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Social networks of reintroduced Przewalski's horses in the Great Gobi B Strictly Protected Area (Mongolia)

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Current Zoology 2024年第2期70卷 182-194页

作者： Anna Bernatkova Ganbaatar Oyunsaikhan Jaroslav Simek Martina Komarkova Francisco Ceacero Faculty of Tropical AgriSciences Czech University of Life Sciences PragueCzech Republic Great Gobi B Strictly Protected Area Takhin TalMongolia Zoo Praha U Trojského zamku 120/3PragueCzech Republic

Analyzing social networks is a powerful tool for understanding the ecology of social *** most studies focus on the role of each group member,few compare groups with different *** current population of Przewalski's horses Equus ferus przewalskii at the Great Gobi B Strictly Protected Area(Mongolia)includes groups of wild-born and captive-bred individuals with different experiences with the area(acclimatizing,long-term reintroduced,and wild-born),therefore serving as an ideal natural behavioral *** filmed 11 groups for 141.5 hours in summer 2018(July),late spring 2019(May,June),and autumn 2019(September,October).Affiliative and agonistic interactions were recorded,and social networks were *** tested the influence of origin,experience,season,sex,age,relative time belonging to the group,relat-edness,and dominance rank on different network indices at the individual and group *** found that groups with greater experience in the area are generally better connected than members of the newly formed ***,these strong networks were created by wild-born individuals with very low interaction *** the contrary,inexperienced groups composed of captive-bred individuals displayed many inter actions but created weak social *** results show a trend of behavioral transition from acclimatizing through long-term reintroduced to wild-born groups,supporting that the newly formed groups of released Przewalski's horses need time to display the typical social behavior patterns of wild-born ***-term monitoring of released Przewalski's horses is recommended to promote the success of this reintroduction program.

关键词： Przewalski's horses reintroduction social behavior soft-release.

Robust Machine Learning Mapping of sEMG Signals to Future Actuator Commands in Biomechatronic Devices

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Journal of Bionic Engineering 2024年第1期21卷 270-287页

作者： Ali Nasr Sydney Bell Rachel L.Whittaker Clark R.Dickerson John McPhee Systems Design Engineering University of WaterlooWaterloo N2L 3G1Canada Kinesiology and Health Sciences University of WaterlooWaterloo N2L3G3Canada

A machine learning model for regression of interrupted Surface Electromyography(sEMG)signals to future control-oriented signals(e.g.,robot’s joint angle and assistive torque)of an active biomechatronic device for high-level myoelectric-based hierarchical control is proposed.A Recurrent Neural Network(RNN)was trained using output data,initially obtained from offline optimization of the biomechatronic(human–robot)device and shifted by the prediction *** input of the RNN consisted of interrupted sEMG signals(to mimic signal disconnections)and previous kinematic signals of the assistive *** RNN with a 0.1-s prediction horizon could predict the control-oriented joint angle and assistive torque with 92%and 86.5%regression accuracy,respectively,for the test *** proposed approach permits a fast,predictive,and direct estimation of control-oriented signals instead of an iterative process that optimizes assistive torque in the inverse dynamic simulation of a multibody human–robot *** with these interrupted input signals significantly improves the regression accuracy in the case of sEMG signal *** Robust Predictive Control-oriented Machine Learning(Robust-MuscleNET)model can support volitional high-level myoelectric-based control of biomechatronic devices,such as exoskeletons,prostheses,and assistive/resistive *** work should study the application to prosthesis control as well as the repeatability of the high-level controller with electrode *** low-level hierarchical controller that manages the human–robot interaction,the assistance/resistance strategy,and the actuator coordination should also be studied.

关键词： Myoelectric-based control-Surface electromyography Machine learning Multibody system dynamics Exoskeleton Bionic

Machine learning-guided accelerated discovery of structure-property correlations in lean magnesium alloys for biomedical applications

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Journal of Magnesium and Alloys 2024年第6期12卷 2267-2283页

作者： Sreenivas Raguraman Maitreyee Sharma Priyadarshini Tram Nguyen Ryan McGovern Andrew Kim Adam J.Griebel Paulette Clancy Timothy P.Weihs Department of Materials Science and Engineering Johns Hopkins University3400 N Charles StBaltimore21218MDU.S.A Hopkins Extreme Materials Institute Johns Hopkins University3400 N Charles StBaltimore21218MDU.S.A Department of Chemical and Biomolecular Engineering Johns Hopkins University3400 N Charles StBaltimore21218MDU.S.A Translational Tissue Engineering Center Johns Hopkins School of Medicine400 N BroadwayBaltimore21231MDU.S.A Department of Biomedical Engineering Johns Hopkins University3400 N Charles StBaltimore21218MDU.S.A Research and Development Fort Wayne Metals Research ProductsLLC9609 Ardmore AveFort Wayne46809INU.S.A Department of Mechanical Engineering Johns Hopkins University3400 N Charles StBaltimore21218MDU.S.A

Magnesium alloys are emerging as promising alternatives to traditional orthopedic implant materials thanks to their biodegradability,biocompatibility,and impressive mechanical ***,their rapid in-vivo degradation presents challenges,notably in upholding mechanical integrity over *** study investigates the impact of high-temperature thermal processing on the mechanical and degradation attributes of a lean Mg-Zn-Ca-Mn alloy,*** rapid,cost-efficient characterization methods like X-ray diffraction and optical microscopy,we swiftly examine microstructural changes post-thermal *** Pearson correlation coefficient analysis,we unveil the relationship between microstructural properties and critical targets(properties):hardness and corrosion ***,leveraging the least absolute shrinkage and selection operator(LASSO),we pinpoint the dominant microstructural factors among closely correlated *** findings underscore the significant role of grain size refinement in strengthening and the predominance of the ternary Ca_(2)Mg_(6)Zn_(3)phase in corrosion *** suggests that achieving an optimal blend of strength and corrosion resistance is attainable through fine grains and reduced concentration of ternary *** thorough investigation furnishes valuable insights into the intricate interplay of processing,structure,and properties in magnesium alloys,thereby advancing the development of superior biodegradable implant materials.

关键词： Magnesium alloys Machine learning Corrosion Mechanical properties Rapid characterization

Controlled deployment of a long tether to operate as a partial space elevator

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Astrodynamics 2024年第2期8卷 311-321页

作者： Jinbang Huang Arun K.Misra Department of Mechanical Engineering McGill UniversityMontrealQCH3A 0C3Canada

The deployment of a long tether to operate as a partial space elevator,starting from a nucleus in geostationary orbit,is *** deployment is an inherently unstable process because the center of orbit gradually decreases from the geostationary altitude when deployment *** is also observed that the elasticity of the tether has an important effect on deployment *** is shown that the application of a transverse force on the main spacecraft,determined by using linear state feedback and appropriate gains,can stabilize the *** LQR controller is *** of the dynamics of the system are carried out using this controller for various parametric values of tether elasticity,deployment rates,etc.,to evaluate the efficacy of the controller.

关键词： tether space elevator deployment stability control

A Survey and Experimental Review on Data Distribution Strategies for Parallel Spatial Clustering Algorithms

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Journal of Computer Science & Technology 2024年第3期39卷 610-636页

作者： Jagat Sesh Challa Navneet Goyal Amogh Sharma Nikhil Sreekumar Sundar Balasubramaniam Poonam Goyal Advanced Data Analytics and Parallel Technologies Laboratory Birla Institute of Technology and Science Pilani 333031India uber New York 11101U.S.A. Computer Science and Engineering Department University of MinnesotaMinneapolis 55455U.S.A.

The advent of Big Data has led to the rapid growth in the usage of parallel clustering algorithms that work over distributed computing frameworks such as MPI,MapReduce,and *** important step for any parallel clustering algorithm is the distribution of data amongst the cluster *** step governs the methodology and performance of the entire *** typically use random,or a spatial/geometric distribution strategy like kd-tree based partitioning and grid-based partitioning,as per the requirements of the ***,these strategies are generic and are not tailor-made for any specific parallel clustering *** this paper,we give a very comprehensive literature survey of MPI-based parallel clustering algorithms with special reference to the specific data distribution strategies they *** also propose three new data distribution strategies namely Parameterized Dimensional Split for parallel density-based clustering algorithms like DBSCAN and OPTICS,Cell-Based Dimensional Split for dGridSLINK,which is a grid-based hierarchical clustering algorithm that exhibits efficiency for disjoint spatial distribution,and Projection-Based Split,which is a generic distribution *** of these preserve spatial locality,achieve disjoint partitioning,and ensure good data load *** experimental analysis shows the benefits of using the proposed data distribution strategies for algorithms they are designed for,based on which we give appropriate recommendations for their usage.

关键词： parallel data mining data distribution parallel clustering spatial locality preservation

Improved State-space Modelling for Microgrids Without Virtual Resistances

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Journal of Modern Power Systems and Clean Energy 2024年第2期12卷 584-596页

作者： Paranagamage S.A.Peiris Shaahin Filizadeh Dharshana Muthumuni Department of Electrical and Computer Engineering University of ManitobaWinnipegMBR3T 5V6Canada Manitoba HVDC Research Center 211 Commerce DriveWinnipegMBR3P 1A3Canada IEEE

Power converters and their interfacing networks are often treated as modular state-space blocks for small-signal stability studies in microgrids;they are interconnected by matching the input and output states of the network and *** resistors have been widely used in existing models to generate a voltage for state-space models of the network that require voltage *** paper accurately quantifies the adverse impacts of adding the virtual resistance and proposes an alternative method for network modelling that eliminates the requirement of the virtual resistor when interfacing converters with *** proposed nonlinear method allows initialization,time-domain simulations of the nonlinear model,and linearization and eigenvalue generation.A numerically linearized small-signal model is used to generate eigenvalues and is compared with the eigenvalues generated using the existing modelling method with virtual *** of the existing method and improvements offered by the proposed modelling method are clearly *** transient(EMT)simulations using detailed switching models are used for validation of the proposed modelling method.

关键词： Low-voltage converter state-space modelling dynamic phasor time-domain simulation eigenvalue analysis

Assimilation of GOES-R Geostationary Lightning Mapper Flash Extent Density Data in GSI 3DVar, EnKF, and Hybrid En3DVar for the Analysis and Short-Term Forecast of a Supercell Storm Case

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Advances in Atmospheric Sciences 2024年第2期41卷 263-277页

作者： Rong KONG Ming XuE Edward R.MANSELL Chengsi LIu Alexandre O.FIERRO Center for Analysis and Prediction of Storms Norman Oklahoma 73072U.S.A university of Oklahoma Norman Oklahoma 73072U.S.A NOAA/National Severe Storms Laboratory NormanOklahoma 73072U.S A.4Zentralanstalt für Meteorologie und Geodynamik Department of Forecasting Models-ZAMGVienna 1190Austria

Capabilities to assimilate Geostationary Operational Environmental Satellite “R-series ”(GOES-R) Geostationary Lightning Mapper(GLM) flash extent density(FED) data within the operational Gridpoint Statistical Interpolation ensemble Kalman filter(GSI-EnKF) framework were previously developed and tested with a mesoscale convective system(MCS) case. In this study, such capabilities are further developed to assimilate GOES GLM FED data within the GSI ensemble-variational(EnVar) hybrid data assimilation(DA) framework. The results of assimilating the GLM FED data using 3DVar, and pure En3DVar(PEn3DVar, using 100% ensemble covariance and no static covariance) are compared with those of EnKF/DfEnKF for a supercell storm case. The focus of this study is to validate the correctness and evaluate the performance of the new implementation rather than comparing the performance of FED DA among different DA schemes. Only the results of 3DVar and pEn3DVar are examined and compared with EnKF/DfEnKF. Assimilation of a single FED observation shows that the magnitude and horizontal extent of the analysis increments from PEn3DVar are generally larger than from EnKF, which is mainly caused by using different localization strategies in EnFK/DfEnKF and PEn3DVar as well as the integration limits of the graupel mass in the observation operator. Overall, the forecast performance of PEn3DVar is comparable to EnKF/DfEnKF, suggesting correct implementation.

关键词： GOES-R lightning data assimilation EnKF EnVar

Technical Perspective:Research on General-Purpose Brain-Inspired Computing Systems

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Journal of Computer Science & Technology 2024年第1期39卷 1-3页

作者： Oliver Rhodes Department of Computer Science University of ManchesterManchester M139PLU.K

Brain-inspired computing is a popular research area with the potential to advance our understanding of brain function,artificial intelligence,and next-generation computing *** referred to as"neuromorphic",these systems and algorithms hope to harness mechanisms present in brains to make step changes in perfor-mance over regular von Neumann based approaches[1].

关键词： artificial computing Brain

VPI:Vehicle Programming Interface for Vehicle Computing

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Journal of Computer Science & Technology 2024年第1期39卷 22-44页

作者：吴宝福仲任王昱心万健张纪林施巍松 School of Computer Science and Technology Hangzhou Dianzi UniversityHangzhou 310018China Department of Computer Science Wayne State UniversityDetroitMI 48202U.S.A Department of Computer and Information Sciences University of DelawareNewarkDE 19716U.S.A

The emergence of software-defined vehicles(SDVs),combined with autonomous driving technologies,has en-abled a new era of vehicle computing(VC),where vehicles serve as a mobile computing ***,the interdisci-plinary complexities of automotive systems and diverse technological requirements make developing applications for au-tonomous vehicles *** simplify the development of applications running on SDVs,we propose a comprehen-sive suite of vehicle programming interfaces(VPIs).In this study,we rigorously explore the nuanced requirements for ap-plication development within the realm of VC,centering our analysis on the architectural intricacies of the Open Vehicu-lar Data Analytics Platform(OpenVDAP).We then detail our creation of a comprehensive suite of standardized VPIs,spanning five critical categories:Hardware,Data,Computation,Service,and Management,to address these evolving pro-gramming *** validate the design of VPIs,we conduct experiments using the indoor autonomous vehicle,Ze-bra,and develop the OpenVDAP prototype *** comparing it with the industry-influential AuTOSAR interface,our VPIs demonstrate significant enhancements in programming efficiency,marking an important advancement in the field of SDV application *** also show a case study and evaluate its *** work highlights that VPIs significantly enhance the efficiency of developing applications on *** meet both current and future technologi-cal demands and propel the software-defined automotive industry toward a more interconnected and intelligent future.

关键词： software-defined vehicle(SDV) vehicle computing(VC) vehicle programming interface(VPI) au-tonomous system