This study explores the link between fingerprints and genetics by analyzing familial fingerprints to show how the fingerprints between family members, and in particular siblings, could be very similar. The hypothesis was that the fingerprints between siblings would be very similar and the dominant fingerprint features within the family would be the same throughout the generations. Fingerprints between the siblings showed a trend of similarity, with only very small differences which makes these fingerprints unique. This work helps to support the link between fingerprints and genetics while providing a modern technological application.

People react to music by moving and dancing. This study examined if different types of music were correlated with higher heart rates and if this was at all affected by music preferences.

The authors test the ability of planarians to remember conditioned stimuli following regeneration.

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.

Here, seeking to understand the effects of emotion on memory recall, the authors used a study of 30 teenagers, comparing their ability to recall details from information or narrative writing. They found improved recall of narrative writing, suggesting emotional response can contribute to improved memory recall.

To best identify tuberculosis and pneumonia diagnoses in chest x-rays, the authors compare different deep learning convolution neural networks.

In this study the authors develop an app for faster chess game entry method to help chess learners improve their game. This culminated in the Augmented Reality Chess Analyzer (ARChessAnalyzer) which uses traditional image and vision techniques for chess board recognition and Convolutional Neural Networks (CNN) for chess piece recognition.

In this article, the authors looked at developing a strategy that would allow for earlier diagnosis of Diabetes as that improves long-term outcomes. They were able to find that BMI, tricep skin fold thickness, and blood pressure are the risk factors with the highest accuracy in predicting diabetes risk.

In this study, the authors investigate the effects of acidity on the survival of commercial probiotic Lovebug bacterial strains.

The authors develop a new method for training machine learning algorithms to differentiate between hate speech and cultural speech in online platforms.