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.

Heterogeneous information fusion recognition method based on belief rule structure

To solve the problem that the existing situation awareness research focuses on multi-sensor data fusion,but the expert knowledge is not fully utilized,a heterogeneous informa-tion fusion recognition method based on belief rule structure is proposed.By defining the continuous probabilistic hesitation fuzzy linguistic term sets(CPHFLTS)and establishing CPHFLTS distance measure,the belief rule base of the relationship between feature space and category space is constructed through information integration,and the evidence reasoning of the input samples is carried out.The experimental results show that the proposed method can make full use of sensor data and expert knowledge for recognition.Compared with the other methods,the proposed method has a higher correct recognition rate under different noise levels.

Alcohol and illicit drugs:prevalence of alcohol and illicit drug use and their predictors in young people from Argentina,Bulgaria,Chile and Romania

Background:Alcohol and illicit drugs(AID)continue to be a major global health concern.Although preventable,AID is linked to millions of deaths annually worldwide.The situation is particularly grave for young people,with AID being a major direct risk factor for disability-adjusted youth life-years lost and death.It further contributes to assaults,road crashes,accidental poisoning,and suicide,leading to long-term issues and public health concerns.Objective:This study aimed at disclosing current AID prevalence data for Argentinian,Bulgarian,Chilean and Romanian youth.It shed light on the predictors of AID in young people from those countries.Method:The study used an online survey to gather data from people aged 18 to 25(n=1,297).The survey was underpinned by the theory of planned behaviour(TPB).Predictors were investigated separately for drinking alcohol and using illicit drugs.Results:Our data revealed that across the four target countries,49%to 90%of the participants drank alcohol,and 8%to 35%used illicit drugs in the past three months.Between 20%and 91%of them intended to drink,and between 8%and 31%intended to use illicit drugs in the following three months.Our TPB model predicted statistically significant(P<0.001)amounts of variance in drinking alcohol(between 61%and 72%)and using illicit drugs(between 20.3%and 74.4%).Intention was consistent in significantly predicting both behaviours.Evidence around the predictive validity of self-efficacy,age and gender was mixed across the investigated countries.Conclusion:This research provided an update on the scarce AID epidemiological data.It also supplied evidence about what theoretically-informed measures might be useful targets of interventions in the case of Argentina,Bulgaria,Chile and Romania.This new knowledge of understanding substance abuse determinants and prevalence may help researchers and practitioners better meet young people's health prevention needs.

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.

Understanding factors affecting non-participants’interest in community-supported agriculture

Community-supported agriculture(CSA)has emerged as a viable solution for addressing the agricultural challenges faced by countries like Indonesia.This study uses the wellestablished unified theory of acceptance and use of technology(UTAUT2)model to examine the interest in CSA of potential customers in Indonesia.A standardized questionnaire was distributed to 1200 respondents,and the data were analyzed using structural equation model-partial least square(SEM-PLS)in SmartPLS 4.0 software.The results capture potential CSA consumer interest and will help to improve CSA development strategies in Indonesia.The model explains 44.4%of customers’intentions,and identifies performance expectancy as the decisive factor in customers’willingness to participate in CSA.Performance expectancy(0.292),hedonic motivation(0.262),social influence(0.259),and facilitating conditions(0.086)positively influence customers’interest in participating in a CSA program.The adoption of CSA programs by both farmers and customers could be increased by implementing regulations that provide tax incentives and subsidies,offering training on sustainable farming practices,facilitating the establishment of distribution channels,and establishing guidelines for fair price and quality standards.This study shows the high potential for the implementation of CSA in Indonesia.It could also be used as a foundation for the development of new policies regarding sustainable agriculture markets in Indonesia.

Measuring Cognitive and Psychosocial Accessibility to Modern Contraception: A Comprehensive Framework

Nowadays, more than ever, the improvement of access to family planning (FP) has become an international goal. What constitutes access to FP? Current human rights-based contraceptive guidelines indicate that access begins as soon as women or couples express a desire to avoid pregnancy and their risk of unintended pregnancy is established. However, few studies have sought to define and measure cognitive and psychosocial access to contraception. To propose a comprehensive framework for the cognitive and psychosocial accessibility of contraception, we critically analyzed the literature on attitudes toward FP. The main dimensions that emerged were knowledge about FP, fear of side effects, approval of contraception, and contraceptive agency. We then identified and adjusted some questions that can capture these dimensions more comprehensively. As a result, we developed a questionnaire module comprising 15 questions, which was integrated into the 6th round of the PMA2020 survey in Burkina Faso in 2019. This research highlighted that previous studies have collected separate dimensions of contraceptive access, and the psychosocial dimension tended to be neglected. Our results demonstrate that it is possible to collect comprehensive data on cognitive and psychosocial dimensions of access to family planning.

Perspectives and Experiences of Education Stakeholders: A Quantitative Study on the Adoption of Artificial Intelligence in Executive Training Using Structural Equation Modeling

The recent increase in the use of artificial intelligence has led to fundamental changes in the development of training and teaching methods for executive education. However, the success of artificial intelligence in regional centers for teaching and training professions will depend on the acceptance of this technology by young executive trainees. This article discusses the potential benefits of adopting AI in executive training institutions in Morocco, specifically focusing on CRMEF Casablanca Settat. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al., 2003), this study proposes a model to identify the factors influencing the acceptance of artificial intelligence in regional centers for teaching professions and training in Morocco. To achieve this, a structural equation modeling approach was used to quantitatively describe the impact of each factor on AI adoption, utilizing data collected from 173 young executive trainees. The results indicate that perceived ease of use, perceived usefulness, trainer influence, and personal innovativeness influence the intention to use artificial intelligence. Our research provides managers of CRMEFs with a set of practical recommendations to enhance the implementation conditions of an artificial intelligence system. It aims to understand which factors should be considered in designing an artificial intelligence system within regional centers for teaching professions and training (CRMEFs).

Metaverse application,flow experience,and Gen-Zers’participation intention of intangible cultural heritage communication

With outstanding advantages in virtuality, immersion, connectivity, and openness, the application of the metaverse in the development of intangible cultural heritage has demonstrated great potential to enhance Gen-Zers’ participation intention, but the effect and its mechanism remain unclear. This study constructs a theoretical model based on the stimuli-organism-response (SOR) theory, the DeLone and McLean model of information system (IS) success (D&M) model, and flow theory, and conducts an empirical study using a structural equation model and regression analysis based on questionnaire survey data in China to uncover whether and how metaverse application exerts its impact. Results show that metaverse application can enhance Gen-Zers’ participation intention in the communication of intangible cultural heritage, and their mechanism follows a chain path of “stimulus-state-response” under the joint action of “technology-individual-environment” in which metaverse application is the key stimulus factor, flow experience is the mediator, and self-efficacy and subjective norm are moderators. The findings can offer new insights for research on metaverse application from the perspectives of consequences and effects and can also provide practical implications for metaverse application as well as the development and communication of intangible cultural heritage.

Determinants of continuous usage intention of branded apps in omni-channel retail environment: comparison between experience-oriented and transaction-oriented apps

Branded applications(apps)have become core touchpoints for improving consumer shopping experiences in omni-channel retailing,and many firms have developed different types of branded apps to provide additional value.Moreover,continuous usage intention is the key to improving enterprises’gain efficiency and consumers’brand loyalty.This study aims to reveal how branded apps achieve continuance intention from the perspective of consumer perceptions by combining the technology acceptance model and investigating the impact of differences in channel features on usage behavior between the two types of branded apps.An experiment was designed comparing transaction-and experience-oriented branded apps.A structural equation modeling technique was employed to validate the model based on the survey data of respondents from the experimental groups.The results show that the supportive role of omni-channel has a unique experience mechanism that promotes continuous usage intention.However,there are two discrepant results regarding the effect of perceived complementarity on perceived usefulness in transaction-and experience-oriented branded apps.The mediating role of perceived usefulness between perceived consistency,complementarity,ease of use and consumer satisfaction was supported in the experience-oriented apps but rejected in the transaction-oriented apps.

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.

Trust beyond Technology Algorithms: A Theoretical Exploration of Consumer Trust and Behavior in Technological Consumption and AI Projects

In an era dominated by artificial intelligence (AI), establishing customer confidence is crucial for the integration and acceptance of AI technologies. This interdisciplinary study examines factors influencing customer trust in AI systems through a mixed-methods approach, blending quantitative analysis with qualitative insights to create a comprehensive conceptual framework. Quantitatively, the study analyzes responses from 1248 participants using structural equation modeling (SEM), exploring interactions between technological factors like perceived usefulness and transparency, psychological factors including perceived risk and domain expertise, and organizational factors such as leadership support and ethical accountability. The results confirm the model, showing significant impacts of these factors on consumer trust and AI adoption attitudes. Qualitatively, the study includes 35 semi-structured interviews and five case studies, providing deeper insight into the dynamics shaping trust. Key themes identified include the necessity of explainability, domain competence, corporate culture, and stakeholder engagement in fostering trust. The qualitative findings complement the quantitative data, highlighting the complex interplay between technology capabilities, human perceptions, and organizational practices in establishing trust in AI. By integrating these findings, the study proposes a novel conceptual model that elucidates how various elements collectively influence consumer trust in AI. This model not only advances theoretical understanding but also offers practical implications for businesses and policymakers. The research contributes to the discourse on trust creation and decision-making in technology, emphasizing the need for interdisciplinary efforts to address societal challenges associated with technological advancements. It lays the groundwork for future research, including longitudinal, cross-cultural, and industry-specific studies, to further explore consumer trust in AI.

人机情感交互智能体及其在控制性能评价中的应用

在智能体的信念、愿望、意图模型基础上,提出了一个人机情感交互模型。根据隐马氏链模型的情感强度空间表达和个性OCC模型的结构框架,融合了一种人工心理应激模型的内涵,建立起一个刺激转移情感计算模型。详细给出了智能体的情感计算方法,并进一步将其加入到智能体的人机交互机制中,构造了人机交互学习模型,提出了人机交互目标完成程度指标及其计算和情感学习算法。以过程控制性能评价为应用实例,讨论了智能体人机情感交互模型的构建和相关算法,并针对具体的控制回路进行了仿真和分析,验证了所提出方法的可行性和有效性。

意图性原则──在语篇水平上翻译的一个重要原则

语篇语言学突破了以句子作为语言研究的最高层次的局限，对实际运用中的语言组织特征和使用特征进行动态的研究，引起了译界的重视，它的一些原则和方法被运用到了翻译理论和实践中。１９８１年ｄｅＢｒａｎｄｅ和Ｄｒｅｓｌｅｒ在《语篇语言学导论》中提出了构筑篇章的七...

基于角色的多Agent的网格资源管理框架与分配策略

提出了一种适应计算网格分布动态环境的基于角色的多代理的资源管理框架,其核心的三种角色代理都采用BDI(Belief,Desire,Intention)代理模型,利用BDI代理的智能交互,进行协同合作以管理复杂的网格资源。还初步探讨了基于此框架的网格资源优化分配的策略和方法。

User-oriented web search based on PLSA

In order to solve the problem that current search engines provide query-oriented searches rather than user-oriented ones, and that this improper orientation leads to the search engines＇ inability to meet the personalized requirements of users, a novel method based on probabilistic latent semantic analysis （PLSA） is proposed to convert query-oriented web search to user-oriented web search. First, a user profile represented as a user＇ s topics of interest vector is created by analyzing the user＇ s click through data based on PLSA, then the user＇ s queries are mapped into categories based on the user＇ s preferences, and finally the result list is re-ranked according to the user＇ s interests based on the new proposed method named user-oriented PageRank （UOPR）. Experiments on real life datasets show that the user-oriented search system that adopts PLSA takes considerable consideration of user preferences and better satisfies a user＇ s personalized information needs.