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
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
Safer,smarter,faster...In China,people prefer high-speed trains to flights if the journey time is under five hours.High-speed train travel is set to become even more attractive with the addition of a new member to the...Safer,smarter,faster...In China,people prefer high-speed trains to flights if the journey time is under five hours.High-speed train travel is set to become even more attractive with the addition of a new member to the high-speed train family:the CR450,the world’s fastest electric multiple unit(EMU).展开更多
With the advancement of computer and mathematical techniques,significant progress has been made in the 3D modeling of foundation piles.Existing methods include the 3D semi-analytical model for non-destructive low-stra...With the advancement of computer and mathematical techniques,significant progress has been made in the 3D modeling of foundation piles.Existing methods include the 3D semi-analytical model for non-destructive low-strain integrity assessment of large-diameter thin-walled pipe piles and the 3D soil-pile dynamic interaction model.However,these methods have complex analysis procedures and substantial limitations.This paper introduces an innovative and streamlined 3D imaging technique tailored for the detection of pile damage.The approach harnesses the power of an eight-channel ring array transducer to capture internal reflection signals within foundation piles.The acquired signals are subsequently processed using the Hilbert-Huang Transform(HHT),a robust analytical tool known for its effectiveness in handling non-stationary signals.Through the development of a sophisticated multi-channel ring array imaging algorithm,this technique empowers engineers and researchers to identify various pile defects,including their specific type,precise location,and obtain detailed 3D imaging representations.The findings of this research offer a valuable blend of theoretical insights and practical guidance,significantly advancing the state-of-the-art in the realm of concrete pile integrity inspection.By simplifying and enhancing the assessment process,this innovative approach not only addresses the complexities of existing methods but also contributes to the overall safety and reliability of concrete engineering structures.展开更多
软测量技术为工业过程中重要变量及难测变量的预测提供了一个有效的解决办法。然而,由于工业过程的复杂化和高昂的数据获取成本,使得标记数据与未标记数据分布不平衡。此时,构建高性能的软测量模型成为一个挑战。针对这一问题,提出了一...软测量技术为工业过程中重要变量及难测变量的预测提供了一个有效的解决办法。然而,由于工业过程的复杂化和高昂的数据获取成本,使得标记数据与未标记数据分布不平衡。此时,构建高性能的软测量模型成为一个挑战。针对这一问题,提出了一种基于时差的多输出tri-training异构软测量方法。通过构建一种新的tri-training框架,采用多输出的高斯过程回归(multi-output Gaussian process regression,MGPR)、相关向量机(multi-output relevance vector machine,MRVM)、最小二乘支持向量机(multi-output least squares support vector machine,MLSSVM)三种模型作为基线监督回归器,使用标记数据进行训练和迭代;同时,引入时间差分(time difference,TD)改进模型的动态特性,并通过卡尔曼滤波(Kalman filtering,KF)优化模型的参数,提高其预测性能;最后通过模拟污水处理平台(benchmark simulation model 1,BSM1)和实际污水处理厂对该模型进行了验证。结果表明,与传统的软测量建模方法相比,该模型能显著提高数据分布不平衡下软测量模型的自适应性和预测性能。展开更多
Purpose–The study aims to build a high-precision longitudinal dynamics model for heavy-haul trains and validate it with line test data,present an optimization method for multi-stage cyclic brakes based on the model a...Purpose–The study aims to build a high-precision longitudinal dynamics model for heavy-haul trains and validate it with line test data,present an optimization method for multi-stage cyclic brakes based on the model and conduct a multi-objective detailed evaluation of the driver’s manipulation during cyclic braking.Design/methodology/approach–The high-precision longitudinal train dynamics model was established and verified by the cyclic braking test data of the 20,000 t heavy-haul combination train on the long and steep downgrade.Then the genetic algorithm is employed for optimization subsequent to decoupling multiple cyclic braking procedures,with due consideration of driver operation rules.For evaluation,key manipulation assessments in the scenario are prioritized,supplemented by multi-objective evaluation requirements,and the computational model is employed for detailed evaluation analysis.Findings–Based on the model,experimental data reveal that the probability of longitudinal force error being less than 64.6 kN is approximately 68%,95%for less than 129.2 kN and 99.7%for less than 193.8 kN.Upon optimizing manipulations during the cyclic braking,the maximum reduction in coupler force spans from 21%∼23.9%.Andtheevaluation scoresimply that a proper elevationof the releasingspeed favorssafety.A high electric braking force,although beneficial to some extent for energy-saving,is detrimental to reducing coupler force.Originality/value–The results will provide a theoretical basis and practical guidance for further ensuring the safety and energy-efficient operation of heavy haul trains on long downhill sections and improving the operational quality of heavy-haul trains.展开更多
In recent years,railway construction in China has developed vigorously.With continuous improvements in the highspeed railway network,the focus is gradually shifting from large-scale construction to large-scale operati...In recent years,railway construction in China has developed vigorously.With continuous improvements in the highspeed railway network,the focus is gradually shifting from large-scale construction to large-scale operations.However,several challenges have emerged within the high-speed railway dispatching and command system,including the heavy workload faced by dispatchers,the difficulty of quantifying subjective expertise,and the need for effective training of professionals.Amid the growing application of artificial intelligence technologies in railway systems,this study leverages Large Language Model(LLM)technology.LLMs bring enhanced intelligence,predictive capabilities,robust memory,and adaptability to diverse real-world scenarios.This study proposes a human-computer interactive intelligent scheduling auxiliary training system built on LLM technology.The system offers capabilities including natural dialogue,knowledge reasoning,and human feedback learning.With broad applicability,the system is suitable for vocational education,guided inquiry,knowledge-based Q&A,and other training scenarios.Validation results demonstrate its effectiveness in auxiliary training,providing substantial support for educators,students,and dispatching personnel in colleges and professional settings.展开更多
Here we compare the efficacy of anti-obesity drugs alone or combined with exercise training on body weight and exercise capacity of obese patients.Randomized clinical trials that assessed the impact of any anti-obesit...Here we compare the efficacy of anti-obesity drugs alone or combined with exercise training on body weight and exercise capacity of obese patients.Randomized clinical trials that assessed the impact of any anti-obesity drug alone or combined with exercise training on body weight,body fat,fat-free mass and cardiorespiratory fitness in obese patients were retrieved from Pubmed and EMBASE up to May 2024.Risk of bias assessment was performed with RoB 2.0,and the GRADE approach assessed the certainty of evidence(CoE)of each main outcome.We included four publications summing up 202 patients.Two publications used orlistat as an anti-obesity drug treatment,while the other two adopted GLP-1 receptor agonist(liraglutide or tirzepatide)as a pharmacotherapy for weight management.Orlistat combined with exercise was superior to change body weight(mean difference(MD):−2.27 kg;95%CI:−2.86 to−1.69;CoE:very low),fat mass(MD:−2.89;95%CI:−3.87 to−1.91;CoE:very low),fat-free mass(MD:0.56;95%CI:0.40–0.72;CoE:very low),and VO_(2)Peak(MD:2.64;95%CI:2.52–2.76;CoE:very low).GLP-1 receptor agonist drugs combined with exercise had a great effect on body weight(MD:−3.96 kg;95%CI:−5.07 to−2.85;CoE:low),fat mass(MD:−1.76;95%CI:−2.24 to−1.27;CoE:low),fat-free mass(MD:0.50;95%CI:−0.98 to 1.98;CoE:very low)and VO_(2)Peak(MD:2.47;95%CI:1.31–3.63;CoE:very low).The results reported here suggest that exercise training remains an important approach in weight management when combined with pharmacological treatment.展开更多
BACKGROUND Cognitive frailty and depression are prevalent among the elderly,significantly impairing physical and cognitive functions,psychological well-being,and quality of life.Effective interventions are essential t...BACKGROUND Cognitive frailty and depression are prevalent among the elderly,significantly impairing physical and cognitive functions,psychological well-being,and quality of life.Effective interventions are essential to mitigate these adverse effects and enhance overall health outcomes in this population.AIM To evaluate the effects of exercise-cognitive dual-task training on frailty,cognitive function,psychological status,and quality of life in elderly patients with cognitive frailty and depression.METHODS A retrospective study was conducted on 130 patients with cognitive frailty and depression admitted between December 2021 and December 2023.Patients were divided into a control group receiving routine intervention and an observation group undergoing exercise-cognitive dual-task training in addition to routine care.Frailty,cognitive function,balance and gait,psychological status,and quality of life were assessed before and after the intervention.RESULTS After the intervention,the frailty score of the observation group was(5.32±0.69),lower than that of the control group(5.71±0.55).The Montreal cognitive assessment basic scale score in the observation group was(24.06±0.99),higher than the control group(23.43±1.40).The performance oriented mobility assessment score in the observation group was(21.81±1.24),higher than the control group(21.15±1.26).The self-efficacy in the observation group was(28.27±2.66),higher than the control group(30.05±2.66).The anxiety score in the hospital anxiety and depression scale(HADS)for the observation group was(5.86±0.68),lower than the control group(6.21±0.64).The depression score in the HADS for the observation group was(5.67±0.75),lower than the control group(6.27±0.92).Additionally,the scores for each dimension of the 36-item short form survey in the observation group were higher than those in the control group,with statistically significant differences(P<0.05).CONCLUSION Exercise-cognitive dual-task training is beneficial for improving frailty,enhancing cognitive function,and improving psychological status and quality of life in elderly patients with cognitive frailty and depression.展开更多
This paper introduces the Surrogate-assisted Multi-objective Grey Wolf Optimizer(SMOGWO)as a novel methodology for addressing the complex problem of empty-heavy train allocation,with a focus on line utilization balanc...This paper introduces the Surrogate-assisted Multi-objective Grey Wolf Optimizer(SMOGWO)as a novel methodology for addressing the complex problem of empty-heavy train allocation,with a focus on line utilization balance.By integrating surrogate models to approximate the objective functions,SMOGWO significantly improves the efficiency and accuracy of the optimization process.The effectiveness of this approach is evaluated using the CEC2009 multi-objective test function suite,where SMOGWO achieves a superiority rate of 76.67%compared to other leading multi-objective algorithms.Furthermore,the practical applicability of SMOGWO is demonstrated through a case study on empty and heavy train allocation,which validates its ability to balance line capacity,minimize transportation costs,and optimize the technical combination of heavy trains.The research highlights SMOGWO's potential as a robust solution for optimization challenges in railway transportation,offering valuable contributions toward enhancing operational efficiency and promoting sustainable development in the sector.展开更多
In recent years,train-tail swaying of 160 km/h electric multiple units(EMUs)inside single-line tunnels has been heavily researched,because the issue needs to be solved urgently.In this paper,a co-simulation model of v...In recent years,train-tail swaying of 160 km/h electric multiple units(EMUs)inside single-line tunnels has been heavily researched,because the issue needs to be solved urgently.In this paper,a co-simulation model of vortex-induced vibration(VIV)of the tail car body is established,and the aerodynamics of train-tail swaying is studied.The simulation results were confirmed through a field test of operating EMUs.Furthermore,the influence mechanism of train-tail swaying on the wake flow field is studied in detail through a wind-tunnel experiment and a simulation of a reduced-scaled train model.The results demonstrate that the aerodynamic force frequency(i.e.,vortex-induced frequency)of the train tail increases linearly with train speed.When the train runs at 130 km/h,with a small amplitude of train-tail swaying(within 10 mm),the vortex-induced frequency is 1.7 Hz,which primarily depends on the nose shape of the train tail.After the tail car body nose is extended,the vortex-induced frequency is decreased.As the swaying amplitude of the train tail increases(exceeding 25 mm),the separation point of the high-intensity vortex in the train wake shifts downstream to the nose tip,and the vortex-induced frequency shifts from 1.7 Hz to the nearby car body hunting(i.e.,the primary hunting)frequency of 1.3 Hz,which leads to the frequency-locking phenomenon of VIV,and the resonance intensifies train-tail swaying.For the motor vehicle of the train tail,optimization of the yaw damper to improve its primary hunting stability can effectively alleviate train-tail swaying inside single-line tunnels.Optimization of the tail car body nose shape reduces the amplitude of the vortex-induced force,thereby weakening the aerodynamic effect and solving the problem of train-tail swaying inside the single-line tunnels.展开更多
Purpose–In recent years,the rapid advancement of artificial intelligence(AI)has exerted profound impacts on and provided strong impetus to numerous fields in the industrial sector.Within the railway industry,AI has d...Purpose–In recent years,the rapid advancement of artificial intelligence(AI)has exerted profound impacts on and provided strong impetus to numerous fields in the industrial sector.Within the railway industry,AI has driven continuous upgrading and optimization of intelligent train control technology,thanks to its enhanced computational capabilities derived from advanced algorithms and models,as well as its role in improving safety performance.Integrating AI technology more extensively into train autonomous driving and control has thus become an inevitable trend in the global development of railways.Design/methodology/approach–This paper,therefore,conducts a comprehensive analysis of the development progress and current status of AI technology applications in the field of train driving and control on a global scale.It systematically sorts out and analyzes the advantages of various AI technologies and the positive impacts they bring to the upgrading of train control technology,elucidates the feasibility and future prospects of applying a range of emerging AI technologies from the perspective of technical theory and provides guidance for the intelligent development of this field from a practical perspective.Findings–The application of AI technology in the train driving and control field is still in its infancy.While a large number of AI technologies have been widely adopted,there remains significant room for further optimization and improvement of these technologies.Additionally,a variety of AI technologies that have been applied in other industrial sectors but not yet widely implemented in training autonomous driving and control have demonstrated tremendous development potential.Originality/value–The research findings provide references and guidance for advancing train control technology,promoting the digital transformation of railways,accelerating the overall optimization and upgrading of railway industry technologies,and facilitating the accelerated development of global railways.展开更多
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 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Safer,smarter,faster...In China,people prefer high-speed trains to flights if the journey time is under five hours.High-speed train travel is set to become even more attractive with the addition of a new member to the high-speed train family:the CR450,the world’s fastest electric multiple unit(EMU).
基金supported by China Scholarship Council(No.202008320084)the National Natural Science Foundation of China(Nos.11872191 and 11702118)Foreign Specialist Project of Ministry of Science and Technology(DL2022014011L).
文摘With the advancement of computer and mathematical techniques,significant progress has been made in the 3D modeling of foundation piles.Existing methods include the 3D semi-analytical model for non-destructive low-strain integrity assessment of large-diameter thin-walled pipe piles and the 3D soil-pile dynamic interaction model.However,these methods have complex analysis procedures and substantial limitations.This paper introduces an innovative and streamlined 3D imaging technique tailored for the detection of pile damage.The approach harnesses the power of an eight-channel ring array transducer to capture internal reflection signals within foundation piles.The acquired signals are subsequently processed using the Hilbert-Huang Transform(HHT),a robust analytical tool known for its effectiveness in handling non-stationary signals.Through the development of a sophisticated multi-channel ring array imaging algorithm,this technique empowers engineers and researchers to identify various pile defects,including their specific type,precise location,and obtain detailed 3D imaging representations.The findings of this research offer a valuable blend of theoretical insights and practical guidance,significantly advancing the state-of-the-art in the realm of concrete pile integrity inspection.By simplifying and enhancing the assessment process,this innovative approach not only addresses the complexities of existing methods but also contributes to the overall safety and reliability of concrete engineering structures.
文摘软测量技术为工业过程中重要变量及难测变量的预测提供了一个有效的解决办法。然而,由于工业过程的复杂化和高昂的数据获取成本,使得标记数据与未标记数据分布不平衡。此时,构建高性能的软测量模型成为一个挑战。针对这一问题,提出了一种基于时差的多输出tri-training异构软测量方法。通过构建一种新的tri-training框架,采用多输出的高斯过程回归(multi-output Gaussian process regression,MGPR)、相关向量机(multi-output relevance vector machine,MRVM)、最小二乘支持向量机(multi-output least squares support vector machine,MLSSVM)三种模型作为基线监督回归器,使用标记数据进行训练和迭代;同时,引入时间差分(time difference,TD)改进模型的动态特性,并通过卡尔曼滤波(Kalman filtering,KF)优化模型的参数,提高其预测性能;最后通过模拟污水处理平台(benchmark simulation model 1,BSM1)和实际污水处理厂对该模型进行了验证。结果表明,与传统的软测量建模方法相比,该模型能显著提高数据分布不平衡下软测量模型的自适应性和预测性能。
文摘Purpose–The study aims to build a high-precision longitudinal dynamics model for heavy-haul trains and validate it with line test data,present an optimization method for multi-stage cyclic brakes based on the model and conduct a multi-objective detailed evaluation of the driver’s manipulation during cyclic braking.Design/methodology/approach–The high-precision longitudinal train dynamics model was established and verified by the cyclic braking test data of the 20,000 t heavy-haul combination train on the long and steep downgrade.Then the genetic algorithm is employed for optimization subsequent to decoupling multiple cyclic braking procedures,with due consideration of driver operation rules.For evaluation,key manipulation assessments in the scenario are prioritized,supplemented by multi-objective evaluation requirements,and the computational model is employed for detailed evaluation analysis.Findings–Based on the model,experimental data reveal that the probability of longitudinal force error being less than 64.6 kN is approximately 68%,95%for less than 129.2 kN and 99.7%for less than 193.8 kN.Upon optimizing manipulations during the cyclic braking,the maximum reduction in coupler force spans from 21%∼23.9%.Andtheevaluation scoresimply that a proper elevationof the releasingspeed favorssafety.A high electric braking force,although beneficial to some extent for energy-saving,is detrimental to reducing coupler force.Originality/value–The results will provide a theoretical basis and practical guidance for further ensuring the safety and energy-efficient operation of heavy haul trains on long downhill sections and improving the operational quality of heavy-haul trains.
基金the Talent Fund of Beijing Jiaotong University(Grant No.2024XKRC055).
文摘In recent years,railway construction in China has developed vigorously.With continuous improvements in the highspeed railway network,the focus is gradually shifting from large-scale construction to large-scale operations.However,several challenges have emerged within the high-speed railway dispatching and command system,including the heavy workload faced by dispatchers,the difficulty of quantifying subjective expertise,and the need for effective training of professionals.Amid the growing application of artificial intelligence technologies in railway systems,this study leverages Large Language Model(LLM)technology.LLMs bring enhanced intelligence,predictive capabilities,robust memory,and adaptability to diverse real-world scenarios.This study proposes a human-computer interactive intelligent scheduling auxiliary training system built on LLM technology.The system offers capabilities including natural dialogue,knowledge reasoning,and human feedback learning.With broad applicability,the system is suitable for vocational education,guided inquiry,knowledge-based Q&A,and other training scenarios.Validation results demonstrate its effectiveness in auxiliary training,providing substantial support for educators,students,and dispatching personnel in colleges and professional settings.
基金supported by Brazilian agencies CAPES(Finance Code 001)CNPq through PQ productivity scholarship.
文摘Here we compare the efficacy of anti-obesity drugs alone or combined with exercise training on body weight and exercise capacity of obese patients.Randomized clinical trials that assessed the impact of any anti-obesity drug alone or combined with exercise training on body weight,body fat,fat-free mass and cardiorespiratory fitness in obese patients were retrieved from Pubmed and EMBASE up to May 2024.Risk of bias assessment was performed with RoB 2.0,and the GRADE approach assessed the certainty of evidence(CoE)of each main outcome.We included four publications summing up 202 patients.Two publications used orlistat as an anti-obesity drug treatment,while the other two adopted GLP-1 receptor agonist(liraglutide or tirzepatide)as a pharmacotherapy for weight management.Orlistat combined with exercise was superior to change body weight(mean difference(MD):−2.27 kg;95%CI:−2.86 to−1.69;CoE:very low),fat mass(MD:−2.89;95%CI:−3.87 to−1.91;CoE:very low),fat-free mass(MD:0.56;95%CI:0.40–0.72;CoE:very low),and VO_(2)Peak(MD:2.64;95%CI:2.52–2.76;CoE:very low).GLP-1 receptor agonist drugs combined with exercise had a great effect on body weight(MD:−3.96 kg;95%CI:−5.07 to−2.85;CoE:low),fat mass(MD:−1.76;95%CI:−2.24 to−1.27;CoE:low),fat-free mass(MD:0.50;95%CI:−0.98 to 1.98;CoE:very low)and VO_(2)Peak(MD:2.47;95%CI:1.31–3.63;CoE:very low).The results reported here suggest that exercise training remains an important approach in weight management when combined with pharmacological treatment.
文摘BACKGROUND Cognitive frailty and depression are prevalent among the elderly,significantly impairing physical and cognitive functions,psychological well-being,and quality of life.Effective interventions are essential to mitigate these adverse effects and enhance overall health outcomes in this population.AIM To evaluate the effects of exercise-cognitive dual-task training on frailty,cognitive function,psychological status,and quality of life in elderly patients with cognitive frailty and depression.METHODS A retrospective study was conducted on 130 patients with cognitive frailty and depression admitted between December 2021 and December 2023.Patients were divided into a control group receiving routine intervention and an observation group undergoing exercise-cognitive dual-task training in addition to routine care.Frailty,cognitive function,balance and gait,psychological status,and quality of life were assessed before and after the intervention.RESULTS After the intervention,the frailty score of the observation group was(5.32±0.69),lower than that of the control group(5.71±0.55).The Montreal cognitive assessment basic scale score in the observation group was(24.06±0.99),higher than the control group(23.43±1.40).The performance oriented mobility assessment score in the observation group was(21.81±1.24),higher than the control group(21.15±1.26).The self-efficacy in the observation group was(28.27±2.66),higher than the control group(30.05±2.66).The anxiety score in the hospital anxiety and depression scale(HADS)for the observation group was(5.86±0.68),lower than the control group(6.21±0.64).The depression score in the HADS for the observation group was(5.67±0.75),lower than the control group(6.27±0.92).Additionally,the scores for each dimension of the 36-item short form survey in the observation group were higher than those in the control group,with statistically significant differences(P<0.05).CONCLUSION Exercise-cognitive dual-task training is beneficial for improving frailty,enhancing cognitive function,and improving psychological status and quality of life in elderly patients with cognitive frailty and depression.
基金supported by the National Natural Science Foundation of China(Project No.5217232152102391)+2 种基金Sichuan Province Science and Technology Innovation Talent Project(2024JDRC0020)China Shenhua Energy Company Limited Technology Project(GJNY-22-7/2300-K1220053)Key science and technology projects in the transportation industry of the Ministry of Transport(2022-ZD7-132).
文摘This paper introduces the Surrogate-assisted Multi-objective Grey Wolf Optimizer(SMOGWO)as a novel methodology for addressing the complex problem of empty-heavy train allocation,with a focus on line utilization balance.By integrating surrogate models to approximate the objective functions,SMOGWO significantly improves the efficiency and accuracy of the optimization process.The effectiveness of this approach is evaluated using the CEC2009 multi-objective test function suite,where SMOGWO achieves a superiority rate of 76.67%compared to other leading multi-objective algorithms.Furthermore,the practical applicability of SMOGWO is demonstrated through a case study on empty and heavy train allocation,which validates its ability to balance line capacity,minimize transportation costs,and optimize the technical combination of heavy trains.The research highlights SMOGWO's potential as a robust solution for optimization challenges in railway transportation,offering valuable contributions toward enhancing operational efficiency and promoting sustainable development in the sector.
基金supported by the National Natural Science Foundation of China(Nos.52372403 and U2268211)the Natural Science Foundation of Sichuan Province(No.2022NSFSC0034),China+1 种基金the National Railway Group Science and Technology Program(No.2023J071)the Traction Power State Key Laboratory of the Independent Research and Development Projects(No.2022TPL-T02),China.
文摘In recent years,train-tail swaying of 160 km/h electric multiple units(EMUs)inside single-line tunnels has been heavily researched,because the issue needs to be solved urgently.In this paper,a co-simulation model of vortex-induced vibration(VIV)of the tail car body is established,and the aerodynamics of train-tail swaying is studied.The simulation results were confirmed through a field test of operating EMUs.Furthermore,the influence mechanism of train-tail swaying on the wake flow field is studied in detail through a wind-tunnel experiment and a simulation of a reduced-scaled train model.The results demonstrate that the aerodynamic force frequency(i.e.,vortex-induced frequency)of the train tail increases linearly with train speed.When the train runs at 130 km/h,with a small amplitude of train-tail swaying(within 10 mm),the vortex-induced frequency is 1.7 Hz,which primarily depends on the nose shape of the train tail.After the tail car body nose is extended,the vortex-induced frequency is decreased.As the swaying amplitude of the train tail increases(exceeding 25 mm),the separation point of the high-intensity vortex in the train wake shifts downstream to the nose tip,and the vortex-induced frequency shifts from 1.7 Hz to the nearby car body hunting(i.e.,the primary hunting)frequency of 1.3 Hz,which leads to the frequency-locking phenomenon of VIV,and the resonance intensifies train-tail swaying.For the motor vehicle of the train tail,optimization of the yaw damper to improve its primary hunting stability can effectively alleviate train-tail swaying inside single-line tunnels.Optimization of the tail car body nose shape reduces the amplitude of the vortex-induced force,thereby weakening the aerodynamic effect and solving the problem of train-tail swaying inside the single-line tunnels.
文摘Purpose–In recent years,the rapid advancement of artificial intelligence(AI)has exerted profound impacts on and provided strong impetus to numerous fields in the industrial sector.Within the railway industry,AI has driven continuous upgrading and optimization of intelligent train control technology,thanks to its enhanced computational capabilities derived from advanced algorithms and models,as well as its role in improving safety performance.Integrating AI technology more extensively into train autonomous driving and control has thus become an inevitable trend in the global development of railways.Design/methodology/approach–This paper,therefore,conducts a comprehensive analysis of the development progress and current status of AI technology applications in the field of train driving and control on a global scale.It systematically sorts out and analyzes the advantages of various AI technologies and the positive impacts they bring to the upgrading of train control technology,elucidates the feasibility and future prospects of applying a range of emerging AI technologies from the perspective of technical theory and provides guidance for the intelligent development of this field from a practical perspective.Findings–The application of AI technology in the train driving and control field is still in its infancy.While a large number of AI technologies have been widely adopted,there remains significant room for further optimization and improvement of these technologies.Additionally,a variety of AI technologies that have been applied in other industrial sectors but not yet widely implemented in training autonomous driving and control have demonstrated tremendous development potential.Originality/value–The research findings provide references and guidance for advancing train control technology,promoting the digital transformation of railways,accelerating the overall optimization and upgrading of railway industry technologies,and facilitating the accelerated development of global railways.
