Alleviating the imbalance between urban and rural areas for regional coordinated development is an imperative response to the Sustainable Development Goal 10 of the United Nations.To track China’s urban-rural integra...Alleviating the imbalance between urban and rural areas for regional coordinated development is an imperative response to the Sustainable Development Goal 10 of the United Nations.To track China’s urban-rural integration progress and address the uneven issues in specific fields,this study constructed a novel seven-dimension index system of urban-rural integration,comprising free population mobility,efficient land transfer,interactive economic growth,highly-linked transportation,equal public services,joint environmental governance and unimpeded informatization between urban and rural areas.Based on a comprehensive measurement framework and multi-source panel data,we uncovered the spatial-temporal evolution of urban-rural integration in China’s 367 prefecture-level administrative units from 1980 to 2022.The results demonstrated that China’s urban-rural integration steadily increased from 27.51 to 57.35 with an average annual growth rate of 3.40%.Whereas,the overall urban-rural integration was relatively inferior in 2022,at the level of moderate integration whose proportion of China’s land area was 88.08%.The urban-rural integration level in eastern region and urban agglomerations was higher than that in mid-west and non-urban agglomerations.From the perspective of seven dimensions,interactive economic growth,joint environmental governance and unimpeded informatization made an obvious improvement and reached higher integration,while free population mobility,efficient land transfer,highly-linked transportation and equal public services maintained the stage of moderate integration in 2022.In the future,China should make targeted efforts for urban-rural integration in terms of population,land use,transportation and public services,and accelerate urban-rural common prosperity in the mid-west and economically underdeveloped areas.展开更多
Objective:This study aimed to compare the efficacy of Traditional Chinese Medicine(TCM)Five-Element Music Therapy(FEMT)versus Western Art Music Therapy(WAMT)in reducing negative emotions and improving sleep quality am...Objective:This study aimed to compare the efficacy of Traditional Chinese Medicine(TCM)Five-Element Music Therapy(FEMT)versus Western Art Music Therapy(WAMT)in reducing negative emotions and improving sleep quality among clinical nurses and to inform future psychological support strategies.Methods:This randomized controlled trial was conducted at the Department of Nursing,Xiyuan Hospital Jining Branch.Sixty nurses were randomized to receive either personalized FEMT based on TCM pattern differentiation or standardized WAMT.The intervention lasted 4 weeks.The outcomes were measured using the Hospital Anxiety and Depression Scale(HADS)and the Pittsburgh Sleep Quality Index(PSQI)at baseline,postintervention,and at 1-week follow-up.Results:Fifty-seven participants completed the study,29 in the FEMT group and 28 in the WAMT group.At the 4th week,both groups showed significant within-group improvements in HADS scores(FEMT:P=0.002;WAMT:P0.05).The WAMT group reported significantly higher scores on music acceptability and familiarity than the FEMT group(mean acceptability:9.39 vs.8.28,P=0.013;mean familiarity:9.29 vs.8.10,P<0.001).Conclusion:Both FEMT and WAMT were effective.FEMT was more effective than WAMT in reducing anxiety and depression symptoms,while WAMT was more familiar and acceptable.Music therapy is a viable intervention for improving nurses’well-being.展开更多
The coal chemical industry serves as an indispensable element in the fabric of the global energy system.However,the wastewater generated from its production processes exhibits high chemical oxygen demand,high toxicity...The coal chemical industry serves as an indispensable element in the fabric of the global energy system.However,the wastewater generated from its production processes exhibits high chemical oxygen demand,high toxicity,and poor biodegradability,posing severe challenges to the ecological sustainability of the coal chemical industry.This review systematically summarizes recent advances in treatment technologies for coal chemical wastewater(CCW)through a“pollutant molecules-technology-process integration”framework analyzed from micro-to macro-scale perspectives.It begins by delineating the complex chemical composition of CCW and identifying key toxic substances,thereby clarifying the current challenges in treatment processes and establishing a micro-scale foundation for technological development.The review then highlights solvent extraction,grounded in intermolecular interactions,as a core method for recovering phenolic compounds.This is followed by an in-depth analysis of the performance and mechanisms of biological treatment and advanced oxidation processes(AOPs)for the deep removal of refractory organic pollutants.Finally,from a macro-scale perspective,the integration of pretreatment,biological treatment,and AOPs into systematic frameworks is discussed.A thorough understanding of the molecular characteristics of pollutants is crucial for developing efficient treatment technologies.Moreover,system-level integration via process intensification and technological synergy is considered essential for achieving efficient purification and resource recovery from CCW.展开更多
Liquid crystal elastomers(LCEs)have emerged as a promising material platform for soft robotics,effectively integrating programmable molecular orientation with the inherent flexibility of elastomers.This unique combina...Liquid crystal elastomers(LCEs)have emerged as a promising material platform for soft robotics,effectively integrating programmable molecular orientation with the inherent flexibility of elastomers.This unique combination enables significant,reversible deformations responding to external stimuli,including heat,light,electric,and magnetic fields.Due to these characteristics,LCEs serve as an ideal material system for bridging biological principles with engineered soft robotic applications,enabling the development of adaptive and multifunctional systems with enhanced biomimetic capabilities.However,the mechanisms of bioinspired motion and the effective integration of biomimetic functions in LCE-based robots remain insufficiently explored.This review systematically examines recent advances in LCE-based biomimetic soft robots,focusing on multimodal actuation strategies,including contraction,crawling,rolling,jumping,swimming,and plant-inspired motions.It highlights integrated functional enhancements achieved via innovative material compositions,structural designs,and advanced manufacturing techniques.These developments have enabled novel robotic functionalities,including programmable actuation,self-healing and recycling,color morphing and camouflage,and tunable bioinspired surface characteristics.展开更多
Ferroelectric hafnium-oxide(HfO2)films have revitalized interest in brain-inspired hardware because of their high scalability,compatibility with complementary metal-oxide-semiconductor(CMOS)processes,and suitability f...Ferroelectric hafnium-oxide(HfO2)films have revitalized interest in brain-inspired hardware because of their high scalability,compatibility with complementary metal-oxide-semiconductor(CMOS)processes,and suitability for three-dimensional(3D)architectures.This review first analyses the origin,deposition routes,and performance of hafnia-based devices,including ferroelectric field-effect transistor,ferroelectric tunnelling junction and ferroelectric capacitor.As artificial intelligence(AI)continues to advance,the demand for higher memory density becomes increasingly critical.This review presents hafnia-based devices and arrays in both planar and 3D architectures.In 3D structures,the review discusses the principal integration constraints—back-end-of-line(BEOL)-compatible crystallization,conformal atomic layer deposition(ALD)with controlled phase and defects in high-aspect-ratio features,and cross-layer stress together with layer-to-layer variability/disturbance,which collectively determine stackable scalability and influence energy efficiency and training stability,thereby pointing toward compact,energy-efficient,and scalable 3D neuromorphic hardware based on hafnia ferroelectrics.展开更多
The fast-changing trajectory of energy systems toward renewables requires flexible,low-emission technologies that can buffer supply intermittently and offer large-scale energy storage systems.Moreso,hydrogen is increa...The fast-changing trajectory of energy systems toward renewables requires flexible,low-emission technologies that can buffer supply intermittently and offer large-scale energy storage systems.Moreso,hydrogen is increasingly viewed as a multi-scale flexibility resource capable of supporting deep decarbonization in renewable-dominated power systems,yet existing reviews often treat production,storage,and conversion technologies in isolation.Hydrogen offers the ability to convert,store and reconvert energy on various timescales.This review critically analyses the current literature of hydrogen production and storage in relation to power systems integration,synthesizing technical,economic and operational advances.The study synthesizes recent advances in electrolysis,particularly PEM and high-temperature SOEC systems,together with emerging PEC routes,biomass-to-hydrogen processes,and long-duration storage technologies.It considers,for storage,the performance and maturity of compressed gas,liquid hydrogen,metal and complex hydrides,liquid organic hydrogen carriers,and geological formations.Integration studies show that the value of hydrogen is enhanced as the share of renewables increases,providing seasonal storage,grid balancing,and sector coupling via power-to-hydrogen-to-power configurations.Yet technical,economic and other hurdles such as conversion losses,infrastructure requirements,and safety considerations are still holding back widespread implementation.The review also underlines the value of policy frameworks,such as country-level hydrogen strategies,carbon pricing,tax incentives,and harmonized safety standards to speed up adoption and reduce barriers to costs.The review synthesizes offer planners,operators,and policymakers a clear roadmap for aligning hydrogen deployment strategies with evolving technical requirements and high-renewable power-system conditions.By summarizing what is known and discussing opportunities for the future,this review is intended to be a roadmap towards maximizing hydrogen in reaching a flexible,resilient and carbon free power system.展开更多
The rapid and accurate detection of concrete sand moisture content(MC)is crucial for ensuring concrete quality.However,existing unimodal detection methods are constrained by limited representative features and lack ro...The rapid and accurate detection of concrete sand moisture content(MC)is crucial for ensuring concrete quality.However,existing unimodal detection methods are constrained by limited representative features and lack robustness.Multimodal operations often involve simple concatenation of features from different modalities,lacking potential interactivity among features.To address this issue,a novel robust cross-modal integration fusion model,which uses five branches to extract the features of images,near-infrared spectrum,and dielectric constant and a multilevel cross-modal integration fusion network to fuse these features,is proposed for the rapid detection of MC in concrete sand.Specifically,the multilevel cross-modal integration fusion network comprises a feature attention module,a cross-modal self-attention fusion module,and an integrated output module.The feature attention module enhances the feature representation from each modality,reducing the interference from redundant features and noise.The cross-modal self-attention fusion module employs a residual self-attention mechanism to deeply mine and fuse interactions between modalities while retaining low-level features,improving model accuracy and stability.The integrated output module is utilized to obtain more robust prediction results.The results show that the proposed model outperforms unimodal,traditional multimodal,and cross-modal methods on our concrete sand dataset,achieving excellent and robust prediction results for both machine-made sand(root mean square error ERMS=0.458,coefficient of determination R2=0.983,and residual predictive deviation DRP=7.900)and natural sand(ERMS=0.705,R2=0.984,and DRP=7.931).The detection time was within 71 s,significantly enhancing the detection frequency and efficiency,which provides a reliable solution for the rapid detection of MC in concrete sand.展开更多
Colorectal cancer(CRC)remains a major global health burden with the gut microbiome emerging as a critical contributor to tumor initiation and progression.Advances in high-throughput sequencing have deepened our unders...Colorectal cancer(CRC)remains a major global health burden with the gut microbiome emerging as a critical contributor to tumor initiation and progression.Advances in high-throughput sequencing have deepened our understanding of host-microbe interactions across genomic,transcriptomic,epigenomic,and metabolomic levels.This review synthesizes current knowledge on how microbial communities shape colorectal carcinogenesis,including induction of genomic instability,remodeling of host transcriptional and epigenetic landscapes,and reprogramming of metabolic pathways within the tumor microenvironment.Integrative multi-omics strategies and advanced computational tools are powerful means for dissecting these complex biological systems.However,analytical challenges,such as data compositionality,sparsity,and high dimensionality,still hinder meaningful interpretation.Emerging technologies,like long-read sequencing and bacterial single-cell spatial transcriptomics,are enhancing the resolution and accuracy of microbiota profiling.Finally,the convergence of advanced experimental models,artificial intelligence-driven computational integration,and precision microbiome medicine are highlighted as key avenues for translating microbiome insights into preventive,diagnostic,and therapeutic innovations in CRC.展开更多
County-to-district conversion(CDC) has restructured the pattern of urban-rural development and influenced the allocation of resources by local governments as well as the urbanization process.However,the impact and mec...County-to-district conversion(CDC) has restructured the pattern of urban-rural development and influenced the allocation of resources by local governments as well as the urbanization process.However,the impact and mechanism of the CDC on China's urban-rural integration development(URID) are not yet clear.Using panel data from 52 county-level cities,districts,and counties in Jiangsu Province of China during 2005–2021,this paper constructed an evaluation system for URID and applied the multi-period difference-in-differences(DID) model to measure the impact of the CDC on URID and identify its primary mechanisms of action.The results demonstrated that the CDC has significantly fostered URID,though with pronounced regional heterogeneity.Specifically,while the CDC facilitated URID in the southern and central Jiangsu Province—regions characterized by high socio-economic development—it exerted a less significant impact in the comparatively underdeveloped northern Jiangsu Province.Mechanistically,the implementation of the CDC promotes equal regional development,enhances rural selfdevelopment capacity,improves environmental quality and living standards,and optimizes urban-rural land allocation and transport networks.Ultimately,this study clarifies the role of the CDC in China,provides insights for achieving URID,and offers a reference for other countries pursuing coordinated urban-rural development.展开更多
Promoting urban-rural integration and facilitating the bidirectional flow of urban and rural elements are core spatial objectives in the new era of China.The urban-rural fringe represents the region with the most inte...Promoting urban-rural integration and facilitating the bidirectional flow of urban and rural elements are core spatial objectives in the new era of China.The urban-rural fringe represents the region with the most intense interaction between urban and rural areas,serving as a key zone for breaking down barriers and promoting urban-rural integration.Based on a systematic review of representative case studies and scholarly literature,this paper synthesizes the evolving research perspectives on the urban-rural fringe,with particular attention to how data-driven approaches that integrate official statistics,remote sensing imagery,points of interest,and mobile phone signaling data have advanced the characterization of fringe features,refined identification methods,and revealed emerging developmental trends through spatial clustering and machine learning classification.It proposes an integrated analytical framework encompassing administrative boundaries,economic metabolism,social activities,material infrastructure,and the ecological environment.The paper further examines the characteristics and emerging development trends of urban-rural fringe areas and advances a set of strategic directions to support urban-rural integration and more efficient resource allocation.These include expanding analytical dimensions,enhancing data integration,refining identification criteria,elucidating mechanisms of internal and external interactions,and strengthening interdisciplinary collaboration.Collectively,these efforts offer actionable insights for optimizing public service delivery,directing infrastructure investment in transportation and utilities,delineating ecological conservation boundaries,and implementing place-based socioeconomic revitalization strategies in the urban-rural fringe regions.展开更多
OBJECTIVE:To evaluate the efficacy of Traditional Chinese Medicine(TCM)psychosomatic integration therapy in treating subthreshold depression(SD).METHODS:A multicenter randomized controlled trial was conducted.Eligible...OBJECTIVE:To evaluate the efficacy of Traditional Chinese Medicine(TCM)psychosomatic integration therapy in treating subthreshold depression(SD).METHODS:A multicenter randomized controlled trial was conducted.Eligible participants were evaluated by physicians and randomly assigned to either the intervention or control group.The intervention group received group psychotherapy,Jue tune music therapy,and Yuleyin oral formula(郁乐饮).The control group received only group psychotherapy.The intervention period lasted 12 weeks,followed by a 12-week follow-up.The primary outcome was the Center for Epidemiologic Studies Depression Scale(CES-D)score at week 12.Secondary outcomes included dropout rate,scores of the Hamilton Anxiety Scale(HAMA)and the Hamilton Depression Rating Scale(HAMD-17)at week 12,and CES-D scores at weeks 4,8,16,20,and 24.RESULTS:A total of 505 patients were randomly allocated to the two groups,and 496 participants[77%female;(38±16)years]were included in the final analysis.The primary outcome showed no statistically significant difference in CES-D scores between the intervention and control groups at week 12(P>0.05).However,the intervention group exhibited significant reductions in CES-D scores at weeks 4,8,12,16,20,and 24 compared to baseline,and at week 24 compared to week 12(P<0.0001).The control group also showed significant reductions in CES-D scores at weeks 4 and 8 during the intervention period(P<0.0001).Although no significant differences were observed between groups at each specific time point,the intervention group showed a more consistent downward trend.Additionally,both HAMD and HAMA scores significantly decreased from baseline to week 12 in both groups(P<0.0001).CONCLUSIONS:TCM psychosomatic integration therapy,which includes group psychotherapy,Jue tune music therapy,and Yuleyin oral formula,may be effective in improving symptoms of SD,with good safety and feasibility.The complete TCM intervention demonstrated better long-term effectiveness than group psychotherapy alone.Further high-quality studies are needed to validate these findings.展开更多
Stable transgene expression in the mammary gland is crucial for recombinant protein production in livestock,yet it is frequently hampered by transgene silencing and random integration.To address this,we profile chroma...Stable transgene expression in the mammary gland is crucial for recombinant protein production in livestock,yet it is frequently hampered by transgene silencing and random integration.To address this,we profile chromatin accessibility in goat mammary epithelial cells(GMECs)using ATAC-seq and identify 15 highly accessible genomic regions.Three of these regions are confirmed to support stable transgene expression.Notably,we identify a goat-derived ubiquitous chromatin opening element(UCOE)in the SF3B1-COQ10B intergenic region,with a high GC content(65%)and CpG island enrichment.This UCOE improves hfCas12Max-mediated integration of large DNA fragments and maintains high-level expression of human lactoferrin(hLTF)in GMECs.Subsequently,we precisely integrate the UCOE-hLTF cassette into the highly accessible loci and generate a transgenic goat via somatic cell nuclear transfer,without detectable off-target effects.Our pipeline,which integrates chromatin accessibility profiling,UCOE discovery,and precision editing,demonstrates the role of CpG island-containing UCOEs in preventing transgene silencing.The study provides valuable tools for enhancing recombinant protein production,supports the breeding of dairy goats for milk with high lactoferrin content,and advances the understanding of the interactions between chromatin,regulatory elements,and transgenes in molecular breeding.展开更多
Alzheimer's disease(AD),the most common cause of dementia,is a progressive neurodegenerative disease characterized by progressive cognitive decline and memory loss.Mild cognitive impairment(MCI)is the prodromal st...Alzheimer's disease(AD),the most common cause of dementia,is a progressive neurodegenerative disease characterized by progressive cognitive decline and memory loss.Mild cognitive impairment(MCI)is the prodromal stage of AD,with a conversion rate of 10%-15%per year and 50%conversion rate longitudinally.The pathological features of AD include the aberrant accumulation of amyloid-βplaques,neurofibrillary tangles formed by hyperphosphorylated tau and synaptic dysfunction(Nussbaumer et al.,2025),all of which have cascading effects on the brain activity of AD patients.展开更多
Synergistic pollution reduction and carbon mitigation(SPRCM)are inherent requirements for high-quality development.This study explores the internal mechanisms through which digital-green integration(DGI)policies facil...Synergistic pollution reduction and carbon mitigation(SPRCM)are inherent requirements for high-quality development.This study explores the internal mechanisms through which digital-green integration(DGI)policies facilitate SPRCM from the perspective of deep integration between“digitalization”and“greenization”.It aims to provide policy recommendations for coordinating the implementation of the“Digital China”and“Beautiful China”strategies.Using panel data from 280 prefecture-level cities(2010-2022)and treating the overlap between the Big Data Comprehensive Pilot Zone policy and the Low-Carbon City Pilot policy as a quasi-natural experiment for DGI,this study applies a double machine learning model to investigate its impact mechanisms and multidimensional policy effects.The findings indicate that,first,DGI enhances pollution emission efficiency and carbon emission efficiency,generating significant synergistic effects.Second,mechanism analysis based on whole-process production control reveals that during the source prevention stage,DGI drives SPRCM by optimizing the energy structure.At the process control stage,it enhances synchronized SPRCM through improved production efficiency.At the end-of-pipe treatment stage,advancements in green end-of-pipe technologies emerge as the dominant force propelling synergistic effects.Third,heterogeneity analysis reveals that the pollution reduction and carbon mitigation effects of DGI are more pronounced in resource-based cities,innovative cities,and cities within the Yangtze River Economic Belt than in non resource-based cities,non-innovative cities,and cities outside this strategic economic region.Consequently,a multipronged policy mix should be implemented to amplify the catalytic role of digital-green policy integration in driving pollution and carbon reduction.Whole-process production controls must be strengthened to streamline mitigation pathways,and region-specific strategies for DGI should be tailored based on local conditions with dynamic guidance.展开更多
This study aims to promote the optimization and upgrading of the economic structure in rural areas of China by focusing on the coupling coordination mechanism between digital economy–agriculture integration and rural...This study aims to promote the optimization and upgrading of the economic structure in rural areas of China by focusing on the coupling coordination mechanism between digital economy–agriculture integration and rural revitalization.By examining panel data from 30 Chinese provinces,autonomous regions,and municipalities between 2011 and 2022,the research constructs a weight-based evaluation system that integrates subjective and objective methods and a coupling coordination model to reveal its dynamic evolution patterns.Key findings indicate that digital economy–agriculture integration and rural revitalization achieve cross-coupling through critical activities.The impact of digital-agriculture integration on advancing rural revitalization lags by 2–3 years.Although the coupling development degree between the two systems continues to improve,it remains at the stage of primary coordination.Regional disparities are significant,showing a gradient pattern of“high degree of coupling development in the east and low degree of coupling development in the west.”展开更多
In reliability analyses,the absence of a priori information on the most probable point of failure(MPP)may result in overlooking critical points,thereby leading to biased assessment outcomes.Moreover,second-order relia...In reliability analyses,the absence of a priori information on the most probable point of failure(MPP)may result in overlooking critical points,thereby leading to biased assessment outcomes.Moreover,second-order reliability methods exhibit limited accuracy in highly nonlinear scenarios.To overcome these challenges,a novel reliability analysis strategy based on a multimodal differential evolution algorithm and a hypersphere integration method is proposed.Initially,the penalty function method is employed to reformulate the MPP search problem as a conditionally constrained optimization task.Subsequently,a differential evolution algorithm incorporating a population delineation strategy is utilized to identify all MPPs.Finally,a paraboloid equation is constructed based on the curvature of the limit-state function at the MPPs,and the failure probability of the structure is calculated by using the hypersphere integration method.The localization effectiveness of the MPPs is compared through multiple numerical cases and two engineering examples,with accuracy comparisons of failure probabilities against the first-order reliability method(FORM)and the secondorder reliability method(SORM).The results indicate that the method effectively identifies existing MPPs and achieves higher solution precision.展开更多
This paper investigates the teaching reform of the Program Comprehension and Analysis course in the context of industry-education integration and AI empowerment.To align with the evolving needs of the software industr...This paper investigates the teaching reform of the Program Comprehension and Analysis course in the context of industry-education integration and AI empowerment.To align with the evolving needs of the software industry,the course content has been updated to incorporate AI techniques such as large language models and deep learning.The reform enriches educational resources and introduces innovative instructional approaches.In addition,high-quality practical teaching cases have been developed,and immersive,hands-on learning experiences have been designed based on industrial platforms and real-world applications.These initiatives aim to enhance the practical skills and innovative thinking of professional degree graduate students,fostering high-caliber talent that aligns with industry demands.A survey of 90 graduate students revealed high levels of satisfaction regarding course content,teaching methodology,and skill development.The reform has proven effective in cultivating interdisciplinary professionals with solid foundations in software engineering and AI-driven innovation.展开更多
The design of covalent organic frameworks(COFs)with strong fluorescence in both solid and solution states present a significant challenge for white-light-emitting diode(WLED)applications,primarily due to the difficult...The design of covalent organic frameworks(COFs)with strong fluorescence in both solid and solution states present a significant challenge for white-light-emitting diode(WLED)applications,primarily due to the difficulty of balancing aggregation-induced emission(AIE)and aggregation-caused quenching(ACQ).Here,we report the synthesis of a 7-fold interpenetrated three-dimensional COF(3D COF)with a pts topology,termed ZJUT-M,constructed by co-condensation of a T4-symmetric monomer with two D2h-symmetric fluorophores exhibiting distinct emission behaviors.ZJUT-M displays robust fluorescence in both solid and solution states,enabling its use in WLEDs.Mechanistic studies reveal that the dual-mode emission is driven by the synergistic integration of high-degree-of-freedom chromophores,which promote AIE emission in the solid state,and conformationally restricted fluorophores,which suppress ACQ effect in solution.These findings provide a strategic pathway for achieving multi-state emissive COFs,opening avenues for their application in advanced optoelectronic devices,including next-generation LEDs.展开更多
General practice is the cornerstone of primary healthcare,but it faces increasing challenges from workforce shortages and the rising burden of chronic diseases with complex comorbidities.The integration of medicine an...General practice is the cornerstone of primary healthcare,but it faces increasing challenges from workforce shortages and the rising burden of chronic diseases with complex comorbidities.The integration of medicine and engineering offers new opportunities to transform service delivery and enhance the sustainability of primary care systems.This narrative review aims to synthesize recent practices and emerging research on medicine–engineering integration in general practice and proposes strategic directions for building a people-centered intelligent health ecosystem.A comprehensive search was conducted across PubMed,Web of Science,IEEE Xplore,Scopus,and the Cochrane Library using relevant keywords.Sixty-four studies were included in the final review.It was summarized key applications of engineering technologies in general practice,including disease screening,clinical decision support,chronic disease management,healthcare accessibility,and professional education.Major barriers to integration are also analyzed across data infrastructure,clinical workflows,workforce capacity,and ethical and regulatory domains.Technologies such as wearable devices,artificial intelligence,telemedicine platforms,and immersive educational tools have demonstrated substantial potential to enhance diagnostic accuracy,improve chronic disease outcomes,expand access to care,and strengthen workforce training.However,persistent challenges(including data silos,algorithmic bias,limited real-world usability,interdisciplinary talent shortages,and ethical concerns)continue to hinder large-scale implementation.Moving beyond fragmented pilot initiatives towards a coordinated,ecosystem-level approach is essential for the effective integration of intelligent health technologies into general practice.A people-centered intelligent health ecosystem,supported by interdisciplinary collaboration and robust governance,can strengthen primary healthcare delivery and contribute to the achievement of universal health coverage.展开更多
Graph Neural Networks(GNNs),as a deep learning framework specifically designed for graph-structured data,have achieved deep representation learning of graph data through message passing mechanisms and have become a co...Graph Neural Networks(GNNs),as a deep learning framework specifically designed for graph-structured data,have achieved deep representation learning of graph data through message passing mechanisms and have become a core technology in the field of graph analysis.However,current reviews on GNN models are mainly focused on smaller domains,and there is a lack of systematic reviews on the classification and applications of GNN models.This review systematically synthesizes the three canonical branches of GNN,Graph Convolutional Network(GCN),Graph Attention Network(GAT),and Graph Sampling Aggregation Network(GraphSAGE),and analyzes their integration pathways from both structural and feature perspectives.Drawing on representative studies,we identify three major integration patterns:cascaded fusion,where heterogeneous modules such as Convolutional Neural Network(CNN),Long Short-Term Memory(LSTM),and GraphSAGE are sequentially combined for hierarchical feature learning;parallel fusion,where multi-branch architectures jointly encode complementary graph features;and feature-level fusion,which employs concatenation,weighted summation,or attention-based gating to adaptively merge multi-source embeddings.Through these patterns,integrated GNNs achieve enhanced expressiveness,robustness,and scalability across domains including transportation,biomedicine,and cybersecurity.展开更多
基金supported by the Innovative Research Group Project of the National Natural Science Foundation of China(Grant No.42121001).
摘要Alleviating the imbalance between urban and rural areas for regional coordinated development is an imperative response to the Sustainable Development Goal 10 of the United Nations.To track China’s urban-rural integration progress and address the uneven issues in specific fields,this study constructed a novel seven-dimension index system of urban-rural integration,comprising free population mobility,efficient land transfer,interactive economic growth,highly-linked transportation,equal public services,joint environmental governance and unimpeded informatization between urban and rural areas.Based on a comprehensive measurement framework and multi-source panel data,we uncovered the spatial-temporal evolution of urban-rural integration in China’s 367 prefecture-level administrative units from 1980 to 2022.The results demonstrated that China’s urban-rural integration steadily increased from 27.51 to 57.35 with an average annual growth rate of 3.40%.Whereas,the overall urban-rural integration was relatively inferior in 2022,at the level of moderate integration whose proportion of China’s land area was 88.08%.The urban-rural integration level in eastern region and urban agglomerations was higher than that in mid-west and non-urban agglomerations.From the perspective of seven dimensions,interactive economic growth,joint environmental governance and unimpeded informatization made an obvious improvement and reached higher integration,while free population mobility,efficient land transfer,highly-linked transportation and equal public services maintained the stage of moderate integration in 2022.In the future,China should make targeted efforts for urban-rural integration in terms of population,land use,transportation and public services,and accelerate urban-rural common prosperity in the mid-west and economically underdeveloped areas.
基金sponsored by the China Academy of Chinese Medical Sciences Youth Science and Technology Training Program(Project No.ZZ15-YQ-009).
摘要Objective:This study aimed to compare the efficacy of Traditional Chinese Medicine(TCM)Five-Element Music Therapy(FEMT)versus Western Art Music Therapy(WAMT)in reducing negative emotions and improving sleep quality among clinical nurses and to inform future psychological support strategies.Methods:This randomized controlled trial was conducted at the Department of Nursing,Xiyuan Hospital Jining Branch.Sixty nurses were randomized to receive either personalized FEMT based on TCM pattern differentiation or standardized WAMT.The intervention lasted 4 weeks.The outcomes were measured using the Hospital Anxiety and Depression Scale(HADS)and the Pittsburgh Sleep Quality Index(PSQI)at baseline,postintervention,and at 1-week follow-up.Results:Fifty-seven participants completed the study,29 in the FEMT group and 28 in the WAMT group.At the 4th week,both groups showed significant within-group improvements in HADS scores(FEMT:P=0.002;WAMT:P0.05).The WAMT group reported significantly higher scores on music acceptability and familiarity than the FEMT group(mean acceptability:9.39 vs.8.28,P=0.013;mean familiarity:9.29 vs.8.10,P<0.001).Conclusion:Both FEMT and WAMT were effective.FEMT was more effective than WAMT in reducing anxiety and depression symptoms,while WAMT was more familiar and acceptable.Music therapy is a viable intervention for improving nurses’well-being.
基金supported by the National Key R&D Program of China(2024YFB4105500)The Natural Science Foundation of Jiangsu Province(BK20240554).
摘要The coal chemical industry serves as an indispensable element in the fabric of the global energy system.However,the wastewater generated from its production processes exhibits high chemical oxygen demand,high toxicity,and poor biodegradability,posing severe challenges to the ecological sustainability of the coal chemical industry.This review systematically summarizes recent advances in treatment technologies for coal chemical wastewater(CCW)through a“pollutant molecules-technology-process integration”framework analyzed from micro-to macro-scale perspectives.It begins by delineating the complex chemical composition of CCW and identifying key toxic substances,thereby clarifying the current challenges in treatment processes and establishing a micro-scale foundation for technological development.The review then highlights solvent extraction,grounded in intermolecular interactions,as a core method for recovering phenolic compounds.This is followed by an in-depth analysis of the performance and mechanisms of biological treatment and advanced oxidation processes(AOPs)for the deep removal of refractory organic pollutants.Finally,from a macro-scale perspective,the integration of pretreatment,biological treatment,and AOPs into systematic frameworks is discussed.A thorough understanding of the molecular characteristics of pollutants is crucial for developing efficient treatment technologies.Moreover,system-level integration via process intensification and technological synergy is considered essential for achieving efficient purification and resource recovery from CCW.
基金supported by the National Natural Science Foundation of China(52263017 and 52173170)the Natural Science Foundation of Jiangxi Province(20252BAC240406,20242BAB26057)+3 种基金the Ganpo Talent Plan:Innovative High-Level Talent Program(gpyc20250072)the College Students’Innovative Entrepreneurial Training Plan Program(202513774006,CSSR24029)the Start-up Funds for Doctoral Research of Yuzhang Normal University(0001845002)funded by Key Laboratory of Key Materials and Safety Technology of Power Lithium Batteries of Jiangxi Education Institutes。
摘要Liquid crystal elastomers(LCEs)have emerged as a promising material platform for soft robotics,effectively integrating programmable molecular orientation with the inherent flexibility of elastomers.This unique combination enables significant,reversible deformations responding to external stimuli,including heat,light,electric,and magnetic fields.Due to these characteristics,LCEs serve as an ideal material system for bridging biological principles with engineered soft robotic applications,enabling the development of adaptive and multifunctional systems with enhanced biomimetic capabilities.However,the mechanisms of bioinspired motion and the effective integration of biomimetic functions in LCE-based robots remain insufficiently explored.This review systematically examines recent advances in LCE-based biomimetic soft robots,focusing on multimodal actuation strategies,including contraction,crawling,rolling,jumping,swimming,and plant-inspired motions.It highlights integrated functional enhancements achieved via innovative material compositions,structural designs,and advanced manufacturing techniques.These developments have enabled novel robotic functionalities,including programmable actuation,self-healing and recycling,color morphing and camouflage,and tunable bioinspired surface characteristics.
基金supported by Next-generation Intelligence Semiconductor R&D Program through the National Research Foundation of Korea(NRF)funded by the Korea government(MSIT)(RS-2023-00258227)by K-CHIPS(RS-202400405179,24048-15TC)funded by the Ministry of Trade,Industry&Energy(MOTIE,Korea)supported by Samsung Electronics Company Ltd.(IO20121508198-01)
摘要Ferroelectric hafnium-oxide(HfO2)films have revitalized interest in brain-inspired hardware because of their high scalability,compatibility with complementary metal-oxide-semiconductor(CMOS)processes,and suitability for three-dimensional(3D)architectures.This review first analyses the origin,deposition routes,and performance of hafnia-based devices,including ferroelectric field-effect transistor,ferroelectric tunnelling junction and ferroelectric capacitor.As artificial intelligence(AI)continues to advance,the demand for higher memory density becomes increasingly critical.This review presents hafnia-based devices and arrays in both planar and 3D architectures.In 3D structures,the review discusses the principal integration constraints—back-end-of-line(BEOL)-compatible crystallization,conformal atomic layer deposition(ALD)with controlled phase and defects in high-aspect-ratio features,and cross-layer stress together with layer-to-layer variability/disturbance,which collectively determine stackable scalability and influence energy efficiency and training stability,thereby pointing toward compact,energy-efficient,and scalable 3D neuromorphic hardware based on hafnia ferroelectrics.
基金funding this research work through the project number(PSAU/2025/01/38318).
摘要The fast-changing trajectory of energy systems toward renewables requires flexible,low-emission technologies that can buffer supply intermittently and offer large-scale energy storage systems.Moreso,hydrogen is increasingly viewed as a multi-scale flexibility resource capable of supporting deep decarbonization in renewable-dominated power systems,yet existing reviews often treat production,storage,and conversion technologies in isolation.Hydrogen offers the ability to convert,store and reconvert energy on various timescales.This review critically analyses the current literature of hydrogen production and storage in relation to power systems integration,synthesizing technical,economic and operational advances.The study synthesizes recent advances in electrolysis,particularly PEM and high-temperature SOEC systems,together with emerging PEC routes,biomass-to-hydrogen processes,and long-duration storage technologies.It considers,for storage,the performance and maturity of compressed gas,liquid hydrogen,metal and complex hydrides,liquid organic hydrogen carriers,and geological formations.Integration studies show that the value of hydrogen is enhanced as the share of renewables increases,providing seasonal storage,grid balancing,and sector coupling via power-to-hydrogen-to-power configurations.Yet technical,economic and other hurdles such as conversion losses,infrastructure requirements,and safety considerations are still holding back widespread implementation.The review also underlines the value of policy frameworks,such as country-level hydrogen strategies,carbon pricing,tax incentives,and harmonized safety standards to speed up adoption and reduce barriers to costs.The review synthesizes offer planners,operators,and policymakers a clear roadmap for aligning hydrogen deployment strategies with evolving technical requirements and high-renewable power-system conditions.By summarizing what is known and discussing opportunities for the future,this review is intended to be a roadmap towards maximizing hydrogen in reaching a flexible,resilient and carbon free power system.
基金supported by the Joint Fund Key Project of the National Natural Science Foundation of China(No.U24B20111)the National Natural Science Foundation of China(No.51839007).
摘要The rapid and accurate detection of concrete sand moisture content(MC)is crucial for ensuring concrete quality.However,existing unimodal detection methods are constrained by limited representative features and lack robustness.Multimodal operations often involve simple concatenation of features from different modalities,lacking potential interactivity among features.To address this issue,a novel robust cross-modal integration fusion model,which uses five branches to extract the features of images,near-infrared spectrum,and dielectric constant and a multilevel cross-modal integration fusion network to fuse these features,is proposed for the rapid detection of MC in concrete sand.Specifically,the multilevel cross-modal integration fusion network comprises a feature attention module,a cross-modal self-attention fusion module,and an integrated output module.The feature attention module enhances the feature representation from each modality,reducing the interference from redundant features and noise.The cross-modal self-attention fusion module employs a residual self-attention mechanism to deeply mine and fuse interactions between modalities while retaining low-level features,improving model accuracy and stability.The integrated output module is utilized to obtain more robust prediction results.The results show that the proposed model outperforms unimodal,traditional multimodal,and cross-modal methods on our concrete sand dataset,achieving excellent and robust prediction results for both machine-made sand(root mean square error ERMS=0.458,coefficient of determination R2=0.983,and residual predictive deviation DRP=7.900)and natural sand(ERMS=0.705,R2=0.984,and DRP=7.931).The detection time was within 71 s,significantly enhancing the detection frequency and efficiency,which provides a reliable solution for the rapid detection of MC in concrete sand.
基金supported by the Noncommunicable Chronic Diseases-National Science and Technology Major Project(Grant No.2023ZD0500200)the Strategic Seed Funding Collaboration Research Scheme CUHK(Grant No.3133344)+1 种基金the Strategic Impact Enhancement Fund CUHK(Grant No.3135509)the Impact Case for RAE CUHK(Grant No.3134277)。
摘要Colorectal cancer(CRC)remains a major global health burden with the gut microbiome emerging as a critical contributor to tumor initiation and progression.Advances in high-throughput sequencing have deepened our understanding of host-microbe interactions across genomic,transcriptomic,epigenomic,and metabolomic levels.This review synthesizes current knowledge on how microbial communities shape colorectal carcinogenesis,including induction of genomic instability,remodeling of host transcriptional and epigenetic landscapes,and reprogramming of metabolic pathways within the tumor microenvironment.Integrative multi-omics strategies and advanced computational tools are powerful means for dissecting these complex biological systems.However,analytical challenges,such as data compositionality,sparsity,and high dimensionality,still hinder meaningful interpretation.Emerging technologies,like long-read sequencing and bacterial single-cell spatial transcriptomics,are enhancing the resolution and accuracy of microbiota profiling.Finally,the convergence of advanced experimental models,artificial intelligence-driven computational integration,and precision microbiome medicine are highlighted as key avenues for translating microbiome insights into preventive,diagnostic,and therapeutic innovations in CRC.
基金supported by the National Natural Science Foundation of China (42271252,42230510)。
摘要County-to-district conversion(CDC) has restructured the pattern of urban-rural development and influenced the allocation of resources by local governments as well as the urbanization process.However,the impact and mechanism of the CDC on China's urban-rural integration development(URID) are not yet clear.Using panel data from 52 county-level cities,districts,and counties in Jiangsu Province of China during 2005–2021,this paper constructed an evaluation system for URID and applied the multi-period difference-in-differences(DID) model to measure the impact of the CDC on URID and identify its primary mechanisms of action.The results demonstrated that the CDC has significantly fostered URID,though with pronounced regional heterogeneity.Specifically,while the CDC facilitated URID in the southern and central Jiangsu Province—regions characterized by high socio-economic development—it exerted a less significant impact in the comparatively underdeveloped northern Jiangsu Province.Mechanistically,the implementation of the CDC promotes equal regional development,enhances rural selfdevelopment capacity,improves environmental quality and living standards,and optimizes urban-rural land allocation and transport networks.Ultimately,this study clarifies the role of the CDC in China,provides insights for achieving URID,and offers a reference for other countries pursuing coordinated urban-rural development.
基金Under the auspices of the Funding Project of Northeast Geological S&T Innovation Center of China Geological Survey(No.QCJJ2024-11)Natural Science Foundation of Liaoning Province(No.2025-BS-0873)+1 种基金Liaoning Provincial Joint Science and Technology Program(No.2024-MSLH-507)National Social Science Foundation of China(No.23ATJ006)。
摘要Promoting urban-rural integration and facilitating the bidirectional flow of urban and rural elements are core spatial objectives in the new era of China.The urban-rural fringe represents the region with the most intense interaction between urban and rural areas,serving as a key zone for breaking down barriers and promoting urban-rural integration.Based on a systematic review of representative case studies and scholarly literature,this paper synthesizes the evolving research perspectives on the urban-rural fringe,with particular attention to how data-driven approaches that integrate official statistics,remote sensing imagery,points of interest,and mobile phone signaling data have advanced the characterization of fringe features,refined identification methods,and revealed emerging developmental trends through spatial clustering and machine learning classification.It proposes an integrated analytical framework encompassing administrative boundaries,economic metabolism,social activities,material infrastructure,and the ecological environment.The paper further examines the characteristics and emerging development trends of urban-rural fringe areas and advances a set of strategic directions to support urban-rural integration and more efficient resource allocation.These include expanding analytical dimensions,enhancing data integration,refining identification criteria,elucidating mechanisms of internal and external interactions,and strengthening interdisciplinary collaboration.Collectively,these efforts offer actionable insights for optimizing public service delivery,directing infrastructure investment in transportation and utilities,delineating ecological conservation boundaries,and implementing place-based socioeconomic revitalization strategies in the urban-rural fringe regions.
基金Sanming Project of Medicine in Shenzhen(No.SZZYSM202105010)the National Key Research and Development Program Project Fund:Clinical Evaluation of Interventions for Subthreshold Depression,Insomnia,and Mild Cognitive Impairment(No.2019YFC1710103)。
摘要OBJECTIVE:To evaluate the efficacy of Traditional Chinese Medicine(TCM)psychosomatic integration therapy in treating subthreshold depression(SD).METHODS:A multicenter randomized controlled trial was conducted.Eligible participants were evaluated by physicians and randomly assigned to either the intervention or control group.The intervention group received group psychotherapy,Jue tune music therapy,and Yuleyin oral formula(郁乐饮).The control group received only group psychotherapy.The intervention period lasted 12 weeks,followed by a 12-week follow-up.The primary outcome was the Center for Epidemiologic Studies Depression Scale(CES-D)score at week 12.Secondary outcomes included dropout rate,scores of the Hamilton Anxiety Scale(HAMA)and the Hamilton Depression Rating Scale(HAMD-17)at week 12,and CES-D scores at weeks 4,8,16,20,and 24.RESULTS:A total of 505 patients were randomly allocated to the two groups,and 496 participants[77%female;(38±16)years]were included in the final analysis.The primary outcome showed no statistically significant difference in CES-D scores between the intervention and control groups at week 12(P>0.05).However,the intervention group exhibited significant reductions in CES-D scores at weeks 4,8,12,16,20,and 24 compared to baseline,and at week 24 compared to week 12(P<0.0001).The control group also showed significant reductions in CES-D scores at weeks 4 and 8 during the intervention period(P<0.0001).Although no significant differences were observed between groups at each specific time point,the intervention group showed a more consistent downward trend.Additionally,both HAMD and HAMA scores significantly decreased from baseline to week 12 in both groups(P<0.0001).CONCLUSIONS:TCM psychosomatic integration therapy,which includes group psychotherapy,Jue tune music therapy,and Yuleyin oral formula,may be effective in improving symptoms of SD,with good safety and feasibility.The complete TCM intervention demonstrated better long-term effectiveness than group psychotherapy alone.Further high-quality studies are needed to validate these findings.
基金supported by the the Major Agricultural Biological Breeding Project (2022ZD04014)the Key Special Project for the Integration of the “Two Chains” in Shaanxi Province's Livestock+2 种基金the Poultry Seed Industry “Molecular Breeding and Rapid Breeding of Dairy Cattle”(2022GD-TSLD-46-0101)the Inner Mongolia Autonomous Region Unveils Marshalled Projects (2022JBGS0021)the National Dairy Industry Technology Innovation Center Project Topics (2022-KYGG-3)。
摘要Stable transgene expression in the mammary gland is crucial for recombinant protein production in livestock,yet it is frequently hampered by transgene silencing and random integration.To address this,we profile chromatin accessibility in goat mammary epithelial cells(GMECs)using ATAC-seq and identify 15 highly accessible genomic regions.Three of these regions are confirmed to support stable transgene expression.Notably,we identify a goat-derived ubiquitous chromatin opening element(UCOE)in the SF3B1-COQ10B intergenic region,with a high GC content(65%)and CpG island enrichment.This UCOE improves hfCas12Max-mediated integration of large DNA fragments and maintains high-level expression of human lactoferrin(hLTF)in GMECs.Subsequently,we precisely integrate the UCOE-hLTF cassette into the highly accessible loci and generate a transgenic goat via somatic cell nuclear transfer,without detectable off-target effects.Our pipeline,which integrates chromatin accessibility profiling,UCOE discovery,and precision editing,demonstrates the role of CpG island-containing UCOEs in preventing transgene silencing.The study provides valuable tools for enhancing recombinant protein production,supports the breeding of dairy goats for milk with high lactoferrin content,and advances the understanding of the interactions between chromatin,regulatory elements,and transgenes in molecular breeding.
基金supported by China Scholarship Council,No.202306100073(to LY)UniBern Forschungsstiftung,No.31/2025(to RN)。
摘要Alzheimer's disease(AD),the most common cause of dementia,is a progressive neurodegenerative disease characterized by progressive cognitive decline and memory loss.Mild cognitive impairment(MCI)is the prodromal stage of AD,with a conversion rate of 10%-15%per year and 50%conversion rate longitudinally.The pathological features of AD include the aberrant accumulation of amyloid-βplaques,neurofibrillary tangles formed by hyperphosphorylated tau and synaptic dysfunction(Nussbaumer et al.,2025),all of which have cascading effects on the brain activity of AD patients.
基金funded by the National Natural Science Foundation of China General Program“Digital-Intelligent Transformation Empowers Green Innovation in High Energy Consumption and High Emission Manufacturing Industries:Mechanism Exploration,Empirical Identification,and Policy Implications”[Grant No.72473059]the National Social Science Foundation of China Project“Research on Key Areas,Statistical Measurement,and Enhancement Pathways for Developing New Quality Productive Forces in China’s Western Regions”[Grant No.24XTJ001]+2 种基金the Yunnan Provincial Philosophy and Social Science Planning Key Program“Measurement and Enhancement Pathways of Green Total Factor Productivity in Yunnan’s Manufacturing Industry under R&D Capitalization Reform”[Grant No.ZD202305]the Ministry of Education Humanities and Social Sciences Planning Fund Project“Mechanisms and Policy Research on Digital-Intelligence Empowerment for Green Transformation in the Manufacturing Industry”[Grant No.23YJA790026]the Yunnan Provincial Department of Education Scientific Research Fund Project“Research on the Implementation Path of Transformation of Scientific and Technological Achievements in Strategic Emerging Industries from the Perspective of Four-Chain Integration”[Grant No.2026Y0272].
摘要Synergistic pollution reduction and carbon mitigation(SPRCM)are inherent requirements for high-quality development.This study explores the internal mechanisms through which digital-green integration(DGI)policies facilitate SPRCM from the perspective of deep integration between“digitalization”and“greenization”.It aims to provide policy recommendations for coordinating the implementation of the“Digital China”and“Beautiful China”strategies.Using panel data from 280 prefecture-level cities(2010-2022)and treating the overlap between the Big Data Comprehensive Pilot Zone policy and the Low-Carbon City Pilot policy as a quasi-natural experiment for DGI,this study applies a double machine learning model to investigate its impact mechanisms and multidimensional policy effects.The findings indicate that,first,DGI enhances pollution emission efficiency and carbon emission efficiency,generating significant synergistic effects.Second,mechanism analysis based on whole-process production control reveals that during the source prevention stage,DGI drives SPRCM by optimizing the energy structure.At the process control stage,it enhances synchronized SPRCM through improved production efficiency.At the end-of-pipe treatment stage,advancements in green end-of-pipe technologies emerge as the dominant force propelling synergistic effects.Third,heterogeneity analysis reveals that the pollution reduction and carbon mitigation effects of DGI are more pronounced in resource-based cities,innovative cities,and cities within the Yangtze River Economic Belt than in non resource-based cities,non-innovative cities,and cities outside this strategic economic region.Consequently,a multipronged policy mix should be implemented to amplify the catalytic role of digital-green policy integration in driving pollution and carbon reduction.Whole-process production controls must be strengthened to streamline mitigation pathways,and region-specific strategies for DGI should be tailored based on local conditions with dynamic guidance.
基金Youth project under the National Social Science Foundation of China(15CJY054)key project in Philosophy and Social Sciences funded by the Chongqing Municipal Education Commission(22SKGH091)。
摘要This study aims to promote the optimization and upgrading of the economic structure in rural areas of China by focusing on the coupling coordination mechanism between digital economy–agriculture integration and rural revitalization.By examining panel data from 30 Chinese provinces,autonomous regions,and municipalities between 2011 and 2022,the research constructs a weight-based evaluation system that integrates subjective and objective methods and a coupling coordination model to reveal its dynamic evolution patterns.Key findings indicate that digital economy–agriculture integration and rural revitalization achieve cross-coupling through critical activities.The impact of digital-agriculture integration on advancing rural revitalization lags by 2–3 years.Although the coupling development degree between the two systems continues to improve,it remains at the stage of primary coordination.Regional disparities are significant,showing a gradient pattern of“high degree of coupling development in the east and low degree of coupling development in the west.”
基金National Natural Science Foundation of China(No.52375236)Fundamental Research Funds for the Central Universities of China(No.23D110316)。
摘要In reliability analyses,the absence of a priori information on the most probable point of failure(MPP)may result in overlooking critical points,thereby leading to biased assessment outcomes.Moreover,second-order reliability methods exhibit limited accuracy in highly nonlinear scenarios.To overcome these challenges,a novel reliability analysis strategy based on a multimodal differential evolution algorithm and a hypersphere integration method is proposed.Initially,the penalty function method is employed to reformulate the MPP search problem as a conditionally constrained optimization task.Subsequently,a differential evolution algorithm incorporating a population delineation strategy is utilized to identify all MPPs.Finally,a paraboloid equation is constructed based on the curvature of the limit-state function at the MPPs,and the failure probability of the structure is calculated by using the hypersphere integration method.The localization effectiveness of the MPPs is compared through multiple numerical cases and two engineering examples,with accuracy comparisons of failure probabilities against the first-order reliability method(FORM)and the secondorder reliability method(SORM).The results indicate that the method effectively identifies existing MPPs and achieves higher solution precision.
基金supported by Project of Higher Education Teaching Reform Research in Heilongjiang Province(Graduate Education)(Grant No.SJGYY2024030).
摘要This paper investigates the teaching reform of the Program Comprehension and Analysis course in the context of industry-education integration and AI empowerment.To align with the evolving needs of the software industry,the course content has been updated to incorporate AI techniques such as large language models and deep learning.The reform enriches educational resources and introduces innovative instructional approaches.In addition,high-quality practical teaching cases have been developed,and immersive,hands-on learning experiences have been designed based on industrial platforms and real-world applications.These initiatives aim to enhance the practical skills and innovative thinking of professional degree graduate students,fostering high-caliber talent that aligns with industry demands.A survey of 90 graduate students revealed high levels of satisfaction regarding course content,teaching methodology,and skill development.The reform has proven effective in cultivating interdisciplinary professionals with solid foundations in software engineering and AI-driven innovation.
基金supported by the National Natural Science Foundation of China(Nos.22375179,52172160,22105202,22275185,223B2117)the Fundamental Research Funds for the Provincial Universities of Zhejiang(No.RF-C2022005)。
摘要The design of covalent organic frameworks(COFs)with strong fluorescence in both solid and solution states present a significant challenge for white-light-emitting diode(WLED)applications,primarily due to the difficulty of balancing aggregation-induced emission(AIE)and aggregation-caused quenching(ACQ).Here,we report the synthesis of a 7-fold interpenetrated three-dimensional COF(3D COF)with a pts topology,termed ZJUT-M,constructed by co-condensation of a T4-symmetric monomer with two D2h-symmetric fluorophores exhibiting distinct emission behaviors.ZJUT-M displays robust fluorescence in both solid and solution states,enabling its use in WLEDs.Mechanistic studies reveal that the dual-mode emission is driven by the synergistic integration of high-degree-of-freedom chromophores,which promote AIE emission in the solid state,and conformationally restricted fluorophores,which suppress ACQ effect in solution.These findings provide a strategic pathway for achieving multi-state emissive COFs,opening avenues for their application in advanced optoelectronic devices,including next-generation LEDs.
基金supported by the Key Supported Discipline of Shanghai Health System(No.2023ZDFC0403)the Teaching Project of Science and Technology Commission of Changning District,Shanghai(No.CNKW2024J01)the Postgraduate Education Project of Shanghai Jiao Tong University School of Medicine(No.BYH20240102)。
摘要General practice is the cornerstone of primary healthcare,but it faces increasing challenges from workforce shortages and the rising burden of chronic diseases with complex comorbidities.The integration of medicine and engineering offers new opportunities to transform service delivery and enhance the sustainability of primary care systems.This narrative review aims to synthesize recent practices and emerging research on medicine–engineering integration in general practice and proposes strategic directions for building a people-centered intelligent health ecosystem.A comprehensive search was conducted across PubMed,Web of Science,IEEE Xplore,Scopus,and the Cochrane Library using relevant keywords.Sixty-four studies were included in the final review.It was summarized key applications of engineering technologies in general practice,including disease screening,clinical decision support,chronic disease management,healthcare accessibility,and professional education.Major barriers to integration are also analyzed across data infrastructure,clinical workflows,workforce capacity,and ethical and regulatory domains.Technologies such as wearable devices,artificial intelligence,telemedicine platforms,and immersive educational tools have demonstrated substantial potential to enhance diagnostic accuracy,improve chronic disease outcomes,expand access to care,and strengthen workforce training.However,persistent challenges(including data silos,algorithmic bias,limited real-world usability,interdisciplinary talent shortages,and ethical concerns)continue to hinder large-scale implementation.Moving beyond fragmented pilot initiatives towards a coordinated,ecosystem-level approach is essential for the effective integration of intelligent health technologies into general practice.A people-centered intelligent health ecosystem,supported by interdisciplinary collaboration and robust governance,can strengthen primary healthcare delivery and contribute to the achievement of universal health coverage.
基金funded by Guangzhou Huashang University(2024HSZD01,HS2023JYSZH01).
摘要Graph Neural Networks(GNNs),as a deep learning framework specifically designed for graph-structured data,have achieved deep representation learning of graph data through message passing mechanisms and have become a core technology in the field of graph analysis.However,current reviews on GNN models are mainly focused on smaller domains,and there is a lack of systematic reviews on the classification and applications of GNN models.This review systematically synthesizes the three canonical branches of GNN,Graph Convolutional Network(GCN),Graph Attention Network(GAT),and Graph Sampling Aggregation Network(GraphSAGE),and analyzes their integration pathways from both structural and feature perspectives.Drawing on representative studies,we identify three major integration patterns:cascaded fusion,where heterogeneous modules such as Convolutional Neural Network(CNN),Long Short-Term Memory(LSTM),and GraphSAGE are sequentially combined for hierarchical feature learning;parallel fusion,where multi-branch architectures jointly encode complementary graph features;and feature-level fusion,which employs concatenation,weighted summation,or attention-based gating to adaptively merge multi-source embeddings.Through these patterns,integrated GNNs achieve enhanced expressiveness,robustness,and scalability across domains including transportation,biomedicine,and cybersecurity.