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Capturing Harmful Air Pollutants Using an Electrospun Mesh Embedded with Zinc-based Nanocrystals

Doppalapudi et al. | May 12, 2020

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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Osmotic characteristics of water retention structures of Bursera microphylla in relation to soil salinity

Groom et al. | Jul 12, 2023

Osmotic characteristics of water retention structures of <i>Bursera microphylla</i> in relation to soil salinity
Image credit: Lisa Fotios

This study hypothesized that sodium chloride was taken up through plant root structures to facilitate water transportation, and that sodium chloride accumulation was directly proportional to the soil salinity. Results showed that most cells within the “bulb” structures were isotonic at a concentration approximately twice as high as that of root tissue and ambient soil salinity, therefore supporting the presented hypothesis.

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Predicting asthma-related emergency department visits and hospitalizations with machine learning techniques

Chatterjee et al. | Oct 25, 2021

Predicting asthma-related emergency department visits and hospitalizations with machine learning techniques

Seeking to investigate the effects of ambient pollutants on human respiratory health, here the authors used machine learning to examine asthma in Lost Angeles County, an area with substantial pollution. By using machine learning models and classification techniques, the authors identified that nitrogen dioxide and ozone levels were significantly correlated with asthma hospitalizations. Based on an identified seasonal surge in asthma hospitalizations, the authors suggest future directions to improve machine learning modeling to investigate these relationships.

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A land use regression model to predict emissions from oil and gas production using machine learning

Cao et al. | Mar 24, 2023

A land use regression model to predict emissions from oil and gas production using machine learning

Emissions from oil and natural gas (O&G) wells such as nitrogen dioxide (NO2), volatile organic compounds (VOCs), and ozone (O3) can severely impact the health of communities located near wells. In this study, we used O&G activity and wind-carried emissions to quantify the extent to which O&G wells affect the air quality of nearby communities, revealing that NO2, NOx, and NO are correlated to O&G activity. We then developed a novel land use regression (LUR) model using machine learning based on O&G prevalence to predict emissions.

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Changes for Development of Al2O3 Coated PVA (Polyvinyl Alcohol) Composite Nonwoven Separator For Improving Thermal and Electrochemical Properties

Kim et al. | Oct 16, 2019

Changes for Development of Al2O3 Coated PVA (Polyvinyl Alcohol) Composite Nonwoven Separator For Improving Thermal and Electrochemical Properties

Lithium-ion batteries, a breakthrough in chemistry that enabled the electronic revolution we live today have become an essential part of our day-to-day life. A phone battery running out after a heavy day of use with limited opportunities for recharging is a well-known and resented experience by almost everyone. How then can we make batteries more efficient? This paper proposes the use of a different type of separator, that improves the charging and discharging capacities of lithium ions compared to the classical separator. This and similar attempts to improve Lithium-ion battery function could facilitate the development of higher-performance batteries that work longer and withstand harsher use.

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Combating Insulin Resistance Using Medicinal Plants as a Supplementary Therapy to Metformin in 3T3-L1 Adipocytes: Improving Early Intervention-Based Diabetes Treatment

Jayram et al. | Apr 08, 2019

Combating Insulin Resistance Using Medicinal Plants as a Supplementary Therapy to Metformin in 3T3-L1 Adipocytes: Improving Early Intervention-Based Diabetes Treatment

A primary cause of diabetes is insulin resistance, which is caused by disruption of insulin signal transduction. The objective of this study was to maximize insulin sensitivity by creating a more effective, early intervention-based treatment to avert severe T2D. This treatment combined metformin, “the insulin sensitizer”, and medicinal plants, curcumin, fenugreek, and nettle.

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Genomic Signature Analysis for the Strategic Bioremediation of Polycyclic Aromatic Hydrocarbons in Mangrove Ecosystems in the Gulf of Tonkin

Dao et al. | Jun 27, 2021

Genomic Signature Analysis for the Strategic Bioremediation of Polycyclic Aromatic Hydrocarbons in Mangrove Ecosystems in the Gulf of Tonkin

Engineered bacteria that degrade oil are currently being considered as a safe option for the treatment of oil spills. For this approach to be successful, the bacteria must effectively express oil-degrading genes they uptake as part of an external genoming vehicle called a "plasmid". Using a computational approach, the authors investigate plasmid-bacterium compatibility to find pairs that ensure high levels of gene expression.

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