Based on the complexity and regional differences of the political,economic,and cultural environments of countries along the“Belt and Road,”this paper analyzes the new characteristics of the current demand for busine...Based on the complexity and regional differences of the political,economic,and cultural environments of countries along the“Belt and Road,”this paper analyzes the new characteristics of the current demand for business English talents.Combining this with the existing problems in China’s current training models,it proposes a reform path for talent training models that are adapted to the construction of the“Belt and Road”Initiative.The aim is to provide theoretical references and practical guidance for enhancing the international competitiveness of business English talents.展开更多
The international development of the petroleum industry has posed an urgent demand for the internationalization capabilities of both academic and professional master’s students.However,there is currently a shortage o...The international development of the petroleum industry has posed an urgent demand for the internationalization capabilities of both academic and professional master’s students.However,there is currently a shortage of such talent in the petroleum energy sector,along with a lack of a collaborative training system.Based on this,this study focuses on featured disciplines in the petroleum energy sector and systematically constructs an international talent training model centered around the“five-element synergy”of“government-school-enterprise-teacher-student.”Firstly,it defines the connotations of the five-element synergy:“government(strategic guidance)-school(platform support)-enterprise(demand verification)-teacher(leading transformation)-student(practical co-creation).”Secondly,it sets distinct training objectives for academic(focusing on academic innovation)and professional(emphasizing engineering practice)master’s students.Furthermore,it constructs a“categorized and layered,progressive and collaborative”curriculum system,builds an international faculty team through a“recruitment+training”dual-path approach,and cultivates students’sense of professional mission to“contribute to the nation’s energy sector”through a“macro+micro”perspective.This model provides a practical pathway for international talent training in the petroleum energy sector and holds significant importance for enhancing the overseas competitiveness of petroleum enterprises and safeguarding national energy security.展开更多
Bronchiectasis is a chronic inflammatory airway disease,and patients often suffer from recurrent airway infections leading to decreased lung function and impaired quality of life.In this study,the effects of supervise...Bronchiectasis is a chronic inflammatory airway disease,and patients often suffer from recurrent airway infections leading to decreased lung function and impaired quality of life.In this study,the effects of supervised pulmonary rehabilitation training on pulmonary function,training compliance,and quality of life in patients with bronchiectasis under home rehabilitation mode are investigated.Ninety stable patients were selected,and the observation group adopted the home-supervised mode of pulmonary rehabilitation training.The results showed that the observation group’s pulmonary function indexes,quality of life,and training adherence were better than those of the control group.The differences were statistically significant(P<0.05).The supervised pulmonary rehabilitation training in home rehabilitation mode can effectively improve patients’pulmonary function and quality of life,and improve training compliance,which has good clinical application value.展开更多
With the continuous development of the nursing discipline,standardized nurse training has always been a crucial link in the development of nursing science and plays an irreplaceable role in talent cultivation.However,...With the continuous development of the nursing discipline,standardized nurse training has always been a crucial link in the development of nursing science and plays an irreplaceable role in talent cultivation.However,in the current standardized training for some nurses,there are problems such as the simplification of nursing skill evaluation models and insufficient post competence of nurses.Therefore,optimizing the training model for nursing talents has become an inevitable measure.The problem-based learning(PBL)method and the Direct Observation of Procedural Skills(DOPS)evaluation model provide new directions and guidance for the development of training.Against this background,this paper explores effective approaches for standardized nurse training,starting from basic concepts and gradually delving into specific practical paths,aiming to improve the quality of talent cultivation and provide valuable references for other researchers.展开更多
In order to help athletes optimize their performances in competitions while prevent overtraining and the risk of overuse injuries,it is important to develop science-based strategies for optimally designing training pr...In order to help athletes optimize their performances in competitions while prevent overtraining and the risk of overuse injuries,it is important to develop science-based strategies for optimally designing training programs.The purpose of the present study is to develop a novel method by the combined use of optimal control theory and a training-performance model for designing optimal training programs,with the hope of helping athletes achieve the best performance exactly on the competition day while properly manage training load during the training course for preventing overtraining.The training-performance model used in the proposed optimal control framework is a conceptual extension of the Banister impulse-response model that describes the dynamics of performance,training load(served as the control variable),fitness(the overall positive effects on performance),and fatigue(the overall negative effects on performance).The objective functional of the proposed optimal control framework is to maximize the fitness and minimize the fatigue on the competition day with the goal of maximizing the performance on the competition day while minimizing the cumulative training load during the training course.The Forward-Backward Sweep Method is used to solve the proposed optimal control framework to obtain the optimal solutions of performance,training load,fitness,and fatigue.The simulation results show that the performance on the competition day is higher while the cumulative training load during the training course is lower with using optimal control theory than those without,successfully showing the feasibility and benefits of using the proposed optimal control framework to design optimal training programs for helping athletes achieve the best performance exactly on the competition day while properly manage training load during the training course for preventing overtraining.The present feasibility study lays the foundation of the combined use of optimal control theory and training-performance models to design personalized optimal training programs in real applications in athletic training and sports science for helping athletes achieve the best performances in competitions while prevent overtraining and the risk of overuse injuries.展开更多
Against the backdrop of the national innovation strategy and the digital transformation of education,the traditional“extensive”training model for innovation and entrepreneurship talents struggles to meet the persona...Against the backdrop of the national innovation strategy and the digital transformation of education,the traditional“extensive”training model for innovation and entrepreneurship talents struggles to meet the personalized development needs of students,making an urgent shift toward precision and intelligence necessary.This study constructs a four-dimensional integrated framework centered on data,“Goal-Data-Intervention-Evaluation”,and proposes a data-driven training model for innovation and entrepreneurship talents in universities.By collecting multi-source data such as learning behaviors,competency assessments,and practical projects,the model conducts in-depth analysis of students’individual characteristics and development potential,enabling precise decision-making in goal setting,teaching intervention,and practical guidance.Based on data analysis,a supportive system for personalized teaching and practical activities is established.Combined with process-oriented and summative evaluations,a closed-loop feedback mechanism is formed to improve training effectiveness.This model provides a theoretical framework and practical path for the scientific,personalized,and intelligent development of innovation and entrepreneurship education in universities.展开更多
Foundation models(FMs)have rapidly evolved and have achieved signicant accomplishments in computer vision tasks.Specically,the prompt mechanism conveniently allows users to integrate image prior information into the m...Foundation models(FMs)have rapidly evolved and have achieved signicant accomplishments in computer vision tasks.Specically,the prompt mechanism conveniently allows users to integrate image prior information into the model,making it possible to apply models without any training.Therefore,we proposed a workflow based on foundation models and zero training to solve the tasks of photoacoustic(PA)image processing.We employed the Segment Anything Model(SAM)by setting simple prompts and integrating the model's outputs with prior knowledge of the imaged objects to accomplish various tasks,including:(1)removing the skin signal in three-dimensional PA image rendering;(2)dual speed-of-sound reconstruction,and(3)segmentation ofnger blood vessels.Through these demonstrations,we have concluded that FMs can be directly applied in PA imaging without the requirement for network design and training.This potentially allows for a hands-on,convenient approach to achieving efficient and accurate segmentation of PA images.This paper serves as a comprehensive tutorial,facilitating the mastery of the technique through the provision of code and sample datasets.展开更多
Accurate assessment of blast furnace conditions is a crucial component in the blast furnace control decision-making process.However,most adversarial models in the field currently update the parameters of the label pre...Accurate assessment of blast furnace conditions is a crucial component in the blast furnace control decision-making process.However,most adversarial models in the field currently update the parameters of the label predictor by minimising the objective function while maximising the objective function to update the domain discriminator's parameters.This strategy results in an excessive maximisation of the domain discriminator's loss.To address this,a friendly adversarial training-based tri-training furnace condition diagnosis model was proposed.This model employed a convolutional neural network-long short-term memory-attention mechanism network as a single-view feature extractor and used decision tree methods as three classifiers to compute the cosine similarity between features and representative vectors of each class.During the knowledge transfer process,the classifiers in this model have a specific goal;they not only seek to maximise the entropy of the target domain samples but also aim to minimise the entropy of the target domain samples when they are misclassified,thus resolving the trade-off in traditional models where robustness is improved at the expense of accuracy.Experimental results indicate that the diagnostic accuracy of this model reaches 96%,with an approximately 8%improvement over existing methods due to the inner optimisation approach.This model provides an effective and feasible solution for the efficient monitoring and diagnosis of blast furnace processes.展开更多
In the context of the rapid advancement of intelligent manufacturing,ensuring the alignment of the skill levels of embedded system developers with industry requirements has emerged as a crucial aspect in the reform of...In the context of the rapid advancement of intelligent manufacturing,ensuring the alignment of the skill levels of embedded system developers with industry requirements has emerged as a crucial aspect in the reform of vocational education.This research delves into a three-stage progressive talent cultivation model denoted as“Cultivation–Growth–Incubation”,which is founded on the Shi Zhenjiang(Z.S.)Intelligent Embedded System Development Master Skills Studio.By means of hierarchical training,project-driven strategies,and industry-academia cooperation,this model effectively elevates students’application capabilities and innovative competencies in embedded systems.Case analyses illustrate the practical efficacy of the model,providing valuable references for the establishment of master skills studios in vocational education.展开更多
The development of Meizhou Hakka cuisine relies on the role of professional cooking talents.Higher vocational colleges serve as the platform for cultivating cooking talents.Among various training models,the implementa...The development of Meizhou Hakka cuisine relies on the role of professional cooking talents.Higher vocational colleges serve as the platform for cultivating cooking talents.Among various training models,the implementation of the progressive talent training model featuring the integration of industry and education and work-study alternation is conducive to carrying out talent cultivation activities,improving the effectiveness of professional talent development,and effectively meeting the needs of market development.From the perspective of Meizhou Hakka cuisine cooking talents,this paper analyzes the problems existing in the implementation of the industry-education integration and work-study alternation model,and puts forward specific practical strategies for talent cultivation.The purpose is to enhance the training effect of Hakka cuisine cooking talents and provide reference for the subsequent optimization of professional teaching.展开更多
With the rapid adoption of artificial intelligence(AI)in domains such as power,transportation,and finance,the number of machine learning and deep learning models has grown exponentially.However,challenges such as dela...With the rapid adoption of artificial intelligence(AI)in domains such as power,transportation,and finance,the number of machine learning and deep learning models has grown exponentially.However,challenges such as delayed retraining,inconsistent version management,insufficient drift monitoring,and limited data security still hinder efficient and reliable model operations.To address these issues,this paper proposes the Intelligent Model Lifecycle Management Algorithm(IMLMA).The algorithm employs a dual-trigger mechanism based on both data volume thresholds and time intervals to automate retraining,and applies Bayesian optimization for adaptive hyperparameter tuning to improve performance.A multi-metric replacement strategy,incorporating MSE,MAE,and R2,ensures that new models replace existing ones only when performance improvements are guaranteed.A versioning and traceability database supports comparison and visualization,while real-time monitoring with stability analysis enables early warnings of latency and drift.Finally,hash-based integrity checks secure both model files and datasets.Experimental validation in a power metering operation scenario demonstrates that IMLMA reduces model update delays,enhances predictive accuracy and stability,and maintains low latency under high concurrency.This work provides a practical,reusable,and scalable solution for intelligent model lifecycle management,with broad applicability to complex systems such as smart grids.展开更多
Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLM...Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.展开更多
In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asy...In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.展开更多
In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and cha...In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.展开更多
Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is empl...Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is employed to simulate the ballistic impact of 7.62 mm armor-piercing projectiles on Aluminum AA5083-H116 and Steel Secure 500 armors,focusing on the evaluation of material deformation and penetration resistance at varying impact points.While the D-shaped armor plate is penetrated by the armor-piercing projectiles,the combination of the perforated D-shaped and base armor plates successfully halts penetration.A numerical model based on the finite element method is developed using software such as SolidWorks and ANSYS to analyze the interaction between radiator armor and bullet.The perforated design of radiator armor is to maintain airflow for radiator function,with hole sizes smaller than the bullet core diameter to protect radiator assemblies.Predictions are made regarding the brittle fracture resulting from the projectile core′s bending due to asymmetric impact,and the resulting fragments failed to penetrate the perforated base armor plate.Craters are formed on the surface of the perforated D-shaped armor plate due to the impact of projectile fragments.The numerical model accurately predicts hole growth and projectile penetration upon impact with the armor,demonstrating effective protection of the radiator assemblies by the radiator armor.展开更多
BACKGROUND Orthopaedic surgical education has traditionally depended on the apprenticeship model of“see one,do one,teach one”.However,reduced operative exposure,stricter work-hour regulations,medicolegal constraints...BACKGROUND Orthopaedic surgical education has traditionally depended on the apprenticeship model of“see one,do one,teach one”.However,reduced operative exposure,stricter work-hour regulations,medicolegal constraints,and patient safety concerns have constrained its practicality.Simulation-based training has become a reliable,safe,and cost-efficient alternative.Dry lab techniques,especially virtual and augmented reality,make up 78%of current dry lab research,whereas wet labs still set the standard for anatomical realism.AIM To evaluate the effectiveness,limitations,and future directions of wet and dry lab simulation in orthopaedic training.METHODS A scoping review was carried out across four databases-PubMed,Cochrane Library,Web of Science,and EBSCOhost-up to 2025.Medical Subject Headings included:"Orthopaedic Education","Wet Lab","Dry Lab","Simulation Training","Virtual Reality",and"Surgical Procedure".Eligible studies focused on orthopaedic or spinal surgical education,employed wet or dry lab techniques,and assessed training effectiveness.Exclusion criteria consisted of non-English publications,abstracts only,non-orthopaedic research,and studies unrelated to simulation.Two reviewers independently screened titles,abstracts,and full texts,resolving discrepancies with a third reviewer.RESULTS From 1851 records,101 studies met inclusion:78 on dry labs,7 on wet labs,4 on both.Virtual reality(VR)simulations were most common,with AI increasingly used for feedback and assessment.Cadaveric training remains the gold standard for accuracy and tactile feedback,while dry labs-especially VR-offer scalability,lower cost(40%-60%savings in five studies),and accessibility for novices.Senior residents prefer wet labs for complex tasks;juniors favour dry labs for basics.Challenges include limited transferability data,lack of standard outcome metrics,and ethical concerns about cadaver use and AI assessment.CONCLUSION Wet and dry labs each have unique strengths in orthopaedic training.A hybrid approach combining both,supported by standardised assessments and outcome studies,is most effective.Future efforts should aim for uniform reporting,integrating new technologies,and policy support for hybrid curricula to enhance skills and patient care.展开更多
The National Geophysical Data Center(NGDC)of the United States has collected aeromagnetic data for input into a series of geomagnetic models to improve model resolution;however,in the Tibetan Plateau region,ground-bas...The National Geophysical Data Center(NGDC)of the United States has collected aeromagnetic data for input into a series of geomagnetic models to improve model resolution;however,in the Tibetan Plateau region,ground-based observations remain insufficient to clearly reflect the characteristics of the region’s lithospheric magnetism.In this study,we evaluate the lithospheric magnetism of the Tibetan Plateau by using a 3D surface spline model based on observations from>200 newly constructed repeat stations(portable stations)to determine the spatial distribution of plateau geomagnetism,as well as its correlation with the tectonic features of the region.We analyze the relationships between M≥5 earthquakes and lithospheric magnetic field variations on the Tibetan Plateau and identify regions susceptible to strong earthquakes.We compare the geomagnetic results with those from an enhanced magnetic model(EMM2015)developed by the NGDC and provide insights into improving lithospheric magnetic field calculations in the Tibetan Plateau region.Further research reveals that these magnetic anomalies exhibit distinct differences from the magnetic-seismic correlation mechanisms observed in other tectonic settings;here,they are governed primarily by the combined effects of compressional magnetism,thermal magnetism,and deep thermal stress.This study provides new evidence of geomagnetic anomalies on the Tibetan Plateau,interprets them physically,and demonstrates their potential for identifying seismic hazard zones on the Plateau.展开更多
Conventional surgical teaching techniques face several challenges,highlighting a necessity for ongoing innovation in ophthalmology education to align with the evolving demands of clinical practice.The recent rapid adv...Conventional surgical teaching techniques face several challenges,highlighting a necessity for ongoing innovation in ophthalmology education to align with the evolving demands of clinical practice.The recent rapid advancement of computer technology has enabled the integration of virtual reality(VR)into medical training,thereby revolutionizing ophthalmic surgical education through VRbased educational methods.VR technology offers a safe,risk-free environment for trainees to practice repeatedly,enhancing surgical skills and accelerating the learning curve without compromising patient safety.This research outlines the application of VR technology in ophthalmic surgical skills training,particularly in cataract and vitreoretinal surgery.Including assessing the effectiveness of intraocular surgery training systems,evaluating skills transfer to the operating room,comparing it with wet lab cataract surgery training,and enhancing non-dominant hand training for cataract surgery,among other aspects.Additionally,this paper will identify the limitations of VR technology in ocular surgical skills training,offer improvement strategies,and detail the advantages and prospects,with the objective of guiding subsequent researchers.展开更多
Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(...Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(2025)].In relation to seasonal forecasting and climate projection in the East Asian summer monsoon season,proper simulation of the seasonal migration of rain bands by models is a challenging and limiting factor[section 7.1 in Wang et al.(2025)].展开更多
To investigate the influence of coarse aggregate parent rock properties on the elastic modulus of concrete,the mineralogical properties and stress-strain curves of granite and dolomite parent rocks,as well as the stre...To investigate the influence of coarse aggregate parent rock properties on the elastic modulus of concrete,the mineralogical properties and stress-strain curves of granite and dolomite parent rocks,as well as the strength and elastic modulus of mortar and concrete prepared with mechanism aggregates of the corresponding lithology,and the stress-strain curves of concrete were investigated.In this paper,a coarse aggregate and mortar matrix bonding assumption is proposed,and a prediction model for the elastic modulus of mortar is established by considering the lithology of the mechanism sand and the slurry components.An equivalent coarse aggregate elastic modulus model was established by considering factors such as coarse aggregate particle size,volume fraction,and mortar thickness between coarse aggregates.Based on the elastic modulus of the equivalent coarse aggregate and the remaining mortar,a prediction model for the elastic modulus of the two and three components of concrete in series and then in parallel was established,and the predicted values differed from the measured values within 10%.It is proposed that the coarse aggregate elastic modulus in highstrength concrete is the most critical factor affecting the elastic modulus of concrete,and as the coarse aggregate elastic modulus increases by 27.7%,the concrete elastic modulus increases by 19.5%.展开更多
文摘Based on the complexity and regional differences of the political,economic,and cultural environments of countries along the“Belt and Road,”this paper analyzes the new characteristics of the current demand for business English talents.Combining this with the existing problems in China’s current training models,it proposes a reform path for talent training models that are adapted to the construction of the“Belt and Road”Initiative.The aim is to provide theoretical references and practical guidance for enhancing the international competitiveness of business English talents.
基金Key Project of Postgraduate Education and Teaching Reform and Research at Southwest Petroleum University(2022JG003)Degree and Postgraduate Education Research Project at Association of Chinese Graduate Education(2020MSA346)+1 种基金Sichuan Provincial Society for Degree and Graduate Education(2023YB0406)Higher Education Teaching Reform Research Project at Southwest Petroleum University(X2021JGYB003)。
文摘The international development of the petroleum industry has posed an urgent demand for the internationalization capabilities of both academic and professional master’s students.However,there is currently a shortage of such talent in the petroleum energy sector,along with a lack of a collaborative training system.Based on this,this study focuses on featured disciplines in the petroleum energy sector and systematically constructs an international talent training model centered around the“five-element synergy”of“government-school-enterprise-teacher-student.”Firstly,it defines the connotations of the five-element synergy:“government(strategic guidance)-school(platform support)-enterprise(demand verification)-teacher(leading transformation)-student(practical co-creation).”Secondly,it sets distinct training objectives for academic(focusing on academic innovation)and professional(emphasizing engineering practice)master’s students.Furthermore,it constructs a“categorized and layered,progressive and collaborative”curriculum system,builds an international faculty team through a“recruitment+training”dual-path approach,and cultivates students’sense of professional mission to“contribute to the nation’s energy sector”through a“macro+micro”perspective.This model provides a practical pathway for international talent training in the petroleum energy sector and holds significant importance for enhancing the overseas competitiveness of petroleum enterprises and safeguarding national energy security.
文摘Bronchiectasis is a chronic inflammatory airway disease,and patients often suffer from recurrent airway infections leading to decreased lung function and impaired quality of life.In this study,the effects of supervised pulmonary rehabilitation training on pulmonary function,training compliance,and quality of life in patients with bronchiectasis under home rehabilitation mode are investigated.Ninety stable patients were selected,and the observation group adopted the home-supervised mode of pulmonary rehabilitation training.The results showed that the observation group’s pulmonary function indexes,quality of life,and training adherence were better than those of the control group.The differences were statistically significant(P<0.05).The supervised pulmonary rehabilitation training in home rehabilitation mode can effectively improve patients’pulmonary function and quality of life,and improve training compliance,which has good clinical application value.
文摘With the continuous development of the nursing discipline,standardized nurse training has always been a crucial link in the development of nursing science and plays an irreplaceable role in talent cultivation.However,in the current standardized training for some nurses,there are problems such as the simplification of nursing skill evaluation models and insufficient post competence of nurses.Therefore,optimizing the training model for nursing talents has become an inevitable measure.The problem-based learning(PBL)method and the Direct Observation of Procedural Skills(DOPS)evaluation model provide new directions and guidance for the development of training.Against this background,this paper explores effective approaches for standardized nurse training,starting from basic concepts and gradually delving into specific practical paths,aiming to improve the quality of talent cultivation and provide valuable references for other researchers.
基金funded by the National Science and Technology Council,grant number NSTC 113-2221-E-002-136-.
文摘In order to help athletes optimize their performances in competitions while prevent overtraining and the risk of overuse injuries,it is important to develop science-based strategies for optimally designing training programs.The purpose of the present study is to develop a novel method by the combined use of optimal control theory and a training-performance model for designing optimal training programs,with the hope of helping athletes achieve the best performance exactly on the competition day while properly manage training load during the training course for preventing overtraining.The training-performance model used in the proposed optimal control framework is a conceptual extension of the Banister impulse-response model that describes the dynamics of performance,training load(served as the control variable),fitness(the overall positive effects on performance),and fatigue(the overall negative effects on performance).The objective functional of the proposed optimal control framework is to maximize the fitness and minimize the fatigue on the competition day with the goal of maximizing the performance on the competition day while minimizing the cumulative training load during the training course.The Forward-Backward Sweep Method is used to solve the proposed optimal control framework to obtain the optimal solutions of performance,training load,fitness,and fatigue.The simulation results show that the performance on the competition day is higher while the cumulative training load during the training course is lower with using optimal control theory than those without,successfully showing the feasibility and benefits of using the proposed optimal control framework to design optimal training programs for helping athletes achieve the best performance exactly on the competition day while properly manage training load during the training course for preventing overtraining.The present feasibility study lays the foundation of the combined use of optimal control theory and training-performance models to design personalized optimal training programs in real applications in athletic training and sports science for helping athletes achieve the best performances in competitions while prevent overtraining and the risk of overuse injuries.
基金Special Fund for Teacher Development Research Program of University of Shanghai for Science and Technology(Project No.:CFTD2025YB28)。
文摘Against the backdrop of the national innovation strategy and the digital transformation of education,the traditional“extensive”training model for innovation and entrepreneurship talents struggles to meet the personalized development needs of students,making an urgent shift toward precision and intelligence necessary.This study constructs a four-dimensional integrated framework centered on data,“Goal-Data-Intervention-Evaluation”,and proposes a data-driven training model for innovation and entrepreneurship talents in universities.By collecting multi-source data such as learning behaviors,competency assessments,and practical projects,the model conducts in-depth analysis of students’individual characteristics and development potential,enabling precise decision-making in goal setting,teaching intervention,and practical guidance.Based on data analysis,a supportive system for personalized teaching and practical activities is established.Combined with process-oriented and summative evaluations,a closed-loop feedback mechanism is formed to improve training effectiveness.This model provides a theoretical framework and practical path for the scientific,personalized,and intelligent development of innovation and entrepreneurship education in universities.
基金support from Strategic Project of Precision Surgery,Tsinghua UniversityInitiative Scientific Research Program,Institute for Intelligent Healthcare,Tsinghua University+5 种基金Tsinghua-Foshan Institute of Advanced ManufacturingNational Natural Science Foundation of China(61735016)Beijing Nova Program(20230484308)Young Elite Scientists Sponsorship Program by CAST(2023QNRC001)Youth Elite Program of Beijing Friendship Hospital(YYQCJH2022-9)Science and Technology Program of Beijing Tongzhou District(KJ2023CX012).
文摘Foundation models(FMs)have rapidly evolved and have achieved signicant accomplishments in computer vision tasks.Specically,the prompt mechanism conveniently allows users to integrate image prior information into the model,making it possible to apply models without any training.Therefore,we proposed a workflow based on foundation models and zero training to solve the tasks of photoacoustic(PA)image processing.We employed the Segment Anything Model(SAM)by setting simple prompts and integrating the model's outputs with prior knowledge of the imaged objects to accomplish various tasks,including:(1)removing the skin signal in three-dimensional PA image rendering;(2)dual speed-of-sound reconstruction,and(3)segmentation ofnger blood vessels.Through these demonstrations,we have concluded that FMs can be directly applied in PA imaging without the requirement for network design and training.This potentially allows for a hands-on,convenient approach to achieving efficient and accurate segmentation of PA images.This paper serves as a comprehensive tutorial,facilitating the mastery of the technique through the provision of code and sample datasets.
基金Thanks are given to Hebei Province Innovation Capacity Enhancement Programme Project(23560301D)the Natural Science Foundation of Hebei Province(E2024105036)the Tangshan Talent Funding Project(B202302007).
文摘Accurate assessment of blast furnace conditions is a crucial component in the blast furnace control decision-making process.However,most adversarial models in the field currently update the parameters of the label predictor by minimising the objective function while maximising the objective function to update the domain discriminator's parameters.This strategy results in an excessive maximisation of the domain discriminator's loss.To address this,a friendly adversarial training-based tri-training furnace condition diagnosis model was proposed.This model employed a convolutional neural network-long short-term memory-attention mechanism network as a single-view feature extractor and used decision tree methods as three classifiers to compute the cosine similarity between features and representative vectors of each class.During the knowledge transfer process,the classifiers in this model have a specific goal;they not only seek to maximise the entropy of the target domain samples but also aim to minimise the entropy of the target domain samples when they are misclassified,thus resolving the trade-off in traditional models where robustness is improved at the expense of accuracy.Experimental results indicate that the diagnostic accuracy of this model reaches 96%,with an approximately 8%improvement over existing methods due to the inner optimisation approach.This model provides an effective and feasible solution for the efficient monitoring and diagnosis of blast furnace processes.
基金The 2025 Guangdong Polytechnic College Innovation-driven School Strengthening Project“Construction of Shi Zhenjiang’s Master Studio for Intelligent Embedded System Development Skills”(Project No.:2025CQ06-05)。
文摘In the context of the rapid advancement of intelligent manufacturing,ensuring the alignment of the skill levels of embedded system developers with industry requirements has emerged as a crucial aspect in the reform of vocational education.This research delves into a three-stage progressive talent cultivation model denoted as“Cultivation–Growth–Incubation”,which is founded on the Shi Zhenjiang(Z.S.)Intelligent Embedded System Development Master Skills Studio.By means of hierarchical training,project-driven strategies,and industry-academia cooperation,this model effectively elevates students’application capabilities and innovative competencies in embedded systems.Case analyses illustrate the practical efficacy of the model,providing valuable references for the establishment of master skills studios in vocational education.
基金2025 Meizhou Municipal Planning Project of Philosophy and Social Sciences(Project No.:mzsklx2025101)。
文摘The development of Meizhou Hakka cuisine relies on the role of professional cooking talents.Higher vocational colleges serve as the platform for cultivating cooking talents.Among various training models,the implementation of the progressive talent training model featuring the integration of industry and education and work-study alternation is conducive to carrying out talent cultivation activities,improving the effectiveness of professional talent development,and effectively meeting the needs of market development.From the perspective of Meizhou Hakka cuisine cooking talents,this paper analyzes the problems existing in the implementation of the industry-education integration and work-study alternation model,and puts forward specific practical strategies for talent cultivation.The purpose is to enhance the training effect of Hakka cuisine cooking talents and provide reference for the subsequent optimization of professional teaching.
基金funded by Anhui NARI ZT Electric Co.,Ltd.,entitled“Research on the Shared Operation and Maintenance Service Model for Metering Equipment and Platform Development for the Modern Industrial Chain”(Grant No.524636250005).
文摘With the rapid adoption of artificial intelligence(AI)in domains such as power,transportation,and finance,the number of machine learning and deep learning models has grown exponentially.However,challenges such as delayed retraining,inconsistent version management,insufficient drift monitoring,and limited data security still hinder efficient and reliable model operations.To address these issues,this paper proposes the Intelligent Model Lifecycle Management Algorithm(IMLMA).The algorithm employs a dual-trigger mechanism based on both data volume thresholds and time intervals to automate retraining,and applies Bayesian optimization for adaptive hyperparameter tuning to improve performance.A multi-metric replacement strategy,incorporating MSE,MAE,and R2,ensures that new models replace existing ones only when performance improvements are guaranteed.A versioning and traceability database supports comparison and visualization,while real-time monitoring with stability analysis enables early warnings of latency and drift.Finally,hash-based integrity checks secure both model files and datasets.Experimental validation in a power metering operation scenario demonstrates that IMLMA reduces model update delays,enhances predictive accuracy and stability,and maintains low latency under high concurrency.This work provides a practical,reusable,and scalable solution for intelligent model lifecycle management,with broad applicability to complex systems such as smart grids.
文摘Model evaluation using benchmark datasets is an important method to measure the capability of large language models(LLMs)in specific domains,and it is mainly used to assess the knowledge and reasoning abilities of LLMs.Therefore,in order to better assess the capability of LLMs in the agricultural domain,Agri-Eval was proposed as a benchmark for assessing the knowledge and reasoning ability of LLMs in agriculture.The assessment dataset used in Agri-Eval covered seven major disciplines in the agricultural domain:crop science,horticulture,plant protection,animal husbandry,forest science,aquaculture science,and grass science,and contained a total of 2283 questions.Among domestic general-purpose LLMs,DeepSeek R1 performed best with an accuracy rate of 75.49%.In the realm of international general-purpose LLMs,Gemini 2.0 pro exp 0205 standed out as the top performer,achieving an accuracy rate of 74.28%.As an LLMs in agriculture vertical,Shennong V2.0 outperformed all the LLMs in China,and the answer accuracy rate of agricultural knowledge exceeded that of all the existing general-purpose LLMs.The launch of Agri-Eval helped the LLM developers to comprehensively evaluate the model's capability in the field of agriculture through a variety of tasks and tests to promote the development of the LLMs in the field of agriculture.
基金Supported by the National Natural Science Foundation of China(12261018)Universities Key Laboratory of Mathematical Modeling and Data Mining in Guizhou Province(2023013)。
文摘In this paper,we establish and study a single-species logistic model with impulsive age-selective harvesting.First,we prove the ultimate boundedness of the solutions of the system.Then,we obtain conditions for the asymptotic stability of the trivial solution and the positive periodic solution.Finally,numerical simulations are presented to validate our results.Our results show that age-selective harvesting is more conducive to sustainable population survival than non-age-selective harvesting.
基金the World Climate Research Programme(WCRP),Climate Variability and Predictability(CLIVAR),and Global Energy and Water Exchanges(GEWEX)for facilitating the coordination of African monsoon researchsupport from the Center for Earth System Modeling,Analysis,and Data at the Pennsylvania State Universitythe support of the Office of Science of the U.S.Department of Energy Biological and Environmental Research as part of the Regional&Global Model Analysis(RGMA)program area。
文摘In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.
文摘Utilizing finite element analysis,the ballistic protection provided by a combination of perforated D-shaped and base armor plates,collectively referred to as radiator armor,is evaluated.ANSYS Explicit Dynamics is employed to simulate the ballistic impact of 7.62 mm armor-piercing projectiles on Aluminum AA5083-H116 and Steel Secure 500 armors,focusing on the evaluation of material deformation and penetration resistance at varying impact points.While the D-shaped armor plate is penetrated by the armor-piercing projectiles,the combination of the perforated D-shaped and base armor plates successfully halts penetration.A numerical model based on the finite element method is developed using software such as SolidWorks and ANSYS to analyze the interaction between radiator armor and bullet.The perforated design of radiator armor is to maintain airflow for radiator function,with hole sizes smaller than the bullet core diameter to protect radiator assemblies.Predictions are made regarding the brittle fracture resulting from the projectile core′s bending due to asymmetric impact,and the resulting fragments failed to penetrate the perforated base armor plate.Craters are formed on the surface of the perforated D-shaped armor plate due to the impact of projectile fragments.The numerical model accurately predicts hole growth and projectile penetration upon impact with the armor,demonstrating effective protection of the radiator assemblies by the radiator armor.
文摘BACKGROUND Orthopaedic surgical education has traditionally depended on the apprenticeship model of“see one,do one,teach one”.However,reduced operative exposure,stricter work-hour regulations,medicolegal constraints,and patient safety concerns have constrained its practicality.Simulation-based training has become a reliable,safe,and cost-efficient alternative.Dry lab techniques,especially virtual and augmented reality,make up 78%of current dry lab research,whereas wet labs still set the standard for anatomical realism.AIM To evaluate the effectiveness,limitations,and future directions of wet and dry lab simulation in orthopaedic training.METHODS A scoping review was carried out across four databases-PubMed,Cochrane Library,Web of Science,and EBSCOhost-up to 2025.Medical Subject Headings included:"Orthopaedic Education","Wet Lab","Dry Lab","Simulation Training","Virtual Reality",and"Surgical Procedure".Eligible studies focused on orthopaedic or spinal surgical education,employed wet or dry lab techniques,and assessed training effectiveness.Exclusion criteria consisted of non-English publications,abstracts only,non-orthopaedic research,and studies unrelated to simulation.Two reviewers independently screened titles,abstracts,and full texts,resolving discrepancies with a third reviewer.RESULTS From 1851 records,101 studies met inclusion:78 on dry labs,7 on wet labs,4 on both.Virtual reality(VR)simulations were most common,with AI increasingly used for feedback and assessment.Cadaveric training remains the gold standard for accuracy and tactile feedback,while dry labs-especially VR-offer scalability,lower cost(40%-60%savings in five studies),and accessibility for novices.Senior residents prefer wet labs for complex tasks;juniors favour dry labs for basics.Challenges include limited transferability data,lack of standard outcome metrics,and ethical concerns about cadaver use and AI assessment.CONCLUSION Wet and dry labs each have unique strengths in orthopaedic training.A hybrid approach combining both,supported by standardised assessments and outcome studies,is most effective.Future efforts should aim for uniform reporting,integrating new technologies,and policy support for hybrid curricula to enhance skills and patient care.
基金supported by the CAS Pioneer Hundred Talents Program and Second Tibetan Plateau Scientific Expedition Research Program(2019QZKK0708)as well as the Basic Research Program of Qinghai Province:Lithospheric Geomagnetic Field of the Qinghai‒Tibet Plateau and the Relationship with Strong Earthquakes(2021-ZJ-969Q).
文摘The National Geophysical Data Center(NGDC)of the United States has collected aeromagnetic data for input into a series of geomagnetic models to improve model resolution;however,in the Tibetan Plateau region,ground-based observations remain insufficient to clearly reflect the characteristics of the region’s lithospheric magnetism.In this study,we evaluate the lithospheric magnetism of the Tibetan Plateau by using a 3D surface spline model based on observations from>200 newly constructed repeat stations(portable stations)to determine the spatial distribution of plateau geomagnetism,as well as its correlation with the tectonic features of the region.We analyze the relationships between M≥5 earthquakes and lithospheric magnetic field variations on the Tibetan Plateau and identify regions susceptible to strong earthquakes.We compare the geomagnetic results with those from an enhanced magnetic model(EMM2015)developed by the NGDC and provide insights into improving lithospheric magnetic field calculations in the Tibetan Plateau region.Further research reveals that these magnetic anomalies exhibit distinct differences from the magnetic-seismic correlation mechanisms observed in other tectonic settings;here,they are governed primarily by the combined effects of compressional magnetism,thermal magnetism,and deep thermal stress.This study provides new evidence of geomagnetic anomalies on the Tibetan Plateau,interprets them physically,and demonstrates their potential for identifying seismic hazard zones on the Plateau.
基金Supported by the Key Special Project of“Cutting-Edge Biotechnology”in the National Key Research and Development Program of China(No.2024YFC3406200)Sanming Project of Medicine in Shenzhen(No.SZSM202411007)Shenzhen Science and Technology Program(No.JCYJ20240813152704006).
文摘Conventional surgical teaching techniques face several challenges,highlighting a necessity for ongoing innovation in ophthalmology education to align with the evolving demands of clinical practice.The recent rapid advancement of computer technology has enabled the integration of virtual reality(VR)into medical training,thereby revolutionizing ophthalmic surgical education through VRbased educational methods.VR technology offers a safe,risk-free environment for trainees to practice repeatedly,enhancing surgical skills and accelerating the learning curve without compromising patient safety.This research outlines the application of VR technology in ophthalmic surgical skills training,particularly in cataract and vitreoretinal surgery.Including assessing the effectiveness of intraocular surgery training systems,evaluating skills transfer to the operating room,comparing it with wet lab cataract surgery training,and enhancing non-dominant hand training for cataract surgery,among other aspects.Additionally,this paper will identify the limitations of VR technology in ocular surgical skills training,offer improvement strategies,and detail the advantages and prospects,with the objective of guiding subsequent researchers.
文摘Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(2025)].In relation to seasonal forecasting and climate projection in the East Asian summer monsoon season,proper simulation of the seasonal migration of rain bands by models is a challenging and limiting factor[section 7.1 in Wang et al.(2025)].
基金Funded by State Railway Administration Research Project(No.2023JS007)National Natural Science Foundation of China(No.52438002)+1 种基金Research and Development Programs for Science and Technology of China Railways Corporation(No.J2023G003)New Cornerstone Science Foundation through the XPLORER PRIZE。
文摘To investigate the influence of coarse aggregate parent rock properties on the elastic modulus of concrete,the mineralogical properties and stress-strain curves of granite and dolomite parent rocks,as well as the strength and elastic modulus of mortar and concrete prepared with mechanism aggregates of the corresponding lithology,and the stress-strain curves of concrete were investigated.In this paper,a coarse aggregate and mortar matrix bonding assumption is proposed,and a prediction model for the elastic modulus of mortar is established by considering the lithology of the mechanism sand and the slurry components.An equivalent coarse aggregate elastic modulus model was established by considering factors such as coarse aggregate particle size,volume fraction,and mortar thickness between coarse aggregates.Based on the elastic modulus of the equivalent coarse aggregate and the remaining mortar,a prediction model for the elastic modulus of the two and three components of concrete in series and then in parallel was established,and the predicted values differed from the measured values within 10%.It is proposed that the coarse aggregate elastic modulus in highstrength concrete is the most critical factor affecting the elastic modulus of concrete,and as the coarse aggregate elastic modulus increases by 27.7%,the concrete elastic modulus increases by 19.5%.
