River segmentation of remote sensing images is of important research significance and application value for environmental monitoring, disaster warning, and agricultural planning in an area. In this study, we propose a river segmentation model in remote sensing images based on composite attention network to solve the problems of abundant river details in images and the interference of non-river information including bridges, shadows, and roads. To improve the segmentation efficiency, a composite attention mechanism is firstly introduced in the central region of (...) the network to obtain the global feature dependence of river information. Next, in this study, we dynamically combine binary cross-entropy loss that is designed for pixel-wise segmentation and the Dice coefficient loss that measures the similarity of two segmentation objects into a weighted one to optimize the training process of the proposed segmentation network. The experimental results show that compared with other semantic segmentation networks, the evaluation indexes of the proposed method are higher than those of others, and the river segmentation effect of CoANet model is significantly improved. This method can segment rivers in remote sensing images more accurately and coherently, which can meet the needs of subsequent research. (shrink)

There has been much research into teacher beliefs about teaching and learning as seen in the general teacher education literature. In the field of language teacher education, this line of research has been evolving, with the recent trend being streamlined into “teacher cognition” as a generic or umbrella term. Despite increasing amounts of research output so far, research into foreign language teachers’ cognitions about their own teaching and decision-making is still insufficient, particularly with regard to university-level English-as-a-foreign-language (EFL) teachers in (...) China. Drawing on Vygotsky’s Sociocultural Theory, this qualitative research focused on EFL teachers’ cognitions about form-focused instruction in Chinese university settings. It intended to discover how teachers’ cognitions changed when they were expected to teach in actual classrooms and what factors contributed to these changes. Data collected from four teacher-participants through semi-structured interviews, classroom observations and follow-up stimulated recall interviews showed participants’ support forfocus-on-forminstruction, which means they not only paid attention to the grammatical form of the language but also to the meaning it is intended to convey. However, data also showed that the teacher-participants shifted fromfocus-on-formtofocus-on-formSinstruction in actual teaching, which suggests that they might have realized the challenges of carrying out teaching activities surroundingfocus-on-formand would like to take an easier approach by only teaching the grammar of the language byfocusing on formS. Such incongruences are interpreted with reference to a plethora of sociocultural factors including traditional Chinese thinking and institutional expectations. The implications of the findings for stakeholders in universities, including faculty members, students, and curriculum developers in similar contexts, are also discussed. (shrink)

Despite the bombardment of AI ethics frameworks (AIEFs) published in the last decade, it is unclear which of the many have been adopted in the industry. What is more, the sheer volume of AIEFs without a clear demonstration of their effectiveness makes it difficult for businesses to select which framework they should adopt. As a first step toward addressing this problem, we employed four different existing frameworks to assess AI ethics concerns of a real-world AI system. We compared the experience (...) of applying the AIEFs from the perspective of (a) a third-party auditor conducting an AI ethics risk assessment for the company, and (b) the company receiving the audit outcomes. Our results suggest that the feel-good factor of doing an assessment is common across the AIEFs that can take anywhere between 1.5 and 20 h to complete. However, each framework provides different benefits (e.g., issue discovery vs. issue monitoring) and is likely best used in conjunction with one another at different stages of an AI development process. As such, we call on the AI ethics community to better specify the suitability and expected benefits of existing frameworks to enable better adoption of AI ethics practice in the industry. (shrink)

The product market competition has become a global challenge for business organizations in the challenging and competitive market environment in the influx of the COVID-19 outbreak. The influence of products competition on organizational performance in developed economies has gained scholars’ attention, and numerous studies explored its impacts on business profitability. The existing studies designate mixed findings between the linkage of CSR practices and Chinese business firms’ healthier performance in emerging economies; however, the current global crisis due to the coronavirus has (...) made product market completion fierce, which ultimately affects business firms’ performance. This study focuses on this logical global challenge, investigates the rationale, and examines product-market completion impact on firms’ performance operating in the Chinese markets. The study collected data from the annual reports of Chinese business organizations with A-share listing and registered with the database of China Stock Markets and Accounting Research. The study employed a Generalized Method of Moment technique and investigated the connection between product market competition and Chinese firm performance. The empirical analysis of this study highlights the conclusion that market competition positively and significantly affected business firms’ performance. This study specified that product market competition play a dynamic and indispensable role in achieving healthier firm performance in the Chinese markets. This study provides valuable insights on practical implications and future research directions for the scholars to draw interesting results with new study models. (shrink)

To obtain effective fusion results of multi source evidences with different importance, an evidence fusion method with importance discounting factors based on neutrosopic probability analysis in DSmT framework is proposed. First, the reasonable evidence sources are selected out based on the statistical analysis of the pignistic probability functions of single focal elements. Secondly, the neutrosophic probability analysis is conducted based on the similarities of the pignistic probability functions from the prior evidence knowledge of the reasonable evidence sources. Thirdly, the importance (...) discounting factors of the reasonable evidence sources are obtained based on the neutrosophic probability analysis and the reliability discounting factors of the real-time evidences are calculated based on probabilistic-based distances. Fourthly, the real-time evidences are discounted by the importance discounting factors and then the evidences with the mass assignments of neutrosophic empty sets are discounted by the reliability discounting factors. Finally, DSmT+PCR5 of importance discounted evidences is applied. Experimental examples show that the decision results based on the proposed fusion method are different from the results based on the existed fusion methods. Simulation experiments of recognition fusion are performed and the superiority of proposed method is testified well by the simulation results. (shrink)

Motion pose capture technology can effectively solve the problem of difficulty in defining character motion in the process of 3D animation production and greatly reduce the workload of character motion control, thereby improving the efficiency of animation development and the fidelity of character motion. Motion gesture capture technology is widely used in virtual reality systems, virtual training grounds, and real-time tracking of the motion trajectories of general objects. This paper proposes an attitude estimation algorithm adapted to be embedded. The previous (...) centralized Kalman filter is divided into two-step Kalman filtering. According to the different characteristics of the sensors, they are processed separately to isolate the cross-influence between sensors. An adaptive adjustment method based on fuzzy logic is proposed. The acceleration, angular velocity, and geomagnetic field strength of the environment are used as the input of fuzzy logic to judge the motion state of the carrier and then adjust the covariance matrix of the filter. The adaptive adjustment of the sensor is converted to the recognition of the motion state. For the study of human motion posture capture, this paper designs a verification experiment based on the existing robotic arm in the laboratory. The experiment shows that the studied motion posture capture method has better performance. The human body motion gesture is designed for capturing experiments, and the capture results show that the obtained pose angle information can better restore the human body motion. A visual model of human motion posture capture was established, and after comparing and analyzing with the real situation, it was found that the simulation approach reproduced the motion process of human motion well. For the research of human motion recognition, this paper designs a two-classification model and human daily behaviors for experiments. Experiments show that the accuracy of the two-category human motion gesture capture and recognition has achieved good results. The experimental effect of SVC on the recognition of two classifications is excellent. In the case of using all optimization algorithms, the accuracy rate is higher than 90%, and the final recognition accuracy rate is also higher than 90%. In terms of recognition time, the time required for human motion gesture capture and recognition is less than 2 s. (shrink)

ObjectivesSeveral studies have examined the effects of repetitive transcranial magnetic stimulation (rTMS) on associative memory (AM) but findings were inconsistent. Here, we aimed to test whether twice-daily rTMS could significantly improve AM.MethodsIn this single-blind, sham-controlled experiment, 40 participants were randomized to receive twice-daily sham or real rTMS sessions for five consecutive days (a total of 16,000 pulses). The stimulation target in left inferior parietal lobule (IPL) exhibiting peak functional connectivity to the left hippocampus was individually defined for each participant. Participants (...) completed both a picture-cued word association task and Stroop test at baseline and 1 day after the final real or sham rTMS session. Effects of twice-daily rTMS on AM and Stroop test performance were compared using two-way repeated measures analysis of variance with main factors Group (real vs. sham) and Time (baseline vs. post-rTMS).ResultsThere was a significant Group × Time interaction effect. AM score was significantly enhanced in the twice-daily real group after rTMS, but this difference could not survive the post hoc analysis after multiple comparison correction. Further, AM improvement in the twice-daily real group was not superior to a previously reported once-daily rTMS group receiving 8,000 pulses. Then, we combined the twice- and once-daily real groups, and found a significant Group × Time interaction effect. Post hoc analysis indicated that the AM score was significantly enhanced in the real group after multiple comparisons correction.ConclusionOur prospective experiment did not show significant rTMS effect on AM, but this effect may become significant if more participants could be recruited as revealed by our retrospective analysis. (shrink)

As a NP-hard problem that needs to be solved in real time, the dynamic task allocation problem of unmanned aerial vehicle swarm has gradually become a difficulty and hotspot in the current planning field. Aiming at the problems of poor real-time performance and low quality of the solution in the dynamic task allocation of heterogeneous UAV swarm in uncertain environment, this paper establishes a dynamic task allocation model that can meet the actual needs and uses the binary wolf pack algorithm (...) to solve it, so as to propose a dynamic task allocation method of heterogeneous UAV swarm in uncertain environment. In this method, a dynamic mechanism of attacking while searching and priority attacking of important targets is designed. A dynamic task allocation model of multitarget, multitask, heterogeneous multiaircraft platform and multiconstraint is established based on the target cost-effectiveness ratio and task execution time window. In addition, one-dimensional 0–1 coding method is adopted to encode the task allocation scheme. Furthermore, the wolf pack algorithm is introduced in brief. This paper focuses on the BWPA with the good computational robustness and strong global search ability to solve the dynamic allocation model. According to the simulation results, the designed task allocation method not only has good adaptability to the change of target and UAV number, as well as good stability and scalability, but also can effectively solve the dynamic task allocation problem of heterogeneous UAV swarm in unknown environment. Therefore, the established model and solution method can provide a useful reference for task allocation and other related problems. (shrink)

PurposeThe primary angle-closure glaucoma is an irreversible blinding eye disease in the world. Previous neuroimaging studies demonstrated that PACG patients were associated with cerebral changes. However, the effect of optic atrophy on local and remote brain functional connectivity in PACG patients remains unknown.Materials and MethodsIn total, 23 patients with PACG and 23 well-matched Health Controls were enrolled in our study and underwent resting-state functional magnetic resonance imaging scanning. The regional homogeneity method and functional connectivity method were used to evaluate the (...) local and remote brain functional connectivity. Moreover, support vector machine method was applied to constructing PACG classification model.ResultsCompared with the HC, PACG patients showed increased ReHo values in right cerebellum _8, left CER_4-5, and right CER_8. In contrast, PACG patients showed decreased ReHo values in the bilateral lingual gyrus /calcarine /superior occipital gyrus and right postcentral gyrus. The ReHo value exhibited an accuracy of 91.30% and area under curve of 0.95 for distinguishing the PACG patients from HC.ConclusionOur study demonstrated that the PACG patients showed abnormal ReHo value in the cerebellum, visual cortex, and supplementary motor area, which might be reflect the neurological mechanisms underlying vision loss and eye pain in PACG patients. Moreover, the ReHo values can be used as a useful biomarker for distinguishing the PACG patients from HCs. (shrink)

国家哲学社会科学创新基地浙江大学语言与认知研究中心研究成果中国博士后科学基金资助.

Understanding and solving the psychological health problems of college students have become a focus of social attention. Complex networks have become important tools to study the factors affecting psychological health, and the Gaussian graphical model is often used to estimate psychological networks. However, previous studies leave some gaps to overcome, including the following aspects. When studying networks of subpopulations, the estimation neglects the intrinsic relationships among subpopulations, leading to a large difference between the estimated network and the real network. Because (...) of the high cost, previous psychological surveys often have a small sample size, and the psychological description is insufficient. Here, the intrinsic connections among multiple tasks are used, and multitask machine learning is applied to develop a multitask Gaussian graphical model. The psychological networks of the population and subpopulations are estimated based on psychological questionnaire data. This study is the first to apply a psychological network to such a large-scale college student psychological analysis, and we obtain some interesting results. The model presented here is a dynamic model based on complex networks which predicts individual behavior and provides insight into the intrinsic links among various symptoms. (shrink)

Extreme Learning Machine is widely used in various fields because of its fast training and high accuracy. However, it does not primarily work well for Domain Adaptation in which there are many annotated data from auxiliary domain and few even no annotated data in target domain. In this paper, we propose a new variant of ELM called Discriminative Extreme Learning Machine with Cross-Domain Mean Approximation for unsupervised domain adaptation. It introduces Cross-Domain Mean Approximation into the hidden layer of ELM to (...) reduce distribution discrepancy between domains for domain bias elimination, which is conducive to train a high accuracy ELM on annotated data from auxiliary domains for target tasks. Linear Discriminative Analysis is also adopted to improve the discrimination of learned model and obtain higher accuracy. Moreover, we further provide a Discriminative Kernel Extreme Learning Machine with Cross-Domain Mean Approximation as the kernelization extension of DELM-CDMA. Some experiments are performed to investigate the proposed approach, and the result shows that DELM-CDMA and DKELM-CDMA could effectively extend ELM suitable for domain adaptation and outperform ELM and many other domain adaptation approaches. (shrink)

Socioeconomic status refers to the social position or class according to their material and non-material social resources. We conducted a study with 60 college students to explore whether SES affects past self-evaluation and used event-related potentials in a self-reference task that required participants to judge whether the trait adjectives describing themselves 5 years ago were appropriate for them. Behavioral data showed that individuals’ positive past self-evaluations were significantly higher than individuals’ negative past self-evaluations, regardless of high or low SES. Individuals (...) with high SES had significantly higher positive past self-evaluations than those with low SES. ERP data showed that in the low SES group, negative adjectives elicited a marginally greater N400 amplitude than positive adjectives; in the high SES group, negative adjectives elicited a greater late positive potential amplitude than positive adjectives. N400 is an index of the accessibility of semantic processing, and a larger N400 amplitude reflects less fluent semantic processing. LPP is an index of continuous attention during late processing; the larger LPP amplitude is elicited, the more attention resources are invested. Our results indicated that compared with college students with low SES, the past self-evaluations of college students with high SES were more positive; college students with high SES paid more attention to negative adjectives. However, college students with low SES were marginally less fluent in processing negative adjectives. (shrink)

In recent years, the analysis of legal judgments and the prediction of outcomes based on case factual descriptions have become hot research topics in the field of judiciary. Among them, the task of charge prediction aims to predict the applicable charges of a judicial case based on its factual description, making it an important research area in the intelligent judiciary. While significant progress has been made in machine learning and deep learning, traditional methods are limited to handling data in Euclidean (...) space and cannot effectively capture the semantic information in the text. To overcome the limitations of traditional learning approaches, many studies have started exploring the use of graphs to represent rich relationships between entities in text and employing graph convolutional neural networks to learn text representations. In this paper, we propose a charge prediction method based on graph convolutional neural networks. By constructing a similarity graph between cases and utilizing graph convolutional neural networks to learn case feature representations, we can better capture the relational information between cases and improve the accuracy of charge prediction. Experimental results on multiple benchmark datasets demonstrate that our proposed model outperforms traditional methods in charge prediction tasks. (shrink)

This study aimed to investigate the relationship of employee growth mindset with innovative behavior and the mediating role of use of strength as well as the moderating role of strengths-based leadership in this relationship. Data with a sample of 244 employees working in diverse Chinese organizations were collected at two points in time. Results of bootstrapping analyses demonstrated that growth mindset is positively related to innovative behavior, employee strengths use partially mediates the positive relationship of growth mindset with innovative behavior, (...) and strengths-based leadership strengthens the direct relationship between employee growth mindset and innovative behavior and the indirect relationship of employee growth mindset with innovative behavior via strengths use. This study advances growth mindset and innovative behavior theories and research. (shrink)

In the context of coronavirus pandemic, the face-recognition-based access control system has been intensively adopted to protect students’ and teachers’ health and safety in school. However, the impact of FACS, as a new technology, on students’ attitude toward accepting FACS has remained unknown from the psychological halo effect. Drawn on “halo effect” theory where psychological effects affect the sense of social identity and belonging, the present study explored college students’ sense of school identity and belonging in using FACS during COVID-19 (...) based on the technology acceptance model. Data collected from 391 college students was analyzed using SEM to verify the relationship among perceived usefulness, perceived ease of use, intention to use, school identity, and school belonging. The results show that PU and PEU can positively predict IU, and consequentially can positively predict school identity and school belonging. Our study expands the application of halo effect theory to study FACS acceptance based on TAM, and provides strong evidence to support the effect of school FACS during the pandemic. The findings of this study also suggest that FACS acceptance can enhance students’ sense of school identity and belonging. (shrink)

This article reviews the history of international mobility of students from China to other countries over the century and a half from 1870 to the present day. Different motivations, goals, courses, and knowledge are considered, together with how the purposes of individuals have matched national policy. Implications for the future development in a globalized context are briefly considered.

Previous studies on crisis know­ledge organization mostly focused on the categorization of crisis know­ledge without regarding its dynamic trend and temporal-spatial features. In order to emphasize the dynamic factors of crisis collaboration, a fine-grained crisis know­ledge model is proposed by integrating temporal-spatial analysis based on ontology, which is one of the commonly used methods for know­ledge organization. The reconstruction of ontology-based crisis know­ledge will be implemented through three steps: analyzing temporal-spatial features of crisis know­ledge, reconstructing crisis know­ledge ontology, and verifying (...) the temporal-spatial ontology. In the process of ontology reconstruction, the main classes and properties of the domain will be identified by investigating the crisis information resources. Meanwhile the fine-grained crisis ontology will be achieved at the level of characteristic representation of crisis know­ledge including temporal relationship, spatial relationship, and semantic relationship. Finally, we conducted case addition and system implementation to verify our crisis know­ledge model. This ontology-based know­ledge organization method theoretically optimizes the static organizational structure of crisis know­ledge, improving the flexibility of know­ledge organization and efficiency of emergency response. In practice, the proposed fine-grained ontology is supposed to be more in line with the real situation of emergency collaboration and management. Moreover, it will also provide the know­ledge base for decision-making during rescue process. (shrink)

Climate change and farming malpractices are harmful to the globe's productive soil and biodiversity, thereby posing a hazard to the survival of future generations. Innovative technologies provide continuous smart conservation solutions, such as regenerative farming, to confront the ongoing climate crisis and maintain biodiversity. Albeit, regenerative farming has the potential to conserve climate change by upgrading the soil's organic materials and reinstating biodiversity leading to carbon attenuation. However, a critical problem remains concerning adapting conservation farming practices that can assist low-income (...) farmers. In this scenario, theoretical-driven communication campaigns are critical for addressing individuals' resistance to innovation. Thereby, this research uncovers the moderating influence of the numerous communication tools in determining the adoption of regenerative farming through diminishing farmers' resistance to innovation. The study employed a cross-sectional design vis-à-vis a survey method. A sample of 863 farmers participated by responding to the self-administrated questionnaire. In line with prior theories, the study's results identified that communication campaigns such as public service advertisements and informative scientific documentaries could reduce the resistance to innovation that increases the attitude toward the adoption of regenerative farming with varied intensity. Besides, informational support also remained a significant contributor in determining the intention to adopt regenerative farming. This specifies that implanting habits of conservation farming requires the initiation of communication campaigns using different media content. These results may be advantageous for policymakers to influence farmers' intentions to adopt regenerative farming. (shrink)

本书内容包括:论计算机网络犯罪现状、民法中的法律行为概念之界定、浅论国家控制力与行政法改革、从国际法谈两岸关系等。.

This study examines whether community social capital in US counties, as captured by strength of civic norms and density of social networks in the counties, affects corporate social responsibility of resident corporations headquartered in the counties. Analyses of longitudinal data from 3688 unique US firms between 1997 and 2009 provide strong empirical support for the propositions that community social capital facilitates positive CSR activities that benefit non-shareholder stakeholders and constrains negative CSR activities that are detrimental to non-shareholder stakeholders. Additionally, we (...) explore the effects of institutional logics arising from community isomorphism on positive and negative CSR activities, respectively. And, we explore the respective effects of corporate engagement in positive and negative CSR activities on corporate financial performance. Firms undertake more positive CSR activities when such activities are more prevalent among other local corporations headquartered in the same county. But, there is no systematic relationship between negative CSR activities and the community-level corporate engagement in negative CSR activities. Positive CSR activities enhance a firm’s future financial performance, and the positive effect is more prominent among firms headquartered in counties with high community social capital. However, negative CSR activities only reduce a firm’s future financial performance among firms headquartered in counties with high community social capital; negative CSR activities do not affect performance among firms headquartered in counties with lower levels of community social capital. Collectively, these results highlight the distinct effects of local social institutions, namely community social capital, on positive CSR activities and negative CSR activities, respectively. (shrink)

Brain structural covariance network can delineate the brain synchronized alterations in a long-range time period. It has been used in the research of cognition or neuropsychiatric disorders. Recently, causal analysis of structural covariance network, winner-take-all and cortex–subcortex covariance network, and modulation analysis of structural covariance network have expended the technology breadth of SCN. However, the lack of user-friendly software limited the further application of SCN for the research. In this work, we developed the graphical user interface toolkit of brain structural (...) covariance connectivity based on MATLAB platform. The software contained the analysis of SCN, CaSCN, MOD-SCN, and WTA-CSSCN. Also, the group comparison and result-showing modules were included in the software. Furthermore, a simple showing of demo dataset was presented in the work. We hope that the toolkit could help the researchers, especially clinical researchers, to do the brain covariance connectivity analysis in further work more easily. (shrink)

In the current study, late Chinese–English bilinguals performed a facial expression identification task with emotion words in the task-irrelevant dimension, in either their first language or second language. The investigation examined the automatic access of the emotional content in words appearing in more than one language. Significant congruency effects were present for both L1 and L2 emotion word processing. Furthermore, the magnitude of emotional face-word Stroop effect in the L1 task was greater as compared to the L2 task, indicating that (...) in L1 participants could access the emotional information in words in a more reliable manner. In summary, these findings provide more support for the automatic access of emotional information in words in the bilinguals’ two languages as well as attenuated emotionality of L2 processing. (shrink)

Abusive supervision is quite common in the service industry. Employees’ proactive customer service performance is essential for the long-term development of service enterprises. This study enriches the antecedents of proactive customer service performance from a new theoretical perspective by incorporating the analysis of abusive supervision into the theoretical framework and fills the research gap between customer orientation and proactive customer service performance. Based on Affective Events Theory and Social Cognitive Theory, this study established the structure equation model between abusive supervision (...) and proactive customer service performance mediated by affective commitment and customer orientation. Utilizing structural equation modeling, a negative association between abusive supervision and proactive customer service performance was found, and affective commitment and customer orientation act as the mediators between abusive supervision and proactive customer service performance. In addition, the implications for future study were also discussed. (shrink)

Changes in the external market environment put forward objective requirements for the formulation of organizational strategic plans, making it difficult for the organization’s leaders to make the right and effective decisions quickly on their own. As a result, participative leadership, which encourages and supports employees to participate in the decision-making process of organizations, has received increasing attention in both theory and practice. We searched the literature related to participative leadership in databases such as Web of Science, EBSCO, ProQuest, and China (...) National Knowledge Infrastructure. Based on this, we clarify the concept of participative leadership, propose a definition of participative leadership, summarize measurement scales for this type of leadership, and compare participative leadership with other leadership styles. We also present a research framework for participative leadership that demonstrates its antecedents; the mechanisms for its development based on social exchange theory, conservation of resources theory, social cognitive theory; social information processing theory, and implicit leadership theory; and outcomes. Finally, we identify five potential research areas: Connotation, antecedents, outcomes, mediators and moderators, and study of participative leadership in China. (shrink)

This study focuses on the evolution and preservation of the cultural heritage of the Ti-Tzu ten-hole bamboo flute in Sichuan Province, China. For collecting data, the researchers conducted interviews and observations. The results of the study show that Shen Wenyi's original work resulted in the invention of bamboo flutes with seven, nine, and ten holes, which are significant findings. These developments resolved issues with pitch discrepancies and broadened the range of playing techniques, influencing the flute's cultural importance and musical repertoire. (...) The study also emphasizes educational endeavors, group development, and textbook creation to safeguard and advance the flute tradition. It highlights the lasting impact and constant evolution of the Ti-Tzu ten-hole bamboo flute as a representation of cultural heritage and a source of pride in Sichuan Province. (shrink)

One aspect of the intellectual changes taking place in China in the late nineteenth and early twentieth centuries was the emergence of utilitarian ideas. Although it may be useful to think of modern Chinese thought from the perspective of the emergence of social Darwinism and nationalism, it is significant that the country's most progressive scholars at the turn of thecentury derived their inspiration from utilitarianism. Utilitarianism was accepted as a weapon with which to challenge traditional social, political, and cultural ideas, (...) and to justify social and political reforms. (shrink)

In recent years, the Audit Pilot of Natural Resources Assets (APNRA) pilot program has been implemented by the Chinese government to strengthen the protection of natural resources and the ecological environment. Based on the APNRA pilot program, we use the multi-period differences–in–differences model to investigate the response of corporate environmental responsibility to external governance pressure. We find that firms significantly improve their environmental investment and performance after the implementation of the APNRA pilot program. Sewage charges (including green fees) and ecological (...) protection incentives constitute the two main channels that explain the positive relationship. We further find that the impact of the program on corporate environmental investment and performance is more pronounced for firms in regions with poor environmental quality, and for firms in heavy-polluting industries. This paper introduces the role of government governance in generating positive externality for firms and provides a valuable understanding of environmental governance in an emerging market. (shrink)

Background Social responsibility can motivate disaster relief nurses to devote themselves to safeguarding rights and interests of people when facing challenges that threaten public health. However, few studies focused on the relationship of moral courage, job-esteem, and social responsibility among disaster relief nurses. Objective To explore the influence of moral courage and job-esteem on the social responsibility in disaster relief nurses and clarify the relationship model between them. Methods A cross-sectional study was conducted among 716 disaster relief nurses from 14 (...) hospitals in central China through an online survey, including moral courage scale, job-esteem scale, and social responsibility questionnaire. The data were analyzed by Pearson’s correlation, and the mechanism of the effect of moral courage and job-esteem on social responsibility was completed. Ethical considerations This study was approved by the Medical Ethics Committee of the Second Xiangya Hospital of Central South University (Approval Number: 2019016). Results Disaster relief nurses’ moral courage positively impacted social responsibility (r = 0.677, p < 0.01), and moral courage could affect social responsibility through the mediating role of job-esteem. Conclusion Job-esteem mediated between moral courage and social responsibility among disaster relief nurses. Nursing managers regular assessment of nurses’ moral courage and interventions such as meetings and workshops can reduce moral distress, foster morally courageous behavior, enhance job-esteem, and improve social responsibility performance among disaster relief nurses. (shrink)

1. IntroductionFirst and foremost, the public sphere is the sphere of our social life. Social media’s naturally low barrier to entry and strong participatory attributes have made it more deeply rooted in human social life than any other media before it. Consequently, many scholars have put forward views and theories arguing that the web is essentially a public sphere.

During late embryonic and early postnatal development, synaptic connections are extensively modified so that some functional connections are weakened and eliminated from a neural circuit while others are strengthened and maintained. The mechanisms that underlie synapse elimination are beginning to be understood from studies of the neuromuscular junction. A recent paper(1) provides some intriguing insights into the role proteases may play in the developmental disassembly of neuromuscular synapses.