Browse Articles

The authors test electrocardiography biofeedback as a treatment for individuals with Postural Orthostatic Tachycardia Syndrome.

Algal blooms pose a threat to ecosystems, but the methods used to combat these blooms might harm more than just the algae. Halepete, Graham, and Lowe-Schmahl demonstrate negative effects of anti-algae treatments on a cyanobacterium (Spirulina major), and the water fleas (Daphnia magna) that live alongside these cyanobacteria.

In this study the authors looked at the extract of Stephania tetrandra and its impact on symptoms related to obsessive compulsive disorder in fruit flies.

Here, the authors considered the effects of relationship status and substance use on the mental health of colleges students, where they specifically examined their correlation with depression, anxiety, and the fear of missing out (FoMO). Through a survey of college students they found that those with higher substance misuse had higher levels of anxiety, depression, and FoMO, while those involved in longer-term relationships had lower levels of FoMo and alcohol use.

The authors looked at how a 3D bioprinter could be used to model the blood brain barrier.

About 25% of the food grown never reaches consumers due to spoilage, and 11.5 billion pounds of produce from gardens are wasted every year. Current solutions involve farmers manually looking for and treating diseased crops. These methods of tending crops are neither time-efficient nor feasible. I used a convolutional neural network to identify signs of plant disease on leaves for garden owners and farmers.

Bacteria cause tooth decay, plaque, bad breath, and other diseases. Despite being cleaned with water and toothpaste, oral bacteria live on our toothbrushes. Bacterial growth has been shown to be inhibited by different toothpastes and common household spices. This study tested how different toothpastes and common household spices, including cinnamon, cumin, nutmeg, and ground white pepper, can inhibit bacteria from growing on toothbrushes

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.

This study is centered around developing biofortification methods: the authors test whether the amount of calcium available to growing crops translates into more calcium present in the crops.

In this study, the authors identify transcripts and gene networks that are changed after infection with the Middle East Respiratory Syndrome-related coronavirus (MERS-CoV).