A new maximum likelihood method for luminosity calibrations

A new statistical parallax method using the Maximum Likelihood principle is presented, allowing the simultaneous determination of a luminosity calibration, kinematic characteristics and spatial distribution of a given sample. This method has been developed for the exploitation of the Hipparcos data and presents several improvements with respect to the previous ones: the effects of the selection of the sample, the observational errors, the galactic rotation and the interstellar absorption are taken into account as an intrinsic part of the formulation (as opposed to external corrections). Furthermore, the method is able to identify and characterize physically distinct groups in inhomogeneous samples, thus avoiding biases due to unidentified components. Moreover, the implementation used by the authors is based on the extensive use of numerical methods, so avoiding the need for simplification of the equations and thus the bias they could introduce. Several examples of application using simulated samples are presented, to be followed by applications to real samples in forthcoming articles.

Statistical analysis of maximum likelihood estimator images of human brain FDG PET studies

The work presented evaluates the statistical characteristics of regional bias and expected error in reconstructions of real positron emission tomography (PET) data of human brain fluoro-deoxiglucose (FDG) studies carried out by the maximum likelihood estimator (MLE) method with a robust stopping rule, and compares them with the results of filtered backprojection (FBP) reconstructions and with the method of sieves. The task of evaluating radioisotope uptake in regions-of-interest (ROIs) is investigated. An assessment of bias and variance in uptake measurements is carried out with simulated data. Then, by using three different transition matrices with different degrees of accuracy and a components of variance model for statistical analysis, it is shown that the characteristics obtained from real human FDG brain data are consistent with the results of the simulation studies.

Factors promoting the exposure to bioaerosols among crop workers

Introduction. Agricultural workers are among the professional groups most at risk of developing acute or chronic respiratory problems. Despite this fact, the etiology of these occupational diseases is poorly known, even in important sectors of agriculture such as the crops sector. Cereals can be colonized by a large number of fungal species throughout the plants' growth, but also during grain storage. Some of these fungi deliver toxins that can have a serious impact on human health when they are ingested via wheat products. Although International and European legislation on contaminants in food, including mycotoxins, include measures to ensure protection of public health by setting down the maximum levels for certain contaminants, the risks associated with the inhalation of such molecules during grain handling remains poorly documented. Goal of study. This project's objective was to characterize worker exposure to pathogenic, irritative or allergenic microorganisms and to identify the abiotic or biotic factors that reduce the growth of these microorganisms in crops. Indeed, the proliferation of microorganisms on wheat is dependent on temperature, rainfall and human disturbance (e.g. usage of tillage, addition of fungicides). A change in the concentration of these microorganisms in the substrate will directly result in a change in the concentration of aerosolized particles of the same microorganisms. Therefore, the exposure of worker to bioaérosols will also change. The Vaud region of Switzerland is a perfect region for conduct such a project as weather conditions vary and agricultural land management programs are divers at a small geographic scale. Methods. Bioaerosols and wheat dust have been sampled during wheat harvesting of summer 2010 at 100 sites uniformly distributed in the Vaud region that are representative of the different agriculture practices. Personal exposure has been evaluated for different wheat related activities: harvesting, grain unload, baling straw, the cleaning of harvesters and silos. Aerosols have been sampled at a rate of 2L/min between 15 min to 4 hours (t) on a 5m PVC filter for estimating the total dust inhaled, on gelatine filter for the identification and quantification of molds, and on a 0.45um polycarbonate filter for endotoxin quantification. Altitude, temperature and annual average rainfall were considered for each site. The physical and chemical characteristics of soils were determined using the methods in effect at Sol Council (Nyon). Total dust has been quantified following NIOSH 0500 method. Reactive endotoxine activity has been determined with Limulus Amebocyte Lysate Assay. All molds have been identified by the pyrosequencing of ITS2 amplicons generated from bioaerosol or wheat dust genomic DNA. Results & Conclusions. Our results confirm the previous quantitative data on the worker exposure to wheat dust. In addition, they show that crop workers are systematically exposed to complex mixtures of allergens, irritants or cytotoxic components. The novelty of our study is the systematic detection of molds such as Fusarium - that is a mycotoxins producer - in the bioaerosols. The results are interpreted by taking in account the agriculture practice, the Phosphorus : Carbon : Nitrogen ratio of the soil, the altitude and the average of rainy days per year.

A methodology for the classification of convective structures using meteorological radar: Application to heavy rainfall events on the Mediterranean coast of the Iberian Peninsula

During the period 1996-2000, forty-three heavy rainfall events have been detected in the Internal Basins of Catalonia (Northeastern of Spain). Most of these events caused floods and serious damage. This high number leads to the need for a methodology to classify them, on the basis of their surface rainfall distribution, their internal organization and their physical features. The aim of this paper is to show a methodology to analyze systematically the convective structures responsible of those heavy rainfall events on the basis of the information supplied by the meteorological radar. The proposed methodology is as follows. Firstly, the rainfall intensity and the surface rainfall pattern are analyzed on the basis of the raingauge data. Secondly, the convective structures at the lowest level are identified and characterized by using a 2-D algorithm, and the convective cells are identified by using a 3-D procedure that looks for the reflectivity cores in every radar volume. Thirdly, the convective cells (3-D) are associated with the 2-D structures (convective rainfall areas). This methodology has been applied to the 43 heavy rainfall events using the meteorological radar located near Barcelona and the SAIH automatic raingauge network.

Analysis of warm season thunderstorms using an object-oriented tracking method based on radar and total lightning data

Monitoring thunderstorms activity is an essential part of operational weather surveillance given their potential hazards, including lightning, hail, heavy rainfall, strong winds or even tornadoes. This study has two main objectives: firstly, the description of a methodology, based on radar and total lightning data to characterise thunderstorms in real-time; secondly, the application of this methodology to 66 thunderstorms that affected Catalonia (NE Spain) in the summer of 2006. An object-oriented tracking procedure is employed, where different observation data types generate four different types of objects (radar 1-km CAPPI reflectivity composites, radar reflectivity volumetric data, cloud-to-ground lightning data and intra-cloud lightning data). In the framework proposed, these objects are the building blocks of a higher level object, the thunderstorm. The methodology is demonstrated with a dataset of thunderstorms whose main characteristics, along the complete life cycle of the convective structures (development, maturity and dissipation), are described statistically. The development and dissipation stages present similar durations in most cases examined. On the contrary, the duration of the maturity phase is much more variable and related to the thunderstorm intensity, defined here in terms of lightning flash rate. Most of the activity of IC and CG flashes is registered in the maturity stage. In the development stage little CG flashes are observed (2% to 5%), while for the dissipation phase is possible to observe a few more CG flashes (10% to 15%). Additionally, a selection of thunderstorms is used to examine general life cycle patterns, obtained from the analysis of normalized (with respect to thunderstorm total duration and maximum value of variables considered) thunderstorm parameters. Among other findings, the study indicates that the normalized duration of the three stages of thunderstorm life cycle is similar in most thunderstorms, with the longest duration corresponding to the maturity stage (approximately 80% of the total time).

Predictive ability of severe rainfall events over Catalonia for the year 2008

This paper analyses the predictive ability of quantitative precipitation forecasts (QPF) and the so-called "poor-man" rainfall probabilistic forecasts (RPF). With this aim, the full set of warnings issued by the Meteorological Service of Catalonia (SMC) for potentially-dangerous events due to severe precipitation has been analysed for the year 2008. For each of the 37 warnings, the QPFs obtained from the limited-area model MM5 have been verified against hourly precipitation data provided by the rain gauge network covering Catalonia (NE of Spain), managed by SMC. For a group of five selected case studies, a QPF comparison has been undertaken between the MM5 and COSMO-I7 limited-area models. Although MM5's predictive ability has been examined for these five cases by making use of satellite data, this paper only shows in detail the heavy precipitation event on the 9¿10 May 2008. Finally, the "poor-man" rainfall probabilistic forecasts (RPF) issued by SMC at regional scale have also been tested against hourly precipitation observations. Verification results show that for long events (>24 h) MM5 tends to overestimate total precipitation, whereas for short events (¿24 h) the model tends instead to underestimate precipitation. The analysis of the five case studies concludes that most of MM5's QPF errors are mainly triggered by very poor representation of some of its cloud microphysical species, particularly the cloud liquid water and, to a lesser degree, the water vapor. The models' performance comparison demonstrates that MM5 and COSMO-I7 are on the same level of QPF skill, at least for the intense-rainfall events dealt with in the five case studies, whilst the warnings based on RPF issued by SMC have proven fairly correct when tested against hourly observed precipitation for 6-h intervals and at a small region scale. Throughout this study, we have only dealt with (SMC-issued) warning episodes in order to analyse deterministic (MM5 and COSMO-I7) and probabilistic (SMC) rainfall forecasts; therefore we have not taken into account those episodes that might (or might not) have been missed by the official SMC warnings. Therefore, whenever we talk about "misses", it is always in relation to the deterministic LAMs' QPFs.

Atributos químicos e físicos de um argissolo cultivado com Panicum maximum Jacq. cv. IPR-86 Milênio, sob lotação rotacionada e adubado com nitrogênio

A avaliação dos atributos químicos e físicos do solo é necessária em estudos que exploram intensivamente os sistemas de pastejo. No presente trabalho, objetivou-se avaliar as variações nos atributos físicos e químicos de um Argissolo cultivado com capim-milênio, sob pastejo, no intervalo compreendido entre outubro/2001 e maio/2002, no quinto ano de aplicação sucessiva das seguintes doses de N: 0, 150, 300 e 450 kg ha-1. Após os cinco anos de aplicação de 450 kg ha-1 de N, o teor de MO aumentou em 5 g dm-3, o que resultou em aumento da CTC. No período de outubro/2001 a maio/2002 houve diminuição nos valores de pH e de V com a aplicação de N. A densidade do solo variou pouco com a adubação nitrogenada; a percentagem de microporos aumentou e a de macroporos diminuiu na camada de 0-5 cm com o aumento das doses de N, mas a porosidade total permaneceu constante; e a resistência à penetração, quando o solo apresentava 90 g kg-1 de água, não foi afetada pelas doses de N e não foi restritiva ao crescimento das plantas.

The generalized index of maximum and minimum level and its application in decision making

[spa] El índice del máximo y el mínimo nivel es una técnica muy útil, especialmente para toma de decisiones, que usa la distancia de Hamming y el coeficiente de adecuación en el mismo problema. En este trabajo, se propone una generalización a través de utilizar medias generalizadas y cuasi aritméticas. A estos operadores de agregación, se les denominará el índice del máximo y el mínimo nivel medio ponderado ordenado generalizado (GOWAIMAM) y cuasi aritmético (Quasi-OWAIMAM). Estos nuevos operadores generalizan una amplia gama de casos particulares como el índice del máximo y el mínimo nivel generalizado (GIMAM), el OWAIMAM, y otros. También se desarrolla una aplicación en la toma de decisiones sobre selección de productos.

The generalized index of maximum and minimum level and its application in decision making

[spa] El índice del máximo y el mínimo nivel es una técnica muy útil, especialmente para toma de decisiones, que usa la distancia de Hamming y el coeficiente de adecuación en el mismo problema. En este trabajo, se propone una generalización a través de utilizar medias generalizadas y cuasi aritméticas. A estos operadores de agregación, se les denominará el índice del máximo y el mínimo nivel medio ponderado ordenado generalizado (GOWAIMAM) y cuasi aritmético (Quasi-OWAIMAM). Estos nuevos operadores generalizan una amplia gama de casos particulares como el índice del máximo y el mínimo nivel generalizado (GIMAM), el OWAIMAM, y otros. También se desarrolla una aplicación en la toma de decisiones sobre selección de productos.

Rainfall erosivity and rainfall return period in the experimental watershed of Aracruz, in the coastal plain of Espirito Santo, Brazil

Knowledge on the factors influencing water erosion is fundamental for the choice of the best land use practices. Rainfall, expressed by rainfall erosivity, is one of the most important factors of water erosion. The objective of this study was to determine rainfall erosivity and the return period of rainfall in the Coastal Plains region, near Aracruz, a town in the state of Espírito Santo, Brazil, based on available data. Rainfall erosivity was calculated based on historic rainfall data, collected from January 1998 to July 2004 at 5 min intervals, by automatic weather stations of the Aracruz Cellulose S.A company. A linear regression with individual rainfall and erosivity data was fit to obtain an equation that allowed data extrapolation to calculate individual erosivity for a 30-year period. Based on this data the annual average rainfall erosivity in Aracruz was 8,536 MJ mm ha-1 h-1 yr-1. Of the total annual rainfall erosivity 85 % was observed in the most critical period October to March. Annual erosive rains accounted for 38 % of the events causing erosion, although the runoff volume represented 88 % of the total. The annual average rainfall erosivity return period was estimated to be 3.4 years.

Mobility of inorganic and organic phosphorus forms under different levels of phosphate and poultry litter fertilization in soils

The eutrophication of aquifers is strongly linked to the mobility of P in soils. Although P mobility was considered irrelevant in a more distant past, more recent studies have shown that P, both in organic (Po) and inorganic forms (Pi), can be lost by leaching and eluviation through the soil profile, particularly in less weathered and/or sandier soils with low P adsorption capacity. The purpose of this study was to determine losses of P forms by leaching and eluviation from soil columns. Each column consisted of five PVC rings (diameter 5 cm, height 10 cm), filled with two soil types: a clayey Red-Yellow Latosol and a sandy loam Red-Yellow Latosol, which were exposed to water percolation. The soils were previously treated with four P rates (as KH2PO4 ) to reach 0, 12.5, 25.0 and 50 % of the maximum P adsorption capacity (MPAC). The P source was homogenized with the whole soil volume and incubated for 60 days. After this period the soils were placed in the columns; the soil of the top ring was mixed with five poultry litter rates of 0, 20, 40, 80, and 160 t ha-1 (dry weight basis). Treatments consisted of a 4 x 5 x 2 factorial scheme corresponding to four MPAC levels, five poultry litter rates, two soils, with three replications, arranged in a completely randomized block design. Deionized water was percolated through the columns 10 times in 35 days to simulate about 1,200 mm rainfall. In the leachate of each column the inorganic P (reactive P, Pi) and organic P forms (unreactive P, Po) were determined. At the end of the experiment, the columns were disassembled and P was extracted with the extractants Mehlich-1 (HCl 0.05 mol L-1 and H2SO4 0.0125 mol L-1) and Olsen (NaHCO3 0.5 mol L-1; pH 8.5) from the soil of each ring. The Pi and Po fractions were measured by the Olsen extractant. It was found that under higher poultry litter rates the losses of unreactive P (Po) were 6.4 times higher than of reactive P (Pi). Both the previous P fertilization and increasing poultry litter rates caused a vertical movement of P down the soil columns, as verified by P concentrations extracted by Mehlich-1 and NaHCO3 (Olsen). The environmental critical level (ECL), i.e., the P soil concentration above which P leaching increases exponentially, was 100 and 150 mg dm-3 by Mehlich-1 and 40 and 60 mg dm-3 by Olsen, for the sandy loam and clay soils, respectively. In highly weathered soils, where residual P is accumulated by successive crops, P leaching through the profile can be significant, particularly when poultry litter is applied as fertilizer.

Maximum mass of neutron stars

We determine the structure of neutron stars within a Brueckner-Hartree-Fock approach based on realistic nucleon-nucleon, nucleon-hyperon, and hyperon-hyperon interactions. Our results indicate rather low maximum masses below 1.4 solar masses. This feature is insensitive to the nucleonic part of the EOS due to a strong compensation mechanism caused by the appearance of hyperons and represents thus strong evidence for the presence of nonbaryonic "quark" matter in the interior of heavy stars.

Relations between soil surface roughness, tortuosity, tillage treatments, rainfall intensity and soil and water losses from a red yellow latosol

The soil surface roughness increases water retention and infiltration, reduces the runoff volume and speed and influences soil losses by water erosion. Similarly to other parameters, soil roughness is affected by the tillage system and rainfall volume. Based on these assumptions, the main purpose of this study was to evaluate the effect of tillage treatments on soil surface roughness (RR) and tortuosity (T) and to investigate the relationship with soil and water losses in a series of simulated rainfall events. The field study was carried out at the experimental station of EMBRAPA Southeastern Cattle Research Center in São Carlos (Fazenda Canchim), in São Paulo State, Brazil. Experimental plots of 33 m² were treated with two tillage practices in three replications, consisting of: untilled (no-tillage) soil (NTS) and conventionally tilled (plowing plus double disking) soil (CTS). Three successive simulated rain tests were applied in 24 h intervals. The three tests consisted of a first rain of 30 mm/h, a second of 30 mm/h and a third rain of 70 mm/h. Immediately after tilling and each rain simulation test, the surface roughness was measured, using a laser profile meter. The tillage treatments induced significant changes in soil surface roughness and tortuosity, demonstrating the importance of the tillage system for the physical surface conditions, favoring water retention and infiltration in the soil. The increase in surface roughness by the tillage treatments was considerably greater than its reduction by rain action. The surface roughness and tortuosity had more influence on the soil volume lost by surface runoff than in the conventional treatment. Possibly, other variables influenced soil and water losses from the no-tillage treatments, e.g., soil type, declivity, slope length, among others not analyzed in this study.

Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping

Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.