Comprehensive Genomic, Mutation, Phylogenetic, and Statistical Analysis of the Monkeypox Virus Across Multiple Countries.

Our study offers a comprehensive Monkeypox virus (MPXV) analysis, utilizing innovative protocols to uncover potential vulnerabilities. We examine MPXV's epidemiology, link to smallpox, genomics, mutation landscape, clinical features, diagnostics, therapeutics, FDA-approved drugs, clinical trials, and preventive strategies. We used various analytical methods to analyse genome data from the NCBI database (2019-2023) to assess sequence alignment, protein identification, and genome diversity.

Exploring the Multifaceted Potential of L.: A Comprehensive Review of Its Nutritional, Pharmacological, and Environmental Significance.

L. is commonly known as oleaster or Russian olive. It is an economically important plant due to its wide applications and ability to thrive under harsh environmental conditions, including various edaphic and topographical circumstances.

Deep learning-based computational approach for predicting ncRNAs-disease associations in metaplastic breast cancer diagnosis.

Non-coding RNAs (ncRNAs) play a crucial role in breast cancer progression, necessitating advanced computational approaches for precise disease classification. This study introduces a Deep Reinforcement Learning (DRL)-based framework for predicting ncRNA-disease associations in metaplastic breast cancer (MBC) using a multi-dimensional descriptor system (ncRNADS) integrating 550 sequence-based features and 1,150 target gene descriptors (miRDB score ≥ 90). The model achieved 96.

Nanoparticles as catalysts of agricultural revolution: enhancing crop tolerance to abiotic stress: a review.

Ensuring global food security and achieving sustainable agricultural productivity remains one of the foremost challenges of the contemporary era. The increasing impacts of climate change and environmental stressors like drought, salinity, and heavy metal (HM) toxicity threaten crop productivity worldwide. Addressing these challenges demands the development of innovative technologies that can increase food production, reduce environmental impacts, and bolster the resilience of agroecosystems against climate variation.

Autophagy: A New Avenue and Biochemical Mechanisms to Mitigate the Climate Change.

Autophagy is a preserved process in eukaryotes that allows large material degeneration and nutrient recovery via vacuoles or lysosomes in cytoplasm. Autophagy starts from the moment of induction during the formation of a phagophore. Degradation may occur in the autophagosomes even without fusion with lysosome or vacuole, particularly in microautophagosomes.

A comparative analysis of feature selection models for spatial analysis of floods using hybrid metaheuristic and machine learning models.

The research aims to propose a feature selection model for hydraulic analysis as such a model has not been proposed previously. For this purpose, hybrids of three metaheuristic algorithms, particle swarm optimization (PSO), ant colony optimization (ACO), and genetic algorithm (GA) with two machine learning models which are support vector machine (SVM) and K-nearest neighbor (KNN) are employed. The dataset considered was hydraulic having an association with flood and possessed topographic, geo-environmental, and human-induced variables.

Local surface warming assessment in response to vegetation shifts over arid lands of Central Asia (2001-2020).

The Northern Eurasia Earth Science Partnership Initiative (NEESPI) was established to address the large-scale environmental change across this region. Regardless of the increasingly insightful literature addressing vegetation change across Central Asia, the biogeophysical warming effects of vegetation shifts still need to be clarified. To contribute, the utility of robust satellite observation is explored to evaluate the surface warming effects of vegetation shifts across Central Asia, which is among NEEPSI's hotspots.

Hydrological and ecological impacts of run off river scheme; a case study of Ghazi Barotha hydropower project on Indus River, Pakistan.

Run off river schemes are getting widespread importance as they are considered environmentally safe. However, number of studies and the consequent information regarding impacts of run off river schemes is very limited worldwide. Present study attempted to analyze impacts of Ghazi Barotha Hydropower Plant, which is a run off river scheme situated in Khyber Pakhtunkhwa province of Pakistan.

Impacts of climate change on wheat phenology and yield in Indus Basin, Pakistan.

Aim of this study is to quantify the impacts of climate change on phenology and yield of winter wheat in rainfed and irrigated regions of Pakistan by using integration of two well-known crop models including STICS and APSIM with CORDEX-SA regional climate models (RCMs). A number of different adaptation strategies based on early sowing (i.e.

Towards Supply Chain Visibility Using Internet of Things: A Dyadic Analysis Review.

The Internet of Things (IoT) and its benefits and challenges are the most emergent research topics among academics and practitioners. With supply chains (SCs) gaining rapid complexity, having high supply chain visibility (SCV) would help companies ease the processes and reduce complexity by improving inaccuracies. Extant literature has given attention to the organisation's capability to collect and evaluate information to balance between strategy and goals.

Landfill site selection by integrating fuzzy logic, AHP, and WLC method based on multi-criteria decision analysis.

Rapid population growth integrated with poor governance and urban planning is highly challenging resulting key for the selection of unsuitable landfill sites, particularly in developing counties. Therefore, the aim of this study is to investigate the suitable solid waste landfill sites in the capital of the country as a case study, by the integration of Geographical Information System (GIS) with fuzzy logic, analytical hierarchy process (AHP), and weighted linear combination (WLC) method based on multi-criteria decision-making (MCDM). We chose thirteen (13) criteria (9 factors and 4 constraints) and grouped them into two main categories (environmental and socioeconomic) to achieve the objectives.

Novel mutant camelina and jatropha as valuable feedstocks for biodiesel production.

Novel mutant camelina has become a crop of interest inspired by its short growing season, low harvesting costs and high oil composition. Despite those advantages, limited research has been done on novel mutant lines to determine applicability for biodiesel production. Jatropha is an extremely hardy, frugal and high oil yielding plant species.

Climatic and hydrological projections to changing climate under CORDEX-South Asia experiments over the Karakoram-Hindukush-Himalayan water towers.

The complex snow and glacier (cryosphere) dynamics over the "third pole" mountainous regions of the Karakoram-Hindukush-Himalayas (HKH) makes this region challenging for accurate hydrological predictions. The objective of this study is to investigate the impacts of climate change on major hydrological components (precipitation-runoff, snow- and glacier-runoff, evapotranspiration and inter-annual change in streamflows) over the Hunza-, Gilgit- and Astore-River basins, located in HKH. For this purpose, three different hydrological models (snowmelt runoff (SRM), HEC-HMS and HBV are tested over snow- and glacier-covered river basins.

Future climate and cryosphere impacts on the hydrology of a scarcely gauged catchment on the Jhelum river basin, Northern Pakistan.

Streamflow projections are fundamental sources for future water resources strategic planning and management, particularly in high-altitude scarcely-gauged basins located in high mountain Asia. Therefore, quantification of the climate change impacts on major hydrological components (evapotranspiration, soil water storage, snowmelt-runoff, rainfall-runoff and streamflow) is of high importance and remains a challenge. For this purpose, we analysed general circulation models (GCMs) using a multiple bias correction approach and two different hydrological models i.

Comprehensive screening and selection of okra (Abelmoschus esculentus) germplasm for salinity tolerance at the seedling stage and during plant ontogeny.

The okra germplasm was screened for salinity tolerance at the seedling stage and during plant ontogeny. Substantial variation existed in okra for salinity tolerance at the seedling stage. An 80 mmol/L NaCl concentration was suitable for discriminating tolerant and non-tolerant okra genotypes.

Extraction of DNA suitable for PCR applications from mature leaves of Mangifera indica L.

Good quality deoxyribonucleic acid (DNA) is the pre-requisite for its downstream applications. The presence of high concentrations of polysaccharides, polyphenols, proteins, and other secondary metabolites in mango leaves poses problem in getting good quality DNA fit for polymerase chain reaction (PCR) applications. The problem is exacerbated when DNA is extracted from mature mango leaves.