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Journal of Forestry Research 2020年第6期31卷 2273-2286页

作者： wen-qiang gao Xiang-Dong Lei Li-Yong Fu Institute of Forest Resource Information Techniques Chinese Academy of ForestryKey Laboratory of Forest Management and Growth ModellingState Forestry and Grassland AdministrationBeijing 100091People’s Republic of China

Climate warming is expected to influence forest growth,composition and ***,accurately estimating and predicting forest biomass,potential productivity or forest growth is still a challenge for forest managers dealing with land-use at the stand to regional *** the present study,we predicted the potential productivity(PP)of forest under current and future climate scenarios(RCP2.6,RCP4.5,RCP6.0 and RCP8.5)in Jilin province,northeastern China by using Paterson’s Climate Vegetation and Productivity(CVP)index *** PP was validated by comparing it with the mean and maximum net primary production calculated from light energy utilization(GLM_PEM).Our results indicated that using the CVP index model is partially valid for predicting the potential forest productivity in northeastern *** exhibited obvious spatial heterogeneity varying from 4.6 to 8.9 m3 ha-1 year-1 with an increasing tendency from northwest to southeast driven by the precipitation across the *** number of vegetation-active months,precipitation and insolation coefficient were identified as the primary factors affecting PP,but no significant relationship was found for warmest temperature or temperature *** future climate scenarios,PP across the Jilin Province is expected to increase from 1.38%(RCP2.6 in 2050)to 15.30%(RCP8.5 in 2070),especially in the eastern Songnen Plain(SE)for the RCP8.5 scenarios.

关键词： Climate vegetation and productivity index Potential productivity Climate change

Investigation of bubbles escape behavior from low basicity mold flux for high-Mn high-Al steels using 3D X-ray microscope

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International Journal of Minerals,Metallurgy and Materials 2025年第1期32卷 102-110页

作者： qiang Liu Xiang Li Shen Du Ming gao Yanbin Yin Jiongming Zhang State Key Laboratory of Advanced Metallurgy University of Science and Technology BeijingBeijing 100083China

During the continuous casting process of high-Mn high-Al steels,various types of gases such as Ar need to escape through the top of the *** which,the behavior of bubbles traversing the liquid slag serves as a restrictive link,closely associated with viscosity and the thickness of liquid *** contrast to two-dimensional surface observation,three-dimensional(3D)analysis method can offer a more intuitive,accurate,and comprehensive ***,this study employs a 3D X-ray microscope(3D-XRM)to obtained spatial distribution and 3D morphological characteristics of residual bubbles in mold flux under different basicity of liquid slag,different temperatures,and different holding *** results indicate that as basicity of slag increases from 0.52 to 1.03,temperature increases from 1423 to 1573 K,the viscosity of slag decreases,the floating rate of bubbles *** addition,when holding time increases from 10 to 30 s,the bubbles floating distance increases,and the volume fraction and average equivalent sphere diameter of the bubbles solidified in the mold flux gradually *** one word,increasing the basicity,temperature,and holding time leading to an increase in the removal rate of bubbles especially for the *** findings of bubbles escape behavior provide valuable insights into optimizing low basicity mold flux for high-Mn high-Al steels.

关键词： mold flux low basicity bubbles three-dimensional X-ray microscope viscosity

Characterization of petrophysical and seismic properties for CO2 storage with sensitivity analysis

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Petroleum Science 2025年第1期22卷 193-209页

作者： Yan-Jiao Dong Yi Shen Kai Guo Xiao-Qin Wu qiang Mao wen-Yue Sun Zhi-qiang Wang State Key Laboratory of Offshore Oil and Gas Exploitation Geosciences Department China University of Petroleum (East China) CNOOC Research Institute Ltd. School of Petroleum Engineering China University of Petroleum (East China)

Saline aquifers are considered as highly favored reservoirs for CO2sequestration due to their favorable properties. Understanding the impact of saline aquifer properties on the migration and distribution of CO2plume is crucial. This study focuses on four key parameters—permeability, porosity, formation pressure, and temperature—to characterize the reservoir and analyse the petrophysical and elastic response of CO2. First, we performed reservoir simulations to simulate CO2saturation, using multiple sets of these four parameters to examine their significance on CO2saturation and the plume migration ***, the effect of these parameters on the elastic properties is tested using rock physics *** established a relationship of compressional wave velocity（Vp） and quality factor（Qp） with the four key parameters, and conducted a sensitivity analysis to test their sensitivity to Vpand Qp. Finally, we utilized visco-acoustic wave equation simulated time-lapse seismic data based on the computed Vpand Qpmodels, and analysed the impact of CO2saturation changes on seismic data. As for the above numerical simulations and analysis, we conducted sensitivity analysis using both homogeneous and heterogeneous models. Consistent results are found between homogeneous and heterogeneous models. The permeability is the most sensitive parameter to the CO2saturation, while porosity emerges as the primary factor affecting both Qpand Vp. Both Qpand Vpincrease with the porosity, which contradicts the observations in gas reservoirs. The seismic simulations highlight significant variations in the seismic response to different parameters. We provided analysis for these observations, which serves as a valuable reference for comprehensive CO2integrity analysis, time-lapse monitoring, injection planning and site selection.

关键词： CO2 storage Time-lapse seismic CO2 plume Sensitivity analysis Rock physics Reservoir simulation Saline aquifer

An efficient quantum proactive incremental learning algorithm

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Science China(Physics,Mechanics & Astronomy) 2025年第1期68卷 45-53页

作者： Lingxiao Li Jing Li Yanqi Song Sujuan Qin Qiaoyan wen Fei gao State Key Laboratory of Networking and Switching Technology Beijing University of Posts and TelecommunicationsBeijing 100876China School of Cyberspace Security Beijing University of Posts and TelecommunicationsBeijing 100876China

In scenarios where a large amount of data needs to be learned,incremental learning can make full use of old knowledge,signif-icantly reduce the computational cost of the overall learning process,and maintain high *** this paper,taking the MaxCut problem as our example,we introduce the idea of incremental learning into quantum computing,and propose a Quantum Proactive Incremental Learning algorithm(QPIL).Instead of a one-off training of quantum circuit,QPIL contains a multi-phase training on gradually-increased subgraphs of all vertices,proactively reducing large-scale problems to smaller ones to solve in steps,providing an efficient solution for ***,some vertices and corresponding edges are randomly selected for training to obtain optimized parameters of the quantum circuit at ***,in each incremental phase,the remaining vertices and corresponding edges are gradually added and the parameters obtained from the previous phase are reused in the parameter initialization of the current *** perform experiments on 120 different small-scale graphs,and it shows that QPIL performs superior to prevalent quantum and classical baselines in terms of approximation ratio(AR),time cost,anti-forgetting,and solv-ing *** particular,QPIL’s AR surpasses 20%of mainstream quantum baselines,and the time cost is less than 1/5 of *** idea of QPIL is expected to inspire efficient and high-quality solutions in large-scale MaxCut and other combinatorial optimization problems.

关键词： variational quantum algorithm incremental learning multi-phase training MaxCut quantum computing

HTEC foot:A novel foot structure for humanoid robots combining static stability and dynamic adaptability

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Defence Technology(防务技术) 2025年第2期44卷 30-51页

作者： Jintao Zhang Xuechao Chen Zhangguo Yu Lianqiang Han Zhifa gao Qingrui Zhao gao Huang Ke Li qiang Huang School of Mechatronical Engineering Beijing Institute of TechnologyNo.5South StreetZhongguancunHaidian DistrictBeijing100081China Key Laboratory of Biomimetic Robots and Systems Ministry of EducationNo.5South StreetZhongguancunHaidian DistrictBeijing100081China School of Information Science and Technology Beijing University of TechnologyNo.100PingleyuanChaoyang DistrictBeijing100124China Innovation Center for Control Actuators Beijing Institute of Precision Mechatronics and ControlsDonggaodiFengtai DistrictBeijing100076China

Passive bionic feet,known for their human-like compliance,have garnered attention for their potential to achieve notable environmental *** this paper,a method was proposed to unifying passive bionic feet static supporting stability and dynamic terrain adaptability through the utilization of the Rigid-Elastic Hybrid(REH)dynamics ***,a bionic foot model,named the Hinge Tension Elastic Complex(HTEC)model,was developed by extracting key features from human ***,the kinematics and REH dynamics of the HTEC model were *** on the foot dynamics,a nonlinear optimization method for stiffness matching(NOSM)was ***,the HTEC-based foot was constructed and applied onto BHR-B2 humanoid *** foot static stability is *** enhanced adaptability is observed as the robot traverses square steel,lawn,and cobblestone *** proposed design method and structure,the mobility of the humanoid robot is improved.

关键词： Humanoid robot Bionic structure Passive foot structure Rigid-elastic hybrid dynamics model Optimal stiffness matching

Thermal-flow-electric coupling performance analysis of a liquid-immersed battery thermal management system

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Science China(Technological Sciences) 2025年第1期68卷 153-172页

作者： qiang gao Jun TIAN Chujin BAO Yangfan ZHONG Chengbin ZHANG Yongping CHEN School of Energy and Environment Southeast UniversityNanjing 210096China Battery Testing Center China North Vehicle Research InstituteBeijing 100072China Zhejiang Immertech Co. Ltd.Hangzhou 310000China Alibaba Cloud Computing Co. Ltd.Shenzhen 518100China

Ensuring the safety and performance of lithium-ion batteries(LIBs)is a significant challenge for electric *** tackle this issue,an innovative liquid-immersed battery thermal management system(LIBTMS)using bionic baffles with fish-like perforations is *** thermal-flow-electric coupling characteristics of LIBTMSs with different baffle structures(no baffle,conventional baffle,baffle with circular perforations and baffle with fish-like perforations)are systematically investigated using experimental and numerical *** results indicate that the forced flow scheme exhibits better thermal management performance and voltage equalization than static ***,the LIB temperatures and voltage deviations of different LIBTMSs increase quickly with increasing discharge *** importantly,the innovative LIBTMS exhibits the best thermoelectric performance due to its excellent thermoelectric equilibrium behavior caused by high electrical and temperature consistency,as well as the best overall performance involving the balance between the pressure loss and heat transfer capacity of the *** with other structures,the innovative LIBTMS using baffles with fish-like perforations exhibits a maximum reduction of 10.1%,15.2%,25.8%and 9.0%in LIB maximum temperature,maximum temperature difference,system pressure drop and voltage deviation,respectively,under the same operating ***,for the LIBTMS using baffles with fish-like perforations,the bottom inlet and top outlet configuration and coolant precooling are suggested to enhance cooling performance.

关键词： baffle liquid-immersed thermoelectric performance lithium-ion battery battery thermal management

Machine learning-assisted fluorescence visualization for sequential quantitative detection of aluminum and fluoride ions

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Journal of Environmental Sciences 2025年第3期149卷 68-78页

作者： qiang Zhang Xin Li Long Yu Lingxiao Wang Zhiqing wen Pengchen Su Zhenli Sun Suhua Wang School of Environmental Science and Engineering Guangdong University of Petrochemical TechnologyMaoming 525000China MOE Key Laboratory of Resources and Environmental System Optimization College of Environmental Science and EngineeringNorth China Electric Power UniversityBeijing 102206China

The presence of aluminum(Al^(3+))and fluoride(F^(−))ions in the environment can be harmful to ecosystems and human health,highlighting the need for accurate and efficient *** this paper,an innovative approach is presented that leverages the power of machine learning to enhance the accuracy and efficiency of fluorescence-based detection for sequential quantitative analysis of aluminum(Al^(3+))and fluoride(F^(−))ions in aqueous *** proposed method involves the synthesis of sulfur-functionalized carbon dots(C-dots)as fluorescence probes,with fluorescence enhancement upon interaction with Al^(3+)ions,achieving a detection limit of 4.2 nmol/***,in the presence of F^(−)ions,fluorescence is quenched,with a detection limit of 47.6 nmol/*** fingerprints of fluorescence images are extracted using a cross-platform computer vision library in Python,followed by data ***,the fingerprint data is subjected to cluster analysis using the K-means model from machine learning,and the average Silhouette Coefficient indicates excellent model ***,a regression analysis based on the principal component analysis method is employed to achieve more precise quantitative analysis of aluminum and fluoride *** results demonstrate that the developed model excels in terms of accuracy and *** groundbreaking model not only showcases exceptional performance but also addresses the urgent need for effective environmental monitoring and risk assessment,making it a valuable tool for safeguarding our ecosystems and public health.

关键词： Machine learning Aluminum ion detection Fluorine ion detection Fluorescence probe K-means model

Cd Enrichment Characteristics and Bioavailability of Soil-crops in the Migration Type Geological High Background Area of Poyang Lake，Jiangxi Province

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Huanjing Kexue/Environmental Science 2025年第3期46卷 1774-1782页

作者： wen, Bang-Yong Qie, Hai-Man gao, Yuan Jiang, Hong-Yu Zhou, qiang-qiang Basic Geological Survey Institute of Jiangxi Geological Survey and Exploration Institute Nanchang330030 China Key Laboratory of Mine Environmental Monitoring and Improving Around Poyang Lake Ministry of Natural Resources East China University of Technology Nanchang330013 China Jiangxi Nonferrous Geological Mineral Exploration and Development Institute Nanchang330030 China

To study the accumulation characteristics and bioavailability of Cd in the soil-crop system in the migration type geologically high background area，140 groups of crops and soil samples were collected from the Jiulong area on the south bank of Poyang Lake. The results showed that the range of ω （Cd） of root soil was 0.03-0.65 mg·kg-1，with an average of 0.16 mg·kg-1，which exceeded the background value of soil in Jiangxi Province，reflecting the characteristics of high geological background of migration type. The over-standard rate of Cd in root soil was 6.43%，which was slightly polluted. Sesame had the strongest enrichment ability of Cd （404%），followed by that of peanut （146%）. The enrichment ability of rice，Camellia oleifera，and Euryale seed was medium，while that of corn was weak. The root soil ω （active Cd） was 76.8 μg·kg-1，and the bioavailability was 48.9%，among which rice was the highest with 98.6 μg·kg-1 and 59.9%，respectively. Principal component analysis （PCA） showed that root soil Cd was mainly caused by the transport and accumulation of industrial and mineral pollutants in the upstream，reflecting the characteristics of the high geological background of the transport type. Correlation showed that the active and bioavailable Cd of root soil were mainly controlled by genetic sources，indicating that the activity of exogenously imported Cd was higher，and the ecological risk was higher. © 2025 Science Press. All rights reserved.

关键词： River pollution

The impacts of concentrations of Tacrolimus on NK cell and receptors in peripheral blood ofrenal transplant recipients

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The impacts of concentrations of Tacrolimus on NK cell and r...

A nuclide identification method ofγspectrum and model building based on the transformer

2012中国器官移植大会

作者： Li Xiao,BingYi Shi,wen qiang Zhou,Yu gao,XiHui Ma,XiuYun He,XiangRui Kong 解放军第309医院

【Objectives】To Study the effects of Tac concentrations on the number of NK cells and receptor expression in peripheral blood of renal transplantation receptors.【Method】A total of 60 first-time kidney transplantation recipients in our institute from december 2007 to july 2009 were followed *** maintenance immunosuppressive therapy were given to all *** were divided into low concentrations of Tac group(6.84±1.72 ug/L.n=30) and high concentrations of Tac group(11.88±2.59 ug/L,n=30)according to

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Nuclear Science and Techniques 2025年第1期36卷 80-93页

作者： Fei Li Chu-Yang Luo Ying-Zi wen Sheng Lv Feng Cheng Guo-qiang Zeng Jian-Feng Jiang Bing-Hai Li College of Nuclear Technology and Automation Engineering Chengdu University of TechnologyChengdu 610000China Applied Nuclear Technology in Geosciences Key Laboratory of Sichuan Province Chengdu 610000China Department of Physics Universitat Politècnica de CatalunyaBarcelona 08028Spain Airborne Survey and Remote Sensing Center of Nuclear Industry Shijiazhuang 050000China Hebei Key Laboratory of Airborne Detection and Remote Sensing Technology Shijiazhuang 050000China

In current neural network algorithms for nuclide identification in high-background,poor-resolution detectors,traditional network paradigms including back-propagation networks,convolutional neural networks,recurrent neural networks,etc.,have been limited in research on γ spectrum analysis because of their inherent mathematical *** is difficult to make progress in terms of training data requirements and prediction *** contrast to traditional network paradigms,network models based on the transformer structure have the characteristics of parallel computing,position encoding,and deep stacking,which have enabled good performance in natural language processing tasks in recent ***,in this paper,a transformer-based neural network (TBNN) model is proposed to achieve nuclide identification for the first ***,the Geant4 program was used to generate the basic single-nuclide energy spectrum through Monte Carlo simulations.A multi-nuclide energy spectrum database was established for neural network training using random matrices of γ-ray energy,activity,and *** on the encoder–decoder structure,a network topology based on the transformer was built,transforming the 1024-channel energy spectrum data into a 32×32 energy spectrum sequence as the model *** experiments and adjustments of model parameters,including the learning rate of the TBNN model,number of attention heads,and number of network stacking layers,the overall recognition rate reached 98.7%.Additionally,this database was used for training AI models such as back-propagation networks,convolutional neural networks,residual networks,and long shortterm memory neural networks,with overall recognition rates of 92.8%,95.3%,96.3%,and 96.6%,*** indicates that the TBNN model exhibited better nuclide identification among these AI models,providing an important reference and theoretical basis for the practical application of transformers in the qualitative and quantitativ

关键词： Nuclide identification Neural network Transformer