In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and cha...In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.展开更多
Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(...Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(2025)].In relation to seasonal forecasting and climate projection in the East Asian summer monsoon season,proper simulation of the seasonal migration of rain bands by models is a challenging and limiting factor[section 7.1 in Wang et al.(2025)].展开更多
Customer churn is the rate at which customers discontinue doing business with a company over a given time period.It is an essential measure for businesses to monitor high churn rates,as they often indicate underlying ...Customer churn is the rate at which customers discontinue doing business with a company over a given time period.It is an essential measure for businesses to monitor high churn rates,as they often indicate underlying issues with services,products,or customer experience,resulting in considerable income loss.Prediction of customer churn is a crucial task aimed at retaining customers and maintaining revenue growth.Traditional machine learning(ML)models often struggle to capture complex temporal dependencies in client behavior data.To address this,an optimized deep learning(DL)approach using a Regularized Bidirectional Long Short-Term Memory(RBiLSTM)model is proposed to mitigate overfitting and improve generalization error.The model integrates dropout,L2-regularization,and early stopping to enhance predictive accuracy while preventing over-reliance on specific patterns.Moreover,this study investigates the effect of optimization techniques on boosting the training efficiency of the developed model.Experimental results on a recent public customer churn dataset demonstrate that the trained model outperforms the traditional ML models and some other DL models,such as Long Short-Term Memory(LSTM)and Deep Neural Network(DNN),in churn prediction performance and stability.The proposed approach achieves 96.1%accuracy,compared with LSTM and DNN,which attain 94.5%and 94.1%accuracy,respectively.These results confirm that the proposed approach can be used as a valuable tool for businesses to identify at-risk consumers proactively and implement targeted retention strategies.展开更多
This study demonstrates a novel integration of large language models,machine learning,and multicriteria decision-making to investigate self-moderation in small online communities,a topic under-explored compared to use...This study demonstrates a novel integration of large language models,machine learning,and multicriteria decision-making to investigate self-moderation in small online communities,a topic under-explored compared to user behavior and platform-driven moderation on social media.The proposed methodological framework(1)utilizes large language models for social media post analysis and categorization,(2)employs k-means clustering for content characterization,and(3)incorporates the TODIM(Tomada de Decisão Interativa Multicritério)method to determine moderation strategies based on expert judgments.In general,the fully integrated framework leverages the strengths of these intelligent systems in a more systematic evaluation of large-scale decision problems.When applied in social media moderation,this approach promotes nuanced and context-sensitive self-moderation by taking into account factors such as cultural background and geographic location.The application of this framework is demonstrated within Facebook groups.Eight distinct content clusters encompassing safety,harassment,diversity,and misinformation are identified.Analysis revealed a preference for content removal across all clusters,suggesting a cautious approach towards potentially harmful content.However,the framework also highlights the use of other moderation actions,like account suspension,depending on the content category.These findings contribute to the growing body of research on self-moderation and offer valuable insights for creating safer and more inclusive online spaces within smaller communities.展开更多
The moving morphable component(MMC)topology optimization method,as a typical explicit topology optimization method,has been widely concerned.In the MMC topology optimization framework,the surrogate material model is m...The moving morphable component(MMC)topology optimization method,as a typical explicit topology optimization method,has been widely concerned.In the MMC topology optimization framework,the surrogate material model is mainly used for finite element analysis at present,and the effectiveness of the surrogate material model has been fully confirmed.However,there are some accuracy problems when dealing with boundary elements using the surrogate material model,which will affect the topology optimization results.In this study,a boundary element reconstruction(BER)model is proposed based on the surrogate material model under the MMC topology optimization framework to improve the accuracy of topology optimization.The proposed BER model can reconstruct the boundary elements by refining the local meshes and obtaining new nodes in boundary elements.Then the density of boundary elements is recalculated using the new node information,which is more accurate than the original model.Based on the new density of boundary elements,the material properties and volume information of the boundary elements are updated.Compared with other finite element analysis methods,the BER model is simple and feasible and can improve computational accuracy.Finally,the effectiveness and superiority of the proposed method are verified by comparing it with the optimization results of the original surrogate material model through several numerical examples.展开更多
To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework ba...To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.展开更多
Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frame...Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frames remains a fundamental yet unresolved challenge.Existing methods typically rely on dense keyframe inputs or complex prior structures,making it difficult to balance motion quality and plausibility under conditions such as sparse constraints,long-term dependencies,and diverse motion styles.To address this,we propose a motion generation framework based on a frequency-domain diffusion model,which aims to better model complex motion distributions and enhance generation stability under sparse conditions.Our method maps motion sequences to the frequency domain via the Discrete Cosine Transform(DCT),enabling more effective modeling of low-frequency motion structures while suppressing high-frequency noise.A denoising network based on self-attention is introduced to capture long-range temporal dependencies and improve global structural awareness.Additionally,a multi-objective loss function is employed to jointly optimize motion smoothness,pose diversity,and anatomical consistency,enhancing the realism and physical plausibility of the generated sequences.Comparative experiments on the Human3.6M and LaFAN1 datasets demonstrate that our method outperforms state-of-the-art approaches across multiple performance metrics,showing stronger capabilities in generating intermediate motion frames.This research offers a new perspective and methodology for human motion generation and holds promise for applications in character animation,game development,and virtual interaction.展开更多
Noninvasive brain stimulation techniques offer promising therapeutic and regenerative prospects in neurological diseases by modulating brain activity and improving cognitive and motor functions.Given the paucity of kn...Noninvasive brain stimulation techniques offer promising therapeutic and regenerative prospects in neurological diseases by modulating brain activity and improving cognitive and motor functions.Given the paucity of knowledge about the underlying modes of action and optimal treatment modalities,a thorough translational investigation of noninvasive brain stimulation in preclinical animal models is urgently needed.Thus,we reviewed the current literature on the mechanistic underpinnings of noninvasive brain stimulation in models of central nervous system impairment,with a particular emphasis on traumatic brain injury and stroke.Due to the lack of translational models in most noninvasive brain stimulation techniques proposed,we found this review to the most relevant techniques used in humans,i.e.,transcranial magnetic stimulation and transcranial direct current stimulation.We searched the literature in Pub Med,encompassing the MEDLINE and PMC databases,for studies published between January 1,2020 and September 30,2024.Thirty-five studies were eligible.Transcranial magnetic stimulation and transcranial direct current stimulation demonstrated distinct strengths in augmenting rehabilitation post-stroke and traumatic brain injury,with emerging mechanistic evidence.Overall,we identified neuronal,inflammatory,microvascular,and apoptotic pathways highlighted in the literature.This review also highlights a lack of translational surrogate parameters to bridge the gap between preclinical findings and their clinical translation.展开更多
Myasthenia gravis is a chronic autoimmune disorder that affects the neuromuscular junction leading to fluctuating skeletal muscle fatigability. The majority of myasthenia gravis patients have detectable antibodies in ...Myasthenia gravis is a chronic autoimmune disorder that affects the neuromuscular junction leading to fluctuating skeletal muscle fatigability. The majority of myasthenia gravis patients have detectable antibodies in their serum, targeting acetylcholine receptor, muscle-specific kinase, or related proteins. Current treatment for myasthenia gravis involves symptomatic therapy, immunosuppressive drugs such as corticosteroids, azathioprine, and mycophenolate mofetil, and thymectomy, which is primarily indicated in patients with thymoma or thymic hyperplasia. However, this condition continues to pose significant challenges including an unpredictable and variable disease progression, differing response to individual therapies, and substantial longterm side effects associated with standard treatments(including an increased risk of infections, osteoporosis, and diabetes), underscoring the necessity for a more personalized approach to treatment. Furthermore, about fifteen percent of patients, called “refractory myasthenia gravis patients”, do not respond adequately to standard therapies. In this context, the introduction of molecular therapies has marked a significant advance in myasthenia gravis management. Advances in understanding myasthenia gravis pathogenesis, especially the role of pathogenic antibodies, have driven the development of these biological drugs, which offer more selective, rapid, and safer alternatives to traditional immunosuppressants. This review aims to provide a comprehensive overview of emerging therapeutic strategies targeting specific immune pathways in myasthenia gravis, with a particular focus on preclinical evidence, therapeutic rationale, and clinical translation of B-cell depletion therapies, neonatal Fc receptor inhibitors, and complement inhibitors.展开更多
The brain is the most complex human organ,and commonly used models,such as two-dimensional-cell cultures and animal brains,often lack the sophistication needed to accurately use in research.In this context,human cereb...The brain is the most complex human organ,and commonly used models,such as two-dimensional-cell cultures and animal brains,often lack the sophistication needed to accurately use in research.In this context,human cerebral organoids have emerged as valuable tools offering a more complex,versatile,and human-relevant system than traditional animal models,which are often unable to replicate the intricate architecture and functionality of the human brain.Since human cerebral organoids are a state-of-the-art model for the study of neurodevelopment and different pathologies affecting the brain,this field is currently under constant development,and work in this area is abundant.In this review,we give a complete overview of human cerebral organoids technology,starting from the different types of protocols that exist to generate different human cerebral organoids.We continue with the use of brain organoids for the study of brain pathologies,highlighting neurodevelopmental,psychiatric,neurodegenerative,brain tumor,and infectious diseases.Because of the potential value of human cerebral organoids,we describe their use in transplantation,drug screening,and toxicology assays.We also discuss the technologies available to study cell diversity and physiological characteristics of organoids.Finally,we summarize the limitations that currently exist in the field,such as the development of vasculature and microglia,and highlight some of the novel approaches being pursued through bioengineering.展开更多
This paper develops a conceptual model and an indicator system for measuring economic resilience of resource-based cities based on the theory of evolutionary resilience and the related concepts of persistence, adaptat...This paper develops a conceptual model and an indicator system for measuring economic resilience of resource-based cities based on the theory of evolutionary resilience and the related concepts of persistence, adaptation, and transformation. Nineteen resource-based cities in Northeast China were analyzed using the indicator system. The results showed that Liaoning and Jilin provinces had higher economic resilience than Heilongjiang Province. Panjin, Benxi, and Anshan in Liaoning Province were the top three cities, while Shuangyashan and other coal-based cities in Heilongjiang Province ranked last. Metals-and petroleum-based cities had significantly higher resilience than coal-based cities. The differences in persistence, adaptability, transformation, and resilience among resource-based cities decreased since the introduction of the Northeast Revitalization Strategy in 2003. Forestry-based cities improved the most in terms of resilience, followed by metals-based and multiple-resource cities; however, resilience dropped for coal-based cities, and petroleum-based cities falling the most. The findings illustrate the importance and the way to develop a differentiated approach to improve resilience among resource-based cities.展开更多
Industry re-feeding agriculture is an important strategy to boost agricultural modernization[1]. As to resource-based regions, the key thing is the way to implement the strategy of resource-based industry re-feeding a...Industry re-feeding agriculture is an important strategy to boost agricultural modernization[1]. As to resource-based regions, the key thing is the way to implement the strategy of resource-based industry re-feeding agriculture. In fact, as a typical resource-based county, Fugu County realizes its quick economic development mainly depending on the local resources and industrial development. And the agricultural development is relatively lagging in the county, more people are beginning to denote themselves to industrial development due to high return brought by resource exploitation, which results that the contradiction between industry and agriculture is gradually prominent in the county. Therefore, it is necessary to seek for a new way to develop industry and agriculture in resource-based counties. This article mainly introduces the mode and method of "industry re-feeding agriculture" in Fugu County, analyzes and summarizes the implementation effects and achievements of modes as well as discusses the problems produced in the course of policy implementation and tries to find countermeasures to coordinate the contradiction between industry and agriculture, then further discuss the development perspective of industry and agriculture in Fugu County.展开更多
A key target of the overall strategy implementation for regional development since the 18th Party Congress of China has involved taking measures to narrow regional disparities. This is because resource-based cities...A key target of the overall strategy implementation for regional development since the 18th Party Congress of China has involved taking measures to narrow regional disparities. This is because resource-based cities' economic development has fallen below general levels due to resource exhaustion and an unbalanced industrial structure, among other factors. Further, an economic gap has long existed between Northeast China's large number of resource-based cities and non-resource-based cities. This article comprehensively studies the economic convergence of Northeast China's resource-based cities and non-resource-based cities from 1996 to 2015 by using a dynamic panel to analyze not only the economic development of different industries and types of cities, but also the main factors that influence economic development. The empirical results demonstrate that economic convergence exists in both resource-based and non-resource-based cities, but the economic gap between them has clearly narrowed since the implementation of a strategy to revitalize the Northeast's old industrial base. Shrinking cities are the fastest to converge, as mature cities are slower and regenerating cities are the slowest; regarding industry structure, the secondary industry dominates the economy in mature and shrinking cities, and the tertiary industry in regenerating cities. The primary stimulus in resource-based cities' economic development involves upgrading the industrial structure and investing in human capital. As China faces a ‘new normal' economy, resource-based cities in Northeast China should restructure the economy and perfect their market system to avoid again widening the economic gap.展开更多
Resource-constrainted and located closer to users,edge servers are more vulnerable to Distributed Denial of Service(DDoS)attacks.In order to mitigate the impact of DDoS attacks on benign users,this paper designed a Re...Resource-constrainted and located closer to users,edge servers are more vulnerable to Distributed Denial of Service(DDoS)attacks.In order to mitigate the impact of DDoS attacks on benign users,this paper designed a Resource-based Pricing Collaborative approach(RPC)in mobile edge computing.By introducing the influence of resource prices on requester in economics,a collaboration model based on resource pricing was established,and the allocation of user request was regarded as a game strategy to obtain the overall minimum offloading cost of the user in network.The article theoretically proved the existence and rationality of the Nash equilibrium.Finally,simulation results verified the effectiveness and feasibility of the proposed approach in two experimental scenes.Experimental results shows that RPC can effectively improve the network ability to mitigate DDoS attacks,and alleviate the adverse effects of server attacks under delay constraints.展开更多
Characteristic towns as a characteristic industry are one of the important measures of China's new urbanization strategy. The construction of characteristic towns in different regions needs to pay attention to reg...Characteristic towns as a characteristic industry are one of the important measures of China's new urbanization strategy. The construction of characteristic towns in different regions needs to pay attention to regional differentiation. At present, the research on characteristic towns focuses on the developed the developed central and eastern regions. There are still few studies on characteristics towns in underdeveloped areas. Starting from the analysis of the concept of the characteristic town, this paper sorted out the general situation of the construction of characteristic towns in China based on the existing research literature, selected Ganzhou City for research, pointed out there were "two restrictions and two singles" in the construction of characteristic towns in Ganzhou City, and clarified that the characteristic towns of Ganzhou City should adhere to the construction path of "two characteristics and two integrations", with a view to providing a useful reference for in Ganzhou City the construction of characteristic towns, industrial transformation and upgrading, and poverty alleviation in such underdeveloped, resource-based cities.展开更多
As people exploit resources vigorously,the amount of exploitable resources is decreasing.Due to long-term unsustainable development,resource-based cities and towns have encountered problems such as lack of resources a...As people exploit resources vigorously,the amount of exploitable resources is decreasing.Due to long-term unsustainable development,resource-based cities and towns have encountered problems such as lack of resources and slow economic growth.Faced with the"resource curse"phenomenon,the transformation of resource-based cities and towns is an inevitable trend to achieve sustainable development.In this article,taking Qingcheng County as an example,by analyzing and researching the development status and existing problems of resource industry,the stage of industrial development in Qingcheng County is discussed to prove the importance of industrial transformation to the sustainable development of Qingcheng County,the experience and lessons that Qingcheng County can learn are summarized,and the objective laws and influencing factors in the acceleration of industrial transformation in Qingcheng County are analyzed in depth.Using SWOT analysis,specific countermeasures are explored to realize the industrial transformation of Qingcheng County.展开更多
With the development of market economy, inter-regional economic competition has become increasingly prominent and concentrated in specific industries compete and contest. Evaluation and analysis of industrial competit...With the development of market economy, inter-regional economic competition has become increasingly prominent and concentrated in specific industries compete and contest. Evaluation and analysis of industrial competitiveness in Yulin City, what is premise by formulating the next step of economic development planning and selecting the industrial development-oriented. Through the analysis of the data, that evaluate the competitiveness of industries in Yulin City with principal component analysis method, the results show that the uneven distribution of industrial competitiveness in Yulin City, and structural imbalance, energy and chemical industry competitive is advantage. To promote the enhancement of industrial competitiveness in Yulin City, that adjusts the industrial structure, to establish the leading industry, by the future,and develope with the sustainable way.展开更多
基金the World Climate Research Programme(WCRP),Climate Variability and Predictability(CLIVAR),and Global Energy and Water Exchanges(GEWEX)for facilitating the coordination of African monsoon researchsupport from the Center for Earth System Modeling,Analysis,and Data at the Pennsylvania State Universitythe support of the Office of Science of the U.S.Department of Energy Biological and Environmental Research as part of the Regional&Global Model Analysis(RGMA)program area。
文摘In recent years,there has been an increasing need for climate information across diverse sectors of society.This demand has arisen from the necessity to adapt to and mitigate the impacts of climate variability and change.Likewise,this period has seen a significant increase in our understanding of the physical processes and mechanisms that drive precipitation and its variability across different regions of Africa.By leveraging a large volume of climate model outputs,numerous studies have investigated the model representation of African precipitation as well as underlying physical processes.These studies have assessed whether the physical processes are well depicted and whether the models are fit for informing mitigation and adaptation strategies.This paper provides a review of the progress in precipitation simulation overAfrica in state-of-the-science climate models and discusses the major issues and challenges that remain.
文摘Climate model prediction has been improved by enhancing model resolution as well as the implementation of sophisticated physical parameterization and refinement of data assimilation systems[section 6.1 in Wang et al.(2025)].In relation to seasonal forecasting and climate projection in the East Asian summer monsoon season,proper simulation of the seasonal migration of rain bands by models is a challenging and limiting factor[section 7.1 in Wang et al.(2025)].
文摘Customer churn is the rate at which customers discontinue doing business with a company over a given time period.It is an essential measure for businesses to monitor high churn rates,as they often indicate underlying issues with services,products,or customer experience,resulting in considerable income loss.Prediction of customer churn is a crucial task aimed at retaining customers and maintaining revenue growth.Traditional machine learning(ML)models often struggle to capture complex temporal dependencies in client behavior data.To address this,an optimized deep learning(DL)approach using a Regularized Bidirectional Long Short-Term Memory(RBiLSTM)model is proposed to mitigate overfitting and improve generalization error.The model integrates dropout,L2-regularization,and early stopping to enhance predictive accuracy while preventing over-reliance on specific patterns.Moreover,this study investigates the effect of optimization techniques on boosting the training efficiency of the developed model.Experimental results on a recent public customer churn dataset demonstrate that the trained model outperforms the traditional ML models and some other DL models,such as Long Short-Term Memory(LSTM)and Deep Neural Network(DNN),in churn prediction performance and stability.The proposed approach achieves 96.1%accuracy,compared with LSTM and DNN,which attain 94.5%and 94.1%accuracy,respectively.These results confirm that the proposed approach can be used as a valuable tool for businesses to identify at-risk consumers proactively and implement targeted retention strategies.
基金funded by the Office of the Vice-President for Research and Development of Cebu Technological University.
文摘This study demonstrates a novel integration of large language models,machine learning,and multicriteria decision-making to investigate self-moderation in small online communities,a topic under-explored compared to user behavior and platform-driven moderation on social media.The proposed methodological framework(1)utilizes large language models for social media post analysis and categorization,(2)employs k-means clustering for content characterization,and(3)incorporates the TODIM(Tomada de Decisão Interativa Multicritério)method to determine moderation strategies based on expert judgments.In general,the fully integrated framework leverages the strengths of these intelligent systems in a more systematic evaluation of large-scale decision problems.When applied in social media moderation,this approach promotes nuanced and context-sensitive self-moderation by taking into account factors such as cultural background and geographic location.The application of this framework is demonstrated within Facebook groups.Eight distinct content clusters encompassing safety,harassment,diversity,and misinformation are identified.Analysis revealed a preference for content removal across all clusters,suggesting a cautious approach towards potentially harmful content.However,the framework also highlights the use of other moderation actions,like account suspension,depending on the content category.These findings contribute to the growing body of research on self-moderation and offer valuable insights for creating safer and more inclusive online spaces within smaller communities.
基金supported by the Science and Technology Research Project of Henan Province(242102241055)the Industry-University-Research Collaborative Innovation Base on Automobile Lightweight of“Science and Technology Innovation in Central Plains”(2024KCZY315)the Opening Fund of State Key Laboratory of Structural Analysis,Optimization and CAE Software for Industrial Equipment(GZ2024A03-ZZU).
文摘The moving morphable component(MMC)topology optimization method,as a typical explicit topology optimization method,has been widely concerned.In the MMC topology optimization framework,the surrogate material model is mainly used for finite element analysis at present,and the effectiveness of the surrogate material model has been fully confirmed.However,there are some accuracy problems when dealing with boundary elements using the surrogate material model,which will affect the topology optimization results.In this study,a boundary element reconstruction(BER)model is proposed based on the surrogate material model under the MMC topology optimization framework to improve the accuracy of topology optimization.The proposed BER model can reconstruct the boundary elements by refining the local meshes and obtaining new nodes in boundary elements.Then the density of boundary elements is recalculated using the new node information,which is more accurate than the original model.Based on the new density of boundary elements,the material properties and volume information of the boundary elements are updated.Compared with other finite element analysis methods,the BER model is simple and feasible and can improve computational accuracy.Finally,the effectiveness and superiority of the proposed method are verified by comparing it with the optimization results of the original surrogate material model through several numerical examples.
基金supported by the confidential research grant No.a8317。
文摘To address the issues of frequent identity switches(IDs)and degraded identification accuracy in multi object tracking(MOT)under complex occlusion scenarios,this study proposes an occlusion-robust tracking framework based on face-pedestrian joint feature modeling.By constructing a joint tracking model centered on“intra-class independent tracking+cross-category dynamic binding”,designing a multi-modal matching metric with spatio-temporal and appearance constraints,and innovatively introducing a cross-category feature mutual verification mechanism and a dual matching strategy,this work effectively resolves performance degradation in traditional single-category tracking methods caused by short-term occlusion,cross-camera tracking,and crowded environments.Experiments on the Chokepoint_Face_Pedestrian_Track test set demonstrate that in complex scenes,the proposed method improves Face-Pedestrian Matching F1 area under the curve(F1 AUC)by approximately 4 to 43 percentage points compared to several traditional methods.The joint tracking model achieves overall performance metrics of IDF1:85.1825%and MOTA:86.5956%,representing improvements of 0.91 and 0.06 percentage points,respectively,over the baseline model.Ablation studies confirm the effectiveness of key modules such as the Intersection over Area(IoA)/Intersection over Union(IoU)joint metric and dynamic threshold adjustment,validating the significant role of the cross-category identity matching mechanism in enhancing tracking stability.Our_model shows a 16.7%frame per second(FPS)drop vs.fairness of detection and re-identification in multiple object tracking(FairMOT),with its cross-category binding module adding aboute 10%overhead,yet maintains near-real-time performance for essential face-pedestrian tracking at small resolutions.
基金supported by the National Natural Science Foundation of China(Grant No.72161034).
文摘Human motion modeling is a core technology in computer animation,game development,and humancomputer interaction.In particular,generating natural and coherent in-between motion using only the initial and terminal frames remains a fundamental yet unresolved challenge.Existing methods typically rely on dense keyframe inputs or complex prior structures,making it difficult to balance motion quality and plausibility under conditions such as sparse constraints,long-term dependencies,and diverse motion styles.To address this,we propose a motion generation framework based on a frequency-domain diffusion model,which aims to better model complex motion distributions and enhance generation stability under sparse conditions.Our method maps motion sequences to the frequency domain via the Discrete Cosine Transform(DCT),enabling more effective modeling of low-frequency motion structures while suppressing high-frequency noise.A denoising network based on self-attention is introduced to capture long-range temporal dependencies and improve global structural awareness.Additionally,a multi-objective loss function is employed to jointly optimize motion smoothness,pose diversity,and anatomical consistency,enhancing the realism and physical plausibility of the generated sequences.Comparative experiments on the Human3.6M and LaFAN1 datasets demonstrate that our method outperforms state-of-the-art approaches across multiple performance metrics,showing stronger capabilities in generating intermediate motion frames.This research offers a new perspective and methodology for human motion generation and holds promise for applications in character animation,game development,and virtual interaction.
基金funded by the Deutsche Forschungsgemeinschaft(DFG,German Research Foundation):project ID 431549029-SFB 1451the Marga-und-Walter-Boll-Stiftung(#210-10-15)(to MAR)a stipend from the'Gerok Program'(Faculty of Medicine,University of Cologne,Germany)。
文摘Noninvasive brain stimulation techniques offer promising therapeutic and regenerative prospects in neurological diseases by modulating brain activity and improving cognitive and motor functions.Given the paucity of knowledge about the underlying modes of action and optimal treatment modalities,a thorough translational investigation of noninvasive brain stimulation in preclinical animal models is urgently needed.Thus,we reviewed the current literature on the mechanistic underpinnings of noninvasive brain stimulation in models of central nervous system impairment,with a particular emphasis on traumatic brain injury and stroke.Due to the lack of translational models in most noninvasive brain stimulation techniques proposed,we found this review to the most relevant techniques used in humans,i.e.,transcranial magnetic stimulation and transcranial direct current stimulation.We searched the literature in Pub Med,encompassing the MEDLINE and PMC databases,for studies published between January 1,2020 and September 30,2024.Thirty-five studies were eligible.Transcranial magnetic stimulation and transcranial direct current stimulation demonstrated distinct strengths in augmenting rehabilitation post-stroke and traumatic brain injury,with emerging mechanistic evidence.Overall,we identified neuronal,inflammatory,microvascular,and apoptotic pathways highlighted in the literature.This review also highlights a lack of translational surrogate parameters to bridge the gap between preclinical findings and their clinical translation.
文摘Myasthenia gravis is a chronic autoimmune disorder that affects the neuromuscular junction leading to fluctuating skeletal muscle fatigability. The majority of myasthenia gravis patients have detectable antibodies in their serum, targeting acetylcholine receptor, muscle-specific kinase, or related proteins. Current treatment for myasthenia gravis involves symptomatic therapy, immunosuppressive drugs such as corticosteroids, azathioprine, and mycophenolate mofetil, and thymectomy, which is primarily indicated in patients with thymoma or thymic hyperplasia. However, this condition continues to pose significant challenges including an unpredictable and variable disease progression, differing response to individual therapies, and substantial longterm side effects associated with standard treatments(including an increased risk of infections, osteoporosis, and diabetes), underscoring the necessity for a more personalized approach to treatment. Furthermore, about fifteen percent of patients, called “refractory myasthenia gravis patients”, do not respond adequately to standard therapies. In this context, the introduction of molecular therapies has marked a significant advance in myasthenia gravis management. Advances in understanding myasthenia gravis pathogenesis, especially the role of pathogenic antibodies, have driven the development of these biological drugs, which offer more selective, rapid, and safer alternatives to traditional immunosuppressants. This review aims to provide a comprehensive overview of emerging therapeutic strategies targeting specific immune pathways in myasthenia gravis, with a particular focus on preclinical evidence, therapeutic rationale, and clinical translation of B-cell depletion therapies, neonatal Fc receptor inhibitors, and complement inhibitors.
基金supported by the Grant PID2021-126715OB-IOO financed by MCIN/AEI/10.13039/501100011033 and"ERDFA way of making Europe"by the Grant PI22CⅢ/00055 funded by Instituto de Salud CarlosⅢ(ISCⅢ)+6 种基金the UFIECPY 398/19(PEJ2018-004965) grant to RGS funded by AEI(Spain)the UFIECPY-396/19(PEJ2018-004961)grant financed by MCIN (Spain)FI23CⅢ/00003 grant funded by ISCⅢ-PFIS Spain) to PMMthe UFIECPY 328/22 (PEJ-2021-TL/BMD-21001) grant to LM financed by CAM (Spain)the grant by CAPES (Coordination for the Improvement of Higher Education Personnel)through the PDSE program (Programa de Doutorado Sanduiche no Exterior)to VSCG financed by MEC (Brazil)
文摘The brain is the most complex human organ,and commonly used models,such as two-dimensional-cell cultures and animal brains,often lack the sophistication needed to accurately use in research.In this context,human cerebral organoids have emerged as valuable tools offering a more complex,versatile,and human-relevant system than traditional animal models,which are often unable to replicate the intricate architecture and functionality of the human brain.Since human cerebral organoids are a state-of-the-art model for the study of neurodevelopment and different pathologies affecting the brain,this field is currently under constant development,and work in this area is abundant.In this review,we give a complete overview of human cerebral organoids technology,starting from the different types of protocols that exist to generate different human cerebral organoids.We continue with the use of brain organoids for the study of brain pathologies,highlighting neurodevelopmental,psychiatric,neurodegenerative,brain tumor,and infectious diseases.Because of the potential value of human cerebral organoids,we describe their use in transplantation,drug screening,and toxicology assays.We also discuss the technologies available to study cell diversity and physiological characteristics of organoids.Finally,we summarize the limitations that currently exist in the field,such as the development of vasculature and microglia,and highlight some of the novel approaches being pursued through bioengineering.
基金Under the auspices of National Natural Science Foundation of China(No.41571152,41201160,41601124,41201159,71541021)the Knowledge Innovation Program of the Chinese Academy of Sciences(No.KSZD-EW-Z-021)the Key Consulting Program of the Chinese Academy of Sciences(No.Y02015005)
文摘This paper develops a conceptual model and an indicator system for measuring economic resilience of resource-based cities based on the theory of evolutionary resilience and the related concepts of persistence, adaptation, and transformation. Nineteen resource-based cities in Northeast China were analyzed using the indicator system. The results showed that Liaoning and Jilin provinces had higher economic resilience than Heilongjiang Province. Panjin, Benxi, and Anshan in Liaoning Province were the top three cities, while Shuangyashan and other coal-based cities in Heilongjiang Province ranked last. Metals-and petroleum-based cities had significantly higher resilience than coal-based cities. The differences in persistence, adaptability, transformation, and resilience among resource-based cities decreased since the introduction of the Northeast Revitalization Strategy in 2003. Forestry-based cities improved the most in terms of resilience, followed by metals-based and multiple-resource cities; however, resilience dropped for coal-based cities, and petroleum-based cities falling the most. The findings illustrate the importance and the way to develop a differentiated approach to improve resilience among resource-based cities.
基金Supported by City and School Joint Key Project for Scientific Measurement Development and Analysis in Yulin City(yl2011158)
文摘Industry re-feeding agriculture is an important strategy to boost agricultural modernization[1]. As to resource-based regions, the key thing is the way to implement the strategy of resource-based industry re-feeding agriculture. In fact, as a typical resource-based county, Fugu County realizes its quick economic development mainly depending on the local resources and industrial development. And the agricultural development is relatively lagging in the county, more people are beginning to denote themselves to industrial development due to high return brought by resource exploitation, which results that the contradiction between industry and agriculture is gradually prominent in the county. Therefore, it is necessary to seek for a new way to develop industry and agriculture in resource-based counties. This article mainly introduces the mode and method of "industry re-feeding agriculture" in Fugu County, analyzes and summarizes the implementation effects and achievements of modes as well as discusses the problems produced in the course of policy implementation and tries to find countermeasures to coordinate the contradiction between industry and agriculture, then further discuss the development perspective of industry and agriculture in Fugu County.
基金Under the auspices of National Natural Science Foundation of China(No.41471111)China’s Postdoctoral Science Foundation(No.2017M621191)Fundamental Research Funds for the Central Universities(No.2412017QD020)
文摘A key target of the overall strategy implementation for regional development since the 18th Party Congress of China has involved taking measures to narrow regional disparities. This is because resource-based cities' economic development has fallen below general levels due to resource exhaustion and an unbalanced industrial structure, among other factors. Further, an economic gap has long existed between Northeast China's large number of resource-based cities and non-resource-based cities. This article comprehensively studies the economic convergence of Northeast China's resource-based cities and non-resource-based cities from 1996 to 2015 by using a dynamic panel to analyze not only the economic development of different industries and types of cities, but also the main factors that influence economic development. The empirical results demonstrate that economic convergence exists in both resource-based and non-resource-based cities, but the economic gap between them has clearly narrowed since the implementation of a strategy to revitalize the Northeast's old industrial base. Shrinking cities are the fastest to converge, as mature cities are slower and regenerating cities are the slowest; regarding industry structure, the secondary industry dominates the economy in mature and shrinking cities, and the tertiary industry in regenerating cities. The primary stimulus in resource-based cities' economic development involves upgrading the industrial structure and investing in human capital. As China faces a ‘new normal' economy, resource-based cities in Northeast China should restructure the economy and perfect their market system to avoid again widening the economic gap.
基金National Natural Science Foundation of China(No.61941114)and(No.61801515).
文摘Resource-constrainted and located closer to users,edge servers are more vulnerable to Distributed Denial of Service(DDoS)attacks.In order to mitigate the impact of DDoS attacks on benign users,this paper designed a Resource-based Pricing Collaborative approach(RPC)in mobile edge computing.By introducing the influence of resource prices on requester in economics,a collaboration model based on resource pricing was established,and the allocation of user request was regarded as a game strategy to obtain the overall minimum offloading cost of the user in network.The article theoretically proved the existence and rationality of the Nash equilibrium.Finally,simulation results verified the effectiveness and feasibility of the proposed approach in two experimental scenes.Experimental results shows that RPC can effectively improve the network ability to mitigate DDoS attacks,and alleviate the adverse effects of server attacks under delay constraints.
文摘Characteristic towns as a characteristic industry are one of the important measures of China's new urbanization strategy. The construction of characteristic towns in different regions needs to pay attention to regional differentiation. At present, the research on characteristic towns focuses on the developed the developed central and eastern regions. There are still few studies on characteristics towns in underdeveloped areas. Starting from the analysis of the concept of the characteristic town, this paper sorted out the general situation of the construction of characteristic towns in China based on the existing research literature, selected Ganzhou City for research, pointed out there were "two restrictions and two singles" in the construction of characteristic towns in Ganzhou City, and clarified that the characteristic towns of Ganzhou City should adhere to the construction path of "two characteristics and two integrations", with a view to providing a useful reference for in Ganzhou City the construction of characteristic towns, industrial transformation and upgrading, and poverty alleviation in such underdeveloped, resource-based cities.
文摘As people exploit resources vigorously,the amount of exploitable resources is decreasing.Due to long-term unsustainable development,resource-based cities and towns have encountered problems such as lack of resources and slow economic growth.Faced with the"resource curse"phenomenon,the transformation of resource-based cities and towns is an inevitable trend to achieve sustainable development.In this article,taking Qingcheng County as an example,by analyzing and researching the development status and existing problems of resource industry,the stage of industrial development in Qingcheng County is discussed to prove the importance of industrial transformation to the sustainable development of Qingcheng County,the experience and lessons that Qingcheng County can learn are summarized,and the objective laws and influencing factors in the acceleration of industrial transformation in Qingcheng County are analyzed in depth.Using SWOT analysis,specific countermeasures are explored to realize the industrial transformation of Qingcheng County.
文摘With the development of market economy, inter-regional economic competition has become increasingly prominent and concentrated in specific industries compete and contest. Evaluation and analysis of industrial competitiveness in Yulin City, what is premise by formulating the next step of economic development planning and selecting the industrial development-oriented. Through the analysis of the data, that evaluate the competitiveness of industries in Yulin City with principal component analysis method, the results show that the uneven distribution of industrial competitiveness in Yulin City, and structural imbalance, energy and chemical industry competitive is advantage. To promote the enhancement of industrial competitiveness in Yulin City, that adjusts the industrial structure, to establish the leading industry, by the future,and develope with the sustainable way.
