is warming remarkable in February and the cooling time occurs in July and December. but the fluctuation in three areas is different in some details. The heat island in Hefei is also researched. It suggests that the urban heat island intensity in 1990s in Hefei was the maximum, and then weakened. At the meanwhile, the summer is cooling and the winter is warming in Hefei. © 2009 SPIE.

关键词： Surface temperature

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Application of MODIS data for assessment of evapotranspiration and drought in Northern China

Application of MODIS data for assessment of evapotranspirati...

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Remote Sensing and Modeling of Ecosystems for Sustainability VI

作者： Liu, Chaoshun Gao, Wei Gao, Zhiqiang Shi, Runhe Joint Laboratory for Environmental Remote Sensing and Data Assimilation ECNU CEODE Shanghai 200062 China Key Laboratory of Geo-Information Science Ministry of Education East China Normal University Shanghai 200062 China USDA UV-B Monitoring and Research Program Natural Resource Ecology Laboratory Colorado State University Fort Collins CO United States Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China

ISBN: (纸本)9780819477446

The objectives of this study are to explore the performance of MODIS remote sensing data in large scale ET and drought mapping based on physical consideration of land surface energy balance. It was revealed from the analysis results that ET derived from MODIS data was in very good agreement with the measured by lysimeter with the consistency index of 0.917, correlation coefficient of 0.872, and daily relative error of -11.34%. Further, regional water stress index (RWSI) was derived from ET by remote sensing demonstrated a strong correlation with field measured soil moisture and is more significantly correlative to mean 0-20cm soil moisture. The case study conducted for fall drought monitoring in North China during years 2005-2006 indicated that the spatial distribution of drought conditions evaluated from RWSI was in good agreement with actual precipitation and drought status. As the efficient method on the basis of relative soil moisture and ET by MODIS data only with Yucheng station measurements, yet more extensive validation with field measurements at regional scale is necessary to be done to discriminate the effects and the accuracy of the proposed RWSI method. © 2009 SPIE.

关键词： Drought

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Atmospheric correction model of Landsat images

Atmospheric correction model of Landsat images

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Remote Sensing and Modeling of Ecosystems for Sustainability VI

作者： Liu, Chaoshun Gao, Wei Gao, Zhiqiang Shi, Runhe Joint Laboratory for Environmental Remote Sensing and Data Assimilation ECNU CEODE Shanghai 200062 China Key Laboratory of Geo-information Science Ministry of Education East China Normal University Shanghai 200062 China USDA UV-B Monitoring and Research Program Natural Resource Ecology Laboratory Colorado State University Fort Collins CO United States Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China

ISBN: (纸本)9780819477446

An operational atmosphere correction algorithm based on dark object method and the look up table which founded by MODTRAN4 model was introduced for Landsat images herein. The information of the satellite remote sensing images was used to support the atmosphere correction. The algorithm was applied to the Landsat ETM+ imagery and the comparison results of before and after atmospheric correction show that the impact of Landsat imagery caused by molecules, water vapor, ozone, and aerosol particles in the atmosphere was reduced effectively after the correction. This new atmospheric correction algorithm is effective and capable of retrieving surface reflectance accurately. The surface reflectivity was retrieved exactly to help remote sensing information extraction and thematic interpretation. © 2009 SPIE.

关键词： Table lookup

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Functional Connectome-based Predictive Modeling in Autism

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bIOLOGICAL PSYCHIATRY 2022年第8期92卷 626-642页

作者： Horien, Corey Floris, Dorothea L. Greene, Abigail S. Noble, Stephanie Rolison, Max Tejavibulya, Link O'Connor, David McPartland, James C. Scheinost, Dustin Chawarska, Katarzyna Lake, Evelyn M. R. Constable, R. Todd [a]Interdepartmental Neuroscience Program Yale School of Medicine New Haven Connecticut [b]MD-PhD Program Yale School of Medicine New Haven Connecticut [c]Department of Pediatrics Yale School of Medicine New Haven Connecticut [d]Department of Neurosurgery Yale School of Medicine New Haven Connecticut [e]Department of Radiology and Biomedical Imaging Yale School of Medicine New Haven Connecticut [f]Department of Biomedical Engineering Yale University New Haven Connecticut [g]Department of Psychology Yale University New Haven Connecticut [h]Department of Statistics and Data Science Yale University New Haven Connecticut [i]Yale Child Study Center New Haven Connecticut [j]Methods of Plasticity Research Department of Psychology University of Zürich Zurich Switzerland [k]Donders Center for Brain Cognition and Behavior Radboud University Nijmegen Nijmegen The Netherlands

Autism is a heterogeneous neurodevelopmental condition, and functional magnetic resonance imaging-based studies have helped advance our understanding of its effects on brain network activity. We review how predictive modeling, using measures of functional connectivity and symptoms, has helped reveal key insights into this condition. We discuss how different prediction frameworks can further our understanding of the brain-based features that underlie complex autism symptomatology and consider how predictive models may be used in clinical settings. Throughout, we highlight aspects of study interpretation, such as data decay and sampling biases, that require consideration within the context of this condition. We close by suggesting exciting future directions for predictive modeling in autism.

关键词： Clinical translation Development Fingerprinting Individual differences Machine learning Resting-state fMRI

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