A[3+4]annulation of α-substituted allenes and Schiff bases is reported.This methodology serves as a conduit for the construction of a series of biologically important benzazepine derivatives in good to excellent yiel...A[3+4]annulation of α-substituted allenes and Schiff bases is reported.This methodology serves as a conduit for the construction of a series of biologically important benzazepine derivatives in good to excellent yields under mild conditions by an unprecedented mode involving β’-carbon of α-substituted allenes and the proposed mechanism is supported by capturing the intermediate.Moreover,this class of benzazepine derivatives exhibited potential ability of cytotoxicity toward cancer cells.展开更多
Improving the accuracy of the evaluation of the performance of wind farms in large wind power bases located in complex terrain under the actual atmosphere is crucial to the sustainable development of wind power.To thi...Improving the accuracy of the evaluation of the performance of wind farms in large wind power bases located in complex terrain under the actual atmosphere is crucial to the sustainable development of wind power.To this end,this study combined the Weather Research and Forecasting(WRF)model with the Wind Farm Parameterization(WFP)method to investigate the wake characteristics and operational performance of large onshore wind farms in the complex terrain of Jiuquan City,Gansu Province,China.The research results showed that after verification,the systematic error of the WRF simulations was less than 3%.The WRF model and the WFP scheme simulated a significant warming phenomenon within the wind power base area,while a cooling effect was observed outside.The analysis of the wake effects indicated that the impact of PhaseⅠconstruction on PhaseⅡconstruction of the wind power base was minimal.During the operation of the entire wind power base,the wind speed within the wind farm decreased by approximately 10%,and the influence range of the predominant wind direction extended over a hundred kilometers downwind.The research conclusions provide a powerful scientific basis for optimizing design and operation,improving efficiency,minimizing the negative impacts on adjacent wind turbines,and ensuring the sustainable development of wind energy through dynamic planning and scientific assessment.展开更多
CHINA.5G Base Stations See Strong Growth.China witnessed substantial growth in the number of 5G base stations in 2025,according to data from the Ministry of Industry and Information Technology.As of the end of October...CHINA.5G Base Stations See Strong Growth.China witnessed substantial growth in the number of 5G base stations in 2025,according to data from the Ministry of Industry and Information Technology.As of the end of October 2025,the total number of 5G base stations in the country reached around 4.76 million,with a net increase of 507,000 from the end of last year,accounting for 37 percent of all mobile base stations.展开更多
Co_(3)O_(4) is a promising catalyst for the chlorine evolution reaction(CER)in seawater;however,its CER selectivity is compromised by the adsorption of the competitive oxygen evolution reaction intermediate(OH^(-))at ...Co_(3)O_(4) is a promising catalyst for the chlorine evolution reaction(CER)in seawater;however,its CER selectivity is compromised by the adsorption of the competitive oxygen evolution reaction intermediate(OH^(-))at Co sites.Inspired by the hard-soft acid-base(HSAB)theory,this study proposes incorporating early transition metal sites(V)with a low degree of electron delocalization into Co_(3)O_(4) to modulate the selective adsorption of reactants on catalytic sites.Experimental and theoretical calculations reveal that V incorporation facilitates the electron accumulation at the Co site,significantly strengthening the interaction between Co and Cl^(-).Meanwhile,the loss of electrons from V sites generates a more localized electronic state that preferentially adsorbs OH^(-),thus reducing the Co-OH interaction and releasing more Co sites for Cl^(-)adsorption.Therefore,Co_(2)VO_(4) exhibits a high CER selectivity of 92.3%and maintains one of the highest stabilities over 300 h in natural seawater.The resulting half-flow cell achieves~100%disinfection efficiency in seawater,validating the HSAB theory-based design strategy and offering new guidance for developing highly selective seawater CER catalysts.展开更多
In the modern era of ubiquitous and highly interconnected information technology,cybersecurity threats stemming from software code vulnerabilities have become increasingly severe,posing significant risks to the confid...In the modern era of ubiquitous and highly interconnected information technology,cybersecurity threats stemming from software code vulnerabilities have become increasingly severe,posing significant risks to the confidentiality,integrity,and availability of modern information systems.To enhance software code quality,enterprises often integrate static code analysis tools into Continuous Integration(CI) pipelines.However,the high rates of false positives and false negatives remain a challenge.The advent of large language models(LLMs),such as ChatGPT,presents a new opportunity to address these challenges.In this paper,we propose AI-SCDF,a framework that utilizes the custombuilt Nebula-Coder AI model for detecting and fixing code security issues in real time during the developer ' s personal build process.We construct a static code checking rule knowledge base through summarizing and classifying Common Weakness Enumeration(CWE) code security problems identified by security and quality assurance teams.The rule knowledge base is combined with CodeFuse-processed code contexts to serve as input for an AI code security detection microservice,which assists in identifying code quality and security issues.If any abnormalities are detected,they are addressed by an AI code security patching microservice,which alerts the developer and requests confirmation before committing the code into the repository.Experimental results show that our approach effectively improves code quality.We also develop a VS Code plugin for code alert detection and fix based on LLMs,which facilitates test shift-left and lowers the risk of software development.展开更多
When one steps inside Caoxian's Youai Cloud Warehouse,a livestreaming base dedicated to hanfu,it feels less like a clothing warehouse and more like a time capsule.Thousands of intricately embroidered garments line...When one steps inside Caoxian's Youai Cloud Warehouse,a livestreaming base dedicated to hanfu,it feels less like a clothing warehouse and more like a time capsule.Thousands of intricately embroidered garments line the racks-from elegant horseface skirts to modernized editions of traditional Chinese clothing.On one side,livestreamers dressed in hanfu smile at their smartphone cameras,twirling for their online audiences while the chime of incoming orders punctuates the air.Behind them,visitors run their hands over organza fabrics,marvelling at the fusion of ageold craftsmanship and contemporary taste.展开更多
The dynamics of calcium(Ca)and magnesium(Mg)in the forest floor and topsoil caused by anthropogenic and natural processes continue to be a concern in temperate forests.However,the impacts of abiotic and biotic variabl...The dynamics of calcium(Ca)and magnesium(Mg)in the forest floor and topsoil caused by anthropogenic and natural processes continue to be a concern in temperate forests.However,the impacts of abiotic and biotic variables as well as their interactions remain unclear,especially in areas undergoing long-term forest restoration.In this study,Ca and Mg concentrations in the forest floor and topsoil from 239 forest plots across the Loess Plateau were measured,and the effects of forest types,climate,soil properties,stand characteristics and nitrogen deposition were explored.The results showed significantly higher Ca concentrations in the forest floor(20.68±8.04 mg/g)than in the topsoil(13.28±12.83 mg/g),whereas Mg exhibited the inverse pattern(3.64±1.09 and 10.11±2.51 mg/g,respectively).The effect of forest types was only significant on forest floor Ca,and Ca concentrations were higher in broadleaf and mixed forests than in coniferous forests.Overall,Ca and Mg concentrations in forest floor and topsoil increased with latitudes while decreased with elevations,and the significance of the trends varied among forest types.Forest floor Ca and Mg were mainly influenced by environmental variables aboveground,i.e.,basal area(BA)and mean annual precipitation(MAP),respectively;topsoil Ca and Mg were more affected by soil properties(soil C/N and pH,respectively).Those suggested a depletion of Ca belowground was associated with forest growth and enriched soil nitrogen,and the leaching of mobile Mg was correlated with rainfall and soil acidification.Besides,the impact of environmental variables on Ca-Mg balance(Ca/Mg ratio)belowground was primarily through the regulation of Ca.Elucidating the influence of environmental variables will improve our ability to predict future changes in base cations and thus forest soil health in the greening vegetated Loess Plateau.展开更多
Domain adaptation aims to reduce the distribution gap between the training data(source domain)and the target data.This enables effective predictions even for domains not seen during training.However,most conventional ...Domain adaptation aims to reduce the distribution gap between the training data(source domain)and the target data.This enables effective predictions even for domains not seen during training.However,most conventional domain adaptation methods assume a single source domain,making them less suitable for modern deep learning settings that rely on diverse and large-scale datasets.To address this limitation,recent research has focused on Multi-Source Domain Adaptation(MSDA),which aims to learn effectively from multiple source domains.In this paper,we propose Efficient Domain Transition for Multi-source(EDTM),a novel and efficient framework designed to tackle two major challenges in existing MSDA approaches:(1)integrating knowledge across different source domains and(2)aligning label distributions between source and target domains.EDTM leverages an ensemble-based classifier expert mechanism to enhance the contribution of source domains that are more similar to the target domain.To further stabilize the learning process and improve performance,we incorporate imitation learning into the training of the target model.In addition,Maximum Classifier Discrepancy(MCD)is employed to align class-wise label distributions between the source and target domains.Experiments were conducted using Digits-Five,one of the most representative benchmark datasets for MSDA.The results show that EDTM consistently outperforms existing methods in terms of average classification accuracy.Notably,EDTM achieved significantly higher performance on target domains such as Modified National Institute of Standards and Technolog with blended background images(MNIST-M)and Street View House Numbers(SVHN)datasets,demonstrating enhanced generalization compared to baseline approaches.Furthermore,an ablation study analyzing the contribution of each loss component validated the effectiveness of the framework,highlighting the importance of each module in achieving optimal performance.展开更多
Reversible data hiding(RDH)enables secret data embedding while preserving complete cover image recovery,making it crucial for applications requiring image integrity.The pixel value ordering(PVO)technique used in multi...Reversible data hiding(RDH)enables secret data embedding while preserving complete cover image recovery,making it crucial for applications requiring image integrity.The pixel value ordering(PVO)technique used in multi-stego images provides good image quality but often results in low embedding capability.To address these challenges,this paper proposes a high-capacity RDH scheme based on PVO that generates three stego images from a single cover image.The cover image is partitioned into non-overlapping blocks with pixels sorted in ascending order.Four secret bits are embedded into each block’s maximum pixel value,while three additional bits are embedded into the second-largest value when the pixel difference exceeds a predefined threshold.A similar embedding strategy is also applied to the minimum side of the block,including the second-smallest pixel value.This design enables each block to embed up to 14 bits of secret data.Experimental results demonstrate that the proposed method achieves significantly higher embedding capacity and improved visual quality compared to existing triple-stego RDH approaches,advancing the field of reversible steganography.展开更多
Correction to:Journal of Forestry Research(2025)36:124 https://doi.org/10.1007/s11676-025-01918-8 In this article the author’s name Yasutomo Hoshika was incorrectly written as Yasutoma Hoshika.The original article ha...Correction to:Journal of Forestry Research(2025)36:124 https://doi.org/10.1007/s11676-025-01918-8 In this article the author’s name Yasutomo Hoshika was incorrectly written as Yasutoma Hoshika.The original article has been corrected.展开更多
Federated Learning(FL)enables joint training over distributed devices without data exchange but is highly vulnerable to attacks by adversaries in the form of model poisoning and malicious update injection.This work pr...Federated Learning(FL)enables joint training over distributed devices without data exchange but is highly vulnerable to attacks by adversaries in the form of model poisoning and malicious update injection.This work proposes Secured-FL,a blockchain-based defensive framework that combines smart contract-based authentication,clustering-driven outlier elimination,and dynamic threshold adjustment to defend against adversarial attacks.The framework was implemented on a private Ethereum network with a Proof-of-Authority consensus algorithm to ensure tamper-resistant and auditable model updates.Large-scale simulation on the Cyber Data dataset,under up to 50%malicious client settings,demonstrates Secured-FL achieves 6%-12%higher accuracy,9%-15%lower latency,and approximately 14%less computational expense compared to the PPSS benchmark framework.Additional tests,including confusion matrices,ROC and Precision-Recall curves,and ablation tests,confirm the interpretability and robustness of the defense.Tests for scalability also show consistent performance up to 500 clients,affirming appropriateness to reasonably large deployments.These results make Secured-FL a feasible,adversarially resilient FL paradigm with promising potential for application in smart cities,medicine,and other mission-critical IoT deployments.展开更多
Traveling wave(TW)fault location technology has been widely used in transmission systems due to its high accuracy and simplicity.Recently,there has been growing interest in applying this technology to medium voltage(M...Traveling wave(TW)fault location technology has been widely used in transmission systems due to its high accuracy and simplicity.Recently,there has been growing interest in applying this technology to medium voltage(MV)distribution lines.However,current practices in its deployment,signal measurement,and threshold setting are usually from the application experiences in transmission lines,despite significant differences in fault-induced wave characteristics between transmission and distribution systems.To address these issues,this paper investigates the feasibility and applicability of TW fault technology in MV overhead distribution lines through characteristic analysis of fault-induced TWs.The propagation characteristics of aerial mode and zero mode TWs on overhead distribution lines are studied.Furthermore,it evaluates the influence of critical distri-bution network components including distribution transformers,multi-branch configurations,and busbar structures on wave propagation characteristics.Deployment strategies for traveling wave fault location(TWFL)devices is proposed to address the unique challenges of distribution networks,while the fault location method is also improved.Field test results demonstrate the effectiveness of the proposed methodology,showing improved fault detection accuracy and system reliability in distri-bution network applications.This research provides practical implementation suggestions for TWFL technology in distribution networks.展开更多
The original online version of this article was revised:Several errors occurred in the published version of the article.These have now been corrected as follows:Page 2,section"2.2 Laser Texturing Procedure of Sur...The original online version of this article was revised:Several errors occurred in the published version of the article.These have now been corrected as follows:Page 2,section"2.2 Laser Texturing Procedure of Surfaces",line 2:The device name was corrected from"YDFLP-E-50-M8"to"YDFLP-50-M8."Page 3,Section 2.4:The phrase"95%confidence interval"has been corrected to"95%confidence level."Page 3,Figure 1 caption:The phrase"fandg"has been corrected to"f and g."The order"C4 and C12"has been reversed to"C12 and C4,"in accordance with the display order in the figure.Page 4,Figure reference:The phrase"Figs.4c and d"has been corrected to"Figs.5b and c."Page 5,paragraph starting with"The ANOVA results are presented...":The phrase"95%confidence interval"has been corrected to"95%confidence level."展开更多
Maize(Zea mays L.)is recognized as one of the most significant cereal crops worldwide,serving as a primary source of human food,animal feed,and industrial raw materials.With increasing diversification of market demand...Maize(Zea mays L.)is recognized as one of the most significant cereal crops worldwide,serving as a primary source of human food,animal feed,and industrial raw materials.With increasing diversification of market demands for specialty maize varieties,distinctive fresh produce cultivars characterized by unique textures have gained considerable popularity among consumers(Boyer and Shannon 1984).Notably,sweet maize is often referred to as the‘King of fruits and vegetables'due to its richness in polysaccharides,dietary fiber,trace elements,vitamins,linoleic acid,and other essential nutrients(Revilla et al.2021).展开更多
When teaching neurology students about epilepsy,selecting appropriate antiseizure medications(ASMs)based on seizure type is a fundamental objective.Carbamazepine(CBZ),a widely used first-line ASM,is effective against ...When teaching neurology students about epilepsy,selecting appropriate antiseizure medications(ASMs)based on seizure type is a fundamental objective.Carbamazepine(CBZ),a widely used first-line ASM,is effective against focal seizures,generalized tonic-clonic seizures,and mixed seizure patterns[1].However,CBZ paradoxically aggravates absence seizures,as demonstrated by increased 36 Hz spike-and-wave discharges(SWDs)in both patients and animal models[2,3].While prior studies implicated altered GABAA receptor function in the thalamic ventrobasal complex[4],the precise mechanisms remained unclear.Recently,an inspiring study published on PNAS by Jang et al.from Stanford University has highlighted the thalamic reticular nucleus(RT)as the key brain region responsible for CBZ's aggravating effect on absence seizures[5].The combination of transgenic mouse models,optogenetics,and detailed electrophysiology in the original study provided exceptional precision in probing mechanistic insights,which greatly strengthens the conclusions.展开更多
In the hilly regions of Oudomxay Province,Laos,rows of deep blue photovoltaic panels are converting the scorching sunlight into clean electricity.They are part of the first phase of the Northern Laos Interconnected Cl...In the hilly regions of Oudomxay Province,Laos,rows of deep blue photovoltaic panels are converting the scorching sunlight into clean electricity.They are part of the first phase of the Northern Laos Interconnected Clean Energy Base,which was developed by China General Nuclear Power Group and became operational at the end of 2025.展开更多
Dear Editor,This letter studies the problem of stealthy attacks targeting stochastic event-based estimation,alongside proposing measures for their mitigation.A general attack framework is introduced,and the correspond...Dear Editor,This letter studies the problem of stealthy attacks targeting stochastic event-based estimation,alongside proposing measures for their mitigation.A general attack framework is introduced,and the corresponding stealthiness condition is analyzed.To enhance system security,we advocate for a single-dimensional encryption method,showing that securing a singular data element is sufficient to shield the system from the perils of stealthy attacks.展开更多
Federated learning is a decentralized model training paradigm with significant potential.However,the quality of Federated Network’s client updates can vary due to non-IID data distributions,leading to suboptimal glob...Federated learning is a decentralized model training paradigm with significant potential.However,the quality of Federated Network’s client updates can vary due to non-IID data distributions,leading to suboptimal global models.To address this issue,we propose a novel client selection strategy called FedPA(Performance-Based Federated Averaging).This proposed model selectively aggregates client updates based on a predefined performance threshold.Only clients whose local models achieve an F1 score of 70%or higher after training are included in the aggregation process.Clients below this threshold receive the updated global model but do not contribute their parameters.In this way,the low-performance clients are still in the process of learning and,after some rounds,will be able to contribute.If no client meets the performance threshold in a given round,the system falls back to standard FedAvg aggregation.This ensures the global model continues to improve even when most clients perform poorly.We evaluate FedPA on a subset of the MURA dataset for abnormality detection in radiographs of four bone types.Compared to baseline federated learning algorithms such as Federated Averaging(FedAvg),Federated Proximal(FedProx),Federated Stochastic Gradient Descent(FedSGD),and Federated Batch Normalization(FedBN),FedPA consistently ranks first or second across key performance metrics,particularly in accuracy,F1 score,and recall.Moreover,FedPA demonstrates notable efficiency,achieving the lowest average round time(≈2270 s)and minimal memory usage(≈645.58 MB),all without relying on GPU resources.These results highlight FedPA’s effectiveness in improving global model quality while reducing computational overhead,positioning it as a promising approach for real-world federated learning applications in resource-constrained environments.展开更多
https://www.sciencedirect.com/journal/energy-and-buildings/vol/354/suppl/C Volume 354,1 March 2026[OA](1)Rule-based peak shaving strategy with battery storage:Evaluating socio-economic impacts in regional grids by Md ...https://www.sciencedirect.com/journal/energy-and-buildings/vol/354/suppl/C Volume 354,1 March 2026[OA](1)Rule-based peak shaving strategy with battery storage:Evaluating socio-economic impacts in regional grids by Md Masud Rana,Huadong Mo,Mohd Fakhizan Romlie,et al,Article 116983 Abstract:The Australian electricity framework includes several demand tariff structures,with peak demand charges constituting a significant cost component for consumers.Efficient peak load shaving techniques can mitigate these charges,leading to substantial economic benefits to the power suppliers,consumers,and society.展开更多
基金financially supported by the National Natural Science Foundation of China(No.21572271).
文摘A[3+4]annulation of α-substituted allenes and Schiff bases is reported.This methodology serves as a conduit for the construction of a series of biologically important benzazepine derivatives in good to excellent yields under mild conditions by an unprecedented mode involving β’-carbon of α-substituted allenes and the proposed mechanism is supported by capturing the intermediate.Moreover,this class of benzazepine derivatives exhibited potential ability of cytotoxicity toward cancer cells.
基金funded by“The Factors Affecting the Accuracy of Wind Resource Assessment and Comprehensive Post-Evaluation Techniques for Operating Wind Power Projects,”grant number YJ24.002“The Research and Application of Future Medium to Long Term Wind Resource Assessment for Wind Farms Based on Artificial Intelligence Project,”grant number 2023021。
文摘Improving the accuracy of the evaluation of the performance of wind farms in large wind power bases located in complex terrain under the actual atmosphere is crucial to the sustainable development of wind power.To this end,this study combined the Weather Research and Forecasting(WRF)model with the Wind Farm Parameterization(WFP)method to investigate the wake characteristics and operational performance of large onshore wind farms in the complex terrain of Jiuquan City,Gansu Province,China.The research results showed that after verification,the systematic error of the WRF simulations was less than 3%.The WRF model and the WFP scheme simulated a significant warming phenomenon within the wind power base area,while a cooling effect was observed outside.The analysis of the wake effects indicated that the impact of PhaseⅠconstruction on PhaseⅡconstruction of the wind power base was minimal.During the operation of the entire wind power base,the wind speed within the wind farm decreased by approximately 10%,and the influence range of the predominant wind direction extended over a hundred kilometers downwind.The research conclusions provide a powerful scientific basis for optimizing design and operation,improving efficiency,minimizing the negative impacts on adjacent wind turbines,and ensuring the sustainable development of wind energy through dynamic planning and scientific assessment.
文摘CHINA.5G Base Stations See Strong Growth.China witnessed substantial growth in the number of 5G base stations in 2025,according to data from the Ministry of Industry and Information Technology.As of the end of October 2025,the total number of 5G base stations in the country reached around 4.76 million,with a net increase of 507,000 from the end of last year,accounting for 37 percent of all mobile base stations.
基金supported by the Guangxi Science and Technology Program(2023AB38061)the National Natural Science Foundation of China(22162004,22479031)the High-performance Computing Platform of Guangxi University。
文摘Co_(3)O_(4) is a promising catalyst for the chlorine evolution reaction(CER)in seawater;however,its CER selectivity is compromised by the adsorption of the competitive oxygen evolution reaction intermediate(OH^(-))at Co sites.Inspired by the hard-soft acid-base(HSAB)theory,this study proposes incorporating early transition metal sites(V)with a low degree of electron delocalization into Co_(3)O_(4) to modulate the selective adsorption of reactants on catalytic sites.Experimental and theoretical calculations reveal that V incorporation facilitates the electron accumulation at the Co site,significantly strengthening the interaction between Co and Cl^(-).Meanwhile,the loss of electrons from V sites generates a more localized electronic state that preferentially adsorbs OH^(-),thus reducing the Co-OH interaction and releasing more Co sites for Cl^(-)adsorption.Therefore,Co_(2)VO_(4) exhibits a high CER selectivity of 92.3%and maintains one of the highest stabilities over 300 h in natural seawater.The resulting half-flow cell achieves~100%disinfection efficiency in seawater,validating the HSAB theory-based design strategy and offering new guidance for developing highly selective seawater CER catalysts.
文摘In the modern era of ubiquitous and highly interconnected information technology,cybersecurity threats stemming from software code vulnerabilities have become increasingly severe,posing significant risks to the confidentiality,integrity,and availability of modern information systems.To enhance software code quality,enterprises often integrate static code analysis tools into Continuous Integration(CI) pipelines.However,the high rates of false positives and false negatives remain a challenge.The advent of large language models(LLMs),such as ChatGPT,presents a new opportunity to address these challenges.In this paper,we propose AI-SCDF,a framework that utilizes the custombuilt Nebula-Coder AI model for detecting and fixing code security issues in real time during the developer ' s personal build process.We construct a static code checking rule knowledge base through summarizing and classifying Common Weakness Enumeration(CWE) code security problems identified by security and quality assurance teams.The rule knowledge base is combined with CodeFuse-processed code contexts to serve as input for an AI code security detection microservice,which assists in identifying code quality and security issues.If any abnormalities are detected,they are addressed by an AI code security patching microservice,which alerts the developer and requests confirmation before committing the code into the repository.Experimental results show that our approach effectively improves code quality.We also develop a VS Code plugin for code alert detection and fix based on LLMs,which facilitates test shift-left and lowers the risk of software development.
文摘When one steps inside Caoxian's Youai Cloud Warehouse,a livestreaming base dedicated to hanfu,it feels less like a clothing warehouse and more like a time capsule.Thousands of intricately embroidered garments line the racks-from elegant horseface skirts to modernized editions of traditional Chinese clothing.On one side,livestreamers dressed in hanfu smile at their smartphone cameras,twirling for their online audiences while the chime of incoming orders punctuates the air.Behind them,visitors run their hands over organza fabrics,marvelling at the fusion of ageold craftsmanship and contemporary taste.
基金supported by the National Natural Science Foundation of China(42401054)Natural Science Foundation of Hebei Province(D2024205019)Science and Technology Project of Hebei Education Department(BJ2025014).
文摘The dynamics of calcium(Ca)and magnesium(Mg)in the forest floor and topsoil caused by anthropogenic and natural processes continue to be a concern in temperate forests.However,the impacts of abiotic and biotic variables as well as their interactions remain unclear,especially in areas undergoing long-term forest restoration.In this study,Ca and Mg concentrations in the forest floor and topsoil from 239 forest plots across the Loess Plateau were measured,and the effects of forest types,climate,soil properties,stand characteristics and nitrogen deposition were explored.The results showed significantly higher Ca concentrations in the forest floor(20.68±8.04 mg/g)than in the topsoil(13.28±12.83 mg/g),whereas Mg exhibited the inverse pattern(3.64±1.09 and 10.11±2.51 mg/g,respectively).The effect of forest types was only significant on forest floor Ca,and Ca concentrations were higher in broadleaf and mixed forests than in coniferous forests.Overall,Ca and Mg concentrations in forest floor and topsoil increased with latitudes while decreased with elevations,and the significance of the trends varied among forest types.Forest floor Ca and Mg were mainly influenced by environmental variables aboveground,i.e.,basal area(BA)and mean annual precipitation(MAP),respectively;topsoil Ca and Mg were more affected by soil properties(soil C/N and pH,respectively).Those suggested a depletion of Ca belowground was associated with forest growth and enriched soil nitrogen,and the leaching of mobile Mg was correlated with rainfall and soil acidification.Besides,the impact of environmental variables on Ca-Mg balance(Ca/Mg ratio)belowground was primarily through the regulation of Ca.Elucidating the influence of environmental variables will improve our ability to predict future changes in base cations and thus forest soil health in the greening vegetated Loess Plateau.
基金supported by the National Research Foundation of Korea(NRF)grant funded by the Korea government(MSIT)(No.RS-2024-00406320)the Institute of Information&Communica-tions Technology Planning&Evaluation(IITP)-Innovative Human Resource Development for Local Intellectualization Program Grant funded by the Korea government(MSIT)(IITP-2026-RS-2023-00259678).
文摘Domain adaptation aims to reduce the distribution gap between the training data(source domain)and the target data.This enables effective predictions even for domains not seen during training.However,most conventional domain adaptation methods assume a single source domain,making them less suitable for modern deep learning settings that rely on diverse and large-scale datasets.To address this limitation,recent research has focused on Multi-Source Domain Adaptation(MSDA),which aims to learn effectively from multiple source domains.In this paper,we propose Efficient Domain Transition for Multi-source(EDTM),a novel and efficient framework designed to tackle two major challenges in existing MSDA approaches:(1)integrating knowledge across different source domains and(2)aligning label distributions between source and target domains.EDTM leverages an ensemble-based classifier expert mechanism to enhance the contribution of source domains that are more similar to the target domain.To further stabilize the learning process and improve performance,we incorporate imitation learning into the training of the target model.In addition,Maximum Classifier Discrepancy(MCD)is employed to align class-wise label distributions between the source and target domains.Experiments were conducted using Digits-Five,one of the most representative benchmark datasets for MSDA.The results show that EDTM consistently outperforms existing methods in terms of average classification accuracy.Notably,EDTM achieved significantly higher performance on target domains such as Modified National Institute of Standards and Technolog with blended background images(MNIST-M)and Street View House Numbers(SVHN)datasets,demonstrating enhanced generalization compared to baseline approaches.Furthermore,an ablation study analyzing the contribution of each loss component validated the effectiveness of the framework,highlighting the importance of each module in achieving optimal performance.
基金funded by University of Transport and Communications(UTC)under grant number T2025-CN-004.
文摘Reversible data hiding(RDH)enables secret data embedding while preserving complete cover image recovery,making it crucial for applications requiring image integrity.The pixel value ordering(PVO)technique used in multi-stego images provides good image quality but often results in low embedding capability.To address these challenges,this paper proposes a high-capacity RDH scheme based on PVO that generates three stego images from a single cover image.The cover image is partitioned into non-overlapping blocks with pixels sorted in ascending order.Four secret bits are embedded into each block’s maximum pixel value,while three additional bits are embedded into the second-largest value when the pixel difference exceeds a predefined threshold.A similar embedding strategy is also applied to the minimum side of the block,including the second-smallest pixel value.This design enables each block to embed up to 14 bits of secret data.Experimental results demonstrate that the proposed method achieves significantly higher embedding capacity and improved visual quality compared to existing triple-stego RDH approaches,advancing the field of reversible steganography.
文摘Correction to:Journal of Forestry Research(2025)36:124 https://doi.org/10.1007/s11676-025-01918-8 In this article the author’s name Yasutomo Hoshika was incorrectly written as Yasutoma Hoshika.The original article has been corrected.
文摘Federated Learning(FL)enables joint training over distributed devices without data exchange but is highly vulnerable to attacks by adversaries in the form of model poisoning and malicious update injection.This work proposes Secured-FL,a blockchain-based defensive framework that combines smart contract-based authentication,clustering-driven outlier elimination,and dynamic threshold adjustment to defend against adversarial attacks.The framework was implemented on a private Ethereum network with a Proof-of-Authority consensus algorithm to ensure tamper-resistant and auditable model updates.Large-scale simulation on the Cyber Data dataset,under up to 50%malicious client settings,demonstrates Secured-FL achieves 6%-12%higher accuracy,9%-15%lower latency,and approximately 14%less computational expense compared to the PPSS benchmark framework.Additional tests,including confusion matrices,ROC and Precision-Recall curves,and ablation tests,confirm the interpretability and robustness of the defense.Tests for scalability also show consistent performance up to 500 clients,affirming appropriateness to reasonably large deployments.These results make Secured-FL a feasible,adversarially resilient FL paradigm with promising potential for application in smart cities,medicine,and other mission-critical IoT deployments.
基金supported by the National Natural Sci-ence Foundation of China(No.52107109).
文摘Traveling wave(TW)fault location technology has been widely used in transmission systems due to its high accuracy and simplicity.Recently,there has been growing interest in applying this technology to medium voltage(MV)distribution lines.However,current practices in its deployment,signal measurement,and threshold setting are usually from the application experiences in transmission lines,despite significant differences in fault-induced wave characteristics between transmission and distribution systems.To address these issues,this paper investigates the feasibility and applicability of TW fault technology in MV overhead distribution lines through characteristic analysis of fault-induced TWs.The propagation characteristics of aerial mode and zero mode TWs on overhead distribution lines are studied.Furthermore,it evaluates the influence of critical distri-bution network components including distribution transformers,multi-branch configurations,and busbar structures on wave propagation characteristics.Deployment strategies for traveling wave fault location(TWFL)devices is proposed to address the unique challenges of distribution networks,while the fault location method is also improved.Field test results demonstrate the effectiveness of the proposed methodology,showing improved fault detection accuracy and system reliability in distri-bution network applications.This research provides practical implementation suggestions for TWFL technology in distribution networks.
文摘The original online version of this article was revised:Several errors occurred in the published version of the article.These have now been corrected as follows:Page 2,section"2.2 Laser Texturing Procedure of Surfaces",line 2:The device name was corrected from"YDFLP-E-50-M8"to"YDFLP-50-M8."Page 3,Section 2.4:The phrase"95%confidence interval"has been corrected to"95%confidence level."Page 3,Figure 1 caption:The phrase"fandg"has been corrected to"f and g."The order"C4 and C12"has been reversed to"C12 and C4,"in accordance with the display order in the figure.Page 4,Figure reference:The phrase"Figs.4c and d"has been corrected to"Figs.5b and c."Page 5,paragraph starting with"The ANOVA results are presented...":The phrase"95%confidence interval"has been corrected to"95%confidence level."
基金supported by the Youth Research Foundation of Beijing Academy of Agriculture and Forestry Sciences,China(QNJJ202420)the Beijing Science and Technology Association Youth Lifting Project,Chinathe Beijing Municipal Rural Revitalization Agricultural Science and Technology Development Project,China(NY2401020224)。
文摘Maize(Zea mays L.)is recognized as one of the most significant cereal crops worldwide,serving as a primary source of human food,animal feed,and industrial raw materials.With increasing diversification of market demands for specialty maize varieties,distinctive fresh produce cultivars characterized by unique textures have gained considerable popularity among consumers(Boyer and Shannon 1984).Notably,sweet maize is often referred to as the‘King of fruits and vegetables'due to its richness in polysaccharides,dietary fiber,trace elements,vitamins,linoleic acid,and other essential nutrients(Revilla et al.2021).
基金supported by the National Natural Science Foundation of China(82173796)the Research Project of Zhejiang Chinese Medical University(2023JKZDZC04).
文摘When teaching neurology students about epilepsy,selecting appropriate antiseizure medications(ASMs)based on seizure type is a fundamental objective.Carbamazepine(CBZ),a widely used first-line ASM,is effective against focal seizures,generalized tonic-clonic seizures,and mixed seizure patterns[1].However,CBZ paradoxically aggravates absence seizures,as demonstrated by increased 36 Hz spike-and-wave discharges(SWDs)in both patients and animal models[2,3].While prior studies implicated altered GABAA receptor function in the thalamic ventrobasal complex[4],the precise mechanisms remained unclear.Recently,an inspiring study published on PNAS by Jang et al.from Stanford University has highlighted the thalamic reticular nucleus(RT)as the key brain region responsible for CBZ's aggravating effect on absence seizures[5].The combination of transgenic mouse models,optogenetics,and detailed electrophysiology in the original study provided exceptional precision in probing mechanistic insights,which greatly strengthens the conclusions.
基金findings from the Research on the Innovative Mechanism for Coordinated Development of Ecological Security between China’s Yunnan Province and the Vietnam-LaosMyanmar Region,a general project of Yunnan Provincial Philosophy and Social Sciences Planning。
文摘In the hilly regions of Oudomxay Province,Laos,rows of deep blue photovoltaic panels are converting the scorching sunlight into clean electricity.They are part of the first phase of the Northern Laos Interconnected Clean Energy Base,which was developed by China General Nuclear Power Group and became operational at the end of 2025.
基金supported by the National Natural Science Foundation of China(62303353,62273030,62573320)。
文摘Dear Editor,This letter studies the problem of stealthy attacks targeting stochastic event-based estimation,alongside proposing measures for their mitigation.A general attack framework is introduced,and the corresponding stealthiness condition is analyzed.To enhance system security,we advocate for a single-dimensional encryption method,showing that securing a singular data element is sufficient to shield the system from the perils of stealthy attacks.
文摘Federated learning is a decentralized model training paradigm with significant potential.However,the quality of Federated Network’s client updates can vary due to non-IID data distributions,leading to suboptimal global models.To address this issue,we propose a novel client selection strategy called FedPA(Performance-Based Federated Averaging).This proposed model selectively aggregates client updates based on a predefined performance threshold.Only clients whose local models achieve an F1 score of 70%or higher after training are included in the aggregation process.Clients below this threshold receive the updated global model but do not contribute their parameters.In this way,the low-performance clients are still in the process of learning and,after some rounds,will be able to contribute.If no client meets the performance threshold in a given round,the system falls back to standard FedAvg aggregation.This ensures the global model continues to improve even when most clients perform poorly.We evaluate FedPA on a subset of the MURA dataset for abnormality detection in radiographs of four bone types.Compared to baseline federated learning algorithms such as Federated Averaging(FedAvg),Federated Proximal(FedProx),Federated Stochastic Gradient Descent(FedSGD),and Federated Batch Normalization(FedBN),FedPA consistently ranks first or second across key performance metrics,particularly in accuracy,F1 score,and recall.Moreover,FedPA demonstrates notable efficiency,achieving the lowest average round time(≈2270 s)and minimal memory usage(≈645.58 MB),all without relying on GPU resources.These results highlight FedPA’s effectiveness in improving global model quality while reducing computational overhead,positioning it as a promising approach for real-world federated learning applications in resource-constrained environments.
文摘https://www.sciencedirect.com/journal/energy-and-buildings/vol/354/suppl/C Volume 354,1 March 2026[OA](1)Rule-based peak shaving strategy with battery storage:Evaluating socio-economic impacts in regional grids by Md Masud Rana,Huadong Mo,Mohd Fakhizan Romlie,et al,Article 116983 Abstract:The Australian electricity framework includes several demand tariff structures,with peak demand charges constituting a significant cost component for consumers.Efficient peak load shaving techniques can mitigate these charges,leading to substantial economic benefits to the power suppliers,consumers,and society.
