In this paper, we measured the privacy budgets and utilities of different differentially private mechanisms combined with different machine learning models that forecast traffic congestion at future timestamps. We expected the ANNs combined with the Staircase mechanism to perform the best with every value in the privacy budget range, especially with the medium high values of the privacy budget. In this study, we used the Autoregressive Integrated Moving Average (ARIMA) and neural network models to forecast and then added differentially private Laplacian, Gaussian, and Staircase noise to our datasets. We tested two real traffic congestion datasets, experimented with the different models, and examined their utility for different privacy budgets. We found that a favorable combination for this application was neural networks with the Staircase mechanism. Our findings identify the optimal models when dealing with tricky time series forecasting and can be used in non-traffic applications like disease tracking and population growth.

Here, seeking to identify an optimal method to classify tree species through remote sensing, the authors used a few machine learning algorithms to classify forest tree species through multispectral satellite imagery. They found the Random Forest algorithm to most accurately classify tree species, with the potential to improve model training and inference based on the inclusion of other tree properties.

Here, the authors investigated the most efficient way to position magnets to hold the most pieces of paper on the surface of a refrigerator. They used a regression model along with an artificial neural network to identify the most efficient positions of four magnets to be at the vertices of a rectangle.

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.

Luteolin (3′,4′,5,7-tetrahydroxyflavone) is a flavonoid that occurs in fruits, vegetables, and herbs. Research suggests that luteolin is effective against various forms of cancer by triggering apoptosis pathways. This experiment analyzes the effects of luteolin on the cell viability of malignant melanoma cells using an in vitro experiment to research alternative melanoma treatments and hopefully to help further cancer research as a whole.

In this work, the authors compared the effects of common natural products, including sesame, cinnamon, garlic, moringa and turmeric on tumor growth in Drosophila eyes. The data showed that these natural products cannot be used to reduce tumor growth once it has completely formed. However, the data suggested that some natural products can reduce cancer cell growth when tumors are treated early.

This study uses a fruit fly model of type 1 diabetes (T1D) to determine whether strengthening intestinal tight junctions to reduce intestinal permeability would improve T1D symptoms.

This study's goal was to identify the Mach numbers for which electrostatic drag and heat transfer manipulation would be most applicable inside the stratosphere. The experiments were conducted using computational fluid dynamics software. The study demonstrated that, on average, higher Mach speeds resulted in a considerably higher potential decrease in density. The study highlights that further research on the surface charge method is warranted to explore higher hypersonic speeds within the stratosphere.

PVC is a widely used plastic that poses harmful health hazards when burned. In this study, the authors ask whether or not burned PVC (PVC char) affects bacterial transformation.

Here the authors investigate whether there are mathematical inaccuracies of perspective in artists' paintings that are undetectable with our naked eyes. Using the cross-ratio method, they find that there are three significant errors in various famous paintings which increase as the structures in the paintings recede from the viewer.