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The characterization of quorum sensing trajectories of Vibrio fischeri using longitudinal data analytics

Abdel-Azim et al. | Dec 16, 2023

The characterization of quorum sensing trajectories of <i>Vibrio fischeri</i> using longitudinal data analytics

Quorum sensing (QS) is the process in which bacteria recognize and respond to the surrounding cell density, and it can be inhibited by certain antimicrobial substances. This study showed that illumination intensity data is insufficient for evaluating QS activity without proper statistical modeling. It concluded that modeling illumination intensity through time provides a more accurate evaluation of QS activity than conventional cross-sectional analysis.

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Developing a neural network to model the mechanical properties of 13-8 PH stainless steel alloy

Zeng et al. | Sep 10, 2023

Developing a neural network to model the mechanical properties of 13-8 PH stainless steel alloy
Image credit: Pixabay

We systematically evaluated the effects of raw material composition, heat treatment, and mechanical properties on 13-8PH stainless steel alloy. The results of the neural network models were in agreement with experimental results and aided in the evaluation of the effects of aging temperature on double shear strength. The data suggests that this model can be used to determine the appropriate 13-8PH alloy aging temperature needed to achieve the desired mechanical properties, eliminating the need for many costly trials and errors through re-heat treatments.

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The influence of purpose-of-use on information overload in online social networking

Agarkar et al. | Nov 01, 2022

The influence of purpose-of-use on information overload in online social networking

Here, seeking to understand the effects of social media in relation to social media fatigue and/or overload in recent years, the authors used various linear models to assess the results of a survey of 27 respondents. Their results showed that increased duration of use of social media did not necessarily lead to fatigue, suggesting that quality may be more important than quantity. They also considered the purpose of an individual's social media usage as well as their engagement behavior during the COVID-19 pandemic.

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A novel deep learning model for visibility correction of environmental factors in autonomous vehicles

Dey et al. | Oct 31, 2022

A novel deep learning model for visibility correction of environmental factors in autonomous vehicles

Intelligent vehicles utilize a combination of video-enabled object detection and radar data to traverse safely through surrounding environments. However, since the most momentary missteps in these systems can cause devastating collisions, the margin of error in the software for these systems is small. In this paper, we hypothesized that a novel object detection system that improves detection accuracy and speed of detection during adverse weather conditions would outperform industry alternatives in an average comparison.

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