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Pseudendoclonium was established in 1900 by N. Wille to include a crust-forming green microalga occurring near the high water line on jetties in Drobak, Norway. Ordinal and familial affiliation of the genus have remained uncertain due to a lack of distinguishing morphological characteristics and because molecular phylogenetic data have not been generated for the type species. Ribosomal SSU rDNA sequence data for Pseudendoclonium submarinum, the type species, are presented. Phylogenetic analysis of these data place Pseudendoclonium within the Ulvales. SSU rDNA sequence data from three additional species, Pseudendoclonium basiliense, Pseudendoclonium akinetum and Pseudendoclonium fucicola are included in the analyses and clearly support the hypothesis that Pseudendoclonium is polyphyletic. Based on the sequence data, P. submarinum and P. fucicola share ulvalean lineage, but these algae are not congeneric and P. fucicola must be removed from Pseudendoclonium. Sequence data support the classification of P. basiliense and P. akinetum as distinct species of a single genus. The close affiliation of these two species with Ulothrix and other Ulotrichalean genera, however, reveals their ordinal separation from P. submarinum. P. basiliense and P. akinetum must also be removed from Pseudendoclonium and require generic reassignment within the Ulotrichales.

The Caradonna lab has utilized the enzyme active site of TauD as a model for a synthetic, metal-based, oxidative catalyst. We have developed a series of small molecule, non-heme, manganese catalysts that are analogous to the previously synthesized iron complexes in our lab. These complexes, denoted MnII(N2Ox), where x = 1–3, were spectroscopically characterized, and their scope of utility explored. In addition to oxidizing methanol to formaldehyde, each catalyst in the series has exhibited the ability to epoxidize alkene substrates, including cyclooctene, cyclohexene, and cis-stilbene. After reaction condition optimization, the reactivity studies revealed certain trends in the reactivity of each catalyst, and the range of TONs was 10-120. A heterogeneous catalyst system was also developed in which the iron catalyst was tethered onto a solid support. The iron catalyst, FeII(N2O1), where N2O1 is N-(2-(dimethylamino)ethyl)-N-methylglycine, is susceptible to dimerization and subsequent inactivation when it is in homogeneous solution. Thus, a homogeneous catalyst system was designed with a resin that contained a low concentration of amine functionalization, which was synthetically transformed into an azide-functionalized resin. An alkyne derivative of the N2O1 ligand scaffold was developed which could then be tethered onto the resin via CuAAC “click” chemistry, and low-loading levels of tethered catalyst were obtained. Efforts towards modulating the N2O1 ligand were also explored. We sought to develop a synthetic methodology for facile ligand functionalization, which would provide greater accessibility to adding desired substituents. These substituents could aid in the solubility of the catalyst or provide ligand-directed asymmetric catalysis for prochiral substrates. The ligand was also modified electronically with electron-withdrawing and electron-donating substituents, in order to probe how the electronic structure of the catalyst affects its reactivity. Finally, efforts were made toward spectroscopically establishing the structure of the Fe(IV)-oxo intermediate with isotopically labeled reagents. The development of the manganese-based oxidative complexes and the optimization efforts towards the O2-activating iron-based complexes have exploited the utility of biomimetic, small molecule catalysis.

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With rapid adoption of cloud solutions across industries, energy consumed by server farms continues to rise. There are numerous approaches to reduce energy consumption in data centres, and one of the approaches is to use energy-aware policies, which focus on how servers should be operated in order to achieve energy saving and meet service level agreements (SLA). In this thesis, we focus on studying a single server model with dynamic voltage scaling (DVS), presenting a framework with explicit solutions to solve for performance metrics and energy consumption. Our framework is convenient and in- tuitive, one can easily identify expected response time and expected energy consumption for a given policy. In addition, we also provide insights on how the value of the faster service rate and the choice of when to use speed scaling impact energy consumption and performance metrics. / Thesis / Master of Computer Science (MCS)

When urbanization occurs, the removal of vegetation, compaction of soil and construction of impervious surfaces—roofs, asphalt, and concrete—and drainage infrastructure result in drastic changes to the natural hydrological cycle. Stormwater runoff occurs when rain does not infiltrate into soil. Instead it ponds at the surface and forms shallow channels of overland flow. The result is increased peak flows and pollutant loads, eroded streambanks, and decreased biodiversity in aquatic habitat. In urban areas, runoff is typically directed into catch basins and underground pipe systems to prevent flooding, however such systems are also failing to meet modern environmental goals. Green infrastructure is the widely evocative idea that development practices and stormwater management infrastructure can do better to mimic the natural hydrological conditions through distributed vegetation and source control measures that prevent runoff from being produced in the first place. This dissertation uses statistics and high-resolution, coupled surfacesubsurface hydrologic simulation (ParFlow.CLM) to examine three understudied aspects of green infrastructure planning. First, I examine how development characteristics affect the runoff response in urban catchments. I find that instead of focusing on site imperviousness, planners should aim to preserve the ecosystem functions of infiltration and evapotranspiration that are lost even with low density development. Second, I look at how the spatial configuration of green infrastructure at the neighborhood scale affects runoff generation. While spatial configuration of green infrastructure does result in statistically significant differences in performance, such differences are not likely to be detectable above noise levels present in empirical monitoring data. In this study, there was no evidence of reduced hydrological effectiveness for green infrastructure located at sag points in the topography. Lastly, using six years of empirical data from a voluntary residential green infrastructure program, I show how the spread of green infrastructure depends on the demographic and physical characteristics of neighborhoods as well as spatially-dependent social processes (such as the spread of information). This dissertation advances the science of green infrastructure planning at multiple scales and in multiple sectors to improve the practice of urban water resource management and sustainable development. / Doctor of Philosophy in City and Regional Planning