Succinonitrile(SN)-based polymer plastic crystal electrolytes(PPCEs)are regarded as promising candidates for lithium metal batteries but suffer from serious side reactions with Li metal.Herein,we propose a multi-dimen...Succinonitrile(SN)-based polymer plastic crystal electrolytes(PPCEs)are regarded as promising candidates for lithium metal batteries but suffer from serious side reactions with Li metal.Herein,we propose a multi-dimensional optimization strategy to alleviate the side reactions between SN and Li metal,and develop a highly stable poly-vinylethylene carbonate-based PPCE(PPCE-VEC).Moreover,we identify the intrinsic factors of multi-dimensional polymer structures on the electrolyte stability by three typical classes of polyesters.The PPCE-VEC constructed by in situ polymerization exhibits much better stability than poly-vinylene carbonate-based PPCE(PPCE-VCA)and poly-trifluoroethyl acrylate-based PPCE(PPCE-TFA),which is verified by its fewer SN-decomposition species in X-ray photoelectron spectroscopy(XPS)and outstanding full cell performance.The PPCE-VEC-enabled LiNi_(0.6)Co_(0.2)Mn_(0.2)O_(2)full cell achieve 73.7%capacity retention after 1400 cycles,which outperforms PPCE-VCA-and PPCE-TFA-enabled full cells(61.9%and 46.9%).Spectral analysis and theoretical calculation reveal that the high solvation ability of the carbonyl site,flexible polymer chain,and homogeneous electrolyte phase of PPCE-VEC are favorable to maximizing competition coordination with Li^(+)to weaken the Li^(+)–SN binding and shape an anion-rich solvation structure.This optimized polymer-involved Li^(+)solvation enhances SN stability and facilitates the formation of B/F enriched solid-electrolyte interphase(SEI),thus significantly improving PPCE stability.展开更多
Evaluating Unmanned Aerial Vehicle(UAV)systems within a System-of-Systems(SoS)environment helps clarify their contribution to the overall combat capability and supports effectiveness-oriented system optimization.When ...Evaluating Unmanned Aerial Vehicle(UAV)systems within a System-of-Systems(SoS)environment helps clarify their contribution to the overall combat capability and supports effectiveness-oriented system optimization.When assessing decision systems in such an environment,cross-level modeling and simulation are required,which often face a trade-off between low modeling cost and high simulation accuracy,while the credibility of results remains challenging to ensure.To address these issues,this study proposes a hybrid-granularity Hardware-In-the-Loop(HIL)SoS environment construction method based on Graphical Evaluation and Review Technique(GERT).The method employs GERT to analyze the relationships between simulation systems,the System Under Test(SUT),and mission outcomes,thereby determining the required model precision for different systems.A dynamic resource allocation algorithm is applied to adjust model granularity on demand,ensuring high-fidelity simulation under constrained total cost.Additionally,GERT estimates the computational frequency and communication bandwidth requirements of the SUT,guiding hardware selection to enhance simulation credibility.A UAV maritime combat case study was conducted for validation.The results demonstrate that,compared to the flat modeling approach,the hybrid-granularity scenario based on GERT analysis achieves higher simulation accuracy with lower overall model complexity.The coefficient of variation in evaluation results significantly decreases in HIL simulations compared to virtual simulations,confirming improved credibility.Under the hybrid-granularity HIL scenario,the decision system was evaluated from an effectiveness perspective,identifying the most sensitive performance parameter.Subsequent targeted optimization led to an 11.90%improvement in effectiveness,validating the method's practical utility.展开更多
Earthquakes are highly destructive spatio-temporal phenomena whose analysis is essential for disaster preparedness and risk mitigation.Modern seismological research produces vast volumes of heterogeneous data from sei...Earthquakes are highly destructive spatio-temporal phenomena whose analysis is essential for disaster preparedness and risk mitigation.Modern seismological research produces vast volumes of heterogeneous data from seismic networks,satellite observations,and geospatial repositories,creating the need for scalable infrastructures capable of integrating and analyzing such data to support intelligent decision-making.Data warehousing technologies provide a robust foundation for this purpose;however,existing earthquake-oriented data warehouses remain limited,often relying on simplified schemas,domain-specific analytics,or cataloguing efforts.This paper presents the design and implementation of a spatio-temporal data warehouse for seismic activity.The framework integrates spatial and temporal dimensions in a unified schema and introduces a novel array-based approach for managing many-to-many relationships between facts and dimensions without intermediate bridge tables.A comparative evaluation against a conventional bridge-table schema demonstrates that the array-based design improves fact-centric query performance,while the bridge-table schema remains advantageous for dimension-centric queries.To reconcile these trade-offs,a hybrid schema is proposed that retains both representations,ensuring balanced efficiency across heterogeneous workloads.The proposed framework demonstrates how spatio-temporal data warehousing can address schema complexity,improve query performance,and support multidimensional visualization.In doing so,it provides a foundation for integrating seismic analysis into broader big data-driven intelligent decision systems for disaster resilience,risk mitigation,and emergency management.展开更多
Intervention strategies to control non-point source nitrogen(N)and phosphorus(P)pollution in agriculture are expensive and there is a trade-off between engineering cost and treatment effectiveness.Implementing strateg...Intervention strategies to control non-point source nitrogen(N)and phosphorus(P)pollution in agriculture are expensive and there is a trade-off between engineering cost and treatment effectiveness.Implementing strategies often result in unsatisfactory outcomes and massive engineering costs when managing diffusive pollution in agricultural catchments.To address this issue,this paper proposes a robust,handy,catchment N&P decision support system(CNPDSS),an Android-based smartphone system integrated with a web-based geographic information system(GIS).The CNPDSS aims to provide artificial intelligence-driven decisions that minimize N&P loadings and engineering costs for mitigating pollution in agricultural catchments.It consists of four components:a general user interface(GUI),GIS,N&P pollution modeling(NPPM),and a DSS.The CNPDSS simplifies the GUI and integrates GIS modules to create a user-friendly interface,enabling non-professional users to operate the system easily through intuitive actions.The NPPM uses straightforward empirical models to predict N&P loadings,enhancing efficiency by avoiding excessive parameters.Taking into account the N&P movement pathway in the catchment,the DSS incorporates three control measures:source reduction in farmland(before migration stage),process retention by ecological ditch(midway transport stage),and down-end purification by constructed wetland(waterbody discharge stage),to formulate a comprehensive ternary controlling strategy.To optimize the cost-effectiveness of any proposed N&P control strategies for sub-catchments,a differential evolution algorithm(DEA)is employed in CNPDSS to carry out a dual-objective decision-making optimization computation.In this study,the CNPDSS is applied to a case study in an agricultural catchment in Central China to develop the most cost-effective ternary N&P control strategies that ensure the catchment water quality within Criterion Ⅲ of the Chinese Surface Water Quality Standard GB3838-2002 is met(total N concentration≤1.0 mg L^(-1)and total P concentration≤0.2 mg L^(-1)).Our results demonstrate that the CNPDSS is feasible and also possesses an adaptive design and flexible architecture to enable its generalization and extension to support strong hands-on applications in other catchments.展开更多
Embodied intelligent systems integrate perception,control,and decision-making within physical agents,and have become a cornerstone of modern aerospace,autonomous driving,and cooperative robotic applications.When opera...Embodied intelligent systems integrate perception,control,and decision-making within physical agents,and have become a cornerstone of modern aerospace,autonomous driving,and cooperative robotic applications.When operating in uncertain and dynamic environments,such systems must address challenges arising from incomplete sensing,unpredictable maneuvers,communication constraints,disturbances,and evolving network structures.展开更多
Transforming urban spatial structures to promote green and low-carbon development is an effective strategy.Although prior studies have examined the impact of urban polycentricity on carbon emissions and economic devel...Transforming urban spatial structures to promote green and low-carbon development is an effective strategy.Although prior studies have examined the impact of urban polycentricity on carbon emissions and economic development,research on its role in the synergistic relationship between these factors regarding carbon emission efficiency is limited.Furthermore,existing literature often overlooks nonlinear effects and interactions with other urban variables.This paper analyzed data from 295 Chinese cities in 2020,calculating urban population polycentricity,population dispersion indices,and carbon emission efficiency.Utilizing local spatial autocorrelation tools,we reveal interactions among urban population polycentricity,dispersion,carbon emissions,and carbon emission efficiency.We then employ a gradient boosting decision tree model(GBDT)to explore nonlinear and synergistic effects of polycentric urbanization.Key findings include:1)polycentric urbanization in Chinese cities exhibits significant spatial differentiation characteristics.The Polycentricity index is relatively high in economically developed eastern coastal regions with an overall low level,carbon emissions are concentrated in industrialized north-central cities and some Yangtze River Delta hubs,and carbon emission efficiency is the highest in the Yangtze River Delta while relatively low in Northeast China;there are significant spatially heterogeneous interaction characteristics among population polycentricity,population dispersion,carbon emissions,and carbon emission efficiency.2)Urban population polycentricity contributes 9.42%to total carbon emissions and 6.24%to carbon emission efficiency.3)The polycentricity index has a nonlinear impact on carbon emissions and carbon emission efficiency:no significant effect when below 0.50 or above 0.55,increased carbon emissions in 0.50-0.53,and reduced carbon emissions with improved efficiency in 0.53-0.55.4)The polycentricity index has an interaction effect with other variables;specifically,when the polycentricity index is between 0.53 and 0.55,its interaction with urban gross domestic product(GDP),urban population,urban built-up area,green coverage rate in built-up areas,urban technological expenditure,and the proportion of the output value of the secondary industry will reduce carbon emissions and improve carbon emission efficiency.These findings enhance the understanding of urban spatial structures and carbon emissions,providing valuable insights for policymakers in developing green and low-carbon strategies.展开更多
During 13 to 16 January 2026,with 148 participating nations,rising global relevance and a marked increase in visitor quality,Heimtextil 2026 stood for stability and reliability in a volatile market environment.Once ag...During 13 to 16 January 2026,with 148 participating nations,rising global relevance and a marked increase in visitor quality,Heimtextil 2026 stood for stability and reliability in a volatile market environment.Once again,3,000 exhibitors from across the globe placed their trust in the industry’s central platform in Frankfurt,presenting current collections,materials and textile solutions for holistic interior design to approximately 47,000 buyers.Under the motto“Lead the Change”,Heimtextil brought evolving market dynamics,Artificial Intelligence(AI)and new business opportunities to life.The focus was on progressive design approaches,visionary talents,functional textiles and new hospitality concepts shaping the future of interior design.A tangible sense of confidence and a clear commitment to Heimtextil as a strong industry partner resonated throughout the exhibition halls.展开更多
A composite anti-disturbance predictive control strategy employing a Multi-dimensional Taylor Network(MTN)is presented for unmanned systems subject to time-delay and multi-source disturbances.First,the multi-source di...A composite anti-disturbance predictive control strategy employing a Multi-dimensional Taylor Network(MTN)is presented for unmanned systems subject to time-delay and multi-source disturbances.First,the multi-source disturbances are addressed according to their specific characteristics as follows:(A)an MTN data-driven model,which is used for uncertainty description,is designed accompanied with the mechanism model to represent the unmanned systems;(B)an adaptive MTN filter is used to remove the influence of the internal disturbance;(C)an MTN disturbance observer is constructed to estimate and compensate for the influence of the external disturbance;(D)the Extended Kalman Filter(EKF)algorithm is utilized as the learning mechanism for MTNs.Second,to address the time-delay effect,a recursiveτstep-ahead MTN predictive model is designed utilizing recursive technology,aiming to mitigate the impact of time-delay,and the EKF algorithm is employed as its learning mechanism.Then,the MTN predictive control law is designed based on the quadratic performance index.By implementing the proposed composite controller to unmanned systems,simultaneous feedforward compensation and feedback suppression to the multi-source disturbances are conducted.Finally,the convergence of the MTN and the stability of the closed-loop system are established utilizing the Lyapunov theorem.Two exemplary applications of unmanned systems involving unmanned vehicle and rigid spacecraft are presented to validate the effectiveness of the proposed approach.展开更多
Across four studies,we explore the impact of solitude on consumers’reliance on feelings versus reasons in decision making,along with the underlying mechanism and boundary conditions.The results indicate that solitude...Across four studies,we explore the impact of solitude on consumers’reliance on feelings versus reasons in decision making,along with the underlying mechanism and boundary conditions.The results indicate that solitude individuals(vs.non-solitude)would prefer feeling-based strategy in decision-making,resulting in a higher intention of choosing the affectively superior option over the cognitively superior option(Study 1).Self-focus plays the underlying mechanism in the solitude effect(Study 2).Moreover,we also examine two boundary conditions:motivation(Study 3)and temporal orientation(Study 4),which indicates that involuntary motivation and future orientation can mitigate the solitude effect on affective processing.These findings provide insights into consumers’judgments of product attributes and selection of decision-making strategies according to their situations.展开更多
Traditional Chinese medicine(TCM)represents a paradigmatic approach to personalized medicine,developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years,and now en...Traditional Chinese medicine(TCM)represents a paradigmatic approach to personalized medicine,developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years,and now encompasses large-scale electronic medical records(EMR)and experimental molecular data.Artificial intelligence(AI)has demonstrated its utility in medicine through the development of various expert systems(e.g.,MYCIN)since the 1970s.With the emergence of deep learning and large language models(LLMs),AI’s potential in medicine shows considerable promise.Consequently,the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction.This survey provides an insightful overview of TCM AI research,summarizing related research tasks from three perspectives:systems-level biological mechanism elucidation,real-world clinical evidence inference,and personalized clinical decision support.The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice.To critically assess the current state of the field,this work identifies major challenges and opportunities that constrain the development of robust research capabilities—particularly in the mechanistic understanding of TCM syndromes and herbal formulations,novel drug discovery,and the delivery of high-quality,patient-centered clinical care.The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality,large-scale data repositories;the construction of comprehensive and domain-specific knowledge graphs(KGs);deeper insights into the biological mechanisms underpinning clinical efficacy;rigorous causal inference frameworks;and intelligent,personalized decision support systems.展开更多
As Artificial Intelligence(AI)is moving fast from Large Language Models(LLMs)to AI Agents and Agentic Intelligence,the need to incorporate new AI into Decision Intelligence(DI)is becoming more and more urgent for both...As Artificial Intelligence(AI)is moving fast from Large Language Models(LLMs)to AI Agents and Agentic Intelligence,the need to incorporate new AI into Decision Intelligence(DI)is becoming more and more urgent for both practical and theoretic reasons:both decision and process complexities would be significantly increased due to the use of advanced AI tools and agents,and both traditional and recent thinking must be rethought and reconstructed accordingly.Our perspective would like to address this important issue based on some historical milestone developments in Computer-Aided Software Engineering(CASE)and recent efforts in digital theatrical technology[1].展开更多
This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with...This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with one source element and multiple sink elements is considered first.Each element can con-nect with other elements within a stochastic connection ranges.The system is regarded as successful as long as the source ele-ment remains connected with all sink elements.An importance measure is proposed to evaluate the performance of non-source elements.Furthermore,to calculate the system reliability and the element importance measure,a multi-valued decision diagram based approach is structured and its complexity is analyzed.Finally,a numerical example about the signal transfer station system is illustrated to analyze the system reliability and the ele-ment importance measure.展开更多
People have been engaged in sports activities both individually and collectively for years.Sports consumption,which refers to the process that covers many issues related to sports in the form of playing,watching,liste...People have been engaged in sports activities both individually and collectively for years.Sports consumption,which refers to the process that covers many issues related to sports in the form of playing,watching,listening or reading,is a form of human behavior.The satisfaction of the four marketing components of product,price,distribution and promotion by using the leisure time of the sports consumer effectively and ensuring its continuity in the future process can be ensured by effective utilization of facilities and quality recreation activities.Consumer behaviors,which have a very complex structure,are seen in the form of choosing,buying,using and obtaining.With this study,it is aimed to determine the mediating role of consumer decision-making styles in determining the effect of marketing components in the consumption of sports activities on the satisfaction of sports consumers.In this direction,data were collected in the province of Istanbul,which was determined as the sample.Data were obtained with a questionnaire form created on Google Form.These data were analyzed in line with the model and hypotheses created with these data and it was determined that the marketing components of sports consumption have an impact on the sports consumer and it was concluded that consumer decision-making styles have a positive mediating effect in this regard.展开更多
Background: Clinical decision support tools provide suggestions to support healthcare providers and clinicians, as they attend to patients. Clinicians use these tools to rapidly consult the evidence at the point of ca...Background: Clinical decision support tools provide suggestions to support healthcare providers and clinicians, as they attend to patients. Clinicians use these tools to rapidly consult the evidence at the point of care, a practice which has been found to reduce the time patients spend in hospitals, promote the quality of care and improve healthcare outcomes. Such tools include Medscape, VisualDx, Clinical Key, DynaMed, BMJ Best Practice and UpToDate. However, use of such tools has not yet been fully embraced in low-resource settings such as Uganda. Objective: This paper intends to collate data on the use and uptake of one such tool, UpToDate, which was provided at no cost to five medical schools in Uganda. Methods: Free access to UpToDate was granted through the IP addresses of five medical schools in Uganda in collaboration with Better Evidence at The Global Health Delivery Project at Harvard and Brigham and Women’s Hospital and Wolters Kluwer Health. Following the donation, medical librarians in the respective institutions conducted training sessions and created awareness of the tool. Usage data was aggregated, based on logins and content views, presented and analyzed using Excel tables and graphs. Results: The data shows similar trends in increased usage over the period of August 2022 to August 2023 across the five medical schools. The most common topics viewed, mode of access (using either the computer or the mobile app), total usage by institution, ratio of uses to eligible users by institution and ratio of uses to students by institution are shared. Conclusion: The study revealed that the tool was used by various user categories across the institutions with similar steady improved usage over the year. These results can inform the librarians as they encourage their respective institutions to continue using the tool to support uptake of point-of-care tools in clinical practice.展开更多
The ancient tacit knowledge behind the logic system permeated the culture and promoted numerous impactful inventions throughout the history. Traditional Chinese medicine with its effectiveness should also have stemmed...The ancient tacit knowledge behind the logic system permeated the culture and promoted numerous impactful inventions throughout the history. Traditional Chinese medicine with its effectiveness should also have stemmed out from such logic system. This article aims to rearticulate the underlying lucid multi-dimensional logic system, which faded in obscurity only because of time-out loss of the mid-right concept. Retracing this past tacit but important concept could uncover a multi-dimensional system over a point relating to all matters while capturing the central core of the matter. The seemingly unmanageable multidimensional logic was strengthened by verification processes which affirmed its further extensions, and made up the language of the people, the concepts of yin-yang(阴阳), and the development of extensions of Ba Gua(八卦) derivatives, which furthered the interpretation of the space-time properties and Chinese medicine.展开更多
The satellite orbital pursuit game focuses on studying spacecraft maneuvering strategies in space.Traditional numerical methods often face real-time inadequacies and adaptability limitations when dealing with highly n...The satellite orbital pursuit game focuses on studying spacecraft maneuvering strategies in space.Traditional numerical methods often face real-time inadequacies and adaptability limitations when dealing with highly nonlinear problems.With the advancement of Deep Reinforcement Learning(DRL)technology,continuous-time orbital control capabilities have significantly improved.Despite this,the existing DRL technologies still need adjustments in action delay and discretization structure to better adapt to practical application scenarios.Combining continuous learning and model planning demonstrates the adaptability of these methods in continuous-time decision problems.Additionally,to more effectively handle action delay issues,a new scheduled action execution technique has been developed.This technique optimizes action execution timing through real-time policy adjustments,thus adapting to the dynamic changes in the orbital environment.A Hierarchical Reinforcement Learning(HRL)strategy was also adopted to simplify the decision-making process for long-distance pursuit tasks by setting phased subgoals to gradually approach the target.The effectiveness of the proposed strategy in practical satellite pursuit scenarios has been verified through simulations of two different tasks.展开更多
This study focuses on the construction and application of intelligent financial decision-making models driven by generative artificial intelligence(AI).It analyzes the mechanisms by which generative AI empowers financ...This study focuses on the construction and application of intelligent financial decision-making models driven by generative artificial intelligence(AI).It analyzes the mechanisms by which generative AI empowers financial decision-making within a dual framework of dynamic knowledge evolution and risk control.The research reveals that generative AI,with its superior data processing,pattern recognition,and autonomous learning capabilities,can transcend the limitations of traditional decision-making models,facilitating a significant shift from causal inference to probabilistic creation in decision-making paradigms.By systematically constructing an intelligent financial decision-making model that includes data governance,core engine,and decision output layers,the study clarifies the functional roles and collaborative mechanisms of each layer.Additionally,it addresses key challenges in technology application,institutional adaptation,and organizational transformation by proposing systematic strategies for technical risk management,institutional innovation,and organizational capability enhancement,aiming to provide robust theoretical support and practical guidance for the intelligent transformation of corporate financial decision-making.展开更多
Objective:To explore factors influencing decision regret among colorectal cancer patients undergoing intestinal ostomy.Methods:A questionnaire survey was conducted among 102 colorectal cancer patients who underwent in...Objective:To explore factors influencing decision regret among colorectal cancer patients undergoing intestinal ostomy.Methods:A questionnaire survey was conducted among 102 colorectal cancer patients who underwent intestinal ostomy surgery and visited the ostomy clinic at a tertiary hospital in Baoding from July to September 2025.The Chinese version of the Ostomy Adaptation Inventory(OAI-20),Decision Regret Scale(DRS),Decision Conflict Scale(DCS),and Functional Assessment of Cancer Therapy-Colorectal(FACT-C)were used to measure patients’adaptation to stoma,decision regret,decision conflict,and quality of life.The Shared Decision-Making Questionnaire(SDM-Q-9)assessed patient involvement in ostomy surgery decisions,while the SSUK-8 evaluated social support.Additional items explored perceptions related to decision-making,participation,and outcomes.Results:Among 134 eligible patients attending the clinic,120 participated in the questionnaire,with 102 completing all items.Stoma patients reported an average decision regret score of 60.83(SD 28.43),an average coping ability score of 54.26(SD 26.69),an average decision conflict score of 62.55(SD 25.95),and a quality of life score of 56.93(SD 27.46).In the multiple regression analysis,decision regret was associated with decision conflict,poor patient coping ability,low quality of life,and low social support.Conclusion:Decision regret is prevalent among Chinese CRC patients following ostomy surgery.Compared with similar studies in other regions,Chinese CRC patients exhibit a higher rate of regret.This may be related to lower patient involvement in decision-making,generally poorer quality of life,and heavier economic burdens.展开更多
基金supported by the National Natural Science Foundation of China(22072048)the Guangdong Provincial Department of Science and Technology(2021A1515010128 and 2022A0505050013).
文摘Succinonitrile(SN)-based polymer plastic crystal electrolytes(PPCEs)are regarded as promising candidates for lithium metal batteries but suffer from serious side reactions with Li metal.Herein,we propose a multi-dimensional optimization strategy to alleviate the side reactions between SN and Li metal,and develop a highly stable poly-vinylethylene carbonate-based PPCE(PPCE-VEC).Moreover,we identify the intrinsic factors of multi-dimensional polymer structures on the electrolyte stability by three typical classes of polyesters.The PPCE-VEC constructed by in situ polymerization exhibits much better stability than poly-vinylene carbonate-based PPCE(PPCE-VCA)and poly-trifluoroethyl acrylate-based PPCE(PPCE-TFA),which is verified by its fewer SN-decomposition species in X-ray photoelectron spectroscopy(XPS)and outstanding full cell performance.The PPCE-VEC-enabled LiNi_(0.6)Co_(0.2)Mn_(0.2)O_(2)full cell achieve 73.7%capacity retention after 1400 cycles,which outperforms PPCE-VCA-and PPCE-TFA-enabled full cells(61.9%and 46.9%).Spectral analysis and theoretical calculation reveal that the high solvation ability of the carbonyl site,flexible polymer chain,and homogeneous electrolyte phase of PPCE-VEC are favorable to maximizing competition coordination with Li^(+)to weaken the Li^(+)–SN binding and shape an anion-rich solvation structure.This optimized polymer-involved Li^(+)solvation enhances SN stability and facilitates the formation of B/F enriched solid-electrolyte interphase(SEI),thus significantly improving PPCE stability.
基金funded by Henan Key Laboratory of General Aviation Technology,grant number ZHKF-240202。
文摘Evaluating Unmanned Aerial Vehicle(UAV)systems within a System-of-Systems(SoS)environment helps clarify their contribution to the overall combat capability and supports effectiveness-oriented system optimization.When assessing decision systems in such an environment,cross-level modeling and simulation are required,which often face a trade-off between low modeling cost and high simulation accuracy,while the credibility of results remains challenging to ensure.To address these issues,this study proposes a hybrid-granularity Hardware-In-the-Loop(HIL)SoS environment construction method based on Graphical Evaluation and Review Technique(GERT).The method employs GERT to analyze the relationships between simulation systems,the System Under Test(SUT),and mission outcomes,thereby determining the required model precision for different systems.A dynamic resource allocation algorithm is applied to adjust model granularity on demand,ensuring high-fidelity simulation under constrained total cost.Additionally,GERT estimates the computational frequency and communication bandwidth requirements of the SUT,guiding hardware selection to enhance simulation credibility.A UAV maritime combat case study was conducted for validation.The results demonstrate that,compared to the flat modeling approach,the hybrid-granularity scenario based on GERT analysis achieves higher simulation accuracy with lower overall model complexity.The coefficient of variation in evaluation results significantly decreases in HIL simulations compared to virtual simulations,confirming improved credibility.Under the hybrid-granularity HIL scenario,the decision system was evaluated from an effectiveness perspective,identifying the most sensitive performance parameter.Subsequent targeted optimization led to an 11.90%improvement in effectiveness,validating the method's practical utility.
文摘Earthquakes are highly destructive spatio-temporal phenomena whose analysis is essential for disaster preparedness and risk mitigation.Modern seismological research produces vast volumes of heterogeneous data from seismic networks,satellite observations,and geospatial repositories,creating the need for scalable infrastructures capable of integrating and analyzing such data to support intelligent decision-making.Data warehousing technologies provide a robust foundation for this purpose;however,existing earthquake-oriented data warehouses remain limited,often relying on simplified schemas,domain-specific analytics,or cataloguing efforts.This paper presents the design and implementation of a spatio-temporal data warehouse for seismic activity.The framework integrates spatial and temporal dimensions in a unified schema and introduces a novel array-based approach for managing many-to-many relationships between facts and dimensions without intermediate bridge tables.A comparative evaluation against a conventional bridge-table schema demonstrates that the array-based design improves fact-centric query performance,while the bridge-table schema remains advantageous for dimension-centric queries.To reconcile these trade-offs,a hybrid schema is proposed that retains both representations,ensuring balanced efficiency across heterogeneous workloads.The proposed framework demonstrates how spatio-temporal data warehousing can address schema complexity,improve query performance,and support multidimensional visualization.In doing so,it provides a foundation for integrating seismic analysis into broader big data-driven intelligent decision systems for disaster resilience,risk mitigation,and emergency management.
基金financially supported by the National Key Research and Development Program of China(2024YFD1700104 and 2022YFE0209200-03)the National Natural Science Foundation of China(42161144002 and 41977156)+3 种基金the Guangxi Natural Science Foundation,China(2022GXNSFBA035625)the Guangxi Technology Base and Talent Subject,China(Guike AD22035927)the Shandong Key Research and Development Project,China(2022TZXD0045)the State Key Laboratory of Earth System Numerical Modeling and Application,Institute of Atmospheric Physics,Chinese Academy of Sciences。
文摘Intervention strategies to control non-point source nitrogen(N)and phosphorus(P)pollution in agriculture are expensive and there is a trade-off between engineering cost and treatment effectiveness.Implementing strategies often result in unsatisfactory outcomes and massive engineering costs when managing diffusive pollution in agricultural catchments.To address this issue,this paper proposes a robust,handy,catchment N&P decision support system(CNPDSS),an Android-based smartphone system integrated with a web-based geographic information system(GIS).The CNPDSS aims to provide artificial intelligence-driven decisions that minimize N&P loadings and engineering costs for mitigating pollution in agricultural catchments.It consists of four components:a general user interface(GUI),GIS,N&P pollution modeling(NPPM),and a DSS.The CNPDSS simplifies the GUI and integrates GIS modules to create a user-friendly interface,enabling non-professional users to operate the system easily through intuitive actions.The NPPM uses straightforward empirical models to predict N&P loadings,enhancing efficiency by avoiding excessive parameters.Taking into account the N&P movement pathway in the catchment,the DSS incorporates three control measures:source reduction in farmland(before migration stage),process retention by ecological ditch(midway transport stage),and down-end purification by constructed wetland(waterbody discharge stage),to formulate a comprehensive ternary controlling strategy.To optimize the cost-effectiveness of any proposed N&P control strategies for sub-catchments,a differential evolution algorithm(DEA)is employed in CNPDSS to carry out a dual-objective decision-making optimization computation.In this study,the CNPDSS is applied to a case study in an agricultural catchment in Central China to develop the most cost-effective ternary N&P control strategies that ensure the catchment water quality within Criterion Ⅲ of the Chinese Surface Water Quality Standard GB3838-2002 is met(total N concentration≤1.0 mg L^(-1)and total P concentration≤0.2 mg L^(-1)).Our results demonstrate that the CNPDSS is feasible and also possesses an adaptive design and flexible architecture to enable its generalization and extension to support strong hands-on applications in other catchments.
文摘Embodied intelligent systems integrate perception,control,and decision-making within physical agents,and have become a cornerstone of modern aerospace,autonomous driving,and cooperative robotic applications.When operating in uncertain and dynamic environments,such systems must address challenges arising from incomplete sensing,unpredictable maneuvers,communication constraints,disturbances,and evolving network structures.
基金Under the auspices of National Natural Science Foundation of China(No.42571300)。
文摘Transforming urban spatial structures to promote green and low-carbon development is an effective strategy.Although prior studies have examined the impact of urban polycentricity on carbon emissions and economic development,research on its role in the synergistic relationship between these factors regarding carbon emission efficiency is limited.Furthermore,existing literature often overlooks nonlinear effects and interactions with other urban variables.This paper analyzed data from 295 Chinese cities in 2020,calculating urban population polycentricity,population dispersion indices,and carbon emission efficiency.Utilizing local spatial autocorrelation tools,we reveal interactions among urban population polycentricity,dispersion,carbon emissions,and carbon emission efficiency.We then employ a gradient boosting decision tree model(GBDT)to explore nonlinear and synergistic effects of polycentric urbanization.Key findings include:1)polycentric urbanization in Chinese cities exhibits significant spatial differentiation characteristics.The Polycentricity index is relatively high in economically developed eastern coastal regions with an overall low level,carbon emissions are concentrated in industrialized north-central cities and some Yangtze River Delta hubs,and carbon emission efficiency is the highest in the Yangtze River Delta while relatively low in Northeast China;there are significant spatially heterogeneous interaction characteristics among population polycentricity,population dispersion,carbon emissions,and carbon emission efficiency.2)Urban population polycentricity contributes 9.42%to total carbon emissions and 6.24%to carbon emission efficiency.3)The polycentricity index has a nonlinear impact on carbon emissions and carbon emission efficiency:no significant effect when below 0.50 or above 0.55,increased carbon emissions in 0.50-0.53,and reduced carbon emissions with improved efficiency in 0.53-0.55.4)The polycentricity index has an interaction effect with other variables;specifically,when the polycentricity index is between 0.53 and 0.55,its interaction with urban gross domestic product(GDP),urban population,urban built-up area,green coverage rate in built-up areas,urban technological expenditure,and the proportion of the output value of the secondary industry will reduce carbon emissions and improve carbon emission efficiency.These findings enhance the understanding of urban spatial structures and carbon emissions,providing valuable insights for policymakers in developing green and low-carbon strategies.
文摘During 13 to 16 January 2026,with 148 participating nations,rising global relevance and a marked increase in visitor quality,Heimtextil 2026 stood for stability and reliability in a volatile market environment.Once again,3,000 exhibitors from across the globe placed their trust in the industry’s central platform in Frankfurt,presenting current collections,materials and textile solutions for holistic interior design to approximately 47,000 buyers.Under the motto“Lead the Change”,Heimtextil brought evolving market dynamics,Artificial Intelligence(AI)and new business opportunities to life.The focus was on progressive design approaches,visionary talents,functional textiles and new hospitality concepts shaping the future of interior design.A tangible sense of confidence and a clear commitment to Heimtextil as a strong industry partner resonated throughout the exhibition halls.
基金co-supported by the National Key R&D Program of China(No.2023YFB4704400)the Zhejiang Provincial Natural Science Foundation of China(No.LQ24F030012)the National Natural Science Foundation of China General Project(No.62373033)。
文摘A composite anti-disturbance predictive control strategy employing a Multi-dimensional Taylor Network(MTN)is presented for unmanned systems subject to time-delay and multi-source disturbances.First,the multi-source disturbances are addressed according to their specific characteristics as follows:(A)an MTN data-driven model,which is used for uncertainty description,is designed accompanied with the mechanism model to represent the unmanned systems;(B)an adaptive MTN filter is used to remove the influence of the internal disturbance;(C)an MTN disturbance observer is constructed to estimate and compensate for the influence of the external disturbance;(D)the Extended Kalman Filter(EKF)algorithm is utilized as the learning mechanism for MTNs.Second,to address the time-delay effect,a recursiveτstep-ahead MTN predictive model is designed utilizing recursive technology,aiming to mitigate the impact of time-delay,and the EKF algorithm is employed as its learning mechanism.Then,the MTN predictive control law is designed based on the quadratic performance index.By implementing the proposed composite controller to unmanned systems,simultaneous feedforward compensation and feedback suppression to the multi-source disturbances are conducted.Finally,the convergence of the MTN and the stability of the closed-loop system are established utilizing the Lyapunov theorem.Two exemplary applications of unmanned systems involving unmanned vehicle and rigid spacecraft are presented to validate the effectiveness of the proposed approach.
文摘Across four studies,we explore the impact of solitude on consumers’reliance on feelings versus reasons in decision making,along with the underlying mechanism and boundary conditions.The results indicate that solitude individuals(vs.non-solitude)would prefer feeling-based strategy in decision-making,resulting in a higher intention of choosing the affectively superior option over the cognitively superior option(Study 1).Self-focus plays the underlying mechanism in the solitude effect(Study 2).Moreover,we also examine two boundary conditions:motivation(Study 3)and temporal orientation(Study 4),which indicates that involuntary motivation and future orientation can mitigate the solitude effect on affective processing.These findings provide insights into consumers’judgments of product attributes and selection of decision-making strategies according to their situations.
基金supported by the National Key Research and Development Program (No.2023YFC3502604)the National Natural Science Foundation of China (Nos.U23B2062, 82274352,82174533, 82374302, 82204941)+3 种基金the Noncommunicable Chronic Diseases-National Science and Technology Major Project (No.2023ZD0505700)the Beijing-Tianjin-Hebei Basic Research Cooperation Project (No.22JCZXJC00070)the State Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture (No.SKL2024Z0102)Key R&D project of Ningxia Autonomous Region (No.2022BEG02036).
文摘Traditional Chinese medicine(TCM)represents a paradigmatic approach to personalized medicine,developed through the systematic accumulation and refinement of clinical empirical data over more than 2000 years,and now encompasses large-scale electronic medical records(EMR)and experimental molecular data.Artificial intelligence(AI)has demonstrated its utility in medicine through the development of various expert systems(e.g.,MYCIN)since the 1970s.With the emergence of deep learning and large language models(LLMs),AI’s potential in medicine shows considerable promise.Consequently,the integration of AI and TCM from both clinical and scientific perspectives presents a fundamental and promising research direction.This survey provides an insightful overview of TCM AI research,summarizing related research tasks from three perspectives:systems-level biological mechanism elucidation,real-world clinical evidence inference,and personalized clinical decision support.The review highlights representative AI methodologies alongside their applications in both TCM scientific inquiry and clinical practice.To critically assess the current state of the field,this work identifies major challenges and opportunities that constrain the development of robust research capabilities—particularly in the mechanistic understanding of TCM syndromes and herbal formulations,novel drug discovery,and the delivery of high-quality,patient-centered clinical care.The findings underscore that future advancements in AI-driven TCM research will rely on the development of high-quality,large-scale data repositories;the construction of comprehensive and domain-specific knowledge graphs(KGs);deeper insights into the biological mechanisms underpinning clinical efficacy;rigorous causal inference frameworks;and intelligent,personalized decision support systems.
基金supported by the Science and Technology Development Fund,Macao Special Administrative Region(SAR)(0093/2023/RIA2,0157/2024/RIA2,0145/2023/RIA3)the Distinguished Program of Obuda University and the DeSci Center for Parallel Intelligence at the Obuda University,Hungary.This article is based on the report of“Digital Theaters and Theatrical Intelligence for Decision Science”Project(DeSCII-0017-1023-2023,PI:Qinghua Ni)initiated by DeSci International.
文摘As Artificial Intelligence(AI)is moving fast from Large Language Models(LLMs)to AI Agents and Agentic Intelligence,the need to incorporate new AI into Decision Intelligence(DI)is becoming more and more urgent for both practical and theoretic reasons:both decision and process complexities would be significantly increased due to the use of advanced AI tools and agents,and both traditional and recent thinking must be rethought and reconstructed accordingly.Our perspective would like to address this important issue based on some historical milestone developments in Computer-Aided Software Engineering(CASE)and recent efforts in digital theatrical technology[1].
基金supported by the National Natural Science Foundation of China(72101025,72271049),the Interdisciplinary Research Project for Young Teachers of USTB(Fundamental Research Funds for the Central Universities,FRF-IDRY-24-024)the Hebei Natural Science Foundation(F2023501011)+1 种基金the Fundamental Research Funds for the Central Universities(FRF-TP-20-073A1)the R&D Program of Beijing Municipal Education Commission(KM202411232015).
文摘This paper proposes a reliability evaluation model for a multi-dimensional network system,which has potential to be applied to the internet of things or other practical networks.A multi-dimensional network system with one source element and multiple sink elements is considered first.Each element can con-nect with other elements within a stochastic connection ranges.The system is regarded as successful as long as the source ele-ment remains connected with all sink elements.An importance measure is proposed to evaluate the performance of non-source elements.Furthermore,to calculate the system reliability and the element importance measure,a multi-valued decision diagram based approach is structured and its complexity is analyzed.Finally,a numerical example about the signal transfer station system is illustrated to analyze the system reliability and the ele-ment importance measure.
文摘People have been engaged in sports activities both individually and collectively for years.Sports consumption,which refers to the process that covers many issues related to sports in the form of playing,watching,listening or reading,is a form of human behavior.The satisfaction of the four marketing components of product,price,distribution and promotion by using the leisure time of the sports consumer effectively and ensuring its continuity in the future process can be ensured by effective utilization of facilities and quality recreation activities.Consumer behaviors,which have a very complex structure,are seen in the form of choosing,buying,using and obtaining.With this study,it is aimed to determine the mediating role of consumer decision-making styles in determining the effect of marketing components in the consumption of sports activities on the satisfaction of sports consumers.In this direction,data were collected in the province of Istanbul,which was determined as the sample.Data were obtained with a questionnaire form created on Google Form.These data were analyzed in line with the model and hypotheses created with these data and it was determined that the marketing components of sports consumption have an impact on the sports consumer and it was concluded that consumer decision-making styles have a positive mediating effect in this regard.
文摘Background: Clinical decision support tools provide suggestions to support healthcare providers and clinicians, as they attend to patients. Clinicians use these tools to rapidly consult the evidence at the point of care, a practice which has been found to reduce the time patients spend in hospitals, promote the quality of care and improve healthcare outcomes. Such tools include Medscape, VisualDx, Clinical Key, DynaMed, BMJ Best Practice and UpToDate. However, use of such tools has not yet been fully embraced in low-resource settings such as Uganda. Objective: This paper intends to collate data on the use and uptake of one such tool, UpToDate, which was provided at no cost to five medical schools in Uganda. Methods: Free access to UpToDate was granted through the IP addresses of five medical schools in Uganda in collaboration with Better Evidence at The Global Health Delivery Project at Harvard and Brigham and Women’s Hospital and Wolters Kluwer Health. Following the donation, medical librarians in the respective institutions conducted training sessions and created awareness of the tool. Usage data was aggregated, based on logins and content views, presented and analyzed using Excel tables and graphs. Results: The data shows similar trends in increased usage over the period of August 2022 to August 2023 across the five medical schools. The most common topics viewed, mode of access (using either the computer or the mobile app), total usage by institution, ratio of uses to eligible users by institution and ratio of uses to students by institution are shared. Conclusion: The study revealed that the tool was used by various user categories across the institutions with similar steady improved usage over the year. These results can inform the librarians as they encourage their respective institutions to continue using the tool to support uptake of point-of-care tools in clinical practice.
文摘The ancient tacit knowledge behind the logic system permeated the culture and promoted numerous impactful inventions throughout the history. Traditional Chinese medicine with its effectiveness should also have stemmed out from such logic system. This article aims to rearticulate the underlying lucid multi-dimensional logic system, which faded in obscurity only because of time-out loss of the mid-right concept. Retracing this past tacit but important concept could uncover a multi-dimensional system over a point relating to all matters while capturing the central core of the matter. The seemingly unmanageable multidimensional logic was strengthened by verification processes which affirmed its further extensions, and made up the language of the people, the concepts of yin-yang(阴阳), and the development of extensions of Ba Gua(八卦) derivatives, which furthered the interpretation of the space-time properties and Chinese medicine.
基金supported by the National Natural Science Foundation of China(No.12202281)the Shanghai Natural Science Foundation,China(No.23ZR1461800)the Research Initiation Fund of Northwestern Polytechnical University,China(No.G2024KY05103)。
文摘The satellite orbital pursuit game focuses on studying spacecraft maneuvering strategies in space.Traditional numerical methods often face real-time inadequacies and adaptability limitations when dealing with highly nonlinear problems.With the advancement of Deep Reinforcement Learning(DRL)technology,continuous-time orbital control capabilities have significantly improved.Despite this,the existing DRL technologies still need adjustments in action delay and discretization structure to better adapt to practical application scenarios.Combining continuous learning and model planning demonstrates the adaptability of these methods in continuous-time decision problems.Additionally,to more effectively handle action delay issues,a new scheduled action execution technique has been developed.This technique optimizes action execution timing through real-time policy adjustments,thus adapting to the dynamic changes in the orbital environment.A Hierarchical Reinforcement Learning(HRL)strategy was also adopted to simplify the decision-making process for long-distance pursuit tasks by setting phased subgoals to gradually approach the target.The effectiveness of the proposed strategy in practical satellite pursuit scenarios has been verified through simulations of two different tasks.
文摘This study focuses on the construction and application of intelligent financial decision-making models driven by generative artificial intelligence(AI).It analyzes the mechanisms by which generative AI empowers financial decision-making within a dual framework of dynamic knowledge evolution and risk control.The research reveals that generative AI,with its superior data processing,pattern recognition,and autonomous learning capabilities,can transcend the limitations of traditional decision-making models,facilitating a significant shift from causal inference to probabilistic creation in decision-making paradigms.By systematically constructing an intelligent financial decision-making model that includes data governance,core engine,and decision output layers,the study clarifies the functional roles and collaborative mechanisms of each layer.Additionally,it addresses key challenges in technology application,institutional adaptation,and organizational transformation by proposing systematic strategies for technical risk management,institutional innovation,and organizational capability enhancement,aiming to provide robust theoretical support and practical guidance for the intelligent transformation of corporate financial decision-making.
文摘Objective:To explore factors influencing decision regret among colorectal cancer patients undergoing intestinal ostomy.Methods:A questionnaire survey was conducted among 102 colorectal cancer patients who underwent intestinal ostomy surgery and visited the ostomy clinic at a tertiary hospital in Baoding from July to September 2025.The Chinese version of the Ostomy Adaptation Inventory(OAI-20),Decision Regret Scale(DRS),Decision Conflict Scale(DCS),and Functional Assessment of Cancer Therapy-Colorectal(FACT-C)were used to measure patients’adaptation to stoma,decision regret,decision conflict,and quality of life.The Shared Decision-Making Questionnaire(SDM-Q-9)assessed patient involvement in ostomy surgery decisions,while the SSUK-8 evaluated social support.Additional items explored perceptions related to decision-making,participation,and outcomes.Results:Among 134 eligible patients attending the clinic,120 participated in the questionnaire,with 102 completing all items.Stoma patients reported an average decision regret score of 60.83(SD 28.43),an average coping ability score of 54.26(SD 26.69),an average decision conflict score of 62.55(SD 25.95),and a quality of life score of 56.93(SD 27.46).In the multiple regression analysis,decision regret was associated with decision conflict,poor patient coping ability,low quality of life,and low social support.Conclusion:Decision regret is prevalent among Chinese CRC patients following ostomy surgery.Compared with similar studies in other regions,Chinese CRC patients exhibit a higher rate of regret.This may be related to lower patient involvement in decision-making,generally poorer quality of life,and heavier economic burdens.
