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PubMed1998

The recursive deterministic perceptron neural network.

We introduce a feedforward multilayer neural network which is a generalization of the single layer perceptron topology (SLPT), called recursive deterministic perceptron (RDP). This new model is capable of solving any two-class classification problem, as opposed to the single layer perceptron which can only solve classification problems dealing with linearly separable sets (two subsets X and Y of R(d) are said to be linearly separable if there exists a hyperplane such that the elements of X and Y lie on the two opposite sides of R(d) delimited by this hyperplane). We propose several growing methods for constructing a RDP. These growing methods build a RDP by successively adding intermediate neurons (IN) to the topology (an IN corresponds to a SLPT). Thus, as a result, we obtain a multilayer perceptron topology, which together with the weights, are determined automatically by the constructing algorithms. Each IN augments the affine dimension of the set of input vectors. This augmentation is done by adding the output of each of these INs, as a new component, to every input vector. The construction of a new IN is made by selecting a subset from the set of augmented input vectors which is LS from the rest of this set. This process ends with LS classes in almost n-1 steps where n is the number of input vectors. For this construction, if we assume that the selected LS subsets are of maximum cardinality, the problem is proven to be NP-complete. We also introduce a generalization of the RDP model for classification of m classes (m>2) allowing to always separate m classes. This generalization is based on a new notion of linear separability for m classes, and it follows naturally from the RDP. This new model can be used to compute functions with a finite domain, and thus, to approximate continuous functions. We have also compared - over several classification problems - the percentage of test data correctly classified, or the topology of the 2 and m classes RDPs with that of the backpropagation (BP), cascade correlation (CC), and two other growing methods.

Journal Article↗
PubMed1987

Pathway: a dynamic food-chain model to predict radionuclide ingestion after fallout deposition.

This manuscript describes the structure and basis for parameter values of a computerized food-chain transport model for radionuclides. The model, called "PATHWAY," estimates the time-integrated ingestion intake by humans of 20 radionuclides after a single deposition from the atmosphere to the landscape. The model solves a set of linear, coupled differential equations to estimate the inventories and concentrations of radionuclides in soil, vegetation, animal tissues and animal products as a function of time following deposition. Dynamic processes in the model include foliar interception, weathering and absorption; plant growth, uptake, harvest and senescence; soil resuspension, percolation, leaching and tillage; radioactive decay; and livestock ingestion, absorption and excretion. Human dietary data are included to permit calculation of time-dependent radionuclide ingestion rates, which are then numerically integrated. The model considers seasonal changes in the biomass of vegetation and animal diets, as well as specific plowing and crop-harvest dates; thus the integrated radionuclide intakes by humans are dependent on the seasonal timing of deposition. The agricultural data base represents the arid and semi-arid regions of the western United States. The foliar deposition parameters apply to regional fallout out to a few hundred miles from nuclear detonations at the Nevada Test Site. With modification, the model could be applied to chronic or other acute releases, providing the ground deposition in Bq m-2 could be estimated. The output of PATHWAY (Bq ingested per Bq m-2 deposited) may be multiplied by the deposition and a dose conversion factor (Gy Bq-1) to yield an organ-specific dose estimate. The model may be run deterministically to yield single estimates or stochastically ("Monte-Carlo" mode) to provide distributional output that reflects uncertainty in the output due to uncertainty in parameters. Tests of the predictive accuracy are briefly described and work published to date on validation trials is cited.

Animals↗
PubMed2001

Modeling the long-term frequency distribution of regional ozone concentrations using synthetic meteorology.

A new method is developed to generate the meteorological input fields required for use with photochemical airshed models that seek to predict the effect of pollutant emissions on the long-term frequency distribution of peak O3 concentrations. Instead of using meteorological fields derived from interpolation of direct weather observations, this method uses synthetically generated meteorological data. These synthetic meteorological fields are created by first constructing a semi-Markov process that generates a time series of large-scale synoptic weather conditions that statistically resemble the occurrence and persistence of synoptic weather patterns during specific months of the year. Then for each day within each synoptic weather category, local weather variables indicative of the meteorological potential for ozone formation are drawn from the approximated joint distribution of the summation of three pressure gradients across the airshed and the 850 mb temperature measured in the early morning. The synthetic initial conditions are combined with boundary values that are extracted from historical days that match the chosen synoptic class, temperature, and pressure gradient values as closely as possible for use in a prognostic mesoscale meteorological model. The prognostic mesoscale meteorological model generates the meteorological input fields necessary for the photochemical airshed model. The airshed model driven by synthetically generated meteorological data is executed for a 31 day period that statistically resembles weather during the month of August in Southern California using pollutant emissions data from the year 1987. The procedure produced a frequency of occurrence of peak 8 h average ozone concentrations that compared well both to that produced by the deterministic model as well as to the O3 concentrations observed over the August months of the years 1984-1990.

Air Pollutants↗
PubMed2001

Extinction and quasi-stationarity in the Verhulst logistic model.

We formulate and analyse a stochastic version of the Verhulst deterministic model for density-dependent growth of a single population. Three parameter regions with qualitatively different behaviours are identified. Explicit approximations of the quasi-stationary distribution and of the expected time to extinction are presented in each of these regions. The quasi-stationary distribution is approximately normal, and the time to extinction is long, in one of these regions. Another region has a short time to extinction and a quasi-stationary distribution that is approximately truncated geometric. A third region is a transition region between these two. Here the time to extinction is moderately long and the quasi-stationary distribution has a more complicated behaviour. Numerical illustrations are given.

Animals↗
PubMed1996

Oscillatory, stochastic and chaotic growth rate fluctuations in permittistatically controlled yeast cultures.

We describe a continuous culture system related to the turbidostat, but using a feedback system based on biomass estimation from the dielectric permittivity of the cell suspension rather than its optical density. It is shown that this system provides an excellent method of maintaining a constant biomass level within a fermentor. The computer-controlled system was able to effect the essentially continuous registration of growth rate by monitoring the rate of medium addition via the time-dependent activity of the pump. At some biomass setpoints for aerobically grown cultures of baker's yeast substantial time-dependent fluctuations in the growth rate of the culture were thereby observed. At some biomass setpoints, however, or under anaerobic conditions, or when using a non-Crabtree yeast, the growth rate was constant, indicating that the fluctuations were inherent to the biological system and not simply a property of the fermentor and control system. A variety of time series analyses (Fourier transformations, Hurst and Lyapunov exponents, the determination of embedding dimension, and non-linear time series predictions based on the methodology of Sugihara and May) were used to demonstrate, for the first time, that as well as stochastic and periodic components these fluctuations exhibited deterministic chaos. 'Trivial predictors' were unable to give accurate predictions of the growth rate in these cultures. The growth rate fluctuations were studied further by means of offline measurements of changes in percentage viability, bud count, and in the external ethanol and glucose concentrations; these data and other evidence suggested that the growth rate fluctuations were closely linked to the primary respiro-fermentative metabolism of this organism. The identification of chaotic growth rates in cell cultures suggests that there may be novel methods for controlling the growth of such cultures.

Biomass↗
PubMed2000

Iterative linear minimum mean-square-error image restoration from partially known blur.

We address the problem of space-invariant image restoration when the blurring operator is not known exactly, a situation that arises regularly in practice. To account for this uncertainty, we model the point-spread function as the sum of a known deterministic component and an unknown random one. Such an approach has been studied before, but the problem of estimating the parameters of the restoration filter to our knowledge has not been addressed systematically. We propose an approach based on a Gaussian statistical assumption and derive an iterative, expectation-maximization algorithm that simultaneously restores the image and estimates the required filter parameters. We obtain two versions of the algorithm based on two different models for the statistics of the image. The computations are performed in the discrete Fourier transform domain; thus they are computationally efficient even for large images. We examine the convergence properties of the resulting estimators and evaluate their performance experimentally.

Algorithms↗
PubMed2005

An arrhythmia classification system based on the RR-interval signal.

OBJECTIVE: This paper proposes a knowledge-based method for arrhythmic beat classification and arrhythmic episode detection and classification using only the RR-interval signal extracted from ECG recordings. METHODOLOGY: A three RR-interval sliding window is used in arrhythmic beat classification algorithm. Classification is performed for four categories of beats: normal, premature ventricular contractions, ventricular flutter/fibrillation and 2 degrees heart block. The beat classification is used as input of a knowledge-based deterministic automaton to achieve arrhythmic episode detection and classification. Six rhythm types are classified: ventricular bigeminy, ventricular trigeminy, ventricular couplet, ventricular tachycardia, ventricular flutter/fibrillation and 2 degrees heart block. RESULTS: The method is evaluated by using the MIT-BIH arrhythmia database. The achieved scores indicate high performance: 98% accuracy for arrhythmic beat classification and 94% accuracy for arrhythmic episode detection and classification. CONCLUSION: The proposed method is advantageous because it uses only the RR-interval signal for arrhythmia beat and episode classification and the results compare well with more complex methods.

Algorithms↗
PubMed2003

A stochastic model on DNA renaturation kinetics.

A simple stochastic model on DNA renaturation kinetics in the presence and absence of cooperativity have been developed [the corresponding deterministic models have been explicitly treated in our previous work. Biochem Biophys Res Commun 293 (2002) 870-873]. Theoretical mean and variance of number of bases in single-stranded DNA (ssDNA), (which is of course a random variable) have been calculated and compared with the experimental values. The results showed that only the cooperative model correctly predicted the time t(m) at which variance becomes maximum whereas, the non-cooperative model overestimated it and thus proved the validity of the cooperative model. Some of the applications of this cooperative theory in resolving the problems of the central dogma of life, PCR etc. have also been discussed.

Algorithms↗
PubMed2003

Dynamical mean-field theory of noisy spiking neuron ensembles: application to the Hodgkin-Huxley model.

A dynamical mean-field approximation (DMA) previously proposed by the present author [H. Hasegawa, Phys. Rev E 67, 041903 (2003)] has been extended to ensembles described by a general noisy spiking neuron model. Ensembles of N-unit neurons, each of which is expressed by coupled K-dimensional differential equations (DEs), are assumed to be subject to spatially correlated white noises. The original KN-dimensional stochastic DEs have been replaced by K(K+2)-dimensional deterministic DEs expressed in terms of means and the second-order moments of local and global variables: the fourth-order contributions are taken into account by the Gaussian decoupling approximation. Our DMA has been applied to an ensemble of Hodgkin-Huxley (HH) neurons (K=4), for which effects of the noise, the coupling strength, and the ensemble size on the response to a single-spike input have been investigated. Numerical results calculated by the DMA theory are in good agreement with those obtained by direct simulations, although the former computation is about a thousand times faster than the latter for a typical HH neuron ensemble with N=100.

Action Potentials↗
PubMed1998

Childhood adoption: long-term effects in adulthood.

Clinicians and researchers have characterized early life experiences as permanent and stable influences on the personality and subsequent life experiences of an individual. Recent conceptualizations have suggested that personal and environmental factors influencing development are not deterministic. Multiple pathways into adulthood are possible. Adoption is one potential early life stressor that may illustrate the usefulness of such conceptualizations for assessing long-term effects in adulthood. Previous studies of adoption have characterized the effects of adoption into adolescence and young adulthood. The purpose of this study was to provide an initial assessment of the long-term impact of adoption. The participants were taken from the Swedish Adoption/Twin Study of Aging. From the original sample, we identified a subsample of 60 pairs of twins who were separated and reared apart, with one member being raised by a biological parent or parents and the other by an adoptive parent or parents with no biological relationship. A series of univariate and multivariate analyses were undertaken to assess the elements associated with being reared in either an adoptive home or the home of biological parent(s). The results suggest few significant effects of adoption on the adult adjustment of adoptees. In particular, the results reflect the important mediating role of childhood socioeconomic status, suggesting that the stress of adoption itself is mediated by the type of rearing environment provided by the adoption process.

Adaptation, Psychological↗
PubMed2002

Rotating unstable Langevin-type dynamics: linear and nonlinear mean passage time distributions.

To characterize the decay process of linear rotating unstable Langevin-type dynamics in the presence of constant external force, through the mean passage time distribution, two theoretical descriptions are proposed: one is called the Quasideterministic (QD) approach described in the limit of long times, and the other approach is formulated for not so long times. Both theories are matrix based and formulated in two x and y dynamical representations, y being the transformed space of coordinates by means of a time-dependent rotation matrix. In the y dynamical representation the noise as well as the external force are rotational. The QD approach is studied when the dynamics is not influenced by the external force and when it is influenced by it. In the absence of this force, the theory is given for n variables and leads to the same results as those obtained in the characterization of nonrotating unstable systems; a fact that is better understood in the space of coordinates y. In the presence of the external force, the characterization is given for two variables and it is only valid for weak amplitude forces. For large amplitudes, the dynamics is almost dominated by the deterministic rotational evolution; then the QD approach is no longer valid and therefore the other approach is required. The theory in this case is general and verified for systems of two and three variables. In the case of two variables we study a laser system and use the experimental data of this system to compare with both theoretical and simulation results. In the case of three variables, the theory foresees application in other fields, for instance, in plasma physics. We also study the time characterization of the nonlinear rotating unstable systems and show in general that the nonlinear correction to the linear case is a quantity evaluated in the deterministic limit. The same laser system studied in the linear case is used as a prototype model.

Journal Article↗
PubMed2005

Robustness properties of apoptosis models with respect to parameter variations and intrinsic noise.

Analyses of different robustness aspects for models of the direct signal transduction pathway of receptor-induced apoptosis is presented. Apoptosis is a form of programmed cell death, removing unwanted cells within multicellular organisms to maintain a proper balance between cell reproduction and death. Its signalling pathway includes an activation feedback loop that generates bistable behaviour, where the two steady states can be seen as 'life' and 'death'. Inherent robustness, widely recognised in biological systems, is of major importance in apoptosis signalling, as it guarantees the same cell fate for similar conditions. First, the influence of the stochastic nature of reactions indicating a role for inhibition reactions as noise filters and justifying a deterministic approach in the further analyses is evaluated. Second, the robustness of the bistable threshold with respect to parameter changes is evaluated by statistical methods, showing the need to balance both the forward and the back part of the activation loop. These analyses can also discriminate between the models favouring the model consistent with novel biological findings. The parameter robustness analyses are also applicable to other signal transduction networks, as several have been shown to display bistable behaviour. These methods therefore have a range of possible applications in systems biology not only to measure robustness, but also for model discrimination.

Animals↗
PubMed2004

Polygonal and polyhedral contour reconstruction in computed tomography.

This paper is about three-dimensional (3-D) reconstruction of a binary image from its X-ray tomographic data. We study the special case of a compact uniform polyhedron totally included in a uniform background and directly perform the polyhedral surface estimation. We formulate this problem as a nonlinear inverse problem using the Bayesian framework. Vertice estimation is done without using a voxel approximation of the 3-D image. It is based on the construction and optimization of a regularized criterion that accounts for surface smoothness. We investigate original deterministic local algorithms, based on the exact computation of the line projections, their update, and their derivatives with respect to the vertice coordinates. Results are first derived in the two-dimensional (2-D) case, which consists of reconstructing a 2-D object of deformable polygonal contour from its tomographic data. Then, we investigate the 3-D extension that requires technical adaptations. Simulation results illustrate the performance of polygonal and polyhedral reconstruction algorithms in terms of quality and computation time.

Algorithms↗
PubMed2000

A theoretical study of the invasion of cleared areas by tsetse flies (Diptera: Glossinidae).

Large-scale eradication campaigns against tsetse flies Glossina spp. are giving way to smaller operations aimed at disease and vector containment. There has been little discussion of the effects of these changes in policy. This study estimates the rate at which tsetse re-infect treated areas after the termination of control efforts. Movement is modelled as a diffusion process with a daily root mean square displacement (lambda) of 0.2-1 km-1/2 and population growth as logistic with a growth rate (r) < or =1.5% day-1. Invasion fronts move as the product of lambda and radicalr. For r = 0.75% day-1 a front advances at 2.5 km year-1 for each 100 m increment in lambda. If there are 0.001% survivors in 10% of the treated area, the population recovers to within 1% of the carrying capacity (K) within three years. If the control area is subject to invasion from all sides, a treated block of 10,000 km2 is effectively lost within two years - except at the lowest values of lambda and r. Cleared areas of 100 km2 are lost in a year, as observed in a community-based suppression programme in Kenya. If the treated area is closed to re-invasion, but if there is a block where tsetse survive at 0.0001-0.1% of K, the population recovers within 3-4 years for up to 20 km outside the surviving block. If the surviving flies are more widely spread, re-infection is even more rapid. The deterministic approach used here over-estimates re-invasion rates at low density, but comparisons between control scenarios are still valid. Stochastic modelling would estimate more exactly rates of re-infection at near-zero population densities.

Animals↗
PubMed1993

A new strategy for multifunction myoelectric control.

This paper describes a novel approach to the control of a multifunction prosthesis based on the classification of myoelectric patterns. It is shown that the myoelectric signal exhibits a deterministic structure during the initial phase of a muscle contraction. Features are extracted from several time segments of the myoelectric signal to preserve pattern structure. These features are then classified using an artificial neural network. The control signals are derived from natural contraction patterns which can be produced reliably with little subject training. The new control scheme increases the number of functions which can be controlled by a single channel of myoelectric signal but does so in a way which does not increase the effort required by the amputee. Results are presented to support this approach.

Amputation, Surgical↗
PubMed2001

Characterization of heart atrial fibrillation: proposal for a deterministic model.

Atrial Fibrillation (AFib) has been shown (e.g. Framingham Study) to increase stroke risk and to induce low cardiac output in patients. It is generally accepted that the mechanism of Atrial Fibrillation is reentry. In order to ease the study of AFib's, we propose a deterministic model that could be used in the characterization cardiac signals. The model is based on a linear combination of several "Atrial Flutter"-like signals. We therefore obtained AFib-like aspects. To demonstrate its usefulness we performed a power spectrum transform (i.e. scalar Fast Fourier Transform) of this model. As a result we found that this transform could not be used as is, could lead to errors in the interpretation of results. We expect that this model will help us to evaluate the relevance of mathematical transforms. This may lead to new findings in the classification of AFib, as well as to improvements in patients treatment, follow-up and survival.

Atrial Fibrillation↗
PubMed2003

The dual biological identity of human beings and the naturalization of morality.

The last two centuries have been the centuries of the discovery of the cell evolution: in the XIX century of the germinal cells and in the XX century of two groups of somatic cells, namely those of the brain-mind and of the immune systems. Since most cells do not behave in this way, the evolutionary character of the brain-mind and of the immune systems renders human beings formed by t wo different groups of somatic cells, one with a deterministic and another with an indeterministic (say Darwinian) behavior. An inherent consequence is that of the generation, during ontogenesis, of a dual biological identity. The concept of the dual biological identity may be used to explain the Kantian concept of the two metaphysical worlds, namely of the causal necessity and of the free will (Azzone, 2001). Two concepts, namely those of complex adaptive systems (CAS) and of emergence (Holland, 2002), are useful tools for understanding the mechanisms of adaptation and of evolution. The concept of complex adaptive systems indicates that living organisms contain series of stratified components, denoted as building blocks, forming stratified layers of increasing complexity. The concept of emergence implies the use of repeating patterns and of building blocks for the generation of structures of increasing levels of complexity, structures capable of exchanging communications both in the top-down and in the bottom-up direction. Against the concept of emergence it has been argued that nothing can produce something which is really new and endowed of causal efficacy. The defence of the concept of emergence is based on two arguments. The first is the interpretation of the variation-selection mechanism as a process of generation of information and of optimization of free energy dissipation in accord with the second principle of thermodynamics. The second is the objective evidence of the cosmological evolution from the Big Bang to the human mind and its products. Darwin has defended the concept of the continuity of evolution. However evolution should be considered as continuous when there is no increase of information and as discontinuous when there is generation of new information. Examples of such generation of information are the acquisition of the innate structures for language and the transition from absence to presence of morality. There are several discontinuity thresholds during both phylogenesis and ontogenesis. Morality is a relational property dependent on the interactions of human beings with the environment. Piaget and Kohlberg have shown that the generation of morality during childhood occurs through several stages and is accompanied by reorganization of the child mental organization. The children respect the conventions in the first stage and gradually generate their autonomous morality. The transition from absence to presence of morality, a major adaptive process, then, not only has occurred during phylogenesis but it occurs again in every human being during ontogenesis. The religious faith does not provide a logical justification of the moral rules (Ayala, 1987) but rather a psychological and anthropological justification of two fundamental needs of human beings: that of rendering Nature an understandable entity, and that of increasing the cooperation among members of the human societies. The positive effects of the altruistic genes in the animal societies are in accord with the positive effects of morality for the survival and development of the human societies.

Adaptation, Biological↗
PubMed2006

Space and stochasticity in population dynamics.

Organisms interact with each other mostly over local scales, so the local density experienced by an individual is of greater importance than the mean density in a population. This simple observation poses a tremendous challenge to theoretical ecology, and because nonlinear stochastic and spatial models cannot be solved exactly, much effort has been spent in seeking effective approximations. Several authors have observed that spatial population systems behave like deterministic nonspatial systems if dispersal averages the dynamics over a sufficiently large scale. We exploit this fact to develop an exact series expansion, which allows one to derive approximations of stochastic individual-based models without resorting to heuristic assumptions. Our approach makes it possible to calculate the corrections to mean-field models in the limit where the interaction range is large, and it provides insight into the performance of moment closure methods. With this approach, we demonstrate how the buildup of spatiotemporal correlations slows down the spread of an invasion, prolongs time lags associated with extinction debt, and leads to locally oscillating but globally stable coexistence of a host and a parasite.

Biological Evolution↗