Improving innovation and entrepreneurship education in higher institutions: the impact of "Mass Entrepreneurship and Innovation" education on undergraduates' entrepreneurial intentions

The exploration of the way"mass entrepreneurship and innovation"(MEI)education influences students'aspirations to become entrepreneurs has grown into an important area of analysis in studies related to higher education.This research intends to examine the consequences of MEI education on students'tendency towards entrepreneurship,and to put forward methods for augmenting the teaching of innovation and entrepreneurship in private higher educational establishments.To achieve this objective,questionnaires and semi-structured interviews were employed in the study,which involved a total of 197 students and five education experts.The statistical analysis of the questionnaire data revealed that MEI education was positively related to students'entrepreneurial intentions,and that both entrepreneurial experience and family entrepreneurial background played moderating roles in this relationship.The interview findings indicated that private universities could enhance educational reforms by designing talent training programs,developing diversified curricula,and developing more professional entrepreneurial platforms to encourage students'entrepreneurial intentions.This study offers fresh insights for improving and perfecting the mechanism of innovation and entrepreneurship education in private universities.

Cardiovascular health awareness,risk perception,behavioural intention and INTERHEART risk stratification among middle-aged adults in Malaysia

Objective:To investigate the interrelationship between cardiovascular health awareness,risk perception,behavioural intention,and INTERHEART risk stratification in a middle-aged adult population in Malaysia.Methods:A cross-sectional survey with convenience sampling was conducted during November 2022 and January 2023.Participants completed validated questionnaires assessing cardiovascular health awareness,risk perception of cardiovascular diseases,behavioural intention towards adopting healthy habits,and INTERHEART risk stratification score(IHRS)based on established risk factors.A total of 602 respondents were included in the final analysis.Data were analysed with independent t-test/one-way ANOVA or Mann-Whitney/Kruskal-Wallis to test the differences,Pearson correlation or linear regression test to analyze the association of independent and dependent variables.Results:There was a significant positive correlation between medical knowledge related to cardiovascular disease(CVD)and knowledge related to CVD risk prevention,risk perception,behavioural intention and IHRS(P<0.05,Pearson correlation).Notably,individuals with higher IHRS tended to have lower knowledge related to CVD and CVD risk prevention,risk perception,and behavioural intention.Males,laborers,active/former smokers,individuals with lower household income and educational levels,those involved in occupations not related to the healthcare sector,and those who did not receive the CVD health brochure or are unaware of health self-assessment tools are likely to have lower levels of knowledge,risk perception,and poorer behavioural intention regarding cardiovascular health(P<0.05,one-way ANOVA).While educational level,smoking status,awareness about CVD poster,self-assessment tools were repeatedly significantly associated with knowledge related to CVD and CVD risk prevention,risk perception,behavioral intention and/or IHRS(P<0.05,linear regression).Conclusions:These findings underscore the importance of promoting cardiovascular health awareness and risk perception among middle-aged adults to foster positive BI and reduce CVD risk.Tailored interventions targeting specific risk factors identified by INTERHEART may enhance risk stratification accuracy and facilitate targeted preventive strategies.

CBA: multi source fusion model for fast and intelligent target intention identification

How to mine valuable information from massive multisource heterogeneous data and identify the intention of aerial targets is a major research focus at present. Aiming at the longterm dependence of air target intention recognition, this paper deeply explores the potential attribute features from the spatiotemporal sequence data of the target. First, we build an intelligent dynamic intention recognition framework, including a series of specific processes such as data source, data preprocessing,target space-time, convolutional neural networks-bidirectional gated recurrent unit-atteneion (CBA) model and intention recognition. Then, we analyze and reason the designed CBA model in detail. Finally, through comparison and analysis with other recognition model experiments, our proposed method can effectively improve the accuracy of air target intention recognition,and is of significance to the commanders’ operational command and situation prediction.

KGTLIR:An Air Target Intention Recognition Model Based on Knowledge Graph and Deep Learning

As a core part of battlefield situational awareness,air target intention recognition plays an important role in modern air operations.Aiming at the problems of insufficient feature extraction and misclassification in intention recognition,this paper designs an air target intention recognition method(KGTLIR)based on Knowledge Graph and Deep Learning.Firstly,the intention recognition model based on Deep Learning is constructed to mine the temporal relationship of intention features using dilated causal convolution and the spatial relationship of intention features using a graph attention mechanism.Meanwhile,the accuracy,recall,and F1-score after iteration are introduced to dynamically adjust the sample weights to reduce the probability of misclassification.After that,an intention recognition model based on Knowledge Graph is constructed to predict the probability of the occurrence of different intentions of the target.Finally,the results of the two models are fused by evidence theory to obtain the target’s operational intention.Experiments show that the intention recognition accuracy of the KGTLIRmodel can reach 98.48%,which is not only better than most of the air target intention recognition methods,but also demonstrates better interpretability and trustworthiness.

Promoting sustainable consumption and circular economy:the intention of Vietnamese youth consumers to purchase products made from recycled plastics

Recycling is viewed as a key component in a circular economy and serves as an ideal solution for promoting sustainability.During the global plastic crisis,plastic recycling practices have been adopted worldwide,leading to the production of various products made from recycled plastics(PRP).Nevertheless,a gap persists between consumption and demand for such products,which is primarily attributed to a lack of comprehension from the consumer perspective.Given the pivotal role consumers play in the adoption of these products,this study explores consumers’intentions to purchase PRP.This is particularly significant in Vietnam,which is an emerging economy aspiring to achieve the objectives of a circular economy and sustainable development.Utilizing an integrated cognitive-emotional framework comprising the Valence Theory and the Norm Activation Model,data from 564 Vietnamese students were gathered and analyzed using structural equation modeling.The results show that awareness of consequences is a major driver of consumer purchase intentions,followed by perceived ease of application and monetary incentives.The results also indicate that health concerns have the strongest effect on purchase intention and in the negative side,meaning that the health-related risk is the primary concern for consumers during the decision-making process.This research holds substantial value for academics and managers,as it aids in the theoretical exploration and the formulation of strategies to improve consumer acceptance of PRP.

Analysis of risk factors for postoperative anxiety and depression in endometriosis patients with reproductive intention

BACKGROUND The occurrence of postoperative depression and anxiety in patients with endomet-riosis(EMS)not only causes psychological distress,but may also harm their physical health.AIM To explore the postoperative depression status,and its influencing factors,of EMS patients with reproductive intention.METHODS A total of 321 EMS patients with reproductive intent were included.Using the self-rating anxiety scale and self-rating depression scale,EMS patients with anxiety or depression were distinguished.A clinical model for predicting anxiety or depression in EMS patients was constructed and evaluated using a nomogram,receiver operating characteristic curve,and calibration curve.RESULTS The results of the single factor analysis showed that smoking,coffee,EMS stage,chronic pelvic pain,and sexual discomfort may be related to anxiety.Further,smoking,drinking,spouse,annual household income and EMS stage may be related to depression in EMS patients.Multivariate logistic regression illustrated that smoking,coffee,chronic pelvic pain and sexual discomfort may be inde-pendent risk factors for anxiety in EMS patients,while smoking,EMS stage(Phase III and Phase IV),spouse and high annual household income may be independent risk factors for depression in EMS patients.Additionally,the models used to predict the risk of anxiety or depression in EMS patients have good predictive value.CONCLUSION The anxiety and depression of EMS patients may be related to many factors.In clinical treatment,additional attention should be paid to the psychological status of EMS patients.

A Cognitive Study on Politeness Intention Processing and Its Association with Pragmatic Failure in Cross-Cultural Communication

Although a large number of studies have focused on various aspects of politeness,very little is known about how politeness intention is activated cognitively during verbal communication.The present study aims to explore the cognitive mechanism of politeness intention processing,and how it is related to pragmatic failure during cross-cultural communication.Using 30 Chinese EFL university students who were instructed to finish a probe word judgment task with 96 virtual scenarios,the results indicate that within both mono-and cross-cultural contexts,the response time in the experimental scenarios was significantly slower than that of the filler scenarios.This suggests that politeness intention was activated while understanding the surface meaning of the conversation;however,the EFL learners could not completely avoid the negative transfer of their native politeness conventions when they were comprehending the conversational intention of the target language.Furthermore,no significant differences in response time were found between the groups with high and low English pragmatic competence,illustrating that transferring the pragmatic rules and principles into cross-cultural communication skills was more cognitively demanding.Overall,this study adds to the literature on politeness research and provides some implications for foreign language pragmatic instructions.

Parental Psychological Control and Internet Gaming Disorder Tendency:A Moderated Mediation Model of Core Self-Evaluation and Intentional Self-Regulation

Internet gaming disorder(IGD)among junior high school students is an increasingly prominent mental health concern.It is important to look for influences behind internet gaming disorder tendency(IGDT)in the junior high school student population.The present study aimed to reveal the explanatory mechanisms underlying the association between parental psychological control(PPC)and internet gaming disorder tendency among junior high school students by testing the mediating role of core self-evaluation(CSE)and the moderating role of intentional self-regulation(ISR).Participants in present study were 735 Chinese junior high school students who completed offline self-report questionnaires on parental psychological control,core self-evaluation,intentional self-regulation,and Internet gaming disorder tendency.Analyses were conducted via mediation and moderated mediation.The results showed that:(1)Parental psychological control was positively related to junior high school students’Internet gaming disorder tendency.Core self-evaluation,and intentional self-regulation were negatively related to junior high school students’Internet gaming disorder tendency,respectively.(2)Core self-evaluation partially mediated the relationship between parental psychological control and junior high school students’Internet gaming disorder tendency.(3)Intentional self-regulation moderated the association between parental psychological control and Internet gaming disorder tendency,as well as the relationships between parental psychological control and core self-evaluation and core self-evaluation and Internet gaming disorder tendency in the mediated model.Based on these findings,we believe that there is a need to weaken parental psychological control,strengthen junior high school students’core self-evaluation and intentional self-regulation,and to recognize the important role of parents as well as their children’s personal positive traits in the healthy development of junior high school students.

The Impact of E-Commerce Live Broadcasts on Consumers’Purchase Intention

E-commerce live broadcast has an important influence on consumers’purchase intention.The three dimensions of live broadcast content in the broadcast room are the number of comments,product quality,and live content as independent variables.A theoretical model is constructed with perceived value and risk as intermediaries and the consumers’purchase intention as the dependent variable,and corresponding hypotheses are put forward.We designed the scale,collected relevant data,and tested the model hypothesis using Statistical Package for Social Sciences(SPSS)and Analysis of Moment Structure(AMOS)software.The study found that the number of comments and product quality had a significant impact on perceived value,perceived risk,and consumers’purchase intention.From this conclusion,it is suggested that businesses should control the number of comments,strengthen the product quality of comments,and distinguish the repetition degree of the content of live broadcasts.

Driver Intent Prediction and Collision Avoidance With Barrier Functions

For autonomous vehicles and driver assist systems,path planning and collision avoidance algorithms benefit from accurate predictions of future location of other vehicles and intent of their drivers.In the literature,the algorithms that provide driver intent belong to two categories:those that use physics based models with some type of filtering,and machine learning based approaches.In this paper we employ barrier functions(BF)to decide driver intent.BFs are typically used to prove safety by establishing forward invariance of an admissible set.Here,we decide if the“target”vehicle is violating one or more possibly fictitious(i.e.,non-physical)barrier constraints determined based on the context provided by the road geometry.The algorithm has a very small computational footprint and better false positive and negative rates than some of the alternatives.The predicted intent is then used by a control barrier function(CBF)based collision avoidance system to prevent unnecessary interventions,for either an autonomous or human-driven vehicle.

Review and Comparison of Classical Entrepreneurial Intention Models

The study of entrepreneurial models carries significance in guiding the development of entrepreneurial activities.On the basis of a literature review,this paper reviews and analyzes six classic and widely influential entrepreneurial models:entrepreneurial event model(EEM),entrepreneurial intention model(EIM),revised EIM,theory of planned behavior(TPB),economic psychological model(EPM),and structural model of entrepreneurial intention(SMEI).This paper aims to discuss the similarities and differences of these entrepreneurial intention models and their applications in different contexts,which carries important theoretical and practical significance for further research on entrepreneurial behavior and intention.

What Drives Migrants Back to Set up Firms?Return-home Entrepreneurial Intention of Rural Migrant Workers in China

The extant literature on international immigrants has discussed migrants’entrepreneurial activities in the context of Western countries but has paid little attention to return-home entrepreneurial intention(RHEI).Rural migrant workers(RMWs)in China,who used to promote rural development by remittances and were characterized by similarities with early international migrants,have gradually returned to their hometowns to initiate entrepreneurial activities.Based on the structured questionnaire conducted in 2015 and 2020in Anhui Province,China,this article combines the concept of mixed embeddedness with the idea of double-layered embeddedness and analyzes the impacts of the social,economic and institutional context in RMWs’hometowns and migration destinations on RMWs’RHEI by using binary logistic regression.The article shows that the social,economic,and institutional environments of RMWs’hometowns and migration destinations have effects on their RHEI.The embeddedness in the economic and informal institutional context in RMWs’RHEI is even more important than personal characteristics.Compared with migration destinations,RMWs’hometowns exert a more influential effect on their RHEI.However,that does not mean that the role of migration destinations can be undervalued.Actually,the better the social,economic,and institutional environments of migration destinations RMWs moved into is,the higher entrepreneurial intention they will have after returning to their hometowns.The article proposes a modified framework in combination of mixed embeddedness with double-layer embeddedness and proves that it is suitable for analyzing RMWs’RHEI.The framework has important implications for strengthening China’s RMWs to return home to start their own businesses.

An Efficient Method for Identifying Lower Limb Behavior Intentions Based on Surface Electromyography

Surface electromyography(sEMG)is widely used for analyzing and controlling lower limb assisted exoskeleton robots.Behavior intention recognition based on sEMG is of great significance for achieving intelligent prosthetic and exoskeleton control.Achieving highly efficient recognition while improving performance has always been a significant challenge.To address this,we propose an sEMG-based method called Enhanced Residual Gate Network(ERGN)for lower-limb behavioral intention recognition.The proposed network combines an attention mechanism and a hard threshold function,while combining the advantages of residual structure,which maps sEMG of multiple acquisition channels to the lower limb motion states.Firstly,continuous wavelet transform(CWT)is used to extract signals features from the collected sEMG data.Then,a hard threshold function serves as the gate function to enhance signals quality,with an attention mechanism incorporated to improve the ERGN’s performance further.Experimental results demonstrate that the proposed ERGN achieves extremely high accuracy and efficiency,with an average recognition accuracy of 98.41%and an average recognition time of only 20 ms-outperforming the state-of-the-art research significantly.Our research provides support for the application of lower limb assisted exoskeleton robots.

Workplace Wellness,Mental Health Literacy,and Usage Intention of E-Mental Health amongst Digital Workers during the COVID-19

The prevalence of mental health problems in both Malaysian and global workplaces has significantly increased due to the presence of the coronavirus disease(COVID-19)pandemic,globalization,technology advancement in Industry 4.0,and other contributing factors.The pervasiveness of the issue poses a huge challenge to improving the occupational safety and health(OSH)of workers in various industries,especially in the digital industry.The emergence of the innovative industry is evident mainly due to the rapid development of Industry 4.0 and the rele-vant demands of multiple businesses in the digital transformation.Nonetheless,limited studies and academic dis-cussions were conducted on the OSH topic of digital employees.Hence,the current study serves tofill the existing gap and provide academic contributions by scrutinising the perceptions of digital workers regarding their work-place well-being,mental health literacy,and the impression of employing e-mental health.The objectives of this study are:1)To examine the mental health literacy and workplace wellness of digital workers,2)to explore the e-mental health usage intention and actual e-mental health utilization,and 3)to identify digital workers’feedback on e-mental health.In the current context,e-mental health focuses on three dimensions,namely,1)“health in our hand(HIOH)”,2)“interacting for health(IFH)”,and 3)“data enabling health(DEH)”.The present study employed an online cross-sectional survey and received 326 digital workers’completed responses.Variables,such as“mental health literacy(MHL)”,“workplace wellness(WW)”,and e-mental health intention and usage were explicated by analysing the data through descriptive statistics.The study results indicated a moderate to a high level of the MHL and the WW.More than half of the workers possessed a high intention level to employ e-mental health,with the HIOH dimension being the most prevalent domain.Nevertheless,the actual e-mental health usage was very low,owing to the online resources being a new concept amongst digital employees.Numerous confounding factors also existed in affecting the low usage,such as privacy concerns,data security levels,and health verification issues.In addition,the mental health issue has not been openly and widely discussed in Malay-sian workplaces due to stigmatisation.As such,the currentfindings could provide additional insights into the OSH literature;it could serve as a guideline for the OSH decision-makers,employers,and eHealth developers when establishing a feasible framework for the practical adoption of e-mental health services by digital workers.

Withdrawal Intention of Farmers from Vacant Rural Homesteads and Its Influencing Mechanism in Northeast China: A Case Study of Jilin Province

The effective use of land in Northeast China is of great significance for ensuring national food security and regional rural revitalization.In this study,based on the survey data collected from Jilin Province,Northeast China,we analyzed the vacancy rates of rural homesteads in suburban,outer suburban,and remote villages,as well as the withdrawal intention of rural-settled farmers,urbansettled farmers,and farmers with urban and rural dual residency from vacant homesteads.From the perspective of farmers’perceptions,this study constructed a theoretical framework of the influence mechanism of their withdrawal intention and analyzed such mechanism by constructing a structural equation model.The results indicated that:1)rural homestead vacancy rates increased with distance from the village to the city.2)rural-settled farmers showed a low withdrawal intention for vacant rural homesteads,followed by urban and rural dual-residence farmers,and urban-settled farmers showed the highest withdrawal intention.3)the relative importance of the factors influencing withdrawal intention is in the following order:policy awareness>interest perception>living environment perception>family characteristics.Finally,this study discussed the reformation of the homestead system and rural homestead transition in Northeast China,which can provide policy support to increase the potential of cultivated land and promote sustainable rural development and urban-rural coordination.

Two-Sided Stable Matching Decision-Making Method Considering Matching Intention under a Hesitant Fuzzy Environment

In this paper,a stable two-sided matching(TSM)method considering the matching intention of agents under a hesitant fuzzy environment is proposed.The method uses a hesitant fuzzy element(HFE)as its basis.First,the HFE preference matrix is transformed into the normalized HFE preference matrix.On this basis,the distance and the projection of the normalized HFEs on positive and negative ideal solutions are calculated.Then,the normalized HFEs are transformed into agent satisfactions.Considering the stable matching constraints,a multiobjective programming model with the objective of maximizing the satisfactions of two-sided agents is constructed.Based on the agent satisfaction matrix,the matching intention matrix of two-sided agents is built.According to the agent satisfaction matrix and matching intention matrix,the comprehensive satisfaction matrix is set up.Furthermore,the multiobjective programming model based on satisfactions is transformed into a multiobjective programming model based on comprehensive satisfactions.Using the G-S algorithm,the multiobjective programming model based on comprehensive satisfactions is solved,and then the best TSM scheme is obtained.Finally,a terminal distribution example is used to verify the feasibility and effectiveness of the proposed method.

Integrating the valence theory and the norm activation theory to understand consumers’ e-waste recycling intention

Electrical and electronic waste(e-waste)is a growing challenge,matching the widespread boom in the use of information and communication technology.Opposite to an alarming increasing amount of e-waste,a low rate of consumer engagement in ensuring the proper disposal of such materials intensifies the pressure on the exist‐ing e-waste crisis.To deal with this thorny problem,it is of great interest to grasp consumers’disposal and re‐cycling behavioral intentions.Therefore,this study attempts to understand complementary perspectives around consumers’e-waste recycling intention based on the integration of the valence theory and the norm activation theory.Four data mining models using classification and prediction-based algorithms,namely Chi squared automatic interaction detector(CHAID),Neural network,Discriminant analysis,and Quick,unbiased,efficient statistical tree(QUEST),were employed to analyze a set of the 398 data collected in Vietnam.The re‐sults revealed that the social support value is by far the most critical predictor,followed by the utilitarian value,task difficulty,and monetary risk.It is also noteworthy that the awareness of consequences,education background,the ascription of responsibility,and age were also ranked as critical affecting factors.The lowest influential predictors found in this study were income and gender.In addition,a comparison was made in terms of the classification performance of the four utilized data mining techniques.Based on several evalua‐tion measurements(confusion matrix,accuracy,precision,recall,specificity,F-measure,ROC curve,and AUC),the aggregated results suggested that CHAID and Neural network performed the best.The findings of this research are expected to assist policymakers and future researchers in updating all information surround‐ing consumer behavioral intention-related topics focusing on e-waste.Furthermore,the adoption of data min‐ing algorithms for prediction is another insight of this study,which may shed the light on data mining applica‐tions in such environmental studies in the future.

Intensive follow-up vs conventional follow-up for patients with nonmetastatic colorectal cancer treated with curative intent:A metaanalysis

BACKGROUND The frequency and content of follow-up strategies remain controversial for colorectal cancer(CRC),and scheduled follow-ups have limited value.AIM To compare intensive and conventional follow-up strategies for the prognosis of non-metastatic CRC treated with curative intent using a meta-analysis.METHODS PubMed,Embase,and the Cochrane Library databases were systematically searched for potentially eligible randomized controlled trials(RCTs)from inception until April 2023.The Cochrane risk of bias was used to assess the methodological quality of the included studies.The hazard ratio,relative risk,and 95%confidence interval were used to calculate survival and categorical data,and pooled analyses were performed using the random-effects model.Additional exploratory analyses were performed for sensitivity,subgroups,and publication bias.RESULTS Eighteen RCTs involving 8533 patients with CRC were selected for the final analysis.Intensive follow-up may be superior to conventional follow-up in improving overall survival,but this difference was not statistically significant.Moreover,intensive follow-up was associated with an increased incidence of salvage surgery compared to conventional follow-up.In addition,there was no significant difference in the risk of recurrence between intensive and conventional follow-up strategies,whereas intensive follow-up was associated with a reduced risk of interval recurrence compared to conventional follow-up.Finally,the effects of intensive and conventional follow-up strategies differed when stratified by tumor location and follow-up duration.CONCLUSION Intensive follow-up may have a beneficial effect on the overall survival of patients with non-metastatic CRC treated with curative intent.

Extension of Goal-Directed Behavior Model for Post-Pandemic Korean Travel Intentions to Alternative Local Destinations: Perceived Risk and Knowledge

Since the outbreak of COVID-19,tourists have been increasingly concerned over various risks of international travel,while knowledge of the pandemic appears to vary significantly.In addition,as travel restrictions continue to impact adversely on international tourism,tourism efforts should be placed more on the domestic markets.Via structural equation modeling,this study unearthed different risk factors impacting Korean travelers’choices of alternative local destinations in the post-pandemic era.In addition,this study extended the goal-directed behavior framework with the acquisition of perceived risk and knowledge of COVID-19,which was proven to hold a sig-nificantly superior explanatory power of tourists’decisions of local alternatives over foreign countries during the COVID-19 pandemic.Furthermore,desire was found to play an imminent mediating role in the conceptual mod-el,maximizing the impact of perceived risk on travel intentions.Henceforth,this research offers meaningful the-oretical implication as thefirst empirical study to deepen the goal-directed behaviour framework with perceived risk and knowledge in the context of post-COVID-19 era.It also serves as insightful knowledge for Korean tour-ism authorities and practitioners to understand local tourists’decision-making processes and tailor effective recovery strategy for domestic tourism.

Behavioral Intention to Continue Using a Library Mobile App

To meet the needs of today’s library users,institutions are developing library mobile apps(LMAs),as their libraries are increasingly intelligent and rely on deep learning.This paper explores the influencing factors and differences in the perception of LMAs at different time points after a user has downloaded an LMA.A research model was constructed based on the technology acceptance model.A questionnaire was designed and distributed twice to LMA users with an interval of three months to collect dynamic data.The analysis was based on structural equation modeling.The empirical results show that the perceived ease of use,the perceived usefulness,the social influence,and the facilitating conditions affected the users’behavioral intention,but their impacts were different at different times.As the usage time increases,the technology acceptance model is still universal for understanding the user perception of LMA.In addition,two extended variables(social impact and convenience)also affect the user’s behavior intention.User behavior is dynamic and changed over time.This study is important both theoretically and practically,as the results could be used to improve the service quality of LMAs and reduce the loss rate of users.Its findings may help the designers and developers of LMAs to optimize them from the perspective of a user and improve the service experience by providing a deeper understanding of the adoption behavior of information systems by LMA users.