Intentional tooth replantation(ITR)is an advanced treatment modality and the procedure of last resort for preserving teeth with inaccessible endodontic or resorptive lesions.ITR is defined as the deliberate extraction...Intentional tooth replantation(ITR)is an advanced treatment modality and the procedure of last resort for preserving teeth with inaccessible endodontic or resorptive lesions.ITR is defined as the deliberate extraction of a tooth;evaluation of the root surface,endodontic manipulation,and repair;and placement of the tooth back into its original socket.Case reports,case series,cohort studies,and randomized controlled trials have demonstrated the efficacy of ITR in the retention of natural teeth that are untreatable or difficult to manage with root canal treatment or endodontic microsurgery.However,variations in clinical protocols for ITR exist due to the empirical nature of the original protocols and rapid advancements in the field of oral biology and dental materials.This heterogeneity in protocols may cause confusion among dental practitioners;therefore,guidelines and considerations for ITR should be explicated.This expert consensus discusses the biological foundation of ITR,the available clinical protocols and current status of ITR in treating teeth with refractory apical periodontitis or anatomical aberration,and the main complications of this treatment,aiming to refine the clinical management of ITR in accordance with the progress of basic research and clinical studies;the findings suggest that ITR may become a more consistent evidence-based option in dental treatment.展开更多
Sustainable development has become a critical global priority,and green transportation solutions,such as electric taxis,play a vital role in achieving this goal.This study examines the factors influencing students’in...Sustainable development has become a critical global priority,and green transportation solutions,such as electric taxis,play a vital role in achieving this goal.This study examines the factors influencing students’intentions to adopt electric taxi services in Hanoi,Vietnam,as a step toward sustainable urban mobility.We surveyed 573 students and ana-lyzed key determinants using reliability tests,exploratory factor analysis(EFA),and linear regression.The results indi-cate that four factors significantly influence adoption intentions:Perceived Usefulness and Sustainability,Price,Brand Awareness,and Service Quality.Among these,Perceived Usefulness and Sustainability had the strongest positive im-pact,while Service Quality exerted the weakest influence.Notably,Habit and Ease of Use&Transaction Convenience were found to be statistically insignificant in the final model.These findings provide practical implications for business-es and policymakers aiming to use electric taxi adoption.To enhance appeal,stakeholders should emphasize environ-mental benefits,competitive pricing,and brand recognition while improving service reliability.By addressing these fac-tors,electric taxi services can accelerate the transition to sustainable transportation,aligning with global climate goals and transforming urban mobility.This study offers actionable insights for encouraging greener travel behaviors among students,a key demographic for long-term sustainability impact.展开更多
Background of the study:The Bangladeshi cosmetics market has witnessed significant growth in recent years,driven by changing consumer lifestyles,increased disposable incomes,and rising awareness of personal grooming.T...Background of the study:The Bangladeshi cosmetics market has witnessed significant growth in recent years,driven by changing consumer lifestyles,increased disposable incomes,and rising awareness of personal grooming.The study investigates the impact of content cues which influence on purchasing intention towards cosmetic brands in Bangladesh.Purpose:The basic purpose of this study was to evaluate the factors influencing consumers’purchasing intentions for cosmetic brands in Bangladesh.Specifically,the study explored the roles of various cosmetic-related attributes and their impact on purchasing intentions within the context of Bangladesh’s cosmetic industry.Research methods:A quantitative research approach was adopted,and data were collected through a structured survey targeting Bangladeshi consumers who frequently engage with cosmetic products.All the valid responses were analyzed using SmartPLS 4.0 to perform structural equation modeling.Research findings:The findings revealed that trust in cosmetic brands and competitive pricing significantly influence consumers’purchasing intentions,highlighting the importance of fostering trust and affordability.However,certain constructs,such as ethnocentric tendencies and concerns about ingredient safety,showed limited impact on consumers’decisions.Conclusion:This study contributes to the existing literature by offering empirical insights into the Bangladeshi context,particularly within the rapidly growing cosmetics market.The findings provide actionable recommendations for cosmetic brands aiming to strengthen their market position through trust-building initiatives,competitive pricing strategies,and educational campaigns to enhance consumer awareness.These insights are particularly relevant for marketing practitioners seeking to understand and respond to the unique dynamics of the Bangladeshi cosmetics industry.展开更多
Objective:This study aims to identify the prevalence of bullying in the workplace and to examine its association with turnover(TO)intention and secondary traumatic stress(STS)among Jordanian nurses employed in Emergen...Objective:This study aims to identify the prevalence of bullying in the workplace and to examine its association with turnover(TO)intention and secondary traumatic stress(STS)among Jordanian nurses employed in Emergency Departments(EDs)and critical care units(CCUs).Nurses employed in the EDs and CCUs are exposed to high levels of bullying behaviors that may contribute to STS,leading to high rates of TO.Methods:A descriptive cross-sectional design was used.A sample of 150 Jordanian nurses working in CCUs and EDs completed the study.Data collection was performed using the Demographical Questionnaire,the Negative Acts Questionnaire-Revised(NAQ-R),ProQOL scale,and TO scale.The IBM SPSS software was used to analyze data.Results:About 10.7%and 89.3%were categorized as“occasionally bullied”and“victims of workplace bullying”subsequently.Workplace bullying was positively associated with TO intention(r=0.46,P<0.001)and STS(r=0.36,P<0.001).TO was positively associated with STS(r=0.36,P<0.001).Bullying was a unique significant predictor of TO intention(t=4.59,B=0.34,P<0.001)and STS(t=4.15,B=0.34,P<0.001).Conclusions:Bullying behavior has negative adversarial effects on TO and the experience of STS.The prevalence of bullying behavior in the EDs and CCUs remains high despite the increasing awareness of its negative impacts.Healthcare organizations should put systems in place to ensure that zero-tolerance policy are monitored in terms of the effectiveness of its implementation.展开更多
This study utilized a sequential mediating model to examine the role of motivation to learn and transfer selfefficacy in the relationships between perceived content validity,mentoring function,continuous learning work...This study utilized a sequential mediating model to examine the role of motivation to learn and transfer selfefficacy in the relationships between perceived content validity,mentoring function,continuous learning work culture and intention to transfer learning.The sample comprized 429 final-year apprentices in Guangdong province,China(females=69.9%,Engineering&Medicine=69%,mean age=20.99,SD=1.60).The apprentices completed standardized measures of motivation to learn,transfer self-efficacy perceived content validity,mentoring function,and continuous learning work culture.Structural equation modeling was used to analyze the data.Results showed perceived content validity,mentoring function,continuous learning culture to predict intention to transfer learning.Of these factors,perceived content validity was the strongest predictor of intention to transfer learning.Of these factors,perceived content validity was the most influential predictor of intention to transfer learning.The motivation to learn and transfer self-efficacy sequentially mediated the relationship between mentoring function and intention to learning transfer to be stronger than by either alone.Although perceived content validity and continuous learning culture exhibited no significant direct effects on intention to transfer learning,they demonstrated positive indirect associations with intention to transfer via motivation to learn and transfer self-efficacy.These study findings extend the applications of the learning transfer framework to individuals undergoing apprenticeship training which also would apply to other a long-term work-based learning programs.展开更多
This study investigated the role of intentional self-regulation and the moderating role of peer relationship in the relationship between teacher-student relationship and learning engagement.The study sample comprised ...This study investigated the role of intentional self-regulation and the moderating role of peer relationship in the relationship between teacher-student relationship and learning engagement.The study sample comprised 540 Chinese senior secondary school students between the ages of 15–18(51.67%boys;Mage=16.56 years;SDage=0.90).They completed surveys on the Teacher-Student Relationship Scale,the Selection,Optimization,and Compensation(SOC)Scale,the Peer Relationship Scale for Children and Adolescents,and the Learning Engagement Scale.The results following regression analysis showed that teacher-student relationship predicted higher learning engagement among senior secondary school students.Intentional self-regulation partially mediated the link between teacher-student relationship and learning engagement for higher learning engagement.Peer relationship moderated the relationships between teacher-student relationship and learning engagement and moderated the relationship between teacher-student relationship and intentional self-regulation for higher learning engagement.Thesefindings imply learning engagement can be enhanced by optimizing teacher-student relationship and strengthening intentional self-regulation interventions.展开更多
Air target intent recognition holds significant importance in aiding commanders to assess battlefield situations and secure a competitive edge in decision-making.Progress in this domain has been hindered by challenges...Air target intent recognition holds significant importance in aiding commanders to assess battlefield situations and secure a competitive edge in decision-making.Progress in this domain has been hindered by challenges posed by imbalanced battlefield data and the limited robustness of traditional recognition models.Inspired by the success of diffusion models in addressing visual domain sample imbalances,this paper introduces a new approach that utilizes the Markov Transfer Field(MTF)method for time series data visualization.This visualization,when combined with the Denoising Diffusion Probabilistic Model(DDPM),effectively enhances sample data and mitigates noise within the original dataset.Additionally,a transformer-based model tailored for time series visualization and air target intent recognition is developed.Comprehensive experimental results,encompassing comparative,ablation,and denoising validations,reveal that the proposed method achieves a notable 98.86%accuracy in air target intent recognition while demonstrating exceptional robustness and generalization capabilities.This approach represents a promising avenue for advancing air target intent recognition.展开更多
To address the issue of neglecting scenarios involving joint operations and collaborative drone swarm operations in air combat target intent recognition.This paper proposes a transfer learning-based intention predicti...To address the issue of neglecting scenarios involving joint operations and collaborative drone swarm operations in air combat target intent recognition.This paper proposes a transfer learning-based intention prediction model for drone formation targets in air combat.This model recognizes the intentions of multiple aerial targets by extracting spatial features among the targets at each moment.Simulation results demonstrate that,compared to classical intention recognition models,the proposed model in this paper achieves higher accuracy in identifying the intentions of drone swarm targets in air combat scenarios.展开更多
This study is based on the Extended Theory of Planned Behavior(ETPB)and focuses on the elderly population in the main urban area of Chongqing to explore their intentions and influencing factors regarding health and we...This study is based on the Extended Theory of Planned Behavior(ETPB)and focuses on the elderly population in the main urban area of Chongqing to explore their intentions and influencing factors regarding health and wellness tourism behavior.Data was collected through questionnaire surveys and field research,and SPSS 26.0 and Amos 29.0 software were used for reliability,validity analysis,and structural equation modeling testing.The study shows that behavioral attitude,perceived behavior control,and the context of health and wellness tourism have a significant positive impact on the elderly’s intentions regarding health and wellness tourism behavior,while the influence of subjective norms is not significant.In addition,subjective norms have a significant positive effect on behavioral attitudes and perceived behavioral control.Based on the research conclusions,suggestions are made to strengthen the behavioral intention of elderly tourists to participate in health and wellness tourism.展开更多
Objective The effects of prolonged exposure to persistently elevated atmospheric pollutants,commonly termed air pollution waves,on fertility intentions remain inadequately understood.This study aims to investigate the...Objective The effects of prolonged exposure to persistently elevated atmospheric pollutants,commonly termed air pollution waves,on fertility intentions remain inadequately understood.This study aims to investigate the association between particulate matter(PM)exposure and fertility intentions.Methods In this nationwide cross-sectional study,we analyzed data from 10,747 participants(5496 females and 5251 males).PM waves were defined as periods lasting 3‒6 consecutive days during which the daily average concentrations exceeded China’s Ambient Air Quality Standards Grade II thresholds(PM2.5>75μg/m3 and PM10>150μg/m3).We employed multivariate logistic regression models to assess the association between exposure to PM waves and fertility intentions.Results Significant inverse associations were detected between exposure to PM2.5 wave events(characterized by concentrations exceeding 75μg/m3 for durations of 4‒6 days,P<0.05)and PM10 wave events(defined as concentrations exceeding 150μg/m3 for 6 consecutive days,P<0.05)and fertility intentions among females.In contrast,neither the PM2.5 wave nor the PM10 wave events demonstrated statistically significant correlations with fertility intentions in males(P>0.05 for all comparisons).The potentially susceptible subgroup was identified as females aged 20–30 years.Conclusions Our results provide the first evidence that PM2.5 and PM10 waves are associated with a reduction in female fertility intentions,offering critical insights for the development of public health policies and strategies aimed at individual protection.展开更多
In the contemporary digital landscape,the proliferation of information has led to an increasing diversity of channels through which consumers obtain information,resulting in a gradual transformation of shopping habits...In the contemporary digital landscape,the proliferation of information has led to an increasing diversity of channels through which consumers obtain information,resulting in a gradual transformation of shopping habits.Consumers now frequently rely on external sources to make well-informed purchasing decisions,leading to the emergence of live shopping as a prominent avenue for gathering product information and completing transactions.E-commerce live streaming has experienced rapid growth,leveraging its ability to generate traffic and capture consumer attention.The integration of content and live streaming not only meets users’psychological needs but also facilitates seamless communication between buyers and sellers.From the perspective of content marketing typologies,this paper examines content marketing across three key dimensions:informational content,entertainment content,and emotional content.It further explores the impact of content marketing on consumers’purchase intentions within the context of e-commerce live streaming.展开更多
This study focuses on the relationship between job stress and intention to leave among obstetric(OB)nurses in the context of China's birth policy adjustment,and provides a scientific basis for policymakers and hea...This study focuses on the relationship between job stress and intention to leave among obstetric(OB)nurses in the context of China's birth policy adjustment,and provides a scientific basis for policymakers and healthcare administrators.This study used a non-experimental descriptive correlation design with a purposive sampling of 230 OB nurses from three tertiary hospitals in Jinan,Shandong Province.Participants were surveyed using three questionnaires and descriptive analysis;ANOVA and correlation analyses were used to analyze the relationship between participants'stressor levels and turnover intention.Pearson's correlation coefficient analysis showed that there was a positive correlation between nurses‘work stressors and turnover intention,with a correlation coefficient of r=0.53,a moderate positive correlation(P<0.001).Based on the survey data from three tertiary hospitals in Shandong Province,the obstetric nurses group has a medium level of work stressors,but a high turnover intention,highlighting the professional identity crisis.展开更多
High complexity and uncertainty of air combat pose significant challenges to target intention prediction.Current interpolation methods for data pre-processing and wrangling have limitations in capturing interrelations...High complexity and uncertainty of air combat pose significant challenges to target intention prediction.Current interpolation methods for data pre-processing and wrangling have limitations in capturing interrelationships among intricate variable patterns.Accordingly,this study proposes a Mogrifier gate recurrent unit-D(Mog-GRU-D)model to address the com-bat target intention prediction issue under the incomplete infor-mation condition.The proposed model directly processes miss-ing data while reducing the independence between inputs and output states.A total of 1200 samples from twelve continuous moments are captured through the combat simulation system,each of which consists of seven dimensional features.To bench-mark the experiment,a missing valued dataset has been gener-ated by randomly removing 20%of the original data.Extensive experiments demonstrate that the proposed model obtains the state-of-the-art performance with an accuracy of 73.25%when dealing with incomplete information.This study provides possi-ble interpretations for the principle of target interactive mecha-nism,highlighting the model’s effectiveness in potential air war-fare implementation.展开更多
The consultation intention of emergency decision-makers in urban rail transit(URT)is input into the emergency knowledge base in the form of domain questions to obtain emergency decision support services.This approach ...The consultation intention of emergency decision-makers in urban rail transit(URT)is input into the emergency knowledge base in the form of domain questions to obtain emergency decision support services.This approach facilitates the rapid collection of complete knowledge and rules to form effective decisions.However,the current structured degree of the URT emergency knowledge base remains low,and the domain questions lack labeled datasets,resulting in a large deviation between the consultation outcomes and the intended objectives.To address this issue,this paper proposes a question intention recognition model for the URT emergency domain,leveraging knowledge graph(KG)and data enhancement technology.First,a structured storage of emergency cases and emergency plans is realized based on KG.Subsequently,a comprehensive question template is developed,and the labeled dataset of emergency domain questions in URT is generated through the KG.Lastly,data enhancement is applied by prompt learning and the NLP Chinese Data Augmentation(NLPCDA)tool,and the intention recognition model combining Generalized Auto-regression Pre-training for Language Understanding(XLNet)and Recurrent Convolutional Neural Network for Text Classification(TextRCNN)is constructed.Word embeddings are generated by XLNet,context information is further captured using Bidirectional Long Short-Term Memory Neural Network(BiLSTM),and salient features are extracted with Convolutional Neural Network(CNN).Experimental results demonstrate that the proposed model can enhance the clarity of classification and the identification of domain questions,thereby providing supportive knowledge for emergency decision-making in URT.展开更多
Despite the gradual transformation of traditional manufacturing by the Human-Robot Collaboration Assembly(HRCA),challenges remain in the robot’s ability to understand and predict human assembly intentions.This study ...Despite the gradual transformation of traditional manufacturing by the Human-Robot Collaboration Assembly(HRCA),challenges remain in the robot’s ability to understand and predict human assembly intentions.This study aims to enhance the robot’s comprehension and prediction capabilities of operator assembly intentions by capturing and analyzing operator behavior and movements.We propose a video feature extraction method based on the Temporal Shift Module Network(TSM-ResNet50)to extract spatiotemporal features from assembly videos and differentiate various assembly actions using feature differences between video frames.Furthermore,we construct an action recognition and segmentation model based on the Refined-Multi-Scale Temporal Convolutional Network(Refined-MS-TCN)to identify assembly action intervals and accurately acquire action categories.Experiments on our self-built reducer assembly action dataset demonstrate that our network can classify assembly actions frame by frame,achieving an accuracy rate of 83%.Additionally,we develop a HiddenMarkovModel(HMM)integrated with assembly task constraints to predict operator assembly intentions based on the probability transition matrix and assembly task constraints.The experimental results show that our method for predicting operator assembly intentions can achieve an accuracy of 90.6%,which is a 13.3%improvement over the HMM without task constraints.展开更多
This study aims to the factors influencing consumer intention to purchase eco-friendly,small-packaged agricultural products using the Theory of Planned Behavior(TPB).With increasing demand for sustainable consumption,...This study aims to the factors influencing consumer intention to purchase eco-friendly,small-packaged agricultural products using the Theory of Planned Behavior(TPB).With increasing demand for sustainable consumption,eco-friendly food packaging has become a critical focus within the circular economy.This study was conducted in Seoul,South Korea,a key marketplace for consumer trends,and surveyed 200 respondents to examine key TPB components—attitude,subjective norms,and perceived behavioral control—along with additional factors shaping sustainable purchasing behavior.The findings indicate that perceived behavioral control is the predictor of purchase intention(β=0.510,p<0.001),followed by attitude(β=0.236,p<0.05)and subjective norms(β=0.199,p<0.05).Moreover,the results suggest that while social influences play a role,individuals who perceive fewer barriers and have a stronger personal attitude toward sustainability are more likely to adopt eco-friendly purchasing behaviors.These results highlight the importance of consumer autonomy and confidence in making eco-friendly choices,suggesting that increasing accessibility and affordability of sustainable packaging can drive adoption.Despite social influences,urban consumers prioritize personal values and perceived control over purchasing behavior.The study might contribute to sustainability literature by offering insights into eco-conscious consumer behavior and implications for marketing strategies that promote sustainable agricultural products.Future research should explore cross-cultural comparisons and additional psychological determinants to enhance the understanding of sustainable consumption patterns.展开更多
A survey was conducted among 616 students from six private undergraduate universities in Hefei City,Anhui Province.Using Likert 5-point scale measurements and SPSS 27.0 for data analysis,the study revealed that studen...A survey was conducted among 616 students from six private undergraduate universities in Hefei City,Anhui Province.Using Likert 5-point scale measurements and SPSS 27.0 for data analysis,the study revealed that students with prior entrepreneurial experience demonstrated lower satisfaction with university entrepreneurship education,and their past entrepreneurial attempts showed a negative correlation with future entrepreneurial intentions.However,high-quality entrepreneurship education exhibited a positive mediating role in this relationship.This study reveals the intrinsic mechanisms through which personal experiences and entrepreneurship education influence college students'entrepreneurial intentions,providing theoretical references for higher education institutions to optimize entrepreneurship education programs and enhance students'entrepreneurial motivations.These findings will contribute to the national strategy of"promoting employment through entrepreneurship".展开更多
The evacuation of people under threat is an effective disaster prevention and mitigation measure in response to flash floods and geological hazards,and it is also an essential element of pre-disaster planning.However,...The evacuation of people under threat is an effective disaster prevention and mitigation measure in response to flash floods and geological hazards,and it is also an essential element of pre-disaster planning.However,the effect of the interactions between perception factors on residents'willingness to evacuate is an urgent problem to be solved.Therefore,this paper introduces risk,stakeholder,and protective action perceptions from the protective action decision model as the main explanatory variables.These three core perceptions are subdivided into affective risk perception,cognitive risk perception,government perception,other-stakeholder perception,resourcerelated attributes,and hazard-related attributes.A questionnaire survey was conducted from June to July 2023 among residents of mountainous communities in nine villages in three towns in Sichuan Province,China.359 cross-sectional data were analyzed using structural equation modeling to explore the effects of six perception factors on evacuation intentions.The results of the study showed that:(1)affective risk perception,government perception,other-stakeholder perception,and hazard-related attributes all directly and positively influence residents'intentions to evacuate;(2)cognitive risk perception is mediated by stakeholder and protective action perceptions,which indirectly and positively affect residents'intentions to evacuate.Based on the hypothesized paths,strategies to improve residents'willingness to evacuate are discussed from the perspective of three core perceptions:strengthening disaster risk education,improving residents'cohesion,and building government credibility.The results of this study can provide theoretical support and practical suggestions for emergency management departments to formulate emergency evacuation strategies,which can aid decision-makers in better understanding residents'intentions to evacuate,optimizing evacuation information dissemination pathways,and strengthening disaster risk management capabilities.展开更多
Semi-supervised new intent discovery is a significant research focus in natural language understanding.To address the limitations of current semi-supervised training data and the underutilization of implicit informati...Semi-supervised new intent discovery is a significant research focus in natural language understanding.To address the limitations of current semi-supervised training data and the underutilization of implicit information,a Semi-supervised New Intent Discovery for Elastic Neighborhood Syntactic Elimination and Fusion model(SNID-ENSEF)is proposed.Syntactic elimination contrast learning leverages verb-dominant syntactic features,systematically replacing specific words to enhance data diversity.The radius of the positive sample neighborhood is elastically adjusted to eliminate invalid samples and improve training efficiency.A neighborhood sample fusion strategy,based on sample distribution patterns,dynamically adjusts neighborhood size and fuses sample vectors to reduce noise and improve implicit information utilization and discovery accuracy.Experimental results show that SNID-ENSEF achieves average improvements of 0.88%,1.27%,and 1.30%in Normalized Mutual Information(NMI),Accuracy(ACC),and Adjusted Rand Index(ARI),respectively,outperforming PTJN,DPN,MTP-CLNN,and DWG models on the Banking77,StackOverflow,and Clinc150 datasets.The code is available at https://github.com/qsdesz/SNID-ENSEF,accessed on 16 January 2025.展开更多
Recognizing target intent is crucial for making decisions on the battlefield.However,the imperfect and ambiguous character of battlefield situations challenges the validity and causation analysis of classical intent r...Recognizing target intent is crucial for making decisions on the battlefield.However,the imperfect and ambiguous character of battlefield situations challenges the validity and causation analysis of classical intent recognition techniques.Facing with the challenge,a target intention causal analysis paradigm is proposed by combining with an Intervention Retrieval(IR)model and a Hybrid Intention Recognition(HIR)model.The target data acquired by the sensors are modelled as Basic Probability Assignments(BPAs)based on evidence theory to create uncertain datasets.Then,the HIR model is utilized to recognize intent for a tested sample from uncertain datasets.Finally,the intervention operator under the evidence structure is utilized to perform attribute intervention on the tested sample.Data retrieval is performed in the sample database based on the IR model to generate the intention distribution of the pseudo-intervention samples to analyze the causal effects of individual sample attributes.The simulation results demonstrate that our framework successfully identifies the target intention under the evidence structure and goes further to analyze the causal impact of sample attributes on the target intention.展开更多
文摘Intentional tooth replantation(ITR)is an advanced treatment modality and the procedure of last resort for preserving teeth with inaccessible endodontic or resorptive lesions.ITR is defined as the deliberate extraction of a tooth;evaluation of the root surface,endodontic manipulation,and repair;and placement of the tooth back into its original socket.Case reports,case series,cohort studies,and randomized controlled trials have demonstrated the efficacy of ITR in the retention of natural teeth that are untreatable or difficult to manage with root canal treatment or endodontic microsurgery.However,variations in clinical protocols for ITR exist due to the empirical nature of the original protocols and rapid advancements in the field of oral biology and dental materials.This heterogeneity in protocols may cause confusion among dental practitioners;therefore,guidelines and considerations for ITR should be explicated.This expert consensus discusses the biological foundation of ITR,the available clinical protocols and current status of ITR in treating teeth with refractory apical periodontitis or anatomical aberration,and the main complications of this treatment,aiming to refine the clinical management of ITR in accordance with the progress of basic research and clinical studies;the findings suggest that ITR may become a more consistent evidence-based option in dental treatment.
文摘Sustainable development has become a critical global priority,and green transportation solutions,such as electric taxis,play a vital role in achieving this goal.This study examines the factors influencing students’intentions to adopt electric taxi services in Hanoi,Vietnam,as a step toward sustainable urban mobility.We surveyed 573 students and ana-lyzed key determinants using reliability tests,exploratory factor analysis(EFA),and linear regression.The results indi-cate that four factors significantly influence adoption intentions:Perceived Usefulness and Sustainability,Price,Brand Awareness,and Service Quality.Among these,Perceived Usefulness and Sustainability had the strongest positive im-pact,while Service Quality exerted the weakest influence.Notably,Habit and Ease of Use&Transaction Convenience were found to be statistically insignificant in the final model.These findings provide practical implications for business-es and policymakers aiming to use electric taxi adoption.To enhance appeal,stakeholders should emphasize environ-mental benefits,competitive pricing,and brand recognition while improving service reliability.By addressing these fac-tors,electric taxi services can accelerate the transition to sustainable transportation,aligning with global climate goals and transforming urban mobility.This study offers actionable insights for encouraging greener travel behaviors among students,a key demographic for long-term sustainability impact.
基金Correspondence concerning this article should be addressed to Meher Neger,Comilla University,Comilla,Bangladesh.
文摘Background of the study:The Bangladeshi cosmetics market has witnessed significant growth in recent years,driven by changing consumer lifestyles,increased disposable incomes,and rising awareness of personal grooming.The study investigates the impact of content cues which influence on purchasing intention towards cosmetic brands in Bangladesh.Purpose:The basic purpose of this study was to evaluate the factors influencing consumers’purchasing intentions for cosmetic brands in Bangladesh.Specifically,the study explored the roles of various cosmetic-related attributes and their impact on purchasing intentions within the context of Bangladesh’s cosmetic industry.Research methods:A quantitative research approach was adopted,and data were collected through a structured survey targeting Bangladeshi consumers who frequently engage with cosmetic products.All the valid responses were analyzed using SmartPLS 4.0 to perform structural equation modeling.Research findings:The findings revealed that trust in cosmetic brands and competitive pricing significantly influence consumers’purchasing intentions,highlighting the importance of fostering trust and affordability.However,certain constructs,such as ethnocentric tendencies and concerns about ingredient safety,showed limited impact on consumers’decisions.Conclusion:This study contributes to the existing literature by offering empirical insights into the Bangladeshi context,particularly within the rapidly growing cosmetics market.The findings provide actionable recommendations for cosmetic brands aiming to strengthen their market position through trust-building initiatives,competitive pricing strategies,and educational campaigns to enhance consumer awareness.These insights are particularly relevant for marketing practitioners seeking to understand and respond to the unique dynamics of the Bangladeshi cosmetics industry.
文摘Objective:This study aims to identify the prevalence of bullying in the workplace and to examine its association with turnover(TO)intention and secondary traumatic stress(STS)among Jordanian nurses employed in Emergency Departments(EDs)and critical care units(CCUs).Nurses employed in the EDs and CCUs are exposed to high levels of bullying behaviors that may contribute to STS,leading to high rates of TO.Methods:A descriptive cross-sectional design was used.A sample of 150 Jordanian nurses working in CCUs and EDs completed the study.Data collection was performed using the Demographical Questionnaire,the Negative Acts Questionnaire-Revised(NAQ-R),ProQOL scale,and TO scale.The IBM SPSS software was used to analyze data.Results:About 10.7%and 89.3%were categorized as“occasionally bullied”and“victims of workplace bullying”subsequently.Workplace bullying was positively associated with TO intention(r=0.46,P<0.001)and STS(r=0.36,P<0.001).TO was positively associated with STS(r=0.36,P<0.001).Bullying was a unique significant predictor of TO intention(t=4.59,B=0.34,P<0.001)and STS(t=4.15,B=0.34,P<0.001).Conclusions:Bullying behavior has negative adversarial effects on TO and the experience of STS.The prevalence of bullying behavior in the EDs and CCUs remains high despite the increasing awareness of its negative impacts.Healthcare organizations should put systems in place to ensure that zero-tolerance policy are monitored in terms of the effectiveness of its implementation.
基金funded by Hanshan Normal University School-Level Research Initiation Program(grant numbers QD202244QD2024207)+3 种基金the Guangdong Higher Education Society’s“Fourteenth Five-Year”Plan 2024 Higher Education Research(grant number 24GYB43)the 2024 Guangdong Provincial Undergraduate Teaching Quality and Teaching Reform Engineering Project:Excellence Program for Cultivating Publicly-Funded Pre-service Teachers for Primary Education in the Context of Rural Revitalizationthe Hanshan Normal University Guangdong East Regional Education Collaborative Innovation Research Centerfunded by these sources.
文摘This study utilized a sequential mediating model to examine the role of motivation to learn and transfer selfefficacy in the relationships between perceived content validity,mentoring function,continuous learning work culture and intention to transfer learning.The sample comprized 429 final-year apprentices in Guangdong province,China(females=69.9%,Engineering&Medicine=69%,mean age=20.99,SD=1.60).The apprentices completed standardized measures of motivation to learn,transfer self-efficacy perceived content validity,mentoring function,and continuous learning work culture.Structural equation modeling was used to analyze the data.Results showed perceived content validity,mentoring function,continuous learning culture to predict intention to transfer learning.Of these factors,perceived content validity was the strongest predictor of intention to transfer learning.Of these factors,perceived content validity was the most influential predictor of intention to transfer learning.The motivation to learn and transfer self-efficacy sequentially mediated the relationship between mentoring function and intention to learning transfer to be stronger than by either alone.Although perceived content validity and continuous learning culture exhibited no significant direct effects on intention to transfer learning,they demonstrated positive indirect associations with intention to transfer via motivation to learn and transfer self-efficacy.These study findings extend the applications of the learning transfer framework to individuals undergoing apprenticeship training which also would apply to other a long-term work-based learning programs.
文摘This study investigated the role of intentional self-regulation and the moderating role of peer relationship in the relationship between teacher-student relationship and learning engagement.The study sample comprised 540 Chinese senior secondary school students between the ages of 15–18(51.67%boys;Mage=16.56 years;SDage=0.90).They completed surveys on the Teacher-Student Relationship Scale,the Selection,Optimization,and Compensation(SOC)Scale,the Peer Relationship Scale for Children and Adolescents,and the Learning Engagement Scale.The results following regression analysis showed that teacher-student relationship predicted higher learning engagement among senior secondary school students.Intentional self-regulation partially mediated the link between teacher-student relationship and learning engagement for higher learning engagement.Peer relationship moderated the relationships between teacher-student relationship and learning engagement and moderated the relationship between teacher-student relationship and intentional self-regulation for higher learning engagement.Thesefindings imply learning engagement can be enhanced by optimizing teacher-student relationship and strengthening intentional self-regulation interventions.
基金co-supported by the National Natural Science Foundation of China(Nos.61806219,61876189 and 61703426)the Young Talent Fund of University Association for Science and Technology in Shaanxi,China(Nos.20190108 and 20220106)the Innvation Talent Supporting Project of Shaanxi,China(No.2020KJXX-065)。
文摘Air target intent recognition holds significant importance in aiding commanders to assess battlefield situations and secure a competitive edge in decision-making.Progress in this domain has been hindered by challenges posed by imbalanced battlefield data and the limited robustness of traditional recognition models.Inspired by the success of diffusion models in addressing visual domain sample imbalances,this paper introduces a new approach that utilizes the Markov Transfer Field(MTF)method for time series data visualization.This visualization,when combined with the Denoising Diffusion Probabilistic Model(DDPM),effectively enhances sample data and mitigates noise within the original dataset.Additionally,a transformer-based model tailored for time series visualization and air target intent recognition is developed.Comprehensive experimental results,encompassing comparative,ablation,and denoising validations,reveal that the proposed method achieves a notable 98.86%accuracy in air target intent recognition while demonstrating exceptional robustness and generalization capabilities.This approach represents a promising avenue for advancing air target intent recognition.
文摘To address the issue of neglecting scenarios involving joint operations and collaborative drone swarm operations in air combat target intent recognition.This paper proposes a transfer learning-based intention prediction model for drone formation targets in air combat.This model recognizes the intentions of multiple aerial targets by extracting spatial features among the targets at each moment.Simulation results demonstrate that,compared to classical intention recognition models,the proposed model in this paper achieves higher accuracy in identifying the intentions of drone swarm targets in air combat scenarios.
基金Chongqing University of Science and Technology 2024 Postgraduate Innovation Program(YKJCX2420803)。
文摘This study is based on the Extended Theory of Planned Behavior(ETPB)and focuses on the elderly population in the main urban area of Chongqing to explore their intentions and influencing factors regarding health and wellness tourism behavior.Data was collected through questionnaire surveys and field research,and SPSS 26.0 and Amos 29.0 software were used for reliability,validity analysis,and structural equation modeling testing.The study shows that behavioral attitude,perceived behavior control,and the context of health and wellness tourism have a significant positive impact on the elderly’s intentions regarding health and wellness tourism behavior,while the influence of subjective norms is not significant.In addition,subjective norms have a significant positive effect on behavioral attitudes and perceived behavioral control.Based on the research conclusions,suggestions are made to strengthen the behavioral intention of elderly tourists to participate in health and wellness tourism.
基金supported by grants from the National Key Research and Development Program of China(No.2023YFC2705700)Guangdong Basic and Applied Basic Research Foundation(No.2024A1515012355)+1 种基金the Shenzhen Science and Technology Program(No.JCYJ20220530140609020)the Scientific Research Project of Wuhan Municipal Health Commission(No.WX21Q36).
文摘Objective The effects of prolonged exposure to persistently elevated atmospheric pollutants,commonly termed air pollution waves,on fertility intentions remain inadequately understood.This study aims to investigate the association between particulate matter(PM)exposure and fertility intentions.Methods In this nationwide cross-sectional study,we analyzed data from 10,747 participants(5496 females and 5251 males).PM waves were defined as periods lasting 3‒6 consecutive days during which the daily average concentrations exceeded China’s Ambient Air Quality Standards Grade II thresholds(PM2.5>75μg/m3 and PM10>150μg/m3).We employed multivariate logistic regression models to assess the association between exposure to PM waves and fertility intentions.Results Significant inverse associations were detected between exposure to PM2.5 wave events(characterized by concentrations exceeding 75μg/m3 for durations of 4‒6 days,P<0.05)and PM10 wave events(defined as concentrations exceeding 150μg/m3 for 6 consecutive days,P<0.05)and fertility intentions among females.In contrast,neither the PM2.5 wave nor the PM10 wave events demonstrated statistically significant correlations with fertility intentions in males(P>0.05 for all comparisons).The potentially susceptible subgroup was identified as females aged 20–30 years.Conclusions Our results provide the first evidence that PM2.5 and PM10 waves are associated with a reduction in female fertility intentions,offering critical insights for the development of public health policies and strategies aimed at individual protection.
文摘In the contemporary digital landscape,the proliferation of information has led to an increasing diversity of channels through which consumers obtain information,resulting in a gradual transformation of shopping habits.Consumers now frequently rely on external sources to make well-informed purchasing decisions,leading to the emergence of live shopping as a prominent avenue for gathering product information and completing transactions.E-commerce live streaming has experienced rapid growth,leveraging its ability to generate traffic and capture consumer attention.The integration of content and live streaming not only meets users’psychological needs but also facilitates seamless communication between buyers and sellers.From the perspective of content marketing typologies,this paper examines content marketing across three key dimensions:informational content,entertainment content,and emotional content.It further explores the impact of content marketing on consumers’purchase intentions within the context of e-commerce live streaming.
文摘This study focuses on the relationship between job stress and intention to leave among obstetric(OB)nurses in the context of China's birth policy adjustment,and provides a scientific basis for policymakers and healthcare administrators.This study used a non-experimental descriptive correlation design with a purposive sampling of 230 OB nurses from three tertiary hospitals in Jinan,Shandong Province.Participants were surveyed using three questionnaires and descriptive analysis;ANOVA and correlation analyses were used to analyze the relationship between participants'stressor levels and turnover intention.Pearson's correlation coefficient analysis showed that there was a positive correlation between nurses‘work stressors and turnover intention,with a correlation coefficient of r=0.53,a moderate positive correlation(P<0.001).Based on the survey data from three tertiary hospitals in Shandong Province,the obstetric nurses group has a medium level of work stressors,but a high turnover intention,highlighting the professional identity crisis.
基金supported by the Aeronautical Science Foundation of China(2020Z023053002).
文摘High complexity and uncertainty of air combat pose significant challenges to target intention prediction.Current interpolation methods for data pre-processing and wrangling have limitations in capturing interrelationships among intricate variable patterns.Accordingly,this study proposes a Mogrifier gate recurrent unit-D(Mog-GRU-D)model to address the com-bat target intention prediction issue under the incomplete infor-mation condition.The proposed model directly processes miss-ing data while reducing the independence between inputs and output states.A total of 1200 samples from twelve continuous moments are captured through the combat simulation system,each of which consists of seven dimensional features.To bench-mark the experiment,a missing valued dataset has been gener-ated by randomly removing 20%of the original data.Extensive experiments demonstrate that the proposed model obtains the state-of-the-art performance with an accuracy of 73.25%when dealing with incomplete information.This study provides possi-ble interpretations for the principle of target interactive mecha-nism,highlighting the model’s effectiveness in potential air war-fare implementation.
基金supported in part by the National Natural Science Foundation of China.The funding numbers 62433005,62272036,62132003,and 62173167.
文摘The consultation intention of emergency decision-makers in urban rail transit(URT)is input into the emergency knowledge base in the form of domain questions to obtain emergency decision support services.This approach facilitates the rapid collection of complete knowledge and rules to form effective decisions.However,the current structured degree of the URT emergency knowledge base remains low,and the domain questions lack labeled datasets,resulting in a large deviation between the consultation outcomes and the intended objectives.To address this issue,this paper proposes a question intention recognition model for the URT emergency domain,leveraging knowledge graph(KG)and data enhancement technology.First,a structured storage of emergency cases and emergency plans is realized based on KG.Subsequently,a comprehensive question template is developed,and the labeled dataset of emergency domain questions in URT is generated through the KG.Lastly,data enhancement is applied by prompt learning and the NLP Chinese Data Augmentation(NLPCDA)tool,and the intention recognition model combining Generalized Auto-regression Pre-training for Language Understanding(XLNet)and Recurrent Convolutional Neural Network for Text Classification(TextRCNN)is constructed.Word embeddings are generated by XLNet,context information is further captured using Bidirectional Long Short-Term Memory Neural Network(BiLSTM),and salient features are extracted with Convolutional Neural Network(CNN).Experimental results demonstrate that the proposed model can enhance the clarity of classification and the identification of domain questions,thereby providing supportive knowledge for emergency decision-making in URT.
文摘Despite the gradual transformation of traditional manufacturing by the Human-Robot Collaboration Assembly(HRCA),challenges remain in the robot’s ability to understand and predict human assembly intentions.This study aims to enhance the robot’s comprehension and prediction capabilities of operator assembly intentions by capturing and analyzing operator behavior and movements.We propose a video feature extraction method based on the Temporal Shift Module Network(TSM-ResNet50)to extract spatiotemporal features from assembly videos and differentiate various assembly actions using feature differences between video frames.Furthermore,we construct an action recognition and segmentation model based on the Refined-Multi-Scale Temporal Convolutional Network(Refined-MS-TCN)to identify assembly action intervals and accurately acquire action categories.Experiments on our self-built reducer assembly action dataset demonstrate that our network can classify assembly actions frame by frame,achieving an accuracy rate of 83%.Additionally,we develop a HiddenMarkovModel(HMM)integrated with assembly task constraints to predict operator assembly intentions based on the probability transition matrix and assembly task constraints.The experimental results show that our method for predicting operator assembly intentions can achieve an accuracy of 90.6%,which is a 13.3%improvement over the HMM without task constraints.
文摘This study aims to the factors influencing consumer intention to purchase eco-friendly,small-packaged agricultural products using the Theory of Planned Behavior(TPB).With increasing demand for sustainable consumption,eco-friendly food packaging has become a critical focus within the circular economy.This study was conducted in Seoul,South Korea,a key marketplace for consumer trends,and surveyed 200 respondents to examine key TPB components—attitude,subjective norms,and perceived behavioral control—along with additional factors shaping sustainable purchasing behavior.The findings indicate that perceived behavioral control is the predictor of purchase intention(β=0.510,p<0.001),followed by attitude(β=0.236,p<0.05)and subjective norms(β=0.199,p<0.05).Moreover,the results suggest that while social influences play a role,individuals who perceive fewer barriers and have a stronger personal attitude toward sustainability are more likely to adopt eco-friendly purchasing behaviors.These results highlight the importance of consumer autonomy and confidence in making eco-friendly choices,suggesting that increasing accessibility and affordability of sustainable packaging can drive adoption.Despite social influences,urban consumers prioritize personal values and perceived control over purchasing behavior.The study might contribute to sustainability literature by offering insights into eco-conscious consumer behavior and implications for marketing strategies that promote sustainable agricultural products.Future research should explore cross-cultural comparisons and additional psychological determinants to enhance the understanding of sustainable consumption patterns.
基金Supported by Key Research Project of Anhui Xinhua University(2022 University-Level)from the Student Quality Education Research Center(IFQE202202)Provincial-Level Quality Engineering Project of Anhui Provincial Department of Education for Higher Education Institutions(2022-JYXM671).
文摘A survey was conducted among 616 students from six private undergraduate universities in Hefei City,Anhui Province.Using Likert 5-point scale measurements and SPSS 27.0 for data analysis,the study revealed that students with prior entrepreneurial experience demonstrated lower satisfaction with university entrepreneurship education,and their past entrepreneurial attempts showed a negative correlation with future entrepreneurial intentions.However,high-quality entrepreneurship education exhibited a positive mediating role in this relationship.This study reveals the intrinsic mechanisms through which personal experiences and entrepreneurship education influence college students'entrepreneurial intentions,providing theoretical references for higher education institutions to optimize entrepreneurship education programs and enhance students'entrepreneurial motivations.These findings will contribute to the national strategy of"promoting employment through entrepreneurship".
基金supported by the National Natural Science Foundation of China(U20A20111)the National key R&D Program(2022YFC3080100)。
文摘The evacuation of people under threat is an effective disaster prevention and mitigation measure in response to flash floods and geological hazards,and it is also an essential element of pre-disaster planning.However,the effect of the interactions between perception factors on residents'willingness to evacuate is an urgent problem to be solved.Therefore,this paper introduces risk,stakeholder,and protective action perceptions from the protective action decision model as the main explanatory variables.These three core perceptions are subdivided into affective risk perception,cognitive risk perception,government perception,other-stakeholder perception,resourcerelated attributes,and hazard-related attributes.A questionnaire survey was conducted from June to July 2023 among residents of mountainous communities in nine villages in three towns in Sichuan Province,China.359 cross-sectional data were analyzed using structural equation modeling to explore the effects of six perception factors on evacuation intentions.The results of the study showed that:(1)affective risk perception,government perception,other-stakeholder perception,and hazard-related attributes all directly and positively influence residents'intentions to evacuate;(2)cognitive risk perception is mediated by stakeholder and protective action perceptions,which indirectly and positively affect residents'intentions to evacuate.Based on the hypothesized paths,strategies to improve residents'willingness to evacuate are discussed from the perspective of three core perceptions:strengthening disaster risk education,improving residents'cohesion,and building government credibility.The results of this study can provide theoretical support and practical suggestions for emergency management departments to formulate emergency evacuation strategies,which can aid decision-makers in better understanding residents'intentions to evacuate,optimizing evacuation information dissemination pathways,and strengthening disaster risk management capabilities.
基金supported by Research Projects of the Nature Science Foundation of Hebei Province(F2021402005).
文摘Semi-supervised new intent discovery is a significant research focus in natural language understanding.To address the limitations of current semi-supervised training data and the underutilization of implicit information,a Semi-supervised New Intent Discovery for Elastic Neighborhood Syntactic Elimination and Fusion model(SNID-ENSEF)is proposed.Syntactic elimination contrast learning leverages verb-dominant syntactic features,systematically replacing specific words to enhance data diversity.The radius of the positive sample neighborhood is elastically adjusted to eliminate invalid samples and improve training efficiency.A neighborhood sample fusion strategy,based on sample distribution patterns,dynamically adjusts neighborhood size and fuses sample vectors to reduce noise and improve implicit information utilization and discovery accuracy.Experimental results show that SNID-ENSEF achieves average improvements of 0.88%,1.27%,and 1.30%in Normalized Mutual Information(NMI),Accuracy(ACC),and Adjusted Rand Index(ARI),respectively,outperforming PTJN,DPN,MTP-CLNN,and DWG models on the Banking77,StackOverflow,and Clinc150 datasets.The code is available at https://github.com/qsdesz/SNID-ENSEF,accessed on 16 January 2025.
基金partially supported by the National Natural Science Foundation of China(No.62173272)。
文摘Recognizing target intent is crucial for making decisions on the battlefield.However,the imperfect and ambiguous character of battlefield situations challenges the validity and causation analysis of classical intent recognition techniques.Facing with the challenge,a target intention causal analysis paradigm is proposed by combining with an Intervention Retrieval(IR)model and a Hybrid Intention Recognition(HIR)model.The target data acquired by the sensors are modelled as Basic Probability Assignments(BPAs)based on evidence theory to create uncertain datasets.Then,the HIR model is utilized to recognize intent for a tested sample from uncertain datasets.Finally,the intervention operator under the evidence structure is utilized to perform attribute intervention on the tested sample.Data retrieval is performed in the sample database based on the IR model to generate the intention distribution of the pseudo-intervention samples to analyze the causal effects of individual sample attributes.The simulation results demonstrate that our framework successfully identifies the target intention under the evidence structure and goes further to analyze the causal impact of sample attributes on the target intention.
