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ENIGMA-Meditation: Worldwide Consortium for Neuroscientific Investigations of Meditation Practices

Biological Psychiatry: Cognitive Neuroscience and Neuroimaging 2025年第4期10卷 425-436页

作者： Ganesan, Saampras Barrios, Fernando A. Batta, Ishaan Bauer, Clemens C.C. Braver, Todd S. Brewer, Judson A. Brown, Kirk Warren Cahn, Rael Cain, Joshua A. Calhoun, Vince D. Cao, Lei Chetelat, Gaël Ching, Christopher R.K. Creswell, J. David Dagnino, Paulina Clara Davanger, Svend Davidson, Richard J. Deco, Gustavo Dutcher, Janine M. Escrichs, Anira Eyler, Lisa T. Fani, Negar Farb, Norman A.S. Fialoke, Suruchi Fresco, David M. Garg, Rahul Garland, Eric L. Goldin, Philippe Hafeman, Danella M. Jahanshad, Neda Kang, Yoona Khalsa, Sahib S. Kirlic, Namik Lazar, Sara W. Lutz, Antoine McDermott, Timothy J. Pagnoni, Giuseppe Piguet, Camille Prakash, Ruchika S. Rahrig, Hadley Reggente, Nicco Saccaro, Luigi F. Sacchet, Matthew D. Siegle, Greg J. Tang, Yi-Yuan Thomopoulos, Sophia I. Thompson, Paul M. Torske, Alyssa Treves, Isaac N. Tripathi, Vaibhav Tsuchiyagaito, Aki Turner, Matthew D. Vago, David R. Valk, Sofie Zeidan, Fadel Zalesky, Andrew Turner, Jessica A. King, Anthony P. Department of Biomedical Engineering The University of Melbourne Carlton VIC Australia Contemplative Studies Centre Melbourne School of Psychological Sciences The University of Melbourne Melbourne VIC Australia Systems Lab of Neuroscience Neuropsychiatry and Neuroengineering The University of Melbourne Parkville VIC Australia Universidad Nacional Autónoma de México Instituto de Neurobiolgía México Querétaro Mexico Center for Translational Research in Neuroimaging and Data Science: Georgia State University Georgia Institute of Technology and Emory University Atlanta GA United States Department of Psychology Northeastern University Boston Massachusetts Brain and Cognitive Science McGovern Institute for Brain Research Massachusetts Institute of Technology Cambridge Massachusetts Department of Psychological and Brain Sciences Washington University St. Louis Missouri Department of Behavioral and Social Sciences Brown University School of Public Health Providence Rhode Island Department of Psychology Carnegie Mellon University Pittsburgh PA United States University of Southern California Department of Psychiatry & Behavioral Sciences Los Angeles California University of Southern California Center for Mindfulness Science Los Angeles California Institute for Advanced Consciousness Studies Santa Monica California Department of Psychiatry and Behavioral Health The Ohio State University College of Medicine Columbus OH United States Normandie University Université de Caen Normandie INSERM U1237 Neuropresage Team Cyceron Caen France Imaging Genetics Center Mark and Mary Stevens Neuroimaging and Informatics Institute Keck School of Medicine of the University of Southern California Los Angeles California Desert-Pacific Mental Illness Research Education and Clinical Center VA San Diego Healthcare System San Diego California Computational Neuroscience Group Center for Brain and Cognition Department of Information and Communication Technologies Universitat Pompeu Fa

Meditation is a family of ancient and contemporary contemplative mind-body practices that can modulate psychological processes, awareness, and mental states. Over the last 40 years, clinical science has manualized meditation practices and designed various meditation interventions that have shown therapeutic efficacy for disorders including depression, pain, addiction, and anxiety. Over the past decade, neuroimaging has been used to examine the neuroscientific basis of meditation practices, effects, states, and outcomes for clinical and nonclinical populations. However, the generalizability and replicability of current neuroscientific models of meditation have not yet been established, because they are largely based on small datasets entrenched with heterogeneity along several domains of meditation (e.g., practice types, meditation experience, clinical disorder targeted), experimental design, and neuroimaging methods (e.g., preprocessing, analysis, task-based, resting-state, structural magnetic resonance imaging). These limitations have precluded a nuanced and rigorous neuroscientific phenotyping of meditation practices and their potential benefits. Here, we present ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis)–Meditation, the first worldwide collaborative consortium for neuroscientific investigations of meditation practices. ENIGMA-Meditation will enable systematic meta- and mega-analyses of globally distributed neuroimaging datasets of meditation using shared, standardized neuroimaging methods and tools to improve statistical power and generalizability. Through this powerful collaborative framework, existing neuroscientific accounts of meditation practices can be extended to generate novel and rigorous neuroscientific insights that account for multidomain heterogeneity. ENIGMA-Meditation will inform neuroscientific mechanisms that underlie therapeutic action of meditation practices on psychological and cognitive attributes, thereby advancing the f

关键词： Consortium ENIGMA Magnetic resonance imaging (MRI) Meditation Mindfulness Neuroimaging

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Satellite-based vertical land motion for infrastructure monitoring: a prototype roadmap in Greater Houston, Texas

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Scientific Reports 2025年第1期15卷 1-12页

作者： Buzzanga, B. Govorcin, M. Kremer, F. Schubert, J.E. Bekaert, D.P.S. Schaeffer, B. Milillo, P. Williams, A.J. Sanders, B.F. Handwerger, A.L. Staniewicz, S. Jet Propulsion Laboratory California Institute of Technology Pasadena CA United States Joint Institute for Regional Earth System Science and Engineering University of California Los Angeles Los Angeles CA United States U.S. Environmental Protection Agency Office of Research and Development Cincinnati OH United States U.S. Environmental Protection Agency Office of Research and Development Research Triangle Park Raleigh NC United States Department of Civil and Environmental Engineering University of Houston Houston TX United States Department of Earth and Atmospheric Science University of Houston Houston TX United States Microwaves and Radar Institute German Aerospace Center (DLR) Oberfaffenhofen Germany Department of Civil and Environmental Engineering University of California Irvine CA United States

Coastal regions are critical hubs for industries reliant on transport and storage. However, vital infrastructure including above-ground storage tanks (ASTs), which store hazardous materials, is vulnerable to flooding and often exacerbated by subsidence (negative vertical land motion;VLM). The U.S. Environmental Protection Agency plays a key role in mitigating risks from ASTs. Satellite remote sensing provides a powerful tool to assess hazards and inform decision-making. Here, we present a roadmap for integrating remotely-sensed observations into decision-making frameworks. Using NASA observational products for end-users from remote sensing analysis (OPERA) VLM products derived from Sentinel-1, we map VLM at ~ 30 m resolution across Greater Houston–Galveston. Our analysis reveals widespread, spatially varying subsidence. We determine where VLM trends were linear from 2016 to 2023 and extrapolate them to estimate future VLM. Combining sea-level rise (SLR) scenarios with VLM data, we estimate that by 2050 ASTs in the region will experience at least 26.1 cm of relative SLR, with 10 (14.9%) exposed to more than 60 cm. Integrating a hydrodynamic model with spatially varying relative SLR shows that flooding hazards are amplified during a Hurricane Harvey-like event under future conditions. Overall, we demonstrate the importance of incorporating high-resolution VLM into hazard assessments to support decision-making. © The Author(s) 2025.

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Clock skew scheduling with optimizing-potential prediction

Clock skew scheduling with optimizing-potential prediction

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2012 International Applied Mechanics, MechatronicsAutomation and system simulation Meeting, AMMASS 2012

作者： Huang, Kai Zhang, Jinguo Cai, Zhikuang National ASIC System Engineering Research Center Southeast University Nanjing China The High Technology Research and Development Center of the Ministry of Science and Technology Beijing China

This paper addresses the issue of increasing the efficiency of the clock skew scheduling. The past research focuses on reducing the time complexity of clock skew scheduling algorithm. However, even if an algorithm has time complexity close to linear, the flow iterations still consumes a lot of time. In this paper, a novel clock skew scheduling scheme with the feature of optimization-potential prediction is proposed. With this feature, the algorithm has timing complexity close to linear, and the number of flow iterations is decreased. The experiment results show that the proposed scheme consumes about half time and achieves almost the same optimization strength (13% highest frequency improvement of ARM1136J-FS) compared to the traditional. © (2012) Trans Tech Publications, Switzerland.

关键词： Scheduling algorithms

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Spacecraft attitude sliding mode control method design 7

Spacecraft attitude sliding mode control method design

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7th IEEE Chinese Guidance, Navigation and Control Conference, CGNCC 2016

作者： Luwen, Zhang Chengchao, Bai Jifeng, Guo Han, Zheng School of Astronautics Harbin Institute of Technology Harbin150001 China Aircraft System Simulation Research Center Harbin Institute of Technology Harbin150001 China

ISBN: (纸本)9781467383189

The control of sliding mode variable structure has become one of an important in the modern control theories. It is also widely concerned by scholars at home and abroad due to its complete robustness such as its perturbation on system parameters, external disturbance and system uncertainty. This paper establishes the mathematical model for spacecraft based on error quaternion, derives the sliding-mode control law based on Lyapunov function by selecting appropriate sliding model and effectively weakens the buffeting by means of boundary layer approach. According to theoretical analysis and system simulation, the sliding-mode controller so designed is provided with robustness and overall stability under circumstances of parameter changes and external disturbances. © 2016 IEEE.

关键词： Sliding mode control

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Chip scale packaging of piezoresistive pressure sensors using the dry-film shielding

Chip scale packaging of piezoresistive pressure sensors usin...

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TRANSDUCERS 2009 - 15th International Conference on Solid-State Sensors, Actuators and Microsystems

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

ISBN: (纸本)9781424441938

In this study, chip scale packaging (CSP) for piezoresistive pressure sensors using a dry-film shielding approach is demonstrated. Experimental results reveal that the silicon membrane of the pressure sensor is free of metal-deposition contamination and functionally operational. The packaged pressure sensor met all of the specifications of an unpackaged bare pressure sensor, holding a maximum sensing error of 0.18psi over an operation temperature range of 25-85C. The proposed pressure sensor packaging has advantages on both low cost and tiny packaging size, making it suitable for portable consumer products. ©2009 IEEE.

关键词： Pressure sensors

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Production Line Capacity Planning Concerning Uncertain Demands for a Class of Manufacturing systems with Multiple Products

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IEEE/CAA Journal of Automatica Sinica 2015年第2期2卷 217-225页

作者： Hao Liu Qianchuan Zhao Ningjian Huang Xiang Zhao Center for Intelligent and Networked Systems(CFINS) Department of AutomationTNList LabTsinghua University Research and Development Center Institute of Space System EngineeringChina Academy of Space Technology Center for Intelligent and Networked Systems(CFINS) Department of AutomationTNList LabTsinghua University Global Research and Development Center General Motors Company

In this paper, we study a class of manufacturing systems which consist of multiple plants and each of the plants has capability of producing multiple distinct products. The production lines of a certain plant may switch between producing different kinds of products in a time-sharing mode. We optimize the capacity configuration of such a system0s production lines with the objective to maximize the overall profit in the capacity planning horizon. Uncertain demand is incorporated in the model to achieve a robust configuration solution. The optimization problem is formulated as a nonlinear polynomial stochastic programming problem, which is difficult to be efficiently solved due to demand uncertainties and large search space. We show the NP-hardness of the problem first, and then apply ordinal optimization (OO) method to search for good enough designs with high probability. At lower level, an mixed integer programming (MIP) solving tool is employed to evaluate the performance of a design under given demand profile. © 2014 Chinese Association of Automation.

关键词： Engineering education Manufacture Optimization Stochastic programming Stochastic systems

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Towards optimized tensor code generation for deep learning on sunway many-core processor

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Frontiers of Computer Science 2024年第2期18卷 1-15页

作者： Mingzhen LI Changxi LIU Jianjin LIAO Xuegui ZHENG Hailong YANG Rujun SUN Jun XU Lin GAN Guangwen YANG Zhongzhi LUAN Depei QIAN State Key Laboratory of Software Development Environment Beijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China National University of Singapore Singapore 119077Singapore State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi 214000China Science and Technology on Special System Simulation Laboratory Beijing Simulation Center Beijing 100854China Department of Computer Science and Technology Tsinghua UniversityBeijing 100084China

The flourish of deep learning frameworks and hardware platforms has been demanding an efficient compiler that can shield the diversity in both software and hardware in order to provide application *** the existing deep learning compilers,TVM is well known for its efficiency in code generation and optimization across diverse hardware *** the meanwhile,the Sunway many-core processor renders itself as a competitive candidate for its attractive computational power in both scientific computing and deep learning *** paper combines the trends in these two ***,we propose swTVM that extends the original TVM to support ahead-of-time compilation for architecture requiring cross-compilation such as *** addition,we leverage the architecture features during the compilation such as core group for massive parallelism,DMA for high bandwidth memory transfer and local device memory for data locality,in order to generate efficient codes for deep learning workloads on *** experiment results show that the codes generated by swTVM achieve 1.79x improvement of inference latency on average compared to the state-of-the-art deep learning framework on Sunway,across eight representative *** work is the first attempt from the compiler perspective to bridge the gap of deep learning and Sunway processor particularly with productivity and efficiency in *** believe this work will encourage more people to embrace the power of deep learning and Sunwaymany-coreprocessor.

关键词： sunway processor deep learning compiler code generation performance optimization

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Optimal deployment of regional multi-objective water resources based on mixed genetic algorithm

Optimal deployment of regional multi-objective water resourc...

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2010 International Conference on Management and Service Science, MASS 2010

作者： Shao, Lei Zhou, Xiaode Yang, Fangting Institute of Water Conservancy and Hydroelectric Power Xi'an University of Technology Xi'an China National Engineering Research Center of System Simulation Technology Application Beijing China

ISBN: (纸本)9781424453269

Based on the theory of large scale system general optimization, a model for optimal deployment of regional water resources with multi-sources and multi-consumers was developed. A new nonlinear integrated objective function was introduced in the model, which synthetically takes economic benefit, expense of water usage and water resource's equilibrium distribution into *** the restriction of water demand and supply, polluntant emission, harmonious development ,the objective function optimal value was calculated by mixed genetic algorithm. The model was applied to water resource deployment in Fenhe River basin. The results show that water demand can meet requirement at different guarantee *** indicate that the model can increase obviously the economic benefit and provide a scientific and balanced decision for future water deployment. © 2010 IEEE.

关键词： Water resources

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Inclusive wealth growth pathways within the carbon peak target for Chinese cities

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Cell Reports Sustainability 2025年第4期2卷

作者： Cheng, Danyang Guan, Dabo Xue, Qianyu Shan, Yuli Huo, Jingwen Cui, Can Zhou, Ya Li, Yuan Department of Earth System Sciences Tsinghua University Beijing 100084 China The Bartlett School of Sustainable Construction University College London London United Kingdom Institute of Blue and Green Development Weihai Institute of Interdisciplinary Research Shandong University Weihai 264209 China School of Geography Earth and Environmental Sciences University of Birmingham Birmingham B15 2TT United Kingdom Institute of Energy and Process Engineering ETH Zurich Zurich 8092 Switzerland Reliability and Risk Engineering ETH Zurich Zurich 8092 Switzerland Guangdong Basic Research Center of Excellence for Ecological Security and Green Development Key Laboratory for City Cluster Environmental Safety and Green Development of the Ministry of Education School of Ecology Environment and Resources Guangdong University of Technology Guangzhou 510006 China School of the Environment Nanjing University Nanjing 210023 China

China is committed to the Sustainable development Agenda and peaking its carbon emissions by 2030. However, interactions between these two agendas and pathways to achieving both remain understudied. This study assesses the sustainability performances and carbon emission patterns of Chinese cities and analyzes their interplay. To measure sustainability, we adopt the Inclusive Wealth Index framework that looks at the productive base of an economy, including produced capital, human capital, and natural capital. The results reveal that several national demonstration zones achieve sustainable peaking in correspondence with declining emissions and increasing sustainability from 2012 to 2019, driven by industrial transformation, education improvement, and renewable resources growth. Comparatively, some northeastern cities mitigate emissions by cutting carbon-intensive industries but fail to develop new sectors to support socioeconomic development, leading to a decline in well-being. Our findings emphasize the need for cities to synergize sustainable development and carbon-peaking pathways while tailoring strategies to local contexts. © 2025 The Author(s)

关键词： China city emission peak Inclusive Wealth sustainable development

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Enhancing Autonomy Capability in Regional Power Grids:A Strategic Planning Approach with Multiple Autonomous Evaluation Indexes

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Energy Engineering 2024年第9期121卷 2449-2477页

作者： Jie Ma Tong Zhao Yuanzhao Hao Wenwen Qin Haozheng Yu Mingxuan Du Yuanhong Liu Liang Zhang Shixia Mu Cuiping Li Junhui Li Planning and Assessment Center Department State Grid Henan Economic Research InstituteZhengzhou450000China Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin132012China Development Planning Department State Grid Henan Electric Power CompanyZhengzhou450000China Innovation Development Research Center State Grid Shanghai Energy Internet Research Institute Co.Ltd.Shanghai201210China State Grid Simulation Center China Electric Power Research Institute Co.Ltd.Beijing100192China

After the integration of large-scale DistributedGeneration(DG)into the distribution network,the randomness and volatility of its output result in a reduction of spatiotemporal alignment between power generation and demand in the distribution network,exacerbating the phenomenon of wind and solar power *** a novel power system model,the fundamental concept of Regional Autonomous Power Grids(RAPGs)is to achieve localized management and energy autonomy,thereby facilitating the effective consumption of ***,this paper proposes a distributed resource planning strategy that enhances the autonomy capabilities of regional power grids by considering multiple evaluation indexes for ***,a regional Energy Storage(ES)configuration strategy is *** strategy can select a suitable reference value for the upper limit of ES configuration based on the regional load andDGoutput to maximize the elimination of source load deviations in the region as the upper limit constraint of ES ***,a control strategy for regional ES is proposed,the charging and discharging reference line of ES is set,and multiple autonomy and economic indexes are used as objective functions to select different proportions of ES to control the distributed resources of the regional power grid and establish evaluation indexes of the internal regional generation and load power ratio,the proportion of power supply matching hours,new energy consumption rate and tie line power imbalance outside the region to evaluate changes in the regional autonomy *** final simulation results showthat in the real regional grid example,the planning method in the planning year in the region of the overall power supply matching hour ratio and new energy consumption rate increased by 3.9%and 4.8%on average,and the power imbalance of the tie line decreased by 7.8%on *** proposed planning approach enables the maximization of regional autonomy while effectively smoothing the fluct

关键词： Regional autonomous power grid distributed generation distributed energy storage regional planning strategy evaluation index

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