Factors determining the size frequency distribution of β-amyloid (Aβ) deposits in Alzheimer's disease

The size frequency distributions of discrete β-amyloid (Aβ) deposits were studied in single sections of the temporal lobe from patients with Alzheimer's disease. The size distributions were unimodal and positively skewed. In 18/25 (72%) tissues examined, a log normal distribution was a good fit to the data. This suggests that the abundances of deposit sizes are distributed randomly on a log scale about a mean value. Three hypotheses were proposed to account for the data: (1) sectioning in a single plane, (2) growth and disappearance of Aβ deposits, and (3) the origin of Aβ deposits from clusters of neuronal cell bodies. Size distributions obtained by serial reconstruction through the tissue were similar to those observed in single sections, which would not support the first hypothesis. The log normal distribution of Aβ deposit size suggests a model in which the rate of growth of a deposit is proportional to its volume. However, mean deposit size and the ratio of large to small deposits were not positively correlated with patient age or disease duration. The frequency distribution of Aβ deposits which were closely associated with 0, 1, 2, 3, or more neuronal cell bodies deviated significantly from a log normal distribution, which would not support the neuronal origin hypothesis. On the basis of the present data, growth and resolution of Aβ deposits would appear to be the most likely explanation for the log normal size distributions.

Income distribution dependence of poverty measure:a theoretical analysis

Using a modified deprivation (or poverty) function, in this paper, we theoretically study the changes in poverty with respect to the 'global' mean and variance of the income distribution using Indian survey data. We show that when the income obeys a log-normal distribution, a rising mean income generally indicates a reduction in poverty while an increase in the variance of the income distribution increases poverty. This altruistic view for a developing economy, however, is not tenable anymore once the poverty index is found to follow a pareto distribution. Here although a rising mean income indicates a reduction in poverty, due to the presence of an inflexion point in the poverty function, there is a critical value of the variance below which poverty decreases with increasing variance while beyond this value, poverty undergoes a steep increase followed by a decrease with respect to higher variance. Identifying this inflexion point as the poverty line, we show that the pareto poverty function satisfies all three standard axioms of a poverty index [N.C. Kakwani, Econometrica 43 (1980) 437; A.K. Sen, Econometrica 44 (1976) 219] whereas the log-normal distribution falls short of this requisite. Following these results, we make quantitative predictions to correlate a developing with a developed economy. © 2006 Elsevier B.V. All rights reserved.

Influence diagnostics for polyhazard models in the presence of covariates

In this paper, we present various diagnostic methods for polyhazard models. Polyhazard models are a flexible family for fitting lifetime data. Their main advantage over the single hazard models, such as the Weibull and the log-logistic models, is to include a large amount of nonmonotone hazard shapes, as bathtub and multimodal curves. Some influence methods, such as the local influence and total local influence of an individual are derived, analyzed and discussed. A discussion of the computation of the likelihood displacement as well as the normal curvature in the local influence method are presented. Finally, an example with real data is given for illustration.

Consumer populations and nutritional transition in Spain in the 20th century: a methodology for their reconstruction

One feature of the modern nutrition transition is the growing consumption of animal proteins. The most common approach in the quantitative analysis of this change used to be the study of averages of food consumption. But this kind of analysis seems to be incomplete without the knowledge of the number of consumers. Data about consumers are not usually published in historical statistics. This article introduces a methodological approach for reconstructing consumer populations. This methodology is based on some assumptions about the diffusion process of foodstuffs and the modeling of consumption patterns with a log-normal distribution. This estimating process is illustrated with the specific case of milk consumption in Spain between 1925 and 1981. These results fit quite well with other data and indirect sources available showing that this dietary change was a slow and late process. The reconstruction of consumer population could shed a new light in the study of nutritional transitions.

Occupational exposure of truck drivers to dust and polynuclear aromatic hydrocarbons: a pilot study in Geneva, Switzerland.

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.

Calidad microbiológica de las aguas de baño del embalse Conde del Guadalhorce, de Málaga (España), 2000-2005.

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.

Critical ruptures in a bundle of slowly relaxing fibers

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

Determining the best population-level alcohol consumption model and its impact on estimates of alcohol-attributable harms.

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.

Diversidade de formigas epigéicas (Hymenoptera, Formicidae) em dois ambientes no Centro-Oeste do Brasil

Diversidade de formigas epigéicas (Hymenoptera, Formicidae) em ambientes no Centro-Oeste do Brasil. Foi comparada, através do uso de índices de diversidade e modelos de abundância de espécies, a diversidade das comunidades de formigas epigéicas que ocorrem em duas estruturas vegetacionais diferentes: mata nativa e cultura de eucalipto. Para a captura das formigas foram utilizadas 800 armadilhas de solo do tipo pitfall, em oito amostras distintas. Um total de 85 espécies, distribuídas em 36 gêneros de sete subfamílias foram coletadas nos dois ambientes, sendo que destas, 83 ocorreram na mata nativa e 60 na cultura de eucalipto. A diversidade de espécies de formigas calculada pelo índice de Simpson não foi significativamente diferente entre os ambientes, ao contrário do resultado obtido a partir da aplicação do índice de Shannon, o qual indicou maior diversidade de espécies na mata nativa. O modelo log-series não se ajustou satisfatoriamente aos dados das comunidades de formigas encontradas na cultura de eucalipto e na mata nativa, mas o modelo log-normal mostrou-se adequado para descrever a estrutura das comunidades dos dois ambientes. O modelo broken-stick, que representa uma comunidade bem estruturada, ajustou-se apenas aos dados da mata nativa.

Size Effect and Notch Size Effect in Metal Fatigue

It is a well known phenomenon that the constant amplitude fatigue limit of a large component is lower than the fatigue limit of a small specimen made of the same material. In notched components the opposite occurs: the fatigue limit defined as the maximum stress at the notch is higher than that achieved with smooth specimens. These two effects have been taken into account in most design handbooks with the help of experimental formulas or design curves. The basic idea of this study is that the size effect can mainly be explained by the statistical size effect. A component subjected to an alternating load can be assumed to form a sample of initiated cracks at the end of the crack initiation phase. The size of the sample depends on the size of the specimen in question. The main objective of this study is to develop a statistical model for the estimation of this kind of size effect. It was shown that the size of a sample of initiated cracks shall be based on the stressed surface area of the specimen. In case of varying stress distribution, an effective stress area must be calculated. It is based on the decreasing probability of equally sized initiated cracks at lower stress level. If the distribution function of the parent population of cracks is known, the distribution of the maximum crack size in a sample can be defined. This makes it possible to calculate an estimate of the largest expected crack in any sample size. The estimate of the fatigue limit can now be calculated with the help of the linear elastic fracture mechanics. In notched components another source of size effect has to be taken into account. If we think about two specimens which have similar shape, but the size is different, it can be seen that the stress gradient in the smaller specimen is steeper. If there is an initiated crack in both of them, the stress intensity factor at the crack in the larger specimen is higher. The second goal of this thesis is to create a calculation method for this factor which is called the geometric size effect. The proposed method for the calculation of the geometric size effect is also based on the use of the linear elastic fracture mechanics. It is possible to calculate an accurate value of the stress intensity factor in a non linear stress field using weight functions. The calculated stress intensity factor values at the initiated crack can be compared to the corresponding stress intensity factor due to constant stress. The notch size effect is calculated as the ratio of these stress intensity factors. The presented methods were tested against experimental results taken from three German doctoral works. Two candidates for the parent population of initiated cracks were found: the Weibull distribution and the log normal distribution. Both of them can be used successfully for the prediction of the statistical size effect for smooth specimens. In case of notched components the geometric size effect due to the stress gradient shall be combined with the statistical size effect. The proposed method gives good results as long as the notch in question is blunt enough. For very sharp notches, stress concentration factor about 5 or higher, the method does not give sufficient results. It was shown that the plastic portion of the strain becomes quite high at the root of this kind of notches. The use of the linear elastic fracture mechanics becomes therefore questionable.

Monthly average temperature modelling

This research is associated with the goal of the horticultural sector of the Colombian southwest, which is to obtain climatic information, specifically, to predict the monthly average temperature in sites where it has not been measured. The data correspond to monthly average temperature, and were recorded in meteorological stations at Valle del Cauca, Colombia, South America. Two components are identified in the data of this research: (1) a component due to the temporal aspects, determined by characteristics of the time series, distribution of the monthly average temperature through the months and the temporal phenomena, which increased (El Nino) and decreased (La Nina) the temperature values, and (2) a component due to the sites, which is determined for the clear differentiation of two populations, the valley and the mountains, which are associated with the pattern of monthly average temperature and with the altitude. Finally, due to the closeness between meteorological stations it is possible to find spatial correlation between data from nearby sites. In the first instance a random coefficient model without spatial covariance structure in the errors is obtained by month and geographical location (mountains and valley, respectively). Models for wet periods in mountains show a normal distribution in the errors; models for the valley and dry periods in mountains do not exhibit a normal pattern in the errors. In models of mountains and wet periods, omni-directional weighted variograms for residuals show spatial continuity. The random coefficient model without spatial covariance structure in the errors and the random coefficient model with spatial covariance structure in the errors are capturing the influence of the El Nino and La Nina phenomena, which indicates that the inclusion of the random part in the model is appropriate. The altitude variable contributes significantly in the models for mountains. In general, the cross-validation process indicates that the random coefficient model with spatial spherical and the random coefficient model with spatial Gaussian are the best models for the wet periods in mountains, and the worst model is the model used by the Colombian Institute for Meteorology, Hydrology and Environmental Studies (IDEAM) to predict temperature.

Start-up rheometry of highly polydisperse magnetorheological fluids: experiments and simulations

An extensive experimental and simulation study is carried out in conventional magnetorheological fluids formulated by dispersion of mixtures of carbonyl iron particles having different sizes in Newtonian carriers. Apparent yield stress data are reported for a wide range of polydispersity indexes (PDI) from PDI = 1.63 to PDI = 3.31, which for a log-normal distribution corresponds to the standard deviation ranging from to . These results demonstrate that the effect of polydispersity is negligible in this range in spite of exhibiting very different microstructures. Experimental data in the magnetic saturation regime are in quantitative good agreement with particle-level simulations under the assumption of dipolar magnetostatic forces. The insensitivity of the yield stresses to the polydispersity can be understood from the interplay between the particle cluster size distribution and the packing density of particles inside the clusters.

Estimating Relative Risk Aversion, Risk-Neutral and Real-World Densities using Brazilian Real Currency Options

Building Risk-Neutral Densities (RND) from options data can provide market-implied expectations about the future behavior of a financial variable. And market expectations on financial variables may influence macroeconomic policy decisions. It can be useful also for corporate and financial institutions decision making. This paper uses the Liu et all (2007) approach to estimate the option-implied Risk-neutral densities from the Brazilian Real/US Dollar exchange rate distribution. We then compare the RND with actual exchange rates, on a monthly basis, in order to estimate the relative risk-aversion of investors and also obtain a Real-world density for the exchange rate. We are the first to calculate relative risk-aversion and the option-implied Real World Density for an emerging market currency. Our empirical application uses a sample of Brazilian Real/US Dollar options traded at BM&F-Bovespa from 1999 to 2011. The RND is estimated using a Mixture of Two Log-Normals distribution and then the real-world density is obtained by means of the Liu et al. (2007) parametric risktransformations. The relative risk aversion is calculated for the full sample. Our estimated value of the relative risk aversion parameter is around 2.7, which is in line with other articles that have estimated this parameter for the Brazilian Economy, such as Araújo (2005) and Issler and Piqueira (2000). Our out-of-sample evaluation results showed that the RND has some ability to forecast the Brazilian Real exchange rate. Abe et all (2007) found also mixed results in the out-of-sample analysis of the RND forecast ability for exchange rate options. However, when we incorporate the risk aversion into RND in order to obtain a Real-world density, the out-of-sample performance improves substantially, with satisfactory results in both Kolmogorov and Berkowitz tests. Therefore, we would suggest not using the “pure” RND, but rather taking into account risk aversion in order to forecast the Brazilian Real exchange rate.

Análise estatística de impedância da pele

In this work we analyze the skin bioimpedance statistical distribution. We focus on the study of two distinct samples: the statistics of impedance of several points in the skin of a single individual and the statistics over a population (many individuals) but in a single skin point. The impedance data was obtained from the literature (Pearson, 2007). Using the Shapiro-Wilk test and the assymmetry test we conclude that the impedance of a population is better described by an assymetric and non-normal distribution. On the other side, the data concerning the individual impedance seems to follow a normal distribution. We have performed a goodnes of fitting test and the better distribution to fit the data of a population is the log-normal distribution. It is interesting to note that our result for skin impedance is in simtony with body impedance from the literature of electrical engeneering. Our results have an impact over the statistical planning and modelling of skin impedance experiments. Special attention we should drive to the treatment of outliers in this kind of dataset. The results of this work are important in the general discussion of low impedance of points of acupuncture and also in the problem of skin biopotentials used in equipments like the Electrodermal Screen Tests.