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Strategies of allocating root-shoot biomass in plantations and natural forests at various community stages and moisture levels 认领 引用
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作者 Wenjing Chen Lei Liu +3 位作者 Josep Penuelas Guoyi Zhou Langqin Hua Zhurong Wu 《Journal of Forestry Research》 SCIE EI CAS CSCD 2026年第2期85-99,共15页
The root-to-shoot(R/S)ratio is a critical indicator of the balance between root biomass and shoot biomass,representing the ecological strategies and adaptive responses of plants to environmental conditions.However,the... The root-to-shoot(R/S)ratio is a critical indicator of the balance between root biomass and shoot biomass,representing the ecological strategies and adaptive responses of plants to environmental conditions.However,the patterns of change in community R/S ratios during forest succession and their response to moisture levels across broad geographic gradients remains unclear.Based on forest biomass data from a national field inventory of 5,825 plots conducted across China between 2011 and 2015,this study looked into allocating biomass shoots and roots at the early,middle,and late stages of growth in plantations and succession in natural forests,and evaluated how moisture availability influences this allocation.The results revealed a significant decline in R/S ratios from early to late stages for both plantations and natural forests.Shoot and root biomass in plantations grew isometrically during the early and middle succession stages but shifted to allometric growth in the late stage,with the slope of the log-transformed shoot-root biomass relationship differing significantly across growth stages.Natural forests,in contrast,maintained isometric growth across successional stages,showing no significant variation in the slope of the log-transformed shoot-root biomass relationship.Environmental factors,particularly moisture levels,strongly influenced R/S ratios.Moisture levels significantly affected size-corrected R/S ratios,particularly in the middle stage of plantations and the early and middle stages of natural forests,supporting the hypothesis of optimal allocation.These findings suggest that in water-limited regions,forest management should prioritize drought-tolerant,deep-rooted native species,encourage mixed-species planting in the early stage,and reduce logging intensity in mature plantations.Conserving natural forests to maintain successional dynamics is essential for long-term ecological resilience.These findings emphasize the importance of balancing productivity with ecological sustainability by adapting practices to specific environments and forest types under climate change. 展开更多
关键词 Root-to-shoot ratios Biomass allocation Forest type Community stage Moisture levels Allometric scaling
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Zoning Search With Adaptive Resource Allocating Method for Balanced and Imbalanced Multimodal Multi-Objective Optimization 认领 引用 被引量：7
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作者 Qinqin Fan Okan K.Ersoy 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2021年第6期1163-1176,共14页
Maintaining population diversity is an important task in the multimodal multi-objective optimization.Although the zoning search(ZS)can improve the diversity in the decision space,assigning the same computational costs... Maintaining population diversity is an important task in the multimodal multi-objective optimization.Although the zoning search(ZS)can improve the diversity in the decision space,assigning the same computational costs to each search subspace may be wasteful when computational resources are limited,especially on imbalanced problems.To alleviate the above-mentioned issue,a zoning search with adaptive resource allocating(ZS-ARA)method is proposed in the current study.In the proposed ZS-ARA,the entire search space is divided into many subspaces to preserve the diversity in the decision space and to reduce the problem complexity.Moreover,the computational resources can be automatically allocated among all the subspaces.The ZS-ARA is compared with seven algorithms on two different types of multimodal multi-objective problems(MMOPs),namely,balanced and imbalanced MMOPs.The results indicate that,similarly to the ZS,the ZS-ARA achieves high performance with the balanced MMOPs.Also,it can greatly assist a“regular”algorithm in improving its performance on the imbalanced MMOPs,and is capable of allocating the limited computational resources dynamically. 展开更多
关键词 Computational resource allocation decision space decomposition evolutionary computation multimodal multi-objective optimization
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An Online Malicious Spam Email Detection System Using Resource Allocating Network with Locality Sensitive Hashing 认领 引用 被引量：2
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作者 Siti-Hajar-Aminah Ali Seiichi Ozawa +2 位作者 Junji Nakazato Tao Ban Jumpei Shimamura 《Journal of Intelligent Learning Systems and Applications》 2015年第2期42-57,共16页
In this paper, we propose a new online system that can quickly detect malicious spam emails and adapt to the changes in the email contents and the Uniform Resource Locator (URL) links leading to malicious websites by ... In this paper, we propose a new online system that can quickly detect malicious spam emails and adapt to the changes in the email contents and the Uniform Resource Locator (URL) links leading to malicious websites by updating the system daily. We introduce an autonomous function for a server to generate training examples, in which double-bounce emails are automatically collected and their class labels are given by a crawler-type software to analyze the website maliciousness called SPIKE. In general, since spammers use botnets to spread numerous malicious emails within a short time, such distributed spam emails often have the same or similar contents. Therefore, it is not necessary for all spam emails to be learned. To adapt to new malicious campaigns quickly, only new types of spam emails should be selected for learning and this can be realized by introducing an active learning scheme into a classifier model. For this purpose, we adopt Resource Allocating Network with Locality Sensitive Hashing (RAN-LSH) as a classifier model with a data selection function. In RAN-LSH, the same or similar spam emails that have already been learned are quickly searched for a hash table in Locally Sensitive Hashing (LSH), in which the matched similar emails located in “well-learned” are discarded without being used as training data. To analyze email contents, we adopt the Bag of Words (BoW) approach and generate feature vectors whose attributes are transformed based on the normalized term frequency-inverse document frequency (TF-IDF). We use a data set of double-bounce spam emails collected at National Institute of Information and Communications Technology (NICT) in Japan from March 1st, 2013 until May 10th, 2013 to evaluate the performance of the proposed system. The results confirm that the proposed spam email detection system has capability of detecting with high detection rate. 展开更多
关键词 Malicious Spam Email Detection System Incremental Learning Resource Allocating Network Locality Sensitive Hashing
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Fitness Sharing Chaotic Particle Swarm Optimization (FSCPSO): A Metaheuristic Approach for Allocating Dynamic Virtual Machine (VM) in Fog Computing Architecture 认领 引用 被引量：1
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作者 Prasanna Kumar Kannughatta Ranganna Siddesh Gaddadevara Matt +2 位作者 Chin-Ling Chen Ananda Babu Jayachandra Yong-Yuan Deng 《Computers, Materials & Continua》 SCIE EI 2024年第8期2557-2578,共22页
In recent decades,fog computing has played a vital role in executing parallel computational tasks,specifically,scientific workflow tasks.In cloud data centers,fog computing takes more time to run workflow applications... In recent decades,fog computing has played a vital role in executing parallel computational tasks,specifically,scientific workflow tasks.In cloud data centers,fog computing takes more time to run workflow applications.Therefore,it is essential to develop effective models for Virtual Machine(VM)allocation and task scheduling in fog computing environments.Effective task scheduling,VM migration,and allocation,altogether optimize the use of computational resources across different fog nodes.This process ensures that the tasks are executed with minimal energy consumption,which reduces the chances of resource bottlenecks.In this manuscript,the proposed framework comprises two phases:(i)effective task scheduling using a fractional selectivity approach and(ii)VM allocation by proposing an algorithm by the name of Fitness Sharing Chaotic Particle Swarm Optimization(FSCPSO).The proposed FSCPSO algorithm integrates the concepts of chaos theory and fitness sharing that effectively balance both global exploration and local exploitation.This balance enables the use of a wide range of solutions that leads to minimal total cost and makespan,in comparison to other traditional optimization algorithms.The FSCPSO algorithm’s performance is analyzed using six evaluation measures namely,Load Balancing Level(LBL),Average Resource Utilization(ARU),total cost,makespan,energy consumption,and response time.In relation to the conventional optimization algorithms,the FSCPSO algorithm achieves a higher LBL of 39.12%,ARU of 58.15%,a minimal total cost of 1175,and a makespan of 85.87 ms,particularly when evaluated for 50 tasks. 展开更多
关键词 Fog computing fractional selectivity approach particle swarm optimization algorithm task scheduling virtual machine allocation
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A Mathematical Model of Global Equity for Allocating Asteroid Resources Based on Analytic Hierarchy Process 认领 引用
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作者 Shuyang Qian 《American Journal of Computational Mathematics》 2022年第4期372-380,共9页
As the Earth’s resources are utilized, we are increasingly seeking access to space-based resources. One of the most promising solutions to the problem of resource scarcity is asteroid mining. However, it brings with ... As the Earth’s resources are utilized, we are increasingly seeking access to space-based resources. One of the most promising solutions to the problem of resource scarcity is asteroid mining. However, it brings with it the problem of resource allocation. Because of the different levels of development of countries, the way of equal distribution is not reasonable. In this paper, we firstly elaborate and define the abstract global equity in a concrete way, linking global equity with comprehensive national strength, and build a new global equity model on this basis. In this way, we can apply the established model to the distribution of space-based resources or other resources. This paper first establishes the corresponding relation between global equity and comprehensive national power, and then determines several important indexes affecting comprehensive national power according to Klein equation. Further, this paper selected four representative large countries and determined the data of each country in each important index by consulting relevant materials. On this basis, the analytic hierarchy process was used to determine the weight of each country in resource allocation. By comparing the weight index obtained by the model in this paper with the actual resource allocation ratio, we can find that they are in good agreement [1]. Therefore, it can be concluded that when allocating space-based resources or other resources, we can use the global equity model established in this paper to calculate the weight index and allocate resources on this basis to ensure the realization of global equity [2]. 展开更多
关键词 Hierarchical Analysis Global Equity Resource Allocation Mod
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Stubble rolling primes axillary bud regeneration and increases grain yield in mechanically harvested ratoon rice in South China 认领 引用 被引量：1
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作者 Jinying Li Bianhong Zhang +12 位作者 Jiahui Song Danyang Li Mengying Chen Zhihan Chen Bin Qin Hailong Xu Jingnan Zou Peiying Weng Wenfei Wang Changxun Fang Hongfei Chen Zhixing Zhang Wenxiong Lin 《The Crop Journal》 SCIE CSCD 2026年第4期1410-1419,共10页
Rice ratooning produces a second harvest from the growth of axillary buds that remain on the stubble after the main crop is harvested.Stubble rolling after mechanical harvesting may regenerate roots and tillers.The ob... Rice ratooning produces a second harvest from the growth of axillary buds that remain on the stubble after the main crop is harvested.Stubble rolling after mechanical harvesting may regenerate roots and tillers.The objective of this study was to elucidate the relationships between axillary bud regeneration and yield formation in ratoon rice.The experimental approach was to measure yield and axillary bud regeneration traits under full-rolling and non-rolling treatments across three sites in Fujian Province,China over two years.Full-rolling increased grain yield by 7.59%-8.40% and the regeneration capacity of axillary buds by 9.45%-17.11%.Further analyses revealed that full-rolling increased the activities of carbon-and nitrogen-metabolizing enzymes in regenerating axillary buds,as well as the expression of genes involved in carbohydrate and nitrogen metabolic pathways.Mechanical harvesting combined with stubble rolling that presses rice stubble close to the soil surface induces a regenerative growth pattern that ultimately increases ratoon rice yield. 展开更多
关键词 Ratoon rice Full-rolling and non-rolling treatments Regenerating axillary buds Carbon and nitrogen allocation in ratooning plants
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Joint multi-dimensional resource scheduling for cooperative tracking of multiple LEO targets via space-based radar networks 认领 引用 被引量：1
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作者 Qingwei YANG Libing JIANG +2 位作者 Shuyu ZHENG Yingjian ZHAO Zhuang WANG 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第4期449-466,共18页
Appropriate resource scheduling is the key to achieving the best performance of Low Earth-Orbit(LEO)Multi-Target Tracking(MTT)for the Space-based Radar Networks(SBRN)system.The high-velocity nature of satellites impos... Appropriate resource scheduling is the key to achieving the best performance of Low Earth-Orbit(LEO)Multi-Target Tracking(MTT)for the Space-based Radar Networks(SBRN)system.The high-velocity nature of satellites imposes high demands on the convergence rate of filtering and tracking accuracy while escalating the complexity of dynamic scheduling.To address these challenges,this paper utilizes Two-Line Elements(TLE)information to fully exploit the limited power-aperture resource of space-based Colocated Multiple-Input Multiple-Output(C-MIMO)radar and constructs a Walker constellation SBRN system.On this basis,a cognitive distributed cooperative tracking framework with fusion feedback mechanism is proposed.Each node can serve as the fusion center,achieving optimal fusion through the Fast Covariance Intersection(FCI)criterion while reducing the communication requirements.The global outcomes are fed back to all local nodes which can hasten the convergence rate of target state estimation.To maximize the global MTT performance,a closed-loop Joint Multi-Dimensional Resource Scheduling(JMDRS)strategy that considers multi-coverage conditions and visible windows is established.Moreover,the Posterior Cramer-Rao Lower Bound under Global Fusion Feedback(GF-PCRLB)is derived to provide a quantifiable metric for the overall performance.Finally,a fast suboptimal solution to the nonconvex model is proposed based on cross-iterative dimension reduction and variable decoupling.It introduces the tracking Efficiency-to-Cost Ratio(ECR)to jointly decide the beam pointing as well as the transmit power and fusion weight of each beam.Numerical results demonstrate that the proposed method significantly outperforms the existing approaches in enhancing the MTT performance of the SBRN system. 展开更多
关键词 Dynamic resource allocation Moving platform cooperative tracking Multi-Target Tracking(MTT) Space-based Radar Networks(SBRN) Task management
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Research on Vehicle Joint Radar Communication Resource Optimization Method Based on GNN-DRL 认领 引用 被引量：1
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作者 Zeyu Chen Jian Sun +1 位作者 Zhengda Huan Ziyi Zhang 《Computers, Materials & Continua》 SCIE EI 2026年第2期1430-1446,共17页
To address the issues of poor adaptability in resource allocation and low multi-agent cooperation efficiency in Joint Radar and Communication(JRC)systems under dynamic environments,an intelligent optimization framewor... To address the issues of poor adaptability in resource allocation and low multi-agent cooperation efficiency in Joint Radar and Communication(JRC)systems under dynamic environments,an intelligent optimization framework integrating Deep Reinforcement Learning(DRL)and Graph Neural Network(GNN)is proposed.This framework models resource allocation as a Partially Observable Markov Game(POMG),designs a weighted reward function to balance radar and communication efficiencies,adopts the Multi-Agent Proximal Policy Optimization(MAPPO)framework,and integrates Graph Convolutional Networks(GCN)and Graph Sample and Aggregate(Graph-SAGE)to optimize information interaction.Simulations show that,compared with traditional methods and pure DRL methods,the proposed framework achieves improvements in performance metrics such as communication success rate,Average Age of Information(AoI),and policy convergence speed,effectively enabling resource management in complex environments.Moreover,the proposed GNN-DRL-based intelligent optimization framework obtains significantly better performance for resource management in multi-agent JRC systems than traditional methods and pure DRL methods. 展开更多
关键词 Graph neural network joint radar and communication resource allocation multi-agent collaboration
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A brief review of evolutionary game dynamics in the reinforcement learning paradigm 认领 引用
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作者 Guozhong Zheng Xin Ou +2 位作者 Shengfeng Deng Jiqiang Zhang Li Chen 《Communications in Theoretical Physics》 SCIE CAS CSCD 2026年第6期220-232,共13页
Cooperation,fairness,trust,and resource coordination are cornerstones of modern civilization,yet their emergence remains inadequately explained,largely due to persistent discrepancies between theoretical predictions a... Cooperation,fairness,trust,and resource coordination are cornerstones of modern civilization,yet their emergence remains inadequately explained,largely due to persistent discrepancies between theoretical predictions and behavioral experiments.Part of this gap may arise from the imitation learning paradigm commonly used in prior theoretical models,which assumes individuals merely copy successful neighbors according to predetermined,fixed rules.This review examines recent advances in evolutionary game dynamics that employ reinforcement learning(RL)as an alternative paradigm.In RL,individuals learn through trial and error and intro spec tively refine their strategies based on environmental feedback.We begin by introducing key concepts in evolutionary game theory and the two learning paradigms,then synthesize progress in applying RL to elucidate cooperation,trust,fairness,optimal resource coordination,and ecological dynamics.Collectively,these studies indicate that RL offers a promising unified framework for understanding the diverse social and ecological phenomena observed in human and natural systems. 展开更多
关键词 reinforcement learning evolutionary game theory cooperation fairness trust resource allocation biodiversity
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High panicle potassium fertilizer application mitigates heat-induced yield loss in mid-season rice by optimizing source-sink relationships and promoting transpirational cooling 认领 引用
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作者 Keran Xie Ti Gao +6 位作者 Qiuqian Hu Chao Wu Dongliang Xiong Zhenmei Wang Jianliang Huang Shaobing Peng Kehui Cui 《The Crop Journal》 SCIE CSCD 2026年第4期1420-1431,共12页
Extremely high temperatures(HT)caused by global warming pose serious threats to rice production.Potassium(K)is critical for plant stress tolerance,but its role in mitigating heat damage remains unclear.This study aime... Extremely high temperatures(HT)caused by global warming pose serious threats to rice production.Potassium(K)is critical for plant stress tolerance,but its role in mitigating heat damage remains unclear.This study aimed to elucidate how high panicle K application affects mid-season rice HT tolerance in central China.A two-year field experiment grew two rice cultivars(heat-resistant Shanyou 63,SY63;heatsensitive Liangyoupeijiu,LYPJ)under varying sowing dates and two K application levels(low K,LK,50 kg K ha-1;high K,HK,90 kg K ha-1)at the panicle initiation stage.Sowing date l(S1)and sowing date 2(S2)increased the risk of heat stress exposure.Compared with late sowing(S3)under LK,early sowing reduced the yield in LYPJ by 41,3%(S1)and 51.3%(S2)in 2022,and by 35.4%(S2)in 2023,but did not affect the yield in SY63.Compared with LK in the same sowing date,HK increased yield by 44.7%(S1)and 61.5%(S2)in LYPJ in 2022,and by 30.6%(S2)in 2023,whereas it showed no significant effect on SY63 yield.Structural equation modeling analysis indicated that the yield loss could be primarily attributed to heat intensity at the panicle initiation and maturity stages.HK increased stomatal conductance and improved leaf water potential,thereby reducing canopy temperature by 1,2-1.3℃at heading and 1.1-2.5℃at maturity.Concurrently,HK enhanced carbohydrate supply and elevated enzyme activity for sugars utilization in anthers,collectively enhancing pollen viability and spikelet fertility.HK optimized source-sink traits via increasing leaf area index,specific leaf weight,spikelets per unit leaf area,post-anthesis translocation of stem dry matter(47.5%-48.9% in 2022 and 24.0% in 2023),and postanthesis dry matter accumulation(33.0%-38.2% in 2022 and 19.0% in 2023).The study indicates that early sowing increases the risk of heat stress exposure for mid-season rice in central China,and the increase of panicle K application can mitigate yield loss by lessening canopy temperature and optimizing source-sink relationships. 展开更多
关键词 High temperature Potassium Rice spikelet fertility Canopy temperature Assimilate allocation
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An allocation strategy integrated power,bandwidth,and subchannel in a RCC network 认领 引用
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作者 Haowei Zhang Weijian Liu +4 位作者 Lin Zhang Youwei Meng Weihang Han Tao Song Rennong Yang 《Defence Technology（防务技术）》 SCIE EI CAS CSCD 2026年第6期138-154,共17页
Owing to the portability,cheapness and flexible deployment,the unmanned aerial vehicle-based radar and communication coexistence(RCC)systems are widely adopted in Internet of Things applications.A joint power,bandwidt... Owing to the portability,cheapness and flexible deployment,the unmanned aerial vehicle-based radar and communication coexistence(RCC)systems are widely adopted in Internet of Things applications.A joint power,bandwidth,and subchannel allocation(JPBSA)strategy is proposed for a RCC network,aiming to optimize resource utilization under mutual spectrum interference.The Cram er-Rao lower bound(CRLB)is employed to assess the target localization accuracy.The optimization model is formulated as minimizing the sum of weighted predicted CRLBs while satisfying the communication data rate requirements and constraints of power and bandwidth budget.It is shown that the JPBSA problem falls into the mixed-integer programming problem.Even worse,the three variables are coherent in the objective function and constraints.A four-phase alternating optimization framework(FPAOF)is developed to address this issue.The FPAOF incorporates the joint convexification of radar and communication power allocation via Taylor approximation,bandwidth upper bound adaptation,and the opportunistic spectrum access-based method for subchannel allocation.Numerical evaluations demonstrate the proposed strategy's superiority in terms of localization accuracy improvement and computational tractability in comparison to state-of-the-art methods.The findings also indicate the superiority of using CRLB as the optimization metric than the signal-to-interference-plus-noise and mutual information. 展开更多
关键词 JRC system Resource allocation Convex optimization
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Joint resource and trajectory optimization in a UAV-enabled dual-function radar-communication network 认领 引用
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作者 Haowei Zhang Weijian Liu +3 位作者 Lin Zhang Youwei Meng Tao Song HeXiu Xu 《Defence Technology（防务技术）》 SCIE EI CAS CSCD 2026年第6期30-49,共20页
The resource and trajectory optimization problem is critical in joint radar and communication systems,as it mitigates spectrum interference and enhances resource utilization.This paper proposes a joint power and subch... The resource and trajectory optimization problem is critical in joint radar and communication systems,as it mitigates spectrum interference and enhances resource utilization.This paper proposes a joint power and subchannel allocation with trajectory optimization(JPSATO)strategy for a dual-function radar-communication network that tracks multiple targets while serving multiple users.The predicted-conditional Cram er-Rao lower bound(PC-CRLB)in the clutter domain is derived as the tracking performance metric,quantifying the accuracy loss caused by clutter.The optimization model is formulated as minimizing the sum of weighted PC-CRLBs of multiple targets while adhering to the communication data ratio constraint of each user.It is shown that the continuous power allocation,trajectory optimization,and binary subchannel allocation variables are all coupled in the objective function and constraints,resulting in a mixed integer programming problem.In addition,an information reduction factor is embedded in the PC-CRLB to express the clutter effects,and it destroys the convexity of objective function with respect to the power allocation.A four-layer alternating optimization-based method(FLAOM)is designed for this problem-solving.The radar power allocation and communication power allocation are solved using the sequential optimization method,where the nonconvex sub-problem is transformed into a near convex one in each iteration using the first-order Taylor expansion.Then,the subchannel allocation is solved using a greedy search idea.Finally,the trajectory is optimized by the reformulation and the sequential optimization method.Simulation results confirm the effectiveness and efficiency of proposed FLAOM compared with the state-of-the-art methods.It is also shown that the trajectory optimization plays important roles in the considered JPSATO problem. 展开更多
关键词 Dual-function radar-communication Unmanned aerial vehicles Resource allocation Nonconvex optimization
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A Wireless Image Semantic Transmission Approach with Joint Spatial-Channel-Power Domain Adaptation 认领 引用
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作者 Liu Jiangtao Liang Zijian +1 位作者 Niu Kai Zhang Ping 《China Communications》 SCIE EI CSCD 2026年第4期37-52,共16页
This paper proposes a novel end-to-end learnable framework for semantic image transmission,pioneering joint optimization across the spatial,channel,and power domains.In this scheme,the transmitter employs semantic ana... This paper proposes a novel end-to-end learnable framework for semantic image transmission,pioneering joint optimization across the spatial,channel,and power domains.In this scheme,the transmitter employs semantic analysis with spatial-channel domain adaptation to extract and compress vital semantic features from image latent representations,enabling efficient compression by integrating spatial structures and retaining channel priority attributes.Subsequently,a dynamic power allocation strategy intelligently adjusts the transmission power of these features based on real-time noise conditions to mitigate channel impairments.At the receiver,a hierarchical reconstruction network subsequently decodes images through cross-feature analysis of semantic relationships from distorted features.Extensive experimental validation under Rayleigh fading channels demonstrates that the proposed framework achieves significantly superior bandwidth utilization and reconstruction quality compared to existing seep joint source channel coding(DJSCC)schemes.It exhibits robust performance across diverse channel conditions and compression ratios,thereby establishing a new benchmark for semantic communications(Sem-Com). 展开更多
关键词 DJSCC image transmission power allocation SemCom spatial-channel compression
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Secure and robust resource allocation for UAV-assisted anti-jamming spectrum sharing under uncertain jamming in airborne maneuvering networks 认领 引用
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作者 Rui DING Haotian QUAN +1 位作者 Zhijie ZENG Fuhui ZHOU 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第5期111-121,共11页
Airborne Maneuvering Network(AMN)has attracted great attention in diverse practical scenarios.Low-altitude maneuvering UAV plays as the operational backbone of AMN to promote the development of an efficient,secure,and... Airborne Maneuvering Network(AMN)has attracted great attention in diverse practical scenarios.Low-altitude maneuvering UAV plays as the operational backbone of AMN to promote the development of an efficient,secure,and low-latency AMN by providing new airborne wireless nerve tracts.However,the widespread adoption of AMNs witnesses a drastic increase of mobile users and data-intensive applications,which makes it suffer from the intense spectrum competition.Spectrum sharing shows promise in alleviating the severe spectrum scarcity of AMNs.Moreover,due to the broadcast nature of wireless channels and the increasing probability of the line-of-sight transmission,the AMN is vulnerable to malicious jamming,especially encountering the coupled uncertainty and dynamic jamming.To solve these problems,UAV-assisted antijamming spectrum sharing in AMNs is investigated.We propose a joint space-power-frequency domain optimization approach to simultaneously mitigate both external malicious jamming and internal sharing interference.The sum rate maximization of the secondary network is studied by jointly optimizing the UAV transmit power,sub-band allocation,and trajectory.To tackle the formulated intractable non-convex problem,we propose a computationally efficient iterative algorithm based on alternating optimization,integrating the S-procedure to handle bounded uncertainties and the successive convex approximation to obtain near-optimal convex solutions.Extensive simulation results show that our proposed scheme can significantly increase the sum transmission rate.Moreover,it is shown that our proposed scheme is the best robust among all benchmark schemes against jammer location and power uncertainties,confirming the practicality for the next-generation UAV based airborne networks. 展开更多
关键词 Airborne maneuvering networks Anti-jamming Resource allocation Spectrum management UAV communication
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A multi-location inventory system with occasional allocation underuncertain defective rates 认领 引用
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作者 Ligang Cui Zuguo Peng +1 位作者 Yingcong Chen Wenjing Xie 《Data Science and Management》 EI CSCD 2026年第1期56-67,共12页
In this study, a multi-location allocation problem is investigated under a temporary allocation system in light ofthe uncertain defective rate inherent to items. Based on the theoretical and modeling foundation of pre... In this study, a multi-location allocation problem is investigated under a temporary allocation system in light ofthe uncertain defective rate inherent to items. Based on the theoretical and modeling foundation of previousresearch, this study contributes in four main aspects. First, a robust optimization model is developed based on thebudget uncertainty of the defective rate of items in a multi-location inventory system. Second, given that thedetermination of uncertainty relies on the subjective judgment of decision-makers with different risk preferences,a pivotal variable method is introduced to approximate the possible thresholds of the uncertain parameter withinthe expected interval. Third, a new evaluation criterion curve, illustrating the cumulative cost differences betweenthe probabilistic and robust models, is employed through large-scale sampling to evaluate the performance of thetwo decision models. Finally, numerical experiments and sensitivity analysis are conducted to verify the performanceof the decision effects under different defective rates and stockout costs, respectively. The resultsconfirm the superior performance of the robust model, as shown through sensitivity analysis under thresholds ofvarying defective rates and stockout costs, and highlight the effectiveness of the proposed cumulative cost differenceevaluation curve. The robust model offers significant cost-control advantages over the probabilistic model,particularly in high-uncertainty scenarios. This study provides a reference method for multi-location inventoryallocation decisions with uncertain defective rates. 展开更多
关键词 Defective rate uncertainty Inventory allocation Uncertainty parameter Criterion
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Amino Acid Transporter OsAAP18 Modulates Nitrogen Allocation to Boost Yield and Grain Quality in Rice 认领 引用
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作者 HE Chongchong YANG Xiaochuan +6 位作者 ZHANG Jie WU Wenhao WANG Chuanbo CHEN Wenbo WU Bowen HUANG Weiting FANG Zhongming 《Rice science》 SCIE CAS CSCD 2026年第2期151-154,I0028-I0040,共4页
Synergistically improving the yield and grain quality of rice remains a major breeding challenge.Amino acid transporters play key roles in regulating plant growth and development,but their mechanisms in synergisticall... Synergistically improving the yield and grain quality of rice remains a major breeding challenge.Amino acid transporters play key roles in regulating plant growth and development,but their mechanisms in synergistically regulating yield and quality remain unclear.Here,we report that the plasma membrane-localized transporter OsAAP18,which is more highly expressed in indica than japonica rice,positively correlates with tiller number and yield but negatively with grain width.OsAAP18 transports eight amino acids,including asparagine(Asn),proline(Pro),leucine(Leu),and valine(Val).Its overexpression increases yield through enhanced tillering and grain number per panicle while also improving rice processing and cooking quality.Transcriptome analysis showed that OsAAP18 coordinates grain development and quality formation by regulating the expression of key genes involved in starch and sucrose metabolism,nitrogen metabolism,and plant hormone signaling pathways.These findings establish OsAAP18 as a dual-function regulator that synergistically enhances yield and quality,offering a promising target for rice breeding. 展开更多
关键词 plasma membrane localized transporter acid transporters nitrogen allocation transports eight amino acidsi OSAAP yield grain quality rice breeding
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A dynamic function allocation method for single pilot operations in commercial aircraft based on Bayesian-enhanced Q-learning 认领 引用
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作者 Yue LUO Yuting DAI +3 位作者 Miao WANG Lei WANG Ruiyuan HONG Guoqing WANG 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2026年第5期411-430,共20页
Human-machine collaboration is a key feature of Single Pilot Operations(SPO).With only a single pilot in the cockpit,workload monitoring and adjustment become even more critical compared to Dual-Pilot Operations(DPO).... Human-machine collaboration is a key feature of Single Pilot Operations(SPO).With only a single pilot in the cockpit,workload monitoring and adjustment become even more critical compared to Dual-Pilot Operations(DPO).Hence,a dynamic function allocation mechanism must be established—increasing the Level of Automation(LOA)under high workload conditions and reducing it under low workload conditions to maintain situational awareness.To address the challenges of excessive subjectivity and limited knowledge transfer in the existing dynamic function allocation methods,this paper proposes a dynamic function allocation method based on Bayesianenhanced Q-Learning(BQL).First,a Bayesian Network(BN)is constructed to predict HumanMachine System(HMS)performance,determining when reallocation should be triggered.Compared to the existing trigger mechanisms,this approach enables earlier activation while maintaining non-intrusive.Then,the BN-predicted HMS performance is integrated into the reward feedback for the reinforcement learning algorithm,allowing the system to continuously refine its strategy through interaction with the environment.Finally,flight experiments conducted in a low-fidelity SPO simulator,incorporating both objective physiological monitoring and subjective assessments,validate the effectiveness of the proposed method. 展开更多
关键词 Bayesian network Dynamic function allocation Human-machine system Reinforcement learning Single Pilot Operations(SPO)
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Heterogeneous resource allocation with latency guarantee for computing power network 认领 引用
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作者 Ailing Zhong Dapeng Wu +1 位作者 Boran Yang Ruyan Wang 《Digital Communications and Networks》 SCIE EI CSCD 2026年第1期25-37,共13页
Computing Power Network(CPN)is a new paradigm that integrates communication,computing,and storage resources to provide services for tasks.However,tasks composed of non-independent subtasks have a preference for the re... Computing Power Network(CPN)is a new paradigm that integrates communication,computing,and storage resources to provide services for tasks.However,tasks composed of non-independent subtasks have a preference for the resources required at each stage,which increases the difficulty of heterogeneous resource allocation and reduces the latency performance of CPN services.Motivated by this,this paper jointly optimizes the full-service cycle of tasks,including transmission,task partitioning,and offloading.First,the transmission bandwidth is dynamically configured based on delay sensitivity of tasks.Second,with the real-time information from edge resource clusters and state resource clusters in the network,the optimal partitioning for a computation task is derived.Third,personalized resource allocation schemes are customized for computation and storage tasks respectively.Finally,the impact of resource parameter configuration on the latency violation probability of CPN is revealed.Moreover,compared with the benchmark schemes,our proposed scheme reduces the network latency violation probability by up to 1.17×in the same network setting. 展开更多
关键词 Latency violation probability Subtask dependencies Resource allocation Computing power network
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Tree biomass allocation is governed by allometry but modulated by optimization 认领 引用
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作者 Man Hu Hang Shi +4 位作者 Rui He Nana Wang Yuzhen Han Haishan Dang Quanfa Zhang 《Forest Ecosystems》 SCIE CAS CSCD 2026年第1期166-177,共12页
Understanding the patterns and drivers of biomass allocation among organs at a broad scale is crucial for predicting the responses of plant growth and carbon sequestration to environmental change.However,the extent to... Understanding the patterns and drivers of biomass allocation among organs at a broad scale is crucial for predicting the responses of plant growth and carbon sequestration to environmental change.However,the extent to which the general rules govern these patterns and the key factors affecting biomass allocation remain poorly understood.Using a global dataset of 239 tree species,we tested the two prevailing theories(i.e.,the allometric partitioning theory(APT)and the optimal partitioning theory(OPT))by investigating the scaling relationships between plant organs and how environmental factors and phylogeny shape the patterns of biomass allocation.Our results generally support APT at the global scale,with variations in biomass allocation patterns explained by OPT.As plant size increased,a significant shift in biomass allocation from leaves to roots and stems,as well as from roots to stems,was observed.Specific environmental factors(including temperature,precipitation variables,and soil properties)significantly influenced biomass allocation with distinct patterns in the angiosperms and gymnosperms,even when the allometric effects were taken into account.We conclude that tree biomass allocation among organs(i.e.,the ratios of leaf to stem,leaf to root,stem to root,and aboveground to belowground)is governed by allometry but modulated by optimization at the global scale.Our findings highlight the importance of considering both the ontogenetic and environmental effects in predicting the responses of biomass sequestration to phylogenetic and environmental factors. 展开更多
关键词 Biomass allocation Allometric partitioning theory Optimal partitioning theory(OPT) Scaling exponent Plant size Environmental factors
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Impact of resource allocation on information-disease coupled propagation considering node importance in multiplex networks 认领 引用
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作者 Liang’an Huo Jiaxue Cha Yue Yu 《Chinese Physics B》 SCIE EI CAS CSCD 2026年第7期901-913,共13页
During a large-scale epidemic outbreak,effective resource allocation is vital for controlling disease transmission.Prioritizing resource provision to communities experiencing severe infections can mitigate further spr... During a large-scale epidemic outbreak,effective resource allocation is vital for controlling disease transmission.Prioritizing resource provision to communities experiencing severe infections can mitigate further spread,while prioritizing information dissemination to influential individuals can expand the publicity effect.This paper proposes a novel two-layer information-disease transmission coupled model that optimizes the allocation of information and medical resources based on node importance analysis,aiming to explore the synergistic effects of resource allocation on disease dynamics.The study employs the microscopic Markov chain approach to construct dynamic equations and derive the epidemic threshold,with Monte Carlo simulations used to validate the theoretical results.Findings demonstrate that expanding the scope of preventive information dissemination through mass media improves public awareness of disease prevention and significantly curbs epidemic transmission.Moreover,reducing the resource deployment threshold in infected communities enables more precise resource allocation during the early stages of an outbreak,which is vital for increasing the epidemic threshold and reducing the final size of the epidemic.These findings provide robust theoretical foundations and actionable guidelines for optimizing resource allocation strategies in public health emergency management. 展开更多
关键词 information dissemination disease transmission resource allocation node importance multilayer network
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