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With the growing popularity and advancements in automation technology, Connected and Automated Vehicles (CAVs) have become the pinnacle of ground-vehicle transportation. Connectivity has the potential to allow all vehicles—new or old, automated or non-automated—to communicate with each other at all times and greatly reduce the possibility of a multi-vehicle collision.

With the growing popularity and advancements in automation technology, Connected and Automated Vehicles (CAVs) have become the pinnacle of ground-vehicle transportation. Connectivity has the potential to allow all vehicles—new or old, automated or non-automated—to communicate with each other at all times and greatly reduce the possibility of a multi-vehicle collision. This project sought to achieve a better understanding of CAV communication technologies by attempting to design, integrate, test, and validate a vehicular ad-hoc network (VANET) amongst three automated ground-vehicle prototypes. The end goal was to determine what current technology best satisfies Vehicle-to-Vehicle (V2V) communication with a real-time physical demonstration. Although different technologies, such as dedicated short-range communication (DSRC) and cellular vehicle to everything (C-V2X) were initially investigated, due to time and budget constraints, a FreeWave ZumLink Z9-PE DEVKIT (900 MHz radio) was used to create a wireless network amongst the ground-vehicle prototypes. The initial testing to create a wireless network was successful and demonstrated but creating a true VANET was unsuccessful as the radios communicate strictly peer to peer. Future work needed to complete the simulated VANET includes programming the ZumLink radios to send and receive data using message queuing telemetry transport (MQTT) protocol to share data amongst multiple vehicles, as well as programming the vehicle controller to send and receive data utilizing terminal control protocol (TCP) to ensure no data loss and all data is communicated in correct sequence.
ContributorsDunn, Brandon (Author) / Chen, Yan (Thesis director) / Wishart, Jeffrey (Committee member) / Engineering Programs (Contributor, Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
Description

Agassiz’s desert tortoise (Gopherus agassizii) is a long-lived species native to the Mojave Desert and is listed as threatened under the US Endangered Species Act. To aid conservation efforts for preserving the genetic diversity of this species, we generated a whole genome reference sequence with an annotation based on dee

Agassiz’s desert tortoise (Gopherus agassizii) is a long-lived species native to the Mojave Desert and is listed as threatened under the US Endangered Species Act. To aid conservation efforts for preserving the genetic diversity of this species, we generated a whole genome reference sequence with an annotation based on deep transcriptome sequences of adult skeletal muscle, lung, brain, and blood. The draft genome assembly for G. agassizii has a scaffold N50 length of 252 kbp and a total length of 2.4 Gbp. Genome annotation reveals 20,172 protein-coding genes in the G. agassizii assembly, and that gene structure is more similar to chicken than other turtles. We provide a series of comparative analyses demonstrating (1) that turtles are among the slowest-evolving genome-enabled reptiles, (2) amino acid changes in genes controlling desert tortoise traits such as shell development, longevity and osmoregulation, and (3) fixed variants across the Gopherus species complex in genes related to desert adaptations, including circadian rhythm and innate immune response. This G. agassizii genome reference and annotation is the first such resource for any tortoise, and will serve as a foundation for future analysis of the genetic basis of adaptations to the desert environment, allow for investigation into genomic factors affecting tortoise health, disease and longevity, and serve as a valuable resource for additional studies in this species complex.

Data Availability: All genomic and transcriptomic sequence files are available from the NIH-NCBI BioProject database (accession numbers PRJNA352725, PRJNA352726, and PRJNA281763). All genome assembly, transcriptome assembly, predicted protein, transcript, genome annotation, repeatmasker, phylogenetic trees, .vcf and GO enrichment files are available on Harvard Dataverse (doi:10.7910/DVN/EH2S9K).

ContributorsTollis, Marc (Author) / DeNardo, Dale F (Author) / Cornelius, John A (Author) / Dolby, Greer A (Author) / Edwards, Taylor (Author) / Henen, Brian T. (Author) / Karl, Alice E. (Author) / Murphy, Robert W. (Author) / Kusumi, Kenro (Author)
Created2017-05-31