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Phytochemical Analysis of Amaranthus spinosus Linn.: An in vitro Analysis

Sharma et al. | Mar 20, 2021

Phytochemical Analysis of <em>Amaranthus spinosus</em> Linn.: An <em>in vitro</em> Analysis

Mainstream cancer treatments, which include radiotherapy and chemotherapeutic drugs, are known to induce oxidative damage to healthy somatic cells due to the liberation of harmful free radicals. In order to avert this, physiological antioxidants must be complemented with external antioxidants. Here the authors performed a preliminary phytochemical screen to identify alkaloids, saponins, flavonoids, polyphenols, and tannins in all parts of the Amaranthus spinosus Linn. plant. This paper describes the preparation of this crude extract and assesses its antioxidant properties for potential use in complementary cancer treatment.

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Analysis of reduction potentials to determine the most efficient metals for electrochemical cell alternatives

Carroll et al. | Jul 10, 2020

Analysis of reduction potentials to determine the most efficient metals for electrochemical cell alternatives

In this study, the authors investigate what metals make the most efficient electrochemical cells, which are batteries that use the difference in electrical potential to generate electricity. Calculations predicted that a cell made of iron and magnesium would have the highest efficiency. Construction of an electrochemical cell of iron and magnesium produced voltages close to the theoretical voltage predicted. These findings are important as work continues towards making batteries with the highest storage efficiency possible.

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The effects of plasticizers on the mechanical properties and chemical composition of a gelatin biopolymer

Ip et al. | Jul 28, 2024

The effects of plasticizers on the mechanical properties and chemical composition of a gelatin biopolymer

Here, in an effort to identify alternatives to oil-based plastic, the authors sought to investigate the effects of plasticizers on the mechanical properties and chemical composition of gelatin bioplastic matrices. Through measurements of their tensile strength and elongation at break, along with FTIR spectroscopy, they identified 3% w/v polyethylene glycol film as having the best performance in their study..

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A novel encoding technique to improve non-weather-based models for solar photovoltaic forecasting

Ahmed et al. | Jun 09, 2023

A novel encoding technique to improve non-weather-based models for solar photovoltaic forecasting

Several studies have applied different machine learning (ML) techniques to the area of forecasting solar photovoltaic power production. Most of these studies use weather data as inputs to predict power production; however, there are numerous practical issues with the procurement of this data. This study proposes models that do not use weather data as inputs, but rather use past power production data as a more practical substitute to weather-based models. Our proposed models demonstrate a better, cheaper, and more reliable alternatives to current weather models.

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A novel deep learning model for visibility correction of environmental factors in autonomous vehicles

Dey et al. | Oct 31, 2022

A novel deep learning model for visibility correction of environmental factors in autonomous vehicles

Intelligent vehicles utilize a combination of video-enabled object detection and radar data to traverse safely through surrounding environments. However, since the most momentary missteps in these systems can cause devastating collisions, the margin of error in the software for these systems is small. In this paper, we hypothesized that a novel object detection system that improves detection accuracy and speed of detection during adverse weather conditions would outperform industry alternatives in an average comparison.

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