Kernicterus causes damage to the auditory system and the basal ganglia in humans. Although the Gunn rat model of kernicterus has been extensively used to characterize the auditory features, this model has not been utilized to systematically investigate the movement disorder. In the present study, spontaneously jaundiced (jj) 16 day old Gunn rat pups were treated with sulfadimethoxine to exacerbate bilirubin neurotoxicity and compared to saline treated jjs and non-jaundiced (Nj) littermates. Electromyographic (EMG) activity was recorded from antagonistic hip muscles in dystonic and in normal appearing rats. Raw EMG signals were decomposed using the Discrete Wavelet Transform based multi-resolution analysis, and signal coefficients corresponding to the dominant EMG frequency band were chosen. Gunn rats exposed to sulfadimethoxine developed a stable clinical state characterized by prolonged abnormal axial and appendicular postures. Coherence plots revealed 4-7 Hz co-activation in antagonistic muscles that was significantly more prominent in jj sulfa treated dystonic compared to normal rats. The EMG findings support the presence of dystonia in sulfadimethoxine exposed jj Gunn rats.

Over the last 20 years, much work has focused on computer-aided clinical decision support systems due to a rapid increase in the need for management and processing of medical knowledge. Among all fields of medicine, trauma care has the highest need for proper information management due to the high prevalence of complex, life-threatening injuries. In particular, hemorrhage, which is encountered in most traumatic injuries, is a dominant factor in determining survival in both civilian and military settings. This complication can be better managed using a more in-depth analysis of patient information. Trauma physicians must make precise and rapid decisions, while considering a large number of patient variables and dealing with stressful environments. The ability of a computer-aided decision making system to rapidly analyze a patient’s condition can enable physicians to make more accurate decisions and thereby significantly improve the quality of care provided to patients. The first part of this study is focused on classification of highly complex databases using a hierarchical method which combines two complementary techniques: logistic regression and machine learning. This method, hereafter referred to as Classification Using Significant Features (CUSF), includes a statistical process to select the most significant variables from the correlated database. Then a machine learning algorithm is used to identify the data into classes using only the significant variables. As the main application addressed by CUSF, a set of computer-assisted rule-based trauma decision making system are designed. Computer aided decision-making system not only provides vital assistance for physicians in making fast and accurate decisions, proposed decisions are supported by transparent reasoning, but also can confirm a physicians’ current knowledge, enabling them to detect complex patterns and information which may reveal new knowledge not easily visible to the human eyes. The second part of this study proposes an algorithm based on a set of novel wavelet features to analyze physiological signals, such as Electrocardiograms (ECGs) that can provide invaluable information typically invisible to human eyes. These wavelet-based method, hereafter referred to as Signal Analysis Based on Wavelet-Extracted Features (SABWEF), extracts information that can be used to detect and analyze complex patterns that other methods such as Fourier cannot deal with. For instance, SABWEF can evaluate the severity of hemorrhagic shock (HS) from ECG, while the traditional technique of applying power spectrum density (PSD) and fractal dimension (FD) cannot distinguish between the ECG patterns of patients with HS (i.e. blood loss), and those of subjects undergoing physical activity. In this study, as the main application of SABWEF, ECG is analyzed to distinguish between HS and physical activity, and show that SABWEF can be used in both civilian and military settings to detect HS and its extent. This is the first reported use of an ECG analysis method to classify blood volume loss. SABWEF has the capability to rapidly determine the degree of volume loss from hemorrhage, providing the chance for more rapid remote triage and decision making.

We study planar systems of difference equations and applications to biological models of species populations. Central to the analysis of this study is the idea of folding - the method of transforming systems of difference equations into higher order scalar difference equations. Two classes of second order equations are studied: quadratic fractional and exponential. We investigate the boundedness and persistence of solutions, the global stability of the positive fixed point and the occurrence of periodic solutions of the quadratic rational equations. These results are applied to a class of linear/rational systems that can be transformed into a quadratic fractional equation via folding. These results apply to systems with negative parameters, instances not commonly considered in previous studies. We also identify ranges of parameter values that provide sufficient conditions on existence of chaotic and multiple stable orbits of different periods for the planar system. We study a second order exponential difference equation with time varying parameters and obtain sufficient conditions for boundedness of solutions and global convergence to zero. For the autonomous case, we show occurrence of multistable periodic and nonperiodic orbits. For the case where parameters are periodic, we show that the nature of the solutions differs qualitatively depending on whether the period of the parameters is even or odd. The above results are applied to biological models of populations. We investigate a broad class of planar systems that arise in the study of stage-structured single species populations. In biological contexts, these results include conditions on extinction or survival of the species in some balanced form, and possible occurrence of complex and chaotic behavior. Special rational (Beverton-Holt) and exponential (Ricker) cases are considered to explore the role of inter-stage competition, restocking strategies, as well as seasonal fluctuations in the vital rates.

An n-dimensional halved cube is a graph whose vertices are the binary strings of length n, where two vertices are adjacent if and only if they differ in exactly two positions. It can be regarded as the graph whose vertex set is one partite set of the n-dimensional hypercube, with an edge joining vertices at hamming distance two. In this thesis we compute the automorphism groups of the halved cubes by embedding them in R n and realizing the automorphism group as a subgroup of GLn(R). As an application we show that a halved cube is a circulant graph if and only if its dimension of is at most four.

On appelle clinker le matériau obtenu par cuisson de calcaire et d'argile et qui constitue le principal ingrédient du ciment Portland, composant essentiel de la majorité des bétons produits dans le monde. Ce clinker doit être finement broyé avant de pouvoir présenter une réactivité suffisante. La maîtrise des procédés de broyage représente un enjeu considérable pour l'industrie cimentière : il s'agit du premier poste en termes de consommation électrique d'une usine, en partie du fait de l'inefficacité des procédés employés. Les techniques de broyage par compression, apparues au cours des années 80, ont constitué un progrès majeur du point de vue de l'efficacité énergétique, mais la généralisation de leur utilisation a été freinée par des problèmes de maîtrise du procédé, en particulier pour des finesses importantes. L'enjeu de cette thèse est une meilleure compréhension des phénomènes en jeu lors du broyage par compression du clinker, en vue d'un meilleur contrôle des installations industrielles lors de la fabrication de produits fins. Nous nous sommes intéressés en particulier au comportement, du point de vue fondamental, d'un matériau granulaire subissant une fragmentation de ses grains, en nous appuyant sur la simulation numérique d'un Volume Elémentaire Représentatif de matière par les éléments discrets (DEM). Nous avons aussi recherché une loi de comportement permettant de relier contraintes, déformation, et évolution de la taille des particules pour le matériau broyé, en nous appuyant à la fois sur la micromécanique et les techniques d'homogénéisation, et un modèle semi-empirique de bilans de masses. Enfin, un premier pas vers la modélisation du procédé industriel et notamment sa simulation par éléments finis a été esquissé, afin de résorber les difficultés rencontrées en pratique par les industriels / Noindent Clinker is the material obtained by calcination of a mix of clay and limestone, and it is the main component of Portland cement, a crucial ingredient for the majority of concrete used around the world. This clinker must be finely ground to have a sufficient reactivity. Mastering the grinding process is a key issue in the cement industry: it is the first source of expense in terms of electric consumption in a factory, partially because of the overall inefficiency of the process. Compressive grinding techniques, first appeared during the 80's, allow major improvements in terms of energy efficiency, but the general implementation is yet to come, hindered by process control issues, especially for high fineness. The goal of this study is a better understanding of phenomenons occurring during compressive grinding of clinker, in order to provide better process control for industrial installations when dealing with fine products. We particularly choose to study the behaviour, on a fundamental point of view, of a granular material subjected to grain fragmentation, using the numerical simulation of an Elementary Representative Volume of material through Discrete Element Method (DEM). We also looked for a behaviour law able to provide a link between stress, strain, and grain size evolution for the ground material, using at the same time micromechanics and homogenization technique, and a semi-empirical mass balance model. Finally, we made first efforts in the direction of modelling the whole process through numerical simulation by Finite Element Method (FEM), in order to tackle the issue met by the industrials in operations

Let G be a finite cyclic group. Solving the equation g^x = y for a given generator g and y is called the discrete logarithm problem. This problem is at the core of many modern cryptographic transformations. In this paper we provide a survey of algorithms to attack this problem, including the function field sieve, the fastest known algorithm applicable to the multiplicative group of a finite field. We also discuss the index calculus algorithm and some techniques improving its performance: the Coppersmith's algorithm and the polynomial sieving. The most important contribution of this paper is a C-language implementation of the function field sieve and its application to real inputs.

Many of today's cryptographic systems are based on the discrete logarithm problem, e.g. the Diffie-Hellman protocol. The number field sieve algorithm (NFS) is the algorithm solving the problem of factorization of integers, but latest works show, it can be also applied to the discrete logarithm problem. In this work, we study the number field sieve algorithm for discrete logarithm and we also compare the NFS for discrete logarithm with the NFS for factoriza- tion. Even though these NFS algorithms are based on the same principle, many differences are found. 1

No description available.

Regression Wavelet Analysis (RWA) is a novel wavelet-based scheme for coding hyperspectral images that employs multiple regression analysis to exploit the relationships among spectral wavelet transformed components. The scheme is based on a pyramidal prediction, using different regression models, to increase the statistical independence in the wavelet domain For lossless coding, RWA has proven to be superior to other spectral transform like PCA and to the best and most recent coding standard in remote sensing, CCSDS-123.0. In this paper we show that RWA also allows progressive lossy-to-lossless (PLL) coding and that it attains a rate-distortion performance superior to those obtained with state-of-the-art schemes. To take into account the predictive significance of the spectral components, we propose a Prediction Weighting scheme for JPEG2000 that captures the contribution of each transformed component to the prediction process.

Doctor of Philosophy / Department of Economics / Philip G. Gayle / This dissertation is composed of two essays in the field of Industrial Organization. Specifically, the empirical studies are conducted by focusing on the market structure and competition issues in the airline industry. The first essay investigates entry deterrence through incumbents’ pricing strategies in the airline industry. Recent research finds evidence that incumbent airlines tend to cut fares in response to the “threat” of entry by Southwest Airlines. Instead of focusing on the entry threat by a single carrier, this essay re-examines this issue by looking at incumbent airlines’ price response when entry is threatened by a wider variety of potential entrant airlines. Results show that incumbents’ response vary by the identity of the firm making the threat. As expected, incumbents cut fares in response to the threat of entry by some potential entrants; however, a new result is also found that incumbents may respond by raising their fare depending on who is making the threat. The second essay looks into an antitrust-relevant issue in the airline industry. Proper antitrust analysis often focuses on whether the concerned differentiated products are truly competing with each other. This essay uses a structural econometric model to investigate whether nonstop and connecting air travel products effectively compete with each other. Estimate results suggest that connecting products may be an attractive alternative to nonstop products for leisure travelers but less so for business travelers. If connecting products are counterfactually eliminated, the empirical model predicts small price changes for nonstop products. This suggests that the two product types only weakly compete with each other and can be treated as being in separate product markets for antitrust purposes.