The authors survey high school students regarding the frequency of microaggressions such as name mispronunciation.
Read More...The frequency and psychological effects of name mispronunciation in an independent school
The authors survey high school students regarding the frequency of microaggressions such as name mispronunciation.
Read More...Simulating natural selection via autonomous agents: Environmental factors create unstable equilibria
Natural selection shapes the evolution of all organisms, and one question of interest is whether natural selection will reach a "stopping point": a stable, ideal, value for any particular trait. Madhan and Kanagavel tackle this question by building a computer simulation of trait evolution in organisms.
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...Building deep neural networks to detect candy from photos and estimate nutrient portfolio
The authors use pictures of candy wrappers and neural networks to improve nutritional accuracy of diet-tracking apps.
Read More...Tomato disease identification with shallow convolutional neural networks
Plant diseases can cause up to 50% crop yield loss for the popular tomato plant. A mobile device-based method to identify diseases from photos of symptomatic leaves via computer vision can be more effective due to its convenience and accessibility. To enable a practical mobile solution, a “shallow” convolutional neural networks (CNNs) with few layers, and thus low computational requirement but with high accuracy similar to the deep CNNs is needed. In this work, we explored if such a model was possible.
Read More...Pediatric probiotic culture survival study in acidic pH using an in vitro model
In this study, the authors investigate the effects of acidity on the survival of commercial probiotic Lovebug bacterial strains.
Read More...A novel CNN-based machine learning approach to identify skin cancers
In this study, the authors developed and assessed the accuracy of a machine learning algorithm to identify skin cancers using images of biopsies.
Read More...Innovative Treatment for Reducing Senescence and Revitalizing Aging Cells through Gene Silencing
Cellular senescence plays a key role in aging cells and is attributed to a number of disease and pathology. These authors find that genetic editing of both RPS6KB1 and PPARGC1A revitalizes a human skin fibroblast cell line.
Read More...Enhancing activity of antibiotics against Staphylococcus aureus with Shuang-Huang-Lian
Staphylococcus aureus is a major pathogen in both hospitals and the community and can cause systemic infections such as pneumonia. Multi-drug resistant strains, such as Methicillin-resistant S. aureus (MRSA) are particularly worrisome. In order to reduce the development of bacterial resistance, we hypothesized that two selected traditional Chinese medicines, Shuang-Huang-Lian (SHL) and Lan-Qin, would be effective against S. aureus. The results showed that SHL had a synergistic effect with gentamicin as well as additive effects with penicillin and cefazolin against S. aureus compared with using antibiotics alone.
Read More...A potentially underestimated source of CO2 and other greenhouse gases in agriculture
Here the authors investigated the role of agricultural fertilizers as potential contributors to greenhouse gas emissions. In contrast to the typical investigations that consider microbiological processes, the authors considered purely chemical processes. Based on their results they found that as much as 20.41% of all CO2 emission from land-based activities could be a result of mineral nitrogen fertilizers.
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