There are believed to be ~20,000 nebulae in the Milky Way Galaxy. However, humans have only cataloged ~1,800 of them even though we have gathered 1.3 million nebula images. Classification of nebulae is important as it helps scientists understand the chemical composition of a nebula which in turn helps them understand the material of the original star. Our research on nebulae classification aims to make the process of classifying new nebulae faster and more accurate using a hybrid of deep learning and machine learning techniques.

The purpose of this study was to investigate the relationship between colorism and police killings of unarmed African American suspects. The authors collected data from the Washington Post database, which reports unarmed African American victims from 2015–2021, and found that the victims who were killed by police were darker on average than a control population of African Americans that had not encountered the police.

Cancer is often caused by improper function of a few proteins, and sometimes it takes only a few proteins to malfunction to cause drastic changes in cells. Here the authors look at the genes that were mutated in patients with a type of pancreatic cancer to identify proteins that are important in causing cancer. They also determined which proteins currently lack effective treatment, and suggest that certain proteins (named KRAS, CDKN2A, and RBBP8) are the most important candidates for developing drugs to treat pancreatic cancer.

Seeking to investigate the effects of ambient pollutants on human respiratory health, here the authors used machine learning to examine asthma in Lost Angeles County, an area with substantial pollution. By using machine learning models and classification techniques, the authors identified that nitrogen dioxide and ozone levels were significantly correlated with asthma hospitalizations. Based on an identified seasonal surge in asthma hospitalizations, the authors suggest future directions to improve machine learning modeling to investigate these relationships.

In this study, the authors investigate the demographic indicators for voter shift between the 2016 and 2020 presidential elections based on demographic data put through a K-nearest neighbors classification algorithm and Principal Component Analysis.

This study compares different methods for cooking vegetables to determine which retain iron and ascorbic acid, or vitamin C, levels the most.

The authors looked at the relation between stress and motivation in high school students with 4+ AP classes that also played a varsity sport. No distinct correlation was observed, however, results indicated that there are other factors at play that influence both stress and motivation.

Kashyap Jha et al. look at the formulation of MAT20, a crude extract of the moringa, amla, and tulsi leaves, as a potential complementary and alternative medicine. Using HeLa cells, they find MAT20 up-regulates expression of inflammation and cell cytotoxicity markers. Their data is important for understanding the anti-cancer and anti-inflammatory properties of MAT20.

Pandemics involve the high transmission of a disease that impacts global and local health and economic patterns. Epidemiological models help propose pandemic control strategies based on non-pharmaceutical interventions such as social distancing, curfews, and lockdowns, reducing the economic impact of these restrictions. In this research, we utilized an epidemiological Susceptible, Exposed, Infected, Recovered, Deceased (SEIRD) model – a compartmental model for virtually simulating a pandemic day by day.

Here, seeking to better understand the genetic associations underlying non-small cell lung cancer, the authors screened hundreds of genes, identifying that KCNMB2 upregulation was significantly correlated with poor prognoses in lung cancer patients. Based on this, they used small interfering RNA to decrease the expression of KCNMB2 in A549 lung cancer cells, finding decreased cell proliferation and increased lung cancer cell death. They suggest this could lead to a new potential target for lung cancer therapies.