Retinal blood vessel segmentation is crucial for diagnosing ocular and cardiovascular diseases.Although the introduction of U-Net in 2015 by Olaf Ronneberger significantly advanced this field,yet issues like limited t...Retinal blood vessel segmentation is crucial for diagnosing ocular and cardiovascular diseases.Although the introduction of U-Net in 2015 by Olaf Ronneberger significantly advanced this field,yet issues like limited training data,imbalance data distribution,and inadequate feature extraction persist,hindering both the segmentation performance and optimal model generalization.Addressing these critical issues,the DEFFA-Unet is proposed featuring an additional encoder to process domain-invariant pre-processed inputs,thereby improving both richer feature encoding and enhanced model generalization.A feature filtering fusion module is developed to ensure the precise feature filtering and robust hybrid feature fusion.In response to the task-specific need for higher precision where false positives are very costly,traditional skip connections are replaced with the attention-guided feature reconstructing fusion module.Additionally,innovative data augmentation and balancing methods are proposed to counter data scarcity and distribution imbalance,further boosting the robustness and generalization of the model.With a comprehensive suite of evaluation metrics,extensive validations on four benchmark datasets(DRIVE,CHASEDB1,STARE,and HRF)and an SLO dataset(IOSTAR),demonstrate the proposed method’s superiority over both baseline and state-of-the-art models.Particularly the proposed method significantly outperforms the compared methods in cross-validation model generalization.展开更多
BACKGROUND The coronavirus disease 2019(COVID-19)outbreak lasted several months,having started in December 2019.This study aimed to report the impacts of various factors on the depression levels of the general public ...BACKGROUND The coronavirus disease 2019(COVID-19)outbreak lasted several months,having started in December 2019.This study aimed to report the impacts of various factors on the depression levels of the general public and ascertain how emotional measures could be affected by psychosocial factors during the COVID-19 pandemic.AIM To investigate the depression levels of the general public in China during the COVID-19 pandemic.METHODS A total of 2001 self-reported questionnaires about Beck Depression Inventory(BDI)were collected on August 22,2022 via the website.Each questionnaire included four levels of depression and other demographic information.The BDI scores and incidences of different depression levels were compared between various groups of respondents.χ2 analysis and the two-tailed t-test were used to assess categorical and continuous data,respectively.Multiple linear regressions and logistic regressions were employed for correlation analysis.RESULTS The averaged BDI score in this study was higher than that for the non-epidemic periods,as reported in previous studies.Even higher BDI scores and incidences of moderate and severe depression were recorded for people who were quarantined for suspected COVID-19 infection,compared to the respondents who were not quarantined.The participants who did not take protective measures were associated with higher BDI scores than those who made efforts to keep themselves relatively safer.Similarly,the people who did not return to work had higher BDI scores compared to those managed to.A significant association existed between the depression levels of the subgroups and each of the factors,except gender and location of residence.However,quarantine was the most relative predictor for depression levels,followed by failure to take preventive measures and losing a partner,either through divorce or death.CONCLUSION Based on these data,psychological interventions for the various subpopulations in the general public can be implemented during and after the COVID-19 pandemic.Other countries can also use the data as a reference.展开更多
随着老龄化与数字化的深度融合,老年群体逐渐成为网络购物的重要消费力量。本文基于解释结构模型(ISM),梳理了影响老年人网络购物行为的多维因素,并构建层级结构模型。研究发现,老年人网络购物行为受表层经验(科技便捷性、信任安全性)...随着老龄化与数字化的深度融合,老年群体逐渐成为网络购物的重要消费力量。本文基于解释结构模型(ISM),梳理了影响老年人网络购物行为的多维因素,并构建层级结构模型。研究发现,老年人网络购物行为受表层经验(科技便捷性、信任安全性)、中介因素(数字技能、健康状况、政策支持及消费风险感知)和深层驱动力(自主性需求、经济地位、社会交互)三大维度的综合影响。其中,科技便捷性和信任安全性直接决定老年人的购物意愿与满意度;中介因素在克服技术障碍和增强信任感方面起桥梁作用;深层驱动力则揭示了老年人的行为本质动因。本文为电商企业优化老年友好型平台设计、提升用户体验,以及政府制定数字普惠政策提供了理论支持和实践建议,助力“银发经济”的高质量发展。With the deep integration of aging and digitalization, the elderly group gradually becomes an important consumption force in online shopping. Based on the Interpretive Structural Model (ISM), this paper combs through the multidimensional factors affecting the online shopping behavior of the elderly and constructs a hierarchical structural model. It is found that the online shopping behavior of the elderly is comprehensively influenced by three dimensions: surface experience (technological convenience and trust security), mediating factors (digital skills, health status, policy support and consumption risk perception), and deeper drivers (autonomy needs, economic status, and social interaction). Among them, technological convenience and trust security directly determine older adults' shopping intention and satisfaction;mediating factors play a bridging role in overcoming technological barriers and enhancing trust;and deeper drivers reveal the essential drivers of older adults' behavior. This paper provides theoretical support and practical suggestions for e-commerce enterprises to optimize the design of age-friendly platforms and enhance user experience, and for the government to formulate digital inclusion policies, so as to facilitate the high-quality development of the “silver-hair economy”.展开更多
The paper is devoted to the study of the gravitational collapse within the framework of the spherically symmetric problem in the Newton theory and general relativity on the basis of the pressure-free model of the cont...The paper is devoted to the study of the gravitational collapse within the framework of the spherically symmetric problem in the Newton theory and general relativity on the basis of the pressure-free model of the continuum. In application to the Newton gravitation theory, the analysis consists of three stages. First, we assume that the gravitational force is determined by the initial sphere radius and constant density and does not change in the process of the sphere collapse. The obtained analytical solution allows us to find the collapse time in the first approximation. Second, we construct the step-by-step process in which the gravitational force at a given time moment depends on the current sphere radius and density. The obtained numerical solution specifies the collapse time depending on the number of steps. Third, we find the exact value of the collapse time which is the limit of the step-by-step solutions and study the collapse and the expansion processes in the Newton theory. In application to general relativity, we use the space model corresponding to the special four-dimensional space which is Euclidean with respect to space coordinates and Riemannian with respect to the time coordinate only. The obtained solution specifies two possible scenarios. First, sphere contraction results in the infinitely high density with the finite collapse time, which does not coincide with the conventional result corresponding to the Schwarzschild geometry. Second, sphere expansion with the velocity which increases with a distance from the sphere center and decreases with time.展开更多
In previous papers, we proposed the important Ztransformations and obtained general solutions to a large number of linear and quasi-linear partial differential equations for the first time. In this paper, we will use ...In previous papers, we proposed the important Ztransformations and obtained general solutions to a large number of linear and quasi-linear partial differential equations for the first time. In this paper, we will use the Z1transformation to get the general solutions of some nonlinear partial differential equations for the first time, and use the general solutions to obtain the exact solutions of some typical definite solution problems.展开更多
文摘Retinal blood vessel segmentation is crucial for diagnosing ocular and cardiovascular diseases.Although the introduction of U-Net in 2015 by Olaf Ronneberger significantly advanced this field,yet issues like limited training data,imbalance data distribution,and inadequate feature extraction persist,hindering both the segmentation performance and optimal model generalization.Addressing these critical issues,the DEFFA-Unet is proposed featuring an additional encoder to process domain-invariant pre-processed inputs,thereby improving both richer feature encoding and enhanced model generalization.A feature filtering fusion module is developed to ensure the precise feature filtering and robust hybrid feature fusion.In response to the task-specific need for higher precision where false positives are very costly,traditional skip connections are replaced with the attention-guided feature reconstructing fusion module.Additionally,innovative data augmentation and balancing methods are proposed to counter data scarcity and distribution imbalance,further boosting the robustness and generalization of the model.With a comprehensive suite of evaluation metrics,extensive validations on four benchmark datasets(DRIVE,CHASEDB1,STARE,and HRF)and an SLO dataset(IOSTAR),demonstrate the proposed method’s superiority over both baseline and state-of-the-art models.Particularly the proposed method significantly outperforms the compared methods in cross-validation model generalization.
文摘BACKGROUND The coronavirus disease 2019(COVID-19)outbreak lasted several months,having started in December 2019.This study aimed to report the impacts of various factors on the depression levels of the general public and ascertain how emotional measures could be affected by psychosocial factors during the COVID-19 pandemic.AIM To investigate the depression levels of the general public in China during the COVID-19 pandemic.METHODS A total of 2001 self-reported questionnaires about Beck Depression Inventory(BDI)were collected on August 22,2022 via the website.Each questionnaire included four levels of depression and other demographic information.The BDI scores and incidences of different depression levels were compared between various groups of respondents.χ2 analysis and the two-tailed t-test were used to assess categorical and continuous data,respectively.Multiple linear regressions and logistic regressions were employed for correlation analysis.RESULTS The averaged BDI score in this study was higher than that for the non-epidemic periods,as reported in previous studies.Even higher BDI scores and incidences of moderate and severe depression were recorded for people who were quarantined for suspected COVID-19 infection,compared to the respondents who were not quarantined.The participants who did not take protective measures were associated with higher BDI scores than those who made efforts to keep themselves relatively safer.Similarly,the people who did not return to work had higher BDI scores compared to those managed to.A significant association existed between the depression levels of the subgroups and each of the factors,except gender and location of residence.However,quarantine was the most relative predictor for depression levels,followed by failure to take preventive measures and losing a partner,either through divorce or death.CONCLUSION Based on these data,psychological interventions for the various subpopulations in the general public can be implemented during and after the COVID-19 pandemic.Other countries can also use the data as a reference.
文摘随着老龄化与数字化的深度融合,老年群体逐渐成为网络购物的重要消费力量。本文基于解释结构模型(ISM),梳理了影响老年人网络购物行为的多维因素,并构建层级结构模型。研究发现,老年人网络购物行为受表层经验(科技便捷性、信任安全性)、中介因素(数字技能、健康状况、政策支持及消费风险感知)和深层驱动力(自主性需求、经济地位、社会交互)三大维度的综合影响。其中,科技便捷性和信任安全性直接决定老年人的购物意愿与满意度;中介因素在克服技术障碍和增强信任感方面起桥梁作用;深层驱动力则揭示了老年人的行为本质动因。本文为电商企业优化老年友好型平台设计、提升用户体验,以及政府制定数字普惠政策提供了理论支持和实践建议,助力“银发经济”的高质量发展。With the deep integration of aging and digitalization, the elderly group gradually becomes an important consumption force in online shopping. Based on the Interpretive Structural Model (ISM), this paper combs through the multidimensional factors affecting the online shopping behavior of the elderly and constructs a hierarchical structural model. It is found that the online shopping behavior of the elderly is comprehensively influenced by three dimensions: surface experience (technological convenience and trust security), mediating factors (digital skills, health status, policy support and consumption risk perception), and deeper drivers (autonomy needs, economic status, and social interaction). Among them, technological convenience and trust security directly determine older adults' shopping intention and satisfaction;mediating factors play a bridging role in overcoming technological barriers and enhancing trust;and deeper drivers reveal the essential drivers of older adults' behavior. This paper provides theoretical support and practical suggestions for e-commerce enterprises to optimize the design of age-friendly platforms and enhance user experience, and for the government to formulate digital inclusion policies, so as to facilitate the high-quality development of the “silver-hair economy”.
文摘The paper is devoted to the study of the gravitational collapse within the framework of the spherically symmetric problem in the Newton theory and general relativity on the basis of the pressure-free model of the continuum. In application to the Newton gravitation theory, the analysis consists of three stages. First, we assume that the gravitational force is determined by the initial sphere radius and constant density and does not change in the process of the sphere collapse. The obtained analytical solution allows us to find the collapse time in the first approximation. Second, we construct the step-by-step process in which the gravitational force at a given time moment depends on the current sphere radius and density. The obtained numerical solution specifies the collapse time depending on the number of steps. Third, we find the exact value of the collapse time which is the limit of the step-by-step solutions and study the collapse and the expansion processes in the Newton theory. In application to general relativity, we use the space model corresponding to the special four-dimensional space which is Euclidean with respect to space coordinates and Riemannian with respect to the time coordinate only. The obtained solution specifies two possible scenarios. First, sphere contraction results in the infinitely high density with the finite collapse time, which does not coincide with the conventional result corresponding to the Schwarzschild geometry. Second, sphere expansion with the velocity which increases with a distance from the sphere center and decreases with time.
文摘In previous papers, we proposed the important Ztransformations and obtained general solutions to a large number of linear and quasi-linear partial differential equations for the first time. In this paper, we will use the Z1transformation to get the general solutions of some nonlinear partial differential equations for the first time, and use the general solutions to obtain the exact solutions of some typical definite solution problems.
