In 1939, the Japanese scientist Michio Takaoka first mentioned resveratrol from Veratrum grandiflorum O. Loes. Majority of plants, such as grapes, berries, and peanuts, are significant sources of resveratrol, a well-known polyphenolic. resveratrol (RV) is noted for its links to several health care benefits, including glucose metabolism, anti-aging, cardioprotective, neuroprotective, antitumor, antidiabetic, and antioxidant effects. Importantly, there have been reports of promising therapeutic qualities in atherosclerosis, dementia, and various malignancies. These properties are controlled through a number of cooperative techniques, which control inflammation besides the effects of oxidative stress and cell death. However, circulating resveratrol is rapidly broken down, according to pharmacokinetic study data. It prompts questions regarding the physiological significance of the high concentrations commonly employed in in vitro studies. To find out if resveratrol or its metabolites accumulate in tissues, further investigation is needed.
Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for
Modern statistical techniques offer a range of methodologies for modelling time series data, with conditional and unconditional approaches providing complementary insights that enhance overall model accuracy. This article introduced a modified ARIMA model employing conditional and unconditional parameter estimates. The methodology for the new model based on novel methods is provided. The prediction process, one and two steps ahead, is covered in detail, and a novel algorithm is presented. The best model is picked based on various measurement criteria, such as coefficient of determination (R2), root mean squared error (RMSE), and mean absolute scaled error (MASE). The suggested model is applied to a monthly petrol sales dataset (Jan
... Show MoreThis paper reports the synthesis and use of a novel metal-organic framework (MOF), named Zr-BADS, within the thin-film nanocomposite (TFN) membranes for reverse osmosis (RO) applications. Two types of zirconium-based MOFs, Zr-BADS-1 and Zr-BADS-2, were synthesized via a solvothermal method using bicinchoninic acid disodium salt as a linker and either dimethylformamide or ethanol as solvent, respectively. TFN membranes were prepared by embedding these MOFs within the polyamide thin film supported by a polysulfone support sheet. The specific surface area of Zr-BADS-1 and Zr-BADS-2 was determined to be 396.1 and 278.6 m2/g, respectively, indicating significant surface area conducive to water permeation. Scanning electron microscopic analysis r
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Two‐dimensional buoyancy‐induced flow and heat transfer inside a square enclosure partially occupied by copper metallic foam subjected to a symmetric side cooling and constant heat flux bottom heating was tested numerically. Finite Element Method was employed to solve the governing partial differential equations of the flow field and the Local Thermal Equilibrium model was used for the energy equation. The system boundaries were defined as lower heated wall by constant heat flux, cooled lateral walls, and insulated top wall. The three parameters elected to conduct the study are heater length (7 ≤
Portulacaria afra is a small succulent tree, previously belonging to the Portulacaceae family, but with further studies, the plant transferred to the Didieracea family. P. afra was used as an ornamental, vegetable, and ethnomedicinal plant. Uses of the plant by rural South Africans to treat chronic skin conditions and rashes, alleviate exhaustion, and aid in treating TB and diarrhea have been documented in folklore. According to pharmaceutical research, plant extracts off er a wide range of remedial outcomes, such as antidiabetic, antifungal, antibacterial, anticancer, antioxidant, and anti-infl ammatory. The study aims to determine some bioactive constituents responsible for pharmacological activities and traditional usefulness. Th
... Show MoreThe Catharanthus roseus plant was extracted and converted to nanoparticles in this work. The Soxhlet method was used to extract alkaloid compounds from the Catharanthus roseus plant and converted them to the nanoscale. Chitosan polymer was used as a linking material and converted to Chitosan nanoparticles (CSNPs). The extracted alkaloids were linked with Chitosan nanoparticles by maleic anhydride to get the final product (CSNPs-Linker-alkaloids). The pure Chitosan, Chitosan nanoparticles, and CSNPs-Linker-alkaloids were characterized by X-ray diffractometer, and Fourier Transform Infrared spectroscopy. X-ray results show that all samples have an orthorhombic structure with crystallite size in nanodimensions. FTIR spectra prove that
... Show MoreThis study is designed to highlight some of the physiological disorders taken place in the renal function, immunological response as well as the ability of the redox system represented by total antioxidant capacity and malondialdehyde levels to combat the toxic exposure of mercuric chloride (HgCl2) with or without collaboration of resveratrol (RES) supplement. Forty-five adult Sprague Dawley, 8-10 weeks old female rats weighing 170-220 g were randomly grouped as following; control group (C) kept without any medication. Dimethyl sulfoxide (DMSO) used as vehicle to prepare RES treatment was given to D-group. RES administered to R-group. Challenge group of rats (HD) was administered HgCl2. The last group of rats (HR) was given HgCl2 with RES i
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