Head injuries are common in American football and the facemasks found on football helmets receive a lot of impact during contacts. This study investigates how effective they are at reducing concussion risk.
Read More...Validation of impact-absorbing football helmet facemask for head injury prevention with simulation
Head injuries are common in American football and the facemasks found on football helmets receive a lot of impact during contacts. This study investigates how effective they are at reducing concussion risk.
Read More...Investigating Lemna minor and microorganisms for the phytoremediation of nanosilver and microplastics
The authors looked at phytoremediation, the process by which plants are used to remove pollutants from our environment, and the ability of Lemna minor to perform phytoremediation in various simulated polluted environments. The authors found that L. minor could remove pollutants from the environment and that the addition of bacteria increased this removal.
Read More...Voltage, power, and energy production of a Shewanella oneidensis biofilm microbial fuel cell in microgravity
The authors looked at the ability of Shewanella oneidensis to generate energy in a microbial fuel cell under varying conditions. They found that the S. Onedensis biofilm was able to produce energy in microgravity and that one of the biggest factors that limited energy production was a decrease in growth medium present.
Read More...A novel approach for predicting Alzheimer’s disease using machine learning on DNA methylation in blood
Here, recognizing the difficulty associated with tracking the progression of dementia, the authors used machine learning models to predict between the presence of cognitive normalcy, mild cognitive impairment, and Alzheimer's Disease, based on blood DNA methylation levels, sex, and age. With four machine learning models and two dataset dimensionality reduction methods they achieved an accuracy of 53.33%.
Read More...Suppress that algae: Mitigating the effects of harmful algal blooms through preemptive detection & suppression
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.
Read More...Solving a new NP-Complete problem that resembles image pattern recognition using deep learning
In this study, the authors tested the ability and accuracy of a neural net to identify patterns in complex number matrices.
Read More...Prediction of preclinical Aβ deposit in Alzheimer’s disease mice using EEG and machine learning
Alzheimer’s disease (AD) is a common disease affecting 6 million people in the U.S., but no cure exists. To create therapy for AD, it is critical to detect amyloid-β protein in the brain at the early stage of AD because the accumulation of amyloid-β over 20 years is believed to cause memory impairment. However, it is difficult to examine amyloid-β in patients’ brains. In this study, we hypothesized that we could accurately predict the presence of amyloid-β using EEG data and machine learning.
Read More...Effect of mass and center of gravity on vehicle speed and braking performance
In this study, the authors test whether a gravity vehicle, which is a vehicle powered by its own gravity on a ramp, could be designed to move faster when mathematical calculations for optimal mass and center of gravity were applied in the design.
Read More...Comparative Gamma Radiation Analysis by Geographic Region
Gamma radiation can be produced by both natural and man-made sources and abnormally high exposure levels could lead to an increase in cell damage. In this study, gamma radiation was measured at different locations and any correlation with various geographic factors, such as distance from a city center, elevation and proximity to the nearest nuclear reactor, was determined.
Read More...Capturing Harmful Air Pollutants Using an Electrospun Mesh Embedded with Zinc-based Nanocrystals
Zeolithic imidazolate framework-8 (ZIF-8) is a specific metal-organic framework that has favorable qualities for use in an air filter and is known to be capable of adsorbing particulate matter. Therefore, the objective of this experiment was to determine the effectiveness of ZIF-8 in adsorbing polar, gaseous air pollutants, specifically nitrogen dioxide and hydrogen sulfide. In order to determine effectiveness, the percent change in concentration for various gases after the application of ZIF-8 crystals was measured via Fourier-transform infrared spectroscopy (FTIR). The work highlights crystals as a potentially promising alternative or addition to current filter materials to reduce atmospheric pollution.
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