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Fitness social media is positively associated with the use of performance-enhancing drugs among young men

Tamaki et al. | Feb 01, 2024

Fitness social media is positively associated with the use of performance-enhancing drugs among young men
Image credit: Samuel Girven

Here the authors investigated the relationship between fitness-related social media and the high usage of performance-enhancing drugs (PEDs) specifically by men in the US age 18-35. In a survey with 149 participants they identified that young men that use fitness-related social media are more likely to use PEDs. Their results suggest the necessity to consider potential risk behaviors which may be related to social media consumption.

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Statistical evaluation of the effects of surface processing on aerospace fastener tested strength

Zeng et al. | Mar 31, 2023

Statistical evaluation of the effects of surface processing on aerospace fastener tested strength
Image credit: Robert Ruggiero

In the aerospace industry, various surface processing or coatings are widely used. However, no detailed research on the aerospace fastener tensile and double shear strength variation due to surface processing has been conducted. Thus, the purpose of this study was to systematically evaluate the effect of surface processing on the standard aerospace fastener's tensile and shear properties.

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Differential privacy in machine learning for traffic forecasting

Vinay et al. | Dec 21, 2022

Differential privacy in machine learning for traffic forecasting

In this paper, we measured the privacy budgets and utilities of different differentially private mechanisms combined with different machine learning models that forecast traffic congestion at future timestamps. We expected the ANNs combined with the Staircase mechanism to perform the best with every value in the privacy budget range, especially with the medium high values of the privacy budget. In this study, we used the Autoregressive Integrated Moving Average (ARIMA) and neural network models to forecast and then added differentially private Laplacian, Gaussian, and Staircase noise to our datasets. We tested two real traffic congestion datasets, experimented with the different models, and examined their utility for different privacy budgets. We found that a favorable combination for this application was neural networks with the Staircase mechanism. Our findings identify the optimal models when dealing with tricky time series forecasting and can be used in non-traffic applications like disease tracking and population growth.

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LawCrypt: Secret Sharing for Attorney-Client Data in a Multi-Provider Cloud Architecture

Zhang et al. | Jul 19, 2020

LawCrypt: Secret Sharing for Attorney-Client Data in a Multi-Provider Cloud Architecture

In this study, the authors develop an architecture to implement in a cloud-based database used by law firms to ensure confidentiality, availability, and integrity of attorney documents while maintaining greater efficiency than traditional encryption algorithms. They assessed whether the architecture satisfies necessary criteria and tested the overall file sizes the architecture could process. The authors found that their system was able to handle larger file sizes and fit engineering criteria. This study presents a valuable new tool that can be used to ensure law firms have adequate security as they shift to using cloud-based storage systems for their files.

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The Effect of Varying Training on Neural Network Weights and Visualizations

Fountain et al. | Dec 04, 2019

The Effect of Varying Training on Neural Network Weights and Visualizations

Neural networks are used throughout modern society to solve many problems commonly thought of as impossible for computers. Fountain and Rasmus designed a convolutional neural network and ran it with varying levels of training to see if consistent, accurate, and precise changes or patterns could be observed. They found that training introduced and strengthened patterns in the weights and visualizations, the patterns observed may not be consistent between all neural networks.

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The effect of molecular weights of chitosan on the synthesis and antifungal effect of copper chitosan

Byakod et al. | Apr 07, 2024

The effect of molecular weights of chitosan on the synthesis and antifungal effect of copper chitosan

Pathogenic fungi such as Alternaria alternata (A. alternata) can decimate crop yields and severely limit food supplies when left untreated. Copper chitosan (CuCts) is a promising alternative fungicide for developing agricultural areas due to being inexpensive and nontoxic. We hypothesized that LMWc CuCts would exhibit greater fungal inhibition due to the beneficial properties of LMWc.

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The impacts of different Al(NO3)3 concentrations on the mitotic index of Allium sativum

Jimenez Pol et al. | Jul 10, 2023

The impacts of different Al(NO<sub>3</sub>)<sub>3</sub> concentrations on the mitotic index of <i>Allium sativum</i>
Image credit: Kylie Paz

Recognizing the increasing threat of acid deposition inn soil through the reaction of NOx and SO2 pollutants with water in Spain, the authors investigates the effects of Al(NO3)3 concentrations on the health of Allium sativum. By tracking its mitotic index, they found a negative exponential correlation between Al(NO3)3 concentrations and the mitotic index of A. sativum.

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