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.
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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.
Read More...Exponential regression analysis of the Canadian Zero Emission Vehicle market’s effects on climate emissions in 2030
Here, the authors explored how the sale and use of electric vehicles could reduce emissions from the transport industry in Canada. By fitting the sale of total of electric vehicles with an exponential model, the authors predicted the number of electric vehicle sales through 2030 and related that to the average emission for such vehicles. Ultimately, they found that the sale and use of electric vehicles alone would likely not meet the 45% reduction in emissions from the transport industry suggested by the Canadian government
Read More...In vitro characterization of umilical cord-dervied MSC's supplemented with PLAY®:A potential FBS substitute
FBS is an important component in in vitro cell culture work, helping to provide needed nutrients to cells to grow. The authors look at the ability of an alternative to FBS to support cell growth in culture.
Read More...An accessible experiment to assess the impact of shapes of buildings and roofs on wind resistance
In this study, the authors determine which house model is most resistant to high winds by building smaller prototypes that could be tested with a handheld source of wind.
Read More...Thermoelectric cooling in greenhouses: Implications for small-holder production
The authors set to test a system that would help with the dehumidification and overall management of greehouses.
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