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The Role of Race in the Stereotyping of a Speaker’s Accent as Native or Non-native

Bhuvanagiri et al. | Jan 07, 2019

The Role of Race in the Stereotyping of a Speaker’s Accent as Native or Non-native

In the modern world, communication and mobility are no longer obstacles. A natural consequence is that people from all over the world are mixing like never before and national identity can no longer be determined simply by a person's appearance or manner of speech. In this article, the authors study how a person's accent interferes with the perception of a their national identity and proposes ways to eliminate such biases.

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Mitigating microplastic exposure from water consumption in junior high students and teachers

Chow et al. | May 10, 2024

Mitigating microplastic exposure from water consumption in junior high students and teachers
Image credit: Pixabay

Microplastics (MPs) are inorganic material that have been observed within items destined for human consumption, including water, and may pose a potential health hazard. Here we estimated the average amount of MPs junior high students and teachers consumed from different water sources and determined whether promoting awareness of microplastic (MP) exposure influenced choice of water source and potential MPs consumed.

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Building an affordable model wave energy converter using a magnet and a coil

Choy et al. | Jul 05, 2023

Building an affordable model wave energy converter using a magnet and a coil
Image credit: Joshua Smith

Here, seeking to identify a method to locally produce and capture renewable energy in Hawai'i and other island communities, the authors built and tested a small-scale model wave energy converter. They tested various configurations of a floated magnet surrounded by a wire coal, where the motion of the magnet due to a wave results in induction current in the coil. While they identified methods to increase the voltage and current generated, they also found that corrosion results in significant deterioration.

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Rhythmic lyrics translation: Customizing a pre-trained language model using stacked fine-tuning

Chong et al. | May 01, 2023

Rhythmic lyrics translation: Customizing a pre-trained language model using stacked fine-tuning
Image credit: Pixabay

Neural machine translation (NMT) is a software that uses neural network techniques to translate text from one language to another. However, one of the most famous NMT models—Google Translate—failed to give an accurate English translation of a famous Korean nursery rhyme, "Airplane" (비행기). The authors fine-tuned a pre-trained model first with a dataset from the lyrics domain, and then with a smaller dataset containing the rhythmical properties, to teach the model to translate rhythmically accurate lyrics. This stacked fine-tuning method resulted in an NMT model that could maintain the rhythmical characteristics of lyrics during translation while single fine-tuned models failed to do so.

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Deciphering correlation and causation in risk factors for heart disease with Mendelian randomization

Singh et al. | Feb 08, 2023

Deciphering correlation and causation in risk factors for heart disease with Mendelian randomization
Image credit: Robina Weermeijer

Here, seeking to identify the risk of coronary artery disease (CAD), a major cause of cardiovascular disease, the authors used Mendelian randomization. With this method they identified several traits such as blood pressure readings, LDL cholesterol and BMI as significant risk factors. While other traits were not found to be significant risk factors.

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