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Here, in an effort to develop a model to predict future groundwater levels, the authors tested a tree-based automated artificial intelligence (AI) model against other methods. Through their analysis they found that groundwater levels in Texas aquifers are down significantly, and found that tree-based AI models most accurately predicted future levels.

In a common high school experiment to measure friction coefficients, a weighted mass attached to a spring scale is dragged across a surface at a constant velocity. While the constant velocity is necessary for an accurate measurement, it can be difficult to maintain and this can lead to large errors. Here, the authors designed a new experiment to measure friction coefficients in the classroom using only static force and show that their method has a lower standard deviation than the traditional experiment.

Because of the COVID-19 pandemic, people are missing important appointments because they are viewed as nonessential, possibly including children's pediatric dentist appointments. This study aims to determine how the COVID-19 pandemic has effected parents' willingness to allow children to visit pediatric dental practices and what safety measures would make them feel more comfortable visiting the dentist. The authors found a weak positive correlation between parents' unwillingness to allow their child to visit the dentist, however overall anxiety towards visiting the dentist during the pandemic was low.

Droughts kill over 45,000 people yearly and affect the livelihoods of 55 million others worldwide, with climate change likely to worsen these effects. However, unlike other natural disasters (hurricanes, etc.), there is no early detection system that can predict droughts far enough in advance to be useful. Bora, Caulkins, and Joycutty tackle this issue by creating a drought prediction model.

The authors analyze political endorsement patterns and impacts from the 2018 and 2020 midterm elections and find that such endorsements may be predictable based on the ideological and demographic factors of the endorser.

The authors looked at the ability to detect heart disease before the onset of severe clinical symptoms.

Current drug discovery processes can cost billions of dollars and usually take five to ten years. People have been researching and implementing various computational approaches to search for molecules and compounds from the chemical space, which can be on the order of 1060 molecules. One solution involves deep generative models, which are artificial intelligence models that learn from nonlinear data by modeling the probability distribution of chemical structures and creating similar data points from the trends it identifies. Aiming for faster runtime and greater robustness when analyzing high-dimensional data, we designed and implemented a Hybrid Quantum-Classical Generative Adversarial Network (QGAN) to synthesize molecules.

The authors studied the impact of AI face-tracking technology on the immersiveness of videogames as an alternative to virtual reality gaming.

Here, the authors wanted to explore mathematical paradoxes in which there are multiple contradictory interpretations or analyses for a problem. They used ChatGPT to generate a novel dataset of fairy tales. They found statistical differences between the artificially generated text and human produced text based on the distribution of parts of speech elements.

The authors looked at different models of semantic segmentation to determine which may be best used in the future for segmentation of CT scans to help diagnose certain conditions.