​I use network models to simulate social learning situations in which the dominant group ignores or devalues testimony from the marginalized group. I find that the marginalized group ends up with several epistemic advantages due to testimonial ignoration and devaluation. The results provide one possible explanation for a key claim of standpoint epistemology, the inversion thesis, by casting it as a consequence of another key claim of the theory, the unidirectional failure of testimonial reciprocity. Moreover, the results complicate the understanding (...) and application of previously discovered network epistemology effects, notably the Zollman effect (Zollman 2007, 2010). (shrink)

Based on the affective events theory, this paper discusses the influence of job insecurity on employees’ extra-role behavior. The mediating effect of negative emotion and the moderating effect of workplace friendship are also tested. The results of an empirical analysis, based on the data of 327 employees, show that job insecurity has a significant negative impact on employees’ extra-role behavior. Negative emotion plays a mediating role in the relationship between job insecurity and extra-role behavior. Workplace friendship moderated the relationship between (...) job insecurity and negative emotions, as well as between job insecurity and extra-role behavior. Workplace friendship also moderates the mediating effect of negative emotion on the relationship between job insecurity and extra-role behavior, that is, the higher the level of the workplace friendship is, the weaker the mediation role mentioned above will be. The research results have implications for the sustainable development of the organization. (shrink)

Truth-telling for terminally ill patients is a challenging ethical and social issue for Chinese health care professionals. However, despite the existence of ethical and moral standards for nurses, they frequently encounter moral dilemmas when making decisions about truth-telling to patients with end-stage diseases in China. This article aims to provide ethical strategies for clinical nurses in China regarding truth-telling decisions for terminally ill patients on the basis of their individual autonomy. This article first presents a common case scenario in China (...) and then critically discusses ethical issues related to ethical principles and philosophical theories. The aim is to provide the much needed strategy for truth-telling for nurses who are terminally ill rather than to focus on attitudes toward disclosure. This article focuses on nursing morality, ethics, norms, and philosophy in health care and discusses countermeasures taken by nurses in truth-telling decision-making in combination with Chinese Confucian culture. The analysis identifies key ethical strategies tailored to Chinese nurses’ practices, emphasizing individual autonomy, cultural sensitivity, and family dynamics in truth-telling decisions. The complexity of end-of-life illness requires Chinese nurses to strengthen the communication training needed to deliver bad news, as well as critical and autonomous thinking and good communication skills when implementing patient- and family-centered care, to achieve true delivery of bad news, thereby increasing patient autonomy and promoting more successful collaboration among patients, families, and providers. To improve the quality of care. Chinese nurses should integrate ethical principles with Confucian values to enhance patient-centered communication, respecting autonomy while adapting to cultural nuances in end-of-life care. (shrink)

Although previous research has highlighted the positive effect of leaders’ voluntary workplace green behavior, limited research attention has been given to empirically testing how and when such behavior produces trickle-down effects. Taking a role model perspective and drawing on social identity theory, this research aims to fill this gap by proposing and testing the mechanism and boundary conditions of the influencing processes whereby leaders’ VWGB can trickle down to employees’ pro-environmental behaviors. By theorizing a moderated mediation model, the current research (...) empirically examines the hypotheses by conducting a hierarchical regression analysis. We employed a survey questionnaire research design to collect two waves of multisource data. The data used in the analysis are from survey responses of 313 subordinate-supervisor dyads at two different time points. The results show that leaders’ VWGB can have a trickle-down influence on employees’ task-related pro-environmental behavior and proactive pro-environmental behaviors through their green self-identity and that this trickle-down effect is greater among employees with higher green climate perceptions. Our results reveal the intervening mechanism and boundary condition of leaders’ VWGB by conducting a systematic examination of how this effect trickles down. (shrink)

Collaboration requires agents to coordinate their behavior on the fly, sometimes cooperating to solve a single task together and other times dividing it up into sub‐tasks to work on in parallel. Underlying the human ability to collaborate is theory‐of‐mind (ToM), the ability to infer the hidden mental states that drive others to act. Here, we develop Bayesian Delegation, a decentralized multi‐agent learning mechanism with these abilities. Bayesian Delegation enables agents to rapidly infer the hidden intentions of others by inverse planning. (...) We test Bayesian Delegation in a suite of multi‐agent Markov decision processes inspired by cooking problems. On these tasks, agents with Bayesian Delegation coordinate both their high‐level plans (e.g., what sub‐task they should work on) and their low‐level actions (e.g., avoiding getting in each other's way). When matched with partners that act using the same algorithm, Bayesian Delegation outperforms alternatives. Bayesian Delegation is also a capable ad hoc collaborator and successfully coordinates with other agent types even in the absence of prior experience. Finally, in a behavioral experiment, we show that Bayesian Delegation makes inferences similar to human observers about the intent of others. Together, these results argue for the centrality of ToM for successful decentralized multi‐agent collaboration. (shrink)

A gradual increase in population and urbanization has increased the demand for global resources, which ultimately burdens the depletion of resources and challenges environmental sustainability worldwide. In recent decades, nature sustainability has been the biggest challenge encountered by humankind. In addition, the changing lifestyle and consumption patterns have enormously played a key role. However, the consumption pattern from the employee’s perspective suffers from the lack of research. Therefore, grounded on the theory of planned behavior, this research explores the antecedents and (...) consequences of employees’ buying intentions in the world’s emerging market. Data were collected using a web-based link shared via WeChat and Q.Q.; resultants into 451 valid responses and partial least square structural equation modeling using SmartPLS 4 have been administered for the analysis. Besides the insignificant effect of descriptive norms on buying intention and environmental concerns on purchasing behavior, other factors significantly impact purchase intention and actual buying behavior. This research witnesses a significant mediating role of buying intention. This research suggests that practitioners develop strategies for public advertisement and launch a general message and campaigns both in urban and rural areas to prevent environmental sustainability and increases awareness related to organic consumption. (shrink)

Accurate identification of legal provisions is crucial for adjudicating criminal cases, but the complexity and volume of legal texts pose significant challenges for legal professionals. This paper addresses these challenges by introducing a novel legal provision selection framework that transforms the task from a simple classification problem into a sophisticated system combining semantic matching with causal relationship learning. Leveraging large language models, our approach enhances the understanding and interpretation of legal language, by extracting nuanced features from legal texts for deeper (...) contextual comprehension. Additionally, integrating causal learning aligns with the inherent causality in legal reasoning, improving model interpretability and mitigating data bias. Our method demonstrates superior accuracy and robustness through extensive experiments on the CAIL2018 dataset and its subsets. This research significantly advances legal AI applications, promoting efficiency and fairness in the criminal justice system by providing precise and reliable legal provision selection. (shrink)

本书内容包括:传统价值观的整体透视、简论传统文化中各学派的价值理论、儒家价值理想及其现代意义论析、道家风骨和生命哲学的现代诠释等。.

Given the prevalence of employees’ workplace cheating behavior (WCB) and its cost to organizations, considerable scholarly effort has been invested in identifying both its antecedents and intrapersonal consequences. However, its interpersonal repercussions, particularly how and when WCB influences coworker relationships, remain underexplored. Our paper enriches the WCB literature by using social information processing theory to examine the effect of employee WCB on coworker disliking and subsequent coworker ostracism. Through a field survey study and experimental studies, we found that coworker disliking (...) mediates the positive relationship between WCB and coworker ostracism. Moreover, team ethical leadership strengthens the positive relationship between WCB and coworker disliking, and focal employees’ negative affectivity strengthens the positive relationship between coworker disliking and ostracism. Furthermore, team ethical leadership and focal employees’ negative affectivity strengthen the indirect effects of WCB on coworker ostracism via coworker disliking. Our findings have important theoretical and practical implications for the literature on WCB. (shrink)

Cheating is prevalent in workplaces and has a significant detrimental impact, and thus considerable scholarly research has been dedicated to investigating its antecedents. While various influential factors (e.g., performance pressure, perceived threats of COVID-19, leadership, and employee characteristics) have been identified, the effects of employment conditions remain relatively underexplored. We extend the research by applying impression management theory to examine how perceived job insecurity contributes to workplace cheating behavior. Through a field survey and an experimental study, we found that impression (...) management motives mediate the positive link between job insecurity and workplace cheating behavior. In addition, job immobility exacerbates the direct effect of job insecurity on impression management motives, which in turn increases workplace cheating behavior. The findings enrich the literature by identifying job insecurity as a critical employment-related antecedent of workplace cheating behavior and by developing a comprehensive impression management framework to elucidate whether, how, and when job insecurity may result in such behavior. (shrink)

The psychological problems and employment problems of college students have always been the focus of attention of all sectors of society. The COVID-19 epidemic has a great impact on the mental health and employment of Chinese college students. Under this background, this study discusses how epidemic anxiety affects the employment confidence and perception of employment situation of Chinese college students. Through the online questionnaire survey of 1,132 college students nationwide, and the ordinal logistic regression analysis of the survey data using (...) Stata 16.0 software, the results show that: Epidemic anxiety negatively affects Chinese college students' employment confidence and employment situation perception, and has a significant impact on employment confidence. The three control variables of employment guidance, older age and higher education have a significant positive impact on college students' employment confidence and employment situation perception. College students in the eastern region have stronger employment confidence and more optimistic employment situation perception. But the expected monthly salary is negatively correlated with employment confidence. Male college students and Science and Engineering students' epidemic anxiety have a stronger negative impact on employment confidence and employment situation perception. Employment guidance has a moderating effect on the relationship between epidemic anxiety, employment confidence and employment situation perception. Employment guidance can enhance college students' employment confidence and reduce their sense of employment crisis by alleviating epidemic anxiety. Combined with the research conclusions, it is proposed that the state and schools should pay attention to the psychological counseling of college students, strengthen the employment guidance of colleges and universities, vigorously support the development of small, medium-sized and micro enterprises, and improve the employment and entrepreneurship service system of college students, so as to promote the employment of college students. (shrink)

Poverty alleviation by consumption is a powerful way to help the poor people get rid of poverty, which plays a significant role in China's rural revitalization. However, the achievement of poverty alleviation by consumption mostly depends on government procurement, and the enthusiasm of customers to participate is low, facing the severe challenge of poor sustainability. Helping the poor is the most common motivation for customers to buy poverty-alleviation agricultural products. However, as the negative events of poverty alleviation such as “tragic (...) marketing” constantly appear in news reports, customers' trust in sellers has been seriously damaged. The psychological protection system for fear of being cheated hinders customers' purchase intention. Therefore, we believed that trust is an important factor in enhancing customers' purchase intention of PAAP. Customers buy PAAP mainly through online channels, and institution-based trust is the most important way to generate trust in online channels. Thus, this study investigated the institutional mechanisms that affect customers' trust in the sellers of PAAP and discussed the influence of trust on the online purchase intention of PAAP. Data were obtained through a questionnaire survey and tested empirically. The results showed that the effectiveness of the user feedback mechanism, platform supervision mechanism, product traceability mechanism, and product certification mechanism can enhance customers' purchase intention by enhancing their trust. Individual trust tendency positively regulated the relationship between the effectiveness of institutional mechanisms and consumer trust. The conclusion can not only provide new theoretical guidance for the practice of poverty alleviation by consumption in China but also offer new ideas for the poverty alleviation undertakings in other countries. (shrink)

Access to legal information is fundamental to access to justice. Yet accessibility refers not only to making legal documents available to the public, but also rendering legal information comprehensible to them. A vexing problem in bringing legal information to the public is how to turn formal legal documents such as legislation and judgments, which are often highly technical, to easily navigable and comprehensible knowledge to those without legal education. In this study, we formulate a three-step approach for bringing legal knowledge (...) to laypersons, tackling the issues of navigability and comprehensibility. First, we translate selected sections of the law into snippets (called CLIC-pages), each being a small piece of article that focuses on explaining certain technical legal concept in layperson’s terms. Second, we construct a _Legal Question Bank_, which is a collection of legal questions whose answers can be found in the CLIC-pages. Third, we design an interactive _CLIC Recommender_. Given a user’s verbal description of a legal situation that requires a legal solution, CRec interprets the user’s input and shortlists questions from the question bank that are most likely relevant to the given legal situation and recommends their corresponding CLIC pages where relevant legal knowledge can be found. In this paper we focus on the technical aspects of creating an LQB. We show how large-scale pre-trained language models, such as GPT-3, can be used to generate legal questions. We compare machine-generated questions against human-composed questions and find that MGQs are more scalable, cost-effective, and more diversified, while HCQs are more precise. We also show a prototype of CRec and illustrate through an example how our 3-step approach effectively brings relevant legal knowledge to the public. (shrink)

Although fear and anxiety have gradually become a shared experience in the time of COVID-19, few studies have examined its content from historical, cultural, and phenomenological perspectives concerning the self-awareness and alterity. We discuss the development of the ubiquitous nature of Taijin-kyōfushō (TKS), a subtype of social anxiety disorder (SAD) originated and considered culturally-bound in the 1930s Japan involving fear of offending or displeasing other people. Considering the historical processes of disease classification, advances in cognitive neurosciences, and the need to (...) better understand the content of suffering, psychiatric nosology for SAD still appears controversial and requires further investigations. (shrink)

Orphans and vulnerable children fall under the category of children who are at risk of exposure to more stressful circumstances and receive less social assistance compared to other children. This study aims to investigate the impact of group counseling based on social intervention and psychological therapy on social support and the perceived stress growth of orphans and vulnerable children. In one special educational needs school in Nanning, China, the SSGPC was developed and implemented. Using the social support and post-stress growth (...) scales, the researchers investigated the effects of SSGPC on orphans and vulnerable children. Twenty-seven orphans and vulnerable children between the ages of nine and 12 were arbitrarily assigned to the experimental and control groups. A pre-test post-test method of quasi-experimental design was applied, with 13 participants in the experimental group and 14 in the control group. The results revealed that the intervention group had significantly higher scores for social support and post-stress growth than the control group. The SSGPC had significantly improved the levels of social support for orphans. The findings indicated that the SSGPC provided an effective way to improve social support and post-stress growth of orphans and vulnerable children. (shrink)

The signals in numerous complex systems of engineering can be regarded as nonlinear parameter trend with noise which is identically distributed random signals or deterministic stationary chaotic signals. The commonly used methods for parameter estimation of nonlinear trend in signals are mainly based on least squares. It can cause inaccurate estimation results when the noise is complex. This paper proposes a calibration method for this issue in the case of single parameter via nonstationarity measure from the perspective of the stationarity (...) of residual sequence. Some numerical studies are conducted for validation. Results of numerical studies show that the proposed calibration method performs well for various models with different noise strengths and types and can significantly improve the accuracy of initial estimates obtained by least squares method. This is the first time that the nonstationarity measure is applied to the parameter calibration. All these results will be a guide for future studies of other parameter calibrations. (shrink)

The ability of bilingual individuals to manage two competing languages is assumed to rely on both domain-specific language control and domain-general control mechanisms. However, previous studies have reported mixed findings about the extent and nature of cross-domain generality. The present study examined the role of language dominance, along with bilingual language experience, in the relationship between word recognition and domain-general cognitive control. Two single-language lexical decision tasks and a domain-general flanker task were administered to bilinguals who live in the sociolinguistic (...) context of a minority and a majority language, namely, Uyghur and Chinese, respectively. The results showed a diversity in language dominance patterns with better performance in L2 than L1 in the recognition modality, even for participants who self-identified as globally being dominant in L1. This finding reflected all bilinguals’ self-evaluation that their preferred language for reading was L2, suggesting that language dominance is dynamic, depending on what language modality is measured. Furthermore, it was found that an earlier onset age of L2 acquisition and a higher across-modality dominance in L2 were related to faster L2 word recognition. When self-reported language dominance was operationalised as a grouping variable, it was further found that both across-modality L1- and L2-dominant bilingual participants demonstrated a significant relationship between L2 word recognition and domain-general monitoring control, while only L1-dominant bilinguals additionally tapped into inhibitory control, indexed by the flanker effect during L2 word recognition. These findings suggest that language dominance has an impact on the extent and nature of the overlap in control mechanisms across specific linguistic and domain-general cognitive domains and add evidence to a domain-general monitoring account of bilingual word recognition. (shrink)

Objective: Tangent Space Mapping using the geometric structure of the covariance matrices is an effective method to recognize multiclass motor imagery. Compared with the traditional CSP method, the Riemann geometric method based on TSM takes into account the nonlinear information contained in the covariance matrix, and can extract more abundant and effective features. Moreover, the method is an unsupervised operation, which can reduce the time of feature extraction. However, EEG features induced by MI mental activities of different subjects are not (...) the same, so selection of subject-specific discriminative EEG frequency components play a vital role in the recognition of multiclass MI. In order to solve the problem, a discriminative and multi-scale filter bank tangent space mapping algorithm is proposed in this article to design the subject-specific Filter Bank so as to effectively recognize multiclass MI tasks. Methods: On the 4-class BCI competition IV-2a dataset, first, a non-parametric method of multivariate analysis of variance based on the sum of squared distances is used to select discriminative frequency bands for a subject; next, a multi-scale FB is generated according to the range of these frequency bands, and then decompose multi-channel EEG of the subject into multiple sub-bands combined with several time windows. Then TSM algorithm is used to estimate Riemannian tangent space features in each sub-band and finally a liner Support Vector Machines is used for classification. Main Results: The analysis results show that the proposed discriminative FB enhances the multi-scale TSM algorithm, improves the classification accuracy and reduces the execution time during training and testing. On the 4-class BCI competition IV-2a dataset, the average session to session classification accuracy of nine subjects reached 77.33 ± 12.3%. When the training time and the test time are similar, the average classification accuracy is 2.56% higher than the latest TSM method based on multi-scale filter bank analysis technology. When the classification accuracy is similar, the training speed is increased by more than three times, and the test speed is increased two times more. Compared with Supervised Fisher Geodesic Minimum Distance to the Mean, another new variant based on Riemann geometry classifier, the average accuracy is 3.36% higher, we also compared with the latest Deep Learning method, and the average accuracy of 10-fold cross validation improved by 2.58%. Conclusion: Research shows that the proposed DMFBTSM algorithm can improve the classification accuracy of MI tasks. Significance: Compared with the MFBTSM algorithm, the algorithm proposed in this article is expected to select frequency bands with good separability for specific subject to improve the classification accuracy of multiclass MI tasks and reduce the feature dimension to reduce training time and testing time. (shrink)

In China, political philosophy is still a comparatively new academic discipline. While there is no such phrase as "political philosophy" in ancient Chinese texts, there are elements within them that could be considered part of that field. Central questions of Chinese ancient political philosophy include the legitimacy of the source of political power, the foundation of moral rationality for the use of political power, and the purpose of political activities. This book explores the ideas of rights, the foundations of law, (...) transference of power, democracy and other topic as debated in ancient times. Focusing on important political thinkers in Chinese history, such as Kongzi, Laozi, Xu Fuguan, Liang Qichao and Li Dazhao, the book explains characteristics that are particular to China, such as the system of abdication, the general will of the people, and the society of Great Harmony. While making comparisons between Chinese and Western political philosophy, the book also discusses how to establish a Chinese modern state and how to promote Chinese culture today so that it can influence more and more people around the world. The book will be a valuable reference for scholars of Chinese philosophy, political philosophy and Chinese culture. (shrink)

Entrepreneurship has flourished in recent years; however, since education on how to raise funds has received little attention from scholars, obtaining funds remains a difficult task. The development of crowdfunding has provided new opportunities to entrepreneurs, thus solving the funding, marketing, and distribution problems they previously faced. The main purpose of this study is to organize crowdfunding literature and to develop a crowdfunding curriculum grounded on output-based education. Students are asked to develop a product and a crowdfunding plan within the (...) span of one semester. This study explains the teaching content separately from the crowdfunding plan competition, course elements, and timetable. (shrink)

In view of the poor recommendation performance of traditional resource collaborative filtering recommendation algorithms, this article proposes a collaborative filtering recommendation model based on deep learning for art and MOOC resources. This model first uses embedding vectors based on the context of metapaths for learning. Embedding vectors based on the context of metapaths aggregate different metapath information and different MOOCs may have different preferences for different metapaths. Secondly, to capture this preference drift, the model introduces an attention mechanism, which can (...) improve the interpretability of the recommendation results. Then, by introducing the Laplacian matrix into the prior distribution of the hidden factor feature matrix, the relational network information is effectively integrated into the model. Finally, compared with the traditional model using the scoring matrix, the model in this article using text word vectors effectively alleviates the impact of data sparsity and greatly improves the accuracy of prediction. After analyzing the experimental results, compared with other algorithms, the resource collaborative filtering recommendation model proposed in this article has achieved better recommendation results, with good stability and scalability. (shrink)

With the development of computer hardware and software, digital art is a new discipline. It uses computers and digital technology as tools to perform artistic expression. It can be expanded to various binary numerical codes with computers as the center and can also be refined to various categories of creation with computers. The research scope is set in the field of digital art, and all kinds of accidental factors of digital art creation based on the machine learning algorithm are mined (...) and analyzed for feature correlation. Based on the hidden association relationship of massive data, the study focuses on the implicit association mining of digital art features of data for the recommendation algorithm. The classification and continuous data feature attributes are introduced and discretized, and the binary representation of data features is extended to ensure the diversity of data feature attributes. In order to mine some correlation features in data, a heuristic feature mining method based on minimum support was studied to discover the frequency of correlation features and construct the optimal feature subset. Based on the frequent items of data features, this study observes the heuristic algorithm of digital art feature association mining based on minimum confidence and carries out feature matching based on digital art feature association mining under different situation modes. The validity of the proposed algorithm is verified by using the experimental data of health and medical situations in the machine learning library. (shrink)

In this paper, we investigate the impact of economic policy uncertainty on the conditional dependence between China and U.S. stock markets by employing the Copula-mixed-data sampling framework. In the case of EPU, we consider the global EPU, the American EPU, and the China EPU. The empirical analysis based on the Shanghai Stock Exchange Composite index in China and the S&P 500 index in the U.S. shows that the tail dependence between China and U.S. stock markets is symmetrical, and the t (...) Copula outperforms alternative Copulas in terms of in-sample goodness of fit. In particular, we find that the t Copula-MIDAS model with EPU dominates the traditional time-varying t Copula in terms of in-sample fitting. Moreover, we observe that both the GEPU and AEPU have a significantly positive impact on the conditional dependence between China and U.S. stock markets, whereas CEPU has no significant impact. The tail dependence between China and U.S. stock markets exhibits an increasing trend, particularly in the recent years. (shrink)

This study investigated the relationship between teachers' mental state talk and young children's theory of mind with a quasi-experiment. In total, 56 young children were assigned to the experiment group and the control group. The experiment group was engaged in a 12-week intervention program with mental state talk in storytelling, casual conversations, and role-playing games, whereas the control group received no interventions. All the children were tested with three theory of mind tasks before and after the intervention. The results indicated (...) that the experimental group had a significant improvement in the ToM scores, whereas the control group showed no significant change. The educational implications of these findings are discussed. (shrink)

This paper chooses car travel and bus travel as the research objects, establishes a dual-mode equilibrium model based on the bottleneck model, and compares the travel characteristics of the no-toll and fine-toll schemes. We find that the fine-toll scheme can eliminate the queuing time at the bottleneck, but it also increases the congestion risk cost of bus travel. In order to eliminate the queuing time at the bottleneck and reduce the congestion risk cost of bus travel without increasing the car (...) travel cost and bus travel cost, we propose an optimization scheme of fine toll and bus departure quantity and analyze its travel characteristics theoretically. Through the numerical example, we calculate and analyze the equilibrium results of no-toll scheme, fine-toll scheme, and optimization scheme of fine toll and bus departure quantity. The results indicate that the optimization scheme of fine toll and bus departure quantity can help travelers to choose a reasonable travel mode and travel time to travel in the rush hour. (shrink)

It has been widely assumed and proven that a firm’s research and development investment is limited if the availability of cash flow is constrained. The purpose of this study is to verify the opposite proposition: whether firms invest heavily in R&D when more cash flow is available. This paper discusses the heterogeneous relationship between cash flow from different sources and the R&D investment of firms. The study divides the firm’s cash flow into three categories according to the business activities that (...) generate firm finance: cash flow from operating activities, cash flow from investing activities, and cash flow from financing activities. On this basis, a dynamic R&D investment model is constructed, and the relevant data for Chinese listed firms are used for the empirical research. The study finds that Chinese listed firms do not necessarily spend more cash on R&D investment, even if the availability of cash flow is not constrained. For young firms, CFO and CFI do not significantly correlate with R&D investment, and CFF significantly negatively correlates with R&D investment. For mature firms, the correlations between cash flow generated from different activities and R&D investment are nonsignificant. (shrink)

COVID-19 mortality rates are increasing worldwide, which has led to many highly restrictive precautionary measures and a strong sense of anxiety about the outbreak for many people around the world. There is thus an increasing concern about COVID-19 anxiety, resulting in recommending approaches for effective self-care. From a positive psychology perspective, it is also important for people to have positive affect when dealing with this pandemic. According to previous literature, respiration is considered to be an effective way to enhance people’s (...) mental health. Among all the wearable devices, Apple Watch has the largest market share, so this study recruited Chinese users that use respiration exercise function on Apple Watch; a total of 316 valid data were retrieved. Meanwhile, to understand one approach related to using Apple Watch to practice respiration to reduce COVID-19 anxiety about being infected during the COVID-19 outbreak, this study used a web-based cross-sectional survey to examine anxiety about being infected by COVID-19 among Chinese people who had been using the Apple Watch to practice respiration during the period of the COVID-19 outbreak. The study was based on the Health Theoretical Model, and the model was developed with four dimensions and was validated with structural equation modeling. The results of this study showed that practicing few minutes had a positive relationship on positive attitude, and positive attitude had a negative relationship on pandemic anxiety and a positive relationship on continuance use intention. Anxiety about the pandemic had a negative relationship on the intention to continue using the function. This showed that respiration practice can help to suppress the increase in anxiety levels regarding this pandemic. (shrink)

Signic knowledge is a crucial link without which the sign as a phenomenon tumbles to the ground. This topic, however, can hardly be incorporated by any existing theory of semiotics. Under the framework of “the theory of intentional sign,” signic knowledge can find its proper niche as an element of the “context” of a sign process. This niche furnishes a good basis on which to investigate the various aspects of signic knowledge, like its role, nature, origin, and life. Signic knowledge (...) can also be automatized or externalized, whose end results tend to create delusions that obscure the nature of the sign and lead semiotics astray. (shrink)

To better understand what information is and to explain information-related issues has become an essential philosophical task. General concepts from science, ethics and sociology are insufficient. As noted by Floridi, a new philosophy, a Philosophy of Information (PI), is needed. In the 80’s, Wu Kun proposed a “The Basic Theory of the Philosophy of Information”, which became available in English only in 2010. Wu and Joseph Brenner then found that the latter’s non-standard “Logic in Reality” provided critical logical support for (...) Wu’s theory. In Part I of our paper, we outline the two basic theories as a metaphilosophy and metalogic for information. We offer our two theories as a further contribution to an informational paradigm. In Part II [WuB14], we develop the relation between information and social value as a basis for the ethical development of the emerging Information Society. (shrink)

EDITOR’S ABSTRACTThis article argues that Shang Yang’s philosophy of law was not only a means to enrich the state and strengthen its army, but also envisioned the orderly rule of all All-under-Heaven. Through a fair, universal, and reliable use of rewards, punishments, and also teaching, this vision of laws could ultimately lead to the promotion of moral values, popular consensus, and people’s self-governance. While the authors admit that in Shang Yang’s own historical context, law was no more than a tool (...) used by the ruler to suppress his people, potentially his ideas could contribute to a future Chinese society fully ruled by law and morality, and inspired by the rule of law. (shrink)