This study attempted to replicate and expand previously published research in order to increase our understanding of how Vocal Function Exercises (VFE) might improve vocal function in normal voices. Measures were made to reflect potential post-treatment changes in acoustic and aerodynamic variables, including a measure of vocal efficiency. The participants of the study included 35 adults with normal voices. Each completed a series of speech tasks (sustained vowels, maximum phonation time, reading of a standardized passage, and repetition of syllable strings) before and after a four-week treatment period. Testing of pre- and post-treatment data revealed no clear improvement in acoustic and aerodynamic measures of the voice. There were also no significant improvements in vocal efficiency following the VFE. These findings suggest the need for further research to better understand the value of VFE in improving vocal function.

Les séismes de grande magnitude (MW > 7) et les tsunamis associés induisent des perturbations qui peuvent être détectées dans l’atmosphère et l’ionosphère à partir des mesures TEC (contenu total en électron). Dans cette thèse, J’étudie la possibilité d’utiliser ce signal ionosphérique afin de compléter le système de surveillance et d’alerte aux tsunamis. Ainsi, j’étudie le couplage entre la Terre solide, l’océan, l’atmosphère. Je démontre en particulier que seule la fréquence à 1.5 mHz entre les modes de tsunami et les modes de gravité atmosphériques peut être détectée via l’ionosphère et met en évidence que l’efficacité du couplage océan/atmosphère est sensible à la profondeur de l’océan et l’heure locale. Ces développements ont permis de réaliser la modélisation complète de la signature ionosphérique de 3 tsunamis d’amplitude 2, 3 et 60 cm en plein océan : respectivement le tsunami d’Haida Gwaii en 2012 et le tsunami des Kouriles en 2006 en champ lointain et le tsunami de Tohoku 2011 en champ plus proche. Enfin, nous avons démontré que l’amplitude crête à crête de la hauteur du tsunami inversée reconstruit avec moins de 20 % d’erreur l’amplitude mesurée par une bouée DART dans ces trois cas / Large earthquake (MW > 7) and tsunamis are known to induce perturbations which can be detected in the atmosphere and ionosphere using total electron content (TEC) measurements. In this thesis, I first investigated on the possibility of using these ionospheric signals in order to complete the tsunami monitoring and warning system. Thus, I study the coupling between the solid Earth, the ocean, the atmosphere. I demonstrate that only the resonance at 1.5 mHz between the tsunami modes and the atmospheric gravity modes can be detected through ionosphere and highlight the fact that the efficiency of the coupling ocean/atmosphere is sensitive to ocean depth and local time. These developments enables the complete modelling of the ionospheric signature of 3 tsunami with an amplitude of 2, 3 and 60cm in deep ocean: the 2012 Haida Gwaii and the 2006 Kuril tsunami in far field and the 2011 Tohoku tsunami in closer field respectively. Finally, we demonstrated that the peak-to- peak amplitude of the height of the inverted tsunami reconstructs with less than 20% error the amplitude measured by a DART buoy in these three cases

The overall goal of this doctoral dissertation is to develop a prototype instrument, a Portable Aerosol Collector and Spectrometer (PACS), that can continuously measure aerosol size distributions by number, surface area and mass concentrations over a wide size range (from 10 nm to 10 µm) while also collecting particles with impactor and diffusion stages for post-sampling chemical analyses. To achieve the goal, in the first study, we designed, built and tested the PACS hardware. The PACS consists of a six-stage particle size selector, a valve system, a water condensation particle counter to measure number concentrations and a photometer to measure mass concentrations. The valve system diverts airflow to pass sequentially through upstream stages of the selector to the detectors. The stages of the selector include three impactor and two diffusion stages, which resolve particles by size and collect particles for chemical analysis. Particle penetration by size was measured through each stage to determine actual performance and account for particle losses. The measured d50 of each stage (aerodynamic diameter for impactor stages and geometric diameter for diffusion stages) was similar to the design. The pressure drop of each stage was sufficiently low to permit its operation with portable air pumps. In the second study, we developed a multi-modal log-normal (MMLN) fitting algorithm to leverage the multi-metric, low-resolution data from one sequence of PACS measurements to estimate aerosol size distributions of number, surface area, and mass concentration in near-real-time. The algorithm uses a grid-search process and a constrained linear least-square (CLLS) solver to find a tri-mode (ultrafine, fine, and coarse), log-normal distribution that best fits the input data. We refined the algorithm to obtain accurate and precise size distributions for four aerosols typical of diverse environments: clean background, urban and freeway, coal power plant, and marine surface. Sensitivity studies were conducted to explore the influence of unknown particle density and shape factor on algorithm output. An adaptive process that refined the ranges and step sizes of the grid-search reduced the computation time to fit a single size distribution in near-real-time. Assuming standard density spheres, the aerosol size distributions fit well with the normalized mean bias (NMB) of -4.9% to 3.5%, normalized mean error (NME) of 3.3% to 27.6%, and R2 values of 0.90 to 1.00. The fitted number and mass concentration biases were within ± 10% regardless of uncertainties in density and shape. With this algorithm, the PACS is able to estimate aerosol size distributions by number, surface area, and mass concentrations from 10 nm to 10 µm in near-real-time. In the third study, we developed a new algorithm–the mass distribution by composition and size (MDCS) algorithm–to estimate the mass size distribution of various particle compositions. Then we compared the PACS for measuring multi-mode aerosols to three reference instruments, including a scanning mobility particle sizer (SMPS), an aerodynamic particle sizer (APS) and a nano micro-orifice uniform deposit impactor (nanoMOUDI). We used inductively coupled plasma mass spectrometry to measure the mass of collected particles on PACS and nanoMOUDI stages by element. For the three-mode aerosol, the aerosol size distributions in three metrics measured with the PACS agreed well with those measured with the SMPS/APS: number concentration, bias = 9.4% and R2 = 0.96; surface area, bias = 17.8%, R2 = 0.77; mass, bias = -2.2%, R2 = 0.94. Agreement was considerably poorer for the two-mode aerosol, especially for surface area and mass concentrations. Comparing to the nanoMOUDI, for the three-mode aerosol, the PACS estimated the mass median diameters (MMDs) of the coarse mode well, but overestimated the MMDs for ultrafine and fine modes. The PACS overestimated the mass concentrations of ultrafine and fine mode, but underestimated the coarse mode. This work provides insight into a novel way to simultaneously assess airborne aerosol size, composition, and concentration by number, surface area and mass using cost-effective handheld technologies.

An inherited muscle hypertrophy in sheep is caused by the callipyge gene (CLPG) located on ovine chromosome 18. It has been suggested that this gene is a single autosomal dominant gene. Animals expressing the callipyge gene show increased muscling in the pelvic and torso regions of the body and, thus, have been given the phenotype- descriptive name callipyge (from Greek calli-beautiful; pyge-buttocks). In this study 21 wether lambs, the offspring of callipyge rams (genotype CLPG /clpg) and normal Rambouillet ewes (genotype clpg/clpg), were used to determine the difference s in muscle fiber type percentages, composition, and tenderness between normal and callipyge lambs . Eleven of these lambs showed muscle hypertrophy typical of the callipyge phenotype; 10 were classified as normal . Several histochemical, biochemical , and physical measures were examined in order to study changes in the physiology and biochemistry of some economically important muscles. When compared to normal lambs, the callipyge lambs have a larger (P < .05) average percentage of fast-twitch glycolytic (FG) muscle fibers and smaller average percentages of fast-twitch oxidative and glycolytic (FOG) and slow-twitch oxidative (SO) muscle fibers in both the longissimus and gluteus medius muscles. The diameter of the fast-twitch muscle fibers was larger in the callipyge group, but slow-twitch fibers were smaller than those of normal lambs. No differences were observed in the supraspinatus muscle of the normal and callipyge groups. Thus there is an indication of a differential effect of the callipyge gene among muscles of the callipyge lambs. The semitendinosis muscles of both the callipyge and normal groups were dissected from the carcasses. This muscle was larger (P < .01) and contained more protein in the callipyge lambs than in the normal lambs. However, the callipyge semitendinosis muscle did not have a significantly higher content of DNA than the normal lamb semitendinosis, suggesting that the muscle hypertrophy is not associated with an increase in muscle nuclei. The protein-to-DNA ratio was larger (P < .05) in the semitendinosis muscle of callipyge lambs than in the normal lambs. Protein-to-RNA and RNA-to-DNA ratios were similar; this suggests that the semitendinosis muscle was enlarged without increased translational or transcriptional activity. Samples from the callipyge longissimus and gluteus medius muscles had RNA, DNA, and protein ratios similar to those of the semitendinosis muscle, suggesting a similar mode of action for muscle enlargement in other muscles affected by this gene. Loin chops from the callipyge lambs had lower tenderness scores (P < .01) as measured by the Wamer-Bratzler shear force and myofibril fragmentation index (MFI). However, aging increased MFI scores and decreased shear scores (P < .0 l) of the callipyge lamb chops . The normal lamb chops also had decreased shear and increased MFI scores following the aging period. The loin chops from the callipyge lambs also tended to be less red (P < .1) than chops from normal animals as measured by Hunter 'L,' 'a,' and 'b' colorimeter scores.

SMART designs tailor individual treatment by re-randomizing patients to subsequent therapies based on their response to initial treatment. However, the classification of patients being responders/non-responders could be inaccurate and thus lead to inappropriate treatment assignment. In a two-step SMART design, by assuming equal randomization, and equal variances of misclassified patients and correctly classified patients, we evaluated misclassification effects on mean, variance, and type I error/ power of single sequential treatment outcome (SST), dynamic treatment outcome (DTRs), and overall outcome. The results showed that misclassification could introduce bias to estimates of treatment effect in all types of outcome. Though the magnitude of bias could vary according to different templates, there were a few constant conclusions: 1) for any fixed sensitivity the bias of mean of SSTs responders always approached to 0 as specificity increased to 1, and for any fixed specificity the bias of mean of SSTs non-responders always approached to 0 as sensitivity increased to 1; 2) for any fixed specificity there was monotonic nonlinear relationship between the bias of mean of SSTs responders and sensitivity, and for any fixed sensitivity there was also monotonic nonlinear relationship between the bias of mean of SSTs non-responders and specificity; 3) the bias of variance of SSTs was always non-monotone nonlinear equation; 4) the variance of SSTs under misclassification was always over-estimated; 5) the maximized absolute relative bias of variance of SSTs was always ¼ of the squared mean difference between misclassified patients and correctly classified patients divided by true variance, but it might not be observed in the range of sensitivity and specificity (0,1); 6) regarding to sensitivity and specificity, the bias of mean of DTRs or overall outcomes was always linear equation and their bias of variance was always non-monotone nonlinear equation; 7) the relative bias of mean/ variance of DTRs or overall outcomes could approach to 0 where sensitivity or specificity wasn’t necessarily to be 1. Furthermore, the results showed that the misclassification could affect statistical inference. Power could be less or bigger than planned 80% under misclassification and showed either monotonic or non-monotonic pattern as sensitivity or specificity decreased. To mitigate these adverse effects, patient observations could be weighted by the likelihood that their response was correctly classified. We investigated both normal-mixture-model (NM) and k-nearest-neighbor (KNN) strategies to attempt to reduce bias of mean and variance and improve inference at final stage outcome. The NM estimated the early stage probabilities of being a responder for each patient through optimizing the likelihood function by EM algorithm, while KNN estimated these probabilities based upon classifications for the k nearest observations. Simulations were used to compare the performance of these approaches. The results showed that 1) KNN and NM produced modest reductions of bias of point estimates of SSTs; 2) both strategies reduced bias on point estimates of DTRs when the misclassified patients and correctly classified patients from same initial treatment had unequal means; 3) NM reduced the bias of point estimates of overall outcome more than KNN; 4) in general, there were little effect on power adjustment; 5) type I error should always be preserved at 0.05 regardless of misclassification when same response rate and same treatment effects among responders or among non-responders were assumed, but the observed type I error tended to be less than 0.05; 6) KNN preserved type I error at 0.05, but NM might increase type I error rate. Even though most of time both KNN and NM strategies improved point estimates in SMART designs while we knew misclassification might be involved, the tradeoff were increased type I error rate and little effect on power. Our work showed that misclassification should be considered in SMART design because it introduced bias, but KNN or NM strategies at the final stage couldn’t completely reduce bias of point estimates or improve power. However, in future by adjusting with covariates, these two strategies might be used to improve the classification accuracy in the early stage outcomes.

Articular cartilage is an avascular, aneural, and alymphatic tissue with a structure consisting of a superficial, a middle and a deep zone, overlie a calcified zone at the cartilage border between. Each zone has biological and mechanical properties. Self-repair of damaged cartilage seldom if ever occurs, and joint injuries that harm cartilage surfaces often result in osteoarthritis. This has prompted researchers to explore diverse approaches to cartilage regeneration. The superficial zone shows the highest cellularity and the lowest matrix density. Cartilage cells (chondrocytes) residing in the superficial zone had been thought to be a subpopulation of chondrocytes. However, our laboratory identified a second population of cells that were distinguishable from chondrocytes based on their clonogenicity, multipotency, migratory activity, higher proliferate rate and substantial morphological differences. These cells later proved to be chondrogenic progenitor cells (CPCs). Our continuing studies have shown that CPCs are less chondrogenic than normal chondrocytes and their function is to protect the cartilage surface rather than to regenerate cartilage matrix as previously supposed. In addition, we found evidence to suggest that CPCs act as pro-inflammatory cells in the context of cartilage injury. For these reasons, we undertook a more comprehensive comparison of the phenotypic differences between CPCs and normal chondrocytes and between CPCs and joint cells (tissue synoviocytes from the joint capsule and cells present in synovial fluid) which have been shown to be play roles in joint inflammation. Gene expression microarray analysis of >25,000 genes revealed that the overall pattern of gene expression in CPCs was distinct from normal chondrocytes, but closely related to synoviocytes and synovial fluid cells. Analysis of specific genes by quantitative PCR (qPCR) showed profound differences between CPCs and normal chondrocytes in terms of cartilage matrix gene expression (Collagen Type ІІ, Aggrecan, Link Protein and COMP) and pro-inflammatory gene expression (IL6, IL8, CCL2 and CXCL12). In contrast, the pattern of CPC gene expression closely resembled. Sulfated glycosaminoglycan assays revealed that cartilage matrix deposition by CPCs, as well as synoviocytes and synovial fluid cells, was significantly inferior to normal chondrocytes. However, chondrogenic and osteogenic differentiation assays, showed no significant differences among the four cell types. In addition to establishing that CPCs are distinct from chondrocytes, this work suggests significant revisions to our understanding of CPC function in cartilage. The weak chondrogenic ability and higher expression of inflammatory cytokines, suggests these cells don't play a regenerative role as previously thought. On the other, we found evidence that CPCs may form a protective layer on the top of the injured cartilage surfaces, preventing further cartilage injury. In vivo studies are needed to fully elucidate the significance of these roles in cartilage health and disease.

Geologic mapping, basin analysis, and tephrochronologic analysis in the Clifton quadrangle of southeast Idaho indicates that the modern Basin-and-Range topography is only a few million years old and that the bulk of Cenozoic extension was accommodated by slip on an older low-angle normal-fault system, the Bannock detachment system. The detachment system was active between ~12 and < 4 Ma and accommodated ~50 % extension. Cross-cutting relationships show that the master detachment fault, the Clifton fault, is the youngest low-angle normal fault of the system, was active at a low angle, and has not been rotated to a low-dip angle through time. Map patterns and relationships indicate that the hanging wall to the detachment system began as a cohesive block that later broke up along listric and planar normal faults that either sole into or are cut by the master detachment fault. The Miocene-Pliocene Salt Lake Formation, a syntectonic, basin-fill deposit of the Bannock detachment system, was deposited during three sub-episodes of extension on the detachment system. Depositional systems within the Salt Lake Formation evolved from saline/alkaline lakes to fresh water lakes and streams to braided streams in response to the changing structural configuration of rift basins in the hanging wall of the detachment system. After breakup of the hanging wall began, the master detachment fault excised part of the hanging wall and cut hanging-wall deposits and structures. The structural geometry of the Bannock detachment system strongly resembles that of detachments documented in metamorphic core complexes. Therefore, we interpret the Bannock detachment system as a proto-metamorphic core complex, akin to the Sevier Desert detachment fault. The Bannock detachment system also collapsed the Cache-Pocatello culmination of the dormant Sevier fold-and-thrust belt, much like the Sevier Desert detachment collapsed the Sevier culmination. Structures of the Bannock detachment system are overprinted by a second episode of extension accommodated by E- and NE-trending normal faults that may be related to subsidence along the Yellowstone hotspot track and a third episode of extension accommodated by high-angle, Basin-and-Range normal faults. This last episode of extension began no earlier than 4-5 Ma and continues today.

Let (X1, X2, X3) be a tri-variate normal vector with a non-singular co-variance matrix ∑ , where for i ≠ j, ∑ij < 0 . It is shown here that it is then possible to determine the three means, the three variances and the three correlation coefficients based only on the knowledge of the probability density function for the minimum variate Y = min{X1 , X2 , X3 }. We will present a method for identifying the nine parameters which consists of careful determination of the asymptotic orders of various bivariate tail probabilities.

The problem of resource allocation and management in the context of multiple crises occurring in an urban environment is challenging. In this thesis, the problem is formulated using game theory and a solution is developed based on the Nash equilibrium to optimize the allocation of resources to the different crisis events in a fair manner considering several constraints such as the availability of resources, the criticality of the events, the amount of resources requested etc. The proposed approach is targeted at managing small to medium level crisis events occurring simultaneously within a specific pre-defined perimeter with the resource allocation centers being located within the same fixed region. The objective is to maximize the utilization of the emergency response units while minimizing the response times. In the proposed model, players represent the crisis events and the strategies correspond to possible allocations. The choice of strategies by each player impacts the decisions of the other players. The Nash equilibrium condition will correspond to the set of strategies chosen by all the players such that the resource allocation optimal for a given player also corresponds to the optimal allocations of the other players. The implementation of the Nash equilibrium condition is based on the Hansen's combinatorial theorem based approximation algorithm. The proposed solution has been implemented using C++ and experimental results are presented for various test cases. Further, metrics are developed for establishing the quality and fairness of the obtained results.

Dans l'objectif d'améliorer et d'automatiser la chaîne de reproductiond'objet qui va de l'acquisition à l'impression 3D. Nous avons cherché à caractériserde la saillance sur les objets 3D modélisés par la structure d'un maillage 3D.Pour cela, nous avons fait un état de l'art des méthodes d'estimation des proprié-tés différentielles, à savoir la normale et la courbure, sur des surfaces discrètes sousla forme de maillage 3D. Pour comparer le comportement des différentes méthodes,nous avons repris un ensemble de critères de comparaison classique dans le domaine,qui sont : la précision, la convergence et la robustesse par rapport aux variations duvoisinage. Pour cela, nous avons établi un protocole de tests mettant en avant cesqualités. De cette première comparaison, il est ressorti que l'ensemble des méthodesexistantes présentent des défauts selon ces différents critères. Afin d'avoir une estimationdes propriétés différentielles plus fiable et précise nous avons élaboré deuxnouveaux estimateurs. / With the aim to improve and automate the object reproduction chainfrom acquisition to 3D printing .We sought to characterize the salience on 3D objectsmodeled by a 3D mesh structure. For this, we have a state of the art of estimatingdifferential properties methods, namely normal and curvature on discrete surfaces inthe form of 3D mesh. To compare the behavior of different methods, we took a set ofclassic benchmarks in the domain, which are : accuracy, convergence and robustnesswith respect to variations of the neighbourhood. For this, we have established atest protocol emphasizing these qualities. From this first comparision, it was foundthat all the existing methods have shortcomings as these criteria. In order to havean estimation of the differential properties more reliable and accurate we developedtwo new estimators.