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Analyzing breath sounds by using deep learning in diagnosing bronchial blockages with artificial lung

Bae et al. | Jan 22, 2024

Analyzing breath sounds by using deep learning in diagnosing bronchial blockages with artificial lung

Many common respiratory illnesses like bronchitis, asthma, and chronic obstructive pulmonary disease (COPD) lead to bronchial inflammation and, subsequently, a blockage. However, there are many difficulties in measuring the severity of the blockage. A numeric metric to determine the degree of the blockage severity is necessary. To tackle this demand, we aimed to develop a novel human respiratory model and design a deep-learning program that can constantly monitor and report bronchial blockage by recording breath sounds in a non-intrusive way.

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Similarity Graph-Based Semi-supervised Methods for Multiclass Data Classification

Balaji et al. | Sep 11, 2021

Similarity Graph-Based Semi-supervised Methods for Multiclass Data Classification

The purpose of the study was to determine whether graph-based machine learning techniques, which have increased prevalence in the last few years, can accurately classify data into one of many clusters, while requiring less labeled training data and parameter tuning as opposed to traditional machine learning algorithms. The results determined that the accuracy of graph-based and traditional classification algorithms depends directly upon the number of features of each dataset, the number of classes in each dataset, and the amount of labeled training data used.

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Fingerprint patterns through genetics

O'Brien et al. | Dec 02, 2020

Fingerprint patterns through genetics

This study explores the link between fingerprints and genetics by analyzing familial fingerprints to show how the fingerprints between family members, and in particular siblings, could be very similar. The hypothesis was that the fingerprints between siblings would be very similar and the dominant fingerprint features within the family would be the same throughout the generations. Fingerprints between the siblings showed a trend of similarity, with only very small differences which makes these fingerprints unique. This work helps to support the link between fingerprints and genetics while providing a modern technological application.

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The impacts of different Al(NO3)3 concentrations on the mitotic index of Allium sativum

Jimenez Pol et al. | Jul 10, 2023

The impacts of different Al(NO<sub>3</sub>)<sub>3</sub> concentrations on the mitotic index of <i>Allium sativum</i>
Image credit: Kylie Paz

Recognizing the increasing threat of acid deposition inn soil through the reaction of NOx and SO2 pollutants with water in Spain, the authors investigates the effects of Al(NO3)3 concentrations on the health of Allium sativum. By tracking its mitotic index, they found a negative exponential correlation between Al(NO3)3 concentrations and the mitotic index of A. sativum.

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How visualization influences strength endurance

Moore et al. | Jul 06, 2022

How visualization influences strength endurance

Recognizing a potential link between mental focus and physical endurance, here, the authors considered the effects of mental visualization on strength endurance. By comparing the number of repetitions completed in sets where the lifter was aware of the weight to be lifted against sets where the lifter was kept unaware, they found that the lifter was able to maintain strength endurance when unable to accurately visualize the weight they lifted in this exploratory study.

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A novel filtration model for microplastics using natural oils and its application to the environment

Park et al. | Jun 27, 2022

A novel filtration model for microplastics using natural oils and its application to the environment

Recognizing the need for a method to filter microplastics from polluted water the authors sought to use nonpolar solvents, palm oil and palm kernel oil, to filter microplastics out of model seawater. By relying on the separation of polar and nonpolar solvents followed by freezing the nonpolar solvent, they reported that microplastics could be extracted with percentages ranging from 96.2% to 94.2%. They also provided an estimation to use this method as part of container ships to clean the Pacific Ocean of microplastics.

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Evaluating cinnamaldehyde as an antibacterial agent in a produce wash for leafy greens

Drennan et al. | Oct 28, 2021

Evaluating cinnamaldehyde as an antibacterial agent in a produce wash for leafy greens

Recognizing a growing demand for organic produce, the authors sought to investigate plant-based antibiotic solutions to meet growing consumer demand for safe produce and also meet microbial standards of the USDA. The authors investigated the use of cinnamaldehyde as an antibacterial again E. coli, finding that lettuce treated with cinnamaldehyde displayed significantly lower colony-forming units of E. coli when compared to lettuce treated with chlorine bleach.

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Polluted water tested from the Potomac River affects invasive species plant growth

Chao et al. | Sep 20, 2023

Polluted water tested from the Potomac River affects invasive species plant growth
Image credit: Alex Korolkoff

Here recognizing the potential for pollution to impact the ecosystems of local waterways, the authors investigated the growth of tiger lilies, which are invasive to the Potomac River, in relation to the level of pollution. The authors report that increasing levels of pollution led to increased growth of the invasive species based on their study.

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Mathematical modeling of plant community composition for urban greenery plans

Fang et al. | Jul 05, 2023

Mathematical modeling of plant community composition for urban greenery plans
Image credit: CHUTTERSNAP

Here recognizing the importance of urban green space for the health of humans and other organisms, the authors investigated if mathematical modeling can be used to develop an urban greenery management plan with high eco-sustainability by calculating the composition of a plant community. They optimized and tested their model against green fields in a Beijing city park. Although the compositions predicted by their models differed somewhat from the composition of testing fields, they conclude that by using a mathematical model such as this urban green space can be finely designed to be ecologically and economically sustainable.

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