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Hybrid Quantum-Classical Generative Adversarial Network for synthesizing chemically feasible molecules

Sikdar et al. | Jan 10, 2023

Hybrid Quantum-Classical Generative Adversarial Network for synthesizing chemically feasible molecules

Current drug discovery processes can cost billions of dollars and usually take five to ten years. People have been researching and implementing various computational approaches to search for molecules and compounds from the chemical space, which can be on the order of 1060 molecules. One solution involves deep generative models, which are artificial intelligence models that learn from nonlinear data by modeling the probability distribution of chemical structures and creating similar data points from the trends it identifies. Aiming for faster runtime and greater robustness when analyzing high-dimensional data, we designed and implemented a Hybrid Quantum-Classical Generative Adversarial Network (QGAN) to synthesize molecules.

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Tap water quality analysis in Ulaanbaatar City

Munkhbat et al. | Sep 25, 2022

Tap water quality analysis in Ulaanbaatar City

There have been several issues concerning the water quality in Ulaanbaatar, Mongolia in the past few years. This study, we collected 28 samples from 6 districts of Ulaanbaatar to check if the water supply quality met the standards of the World Health Organization, the Environmental Protection Agency, and a Mongolian National Standard. Only three samples fully met all the requirements of the global standards. Samples in Zaisan showed higher hardness (>120 ppm) and alkalinity levels (20–200 ppm) over the other districts in the city. Overall, the results show that it is important to ensure a safe and accessible water supply in Ulaanbaatar to prevent future water quality issues.

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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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Are Teens Willing to Pay More for Their Preferred Goods?

Johnson et al. | Sep 28, 2019

Are Teens Willing to Pay More for Their Preferred Goods?

Each day we are flooded with new items that promise us a better experience at a better price. This forces buyers to continuously chose between sticking to what they know, or trying something new. In turn, companies need to be aware of the factors affecting consumer choices, that too within the different fractions of society. In this study the authors investigate the effect of survey-based price setting on profits made based on African American teen purchases, and how African-American teen loyalty to a particular brand affects their willingness to pay a higher price than the market average for their preferred brand items.

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Measuring Exoplanetary Radii Using Transit Photometry

Tang et al. | May 07, 2019

Measuring Exoplanetary Radii Using Transit Photometry

Studying exoplanets, or planets that orbit a star other than the Sun, is critical to a greater understanding the formation of planets and how Earth's solar system differs from others. In this study the authors analyze the transit light curves of three hot Jupiter exoplanets to ultimately determine if and how these planets have changed since their discovery.

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What is the optimal fuel for space flight? Efficiency, cost, and environmental impact

Kapitonova et al. | Dec 28, 2023

What is the optimal fuel for space flight? Efficiency, cost, and environmental impact
Image credit: NASA

Here, the authors sought to investigate the efficiency, cost, and environmental impact of several possible propellants that are or could be used for space flight. By deriving three novel equations, they identified harm, energy, and cost scores for each fuel, suggesting that considering each factor will be essential to the ongoing growth of the space industry.

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Estimating Paleoenvironments Utilizing Foraminiferal Fossils from the Toyohama Formation, Aichi Prefecture, Central Japan

Kimitsuki et al. | Dec 11, 2017

Estimating Paleoenvironments Utilizing Foraminiferal Fossils from the Toyohama Formation, Aichi Prefecture, Central Japan

Foraminifera are a diverse phylum of marine protists that produce elaborate shells. Because of their abundance and morphological diversity, foraminiferal fossil assemblages are used for biostratigraphy, to accurately date sedimentary rocks and to characterize past ocean environments. In this paper, authors collected fossils within the Morozaki Group in central Honshu, Japan, to assess past marine environments and species diversity.

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Aberrant response to dexamethasone suppression test associated with inflammatory response in MDD patients

Ulery et al. | Nov 06, 2023

Aberrant response to dexamethasone suppression test associated with inflammatory response in MDD patients

Major depressive disorder (MDD) is a prevalent mood disorder. The direct causes and biological mechanisms of depression still elude understanding, though genetic factors have been implicated. This study looked to identify the mechanism behind the aberrant response to the dexamethasone suppression test (DST) displayed by MDD patients, in which they display a lack of cortisol suppression. Analysis revealed several pro-inflammatory genes that were significant and differentially expressed between affected and non-affected groups in response to the DST. Looking at ways to decrease the inflammatory response could have implications for treatment and may explain why some people treated for depression still display symptoms or may lead researchers to different classes of drugs for treatment.

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Functional Network Connectivity: Possible Biomarker for Autism Spectrum Disorders (ASD)

Wang et al. | Feb 23, 2015

Functional Network Connectivity: Possible Biomarker for Autism Spectrum Disorders (ASD)

Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder and is difficult to diagnose in young children. Here magnetoencephalography was used to compare the brain activity in patients with ASD to patients in a control group. The results show that patients with ASD have a high level of activity in different areas of the brain than those in the control group.

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Assessing Attitude Across Different Age Groups in Regard to Global Issues: Are Kids More Optimistic Than Adults?

Luck et al. | Jan 11, 2020

Assessing Attitude Across Different Age Groups in Regard to Global Issues: Are Kids More Optimistic Than Adults?

In this article the authors investigate whether there is a correlation between age of a person and their outlook on global issues such as technology, politics, and environment. They find a correlation between increased age and decreased optimism. However regardless of age, they find that respondents believe certain characteristics such as technology and willingness to change are essential for improvements.

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