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- 저자 : Anil Kumar Sahu (검색결과 3 건)
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Damodar Sahu,Varsha Ranjan,Nalini Chandra,Saritha Nair,Anil Kumar,Elangovan Arumugam,Mendu Vishnu Vardhana Rao 대한예방의학회 2022 예방의학회지 Vol.55 No.4
Objectives: This study provides insights on the impact of a targeted intervention (TI) programme on behaviour change among injecting drug users (IDUs) in India. Methods: This paper examined the data from the Integrated Biological and Behavioural Surveillance 2014-2015 for IDUs in India. Logistic regression was performed to understand the factors (TI programme services) that affected injecting risk behaviours by adjusting for covariates. Propensity score matching was conducted to understand the impact of the TI programme on using new needles/syringes and sharing needles/syringes in the most recent injecting episode by accounting for the covariates that predicted receiving the intervention. Results: Participants who received new needles and syringes from peer educators or outreach workers were 1.3 times (adjusted odds ratio, 1.29; 95% confidence interval [CI], 1.09 to 1.53) more likely to use new needles/syringes during most recent injecting episode than participants who did not receive needles/syringes. The matched-samples estimate (i.e., average treatment effect on treated) of using new needles in the most recent injecting episode showed a 2.8% (95% CI, 0.0 to 5.6) increase in the use of new needles and a 6.5% (95% CI, -9.7 to -3.3) decrease in needle sharing in the most recent injecting episode in participants who received new needles/syringes. There was a 2.2% (95% CI, -3.8 to -0.6) decrease in needle sharing in the most recent injecting episode among participants who were referred to other services (integrated counselling and testing centre, detox centres, etc.). Conclusions: The TI programme proved to be effective for behaviour change among IDUs, as substantiated by the use of new needles/syringes and sharing of needles/syringes.
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Morin ameliorates myocardial injury in diabetic rats via modulation of inflammatory pathways
Vipin Kumar Verma,Salma Malik,Ekta Mutneja,Anil Kumar Sahu,Vaishali Prajapati,Prashant Mishra,Jagriti Bhatia,Dharamveer Singh Arya 한국실험동물학회 2024 Laboratory Animal Research Vol.40 No.1
Background: High blood glucose levels in diabetes lead to vascular inflammation which accelerates atherosclerosis. Herein, Morin was orally administered in male Wistar rats, at the dose of 40 mg/kg for 28 days, and on the 27th and 28th day, ISO was administered to designate groups at the dose of 85 mg/kg s.c., to induce myocardial infarction. Results: Free radical generation, including ROS, in diabetes following ISO administration, leads to the activation of both intrinsic and extrinsic pathways of apoptosis. Morin significantly (p ≤ 0.05) reduced oxidative stress (GSH, MDA, SOD), cardiac injury markers (CK-MB, LDH), inflammation (TNF, IL-6), and apoptosis (Bax, BCl2, Caspase-3). In addition, it also reduced insulin and blood glucose levels. Akt/eNOS, Nrf2/HO-1, MAPK signaling pathways, and Insulin signal transduction pathways were positively modulated by morin pre-treatment. Conclusions: Morin attenuated oxidative stress and inflammation and also modified the activity of various molecular pathways to mitigate cardiomyocyte damage during ISO-induced MI in diabetic rats.
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EDNN based prediction of strength and durability properties of HPC using fibres & copper slag
Gupta, Mohit,Raj, Ritu,Sahu, Anil Kumar Techno-Press 2022 Advances in concrete construction Vol.14 No.3
For producing cement and concrete, the construction field has been encouraged by the usage of industrial soil waste (or) secondary materials since it decreases the utilization of natural resources. Simultaneously, for ensuring the quality, the analyses of the strength along with durability properties of that sort of cement and concrete are required. The prediction of strength along with other properties of High-Performance Concrete (HPC) by optimization and machine learning algorithms are focused by already available research methods. However, an error and accuracy issue are possessed. Therefore, the Enhanced Deep Neural Network (EDNN) based strength along with durability prediction of HPC was utilized by this research method. Initially, the data is gathered in the proposed work. Then, the data's pre-processing is done by the elimination of missing data along with normalization. Next, from the pre-processed data, the features are extracted. Hence, the data input to the EDNN algorithm which predicts the strength along with durability properties of the specific mixing input designs. Using the Switched Multi-Objective Jellyfish Optimization (SMOJO) algorithm, the weight value is initialized in the EDNN. The Gaussian radial function is utilized as the activation function. The proposed EDNN's performance is examined with the already available algorithms in the experimental analysis. Based on the RMSE, MAE, MAPE, and R<sup>2</sup> metrics, the performance of the proposed EDNN is compared to the existing DNN, CNN, ANN, and SVM methods. Further, according to the metrices, the proposed EDNN performs better. Moreover, the effectiveness of proposed EDNN is examined based on the accuracy, precision, recall, and F-Measure metrics. With the already-existing algorithms i.e., JO, GWO, PSO, and GA, the fitness for the proposed SMOJO algorithm is also examined. The proposed SMOJO algorithm achieves a higher fitness value than the already available algorithm.
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