966 resultados para NUMBER OF ABDOMINAL SPOTS
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The abdominal compartment syndrome (ACS) is the result of various physiological alterations produced by an abnormal increase of the intra-abdominal pressure. Some of these patients will undergo a surgical procedure for its management. Methods: This is a retrospective case series of 28 patients with ACS who required surgical treatment at the Hospital Occidente de Kennedy between 1999 and 2003. We assessed retrospectively the behavior of McNelis’s equation for prediction of the development of the ACS. Results: The leading cause of ACS in our study was intraabadominal infection (n=6 21,4%). Time elapsed between diagnosis and surgical decompression was less than 4 hours in 75% (n=21) of the cases. The variables that improved significantly after the surgical decompression were CVP (T: 4,0 p: 0,0001), PIM (T: 2,7; p: 0,004), PIA (T1,8; p:0,034) and Urine Output (T:-2,4; p:0,02). The values of BUN, Creatinine and the cardiovascular instability did not show improvement. The ICU and hospital length of stay were 11 days (SD: 9) and 18 days (SD13) respectively. Global mortality was 67,9% (n=19) and mortality directly attributable to the syndrome was 30% (n=8). The behavior of the McNelis’s equation was erratic. Conclusions: The demographic characteristics as well as disease processes associated with ACS are consistent with the literature. The association between physiological variables and ACS is heterogeneous between patients. Mortality rates attributable to ACS in our institution are within the range described world-wide. The behavior of the McNelis’s equation seems to depend greatly upon fluid balance.
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L'increment de bases de dades que cada vegada contenen imatges més difícils i amb un nombre més elevat de categories, està forçant el desenvolupament de tècniques de representació d'imatges que siguin discriminatives quan es vol treballar amb múltiples classes i d'algorismes que siguin eficients en l'aprenentatge i classificació. Aquesta tesi explora el problema de classificar les imatges segons l'objecte que contenen quan es disposa d'un gran nombre de categories. Primerament s'investiga com un sistema híbrid format per un model generatiu i un model discriminatiu pot beneficiar la tasca de classificació d'imatges on el nivell d'anotació humà sigui mínim. Per aquesta tasca introduïm un nou vocabulari utilitzant una representació densa de descriptors color-SIFT, i desprès s'investiga com els diferents paràmetres afecten la classificació final. Tot seguit es proposa un mètode par tal d'incorporar informació espacial amb el sistema híbrid, mostrant que la informació de context es de gran ajuda per la classificació d'imatges. Desprès introduïm un nou descriptor de forma que representa la imatge segons la seva forma local i la seva forma espacial, tot junt amb un kernel que incorpora aquesta informació espacial en forma piramidal. La forma es representada per un vector compacte obtenint un descriptor molt adequat per ésser utilitzat amb algorismes d'aprenentatge amb kernels. Els experiments realitzats postren que aquesta informació de forma te uns resultats semblants (i a vegades millors) als descriptors basats en aparença. També s'investiga com diferents característiques es poden combinar per ésser utilitzades en la classificació d'imatges i es mostra com el descriptor de forma proposat juntament amb un descriptor d'aparença millora substancialment la classificació. Finalment es descriu un algoritme que detecta les regions d'interès automàticament durant l'entrenament i la classificació. Això proporciona un mètode per inhibir el fons de la imatge i afegeix invariança a la posició dels objectes dins les imatges. S'ensenya que la forma i l'aparença sobre aquesta regió d'interès i utilitzant els classificadors random forests millora la classificació i el temps computacional. Es comparen els postres resultats amb resultats de la literatura utilitzant les mateixes bases de dades que els autors Aixa com els mateixos protocols d'aprenentatge i classificació. Es veu com totes les innovacions introduïdes incrementen la classificació final de les imatges.
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Predation by house cats (Felis catus) is one of the largest human-related sources of mortality for wild birds in the United States and elsewhere, and has been implicated in extinctions and population declines of several species. However, relatively little is known about this topic in Canada. The objectives of this study were to provide plausible estimates for the number of birds killed by house cats in Canada, identify information that would help improve those estimates, and identify species potentially vulnerable to population impacts. In total, cats are estimated to kill between 100 and 350 million birds per year in Canada (> 95% of estimates were in this range), with the majority likely to be killed by feral cats. This range of estimates is based on surveys indicating that Canadians own about 8.5 million pet cats, a rough approximation of 1.4 to 4.2 million feral cats, and literature values of predation rates from studies conducted elsewhere. Reliability of the total kill estimate would be improved most by better knowledge of feral cat numbers and diet in Canada, though any data on birds killed by cats in Canada would be helpful. These estimates suggest that 2-7% of birds in southern Canada are killed by cats per year. Even at the low end, predation by house cats is probably the largest human-related source of bird mortality in Canada. Many species of birds are potentially vulnerable to at least local population impacts in southern Canada, by virtue of nesting or feeding on or near ground level, and habitat choices that bring them into contact with human-dominated landscapes where cats are abundant. Because cat predation is likely to remain a primary source of bird mortality in Canada for some time, this issue needs more scientific attention in Canada.
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None of the current surveillance streams monitoring the presence of scrapie in Great Britain provide a comprehensive and unbiased estimate of the prevalence of the disease at the holding level. Previous work to estimate the under-ascertainment adjusted prevalence of scrapie in Great Britain applied multiple-list capture–recapture methods. The enforcement of new control measures on scrapie-affected holdings in 2004 has stopped the overlapping between surveillance sources and, hence, the application of multiple-list capture–recapture models. Alternative methods, still under the capture–recapture methodology, relying on repeated entries in one single list have been suggested in these situations. In this article, we apply one-list capture–recapture approaches to data held on the Scrapie Notifications Database to estimate the undetected population of scrapie-affected holdings with clinical disease in Great Britain for the years 2002, 2003, and 2004. For doing so, we develop a new diagnostic tool for indication of heterogeneity as well as a new understanding of the Zelterman and Chao’s lower bound estimators to account for potential unobserved heterogeneity. We demonstrate that the Zelterman estimator can be viewed as a maximum likelihood estimator for a special, locally truncated Poisson likelihood equivalent to a binomial likelihood. This understanding allows the extension of the Zelterman approach by means of logistic regression to include observed heterogeneity in the form of covariates—in case studied here, the holding size and country of origin. Our results confirm the presence of substantial unobserved heterogeneity supporting the application of our two estimators. The total scrapie-affected holding population in Great Britain is around 300 holdings per year. None of the covariates appear to inform the model significantly.
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Field experiments were carried out to assess the effects of nitrogen fertilization and seed rate on the Hagberg falling number (HFN) of commercial wheat hybrids and their parents. Applying nitrogen (200 kg N ha(-1)) increased HFN in two successive years. The HFN of the hybrid Hyno Esta was lower than either of its parents (Estica and Audace), particularly when nitrogen was not applied. Treatment effects on HFN were negatively associated with a-amylase activity. Phadebas grain blotting suggested two populations of grains with different types of a-amylase activity: Estica appeared to have a high proportion of grains with low levels of late maturity endosperm a-amylase activity (LMEA); Audace had a few grains showing high levels of germination amylase; and the hybrid, Hyno Esta, combined the sources from both parents to show heterosis for a-amylase activity. Applying nitrogen reduced both apparent LMEA and germination amylase. The effects on LMEA were associated with the size and disruption of the grain cavity, which was greater in Hyno Esta and Estica and in zero-nitrogen treatments. External grain morphology failed to explain much of the variation in LMEA and cavity size, but there was a close negative correlation between cavity size and protein content. Applying nitrogen increased post-harvest dormancy of the grain. Dormancy was greatest in Estica and least in Audace. It is proposed that effects of seed rate, genotype and nitrogen fertilizer on HFN are mediated through factors affecting the size and disruption of the grain cavity and therefore LMEA, and through factors affecting dormancy and therefore germination amylase. (c) 2004 Society of Chemical Industry.
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This paper reviews Bayesian procedures for phase 1 dose-escalation studies and compares different dose schedules and cohort sizes. The methodology described is motivated by the situation of phase 1 dose-escalation studiesin oncology, that is, a single dose administered to each patient, with a single binary response ("toxicity"' or "no toxicity") observed. It is likely that a wider range of applications of the methodology is possible. In this paper, results from 10000-fold simulation runs conducted using the software package Bayesian ADEPT are presented. Four designs were compared under six scenarios. The simulation results indicate that there are slight advantages of having more dose levels and smaller cohort sizes.
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None of the current surveillance streams monitoring the presence of scrapie in Great Britain provide a comprehensive and unbiased estimate of the prevalence of the disease at the holding level. Previous work to estimate the under-ascertainment adjusted prevalence of scrapie in Great Britain applied multiple-list capture-recapture methods. The enforcement of new control measures on scrapie-affected holdings in 2004 has stopped the overlapping between surveillance sources and, hence, the application of multiple-list capture-recapture models. Alternative methods, still under the capture-recapture methodology, relying on repeated entries in one single list have been suggested in these situations. In this article, we apply one-list capture-recapture approaches to data held on the Scrapie Notifications Database to estimate the undetected population of scrapie-affected holdings with clinical disease in Great Britain for the years 2002, 2003, and 2004. For doing so, we develop a new diagnostic tool for indication of heterogeneity as well as a new understanding of the Zelterman and Chao's lower bound estimators to account for potential unobserved heterogeneity. We demonstrate that the Zelterman estimator can be viewed as a maximum likelihood estimator for a special, locally truncated Poisson likelihood equivalent to a binomial likelihood. This understanding allows the extension of the Zelterman approach by means of logistic regression to include observed heterogeneity in the form of covariates-in case studied here, the holding size and country of origin. Our results confirm the presence of substantial unobserved heterogeneity supporting the application of our two estimators. The total scrapie-affected holding population in Great Britain is around 300 holdings per year. None of the covariates appear to inform the model significantly.
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Background: Severe malarial anaemia is a major complication of malaria infection and is multifactorial resulting from loss of circulating red blood cells (RBCs) from parasite replication, as well as immune-mediated mechanisms. An understanding of the causes of severe malarial anaemia is necessary to develop and implement new therapeutic strategies to tackle this syndrome of malaria infection. Methods: Using analysis of variance, this work investigated whether parasite-destruction of RBCs always accounts for the severity of malarial anaemia during infections of the rodent malaria model Plasmodium chabaudi in mice of a BALB/c background. Differences in anaemia between two different clones of P. chabaudi were also examined. Results: Circulating parasite numbers were not correlated with the severity of anaemia in either BALB/c mice or under more severe conditions of anaemia in BALB/c RAG2 deficient mice (lacking T and B cells). Mice infected with P. chabaudi clone CB suffered more severe anaemia than mice infected with clone AS, but this was not correlated with the number of parasites in the circulation. Instead, the peak percentage of parasitized RBCs was higher in CB-infected animals than in AS-infected animals, and was correlated with the severity of anaemia, suggesting that the availability of uninfected RBCs was impaired in CB-infected animals. Conclusion: This work shows that parasite numbers are a more relevant measure of parasite levels in P. chabaudi infection than % parasitaemia, a measure that does not take anaemia into account. The lack of correlation between parasite numbers and the drop in circulating RBCs in this experimental model of malaria support a role for the host response in the impairment or destruction of uninfected RBC in P. chabaudi infections, and thus development of acute anaemia in this malaria model.
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This paper describes a method for reconstructing 3D frontier points, contour generators and surfaces of anatomical objects or smooth surfaces from a small number, e. g. 10, of conventional 2D X-ray images. The X-ray images are taken at different viewing directions with full prior knowledge of the X-ray source and sensor configurations. Unlike previous works, we empirically demonstrate that if the viewing directions are uniformly distributed around the object's viewing sphere, then the reconstructed 3D points automatically cluster closely on a highly curved part of the surface and are widely spread on smooth or flat parts. The advantage of this property is that the reconstructed points along a surface or a contour generator are not under-sampled or under-represented because surfaces or contours should be sampled or represented with more densely points where their curvatures are high. The more complex the contour's shape, the greater is the number of points required, but the greater the number of points is automatically generated by the proposed method. Given that the number of viewing directions is fixed and the viewing directions are uniformly distributed, the number and distribution of the reconstructed points depend on the shape or the curvature of the surface regardless of the size of the surface or the size of the object. The technique may be used not only in medicine but also in industrial applications.
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The low-energy electron diffraction (LEED) pattern of the step-kinked Pt{531} surface at 200 K shows energy-dependent cancellation of diffraction spots over unusually large energy ranges, up to 100 eV. This cannot be reproduced theoretically when a flat surface geometry is assumed. A relatively simple model of roughening, however, involving 0.25 ML of vacancies and adatoms leads to very good agreement with the experiment. The cancellation of intensities within a very narrow range of adatom or vacancy coverages is caused by the interference of electrons emerging from different heights but similar local environments. This is a rare example where the energy dependence of integrated LEED spot intensities is dramatically affected by the long-range arrangement of atoms.