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Correction: Associations between demographics and clinical ideology, beliefs, and practice patterns: a secondary analysis of a survey of randomly sampled United States chiropractors

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BMC complementary medicine and therapies 2023年第1期23卷 426页

作者： Zachary A Cupler Jordan A Gliedt Stephen M Perle Aaron A Puhl Michael J Schneider Butler VA Health Care System Butler PA USA. Zachary.cupler@va.gov. Institute for Clinical Research Education University of Pittsburgh Pittsburgh PA USA. Zachary.cupler@va.gov. Department of Neurosurgery Medical College of Wisconsin Milwaukee WI USA. Big Data Interrogation Group AECC University College Bournemouth Dorset UK. Discipline of Chiropractic College of Science Health Engineering and Education Murdoch University Murdoch WA Australia. Private Practice Able Body Health Clinic Lethbridge AB Canada. Department of Physical Therapy University of Pittsburgh Pittsburgh PA USA. Clinical and Translational Science Institute University of Pittsburgh Pittsburgh PA USA.

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Flexible, ultrathin bioelectronic materials and devices for chronically stable neural interfaces

Brain‐X

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Brain‐X 2023年第4期1卷

作者： Lianjie Zhou Zhongyuan Wu Mubai Sun Jaejin Park Mengdi Han Ming Wang Junsheng Yu Zengfeng Di Yongfeng Mei Wubin Bai Xinge Yu Ki Jun Yu Enming Song Shanghai Frontiers Science Research Base of Intelligent Optoelectronics and Perception Institute of Optoelectronics Fudan University Shanghai China Contribution: Investigation Visualization Writing - original draft Institute of Agro-food Technology Jilin Academy of Agricultural Sciences Changchun Jilin China Contribution: Data curation Investigation Functional Bio-integrated Electronics and Energy Management Lab School of Electrical and Electronic Engineering Yonsei University Seoul Korea Department of Biomedical Engineering College of Future Technology Peking University Beijing China Contribution: Resources Validation State Key Laboratory of Integrated Chips and Systems Frontier Institute of Chip and System Fudan University Shanghai China State Key Laboratory of Electronic Thin Films and Integrated Devices School of Optoelectronic Science and Engineering University of Electronic Science and Technology of China (UESTC) Chengdu Sichuan China State Key Laboratory of Functional Materials for Informatics Shanghai Institute of Microsystem and Information Technology Chinese Academy of Sciences Shanghai China Department of Material Science Fudan University Shanghai China Department of Applied Physical Sciences University of North Carolina at Chapel Hill Chapel Hill North Carolina USA Department of Biomedical Engineering City University of Hong Kong Hong Kong SAR China Wubin Bai Xinge Yu Ki Jun Yu and Enming Song. Contribution: Conceptualization Methodology Resources Supervision Writing - review & editing

Advanced technologies that can establish intimate, long-lived functional interfaces with neural systems have attracted increasing interest due to their wide-ranging applications in neuroscience, bioelectronic medicine, and the associated treatment of neurodegenerative diseases. A critical challenge of significance remains in the development of electronic platforms that offer conformal contact with soft brain tissue for the sensing or stimulation of brain activities and chronically stable operation in vivo, at scales that range from cellular-level resolution to macroscopic areas. This review summarizes recent advances in this field, with an emphasis on the use of demonstrated concepts, constituent materials, engineered designs, and system integration to address the current challenges. The article begins with an overview of recent bioelectronic platforms with unique form factors, ranging from filamentary probes to conformal sheets and three-dimensional frameworks for alleviating the mechanical mismatch between interface materials and neural tissues. Next, active interfaces which utilize inorganic/organic semiconductor-enabled devices are reviewed, highlighting various working principles of recording mechanisms including capacitively and conductively coupled sensing enabled by high transistor matrices at high spatiotemporal resolution. The subsequent section presents approaches to biological integration which use active materials for multiplexed addressing, local amplification and multimodal operation with high-channel-count and large-scale electronic systems in a safe fashion that provides multi-decade stable performance in both animal models and human subjects. The advances summarized in this review will guide the future direction of this technology and provide a basis for next-generation chronic neural interfaces with long-lived high-performance operation.

关键词： neural interface flexibility passive electrodes active recording barrier materials chronic stability

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Secure Cryptography Infrastructures in the Cloud

Secure Cryptography Infrastructures in the Cloud

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IEEE Global Communications Conference

作者： Dawei Chu Kaijie Zhu Quanwei Cai Jingqiang Lin Fengjun Li Le Guan Lingchen Zhang State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences School of Cyber Security University of Chinese Academy of Sciences National Digital Switching System Engineering & Technological R&D Center CHINA Data Assurance and Communication Security Research Center Chinese Academy of Sciences Department of Electrical Engineering and Computer Science The University of Kansas USA Department of Computer Science University of Georgia USA

ISBN: (数字)9781728109626

ISBN: (纸本)9781728109633

Information systems are deployed in clouds as virtual machines (VMs) for better agility, elasticity and reliability. It is necessary to safekeep their cryptographic keys, e.g., the private keys used in TLS and SSH, against various attacks. However, existing virtualization solutions do not improve the cryptography facilities of in-cloud systems. This paper presents SECRIN, a secure cryptography infrastructure for VMs in the cloud. SECRIN is composed of a) virtual cryptographic devices implemented in VM monitors (VMMs), and b) a device management tool integrated in the virtualization management system. A virtual device receives requests from VMs, computes with cryptographic keys within the VMM and returns results. The keys appear only in the VMM's memory space, so that they are kept secret even if the VMs were compromised. With the management tool, the operator of virtualization management systems assigns virtual cryptographic devices to a VM as well as other resources, while the tenant (or owner) of a VM still holds proper controls on the keys. The virtual devices work compatibly with live migration, and the cryptographic computations are not interrupted when the VMs are moving from a host to another. We develop the SECRIN prototype with KVM-QEMU and oVirt. Experimental results show that, it works compatibly with existing virtualization solutions, provides reliable cryptographic computing services for applications, and is secure against attacks happening in VMs.

关键词： Cryptography Virtualization Cloud computing Virtual machine monitors Password Reliability Tools

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A fundamental theorem for eco-environmental surface modelling and its applications

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Science China Earth Sciences 2020年第8期63卷 1092-1112页

作者： Tianxiang YUE Na ZHAO Yu LIU Yifu WANG Bin ZHANG Zhengping DU Zemeng FAN Wenjiao SHI Chuanfa CHEN Mingwei ZHAO Dunjiang SONG Shihai WANG Yinjun SONG Changqing YAN Qiquan LI Xiaofang SUN Lili ZHANG Yongzhong TIAN Wei WANG Ying’an WANG Shengnan MA Hongsheng HUANG Yimin LU Qing WANG Chenliang WANG Yuzhu WANG Ming LU Wei ZHOU Yi LIU Xiaozhe YIN Zong WANG Zhengyi BAO Miaomiao ZHAO Yapeng ZHAO Yimeng JIAO Ufra NASEER Bin FAN Saibo LI Yang YANG John PWILSON State Key L aboratory of Resources and Environment Information System Institute of Geographical Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101China College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049China College of Land Resources and Environment Jiangxi Agricultural UniversityNanchang 330045China College of Geomatics Shandong University of Science and TechnologyQingdao 266590China College of Forestry Beijing Forestry UniversityBeijing 100083China School of Land and Resources China West Normal UniversityNanchong 637002China College of Geographical Information and Tourism Chuzhou UniversityChuzhou 239000China Institutes of Science and Development Chinese Academy of SciencesBeijing 100190China Department of Information Engineering Shandong University of Science and TechnologyTai'an 271019China College of Resources Sichuan Agricultural UniversityChengdu 611130China College of Geography and Tourism Qufu Normal UniversityRizhao 276828China Aerospace Information Research Institute Chinese Academy of SciencesBeijing 100101China School of Geographical Science Southwest UniversityChongqing 400715China National Disaster Reduction Center of China Ministry of Emergency ManagementBeijing 100721China Department for Population Data China Population and Development Research CenterBeijing 100081China Department for Industrial Standard China Standardization AdministrationBeijing 100088China The Academy of Digital China Fuzhou UniversityFuzhou 350002China National Institute of Environmental Health Chinese Center for Disease Control and PreventionBeijing 100021China School of Information Engineering China University of GeoscienceBeijing 100083China Qian Xuesen Laboratory of Space Technology Beijing 100094China College of Architecture and Urban Planning Chongqing Jiaotong UniversityChongqing 400074China Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application Nanjing

We propose a fundamental theorem for eco-environmental surface modelling(FTEEM) in order to apply it into the fields of ecology and environmental science more easily after the fundamental theorem for Earth’s surface system modeling(FTESM). The Beijing-Tianjin-Hebei(BTH) region is taken as a case area to conduct empirical studies of algorithms for spatial upscaling, spatial downscaling, spatial interpolation, data fusion and model-data assimilation, which are based on high accuracy surface modelling(HASM), corresponding with corollaries of FTEEM. The case studies demonstrate how eco-environmental surface modelling is substantially improved when both extrinsic and intrinsic information are used along with an appropriate method of HASM. Compared with classic algorithms, the HASM-based algorithm for spatial upscaling reduced the root-meansquare error of the BTH elevation surface by 9 m. The HASM-based algorithm for spatial downscaling reduced the relative error of future scenarios of annual mean temperature by 16%. The HASM-based algorithm for spatial interpolation reduced the relative error of change trend of annual mean precipitation by 0.2%. The HASM-based algorithm for data fusion reduced the relative error of change trend of annual mean temperature by 70%. The HASM-based algorithm for model-data assimilation reduced the relative error of carbon stocks by 40%. We propose five theoretical challenges and three application problems of HASM that need to be addressed to improve FTEEM.

关键词： HASM FTEEM Spatial upscaling Spatial downscaling Spatial interpolation data fusion Model-data assimilation Model coupling

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Designing metamaterials with quantum annealing and factorization machines

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Physical Review Research 2020年第1期2卷 013319-013319页

作者： Koki Kitai Jiang Guo Shenghong Ju Shu Tanaka Koji Tsuda Junichiro Shiomi Ryo Tamura Graduate School of Frontier Sciences The University of Tokyo Chiba 277-8568 Japan Department of Mechanical Engineering The University of Tokyo Tokyo 113-8654 Japan Research and Services Division of Materials Data and Integrated System National Institute for Materials Science Ibaraki 305-0047 Japan Green Computing Systems Research Organization Waseda University Tokyo 162-0042 Japan JST PRESTO Saitama 332-0012 Japan RIKEN Center for Advanced Intelligence Project Tokyo 103-0027 Japan International Center for Materials Nanoarchitectonics National Institute for Materials Science Ibaraki 305-0044 Japan

Automated materials design with machine learning is increasingly common in recent years. Theoretically, it is characterized as black-box optimization in the space of candidate materials. Since the difficulty of this problem grows exponentially in the number of variables, designing complex materials is often beyond the ability of classical algorithms. We show how quantum annealing can be incorporated into automated materials discovery and conduct a proof-of-principle study on designing complex thermofunctional metamaterials. Our algorithm consists of three parts: regression for a target property by factorization machine, selection of candidate metamaterial based on the regression results, and simulation of the metamaterial property. To accelerate the selection part, we rely on the D-Wave 2000Q quantum annealer. Our method is used to design complex structures of wavelength selective radiators showing much better concordance with the thermal atmospheric transparency window in comparison to existing human-designed alternatives.

关键词： Adiabatic quantum optimization Metamaterials Machine learning

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Deep learning for LiDAR point clouds in autonomous driving: A review

arXiv

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arXiv 2020年

作者： Li, Ying Ma, Lingfei Zhong, Zilong Liu, Fei Cao, Dongpu Li, Jonathan Chapman, Michael A. Department of Geography and Environmental Management University of Waterloo 200 University Avenue West WaterlooN2L 3G1 Canada School of Data and Computer Science Sun Yat-Sen University Guangzhou510006 China Xilinx Technology Beijing Limited Beijing100083 China Waterloo Cognitive Autonomous Driving Lab University of Waterloo N2L 3G1 Canada Departments of System Design Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Civil Engineering Ryerson University TorontoONM5B 2K3 Canada

Recently, the advancement of deep learning in discriminative feature learning from 3D LiDAR data has led to rapid development in the field of autonomous driving. However, automated processing uneven, unstructured, noisy, and massive 3D point clouds is a challenging and tedious task. In this paper, we provide a systematic review of existing compelling deep learning architectures applied in LiDAR point clouds, detailing for specific tasks in autonomous driving such as segmentation, detection, and classification. Although several published research papers focus on specific topics in computer vision for autonomous vehicles, to date, no general survey on deep learning applied in LiDAR point clouds for autonomous vehicles exists. Thus, the goal of this paper is to narrow the gap in this topic. More than 140 key contributions in the recent five years are summarized in this survey, including the milestone 3D deep architectures, the remarkable deep learning applications in 3D semantic segmentation, object detection, and classification;specific datasets, evaluation metrics, and the state of the art performance. Finally, we conclude the remaining challenges and future researches. Copyright © 2020, The Authors. All rights reserved.

关键词： Object detection

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Petri Net Control Method for Pipe-line systems and Its Implementation via CIF3 ⁎

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IFAC-PapersOnLine 2019年第24期52卷 261-266页

作者： YuHao Fu JiLiang Luo Huifeng Wu Jianhong Ye Yi-sheng Huang College Information Science and Engineering Huaqiao University Xiamen 361021 China College Information Science and Engineering Huaqiao University Xiamen 361021 China and also with Fujian Engineering Research Center of Motor Control and System Optimal Schedule Xiamen 361021 China Institute of Intelligent and Software Technology Hangzhou Dianzi University Hangzhou 310018 China Computer Science and Technology Huaqiao University Xiamen 361021 China and also with Fujian Provincial Key Laboratory of Data Intensive Computing Quanzhou 362000 China Department of Electrical Engineering National Ilan University Taiwan

As for a pipe-line system subjected to complex operations, an approach is proposed to synthesize the controller via Petri nets (PNs) such that the plant is run as concurrently as possible and the loads of equipments are balanced. A P-timed and labeled PN is designed to model the whole process of a pipe-line system, where tasks, including transporting material from one tank to another and cleaning tank, are represented by operational places, and level sensors amounted in tanks are represented by labels assigned to transitions. Further, monitor places are designed to resolve the conflict relations among tasks due to the shared valves and pipes. An method is presented to translate an PN controller into a CIF3 (Compositional Interchange Format) model, which can be converted into a PLC program in the CIF3 tool. A beer filtration plant is taken as an example to illustrate the approach, and its simulation experiments are carried out to verify the theoretic results.

关键词： Chemical plant Valve control Petri net CIF3

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Author Correction: Mapping annual 10-m soybean cropland with spatiotemporal sample migration

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Scientific data 2024年第1期11卷 565页

作者： Hongchi Zhang Zihang Lou Dailiang Peng Bing Zhang Wang Luo Jianxi Huang Xiaoyang Zhang Le Yu Fumin Wang Linsheng Huang Guohua Liu Shuang Gao Jinkang Hu Songlin Yang Enhui Cheng Key Laboratory of Digital Earth Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing 100094 China. International Research Center of Big Data for Sustainable Development Goals Beijing 100094 China. University of Chinese Academy of Sciences Beijing 100094 China. Key Laboratory of Digital Earth Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing 100094 China. pengdl@***. International Research Center of Big Data for Sustainable Development Goals Beijing 100094 China. pengdl@***. Key Laboratory of Digital Earth Science Aerospace Information Research Institute Chinese Academy of Sciences Beijing 100094 China. zhangbing@***. University of Chinese Academy of Sciences Beijing 100094 China. zhangbing@***. Jiangxi Nuclearindustry Surveying and Mapping Institute Group Co. Ltd Nanchang 330038 China. College of Land Science and Technology China Agricultural University Beijing 100083 China. Geospatial Sciences Center of Excellence Department of Geography Geospatial Sciences South Dakota State University Brookings SD 57007 USA. Department of Earth System Science Tsinghua University Beijing 100084 China. Institute of Applied Remote Sensing & Information Technology Zhejiang University Hangzhou 310058 China. National Engineering Research Center for Agro-Ecological Big Data Analysis & Application Anhui University Hefei 230601 China. Innovation Academy for Microsatellites Chinese Academy of Sciences Shanghai 200120 China.

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The Extreme Space Weather Event of 1872 February: Sunspots, Magnetic Disturbance, and Auroral Displays

arXiv

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arXiv 2024年

作者： Hayakawa, Hisashi Cliver, Edward W. Clette, Frédéric Ebihara, Yusuke Toriumi, Shin Ermolli, Ilaria Chatzistergos, Theodosios Hattori, Kentaro Knipp, Delores J. Blake, Séan P. Cauzzi, Gianna Reardon, Kevin Bourdin, Philippe-A Just, Dorothea Vokhmyanin, Mikhail Matsumoto, Keitaro Miyoshi, Yoshizumi Ribeiro, José R. Correia, Ana P. Willis, David M. Wild, Matthew N. Silverman, Sam M. Institute for Space-Earth Environmental Research and Institute for Advanced Researches Nagoya University Nagoya4648601 Japan Science and Technology Facilities Council RAL Space Rutherford Appleton Laboratory Harwell Campus DidcotOX11 0QX United Kingdom National Solar Observatory BoulderCO80303 United States World Data Center SILSO Observatoire Royal de Belgique Brussels1180 Belgium Research Institute for Sustainable Humanosphere Kyoto University Uji6100011 Japan Unit of Synergetic Studies for Space Kyoto University Kyoto6068306 Japan Institute of Space and Astronautical Science Japan Aerospace Exploration Agency Kanagawa Sagamihara2525210 Japan INAF Osservatorio Astronomico di Roma Monte Porzio CatoneI-00078 Italy Max Planck Institute for Solar System Research GöttingenD-37077 Germany Faculty of Societal Safety Sciences Kansai University Takatsuki5691116 Japan Smead Aerospace Engineering Sciences Department 429 UCB University of Colorado Boulder BoulderCO80309 United States Heliophysics Science Division NASA Goddard Space Flight Center GreenbeltMD United States Catholic University of America WashingtonDC United States University of Graz Institute of Physics Universitätsplatz 5 Graz8010 Austria Institut für Weltraumforschung Österreichische Akademie der Wissenschaften Graz8042 Austria University of Oulu OuluFI-90014 Finland Escola Secundária Henrique Medina Esposende Av. Dr. Henrique Barros Lima Esposende4740-203 Portugal 18 Ingleside Road LexingtonMA02420 United States

We review observations of solar activity, geomagnetic variation, and auroral visibility for the extreme geomagnetic storm on 1872 February 4. The extreme storm (referred to here as the Chapman-Silverman storm) apparently originated from a complex active region of moderate area (≈ 500 μsh) that was favorably situated near disk center (S19° E05°). There is circumstantial evidence for an eruption from this region at 9-10 UT on 1872 February 3, based on the location, complexity, and evolution of the region, and on reports of prominence activations, which yields a plausible transit time of ≈29 hr to Earth. Magnetograms show that the storm began with a sudden commencement at ≈14:27 UT and allow a minimum Dst estimate of £ −834 nT. Overhead aurorae were credibly reported at Jacobabad (British India) and Shanghai (China), both at 19°.9 in magnetic latitude (MLAT) and 24°.2 in invariant latitude (ILAT). Auroral visibility was reported from 13 locations with MLAT below |20|° for the 1872 storm (ranging from |10°.0|-|19°.9| MLAT) versus one each for the 1859 storm (|17°.3| MLAT) and the 1921 storm (|16.°2| MLAT). The auroral extension and conservative storm intensity indicate a magnetic storm of comparable strength to the extreme storms of 1859 September (25°.1 ± 0°.5 ILAT and −949 ± 31 nT) and 1921 May (27°.1 ILAT and −907 ± 132 nT), which places the 1872 storm among the three largest magnetic storms yet observed. © 2024, CC BY.

关键词： Geomagnetism

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OpenHI2 - Open source histopathological image platform

OpenHI2 - Open source histopathological image platform

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IEEE International Conference on Bioinformatics and Biomedicine

作者： Pargorn Puttapirat Haichuan Zhang Jingyi Deng Yuxin Dong Jiangbo Shi Hongyu He Zeyu Gao Chunbao Wang Xiangrong Zhang Chen Li National Engineering Lab for Big Data Analytics Xi'an Jiao tong University Shaanxi Province Key Laboratory of Satellite and Terrestrial Network Tech. R&D Xi'an Jiaotong University Department of Power System and Automation School of Electrical Engineering Xi'an Jiaotong University Department of Pathology the First Affiliated Hospital of Xi'an Jiaotong University Institute of Intelligent Information Processing Xidian University

ISBN: (纸本)9781728118680

Transition from conventional to digital pathology requires a new category of biomedical informatic infrastructure which could facilitate delicate pathological routine. Pathological diagnoses are sensitive to many external factors and is known to be subjective. Only systems that can meet strict requirements in pathology would be able to run along pathological routines and eventually digitized the area, and the developed platform should comply with existing pathological routines and international standards. Currently, there are a number of available software tools which can perform histopathological tasks including virtual slide viewing, annotating, and basic image analysis, however, none of them can serve as a digital platform for pathology. Here we describe OpenHI2, an enhanced version Open Histopathological Image platform which is capable of supporting all basic pathological tasks and file formats;ready to be deployed in medical institutions on a standard server environment or cloud computing infrastructure. In this paper, we also describe the development decisions for the platform and propose solutions to overcome technical challenges including responsive region retrieval and viewing, virtual slide magnification, recording of diagnostic areas. These factors would promote OpenHI2 be used as a platform for histopathological images in real-world clinical settings. Furthermore, in research, OpenHI2 inherited the annotation functionality from the previous version, thus acquired annotations can be directly utilized by the newly added machine learning module which include popular machine learning models to perform tasks such as histology image classification and segmentation in the same environment. Addition can be made to the platform since each component is modularized and fully documented. OpenHI2 is free, open-source, and available at .

关键词： OpenHI digital pathology histopathological image analysis open source software open source software pathology Platform Software Tools open source Religious Missions External factors images

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