Social Media-Based Surveillance Systems for Health Informatics Using Machine and Deep Learning Techniques:A Comprehensive Review and Open Challenges

Social media(SM)based surveillance systems,combined with machine learning(ML)and deep learning(DL)techniques,have shown potential for early detection of epidemic outbreaks.This review discusses the current state of SM-based surveillance methods for early epidemic outbreaks and the role of ML and DL in enhancing their performance.Since,every year,a large amount of data related to epidemic outbreaks,particularly Twitter data is generated by SM.This paper outlines the theme of SM analysis for tracking health-related issues and detecting epidemic outbreaks in SM,along with the ML and DL techniques that have been configured for the detection of epidemic outbreaks.DL has emerged as a promising ML technique that adaptsmultiple layers of representations or features of the data and yields state-of-the-art extrapolation results.In recent years,along with the success of ML and DL in many other application domains,both ML and DL are also popularly used in SM analysis.This paper aims to provide an overview of epidemic outbreaks in SM and then outlines a comprehensive analysis of ML and DL approaches and their existing applications in SM analysis.Finally,this review serves the purpose of offering suggestions,ideas,and proposals,along with highlighting the ongoing challenges in the field of early outbreak detection that still need to be addressed.

SARS-CoV-2 Infection Caused COVID-19 Related Otitis Media Is Commonly Existed with Good Prognosis

Otitis media with effusion is a common disease in otolaryngology. Bacteria are the most common pathogen of otitis media with effusion, and other factors such as viruses have also been reported. The present study is aimed to investigate whether the increasing otitis media cases recently is correlated with Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) infection and the COVID-19-related otitis media is commonly existed. Thirty-two patients with otitis media were enrolled Blood cell analysis, C-reactive protein, interleukin-6 test bacterial and fungal cultures were tested. Nine patients were identified with positive SARS-CoV-2 RNA in middle ear discharge. All the subjects had the common symptoms of stuffy ear, hearing loss, and echoacousia. No positive results were found in cultures for bacterial and fungus of middle ear discharge. The levels of C-reactive protein (CRP) were significantly up-regulated in positive cases (P = 0.0335). The levels of proinflammatory cytokine interleukin-6 (IL-6) were higher in positive cases. There were no significant differences of age, gender and prothrombin time (PT) between positive and negative cases. Nasal sprays, ciliary stimulants, and prophylactic antibiotics or low-dose steroid treatments were sequentially used in the otitis media patients caused by SARS-CoV-2 infection. All the patients had improvements of typical symptoms within two to four weeks during the following-up. Thus, SARS-CoV-2 infection caused COVID-19 related otitis media is commonly existed, and the prognosis is good after treatments.

Research on the Evolution of Media Practices of Leading Cadres’ New Media and the Communication Characteristics

Purpose/Significance: This study aims to define the concept of leading cadres new media usage in China specifically, and to describe and analyze the forms and typical cases and characteristics of leading cadres new media in different stages. Method/Process: Based on the themes and contents of a few media accounts of leading cadres at different ranks, we summarizes leading cadres new media usage in a systematic perspective and content analysize method. Result/Conclusion: The study defines the concept of Leading Cadres’ new media from the perspective of media practice, determine its position as a media communication platform in the government affairs new media communication system and its relationship with the other elements, and then systematically review the evolution of its media practice from personal website, blog, microblog and microblog to WeChat, live show. On this basis, with the Harold Lasswell communication model, this article summarizes leading cadres new media communication characteristics from five aspects: content producer, content, channel, audience, and effect. Future studies may also enhance the empirical research from the effect perspective.

The Effect of Latinization on Reading Time and Understanding: Greeklish in Communication and Social Media

The increasing prevalence of technology in society has an impact on young people’s language use and development. Greeklish is the writing of Greek texts using the Latin instead of the Greek alphabet, a practice known as Latinization, also employed for many non-latin alphabet languages. The primary aim of this research is to evaluate the effect of Greeklish on reading time. A sample of 732 young Greeks were asked about their habits when communicating through e-mail and social media with their friends and they then participated in an experiment in which they were asked to read and understand two short texts, one written in Greek and the other in Greeklish. The findings of the research show that nearly one third of the participants use Greeklish. The results of the experiment conducted reveal that understanding is not affected by the alphabet used but reading Greeklish is significantly more time consuming than reading Greek independently of the sex and the familiarity of the participants with Greeklish. The findings suggest that amending social and communication media with software utilities related to Latinization such as language identifiers and converters may reduce reading time and thus facilitate written communication among the users.

Complete Cototal Roman Domination Number of a Graph for User Preference Identification in Social Media

Many graph domination applications can be expanded to achieve complete cototal domination.If every node in a dominating set is regarded as a record server for a PC organization,then each PC affiliated with the organization has direct access to a document server.It is occasionally reasonable to believe that this gateway will remain available even if one of the scrape servers fails.Because every PC has direct access to at least two documents’servers,a complete cototal dominating set provides the required adaptability to non-critical failure in such scenarios.In this paper,we presented a method for calculating a graph’s complete cototal roman domination number.We also examined the properties and determined the bounds for a graph’s complete cototal roman domination number,and its applications are presented.It has been observed that one’s interest fluctuate over time,therefore inferring them just from one’s own behaviour may be inconclusive.However,it may be able to deduce a user’s constant interest to some level if a user’s networking is also watched for similar or related actions.This research proposes a method that considers a user’s and his channel’s activity,as well as common tags,persons,and organizations from their social media posts in order to establish a solid foundation for the required conclusion.

Computational Linguistics with Optimal Deep Belief Network Based Irony Detection in Social Media

Computational linguistics refers to an interdisciplinary field associated with the computational modelling of natural language and studying appropriate computational methods for linguistic questions.The number of social media users has been increasing over the last few years,which have allured researchers’interest in scrutinizing the new kind of creative language utilized on the Internet to explore communication and human opinions in a betterway.Irony and sarcasm detection is a complex task inNatural Language Processing(NLP).Irony detection has inferences in advertising,sentiment analysis(SA),and opinion mining.For the last few years,irony-aware SA has gained significant computational treatment owing to the prevalence of irony in web content.Therefore,this study develops Computational Linguistics with Optimal Deep Belief Network based Irony Detection and Classification(CLODBN-IRC)model on social media.The presented CLODBN-IRC model mainly focuses on the identification and classification of irony that exists in social media.To attain this,the presented CLODBN-IRC model performs different stages of pre-processing and TF-IDF feature extraction.For irony detection and classification,the DBN model is exploited in this work.At last,the hyperparameters of the DBN model are optimally modified by improved artificial bee colony optimization(IABC)algorithm.The experimental validation of the presentedCLODBN-IRCmethod can be tested by making use of benchmark dataset.The simulation outcomes highlight the superior outcomes of the presented CLODBN-IRC model over other approaches.

Pressure evolution in shock-compacted granular media

The pressure evolution associated with the transient shock-induced infiltration of gas flow through granular media consisting of mobile particles is numerically investigated using a coupled Eulerian–Lagrangian approach.The coupling between shock compaction and interstitial flow has been revealed.A distinctive two-stage diffusing pressure field with deflection occurring at the tail of the compaction front is found,with corresponding spikes in both gaseous velocity and temperature profiles emerging within the width of the compaction front.The compaction front,together with the deflection pressure,reaches a steady state during the later period.An analytical prediction of the steady deflection pressure that considers the contributions of porosity and the non-isothermal effect is proposed.The isothermal single-phase method we developed,combining the porosity jump condition across the compaction front,shows consistent pressure evolution with the non-isothermal CMP-PIC one under weak shock strength and low column permeability.Lastly,the microscale mechanism governing the formation of not only pressure deflection but also gaseous velocity and temperature spikes within the width of the compaction front has been described.These aforementioned evolutions of the flow field are shown to arise from the nozzling effects associated with the particle-scale variations in the volume fraction.

Social Comparison Orientation Associated with Psychological Well Being:The Mediated Role of Self-efficacy

The paper focused on how social comparison orientation people apply influences their psychological well-being and how self-efficacy plays an important role in buffering some negative influence from upward social comparison compared with someone better in one domain.In Festinger’s(1954)social comparison theory,the social comparison orientation instructed how people process the information they compared for,and related emotion was induced differently.In this paper,2,000 college students in Boston were proposed to participate in two experiments that discuss how different social comparison orientations affect their perception of life satisfaction.For the hypothetical result,we proposed that a high level of engagement in social comparison and ability-based social comparison was associated with less life satisfaction than the participants who had a low level of social comparison and opinion-based social comparison.In terms of coping strategy,we assumed that a high level of self-efficacy,which is the belief in capability to achieve a certain goal,will buffer the negative impact from upward comparison and improve the life satisfaction of those participants who like to engage with social comparison and ability-based comparison orientation.

基于COM-B模型晚期肺癌患者预立医疗照护计划参与度影响因素分析

目的 基于COM-B模型分析晚期肺癌患者预立医疗照护计划参与度的影响因素,为临床干预决策提供参考。方法 便利选取317例晚期肺癌患者,采用预立医疗照护计划参与问卷、预立医疗照护计划问卷、心理韧性量表等进行调查。根据COM-B模型中能力、机会、动机3维度分析晚期肺癌患者预立医疗照护计划参与度的影响因素。结果 晚期肺癌患者预立医疗照护计划参与度得分为(67.37±6.14)分。多元线性分层回归分析显示,知晓疾病诊断时间,能力因素中预立医疗照护计划知识和心理弹性,动机因素中预立医疗照护计划信念、动机、死亡态度(自然接受)、焦虑和抑郁,机会因素中社会支持是晚期肺癌患者预立医疗照护计划参与度的主要影响因素(均P<0.05),可解释总变异的50.4%。能力因素、动机因素、机会因素的新增解释量分别为18.6%、18.4%、3.4%。结论 晚期肺癌患者预立医疗照护计划参与度偏低,能力和动机因素的影响较大,机会因素的影响相对较小。医护人员需提高晚期肺癌患者预立医疗照护计划相关知识和心理弹性水平,激发预立医疗照护计划信念和动机,树立正确的死亡态度,减轻焦虑和抑郁水平,增加社会支持,以提高预立医疗照护计划的参与。

On the Feasibility of the Chinese County-Level Convergence Media Centers in Participating in International Communication:Evidence from CDHT’s First-Hand Communication Practice

With the advent of new technologies,China is faced with the practical need to enhance its international communication capacity and address reforms in the modes,content,and channels of international communication.Therefore,more efforts should be made to further enrich the participants in international communication by optimizing China’s four-level journalism communication system and crafting a“great external publicity pattern.”Guiding and promoting county-level convergence media centers to participate in international communication is conducive to promoting the building of a vertical international communication system and a multi-level integrated communication matrix and facilitating the resource alignment and information sharing between domestic and international communication.In practice,some county-level convergence media centers in China have achieved certain results in international communication.A good example is the Chengdu Hi-tech Industrial Development Zone(CDHT),a pioneer in the reform of Chinese county-level convergence media.Therefore,this paper has used CDHT as an example to discuss the reality and basic conditions for Chinese county-level convergence media centers to participate in international communication and put forward general paths for county-level convergence media centers to engage in international communication.

Study of Advertising Communication Form in the New Media Age

As the development of internet and different social media platform, the advertising has also changed a lot. In traditional media, the advertising producer is professional, the advertising communication channel is simple. However, as a lot of media platform such as TikTok, QQ, WeChat and Little Red book widely used, the advertising form has become more pluralistic, the advertising content producer are not only by professional companies but also by influencers. Thus the content is becoming diversified. The advertising is entering people’s daily life as a fragmented, concealed, more entertaining way. The communication affect is gaining more widespread and effective.

Computer simulation of Cu:AlOOH/water in a microchannel heat sink using a porous media technique and solved by numerical analysis AGM and FEM

Extensive improvements in small-scale thermal systems in electronic circuits,automotive industries,and microcomputers conduct the study of microsystems as essential.Flow and thermic field characteristics of the coherent nanofluid-guided microchannel heat sink are described in this perusal.The porous media approximate was used to search the heat distribution in the expanded sheet and Cu:γ-AlOOH/water.A hybrid blend of Boehme copper and aluminum nanoparticles is evaluated to have a cooling effect on the microchannel heat sink.By using Akbari Ganji and finite element methods,linear and non-linear differential equations as well as simple dimensionless equations have been analyzed.The purpose of this study is to investigate the fluid and thermal parameters of copper hybrid solution added to water,such as Nusselt number and Darcy number so that we can reach the best cooling of the fluid.Also,by installing a piece of fin on the wall of the heat sink,the coefficient of conductive heat transfer and displacement heat transfer with the surrounding air fluid increases,and the efficiency of the system increases.The overall results show that expanding values on the NP(series heat transfer fluid system maximizes performance with temperatures)volume division of copper,as well as boehmite alumina particles,lead to a decrease within the stream velocity of the Cu:AlOOH/water.Increasing the volume fraction of nanoparticles in the hybrid mixture decreases the temperature of the solid surface and the hybrid nanofluid.The Brownian movement improves as the volume percentage of nanoparticles in the hybrid mixture grows,spreading the heat across the environment.As a result,heat transmission rates rise.As the Darcy number increases,the thermal field for solid sections and Cu:AlOOH/water improves.

Deep Learning Enabled Social Media Recommendation Based on User Comments

Nowadays,review systems have been developed with social media Recommendation systems(RS).Although research on RS social media is increas-ing year by year,the comprehensive literature review and classification of this RS research is limited and needs to be improved.The previous method did notfind any user reviews within a time,so it gets poor accuracy and doesn’tfilter the irre-levant comments efficiently.The Recursive Neural Network-based Trust Recom-mender System(RNN-TRS)is proposed to overcome this method’s problem.So it is efficient to analyse the trust comment and remove the irrelevant sentence appropriately.Thefirst step is to collect the data based on the transactional reviews of social media.The second step is pre-processing using Imbalanced Col-laborative Filtering(ICF)to remove the null values from the dataset.Extract the features from the pre-processing step using the Maximum Support Grade Scale(MSGS)to extract the maximum number of scaling features in the dataset and grade the weights(length,count,etc.).In the Extracting features for Training and testing method before that in the feature weights evaluating the softmax acti-vation function for calculating the average weights of the features.Finally,In the classification method,the Recursive Neural Network-based Trust Recommender System(RNN-TRS)for User reviews based on the Positive and negative scores is analysed by the system.The simulation results improve the predicting accuracy and reduce time complexity better than previous methods.

Application of Social Media Tool in Disaster Management in Disaster-Prone Communities in Freetown, Sierra Leone

This study used both the “digital divide” and “attribution theory” to analyze the propensity of social media use by disaster-prone communities. The study focused on the variables that may affect how social media is used for disaster management. Structural equation modeling (SEM) was utilized in the study to analyze the data and test the hypotheses after using a survey questionnaire to collect the data. The study’s findings show that: 1) communities that are vulnerable to disasters are less likely to use social media for disaster management, 2) personal effort and intention to use social media for disaster management are positively correlated, and 3) task complexity and intention to use social media for disaster management are negatively correlated. The study added to the body of knowledge regarding the role social media plays in disaster management.

基于COM-B理论的老年慢性心力衰竭病人容量超负荷居家管理行为体验的质性研究

目的探索基于能力-机会-动机-行为(COM-B)理论的老年CHF病人居家容量管理行为的真实体验,为制定个性化的老年CHF病人容量超负荷居家管理方案提供参考。方法采用目的抽样法,对15例老年CHF病人进行半结构式访谈,运用内容分析法对资料进行分析。结果老年CHF病人容量超负荷居家管理行为共提炼出3个主题及9个亚主题,分别是能力方面:症状感知能力欠佳、管理知识欠缺或偏差、居家管理应对无效;动机方面:容量管理信心缺乏、容量管理体验不佳、运动自我效能低下;机会方面:医院支持、社区支持、家庭支持。结论老年CHF病人容量超负荷居家管理行为受多种因素的影响,需拓展容量管理教育方式及途径,切实提高老年CHF病人的自我决策及应对能力;重视不良体验,树立积极信念,激发容量管理行为动机;优化居家容量管理策略,加强医院-社区-家庭容量管理的连续性。

Potential use of large language models for mitigating students’problematic social media use:ChatGPT as an example

The problematic use of social media has numerous negative impacts on individuals'daily lives,interpersonal relationships,physical and mental health,and more.Currently,there are few methods and tools to alleviate problematic social media,and their potential is yet to be fully realized.Emerging large language models(LLMs)are becoming increasingly popular for providing information and assistance to people and are being applied in many aspects of life.In mitigating problematic social media use,LLMs such as ChatGPT can play a positive role by serving as conversational partners and outlets for users,providing personalized information and resources,monitoring and intervening in problematic social media use,and more.In this process,we should recognize both the enormous potential and endless possibilities of LLMs such as ChatGPT,leveraging their advantages to better address problematic social media use,while also acknowledging the limitations and potential pitfalls of ChatGPT technology,such as errors,limitations in issue resolution,privacy and security concerns,and potential overreliance.When we leverage the advantages of LLMs to address issues in social media usage,we must adopt a cautious and ethical approach,being vigilant of the potential adverse effects that LLMs may have in addressing problematic social media use to better harness technology to serve individuals and society.

A study on the temperature sensitivity of NMR porosity in porous media based on the intensity of magnetization Dedicated to the special issue “Magnetic Resonance in Porous Media”

The measurement of nuclear magnetic resonance(NMR)porosity is affected by temperature.Without considering the impact of NMR logging tools,this phenomenon is mainly caused by variations in magnetization intensity of the measured system due to temperature fluctuations and difference between the temperature of the porous medium and calibration sample.In this study,the effect of temperature was explained based on the thermodynamic theory,and the rules of NMR porosity responses to temperature changes were identified through core physics experiments.In addition,a method for correcting the influence of temperature on NMR porosity measurement was proposed,and the possible factors that may affect its application were also discussed.

Acute Otitis Media in Children Aged 0-5 Years, Epidemiological Aspects and Management in the Paediatrics Department of the Hospital National Ignace Deen (Conakry)

Introduction: Acute otitis media is an acute inflammation of the mucosa of the middle ear cavities. It is often secondary to nasopharyngitis, which favors the passage of infection through the Eustachian tube to the middle ear. The aim of our study was to improve the management of AOM in the Paediatric Department of the Hospital National Ignace Deen (Conakry). Patients and Methods: This was a prospective descriptive study lasting 6 months from 01 July to 31 December 2011;the study covered 525 cases out of a total of 6276 children, i.e. a frequency of 8.36%. Results: The most affected age group was 6 to 11 months. Males predominated (69.71%). 82.29% had a history of recurrent rhinopharyngitis. The most frequent reason for consultation was incessant crying (66.29%). Rhinopharyngitis and malaria were the most commonly associated pathologies (87.62% and 39.62% respectively). 72.19% of our patients were admitted with congestive AOM and received medical treatment. We recorded one case of otomastoiditis which was treated surgically. Conclusion: AOM is more common in children aged between 6 and 24 months. Good collaboration between paediatricians and ENT specialists is essential to reduce the morbidity of AOM.

Modeling Method of C/C-ZrC Composites and Prediction of Equivalent Thermal Conductivity Tensor Based on Asymptotic Homogenization

This article proposes a modeling method for C/C-ZrC composite materials.According to the superposition of Gaussian random field,the original gray model is obtained,and the threshold segmentation method is used to generate the C-ZrC inclusion model.Finally,the fiber structure is added to construct the microstructure of the three-phase plain weave composite.The reconstructed inclusions can meet the randomness of the shape and have a uniform distribution.Using an algorithm based on asymptotic homogenization and finite element method,the equivalent thermal conductivity prediction of the microstructure finite element model was carried out,and the influence of component volume fraction on material thermal properties was explored.The sensitivity of model parameters was studied,including the size,mesh sensitivity,Gaussian complexity,and correlation length of the RVE model,and the optimal calculation model was selected.The results indicate that the volume fraction of the inclusion phase has a significant impact on the equivalent thermal conductivity of the material.As the volume fraction of carbon fiber and ZrC increases,the equivalent thermal conductivity tensor gradually decreases.This model can be used to explore the impact of materialmicrostructure on the results,and numerical simulations have studied the relationship between structure and performance,providing the possibility of designing microstructure based on performance.

Effects of confining pressure and pore pressure on multipole borehole acoustic field in fluid-saturated porous media

In-situ stress is a common stress in the exploration and development of oil reservoirs. Therefore, it is of great significance to study the propagation characteristics of borehole acoustic waves in fluid-saturated porous media under stress.Based on the acoustoelastic theory of fluid-saturated porous media, the field equation of fluid-saturated porous media under the conditions of confining pressure and pore pressure and the acoustic field formula of multipole source excitation in open hole are given. The influences of pore pressure and confining pressure on guided waves of multipole borehole acoustic field in fluid-saturated porous media are investigated. The numerical results show that the phase velocity and excitation intensity of guided wave increase significantly under the confining pressure. For a given confining pressure, the phase velocity of the guided wave decreases with pore pressure increasing. The excitation intensity of guided wave increases at low frequency and then decreases at high frequency with pore pressure increasing, except for that of Stoneley wave which decreases in the whole frequency range. These results will help us get an insight into the influences of confining pressure and pore pressure on the acoustic field of multipole source in borehole around fluid-saturated porous media.