
In the age of global warming, these authors studied which of the four major greenhouse gases (water vapor, carbon dioxide, and nitrous oxide) change the most with increased temperature.
Read More...Measuring the efficiency of greenhouse gases to absorb heat
In the age of global warming, these authors studied which of the four major greenhouse gases (water vapor, carbon dioxide, and nitrous oxide) change the most with increased temperature.
Read More...Integrating microbial fuel cell with sedum green roof for stormwater retention and renewable energy generation
The authors looked at renewable energy generators and the ability to utilize green roofs as a solution to climate change.
Read More...Analyzing aerosol variation during the COVID-19 pandemic lockdown using satellite data
In this study, the authors use aerosol optical depth data to determine if aerosol levels were lower in major metropolitan areas around the world during the COVID-19 pandemic.
Read More...Failure of colony growth in probiotic Lactobacillus casei Shirota as result of preservative sorbic acid
This study tested the proficiency of different concentrations of the antimicrobial sorbic acid to inhibit the probiotic Lactobacillus casei Shirota. It was hypothesized that sorbic acid’s use as a bacterial deterrent would also target this bacterial strain of Lactobacillus. The results supported the hypothesis, with the colony count of L. casei Shirota having significant decreases at all concentrations of sorbic acid. These results additionally suggest that even under the FDA sorbic acid restrictions of 0.03% concentration, damaging effects could be seen in L. casei Shirota.
Read More...Pressure and temperature influence the efficacy of metal-organic frameworks for carbon capture and conversion
Metal-organic frameworks (MOFs) are promising new nanomaterials for use in the fight against climate change that can efficiently capture and convert CO2 to other useful carbon products. This research used computational models to determine the reaction conditions under which MOFs can more efficiently capture and convert CO2. In a cost-efficient manner, this analysis tested the hypothesis that pressure and temperature affect the efficacy of carbon capture and conversion, and contribute to understanding the optimal conditions for MOF performance to improve the use of MOFs for controlling greenhouse CO2 emissions.
Read More...A comparative analysis of synthetic and natural fabrics
The authors test the durability of synthetic versus non-synthetic fabrics though loose thread counts, color fade over time, and shrinkage tests.
Read More...Socio-economic factor impact on malnutrition in South Indian government school children
The authors look at malnutrition in children and how socio-economic factors impact this.
Read More...Efficacy of electrolytic treatment on degrading microplastics in tap water
Here seeking to identify a method to remove harmful microplastics from water, the authors investigated the viability of using electrolysis to degrade microplastics in tap water. Compared to control samples, they found electrolysis treatment to significantly the number of net microplastics, suggesting that this treatment could potentially implemented into homes or drinking water treatment facilities.
Read More...Interleukin family (IL-2 and IL-1β) as predictive biomarkers in Indian cancer patients: A proof of concept study
Here, recognizing that the immune response to cancer results in biomarkers that can be used to assess the immune status of cancer patients, the authors investigated the concentrations of key cytokines (TH1 and TH2 cytokines) in healthy controls and cancer patients. They identified significant changes in resting and activated cytokine profiles, suggesting that data of biomarkers such as these could serve as a starting point for further treatment with regard to a patient's specific immune profile.
Read More...Evaluating machine learning algorithms to classify forest tree species through satellite imagery
Here, seeking to identify an optimal method to classify tree species through remote sensing, the authors used a few machine learning algorithms to classify forest tree species through multispectral satellite imagery. They found the Random Forest algorithm to most accurately classify tree species, with the potential to improve model training and inference based on the inclusion of other tree properties.
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