In this work,we compute the Grothendieck groups of finite 2-Calabi-Yau triangulated categories with maximal rigid objects which are not cluster tilting.These finite 2-Calabi-Yau triangulated categories are divided int...In this work,we compute the Grothendieck groups of finite 2-Calabi-Yau triangulated categories with maximal rigid objects which are not cluster tilting.These finite 2-Calabi-Yau triangulated categories are divided into,by the work of Amiot[Bull.Soc.Math.France,2007,135(3):435-474](see also[Adv.Math.,2008,217(6):2443-2484]and[J.Algebra,2016,446:426-449]),three classes:type A,type D and type E.展开更多
Semantic segmentation of novel object categories with limited labeled data remains a challenging problem in computer vision.Few-shot segmentation methods aim to address this problem by recognizing objects from specifi...Semantic segmentation of novel object categories with limited labeled data remains a challenging problem in computer vision.Few-shot segmentation methods aim to address this problem by recognizing objects from specific target classes with a few provided examples.Previous approaches for few-shot semantic segmentation typically represent target classes using class prototypes.These prototypes are matched with the features of the query set to get segmentation results.However,class prototypes are usually obtained by applying global average pooling on masked support images.Global pooling discards much structural information,which may reduce the accuracy of model predictions.To address this issue,we propose a Category-Guided Frequency Modulation(CGFM)method.CGFM is designed to learn category-specific information in the frequency space and leverage it to provide a twostage guidance for the segmentation process.First,to self-adaptively activate class-relevant frequency bands while suppressing irrelevant ones,we leverage the Dual-Perception Gaussian Band Pre-activation(DPGBP)module to generate Gaussian filters using class embedding vectors.Second,to further enhance category-relevant frequency components in activated bands,we design a Support-Guided Category Response Enhancement(SGCRE)module to effectively introduce support frequency components into the modulation of query frequency features.Experiments on the PASCAL-5^(i) and COCO-20^(i) datasets demonstrate the promising performance of our model.展开更多
The article presents an original concept of a universal philosophical language capable of transcending the boundaries between individual sciences and serving as a foundation for transdisciplinary thinking.This approac...The article presents an original concept of a universal philosophical language capable of transcending the boundaries between individual sciences and serving as a foundation for transdisciplinary thinking.This approach,developed by the author since the 1980s,is based on particular and general comparative concepts-concepts of practical mind and categories of pure mind.Therefore,the key element of the concept is the category of"particular and general",which fundamentally differs from the traditional category of"part and whole".This allows for the description of both structural and functional aspects of complex systems not only at the interdisciplinary but also at the transdisciplinary level.The primary categories of thought-Identity,Difference,Correlated,Opposite,and others-are regarded as universal notions that connect levels of reality and ensure the integration of individual sciences.Unlike contemporary transdisciplinary concepts based on Basarab Nicolescu's logic of the included middle and Edgar Morin's dialogics,the author's theory is built on the ultimate general Hegelian notion of"concrete identity"and its differentiation into a multitude of"concrete differences"-comparative concepts.As a result,a unique philosophical language has been developed,presented within the framework of the Philosophical Matrix as a system of categories of pure mind capable of describing the dynamics and wholeness of complex processes at the transdisciplinary level.The article is intended for researchers interested in the philosophical foundations of transdisciplinarity,the theory of complexity,and the development of universal categories of thought.展开更多
With the purpose of improving the accuracy of text categorization and reducing the dimension of the feature space,this paper proposes a two-stage feature selection method based on a novel category correlation degree(C...With the purpose of improving the accuracy of text categorization and reducing the dimension of the feature space,this paper proposes a two-stage feature selection method based on a novel category correlation degree(CCD)method and latent semantic indexing(LSI).In the first stage,a novel CCD method is proposed to select the most effective features for text classification,which is more effective than the traditional feature selection method.In the second stage,document representation requires a high dimensionality of the feature space and does not take into account the semantic relation between features,which leads to a poor categorization accuracy.So LSI method is proposed to solve these problems by using statistically derived conceptual indices to replace the individual terms which can discover the important correlative relationship between features and reduce the feature space dimension.Firstly,each feature in our algorithm is ranked depending on their importance of classification using CCD method.Secondly,we construct a new semantic space based on LSI method among features.The experimental results have proved that our method can reduce effectively the dimension of text vector and improve the performance of text categorization.展开更多
Let A be an abelian category,T a self-orthogonal subcategory of A and each object in T admit finite projective and injective dimensions.If the left Gorenstein subcategory lG(T)equals to the right orthogonal class of T...Let A be an abelian category,T a self-orthogonal subcategory of A and each object in T admit finite projective and injective dimensions.If the left Gorenstein subcategory lG(T)equals to the right orthogonal class of T and the right Gorenstein subcategory rG(T)equals to the left orthogonal class of T,we prove that the Gorenstein subcategory G(T)equals to the intersection of the left orthogonal class of T and the right orthogonal class of T,and prove that their stable categories are triangle equivalent to the relative singularity category of A with respect to T.As applications,let R be a left Noetherian ring with finite left self-injective dimension and _(R)C_(S) a semidualizing bimodule,and let the supremum of the flat dimensions of all injective left R-modules be finite.We prove that if RC has finite injective(or flat)dimension and the right orthogonal class of C contains R,then there exists a triangle-equivalence between the intersection of C-Gorenstein projective modules and Bass class with respect to C,and the relative singularity category with respect to C-projective modules.Some classical results are generalized.展开更多
Objectives: This study aims to explore the latent categories of mental health literacy among patients with coronary artery disease and examine their associations with quality of life. Design: A cross-sectional quantit...Objectives: This study aims to explore the latent categories of mental health literacy among patients with coronary artery disease and examine their associations with quality of life. Design: A cross-sectional quantitative design was used. Methods: The study sample consisted of 208 patients with coronary artery disease from five wards in the Department of Cardiology at a tertiary hospital. Data were collected using a general information questionnaire, the Chinese version of the Multiple Mental Health Literacy Scale and the Chinese Cardiovascular Patient Quality of Life Assessment Questionnaire. The data were analysed with Mplus (v.8.3) and SPSS (v.25.0). Results: The mental health literacy of the 208 patients was categorised into four latent categories: low literacy (n = 28, 13.5%), high knowledge-low resources (n = 53, 25.5%), low knowledge-high resources (n = 63, 30.2%) and high literacy (n = 64, 30.8%). A significant difference in quality of life was observed according to mental health literacy category (P Conclusion: The quality of life of patients with coronary artery disease is significantly influenced by their levels of mental health literacy. Targeted interventions addressing the various profiles of mental health literacy should be implemented to improve the quality of life for patients with coronary artery disease.展开更多
This study focuses on the analysis of the Chinese composition writing performance of fourth,fifth,and sixth grade students in 16 selected schools in Longhua District,Shenzhen during the spring semester of 2023.Using L...This study focuses on the analysis of the Chinese composition writing performance of fourth,fifth,and sixth grade students in 16 selected schools in Longhua District,Shenzhen during the spring semester of 2023.Using LIWC(Linguistic Inquiry and Word Count)as a text analysis tool,the study explores the impact of LIWC categories on writing performance which is scaled by score.The results show that the simple LIWC word categories have a significant positive influence on the composition scores of lower-grade students;while complex LIWC word categories have a significant negative influence on the composition scores of lower-grade students but a significant positive influence on the composition scores of higher-grade students.Process word categories have a positive influence on the composition scores of all three grades,but the impact of complex process word categories increases as the grade level rises.展开更多
To better understand the challenges faced by public hospitals in implementing charitable medical assistance,this study examines Nanjing R Hospital as a case study.By combining literature review and field research,the ...To better understand the challenges faced by public hospitals in implementing charitable medical assistance,this study examines Nanjing R Hospital as a case study.By combining literature review and field research,the current status and fundamental methods of charitable medical assistance at R Hospital are systematically analyzed.The findings indicate that medical social workers play a multifaceted role in the hospital’s charitable assistance efforts.They contribute significantly to building assistance networks and addressing patients’multi-dimensional needs.However,challenges persist in the assistance process,including both external and internal obstacles.This study explores ways to overcome these barriers to enhance the efficient utilization of healthcare resources.Through empirical investigation,the study identifies the types of charitable aid resources available and highlights the practical difficulties in their application within public hospitals.These findings provide a valuable reference for optimizing resource allocation,improving the effectiveness of assistance programs,and fostering institutional collaboration.展开更多
Being different from testing for popular GUI software, the “instruction-category” approach is proposed for testing embedded system. This approach is constructed by three steps including refining items, drawing instr...Being different from testing for popular GUI software, the “instruction-category” approach is proposed for testing embedded system. This approach is constructed by three steps including refining items, drawing instruction-brief and instruction-category, and constructing test suite. Consequently, this approach is adopted to test oven embedded system, and detail process is deeply discussed. As a result, the factual result indicates that the “instruction-category” approach can be effectively applied in embedded system testing as a black-box method for conformity testing.展开更多
文摘In this work,we compute the Grothendieck groups of finite 2-Calabi-Yau triangulated categories with maximal rigid objects which are not cluster tilting.These finite 2-Calabi-Yau triangulated categories are divided into,by the work of Amiot[Bull.Soc.Math.France,2007,135(3):435-474](see also[Adv.Math.,2008,217(6):2443-2484]and[J.Algebra,2016,446:426-449]),three classes:type A,type D and type E.
文摘Semantic segmentation of novel object categories with limited labeled data remains a challenging problem in computer vision.Few-shot segmentation methods aim to address this problem by recognizing objects from specific target classes with a few provided examples.Previous approaches for few-shot semantic segmentation typically represent target classes using class prototypes.These prototypes are matched with the features of the query set to get segmentation results.However,class prototypes are usually obtained by applying global average pooling on masked support images.Global pooling discards much structural information,which may reduce the accuracy of model predictions.To address this issue,we propose a Category-Guided Frequency Modulation(CGFM)method.CGFM is designed to learn category-specific information in the frequency space and leverage it to provide a twostage guidance for the segmentation process.First,to self-adaptively activate class-relevant frequency bands while suppressing irrelevant ones,we leverage the Dual-Perception Gaussian Band Pre-activation(DPGBP)module to generate Gaussian filters using class embedding vectors.Second,to further enhance category-relevant frequency components in activated bands,we design a Support-Guided Category Response Enhancement(SGCRE)module to effectively introduce support frequency components into the modulation of query frequency features.Experiments on the PASCAL-5^(i) and COCO-20^(i) datasets demonstrate the promising performance of our model.
文摘The article presents an original concept of a universal philosophical language capable of transcending the boundaries between individual sciences and serving as a foundation for transdisciplinary thinking.This approach,developed by the author since the 1980s,is based on particular and general comparative concepts-concepts of practical mind and categories of pure mind.Therefore,the key element of the concept is the category of"particular and general",which fundamentally differs from the traditional category of"part and whole".This allows for the description of both structural and functional aspects of complex systems not only at the interdisciplinary but also at the transdisciplinary level.The primary categories of thought-Identity,Difference,Correlated,Opposite,and others-are regarded as universal notions that connect levels of reality and ensure the integration of individual sciences.Unlike contemporary transdisciplinary concepts based on Basarab Nicolescu's logic of the included middle and Edgar Morin's dialogics,the author's theory is built on the ultimate general Hegelian notion of"concrete identity"and its differentiation into a multitude of"concrete differences"-comparative concepts.As a result,a unique philosophical language has been developed,presented within the framework of the Philosophical Matrix as a system of categories of pure mind capable of describing the dynamics and wholeness of complex processes at the transdisciplinary level.The article is intended for researchers interested in the philosophical foundations of transdisciplinarity,the theory of complexity,and the development of universal categories of thought.
基金the National Natural Science Foundation of China(Nos.61073193 and 61300230)the Key Science and Technology Foundation of Gansu Province(No.1102FKDA010)+1 种基金the Natural Science Foundation of Gansu Province(No.1107RJZA188)the Science and Technology Support Program of Gansu Province(No.1104GKCA037)
文摘With the purpose of improving the accuracy of text categorization and reducing the dimension of the feature space,this paper proposes a two-stage feature selection method based on a novel category correlation degree(CCD)method and latent semantic indexing(LSI).In the first stage,a novel CCD method is proposed to select the most effective features for text classification,which is more effective than the traditional feature selection method.In the second stage,document representation requires a high dimensionality of the feature space and does not take into account the semantic relation between features,which leads to a poor categorization accuracy.So LSI method is proposed to solve these problems by using statistically derived conceptual indices to replace the individual terms which can discover the important correlative relationship between features and reduce the feature space dimension.Firstly,each feature in our algorithm is ranked depending on their importance of classification using CCD method.Secondly,we construct a new semantic space based on LSI method among features.The experimental results have proved that our method can reduce effectively the dimension of text vector and improve the performance of text categorization.
基金Supported by the Project of Natural Science Foundation of Changzhou College of Information Technology(Grant No.CXZK202204Y)the Project of Youth Innovation Team of Universities of Shandong Province(Grant No.2022KJ314)。
文摘Let A be an abelian category,T a self-orthogonal subcategory of A and each object in T admit finite projective and injective dimensions.If the left Gorenstein subcategory lG(T)equals to the right orthogonal class of T and the right Gorenstein subcategory rG(T)equals to the left orthogonal class of T,we prove that the Gorenstein subcategory G(T)equals to the intersection of the left orthogonal class of T and the right orthogonal class of T,and prove that their stable categories are triangle equivalent to the relative singularity category of A with respect to T.As applications,let R be a left Noetherian ring with finite left self-injective dimension and _(R)C_(S) a semidualizing bimodule,and let the supremum of the flat dimensions of all injective left R-modules be finite.We prove that if RC has finite injective(or flat)dimension and the right orthogonal class of C contains R,then there exists a triangle-equivalence between the intersection of C-Gorenstein projective modules and Bass class with respect to C,and the relative singularity category with respect to C-projective modules.Some classical results are generalized.
文摘Objectives: This study aims to explore the latent categories of mental health literacy among patients with coronary artery disease and examine their associations with quality of life. Design: A cross-sectional quantitative design was used. Methods: The study sample consisted of 208 patients with coronary artery disease from five wards in the Department of Cardiology at a tertiary hospital. Data were collected using a general information questionnaire, the Chinese version of the Multiple Mental Health Literacy Scale and the Chinese Cardiovascular Patient Quality of Life Assessment Questionnaire. The data were analysed with Mplus (v.8.3) and SPSS (v.25.0). Results: The mental health literacy of the 208 patients was categorised into four latent categories: low literacy (n = 28, 13.5%), high knowledge-low resources (n = 53, 25.5%), low knowledge-high resources (n = 63, 30.2%) and high literacy (n = 64, 30.8%). A significant difference in quality of life was observed according to mental health literacy category (P Conclusion: The quality of life of patients with coronary artery disease is significantly influenced by their levels of mental health literacy. Targeted interventions addressing the various profiles of mental health literacy should be implemented to improve the quality of life for patients with coronary artery disease.
文摘This study focuses on the analysis of the Chinese composition writing performance of fourth,fifth,and sixth grade students in 16 selected schools in Longhua District,Shenzhen during the spring semester of 2023.Using LIWC(Linguistic Inquiry and Word Count)as a text analysis tool,the study explores the impact of LIWC categories on writing performance which is scaled by score.The results show that the simple LIWC word categories have a significant positive influence on the composition scores of lower-grade students;while complex LIWC word categories have a significant negative influence on the composition scores of lower-grade students but a significant positive influence on the composition scores of higher-grade students.Process word categories have a positive influence on the composition scores of all three grades,but the impact of complex process word categories increases as the grade level rises.
文摘To better understand the challenges faced by public hospitals in implementing charitable medical assistance,this study examines Nanjing R Hospital as a case study.By combining literature review and field research,the current status and fundamental methods of charitable medical assistance at R Hospital are systematically analyzed.The findings indicate that medical social workers play a multifaceted role in the hospital’s charitable assistance efforts.They contribute significantly to building assistance networks and addressing patients’multi-dimensional needs.However,challenges persist in the assistance process,including both external and internal obstacles.This study explores ways to overcome these barriers to enhance the efficient utilization of healthcare resources.Through empirical investigation,the study identifies the types of charitable aid resources available and highlights the practical difficulties in their application within public hospitals.These findings provide a valuable reference for optimizing resource allocation,improving the effectiveness of assistance programs,and fostering institutional collaboration.
文摘Being different from testing for popular GUI software, the “instruction-category” approach is proposed for testing embedded system. This approach is constructed by three steps including refining items, drawing instruction-brief and instruction-category, and constructing test suite. Consequently, this approach is adopted to test oven embedded system, and detail process is deeply discussed. As a result, the factual result indicates that the “instruction-category” approach can be effectively applied in embedded system testing as a black-box method for conformity testing.
