Search

Introduction: Over the course of the last decade social media has become a very important part of the human experience; it has become the main source of communication and entertainment for a lot of people young and old. Objectives: This study aimed to examine the influence of social media on undergraduates working memory and academic performance. We assessed the association between the harmful use of social media on gender differences, physical activities, academic performance, and working memory. Methods: This cross-sectional study was designed to examine the effect of social media on the working memory of undergraduate students from three different Universities in Georgia involving 722 participants. The collection survey form was distributed among Undergraduate students from the University of Georgia (UG), Eastern European University (EEU), and Batumi State University (BSU) through google forms from 14th June to 2nd July 2023. The questionnaire consisted of sociodemographic characteristics (e.g., age, gender, and institution), social media disorder scale (SMD), academic performance scale (APS), and working memory (WM). Results: 58.7% were female students, the mean age was 21.94 (SD ± 2.8), and most of the participants were international students. More students from Tbilisi had persistence (59.8%), escape (69%) complaints, and students from Batumi had more preoccupation (43%), persistence (62.5%) and escape (65.7%) complaints. 64.1% of female students are at increased risk of using social media as an 'escape' from negative feelings (OR 0.50; χ2 (18.206), p= 0.000, 95% Cl[0.368-0.692]). 51.6% of male students and 48.4% of female students had the risk of 'conflict' with families and friends because of social media (OR 1.65; χ2 (6.507), p= 0.011, 95% Cl[1.122-2.452]. 80.3% of students that had good academic performance are at risk of neglecting activities such as hobbies, sports, and class assignments because of social media (OR 0.63; χ2 (5.133), p= 0.023, 95% Cl[0.425-0.942]). 94% of students with good working memory had the risk of withdrawal complaints (OR 0.34; χ2 (6.865a), p= 0.009, 95% Cl[0.154-0.793]). As 93.4% of having conflicts with parents, siblings, and partners because of social media. Conclusions: Our studies presented the prevalence of social media addiction and its effect on academic performance and working memory among undergraduate students. The influence of social media on students has been significant. Students should establish boundaries, use digital moderation, and seek treatment for emotional difficulties as further studies are recommended. Disclosure of Interest: None Declared [ABSTRACT FROM AUTHOR]

Rolling stock approval protocols, such as UIC 518, demand monitoring of lateral and vertical forces at rail-wheel contact. Continuous monitoring through on-board instrumentation needs algorithms to convert the on-board sensor data into rail-wheel forces and track irregularities. In this work a Feed Forward Neural Network architecture, for fast and accurate estimation of rail-wheel forces and track irregularities from data obtained from a cluster of accelerometers mounted on the rolling stock, is presented. Simulation study is conducted for a passenger coach running over numerically generated set of one hundred rail tracks, each with a different irregularity. Power spectral density (PSD) function of ERRI B176 is used for creating rail irregularities. Multi-body rail coach model consists of wheel-sets, axle-box, bogie, bolster and car body. The input comprises acceleration, yaw and roll rate data from axle-box, bogie and car body, to produce contact forces and rail irregularities as outputs. Goodness of fit between actual and estimated values is illustrated through point-by-point graphs of actual and estimated track forces and irregularities. R-Squared ( R 2 ) values, representing the fraction by which the variance of errors are less than the variance of actual values, are computed as indices of the accuracy of estimates. [ABSTRACT FROM AUTHOR]

Byline: N. Vyas, A. Hassan Chronic lymphocytic leukemia (CLL) was largely considered to be a disease of slow progression, standard treatment with Chlorambucil and having almost similar prognosis. With the [...]

Objective: Vesical Imaging Reporting and Data System (VIRADS) score was developed to standardize the reporting and staging of bladder tumors on pre-operative multiparametric magnetic resonance imaging. It helps in avoiding unnecessary repeat transurethral resection of bladder tumor in high-risk non-muscle-invasive bladder cancer patients. This study was done to determine the validity of VIRADS score prospectively for the diagnosis of muscle-invasive bladder cancer. Methods: This study was conducted from March 2019 to March 2020 at Sawai Man Singh Medical College and Hospital, Jaipur, Rajasthan, India. Patients admitted with the provisional diagnosis of bladder tumor were included as participants. All these patients underwent a 3 Tesla mpMRI to obtain a VIRADS score before they underwent transurethral resection of bladder tumor and these data were analyzed to evaluate the correlation of pre-operative VIRADS score with muscle invasiveness of the tumor in final biopsy report. Results: A cut-off of VIRADS ≥4 for prediction of detrusor muscle invasion yielded a sensitivity of 79.4%, specificity of 94.2%, positive predictive value of 90.0%, negative predictive value of 87.5%, and diagnostic accuracy of 86.4%. A cut off of VIRADS ≥3 for prediction of detrusor muscle invasion yielded a sensitivity of 91.2%, specificity of 78.8%, positive predictive value of 73.8%, negative predictive value of 93.2%, and accuracy of 83.7%. The receiver operating curve showed the area under the curve to be 0.922 (95% confidence interval: 0.862–0.983). Conclusion: VIRADS score appears to be an excellent and effective pre-operative radiological tool for the prediction of detrusor muscle invasion in bladder cancer.