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The authors looked at different strategies to extract oil from almonds to determine which gave the best results.

The authors created a 1D model to diagnose hepatomegaly and cirrhosis via ultrasound of the liver.

The global issue of water quality has led to the use of machine learning models, like ANN and SVM, to predict water potability. However, these models can be complex and resource-intensive. This research aimed to find a simpler, more efficient model for water quality prediction.

Here the authors sought to use three machine learning models to predict poverty levels in Cambodia based on available household data. They found teat multilayer perceptron outperformed the other models, with an accuracy of 87 %. They suggest that data-driven approaches such as these could be used more effectively target and alleviate poverty.

The authors investigate the ability of machine learning models to developing new drug-like molecules by learning desired chemical properties versus simply generating molecules that similar to those in the training set.

In this study, the authors develop a new hydrogel using photochemical crosslinking with bovine serum albumin and methylene blue. They find that this new hydrogel has some useful applications!