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Hydroponics is often promoted as a highly efficient alternative to traditional soil farming, but its effectiveness in small indoor polyculture systems is not well understood. In this study, students compared plant growth and maturity across hydroponic and soil-based indoor polycultures and found that soil grown plants were generally taller and more mature than those grown hydroponically. These results suggest that soil-based methods may outperform hydroponics in certain household polyculture settings.

This study found that anxiety induced by a suspenseful story increased communication between the brain’s salience, default mode, and central executive networks, with the central executive network acting as a bridge during peak tension. These findings suggest that anxiety alters large-scale brain connectivity patterns and may help inform future diagnostic tools and personalized treatments for anxiety disorders.

Advertising platforms like Google Ads use AI to drive the algorithms used to maximize advertisers benefits. This study shows that AI does not adjust it strategy based on auction type and highlights the limitations of AI running without explicit guidance.

In this study, the authors investigate the crystallization kinetics of vanillin thin films from a solution or a melt, as well as how a silane coating on the glass surface affects these properties.

This study explores the factors that influence coffee quality ratings using data from the Coffee Quality Institute. Through a regression model based on gradient descent, the authors aimed to predict coffee ratings (total cup points) and hypothesized that sweetness and the coffee producer would be the most influential factors.

The authors train a neural network to detect text-based emotions including joy, sadness, anger, fear, love, and surprise.

Pulmonary diseases like lung cancer and valley fever pose serious health challenges, making accurate and rapid diagnostics essential. This study developed a MATLAB-based software tool that uses computer vision techniques to differentiate between these diseases by analyzing features of lung nodules in CT scans, achieving higher precision than traditional methods.

The authors looked at using machine learning to identify skills needed to apply for certain jobs, specifically looking at different techniques to parse apart the text. They found that Bidirectional Encoder Representation of Transforms (BERT) performed best.

The authors use machine learning to develop an evidence-based detection tool for identifying human trafficking.

In this article the authors looked at different attributes of apps within the Google Play store to determine how those may impact the overall app rating out of five stars. They found that review count, amount of storage needed and when the app was last updated to be the most influential factors on an app's rating.