Life cycle sustainability assessment of crops in India

In India, the modernization in the agricultural sector is continuously growing to meet the food demand of rising population. However, along with addressing hunger, modern agriculture impacts the ecosystem, human health, and resources, due to huge consumption of agrochemicals, and emission-intensive farming hence urges sustainable assessment. Till now, no impact assessment is reported on world's second-largest agricultural country- India. This paper is the first of its kind in evaluating the impact of the cultivation of 21 commonly grown crops that possess high production and emissions in India. The results were discussed in the order of impact parameters in respective years with possible causes and remedial measures. The results showed that rice has topped in maximum indices followed by sugarcane, wheat, and banana. The study forecasted that coconut played a concentrated role in global warming, while potato and sugarcane have a higher impact on water and ozone depletion, respectively. The outcomes of this study suggested appropriate improvements in farming practices, which can bring the emissions down and make the system more sustainable. Besides, these 18 indices were individually assessed for their connection with the 17 sustainable development goals (SDGs) in the aspects of agricultural activities to select the appropriate indices to measure the agricultural sustainability along with the identification of gaps to upgrade the existing indices or formulate a new one. Subsequently, this helps in achieving the SDGs in India with the least impact on the environment without compromising the socio-economic aspects involved in crop production and agricultural systems. © 2021 The Author

Smart Handover with Predicted User Behavior using Convolutional Neural Networks for WiGig Systems

WiGig networks and 60 GHz frequency communications have a lot of potential for commercial and personal use. They can offer extremely high transmission rates but at the cost of low range and penetration. Due to these issues, WiGig systems are unstable and need to rely on frequent handovers to maintain high-quality connections. However, this solution is problematic as it forces users into bad connections and downtime before they are switched to a better access point. In this work, we use Machine Learning to identify patterns in user behaviors and predict user actions. This prediction is used to do proactive handovers, switching users to access points with better future transmission rates and a more stable environment based on the future state of the user. Results show that not only the proposal is effective at predicting channel data, but the use of such predictions improves system performance and avoids unnecessary handovers.Comment: Submitted to IEEE Networ

Pharmacological screening of ethanolic extract of Pithecellobium dulce for antiarthritic activity in Rats

418-424Arthritis is an inflammatory joint disorder in which cartilage of the joint is gradually lost and categorized by swelling of joints, pain, and loss of function. The present study was conducted to explore the antiarthritic activity of ethanolic extract of Pithecellobium dulce against formaldehyde induced at sub plantar region of the left hind paw during days 1 and 3 of the study period. The changes observed in paw diameter during the study period, various biochemical, and haematological parameters were monitored. The Radiographic analysis and histopathology significantly improved after treatment with test extract P. dulce (250 mg/kg, b.w., p.o.) as compared to the standard treatment with indomethacin (10 mg/kg, b.w., p.o.).The results of the current investigation concluded that ethanolic extract of P. dulce possesses significant anti-arthritic activity against formaldehyde induced arthritis model, justifying its therapeutic role in arthritic conditions. The observed antiarthritic activity may be due to the presence of phytoconstituents such as alkaloids and flavonoids. P. dulce significantly suppressed the paw oedema in formaldehyde models (P <0.001). The Histopathological and radiographic studies of joints also showed a protective effect of P. dulce

Pharmacological screening of ethanolic extract of Pithecellobium dulce for antiarthritic activity in Rats

Arthritis is an inflammatory joint disorder in which cartilage of the joint is gradually lost and categorized by swelling of joints, pain, and loss of function. The present study was conducted to explore the antiarthritic activity of ethanolic extract of Pithecellobium dulce against formaldehyde induced at sub plantar region of the left hind paw during days 1 and 3 of the study period. The changes observed in paw diameter during the study period, various biochemical, and haematological parameters were monitored. The Radiographic analysis and histopathology significantly improved after treatment with test extract P. dulce (250 mg/kg, b.w., p.o.) as compared to the standard treatment with indomethacin (10 mg/kg, b.w., p.o.).The results of the current investigation concluded that ethanolic extract of P. dulce possesses significant anti-arthritic activity against formaldehyde induced arthritis model, justifying its therapeutic role in arthritic conditions. The observed antiarthritic activity may be due to the presence of phytoconstituents such as alkaloids and flavonoids. P. dulce significantly suppressed the paw oedema in formaldehyde models (P &lt;0.001). The Histopathological and radiographic studies of joints also showed a protective effect of P. dulce

MoNuSAC2020:A Multi-Organ Nuclei Segmentation and Classification Challenge

Detecting various types of cells in and around the tumor matrix holds a special significance in characterizing the tumor micro-environment for cancer prognostication and research. Automating the tasks of detecting, segmenting, and classifying nuclei can free up the pathologists' time for higher value tasks and reduce errors due to fatigue and subjectivity. To encourage the computer vision research community to develop and test algorithms for these tasks, we prepared a large and diverse dataset of nucleus boundary annotations and class labels. The dataset has over 46,000 nuclei from 37 hospitals, 71 patients, four organs, and four nucleus types. We also organized a challenge around this dataset as a satellite event at the International Symposium on Biomedical Imaging (ISBI) in April 2020. The challenge saw a wide participation from across the world, and the top methods were able to match inter-human concordance for the challenge metric. In this paper, we summarize the dataset and the key findings of the challenge, including the commonalities and differences between the methods developed by various participants. We have released the MoNuSAC2020 dataset to the public

Water, Sanitation, and Hygiene: A Global Imperative for Health

Clean water, proper sanitation, and hygiene (WaSH) can have a significant impact on human health. Lack of financial resources prevent developing nations from making investments in WASH infrastructure, such as water treatment plants and sanitation facilities. Achieving universal access to clean water and sanitation is hampered by poor governance and insufficient policy frameworks. Governments, civil society organisations, and the private sector need&nbsp;to collaborate to invest in infrastructure and technology, promote good hygiene practises, and undertake education and awareness-raising programmes in order to ensure that everyone has access to clean water and sanitation

Saccular cyst – Cause of intermittent stridor in a child: A case report

Saccular cyst is a rare lesion of larynx causing respiratory obstruction and stridor in neonates and infants. Herein we present a case of a 4 year old who presented to us with intermittent respiratory distress and stridor. Fibreoptic bronchoscopy showed the presence of saccular cyst overhanging the anterior part of right vocal cord. Endoscopic marsupialization of cyst is done using laryngeal microdebrider with stripping of cyst lining. Saccular cyst should be considered in the differential diagnosis of children presenting with intermittent stridor

Prevalence of Diabetes Mellitus and its associated risk factors

Background: Type 2 diabetes mellitus (T2DM) is a chronic, debilitating non communicable diseases (NCDs) which has emerged as a leading global health problem. Aim &amp; Objective: To find out the prevalence of known cases of diabetes mellitus and associated risk factors in the study area. Material &amp; Methods: Community-based cross-sectional study was conducted among people living in Barrage colony of Rishikesh, Uttarakhand for a period of 3 months from December 2018 to February 2019. House to house survey was done in all the four blocks (A, B, C, D) of Barrage colony. Total of 815 study participants (both male and female) ≥ 20 years of age were surveyed. Data collected was entered into Microsoft Excel and analyzed using epi info software version 7. Results: The prevalence of DM was found to be high i.e 5.6% among the study participants. Prevalence was significantly more among females as compared to males and significantly increased by aging in both genders. Conclusions: It seems that the prevalence of diabetes is increasing in our region as well as our country and the world. To control DM public health education regarding consumption of balanced diet, increasing physical activity and leading a stress-free life is needed