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.
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Investigating the impact of the COVID-19 pandemic on the cognitive dissonance of adolescents
The authors survey adolescents about aspects of the COVID-19 pandemic to explore perspectives that may give rise to cognitive dissonance.
Read More... Machine learning-based enzyme engineering of PETase for improved efficiency in plastic degradation
Here, recognizing the recognizing the growing threat of non-biodegradable plastic waste, the authors investigated the ability to use a modified enzyme identified in bacteria to decompose polyethylene terephthalate (PET). They used simulations to screen and identify an optimized enzyme based on machine learning models. Ultimately, they identified a potential mutant PETases capable of decomposing PET with improved thermal stability.
Read More...The effects of age on quality of mental health during the COVID-19 pandemic
The impact of age on mental health is a crucial yet understudied aspect of public health. While mental health is gaining recognition as a vital component of overall well-being, its correlation with age remains largely unexplored. In Canada, where the median age has risen significantly over the past half-century, understanding this relationship becomes increasingly pertinent. Researchers hypothesized that older adults would exhibit lower rates of mental health disorders and report better perceived mental health due to increased emotional stability and maturity.
Read More...Genetic algorithm based features selection for predicting the unemployment rate of India
The authors looked at using genetic algorithms to look at the Indian labor market and what features might best explain any variation seen. They found that features such as economic growth and household consumption, among others, best explained variation.
Read More...Examining the relationship between screen time and achievement motivation in an adolescent population
In this study, the authors conduct a survey of high school students to evaluate the effects of screen time and habits on motivation.
Read More...Modeling Hartree-Fock approximations of the Schrödinger Equation for multielectron atoms from Helium to Xenon using STO-nG basis sets
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.
Read More...Evaluating the predicted eruption times of geysers in Yellowstone National Park
The authors compare the predicted versus actual geyser eruption times for the Old Faithful and Beehive Geysers at Yellowstone National Park.
Read More...Linear and non-linear summation of responses to visual and olfactory cues in male Drosophila melanogaster
In this study, the authors investigate whether phototaxis and odortaxis in Drosophila melanogaster occurs through linear summation of cues including light and attractive odorants.
Read More...Taft linear free-energy relationships in the biocatalytic hydrolysis of sterically hindered nitrophenyl ester substrates
This study applies Taft linear free-energy relationships to study kinetic trends in the enzymatic hydrolysis of sterically hindered substrates.
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