Search

Background: The husband has a great role to play in the antenatal care of his wife during pregnancy. Male spouse involvement is crucial and essential in utilization of the services and benefits, antenatal services to the maximum by the woman. The male spouse involvement will have positive impact on reproductive and child health. The extent of involvement of male spouse depends on the gender role attitudes and the social network. Objective: To assess the involvement of Male spouse in Antenatal care. Methodology: A community based cross-sectional study was conducted in the month of June to November 2023 among 263 Male partners of parous women between the reproductive age 15-45yr, in the urban slum area of BMCRI, Bangalore through simple random sampling technique. A pre-tested, semi-structured, questionnaire was used to collect the data, to assess their involvement during antenatal care. Data collected was entered in MS Excel and analysis was done using SPSS version 21.0. Results: In our study, 84% were actually present at the hospital during the delivery and 82.5% had good practice of taking appointment for ANC visits of their wives. About 77.6% were aware of pregnancy related danger signs. But only 35% participants accompanied their wives to ANC visit at least four times. Conclusion: There is a need to recognize importance and positive impact of male participation in antenatal care. Knowledge and attitude of men are the prime determinants of their level of participation in antenatal care.

Analyzing how AI will change HRM strategies is the focus of this research. We may achieve our goals by concentrating on the following: precision, automation, processing capacity and power, real-time experience, customization, and saving time and money. The possible advantages of AI adoption are the target of the study. A well-structured online survey is utilized to gather data from 300 IT employees in the city of Coimbatore. The study presents a new research framework that makes use of AMOS version 21 and IBM SPSS version 21 for analysis. The outcomes show that factors like Personalization, Computing Power and Capacity, and Accuracy have a substantial impact on Time-Saving and Cost Reduction, however factors like Real-Time Experience and Automation do not. This unique addition of the study’s is to investigate the concrete results of implementing artificial intelligence technologies into human resource management procedures. The study delves deeply into the expected results and interrelationships of artificial intelligence implementation in human resource management by concentrating on critical variables including Computing Power & Capacity, Precision, Real-time experience, Time-Saving and Cost Saving, Automation, and Personalization.

The objective of this study is to enhance the precision of AI virtual systems by implementing Novel Hand Gesture Recognition techniques in comparison to Convolutional Neural Network. Materials and Methods: To recognise hand motions, a Convolutional Neural Network with distinct training and testing stages is utilized. The average Gpower for the test is between 0.05 and 0.85, or around 85%. Sample size is determined as 27,455 for each group using G Power 3.1 software (G Power setting parameters: α=0.05 and power=0.85). Results and Discussion: Novel Hand gesture recognition 92.60% identifies between objects and boosts the observed accuracy with a statistically non-significant value of p=0.123 (p>0.05) in comparison to the convolutional neural network's 88.59%. Conclusion: Comparison of the Novel Hand gesture Recognition algorithm and Convolutional Neural Network in terms of performance that shows Hand gesture recognition has 91.62% with better accuracy.

Leucinodes orbonalis is a monophagous pest on brinjal. However, it is also being reported that it may switch to other Solanaceae plants under the stress of the non-availability of the host for feeding. The larvae feed inside the fruit and reduce its nutritive value, and yield loss may reach up to 90%. The pest has discouraged farmers from growing brinjal, which is a profitable crop labelling it as a devastating pest of brinjal. The management methods use biological means such as the use of natural enemies, and other approaches such as sex pheromones, neuropeptides, improvement of genetically modified crops, and RNA interference tools. Though these methods have faced some challenges in implementation, are harmless, supportable, and also species-specific. In the current review, we have discussed the cultural practices, chemical control, and biological methods that have been used in the past or are currently in practice for pest management. Apart from this, we have also discussed a few of the quite recent but hopeful technologies, that can be thought for a tool for the control of L. orbonalis. [ABSTRACT FROM AUTHOR]

ABSTRACT: Context: The annual incidence cases report depicts India as having the highest tuberculosis (TB) burden globally. Following a programmatic change, the daily fixed-dose combination (FDC) anti-TB treatment regimens were introduced by the Indian government's National Tuberculosis Elimination Program (NTEP). Aims: The aim of the study was to assess the treatment outcomes among drug-sensitive pulmonary TB patients receiving daily FDC drugs and the associated factors influencing the treatment outcomes. Settings and Design: A prospective study was conducted among 300 drug-sensitive pulmonary TB cases in the Bruhat Bengaluru Mahanagara Palike (BBMP) area. Materials and Methods: The TB units and designated microscopic centers (DMCs) were selected by multistage random sampling. Data were collected through a pre-tested and semi-structured questionnaire. Patients were followed up until treatment completion. Statistical Analysis Used: Data were compiled and analyzed using IBM Statistical Package for Social Sciences (SPSS) statistics version 20.0. Descriptive statistics and the Chi-square test were used for interpretation. A P -value less than 0.05 was considered statistically significant. Results: Around 86.33% of patients were cured, 4% had completed treatment, and 1% had treatment failure. Older age, human immunodeficiency virus (HIV) reactive status, alcohol intake, tobacco use, and migrants were associated with poor outcomes. Conclusions: The daily FDC regimen had better outcomes than intermittent regimens. Smokers, alcoholics, migrants, and patients with co-morbidity need to be given priority in management as they are prone to poorer outcomes. [ABSTRACT FROM AUTHOR]

The intrusion detection system (IDS) plays an imperative role in defending the network from attacks. But, the IDS data is imbalanced, making the process complex for detecting the attacks accurately. According to these problems, this study proposes a network intrusion detection system based on an enhanced synthetic minority oversampling technique (SMOTE) and lightweight hybrid CAE (convolutional auto encoder)-ELM (extreme learning machine) model. Initially, the normalization of the original data is performed to avoid the influence of the maximum and minimum values. Secondly, an enhanced SMOTE is employed for solving the issues of the less detection rate of minority-attacks because of less training data. Here, the war strategy optimization (WSO) is incorporated with the SMOTE to design a novel WSO-based SMOTE technique for balancing the dataset. The three major steps utilized in WSO-based SMOTE are WSO based clustering, filtering and over-sampling. Then, the Information gain and fisher score based features extraction is employed for the reduction of computational complexity prior to the intrusion detection. Finally, the lightweight hybrid CAE-ELM model is executed for attack detection. CAEs are one of the most commonly used learning models because of their ability to construct a higher-level feature representation from the input data. Another model used in intrusion detection is the ELM, which provides an acceptable discrimination performance as well as a fast speed of learning. The performance of the proposed NIDS model is tested on the two benchmark datasets and achieved better accuracies of 99.21% and 99.15% on the UNSW-NB15 and CSE-CIC-IDS2018 datasets. [ABSTRACT FROM AUTHOR]

Background: Gallstones are the most important risk factor for gall bladder carcinoma. Understanding the burden of asymptomatic gallstone and its associated factors is essential to identify risk group likely to develop complication. Objectives: To estimate the burden of asymptomatic gallstone (AGS) and assess the factors contributing towards the same. Material and methods: A cross-sectional study was done during February to August 2023 in a tertiary care teaching hospital among adults aged above 18 years undergoing ultrasound of the abdomen as a part of routine master health check-up. A questionnaire was used collect the socio-demographic details, medical history and laboratory investigation. A total 1300 individuals were screened for AGS and included for analysis. Results: The mean age of study participants was 55.99 ± 15.83 years. The study found 36 individuals with AGS i.e 2.8% (95% CI:1.9-3.8%). The mean size of gallstone was 8.19 ± 4.6 mm with a range of 2 to 25 mm. Medical condition such as diabetes, hypertension and body mass index was found to be associated with AGS (p