Forecasting major impacts of COVID-19 pandemic on country-driven sectors: challenges, lessons, and future roadmap.

The pandemic caused by the coronavirus disease 2019 (COVID-19) has produced a global health calamity that has a profound impact on the way of perceiving the world and everyday lives. This has appeared as the greatest threat of the time for the entire world in terms of its impact on human mortality rate and many other societal fronts or driving forces whose estimations are yet to be known. Therefore, this study focuses on the most crucial sectors that are severely impacted due to the COVID-19 pandemic, in particular reference to India. Considered based on their direct link to a country's overall economy, these sectors include economic and financial, educational, healthcare, industrial, power and energy, oil market, employment, and environment. Based on available data about the pandemic and the above-mentioned sectors, as well as forecasted data about COVID-19 spreading, four inclusive mathematical models, namely-exponential smoothing, linear regression, Holt, and Winters, are used to analyse the gravity of the impacts due to this COVID-19 outbreak which is also graphically visualized. All the models are tested using data such as COVID-19 infection rate, number of daily cases and deaths, GDP of India, and unemployment. Comparing the obtained results, the best prediction model is presented. This study aims to evaluate the impact of this pandemic on country-driven sectors and recommends some strategies to lessen these impacts on a country's economy.

Green fodder cultivation improves technical efficiency of dairy farmers in semi-arid tropics of central India: a micro-analysis.

This study assessed the impact of improved green fodder production activities on technical efficiency (TE) of dairy farmers in climate vulnerable landscapes of central India. We estimated stochastic production frontiers, considering potential self-selection bias stemming from both observable and unobservable factors in adoption of fodder interventions at farm level. The empirical results show that TE for treated group ranges from 0.55 to 0.59 and that for control ranges from 0.41 to 0.48, depending on how biases are controlled. Additionally, the efficiency levels of both adopters and non-adopters would be underestimated if the selectivity bias is not appropriately accounted. As the average TE is consistently higher for adopter farmers than the control group, promoting improved fodder cultivation would increase input use efficiency, especially in resource-deprived small holder dairy farmers in the semi-arid tropics.

Classification model for accuracy and intrusion detection using machine learning approach.

In today's cyber world, the demand for the internet is increasing day by day, increasing the concern of network security. The aim of an Intrusion Detection System (IDS) is to provide approaches against many fast-growing network attacks (e.g., DDoS attack, Ransomware attack, Botnet attack, etc.), as it blocks the harmful activities occurring in the network system. In this work, three different classification machine learning algorithms-Naïve Bayes (NB), Support Vector Machine (SVM), and K-nearest neighbor (KNN)-were used to detect the accuracy and reducing the processing time of an algorithm on the UNSW-NB15 dataset and to find the best-suited algorithm which can efficiently learn the pattern of the suspicious network activities. The data gathered from the feature set comparison was then applied as input to IDS as data feeds to train the system for future intrusion behavior prediction and analysis using the best-fit algorithm chosen from the above three algorithms based on the performance metrics found. Also, the classification reports (Precision, Recall, and F1-score) and confusion matrix were generated and compared to finalize the support-validation status found throughout the testing phase of the model used in this approach.

Suitable habitat of wild Asian elephant in Western Terai of Nepal.

BACKGROUND: There is currently very little available research on the habitat suitability, the influence of infrastructure on distribution, and the extent and connectivity of habitat available to the wild Asian elephant (Elephas maximus). Information related to the habitat is crucial for conservation of this species. METHODS: In this study, we identified suitable habitat for wild Asian elephants in the Western Terai region of Nepal using Maximum Entropy (MaxEnt) software. RESULTS: Of 9,207 km2, we identified 3194.82 km2 as suitable habitat for wild Asian elephants in the study area. Approximately 40% of identified habitat occurs in existing protected areas. Most of these habitat patches are smaller than previous estimations of the species home range, and this may reduce the probability of the species continued survival in the study area. Proximity to roads was identified as the most important factor defining habitat suitability, with elephants preferring habitats far from roads. CONCLUSIONS: We conclude that further habitat fragmentation in the study area can be reduced by avoiding the construction of new roads and connectivity between areas of existing suitable habitat can be increased through the identification and management of wildlife corridors between habitat patches.

Development and characterization of dutasteride bearing liposomal systems for topical use.

Dutasteride loaded liposomal system were developed for topical application in order to avoid the side effects associated with the oral administration of the drug. Drug-loaded multilamellar liposomes were prepared using thin-film hydration method followed by sonication and optimized with respect to entrapment efficiency, drug payload, size and lamellarity. The vesicular systems consisting of egg phosphatidylcholine (100 mg), cholesterol (50 mg), and dutasteride (5 mg) showed highest drug entrapment efficiency (94.6%) and drug payload (31.5 µg/mg of total lipids). Mean vesicle size of these liposomes was noted to be 1.82 ± 0.15 µm. Significantly higher skin permeation of dutasteride through excised abdominal mouse skin was achieved via the developed liposomal formulations as compared to hydro-alcoholic solution and conventional gels. The formulation exhibited about seven fold higher deposition of drug in skin. Stability studies indicated that the liposomal formulations were quite stable in the refrigerated conditions for 10 weeks with negligible drug leakage or vesicle size alteration. Results of the current studies exhibited improved and localized drug action in the skin and thus could be formulated as a better option to cure androgenetic alopecia.

Insights into the effects of alpha-synuclein expression and proteasome inhibition on glutathione metabolism through a dynamic in silico model of Parkinson's disease: validation by cell culture data.

Dopaminergic neurodegeneration during Parkinson disease (PD) involves several pathways including proteasome inhibition, alpha-synuclein (alpha-syn) aggregation, mitochondrial dysfunction, and glutathione (GSH) depletion. We have utilized a systems biology approach and built a dynamic model to understand and link the various events related to PD pathophysiology. We have corroborated the modeling data by examining the effects of alpha-syn expression in the absence and presence of proteasome inhibition on GSH metabolism in dopaminergic neuronal cultures. We report here that the expression of the mutant A53T form of alpha-syn is neurotoxic and causes GSH depletion in cells after proteasome inhibition, compared to wild-type alpha-syn-expressing cells and vector control. Modeling data predicted that GSH depletion in these cells was due to ATP loss associated with mitochondrial dysfunction. ATP depletion elicited by combined A53T expression and proteasome inhibition results in decreased de novo synthesis of GSH via the rate-limiting enzyme gamma-glutamyl cysteine ligase. Based on these data and other recent reports, we propose a novel dynamic model to explain how the presence of mutated alpha-syn protein or proteasome inhibition may individually impact on mitochondrial function and in combination result in alterations in GSH metabolism via enhanced mitochondrial dysfunction.