Photonic signals are broadly exploited in communication and sensing and they typically exhibit Poisson-like statistics. In a common scenario where the intensity of the photonic signals is low and one needs to remove a nonstationary trend of the signals for any further analysis, one faces an obstacle: due to the dependence between the mean and variance typical for a Poisson-like process, information about the trend remains in the variance even after the trend has been subtracted, possibly yielding artifactual results in further analyses. Commonly available detrending or normalizing methods cannot cope with this issue. To alleviate this issue we developed a suitable pre-processing method for the signals that originate from a Poisson-like process. In this paper, a Poisson pre-processing method for nonstationary time series with Poisson distribution is developed and tested on computer-generated model data and experimental data of chemiluminescence from human neutrophils and mung seeds. The presented method transforms a nonstationary Poisson signal into a stationary signal with a Poisson distribution while preserving the type of photocount distribution and phase-space structure of the signal. The importance of the suggested pre-processing method is shown in Fano factor and Hurst exponent analysis of both computer-generated model signals and experimental photonic signals. It is demonstrated that our pre-processing method is superior to standard detrending-based methods whenever further signal analysis is sensitive to variance of the signal.

• MeSH
• fotony * MeSH
• lidé MeSH
• neutrofily metabolismus   MeSH
• počítačová simulace MeSH
• Poissonovo rozdělení * MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH

• Klíčová slova
• Arteknit Ra K,
• MeSH
• aorta chirurgie   MeSH
• biologické jevy MeSH
• cévy - implantace protéz MeSH
• experimenty na zvířatech MeSH
• fibrinogen MeSH
• polyestery MeSH
• psi MeSH
• thromboxan A2 MeSH
• vápník diagnostické užití   MeSH
• zvířata MeSH
• Check Tag
• psi MeSH
• zvířata MeSH

Five parameters of one of the most common neuronal models, the diffusion leaky integrate-and-fire model, also known as the Ornstein-Uhlenbeck neuronal model, were estimated on the basis of intracellular recording. These parameters can be classified into two categories. Three of them (the membrane time constant, the resting potential and the firing threshold) characterize the neuron itself. The remaining two characterize the neuronal input. The intracellular data were collected during spontaneous firing, which in this case is characterized by a Poisson process of interspike intervals. Two methods for the estimation were applied, the regression method and the maximum-likelihood method. Both methods permit to estimate the input parameters and the membrane time constant in a short time window (a single interspike interval). We found that, at least in our example, the regression method gave more consistent results than the maximum-likelihood method. The estimates of the input parameters show the asymptotical normality, which can be further used for statistical testing, under the condition that the data are collected in different experimental situations. The model neuron, as deduced from the determined parameters, works in a subthreshold regimen. This result was confirmed by both applied methods. The subthreshold regimen for this model is characterized by the Poissonian firing. This is in a complete agreement with the observed interspike interval data.

• MeSH
• akční potenciály fyziologie   MeSH
• buněčná membrána fyziologie   MeSH
• financování organizované MeSH
• lidé MeSH
• mozek fyziologie   MeSH
• nervové dráhy fyziologie   MeSH
• nervový přenos fyziologie   MeSH
• neuronové sítě MeSH
• neurony fyziologie   MeSH
• počítačové zpracování signálu MeSH
• Poissonovo rozdělení MeSH
• stochastické procesy MeSH
• synapse fyziologie   MeSH
• zvířata MeSH
• Check Tag
• lidé MeSH
• zvířata MeSH

In the Czech Hydrometeorological Institute (CHMI) there exists a unique set of meteorological measurements consisting of the values of vertical atmospheric levels of beta and gamma radiation. In this paper a stochastic data-driven model based on nonlinear regression and on nonhomogeneous Poisson process is suggested. In the first part of the paper, growth curves were used to establish an appropriate nonlinear regression model. For comparison we considered a nonhomogeneous Poisson process with its intensity based on growth curves. In the second part both approaches were applied to the real data and compared. Computational aspects are briefly discussed as well. The primary goal of this paper is to present an improved understanding of the distribution of environmental radiation as obtained from the measurements of the vertical radioactivity profiles by the radioactivity sonde system.

• MeSH
• atmosféra chemie   MeSH
• beta částice MeSH
• chemické modely MeSH
• monitorování radiace MeSH
• nelineární dynamika MeSH
• Poissonovo rozdělení MeSH
• regresní analýza MeSH
• záření gama MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Poisson׳s ratio of fibrous soft tissues is analyzed in this paper on the basis of constitutive models and experimental data. Three different up-to-date constitutive models accounting for the dispersion of fibre orientations are analyzed. Their predictions of the anisotropic Poisson׳s ratios are investigated under finite strain conditions together with the effects of specific orientation distribution functions and of other parameters. The applied constitutive models predict the tendency to lower (or even negative) out-of-plane Poisson׳s ratio. New experimental data of porcine arterial layer under uniaxial tension in orthogonal directions are also presented and compared with the theoretical predictions and other literature data. The results point out the typical features of recent constitutive models with fibres concentrated in circumferential-axial plane of arterial layers and their potential inconsistence with some experimental data. The volumetric (in)compressibility of arterial tissues is also discussed as an eventual and significant factor influencing this inconsistency.

• MeSH
• anizotropie MeSH
• arterie * MeSH
• biologické modely * MeSH
• biomechanika MeSH
• mechanické jevy * MeSH
• mechanický stres MeSH
• Poissonovo rozdělení MeSH
• Publikační typ
• časopisecké články MeSH

Leaky integrate-and-fire neuronal models with reversal potentials have a number of different diffusion approximations, each depending on the form of the amplitudes of the postsynaptic potentials. Probability distributions of the first-passage times of the membrane potential in the original model and its diffusion approximations are numerically compared in order to find which of the approximations is the most suitable one. The properties of the random amplitudes of postsynaptic potentials are discussed. It is shown on a simple example that the quality of the approximation depends directly on them.

• MeSH
• akční potenciály fyziologie   MeSH
• difuze MeSH
• lidé MeSH
• matematika MeSH
• membránové potenciály fyziologie   MeSH
• modely neurologické * MeSH
• neurony fyziologie   MeSH
• normální rozdělení MeSH
• počítačová simulace MeSH
• Poissonovo rozdělení MeSH
• pravděpodobnost MeSH
• stochastické procesy MeSH
• synaptické potenciály MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

The input of Stein's model of a single neuron is usually described by using a Poisson process, which is assumed to represent the behaviour of spikes pooled from a large number of presynaptic spike trains. However, such a description of the input is not always appropriate as the variability cannot be separated from the intensity. Therefore, we create and study Stein's model with a more general input, a sum of equilibrium renewal processes. The mean and variance of the membrane potential are derived for this model. Using these formulas and numerical simulations, the model is analyzed to study the influence of the input variability on the properties of the membrane potential and the output spike trains. The generalized Stein's model is compared with the original Stein's model with Poissonian input using the relative difference of variances of membrane potential at steady state and the integral square error of output interspike intervals. Both of the criteria show large differences between the models for input with high variability.

• MeSH
• lidé MeSH
• membránové potenciály fyziologie   MeSH
• modely neurologické * MeSH
• nervová síť fyziologie   MeSH
• neurony fyziologie   MeSH
• stochastické procesy MeSH
• zvířata MeSH
• Check Tag
• lidé MeSH
• zvířata MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Ectoparasites are an important factor in bat health due to emergent diseases and their associated threats to global public health. The diverse foraging habits of bats expose them to different surfaces which may influence ectoparasite infestations. In spite of these, most studies often overlook dietary specialisations when observing ectoparasite loads. The present paper quantitatively investigates whether foraging strategies as well as other host characteristics (sex, age, trunk and patagial area) influence ectoparasite (nycteribiids and mites) loads of bats. Ectoparasite counts and morphometric data were taken from mist net captures of bats. We then developed and compared models for modeling bat ectoparasite abundance under various distributions using generalised linear models. The negative binomial distribution consistently proved to be adequate for modeling mite, nycteribiid and total ectoparasite abundance based on information-theoretic approaches. Generally, females and frugivores had higher ectoparasite loads conditional on bat sex and diet, respectively. Contrary to nycteribiid abundance, mite abundance was positively related to patagial area. Thus, our findings suggest that dietary guild, sex and patagia of hosts (as well as age-nycteribiid abundance) are significant determinants of ectoparasite abundance.

• Klíčová slova
• patagium,
• MeSH
• binomické rozdělení MeSH
• Chiroptera * parazitologie   MeSH
• Diptera MeSH
• fyziologie výživy * MeSH
• kůže parazitologie   MeSH
• lineární modely MeSH
• parazitární zátěž MeSH
• Poissonovo rozdělení MeSH
• roztoči MeSH
• sexuální faktory MeSH
• statistika jako téma MeSH
• věkové faktory MeSH
• Publikační typ
• časopisecké články MeSH

The concentration of a drug in the circulatory system is studied under two different elimination strategies. The first strategy--geometric elimination--is the classical one which assumes a constant elimination rate per cycle. The second strategy--Poisson elimination--assumes that the elimination rate changes during the process of elimination. The problem studied here is to find a relationship between the residence-time distribution and the cycle-time distribution for a given rule of elimination. While the presented model gives this relationship in terms of Laplace-Stieltjes transform., the aim here is to determine the shapes of the corresponding probability density functions. From experimental data, we expect positively skewed, gamma-like distributions for the residence time of the drug in the body. Also, as some elimination parameter in the model approaches a limit, the exponential distribution often arises. Therefore, we use Laguerre series expansions, which yield a parsimonious approximation of positively skewed probability densities that are close to a gamma distribution. The coefficients in the expansion are determined by the central moments, which can be obtained from experimental data or as a consequence of theoretical assumptions. The examples presented show that gamma-like densities arise for a diverse set of cycle-time distribution and under both elimination rules.

• MeSH
• biologické modely * MeSH
• farmakokinetika * MeSH
• lidé MeSH
• matematika MeSH
• metabolická clearance MeSH
• stochastické procesy MeSH
• Check Tag
• lidé MeSH
• Publikační typ
• práce podpořená grantem MeSH

We propose a measure of the information rate of a single stationary neuronal activity with respect to the state of null information. The measure is based on the Kullback-Leibler distance between two interspike interval distributions. The selected activity is compared with the Poisson model with the same mean firing frequency. We show that the approach is related to the notion of specific information and that the method allows us to judge the relative encoding efficiency. Two classes of neuronal activity models are classified according to their information rate: the renewal process models and the first-order Markov chain models. It has been proven that information can be transmitted changing neither the spike rate nor the coefficient of variation and that the increase in serial correlation does not necessarily increase the information gain. We employ the simple, but powerful, Vasicek's estimator of differential entropy to illustrate an application on the experimental data coming from olfactory sensory neurons of rats.

• MeSH
• akční potenciály fyziologie   MeSH
• časové faktory MeSH
• entropie MeSH
• financování organizované MeSH
• Markovovy řetězce MeSH
• modely neurologické MeSH
• nervové dráhy fyziologie   MeSH
• neurony fyziologie   klasifikace   MeSH
• počítačové zpracování signálu MeSH
• zvířata MeSH
• Check Tag
• zvířata MeSH
• Publikační typ
• srovnávací studie MeSH