In light of degradation of particle filtering and robust weakness in the utilization of single feature tracking,this paper presents a kernel particle filtering tracking method based on multi-feature integration.In thi...In light of degradation of particle filtering and robust weakness in the utilization of single feature tracking,this paper presents a kernel particle filtering tracking method based on multi-feature integration.In this paper,a new weight upgrading method is given out during kernel particle filtering at first,and then robust tracking is realized by integrating color and texture features under the framework of kernel particle filtering.Space histogram and integral histogram is adopted to calculate color and texture features respectively.These two calculation methods effectively overcome their own defectiveness,and meanwhile,improve the real timing for particle filtering.This algorithm has also improved sampling effectiveness,resolved redundant calculation for particle filtering and degradation of particles.Finally,the experiment for target tracking is realized by using the method under complicated background and shelter.Experiment results show that the method can reliably and accurately track target and deal with target sheltering situation properly.展开更多
Objective To construct and validate an artificial intelligence diagnostic system based on multi-feature integration for diagnosing gastric whitish neoplastic lesions under white-light endoscopy.Methods Gastroscopic im...Objective To construct and validate an artificial intelligence diagnostic system based on multi-feature integration for diagnosing gastric whitish neoplastic lesions under white-light endoscopy.Methods Gastroscopic images from Renmin Hospital of Wuhan University and the Seventh Medical Center of Chinese PLA General Hospital were collected from November 2012 to July 2021.A total of 823 images of gastric whitish lesions from 267 patients were finally selected.展开更多
Digital watermarking technology plays an important role in detecting malicious tampering and protecting image copyright.However,in practical applications,this technology faces various problems such as severe image dis...Digital watermarking technology plays an important role in detecting malicious tampering and protecting image copyright.However,in practical applications,this technology faces various problems such as severe image distortion,inaccurate localization of the tampered regions,and difficulty in recovering content.Given these shortcomings,a fragile image watermarking algorithm for tampering blind-detection and content self-recovery is proposed.The multi-feature watermarking authentication code(AC)is constructed using texture feature of local binary patterns(LBP),direct coefficient of discrete cosine transform(DCT)and contrast feature of gray level co-occurrence matrix(GLCM)for detecting the tampered region,and the recovery code(RC)is designed according to the average grayscale value of pixels in image blocks for recovering the tampered content.Optimal pixel adjustment process(OPAP)and least significant bit(LSB)algorithms are used to embed the recovery code and authentication code into the image in a staggered manner.When detecting the integrity of the image,the authentication code comparison method and threshold judgment method are used to perform two rounds of tampering detection on the image and blindly recover the tampered content.Experimental results show that this algorithm has good transparency,strong and blind detection,and self-recovery performance against four types of malicious attacks and some conventional signal processing operations.When resisting copy-paste,text addition,cropping and vector quantization under the tampering rate(TR)10%,the average tampering detection rate is up to 94.09%,and the peak signal-to-noise ratio(PSNR)of the watermarked image and the recovered image are both greater than 41.47 and 40.31 dB,which demonstrates its excellent advantages compared with other related algorithms in recent years.展开更多
Ningxia is an ethnic gathering area boasting abundant tourism and cultural resources.Developing the cause of tourism and culture is an important way to encourage all ethnic groups to respect differences,embrace divers...Ningxia is an ethnic gathering area boasting abundant tourism and cultural resources.Developing the cause of tourism and culture is an important way to encourage all ethnic groups to respect differences,embrace diversity,and demonstrate their interactions,exchanges,and integration in tourism activities.As an important preserve of the distinctive cultures of the Chinese nation and a prominent world tourist destination,Ningxia should strive to foster and consolidate the sense of a community with a shared future for the Chinese nation in developing its tourism and culture under the new historical conditions.It is imperative to advance the prosperity and development of tourism and culture in boosting ethnic interactions,exchanges,and integration through the formulation of tourism and cultural policies and plans,as well as the development and design of tourism and cultural projects.展开更多
This paper undertakes a systematic combing of the development of research on integrating Chinese culture into foreign language education in China from the 1980s to 2025,dividing it into three stages:cultural attachmen...This paper undertakes a systematic combing of the development of research on integrating Chinese culture into foreign language education in China from the 1980s to 2025,dividing it into three stages:cultural attachment,cultural compensation,and cultural symbiosis,and reveals the logical shift of the research from the dominance of target language culture to the construction of the subjectivity of Chinese culture.Through quantitative and qualitative analysis of 435 CSSCI papers,three core themes are extracted:what to integrate,why to integrate,and how to integrate.This paper critically analyzes three pairs of contradictions:the imbalance between instrumentality and humanism,the separation of national narrative and individual expression,and the disconnection between traditional inheritance and modern transformation.It is proposed that future research should reconstruct the educational logic based on the Chinese context,integrate the national and individual dimensions,and build a dialogue mechanism between tradition and modernity,so as to provide theoretical and practical reference for the construction of a foreign language education system with Chinese characteristics.展开更多
Multi-organ-on-a-chip(MOOC)technology represents a pivotal direction in the organ-on-a-chip field,seeking to emulate the complex interactions of multiple human organs in vitro through microfluidic systems.This technol...Multi-organ-on-a-chip(MOOC)technology represents a pivotal direction in the organ-on-a-chip field,seeking to emulate the complex interactions of multiple human organs in vitro through microfluidic systems.This technology overcomes the limitations of traditional single-organ models,providing a novel platform for investigating complex disease mechanisms and evaluating drug efficacy and toxicity.Although it demonstrates broad application prospects,its development still faces critical bottlenecks,including inadequate physiological coupling between organs,short functional maintenance durations,and limited real-time monitoring capabilities.Contemporary research is advancing along three key directions,including functional coupling,sensor integration,and full-process automation systems,to propel the technology toward enhanced levels of physiological relevance and predictive accuracy.展开更多
Objective:To analyze the clinical effect of sensory integration training combined with cognitive training in the rehabilitation treatment of children with mental retardation.Methods:A total of 120 children with mental...Objective:To analyze the clinical effect of sensory integration training combined with cognitive training in the rehabilitation treatment of children with mental retardation.Methods:A total of 120 children with mental retardation who received rehabilitation intervention in our hospital from January 2022 to December 2025 were selected and divided into a control group and an experimental group,with 60 children in each group.The control group adopted a conventional rehabilitation training program;the experimental group adopted a combined sensory integration training and cognitive training program.The sensory integration ability,cognitive function,and daily living skills of children in the two groups were compared.Results:The sensory integration ability score of the experimental group(85.3±6.2)was significantly higher than that of the control group(72.1±7.5)(p<0.05);the cognitive function score(88.7±5.8)was significantly improved compared with that of the control group(76.4±6.9)(p<0.05);the daily living skills score(90.2±4.7)was significantly higher than that of the control group(80.5±5.3)(p<0.05).The social interaction ability of the experimental group reached 92.5%,which was significantly higher than that of the control group(81.3%)(p<0.05).Conclusion:Sensory integration training combined with cognitive training demonstrates favorable outcomes in the rehabilitation treatment of children with mental retardation,exhibiting a notable neurofunctional remodeling effect.It can optimize the multidimensional rehabilitation process,effectively enhance the comprehensive developmental potential of children,and hold significant clinical application value.展开更多
China is carving out a distinctive development path which features urban-rural integration.This approach has not only yielded tangible results domestically but also drawn the attention of other countries.
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
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
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
Against the backdrop of integrated development between technical education and higher vocational education,the teaching of Chinese Medicine Processing Technology courses faces new opportunities and challenges.This pap...Against the backdrop of integrated development between technical education and higher vocational education,the teaching of Chinese Medicine Processing Technology courses faces new opportunities and challenges.This paper analyzes the existing problems in the current teaching of Chinese Medicine Processing Technology courses,discusses the necessity of reforming the teaching model under the context of integration,and proposes the construction of a"Dual-Capability Progression,Six-Dimensional Empowerment"teaching model.The aim is to enhance the teaching quality of Chinese Medicine Processing Technology courses and cultivate high-quality skilled talents in Chinese medicine processing who can meet industry demands.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
Urinary tract infections(UTIs)are among the most prevalent pediatric bacterial infections,and undertreated episodes may lead to renal scarring,hypertension,or chronic kidney disease.Multidrug-resistant(MDR)Enterobacte...Urinary tract infections(UTIs)are among the most prevalent pediatric bacterial infections,and undertreated episodes may lead to renal scarring,hypertension,or chronic kidney disease.Multidrug-resistant(MDR)Enterobacterales have been increasingly reported in children,with higher rates in Asian and Middle Eastern settings than in high-income countries[1,2].展开更多
In global navigation satellite system denial environment,cross-view geo-localization based on image retrieval presents an exceedingly critical visual localization solution for Unmanned Aerial Vehicle(UAV)systems.The e...In global navigation satellite system denial environment,cross-view geo-localization based on image retrieval presents an exceedingly critical visual localization solution for Unmanned Aerial Vehicle(UAV)systems.The essence of cross-view geo-localization resides in matching images containing the same geographical targets from disparate platforms,such as UAV-view and satellite-view images.However,images of the same geographical targets may suffer from occlusions and geometric distortions due to variations in the capturing platform,view,and timing.The existing methods predominantly extract features by segmenting feature maps,which overlook the holistic semantic distribution and structural information of objects,resulting in loss of image information.To address these challenges,dilated neighborhood attention Transformer is employed as the feature extraction backbone,and Multi-feature representations based on Multi-scale Hierarchical Contextual Aggregation(MMHCA)is proposed.In the proposed MMHCA method,the multiscale hierarchical contextual aggregation method is utilized to extract contextual information from local to global across various granularity levels,establishing feature associations of contextual information with global and local information in the image.Subsequently,the multi-feature representations method is utilized to obtain rich discriminative feature information,bolstering the robustness of model in scenarios characterized by positional shifts,varying distances,and scale ambiguities.Comprehensive experiments conducted on the extensively utilized University-1652 and SUES-200 benchmarks indicate that the MMHCA method surpasses the existing techniques.showing outstanding results in UAV localization and navigation.展开更多
Complex network models are frequently employed for simulating and studyingdiverse real-world complex systems.Among these models,scale-free networks typically exhibit greater fragility to malicious attacks.Consequently...Complex network models are frequently employed for simulating and studyingdiverse real-world complex systems.Among these models,scale-free networks typically exhibit greater fragility to malicious attacks.Consequently,enhancing the robustness of scale-free networks has become a pressing issue.To address this problem,this paper proposes a Multi-Granularity Integration Algorithm(MGIA),which aims to improve the robustness of scale-free networks while keeping the initial degree of each node unchanged,ensuring network connectivity and avoiding the generation of multiple edges.The algorithm generates a multi-granularity structure from the initial network to be optimized,then uses different optimization strategies to optimize the networks at various granular layers in this structure,and finally realizes the information exchange between different granular layers,thereby further enhancing the optimization effect.We propose new network refresh,crossover,and mutation operators to ensure that the optimized network satisfies the given constraints.Meanwhile,we propose new network similarity and network dissimilarity evaluation metrics to improve the effectiveness of the optimization operators in the algorithm.In the experiments,the MGIA enhances the robustness of the scale-free network by 67.6%.This improvement is approximately 17.2%higher than the optimization effects achieved by eight currently existing complex network robustness optimization algorithms.展开更多
The rapid growth of artificial intelligence has accelerated data generation,which increasingly exposes the limitations faced by traditional computational architectures,particularly in terms of energy consumption and d...The rapid growth of artificial intelligence has accelerated data generation,which increasingly exposes the limitations faced by traditional computational architectures,particularly in terms of energy consumption and data latency.In contrast,data-centric computing that integrates processing and storage has the potential of reducing latency and energy usage.Organic optoelectronic synaptic transistors have emerged as one type of promising devices to implement the data-centric com-puting paradigm owing to their superiority of flexibility,low cost,and large-area fabrication.However,sophisticated functions including vector-matrix multiplication that a single device can achieve are limited.Thus,the fabrication and utilization of organic optoelectronic synaptic transistor arrays(OOSTAs)are imperative.Here,we summarize the recent advances in OOSTAs.Various strategies for manufacturing OOSTAs are introduced,including coating and casting,physical vapor deposition,printing,and photolithography.Furthermore,innovative applications of the OOSTA system integration are discussed,including neuromor-phic visual systems and neuromorphic computing systems.At last,challenges and future perspectives of utilizing OOSTAs in real-world applications are discussed.展开更多
This study proposes a learner profile framework based on multi-feature fusion,aiming to enhance the precision of personalized learning recommendations by integrating learners’static attributes(e.g.,demographic data a...This study proposes a learner profile framework based on multi-feature fusion,aiming to enhance the precision of personalized learning recommendations by integrating learners’static attributes(e.g.,demographic data and historical academic performance)with dynamic behavioral patterns(e.g.,real-time interactions and evolving interests over time).The research employs Term Frequency-Inverse Document Frequency(TF-IDF)for semantic feature extraction,integrates the Analytic Hierarchy Process(AHP)for feature weighting,and introduces a time decay function inspired by Newton’s law of cooling to dynamically model changes in learners’interests.Empirical results demonstrate that this framework effectively captures the dynamic evolution of learners’behaviors and provides context-aware learning resource recommendations.The study introduces a novel paradigm for learner modeling in educational technology,combining methodological innovation with a scalable technical architecture,thereby laying a foundation for the development of adaptive learning systems.展开更多
基金Sponsored by Natural Science Foundation of Heilongjiang Province of China(Grant No.QC2001C060)the Science and Technology Research Projectsin Office of Education of Heilongjiang province(Grant No.11531307)
文摘In light of degradation of particle filtering and robust weakness in the utilization of single feature tracking,this paper presents a kernel particle filtering tracking method based on multi-feature integration.In this paper,a new weight upgrading method is given out during kernel particle filtering at first,and then robust tracking is realized by integrating color and texture features under the framework of kernel particle filtering.Space histogram and integral histogram is adopted to calculate color and texture features respectively.These two calculation methods effectively overcome their own defectiveness,and meanwhile,improve the real timing for particle filtering.This algorithm has also improved sampling effectiveness,resolved redundant calculation for particle filtering and degradation of particles.Finally,the experiment for target tracking is realized by using the method under complicated background and shelter.Experiment results show that the method can reliably and accurately track target and deal with target sheltering situation properly.
文摘Objective To construct and validate an artificial intelligence diagnostic system based on multi-feature integration for diagnosing gastric whitish neoplastic lesions under white-light endoscopy.Methods Gastroscopic images from Renmin Hospital of Wuhan University and the Seventh Medical Center of Chinese PLA General Hospital were collected from November 2012 to July 2021.A total of 823 images of gastric whitish lesions from 267 patients were finally selected.
基金supported by Postgraduate Research&Practice Innovation Program of Jiangsu Province,China(Grant No.SJCX24_1332)Jiangsu Province Education Science Planning Project in 2024(Grant No.B-b/2024/01/122)High-Level Talent Scientific Research Foundation of Jinling Institute of Technology,China(Grant No.jit-b-201918).
文摘Digital watermarking technology plays an important role in detecting malicious tampering and protecting image copyright.However,in practical applications,this technology faces various problems such as severe image distortion,inaccurate localization of the tampered regions,and difficulty in recovering content.Given these shortcomings,a fragile image watermarking algorithm for tampering blind-detection and content self-recovery is proposed.The multi-feature watermarking authentication code(AC)is constructed using texture feature of local binary patterns(LBP),direct coefficient of discrete cosine transform(DCT)and contrast feature of gray level co-occurrence matrix(GLCM)for detecting the tampered region,and the recovery code(RC)is designed according to the average grayscale value of pixels in image blocks for recovering the tampered content.Optimal pixel adjustment process(OPAP)and least significant bit(LSB)algorithms are used to embed the recovery code and authentication code into the image in a staggered manner.When detecting the integrity of the image,the authentication code comparison method and threshold judgment method are used to perform two rounds of tampering detection on the image and blindly recover the tampered content.Experimental results show that this algorithm has good transparency,strong and blind detection,and self-recovery performance against four types of malicious attacks and some conventional signal processing operations.When resisting copy-paste,text addition,cropping and vector quantization under the tampering rate(TR)10%,the average tampering detection rate is up to 94.09%,and the peak signal-to-noise ratio(PSNR)of the watermarked image and the recovered image are both greater than 41.47 and 40.31 dB,which demonstrates its excellent advantages compared with other related algorithms in recent years.
文摘Ningxia is an ethnic gathering area boasting abundant tourism and cultural resources.Developing the cause of tourism and culture is an important way to encourage all ethnic groups to respect differences,embrace diversity,and demonstrate their interactions,exchanges,and integration in tourism activities.As an important preserve of the distinctive cultures of the Chinese nation and a prominent world tourist destination,Ningxia should strive to foster and consolidate the sense of a community with a shared future for the Chinese nation in developing its tourism and culture under the new historical conditions.It is imperative to advance the prosperity and development of tourism and culture in boosting ethnic interactions,exchanges,and integration through the formulation of tourism and cultural policies and plans,as well as the development and design of tourism and cultural projects.
基金“A Study on the Value and Path of Integrating Excellent Traditional Chinese Culture Into Intercultural Communication Courses”(ZD2024)a project by the Beijing Higher Education Association,as well as“A Study on the Path of Empowering the Integration of Excellent Traditional Chinese Culture Into Intercultural Communication Courses With Generative AI”(2024),an institutional project of Beijing International Studies University.
文摘This paper undertakes a systematic combing of the development of research on integrating Chinese culture into foreign language education in China from the 1980s to 2025,dividing it into three stages:cultural attachment,cultural compensation,and cultural symbiosis,and reveals the logical shift of the research from the dominance of target language culture to the construction of the subjectivity of Chinese culture.Through quantitative and qualitative analysis of 435 CSSCI papers,three core themes are extracted:what to integrate,why to integrate,and how to integrate.This paper critically analyzes three pairs of contradictions:the imbalance between instrumentality and humanism,the separation of national narrative and individual expression,and the disconnection between traditional inheritance and modern transformation.It is proposed that future research should reconstruct the educational logic based on the Chinese context,integrate the national and individual dimensions,and build a dialogue mechanism between tradition and modernity,so as to provide theoretical and practical reference for the construction of a foreign language education system with Chinese characteristics.
基金supported by the Shenzhen Medical Research Fund(Grant No.A2303049)Guangdong Basic and Applied Basic Research(Grant No.2023A1515010647)+1 种基金National Natural Science Foundation of China(Grant No.22004135)Shenzhen Science and Technology Program(Grant No.RCBS20210706092409020,GXWD20201231165807008,20200824162253002).
文摘Multi-organ-on-a-chip(MOOC)technology represents a pivotal direction in the organ-on-a-chip field,seeking to emulate the complex interactions of multiple human organs in vitro through microfluidic systems.This technology overcomes the limitations of traditional single-organ models,providing a novel platform for investigating complex disease mechanisms and evaluating drug efficacy and toxicity.Although it demonstrates broad application prospects,its development still faces critical bottlenecks,including inadequate physiological coupling between organs,short functional maintenance durations,and limited real-time monitoring capabilities.Contemporary research is advancing along three key directions,including functional coupling,sensor integration,and full-process automation systems,to propel the technology toward enhanced levels of physiological relevance and predictive accuracy.
基金Baoding Science and Technology Plan Project(Project No.:2541ZF307)。
文摘Objective:To analyze the clinical effect of sensory integration training combined with cognitive training in the rehabilitation treatment of children with mental retardation.Methods:A total of 120 children with mental retardation who received rehabilitation intervention in our hospital from January 2022 to December 2025 were selected and divided into a control group and an experimental group,with 60 children in each group.The control group adopted a conventional rehabilitation training program;the experimental group adopted a combined sensory integration training and cognitive training program.The sensory integration ability,cognitive function,and daily living skills of children in the two groups were compared.Results:The sensory integration ability score of the experimental group(85.3±6.2)was significantly higher than that of the control group(72.1±7.5)(p<0.05);the cognitive function score(88.7±5.8)was significantly improved compared with that of the control group(76.4±6.9)(p<0.05);the daily living skills score(90.2±4.7)was significantly higher than that of the control group(80.5±5.3)(p<0.05).The social interaction ability of the experimental group reached 92.5%,which was significantly higher than that of the control group(81.3%)(p<0.05).Conclusion:Sensory integration training combined with cognitive training demonstrates favorable outcomes in the rehabilitation treatment of children with mental retardation,exhibiting a notable neurofunctional remodeling effect.It can optimize the multidimensional rehabilitation process,effectively enhance the comprehensive developmental potential of children,and hold significant clinical application value.
文摘China is carving out a distinctive development path which features urban-rural integration.This approach has not only yielded tangible results domestically but also drawn the attention of other countries.
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)。
文摘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)。
文摘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National Natural Science Foundation of China(No.52375236)Fundamental Research Funds for the Central Universities of China(No.23D110316)。
文摘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 Scientific Research Fund Project of Yunnan Provincial Department of Education(2025J1950).
文摘Against the backdrop of integrated development between technical education and higher vocational education,the teaching of Chinese Medicine Processing Technology courses faces new opportunities and challenges.This paper analyzes the existing problems in the current teaching of Chinese Medicine Processing Technology courses,discusses the necessity of reforming the teaching model under the context of integration,and proposes the construction of a"Dual-Capability Progression,Six-Dimensional Empowerment"teaching model.The aim is to enhance the teaching quality of Chinese Medicine Processing Technology courses and cultivate high-quality skilled talents in Chinese medicine processing who can meet industry demands.
基金funded by Guangzhou Huashang University(2024HSZD01,HS2023JYSZH01).
文摘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.
文摘Urinary tract infections(UTIs)are among the most prevalent pediatric bacterial infections,and undertreated episodes may lead to renal scarring,hypertension,or chronic kidney disease.Multidrug-resistant(MDR)Enterobacterales have been increasingly reported in children,with higher rates in Asian and Middle Eastern settings than in high-income countries[1,2].
基金supported by the National Natural Science Foundation of China(Nos.12072027,62103052,61603346 and 62103379)the Henan Key Laboratory of General Aviation Technology,China(No.ZHKF-230201)+3 种基金the Funding for the Open Research Project of the Rotor Aerodynamics Key Laboratory,China(No.RAL20200101)the Key Research and Development Program of Henan Province,China(Nos.241111222000 and 241111222900)the Key Science and Technology Program of Henan Province,China(No.232102220067)the Scholarship Funding from the China Scholarship Council(No.202206030079).
文摘In global navigation satellite system denial environment,cross-view geo-localization based on image retrieval presents an exceedingly critical visual localization solution for Unmanned Aerial Vehicle(UAV)systems.The essence of cross-view geo-localization resides in matching images containing the same geographical targets from disparate platforms,such as UAV-view and satellite-view images.However,images of the same geographical targets may suffer from occlusions and geometric distortions due to variations in the capturing platform,view,and timing.The existing methods predominantly extract features by segmenting feature maps,which overlook the holistic semantic distribution and structural information of objects,resulting in loss of image information.To address these challenges,dilated neighborhood attention Transformer is employed as the feature extraction backbone,and Multi-feature representations based on Multi-scale Hierarchical Contextual Aggregation(MMHCA)is proposed.In the proposed MMHCA method,the multiscale hierarchical contextual aggregation method is utilized to extract contextual information from local to global across various granularity levels,establishing feature associations of contextual information with global and local information in the image.Subsequently,the multi-feature representations method is utilized to obtain rich discriminative feature information,bolstering the robustness of model in scenarios characterized by positional shifts,varying distances,and scale ambiguities.Comprehensive experiments conducted on the extensively utilized University-1652 and SUES-200 benchmarks indicate that the MMHCA method surpasses the existing techniques.showing outstanding results in UAV localization and navigation.
基金National Natural Science Foundation of China(11971211,12171388).
文摘Complex network models are frequently employed for simulating and studyingdiverse real-world complex systems.Among these models,scale-free networks typically exhibit greater fragility to malicious attacks.Consequently,enhancing the robustness of scale-free networks has become a pressing issue.To address this problem,this paper proposes a Multi-Granularity Integration Algorithm(MGIA),which aims to improve the robustness of scale-free networks while keeping the initial degree of each node unchanged,ensuring network connectivity and avoiding the generation of multiple edges.The algorithm generates a multi-granularity structure from the initial network to be optimized,then uses different optimization strategies to optimize the networks at various granular layers in this structure,and finally realizes the information exchange between different granular layers,thereby further enhancing the optimization effect.We propose new network refresh,crossover,and mutation operators to ensure that the optimized network satisfies the given constraints.Meanwhile,we propose new network similarity and network dissimilarity evaluation metrics to improve the effectiveness of the optimization operators in the algorithm.In the experiments,the MGIA enhances the robustness of the scale-free network by 67.6%.This improvement is approximately 17.2%higher than the optimization effects achieved by eight currently existing complex network robustness optimization algorithms.
基金supported by the National Key Research and Development Program of China(2021YFA1101303)the National Natural Science Foundation of China(62374115)the Innovation Program of Shanghai Municipal Education Commission(2021-01-07-00-07-E00096).
文摘The rapid growth of artificial intelligence has accelerated data generation,which increasingly exposes the limitations faced by traditional computational architectures,particularly in terms of energy consumption and data latency.In contrast,data-centric computing that integrates processing and storage has the potential of reducing latency and energy usage.Organic optoelectronic synaptic transistors have emerged as one type of promising devices to implement the data-centric com-puting paradigm owing to their superiority of flexibility,low cost,and large-area fabrication.However,sophisticated functions including vector-matrix multiplication that a single device can achieve are limited.Thus,the fabrication and utilization of organic optoelectronic synaptic transistor arrays(OOSTAs)are imperative.Here,we summarize the recent advances in OOSTAs.Various strategies for manufacturing OOSTAs are introduced,including coating and casting,physical vapor deposition,printing,and photolithography.Furthermore,innovative applications of the OOSTA system integration are discussed,including neuromor-phic visual systems and neuromorphic computing systems.At last,challenges and future perspectives of utilizing OOSTAs in real-world applications are discussed.
基金This work is supported by the Ministry of Education of Humanities and Social Science projects in China(No.20YJCZH124)Guangdong Province Education and Teaching Reform Project No.640:Research on the Teaching Practice and Application of Online Peer Assessment Methods in the Context of Artificial Intelligence.
文摘This study proposes a learner profile framework based on multi-feature fusion,aiming to enhance the precision of personalized learning recommendations by integrating learners’static attributes(e.g.,demographic data and historical academic performance)with dynamic behavioral patterns(e.g.,real-time interactions and evolving interests over time).The research employs Term Frequency-Inverse Document Frequency(TF-IDF)for semantic feature extraction,integrates the Analytic Hierarchy Process(AHP)for feature weighting,and introduces a time decay function inspired by Newton’s law of cooling to dynamically model changes in learners’interests.Empirical results demonstrate that this framework effectively captures the dynamic evolution of learners’behaviors and provides context-aware learning resource recommendations.The study introduces a novel paradigm for learner modeling in educational technology,combining methodological innovation with a scalable technical architecture,thereby laying a foundation for the development of adaptive learning systems.
