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The effect of economic downturns on the frequency of mass shootings

Bhupathi et al. | Jul 11, 2025

The effect of economic downturns on the frequency of mass shootings

Researching gun violence and mass shootings in the U.S. is difficult due to the lack of consistent data collection. Some studies have linked mass shootings to personal financial stress, but little formal research exists on the impact of broader economic conditions. This study hypothesized an inverse relationship between mass shootings and economic performance, using the S&P 500 and unemployment rate as indicators.

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A HOG feature extraction and CNN approach to Parkinson’s spiral drawing diagnosis

Tripathi et al. | Aug 09, 2024

A HOG feature extraction and CNN approach to Parkinson’s spiral drawing diagnosis

Parkinson’s disease (PD) is a prevalent neurodegenerative disorder in the U.S., second only to Alzheimer’s disease. Current diagnostic methods are often inefficient and dependent on clinical exams. This study explored using machine and deep learning to enhance PD diagnosis by analyzing spiral drawings affected by hand tremors, a common PD symptom.

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A Simple Printing Solution to Aid Deficit Reduction

Mirchandani et al. | Mar 09, 2014

A Simple Printing Solution to Aid Deficit Reduction

The printing-related expenditure that is budgeted in 2014 for U.S. Federal agencies is $1.8 billion. A sample of five publically available documents produced by various federal agencies is analyzed and the cost savings arising from a change in font type are estimated. The analysis predicts that the Government’s annual savings by switching to Garamond are likely to be about $234 million with worst-case savings of $62 million and best-case savings of $394 million. Indirect benefits arising from a less detrimental impact on the environment due to lower ink production and disposal volumes are not included in these estimates. Times New Roman is not as efficient as Garamond, and the third federally-recommended font, Century Gothic, is actually worse on average than the fonts used in the sample documents.

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Using broad health-related survey questions to predict the presence of coronary heart disease

Chavda et al. | Aug 23, 2024

Using broad health-related survey questions to predict the presence of coronary heart disease

Coronary heart disease (CHD) is the leading cause of death in the U.S., responsible for nearly 700,000 deaths in 2021, and is marked by artery clogging that can lead to heart attacks. Traditional prediction methods require expensive clinical tests, but a new study explores using machine learning on demographic, clinical, and behavioral survey data to predict CHD.

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Prediction of preclinical Aβ deposit in Alzheimer’s disease mice using EEG and machine learning

Igarashi et al. | Nov 29, 2022

Prediction of preclinical Aβ deposit in Alzheimer’s disease mice using EEG and machine learning

Alzheimer’s disease (AD) is a common disease affecting 6 million people in the U.S., but no cure exists. To create therapy for AD, it is critical to detect amyloid-β protein in the brain at the early stage of AD because the accumulation of amyloid-β over 20 years is believed to cause memory impairment. However, it is difficult to examine amyloid-β in patients’ brains. In this study, we hypothesized that we could accurately predict the presence of amyloid-β using EEG data and machine learning.

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