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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]

Effective biofilm removal from surfaces in the mouth is a clinical challenge. Cavitation bubbles generated around a dental ultrasonic scaler are being investigated as a method to remove biofilms effectively. It is not known how parameters such as surface roughness and instrument distance from biofilm affect the removal. We grew Strepotococcus sanguinis biofilms on coverslips and titanium discs with varying surface roughness (between 0.02–3.15 μm). Experimental studies were carried out for the biofilm removal using high speed imaging and image analysis to calculate the area of biofilm removed at varying ultrasonic scaler standoff distances from the biofilm. We found that surface roughness up to 2 μm does not adversely affect biofilm removal but a surface roughness of 3 μm caused less biofilm removal. The standoff distance also has different effects depending on the surface roughness but overall a distance of 1 mm is just as effective as a distance of 0.5 mm. The results show significant biofilm removal due to an ultrasonic scaler tip operating for only 2s versus 15-60s in previous studies. The technique developed for high speed imaging and image analysis of biofilm removal can be used to investigate physical biofilm disruption from biomaterial surfaces in other fields. [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.

Most of the researchers have developed Artificial Neural Network (ANN) models to forecast the cutting tool life based on whether it has either a flank wear or a crater wear or a nose wear. In this paper, an attempt has been made to classify the cutting tool wear based on whether it has flank wear, chipped-off cutting edge or a combination of both failures. To obtain the experimental results, both the failures namely flank wear and chipped-off cutting edge have been produced using Electric Discharge Machining (EDM) process. Experiments were carried out using cemented carbide-coated inserts on EN-8 steel and all the responses were acquired by using virtual instruments. The acquired data were analyzed to develop the ANN models to forecast the condition of cutting tool. Vibration and strain data were recorded using accelerometer and strain gauge half-bridge circuit. [ABSTRACT FROM AUTHOR]

Land Use – Land Cover (LULC) classification mapping is an important tool for management of natural resources of an area. The remote sensing technology in recent times has been used in monitoring the changing patterns of land use-land cover. The aim of the study is to monitor the LULC changes in Jodhpur city over the period 1990–2018. Satellite imagery of Landsat 8 OLI (June, 2018) & Landsat TM (Oct, 1990) were used for classification analysis. Supervised classification-maximum likelihood algorithm is used in ENVI software to detect land use land cover changes. Five LULC categories were used, namely- urban area, mining area, vegetation, water bodies and other area (Rock outcrops and barren land). The LULC classified maps of two different periods i.e. 2018 and 1990 were generated on 1 : 50,000 scale. The accuracy assessment method was used to measure the accuracy of classified maps. This study shall be of good assistance to the town planners of Jodhpur city for the purpose of the sustainable development as per the master plan 2031. [ABSTRACT FROM AUTHOR]

Sudden changes in environment causes abiotic and biotic stress due to which farmers are facing problem of decreased yield. The present study was designed to improve yield by alleviating oxidative stress in crops. Silicon is gaining importance in promoting growth and yield of plants. Soluble silica in the form of AgriboosterTM was sprayed on test field of soybean during cultivation. Proline content was found to be decreased significantly in soybean sprayed with soluble silica. Significantly decreased malondialdehyde content was observed in soybean which indicates beneficial role of silica in preventing lipid peroxidation. Soluble silica increased peroxidase activity by increasing water availability and total phenol content was also found to be increased significantly in soybean. So from the present study it can be concluded that silica when applied on crops in soluble form prevent oxidative stress caused due to various environmental factors which may help in better quality product and yield. [ABSTRACT FROM AUTHOR]

Purpose The occupational risk associated with handling of cytotoxic anticancer drugs is well documented and, in many countries, pharmaceutical isolators are used to contain cytotoxic residues during preparation of cytotoxic infusions. Isolators are difficult to clean leading to concerns that cytotoxic contamination from the work area could be transferred to surfaces of products leaving the isolator. This study investigated the surface contamination arising from the preparation of five anticancer drug infusions (Epirubicin, Fluorouracil, Cisplatin, Oxaliplatin and Carboplatin) in a pharmaceutical isolator and compared use of a conventional syringe and needle technique with a closed-system drug transfer device (CSDTD). Methods Wipe samples were taken over 1 week from pre-defined areas in the isolator, gloves, preparation mats, and also from the surfaces of prepared cytotoxic infusion bags and pre-filled syringes to obtain baseline surface contamination data. Following operator familiarisation, the CSDTD was then introduced and sampling repeated for a further week (intervention period). The samples obtained were analysed using validated HPLC-UV, HPLC-FL and ICP-MS techniques, as appropriate. Results All surfaces sampled during baseline, including external surfaces of infusions and syringes, were contaminated with each marker drug. During the intervention phase, isolator surfaces were free from detectable contamination and the contamination measured on gloves, preparation mats and surface of infusions was markedly reduced. The frequency of contamination on syringe and infusion surfaces was also lower. Conclusion Surface contamination from cytotoxic infusion preparation in a pharmaceutical isolator was significant and could transmit cytotoxic residues to patient and public areas via infusion surfaces. The frequency and amount of contamination were reduced by the CSDTD. [ABSTRACT FROM AUTHOR]