The authors looked at how the length of an audio clip used of a song impacted the ability to properly classify it by musical genre.
Read More...Impact of length of audio on music classification with deep learning
The authors looked at how the length of an audio clip used of a song impacted the ability to properly classify it by musical genre.
Read More...The relationship between digit ratio and personality: 4D:5D digit ratio, sex, and the trait of conscientiousness
In this study, the authors use quantitative digit ratio measurements and a survey of personality traits to evaluate the potential relationship between sex and levels of conscientiousness.
Read More...Drought prediction in the Midwestern United States using deep learning
The authors studied the ability of deep learning models to predict droughts in the midwestern United States.
Read More...Understanding the battleground of identity fraud
The authors looked at variables associated with identity fraud in the US. They found that national unemployment rate and online banking usage are among significant variables that explain identity fraud.
Read More...Reactivity-informed design, synthesis, and Michael addition kinetics of C-ring andrographolide analogs
Here, based on the identification of androgapholide as a potential therapeutic treatment against cancer, Alzheimer's disease, diabetes, and multiple sclerosis, due to its ability to inhibit a signaling pathway in immune system function, the authors sought ways to optimize the natural product human systems by manipulating its chemical structure. Through the semisynthesis of a natural product along with computational studies, the authors developed an understanding of the kinetic mechanisms of andrographolide and semisynthetic analogs in the context of Michael additions.
Read More...The Effects of Altered Microbiome on Caenorhabditis elegans Egg Laying Behavior
Since the discovery that thousands of different bacteria colonize our gut, many of which are important for human wellbeing, understanding the significance of balancing the different species on the human body has been intensely researched. Untangling the complexity of the gut microbiome and establishing the effect of the various strains on human health is a challenge in many circumstances, and the need for simpler systems to improve our basic understanding of microbe-host interactions seems necessary. C. elegans are a well-established laboratory animal that feed on bacteria and can thus serve as a less complex system for studying microbe-host interactions. Here the authors investigate how the choice of bacterial diet affects worm fertility. The same approach could be applied to many different outcomes, and facilitate our understanding of how the microbes colonizing our guts affect various bodily functions.
Read More...The impact of attending a more selective college on future income
Debates around legacy preferences, recruited athletes, and affirmative action in U.S. college admissions often focus on the belief that graduating from a more selective institution leads to higher future earnings. The study hypothesized a positive correlation between college selectivity and future income due to enhanced resources and opportunities.
Read More...Influenza vaccine effectiveness by age for Influenza A/B viruses between 2011-2020
In this manuscript the authors looked at current vaccine strategies against different strains of influenza. Looking at several factors they found that influenza strain as well as vaccinated age group, among other factors, impact vaccine effectiveness.
Read More...Estimation of Reproduction Number of Influenza in Greece using SIR Model
In this study, we developed an algorithm to estimate the contact rate and the average infectious period of influenza using a Susceptible, Infected, and Recovered (SIR) epidemic model. The parameters in this model were estimated using data on infected Greek individuals collected from the National Public Health Organization. Our model labeled influenza as an epidemic with a basic reproduction value greater than one.
Read More...Augmented Reality Chess Analyzer (ARChessAnalyzer): In-Device Inference of Physical Chess Game Positions through Board Segmentation and Piece Recognition using Convolutional Neural Networks
In this study the authors develop an app for faster chess game entry method to help chess learners improve their game. This culminated in the Augmented Reality Chess Analyzer (ARChessAnalyzer) which uses traditional image and vision techniques for chess board recognition and Convolutional Neural Networks (CNN) for chess piece recognition.
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