RESUMO

Silver iodide is a prototype compound of superionic conductors that allows ions to flow through its structure. It exhibits a first-order phase transition at 420 K, characterized by an abrupt change in its ionic conductivity behavior, and above this temperature, its ionic conductivity increases by more than three orders of magnitude. Introducing small concentrations of carbon into the silver iodide structure produces a new material with a mixed conductivity (ionic and electronic) that increases with increasing temperature. In this work, we report the experimental results of the ionic conductivity as a function of the reciprocal temperature for the (AgI)x - C(1-x) mixture at low carbon concentrations (x = 0.99, 0.98, and 0.97). The ionic conductivity behavior as a function of reciprocal temperature was well fitted using a phenomenological model based on a random variable theory with a probability distribution function for the carriers. The experimental data show a proximity effect between the C and AgI phases. As a consequence of this proximity behavior, carbon concentration or temperature can control the conductivity of the (AgI)x - C(1-x) mixture.

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We propose a theoretical model to investigate the thermodynamics of single and coupled two-state ion channels, associated with mechanoelectrical transduction (MET) and hair cell biophysics. The modeling was based on the Tsallis nonextensive statistical mechanics. The choice for a nonextensive framework in modeling ion channels is encouraged on the fact that we take into account the presence of interactions or long-range correlations in the dynamics of single and coupled ion channels. However, the basic assumptions that support Boltzmann-Gibbs statistics, traditionally used to model ion channel dynamics, state that the system is formed by independent or weakly interacting elements. Despite being well studied in many biological systems, the literature has not yet addressed the study of both entropy and mutual information related to isolated or physically interacting pairs of MET channels. Inspired by hair cell biophysics, we show how the presence of nonextensivity, or subadditivity and superadditivity modulates the nonextensive entropy and mutual information as functions of stereocilia displacements. We also observe that the magnitude of the interaction between the two channels, given by a nonextensive parameter, influences the amplitude of the nonextensive joint entropy and mutual information as functions of the hair cell displacements. Finally, we show how nonextensivity regulates the current versus displacement curve for a single and a pair of interacting two-state channels. The present findings shed light on the thermodynamic process involved in the molecular mechanisms of the auditory system.

Assuntos

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A large set of variables is assessed for progeny selection in a plant-breeding program and other agronomic fields. The meta-analysis of the coefficient of variation (CVe) produces information for researchers and breeders on the experimental quality of trials. This analysis can also be applied in the decision-making process of the experimental plan regarding the experimental design, the number of repetitions, and the treatments and plants/progenies to be measured. In this study, we evaluated the dataset distribution and the descriptive statistics of CVe through the Frequentist and Bayesian approaches, aiming to establish the credibility and confidence intervals. We submitted CVe data of ten wheat (Triticum aestivum L.) traits reported in 1,068 articles published to the Bayesian and Frequentist analyses. Sample data were analyzed via Gamma and normal models. We selected the model with the lowest Akaike Information Criterion (AIC) value, and then we tested three link functions. In the Bayesian analysis, uniform distributions were used as non-informative priors for the Gamma distribution parameters with three ranges of q~U (a,b,). Thus, the prior probability density function was given by: [formula] The Bayesian and Frequentist approaches with the Gamma model presented similar results for CVe; however, the range Bayesian credible intervals was narrower than the Frequentist confidence intervals. Gamma distribution fitted the CVe data better than the normal distribution. The credible and confidence intervals of CVe were successfully applied to wheat traits and could be used as experimental accuracy measurements in other experiments.(AU)

Assuntos

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The COVID-19 pandemic has changed the way resources are consumed around the world. The relationship between the pandemic and water consumption has important implications for the management of water use and must be evaluated in depth. The main goal of this research paper is to establish a comparison between pre-pandemic and pandemic water consumption profiles for 14 social-housing buildings located in Joinville, Southern Brazil. Telemetry data from each apartment were collected on an hourly basis before and during the COVID-19 pandemic. The analysis was based on descriptive statistics on the hourly and daily water consumption in addition to its profile plots. The best probability distribution fitting was also determined. To assess the differences in water consumption due to de pandemic, the Wilcoxon-Mann-Whitney test was employed and a Generalized Linear Model with mixed effects was fitted to the data. The Lognormal distribution was shown to be the most appropriate to model the water consumption data. Due to the COVID-19 pandemic, the two daily peak consumption periods changed from 12 h to 15 h and from 19 h to 21 h. The COVID-19 pandemic also impacted daily water consumption, leading to a small, yet significant, increase in demand in the first quarter of the pandemic period.

RESUMO

This paper aims to find probabilities of extreme values of the air temperature for the Cerrado, Pantanal and Atlantic Forest biomes in Mato Grosso do Sul in Brazil. In this case a maximum likelihood estimation was employed for the probability distributions fitting the extreme monthly air temperatures for 2007-2018. Using the Extreme Value Theory approach this work estimates three probability distributions: the Generalized Distribution of Extreme Values (GEV), the Gumbel (GUM) and the Log-Normal (LN). The Kolmogorov-Smirnov test, the corrected Akaike criterion AIC c , the Bayesian information criterion BIC, the root of the mean square error RMSE and the determination coefficient R 2 were applied to measure the goodness-of-fit. The estimated distributions were used to calculate the probabilities of occurrence of maximum monthly air temperatures over 28-32 °C. Temperature predictions were done for the 2-, 5-, 10-, 30-, 50- and 100-year return periods. The GEV and GUM distributions are recommended to be used in the warmer months. In the coldest months, the LN distribution gave a better fit to a series of extreme air temperatures. Deforestation, combustion and extensive fires, and the related aerosol emissions contribute, alongside climate change, to the generation of extreme air temperatures in the studied biomes. Supplementary Information: The online version contains supplementary material available at 10.1007/s00477-022-02206-1.

RESUMO

Interactive movements of bees facilitate the division and organization of collective tasks, notably when they need to face internal or external environmental challenges. Here, we present a Bayesian and computational approach to track the movement of several honey bee, Apis mellifera, workers at colony level. We applied algorithms that combined tracking and Kernel Density Estimation (KDE), allowing measurements of entropy and Probability Distribution Function (PDF) of the motion of tracked organisms. We placed approximately 200 recently emerged and labeled bees inside an experimental colony, which consists of a mated queen, approximately 1000 bees, and a naturally occurring beehive background. Before release, labeled bees were fed for one hour with uncontaminated diets or diets containing a commercial mixture of synthetic fungicides (thiophanate-methyl and chlorothalonil). The colonies were filmed (12 min) at the 1st hour, 5th and 10th days after the bees' release. Our results revealed that the algorithm tracked the labeled bees with great accuracy. Pesticide-contaminated colonies showed anticipated collective activities in peripheral hive areas, far from the brood area, and exhibited reduced swarm entropy and energy values when compared to uncontaminated colonies. Collectively, our approach opens novel possibilities to quantify and predict potential alterations mediated by pollutants (e.g., pesticides) at the bee colony-level.

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Keystroke dynamics is a soft biometric trait. Although the shape of the timing distributions in keystroke dynamics profiles is a central element for the accurate modeling of the behavioral patterns of the user, a simplified approach has been to presuppose normality. Careful consideration of the individual shapes for the timing models could lead to improvements in the error rates of current methods or possibly inspire new ones. The main objective of this study is to compare several heavy-tailed and positively skewed candidate distributions in order to rank them according to their merit for fitting timing histograms in keystroke dynamics profiles. Results are summarized in three ways: counting how many times each candidate distribution provides the best fit and ranking them in order of success, measuring average information content, and ranking candidate distributions according to the frequency of hypothesis rejection with an Anderson-Darling goodness of fit test. Seven distributions with two parameters and seven with three were evaluated against three publicly available free-text keystroke dynamics datasets. The results confirm the established use in the research community of the log-normal distribution, in its two- and three-parameter variations, as excellent choices for modeling the shape of timings histograms in keystroke dynamics profiles. However, the log-logistic distribution emerges as a clear winner among all two- and three-parameter candidates, consistently surpassing the log-normal and all the rest under the three evaluation criteria for both hold and flight times.

RESUMO

The influence of the internal defects in the anchorages of cable-stayed bridges, generated either during the fabrication process or due to the usage time on their mechanical properties and failure probability is studied. Internal defects were distributed according to the probability density functions of types, sizes, quantities, and locations obtained from the experimental studies. The Finite Element Method (FEM) is applied to simulate the behaviour of the anchorages with and without internal defects under external forces, which affect the bridge, such as wind and traffic. It was shown that the mechanical properties of the anchorage without internal defects are in the range of its application, but in the case of an anchorage with internal defects, approximately 0.1% of the observed maximum stresses approximate the yield stress. The latter could result in permanent material deformation or fracture. The probability of failure of an anchorage is discussed.

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Large anthropogenic 14C datasets are widely used to generate summed probability distributions (SPDs) as a proxy for past human population levels. However, SPDs are a poor proxy when datasets are small, bearing little relationship to true population dynamics. Instead, more robust inferences can be achieved by directly modelling the population and assessing the model likelihood given the data. We introduce the R package ADMUR which uses a continuous piecewise linear (CPL) model of population change, calculates the model likelihood given a 14C dataset, estimates credible intervals using Markov chain Monte Carlo, applies a goodness-of-fit test, and uses the Schwarz Criterion to compare CPL models. We demonstrate the efficacy of this method using toy data, showing that spurious dynamics are avoided when sample sizes are small, and true population dynamics are recovered as sample sizes increase. Finally, we use an improved 14C dataset for the South American Arid Diagonal to compare CPL modelling to current simulation methods, and identify three Holocene phases when population trajectory estimates changed from rapid initial growth of 4.15% per generation to a decline of 0.05% per generation between 10 821 and 7055 yr BP, then gently grew at 0.58% per generation until 2500 yr BP. This article is part of the theme issue 'Cross-disciplinary approaches to prehistoric demography'.

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RESUMO

This paper presents wind speed and direction data measured with a weather station located in Puerto Bolivar, department of La Guajira, situated in the extreme north of Colombia, whose geographic coordinates are 12°11'N 71°55'W. A wind speed and direction sensor, a barometric pressure sensor, and a temperature sensor were used to obtain the presented data. These data were taken at the height of 10 m, which is the highest point of the weather station. The data taken by the meteorological station correspond to a period of 20 years (1993-2013), with hourly frequency. For the missing data, a mathematical model to estimate the Julian averages was developed, allowing to calculate the frequency histograms and four types of probability distributions for these data. Also, the representative wind roses were generated, taking into account the averages in each of the 12 months of the year.

RESUMO

The study of monthly rainfall probabilities is of great importance due to the increasing occurrences of extreme events in different regions of Brazil. However, the rainfall distribution at the southwest region of Paraná State, Brazil, is still unknown. Thus, the aim of this work is to assess the probabilistic distribution of rainfall frequency at Dois Vizinhos, in the southwest of Paraná State, Brazil. A probabilistic analysis was performed using a historic 40-year rainfall dataset (1973-2012). The gamma, Weibull, normal log, and normal probability distributions were compared. The distribution adherence was performed through Akaike Information Criterion, and the R statistical software was used for estimation. The results showed that the gamma and Weibull distributions were most suitable for probabilistic fitting. Based on this, the average annual rainfall for Dois Vizinhos (PR) was found to be 2,010.6 mm. Moreover, we found that throughout the year, October has the highest rainfall occurrence probability, with an 86% rainfall probability of above 150 mm and 64% rainfall probability above 200 mm.(AU)

O estudo de probabilidades mensais de precipitação pluvial torna-se importante em virtude do aumento de ocorrências de eventos extremos em diversas regiões do país. Entretanto, poucas informações são conhecidas a respeito da distribuição de chuva na região do sudoeste do Paraná. Com base no exposto objetivou-se por meio desta pesquisa analisar a distribuição probabilística mensal da precipitação pluvial na região de Dois Vizinhos, sudoeste do estado do Paraná. Analisou-se a série histórica de precipitação pluvial de 40 anos (1973-2012). Foram comparadas as seguintes distribuições de probabilidade: gama, Weibull, log normal e normal. A aderência das distribuições aos dados pluviométricos da região foi verificada através do critério de Akaike (AIC). As análises foram realizadas utilizando o software estatístico R. Por meio dos resultados observou-se que as distribuições de gama e Weibull foram as mais adequadas em termos de ajustes probabilísticos. Com base nas distribuições, a média anual de chuva na região de Dois Vizinhos é de 2.010,6 mm e o mês de outubro registra a maior probabilidade de ocorrência de precipitação, sendo 86% de probabilidade de chuvas acima de 150 mm e 64% acima de 200 mm.(AU)

Assuntos

RESUMO

The study of monthly rainfall probabilities is of great importance due to the increasing occurrences of extreme events in different regions of Brazil. However, the rainfall distribution at the southwest region of Paraná State, Brazil, is still unknown. Thus, the aim of this work is to assess the probabilistic distribution of rainfall frequency at Dois Vizinhos, in the southwest of Paraná State, Brazil. A probabilistic analysis was performed using a historic 40-year rainfall dataset (1973-2012). The gamma, Weibull, normal log, and normal probability distributions were compared. The distribution adherence was performed through Akaike Information Criterion, and the R statistical software was used for estimation. The results showed that the gamma and Weibull distributions were most suitable for probabilistic fitting. Based on this, the average annual rainfall for Dois Vizinhos (PR) was found to be 2,010.6 mm. Moreover, we found that throughout the year, October has the highest rainfall occurrence probability, with an 86% rainfall probability of above 150 mm and 64% rainfall probability above 200 mm.

O estudo de probabilidades mensais de precipitação pluvial torna-se importante em virtude do aumento de ocorrências de eventos extremos em diversas regiões do país. Entretanto, poucas informações são conhecidas a respeito da distribuição de chuva na região do sudoeste do Paraná. Com base no exposto objetivou-se por meio desta pesquisa analisar a distribuição probabilística mensal da precipitação pluvial na região de Dois Vizinhos, sudoeste do estado do Paraná. Analisou-se a série histórica de precipitação pluvial de 40 anos (1973-2012). Foram comparadas as seguintes distribuições de probabilidade: gama, Weibull, log normal e normal. A aderência das distribuições aos dados pluviométricos da região foi verificada através do critério de Akaike (AIC). As análises foram realizadas utilizando o software estatístico R. Por meio dos resultados observou-se que as distribuições de gama e Weibull foram as mais adequadas em termos de ajustes probabilísticos. Com base nas distribuições, a média anual de chuva na região de Dois Vizinhos é de 2.010,6 mm e o mês de outubro registra a maior probabilidade de ocorrência de precipitação, sendo 86% de probabilidade de chuvas acima de 150 mm e 64% acima de 200 mm.

Assuntos

RESUMO

The aim of this study was to identify soybean sowing dates on which there was low water surplus risk. The crop was raised on a Haplic Planosol soil in the Central Depression of Rio Grande do Sul, Brazil. Soybean development simulations and daily water balances were calculated for different sowing dates from August 1968 to July 2012. Water surplus data was subjected to BoxPlot analyses and Scott-Knott tests at a 5% error probability. Exponential, gamma, lognormal, normal and Weibull functions were tested and the best fits to the data were obtained for both subperiods and total cycle. The highest number of fits for the development cycle and subperiods were obtained using the gamma and weibull functions, respectively. For sowing carried out after November 1, there was a low water surplus risk in the sowing-emergence subperiod. The risk of water surplus during the development cycle decreased with the advance of the sowing date. (AU)

O objetivo deste trabalho foi identificar as datas de semeadura com menor risco de ocorrência de excesso hídrico para a cultura da soja, em um Planossolo Háplico na Depressão Central do Rio Grande do Sul. A simulação do desenvolvimento da soja e o balanço hídrico sequencial diário foram realizados para diferentes datas de semeadura em cada ano do período de agosto de 1968 a julho de 2012. Os dados dos dias de excesso hídrico, obtidos para o ciclo da cultura, foram submetidos à análise BoxPlot e teste de Scott-Knott a 5% de probabilidade de erro. Foram testadas as funções exponencial, gama, lognormal, normal e weibull, verificando-se a de melhor ajuste aos dados obtidos para os subperíodos e ciclo total. O maior número de ajustes para o ciclo de desenvolvimento e para os subperíodos foram obtidos para as funções gama e weibull, respectivamente. As semeaduras, realizadas após o dia primeiro de novembro, apresentam menor risco de ocorrência de excesso hídrico no subperíodo semeadura-emergência. O risco de ocorrência de excesso hídrico para o ciclo de desenvolvimento é decrescente, conforme o avanço da data de semeadura. (AU)

Assuntos

RESUMO

The aim of this study was to identify soybean sowing dates on which there was low water surplus risk. The crop was raised on a Haplic Planosol soil in the Central Depression of Rio Grande do Sul, Brazil. Soybean development simulations and daily water balances were calculated for different sowing dates from August 1968 to July 2012. Water surplus data was subjected to BoxPlot analyses and Scott-Knott tests at a 5% error probability. Exponential, gamma, lognormal, normal and Weibull functions were tested and the best fits to the data were obtained for both subperiods and total cycle. The highest number of fits for the development cycle and subperiods were obtained using the gamma and weibull functions, respectively. For sowing carried out after November 1, there was a low water surplus risk in the sowing-emergence subperiod. The risk of water surplus during the development cycle decreased with the advance of the sowing date.

O objetivo deste trabalho foi identificar as datas de semeadura com menor risco de ocorrência de excesso hídrico para a cultura da soja, em um Planossolo Háplico na Depressão Central do Rio Grande do Sul. A simulação do desenvolvimento da soja e o balanço hídrico sequencial diário foram realizados para diferentes datas de semeadura em cada ano do período de agosto de 1968 a julho de 2012. Os dados dos dias de excesso hídrico, obtidos para o ciclo da cultura, foram submetidos à análise BoxPlot e teste de Scott-Knott a 5% de probabilidade de erro. Foram testadas as funções exponencial, gama, lognormal, normal e weibull, verificando-se a de melhor ajuste aos dados obtidos para os subperíodos e ciclo total. O maior número de ajustes para o ciclo de desenvolvimento e para os subperíodos foram obtidos para as funções gama e weibull, respectivamente. As semeaduras, realizadas após o dia primeiro de novembro, apresentam menor risco de ocorrência de excesso hídrico no subperíodo semeadura-emergência. O risco de ocorrência de excesso hídrico para o ciclo de desenvolvimento é decrescente, conforme o avanço da data de semeadura.

Assuntos

RESUMO

ABSTRACT: The aim of this study was to identify soybean sowing dates on which there was low water surplus risk. The crop was raised on a Haplic Planosol soil in the Central Depression of Rio Grande do Sul, Brazil. Soybean development simulations and daily water balances were calculated for different sowing dates from August 1968 to July 2012. Water surplus data was subjected to BoxPlot analyses and Scott-Knott tests at a 5% error probability. Exponential, gamma, lognormal, normal and Weibull functions were tested and the best fits to the data were obtained for both subperiods and total cycle. The highest number of fits for the development cycle and subperiods were obtained using the gamma and weibull functions, respectively. For sowing carried out after November 1, there was a low water surplus risk in the sowing-emergence subperiod. The risk of water surplus during the development cycle decreased with the advance of the sowing date.

RESUMO: O objetivo deste trabalho foi identificar as datas de semeadura com menor risco de ocorrência de excesso hídrico para a cultura da soja, em um Planossolo Háplico na Depressão Central do Rio Grande do Sul. A simulação do desenvolvimento da soja e o balanço hídrico sequencial diário foram realizados para diferentes datas de semeadura em cada ano do período de agosto de 1968 a julho de 2012. Os dados dos dias de excesso hídrico, obtidos para o ciclo da cultura, foram submetidos à análise BoxPlot e teste de Scott-Knott a 5% de probabilidade de erro. Foram testadas as funções exponencial, gama, lognormal, normal e weibull, verificando-se a de melhor ajuste aos dados obtidos para os subperíodos e ciclo total. O maior número de ajustes para o ciclo de desenvolvimento e para os subperíodos foram obtidos para as funções gama e weibull, respectivamente. As semeaduras, realizadas após o dia primeiro de novembro, apresentam menor risco de ocorrência de excesso hídrico no subperíodo semeadura-emergência. O risco de ocorrência de excesso hídrico para o ciclo de desenvolvimento é decrescente, conforme o avanço da data de semeadura.

RESUMO

ABSTRACT: The aim of this study was to identify soybean sowing dates on which there was low water surplus risk. The crop was raised on a Haplic Planosol soil in the Central Depression of Rio Grande do Sul, Brazil. Soybean development simulations and daily water balances were calculated for different sowing dates from August 1968 to July 2012. Water surplus data was subjected to BoxPlot analyses and Scott-Knott tests at a 5% error probability. Exponential, gamma, lognormal, normal and Weibull functions were tested and the best fits to the data were obtained for both subperiods and total cycle. The highest number of fits for the development cycle and subperiods were obtained using the gamma and weibull functions, respectively. For sowing carried out after November 1, there was a low water surplus risk in the sowing-emergence subperiod. The risk of water surplus during the development cycle decreased with the advance of the sowing date.

RESUMO: O objetivo deste trabalho foi identificar as datas de semeadura com menor risco de ocorrência de excesso hídrico para a cultura da soja, em um Planossolo Háplico na Depressão Central do Rio Grande do Sul. A simulação do desenvolvimento da soja e o balanço hídrico sequencial diário foram realizados para diferentes datas de semeadura em cada ano do período de agosto de 1968 a julho de 2012. Os dados dos dias de excesso hídrico, obtidos para o ciclo da cultura, foram submetidos à análise BoxPlot e teste de Scott-Knott a 5% de probabilidade de erro. Foram testadas as funções exponencial, gama, lognormal, normal e weibull, verificando-se a de melhor ajuste aos dados obtidos para os subperíodos e ciclo total. O maior número de ajustes para o ciclo de desenvolvimento e para os subperíodos foram obtidos para as funções gama e weibull, respectivamente. As semeaduras, realizadas após o dia primeiro de novembro, apresentam menor risco de ocorrência de excesso hídrico no subperíodo semeadura-emergência. O risco de ocorrência de excesso hídrico para o ciclo de desenvolvimento é decrescente, conforme o avanço da data de semeadura.

RESUMO

Os objetivos deste estudo foram ajustar e selecionar funções de densidade probabilística que caracterizem a estrutura diamétrica desse fragmento e das espécies: Cedrela fissilis (Cedro), Luehea divaricata (Açoita Cavalo), Gochnatia polymorpha (Cambará), Sebastiania commersoniana (Branquilho) e Casearia sylvestris (Cafezeiro) de um fragmento de Floresta Ombrófila Mista com 15,24ha, localizado em Curitiba, Paraná. Para avaliar a distribuição diamétrica dessa floresta e das cinco espécies selecionadas, foram ajustadas sete funções probabilísticas para intervalos de classe de 5cm. Segundo os critérios de seleção adotados, o modelo que melhor representou a distribuição diamétrica para toda a floresta, o cedro, o cambará e o branquilho foi o de Weber; para o cafezeiro, a função Gamma (Adaptada) foi a mais eficiente e para o açoita cavalo nenhuma dessas funções foi aderente. O branquilho, o açoita cavalo, o cafezeiro e a floresta como um todo apresentaram distribuição em "J" invertido ou decrescente. Entretanto, o cedro e o cambará apresentaram distribuição tendendo à unimodalidade com forte assimetria à direita.

The objective of this study was to adjust and select probability density functions that characterize the diametric structure of this forest fragment and for the species: Cedrela fissilis, Luehea divaricata, Gochnatia polymorpha, Sebastiania commersoniana and Casearia sylvestris for a 15.24 hectare fragment of Mixed Ombrophylous Forest, located in Curitiba, State of Paraná. In order to evaluate the diametric distributions of this forest and the five selected species, seven probability functions were adjusted for 5cm class intervals. According to the criteria of selection adopted, the model that best represented the diametric distributions for the whole forest, Cedrela fissilis, Gochnatia polymorpha and Sebastiania commersoniana was the Weber model; for Casearia sylvestris, the Gamma function (adapted) was the most efficient, and for Luehea divaricata, none of these functions showed adherence. The Sebastiania commersoniana, Luehea divaricata, Casearia sylvestris and the forest as a whole showed inverted "J" or decreasing distribution, while, Cedrela fissilis and Gochnatia polymorpha showed an almost unimodal distribution with a strong asymmetry to the right.

RESUMO

The objective of this study was to adjust and select probability density functions that characterize the diametric structure of this forest fragment and for the species: Cedrela fissilis, Luehea divaricata, Gochnatia polymorpha, Sebastiania commersoniana and Casearia sylvestris for a 15.24 hectare fragment of Mixed Ombrophylous Forest, located in Curitiba, State of Paraná. In order to evaluate the diametric distributions of this forest and the five selected species, seven probability functions were adjusted for 5cm class intervals. According to the criteria of selection adopted, the model that best represented the diametric distributions for the whole forest, Cedrela fissilis, Gochnatia polymorpha and Sebastiania commersoniana was the Weber model; for Casearia sylvestris, the Gamma function (adapted) was the most efficient, and for Luehea divaricata, none of these functions showed adherence. The Sebastiania commersoniana, Luehea divaricata, Casearia sylvestris and the forest as a whole showed inverted "J" or decreasing distribution, while, Cedrela fissilis and Gochnatia polymorpha showed an almost unimodal distribution with a strong asymmetry to the right.

Os objetivos deste estudo foram ajustar e selecionar funções de densidade probabilística que caracterizem a estrutura diamétrica desse fragmento e das espécies: Cedrela fissilis (Cedro), Luehea divaricata (Açoita Cavalo), Gochnatia polymorpha (Cambará), Sebastiania commersoniana (Branquilho) e Casearia sylvestris (Cafezeiro) de um fragmento de Floresta Ombrófila Mista com 15,24ha, localizado em Curitiba, Paraná. Para avaliar a distribuição diamétrica dessa floresta e das cinco espécies selecionadas, foram ajustadas sete funções probabilísticas para intervalos de classe de 5cm. Segundo os critérios de seleção adotados, o modelo que melhor representou a distribuição diamétrica para toda a floresta, o cedro, o cambará e o branquilho foi o de Weber; para o cafezeiro, a função Gamma (Adaptada) foi a mais eficiente e para o açoita cavalo nenhuma dessas funções foi aderente. O branquilho, o açoita cavalo, o cafezeiro e a floresta como um todo apresentaram distribuição em "J" invertido ou decrescente. Entretanto, o cedro e o cambará apresentaram distribuição tendendo à unimodalidade com forte assimetria à direita.

RESUMO

The objective of this study was to adjust and select probability density functions that characterize the diametric structure of this forest fragment and for the species: Cedrela fissilis, Luehea divaricata, Gochnatia polymorpha, Sebastiania commersoniana and Casearia sylvestris for a 15.24 hectare fragment of Mixed Ombrophylous Forest, located in Curitiba, State of Paraná. In order to evaluate the diametric distributions of this forest and the five selected species, seven probability functions were adjusted for 5cm class intervals. According to the criteria of selection adopted, the model that best represented the diametric distributions for the whole forest, Cedrela fissilis, Gochnatia polymorpha and Sebastiania commersoniana was the Weber model; for Casearia sylvestris, the Gamma function (adapted) was the most efficient, and for Luehea divaricata, none of these functions showed adherence. The Sebastiania commersoniana, Luehea divaricata, Casearia sylvestris and the forest as a whole showed inverted "J" or decreasing distribution, while, Cedrela fissilis and Gochnatia polymorpha showed an almost unimodal distribution with a strong asymmetry to the right.

Os objetivos deste estudo foram ajustar e selecionar funções de densidade probabilística que caracterizem a estrutura diamétrica desse fragmento e das espécies: Cedrela fissilis (Cedro), Luehea divaricata (Açoita Cavalo), Gochnatia polymorpha (Cambará), Sebastiania commersoniana (Branquilho) e Casearia sylvestris (Cafezeiro) de um fragmento de Floresta Ombrófila Mista com 15,24ha, localizado em Curitiba, Paraná. Para avaliar a distribuição diamétrica dessa floresta e das cinco espécies selecionadas, foram ajustadas sete funções probabilísticas para intervalos de classe de 5cm. Segundo os critérios de seleção adotados, o modelo que melhor representou a distribuição diamétrica para toda a floresta, o cedro, o cambará e o branquilho foi o de Weber; para o cafezeiro, a função Gamma (Adaptada) foi a mais eficiente e para o açoita cavalo nenhuma dessas funções foi aderente. O branquilho, o açoita cavalo, o cafezeiro e a floresta como um todo apresentaram distribuição em "J" invertido ou decrescente. Entretanto, o cedro e o cambará apresentaram distribuição tendendo à unimodalidade com forte assimetria à direita.

RESUMO

Estudos probabilísticos envolvendo variáveis climáticas são de extrema importância para as atividades da agropecuária, construção civil, turismo, transporte, dentre outros. Visando contribuir para o planejamento da agricultura irrigada, este trabalho teve como objetivos comparar distribuições de probabilidade ajustadas às séries históricas decendiais e mensais, e estimar as precipitações prováveis para o município de Barbacena, MG. Foram estudados os meses de dezembro, janeiro e fevereiro, no período de 1942 a 2003, constituindo-se séries históricas com 62 anos de observações. As lâminas diárias foram totalizadas em períodos mensais e decendiais, sendo aplicadas as distribuições log-Normal 2 parâmetros, log-Normal 3 parâmetros e Gama. Para avaliar a adequabilidade das distribuições, nos períodos estudados, utilizou-se o teste de Qui-quadrado (chi2), ao nível de 5 por cento de significância. As precipitações prováveis foram estimadas para cada período estudado utilizando a distribuição que apresentou o menor valor de chi2, nos níveis de probabilidade de excedência de 75, 90 e 98 por cento. A distribuição Gama foi a que melhor se ajustou aos dados. O estudo de precipitações prováveis é uma boa ferramenta no auxílio da tomada de decisão quanto ao planejamento e uso da irrigação.

Probabilistic studies involving climatic variables are of extreme importance for farming activities, construction, tourism, among others. Seeking to contribute for the planning of irrigate agriculture, this work had as objectives to compare adjusted probability distribution models to the monthly and decennial historical series and to estimate the probable rainfall for the Barbacena County, Minas Gerais State, Brazil. Rainfall data of December, January and February, from 1942 to 2003, were studied, constituting historical series with 62 years of observations. Daily rainfall depths were added for 10 and 30 days, applying Gama, log-Normal 2 and log-Normal 3 parameters probability distribution models. Probability distributions models, were compared with Qui-square statistical test, at 5 percent significance level. Probable rainfall was estimated for each period, using the best distribution, which was evaluated based on the smallest Qui-square value, for the probability occurrence levels of 75, 90 and 98 percent. Gama probability distribution was the most adequate model.