Recurrent neural networks (RNNs) are useful for text generation since they can generate outputs in the context of previous ones. Baroque music and language are similar, as every word or note exists in context with others, and they both follow strict rules. The authors hypothesized that if we represent music in a text format, an RNN designed to generate language could train on it and create music structurally similar to Bach’s. They found that the music generated by our RNN shared a similar structure with Bach’s music in the input dataset, while Bachbot’s outputs are significantly different from this experiment’s outputs and thus are less similar to Bach’s repertoire compared to our algorithm.
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Population Forecasting by Population Growth Models based on MATLAB Simulation
In this work, the authors investigate the accuracy with which two different population growth models can predict population growth over time. They apply the Malthusian law or Logistic law to US population from 1951 until 2019. To assess how closely the growth model fits actual population data, a least-squared curve fit was applied and revealed that the Logistic law of population growth resulted in smaller sum of squared residuals. These findings are important for ensuring optimal population growth models are implemented to data as population forecasting affects a country's economic and social structure.
Read More...Crystallization kinetics of vanillin thin films
In this study, the authors investigate the crystallization kinetics of vanillin thin films from a solution or a melt, as well as how a silane coating on the glass surface affects these properties.
Read More...Observing food and density effects on the reproductive strategies of Heterandria formosa
The authors looked at the impact of different harvest and feeding treatments on Heterandria formosa over three generations as a model for changes in marine ecosystems.
Read More...Cathodal Galvanotaxis: The Effect of Voltage on the distribution of Tetrahymena pyriformis
The surface of the unicellular eukaryote, Tetrahymena pyriformis, is covered with thousands of hair-like cilia. These cilia are very similar to cilia of the human olfactory and respiratory tracts making them model organisms for studying cilia function and pathology. The authors of this study investigated the effect of voltage on T. pyriformis galvanotaxis, the movement towards an electrical stimulus. They observed galvanotaxis towards the cathode at voltages over 4V which plateau, indicating opening of voltage gated-ion channels to trigger movement.
Read More...Preliminary investigation of Allosauroidea facial integument and the evolution of theropod facial armor
The facial integument, or external skin tissues, were assessed on set of dinosaurs from the Allosauroidea clade to test whether dermal patterns served specific functions.
Read More...Comparing Virulence of Three T4 Bacteriophage Strains on Ampicillin-Resistant and Sensitive E. coli Bacteria
In this study, the authors investigate an alternative way to kill bacteria other than the use of antibiotics, which is useful when considering antibiotic-resistance bacteria. They use bacteriophages, which are are viruses that can infect bacteria, and measure cell lysis. They make some important findings that these bacteriophage can lyse both antibiotic-resistant and non-resistant bacteria.
Read More...Innovative fake health news detection: Integrating emotional features into graph neural networks
This manuscript tackles a major social issue in the health news sector, with social media being one of the primary sources of information and a prime spot to propagate fake news. The author proposes X-HND , which is a unique architecture that combines emotional and contextual analysis in a Graph Neural Network to accurately detect fake news. This was a multi-step process which involved the creation of a custom health news dataset (HNDataset), and an emotional variant that uses RoBERTa to extract emotion. These dataset were then used to prove the hypothesis that accuracy increases when the custom dataset is used to train the model and that with the integration of emotion capture, the detection accuracy increases further.
Read More...AI-designed mini-protein targeting claudin-5 to enhance blood–brain barrier integrity
The authors employ computational protein design to identify a mini-protein with the potential to enhance binding of the tight junction protein, claudin-5, at the blood-blood barrier with therapeutic potential for neurodegenerative diseases.
Read More...Deep sequential models versus statistical models for web traffic forecasting
The authors looked at ways to provide better forecasting on website traffic. They found that deep learning models performed better than statistical models.
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