工业远程控制网关是用来解决数据采集与监控系统和工业计算机之间网络通信的安全问题,给工业网络连接到因特网的时候提供安全保证。该网关普遍适用各类的工业环境,且支持任何工业设备和所有类型的数据采集与监控系统,在工业设备和SC AD ...工业远程控制网关是用来解决数据采集与监控系统和工业计算机之间网络通信的安全问题,给工业网络连接到因特网的时候提供安全保证。该网关普遍适用各类的工业环境,且支持任何工业设备和所有类型的数据采集与监控系统,在工业设备和SC AD A设备之间处理数据包。由于工业设备无法安装使用VPN软件,因此本设计运用M anager/Agent模型的方式来实现VPN的功能。展开更多
The purpose of this study is to investigate the effectiveness of the“expiration manager”mini program in managing the validity of ward items.The program was used to manage frequently and infrequently used consumables...The purpose of this study is to investigate the effectiveness of the“expiration manager”mini program in managing the validity of ward items.The program was used to manage frequently and infrequently used consumables by setting up an automatic reminder function.The item failure rate and the time required for nurses to conduct counts over 6 months before and after implementation were compared,as well as evaluated system availability using the System Usability scale(SUS).Results showed that after implementing the mini program,both the item failure rate and non-recognition rate significantly decreased(P<0.05),while the inspection pass rate significantly increased(P<0.05),and the monthly inventory time was reduced(P<0.05).The SUS evaluation yielded a total score of 74.38±11.73,with learnability at 80.21±20.27 and availability at 72.92±11.18,all indicating good user acceptance.In conclusion,the“expiration manager”mini program can effectively improve the efficiency of item expiration management,reduce the risk of expiration,and save inspection time,thereby demonstrating high user acceptance and promising potential for wider adoption.展开更多
The development of villas in Bali is very rapid, especially in Badung regency with the distribution of the number of dominant villas in North Kuta district. Based on preliminary study, tourists tend to make reservatio...The development of villas in Bali is very rapid, especially in Badung regency with the distribution of the number of dominant villas in North Kuta district. Based on preliminary study, tourists tend to make reservations through online travel agents （OTA）. Therefore, there is a tendency if the villa manager in North Kuta district makes promotion through OTA. The aim of this research is to explain and analyze the dominant factors that influence the perception of villa managers in North Kuta district on using OTA as marketing media. The population in this research is composed of 191 villas. The final sample villas, using Slovin formula, were chosen based on cluster proportional sampling technique, totally 66 unit villas. Respondent in this research is the villa manager of each sample villa, so there are as much as 66 respondents. For data analysis, we used confirmatory factor analysis and descriptive statistics. In general, the perception of managers in North Kuta district on the use of OTA as marketing media is strongly agree or strongly positive with an average value of 4.37. The analysis of factors simultaneously showed that the perception of villa managers in North Kuta district on the use of OTA is determined by three factors, namely, factor in the self-perception of villa manager （F 1）, the factors in the self-perception of OTA （F2）, and situational factors （F3）.展开更多
This paper presents a novel approach to dynamic pricing and distributed energy management in virtual power plant(VPP)networks using multi-agent reinforcement learning(MARL).As the energy landscape evolves towards grea...This paper presents a novel approach to dynamic pricing and distributed energy management in virtual power plant(VPP)networks using multi-agent reinforcement learning(MARL).As the energy landscape evolves towards greater decentralization and renewable integration,traditional optimization methods struggle to address the inherent complexities and uncertainties.Our proposed MARL framework enables adaptive,decentralized decision-making for both the distribution system operator and individual VPPs,optimizing economic efficiency while maintaining grid stability.We formulate the problem as a Markov decision process and develop a custom MARL algorithm that leverages actor-critic architectures and experience replay.Extensive simulations across diverse scenarios demonstrate that our approach consistently outperforms baseline methods,including Stackelberg game models and model predictive control,achieving an 18.73%reduction in costs and a 22.46%increase in VPP profits.The MARL framework shows particular strength in scenarios with high renewable energy penetration,where it improves system performance by 11.95%compared with traditional methods.Furthermore,our approach demonstrates superior adaptability to unexpected events and mis-predictions,highlighting its potential for real-world implementation.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
Cellulose frameworks have emerged as promising materials for light management due to their exceptional light-scattering capabilities and sustainable nature.Conventional biomass-derived cellulose frameworks face a fund...Cellulose frameworks have emerged as promising materials for light management due to their exceptional light-scattering capabilities and sustainable nature.Conventional biomass-derived cellulose frameworks face a fundamental trade-off between haze and transparency,coupled with impractical thicknesses(≥1 mm).Inspired by squid’s skin-peeling mechanism,this work develops a peroxyformic acid(HCOOOH)-enabled precision peeling strategy to isolate intact 10-μm-thick bamboo green(BG)frameworks—100×thinner than wood-based counterparts while achieving an unprecedented optical performance(88%haze with 80%transparency).This performance surpasses delignified biomass(transparency<40%at 1 mm)and matches engineered cellulose composites,yet requires no energy-intensive nanofibrillation.The preserved native cellulose I crystalline structure(64.76%crystallinity)and wax-coated uniaxial fibril alignment(Hermans factor:0.23)contribute to high mechanical strength(903 MPa modulus)and broadband light scattering.As a light-management layer in polycrystalline silicon solar cells,the BG framework boosts photoelectric conversion efficiency by 0.41%absolute(18.74%→19.15%),outperforming synthetic anti-reflective coatings.The work establishes a scalable,waste-to-wealth route for optical-grade cellulose materials in next-generation optoelectronics.展开更多
Industrial waste salts are commonly used to make value-added snow-melting agents to ensure traffic safety in northern China during winter and spring after snowfall.However,heavy metals in industrial waste salts may po...Industrial waste salts are commonly used to make value-added snow-melting agents to ensure traffic safety in northern China during winter and spring after snowfall.However,heavy metals in industrial waste salts may pose certain environmental risks.Snow-melting agents and snow samples were collected and analyzed from highways,arterial roads,footbridges,and other locations in Beijing after the snowstorm in December 2023.It was found that the main component of snow-melting agents was sodium chloride with high concentrations of Cu,Mn,and Zn,which are not regulated in the current policies,despite the recent promotion of environmentally friendly snow-melting agents.The Pb,Zn and Cr contents of some snow samples exceeded the limitation value of surface water quality standards,potentially affecting the soil and water environment near roadsides,although the snow-melting agents comply with relevant standards,which indicates the policy gap in the management of recycled industrial salts.We reviewed and analyzed the relevant standards for snow-melting agents and industrial waste salts proposed nationally and internationally over the past 30 years.Through comparative analysis,we proposed relevant policy recommendations to the existing quality standards of snow-melting agents and the management regulations of industrial waste salts,and the formulation of corresponding usage strategies,aimed at reducing the potential environmental release of heavy metals from the use of snow-melting agents,thereby promoting more sustainable green urban development and environmentally sound waste management.展开更多
Perovskite solar cells(PSCs)have emerged as promising photovoltaic technologies owing to their remarkable power conversion efficiency(PCE).However,heat accumulation under continuous illumination remains a critical bot...Perovskite solar cells(PSCs)have emerged as promising photovoltaic technologies owing to their remarkable power conversion efficiency(PCE).However,heat accumulation under continuous illumination remains a critical bottleneck,severely affecting device stability and long-term operational performance.Herein,we present a multifunctional strategy by incorporating highly thermally conductive Ti_(3)C_(2)T_(X) MXene nanosheets into the perovskite layer to simultaneously enhance thermal management and optoelectronic properties.The Ti_(3)C_(2)T_(X) nanosheets,embedded at perovskite grain boundaries,construct efficient thermal conduction pathways,significantly improving the thermal conductivity and diffusivity of the film.This leads to a notable reduction in the device’s steady-state operating temperature from 42.96 to 39.97 under 100 mW cm^(−2) illumination,thereby alleviating heat-induced performance degradation.Beyond thermal regulation,Ti_(3)C_(2)T_(X),with high conductivity and negatively charged surface terminations,also serves as an effective defect passivation agent,reducing trap-assisted recombination,while simultaneously facilitating charge extraction and transport by optimizing interfacial energy alignment.As a result,the Ti_(3)C_(2)T_(X)-modified PSC achieve a champion PCE of 25.13%and exhibit outstanding thermal stability,retaining 80%of the initial PCE after 500 h of thermal aging at 85 and 30±5%relative humidity.(In contrast,control PSC retain only 58%after 200 h.)Moreover,under continuous maximum power point tracking in N2 atmosphere,Ti_(3)C_(2)T_(X)-modified PSC retained 70%of the initial PCE after 500 h,whereas the control PSC drop sharply to 20%.These findings highlight the synergistic role of Ti_(3)C_(2)T_(X) in thermal management and optoelectronic performance,paving the way for the development of high-efficiency and heat-resistant perovskite photovoltaics.展开更多
As a major source of freshwater in Central Asia,Tajikistan is endowed with abundant glaciers and water resources.However,the country faces multiple challenges,including accelerated glacier retreat,complex inter-govern...As a major source of freshwater in Central Asia,Tajikistan is endowed with abundant glaciers and water resources.However,the country faces multiple challenges,including accelerated glacier retreat,complex inter-government water resource management,and inefficient water use.Existing research has predominantly focused on individual hydrological processes,such as glacier retreat,snow cover change,or transboundary water issues,but it has yet to fully capture the overall complexity of water system.Tajikistan’s water system functions as an integrated whole from mountain runoff to downstream supply,but a comprehensive study of its water resource has yet to be conducted.To address this research gap,this study systematically examined the status,challenges,and sustainable management strategies of Tajikistan’s water resources based on a literature review,remote sensing data analysis,and case studies.Despite Tajikistan’s relative abundance of water resources,global warming is accelerating glacier melting and altering the hydrological cycles,which have resulted in unstable runoff patterns and heightened risks of extreme events.In Tajikistan,outdated infrastructure and poor management are primary causes of low water-use efficiency in the agricultural sector,which accounts for 85.00%of the total water withdrawals.At the governance level,Tajikistan faces challenges in balancing the water-energy-food nexus and transboundary water resource issues.To address these issues,this study proposes core paths for Tajikistan to achieve sustainable water resource management,such as accelerating technological innovation,promoting water-saving agricultural technologies,improving water resource utilization efficiency,and establishing a community participation-based comprehensive management framework.Additionally,strengthening cross-border cooperation and improving real-time monitoring systems have been identified as critical steps to advance sustainable water resource utilization and evidence-based decision-making in Tajikistan and across Central Asia.展开更多
Chemical warfare agents(CWAs)remain a persistent hazard in many parts of the world,necessitating a deeper exploration of their chemical and physical characteristics and reactions under diverse conditions.Diisopropyl m...Chemical warfare agents(CWAs)remain a persistent hazard in many parts of the world,necessitating a deeper exploration of their chemical and physical characteristics and reactions under diverse conditions.Diisopropyl methylphosphonate(DIMP),a commonly used CWA surrogate,is widely studied to enhance our understanding of CWA behavior.The prevailing thermal decomposition model for DIMP,developed approximately 25 years ago,is based on data collected in nitrogen atmospheres at temperatures ranging from 700 K to 800 K.Despite its limitations,this model continues to serve as a foundation for research across various thermal and reactive environments,including combustion studies.Our recent experiments have extended the scope of decomposition analysis by examining DIMP in both nitrogen and zero air across a lower temperature range of 175??C to 250??C.Infrared spectroscopy results under nitrogen align well with the established model;however,we observed that catalytic effects,stemming from decomposition byproducts and interactions with stainless steel surfaces,alter the reaction kinetics.In zero air environments,we observed a novel infrared absorption band.Spectral fitting suggests this band may represent a combination of propanal and acetone,while GCMS analysis points to vinyl formate and acetone as possible constituents.Although the precise identity of these new products remains unresolved,our findings clearly indicate that the existing decomposition model cannot be reliably extended to lower temperatures or non-nitrogen environments without further revisions.展开更多
BACKGROUND Humeral shaft fractures are common and vary by age,with high-energy trauma observed in younger adults and low-impact injuries in older adults.Radial nerve palsy is a frequent complication.Treatment ranges f...BACKGROUND Humeral shaft fractures are common and vary by age,with high-energy trauma observed in younger adults and low-impact injuries in older adults.Radial nerve palsy is a frequent complication.Treatment ranges from nonoperative methods to surgical interventions such as intramedullary K-wires,which promote faster rehabilitation and improved elbow mobility.AIM To evaluate the outcomes of managing humeral shaft fractures using closed reduction and internal fixation with flexible intramedullary K-wires.METHODS This was a retrospective cohort study analyzing the medical records of patients with humeral shaft fractures managed with flexible intramedullary K-wires at King Abdulaziz Medical City,using non-random sampling and descriptive analysis for outcome evaluation.RESULTS This study assessed the clinical outcomes of 20 patients treated for humeral shaft fractures with intramedullary K-wires.Patients were predominantly male(n=16,80%),had an average age of 39.2 years,and a mean body mass index of 29.5 kg/m^(2).The fractures most frequently occurred in the middle third of the humerus(n=14,70%),with oblique fractures being the most common type(n=7,35%).All surgeries used general anesthesia and a posterior approach,with no intraoperative complications reported.Postoperatively,all patients achieved clinical and radiological union(n=20,100%),and the majority(n=13,65%)reached an elbow range of motion from 0 to 150 degrees.CONCLUSION These results suggest that intramedullary K-wire fixation may be an effective option for treating humeral shaft fractures,with favorable outcomes in range of motion recovery,fracture union,and a low rate of intraoperative complications.展开更多
Objective expertise evaluation of individuals,as a prerequisite stage for team formation,has been a long-term desideratum in large software development companies.With the rapid advancements in machine learning methods...Objective expertise evaluation of individuals,as a prerequisite stage for team formation,has been a long-term desideratum in large software development companies.With the rapid advancements in machine learning methods,based on reliable existing data stored in project management tools’datasets,automating this evaluation process becomes a natural step forward.In this context,our approach focuses on quantifying software developer expertise by using metadata from the task-tracking systems.For this,we mathematically formalize two categories of expertise:technology-specific expertise,which denotes the skills required for a particular technology,and general expertise,which encapsulates overall knowledge in the software industry.Afterward,we automatically classify the zones of expertise associated with each task a developer has worked on using Bidirectional Encoder Representations from Transformers(BERT)-like transformers to handle the unique characteristics of project tool datasets effectively.Finally,our method evaluates the proficiency of each software specialist across already completed projects from both technology-specific and general perspectives.The method was experimentally validated,yielding promising results.展开更多
Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2)...Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2) management in life-support systems of confined space.Here,a micro/nano-reconfigurable robot is constructed from the CO_(2) molecular hunters,temperature-sensitive molecular switch,solar photothermal conversion,and magnetically-driven function engines.The molecular hunters within the molecular extension state can capture 6.19 mmol g^(−1) of CO_(2) to form carbamic acid and ammonium bicarbonate.Interestingly,the molecular switch of the robot activates a molecular curling state that facilitates CO_(2) release through nano-reconfiguration,which is mediated by the temperature-sensitive curling of Pluronic F127 molecular chains during the photothermal desorption.Nano-reconfiguration of robot alters the amino microenvironment,including increasing surface electrostatic potential of the amino group and decreasing overall lowest unoccupied molecular orbital energy level.This weakened the nucleophilic attack ability of the amino group toward the adsorption product derivatives,thereby inhibiting the side reactions that generate hard-to-decompose urea structures,achieving the lowest regeneration temperature of 55℃ reported to date.The engine of the robot possesses non-contact magnetically-driven micro-reconfiguration capability to achieve efficient photothermal regeneration while avoiding local overheating.Notably,the robot successfully prolonged the survival time of mice in the sealed container by up to 54.61%,effectively addressing the issue of carbon suffocation in confined spaces.This work significantly enhances life-support systems for deep-space exploration,while stimulating innovations in sustainable carbon management technologies for terrestrial extreme environments.展开更多
The integration of Artificial Intelligence(AI)and Machine Learning(ML)into groundwater exploration and water resources management has emerged as a transformative approach to addressing global water challenges.This rev...The integration of Artificial Intelligence(AI)and Machine Learning(ML)into groundwater exploration and water resources management has emerged as a transformative approach to addressing global water challenges.This review explores key AI and ML concepts,methodologies,and their applications in hydrology,focusing on groundwater potential mapping,water quality prediction,and groundwater level forecasting.It discusses various data acquisition techniques,including remote sensing,geospatial analysis,and geophysical surveys,alongside preprocessing methods that are essential for enhancing model accuracy.The study highlights AI-driven solutions in water distribution,allocation optimization,and realtime resource management.Despite their advantages,the application of AI and ML in water sciences faces several challenges,including data scarcity,model reliability,and the integration of these tools with traditional water management systems.Ethical and regulatory concerns also demand careful consideration.The paper also outlines future research directions,emphasizing the need for improved data collection,interpretable models,real-time monitoring capabilities,and interdisciplinary collaboration.By leveraging AI and ML advancements,the water sector can enhance decision-making,optimize resource distribution,and support the development of sustainable water management strategies.展开更多
Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods a...Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods allow for EVs to be charged without thought being given to the condition of the battery or the grid demand,thus increasing energy costs and battery aging.This study proposes a smart charging station with an AI-powered Battery Management System(BMS),developed and simulated in MATLAB/Simulink,to increase optimality in energy flow,battery health,and impractical scheduling within the IoEV environment.The system operates through real-time communication,load scheduling based on priorities,and adaptive charging based on batterymathematically computed State of Charge(SOC),State of Health(SOH),and thermal state,with bidirectional power flow(V2G),thus allowing EVs’participation towards grid stabilization.Simulation results revealed that the proposed model can reduce peak grid load by 37.8%;charging efficiency is enhanced by 92.6%;battery temperature lessened by 4.4℃;SOH extended over 100 cycles by 6.5%,if compared against the conventional technique.By this way,charging time was decreased by 12.4% and energy costs dropped by more than 20%.These results showed that smart charging with intelligent BMS can boost greatly the operational efficiency and sustainability of the IoEV ecosystem.展开更多
文摘工业远程控制网关是用来解决数据采集与监控系统和工业计算机之间网络通信的安全问题,给工业网络连接到因特网的时候提供安全保证。该网关普遍适用各类的工业环境,且支持任何工业设备和所有类型的数据采集与监控系统,在工业设备和SC AD A设备之间处理数据包。由于工业设备无法安装使用VPN软件,因此本设计运用M anager/Agent模型的方式来实现VPN的功能。
基金The First Affiliated Hospital of Shaoyang University,China(Project No.:23FY1015)。
文摘The purpose of this study is to investigate the effectiveness of the“expiration manager”mini program in managing the validity of ward items.The program was used to manage frequently and infrequently used consumables by setting up an automatic reminder function.The item failure rate and the time required for nurses to conduct counts over 6 months before and after implementation were compared,as well as evaluated system availability using the System Usability scale(SUS).Results showed that after implementing the mini program,both the item failure rate and non-recognition rate significantly decreased(P<0.05),while the inspection pass rate significantly increased(P<0.05),and the monthly inventory time was reduced(P<0.05).The SUS evaluation yielded a total score of 74.38±11.73,with learnability at 80.21±20.27 and availability at 72.92±11.18,all indicating good user acceptance.In conclusion,the“expiration manager”mini program can effectively improve the efficiency of item expiration management,reduce the risk of expiration,and save inspection time,thereby demonstrating high user acceptance and promising potential for wider adoption.
文摘The development of villas in Bali is very rapid, especially in Badung regency with the distribution of the number of dominant villas in North Kuta district. Based on preliminary study, tourists tend to make reservations through online travel agents （OTA）. Therefore, there is a tendency if the villa manager in North Kuta district makes promotion through OTA. The aim of this research is to explain and analyze the dominant factors that influence the perception of villa managers in North Kuta district on using OTA as marketing media. The population in this research is composed of 191 villas. The final sample villas, using Slovin formula, were chosen based on cluster proportional sampling technique, totally 66 unit villas. Respondent in this research is the villa manager of each sample villa, so there are as much as 66 respondents. For data analysis, we used confirmatory factor analysis and descriptive statistics. In general, the perception of managers in North Kuta district on the use of OTA as marketing media is strongly agree or strongly positive with an average value of 4.37. The analysis of factors simultaneously showed that the perception of villa managers in North Kuta district on the use of OTA is determined by three factors, namely, factor in the self-perception of villa manager （F 1）, the factors in the self-perception of OTA （F2）, and situational factors （F3）.
基金supported by the Science and Technology Project of State Grid Sichuan Electric Power Company Chengdu Power Supply Company under Grant No.521904240005.
文摘This paper presents a novel approach to dynamic pricing and distributed energy management in virtual power plant(VPP)networks using multi-agent reinforcement learning(MARL).As the energy landscape evolves towards greater decentralization and renewable integration,traditional optimization methods struggle to address the inherent complexities and uncertainties.Our proposed MARL framework enables adaptive,decentralized decision-making for both the distribution system operator and individual VPPs,optimizing economic efficiency while maintaining grid stability.We formulate the problem as a Markov decision process and develop a custom MARL algorithm that leverages actor-critic architectures and experience replay.Extensive simulations across diverse scenarios demonstrate that our approach consistently outperforms baseline methods,including Stackelberg game models and model predictive control,achieving an 18.73%reduction in costs and a 22.46%increase in VPP profits.The MARL framework shows particular strength in scenarios with high renewable energy penetration,where it improves system performance by 11.95%compared with traditional methods.Furthermore,our approach demonstrates superior adaptability to unexpected events and mis-predictions,highlighting its potential for real-world implementation.
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supported by National Natural Science Foundation of China(32494793).
文摘Cellulose frameworks have emerged as promising materials for light management due to their exceptional light-scattering capabilities and sustainable nature.Conventional biomass-derived cellulose frameworks face a fundamental trade-off between haze and transparency,coupled with impractical thicknesses(≥1 mm).Inspired by squid’s skin-peeling mechanism,this work develops a peroxyformic acid(HCOOOH)-enabled precision peeling strategy to isolate intact 10-μm-thick bamboo green(BG)frameworks—100×thinner than wood-based counterparts while achieving an unprecedented optical performance(88%haze with 80%transparency).This performance surpasses delignified biomass(transparency<40%at 1 mm)and matches engineered cellulose composites,yet requires no energy-intensive nanofibrillation.The preserved native cellulose I crystalline structure(64.76%crystallinity)and wax-coated uniaxial fibril alignment(Hermans factor:0.23)contribute to high mechanical strength(903 MPa modulus)and broadband light scattering.As a light-management layer in polycrystalline silicon solar cells,the BG framework boosts photoelectric conversion efficiency by 0.41%absolute(18.74%→19.15%),outperforming synthetic anti-reflective coatings.The work establishes a scalable,waste-to-wealth route for optical-grade cellulose materials in next-generation optoelectronics.
基金supported by the National Natural Science Foundation of China(No.22176200)the Industrial Innovation Entrepreneurial Team Project of Ordos 2021.
文摘Industrial waste salts are commonly used to make value-added snow-melting agents to ensure traffic safety in northern China during winter and spring after snowfall.However,heavy metals in industrial waste salts may pose certain environmental risks.Snow-melting agents and snow samples were collected and analyzed from highways,arterial roads,footbridges,and other locations in Beijing after the snowstorm in December 2023.It was found that the main component of snow-melting agents was sodium chloride with high concentrations of Cu,Mn,and Zn,which are not regulated in the current policies,despite the recent promotion of environmentally friendly snow-melting agents.The Pb,Zn and Cr contents of some snow samples exceeded the limitation value of surface water quality standards,potentially affecting the soil and water environment near roadsides,although the snow-melting agents comply with relevant standards,which indicates the policy gap in the management of recycled industrial salts.We reviewed and analyzed the relevant standards for snow-melting agents and industrial waste salts proposed nationally and internationally over the past 30 years.Through comparative analysis,we proposed relevant policy recommendations to the existing quality standards of snow-melting agents and the management regulations of industrial waste salts,and the formulation of corresponding usage strategies,aimed at reducing the potential environmental release of heavy metals from the use of snow-melting agents,thereby promoting more sustainable green urban development and environmentally sound waste management.
基金the National Natural Science Foundation of China(Nos.62374029,22175029,62474033,and W2433038)the Young Elite Scientists Sponsorship Program by CAST(No.YESS20220550)+2 种基金the Sichuan Science and Technology Program(No.2024NSFSC0250)the Natural Science Foundation of Shenzhen Innovation Committee(JCYJ20210324135614040)the Fundamental Research Funds for the Central Universities of China(No.ZYGX2022J032).
文摘Perovskite solar cells(PSCs)have emerged as promising photovoltaic technologies owing to their remarkable power conversion efficiency(PCE).However,heat accumulation under continuous illumination remains a critical bottleneck,severely affecting device stability and long-term operational performance.Herein,we present a multifunctional strategy by incorporating highly thermally conductive Ti_(3)C_(2)T_(X) MXene nanosheets into the perovskite layer to simultaneously enhance thermal management and optoelectronic properties.The Ti_(3)C_(2)T_(X) nanosheets,embedded at perovskite grain boundaries,construct efficient thermal conduction pathways,significantly improving the thermal conductivity and diffusivity of the film.This leads to a notable reduction in the device’s steady-state operating temperature from 42.96 to 39.97 under 100 mW cm^(−2) illumination,thereby alleviating heat-induced performance degradation.Beyond thermal regulation,Ti_(3)C_(2)T_(X),with high conductivity and negatively charged surface terminations,also serves as an effective defect passivation agent,reducing trap-assisted recombination,while simultaneously facilitating charge extraction and transport by optimizing interfacial energy alignment.As a result,the Ti_(3)C_(2)T_(X)-modified PSC achieve a champion PCE of 25.13%and exhibit outstanding thermal stability,retaining 80%of the initial PCE after 500 h of thermal aging at 85 and 30±5%relative humidity.(In contrast,control PSC retain only 58%after 200 h.)Moreover,under continuous maximum power point tracking in N2 atmosphere,Ti_(3)C_(2)T_(X)-modified PSC retained 70%of the initial PCE after 500 h,whereas the control PSC drop sharply to 20%.These findings highlight the synergistic role of Ti_(3)C_(2)T_(X) in thermal management and optoelectronic performance,paving the way for the development of high-efficiency and heat-resistant perovskite photovoltaics.
基金supported by the National Natural Science Foundation of China(W2412135)the Youth Innovation Promotion Association of the Chinese Academy of Sciences.
文摘As a major source of freshwater in Central Asia,Tajikistan is endowed with abundant glaciers and water resources.However,the country faces multiple challenges,including accelerated glacier retreat,complex inter-government water resource management,and inefficient water use.Existing research has predominantly focused on individual hydrological processes,such as glacier retreat,snow cover change,or transboundary water issues,but it has yet to fully capture the overall complexity of water system.Tajikistan’s water system functions as an integrated whole from mountain runoff to downstream supply,but a comprehensive study of its water resource has yet to be conducted.To address this research gap,this study systematically examined the status,challenges,and sustainable management strategies of Tajikistan’s water resources based on a literature review,remote sensing data analysis,and case studies.Despite Tajikistan’s relative abundance of water resources,global warming is accelerating glacier melting and altering the hydrological cycles,which have resulted in unstable runoff patterns and heightened risks of extreme events.In Tajikistan,outdated infrastructure and poor management are primary causes of low water-use efficiency in the agricultural sector,which accounts for 85.00%of the total water withdrawals.At the governance level,Tajikistan faces challenges in balancing the water-energy-food nexus and transboundary water resource issues.To address these issues,this study proposes core paths for Tajikistan to achieve sustainable water resource management,such as accelerating technological innovation,promoting water-saving agricultural technologies,improving water resource utilization efficiency,and establishing a community participation-based comprehensive management framework.Additionally,strengthening cross-border cooperation and improving real-time monitoring systems have been identified as critical steps to advance sustainable water resource utilization and evidence-based decision-making in Tajikistan and across Central Asia.
基金sponsored by the Department of Defense,Defense Threat Reduction Agency under the Materials Science in Extreme Environments University Research Alliance,HDTRA1-20-2-0001。
文摘Chemical warfare agents(CWAs)remain a persistent hazard in many parts of the world,necessitating a deeper exploration of their chemical and physical characteristics and reactions under diverse conditions.Diisopropyl methylphosphonate(DIMP),a commonly used CWA surrogate,is widely studied to enhance our understanding of CWA behavior.The prevailing thermal decomposition model for DIMP,developed approximately 25 years ago,is based on data collected in nitrogen atmospheres at temperatures ranging from 700 K to 800 K.Despite its limitations,this model continues to serve as a foundation for research across various thermal and reactive environments,including combustion studies.Our recent experiments have extended the scope of decomposition analysis by examining DIMP in both nitrogen and zero air across a lower temperature range of 175??C to 250??C.Infrared spectroscopy results under nitrogen align well with the established model;however,we observed that catalytic effects,stemming from decomposition byproducts and interactions with stainless steel surfaces,alter the reaction kinetics.In zero air environments,we observed a novel infrared absorption band.Spectral fitting suggests this band may represent a combination of propanal and acetone,while GCMS analysis points to vinyl formate and acetone as possible constituents.Although the precise identity of these new products remains unresolved,our findings clearly indicate that the existing decomposition model cannot be reliably extended to lower temperatures or non-nitrogen environments without further revisions.
基金approved by King Abdullah International Medical Research Center Ethics Committee(approval No.0000074524).
文摘BACKGROUND Humeral shaft fractures are common and vary by age,with high-energy trauma observed in younger adults and low-impact injuries in older adults.Radial nerve palsy is a frequent complication.Treatment ranges from nonoperative methods to surgical interventions such as intramedullary K-wires,which promote faster rehabilitation and improved elbow mobility.AIM To evaluate the outcomes of managing humeral shaft fractures using closed reduction and internal fixation with flexible intramedullary K-wires.METHODS This was a retrospective cohort study analyzing the medical records of patients with humeral shaft fractures managed with flexible intramedullary K-wires at King Abdulaziz Medical City,using non-random sampling and descriptive analysis for outcome evaluation.RESULTS This study assessed the clinical outcomes of 20 patients treated for humeral shaft fractures with intramedullary K-wires.Patients were predominantly male(n=16,80%),had an average age of 39.2 years,and a mean body mass index of 29.5 kg/m^(2).The fractures most frequently occurred in the middle third of the humerus(n=14,70%),with oblique fractures being the most common type(n=7,35%).All surgeries used general anesthesia and a posterior approach,with no intraoperative complications reported.Postoperatively,all patients achieved clinical and radiological union(n=20,100%),and the majority(n=13,65%)reached an elbow range of motion from 0 to 150 degrees.CONCLUSION These results suggest that intramedullary K-wire fixation may be an effective option for treating humeral shaft fractures,with favorable outcomes in range of motion recovery,fracture union,and a low rate of intraoperative complications.
基金supported by the project“Romanian Hub for Artificial Intelligence-HRIA”,Smart Growth,Digitization and Financial Instruments Program,2021–2027,MySMIS No.334906.
文摘Objective expertise evaluation of individuals,as a prerequisite stage for team formation,has been a long-term desideratum in large software development companies.With the rapid advancements in machine learning methods,based on reliable existing data stored in project management tools’datasets,automating this evaluation process becomes a natural step forward.In this context,our approach focuses on quantifying software developer expertise by using metadata from the task-tracking systems.For this,we mathematically formalize two categories of expertise:technology-specific expertise,which denotes the skills required for a particular technology,and general expertise,which encapsulates overall knowledge in the software industry.Afterward,we automatically classify the zones of expertise associated with each task a developer has worked on using Bidirectional Encoder Representations from Transformers(BERT)-like transformers to handle the unique characteristics of project tool datasets effectively.Finally,our method evaluates the proficiency of each software specialist across already completed projects from both technology-specific and general perspectives.The method was experimentally validated,yielding promising results.
基金supported by the National Natural Science Foundation of China(22168008,22378085)the Guangxi Natural Science Foundation(2024GXNSFDA010053)+1 种基金the Technology Development Project of Guangxi Bossco Environmental Protection Technology Co.,Ltd(202100039)Innovation Project of Guangxi Graduate Education(YCBZ2024065).
文摘Strategically coupling nanoparticle hybrids and internal thermosensitive molecular switches establishes an innovative paradigm for constructing micro/nanoscale-reconfigurable robots,facilitating energyefficient CO_(2) management in life-support systems of confined space.Here,a micro/nano-reconfigurable robot is constructed from the CO_(2) molecular hunters,temperature-sensitive molecular switch,solar photothermal conversion,and magnetically-driven function engines.The molecular hunters within the molecular extension state can capture 6.19 mmol g^(−1) of CO_(2) to form carbamic acid and ammonium bicarbonate.Interestingly,the molecular switch of the robot activates a molecular curling state that facilitates CO_(2) release through nano-reconfiguration,which is mediated by the temperature-sensitive curling of Pluronic F127 molecular chains during the photothermal desorption.Nano-reconfiguration of robot alters the amino microenvironment,including increasing surface electrostatic potential of the amino group and decreasing overall lowest unoccupied molecular orbital energy level.This weakened the nucleophilic attack ability of the amino group toward the adsorption product derivatives,thereby inhibiting the side reactions that generate hard-to-decompose urea structures,achieving the lowest regeneration temperature of 55℃ reported to date.The engine of the robot possesses non-contact magnetically-driven micro-reconfiguration capability to achieve efficient photothermal regeneration while avoiding local overheating.Notably,the robot successfully prolonged the survival time of mice in the sealed container by up to 54.61%,effectively addressing the issue of carbon suffocation in confined spaces.This work significantly enhances life-support systems for deep-space exploration,while stimulating innovations in sustainable carbon management technologies for terrestrial extreme environments.
文摘The integration of Artificial Intelligence(AI)and Machine Learning(ML)into groundwater exploration and water resources management has emerged as a transformative approach to addressing global water challenges.This review explores key AI and ML concepts,methodologies,and their applications in hydrology,focusing on groundwater potential mapping,water quality prediction,and groundwater level forecasting.It discusses various data acquisition techniques,including remote sensing,geospatial analysis,and geophysical surveys,alongside preprocessing methods that are essential for enhancing model accuracy.The study highlights AI-driven solutions in water distribution,allocation optimization,and realtime resource management.Despite their advantages,the application of AI and ML in water sciences faces several challenges,including data scarcity,model reliability,and the integration of these tools with traditional water management systems.Ethical and regulatory concerns also demand careful consideration.The paper also outlines future research directions,emphasizing the need for improved data collection,interpretable models,real-time monitoring capabilities,and interdisciplinary collaboration.By leveraging AI and ML advancements,the water sector can enhance decision-making,optimize resource distribution,and support the development of sustainable water management strategies.
文摘Rapid evolutions of the Internet of Electric Vehicles(IoEVs)are reshaping and modernizing transport systems,yet challenges remain in energy efficiency,better battery aging,and grid stability.Typical charging methods allow for EVs to be charged without thought being given to the condition of the battery or the grid demand,thus increasing energy costs and battery aging.This study proposes a smart charging station with an AI-powered Battery Management System(BMS),developed and simulated in MATLAB/Simulink,to increase optimality in energy flow,battery health,and impractical scheduling within the IoEV environment.The system operates through real-time communication,load scheduling based on priorities,and adaptive charging based on batterymathematically computed State of Charge(SOC),State of Health(SOH),and thermal state,with bidirectional power flow(V2G),thus allowing EVs’participation towards grid stabilization.Simulation results revealed that the proposed model can reduce peak grid load by 37.8%;charging efficiency is enhanced by 92.6%;battery temperature lessened by 4.4℃;SOH extended over 100 cycles by 6.5%,if compared against the conventional technique.By this way,charging time was decreased by 12.4% and energy costs dropped by more than 20%.These results showed that smart charging with intelligent BMS can boost greatly the operational efficiency and sustainability of the IoEV ecosystem.
