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Using NLP to ascertain changes in the fast-fashion industry based on UN sustainable development goals

Chadha et al. | Sep 11, 2023

Using NLP to ascertain changes in the fast-fashion industry based on UN sustainable development goals
Image credit: Prudence Earl

Here, the authors sought to evaluate the efforts of fast fashion clothing companies towards sustainability, specifically in regards to the United Nations Sustainable Development Goals. The authors used natural language processing to investigate the sustainability reports of fast fashion companies focusing on terms established by the UN. They found that the most consistently addressed areas were related to sustainable consumption/production, with a focus on health and well-being emerging during the recent pandemic.

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Developing novel plant waste-based hydrogels for skin regeneration and infection detection in diabetic wounds

Mathew et al. | Aug 10, 2023

Developing novel plant waste-based hydrogels for skin regeneration and infection detection in diabetic wounds

The purpose of this investigation is to develop a hydrogel to aid skin regeneration by creating an extracellular matrix for fibroblast growth with antibacterial and infection-detection properties. Authors developed two natural hydrogels based on pectin and potato peels and characterized the gels for fibroblast compatibility through rheology, scanning electron microscopy, swelling, degradation, and cell cytotoxicity assays. Overall, this experiment fabricated various hydrogels capable of acting as skin substitutes and counteracting infections to facilitate wound healing. Following further testing and validation, these hydrogels could help alleviate the 13-billion-dollar financial burden of foot ulcer treatment.

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Tomato disease identification with shallow convolutional neural networks

Trinh et al. | Mar 03, 2023

Tomato disease identification with shallow convolutional neural networks

Plant diseases can cause up to 50% crop yield loss for the popular tomato plant. A mobile device-based method to identify diseases from photos of symptomatic leaves via computer vision can be more effective due to its convenience and accessibility. To enable a practical mobile solution, a “shallow” convolutional neural networks (CNNs) with few layers, and thus low computational requirement but with high accuracy similar to the deep CNNs is needed. In this work, we explored if such a model was possible.

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A Crossover Study Comparing the Effect of a Processed vs. Unprocessed Diet on the Spatial Learning Ability of Zebrafish

Banga et al. | Sep 18, 2022

A Crossover Study Comparing the Effect of a Processed vs. Unprocessed Diet on the Spatial Learning Ability of Zebrafish

The authors compared the short-term effects of processed versus unprocessed food on spatial learning and survival in zebrafish, given the large public concern regarding processed foods. By randomly assigning zebrafish to a diet of brine shrimp flakes (processed) or live brine shrimp (unprocessed), the authors show while there is no immediate effect on a fish's decision process between the two diets, there are significant correlations between improved learning and stress response with the unprocessed diet.

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Building an affordable model wave energy converter using a magnet and a coil

Choy et al. | Jul 05, 2023

Building an affordable model wave energy converter using a magnet and a coil
Image credit: Joshua Smith

Here, seeking to identify a method to locally produce and capture renewable energy in Hawai'i and other island communities, the authors built and tested a small-scale model wave energy converter. They tested various configurations of a floated magnet surrounded by a wire coal, where the motion of the magnet due to a wave results in induction current in the coil. While they identified methods to increase the voltage and current generated, they also found that corrosion results in significant deterioration.

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Does technology help or hurt learning? Evidence from middle school and high school students

Lu et al. | Oct 02, 2022

Does technology help or hurt learning? Evidence from middle school and high school students

Here, recognizing the vastly different opinion held regarding device usage, the authors considered the effects of technology use on middle and high school students' learning effectiveness. Using an anonymous online survey they found partial support that device use at school increases learning effectiveness, but found strong support for a negative effect of technology use at home on learning effectiveness. Based on their findings they suggest that the efficacy of technology depends on environmental context along with other important factors that need consideration.

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Reddit v. Wall Street: Why Redditors beat Wall Street at its own game

Bhakar et al. | Sep 13, 2022

Reddit v. Wall Street: Why Redditors beat Wall Street at its own game

Here the authors investigated the motivation of a short squeeze of GameStop stock where users of the internet forum Reddit drove a sudden increase in GameStop stock price during the start of 2021. They relied on both qualitative and quantitative analyses where they tracked activity on the r/WallStreetBets subreddit in relation to mentions of GameStop. With these methods they found that while initially the short squeeze was driven by financial motivations, later on emotional motivations became more important. They suggest that social phenomena can be dynamic and evolve necessitating mixed method approaches to study them.

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