Recurrent neural networks (RNNs) are useful for text generation since they can generate outputs in the context of previous ones. Baroque music and language are similar, as every word or note exists in context with others, and they both follow strict rules. The authors hypothesized that if we represent music in a text format, an RNN designed to generate language could train on it and create music structurally similar to Bach’s. They found that the music generated by our RNN shared a similar structure with Bach’s music in the input dataset, while Bachbot’s outputs are significantly different from this experiment’s outputs and thus are less similar to Bach’s repertoire compared to our algorithm.

Major depressive disorder (MDD) is a prevalent mood disorder. The direct causes and biological mechanisms of depression still elude understanding, though genetic factors have been implicated. This study looked to identify the mechanism behind the aberrant response to the dexamethasone suppression test (DST) displayed by MDD patients, in which they display a lack of cortisol suppression. Analysis revealed several pro-inflammatory genes that were significant and differentially expressed between affected and non-affected groups in response to the DST. Looking at ways to decrease the inflammatory response could have implications for treatment and may explain why some people treated for depression still display symptoms or may lead researchers to different classes of drugs for treatment.

In this study, the authors sample water at different points closer and closer to two different airports to determine if these airports may be contributing to water pollution, specifically by measuring metals, nitrates, and pH.

In this article the authors explore the peculiar behavior of sinking bubbles. By investigating the relationship between the viscosity of a fluid and the the formation of stationary bubbles, they identify why bubbles behave differently between in different fluids.

Collisions of heavy ions, such as muons result in jets and noise. In high-energy particle physics, researchers use jets as crucial event-shaped observable objects to determine the properties of a collision. However, many ionic collisions result in large amounts of energy lost as noise, thus reducing the efficiency of collisions with heavy ions. The purpose of our study is to analyze the relationships between properties of muons in a dimuon collision to optimize conditions of dimuon collisions and minimize the noise lost. We used principles of Newtonian mechanics at the particle level, allowing us to further analyze different models. We used simple Python algorithms as well as linear regression models with tools such as sci-kit Learn, NumPy, and Pandas to help analyze our results. We hypothesized that since the invariant mass, the energy, and the resultant momentum vector are correlated with noise, if we constrain these inputs optimally, there will be scenarios in which the noise of the heavy-ion collision is minimized.

Microwave energy (ME) is used in the medical field to denature protein structures, resulting in inactivation or destruction of abnormal cells. Identifying the extent of destruction of abnormal tissue (cancer tissue or tissue with abnormal electrical activity) is essential for accomplishing successful therapy and reducing collateral damage. Our study was an ex vivo assessment of the changes on ultrasound scans (US) in chicken tissue exposed to ME. We hypothesized that any changes in tissue structures would be recognized on the reflected ultrasound waves. Ultrasound scans of tissues change with exposure to microwaves with increasing reflection of ultrasound waves. With exposure to microwaves, surface level brightness on the ultrasound scans increases statistically significantly. The findings could be used in heat related (ME and radiofrequency) procedures where clinicians would be able to actively assess lesions in real-time. Further studies are required to assess changes in tissue during active exposure to different types of energies.

Researchers query whether reading comprehension is the same, worse, or better when using e-books as compared with standard paper texts. This study evaluated this question in the elementary school population. Our hypothesis was that information would be retained equally whether read from paper or from an electronic device. Each participant read four stories, alternating between electronic and paper media types. After each reading, the participants completed a five-question test covering the information read. The study participants correctly answered 167 out of 200 comprehension questions when reading from an electronic device. These same participants correctly answered 145 out of 200 comprehension questions when reading from paper. At a significance level of p < 0.05, the results showed that there was a statistically significant difference in reading comprehension between the two media, demonstrating better comprehension when using electronic media. The unexpected results of this study demonstrate a shift in children’s performance and desirability of using electronic media as a reading source.

For public health, drinking water should be free of bacterial contamination. The objective of this research is to identify the fate of bacteria if drinking water becomes contaminated and inform consumers on which water type enables the least bacteria to survive. We hypothesized that bottled mineral water would provide the most sufficient conditions for E. coli to survive. We found that if water becomes contaminated, the conditions offered by the three water types at room temperature allow E. coli to survive up to three days. At 72 hours, the bottled spring water had the highest average colony forming units (CFUs), with tap and mineral water CFU values statistically lower than spring water but not significantly different from each other. The findings of this research highlight the need of implementing accessible quality drinking water for the underserved population and for the regulation of water sources.

Here, authors characterize how different acoustics affect the properties of a Bunsen-type flame.

The authors investigate how well AI-detection machine learning models can detect real versus AI-generated art across different art styles.