Since school bathrooms are widely suspected to be unsanitary, we wanted to compare the total amount of bacteria with the amount of bacteria that had ampicillin or streptomycin resistance across different school bathrooms in the Boston area. We hypothesized that because people interact with the faucet, outdoor handle, and indoor handle of the bathroom, based on whether or not they have washed their hands, there would be differences in the quantity of the bacteria presented on these surfaces. Therefore, we predicted certain surfaces of the bathroom would be less sanitary than others.

In this article the authors investigate whether there is a correlation between age of a person and their outlook on global issues such as technology, politics, and environment. They find a correlation between increased age and decreased optimism. However regardless of age, they find that respondents believe certain characteristics such as technology and willingness to change are essential for improvements.

Here the author investigates how much heat energy is output and recovered from a conventional electric light bulb.

Previous studies have found that how a food item is labeled may influence people's liking of it. This study used a cookie taste test to investigate whether people's liking of a dessert item would be swayed by the use of different labels.

The authors looked at the emissions from a small, carbureted engine that was being powered by a mix of ethanol and methanol compared to E10 gasoline. The found that across all four pollutants measured, the ethanol-methanol mixture resulted in less emissions compared to the E10 fuel.

The authors test whether basil can grow in a simulated Martian soil improved with a waste-based fertilizer called Milorganite.

In this article the authors look at the lung microbiome in patients with cystic fibrosis to determine what the major bacterial species present are.

The authors looked at the dynamics of tennis serves from professional and amateur athletes.

Intelligent vehicles utilize a combination of video-enabled object detection and radar data to traverse safely through surrounding environments. However, since the most momentary missteps in these systems can cause devastating collisions, the margin of error in the software for these systems is small. In this paper, we hypothesized that a novel object detection system that improves detection accuracy and speed of detection during adverse weather conditions would outperform industry alternatives in an average comparison.

With molecular energy being an integral element to the study of molecules and molecular interactions, computational methods to determine molecular energy are used for the preservation of time and resources. However, these computational methods have high demand for computer resources, limiting their widespread feasibility. The authors of this study employed machine learning to address this disadvantage, utilizing neural networks trained on different representations of molecules to predict molecular properties without the requirement of computationally-intensive processing. In their findings, the authors determined the Feedforward Neural Network, trained by two separate models, as capable of predicting molecular energy with limited prediction error.