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A Quantitative Analysis of the Proliferation of Microplastics in Williamston’s Waterways

Schafer et al. | Feb 17, 2019

A Quantitative Analysis of the Proliferation of Microplastics in Williamston’s Waterways

Plastic debris can disrupt marine ecosystems, spread contaminants, and take years to naturally degrade. In this study, Wu et al aim to establish an understanding of the scope of Williamston, Michigan’s microplastics problem, as well as to attempt to find the source of these plastics. Initially, the authors hypothesize that the Williamston Wastewater Treatment Plant was the primary contributor to Williamston’s microplastics pollution. Although they find a general trend of increasing concentrations of microplastics from upstream to downstream, they do not pinpoint the source of Williamston’s microplastics pollution in the present research.

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Propagation of representation bias in machine learning

Dass-Vattam et al. | Jun 10, 2021

Propagation of representation bias in machine learning

Using facial recognition as a use-case scenario, we attempt to identify sources of bias in a model developed using transfer learning. To achieve this task, we developed a model based on a pre-trained facial recognition model, and scrutinized the accuracy of the model’s image classification against factors such as age, gender, and race to observe whether or not the model performed better on some demographic groups than others. By identifying the bias and finding potential sources of bias, his work contributes a unique technical perspective from the view of a small scale developer to emerging discussions of accountability and transparency in AI.

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Impact of light intensity and electrolyte volume on performance of photo-electrochemical (PEC) solar cell

Patel et al. | Mar 14, 2022

Impact of light intensity and electrolyte volume on performance of photo-electrochemical (PEC) solar cell

Here, seeking to develop more efficient solar cells, the authors investigated photo-electrochemical (PEC) solar cells, specifically molybdenum diselenide (MoSe2) based on its high resistance to corrosion. They found that the percentage efficiency of these PEC solar cells was proportional to light intensity–0.9 and that performance was positively influenced by increasing the electrolyte volume. They suggest that studies such as these can lead to new insight into reaction-based solar cells.

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Computational Structure-Activity Relationship (SAR) of Berberine Analogs in Double-Stranded and G-Quadruplex DNA Binding Reveals Both Position and Target Dependence

Sun et al. | Dec 18, 2020

Computational Structure-Activity Relationship (SAR) of Berberine Analogs in Double-Stranded and G-Quadruplex DNA Binding Reveals Both Position and Target Dependence

Berberine, a natural product alkaloid, and its analogs have a wide range of medicinal properties, including antibacterial and anticancer effects. Here, the authors explored a library of alkyl or aryl berberine analogs to probe binding to double-stranded and G-quadruplex DNA. They determined that the nature of the substituent, the position of the substituent, and the nucleic acid target affect the free energy of binding of berberine analogs to DNA and G-quadruplex DNA, however berberine analogs did not result in net stabilization of G-quadruplex DNA.

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The effect of molecular weights of chitosan on the synthesis and antifungal effect of copper chitosan

Byakod et al. | Apr 07, 2024

The effect of molecular weights of chitosan on the synthesis and antifungal effect of copper chitosan

Pathogenic fungi such as Alternaria alternata (A. alternata) can decimate crop yields and severely limit food supplies when left untreated. Copper chitosan (CuCts) is a promising alternative fungicide for developing agricultural areas due to being inexpensive and nontoxic. We hypothesized that LMWc CuCts would exhibit greater fungal inhibition due to the beneficial properties of LMWc.

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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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How does light affect the distribution of Euglena sp. and Tetrahymena pyriformis

Singh et al. | Mar 03, 2022

How does light affect the distribution of <em>Euglena sp.</em> and <em>Tetrahymena pyriformis</em>

In this article, the authors explored the locomotory movement of Euglena sp. and Tetrahymena pyriformis in response to light. Such research bears relevance to the migration and distribution patterns of both T. pyriformis and Euglena as they differ in their method of finding sustenance in their native environments. With little previous research done on the exploration of a potential response to photostimulation enacted by T. pyriformis, the authors found that T. pyriformis do not bias in distribution towards areas of light - unlike Euglena, which displayed an increased prevalence in areas of light.

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Effects of various alkaline carbonic solutions on the growth of the freshwater algae Chlorophyceae

Jani et al. | Aug 11, 2023

Effects of various alkaline carbonic solutions on the growth of the freshwater algae Chlorophyceae
Image credit: Jordan Whitfield

Modern day fossil fuels are prone to polluting our environment, which can provide major habitat loss to many animals in our ecosystems. Algae-based biofuels have become an increasingly popular alternative to fossil fuels because of their sustainability, effectiveness, and environmentally-friendly nature. To encourage algae growth and solidify its role as an emerging biofuel, we tested basic (in terms of pH) solutions on pond water to determine which solution is most efficient in inducing the growth of algae.

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