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Detour for the inexperienced? Migration count data suggest mostly juvenile Greater Spotted Eagles appear in coastal peninsulas in China

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Avian Research 2024年第2期15卷 249-254页

作者： Xu Shi xiaoping wang Qian Wei Qiwei Lin Lei Zhu School of the Environment The University of QueenslandSt LuciaQLD4072AustraliaAustralia Centre for Ecology and Conservation and Environment and Sustainability InstituteUniversity of ExeterPenrynCornwallTR109FEUK Guangxi Biodiversity Research and Conservation Association Nanning530022China Snake Island Laotieshan National Nature Reserve Dalian116041China Chongqing Birdwatching Society Chongqing400054China Huqiu Rd Gusu DistrictSuzhou215008China Raptor Research Group of Chengdu Chengdu610000China Guangxi Academy of Marine Science Nanning530007China

Soaring bird migration often relies on suitable terrain and airflow;therefore,route selection is vital for successful migration.While age and experience have been identified as key factor influencing migration route selection among soaring raptors in the African-Eurasian Flyway,how they shape the migration route of soaring raptors in East Asia is still largely unknown.In this study,we investigated potential variations in the routes and timing in autumn migration of juvenile and older soaring birds,using count data of Greater Spotted Eagles(Clanga clanga)from two coastal sites and two inland sites in China.From 2020 to 2023,we recorded a total of 340 individuals,with the highest site averaging over 90 individuals per autumn,making it one of the world’s top single-season counts and thus a globally important site for this species.We found that 82% and 61% records from coastal sites were juveniles,significantly higher than inland sites(15% and 24%).Juveniles at all four sites exhibited markedly earlier median passage time than non-juveniles,with brief overlapping in their main migration periods.Both coastal sites are located on the tip of peninsulas stretching southwest,requiring long overwater flights if crossing the Bohai Bay or Beibu Gulf,which would be energetically demanding and increase mortality risk.Experienced individuals may have learned to avoid such terrain and subsequent detour,while juveniles are more prone to enter these peninsulas due to lack of experience and opportunities for social learning,or following other raptor species that are more capable of powered flight.Our findings highlight the importance of age and experience in migration route selection of large soaring birds.

关键词： Clanga clanga East Asia Greater Spotted Eagle Juvenile Migration route Social learning

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Laser speckle contrast imaging to predict the effect of temporary spinal cord stimulation in postherpetic neuralgia patients: A prospective observational study

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Journal of Innovative Optical Health Sciences 2024年第1期17卷 69-75页

作者： Xiang Huang Dacheng Tang Pan Chen Lumiao Chen Xiaohong Li xiaoping wang Department of Pain Management The First A±liated Hospital Jinan University Guang ZhouGuangdong 510630P.R.China Department of Pain Management The First People's Hospital of Foshan Foshan City Guangdong 528000P.R.China

Temporary spinal cord stimulation(tSCS)can effectively reduce the pain and severity of postherpetic neuralgia(PHN).However,there are no effective and objective methods for predicting the effects of tSCS on PHN.Laser speckle contrast imaging(LSCI)is frequently used in neurology to evaluate the effectiveness of treatment.To assess the accuracy of LSCI in predicting the impact of tSCS on PHN,14 adult patients receiving tSCS treatments for spinal nerve-innervated(C6-T2)PHN participated in this observational study.Visual analog scale(VAS)assessments and LSCI bloodflow images of the-ngers were recorded after the tSCS procedure.The results showed that the VAS scores of all patients decreased signi-cantly.Moreover,the bloodflow index(BFI)values were signi-cantly higher than they were before the procedure.Increased bloodflow and pain alleviation were positively correlated.The-ndings indicated that spinal nerve PHN(C6-T2)was signi-cantly reduced by tSCS.Pain alleviation by tSCS was positively correlated with increased bloodflow in the hand.The effect of tSCS on PHN may thus be predicted using an independent and consistent indicator such as LSCI.

关键词： Laser speckle contrast imaging temporary spinal cord stimulation postherpetic neuralgia

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A Comparison of Four Neural Networks Algorithms on Locomotion Intention Recognition of Lower Limb Exoskeleton Based on Multi-source Information

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Journal of Bionic Engineering 2024年第1期21卷 224-235页

作者： Duojin wang xiaoping Gu Hongliu Yu Institute of Rehabilitation Engineering and Technology University of Shanghai for Science and Technology516 Jungong RoadShanghai 200093China Shanghai Engineering Research Center of Assistive Devices 516 Jungong RoadShanghai 200093China

Lower Limb Exoskeletons(LLEs)are receiving increasing attention for supporting activities of daily living.In such active systems,an intelligent controller may be indispensable.In this paper,we proposed a locomotion intention recognition system based on time series data sets derived from human motion signals.Composed of input data and Deep Learning(DL)algorithms,this framework enables the detection and prediction of users’movement patterns.This makes it possible to predict the detection of locomotion modes,allowing the LLEs to provide smooth and seamless assistance.The pre-processed eight subjects were used as input to classify four scenes:Standing/Walking on Level Ground(S/WOLG),Up the Stairs(US),Down the Stairs(DS),and Walking on Grass(WOG).The result showed that the ResNet performed optimally compared to four algorithms(CNN,CNN-LSTM,ResNet,and ResNet-Att)with an approximate evaluation indicator of 100%.It is expected that the proposed locomotion intention system will significantly improve the safety and the effectiveness of LLE due to its high accuracy and predictive performance.

关键词： Lower limb exoskeletons(LLEs) Locomotion intention ResNet Multi-source

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Deep-reinforcement-learning-based UAV autonomous navigation and collision avoidance in unknown environments

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Chinese Journal of Aeronautics 2024年第3期37卷 237-257页

作者： Fei wang xiaoping ZHU Zhou ZHOU Yang TANG School of Astronautics Northwestern Polytechnical UniversityXi’an 710072China School of Aeronautics Northwestern Polytechnical UniversityXi’an 710072China

In some military application scenarios,Unmanned Aerial Vehicles(UAVs)need to perform missions with the assistance of on-board cameras when radar is not available and communication is interrupted,which brings challenges for UAV autonomous navigation and collision avoidance.In this paper,an improved deep-reinforcement-learning algorithm,Deep Q-Network with a Faster R-CNN model and a Data Deposit Mechanism(FRDDM-DQN),is proposed.A Faster R-CNN model(FR)is introduced and optimized to obtain the ability to extract obstacle information from images,and a new replay memory Data Deposit Mechanism(DDM)is designed to train an agent with a better performance.During training,a two-part training approach is used to reduce the time spent on training as well as retraining when the scenario changes.In order to verify the performance of the proposed method,a series of experiments,including training experiments,test experiments,and typical episodes experiments,is conducted in a 3D simulation environment.Experimental results show that the agent trained by the proposed FRDDM-DQN has the ability to navigate autonomously and avoid collisions,and performs better compared to the FRDQN,FR-DDQN,FR-Dueling DQN,YOLO-based YDDM-DQN,and original FR outputbased FR-ODQN.

关键词： Faster R-CNN model Replay memory Data Deposit Mechanism(DDM) Two-part training approach Image-based Autonomous Navigation and Collision Avoidance(ANCA) Unmanned Aerial Vehicle(UAV)

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Detection of a temporal salient object benefits from visual stimulus-specific adaptation in avian midbrain inhibitory nucleus

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Integrative Zoology 2024年第2期19卷 288-306页

作者： Jiangtao wang xiaoping RAO Shuman HUANG Zhizhong wang Xiaoke NIU Minjie ZHU Songwei wang Li SHI Department of Automation Zhengzhou University School of Electrical EngineeringZhengzhouChina State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics National Center for Magnetic Resonance in WuhanKey Laboratory of Magnetic Resonance in Biological SystemsInnovation Academy for Precision Measurement Science and TechnologyChinese Academy of SciencesWuhanChina Department of Automation Tsinghua UniversityBeijingChina

Food and predators are the most noteworthy objects for the basic survival of wild animals,and both are often deviant in both spatial and temporal domains and quickly attract an animal’s attention.Although stimulus-specific adaptation(SSA)is considered a potential neural basis of salient sound detection in the temporal domain,related research on visual SSA is limited and its relationship with temporal saliency is uncertain.The avian nucleus isthmi pars magnocellularis(Imc),which is central to midbrain selective attention network,is an ideal site to investigate the neural correlate of visual SSA and detection of a salient object in the time domain.Here,the constant order paradigm was applied to explore the visual SSA in the Imc of pigeons.The results showed that the firing rates of Imc neurons gradually decrease with repetitions of motion in the same direction,but recover when a motion in a deviant direction is presented,implying visual SSA to the direction of a moving object.Furthermore,enhanced response for an object moving in other directions that were not presented ever in the paradigm is also observed.To verify the neural mechanism underlying these phenomena,we introduced a neural computation model involving a recoverable synaptic change with a“center-surround”pattern to reproduce the visual SSA and temporal saliency for the moving object.These results suggest that the Imc produces visual SSA to motion direction,allowing temporal salient object detection,which may facilitate the detection of the sudden appearance of a predator.

关键词： adaptation attention model pigeon saliency

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A laser-engraved wearable gait recognition sensor system for exoskeleton robots

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Microsystems & Nanoengineering 2024年第2期10卷 269-277页

作者： Maowen Sun Songya Cui Zezheng wang Huayu Luo Huayong Yang xiaoping Ouyang Kaichen Xu State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical EngineeringZhejiang UniversityHangzhou310027China School of Information and Electrical Engineering Hangzhou City UniversityHangzhou310015China

As a reinforcement technology that improves load-bearing ability and prevents injuries,assisted exoskeleton robots have extensive applications in freight transport and health care.The perception of gait information by such robots is vital for their control.This information is the basis for motion planning in assistive and collaborative functions.Here,a wearable gait recognition sensor system for exoskeleton robots is presented.Pressure sensor arrays based on laser-induced graphene are developed with flexibility and reliability.Multiple sensor units are integrated into an insole to detect real-time pressure at key plantar positions.In addition,the circuit hardware and the algorithm are designed to reinforce the sensor system with the capability of gait recognition.The experimental results show that the accuracy of gait recognition by the proposed system is 99.85%,and the effectiveness of the system is further verified through testing on an exoskeleton robot.

关键词： hardware robot skeleton

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Pedestrian wind flow prediction using spatial-frequency generative adversarial network

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Building Simulation 2024年第2期17卷 319-334页

作者： Pengyue wang Maozu Guo Yingeng Cao Shimeng Hao xiaoping Zhou Lingling Zhao School of Architecture and Urban Planning Beijing University of Civil Engineering and ArchitectureBeijing100044China Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing100044China School of Electrical and Information Engineering Beijing University of Civil Engineering and ArchitectureBeijing100044China School of Computer Science and Technology Harbin Institute of TechnologyHarbin150001China

Pedestrian wind flow is a critical factor in designing livable residential environments under growing complex urban conditions.Predicting pedestrian wind flow during the early design stages is essential but currently suffers from inefficiencies in numerical simulations.Deep learning,particularly generative adversarial networks(GAN),has been increasingly adopted as an alternative method to provide efficient prediction of pedestrian wind flow.However,existing GAN-based wind flow prediction schemes have limitations due to the lack of considering the spatial and frequency characteristics of wind flow images.This study proposes a novel approach termed SFGAN,which embeds spatial and frequency characteristics to enhance pedestrian wind flow prediction.In the spatial domain,Gaussian blur is employed to decompose wind flow into components containing wind speed and distinguished flow edges,which are used as the embedded spatial characteristics.Detailed information of wind flow is obtained through discrete wavelet transformation and used as the embedded frequency characteristics.These spatial and frequency characteristics of wind flow are jointly utilized to enforce consistency between the predicted wind flow and ground truth during the training phase,thereby leading to enhanced predictions.Experimental results demonstrate that SFGAN clearly improves wind flow prediction,reducing Wind_MAE,Wind_RMSE and the Fréchet Inception Distance(FID)score by 5.35%,6.52%and 12.30%,compared to the previous best method,respectively.We also analyze the effectiveness of incorporating the spatial and frequency characteristics of wind flow in predicting pedestrian wind flow.SFGAN reduces errors in predicting wind flow at large error intervals and performs well in wake regions and regions surrounding buildings.The enhanced predictions provide a better understanding of performance variability,bringing insights at the early design stage to improve pedestrian wind comfort.The proposed spatial-frequency loss term is general and can be flexibly inte

关键词： pedestrian wind flow prediction generative adversarial network Gaussian kernel wavelet transform objective function

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The life-history trait trade-offs mediated by reproduction and immunity in the brown planthopper,Nilaparvata lugens Stål

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Journal of Integrative Agriculture 2024年第6期23卷 2018-2032页

作者： Dan Sun Hongfeng wang Jiahui Zeng Qiuchen Xu Mingyun wang xiaoping Yu Xuping Shentu Zhejiang Provincial Key Laboratory of Biometrology and Inspection&Quarantine College of Life ScienceChina Jiliang UniversityHangzhou 310018China

Reproduction and immune defense are costly functions,and they are expected to tradeoff with each other to drive evolution.The brown planthopper(BPH),Nilaparvata lugens Stål(Hemiptera,Delphacidae),is a global superpest that mostly damages rice crops.Yeast-like symbionts(YLS)exist in the abdominal fat body tissue and are tightly associated with the development,growth,and reproduction of BPH.Our previous research demonstrated that mating behavior promotes the release of YLS from the fat body into the hemolymph in the BPH,thereby triggering an immune response.Additionally,the fitness costs related to life-history traits of BPH(such as survival rate)have a strong dependence on the relative abundance of YLS.However,the possible relationship between reproduction and the immune response in BPH has not been identified.In this study,an omics-based approach was used to analyze the transcriptome of fat body tissues in mated and unmated BPH at 72 h post-eclosion,from which two antimicrobial peptide genes,NlDefensin A(NlDfA)and NlDefensin B(NlDfB),were selected since they were highly expressed in mated BPH.Subsequently,the full-length cDNA sequences of the NlDfA and NlDfB genes were cloned and analyzed.qPCR results showed up-regulation of the NlDfA and NlDfB genes in mated BPH when compared to unmated BPH.Spatial-temporal expression analysis indicated that the NlDfA and NlDfB genes were expressed in all tissues and developmental stages,and they were most highly expressed in the fat body at 24 h post-eclosion.Moreover,the symbionts in BPH were significantly inhibited by the in vitro expression of the NlDfA and NlDfB proteins.Furthermore,RNA interference(RNAi)-mediated suppression of NlDfA and NlDfB dramatically increased the relative abundance of YLS in the fat body,while YLS in the hemolymph decreased significantly.These BPHs also displayed some fitness disadvantages in survival,fecundity,hatchability,and possibly the vertical transmission of YLS from hemolymph to egg.Our results indicated that mating could heighten the immuni

关键词： Nilaparvata lugens reproduction immune defense trade-off

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(DarkAI)Mapping the large-scale density field of dark matter using artificial intelligence

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Science China(Physics,Mechanics & Astronomy) 2024年第1期67卷 143-159页

作者： Zitong wang Feng Shi Xiaohu Yang Qingyang Li Yanming Liu xiaoping Li School of Aerospace Science and Technology Xidian UniversityXi’an 710126China Department of Astronomy School of Physics and Astronomyand Shanghai Key Laboratory for Particle Physics and CosmologyShanghai Jiao Tong UniversityShanghai 200240China Tsung-Dao Lee Institute and Key Laboratory for Particle Physics Astrophysics and CosmologyMinistry of EducationShanghai Jiao Tong UniversityShanghai 200240China Institute for Astronomy University of EdinburghRoyal ObservatoryEdinburgh EH93HJUnited Kingdom

Herein,we present a deep-learning technique for reconstructing the dark-matter density field from the redshift-space distribution of dark-matter halos.We built a UNet-architecture neural network and trained it using the COmoving Lagrangian Acceleration fast simulation,which is an approximation of the N-body simulation with 5123 particles in a box size of 500 h^(-1)Mpc.Further,we tested the resulting UNet model not only with training-like test samples but also with standard N-body simulations,such as the Jiutian simulation with 61443particles in a box size of 1000 h^(-1)Mpc and the ELUCID simulation,which has a different cosmology.The real-space dark-matter density fields in the three simulations can be reconstructed reliably with only a small reduction of the cross-correlation power spectrum at 1%and 10%levels at k=0.1 and 0.3 h Mpc-1,respectively.The reconstruction clearly helps to correct for redshift-space distortions and is unaffected by the different cosmologies between the training(Planck2018)and test samples(WMAP5).Furthermore,we tested the application of the UNet-reconstructed density field to obtain the velocity&tidal field and found that this approach provides better results compared with the traditional approach based on the linear bias model,showing a 12.2%improvement in the correlation slope and a 21.1%reduction in the scatter between the predicted and true velocities.Thus,our method is highly efficient and has excellent extrapolation reliability beyond the training set.This provides an ideal solution for determining the three-dimensional underlying density field from the plentiful galaxy survey data.

关键词： dark matter large-scale structure cosmology

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Identity-based searchable attribute signcryption in lattice for a blockchain-based medical system

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Frontiers of Information Technology & Electronic Engineering 2024年第3期25卷 461-471页

作者： Huifang YU xiaoping BAI School of Cyberspace Security Xi'an University of Posts&TelecommunicationsXi'an 710121China School of Information Engineering Qinghai Communications Technical CollegeXining 810003China

Electronic healthcare systems can offer convenience but face the risk of data forgery and information leakage.To solve these issues,we propose an identity-based searchable attribute signcryption in lattice for a blockchain-based medical system(BCMS-LIDSASC).BCMS-LIDSASC achieves decentralization and anti-quantum security in the blockchain environment,and provides fine-grained access control and searchability.Furthermore,smart contracts are used to replace traditional trusted third parties,and the interplanetary file system(IPFS)is used for ciphertext storage to alleviate storage pressure on the blockchain.Compared to other schemes,BCMS-LIDSASC requires smaller key size and less storage,and has lower computation cost.It contributes to secure and efficient management of medical data and can protect patient privacy and ensure the integrity of electronic healthcare systems.

关键词： Blockchain Identity-based searchable attribute signcryption Distributed storage NTRU lattice

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