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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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Where Does AlphaGo Go: From Church-Turing Thesis to AlphaGo Thesis and Beyond

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IEEE/CAA Journal of Automatica Sinica 2016年第2期3卷 113-120页

作者： Fei-Yue Wang Jun Jason Zhang Xinhu Zheng Xiao Wang Yong Yuan Xiaoxiao Dai Jie Zhang Liuqing Yang IEEE the State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences (SKL-MCCS CASIA) Research Center of Computational Experiments and Parallel Systems The National University of Defense Technology the Department of Electrical and Computer Engineering Ritchie School of Engineering and Computer Science University of Denver the Department of Computer Science and Engineering University of Minnesota the Qingdao Academy of Intelligent Industries (QAII) Qingdao Shandong China and SKL-MCCS CASIA the Department of Electrical and Computer Engineering Colorado State University

An investigation on the impact and significance of the AlphaGo vs. Lee Sedol Go match is conducted, and concludes with a conjecture of the AlphaGo Thesis and its extension in accordance with the Church-Turing Thesis in the history of computing. It is postulated that the architecture and method utilized by the AlphaGo program provide an engineering solution for tackling issues in complexity and intelligence. Specifically, the AlphaGo Thesis implies that any effective procedure for hard decision problems such as NP-hard can be implemented with AlphaGo-like approach. Deep rule-based networks are proposed in attempt to establish an understandable structure for deep neural networks in deep learning. The success of AlphaGo and corresponding thesis ensure the technical soundness of the parallel intelligence approach for intelligent control and management of complex systems and knowledge automation. © 2014 Chinese Association of Automation.

关键词： Religious buildings

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XGCN:a library for large-scale graph neural network recommendations

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Frontiers of computer Science 2024年第3期18卷 247-249页

作者： Xiran SONG Hong HUANG Jianxun LIAN Hai JIN National Engineering Research Center for Big Data Technology and System Services Computing Technology and System LabCluster and Grid Computing LabSchool of Computer Science and TechnologyHuazhong University of Science and TechnologyWuhan 430074China Microsoft Research Asia Beijing 100080China

1 Introduction Graph Neural Networks(GNNs)have gained widespread adoption in recommendation systems,and nowadays there is a pressing need to effectively manage large-scale graph data[1].When it comes to large graphs,GNNs may encounter the scalability issue stemming from their multi-layer messagepassing ***,scaling GNNs has emerged as a crucial research area in recent years,with numerous scaling strategies being proposed.

关键词： scaling gained operations

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Grading the Severity of Mispronunciations in CAPT Based on Statistical Analysis and Computational Speech Perception

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Journal of computer Science & technology 2014年第5期29卷 751-761页

作者：贾珈梁伟俭吴育昊张秀龙王昊蔡莲红蒙美玲 Department of Computer Science and Technology Tsinghua University Tsinghua National Laboratory for Information Science and Technology Tsinghua University Key Laboratory of Pervasive Computing Ministry of Education Human-Computer Communications Laboratory Department of Systems Engineering and Engineering Management The Chinese University of Hong Kong Tsinghua-CUHK Joint Research Center for Media Sciences Technologies and Systems

computer-aided pronunciation training（CAPT） technologies enable the use of automatic speech recognition to detect mispronunciations in second language（L2） learners＇ speech. In order to further facilitate learning, we aim to develop a principle-based method for generating a gradation of the severity of mispronunciations. This paper presents an approach towards gradation that is motivated by auditory perception. We have developed a computational method for generating a perceptual distance（PD） between two spoken phonemes. This is used to compute the auditory confusion of native language（L1）. PD is found to correlate well with the mispronunciations detected in CAPT system for Chinese learners of English,i.e., L1 being Chinese（Mandarin and Cantonese） and L2 being US English. The results show that auditory confusion is indicative of pronunciation confusions in L2 learning. PD can also be used to help us grade the severity of errors（i.e.,mispronunciations that confuse more distant phonemes are more severe） and accordingly prioritize the order of corrective feedback generated for the learners.

关键词： second language learning computer-aided pronunciation training mispronunciation computational speech perception

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Method for segmentation of overlapping fish images in aquaculture

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International Journal of Agricultural and Biological engineering 2019年第6期12卷 135-142页

作者： Chao Zhou Kai Lin Daming Xu Jintao Liu Song Zhang Chuanheng Sun Xinting Yang Beijing Research Center for Information Technology in Agriculture Beijing 100097China National Engineering Research Center for Information Technology in Agriculture Beijing 100097China National Engineering Laboratory for Agri-product Quality Traceability Beijing 100097China Beijing Fisheries Research Institute Beijing 100068China Department of Computer Science University of AlmeriaAlmeria04120Spain

Individual fish segmentation is a prerequisite for feature extraction and object identification in any machine vision *** this paper,a method for segmentation of overlapping fish images in aquaculture was ***,the shape factor was used to determine whether an overlap exists in the ***,the corner points were extracted using the curvature scale space algorithm,and the skeleton obtained by the improved Zhang-Suen thinning ***,intersecting points were obtained,and the overlapped region was *** results show that the average error rate and average segmentation efficiency of this method was 10%and 90%,*** with the traditional watershed method,the separation point is accurate,and the segmentation accuracy is ***,the proposed method achieves better performance in segmentation accuracy and *** method can be applied to multi-target segmentation and fish behavior analysis systems,and it can effectively improve recognition precision.

关键词： aquaculture image processing overlapping segmentation corner detection improved Zhang-Suen algorithm

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Evaluation model for service life of dam based on time-varying risk probability

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Science China(Technological Sciences) 2009年第7期52卷 1966-1973页

作者： SU HuaiZhi WEN ZhiPing HU Jiang WU ZhongRu College of Water Conservancy and Hydropower Engineering of Hohai University Nanjing 210098China National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety Nanjing 210098China College of Computer Engineering Nanjing Institute of TechnologyNanjing 211167China

For many dam projects in China, the 50-year designed life time is coming to an end. It is urgent to study the theory and method to evaluate the dam service life. In this paper, firstly, the probability theory of fuzzy event and time-varying effect theory are used to analyze the time-variety of various risk factors in the process of dam operations. A method is proposed to quantify the above time-variety and a model to describe the fuzzy time-varying risk probability for the dam structure is also built. Secondly, the information entropy theory is used to analyze the uncertain degree relationship between the characteristic value of membership function and fuzzy risk probability, and a mathematical method is presented to calculate the time-varying risk probability accordingly. Thirdly, the relation mode between time-varying risk probability and service life is discussed. Based on this relation mode and the acceptable risk probability of dams in China, a method is put forward to evaluate and forecast the dam service life. Finally, the proposed theory and method are used to analyze one concrete dam. The dynamic variability and mutation feature of the dam risk probability are analyzed. The remaining service life of this dam is forecasted. The obtained results can provide technology support for the project management department to make treatment measures of engineering and reasonably arrange reinforce cost. The principles in this paper have wide applicability and can be used in risk analysis for slope instability and other fields.

关键词： dam service life evaluation time-varying risk probability fuzzy probability theory information entropy theory

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Game model of safety monitoring for arch dam deformation

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Science China(Technological Sciences) 2008年第S2期51卷 76-81页

作者： SU HuaiZhi1,2,WU ZhongRu1,2,GU YanChang1,2,HU Jiang1 & WEN ZhiPing3 1 College of Water Conservancy and Hydropower engineering,Hohai University,Nanjing 210098,China 2 national engineering research center of Water Resources Efficient Utilization and engineering Safety,Nanjing 210098,China 3 Department of computer engineering,Nanjing Institute of technology,Nanjing 210013,China College of Water Conservancy and Hydropower Engineering Hohai University Nanjing 210098 China National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety Nanjing 210098 China Department of Computer Engineering Nanjing Institute of Technology Nanjing 210013 China

Arch dam deformation is comprehensively affected by water pressure,temperature,dam's structural behavior and material properties as well as other *** them the water pressure and temperature are external factors(source factors) that cause dam deformation,and dam's structural behavior and material properties are the internal factors of deformation(resistance factors).The dam deformation is the result of the mutual game playing between source factors and resistance ***,resistance factors of structure and materials that reflect resistance character of arch dam structure are introduced into the traditional model,where structure factor is embodied by the flexibility coefficient of dam body and the maximum dam height,and material property is embodied by the elastic modulus of *** the basis of analyzing the correlation between dam deformation and resistance factors,the game model of safety monitoring for arch dam deformation is put forward.

关键词： arch dam deformation monitoring model flexibility coefficient game theory

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Liquid Metal-Exfoliated SnO2-Based Mixed-dimensional Heterostructures for Visible-to-Near-Infrared Photodetection

arXiv

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arXiv 2025年

作者： Nath, Shimul Kanti Syed, Nitu Pan, Wenwu Yu, Yang Liu, Dawei Nielsen, Michael P. Yuwono, Jodie Kumar, Priyank Zhu, Yan Cortie, David L. Nguyen, Chung K. Fu, Lan Roberts, Ann Faraone, Lorenzo Ekins-Daukes, Nicholas J. Lei, Wen KensingtonNSW2052 Australia Australian Research Council Centre of Excellence for Transformative Meta-Optical Systems Department of Electrical Electronic and Computer Engineering The University of Western Australia 35 Stirling Highway PerthWA6009 Australia Australian Research Council Centre of Excellence for Transformative Meta-Optical Systems School of Physics University of Melbourne VIC3010 Australia School of Engineering RMIT University MelbourneVIC3001 Australia Australian Research Council Centre of Excellence for Transformative Meta-Optical Systems Department of Electronic Materials Engineering Research School of Physics The Australian National University CanberraACT2601 Australia Institute of Applied Physics Abbe Center of Photonics Friedrich Schiller University Jena Albert-Einstein-Straße 15 Jena07745 Germany School of Chemical Engineering The University of Adelaide AdelaideSA5005 Australia KensingtonNSW2052 Australia Australian Centre for Neutron Scattering Australian Nuclear Science and Technology Organisation Lucas HeightsNSW2234 Australia

Ultra-thin two-dimensional (2D) materials have gained significant attention for making next-generation optoelectronic devices. Here, we report a large-area heterojunction photodetector fabricated using a liquid metal-printed 2D SnO2 layer transferred onto CdTe thin films. The resulting device demonstrates efficient broadband light sensing from visible to near-infrared wavelengths, with enhanced detectivity and faster photo response than bare CdTe photodetectors. Significantly, the device shows a nearly 105-fold increase in current than the dark current level when illuminated with a 780 nm laser and achieves a specific detectivity of around 1012 Jones, nearly two orders of magnitude higher than a device with pure CdTe thin film. Additionally, temperature-dependent optoelectronic testing shows that the device maintains a stable response up to 140 °C and generates distinctive photocurrent at temperatures up to 80°C, demonstrating its thermal stability. Using band structure analysis, density functional theory (DFT) calculations, and photocurrent mapping, the formation of a p-n junction is indicated, contributing to the enhanced photo response attributed to the efficient carrier separation by the built-in potential in the hetero-junction and the superior electron mobility of 2D SnO2. Our results highlight the effectiveness of integrating liquid metal-exfoliated 2D materials for enhanced photodetector performance. © 2025, CC BY.

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Multi-Class Segmentation of Aortic Branches and Zones in Computed Tomography Angiography: The AortaSeg24 Challenge

arXiv

引用

arXiv 2025年

作者： Imran, Muhammad Krebs, Jonathan R. Sivaraman, Vishal Balaji Zhang, Teng Kumar, Amarjeet Ueland, Walker R. Fassler, Michael J. Huang, Jinlong Sun, Xiao Wang, Lisheng Shi, Pengcheng Rokuss, Maximilian Baumgartner, Michael Kirchhof, Yannick Maier-Hein, Klaus H. Isensee, Fabian Liu, Shuolin Han, Bing Nguyen, Bong Thanh Shin, Dong-Jin Ji-Woo, Park Choi, Mathew Uhm, Kwang-Hyun Ko, Sung-Jea Lee, Chanwoong Chun, Jaehee Kim, Jin Sung Zhang, Minghui Zhang, Hanxiao You, Xin Gu, Yun Pan, Zhaohong Liu, Xuan Liang, Xiaokun Tiefenthaler, Markus Almar-Munoz, Enrique Schwab, Matthias Kotyushev, Mikhail Epifanov, Rostislav Wodzinski, Marek Müller, Henning Qayyum, Abdul Mazher, Moona Niederer, Steven A. Wang, Zhiwei Yang, Kaixiang Ren, Jintao Korreman, Stine Sofia Gao, Yuchong Zeng, Hongye Zheng, Haoyu Zheng, Rui Yue, Jinghua Zhou, Fugen Liu, Bo Cosman, Alexander Liang, Muxuan Zhao, Chang Upchurch, Gilbert R. Ma, Jun Zhou, Yuyin Cooper, Michol A. Shao, Wei Department of Medicine University of Florida GainesvilleFL32611 United States Department of Surgery University of Florida GainesvilleFL32611 United States Department of Electrical and Computer Engineering University of Florida GainesvilleFL32611 United States Department of Computer Information Science and Engineering University of Florida GainesvilleFL32611 United States Shanghai Jiao Tong University Shanghai China Electronic & Information Engineering School Harbin Institute of Technology [Shenzhen Shenzhen China Division of Medical Image Computing German Cancer Research Center [DKFZ Heidelberg Germany CO. LTD Beijing China MedAI Seoul Korea Republic of Korea University Seoul Korea Republic of Department of Radiation Oncology Yonsei Cancer Center Heavy Ion Therapy Research Institute Yonsei University College of Medicine Seoul Korea Republic of Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Medical University of Innsbruck Innsbruck Austria Novosibirsk State University Novosibirsk Russia AGH University of Krakow Krakow Poland Sierre Switzerland University of Geneva Geneva Switzerland The Sense Innovation and Research Center Sion Switzerland National Heart and Lung Institute Faculty of Medicine Imperial College London London United Kingdom Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Hubei Wuhan China Aarhus University Department of Clinical Medicine Nordre Palle Juul-Jensens Blvd. 11 Aarhus8200 Denmark Shanghaitech University Pudong Shanghai China Image Processing Center Beihang University Beijing China Department of Computer Science and Engineering University of California Santa CruzCA95064 United States Department of Biostatistics University of Florida GainesvilleFL32611 United States University Health Network ON Canada Agronomy Department University of F

Multi-class segmentation of the aorta in computed tomography angiography (CTA) scans is essential for diagnosing and planning complex endovascular treatments for patients with aortic dissections. However, existing methods reduce aortic segmentation to a binary problem, limiting their ability to measure diameters across different branches and zones. Furthermore, no open-source dataset is currently available to support the development of multi-class aortic segmentation methods. To address this gap, we organized the AortaSeg24 MICCAI Challenge, introducing the first dataset of 100 CTA volumes annotated for 23 clinically relevant aortic branches and zones. This dataset was designed to facilitate both model development and validation. The challenge attracted 121 teams worldwide, with participants leveraging state-of-the-art frameworks such as nnU-Net and exploring novel techniques, including cascaded models, data augmentation strategies, and custom loss functions. We evaluated the submitted algorithms using the Dice Similarity Coefficient (DSC) and Normalized Surface Distance (NSD), highlighting the approaches adopted by the top five performing teams. This paper presents the challenge design, dataset details, evaluation metrics, and an in-depth analysis of the top-performing algorithms. The annotated dataset, evaluation code, and implementations of the leading methods are publicly available to support further research. All resources can be accessed at https://***. © 2025, CC BY-NC-SA.

关键词： computerized tomography

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Towards Atomic Scale Quantum Dots in Silicon: An Ultra-Efficient and Robust Subtractor Using Proposed P-Shaped Pattern

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IEEE Transactions on Nanotechnology 2024年 23卷 482-489页

作者： Rasmi, Hadi Mosleh, Mohammad Navimipour, Nima Jafari Kheyrandish, Mohammad Dezful Branch Islamic Azad University Department of Computer Engineering Dezful313 Iran Kadir Has University Department of Computer Engineering Faculty of Engineering and Natural Sciences Istanbul34083 Turkey National Yunlin University of Science and Technology Future Technology Research Center Yunlin Douliou64002 Taiwan Western Caspian University Research Center of High Technologies and Innovative Engineering Baku Azerbaijan

Today, Complementary Metal-Oxide-Semiconductor (CMOS) technology faces critical challenges, such as power consumption and current leakage at the nanoscale. Therefore, Atomic Silicon Dangling Bond (ASDB) technology has been proposed as one of the best candidates to replace CMOS technology;due to its high-speed switching and low power consumption. Among the most important issues in ASDB nanotechnology, output stability and robustness against possible faults may be focused. This paper first introduces a novel P-shaped pattern in ASDB, for designing stable and robust primitive logic gates, including AND, NAND, OR, NOR and XOR. Then, two combinational circuits, half-subtractor and full-subtractor, are proposed by the proposed ASDB gates. The simulation results show high output stability as well as adequate robustness, against various defects obtained by the proposed designs;on average, they have improvements of more than 56% and 62%, against DB omission defects and extra cell deposition defects;respectively. Also, the results of the investigations show that the proposed circuits have been improved by 65%, 21% and 2%, in terms of occupied area, energy and occurrence, respectively;compared to the previous works. © 2002-2012 IEEE.

关键词： Silicon

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