Determining the relationship between components of knowledge management and organizational citizenship behavior in experts’ Science and Research Branch of Islamic Azad University

This study aimed to investigate the relationship between components of knowledge management and organizational citizenship behavior in experts’ Science and Research Branch of Islamic Azad University. The study population was selected using the table Morgan 130 stratified random sampling method. In order to collect data, Newman knowledge management in terms of knowledge creation, preserve and maintain knowledge, knowledge transfer and sharing, and application of knowledge, consisting of 21 questions, as well as organizational citizenship behavior and Organ dimensions of altruism, conscientiousness, Chivalry, civic behavior, currency were used. The results showed that there is a significant relationship between knowledge management and organizational citizenship behavior in the population. There are also components of the transfer of knowledge, application of knowledge, creation of knowledge to the highest and most variable correlation with organizational citizenship behavior in the population and there was no relationship between the variable component and maintenance of organizational citizenship behavior in the population

Improving long line stability by integrating renewables using static synchronous generators

Postprint (author's final draft

Synchronous power controller merits for dynamic stability improvement in long line by renewables

Postprint (author's final draft

An Efficient Metric for Physical-layer Jammer Detection in Internet of Things Networks

An active jammer could severely degrade the communication quality for wireless networks. Since all wireless nodes openly access the shared media, the harsh effects are exaggerated by retransmission attempts of affected devices. Fast and precise detection of the jammer is of vital importance for heterogeneous wireless environments such as the Internet of things (IoT). It could activate a series of corrective countermeasures to ensure the robust operation of the network. In this paper, we propose a local, straightforward, and numerical metric called the number of jammed slots (NJS), by which we can quickly detect the presence of a jammer and identify the jammed nodes at the software level in broadcast networks. NJS calculation is carried out by a central node which collects the MAC-layer statuses of all wireless nodes in a periodical fashion. Our simulation results indicate that NJS outperforms current detection methods in terms of accuracy and precision

Supporting phase stability on interconnected grids by synchronous renewable virtual power plants

Rapid growing on the power level of renewable generation units leads to that using more adaptable and flexible control techniques in this units becomes more important for grid operators. In this paper, after introducing Renewable Static Synchronous Generation Units (RSSGU) as units with flexible dynamics capability, forming of renewable Virtual Power Plants based on this RSSGUs (VPP-SSG) is suggested as a solution for overcoming phase stability challenges on interconnected generation areas. Based on the dynamic modeling and small signal analysis, an algorithm is presented for the dynamic designing of VPP-SSGs aims to provide supporting damping for both local and interarea oscillatory modes. Modal analysis and time domain study on active powers inside of generation areas and tie lines on two area system using Simulink confirms that these type of VPP-SSGs can support phase stability on power grid with interconnected generation areasPeer ReviewedPostprint (author's final draft

A comparative study on effectiveness of workshop education versus education via mobile learning (m-learning) in developing medical students’ knowledge and skill about cardiopulmonary resuscitation

INTRODUCTION: A variety of educational approaches are being used today to improve learning in the field of cardiopulmonary resuscitation. Therefore, the present study was conducted to compare workshop education with education via mobile learning (M-learning) in terms of their efficacy in developing medical students’ knowledge and skills about cardiopulmonary resuscitation. MATERIAL AND METHODS: The present study was quasi-experimental performed on 60 interns selected from a university of medical sciences in southwest Iran. Participants were assigned to either the workshop education group (n = 30) or the mobile learning group (n = 30). Before and after the intervention, the knowledge and skills of the participants in terms of basic and advanced cardiopulmonary resuscitation were measured by a questionnaire. The collected data were analyzed using descriptive statistics, Independent-Samples t-Test, Paired-Samples t-Test, and Chi-Square Test in SPSS software v. 22. RESULTS: Education via mobile learning caused a significant increase in the participants’ knowledge about cardiopulmonary resuscitation (p < 0.05). However, this method did not result in a significant difference in the participants’ skill scores, while the workshop education group showed a significant increase in their cardiopulmonary resuscitation skill scores (p < 0.05). CONCLUSIONS: Our results revealed that education via mobile learning was better in enhancing medical students’ knowledge about cardiopulmonary resuscitation. However, workshop education was more effective in developing practical skills in the field of cardiopulmonary resuscitation. Accordingly, educators are recommended to employ a combination of mobile learning and workshop education for achieving better results

Impact of feature harmonization on radiogenomics analysis:Prediction of EGFR and KRAS mutations from non-small cell lung cancer PET/CT images

Objective: To investigate the impact of harmonization on the performance of CT, PET, and fused PET/CT radiomic features toward the prediction of mutations status, for epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene (KRAS) genes in non-small cell lung cancer (NSCLC) patients. Methods: Radiomic features were extracted from tumors delineated on CT, PET, and wavelet fused PET/CT images obtained from 136 histologically proven NSCLC patients. Univariate and multivariate predictive models were developed using radiomic features before and after ComBat harmonization to predict EGFR and KRAS mutation statuses. Multivariate models were built using minimum redundancy maximum relevance feature selection and random forest classifier. We utilized 70/30% splitting patient datasets for training/testing, respectively, and repeated the procedure 10 times. The area under the receiver operator characteristic curve (AUC), accuracy, sensitivity, and specificity were used to assess model performance. The performance of the models (univariate and multivariate), before and after ComBat harmonization was compared using statistical analyses. Results: While the performance of most features in univariate modeling was significantly improved for EGFR prediction, most features did not show any significant difference in performance after harmonization in KRAS prediction. Average AUCs of all multivariate predictive models for both EGFR and KRAS were significantly improved (q-value &lt; 0.05) following ComBat harmonization. The mean ranges of AUCs increased following harmonization from 0.87-0.90 to 0.92-0.94 for EGFR, and from 0.85-0.90 to 0.91-0.94 for KRAS. The highest performance was achieved by harmonized F_R0.66_W0.75 model with AUC of 0.94, and 0.93 for EGFR and KRAS, respectively. Conclusion: Our results demonstrated that regarding univariate modelling, while ComBat harmonization had generally a better impact on features for EGFR compared to KRAS status prediction, its effect is feature-dependent. Hence, no systematic effect was observed. Regarding the multivariate models, ComBat harmonization significantly improved the performance of all radiomics models toward more successful prediction of EGFR and KRAS mutation statuses in lung cancer patients. Thus, by eliminating the batch effect in multi-centric radiomic feature sets, harmonization is a promising tool for developing robust and reproducible radiomics using vast and variant datasets.</p

Prevalence of Antibiotic Residues in Milk Consumed in Iran: A Systematic Review and Meta-Analysis

Background: Improper use of antibiotics and not paying attention to withdrawal time causes antibiotics to enter the milk, which can cause allergies in humans and cause antibiotic-resistant pathogenic bacteria in the long run, so quality and hygienic milk control is essential.Methods: This study aimed to investigate the prevalence of antibiotic residues in milk as a systematic review and metaanalysis from 2004 to 2021 for 15 years in Iran. The data were collected from four international search databases, including PubMed, Scopus, Science Direct, and Google Scholar, and four Iranian databases, including SID, MagIran, Civilica, and IranDoc.Results: After reviews of 314 studies, 38 were finally selected, and the information was recorded and analyzed in Stata software. The results of this study show that the residual prevalence of antibiotics in milk using the screening method was 28% (CI: 0.34-0.22). The residual rates of antibiotics using enzymelinked immunosorbent assay (ELISA) and high-pressure liquid chromatography (HPLC) methods were 43% (CI: 0.26-0.59) and 27% (CI: 0.05-0.49), respectively.Conclusion: The data obtained from the meta-analysis show that despite various reports of a quantitative amount of antibiotic residue in milk, the average amount in the ELISA method was 16.98 ppm. Although the prevalence of antibiotics in Iran is relatively high, a quantitative amount is optimal. Also, since the use of antibiotics in livestock is almost inevitable, proper withdrawal time of antibiotics can play an important role in preventing the release of antibiotic residues in milk