Elucidating the Space-Time Structure of Low Level Warm Season Precipitation Processes in the Southern Appalachian Mountains Using Models and Observations

Light rainfall is the baseline input to the annual water budget in mountainous landscapes through the tropics and at mid-latitudes. In the Southern Appalachians, the contribution from light rainfall ranges from 50-60% during wet years to 80-90% during dry years, with convective activity and tropical cyclone input providing most of the interannual variability. The Southern Appalachians is a region characterized by rich biodiversity that is vulnerable to land use/land cover changes due to its proximity to a rapidly growing population. Persistent near surface moisture and associated microclimates observed in this region has been well documented since the colonization of the area in terms of species health, fire frequency, and overall biodiversity. The overarching objective of this research is to elucidate the microphysics of light rainfall and the dynamics of low level moisture in the inner region of the Southern Appalachians during the warm season, with a focus on orographically mediated processes. The overarching research hypothesis is that physical processes leading to and governing the life cycle of orographic fog, low level clouds, and precipitation, and their interactions, are strongly tied to landform, land cover, and the diurnal cycles of flow patterns, radiative forcing, and surface fluxes at the ridge-valley scale. The following science questions will be addressed specifically: 1) How do orographic clouds and fog affect the hydrometeorological regime from event to annual scale and as a function of terrain characteristics and land cover?; 2) What are the source areas, governing processes, and relevant time-scales of near surface moisture convergence patterns in the region?; and 3) What are the four dimensional microphysical and dynamical characteristics, including variability and controlling factors and processes, of fog and light rainfall? The research was conducted with two major components: 1) ground-based high-quality observations using multi-sensor platforms and 2) interpretive numerical modeling guided by the analysis of the in situ data collection. Findings illuminate a high level of spatial – down to the ridge scale - and temporal – from event to annual scale - heterogeneity in observations, and a significant impact on the hydrological regime as a result of seeder-feeder interactions among fog, low level clouds, and stratiform rainfall that enhance coalescence efficiency and lead to significantly higher rainfall rates at the land surface. Specifically, results show that enhancement of an event up to one order of magnitude in short-term accumulation can occur as a result of concurrent fog presence. Results also show that events are modulated strongly by terrain characteristics including elevation, slope, geometry, and land cover. These factors produce interactions between highly localized flows and gradients of temperature and moisture with larger scale circulations. Resulting observations of DSD and rainfall patterns are stratified by region and altitude and exhibit clear diurnal and seasonal cycles.

Structure maps for hcp metals from first-principles calculations

The ability to predict the existence and crystal type of ordered structures of materials from their components is a major challenge of current materials research. Empirical methods use experimental data to construct structure maps and make predictions based on clustering of simple physical parameters. Their usefulness depends on the availability of reliable data over the entire parameter space. Recent development of high-throughput methods opens the possibility to enhance these empirical structure maps by ab initio calculations in regions of the parameter space where the experimental evidence is lacking or not well characterized. In this paper we construct enhanced maps for the binary alloys of hcp metals, where the experimental data leaves large regions of poorly characterized systems believed to be phase separating. In these enhanced maps, the clusters of noncompound-forming systems are much smaller than indicated by the empirical results alone. © 2010 The American Physical Society.

Anti-AIDS agents 81. Design, synthesis, and structure-activity relationship study of betulinic acid and moronic acid derivatives as potent HIV maturation inhibitors.

In our continuing study of triterpene derivatives as potent anti-HIV agents, different C-3 conformationally restricted betulinic acid (BA, 1) derivatives were designed and synthesized in order to explore the conformational space of the C-3 pharmacophore. 3-O-Monomethylsuccinyl-betulinic acid (MSB) analogues were also designed to better understand the contribution of the C-3' dimethyl group of bevirimat (2), the first-in-class HIV maturation inhibitor, which is currently in phase IIb clinical trials. In addition, another triterpene skeleton, moronic acid (MA, 3), was also employed to study the influence of the backbone and the C-3 modification toward the anti-HIV activity of this compound class. This study enabled us to better understand the structure-activity relationships (SAR) of triterpene-derived anti-HIV agents and led to the design and synthesis of compound 12 (EC(50): 0.0006 microM), which displayed slightly better activity than 2 as a HIV-1 maturation inhibitor.

Different stimuli, different spatial codes: a visual map and an auditory rate code for oculomotor space in the primate superior colliculus.

Maps are a mainstay of visual, somatosensory, and motor coding in many species. However, auditory maps of space have not been reported in the primate brain. Instead, recent studies have suggested that sound location may be encoded via broadly responsive neurons whose firing rates vary roughly proportionately with sound azimuth. Within frontal space, maps and such rate codes involve different response patterns at the level of individual neurons. Maps consist of neurons exhibiting circumscribed receptive fields, whereas rate codes involve open-ended response patterns that peak in the periphery. This coding format discrepancy therefore poses a potential problem for brain regions responsible for representing both visual and auditory information. Here, we investigated the coding of auditory space in the primate superior colliculus(SC), a structure known to contain visual and oculomotor maps for guiding saccades. We report that, for visual stimuli, neurons showed circumscribed receptive fields consistent with a map, but for auditory stimuli, they had open-ended response patterns consistent with a rate or level-of-activity code for location. The discrepant response patterns were not segregated into different neural populations but occurred in the same neurons. We show that a read-out algorithm in which the site and level of SC activity both contribute to the computation of stimulus location is successful at evaluating the discrepant visual and auditory codes, and can account for subtle but systematic differences in the accuracy of auditory compared to visual saccades. This suggests that a given population of neurons can use different codes to support appropriate multimodal behavior.

An Exploration into Fern Genome Space.

Ferns are one of the few remaining major clades of land plants for which a complete genome sequence is lacking. Knowledge of genome space in ferns will enable broad-scale comparative analyses of land plant genes and genomes, provide insights into genome evolution across green plants, and shed light on genetic and genomic features that characterize ferns, such as their high chromosome numbers and large genome sizes. As part of an initial exploration into fern genome space, we used a whole genome shotgun sequencing approach to obtain low-density coverage (∼0.4X to 2X) for six fern species from the Polypodiales (Ceratopteris, Pteridium, Polypodium, Cystopteris), Cyatheales (Plagiogyria), and Gleicheniales (Dipteris). We explore these data to characterize the proportion of the nuclear genome represented by repetitive sequences (including DNA transposons, retrotransposons, ribosomal DNA, and simple repeats) and protein-coding genes, and to extract chloroplast and mitochondrial genome sequences. Such initial sweeps of fern genomes can provide information useful for selecting a promising candidate fern species for whole genome sequencing. We also describe variation of genomic traits across our sample and highlight some differences and similarities in repeat structure between ferns and seed plants.

Structure, Morphology, and Electrochemical Properties of Transition Metal Oxide, Hydroxide, and Phosphate Nanomaterials for Energy Storage

Energy storage technologies are crucial for efficient utilization of electricity. Supercapacitors and rechargeable batteries are of currently available energy storage systems. Transition metal oxides, hydroxides, and phosphates are the most intensely investigated electrode materials for supercapacitors and rechargeable batteries due to their high theoretical charge storage capacities resulted from reversible electrochemical reactions. Their insulating nature, however, causes sluggish electron transport kinetics within these electrode materials, hindering them from reaching the theoretical maximum. The conductivity of these transition metal based-electrode materials can be improved through three main approaches; nanostructuring, chemical substitution, and introducing carbon matrices. These approaches often lead to unique electrochemical properties when combined and balanced.

Ethanol-mediated solvothermal synthesis we developed is found to be highly effective for controlling size and morphology of transition metal-based electrode materials for both pseudocapacitors and batteries. The morphology and the degree of crystallinity of nickel hydroxide are systematically changed by adding various amounts glucose to the solvothermal synthesis. Nickel hydroxide produced in this manner exhibited increased pseudocapacitance, which is partially attributed to the increased surface area. Interestingly, this morphology effect on cobalt doped-nickel hydroxide is found to be more effective at low cobalt contents than at high cobalt contents in terms of improving the electrochemical performance.

Moreover, a thin layer of densely packed nickel oxide flakes on carbon paper substrate was successfully prepared via the glucose-assisted solvothermal synthesis, resulting in the improved electrode conductivity. When reduced graphene oxide was used for conductive coating on as-prepared nickel oxide electrode, the electrode conductivity was only slightly improved. This finding reveals that the influence of reduced graphene oxide coating, increasing the electrode conductivity, is not that obvious when the electrode is already highly conductive to begin with.

We were able to successfully control the interlayer spacing and reduce the particle size of layered titanium hydrogeno phosphate material using our ethanol-mediated solvothermal reaction. In layered structure, interlayer spacing is the key parameter for fast ion diffusion kinetics. The nanosized layered structure prepared via our method, however, exhibited high sodium-ion storage capacity regardless of the interlayer spacing, implying that interlayer space may not be the primary factor for sodium-ion diffusion in nanostructured materials, where many interstitials are available for sodium-ion diffusion.

Our ethanol-mediated solvothermal reaction was also effective for synthesis of NaTi2(PO4)3 nanoparticles with uniform size and morphology, well connected by a carbon nanotube network. This composite electrode exhibited high capacity, which is comparable to that in aqueous electrolyte, probably due to the uniform morphology and size where the preferable surface for sodium-ion diffusion is always available in all individual particles.

Fundamental understandings of the relationship between electrode microstructures and electrochemical properties discussed in this dissertation will be important to design high performance energy storage system applications.

Identifying the Structure and Fate of Wastewater Derived Organic Micropollutants by High-resolution Mass Spectrometry

Human activities represent a significant burden on the global water cycle, with large and increasing demands placed on limited water resources by manufacturing, energy production and domestic water use. In addition to changing the quantity of available water resources, human activities lead to changes in water quality by introducing a large and often poorly-characterized array of chemical pollutants, which may negatively impact biodiversity in aquatic ecosystems, leading to impairment of valuable ecosystem functions and services. Domestic and industrial wastewaters represent a significant source of pollution to the aquatic environment due to inadequate or incomplete removal of chemicals introduced into waters by human activities. Currently, incomplete chemical characterization of treated wastewaters limits comprehensive risk assessment of this ubiquitous impact to water. In particular, a significant fraction of the organic chemical composition of treated industrial and domestic wastewaters remains uncharacterized at the molecular level. Efforts aimed at reducing the impacts of water pollution on aquatic ecosystems critically require knowledge of the composition of wastewaters to develop interventions capable of protecting our precious natural water resources.

The goal of this dissertation was to develop a robust, extensible and high-throughput framework for the comprehensive characterization of organic micropollutants in wastewaters by high-resolution accurate-mass mass spectrometry. High-resolution mass spectrometry provides the most powerful analytical technique available for assessing the occurrence and fate of organic pollutants in the water cycle. However, significant limitations in data processing, analysis and interpretation have limited this technique in achieving comprehensive characterization of organic pollutants occurring in natural and built environments. My work aimed to address these challenges by development of automated workflows for the structural characterization of organic pollutants in wastewater and wastewater impacted environments by high-resolution mass spectrometry, and to apply these methods in combination with novel data handling routines to conduct detailed fate studies of wastewater-derived organic micropollutants in the aquatic environment.

In Chapter 2, chemoinformatic tools were implemented along with novel non-targeted mass spectrometric analytical methods to characterize, map, and explore an environmentally-relevant “chemical space” in municipal wastewater. This was accomplished by characterizing the molecular composition of known wastewater-derived organic pollutants and substances that are prioritized as potential wastewater contaminants, using these databases to evaluate the pollutant-likeness of structures postulated for unknown organic compounds that I detected in wastewater extracts using high-resolution mass spectrometry approaches. Results showed that application of multiple computational mass spectrometric tools to structural elucidation of unknown organic pollutants arising in wastewaters improved the efficiency and veracity of screening approaches based on high-resolution mass spectrometry. Furthermore, structural similarity searching was essential for prioritizing substances sharing structural features with known organic pollutants or industrial and consumer chemicals that could enter the environment through use or disposal.

I then applied this comprehensive methodological and computational non-targeted analysis workflow to micropollutant fate analysis in domestic wastewaters (Chapter 3), surface waters impacted by water reuse activities (Chapter 4) and effluents of wastewater treatment facilities receiving wastewater from oil and gas extraction activities (Chapter 5). In Chapter 3, I showed that application of chemometric tools aided in the prioritization of non-targeted compounds arising at various stages of conventional wastewater treatment by partitioning high dimensional data into rational chemical categories based on knowledge of organic chemical fate processes, resulting in the classification of organic micropollutants based on their occurrence and/or removal during treatment. Similarly, in Chapter 4, high-resolution sampling and broad-spectrum targeted and non-targeted chemical analysis were applied to assess the occurrence and fate of organic micropollutants in a water reuse application, wherein reclaimed wastewater was applied for irrigation of turf grass. Results showed that organic micropollutant composition of surface waters receiving runoff from wastewater irrigated areas appeared to be minimally impacted by wastewater-derived organic micropollutants. Finally, Chapter 5 presents results of the comprehensive organic chemical composition of oil and gas wastewaters treated for surface water discharge. Concurrent analysis of effluent samples by complementary, broad-spectrum analytical techniques, revealed that low-levels of hydrophobic organic contaminants, but elevated concentrations of polymeric surfactants, which may effect the fate and analysis of contaminants of concern in oil and gas wastewaters.

Taken together, my work represents significant progress in the characterization of polar organic chemical pollutants associated with wastewater-impacted environments by high-resolution mass spectrometry. Application of these comprehensive methods to examine micropollutant fate processes in wastewater treatment systems, water reuse environments, and water applications in oil/gas exploration yielded new insights into the factors that influence transport, transformation, and persistence of organic micropollutants in these systems across an unprecedented breadth of chemical space.

Moduli Space of (0,2) Conformal Field Theories

In this thesis we study aspects of (0,2) superconformal field theories (SCFTs), which are suitable for compactification of the heterotic string. In the first part, we study a class of (2,2) SCFTs obtained by fibering a Landau-Ginzburg (LG) orbifold CFT over a compact K\"ahler base manifold. While such models are naturally obtained as phases in a gauged linear sigma model (GLSM), our construction is independent of such an embedding. We discuss the general properties of such theories and present a technique to study the massless spectrum of the associated heterotic compactification. We test the validity of our method by applying it to hybrid phases of GLSMs and comparing spectra among the phases. In the second part, we turn to the study of the role of accidental symmetries in two-dimensional (0,2) SCFTs obtained by RG flow from (0,2) LG theories. These accidental symmetries are ubiquitous, and, unlike in the case of (2,2) theories, their identification is key to correctly identifying the IR fixed point and its properties. We develop a number of tools that help to identify such accidental symmetries in the context of (0,2) LG models and provide a conjecture for a toric structure of the SCFT moduli space in a large class of models. In the final part, we study the stability of heterotic compactifications described by (0,2) GLSMs with respect to worldsheet instanton corrections to the space-time superpotential following the work of Beasley and Witten. We show that generic models elude the vanishing theorem proved there, and may not determine supersymmetric heterotic vacua. We then construct a subclass of GLSMs for which a vanishing theorem holds.