Multinomial Logistic And Negative Binomial Regressions Of Campus Instructional Modes, Institutional Characteristics, And Covid-19 Case Counts In Fall 2020 In The Midwest

In spring of 2020, a global pandemic shifted American institutions of higher education into a crisis with unprecedented unknown information, guidelines that changed continuously, and impacted the personal and professional lives of students, faculty and staff. This study examined the relationships (1) between campus size, geographic setting, locus of control in Midwest and Mountain American higher educational institutions and their instructional mode in fall 2020, and (2) between those institutional characteristics and the number of reported campus COVID-19 cases in the fall of 2020. Using a multinomial logistic regression and a negative binomial regression with an estimated parameter dispersion, the study suggested that campus control and campus setting did relate to the instructional mode response. Campus size, instructional mode, and campus setting related to the number of COVID-19 cases in fall 2020. One major implication of the findings would be to include an evaluation of instructional mode and a consideration of a campus’ size and location to impact a campus crisis response, specifically for COVID-19. Additionally, providing faculty support to overcome barriers found during COVID-19 is essential to the future planning for similar crises

Evaluating land use impacts of self-driving vehicles and leveraging intelligently charged electrified transit to support a renewable energy grid in the Austin, Texas region

This thesis is divided into two parts. The first part focuses heavily on the land use model SILO and its implementation in the Austin, Texas six-county region over a 27-year period of full adoption of self-driving vehicles. It discusses the model framework and capabilities and critically evaluates SILO’s specifications. SILO was then integrated with the agent-based transportation model MATSim for the Austin region. Land use and travel results were generated for a business-as-usual case (BAU) of 0% self-driving or “autonomous” vehicles (AVs) over the model timeframe versus a scenario where households’ value of travel time savings (VTTS) is reduced by 50%, to reflect the travel-burden reductions of no longer having to drive. A third scenario is also compared and examined against BAU to understand the impacts of rising vehicle occupancy (VO), and/or higher roadway capacities, due to dynamic ride-sharing (DRS) options in shared AV (SAV) fleets. Results suggest an 8.1% increase in average commute times when VTTS falls by 50% and VO remains unaffected (the 100% AV scenario), and a 33.3% increase in the number of households with “extreme commutes” (over 1 hour, each way) in the final model year (versus BAU of 0% AVs). When VO is raised to 2.0 and VTTS falls instead by 25% (the “Hi-DRS” SAV scenario), average commute times increase by 3.5% and the number of households with “extreme commutes” increase by 16.4% in the final model year (versus BAU of 0% AVs). The ITLUM also predicts 5.3% fewer households and 19.1% more available, developable land in the City of Austin in the 100% AV scenario in the final model year relative to the BAU scenario’s final year, with 5.6% more households and 10.2% less developable land outside the City. In addition, the model results predict 5.6% fewer households and 62.9% more available developable land in the City of Austin in the Hi-DRS SAV scenario in the final model year relative to the BAU scenario’s final year, with 6.2% more households and 9.9% less developable land outside the City. This thesis’ second part looks at how electric buses can support a power grid that relies heavily on renewable energy sources, like wind and solar. The transportation sector is a major greenhouse gas (GHG) emitter. Concurrent electrification of vehicles and investment in renewable energy is required to deeply decarbonize this and other sectors of our economies. The introduction of intermittent renewable energy sources, like solar and wind, at a large scale presents major challenges to grid operators and utility companies. This study examines the benefits and costs that a Vehicle-to-Grid (V2G) Battery Electric Bus (BEB) fleet offers Austin, Texas by buffering against sharp shifts in renewable energy production to help smooth power demands from traditional energy sources (like coal, natural gas, and nuclear power plants). A V2G BEB “smart charging” (SC) scenario’s cost and emissions were compared to those in a BEB “charge-as-needed” scenario and to those in a diesel bus scenario, for 423+ buses and over 88,000 bus-miles per day. By simply electrifying Austin’s buses, without any SC strategies, the total external cost of all of Austin’s electricity grid emissions and bus emissions falls by approximately 3.42%, amounting to over 21¢-savings per bus-mile, relative to the diesel-bus scenario. By using SC strategies, those same emission costs fell by 5.64% or over 35¢-savings per bus-mile. These emissions savings become very significant when summed over the course of a year. In the non-SC BEB scenario, emissions savings amount to approximately $6.86M/year, and in the SC BEB scenario, emissions savings reach approximately$11.3M/year. Such reductions are thanks to high renewable energy use in Austin’s power mix and because diesel fuel is much more emitting (per kWh) than power plants. From the transit operator’s perspective, a BEB fleet costs more than a diesel bus fleet, but such costs can be more than offset by renewable energy savings and emissions-costs benefits. Thanks to SC strategies, the utility manager is estimated to save 22% of their daily power-purchase cost in this case study.Civil, Architectural, and Environmental Engineerin

Blending Bathymetry: Combination of image-derived parametric approximations and celerity data sets for nearshore bathymetry estimation

Estimation of nearshore bathymetry is important for accurate prediction of nearshore wave conditions. However, direct data collection is expensive and time-consuming while accurate airborne lidar-based survey is limited by breaking waves and decreased light penetration affected by water turbidity. Instead, tower-based platforms or Unmanned Aircraft System (UAS) can provide indirect video-based observations. The video-based time-series imagery provides wave celerity information and time-averaged (timex) or variance enhanced (var) images identify persistent regions of wave breaking. In this work, we propose a rapid and improved bathymetry estimation method that takes advantage of image-derived wave celerity and a first-order bathymetry estimate from Parameter Beach Tool (PBT), software that fits parameterized sandbar and slope forms to the timex or var images. Two different sources of the data, PBT and wave celerity, are combined or blended optimally based on their assumed accuracy in a statistical framework. The PBT-derived bathymetry serves as "prior" coarse-scale background information and then is updated and corrected with the imagery-derived wave data through the dispersion relationship, which results in a better bathymetry estimate that is consistent with imagery-based wave data. To illustrate the accuracy of our proposed method, imagery data sets collected in 2017 at the US Army EDRC's Field Research Facility in Duck, NC under different weather and wave height conditions are tested. Estimated bathymetry profiles are remarkably close to the direct survey data. The computational time for the estimation from PBT-based bathymetry and imagery-derived wave celerity is only about five minutes on a free Google Cloud node with one CPU core. These promising results indicate the feasibility of reliable real-time bathymetry imaging during a single flight of UAS.Comment: 21 pages, 14 figures, preprint

Assessing the Sensitivity of Different Life Stages for Sexual Disruption in Roach (Rutilus rutilus) Exposed to Effluents from Wastewater Treatment Works

Surveys of U.K. rivers have shown a high incidence of sexual disruption in populations of wild roach (Rutilus rutilus) living downstream from wastewater treatment works (WwTW), and the degree of intersex (gonads containing both male and female structural characteristics) has been correlated with the concentration of effluent in those rivers. In this study, we investigated feminized responses to two estrogenic WwTWs in roach exposed for periods during life stages of germ cell division (early life and the postspawning period). Roach were exposed as embryos from fertilization up to 300 days posthatch (dph; to include the period of gonadal sex differentiation) or as postspawning adult males, and including fish that had received previous estrogen exposure, for either 60 or 120 days when the annual event of germ cell proliferation occurs. Both effluents induced vitellogenin synthesis in both life stages studied, and the magnitude of the vitellogenic responses paralleled the effluent content of steroid estrogens. Feminization of the reproductive ducts occurred in male fish in a concentration-dependent manner when the exposure occurred during early life, but we found no effects on the reproductive ducts in adult males. Depuration studies (maintenance of fish in clean water after exposure to WwTW effluent) confirmed that the feminization of the reproductive duct was permanent. We found no evidence of ovotestis development in fish that had no previous estrogen exposure for any of the treatments. In wild adult roach that had previously received exposure to estrogen and were intersex, the degree of intersex increased during the study period, but this was not related to the immediate effluent exposure, suggesting a previously determined programming of ovotestis formation

New Roles for New Times: Digital Curation for Preservation

The report looks at how libraries are developing new roles and services in the arena of digital curation for preservation. The authors consider a "promising set of new roles that libraries are currently carving out in the digital arena," describing emerging strategies for libraries and librarians and highlighting collaborative approaches through a series of case studies of key programs and projects. They also provide helpful definitions and offer recommendations for libraries considering how best to make or expand their investments in digital curation. Issues and developments within and across the sciences and humanities are considered

Teleporters, tunnels & time : Understanding warp devices in videogames

Catchment land uses, particularly agriculture and urban uses, have long been recognized as major drivers of nutrient concentrations in surface waters. However, few simple models have been developed that relate the amount of catchment land use to downstream freshwater nutrients. Nor are existing models applicable to large numbers of freshwaters across broad spatial extents such as regions or continents. This research aims to increase model performance by exploring three factors that affect the relationship between land use and downstream nutrients in freshwater: the spatial extent for measuring land use, hydrologic connectivity, and the regional differences in both the amount of nutrients and effects of land use on them. We quantified the effects of these three factors that relate land use to lake total phosphorus (TP) and total nitrogen (TN) in 346 north temperate lakes in 7 regions in Michigan, USA. We used a linear mixed modeling framework to examine the importance of spatial extent, lake hydrologic class, and region on models with individual lake nutrients as the response variable, and individual land use types as the predictor variables. Our modeling approach was chosen to avoid problems of multi-collinearity among predictor variables and a lack of independence of lakes within regions, both of which are common problems in broad-scale analyses of freshwaters. We found that all three factors influence land use-lake nutrient relationships. The strongest evidence was for the effect of lake hydrologic connectivity, followed by region, and finally, the spatial extent of land use measurements. Incorporating these three factors into relatively simple models of land use effects on lake nutrients should help to improve predictions and understanding of land use-lake nutrient interactions at broad scales