Objective: Synthetic fluorescent dyes that are conjugated to antibodies are useful tools to probe molecules. Based on dye chemical structures, their photobleaching and photostability indices are quite diverse. It is generally believed that among different fluorescent dyes, Alexa Fluor family has greater photostability than traditional dyes like fluorescein isothiocyanate (FITC) and Cy5. Alexa Fluor 568 is a member of Alexa Fluor family presumed to have superior photostability and photobleahing profiles than FITC.Materials and Methods: In this experimental study, we conjugated Alexa Fluor 568 and FITC dyes to a mouse anti-human nestin monoclonal antibody (ANM) to acquire their photobleaching profiles and photostability indices. Then, the fluorophore/antibody ratios were calculated using a spectrophotometer. The photobleaching profiles and photostability indices of conjugated antibodies were subsequently studied by immunocytochemistry (ICC). Samples were continuously illuminated and digital images acquired under a fluorescent microscope. Data were processed by ImageJ software.Results: Alexa Fluor 568 has a brighter fluorescence and higher photostability than FITC.Conclusion: Alexa Fluor 568 is a capable dye to use in photostaining techniques and it has a longer photostability when compared to FITC.

All of today's dynamic organizations have selected the Internet as one of the best means of communication with all the individuals and stakeholders. The purpose of this research was to evaluate and cluster the website of the 43 Iranian sports federations based on the Alexa website traffic indicators. The indexes included the number of pages viewed، the average browsing time of the site، the percentage of visitors inside the country، the percentage of visitors from outside the country، the number of links and loading rates. Using hierarchical clustering method، similar federations were grouped together in the form of homogeneous clusters، and eventually three clusters were created. The quality and validity of each of the clusters created by the diagnostic analysis method were confirmed and finally، the characteristics of each of these clusters were analyzed. The basis for cluster analysis was considered to be a comparison of the average of each indicator in each cluster with the average of the same indicator in all the clusters (total data). Since there was no significant difference between the average time of browsing the site and the average number of pages visited among different clusters، these indices were not considered in cluster analysis. The results of the study showed that Iran's sports federations have a poor and unexpected performance in the field of webometrics. . .

There is an urgent need for precise and trustworthy models to forecast device behavior and evaluate vulnerabilities as a result of the Internet of Things' (IoT) explosive growth. By assessing the effectiveness of several machine learning algorithms logistic regression, decision trees, random forests, Naïve Bayes, and KNN on two popular IoT devices Alexa and Google Home Mini this study seeks to enhance IoT device behavior forecasting. Our results show that Naïve Bayes and random forest models are more accurate and efficient than other algorithms at predicting device behavior. These findings demonstrate how important algorithm selection is for maximizing the performance of IoT systems. The study also emphasizes the usefulness of precise device behavior prediction for practical uses such as industrial control systems, home automation, and medical monitoring. For example, accurate forecasts can improve decision-making in crucial situations, facilitate more seamless automation, and stop system failures. In addition to adding to the expanding corpus of research on IoT data analysis, this study establishes the foundation for the creation of increasingly sophisticated machine learning models that can manage the intricate and ever-changing nature of IoT ecosystems. Future studies should concentrate on increasing the dataset's diversity to encompass a wider range of IoT environments and devices and enhancing the model's adaptability to changing IoT environments.

Purpose: (i) to assess the quality of health websites on kidney transplant and (ii) to evaluate the accessibility of these websites and their concordance with the existing guidelines. Materials and Methods: The terms “ kidney transplantation” and “ renal transplantation” were searched in the three most popular search engines Google, Yahoo, and Bing. 58 unique websites were eligible for the analysis. The Websites accessibility was evaluated using the AChecker tool. Kruskal– Wallis test was performed to examine any significant difference between accessibility issues across different domains. The eligible websites were screened for quality based on the HONcode of conducts. Moreover, the daily traffic data of each website was determined by Alexa. The correlation of known accessibility problems with website popularity was examined too. Result: The main reported known problems belonged to “ scripts must have functional text, ” “ text equivalents, ” “ accessible forms, ” and “ text links for server-side image map” . Although the mean accessibility errors in governmental (10. 25 ± 7. 274) and organizational (12. 31 ± 9. 469) websites were less than those in the other domains, the differences were not significant (P = 0. 60). Findings showed no significant correlation (P > 0. 05) between the extent of known problems (16. 50 ± 12. 18) and Alexa ranking (253675. 07 ± 534690. 947). Furthermore, most websites on kidney transplant were not certified by the HONcode. Conclusion: The health websites designers should be aware of accessibility problems, because there is a growing population of potential users with disabilities. This study indicated the need to ensure the compliance of kidney transplant websites with accessibility guidelines such as Section 508. Furthermore, most surveyed websites were of poor quality and unreliable. Therefore, physicians should warn their patients about unqualified online health information and guide them to websites which are more reliable.

The websites of Iranian medical universities under Ministry of Health, Treatment, and Medical Education have been studied in the present paper. 41 websites have been studied structurally using a checklist containing 60 items. Number of pages indexed from each website, total number of links, received links, self-links, total impact factor, and individual impact factor of those websites were studied in order to assess their visibility and impact. Number of visits to the websites under study was also studied and factors such as traffic rank at national and universal levels, percentage of web users browsing the designated websites, average number of pages browsed by users, and their browse rate both in Iran and abroad, were extracted from Alexa site and analyzed.

Using correspondence analysis, this study aims to evaluate the Iranian Medical Universities websites based on six criteria obtained from Alexa Internet.41 medical universities websites affiliated to The Ministry of Health and Medical Education were identified on the Web. The research findings provide an evaluation of medical universities websites status in terms of their functions and performance on the Web. Results show that most of universities websites did not act successfully on the Web regarding the six criteria. The investigated websites had a weak function in traffic rank and most of them were ranked top of 100'000. As a whole, Tehran and Shiraz universities acted more successful in comparison to others whilst Qom university was weak regarding most of the criteria. Correspondence analysis classified 41 websites into 3 groupings which were related based on some attributes.

Objective: The present study seeks to show the extent to which the quality of user experience of platforms is influenced by their gamification and pricing strategy. Methodology: The statistical population of this study includes 114 Iranian and foreign platforms and the statistical sample includes 88 platforms based on Alexa ranking. Structural equation modeling and SMART-PLS3 software were used to analyze the data. Findings: The results indicate that gamification does not have a positive and significant effect on the quality of user experience. According to the studies, the adjustment effect of pricing strategies on the relationship between gamification and user experience quality was confirmed. Conclusion: Using gamification tools on platforms does not in itself improve or enhance the quality of the user experience. Platforms and companies or organizations that have a platform business model can use gamification to enhance the quality of the user experience if they use appropriate pricing strategies.