Walkability as a concept that captures the ability to walk from one place to another has multiple dimensions. Between traversability to being a proxy for better urban places, there are also numerous measurements of walkability that attempts to quantify certain or all aspects of walkability. It is, however, unclear, through a review of available literature, how these measurements of walkability relate to each other statistically. This methodology focuses on generating a framework for analysts to evaluate and prioritize pedestrian infrastructure. WalkScore™ (WS), HCM Pedestrian Level of Service (PLOS), Average Nodal Degree (AND), and Intersection Density are the four metrics selected for this analysis that focuses on distinctive aspects of walkability (proximity, amenity, network-connectivity, respectively). A sample of 51 street segments from the County of San Luis Obispo is selected according to their respective Average Daily Traffic (ADT) volumes. Pearson’s Correlations between the six combinations of relationships are measured, and the strongest correlation between the six relationships is between WalkScore™ and Intersection Density with an R2 of 0.44. A regression model that includes external factors such as population and adjacent land use is used to analyze and predict PLOS of the street segment. Although the model is not statistically significant, the goal of this research is to identify gaps in current and potential walkability of street segments in the sample. Therefore, this framework of using established walkability metrics to predict PLOS, and then distinguishing places for improvements is proposed as a result of this research to be used by government agencies to prioritize pedestrian infrastructure.

Atriplex hortensis (2n = 2x = 18, 1C genome size ~1.1 gigabases), also known as garden orach, is a highly nutritious, broadleaf annual of the Amaranthaceae-Chenopodiaceae family that has spread from its native Eurasia to other temperate and subtropical environments worldwide. Atriplex is a highly complex and polyphyletic genus of generally halophytic and/or xerophytic plants, some of which have been used as food sources for humans and animals alike. Although there is some literature describing the taxonomy and ecology of orach, there is a lack of genetic and genomic data that would otherwise help elucidate the genetic variation, phylogenetic position, and future potential of this species. Here, we report the assembly of the first highquality, chromosome-scale reference genome for orach cv. ‘Golden’. Sequence data was produced using Oxford Nanopore’s MinION sequencing technology in conjunction with Illumina short-reads and chromatin-contact mapping. Genome assembly was accomplished using the high-noise, single-molecule sequencing assembler, Canu. The genome is enriched for highly repetitive DNA (68%). The Canu assembly combined with the Hi-C chromatin-proximity data yielded a final assembly containing 1,325 scaffolds with a contig N50 of 98.9 Mb and with 94.7% of the assembly represented in the nine largest, chromosome-scale scaffolds. Sixty-eight percent of the genome was classified as highly repetitive DNA, with the most common repetitive elements being Gypsy and Copia-like LTRs. The annotation was completed using MAKER which identified 31,010 gene models and 2,555 tRNA genes. Completeness of the genome was assessed using the Benchmarking Universal Single Copy Orthologs (BUSCO) platform, which quantifies functional gene content using a large core set of highly conserved orthologous genes (COGs). Of the 1,375 plant-specific COGs in the Embryophyta database, 1,330 (96.7%) were identified in the Atriplex assembly. We also report the results of a resequencing panel consisting of 21 accessions which illustrates a high degree of genetic similarity among cultivars and wild material from various locations in North America and Europe. These genome resources provide vital information to better understand orach and facilitate future study and comparison.

We use autonomous line-following robots in various industrial environments, surveillance applications, and construction and mining industries for object transportation tasks where rail, conveyer, and gantry solutions are unavailable. They help us reduce the work process and improve efficiency. In this report, we will illustrate how a 2WD robot can move on a predefined path and detect obstacles along the way. In this project, we have used a proximity sensor to detect the obstacle in the path and turn the robot from the obstacle. Also, we used an IR sensor so that robot could follow along the predefined path. The used in the project sensors were connected to Arduino UNO, which was programmed to control the robot's movements and decisions. By employing these two techniques, we can efficiently use such robots in various scenarios. For example, in the current Covid scenario, physical contact has become minimal, so if we use this line-following robot to deliver medicines to the patient, the physical contact between people can be reduced. The obstacle avoidance robot technique can be used in cars to improve safety. If an obstacle is detected in the path of the car and the driver does not apply the brakes, this type of technique can be used to bring the car to a stop by applying breaks. Using the proposed robotic techniques we can save time and work efficiently with minimal physical touch. Overall, the project achieved its primary goal of moving the robot on a predefined path and detecting obstacles on the path

Gossypium herbaceum is a species of cotton native to Africa and Asia. As part of a larger effort to investigate structural variation in assorted diploid and polyploid cotton genomes we have sequenced and assembled the genome of G. herbaceum. Cultivated G. herbaceum is an A1-genome diploid from the Old World (Africa) with a genome size of approximately 1.7 Gb. Long range information is essential in constructing a high-quality assembly, especially when the genome is expected to be highly repetitive. Here we present a quality draft genome of G. herbaceum (cv. Wagad) using a multi-platform sequencing strategy (PacBio RS II, Dovetail Genomics, Phase Genomics, BioNano Genomics). PacBio RS II (60X) long reads were de novo assembled using the CANU assembler. Illumina sequence reads generated from the PROXIMO library method from Phase Genomics, and BioNano high-fidelity whole genome maps were used to further scaffolding. Finally, the assembly was polished using PILON. This multi-platform long range sequencing strategy will help greatly in attaining high quality de novo reconstructions of genomes. This assembly will be used towards comparative analysis with G. arboreum, which is also a domesticated A2-genome diploid. Not only will this provide a quality reference genome for G. herbaceum, it also provides an opportunity to assess recent technologies such as Dovetail Genomics, Phase Genomics, and Bionano Genomics. The G. herbaceum genome sequence serves as an example to the plant genomics community for those who have an interest in using multi-platform sequencing technologies for de novo genome sequencing.

Antibody-recruiting molecules (ARMs) are therapeutic tools that simultaneously bind a hapten-specific serum antibody and a cancer cell surface protein, resulting in the activation and recruitment of an immune cell to the cancer surface. However, ARM efficacy is limited by the ability of ARMs to form a quaternary complex with the immune cell receptor, antibody, and cancer cell surface. The Rullo lab has previously developed and characterized a covalent ARM (cARM) that irreversibly links the ARM to the antibody and simplifies the quaternary binding equilibria. cARMs have shown a marked increase in both target immune recognition and therapeutic efficacy. However, cARM efficacy is still limited by the affinity of the antibody for the immune receptor. We aim to investigate how direct covalent engagement of the immune receptor and elimination the antibody-immune receptor binding equilibria impacts immune activation and therapeutic efficacy. This thesis focuses on the chemical programming of macrophages through direct covalent immune receptor engagement. We have developed and characterized covalent immune programmers (CIPs), which are molecules that contain a macrophage targeting domain and a tumour targeting domain. The macrophage targeting domain binds the activating receptor CD64 on the macrophage surface and contains a chemical warhead that covalently labels the receptor once bound. The tumour targeting domain can promote macrophage tumour engagement resulting in tumoricidal function. Flow cytometry experiments have shown that CIPS are able to bind Fc receptors specifically and effectively on the surface of macrophages. Further, CIPs were able to induce macrophage activation and induce target specific phagocytosis. These experiments have also shown that direct engagement of the receptor by the CIP is more effective than antibody-mediated engagement, suggesting that overall immune complex stability affects immune cell activation. Taken together, these concepts can be used to guide future immunotherapeutic design. / Thesis / Master of Science (MSc)

Tornadoes frequently occur in Tornado Alley (Northern Texas, Oklahoma, Kansas, and Nebraska) and Dixie Alley (Louisiana, Arkansas, Tennessee, Mississippi, Alabama, and Georgia). This study utilizes sounding variables taken within 2-hours and 80 km of a tornado event for the period 1995-2015 to compare and differentiate between these regions. Data bootstrapping and cluster analysis were used to assess differences and similarities in the environmental data between the regions. Of the variables used, the thermodynamic variables showed the greatest discrimination between Dixie Alley and Tornado Alley tornado environments with Dixie Alley having lower LCL heights and CAPE values as well as higher SREH and BWD values when compared to Tornado Alley. However, due to thermodynamic and kinematic inputs, EHI shows the greatest potential in discriminating between tornadic environments in Dixie Alley and Tornado Alley which is beneficial in severe weather forecasting.

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