Traffic at urban intersections frequently encounters unexpected obstructions,resulting in congestion due to uncooperative and priority-based driving behavior.This paper presents an optimal right-turn coordination syst...Traffic at urban intersections frequently encounters unexpected obstructions,resulting in congestion due to uncooperative and priority-based driving behavior.This paper presents an optimal right-turn coordination system for Connected and Automated Vehicles(CAVs)at single-lane intersections,particularly in the context of left-hand side driving on roads.The goal is to facilitate smooth right turns for certain vehicles without creating bottlenecks.We consider that all approaching vehicles share relevant information through vehicular communications.The Intersection Coordination Unit(ICU)processes this information and communicates the optimal crossing or turning times to the vehicles.The primary objective of this coordination is to minimize overall traffic delays,which also helps improve the fuel consumption of vehicles.By considering information from upcoming vehicles at the intersection,the coordination system solves an optimization problem to determine the best timing for executing right turns,ultimately minimizing the total delay for all vehicles.The proposed coordination system is evaluated at a typical urban intersection,and its performance is compared to traditional traffic systems.Numerical simulation results indicate that the proposed coordination system significantly enhances the average traffic speed and fuel consumption compared to the traditional traffic system in various scenarios.展开更多
Artificial sensory systems mimic the five human senses to facilitate data interaction between the real and virtual worlds.Accurate data analysis is crucial for converting external stimuli from each artificial sense in...Artificial sensory systems mimic the five human senses to facilitate data interaction between the real and virtual worlds.Accurate data analysis is crucial for converting external stimuli from each artificial sense into user-relevant information,yet conventional signal processing methods struggle with the massive scale,noise,and artificial sensory systems characteristics of data generated by artificial sensory devices.Integrating artificial intelligence(AI)is essential for addressing these challenges and enhancing the performance of artificial sensory systems,making it a rapidly growing area of research in recent years.However,no studies have systematically categorized the output functions of these systems or analyzed the associated AI algorithms and data processing methods.In this review,we present a systematic overview of the latest AI techniques aimed at enhancing the cognitive capabilities of artificial sensory systems replicating the five human senses:touch,taste,vision,smell,and hearing.We categorize the AI-enabled capabilities of artificial sensory systems into four key areas:cognitive simulation,perceptual enhancement,adaptive adjustment,and early warning.We introduce specialized AI algorithms and raw data processing methods for each function,designed to enhance and optimize sensing performance.Finally,we offer a perspective on the future of AI-integrated artificial sensory systems,highlighting technical challenges and potential real-world application scenarios for further innovation.Integration of AI with artificial sensory systems will enable advanced multimodal perception,real-time learning,and predictive capabilities.This will drive precise environmental adaptation and personalized feedback,ultimately positioning these systems as foundational technologies in smart healthcare,agriculture,and automation.展开更多
To investigate groundwater flow and solute transport characteristics of the karst trough zone in China,tracer experiments were conducted at two adjacent typical karst groundwater flow systems(Yuquandong(YQD)and Migong...To investigate groundwater flow and solute transport characteristics of the karst trough zone in China,tracer experiments were conducted at two adjacent typical karst groundwater flow systems(Yuquandong(YQD)and Migongquan(MGQ))in Sixi valley,western Hubei,China.Highresolution continuous monitoring was utilized to obtain breakthrough curves(BTCs),which were then analyzed using the multi-dispersion model(MDM)and the two-region nonequilibrium model(2RNE)with basic parameters calculated by CXTFIT and QTRACER2.Results showed that:(1)YQD flow system had a complex infiltration matrix with overland flow,conduit flow and fracture flow,while the MGQ flow system was dominated by conduit flow with fast flow transport velocity,but also small amount of fracture flow there;(2)They were well fitted based on the MDM(R^2=0.928)and 2RNE(R^2=0.947)models,indicating that they had strong adaptability in the karst trough zone;(3)conceptual models for YQD and MGQ groundwater systems were generalized.In YQD system,the solute was transported via overland flow during intense rainfall,while some infiltrated down into fissures and conduits.In MGQ system,most were directly transported to spring outlet in the fissureconduit network.展开更多
The ability to control the preparation of one-dimensional(1D)porous carbon nanorods,especially during rapid polymerization,is key to their practical application.We report a method for synthesizing 1D porous carbon nan...The ability to control the preparation of one-dimensional(1D)porous carbon nanorods,especially during rapid polymerization,is key to their practical application.We report a method for synthesizing 1D porous carbon nanorods,characterized by the formation of rod-like mi-celles that are assembled from sodium palmitate and Pluronic F127,facilitated by protonated melamine,and subsequently converted into melamine-based N-doped polymer nanorods which were carbonized to produce the corres-ponding N-doped carbon nanorods.The specific capacitance of the supercapacitor used the as-pre-pared N-doped nanorods as electrode material in a three-electrode system was calculated to be 301.66 F g^(-1) at a current density of 0.2 A g^(-1),with an ultra-high specific surface area normalized capacitance of up to 67.07μF cm^(-2).The N-doping and their one-dimensionality give the nanorods a low internal resistance and good stability,making them well suited for fundamental studies and practical applications ranging from materials chemistry to electrochemical energy storage.展开更多
1.Background In the chemical industry,process plants-commonly referred to as plantwide systems-typically consist of many process units(unit operations).Driven by the considerable economic efficiency offered by complex...1.Background In the chemical industry,process plants-commonly referred to as plantwide systems-typically consist of many process units(unit operations).Driven by the considerable economic efficiency offered by complex and interactive process designs,modern plantwide systems are becoming increasingly sophisticated.The operation of these processes is typically characterized by the complexity of individual units(subsystems)and the intricate interactions between geographically distributed units through networks of material and energy flows,as well as control loops[1].展开更多
Fiber quality measurement in spinning preparation is crucial for optimizing waste and meeting yarn quality specifications.The brand-new Uster AFIS 6–the next-generation laboratory instrument from Uster Technologies–...Fiber quality measurement in spinning preparation is crucial for optimizing waste and meeting yarn quality specifications.The brand-new Uster AFIS 6–the next-generation laboratory instrument from Uster Technologies–uniquely tests man-made fiber properties in addition to cotton.It provides critical data to optimize fiber process control for cotton,man-made fibers,and blended yarns.展开更多
Accurate quantification of life-cycle greenhouse gas(GHG)footprints(GHG_(fp))for a crop cultivation system is urgently needed to address the conflict between food security and global warming mitigation.In this study,t...Accurate quantification of life-cycle greenhouse gas(GHG)footprints(GHG_(fp))for a crop cultivation system is urgently needed to address the conflict between food security and global warming mitigation.In this study,the hydrobiogeochemical model,CNMM-DNDC,was validated with in situ observations from maize-based cultivation systems at the sites of Yongji(YJ,China),Yanting(YT,China),and Madeya(MA,Kenya),subject to temperate,subtropical,and tropical climates,respectively,and updated to enable life-cycle GHG_(fp)estimation.The model validation provided satisfactory simulations on multiple soil variables,crop growth,and emissions of GHGs and reactive nitrogen gases.The locally conventional management practices resulted in GHG_(fp)values of 0.35(0.09–0.53 at the 95%confidence interval),0.21(0.01–0.73),0.46(0.27–0.60),and 0.54(0.21–0.77)kg CO_(2)e kg~(-1)d.m.(d.m.for dry matter in short)for maize–wheat rotation at YJ and YT,and for maize–maize and maize–Tephrosia rotations at MA,respectively.YT's smallest GHG_(fp)was attributed to its lower off-farm GHG emissions than YJ,though the soil organic carbon(SOC)storage and maize yield were slightly lower than those of YJ.MA's highest SOC loss and low yield in shifting cultivation for maize–Tephrosia rotation contributed to its highest GHG_(fp).Management practices of maize cultivation at these sites could be optimized by combination of synthetic and organic fertilizer(s)while incorporating 50%–100%crop residues.Further evaluation of the updated CNMM-DNDC is needed for different crops at site and regional scales to confirm its worldwide applicability in quantifying GHG_(fp)and optimizing management practices for achieving multiple sustainability goals.展开更多
With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Alth...With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Although distributed streaming data processing frameworks such asApache Flink andApache Spark Streaming provide solutions,meeting stringent response time requirements while ensuring high throughput and resource utilization remains an urgent problem.To address this,the study proposes a formal modeling approach based on Performance Evaluation Process Algebra(PEPA),which abstracts the core components and interactions of cloud-based distributed streaming data processing systems.Additionally,a generic service flow generation algorithmis introduced,enabling the automatic extraction of service flows fromthe PEPAmodel and the computation of key performance metrics,including response time,throughput,and resource utilization.The novelty of this work lies in the integration of PEPA-based formal modeling with the service flow generation algorithm,bridging the gap between formal modeling and practical performance evaluation for IoT systems.Simulation experiments demonstrate that optimizing the execution efficiency of components can significantly improve system performance.For instance,increasing the task execution rate from 10 to 100 improves system performance by 9.53%,while further increasing it to 200 results in a 21.58%improvement.However,diminishing returns are observed when the execution rate reaches 500,with only a 0.42%gain.Similarly,increasing the number of TaskManagers from 10 to 20 improves response time by 18.49%,but the improvement slows to 6.06% when increasing from 20 to 50,highlighting the importance of co-optimizing component efficiency and resource management to achieve substantial performance gains.This study provides a systematic framework for analyzing and optimizing the performance of IoT systems for large-scale real-time streaming data processing.The proposed approach not only identifies performance bottlenecks but also offers insights into improving system efficiency under different configurations and workloads.展开更多
The multi-stage development strategy is often adopted in the gas field.However,when the productivity decline occurs,many large processing stations will be severely idle and underutilized,significantly reducing operati...The multi-stage development strategy is often adopted in the gas field.However,when the productivity decline occurs,many large processing stations will be severely idle and underutilized,significantly reducing operating efficiency and revenue.This study proposes a novel operation mode of multiple gathering production systems for gas field multi-stage development,integrating the decisions about processing capacity allocation and infrastructure construction to share processing stations and improve multi-system operating efficiency.A multi-period mixed integer linear programming model for multisystem operation optimization is established to optimize the net present value(NPV),considering the production of gas wells,time-varying gas prices,and the capacity of processing stations.The decision of processing capacity,location,construction timing,and capacity expansion of processing stations,as well as transmission capacity of pipelines and processing capacity allocation schemes,can be obtained to meet long-term production demand.Furthermore,a real case study indicates that the proposed processing capacity allocation approach not only has a shorter payback period and increases NPV by 4.8%,but also increases the utilization efficiency of processing stations from 27.37% to 48.94%.This work demonstrates that the synergy between the processing capacity allocation and infrastructure construction can hedge against production fluctuations and increase potential profits.展开更多
The Ground-based Wide-Angle Cameras array necessitates the integration of more than 100 hardware devices,100 servers,and 2500 software modules that must be synchronized within a 3-second imaging cycle.However,the comp...The Ground-based Wide-Angle Cameras array necessitates the integration of more than 100 hardware devices,100 servers,and 2500 software modules that must be synchronized within a 3-second imaging cycle.However,the complexity of real-time,high-concurrency processing of large datasets has historically resulted in substantial failure rates,with an observation efficiency estimated at less than 50%in 2023.To mitigate these challenges,we developed a monitoring system designed to improve fault diagnosis efficiency.It includes two innovative monitoring views for“state evolution”and“transient lifecycle”.Combining these with“instantaneous state”and“key parameter”monitoring views,the system represents a comprehensive monitoring strategy.Here we detail the system architecture,data collection methods,and design philosophy of the monitoring views.During one year of fault diagnosis experimental practice,the proposed system demonstrated its ability to identify and localize faults within minutes,achieving fault localization nearly ten times faster than traditional methods.Additionally,the system design exhibited high generalizability,with possible applicability to other telescope array systems.展开更多
This article focuses on the remote diagnosis and analysis of rail vehicle status based on the data of the Train Control Management System(TCMS).It first expounds on the importance of train diagnostic analysis and desi...This article focuses on the remote diagnosis and analysis of rail vehicle status based on the data of the Train Control Management System(TCMS).It first expounds on the importance of train diagnostic analysis and designs a unified TCMS data frame transmission format.Subsequently,a remote data transmission link using 4G signals and data processing methods is introduced.The advantages of remote diagnosis are analyzed,and common methods such as correlation analysis,fault diagnosis,and fault prediction are explained in detail.Then,challenges such as data security and the balance between diagnostic accuracy and real-time performance are discussed,along with development prospects in technological innovation,algorithm optimization,and application promotion.This research provides ideas for remote analysis and diagnosis based on TCMS data,contributing to the safe and efficient operation of rail vehicles.展开更多
Chimeric antigen receptor natural killer(CAR-NK)cell therapy is an alternative immunotherapy that provides robust tumor-eliminating effects without inducing life-threatening toxicities and graft-versus-host disease.CA...Chimeric antigen receptor natural killer(CAR-NK)cell therapy is an alternative immunotherapy that provides robust tumor-eliminating effects without inducing life-threatening toxicities and graft-versus-host disease.CAR-NK cell therapy has enabled the development of“off-the-shelf”products that bypass the lengthy and expensive cell manufacturing process1.展开更多
With the advancement of artificial intelligence,optic in-sensing reservoir computing based on emerging semiconductor devices is high desirable for real-time analog signal processing.Here,we disclose a flexible optomem...With the advancement of artificial intelligence,optic in-sensing reservoir computing based on emerging semiconductor devices is high desirable for real-time analog signal processing.Here,we disclose a flexible optomemristor based on C_(27)H_(30)O_(15)/FeOx heterostructure that presents a highly sensitive to the light stimuli and artificial optic synaptic features such as short-and long-term plasticity(STP and LTP),enabling the developed optomemristor to implement complex analogy signal processing through building a real-physical dynamic-based in-sensing reservoir computing algorithm and yielding an accuracy of 94.88%for speech recognition.The charge trapping and detrapping mediated by the optic active layer of C_(27)H_(30)O_(15) that is extracted from the lotus flower is response for the positive photoconductance memory in the prepared optomemristor.This work provides a feasible organic−inorganic heterostructure as well as an optic in-sensing vision computing for an advanced optic computing system in future complex signal processing.展开更多
In the anticorrosive coating line of a welded tube plant, the current status and existing problems of the medium-frequency induction heating equipment were discussed.Partial renovations of the power control cabinet ha...In the anticorrosive coating line of a welded tube plant, the current status and existing problems of the medium-frequency induction heating equipment were discussed.Partial renovations of the power control cabinet have been conducted.Parameters such as the DC current, DC voltage, intermediate frequency power, heating temperature, and the positioning signal at the pipe end were collected.A data acquisition and processing system, which can process data according to user needs and provide convenient data processing functions, has been developed using LabVIEW software.This system has been successfully applied in the coating line for the automatic control of high-power induction heating equipment, production management, and digital steel tube and/or digital delivery.展开更多
The food processing industry generates large quantities of wastewater rich in organic matter and nutrients,which poses significant environmental pressures while also serving as a valuable resource carrier.The sector i...The food processing industry generates large quantities of wastewater rich in organic matter and nutrients,which poses significant environmental pressures while also serving as a valuable resource carrier.The sector is transitioning from simple compliance-based discharge to an integrated management model of“reduction–reuse–resource recovery.”For water reclamation,multi-layer membrane technologies have become the mainstream advanced treatment approach,significantly increasing reuse rates.Treated water can be used for cooling,washing,and even certain production processes,effectively reducing freshwater consumption.In terms of resource recovery,anaerobic digestion technology has matured and is widely applied for biogas production,while recovering high-value substances from wastewater has become a research focus.Nevertheless,challenges such as large fluctuations in wastewater composition,high treatment costs,and incomplete regulatory standards for reclaimed water and by-products(e.g.,fertilizers)hinder wider adoption.Moving forward,it is essential to strengthen collaboration among industry,academia,and research institutions to develop more economical and adaptable integrated technological solutions,fostering closed-loop water resource management and promoting green,low-carbon development in the food processing industry.展开更多
Performance-based warranties(PBWs)are widely used in industry and manufacturing.Given that PBW can impose financial burdens on manufacturers,rational maintenance decisions are essential for expanding profit margins.Th...Performance-based warranties(PBWs)are widely used in industry and manufacturing.Given that PBW can impose financial burdens on manufacturers,rational maintenance decisions are essential for expanding profit margins.This paper proposes an optimization model for PBW decisions for systems affected by Gamma degradation processes,incorporating periodic inspection.A system performance degradation model is established.Preventive maintenance probability and corrective renewal probability models are developed to calculate expected warranty costs and system availability.A benefits function,which includes incentives,is constructed to optimize the initial and subsequent inspection intervals and preventive maintenance thresholds,thereby maximizing warranty profit.An improved sparrow search algorithm is developed to optimize the model,with a case study on large steam turbine rotor shafts.The results suggest the optimal PBW strategy involves an initial inspection interval of approximately 20 months,with subsequent intervals of about four months,and a preventive maintenance threshold of approximately 37.39 mm wear.When compared to common cost-minimization-based condition maintenance strategies and PBW strategies that do not differentiate between initial and subsequent inspection intervals,the proposed PBW strategy increases the manufacturer’s profit by 1%and 18%,respectively.Sensitivity analyses provide managerial recommendations for PBW implementation.The PBW strategy proposed in this study significantly increases manufacturers’profits by optimizing inspection intervals and preventive maintenance thresholds,and manufacturers should focus on technological improvement in preventive maintenance and cost control to further enhance earnings.展开更多
Wheat-maize(WM)and wheat-soybean(WS)double-cropping rotation systems are predominant in the North China Plain,with implications for national agricultural output and sustainability.As rotation systems exert legacy effe...Wheat-maize(WM)and wheat-soybean(WS)double-cropping rotation systems are predominant in the North China Plain,with implications for national agricultural output and sustainability.As rotation systems exert legacy effects on soil health and crop productivity,the role of crop rotation in shaping the root-associated microbiome of the succeeding crops has emerged as a pivotal aspect of crop management research.Here,the effects of the preceding two cycles of WM and WS rotations on the recruitment and filtering of wheat root-associated bacterial communities across wheat developmental stages were investigated.Our results revealed that bacterial community diversity and composition were primarily influenced by compartment and developmental stage,while the preceding rotation systems had a slight but significant effect on wheat root-associated bacterial communities.The co-occurrence networks under WM were more complex in the wheat rhizosphere and rhizoplane,with the operational taxonomic units(OTUs)related to cellulolysis showing greater connectivity.The co-occurrence networks under WS were simple but stable in the rhizosphere and complex in the rhizoplane and endosphere,with the OTUs related to ureolysis and nitrogen fixation showing greater connectivity.While both stochastic and deterministic processes contributed to the assembly of wheat root-associated bacterial communities,the contributions of deterministic processes under WS were 19.4-38.5%higher than those under the WM rotation across the root-associated compartments,indicating the substantial impact of a soybean legacy effect on wheat root selection of microbes.Plant growthpromoting rhizobacteria with the potential to fix nitrogen,produce indole-3-acetic acid,and inhibit diseases such as Betaproteobacteriales,Azospirillales and Dyella sp.,were identified within the OTUs that were consistently enriched across all the wheat root-associated compartments and developmental stages,which were also important predictors of wheat yield.This study elucidates the role of crop rotation in modulating the dynamics of crop root-associated bacterial communities,and underscores the potential of targeted microbiome manipulation for optimizing wheat production and enhancing soil health.展开更多
With the advent of the big data era,real-time data analysis and decision-support systems have been recognized as essential tools for enhancing enterprise competitiveness and optimizing the decision-making process.This...With the advent of the big data era,real-time data analysis and decision-support systems have been recognized as essential tools for enhancing enterprise competitiveness and optimizing the decision-making process.This study aims to explore the development strategies of real-time data analysis and decision-support systems,and analyze their application status and future development trends in various industries.The article first reviews the basic concepts and importance of real-time data analysis and decision-support systems,and then discusses in detail the key technical aspects such as system architecture,data collection and processing,analysis methods,and visualization techniques.展开更多
Microplastics(MPs)are ubiquitous in the environment,continuously undergo aging processes and release toxic chemical substances.Understanding the environmental behaviors of MPs is critical to accurately evaluate their ...Microplastics(MPs)are ubiquitous in the environment,continuously undergo aging processes and release toxic chemical substances.Understanding the environmental behaviors of MPs is critical to accurately evaluate their long-term ecological risk.Generalized twodimensional correlation spectroscopy(2D-COS)is a powerful tool for MPs studies,which can dig more comprehensive information hiding in the conventional one-dimensional spectra,such as infrared(IR)and Raman spectra.The recent applications of 2D-COS in analyzing the behaviors and fates of MPs in the environment,including their aging processes,and interactions with natural organicmatter(NOM)or other chemical substances,were summarized systematically.The main requirements and limitations of current approaches for exploring these processes are discussed,and the corresponding strategies to address these limitations and drawbacks are proposed as well.Finally,new trends of 2D-COS are prospected for analyzing the properties and behaviors of MPs in both natural and artificial environmental processes.展开更多
The persistence of chlorinated alkanes in aquatic environments poses significant health risks due to its biotoxicity and high volatility,which contributes to both water and air pollution.This study investigates the ef...The persistence of chlorinated alkanes in aquatic environments poses significant health risks due to its biotoxicity and high volatility,which contributes to both water and air pollution.This study investigates the efficacy of carbon dioxide radical anion(CO_(2)·^(-))mediated advanced reduction processes(ARPs)for the reductive dechlorination of chlorinated alkanes using small molecular monocarboxylic acids(SMAs)under UV irradiation.The study focused on formic acid(HCOOH),acetic acid(CH_3COOH),and propionic acid(CH_3CH_(2)COOH)to generate CO_(2)·^(-),revealing that UV/HCOOH system exhibits a notably high chloroform(CF)degradation efficiency of 97.8%in 90 min.Kinetic studies indicated a linear relationship between the HCOOH concentrations and the observed reaction rate constants(k_(obs)),demonstrating that CO_(2)·^(-)production is crucial for CF degradation.Electron paramagnetic resonance spectroscopy identified CO_(2)·^(-)and hydroxyl radicals(HO·)as the active species,with the former playing a predominant role in CF degradation.The study also explored the influence of carbon chain length in SMAs on CF degradation,finding that longer chains decrease the degradation efficiency,potentially due to reduced UV activation.A higher reaction rate constant(k_(obs))under acidic conditions,with a marked decrease in efficiency as the pH exceeds 3.7,where HCOO^(-)becomes predominant.This study enhances our understanding of CO_(2)·^(-)mediated ARPs and explores potential applications in environmental remediation,providing insights into the pathways and mechanisms of CF degradation.The UV/SMAs systems offer advantages for practical applications,such as milder reaction conditions and higher efficiency compared to traditional methods.展开更多
基金supported by the Japan Society for the Promotion of Science(JSPS)Grants-in-Aid for Scientific Research(C)23K03898.
文摘Traffic at urban intersections frequently encounters unexpected obstructions,resulting in congestion due to uncooperative and priority-based driving behavior.This paper presents an optimal right-turn coordination system for Connected and Automated Vehicles(CAVs)at single-lane intersections,particularly in the context of left-hand side driving on roads.The goal is to facilitate smooth right turns for certain vehicles without creating bottlenecks.We consider that all approaching vehicles share relevant information through vehicular communications.The Intersection Coordination Unit(ICU)processes this information and communicates the optimal crossing or turning times to the vehicles.The primary objective of this coordination is to minimize overall traffic delays,which also helps improve the fuel consumption of vehicles.By considering information from upcoming vehicles at the intersection,the coordination system solves an optimization problem to determine the best timing for executing right turns,ultimately minimizing the total delay for all vehicles.The proposed coordination system is evaluated at a typical urban intersection,and its performance is compared to traditional traffic systems.Numerical simulation results indicate that the proposed coordination system significantly enhances the average traffic speed and fuel consumption compared to the traditional traffic system in various scenarios.
基金supported by the National Research Foundation(NRF)grant funded by the Korean government(MSIT)(RS-2023-00211580,RS-2023-00237308).
文摘Artificial sensory systems mimic the five human senses to facilitate data interaction between the real and virtual worlds.Accurate data analysis is crucial for converting external stimuli from each artificial sense into user-relevant information,yet conventional signal processing methods struggle with the massive scale,noise,and artificial sensory systems characteristics of data generated by artificial sensory devices.Integrating artificial intelligence(AI)is essential for addressing these challenges and enhancing the performance of artificial sensory systems,making it a rapidly growing area of research in recent years.However,no studies have systematically categorized the output functions of these systems or analyzed the associated AI algorithms and data processing methods.In this review,we present a systematic overview of the latest AI techniques aimed at enhancing the cognitive capabilities of artificial sensory systems replicating the five human senses:touch,taste,vision,smell,and hearing.We categorize the AI-enabled capabilities of artificial sensory systems into four key areas:cognitive simulation,perceptual enhancement,adaptive adjustment,and early warning.We introduce specialized AI algorithms and raw data processing methods for each function,designed to enhance and optimize sensing performance.Finally,we offer a perspective on the future of AI-integrated artificial sensory systems,highlighting technical challenges and potential real-world application scenarios for further innovation.Integration of AI with artificial sensory systems will enable advanced multimodal perception,real-time learning,and predictive capabilities.This will drive precise environmental adaptation and personalized feedback,ultimately positioning these systems as foundational technologies in smart healthcare,agriculture,and automation.
基金supported by the National Natural Science Foundation of China(Nos.42007178 and 41907327)the Natural Science Foundation of Hubei(Nos.2020CFB463 and 2019CFB372)+4 种基金China Geological Survey(Nos.DD20160304 and DD20190824)Fundamental Research Funds for the Central Universities(Nos.CUG 190644 and CUGL180817)National Key Research and Development Program(No.2019YFC1805502)Key Laboratory of Karst Dynamics,MNR and GZAR(Institute of Karst Geology,CAGS)Guilin(No.KDL201703)Key Laboratory of Karst Ecosystem and Treatment of Rocky Desertification,MNR and IRCK by UNESCO(No.KDL201903)。
文摘To investigate groundwater flow and solute transport characteristics of the karst trough zone in China,tracer experiments were conducted at two adjacent typical karst groundwater flow systems(Yuquandong(YQD)and Migongquan(MGQ))in Sixi valley,western Hubei,China.Highresolution continuous monitoring was utilized to obtain breakthrough curves(BTCs),which were then analyzed using the multi-dispersion model(MDM)and the two-region nonequilibrium model(2RNE)with basic parameters calculated by CXTFIT and QTRACER2.Results showed that:(1)YQD flow system had a complex infiltration matrix with overland flow,conduit flow and fracture flow,while the MGQ flow system was dominated by conduit flow with fast flow transport velocity,but also small amount of fracture flow there;(2)They were well fitted based on the MDM(R^2=0.928)and 2RNE(R^2=0.947)models,indicating that they had strong adaptability in the karst trough zone;(3)conceptual models for YQD and MGQ groundwater systems were generalized.In YQD system,the solute was transported via overland flow during intense rainfall,while some infiltrated down into fissures and conduits.In MGQ system,most were directly transported to spring outlet in the fissureconduit network.
文摘The ability to control the preparation of one-dimensional(1D)porous carbon nanorods,especially during rapid polymerization,is key to their practical application.We report a method for synthesizing 1D porous carbon nanorods,characterized by the formation of rod-like mi-celles that are assembled from sodium palmitate and Pluronic F127,facilitated by protonated melamine,and subsequently converted into melamine-based N-doped polymer nanorods which were carbonized to produce the corres-ponding N-doped carbon nanorods.The specific capacitance of the supercapacitor used the as-pre-pared N-doped nanorods as electrode material in a three-electrode system was calculated to be 301.66 F g^(-1) at a current density of 0.2 A g^(-1),with an ultra-high specific surface area normalized capacitance of up to 67.07μF cm^(-2).The N-doping and their one-dimensionality give the nanorods a low internal resistance and good stability,making them well suited for fundamental studies and practical applications ranging from materials chemistry to electrochemical energy storage.
基金the National Natural Science Foundation of China(NSFC)(62103283)the Australia Research Council’s Discovery Pro-jects Scheme(DP220100355).
文摘1.Background In the chemical industry,process plants-commonly referred to as plantwide systems-typically consist of many process units(unit operations).Driven by the considerable economic efficiency offered by complex and interactive process designs,modern plantwide systems are becoming increasingly sophisticated.The operation of these processes is typically characterized by the complexity of individual units(subsystems)and the intricate interactions between geographically distributed units through networks of material and energy flows,as well as control loops[1].
文摘Fiber quality measurement in spinning preparation is crucial for optimizing waste and meeting yarn quality specifications.The brand-new Uster AFIS 6–the next-generation laboratory instrument from Uster Technologies–uniquely tests man-made fiber properties in addition to cotton.It provides critical data to optimize fiber process control for cotton,man-made fibers,and blended yarns.
基金jointly supported by the National Key R&D Program of China(Grant No.2022YFE0209200)the National Natural Science Foundation of China(Grant Nos.U22A20562,42330607 and 41761144054)the National Large Scientific and Technological Infrastructure“Earth System Science Numerical Simulator Facility”(Earth-Lab)(https://cstr.cn/31134.02.EL)。
文摘Accurate quantification of life-cycle greenhouse gas(GHG)footprints(GHG_(fp))for a crop cultivation system is urgently needed to address the conflict between food security and global warming mitigation.In this study,the hydrobiogeochemical model,CNMM-DNDC,was validated with in situ observations from maize-based cultivation systems at the sites of Yongji(YJ,China),Yanting(YT,China),and Madeya(MA,Kenya),subject to temperate,subtropical,and tropical climates,respectively,and updated to enable life-cycle GHG_(fp)estimation.The model validation provided satisfactory simulations on multiple soil variables,crop growth,and emissions of GHGs and reactive nitrogen gases.The locally conventional management practices resulted in GHG_(fp)values of 0.35(0.09–0.53 at the 95%confidence interval),0.21(0.01–0.73),0.46(0.27–0.60),and 0.54(0.21–0.77)kg CO_(2)e kg~(-1)d.m.(d.m.for dry matter in short)for maize–wheat rotation at YJ and YT,and for maize–maize and maize–Tephrosia rotations at MA,respectively.YT's smallest GHG_(fp)was attributed to its lower off-farm GHG emissions than YJ,though the soil organic carbon(SOC)storage and maize yield were slightly lower than those of YJ.MA's highest SOC loss and low yield in shifting cultivation for maize–Tephrosia rotation contributed to its highest GHG_(fp).Management practices of maize cultivation at these sites could be optimized by combination of synthetic and organic fertilizer(s)while incorporating 50%–100%crop residues.Further evaluation of the updated CNMM-DNDC is needed for different crops at site and regional scales to confirm its worldwide applicability in quantifying GHG_(fp)and optimizing management practices for achieving multiple sustainability goals.
基金funded by the Joint Project of Industry-University-Research of Jiangsu Province(Grant:BY20231146).
文摘With the widespread application of Internet of Things(IoT)technology,the processing of massive realtime streaming data poses significant challenges to the computational and data-processing capabilities of systems.Although distributed streaming data processing frameworks such asApache Flink andApache Spark Streaming provide solutions,meeting stringent response time requirements while ensuring high throughput and resource utilization remains an urgent problem.To address this,the study proposes a formal modeling approach based on Performance Evaluation Process Algebra(PEPA),which abstracts the core components and interactions of cloud-based distributed streaming data processing systems.Additionally,a generic service flow generation algorithmis introduced,enabling the automatic extraction of service flows fromthe PEPAmodel and the computation of key performance metrics,including response time,throughput,and resource utilization.The novelty of this work lies in the integration of PEPA-based formal modeling with the service flow generation algorithm,bridging the gap between formal modeling and practical performance evaluation for IoT systems.Simulation experiments demonstrate that optimizing the execution efficiency of components can significantly improve system performance.For instance,increasing the task execution rate from 10 to 100 improves system performance by 9.53%,while further increasing it to 200 results in a 21.58%improvement.However,diminishing returns are observed when the execution rate reaches 500,with only a 0.42%gain.Similarly,increasing the number of TaskManagers from 10 to 20 improves response time by 18.49%,but the improvement slows to 6.06% when increasing from 20 to 50,highlighting the importance of co-optimizing component efficiency and resource management to achieve substantial performance gains.This study provides a systematic framework for analyzing and optimizing the performance of IoT systems for large-scale real-time streaming data processing.The proposed approach not only identifies performance bottlenecks but also offers insights into improving system efficiency under different configurations and workloads.
基金supported by Zhejiang Provincial Natural Science Foundation of China under Grant No.LQ23E040004。
文摘The multi-stage development strategy is often adopted in the gas field.However,when the productivity decline occurs,many large processing stations will be severely idle and underutilized,significantly reducing operating efficiency and revenue.This study proposes a novel operation mode of multiple gathering production systems for gas field multi-stage development,integrating the decisions about processing capacity allocation and infrastructure construction to share processing stations and improve multi-system operating efficiency.A multi-period mixed integer linear programming model for multisystem operation optimization is established to optimize the net present value(NPV),considering the production of gas wells,time-varying gas prices,and the capacity of processing stations.The decision of processing capacity,location,construction timing,and capacity expansion of processing stations,as well as transmission capacity of pipelines and processing capacity allocation schemes,can be obtained to meet long-term production demand.Furthermore,a real case study indicates that the proposed processing capacity allocation approach not only has a shorter payback period and increases NPV by 4.8%,but also increases the utilization efficiency of processing stations from 27.37% to 48.94%.This work demonstrates that the synergy between the processing capacity allocation and infrastructure construction can hedge against production fluctuations and increase potential profits.
基金supported by the Young Data Scientist Program of the China National Astronomical Data Center,the Strategic Priority Research Program of the Chinese Academy of Sciences(XDB0550401)the National Natural Science Foundation of China(12494573).
文摘The Ground-based Wide-Angle Cameras array necessitates the integration of more than 100 hardware devices,100 servers,and 2500 software modules that must be synchronized within a 3-second imaging cycle.However,the complexity of real-time,high-concurrency processing of large datasets has historically resulted in substantial failure rates,with an observation efficiency estimated at less than 50%in 2023.To mitigate these challenges,we developed a monitoring system designed to improve fault diagnosis efficiency.It includes two innovative monitoring views for“state evolution”and“transient lifecycle”.Combining these with“instantaneous state”and“key parameter”monitoring views,the system represents a comprehensive monitoring strategy.Here we detail the system architecture,data collection methods,and design philosophy of the monitoring views.During one year of fault diagnosis experimental practice,the proposed system demonstrated its ability to identify and localize faults within minutes,achieving fault localization nearly ten times faster than traditional methods.Additionally,the system design exhibited high generalizability,with possible applicability to other telescope array systems.
文摘This article focuses on the remote diagnosis and analysis of rail vehicle status based on the data of the Train Control Management System(TCMS).It first expounds on the importance of train diagnostic analysis and designs a unified TCMS data frame transmission format.Subsequently,a remote data transmission link using 4G signals and data processing methods is introduced.The advantages of remote diagnosis are analyzed,and common methods such as correlation analysis,fault diagnosis,and fault prediction are explained in detail.Then,challenges such as data security and the balance between diagnostic accuracy and real-time performance are discussed,along with development prospects in technological innovation,algorithm optimization,and application promotion.This research provides ideas for remote analysis and diagnosis based on TCMS data,contributing to the safe and efficient operation of rail vehicles.
基金supported by grants from the Noncommunicable Chronic Diseases-National Science and Technology Major Project(Grant No.2023ZD0501300)Science Technology Department of Zhejiang Province(Grant No.2021C03117)+2 种基金National Natural Science Foundation of China(Grant No.82350104 and 82170219)Natural Science Foundation of Zhejiang Province,China(Grant No.LY23H080004 and LY24H080001)Medical Health Science and Technology Project of Zhejiang Provincial Health Commission(Grant No.2021KY199)。
文摘Chimeric antigen receptor natural killer(CAR-NK)cell therapy is an alternative immunotherapy that provides robust tumor-eliminating effects without inducing life-threatening toxicities and graft-versus-host disease.CAR-NK cell therapy has enabled the development of“off-the-shelf”products that bypass the lengthy and expensive cell manufacturing process1.
基金supported by the Key Project of Chongqing Natural Science Foundation Joint Fund[CSTB2023NSCQ-LZX0103,(G.Z.)]Chongqing Natural Science Foundation[CSTB2024NSCQ-MSX0012,(C.L.)]+1 种基金Fundamental Research Funds for the Central Universities[SWUZLPY03,(G.Z.)]Fundamental Research Funds for the Central Universities[Swu020019,(G.Z.):SWU-XDJH202319,(G.Z.)1].
文摘With the advancement of artificial intelligence,optic in-sensing reservoir computing based on emerging semiconductor devices is high desirable for real-time analog signal processing.Here,we disclose a flexible optomemristor based on C_(27)H_(30)O_(15)/FeOx heterostructure that presents a highly sensitive to the light stimuli and artificial optic synaptic features such as short-and long-term plasticity(STP and LTP),enabling the developed optomemristor to implement complex analogy signal processing through building a real-physical dynamic-based in-sensing reservoir computing algorithm and yielding an accuracy of 94.88%for speech recognition.The charge trapping and detrapping mediated by the optic active layer of C_(27)H_(30)O_(15) that is extracted from the lotus flower is response for the positive photoconductance memory in the prepared optomemristor.This work provides a feasible organic−inorganic heterostructure as well as an optic in-sensing vision computing for an advanced optic computing system in future complex signal processing.
文摘In the anticorrosive coating line of a welded tube plant, the current status and existing problems of the medium-frequency induction heating equipment were discussed.Partial renovations of the power control cabinet have been conducted.Parameters such as the DC current, DC voltage, intermediate frequency power, heating temperature, and the positioning signal at the pipe end were collected.A data acquisition and processing system, which can process data according to user needs and provide convenient data processing functions, has been developed using LabVIEW software.This system has been successfully applied in the coating line for the automatic control of high-power induction heating equipment, production management, and digital steel tube and/or digital delivery.
文摘The food processing industry generates large quantities of wastewater rich in organic matter and nutrients,which poses significant environmental pressures while also serving as a valuable resource carrier.The sector is transitioning from simple compliance-based discharge to an integrated management model of“reduction–reuse–resource recovery.”For water reclamation,multi-layer membrane technologies have become the mainstream advanced treatment approach,significantly increasing reuse rates.Treated water can be used for cooling,washing,and even certain production processes,effectively reducing freshwater consumption.In terms of resource recovery,anaerobic digestion technology has matured and is widely applied for biogas production,while recovering high-value substances from wastewater has become a research focus.Nevertheless,challenges such as large fluctuations in wastewater composition,high treatment costs,and incomplete regulatory standards for reclaimed water and by-products(e.g.,fertilizers)hinder wider adoption.Moving forward,it is essential to strengthen collaboration among industry,academia,and research institutions to develop more economical and adaptable integrated technological solutions,fostering closed-loop water resource management and promoting green,low-carbon development in the food processing industry.
基金supported by the National Natural Science Foundation of China(71871219).
文摘Performance-based warranties(PBWs)are widely used in industry and manufacturing.Given that PBW can impose financial burdens on manufacturers,rational maintenance decisions are essential for expanding profit margins.This paper proposes an optimization model for PBW decisions for systems affected by Gamma degradation processes,incorporating periodic inspection.A system performance degradation model is established.Preventive maintenance probability and corrective renewal probability models are developed to calculate expected warranty costs and system availability.A benefits function,which includes incentives,is constructed to optimize the initial and subsequent inspection intervals and preventive maintenance thresholds,thereby maximizing warranty profit.An improved sparrow search algorithm is developed to optimize the model,with a case study on large steam turbine rotor shafts.The results suggest the optimal PBW strategy involves an initial inspection interval of approximately 20 months,with subsequent intervals of about four months,and a preventive maintenance threshold of approximately 37.39 mm wear.When compared to common cost-minimization-based condition maintenance strategies and PBW strategies that do not differentiate between initial and subsequent inspection intervals,the proposed PBW strategy increases the manufacturer’s profit by 1%and 18%,respectively.Sensitivity analyses provide managerial recommendations for PBW implementation.The PBW strategy proposed in this study significantly increases manufacturers’profits by optimizing inspection intervals and preventive maintenance thresholds,and manufacturers should focus on technological improvement in preventive maintenance and cost control to further enhance earnings.
基金the National Natural Science Foundation of China(42107339)the China Agriculture Research System(CARS-04)。
文摘Wheat-maize(WM)and wheat-soybean(WS)double-cropping rotation systems are predominant in the North China Plain,with implications for national agricultural output and sustainability.As rotation systems exert legacy effects on soil health and crop productivity,the role of crop rotation in shaping the root-associated microbiome of the succeeding crops has emerged as a pivotal aspect of crop management research.Here,the effects of the preceding two cycles of WM and WS rotations on the recruitment and filtering of wheat root-associated bacterial communities across wheat developmental stages were investigated.Our results revealed that bacterial community diversity and composition were primarily influenced by compartment and developmental stage,while the preceding rotation systems had a slight but significant effect on wheat root-associated bacterial communities.The co-occurrence networks under WM were more complex in the wheat rhizosphere and rhizoplane,with the operational taxonomic units(OTUs)related to cellulolysis showing greater connectivity.The co-occurrence networks under WS were simple but stable in the rhizosphere and complex in the rhizoplane and endosphere,with the OTUs related to ureolysis and nitrogen fixation showing greater connectivity.While both stochastic and deterministic processes contributed to the assembly of wheat root-associated bacterial communities,the contributions of deterministic processes under WS were 19.4-38.5%higher than those under the WM rotation across the root-associated compartments,indicating the substantial impact of a soybean legacy effect on wheat root selection of microbes.Plant growthpromoting rhizobacteria with the potential to fix nitrogen,produce indole-3-acetic acid,and inhibit diseases such as Betaproteobacteriales,Azospirillales and Dyella sp.,were identified within the OTUs that were consistently enriched across all the wheat root-associated compartments and developmental stages,which were also important predictors of wheat yield.This study elucidates the role of crop rotation in modulating the dynamics of crop root-associated bacterial communities,and underscores the potential of targeted microbiome manipulation for optimizing wheat production and enhancing soil health.
文摘With the advent of the big data era,real-time data analysis and decision-support systems have been recognized as essential tools for enhancing enterprise competitiveness and optimizing the decision-making process.This study aims to explore the development strategies of real-time data analysis and decision-support systems,and analyze their application status and future development trends in various industries.The article first reviews the basic concepts and importance of real-time data analysis and decision-support systems,and then discusses in detail the key technical aspects such as system architecture,data collection and processing,analysis methods,and visualization techniques.
基金supported by the National Natural Science Foundation of China(Nos.52293444 and 22076209)the Key R&D Project of Ningxia(No.2021BEG02006).
文摘Microplastics(MPs)are ubiquitous in the environment,continuously undergo aging processes and release toxic chemical substances.Understanding the environmental behaviors of MPs is critical to accurately evaluate their long-term ecological risk.Generalized twodimensional correlation spectroscopy(2D-COS)is a powerful tool for MPs studies,which can dig more comprehensive information hiding in the conventional one-dimensional spectra,such as infrared(IR)and Raman spectra.The recent applications of 2D-COS in analyzing the behaviors and fates of MPs in the environment,including their aging processes,and interactions with natural organicmatter(NOM)or other chemical substances,were summarized systematically.The main requirements and limitations of current approaches for exploring these processes are discussed,and the corresponding strategies to address these limitations and drawbacks are proposed as well.Finally,new trends of 2D-COS are prospected for analyzing the properties and behaviors of MPs in both natural and artificial environmental processes.
基金supported by the National Natural Science Foundation of China(Nos.52270165 and 51978537)the Key Laboratory of Safety for Geotechnical and Structural Engineering of Hubei Province。
文摘The persistence of chlorinated alkanes in aquatic environments poses significant health risks due to its biotoxicity and high volatility,which contributes to both water and air pollution.This study investigates the efficacy of carbon dioxide radical anion(CO_(2)·^(-))mediated advanced reduction processes(ARPs)for the reductive dechlorination of chlorinated alkanes using small molecular monocarboxylic acids(SMAs)under UV irradiation.The study focused on formic acid(HCOOH),acetic acid(CH_3COOH),and propionic acid(CH_3CH_(2)COOH)to generate CO_(2)·^(-),revealing that UV/HCOOH system exhibits a notably high chloroform(CF)degradation efficiency of 97.8%in 90 min.Kinetic studies indicated a linear relationship between the HCOOH concentrations and the observed reaction rate constants(k_(obs)),demonstrating that CO_(2)·^(-)production is crucial for CF degradation.Electron paramagnetic resonance spectroscopy identified CO_(2)·^(-)and hydroxyl radicals(HO·)as the active species,with the former playing a predominant role in CF degradation.The study also explored the influence of carbon chain length in SMAs on CF degradation,finding that longer chains decrease the degradation efficiency,potentially due to reduced UV activation.A higher reaction rate constant(k_(obs))under acidic conditions,with a marked decrease in efficiency as the pH exceeds 3.7,where HCOO^(-)becomes predominant.This study enhances our understanding of CO_(2)·^(-)mediated ARPs and explores potential applications in environmental remediation,providing insights into the pathways and mechanisms of CF degradation.The UV/SMAs systems offer advantages for practical applications,such as milder reaction conditions and higher efficiency compared to traditional methods.
