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Science China Life Sciences 2025年第5期68卷 1536-1540页

作者： Hao Xu Shibo Zhou Zefeng Zhu Vincenzo Vitelli Liangyi Chen Ziwei Dai Ning Yang Luhua Lai Shengyong Yang Sergey Ovchinnikov Zhuoran Qiao Sirui Liu Chen Song Jianfeng Pei Han Wen Jianfeng Feng Yaoyao Zhang Zhengwei Xie Yang-Yu Liu Zhiyuan Li Fulai Jin Hao Li Mohammad Lotfollahi Xuegong Zhang Ge Yang Shihua Zhang Ge Gao Pulin Li Qi Liu Jing-Dong Jackie Han Peking-Tsinghua Center for Life Sciences (CLS) Academy for Advanced Interdisciplinary StudiesPeking University Center for Quantitative Biology (CQB) Academy for Advanced Interdisciplinary StudiesPeking University Peking University-Tsinghua University-National Institute of Biological Sciences Joint Graduate Program Academy for Advanced Interdisciplinary StudiesPeking University Department of Physics University of Chicago School of Life Sciences Southern University of Science and Technology Peking University Chengdu Academy for Advanced Interdisciplinary Biotechnologies College of Chemistry and Molecular Engineering Peking University Department of Biotherapy Cancer Center and State Key Laboratory of BiotherapyWest China HospitalSichuan University Department of Biology Massachusetts Institute of Technology Lambic Therapeutics Inc. Changping Laboratory Al for Science Institute Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University Department of Obstetrics and Gynecology West China Second University HospitalSichuan University Peking University International Cancer Institute and Peking University-Yunnan Baiyao International Medical Institute and State Key Laboratory of Natural and Biomimetic Drugs Department of Molecular and Cellular PharmacologySchool of Pharmaceutical SciencesPeking University Health Science CenterPeking University Channing Division of Network Medicine Department of MedicineBrigham and Women's Hospital and Harvard Medical School Center for Artificial Intelligence and Modeling the Carl R.Woese Institute for Genomic BiologyUniversity of Illinois Urbana-Champaign Department of Genetics and Genome Sciences School of Medicine and Department of Computer and Data Sciences and Department of Population and Quantitative Health SciencesCase Western Reserve University Department of Biochemistry and Biophysics University of California Sanger Institute Department of Automation Tsinghua University State Key Laboratory of Multimodal Artificial Intelligence Systems I

The development of artificial intelligence(AI) and the mining of biomedical data complement each other. From the direct use of computer vision results to analyze medical images for disease screening, to now integrating biological knowledge into models and even accelerating the development of new AI based on biological discoveries, the boundaries of both are constantly expanding, and their connections are becoming closer.

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Long-term effects of PM2.5 constituents on childhood attention deficit hyperactivity disorder: evidence from a large population-based study in the Pearl River Delta Region, China

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Environmental research 2025年 277卷 121641页

作者： Zeng, Hui-Xian Meng, Wen-Jie Zeng, Qing-Guo Wei, Jing Liu, Lu-Sheng Wu, Qi-Zhen Zhao, Bin Oudin, Anna Yang, Mo Jalava, Pasi Dong, Guang-Hui Zeng, Xiao-Wen Joint International Research Laboratory of Environment and Health Ministry of Education Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment Department of Occupational and Environmental Health School of Public Health Sun Yat-sen University Guangzhou510080 China Department of Atmospheric and Oceanic Science Earth System Science Interdisciplinary Center University of Maryland College ParkMD United States State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Tsinghua University Beijing100084 China State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex Beijing100084 China Department of Public Health and Clinical Medicine Umeå University Umeå Sweden Department of Environmental and Biological Science University of Eastern Finland Kuopio Finland

Background: Evidence linking fine particulate matter (PM2.5) constituents to childhood attention deficit hyperactivity disorder (ADHD) was limited. Objectives: To investigate the individual and joint effects of exposure to PM2.5 constituents on ADHD. Methods: We conducted a large population-based survey involving 110,818 school children aged 6–18 years across six cities in the Pearl River Delta region, China. The three-year average concentrations of PM2.5 constituents (black carbon (BC), organic matter (OM), sulfate, nitrate, and ammonium) were estimated using the ChinaHighAirPollutants dataset. Parents completed an ADHD checklist using the Diagnostic and Statistical Manual of Mental Disorders-IV criteria. The individual and joint associations between PM2.5 components and ADHD were estimated using generalized linear mixed models and the quantile g-computation regression model, respectively. Results: The exposure-response relationships between PM2.5 constituents and ADHD primarily exhibited a nonlinear pattern. Compared with the lowest tertile, the highest tertiles of PM2.5 and its components were linked to greater odds for ADHD (e.g., the adjusted odds ratio (OR) was 1.37 (95 % confidential interval (CI): 1.27, 1.47) for PM2.5, 1.51 (95 %CI: 1.40, 1.63) for OM, 1.29 (95 %CI: 1.20, 1.39) for BC, and 1.20 (95 %CI:1.08, 1.34) for sulfate). Similar positive associations were observed between BC and sulfate exposure and ADHD subtypes. Moreover, joint exposure to PM2.5 components was associated with ADHD (OR = 1.14, 95 % CI:1.10, 1.18), with OM and BC contributing more to the observed associations. Conclusions: These findings highlight the varying contributions of PM2.5 constituents to ADHD and underscore the importance of reducing specific PM2.5 component emissions to mitigate the burden of PM2.5-associated neurodevelopmental diseases. © 2025 Elsevier Inc.

关键词： Regression analysis

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A comparative study of the accuracy between conventional and digital impressions in different implant angulations and depths

Digital Dentistry Journal

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Digital Dentistry Journal 2025年第1期1卷 100009-100009页

作者： Sirikarn Aneakgerawat Walita Narkbuakaew Weerapan Aunmeungtong Pathawee Khongkhunthian Center of Excellence for Dental Implantology Faculty of Dentistry Chiang Mai University Chiang Mai Thailand Medical Imaging System Research Team Assistive Technology and Medical Devices Research Group National Electronics and Computer Technology Center National Science and Technology Development Agency Pathumthani Thailand

Purpose To compare the accuracy of implant impression technique between conventional and digital impressions (digital scans) in different implant angulations and depths (gingival heights). Material and methods Seven master models with polyester resin and condensation-cured silicone, featuring three dental implants at 0°, 15°, and 30° buccal angulations and varying gingival heights (GH2-8), were used. Seventy STL files were generated using conventional impressions and digital scans. Accuracy of the impressions were evaluated by comparing STL files to the reference models, measuring linear and angular deviations. Trueness was determined by average deviation, while precision was assessed by intra-group variation. Statistical significance was set at p < 0.05. Results This study revealed that, in the 0-degree group, no significant differences were found between the two impression methods at different heights. The 15-degree buccally angulated implant showed significant differences between GH4 and GH8 (p = 0.009), while a 30-degree buccally angulated implant showed significant differences between GH 4 and GH 6, 7, 8 (p = 0.013, 0.005, 0.003 respectively). Digital scans consistently exhibited significantly lower angular deviation of precision compared to conventional impressions, except for GH2 (p < 0.001). There were no statistically significant differences in the precision of linear deviation. Conclusions Within the limitations of this in vitro study, no significant differences in accuracy were observed between the two impression methods at different heights in the parallel groups, but significant differences found when implant depths in angulated implants were increased.

关键词： Implant impression technique Digital scans Conventional impression Dental impression accuracy Implant angulation Implant depth

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Chip Scale Packaging of Piezoresistive Pressure Sensors using Dry-Film Shielding

Chip Scale Packaging of Piezoresistive Pressure Sensors usin...

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59th Electronic Components and technology Conference

作者： Huang, Tyson Chen, Lung-Tai Chu, Peter Chen, Y. S. Ho, C. W. Hsu, Chung-Yi Pan, Jason Research and Development Department IST Taiwan Micro-System Technology Center ITRI Taiwan

ISBN: (纸本)9781424444755

In this study, a chip scale packaging (CSP) of piezoresistive pressure sensors using a dry-film shielding approach is demonstrated. A sensing-channel just above the silicon membrane of the pressure sensor has to be reserved in the package body. To prevent the silicon membrane of the pressure sensors from the metal-deposition contaminations, a dry-film with a redistribution pattern is used to shield the sensing-channel opening during seed layer sputter process of the trace redistribution. Experimental results reveal that the silicon membrane of the pressure sensor is free of metal-deposition contamination and functional operation. The packaged pressure sensor has a linearity error of 0.2 psi at 25 degrees C and sensitivity repeatability of 3.5x10(-4)mVV(-1)psi(-1) at pressure range of 0 similar to 100psi (3 sigma). The proposed pressure sensor package holds advantages on both low cost and tiny packaging size, making it suitable for portable consumer products.

关键词： Shielding

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Underground well water level observation grid dataset from 2005 to 2022

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Scientific Data 2025年第1期12卷 1-9页

作者： Wang, Mengran Yao, Jiaqi Chang, Huanyu Liu, Rong Xu, Nan Liu, Zihua Gong, Haiying Zheng, Hengliang Wang, Jinke Guo, Xueer Cao, Yongqiang Zhao, Yong Lu, Hui Academy of Ecological Civilization Development for JING-JIN-JI Megalopolis Tianjin Normal University Tianjin 300387 China State Key Laboratory of Simulation and Regulation of Water Cycle in River Basin China Institute of Water Resources and Hydropower Research (IWHR) Beijing 100038 China College of Geography and Remote Sensing Hohai University Jiangsu Nanjing 210098 China Department of Earth System Science Institute for Global Change Studies Tsinghua University Beijing 100084 China State Key Laboratory of Hydroscience and Engineering Tsinghua University Beijing 100084 China Tsinghua University (Department of Earth System Science)- Xi’an Institute of Surveying and Mapping Joint Research Center for Next-Generation Smart Mapping Beijing China

Groundwater, a vital hydrological cycle component, is essential in sustaining ecosystem functions and human livelihoods. The dataset presented herein, derived from the China Geological Environment Monitoring Groundwater Level Yearbook (2005–2022) compiled by the China Geological Environment Monitoring Institute, integrates long-term observational data from groundwater monitoring wells across China. The dataset comprises 11,911 monitoring points and 4,275,506 observation records, with each site providing five observations per month. To enhance its spatial and temporal coverage, the dataset was processed using the inverse distance weighting interpolation method, generating groundwater level raster data with spatial and temporal resolutions of 1 km and one month, respectively. Validation of the interpolated data demonstrated high accuracy, with regression coefficients and R² values approaching 1 across multiple validation regions, and root-mean-square error and mean-square error metrics remaining acceptable. Spanning 2005–2022, the dataset is available in standard GeoTIFF format, rendering it ideal for geographic information system analysis. It provides a robust foundation for investigating groundwater dynamics, exploring interactions with surface ecosystems, and supporting sustainable water management practices. © The Author(s) 2025.

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Facilitating sensitivity analysis of hydrological models through knowledge-driven configuration and distributed online model services

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Journal of Hydrology 2025年 660卷

作者： Ma, Peilong Chen, Min Zhang, Shuo Zhu, Zhiyi Qian, Zhen Ma, Zaiyang Zhang, Fengyuan Li, Wenwen Yue, Songshan Wen, Yongning Nanjing Normal University Jiangsu Nanjing210023 China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Jiangsu Nanjing210023 China State Key Laboratory Cultivation Base of Geographical Environment Evolution Jiangsu Nanjing210023 China Earth System Modelling School of Engineering and Design Technical University of Munich Bavaria Munich80333 Germany Potsdam Institute for Climate Impact Research Brandenburg Postdam14473 Germany School of Geographical Sciences Nanjing University of Information Science and Technology Jiangsu Nanjing210044 China

Hydrological models (HMs) are essential for understanding the complexities of the water cycle and runoff dynamics. Sensitivity analysis (SA), an essential component of HMs, plays a key role in identifying the parameters that have the greatest impact on model outcomes. It helps to simplify the complexity of hydrological systems and provides a comprehensive understanding of the underlying physical processes. However, the complexity of HMs and the diversity of SA methods pose significant challenges for researchers, making the SA configuration process intricate and requiring substantial computational resources. To address these challenges, we propose a comprehensive strategy that integrates knowledge-driven configuration services with distributed online model services. First, we establish a rule-based knowledge repository and a case-based knowledge repository. These repositories provide general configuration guidance and similar SA case recommendations, respectively, to support decision-making in critical SA steps. This ensures that the configuration of SA is accurate and reliable. Secondly, we encapsulate HMs as web services and leverage distributed computing resources to optimize execution efficiency. Then, we integrate the HM services with the SA modules to achieve a complete SA experiment. Based on this strategy, we finally developed a prototype system that offers a user-friendly tool for conducting SA with enhanced computational performance and streamlined workflow. The watershed-scale HM, SWAT, was used to test the effectiveness of the prototype system. The results demonstrate that this strategy enables more comprehensive analysis and improves decision-making through configuration guidance, and holds promise for enhancing the reliability and efficiency of SA in hydrological modeling. © 2025 Elsevier B.V.

关键词： Platform as a Service (PaaS)

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Slab morphology and associated seismic and volcanic activities beneath Sulawesi Island, Indonesia

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Journal of Volcanology and Geothermal research 2025年 465卷

作者： Wibowo, Bagus Adi Bai, Ling Rohadi, Supriyanto Sahara, David Prambudi Chen, Zhiwen Karyono, Karyono Setiawan, Yosi Widyadharma, Putu Hendra Arimuko, Abraham Rahayu, Anisa Nurbaeti Adi, Suko Prayitno Karnawati, Dwikorita State Key Laboratory of Tibetan Plateau Earth System Environment and Resources Institute of Tibetan Plateau Research Chinese Academy of Sciences No. 16 Lincui Road Chaoyang District Beijing100101 China University of Chinese Academy of Sciences No.80 Zhongguancun East Road Haidian District Beijing100049 China Center of Earthquake and Tsunami's Early Warning System Deputy of Geophysics Agency of Meteorology Climatology and Geophysics Angkasa I Street No.2 PO Box 3540 Jakarta Indonesia Center of Research and Development Geophysics Section Agency of Meteorology Climatology and Geophysics Angkasa I Street No.2 PO Box 3540 Jakarta Indonesia Agency of Meteorology Climatology and Geophysics Angkasa I Street No.2 PO Box 3540 Jakarta Indonesia Faculty of Mining and Petroleum Engineering Bandung Institute of Technology Ganesa Street No. 10 Coblong Bandung Indonesia

The Sulawesi Island, Indonesia, represents a complex deformation with multiple subducting slabs and produces frequent earthquake, volcano, and tsunami hazards. Here, we investigate lithospheric velocity structures beneath Sulawesi Island to study the subducting slabs and their associated seismicity and volcanism. P- and S-wave arrival time data are acquired from the dense seismic network of the Indonesia Tsunami Early Warning system. We collected 192,301 P-wave and 40,345 S-wave phases arrival time data from 10,421 earthquakes with 2.5 ≤ Mw ≤ 7.5 that occurred between 2017 and 2022. Earthquake data are recorded by 137 InaTEWS seismic stations which provide sufficient ray path density for the entire Sulawesi Island. There are high velocity anomalies for subducting slabs and low velocity anomalies beneath active volcanoes. These observations revealed southward subduction of the Celebes slab, northward subduction of the Banggai-Sula slab, southwest subduction of the Sangihe slab, and double subduction of the Sangihe and Halmahera arcs northeast of the Sulawesi Island. The 2018 Mw7.5 Palu earthquake occurred on the left-lateral strike-slip Palu-Koro fault, which was formed by the northward subduction of the Banggai-Sula slab with respect to the Makassar Strait. The 2018 Mw7.5 Palu earthquake sequence and the 2018 Mamasa earthquake swarm are located with low Vp and Vs anomalies, probably due to the combination of active fault activity and fluid migration. © 2025 Elsevier B.V.

关键词： Earthquake effects

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Modified ddpg algorithm applied to simulation supervised learning 48

Modified ddpg algorithm applied to simulation supervised lea...

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48th International Conference on Computers and Industrial Engineering, CIE 2018

作者： Jia, Zhengxuan Xiao, Yingying Zhao, Zhilong Lin, Tingyu State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing China Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing Simulation Center Beijing China Science and Technology on Space System Simulation Laboratory Beijing Simulation Center Beijing China

With rapid development of machine learning, supervised learning and reinforcement learning have witnessed a considerable success. However, some problems like the absence of supervising signal in supervised learning are not yet solved. In this paper, a novel approach has been proposed based on the deep deterministic policy gradient algorithm to address such kind of problems, forming the training of an agent supervised by the simulation environment. As verification, our proposed approach is applied to a modified tower defense game, and the experimental results confirmed the effectiveness of our proposed approach. © 2018, Curran Associates Inc. All rights reserved.

关键词： Supervised learning

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User-level failure detection and auto-recovery of parallel programs in HPC systems

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Frontiers of Computer Science 2021年第6期15卷 31-42页

作者： Guozhen ZHANG Yi LIU Hailong YANG Jun XU Depei QIAN State Key Laboratory of Software Development Environment Beijing 100191China Sino-German Joint Software Institute Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China Science and Technology on Space System Simulation Laboratory Beijing Simulation Center Beijing 100854China

As the mean-time-between-failures(MTBF)continues to decline with the increasing number of components on large-scale high performance computing(HPC)systems,program failures might occur during the execution period with high *** successful execution of the HPC programs has become an issue that the unprivileged users should be *** the user perspective,if the program failure cannot be detected and handled in time,it would waste resources and delay the progress of program ***,the unprivileged users are unable to perform program state checking due to execution control by the job management system as well as the limited ***,automated tools for supporting user-level failure detection and autorecovery of parallel programs in HPC systems are *** paper proposes an innovative method for the unprivileged user to achieve failure detection of job execution and automatic resubmission of failed *** state checker in our method is encapsulated as an independent job to reduce interference with the user *** addition,we propose a dual-checker mechanism to improve the robustness of our *** implement the proposed method as a tool named automatic re-launcher(ARL)and evaluate it on the Tianhe-2 *** results show that ARL can detect the execution failures effectively on Tianhe-2 *** addition,the communication and performance overhead caused by ARL is *** good scalability of ARL makes it applicable for large-scale HPC systems.

关键词： high performance computing parallel program failure detection failure auto-recovery

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Modeling of service correlation for service composition in cloud manufacturing 31

Modeling of service correlation for service composition in c...

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31st European Modeling and simulation Symposium, EMSS 2019

作者： Wang, Fei Laili, Yuanjun Zhang, Lin Xing, Chi Guo, Liqin School of Automation Science and Electrical Engineering Beihang University China Beijing Complex Product Advanced Manufacturing Engineering Research Center Beijing Simulation Center China State Key Laboratory of Intelligent Manufacturing System Technology Beijing Institute of Electronic System Engineering Beijing Simulation Center China Science and Technology on Space System Simulation Laboratory Beijing Simulation Center China

ISBN: (纸本)9788885741263

Cloud manufacturing (CMfg), integrating distributed manufacturing resources as services to cloud center, aims at intelligent, green, and economic customized manufacturing. The optimal composition of services to fulfill particular manufacturing requirement is a core issue to realize efficient cloud manufacturing. Many researchers have studied the problem considering the Quality-of-Service (QoS) of independent services. However, the correlation between services is rarely considered. In this paper, the importance of service correlation is emphasized. Two kinds of service correlation, service exclusion and service collaboration, are modeled for service composition. An improved algorithm DET, which combines Differential Evolution Algorithm (DE) with a Tabu table based on service exclusive and collaborative relationships, is designed to filter composable services and find better solutions for complex tasks. Experiments have shown the effects of service correlation on the quality of composed services and demonstrated the effectiveness of the proposed method DET compared with traditional DE. © 2019 Dime Universita di Genova, DIMEG University of Calabria.

关键词： Quality of service

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