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<p>  </p> <p>The major concern about vehicle crashes has led to a great amount of research on the topic in the road safety area. Nevertheless, real-world crash data collection periods are often extensive and they result in a great delay in improving safety. Therefore, surrogate measures of safety, such as traffic conflicts, are considered for safety management.</p> <p>The definition of a traffic conflict has evolved over the course of half a century. One of the current definitions encompasses a failure-based road event that inevitably results in a crash if no evasive action is taken by involved road users. This counterfactual concept was validated with specific road events datasets, including rear-end events and vehicle-bicycle encounters. However, observing conflicts for an extended period is still a major difficulty. For example, a LIDAR-based technique applicable to intersections can collect conflict data for a relatively short period of several days. The LiDAR-collected data are then converted to the corresponding expected crash frequency during the observation period, which eventually must be expanded to the corresponding annual value. The conversion step has not been sufficiently addressed in the past research. Thus, an important task of estimating the annual expected crash frequency based on a short-term estimate remains unanswered. Addressing this need is the research objectives and contribution of this study.</p> <p>Advanced statistical methods allow developing models to estimate expected crash frequencies for annual and short periods. The ratio of such two estimates is defined as an expansion factor in this study. This thesis presents the modeling effort and its results for different types of crashes at signalized and unsignalized intersections in Indiana. Traditional and emerging data, such as traffic volume, speed, road characteristics, weather, and other features were collected and assembled at randomly selected 194 intersections. Then, they were used to estimate the logistic models of hourly crash probability. The models were then utilized to calculate expansion factors for a specific intersection.to evaluate the method.</p>

More than 40 neurological diseases are known to be caused by large expansions oftandem repeat sequences scattered throughout the human genome in introns, exons and untranslated regions. The GGGGCC (G4C2) repeat expansion located in the first intron of the C9ORF72 gene is the most common genetic cause of amyotrophic lateral sclerosis and frontotemporal dementia (ALS/FTD). In C9 FTD/ALS, expanded transcripts are known to aggregate and accumulate in the cell nucleus, sequestering RNA binding proteins. Other expanded RNA species are exported to the cytoplasm to undergo a non-canonical form of translation termed ‘repeat-associated non-AUG (RAN) translation’. RAN translation leads to the production of toxic polydipeptide repeat proteins in the absence of a canonical AUG start codon. This dissertation will highlight new mechanistic features of translation across the G4C2 repeat expansion, identify a potential therapeutic for C9 FTD/ALS using RNAi and develop a cellular system to explore the G4C2 repeat RNA lifecycle. First, we demonstrate that increasing G4C2 repeat expansion size results in suppression of translation from both canonical and non-canonical start codons, suggesting that large polydipeptide repeats are rarely fully translated. We further find that initiation does not occur from within the repeat expansion, relying on upstream sequence for initiation. However, some reading frames are prone to substantial frameshifting, such as poly-GA. We also show that a bias in ii codon usage efficiency contributes to previously observed variations in the levels of each polydipeptide. Our results support and extend previous studies by identifying two new mechanisms that bias production of poly-dipeptides toward poly-GA in C9 FTD/ALS. Further, we generated central mismatch-containing short hairpin RNAs (shRNAs) targeting the G4C2 repeat expansion to reduce aggregation or block translation of repeatcontaining transcripts. Iterative design was able to improve shRNA processing efficiency and cellular abundance, yet they were unable to reduce nuclear RNA foci in patient-derived cells. Despite this, we show preliminary data suggesting that these shRNAs are able to target cytoplasmic repeat-containing transcripts and resulting in a reduced translation of poly-GP. Finally, we optimized the previously published RNA-protein interaction detection (RaPID) technique, which uses proximity dependent labelling by a mutant biotin ligase and mass spectrometry for protein identification in living cells, to identify proteins interacting with the G4C2 repeat expansion. We embedded the box B RNA hairpin between G4C2 repeats and tested the ability for λN fused to a biotin ligase mutant, BASU, to specifically bind the box B hairpin in vitro. We show that 6 repeats each side of the hairpin combined with an extended hairpin stem promotes specific binding of the λN-BASU fusion protein and is likely to be successful in cells. C9 FTD/ALS is a currently incurable neurodegenerative disorder largely due to the limited understanding of disease mechanism. This dissertation demonstrates new mechanisms of translation across the G4C2 repeat expansion that results in toxic DPR production while also developing a nucleic acid therapeutic for long-term treatment of C9 FTD/ALS and further developing systems to explore RNA-mediated toxicity in cells.