Recently automotive nets are adopted to solve increasing problems in automotive electronic systems.Technologies of automotive local area network from CAN and LIN can solve the problems of the increasing of wire bunch ...Recently automotive nets are adopted to solve increasing problems in automotive electronic systems.Technologies of automotive local area network from CAN and LIN can solve the problems of the increasing of wire bunch weight and lack in module installation space.However,the multilayer automotive nets software becomes more and more complex,and the development expense is difficult to predict and to keep in check.In this paper,the modeling method of hierarchical automotive nets and the substitution operation based on object-oriented colored Petri net(OOCPN) are proposed.The OOCPN model which analyzes the software structure and validates the collision mechanism of CAN/LIN bus can speed the automobile system development.First,the subsystems are divided and modeled by object-oriented Petri net(OOPN).According to the sets of message sharing relations,the message ports among them are set and the communication gate transitions are defined.Second,the OOPN model is substituted step by step until the inner objects in the automotive body control modules(BCM) are indivisible and colored by colored Petri net(CPN).And the color subsets mark the node messages for the collision mechanism.Third,the OOCPN model of the automotive body CAN/LIN nets is assembled,which keeps the message sets and the system can be expanded.The proposed model is used to analyze features of information sharing among the objects,and it is also used to describe each subsystem real-time behavior of processing messages and implemental device controllers operating,and puts forward a reasonable software framework for the automotive body control subsystem.The research can help to design the communication model in the automotive body system effectively and provide a convenient and rapid way for developing the logical hierarchy software.展开更多
Object-oriented Petri nets (OPNs) is extended into stochastic object-oriented Petri nets (SOPNs) by associating the OPN of an object with stochastic transitions and introducing stochastic places. The stochastic transi...Object-oriented Petri nets (OPNs) is extended into stochastic object-oriented Petri nets (SOPNs) by associating the OPN of an object with stochastic transitions and introducing stochastic places. The stochastic transition of the SOPNs of a production resources can be used to model its reliability, while the SOPN of a production resource can describe its performance with reliability considered. The SOPN model of a case production system is built to illustrate the relationship between the system's performances and the failures of individual production resources.展开更多
Object-oriented programming divides the crop production into subsystems and simulates their behaviors. Many classes were designed to simulate the behaviors of different parts or different physiological processes in cr...Object-oriented programming divides the crop production into subsystems and simulates their behaviors. Many classes were designed to simulate the behaviors of different parts or different physiological processes in crop production system. At the same time, many classes have to be employed for bettering user's interface. But how to manage these classes on a higher level to cooperate them into a perfect system is another problem to study. The Rice Growth Models (RGM) system represents an effort to define and implement a framework to manage these classes. In RGM system, the classes were organized into the model-document-view architecture to separate the domain models, data management and user interface. A single document with multiple views interface frame window was adopted in RGM. In the architectures, the simulation models only exchange data with documents while documents act as intermediacies between simulation models and interfaces. Views get data from documents and show the results to users. The classes for the different functions can be grouped into different architectures. Different architectures communicate with each other through documents. The classes for the different functions can be grouped into different architectures. By using the architecture, communication between classes is more efficient. Modeler can add classes in architectures or other architectures to extend the system without having to change system structure, which is useful for construction and maintenance of agricultural system models.展开更多
reshwater essential for civilization faces risk from untreated effluents discharged by industries,agriculture,urban areas,and other sources.Increasing demand and abstraction of freshwater deteriorate the pollution sce...reshwater essential for civilization faces risk from untreated effluents discharged by industries,agriculture,urban areas,and other sources.Increasing demand and abstraction of freshwater deteriorate the pollution scenario more.Hence,water quality analysis(WQA)is an important task for researchers and policymakers to maintain sustainability and public health.This study aims to gather and discuss the methods used for WQA by the researchers,focusing on their advantages and limitations.Simultaneously,this study compares different WQA methods,discussing their trends and future directions.Publications from the past decade on WQA are reviewed,and insights are explored to aggregate them in particular categories.Three major approaches,namely—water quality indexing,water quality modeling(WQM)and artificial intelligence-based WQM,are recognized.Different methodologies adopted to execute these three approaches are presented in this study,which leads to formulate a comparative discussion.Using statistical operations and soft computing techniques have been done by researchers to combat the subjectivity error in indexing.To achieve better results,WQMs are being modified to incorporate the physical processes influencing water quality more robustly.The utilization of artificial intelligence was primarily restricted to conventional networks,but in the last 5 years,implications of deep learning have increased rapidly and exhibited good results with the hybridization of feature extracting and time series modeling.Overall,this study is a valuable resource for researchers dedicated to WQA.展开更多
Background GOSSYM is a mechanistic,process-based cotton model that can simulate cotton crop growth and development,yield,and fiber quality.Its fiber quality module was developed based on controlled experiments explici...Background GOSSYM is a mechanistic,process-based cotton model that can simulate cotton crop growth and development,yield,and fiber quality.Its fiber quality module was developed based on controlled experiments explicitly conducted on the Texas Marker^(-1)(TM1)variety,potentially making its functional equations more aligned with this cultivar.To assess the model’s broader applicability,this study analyzed fiber quality data from 40 upland cotton cultivars,including TM1.The measured fiber quality from all cultivars was then compared with the modelsimulated fiber quality.Results Among the 40 upland cultivars,fiber strength varied from 28.4 cN·tex^(-1) to 34.6 cN·tex^(-1),fiber length ranged from 27.1 mm to 33.3 mm,micronaire value ranged from 2.7 to 4.6,and length uniformity index varied from 82.3%to 85.5%.The model simulated fiber quality closely matched the measured values for TM1,with the absolute percentage error(APE)being less than 0.92%for fiber strength,fiber length,and length uniformity index and 4.7%for micronaire.However,significant differences were observed for the other cultivars.The Pearson correlation coefficient(r)between the measured and simulated values was negative for all fiber quality traits,and Wilmotts’s index of agreement(WIA)was below 0.45,indicating a strong model bias toward TM1 without incorporating cultivar-specific parameters.After incorporating cultivar-specific parameters,the model’s performance improved significantly,with an average r-value of 0.84 and WIA of 0.88.Conclusions The adopted methodology and estimated cultivar-specific parameters improved the model’s simulation accuracy.This approach can be applied to newer cotton cultivars,enhancing the GOSSYM model’s utility and its applicability for agricultural management and policy decisions.展开更多
With the rapid development of generative artificial intelligence technologies,represented by large language models,university-level computer science education is undergoing a critical transition-from knowledge-based i...With the rapid development of generative artificial intelligence technologies,represented by large language models,university-level computer science education is undergoing a critical transition-from knowledge-based instruction to competency-oriented teaching.A postgraduate student competency evaluation model can serve as a framework to organize and guide both teaching and research activities at the postgraduate level.A number of relevant research efforts have already been conducted in this area.Graduate education plays a vital role not only as a continuation and enhancement of undergraduate education but also as essential preparation for future research endeavors.An analysis of the acceptance of competency evaluation models refers to the assessment of how various stakeholders perceive the importance of different components within the model.Investigating the degree of acceptance among diverse groups-such as current undergraduate students,current postgraduate students,graduates with less than three years of work experience,and those with more than three years of work experience-can offer valuable insights for improving and optimizing postgraduate education and training practices.展开更多
In Hyperspectral Imaging(HSI),the detrimental influence of noise and distortions on data quality is profound,which has severely affected the following-on analytics and decisionmaking such as land mapping.This study pr...In Hyperspectral Imaging(HSI),the detrimental influence of noise and distortions on data quality is profound,which has severely affected the following-on analytics and decisionmaking such as land mapping.This study presents an innovative framework for assessing HSI band quality and reconstructing the low-quality bands,based on the Prophet model.By introducing a comprehensive quality metric to start,the authors approach factors in both spatial and spectral characteristics across local and global scales.This metric effectively captures the intricate noise and distortions inherent in the HSI data.Subsequently,the authors employ the Prophet model to forecast information within the low-quality bands,leveraging insights from neighbouring high-quality bands.To validate the effectiveness of the authors’proposed model,extensive experiments on three publicly available uncorrected datasets are conducted.In a head-to-head comparison,the framework against six state-ofthe-art band reconstruction algorithms including three spectral methods,two spatialspectral methods and one deep learning method is benchmarked.The authors’experiments also delve into strategies for band selection based on quality metrics and the quality evaluation of the reconstructed bands.In addition,the authors assess the classification accuracy utilising these reconstructed bands.In various experiments,the results consistently affirm the efficacy of the authors’method in HSI quality assessment and band reconstruction.Notably,the authors’approach obviates the need for manually prefiltering of noisy bands.This comprehensive framework holds promise in addressing HSI data quality concerns whilst enhancing the overall utility of HSI.展开更多
Objective:To analyze the impact of the predictive rehabilitation nursing model on the quality of emergency transport and rehabilitation outcomes for patients with acute cerebral hemorrhage(ICH).Methods:A total of 62 p...Objective:To analyze the impact of the predictive rehabilitation nursing model on the quality of emergency transport and rehabilitation outcomes for patients with acute cerebral hemorrhage(ICH).Methods:A total of 62 patients with acute cerebral hemorrhage admitted to the hospital from January 2022 to December 2024 were selected as the study subjects.The observation group(n=31)received conventional nursing combined with the predictive rehabilitation nursing model during the emergency process,while the control group(n=31)received conventional nursing.The recovery conditions(Fuel-Meyer Assessment(FMA)score,Barthel Index(BI)),incidence of complications,nursing satisfaction,and time to regain consciousness were compared between the two groups.Results:After the intervention,the FMA and BI scores of the observation group were significantly higher than those of the control group,with statistically significant differences.The incidence of complications in the observation group was significantly lower than that in the control group.In terms of nursing satisfaction,the scores of various indicators in the observation group were higher than those in the control group,with statistically significant differences.The time to regain consciousness in the observation group was(48.72±11.76)minutes,compared to(64.29±14.58)minutes in the control group,with the observation group regaining consciousness earlier than the control group.Conclusion:The application of the predictive rehabilitation nursing model in the emergency transport process of patients with acute cerebral hemorrhage can reduce the incidence of complications,shorten the duration of consciousness disorder,improve the quality of transport,and enhance functional rehabilitation levels.展开更多
For modeling and simulation of distillation process, there are lots of special purpose simulators along with their model libraries, such as Aspen Plus and HYSYS. However, the models in these tools lack of flexibility ...For modeling and simulation of distillation process, there are lots of special purpose simulators along with their model libraries, such as Aspen Plus and HYSYS. However, the models in these tools lack of flexibility and are not open to the end-user. Models developed in one tool can not be conveniently used in others because of the barriers among these simulators. In order to solve those problems, a flexible and extensible distillation system model library is constructed in this study, based on the Modelica and Modelica-supported platform MWorks, by the object-oriented technology and level progressive modeling strategy. It supports the reuse of knowledge on different granularities： physical phenomenon, unit model and system model. It is also an interface-friendly, accurate, fast PC-based and easily reusable simulation tool, which enables end-user to customize and extend the framework to add new functionality or adapt the simulation behavior as required. It also allows new models to be composed programmatically or graphically to form more complex models by invoking the existing components. A conventional air distillation column model is built and calculated using the library, and the results agree well with that simulated in Anen Plus.展开更多
Modern satellite propulsion systems are generally designed to fulfill multiphase-missions.Traditional reliability modelling methods have problems of inadequate depict capacity considering complex systems such as satel...Modern satellite propulsion systems are generally designed to fulfill multiphase-missions.Traditional reliability modelling methods have problems of inadequate depict capacity considering complex systems such as satellite propulsion system.An extended object-oriented Petri net(EOOPN)method was proposed to facilitate the reliability modelling of satellite propulsion system in the paper.The proposed method was specified for modelling of phased mission system,and it could be implemented by generating combination of Petri net(PN)principles and object-oriented(OO)programming.The effectiveness of the proposed method was demonstrated through the reliability modelling of a satellite propulsion system with EOOPN.The major advantage of the proposed method is that the dimension of net model can be reduced significantly,and phased mission system at system,phase,or component levels can be respectively depicted.Furthermore,the state-space explosion problem is solved by the proposed EOOPN model efficiently.展开更多
Objective:To investigate the impact of precise nursing care based on dynamic nursing quality feedback model on the postoperative recovery of elderly patients undergoing radical resection for colon cancer,with a partic...Objective:To investigate the impact of precise nursing care based on dynamic nursing quality feedback model on the postoperative recovery of elderly patients undergoing radical resection for colon cancer,with a particular focus on its effects on psychological flexibility.Methods:Medical records of 124 elderly patients undergoing radical resection for colon cancer at The First Affiliated Hospital of Baotou Medical College between January 2021 and May 2024 were retrospectively analyzed in this study.Based on the received nursing interventions,the patients were divided into a control group(standard nursing care)and an observation group(precise nursing care based on a dynamic nursing quality feedback model).Results:The observation group exhibited significantly higher levels of hemoglobin,prealbumin,and albumin compared to the control group.Additionally,the observation group had lower scores in somatization,interpersonal sensitivity,depression,anxiety,obsessions-compulsions,hostility,phobic anxiety,psychoticism,and paranoid ideation.The observation group also demonstrated higher scores in active coping,self-efficacy,and the management of emotions,life,and symptoms.Improvements were also observed in nursing quality,perioperative intervention,satisfaction with rehabilitation guidance,and awareness of regular reexaminations,diet intervention,and complication prevention(all with P<0.05).Conclusion:Precise nursing based on a dynamic nursing quality feedback model can improve nutritional status and medical coping style,reduce psychological issues,and enhance self-management abilities in elderly patients following radical resection of colon cancer.Additionally,it increases nursing satisfaction and raises awareness regarding the importance of regular reexaminations and complication prevention.展开更多
The discontinuation of denosumab[antibody targeting receptor activator of nuclear factor kappa B ligand(RANKL)]therapy may increase the risk of multiple vertebral fractures;however,the underlying pathophysiology is la...The discontinuation of denosumab[antibody targeting receptor activator of nuclear factor kappa B ligand(RANKL)]therapy may increase the risk of multiple vertebral fractures;however,the underlying pathophysiology is largely unknown.In patients who underwent discontinuation after multiple injections of denosumab,the levels of tartrate-resistant acid phosphatase 5b increased compared to pretreatment levels,indicating a phenomenon known as“overshoot.”The rate of decrease in bone mineral density during the withdrawal period was higher than the rate of decrease associated with aging,suggesting that the physiological bone metabolism had broken down.Overshoot and significant bone loss were also observed in mice receiving continuous administration of anti-RANKL antibody after treatment was interrupted,resembling the original pathology.In mice long out of overshoot,bone resorption recovered,but osteoblast numbers and bone formation remained markedly reduced.The bone marrow exhibited a significant reduction in stem cell(SC)antigen 1-and platelet-derived growth factor receptor alpha-expressing osteoblast progenitors(PαS cells)and alkaline phosphatase-positive early osteoblasts.Just before the overshoot phase,the osteoclast precursor cell population expands and RANKL-bearing extracellular vesicles(EVs)became abundant in the serum,leading to robust osteoclastogenesis after cessation of anti-RANKL treatment.Thus,accelerated bone resorption due to the accumulation of RANKLbearing EVs and long-term suppression of bone formation uncoupled from bone resorption leads to the severe bone loss characteristic of denosumab discontinuation.展开更多
Automated operation and artificial intelligence technology have become essential for ensuring the safety, efficiency, and punctuality of railways, with applications such as ATO (Automatic Train Operation). In this stu...Automated operation and artificial intelligence technology have become essential for ensuring the safety, efficiency, and punctuality of railways, with applications such as ATO (Automatic Train Operation). In this study, the authors propose a method to efficiently simulate the kinematic characteristics of railroad vehicles depending on their speed zone. They utilized the function overloading function supported by a programming language and applied the fourth-order Lunge-Kutta method for dynamic simulation. By constructing an object model, the authors calculated vehicle characteristics and TPS and compared them with actual values, verifying that the developed model represents the real-life vehicle characteristics accurately. The study highlights potential improvements in automated driving and energy consumption optimization in the railway industry.展开更多
As a tropical island confronting the dual imperatives of tourism-driven economic growth and ecological vulnerability,Hainan's land-use sustainability critically impacts both regional development and coastal ecosys...As a tropical island confronting the dual imperatives of tourism-driven economic growth and ecological vulnerability,Hainan's land-use sustainability critically impacts both regional development and coastal ecosystem security.This study employs a coupled PLUS-InVEST modeling framework to analyze land-use changes and habitat quality dynamics from 2000 to 2020,projecting ecological outcomes under three development scenarios for 2030.Key findings reveal:(1)A persistent bimodal habitat distribution pattern,with high-quality areas concentrated in the central forest zone and degraded areas in coastal peripheries,exhibiting a continuous decline over the 20-year period.(2)Accelerated urbanization between 2010 and 2020 resulted in the conversion of ecological land to construction use,correlating strongly with habitat fragmentation intensity.(3)Baseline projections for 2030 indicate that construction land will dominate new conversions.(4)Ecological protection scenarios demonstrate recoverable habitat potentials,particularly within coastal buffer zones.These findings provide empirical validation of scenario-driven land-use planning as a viable tool for island ecosystems,highlighting the critical need to balance tourism infrastructure development with coastal conservation imperatives in tropical island sustainability management.This methodology advances spatial decision-making for balancing island economic growth with biodiversity preservation,offering replicable strategies for global island ecosystems facing similar sustainability challenges.展开更多
The rapid melting of Arctic sea ice poses significant risks to the safety of shipping routes.Accurate remote sensing data on sea ice concentration(SIC)is crucial for effective route planning of ships and ensuring navi...The rapid melting of Arctic sea ice poses significant risks to the safety of shipping routes.Accurate remote sensing data on sea ice concentration(SIC)is crucial for effective route planning of ships and ensuring navigational safety.Despite the availability of numerous SIC products in China,these datasets still lag behind mainstream international products in terms of data accuracy,spatiotemporal resolution,and time span.To enhance the accuracy of China's domestic SIC remote sensing data,this study used the SIC data derived from the passive microwave remote sensing dataset provided by the University of Bremen(BRM-SIC)as a reference to conduct a comprehensive evaluation and analysis of two additional SIC datasets:the dataset derived from the microwave radiation imager(MWRI)aboard the FY-3D satellite,provided by the National Satellite Meteorological Center(FY-SIC),and the dataset obtained through the DT-ASI algorithm from the microwave imager of the FY-3D satellite,provided by Ocean University of China(OUC-SIC).Based on the evaluation results,a TransUnet fusion correction model was developed.The performance of this model was then compared against Ordinary Least Squares(OLS),Random Forest(RF),and UNet correction models,through spatial and temporal analyses.Results indicate that,compared to FY-SIC data,the RMSE of the OUC-SIC data and the standard data is reduced by24.245%,while the R is increased by 12.516%.Overall,the accuracy of OUC-SIC data is superior to that of FY-SIC data.During the research period(2020–2022),the standard deviation(SD)and coefficient of variation(CV)of OUC-SIC were 3.877%and 10.582%,respectively,while those for FY-SIC were 7.836%and 7.982%,respectively.In the study area,compared with OUC-SIC data,FYSIC data exhibited a larger standard deviation of deviation and a smaller coefficient of variation of deviation across most sea areas.These results indicate that the OUC-SIC data exhibit better temporal and spatial stability,whereas the FY-SIC data show stronger relative dimensionless stability.Among the four correction models,all showed improvements over the original,unfused corrected data.The fusion corrections using the OLS,RF,UNet,and TransUnet models reduced RMSE by 5.563%,14.601%,42.927%,and48.316%,respectively.Correspondingly,R increased by 0.463%,1.176%,3.951%,and 4.342%,respectively.Among these models,TransUnet performed the best,effectively integrating the advantages of FY-SIC and OUC-SIC data and notably improving the overall accuracy and spatiotemporal stability of SIC data.展开更多
As the global economy navigates through a complex landscape of uncertainty and shifting dynamics,the Chinese economy stands out for its remarkable resilience,inherent vitality,and steadfast commitment to a transformat...As the global economy navigates through a complex landscape of uncertainty and shifting dynamics,the Chinese economy stands out for its remarkable resilience,inherent vitality,and steadfast commitment to a transformative,high-quality development path.The latest economic indicators,strategic policy guidance from the Central Economic Work Conference,and a surge in international confidence collectively present a picture of an economy not merely recovering,but actively building its new growth engines.China is transitioning towards a more sustainable and innovation-driven model,with new quality productive forces playing an increasingly prominent role.展开更多
Virtual assembly is a Virtual Reality (VR) based engineering application which allows engineers to evaluate, analyze, and plan the assembly of mechanical systems. To model the virtual assembly process, new methodology...Virtual assembly is a Virtual Reality (VR) based engineering application which allows engineers to evaluate, analyze, and plan the assembly of mechanical systems. To model the virtual assembly process, new methodology must be applied. Based on the idea that the virtual assembly system is an event driven system, the interactive behavior and information model is proposed to describe the dynamic process of virtual assembly. Definition of the object-oriented model of virtual assembly is put forward.展开更多
The conventional single model strategy may be ill- suited due to the multiplicity of operation phases and system uncertainty. A novel global-local discriminant analysis （GLDA） based Gaussian process regression （GPR...The conventional single model strategy may be ill- suited due to the multiplicity of operation phases and system uncertainty. A novel global-local discriminant analysis （GLDA） based Gaussian process regression （GPR） approach is developed for the quality prediction of nonlinear and multiphase batch processes. After the collected data is preprocessed through batchwise unfolding, the hidden Markov model （HMM） is applied to identify different operation phases. A GLDA algorithm is also presented to extract the appropriate process variables highly correlated with the quality variables, decreasing the complexity of modeling. Besides, the multiple local GPR models are built in the reduced- dimensional space for all the identified operation phases. Furthermore, the HMM-based state estimation is used to classify each measurement sample of a test batch into a corresponding phase with the maximal likelihood estimation. Therefore, the local GPR model with respect to specific phase is selected for online prediction. The effectiveness of the proposed prediction approach is demonstrated through the multiphase penicillin fermentation process. The comparison results show that the proposed GLDA-GPR approach is superior to the regular GPR model and the GPR based on HMM （HMM-GPR） model.展开更多
基金supported by National Natural Science Foundation of China (Grant No. 60873003)
文摘Recently automotive nets are adopted to solve increasing problems in automotive electronic systems.Technologies of automotive local area network from CAN and LIN can solve the problems of the increasing of wire bunch weight and lack in module installation space.However,the multilayer automotive nets software becomes more and more complex,and the development expense is difficult to predict and to keep in check.In this paper,the modeling method of hierarchical automotive nets and the substitution operation based on object-oriented colored Petri net(OOCPN) are proposed.The OOCPN model which analyzes the software structure and validates the collision mechanism of CAN/LIN bus can speed the automobile system development.First,the subsystems are divided and modeled by object-oriented Petri net(OOPN).According to the sets of message sharing relations,the message ports among them are set and the communication gate transitions are defined.Second,the OOPN model is substituted step by step until the inner objects in the automotive body control modules(BCM) are indivisible and colored by colored Petri net(CPN).And the color subsets mark the node messages for the collision mechanism.Third,the OOCPN model of the automotive body CAN/LIN nets is assembled,which keeps the message sets and the system can be expanded.The proposed model is used to analyze features of information sharing among the objects,and it is also used to describe each subsystem real-time behavior of processing messages and implemental device controllers operating,and puts forward a reasonable software framework for the automotive body control subsystem.The research can help to design the communication model in the automotive body system effectively and provide a convenient and rapid way for developing the logical hierarchy software.
基金This project is supported by National Natural Science Foundation of China (No.50085003).
文摘Object-oriented Petri nets (OPNs) is extended into stochastic object-oriented Petri nets (SOPNs) by associating the OPN of an object with stochastic transitions and introducing stochastic places. The stochastic transition of the SOPNs of a production resources can be used to model its reliability, while the SOPN of a production resource can describe its performance with reliability considered. The SOPN model of a case production system is built to illustrate the relationship between the system's performances and the failures of individual production resources.
文摘Object-oriented programming divides the crop production into subsystems and simulates their behaviors. Many classes were designed to simulate the behaviors of different parts or different physiological processes in crop production system. At the same time, many classes have to be employed for bettering user's interface. But how to manage these classes on a higher level to cooperate them into a perfect system is another problem to study. The Rice Growth Models (RGM) system represents an effort to define and implement a framework to manage these classes. In RGM system, the classes were organized into the model-document-view architecture to separate the domain models, data management and user interface. A single document with multiple views interface frame window was adopted in RGM. In the architectures, the simulation models only exchange data with documents while documents act as intermediacies between simulation models and interfaces. Views get data from documents and show the results to users. The classes for the different functions can be grouped into different architectures. Different architectures communicate with each other through documents. The classes for the different functions can be grouped into different architectures. By using the architecture, communication between classes is more efficient. Modeler can add classes in architectures or other architectures to extend the system without having to change system structure, which is useful for construction and maintenance of agricultural system models.
基金State University Research Excellence(SURE),SERB,GOI,Grant/Award Number:SUR/2022/001557。
文摘reshwater essential for civilization faces risk from untreated effluents discharged by industries,agriculture,urban areas,and other sources.Increasing demand and abstraction of freshwater deteriorate the pollution scenario more.Hence,water quality analysis(WQA)is an important task for researchers and policymakers to maintain sustainability and public health.This study aims to gather and discuss the methods used for WQA by the researchers,focusing on their advantages and limitations.Simultaneously,this study compares different WQA methods,discussing their trends and future directions.Publications from the past decade on WQA are reviewed,and insights are explored to aggregate them in particular categories.Three major approaches,namely—water quality indexing,water quality modeling(WQM)and artificial intelligence-based WQM,are recognized.Different methodologies adopted to execute these three approaches are presented in this study,which leads to formulate a comparative discussion.Using statistical operations and soft computing techniques have been done by researchers to combat the subjectivity error in indexing.To achieve better results,WQMs are being modified to incorporate the physical processes influencing water quality more robustly.The utilization of artificial intelligence was primarily restricted to conventional networks,but in the last 5 years,implications of deep learning have increased rapidly and exhibited good results with the hybridization of feature extracting and time series modeling.Overall,this study is a valuable resource for researchers dedicated to WQA.
基金supported by United States Department of Agriculture,Agricultural Research Service(No.58-8042-9-072)United States Department of Agriculture-National Institute of Food and Agriculture(No.2019-34263-30552)+1 种基金Management Information System(No.043050)United States Department of Agriculture-Agricultural Research Service-Non-Assistance Cooperative Agreement(No.58-6066-2-030).
文摘Background GOSSYM is a mechanistic,process-based cotton model that can simulate cotton crop growth and development,yield,and fiber quality.Its fiber quality module was developed based on controlled experiments explicitly conducted on the Texas Marker^(-1)(TM1)variety,potentially making its functional equations more aligned with this cultivar.To assess the model’s broader applicability,this study analyzed fiber quality data from 40 upland cotton cultivars,including TM1.The measured fiber quality from all cultivars was then compared with the modelsimulated fiber quality.Results Among the 40 upland cultivars,fiber strength varied from 28.4 cN·tex^(-1) to 34.6 cN·tex^(-1),fiber length ranged from 27.1 mm to 33.3 mm,micronaire value ranged from 2.7 to 4.6,and length uniformity index varied from 82.3%to 85.5%.The model simulated fiber quality closely matched the measured values for TM1,with the absolute percentage error(APE)being less than 0.92%for fiber strength,fiber length,and length uniformity index and 4.7%for micronaire.However,significant differences were observed for the other cultivars.The Pearson correlation coefficient(r)between the measured and simulated values was negative for all fiber quality traits,and Wilmotts’s index of agreement(WIA)was below 0.45,indicating a strong model bias toward TM1 without incorporating cultivar-specific parameters.After incorporating cultivar-specific parameters,the model’s performance improved significantly,with an average r-value of 0.84 and WIA of 0.88.Conclusions The adopted methodology and estimated cultivar-specific parameters improved the model’s simulation accuracy.This approach can be applied to newer cotton cultivars,enhancing the GOSSYM model’s utility and its applicability for agricultural management and policy decisions.
文摘With the rapid development of generative artificial intelligence technologies,represented by large language models,university-level computer science education is undergoing a critical transition-from knowledge-based instruction to competency-oriented teaching.A postgraduate student competency evaluation model can serve as a framework to organize and guide both teaching and research activities at the postgraduate level.A number of relevant research efforts have already been conducted in this area.Graduate education plays a vital role not only as a continuation and enhancement of undergraduate education but also as essential preparation for future research endeavors.An analysis of the acceptance of competency evaluation models refers to the assessment of how various stakeholders perceive the importance of different components within the model.Investigating the degree of acceptance among diverse groups-such as current undergraduate students,current postgraduate students,graduates with less than three years of work experience,and those with more than three years of work experience-can offer valuable insights for improving and optimizing postgraduate education and training practices.
基金National Natural Science Foundation Major Project of China,Grant/Award Number:42192580Guangdong Province Key Construction Discipline Scientific Research Ability Promotion Project,Grant/Award Number:2022ZDJS015。
文摘In Hyperspectral Imaging(HSI),the detrimental influence of noise and distortions on data quality is profound,which has severely affected the following-on analytics and decisionmaking such as land mapping.This study presents an innovative framework for assessing HSI band quality and reconstructing the low-quality bands,based on the Prophet model.By introducing a comprehensive quality metric to start,the authors approach factors in both spatial and spectral characteristics across local and global scales.This metric effectively captures the intricate noise and distortions inherent in the HSI data.Subsequently,the authors employ the Prophet model to forecast information within the low-quality bands,leveraging insights from neighbouring high-quality bands.To validate the effectiveness of the authors’proposed model,extensive experiments on three publicly available uncorrected datasets are conducted.In a head-to-head comparison,the framework against six state-ofthe-art band reconstruction algorithms including three spectral methods,two spatialspectral methods and one deep learning method is benchmarked.The authors’experiments also delve into strategies for band selection based on quality metrics and the quality evaluation of the reconstructed bands.In addition,the authors assess the classification accuracy utilising these reconstructed bands.In various experiments,the results consistently affirm the efficacy of the authors’method in HSI quality assessment and band reconstruction.Notably,the authors’approach obviates the need for manually prefiltering of noisy bands.This comprehensive framework holds promise in addressing HSI data quality concerns whilst enhancing the overall utility of HSI.
基金The Hospital-level Project of Shiyan Taihe Hospital(Project No.:2022JJXM144)Hubei Provincial Health Commission Scientific Research Project(Project No.:WJ2021M058)。
文摘Objective:To analyze the impact of the predictive rehabilitation nursing model on the quality of emergency transport and rehabilitation outcomes for patients with acute cerebral hemorrhage(ICH).Methods:A total of 62 patients with acute cerebral hemorrhage admitted to the hospital from January 2022 to December 2024 were selected as the study subjects.The observation group(n=31)received conventional nursing combined with the predictive rehabilitation nursing model during the emergency process,while the control group(n=31)received conventional nursing.The recovery conditions(Fuel-Meyer Assessment(FMA)score,Barthel Index(BI)),incidence of complications,nursing satisfaction,and time to regain consciousness were compared between the two groups.Results:After the intervention,the FMA and BI scores of the observation group were significantly higher than those of the control group,with statistically significant differences.The incidence of complications in the observation group was significantly lower than that in the control group.In terms of nursing satisfaction,the scores of various indicators in the observation group were higher than those in the control group,with statistically significant differences.The time to regain consciousness in the observation group was(48.72±11.76)minutes,compared to(64.29±14.58)minutes in the control group,with the observation group regaining consciousness earlier than the control group.Conclusion:The application of the predictive rehabilitation nursing model in the emergency transport process of patients with acute cerebral hemorrhage can reduce the incidence of complications,shorten the duration of consciousness disorder,improve the quality of transport,and enhance functional rehabilitation levels.
基金Supported by the Major State Basic Research Development Program of China (2011CB706502)
文摘For modeling and simulation of distillation process, there are lots of special purpose simulators along with their model libraries, such as Aspen Plus and HYSYS. However, the models in these tools lack of flexibility and are not open to the end-user. Models developed in one tool can not be conveniently used in others because of the barriers among these simulators. In order to solve those problems, a flexible and extensible distillation system model library is constructed in this study, based on the Modelica and Modelica-supported platform MWorks, by the object-oriented technology and level progressive modeling strategy. It supports the reuse of knowledge on different granularities： physical phenomenon, unit model and system model. It is also an interface-friendly, accurate, fast PC-based and easily reusable simulation tool, which enables end-user to customize and extend the framework to add new functionality or adapt the simulation behavior as required. It also allows new models to be composed programmatically or graphically to form more complex models by invoking the existing components. A conventional air distillation column model is built and calculated using the library, and the results agree well with that simulated in Anen Plus.
文摘Modern satellite propulsion systems are generally designed to fulfill multiphase-missions.Traditional reliability modelling methods have problems of inadequate depict capacity considering complex systems such as satellite propulsion system.An extended object-oriented Petri net(EOOPN)method was proposed to facilitate the reliability modelling of satellite propulsion system in the paper.The proposed method was specified for modelling of phased mission system,and it could be implemented by generating combination of Petri net(PN)principles and object-oriented(OO)programming.The effectiveness of the proposed method was demonstrated through the reliability modelling of a satellite propulsion system with EOOPN.The major advantage of the proposed method is that the dimension of net model can be reduced significantly,and phased mission system at system,phase,or component levels can be respectively depicted.Furthermore,the state-space explosion problem is solved by the proposed EOOPN model efficiently.
文摘Objective:To investigate the impact of precise nursing care based on dynamic nursing quality feedback model on the postoperative recovery of elderly patients undergoing radical resection for colon cancer,with a particular focus on its effects on psychological flexibility.Methods:Medical records of 124 elderly patients undergoing radical resection for colon cancer at The First Affiliated Hospital of Baotou Medical College between January 2021 and May 2024 were retrospectively analyzed in this study.Based on the received nursing interventions,the patients were divided into a control group(standard nursing care)and an observation group(precise nursing care based on a dynamic nursing quality feedback model).Results:The observation group exhibited significantly higher levels of hemoglobin,prealbumin,and albumin compared to the control group.Additionally,the observation group had lower scores in somatization,interpersonal sensitivity,depression,anxiety,obsessions-compulsions,hostility,phobic anxiety,psychoticism,and paranoid ideation.The observation group also demonstrated higher scores in active coping,self-efficacy,and the management of emotions,life,and symptoms.Improvements were also observed in nursing quality,perioperative intervention,satisfaction with rehabilitation guidance,and awareness of regular reexaminations,diet intervention,and complication prevention(all with P<0.05).Conclusion:Precise nursing based on a dynamic nursing quality feedback model can improve nutritional status and medical coping style,reduce psychological issues,and enhance self-management abilities in elderly patients following radical resection of colon cancer.Additionally,it increases nursing satisfaction and raises awareness regarding the importance of regular reexaminations and complication prevention.
文摘The discontinuation of denosumab[antibody targeting receptor activator of nuclear factor kappa B ligand(RANKL)]therapy may increase the risk of multiple vertebral fractures;however,the underlying pathophysiology is largely unknown.In patients who underwent discontinuation after multiple injections of denosumab,the levels of tartrate-resistant acid phosphatase 5b increased compared to pretreatment levels,indicating a phenomenon known as“overshoot.”The rate of decrease in bone mineral density during the withdrawal period was higher than the rate of decrease associated with aging,suggesting that the physiological bone metabolism had broken down.Overshoot and significant bone loss were also observed in mice receiving continuous administration of anti-RANKL antibody after treatment was interrupted,resembling the original pathology.In mice long out of overshoot,bone resorption recovered,but osteoblast numbers and bone formation remained markedly reduced.The bone marrow exhibited a significant reduction in stem cell(SC)antigen 1-and platelet-derived growth factor receptor alpha-expressing osteoblast progenitors(PαS cells)and alkaline phosphatase-positive early osteoblasts.Just before the overshoot phase,the osteoclast precursor cell population expands and RANKL-bearing extracellular vesicles(EVs)became abundant in the serum,leading to robust osteoclastogenesis after cessation of anti-RANKL treatment.Thus,accelerated bone resorption due to the accumulation of RANKLbearing EVs and long-term suppression of bone formation uncoupled from bone resorption leads to the severe bone loss characteristic of denosumab discontinuation.
文摘Automated operation and artificial intelligence technology have become essential for ensuring the safety, efficiency, and punctuality of railways, with applications such as ATO (Automatic Train Operation). In this study, the authors propose a method to efficiently simulate the kinematic characteristics of railroad vehicles depending on their speed zone. They utilized the function overloading function supported by a programming language and applied the fourth-order Lunge-Kutta method for dynamic simulation. By constructing an object model, the authors calculated vehicle characteristics and TPS and compared them with actual values, verifying that the developed model represents the real-life vehicle characteristics accurately. The study highlights potential improvements in automated driving and energy consumption optimization in the railway industry.
基金National Science and Technology Basic Resources Investigation Program(2022FY101901-2)。
文摘As a tropical island confronting the dual imperatives of tourism-driven economic growth and ecological vulnerability,Hainan's land-use sustainability critically impacts both regional development and coastal ecosystem security.This study employs a coupled PLUS-InVEST modeling framework to analyze land-use changes and habitat quality dynamics from 2000 to 2020,projecting ecological outcomes under three development scenarios for 2030.Key findings reveal:(1)A persistent bimodal habitat distribution pattern,with high-quality areas concentrated in the central forest zone and degraded areas in coastal peripheries,exhibiting a continuous decline over the 20-year period.(2)Accelerated urbanization between 2010 and 2020 resulted in the conversion of ecological land to construction use,correlating strongly with habitat fragmentation intensity.(3)Baseline projections for 2030 indicate that construction land will dominate new conversions.(4)Ecological protection scenarios demonstrate recoverable habitat potentials,particularly within coastal buffer zones.These findings provide empirical validation of scenario-driven land-use planning as a viable tool for island ecosystems,highlighting the critical need to balance tourism infrastructure development with coastal conservation imperatives in tropical island sustainability management.This methodology advances spatial decision-making for balancing island economic growth with biodiversity preservation,offering replicable strategies for global island ecosystems facing similar sustainability challenges.
基金supported by the National Natural Science Foundation of China(No.41971339)the SDUST Research Fund(No.2019TDJH103)。
文摘The rapid melting of Arctic sea ice poses significant risks to the safety of shipping routes.Accurate remote sensing data on sea ice concentration(SIC)is crucial for effective route planning of ships and ensuring navigational safety.Despite the availability of numerous SIC products in China,these datasets still lag behind mainstream international products in terms of data accuracy,spatiotemporal resolution,and time span.To enhance the accuracy of China's domestic SIC remote sensing data,this study used the SIC data derived from the passive microwave remote sensing dataset provided by the University of Bremen(BRM-SIC)as a reference to conduct a comprehensive evaluation and analysis of two additional SIC datasets:the dataset derived from the microwave radiation imager(MWRI)aboard the FY-3D satellite,provided by the National Satellite Meteorological Center(FY-SIC),and the dataset obtained through the DT-ASI algorithm from the microwave imager of the FY-3D satellite,provided by Ocean University of China(OUC-SIC).Based on the evaluation results,a TransUnet fusion correction model was developed.The performance of this model was then compared against Ordinary Least Squares(OLS),Random Forest(RF),and UNet correction models,through spatial and temporal analyses.Results indicate that,compared to FY-SIC data,the RMSE of the OUC-SIC data and the standard data is reduced by24.245%,while the R is increased by 12.516%.Overall,the accuracy of OUC-SIC data is superior to that of FY-SIC data.During the research period(2020–2022),the standard deviation(SD)and coefficient of variation(CV)of OUC-SIC were 3.877%and 10.582%,respectively,while those for FY-SIC were 7.836%and 7.982%,respectively.In the study area,compared with OUC-SIC data,FYSIC data exhibited a larger standard deviation of deviation and a smaller coefficient of variation of deviation across most sea areas.These results indicate that the OUC-SIC data exhibit better temporal and spatial stability,whereas the FY-SIC data show stronger relative dimensionless stability.Among the four correction models,all showed improvements over the original,unfused corrected data.The fusion corrections using the OLS,RF,UNet,and TransUnet models reduced RMSE by 5.563%,14.601%,42.927%,and48.316%,respectively.Correspondingly,R increased by 0.463%,1.176%,3.951%,and 4.342%,respectively.Among these models,TransUnet performed the best,effectively integrating the advantages of FY-SIC and OUC-SIC data and notably improving the overall accuracy and spatiotemporal stability of SIC data.
文摘As the global economy navigates through a complex landscape of uncertainty and shifting dynamics,the Chinese economy stands out for its remarkable resilience,inherent vitality,and steadfast commitment to a transformative,high-quality development path.The latest economic indicators,strategic policy guidance from the Central Economic Work Conference,and a surge in international confidence collectively present a picture of an economy not merely recovering,but actively building its new growth engines.China is transitioning towards a more sustainable and innovation-driven model,with new quality productive forces playing an increasingly prominent role.
文摘Virtual assembly is a Virtual Reality (VR) based engineering application which allows engineers to evaluate, analyze, and plan the assembly of mechanical systems. To model the virtual assembly process, new methodology must be applied. Based on the idea that the virtual assembly system is an event driven system, the interactive behavior and information model is proposed to describe the dynamic process of virtual assembly. Definition of the object-oriented model of virtual assembly is put forward.
基金The Fundamental Research Funds for the Central Universities(No.JUDCF12027,JUSRP51323B)the Scientific Innovation Research of College Graduates in Jiangsu Province(No.CXLX12_0734)
文摘The conventional single model strategy may be ill- suited due to the multiplicity of operation phases and system uncertainty. A novel global-local discriminant analysis （GLDA） based Gaussian process regression （GPR） approach is developed for the quality prediction of nonlinear and multiphase batch processes. After the collected data is preprocessed through batchwise unfolding, the hidden Markov model （HMM） is applied to identify different operation phases. A GLDA algorithm is also presented to extract the appropriate process variables highly correlated with the quality variables, decreasing the complexity of modeling. Besides, the multiple local GPR models are built in the reduced- dimensional space for all the identified operation phases. Furthermore, the HMM-based state estimation is used to classify each measurement sample of a test batch into a corresponding phase with the maximal likelihood estimation. Therefore, the local GPR model with respect to specific phase is selected for online prediction. The effectiveness of the proposed prediction approach is demonstrated through the multiphase penicillin fermentation process. The comparison results show that the proposed GLDA-GPR approach is superior to the regular GPR model and the GPR based on HMM （HMM-GPR） model.
