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Developing a Portable, Reusable, and Inexpensive Magnesium-Air Fuel Cell

Tota et al. | Mar 28, 2019

Developing a Portable, Reusable, and Inexpensive Magnesium-Air Fuel Cell

One of the greatest challenges we face today is the sustainable production, storage, and distribution of electrical power. One emerging technology with great promise in this area is that of metal-air fuel cells—a long-term and reusable electricity storage system made from a reactive metal anode and a saline solution. In this study the authors tested several different types of metal to determine which was the most suitable for this application. They found that a fuel cell with a magnesium anode was superior to fuel cells made from aluminum or zinc, producing a voltage and current sufficient for real-world applications such as charging a mobile phone.

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Impact of daf-25 and daf-11 Mutations on Olfactory Function in C. elegans

Gardner et al. | Feb 02, 2019

Impact of daf-25 and daf-11 Mutations on Olfactory Function in C. elegans

Cilia are little hair-like protrusions on many cells in the human body, including those lining the trachea where they play a role in clearing our respiratory tract of mucous and other irritants. Genetic mutations that impair ciliary function have serious consequences on our well-being making it important to understand how ciliary function is regulated. By using a simple organism, such as the worm C. elegans that use cilia to move, the authors explore the effect of certain genetic mutations on the cilia of the worms by measuring their ability to move towards or away from certain odorants.

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Optimizing Interplanetary Travel Using a Genetic Algorithm

Murali et al. | Oct 28, 2018

Optimizing Interplanetary Travel Using a Genetic Algorithm

In this work, the authors develop an algorithm that solves the problem of efficient space travel between planets. This is a problem that could soon be of relevance as mankind continues to expand its exploration of outer space, and potentially attempt to inhabit it.

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Characterization of a UPEC DegS Mutant in vitro and in vivo

Bradley et al. | Mar 16, 2015

Characterization of a UPEC <em>DegS</em> Mutant <em>in vitro</em> and <em>in vivo</em>

DegS is an integral inner membrane protein in E. coli that helps break down misfolded proteins. When it is mutated, there is a large increase in the production of outer membrane vesicles (OMVs), which are thought to play a role in pathogenesis. This study used mutant strains of uropathogenic E. coli (UPEC) to characterize the role of DegS and OMVs on UPEC virulence.

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Effect of Gram-positive bacteria on antibiotic resistance in Gram-negative bacteria

Willem et al. | Mar 12, 2024

Effect of Gram-positive bacteria on antibiotic resistance in Gram-negative bacteria

Antibiotics are one of the most common treatments for bacterial infections, but the emergence of antibiotic resistance is a major threat to the control of infectious diseases. Many factors contribute to the development of antibiotic resistance. One is bacterial conjugation from Gram-positive to Gram-negative bacteria where there is a transfer of resistance genes from Gram-positive to Gram-negative bacteria that could increase antibiotic resistance in the latter. In light of these observations, we decided to test whether Gram-negative bacteria that came into contact with Gram-positive bacteria had a higher resistance to the antimicrobial properties of spices than Gram-negative bacteria that did not come into contact with Gram-positive bacteria.

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Utilizing meteorological data and machine learning to predict and reduce the spread of California wildfires

Bilwar et al. | Jan 15, 2024

Utilizing meteorological data and machine learning to predict and reduce the spread of California wildfires
Image credit: Pixabay

This study hypothesized that a machine learning model could accurately predict the severity of California wildfires and determine the most influential meteorological factors. It utilized a custom dataset with information from the World Weather Online API and a Kaggle dataset of wildfires in California from 2013-2020. The developed algorithms classified fires into seven categories with promising accuracy (around 55 percent). They found that higher temperatures, lower humidity, lower dew point, higher wind gusts, and higher wind speeds are the most significant contributors to the spread of a wildfire. This tool could vastly improve the efficiency and preparedness of firefighters as they deal with wildfires.

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The impact of genetic analysis on the early detection of colorectal cancer

Agrawal et al. | Aug 24, 2023

The impact of genetic analysis on the early detection of colorectal cancer

Although the 5-year survival rate for colorectal cancer is below 10%, it increases to greater than 90% if it is diagnosed early. We hypothesized from our research that analyzing non-synonymous single nucleotide variants (SNVs) in a patient's exome sequence would be an indicator for high genetic risk of developing colorectal cancer.

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