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Greenspaces (urban and wetland areas that contain vegetation) are beneficial to reducing pollution, while airplanes are a highly-polluting method of transportation. The authors examine the intersection of these two environmental factors by processing satellite images to reveal what percentage of flight paths go over greenspaces at major US airports.

Some spices have antimicrobial or antibacterial properties that people have already tested. Turmeric has a wide variety of uses and has even been implemented in alternative medicine as a treatment for cancer, inflammation, osteoarthritis, and other diseases. We tested the antimicrobial effects of turmeric under two different pHs to characterize this effect in vitro. Decreasing the pH of a solution of turmeric may increase antibacterial properties.

This study collected samples from water bodies near hog farms and an aquatic environment not near a hog farm. It was hypothesized that water bodies near the hog farms would have lower water quality with higher turbidity, total dissolved solids (TDS), and pH than the water body not in proximity to a hog farm because of water contamination with hog waste. Results showed that the turbidity was 4–6 times higher, TDS was 1.5–2 times higher, and pH was 3 units higher in the 2 experimental locations compared to the control location. This study and its findings are important for understanding the impact of hog farming on the proximal water bodies.

Cardiovascular diseases are the largest cause of death globally, making it a critical area of focus. The circulatory system is required to make the heart function. One component of this system is blood vessels, which is the focus of our study. Our work aims to demonstrate the numeric relationship between a blood vessel's diameter and the number of pumps needed to transport blood.

Plant diseases can cause up to 50% crop yield loss for the popular tomato plant. A mobile device-based method to identify diseases from photos of symptomatic leaves via computer vision can be more effective due to its convenience and accessibility. To enable a practical mobile solution, a “shallow” convolutional neural networks (CNNs) with few layers, and thus low computational requirement but with high accuracy similar to the deep CNNs is needed. In this work, we explored if such a model was possible.

The purpose of this study was to test the anti-cancer properties and pro-apoptotic effects of the polyherbal formulation MAT20 as a complementary treatment. Moringa oleifera (Moringa), Phyllanthus emblica (Amla) and Ocimum sanctum (Tulsi), these 3 herbs were used to formulate MAT20, which contain phytochemicals that are known to display anti-cancer properties. In this study, we hypothesized that MCF-7 breast cancer cells treated with MAT20 would show increased cytotoxicity compared to its individual plant extracts.

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.

In organic synthesis, protecting groups are derivatives of reactive functionalities that play a key role in ensuring chemoselectivity of chemical transformations. To protect alcohols and amines, acid-labile tert-butyloxycarbonyl protecting groups are often employed but are avoided when the substrate is acid-sensitive. Thus, orthogonal base-labile protecting groups have been in demand to enable selective deprotection and to preserve the reactivity of acid-sensitive substrates. To meet this demand, we present 4-nitrophenyl carbonates and carbamates as orthogonal base-labile protecting group strategies.

Over the last few decades, childhood stunting has persisted as a major global challenge. This study hypothesized that TPTO (Tree-based Pipeline Optimization Tool), an AutoML (automated machine learning) tool, would outperform all pre-existing machine learning models and reveal the positive impact of economic prosperity, strong familial traits, and resource attainability on reducing stunting risk. Feature correlation plots revealed that maternal height, wealth indicators, and parental education were universally important features for determining stunting outcomes approximately two years after birth. These results help inform future research by highlighting how demographic, familial, and socio-economic conditions influence stunting and providing medical professionals with a deployable risk assessment tool for predicting childhood stunting.

Since cancer cells inhibit T-cell activity, the authors investigated a method to reverse T-cell disfunction with gene therapy, so that the T-cells would become effective once again in fighting cancer cells. They used the inhibition of proprotein convertases (PCSK1) in T cells and programmed death-ligand 1 (CD274) in cancer cells. They observed the recovery of IL-2 expression in Jurkat cells, with increased recovery noted in a co-culture sample. This study suggests a novel strategy to reactivate T cells.