925 resultados para Data clustering. Fuzzy C-Means. Cluster centers initialization. Validation indices
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Constructing a 3D surface model from sparse-point data is a nontrivial task. Here, we report an accurate and robust approach for reconstructing a surface model of the proximal femur from sparse-point data and a dense-point distribution model (DPDM). The problem is formulated as a three-stage optimal estimation process. The first stage, affine registration, is to iteratively estimate a scale and a rigid transformation between the mean surface model of the DPDM and the sparse input points. The estimation results of the first stage are used to establish point correspondences for the second stage, statistical instantiation, which stably instantiates a surface model from the DPDM using a statistical approach. This surface model is then fed to the third stage, kernel-based deformation, which further refines the surface model. Handling outliers is achieved by consistently employing the least trimmed squares (LTS) approach with a roughly estimated outlier rate in all three stages. If an optimal value of the outlier rate is preferred, we propose a hypothesis testing procedure to automatically estimate it. We present here our validations using four experiments, which include 1 leave-one-out experiment, 2 experiment on evaluating the present approach for handling pathology, 3 experiment on evaluating the present approach for handling outliers, and 4 experiment on reconstructing surface models of seven dry cadaver femurs using clinically relevant data without noise and with noise added. Our validation results demonstrate the robust performance of the present approach in handling outliers, pathology, and noise. An average 95-percentile error of 1.7-2.3 mm was found when the present approach was used to reconstruct surface models of the cadaver femurs from sparse-point data with noise added.
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In 1969, Lovasz asked whether every connected, vertex-transitive graph has a Hamilton path. This question has generated a considerable amount of interest, yet remains vastly open. To date, there exist no known connected, vertex-transitive graph that does not possess a Hamilton path. For the Cayley graphs, a subclass of vertex-transitive graphs, the following conjecture was made: Weak Lovász Conjecture: Every nontrivial, finite, connected Cayley graph is hamiltonian. The Chen-Quimpo Theorem proves that Cayley graphs on abelian groups flourish with Hamilton cycles, thus prompting Alspach to make the following conjecture: Alspach Conjecture: Every 2k-regular, connected Cayley graph on a finite abelian group has a Hamilton decomposition. Alspach’s conjecture is true for k = 1 and 2, but even the case k = 3 is still open. It is this case that this thesis addresses. Chapters 1–3 give introductory material and past work on the conjecture. Chapter 3 investigates the relationship between 6-regular Cayley graphs and associated quotient graphs. A proof of Alspach’s conjecture is given for the odd order case when k = 3. Chapter 4 provides a proof of the conjecture for even order graphs with 3-element connection sets that have an element generating a subgroup of index 2, and having a linear dependency among the other generators. Chapter 5 shows that if Γ = Cay(A, {s1, s2, s3}) is a connected, 6-regular, abelian Cayley graph of even order, and for some1 ≤ i ≤ 3, Δi = Cay(A/(si), {sj1 , sj2}) is 4-regular, and Δi ≄ Cay(ℤ3, {1, 1}), then Γ has a Hamilton decomposition. Alternatively stated, if Γ = Cay(A, S) is a connected, 6-regular, abelian Cayley graph of even order, then Γ has a Hamilton decomposition if S has no involutions, and for some s ∈ S, Cay(A/(s), S) is 4-regular, and of order at least 4. Finally, the Appendices give computational data resulting from C and MAGMA programs used to generate Hamilton decompositions of certain non-isomorphic Cayley graphs on low order abelian groups.
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Introduction: Slow conduction and ectopic activity are key elements of cardiac arrhythmogenesis. Both anomalies can be caused by myofibroblasts (MFBs) following establishment of heterocellular gap junctional coupling with cardiomyocytes. Because MFBs are characterized by the expression of {alpha}-smooth muscle actin ({alpha}-SMA) containing stress fibers, we investigated whether pharmacological interference with stress fiber formation might affect myofibroblast arrhythmogenicity. Methods: Experiments were done with patterned growth strands of neonatal rat ventricular cardiomyocytes coated with cardiac MFBs. Impulse propagation characteristics were measured optically using voltage sensitive dyes. Electrophysiological characteristics of single MFBs were assessed using patch clamp techniques. Actin polymerization was inhibited by latrunculin B (LtB). Data are given as mean±S.D. (n=5 to 22). Results: As assessed by immunocytochemistry, exposure of MFBs to LtB (0.3–10 µmol/L) profoundly disrupted stress fiber formation. This led, within minutes, to a dramatic change in cell morphology with MFBs assuming an astrocyte-like shape. In pure cardiomyocyte preparations, LtB had negligible effects on impulse conduction velocity ({theta}) and maximal action potential upstroke velocities (dV/dtmax). In contrast, LtB applied to MFB coated cardiomyocyte strands substantially increased {theta} from 247±32 to 371±26 mm/s and dV/dtmax from 40±7 to 81±1 %APA/ms, i.e., to values similar to those of pure cardiomyocyte strands (342±13 mm/s; 82±1 %APA/ms). Moreover, LtB at 1 µmol/L completely abolished MFB induced ectopic activity. LtB induced normalization of electrophysiologic parameters can be explained by the finding that LtB hyperpolarized MFBs from –25 mV to –50 mV, thus limiting their depolarizing effect on cardiomyocytes which was shown before to cause slow conduction and ectopic activity. Conclusions: Pharmacological interference with the cytoskeleton of cardiac MFBs alters their electrophysiological phenotype to such an extent that detrimental effects on cardiomyocyte electrophysiology are completely abolished. This observation might form a basis for the development of therapeutic strategies aimed at limiting the arrhythmogenic potential of MFBs.
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We present an algorithm for estimating dense image correspondences. Our versatile approach lends itself to various tasks typical for video post-processing, including image morphing, optical flow estimation, stereo rectification, disparity/depth reconstruction, and baseline adjustment. We incorporate recent advances in feature matching, energy minimization, stereo vision, and data clustering into our approach. At the core of our correspondence estimation we use Efficient Belief Propagation for energy minimization. While state-of-the-art algorithms only work on thumbnail-sized images, our novel feature downsampling scheme in combination with a simple, yet efficient data term compression, can cope with high-resolution data. The incorporation of SIFT (Scale-Invariant Feature Transform) features into data term computation further resolves matching ambiguities, making long-range correspondence estimation possible. We detect occluded areas by evaluating the correspondence symmetry, we further apply Geodesic matting to automatically determine plausible values in these regions.
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Background: Obesity is a growing problem in industrial nations. The aim of this study was to determine the relationship between the body mass index (BMI) and the pattern of injury after polytrauma. Methods: This retrospective study included 651 patients with an injury severity score (ISS) ≥16 and aged ≥16 years who were subdivided into three groups: BMI < 25 kg/m2, BMI 25–30 kg/m2, and BMI > 30 kg/m2. The Abbreviated Injury Scale (AIS) was used to quantify the injuries in the different anatomical regions. The Murray score was assessed at admission and at its maximum during hospitalization to evaluate pulmonary problems. Data are presented as means ± standard errors of the means. One way analysis of variance, χ2 test and Kruskal-Wallis test were used for the analyses and the significance level was set at p < 0.05. Results: The AIS of the thorax was 3.2 ± 0.1 in the BMI < 25 kg/m2 group, 3.3 ± 0.1 in the BMI 25–30 kg/m2 group, and 2.8 ± 0.2 in the BMI > 30 kg/m2 group; p < 0.05. The Murray score at admission increased significantly with increasing BMI (0.8 ± 0.8 for BMI < 25 kg/m2, 0.9 ± 0.9 for BMI 25–30 kg/m2, and 1.0 ± 0.8 for BMI > 30 kg/m2; p < 0.05) as was the maximum Murray score during hospitalization (1.2 ± 0.9 for BMI < 25 kg/m2, 1.6 ± 1.0 for BMI 25–30 kg/m2, and 1.5 ± 0.9 for BMI > 30 kg/m2; p < 0.001). The number of ventilator days was also elevated significantly with increasing BMI (5.9 ± 0.4 for BMI < 25 kg/m2, 7.7 ± 0.8 for BMI 25–30 kg/m2, and 7.9 ± 1.6 for BMI > 30 kg/m2; p < 0.05). Conclusion: Overweight and obesity lead to a higher incidence of thoracic trauma in a polytrauma situation and may additionally handicap ventilation in an obstructive manner.
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Biodiversity, a multidimensional property of natural systems, is difficult to quantify partly because of the multitude of indices proposed for this purpose. Indices aim to describe general properties of communities that allow us to compare different regions, taxa, and trophic levels. Therefore, they are of fundamental importance for environmental monitoring and conservation, although there is no consensus about which indices are more appropriate and informative. We tested several common diversity indices in a range of simple to complex statistical analyses in order to determine whether some were better suited for certain analyses than others. We used data collected around the focal plant Plantago lanceolata on 60 temperate grassland plots embedded in an agricultural landscape to explore relationships between the common diversity indices of species richness (S), Shannon's diversity (H'), Simpson's diversity (D-1), Simpson's dominance (D-2), Simpson's evenness (E), and Berger-Parker dominance (BP). We calculated each of these indices for herbaceous plants, arbuscular mycorrhizal fungi, aboveground arthropods, belowground insect larvae, and P.lanceolata molecular and chemical diversity. Including these trait-based measures of diversity allowed us to test whether or not they behaved similarly to the better studied species diversity. We used path analysis to determine whether compound indices detected more relationships between diversities of different organisms and traits than more basic indices. In the path models, more paths were significant when using H', even though all models except that with E were equally reliable. This demonstrates that while common diversity indices may appear interchangeable in simple analyses, when considering complex interactions, the choice of index can profoundly alter the interpretation of results. Data mining in order to identify the index producing the most significant results should be avoided, but simultaneously considering analyses using multiple indices can provide greater insight into the interactions in a system.
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BACKGROUND AND AIMS Inflammatory bowel disease (IBD) frequently manifests during childhood and adolescence. For providing and understanding a comprehensive picture of a patients' health status, health-related quality of life (HRQoL) instruments are an essential complement to clinical symptoms and functional limitations. Currently, the IMPACT-III questionnaire is one of the most frequently used disease-specific HRQoL instrument among patients with IBD. However, there is a lack of studies examining the validation and reliability of this instrument. METHODS 146 paediatric IBD patients from the multicenter Swiss IBD paediatric cohort study database were included in the study. Medical and laboratory data were extracted from the hospital records. HRQoL data were assessed by means of standardized questionnaires filled out by the patients in a face-to-face interview. RESULTS The original six IMPACT-III domain scales could not be replicated in the current sample. A principal component analysis with the extraction of four factor scores revealed the most robust solution. The four factors indicated good internal reliability (Cronbach's alpha=.64-.86), good concurrent validity measured by correlations with the generic KIDSCREEN-27 scales and excellent discriminant validity for the dimension of physical functioning measured by HRQoL differences for active and inactive severity groups (p<.001, d=1.04). CONCLUSIONS This study with Swiss children with IBD indicates good validity and reliability for the IMPACT-III questionnaire. However, our findings suggest a slightly different factor structure than originally proposed. The IMPACT-III questionnaire can be recommended for its use in clinical practice. The factor structure should be further examined in other samples.
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Improvements in the analysis of microarray images are critical for accurately quantifying gene expression levels. The acquisition of accurate spot intensities directly influences the results and interpretation of statistical analyses. This dissertation discusses the implementation of a novel approach to the analysis of cDNA microarray images. We use a stellar photometric model, the Moffat function, to quantify microarray spots from nylon microarray images. The inherent flexibility of the Moffat shape model makes it ideal for quantifying microarray spots. We apply our novel approach to a Wilms' tumor microarray study and compare our results with a fixed-circle segmentation approach for spot quantification. Our results suggest that different spot feature extraction methods can have an impact on the ability of statistical methods to identify differentially expressed genes. We also used the Moffat function to simulate a series of microarray images under various experimental conditions. These simulations were used to validate the performance of various statistical methods for identifying differentially expressed genes. Our simulation results indicate that tests taking into account the dependency between mean spot intensity and variance estimation, such as the smoothened t-test, can better identify differentially expressed genes, especially when the number of replicates and mean fold change are low. The analysis of the simulations also showed that overall, a rank sum test (Mann-Whitney) performed well at identifying differentially expressed genes. Previous work has suggested the strengths of nonparametric approaches for identifying differentially expressed genes. We also show that multivariate approaches, such as hierarchical and k-means cluster analysis along with principal components analysis, are only effective at classifying samples when replicate numbers and mean fold change are high. Finally, we show how our stellar shape model approach can be extended to the analysis of 2D-gel images by adapting the Moffat function to take into account the elliptical nature of spots in such images. Our results indicate that stellar shape models offer a previously unexplored approach for the quantification of 2D-gel spots. ^
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The rates of syphilis in the United States have increased since the all time low in 2000. In 2003, the rates of syphilis in the United States were 2.5 cases per 100,000. There were 178 reported cases of primary and secondary syphilis (8.9 cases per 100,000) in Houston, Texas, which was a 58.9% increase from 2002. While syphilis can be completely treated now, unlike in times past, it is still a public health concern. The purpose of this study is to examine the possibility of modeling the impact of an immune response in primary and secondary syphilis in 63 major cities across the United States, stratified by gender and racial-ethnic groups. A Fourier analysis will be performed by SAS. Subsequently, this study will compare the results to a similar study of syphilis in 68 US cities, that focused on immune response, however, did not stratified by race and gender. This study will help determine if the oscillating rates of syphilis are due to biological factors of the disease or to behavioral changes in the population. This study will use surveillance data from 63 major cities across the United States. The data will be provided by the Centers of Disease Control. Ultimately, this study will expand the knowledge of the effect of immunity on endemics.^
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This study retrospectively evaluated the spatial and temporal disease patterns associated with influenza-like illness (ILI), positive rapid influenza antigen detection tests (RIDT), and confirmed H1N1 S-OIV cases reported to the Cameron County Department of Health and Human Services between April 26 and May 13, 2009 using the space-time permutation scan statistic software SaTScan in conjunction with geographical information system (GIS) software ArcGIS 9.3. The rate and age-adjusted relative risk of each influenza measure was calculated and a cluster analysis was conducted to determine the geographic regions with statistically higher incidence of disease. A Poisson distribution model was developed to identify the effect that socioeconomic status, population density, and certain population attributes of a census block-group had on that area's frequency of S-OIV confirmed cases over the entire outbreak. Predominant among the spatiotemporal analyses of ILI, RIDT and S-OIV cases in Cameron County is the consistent pattern of a high concentration of cases along the southern border with Mexico. These findings in conjunction with the slight northward space-time shifts of ILI and RIDT cluster centers highlight the southern border as the primary site for public health interventions. Finally, the community-based multiple regression model revealed that three factors—percentage of the population under age 15, average household size, and the number of high school graduates over age 25—were significantly associated with laboratory-confirmed S-OIV in the Lower Rio Grande Valley. Together, these findings underscore the need for community-based surveillance, improve our understanding of the distribution of the burden of influenza within the community, and have implications for vaccination and community outreach initiatives.^
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Clostridium difficile is the leading definable cause of nosocomial diarrhea worldwide due to its virulence, multi-drug resistance, spore-forming ability, and environmental persistence. The incidence of C. difficile infection (CDI) has been increasing exponentially in the last decade. Virulent strains of C. difficile produce either toxin A and/or toxin B, which are essential for the pathogenesis of this bacterium. Current methods for diagnosing CDI are mostly qualitative tests that detect the bacterium, the toxins, or the toxin genes. These methods do not differentiate virulent C. difficile strains that produce active toxins from non-virulent strains that do not produce toxins or produce inactive toxins. Based on the knowledge that C. difficile toxins A and B cleave a substrate that is stereochemically similar to the native substrate of the toxins, uridine diphosphoglucose, a quantitative, cost-efficient assay, the Cdifftox activity assay, was developed to measure C. difficile toxin activity. The concept behind the activity assay was modified to develop a novel, rapid, sensitive, and specific assay for C. difficile toxins in the form of a selective and differential agar plate culture medium, the Cdifftox Plate assay (CDPA). This assay combines in a single step the specific identification of C. difficile strains and the detection of active toxin(s). The CDPA was determined to be extremely accurate (99.8% effective) at detecting toxin-producing strains based on the analysis of 528 C. difficile isolates selected from 50 tissue culture cytotoxicity assay-positive clinical stool samples. This new assay advances and improves the culture methodology in that only C. difficile strains will grow on this medium and virulent strains producing active toxins can be differentiated from non-virulent strains. This new method reduces the time and effort required to isolate and confirm toxin-producing C. difficile strains and provides a clinical isolate for antibiotic susceptibility testing and strain typing. The Cdifftox activity assay was used to screen for inhibitors of toxin activity. Physiological levels of the common human conjugated bile salt, taurocholate, was found to inhibit toxin A and B in vitro activities. When co-incubated ex vivo with purified toxin B, taurocholate protected Caco-2 colonic epithelial cells from the damaging effects of the toxin. Furthermore, using a caspase-3 detection assay, taurocholate reduced the extent of toxin B-induced Caco-2 cell apoptosis. These results suggest that bile salts can be effective in protecting the gut epithelium from C. difficile toxin damage, thus, the delivery of physiologic amounts of taurocholate to the colon, where it is normally in low concentration, could be useful in CDI treatment. These findings may help to explain why bile rich small intestine is spared damage in CDI, while the bile salt poor colon is vulnerable in CDI. Toxin synthesis in C. difficile occurs during the stationary phase, but little is known about the regulation of these toxins. It was hypothesized that C. difficile toxin synthesis is regulated by a quorum sensing mechanism. Two lines of evidence supported this hypothesis. First, a small (KDa), diffusible, heat-stable toxin-inducing activity accumulates in the medium of high-density C. difficile cells. This conditioned medium when incubated with low-density log-phase cells causes them to produce toxin early (2-4 hrs instead of 12-16 hrs) and at elevated levels when compared with cells grown in fresh medium. These data suggested that C. difficile cells extracellularly release an inducing molecule during growth that is able to activate toxin synthesis prematurely and demonstrates for the first time that toxin synthesis in C. difficile is regulated by quorum signaling. Second, this toxin-inducing activity was partially purified from high-density stationary-phase culture supernatant fluid by HPLC and confirmed to induce early toxin synthesis, even in C. difficile virulent strains that over-produce the toxins. Mass spectrometry analysis of the purified toxin-inducing fraction from HPLC revealed a cyclic compound with a mass of 655.8 Da. It is anticipated that identification of this toxin-inducing compound will advance our understanding of the mechanism involved in the quorum-dependent regulation of C. difficile toxin synthesis. This finding should lead to the development of even more sensitive tests to diagnose CDI and may lead to the discovery of promising novel therapeutic targets that could be harnessed for the treatment C. difficile infections.
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La disminución del agua destinada al uso agrícola, la salinización de los acuíferos subterráneos y el advenimiento de la tecnología de Sistemas de Información Geográfica (SIG) han posibilitado conocer la calidad de los sitios, fundamentalmente los riesgos de salinización de los suelos del oasis del río Mendoza-Argentina. El presente trabajo se fundamenta en dos estudios anteriores: uno de relevantamiento de suelos y el otro de análisis de calidad de aguas subterráneas. En el primero se efectúo la actualización del relevantamiento de suelos del río Mendoza usando SIG. El muestreo de suelos y los análisis físicos (textura) y químicos (salinidad, conductividad eléctrica) se realizaron en 1974. Los lugares de muestreo y sus atributos, graficados como cobertura de puntos, se extrapolaron a sus zonas de influencia convirtiéndolos en polígonos y posteriormente se rasterizaron. El segundo trabajo fue la digitalización y georreferenciación, también al sistema de coordenadas Universal Transverse Mercator (UTM), de los mapas de las curvas de isosalinidad. La salinidad está medida por la conductividad eléctrica específica del agua subterránea de los tres niveles de explotación que existen en la cuenca norte de Mendoza. El monitoreo se realizó en el período 1990/1991. Las isolíneas, posteriormente, fueron rasterizadas. Con los procesos de superposición y tabulación cruzada de los SIG se integraron las diversas "capas" de datos de suelos y calidades de aguas subterráneas y se generaron mapas temáticos que expresan la clasificación y localización regional de calidades del sitio, basado fundamentalmente en los riesgos de salinización de los suelos.