Typescript (photocopy). / Digitized by Kansas Correctional Industries

Data resulting from eye-tracking experiments allows researchers to analyze the decision making process as study participants consider alternative items prior to the ultimate end point selection. The aim of such an analysis is to extract the underlying cognitive decision making process that develops throughout the experiment. Resulting data can be difficult to analyze, however, as eye-tracking curves have very high autocorrelation values which consists of measurements that are milliseconds apart, as mandated by the nature of eye movements. We propose an analytic approach to eye-tracking data that tests for statistically significant differences at every time point along the curve while calculating an appropriate familywise error rate correction which is based upon an autoregressive correlation assumption of the test statistics. Our technique has been implemented in the R package BDOTS with various extensions relevant to the real-world analysis of highly correlated nonlinear data. A popular alternative approach to analyzing eye-tracking data is to fit mixed models to the area under the curve. Through simulation studies we provide evidence for the benefit of using information criterion measures in selection of the random effects structure and make an argument against current industry-standard approaches such as sequential likelihood ratio tests or always using a maximal random effects structure.

The Mitochondrial Pyruvate Carrier (MPC) occupies a central metabolic node by transporting cytosolic pyruvate into the mitochondrial matrix, thereby linking glycolysis with mitochondrial metabolism. Two reported human MPC1 mutations cause developmental abnormalities, neurological problems, metabolic deficits, and for one patient, early death. We aimed to understand biochemical mechanisms by which the human patient c.C289T and c.T236A MPC1 alleles disrupt MPC function. MPC1 c.C289T encodes two protein variants, a mis-spliced, truncation mutant (A58G) and full-length point mutant (R97W). MPC1 c.T236A encodes a full-length point mutant (L79H). Using human patient fibroblasts and complementation of CRISPR-deleted, MPC1 null mouse C2C12 cells, we investigated how MPC1 mutations cause MPC deficiency. Truncated MPC1 A58G protein was intrinsically unstable and failed to form MPC complexes. The MPC1 R97W protein was less stable but when overexpressed formed complexes with MPC2 that retained pyruvate transport activity. Conversely, MPC1 L79H protein formed stable complexes with MPC2, but these complexes failed to transport pyruvate. These findings inform MPC structure-function relationships and delineate three distinct biochemical pathologies resulting from human patient MPC1 mutations and inform fundamental MPC structure-function relationships. These results also demonstrate an efficient molecular genetic system using the mouse C2C12 cell line to mechanistically investigate human inborn errors in pyruvate metabolism.

In der vorliegenden Arbeit sollte anhand der error-related negativity (ERN) eine eingeschränkte Fehlerwahrnehmung und im weiteren Sinne eine eingeschränkte Handlungskontrolle bei Patienten mit Erkrankungn aus dem schizophrenen Formenkreis im Vergleich zu gesunden Probanden dargestellt werden. Für diesen Vergleich wurde zusätzlich die error- positivity (Pe) herangezogen. Anhand dieser Parameter erfolgte zusätzlich ein Vergleich der Patienten mit einer klassischen Schizophrenie und solchen mit einer Zykloiden Psychose mit Blick auf die bereits existierende klinische Differenzierung gemäß Leonhard. Als Ergebnis ließen sich im Vergleich zu den Kontrollprobanden eine eingeschränkte ERN und eine eingeschränkte Pe bei beiden Patientengruppen feststellen. Die Hypothese, dass Patienten mit einer Zykloiden Psychose sich nicht nur klinisch, sondern auch elektrophysiologisch von den Patienten mit einer klassischen Schizophrenie unterscheiden, ließ sich anhand der ERN und der Pe nicht untermauern. Anders als angenommen wiesen die Patienten mit einer Zykloiden Psychose keine weniger starke Einschränkung der beiden elektrophysiologischen Parameter auf. / In this study we used the error-related negativity (ERN) to show a restricted error- perception and in a broader sense, a limited executive control in patients with schizophrenia spectrum psychoses compared to healthy subjects. Additionally we took the error-positivity (Pe) into account in order to compare these groups. Moreover we tried to differentiate patients with a classical schizophrenia from patients with a cycloid psychosis based on the parameters mentioned above in view of the already existing clinical differentiation according to Leonhard. As a result both patient groups showed lower amplitudes for the ERN and the Pe. The hypothesis that patients with cycloid psychosis differ not only clinically but also electrophysiologically from the patients with classical schizophrenia could not be corroborated by means of the ERN and the Pe. Unlike our assumption patients with a cycloid psychosis did not show less severe restrictions in both electrophysiological parameters compared to those with a classical schizophrenia.

ASABE/ISO Standard 12188-2 provides test procedures for positioning and guidance systems in agricultural vehicles during straight and level travel. The standard provides excellent descriptions of test procedures, however it does not provide detail on methods to carry out the calculations necessary to calculate relative cross-track error (XTE), which is the primary measurement used to judge accuracy of the system. The standard was used to estimate the guidance accuracy of a relatively low-accuracy vehicle at 1.25 and 0.5 m s-1. At 1.25 m s-1, a nearest point calculation overestimated mean XTE by 0.8 cm, or 8.2%. The location sampling density was much higher with a 0.5 m s-1 travel speed, and mean XTE was only overestimated by 0.1 cm with the nearest point method. Power and energy data were recorded using a sled with a known weight to vary the drawbar force on asphalt. This will allow a comparison between the electric and conventional tractor over a range of forces applicable to a 20 HP tractor. The electric tractor was found to consume less than half the energy compared to a Kubota L5030 in a common configuration and a custom configuration to match the weight distribution of the electric tractor. Finger weeding tasks were recorded throughout the year capturing the duration and frequency of these tasks at the University of Kentucky (UK) consumer supported agriculture (CSA) farm. Power and energy data were recorded from the electric tractor while finger weeding. Diesel consumption was also recorded from a conventional tractor while finger weeding. Field data shows that the electric tractor needs approximately 0.532 kWh of energy while a conventional tractor requires approximately 1.258 kWh or energy to finger weed each row of vegetables. Conventional electric bills were compiled for the University of Kentucky CSA establishing an average monthly electric need. Historic NREL data was compiled establishing an average potential solar resource for central Kentucky. It was determined that a 15 kW photovoltaic array could meet the conventional electric needs of the UK CSA and supply the net energy allowing the electric tractor to meet the finger weeding need.

Four-dimensional variational data assimilation (4D-Var) provides an estimate to the state of a dynamical system through the minimization of a cost functional that measures the distance to a prior state (background) estimate and observations over a time window. The analysis fit to each information input component is determined by the specification of the error covariance matrices in the data assimilation system (DAS). Weak-constraint 4D-Var (w4D-Var) provides a theoretical framework to account for modeling errors in the analysis scheme. In addition to the specification of the background error covariance matrix, the w4D-Var formulation requires information on the model error statistics and specification of the model error covariance. Up to now, the increased computational cost associated with w4D-Var has prevented its practical implementation. Various simplifications to reduce the computational burden have been considered, including writing the model error covariance as a scalar multiple of the background error covariance and modeling the model error. In this thesis, the main objective is the development of computationally feasible techniques for the improved representation of the model error statistics in a data assimilation system. Three new approaches are considered. A Monte Carlo method that uses an ensemble of w4D-Var systems to obtain flow-dependent estimates to the model error statistics. The evaluation of statistical diagnostic equations involving observation residuals to estimate the model error covariance matrix. An adaptive tuning procedure based on the sensitivity of a short-range forecast error measure to the model error DAS parametrization. The validity and benefits of these approaches are shown in two stages of numerical experiments. A proof-of-concept is shown using the Lorenz multi-scale model and the shallow water equations for a one-dimensional domain. The results show the potential of these methodologies to produce improved state estimates, as compared to other approaches in data assimilation. It is expected that the techniques presented will find an extended range of applications to assess and improve the performance of a w4D-Var system.

To gain an appreciation or understanding for the title of this study we must first understand what the phrases "non-orthogonal" and "error structure" mean. With an understanding of these terms the title of this study will become clear. To obtain an understanding of the term non-orthogonal, consider an experiment where differing treatments are applied to groups of experi­mental units in order to observe the differential treatment responses. If an equal number of experimental units are in each group, then we say we have an orthogonal situation. This means that when equal numbers exist among the experimental units, that the variability associated with the individual sources of variation can be orthogonally partitioned, such that the sources of variability add to the total source of variation. However, if unequal numbers exist among the experimental units, then we say we have a non-orthogonal situation. This implies that we can no longer obtain a completely orthogonal partition, and that the sources of variability associated with the individual sources of variation do not add to the total source of variation. The phrase, error structure, can best be described with reference to the statistical technique known as the analysis of variance. For any typical analysis of variance, there exists a one to one correspondence between the mean squares and the recognized sources of variation in the underlying model.

A wide range of modern large-scale systems relies on recovering a signal from noisy linear measurements. In many applications, the useful signal has inherent properties, such as sparsity, low-rankness, or boundedness, and making use of these properties and structures allow a more efficient recovery. Hence, a significant amount of work has been dedicated to developing and analyzing algorithms that can take advantage of the signal structure. Especially, since the advent of Compressed Sensing (CS) there has been significant progress towards this direction. Generally speaking, the signal structure can be harnessed by solving an appropriate regularized or constrained M-estimator. In modern Multi-input Multi-output (MIMO) communication systems, all transmitted signals are drawn from finite constellations and are thus bounded. Besides, most recent modulation schemes such as Generalized Space Shift Keying (GSSK) or Generalized Spatial Modulation (GSM) yield signals that are inherently sparse. In the recovery procedure, boundedness and sparsity can be promoted by using the ℓ1 norm regularization and by imposing an ℓ∞ norm constraint respectively. In this thesis, we propose novel optimization algorithms to recover certain classes of structured signals with emphasis on MIMO communication systems. The exact analysis permits a clear characterization of how well these systems perform. Also, it allows an automatic tuning of the parameters. In each context, we define the appropriate performance metrics and we analyze them exactly in the High Dimentional Regime (HDR). The framework we use for the analysis is based on Gaussian process inequalities; in particular, on a new strong and tight version of a classical comparison inequality (due to Gordon, 1988) in the presence of additional convexity assumptions. The new framework that emerged from this inequality is coined as Convex Gaussian Min-max Theorem (CGMT).

Stress and intonation play important roles in the production and perception of the English language. They are always very difficult for second language learners to acquire. Yet, a review of literature reveals that these important suprasegmental features have not received due attention from second language researchers or teachers. In Vietnam in particular, there is no research to date which studies the stress and intonation errors in the performance of Vietnamese learners of English. This study uses the procedures of Error Analysis to investigate the problem. Chapter one and two give a review of relevant literature and a description of the methodology of the study. In chapter three, the students' stress and intonation errors are described and classified, and the possible sources of those errors are discussed. Finally, chapter four shows implications and makes suggestions for the improvement of teaching and learning English stress and intonation.

This case study was explored to determine effective error-correction/feedback methods for two ESL Korean children's writing (recounting task) in terms of accuracy, fluency and attitudes. Three different error-correction methods - written comments focusing on meaning by researcher (Case1), direct and global error-correction focusing on form by researcher (Case2) and self-directed error-correction using check lists by subjects (Case 3) - were applied over a period of 7 months. Thirty pieces of recount writing per subject were collected (10 pieces per case) and analysed by structured criteria of fluency and accuracy. Through participant observation, the subjects' changing attitudes were recorded in notes and video tapes. The results of the analysis showed that for Subject B, who was 7 years old and a more advanced writer of English than Subject A, self-directed error-correction using check lists (Case 3) was the most effective method in relation to both fluency and accuracy as well as attitude. Yet, for Subject A who was 5 years old and an early beginner in her writing, Case 1 seemed to be more effective in terms of fluency and attitude and Case 3 was likely to be more effective in terms of accuracy. In discussion, the method of error correction / feedback, the issue of ownership in children's writing including errorcorrection and the necessity of process writing were highlighted in the light of the whole context of the case study.