No abstract

Diabetes Mellitus (DM) which is a chronic disease and difficult to cure. If diabetes is not treated in a timely manner, it may cause serious complications. For timely treatment, an early detection of the disease is of great interest. Diabetes can be detected by analyzing the RR-interval signals. This work presents a methodology for classification of diabetic and normal RR-interval signals. Firstly, empirical mode decomposition (EMD) method is applied to decompose the RR-interval signals in to intrinsic mode functions (IMFs). Then five parameters namely, area of analytic signal representation (AASR), mean frequency computed using Fourier-Bessel series expansion (MFFB), area of ellipse evaluated from second-order difference plot (ASODP), bandwidth due to frequency modulation (BFM) and bandwidth due to amplitude modulation (BAM) are extracted from IMFs obtained from RR-interval signals. Statistically significant features are fed to least square-support vector machine (LS-SVM) classifier. The three kernels namely, Radial Basis Function (RBF), Morlet wavelet, and Mexican hat wavelet kernels have been studied to obtain the suitable kernel function for the classification of diabetic and normal RR-interval signals. In this work, we have obtained the highest classification accuracy of 95.63%, using Morlet wavelet kernel function with 10-fold cross-validation. The classification system proposed in this work can help the clinicians to diagnose diabetes using electrocardiogram (ECG) signals.

Background: Acute respiratory infection includes any infection of the upper or lower respiratory system, as defined by the International Classification of Diseases. Acute respiratory infection is a leading cause of morbidity and mortality in under-five children in developing countries. Objective: This study was undertaken to identify various modifiable risk factors for acute lower respiratory tract infections (ALRI) in children aged from2 months to 5 years. Methodology: This hospital-based case–control study was conducted at Basaveshwarand Sangameshwar general hospital, Gulbarga over 1½. year 200 ALRI cases fulfilling WHO criteria for pneumonia, in the age group of 2 months to 5 years were interrogated for potentially modifiable risk factors as per a predesigned preformed. 200 healthy control children in the same age group were also interrogated. Results: The significant socio-demographic risk factors were incomplete immunization for age, low parental education, low socioeconomic status, and overcrowding (p<0.05 in all). Significant nutritional risk factors includemalnutrition, anemia, and rickets (p<0.05 in all). Significant environmental risk factors were parental smoking, use of biomass fuel, and mud/cow dung flooring (p<0.05 in all). Using multiple logistic regression analysis, the factors which were found to be significantly associated were younger age (p=0.000), anemia (p=0.000), incomplete immunization for age (p=0.002), malnutrition (p=0.00), low literacy level of father (p=0.000), and overcrowding (p=0.000). Conclusion: This study has identified various socio-demographic, nutritional, and environmental modifiable risk factors for ALRI which can be tackled by effective education of the community and appropriate initiatives taken by the government.

From last few decades there are many changes are taking place in the field of medical education moving from traditional method to more towards online/ e-learning method using internet. The advent of electronic devices like mobile, i- pad, laptops and explosion of social media technology provides opportunities for learners to create their own personalised learning experience. To asses the effectiveness of online learning in Anatomy among first MBBS students during COVID-19. A Cross sectional study was conducted among 120 MBBS First year medical students for a period of 6 months (May 2020 to November 2020) at Chamarajanagara Institute of Medical Sciences, Chamarajanagara. Informed consent was obtained from all the students prior to the start of the study. The online classes were conducted due to covid-19 lockdown in our institution from May 2020 as per the guidelines from RGUHS. In the study majority of students had concentration time of 30 min (71.7%), majority of them opined that there as moderate disturbance during online class (53.3%), majority of them opined that they had moderate internet or network issues (53.3%), majority of them used mobile phone for online class (70%). In the study overall effectiveness of online teaching in anatomy among 1 year students was 61.7% and 38.3% opined that it was not effective. The study concludes that online classes were not so effective as students encountered lot of technical problems, reduced attention span, low motivation and lesser understanding in the concepts of subject thought.

The discourse on the ASHA's role centres around three typologies - ASHA as an activist, ASHA as a link worker or facilitator, and ASHA as a community level health care provider. She will counsel women on birth preparedness, importance of safe delivery, breastfeeding and complementary feeding, immunization, contraception and prevention of common infections including Reproductive Tract Infection/Sexually Transmitted Infection (RTIs/STIs) and care of the young child. A cross sectional study was done on 132 ASHA workers selected from 5 random PHCs in Bijapur taluk. Data was collected in a prestructured proforma using interview technique from June to October, 2012. Most of the ASHA workers were not aware about the newer roles and responsibilities been implied on them under various national programmes including the immunization guidelines and schedule. All the ASHA workers were aware about the performance based incentive for the their work in the community and its their right to claim that incentive. Under the cascade model of training to the ASHA, trainings should provide complete knowledge and skills to the trainees within the stipulated time. Quality of training should be enhanced and refresher trainings should be planned regularly.