Understanding how bacteria respond to other bacteria could facilitate their ability to initiate and maintain their infectiousness. The phenomenon by which bacteria signal to each other via chemical signals is called quorum sensing, which could be targeted to deter bacterial infection in some cases if better understood. In this article, the authors study how a bacterium called V. fischeri uses quorum sensing to change bioluminescence, an easy readout that facilitates studying quorum sensing in this strain.
Due to a critical shortage of donor hearts, researchers are exploring cardiac xenotransplantation—transplanting animal hearts into humans—as a potential solution. This study synthesized nearly two decades of preclinical research to evaluate multiple factors affecting xenograft survival.
Industrial process are designed to optimize speed, energy use and quality. Some steps involve the translation of product-filled barrels, how far and fast this happens depends on the properties of the product within. This article investigates such properties on a mini-scale, where the roll of bead size, texture and material on the distance travelled by a cylindrical capsule is investigated.
Although there has been great progress in the field of Natural language processing (NLP) over the last few years, particularly with the development of attention-based models, less research has contributed towards modeling keystroke log data. State of the art methods handle textual data directly and while this has produced excellent results, the time complexity and resource usage are quite high for such methods. Additionally, these methods fail to incorporate the actual writing process when assessing text and instead solely focus on the content. Therefore, we proposed a framework for modeling textual data using keystroke-based features. Such methods pay attention to how a document or response was written, rather than the final text that was produced. These features are vastly different from the kind of features extracted from raw text but reveal information that is otherwise hidden. We hypothesized that pairing efficient machine learning techniques with keystroke log information should produce results comparable to transformer techniques, models which pay more or less attention to the different components of a text sequence in a far quicker time. Transformer-based methods dominate the field of NLP currently due to the strong understanding they display of natural language. We showed that models trained on keystroke log data are capable of effectively evaluating the quality of writing and do it in a significantly shorter amount of time compared to traditional methods. This is significant as it provides a necessary fast and cheap alternative to increasingly larger and slower LLMs.
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.
Here, the authors sought to evaluate the efforts of fast fashion clothing companies towards sustainability, specifically in regards to the United Nations Sustainable Development Goals. The authors used natural language processing to investigate the sustainability reports of fast fashion companies focusing on terms established by the UN. They found that the most consistently addressed areas were related to sustainable consumption/production, with a focus on health and well-being emerging during the recent pandemic.
Current drug discovery processes can cost billions of dollars and usually take five to ten years. People have been researching and implementing various computational approaches to search for molecules and compounds from the chemical space, which can be on the order of 1060 molecules. One solution involves deep generative models, which are artificial intelligence models that learn from nonlinear data by modeling the probability distribution of chemical structures and creating similar data points from the trends it identifies. Aiming for faster runtime and greater robustness when analyzing high-dimensional data, we designed and implemented a Hybrid Quantum-Classical Generative Adversarial Network (QGAN) to synthesize molecules.
This study follows the process of single-cloning and the growth of a homogeneous cell population in a superficial environment over the course of six weeks with the end goal of showing which of five tumor growth models commonly used to predict heterogeneous cancer cell population growth (Exponential, Logistic, Gompertz, Linear, and Bertalanffy) would also best exemplify that of homogeneous cell populations.
Crumpling is the process whereby a sheet of paper undergoes deformation to yield a three-dimensional structure comprising a random network of ridges and facets with variable density. The authors hypothesized that the more times a paper sheet is crumpled, the greater its compressive strength. Their results show a relatively strong linear relationship between the number of times a paper sheet is crumpled and its compressive strength.
The authors looked at alternative production processes for PHB plastic in an effort to reduce environmental impact. They found that no alternative process was able to significantly decrease the environmental impact of PHB production, but that optimizing dewatering steps during production could lead to the largest improvement on environmental impact.
