THE EFFECT OF MEDIA LITERACY ON THE SOCIAL IDENTITY OF VOLLEYBALL SPECTATORS THROUGH PERSONAL IDENTITY

This research aim was investigating the effect of media literacy on volleyball spectator's social identity through personal identity. The present study, psychologically, is divided in to 8 layers of view paradigm, the main type of applied research: deductive research approaches, quantity research strategies theories, field research tone, cross sectional survey methods, research objectives, description and finally data collection methods, library resource reviews, and questionnaires. The statistical society consisted of premier league volleyball spectators from Iran. Number of samples consisted on 342 members, in terms of Cochran formula. To collect data, Chang et al media literacy questionnaire (2011), Safarnia & Roshan social identity (2011) and Bordbar personal identity (2012) were used. Content validity was used for questionnaires and their stability was evaluated through Cronbach's alpha. Cronbach's alpha coefficient for media literacy variable (.894), social identity (.824) and personal identity (.801) were resulted. For research findings analysis, structural equation modeling was used. The results showed that media literacy is indirectly effective on social volleyball spectator's identity, and also cleared that personal identity has an effective and positive influence on social identity. Media literacy is one of the most effective regulatory and identity strategies that affects effectively and positively.   Article visualizations

THE EFFECT OF ADVERTISING ON SOCIAL NETWORKS ON THE MARKETING OF SPORTS SERVICES - CASE STUDY: SOCIAL TELEGRAM USERS

Today, the number of social networks in which communications are made is increasing rapidly, and most teenagers and adults, as part of everyday life, use the benefits of knowing others and introducing themselves to others from social networks such as Facebook, MySpace, LinkedIn, YouTube, Weblogs and Wikiquote. The purpose of this study was to investigate the effect of advertising on social networks on the marketing of sports services. Methodologically, this descriptive study was of correlational type and its statistical community was formed by active users in social sports networks. The statistical sample was available (from users who were active social sports networks). In this research, social networking was measured using the scale of Soleimani-Bashli and Talibi (2010) and marketing mix of sport services using Yaghoobi et al. (2011) scale. To test the research hypotheses, structural equation modeling was used. The results of the research showed that advertising in social networks has a positive and significant effect on marketing of sports services. As a result, the greater the amount of advertising on social networks, the more likely it is that customer satisfaction, attracting new customers, and increasing investment in sports services will increase. Therefore, it is necessary to pay more attention to the aspect of advertising in these networks and to be taken into consideration in strategic strategies of sports providers.  Article visualizations

THE RELATIONSHIP OF SELF-EFFICACY WITH TEHRAN CITY HIGH SCHOOL STUDENT'S MOTIVATION AND TAKING PART IN PHYSICAL ACTIVITIES

The present study has investigated the relationship of self-efficacy with Tehran city high school student's motivation and taking part in physical activities. The present study methodologically is divided in to 8 kind's hypothesis inductive research approaches, quantitative research strategy, the objectives of the research are descriptive and explaining, and in the end of method and data collection, library resources review and questionnaire. The statistical society of this research consists of all the students of Tehran education districts 14, 6, 3 in 2013 – 2014 academic years. To specify the sample volume Cochran formula was used. Based on this formula the minimum needed volume for this sample for such a research are 203 individuals. The research sample consisted in 400 of Tehran education students (boys and girls) that were selected via stratified cluster sampling method among girls and boys students. The data collection tool was a standard questionnaire. To analyses the research findings, Pearson correlation coefficient and multi-variable regression model in %95 coefficient level were used. The result showed that in the research statistical sample, the subjects have evaluated self-efficacy characteristics higher than average, and evaluated important individuals subscales lower than average. And also specified that there isn’t significant relation between self-efficacy and physical activities and motivation to participate in sports, with %95 confidence level. And also calculated coefficient of determination showed that %2.56 of physical activities variance and %3.68 of motivation to participate in sports is specified via self-efficacy.   Article visualizations

Maximizing Coverage and Maintaining Connectivity in WSN and Decentralized Iot: An Efficient Metaheuristic-Based Method for Environment-Aware Node Deployment

The node deployment problem is a non-deterministic polynomial time (NP-hard). This study proposes a new and efficient method to solve this problem without the need for predefined circumstances about the environments independent of terrain. The proposed method is based on a metaheuristic algorithm and mimics the grey wolf optimizer (GWO) algorithm. In this study, we also suggested an enhanced version of the GWO algorithm to work adaptively in such problems and named it Mutant-GWO (MuGWO). Also, the suggested model ensures connectivity by generating topology graphs and potentially supports data transmission mechanisms. Therefore, the proposed method based on MuGWO can enhance resources utilization, such as reducing the number of nodes, by maximizing the coverage rate and maintaining the connectivity. While most studies assume classical rectangle uniform environments, this study also focuses on custom (environmentaware) maps in line with the importance and requirements of the real world. The motivation of supporting custom maps by this study is that environments can consist of custom shapes with prioritized and critical areas. In this way, environment awareness halts the deployment of nodes in undesired regions and averts resource waste. Besides, novel multi-purpose fitness functions of the proposed method satisfy a convenient approach to calculate costs instead of using complicated processes. Accordingly, this method is suitable for large-scale networks thanks to the capability of the distributed architecture and the metaheuristic-based approach. This study justifies the improvements in the suggested model by presenting comparisons with a Deterministic Grid-based approach and the Original GWO. Moreover, this method outperforms the fruit fly optimization algorithm, bat algorithm (BA), Optimized BA, harmony search, and improved dynamic deployment technique based on genetic algorithm methods in declared scenarios in literature, considering the results of simulations

Application of Protein-Protein Interaction Network Analysis in Order to Identify Cervical Cancer miRNA and mRNA Biomarkers

Cervical cancer (CC) is one of the world’s most common and severe cancers. This cancer includes two histological types: squamous cell carcinoma (SCC) and adenocarcinoma (ADC). The current study aims at identifying novel potential candidate mRNA and miRNA biomarkers for SCC based on a protein-protein interaction (PPI) and miRNA-mRNA network analysis. The current project utilized a transcriptome profile for normal and SCC samples. First, the PPI network was constructed for the 1335 DEGs, and then, a significant gene module was extracted from the PPI network. Next, a list of miRNAs targeting module’s genes was collected from the experimentally validated databases, and a miRNA-mRNA regulatory network was formed. After network analysis, four driver genes were selected from the module’s genes including MCM2, MCM10, POLA1, and TONSL and introduced as potential candidate biomarkers for SCC. In addition, two hub miRNAs, including miR-193b-3p and miR-615-3p, were selected from the miRNA-mRNA regulatory network and reported as possible candidate biomarkers. In summary, six potential candidate RNA-based biomarkers consist of four genes containing MCM2, MCM10, POLA1, and TONSL, and two miRNAs containing miR-193b-3p and miR-615-3p are opposed as potential candidate biomarkers for CC

RPINBASE: An online toolbox to extract features for predicting RNA-protein interactions

Feature extraction is one of the most important preprocessing steps in predicting the interactions between RNAs and proteins by applying machine learning approaches. Despite many efforts in this area, still, no suitable structural feature extraction tool has been designed. Therefore, an online toolbox, named RPINBASE which can be applied to different scopes of biological applications, is introduced in this paper. This toolbox employs efficient nested queries that enhance the speed of the requests and produces desired features in the form of positive and negative samples. To show the capabilities of the proposed toolbox, the developed toolbox was investigated in the aptamer design problem, and the obtained results are discussed. RPINBASE is an online toolbox and is accessible at http://rpinbase.com