Introduction: Few studies are available on the prevalence and sleep-related factors of dementia with Lewy bodies (DLB) in Chinese older adults, aiming to explore the associations between sleep characteristics and DLB.Methods: A cross-sectional study with 7,528 individuals aged ≥65 years in 106 communities in Northern China was conducted from April 2019 to January 2020. Questionaries (including demographic characteristics, comorbidities, lifestyles, and sleep characteristics) were administered, and neuropsychological assessments and physical examination were conducted in phase I; screening for probable DLB was (...) done in phase II. Logistic regressions were used to assess associations.Results: A total of 919 (12.2%, 919/7,528) participants had dementia, and 101 (1.3%, 101/7,528) participants were diagnosed with DLB. The prevalence of dementia and DLB were slightly higher or equal in women, increased with age, and roughly decreased with nighttime sleep duration. Of the 101 participants, all of them (100.0%) had cognitive impairment, 46 (44.54%) displayed fluctuating cognition, 72 (71.29%) of them showed visual hallucination, 22 (21.78%) individuals reported RBD, and 27.71% showed Parkinsonism. Sleeping for 8 h had combined diagnostic value for DLB (AUC = 0.783, 95%CI: 0.734–0.831, p < 0.001).Conclusions: The current prevalence of DLB is 1.3% in Northern China. Short or long nighttime sleep duration is independently associated with the occurrence of dementia and DLB. (shrink)

Mindfulness and accordant interventions are often used as complementary treatments to psychological or psychosomatic problems. This has also been gradually integrated into daily lives for the promotion of psychological well-being in non-clinical populations. The experience of mindful acceptance in a non-judgmental way brought about the state, which was less interfered by a negative effect. Mindfulness practice often begins with focused attention meditation restricted to an inner experience. We postulate that the brain areas related to an interoceptive function would demonstrate an (...) intrinsic functional change after mindfulness training for the mindful novices along with paying more attention to internal processes. To further explore the influence of mindfulness on the organization of the brain regions, both functional connectivity in the voxel and the region of interest level were calculated. In the current study, 32 healthy volunteers, without any meditation experiences, were enrolled and randomly assigned to a mindfulness-based stress reduction group or control group. Participants in the MBSR group completed 8 weeks of mindfulness-based stress reduction and rated their mindfulness skills before and after MBSR. All subjects were evaluated via resting-state functional MRI in both baselines and after 8 weeks. They also completed a self-report measure of their state and trait anxiety as well as a positive and negative affect. Pre- and post-MBSR assessments revealed a decreased amplitude of low-frequency fluctuations in the right anterior cingulate gyrus, left anterior and posterior insula, as well as left superior medial frontal gyrus in MBSR practitioners. Strengthened FC between right anterior cingulate cortex and aIC.R was observed. The mean ALFF values of those regions were inversely and positively linked to newly acquired mindful abilities. Along with a decreased negative affect score, our results suggest that the brain regions related to attention and interoceptive function were involved at the beginning of mindfulness. This study provides new clues in elucidating the time of evaluating the brain mechanisms of mindfulness novices. (shrink)

本书包括:导论:论应用伦理学;基因超人与后现代前景;从辛格的“人”的概念看堕胎与安乐死等内容。.

Background: The coronavirus disease 2019 has been rapidly transmitted worldwide, which contributed to various psychological problems among the general population in China. The purpose of this study is to investigate the prevalence and associated factors of depressive symptoms among Chinese adults.Methods: A cross-sectional study of Chinese adults was conducted during 17–29 February 2020. Symptoms of depression were assessed using the Center for Epidemiologic Studies Depression scale.Results: A total of 3,399 respondents were included in the analysis. It was observed that 14.2% (...) of the participants were screened positive for depressive symptoms. In a multivariate logistic regression analysis, older age, smoking, self-rated health, having greater support scores, knowledge about the main symptom of COVID-19, and staying in Wuhan within 3 months before the outbreak of epidemic were associated with depressive symptoms.Conclusion: A considerable proportion of the general population in China had depressive symptoms during the COVID-19 epidemic. Routine screening and targeted interventions for depression are needed among high-risk depressed individuals during the COVID-19 epidemic. (shrink)

The making of infrared templates is of great significance for improving the accuracy and precision of infrared imaging guidance. However, collecting infrared images from fields is difficult, of high cost, and time-consuming. In order to address this problem, an infrared image generation method, infrared generative adversarial networks, based on conditional generative adversarial networks architecture is proposed. In I-GANs, visible images instead of random noise are used as the inputs, and the D-LinkNet network is also utilized to build the generative model, (...) enabling improved learning of rich image textures and identification of dependencies between images. Moreover, the PatchGAN architecture is employed to build a discriminant model to process the high-frequency components of the images effectively and reduce the amount of calculation required. In addition, batch normalization is used to optimize the training process, and thereby, the instability and mode collapse of the generated adversarial network training can be alleviated. Finally, experimental verification is conducted on the produced infrared/visible light dataset. The experimental results reveal that high-quality and reliable infrared data are generated by the proposed I-GANs. (shrink)

本书包括:论实用理性与乐感文化、哲学答问、哲学探寻录、主体性哲学论纲系列、美的哲学等内容。.

《中庸原論:儒家情感形上學之創發與潛變》認為，孔子的心性之學包括兩個部分，即「心學」與「情學」。 儒學內化就是道德情感與良知之心內化為天命之性，成為道德實踐的內在本體和形上根據。 《中庸》作為思孟學派的早期作品，承擔着為儒學建立道德本體和尋找道德終極根源的形上課題。在這兩個課題中，道德情感都具有本質的意義，《中庸》初步建立起來的儒家形上學可以說是一種情感形上學。 宋明時期，孔子的「心學」得到充分發展，朱子是孔子「心學」之認知派，陸王是孔子「心學」之良知派，孔子的「情學」卻隱而不彰。 直到明末，劉蕺山才重新認識到道德情感的重要地位，並在一定程度上復歸了思孟學派心性情為一的義理結構。 楊少涵，河南桐柏人，副教授，碩士生導師。1999年7月畢業於鄭州大學，獲文學學士學位。2006年3月畢業於南京政治學院上海分院，獲哲學碩士學位。2009年6月畢業於上海復旦大學，獲哲學博士學位。201 1年6月於上海師范大學博士后出站。現任為華僑大學哲學與社會發展學院副教授。先后在《哲學研究》、《光明日報》等報刊上發表論文二十余篇。校理古籍《中庸集說》（衛湜著，漓江出版社，2011年）一部。.

1. Sae sidae rŭl yŏrŏ gan saramdŭl -- 2. Ŏdum ŭi sidae.

In recent years, the field of AI & Law has increasingly focused on predicting legal judgments, particularly in civil cases. While traditional neural network methods are highly effective at automatically learning patterns from large datasets, they often suffer from a lack of interpretability. To address this limitation, we propose a neuro-symbolic framework for legal judgment prediction, based on large language models (LLMs). This framework combines legal knowledge (e.g., legal rules), represented through first-order logic rules, with deep neural networks (DNNs), using (...) a discrepancy loss to minimize prediction differences between the two components. By integrating the logic module during end-to-end training, knowledge is effectively transferred to the model parameters. Additionally, we develop a Chain-of-Thought prompt that uses LLMs to extract fact elements from legal cases. These elements act as logical variables within the rules, supporting the reasoning process in the logic module and improving overall interpretability. To validate the effectiveness of this framework, we conduct extensive experiments on a large dataset of private lending cases. The results demonstrate that the framework not only improves predictive performance but also enhances the interpretability of judgment predictions. (shrink)

The COVID-19 pandemic has caused a record global crisis, particularly and extremely, for the service sectors. Due to extensive security measures, many service sector employees have to work remotely to maintain services. Drawing upon the conservation of resources theory, this research investigates the impact of servant leadership on the task performance of employees in virtual working environments during the COVID-19 crisis. Our theoretical model was tested using data collected from 335 individual employees in the education sector of Pakistan. SPSS version (...) 26.0 was applied to find the hypothesized relationship between the study variables. To find the indirect mediating effect, we applied Model 4; for moderation, we applied Model 1; and for the moderation and mediation effect, we applied Model 7 of the Process Macro model of Hayes. The results of the study revealed that servant leadership is positively related to task performance in a virtual environment during crises. Furthermore, psychological empowerment partially mediates the relationship between servant leadership and task performance. Perceived supervisor support positively moderates the relationship between servant leadership and task performance. Moreover, the indirect effect of servant leadership on task performance via psychological empowerment is moderated by perceived supervisor support. The results provided guidance to the educational sector on how to lead effectively in times of crisis when service sector employees work predominantly in virtual environments. The theoretical and practical implications of these findings are discussed. (shrink)

Named entity recognition is a subtask in natural language processing, and its accuracy greatly affects the effectiveness of downstream tasks. Aiming at the problem of insufficient expression of potential Chinese features in named entity recognition tasks, this paper proposes a multifeature adaptive fusion Chinese named entity recognition model. The model uses bidirectional long short-term memory neural network to extract stroke and radical features and adopts a weighted concatenation method to fuse two sets of features adaptively. This method can better integrate (...) the two sets of features, thereby improving the model entity recognition ability. In order to fully test the entity recognition performance of this model, we compared the basic model and other mainstream models on Microsoft Research Asia and “China People’s Daily” dataset from January to June 1998. Experimental results show that this model is better than other models, with F1 values of 97.01% and 96.78%, respectively. (shrink)

In recent years, while extensive researches on various networks properties have been proposed and accomplished, little has been proposed and done on network robustness and node vulnerability assessment under cascades in directed large-scale online community networks. In essential, an online directed social network is a group-centered and information spread-dominated online platform which is very different from the traditional undirected social network. Some further research studies have indicated that the online social network has high robustness to random removals of nodes but (...) fails to the intentional attacks, particularly to those attacks based on node betweenness or node directed coefficient. To explore on the robustness of directed social network, in this article, we have proposed two novel node centralities of ITG and I M p v. These two new centrality models are designed to capture this cascading effect in directed online social networks. Furthermore, we also propose a new and highly efficient computing method based on iterations for I M p v. Then, with the abundant experiments on the synthetic signed network and real-life networks derived from directed online social media and directed human mobile phone calling network, it has been proved that our ITG and I M p v based on directed social network robustness and node vulnerability assessment method is more accurate, efficient, and faster than several traditional centrality methods such as degree and betweenness. And we also have proposed the solid reasoning and proof process of iteration times k in computation of I M p v. To the best knowledge of us, our research has drawn some new light on the leading edge of robustness on the directed social network. (shrink)

Is the societal-level of analysis sufficient today to understand the values of those in the global workforce? Or are individual-level analyses more appropriate for assessing the influence of values on ethical behaviors across country workforces? Using multi-level analyses for a 48-society sample, we test the utility of both the societal-level and individual-level dimensions of collectivism and individualism values for predicting ethical behaviors of business professionals. Our values-based behavioral analysis indicates that values at the individual-level make a more significant contribution to (...) explaining variance in ethical behaviors than do values at the societal-level. Implicitly, our findings question the soundness of using societal-level values measures. Implications for international business research are discussed. (shrink)

With the development of geoscience, users are eager to obtain preferred service from geospatial information intelligently and automatically. However, the information grows rapidly while the service gets more complicated, which makes it difficult to find out the targeted information for an exact service in geospatial issues. In this paper, a novel method is proposed to promote the geospatial service from information to knowledge with spatiotemporal semantics. Both prompted and professional knowledge are further refined to be published as a service. In (...) terms of an exact task, numerous related services are recombined to a service chain under user requirement. Finally, the proposed method is applied to monitor the environment on the Air Quality Index and soil moisture in the Sensor Web service platform, the results of which indicate geospatial knowledge service is more efficient to support spatial decision-making. (shrink)

Educational institutions have failed to achieve desired goals due to the lack of technology adoption, and this situation needs researchers’ emphasis. Hence, the current study examines the impact of digitalization and digital competencies among students on the educational performance of low-income college students in China. The article also investigates the moderating impact of parental support at the nexus of digitalization, digital competencies among students, and educational performance in low-income college students in China. The questionnaires were used by the researchers to (...) gather the data from the selected respondents. The article has applied the smart-PLS to check the linkage among understudy constructs and test the hypotheses. The results revealed that digitalization and digital competencies among students positively link educational performance. The results also exposed that parental support significantly moderates digitalization, digital competencies, and educational performance in low-income college students in China. This article helps policymakers develop policies to improve educational performance using technology adoption. (shrink)

Focusing on the domain of self-compassion, this study explored the promotion mechanism of online learning behavioral engagement of international students in China under COVID-19. Positive emotion and self-improvement motivation were selected as mediators. Participants were 606 international students from 8 countries who were studying online in their own countries due to the international travel restriction of COVID-19. Results showed positive emotion and self-improvement motivation completely mediated self-compassionate mindfulness and OLBE of international students. Positive emotion and self-improvement partially mediated SCM and (...) OLBE of international students respectively. Students with higher SCM engage with online learning more in that they possess more positive emotion and self-improvement motivation. This study suggested that SCM may facilitate OLBE via positive emotion and effective self-improvement motivation. (shrink)

We derive, in path integral approach, the (anomalous) master Ward identity associated with an infinite set of nonlocal conservation laws in two-dimensional principal chiral models.

This study investigated Chinese university students’ technology-assisted self-regulated learning strategies and whether the technology-based SRL strategies mediated the associations between English language self-efficacy, English enjoyment, and learning outcomes. Data were collected from 525 undergraduate students in mainland China through three self-report questionnaires and the performance on an English language proficiency test. While students reported an overall moderate level of SRL strategies, they reported a high level of technology-based vocabulary learning strategies. A statistically significant positive relationship was noted between the use (...) of technology-based SRL strategies and students’ English learning outcomes. English language self-efficacy and English language enjoyment were both related to technology-based SRL strategies. Furthermore, SRL strategies fully mediated the relationship between English enjoyment and English learning outcomes, but the association between English enjoyment and SRL strategies was only partially mediated by English language self-efficacy. Pedagogically, findings of this study suggest that training and instruction aimed at promotion of modern educational technology among students need to give attention to developing their strategic awareness of motivation regulation in optimizing effectiveness of their technology use in learning the target language. (shrink)

Coronavirus disease is having an unprecedented and unpredictable impact on the world's economy. The pandemic has driven the world toward adapting to the current circumstances regardless of the business, sector, or industry. The coronavirus epidemic has affected the global economy and service sector. The purpose of the current study is to assess the effect of COVID-19 on service sector growth and sustainability. Global sectors and industries are trying to anchor themselves amidst the pandemic. The study focuses on the sectors that (...) are badly hit by the outbreak and discussed the strategies and responses different countries are taking to sustain their economies. This study concludes that the vital role of Information Technology and digitization supports the economies in their fight against the pandemic and helps them sustain themselves amid crises. This study also contributes to the body of literature by suggesting IT-based solutions for various industries to elevate effective responsiveness and avoid significant losses. (shrink)

This article provides current Schwartz Values Survey (SVS) data from samples of business managers and professionals across 50 societies that are culturally and socioeconomically diverse. We report the society scores for SVS values dimensions for both individual- and societal-level analyses. At the individual-level, we report on the ten circumplex values sub-dimensions and two sets of values dimensions (collectivism and individualism; openness to change, conservation, self-enhancement, and self-transcendence). At the societal-level, we report on the values dimensions of embeddedness, hierarchy, mastery, affective (...) autonomy, intellectual autonomy, egalitarianism, and harmony. For each society, we report the Cronbach’s α statistics for each values dimension scale to assess their internal consistency (reliability) as well as report interrater agreement (IRA) analyses to assess the acceptability of using aggregated individual level values scores to represent country values. We also examined whether societal development level is related to systematic variation in the measurement and importance of values. Thus, the contributions of our evaluation of the SVS values dimensions are two-fold. First, we identify the SVS dimensions that have cross-culturally internally reliable structures and within-society agreement for business professionals. Second, we report the society cultural values scores developed from the twenty-first century data that can be used as macro-level predictors in multilevel and single-level international business research. (shrink)

We construct a causal-modeling semantics for both indicative and counterfactual conditionals. As regards counterfactuals, we adopt the orthodox view that a counterfactual conditional is true in a causal model M just in case its consequent is true in the submodel M∗, generated by intervening in M, in which its antecedent is true. We supplement the orthodox semantics by introducing a new manipulation called extrapolation. We argue that an indicative conditional is true in a causal model M just in case its (...) con- sequent is true in certain submodels M∗, generated by extrapolating M, in which its antecedent is true. We show that the proposed semantics can account for some important minimal pairs nicely and naturally. We also prove a theorem showing under what conditions intervention and extrapolation will yield the same result, and thus explain how counterfactual and indicative conditionals would behave in a causal-modeling semantics. (shrink)

This article introduces a satellite technology, High Resolution Picture Transmission (HRPT), for a science activity. HRPT is a digital data stream transmitted from environmental satellites. The HRPT imagery is capable of providing real-time studies of regional geology, glacial processes, atmospheric processes, ocean circulation, coastal processes, hydrology, and so on. Obtaining and manipulating HRPT data creates a variety of exciting experiences in science classrooms. A Science and Technology for Individuals, Societies, and the Environment (STISE) teaching model was developed to use satellite (...) technologies for science activities. STISE is a conceptual model for addressing key cognitive and affective parameters when designing science lessons. STISE is designed to encourage students to understand science and technology from their levels of cognition, then relate their understanding to the environment, levels of societies, and their lives. Relationships among science, technology, and society become both obvious and interesting to students as they process and interpret the HRPT imagery. (shrink)