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The Clinical Accuracy of Non-Invasive Glucose Monitoring for ex vivo Artificial Pancreas

Levy et al. | Jul 10, 2016

The Clinical Accuracy of Non-Invasive Glucose Monitoring for <i>ex vivo</i> Artificial Pancreas

Diabetes is a serious worldwide epidemic that affects a growing portion of the population. While the most common method for testing blood glucose levels involves finger pricking, it is painful and inconvenient for patients. The authors test a non-invasive method to measure glucose levels from diabetic patients, and investigate whether the method is clinically accurate and universally applicable.

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The Effect of Font Type on a School’s Ink Cost

Mirchandani et al. | May 10, 2013

The Effect of Font Type on a School’s Ink Cost

Your choice of font can impact more than style. Here the authors demonstrate that font choice can affect the amount of ink a given print-out requires. The authors estimate that a switch to Garamond font, size 12, by all teachers in his school district would save almost $21,000 annually.

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Utilizing meteorological data and machine learning to predict and reduce the spread of California wildfires

Bilwar et al. | Jan 15, 2024

Utilizing meteorological data and machine learning to predict and reduce the spread of California wildfires
Image credit: Pixabay

This study hypothesized that a machine learning model could accurately predict the severity of California wildfires and determine the most influential meteorological factors. It utilized a custom dataset with information from the World Weather Online API and a Kaggle dataset of wildfires in California from 2013-2020. The developed algorithms classified fires into seven categories with promising accuracy (around 55 percent). They found that higher temperatures, lower humidity, lower dew point, higher wind gusts, and higher wind speeds are the most significant contributors to the spread of a wildfire. This tool could vastly improve the efficiency and preparedness of firefighters as they deal with wildfires.

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Interleukin family (IL-2 and IL-1β) as predictive biomarkers in Indian cancer patients: A proof of concept study

Parthasarathy et al. | Apr 03, 2023

Interleukin family (IL-2 and IL-1β) as predictive biomarkers in Indian cancer patients: A proof of concept study
Image credit: National Cancer Institute

Here, recognizing that the immune response to cancer results in biomarkers that can be used to assess the immune status of cancer patients, the authors investigated the concentrations of key cytokines (TH1 and TH2 cytokines) in healthy controls and cancer patients. They identified significant changes in resting and activated cytokine profiles, suggesting that data of biomarkers such as these could serve as a starting point for further treatment with regard to a patient's specific immune profile.

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Optimizing airfoil shape for small, low speed, unmanned gliders: A homemade investigation

Lara et al. | Mar 30, 2023

Optimizing airfoil shape for small, low speed, unmanned gliders: A homemade investigation
Image credit: Konrad Wojciechowski

Here, the authors sought to identify a method to optimize the lift generated by an airfoil based solely on its shape. By beginning with a Bernoullian model to predict an optimized wing shape, the authors then tested their model against other possible shapes by constructing them from Styrofoam and testing them in a small wind tunnel. Contrary to their hypothesis, they found their expected optimal airfoil shape did not result in the greatest lift generation. They attributed this to a variety of confounding variables and concluded that their results pointed to a correlation between airfoil shape and lift generation.

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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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Socio-economic and awareness correlates of physical activity of government school children in India

Nandivada et al. | Dec 11, 2022

Socio-economic and awareness correlates of physical activity of government school children in India

Here, based on the identified importance of physical activity in the development of young children, the authors investigated the effects of socioeconomic factors on the amount of physical activity of government-school children in India. They found significant differences between boys and girls, rural and urban, and children who were encouraged to exercise and those who were not. Overall, they suggest that their findings point to the important role of schools and communities in promoting healthy active lifestyles for developing children.

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Effect of heme vs. non-heme iron supplements on gut microbiome fitness

Dogra et al. | Nov 07, 2022

Effect of heme vs. non-heme iron supplements on gut microbiome fitness

Here, based on identification of iron deficiencies of a majority of people around the world, the authors sought to understand how the two main forms of dietary iron, heme and non-heme, affect the bacteria found in the human gut. by using a cell plate study, they found that bacterial growth increased with increasing concentration os either form of iron, up until the point where the high iron content resulted in cytotoxicity. They suggest this evidence points to the potential dangers of overconsumption of iron.

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The Impact of the COVID-19 Pandemic on Mental Health of Teens

Qureshi et al. | Nov 19, 2020

The Impact of the COVID-19 Pandemic on Mental Health of Teens

In this study, the authors investigate whether the COVID-19 pandemic is affecting the mental health of teens. Using data from a study done in Islamabad, Pakistan, the authors find that many teens between the ages of 13 and 19 show signs of mental illness. This study reports important data regarding the mental health of youth and points toward an increased need to address this topic during the pandemic.

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Varying Growth Hormone Levels in Chondrocytes Increases Proliferation Rate and Collagen Production by a Direct Pathway

Bennett et al. | Sep 03, 2019

Varying Growth Hormone Levels in Chondrocytes Increases Proliferation Rate and Collagen Production by a Direct Pathway

Bennett and Joykutty test whether growth hormone directly or indirectly affected the rate at which cartilage renewed itself. Growth hormone could exert a direct effect on cartilage or chondrocytes by modifying the expression of different genes, whereas an indirect effect would come from growth hormone stimulating insulin-like growth factor. The results from this research support the hypothesis that growth hormone increases proliferation rate using the direct pathway. This research can be used in the medical sciences for people who suffer from joint damage and other cartilage-related diseases, since the results demonstrated conditions that lead to increased proliferation of chondrocytes. These combined results could be applied in a clinical setting with the goal of allowing patient cartilage to renew itself at a faster pace, therefore keeping those patients out of pain from these chondrocyte-related diseases.

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