While 75% of waste in the United States is stated to be recyclable, only about 34% truly is. This project takes a stance to combat the pillars of mismanaged waste through a modern means of convenience: the TracedWaste app. The purpose of this study was to identify how individuals' waste disposal habits improved and knowledge increased (i.e. correctly disposing of waste, understanding negative incorrect waste disposal) due to their use of an informational waste management app as measured by a survey using a 1-5 Likert Scale. The results showed that the TracedWaste app helped conserve abundant resources such as energy and wood, decrease carbon emissions, and minimize financial toll all through reducing individual impact.

As levels of food waste continue to rise, it is essential to find improved techniques of prolonging the shelf life of produce. The authors aimed to find a simple, yet effective, method of slowing down spoilage in tomatoes. Linear regression analysis revealed that the tomatoes soaked salt water and not dried displayed the lowest correlation between time and spoilage, confirming that this preparation was the most effective.

In this study a student uses Daphnia magna, or water fleas, to assay the purity of local soil samples. Daphnia magna are a helpful organism to detect potentially harmful levels of toxins in water.

Your choice of font can impact more than style. Here the authors demonstrate that font choice can affect the amount of ink a given print-out requires. The authors estimate that a switch to Garamond font, size 12, by all teachers in his school district would save almost $21,000 annually.

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.

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.

In this article the authors look at sugar consumption and the relationship to productivity in the work/labor force.

Emissions from oil and natural gas (O&G) wells such as nitrogen dioxide (NO₂), volatile organic compounds (VOCs), and ozone (O₃) can severely impact the health of communities located near wells. In this study, we used O&G activity and wind-carried emissions to quantify the extent to which O&G wells affect the air quality of nearby communities, revealing that NO₂, NO_x, and NO are correlated to O&G activity. We then developed a novel land use regression (LUR) model using machine learning based on O&G prevalence to predict emissions.

Inefficient penetration of cancer drugs into the interior of the three-dimensional (3D) tumor tissue limits drugs' delivery. The authors hypothesized that the addition of phospholipase A2 (PLA2) would increase the permeability of the drug doxorubicin for efficient drug penetration. They found that 1 mM PLA2 had the highest permeability. Increased efficiency in drug delivery would allow lower concentrations of drugs to be used, minimizing damage to normal cells.

Identifying treatments that can stimulate hair growth use could help those struggling with undesirable hair loss. Here, the authors show that Fibroblast Growth Factors can stimulate the division of cells isolated from the mouse hair follicle. Their results suggest that this family of growth factors might be helpful in stimulating hair growth in living animals as well.