Master of Science

thesisFor over a dozen years the Oklahoma Mesonet network has provided surface observations at over 100 stations. These observations are used to analyze mass flux estimates from surface divergence, frontal passages, and cold pools, the latter defined herein as active regions where precipitation processes are creating near-surface cold air masses. Case studies are detailed and a 15-yr climatology of frontal passages and cold pools was computed in this research. Convergence, divergence, and precipitation are most strongly correlated in the summer months and least correlated in the winter months. Wet spring and summer days had the highest average convergence and divergence values while dry summer and fall days had the lowest average convergence and divergence. Frontal passages and cold pools are tracked throughout the Mesonet in various case studies, four of which are covered herein. The methodology is able to represent front location and cold pool areas quite well despite the low resolution of the Mesonet grid. The climatology of front and cold pool data yielded many similarities. Winter has the largest magnitude changes in AT, AP, and Ah/cp while spring and fall had the largest magnitude change in Aq^. Summer has the lowest with the exception of spring AT. Correlations between these variables are lowest in the more convectively active summer season. Convergence is roughly equal ahead of fronts from spring through fall; however, divergence is present in summer frontal passages earlier and stronger compared to the other seasons. Fronts and cold pools are most likely to occur in summer and spring with summer having the highest percentage of fronts which lead to cold pools. Fronts and cold pools are substantially more likely to occur during the late afternoon and early evening in the summer; other seasons had a slighter nocturnal increase in frequency. Western Oklahoma had higher frequencies of frontal passages and cold pools than Eastern Oklahoma with frontal passages having the stronger signal. These findings help identify seasonal, diurnal, and geographic distributions of fronts and cold pools and can be used in modeling studies to better the understanding of cold pool processes and parameterizations

Extraction of Airways with Probabilistic State-space Models and Bayesian Smoothing

Segmenting tree structures is common in several image processing applications. In medical image analysis, reliable segmentations of airways, vessels, neurons and other tree structures can enable important clinical applications. We present a framework for tracking tree structures comprising of elongated branches using probabilistic state-space models and Bayesian smoothing. Unlike most existing methods that proceed with sequential tracking of branches, we present an exploratory method, that is less sensitive to local anomalies in the data due to acquisition noise and/or interfering structures. The evolution of individual branches is modelled using a process model and the observed data is incorporated into the update step of the Bayesian smoother using a measurement model that is based on a multi-scale blob detector. Bayesian smoothing is performed using the RTS (Rauch-Tung-Striebel) smoother, which provides Gaussian density estimates of branch states at each tracking step. We select likely branch seed points automatically based on the response of the blob detection and track from all such seed points using the RTS smoother. We use covariance of the marginal posterior density estimated for each branch to discriminate false positive and true positive branches. The method is evaluated on 3D chest CT scans to track airways. We show that the presented method results in additional branches compared to a baseline method based on region growing on probability images.Comment: 10 pages. Pre-print of the paper accepted at Workshop on Graphs in Biomedical Image Analysis. MICCAI 2017. Quebec Cit

Coherence correlations in the dissipative two-state system

We study the dynamical equilibrium correlation function of the polaron-dressed tunneling operator in the dissipative two-state system. Unlike the position operator, this coherence operator acts in the full system-plus-reservoir space. We calculate the relevant modified influence functional and present the exact formal expression for the coherence correlations in the form of a series in the number of tunneling events. For an Ohmic spectral density with the particular damping strength $K=1/2$, the series is summed in analytic form for all times and for arbitrary values of temperature and bias. Using a diagrammatic approach, we find the long-time dynamics in the regime $K<1$. In general, the coherence correlations decay algebraically as $t^{-2K}$ at T=0. This implies that the linear static susceptibility diverges for $K\le 1/2$ as $T\to 0$, whereas it stays finite for $K>1/2$ in this limit. The qualitative differences with respect to the asymptotic behavior of the position correlations are explained.Comment: 19 pages, 4 figures, to be published in Phys. Rev.

Neural signatures of cognitive flexibility and reward sensitivity following nicotinic receptor stimulation in dependent smokers : a randomized trial

IMPORTANCE Withdrawal from nicotine is an important contributor to smoking relapse. Understanding how reward-based decision making is affected by abstinence and by pharmacotherapies such as nicotine replacement therapy and varenicline tartrate may aid cessation treatment. OBJECTIVE To independently assess the effects of nicotine dependence and stimulation of the nicotinic acetylcholine receptor on the ability to interpret valence information (reward sensitivity) and subsequently alter behavior as reward contingencies change (cognitive flexibility) in a probabilistic reversal learning task. DESIGN, SETTING, AND PARTICIPANTS Nicotine-dependent smokers and nonsmokers completed a probabilistic reversal learning task during acquisition of functional magnetic resonance imaging (fMRI) in a 2-drug, double-blind placebo-controlled crossover design conducted from January 21, 2009, to September 29, 2011. Smokers were abstinent from cigarette smoking for 12 hours for all sessions. In a fully Latin square fashion, participants in both groups underwent MRI twice while receiving varenicline and twice while receiving a placebo pill, wearing either a nicotine or a placebo patch. Imaging analysis was performed from June 15, 2015, to August 10, 2016. MAIN OUTCOME AND MEASURES A well-established computational model captured effects of smoking status and administration of nicotine and varenicline on probabilistic reversal learning choice behavior. Neural effects of smoking status, nicotine, and varenicline were tested for on MRI contrasts that captured reward sensitivity and cognitive flexibility. RESULTS The study included 24 nicotine-dependent smokers (12 women and 12 men; mean [SD] age, 35.8 [9.9] years) and 20 nonsmokers (10 women and 10 men; mean [SD] age, 30.4 [7.2] years). Computational modeling indicated that abstinent smokers were biased toward response shifting and that their decisions were less sensitive to the available evidence, suggesting increased impulsivity during withdrawal. These behavioral impairments were mitigated with nicotine and varenicline. Similarly, decreased mesocorticolimbic activity associated with cognitive flexibility in abstinent smokers was restored to the level of nonsmokers following stimulation of nicotinic acetylcholine receptors (familywise error-corrected P<.05). Conversely, neural signatures of decreased reward sensitivity in smokers (vs nonsmokers; familywise error-corrected P<.05) in the dorsal striatum and anterior cingulate cortex were not mitigated by nicotine or varenicline. CONCLUSIONS AND RELEVANCE There was a double dissociation between the effects of chronic nicotine dependence on neural representations of reward sensitivity and acute effects of stimulation of nicotinic acetylcholine receptors on behavioral and neural signatures of cognitive flexibility in smokers. These chronic and acute pharmacologic effects were observed in overlapping mesocorticolimbic regions, suggesting that available pharmacotherapies may alleviate deficits in the same circuitry for certain mental computations but not for others

Boundary interactions changing operators and dynamical correlations in quantum impurity problems

Recent developments have made possible the computation of equilibrium dynamical correlators in quantum impurity problems. In many situations however, one is rather interested in correlators subject to a non equilibrium initial preparation; this is the case for instance for the occupation probability $P(t)$ in the double well problem of dissipative quantum mechanics (DQM). We show in this paper how to handle this situation in the framework of integrable quantum field theories by introducing ``boundary interactions changing operators''. We determine the properties of these operators by using an axiomatic approach similar in spirit to what is done for form-factors. This allows us to obtain new exact results for $P(t)$; for instance, we find that that at large times (or small $g$), the leading behaviour for g < 1/2} is $P(t)\propto e^{-\Gamma t}\cos\Omega t$, with the universal ratio. $\Omega/\Gamma = \cot {\pi g}/{2(1-g)}$.Comment: 4 pages, revte

Perturbative versus Non-perturbative QFT -- Lessons from the O(3) NLS Model

The two-point functions of the energy-momentum tensor and the Noether current are used to probe the O(3) nonlinear sigma model in an energy range below 10^4 in units of the mass gap $m$. We argue that the form factor approach, with the form factor series trunctated at the 6-particle level, provides an almost exact solution of the model in this energy range. The onset of the (2-loop) perturbative regime is found to occur only at energies around $100m$.Comment: 13 pages LaTex, 4 PostScript figures; version published in Physics Letters

Empirical likelihood estimation of the spatial quantile regression

The spatial quantile regression model is a useful and flexible model for analysis of empirical problems with spatial dimension. This paper introduces an alternative estimator for this model. The properties of the proposed estimator are discussed in a comparative perspective with regard to the other available estimators. Simulation evidence on the small sample properties of the proposed estimator is provided. The proposed estimator is feasible and preferable when the model contains multiple spatial weighting matrices. Furthermore, a version of the proposed estimator based on the exponentially tilted empirical likelihood could be beneficial if model misspecification is suspect

About Swarms of Long - Period Earthquakes at Volcano Nyamuragira of the Virunga Region, Western Rift Valley of Africa (D.R. Congo)

International audienceSwarms of Long Period earthquakes generated by the Nyamuragira volcano for the period from January 2000 to November 2006 before 21 January 2000, 5 February 2001, 25 July 2002, 8 May 2004 and 27 November 2006 Nyamuragira eruptions have been analyzed. Interest is focused on the frequency distribution of these earthquakes and on the variation of the m-value of observed earthquake swarms. It is found that m-values which generally vary between 0.9 and 1.6, and shifts towards larger values of 1.7 to 3.23 two to four months prior to eruptions of the volcano