检索结果-南通市图书馆

Short-term effects of fine particulate matter constituents on myocardial infarction death

环境科学学报:英文版 2023年第11期133卷 60-69页

作者： Shaocai Mo Jianlin Hu Chuanhua Yu Junzhe Bao Zhihao Shi Peixuan Zhou Zhiming Yang Siqi Luo Zhouxin Yin Yunquan Zhang Department of Epidemiology and Biostatistics School of Public HealthWuhan University of Science and TechnologyWuhan 430065China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution ControlNanjing University of Information Science&TechnologyNanjing 210044China Department of Epidemiology and Biostatistics School of Public HealthWuhan UniversityWuhan 430071China Department of Epidemiology and Biostatistics School of Public HealthZhengzhou UniversityZhengzhou 450001China School of Economics and Management University of Science and Technology BeijingBeijing 100083China Hubei Province Key Laboratory of Occupational Hazard Identification and Control Wuhan University of Science and TechnologyWuhan 430065China

Existing evidence suggested that short-term exposure to fine particulate matter(PM_(2.5))may increase the risk of death from myocardial infarction(MI),while PM_(2.5) constituents responsible for this association has not been determined.We collected 12,927 MI deaths from 32 counties in southern China during 2011–2013.County-level exposures of ambient PM_(2.5) and its 5 constituents(i.e.,elemental carbon(EC),organic carbon(OC),sulfate(SO_(4)^(2-)),ammonium(NH_(4)^(+)),and nitrate(NO_(3)^(-)))were aggregated from gridded datasets predicted by Community Multiscale Air Quality Modeling System.We employed a space-time-stratified casecrossover design and conditional logistic regression models to quantify the association of MI mortality with short-term exposure to PM_(2.5) and its constituents across various lag days.Over the study period,the daily mean PM_(2.5) mass concentration was 77.8(standard deviation(SD)=72.7)μg/m^(3).We estimated an odds ratio of 1.038(95%confidence interval(CI):1.003-1.074),1.038(1.013-1.063)and 1.057(1.023-1.097)for MI mortality associated with per interquartile range(IQR)increase in the 3-day moving-average exposure to PM_(2.5)(IQR=76.3μg/m 3),EC(4.1μg/m^(3))and OC(9.1μg/m^(3)),respectively.We did not identify significant association between MI death and exposure to water-soluble ions(SO_(4)^(2-),NH_(4)^(+)and NO_(3)^(-)).Likelihood ratio tests supported no evident violations of linear assumptions for constituents-MI associations.Subgroup analyses showed stronger associations between MI death and EC/OC exposure in the elderly,males and cold months.Short-term exposure to PM_(2.5) constituents,particularly those carbonaceous aerosols,was associated with increased risks of MI mortality.

关键词： Air pollution Particulate constituents Myocardial infarction Case-crossover study

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Short-term exposure to fine particulate matter constituents and mortality:case-crossover evidence from 32 counties in China

引用

Science China(Life Sciences) 2022年第12期65卷 2527-2538页

作者： Peixuan Zhou Jianlin Hu Chuanhua Yu Junzhe Bao Siqi Luo Zhihao Shi Yang Yuan Shaocai Mo Zhouxin Yin Yunquan Zhang Department of Epidemiology and Biostatistics School of Public HealthWuhan University of Science and TechnologyWuhan 430065China Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution ControlNanjing University of Information Science&TechnologyNanjing 210044China Department of Epidemiology and Biostatistics School of Public HealthWuhan UniversityWuhan 430071China Department of Epidemiology and Biostatistics College of Public HealthZhengzhou UniversityZhengzhou 450001China Hubei Province Key Laboratory of Occupational Hazard Identification and Control Wuhan University of Science and TechnologyWuhan 430065China

A growing number of studies associated increased mortality with exposures to specific fine particulate(PM_(2.5))constituents,while great heterogeneity exists between locations.In China,evidence linking PM_(2.5)constituents and mortality was extensively sparse.This study primarily aimed to quantify short-term associations between PM_(2.5)constituents and non-accidental mortality among the Chinese population.We collected daily mortality records from 32 counties in China between January 1,2011,and December 31,2013.Daily concentrations of main PM_(2.5)constituents(organic carbon(OC),elemental carbon(EC),nitrate(NO_(3)^(-)),sulfate(SO_(4)^(2−)),and ammonium(NH_(4)^(+)))were estimated using the modified Community Multiscale Air Quality model.Time-stratified case-crossover design with conditional logistic regression models was adopted to estimate mortality risks associated with short-term exposures to PM_(2.5)mass and its constituents.Stratification analyses were done by sex,age,and season.A total of 116,959 non-accidental deaths were investigated.PM_(2.5)concentrations on the day of death were averaged at 75.7μg m^(−3)(control day:75.6μg m^(−3)),with an interquartile range(IQR)of 65.2μg m^(−3).Per IQR rise in PM_(2.5),EC,OC,NO_(3)^(-),SO_(4)^(2−),and NH_(4)^(+)at lag-04 day was associated with an increase in non-accidental mortality of 2.4%(95%confidence interval,(1.0–3.7),1.7%(0.8–2.7),2.9%(1.6–4.3),2.1%(0.4–3.9),1.0%(0.2–1.9),and 1.6%(0.3–2.9),respectively.Both PM_(2.5)mass and its constituents were strongly associated with elevated cardiovascular mortality risks,but only PM_(2.5),EC,and OC were positively associated with respiratory mortality at lag-3 day.PM_(2.5)mass and its constituents associated effects on mortality varied among sex-and age-specific subpopulations.Differences in the seasonal pattern of associations exist among PM_(2.5)constituents,with stronger effects related to EC and NO_(3)^(-)in warm months but SO_(4)^(2−)and NH_(4)^(+)in cold months.Short-term exposures to PM_(2.5)compositions were positive

关键词： PM_(2.5)constituents mortality case-crossover design China

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Parallelization and Performance Optimization on Face Detection Algorithm with OpenCL: A Case Study

引用

Tsinghua Science and Technology 2012年第3期17卷 287-295页

作者： Weiyan Wang Yunquan Zhang Shengen Yan Ying zhang Haipeng Jia Laboratory of Parallel Software and Computational Science Institute of Softwarethe Chinese Academy of ScienceBeijing 100190China State Key Laboratory of Computer Science Institute of Softwarethe Chinese Academy of ScienceBeijing 100190China Graduate University of Chinese Academy of Sciences the Chinese Academy of ScienceBeijing 100190China Ocean University of China Qingdao 26610China

Face detect application has a real time need in nature. Although Viola-Jones algorithm can handle it elegantly, today＇s bigger and bigger high quality images and videos still bring in the new challenge of real time needs. It is a good idea to parallel the Viola-Jones algorithm with OpenCL to achieve high performance across both AMD and NVidia GPU platforms without bringing up new algorithms. This paper presents the bottleneck of this application and discusses how to optimize the face detection step by step from a very naive implementation. Some brilliant tricks and methods like CPU execution time hidden, stubbles usage of local memory as high speed scratchpad and manual cache, and variable granularity were used to improve the performance. Those technologies result in 4-13 times speedup varying with the image size. Furthermore those ideas may throw on some light on the way to parallel applications efficiently with OpenCL. Taking face detection as an example, this paper also summarizes some universal advice on how to optimize OpenCL program, trying to help other applications do better on GPU.

关键词： Viola-Jones OpenCL time cost hidden local memory usage parallel granularity

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Automatic tuning of sparse matrix-vector multiplication on multicore clusters

引用

Science China(Information Sciences) 2015年第9期58卷 17-30页

作者： LI ShiGang HU ChangJun zhang JunChao zhang yunquan State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences School of Computer and Communication Engineering University of Science and Technology Beijing Department of Computer Science University of Illinois at Urbana-Champaign

To have good performance and scalability, parallel applications should be sophisticatedly optimized to exploit intra-node parallelism and reduce inter-node communication on multicore clusters. This paper investigates the automatic tuning of the sparse matrix-vector(Sp MV) multiplication kernel implemented in a partitioned global address space language, which supports a hybrid thread- and process-based communication layer for multicore systems. One-sided communication is used for inter-node data exchange, while intra-node communication uses a mix of process shared memory and multithreading. We develop performance models to facilitate selecting the best configuration of threads and processes hybridization as well as the best communication pattern for Sp MV. As a result, our tuned Sp MV in the hybrid runtime environment consumes less memory and reduces inter-node communication volume, without damaging the data locality. Experiments are conducted on 12 real sparse matrices. On 16-node Xeon and 8-node Opteron clusters, our tuned Sp MV kernel gets on average 1.4X and 1.5X improvement in performance over the well-optimized process-based message-passing implementation, respectively.

关键词： Sp MV PGAS hybridization model-driven multicore clusters

来源：

同方期刊数据库评论

在线全文

同方期刊数据库

学校读者我要写书评

暂无评论

AIPerf: Automated Machine Learning as an AI-HPC Benchmark

引用

Big Data Mining and Analytics 2021年第3期4卷 208-220页

作者： Zhixiang Ren Yongheng Liu Tianhui Shi Lei Xie Yue Zhou Jidong Zhai Youhui zhang Yunquan Zhang Wenguang Chen Peng Cheng National Laboratory Shenzhen 518000China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China Institute of Computing Technology Chinese Academy of SciencesBeijing 100086China

The plethora of complex Artificial Intelligence(AI)algorithms and available High-Performance Computing(HPC)power stimulates the expeditious development of AI components with heterogeneous designs.Consequently,the need for cross-stack performance benchmarking of AI-HPC systems has rapidly emerged.In particular,the de facto HPC benchmark,LINPACK,cannot reflect the AI computing power and input/output performance without a representative workload.Current popular AI benchmarks,such as MLPerf,have a fixed problem size and therefore limited scalability.To address these issues,we propose an end-to-end benchmark suite utilizing automated machine learning,which not only represents real AI scenarios,but also is auto-adaptively scalable to various scales of machines.We implement the algorithms in a highly parallel and flexible way to ensure the efficiency and optimization potential on diverse systems with customizable configurations.We utilize Operations Per Second(OPS),which is measured in an analytical and systematic approach,as a major metric to quantify the AI performance.We perform evaluations on various systems to ensure the benchmark’s stability and scalability,from 4 nodes with 32 NVIDIA Tesla T4(56.1 Tera-OPS measured)up to 512 nodes with 4096 Huawei Ascend 910(194.53 Peta-OPS measured),and the results show near-linear weak scalability.With a flexible workload and single metric,AIPerf can easily scale on and rank AI-HPC,providing a powerful benchmark suite for the coming supercomputing era.

关键词： High-Performance Computing(HPC) Artificial Intelligence(AI) automated machine learning

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Association of diurnal temperature range with mortality in England and Wales:A nationwide time-series study

Association of diurnal temperature range with mortality in E...

引用

2017年中国卫生统计学学术年会

作者： Yunquan Zhang Chuanhua Yu Department of Preventive Medicine School of Health SciencesWuhan University Global Health Institute Wuhan University

＜正＞Background:Diurnal temperature range（DTR）reflects within-day temperature variability and is closely associated with climate change.In comparison to temperature extremes,up-to-date DTR-health evidence at the regional and national scales has been still very limited worldwide,especially in Europe.This study aimed to provide national estimates of DTR-mortality association in United Kingdom.

关键词：

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

专刊序言

引用

数据与计算发展前沿 2022年第6期4卷 1-2页

作者：张玉志南开大学软件学院天津300350

业界众所周知,新一代人工智能技术以深度学习为代表,而深度学习的开发离不开深度学习框架的支持。目前的深度学习开源框架百花齐放,有数十种之多,从早期的caffe、theano到主流的TensorFlow、PyTorch、MXNet等,越来越多的科技巨头公司加... 详细信息

业界众所周知,新一代人工智能技术以深度学习为代表,而深度学习的开发离不开深度学习框架的支持。目前的深度学习开源框架百花齐放,有数十种之多,从早期的caffe、theano到主流的TensorFlow、PyTorch、MXNet等,越来越多的科技巨头公司加入到机器学习框架的研发中,国内也有百度的PaddlePaddle、华为的MindSpore等。但得益于良好的开发生态和早期的布局,目前在产业界和学术界占据主导地位的仍是谷歌的TensorFlow与Facebook的PyTorch这两大开源框架。

关键词：开源框架人工智能技术深度学习谷歌 Facebook 百度学习框架

来源：

维普期刊数据库

维普期刊数据库更多评论

在线全文

学校读者我要写书评

暂无评论

Excess mortality associated with high ozone exposure:A national cohort study in China

引用

Environmental Science and Ecotechnology 2023年第3期15卷 98-105页

作者： Yang Yuan Kai Wang Haitong Zhe Sun Yu Zhan Zhiming Yang Kejia Hu Yunquan Zhang Institute of Social Development and Health Management Hubei Province Key Laboratory of Occupational Hazard Identification and ControlSchool of Public HealthWuhan University of Science and TechnologyWuhan430065China Centre for Atmospheric Science Yusuf Hamied Department of ChemistryUniversity of CambridgeCambridgeCB21EWUK Department of Earth Sciences University of CambridgeCambridgeCB23EQUK Department of Environmental Science and Engineering Sichuan UniversityChengduSichuan610065China School of Economics and Management University of Science and Technology BeijingBeijing100083China Department of Big Data in Health Science School of Public HealthZhejiang UniversityHangzhou310058China

Emerging epidemiological studies suggest that long-term ozone(O_(3))exposure may increase the risk of mortality,while pre-existing evidence is mixed and has been generated predominantly in North America and Europe.In this study,we investigated the impact of long-term O_(3)exposure on all-cause mortality in a national cohort in China.A dynamic cohort of 20882 participants aged40 years was recruited between 2011 and 2018 from four waves of the China Health and Retirement Longitudinal Study.A Cox proportional hazard regression model with time-varying exposures on an annual scale was used to estimate the mortality risk associated with warm-season(Aprile September)O_(3)exposure.The annual average level of participant exposure to warm-season O_(3)concentrations was 100 mg m^(-3)(range:61 e142 mg m^(-3)).An increase of 10 mg m^(-3)in O_(3)was associated with a hazard ratio(HR)of 1.18(95%confidence interval[CI]:1.13e1.23)for all-cause mortality.Compared with the first exposure quartile of O_(3),HRs of mortality associated with the second,third,and highest exposure quartiles were 1.09(95%CI:0.95e1.25),1.02(95%CI:0.88e1.19),and 1.56(95%CI:1.34e1.82),respectively.A J-shaped concentration eresponse associationwas observed,revealing a non-significant increase in risk below a concentration of approximately 110 mg m^(-3).Low-temperature-exposure residents had a higher risk of mortality associated with long-term O_(3)exposure.This study expands current epidemiological evidence from China and reveals that high-concentration O_(3)exposure curtails the long-term survival of middle-aged and older adults.

关键词： Ozone Long-term exposure All-cause mortality Cohort study

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

异构平台上性能自适应FFT框架

引用

计算机研究与发展 2014年第3期51卷 637-649页

作者：李焱张云泉并行软件与计算科学实验室(中国科学院软件研究所) 北京100190 中国科学院大学北京100049 计算机体系结构国家重点实验室(中国科学院计算技术研究所) 北京100190

快速傅里叶变换(fast Fourier transform,FFT)在科学和工程界中具有着广泛的应用,尤其是在信号处理、图像处理以及求解偏微分方程领域.基于图形处理器(graphic processing unit,GPU)和加速处理器(accelerated processing unit,APU)的异... 详细信息

快速傅里叶变换(fast Fourier transform,FFT)在科学和工程界中具有着广泛的应用,尤其是在信号处理、图像处理以及求解偏微分方程领域.基于图形处理器(graphic processing unit,GPU)和加速处理器(accelerated processing unit,APU)的异构平台,提出了自适应性能优化的大规模并行FFT(massively parallel FFT,MPFFT)框架.MPFFT框架采用了安装时和运行时2层自适应策略.安装时借助代码产生器可以生成被GPU程序内核(kernel)调用的任意长度的代码模板库(codelet);运行时根据自动调优技术使代码产生器生成高度优化的GPU计算代码.实验结果表明:MPFFT在APU平台上,一维、二维以及三维FFT相对于AMD clAmdFft 1.6取得的平均加速比分别为3.45,15.20以及4.47,在AMD HD7970GPU上平均加速比分别为1.75,3.01和1.69.在NVIDIA Tesla C2050GPU上取得的整体性能都达到了CUFFT 4.1的93%,最大加速比能够达到1.28.

关键词：快速傅里叶变换自适应性能优化加速处理器图形处理器异构

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Predictive Model and Risk Factors for Case Fatality of COVID-19: A Cohort of 21,392 Cases in Hubei, China

引用

The Innovation 2020年第2期1卷 85-92,84页

作者： Ran Wu Siqi Ai Jing Cai Shiyu zhang Zhengmin(Min)Qian Yunquan Zhang Yinglin Wu Lan Chen Fei Tian Huan Li Mingyan Li Hualiang Lin Institute of Preventive Medicine Information Hubei Provincial Center for Disease Control and Prevention6 Zhuodaoquan North RoadWuhanHubei 430079China Department of Epidemiology School of Public HealthSun Yat-sen University74 Zhongshan 2nd RoadGuangzhouGuangdong 510080China College for Public Health&Social Justice Saint Louis UniversitySt.LouisMOUSA Department of Epidemiology and Biostatistics School of Public HealthMedical CollegeWuhan University of Science and TechnologyWuhan 430065China These authors contributed equally Lead Contact

An increasing number of patients are being killed by coronavirus disease 2019(COVID-19),however,risk factors for the fatality of COVID-19 remain unclear.A total of 21,392 COVID-19 cases were recruited in the Hubei Province of China between December 2019 and February 2020,and followed up until March 18,2020.We adopted Cox regression models to investigate the risk factors for case fatality and predicted the death probability under specific combinations of key predictors.Among the 21,392 patients,1,020(4.77%)died of COVID-19.Multivariable analyses showed that factors,including age(R60 versus39C versus103109/L versus(4–10)3109/L,HR=1.69;95%CI,1.35,2.13),and lymphocyte counts(<0.83109/L versus(0.8–4)3109/L,HR=1.26;95%CI,1.06,1.50)were significantly associated with case fatality of COVID-19 patients.Individuals of an older age,who were male,with comorbidities,and had a critical illness had the highest death probability,with 21%,36%,46%,and 54%within 1–4 weeks after the symptom onset.Risk factors,including demographic characteristics,clinical symptoms,and laboratory factors were confirmed to be important determinants of fatality of COVID-19.Our predictive model can provide scientific evidence for a more rational,evidence-driven allocation of scarce medical resources to reduce the fatality of COVID-19.

关键词： COVID-19 FATALITY RISK FACTOR

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：