Research on the Evolution Structure of Fragment Disordering Public Opinion in College Students’ Network Circle Group

Clarifying the evolution structure of public opinion induced and spread by fragmentation in college students’ network circle group is the key to understanding college students’ online social psychological demands, grasping the development trend of public opinion, and designing targeted public opinion governance strategies. On the basis of identifying the key variables in the process of public opinion communication, DEMATEL-ISM model is used to explore the attribute positioning, relative importance level and hierarchical association mechanism of ante-variable and result variable, and then the governance strategies for fragment disordering public opinion in network circle groups of college students is designed. According to the study, exogenous stimuli, the uniqueness of discourse system, the number of spectacular texts and micro-narrative mode constituted the deep-rooted causes of fragment disordering public opinion. The unique situational and information attributes of network circle groups often become an important “booster” of disordered public opinion. The topic deviation is often accompanied with the formation of negative emotions. The corresponding public opinion governance strategies are sought from the aspects of shaping the network environment, adjusting the operation mechanism of the network circle group, improving the efficiency of using fragmented information, and optimizing the human resources of colleges.

The Impact of Social Media Networks Websites Usage on Students’ Academic Performance

Social Networks Sites (SNSs) are dominating all internet users’ generations, especially the students’ communities. Consequently, academic institutions are increasingly using SNSs which leads to emerge a crucial question regarding the impact of SNSs on students’ academic performance. This research investigates how and to what degree the use of SNSs affects the students’ academic performance. The current research’s data was conducted by using drop and collect surveys on a large population from the University of Jordan. 366 undergraduate students answered the survey from different faculties at the university. In order to study the impact of SNSs on student’s academic performance, the research hypotheses was tested by using descriptive analysis, T-test and ANOVA. Research results showed that there was a significant impact of SNS on the student’s academic performance. Also, there was a significant impact of SNS use per week on the student’s academic performance, whereas no differences found in the impact of use of SNSs on academic performance due to age, academic achievement, and use per day to most used sites. The findings of this research can be used to suggest future strategies in enhancing student’s awareness in efficient time management and better multitasking that can lead to improving study activities and academic achievements.

Tracking direct and indirect impact on technology and policy of transformative research via ego citation network

Purpose:The disseminating of academic knowledge to nonacademic audiences partly relies on the transition of subsequent citing papers.This study aims to investigate direct and indirect impact on technology and policy originating from transformative research based on ego citation network.Design/methodology/approach:Key Nobel Prize-winning publications(NPs)in fields of gene engineering and astrophysics are regarded as a proxy for transformative research.In this contribution,we introduce a network-structural indicator of citing patents to measure technological impact of a target article and use policy citations as a preliminary tool for policy impact.Findings:The results show that the impact on technology and policy of NPs are higher than that of their subsequent citation generations in gene engineering but not in astrophysics.Research limitations:The selection of Nobel Prizes is not balanced and the database used in this study,Dimensions,suffers from incompleteness and inaccuracy of citation links.Practical implications:Our findings provide useful clues to better understand the characteristics of transformative research in technological and policy impact.Originality/value:This study proposes a new framework to explore the direct and indirect impact on technology and policy originating from transformative research.

Comparative Analysis of Machine Learning Models for Customer Churn Prediction in the U.S. Banking and Financial Services: Economic Impact and Industry-Specific Insights

Customer churn poses a significant challenge for the banking and finance industry in the United States, directly affecting profitability and market share. This study conducts a comprehensive comparative analysis of machine learning models for customer churn prediction, focusing on the U.S. context. The research evaluates the performance of logistic regression, random forest, and neural networks using industry-specific datasets, considering the economic impact and practical implications of the findings. The exploratory data analysis reveals unique patterns and trends in the U.S. banking and finance industry, such as the age distribution of customers and the prevalence of dormant accounts. The study incorporates macroeconomic factors to capture the potential influence of external conditions on customer churn behavior. The findings highlight the importance of leveraging advanced machine learning techniques and comprehensive customer data to develop effective churn prevention strategies in the U.S. context. By accurately predicting customer churn, financial institutions can proactively identify at-risk customers, implement targeted retention strategies, and optimize resource allocation. The study discusses the limitations and potential future improvements, serving as a roadmap for researchers and practitioners to further advance the field of customer churn prediction in the evolving landscape of the U.S. banking and finance industry.

Data for critical infrastructure network modelling of natural hazard impacts:Needs and influence on model characteristics

Natural hazards impact interdependent infrastructure networks that keep modern society functional.While a va-riety of modelling approaches are available to represent critical infrastructure networks(CINs)on different scales and analyse the impacts of natural hazards,a recurring challenge for all modelling approaches is the availability and accessibility of sufficiently high-quality input and validation data.The resulting data gaps often require mod-ellers to assume specific technical parameters,functional relationships,and system behaviours.In other cases,expert knowledge from one sector is extrapolated to other sectoral structures or even cross-sectorally applied to fill data gaps.The uncertainties introduced by these assumptions and extrapolations and their influence on the quality of modelling outcomes are often poorly understood and difficult to capture,thereby eroding the reliability of these models to guide resilience enhancements.Additionally,ways of overcoming the data avail-ability challenges in CIN modelling,with respect to each modelling purpose,remain an open question.To address these challenges,a generic modelling workflow is derived from existing modelling approaches to examine model definition and validations,as well as the six CIN modelling stages,including mapping of infrastructure assets,quantification of dependencies,assessment of natural hazard impacts,response&recovery,quantification of CI services,and adaptation measures.The data requirements of each stage were systematically defined,and the literature on potential sources was reviewed to enhance data collection and raise awareness of potential pitfalls.The application of the derived workflow funnels into a framework to assess data availability challenges.This is shown through three case studies,taking into account their different modelling purposes:hazard hotspot assess-ments,hazard risk management,and sectoral adaptation.Based on the three model purpose types provided,a framework is suggested to explore the implications of data scarcity for certain data types,as well as their reasons and consequences for CIN model reliability.Finally,a discussion on overcoming the challenges of data scarcity is presented.

Prediction of the Charpy V-notch impact energy of low carbon steel using a shallow neural network and deep learning

The impact energy prediction model of low carbon steel was investigated based on industrial data. A three-layer neural network, extreme learning machine, and deep neural network were compared with different activation functions, structure parameters, and training functions. Bayesian optimization was used to determine the optimal hyper-parameters of the deep neural network. The model with the best performance was applied to investigate the importance of process parameter variables on the impact energy of low carbon steel. The results show that the deep neural network obtains better prediction results than those of a shallow neural network because of the multiple hidden layers improving the learning ability of the model. Among the models, the Bayesian optimization deep neural network achieves the highest correlation coefficient of 0.9536, the lowest mean absolute relative error of 0.0843, and the lowest root mean square error of 17.34 J for predicting the impact energy of low carbon steel. Among the variables, the main factors affecting the impact energy of low carbon steel with a final thickness of7.5 mm are the thickness of the original slab, the thickness of intermediate slab, and the rough rolling exit temperature from the specific hot rolling production line.

Impact of clinical posting in psychiatry on the attitudes towards psychiatry and mental illness in undergraduate medical students

Background A major public health problem around the world today is mental illness. Although there are several studies on the topic, it is rarely conducted in the context like the current study. Aims This study aims to find out the attitudes of medical students towards psychiatry and mental illness as a clinical medicine major and evaluate the effects of clinical posting on their attitudes towards psychiatry and mental illness. Methods This is a longitudinal study of 6 months* duration conducted with students in their fifth semester of medical college in Western India during the academic year of 2016-2017. The participants were assessed by pro forma containing demographic details, and the questionnaires—Attitude Towards Psychiatry-30 items (ATP-30) scale and Mental Illness Clinician's Attitude (MICA) scale, which were presented to the students at the beginning and at the end of their psychiatry clinical posting. The statistical analysis was done with GraphPad, InStat V.3.06. A p value <0.05 was considered statistically significant. Results The students' attitudes towards psychiatry were neutral at the beginning of the psychiatry clinical posting, and improved significantly at the end of the posting on both scales: ATP-30 (p=0.002) and MICA (p=0.048). The students became more positive towards the subject and mental illness in general, negative attitudes also reduced but the change was not statistically significant (p=0.058). We found significant improvement in students' thinking towards being a psychiatrist in the future post-term (p=0.0002). The changes in attitude in terms of gender were equivocal, with an increase in positive attitude and reduction in negative attitude post-term in both sexes. Conclusion Psychiatry clinical posting aids in cultivating positive attitude towards psychiatry and mental illness and reduces the stigma associated with the students of this major and psychiatric patients.

Associated Factors and Impacts of Social Phobia on Academic Performance among Students from the University of Parakou (UP)

Background: Social phobia disrupts students in their academic career. The aim of this research work was to study this anxious disorder impact on the academic performance among students from the University of Parakou (UP). Study methods: It was a descriptive cross-sectional study with prospective data collection among 363 students recruited through systematic random sampling from April to June 2015 at the campus of the UP. A questionnaire including the Mini International Neuropsychiatric Interview (MINI), the Liebowitz social anxiety intensity evaluation scale and the ASSIST was used for data collection in compliance with recommended ethical principles. Results and Conclusion Social phobia prevalence among students from the campus of University of Parakou was 11. 6% [CI95% = 10. 9 - 21. 2]. Its intensity was moderate (66.7%), medium (23.4%), severe (7.1%) and very severe (4.8%) only among female students. Moreover, gender, rural or urban living environment and field of study were statistically associated with this social phobia which reduced academic performance by 57.1%, among the studied population. However, 42.9% were not influenced in any way. Addiction to alcoholic beverages (23.8%) and anxiolytics (9.5%) were used to overcome the disorder. Although the risk of dependency to these substances was low, adverse effects on their health and socio-professional future were to be taken seriously.

The Impact of Directly Observed Therapy on Preventive Treatment for Latent Tuberculosis Infection among Students in Dalian, China

Preventive treatment has an essential effect on latent tuberculosis infection(LTBI)[purified protein derivative(PPD)induration≥15 mm].Between2010 and 2013,there were 6 tuberculosis(TB)outbreaks in the universities in Dalian,China.So far,in Dalian,the directly observed therapy(DOT)and

An Analysis of College Students＇ Autonomous English Learning Ability under the Network Environment

Referring to the questionnaire survey and literature materials, this paper describes the current situation of college students＇ insufficient autonomous English learning ability and thefactors that influence this ability; it also suggests feasible suggestions under the network environment. Students （N= 178） from different grades, majors, universities and areas responded to a questionnaire survey, and the collected data were analyzed. The results indicate that complex external environment and insufficient internal subject cognition influence college students＇ autonomous English learning ability. Finally, this paper suggests that a good network environment is necessary for autonomous learners to enhance insufficient autonomous English learning ability and interaction, continuous thinking and cultural introduction are also indispensable to develop this ability.

Research on the New Mode of college students’mental Health Education under the Network environment

With the rapid development of science andtechnology, internet technology has become matureincreasingly. It has become an important part ofpeople’s work, life and study. At the same time, thenetwork environment has also brought an impact onthe physical and mental health of college students.Nowadays, the quality and level of college students’mental health education has become society topics.College psychological health education work shouldkeep pace with the network environment developmentand the students’ physical and mental development.It is the effective innovation of psychological healtheducation work. The new model of college students’psychological health education development isconstructed. It is improve the level of students’ physicaland mental health development, and the psychologicalquality of college students is strengthen. Based onthis, this paper analyzes the existing problems on thecollege students’ mental health development. Under thenetwork environment, it proposes an effective method toconstruct a new mode of college students’ mental healtheducation .

A quantitative BP neural network analysis of the relationships between ΣREE content and impact factors in the Beibu Gulf

The distribution characteristics of rare earth elements （REE） in bottomsediments are influenced by many factors. Hence, conducting a quantitative analysis isdifficult. A qualitative analysis of the relationships between ΣREE content andprovenance, hydrodynamics, grain size and mineral distribution in the Beibu Gulf showsthat terrestrial rocks control the ΣREE composition. Both weaker hydrodynamics andfiner grain size lead to a higher ΣREE content. Relative curves revealing therelationships between individual impact factors and ΣREE content were obtained fromthe combination of qualitative and quantitative analyses of the BP neural network,which trained the position of samples, gravel content, sand content, silt content, claycontent and clay mineral content. The results are consistent with those of thequantitative analysis. The self-learning algorithm is automatically determined andcalculated quantitatively. The impact of each factor on REEs and how each factorcontrols the ΣREE distribution is identified. Thus, environmental changes and thegeological evolution of the region can be inferred based on curve variation and the geological evolution of the region can be inferred based on curve variation and theactual situation. This method also provides useful theoretical guidance for the analysisof REE enrichment and dispersion.

A Study of Chinese College Students’ View on the Latest Network Catchwords

随着网络技术的迅猛发展,人们对网络的研究也风生水起。互联网是一个虚拟社区,它和现实社会有着直接的割不断的联系。在虚拟社区中,人与人交往离不开网络语言。本文主要研究中国大学生对网络流行语的态度并总结了网络语言的发展前景。

An Empirical Research on the Behavior and Influencing Factors of College Students Network Course Learning

＂Using technology to support learning＂ gradually becomes the main trend of technology application and technology-curriculum integration at home and abroad. The empirical research based on newly-established universities shows that college students＇ usage intention on network course and study behavior is not real. Study behavior of network course is passive and outside stimulation. They are more concerned about the usefulness and relative advantages of the learning mode in the network course learning; however, learning environment of the network course at present still is given on material and tool level. The institutions should, in compliance with the trend of higher education development in the world, actively build learning environment to meet the learning needs of students in the information age, deepen the reform of information technology application and curriculum based on the learner-centered concept, focus on the training of initiative learning of college students, put community impact into full play to promote the integration of the superiority of the material platform and initiative, and finally improve the efficiency and quality of teaching and education.

An Analysis of Fragmented Reading and Its Social Impact on College Students in the Era of New Media

In the era of new media,people’s lifestyle,education and the like are inseparable from the Internet.At the same time,due to the emergence of smart devices such as mobile phones and tablet computers,people’s reading habits have changed.Fragmented reading has become an important form of reading for college students.College students themselves have the strong ability to accept change,so fragmented reading has gradually become an important form of student learning.This paper mainly analyses fragmented reading by college students and its impact on society in the era of new media.

Study on the Promotion Strategy of College Students’ Reading and Writing Ability Under the Micro Network Environment

Network media has become more and more involved in our daily life. It has become a part of modern life that cannot be stopped or rejected. Then, how to correctly face the changes in the Internet era is placed in front of everyone. Students need to “learn how to use the media to get their all-round development, effectively prevent the foreign information pollution, and actively guide students to a truly rational attitude for WeChat, blog and micro-blog”. It is a kind of media literacy being confronted with the network’s ability to consciously resist the harmful information, but also to benefit their own development and firmly grasp the information, so as to make full use of the convenience of network self promotion. “Screen reading” network plays an important role in college students’ life, and the fragmentation, the text features of the writing ability of college students also have a strong impact; this paper focuses on the influence of college students in the network reading and writing patterns on their writing ability and influence. From the perspective of media literacy education for college students, writing ability and reading ability provide a feasible way.

Educational, psychosocial, and clinical impact of SARS-CoV-2 (COVID-19) pandemic on medical students in the United States

BACKGROUND The coronavirus disease 2019(COVID-19)pandemic altered education,exams,and residency applications for United States medical students.AIM To determine the specific impact of the pandemic on US medical students and its correlation to their anxiety levels.METHODS An 81-question survey was distributed via email,Facebook and social media groups using REDCapTM.To investigate risk factors associated with elevated anxiety level,we dichotomized the 1-10 anxiety score into low(≤5)and high(≥6).This cut point represents the 25th percentile.There were 90(29%)shown as low anxiety and 219(71%)as high anxiety.For descriptive analyses,we used contingency tables by anxiety categories for categorical measurements with chi square test,or mean±STD for continuous measurements followed by t-test or Wilcoxson rank sum test depending on data normality.Least Absolute Shrinkage and Selection Operator was used to select important predictors for the final multivariate model.Hierarchical Poisson regression model was used to fit the final multivariate model by considering the nested data structure of students clustered within State.RESULTS 397 medical students from 29 states were analyzed.Approximately half of respondents reported feeling depressed since the pandemic onset.62%of participants rated 7 or higher out of 10 when asked about anxiety levels.Stressors correlated with higher anxiety scores included“concern about being unable to complete exams or rotations if contracting COVID-19”(RR 1.34;95%CI:1.05-1.72,P=0.02)and the use of mental health services such as a“psychiatrist”(RR 1.18;95%CI:1.01-1.3,P=0.04).However,those students living in cities that limited restaurant operations to exclusively takeout or delivery as the only measure of implementing social distancing(RR 0.64;95%CI:0.49-0.82,P<0.01)and those who selected“does not apply”for financial assistance available if needed(RR 0.83;95%CI:0.66-0.98,P=0.03)were less likely to have a high anxiety.CONCLUSION COVID-19 significantly impacted medical students in numerous ways.Medical student education and clinical readiness were reduced,and anxiety levels increased.It is vital that medical students receive support as they become physicians.Further research should be conducted on training medical students in telemedicine to better prepare students in the future for pandemic planning and virtual healthcare.

Research on Ideological and Political Education of Higher Vocational College Students' Network Groups in the New Era

With the rapid development of modern information technology, Internet technology has become a major driver of social and economic development. It also has a great influence on higher vocational school education, especially the ideological and political education of young students. The network has brought new changes to the students' cognition, thoughts and conduct, learning methods, and physical and mental development. At the same time, it has a negative effect on students' own development and student group development. In order to better serve the ideological and political education of higher vocational students and improve the pragmaticality and effectiveness of the ideological and political work, we have actively enriched the network carriers, took the initiative to fight for Internet public opinion, actively built a network response mechanism, and focus on the training of network leaders and other measures to strengthen the online community ideological and political education.

Research on the oral teaching of university network English in promoting students＇ creative thinking abilities

Many authors probe into the models of promoting college students＇ creative thinking abilities from their own perspectives, among which there are innovative works. However, whether we can improve the above abilities of college students in the oral teaching of university network English still remains blank in the study. Based on the deconstruction of the creative thinking abilities of the students, we should build the components of this capacity from four aspects.

The Development and Operation Mechanism of the Colleges’E-class Network Ideological and Political Education Platform——Based on post-95 college students’social behavior characteristics

Based on the investigation and analysis of the social behavior characteristics of post-95undergraduates, this paper puts forward the principle of sharing and building e-class platform and analyzes thedevelopment of the functions of the four platforms such as the teacher-student service system, instant interactionsystem, SNS community system and vertical segmental pushing system and the realization of the function of modularoperation. Finally, in order to ensure the stable operation of the E-class platform, four measures are put forward suchas the systematic construction of the system, the innovation of team work, the assessment of key performances and thecomprehensive guarantee, thus providing an external guarantee for the stable operation of the E-class platform.