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Doctor of Philosophy / Department of Agronomy / Jianming Yu / Knowledge of the genetic bases of grain quality traits will complement plant breeding efforts to improve the end use value of sorghum (Sorghum bicolor (L.) Moench). The objective of the first experiment was to assess marker-trait associations for 10 grain quality traits through candidate gene association mapping on a diverse panel of 300 sorghum accessions. The 10 grain quality traits were measured using the single kernel characterization system (SKCS) and near-infrared reflectance spectroscopy (NIRS). The analysis of the accessions through 1,290 genome-wide single nucleotide polymorphisms (SNPs) separated the panel into five subpopulations that corresponded to three major sorghum races (durra, kafir, and caudatum), one intermediate race (guinea-caudatum), and one working group (zerazera/caudatum). Association analysis between 333 SNPs in candidate genes/loci and grain quality traits resulted in eight significant marker-trait associations. A SNP in starch synthase IIa (SSIIa) gene was associated with kernel hardness (KH) with a likelihood ratio–based R[superscript]2 (R[subscript]L[subscript]R[superscript]2) value of 0.08. SNPs in starch synthase (SSIIb) gene (R[subscript]L[subscript]R[superscript]2 = 0.10) and loci pSB1120 (R[subscript]L[subscript]R[superscript]2 = 0.09) was associated with starch content. Sorghum is a crop well adapted to the semi arid regions of the world and my harbor genes for drought tolerance. The objective of second experiment was to identify quantitative trait loci (QTLs) for yield potential and drought tolerance. From a cross between Tx436 (food grain type) and 00MN7645 (drought tolerant) 248 recombinant inbred lines (RILs) was developed. Multi-location trials were conducted in 8 environments to evaluate agronomic performance of the RILs under favorable and drought stress conditions. The 248 RILs and their parents were genotyped by genotyping-by-sequencing (GBS). A subset of 800 SNPs was used for linkage map construction and QTL detection. Composite interval mapping identified a major QTLs for grain yield in chromosome 8 and QTL for flowering time in chromosome 9 under favorable conditions. Three major QTLs were detected for grain yield in chromosomes 1, 6, and 8 and two flowering time QTLs on chromosome 1 under drought conditions. Six QTLs were identified for stay green: two on chromosome 4; one each on chromosome 5, 6, 7, and 10 under drought conditions.

Visual navigation is a ubiquitous yet complex task which is performed by many species for the purpose of survival. Although visual navigation is actively being studied within the robotics community, the determination of elemental constituents of a robust visual navigation system remains a challenge. Motion estimation is mistakenly considered as the sole ingredient to make a robust autonomous visual navigation system and therefore efforts are made to improve the accuracy of motion estimations. On the contrary, there are other factors which are as important as motion and whose absence could result in inability to perform seamless visual navigation such as the one exhibited by humans. Therefore, it is needed that a general model for a visual navigation system be devised which would describe it in terms of a set of elemental units. In this regard, a set of visual navigation elements (i.e. spatial memory, motion memory, scene geometry, context and scene semantics) are suggested as building blocks of a visual navigation system in this thesis. A set of methods are proposed which investigate the existence and role of visual navigation elements in a visual navigation system. A quantitative research methodology in the form of a series of systematic experiments is conducted on these methods. The thesis formulates, implements and analyzes the proposed methods in the context of visual navigation elements which are arranged into three major groupings; a) Spatial memory b) Motion Memory c) Manhattan, context and scene semantics. The investigations are carried out on multiple image datasets obtained by robot mounted cameras (2D/3D) moving in different environments. Spatial memory is investigated by evaluation of proposed place recognition methods. The recognized places and inter-place associations are then used to represent a visited set of places in the form of a topological map. Such a representation of places and their spatial associations models the concept of spatial memory. It resembles the humans’ ability of place representation and mapping for large environments (e.g. cities). Motion memory in a visual navigation system is analyzed by a thorough investigation of various motion estimation methods. This leads to proposals of direct motion estimation methods which compute accurate motion estimates by basing the estimation process on dominant surfaces. In everyday world, planar surfaces, especially the ground planes, are ubiquitous. Therefore, motion models are built upon this constraint. Manhattan structure provides geometrical cues which are helpful in solving navigation problems. There are some unique geometric primitives (e.g. planes) which make up an indoor environment. Therefore, a plane detection method is proposed as a result of investigations performed on scene structure. The method uses supervised learning to successfully classify the segmented clusters in 3D point-cloud datasets. In addition to geometry, the context of a scene also plays an important role in robustness of a visual navigation system. The context in which navigation is being performed imposes a set of constraints on objects and sections of the scene. The enforcement of such constraints enables the observer to robustly segment the scene and to classify various objects in the scene. A contextually aware scene segmentation method is proposed which classifies the image of a scene into a set of geometric classes. The geometric classes are sufficient for most of the navigation tasks. However, in order to facilitate the cognitive visual decision making process, the scene ought to be semantically segmented. The semantic of indoor scenes as well as semantic of the outdoor scenes are dealt with separately and separate methods are proposed for visual mapping of environments belonging to each type. An indoor scene consists of a corridor structure which is modeled as a cubic space in order to build a map of the environment. A “flash-n-extend” strategy is proposed which is responsible for controlling the map update frequency. The semantics of the outdoor scenes is also investigated and a scene classification method is proposed. The method employs a Markov Random Field (MRF) based classification framework which generates a set of semantic maps.

A gene dosage study was conducted on a rare complete trisomy 22 human fibroblast cell line utilizing three lysosomal enzymes, ∝-iduronidase, ∝-galactosidase B, and arylsulfatase A, whose genes are located on chromosome 22 and two control enzymes, ,β-hexosaminidase A and -- fucosidase, with genes not on chromosome 22. A gene dosage effect was clearly demonstrated for an early passage number of the fibroblasts; however, later passage numbers gave inconclusive results. This study suggests that gene dosage studies must be carefully designed to be conducted only on early, matched passage number cells. ∝-fucosidase gave anomalous results most likely due to pleiotropic effects. The present gene dosage study confirmed the trisomic nature of the cell line studied and suggests that this type of study may be a useful diagnostic tool for small deletions, additions, or unbalanced translocations.

When animals explore a new environment, they do not acquire a precise map of the places visited. In fact, research has shown that learning is a recurring process. Over time, new information helps the animal to update their perception of the locations it has visited. Yet, they are still able to use the fuzzy and often incomplete representation to find their way home. This process has been termed the cognitive mapping process. The work presented in this thesis uses a mobile robot equipped with sonar sensors to investigate the nature of such a process. Specifically, what is the information that is fundamental and prevalent in spatial navigation? Initially, the robot is instructed to compute a “cognitive map” of its environment. Since a robot is not a cognitive agent, it cannot, by definition, compute a cognitive map. Hence the robot is used as a test bed for understanding the cognitive mapping process. Yeap’s (1988) theory of cognitive mapping forms the foundation for computing the robot’s representation of the places it has visited. He argued that a network of local spaces is computed early in the cognitive mapping process. Yeap coined these local spaces as Absolute Space Representations (ASRs). However, ASR is not just a process of partitioning the environment into smaller local regions. The ASRs describe the bounded space that one is in, how one could leave that space (exits) and how the exits serves to link the ASRs to form a network that serves as the cognitive map (see Jefferies (1999)). Like the animal’s cognitive map, ASRs are not precise geometrical maps of the environment but rather, provide a rough shape or feel of the space the robot is currently in. Once the robot computes its “cognitive map”, it is then, like foraging and hoarding animals, instructed to find its way home. To do so, the robot uses two crucial pieces of information: distance between exits of ASRs and relative orientation of adjacent ASRs. A simple animal-like strategy was implemented for the robot to locate home. Results from the experiments demonstrated the robot’s ability to determine its location within the visited environment along its journey. This task was performed without the use of an accurate map. From these results and reviews of various findings related to cognitive mapping for various animals, we deduce that: Different animals have different sensing capabilities. They live in different environments and therefore face unique challenges. Consequently, they evolve to have different navigational strategies. However, we believe two crucial pieces of information are inherent in all animals and form the fundamentals of navigation: distance and orientation. Higher level animals may encode and may even prefer richer information to enhance the animal’s cognitive map. Nonetheless, distance and orientation will always be computed as a core process of cognitive mapping. We believe this insight will help future research to better understand the complex nature of cognitive mapping.

In this thesis the mathematics of the potential field gradient tensor is thoroughly reviewed and the inter - relationships between the various components and quantities are established. Numerical forward modelling of 3D regolith scenarios is undertaken, showing that current instrumentation for measuring magnetic gradients is useful for near - surface exploration. Gravity gradiometry is only able to detect relatively large contrasts in density, and does not offer the same small - scale resolution as magnetic gradiometry. I examine the magnetic case further by incorporating surface measurements of magnetic susceptibility. These data are highly variable, and forward modelling shows while gradiometry is useful for regolith exploration, interpretation is difficult due to the high level of geological noise. I have tested new and standard filters as tools for extracting information from gradient tensor data. This includes boundaries between geological units and possible mineralisation positions. New techniques developed involve calculating an Analytic Signal for the entire gradient tensor, and forming multiplicative combinations of the individual gradient tensor components. The determinant and inverse of the gradient tensor 3 x 3 matrix can also yield useful information pertaining to source position and geological boundaries. These are illustrated by means of synthetic data examples. Examination of inversion techniques on gradient tensor data illustrates that single component inversion is comparable in the quality of the final result to a multi - component inversion, albeit much faster. Eigenvalues and eigenvectors of the full tensor produce information about depth and direction, although interpretation must be taken with care. I have developed an inversion routine to locate magnetic dipole sources, and illustrate how it produces multiple solutions to a problem, and how it is not possible to unambiguously determine which of these is correct. A new inversion routine was therefore developed. This new hybrid global inversion routine is an automated technique to locate a generalised magnetic multipole. It can locate dipole and quadrupole ( and some octupole ) sources successfully, and be used either in real time as data is being collected, or as post - processing on an entire data set. / Philip Heath / Thesis (Ph.D.)--School of Chemistry and Physics, 2007.

We propose a framework for semi-automatically verifying relational database schema mappings for data exchange. Schema mappings for data exchange formally describe how to move data between a source and target database. State-of-the-art schema mapping tools propose several mappings, but require user intervention to determine their semantic correctness. For this, the user must understand the domain the schemas represent and the meanings of individual schema elements in relation to the domain. Our framework eases the task of understanding the domain and schemas and performs preliminary mapping verification. We use a readable, expressive, and formal conceptual model - a domain ontology - to model the source and target schema domain. We model the schema semantics by annotating schema elements with ontology elements. Our mapping verification algorithm rewrites mappings as statements in terms of the ontology, and uses a reasoner to check that the statements are entailed by the ontology.

Criminal justice researchers and crime geographers have long recognized the importance of understanding where crimes happen as well as to whom and by whom. Although past research often focused on violent crimes, calls for research into non-lethal white-collar crimes emerged in the 1970s. Today, identity theft is among the fastest growing white-collar crimes in the United States, although official recognition of it as a criminal act is a relatively recent development. Remaining largely unmet, the need for white-collar crime research has greatly intensified considering the escalating identity theft problem. Furthermore, many studies conclude that identity theft will continue to rise due to increasing technology-driven offenses via the Internet and widespread use of digital consumer databases. Utilizing theoretical framework established in crime geography, GIS mapping and spatial statistics are employed to produce a spatial analysis of identity theft in the U.S. from 2002-2006. Distinct regional variations, such as high rates in the western and southwestern states, and low rates in New England and the central plains states, are identified for identity theft as reported by the FTC. Significant spatial patterns of identity theft victims alongside social demographic variables are also revealed in order to better understand the regional patterns that may indicate underlying social indicators contributing to identity theft. Potential social variables, such as race/ethnicity and urban-rural populations, are shown to have similar patterns that may be directly associated with U.S. identity theft victims. To date, no in-depth geographic studies exist on the geographic patterns of identity theft, although numerous existing studies attempt basic spatial pattern recognition and propose the need for better spatial interpretation. This thesis is the first empirical study on the geographies of identity theft. It fills in a void in the literature by revealing significant geographical patterns of identity theft in the digital age, attempts at understanding the social factors driving the patterns, and examines some of the social implications of identity theft.

The ability to map the profit made across a cotton field would enable producers to see in detail where money is being made or lost on their farms. This ability, which requires sitespecific knowledge of yield, fiber quality, and input costs would further enable them to implement precise field management practices to ensure that they receive the highest return possible on each portion of a field and do not waste materials and other inputs throughout the field. Investigators at Texas A&M previously developed a wireless-GPS system that tracks where a module of cotton comes from within a field. This system is a necessary component in mapping fiber quality, which is a major determiner of price and thus profit. Three drawbacks to the previous wireless-GPS system are that (1) a person must manually trigger the system to send wireless communications when a field machine dumps its load of cotton, (2) multiple field machines of the same type (e.g., two cotton pickers) cannot be used simultaneously on the same system within the same field, and (3) no software is available to automatically produce fiber-quality maps after the data are downloaded from the gin. The first two drawbacks, the need for an automatic communication-triggering system and the needed capability for multiple field machines of the same type are the problems addressed in this work. To solve the first problem, a sensing and control system was added to a harvester to automatically indicate when the machine is dumping a basket load of cotton so that wireless messages can be automatically sent from the harvester to subsequent field machines without human intervention. This automated communication-triggering system was incorporated into the existing wireless- GPS system, rigorously field tested, and ultimately proven to operate as designed. Linking data collected with this system together with classing information will enable producers to create fiber-quality maps, and linking fiber-quality maps with yield and input-cost maps will enable them to create profit maps. Additionally, a radio-frequency identification (RFID) system was integrated with the wireless-GPS system to allow for multiple field machines of the same type. The RFID system was also rigorously field tested and proven to operate as designed. Finally, the entire system was field tested as a whole and operated according to design. Thus, the wireless-GPS module tracking system now operates without human intervention and works with multiple field machines of each type, two additional capabilities required for practical use in large farming operations.