abstract: Accounting for over a third of all emerging and re-emerging infections, viruses represent a major public health threat, which researchers and epidemiologists across the world have been attempting to contain for decades. Recently, genomics-based surveillance of viruses through methods such as virus phylogeography has grown into a popular tool for infectious disease monitoring. When conducting such surveillance studies, researchers need to manually retrieve geographic metadata denoting the location of infected host (LOIH) of viruses from public sequence databases such as GenBank and any publication related to their study. The large volume of semi-structured and unstructured information that must be reviewed for this task, along with the ambiguity of geographic locations, make it especially challenging. Prior work has demonstrated that the majority of GenBank records lack sufficient geographic granularity concerning the LOIH of viruses. As a result, reviewing full-text publications is often necessary for conducting in-depth analysis of virus migration, which can be a very time-consuming process. Moreover, integrating geographic metadata pertaining to the LOIH of viruses from different sources, including different fields in GenBank records as well as full-text publications, and normalizing the integrated metadata to unique identifiers for subsequent analysis, are also challenging tasks, often requiring expert domain knowledge. Therefore, automated information extraction (IE) methods could help significantly accelerate this process, positively impacting public health research. However, very few research studies have attempted the use of IE methods in this domain. This work explores the use of novel knowledge-driven geographic IE heuristics for extracting, integrating, and normalizing the LOIH of viruses based on information available in GenBank and related publications; when evaluated on manually annotated test sets, the methods were found to have a high accuracy and shown to be adequate for addressing this challenging problem. It also presents GeoBoost, a pioneering software system for georeferencing GenBank records, as well as a large-scale database containing over two million virus GenBank records georeferenced using the algorithms introduced here. The methods, database and software developed here could help support diverse public health domains focusing on sequence-informed virus surveillance, thereby enhancing existing platforms for controlling and containing disease outbreaks. / Dissertation/Thesis / Doctoral Dissertation Biomedical Informatics 2019

<p> Electoral districts drawn by independent commissions are seen by political reformers to be preferable to those drawn by state legislatures. The overtly partisan interests of elected officials, say the reformers, lead to oddly-shaped, and gerrymandered districts. To test this, shapes of districts in states with commissions are compared to those within the same state prior to the commission&rsquo;s establishment. Additionally, shapes of districts in states with commissions are compared to those in a selected group of states without commissions. This study tests hypotheses on two methods of measuring compactness, Reock and Polsby-Popper, and coterminosity, the congruence of district lines and pre-existing political boundaries. The study finds that each state with a commission shows no significant difference in mean compactness compared to its pre-commission form. However, in aggregate, all post-commission districts show a significant increase in mean Reock compactness compared to all pre-commission districts, and all districts in states with commissions show significantly less Polsby-Popper compactness than districts in non-commission states. The study also finds no significant difference in coterminosity between commission states and non-commission states. Though the true effect of commissions may not be discernible from averages, other redistricting criteria also need to be controlled for and evaluated over time.</p>

<p> Water resources have become an increasingly important topic in the world of resource management. Researchers are constantly looking for ways to make the process of data collection, analyzation and visualization more efficient. The current methods involve a multi-step process that is cumbersome and require a lot of man-hours from start to finish. The cost of water quality sensors is also an issue for researchers. Many sensors on the market today range from the $1,000 to $10,000 range making it difficult for small research firms and non profits to conduct water quality monitoring projects. This project attempts to construct a water quality-monitoring platform that will automate the process of collecting, analyzing and visualization water quality data. Special attention will be given to the data visualization aspect of the process with an emphasis on web mapping applications.</p>

This work have quantitatively determine the catchment variables controlling the sinuosity transition of non-valley constrained DFS channels in Alaska, Himalaya and the Andes. Results from the characterisation of channel sinuosity were used through regression analyses to determine the catchment and channel bed parameters controlling reach sinuosity trend and transition of fluvial channel planforms in order to infer a control on the heterogeneity of DFS in the rock record. The catchment approach used was necessary because the studied fluvial systems are associated with DFS (which are regarded as larger forms of alluvial fans) and catchment based approach have been used to investigate controls on alluvial fan morphology. In addition, catchment based investigations are rare in the analyses of the discriminant functions that are considered as controlling factors on channel sinuosity and planform employed previously in the tributary systems. Two distinct channel types were found through the characterisation of 553 reaches of fluvial channels in 3 different modern continental sedimentary basins; channels with no transition in sinuosity/planform (group 1), and channels with transition in sinuosity/planform (group 2) Among the channel bed and catchment quantitative variables investigated in this work, catchment area is the only parameter that shows a general relationship with the channel distance from the apex to the transition point in channel sinuosity through the overall regression results. The result shows that the bigger the catchment area the longer the transition point which is related to a higher water and sediment discharge. Thus, the point at which the channel sinuosity transition will occur can be predicted from the catchment area through the regression equation [y=0.0017x + 28] of the overall linear regression line, where x is the catchment area and y is the channel distance from the apex to the point of transition in channel sinuosity. As the studied channels are associated with DFS, this relation also reflects the prediction of the transition point in the DFS fluvial styles in the rock record. Overall regression analysis results show statistically poor results for the relationship between catchment elevation, catchment slope, channel bed elevation, channel bed slope and either the channel sinuosity or the sinuosity transition. However, in all the three study areas, the majority of the datasets show a trend with the catchment area/sinuosity transition relationship. Additionally, the study area with mainly the biggest catchments (longer channel sinuosity transition) is associated with the highest catchment slope, lowest channel bed elevation and more anabranching channels. Also, the study area with mainly the smallest catchments (shorter channel sinuosity transition) is associated with lower catchment slope, higher channel bed elevation and fewer anabranching channels. This suggests that the higher water and sediment discharge may be related to the steeper slopes and the anabranching channels may reflect the lower channel bed elevation. However, deviations obeserved in the overall regression result in the three study areas are attributed to the differences in the climatic, geologic and tectonic factors in the 3 settings. Although, the differences in these study areas have been shown, nevertheless the interpretations cannot be substantiated in this work with the available data. Thus, there is need for further research to prove any conclusive relationship between these factors and hence remains an issue of debate. In conclusion, this work shows that catchment area is an important controlling parameter on the transition in channel sinuosity of non-valley constrained DFS channels and consequently reflects a a control on the transition in spatial variations of the associated DFS in the rock record.

<p> The Truckee Meadows (Reno, NV) sits in a tectonically complex area of western Nevada, where Walker Lane-style transtension is dominant throughout the region. A new Light Detection and Ranging (LiDAR) study focuses on the Truckee Meadows region of western Nevada, including the Reno/Sparks metropolitan area in Washoe County. We use the airborne LiDAR imagery (1485 sq. km) to create high quality, bare-earth topographic maps that were previously unattainable in vegetated, populated or alpine terrain. This approach gives us an opportunity to improve fault maps that may be outdated or incomplete in the area. Here we provide LiDAR imagery of a large section of Washoe County and an updated fault map of the greater Truckee Meadows region. </p><p> We also use this new LiDAR survey of the Truckee Meadows and nearby basins to constrain geometry, length, distribution, and slip rates along faults imaged by this new dataset. Estimated slip rates are compared to those derived from a geodetic block model constrained by Global Positioning Station (GPS) data to test for consistency. GPS station data and geologic mapping show that both east-west oriented extension and northwest-oriented right-lateral strike slip accommodate transtension as a backdrop for tectonics studies of region, with some northeast-oriented left-lateral strike slip. This study aims to better understand how this transtension is partitioned along remapped faults and newly identified structures in this urban setting, as the framework for strain accommodation in this area remains poorly understood. </p><p> Faults with normal offset were measured along strike using bare-earth LiDAR returns to determine the amount of vertical separation across geomorphic surfaces, and then converted to extension assuming a fault dip of 60 (+/-10) degrees. Since the primary geomorphic surfaces in this region are the result of Sierra Nevadan glacial outwash episodes, we use previously published geologic maps to link each surface to an associated date. When integrated across several basin perpendicular transects within the Mt. Rose pediment, we calculate a total extension rate of 0.87 (+0.40/-0.48) mm/yr for the southern Truckee Meadows basin. Integrated slip rates from fault scarp offsets are within the bounds of 1.23 (+/-0.70) mm/yr suggested by geodetic modeling. Block modeling highlights that north-striking faults primarily accommodate east-west extension, and so northwest-striking faults and/or block rotations must accommodate the northwest-directed shear seen in GPS velocities. This trend is bolstered by the discovery of a new northwest-oriented fault on Peavine Mountain 6 km east of the Mogul (2008) seismicity trend. Our study provides further evidence that the Truckee Meadows sits at a critical transition from north-striking normal faults in the southern part of the basin to northwest-oriented strike-slip faults to the north, an observation that mimics regional tectonics and geomorphology of the adjacent Lake Tahoe/Truckee system to the west.</p>

<p> Eastern Equine Encephalitis virus is a vector-borne virus amplified by the <i>Culiseta melanura</i> mosquito in an enzootic avian cycle, causing high morbidity and mortality to horses and humans when contracted as incidental hosts. The virus is distributed across most of the eastern United States, Canada, and Gulf coast, and has been expanding in geographic range and season of activity over time. Spatial-temporal trends in <i>Cs. melanura </i> abundance were correlated with available meteorological (temperature and precipitation) and remotely sensed environmental data for the period of 1997-2012 in Connecticut. The effects of inter-annual changes in precipitation, temperature, and groundwater levels on <i>Cs. melanura</i> abundances using time-series linear regression and cross-correlation analyses were inconclusive. Habitat modeling using logistic regression and landscape-based predictive variables demonstrated strong efficiency (46.2%) and acceptable sensitivity and specificity (65.6 and 78.6%, respectively) using NDVI difference and distance from palustrine areas as predictive factors. Remotely sensed data can improve the understanding of vector abundance patterns, helping to forecast future outbreaks and regional expansions by guiding surveillance efforts. </p>

published_or_final_version / Geography and Geology / Doctoral / Doctor of Philosophy

published_or_final_version / Civil Engineering / Doctoral / Doctor of Philosophy

published_or_final_version / Geography / Master / Master of Geographic Information System

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