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Testing Epoxy Strength: The High Strength Claims of Selleys’s Araldite Epoxy Glues

Nguyen et al. | Jul 14, 2020

Testing Epoxy Strength: The High Strength Claims of Selleys’s Araldite Epoxy Glues

Understanding the techniques used to improve the adhesion strength of the epoxy resin is important especially for consumer applications such as repairing car parts, bonding aluminum sheeting, and repairing furniture or applications within the aviation or civil industry. Selleys Araldite epoxy makes specific strength claims emphasizing that the load or weight that can be supported by the adhesive is 72 kg/cm2. Nguyen and Clarke aimed to test the strength claims of Selley’s Araldite Epoxy by gluing two steel adhesion surfaces: a steel tube and bracket. Results showed that there is a lack of consideration by Selleys for adhesion loss mechanisms and environmental factors when accounting for consumer use of the product leading to disputable claims.

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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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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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The Effects of Ultraviolet Light on Escherichia coli

Kodoth et al. | Sep 07, 2015

The Effects of Ultraviolet Light on <em>Escherichia coli</em>

In this study E. coli bacteria was exposed to small UV lights currently used in school laboratories to see the effect on colony growth. This project explores how UV radiation methods could be applied in common households to inhibit bacterial growth.

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The Effect of UV Treatment on the Degradation of Compostable Polylactic Acid

Zhang et al. | Nov 28, 2013

The Effect of UV Treatment on the Degradation of Compostable Polylactic Acid

Polylactic acid (PLA) is a bio-based, compostable plastic that is comparable in cost to petroleum-based plastics. This study aims to evaluate the effects of UV treatment and mechanical chopping on the degradation of PLA. Based on their findings, the authors propose an alternative PLA degradation process that may be more time and energy efficient than current processes.

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