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Applying Machine Learning Approach to Explore Childhood Circumstances and Self-Rated Health in Old Age-China and the US,2020-2021

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China CDC weekly 2024年第11期6卷 213-218,I0008-I0013页

作者： Shutong Huo Derek Feng Thomas M.gill Xi Chen Department of Health Society&BehaviorPublic HealthUniversity of CaliforniaIrvineCAUSA Department of Statistics and Data Science Yale UniversityNew HavenCTUS Department of Internal Medicine Yale School of MedicineNew HavenCTUS Department of Health Policy and Management Yale School of Public HealthNew HavenCTUS Department of Economics Yale UniversityNew HavenCTUS.

Introduction:Childhood circumstances impact senior health,prompting the introduction of machine learning methods to assess their individual and collective contributions to senior ***:Using health and retirement study(HRS)and China Health and Retirement Longitudinal Study(CHARLS),we analyzed 2,434 American and 5,612 Chinese participants aged 60 and *** inference trees and forests were employed to estimate the influence of childhood circumstances on self-rated health(SRH).Results:The conventional method estimated higher inequality of opportunity(IOP)values in both China(0.039,accounting for 22.67%of the total Gini coefficient 0.172)and the US(0.067,accounting for 35.08%of the total Gini coefficient 0.191).In contrast,the conditional inference tree yielded lower estimates(China:0.022,accounting for 12.79%of 0.172;US:0.044,accounting for 23.04%of 0.191),as did the forest(China:0.035,accounting for 20.35%of 0.172;US:0.054,accounting for 28.27%of 0.191).Childhood health,financial status,and regional differences were key determinants of senior *** conditional inference forest consistently outperformed others in predictive accuracy,as demonstrated by lower out-of-sample mean squared error(MSE).Discussion:The findings emphasize the need for early-life interventions to promote health equity in aging *** learning showcases the potential in identifying contributing factors.

关键词： collective inequality estimates

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Design of a Lightweight Compressed Video Stream-Based Patient Activity Monitoring System

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Computers, Materials & Continua 2024年第1期78卷 1253-1274页

作者： Sangeeta Yadav Preeti Gulia Nasib Singh gill Piyush Kumar Shukla Arfat Ahmad Khan Sultan Alharby Ahmed Alhussen Mohd Anul Haq Department of Computer Science&Applications Maharshi Dayanand UniversityRohtak124001India University Institute of Technology Rajiv Gandhi Proudyogiki VishwavidyalayaBhopal462033India Department of Computer Science College of ComputingKhon Kaen UniversityKhon Kaen40002Thailand Department of Computer Science College of Computer and Information SciencesMajmaah UniversityAl Majmaah11952Kingdom of Saudi Arabia Department of Computer Engineering College of Computer and Information SciencesMajmaah UniversityAl Majmaah11952Kingdom of Saudi Arabia

Inpatient falls from beds in hospitals are a common *** falls may result in severe *** problem can be addressed by continuous monitoring of patients using *** advancements in deep learning-based video analytics have made this task of fall detection more effective and *** with fall detection,monitoring of different activities of the patients is also of significant concern to assess the improvement in their *** computation-intensive models are required to monitor every action of the patient *** requirement limits the applicability of such ***,to keep the model lightweight,the already designed fall detection networks can be extended to monitor the general activities of the patients along with the fall *** by the same notion,we propose a novel,lightweight,and efficient patient activity monitoring system that broadly classifies the patients’activities into fall,activity,and rest classes based on their *** whole network comprises three sub-networks,namely a Convolutional Neural Networks(CNN)based video compression network,a Lightweight Pose Network(LPN)and a Residual Network(ResNet)Mixer block-based activity recognition *** compression network compresses the video streams using deep learning networks for efficient storage and retrieval;after that,LPN estimates human ***,the activity recognition network classifies the patients’activities based on their *** proposed system shows an overall accuracy of approx.99.7% over a standard dataset with 99.63% fall detection accuracy and efficiently monitors different events,which may help monitor the falls and improve the inpatients’health.

关键词： Fall detection activity recognition human pose estimation accuracy

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基于CWT-CARS-CNN综合方法的矿区土壤煤源碳质量分数高光谱估测

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河南理工大学学报（自然科学版） 2024年第3期43卷 91-100页

作者：聂小军洪雯雯 gill Ammara 于海洋陈晓东河南理工大学测绘与国土信息工程学院河南焦作454000

目的目前,尚无可靠方法定量识别土壤中煤源碳,为此,方法采集焦作矿区耕地土壤,配制249个不同质量分数的煤源碳土壤样品,利用ASD FieldSpec4获取样品光谱数据,采用连续小波变换(continuous wavelet transform,CWT)-竞争性自适应重加权采... 详细信息

目的目前,尚无可靠方法定量识别土壤中煤源碳,为此,方法采集焦作矿区耕地土壤,配制249个不同质量分数的煤源碳土壤样品,利用ASD FieldSpec4获取样品光谱数据,采用连续小波变换(continuous wavelet transform,CWT)-竞争性自适应重加权采样(competitive adaptive reweighted sampling,CARS)-卷积神经网络(convolutional neural networks,CNN)方法估测土壤中煤源碳质量分数,并对比CWT-CARS-CNN方法与传统光谱指数法构建的煤源碳估测模型估测效果,检验CWT-CARS-CNN估测模型的适用性。结果结果表明:350~2500 nm波段内,煤与土壤光谱特征截然不同,含煤土壤样品光谱反射率随煤源碳质量分数增加而降低;CWT方法提高了光谱对土壤煤源碳的敏感性,CARS方法提取的煤源碳敏感波段数量明显增加,基于CWT-CARS-CNN方法的煤源碳质量分数估测模型精度明显高于传统光谱指数法的;以L8分解尺度构建的CWT-CARS-CNN模型精度最高,验证集R2=0.9993,RPD=40.3081。结论基于CWT-CARS-CNN的高光谱估测方法能较准确地估测矿区不同土地利用类型下土壤中的煤源碳质量分数,可为“双碳”背景下矿区土壤碳固存与肥力评估提供参考。

关键词：煤源碳碳固存高光谱估测深度学习矿区土壤

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A Comprehensive Review of High Throughput Phenotyping and Machine Learning for Plant Stress Phenotyping

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Phenomics 2022年第3期2卷 156-183页

作者： taqdeer.gill Simranveer K.gill Dinesh K.Saini Yuvraj Chopra Jason P.de Koff Karansher S.Sandhu Department of Agricultural and Environmental Sciences Tennessee State UniversityNashvilleTN 37209USA College of Agriculture Punjab Agricultural UniversityLudhianaPunjab 141004India Department of Plant Breeding and Genetics Punjab Agricultural UniversityLudhianaPunjab 141004India Department of Crop and Soil Sciences Washington State UniversityPullmanWA 99163USA

During the last decade,there has been rapid adoption of ground and aerial platforms with multiple sensors for phenotyping various biotic and abiotic stresses throughout the developmental stages of the crop *** throughput phenotyping(HTP)involves the application of these tools to phenotype the plants and can vary from ground-based imaging to aerial phenotyping to remote *** of these HTP tools has tried to reduce the phenotyping bottleneck in breeding programs and help to increase the pace of genetic *** specifically,several root phenotyping tools are discussed to study the plant’s hidden half and an area long ***,the use of these HTP technologies produces big data sets that impede the inference from those *** learning and deep learning provide an alternative opportunity for the extraction of useful information for making *** are interdisciplinary approaches for data analysis using probability,statistics,classification,regression,decision theory,data visualization,and neural networks to relate information extracted with the phenotypes *** techniques use feature extraction,identification,classification,and prediction criteria to identify pertinent data for use in plant breeding and pathology *** review focuses on the recent findings where machine learning and deep learning approaches have been used for plant stress phenotyping with data being collected using various HTP *** have provided a comprehensive overview of different machine learning and deep learning tools available with their potential advantages and ***,this review provides an avenue for studying various HTP platforms with particular emphasis on using the machine learning and deep learning tools for drawing legitimate ***,we propose the conceptual challenges being faced and provide insights on future perspectives for managing those issues.

关键词： Biotic and abiotic stresses Deep learning Ground-based imaging High throughput phenotyping Machine learning Unmanned aerial vehicle

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Identification of Rhizobia Isolated from Nodules of Mexican Commercial Soybean Varieties

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American Journal of Plant Sciences 2024年第1期15卷 29-45页

作者： Cecilia Vázquez Rodríguez Lourdes Vital López Jesús Gerardo García Olivares Homar Rene gill Langarica Laboratorio de Biotecnología Vegetal Centro de Biotecnología Genómica Instituto Politécnico Nacional Reynosa México Carrera de Mantenimiento Industrial Universidad Tecnológica de Tamaulipas Norte Universidad Tecnológica Reynosa México

Rhizobia, crucial for nitrogen fixation in leguminous plants, play a vital role in soybean cultivation. This study, conducted in Mexico, a major soybean importer, aimed to identify bacteria from nodules of five soybean varieties in high-production regions. Multilocus sequence analysis (MLSA) was employed for enhanced species resolution. The study identified six Bradyrhizobium species: Bradyrhizobium japonicum USDA 110, Bradyrhizobium japonicum USDA 6, Bradyrhizobium elkanii USDA 76, Bradyrhizobium neotropicale, Bradyrhizobium lablabi, and Bradyrhizobium icense. Bradyrhizobium japonicum USDA 110 predominated in the soils, displaying symbiotic preference for the Huasteca 400 variety. However, phylogenetic analysis didn't reveal a clear association between strains, soil, and soybean variety. This research sheds light on the diversity of rhizobia in Mexican soybean cultivation, contributing to the understanding of symbiotic relationships in soybean production systems.

关键词： Nodules Soybean Housekeeping Genes MLSA Rhizobia Bradyrhizobium Nitrogen Fixation Symbiosis Phylogenetic Analysis

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Photophysical,optical,and photocatalytic hydrogen production properties of layered-type BaNb_(2-x)Ta_(x)P_(2)O_(11)(x=0,0.5,1.0,1.5,and 2.0)compounds

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Journal of Materials Science & Technology 2022年第3期98卷 26-32页

作者： Min Je Kang gill Sang Han In Sun Cho Department of Materials Science and Engineering Ajou UniversitySuwon 16499Republic of Korea Department of Energy Systems Research Ajou UniversitySuwon 16499Republic of Korea School of Advanced Materials Science and Engineering Sungkyunkwan UniversitySuwon 16419Republic of Korea

Layered-type metal phosphates of BaNb_(2-x)Ta_(x)P_(2)O_(11)(x=0,0.5,1.0,1.5,and 2.0)were synthesized using a solid-state reaction *** photophysical,optical,and photocatalytic hydrogen production properties of the resulting powders were investigated for the first ***-pure and homogeneous powders with irregular morphologies were obtained at a calcination temperature of 1200℃.As the Ta content increased,the interlayer distance along the c-axis increased by up to 0.14%.Additionally,the optical bandgap values increased from 3.32 to 3.59 *** energy band positions were estimated from the Mott–Schottky ***_(2)P_(2)O_(11)(x=0)exhibited the lowest conduction band edge position(-0.14 V *** normal hydrogen electrode,NHE),which is located above the water reduction potential(0.0 V ***).In comparison,BaTa_(2)P_(2)O_(11)(x=2.0)exhibited the highest conduction band edge position(-0.29 V ***),comparable to that of TiO_(2).The photocatalytic activity for hydrogen produced from splitting water was measured under ultraviolet light ***,BaTa_(2)P_(2)O_(11)exhibited the highest activity(7.3μmol/h),which was 15 and 10 times larger than BaNb_(2)P_(2)O_(11)(0.5μmol/h)and nano-TiO_(2)(0.7μmol/h),*** activity of BaTa_(2)P_(2)O_(11)increased to 24.4μmol/h after deposition of the NiO_(x)co-catalyst(1 wt.%),which remained stable during continuous operation(~35 h).

关键词： BaNb_(2)P_(2)O_(11) BaTa_(2)P_(2)O_(11) Layered crystal structure Bandgap Band edge positions Photocatalytic hydrogen production

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专访戈登·吉尔:“形式追随效能”的建筑探索

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当代建筑 2024年第4期 116-120页

作者：戈登·吉尔贾丽丽 AS+GG建筑设计事务所《当代建筑》编辑部

超高层建筑作为城市高速发展的重要代表,已然成为现代城市中的地标建筑,并不断改变着城市景观。在众多深耕于超高层建筑设计领域的国外设计团队中,AS+GG建筑设计事务所打造了一系列横跨亚洲、北美洲、欧洲等地区的“摩天大楼”,并长期... 详细信息

超高层建筑作为城市高速发展的重要代表,已然成为现代城市中的地标建筑,并不断改变着城市景观。在众多深耕于超高层建筑设计领域的国外设计团队中,AS+GG建筑设计事务所打造了一系列横跨亚洲、北美洲、欧洲等地区的“摩天大楼”,并长期致力于国际化、高性能和可持续的建筑设计实践。本期特邀请AS+GG建筑设计事务所创始合伙人戈登·吉尔围绕其“形式追随效能”的设计理念展开讨论。

关键词：建筑设计事务所超高层建筑地标建筑城市景观摩天大楼建筑探索设计理念戈登

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Computational-Analysis of the Non-Isothermal Dynamics of the Gravity-Driven Flow of Viscoelastic-Fluid-Based Nanofluids Down an Inclined Plane

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Fluid Dynamics & Materials Processing 2023年第3期19卷 767-781页

作者： Idrees Khan Tiri Chinyoka Andrew gill Centre for Research in Computational&Applied Mechanics University of Cape TownRondebosch7701South Africa Department of Mathematics and Applied Mathematics University of Cape TownRondebosch7701South Africa Centre for High Performance and Computing Council for Scientific and Industrial ResearchRosebankCape Town7700South Africa

The paper explores the gravity-driven flow of the thin film of a viscoelastic-fluid-based nanofluids(VFBN)along an inclined plane under non-isothermal conditions and subjected to convective cooling at the *** Newton’s law of cooling is used to model the convective heat-exchange with the ambient at the *** Giesekus viscoelastic constitutive model,with appropriate modifications to account for non-isothermal effects,is employed to describe the polymeric *** unsteady and coupled non-linear partial differential equations(PDEs)describing the model problem are obtained and solved via efficient semi-implicit numerical schemes based on finite difference methods(FDM)implemented in *** response of the VFBN velocity,temperature,thermal-conductivity and polymeric-stresses to variations in the volume-fraction of embedded nanoparticles is *** is shown that these quantities all increase as the nanoparticle volume-fraction becomes higher.

关键词： Semi-implicit numerical scheme finite difference methods viscoelastic-fluid-based nanofluid(VFBN) nonisothermal viscoelastic flow giesekus constitutive model nanofluid thermal-conductivity gravity-driven flow

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Seasonal Prediction Skill and Biases in GloSea5 Relating to the East Asia Winter Monsoon

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Advances in Atmospheric Sciences 2023年第11期40卷 2013-2028页

作者： Daquan ZHANG Lijuan CHEN gill MMARTIN Zongjian KE China Meteorological Administration Key Laboratory for Climate Prediction Studies National Climate CentreBeijing 100081China Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters(CIC-FEMD) Nanjing University of Information Science&TechnologyNanjing 210044China Met Office Hadley Centre Met OfficeExeter EX13PBUK

The simulation and prediction of the climatology and interannual variability of the East Asia winter monsoon(EAWM),as well as the associated atmospheric circulation,was investigated using the hindcast data from Global Seasonal Forecast System version 5(GloSea5),with a focus on the evolution of model bias among different forecast lead *** GloSea5 reproduces the climatological means of large-scale circulation systems related to the EAWM well,systematic biases exist,including a cold bias for most of China’s mainland,especially for North and Northeast ***5 shows robust skill in predicting the EAWM intensity index two months ahead,which can be attributed to the performance in representing the leading modes of surface air temperature and associated background ***5 realistically reproduces the synergistic effect of El Niño–Southern Oscillation(ENSO)and the Arctic Oscillation(AO)on the EAWM,especially for the western North Pacific anticyclone(WNPAC).Compared with the North Pacific and North America,the representation of circulation anomalies over Eurasia is poor,especially for sea level pressure(SLP),which limits the prediction skill for surface air temperature over East *** representation of SLP anomalies might be associated with the model performance in simulating the interaction between atmospheric circulations and underlying surface conditions.

关键词： East Asia winter monsoon(EAWM) Global Seasonal Forecast System version 5(GloSea5) El Niño–Southern Oscillation(ENSO) prediction skill model bias

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Exploring influential factors and endogeneity of traffic flow of different lanes on urban freeways using Bayesian multivariate spatial models

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Journal of Traffic and Transportation Engineering(English Edition) 2023年第1期10卷 104-115页

作者： Yongping Zhang Gurdiljot Singh gill Wen Cheng Paulina Reina Mankirat Singh Department of Civil Engineering California State Polytechnic UniversityPomonaCA 91768USA Department of Civil and Environmental Engineering California State UniversityFullertonCA 91768USA

The traffic flow pertinent modelling is essential for distinct strategy ***,the present literature illustrated some needed improvements for such models,especially those related to lane-specific *** such context,this study aims to bridge the research gap by generating regression models to investigate influential factors for traffic flow based on the data collected from one multilane *** the Full Bayesian specification,the hierarchical models were built by accounting for three types of random effects:the structured and unstructured spatial effects,and the one addressing the multivariate heterogeneity across multiple *** endogenous relationship of traffic flow of adjacent lanes was also explored by utilizing the capability of multivariate correlation structure for simultaneous estimation of lane *** model estimates revealed the presence of endogeneity with statistical significance for the flow of neighbouring lanes for both directions of *** impact of flow was not only limited to the adjacent lanes but also to non-adjacent *** multivariate specification also confirmed interdependency for lane *** to conventional approaches,the more accurate model estimation in the study indicates the advantage of incorporating the various correlation structures in the models.

关键词： Spatial interdependency Structured and unstructured random effects Multivariate specification Endogeneity Traffic flow

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