Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the i...Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the interfaces of verbal and emotional communications. The progress of AI is significant on the verbal level but modest in terms of the recognition of facial emotions even if this functionality is one of the oldest in humans and is omnipresent in our daily lives. Dysfunction in the ability for facial emotional expressions is present in many brain pathologies encountered by psychiatrists, neurologists, psychotherapists, mental health professionals including social workers. It cannot be objectively verified and measured due to a lack of reliable tools that are valid and consistently sensitive. Indeed, the articles in the scientific literature dealing with Visual-Facial-Emotions-Recognition (ViFaEmRe), suffer from the absence of 1) consensual and rational tools for continuous quantified measurement, 2) operational concepts. We have invented a software that can use computer-morphing attempting to respond to these two obstacles. It is identified as the Method of Analysis and Research of the Integration of Emotions (M.A.R.I.E.). Our primary goal is to use M.A.R.I.E. to understand the physiology of ViFaEmRe in normal healthy subjects by standardizing the measurements. Then, it will allow us to focus on subjects manifesting abnormalities in this ability. Our second goal is to make our contribution to the progress of AI hoping to add the dimension of recognition of facial emotional expressions. Objective: To study: 1) categorical vs dimensional aspects of recognition of ViFaEmRe, 2) universality vs idiosyncrasy, 3) immediate vs ambivalent Emotional-Decision-Making, 4) the Emotional-Fingerprint of a face and 5) creation of population references data. Methods: M.A.R.I.E. enables the rational, quantified measurement of Emotional Visual Acuity (EVA) in an individual observer and a population aged 20 to 70 years. Meanwhile, it can measure the range and intensity of expressed emotions through three Face- Tests, quantify the performance of a sample of 204 observers with hypernormal measures of cognition, “thymia” (defined elsewhere), and low levels of anxiety, and perform analysis of the six primary emotions. Results: We have individualized the following continuous parameters: 1) “Emotional-Visual- Acuity”, 2) “Visual-Emotional-Feeling”, 3) “Emotional-Quotient”, 4) “Emotional-Decision-Making”, 5) “Emotional-Decision-Making Graph” or “Individual-Gun-Trigger”, 6) “Emotional-Fingerprint” or “Key-graph”, 7) “Emotional-Fingerprint-Graph”, 8) detecting “misunderstanding” and 9) detecting “error”. This allowed us a taxonomy with coding of the face-emotion pair. Each face has specific measurements and graphics. The EVA improves from ages of 20 to 55 years, then decreases. It does not depend on the sex of the observer, nor the face studied. In addition, 1% of people endowed with normal intelligence do not recognize emotions. The categorical dimension is a variable for everyone. The range and intensity of ViFaEmRe is idiosyncratic and not universally uniform. The recognition of emotions is purely categorical for a single individual. It is dimensional for a population sample. Conclusions: Firstly, M.A.R.I.E. has made possible to bring out new concepts and new continuous measurements variables. The comparison between healthy and abnormal individuals makes it possible to take into consideration the significance of this line of study. From now on, these new functional parameters will allow us to identify and name “emotional” disorders or illnesses which can give additional dimension to behavioral disorders in all pathologies that affect the brain. Secondly, the ViFaEmRe is idiosyncratic, categorical, and a function of the identity of the observer and of the observed face. These findings stack up against Artificial Intelligence, which cannot have a globalist or regionalist algorithm that can be programmed into a robot, nor can AI compete with human abilities and judgment in this domain. *Here “Emotional disorders” refers to disorders of emotional expressions and recognition.展开更多
Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the i...Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the interfaces of verbal and emotional communications. The progress of AI is significant on the verbal level but modest in terms of the recognition of facial emotions even if this functionality is one of the oldest in humans and is omnipresent in our daily lives. Dysfunction in the ability for facial emotional expressions is present in many brain pathologies encountered by psychiatrists, neurologists, psychotherapists, mental health professionals including social workers. It cannot be objectively verified and measured due to a lack of reliable tools that are valid and consistently sensitive. Indeed, the articles in the scientific literature dealing with Visual-Facial-Emotions-Recognition (ViFaEmRe), suffer from the absence of 1) consensual and rational tools for continuous quantified measurement, 2) operational concepts. We have invented a software that can use computer-morphing attempting to respond to these two obstacles. It is identified as the Method of Analysis and Research of the Integration of Emotions (M.A.R.I.E.). Our primary goal is to use M.A.R.I.E. to understand the physiology of ViFaEmRe in normal healthy subjects by standardizing the measurements. Then, it will allow us to focus on subjects manifesting abnormalities in this ability. Our second goal is to make our contribution to the progress of AI hoping to add the dimension of recognition of facial emotional expressions. Objective: To study: 1) categorical vs dimensional aspects of recognition of ViFaEmRe, 2) universality vs idiosyncrasy, 3) immediate vs ambivalent Emotional-Decision-Making, 4) the Emotional-Fingerprint of a face and 5) creation of population references data. Methods: With M.A.R.I.E. enable a rational quantified measurement of Emotional-Visual-Acuity (EVA) of 1) a) an individual observer, b) in a population aged 20 to 70 years old, 2) measure the range and intensity of expressed emotions by 3 Face-Tests, 3) quantify the performance of a sample of 204 observers with hyper normal measures of cognition, “thymia,” (ibid. defined elsewhere) and low levels of anxiety 4) analysis of the 6 primary emotions. Results: We have individualized the following continuous parameters: 1) “Emotional-Visual-Acuity”, 2) “Visual-Emotional-Feeling”, 3) “Emotional-Quotient”, 4) “Emotional-Deci-sion-Making”, 5) “Emotional-Decision-Making Graph” or “Individual-Gun-Trigger”6) “Emotional-Fingerprint” or “Key-graph”, 7) “Emotional-Finger-print-Graph”, 8) detecting “misunderstanding” and 9) detecting “error”. This allowed us a taxonomy with coding of the face-emotion pair. Each face has specific measurements and graphics. The EVA improves from ages of 20 to 55 years, then decreases. It does not depend on the sex of the observer, nor the face studied. In addition, 1% of people endowed with normal intelligence do not recognize emotions. The categorical dimension is a variable for everyone. The range and intensity of ViFaEmRe is idiosyncratic and not universally uniform. The recognition of emotions is purely categorical for a single individual. It is dimensional for a population sample. Conclusions: Firstly, M.A.R.I.E. has made possible to bring out new concepts and new continuous measurements variables. The comparison between healthy and abnormal individuals makes it possible to take into consideration the significance of this line of study. From now on, these new functional parameters will allow us to identify and name “emotional” disorders or illnesses which can give additional dimension to behavioral disorders in all pathologies that affect the brain. Secondly, the ViFaEmRe is idiosyncratic, categorical, and a function of the identity of the observer and of the observed face. These findings stack up against Artificial Intelligence, which cannot have a globalist or regionalist algorithm that can be programmed into a robot, nor can AI compete with human abilities and judgment in this domain. *Here “Emotional disorders” refers to disorders of emotional expressions and recognition.展开更多
Introduction: Emotional intelligence, or the capacity to cope one’s emotions, makes it simpler to form good connections with others and do caring duties. Nursing students can enroll a health team in a helpful and ben...Introduction: Emotional intelligence, or the capacity to cope one’s emotions, makes it simpler to form good connections with others and do caring duties. Nursing students can enroll a health team in a helpful and beneficial way with the use of emotional intelligence. Nurses who can identify, control, and interpret both their own emotions and those of their patients provide better patient care. The purpose of this study was to assess the emotional intelligence and to investigate the relationship and differences between emotional intelligence and demographic characteristics of nursing students. Methods: A cross-sectional study was carried out on 381 nursing students. Data collection was completed by “Schutte Self Report Emotional Intelligence Test”. Data were analyzed with the Statistical Package for Social Science. An independent t test, ANOVA, and Pearson correlation, multiple linear regression were used. Results: The results revealed that the emotional intelligence mean was 143.1 ± 21.6 (ranging from 33 to 165), which is high. Also, the analysis revealed that most of the participants 348 (91.3%) had higher emotional intelligence level. This finding suggests that nursing students are emotionally intelligent and may be able to notice, analyze, control, manage, and harness emotion in an adaptive manner. Also, academic year of nursing students was a predictor of emotional intelligence. Furthermore, there was positive relationship between the age and emotional intelligence (p < 0.05). The students’ ability to use their EI increased as they rose through the nursing grades. Conclusion: This study confirmed that the emotional intelligence score of the nursing students was high. Also, academic year of nursing students was a predictor of emotional intelligence. In addition, a positive relationship was confirmed between the emotional intelligence and age of nursing students. .展开更多
With the rapid spread of Internet information and the spread of fake news,the detection of fake news becomes more and more important.Traditional detection methods often rely on a single emotional or semantic feature t...With the rapid spread of Internet information and the spread of fake news,the detection of fake news becomes more and more important.Traditional detection methods often rely on a single emotional or semantic feature to identify fake news,but these methods have limitations when dealing with news in specific domains.In order to solve the problem of weak feature correlation between data from different domains,a model for detecting fake news by integrating domain-specific emotional and semantic features is proposed.This method makes full use of the attention mechanism,grasps the correlation between different features,and effectively improves the effect of feature fusion.The algorithm first extracts the semantic features of news text through the Bi-LSTM(Bidirectional Long Short-Term Memory)layer to capture the contextual relevance of news text.Senta-BiLSTM is then used to extract emotional features and predict the probability of positive and negative emotions in the text.It then uses domain features as an enhancement feature and attention mechanism to fully capture more fine-grained emotional features associated with that domain.Finally,the fusion features are taken as the input of the fake news detection classifier,combined with the multi-task representation of information,and the MLP and Softmax functions are used for classification.The experimental results show that on the Chinese dataset Weibo21,the F1 value of this model is 0.958,4.9% higher than that of the sub-optimal model;on the English dataset FakeNewsNet,the F1 value of the detection result of this model is 0.845,1.8% higher than that of the sub-optimal model,which is advanced and feasible.展开更多
Under the effects of COVID-19 and a number of ongoing lockdown tactics,anxiety symptoms and poor sleep quality have become common mental health issues among college freshmen and are intimately related to their emotion...Under the effects of COVID-19 and a number of ongoing lockdown tactics,anxiety symptoms and poor sleep quality have become common mental health issues among college freshmen and are intimately related to their emotional adaptation.To explore this connection,this study gathered data from a sample of 256 freshmen enrolled in an elite university in China in September 2022.The association between sleep quality,anxiety symptoms,and emotional adaptation was clarified using correlation analysis.Additionally,the mediating function of anxiety symptoms between sleep quality and emotional adaptation was investigated using a structural equation model.The results reveal that:(1)Chinese elite university freshmen who were subjected to prolonged lockdown had poor sleep quality and mild anxiety symptoms;(2)a significant positive correlation between poor sleep quality and anxiety symptoms was identified;(3)anxiety symptoms were found to have a significant negative impact on emotional adaptation;(4)poor sleep quality had a negative impact on emotional adaptation through anxiety symptoms.This research makes a valuable contribution by offering insights into the intricate relationship between sleep quality and emotional adaptation among freshmen in elite Chinese universities during prolonged lockdown conditions,and it is beneficial for schools and educators to further improve school schedules and psychological health initiatives.展开更多
Adolescents are considered one of the most vulnerable groups affected by suicide.Rapid changes in adolescents’physical and mental states,as well as in their lives,significantly and undeniably increase the risk of sui...Adolescents are considered one of the most vulnerable groups affected by suicide.Rapid changes in adolescents’physical and mental states,as well as in their lives,significantly and undeniably increase the risk of suicide.Psychological,social,family,individual,and environmental factors are important risk factors for suicidal behavior among teenagers and may contribute to suicide risk through various direct,indirect,or combined pathways.Social-emotional learning is considered a powerful intervention measure for addressing the crisis of adolescent suicide.When deliberately cultivated,fostered,and enhanced,selfawareness,self-management,social awareness,interpersonal skills,and responsible decision-making,as the five core competencies of social-emotional learning,can be used to effectively target various risk factors for adolescent suicide and provide necessary mental and interpersonal support.Among numerous suicide intervention methods,school-based interventions based on social-emotional competence have shown great potential in preventing and addressing suicide risk factors in adolescents.The characteristics of school-based interventions based on social-emotional competence,including their appropriateness,necessity,cost-effectiveness,comprehensiveness,and effectiveness,make these interventions an important means of addressing the crisis of adolescent suicide.To further determine the potential of school-based interventions based on social-emotional competence and better address the issue of adolescent suicide,additional financial support should be provided,the combination of socialemotional learning and other suicide prevention programs within schools should be fully leveraged,and cooperation between schools and families,society,and other environments should be maximized.These efforts should be considered future research directions.展开更多
Objective:To assess emotional fluctuations,physical and mental health status,and indicators closely related to red blood cells,such as RIO kinase 3(Riok3),MAX interactor 1(Mxi1),and microRNA 191(miR191),in participant...Objective:To assess emotional fluctuations,physical and mental health status,and indicators closely related to red blood cells,such as RIO kinase 3(Riok3),MAX interactor 1(Mxi1),and microRNA 191(miR191),in participants with different levels of red blood cells.Methods:Participants who underwent physical examinations at Dongfang Hospital between April and October 2019 were divided into healthy,blood deficiency,and anemia groups(30 individuals in the healthy and blood deficiency group respectively,and 13 in the anemia group).The physical and mental conditions of the participants were evaluated through questionnaires,and emotional fluctuations were assessed through an emotion-inducing experiment,in which participants watched video segments designed to induce specific emotions.Relative expression levels of miR191,Riok3,and Mxi1 from venous blood samples were also determined.Results:The main psychological factors identified in the anemia and blood deficiency groups were obsessive-compulsive symptoms,depression,anxiety,and other negative emotions.Relative gene expression levels indicated that miR191 was upregulated and Riok3 and Mxi1 were downregulated in both the blood deficiency and anemia groups.Regarding the emotional score of disgust on video stage,the main effect was significant(F=335.58,P<.001),which showed that watching the three videos caused participants to have a dominant emotion,and there is a difference on group(F=5.35,P=.01),with higher disgust scores in the anemia and blood deficiency groups.The symptoms of blood deficiency and anemia,such as weakness in limbs were significantly negatively correlated with Riok3 and Mxi1 expression(r=-0.38 and-0.31 respectively),but was significantly positively correlated with miR191 expression(r=0.29).Conclusion:We determined that a close relationship exists between red blood cell levels and emotional status.Our findings suggest that individuals with anemia and blood deficiency are more likely to experience psychological problems and negative emotions,particularly disgust.We also demonstrate that emotional regulation is related to mir191-Riok3-Mxi1 pathway activity,identifying these pathway components are potential targets for genetic therapies in combination with psychological therapy.展开更多
The Japanese movie“0.5mm”connects the life clips between the nursing-care helper Sawa and several old people in the form of a road movie,highlighting many thought-provoking social problems,and revealing how the elem...The Japanese movie“0.5mm”connects the life clips between the nursing-care helper Sawa and several old people in the form of a road movie,highlighting many thought-provoking social problems,and revealing how the elements of emotional abuse hidden between the old people and their relatives and friends affect people’s dignity and decency,and at the same time trying to offset the persecution from the emotional abuse with the warm kindness between the elderly and the care workers.The film’s implicit description of emotional abuse and explicit display of good deeds are blended in the quiet and mysterious narrative character,achieving the effect of synchronizing the artistic narrative rhythm with the flow of life,reflecting the unique aesthetic characteristics of Japanese films.展开更多
Sentiment analysis is a method to identify and understand the emotion in the text through NLP and text analysis. In the era of information technology, there is often a certain error between the comments on the movie w...Sentiment analysis is a method to identify and understand the emotion in the text through NLP and text analysis. In the era of information technology, there is often a certain error between the comments on the movie website and the actual score of the movie, and sentiment analysis technology provides a new way to solve this problem. In this paper, Python is used to obtain the movie review data from the Douban platform, and the model is constructed and trained by using naive Bayes and Bi-LSTM. According to the index, a better Bi-LSTM model is selected to classify the emotion of users’ movie reviews, and the classification results are scored according to the classification results, and compared with the real ratings on the website. According to the error of the final comparison results, the feasibility of this technology in the scoring direction of film reviews is being verified. By applying this technology, the phenomenon of film rating distortion in the information age can be prevented and the rights and interests of film and television works can be safeguarded.展开更多
This article presents an analysis of the patterns of interactions resulting from the positive and negative emotional events that occur in cities,considering them as complex systems.It explores,from the imaginaries,how...This article presents an analysis of the patterns of interactions resulting from the positive and negative emotional events that occur in cities,considering them as complex systems.It explores,from the imaginaries,how certain urban objects can act as emotional agents and how these events affect the urban system as a whole.An adaptive complex systems perspective is used to analyze these patterns.The results show patterns in the processes and dynamics that occur in cities based on the objects that affect the emotions of the people who live there.These patterns depend on the characteristics of the emotional charge of urban objects,but they can be generalized in the following process:(1)immediate reaction by some individuals;(2)emotions are generated at the individual level which begins to generalize,permuting to a collective emotion;(3)a process of reflection is detonated in some individuals from the reading of collective emotions;(4)integration/significance in the community both at the individual and collective level,on the concepts,roles and/or functions that give rise to the process in the system.Therefore,it is clear that emotions play a significant role in the development of cities and these aspects should be considered in the design strategies of all kinds of projects for the city.Future extensions of this work could include a deeper analysis of specific emotional events in urban environments,as well as possible implications for urban policy and decision making.展开更多
Objective:According to the World Federation of Medical Education,critical thinking should be part of the training of medical and paramedical students.Professionals can improve the quality of care of patients after sur...Objective:According to the World Federation of Medical Education,critical thinking should be part of the training of medical and paramedical students.Professionals can improve the quality of care of patients after surgery by having or acquiring this skill in health care.Also,Emotional intelligence is introduced as an impor tant and effective factor on the professional performance and mental health of healthcare professionals.Thus,the present study was designed and implemented to determine the relationship between emotional intelligence and critical thinking among operating room nursing students of medical sciences universities in Iran.Methods:This cross-sectional study was done on 420 operating room students in 10 top medical sciences universities of Iran in 2022.The sampling method in this research was multistage sampling.The data collection instruments included demographic characteristics,Rickett's critical thinking,and Bradberry-Greaves'emotional intelligence questionnaires.After receiving the ethics code,data collection was done for 2 months.For data analysis,descriptive and inferential analyses including independent t-tests,analysis of variance,and Pearson correlation were used.The collected data were analyzed by SPSS 18(IBM Corporation,Armonk,New York,United States).P-value<0.05 was considered significant.Results:The mean age of the students participating in this study was 23.02±3.70 years,with women constituting 67.4%of them.The results of data analysis indicated that the mean total score of critical thinking and emotional intelligence was 124.10±37.52 and 114.12±43.63,respectively.A direct significant correlation between critical thinking and emotional intelligence(r=0.459,P-value<0.001)and a significant relationship between gender and emotional intelligence(P-value=0.028)were found.Conclusions:Based on the present study results,educational managers in the Ministry of Health are suggested to consider suitable educational programs for improving critical thinking and emotional intelligence to enhance the quality of care provided by students in operating rooms.展开更多
The adequacy of language education largely depends on the favorable and unfavorable emotions that teachers and students experience throughout the education process.Simply said,emotional factors play a key role in impr...The adequacy of language education largely depends on the favorable and unfavorable emotions that teachers and students experience throughout the education process.Simply said,emotional factors play a key role in improving the quality of language teaching and learning.Furthermore,these emotional factors also promote the well-being of language teachers and learners and place them in a suitable mental condition.In view of the favorable impact of emotional factors on the mental health of language teachers and learners,many educational scholars around the world have studied these factors,their background,and their pedagogical consequences.Nonetheless,the majority of previous studies have employed traditional research methods in assessing these variables and their influences on language teachers’and learners’mental health.Because of the complex and dynamic quality of emotional factors,traditional research approaches often fail to evaluate these factors and their dynamic,non-linear connections with teachers’and learners’mental health and well-being.Accordingly,some novel research approaches are required to measure the dynamicity and complexity of emotional factors in language education settings.To address this call,the current state-of-the-art conceptual article seeks to provide new insights for investigating emotional factors and their potential impact on language teachers’and learners’mental states.This study also intends to offer a comprehensive list of emerging methods that take into account the complex and dynamic nature of emotional variables.Finally,the study outlines the potential implications of this review for educational researchers.展开更多
Background:The prevalence of pediatric mental illnesses has been increasing in recent years,with a great potential to impact on individual's functionality and adaptation in adulthood.Objective:This study aims to a...Background:The prevalence of pediatric mental illnesses has been increasing in recent years,with a great potential to impact on individual's functionality and adaptation in adulthood.Objective:This study aims to assess emotional and behavioral problems among schoolchildren in Herat City of Afghanistan.Methods:This cross-sectional study was conducted on schoolchildren(grade 5-10),between September and November 2021.Sociodemographic data was collected using a paper-based 14-item structured questionnaire.Data on emotional and behavioral problems was collected using the Strengths and Difficulties Questionnaire(SDQ)based on teachers'and children's report.Statistical analyses were performed in IBM SPSS Statistics(version 27).Results:A total of 418 students,including 190(45.5%)males and 228(54.5%)females with a mean age of 14.1±1.7(11-<18)years were included in the study.The prevalence of students*self-reported total difficulties and prosocial problem were 5.7%and 1.2%,respectively.An insignificant difference was observed between mean total difficulties scores between students'self-reported and teachers'reported SDQ.Gender,grade,concern about shortage of food,and concern about losing house were significantly predicting students'self-reported total difficulties scores.Conclusion:This is the first study to report the prevalence of emotional and behavioral problems among schoolchildren in Herat City,Afghanistan.This,together with relevant global literature,highlight the need to address pediatric mental health,and provide services aimed at preventing,and treating children with these problems around the world.展开更多
Handling emotions in human‐computer dialogues has emerged as a challenging task which requires artificial intelligence systems to generate emotional responses by jointly perceiving the emotion involved in the input p...Handling emotions in human‐computer dialogues has emerged as a challenging task which requires artificial intelligence systems to generate emotional responses by jointly perceiving the emotion involved in the input posts and incorporating it into the gener-ation of semantically coherent and emotionally reasonable responses.However,most previous works generate emotional responses solely from input posts,which do not take full advantage of the training corpus and suffer from generating generic responses.In this study,we introduce a hierarchical semantic‐emotional memory module for emotional conversation generation(called HSEMEC),which can learn abstract semantic conver-sation patterns and emotional information from the large training corpus.The learnt semantic and emotional knowledge helps to enrich the post representation and assist the emotional conversation generation.Comprehensive experiments on a large real‐world conversation corpus show that HSEMEC can outperform the strong baselines on both automatic and manual evaluation.For reproducibility,we release the code and data publicly at:https://github.com/siat‐nlp/HSEMEC‐code‐data.展开更多
At present, the channels used for EEG acquisition are more than 16, which makes it difficult to wear EEG caps and has poor contact. Therefore, it brings difficulties to the collection of brain waves is not conducive t...At present, the channels used for EEG acquisition are more than 16, which makes it difficult to wear EEG caps and has poor contact. Therefore, it brings difficulties to the collection of brain waves is not conducive to converting research into applications. It is a well worth studying work in researching how to find the key brain electrode in the existing brain wave, which will greatly reduce the number of EEG acquisition points during application, making it easier to translate the research into practical application. This paper takes emotional EEG as an example to study how to find the key brain electrode points of emotional EEG with deep learning method. Firstly, using the least square regression algorithm to calculate the characteristic coefficients of each electrode point;secondly, according to the law of the characteristic coefficient value, grouping the key EEG poles for experiment. In the grouping experiment, the Conv1d-GRU model used to train and verify the EEG data of the corresponding electrode points. Finally, from the results of various grouping experiments, it concluded that the selection method of the key EEG level points should be the electrode points with positive characteristic coefficient, and the accuracy of verification is 97.6%. With experiments, it confirmed that there are key electrode points in the detection of emotional EEG by 16-channel OpenBCI. There are only six key electrode points of emotional EEG;that is to say, the EEG data collected by only six key electrode points can identify seven kinds of emotional EEG. .展开更多
The relapse of methamphetamine (meth) is associated with decision-making dysfunction. The present study aims to investigate theimpact of different emotions on the decision-making behavior of meth users. We used 2 (gen...The relapse of methamphetamine (meth) is associated with decision-making dysfunction. The present study aims to investigate theimpact of different emotions on the decision-making behavior of meth users. We used 2 (gender: male, female) × 3 (emotion:positive, negative, neutral) × 5 (block: 1, 2, 3, 4, 5) mixed experiment design. The study involved 168 meth users who weredivided into three groups: positive emotion, negative emotion and neutral emotion group, and tested by the emotional IowaGambling Task (IGT). The IGT performance of male users exhibited a decreasing trend from Block 1 to Block 3. Female methusers in positive emotion had the best performance in IGT than females in the other two groups. In positive emotion, the IGTperformance of female meth users was significantly better than that of men. Female meth users in positive emotion had betterdecision-making than those in negative or neutral emotion. Female meth users in positive emotion had better decision-makingperformance than males in positive emotion. In negative and neutral emotions, there was no significant gender difference indecision-making.展开更多
This study aimed to explore citizens’emotional responses and issues of interest in the context of the coronavirus disease 2019(COVID-19)pandemic.The dataset comprised 65,313 tweets with the location marked as New Yor...This study aimed to explore citizens’emotional responses and issues of interest in the context of the coronavirus disease 2019(COVID-19)pandemic.The dataset comprised 65,313 tweets with the location marked as New York State.The data collection period was four days of tweets when New York City imposed a lockdown order due to an increase in confirmed cases.Data analysis was performed using R Studio.The emotional responses in tweets were analyzed using the Bing and NRC(National Research Council Canada)dictionaries.The tweets’central issue was identified by Text Network Analysis.When tweets were classified as either positive or negative,the negative sentiment was higher.Using the NRC dictionary,eight emotional classifications were devised:“trust,”“fear,”“anticipation,”“sadness,”“anger,”“joy,”“surprise,”and“disgust.”These results indicated that citizens showed negative and trusting emotional reactions in the early days of the pandemic.Moreover,citizens showed a strong interest in overcoming and coping with other people such as social solidarity.Citizens were concerned about the confirmation of COVID-19 infection status and death.Efforts should be made to ensure citizens’psychological stability by promptly informing them of the status of infectious disease management and the route of infection.展开更多
In recent years,speech synthesis systems have allowed for the produc-tion of very high-quality voices.Therefore,research in this domain is now turning to the problem of integrating emotions into speech.However,the met...In recent years,speech synthesis systems have allowed for the produc-tion of very high-quality voices.Therefore,research in this domain is now turning to the problem of integrating emotions into speech.However,the method of con-structing a speech synthesizer for each emotion has some limitations.First,this method often requires an emotional-speech data set with many sentences.Such data sets are very time-intensive and labor-intensive to complete.Second,training each of these models requires computers with large computational capabilities and a lot of effort and time for model tuning.In addition,each model for each emotion failed to take advantage of data sets of other emotions.In this paper,we propose a new method to synthesize emotional speech in which the latent expressions of emotions are learned from a small data set of professional actors through a Flow-tron model.In addition,we provide a new method to build a speech corpus that is scalable and whose quality is easy to control.Next,to produce a high-quality speech synthesis model,we used this data set to train the Tacotron 2 model.We used it as a pre-trained model to train the Flowtron model.We applied this method to synthesize Vietnamese speech with sadness and happiness.Mean opi-nion score(MOS)assessment results show that MOS is 3.61 for sadness and 3.95 for happiness.In conclusion,the proposed method proves to be more effec-tive for a high degree of automation and fast emotional sentence generation,using a small emotional-speech data set.展开更多
Standalone systems cannot handle the giant traffic loads generated by Twitter due to memory constraints.A parallel computational environment pro-vided by Apache Hadoop can distribute and process the data over differen...Standalone systems cannot handle the giant traffic loads generated by Twitter due to memory constraints.A parallel computational environment pro-vided by Apache Hadoop can distribute and process the data over different desti-nation systems.In this paper,the Hadoop cluster with four nodes integrated with RHadoop,Flume,and Hive is created to analyze the tweets gathered from the Twitter stream.Twitter stream data is collected relevant to an event/topic like IPL-2015,cricket,Royal Challengers Bangalore,Kohli,Modi,from May 24 to 30,2016 using Flume.Hive is used as a data warehouse to store the streamed tweets.Twitter analytics like maximum number of tweets by users,the average number of followers,and maximum number of friends are obtained using Hive.The network graph is constructed with the user’s unique screen name and men-tions using‘R’.A timeline graph of individual users is generated using‘R’.Also,the proposed solution analyses the emotions of cricket fans by classifying their Twitter messages into appropriate emotional categories using the optimized sup-port vector neural network(OSVNN)classification model.To attain better classi-fication accuracy,the performance of SVNN is enhanced using a chimp optimization algorithm(ChOA).Extracting the users’emotions toward an event is beneficial for prediction,but when coupled with visualizations,it becomes more powerful.Bar-chart and wordcloud are generated to visualize the emotional analysis results.展开更多
There are a plethora of empirical pieces about employees’pro-environmental behaviors.However,the extant literature has either ignored or not fully examined various factors(e.g.,negative or positive non-green workplac...There are a plethora of empirical pieces about employees’pro-environmental behaviors.However,the extant literature has either ignored or not fully examined various factors(e.g.,negative or positive non-green workplace factors)that might affect employees’pro-environmental behaviors.Realizing these voids,the present paper proposes and tests a serial mediation model that examines the interrelationships of job insecurity,emotional exhaustion,met expectations,and proactive pro-environmental behavior.We used data gathered from hotel customer-contact employees with a time lag of one week and their direct supervisors in China.After presenting support for the psychometric properties of the measures via confirmatory analysis in LISREL 8.30,the abovementioned linkages were gauged using the PROCESS plug-in for statistical package for social sciences.The findings delineated support for the hypothesized associations.Specifically,emotional exhaustion and met expectations partly mediated the effect of job insecurity on proactive pro-environmental behavior.More importantly,emotional exhaustion and met expectations serially mediated the influence of job insecurity on proactive pro-environmental behavior.These findings have important theoretical implications as well as significant implications for diminishing job insecurity,managing emotional exhaustion,increasing met expectations,and enhancing ecofriendly behaviors.展开更多
文摘Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the interfaces of verbal and emotional communications. The progress of AI is significant on the verbal level but modest in terms of the recognition of facial emotions even if this functionality is one of the oldest in humans and is omnipresent in our daily lives. Dysfunction in the ability for facial emotional expressions is present in many brain pathologies encountered by psychiatrists, neurologists, psychotherapists, mental health professionals including social workers. It cannot be objectively verified and measured due to a lack of reliable tools that are valid and consistently sensitive. Indeed, the articles in the scientific literature dealing with Visual-Facial-Emotions-Recognition (ViFaEmRe), suffer from the absence of 1) consensual and rational tools for continuous quantified measurement, 2) operational concepts. We have invented a software that can use computer-morphing attempting to respond to these two obstacles. It is identified as the Method of Analysis and Research of the Integration of Emotions (M.A.R.I.E.). Our primary goal is to use M.A.R.I.E. to understand the physiology of ViFaEmRe in normal healthy subjects by standardizing the measurements. Then, it will allow us to focus on subjects manifesting abnormalities in this ability. Our second goal is to make our contribution to the progress of AI hoping to add the dimension of recognition of facial emotional expressions. Objective: To study: 1) categorical vs dimensional aspects of recognition of ViFaEmRe, 2) universality vs idiosyncrasy, 3) immediate vs ambivalent Emotional-Decision-Making, 4) the Emotional-Fingerprint of a face and 5) creation of population references data. Methods: M.A.R.I.E. enables the rational, quantified measurement of Emotional Visual Acuity (EVA) in an individual observer and a population aged 20 to 70 years. Meanwhile, it can measure the range and intensity of expressed emotions through three Face- Tests, quantify the performance of a sample of 204 observers with hypernormal measures of cognition, “thymia” (defined elsewhere), and low levels of anxiety, and perform analysis of the six primary emotions. Results: We have individualized the following continuous parameters: 1) “Emotional-Visual- Acuity”, 2) “Visual-Emotional-Feeling”, 3) “Emotional-Quotient”, 4) “Emotional-Decision-Making”, 5) “Emotional-Decision-Making Graph” or “Individual-Gun-Trigger”, 6) “Emotional-Fingerprint” or “Key-graph”, 7) “Emotional-Fingerprint-Graph”, 8) detecting “misunderstanding” and 9) detecting “error”. This allowed us a taxonomy with coding of the face-emotion pair. Each face has specific measurements and graphics. The EVA improves from ages of 20 to 55 years, then decreases. It does not depend on the sex of the observer, nor the face studied. In addition, 1% of people endowed with normal intelligence do not recognize emotions. The categorical dimension is a variable for everyone. The range and intensity of ViFaEmRe is idiosyncratic and not universally uniform. The recognition of emotions is purely categorical for a single individual. It is dimensional for a population sample. Conclusions: Firstly, M.A.R.I.E. has made possible to bring out new concepts and new continuous measurements variables. The comparison between healthy and abnormal individuals makes it possible to take into consideration the significance of this line of study. From now on, these new functional parameters will allow us to identify and name “emotional” disorders or illnesses which can give additional dimension to behavioral disorders in all pathologies that affect the brain. Secondly, the ViFaEmRe is idiosyncratic, categorical, and a function of the identity of the observer and of the observed face. These findings stack up against Artificial Intelligence, which cannot have a globalist or regionalist algorithm that can be programmed into a robot, nor can AI compete with human abilities and judgment in this domain. *Here “Emotional disorders” refers to disorders of emotional expressions and recognition.
文摘Context: The advent of Artificial Intelligence (AI) requires modeling prior to its implementation in algorithms for most human skills. This observation requires us to have a detailed and precise understanding of the interfaces of verbal and emotional communications. The progress of AI is significant on the verbal level but modest in terms of the recognition of facial emotions even if this functionality is one of the oldest in humans and is omnipresent in our daily lives. Dysfunction in the ability for facial emotional expressions is present in many brain pathologies encountered by psychiatrists, neurologists, psychotherapists, mental health professionals including social workers. It cannot be objectively verified and measured due to a lack of reliable tools that are valid and consistently sensitive. Indeed, the articles in the scientific literature dealing with Visual-Facial-Emotions-Recognition (ViFaEmRe), suffer from the absence of 1) consensual and rational tools for continuous quantified measurement, 2) operational concepts. We have invented a software that can use computer-morphing attempting to respond to these two obstacles. It is identified as the Method of Analysis and Research of the Integration of Emotions (M.A.R.I.E.). Our primary goal is to use M.A.R.I.E. to understand the physiology of ViFaEmRe in normal healthy subjects by standardizing the measurements. Then, it will allow us to focus on subjects manifesting abnormalities in this ability. Our second goal is to make our contribution to the progress of AI hoping to add the dimension of recognition of facial emotional expressions. Objective: To study: 1) categorical vs dimensional aspects of recognition of ViFaEmRe, 2) universality vs idiosyncrasy, 3) immediate vs ambivalent Emotional-Decision-Making, 4) the Emotional-Fingerprint of a face and 5) creation of population references data. Methods: With M.A.R.I.E. enable a rational quantified measurement of Emotional-Visual-Acuity (EVA) of 1) a) an individual observer, b) in a population aged 20 to 70 years old, 2) measure the range and intensity of expressed emotions by 3 Face-Tests, 3) quantify the performance of a sample of 204 observers with hyper normal measures of cognition, “thymia,” (ibid. defined elsewhere) and low levels of anxiety 4) analysis of the 6 primary emotions. Results: We have individualized the following continuous parameters: 1) “Emotional-Visual-Acuity”, 2) “Visual-Emotional-Feeling”, 3) “Emotional-Quotient”, 4) “Emotional-Deci-sion-Making”, 5) “Emotional-Decision-Making Graph” or “Individual-Gun-Trigger”6) “Emotional-Fingerprint” or “Key-graph”, 7) “Emotional-Finger-print-Graph”, 8) detecting “misunderstanding” and 9) detecting “error”. This allowed us a taxonomy with coding of the face-emotion pair. Each face has specific measurements and graphics. The EVA improves from ages of 20 to 55 years, then decreases. It does not depend on the sex of the observer, nor the face studied. In addition, 1% of people endowed with normal intelligence do not recognize emotions. The categorical dimension is a variable for everyone. The range and intensity of ViFaEmRe is idiosyncratic and not universally uniform. The recognition of emotions is purely categorical for a single individual. It is dimensional for a population sample. Conclusions: Firstly, M.A.R.I.E. has made possible to bring out new concepts and new continuous measurements variables. The comparison between healthy and abnormal individuals makes it possible to take into consideration the significance of this line of study. From now on, these new functional parameters will allow us to identify and name “emotional” disorders or illnesses which can give additional dimension to behavioral disorders in all pathologies that affect the brain. Secondly, the ViFaEmRe is idiosyncratic, categorical, and a function of the identity of the observer and of the observed face. These findings stack up against Artificial Intelligence, which cannot have a globalist or regionalist algorithm that can be programmed into a robot, nor can AI compete with human abilities and judgment in this domain. *Here “Emotional disorders” refers to disorders of emotional expressions and recognition.
文摘Introduction: Emotional intelligence, or the capacity to cope one’s emotions, makes it simpler to form good connections with others and do caring duties. Nursing students can enroll a health team in a helpful and beneficial way with the use of emotional intelligence. Nurses who can identify, control, and interpret both their own emotions and those of their patients provide better patient care. The purpose of this study was to assess the emotional intelligence and to investigate the relationship and differences between emotional intelligence and demographic characteristics of nursing students. Methods: A cross-sectional study was carried out on 381 nursing students. Data collection was completed by “Schutte Self Report Emotional Intelligence Test”. Data were analyzed with the Statistical Package for Social Science. An independent t test, ANOVA, and Pearson correlation, multiple linear regression were used. Results: The results revealed that the emotional intelligence mean was 143.1 ± 21.6 (ranging from 33 to 165), which is high. Also, the analysis revealed that most of the participants 348 (91.3%) had higher emotional intelligence level. This finding suggests that nursing students are emotionally intelligent and may be able to notice, analyze, control, manage, and harness emotion in an adaptive manner. Also, academic year of nursing students was a predictor of emotional intelligence. Furthermore, there was positive relationship between the age and emotional intelligence (p < 0.05). The students’ ability to use their EI increased as they rose through the nursing grades. Conclusion: This study confirmed that the emotional intelligence score of the nursing students was high. Also, academic year of nursing students was a predictor of emotional intelligence. In addition, a positive relationship was confirmed between the emotional intelligence and age of nursing students. .
基金The authors are highly thankful to the National Social Science Foundation of China(20BXW101,18XXW015)Innovation Research Project for the Cultivation of High-Level Scientific and Technological Talents(Top-Notch Talents of theDiscipline)(ZZKY2022303)+3 种基金National Natural Science Foundation of China(Nos.62102451,62202496)Basic Frontier Innovation Project of Engineering University of People’s Armed Police(WJX202316)This work is also supported by National Natural Science Foundation of China(No.62172436)Engineering University of PAP’s Funding for Scientific Research Innovation Team,Engineering University of PAP’s Funding for Basic Scientific Research,and Engineering University of PAP’s Funding for Education and Teaching.Natural Science Foundation of Shaanxi Province(No.2023-JCYB-584).
文摘With the rapid spread of Internet information and the spread of fake news,the detection of fake news becomes more and more important.Traditional detection methods often rely on a single emotional or semantic feature to identify fake news,but these methods have limitations when dealing with news in specific domains.In order to solve the problem of weak feature correlation between data from different domains,a model for detecting fake news by integrating domain-specific emotional and semantic features is proposed.This method makes full use of the attention mechanism,grasps the correlation between different features,and effectively improves the effect of feature fusion.The algorithm first extracts the semantic features of news text through the Bi-LSTM(Bidirectional Long Short-Term Memory)layer to capture the contextual relevance of news text.Senta-BiLSTM is then used to extract emotional features and predict the probability of positive and negative emotions in the text.It then uses domain features as an enhancement feature and attention mechanism to fully capture more fine-grained emotional features associated with that domain.Finally,the fusion features are taken as the input of the fake news detection classifier,combined with the multi-task representation of information,and the MLP and Softmax functions are used for classification.The experimental results show that on the Chinese dataset Weibo21,the F1 value of this model is 0.958,4.9% higher than that of the sub-optimal model;on the English dataset FakeNewsNet,the F1 value of the detection result of this model is 0.845,1.8% higher than that of the sub-optimal model,which is advanced and feasible.
基金the Tianjin Philosophy and Social Science Planning Project“Research on Value-Added Evaluation of Career Adaptability for Engineering Students Oriented towards Outstanding Engineers”,Grant Number TJJXQN22-001.
文摘Under the effects of COVID-19 and a number of ongoing lockdown tactics,anxiety symptoms and poor sleep quality have become common mental health issues among college freshmen and are intimately related to their emotional adaptation.To explore this connection,this study gathered data from a sample of 256 freshmen enrolled in an elite university in China in September 2022.The association between sleep quality,anxiety symptoms,and emotional adaptation was clarified using correlation analysis.Additionally,the mediating function of anxiety symptoms between sleep quality and emotional adaptation was investigated using a structural equation model.The results reveal that:(1)Chinese elite university freshmen who were subjected to prolonged lockdown had poor sleep quality and mild anxiety symptoms;(2)a significant positive correlation between poor sleep quality and anxiety symptoms was identified;(3)anxiety symptoms were found to have a significant negative impact on emotional adaptation;(4)poor sleep quality had a negative impact on emotional adaptation through anxiety symptoms.This research makes a valuable contribution by offering insights into the intricate relationship between sleep quality and emotional adaptation among freshmen in elite Chinese universities during prolonged lockdown conditions,and it is beneficial for schools and educators to further improve school schedules and psychological health initiatives.
文摘Adolescents are considered one of the most vulnerable groups affected by suicide.Rapid changes in adolescents’physical and mental states,as well as in their lives,significantly and undeniably increase the risk of suicide.Psychological,social,family,individual,and environmental factors are important risk factors for suicidal behavior among teenagers and may contribute to suicide risk through various direct,indirect,or combined pathways.Social-emotional learning is considered a powerful intervention measure for addressing the crisis of adolescent suicide.When deliberately cultivated,fostered,and enhanced,selfawareness,self-management,social awareness,interpersonal skills,and responsible decision-making,as the five core competencies of social-emotional learning,can be used to effectively target various risk factors for adolescent suicide and provide necessary mental and interpersonal support.Among numerous suicide intervention methods,school-based interventions based on social-emotional competence have shown great potential in preventing and addressing suicide risk factors in adolescents.The characteristics of school-based interventions based on social-emotional competence,including their appropriateness,necessity,cost-effectiveness,comprehensiveness,and effectiveness,make these interventions an important means of addressing the crisis of adolescent suicide.To further determine the potential of school-based interventions based on social-emotional competence and better address the issue of adolescent suicide,additional financial support should be provided,the combination of socialemotional learning and other suicide prevention programs within schools should be fully leveraged,and cooperation between schools and families,society,and other environments should be maximized.These efforts should be considered future research directions.
基金supported by the National Natural Science Foundation of China(81674100).
文摘Objective:To assess emotional fluctuations,physical and mental health status,and indicators closely related to red blood cells,such as RIO kinase 3(Riok3),MAX interactor 1(Mxi1),and microRNA 191(miR191),in participants with different levels of red blood cells.Methods:Participants who underwent physical examinations at Dongfang Hospital between April and October 2019 were divided into healthy,blood deficiency,and anemia groups(30 individuals in the healthy and blood deficiency group respectively,and 13 in the anemia group).The physical and mental conditions of the participants were evaluated through questionnaires,and emotional fluctuations were assessed through an emotion-inducing experiment,in which participants watched video segments designed to induce specific emotions.Relative expression levels of miR191,Riok3,and Mxi1 from venous blood samples were also determined.Results:The main psychological factors identified in the anemia and blood deficiency groups were obsessive-compulsive symptoms,depression,anxiety,and other negative emotions.Relative gene expression levels indicated that miR191 was upregulated and Riok3 and Mxi1 were downregulated in both the blood deficiency and anemia groups.Regarding the emotional score of disgust on video stage,the main effect was significant(F=335.58,P<.001),which showed that watching the three videos caused participants to have a dominant emotion,and there is a difference on group(F=5.35,P=.01),with higher disgust scores in the anemia and blood deficiency groups.The symptoms of blood deficiency and anemia,such as weakness in limbs were significantly negatively correlated with Riok3 and Mxi1 expression(r=-0.38 and-0.31 respectively),but was significantly positively correlated with miR191 expression(r=0.29).Conclusion:We determined that a close relationship exists between red blood cell levels and emotional status.Our findings suggest that individuals with anemia and blood deficiency are more likely to experience psychological problems and negative emotions,particularly disgust.We also demonstrate that emotional regulation is related to mir191-Riok3-Mxi1 pathway activity,identifying these pathway components are potential targets for genetic therapies in combination with psychological therapy.
文摘The Japanese movie“0.5mm”connects the life clips between the nursing-care helper Sawa and several old people in the form of a road movie,highlighting many thought-provoking social problems,and revealing how the elements of emotional abuse hidden between the old people and their relatives and friends affect people’s dignity and decency,and at the same time trying to offset the persecution from the emotional abuse with the warm kindness between the elderly and the care workers.The film’s implicit description of emotional abuse and explicit display of good deeds are blended in the quiet and mysterious narrative character,achieving the effect of synchronizing the artistic narrative rhythm with the flow of life,reflecting the unique aesthetic characteristics of Japanese films.
文摘Sentiment analysis is a method to identify and understand the emotion in the text through NLP and text analysis. In the era of information technology, there is often a certain error between the comments on the movie website and the actual score of the movie, and sentiment analysis technology provides a new way to solve this problem. In this paper, Python is used to obtain the movie review data from the Douban platform, and the model is constructed and trained by using naive Bayes and Bi-LSTM. According to the index, a better Bi-LSTM model is selected to classify the emotion of users’ movie reviews, and the classification results are scored according to the classification results, and compared with the real ratings on the website. According to the error of the final comparison results, the feasibility of this technology in the scoring direction of film reviews is being verified. By applying this technology, the phenomenon of film rating distortion in the information age can be prevented and the rights and interests of film and television works can be safeguarded.
文摘This article presents an analysis of the patterns of interactions resulting from the positive and negative emotional events that occur in cities,considering them as complex systems.It explores,from the imaginaries,how certain urban objects can act as emotional agents and how these events affect the urban system as a whole.An adaptive complex systems perspective is used to analyze these patterns.The results show patterns in the processes and dynamics that occur in cities based on the objects that affect the emotions of the people who live there.These patterns depend on the characteristics of the emotional charge of urban objects,but they can be generalized in the following process:(1)immediate reaction by some individuals;(2)emotions are generated at the individual level which begins to generalize,permuting to a collective emotion;(3)a process of reflection is detonated in some individuals from the reading of collective emotions;(4)integration/significance in the community both at the individual and collective level,on the concepts,roles and/or functions that give rise to the process in the system.Therefore,it is clear that emotions play a significant role in the development of cities and these aspects should be considered in the design strategies of all kinds of projects for the city.Future extensions of this work could include a deeper analysis of specific emotional events in urban environments,as well as possible implications for urban policy and decision making.
文摘Objective:According to the World Federation of Medical Education,critical thinking should be part of the training of medical and paramedical students.Professionals can improve the quality of care of patients after surgery by having or acquiring this skill in health care.Also,Emotional intelligence is introduced as an impor tant and effective factor on the professional performance and mental health of healthcare professionals.Thus,the present study was designed and implemented to determine the relationship between emotional intelligence and critical thinking among operating room nursing students of medical sciences universities in Iran.Methods:This cross-sectional study was done on 420 operating room students in 10 top medical sciences universities of Iran in 2022.The sampling method in this research was multistage sampling.The data collection instruments included demographic characteristics,Rickett's critical thinking,and Bradberry-Greaves'emotional intelligence questionnaires.After receiving the ethics code,data collection was done for 2 months.For data analysis,descriptive and inferential analyses including independent t-tests,analysis of variance,and Pearson correlation were used.The collected data were analyzed by SPSS 18(IBM Corporation,Armonk,New York,United States).P-value<0.05 was considered significant.Results:The mean age of the students participating in this study was 23.02±3.70 years,with women constituting 67.4%of them.The results of data analysis indicated that the mean total score of critical thinking and emotional intelligence was 124.10±37.52 and 114.12±43.63,respectively.A direct significant correlation between critical thinking and emotional intelligence(r=0.459,P-value<0.001)and a significant relationship between gender and emotional intelligence(P-value=0.028)were found.Conclusions:Based on the present study results,educational managers in the Ministry of Health are suggested to consider suitable educational programs for improving critical thinking and emotional intelligence to enhance the quality of care provided by students in operating rooms.
基金supported by Nanjing Normal University’s New Liberal Arts Research and Reform Project in 2021.
文摘The adequacy of language education largely depends on the favorable and unfavorable emotions that teachers and students experience throughout the education process.Simply said,emotional factors play a key role in improving the quality of language teaching and learning.Furthermore,these emotional factors also promote the well-being of language teachers and learners and place them in a suitable mental condition.In view of the favorable impact of emotional factors on the mental health of language teachers and learners,many educational scholars around the world have studied these factors,their background,and their pedagogical consequences.Nonetheless,the majority of previous studies have employed traditional research methods in assessing these variables and their influences on language teachers’and learners’mental health.Because of the complex and dynamic quality of emotional factors,traditional research approaches often fail to evaluate these factors and their dynamic,non-linear connections with teachers’and learners’mental health and well-being.Accordingly,some novel research approaches are required to measure the dynamicity and complexity of emotional factors in language education settings.To address this call,the current state-of-the-art conceptual article seeks to provide new insights for investigating emotional factors and their potential impact on language teachers’and learners’mental states.This study also intends to offer a comprehensive list of emerging methods that take into account the complex and dynamic nature of emotional variables.Finally,the study outlines the potential implications of this review for educational researchers.
基金supported by the International Assistance Mission,Herat Office(Grant number#IDR0220526IAM).
文摘Background:The prevalence of pediatric mental illnesses has been increasing in recent years,with a great potential to impact on individual's functionality and adaptation in adulthood.Objective:This study aims to assess emotional and behavioral problems among schoolchildren in Herat City of Afghanistan.Methods:This cross-sectional study was conducted on schoolchildren(grade 5-10),between September and November 2021.Sociodemographic data was collected using a paper-based 14-item structured questionnaire.Data on emotional and behavioral problems was collected using the Strengths and Difficulties Questionnaire(SDQ)based on teachers'and children's report.Statistical analyses were performed in IBM SPSS Statistics(version 27).Results:A total of 418 students,including 190(45.5%)males and 228(54.5%)females with a mean age of 14.1±1.7(11-<18)years were included in the study.The prevalence of students*self-reported total difficulties and prosocial problem were 5.7%and 1.2%,respectively.An insignificant difference was observed between mean total difficulties scores between students'self-reported and teachers'reported SDQ.Gender,grade,concern about shortage of food,and concern about losing house were significantly predicting students'self-reported total difficulties scores.Conclusion:This is the first study to report the prevalence of emotional and behavioral problems among schoolchildren in Herat City,Afghanistan.This,together with relevant global literature,highlight the need to address pediatric mental health,and provide services aimed at preventing,and treating children with these problems around the world.
基金supported by the National Natural Science Foundation of China(No.61906185,61876053)the Natural Science Foundation of Guangdong Province of China(No.2019A1515011705 and No.2021A1515011905)+2 种基金the Youth Innovation Promotion Association of CAS China(No.2020357)the Shenzhen Basic Research Foundation(No.JCYJ20210324115614039 and No.JCYJ20200109113441941)the Shenzhen Science and Technology Innovation Program(Grant No.KQTD20190929172835662).
文摘Handling emotions in human‐computer dialogues has emerged as a challenging task which requires artificial intelligence systems to generate emotional responses by jointly perceiving the emotion involved in the input posts and incorporating it into the gener-ation of semantically coherent and emotionally reasonable responses.However,most previous works generate emotional responses solely from input posts,which do not take full advantage of the training corpus and suffer from generating generic responses.In this study,we introduce a hierarchical semantic‐emotional memory module for emotional conversation generation(called HSEMEC),which can learn abstract semantic conver-sation patterns and emotional information from the large training corpus.The learnt semantic and emotional knowledge helps to enrich the post representation and assist the emotional conversation generation.Comprehensive experiments on a large real‐world conversation corpus show that HSEMEC can outperform the strong baselines on both automatic and manual evaluation.For reproducibility,we release the code and data publicly at:https://github.com/siat‐nlp/HSEMEC‐code‐data.
文摘At present, the channels used for EEG acquisition are more than 16, which makes it difficult to wear EEG caps and has poor contact. Therefore, it brings difficulties to the collection of brain waves is not conducive to converting research into applications. It is a well worth studying work in researching how to find the key brain electrode in the existing brain wave, which will greatly reduce the number of EEG acquisition points during application, making it easier to translate the research into practical application. This paper takes emotional EEG as an example to study how to find the key brain electrode points of emotional EEG with deep learning method. Firstly, using the least square regression algorithm to calculate the characteristic coefficients of each electrode point;secondly, according to the law of the characteristic coefficient value, grouping the key EEG poles for experiment. In the grouping experiment, the Conv1d-GRU model used to train and verify the EEG data of the corresponding electrode points. Finally, from the results of various grouping experiments, it concluded that the selection method of the key EEG level points should be the electrode points with positive characteristic coefficient, and the accuracy of verification is 97.6%. With experiments, it confirmed that there are key electrode points in the detection of emotional EEG by 16-channel OpenBCI. There are only six key electrode points of emotional EEG;that is to say, the EEG data collected by only six key electrode points can identify seven kinds of emotional EEG. .
基金supported by grants from the National Social Science Foundation of China(19BGL230)the Key Project of Social Science Planning in Jiangxi Province(23JY01).
文摘The relapse of methamphetamine (meth) is associated with decision-making dysfunction. The present study aims to investigate theimpact of different emotions on the decision-making behavior of meth users. We used 2 (gender: male, female) × 3 (emotion:positive, negative, neutral) × 5 (block: 1, 2, 3, 4, 5) mixed experiment design. The study involved 168 meth users who weredivided into three groups: positive emotion, negative emotion and neutral emotion group, and tested by the emotional IowaGambling Task (IGT). The IGT performance of male users exhibited a decreasing trend from Block 1 to Block 3. Female methusers in positive emotion had the best performance in IGT than females in the other two groups. In positive emotion, the IGTperformance of female meth users was significantly better than that of men. Female meth users in positive emotion had betterdecision-making than those in negative or neutral emotion. Female meth users in positive emotion had better decision-makingperformance than males in positive emotion. In negative and neutral emotions, there was no significant gender difference indecision-making.
基金supported by the National Research Foundation of Korea(NRF)Grant Funded by the Korea Government(MSIT)(NRF-2020R1A2B5B0100208).
文摘This study aimed to explore citizens’emotional responses and issues of interest in the context of the coronavirus disease 2019(COVID-19)pandemic.The dataset comprised 65,313 tweets with the location marked as New York State.The data collection period was four days of tweets when New York City imposed a lockdown order due to an increase in confirmed cases.Data analysis was performed using R Studio.The emotional responses in tweets were analyzed using the Bing and NRC(National Research Council Canada)dictionaries.The tweets’central issue was identified by Text Network Analysis.When tweets were classified as either positive or negative,the negative sentiment was higher.Using the NRC dictionary,eight emotional classifications were devised:“trust,”“fear,”“anticipation,”“sadness,”“anger,”“joy,”“surprise,”and“disgust.”These results indicated that citizens showed negative and trusting emotional reactions in the early days of the pandemic.Moreover,citizens showed a strong interest in overcoming and coping with other people such as social solidarity.Citizens were concerned about the confirmation of COVID-19 infection status and death.Efforts should be made to ensure citizens’psychological stability by promptly informing them of the status of infectious disease management and the route of infection.
基金funded by the Hanoi University of Science and Technology(HUST)under grant number T2018-PC-210.
文摘In recent years,speech synthesis systems have allowed for the produc-tion of very high-quality voices.Therefore,research in this domain is now turning to the problem of integrating emotions into speech.However,the method of con-structing a speech synthesizer for each emotion has some limitations.First,this method often requires an emotional-speech data set with many sentences.Such data sets are very time-intensive and labor-intensive to complete.Second,training each of these models requires computers with large computational capabilities and a lot of effort and time for model tuning.In addition,each model for each emotion failed to take advantage of data sets of other emotions.In this paper,we propose a new method to synthesize emotional speech in which the latent expressions of emotions are learned from a small data set of professional actors through a Flow-tron model.In addition,we provide a new method to build a speech corpus that is scalable and whose quality is easy to control.Next,to produce a high-quality speech synthesis model,we used this data set to train the Tacotron 2 model.We used it as a pre-trained model to train the Flowtron model.We applied this method to synthesize Vietnamese speech with sadness and happiness.Mean opi-nion score(MOS)assessment results show that MOS is 3.61 for sadness and 3.95 for happiness.In conclusion,the proposed method proves to be more effec-tive for a high degree of automation and fast emotional sentence generation,using a small emotional-speech data set.
文摘Standalone systems cannot handle the giant traffic loads generated by Twitter due to memory constraints.A parallel computational environment pro-vided by Apache Hadoop can distribute and process the data over different desti-nation systems.In this paper,the Hadoop cluster with four nodes integrated with RHadoop,Flume,and Hive is created to analyze the tweets gathered from the Twitter stream.Twitter stream data is collected relevant to an event/topic like IPL-2015,cricket,Royal Challengers Bangalore,Kohli,Modi,from May 24 to 30,2016 using Flume.Hive is used as a data warehouse to store the streamed tweets.Twitter analytics like maximum number of tweets by users,the average number of followers,and maximum number of friends are obtained using Hive.The network graph is constructed with the user’s unique screen name and men-tions using‘R’.A timeline graph of individual users is generated using‘R’.Also,the proposed solution analyses the emotions of cricket fans by classifying their Twitter messages into appropriate emotional categories using the optimized sup-port vector neural network(OSVNN)classification model.To attain better classi-fication accuracy,the performance of SVNN is enhanced using a chimp optimization algorithm(ChOA).Extracting the users’emotions toward an event is beneficial for prediction,but when coupled with visualizations,it becomes more powerful.Bar-chart and wordcloud are generated to visualize the emotional analysis results.
文摘There are a plethora of empirical pieces about employees’pro-environmental behaviors.However,the extant literature has either ignored or not fully examined various factors(e.g.,negative or positive non-green workplace factors)that might affect employees’pro-environmental behaviors.Realizing these voids,the present paper proposes and tests a serial mediation model that examines the interrelationships of job insecurity,emotional exhaustion,met expectations,and proactive pro-environmental behavior.We used data gathered from hotel customer-contact employees with a time lag of one week and their direct supervisors in China.After presenting support for the psychometric properties of the measures via confirmatory analysis in LISREL 8.30,the abovementioned linkages were gauged using the PROCESS plug-in for statistical package for social sciences.The findings delineated support for the hypothesized associations.Specifically,emotional exhaustion and met expectations partly mediated the effect of job insecurity on proactive pro-environmental behavior.More importantly,emotional exhaustion and met expectations serially mediated the influence of job insecurity on proactive pro-environmental behavior.These findings have important theoretical implications as well as significant implications for diminishing job insecurity,managing emotional exhaustion,increasing met expectations,and enhancing ecofriendly behaviors.