In this study, the authors develop an architecture to implement in a cloud-based database used by law firms to ensure confidentiality, availability, and integrity of attorney documents while maintaining greater efficiency than traditional encryption algorithms. They assessed whether the architecture satisfies necessary criteria and tested the overall file sizes the architecture could process. The authors found that their system was able to handle larger file sizes and fit engineering criteria. This study presents a valuable new tool that can be used to ensure law firms have adequate security as they shift to using cloud-based storage systems for their files.

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder and is difficult to diagnose in young children. Here magnetoencephalography was used to compare the brain activity in patients with ASD to patients in a control group. The results show that patients with ASD have a high level of activity in different areas of the brain than those in the control group.

This study used hand-collected Greenhouse gas (GHG) emissions data from the Environmental Protection Agency (EPA) and aimed to understand the determinants and incentives of GHG emissions reduction. It explored how companies’ financials, Chief Executive Officer (CEO) compensation, and corporate governance affected GHG emissions. Results showed that companies reporting GHG emissions were wide-spread among the 48 industries represented by two-digit Standard Industrial Classification (SIC) codes.

Fertilizers are commonly used to improve agricultural yield. Unfortunately, chemical fertilizers can seep into drinking water, potentially harming humans and other forms of life. Here, the authors investigate the effect of fertilizer on the water quality of Saratoga Creek over time. They find that fertilizers can alter the acidity of the creek's water, which can be harmful to aquatic species, as well as increase the levels of nitrates temporarily.

Every year, around 40% of undergraduate students in the United States discontinue their studies, resulting in a loss of valuable education for students and a loss of money for colleges. Even so, colleges across the nation struggle to discover the underlying causes of these high dropout rates. In this paper, the authors discuss the use of machine learning to find correlations between the built environment factors and the retention rates of colleges. They hypothesized that one way for colleges to improve their retention rates could be to improve the physical characteristics of their campus to be more pleasing. The authors used image classification techniques to look at images of colleges and correlate certain features like colors, cars, and people to higher or lower retention rates. With three possible options of high, medium, and low retention rates, the probability that their models reached the right conclusion if they simply chose randomly was 33%. After finding that this 33%, or 0.33 mark, always fell outside of the 99% confidence intervals built around their models’ accuracies, the authors concluded that their machine learning techniques can be used to find correlations between certain environmental factors and retention rates.

Coronary artery bypass grafts are a common technique to treat coronary heart disease. The authors compared the efficacy of suturing and stapling techniques using an artificial heart pump and silicone tubing and found that suturing, while more time and skill intensive, held pressure in the tubing better than stapling.

Here, seeking to address the growing threat of multidrug-resistant bacteria (MDR). the authors used in silico virtual screening to target MDR Pseudomonas aeruginosa. They considered a key protein in its biosynthesis and virtually screened 20,000 candidates and 30 derivatives of brequinar. In the end, they identified a possible candidate with the highest degree of potential to inhibit the pathogen's lipid A synthesis.

In this study, the authors test new antimicrobials by measuring the ability of extracts from Australian-native Myrtaceae species to induce death of two bacteria S. aureus and P. aeruginosa.

Here recognizing the importance of urban green space for the health of humans and other organisms, the authors investigated if mathematical modeling can be used to develop an urban greenery management plan with high eco-sustainability by calculating the composition of a plant community. They optimized and tested their model against green fields in a Beijing city park. Although the compositions predicted by their models differed somewhat from the composition of testing fields, they conclude that by using a mathematical model such as this urban green space can be finely designed to be ecologically and economically sustainable.

Palermo et al. examined the effect of group size on drinking habits of college and high school students. The authors found that both high school and college students tended to consume the most alcohol in group sizes of 4 or more, independent of how frequently they drink. They also found that the proportion of college students that drink is nearly twice the proportion of high school students that drink. This study supports previous findings that underage drinking happens in large groups and suggests that effective intervention in underage drinking would be at the group level.