1.Introduction Climate change mitigation pathways aimed at limiting global anthropogenic carbon dioxide(CO_(2))emissions while striving to constrain the global temperature increase to below 2℃—as outlined by the Int...1.Introduction Climate change mitigation pathways aimed at limiting global anthropogenic carbon dioxide(CO_(2))emissions while striving to constrain the global temperature increase to below 2℃—as outlined by the Intergovernmental Panel on Climate Change(IPCC)—consistently predict the widespread implementation of CO_(2)geological storage on a global scale.展开更多
The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(I...The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(IoT)relies on the support of base stations,which provide a solid foundation for achieving a more intelligent way of living.In a specific area,achieving higher signal coverage with fewer base stations has become an urgent problem.Therefore,this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization(EPSO)algorithm based on collective prediction,referred to herein as ECPPSO.Introducing a new strategy called neighbor-based evolution prediction(NEP)addresses the issue of premature convergence often encountered by PSO.ECPPSO also employs a strengthening evolution(SE)strategy to enhance the algorithm’s global search capability and efficiency,ensuring enhanced robustness and a faster convergence speed when solving complex optimization problems.To better adapt to the actual communication needs of base stations,this article conducts simulation experiments by changing the number of base stations.The experimental results demonstrate thatunder the conditionof 50 ormore base stations,ECPPSOconsistently achieves the best coverage rate exceeding 95%,peaking at 99.4400%when the number of base stations reaches 80.These results validate the optimization capability of the ECPPSO algorithm,proving its feasibility and effectiveness.Further ablative experiments and comparisons with other algorithms highlight the advantages of ECPPSO.展开更多
Metal-support interactions and hydrogen spillover effects in heterogeneous catalysts play a crucial role in aromatic hydrogenation reactions;however,these effects are limited by the metal dispersion on the catalyst an...Metal-support interactions and hydrogen spillover effects in heterogeneous catalysts play a crucial role in aromatic hydrogenation reactions;however,these effects are limited by the metal dispersion on the catalyst and the number of acceptable H*receptors.This study prepares highly dispersed Ni nanoparticles(NPs)catalysts on a Beta substrate via precursor structure topology transformation.In contrast to traditional support materials,the coordination and electronic structure changes between the Ni NPs and the support were achieved,further optimizing the active interface sites and enhancing hydrogen activation and hydrogenation performance.Additionally,the-OH groups at the strong acid sites in zeolite effectively intensified the hydrogen spillover effect as receptors for H^(*)migration and anchoring,accelerating the hydrogenation rate of aromatic rings.Under solvent-free conditions,this catalyst was used for the hydrogenation reaction of aromatic-rich oils,directly producing a C_(8)-C_(14)branched cycloalkanes mixture with an aromatic conversion rate of>99%.The cycloalkanes mixture produced by this method features high density(0.92 g/mL)and a low freezing point(<-60℃),making it suitable for use as high-density aviation fuel or as an additive to enhance the volumetric heat value of conventional aviation fuels in practical applications.展开更多
The quantity of space debris on Earth orbit has escalated tremendously in recent years, presenting a significant hazard to human space operations. It is urgent to develop effective measures to capture and remove vario...The quantity of space debris on Earth orbit has escalated tremendously in recent years, presenting a significant hazard to human space operations. It is urgent to develop effective measures to capture and remove various space debris. For this purpose, this paper presents a tendon-actuated flexible deployable manipulator. The flexible manipulator consists of several deployable units connected by Cardan joints and actuated by tendons. Compared with the present technologies for capturing space debris such as rigid robotic arm or flying net, this flexible manipulator is deployable, reusable, lightweight and applicable to the capture of large space debris. In order to investigate its deployment dynamics, an accurate dynamic model of the flexible manipulator is established based on the natural coordinate formulation (NCF) and the absolute nodal coordinate formulation (ANCF). Subsequently, numerical simulations are carried out to study the effects of system parameters and the base satellite on its deployment dynamics. Finally, ground experiments for both deployment and bending of the flexible manipulator are conducted to verify its effectiveness and feasibility.展开更多
In rotationally extruded fittings,high-density polyethylene(HDPE)pipes prepared using conventional processing methods often suffer from poor pressure resistance and low toughness.This study introduces an innovative ro...In rotationally extruded fittings,high-density polyethylene(HDPE)pipes prepared using conventional processing methods often suffer from poor pressure resistance and low toughness.This study introduces an innovative rotary shear system(RSS)to address these deficiencies through controlled mandrel rotation and cooling rates.We successfully prepared self-reinforced HDPE pipes with a three-layer structure combining spherical and shish-kebab crystals.Rotational processing aligned the molecular chains in the ring direction and formed shish-kebab crystals.As a result,the annular tensile strength of the rotationally processed three-layer shish-kebab structure(TSK)pipe increased from 26.7 MPa to 76.3 MPa,an enhancement of 185.8%.Notably,while maintaining excellent tensile strength(73.4 MPa),the elongation at break of the spherulite shishkebab spherulite(SKS)tubes was improved to 50.1%,as compared to 33.8%in the case of shish-kebab spherulite shish-kebab(KSK)tubes.This improvement can be attributed to the changes in the micro-morphology and polymer structure within the SKS tubes,specifically due to the formation of small-sized shish-kebab crystals and the low degrees of interlocking.In addition,2D-SAXS analysis revealed that KSK tubes have higher tensile strength due to smaller crystal sizes and larger shish dimensions,forming dense interlocking structures.In contrast,the SKS and TSK tubes had thicker amorphous regions and smaller shish sizes,resulting in reduced interlocking and mechanical performance.展开更多
Mesh reflector antennas are the mainstream of large space-borne antennas,and the stretching of the truss achieves their deployment.Currently,the truss is commonly designed to be a single degree of freedom(DOF)deployab...Mesh reflector antennas are the mainstream of large space-borne antennas,and the stretching of the truss achieves their deployment.Currently,the truss is commonly designed to be a single degree of freedom(DOF)deployable mechanism with synchronization constraints.However,each deployable unit’s drive distribution and resistance load are uneven,and the forced synchronization constraints lead to the flexible deformation of rods and difficulties in the deployment scheme design.This paper introduces an asynchronous deployment scheme with a multi-DOF closed-chain deployable truss.The DOF of the truss is calculated,and the kinematic and dynamic models are established,considering the truss’s and cable net’s real-time coupling.An integrated solving algorithm for implicit differential-algebraic equations is proposed to solve the dynamic models.A prototype of a six-unit antenna was fabricated,and the experiment was carried out.The dynamic performances in synchronous and asynchronous deployment schemes are analyzed,and the results show that the cable resistance and truss kinetic energy impact under the asynchronous deployment scheme are minor,and the antenna is more straightforward to deploy.The work provides a new asynchronous deployment scheme and a universal antenna modeling method for dynamic design and performance improvement.展开更多
The aerial deployment method enables Unmanned Aerial Vehicles(UAVs)to be directly positioned at the required altitude for their mission.This method typically employs folding technology to improve loading efficiency,wi...The aerial deployment method enables Unmanned Aerial Vehicles(UAVs)to be directly positioned at the required altitude for their mission.This method typically employs folding technology to improve loading efficiency,with applications such as the gravity-only aerial deployment of high-aspect-ratio solar-powered UAVs,and aerial takeoff of fixed-wing drones in Mars research.However,the significant morphological changes during deployment are accompanied by strong nonlinear dynamic aerodynamic forces,which result in multiple degrees of freedom and an unstable character.This hinders the description and analysis of unknown dynamic behaviors,further leading to difficulties in the design of deployment strategies and flight control.To address this issue,this paper proposes an analysis method for dynamic behaviors during aerial deployment based on the Variational Autoencoder(VAE).Focusing on the gravity-only deployment problem of highaspect-ratio foldable-wing UAVs,the method encodes the multi-degree-of-freedom unstable motion signals into a low-dimensional feature space through a data-driven approach.By clustering in the feature space,this paper identifies and studies several dynamic behaviors during aerial deployment.The research presented in this paper offers a new method and perspective for feature extraction and analysis of complex and difficult-to-describe extreme flight dynamics,guiding the research on aerial deployment drones design and control strategies.展开更多
High-density interconnect(HDI)soft electronics that can integrate multiple individual functions into one miniaturized monolithic system is promising for applications related to smart healthcare,soft robotics,and human...High-density interconnect(HDI)soft electronics that can integrate multiple individual functions into one miniaturized monolithic system is promising for applications related to smart healthcare,soft robotics,and human-machine interactions.However,despite the recent advances,the development of three-dimensional(3D)soft electronics with both high resolution and high integration is still challenging because of the lack of efficient manufacturing methods to guarantee interlayer alignment of the high-density vias and reliable interlayer electrical conductivity.Here,an advanced 3D laser printing pathway,based on femtosecond laser direct writing(FLDW),is demonstrated for preparing liquid metal(LM)-based any layer HDI soft electronics.FLDW technology,with the characteristics of high spatial resolution and high precision,allows the maskless fabrication of high-resolution embedded LM microchannels and high-density vertical interconnect accesses for 3D integrated circuits.High-aspect-ratio blind/through LM microstructures are formed inside the elastomer due to the supermetalphobicity induced during laser ablation.The LM-based HDI circuit featuring high resolution(~1.5μm)and high integration(10-layer electrical interconnection)is achieved for customized soft electronics,including various customized multilayer passive electric components,soft multilayer circuit,and cross-scale multimode sensors.The 3D laser printing method provides a versatile approach for developing chip-level soft electronics.展开更多
Deep learning-based intelligent recognition algorithms are increasingly recognized for their potential to address the labor-intensive challenge of manual pest detection.However,their deployment on mobile devices has b...Deep learning-based intelligent recognition algorithms are increasingly recognized for their potential to address the labor-intensive challenge of manual pest detection.However,their deployment on mobile devices has been constrained by high computational demands.Here,we developed GBiDC-PEST,a mobile application that incorporates an improved,lightweight detection algorithm based on the You Only Look Once(YOLO)series singlestage architecture,for real-time detection of four tiny pests(wheat mites,sugarcane aphids,wheat aphids,and rice planthoppers).GBiDC-PEST incorporates several innovative modules,including GhostNet for lightweight feature extraction and architecture optimization by reconstructing the backbone,the bi-directional feature pyramid network(BiFPN)for enhanced multiscale feature fusion,depthwise convolution(DWConv)layers to reduce computational load,and the convolutional block attention module(CBAM)to enable precise feature focus.The newly developed GBiDC-PEST was trained and validated using a multitarget agricultural tiny pest dataset(Tpest-3960)that covered various field environments.GBiDC-PEST(2.8 MB)significantly reduced the model size to only 20%of the original model size,offering a smaller size than the YOLO series(v5-v10),higher detection accuracy than YOLOv10n and v10s,and faster detection speed than v8s,v9c,v10m and v10b.In Android deployment experiments,GBiDCPEST demonstrated enhanced performance in detecting pests against complex backgrounds,and the accuracy for wheat mites and rice planthoppers was improved by 4.5-7.5%compared with the original model.The GBiDC-PEST optimization algorithm and its mobile deployment proposed in this study offer a robust technical framework for the rapid,onsite identification and localization of tiny pests.This advancement provides valuable insights for effective pest monitoring,counting,and control in various agricultural settings.展开更多
In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel.Most studies focus on optimizing base station deploym...In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel.Most studies focus on optimizing base station deployment under the assumption of static obstacles,aiming to maximize the perception coverage of wireless RF(Radio Frequency)signals and reduce positioning blind spots.However,in practical security systems,obstacles are subject to change,necessitating the consideration of base station deployment in dynamic environments.Nevertheless,research in this area still needs to be conducted.This paper proposes a Dynamic Indoor Environment Beacon Deployment Algorithm(DIE-BDA)to address this problem.This algorithm considers the dynamic alterations in obstacle locations within the designated area.It determines the requisite number of base stations,the requisite time,and the area’s practical and overall signal coverage rates.The experimental results demonstrate that the algorithm can calculate the deployment strategy in 0.12 s following a change in obstacle positions.Experimental results show that the algorithm in this paper requires 0.12 s to compute the deployment strategy after the positions of obstacles change.With 13 base stations,it achieves an effective coverage rate of 93.5%and an overall coverage rate of 97.75%.The algorithm can rapidly compute a revised deployment strategy in response to changes in obstacle positions within security systems,thereby ensuring the efficacy of signal coverage.展开更多
In the deployment of wireless networks in two-dimensional outdoor campus spaces,aiming at the problem of efficient coverage of the monitoring area by limited number of access points(APs),this paper proposes a deployme...In the deployment of wireless networks in two-dimensional outdoor campus spaces,aiming at the problem of efficient coverage of the monitoring area by limited number of access points(APs),this paper proposes a deployment method of multi-objective optimization with virtual force fusion bat algorithm(VFBA)using the classical four-node regular distribution as an entry point.The introduction of Lévy flight strategy for bat position updating helps to maintain the population diversity,reduce the premature maturity problem caused by population convergence,avoid the over aggregation of individuals in the local optimal region,and enhance the superiority in global search;the virtual force algorithm simulates the attraction and repulsion between individuals,which enables individual bats to precisely locate the optimal solution within the search space.At the same time,the fusion effect of virtual force prompts the bat individuals to move faster to the potential optimal solution.To validate the effectiveness of the fusion algorithm,the benchmark test function is selected for simulation testing.Finally,the simulation result verifies that the VFBA achieves superior coverage and effectively reduces node redundancy compared to the other three regular layout methods.The VFBA also shows better coverage results when compared to other optimization algorithms.展开更多
Dislocation strengthening,as one of the methods to simultaneously enhance the room temperature strength and ductility of alloys,does not achieve the desired strengthening and plasticity effect during elevated-temperat...Dislocation strengthening,as one of the methods to simultaneously enhance the room temperature strength and ductility of alloys,does not achieve the desired strengthening and plasticity effect during elevated-temperature deformation.Here,we report a novel strategy to boost the dislocation multiplication and accumulation during deformation at elevated temperatures through dynamic strain aging(DSA).With the introduction of the rare-earth element Ho in Mg-Y-Zn alloy,Ho atoms diffuse toward dislocations during deformation at elevated temperatures,provoking the DSA effect,which increases the dislocation density significantly via the interactions of mobile dislocations and Ho atoms.The resulting alloy achieves a great enhancement of dislocation hardening and obtains the dual benefits of high strength and good ductility simultaneously at high homologous temperatures.The present work provides an effective strategy to enhancing the strength and ductility for elevated-temperature materials.展开更多
This study investigates the disparities in the deployment of photovoltaic(PV)technology for carbon emissions reduction across different nations,highlighting the mismatch between countries with high economic capacity a...This study investigates the disparities in the deployment of photovoltaic(PV)technology for carbon emissions reduction across different nations,highlighting the mismatch between countries with high economic capacity and those where PV installation would maximize global decarbonization benefits.This mismatch is discussed based on three key factors influencing decarbonization via PV technology:per capita gross domestic product;carbon intensity of the energy system;and solar resource availability.Current PV deployment is predominantly concentrated in economically advanced countries,and does not coincide with regions where the environmental and economic impact of such installations would be most significant.Through a series of thought experiments,it is demonstrated how alternative prioritization strategies could significantly reduce global carbon emissions.Argument is put forward for a globally coordinated approach to PV deployment,particularly targeting high-impact sunbelt regions,to enhance the efficacy of decarbonization efforts and promote equitable energy access.The study underscores the need for international policies that support sustainable energy transitions in economically less developed regions through workforce development and assistance with the activation of capital.展开更多
As Internet ofThings(IoT)technologies continue to evolve at an unprecedented pace,intelligent big data control and information systems have become critical enablers for organizational digital transformation,facilitati...As Internet ofThings(IoT)technologies continue to evolve at an unprecedented pace,intelligent big data control and information systems have become critical enablers for organizational digital transformation,facilitating data-driven decision making,fostering innovation ecosystems,and maintaining operational stability.In this study,we propose an advanced deployment algorithm for Service Function Chaining(SFC)that leverages an enhanced Practical Byzantine Fault Tolerance(PBFT)mechanism.The main goal is to tackle the issues of security and resource efficiency in SFC implementation across diverse network settings.By integrating blockchain technology and Deep Reinforcement Learning(DRL),our algorithm not only optimizes resource utilization and quality of service but also ensures robust security during SFC deployment.Specifically,the enhanced PBFT consensus mechanism(VRPBFT)significantly reduces consensus latency and improves Byzantine node detection through the introduction of a Verifiable Random Function(VRF)and a node reputation grading model.Experimental results demonstrate that compared to traditional PBFT,the proposed VRPBFT algorithm reduces consensus latency by approximately 30%and decreases the proportion of Byzantine nodes by 40%after 100 rounds of consensus.Furthermore,the DRL-based SFC deployment algorithm(SDRL)exhibits rapid convergence during training,with improvements in long-term average revenue,request acceptance rate,and revenue/cost ratio of 17%,14.49%,and 20.35%,respectively,over existing algorithms.Additionally,the CPU resource utilization of the SDRL algorithmreaches up to 42%,which is 27.96%higher than other algorithms.These findings indicate that the proposed algorithm substantially enhances resource utilization efficiency,service quality,and security in SFC deployment.展开更多
For large-scale heterogeneous multi-agent systems(MASs)with characteristics of dense-sparse mixed distribution,this paper investigates the practical finite-time deployment problem by establishing a novel crossspecies ...For large-scale heterogeneous multi-agent systems(MASs)with characteristics of dense-sparse mixed distribution,this paper investigates the practical finite-time deployment problem by establishing a novel crossspecies bionic analytical framework based on the partial differential equation-ordinary differential equation(PDE-ODE)approach.Specifically,by designing a specialized network communication protocol and employing the spatial continuum method for densely distributed agents,this paper models the tracking errors of densely distributed agents as a PDE equivalent to a human disease transmission model,and that of sparsely distributed agents as several ODEs equivalent to the predator population models.The coupling relationship between the PDE and ODE models is established through boundary conditions of the PDE,thereby forming a PDE-ODE-based tracking error model for the considered MASs.Furthermore,by integrating adaptive neural control scheme with the aforementioned biological models,a“Flexible Neural Network”endowed with adaptive and self-stabilized capabilities is constructed,which acts upon the considered MASs,enabling their practical finite-time deployment.Finally,effectiveness of the developed approach is illustrated through a numerical example.展开更多
Aiming at node deployment in the monitoring area of the field observation instrument network in the cold and arid regions,we propose a virtual force algorithm based on Voronoi diagram(VFAVD),which adopts probabilistic...Aiming at node deployment in the monitoring area of the field observation instrument network in the cold and arid regions,we propose a virtual force algorithm based on Voronoi diagram(VFAVD),which adopts probabilistic sensing model that is more in line with the actual situation.First,the Voronoi diagram is constructed in the monitoring area to determine the Thiessen polygon of each node.Then,the virtual force on each node is calculated,and the node update its position according to the direction and size of the total force,so as to achieve the purpose of improving the network coverage rate.The simulation results show that the proposed algorithm can effectively improve the coverage rate of the network,and also has a good effect on the coverage uniformity.展开更多
Wireless sensor network deployment optimization is a classic NP-hard problem and a popular topic in academic research.However,the current research on wireless sensor network deployment problems uses overly simplistic ...Wireless sensor network deployment optimization is a classic NP-hard problem and a popular topic in academic research.However,the current research on wireless sensor network deployment problems uses overly simplistic models,and there is a significant gap between the research results and actual wireless sensor networks.Some scholars have now modeled data fusion networks to make them more suitable for practical applications.This paper will explore the deployment problem of a stochastic data fusion wireless sensor network(SDFWSN),a model that reflects the randomness of environmental monitoring and uses data fusion techniques widely used in actual sensor networks for information collection.The deployment problem of SDFWSN is modeled as a multi-objective optimization problem.The network life cycle,spatiotemporal coverage,detection rate,and false alarm rate of SDFWSN are used as optimization objectives to optimize the deployment of network nodes.This paper proposes an enhanced multi-objective mongoose optimization algorithm(EMODMOA)to solve the deployment problem of SDFWSN.First,to overcome the shortcomings of the DMOA algorithm,such as its low convergence and tendency to get stuck in a local optimum,an encircling and hunting strategy is introduced into the original algorithm to propose the EDMOA algorithm.The EDMOA algorithm is designed as the EMODMOA algorithm by selecting reference points using the K-Nearest Neighbor(KNN)algorithm.To verify the effectiveness of the proposed algorithm,the EMODMOA algorithm was tested at CEC 2020 and achieved good results.In the SDFWSN deployment problem,the algorithm was compared with the Non-dominated Sorting Genetic Algorithm II(NSGAII),Multiple Objective Particle Swarm Optimization(MOPSO),Multi-Objective Evolutionary Algorithm based on Decomposition(MOEA/D),and Multi-Objective Grey Wolf Optimizer(MOGWO).By comparing and analyzing the performance evaluation metrics and optimization results of the objective functions of the multi-objective algorithms,the algorithm outperforms the other algorithms in the SDFWSN deployment results.To better demonstrate the superiority of the algorithm,simulations of diverse test cases were also performed,and good results were obtained.展开更多
Resource management must attach importance to effective resource deployment.Aiming at the research of resource deployment system,firstly,as an important factor of resource deployment system,corporate technological inn...Resource management must attach importance to effective resource deployment.Aiming at the research of resource deployment system,firstly,as an important factor of resource deployment system,corporate technological innovation social responsibility(CISR)is analyzed.Based on this,this paper constructs a system dynamics model to analyze the changes in resource deployment system affected by CISR.The simulation model is developed using Venism personal learning edition(PLE).The results show that CISR,acted as a new factor affecting the resource deployment system,has a positive effect on resource deployment system performance.Moreover,when CISR exceeds the threshold value,the resource deployment system performance increases significantly faster,reflecting that the resource deployment system becomes more efficient.The results show that the method proposed in this paper is feasible and efficient.This research provides theoretical and practical implications for resource deployment system research.展开更多
Rapeseed mustard(Brassica juncea L.) is the third most important oilseed crop in the world, but the geneticmechanism underlying its massive phenotypic variation remains largely unexplored. In this study, specific leng...Rapeseed mustard(Brassica juncea L.) is the third most important oilseed crop in the world, but the geneticmechanism underlying its massive phenotypic variation remains largely unexplored. In this study, specific length amplified fragment sequencing(SLAF-Seq) was used to resequence a population comprising 197 F8recombinantinbred lines(RILs) derived from a cross between vegetable-type Qichi881 and oilseed-type YufengZC of B. juncea. In total, 438,895 high-quality SLAFs were discovered, 47,644 of which were polymorphic, and 3,887 of the polymorphic markers met the requirements for genetic map construction. The final map included 3,887 markers on 18 linkage groups and was 1,830.23 centiMorgan(cM) in length, with an average distance of 0.47 cM between adjacent markers. Using the newly constructed high-density genetic map, a total of 53 QTLs for erucicacid(EA), oleic acid(OA), and linolenic acid(LNA) were detected and integrated into eight consensus QTLswith two for each of these traits. For each of these three traits, two candidate genes were cloned and sequence analysis indicated colocalization with their respective consensus QTLs. The co-dominant allele-specific markers for Bju.FAD3.A03 and Bju.FAD3.B07 were developed and showed co-localization with their consensus QTLs andco-segregation with LNA content, further supporting the results of QTL mapping and bioinformatic analysis. Theexpression levels of the cloned homologous genes were also determined, and the genes were tightly correlatedwith the EA, OA and LNA contents of different lines. The results of this study will facilitate the improvement offatty acid traits and molecular breeding of B. juncea. Further uses of the high-density genetic map created in this study are also discussed.展开更多
Stroke survivors often face significant challenges when performing daily self-care activities due to upper limb motor impairments.Traditional surface electromyography(sEMG)analysis typically focuses on isolated hand p...Stroke survivors often face significant challenges when performing daily self-care activities due to upper limb motor impairments.Traditional surface electromyography(sEMG)analysis typically focuses on isolated hand postures,overlooking the complexity of object-interactive behaviors that are crucial for promoting patient independence.This study introduces a novel framework that combines high-density sEMG(HD-sEMG)signals with an improved Whale Optimization Algorithm(IWOA)-optimized Long Short-Term Memory(LSTM)network to address this limitation.The key contributions of this work include:(1)the creation of a specialized HD-sEMG dataset that captures nine continuous self-care behaviors,along with time and posture markers,to better reflect real-world patient interactions;(2)the development of a multi-channel feature fusion module based on Pascal’s theorem,which enables efficient signal segmentation and spatial–temporal feature extraction;and(3)the enhancement of the IWOA algorithm,which integrates optimal point set initialization,a diversity-driven pooling mechanism,and cosine-based differential evolution to optimize LSTM hyperparameters,thereby improving convergence and global search capabilities.Experimental results demonstrate superior performance,achieving 99.58%accuracy in self-care behavior recognition and 86.19%accuracy for 17 continuous gestures on the Ninapro db2 benchmark.The framework operates with low latency,meeting the real-time requirements for assistive devices.By enabling precise,context-aware recognition of daily activities,this work advances personalized rehabilitation technologies,empowering stroke patients to regain autonomy in self-care tasks.The proposed methodology offers a robust,scalable solution for clinical applications,bridging the gap between laboratory-based gesture recognition and practical,patient-centered care.展开更多
基金supported by the National Key Research and Development Program of China(2022YFE0206700)。
文摘1.Introduction Climate change mitigation pathways aimed at limiting global anthropogenic carbon dioxide(CO_(2))emissions while striving to constrain the global temperature increase to below 2℃—as outlined by the Intergovernmental Panel on Climate Change(IPCC)—consistently predict the widespread implementation of CO_(2)geological storage on a global scale.
基金supported by the National Natural Science Foundation of China(Nos.62272418,62102058)Basic Public Welfare Research Program of Zhejiang Province(No.LGG18E050011)the Major Open Project of Key Laboratory for Advanced Design and Intelligent Computing of the Ministry of Education under Grant ADIC2023ZD001,National Undergraduate Training Program on Innovation and Entrepreneurship(No.202410345054).
文摘The wireless signals emitted by base stations serve as a vital link connecting people in today’s society and have been occupying an increasingly important role in real life.The development of the Internet of Things(IoT)relies on the support of base stations,which provide a solid foundation for achieving a more intelligent way of living.In a specific area,achieving higher signal coverage with fewer base stations has become an urgent problem.Therefore,this article focuses on the effective coverage area of base station signals and proposes a novel Evolutionary Particle Swarm Optimization(EPSO)algorithm based on collective prediction,referred to herein as ECPPSO.Introducing a new strategy called neighbor-based evolution prediction(NEP)addresses the issue of premature convergence often encountered by PSO.ECPPSO also employs a strengthening evolution(SE)strategy to enhance the algorithm’s global search capability and efficiency,ensuring enhanced robustness and a faster convergence speed when solving complex optimization problems.To better adapt to the actual communication needs of base stations,this article conducts simulation experiments by changing the number of base stations.The experimental results demonstrate thatunder the conditionof 50 ormore base stations,ECPPSOconsistently achieves the best coverage rate exceeding 95%,peaking at 99.4400%when the number of base stations reaches 80.These results validate the optimization capability of the ECPPSO algorithm,proving its feasibility and effectiveness.Further ablative experiments and comparisons with other algorithms highlight the advantages of ECPPSO.
基金financially supported by the National Natural Science Foundation of China(Grant 22278439,21776313)the Shandong Province Higher Education Youth Innovation Technology Support Program(Grant 2022KJ074)。
文摘Metal-support interactions and hydrogen spillover effects in heterogeneous catalysts play a crucial role in aromatic hydrogenation reactions;however,these effects are limited by the metal dispersion on the catalyst and the number of acceptable H*receptors.This study prepares highly dispersed Ni nanoparticles(NPs)catalysts on a Beta substrate via precursor structure topology transformation.In contrast to traditional support materials,the coordination and electronic structure changes between the Ni NPs and the support were achieved,further optimizing the active interface sites and enhancing hydrogen activation and hydrogenation performance.Additionally,the-OH groups at the strong acid sites in zeolite effectively intensified the hydrogen spillover effect as receptors for H^(*)migration and anchoring,accelerating the hydrogenation rate of aromatic rings.Under solvent-free conditions,this catalyst was used for the hydrogenation reaction of aromatic-rich oils,directly producing a C_(8)-C_(14)branched cycloalkanes mixture with an aromatic conversion rate of>99%.The cycloalkanes mixture produced by this method features high density(0.92 g/mL)and a low freezing point(<-60℃),making it suitable for use as high-density aviation fuel or as an additive to enhance the volumetric heat value of conventional aviation fuels in practical applications.
基金the National Natural Science Foundation of China(Nos.11832005,12372042,12232011)Young Elite Scientists Sponsorship Program by CAST(No.2022QNRC001)+1 种基金the Fundamental Research Funds for the Central Universities(No.NS2023002)State Key Laboratory of Mechanics and Control for Aerospace Structures(Nanjing University of Aeronautics and Astronautics)(No.MCAS-S-0223K04).
文摘The quantity of space debris on Earth orbit has escalated tremendously in recent years, presenting a significant hazard to human space operations. It is urgent to develop effective measures to capture and remove various space debris. For this purpose, this paper presents a tendon-actuated flexible deployable manipulator. The flexible manipulator consists of several deployable units connected by Cardan joints and actuated by tendons. Compared with the present technologies for capturing space debris such as rigid robotic arm or flying net, this flexible manipulator is deployable, reusable, lightweight and applicable to the capture of large space debris. In order to investigate its deployment dynamics, an accurate dynamic model of the flexible manipulator is established based on the natural coordinate formulation (NCF) and the absolute nodal coordinate formulation (ANCF). Subsequently, numerical simulations are carried out to study the effects of system parameters and the base satellite on its deployment dynamics. Finally, ground experiments for both deployment and bending of the flexible manipulator are conducted to verify its effectiveness and feasibility.
基金supported by the National Natural Science Foundation of China(Nos.52373045 and 52033005).
文摘In rotationally extruded fittings,high-density polyethylene(HDPE)pipes prepared using conventional processing methods often suffer from poor pressure resistance and low toughness.This study introduces an innovative rotary shear system(RSS)to address these deficiencies through controlled mandrel rotation and cooling rates.We successfully prepared self-reinforced HDPE pipes with a three-layer structure combining spherical and shish-kebab crystals.Rotational processing aligned the molecular chains in the ring direction and formed shish-kebab crystals.As a result,the annular tensile strength of the rotationally processed three-layer shish-kebab structure(TSK)pipe increased from 26.7 MPa to 76.3 MPa,an enhancement of 185.8%.Notably,while maintaining excellent tensile strength(73.4 MPa),the elongation at break of the spherulite shishkebab spherulite(SKS)tubes was improved to 50.1%,as compared to 33.8%in the case of shish-kebab spherulite shish-kebab(KSK)tubes.This improvement can be attributed to the changes in the micro-morphology and polymer structure within the SKS tubes,specifically due to the formation of small-sized shish-kebab crystals and the low degrees of interlocking.In addition,2D-SAXS analysis revealed that KSK tubes have higher tensile strength due to smaller crystal sizes and larger shish dimensions,forming dense interlocking structures.In contrast,the SKS and TSK tubes had thicker amorphous regions and smaller shish sizes,resulting in reduced interlocking and mechanical performance.
基金supported by the National Key R&D Program of China(Grant No.2023YFB3407103)the National Natural Science Foundation of China(Grant Nos.52175242 and 52175027)Young Elite Scientists Sponsorship Program by China Association for Science and Technology(Grant No.2022QNRC001).
文摘Mesh reflector antennas are the mainstream of large space-borne antennas,and the stretching of the truss achieves their deployment.Currently,the truss is commonly designed to be a single degree of freedom(DOF)deployable mechanism with synchronization constraints.However,each deployable unit’s drive distribution and resistance load are uneven,and the forced synchronization constraints lead to the flexible deformation of rods and difficulties in the deployment scheme design.This paper introduces an asynchronous deployment scheme with a multi-DOF closed-chain deployable truss.The DOF of the truss is calculated,and the kinematic and dynamic models are established,considering the truss’s and cable net’s real-time coupling.An integrated solving algorithm for implicit differential-algebraic equations is proposed to solve the dynamic models.A prototype of a six-unit antenna was fabricated,and the experiment was carried out.The dynamic performances in synchronous and asynchronous deployment schemes are analyzed,and the results show that the cable resistance and truss kinetic energy impact under the asynchronous deployment scheme are minor,and the antenna is more straightforward to deploy.The work provides a new asynchronous deployment scheme and a universal antenna modeling method for dynamic design and performance improvement.
基金co-supported by the Natural Science Basic Research Program of Shaanxi,China(No.2023-JC-QN-0043)the ND Basic Research Funds,China(No.G2022WD).
文摘The aerial deployment method enables Unmanned Aerial Vehicles(UAVs)to be directly positioned at the required altitude for their mission.This method typically employs folding technology to improve loading efficiency,with applications such as the gravity-only aerial deployment of high-aspect-ratio solar-powered UAVs,and aerial takeoff of fixed-wing drones in Mars research.However,the significant morphological changes during deployment are accompanied by strong nonlinear dynamic aerodynamic forces,which result in multiple degrees of freedom and an unstable character.This hinders the description and analysis of unknown dynamic behaviors,further leading to difficulties in the design of deployment strategies and flight control.To address this issue,this paper proposes an analysis method for dynamic behaviors during aerial deployment based on the Variational Autoencoder(VAE).Focusing on the gravity-only deployment problem of highaspect-ratio foldable-wing UAVs,the method encodes the multi-degree-of-freedom unstable motion signals into a low-dimensional feature space through a data-driven approach.By clustering in the feature space,this paper identifies and studies several dynamic behaviors during aerial deployment.The research presented in this paper offers a new method and perspective for feature extraction and analysis of complex and difficult-to-describe extreme flight dynamics,guiding the research on aerial deployment drones design and control strategies.
基金supported by the National Science Foundation of China under the Grant Nos.12127806 and 62175195the International Joint Research Laboratory for Micro/Nano Manufacturing and Measurement Technologies。
文摘High-density interconnect(HDI)soft electronics that can integrate multiple individual functions into one miniaturized monolithic system is promising for applications related to smart healthcare,soft robotics,and human-machine interactions.However,despite the recent advances,the development of three-dimensional(3D)soft electronics with both high resolution and high integration is still challenging because of the lack of efficient manufacturing methods to guarantee interlayer alignment of the high-density vias and reliable interlayer electrical conductivity.Here,an advanced 3D laser printing pathway,based on femtosecond laser direct writing(FLDW),is demonstrated for preparing liquid metal(LM)-based any layer HDI soft electronics.FLDW technology,with the characteristics of high spatial resolution and high precision,allows the maskless fabrication of high-resolution embedded LM microchannels and high-density vertical interconnect accesses for 3D integrated circuits.High-aspect-ratio blind/through LM microstructures are formed inside the elastomer due to the supermetalphobicity induced during laser ablation.The LM-based HDI circuit featuring high resolution(~1.5μm)and high integration(10-layer electrical interconnection)is achieved for customized soft electronics,including various customized multilayer passive electric components,soft multilayer circuit,and cross-scale multimode sensors.The 3D laser printing method provides a versatile approach for developing chip-level soft electronics.
基金support of the Natural Science Foundation of Jiangsu Province,China(BK20240977)the China Scholarship Council(201606850024)+1 种基金the National High Technology Research and Development Program of China(2016YFD0701003)the Postgraduate Research&Practice Innovation Program of Jiangsu Province,China(SJCX23_1488)。
文摘Deep learning-based intelligent recognition algorithms are increasingly recognized for their potential to address the labor-intensive challenge of manual pest detection.However,their deployment on mobile devices has been constrained by high computational demands.Here,we developed GBiDC-PEST,a mobile application that incorporates an improved,lightweight detection algorithm based on the You Only Look Once(YOLO)series singlestage architecture,for real-time detection of four tiny pests(wheat mites,sugarcane aphids,wheat aphids,and rice planthoppers).GBiDC-PEST incorporates several innovative modules,including GhostNet for lightweight feature extraction and architecture optimization by reconstructing the backbone,the bi-directional feature pyramid network(BiFPN)for enhanced multiscale feature fusion,depthwise convolution(DWConv)layers to reduce computational load,and the convolutional block attention module(CBAM)to enable precise feature focus.The newly developed GBiDC-PEST was trained and validated using a multitarget agricultural tiny pest dataset(Tpest-3960)that covered various field environments.GBiDC-PEST(2.8 MB)significantly reduced the model size to only 20%of the original model size,offering a smaller size than the YOLO series(v5-v10),higher detection accuracy than YOLOv10n and v10s,and faster detection speed than v8s,v9c,v10m and v10b.In Android deployment experiments,GBiDCPEST demonstrated enhanced performance in detecting pests against complex backgrounds,and the accuracy for wheat mites and rice planthoppers was improved by 4.5-7.5%compared with the original model.The GBiDC-PEST optimization algorithm and its mobile deployment proposed in this study offer a robust technical framework for the rapid,onsite identification and localization of tiny pests.This advancement provides valuable insights for effective pest monitoring,counting,and control in various agricultural settings.
文摘In the context of security systems,adequate signal coverage is paramount for the communication between security personnel and the accurate positioning of personnel.Most studies focus on optimizing base station deployment under the assumption of static obstacles,aiming to maximize the perception coverage of wireless RF(Radio Frequency)signals and reduce positioning blind spots.However,in practical security systems,obstacles are subject to change,necessitating the consideration of base station deployment in dynamic environments.Nevertheless,research in this area still needs to be conducted.This paper proposes a Dynamic Indoor Environment Beacon Deployment Algorithm(DIE-BDA)to address this problem.This algorithm considers the dynamic alterations in obstacle locations within the designated area.It determines the requisite number of base stations,the requisite time,and the area’s practical and overall signal coverage rates.The experimental results demonstrate that the algorithm can calculate the deployment strategy in 0.12 s following a change in obstacle positions.Experimental results show that the algorithm in this paper requires 0.12 s to compute the deployment strategy after the positions of obstacles change.With 13 base stations,it achieves an effective coverage rate of 93.5%and an overall coverage rate of 97.75%.The algorithm can rapidly compute a revised deployment strategy in response to changes in obstacle positions within security systems,thereby ensuring the efficacy of signal coverage.
基金supported in part by the National Natural Science Foundation of China under Grant No.62271453in part by the National Natural Science Foundation of China No.62101512+2 种基金in part by the Central Support for Local Projects under Grant No.YDZJSX2024D031in part by Project supported by the Shanxi Provincial Foundation for Leaders of Disciplines in Science,China under Grant No.2024Q022in part by Shanxi Province Patent Conversion Special Plan Funding Projects under Grant No.202405004。
文摘In the deployment of wireless networks in two-dimensional outdoor campus spaces,aiming at the problem of efficient coverage of the monitoring area by limited number of access points(APs),this paper proposes a deployment method of multi-objective optimization with virtual force fusion bat algorithm(VFBA)using the classical four-node regular distribution as an entry point.The introduction of Lévy flight strategy for bat position updating helps to maintain the population diversity,reduce the premature maturity problem caused by population convergence,avoid the over aggregation of individuals in the local optimal region,and enhance the superiority in global search;the virtual force algorithm simulates the attraction and repulsion between individuals,which enables individual bats to precisely locate the optimal solution within the search space.At the same time,the fusion effect of virtual force prompts the bat individuals to move faster to the potential optimal solution.To validate the effectiveness of the fusion algorithm,the benchmark test function is selected for simulation testing.Finally,the simulation result verifies that the VFBA achieves superior coverage and effectively reduces node redundancy compared to the other three regular layout methods.The VFBA also shows better coverage results when compared to other optimization algorithms.
基金supported by the National Key Research and Development Project(2023YFA1609100)the NSFC Funding(U2141207,52171111,52001083)+6 种基金Natural Science Foundation of Heilongjiang(YQ2023E026)China Postdoctoral Science foundation(2024M754149)Postdoctoral Fellowship Program of CPSF(GZC20242192)support from the National Science Foundation(DMR-1611180 and 1809640)with the program directors,DrsHKU Seed Fund for Collaborative Research(#2207101618)support by Croucher Senior Research Fellowship and City U Project(Project No.9229019)Shenzhen Science and Technology Program(Project No.JCYJ20220818101203007)。
文摘Dislocation strengthening,as one of the methods to simultaneously enhance the room temperature strength and ductility of alloys,does not achieve the desired strengthening and plasticity effect during elevated-temperature deformation.Here,we report a novel strategy to boost the dislocation multiplication and accumulation during deformation at elevated temperatures through dynamic strain aging(DSA).With the introduction of the rare-earth element Ho in Mg-Y-Zn alloy,Ho atoms diffuse toward dislocations during deformation at elevated temperatures,provoking the DSA effect,which increases the dislocation density significantly via the interactions of mobile dislocations and Ho atoms.The resulting alloy achieves a great enhancement of dislocation hardening and obtains the dual benefits of high strength and good ductility simultaneously at high homologous temperatures.The present work provides an effective strategy to enhancing the strength and ductility for elevated-temperature materials.
基金supported by the Helmholtz Association within the framework of the innovation platform“Solar TAP”[Az:714-62150-3/1(2023)]co-funded by the European Union(ERC,C2C-PV,project number 101088359)。
文摘This study investigates the disparities in the deployment of photovoltaic(PV)technology for carbon emissions reduction across different nations,highlighting the mismatch between countries with high economic capacity and those where PV installation would maximize global decarbonization benefits.This mismatch is discussed based on three key factors influencing decarbonization via PV technology:per capita gross domestic product;carbon intensity of the energy system;and solar resource availability.Current PV deployment is predominantly concentrated in economically advanced countries,and does not coincide with regions where the environmental and economic impact of such installations would be most significant.Through a series of thought experiments,it is demonstrated how alternative prioritization strategies could significantly reduce global carbon emissions.Argument is put forward for a globally coordinated approach to PV deployment,particularly targeting high-impact sunbelt regions,to enhance the efficacy of decarbonization efforts and promote equitable energy access.The study underscores the need for international policies that support sustainable energy transitions in economically less developed regions through workforce development and assistance with the activation of capital.
基金supported by the National Natural Science Foundation of China under Grant 62471493 and 62402257partially supported by the Natural Science Foundation of Shandong Province under Grant ZR2023LZH017,ZR2024MF066 and 2023QF025+2 种基金partially supported by the Open Research Subject of State Key Laboratory of Intelligent Game(No.ZBKF-24-12)partially supported by the Foundation of Key Laboratory of Education Informatization for Nationalities(Yunnan Normal University),the Ministry of Education(No.EIN2024C006)partially supported by the Key Laboratory of Ethnic Language Intelligent Analysis and Security Governance of MOE(No.202306).
文摘As Internet ofThings(IoT)technologies continue to evolve at an unprecedented pace,intelligent big data control and information systems have become critical enablers for organizational digital transformation,facilitating data-driven decision making,fostering innovation ecosystems,and maintaining operational stability.In this study,we propose an advanced deployment algorithm for Service Function Chaining(SFC)that leverages an enhanced Practical Byzantine Fault Tolerance(PBFT)mechanism.The main goal is to tackle the issues of security and resource efficiency in SFC implementation across diverse network settings.By integrating blockchain technology and Deep Reinforcement Learning(DRL),our algorithm not only optimizes resource utilization and quality of service but also ensures robust security during SFC deployment.Specifically,the enhanced PBFT consensus mechanism(VRPBFT)significantly reduces consensus latency and improves Byzantine node detection through the introduction of a Verifiable Random Function(VRF)and a node reputation grading model.Experimental results demonstrate that compared to traditional PBFT,the proposed VRPBFT algorithm reduces consensus latency by approximately 30%and decreases the proportion of Byzantine nodes by 40%after 100 rounds of consensus.Furthermore,the DRL-based SFC deployment algorithm(SDRL)exhibits rapid convergence during training,with improvements in long-term average revenue,request acceptance rate,and revenue/cost ratio of 17%,14.49%,and 20.35%,respectively,over existing algorithms.Additionally,the CPU resource utilization of the SDRL algorithmreaches up to 42%,which is 27.96%higher than other algorithms.These findings indicate that the proposed algorithm substantially enhances resource utilization efficiency,service quality,and security in SFC deployment.
基金The National Key R&D Program of China(2021ZD0201300)the National Natural Science Foundation of China(624B2058,U1913602 and 61936004)+1 种基金the Innovation Group Project of the National Natural Science Foundation of China(61821003)the 111 Project on Computational Intelligence and Intelligent Control(B18024).
文摘For large-scale heterogeneous multi-agent systems(MASs)with characteristics of dense-sparse mixed distribution,this paper investigates the practical finite-time deployment problem by establishing a novel crossspecies bionic analytical framework based on the partial differential equation-ordinary differential equation(PDE-ODE)approach.Specifically,by designing a specialized network communication protocol and employing the spatial continuum method for densely distributed agents,this paper models the tracking errors of densely distributed agents as a PDE equivalent to a human disease transmission model,and that of sparsely distributed agents as several ODEs equivalent to the predator population models.The coupling relationship between the PDE and ODE models is established through boundary conditions of the PDE,thereby forming a PDE-ODE-based tracking error model for the considered MASs.Furthermore,by integrating adaptive neural control scheme with the aforementioned biological models,a“Flexible Neural Network”endowed with adaptive and self-stabilized capabilities is constructed,which acts upon the considered MASs,enabling their practical finite-time deployment.Finally,effectiveness of the developed approach is illustrated through a numerical example.
基金supported by National Natural Science Foundation of China(No.61862038)Lanzhou Talent Innovation and Entrepreneurship Technology Plan Project(No.2019-RC-14).
文摘Aiming at node deployment in the monitoring area of the field observation instrument network in the cold and arid regions,we propose a virtual force algorithm based on Voronoi diagram(VFAVD),which adopts probabilistic sensing model that is more in line with the actual situation.First,the Voronoi diagram is constructed in the monitoring area to determine the Thiessen polygon of each node.Then,the virtual force on each node is calculated,and the node update its position according to the direction and size of the total force,so as to achieve the purpose of improving the network coverage rate.The simulation results show that the proposed algorithm can effectively improve the coverage rate of the network,and also has a good effect on the coverage uniformity.
基金supported by the National Natural Science Foundation of China under Grant Nos.U21A20464,62066005Innovation Project of Guangxi Graduate Education under Grant No.YCSW2024313.
文摘Wireless sensor network deployment optimization is a classic NP-hard problem and a popular topic in academic research.However,the current research on wireless sensor network deployment problems uses overly simplistic models,and there is a significant gap between the research results and actual wireless sensor networks.Some scholars have now modeled data fusion networks to make them more suitable for practical applications.This paper will explore the deployment problem of a stochastic data fusion wireless sensor network(SDFWSN),a model that reflects the randomness of environmental monitoring and uses data fusion techniques widely used in actual sensor networks for information collection.The deployment problem of SDFWSN is modeled as a multi-objective optimization problem.The network life cycle,spatiotemporal coverage,detection rate,and false alarm rate of SDFWSN are used as optimization objectives to optimize the deployment of network nodes.This paper proposes an enhanced multi-objective mongoose optimization algorithm(EMODMOA)to solve the deployment problem of SDFWSN.First,to overcome the shortcomings of the DMOA algorithm,such as its low convergence and tendency to get stuck in a local optimum,an encircling and hunting strategy is introduced into the original algorithm to propose the EDMOA algorithm.The EDMOA algorithm is designed as the EMODMOA algorithm by selecting reference points using the K-Nearest Neighbor(KNN)algorithm.To verify the effectiveness of the proposed algorithm,the EMODMOA algorithm was tested at CEC 2020 and achieved good results.In the SDFWSN deployment problem,the algorithm was compared with the Non-dominated Sorting Genetic Algorithm II(NSGAII),Multiple Objective Particle Swarm Optimization(MOPSO),Multi-Objective Evolutionary Algorithm based on Decomposition(MOEA/D),and Multi-Objective Grey Wolf Optimizer(MOGWO).By comparing and analyzing the performance evaluation metrics and optimization results of the objective functions of the multi-objective algorithms,the algorithm outperforms the other algorithms in the SDFWSN deployment results.To better demonstrate the superiority of the algorithm,simulations of diverse test cases were also performed,and good results were obtained.
基金supported by the National Natural Science Foundation of China(72072047)the Fundamental Research Funds for the Central Universities(HIT.HSS.ESD202310)+3 种基金the Research Project on Graduates’Education and Teaching Reform of HIT(23MS011)the research Project on Higher Education of Heilongjiang Higher Education Association(23GJYBC011)the Natural Science Foundation of Shandong Province(ZR2023QG010)the Shandong Philosophy and Social Science Research Project(22CSDJ03).
文摘Resource management must attach importance to effective resource deployment.Aiming at the research of resource deployment system,firstly,as an important factor of resource deployment system,corporate technological innovation social responsibility(CISR)is analyzed.Based on this,this paper constructs a system dynamics model to analyze the changes in resource deployment system affected by CISR.The simulation model is developed using Venism personal learning edition(PLE).The results show that CISR,acted as a new factor affecting the resource deployment system,has a positive effect on resource deployment system performance.Moreover,when CISR exceeds the threshold value,the resource deployment system performance increases significantly faster,reflecting that the resource deployment system becomes more efficient.The results show that the method proposed in this paper is feasible and efficient.This research provides theoretical and practical implications for resource deployment system research.
基金funded by the Scientific and Technological Key Program of Guizhou Province, China (Qiankehezhicheng [2022] Key 031)the National Natural Science Foundation of China (32160483 and 32360497)+2 种基金the Post-Funded Project for the National Natural Science Foundation of China from Guizhou University ([2023]093)the Key Laboratory of Molecular Breeding for Grain and Oil Crops in Guizhou Province, China (Qiankehezhongyindi [2023]008)the Key Laboratory of Functional Agriculture of Guizhou Provincial Higher Education Institutions, China (Qianjiaoji [2023] 007)。
文摘Rapeseed mustard(Brassica juncea L.) is the third most important oilseed crop in the world, but the geneticmechanism underlying its massive phenotypic variation remains largely unexplored. In this study, specific length amplified fragment sequencing(SLAF-Seq) was used to resequence a population comprising 197 F8recombinantinbred lines(RILs) derived from a cross between vegetable-type Qichi881 and oilseed-type YufengZC of B. juncea. In total, 438,895 high-quality SLAFs were discovered, 47,644 of which were polymorphic, and 3,887 of the polymorphic markers met the requirements for genetic map construction. The final map included 3,887 markers on 18 linkage groups and was 1,830.23 centiMorgan(cM) in length, with an average distance of 0.47 cM between adjacent markers. Using the newly constructed high-density genetic map, a total of 53 QTLs for erucicacid(EA), oleic acid(OA), and linolenic acid(LNA) were detected and integrated into eight consensus QTLswith two for each of these traits. For each of these three traits, two candidate genes were cloned and sequence analysis indicated colocalization with their respective consensus QTLs. The co-dominant allele-specific markers for Bju.FAD3.A03 and Bju.FAD3.B07 were developed and showed co-localization with their consensus QTLs andco-segregation with LNA content, further supporting the results of QTL mapping and bioinformatic analysis. Theexpression levels of the cloned homologous genes were also determined, and the genes were tightly correlatedwith the EA, OA and LNA contents of different lines. The results of this study will facilitate the improvement offatty acid traits and molecular breeding of B. juncea. Further uses of the high-density genetic map created in this study are also discussed.
基金supported by the National Natural Science Foundation of China(72061006)the research on the auxiliary diagnosis system of chronic injury of levator scapulae based on the concept of digital twin(Contract No:Qian Kehe Support[2023]General 117)Research on indoor intelligent assisted walking robot for the rehabilitation of walking ability of the elderly(Contract No:Qian kehe Support[2023]General 124).
文摘Stroke survivors often face significant challenges when performing daily self-care activities due to upper limb motor impairments.Traditional surface electromyography(sEMG)analysis typically focuses on isolated hand postures,overlooking the complexity of object-interactive behaviors that are crucial for promoting patient independence.This study introduces a novel framework that combines high-density sEMG(HD-sEMG)signals with an improved Whale Optimization Algorithm(IWOA)-optimized Long Short-Term Memory(LSTM)network to address this limitation.The key contributions of this work include:(1)the creation of a specialized HD-sEMG dataset that captures nine continuous self-care behaviors,along with time and posture markers,to better reflect real-world patient interactions;(2)the development of a multi-channel feature fusion module based on Pascal’s theorem,which enables efficient signal segmentation and spatial–temporal feature extraction;and(3)the enhancement of the IWOA algorithm,which integrates optimal point set initialization,a diversity-driven pooling mechanism,and cosine-based differential evolution to optimize LSTM hyperparameters,thereby improving convergence and global search capabilities.Experimental results demonstrate superior performance,achieving 99.58%accuracy in self-care behavior recognition and 86.19%accuracy for 17 continuous gestures on the Ninapro db2 benchmark.The framework operates with low latency,meeting the real-time requirements for assistive devices.By enabling precise,context-aware recognition of daily activities,this work advances personalized rehabilitation technologies,empowering stroke patients to regain autonomy in self-care tasks.The proposed methodology offers a robust,scalable solution for clinical applications,bridging the gap between laboratory-based gesture recognition and practical,patient-centered care.
