Here, seeking to understand the correlation of 50 of the most important economic indicators with inflation, the authors used a rolling linear regression to identify indicators with the most significant correlation with the Month over Month Consumer Price Index Seasonally Adjusted (CPI). Ultimately the concluded that the average gasoline price, U.S. import price index, and 5-year market expected inflation had the most significant correlation with the CPI.

This study aimed to predict and explain chaotic behavior in the Mandelbrot Set, one of the world’s most popular models of fractals and exhibitors of Chaos Theory. The authors hypothesized that repeatedly iterating the Mandelbrot Set’s characteristic function would give rise to a more intricate layout of the fractal and elliptical models that predict and highlight “hotspots” of chaos through their overlaps. The positive and negative results from this study may provide a new perspective on fractals and their chaotic nature, helping to solve problems involving chaotic phenomena.

In an extensive study of gene mutations, and their resulting effect on protein-protein interactions, Desai and Stork found that HTT-PRPF40B-MECP2 interactions are weakened with progression of Lopes-Maciel-Rodan syndrome.

There are two types of competing TV screens on the market, organic light emitting diode (OLED) and liquid crystal display (LCD). The better capability to exhibit black results in higher contrast images. Here, authors compared the ability of the two types of screens to show black in an environment eliminating external light.

This study investigated how fashion brand personalities are similar to people’s personalities and whether people may prefer a particular clothing brand based on their own personal traits. All together, Stevenson and Scott found that the Big Five Personality Factors are generally not related to participants’ preferred brand personalities. Generally, brands should consider different factors besides the Big Five Personality Factors for identifying potential customers.

Each day we are flooded with new items that promise us a better experience at a better price. This forces buyers to continuously chose between sticking to what they know, or trying something new. In turn, companies need to be aware of the factors affecting consumer choices, that too within the different fractions of society. In this study the authors investigate the effect of survey-based price setting on profits made based on African American teen purchases, and how African-American teen loyalty to a particular brand affects their willingness to pay a higher price than the market average for their preferred brand items.

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.

Recent declines in the brook trout population of the Lake Champlain Basin have made the genetic screening of this and other trout species of utmost importance. In this study, the authors collected and analyzed 21 DNA samples from Lake Champlain Basin trout populations and performed a phylogenetic analysis on these samples using the cytochrome b gene. The findings presented in this study may influence future habitat decisions in this region.

While resources on the safety of household cleaning products are plentiful, measures of efficacy of these cleaning chemicals against bacteria and viruses remain without standardization in the consumer market. The COVID pandemic has exasperated this knowledge gap, stoking the growth of misinformation and misuse surrounding household cleaning chemicals. Arriving at a time dire for sanitization standardization, the authors of this paper have created a quantifying framework for consumers by comparing a wide range of household cleaning products in their efficacy against bacteria generated by a safe and easily replicable yogurt model.

With advancements in machine learning a large data scale, high throughput virtual screening has become a more attractive method for screening drug candidates. This study compared the accuracy of molecular descriptors from two cheminformatics Mordred and PaDEL, software libraries, in characterizing the chemo-structural composition of 53 compounds from the non-nucleoside reverse transcriptase inhibitors (NNRTI) class. The classification model built with the filtered set of descriptors from Mordred was superior to the model using PaDEL descriptors. This approach can accelerate the identification of hit compounds and improve the efficiency of the drug discovery pipeline.