Guided by the"Healthy China 2030"strategy,improving national nutrition and health literacy has become a core task in public health system development.The National Nutrition Plan(2017-2030)explicitly calls fo...Guided by the"Healthy China 2030"strategy,improving national nutrition and health literacy has become a core task in public health system development.The National Nutrition Plan(2017-2030)explicitly calls for"strengthening the training of nutrition talents"and"promoting nutrition science education".As a key vehicle for this mission,the Food Nutrition and Health course in higher education urgently needs to address bottlenecks in traditional teaching,such as low knowledge application and transfer rates,insufficient student engagement,and ineffective guidance on healthy behaviors.The BOPPPS teaching model,with its structured design(Bridge-in,Objective,Pre-assessment,Participatory Learning,Post-assessment,Summary),effectively promotes the internalization of nutritional knowledge and the transformation into healthy behaviors among students by emphasizing practice-oriented teaching activities.In this study,focusing on this course,an in-depth exploration of curriculum teaching design was conducted based on the BOPPPS instructional model,aiming to deeply integrate the strategic objectives of Healthy China into the curriculum,and promote the transformation of nutritional knowledge into healthy decision-making ability.This study provides new insights for food and nutrition education.展开更多
Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical si...Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical simulation plays a significant role in quantitatively evaluating current processes and making targeted improvements,but its limitations lie in the inability to dynamically reflect the formation outcomes of castings under varying process conditions,making real-time adjustments to gating and riser designs challenging.In this study,an automated design model for gating and riser systems based on integrated parametric 3D modeling-simulation framework is proposed,which enhances the flexibility and usability of evaluating the casting process by simulation.Firstly,geometric feature extraction technology is employed to obtain the geometric information of the target casting.Based on this information,an automated design framework for gating and riser systems is established,incorporating multiple structural parameters for real-time process control.Subsequently,the simulation results for various structural parameters are analyzed,and the influence of these parameters on casting formation is thoroughly investigated.Finally,the optimal design scheme is generated and validated through experimental verification.Simulation analysis and experimental results show that using a larger gate neck(24 mm in side length) and external risers promotes a more uniform temperature distribution and a more stable flow state,effectively eliminating shrinkage cavities and enhancing process yield by 15%.展开更多
Soft robotic manipulators represent a rapidly evolving field characterized by inherent compliance,adaptability,and safe interactions within unstructured environments.Over the past decade(2015-2025),significant advance...Soft robotic manipulators represent a rapidly evolving field characterized by inherent compliance,adaptability,and safe interactions within unstructured environments.Over the past decade(2015-2025),significant advancements have trans-formed their capabilities through novel designs inspired by biological systems,advanced modeling frameworks,sophisti-cated control strategies,and integration into diverse real-world applications.Recent innovations in multifunctional mate-rials and emerging actuation technologies have markedly expanded manipulator performance,reliability,and dexterity.Concurrently,developments in modeling have progressed from simplified geometric methods toward highly accurate physics-based and hybrid data-driven approaches,substantially improving real-time prediction and controllability.Coupled with these developments,adaptive and robust control strategies-including learning-based techniques-have enabled unprec-edented autonomy and precision in challenging application domains such as Minimally Invasive Surgery(MIS),precision agriculture,deep-sea exploration,disaster recovery,and space missions.Despite these remarkable strides,key challenges remain,notably regarding scalability,long-term material durability,robust integrated sensing,and standardized evaluation procedures.This review comprehensively synthesizes recent advances,critically evaluates state-of-the-art methodologies,and systematically identifies existing gaps to provide a clear roadmap and targeted research directions,guiding future developments toward the broader adoption and optimal utilization of soft robotic manipulators.展开更多
Magnesium hydride(MgH_(2)),a promising high-capacity hydrogen storage material,is hindered by slow dehydrogenation kinetics.AIdriven catalyst discovery to address this is often hampered by the laborious extraction of ...Magnesium hydride(MgH_(2)),a promising high-capacity hydrogen storage material,is hindered by slow dehydrogenation kinetics.AIdriven catalyst discovery to address this is often hampered by the laborious extraction of data from unstructured literature.To overcome this,we introduce a transformative“LLM to Agent”framework that synergistically integrates Large Language Models(LLMs)for automated data curation with Machine Learning(ML)for predictive design.We automatically constructed a comprehensive database of 809 MgH_(2)catalysts(6555 data rows)with high fidelity and an~40-fold acceleration over manual methods.The resulting ML models achieved high accuracy(average R^(2)>0.91)in predicting dehydrogenation temperature and activation energy,subsequently guiding a Genetic Algorithm(GA)in an exploratory inverse design that autonomously uncovered key design principles for high-performance catalysts.Encouragingly,a strong alignment was found between these AI-discovered principles and the design strategies of recently reported,state-of-the-art experimental systems,providing substantial evidence for the validity of our approach.The framework culminates in Cat-Advisor,a novel,domain-adapted multi-agent system.Cat-Advisor translates ML predictions and retrieval-augmented knowledge into actionable design guidance,demonstrating capabilities that surpass those of general-purpose LLMs in this specialized domain.This work delivers a practical AI toolkit for accelerated materials discovery and advances the emerging Agent-based paradigm for designing next-generation energy technologies.展开更多
To meet the extreme precision requirements of nanometer-scale semiconductor manufacturing and micrometer-level aerospace component processing,the complexity of precision manufacturing equipment design has exceeded the...To meet the extreme precision requirements of nanometer-scale semiconductor manufacturing and micrometer-level aerospace component processing,the complexity of precision manufacturing equipment design has exceeded the capabilities of traditional design methodologies.Conventional experience-driven design approaches exhibit fundamental limitations when confronting high-dimensional parameter spaces,complex multidisciplinary coupling effects,and dynamic performance prediction requirements,rendering trial-and-error iterative optimization processes inefficient and incapable of achieving optimal solutions.Intelligent design offers new pathways to overcome these limitations through the integration of artificial intelligence(AI)with traditional engineering workflows.However,the transition from theoretical concepts to manufacturing practice encounters three critical technical bottlenecks:the sparsity and heterogeneity of design data constrain the development of domain-specific large models,hallucination phenomena in generative design compromise solution trustworthiness,and numerical simulation methods face fundamental trade-offs between computational accuracy and efficiency.This paper conducts comprehensive analysis of the underlying causes of these challenges and proposes a knowledge-generation-simulation integrated intelligent design ecosystem as a development pathway.This approach achieves deep integration of large models with manufacturing domain knowledge,seamless fusion of AI with Computer-Aided Design/Computer-Aided Engineering(CAD/CAE)systems,and comprehensive synthesis of physics-based mechanisms with data-driven methods,driving the evolution of intelligent design from human-dominated iterative processes toward autonomous collaborative innovation systems,thereby providing robust support for technological breakthroughs in precision and extreme manufacturing equipment while facilitating the intelligent transformation of the manufacturing industry.展开更多
Over the past century,advancements in chemistry have significantly propelled human innovation,enhancing both industrial and consumer products.However,this rapid progression has resulted in chemical pollution increasin...Over the past century,advancements in chemistry have significantly propelled human innovation,enhancing both industrial and consumer products.However,this rapid progression has resulted in chemical pollution increasingly surpassing planetary boundaries,as production and release rates have outpaced our monitoring capabilities.To catalyze more impactful efforts,this study transitions from traditional chemical assessment to inverse chemical design,introducing a generative graph latent diffusion model aimed at discovering safer alternatives.In a case study on the design of green solvents for cyclohexane/benzene extraction distillation,we constructed a design database encompassing functional,environmental hazards,and process constraints.Virtual screening of previous design dataset revealed distinct trade-off trends between these design requirements.Based on the screening outcomes,an unconstrained generative model was developed,which covered a broader chemical space and demonstrated superior capabilities for structural interpolation and extrapolation.To further optimize molecular generation towards desired properties,a multi-objective latent diffusion method was applied,yielding 19 candidate molecules.Of these,7 were identified in PubChem as the most viable green solvent candidates,while the remaining 12 as potential novel candidates.Overall,this study effectively designed green solvent candidates for safer and more sustainable industrial production,setting a promising precedent for the development of environmentally friendly alternatives in other areas of chemical research.展开更多
With the continuous improvement of signal processing accuracy requirements in modern electronic systems,the demand for high-precision analog-to-digital converters(ADCs)is increasing.Sigma-Delta modulator,as the most i...With the continuous improvement of signal processing accuracy requirements in modern electronic systems,the demand for high-precision analog-to-digital converters(ADCs)is increasing.Sigma-Delta modulator,as the most important component of high-precision ADC,is widely used in high-quality audio,high-precision instrument measurement,and other fields due to its advantages of high precision,strong noise resistance,and low hardware cost.This article designs a discrete structure third-order four-bit high-precision Sigma-Delta modulator through modeling,with an oversampling rate set to 512.Under ideal conditions,the simulation results show that the SDNR reaches 152.7db and the ENOB is 25.24bits.After introducing non-ideal noise,the system performance has decreased.The simulation results show that the SDNR is as high as 124.5db and the ENOB is 20.39bits.This indicates that the design can achieve high-precision conversion and provide assistance for further research in the future.展开更多
Cobalt phosphide has been successfully used as a catalyst in the production of ammonia from nitric acid.Substituting appropriate atoms is expected to further improve its catalytic performance.Owing to the diversity of...Cobalt phosphide has been successfully used as a catalyst in the production of ammonia from nitric acid.Substituting appropriate atoms is expected to further improve its catalytic performance.Owing to the diversity of substituting elements,substitution sites,adsorption sites,and adsorption configurations,extensive time-consuming simulation calculations are required for the high-throughput screening method.Additionally,multi-objective attributes should be considered simultaneously in catalytic design.To tackle this challenge,this paper suggests a multi-objective cobalt phosphide catalytic material design method based on surrogate models.And the effectiveness of the proposed method was validated through comparative experiments.The proposed method led to the discovery of fifteen promising cobalt phosphide catalyst configurations.This study provides a new avenue for expediting the design of catalyst,with the potential for application in other systems.展开更多
Surgery of Traditional Chinese Medicine(TCM)is a core course within the TCM curriculum and an indispensable clinical discipline for all medical students transitioning to professional practice.With the deepening of cur...Surgery of Traditional Chinese Medicine(TCM)is a core course within the TCM curriculum and an indispensable clinical discipline for all medical students transitioning to professional practice.With the deepening of curriculum reforms,the integrated teaching model has proven effective in helping students master basic theories and clinical skills.Among various teaching models,the Bridge-in,Learning Objectives,Pre-Assessment,Participatory Learning,Post-Assessment,and Summary(BOPPPS)model combined with Problem-Based Learning has gained widespread recognition and application.However,its application in TCM surgery education remains limited.This paper integrates the BOPPPS and problem-based learning(PBL)teaching models into the TCM surgery classroom,using eczema as a case study.This teaching design encompasses six elements:bridge-in,learning objectives,pre-assessment,participatory learning based on Problem-Based Learning,post-assessment,and summary.Potential challenges during the teaching process are also examined to enhance students’clinical critical thinking abilities,improve the quality of classroom teaching,and further cultivate high-quality TCM professionals through the application of the BOPPPS-PBL model.展开更多
Underwater jet propulsion bio-inspired robots have typically been designed based on soft-bodied organisms, exhibiting relatively limited forms of locomotion. Scallop, a bivalve organism capable of jet propulsion, hold...Underwater jet propulsion bio-inspired robots have typically been designed based on soft-bodied organisms, exhibiting relatively limited forms of locomotion. Scallop, a bivalve organism capable of jet propulsion, holds significant importance in the study of underwater motion mechanisms. In this study, we present theoretical fluid mechanics analysis and modeling of the three distinct motion stages of scallops, providing parameterized descriptions of scallop locomotion mechanisms. Accordingly, three-stage adaptive motion control for the scallop robot and model-based robot configuration optimization design were achieved. An experimental platform and a robot prototype were built to validate the accuracy of the motion model and the effectiveness of the control strategy. Additionally, based on the models, future optimization directions for the robot are proposed.展开更多
The design and analysis of continuum robots have consistently been a prominent research focus in the field of mechanics.However,portable continuum robots with minimal spatial occupancy,which have great potential for a...The design and analysis of continuum robots have consistently been a prominent research focus in the field of mechanics.However,portable continuum robots with minimal spatial occupancy,which have great potential for applications such as search and rescue,are scarcely available.This paper presents a novel helical-coiled multi-segment flexible continuum robot featuring helical deployment and compact design,with an integrated framework for structural design,kinematic modeling,and experimental validation.The design of the helical-coiled multi-segment flexible continuum robot for unstructured environment detection,including a flexible body,an actuation module,a feed module,and a sensing module,is presented systematically.Kinematic models of both single-and multisegment continuum robots were established based on the constant curvature model to analyze the parameter mapping relationship from the end-effector position and orientation to the driving inputs.Furthermore,the feedforward motion of the robot was examined,and an uncoiling strategy based on S-curve compensation was employed to complete the kinematic analysis.Finally,the accuracy of the kinematic model considering the active uncoiling feed motion was validated through experimental analysis,demonstrating the motion characteristics of the continuum robot.Altogether,this study provides a framework for the design and analysis of helical-coiled continuum robots.展开更多
To capture the nonlinear dynamics and gain evolution in chirped pulse amplification(CPA)systems,the split-step Fourier method and the fourth-order Runge–Kutta method are integrated to iteratively address the generali...To capture the nonlinear dynamics and gain evolution in chirped pulse amplification(CPA)systems,the split-step Fourier method and the fourth-order Runge–Kutta method are integrated to iteratively address the generalized nonlinear Schrödinger equation and the rate equations.However,this approach is burdened by substantial computational demands,resulting in significant time expenditures.In the context of intelligent laser optimization and inverse design,the necessity for numerous simulations further exacerbates this issue,highlighting the need for fast and accurate simulation methodologies.Here,we introduce an end-to-end model augmented with active learning(E2E-AL)with decent generalization through different dedicated embedding methods over various parameters.On an identical computational platform,the artificial intelligence–driven model is 2000 times faster than the conventional simulation method.Benefiting from the active learning strategy,the E2E-AL model achieves decent precision with only two-thirds of the training samples compared with the case without such a strategy.Furthermore,we demonstrate a multi-objective inverse design of the CPA systems enabled by the E2E-AL model.The E2E-AL framework manifests the potential of becoming a standard approach for the rapid and accurate modeling of ultrafast lasers and is readily extended to simulate other complex systems.展开更多
With the raising complexity of modern civil aircraft,both academy and industry have shown strong interests on MBSE(Model-Based System Engineering).However,following the application of MBSE,the duration of the design p...With the raising complexity of modern civil aircraft,both academy and industry have shown strong interests on MBSE(Model-Based System Engineering).However,following the application of MBSE,the duration of the design phase exceeded expectations.This paper conducted a survey to the relevant participants involved in the design,revealed that a lack of proper process management is a critical issue.The current MBSE methodology does not provide clear guidelines for monitoring,controlling,and managing processes,which are crucial for both efficiency and effectiveness.To address this,the present paper introduced an improved Process Model(PM)within the MBSE framework for civil aircraft design.This improved model incorporates three new Management Blocks(MB):Progress Management Block(PMB),Review Management Block(RMB),and Configuration Management Block(CMB),developed based on the Capability Maturity Model Integration(CMMI).These additions aim to streamline the design process and better align it with engineering practices.The upgraded MBSE method with the improved PM offers a more structured approach to manage complex aircraft design projects,and a case study is conducted to validate its potential to reduce timelines and enhance overall project outcomes.展开更多
AlphaPanda(AlphaFold2[1]inspired protein-specific antibody design in a diffusional manner)is an advanced algorithm for designing complementary determining regions(CDRs)of the antibody targeted the specific epitope,com...AlphaPanda(AlphaFold2[1]inspired protein-specific antibody design in a diffusional manner)is an advanced algorithm for designing complementary determining regions(CDRs)of the antibody targeted the specific epitope,combining transformer[2]models,3DCNN[3],and diffusion[4]generative models.展开更多
Design patterns offer reusable solutions for common software issues,enhancing quality.The advent of generative large language models(LLMs)marks progress in software development,but their efficacy in applying design pa...Design patterns offer reusable solutions for common software issues,enhancing quality.The advent of generative large language models(LLMs)marks progress in software development,but their efficacy in applying design patterns is not fully assessed.The recent introduction of generative large language models(LLMs)like ChatGPT and CoPilot has demonstrated significant promise in software development.They assist with a variety of tasks including code generation,modeling,bug fixing,and testing,leading to enhanced efficiency and productivity.Although initial uses of these LLMs have had a positive effect on software development,their potential influence on the application of design patterns remains unexplored.This study introduces a method to quantify LLMs’ability to implement design patterns,using Role-Based Metamodeling Language(RBML)for a rigorous specification of the pattern’s problem,solution,and transformation rules.The method evaluates the pattern applicability of a software application using the pattern’s problem specification.If deemed applicable,the application is input to the LLM for pattern application.The resulting application is assessed for conformance to the pattern’s solution specification and for completeness against the pattern’s transformation rules.Evaluating the method with ChatGPT 4 across three applications reveals ChatGPT’s high proficiency,achieving averages of 98%in conformance and 87%in completeness,thereby demonstrating the effectiveness of the method.Using RBML,this study confirms that LLMs,specifically ChatGPT 4,have great potential in effective and efficient application of design patterns with high conformance and completeness.This opens avenues for further integrating LLMs into complex software engineering processes.展开更多
Accurate vector extraction from design drawings is required first to automatically create 3D models from pixel-level engineering design drawings. However, this task faces the challenges of complicated design shapes as...Accurate vector extraction from design drawings is required first to automatically create 3D models from pixel-level engineering design drawings. However, this task faces the challenges of complicated design shapes as well as cumbersome and cluttered annotations on drawings, which interfere with the vector extraction heavily. In this article, the transmission tower containing the most complex structure is taken as the research object, and a semantic segmentation network is constructed to first segment the shape masks from the pixel-level drawings. Preprocessing and postprocessing are also proposed to ensure the stability and accuracy of the shape mask segmentation. Then, based on the obtained shape masks, a vector extraction network guided by heatmaps is designed to extract structural vectors by fusing the features from node heatmap and skeleton heatmap, respectively. Compared with the state-of-the-art methods, experiment results illustrate that the proposed semantic segmentation method can effectively eliminate the interference of many elements on drawings to segment the shape masks effectively, meanwhile, the model trained by the proposed vector extraction network can accurately extract the vectors such as nodes and line connections, avoiding redundant vector detection. The proposed method lays a solid foundation for automatic 3D model reconstruction and contributes to technological advancements in relevant fields.展开更多
Reconstruction of a traumatic distal femur defect remains a therapeutic challenge.Bone defect implants have been proposed to substitute the bone defect,and their biomechanical performances can be analyzed via a numeri...Reconstruction of a traumatic distal femur defect remains a therapeutic challenge.Bone defect implants have been proposed to substitute the bone defect,and their biomechanical performances can be analyzed via a numerical approach.However,the material assumptions for past computational human femur simulations were mainly homogeneous.Thus,this study aimed to design and analyze scaffolds for reconstructing the distal femur defect using a patient-specific finite element modeling technique.A three-dimensional finite element model of the human femur with accurate geometry and material distribution was developed using the finite element method and material mapping technique.An intact femur and a distal femur defect model treated with nine microstructure scaffolds and two solid scaffolds were investigated and compared under a single-leg stance loading.The results showed that the metal solid scaffold design could provide the most stable fixation for reconstructing the distal femur defect.However,the fixation stability was affected by various microstructure designs and pillar diameters.A microstructure scaffold can be designed to satisfy all the biomechanical indexes,opening up future possibilities for more stable reconstructions.A three-dimensional finite element model of the femur with real bone geometry and bone material distribution can be developed,and this patient-specific femur model can be used for studying other femoral fractures or injuries,paving the way for more comprehensive research in the field.Besides,this patient-specific finite element modeling technique can also be applied to developing other human or animal bone models,expanding the scope of biomechanical research.展开更多
“Algorithm Design and Analysis”is not only one of the important courses in the undergraduate teaching of computer science and technology but also a key part of computer professional skills.In recent years,with the r...“Algorithm Design and Analysis”is not only one of the important courses in the undergraduate teaching of computer science and technology but also a key part of computer professional skills.In recent years,with the rise and widespread application of big language models,many teaching reform plans have been produced to promote the quality and efficiency of teaching.This paper studies how to refer to software development professional skills standards,investigates the knowledge points of“Algorithm Design and Analysis”courses in other educational institutions,uses cutting-edge core technology big language models to drive the improvement of teaching evaluation methods,improves teaching efficiency,and carries out reforms and practices in teaching content for undergraduate students in computer science.展开更多
To explore mix proportion design of RAC with aggregates tightly packed,the dry and wet packing density of recycled coarse aggregates mixture system and recycled coarse and fine aggregates were tested,then the influenc...To explore mix proportion design of RAC with aggregates tightly packed,the dry and wet packing density of recycled coarse aggregates mixture system and recycled coarse and fine aggregates were tested,then the influence of replacement rate and particle size ratio on the packing density of particle system was explored,the packing density prediction model of recycled coarse aggregates based on particle morphology was constructed,and the mix proportion optimization for recycled aggregate concrete with dry-wet packing model was carried out.The experimental results show that,with the increasing of recycled aggregate replacement rate or fine-grained volume ratio,the dry packing density of recycled coarse aggregates decreases gradually.With the increasing of replacement rate,the particle gradation can be optimized by increasing coarsegrained volume ratio.There is a significant effect for particle morphology parameter K and the particle size ratio on the packing density of the binary mixed system,and the packing density prediction model of recycled coarse aggregates based on particle morphology was constructed.The maximum increase in compressive strength and tensile strength of RAC with mix proportion optimized by the dry-wet packing model are 12.94%and 11.09%,and the cementitious materials is reduced by 21.83%,then the superiority of the mix proportion optimization of RAC with the dry-wet close packing model is confirmed.The results of this paper can provide a theoretical basis for the mix proportion design of RAC.展开更多
A distributed capacitance model for monolithic inductors is developed to predict the equivalently parasitical capacitances of the inductor.The ratio of the self-resonant frequency (f SR) of the differential-driven sym...A distributed capacitance model for monolithic inductors is developed to predict the equivalently parasitical capacitances of the inductor.The ratio of the self-resonant frequency (f SR) of the differential-driven symmetric inductor to the f SR of the single-ended driven inductor is firstly predicted and explained.Compared with a single-ended configuration,experimental data demonstrate that the differential inductor offers a 127% greater maximum quality factor and a broader range of operating frequencies.Two differential inductors with low parasitical capacitance are developed and validated.展开更多
文摘Guided by the"Healthy China 2030"strategy,improving national nutrition and health literacy has become a core task in public health system development.The National Nutrition Plan(2017-2030)explicitly calls for"strengthening the training of nutrition talents"and"promoting nutrition science education".As a key vehicle for this mission,the Food Nutrition and Health course in higher education urgently needs to address bottlenecks in traditional teaching,such as low knowledge application and transfer rates,insufficient student engagement,and ineffective guidance on healthy behaviors.The BOPPPS teaching model,with its structured design(Bridge-in,Objective,Pre-assessment,Participatory Learning,Post-assessment,Summary),effectively promotes the internalization of nutritional knowledge and the transformation into healthy behaviors among students by emphasizing practice-oriented teaching activities.In this study,focusing on this course,an in-depth exploration of curriculum teaching design was conducted based on the BOPPPS instructional model,aiming to deeply integrate the strategic objectives of Healthy China into the curriculum,and promote the transformation of nutritional knowledge into healthy decision-making ability.This study provides new insights for food and nutrition education.
基金financially supported by the National Key Research and Development Program of China (2022YFB3706802)。
文摘Automation and intelligence have become the primary trends in the design of investment casting processes.However,the design of gating and riser systems still lacks precise quantitative evaluation criteria.Numerical simulation plays a significant role in quantitatively evaluating current processes and making targeted improvements,but its limitations lie in the inability to dynamically reflect the formation outcomes of castings under varying process conditions,making real-time adjustments to gating and riser designs challenging.In this study,an automated design model for gating and riser systems based on integrated parametric 3D modeling-simulation framework is proposed,which enhances the flexibility and usability of evaluating the casting process by simulation.Firstly,geometric feature extraction technology is employed to obtain the geometric information of the target casting.Based on this information,an automated design framework for gating and riser systems is established,incorporating multiple structural parameters for real-time process control.Subsequently,the simulation results for various structural parameters are analyzed,and the influence of these parameters on casting formation is thoroughly investigated.Finally,the optimal design scheme is generated and validated through experimental verification.Simulation analysis and experimental results show that using a larger gate neck(24 mm in side length) and external risers promotes a more uniform temperature distribution and a more stable flow state,effectively eliminating shrinkage cavities and enhancing process yield by 15%.
基金Open access funding provided by The Science,Technology&Innovation Funding Authority(STDF)in cooperation with The Egyptian Knowledge Bank(EKB).
文摘Soft robotic manipulators represent a rapidly evolving field characterized by inherent compliance,adaptability,and safe interactions within unstructured environments.Over the past decade(2015-2025),significant advancements have trans-formed their capabilities through novel designs inspired by biological systems,advanced modeling frameworks,sophisti-cated control strategies,and integration into diverse real-world applications.Recent innovations in multifunctional mate-rials and emerging actuation technologies have markedly expanded manipulator performance,reliability,and dexterity.Concurrently,developments in modeling have progressed from simplified geometric methods toward highly accurate physics-based and hybrid data-driven approaches,substantially improving real-time prediction and controllability.Coupled with these developments,adaptive and robust control strategies-including learning-based techniques-have enabled unprec-edented autonomy and precision in challenging application domains such as Minimally Invasive Surgery(MIS),precision agriculture,deep-sea exploration,disaster recovery,and space missions.Despite these remarkable strides,key challenges remain,notably regarding scalability,long-term material durability,robust integrated sensing,and standardized evaluation procedures.This review comprehensively synthesizes recent advances,critically evaluates state-of-the-art methodologies,and systematically identifies existing gaps to provide a clear roadmap and targeted research directions,guiding future developments toward the broader adoption and optimal utilization of soft robotic manipulators.
基金supported by the Natural Science Foundation of Hebei Province(E2023502006)Fundamental Research Fund for the Central Universities(2025MS131).
文摘Magnesium hydride(MgH_(2)),a promising high-capacity hydrogen storage material,is hindered by slow dehydrogenation kinetics.AIdriven catalyst discovery to address this is often hampered by the laborious extraction of data from unstructured literature.To overcome this,we introduce a transformative“LLM to Agent”framework that synergistically integrates Large Language Models(LLMs)for automated data curation with Machine Learning(ML)for predictive design.We automatically constructed a comprehensive database of 809 MgH_(2)catalysts(6555 data rows)with high fidelity and an~40-fold acceleration over manual methods.The resulting ML models achieved high accuracy(average R^(2)>0.91)in predicting dehydrogenation temperature and activation energy,subsequently guiding a Genetic Algorithm(GA)in an exploratory inverse design that autonomously uncovered key design principles for high-performance catalysts.Encouragingly,a strong alignment was found between these AI-discovered principles and the design strategies of recently reported,state-of-the-art experimental systems,providing substantial evidence for the validity of our approach.The framework culminates in Cat-Advisor,a novel,domain-adapted multi-agent system.Cat-Advisor translates ML predictions and retrieval-augmented knowledge into actionable design guidance,demonstrating capabilities that surpass those of general-purpose LLMs in this specialized domain.This work delivers a practical AI toolkit for accelerated materials discovery and advances the emerging Agent-based paradigm for designing next-generation energy technologies.
基金supported by the National Key Research and Development Program of China(Grant No.2024YFB3309500)the National Natural Science Foundation of China(Grant Nos.U24B6005,U22A6001)。
文摘To meet the extreme precision requirements of nanometer-scale semiconductor manufacturing and micrometer-level aerospace component processing,the complexity of precision manufacturing equipment design has exceeded the capabilities of traditional design methodologies.Conventional experience-driven design approaches exhibit fundamental limitations when confronting high-dimensional parameter spaces,complex multidisciplinary coupling effects,and dynamic performance prediction requirements,rendering trial-and-error iterative optimization processes inefficient and incapable of achieving optimal solutions.Intelligent design offers new pathways to overcome these limitations through the integration of artificial intelligence(AI)with traditional engineering workflows.However,the transition from theoretical concepts to manufacturing practice encounters three critical technical bottlenecks:the sparsity and heterogeneity of design data constrain the development of domain-specific large models,hallucination phenomena in generative design compromise solution trustworthiness,and numerical simulation methods face fundamental trade-offs between computational accuracy and efficiency.This paper conducts comprehensive analysis of the underlying causes of these challenges and proposes a knowledge-generation-simulation integrated intelligent design ecosystem as a development pathway.This approach achieves deep integration of large models with manufacturing domain knowledge,seamless fusion of AI with Computer-Aided Design/Computer-Aided Engineering(CAD/CAE)systems,and comprehensive synthesis of physics-based mechanisms with data-driven methods,driving the evolution of intelligent design from human-dominated iterative processes toward autonomous collaborative innovation systems,thereby providing robust support for technological breakthroughs in precision and extreme manufacturing equipment while facilitating the intelligent transformation of the manufacturing industry.
基金supported by Shanghai Science and Technology Commission Project(No.21DZ1201502)Shanghai Municipal Bureau of Ecology and Environment(Shanghai Environ-mental Science[2023]No.40)+1 种基金the Interdisciplinary Joint Research Project of Tongji University(No.2022-4-YB-12)Shanghai Science and Technology Commission Project(No.22DZ2200200).
文摘Over the past century,advancements in chemistry have significantly propelled human innovation,enhancing both industrial and consumer products.However,this rapid progression has resulted in chemical pollution increasingly surpassing planetary boundaries,as production and release rates have outpaced our monitoring capabilities.To catalyze more impactful efforts,this study transitions from traditional chemical assessment to inverse chemical design,introducing a generative graph latent diffusion model aimed at discovering safer alternatives.In a case study on the design of green solvents for cyclohexane/benzene extraction distillation,we constructed a design database encompassing functional,environmental hazards,and process constraints.Virtual screening of previous design dataset revealed distinct trade-off trends between these design requirements.Based on the screening outcomes,an unconstrained generative model was developed,which covered a broader chemical space and demonstrated superior capabilities for structural interpolation and extrapolation.To further optimize molecular generation towards desired properties,a multi-objective latent diffusion method was applied,yielding 19 candidate molecules.Of these,7 were identified in PubChem as the most viable green solvent candidates,while the remaining 12 as potential novel candidates.Overall,this study effectively designed green solvent candidates for safer and more sustainable industrial production,setting a promising precedent for the development of environmentally friendly alternatives in other areas of chemical research.
文摘With the continuous improvement of signal processing accuracy requirements in modern electronic systems,the demand for high-precision analog-to-digital converters(ADCs)is increasing.Sigma-Delta modulator,as the most important component of high-precision ADC,is widely used in high-quality audio,high-precision instrument measurement,and other fields due to its advantages of high precision,strong noise resistance,and low hardware cost.This article designs a discrete structure third-order four-bit high-precision Sigma-Delta modulator through modeling,with an oversampling rate set to 512.Under ideal conditions,the simulation results show that the SDNR reaches 152.7db and the ENOB is 25.24bits.After introducing non-ideal noise,the system performance has decreased.The simulation results show that the SDNR is as high as 124.5db and the ENOB is 20.39bits.This indicates that the design can achieve high-precision conversion and provide assistance for further research in the future.
基金supported by the Jiangxi Provincial Natural Science Foundation(No.20224BAB212022)Science and Technology Project of Education Department of Jiangxi Province(No.GJJ211435)+3 种基金the National Key Research and Development Program of China(No.2021YFA1400204)the Project of China Postdoctoral Science Foundation(No.2022M712909)the Natural Science Foundation of China(No.21603109)the Henan Joint Fund of the National Natural Science Foundation of China(No.U1404216)。
文摘Cobalt phosphide has been successfully used as a catalyst in the production of ammonia from nitric acid.Substituting appropriate atoms is expected to further improve its catalytic performance.Owing to the diversity of substituting elements,substitution sites,adsorption sites,and adsorption configurations,extensive time-consuming simulation calculations are required for the high-throughput screening method.Additionally,multi-objective attributes should be considered simultaneously in catalytic design.To tackle this challenge,this paper suggests a multi-objective cobalt phosphide catalytic material design method based on surrogate models.And the effectiveness of the proposed method was validated through comparative experiments.The proposed method led to the discovery of fifteen promising cobalt phosphide catalyst configurations.This study provides a new avenue for expediting the design of catalyst,with the potential for application in other systems.
文摘Surgery of Traditional Chinese Medicine(TCM)is a core course within the TCM curriculum and an indispensable clinical discipline for all medical students transitioning to professional practice.With the deepening of curriculum reforms,the integrated teaching model has proven effective in helping students master basic theories and clinical skills.Among various teaching models,the Bridge-in,Learning Objectives,Pre-Assessment,Participatory Learning,Post-Assessment,and Summary(BOPPPS)model combined with Problem-Based Learning has gained widespread recognition and application.However,its application in TCM surgery education remains limited.This paper integrates the BOPPPS and problem-based learning(PBL)teaching models into the TCM surgery classroom,using eczema as a case study.This teaching design encompasses six elements:bridge-in,learning objectives,pre-assessment,participatory learning based on Problem-Based Learning,post-assessment,and summary.Potential challenges during the teaching process are also examined to enhance students’clinical critical thinking abilities,improve the quality of classroom teaching,and further cultivate high-quality TCM professionals through the application of the BOPPPS-PBL model.
基金supported by the Fundamental Research Funds for the Central Universities(No.30922010719).
文摘Underwater jet propulsion bio-inspired robots have typically been designed based on soft-bodied organisms, exhibiting relatively limited forms of locomotion. Scallop, a bivalve organism capable of jet propulsion, holds significant importance in the study of underwater motion mechanisms. In this study, we present theoretical fluid mechanics analysis and modeling of the three distinct motion stages of scallops, providing parameterized descriptions of scallop locomotion mechanisms. Accordingly, three-stage adaptive motion control for the scallop robot and model-based robot configuration optimization design were achieved. An experimental platform and a robot prototype were built to validate the accuracy of the motion model and the effectiveness of the control strategy. Additionally, based on the models, future optimization directions for the robot are proposed.
基金Supported by National Natural Science Foundation of China(Grant Nos.52305003,52175019)National Key R&D Program of China(Grant No.2023YFD2001100)+2 种基金Beijing Natural Science Foundation(Grant No.L222038)Beijing Nova Programme Interdisciplinary Cooperation Project(Grant No.20240484699)Project“Vice President of Science and Technology”of Changping District of Beijing.
文摘The design and analysis of continuum robots have consistently been a prominent research focus in the field of mechanics.However,portable continuum robots with minimal spatial occupancy,which have great potential for applications such as search and rescue,are scarcely available.This paper presents a novel helical-coiled multi-segment flexible continuum robot featuring helical deployment and compact design,with an integrated framework for structural design,kinematic modeling,and experimental validation.The design of the helical-coiled multi-segment flexible continuum robot for unstructured environment detection,including a flexible body,an actuation module,a feed module,and a sensing module,is presented systematically.Kinematic models of both single-and multisegment continuum robots were established based on the constant curvature model to analyze the parameter mapping relationship from the end-effector position and orientation to the driving inputs.Furthermore,the feedforward motion of the robot was examined,and an uncoiling strategy based on S-curve compensation was employed to complete the kinematic analysis.Finally,the accuracy of the kinematic model considering the active uncoiling feed motion was validated through experimental analysis,demonstrating the motion characteristics of the continuum robot.Altogether,this study provides a framework for the design and analysis of helical-coiled continuum robots.
基金supported by the National Natural Science Foundation of China(Grant Nos.62227821,62025503,and 62205199).
文摘To capture the nonlinear dynamics and gain evolution in chirped pulse amplification(CPA)systems,the split-step Fourier method and the fourth-order Runge–Kutta method are integrated to iteratively address the generalized nonlinear Schrödinger equation and the rate equations.However,this approach is burdened by substantial computational demands,resulting in significant time expenditures.In the context of intelligent laser optimization and inverse design,the necessity for numerous simulations further exacerbates this issue,highlighting the need for fast and accurate simulation methodologies.Here,we introduce an end-to-end model augmented with active learning(E2E-AL)with decent generalization through different dedicated embedding methods over various parameters.On an identical computational platform,the artificial intelligence–driven model is 2000 times faster than the conventional simulation method.Benefiting from the active learning strategy,the E2E-AL model achieves decent precision with only two-thirds of the training samples compared with the case without such a strategy.Furthermore,we demonstrate a multi-objective inverse design of the CPA systems enabled by the E2E-AL model.The E2E-AL framework manifests the potential of becoming a standard approach for the rapid and accurate modeling of ultrafast lasers and is readily extended to simulate other complex systems.
基金supported by the National Natural Science Foundation of China(No.62073267)。
文摘With the raising complexity of modern civil aircraft,both academy and industry have shown strong interests on MBSE(Model-Based System Engineering).However,following the application of MBSE,the duration of the design phase exceeded expectations.This paper conducted a survey to the relevant participants involved in the design,revealed that a lack of proper process management is a critical issue.The current MBSE methodology does not provide clear guidelines for monitoring,controlling,and managing processes,which are crucial for both efficiency and effectiveness.To address this,the present paper introduced an improved Process Model(PM)within the MBSE framework for civil aircraft design.This improved model incorporates three new Management Blocks(MB):Progress Management Block(PMB),Review Management Block(RMB),and Configuration Management Block(CMB),developed based on the Capability Maturity Model Integration(CMMI).These additions aim to streamline the design process and better align it with engineering practices.The upgraded MBSE method with the improved PM offers a more structured approach to manage complex aircraft design projects,and a case study is conducted to validate its potential to reduce timelines and enhance overall project outcomes.
基金supported by the Key Project of International Cooperation of Qilu University of Technology(Grant No.:QLUTGJHZ2018008)Shandong Provincial Natural Science Foundation Committee,China(Grant No.:ZR2016HB54)Shandong Provincial Key Laboratory of Microbial Engineering(SME).
文摘AlphaPanda(AlphaFold2[1]inspired protein-specific antibody design in a diffusional manner)is an advanced algorithm for designing complementary determining regions(CDRs)of the antibody targeted the specific epitope,combining transformer[2]models,3DCNN[3],and diffusion[4]generative models.
文摘Design patterns offer reusable solutions for common software issues,enhancing quality.The advent of generative large language models(LLMs)marks progress in software development,but their efficacy in applying design patterns is not fully assessed.The recent introduction of generative large language models(LLMs)like ChatGPT and CoPilot has demonstrated significant promise in software development.They assist with a variety of tasks including code generation,modeling,bug fixing,and testing,leading to enhanced efficiency and productivity.Although initial uses of these LLMs have had a positive effect on software development,their potential influence on the application of design patterns remains unexplored.This study introduces a method to quantify LLMs’ability to implement design patterns,using Role-Based Metamodeling Language(RBML)for a rigorous specification of the pattern’s problem,solution,and transformation rules.The method evaluates the pattern applicability of a software application using the pattern’s problem specification.If deemed applicable,the application is input to the LLM for pattern application.The resulting application is assessed for conformance to the pattern’s solution specification and for completeness against the pattern’s transformation rules.Evaluating the method with ChatGPT 4 across three applications reveals ChatGPT’s high proficiency,achieving averages of 98%in conformance and 87%in completeness,thereby demonstrating the effectiveness of the method.Using RBML,this study confirms that LLMs,specifically ChatGPT 4,have great potential in effective and efficient application of design patterns with high conformance and completeness.This opens avenues for further integrating LLMs into complex software engineering processes.
基金funded by the Chinese State Grid Jiangsu Electric Power Co.,Ltd.Science and Technology Project Funding,Grant Number J2023031.
文摘Accurate vector extraction from design drawings is required first to automatically create 3D models from pixel-level engineering design drawings. However, this task faces the challenges of complicated design shapes as well as cumbersome and cluttered annotations on drawings, which interfere with the vector extraction heavily. In this article, the transmission tower containing the most complex structure is taken as the research object, and a semantic segmentation network is constructed to first segment the shape masks from the pixel-level drawings. Preprocessing and postprocessing are also proposed to ensure the stability and accuracy of the shape mask segmentation. Then, based on the obtained shape masks, a vector extraction network guided by heatmaps is designed to extract structural vectors by fusing the features from node heatmap and skeleton heatmap, respectively. Compared with the state-of-the-art methods, experiment results illustrate that the proposed semantic segmentation method can effectively eliminate the interference of many elements on drawings to segment the shape masks effectively, meanwhile, the model trained by the proposed vector extraction network can accurately extract the vectors such as nodes and line connections, avoiding redundant vector detection. The proposed method lays a solid foundation for automatic 3D model reconstruction and contributes to technological advancements in relevant fields.
基金funded by the TaipeiMedical University-National Taiwan University of Science and Technology joint research program under Grant No.TMU-NTUST-109-09.
文摘Reconstruction of a traumatic distal femur defect remains a therapeutic challenge.Bone defect implants have been proposed to substitute the bone defect,and their biomechanical performances can be analyzed via a numerical approach.However,the material assumptions for past computational human femur simulations were mainly homogeneous.Thus,this study aimed to design and analyze scaffolds for reconstructing the distal femur defect using a patient-specific finite element modeling technique.A three-dimensional finite element model of the human femur with accurate geometry and material distribution was developed using the finite element method and material mapping technique.An intact femur and a distal femur defect model treated with nine microstructure scaffolds and two solid scaffolds were investigated and compared under a single-leg stance loading.The results showed that the metal solid scaffold design could provide the most stable fixation for reconstructing the distal femur defect.However,the fixation stability was affected by various microstructure designs and pillar diameters.A microstructure scaffold can be designed to satisfy all the biomechanical indexes,opening up future possibilities for more stable reconstructions.A three-dimensional finite element model of the femur with real bone geometry and bone material distribution can be developed,and this patient-specific femur model can be used for studying other femoral fractures or injuries,paving the way for more comprehensive research in the field.Besides,this patient-specific finite element modeling technique can also be applied to developing other human or animal bone models,expanding the scope of biomechanical research.
基金supported by Harbin Engineering University’s 2021 Education Reform Project“How to Make Computer Theory Teaching Serve Employment”(Grant No.JG2021B0609).
文摘“Algorithm Design and Analysis”is not only one of the important courses in the undergraduate teaching of computer science and technology but also a key part of computer professional skills.In recent years,with the rise and widespread application of big language models,many teaching reform plans have been produced to promote the quality and efficiency of teaching.This paper studies how to refer to software development professional skills standards,investigates the knowledge points of“Algorithm Design and Analysis”courses in other educational institutions,uses cutting-edge core technology big language models to drive the improvement of teaching evaluation methods,improves teaching efficiency,and carries out reforms and practices in teaching content for undergraduate students in computer science.
基金Funded by joint Funds of the National Natural Science Foundation of China(No.U1904188)the Key Research Project of Henan Province for Colleges and Universities(No.26A560009)+3 种基金the Jiaozuo City Science and Technology Planning Project(No.2025210099)the Henan Provincial Science and Technology Research Project(No.252102320305)the Natural Science Foundation of Henan Province(No.252300421917)the Project by Key Laboratory of Intelligent Construction and Safety Operation and Maintenance of Underground Engineering in Henan Province(No.KFKT2024-01)。
文摘To explore mix proportion design of RAC with aggregates tightly packed,the dry and wet packing density of recycled coarse aggregates mixture system and recycled coarse and fine aggregates were tested,then the influence of replacement rate and particle size ratio on the packing density of particle system was explored,the packing density prediction model of recycled coarse aggregates based on particle morphology was constructed,and the mix proportion optimization for recycled aggregate concrete with dry-wet packing model was carried out.The experimental results show that,with the increasing of recycled aggregate replacement rate or fine-grained volume ratio,the dry packing density of recycled coarse aggregates decreases gradually.With the increasing of replacement rate,the particle gradation can be optimized by increasing coarsegrained volume ratio.There is a significant effect for particle morphology parameter K and the particle size ratio on the packing density of the binary mixed system,and the packing density prediction model of recycled coarse aggregates based on particle morphology was constructed.The maximum increase in compressive strength and tensile strength of RAC with mix proportion optimized by the dry-wet packing model are 12.94%and 11.09%,and the cementitious materials is reduced by 21.83%,then the superiority of the mix proportion optimization of RAC with the dry-wet close packing model is confirmed.The results of this paper can provide a theoretical basis for the mix proportion design of RAC.
文摘A distributed capacitance model for monolithic inductors is developed to predict the equivalently parasitical capacitances of the inductor.The ratio of the self-resonant frequency (f SR) of the differential-driven symmetric inductor to the f SR of the single-ended driven inductor is firstly predicted and explained.Compared with a single-ended configuration,experimental data demonstrate that the differential inductor offers a 127% greater maximum quality factor and a broader range of operating frequencies.Two differential inductors with low parasitical capacitance are developed and validated.
