Amazon Web Services(AWS)Cloud Trail auditing service provides detailed records of operational and security events,enabling cloud administrators to monitor user activity and manage compliance.Although signaturebased th...Amazon Web Services(AWS)Cloud Trail auditing service provides detailed records of operational and security events,enabling cloud administrators to monitor user activity and manage compliance.Although signaturebased threat detection methods have been enhanced with machine learning and Large Language Models(LLMs),these approaches remain limited in addressing emerging threats.This study evaluates a two-step Retrieval Augmented Generation(RAG)approach using Gemini 2.5 Pro to enhance threat detection accuracy and contextual relevance.The RAG system integrates external cybersecurity knowledge sources including the MITRE ATT&CK framework,AWS Threat Technique Catalogue,and threat reports to overcome limitations of static pre-trained LLMs.We constructed an evaluation dataset of 200 unique CloudTrail events(122 malicious,78 benign)using the Stratus Red Team adversary emulation framework,covering 9 MITRE ATT&CK techniques across 8 tactics.Events were sampled from 1724 total events using stratified sampling.Ground truth labels were created through systematic expert annotation with 90%inter-annotator agreement.The RAG-enabled model achieved estimated 78%accuracy,85%precision,and 79%F1-score,representing 70.5%accuracy improvement and 76.4%F1-score improvement over baseline Gemini 2.5 Pro(46%accuracy,45%F1-score).Performance are based on evaluation results on 200-event dataset.Cost-latency analysis revealed processing time of 4.1 s and cost of$0.00376 per event,comparable to commercial SIEM solutions while providing superior MITRE ATT&CK attribution.The findings demonstrate that RAG substantially enhances context-aware threat detection,providing actionable insights for cloud security operations.展开更多
Saud Khan,a Pakistani physician,collected his work and residence permits at the Yangpu Government Service Centre in Danzhou City,Hainan Province,on 18 December 2025.Khan had arrived in Hainan three months earlier to p...Saud Khan,a Pakistani physician,collected his work and residence permits at the Yangpu Government Service Centre in Danzhou City,Hainan Province,on 18 December 2025.Khan had arrived in Hainan three months earlier to participate in a medical training programme at Hainan Western Central Hospital.By the time the programme concluded,he had made up his mind to stay and broaden his professional experience and long-term career prospects in Hainan.展开更多
Announcements for this section should be submitted in the correct format at least 3 months before the required date of publication.This list is provided as a service to readers;inclusion does not imply endorsement by ...Announcements for this section should be submitted in the correct format at least 3 months before the required date of publication.This list is provided as a service to readers;inclusion does not imply endorsement by the Hepatobiliary&Pancreatic Diseases International.展开更多
In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation ...In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation is provided”and that“the validation step is largely overlooked”.This assertion may have been true several years ago,for example,when Ochoa and Urbina-Cardona(2017)made a similar observation.However,there has been much work on ES model validation over the last decade.展开更多
As the sunlight scattered on the sea of Guanyinshan in Xiamen,a space that bridges creativity and industry opened its door to the world.On December 15th,following a ribbon-cutting and unveiling ceremony,YKK Xiamen Gua...As the sunlight scattered on the sea of Guanyinshan in Xiamen,a space that bridges creativity and industry opened its door to the world.On December 15th,following a ribbon-cutting and unveiling ceremony,YKK Xiamen Guanyinshan Showroom,the brand's second and largest comprehensive showroom,was officially inaugurated.This showroom is more than a product display window,it is an"Inspiration Hub"integrating exhibition,co-creation,and service.Its launch signifies YKK's progression in the Chinese market from“building an efficient product proposal system”to a new stage of“deep collaborative co-creation.”展开更多
Common mental disorders(CMDs),such as depressive and anxiety disorders,constitute a significant public health problem in low-and middle-income countries,such as India,where they rank among the leading causes of disabi...Common mental disorders(CMDs),such as depressive and anxiety disorders,constitute a significant public health problem in low-and middle-income countries,such as India,where they rank among the leading causes of disability and impaired quality of life.Outcomes are further compromised by a large treatment gap,poor adherence to therapeutic regimens,and high attrition rates.The prevalence and severity of CMDs are disproportionately higher in women.Additionally,structural factors influencing healthcare access,along with sociocultural factors,such as gender-based violence,limited autonomy in healthcare decisions,and greater levels of discrimination and stigma,result in poorer outcomes among women with CMDs.Therefore,there is a pressing need for care packages that are culturally sensitive,gender-responsive,and designed to address these structural and sociocultural factors,as highlighted in the literature from India.展开更多
Artificial intelligence(AI)is reshaping financial systems and services,as intelligent AI agents increasingly form the foundation of autonomous,goal-driven systems capable of reasoning,learning,and action.This review s...Artificial intelligence(AI)is reshaping financial systems and services,as intelligent AI agents increasingly form the foundation of autonomous,goal-driven systems capable of reasoning,learning,and action.This review synthesizes recent research and developments in the application of AI agents across core financial domains.Specifically,it covers the deployment of agent-based AI in algorithmic trading,fraud detection,credit risk assessment,roboadvisory,and regulatory compliance(RegTech).The review focuses on advanced agent-based methodologies,including reinforcement learning,multi-agent systems,and autonomous decision-making frameworks,particularly those leveraging large language models(LLMs),contrasting these with traditional AI or purely statistical models.Our primary goals are to consolidate current knowledge,identify significant trends and architectural approaches,review the practical efficiency and impact of current applications,and delineate key challenges and promising future research directions.The increasing sophistication of AI agents offers unprecedented opportunities for innovation in finance,yet presents complex technical,ethical,and regulatory challenges that demand careful consideration and proactive strategies.This review aims to provide a comprehensive understanding of this rapidly evolving landscape,highlighting the role of agent-based AI in the ongoing transformation of the financial industry,and is intended to serve financial institutions,regulators,investors,analysts,researchers,and other key stakeholders in the financial ecosystem.展开更多
Lhasa,one of the world's highest cities,confronts the challenge of harmonizing cultural heritage preservation with ecological protection.Assessing the spatiotemporal dynamics of ecosystem service value(ESV)in its ...Lhasa,one of the world's highest cities,confronts the challenge of harmonizing cultural heritage preservation with ecological protection.Assessing the spatiotemporal dynamics of ecosystem service value(ESV)in its central urban area is therefore critical for informing future urban planning and land management.This study systematically analyzed land use evolution,the spatiotemporal characteristics of ecosystem services,and ecological network construction within Lhasa's central urban area.It integrated multi-source data,including Landsat remote sensing imagery from 2000,2010,and 2023,with multiple modeling methods such as the InVEST model,MaxEnt for cultural service assessment,the Minimum Cumulative Resistance(MCR)model,and circuit theory.Based on these analyses,optimization strategies were proposed.The results indicate that from 2000 to 2023,areas of cultivated land,grassland,and water bodies decreased by 7.47%,6.85%,and 0.68%,respectively,while wetland and forest areas expanded by 1.44%and 0.64%.Construction land exhibited significant expansion(12.94%),leading to an overall ESV reduction of 462.8×10^(5)yuan.Vegetation coverage was identified as the pivotal factor influencing ESV distribution,with higher values concentrated in the Lhasa River Basin and near the Lhalu Wetland,diminishing towards the urban core.Furthermore,spatial autocorrelation analysis revealed significant positive spatial clustering,with low-low aggregation in the eastern and central regions and high-high aggregation in the Lhasa River Basin and its surrounding water bodies.Moreover,based on a comprehensive ecosystem service assessment,11 ecological source sites were identified,primarily in the southwestern mountains and northeastern foothills.A comprehensive resistance surface,incorporating factors such as elevation,Normalized Difference Vegetation Index(NDVI),and land use,facilitated the extraction of 23 potential ecological corridors totaling 124.96 km in length.Topological network analysis indicated high redundancy and connectivity;however,marginal source sites relying on single connections exhibited significant vulnerability to rupture.Additionally,the application of circuit theory identified 30 ecological pinch points(current density≥1.5 A/km^(2))and 23 obstacle points,revealing significant blockages to ecological flow along the Qinghai-Xizang Highway,within the old city,and in other areas of high-intensity human activity.To address the identified network deficiencies—‘scattered cores,fragmented corridors,and insufficient resilience’—this study proposes an optimization strategy conceptualized as‘one vein,three corridors,and multiple cores’.Recommendations for enhancing network resilience include the delineation of ecological protection red lines,the integration of plateau-adapted technologies,and the fostering of community governance mechanisms.This approach aims to provide a scientific basis for constructing an ecological security pattern and promoting sustainable development in plateau cities.Ultimately,this research contributes to the enhancement of ecological well-being in the Himalayan region.展开更多
Identifying the community structure of complex networks is crucial to extracting insights and understanding network properties.Although several community detection methods have been proposed,many are unsuitable for so...Identifying the community structure of complex networks is crucial to extracting insights and understanding network properties.Although several community detection methods have been proposed,many are unsuitable for social networks due to significant limitations.Specifically,most approaches depend mainly on user-user structural links while overlooking service-centric,semantic,and multi-attribute drivers of community formation,and they also lack flexible filtering mechanisms for large-scale,service-oriented settings.Our proposed approach,called community discovery-based service(CDBS),leverages user profiles and their interactions with consulted web services.The method introduces a novel similarity measure,global similarity interaction profile(GSIP),which goes beyond typical similarity measures by unifying user and service profiles for all attributes types into a coherent representation,thereby clarifying its novelty and contribution.It applies multiple filtering criteria related to user attributes,accessed services,and interaction patterns.Experimental comparisons against Louvain,Hierarchical Agglomerative Clustering,Label Propagation and Infomap show that CDBS reveals the higher performance as it achieves 0.74 modularity,0.13 conductance,0.77 coverage,and significantly fast response time of 9.8 s,even with 10,000 users and 400 services.Moreover,community discoverybased service consistently detects a larger number of communities with distinct topics of interest,underscoring its capacity to generate detailed and efficient structures in complex networks.These results confirm both the efficiency and effectiveness of the proposed method.Beyond controlled evaluation,communities discovery based service is applicable to targeted recommendations,group-oriented marketing,access control,and service personalization,where communities are shaped not only by user links but also by service engagement.展开更多
The Internet of Things(IoT)ecosystem is inherently heterogeneous,comprising diverse devices that must interoperate seamlessly to enable federated message and data exchange.However,as the number of service requests gro...The Internet of Things(IoT)ecosystem is inherently heterogeneous,comprising diverse devices that must interoperate seamlessly to enable federated message and data exchange.However,as the number of service requests grows,existing approaches suffer from increased discovery time and degraded Quality of Service(QoS).Moreover,the massive data generated by heterogeneous IoT devices often contain redundancy and noise,posing challenges to efficient data management.To address these issues,this paper proposes a lightweight ontology-based architecture that enhances service discovery and QoS-aware semantic data management.The architecture employs Modified-Ordered Points to Identify theClustering Structure(M-OPTICS)to cluster and eliminate redundant IoT data.The clustered data are then modelled into a lightweight ontology,enabling semantic relationship inference and rule generation through an embedded inference engine.User requests,transmitted via theConstrainedApplication Protocol(CoAP),are semantically enriched and matched to QoS parameters using Dynamic Shannon Entropy optimized with the Salp Swarm Algorithm.Semantic matching is further refined using a bidirectional recurrent neural network(Bi-RNN),while a State–Action–Reward–State–Action(SARSA)reinforcement learning model dynamically defines and updates semantic rules to retrieve themost recent and relevant data across heterogeneous devices.Experimental results demonstrate that the proposed architecture outperforms existing methods in terms of response time,service delay,execution time,precision,recall,and F-score under varying CoAP request loads and communication overheads.The results confirm the effectiveness of the proposed lightweight ontology architecture for service discovery and data management in heterogeneous IoT environments.展开更多
With the accelerating aging process of China’s population,the demand for community elderly care services has shown diversified and personalized characteristics.However,problems such as insufficient total care service...With the accelerating aging process of China’s population,the demand for community elderly care services has shown diversified and personalized characteristics.However,problems such as insufficient total care service resources,uneven distribution,and prominent supply-demand contradictions have seriously affected service quality.Big data technology,with core advantages including data collection,analysis and mining,and accurate prediction,provides a new solution for the allocation of community elderly care service resources.This paper systematically studies the application value of big data technology in the allocation of community elderly care service resources from three aspects:resource allocation efficiency,service accuracy,and management intelligence.Combined with practical needs,it proposes optimal allocation strategies such as building a big data analysis platform and accurately grasping the elderly’s care needs,striving to provide operable path references for the construction of community elderly care service systems,promoting the early realization of the elderly care service goal of“adequate support and proper care for the elderly”,and boosting the high-quality development of China’s elderly care service industry.展开更多
This paper proposes a threat assessment framework for non-cooperative satellites by analyzing their motion characteristics,developing a quantitative evaluation methodology,and demonstrating its effectiveness via repre...This paper proposes a threat assessment framework for non-cooperative satellites by analyzing their motion characteristics,developing a quantitative evaluation methodology,and demonstrating its effectiveness via representative scenarios with neural network acceleration.The framework first establishes a threat evaluation model that integrates three core parameters:capability,opportunity,and hidden values.Subsequently,this research systematically investigates the critical role of transfer windows in threat quantification and introduces a transfer window-based threat assessment approach.The proposed methodology is validated through multiple representative scenarios,with simulation results demonstrating superior performance compared to conventional methods relying solely on optimal transfer windows or minimum distance metrics,enabling more nuanced threat ranking in scenarios where traditional techniques prove inadequate.To address computational demands,a neural networkbased approximation system is implemented to achieve a 25,200×speedup(0.005 s vs.baseline 126 s per 1000-sample batch)through parallel processing,maintaining 99.3%accuracy.Finally,the study explores the framework's extensibility to diverse NCS objectives.It identifies discrepancies between intention inference models and threat evaluation paradigms,providing methodological insights for next-generation space domain awareness systems.展开更多
Northwest China serves as a critical ecological barrier region for maintaining national water,energy,and food security,as well as transboundary ecological governance.However,under the dual pressures of climate change ...Northwest China serves as a critical ecological barrier region for maintaining national water,energy,and food security,as well as transboundary ecological governance.However,under the dual pressures of climate change and human activities,ecosystem services(ESs)are facing severe challenges in this region.Based on multi-source remote sensing and statistical data during 2000–2020,this study investigated the spatiotemporal evolution characteristics of four key ESs(water yield,habitat quality,carbon storage,and food provisioning)in Northwest China using the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)model.Integrating morphological spatial pattern analysis(MSPA)and circuit theory,we identified ecological sources,corridors,pinch points,and barriers,and further designed three optimization scenarios(bottleneck optimization,high-resistance corridor buffering,and barrier removal optimization)to enhance landscape connectivity.The results revealed that ES supply and demand exhibited marked spatial heterogeneity,with high-supply areas concentrated in the southeastern sectors.Ecological sources primarily distributed in the southeastern and northern sectors,and ecological resistance surfaces continuously intensified.Water yield and habitat quality demands were increasing,food provisioning demand was decreasing,and carbon storage demand was surging.A total of 61 ecological sources(8%of the study area),142 ecological corridors(24,957 km in total length),237 ecological pinch points,and 89 barrier zones were identified.Among the three optimization scenarios,barrier removal achieved optimal connectivity improvement across all distance thresholds,with the probability of connectivity index improvement reaching up to 4%.This study provides scientific foundations and spatial decision support for ecological network optimization and sustainable governance in arid and semi-arid areas.展开更多
Purpose-This study investigates the impact of flagship trains on high-speed railway capacity utilization and develops a brand value-oriented optimization framework that balances service quality enhancement with operat...Purpose-This study investigates the impact of flagship trains on high-speed railway capacity utilization and develops a brand value-oriented optimization framework that balances service quality enhancement with operational efficiency.Design/methodology/approach-A mathematical optimization model based on integer programming is developed,incorporating flagship train constraints into capacity optimization.Case studies compare scenarios with and without flagship train considerations using the Beijing-Shanghai High-Speed Railway data across 20 experimental groups.Findings-Operating flagship trains with hourly departure constraints results in an average decrease of 0.9 trains and an 8.4%reduction in capacity utilization rate.When scheduling 2 flagship trains within a 2-h timeframe,capacity utilization decreases from 86.43%to 83.73%,quantifying the trade-off between brand positioning and operational capacity.Originality/value-This research provides the first quantitative framework for brand value-oriented railway capacity optimization,establishing clear definitions for flagship trains and mathematical foundations for evaluating service quality versus efficiency trade-offs.The findings offer practical decision support for railway operators balancing competitive positioning with capacity maximization.展开更多
Objective:To systematically summarize and evaluate the evidence on discharge preparation services for patients undergoing total knee arthroplasty,providing an evidence-based foundation for developing scientific and st...Objective:To systematically summarize and evaluate the evidence on discharge preparation services for patients undergoing total knee arthroplasty,providing an evidence-based foundation for developing scientific and standardized discharge preparation intervention programs in clinical practice.Methods:Following the“5S”evidence model,literature such as guidelines,expert consensuses,evidence summaries and randomized controlled trials related to discharge preparation services for total knee arthroplasty patients were retrieved from relevant websites and databases,both domestic and international,from database inception to August 31,2025.Two researchers independently screened the literature,conducted quality appraisals,and extracted and synthesized the evidence.Results:A total of 15 articles were included,comprising 3 guidelines,4 expert consensuses,3 evidence summaries,3 systematic reviews and 2 randomized controlled trials.Ultimately,23 pieces of evidence were summarized across five aspects.Conclusion:This study synthesizes the evidence on discharge preparation services for patients undergoing total knee arthroplasty.It is recommended that healthcare professionals apply this evidence in clinical practice,considering specific circumstances and patient needs.展开更多
Extreme heat events contribute to high mortality[1,2]and overwhelm emergency medical services through increased ambulance calls and overcrowded emergency departments.[3]Because morbidity and mortality are directly rel...Extreme heat events contribute to high mortality[1,2]and overwhelm emergency medical services through increased ambulance calls and overcrowded emergency departments.[3]Because morbidity and mortality are directly related to both the degree and duration of hyperthermia,timely recognition and management of heat exhaustion and heat stroke are critical for preventing death and reducing healthcare burdens.展开更多
With the rapid development of the aviation industry,air travel has become one of the most important modes.Improving the service quality of civil aviation airports is crucial to their competitiveness.This study intends...With the rapid development of the aviation industry,air travel has become one of the most important modes.Improving the service quality of civil aviation airports is crucial to their competitiveness.This study intends to develop a scientific and rational evaluation methodology and framework for assessing service quality in civil aviation airports,thereby providing a theoretical foundation and practical guidance for enhancing service standards in the aviation industry.First,the study constructs a CRITIC-bidirectional grey possibility clustering model,which uses the CRITIC method to determine the weights of indicators and integrates the forward grey possibility clustering model and the inverse grey possibility clustering model to determine possibility functions from two perspectives.Second,a service quality evaluation index system for civil airports is constructed from four dimensions,and the weights of each index within the system are subsequently calculated.Finally,the constructed model is applied to evaluate the service quality of nine domestic civil airports.Based on the clustering results,targeted countermeasures and suggestions are proposed.Empirical results demonstrate that,compared to the traditional grey possibility clustering model,the proposed model balances the objectivity of indicator weighting,the objectivity of possibility function construction,and the simplicity of the computational process,thereby possessing significant theoretical and practical implications.展开更多
The concepts of the circular economy(CE)are actively popularized as ways of minimizing waste products and the need to rely on virgin resources.Nevertheless,their sustainability is doubtful at a general level where eco...The concepts of the circular economy(CE)are actively popularized as ways of minimizing waste products and the need to rely on virgin resources.Nevertheless,their sustainability is doubtful at a general level where ecosystem functioning and ecosystem services(ES)are not given explicit attention.This review will combine both conceptual and empirical evidence of the connection between CE interventions and ES outcomes to enable more sustainable management of resources.We describe the effects of the CE strategies on the key environmental pressure pathways,altering ecosystem conditions,and impacting the delivery of regulating,provisioning,and cultural ecosystem services using a pressure condition-service framework.Analysis reveals that demand-side reduction and product life-extension strategies tend to offer more consistent ecosystem service co-benefits than recycling and recovery strategies because they do not involve production,and will cause less disturbance to the upstream environment.Contrastingly,recycling and recovery sustainability performance is highly dependent on the sources of energy,intensity of processing,and the safety of materials.Bio-based circularity has the potential to increase soil functionality and nutrient cycling,and mass application will result in trade-offs in terms of land competition and nutrient leakage.The sectoral analysis identifies the unique opportunities and threats in the agri-food systems,the built environment,plastics and textiles,electronics and critical minerals,and water and wastewater systems in terms of the burden displacement,local environmental pressures,and equity concerns.Harmonized reporting,coupled with supply-chain and spatial ecological assessment,threshold-conscious strategies that promote safe and regenerative circular systems should be put into the line of future research.展开更多
Understanding the scale-dependent dynamics of ecosystem services(ESs)and their socio-ecological drivers is essential for sustainable development.While many studies rely on static or single-scale approaches,this resear...Understanding the scale-dependent dynamics of ecosystem services(ESs)and their socio-ecological drivers is essential for sustainable development.While many studies rely on static or single-scale approaches,this research employs an integrated multi-temporal(2000–2020)and multi-scale(grid,county,and landscape levels)framework to investigate China’s Central Asian frontier,a representative dryland region.We quantified six ESs:habitat quality(HQ),net primary productivity(NPP),carbon sequestration(CS),water yield(WY),soil conservation(SC),and grain production(GP).Furthermore,we explored their interrelationships and identified the drivers influencing these services across different spatial scales.Our results revealed divergent ES trajectories:the declining HQ(−0.03 a^(−1)),NPP(−0.43 t km^(−2)a^(−1)),and SC(−3.41 t ha a^(−1))contrasted with rising WY(+2.33 mm a^(−1)),GP(+0.06 t km^(−2)a^(−1)),and CS(+0.02 t km^(−2)a^(−1)).The ES relationships were predominantly synergistic,while HQ–WY exhibited a trade-off(grid:−0.03;county:−0.02;landscape:−0.03)at temporal dimension but a synergistic relationship(grid:0.45;county:0.92;landscape:0.92)at spatial dimension.As spatial scale increased,SC–CS shifted from synergy(grid:0.001)to trade-off(county:−0.01;landscape:−0.005)in the temporal dimension,while all trade-off relationships in the spatial dimension were transformed into synergies.Key drivers of ES relationships varied with spatial scale:fraction vegetation coverage(FVC)and leaf area index(LAI)at the grid scale,annual precipitation(MAP)and soil moisture(SMA)at the county scale,and population density(POP),gross domestic product(GDP),and silt content(Silt)at the landscape scale.Based on the multi-scale findings,the study divides northern Xinjiang into Grain Priority Region,Ecological Priority Region,and Desert Containment Region,and proposes tailored management recommendations,offering a flexible framework for balancing ecological and socioeconomic needs.展开更多
文摘Amazon Web Services(AWS)Cloud Trail auditing service provides detailed records of operational and security events,enabling cloud administrators to monitor user activity and manage compliance.Although signaturebased threat detection methods have been enhanced with machine learning and Large Language Models(LLMs),these approaches remain limited in addressing emerging threats.This study evaluates a two-step Retrieval Augmented Generation(RAG)approach using Gemini 2.5 Pro to enhance threat detection accuracy and contextual relevance.The RAG system integrates external cybersecurity knowledge sources including the MITRE ATT&CK framework,AWS Threat Technique Catalogue,and threat reports to overcome limitations of static pre-trained LLMs.We constructed an evaluation dataset of 200 unique CloudTrail events(122 malicious,78 benign)using the Stratus Red Team adversary emulation framework,covering 9 MITRE ATT&CK techniques across 8 tactics.Events were sampled from 1724 total events using stratified sampling.Ground truth labels were created through systematic expert annotation with 90%inter-annotator agreement.The RAG-enabled model achieved estimated 78%accuracy,85%precision,and 79%F1-score,representing 70.5%accuracy improvement and 76.4%F1-score improvement over baseline Gemini 2.5 Pro(46%accuracy,45%F1-score).Performance are based on evaluation results on 200-event dataset.Cost-latency analysis revealed processing time of 4.1 s and cost of$0.00376 per event,comparable to commercial SIEM solutions while providing superior MITRE ATT&CK attribution.The findings demonstrate that RAG substantially enhances context-aware threat detection,providing actionable insights for cloud security operations.
文摘Saud Khan,a Pakistani physician,collected his work and residence permits at the Yangpu Government Service Centre in Danzhou City,Hainan Province,on 18 December 2025.Khan had arrived in Hainan three months earlier to participate in a medical training programme at Hainan Western Central Hospital.By the time the programme concluded,he had made up his mind to stay and broaden his professional experience and long-term career prospects in Hainan.
文摘Announcements for this section should be submitted in the correct format at least 3 months before the required date of publication.This list is provided as a service to readers;inclusion does not imply endorsement by the Hepatobiliary&Pancreatic Diseases International.
文摘In their recent paper Pereira et al.(2025)claim that validation is overlooked in mapping and modelling of ecosystem services(ES).They state that“many studies lack critical evaluation of the results and no validation is provided”and that“the validation step is largely overlooked”.This assertion may have been true several years ago,for example,when Ochoa and Urbina-Cardona(2017)made a similar observation.However,there has been much work on ES model validation over the last decade.
文摘As the sunlight scattered on the sea of Guanyinshan in Xiamen,a space that bridges creativity and industry opened its door to the world.On December 15th,following a ribbon-cutting and unveiling ceremony,YKK Xiamen Guanyinshan Showroom,the brand's second and largest comprehensive showroom,was officially inaugurated.This showroom is more than a product display window,it is an"Inspiration Hub"integrating exhibition,co-creation,and service.Its launch signifies YKK's progression in the Chinese market from“building an efficient product proposal system”to a new stage of“deep collaborative co-creation.”
文摘Common mental disorders(CMDs),such as depressive and anxiety disorders,constitute a significant public health problem in low-and middle-income countries,such as India,where they rank among the leading causes of disability and impaired quality of life.Outcomes are further compromised by a large treatment gap,poor adherence to therapeutic regimens,and high attrition rates.The prevalence and severity of CMDs are disproportionately higher in women.Additionally,structural factors influencing healthcare access,along with sociocultural factors,such as gender-based violence,limited autonomy in healthcare decisions,and greater levels of discrimination and stigma,result in poorer outcomes among women with CMDs.Therefore,there is a pressing need for care packages that are culturally sensitive,gender-responsive,and designed to address these structural and sociocultural factors,as highlighted in the literature from India.
基金supported by the Ministry of Education and Science of the Republic of North Macedonia through the project“Utilizing AI and National Large Language Models to Advance Macedonian Language Capabilties”。
文摘Artificial intelligence(AI)is reshaping financial systems and services,as intelligent AI agents increasingly form the foundation of autonomous,goal-driven systems capable of reasoning,learning,and action.This review synthesizes recent research and developments in the application of AI agents across core financial domains.Specifically,it covers the deployment of agent-based AI in algorithmic trading,fraud detection,credit risk assessment,roboadvisory,and regulatory compliance(RegTech).The review focuses on advanced agent-based methodologies,including reinforcement learning,multi-agent systems,and autonomous decision-making frameworks,particularly those leveraging large language models(LLMs),contrasting these with traditional AI or purely statistical models.Our primary goals are to consolidate current knowledge,identify significant trends and architectural approaches,review the practical efficiency and impact of current applications,and delineate key challenges and promising future research directions.The increasing sophistication of AI agents offers unprecedented opportunities for innovation in finance,yet presents complex technical,ethical,and regulatory challenges that demand careful consideration and proactive strategies.This review aims to provide a comprehensive understanding of this rapidly evolving landscape,highlighting the role of agent-based AI in the ongoing transformation of the financial industry,and is intended to serve financial institutions,regulators,investors,analysts,researchers,and other key stakeholders in the financial ecosystem.
基金National Natural Science Foundation of China Youth Fund Project:Research on the Construction of Ecological Security Pattern in the Transition Zone of Nature Reserves along the Sichuan-Xizang Railway(Western Sichuan Section)(51908470).
文摘Lhasa,one of the world's highest cities,confronts the challenge of harmonizing cultural heritage preservation with ecological protection.Assessing the spatiotemporal dynamics of ecosystem service value(ESV)in its central urban area is therefore critical for informing future urban planning and land management.This study systematically analyzed land use evolution,the spatiotemporal characteristics of ecosystem services,and ecological network construction within Lhasa's central urban area.It integrated multi-source data,including Landsat remote sensing imagery from 2000,2010,and 2023,with multiple modeling methods such as the InVEST model,MaxEnt for cultural service assessment,the Minimum Cumulative Resistance(MCR)model,and circuit theory.Based on these analyses,optimization strategies were proposed.The results indicate that from 2000 to 2023,areas of cultivated land,grassland,and water bodies decreased by 7.47%,6.85%,and 0.68%,respectively,while wetland and forest areas expanded by 1.44%and 0.64%.Construction land exhibited significant expansion(12.94%),leading to an overall ESV reduction of 462.8×10^(5)yuan.Vegetation coverage was identified as the pivotal factor influencing ESV distribution,with higher values concentrated in the Lhasa River Basin and near the Lhalu Wetland,diminishing towards the urban core.Furthermore,spatial autocorrelation analysis revealed significant positive spatial clustering,with low-low aggregation in the eastern and central regions and high-high aggregation in the Lhasa River Basin and its surrounding water bodies.Moreover,based on a comprehensive ecosystem service assessment,11 ecological source sites were identified,primarily in the southwestern mountains and northeastern foothills.A comprehensive resistance surface,incorporating factors such as elevation,Normalized Difference Vegetation Index(NDVI),and land use,facilitated the extraction of 23 potential ecological corridors totaling 124.96 km in length.Topological network analysis indicated high redundancy and connectivity;however,marginal source sites relying on single connections exhibited significant vulnerability to rupture.Additionally,the application of circuit theory identified 30 ecological pinch points(current density≥1.5 A/km^(2))and 23 obstacle points,revealing significant blockages to ecological flow along the Qinghai-Xizang Highway,within the old city,and in other areas of high-intensity human activity.To address the identified network deficiencies—‘scattered cores,fragmented corridors,and insufficient resilience’—this study proposes an optimization strategy conceptualized as‘one vein,three corridors,and multiple cores’.Recommendations for enhancing network resilience include the delineation of ecological protection red lines,the integration of plateau-adapted technologies,and the fostering of community governance mechanisms.This approach aims to provide a scientific basis for constructing an ecological security pattern and promoting sustainable development in plateau cities.Ultimately,this research contributes to the enhancement of ecological well-being in the Himalayan region.
文摘Identifying the community structure of complex networks is crucial to extracting insights and understanding network properties.Although several community detection methods have been proposed,many are unsuitable for social networks due to significant limitations.Specifically,most approaches depend mainly on user-user structural links while overlooking service-centric,semantic,and multi-attribute drivers of community formation,and they also lack flexible filtering mechanisms for large-scale,service-oriented settings.Our proposed approach,called community discovery-based service(CDBS),leverages user profiles and their interactions with consulted web services.The method introduces a novel similarity measure,global similarity interaction profile(GSIP),which goes beyond typical similarity measures by unifying user and service profiles for all attributes types into a coherent representation,thereby clarifying its novelty and contribution.It applies multiple filtering criteria related to user attributes,accessed services,and interaction patterns.Experimental comparisons against Louvain,Hierarchical Agglomerative Clustering,Label Propagation and Infomap show that CDBS reveals the higher performance as it achieves 0.74 modularity,0.13 conductance,0.77 coverage,and significantly fast response time of 9.8 s,even with 10,000 users and 400 services.Moreover,community discoverybased service consistently detects a larger number of communities with distinct topics of interest,underscoring its capacity to generate detailed and efficient structures in complex networks.These results confirm both the efficiency and effectiveness of the proposed method.Beyond controlled evaluation,communities discovery based service is applicable to targeted recommendations,group-oriented marketing,access control,and service personalization,where communities are shaped not only by user links but also by service engagement.
文摘The Internet of Things(IoT)ecosystem is inherently heterogeneous,comprising diverse devices that must interoperate seamlessly to enable federated message and data exchange.However,as the number of service requests grows,existing approaches suffer from increased discovery time and degraded Quality of Service(QoS).Moreover,the massive data generated by heterogeneous IoT devices often contain redundancy and noise,posing challenges to efficient data management.To address these issues,this paper proposes a lightweight ontology-based architecture that enhances service discovery and QoS-aware semantic data management.The architecture employs Modified-Ordered Points to Identify theClustering Structure(M-OPTICS)to cluster and eliminate redundant IoT data.The clustered data are then modelled into a lightweight ontology,enabling semantic relationship inference and rule generation through an embedded inference engine.User requests,transmitted via theConstrainedApplication Protocol(CoAP),are semantically enriched and matched to QoS parameters using Dynamic Shannon Entropy optimized with the Salp Swarm Algorithm.Semantic matching is further refined using a bidirectional recurrent neural network(Bi-RNN),while a State–Action–Reward–State–Action(SARSA)reinforcement learning model dynamically defines and updates semantic rules to retrieve themost recent and relevant data across heterogeneous devices.Experimental results demonstrate that the proposed architecture outperforms existing methods in terms of response time,service delay,execution time,precision,recall,and F-score under varying CoAP request loads and communication overheads.The results confirm the effectiveness of the proposed lightweight ontology architecture for service discovery and data management in heterogeneous IoT environments.
文摘With the accelerating aging process of China’s population,the demand for community elderly care services has shown diversified and personalized characteristics.However,problems such as insufficient total care service resources,uneven distribution,and prominent supply-demand contradictions have seriously affected service quality.Big data technology,with core advantages including data collection,analysis and mining,and accurate prediction,provides a new solution for the allocation of community elderly care service resources.This paper systematically studies the application value of big data technology in the allocation of community elderly care service resources from three aspects:resource allocation efficiency,service accuracy,and management intelligence.Combined with practical needs,it proposes optimal allocation strategies such as building a big data analysis platform and accurately grasping the elderly’s care needs,striving to provide operable path references for the construction of community elderly care service systems,promoting the early realization of the elderly care service goal of“adequate support and proper care for the elderly”,and boosting the high-quality development of China’s elderly care service industry.
基金supported by the National Key R&D Programof China:Gravitational Wave Detection Project(Grant Nos.2021YFC2026,2021YFC2202601,2021YFC2202603)the Na-tional Natural Science Foundation of China(Grant Nos.12172288and 12472046)。
文摘This paper proposes a threat assessment framework for non-cooperative satellites by analyzing their motion characteristics,developing a quantitative evaluation methodology,and demonstrating its effectiveness via representative scenarios with neural network acceleration.The framework first establishes a threat evaluation model that integrates three core parameters:capability,opportunity,and hidden values.Subsequently,this research systematically investigates the critical role of transfer windows in threat quantification and introduces a transfer window-based threat assessment approach.The proposed methodology is validated through multiple representative scenarios,with simulation results demonstrating superior performance compared to conventional methods relying solely on optimal transfer windows or minimum distance metrics,enabling more nuanced threat ranking in scenarios where traditional techniques prove inadequate.To address computational demands,a neural networkbased approximation system is implemented to achieve a 25,200×speedup(0.005 s vs.baseline 126 s per 1000-sample batch)through parallel processing,maintaining 99.3%accuracy.Finally,the study explores the framework's extensibility to diverse NCS objectives.It identifies discrepancies between intention inference models and threat evaluation paradigms,providing methodological insights for next-generation space domain awareness systems.
基金supported by the Tianchi Talent Introduction Program of Xinjiang Uygur Autonomous Region(2024000104)the National Key Research and Development Program of China(2023YFF0805603).
文摘Northwest China serves as a critical ecological barrier region for maintaining national water,energy,and food security,as well as transboundary ecological governance.However,under the dual pressures of climate change and human activities,ecosystem services(ESs)are facing severe challenges in this region.Based on multi-source remote sensing and statistical data during 2000–2020,this study investigated the spatiotemporal evolution characteristics of four key ESs(water yield,habitat quality,carbon storage,and food provisioning)in Northwest China using the Integrated Valuation of Ecosystem Services and Tradeoffs(InVEST)model.Integrating morphological spatial pattern analysis(MSPA)and circuit theory,we identified ecological sources,corridors,pinch points,and barriers,and further designed three optimization scenarios(bottleneck optimization,high-resistance corridor buffering,and barrier removal optimization)to enhance landscape connectivity.The results revealed that ES supply and demand exhibited marked spatial heterogeneity,with high-supply areas concentrated in the southeastern sectors.Ecological sources primarily distributed in the southeastern and northern sectors,and ecological resistance surfaces continuously intensified.Water yield and habitat quality demands were increasing,food provisioning demand was decreasing,and carbon storage demand was surging.A total of 61 ecological sources(8%of the study area),142 ecological corridors(24,957 km in total length),237 ecological pinch points,and 89 barrier zones were identified.Among the three optimization scenarios,barrier removal achieved optimal connectivity improvement across all distance thresholds,with the probability of connectivity index improvement reaching up to 4%.This study provides scientific foundations and spatial decision support for ecological network optimization and sustainable governance in arid and semi-arid areas.
基金funded by the Science and Technology Research and Development Program Project of China Railway Group Co.,Ltd,grant number P2024X002the China Academy of Railway Sciences Corporation Limited,grant number 2024YJ154.
文摘Purpose-This study investigates the impact of flagship trains on high-speed railway capacity utilization and develops a brand value-oriented optimization framework that balances service quality enhancement with operational efficiency.Design/methodology/approach-A mathematical optimization model based on integer programming is developed,incorporating flagship train constraints into capacity optimization.Case studies compare scenarios with and without flagship train considerations using the Beijing-Shanghai High-Speed Railway data across 20 experimental groups.Findings-Operating flagship trains with hourly departure constraints results in an average decrease of 0.9 trains and an 8.4%reduction in capacity utilization rate.When scheduling 2 flagship trains within a 2-h timeframe,capacity utilization decreases from 86.43%to 83.73%,quantifying the trade-off between brand positioning and operational capacity.Originality/value-This research provides the first quantitative framework for brand value-oriented railway capacity optimization,establishing clear definitions for flagship trains and mathematical foundations for evaluating service quality versus efficiency trade-offs.The findings offer practical decision support for railway operators balancing competitive positioning with capacity maximization.
文摘Objective:To systematically summarize and evaluate the evidence on discharge preparation services for patients undergoing total knee arthroplasty,providing an evidence-based foundation for developing scientific and standardized discharge preparation intervention programs in clinical practice.Methods:Following the“5S”evidence model,literature such as guidelines,expert consensuses,evidence summaries and randomized controlled trials related to discharge preparation services for total knee arthroplasty patients were retrieved from relevant websites and databases,both domestic and international,from database inception to August 31,2025.Two researchers independently screened the literature,conducted quality appraisals,and extracted and synthesized the evidence.Results:A total of 15 articles were included,comprising 3 guidelines,4 expert consensuses,3 evidence summaries,3 systematic reviews and 2 randomized controlled trials.Ultimately,23 pieces of evidence were summarized across five aspects.Conclusion:This study synthesizes the evidence on discharge preparation services for patients undergoing total knee arthroplasty.It is recommended that healthcare professionals apply this evidence in clinical practice,considering specific circumstances and patient needs.
文摘Extreme heat events contribute to high mortality[1,2]and overwhelm emergency medical services through increased ambulance calls and overcrowded emergency departments.[3]Because morbidity and mortality are directly related to both the degree and duration of hyperthermia,timely recognition and management of heat exhaustion and heat stroke are critical for preventing death and reducing healthcare burdens.
基金support supplied by the National Natural Science Foundation of China(Nos.72571136,72271120)the Ministry of Education of the People’s Republic of China Humanities and Social Science project(No.24YJA630087)。
文摘With the rapid development of the aviation industry,air travel has become one of the most important modes.Improving the service quality of civil aviation airports is crucial to their competitiveness.This study intends to develop a scientific and rational evaluation methodology and framework for assessing service quality in civil aviation airports,thereby providing a theoretical foundation and practical guidance for enhancing service standards in the aviation industry.First,the study constructs a CRITIC-bidirectional grey possibility clustering model,which uses the CRITIC method to determine the weights of indicators and integrates the forward grey possibility clustering model and the inverse grey possibility clustering model to determine possibility functions from two perspectives.Second,a service quality evaluation index system for civil airports is constructed from four dimensions,and the weights of each index within the system are subsequently calculated.Finally,the constructed model is applied to evaluate the service quality of nine domestic civil airports.Based on the clustering results,targeted countermeasures and suggestions are proposed.Empirical results demonstrate that,compared to the traditional grey possibility clustering model,the proposed model balances the objectivity of indicator weighting,the objectivity of possibility function construction,and the simplicity of the computational process,thereby possessing significant theoretical and practical implications.
文摘The concepts of the circular economy(CE)are actively popularized as ways of minimizing waste products and the need to rely on virgin resources.Nevertheless,their sustainability is doubtful at a general level where ecosystem functioning and ecosystem services(ES)are not given explicit attention.This review will combine both conceptual and empirical evidence of the connection between CE interventions and ES outcomes to enable more sustainable management of resources.We describe the effects of the CE strategies on the key environmental pressure pathways,altering ecosystem conditions,and impacting the delivery of regulating,provisioning,and cultural ecosystem services using a pressure condition-service framework.Analysis reveals that demand-side reduction and product life-extension strategies tend to offer more consistent ecosystem service co-benefits than recycling and recovery strategies because they do not involve production,and will cause less disturbance to the upstream environment.Contrastingly,recycling and recovery sustainability performance is highly dependent on the sources of energy,intensity of processing,and the safety of materials.Bio-based circularity has the potential to increase soil functionality and nutrient cycling,and mass application will result in trade-offs in terms of land competition and nutrient leakage.The sectoral analysis identifies the unique opportunities and threats in the agri-food systems,the built environment,plastics and textiles,electronics and critical minerals,and water and wastewater systems in terms of the burden displacement,local environmental pressures,and equity concerns.Harmonized reporting,coupled with supply-chain and spatial ecological assessment,threshold-conscious strategies that promote safe and regenerative circular systems should be put into the line of future research.
基金National Natural Science Foundation of China,No.42377302Ministry of Science and Technology of the People’s Republic of China,No.2022XJKK0904State Key Laboratory of Soil and Sustainable Agriculture,No.SKLSSA25K03。
文摘Understanding the scale-dependent dynamics of ecosystem services(ESs)and their socio-ecological drivers is essential for sustainable development.While many studies rely on static or single-scale approaches,this research employs an integrated multi-temporal(2000–2020)and multi-scale(grid,county,and landscape levels)framework to investigate China’s Central Asian frontier,a representative dryland region.We quantified six ESs:habitat quality(HQ),net primary productivity(NPP),carbon sequestration(CS),water yield(WY),soil conservation(SC),and grain production(GP).Furthermore,we explored their interrelationships and identified the drivers influencing these services across different spatial scales.Our results revealed divergent ES trajectories:the declining HQ(−0.03 a^(−1)),NPP(−0.43 t km^(−2)a^(−1)),and SC(−3.41 t ha a^(−1))contrasted with rising WY(+2.33 mm a^(−1)),GP(+0.06 t km^(−2)a^(−1)),and CS(+0.02 t km^(−2)a^(−1)).The ES relationships were predominantly synergistic,while HQ–WY exhibited a trade-off(grid:−0.03;county:−0.02;landscape:−0.03)at temporal dimension but a synergistic relationship(grid:0.45;county:0.92;landscape:0.92)at spatial dimension.As spatial scale increased,SC–CS shifted from synergy(grid:0.001)to trade-off(county:−0.01;landscape:−0.005)in the temporal dimension,while all trade-off relationships in the spatial dimension were transformed into synergies.Key drivers of ES relationships varied with spatial scale:fraction vegetation coverage(FVC)and leaf area index(LAI)at the grid scale,annual precipitation(MAP)and soil moisture(SMA)at the county scale,and population density(POP),gross domestic product(GDP),and silt content(Silt)at the landscape scale.Based on the multi-scale findings,the study divides northern Xinjiang into Grain Priority Region,Ecological Priority Region,and Desert Containment Region,and proposes tailored management recommendations,offering a flexible framework for balancing ecological and socioeconomic needs.
