In this study, the authors investigate whether Moringa Oleifera seeds can serve as material to aid in purifying water. M. oleifera seeds have coagulating properties and the authors hypothesized that including it in a water filtration system would reduce particles, specifically bacteria, in water. Their results show that this system removed the largest percent of bacteria. When used in combination with cilantro, it was actually more efficient than the other techniques! These findings have important implications for creating better and more economical water purification systems.
Read More...Browse Articles
The Effects of Antibiotics on Nutrient Digestion
One disadvantage of antibiotic therapy is the potential for unpleasant gastrointestinal side effects. Here, the authors test whether some common antibiotics directly interfere with the digestion of protein, fat, or sugars. This study provides motivation to more carefully investigate the interactions between antibiotics and gut enzymes in order to inform treatment decisions and improve patient outcomes.
Read More...Feature extraction from peak detection algorithms for enhanced EMG-based hand gesture recognition models
This manuscript evaluates peak detection algorithms for feature extraction in EMG-based hand gesture recognition using a random forest classifier. The study demonstrates that wavelet-based peak detection features achieve the highest classification accuracy (96.5%), outperforming other methods. The results highlight the potential of peak features to improve EMG-based prosthetic control systems.
Read More...Battling cultural bias within hate speech detection: An experimental correlation analysis
The authors develop a new method for training machine learning algorithms to differentiate between hate speech and cultural speech in online platforms.
Read More...Testing antimicrobial properties of common household spices in a real-world scenario
In this article the authors look at the ability of spices to reduce microbial load on a cutting surface by comparing growth of bacteria cultured before and after cleaning with various spice mixtures.
Read More...Percentages are a better format for conveying medical risk than frequencies
It can be challenging for the general public to understand data on medical risk. Weseley-Jones and Mordechai tackle this issue by conducting a survey to assess people's skill and comfort with understanding medical risk information in percentage and frequency formats.
Read More...Impact of salinity and phosphorus on growth of Phaseolus Vulgaris inoculated with Arbuscular Mycorrhizal Fungi
Here, recognizing a declining supply of rock phosphate, as well as its role in crop fertilization, the authors investigated a fungus that forms a symbiotic relationship with many crops. They found that symbiosis between the fungus and common bean plant increased the affinity of the plant towards absorbing nutrients as evidenced by lower root-to-shoot ratios in beans planted in soil with various concentrations of phosphorous and salinity.
Read More...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.
Read More...Assessing the accuracy and efficiency of simplified gridded ion thruster simulations
The authors used a particle-in-cell simulation to determine the effects on extensive and intensive metrics. They found that preliminary simulations could be run quickly with much lower particle counts before more technically demanding and comprehensive simulations are performed.
Read More...Advancements in glioma segmentation: comparing the U-Net and DeconvNet models
This study compares the performance of two deep learning models, U-Net and DeconvNet, for segmenting gliomas from MRI scans.
Read More...