In the current digital era,new technologies are becoming an essential part of our lives.Consequently,the number ofmalicious software ormalware attacks is rapidly growing.There is no doubt,themajority ofmalware attacks...In the current digital era,new technologies are becoming an essential part of our lives.Consequently,the number ofmalicious software ormalware attacks is rapidly growing.There is no doubt,themajority ofmalware attacks can be detected by most antivirus programs.However,such types of antivirus programs are one step behind malicious software.Due to these dilemmas,deep learning become popular in the detection and classification of malicious data.Therefore,researchers have significantly focused on finding solutions for malware attacks by analyzing malicious samples with the help of different techniques and models.In this research,we presented a lightweight attention-based novel deep Convolutional Neural Network(DNN-CNN)model for binary and multi-class malware classification,including benign,trojan horse,ransomware,and spyware.We applied the Principal Component Analysis(PCA)technique for feature extraction for binary classification.We used the Synthetic Minority Oversampling Technique(SMOTE)to handle the imbalanced data during multi-class classification.Our proposed attention-based malware detectionmodel is trained on the benchmarkmalware memory dataset named CIC-MalMem-2022.Theresults indicate that our model obtained high accuracy for binary and multi-class classification,99.5% and 97.9%,respectively.展开更多
Dynamic sign language recognition holds significant importance, particularly with the application of deep learning to address its complexity. However, existing methods face several challenges. Firstly, recognizing dyn...Dynamic sign language recognition holds significant importance, particularly with the application of deep learning to address its complexity. However, existing methods face several challenges. Firstly, recognizing dynamic sign language requires identifying keyframes that best represent the signs, and missing these keyframes reduces accuracy. Secondly, some methods do not focus enough on hand regions, which are small within the overall frame, leading to information loss. To address these challenges, we propose a novel Video Transformer Attention-based Network (VTAN) for dynamic sign language recognition. Our approach prioritizes informative frames and hand regions effectively. To tackle the first issue, we designed a keyframe extraction module enhanced by a convolutional autoencoder, which focuses on selecting information-rich frames and eliminating redundant ones from the video sequences. For the second issue, we developed a soft attention-based transformer module that emphasizes extracting features from hand regions, ensuring that the network pays more attention to hand information within sequences. This dual-focus approach improves effective dynamic sign language recognition by addressing the key challenges of identifying critical frames and emphasizing hand regions. Experimental results on two public benchmark datasets demonstrate the effectiveness of our network, outperforming most of the typical methods in sign language recognition tasks.展开更多
Electrocardiogram(ECG)signal is one of the noninvasive physiological measurement techniques commonly usedin cardiac diagnosis.However,in real scenarios,the ECGsignal is susceptible to various noise erosion,which affec...Electrocardiogram(ECG)signal is one of the noninvasive physiological measurement techniques commonly usedin cardiac diagnosis.However,in real scenarios,the ECGsignal is susceptible to various noise erosion,which affectsthe subsequent pathological analysis.Therefore,the effective removal of the noise from ECG signals has becomea top priority in cardiac diagnostic research.Aiming at the problem of incomplete signal shape retention andlow signal-to-noise ratio(SNR)after denoising,a novel ECG denoising network,named attention-based residualdense shrinkage network(ARDSN),is proposed in this paper.Firstly,the shallow ECG characteristics are extractedby a shallow feature extraction network(SFEN).Then,the residual dense shrinkage attention block(RDSAB)isused for adaptive noise suppression.Finally,feature fusion representation(FFR)is performed on the hierarchicalfeatures extracted by a series of RDSABs to reconstruct the de-noised ECG signal.Experiments on the MIT-BIHarrhythmia database and MIT-BIH noise stress test database indicate that the proposed scheme can effectively resistthe interference of different sources of noise on the ECG signal.展开更多
The establishment of a sound science and technology ethics governance system is an inevitable requirement for national modernization.Faced with the development of human gene technology and the chaos in research activi...The establishment of a sound science and technology ethics governance system is an inevitable requirement for national modernization.Faced with the development of human gene technology and the chaos in research activities,the ethical standards and legal positioning of human gene research activities urgently need to be clarified.The human rights ethics view has value inclusiveness and value fundamentality,and includes three levels of connotations:content dimension,relationship dimension,and obligation dimension.It should serve as the ethical standard for human gene research activities.Based on the provisions of China’s Constitution,the human rights ethics view on human gene research,as a constitutional ethics view,can elucidate different levels of rights content,such as human dignity,life and health,and research freedom.It also addresses the weighing of basic rights conflicts and the dual obligation subjects of public and private nature.Relying on the constitutional value embedding of the research ethics view to form ethical consensus,improving ethical review through framework legislation for human rights interests,and implementing ethical responsibility through the human rights-oriented interpretation of ethical legal norms are the three pathways to realizing the human rights ethics view on human gene research.展开更多
In recent years,with the rapid development of software systems,the continuous expansion of software scale and the increasing complexity of systems have led to the emergence of a growing number of software metrics.Defe...In recent years,with the rapid development of software systems,the continuous expansion of software scale and the increasing complexity of systems have led to the emergence of a growing number of software metrics.Defect prediction methods based on software metric elements highly rely on software metric data.However,redundant software metric data is not conducive to efficient defect prediction,posing severe challenges to current software defect prediction tasks.To address these issues,this paper focuses on the rational clustering of software metric data.Firstly,multiple software projects are evaluated to determine the preset number of clusters for software metrics,and various clustering methods are employed to cluster the metric elements.Subsequently,a co-occurrence matrix is designed to comprehensively quantify the number of times that metrics appear in the same category.Based on the comprehensive results,the software metric data are divided into two semantic views containing different metrics,thereby analyzing the semantic information behind the software metrics.On this basis,this paper also conducts an in-depth analysis of the impact of different semantic view of metrics on defect prediction results,as well as the performance of various classification models under these semantic views.Experiments show that the joint use of the two semantic views can significantly improve the performance of models in software defect prediction,providing a new understanding and approach at the semantic view level for defect prediction research based on software metrics.展开更多
The increasing prevalence of multi-view data has made multi-view clustering a crucial technique for discovering latent structures from heterogeneous representations.However,traditional fuzzy clustering algorithms show...The increasing prevalence of multi-view data has made multi-view clustering a crucial technique for discovering latent structures from heterogeneous representations.However,traditional fuzzy clustering algorithms show limitations with the inherent uncertainty and imprecision of such data,as they rely on a single-dimensional membership value.To overcome these limitations,we propose an auto-weighted multi-view neutrosophic fuzzy clustering(AW-MVNFC)algorithm.Our method leverages the neutrosophic framework,an extension of fuzzy sets,to explicitly model imprecision and ambiguity through three membership degrees.The core novelty of AWMVNFC lies in a hierarchical weighting strategy that adaptively learns the contributions of both individual data views and the importance of each feature within a view.Through a unified objective function,AW-MVNFC jointly optimizes the neutrosophic membership assignments,cluster centers,and the distributions of view and feature weights.Comprehensive experiments conducted on synthetic and real-world datasets demonstrate that our algorithm achieves more accurate and stable clustering than existing methods,demonstrating its effectiveness in handling the complexities of multi-view data.展开更多
This paper is dedicated to constructing a theoretical framework for the identification and treatment of affective disorders in traditional Chinese medicine based on the“five-organ view”.Through in-depth analysis of ...This paper is dedicated to constructing a theoretical framework for the identification and treatment of affective disorders in traditional Chinese medicine based on the“five-organ view”.Through in-depth analysis of the theoretical connotation of the“five-organ concept”,we discussed the characteristics of the five-organ mechanism of affective-philosophical disorders in detail,systematically constructed a system of identification based on the association of the five organs,and proposed a comprehensive and holistic treatment strategy.The results of the study clearly show that the theoretical framework can provide systematic theoretical guidance for the clinical diagnosis and treatment of affective-philosophical disorders in Chinese medicine,help to improve the diagnostic and therapeutic effects of affective-philosophical disorders,and provide new ideas and methods for the theoretical development and clinical practice of affective-philosophical disorders in Chinese medicine,which is of important theoretical and practical significance,and can further promote the modernization of the development of affective-philosophical disorders in Chinese medicine.展开更多
Trends Traveler Issue6,2025 The Young Traveler The"Grand Tour,"a form of long distance travel that allows young adults to gain insights and broeden their view of the world,began to emerge around the world du...Trends Traveler Issue6,2025 The Young Traveler The"Grand Tour,"a form of long distance travel that allows young adults to gain insights and broeden their view of the world,began to emerge around the world during the Renaissance in Burope and the Tang Dynasty in China.展开更多
Urban environments offer a wealth of opportunities for residents to respite from their hectic life.Outdoor running or jogging becomes increasingly popular of an option.Impacts of urban environments on outdoor running,...Urban environments offer a wealth of opportunities for residents to respite from their hectic life.Outdoor running or jogging becomes increasingly popular of an option.Impacts of urban environments on outdoor running,despite some initial studies,remain underexplored.This study aims to establish an analytical framework that can holistically assess the urban environment on the healthy vitality of running.The proposed framework is applied to two modern Chinese cities,i.e.,Guangzhou and Shenzhen.We construct three interpretable random forest models to explore the non-linear relationship between environmental variables and running intensity(RI)through analyzing the runners'trajectories and integrating with multi-source urban big data(e.g.,street view imagery,remote sensing,and socio-economic data)across the built,natural,and social dimensions,The findings uncover that road density has the greatest impact on RI,and social variables(e.g.,population density and housing price)and natural variables(e.g.,slope and humidity)all make notable impact on outdoor running.Despite these findings,the impact of environmental variables likely change across different regions due to disparate regional construction and micro-environments,and those specific impacts as well as optimal thresholds also alter.Therefore,construction of healthy cities should take the whole urban environment into account and adapt to local conditions.This study provides a comprehensive evaluation on the influencing variables of healthy vitality and guides sustainable urban planning for creating running-friendly cities.展开更多
Human dignity is widely regarded as the foundation of modern human rights concepts and norms.The doctrine of human dignity in Chinese culture enjoys a long and profound history,and the pre-Qin assertion that“humans a...Human dignity is widely regarded as the foundation of modern human rights concepts and norms.The doctrine of human dignity in Chinese culture enjoys a long and profound history,and the pre-Qin assertion that“humans are the most precious”is the most representative expression of human dignity.Ancient Chinese scholars’elaboration on dignity was ethically oriented;they affirmed that humans have the freedom to make moral choices in spirit and required them to assume moral responsibilities towards others and society.Since modern times,with the changes of the times and the introduction of Western liberalism,the traditional view of moral dignity has seen a significant expansion of its scope,incorporating freedom in economic,political,and social life into the category of human dignity and establishing a closer connection with human rights.In contemporary China,under the guidance of Marxism,the view of dignity regards the free,comprehensive,and common development of human beings as the intrinsic requirement and external manifestation of human dignity,takes the rights to subsistence and development as the primary and fundamental human rights,and comprehensively safeguards the dignity of every individual through the coordinated protection of economic,political,social,and cultural rights.展开更多
Newspapers and magazines were primary media for Sino-Western cultural exchange in the early 19th century.The Chinese Repository,a monthly periodical founded by American missionary Elijah Bridgman in 1832,reported on C...Newspapers and magazines were primary media for Sino-Western cultural exchange in the early 19th century.The Chinese Repository,a monthly periodical founded by American missionary Elijah Bridgman in 1832,reported on Chinese social life as well as legal cases,system,and penalty.These reports served as a crucial window for the West to observe 19th-century Chinese criminal practices and significantly shaped Western perceptions of Chinese penal systems.Analysis of the periodical’s reports and reviews reveals a predominantly critical and negative Western view on China,arising from the collective Western impressions of China at the time and the identities and experiences of The Chinese Repository’s main contributors.The Western impressions of China formed during this period of time have had lasting negative impacts on Western legal demands towards China.Studies on the negative Western impressions of the Chinese view of legal penalty with a case study of The Chinese Repository offer valuable insights into the current Sino-Western legal cultural exchanges and dissemination.展开更多
The relationship between heaven and humanity is one of the fundamental philosophical foundations of ecological ethics in ancient Chinese Confucian thought.As a master of Confucian philosophy of mind,Wang Yangming inte...The relationship between heaven and humanity is one of the fundamental philosophical foundations of ecological ethics in ancient Chinese Confucian thought.As a master of Confucian philosophy of mind,Wang Yangming integrated the traditional Confucian discourse on the relationship between heaven and humanity into the principles of the philosophy of mind.Building on the traditional doctrine of benevolence centered on moral concern,he further developed an ecological view of‘benevolence as the unity of heaven and earth’.In his work Inquiry on the Great Learning,Wang Yangming systematically elaborated on this notion,emphasizing the philosophical expression of the relationship between humans and nature within an ethical framework and outlining the new implications of traditional Confucian ecological thought.This paper aims to analyze Wang Yangming’s ecological view of‘benevolence as the unity of heaven and earth’by examining the ecological ideas in his Inquiry on the Great Learning.On this basis,it seeks to refine the valuable achievements of traditional Chinese ecological civilization thought and strengthen the theoretical foundation of contemporary ecological ideas with Chinese characteristics.展开更多
Drone-based small object detection is of great significance in practical applications such as military actions, disaster rescue, transportation, etc. However, the severe scale differences in objects captured by drones...Drone-based small object detection is of great significance in practical applications such as military actions, disaster rescue, transportation, etc. However, the severe scale differences in objects captured by drones and lack of detail information for small-scale objects make drone-based small object detection a formidable challenge. To address these issues, we first develop a mathematical model to explore how changing receptive fields impacts the polynomial fitting results. Subsequently, based on the obtained conclusions, we propose a simple but effective Hybrid Receptive Field Network (HRFNet), whose modules include Hybrid Feature Augmentation (HFA), Hybrid Feature Pyramid (HFP) and Dual Scale Head (DSH). Specifically, HFA employs parallel dilated convolution kernels of different sizes to extend shallow features with different receptive fields, committed to improving the multi-scale adaptability of the network;HFP enhances the perception of small objects by capturing contextual information across layers, while DSH reconstructs the original prediction head utilizing a set of high-resolution features and ultrahigh-resolution features. In addition, in order to train HRFNet, the corresponding dual-scale loss function is designed. Finally, comprehensive evaluation results on public benchmarks such as VisDrone-DET and TinyPerson demonstrate the robustness of the proposed method. Most impressively, the proposed HRFNet achieves a mAP of 51.0 on VisDrone-DET with 29.3 M parameters, which outperforms the extant state-of-the-art detectors. HRFNet also performs excellently in complex scenarios captured by drones, achieving the best performance on the CS-Drone dataset we built.展开更多
The growing number of COVID-19 cases puts pressure on healthcare services and public institutions worldwide.The pandemic has brought much uncertainty to the global economy and the situation in general.Forecasting meth...The growing number of COVID-19 cases puts pressure on healthcare services and public institutions worldwide.The pandemic has brought much uncertainty to the global economy and the situation in general.Forecasting methods and modeling techniques are important tools for governments to manage critical situations caused by pandemics,which have negative impact on public health.The main purpose of this study is to obtain short-term forecasts of disease epidemiology that could be useful for policymakers and public institutions to make necessary short-term decisions.To evaluate the effectiveness of the proposed attention-based method combining certain data mining algorithms and the classical ARIMA model for short-term forecasts,data on the spread of the COVID-19 virus in Lithuania is used,the forecasts of epidemic dynamics were examined,and the results were presented in the study.Nevertheless,the approach presented might be applied to any country and other pandemic situations.The COVID-19 outbreak started at different times in different countries,hence some countries have a longer history of the disease with more historical data than others.The paper proposes a novel approach to data registration and machine learning-based analysis using data from attention-based countries for forecast validation to predict trends of the spread of COVID-19 and assess risks.展开更多
基金funded by Naif Arab University for Security Sciences under grant No.NAUSS-23-R11.
文摘In the current digital era,new technologies are becoming an essential part of our lives.Consequently,the number ofmalicious software ormalware attacks is rapidly growing.There is no doubt,themajority ofmalware attacks can be detected by most antivirus programs.However,such types of antivirus programs are one step behind malicious software.Due to these dilemmas,deep learning become popular in the detection and classification of malicious data.Therefore,researchers have significantly focused on finding solutions for malware attacks by analyzing malicious samples with the help of different techniques and models.In this research,we presented a lightweight attention-based novel deep Convolutional Neural Network(DNN-CNN)model for binary and multi-class malware classification,including benign,trojan horse,ransomware,and spyware.We applied the Principal Component Analysis(PCA)technique for feature extraction for binary classification.We used the Synthetic Minority Oversampling Technique(SMOTE)to handle the imbalanced data during multi-class classification.Our proposed attention-based malware detectionmodel is trained on the benchmarkmalware memory dataset named CIC-MalMem-2022.Theresults indicate that our model obtained high accuracy for binary and multi-class classification,99.5% and 97.9%,respectively.
基金supported by the National Natural Science Foundation of China under Grant Nos.62076117 and 62166026the Jiangxi Provincial Key Laboratory of Virtual Reality under Grant No.2024SSY03151.
文摘Dynamic sign language recognition holds significant importance, particularly with the application of deep learning to address its complexity. However, existing methods face several challenges. Firstly, recognizing dynamic sign language requires identifying keyframes that best represent the signs, and missing these keyframes reduces accuracy. Secondly, some methods do not focus enough on hand regions, which are small within the overall frame, leading to information loss. To address these challenges, we propose a novel Video Transformer Attention-based Network (VTAN) for dynamic sign language recognition. Our approach prioritizes informative frames and hand regions effectively. To tackle the first issue, we designed a keyframe extraction module enhanced by a convolutional autoencoder, which focuses on selecting information-rich frames and eliminating redundant ones from the video sequences. For the second issue, we developed a soft attention-based transformer module that emphasizes extracting features from hand regions, ensuring that the network pays more attention to hand information within sequences. This dual-focus approach improves effective dynamic sign language recognition by addressing the key challenges of identifying critical frames and emphasizing hand regions. Experimental results on two public benchmark datasets demonstrate the effectiveness of our network, outperforming most of the typical methods in sign language recognition tasks.
基金the National Natural Science Foundation of China under Grant 62172059 and 62072055Hunan Provincial Natural Science Foundations of China under Grant 2022JJ50318 and 2022JJ30621Scientific Research Fund of Hunan Provincial Education Department of China under Grant 22A0200 and 20K098。
文摘Electrocardiogram(ECG)signal is one of the noninvasive physiological measurement techniques commonly usedin cardiac diagnosis.However,in real scenarios,the ECGsignal is susceptible to various noise erosion,which affectsthe subsequent pathological analysis.Therefore,the effective removal of the noise from ECG signals has becomea top priority in cardiac diagnostic research.Aiming at the problem of incomplete signal shape retention andlow signal-to-noise ratio(SNR)after denoising,a novel ECG denoising network,named attention-based residualdense shrinkage network(ARDSN),is proposed in this paper.Firstly,the shallow ECG characteristics are extractedby a shallow feature extraction network(SFEN).Then,the residual dense shrinkage attention block(RDSAB)isused for adaptive noise suppression.Finally,feature fusion representation(FFR)is performed on the hierarchicalfeatures extracted by a series of RDSABs to reconstruct the de-noised ECG signal.Experiments on the MIT-BIHarrhythmia database and MIT-BIH noise stress test database indicate that the proposed scheme can effectively resistthe interference of different sources of noise on the ECG signal.
基金This paper is an interim result of“Constitutional Boundaries of the Application of Human Gene Editing Technology,”a Youth Project of the National Social Science Fund of China(Project Approval Number 23CFX040)supported by the“National Funded Programs for Postdoctoral Researchers”(GZC20230937).
文摘The establishment of a sound science and technology ethics governance system is an inevitable requirement for national modernization.Faced with the development of human gene technology and the chaos in research activities,the ethical standards and legal positioning of human gene research activities urgently need to be clarified.The human rights ethics view has value inclusiveness and value fundamentality,and includes three levels of connotations:content dimension,relationship dimension,and obligation dimension.It should serve as the ethical standard for human gene research activities.Based on the provisions of China’s Constitution,the human rights ethics view on human gene research,as a constitutional ethics view,can elucidate different levels of rights content,such as human dignity,life and health,and research freedom.It also addresses the weighing of basic rights conflicts and the dual obligation subjects of public and private nature.Relying on the constitutional value embedding of the research ethics view to form ethical consensus,improving ethical review through framework legislation for human rights interests,and implementing ethical responsibility through the human rights-oriented interpretation of ethical legal norms are the three pathways to realizing the human rights ethics view on human gene research.
基金supported by the CCF-NSFOCUS‘Kunpeng’Research Fund(CCF-NSFOCUS2024012).
文摘In recent years,with the rapid development of software systems,the continuous expansion of software scale and the increasing complexity of systems have led to the emergence of a growing number of software metrics.Defect prediction methods based on software metric elements highly rely on software metric data.However,redundant software metric data is not conducive to efficient defect prediction,posing severe challenges to current software defect prediction tasks.To address these issues,this paper focuses on the rational clustering of software metric data.Firstly,multiple software projects are evaluated to determine the preset number of clusters for software metrics,and various clustering methods are employed to cluster the metric elements.Subsequently,a co-occurrence matrix is designed to comprehensively quantify the number of times that metrics appear in the same category.Based on the comprehensive results,the software metric data are divided into two semantic views containing different metrics,thereby analyzing the semantic information behind the software metrics.On this basis,this paper also conducts an in-depth analysis of the impact of different semantic view of metrics on defect prediction results,as well as the performance of various classification models under these semantic views.Experiments show that the joint use of the two semantic views can significantly improve the performance of models in software defect prediction,providing a new understanding and approach at the semantic view level for defect prediction research based on software metrics.
文摘The increasing prevalence of multi-view data has made multi-view clustering a crucial technique for discovering latent structures from heterogeneous representations.However,traditional fuzzy clustering algorithms show limitations with the inherent uncertainty and imprecision of such data,as they rely on a single-dimensional membership value.To overcome these limitations,we propose an auto-weighted multi-view neutrosophic fuzzy clustering(AW-MVNFC)algorithm.Our method leverages the neutrosophic framework,an extension of fuzzy sets,to explicitly model imprecision and ambiguity through three membership degrees.The core novelty of AWMVNFC lies in a hierarchical weighting strategy that adaptively learns the contributions of both individual data views and the importance of each feature within a view.Through a unified objective function,AW-MVNFC jointly optimizes the neutrosophic membership assignments,cluster centers,and the distributions of view and feature weights.Comprehensive experiments conducted on synthetic and real-world datasets demonstrate that our algorithm achieves more accurate and stable clustering than existing methods,demonstrating its effectiveness in handling the complexities of multi-view data.
文摘This paper is dedicated to constructing a theoretical framework for the identification and treatment of affective disorders in traditional Chinese medicine based on the“five-organ view”.Through in-depth analysis of the theoretical connotation of the“five-organ concept”,we discussed the characteristics of the five-organ mechanism of affective-philosophical disorders in detail,systematically constructed a system of identification based on the association of the five organs,and proposed a comprehensive and holistic treatment strategy.The results of the study clearly show that the theoretical framework can provide systematic theoretical guidance for the clinical diagnosis and treatment of affective-philosophical disorders in Chinese medicine,help to improve the diagnostic and therapeutic effects of affective-philosophical disorders,and provide new ideas and methods for the theoretical development and clinical practice of affective-philosophical disorders in Chinese medicine,which is of important theoretical and practical significance,and can further promote the modernization of the development of affective-philosophical disorders in Chinese medicine.
文摘Trends Traveler Issue6,2025 The Young Traveler The"Grand Tour,"a form of long distance travel that allows young adults to gain insights and broeden their view of the world,began to emerge around the world during the Renaissance in Burope and the Tang Dynasty in China.
基金National Natural Science Foundation of China,No.42171455The Hong Kong RGC Research Impact Fund,No.R5011-23The Hong Kong General Research Fund,No.15204121。
文摘Urban environments offer a wealth of opportunities for residents to respite from their hectic life.Outdoor running or jogging becomes increasingly popular of an option.Impacts of urban environments on outdoor running,despite some initial studies,remain underexplored.This study aims to establish an analytical framework that can holistically assess the urban environment on the healthy vitality of running.The proposed framework is applied to two modern Chinese cities,i.e.,Guangzhou and Shenzhen.We construct three interpretable random forest models to explore the non-linear relationship between environmental variables and running intensity(RI)through analyzing the runners'trajectories and integrating with multi-source urban big data(e.g.,street view imagery,remote sensing,and socio-economic data)across the built,natural,and social dimensions,The findings uncover that road density has the greatest impact on RI,and social variables(e.g.,population density and housing price)and natural variables(e.g.,slope and humidity)all make notable impact on outdoor running.Despite these findings,the impact of environmental variables likely change across different regions due to disparate regional construction and micro-environments,and those specific impacts as well as optimal thresholds also alter.Therefore,construction of healthy cities should take the whole urban environment into account and adapt to local conditions.This study provides a comprehensive evaluation on the influencing variables of healthy vitality and guides sustainable urban planning for creating running-friendly cities.
基金“Research on the Content and Realization Methods of Citizens’Participation Rights,”a major project(Project Number 21JJD820003)funded by the National Human Rights Education and Training Base of the Ministry of Education of China.
文摘Human dignity is widely regarded as the foundation of modern human rights concepts and norms.The doctrine of human dignity in Chinese culture enjoys a long and profound history,and the pre-Qin assertion that“humans are the most precious”is the most representative expression of human dignity.Ancient Chinese scholars’elaboration on dignity was ethically oriented;they affirmed that humans have the freedom to make moral choices in spirit and required them to assume moral responsibilities towards others and society.Since modern times,with the changes of the times and the introduction of Western liberalism,the traditional view of moral dignity has seen a significant expansion of its scope,incorporating freedom in economic,political,and social life into the category of human dignity and establishing a closer connection with human rights.In contemporary China,under the guidance of Marxism,the view of dignity regards the free,comprehensive,and common development of human beings as the intrinsic requirement and external manifestation of human dignity,takes the rights to subsistence and development as the primary and fundamental human rights,and comprehensively safeguards the dignity of every individual through the coordinated protection of economic,political,social,and cultural rights.
基金Supported by the National Social Science Fund General Project titled“The Millard’s Review and the Study of Sino-American Legal Civilization Exchange in the First Half of the 20th Century”.
文摘Newspapers and magazines were primary media for Sino-Western cultural exchange in the early 19th century.The Chinese Repository,a monthly periodical founded by American missionary Elijah Bridgman in 1832,reported on Chinese social life as well as legal cases,system,and penalty.These reports served as a crucial window for the West to observe 19th-century Chinese criminal practices and significantly shaped Western perceptions of Chinese penal systems.Analysis of the periodical’s reports and reviews reveals a predominantly critical and negative Western view on China,arising from the collective Western impressions of China at the time and the identities and experiences of The Chinese Repository’s main contributors.The Western impressions of China formed during this period of time have had lasting negative impacts on Western legal demands towards China.Studies on the negative Western impressions of the Chinese view of legal penalty with a case study of The Chinese Repository offer valuable insights into the current Sino-Western legal cultural exchanges and dissemination.
文摘The relationship between heaven and humanity is one of the fundamental philosophical foundations of ecological ethics in ancient Chinese Confucian thought.As a master of Confucian philosophy of mind,Wang Yangming integrated the traditional Confucian discourse on the relationship between heaven and humanity into the principles of the philosophy of mind.Building on the traditional doctrine of benevolence centered on moral concern,he further developed an ecological view of‘benevolence as the unity of heaven and earth’.In his work Inquiry on the Great Learning,Wang Yangming systematically elaborated on this notion,emphasizing the philosophical expression of the relationship between humans and nature within an ethical framework and outlining the new implications of traditional Confucian ecological thought.This paper aims to analyze Wang Yangming’s ecological view of‘benevolence as the unity of heaven and earth’by examining the ecological ideas in his Inquiry on the Great Learning.On this basis,it seeks to refine the valuable achievements of traditional Chinese ecological civilization thought and strengthen the theoretical foundation of contemporary ecological ideas with Chinese characteristics.
基金supported by the National Natural Science Foundation of China(Nos.62276204 and 62203343)the Fundamental Research Funds for the Central Universities(No.YJSJ24011)+1 种基金the Natural Science Basic Research Program of Shanxi,China(Nos.2022JM-340 and 2023-JC-QN-0710)the China Postdoctoral Science Foundation(Nos.2020T130494 and 2018M633470).
文摘Drone-based small object detection is of great significance in practical applications such as military actions, disaster rescue, transportation, etc. However, the severe scale differences in objects captured by drones and lack of detail information for small-scale objects make drone-based small object detection a formidable challenge. To address these issues, we first develop a mathematical model to explore how changing receptive fields impacts the polynomial fitting results. Subsequently, based on the obtained conclusions, we propose a simple but effective Hybrid Receptive Field Network (HRFNet), whose modules include Hybrid Feature Augmentation (HFA), Hybrid Feature Pyramid (HFP) and Dual Scale Head (DSH). Specifically, HFA employs parallel dilated convolution kernels of different sizes to extend shallow features with different receptive fields, committed to improving the multi-scale adaptability of the network;HFP enhances the perception of small objects by capturing contextual information across layers, while DSH reconstructs the original prediction head utilizing a set of high-resolution features and ultrahigh-resolution features. In addition, in order to train HRFNet, the corresponding dual-scale loss function is designed. Finally, comprehensive evaluation results on public benchmarks such as VisDrone-DET and TinyPerson demonstrate the robustness of the proposed method. Most impressively, the proposed HRFNet achieves a mAP of 51.0 on VisDrone-DET with 29.3 M parameters, which outperforms the extant state-of-the-art detectors. HRFNet also performs excellently in complex scenarios captured by drones, achieving the best performance on the CS-Drone dataset we built.
基金This project has received funding from the Research Council of Lithuania(LMTLT),agreement No S-COV-20-4.
文摘The growing number of COVID-19 cases puts pressure on healthcare services and public institutions worldwide.The pandemic has brought much uncertainty to the global economy and the situation in general.Forecasting methods and modeling techniques are important tools for governments to manage critical situations caused by pandemics,which have negative impact on public health.The main purpose of this study is to obtain short-term forecasts of disease epidemiology that could be useful for policymakers and public institutions to make necessary short-term decisions.To evaluate the effectiveness of the proposed attention-based method combining certain data mining algorithms and the classical ARIMA model for short-term forecasts,data on the spread of the COVID-19 virus in Lithuania is used,the forecasts of epidemic dynamics were examined,and the results were presented in the study.Nevertheless,the approach presented might be applied to any country and other pandemic situations.The COVID-19 outbreak started at different times in different countries,hence some countries have a longer history of the disease with more historical data than others.The paper proposes a novel approach to data registration and machine learning-based analysis using data from attention-based countries for forecast validation to predict trends of the spread of COVID-19 and assess risks.
