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The COVID 19 pandemic has challenged the humankind’s livelihood, physical health, mental health, employment, and economy. Lockdowns, quarantines, online teaching, and learning have become new normal. Negativities have been spread across the globe and society by the pandemic. The negative effects caused a confused mindset, fear, anxiety, stress, and other psychological complications amongst the people especially among the Health Care Workers (HCWs), children, elderly people, and Frontline Workers (FLWs). This research work examines the levels of Occupational Stress (OS), and psychological well-being (PWB) of HCWs and police personnel during the pandemic and the relationship between OS and PWB. Further, the study analyzed the role of Positive Psychological Capital (PPC) as a mediator and Emotional Quotient (EQ) as a moderator in the relationship between OS and PWB. Positive Psychological Capital (PPC) characteristics of the respondents such as having faith in one's ability, and performance, willingness to succeed or attain the goals framed, ability to bounce back from the hard times, and their optimism about the future have helped them to tackle the stress caused by the pandemic and to maintain a better state of psychological wellbeing in the fight against the pandemic.

The ongoing COVID-19 pandemic has considerably promoted the usage of Digital Financial Services (DFS) in India. Therefore, exploring the various determinants influencing the DFS users is crucial for the DFS providers to understand their customers better. This study aims to identify, measure, and validate the determinants of Digital Financial Literacy (DFL) from the Indian adults who use Digital Financial Services. A sample of 384 adult DFS users from India was surveyed using a self-administered questionnaire in 2021. A multidimensional scale was developed to measure the Digital Financial Literacy in this study. The results exhibit that Digital Knowledge, Financial Knowledge, Knowledge of DFS, Awareness of Digital Finance Risk, Digital Finance Risk Control, Knowledge of Customer Right, Product Suitability, Product Quality, Gendered Social Norm, Practical Application of Knowledge and Skill, Self-determination to use the Knowledge and Skill and Decision Making are the determinants of DFL among the adults in India. Further, the users of DFS without DFL will face numerous challenges such as inability to complete the transaction, financial loss and privacy breach, etc. Hence, the study concludes that DFL is prerequisite to use DFS effectively.

Brain tumours (BTs) are severe neurological disorders. They affect more than 308,000 people each year worldwide. The mortality rate is over 251,000 deaths annually (IARC, 2020 reports). Detecting BTs is complex because they vary in nature. Early diagnosis is essential for better survival rates. The study presents a new system for detecting BTs. It combines deep (DL) learning and machine (ML) learning techniques. The system uses advanced models like Inception-V3, ResNet-50, and VGG-16 for feature extraction, and for dimensional reduction, it uses the PCA model. It also employs ensemble methods such as Stacking, k-NN, Gradient Boosting, AdaBoost, Multi-Layer Perceptron (MLP), and Support Vector Machines for classification and predicts the BTs using MRI scans. The MRI scans were resized to 224 × 224 pixels, and pixel intensities were normalized to a [0,1] scale. We apply the Gaussian filter for stability. We use the Keras Image Data Generator for image augmentation. It applied methods like zooming and ± 10% brightness adjustments. The dataset has 5,712 MRI scans. These scans are classified into four groups: Meningioma, No-Tumor, Glioma, and Pituitary. A tenfold cross-validation method helps check if the model is reliable. Deep transfer (TL) learning and ensemble ML models work well together. They showed excellent results in detecting BTs. The stacking ensemble model achieved the highest accuracy across all feature extraction methods, with ResNet-50 features reduced by PCA (500), producing an accuracy of 0.957, 95% CI: 0.948–0.966; AUC: 0.996, 95% CI: 0.989–0.998, significantly outperforming baselines (p < 0.01). Neural networks and gradient-boosting models also show strong performance. The stacking model is robust and reliable. This method is useful for medical applications. Future studies will focus on using multi-modal imaging. This will help improve diagnostic accuracy. The research improves early detection of brain tumors.

We report a case of a young male from Udupi, Karnataka, presenting with features of bilateral non-granulomatous anterior uveitis with mild vitritis. There was a history of fever and myalgia a month before ocular features, which was partially treated. He also gave a history of being actively involved in the flood relief work in the district, before the onset of fever. This prompted an evaluation of leptospirosis, which came positive. The possibility of leptospira uveitis needs to be considered, especially in cases of non-granulomatous uveitis after floods in areas endemic for leptospirosis, which may otherwise be wrongly labeled idiopathic.

Background. Medication errors have an adverse impact on the healthcare system by increasing patient morbidity and mortality. They are preventable, and educational or technology-based interventions are needed to reduce their prevalence and improve medication safety. We aimed to study the impact of a sensitization programme and a blame-free reporting tool for doctors and nurses on the prevalence and reporting of medication errors in the intensive care units (ICUs) of a tertiary care teaching hospital. Methods. This prospective interventional study was conducted in the ICUs of cardiology, medicine, paediatrics and neonatology. Baseline medication errors were detected by prescription order review and direct observation of administration of medication for 30 days. A sensitization programme was conducted for doctors and nurses in these ICUs, the results were discussed, and a blame-free medication error reporting tool was introduced. Medication charts were modified to remove the transcription process in the cardiology and paediatrics ICUs. The follow-up study was conducted for 30 days in each ICU to monitor the impact of the sensitization programme. Results. The prevalence of medication errors was found to be 334.1/1000 patient observation days. Prescription errors were the most common types of errors at 129.1/1000 patient observation days. The interventions significantly reduced the error rate in all four ICUs. The overall number of prescriptions with errors was reduced from 9.1% (177/1944) to 3.5% (48/1373) and no medication error was reported using the tool. Conclusion. The sensitization programme on medication errors for doctors and nurses may be effective in improving medication safety. The impact was more pronounced in prescription errors. Reporting of medication errors did not improve in this study despite the introduction of a blame-free reporting tool.

Aim: The study designs and fabricates traps with diverse wire mesh colors and shapes for field experiments. It also collects detailed catch data to assess their catch efficiency and determine the most effective design. Methodology: Experimental fish traps were fabricated utilizing four distinct colors (Light green, Dark green, White and Orange) and three different shapes (rectangle, square and circle). Fishing trials were conducted in selected fishing villages of Thereshpuram, with the traps operated fortnightly from June 2022 to May 2023. The catch rate per trip (CPUE) was calculated using the Total catch (in numbers) divided by the Unit Effort (White, 1987). An economic analysis of trap fishery was also performed based on gross revenue and total cost (Geetha et al., 2014). Results: The traps' overall catch per unit effort (CPUE) was recorded at 0.48Nos hr-1. Siganus canaliculatus emerged as the dominant species among the fishes trapped, constituting 16% of the total catch. Regarding trap color, the highest CPUE was observed with traps of dark green color (0.63 Nos hr-1), followed by light green (0.51 Nos hr-1), white (0.49 Nos hr-1) and orange (0.38 Nos hr-1). Economically, the performance of the trap fishery was evaluated using indicators such as operating cost/year, fixed cost, gross revenue and profit cost ratio. The success of the trap fishery was further emphasized by a benefit-cost ratio (BCR) of 3.50. Interpretation: Dark green-colored, square-shaped traps show promise in significantly enhancing fishermen's profits due to their higher catch per unit effort (CPUE) compared to other colors. Moreover, dark green traps may offer ecological advantages by blending into natural surroundings. This study highlights their potential and provides practical insights for fishermen to make informed gear choices, considering factors like color and shape. Key words: BCR, Color, CPUE, Shape, Trap

Because of its superior thermal properties and multiple prospective uses, nanofluids had sparked the interest of investigators. Addition of nanoparticles to refrigerants and lubricants improves thermal characteristics and lowers power wastage. In this paper R134a refrigerant is added with nanoparticle CuO in the concentration of 0.1%v to 0.5%v and its performance is evaluated. The suction pressure of R134a at 32C is 9% higher than R134a+0.1nm and 17% higher than R13a+0.5nm.The discharge temperature of R134a is more than nano refrigerant. Due to this, the power consumption of R134a is more than nano refrigerant. By adding nanoparticles to refrigerant, the power consumption at 28C is 23% less than R134a which shows nanoparticles works normally when mixed with R134a. Due to high thermal conductivity of nanoparticles, the coefficient of performance of R134a is 35% less than R134a+0.1nm and 41% less than R134a+0.5nm.

Aluminium metal matrix composites are generally produced employing stir casting technique. The effect of stirrer blade on stir casting of aluminium composite with 12 wt% SiC, 4 wt% magnesium and 2 wt% copper was observed. The composites were prepared with 6061 base metal using three different design of stirrer blade which created different vortex fluid flow while stirring. Due to high density of SiC particles, it tries to settle in lower part of the molten metal matrix. Hence change in vortex technique by stirrer design modification can have influence on the mechanical and microstructure behaviour of the composites. The aluminium SiC composite are evaluated by mechanical properties and microstructure analysis based on stirrer blade design used while stir casting. The change in blade stirrer shows variation in testing tensile strength and hardness. The optical microstructure and SEM images were observed to analyze the cast structure and reinforcement distribution in the composites. The SiC particles were appeared to distribute along the grain boundaries of the composite and also cast defects were observed. Composite prepared with alternate peddle blade produced best mechanical properties.

Background: Prevalence of cardiovascular diseases are reported to be high in police force, which constitute a special occupational group. \"Partners in Prevention\" was a special surveillance activity carried out among the personnel of the Department of Police, Government of Puducherry by JIPMER, Puducherry. The present study reports the prevalence of metabolic syndrome and other cardiovascular risk factors in this group. Materials and Methods: The design was cross-sectional analytical study covering 1618 policemen during 2013-15. A pre-tested questionnaire was used for collecting data. Anthropometric and biochemical measurements were carried out using standard techniques. Metabolic syndrome was diagnosed using the International Diabetes Federation (IDF) consensus worldwide definition. Statistical analysis was performed using the IBM- SPSS 21 software. Results: The mean (SD) age of the participants was 45.7 (10.1) years. Majority (90%) of the participants were males and were in the age group of 30-59 years. Metabolic syndrome was observed in two-fifth (42%) of the study population. We found the prevalence as: hypertension (45.2%), abnormal HDL levels (62.3%), diabetes (34.7.1%), and high body mass index of >=25 kg/m2 (60.5%). Conclusion: Our study identified that police personnel were having high CVDs and risk factors. It calls for an urgent need to initiate screening and secondary prevention programmes.

Magnesium based alloys are some of the widely used light weight metals in vehicles and aerospace industries, but these materials are having low strength to weight ratio when compared to aluminium. To enhance their strength to weight ratio, some ceramic materials like carbides and oxides of metals are added as reinforcements. In this work, AZ31 magnesium alloy is reinforced with 1%, 2% and 3% of Groundnut Shell Ash particles (GSAp) through powder metallurgy. Micro hardness and compressive strength are studied and the microstructural analysis is also done. The addition of ash particles as reinforcement has not shown much variation in the strength and hardness. The addition of ash particles of more than 3% leads to crack. The addition of ash particles increases the rate of corrosion.