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Abstract This study aimed to evaluate the clinical benefits of incorporating a widefield lens (WFL) in optical coherence tomography angiography (OCT-A) in patients with retinal vascular diseases in comparison to standard single-shot OCT-A scans. Sixty patients with retinal vascular diseases including diabetic retinopathy (DR) and retinal vein occlusion (RVO) were recruited. OCT-A imaging (PlexElite 9000) with and without WFL was performed in randomized order. The assessment included patient comfort, time, field of view (FoV), image quality and pathology detection. Statistical analysis included paired t-tests, Mann–Whitney U-tests and Bonferroni correction for multiple tests, with inter-grader agreement using the kappa coefficient. Using a WFL did not lead to statistically significant differences in DR and RVO group test times. Patient comfort remained high, with similar responses for WFL and non-WFL measurements. The WFL notably expanded the scan field (1.6× FoV increase), enhancing peripheral retinal visibility. However, image quality varied due to pathology and eye dominance, affecting the detection of peripheral issues in RVO and DR cases. The use of a WFL widens the scan field, aiding vascular retinal disease imaging with minor effects on comfort, time, and image quality. Further enhancements are needed for broader view angles, enabling improved quantification of non-perfused areas and more reliable peripheral proliferation detection.

This study aimed to explain the resilience model based on purposeful life and quality of relationships mediated by spiritual health in the face of stress conditions caused by Covid-19 disease. The present study is applied in terms of purpose, and the data collection method was a descriptive correlation. The study's statistical population was family members of patients with Covid-19 disease who lived in Tehran. The sample consisted of 300 family members of patients with Covid-19 disease who participated in the study through available sampling and online methods. Data collection instruments included Mahvlyk & Krambaf purpose in Life Questionnaire (1969), Pierce et al. quality of relationships Questionnaire (1991), Connor and Davidson resilience Questionnaire (2003), and Paloutzian & Ellison's spiritual health Questionnaire (1982). Data were analyzed using the Pearson correlation method and path analysis using SPSS and AMOS software. The results showed that the direct effect of purposefulness in life (P > 0.01) and its indirect effect due to spiritual health (P > 0.005) on resilience is significant. The results also show that the indirect effects of social support (P > 0.04) and interpersonal conflict (P > 0.006) on resilience through spiritual health are significant. Therefore, spiritual health can mediate between purposefulness in life and social support and interpersonal conflict on resilience in the face of psychological pressure and increase resilience.

Banks are one of the main pillars of any country's economic system and their proper functioning will lead to the country's economic development. Due to the increasing demand for bank facilities and the risk in these activities, it is necessary to examine the risk management tools to organize, control and manage the credit risk of banks. In this study, by examining the literature and collecting information from experts through snowball sampling, credit risk management tools in banks in the form of 15 tools were extracted. Then, by compiling a questionnaire and obtaining the experts' opinions, eight final tools were selected and ranked using fuzzy Vikor, fuzzy TOPSIS, and fuzzy vaspas methods. In order to determine the final ranking of instruments based on the results obtained from fuzzy methods, two techniques of mean averaging and Copeland were used. The results showed that collateral and guarantee are the most important tools in credit risk management. Also, the design of the credit rating system and the facility ceiling determination are in the next ranks. Therefore, banks need to pay special attention to these tools to control and manage their credit risk.

The purpose of this study was to determine the effectiveness of life skills training (problem-solving and decision-making) on teacher-student relationships, academic buoyancy, and academic optimism in sixth grade elementary students. The method was quasi-experimental with pre/post-test and a control group. The statistical population was sixth-graders in Hasanabad city schools during the academic year of 2019-20. The sample consisted of 50 sixth grade male students who were assigned to the experimental or control group (25 students in each group). Assessment tools included standard questionnaires of teacher-student relationship quality, academic optimism, and academic buoyancy. Also, students who had much higher scores in buoyancy, optimism, and/or the quality of relationship with their teacher were excluded from the sample due to statistical reasons. The participants were educated in a problem-solving and decision-making training for ten sessions. Following the training, the post test was administered. Multivariate analysis of covariance (MANCOVA) was used to analyze the data. The results showed that the quality of teacher-student relationship, academic buoyancy and academic optimism were higher in the experimental group than those of the control group. As a result, problem-solving and decision-making trainings can be used as part of students’ empowerment programs.

Abstract— Bot networks are a serious threat to cyber security, whose destructive behavior affects network performance directly. Detecting of infected HTTP communications is a big challenge because infected HTTP connections are clearly merged with other types of HTTP traffic. Cybercriminals prefer to use the web as a communication environment to launch application layer attacks and secretly engage in forbidden activities, while TLS (Transport Layer Security) protocols allow encrypted communication between client and server in the context of Internet provides. Methods of analyzing traffic behavior do not depend on payloads. This means that they can work with encrypted network communication protocols. Traffic behavior analysis methods do not depend on package shipments, which means they can work with encrypted network communication protocols. Hence, the analysis of TLS and HTTP traffic behavior has been considered for detecting malicious activities. Because of the exchange of information in the network context is very high and the volume of information is very large, storing and indexing of this massive data require a Big data platform.

Abstract—One of the serious threats to cyberspace is the Bot networks or Botnets. Bots are malicious software that acts as a network and allows hackers to remotely manage and control infected computer victims. Given the fact that DNS is one of the most common protocols in the network and is essential for the proper functioning of the network, it is very useful for monitoring, detecting and reducing the activity of the Botnets. DNS queries are sent in the early stages of the life cycle of each Botnet, so infected hosts are identified before any malicious activity is performed. Because the exchange of information in the network environment and the volume of information is very high, Storing and indexing this massive data requires a large database. By using the DNS traffic analysis, we try to identify the Botnets. We used the data generated from the network traffic and information of known Botnets with the Splunk platform to conduct data analysis to quickly identify attacks and predict potential dangers that could arise. The analysis results were used in tests conducted on real network environments to determine the types of attacks. Visual IP mapping was then used to determine actions that could be taken. The proposed method is capable of recognizing known and unknown Bots.