Measurement of background radiation in Jhapa, Ilam, Panchthar, and Taplejung districts of Nepal

In this study, we investigated the levels of background radiation in different locations across the Eastern part of Koshi province, specifically in Taplejung, Panchthar, Ilam, and Jhapa. We used a portable Geiger Muller counter to collect data from twenty different locations, with five sites taken from each district. The average absorbed dose rate was found to be 0.243±0.035 mSv/y. The highest measured value of absorbed dose was 0.335±0.041 mSv/y at Pathivara temple in Taplejung, and the lowest was found to be 0.197±0.039 mSv/y at Kakarvita, Jhapa. The results suggest that these four districts do not pose any radiation risk because it was below the threshold of risk (1mSv/y). We also measured the variation of absorption dose with altitude which is positively correlated with altitude with a correlation coefficient of +0.57. This might be because of the surge in cosmic radiation with an increase in altitude

Measurement of background radiation in Jhapa, Ilam, Panchthar, and Taplejung districts of Nepal

In this study, we investigated the levels of background radiation in different locations across the Eastern part of Koshi province, specifically in Taplejung, Panchthar, Ilam, and Jhapa. We used a portable Geiger Muller counter to collect data from twenty different locations, with five sites taken from each district. The average absorbed dose rate was found to be 0.243±0.035 mSv/y. The highest measured value of absorbed dose was 0.335±0.041 mSv/y at Pathivara temple in Taplejung, and the lowest was found to be 0.197±0.039 mSv/y at Kakarvita, Jhapa. The results suggest that these four districts do not pose any radiation risk because it was below the threshold of risk (1mSv/y). We also measured the variation of absorption dose with altitude which is positively correlated with altitude with a correlation coefficient of +0.57. This might be because of the surge in cosmic radiation with an increase in altitude

Village Baseline Study: Site Analysis Report for Vaishali, Mukundpur Village, India

The baseline effort consists of three components – a household survey, village study and organisational survey. The household baseline survey, a quantitative questionnaire on basic indicators of welfare, information sources, livelihood/agriculture/natural resource management strategies, needs and uses of climate and agricultural-related information and current risk management, mitigation and adaptation practices, was implemented by CCAFS partners in 35 sites (245 villages) with nearly 5,000 households in 12 countries to date. CCAFS partners are implementing village baseline studies (VBS) and organisational surveys in one out of the seven villages within each CCAFS site where the household survey was implemented. The plan is to revisit these villages in roughly 5 years, and again in 10 years, to monitor what changes have occurred since the baseline was carried out. The goal is not to attribute these changes to the program, but to be able to assess what kinds of changes have occurred and whether these changes are helping villages adapt to, and mitigate, climate change. The focus of this site analysis report is the VBS. To date, seventeen VBS were conducted. The VBS aims to provide baseline information at the village level about some basic indicators of natural resource utilisation, organisational landscapes, information networks for weather and agricultural information, as well as mitigation baseline information, which can be compared across sites and monitored over time

Village Baseline Study: Site Analysis Report for Haryana - Karnal, India

This is the report of the village baseline study of Pakhana in the CCAFS benchmark site of Karnal, India conducted from March 15-17, 2013 to complement an earlier household baseline survey done in the same village. Pakhana is located in the fertile flat land of the Indo-Gangetic plains and has good access to roads, markets, electricity and communication. The community has not experienced a food crisis and 90% of the population enjoys year-round food security. Pakhana benefited from the Green Revolution and has adopted improved varieties and the use of chemical fertilizers and pesticides. However, Pakhana now faces challenges resulting from population growth, deforestation, reduced and variable rainfall, declining soil fertility and organic matter, monocropping, over application of chemical inputs, and depletion of the water table. As a result, access to water resources is more difficult, profits have decreased and production is constrained. Without adjustments, Pakhana’s food security, livelihoods and natural resources will be further strained and threatened

Empirical model for estimation of global solar radiation at lowland region Biratnagar using satellite data

This study proposes to find the regression coefficient of the modified Angstrom type model for the estimation of global solar radiation (GSR) in lowland Biratnagar (Lat. 26.5º N, Long. 87.3º E and Alt. 72m) using relative sunshine duration and satellite data of GSR. Using the regression technique, the empirical constants 0.29 and 0.56 are found in the modified Angstrom model. Furthermore, the Modified Angstrom model along with other linear models such as Glover and McCulloch model, Page model, Rietveld model, and Turton's model are statistically assessed to evaluate the significance of models. Statistical tests like MPE, MBE, RMSE, and CC reveal that all these models are statistically significant. These findings can be utilized for other locations with a high confidence level at the similar climatic locations of Nepal. BIBECHANA 18 (1) (2021) 193-20

Empirical model for estimation of global solar radiation at lowland region Biratnagar using satellite data

This study proposes to find the regression coefficient of the modified Angstrom type model for the estimation of global solar radiation (GSR) in lowland Biratnagar (Lat. 26.5º N, Long. 87.3º E and Alt. 72m) using relative sunshine duration and satellite data of GSR. Using the regression technique, the empirical constants 0.29 and 0.56 are found in the modified Angstrom model. Furthermore, the Modified Angstrom model along with other linear models such as Glover and McCulloch model, Page model, Rietveld model, and Turton's model are statistically assessed to evaluate the significance of models. Statistical tests like MPE, MBE, RMSE, and CC reveal that all these models are statistically significant. These findings can be utilized for other locations with a high confidence level at the similar climatic locations of Nepal. BIBECHANA 18 (1) (2021) 193-20

Multimorbidity in Diabetic Patients Admitted to a Tertiary Care Center: A Descriptive Cross-sectional Study

Introduction: Multimorbidity is defined as the co-occurrence of two or more chronic conditions in the same individual. Type 2 Diabetes Mellitus rarely occurs without coexisting diseases. With an increasing elder population and longevity, elder adults have a higher prevalence of chronic morbidity, thus increasing the chances of experiencing more than one non-communicable chronic condition, where the impact of multimorbidity is greater than the cumulative effect of the single condition. The study aimed to find out the prevalence of multimorbidity in diabetic patients admitted to a tertiary care centre. Methods: A descriptive cross-sectional study was conducted utilising hospital records of patients with type 2 diabetes mellitus admitted to the Department of Medicine from 1 April 2021 to 1 April 2022. Ethical clearance was obtained from the Institutional Review Committee of the same institute (Reference number: 12082022/07). The diagnosed cases of type 2 diabetic patients aged more than 18 years and confirmed with serum glucose levels were included in the study. Convenience sampling was used. Point estimate and 95% Confidence Interval were calculated. Results: Out of the 107 diabetic patients, multimorbidity was present in 75 patients (70.10%) (61.42-78.77, 95% Confidence Interval). Conclusions: The prevalence of multimorbidity is higher than the similar studies done in similar settings

Porous activated carbon materials from Triphala seed stones for high-performance supercapacitor applications

Porous activated carbon materials derived from biomass could be the suitable materials for high-rate performance electrochemical supercapacitors as it exhibits high surface area due to well-defined pore structure. Here, we report the novel porous activated carbon from Triphala seed stones by chemical activation with zinc chloride at different carbonization temperature (400-700 °C) under the nitrogen gas atmosphere. The activated carbon was characterized by Fourier transform-infrared (FTIR) spectroscopy, Raman scattering and scanning electron microscopy (SEM). Nitrogen adsorption-desorption measurements was used to study the surface properties (effective surface areas, pore volumes and pore size distributions). The electrochemical measurements were performed in an aqueous 1 M sulphuric acid (H2SO4) solution in a three-electrode cell set up. Triphala seed stones-derived porous carbon materials with well-defined micro- and mesopores exhibit high specific surface area ranges from 878.7 to 1233.3 m2 g-1 and total pore volume ranges from 0.439 to 0.626 cm3 g-1. The specific capacitance obtained by electrochemical measurement experiment was 208.7 F g-1 at 1 A g-1. These results indicate that the prepared nanoporous activated carbon material from Triphala seed stones would have significant possibility as supercapacitor electrode material for high-energy-storage supercapacitor applications

Porous activated carbon materials from Triphala seed stones for high-performance supercapacitor applications

Porous activated carbon materials derived from biomass could be the suitable materials for high-rate performance electrochemical supercapacitors as it exhibits high surface area due to well-defined pore structure. Here, we report the novel porous activated carbon from Triphala seed stones by chemical activation with zinc chloride at different carbonization temperature (400-700 °C) under the nitrogen gas atmosphere. The activated carbon was characterized by Fourier transform-infrared (FTIR) spectroscopy, Raman scattering and scanning electron microscopy (SEM). Nitrogen adsorption-desorption measurements was used to study the surface properties (effective surface areas, pore volumes and pore size distributions). The electrochemical measurements were performed in an aqueous 1 M sulphuric acid (H2SO4) solution in a three-electrode cell set up. Triphala seed stones-derived porous carbon materials with well-defined micro- and mesopores exhibit high specific surface area ranges from 878.7 to 1233.3 m2 g-1 and total pore volume ranges from 0.439 to 0.626 cm3 g-1. The specific capacitance obtained by electrochemical measurement experiment was 208.7 F g-1 at 1 A g-1. These results indicate that the prepared nanoporous activated carbon material from Triphala seed stones would have significant possibility as supercapacitor electrode material for high-energy-storage supercapacitor applications

Federated learning enables big data for rare cancer boundary detection.

Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing