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The authors use molecular modeling to test analogs of the stearoyl-coenzyme A desaturase 1 (SCD1) inhibitor MF-438 with implications for future development of Parkinson's disease therapeutics.

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.

The authors looked at the antibacterial effects of oregano and star anise essential oils against E. coli or S. epidermis. They found that oregano oil showed antibacterial activity against both E. coli or S. epidermis, and that star anise oil had a larger zone of inhibition in E. coli than tetracycline, a conventional antibiotic.

Here, seeking a way to convert the vast quantity of seawater to drinking water, the authors investigated the purification of seawater to drinking water through electrodialysis. Using total dissolved solids (TDS) as their measure, they found that electrodialysis was able to produce deionized water with TDS values under the acceptable range for consumable water.

The energy conservation in a system of objects in collision depends on the elasticity of the objects and environmental factors such as air resistance. One system that relies heavily on elasticity is the Newton’s Cradle. We aimed to determine the extent to which these adhesives serve to mitigate or worsen the chaotic movements and elastic collisions.

In this article the authors created an interaction map of proteins involved in colorectal cancer to look for driver vs. non-driver genes. That is they wanted to see if they could determine what genes are more likely to drive the development and progression in colorectal cancer and which are present in altered states but not necessarily driving disease progression.

Using the data provided by the University of Twente High School Project on Astrophysics Research with Cosmics (HiSPARC), an analysis of locations for possible high-energy cosmic ray air showers was conducted. An example includes an analysis conducted of the high-energy rain shower recorded in January 2014 and the use of Stellarium™ to discern its location.

The authors look at using publicly available data and machine learning to see if they can develop a criminal activity index for counties within the state of California.

In this study the authors looked at sustainable ways to clean up oil spills that harm marine life. Using water spangle leaves and milk week the authors looked at the ability to recovery oil from both fresh and salt water and the ability to reuse the organic material to clean up spills. Their results show promise to help find a sustainable, eco-friendly way to clean up oil spills and protect marine life and habitats.

Neural machine translation (NMT) is a software that uses neural network techniques to translate text from one language to another. However, one of the most famous NMT models—Google Translate—failed to give an accurate English translation of a famous Korean nursery rhyme, "Airplane" (비행기). The authors fine-tuned a pre-trained model first with a dataset from the lyrics domain, and then with a smaller dataset containing the rhythmical properties, to teach the model to translate rhythmically accurate lyrics. This stacked fine-tuning method resulted in an NMT model that could maintain the rhythmical characteristics of lyrics during translation while single fine-tuned models failed to do so.