This study utilizes machine learning models to predict missing and unclear signs from the Indus script, a writing system from an ancient civilization in the Indian subcontinent.
Read More...Statistical models for identifying missing and unclear signs of the Indus script
This study utilizes machine learning models to predict missing and unclear signs from the Indus script, a writing system from an ancient civilization in the Indian subcontinent.
Read More...Who controls U.S. politics? An analysis of major political endorsements in U.S. midterm elections
The authors analyze political endorsement patterns and impacts from the 2018 and 2020 midterm elections and find that such endorsements may be predictable based on the ideological and demographic factors of the endorser.
Read More...Building an affordable model wave energy converter using a magnet and a coil
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.
Read More...Rhythmic lyrics translation: Customizing a pre-trained language model using stacked fine-tuning
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.
Read More...Deciphering correlation and causation in risk factors for heart disease with Mendelian randomization
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.
Read More...An accessible experiment to assess the impact of shapes of buildings and roofs on wind resistance
In this study, the authors determine which house model is most resistant to high winds by building smaller prototypes that could be tested with a handheld source of wind.
Read More...More efficient sources of water distribution for agricultural and general usage
Here, the authors investigated alternative methods to irrigate plants based on the their identification that current irrigation systems waste a large amount of fresh water. They compared three different delivery methods for water: conventional sprinkler, underground cloth, and a perforated pipe embedded in the soil. They found the cloth method to save the most water, although plant growth was slightly less in comparison to plants watered with the sprinkler method or pipe method.
Read More...Identification of a core set of model agnostic mRNA associated with nonalcoholic steatohepatitis (NASH)
In this study, the authors analyze gene expression datasets to determine if there is a core set of genes dysregulated during nonalcoholic steatohepatitis.
Read More...The impact of COVID-19 quarantine on physical activities in Basra, Iraq: A cross-sectional study
As the COVID-19 pandemic continues, the authors noticed a change in the physical activity of many people, as well as a change in the type of physical activity they practice. Here, the authors used a cross-sectional survey of 150 participants from the province of Basra in Iraq. They found an overall decrease in the number of days of physical activity for participants along with an increasing proportion of at-home exercises compared to other activities that are performed inside sports clubs during the pandemic.
Read More...Inflated scores on the online exams during the COVID-19 pandemic school lockdown
In this study, the authors explored whether students' test scores were significantly higher on online exams during the COVID-19 school lockdown when compared to those of the in-person exams before the lockdown.
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