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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

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

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)

End-to-End Paired Ambisonic-Binaural Audio Rendering

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 502-513页

作者： yin zhu Qiuqiang Kong Junjie shi shilei Liu Xuzhou Ye Ju-Chiang Wang Hongming Shan Junping Zhang Shanghai Key Laboratory of Intelligent Information Processing School of Computer ScienceFudan UniversityShanghai 200433China Beijing ByteDance Technology Co.Ltd. Shanghai 201102China. Chinese University of Hong Kong Hong KongChina IEEE Institute of Science and Technology for Brain-Inspired Intelligence and MOE Frontiers Center for Brain Science Fudan UniversityShanghai 200433 Shanghai Center for Brain Science and Brain-Inspired Technology Shanghai 200031China

Binaural rendering is of great interest to virtual reality and immersive media. Although humans can naturally use their two ears to perceive the spatial information contained in sounds, it is a challenging task for machines to achieve binaural rendering since the description of a sound field often requires multiple channels and even the metadata of the sound sources. In addition, the perceived sound varies from person to person even in the same sound field. Previous methods generally rely on individual-dependent head-related transferred function(HRTF)datasets and optimization algorithms that act on HRTFs. In practical applications, there are two major drawbacks to existing methods. The first is a high personalization cost, as traditional methods achieve personalized needs by measuring HRTFs. The second is insufficient accuracy because the optimization goal of traditional methods is to retain another part of information that is more important in perception at the cost of discarding a part of the information. Therefore, it is desirable to develop novel techniques to achieve personalization and accuracy at a low cost. To this end, we focus on the binaural rendering of ambisonic and propose 1) channel-shared encoder and channel-compared attention integrated into neural networks and 2) a loss function quantifying interaural level differences to deal with spatial information. To verify the proposed method, we collect and release the first paired ambisonic-binaural dataset and introduce three metrics to evaluate the content information and spatial information accuracy of the end-to-end methods. Extensive experimental results on the collected dataset demonstrate the superior performance of the proposed method and the shortcomings of previous methods.

关键词： Ambisonic attention binaural rendering neural network

(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

Novel milestones for early esophageal carcinoma:From bench to bed

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World Journal of Gastrointestinal Oncology 2024年第4期16卷 1104-1118页

作者： Ji-Han Qi shi-Ling Huang shi-zhu Jin Department of Gastroenterology and Hepatology The Second Affiliated Hospital of Harbin Medical UniversityHarbin 150086Heilongjiang ProvinceChina

Esophageal cancer(EC)is the seventh most common cancer worldwide,and esophageal squamous cell carcinoma(ESCC)accounts for the majority of cases of EC.To effectively diagnose and treat ESCC and improve patient prognosis,timely diagnosis in the initial phase of the illness is necessary.This article offers a detailed summary of the latest advancements and emerging technologies in the timely identification of ECs.Molecular biology and epigenetics approaches involve the use of molecular mechanisms combined with fluorescence quanti-tative polymerase chain reaction(qPCR),high-throughput sequencing technology(next-generation sequencing),and digital PCR technology to study endogenous or exogenous biomolecular changes in the human body and provide a decision-making basis for the diagnosis,treatment,and prognosis of diseases.The invest-igation of the microbiome is a swiftly progressing area in human cancer research,and microorganisms with complex functions are potential components of the tumor microenvironment.The intratumoral microbiota was also found to be connected to tumor progression.The application of endoscopy as a crucial technique for the early identification of ESCC has been essential,and with ongoing advancements in technology,endoscopy has continuously improved.With the advancement of artificial intelligence(AI)technology,the utilization of AI in the detection of gastrointestinal tumors has become increasingly prevalent.The implementation of AI can effectively resolve the discrepancies among observers,improve the detection rate,assist in predicting the depth of invasion and differentiation status,guide the pericancerous margins,and aid in a more accurate diagnosis of ESCC.

关键词： Early esophageal squamous cell carcinoma Epidemiology and risk factors Molecular biology Epigenetic Microbiology Endoscopy and artificial intelligence

A unified intelligent control strategy synthesizing multi-constrained guidance and avoidance penetration

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Science China(Information Sciences) 2024年第7期67卷 329-330页

作者： Sibo ZHAO Jianwen zhu Weimin BAO xiaoping LI School of Aerospace Science and Technology Xidian University College of Missile Engineering Rocket Force University of Engineering China Aerospace Science and Technology Corporation

Satisfying various terminal constraints and achieving evasive flight in no-flying-zones (NFZs) are two important flight missions undertaken by high velocity vehicles. We studied an intelligent maneuvering guidance strategy using deep reinforcement learning (DRL) methods to achieve the coordination and unification of evasive flight and multi-constrained guidance with minimal energy loss.

关键词： Energy dissipation

Explainable-AI-based two-stage solution for WSN object localization using zero-touch mobile transceivers

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Science China(Information Sciences) 2024年第7期67卷 27-45页

作者： Kai FANG Junxin CHEN Han zhu Thippa Reddy GADEKALLU xiaoping WU Wei WANG School of Mathematics and Computer Science Zhejiang A&F University School of Software Dalian University of Technology Faculty of Applied Sciences Macao Polytechnic University Department of Electrical and Computer Engineering Lebanese American University School of Information Engineering Huzhou University Guangdong-Hong Kong-Macao Joint Laboratory for Emotional Intelligence and Pervasive Computing Artificial Intelligence Research Institute Shenzhen MSU-BIT University

Artificial intelligence technology is widely used in the field of wireless sensor networks(WSN).Due to its inexplicability, the interference factors in the process of WSN object localization cannot be effectively eliminated. In this paper, an explainable-AI-based two-stage solution is proposed for WSN object localization. In this solution, mobile transceivers are used to enlarge the positioning range and eliminate the blind area for object localization. The motion parameters of transceivers are considered to be unavailable,and the localization problem is highly nonlinear with respect to the unknown parameters. To address this,an explainable AI model is proposed to solve the localization problem. Since the relationship among the variables is difficult to fully include in the first-stage traditional model, we develop a two-stage explainable AI solution for this localization problem. The two-stage solution is actually a comprehensive consideration of the relationship between variables. The solution can continue to use the constraints unused in the firststage during the second-stage, thereby improving the performance of the solution. Therefore, the two-stage solution has stronger robustness compared to the closed-form solution. Experimental results show that the performance of both the two-stage solution and the traditional solution will be affected by numerical changes in unknown parameters. However, the two-stage solution performs better than the traditional solution, especially with a small number of mobile transceivers and sensors or in the presence of high noise. Furthermore,we have also verified the feasibility of the proposed explainable-AI-based two-stage solution.

关键词： explainable AI object localization semidefinite relaxation mobile transceiver two-stage solution closed-form solution

Enhancing the Interaction of Carbon Nanotubes by Metal-Organic Decomposition with Improved Mechanical Strength and Ultra-Broadband EMI shielding Performance

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Nano-Micro Letters 2024年第7期16卷 281-294页

作者： Yu-ying shi Si-Yuan Liao Qiao-Feng Wang Xin-Yun Xu Xiao-Yun Wang Xin-yin Gu You-Gen Hu Peng-Li zhu Rong Sun Yan-Jun Wan Shenzhen Institute of Advanced Electronic Materials Shenzhen Institutes of Advanced TechnologyChinese Academy of SciencesShenzhen 518055People’s Republic of China Southern University of Science and Technology Shenzhen 518055People’s Republic of China National Key Laboratory of Materials for Integrated Circuits Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghai 200050People’s Republic of China

The remarkable properties of carbon nanotubes(CNTs)have led to promising applications in the field of electromagnetic inter-ference(EMI)shielding.However,for macroscopic CNT assemblies,such as CNT film,achieving high electrical and mechanical properties remains challenging,which heavily depends on the tube-tube interac-tions of CNTs.Herein,we develop a novel strategy based on metal-organic decomposition(MOD)to fabricate a flexible silver-carbon nanotube(Ag-CNT)film.The Ag particles are introduced in situ into the CNT film through annealing of MOD,leading to enhanced tube-tube interactions.As a result,the electrical conductivity of Ag-CNT film is up to 6.82×10^(5) S m^(-1),and the EMI shielding effectiveness of Ag-CNT film with a thickness of~7.8μm exceeds 66 dB in the ultra-broad frequency range(3-40 GHz).The tensile strength and Young’s modulus of Ag-CNT film increase from 30.09±3.14 to 76.06±6.20 MPa(~253%)and from 1.12±0.33 to 8.90±0.97 GPa(~795%),respectively.Moreover,the Ag-CNT film exhibits excellent near-field shield-ing performance,which can effectively block wireless transmission.This innovative approach provides an effective route to further apply macroscopic CNT assemblies to future portable and wearable electronic devices.

关键词： EMI shielding Mechanical strength Carbon nanotubes Metal-organic decomposition Flexibility