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In this study, the authors investigate just how effectively paper towels can absorb different types of liquid and whether changing the properties of the towel (such as folding it) affects absorbance. Using variables of either different liquid types or the folded state of the paper towels, they used thorough approaches to make some important and very useful conclusions about optimal ways to use paper towels. This has important implications as we as a society continue to use more and more paper towels.

The authors tested the impact of various additives on biopolymer degradation.

The authors looked at the ability of berberine in combination with melatonin to have anticancer effects when tested in an in vitro cell model.

The authors examined the effect of varying glucose concentrations on cut rose longevity.

The authors studied the response of various construction materials to UV solar radiation and heat.

Here the authors performed a comparative analysis to investigate the viability of using PLAY® instead of fetal bovine serum (FBS) as a growth medium to culture cells with an enzyme-linked immunosorbent assay.

The authors use machine learning and electroencephalogram data to propose a method for improving epilepsy diagnosis.

The authors use the unique movements of the jumping gall wasp to study momentum transfer with potential applications in robotics and extraterrestrial research.

The authors looked at the antibacterial effects of oregano and star anise essential oils against E. coli or S. epidermis. They found that oregano oil showed antibacterial activity against both E. coli or S. epidermis, and that star anise oil had a larger zone of inhibition in E. coli than tetracycline, a conventional antibiotic.

Many common respiratory illnesses like bronchitis, asthma, and chronic obstructive pulmonary disease (COPD) lead to bronchial inflammation and, subsequently, a blockage. However, there are many difficulties in measuring the severity of the blockage. A numeric metric to determine the degree of the blockage severity is necessary. To tackle this demand, we aimed to develop a novel human respiratory model and design a deep-learning program that can constantly monitor and report bronchial blockage by recording breath sounds in a non-intrusive way.