Texas A&M University

About: Texas A&M University is a education organization based out in College Station, Texas, United States. It is known for research contribution in the topics: Population & Gene. The organization has 72169 authors who have published 164372 publications receiving 5764236 citations.

Engineering the Caenorhabditis elegans genome using Cas9-triggered homologous recombination

Abstract: Study of the nematode Caenorhabditis elegans has provided important insights in a wide range of fields in biology. The ability to precisely modify genomes is critical to fully realize the utility of model organisms. Here we report a method to edit the C. elegans genome using the clustered, regularly interspersed, short palindromic repeats (CRISPR) RNA-guided Cas9 nuclease and homologous recombination. We demonstrate that Cas9 is able to induce DNA double-strand breaks with specificity for targeted sites and that these breaks can be repaired efficiently by homologous recombination. By supplying engineered homologous repair templates, we generated gfp knock-ins and targeted mutations. Together our results outline a flexible methodology to produce essentially any desired modification in the C. elegans genome quickly and at low cost. This technology is an important addition to the array of genetic techniques already available in this experimentally tractable model organism.

Influence of connected and autonomous vehicles on traffic flow stability and throughput

Abstract: The introduction of connected and autonomous vehicles will bring changes to the highway driving environment. Connected vehicle technology provides real-time information about the surrounding traffic condition and the traffic management center’s decisions. Such information is expected to improve drivers’ efficiency, response, and comfort while enhancing safety and mobility. Connected vehicle technology can also further increase efficiency and reliability of autonomous vehicles, though these vehicles could be operated solely with their on-board sensors, without communication. While several studies have examined the possible effects of connected and autonomous vehicles on the driving environment, most of the modeling approaches in the literature do not distinguish between connectivity and automation, leaving many questions unanswered regarding the implications of different contemplated deployment scenarios. There is need for a comprehensive acceleration framework that distinguishes between these two technologies while modeling the new connected environment. This study presents a framework that utilizes different models with technology-appropriate assumptions to simulate different vehicle types with distinct communication capabilities. The stability analysis of the resulting traffic stream behavior using this framework is presented for different market penetration rates of connected and autonomous vehicles. The analysis reveals that connected and autonomous vehicles can improve string stability. Moreover, automation is found to be more effective in preventing shockwave formation and propagation under the model’s assumptions. In addition to stability, the effects of these technologies on throughput are explored, suggesting substantial potential throughput increases under certain penetration scenarios.

Encyclopedia of research design

Abstract: Research design, with its statistical underpinnings, can be especially daunting for students and novice researchers. At its heart, research design might be described simply as a formalized approach toward problem solving, thinking, and acquiring knowledge, the success of which depends upon clearly defined objectives and appropriate choice of statistical design and analysis to meet those objectives. Our three-volume Encyclopedia of Research Design elucidates how one makes decisions about research design, interprets data and draws valid inferences, undertakes research projects in an ethical manner, and evaluates experimental design strategies and results. From A-to-Z, this work covers the spectrum of research design strategies and topics including, among other things: fundamental research design principles, ethics in the research process, quantitative versus qualitative and mixed-method designs, completely randomized designs, multiple comparison tests, diagnosing agreement between data and models, fundamental assumptions in analysis of variance, factorial treatment designs, complete and incomplete block designs, Latin square and related designs, hierarchical designs, response surface designs, split-plot designs, repeated measures designs, crossover designs, analysis of covariance, statistical software packages, and much more.