The emergence of antibiotic-resistant pathogenic bacteria is a major concern for human health, rendering some antibiotics ineffective in treating diseases. The authors of this study tested the hypothesis that exposing rumen bacteria to tetracycline will gradually lead to the development of tetracycline-resistant bacteria, some of which will develop multidrug resistance.

The authors looked at the ability of plants to transfer phosphate between each other through mycorrhizal fungi. Specifically, they looked at whether plants with excess phosphate would transfer this nutrient to other plants that had depleted levels of phosphate.

The authors looked at how molarity impacts the degree to which ionic compounds dissociate in solution. They found that lower molarities led to decreased conductivity of solutions in a manner that did not follow the theoretical predictions.

Reinforcement learning (RL) is a form of machine learning that can be harnessed to develop artificial intelligence by exposing the intelligence to multiple generations of data. The study demonstrates how reply buffer reward mechanics can inform the creation of new pruning methods to improve RL efficiency.

In this study the authors look at the use of Indole 3 Carbinol as a treatment for Type II Diabetes finding that it may be an effective treatment.

This study investigates the feasibility of using long-range radio communication in a busy city environment in order to begin better understanding how the Internet of Things might be implemented into smart cities.

In this study, the biodiversity of marine animals was studied at different locations along a mangrove, which is a salt-tolerant shrub with elaborate root structures that is found on tropical coastlines.

Using a convolution neural network, these authors show machine learning can clinically diagnose breast cancer with high accuracy.

In this study, the authors investigate the effects that flagella have on E. coli's ability to adhere to glass surfaces.

The Tor network allows individuals to secure their online identities by encrypting their traffic, however it is vulnerable to fingerprinting attacks that threaten users' online privacy. In this paper, the authors develop a new video fingerprinting model to explore how well video streaming can be fingerprinted in Tor. They found that their model could distinguish which one of 50 videos a user was hypothetically watching on the Tor network with 85% accuracy, demonstrating that video fingerprinting is a serious threat to the privacy of Tor users.