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The authors looked at whether youth use of marijuana related to later high-risk drug use. Using survey data from 2010-2019 they found that youth marijuana use did correlate to an increased risk of high-risk drug use.

The authors test the ability of planarians to remember conditioned stimuli following regeneration.

The authors survey high school students regarding the frequency of microaggressions such as name mispronunciation.

The COVID-19 pandemic demonstrated the depth and significance of healthcare inequality in the United States. Xiao, Xiao, and Gong examine healthcare disparities in the Richmond (Virginia) metropolitan area by analyzing whether people from disadvantaged populations must travel for longer to reach healthcare facilities.

The energy of an atom is extremely useful in nuclear physics and reaction mechanism pathway determination but is challenging to compute. This work aimed to synthesize regression models for Pople Gaussian expansions of Slater-type Orbitals (STO-nG) atomic energy vs. atomic number scatter plots to allow for easy approximation of atomic energies without using computational chemistry methods. The data indicated that of the regressions, sinusoidal regressions most aptly modeled the scatter plots.

The authors looked at the effect of microconvection on displacing bubbles during electrolysis. They found that microconvection does have a role in bubble displacement in water electrolysis which can be applied in the production of hydrogen.

Here, beginning from an interest in fractals, infinitely complex shapes. The authors investigated the fractal object that results from crumpling a sheet of paper. They determined its fractal dimension using continuous Chi-squared analysis, thereby testing and validating their model against the more conventional least squares analysis.

Although commonly associated with cryptocurrency, blockchains offer security that other databases could benefit from. These student authors tested a blockchain database framework, and by tracking runtime of four independent variables, they prove this framework is feasible for application.

In this study, the authors determined whether tautomerization dynamics in protic and aprotic solvents displayed differences in reaction rates and in the proportion of the keto and enol tautomers present.

Using a convolution neural network, these authors show machine learning can clinically diagnose breast cancer with high accuracy.