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A novel approach for early detection of Alzheimer’s disease using deep neural networks with magnetic resonance imaging

Ganesh et al. | Mar 20, 2022

A novel approach for early detection of Alzheimer’s disease using deep neural networks with magnetic resonance imaging

In the battle against Alzheimer's disease, early detection is critical to mitigating symptoms in patients. Here, the authors use a collection of MRI scans, layering with deep learning computer modeling, to investigate early stages of AD which can be hard to catch by human eye. Their model is successful, able to outperform previous models, and detected regions of interest in the brain for further consideration.

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Banana-based Biofuels for Combating Climate Change: How the Composition of Enzyme Catalyzed Solutions Affects Biofuel Yield

Klein-Hessling Barrientos et al. | May 27, 2020

Banana-based Biofuels for Combating Climate Change: How the Composition of Enzyme Catalyzed Solutions Affects Biofuel Yield

The authors investigate whether amylase or yeast had a more prominent role in determining the bioethanol concentration and bioethanol yield of banana samples. They hypothesized that amylase would have the most significant impact on the bioethanol yield and concentration of the samples. They found that while yeast is an essential component for producing bioethanol, the proportion of amylase supplied through a joint amylase-yeast mixture has a more significant impact on the bioethanol yield. This study provides a greater understanding of the mechanisms and implications involved in enzyme-based biofuel production, specifically of those pertaining to amylase and yeast.

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Suppress that algae: Mitigating the effects of harmful algal blooms through preemptive detection & suppression

Natarajan et al. | Jul 17, 2023

Suppress that algae: Mitigating the effects of harmful algal blooms through preemptive detection & suppression
Image credit: Sharanya Natarajan

A bottleneck in deleting algal blooms is that current data section is manual and is reactionary to an existing algal bloom. These authors made a custom-designed Seek and Destroy Algal Mitigation System (SDAMS) that detects harmful algal blooms at earlier time points with astonishing accuracy, and can instantaneously suppress the pre-bloom algal population.

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Testing Epoxy Strength: The High Strength Claims of Selleys’s Araldite Epoxy Glues

Nguyen et al. | Jul 14, 2020

Testing Epoxy Strength: The High Strength Claims of Selleys’s Araldite Epoxy Glues

Understanding the techniques used to improve the adhesion strength of the epoxy resin is important especially for consumer applications such as repairing car parts, bonding aluminum sheeting, and repairing furniture or applications within the aviation or civil industry. Selleys Araldite epoxy makes specific strength claims emphasizing that the load or weight that can be supported by the adhesive is 72 kg/cm2. Nguyen and Clarke aimed to test the strength claims of Selley’s Araldite Epoxy by gluing two steel adhesion surfaces: a steel tube and bracket. Results showed that there is a lack of consideration by Selleys for adhesion loss mechanisms and environmental factors when accounting for consumer use of the product leading to disputable claims.

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RNAi-based Gene Therapy Targeting ZGPAT Promotes EGF-dependent Wound Healing

Lee et al. | Nov 15, 2021

RNAi-based Gene Therapy Targeting ZGPAT Promotes EGF-dependent Wound Healing

Wound-healing involves a sequence of events, such as inflammation, proliferation, and migration of different cell types like fibroblasts. Zinc Finger CCCH-type with G-Patch Domain Containing Protein (ZGPAT), encodes a protein that has its main role as a transcription repressor by binding to a specific DNA sequence. The aim of the study was to find out whether inhibiting ZGPAT will expedite the wound healing process by accelerating cell migration. This treatment strategy can provide a key to the development of wound healing strategies in medicine and cellular biology.

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Creating a Phenology Trail Around Central Park Pond

Flynn et al. | Jul 16, 2020

Creating a Phenology Trail Around Central Park Pond

This study aimed to determine whether the life cycle stages, or phenophases, of some plants in the urban environment of Central Park, New York, differ from the typical phenophases of the same plant species. The authors hypothesized that the phenophases of the thirteen plants we studied would differ from their typical phenophases due to the urban heat island effect. Although the phenophases of five plants matched up with typical trends, there were distinct changes in the phenophases of the other eight, possibly resulting from the urban heat island effect.

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Geographic Distribution of Scripps National Spelling Bee Spellers Resembles Geographic Distribution of Child Population in US States upon Implementation of the RSVBee “Wildcard” Program

Kannankeril et al. | Aug 17, 2020

Geographic Distribution of Scripps National Spelling Bee Spellers Resembles Geographic Distribution of Child Population in US States upon Implementation of the RSVBee “Wildcard” Program

The Scripps National Spelling Bee (SNSB) is an iconic academic competition for United States (US) schoolchildren, held annually since 1925. However, the sizes and geographic distributions of sponsored regions are uneven. One state may send more than twice as many spellers as another state, despite similar numbers in child population. In 2018, the SNSB introduced a wildcard program known as RSVBee, which allowed students to apply to compete as a national finalist, even if they did not win their regional spelling bee. In this study, the authors tested the hypothesis that the geographic distribution of SNSB national finalists more closely matched the child population of the US after RSVBee was implemented.

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