966 resultados para SLASHED HALF-NORMAL DISTRIBUTION
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The exposure to dust and polynuclear aromatic hydrocarbons (PAH) of 15 truck drivers from Geneva, Switzerland, was measured. The drivers were divided between "long-distance" drivers and "local" drivers and between smokers and nonsmokers and were compared with a control group of 6 office workers who were also divided into smokers and nonsmokers. Dust was measured on 1 workday both by a direct-reading instrument and by sampling. The local drivers showed higher exposure to dust (0.3 mg/m3) and PAH than the long-distance drivers (0.1 mg/m3), who showed no difference with the control group. This observation may be due to the fact that the local drivers spend more time in more polluted areas, such as streets with heavy traffic and construction sites, than do the long-distance drivers. Smoking does not influence exposure to dust and PAH of professional truck drivers, as measured in this study, probably because the ventilation rate of the truck cabins is relatively high even during cold days (11-15 r/h). The distribution of dust concentrations was shown in some cases to be quite different from the expected log-normal distribution. The contribution of diesel exhaust to these exposures could not be estimated since no specific tracer was used. However, the relatively low level of dust exposure dose not support the hypothesis that present day levels of diesel exhaust particulates play a significant role in the excess occurrence of lung cancer observed in professional truck drivers.
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Introducing and describing data and understanding the normal distribution.
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The preceding two editions of CoDaWork included talks on the possible considerationof densities as infinite compositions: Egozcue and D´ıaz-Barrero (2003) extended theEuclidean structure of the simplex to a Hilbert space structure of the set of densitieswithin a bounded interval, and van den Boogaart (2005) generalized this to the setof densities bounded by an arbitrary reference density. From the many variations ofthe Hilbert structures available, we work with three cases. For bounded variables, abasis derived from Legendre polynomials is used. For variables with a lower bound, westandardize them with respect to an exponential distribution and express their densitiesas coordinates in a basis derived from Laguerre polynomials. Finally, for unboundedvariables, a normal distribution is used as reference, and coordinates are obtained withrespect to a Hermite-polynomials-based basis.To get the coordinates, several approaches can be considered. A numerical accuracyproblem occurs if one estimates the coordinates directly by using discretized scalarproducts. Thus we propose to use a weighted linear regression approach, where all k-order polynomials are used as predictand variables and weights are proportional to thereference density. Finally, for the case of 2-order Hermite polinomials (normal reference)and 1-order Laguerre polinomials (exponential), one can also derive the coordinatesfrom their relationships to the classical mean and variance.Apart of these theoretical issues, this contribution focuses on the application of thistheory to two main problems in sedimentary geology: the comparison of several grainsize distributions, and the comparison among different rocks of the empirical distribution of a property measured on a batch of individual grains from the same rock orsediment, like their composition
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OBJECTIVE: Previous studies reported that the severity of cognitive deficits in euthymic patients with bipolar disorder (BD) increases with the duration of illness and postulated that progressive neuronal loss or shrinkage and white matter changes may be at the origin of this phenomenon. To explore this issue, the authors performed a case-control study including detailed neuropsychological and magnetic resonance imaging analyses in 17 euthymic elderly patients with BD and 17 healthy individuals. METHODS: Neuropsychological evaluation concerned working memory, episodic memory, processing speed, and executive functions. Volumetric estimates of the amygdala, hippocampus, entorhinal cortex, and anterior cingulate cortex were obtained using both voxel-based and region of interest morphometric methods. Periventricular and deep white matter were assessed semiquantitatively. Differences in cognitive performances and structural data between BD and comparison groups were analyzed using paired t-test or analysis of variance. Wilcoxon test was used in the absence of normal distribution. RESULTS: Compared with healthy individuals, patients with BD obtained significantly lower performances in processing speed, working memory, and episodic memory but not in executive functions. Morphometric analyses did not show significant volumetric or white matter differences between the two groups. CONCLUSIONS: Our results revealed impairment in verbal memory, working memory, and processing speed in euthymic older adults with BD. These cognitive deficits are comparable both in terms of affected functions and size effects to those previously reported in younger cohorts with BD. Both this observation and the absence of structural brain abnormalities in our cohort do not support a progressively evolving neurotoxic effect in BD.
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Aitchison and Bacon-Shone (1999) considered convex linear combinations ofcompositions. In other words, they investigated compositions of compositions, wherethe mixing composition follows a logistic Normal distribution (or a perturbationprocess) and the compositions being mixed follow a logistic Normal distribution. Inthis paper, I investigate the extension to situations where the mixing compositionvaries with a number of dimensions. Examples would be where the mixingproportions vary with time or distance or a combination of the two. Practicalsituations include a river where the mixing proportions vary along the river, or acrossa lake and possibly with a time trend. This is illustrated with a dataset similar to thatused in the Aitchison and Bacon-Shone paper, which looked at how pollution in aloch depended on the pollution in the three rivers that feed the loch. Here, I explicitlymodel the variation in the linear combination across the loch, assuming that the meanof the logistic Normal distribution depends on the river flows and relative distancefrom the source origins
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This study is part of an ongoing collaborative effort between the medical and the signal processing communities to promote research on applying standard Automatic Speech Recognition (ASR) techniques for the automatic diagnosis of patients with severe obstructive sleep apnoea (OSA). Early detection of severe apnoea cases is important so that patients can receive early treatment. Effective ASR-based detection could dramatically cut medical testing time. Working with a carefully designed speech database of healthy and apnoea subjects, we describe an acoustic search for distinctive apnoea voice characteristics. We also study abnormal nasalization in OSA patients by modelling vowels in nasal and nonnasal phonetic contexts using Gaussian Mixture Model (GMM) pattern recognition on speech spectra. Finally, we present experimental findings regarding the discriminative power of GMMs applied to severe apnoea detection. We have achieved an 81% correct classification rate, which is very promising and underpins the interest in this line of inquiry.
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Background. Determine the presence and evolution of indicators microorganisms of water pollution in “Conde del Guadalhorce” reservoir, Málaga city, Spain. A second objective was to analyze pollution degree and evaluate the sanitary quality of bathing water and compliance with European Directive 76/160/CE. Method. A total of 120 water samples were collected in two bathing freshwater sites during May to September sampling period between 2000 to 2005, and the numbers of total coliforms (CT), faecal coliforms (CF) and faecal streptococci (EF) were enumerated using the membrane filtration method. We used the log-normal distribution method and calculate the logarithmic means, percentile points, ratios CF:EF, ANOVA and Pearson correlations. Results. Only two samples overcome CF limit values at Camping sampling station during 2000 year. Ratios CF:EF values were higher (> 4) during 2000 to 2002, and lower (< 0,7) during 2003 to 2005. Significant differences (ANOVA F = 3,41, ∝ < 0,01) was only observed with EF during evaluated period. There was no significant difference between concentration means at bathing water sites (ANOVA, F = 3,395, ∝ < 0,01). The counts of CT and CF were significantly correlated in Kiosko water samples, while in Camping water, significant correlation (t = 0,632, p < 0,05) was only observed with EF at the Camping station during 2000, 2003 and 2005 years. Conclusions. “Conde del Guadalhorce” reservoir showed hygienic conditions for safety bathing. Globally, water bathing quality is good. CT, CF y EF indicators were agreed with UE Directive during 2000- 2005, with exception CF at Camping station in 2000 year. CT y CF concentrations at Camping were frecuently higher than Kiosko, it could be caused to swimmers abundance and recreational activities. There was a trend towards rising EF, it could be caused to faecal pollution source of animal origin, needed to research it.
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In a seminal paper, Aitchison and Lauder (1985) introduced classical kernel densityestimation techniques in the context of compositional data analysis. Indeed, they gavetwo options for the choice of the kernel to be used in the kernel estimator. One ofthese kernels is based on the use the alr transformation on the simplex SD jointly withthe normal distribution on RD-1. However, these authors themselves recognized thatthis method has some deficiencies. A method for overcoming these dificulties based onrecent developments for compositional data analysis and multivariate kernel estimationtheory, combining the ilr transformation with the use of the normal density with a fullbandwidth matrix, was recently proposed in Martín-Fernández, Chacón and Mateu-Figueras (2006). Here we present an extensive simulation study that compares bothmethods in practice, thus exploring the finite-sample behaviour of both estimators
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Autoantibodies to apolipoprotein/A-1 (anti-ApoA-1 IgG) have pro-atherogenic properties in patients at high cardiovascular risk, but its prevalence in patients with end-stage kidney disease is unknown. The aims of this single-center, cross-sectional study were to assess the prevalence of anti-ApoA-1 antibodies in patients on maintenance hemodialysis (MHD), and to examine its correlation with inflammatory biomarkers related to atherosclerotic plaque vulnerability and dialysis vintage. To this purpose, anti-ApoA-1 IgG levels and the concentrations of interleukin-6 (IL-6), interleukin-8 (IL-8), monocyte chemoattractant protein-1 (MCP-1), metalloproteinase-9 (MMP-9), tumor necrosis factor-α, and C-reactive protein (CRP) were assessed in the sera of 66 MHD patients (mean age: 68 ± 14 years, 36% women, 32% diabetics). Anti-ApoA-1 IgG positivity (defined as a blood value ≥ 97.5(th) percentile of the normal distribution as assessed in healthy blood donors) was 20%. Circulating levels of anti-ApoA-1 IgG correlated positively with dialysis vintage, but not with cardiovascular risk factors or previous cardiovascular events; no significant correlations were found between the anti-ApoA1 IgG levels and circulating levels of IL-6, IL-8, MCP-1, MMP-9, CRP, or low-density lipoprotein-cholesterol. In multivariable linear regression, adjusted for age and sex, only dialysis vintage remained positively and independently associated with anti-ApoA-1 titers (β = 0.05, 95% CI: 0.006; 0.28, P = 0.049). In conclusion, the prevalence of anti-ApoA-1 IgG is raised in the MHD-population, and positively associated with dialysis vintage, a major determinant of cardiovascular outcome. Whether antiApoA-1 antibodies play a role in the pathophysiology of accelerated atherosclerosis in the MHD-population merits further study.
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We study the damage enhanced creep rupture of disordered materials by means of a fiber bundle model. Broken fibers undergo a slow stress relaxation modeled by a Maxwell element whose stress exponent m can vary in a broad range. Under global load sharing we show that due to the strength disorder of fibers, the lifetime ʧ of the bundle has sample-to-sample fluctuations characterized by a log-normal distribution independent of the type of disorder. We determine the Monkman-Grant relation of the model and establish a relation between the rupture life tʄ and the characteristic time tm of the intermediate creep regime of the bundle where the minimum strain rate is reached, making possible reliable estimates of ʧ from short term measurements. Approaching macroscopic failure, the deformation rate has a finite time power law singularity whose exponent is a decreasing function of m. On the microlevel the distribution of waiting times is found to have a power law behavior with m-dependent exponents different below and above the critical load of the bundle. Approaching the critical load from above, the cutoff value of the distributions has a power law divergence whose exponent coincides with the stress exponent of Maxwell elements
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BACKGROUND: The goals of our study are to determine the most appropriate model for alcohol consumption as an exposure for burden of disease, to analyze the effect of the chosen alcohol consumption distribution on the estimation of the alcohol Population- Attributable Fractions (PAFs), and to characterize the chosen alcohol consumption distribution by exploring if there is a global relationship within the distribution. METHODS: To identify the best model, the Log-Normal, Gamma, and Weibull prevalence distributions were examined using data from 41 surveys from Gender, Alcohol and Culture: An International Study (GENACIS) and from the European Comparative Alcohol Study. To assess the effect of these distributions on the estimated alcohol PAFs, we calculated the alcohol PAF for diabetes, breast cancer, and pancreatitis using the three above-named distributions and using the more traditional approach based on categories. The relationship between the mean and the standard deviation from the Gamma distribution was estimated using data from 851 datasets for 66 countries from GENACIS and from the STEPwise approach to Surveillance from the World Health Organization. RESULTS: The Log-Normal distribution provided a poor fit for the survey data, with Gamma and Weibull distributions providing better fits. Additionally, our analyses showed that there were no marked differences for the alcohol PAF estimates based on the Gamma or Weibull distributions compared to PAFs based on categorical alcohol consumption estimates. The standard deviation of the alcohol distribution was highly dependent on the mean, with a unit increase in alcohol consumption associated with a unit increase in the mean of 1.258 (95% CI: 1.223 to 1.293) (R2 = 0.9207) for women and 1.171 (95% CI: 1.144 to 1.197) (R2 = 0. 9474) for men. CONCLUSIONS: Although the Gamma distribution and the Weibull distribution provided similar results, the Gamma distribution is recommended to model alcohol consumption from population surveys due to its fit, flexibility, and the ease with which it can be modified. The results showed that a large degree of variance of the standard deviation of the alcohol consumption Gamma distribution was explained by the mean alcohol consumption, allowing for alcohol consumption to be modeled through a Gamma distribution using only average consumption.
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La biomasa planctónica fluctuó entre 0,30 mL/m3 (Chimbote) y 1,90 mL/m3 (Paita), promedio 0,30 mL/m3; el 86% del volumen fue menor a 0,5 mL/m3. El fitoplancton fue abundante (70%) predominando diatomeas sobre dinoflagelados. Géneros de mayor importancia fueron Bacteriastrum, Planktoniella, Ditylum, Chaetoceros, Thalassiosira, Hemiaulus, Asteromphalus, Pleurosigma, Coscinodiscus, Guinardia, Leptocylindrus, Roperia, Eucampia y Prorocentrum. Los indicadores biológicos mostraron distribución normal, P. obtusum se registró entre Paita y Chimbote, dentro de las 20 mn hasta las 40 mn en Callao y Pisco. Ceratium incisum (ASS) solo fue encontrado frente a San Juan, fuera de las 180 mn.
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Los volúmenes de plancton presentaron un rango entre 0,008 y 5,251 mL.m-3 localizados frente a Punta La Negra y Salaverry, promedio 0,61 mL.m-3. El fitoplancton de red fue muy abundante y predominó en el 52% de las estaciones costeras conformado por especies de afloramiento. A 10 m de profundidad el fitoplancton registró una variación entre 69,32x103 cels.L-1 (San Juan) y 2.439,76x103 cels.L-1 (Chimbote), diversidad (H’) entre 0,05 bits.cel-1 (1 mn de Ilo) y 2,84 bits.cel-1 (7 mn de San Juan), y uniformidad entre 0,02 (Ilo) y 0,921 (San Juan). Las diatomeas Cerataulina pelagica y Chaetoceros spp. fueron las que aportaron las mayores densidades celulares en la zona costera. La distribución de los indicadores biológicos demostraron una relación con las condiciones ambientales, cuando Protoperidinium obtusum, indicador de Aguas Costeras Frías (ACF) se distribuyó desde Paita hasta Mollendo (30 mn), Ceratium breve, indicador de AES fue registrado de manera normal al norte de los 6°S asociado en algunas estaciones a Ceratium praelongum y C. incisum, indicadores de Aguas Subtropicales Superficiales (ASS).
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Leaf analysis is the chemical evaluation of the nutritional status where the nutrient concentrations found in the tissue reflect the nutritional status of the plants. Thus, a correct interpretation of the results of leaf analysis is fundamental for an effective use of this tool. The purpose of this study was to propose and compare the method of Fertilization Response Likelihood (FRL) for interpretation of leaf analysis with that of the Diagnosis and Recommendation Integrated System (DRIS). The database consisted of 157 analyses of the N, P, K, Ca, Mg, S, Cu, Fe, Mn, Zn, and B concentrations in coffee leaves, which were divided into two groups: low yield (< 30 bags ha-1) and high yield (> 30 bags ha-1). The DRIS indices were calculated using the method proposed by Jones (1981). The fertilization response likelihood was computed based on the approximation of normal distribution. It was found that the Fertilization Response Likelihood (FRL) allowed an evaluation of the nutritional status of coffee trees, coinciding with the DRIS-based diagnoses in 84.96 % of the crops.