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Effects of Coolant Temperature on the Characteristics of Soil Cooling Curve

Wang et al. | Jan 16, 2020

Effects of Coolant Temperature on the Characteristics of Soil Cooling Curve

In this article, the authors investigate whether coolant temperature affects soil cooling curves of soil with otherwise identical properties. The coolant temperature is representative of environmental temperature, and the authors hypothesized that differences in this temperature would not affect the freezing temperature of soil. Their findings validated their hypothesis providing helpful information relevant to understanding how frost heaves happen and how to predict their occurrence more accurately.

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Changes for Development of Al2O3 Coated PVA (Polyvinyl Alcohol) Composite Nonwoven Separator For Improving Thermal and Electrochemical Properties

Kim et al. | Oct 16, 2019

Changes for Development of Al2O3 Coated PVA (Polyvinyl Alcohol) Composite Nonwoven Separator For Improving Thermal and Electrochemical Properties

Lithium-ion batteries, a breakthrough in chemistry that enabled the electronic revolution we live today have become an essential part of our day-to-day life. A phone battery running out after a heavy day of use with limited opportunities for recharging is a well-known and resented experience by almost everyone. How then can we make batteries more efficient? This paper proposes the use of a different type of separator, that improves the charging and discharging capacities of lithium ions compared to the classical separator. This and similar attempts to improve Lithium-ion battery function could facilitate the development of higher-performance batteries that work longer and withstand harsher use.

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Evaluating Biomarkers and Treatments for Acute Kidney Injury in a Zebrafish Model

Mathew et al. | Aug 11, 2019

Evaluating Biomarkers and Treatments for Acute Kidney Injury in a Zebrafish Model

Coronary Artery Disease (CAD) is the leading cause of death in the United States, and 81% of Acute Kidney Injury (AKI) patients in the renal fibrosis stage later develop CAD. In this study, Mathew and Joykutty aimed to create a cost-effective strategy to treat AKI and thus prevent CAD using a model of the zebrafish, Danio rerio. They first tested whether AKI is induced in Danio rerio upon exposure to environmental toxins, then evaluated nitrotyrosine as an early biomarker for toxin-induced AKI. Finally, they evaluated 4 treatments of renal fibrosis, the last stage of AKI, and found that the compound SB431542 was the most effective treatment (reduced fibrosis by 99.97%). Their approach to treating AKI patients, and potentially prevent CAD, is economically feasible for translation into the clinic in both developing and developed countries.

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Developing a Portable, Reusable, and Inexpensive Magnesium-Air Fuel Cell

Tota et al. | Mar 28, 2019

Developing a Portable, Reusable, and Inexpensive Magnesium-Air Fuel Cell

One of the greatest challenges we face today is the sustainable production, storage, and distribution of electrical power. One emerging technology with great promise in this area is that of metal-air fuel cells—a long-term and reusable electricity storage system made from a reactive metal anode and a saline solution. In this study the authors tested several different types of metal to determine which was the most suitable for this application. They found that a fuel cell with a magnesium anode was superior to fuel cells made from aluminum or zinc, producing a voltage and current sufficient for real-world applications such as charging a mobile phone.

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Artificial intelligence assisted violin performance learning

Zhang et al. | Aug 30, 2023

Artificial intelligence assisted violin performance learning
Image credit: Philip Myrtorp

In this study the authors looked at the ability of artificial intelligence to detect tempo, rhythm, and intonation of a piece played on violin. Technology such as this would allow for students to practice and get feedback without the need of a teacher.

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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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Reactivity-informed design, synthesis, and Michael addition kinetics of C-ring andrographolide analogs

Zhou et al. | Nov 17, 2022

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.

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