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
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
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
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
In this paper,we study the asymptotic behavior of a class of inverse quotient curvature flow in the anti-de Sitter-Schwarzschild manifold.We prove that under suitable convex conditions for the initial hypersurface,one...In this paper,we study the asymptotic behavior of a class of inverse quotient curvature flow in the anti-de Sitter-Schwarzschild manifold.We prove that under suitable convex conditions for the initial hypersurface,one can get the long-time existence for the inverse curvature flow.Moreover,we also get that the principal curvatures of the evolving hypersurface converge to 1 when t→+∞.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
In the face offierce competition in the social environment,mental health problems gradually get the attention of the public,in order to achieve accurate mental health data analysis,the construction of music education ...In the face offierce competition in the social environment,mental health problems gradually get the attention of the public,in order to achieve accurate mental health data analysis,the construction of music education is based on emotional tendency analysis of psychological adjustment function model.Design emotional tendency analysis of music education psychological adjustment function architecture,music teaching goal as psychological adjust-ment function architecture building orientation,music teaching content as a foundation for psychological adjust-ment function architecture and music teaching process as a psychological adjustment function architecture building,music teaching evaluation as the key of building key regulating function architecture,Establish a core literacy oriented evaluation system.Different evaluation methods were used to obtain the evaluation results.Four levels of psychological adjustment function model of music education are designed,and the psychological adjust-ment function of music education is put forward,thus completing the construction of psychological adjustment function model of music education.The experimental results show that the absolute value of the data acquisition error of the designed model is minimum,which is not more than 0.2.It is less affected by a bad coefficient and has good performance.It can quickly converge to the best state in the actual prediction process and has a strong con-vergence ability.展开更多
Background:During the early stages of the COVID-19 pandemic in China,social interactions shifted to online spaces due to lockdowns and social distancing measures.As a result,the impact of online social networking on u...Background:During the early stages of the COVID-19 pandemic in China,social interactions shifted to online spaces due to lockdowns and social distancing measures.As a result,the impact of online social networking on users’emotional status has become stronger than ever.This study examines the association between online social networking and Internet users’emotional status and how offline reality affects this relationship.Methods:The study utilizes cross-sectional online survey data(n=3004)and Baidu Migration big data from the first 3 months of the pandemic.Two dimensions of online networking are measured:social support and information sources.Results:First,individuals’online social support(β=0.16,p<0.05)and information sources(β=0.08,p<0.01)are both positively associated to their emotional status during the epidemic.Second,these positive associations are moderated by social status and provincial pandemic control interventions.With regards to the moderation effect of social status,the constructive impact of information sources on emotional well-being is more pronounced among individuals from vulnerable groups compared to those who are not.With regard to the moderation effect of provincial interventions,online social support has the potential to alleviate the adverse repercussions of high rates of confirmed COVID-19 cases and strict lockdown measures while simultaneously augmenting the favorable effects of recovery.Conclusion:The various dimensions of social networking exert distinct effects on emotional status through diverse mechanisms,all of which must be taken into account when designing and adapting pandemic-control interventions.展开更多
Speech disorders are a common type of childhood disease.Through experimental intervention,this study aims to improve the vocabulary comprehension levels and language ability of children with speech disorders through t...Speech disorders are a common type of childhood disease.Through experimental intervention,this study aims to improve the vocabulary comprehension levels and language ability of children with speech disorders through the language cognition and emotional speech community method.We also conduct a statistical analysis of the inter-ventional effect.Among children with speech disorders in Dongguan City,224 were selected and grouped accord-ing to their receptive language ability and IQ.The 112 children in the experimental group(EG)received speech therapy with language cognitive and emotional speech community,while the 112 children in the control group(CG)only received conventional treatment.After six months of experimental intervention,the Peabody Picture Vocabulary Test-Revised(PPVT-R)was used to test the language ability of the two groups.Overall,we employed a quantitative approach to obtain numerical values,examine the variables identified,and test hypotheses.Further-more,we used descriptive statistics to explore the research questions related to the study and statistically describe the overall distribution of the demographic variables.The statistical t-test was used to analyze the data.The data shows that after intervention through language cognition and emotional speech community therapy,the PPVT-R score of the EG was significantly higher than that of the CG.Therefore,we conclude that there is a significant difference in language ability between the EG and CG after the therapy.Although both groups improved,the post-therapy language level of EG is significantly higher than that of CG.The total effective rate in EG is higher than CG,and the difference is statistically significant(p<0.05).Therefore,we conclude that the language cogni-tion and emotional speech community method is effective as an interventional treatment of children’s speech dis-orders and that it is more effective than traditional treatment methods.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: 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 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 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 Postdoctoral Fund of Zhejiang Province,China (ZJ2022004).
文摘In this paper,we study the asymptotic behavior of a class of inverse quotient curvature flow in the anti-de Sitter-Schwarzschild manifold.We prove that under suitable convex conditions for the initial hypersurface,one can get the long-time existence for the inverse curvature flow.Moreover,we also get that the principal curvatures of the evolving hypersurface converge to 1 when t→+∞.
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.
基金supported by Shandong Provincial Social Science Planning Research Project“Research on Inheritance and Innovation of Shandong Wooden Clappers Culture”(20CCXJ26).
文摘In the face offierce competition in the social environment,mental health problems gradually get the attention of the public,in order to achieve accurate mental health data analysis,the construction of music education is based on emotional tendency analysis of psychological adjustment function model.Design emotional tendency analysis of music education psychological adjustment function architecture,music teaching goal as psychological adjust-ment function architecture building orientation,music teaching content as a foundation for psychological adjust-ment function architecture and music teaching process as a psychological adjustment function architecture building,music teaching evaluation as the key of building key regulating function architecture,Establish a core literacy oriented evaluation system.Different evaluation methods were used to obtain the evaluation results.Four levels of psychological adjustment function model of music education are designed,and the psychological adjust-ment function of music education is put forward,thus completing the construction of psychological adjustment function model of music education.The experimental results show that the absolute value of the data acquisition error of the designed model is minimum,which is not more than 0.2.It is less affected by a bad coefficient and has good performance.It can quickly converge to the best state in the actual prediction process and has a strong con-vergence ability.
基金This research was funded by“the Fundamental Research Funds for the Central Universities,Grant Number XJSJ23180”,https://www.xidian.edu.cn/index.htmand“Shaanxi Province Philosophy and Social Science Research Project,Grant Number 2023QN0046”,http://www.sxsskw.org.cn/.
文摘Background:During the early stages of the COVID-19 pandemic in China,social interactions shifted to online spaces due to lockdowns and social distancing measures.As a result,the impact of online social networking on users’emotional status has become stronger than ever.This study examines the association between online social networking and Internet users’emotional status and how offline reality affects this relationship.Methods:The study utilizes cross-sectional online survey data(n=3004)and Baidu Migration big data from the first 3 months of the pandemic.Two dimensions of online networking are measured:social support and information sources.Results:First,individuals’online social support(β=0.16,p<0.05)and information sources(β=0.08,p<0.01)are both positively associated to their emotional status during the epidemic.Second,these positive associations are moderated by social status and provincial pandemic control interventions.With regards to the moderation effect of social status,the constructive impact of information sources on emotional well-being is more pronounced among individuals from vulnerable groups compared to those who are not.With regard to the moderation effect of provincial interventions,online social support has the potential to alleviate the adverse repercussions of high rates of confirmed COVID-19 cases and strict lockdown measures while simultaneously augmenting the favorable effects of recovery.Conclusion:The various dimensions of social networking exert distinct effects on emotional status through diverse mechanisms,all of which must be taken into account when designing and adapting pandemic-control interventions.
文摘Speech disorders are a common type of childhood disease.Through experimental intervention,this study aims to improve the vocabulary comprehension levels and language ability of children with speech disorders through the language cognition and emotional speech community method.We also conduct a statistical analysis of the inter-ventional effect.Among children with speech disorders in Dongguan City,224 were selected and grouped accord-ing to their receptive language ability and IQ.The 112 children in the experimental group(EG)received speech therapy with language cognitive and emotional speech community,while the 112 children in the control group(CG)only received conventional treatment.After six months of experimental intervention,the Peabody Picture Vocabulary Test-Revised(PPVT-R)was used to test the language ability of the two groups.Overall,we employed a quantitative approach to obtain numerical values,examine the variables identified,and test hypotheses.Further-more,we used descriptive statistics to explore the research questions related to the study and statistically describe the overall distribution of the demographic variables.The statistical t-test was used to analyze the data.The data shows that after intervention through language cognition and emotional speech community therapy,the PPVT-R score of the EG was significantly higher than that of the CG.Therefore,we conclude that there is a significant difference in language ability between the EG and CG after the therapy.Although both groups improved,the post-therapy language level of EG is significantly higher than that of CG.The total effective rate in EG is higher than CG,and the difference is statistically significant(p<0.05).Therefore,we conclude that the language cogni-tion and emotional speech community method is effective as an interventional treatment of children’s speech dis-orders and that it is more effective than traditional treatment methods.
