This study aims to explore effective ways to improve college students’ entrepreneurial self-efficacy and intentions through entrepreneurship education. The survey used a random sample of 804 college students in Zhejiang Province, China. The results show that: In terms of the characteristics of entrepreneurial intention, there are significant differences in gender, entrepreneurial experience, entrepreneurial competition experience, and family background of self-employment. There are significant differences in the characteristics of entrepreneurship education in gender, entrepreneurial competition experience, and the family background of self-employment. (...) In the relationship among entrepreneurship education, entrepreneurial self-efficacy, and entrepreneurial intention, entrepreneurship education is significantly and positively related to entrepreneurial self-efficacy and entrepreneurial intention. Entrepreneurial self-efficacy is significantly and positively associated with entrepreneurial intention. Entrepreneurial self-efficacy plays a complete mediating role between entrepreneurship education and entrepreneurial intention. Entrepreneurial self-efficacy also has a suppressing effect on the relationship between the two. Entrepreneurial competition experience moderates the second half of the mediating effect of entrepreneurial self-efficacy. Finally, the study offers several proposals for the teaching practice of entrepreneurship education. (shrink)
Robot is definitely playing important role in human society. Low contact on machine standards is mostly on industrial robot while close contacts are in increasing demand in service robot, etc. The development of robotics with advanced hardware and artificial intelligence (AI) provide the possibility with human beings while close contacts raise many new issues on ethics and risks. For interaction, the related technique of perception, cognition and interaction are briefly introduced. For ethics, rules should be given for the robot designers (...) to include ethics for certain application while risks should be evaluated during the experiment test. To make efficient decision, safety design with AI technology should be put on agenda for roboticists. Except from the risks, ethics raise many challenges while most of them can be solved by developing technologies while some of the problems exist in human’s society which also raise the questions for the human beings. More broader vision should be taken from different social departments together to avoid the possible embarrassed issues. It’s time to welcome the world of robotics and related techniques will make life more efficient while human-robot coexistence society will come one day and law should be imposed on both. (shrink)
Statistics play a critical role in biological and clinical research. However, most reports of scientific results in the published literature make it difficult for the reader to reproduce the statistical analyses performed in achieving those results because they provide inadequate documentation of the statistical tests and algorithms applied. The Ontology of Biological and Clinical Statistics (OBCS) is put forward here as a step towards solving this problem. Terms in OBCS, including ‘data collection’, ‘data transformation in statistics’, ‘data visualization’, ‘statistical data (...) analysis’, and ‘drawing a conclusion based on data’, cover the major types of statistical processes used in basic biological research and clinical outcome studies. OBCS is aligned with the Basic Formal Ontology (BFO) and extends the Ontology of Biomedical Investigations (OBI), an OBO (Open Biological and Biomedical Ontologies) Foundry ontology supported by over 20 research communities. We discuss two examples illustrating how the ontology is being applied. In the first (biological) use case, we describe how OBCS was applied to represent the high throughput microarray data analysis of immunological transcriptional profiles in human subjects vaccinated with an influenza vaccine. In the second (clinical outcomes) use case, we applied OBCS to represent the processing of electronic health care data to determine the associations between hospital staffing levels and patient mortality. Our case studies were designed to show how OBCS can be used for the consistent representation of statistical analysis pipelines under two different research paradigms. By representing statistics-related terms and their relations in a rigorous fashion, OBCS facilitates standard data analysis and integration, and supports reproducible biological and clinical research. (shrink)
In recent years, sequencing technologies have enabled the identification of a wide range of non-coding RNAs (ncRNAs). Unfortunately, annotation and integration of ncRNA data has lagged behind their identification. Given the large quantity of information being obtained in this area, there emerges an urgent need to integrate what is being discovered by a broad range of relevant communities. To this end, the Non-Coding RNA Ontology (NCRO) is being developed to provide a systematically structured and precisely defined controlled vocabulary for the (...) domain of ncRNAs, thereby facilitating the discovery, curation, analysis, exchange, and reasoning of data about structures of ncRNAs, their molecular and cellular functions, and their impacts upon phenotypes. The goal of NCRO is to serve as a common resource for annotations of diverse research in a way that will significantly enhance integrative and comparative analysis of the myriad resources currently housed in disparate sources. It is our belief that the NCRO ontology can perform an important role in the comprehensive unification of ncRNA biology and, indeed, fill a critical gap in both the Open Biological and Biomedical Ontologies (OBO) Library and the National Center for Biomedical Ontology (NCBO) BioPortal. Our initial focus is on the ontological representation of small regulatory ncRNAs, which we see as the first step in providing a resource for the annotation of data about all forms of ncRNAs. (shrink)
Classification and gradation system adopts different security protection schemes for different types of data by implementing classification and gradation management of data, which is an important pretechnical means for data security protection and prevention of data leakage. This paper introduces artificial intelligence classification, machine learning, and other means to learn and train enterprise documents according to the characteristics of enterprise sensitive data. The generated training model can intelligently identify and classify file streams, improving work efficiency and accuracy of classification and (...) gradation. At the same time, the differences, advantages, and disadvantages of K-NN, DT, and LinearSVC algorithms are compared. The experimental data shows that LinearSVC algorithm is applicable to high-dimensional data, with discrete, sparse data features and large number of features, which is more suitable for classification of sensitive data of enterprises. (shrink)
Closed-loop transcutaneous auricular vagal nerve stimulation was officially proposed in 2020. This work firstly reviewed two existing CL-taVNS forms: motor-activated auricular vagus nerve stimulation and respiratory-gated auricular vagal afferent nerve stimulation, and then proposed three future CL-taVNS systems: electroencephalography -gated CL-taVNS, electrocardiography -gated CL-taVNS, and subcutaneous humoral signals -gated CL-taVNS. We also highlighted the mechanisms, targets, technical issues, and patterns of CL-taVNS. By reviewing, proposing, and highlighting, this work might draw a preliminary blueprint for the development of CL-taVNS.
We investigated if emotion regulation can be improved through self-regulation training on non-emotional brain regions, as well as how to change the brain networks implicated in this process. During the training period, the participants were instructed to up-regulate their right dorsolateral prefrontal cortex activity according to real-time functional near-infrared spectroscopy neurofeedback signals, and there was no emotional element. The results showed that the training significantly increased emotion regulation, resting-state functional connectivity within the emotion regulation network and frontoparietal network, and rsFC (...) between the ERN and amygdala; however, training did not influence the rsFC between the FPN and the amygdala. However, self-regulation training on rDLPFC significantly improved emotion regulation and generally increased the rsFCs within the networks; the rsFC between the ERN and amygdala was also selectively increased. The present study also described a safe approach that may improve emotion regulation through self-regulation training on non-emotional brain regions. (shrink)
Hindrance stress is a stimulus factor in the workplace that has a certain impact on the innovative behavior of employees. Most existing studies focus on the analysis of individual-level factors, ignoring the important role of organizational-level factors. This study uses multiple linear models to empirically analyze the interaction mechanisms among hindrance stress, proactive personality, employment relationship atmosphere, and employee innovative behavior factors in the workplace. This study found the following: Hindrance stress negatively affects employees’ innovative behavior. A proactive personality positively (...) affects employees’ innovative behavior. A proactive personality plays a moderating role in the relationship between hindrance stress and employees’ innovative behavior. The employment relationship atmosphere has a positive impact on employees’ innovative behavior. The employment relationship atmosphere plays a moderating role in the relationship between hindrance stress and employees’ innovative behavior. This study enriches theoretical knowledge in the field of human resources and provides guidance for business managers on the effective encouragement of employees’ innovative behavior. (shrink)