ESTIMATIVA E DISTRIBUIÇÃO DE PRECIPITAÇÕES DECENDIAIS PARA O ESTADO DO PARANÁ

ESTIMATIVA E DISTRIBUIÇÃO DE PRECIPITAÇÕES DECENDIAIS PARA O ESTADO DO PARANÁ Silvio César Sampaio; Manoel Moisés Ferreira de Queiroz; Elisandro Pires Frigo; Adair José Longo; Morgana SuszekSetor de Recursos Hídricos e Saneamento Ambiental (RHESA), Universidade Estadual do Oeste do Paraná, Cascavel, Paraná, [email protected] 1 RESUMO O objetivo deste trabalho foi estimar a precipitação provável com 75% de probabilidade nos períodos decendiais, a partir de dados diários de precipitação de 22 postos de medição, com um mínimo de 12 anos de observação, fazendo-se uso das distribuições Gama e Log-normal. Os testes Qui-quadrado e Kolmogorov-Smirnov, ambos com 5% de significância, foram utilizados para verificar a aderência das distribuições às condições pluviométricas decendiais do estado do Paraná. Os resultados mostraram que a distribuição Gama ajustou-se mais adequadamente às condições pluviométricas do estado nos períodos estudados. Os meses mais chuvosos são janeiro e fevereiro, enquanto os mais secos, são julho e agosto. O estado do Paraná apresenta aumento na quantidade de precipitação pluviométrica na direção litoral/oeste e norte/sul. UNITERMOS: probabilidades, chuva provável, distribuição Gama, distribuição log-normal. SAMPAIO, S.C.; QUEIROZ, M.M.F. de; FRIGO, E.P.; LONGO, A.J.; SUSZEK, M.DISTRIBUTION AND ESTIMATE OF PROBABLE 10-DAY PRECIPITATION INPARANÁSTATE 2 ABSTRACT The objective of this study was to estimate the probable 10-day precipitation, 75% probability, using daily rainfall data from 22 rain gauge sites, which had been collecting observation data for at least 12 years; Gamma and Log-normal distributions were used. Qui-square and Kolmogorov-Smirnov tests, at 5% significance, were utilized to verify distribution adherence to 10-day rainfall conditions in the state of Paraná. The results showed that Gamma distribution was more adequately adjusted to rainfall conditions in the studied periods than Log-normal distributions. January and February are the rainiest months whereas July and August are the driest ones. There is an increase in the east/west and north/south bound rainfall inParanastate. KEYWORDS: probabilities, probable rainfall, gamma distribution, log-normal distribution.

Download Full-text

Spike-timing pattern operates as gamma-distribution across cell types, regions and animal species and is essential for naturally-occurring cognitive states

10.1101/145813 ◽

2017 ◽

Cited By ~ 2

Author(s):

Meng Li ◽

Kun Xie ◽

Hui Kuang ◽

Jun Liu ◽

Deheng Wang ◽

...

Keyword(s):

Normal Distribution ◽

Gamma Distribution ◽

Animal Species ◽

Distribution Patterns ◽

Spike Timing ◽

Projection Neurons ◽

Cognitive States ◽

Timing Pattern ◽

Log Normal ◽

Log Normal Distribution

AbstractSpike-timing patterns - crucial for synaptic plasticity and neural computation - are often modeled as Poisson-like random processes, log-normal distribution or gamma-distribution patterns, each with different underlying assumptions that may or may not be biologically true. However, it is not entirely clear whether (and how well) these different models would or would not capture spike-timing statistical patterns across different neurons, regions, animal species and cognitive states. Here, we examine statistical patterns of spike-timing irregularity in 13 different cortical and subcortical regions from mouse, hamster, cat and monkey brains. In contrast to the widely-assumed Poisson or log-normal distribution patterns, we show that spike-timing patterns of various projection neurons-including cortical excitatory principal cells, hippocampal pyramidal cells, inhibitory striatal medium spiny neurons and dopaminergic neurons, as well as fast-spiking interneurons – all invariantly conform to the gamma-distribution model. While higher regularity in spike-timing patterns are observed in a few cases, such as mouse DA neurons and monkey motor cortical neurons, there is no clear tendency in increased firing regularity from the sensory and subcortical neurons to prefrontal or motor cortices, as previously entertained. Moreover, gamma shapes of spike-timing patterns remain robust over various natural cognitive states, such as sleep, awake periods, or during fearful episodic experiences. Interestingly, ketamine-induced general anesthesia or unconsciousness is associated with the breakdown of forebrain spike patterns from a singular gamma distribution into two distinct subtypes of gamma distributions, suggesting the importance of this spike-timing pattern in supporting natural cognitive states. These results suggest that gamma-distribution patterns of spike timing reflect not only a fundamental property conserved across different neurons, regions and animal species, but also an operation crucial for supporting natural cognitive states. Such gamma-distribution-based spike-timing patterns can also have important implications for real-time neural coding and realistic neuromorphic computing.

Download Full-text

A Universal Model for the Log-Normal Distribution of Elasticity in Polymeric Gels and Its Relevance to Mechanical Signature of Biological Tissues

Biology ◽

10.3390/biology10010064 ◽

2021 ◽

Vol 10 (1) ◽

pp. 64

Author(s):

Arnaud Millet

Keyword(s):

Elastic Modulus ◽

Normal Distribution ◽

Biological Tissues ◽

Force Microscopy ◽

Polymeric Gels ◽

Atomic Force ◽

Clear Explanation ◽

Log Normal ◽

Log Normal Distribution

The mechanosensitivity of cells has recently been identified as a process that could greatly influence a cell’s fate. To understand the interaction between cells and their surrounding extracellular matrix, the characterization of the mechanical properties of natural polymeric gels is needed. Atomic force microscopy (AFM) is one of the leading tools used to characterize mechanically biological tissues. It appears that the elasticity (elastic modulus) values obtained by AFM presents a log-normal distribution. Despite its ubiquity, the log-normal distribution concerning the elastic modulus of biological tissues does not have a clear explanation. In this paper, we propose a physical mechanism based on the weak universality of critical exponents in the percolation process leading to gelation. Following this, we discuss the relevance of this model for mechanical signatures of biological tissues.

Download Full-text