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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.

Cell segmentation is the task of identifying cell nuclei instances in fluorescence microscopy images. The goal of this paper is to benchmark the performance of representative deep learning techniques for cell nuclei segmentation using standard datasets and common evaluation criteria. This research establishes an important baseline for cell nuclei segmentation, enabling researchers to continually refine and deploy neural models for real-world clinical applications.

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.

One common age-related health problem is the loss of bone mineral density (BMD), which can lead to a variety of negative health outcomes, including increased risk of spinal fracture. In this study, the authors investigate risk factors that may be predictive of an individual's risk of spinal fracture. Their findings provide valuable information that clinicians can use in patient evaluations.

Large corporations often are known for their financial power, but what social and environmental power and conscious do they have? The more responsible corporations are in relation to environmental, social, and governance criteria the better they do fiscally.

Digital compasses are essential in technology that we use in our everyday lives: phones, vehicles, and more. Li and Liu address the accuracy of these devices by presenting a new algorithm for accurately calibrating low-cost magnetometers.

Mortality from opioid abuse has risen dramatically in the United States over the last two decades and has become a national health crisis. Bernstein and Chisesi explore whether revised pain management standards for hospitals contributed to this epidemic.

Some cancer treatments lose efficacy when combined with treatments for excessive stomach acid, due to the changes in the stomach environment caused by the stomach acid treatments. Lin and Lin investigate information on oral cancer drugs to see what information is available on interactions of these drugs.

The authors looked at two peptides, gluteomorphin and casomorphin, that are present after the digestion of bread and cheese. As these peptides can bind opioid receptors the authors want to know if they could be addictive in the same way as conventional opioids (i.e., morphine) are known to be. Their results in a planaria model suggest that both of these peptides are addictive.

Skin cancer is a common and potentially deadly form of cancer. This study’s purpose was to develop an automated approach for early detection for skin cancer. We hypothesized that convolutional neural network-based models using transfer learning could accurately differentiate between benign and malignant moles using natural images of human skin.