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Objectives: The purpose of this study is to explore and evaluate the knowledge, attitude, and practice of using antibiotics among the community in the Eastern Province, of Saudi Arabia. Methods: A cross-sectional study was conducted, from February 2022 through March 2022, among people in Eastern Province, Saudi Arabia. Results: The study population was 753 of the Saudi community. The questionnaire used open-ended and multiple-choice questions. Out of 753 participants, only 254 (55.6%) think that antibiotics can treat a bacterial infection, whereas 163 (35.7%) and 82 (17.9%) think it treats viral and fungal infections respectively. 26 (5.7%) of the respondents think that they should be stopped when the antibiotics are finished, while 72 (15.8%) think that they should be stopped when the symptoms disappear. The most common side effect in the respondent's opinion was diarrhea 183 (40%), followed by 168 (36.76%) antibiotics resistance. The major reason for taking antibiotics without a prescription was found to be mild symptoms 28 (50.90%), adequate information 21 (38.18%), difficulty in taking appointments 17 (30.90%), long waiting hours during the hospital visits 15 (27.27%). 169 (36.9%) kept the leftover antibiotics for reuse. The most common antibiotics used for self-medication were found to be Amoxicillin and clavulanic acid 23 (41.8%), followed by Amoxicillin 9 (16.36%). Knowledge of antibiotic resistance was highest in the age group 20-30 (62.7%) (P < 0.05). Conclusion: People in Saudi Arabia show a high awareness of antibiotics' proper usage, and this returns to the great awareness campaign held by The Ministry of Health (MoH).

This study assessed antimicrobial prescription at our institute to promote rational antimicrobial use and implement customized antimicrobial stewardship programs. This study is a cross sectional point-prevalence survey on antimicrobial utilisation conducted at HAH Centenary hospital, New Delhi in April, 2019, over a period of 3 days. All in-patients were included in the analysis. However, neonates, emergency room patients and palliative care patients, orders for anti-viral, anti-fungal, anti-tubercular and anti-parasitic medications were excluded. SPSS version 13.0 was planned to be used for analysis of the statistical data. The number of patients admitted at the point of time of our survey was 217, out of which 101 (46.54%) patients were receiving antimicrobial agents (AMA) with 160 (73.73%) AMAs prescribed. 50 patients (49.5%) were prescribed AMAs for infections, whereas, 49 patients (48.51%) were prescribed AMAs prophylactically and 2 (1.98%) patients received AMAs for reasons not defined. The intensive care units exhibited 93.33% patients receiving antimicrobials. The most common indication was intra-abdominal infections (32.40%). The most commonly used antibiotics were beta-lactam antibiotics (60.62%). The study suggests a high rate of antimicrobial use and highlights areas for intervention for rational antimicrobial use. We propose to sensitise the government on initiating a national antimicrobial stewardship program such as the Global Point Prevalence Survey and facilitate evidence-based antimicrobial practice.

Background: Reports of local and systemic side-effects of COVID-19 vaccination may play an important role in public confidence in the acceptance of the COVID-19 vaccine booster dose. Methods: We conducted a retrospective cross-sectional study among adults living in Eastern Province of Saudi Arabia. A link to the survey was distributed to community members via WhatsApp, SMS, or e-mail. Participants' general and demographic information was also collected, as well as information about any local and systemic side-effects reported following vaccination. Results: A total of 370/390 (94.87%) of respondents reported one or more side-effects. Pain or redness at the site of injection (88.92%), fatigue (43.78%), body pain fever (37.84%), and headache (15.95%) were the most commonly reported side-effects. Moreover, 2.43% of the participants reported side-effects needed to see a physician; only four were admitted to the hospital. The non-healthcare respondents (n=273 (97.15%), OR (95% CI) = 5.22 (2.02, 13.48, P

This research paper presents the development and analysis of a multifaceted smart grid prototype. It combines various technologies for the smart grid operation. The first technology is environmental analysis of smart grid and solar panel cleaning. Secondly, radio-frequency identification (RFID)-based security and access control system has been integrated for smart grid. The third component is internet of things (IoT)-based energy monitoring and load management. For environmental analysis sensors such as temperature, humidity, light-dependent resistor, and flame sensors are connected to a NodeMCU controller for real time monitoring. Moreover, IoT based solar cleaning system is developed in the form of prototype with the help of Blynk and servo motor. The second component of prototype is smart security system which is developed with the help of Arduino and RFID module to facilitate secure access control. The third part of prototype employs voltage and current sensors with an ESP32 microcontroller and the Blynk application for real-time energy consumption analysis. This setup enables remote monitoring of voltage, power dynamics, and consumption patterns in a smart grid. It also offers an IoT based solution for load management and load shedding within the smart grid. The complete prototype overall demonstrates a comprehensive approach to 1) smart grid management, 2) environmental analysis, 3) security, and 4) energy monitoring. [ABSTRACT FROM AUTHOR]

Objectives: The present study was conducted to examine the prevalence of tobacco smoking among students' of different departments of private medical science college at Dammam, as well as to assess students' attitude, practice, knowledge, and awareness towards smoking and its harmful effects. Materials and Methods: A cross-sectional study was performed at Mohammed Al-Mana College for Medical Sciences (MACHS) in February 2020. Data were obtained through adopted pretested validated questionnaire based on the Global Adult Tobacco Survey. The questionnaire contains demographic details, smoking behavior, knowledge, and behavior attitude toward smoking. Results: A total of 388 students completed the questionnaire out of them 108 males (27.8%) and 280 females (76.2%), the prevalence ratio of tobacco use 19.84%. The prevalence ratio of female current smokers was 7.9%, whereas male 11.8%, even though the number of female participants were high. Female students had better knowledge in comparison with male students regarding the harmful effects of tobacco smoking on health (78.7% vs. 82.8%; P ≤ 0.001), and as a risk factor of brain thrombosis (59.2% vs. 60%; P ≤ 0.001), gastric ulcer (55.5% vs. 62.1%; P ≤ 0.001), asthma (62.9% vs. 72.1%; P ≤ 0.001), and lung cancer (81.4% vs. 86.7%; P ≤ 0.001). Conclusion: The prevalence of smoking tobacco was relatively low among MACHS students who had good general knowledge regarding the harmful effects of smoking tobacco. This study results showed the harmful effects of smoking and can be used as a basis for the development of tobacco education programs at MACHS and any other institution for providing professional support for students to quit smoking.

Isoniazid is the most commonly used drug for treatment of tuberculosis, and is administered individually or in combination with other drugs as standard first line therapy. Offsetting its efficacy, severe adverse effects, especially peripheral neuropathy and hepatotoxicity, are associated with isoniazid therapy, limiting its use in tuberculosis. Isoniazid is acetylated in vivo producing hydrazine and acetyl hydrazine, which are responsible for hepatotoxicity. Marked pharmacogenetic differences in acetylation have been reported among different population across the globe. This study evaluates isoniazid acetylation patterns in tuberculosis patients receiving DOT therapy under the Revised National Tuberculosis Control Program (RNTCP) in a specialized tuberculosis hospital in north India. Of 351 patients from whom samples were taken for biochemical analysis of adverse events, 36 were assessed for acetylation patterns. Blood samples were taken 1 h after administration of a 600 mg dose of isoniazid, and plasma concentrations of isoniazid were determined using a validated HPLC method. Of these 36 patients, 20 (55.56%) were slow acetylators and 16 (44.44%) were fast acetylators. Our results are consistent with those of an earlier study conducted in a different region of India. Most biochemical changes produced during long-term isoniazid therapy resolve after therapy is terminated.

Purpose: Understanding the appearance of anti-tubercular drug-related adverse drug reactions (ADRs) in patients receiving tuberculosis (TB) treatment is important, and may be related to morbidity and mortality if not recognized early. Here, we aimed to characterize the mechanisms underlying adverse drug reactions due to combination anti-tuberculosis therapy of the Revised National Tuberculosis Control Program (RNTCP). Methods: This was a prospective observational study conducted in 9 DOTS centers of New Delhi, India. All enrolled TB patients receiving first-line tuberculosis treatment as per RNTCP guidelines were monitored for ADRs. All ADRs that appeared during the treatment were recorded and analyzed. Results: The study included 1011 TB patients on anti-TB treatment under DOTS. According to Naranjo’s probability scale, of a total 351 (34.72%) reported adverse events, 102 (10.09%) were definite, 59 (5.83%) probable, 123 (12.17%) possible, and 67 (6.63%) doubtful. On the Hartwig severity scale, of the 351 adverse drug events, 225 (22.26%) were mild, 105 (10.38%) were moderate, and 21 (2.08%) were severe. Out of 102 reported adverse drug reactions, 81 (79.41%) were moderate and 21 (20.59%), while 65.28% did not experience any ADRs. Conclusions: Directly Observed Treatment (DOT) is effective and safe compared to daily treatment regimens. Patients receiving DOTS therapy needed close monitoring for adverse events. Therefore, a pharmacovigilance program should be added at the National level to accesses the adverse event incidence.

The integration of the Internet of Medical Things (IoMT) and the Internet of Things (IoT), which has revolutionized patient care through features like remote critical care and real-time therapy, is examined in this study in response to the changing healthcare landscape. Even with these improvements, security threats are associated with the increased connectivity of medical equipment, which calls for a thorough assessment. With a primary focus on addressing security and performance enhancement challenges, the research classifies current IoT communication devices, examines their applications in IoMT, and investigates important aspects of IoMT devices in healthcare. The evaluation extends so far as to examine an IoMT-based system in the healthcare space, highlighting limitations in Industry 5.0 and healthcare institutions. IoMT devices are systematically categorized according to how well they can strengthen infrastructures; this process exposes operational flaws, gaps in the literature, and real-world risks. The importance of this research is in its thorough analysis of the security and operational facets of IoMT devices, with the explicit objective of promoting secure and efficient medical practices. [ABSTRACT FROM AUTHOR]

Software development effort estimation (SDEE) is recognized as vital activity for effective project management since under or over estimating can lead to unsuccessful utilization of project resources. Machine learning (ML) algorithms are largely contributing in SDEE domain, particularly ensemble effort estimation (EEE) works well in rectifying bias and subjectivity to solo ML learners. Performance of EEE significantly depends on hyperparameter composition as well as weight assignment mechanism of solo learners. However, in EEE domain, impact of optimization in terms of hyperparameter tunning as well as weight assignment is explored by few researchers. This study aims in improving SDEE performance by incorporating metaheuristic hyperparameter and weight optimization in EEE, which enables accuracy and diversity to the ensemble model. The study proposed Metaheuristic-optimized Multi-dimensional bagging scheme and Weighted Ensemble (MoMdbWE) approach. This is achieved by proposed search space division and hyperparameter optimization method named as Multi-dimensional bagging (Mdb). Metaheuristic algorithm considered for this work is Firefly algorithm (FFA), to get best hyperparameters of three base ML algorithms (Random Forest, Support vector machine and Deep Neural network) since FFA has shown promising results of fitness in terms of MAE. Further enhancement in performance is achieved by incorporating FFA-based weight optimization to construct Metaheuristic-optimized weighted ensemble (MoWE) of individual multi-dimensional bagging schemes. Proposed scheme is implemented on eight frequently utilized effort estimation datasets and results are evaluated by 5 error metrices (MAE, RMSE, MMRE, MdMRE, Pred), standard accuracy and effect size along with Wilcox statistical test. Findings confirmed that the use of FFA optimization for hyperparameter (with search space sub-division) and for ensemble weights, has significantly enhanced performance in comparison with individual base algorithms as well as other homogeneous and heterogenous EEE techniques. [ABSTRACT FROM AUTHOR]