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Tax incentives for sustainable technology are a key part of the push for a greener future. However, these incentives may not reach all income strata equally. Using a machine learning approach, this study analyzed the distributional effects of residential energy tax credits across different income levels in the United States.

The authors looked at how soil temperature changes with fire to develop a sensor system that could aid in earlier detection of fires.

The authors looked at the ability to use graphite from pencils in anodes of lithium-anode batteries.

The authors evaluated the effect of concentration and variant of N-Acetylcysteine in hydrolyzing mucus.

The authors test the effect of test score comparison on the self-efficacy of adolescents versus adults.

The authors test the effectiveness of machine learning to predict onset of cardiovascular disease.

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

In this study, the authors address the concerns of heavy metal contamination in industrial and feedlot water waste. They test whether added probiotics are capable of taking up heavy metals in water to attenuate pollution.

Here, the authors aimed to apply home soil testing to identify the cause of the growth differences between two lemon trees. They hypothesized that differences in physical and chemical soil characteristics were influencing differences in soil productivity and plant growth. Overall, the study demonstrated the effectiveness of home soil testing to characterize soils and help homeowners solve common gardening problems.

Oil spills are one of the most devastating events for marine life. Finding ways to clean up oil spills without the need for harsh chemicals could help decrease the negative impact of such spills. Here the authors demonstrate that using a combination of several biodegradable substances can effectively adsorb oil in seawater in a laboratory setting. They suggest further exploring the potential of such a combination as a possible alternative to commonly-used non-biodegradable substances in oil spill management.