Prevalence and knowledge of hypertension among students of medical college of central Uttar Pradesh, India

Background: Hypertension is one of the biggest health challenges, which is continuously increasing among young adults, especially students. The aim of the present study was to find out the prevalence, associated factors and knowledge of hypertension among undergraduate students of a medical college of a rural area in central Uttar Pradesh, India. Methodology:  A cross-sectional study was conducted in one of the medical college of central Uttar Pradesh, India. Data were collected on socio-demographic and behavioral factors, and anthropometric assessments were carried out using standard equipment and procedures. Results: The present research involved 147 undergraduate medical students with a mean age of 21.9±2.2 years. Knowledge about hypertension was poor, average and good among19.7% (n=29), 76.8% (n=113) and 3.4% (n=5) students, respectively. Mean systolic blood pressure (mean SBP) was 127.07 ± 10.109 mm of Hg with a range 110 to 154mm of Hg, and mean diastolic blood pressure (mean DBP) was 80.5 ± 6.587 mm Hg with a range 68 to 94 mm of Hg. Conclusions: Smoking, alcoholism, non-vegetarian diet, body weight over 60 kgs and waist-hip ratio over 0.9 were recognized as risk factors of hypertension. Hence it needs a powerful surveillance program to find the exact problem

Detection of Wormhole Attack using Hop-count and Time delay Analysis

Abstract- MANET, due to the nature of wireless transmission, has more security issues compared to wired environments. In this paper we specifically considering Tunneling attack which does not require exploiting any nodes in the network and can interfere with the route establishment process. Instead of detecting suspicious routes as in previous methods, we implement a new method which detects the attacker nodes and works without modification of protocol, using a hop-count and time delay analysis from the viewpoint of users without any special environment assumptions. The proposed work is simulated using OPNET and results showing the advantages of proposed work. Index Terms- Ad hoc network, hop-count analysis, network security, Tunneling attack

Impact of health education on knowledge and attitude of self-breast examination among female nursing students

Background: Breast cancer is the most common cancer among women and a leading cause of death worldwide, including in India. Breast cancer usually shows a slow development rate, and when it is recognized in the early stages, successful treatment results can be achieved. Breast self-examination is a screening option for young women. Health awareness programs on screening and early detection are the cornerstones for reducing the morbidity and mortality resulting from breast cancer. Objective: To assess the impact of health education on knowledge and attitude of self-breast examination among nursing students. Study Design: The present interventional study was conducted between September and October 2019. Setting: This study was done among 79 nursing students of a tertiary care hospital situated in a central district of Uttar Pradesh. Main Outcome Measures: The self-reported pre-designed and structured questionnaire was used. It included three sections: 1. Sociodemographic profile 2. Knowledge regarding self-breast examination (SBE) 3. Attitude regarding self-breast examination (SBE). Knowledge and attitude scores were calculated and divided into the poor, average, and good categories. Results: There were 87.3% of girls had prior knowledge of the self-breast examination, while 12.7% of girls were not aware of the self-breast examination. Post-intervention, there was a significant increase (p<0.05) in their knowledge about self-breast examination. Conclusion and Relevance: Planned teaching intervention had a significant impact on the knowledge and attitude of self-breast examination. The knowledge and attitude were poor at the early stages, but it had increased significantly after the health education intervention

Reference Evapotranspiration Retrievals from a Mesoscale Model Based Weather Variables for Soil Moisture Deficit Estimation

Reference Evapotranspiration (ETo) and soil moisture deficit (SMD) are vital for understanding the hydrological processes, particularly in the context of sustainable water use efficiency in the globe. Precise estimation of ETo and SMD are required for developing appropriate forecasting systems, in hydrological modeling and also in precision agriculture. In this study, the surface temperature downscaled from Weather Research and Forecasting (WRF) model is used to estimate ETo using the boundary conditions that are provided by the European Center for Medium Range Weather Forecast (ECMWF). In order to understand the performance, the Hamon’s method is employed to estimate the ETo using the temperature from meteorological station and WRF derived variables. After estimating the ETo, a range of linear and non-linear models is utilized to retrieve SMD. The performance statistics such as RMSE, %Bias, and Nash Sutcliffe Efficiency (NSE) indicates that the exponential model (RMSE = 0.226; %Bias = −0.077; NSE = 0.616) is efficient for SMD estimation by using the Observed ETo in comparison to the other linear and non-linear models (RMSE range = 0.019–0.667; %Bias range = 2.821–6.894; NSE = 0.013–0.419) used in this study. On the other hand, in the scenario where SMD is estimated using WRF downscaled meteorological variables based ETo, the linear model is found promising (RMSE = 0.017; %Bias = 5.280; NSE = 0.448) as compared to the non-linear models (RMSE range = 0.022–0.707; %Bias range = −0.207–−6.088; NSE range = 0.013–0.149). Our findings also suggest that all the models are performing better during the growing season (RMSE range = 0.024–0.025; %Bias range = −4.982–−3.431; r = 0.245–0.281) than the non−growing season (RMSE range = 0.011–0.12; %Bias range = 33.073–32.701; r = 0.161–0.244) for SMD estimation

Landscape transform and spatial metrics for mapping spatiotemporal land cover dynamics using Earth Observation data-sets

Analysis of Earth observation (EO) data, often combined with geographical information systems (GIS), allows monitoring of land cover dynamics over different ecosystems, including protected or conservation sites. The aim of this study is to use contemporary technologies such as EO and GIS in synergy with fragmentation analysis, to quantify the changes in the landscape of the Rajaji National Park (RNP) during the period of 19 years (1990–2009). Several statistics such as principal component analysis (PCA) and spatial metrics are used to understand the results. PCA analysis has produced two principal components (PC) and explained 84.1% of the total variance, first component (PC1) accounted for the 57.8% of the total variance while the second component (PC2) has accounted for the 26.3% of the total variance calculated from the core area metrics, distance metrics and shape metrics. Our results suggested that notable changes happened in the RNP landscape, evidencing the requirement of taking appropriate measures to conserve this natural ecosystem