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An AIEgen nano-assembly for simultaneous detection of ATP and H_(2)S

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Chinese Chemical Letters 2024年第6期35卷 376-379页

作者： Jia-Mei qin xue Li Wei Lang Fu-Hao Zhang Qian-Yong cao School of Chemistry and Chemical Engineering Nanchang UniversityNanchang 330031China

A new aggregation-induced emission(AIE)-based fluorescence sensor,TPEPy-SS-C14,for simultaneous recognition of adenosine triphosphate(ATP)and hydrogen sulfide(H_(2)S)has been reported via the aggregation-disaggregation *** probe self-assembles nano-structure aggregations in aqueous *** shows fluorescence turn-on response toward ATP for the complexation-enhanced aggregation,but leads to fluorescence quenching of H_(2)S for cleavage the aggregations.

关键词： AIE-based ATP detection H_(2)S detection Fluorescent sensor Cell imaging

L_(1)-Smooth SVM with Distributed Adaptive Proximal Stochastic Gradient Descent with Momentum for Fast Brain Tumor Detection

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Computers, Materials & Continua 2024年第5期79卷 1975-1994页

作者： Chuandong qin Yu cao Liqun Meng School of Mathematics and Information Science North Minzu UniversityYinchuan750021China Ningxia Key Laboratory of Intelligent Information and Big Data Processing Yinchuan750021China

Brain tumors come in various types,each with distinct characteristics and treatment approaches,making manual detection a time-consuming and potentially ambiguous *** tumor detection is a valuable tool for gaining a deeper understanding of tumors and improving treatment *** learning models have become key players in automating brain tumor *** descent methods are the mainstream algorithms for solving machine learning *** this paper,we propose a novel distributed proximal stochastic gradient descent approach to solve the L_(1)-Smooth Support Vector Machine(SVM)classifier for brain tumor ***,the smooth hinge loss is introduced to be used as the loss function of *** avoids the issue of nondifferentiability at the zero point encountered by the traditional hinge loss function during gradient descent ***,the L_(1) regularization method is employed to sparsify features and enhance the robustness of the ***,adaptive proximal stochastic gradient descent(PGD)with momentum,and distributed adaptive PGDwithmomentum(DPGD)are proposed and applied to the L_(1)-Smooth *** computing is crucial in large-scale data analysis,with its value manifested in extending algorithms to distributed clusters,thus enabling more efficient processing ofmassive amounts of *** DPGD algorithm leverages Spark,enabling full utilization of the computer’s multi-core *** to its sparsity induced by L_(1) regularization on parameters,it exhibits significantly accelerated convergence *** the perspective of loss reduction,DPGD converges faster than *** experimental results show that adaptive PGD withmomentumand its variants have achieved cutting-edge accuracy and efficiency in brain tumor ***-trained models,both the PGD andDPGD outperform other models,boasting an accuracy of 95.21%.

关键词： Support vector machine proximal stochastic gradient descent brain tumor detection distributed computing

Random Forest-Based Fatigue Reliability-Based Design Optimization for Aeroengine Structures

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 665-684页

作者： xue-qin Li Lu-Kai Song School of Energy and Power Engineering Beihang UniversityBeijing100191China Department of Mechanical Engineering The Hong Kong Polytechnic UniversityKowloonHong Kong999077China Research Institute of Aero-Engine Beihang UniversityBeijing100191China

Fatigue reliability-based design optimization of aeroengine structures involves multiple repeated calculations of reliability degree and large-scale calls of implicit high-nonlinearity limit state function,leading to the traditional direct Monte Claro and surrogate methods prone to unacceptable computing efficiency and *** this case,by fusing the random subspace strategy and weight allocation technology into bagging ensemble theory,a random forest(RF)model is presented to enhance the computing efficiency of reliability degree;moreover,by embedding the RF model into multilevel optimization model,an efficient RF-assisted fatigue reliability-based design optimization framework is *** the low-cycle fatigue reliability-based design optimization of aeroengine turbine disc as a case,the effectiveness of the presented framework is *** reliabilitybased design optimization results exhibit that the proposed framework holds high computing accuracy and computing *** current efforts shed a light on the theory/method development of reliability-based design optimization of complex engineering structures.

关键词： Random forest reliability-based design optimization ensemble learning machine learning

MTCR-CR Routing Strategy for Connection-Oriented Routing over Satellite Networks

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China Communications 2024年第5期21卷 280-296页

作者： Li Changhao Sun xue Yan Lei cao Suzhi The University of Chinese Academy of Sciences Beijing 100094China Key Laboratory of Space Utilization Chinese Academy of SciencesBeijing 100094China Technology and Engineering Center for Space Utilization Chinese Academy of SciencesBeijing 100094China

The high-speed movement of satellites makes it not feasible to directly apply the mature routing scheme on the ground to the satellite ***-DVTR in the snapshot-based connectionoriented routing strategy is one of the representative solutions,but it still has room for improvement in terms of routing *** this paper,we propose an improved scheme for connection-oriented routing strategy named the Minimal Topology Change Routing based on Collaborative Rules(MTCR-CR).The MTCR-CR uses continuous time static topology snapshots based on satellite status to search for intersatellite link(ISL)construction solutions that meet the minimum number of topology changes to avoid route *** simulation results in Beidou-3 show that compared with DT-DVTR,MTCR-CR reduces the number of routing changes by about 92%,the number of path changes caused by routing changes is about38%,and the rerouting time is reduced by approximately 47%.At the same time,in order to show our algorithm more comprehensively,the same experimental index test was also carried out on the Globalstar satellite constellation.

关键词： ISL routing stability satellite networks satellite routing dynamic strategy

Peeling of Magneto-responsive Beams with Large Deformation Mediated by the Parallel Magnetic Field

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Acta Mechanica Solida Sinica 2024年第3期37卷 457-467页

作者： Gongqi cao Zhangna xue Shiyang Liu Yuchen Jin Jianlin Liu College of Pipeline and Civil Engineering China University of Petroleum(East China)Qingdao266580China

Elasto-capillarity phenomena are prevalent in various industrial fields such as mechanical engineering,material science,aerospace,soft robotics,and *** this study,two typical peeling processes of slender beams driven by the parallel magnetic field are investigated based on experimental and theoretical *** first is the adhesion of two parallel beams,and the second is the self-folding of a long *** these two cases,the energy variation method on the elastica is used,and then,the governing equations and transversality boundary conditions are *** is shown that the analytical solutions are in excellent agreement with the experimental *** effects of magnetic induction intensity,distance,and surface tension on the deflection curve and peeling length of the elastica are fully *** results are instrumental in accurately regulating elasto-capillarity in structures and provide insights for the engineering design of programmable microstructures on surfaces,microsensors,and bionic robots.

关键词： Magneto-responsive beam Adhesion and peeling Self-folding Elastica Transversality condition

Critical environmental factors affecting mountain geohazards in a warming climate in Southwest China

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Advances in Climate Change Research 2024年第4期15卷 695-707页

作者： Xiao-Ming XU Peng CUI xue-qin ZHANG Key Lab of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 10010lChina University of Chinese Academy of Sciences Beijing 100049China China-Pakistan Joint Research Center on Earth Sciences Chinese Academy of Sciences and Higher Education CommissionIslamabad 45320Pakistan

Environmental factors are essential input variables for susceptibility assessment models of mountain ***,the existing literature provides a limited understanding of the relative contribution of these factors to the occurrence of geohazards with a warming climate,posing tremendous challenges for risk management in mountainous ***'an city is susceptible to hazards because of its steep terrain,abundant precipitation and active seismic *** this regard,we utilise the GeoDetector model to extract critical environmental factors affecting the spatial patterns of mountain geohazards(i.e.,landslide,debris flow and rockfall)in Southwest *** analysis indicates that the factors with the highest explanatory power for the spatial distribution of landslides,debris flows,and rockfalls are soil property,extreme precipitation and extreme temperature,***,we revealed the synergistic effects among factors given their larger q-value than individual *** further explored the responses of mountain geohazards to climate change,including the rising temperature and precipitation,because the frequent occurrence of mountain geohazards is closely related to a warming *** variation in snow water equivalent caused by antecedent snowfall and snowdrifts acts as a crucial indicator for geohazards,highlighting the significance of snow and wind observations in meteorological nowcasting and disaster *** disclose the phenomenon of the geohazard hysteresis to the precipitation peak resulting from the top-down(i.e.,precipitation-runoff and surface-deep soil moisture)peak *** work is expected to enhance the precision of susceptibility assessment models and the reliability of short-term forecasts for mountain geohazards.

关键词： Mountain geohazards Environmental factors Climate change GeoDetector Southwest China

Ligand-controlled electrochemiluminescence generation from CdSe/CdS/ZnS core/shell/shell quantum dots

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Nano Research 2024年第8期17卷 7776-7785页

作者： Hui Sun Zhiyuan cao Haiyan qin Xiaogang Peng Bin Su Key Laboratory of Excited-State Materials of Zhejiang Province Department of ChemistryZhejiang UniversityHangzhou 310058China

The CdSe/CdS/ZnS core/shell/shell quantum dots(QDs)with strong exciton confinement have manifested themselves as competitive light-emitting materials in electrochemiluminescence(ECL).However,cathodic ECL generation by these QDs requires the injection of electron and hole from solid electrode and electrogenerated radicals(for example SO_(4)•^(−)),which is inevitably influenced by not only the inorganic structure of QDs but also the organic ligands on the *** this work we aimed at studying the impact of surface organic ligands on ECL performance of CdSe/CdS/ZnS *** changing the surface ligand from oleate to acetate,we phenomenologically observed the positive shift of ECL onset potential by ca.200 mV and the increase of ECL intensity by~100 times,suggesting that a short ligand is more favorable for ECL *** further comprehend the ligand effect,we measured the charge injection kinetics using potential-modulated,time-resolved photoluminescence,and thinlayer spectroelectrochemistry *** electron and hole injection into QDs were found to be accelerated by 2–20 times if shortening the ligand from oleate to acetate,confirming the significant impact of surface ligands on ECL performance of *** study is expected to provide guidance on how to design surface functionalized QDs for specific applications such as ECL immunodiagnosis,photocatalysis,and photovoltaics.

关键词： electrochemiluminescence quantum dots spectroelectrochemistry surface ligands charge injection charge transfer

Intensified warming suppressed the snowmelt in the Tibetan Plateau

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Advances in Climate Change Research 2024年第3期15卷 452-463页

作者： Xiang LI Peng CUI xue-qin ZHANG Fang ZHANG Key Lab of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources ResearchBeijing 100101China University of Chinese Academy of Sciences Beijing 100049China China‒Pakistan Joint Research Center on Earth Sciences Chinese Academy of Sciences and Higher Education CommissionIslamabad 45320Pakistan

Understanding how hydrological factors interrelate is crucial when examining the impact of climate warming on ***,these connections are often overlooked,leading to an unclear relationship between temperature and *** study investigates the complex interplay between temperature and snowmelt in the Tibetan Plateau from 1961 to 2020,focusing on how extreme high-temperature events affect the frequency of extreme *** a structural equation model,we detected three temperature-related factors that predominantly influenced snowmelt and extreme *** annual average temperature was found to have a significant indirect impact on snowmelt,mediated by changes in snowfall,snow depth and snow *** contrast,high-temperature days(daily maximum temperatures exceeding the 90th percentile)and heat waves(at least three consecutive high-temperature days)negatively affected extreme snowmelt directly or *** direct effect of increasing extreme temperature events was associated with an earlier onset of high-temperature periods,which accelerated snowmelt and shortened the duration of extreme snowmelt ***,the reduction in snow cover owing to warming emerged as a main factor suppressing snowmelt and extreme snowmelt *** also revealed spatiotemporal variations in the temperature‒snowmelt relationship that highly depended on changes in snowmelt *** study elucidated why warming suppresses snowmelt and extreme snowmelt events in the Tibetan Plateau,highlighting the mediating roles of snow-related and phenological *** findings will provide scientific support for climate simulation and water management policymaking in alpine regions worldwide.

关键词： Climate change Extreme temperature Snowmelt Structural equation model Tibetan Plateau

Model-based offline reinforcement learning framework for optimizing tunnel boring machine operation

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Underground Space 2024年第6期19卷 47-71页

作者： Yupeng cao Wei Luo Yadong xue Weiren Lin Feng Zhang Department of Urban Management Kyoto UniversityKyoto 615-8540Japan Department of Geotechnical Engineering College of Civil EngineeringTongji UniversityShanghai 200092China Key Laboratory of Geotechnical and Underground Engineering of Ministry of Education Tongji UniversityShanghai 200092China

Research on automation and intelligent operation of tunnel boring machine(TBM)is receiving more and more attention,benefiting from the increasing construction ***,most studies on TBM operations optimization were trained by the labels of human drivers’decisions,which were subjective and *** a result,the control parameters suggested by these models could hardly surpass the performance of a human driver,even the possibility of subjective incorrect *** that the geomechanical feedback to TBM under drivers’actions is objective,in this paper,a transformer-based model called the geological response for tunnel boring machine(GRTBM),is proposed to learn the relationship between operation-adjust and TBM monitoring ***,with the model-based offline reinforcement learning,this paper provided a novel approach to optimizing the TBM excavation *** decision processes,recorded in the Yin-song TBM project for a waterway tunnel in Jilin Province of China,were used for the validation of the *** adopting an implicit perception of geological conditions in the GRTBM model,the suggested method achieved the desired state within a single action,greatly outperformed the practical adjustments where 500 s were taken,revealing the fact that the proposed model has the potential to surpass the capability of human beings.

关键词： TBM Reinforcement learning Transformer Data mining