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Impacts of environmental variability in open populations and communities: "inflation" in sink environments.

Ecological communities are typically open to the immigration and emigration of individuals, and also variable through time. In this paper we argue that interesting and potentially important effects arise when one splices together spatial fluxes and temporal variability. The particular system we examine is a sink habitat, where a species faces deterministic extinction but is rescued by recurrent immigration. We have shown, using a simple extension of the canonical exponential growth model in a time-varying environment, that variation "inflates" the average abundance of sink populations. We can analytically quantify the magnitude of this effect in several special cases (square-wave temporal variation and Gaussian stochastic variation). The inflationary effect can be large in "intermittent" sinks (where there are periods with positive growth), and when temporal variation is strongly autocorrelated. The effect appears to be robust to incorporation of demographic stochasticity (due to discrete birth-death-immigration processes), and to direct density dependence. With discrete generations, however, one can observe a wide range of effects of temporal variation, including depression as well as inflation. We argue that the inflationary effect of temporal variation in sink habitats can have important implications for community structure, because it can increase the average abundance (and hence local impacts) of species that on average are being excluded from a local community. We illustrate the latter effect using a familiar model of exploitative competition for a single limiting resource. We demonstrate that temporal variation can reverse local competitive dominance, even to the extent of allowing an inferior competitor maintained by immigration to exclude a competing species that would be locally superior in a constant environment.

Algorithms↗

Recurrence quantification analysis of postural fluctuations.

A technique (recurrence quantification analysis; RQA) for analyzing center of pressure (COP) signals is presented and applied to data obtained by having participants stand with the head forward or sideways and with eyes open or closed. RQA is suitable for short, nonstationary signals and quantifies dynamical (deterministic) structure and nonstationarity. Results indicated that vision affects the deterministic structure (in degree and complexity) of COP motions and that differential optical flow structure (radial versus lamellar flow) induced by spontaneous sway under different head orientations affects COP nonstationarity. Implications of these findings and the sensitivity of RQA to subtle time-evolutionary properties of the COP are discussed.

Adolescent↗

Noise can play an organizing role for the recurrent dynamics in excitable media.

We analyze patterns of recurrent activity in a prototypical model of an excitable medium in the presence of noise. Without noise, this model robustly predicts the existence of spiral waves as the only recurrent patterns in two dimensions. With small noise, however, we found that this model is also capable of generating coherent target patterns, another type of recurrent activity that is widely observed experimentally. These patterns remain essentially deterministic despite the presence of the noise, yet their existence is impossible without it. Their degree of coherence can also be made arbitrarily high for wide ranges of the parameters, which does not require fine-tuning. Our findings demonstrate the need to reexamine current modeling approaches to active biological media.

Animals↗

Dynamical characteristics common to neuronal competition models.

Models implementing neuronal competition by reciprocally inhibitory populations are widely used to characterize bistable phenomena such as binocular rivalry. We find common dynamical behavior in several models of this general type, which differ in their architecture in the form of their gain functions, and in how they implement the slow process that underlies alternating dominance. We focus on examining the effect of the input strength on the rate (and existence) of oscillations. In spite of their differences, all considered models possess similar qualitative features, some of which we report here for the first time. Experimentally, dominance durations have been reported to decrease monotonically with increasing stimulus strength (such as Levelt's "Proposition IV"). The models predict this behavior; however, they also predict that at a lower range of input strength dominance durations increase with increasing stimulus strength. The nonmonotonic dependency of duration on stimulus strength is common to both deterministic and stochastic models. We conclude that additional experimental tests of Levelt's Proposition IV are needed to reconcile models and perception.

Action Potentials↗

Perishable inventory theory: a review.

This paper reviews the relevant literature on the problem of determining suitable ordering policies for both fixed life perishable inventory, and inventory subject to continuous exponential decay. We consider both deterministic and stochastic demand for single and multiple products. Both optimal and suboptimal order policies are discussed. In addition, a brief review of the application of these models to blood bank management is included. The review concludes with a discussion of some of the interesting open research questions in the area.

Blood Banks↗

A state space model for the HIV epidemic in homosexual populations and some applications.

In this paper we have developed a state space model for the HIV epidemic in homosexual populations which have been divided into subpopulations according to sexual activity levels. In this model, the stochastic dynamic system model is the stochastic model of the HIV epidemic in terms of the chain multinomial model whereas the observation model is a statistical model based on the observed AIDS incidences. This model is applied to the San Francisco homosexual population for estimating the numbers of susceptible people, infective people and AIDS cases and for estimating the probabilities of HIV transmission from infective people to susceptible people given sexual contacts. The results show that the estimated numbers of AIDS incidence trace closely the observed numbers indicating the usefulness of the model. It is observed that the estimated numbers of latent people show multimodal curves and that HIV infection takes place during the primary stage and very late stage. The results have further shown that there are significant differences between the observed AIDS incidences and the estimates by the embedded deterministic model. These results indicate that using the embedded deterministic model to estimate the HIV-infected people and to predict future AIDS cases can be very misleading in some cases.

Acquired Immunodeficiency Syndrome↗

Stochasticity accelerates nematode egg development.

Day-degrees models of nematode development assume that temperature stochasticity has no effect on the development rate of infective stages as long as the mean temperature is held constant. This assumption was tested in this study. Unembryonated Heterakis gallinarum eggs were subjected to nocturnal and diurnal daily temperature cycles at 12 and 17 C. respectively, and embryonation was compared with eggs subjected to similar stochastic daily cycles, in which random normal variations in the temperature were added to the 2 temperatures. The prediction that there is no effect of stochasticity was refuted. Embryonation of eggs subjected to variable daily cycles occurred significantly earlier than that of eggs subjected to deterministic daily cycles, suggesting that stochastic variation in temperature accelerated embryonation even though mean temperatures were the same. These findings show that the development time of H. gallnarum eggs is decreased by stochastic variation in temperature, which may have important implications for the effects of climate change on parasite availability.

Animals↗

The role of cognition in classical and operant conditioning.

For the past 35 years, learning theorists have been providing models that depend on mental representations, even in their most simple, deterministic, and mechanistic approaches. Hence, cognitive involvement (typically thought of as expectancy) is assumed for most instances of classical and operant conditioning, with current theoretical differences concerning the level of cognition that is involved (e.g., simple association vs. rule learning), rather than its presence. Nevertheless, many psychologists not in the mainstream of learning theory continue to think of cognitive and conditioning theories as rival families of hypotheses. In this article, the data pertaining to the role of higher-order cognition in conditioning is reviewed, and a theoretical synthesis is proposed that provides a role for both automatic and cognitively mediated processes.

Cognition↗

Extinction dynamics in mainland-island metapopulations: an N-patch stochastic model.

A generalization of the well-known Levins' model of metapopulations is studied. The generalization consists of (i) the introduction of immigration from a mainland, and (ii) assuming the dynamics is stochastic, rather than deterministic. A master equation, for the probability that n of the patches are occupied, is derived and the stationary probability Ps(n), together with the mean and higher moments in the stationary state, determined. The time-dependence of the probability distribution is also studied: through a Gaussian approximation for general n when the boundary at n = 0 has little effect, and by calculating P(0, t), the probability that no patches are occupied at time t, by using a linearization procedure. These analytic calculations are supplemented by carrying out numerical solutions of the master equation and simulations of the stochastic process. The various approaches are in very good agreement with each other. This allows us to use the forms for Ps(0) and P(0,t) in the linearization approximation as a basis for calculating the mean time for a metapopulation to become extinct. We give an analytical expression for the mean time to extinction derived within a mean field approach. We devise a simple method to apply our mean field approach even to complex patch networks in realistic model metapopulations. After studying two spatially extended versions of this nonspatial metapopulation model--a lattice metapopulation model and a spatially realistic model--we conclude that our analytical formula for the mean extinction time is generally applicable to those metapopulations which are really endangered, where extinction dynamics dominates over local colonization processes. The time evolution and, in particular, the scope of our analytical results, are studied by comparing these different models with the analytical approach for various values of the parameters: the rates of immigration from the mainland, the rates of colonization and extinction, and the number of patches making up the metapopulation.

Animals↗

Autonomous informational stability in connective tissues.

No coherent theories currently explain connective tissue stability (i.e. 'memory') as well as spatial and temporal adaptability in the face of continual flux of its constituents. Furthermore, explanations of stability based exclusively upon DNA raise certain inherent problems, particularly with the spatial concordance of somatic tissues. As an alternative explanation, it is hypothesized that while connective tissue cells produce extracellular protein precursors through DNA-dependent processes, the assembly, location, orientation and configuration of the extracellular macromolecules as well as their degree of cell attachment depend primarily upon local micro-environmental conditions and/or self-organization rather than strictly cellular processes. The resulting extracellular matrix (ECM) serves as a time- and spatially-variable filter about each cell to afford a relatively consistent micro-environment for all similar cells, regardless of the more variable macro-environment. By insuring a consistent set of signals to the cell, the filter provides a non-genetic memory complementary to genetic memory. The half-lives of constituent molecules define the duration of the filter, allowing the filter to adapt to new environmental demands, yet to maintain a consistent milieu for the cell. The cell/matrix construct permits local, self-optimizing, non-deterministic tissue autonomy obviating the need to postulate certain intricate mechanisms coordinating spatial morphology and temporal behavior.

Animals↗

Estimating the human health risks from polychlorinated dioxins and furans in stack gas emissions from combustion units: implications of USEPA's dioxin reassessment.

Shortly after promulgation of the Hazardous Waste Combustor MACT rule established regulatory limits for polychlorinated dioxins and furans (dioxins/furans) in incinerator stack gas, the US Environmental Protection Agency (USEPA) announced that facilities could still be required to demonstrate that stack emissions do not present an unacceptable risk to human health and the environment. Guidance for conducting this risk assessment activity, which was to be required under RCRA omnibus authority, was developed by the agency and released in 1998. The guidance represented an increase in complexity over previous documents developed by the agency and contains multiple chemical, fate and transport, and toxicological parameters which are to be used as default deterministic parameters in a complex series of algorithms which ultimately lead to numerical estimates of risk. As these changes were occurring, USEPA was also moving towards completion of its reassessment of dioxin. That series of documents has been the subject of considerable controversy and has, in several of its various drafts, proposed a number of changes, including modification of the existing toxic equivalency factor (TEF) approach and of the cancer potency factor of 2,3,7,8-tetachlorodibenzo-p-dioxin. At this time it is unclear what the impact of these changes will be on facilities progressing through the permitting process, because it is not intuitively obvious how changes in the risk assessment input parameters will impact the magnitude of the dioxinlfuran risk. In this paper, the receptor usually associated with the highest potential risk from dioxins/furans in a combustion risk assessment, the Subsistence Farmer, will be subjected to a sensitivity analysis to determine which of the multiple default input parameters will have the greatest influence on the potential cancer risk.

Algorithms↗

Time-frequency analysis of heart murmurs. Part I: Parametric modelling and numerical simulations.

The object of this study is to compare the performance of two new bilinear time-frequency representation techniques with the spectrogram to characterise the behaviour of heart murmurs produced by bioprosthetic heart valves implanted in the mitral or aortic position. The murmurs are those of mitral stenosis, mitral regurgitation, aortic stenosis, aortic regurgitation, a diastolic musical murmur and a systolic musical murmur. In the first part of the study, the general characteristics of the amplitude and the spectral content of these murmurs are determined by visual observation of the spectrogram of phonocardiograms obtained from several patients with known valvular pathology complemented with a literature review. A parametric model is then generated for each murmur signal. Stenotic and regurgitant murmurs are modelled as the sequential output of a bank of low-pass filters excited by a white noise input signal. The basic parameters of each filter are selected to simulate, as a function of time, the basic characteristics of random heart murmurs. Musical murmurs are modelled as a frequency-modulated deterministic sinusoid of constant amplitude. Numerical simulations of these random and musical heart murmurs are then generated and will be used in Part II to determine the best of three time-frequency representation techniques for analysing heart murmur signals.

Aortic Valve↗

Scaling concepts in cellular and subcellular dynamics.

After developing a map for certain states typical of hemopoietic stem cells (SCs), we identify a number of parameters (e.g. fractal dimensions, oscillatory behavior in a multistable landscape, etc.) that scale down to subcellular structures such as interphase genome, chromatids, chromatin entanglements and DNA segmental motions. A curious aspect is the continuous reappearance of recursive processes even at very small biologic scales. These iterations are relevant not only for the normal behavior of (hemopoietic) cells but also for amplifying hidden genomic singularities above some critical threshold. When that happens, there are sudden quali-quantitative and often clonal changes in the cell behavior. As illustrated by specific leukemic cases, many paradoxes of malignant growth seem best explained by the peculiar sensitivity to initial condition of (hemopoietic) cells. Interpreted as chaotic oscillators, these cells display a spectrum of disorders that, in spite of appearing as random, are in fact triggered by amplification of subtle preconditions with statistico-deterministic outcomes, that are predictable within certain time limits.

Animals↗

Coexistence of multiple pathogen strains in stochastic epidemic models with density-dependent mortality.

Stochastic differential equations that model an SIS epidemic with multiple pathogen strains are derived from a system of ordinary differential equations. The stochastic model assumes there is demographic variability. The dynamics of the deterministic model are summarized. Then the dynamics of the stochastic model are compared to the deterministic model. In the deterministic model, there can be either disease extinction, competitive exclusion, where only one strain persists, or coexistence, where more than one strain persists. In the stochastic model, all strains are eventually eliminated because the disease-free state is an absorbing state. However, if the population size and the initial number of infected individuals are sufficiently large, it may take a long time until all strains are eliminated. Numerical simulations of the stochastic model show that coexistence cases predicted by the deterministic model are an unlikely occurrence in the stochastic model even for short time periods. In the stochastic model, either disease extinction or competitive exclusion occur. The initial number of infected individuals, the basic reproduction numbers, and other epidemiological parameters are important determinants of the dominant strain in the stochastic epidemic model.

Communicable Diseases↗

Global optimization of mutual information: application to three-dimensional retrospective registration of magnetic resonance images.

A global optimization technique for image registration, based on mutual information, that can be used in conjunction with a multi-resolution paradigm is described. This technique combines genetic algorithm in continuous space, which is a stochastic method and is very efficient in large search space, with dividing rectangle, which is a deterministic method that theoretically guarantees global optimization and is efficient in small search space. Calculations were performed for determining the optimum parameters for implementing this method. This technique was applied to register magnetic resonance images of brain. For comparison, the registration results using AIR, a commonly employed software package, are presented.

Algorithms↗

Transfer of 137Cs from soil to grass--analysis of possible sources of uncertainty.

On the basis of experimental data on the fallout of 137Cs from the Chernobyl accident, a statistical analysis was made of possible values of the coefficients of transfer via the soil-grass pathway. Model calculations of the possible radionuclide concentration in milk are performed by the Monte Carlo method using the probability distribution function obtained. It is shown that not only our limited knowledge and the possible diversity of the external conditions, but also the very nature of the phenomenon under consideration, make it desirable to switch from a deterministic to a stochastic formulation of the model. The fact that the dependence of the soil-to-grass radionuclide transfer coefficients on the initial concentration in soil might be non-linear in character is an indication of the limitation of the conventional linear model.

Accidents↗

Cost-effectiveness and choice of infant transport systems.

OBJECTIVE: To compare cost-effectiveness of three types of infant transport models (Emergency Medical Technicians [EMT], Registered Nurses [RN], or Combined Teams [CT] of RNs and Respiratory Therapists) and to derive a decision model to guide choice of a transport system. RESEARCH DESIGN: A prospective, multicenter, observational study was conducted to compare infant physiologic status before and after transport. Cost-effectiveness analysis from the perspective of the third-party payer, sensitivity analysis and threshold analysis were performed. SUBJECTS: All (n = 1931) out born infants with complete transport data admitted to 11 regional tertiary-level Canadian NICUs from January 1996 to October 1997. MEASURES: Change in Transport Risk Index of Physiologic Stability (TRIPS) Score before and after transport, transport costs. RESULTS: Change in TRIPS was predicted by gestational age at transport, transport duration, and pretransport TRIPS score, but not the type (EMT, RN, CT) of transport team, mode (air/ground) or direction (forward/retrograde) of transport, presence of a physician, and other baseline population risks (sex, small for gestational age, antenatal corticosteroid treatment, Apgar score). The RN model is least costly under most assumptions. At high transport volumes (>2760 transports per year) and long average transport times (>6.8 h per transport), the EMT model was less costly. Cost drivers of transport were volume of transport, relative wages of transport personnel, and percent of waiting time dedicated to infant transport. CONCLUSIONS: A deterministic decision-analytic model can be used to model transport cost-effectiveness and derive a threshold analytic chart for identifying the least costly transport model.

Canada↗

Stochastic population dynamics: the Poisson approximation.

We introduce an approximation to stochastic population dynamics based on almost independent Poisson processes whose parameters obey a set of coupled ordinary differential equations. The approximation applies to systems that evolve in terms of events such as death, birth, contagion, emission, absorption, etc., and we assume that the event-rates satisfy a generalized mass-action law. The dynamics of the populations is then the result of the projection from the space of events into the space of populations that determine the state of the system (phase space). The properties of the Poisson approximation are studied in detail. Especially, error bounds for the moment generating function and the generating function receive particular attention. The deterministic approximation for the population fractions and the Langevin-type approximation for the fluctuations around the mean value are recovered within the framework of the Poisson approximation as particular limit cases. However, the proposed framework allows to treat other limit cases and general situations with small populations that lie outside the scope of the standard approaches. The Poisson approximation can be viewed as a general (numerical) integration scheme for this family of problems in population dynamics.

Monte Carlo Method↗