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A mite parasitoid,Pyemotes zhonghuajia,negatively impacts the fitness traits and immune response of the fall armyworm,Spodoptera frugiperda

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Journal of Integrative Agriculture 2024年第1期23卷 205-216页

作者： Yanfei Song Tai’an tian Yichai Chen Keshi zhang Maofa yang Jianfeng Liu Institute of Entomology Guizhou Provincial Key Laboratory for Agricultural Pest Management of the Mountainous RegionGuizhou University/Scientific Observing and Experiment Station of Crop Pests in GuiyangMinistry of Agriculture and Rural AffairsGuiyang 550025China Administration of Guizhou Fanjingshan National Nature Reserve Jiangkou 554400China Centre for Biodiversity and Biosecurity School of Biological SciencesThe University of AucklandAuckland 1072New Zealand College of Tobacco Science Guizhou UniversityGuiyang 550025China

Parasitoids are key regulators in ecological communities and widely used as agents in biocontrol *** fall armyworm,Spodoptera frugiperda,recently invaded multiple continents and caused substantial economic losses in *** zhonghuajia,a newly identified mite parasitoid,has shown potential for controlling various agricultural insect ***,this study tested the performance of *** in parasitising *** also investigated the sublethal effects of parasitism by *** on host fitness traits,transgenerational impacts,and cellular and humoral *** result showed that the fifth-instar larvae of *** parasitised by 40 *** were all dead(i.e.,a lethal effect),while parasitism by 5 or 10 *** was considered sublethal since many *** survived to adulthood and produced offspring after *** sublethal influences from parasitism by *** resulted in reduced pupal weight,adult emergence rate and fecundity,but increased developmental time and *** at both lethal(40 mites)and sublethal(10 mites)levels impaired the cellular and humoral immunity of *** study presents the first empirical evidence that mite parasitoids can negatively influence host ***,it provides insights into the biocontrol potential of mite parasitoids and their interactions with hosts.

关键词： Pyemotes zhonghuajia Spodoptera frugiperda immunity parasitically-induced influence biocontrol parasitoid

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Ferroptosis in early brain injury after subarachnoid hemorrhage: review of literature

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中华神经外科杂志(英文) 2024年第2期10卷 134-149页

作者： Kang Junlin tian Shilai zhang Lei yang Gang The First Hospital of Lanzhou University Lanzhou City Gansu Province China Gansu Provincial Hospital Lanzhou City Gansu Province China

Spontaneous subarachnoid hemorrhage (SAH), mainly caused by ruptured intracranial aneurysms, is a serious acute cerebrovascular disease. Early brain injury (EBI) is all brain injury occurring within 72 h after SAH, mainly including increased intracranial pressure, decreased cerebral blood flow, disruption of the blood-brain barrier, brain edema, oxidative stress, and neuroinflammation. It activates cell death pathways, leading to neuronal and glial cell death, and is significantly associated with poor prognosis. Ferroptosis is characterized by iron-dependent accumulation of lipid peroxides and is involved in the process of neuron and glial cell death in early brain injury. This paper reviews the research progress of ferroptosis in early brain injury after subarachnoid hemorrhage and provides new ideas for future research.

关键词： Subarachnoid hemorrhage Early brain injury Ferroptosis Intracranial aneurysm

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Artificial intelligence-assisted repair of peripheral nerve injury: a new research hotspot and associated challenges

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Neural Regeneration Research 2024年第3期19卷 663-670页

作者： yang Guo Liying Sun Wenyao Zhong Nan zhang Zongxuan Zhao Wen tian Department of Hand Surgery Beijing Jishuitan HospitalBeijingChina

Artificial intelligence can be indirectly applied to the repair of peripheral nerve ***,it can be used to analyze and process data regarding peripheral nerve injury and repair,while study findings on peripheral nerve injury and repair can provide valuable data to enrich artificial intelligence *** investigate advances in the use of artificial intelligence in the diagnosis,rehabilitation,and scientific examination of peripheral nerve injury,we used CiteSpace and VOSviewer software to analyze the relevant literature included in the Web of Science from 1994–*** identified the following research hotspots in peripheral nerve injury and repair:(1)diagnosis,classification,and prognostic assessment of peripheral nerve injury using neuroimaging and artificial intelligence techniques,such as corneal confocal microscopy and coherent anti-Stokes Raman spectroscopy;(2)motion control and rehabilitation following peripheral nerve injury using artificial neural networks and machine learning algorithms,such as wearable devices and assisted wheelchair systems;(3)improving the accuracy and effectiveness of peripheral nerve electrical stimulation therapy using artificial intelligence techniques combined with deep learning,such as implantable peripheral nerve interfaces;(4)the application of artificial intelligence technology to brain-machine interfaces for disabled patients and those with reduced mobility,enabling them to control devices such as networked hand prostheses;(5)artificial intelligence robots that can replace doctors in certain procedures during surgery or rehabilitation,thereby reducing surgical risk and complications,and facilitating postoperative *** artificial intelligence has shown many benefits and potential applications in peripheral nerve injury and repair,there are some limitations to this technology,such as the consequences of missing or imbalanced data,low data accuracy and reproducibility,and ethical issues(e.g.,privac

关键词： artificial intelligence artificial prosthesis medical-industrial integration brain-machine interface deep learning machine learning networked hand prosthesis neural interface neural network neural regeneration peripheral nerve

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Deep learning CNN-APSO-LSSVM hybrid fusion model for feature optimization and gas-bearing prediction

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Petroleum Science 2024年第4期21卷 2329-2344页

作者： Jiu-Qiang yang Nian-tian Lin Kai zhang Yan Cui Chao Fu Dong zhang College of Earth Sciences and Engineering Shandong University of Science and Technology Laboratory for Marine Mineral Resources Qingdao National Laboratory for Marine Science and Technology Transportation Institute of Inner Mongolia University Key Laboratory of Gas Hydrate Qingdao Institute of Marine Geology Ministry of Natural Resources

Conventional machine learning(CML) methods have been successfully applied for gas reservoir prediction. Their prediction accuracy largely depends on the quality of the sample data; therefore, feature optimization of the input samples is particularly important. Commonly used feature optimization methods increase the interpretability of gas reservoirs; however, their steps are cumbersome, and the selected features cannot sufficiently guide CML models to mine the intrinsic features of sample data efficiently. In contrast to CML methods, deep learning(DL) methods can directly extract the important features of targets from raw data. Therefore, this study proposes a feature optimization and gas-bearing prediction method based on a hybrid fusion model that combines a convolutional neural network(CNN)and an adaptive particle swarm optimization-least squares support vector machine(APSO-LSSVM). This model adopts an end-to-end algorithm structure to directly extract features from sensitive multicomponent seismic attributes, considerably simplifying the feature optimization. A CNN was used for feature optimization to highlight sensitive gas reservoir information. APSO-LSSVM was used to fully learn the relationship between the features extracted by the CNN to obtain the prediction results. The constructed hybrid fusion model improves gas-bearing prediction accuracy through two processes of feature optimization and intelligent prediction, giving full play to the advantages of DL and CML methods. The prediction results obtained are better than those of a single CNN model or APSO-LSSVM model. In the feature optimization process of multicomponent seismic attribute data, CNN has demonstrated better gas reservoir feature extraction capabilities than commonly used attribute optimization methods. In the prediction process, the APSO-LSSVM model can learn the gas reservoir characteristics better than the LSSVM model and has a higher prediction accuracy. The constructed CNN-APSO-LSSVM mode

关键词： Multicomponent seismic data Deep learning Adaptive particle swarm optimization Convolutional neural network Least squares support vector machine Feature optimization Gas-bearing distribution prediction

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Phase transfer-based high-efficiency recycling of precious metal electrocatalysts

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Green Chemical Engineering 2024年第1期5卷 68-74页

作者： Qing Zeng Shaonan tian Yu zhang Hui Liu Dong Chen Xinlong tian Chaoquan Hu Jun yang State Key Laboratory of Multiphase Complex Systems Institute of Process EngineeringChinese Academy of SciencesBeijing100190China State Key Laboratory of Marine Resource Utilization in South China Sea Hainan Provincial Key Lab of Fine ChemistrySchool of Chemical Engineering and TechnologyHainan UniversityHaikou570228China Nanjing IPE Institute of Green Manufacturing Industry Nanjing211100China Center of Materials Science and Optoelectronics Engineering University of Chinese Academy of SciencesBeijing100049China

Recycling precious metals with high-efficiency is undoubtedly beneficial to optimize resource utilization for environmental remediation and sustainable ***,we report an efficient route to recycle the palladium(Pd)and platinum(Pt)electrocatalysts using a phase transfer *** strategy involves acidic dissolution of deactivated precious metal(Pd/Pt)electrocatalysts from their loading substrates,mixing with an ethanolic solution of dodecylamine(DDA),subsequent extraction of metal ions into a non-polar organic phase,and final reduction by sodium borohydride to reproduce high-performance electrocatalysts towards typical electrochemical reactions,e.g.,oxygen reduction reaction(ORR)and ethanol oxidation reaction(EOR).In specific,the transfer efficiencies are up to 98%and the final recovery rate is over 85%for Pd and Pt electrocatalysts in each *** approach symbolizes a facile and efficient way to recover precious metals,which might be applied to recycling a wide range of metals in various realms after appropriate modifications.

关键词： Precious metal Phase transfer Extraction Recovery Electrocatalyst

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On the two-layer high-level Green-Naghdi model in a general form

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Journal of Hydrodynamics 2024年第1期36卷 78-86页

作者： Bin-bin Zhao tian-yu zhang Zhan Wang Wen-yang Duan Alexander Chesnokov Natalia Shmakova College of Shipbuilding Engineering Harbin Engineering UniversityHarbin150001China Qingdao Innovation and Development Center of Harbin Engineering University Qingdao266000China Lavrentyev Institute of Hydrodynamics NovosibirskRussia

The traditional high-level Green-Naghdi(HLGN)model,which uses the polynomial as the shape function to approximate the variation of the horizontal-and vertical-velocity components along the vertical direction for each-fluid layer,can accurately describe the large-amplitude internal waves in a two-layer system for the shallow configuration(h_(2)/λ■1,h_(1)/λ■1).However,for the cases of the deep configuration(h_(2)/λ■1,h_(1)/λ=O(1)),higher-order polynomial is needed to approximate the variation of the velocity components along the vertical direction for the lower-fluid ***,however,introduces additional unknowns,leading to a significant increase in computational *** paper,for the first time,derives a general form of the HLGN model for a two-layer fluid system,where the general form of the shape function is used during the *** obtaining the general form of the two-layer HLGN equations,corresponding solutions can be obtained by determining the reasonable shape ***-amplitude internal solitary waves in a deep configuration are studied by use of two different HLGN *** of the two HLGN models shows that the polynomial as the shape function for the upper-fluid layer and the production of exponential and polynomial as the shape function for the lower-fluid layer is a good *** comparing with Euler’s solutions and the laboratory measurements,the accuracy of the two-layer HLGN model is verified.

关键词： High-level Green-Naghdi(HLGN)model general form internal waves deep configuration

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Frequency Domain Fatigue Evaluation on SCR Girth-Weld Based on Structural Stress

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China Ocean Engineering 2024年第2期38卷 255-270页

作者： zhang Long ZHAO tian-feng College of Safety and Ocean Engineering China University of Petroleum(Beijing)Beijing 102249China

The Steel Catenary Riser(SCR)is a vital component for transporting oil and gas from the seabed to the floating *** harsh environmental conditions and complex platform motion make the SCR’s girth-weld prone to fatigue *** structural stress fatigue theory and Master S-N curve method provide accurate predictions for the fatigue damage on the welded joints,which demonstrate significant potential and compatibility in multi-axial and random fatigue ***,we propose a new frequency fatigue model subjected to welded joints of SCR under multiaxial stress,which fully integrates the mesh-insensitive structural stress and frequency domain random process and transforms the conventional welding fatigue technique of SCR into a spectrum analysis technique utilizing structural ***,a full-scale FE model of SCR with welds is established to obtain the modal structural stress of the girth weld and the frequency response function(FRF)of modal coordinate,and a biaxial fatigue evaluation about the girth weld of the SCR can be achieved by taking the effects of multi-load correlation and pipe-soil interaction into *** research results indicate that the frequency-domain fatigue results are aligned with the time-domain results,meeting the fatigue evaluation requirements of the SCR.

关键词： SCR girth weld random vibration self(cross)power spectrum structural stress method biaxial fatigue damage

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A survey on model-based reinforcement learning

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Science China(Information Sciences) 2024年第2期67卷 59-84页

作者： Fan-Ming LUO tian XU Hang LAI Xiong-Hui CHEN Weinan zhang yang YU National Key Laboratory for Novel Software Technology Nanjing University Polixir. ai Department of Computer Science and Engineering Shanghai Jiao Tong University

Reinforcement learning(RL) interacts with the environment to solve sequential decision-making problems via a trial-and-error approach. Errors are always undesirable in real-world applications, even though RL excels at playing complex video games that permit several trial-and-error attempts. To improve sample efficiency and thus reduce errors, model-based reinforcement learning(MBRL) is believed to be a promising direction, as it constructs environment models in which trial-and-errors can occur without incurring actual costs. In this survey, we investigate MBRL with a particular focus on the recent advancements in deep RL. There is a generalization error between the learned model of a non-tabular environment and the actual environment. Consequently, it is crucial to analyze the disparity between policy training in the environment model and that in the actual environment, guiding algorithm design for improved model learning, model utilization, and policy training. In addition, we discuss the recent developments of model-based techniques in other forms of RL, such as offline RL, goal-conditioned RL, multi-agent RL, and meta-RL. Furthermore,we discuss the applicability and benefits of MBRL for real-world tasks. Finally, this survey concludes with a discussion of the promising future development prospects for MBRL. We believe that MBRL has great unrealized potential and benefits in real-world applications, and we hope this survey will encourage additional research on MBRL.

关键词： reinforcement learning model-based reinforcement learning planning model learning model learning with reduced error model usage

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Analyze the Performance of Electroactive Anticorrosion Coating of Medical Magnesium Alloy Using Deep Learning

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Computers, Materials & Continua 2024年第4期79卷 263-278页

作者： Yashan Feng Yafang tian Yongxin yang Yufang zhang Haiwei Guo Jing’an Li Advanced Functional Materials Laboratory Zhengzhou Railway Vocational and Technical CollegeZhengzhou450000China School of Materials Science and Engineering Zhengzhou UniversityZhengzhou450000China

Electroactive anticorrosion coatings are specialized surface treatments that prevent or minimize corrosion. Thestudy employs strategic thermodynamic equilibriumcalculations to pioneer a novel factor in corrosion protection.A first-time proposal, the total acidity (TA) potential of the hydrogen (pH) concept significantly shapes medicalmagnesium alloys. These coatings are meticulously designed for robust corrosion resistance, blending theoreticalinsights and practical applications to enhance our grasp of corrosion prevention mechanisms and establisha systematic approach to coating design. The groundbreaking significance of this study lies in its innovativeintegration of the TA/pH concept,which encompasses the TA/pH ratio of the chemical environment. This approachsurpasses convention by acknowledging the intricate interplay between the acidity and pH levels within thecoating formulation, thereby optimizing metal-phosphate-based conversion coatings and transforming corrosionmitigation strategies. To authenticate the TA/pH concept, the study comprehensively compares its findings withexisting research, rigorously validating the theoretical framework and reinforcing the correlates among TA/pHvalues and observed corrosion resistance in the coatings. The influence of mutations that occur naturally inthe detergent solution on persistent phosphorus changes is shown by empirical confirmation, which improvescorrosion resistance. This realization advances the field ofmaterials and the field’s knowledge of coated generation,particularly anticorrosion converter layers.

关键词： Medical magnesium alloys hydrogen gas anticorrosion total acidity potential of the hydrogen(pH)

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Migration pattern of a population of Barn Swallows(Hirundo rustica)breeding in East Asian tropical region

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Avian Research 2024年第3期15卷 299-307页

作者： Li tian Yu Liu yang Wu Zimei Feng Dan Hu Zhengwang zhang Key Laboratory for Biodiversity Sciences and Ecological Engineering Ministry of EducationCollege of Life SciencesBeijing Normal UniversityBeijing100875China State Key Laboratory of Environmental Criteria and Risk Assessment Chinese Research Academy of Environmental SciencesBeijing100107China Life Science and Technology School Lingnan Normal UniversityZhanjiang524048China

Birds exhibit a high degree of migratory diversity,which is influenced by various ecological factors and life history *** studies on tropical bird migration,of which research is scarce,and comparing it with temperate birds can enhance our understanding of bird migration behaviour and its underlying *** this study,we explored the migration behaviour of a breeding population of the Barn Swallow(Hirundo rustica)in Zhanjiang,southern China,a region located in the northern tropics,using light-level *** 2021 to 2023,we deployed geolocators on 92 breeding swallows and retrieved geolocators successfully from 23 *** swallows all exhibited migratory behaviour,and wintering on various islands in Southeast *** displayed sex differences in their wintering *** males concentrated in Borneo,while females primarily chose Borneo but also dispersed to the Philippines,South China Sea,and Vietnam for *** studied swallow population adopted a seasonal migration pattern of“indirect in autumn,direct in spring”,bypassing the ecological barrier of the South China Sea in autumn and tending to directly cross it in spring ***,the distance and duration of autumn migration was significantly longer than those of the spring *** to temperate Barn Swallows,the Barn Swallow population breeding in Zhanjiang adopts a pattern of“intra-tropical migration”and initiates autumn migration *** formation of their migration pattern may be limited by ecological and physiological factors.

关键词： Asia Chain migration Light-level geolocators Migration Northern tropics

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