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Integrated Ocean Cleanup System for Sustainable and Healthy Aquatic Ecosystems

Anand et al. | Nov 14, 2020

Integrated Ocean Cleanup System for Sustainable and Healthy Aquatic Ecosystems

Oil spills are one of the most devastating events for marine life. Finding ways to clean up oil spills without the need for harsh chemicals could help decrease the negative impact of such spills. Here the authors demonstrate that using a combination of several biodegradable substances can effectively adsorb oil in seawater in a laboratory setting. They suggest further exploring the potential of such a combination as a possible alternative to commonly-used non-biodegradable substances in oil spill management.

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Quantitative NMR spectroscopy reveals solvent effects in the photochemical degradation of thymoquinone

Mandava et al. | Dec 16, 2023

Quantitative NMR spectroscopy reveals solvent effects in the photochemical degradation of thymoquinone

Thymoquinone is a compound of great therapeutic potential and scientific interest. However, its clinical administration and synthetic modifications are greatly limited by its instability in the presence of light. This study employed quantitative 1H nuclear magnetic resonance (NMR) spectroscopy to identify the effect of solvation on the degradation of thymoquinone under ultraviolet light (UV). It found that the rate of degradation is highly solvent dependent occurs maximally in chloroform.

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Plasmid Variance and Nutrient Regulation of Bioluminescence Genes

Uhler et al. | Dec 09, 2014

Plasmid Variance and Nutrient Regulation of Bioluminescence Genes

Numerous organisms, including the marine bacterium Aliivibrio fischeri, produce light. This bioluminescence is involved in many important symbioses and may one day be an important source of light for humans. In this study, the authors investigated ways to increase bioluminescence production from the model organism E. coli.

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The effect of activation function choice on the performance of convolutional neural networks

Wang et al. | Sep 15, 2023

The effect of activation function choice on the performance of convolutional neural networks
Image credit: Tara Winstead

With the advance of technology, artificial intelligence (AI) is now applied widely in society. In the study of AI, machine learning (ML) is a subfield in which a machine learns to be better at performing certain tasks through experience. This work focuses on the convolutional neural network (CNN), a framework of ML, applied to an image classification task. Specifically, we analyzed the performance of the CNN as the type of neural activation function changes.

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Comparative screening of dose-dependent and strain-specific antimicrobial efficacy of berberine against a representative library of broad-spectrum antibiotics

Sun et al. | May 10, 2021

Comparative screening of dose-dependent and strain-specific antimicrobial efficacy of berberine against a representative library of broad-spectrum antibiotics

We hypothesize that berberine has broad-spectrum antibacterial properties, along with potency that is comparable to current broad-spectrum antibiotics that are commercially available. Here, we screened berberine against four strains of bacteria and evaluated its antimicrobial activity against five broad-spectrum antibiotics from different classes to better quantify berberine’s antibacterial activity and compare its efficacy as an antibacterial agent to the broad-spectrum antibiotics. Our results indicated that berberine had strain-selective cytotoxic effects and was significantly less potent than most of the broad-spectrum antibiotics

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A Cloud-Enabled Communication Strategy for Wildfire Alerts

Vinaithirthan et al. | Jul 19, 2020

A Cloud-Enabled Communication Strategy for Wildfire Alerts

The traditional alert system in California consists of Wireless Emergency Alerts (WEAs), which lack location specificity, and sign-up-based technology which is limited by the number of sign ups. Those who do not have phones or have a silence option on their devices are most at risk from the current alert system. Here the authors developed cloud-enabled crisis connection for disaster alerts (CRISIS-CONNECT) to mitigate problems associated with the current alert system.

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