A simple branching model that reproduces language family and language population distributions

NASA Astrophysics Data System (ADS)

Schwämmle, Veit; de Oliveira, Paulo Murilo Castro

2009-07-01

Human history leaves fingerprints in human languages. Little is known about language evolution and its study is of great importance. Here we construct a simple stochastic model and compare its results to statistical data of real languages. The model is based on the recent finding that language changes occur independently of the population size. We find agreement with the data additionally assuming that languages may be distinguished by having at least one among a finite, small number of different features. This finite set is also used in order to define the distance between two languages, similarly to linguistics tradition since Swadesh.

A simple mathematical model of gradual Darwinian evolution: emergence of a Gaussian trait distribution in adaptation along a fitness gradient.

PubMed

Biktashev, Vadim N

2014-04-01

We consider a simple mathematical model of gradual Darwinian evolution in continuous time and continuous trait space, due to intraspecific competition for common resource in an asexually reproducing population in constant environment, while far from evolutionary stable equilibrium. The model admits exact analytical solution. In particular, Gaussian distribution of the trait emerges from generic initial conditions.

Effects of host social hierarchy on disease persistence.

PubMed

Davidson, Ross S; Marion, Glenn; Hutchings, Michael R

2008-08-07

The effects of social hierarchy on population dynamics and epidemiology are examined through a model which contains a number of fundamental features of hierarchical systems, but is simple enough to allow analytical insight. In order to allow for differences in birth rates, contact rates and movement rates among different sets of individuals the population is first divided into subgroups representing levels in the hierarchy. Movement, representing dominance challenges, is allowed between any two levels, giving a completely connected network. The model includes hierarchical effects by introducing a set of dominance parameters which affect birth rates in each social level and movement rates between social levels, dependent upon their rank. Although natural hierarchies vary greatly in form, the skewing of contact patterns, introduced here through non-uniform dominance parameters, has marked effects on the spread of disease. A simple homogeneous mixing differential equation model of a disease with SI dynamics in a population subject to simple birth and death process is presented and it is shown that the hierarchical model tends to this as certain parameter regions are approached. Outside of these parameter regions correlations within the system give rise to deviations from the simple theory. A Gaussian moment closure scheme is developed which extends the homogeneous model in order to take account of correlations arising from the hierarchical structure, and it is shown that the results are in reasonable agreement with simulations across a range of parameters. This approach helps to elucidate the origin of hierarchical effects and shows that it may be straightforward to relate the correlations in the model to measurable quantities which could be used to determine the importance of hierarchical corrections. Overall, hierarchical effects decrease the levels of disease present in a given population compared to a homogeneous unstructured model, but show higher levels of disease than structured models with no hierarchy. The separation between these three models is greatest when the rate of dominance challenges is low, reducing mixing, and when the disease prevalence is low. This suggests that these effects will often need to be considered in models being used to examine the impact of control strategies where the low disease prevalence behaviour of a model is critical.

Does Specification Matter? Experiments with Simple Multiregional Probabilistic Population Projections

PubMed Central

Raymer, James; Abel, Guy J.; Rogers, Andrei

2012-01-01

Population projection models that introduce uncertainty are a growing subset of projection models in general. In this paper, we focus on the importance of decisions made with regard to the model specifications adopted. We compare the forecasts and prediction intervals associated with four simple regional population projection models: an overall growth rate model, a component model with net migration, a component model with in-migration and out-migration rates, and a multiregional model with destination-specific out-migration rates. Vector autoregressive models are used to forecast future rates of growth, birth, death, net migration, in-migration and out-migration, and destination-specific out-migration for the North, Midlands and South regions in England. They are also used to forecast different international migration measures. The base data represent a time series of annual data provided by the Office for National Statistics from 1976 to 2008. The results illustrate how both the forecasted subpopulation totals and the corresponding prediction intervals differ for the multiregional model in comparison to other simpler models, as well as for different assumptions about international migration. The paper ends end with a discussion of our results and possible directions for future research. PMID:23236221

Predicting the Ability of Marine Mammal Populations to Compensate for Behavioral Disturbances

DTIC Science & Technology

2015-09-30

approaches, including simple theoretical models as well as statistical analysis of data rich conditions. Building on models developed for PCoD [2,3], we...conditions is population trajectory most likely to be affected (the central aim of PCoD ). For the revised model presented here, we include a population...averaged condition individuals (here used as a proxy for individual health as defined in PCoD ), and E is the quality of the environment in which the

A cognitive-consistency based model of population wide attitude change.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lakkaraju, Kiran; Speed, Ann Elizabeth

Attitudes play a significant role in determining how individuals process information and behave. In this paper we have developed a new computational model of population wide attitude change that captures the social level: how individuals interact and communicate information, and the cognitive level: how attitudes and concept interact with each other. The model captures the cognitive aspect by representing each individuals as a parallel constraint satisfaction network. The dynamics of this model are explored through a simple attitude change experiment where we vary the social network and distribution of attitudes in a population.

Population Genetics of Three Dimensional Range Expansions

NASA Astrophysics Data System (ADS)

Lavrentovich, Maxim; Nelson, David

2014-03-01

We develop a simple model of genetic diversity in growing spherical cell clusters, where the growth is confined to the cluster surface. This kind of growth occurs in cells growing in soft agar, and can also serve as a simple model of avascular tumors. Mutation-selection balance in these radial expansions is strongly influenced by scaling near a neutral, voter model critical point and by the inflating frontier. We develop a scaling theory to describe how the dynamics of mutation-selection balance is cut off by inflation. Genetic drift, i.e., local fluctuations in the genetic diversity, also plays an important role, and can lead to the extinction even of selectively advantageous strains. We calculate this extinction probability, taking into account the effect of rough population frontiers.

Unresolved versus resolved: testing the validity of young simple stellar population models with VLT/MUSE observations of NGC 3603

NASA Astrophysics Data System (ADS)

Kuncarayakti, H.; Galbany, L.; Anderson, J. P.; Krühler, T.; Hamuy, M.

2016-09-01

Context. Stellar populations are the building blocks of galaxies, including the Milky Way. The majority, if not all, extragalactic studies are entangled with the use of stellar population models given the unresolved nature of their observation. Extragalactic systems contain multiple stellar populations with complex star formation histories. However, studies of these systems are mainly based upon the principles of simple stellar populations (SSP). Hence, it is critical to examine the validity of SSP models. Aims: This work aims to empirically test the validity of SSP models. This is done by comparing SSP models against observations of spatially resolved young stellar population in the determination of its physical properties, that is, age and metallicity. Methods: Integral field spectroscopy of a young stellar cluster in the Milky Way, NGC 3603, was used to study the properties of the cluster as both a resolved and unresolved stellar population. The unresolved stellar population was analysed using the Hα equivalent width as an age indicator and the ratio of strong emission lines to infer metallicity. In addition, spectral energy distribution (SED) fitting using STARLIGHT was used to infer these properties from the integrated spectrum. Independently, the resolved stellar population was analysed using the colour-magnitude diagram (CMD) to determine age and metallicity. As the SSP model represents the unresolved stellar population, the derived age and metallicity were tested to determine whether they agree with those derived from resolved stars. Results: The age and metallicity estimate of NGC 3603 derived from integrated spectroscopy are confirmed to be within the range of those derived from the CMD of the resolved stellar population, including other estimates found in the literature. The result from this pilot study supports the reliability of SSP models for studying unresolved young stellar populations. Based on observations collected at the European Organisation for Astronomical Research in the Southern Hemisphere under ESO programme 60.A-9344.

Replicating receptive fields of simple and complex cells in primary visual cortex in a neuronal network model with temporal and population sparseness and reliability.

PubMed

Tanaka, Takuma; Aoyagi, Toshio; Kaneko, Takeshi

2012-10-01

We propose a new principle for replicating receptive field properties of neurons in the primary visual cortex. We derive a learning rule for a feedforward network, which maintains a low firing rate for the output neurons (resulting in temporal sparseness) and allows only a small subset of the neurons in the network to fire at any given time (resulting in population sparseness). Our learning rule also sets the firing rates of the output neurons at each time step to near-maximum or near-minimum levels, resulting in neuronal reliability. The learning rule is simple enough to be written in spatially and temporally local forms. After the learning stage is performed using input image patches of natural scenes, output neurons in the model network are found to exhibit simple-cell-like receptive field properties. When the output of these simple-cell-like neurons are input to another model layer using the same learning rule, the second-layer output neurons after learning become less sensitive to the phase of gratings than the simple-cell-like input neurons. In particular, some of the second-layer output neurons become completely phase invariant, owing to the convergence of the connections from first-layer neurons with similar orientation selectivity to second-layer neurons in the model network. We examine the parameter dependencies of the receptive field properties of the model neurons after learning and discuss their biological implications. We also show that the localized learning rule is consistent with experimental results concerning neuronal plasticity and can replicate the receptive fields of simple and complex cells.

Using Dynamic Stochastic Modelling to Estimate Population Risk Factors in Infectious Disease: The Example of FIV in 15 Cat Populations

PubMed Central

Fouchet, David; Leblanc, Guillaume; Sauvage, Frank; Guiserix, Micheline; Poulet, Hervé; Pontier, Dominique

2009-01-01

Background In natural cat populations, Feline Immunodeficiency Virus (FIV) is transmitted through bites between individuals. Factors such as the density of cats within the population or the sex-ratio can have potentially strong effects on the frequency of fight between individuals and hence appear as important population risk factors for FIV. Methodology/Principal Findings To study such population risk factors, we present data on FIV prevalence in 15 cat populations in northeastern France. We investigate five key social factors of cat populations; the density of cats, the sex-ratio, the number of males and the mean age of males and females within the population. We overcome the problem of dependence in the infective status data using sexually-structured dynamic stochastic models. Only the age of males and females had an effect (p = 0.043 and p = 0.02, respectively) on the male-to-female transmission rate. Due to multiple tests, it is even likely that these effects are, in reality, not significant. Finally we show that, in our study area, the data can be explained by a very simple model that does not invoke any risk factor. Conclusion Our conclusion is that, in host-parasite systems in general, fluctuations due to stochasticity in the transmission process are naturally very large and may alone explain a larger part of the variability in observed disease prevalence between populations than previously expected. Finally, we determined confidence intervals for the simple model parameters that can be used to further aid in management of the disease. PMID:19888418

Estimation of sex and stature using anthropometry of the upper extremity in an Australian population.

PubMed

Howley, Donna; Howley, Peter; Oxenham, Marc F

2018-06-01

Stature and a further 8 anthropometric dimensions were recorded from the arms and hands of a sample of 96 staff and students from the Australian National University and The University of Newcastle, Australia. These dimensions were used to create simple and multiple logistic regression models for sex estimation and simple and multiple linear regression equations for stature estimation of a contemporary Australian population. Overall sex classification accuracies using the models created were comparable to similar studies. The stature estimation models achieved standard errors of estimates (SEE) which were comparable to and in many cases lower than those achieved in similar research. Generic, non sex-specific models achieved similar SEEs and R 2 values to the sex-specific models indicating stature may be accurately estimated when sex is unknown. Copyright © 2018 Elsevier B.V. All rights reserved.

Evolutionary synthesis of simple stellar populations. Colours and indices

NASA Astrophysics Data System (ADS)

Kurth, O. M.; Fritze-v. Alvensleben, U.; Fricke, K. J.

1999-07-01

We construct evolutionary synthesis models for simple stellar populations using the evolutionary tracks from the Padova group (1993, 1994), theoretical colour calibrations from \\cite[Lejeune et al. (1997, 1998)]{lejeune} and fit functions for stellar atmospheric indices from \\cite[Worthey et al. (1994)]{worthey}. A Monte-Carlo technique allows us to obtain a smooth time evolution of both broad band colours in UBVRIK and a series of stellar absorption features for Single Burst Stellar Populations (SSPs). We present colours and indices for SSPs with ages from 1 \\ 10(9) yrs to 1.6 \\ 10(10) yrs and metallicities [M/H]=-2.3, -1.7, -0.7, -0.4, 0.0 and 0.4. Model colours and indices at an age of about a Hubble time are in good agreement with observed colours and indices of the Galactic and M 31 GCs.

A coarse-grained biophysical model of sequence evolution and the population size dependence of the speciation rate

PubMed Central

Khatri, Bhavin S.; Goldstein, Richard A.

2015-01-01

Speciation is fundamental to understanding the huge diversity of life on Earth. Although still controversial, empirical evidence suggests that the rate of speciation is larger for smaller populations. Here, we explore a biophysical model of speciation by developing a simple coarse-grained theory of transcription factor-DNA binding and how their co-evolution in two geographically isolated lineages leads to incompatibilities. To develop a tractable analytical theory, we derive a Smoluchowski equation for the dynamics of binding energy evolution that accounts for the fact that natural selection acts on phenotypes, but variation arises from mutations in sequences; the Smoluchowski equation includes selection due to both gradients in fitness and gradients in sequence entropy, which is the logarithm of the number of sequences that correspond to a particular binding energy. This simple consideration predicts that smaller populations develop incompatibilities more quickly in the weak mutation regime; this trend arises as sequence entropy poises smaller populations closer to incompatible regions of phenotype space. These results suggest a generic coarse-grained approach to evolutionary stochastic dynamics, allowing realistic modelling at the phenotypic level. PMID:25936759

Time delays, population, and economic development

NASA Astrophysics Data System (ADS)

Gori, Luca; Guerrini, Luca; Sodini, Mauro

2018-05-01

This research develops an augmented Solow model with population dynamics and time delays. The model produces either a single stationary state or multiple stationary states (able to characterise different development regimes). The existence of time delays may cause persistent fluctuations in both economic and demographic variables. In addition, the work identifies in a simple way the reasons why economics affects demographics and vice versa.

Population and Pollution in the United States

ERIC Educational Resources Information Center

Ridker, Ronald G.

1972-01-01

Analyzes a simple model relating environmental pollution to population and per capita income and concludes that no single cause is sufficient to explain.... environmental problems, and that there is little about the pollution problems.... of the next 50 years that is inevitable." (Author/AL)

Development and verification of a model for estimating the screening utility in the detection of PCBs in transformer oil.

PubMed

Terakado, Shingo; Glass, Thomas R; Sasaki, Kazuhiro; Ohmura, Naoya

2014-01-01

A simple new model for estimating the screening performance (false positive and false negative rates) of a given test for a specific sample population is presented. The model is shown to give good results on a test population, and is used to estimate the performance on a sampled population. Using the model developed in conjunction with regulatory requirements and the relative costs of the confirmatory and screening tests allows evaluation of the screening test's utility in terms of cost savings. Testers can use the methods developed to estimate the utility of a screening program using available screening tests with their own sample populations.

Utilitarian pension and retirement policies under population ageing.

PubMed

Jackson, W A

1989-01-01

The author analyzes population aging and its impact on pension and retirement policies by utilizing a simple utilitarian model for alternative types of pension finance. Findings indicate that "when specific adjustments to population ageing are necessary, changes in the retirement age are preferred to changes in pensions or contributions." A geographical focus on developed countries is implied. excerpt

Are Statisticians Cold-Blooded Bosses? A New Perspective on the "Old" Concept of Statistical Population

ERIC Educational Resources Information Center

Lu, Yonggang; Henning, Kevin S. S.

2013-01-01

Spurred by recent writings regarding statistical pragmatism, we propose a simple, practical approach to introducing students to a new style of statistical thinking that models nature through the lens of data-generating processes, not populations. (Contains 5 figures.)

Stochastic multi-scale models of competition within heterogeneous cellular populations: Simulation methods and mean-field analysis.

PubMed

Cruz, Roberto de la; Guerrero, Pilar; Spill, Fabian; Alarcón, Tomás

2016-10-21

We propose a modelling framework to analyse the stochastic behaviour of heterogeneous, multi-scale cellular populations. We illustrate our methodology with a particular example in which we study a population with an oxygen-regulated proliferation rate. Our formulation is based on an age-dependent stochastic process. Cells within the population are characterised by their age (i.e. time elapsed since they were born). The age-dependent (oxygen-regulated) birth rate is given by a stochastic model of oxygen-dependent cell cycle progression. Once the birth rate is determined, we formulate an age-dependent birth-and-death process, which dictates the time evolution of the cell population. The population is under a feedback loop which controls its steady state size (carrying capacity): cells consume oxygen which in turn fuels cell proliferation. We show that our stochastic model of cell cycle progression allows for heterogeneity within the cell population induced by stochastic effects. Such heterogeneous behaviour is reflected in variations in the proliferation rate. Within this set-up, we have established three main results. First, we have shown that the age to the G1/S transition, which essentially determines the birth rate, exhibits a remarkably simple scaling behaviour. Besides the fact that this simple behaviour emerges from a rather complex model, this allows for a huge simplification of our numerical methodology. A further result is the observation that heterogeneous populations undergo an internal process of quasi-neutral competition. Finally, we investigated the effects of cell-cycle-phase dependent therapies (such as radiation therapy) on heterogeneous populations. In particular, we have studied the case in which the population contains a quiescent sub-population. Our mean-field analysis and numerical simulations confirm that, if the survival fraction of the therapy is too high, rescue of the quiescent population occurs. This gives rise to emergence of resistance to therapy since the rescued population is less sensitive to therapy. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Cell population modelling of yeast glycolytic oscillations.

PubMed Central

Henson, Michael A; Müller, Dirk; Reuss, Matthias

2002-01-01

We investigated a cell-population modelling technique in which the population is constructed from an ensemble of individual cell models. The average value or the number distribution of any intracellular property captured by the individual cell model can be calculated by simulation of a sufficient number of individual cells. The proposed method is applied to a simple model of yeast glycolytic oscillations where synchronization of the cell population is mediated by the action of an excreted metabolite. We show that smooth one-dimensional distributions can be obtained with ensembles comprising 1000 individual cells. Random variations in the state and/or structure of individual cells are shown to produce complex dynamic behaviours which cannot be adequately captured by small ensembles. PMID:12206713

Econometric model for age- and population-dependent radiation exposures

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sandquist, G.M.; Slaughter, D.M.; Rogers, V.C.

1991-01-01

The economic impact associated with ionizing radiation exposures in a given human population depends on numerous factors including the individual's mean economic status as a function age, the age distribution of the population, the future life expectancy at each age, and the latency period for the occurrence of radiation-induced health effects. A simple mathematical model has been developed that provides an analytical methodology for estimating the societal econometrics associated with radiation effects are to be assessed and compared for economic evaluation.

A frictional population model of seismicity rate change

USGS Publications Warehouse

Gomberg, J.; Reasenberg, P.; Cocco, M.; Belardinelli, M.E.

2005-01-01

We study models of seismicity rate changes caused by the application of a static stress perturbation to a population of faults and discuss our results with respect to the model proposed by Dieterich (1994). These models assume distribution of nucleation sites (e.g., faults) obeying rate-state frictional relations that fail at constant rate under tectonic loading alone, and predicts a positive static stress step at time to will cause an immediate increased seismicity rate that decays according to Omori's law. We show one way in which the Dieterich model may be constructed from simple general idead, illustratted using numerically computed synthetic seismicity and mathematical formulation. We show that seismicity rate change predicted by these models (1) depend on the particular relationship between the clock-advanced failure and fault maturity, (2) are largest for the faults closest to failure at to, (3) depend strongly on which state evolution law faults obey, and (4) are insensitive to some types of population hetrogeneity. We also find that if individual faults fail repeatedly and populations are finite, at timescales much longer than typical aftershock durations, quiescence follows at seismicity rate increase regardless of the specific frictional relations. For the examined models the quiescence duration is comparable to the ratio of stress change to stressing rate ????/??,which occurs after a time comparable to the average recurrence interval of the individual faults in the population and repeats in the absence of any new load may pertubations; this simple model may partly explain observations of repeated clustering of earthquakes. Copyright 2005 by the American Geophysical Union.

Modelling Nitrogen Oxides in Los Angeles Using a Hybrid Dispersion/Land Use Regression Model

NASA Astrophysics Data System (ADS)

Wilton, Darren C.

The goal of this dissertation is to develop models capable of predicting long term annual average NOx concentrations in urban areas. Predictions from simple meteorological dispersion models and seasonal proxies for NO2 oxidation were included as covariates in a land use regression (LUR) model for NOx in Los Angeles, CA. The NO x measurements were obtained from a comprehensive measurement campaign that is part of the Multi-Ethnic Study of Atherosclerosis Air Pollution Study (MESA Air). Simple land use regression models were initially developed using a suite of GIS-derived land use variables developed from various buffer sizes (R²=0.15). Caline3, a simple steady-state Gaussian line source model, was initially incorporated into the land-use regression framework. The addition of this spatio-temporally varying Caline3 covariate improved the simple LUR model predictions. The extent of improvement was much more pronounced for models based solely on the summer measurements (simple LUR: R²=0.45; Caline3/LUR: R²=0.70), than it was for models based on all seasons (R²=0.20). We then used a Lagrangian dispersion model to convert static land use covariates for population density, commercial/industrial area into spatially and temporally varying covariates. The inclusion of these covariates resulted in significant improvement in model prediction (R²=0.57). In addition to the dispersion model covariates described above, a two-week average value of daily peak-hour ozone was included as a surrogate of the oxidation of NO2 during the different sampling periods. This additional covariate further improved overall model performance for all models. The best model by 10-fold cross validation (R²=0.73) contained the Caline3 prediction, a static covariate for length of A3 roads within 50 meters, the Calpuff-adjusted covariates derived from both population density and industrial/commercial land area, and the ozone covariate. This model was tested against annual average NOx concentrations from an independent data set from the EPA's Air Quality System (AQS) and MESA Air fixed site monitors, and performed very well (R²=0.82).

Cognitive Impairment among the Aging Population in a Community in Southwest Nigeria

ERIC Educational Resources Information Center

Adebiyi, Akindele O.; Ogunniyi, Adesola; Adediran, Babatunde A.; Olakehinde, Olaide O.; Siwoku, Akeem A.

2016-01-01

Background: Vascular risk models can be quite informative in assisting the clinician to make a prediction of an individual's risk of cognitive impairment. Thus, a simple marker is a priority for low-capacity settings. This study examines the association of selected simple to deploy vascular markers with cognitive impairment in an elderly…

Improving Estimation of Ground Casualty Risk From Reentering Space Objects

NASA Technical Reports Server (NTRS)

Ostrom, Chris L.

2017-01-01

A recent improvement to the long-term estimation of ground casualties from reentering space debris is the further refinement and update to the human population distribution. Previous human population distributions were based on global totals with simple scaling factors for future years, or a coarse grid of population counts in a subset of the world's countries, each cell having its own projected growth rate. The newest population model includes a 5-fold refinement in both latitude and longitude resolution. All areas along a single latitude are combined to form a global population distribution as a function of latitude, creating a more accurate population estimation based on non-uniform growth at the country and area levels. Previous risk probability calculations used simplifying assumptions that did not account for the ellipsoidal nature of the Earth. The new method uses first, a simple analytical method to estimate the amount of time spent above each latitude band for a debris object with a given orbit inclination and second, a more complex numerical method that incorporates the effects of a non-spherical Earth. These new results are compared with the prior models to assess the magnitude of the effects on reentry casualty risk.

Improving Estimation of Ground Casualty Risk from Reentering Space Objects

NASA Technical Reports Server (NTRS)

Ostrom, C.

2017-01-01

A recent improvement to the long-term estimation of ground casualties from reentering space debris is the further refinement and update to the human population distribution. Previous human population distributions were based on global totals with simple scaling factors for future years, or a coarse grid of population counts in a subset of the world's countries, each cell having its own projected growth rate. The newest population model includes a 5-fold refinement in both latitude and longitude resolution. All areas along a single latitude are combined to form a global population distribution as a function of latitude, creating a more accurate population estimation based on non-uniform growth at the country and area levels. Previous risk probability calculations used simplifying assumptions that did not account for the ellipsoidal nature of the earth. The new method uses first, a simple analytical method to estimate the amount of time spent above each latitude band for a debris object with a given orbit inclination, and second, a more complex numerical method that incorporates the effects of a non-spherical Earth. These new results are compared with the prior models to assess the magnitude of the effects on reentry casualty risk.

Theory and applications of a deterministic approximation to the coalescent model

PubMed Central

Jewett, Ethan M.; Rosenberg, Noah A.

2014-01-01

Under the coalescent model, the random number nt of lineages ancestral to a sample is nearly deterministic as a function of time when nt is moderate to large in value, and it is well approximated by its expectation E[nt]. In turn, this expectation is well approximated by simple deterministic functions that are easy to compute. Such deterministic functions have been applied to estimate allele age, effective population size, and genetic diversity, and they have been used to study properties of models of infectious disease dynamics. Although a number of simple approximations of E[nt] have been derived and applied to problems of population-genetic inference, the theoretical accuracy of the formulas and the inferences obtained using these approximations is not known, and the range of problems to which they can be applied is not well understood. Here, we demonstrate general procedures by which the approximation nt ≈ E[nt] can be used to reduce the computational complexity of coalescent formulas, and we show that the resulting approximations converge to their true values under simple assumptions. Such approximations provide alternatives to exact formulas that are computationally intractable or numerically unstable when the number of sampled lineages is moderate or large. We also extend an existing class of approximations of E[nt] to the case of multiple populations of time-varying size with migration among them. Our results facilitate the use of the deterministic approximation nt ≈ E[nt] for deriving functionally simple, computationally efficient, and numerically stable approximations of coalescent formulas under complicated demographic scenarios. PMID:24412419

Mathematical demography of spotted owls in the Pacific Northwest

Treesearch

B.R. Noon; C.M. Biles

1990-01-01

We examined the mathematical demography of northern spotted owls (Strix occidentalis caurina) using simple deterministic population models. Our goals were to gain insights into the life history strategy, to determine demographic attributes most affecting changes in population size, and to provide guidelines for effective management of spotted owl...

Prevalence Incidence Mixture Models

Cancer.gov

The R package and webtool fits Prevalence Incidence Mixture models to left-censored and irregularly interval-censored time to event data that is commonly found in screening cohorts assembled from electronic health records. Absolute and relative risk can be estimated for simple random sampling, and stratified sampling (the two approaches of superpopulation and a finite population are supported for target populations). Non-parametric (absolute risks only), semi-parametric, weakly-parametric (using B-splines), and some fully parametric (such as the logistic-Weibull) models are supported.

A model-based 'varimax' sampling strategy for a heterogeneous population.

PubMed

Akram, Nuzhat A; Farooqi, Shakeel R

2014-01-01

Sampling strategies are planned to enhance the homogeneity of a sample, hence to minimize confounding errors. A sampling strategy was developed to minimize the variation within population groups. Karachi, the largest urban agglomeration in Pakistan, was used as a model population. Blood groups ABO and Rh factor were determined for 3000 unrelated individuals selected through simple random sampling. Among them five population groups, namely Balochi, Muhajir, Pathan, Punjabi and Sindhi, based on paternal ethnicity were identified. An index was designed to measure the proportion of admixture at parental and grandparental levels. Population models based on index score were proposed. For validation, 175 individuals selected through stratified random sampling were genotyped for the three STR loci CSF1PO, TPOX and TH01. ANOVA showed significant differences across the population groups for blood groups and STR loci distribution. Gene diversity was higher across the sub-population model than in the agglomerated population. At parental level gene diversities are significantly higher across No admixture models than Admixture models. At grandparental level the difference was not significant. A sub-population model with no admixture at parental level was justified for sampling the heterogeneous population of Karachi.

Spatial surplus production modeling of Atlantic tunas and billfish.

PubMed

Carruthers, Thomas R; McAllister, Murdoch K; Taylor, Nathan G

2011-10-01

We formulate and simulation-test a spatial surplus production model that provides a basis with which to undertake multispecies, multi-area, stock assessment. Movement between areas is parameterized using a simple gravity model that includes a "residency" parameter that determines the degree of stock mixing among areas. The model is deliberately simple in order to (1) accommodate nontarget species that typically have fewer available data and (2) minimize computational demand to enable simulation evaluation of spatial management strategies. Using this model, we demonstrate that careful consideration of spatial catch and effort data can provide the basis for simple yet reliable spatial stock assessments. If simple spatial dynamics can be assumed, tagging data are not required to reliably estimate spatial distribution and movement. When applied to eight stocks of Atlantic tuna and billfish, the model tracks regional catch data relatively well by approximating local depletions and exchange among high-abundance areas. We use these results to investigate and discuss the implications of using spatially aggregated stock assessment for fisheries in which the distribution of both the population and fishing vary over time.

Modelling food and population dynamics in honey bee colonies.

PubMed

Khoury, David S; Barron, Andrew B; Myerscough, Mary R

2013-01-01

Honey bees (Apis mellifera) are increasingly in demand as pollinators for various key agricultural food crops, but globally honey bee populations are in decline, and honey bee colony failure rates have increased. This scenario highlights a need to understand the conditions in which colonies flourish and in which colonies fail. To aid this investigation we present a compartment model of bee population dynamics to explore how food availability and bee death rates interact to determine colony growth and development. Our model uses simple differential equations to represent the transitions of eggs laid by the queen to brood, then hive bees and finally forager bees, and the process of social inhibition that regulates the rate at which hive bees begin to forage. We assume that food availability can influence both the number of brood successfully reared to adulthood and the rate at which bees transition from hive duties to foraging. The model predicts complex interactions between food availability and forager death rates in shaping colony fate. Low death rates and high food availability results in stable bee populations at equilibrium (with population size strongly determined by forager death rate) but consistently increasing food reserves. At higher death rates food stores in a colony settle at a finite equilibrium reflecting the balance of food collection and food use. When forager death rates exceed a critical threshold the colony fails but residual food remains. Our model presents a simple mathematical framework for exploring the interactions of food and forager mortality on colony fate, and provides the mathematical basis for more involved simulation models of hive performance.

A population pharmacokinetic model of valproic acid in pediatric patients with epilepsy: a non-linear pharmacokinetic model based on protein-binding saturation.

PubMed

Ding, Junjie; Wang, Yi; Lin, Weiwei; Wang, Changlian; Zhao, Limei; Li, Xingang; Zhao, Zhigang; Miao, Liyan; Jiao, Zheng

2015-03-01

Valproic acid (VPA) follows a non-linear pharmacokinetic profile in terms of protein-binding saturation. The total daily dose regarding VPA clearance is a simple power function, which may partially explain the non-linearity of the pharmacokinetic profile; however, it may be confounded by the therapeutic drug monitoring effect. The aim of this study was to develop a population pharmacokinetic model for VPA based on protein-binding saturation in pediatric patients with epilepsy. A total of 1,107 VPA serum trough concentrations at steady state were collected from 902 epileptic pediatric patients aged from 3 weeks to 14 years at three hospitals. The population pharmacokinetic model was developed using NONMEM(®) software. The ability of three candidate models (the simple power exponent model, the dose-dependent maximum effect [DDE] model, and the protein-binding model) to describe the non-linear pharmacokinetic profile of VPA was investigated, and potential covariates were screened using a stepwise approach. Bootstrap, normalized prediction distribution errors and external evaluations from two independent studies were performed to determine the stability and predictive performance of the candidate models. The age-dependent exponent model described the effects of body weight and age on the clearance well. Co-medication with carbamazepine was identified as a significant covariate. The DDE model best fitted the aim of this study, although there were no obvious differences in the predictive performances. The condition number was less than 500, and the precision of the parameter estimates was less than 30 %, indicating stability and validity of the final model. The DDE model successfully described the non-linear pharmacokinetics of VPA. Furthermore, the proposed population pharmacokinetic model of VPA can be used to design rational dosage regimens to achieve desirable serum concentrations.

Luminance, Colour, Viewpoint and Border Enhanced Disparity Energy Model

PubMed Central

Martins, Jaime A.; Rodrigues, João M. F.; du Buf, Hans

2015-01-01

The visual cortex is able to extract disparity information through the use of binocular cells. This process is reflected by the Disparity Energy Model, which describes the role and functioning of simple and complex binocular neuron populations, and how they are able to extract disparity. This model uses explicit cell parameters to mathematically determine preferred cell disparities, like spatial frequencies, orientations, binocular phases and receptive field positions. However, the brain cannot access such explicit cell parameters; it must rely on cell responses. In this article, we implemented a trained binocular neuronal population, which encodes disparity information implicitly. This allows the population to learn how to decode disparities, in a similar way to how our visual system could have developed this ability during evolution. At the same time, responses of monocular simple and complex cells can also encode line and edge information, which is useful for refining disparities at object borders. The brain should then be able, starting from a low-level disparity draft, to integrate all information, including colour and viewpoint perspective, in order to propagate better estimates to higher cortical areas. PMID:26107954

Simulation of C. elegans thermotactic behavior in a linear thermal gradient using a simple phenomenological motility model.

PubMed

Matsuoka, Tomohiro; Gomi, Sohei; Shingai, Ryuzo

2008-01-21

The nematode Caenorhabditis elegans has been reported to exhibit thermotaxis, a sophisticated behavioral response to temperature. However, there appears to be some inconsistency among previous reports. The results of population-level thermotaxis investigations suggest that C. elegans can navigate to the region of its cultivation temperature from nearby regions of higher or lower temperature. However, individual C. elegans nematodes appear to show only cryophilic tendencies above their cultivation temperature. A Monte-Carlo style simulation using a simple individual model of C. elegans provides insight into clarifying apparent inconsistencies among previous findings. The simulation using the thermotaxis model that includes the cryophilic tendencies, isothermal tracking and thermal adaptation was conducted. As a result of the random walk property of locomotion of C. elegans, only cryophilic tendencies above the cultivation temperature result in population-level thermophilic tendencies. Isothermal tracking, a period of active pursuit of an isotherm around regions of temperature near prior cultivation temperature, can strengthen the tendencies of these worms to gather around near-cultivation-temperature regions. A statistical index, the thermotaxis (TTX) L-skewness, was introduced and was useful in analyzing the population-level thermotaxis of model worms.

Addressing population heterogeneity and distribution in epidemics models using a cellular automata approach

PubMed Central

2014-01-01

Background The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. Methods An epidemic is characterized trough an individual–based–model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. Results A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. Conclusions The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area play a central role in the dynamics of the desease. PMID:24725804

Addressing population heterogeneity and distribution in epidemics models using a cellular automata approach.

PubMed

López, Leonardo; Burguerner, Germán; Giovanini, Leonardo

2014-04-12

The spread of an infectious disease is determined by biological and social factors. Models based on cellular automata are adequate to describe such natural systems consisting of a massive collection of simple interacting objects. They characterize the time evolution of the global system as the emergent behaviour resulting from the interaction of the objects, whose behaviour is defined through a set of simple rules that encode the individual behaviour and the transmission dynamic. An epidemic is characterized trough an individual-based-model built upon cellular automata. In the proposed model, each individual of the population is represented by a cell of the automata. This way of modeling an epidemic situation allows to individually define the characteristic of each individual, establish different scenarios and implement control strategies. A cellular automata model to study the time evolution of a heterogeneous populations through the various stages of disease was proposed, allowing the inclusion of individual heterogeneity, geographical characteristics and social factors that determine the dynamic of the desease. Different assumptions made to built the classical model were evaluated, leading to following results: i) for low contact rate (like in quarantine process or low density population areas) the number of infective individuals is lower than other areas where the contact rate is higher, and ii) for different initial spacial distributions of infected individuals different epidemic dynamics are obtained due to its influence on the transition rate and the reproductive ratio of disease. The contact rate and spatial distributions have a central role in the spread of a disease. For low density populations the spread is very low and the number of infected individuals is lower than in highly populated areas. The spacial distribution of the population and the disease focus as well as the geographical characteristic of the area play a central role in the dynamics of the desease.

Effect of lethality on the extinction and on the error threshold of quasispecies.

PubMed

Tejero, Hector; Marín, Arturo; Montero, Francisco

2010-02-21

In this paper the effect of lethality on error threshold and extinction has been studied in a population of error-prone self-replicating molecules. For given lethality and a simple fitness landscape, three dynamic regimes can be obtained: quasispecies, error catastrophe, and extinction. Using a simple model in which molecules are classified as master, lethal and non-lethal mutants, it is possible to obtain the mutation rates of the transitions between the three regimes analytically. The numerical resolution of the extended model, in which molecules are classified depending on their Hamming distance to the master sequence, confirms the results obtained in the simple model and shows how an error catastrophe regime changes when lethality is taken in account. (c) 2009 Elsevier Ltd. All rights reserved.

Computing local edge probability in natural scenes from a population of oriented simple cells

PubMed Central

Ramachandra, Chaithanya A.; Mel, Bartlett W.

2013-01-01

A key computation in visual cortex is the extraction of object contours, where the first stage of processing is commonly attributed to V1 simple cells. The standard model of a simple cell—an oriented linear filter followed by a divisive normalization—fits a wide variety of physiological data, but is a poor performing local edge detector when applied to natural images. The brain's ability to finely discriminate edges from nonedges therefore likely depends on information encoded by local simple cell populations. To gain insight into the corresponding decoding problem, we used Bayes's rule to calculate edge probability at a given location/orientation in an image based on a surrounding filter population. Beginning with a set of ∼ 100 filters, we culled out a subset that were maximally informative about edges, and minimally correlated to allow factorization of the joint on- and off-edge likelihood functions. Key features of our approach include a new, efficient method for ground-truth edge labeling, an emphasis on achieving filter independence, including a focus on filters in the region orthogonal rather than tangential to an edge, and the use of a customized parametric model to represent the individual filter likelihood functions. The resulting population-based edge detector has zero parameters, calculates edge probability based on a sum of surrounding filter influences, is much more sharply tuned than the underlying linear filters, and effectively captures fine-scale edge structure in natural scenes. Our findings predict nonmonotonic interactions between cells in visual cortex, wherein a cell may for certain stimuli excite and for other stimuli inhibit the same neighboring cell, depending on the two cells' relative offsets in position and orientation, and their relative activation levels. PMID:24381295

Mate-finding as an overlooked critical determinant of dispersal variation in sexually-reproducing animals.

PubMed

Gilroy, James J; Lockwood, Julie L

2012-01-01

Dispersal is a critically important process in ecology, but robust predictive models of animal dispersal remain elusive. We identify a potentially ubiquitous component of variation in animal dispersal that has been largely overlooked until now: the influence of mate encounters on settlement probability. We use an individual-based model to simulate dispersal in sexually-reproducing organisms that follow a simple set of movement rules based on conspecific encounters, within an environment lacking spatial habitat heterogeneity. We show that dispersal distances vary dramatically with fluctuations in population density in such a model, even in the absence of variation in dispersive traits between individuals. In a simple random-walk model with promiscuous mating, dispersal distributions become increasingly 'fat-tailed' at low population densities due to the increasing scarcity of mates. Similar variation arises in models incorporating territoriality. In a model with polygynous mating, we show that patterns of sex-biased dispersal can even be reversed across a gradient of population density, despite underlying dispersal mechanisms remaining unchanged. We show that some widespread dispersal patterns found in nature (e.g. fat tailed distributions) can arise as a result of demographic variability in the absence of heterogeneity in dispersive traits across the population. This implies that models in which individual dispersal distances are considered to be fixed traits might be unrealistic, as dispersal distances vary widely under a single dispersal mechanism when settlement is influenced by mate encounters. Mechanistic models offer a promising means of advancing our understanding of dispersal in sexually-reproducing organisms.

The application of sensitivity analysis to models of large scale physiological systems

NASA Technical Reports Server (NTRS)

Leonard, J. I.

1974-01-01

A survey of the literature of sensitivity analysis as it applies to biological systems is reported as well as a brief development of sensitivity theory. A simple population model and a more complex thermoregulatory model illustrate the investigatory techniques and interpretation of parameter sensitivity analysis. The role of sensitivity analysis in validating and verifying models, and in identifying relative parameter influence in estimating errors in model behavior due to uncertainty in input data is presented. This analysis is valuable to the simulationist and the experimentalist in allocating resources for data collection. A method for reducing highly complex, nonlinear models to simple linear algebraic models that could be useful for making rapid, first order calculations of system behavior is presented.

A simple spatiotemporal rabies model for skunk and bat interaction in northeast Texas.

PubMed

Borchering, Rebecca K; Liu, Hao; Steinhaus, Mara C; Gardner, Carl L; Kuang, Yang

2012-12-07

We formulate a simple partial differential equation model in an effort to qualitatively reproduce the spread dynamics and spatial pattern of rabies in northeast Texas with overlapping reservoir species (skunks and bats). Most existing models ignore reservoir species or model them with patchy models by ordinary differential equations. In our model, we incorporate interspecies rabies infection in addition to rabid population random movement. We apply this model to the confirmed case data from northeast Texas with most parameter values obtained or computed from the literature. Results of simulations using both our skunk-only model and our skunk and bat model demonstrate that the model with overlapping reservoir species more accurately reproduces the progression of rabies spread in northeast Texas. Copyright © 2012 Elsevier Ltd. All rights reserved.

Mathematical Modeling for Scrub Typhus and Its Implications for Disease Control.

PubMed

Min, Kyung Duk; Cho, Sung Il

2018-03-19

The incidence rate of scrub typhus has been increasing in the Republic of Korea. Previous studies have suggested that this trend may have resulted from the effects of climate change on the transmission dynamics among vectors and hosts, but a clear explanation of the process is still lacking. In this study, we applied mathematical models to explore the potential factors that influence the epidemiology of tsutsugamushi disease. We developed mathematical models of ordinary differential equations including human, rodent and mite groups. Two models, including simple and complex models, were developed, and all parameters employed in the models were adopted from previous articles that represent epidemiological situations in the Republic of Korea. The simulation results showed that the force of infection at the equilibrium state under the simple model was 0.236 (per 100,000 person-months), and that in the complex model was 26.796 (per 100,000 person-months). Sensitivity analyses indicated that the most influential parameters were rodent and mite populations and contact rate between them for the simple model, and trans-ovarian transmission for the complex model. In both models, contact rate between humans and mites is more influential than morality rate of rodent and mite group. The results indicate that the effect of controlling either rodents or mites could be limited, and reducing the contact rate between humans and mites is more practical and effective strategy. However, the current level of control would be insufficient relative to the growing mite population. © 2018 The Korean Academy of Medical Sciences.

Age estimation standards for a Western Australian population using the coronal pulp cavity index.

PubMed

Karkhanis, Shalmira; Mack, Peter; Franklin, Daniel

2013-09-10

Age estimation is a vital aspect in creating a biological profile and aids investigators by narrowing down potentially matching identities from the available pool. In addition to routine casework, in the present global political scenario, age estimation in living individuals is required in cases of refugees, asylum seekers, human trafficking and to ascertain age of criminal responsibility. Thus robust methods that are simple, non-invasive and ethically viable are required. The aim of the present study is, therefore, to test the reliability and applicability of the coronal pulp cavity index method, for the purpose of developing age estimation standards for an adult Western Australian population. A total of 450 orthopantomograms (220 females and 230 males) of Australian individuals were analyzed. Crown and coronal pulp chamber heights were measured in the mandibular left and right premolars, and the first and second molars. These measurements were then used to calculate the tooth coronal index. Data was analyzed using paired sample t-tests to assess bilateral asymmetry followed by simple linear and multiple regressions to develop age estimation models. The most accurate age estimation based on simple linear regression model was with mandibular right first molar (SEE ±8.271 years). Multiple regression models improved age prediction accuracy considerably and the most accurate model was with bilateral first and second molars (SEE ±6.692 years). This study represents the first investigation of this method in a Western Australian population and our results indicate that the method is suitable for forensic application. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

When push comes to shove: Exclusion processes with nonlocal consequences

NASA Astrophysics Data System (ADS)

Almet, Axel A.; Pan, Michael; Hughes, Barry D.; Landman, Kerry A.

2015-11-01

Stochastic agent-based models are useful for modelling collective movement of biological cells. Lattice-based random walk models of interacting agents where each site can be occupied by at most one agent are called simple exclusion processes. An alternative motility mechanism to simple exclusion is formulated, in which agents are granted more freedom to move under the compromise that interactions are no longer necessarily local. This mechanism is termed shoving. A nonlinear diffusion equation is derived for a single population of shoving agents using mean-field continuum approximations. A continuum model is also derived for a multispecies problem with interacting subpopulations, which either obey the shoving rules or the simple exclusion rules. Numerical solutions of the derived partial differential equations compare well with averaged simulation results for both the single species and multispecies processes in two dimensions, while some issues arise in one dimension for the multispecies case.

The Population Tracking Model: A Simple, Scalable Statistical Model for Neural Population Data

PubMed Central

O'Donnell, Cian; alves, J. Tiago Gonç; Whiteley, Nick; Portera-Cailliau, Carlos; Sejnowski, Terrence J.

2017-01-01

Our understanding of neural population coding has been limited by a lack of analysis methods to characterize spiking data from large populations. The biggest challenge comes from the fact that the number of possible network activity patterns scales exponentially with the number of neurons recorded (∼2Neurons). Here we introduce a new statistical method for characterizing neural population activity that requires semi-independent fitting of only as many parameters as the square of the number of neurons, requiring drastically smaller data sets and minimal computation time. The model works by matching the population rate (the number of neurons synchronously active) and the probability that each individual neuron fires given the population rate. We found that this model can accurately fit synthetic data from up to 1000 neurons. We also found that the model could rapidly decode visual stimuli from neural population data from macaque primary visual cortex about 65 ms after stimulus onset. Finally, we used the model to estimate the entropy of neural population activity in developing mouse somatosensory cortex and, surprisingly, found that it first increases, and then decreases during development. This statistical model opens new options for interrogating neural population data and can bolster the use of modern large-scale in vivo Ca2+ and voltage imaging tools. PMID:27870612

The division of labor: genotypic versus phenotypic specialization.

PubMed

Wahl, L M

2002-07-01

A model of the division of labor in simple evolving systems is explored to compare two strategies evident in natural populations: phenotypic specialization (such as differentiation by regulated gene expression) and genotypic specialization (such as co-infection by complementary covirus populations). While genotypic specialization is vulnerable to the chance extinction of an essential specialist type and to parasitism, phenotypic specialization is able to overcome these hurdles. When simple spatial effects are included, phenotypic specialization has further benefits, protecting against destructive dynamic patterns. Many of the advantages of phenotypic specialization, however, can only be realized when a high degree of relatedness within groups is ensured.

Yonsei Evolutionary Population Synthesis (YEPS). II. Spectro-photometric Evolution of Helium-enhanced Stellar Populations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chung, Chul; Yoon, Suk-Jin; Lee, Young-Wook, E-mail: chulchung@yonsei.ac.kr, E-mail: sjyoon0691@yonsei.ac.kr

The discovery of multiple stellar populations in Milky Way globular clusters (GCs) has stimulated various follow-up studies on helium-enhanced stellar populations. Here we present the evolutionary population synthesis models for the spectro-photometric evolution of simple stellar populations (SSPs) with varying initial helium abundance ( Y {sub ini}). We show that Y {sub ini} brings about dramatic changes in spectro-photometric properties of SSPs. Like the normal-helium SSPs, the integrated spectro-photometric evolution of helium-enhanced SSPs is also dependent on metallicity and age for a given Y {sub ini}. We discuss the implications and prospects for the helium-enhanced populations in relation to themore » second-generation populations found in the Milky Way GCs. All of the models are available at http://web.yonsei.ac.kr/cosmic/data/YEPS.htm.« less

The Evonik-Mainz Eye Care-Study (EMECS): Development of an Expert System for Glaucoma Risk Detection in a Working Population

PubMed Central

Wahl, Jochen; Barleon, Lorenz; Morfeld, Peter; Lichtmeß, Andrea; Haas-Brähler, Sibylle; Pfeiffer, Norbert

2016-01-01

Purpose To develop an expert system for glaucoma screening in a working population based on a human expert procedure using images of optic nerve head (ONH), visual field (frequency doubling technology, FDT) and intraocular pressure (IOP). Methods 4167 of 13037 (32%) employees between 40 and 65 years of Evonik Industries were screened. An experienced glaucoma expert (JW) assessed papilla parameters and evaluated all individual screening results. His classification into “no glaucoma”, “possible glaucoma” and “probable glaucoma” was defined as “gold standard”. A screening model was developed which was tested versus the gold-standard. This model took into account the assessment of the ONH. Values and relationships of CDR and IOP and the FDT were considered additionally and a glaucoma score was generated. The structure of the screening model was specified a priori whereas values of the parameters were chosen post-hoc to optimize sensitivity and specificity of the algorithm. Simple screening models based on IOP and / or FDT were investigated for comparison. Results 111 persons (2.66%) were classified as glaucoma suspects, thereof 13 (0.31%) as probable and 98 (2.35%) as possible glaucoma suspects by the expert. Re-evaluation by the screening model revealed a sensitivity of 83.8% and a specificity of 99.6% for all glaucoma suspects. The positive predictive value of the model was 80.2%, the negative predictive value 99.6%. Simple screening models showed insufficient diagnostic accuracy. Conclusion Adjustment of ONH and symmetry parameters with respect to excavation and IOP in an expert system produced sufficiently satisfying diagnostic accuracy. This screening model seems to be applicable in such a working population with relatively low age and low glaucoma prevalence. Different experts should validate the model in different populations. PMID:27479301

The Evonik-Mainz Eye Care-Study (EMECS): Development of an Expert System for Glaucoma Risk Detection in a Working Population.

PubMed

Wahl, Jochen; Barleon, Lorenz; Morfeld, Peter; Lichtmeß, Andrea; Haas-Brähler, Sibylle; Pfeiffer, Norbert

2016-01-01

To develop an expert system for glaucoma screening in a working population based on a human expert procedure using images of optic nerve head (ONH), visual field (frequency doubling technology, FDT) and intraocular pressure (IOP). 4167 of 13037 (32%) employees between 40 and 65 years of Evonik Industries were screened. An experienced glaucoma expert (JW) assessed papilla parameters and evaluated all individual screening results. His classification into "no glaucoma", "possible glaucoma" and "probable glaucoma" was defined as "gold standard". A screening model was developed which was tested versus the gold-standard. This model took into account the assessment of the ONH. Values and relationships of CDR and IOP and the FDT were considered additionally and a glaucoma score was generated. The structure of the screening model was specified a priori whereas values of the parameters were chosen post-hoc to optimize sensitivity and specificity of the algorithm. Simple screening models based on IOP and / or FDT were investigated for comparison. 111 persons (2.66%) were classified as glaucoma suspects, thereof 13 (0.31%) as probable and 98 (2.35%) as possible glaucoma suspects by the expert. Re-evaluation by the screening model revealed a sensitivity of 83.8% and a specificity of 99.6% for all glaucoma suspects. The positive predictive value of the model was 80.2%, the negative predictive value 99.6%. Simple screening models showed insufficient diagnostic accuracy. Adjustment of ONH and symmetry parameters with respect to excavation and IOP in an expert system produced sufficiently satisfying diagnostic accuracy. This screening model seems to be applicable in such a working population with relatively low age and low glaucoma prevalence. Different experts should validate the model in different populations.

Density dependence in demography and dispersal generates fluctuating invasion speeds

PubMed Central

Li, Bingtuan; Miller, Tom E. X.

2017-01-01

Density dependence plays an important role in population regulation and is known to generate temporal fluctuations in population density. However, the ways in which density dependence affects spatial population processes, such as species invasions, are less understood. Although classical ecological theory suggests that invasions should advance at a constant speed, empirical work is illuminating the highly variable nature of biological invasions, which often exhibit nonconstant spreading speeds, even in simple, controlled settings. Here, we explore endogenous density dependence as a mechanism for inducing variability in biological invasions with a set of population models that incorporate density dependence in demographic and dispersal parameters. We show that density dependence in demography at low population densities—i.e., an Allee effect—combined with spatiotemporal variability in population density behind the invasion front can produce fluctuations in spreading speed. The density fluctuations behind the front can arise from either overcompensatory population growth or density-dependent dispersal, both of which are common in nature. Our results show that simple rules can generate complex spread dynamics and highlight a source of variability in biological invasions that may aid in ecological forecasting. PMID:28442569

Mathematical toy model inspired by the problem of the adaptive origins of the sexual orientation continuum

NASA Astrophysics Data System (ADS)

Skinner, Brian

2016-09-01

Same-sex sexual behaviour is ubiquitous in the animal kingdom, but its adaptive origins remain a prominent puzzle. Here, I suggest the possibility that same-sex sexual behaviour arises as a consequence of the competition between an evolutionary drive for a wide diversity in traits, which improves the adaptability of a population, and a drive for sexual dichotomization of traits, which promotes opposite-sex attraction and increases the rate of reproduction. This trade-off is explored via a simple mathematical `toy model'. The model exhibits a number of interesting features and suggests a simple mathematical form for describing the sexual orientation continuum.

Mathematical toy model inspired by the problem of the adaptive origins of the sexual orientation continuum.

PubMed

Skinner, Brian

2016-09-01

Same-sex sexual behaviour is ubiquitous in the animal kingdom, but its adaptive origins remain a prominent puzzle. Here, I suggest the possibility that same-sex sexual behaviour arises as a consequence of the competition between an evolutionary drive for a wide diversity in traits, which improves the adaptability of a population, and a drive for sexual dichotomization of traits, which promotes opposite-sex attraction and increases the rate of reproduction. This trade-off is explored via a simple mathematical 'toy model'. The model exhibits a number of interesting features and suggests a simple mathematical form for describing the sexual orientation continuum.

The noisy edge of traveling waves

PubMed Central

Hallatschek, Oskar

2011-01-01

Traveling waves are ubiquitous in nature and control the speed of many important dynamical processes, including chemical reactions, epidemic outbreaks, and biological evolution. Despite their fundamental role in complex systems, traveling waves remain elusive because they are often dominated by rare fluctuations in the wave tip, which have defied any rigorous analysis so far. Here, we show that by adjusting nonlinear model details, noisy traveling waves can be solved exactly. The moment equations of these tuned models are closed and have a simple analytical structure resembling the deterministic approximation supplemented by a nonlocal cutoff term. The peculiar form of the cutoff shapes the noisy edge of traveling waves and is critical for the correct prediction of the wave speed and its fluctuations. Our approach is illustrated and benchmarked using the example of fitness waves arising in simple models of microbial evolution, which are highly sensitive to number fluctuations. We demonstrate explicitly how these models can be tuned to account for finite population sizes and determine how quickly populations adapt as a function of population size and mutation rates. More generally, our method is shown to apply to a broad class of models, in which number fluctuations are generated by branching processes. Because of this versatility, the method of model tuning may serve as a promising route toward unraveling universal properties of complex discrete particle systems. PMID:21187435

Binary Population and Spectral Synthesis Version 2.1: Construction, Observational Verification, and New Results

NASA Astrophysics Data System (ADS)

Eldridge, J. J.; Stanway, E. R.; Xiao, L.; McClelland, L. A. S.; Taylor, G.; Ng, M.; Greis, S. M. L.; Bray, J. C.

2017-11-01

The Binary Population and Spectral Synthesis suite of binary stellar evolution models and synthetic stellar populations provides a framework for the physically motivated analysis of both the integrated light from distant stellar populations and the detailed properties of those nearby. We present a new version 2.1 data release of these models, detailing the methodology by which Binary Population and Spectral Synthesis incorporates binary mass transfer and its effect on stellar evolution pathways, as well as the construction of simple stellar populations. We demonstrate key tests of the latest Binary Population and Spectral Synthesis model suite demonstrating its ability to reproduce the colours and derived properties of resolved stellar populations, including well-constrained eclipsing binaries. We consider observational constraints on the ratio of massive star types and the distribution of stellar remnant masses. We describe the identification of supernova progenitors in our models, and demonstrate a good agreement to the properties of observed progenitors. We also test our models against photometric and spectroscopic observations of unresolved stellar populations, both in the local and distant Universe, finding that binary models provide a self-consistent explanation for observed galaxy properties across a broad redshift range. Finally, we carefully describe the limitations of our models, and areas where we expect to see significant improvement in future versions.

Food-web models predict species abundances in response to habitat change.

PubMed

Gotelli, Nicholas J; Ellison, Aaron M

2006-10-01

Plant and animal population sizes inevitably change following habitat loss, but the mechanisms underlying these changes are poorly understood. We experimentally altered habitat volume and eliminated top trophic levels of the food web of invertebrates that inhabit rain-filled leaves of the carnivorous pitcher plant Sarracenia purpurea. Path models that incorporated food-web structure better predicted population sizes of food-web constituents than did simple keystone species models, models that included only autecological responses to habitat volume, or models including both food-web structure and habitat volume. These results provide the first experimental confirmation that trophic structure can determine species abundances in the face of habitat loss.

Applying the multivariate time-rescaling theorem to neural population models

PubMed Central

Gerhard, Felipe; Haslinger, Robert; Pipa, Gordon

2011-01-01

Statistical models of neural activity are integral to modern neuroscience. Recently, interest has grown in modeling the spiking activity of populations of simultaneously recorded neurons to study the effects of correlations and functional connectivity on neural information processing. However any statistical model must be validated by an appropriate goodness-of-fit test. Kolmogorov-Smirnov tests based upon the time-rescaling theorem have proven to be useful for evaluating point-process-based statistical models of single-neuron spike trains. Here we discuss the extension of the time-rescaling theorem to the multivariate (neural population) case. We show that even in the presence of strong correlations between spike trains, models which neglect couplings between neurons can be erroneously passed by the univariate time-rescaling test. We present the multivariate version of the time-rescaling theorem, and provide a practical step-by-step procedure for applying it towards testing the sufficiency of neural population models. Using several simple analytically tractable models and also more complex simulated and real data sets, we demonstrate that important features of the population activity can only be detected using the multivariate extension of the test. PMID:21395436

Tangled nature: a model of evolutionary ecology.

PubMed

Christensen, Kim; di Collobiano, Simone A; Hall, Matt; Jensen, Henrik J

2002-05-07

We discuss a simple model of co-evolution. In order to emphasize the effect of interaction between individuals, the entire population is subjected to the same physical environment. Species are emergent structures and extinction, origination and diversity are entirely a consequence of co-evolutionary interaction between individuals. For comparison, we consider both asexual and sexually reproducing populations. In either case, the system evolves through periods of hectic reorganization separated by periods of coherent stable coexistence. Copyright 2002 Elsevier Science Ltd. All rights reserved.

Modeling individual effects in the Cormack-Jolly-Seber Model: A state-space formulation

USGS Publications Warehouse

Royle, J. Andrew

2008-01-01

In population and evolutionary biology, there exists considerable interest in individual heterogeneity in parameters of demographic models for open populations. However, flexible and practical solutions to the development of such models have proven to be elusive. In this article, I provide a state-space formulation of open population capture-recapture models with individual effects. The state-space formulation provides a generic and flexible framework for modeling and inference in models with individual effects, and it yields a practical means of estimation in these complex problems via contemporary methods of Markov chain Monte Carlo. A straightforward implementation can be achieved in the software package WinBUGS. I provide an analysis of a simple model with constant parameter detection and survival probability parameters. A second example is based on data from a 7-year study of European dippers, in which a model with year and individual effects is fitted.

Ability of matrix models to explain the past and predict the future of plant populations.

USGS Publications Warehouse

McEachern, Kathryn; Crone, Elizabeth E.; Ellis, Martha M.; Morris, William F.; Stanley, Amanda; Bell, Timothy; Bierzychudek, Paulette; Ehrlen, Johan; Kaye, Thomas N.; Knight, Tiffany M.; Lesica, Peter; Oostermeijer, Gerard; Quintana-Ascencio, Pedro F.; Ticktin, Tamara; Valverde, Teresa; Williams, Jennifer I.; Doak, Daniel F.; Ganesan, Rengaian; Thorpe, Andrea S.; Menges, Eric S.

2013-01-01

Uncertainty associated with ecological forecasts has long been recognized, but forecast accuracy is rarely quantified. We evaluated how well data on 82 populations of 20 species of plants spanning 3 continents explained and predicted plant population dynamics. We parameterized stage-based matrix models with demographic data from individually marked plants and determined how well these models forecast population sizes observed at least 5 years into the future. Simple demographic models forecasted population dynamics poorly; only 40% of observed population sizes fell within our forecasts' 95% confidence limits. However, these models explained population dynamics during the years in which data were collected; observed changes in population size during the data-collection period were strongly positively correlated with population growth rate. Thus, these models are at least a sound way to quantify population status. Poor forecasts were not associated with the number of individual plants or years of data. We tested whether vital rates were density dependent and found both positive and negative density dependence. However, density dependence was not associated with forecast error. Forecast error was significantly associated with environmental differences between the data collection and forecast periods. To forecast population fates, more detailed models, such as those that project how environments are likely to change and how these changes will affect population dynamics, may be needed. Such detailed models are not always feasible. Thus, it may be wiser to make risk-averse decisions than to expect precise forecasts from models.

Ability of matrix models to explain the past and predict the future of plant populations.

PubMed

Crone, Elizabeth E; Ellis, Martha M; Morris, William F; Stanley, Amanda; Bell, Timothy; Bierzychudek, Paulette; Ehrlén, Johan; Kaye, Thomas N; Knight, Tiffany M; Lesica, Peter; Oostermeijer, Gerard; Quintana-Ascencio, Pedro F; Ticktin, Tamara; Valverde, Teresa; Williams, Jennifer L; Doak, Daniel F; Ganesan, Rengaian; McEachern, Kathyrn; Thorpe, Andrea S; Menges, Eric S

2013-10-01

Uncertainty associated with ecological forecasts has long been recognized, but forecast accuracy is rarely quantified. We evaluated how well data on 82 populations of 20 species of plants spanning 3 continents explained and predicted plant population dynamics. We parameterized stage-based matrix models with demographic data from individually marked plants and determined how well these models forecast population sizes observed at least 5 years into the future. Simple demographic models forecasted population dynamics poorly; only 40% of observed population sizes fell within our forecasts' 95% confidence limits. However, these models explained population dynamics during the years in which data were collected; observed changes in population size during the data-collection period were strongly positively correlated with population growth rate. Thus, these models are at least a sound way to quantify population status. Poor forecasts were not associated with the number of individual plants or years of data. We tested whether vital rates were density dependent and found both positive and negative density dependence. However, density dependence was not associated with forecast error. Forecast error was significantly associated with environmental differences between the data collection and forecast periods. To forecast population fates, more detailed models, such as those that project how environments are likely to change and how these changes will affect population dynamics, may be needed. Such detailed models are not always feasible. Thus, it may be wiser to make risk-averse decisions than to expect precise forecasts from models. © 2013 Society for Conservation Biology.

A General Model of Negative Frequency Dependent Selection Explains Global Patterns of Human ABO Polymorphism

PubMed Central

Villanea, Fernando A.; Safi, Kristin N.; Busch, Jeremiah W.

2015-01-01

The ABO locus in humans is characterized by elevated heterozygosity and very similar allele frequencies among populations scattered across the globe. Using knowledge of ABO protein function, we generated a simple model of asymmetric negative frequency dependent selection and genetic drift to explain the maintenance of ABO polymorphism and its loss in human populations. In our models, regardless of the strength of selection, models with large effective population sizes result in ABO allele frequencies that closely match those observed in most continental populations. Populations must be moderately small to fall out of equilibrium and lose either the A or B allele (Ne ≤ 50) and much smaller (N e ≤ 25) for the complete loss of diversity, which nearly always involved the fixation of the O allele. A pattern of low heterozygosity at the ABO locus where loss of polymorphism occurs in our model is consistent with small populations, such as Native American populations. This study provides a general evolutionary model to explain the observed global patterns of polymorphism at the ABO locus and the pattern of allele loss in small populations. Moreover, these results inform the range of population sizes associated with the recent human colonization of the Americas. PMID:25946124

Metapopulation models for historical inference.

PubMed

Wakeley, John

2004-04-01

The genealogical process for a sample from a metapopulation, in which local populations are connected by migration and can undergo extinction and subsequent recolonization, is shown to have a relatively simple structure in the limit as the number of populations in the metapopulation approaches infinity. The result, which is an approximation to the ancestral behaviour of samples from a metapopulation with a large number of populations, is the same as that previously described for other metapopulation models, namely that the genealogical process is closely related to Kingman's unstructured coalescent. The present work considers a more general class of models that includes two kinds of extinction and recolonization, and the possibility that gamete production precedes extinction. In addition, following other recent work, this result for a metapopulation divided into many populations is shown to hold both for finite population sizes and in the usual diffusion limit, which assumes that population sizes are large. Examples illustrate when the usual diffusion limit is appropriate and when it is not. Some shortcomings and extensions of the model are considered, and the relevance of such models to understanding human history is discussed.

Generative Models in Deep Learning: Constraints for Galaxy Evolution

NASA Astrophysics Data System (ADS)

Turp, Maximilian Dennis; Schawinski, Kevin; Zhang, Ce; Weigel, Anna K.

2018-01-01

New techniques are essential to make advances in the field of galaxy evolution. Recent developments in the field of artificial intelligence and machine learning have proven that these tools can be applied to problems far more complex than simple image recognition. We use these purely data driven approaches to investigate the process of star formation quenching. We show that Variational Autoencoders provide a powerful method to forward model the process of galaxy quenching. Our results imply that simple changes in specific star formation rate and bulge to disk ratio cannot fully describe the properties of the quenched population.

Sustainability of a Compartmentalized Host-Parasite Replicator System under Periodic Washout-Mixing Cycles

PubMed Central

Furubayashi, Taro

2018-01-01

The emergence and dominance of parasitic replicators are among the major hurdles for the proliferation of primitive replicators. Compartmentalization of replicators is proposed to relieve the parasite dominance; however, it remains unclear under what conditions simple compartmentalization uncoupled with internal reaction secures the long-term survival of a population of primitive replicators against incessant parasite emergence. Here, we investigate the sustainability of a compartmentalized host-parasite replicator (CHPR) system undergoing periodic washout-mixing cycles, by constructing a mathematical model and performing extensive simulations. We describe sustainable landscapes of the CHPR system in the parameter space and elucidate the mechanism of phase transitions between sustainable and extinct regions. Our findings revealed that a large population size of compartments, a high mixing intensity, and a modest amount of nutrients are important factors for the robust survival of replicators. We also found two distinctive sustainable phases with different mixing intensities. These results suggest that a population of simple host–parasite replicators assumed before the origin of life can be sustained by a simple compartmentalization with periodic washout-mixing processes. PMID:29373536

Scaling laws between population and facility densities.

PubMed

Um, Jaegon; Son, Seung-Woo; Lee, Sung-Ik; Jeong, Hawoong; Kim, Beom Jun

2009-08-25

When a new facility like a grocery store, a school, or a fire station is planned, its location should ideally be determined by the necessities of people who live nearby. Empirically, it has been found that there exists a positive correlation between facility and population densities. In the present work, we investigate the ideal relation between the population and the facility densities within the framework of an economic mechanism governing microdynamics. In previous studies based on the global optimization of facility positions in minimizing the overall travel distance between people and facilities, it was shown that the density of facility D and that of population rho should follow a simple power law D approximately rho(2/3). In our empirical analysis, on the other hand, the power-law exponent alpha in D approximately rho(alpha) is not a fixed value but spreads in a broad range depending on facility types. To explain this discrepancy in alpha, we propose a model based on economic mechanisms that mimic the competitive balance between the profit of the facilities and the social opportunity cost for populations. Through our simple, microscopically driven model, we show that commercial facilities driven by the profit of the facilities have alpha = 1, whereas public facilities driven by the social opportunity cost have alpha = 2/3. We simulate this model to find the optimal positions of facilities on a real U.S. map and show that the results are consistent with the empirical data.

Computer simulations of sympatric speciation in a simple food web

NASA Astrophysics Data System (ADS)

Luz-Burgoa, K.; Dell, Tony; de Oliveira, S. Moss

2005-07-01

Galapagos finches, have motivated much theoretical research aimed at understanding the processes associated with the formation of the species. Inspired by them, in this paper we investigate the process of sympatric speciation in a simple food web model. For that we modify the individual-based Penna model that has been widely used to study aging as well as other evolutionary processes. Initially, our web consists of a primary food source and a single herbivore species that feeds on this resource. Subsequently we introduce a predator that feeds on the herbivore. In both instances we manipulate directly a basal resource distribution and monitor the changes in the populations. Sympatric speciation is obtained for the top species in both cases, and our results suggest that the speciation velocity depends on how far up, in the food chain, the focus population is feeding. Simulations are done with three different sexual imprintinglike mechanisms, in order to discuss adaptation by natural selection.

Structure of velocity distributions in shock waves in granular gases with extension to molecular gases.

PubMed

Vilquin, A; Boudet, J F; Kellay, H

2016-08-01

Velocity distributions in normal shock waves obtained in dilute granular flows are studied. These distributions cannot be described by a simple functional shape and are believed to be bimodal. Our results show that these distributions are not strictly bimodal but a trimodal distribution is shown to be sufficient. The usual Mott-Smith bimodal description of these distributions, developed for molecular gases, and based on the coexistence of two subpopulations (a supersonic and a subsonic population) in the shock front, can be modified by adding a third subpopulation. Our experiments show that this additional population results from collisions between the supersonic and subsonic subpopulations. We propose a simple approach incorporating the role of this third intermediate population to model the measured probability distributions and apply it to granular shocks as well as shocks in molecular gases.

Learning Natural Selection in 4th Grade with Multi-Agent-Based Computational Models

ERIC Educational Resources Information Center

Dickes, Amanda Catherine; Sengupta, Pratim

2013-01-01

In this paper, we investigate how elementary school students develop multi-level explanations of population dynamics in a simple predator-prey ecosystem, through scaffolded interactions with a multi-agent-based computational model (MABM). The term "agent" in an MABM indicates individual computational objects or actors (e.g., cars), and these…

Dynamics and forecast in a simple model of sustainable development for rural populations.

PubMed

Angulo, David; Angulo, Fabiola; Olivar, Gerard

2015-02-01

Society is becoming more conscious on the need to preserve the environment. Sustainable development schemes have grown rapidly as a tool for managing, predicting and improving the growth path in different regions and economy sectors. We introduce a novel and simple mathematical model of ordinary differential equations (ODEs) in order to obtain a dynamical description for each one of the sustainability components (economy, social development and environment conservation), together with their dependence with demographic dynamics. The main part in the modeling task is inspired by the works by Cobb, Douglas, Brander and Taylor. This is completed through some new insights by the authors. A model application is presented for three specific geographical rural regions in Caldas (Colombia).

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dong, J. J.; Skinner, B.; Breecher, N.

Spatial patterning can be crucially important for understanding the behavior of interacting populations. Here we investigate a simple model of parasite and host populations in which parasites are random walkers that must come into contact with a host in order to reproduce. We focus on the spatial arrangement of parasites around a single host, and we derive using analytics and numerical simulations the necessary conditions placed on the parasite fecundity and lifetime for the populations long-term survival. We also show that the parasite population can be pushed to extinction by a large drift velocity, but, counterintuitively, a small drift velocitymore » generally increases the parasite population.« less

Adaptive Topographies and Equilibrium Selection in an Evolutionary Game

PubMed Central

Osinga, Hinke M.; Marshall, James A. R.

2015-01-01

It has long been known in the field of population genetics that adaptive topographies, in which population equilibria maximise mean population fitness for a trait regardless of its genetic bases, do not exist. Whether one chooses to model selection acting on a single locus or multiple loci does matter. In evolutionary game theory, analysis of a simple and general game involving distinct roles for the two players has shown that whether strategies are modelled using a single ‘locus’ or one ‘locus’ for each role, the stable population equilibria are unchanged and correspond to the fitness-maximising evolutionary stable strategies of the game. This is curious given the aforementioned population genetical results on the importance of the genetic bases of traits. Here we present a dynamical systems analysis of the game with roles detailing how, while the stable equilibria in this game are unchanged by the number of ‘loci’ modelled, equilibrium selection may differ under the two modelling approaches. PMID:25706762

HABSEED: a Simple Spatially Explicit Meta-Populations Model Using Remote Sensing Derived Habitat Quality Data

NASA Astrophysics Data System (ADS)

Heumann, B. W.; Guichard, F.; Seaquist, J. W.

2005-05-01

The HABSEED model uses remote sensing derived NPP as a surrogate for habitat quality as the driving mechanism for population growth and local seed dispersal. The model has been applied to the Sahel region of Africa. Results show that the functional response of plants to habitat quality alters population distribution. Plants more tolerant of medium quality habitat have greater distributions to the North while plants requiring only the best habitat are limited to the South. For all functional response types, increased seed production results in diminishing returns. Functional response types have been related to life history tradeoffs and r-K strategies based on the results. Results are compared to remote sensing derived vegetation land cover.

Food-Web Models Predict Species Abundances in Response to Habitat Change

PubMed Central

Gotelli, Nicholas J; Ellison, Aaron M

2006-01-01

Plant and animal population sizes inevitably change following habitat loss, but the mechanisms underlying these changes are poorly understood. We experimentally altered habitat volume and eliminated top trophic levels of the food web of invertebrates that inhabit rain-filled leaves of the carnivorous pitcher plant Sarracenia purpurea. Path models that incorporated food-web structure better predicted population sizes of food-web constituents than did simple keystone species models, models that included only autecological responses to habitat volume, or models including both food-web structure and habitat volume. These results provide the first experimental confirmation that trophic structure can determine species abundances in the face of habitat loss. PMID:17002518

Biology Notes

ERIC Educational Resources Information Center

Holt, S.

1972-01-01

Short articles describing a model of protein synthesis, a simple constant temperature incubator, techniques for determining the age structure of populations from qualitative characters, an experimental demonstration of proteolytic enzyme action, and apparatus for demonstrating hydrotrophic response of roots and for measuring photosynthetic rate of…

Noise shaping in populations of coupled model neurons.

PubMed

Mar, D J; Chow, C C; Gerstner, W; Adams, R W; Collins, J J

1999-08-31

Biological information-processing systems, such as populations of sensory and motor neurons, may use correlations between the firings of individual elements to obtain lower noise levels and a systemwide performance improvement in the dynamic range or the signal-to-noise ratio. Here, we implement such correlations in networks of coupled integrate-and-fire neurons using inhibitory coupling and demonstrate that this can improve the system dynamic range and the signal-to-noise ratio in a population rate code. The improvement can surpass that expected for simple averaging of uncorrelated elements. A theory that predicts the resulting power spectrum is developed in terms of a stochastic point-process model in which the instantaneous population firing rate is modulated by the coupling between elements.

The finite state projection approach to analyze dynamics of heterogeneous populations

NASA Astrophysics Data System (ADS)

Johnson, Rob; Munsky, Brian

2017-06-01

Population modeling aims to capture and predict the dynamics of cell populations in constant or fluctuating environments. At the elementary level, population growth proceeds through sequential divisions of individual cells. Due to stochastic effects, populations of cells are inherently heterogeneous in phenotype, and some phenotypic variables have an effect on division or survival rates, as can be seen in partial drug resistance. Therefore, when modeling population dynamics where the control of growth and division is phenotype dependent, the corresponding model must take account of the underlying cellular heterogeneity. The finite state projection (FSP) approach has often been used to analyze the statistics of independent cells. Here, we extend the FSP analysis to explore the coupling of cell dynamics and biomolecule dynamics within a population. This extension allows a general framework with which to model the state occupations of a heterogeneous, isogenic population of dividing and expiring cells. The method is demonstrated with a simple model of cell-cycle progression, which we use to explore possible dynamics of drug resistance phenotypes in dividing cells. We use this method to show how stochastic single-cell behaviors affect population level efficacy of drug treatments, and we illustrate how slight modifications to treatment regimens may have dramatic effects on drug efficacy.

The evolution of labile traits in sex- and age-structured populations.

PubMed

Childs, Dylan Z; Sheldon, Ben C; Rees, Mark

2016-03-01

Many quantitative traits are labile (e.g. somatic growth rate, reproductive timing and investment), varying over the life cycle as a result of behavioural adaptation, developmental processes and plastic responses to the environment. At the population level, selection can alter the distribution of such traits across age classes and among generations. Despite a growing body of theoretical research exploring the evolutionary dynamics of labile traits, a data-driven framework for incorporating such traits into demographic models has not yet been developed. Integral projection models (IPMs) are increasingly being used to understand the interplay between changes in labile characters, life histories and population dynamics. One limitation of the IPM approach is that it relies on phenotypic associations between parents and offspring traits to capture inheritance. However, it is well-established that many different processes may drive these associations, and currently, no clear consensus has emerged on how to model micro-evolutionary dynamics in an IPM framework. We show how to embed quantitative genetic models of inheritance of labile traits into age-structured, two-sex models that resemble standard IPMs. Commonly used statistical tools such as GLMs and their mixed model counterparts can then be used for model parameterization. We illustrate the methodology through development of a simple model of egg-laying date evolution, parameterized using data from a population of Great tits (Parus major). We demonstrate how our framework can be used to project the joint dynamics of species' traits and population density. We then develop a simple extension of the age-structured Price equation (ASPE) for two-sex populations, and apply this to examine the age-specific contributions of different processes to change in the mean phenotype and breeding value. The data-driven framework we outline here has the potential to facilitate greater insight into the nature of selection and its consequences in settings where focal traits vary over the lifetime through ontogeny, behavioural adaptation and phenotypic plasticity, as well as providing a potential bridge between theoretical and empirical studies of labile trait variation. © 2016 The Authors Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.

Controlled recovery of phylogenetic communities from an evolutionary model using a network approach

NASA Astrophysics Data System (ADS)

Sousa, Arthur M. Y. R.; Vieira, André P.; Prado, Carmen P. C.; Andrade, Roberto F. S.

2016-04-01

This works reports the use of a complex network approach to produce a phylogenetic classification tree of a simple evolutionary model. This approach has already been used to treat proteomic data of actual extant organisms, but an investigation of its reliability to retrieve a traceable evolutionary history is missing. The used evolutionary model includes key ingredients for the emergence of groups of related organisms by differentiation through random mutations and population growth, but purposefully omits other realistic ingredients that are not strictly necessary to originate an evolutionary history. This choice causes the model to depend only on a small set of parameters, controlling the mutation probability and the population of different species. Our results indicate that for a set of parameter values, the phylogenetic classification produced by the used framework reproduces the actual evolutionary history with a very high average degree of accuracy. This includes parameter values where the species originated by the evolutionary dynamics have modular structures. In the more general context of community identification in complex networks, our model offers a simple setting for evaluating the effects, on the efficiency of community formation and identification, of the underlying dynamics generating the network itself.

An overview of methods for developing bioenergetic and life history models for rare and endangered species

USGS Publications Warehouse

Petersen, J.H.; DeAngelis, D.L.; Paukert, C.P.

2008-01-01

Many fish species are at risk to some degree, and conservation efforts are planned or underway to preserve sensitive populations. For many imperiled species, models could serve as useful tools for researchers and managers as they seek to understand individual growth, quantify predator-prey dynamics, and identify critical sources of mortality. Development and application of models for rare species however, has been constrained by small population sizes, difficulty in obtaining sampling permits, limited opportunities for funding, and regulations on how endangered species can be used in laboratory studies. Bioenergetic and life history models should help with endangered species-recovery planning since these types of models have been used successfully in the last 25 years to address management problems for many commercially and recreationally important fish species. In this paper we discuss five approaches to developing models and parameters for rare species. Borrowing model functions and parameters from related species is simple, but uncorroborated results can be misleading. Directly estimating parameters with laboratory studies may be possible for rare species that have locally abundant populations. Monte Carlo filtering can be used to estimate several parameters by means of performing simple laboratory growth experiments to first determine test criteria. Pattern-oriented modeling (POM) is a new and developing field of research that uses field-observed patterns to build, test, and parameterize models. Models developed using the POM approach are closely linked to field data, produce testable hypotheses, and require a close working relationship between modelers and empiricists. Artificial evolution in individual-based models can be used to gain insight into adaptive behaviors for poorly understood species and thus can fill in knowledge gaps. ?? Copyright by the American Fisheries Society 2008.

Modeling Population and Ecosystem Response to Sublethal Toxicant Exposure

DTIC Science & Technology

2001-09-30

mutualism utilized modified Lotka - Volterra (L-V) competition equations in which the sign of the interspecific interaction term was changed from...within complex communities and ecosystems. Prior to the current award, the PIs formulated and tested general dynamic energy budget models...Nisbet, 1998; chapter 7) make a convincing case that ecosystems do truly have dynamics that can be described by relatively simple, general , models

An Automated Microfluidic Multiplexer for Fast Delivery of C. elegans Populations from Multiwells

PubMed Central

Ghorashian, Navid; Gökçe, Sertan Kutal; Guo, Sam Xun; Everett, William Neil; Ben-Yakar, Adela

2013-01-01

Automated biosorter platforms, including recently developed microfluidic devices, enable and accelerate high-throughput and/or high-resolution bioassays on small animal models. However, time-consuming delivery of different organism populations to these systems introduces a major bottleneck to executing large-scale screens. Current population delivery strategies rely on suction from conventional well plates through tubing periodically exposed to air, leading to certain disadvantages: 1) bubble introduction to the sample, interfering with analysis in the downstream system, 2) substantial time drain from added bubble-cleaning steps, and 3) the need for complex mechanical systems to manipulate well plate position. To address these concerns, we developed a multiwell-format microfluidic platform that can deliver multiple distinct animal populations from on-chip wells using multiplexed valve control. This Population Delivery Chip could operate autonomously as part of a relatively simple setup that did not require any of the major mechanical moving parts typical of plate-handling systems to address a given well. We demonstrated automatic serial delivery of 16 distinct C. elegans worm populations to a single outlet without introducing any bubbles to the samples, causing cross-contamination, or damaging the animals. The device achieved delivery of more than 90% of the population preloaded into a given well in 4.7 seconds; an order of magnitude faster than delivery modalities in current use. This platform could potentially handle other similarly sized model organisms, such as zebrafish and drosophila larvae or cellular micro-colonies. The device’s architecture and microchannel dimensions allow simple expansion for processing larger numbers of populations. PMID:24069313

A Complex-Valued Firing-Rate Model That Approximates the Dynamics of Spiking Networks

PubMed Central

Schaffer, Evan S.; Ostojic, Srdjan; Abbott, L. F.

2013-01-01

Firing-rate models provide an attractive approach for studying large neural networks because they can be simulated rapidly and are amenable to mathematical analysis. Traditional firing-rate models assume a simple form in which the dynamics are governed by a single time constant. These models fail to replicate certain dynamic features of populations of spiking neurons, especially those involving synchronization. We present a complex-valued firing-rate model derived from an eigenfunction expansion of the Fokker-Planck equation and apply it to the linear, quadratic and exponential integrate-and-fire models. Despite being almost as simple as a traditional firing-rate description, this model can reproduce firing-rate dynamics due to partial synchronization of the action potentials in a spiking model, and it successfully predicts the transition to spike synchronization in networks of coupled excitatory and inhibitory neurons. PMID:24204236

High school students' understanding and problem solving in population genetics

NASA Astrophysics Data System (ADS)

Soderberg, Patti D.

This study is an investigation of student understanding of population genetics and how students developed, used and revised conceptual models to solve problems. The students in this study participated in three rounds of problem solving. The first round involved the use of a population genetics model to predict the number of carriers in a population. The second round required them to revise their model of simple dominance population genetics to make inferences about populations containing three phenotype variations. The third round of problem solving required the students to revise their model of population genetics to explain anomalous data where the proportions of males and females with a trait varied significantly. As the students solved problems, they were involved in basic scientific processes as they observed population phenomena, constructed explanatory models to explain the data they observed, and attempted to persuade their peers as to the adequacy of their models. In this study, the students produced new knowledge about the genetics of a trait in a population through the revision and use of explanatory population genetics models using reasoning that was similar to what scientists do. The students learned, used and revised a model of Hardy-Weinberg equilibrium to generate and test hypotheses about the genetics of phenotypes given only population data. Students were also interviewed prior to and following instruction. This study suggests that a commonly held intuitive belief about the predominance of a dominant variation in populations is resistant to change, despite instruction and interferes with a student's ability to understand Hardy-Weinberg equilibrium and microevolution.

Geoscience Meets Social Science: A Flexible Data Driven Approach for Developing High Resolution Population Datasets at Global Scale

NASA Astrophysics Data System (ADS)

Rose, A.; McKee, J.; Weber, E.; Bhaduri, B. L.

2017-12-01

Leveraging decades of expertise in population modeling, and in response to growing demand for higher resolution population data, Oak Ridge National Laboratory is now generating LandScan HD at global scale. LandScan HD is conceived as a 90m resolution population distribution where modeling is tailored to the unique geography and data conditions of individual countries or regions by combining social, cultural, physiographic, and other information with novel geocomputation methods. Similarities among these areas are exploited in order to leverage existing training data and machine learning algorithms to rapidly scale development. Drawing on ORNL's unique set of capabilities, LandScan HD adapts highly mature population modeling methods developed for LandScan Global and LandScan USA, settlement mapping research and production in high-performance computing (HPC) environments, land use and neighborhood mapping through image segmentation, and facility-specific population density models. Adopting a flexible methodology to accommodate different geographic areas, LandScan HD accounts for the availability, completeness, and level of detail of relevant ancillary data. Beyond core population and mapped settlement inputs, these factors determine the model complexity for an area, requiring that for any given area, a data-driven model could support either a simple top-down approach, a more detailed bottom-up approach, or a hybrid approach.

Estimating population trends with a linear model: Technical comments

USGS Publications Warehouse

Sauer, John R.; Link, William A.; Royle, J. Andrew

2004-01-01

Controversy has sometimes arisen over whether there is a need to accommodate the limitations of survey design in estimating population change from the count data collected in bird surveys. Analyses of surveys such as the North American Breeding Bird Survey (BBS) can be quite complex; it is natural to ask if the complexity is necessary, or whether the statisticians have run amok. Bart et al. (2003) propose a very simple analysis involving nothing more complicated than simple linear regression, and contrast their approach with model-based procedures. We review the assumptions implicit to their proposed method, and document that these assumptions are unlikely to be valid for surveys such as the BBS. One fundamental limitation of a purely design-based approach is the absence of controls for factors that influence detection of birds at survey sites. We show that failure to model observer effects in survey data leads to substantial bias in estimation of population trends from BBS data for the 20 species that Bart et al. (2003) used as the basis of their simulations. Finally, we note that the simulations presented in Bart et al. (2003) do not provide a useful evaluation of their proposed method, nor do they provide a valid comparison to the estimating- equations alternative they consider.

Applying the compound Poisson process model to the reporting of injury-related mortality rates.

PubMed

Kegler, Scott R

2007-02-16

Injury-related mortality rate estimates are often analyzed under the assumption that case counts follow a Poisson distribution. Certain types of injury incidents occasionally involve multiple fatalities, however, resulting in dependencies between cases that are not reflected in the simple Poisson model and which can affect even basic statistical analyses. This paper explores the compound Poisson process model as an alternative, emphasizing adjustments to some commonly used interval estimators for population-based rates and rate ratios. The adjusted estimators involve relatively simple closed-form computations, which in the absence of multiple-case incidents reduce to familiar estimators based on the simpler Poisson model. Summary data from the National Violent Death Reporting System are referenced in several examples demonstrating application of the proposed methodology.

Applications of Perron-Frobenius theory to population dynamics.

PubMed

Li, Chi-Kwong; Schneider, Hans

2002-05-01

By the use of Perron-Frobenius theory, simple proofs are given of the Fundamental Theorem of Demography and of a theorem of Cushing and Yicang on the net reproductive rate occurring in matrix models of population dynamics. The latter result, which is closely related to the Stein-Rosenberg theorem in numerical linear algebra, is further refined with some additional nonnegative matrix theory. When the fertility matrix is scaled by the net reproductive rate, the growth rate of the model is $1$. More generally, we show how to achieve a given growth rate for the model by scaling the fertility matrix. Demographic interpretations of the results are given.

Consequences of increased longevity for wealth, fertility, and population growth

NASA Astrophysics Data System (ADS)

Bogojević, A.; Balaž, A.; Karapandža, R.

2008-01-01

We present, solve and numerically simulate a simple model that describes the consequences of increased longevity for fertility rates, population growth and the distribution of wealth in developed societies. We look at the consequences of the repeated use of life extension techniques and show that they represent a novel commodity whose introduction will profoundly influence key aspects of the economy and society in general. In particular, we uncover two phases within our simplified model, labeled as ‘mortal’ and ‘immortal’. Within the life extension scenario it is possible to have sustainable economic growth in a population of stable size, as a result of dynamical equilibrium between the two phases.

Simple deterministic models and applications. Comment on "Coupled disease-behavior dynamics on complex networks: A review" by Z. Wang et al.

NASA Astrophysics Data System (ADS)

Yang, Hyun Mo

2015-12-01

Currently, discrete modellings are largely accepted due to the access to computers with huge storage capacity and high performance processors and easy implementation of algorithms, allowing to develop and simulate increasingly sophisticated models. Wang et al. [7] present a review of dynamics in complex networks, focusing on the interaction between disease dynamics and human behavioral and social dynamics. By doing an extensive review regarding to the human behavior responding to disease dynamics, the authors briefly describe the complex dynamics found in the literature: well-mixed populations networks, where spatial structure can be neglected, and other networks considering heterogeneity on spatially distributed populations. As controlling mechanisms are implemented, such as social distancing due 'social contagion', quarantine, non-pharmaceutical interventions and vaccination, adaptive behavior can occur in human population, which can be easily taken into account in the dynamics formulated by networked populations.

A review of statistical updating methods for clinical prediction models.

PubMed

Su, Ting-Li; Jaki, Thomas; Hickey, Graeme L; Buchan, Iain; Sperrin, Matthew

2018-01-01

A clinical prediction model is a tool for predicting healthcare outcomes, usually within a specific population and context. A common approach is to develop a new clinical prediction model for each population and context; however, this wastes potentially useful historical information. A better approach is to update or incorporate the existing clinical prediction models already developed for use in similar contexts or populations. In addition, clinical prediction models commonly become miscalibrated over time, and need replacing or updating. In this article, we review a range of approaches for re-using and updating clinical prediction models; these fall in into three main categories: simple coefficient updating, combining multiple previous clinical prediction models in a meta-model and dynamic updating of models. We evaluated the performance (discrimination and calibration) of the different strategies using data on mortality following cardiac surgery in the United Kingdom: We found that no single strategy performed sufficiently well to be used to the exclusion of the others. In conclusion, useful tools exist for updating existing clinical prediction models to a new population or context, and these should be implemented rather than developing a new clinical prediction model from scratch, using a breadth of complementary statistical methods.

Minimum variance geographic sampling

NASA Technical Reports Server (NTRS)

Terrell, G. R. (Principal Investigator)

1980-01-01

Resource inventories require samples with geographical scatter, sometimes not as widely spaced as would be hoped. A simple model of correlation over distances is used to create a minimum variance unbiased estimate population means. The fitting procedure is illustrated from data used to estimate Missouri corn acreage.

Did the ever dead outnumber the living and when? A birth-and-death approach

NASA Astrophysics Data System (ADS)

Avan, Jean; Grosjean, Nicolas; Huillet, Thierry

2015-02-01

This paper is an attempt to formalize analytically the question raised in 'World Population Explained: Do Dead People Outnumber Living, Or Vice Versa?' Huffington Post, Howard (2012). We start developing simple deterministic Malthusian growth models of the problem (with birth and death rates either constant or time-dependent) before running into both linear birth and death Markov chain models and age-structured models.

External validation of a six simple variable model of stroke outcome and verification in hyper-acute stroke.

PubMed

Reid, J M; Gubitz, G J; Dai, D; Reidy, Y; Christian, C; Counsell, C; Dennis, M; Phillips, S J

2007-12-01

We aimed to validate a previously described six simple variable (SSV) model that was developed from acute and sub-acute stroke patients in our population that included hyper-acute stroke patients. A Stroke Outcome Study enrolled patients from 2001 to 2002. Functional status was assessed at 6 months using the modified Rankin Scale (mRS). SSV model performance was tested in our cohort. 538 acute ischaemic (87%) and haemorrhagic stroke patients were enrolled, 51% of whom presented to hospital within 6 h of symptom recognition. At 6 months post-stroke, 42% of patients had a good outcome (mRS < or = 2). Stroke patients presenting within 6 h of symptom recognition were significantly older with higher stroke severity. In our Stroke Outcome Study dataset, the SSV model had an area under the curve of 0.792 for 6 month outcomes and performed well for hyper-acute or post-acute stroke, age < or > or = 75 years, haemorrhagic or ischaemic stroke, men or women, moderate and severe stroke, but poorly for mild stroke. This study confirms the external validity of the SSV model in our hospital stroke population. This model can therefore be utilised for stratification in acute and hyper-acute stroke trials.

Mutant number distribution in an exponentially growing population

NASA Astrophysics Data System (ADS)

Keller, Peter; Antal, Tibor

2015-01-01

We present an explicit solution to a classic model of cell-population growth introduced by Luria and Delbrück (1943 Genetics 28 491-511) 70 years ago to study the emergence of mutations in bacterial populations. In this model a wild-type population is assumed to grow exponentially in a deterministic fashion. Proportional to the wild-type population size, mutants arrive randomly and initiate new sub-populations of mutants that grow stochastically according to a supercritical birth and death process. We give an exact expression for the generating function of the total number of mutants at a given wild-type population size. We present a simple expression for the probability of finding no mutants, and a recursion formula for the probability of finding a given number of mutants. In the ‘large population-small mutation’ limit we recover recent results of Kessler and Levine (2014 J. Stat. Phys. doi:10.1007/s10955-014-1143-3) for a fully stochastic version of the process.

A diffusion model of protected population on bilocal habitat with generalized resource

NASA Astrophysics Data System (ADS)

Vasilyev, Maxim D.; Trofimtsev, Yuri I.; Vasilyeva, Natalya V.

2017-11-01

A model of population distribution in a two-dimensional area divided by an ecological barrier, i.e. the boundaries of natural reserve, is considered. Distribution of the population is defined by diffusion, directed migrations and areal resource. The exchange of specimens occurs between two parts of the habitat. The mathematical model is presented in the form of a boundary value problem for a system of non-linear parabolic equations with variable parameters of diffusion and growth function. The splitting space variables, sweep method and simple iteration methods were used for the numerical solution of a system. A set of programs was coded in Python. Numerical simulation results for the two-dimensional unsteady non-linear problem are analyzed in detail. The influence of migration flow coefficients and functions of natural birth/death ratio on the distributions of population densities is investigated. The results of the research would allow to describe the conditions of the stable and sustainable existence of populations in bilocal habitat containing the protected and non-protected zones.

Spatial Evolution of Human Dialects

NASA Astrophysics Data System (ADS)

Burridge, James

2017-07-01

The geographical pattern of human dialects is a result of history. Here, we formulate a simple spatial model of language change which shows that the final result of this historical evolution may, to some extent, be predictable. The model shows that the boundaries of language dialect regions are controlled by a length minimizing effect analogous to surface tension, mediated by variations in population density which can induce curvature, and by the shape of coastline or similar borders. The predictability of dialect regions arises because these effects will drive many complex, randomized early states toward one of a smaller number of stable final configurations. The model is able to reproduce observations and predictions of dialectologists. These include dialect continua, isogloss bundling, fanning, the wavelike spread of dialect features from cities, and the impact of human movement on the number of dialects that an area can support. The model also provides an analytical form for Séguy's curve giving the relationship between geographical and linguistic distance, and a generalization of the curve to account for the presence of a population center. A simple modification allows us to analytically characterize the variation of language use by age in an area undergoing linguistic change.

Mathematics and mallard management

USGS Publications Warehouse

Cowardin, L.M.; Johnson, D.H.

1979-01-01

Waterfowl managers can effectively use simple population models to aid in making management decisions. We present a basic model of the change in population size as related to survival and recruitment. A management technique designed to increase survival of mallards (Anas platyrhynchos) by limiting harvest on the Chippewa National Forest, Minnesota, is used to illustrate the application of models in decision making. The analysis suggests that the management technique would be of limited effectiveness. In a 2nd example, the change in mallard population in central North Dakota is related to implementing programs to create dense nesting cover with or without supplementary predator control. The analysis suggests that large tracts of land would be required to achieve a hypothetical management objective of increasing harvest by 50% while maintaining a stable population. Less land would be required if predator reduction were used in combination with cover management, but questions about effectiveness and ecological implications of large scale predator reduction remain unresolved. The use of models as a guide to planning research responsive to the needs of management is illustrated.

Emergence of social complexity among coastal hunter-gatherers in the Atacama Desert of northern Chile

PubMed Central

Marquet, Pablo A.; Santoro, Calogero M.; Latorre, Claudio; Standen, Vivien G.; Abades, Sebastián R.; Rivadeneira, Marcelo M.; Arriaza, Bernardo; Hochberg, Michael E.

2012-01-01

The emergence of complex cultural practices in simple hunter-gatherer groups poses interesting questions on what drives social complexity and what causes the emergence and disappearance of cultural innovations. Here we analyze the conditions that underlie the emergence of artificial mummification in the Chinchorro culture in the coastal Atacama Desert in northern Chile and southern Peru. We provide empirical and theoretical evidence that artificial mummification appeared during a period of increased coastal freshwater availability and marine productivity, which caused an increase in human population size and accelerated the emergence of cultural innovations, as predicted by recent models of cultural and technological evolution. Under a scenario of increasing population size and extreme aridity (with little or no decomposition of corpses) a simple demographic model shows that dead individuals may have become a significant part of the landscape, creating the conditions for the manipulation of the dead that led to the emergence of complex mortuary practices. PMID:22891345

An Application of Epidemiological Modeling to Information Diffusion

NASA Astrophysics Data System (ADS)

McCormack, Robert; Salter, William

Messages often spread within a population through unofficial - particularly web-based - media. Such ideas have been termed "memes." To impede the flow of terrorist messages and to promote counter messages within a population, intelligence analysts must understand how messages spread. We used statistical language processing technologies to operationalize "memes" as latent topics in electronic text and applied epidemiological techniques to describe and analyze patterns of message propagation. We developed our methods and applied them to English-language newspapers and blogs in the Arab world. We found that a relatively simple epidemiological model can reproduce some dynamics of observed empirical relationships.

Biology as population dynamics: heuristics for transmission risk.

PubMed

Keebler, Daniel; Walwyn, David; Welte, Alex

2013-02-01

Population-type models, accounting for phenomena such as population lifetimes, mixing patterns, recruitment patterns, genetic evolution and environmental conditions, can be usefully applied to the biology of HIV infection and viral replication. A simple dynamic model can explore the effect of a vaccine-like stimulus on the mortality and infectiousness, which formally looks like fertility, of invading virions; the mortality of freshly infected cells; and the availability of target cells, all of which impact on the probability of infection. Variations on this model could capture the importance of the timing and duration of different key events in viral transmission, and hence be applied to questions of mucosal immunology. The dynamical insights and assumptions of such models are compatible with the continuum of between- and within-individual risks in sexual violence and may be helpful in making sense of the sparse data available on the association between HIV transmission and sexual violence. © 2012 John Wiley & Sons A/S.

Astrophysical Model Selection in Gravitational Wave Astronomy

NASA Technical Reports Server (NTRS)

Adams, Matthew R.; Cornish, Neil J.; Littenberg, Tyson B.

2012-01-01

Theoretical studies in gravitational wave astronomy have mostly focused on the information that can be extracted from individual detections, such as the mass of a binary system and its location in space. Here we consider how the information from multiple detections can be used to constrain astrophysical population models. This seemingly simple problem is made challenging by the high dimensionality and high degree of correlation in the parameter spaces that describe the signals, and by the complexity of the astrophysical models, which can also depend on a large number of parameters, some of which might not be directly constrained by the observations. We present a method for constraining population models using a hierarchical Bayesian modeling approach which simultaneously infers the source parameters and population model and provides the joint probability distributions for both. We illustrate this approach by considering the constraints that can be placed on population models for galactic white dwarf binaries using a future space-based gravitational wave detector. We find that a mission that is able to resolve approximately 5000 of the shortest period binaries will be able to constrain the population model parameters, including the chirp mass distribution and a characteristic galaxy disk radius to within a few percent. This compares favorably to existing bounds, where electromagnetic observations of stars in the galaxy constrain disk radii to within 20%.

Discussion and revision of the mathematical modeling tool described in the previously published article "Modeling HIV Transmission risk among Mozambicans prior to their initiating highly active antiretroviral therapy".

PubMed

Cassels, Susan; Pearson, Cynthia R; Kurth, Ann E; Martin, Diane P; Simoni, Jane M; Matediana, Eduardo; Gloyd, Stephen

2009-07-01

Mathematical models are increasingly used in social and behavioral studies of HIV transmission; however, model structures must be chosen carefully to best answer the question at hand and conclusions must be interpreted cautiously. In Pearson et al. (2007), we presented a simple analytically tractable deterministic model to estimate the number of secondary HIV infections stemming from a population of HIV-positive Mozambicans and to evaluate how the estimate would change under different treatment and behavioral scenarios. In a subsequent application of the model with a different data set, we observed that the model produced an unduly conservative estimate of the number of new HIV-1 infections. In this brief report, our first aim is to describe a revision of the model to correct for this underestimation. Specifically, we recommend adjusting the population-level sexually transmitted infection (STI) parameters to be applicable to the individual-level model specification by accounting for the proportion of individuals uninfected with an STI. In applying the revised model to the original data, we noted an estimated 40 infections/1000 HIV-positive persons per year (versus the original 23 infections/1000 HIV-positive persons per year). In addition, the revised model estimated that highly active antiretroviral therapy (HAART) along with syphilis and herpes simplex virus type 2 (HSV-2) treatments combined could reduce HIV-1 transmission by 72% (versus 86% according to the original model). The second aim of this report is to discuss the advantages and disadvantages of mathematical models in the field and the implications of model interpretation. We caution that simple models should be used for heuristic purposes only. Since these models do not account for heterogeneity in the population and significantly simplify HIV transmission dynamics, they should be used to describe general characteristics of the epidemic and demonstrate the importance or sensitivity of parameters in the model.

Generalized estimators of avian abundance from count survey data

USGS Publications Warehouse

Royle, J. Andrew

2004-01-01

I consider modeling avian abundance from spatially referenced bird count data collected according to common protocols such as capture?recapture, multiple observer, removal sampling and simple point counts. Small sample sizes and large numbers of parameters have motivated many analyses that disregard the spatial indexing of the data, and thus do not provide an adequate treatment of spatial structure. I describe a general framework for modeling spatially replicated data that regards local abundance as a random process, motivated by the view that the set of spatially referenced local populations (at the sample locations) constitute a metapopulation. Under this view, attention can be focused on developing a model for the variation in local abundance independent of the sampling protocol being considered. The metapopulation model structure, when combined with the data generating model, define a simple hierarchical model that can be analyzed using conventional methods. The proposed modeling framework is completely general in the sense that broad classes of metapopulation models may be considered, site level covariates on detection and abundance may be considered, and estimates of abundance and related quantities may be obtained for sample locations, groups of locations, unsampled locations. Two brief examples are given, the first involving simple point counts, and the second based on temporary removal counts. Extension of these models to open systems is briefly discussed.

A simple theoretical framework for understanding heterogeneous differentiation of CD4+ T cells

PubMed Central

2012-01-01

Background CD4+ T cells have several subsets of functional phenotypes, which play critical yet diverse roles in the immune system. Pathogen-driven differentiation of these subsets of cells is often heterogeneous in terms of the induced phenotypic diversity. In vitro recapitulation of heterogeneous differentiation under homogeneous experimental conditions indicates some highly regulated mechanisms by which multiple phenotypes of CD4+ T cells can be generated from a single population of naïve CD4+ T cells. Therefore, conceptual understanding of induced heterogeneous differentiation will shed light on the mechanisms controlling the response of populations of CD4+ T cells under physiological conditions. Results We present a simple theoretical framework to show how heterogeneous differentiation in a two-master-regulator paradigm can be governed by a signaling network motif common to all subsets of CD4+ T cells. With this motif, a population of naïve CD4+ T cells can integrate the signals from their environment to generate a functionally diverse population with robust commitment of individual cells. Notably, two positive feedback loops in this network motif govern three bistable switches, which in turn, give rise to three types of heterogeneous differentiated states, depending upon particular combinations of input signals. We provide three prototype models illustrating how to use this framework to explain experimental observations and make specific testable predictions. Conclusions The process in which several types of T helper cells are generated simultaneously to mount complex immune responses upon pathogenic challenges can be highly regulated, and a simple signaling network motif can be responsible for generating all possible types of heterogeneous populations with respect to a pair of master regulators controlling CD4+ T cell differentiation. The framework provides a mathematical basis for understanding the decision-making mechanisms of CD4+ T cells, and it can be helpful for interpreting experimental results. Mathematical models based on the framework make specific testable predictions that may improve our understanding of this differentiation system. PMID:22697466

Estimation of Thalamocortical and Intracortical Network Models from Joint Thalamic Single-Electrode and Cortical Laminar-Electrode Recordings in the Rat Barrel System

PubMed Central

Blomquist, Patrick; Devor, Anna; Indahl, Ulf G.; Ulbert, Istvan; Einevoll, Gaute T.; Dale, Anders M.

2009-01-01

A new method is presented for extraction of population firing-rate models for both thalamocortical and intracortical signal transfer based on stimulus-evoked data from simultaneous thalamic single-electrode and cortical recordings using linear (laminar) multielectrodes in the rat barrel system. Time-dependent population firing rates for granular (layer 4), supragranular (layer 2/3), and infragranular (layer 5) populations in a barrel column and the thalamic population in the homologous barreloid are extracted from the high-frequency portion (multi-unit activity; MUA) of the recorded extracellular signals. These extracted firing rates are in turn used to identify population firing-rate models formulated as integral equations with exponentially decaying coupling kernels, allowing for straightforward transformation to the more common firing-rate formulation in terms of differential equations. Optimal model structures and model parameters are identified by minimizing the deviation between model firing rates and the experimentally extracted population firing rates. For the thalamocortical transfer, the experimental data favor a model with fast feedforward excitation from thalamus to the layer-4 laminar population combined with a slower inhibitory process due to feedforward and/or recurrent connections and mixed linear-parabolic activation functions. The extracted firing rates of the various cortical laminar populations are found to exhibit strong temporal correlations for the present experimental paradigm, and simple feedforward population firing-rate models combined with linear or mixed linear-parabolic activation function are found to provide excellent fits to the data. The identified thalamocortical and intracortical network models are thus found to be qualitatively very different. While the thalamocortical circuit is optimally stimulated by rapid changes in the thalamic firing rate, the intracortical circuits are low-pass and respond most strongly to slowly varying inputs from the cortical layer-4 population. PMID:19325875

A simple generative model of collective online behavior.

PubMed

Gleeson, James P; Cellai, Davide; Onnela, Jukka-Pekka; Porter, Mason A; Reed-Tsochas, Felix

2014-07-22

Human activities increasingly take place in online environments, providing novel opportunities for relating individual behaviors to population-level outcomes. In this paper, we introduce a simple generative model for the collective behavior of millions of social networking site users who are deciding between different software applications. Our model incorporates two distinct mechanisms: one is associated with recent decisions of users, and the other reflects the cumulative popularity of each application. Importantly, although various combinations of the two mechanisms yield long-time behavior that is consistent with data, the only models that reproduce the observed temporal dynamics are those that strongly emphasize the recent popularity of applications over their cumulative popularity. This demonstrates--even when using purely observational data without experimental design--that temporal data-driven modeling can effectively distinguish between competing microscopic mechanisms, allowing us to uncover previously unidentified aspects of collective online behavior.

A simple generative model of collective online behavior

PubMed Central

Gleeson, James P.; Cellai, Davide; Onnela, Jukka-Pekka; Porter, Mason A.; Reed-Tsochas, Felix

2014-01-01

Human activities increasingly take place in online environments, providing novel opportunities for relating individual behaviors to population-level outcomes. In this paper, we introduce a simple generative model for the collective behavior of millions of social networking site users who are deciding between different software applications. Our model incorporates two distinct mechanisms: one is associated with recent decisions of users, and the other reflects the cumulative popularity of each application. Importantly, although various combinations of the two mechanisms yield long-time behavior that is consistent with data, the only models that reproduce the observed temporal dynamics are those that strongly emphasize the recent popularity of applications over their cumulative popularity. This demonstrates—even when using purely observational data without experimental design—that temporal data-driven modeling can effectively distinguish between competing microscopic mechanisms, allowing us to uncover previously unidentified aspects of collective online behavior. PMID:25002470

Terrestrial population models for ecological risk assessment: A state-of-the-art review

USGS Publications Warehouse

Emlen, J.M.

1989-01-01

Few attempts have been made to formulate models for predicting impacts of xenobiotic chemicals on wildlife populations. However, considerable effort has been invested in wildlife optimal exploitation models. Because death from intoxication has a similar effect on population dynamics as death by harvesting, these management models are applicable to ecological risk assessment. An underlying Leslie-matrix bookkeeping formulation is widely applicable to vertebrate wildlife populations. Unfortunately, however, the various submodels that track birth, death, and dispersal rates as functions of the physical, chemical, and biotic environment are by their nature almost inevitably highly species- and locale-specific. Short-term prediction of one-time chemical applications requires only information on mortality before and after contamination. In such cases a simple matrix formulation may be adequate for risk assessment. But generally, risk must be projected over periods of a generation or more. This precludes generic protocols for risk assessment and also the ready and inexpensive predictions of a chemical's influence on a given population. When designing and applying models for ecological risk assessment at the population level, the endpoints (output) of concern must be carefully and rigorously defined. The most easily accessible and appropriate endpoints are (1) pseudoextinction (the frequency or probability of a population falling below a prespecified density), and (2) temporal mean population density. Spatial and temporal extent of predicted changes must be clearly specified a priori to avoid apparent contradictions and confusion.

Density-dependence as a size-independent regulatory mechanism.

PubMed

de Vladar, Harold P

2006-01-21

The growth function of populations is central in biomathematics. The main dogma is the existence of density-dependence mechanisms, which can be modelled with distinct functional forms that depend on the size of the population. One important class of regulatory functions is the theta-logistic, which generalizes the logistic equation. Using this model as a motivation, this paper introduces a simple dynamical reformulation that generalizes many growth functions. The reformulation consists of two equations, one for population size, and one for the growth rate. Furthermore, the model shows that although population is density-dependent, the dynamics of the growth rate does not depend either on population size, nor on the carrying capacity. Actually, the growth equation is uncoupled from the population size equation, and the model has only two parameters, a Malthusian parameter rho and a competition coefficient theta. Distinct sign combinations of these parameters reproduce not only the family of theta-logistics, but also the van Bertalanffy, Gompertz and Potential Growth equations, among other possibilities. It is also shown that, except for two critical points, there is a general size-scaling relation that includes those appearing in the most important allometric theories, including the recently proposed Metabolic Theory of Ecology. With this model, several issues of general interest are discussed such as the growth of animal population, extinctions, cell growth and allometry, and the effect of environment over a population.

Excitatory and Inhibitory Interactions in Localized Populations of Model Neurons

PubMed Central

Wilson, Hugh R.; Cowan, Jack D.

1972-01-01

Coupled nonlinear differential equations are derived for the dynamics of spatially localized populations containing both excitatory and inhibitory model neurons. Phase plane methods and numerical solutions are then used to investigate population responses to various types of stimuli. The results obtained show simple and multiple hysteresis phenomena and limit cycle activity. The latter is particularly interesting since the frequency of the limit cycle oscillation is found to be a monotonic function of stimulus intensity. Finally, it is proved that the existence of limit cycle dynamics in response to one class of stimuli implies the existence of multiple stable states and hysteresis in response to a different class of stimuli. The relation between these findings and a number of experiments is discussed. PMID:4332108

Shot noise perturbations and mean first passage times between stable states.

PubMed

Drury, Kevin L S

2007-08-01

Predicting crossings between stable states is a central issue in population biology. Crossings from low-density to high-density equilibria are often associated with pest outbreaks, while the opposite crossings are often associated with population collapse of harvested species. Here I use a simple, bistable model to demonstrate a technique for estimating mean first passage times (MFPT) of thresholds, including boundaries between stable equilibria. The approach is based on stochastic "shot-noise" perturbations to the population and the MFPTs compare favorably with mean crossing times from Monte Carlo numerical solutions of the stochastically perturbed model. This agreement suggests that MFPT approximations can be used to quantify expected effects of species manipulations, whether the goal is pest control or sustainable harvest.

Signatures of positive selection: from selective sweeps at individual loci to subtle allele frequency changes in polygenic adaptation.

PubMed

Stephan, Wolfgang

2016-01-01

In the past 15 years, numerous methods have been developed to detect selective sweeps underlying adaptations. These methods are based on relatively simple population genetic models, including one or two loci at which positive directional selection occurs, and one or two marker loci at which the impact of selection on linked neutral variation is quantified. Information about the phenotype under selection is not included in these models (except for fitness). In contrast, in the quantitative genetic models of adaptation, selection acts on one or more phenotypic traits, such that a genotype-phenotype map is required to bridge the gap to population genetics theory. Here I describe the range of population genetic models from selective sweeps in a panmictic population of constant size to evolutionary traffic when simultaneous sweeps at multiple loci interfere, and I also consider the case of polygenic selection characterized by subtle allele frequency shifts at many loci. Furthermore, I present an overview of the statistical tests that have been proposed based on these population genetics models to detect evidence for positive selection in the genome. © 2015 John Wiley & Sons Ltd.

Poverty trap formed by the ecology of infectious diseases

PubMed Central

Bonds, Matthew H.; Keenan, Donald C.; Rohani, Pejman; Sachs, Jeffrey D.

2010-01-01

While most of the world has enjoyed exponential economic growth, more than one-sixth of the world is today roughly as poor as their ancestors were many generations ago. Widely accepted general explanations for the persistence of such poverty have been elusive and are needed by the international development community. Building on a well-established model of human infectious diseases, we show how formally integrating simple economic and disease ecology models can naturally give rise to poverty traps, where initial economic and epidemiological conditions determine the long-term trajectory of the health and economic development of a society. This poverty trap may therefore be broken by improving health conditions of the population. More generally, we demonstrate that simple human ecological models can help explain broad patterns of modern economic organization. PMID:20007179

The Star Formation Histories of Disk Galaxies: The Live, the Dead, and the Undead

DOE Office of Scientific and Technical Information (OSTI.GOV)

Oemler, Augustus Jr; Dressler, Alan; Abramson, Louis E.

We reexamine the properties of local galaxy populations using published surveys of star formation, structure, and gas content. After recalibrating star formation measures, we are able to reliably measure specific star formation rates well below that of the so-called “main sequence” of star formation versus mass. We find an unexpectedly large population of quiescent galaxies with star formation rates intermediate between the main sequence and passive populations and with disproportionately high star formation rates. We demonstrate that a tight main sequence is a natural outcome of most histories of star formation and has little astrophysical significance but that the quiescentmore » population requires additional astrophysics to explain its properties. Using a simple model for disk evolution based on the observed dependence of star formation on gas content in local galaxies, and assuming simple histories of cold gas inflow, we show that the evolution of galaxies away from the main sequence can be attributed to the depletion of gas due to star formation after a cutoff of gas inflow. The quiescent population is composed of galaxies in which the density of disk gas has fallen below a threshold for star formation probably set by disk stability. The evolution of galaxies beyond the quiescent state to gas exhaustion and the end of star formation requires another process, probably wind-driven mass loss. The environmental dependence of the three galaxy populations is consistent with recent numerical modeling, which indicates that cold gas inflows into galaxies are truncated at earlier epochs in denser environments.« less

App Usage Factor: A Simple Metric to Compare the Population Impact of Mobile Medical Apps.

PubMed

Lewis, Thomas Lorchan; Wyatt, Jeremy C

2015-08-19

One factor when assessing the quality of mobile apps is quantifying the impact of a given app on a population. There is currently no metric which can be used to compare the population impact of a mobile app across different health care disciplines. The objective of this study is to create a novel metric to characterize the impact of a mobile app on a population. We developed the simple novel metric, app usage factor (AUF), defined as the logarithm of the product of the number of active users of a mobile app with the median number of daily uses of the app. The behavior of this metric was modeled using simulated modeling in Python, a general-purpose programming language. Three simulations were conducted to explore the temporal and numerical stability of our metric and a simulated app ecosystem model using a simulated dataset of 20,000 apps. Simulations confirmed the metric was stable between predicted usage limits and remained stable at extremes of these limits. Analysis of a simulated dataset of 20,000 apps calculated an average value for the app usage factor of 4.90 (SD 0.78). A temporal simulation showed that the metric remained stable over time and suitable limits for its use were identified. A key component when assessing app risk and potential harm is understanding the potential population impact of each mobile app. Our metric has many potential uses for a wide range of stakeholders in the app ecosystem, including users, regulators, developers, and health care professionals. Furthermore, this metric forms part of the overall estimate of risk and potential for harm or benefit posed by a mobile medical app. We identify the merits and limitations of this metric, as well as potential avenues for future validation and research.

Life-history plasticity and sustainable exploitation: a theory of growth compensation applied to walleye management.

PubMed

Lester, Nigel P; Shuter, Brian J; Venturelli, Paul; Nadeau, Daniel

2014-01-01

A simple population model was developed to evaluate the role of plastic and evolutionary life-history changes on sustainable exploitation rates. Plastic changes are embodied in density-dependent compensatory adjustments to somatic growth rate and larval/juvenile survival, which can compensate for the reductions in reproductive lifetime and mean population fecundity that accompany the higher adult mortality imposed by exploitation. Evolutionary changes are embodied in the selective pressures that higher adult mortality imposes on age at maturity, length at maturity, and reproductive investment. Analytical development, based on a biphasic growth model, led to simple equations that show explicitly how sustainable exploitation rates are bounded by each of these effects. We show that density-dependent growth combined with a fixed length at maturity and fixed reproductive investment can support exploitation-driven mortality that is 80% of the level supported by evolutionary changes in maturation and reproductive investment. Sustainable fishing mortality is proportional to natural mortality (M) times the degree of density-dependent growth, as modified by both the degree of density-dependent early survival and the minimum harvestable length. We applied this model to estimate sustainable exploitation rates for North American walleye populations (Sander vitreus). Our analysis of demographic data from walleye populations spread across a broad latitudinal range indicates that density-dependent variation in growth rate can vary by a factor of 2. Implications of this growth response are generally consistent with empirical studies suggesting that optimal fishing mortality is approximately 0.75M for teleosts. This approach can be adapted to the management of other species, particularly when significant exploitation is imposed on many, widely distributed, but geographically isolated populations.

Population modeling and its role in toxicological studies

USGS Publications Warehouse

Sauer, John R.; Pendleton, Grey W.; Hoffman, David J.; Rattner, Barnett A.; Burton, G. Allen; Cairns, John

1995-01-01

A model could be defined as any abstraction from reality that is used to provide some insight into the real system. In this discussion, we will use a more specific definition that a model is a set of rules or assumptions, expressed as mathematical equations, that describe how animals survive and reproduce, including the external factors that affect these characteristics. A model simplifies a system, retaining essential components while eliminating parts that are not of interest. ecology has a rich history of using models to gain insight into populations, often borrowing both model structures and analysis methods from demographers and engineers. Much of the development of the models has been a consequence of mathematicians and physicists seeing simple analogies between their models and patterns in natural systems. Consequently, one major application of ecological modeling has been to emphasize the analysis of dynamics of often complex models to provide insight into theoretical aspects of ecology.1

A necessary condition for dispersal driven growth of populations with discrete patch dynamics.

PubMed

Guiver, Chris; Packman, David; Townley, Stuart

2017-07-07

We revisit the question of when can dispersal-induced coupling between discrete sink populations cause overall population growth? Such a phenomenon is called dispersal driven growth and provides a simple explanation of how dispersal can allow populations to persist across discrete, spatially heterogeneous, environments even when individual patches are adverse or unfavourable. For two classes of mathematical models, one linear and one non-linear, we provide necessary conditions for dispersal driven growth in terms of the non-existence of a common linear Lyapunov function, which we describe. Our approach draws heavily upon the underlying positive dynamical systems structure. Our results apply to both discrete- and continuous-time models. The theory is illustrated with examples and both biological and mathematical conclusions are drawn. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

[Orientation hypercolumns of the visual cortex: ring model].

PubMed

Smirnova, E Iu; Chizhov, A V

2011-01-01

A hypercolumn of the visual cortex is a functional unit formed of the neighbouring columns whose neurons respond to a stimulus of particular orientation. The function of the hypercolumn is to amplify the orientation tuning of visually evoked responses. According to the conventional simple model of a hypercolumn, neuronal populations with different orientation preferences are distributed on a ring. Every population is described by the frequency (FR) model. To determine the limitations of the FR-ring model, it was compared with a more detailed ring model, which takes into account the distribution of neurons of each population according to their voltage values. In the case of the leaky integrate-and-fire neurons, every neural population is described by the Fokker-Planck (FP) equation. The mapping of parameters was obtained. The simulations revealed differences in the behaviour of the two models. Contrary to the FR model, the model based on the Fokker-Planck equation reacts faster to a change in stimulus orientation. The Fokker-Planck ring model gives a steady-state solution in the form of waves of activity travelling on the ring, whereas the FR ring model presents amplitude instability for the same parameter set. The FR ring model reproduces the characteristic effects of the ring model: the virtual rotation and the symmetry breaking.

A modified chain binomial model to analyse the ongoing measles epidemic in Greece, July 2017 to February 2018

PubMed Central

Lytras, Theodore; Georgakopoulou, Theano; Tsiodras, Sotirios

2018-01-01

Greece is currently experiencing a large measles outbreak, in the context of multiple similar outbreaks across Europe. We devised and applied a modified chain-binomial epidemic model, requiring very simple data, to estimate the transmission parameters of this outbreak. Model results indicate sustained measles transmission among the Greek Roma population, necessitating a targeted mass vaccination campaign to halt further spread of the epidemic. Our model may be useful for other countries facing similar measles outbreaks. PMID:29717695

A modified chain binomial model to analyse the ongoing measles epidemic in Greece, July 2017 to February 2018.

PubMed

Lytras, Theodore; Georgakopoulou, Theano; Tsiodras, Sotirios

2018-04-01

Greece is currently experiencing a large measles outbreak, in the context of multiple similar outbreaks across Europe. We devised and applied a modified chain-binomial epidemic model, requiring very simple data, to estimate the transmission parameters of this outbreak. Model results indicate sustained measles transmission among the Greek Roma population, necessitating a targeted mass vaccination campaign to halt further spread of the epidemic. Our model may be useful for other countries facing similar measles outbreaks.

Interaction Analysis in MANOVA.

ERIC Educational Resources Information Center

Betz, M. Austin

Simultaneous test procedures (STPS for short) in the context of the unrestricted full rank general linear multivariate model for population cell means are introduced and utilized to analyze interactions in factorial designs. By appropriate choice of an implying hypothesis, it is shown how to test overall main effects, interactions, simple main,…

Population. Readings for Senior Secondary Social Studies. Updated 1989.

ERIC Educational Resources Information Center

Victoria International Development Education Association (British Columbia).

This document contains the information kit developed for the annual Model Summit Conferences for schools in the Victoria, British Columbia (Canada) and surrounding school districts. Materials germane to the conference topic were compiled and assembled for participants. The materials are of current interest, concise, simple and provide a balanced…

Academic Self-Efficacy Perceptions of Teacher Candidates

ERIC Educational Resources Information Center

Yesilyurt, Etem

2013-01-01

This study aims determining academic self-efficacy perception of teacher candidates. It is survey model. Population of the study consists of teacher candidates in 2010-2011 academic years at Ahmet Kelesoglu Education Faculty of Education Formation of Selcuk University. A simple random sample was selected as sampling method and the study was…

Estimation by capture-recapture of recruitment and dispersal over several sites

USGS Publications Warehouse

Lebreton, J.D.; Hines, J.E.; Pradel, R.; Nichols, J.D.; Spendelow, J.A.

2003-01-01

Dispersal in animal populations is intimately linked with accession to reproduction, i.e. recruitment, and population regulation. Dispersal processes are thus a key component of population dynamics to the same extent as reproduction or mortality processes. Despite the growing interest in spatial aspects of population dynamics, the methodology for estimating dispersal, in particular in relation with recruitment, is limited. In many animal populations, in particular vertebrates, the impossibility of following individuals over space and time in an exhaustive way leads to the need to frame the estimation of dispersal in the context of capture-recapture methodology. We present here a class of age-dependent multistate capture-recapture models for the simultaneous estimation of natal dispersal, breeding dispersal, and age-dependent recruitment. These models are suitable for populations in which individuals are marked at birth and then recaptured over several sites. Under simple constraints, they can be used in populations where non-breeders are not observed, as is often the case with colonial waterbirds monitored on their breeding grounds. Biological questions can be addressed by comparing models differing in structure, according to the generalized linear model philosophy broadly used in capture-recapture methodology. We illustrate the potential of this approach by an analysis of recruitment and dispersal in the roseate tern Sterna dougallii.

Population pharmacokinetics of busulfan in pediatric and young adult patients undergoing hematopoietic cell transplant: a model-based dosing algorithm for personalized therapy and implementation into routine clinical use.

PubMed

Long-Boyle, Janel R; Savic, Rada; Yan, Shirley; Bartelink, Imke; Musick, Lisa; French, Deborah; Law, Jason; Horn, Biljana; Cowan, Morton J; Dvorak, Christopher C

2015-04-01

Population pharmacokinetic (PK) studies of busulfan in children have shown that individualized model-based algorithms provide improved targeted busulfan therapy when compared with conventional dose guidelines. The adoption of population PK models into routine clinical practice has been hampered by the tendency of pharmacologists to develop complex models too impractical for clinicians to use. The authors aimed to develop a population PK model for busulfan in children that can reliably achieve therapeutic exposure (concentration at steady state) and implement a simple model-based tool for the initial dosing of busulfan in children undergoing hematopoietic cell transplantation. Model development was conducted using retrospective data available in 90 pediatric and young adult patients who had undergone hematopoietic cell transplantation with busulfan conditioning. Busulfan drug levels and potential covariates influencing drug exposure were analyzed using the nonlinear mixed effects modeling software, NONMEM. The final population PK model was implemented into a clinician-friendly Microsoft Excel-based tool and used to recommend initial doses of busulfan in a group of 21 pediatric patients prospectively dosed based on the population PK model. Modeling of busulfan time-concentration data indicates that busulfan clearance displays nonlinearity in children, decreasing up to approximately 20% between the concentrations of 250-2000 ng/mL. Important patient-specific covariates found to significantly impact busulfan clearance were actual body weight and age. The percentage of individuals achieving a therapeutic concentration at steady state was significantly higher in subjects receiving initial doses based on the population PK model (81%) than in historical controls dosed on conventional guidelines (52%) (P = 0.02). When compared with the conventional dosing guidelines, the model-based algorithm demonstrates significant improvement for providing targeted busulfan therapy in children and young adults.

Why Sex? — Monte Carlo Simulations of Survival after Catastrophes

NASA Astrophysics Data System (ADS)

Sá Martins, J. S.; de Oliveira, S. Moss

Using the Penna bit-string model for biological ageing we compare two kinds of reproductive regimes: Sexual reproduction (SR) and meiotic parthenogenesis (MP). The last one is a common type of asexual reproduction with recombination, found in diploid organisms. We show that although both regimes present roughly the same survival rates, the diversity generated by SR is much larger, and can prevent the extinction of a population submitted to a natural disaster. The fixation of bad genes inside an MP population, after many generations, explains our results. We also study the consequences of cloning (simple copy) on population diversity.

Changes of scaling relationships in an evolving population: The example of "sedimentary" stylolites

NASA Astrophysics Data System (ADS)

Peacock, D. C. P.; Korneva, I.; Nixon, C. W.; Rotevatn, A.

2017-03-01

Bed-parallel (;sedimentary;) stylolites are used as an example of a population that evolves by the addition of new components, their growth and their merger. It is shown that this style of growth controls the changes in the scaling relationships of the population. Stylolites tend to evolve in carbonate rocks through time, for example by compaction during progressive burial. The evolution of a population of stylolites, and their likely effects on porosity, are demonstrated using simple numerical models. Starting with a power-law distribution, the adding of new stylolites, the increase in their amplitudes and their merger decrease the slope of magnitude versus cumulative frequency of the population. The population changes to a non-power-law distribution as smaller stylolites merge to form larger stylolites. The results suggest that other populations can be forward- or backward-modelled, such as fault lengths, which also evolve by the addition of components, their growth and merger. Consideration of the ways in which populations change improves understanding of scaling relationships and vice versa, and would assist in the management of geofluid reservoirs.

Sustainability Indicators for Coupled Human-Earth Systems

NASA Astrophysics Data System (ADS)

Motesharrei, S.; Rivas, J. R.; Kalnay, E.

2014-12-01

Over the last two centuries, the Human System went from having a small impact on the Earth System (including the Climate System) to becoming dominant, because both population and per capita consumption have grown extremely fast, especially since about 1950. We therefore argue that Human System Models must be included into Earth System Models through bidirectional couplings with feedbacks. In particular, population should be modeled endogenously, rather than exogenously as done currently in most Integrated Assessment Models. The growth of the Human System threatens to overwhelm the Carrying Capacity of the Earth System, and may be leading to catastrophic climate change and collapse. We propose a set of Ecological and Economic "Sustainability Indicators" that can employ large data-sets for developing and assessing effective mitigation and adaptation policies. Using the Human and Nature Dynamical Model (HANDY) and Coupled Human-Climate-Water Model (COWA), we carry out experiments with this set of Sustainability Indicators and show that they are applicable to various coupled systems including Population, Climate, Water, Energy, Agriculture, and Economy. Impact of nonrenewable resources and fossil fuels could also be understood using these indicators. We demonstrate interconnections of Ecological and Economic Indicators. Coupled systems often include feedbacks and can thus display counterintuitive dynamics. This makes it difficult for even experts to see coming catastrophes from just the raw data for different variables. Sustainability Indicators boil down the raw data into a set of simple numbers that cross their sustainability thresholds with a large time-lag before variables enter their catastrophic regimes. Therefore, we argue that Sustainability Indicators constitute a powerful but simple set of tools that could be directly used for making policies for sustainability.

Description of a New Predictive Modeling Approach That Correlates the Risk and Associated Cost of Well-Defined Diabetes-Related Complications With Changes in Glycated Hemoglobin (HbA1c)

PubMed Central

Fortwaengler, Kurt; Parkin, Christopher G.; Neeser, Kurt; Neumann, Monika; Mast, Oliver

2017-01-01

The modeling approach described here is designed to support the development of spreadsheet-based simple predictive models. It is based on 3 pillars: association of the complications with HbA1c changes, incidence of the complications, and average cost per event of the complication. For each pillar, the goal of the analysis was (1) to find results for a large diversity of populations with a focus on countries/regions, diabetes type, age, diabetes duration, baseline HbA1c value, and gender; (2) to assess the range of incidences and associations previously reported. Unlike simple predictive models, which mostly are based on only 1 source of information for each of the pillars, we conducted a comprehensive, systematic literature review. Each source found was thoroughly reviewed and only sources meeting quality expectations were considered. The approach allows avoidance of unintended use of extreme data. The user can utilize (1) one of the found sources, (2) the found range as validation for the found figures, or (3) the average of all found publications for an expedited estimate. The modeling approach is intended for use in average insulin-treated diabetes populations in which the baseline HbA1c values are within an average range (6.5% to 11.5%); it is not intended for use in individuals or unique diabetes populations (eg, gestational diabetes). Because the modeling approach only considers diabetes-related complications that are positively associated with HbA1c decreases, the costs of negatively associated complications (eg, severe hypoglycemic events) must be calculated separately. PMID:27510441

Analytic derivation of bacterial growth laws from a simple model of intracellular chemical dynamics.

PubMed

Pandey, Parth Pratim; Jain, Sanjay

2016-09-01

Experiments have found that the growth rate and certain other macroscopic properties of bacterial cells in steady-state cultures depend upon the medium in a surprisingly simple manner; these dependencies are referred to as 'growth laws'. Here we construct a dynamical model of interacting intracellular populations to understand some of the growth laws. The model has only three population variables: an amino acid pool, a pool of enzymes that transport an external nutrient and produce the amino acids, and ribosomes that catalyze their own and the enzymes' production from the amino acids. We assume that the cell allocates its resources between the enzyme sector and the ribosomal sector to maximize its growth rate. We show that the empirical growth laws follow from this assumption and derive analytic expressions for the phenomenological parameters in terms of the more basic model parameters. Interestingly, the maximization of the growth rate of the cell as a whole implies that the cell allocates resources to the enzyme and ribosomal sectors in inverse proportion to their respective 'efficiencies'. The work introduces a mathematical scheme in which the cellular growth rate can be explicitly determined and shows that two large parameters, the number of amino acid residues per enzyme and per ribosome, are useful for making approximations.

Accounting for Space—Quantification of Cell-To-Cell Transmission Kinetics Using Virus Dynamics Models.

PubMed

Kumberger, Peter; Durso-Cain, Karina; Uprichard, Susan L; Dahari, Harel; Graw, Frederik

2018-04-17

Mathematical models based on ordinary differential equations (ODE) that describe the population dynamics of viruses and infected cells have been an essential tool to characterize and quantify viral infection dynamics. Although an important aspect of viral infection is the dynamics of viral spread, which includes transmission by cell-free virions and direct cell-to-cell transmission, models used so far ignored cell-to-cell transmission completely, or accounted for this process by simple mass-action kinetics between infected and uninfected cells. In this study, we show that the simple mass-action approach falls short when describing viral spread in a spatially-defined environment. Using simulated data, we present a model extension that allows correct quantification of cell-to-cell transmission dynamics within a monolayer of cells. By considering the decreasing proportion of cells that can contribute to cell-to-cell spread with progressing infection, our extension accounts for the transmission dynamics on a single cell level while still remaining applicable to standard population-based experimental measurements. While the ability to infer the proportion of cells infected by either of the transmission modes depends on the viral diffusion rate, the improved estimates obtained using our novel approach emphasize the need to correctly account for spatial aspects when analyzing viral spread.

Zero-inflated Poisson regression models for QTL mapping applied to tick-resistance in a Gyr × Holstein F2 population

PubMed Central

Silva, Fabyano Fonseca; Tunin, Karen P.; Rosa, Guilherme J.M.; da Silva, Marcos V.B.; Azevedo, Ana Luisa Souza; da Silva Verneque, Rui; Machado, Marco Antonio; Packer, Irineu Umberto

2011-01-01

Now a days, an important and interesting alternative in the control of tick-infestation in cattle is to select resistant animals, and identify the respective quantitative trait loci (QTLs) and DNA markers, for posterior use in breeding programs. The number of ticks/animal is characterized as a discrete-counting trait, which could potentially follow Poisson distribution. However, in the case of an excess of zeros, due to the occurrence of several noninfected animals, zero-inflated Poisson and generalized zero-inflated distribution (GZIP) may provide a better description of the data. Thus, the objective here was to compare through simulation, Poisson and ZIP models (simple and generalized) with classical approaches, for QTL mapping with counting phenotypes under different scenarios, and to apply these approaches to a QTL study of tick resistance in an F2 cattle (Gyr × Holstein) population. It was concluded that, when working with zero-inflated data, it is recommendable to use the generalized and simple ZIP model for analysis. On the other hand, when working with data with zeros, but not zero-inflated, the Poisson model or a data-transformation-approach, such as square-root or Box-Cox transformation, are applicable. PMID:22215960

Cell-Division Behavior in a Heterogeneous Swarm Environment.

PubMed

Erskine, Adam; Herrmann, J Michael

2015-01-01

We present a system of virtual particles that interact using simple kinetic rules. It is known that heterogeneous mixtures of particles can produce particularly interesting behaviors. Here we present a two-species three-dimensional swarm in which a behavior emerges that resembles cell division. We show that the dividing behavior exists across a narrow but finite band of parameters and for a wide range of population sizes. When executed in a two-dimensional environment the swarm's characteristics and dynamism manifest differently. In further experiments we show that repeated divisions can occur if the system is extended by a biased equilibrium process to control the split of populations. We propose that this repeated division behavior provides a simple model for cell-division mechanisms and is of interest for the formation of morphological structure and to swarm robotics.

Population-reaction model and microbial experimental ecosystems for understanding hierarchical dynamics of ecosystems.

PubMed

Hosoda, Kazufumi; Tsuda, Soichiro; Kadowaki, Kohmei; Nakamura, Yutaka; Nakano, Tadashi; Ishii, Kojiro

2016-02-01

Understanding ecosystem dynamics is crucial as contemporary human societies face ecosystem degradation. One of the challenges that needs to be recognized is the complex hierarchical dynamics. Conventional dynamic models in ecology often represent only the population level and have yet to include the dynamics of the sub-organism level, which makes an ecosystem a complex adaptive system that shows characteristic behaviors such as resilience and regime shifts. The neglect of the sub-organism level in the conventional dynamic models would be because integrating multiple hierarchical levels makes the models unnecessarily complex unless supporting experimental data are present. Now that large amounts of molecular and ecological data are increasingly accessible in microbial experimental ecosystems, it is worthwhile to tackle the questions of their complex hierarchical dynamics. Here, we propose an approach that combines microbial experimental ecosystems and a hierarchical dynamic model named population-reaction model. We present a simple microbial experimental ecosystem as an example and show how the system can be analyzed by a population-reaction model. We also show that population-reaction models can be applied to various ecological concepts, such as predator-prey interactions, climate change, evolution, and stability of diversity. Our approach will reveal a path to the general understanding of various ecosystems and organisms. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Dynamics of stochastic SEIS epidemic model with varying population size

NASA Astrophysics Data System (ADS)

Liu, Jiamin; Wei, Fengying

2016-12-01

We introduce the stochasticity into a deterministic model which has state variables susceptible-exposed-infected with varying population size in this paper. The infected individuals could return into susceptible compartment after recovering. We show that the stochastic model possesses a unique global solution under building up a suitable Lyapunov function and using generalized Itô's formula. The densities of the exposed and infected tend to extinction when some conditions are being valid. Moreover, the conditions of persistence to a global solution are derived when the parameters are subject to some simple criteria. The stochastic model admits a stationary distribution around the endemic equilibrium, which means that the disease will prevail. To check the validity of the main results, numerical simulations are demonstrated as end of this contribution.

Neutral null models for diversity in serial transfer evolution experiments.

PubMed

Harpak, Arbel; Sella, Guy

2014-09-01

Evolution experiments with microorganisms coupled with genome-wide sequencing now allow for the systematic study of population genetic processes under a wide range of conditions. In learning about these processes in natural, sexual populations, neutral models that describe the behavior of diversity and divergence summaries have played a pivotal role. It is therefore natural to ask whether neutral models, suitably modified, could be useful in the context of evolution experiments. Here, we introduce coalescent models for polymorphism and divergence under the most common experimental evolution assay, a serial transfer experiment. This relatively simple setting allows us to address several issues that could affect diversity patterns in evolution experiments, whether selection is operating or not: the transient behavior of neutral polymorphism in an experiment beginning from a single clone, the effects of randomness in the timing of cell division and noisiness in population size in the dilution stage. In our analyses and discussion, we emphasize the implications for experiments aimed at measuring diversity patterns and making inferences about population genetic processes based on these measurements. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Representation of limb kinematics in Purkinje cell simple spike discharge is conserved across multiple tasks

PubMed Central

Hewitt, Angela L.; Popa, Laurentiu S.; Pasalar, Siavash; Hendrix, Claudia M.

2011-01-01

Encoding of movement kinematics in Purkinje cell simple spike discharge has important implications for hypotheses of cerebellar cortical function. Several outstanding questions remain regarding representation of these kinematic signals. It is uncertain whether kinematic encoding occurs in unpredictable, feedback-dependent tasks or kinematic signals are conserved across tasks. Additionally, there is a need to understand the signals encoded in the instantaneous discharge of single cells without averaging across trials or time. To address these questions, this study recorded Purkinje cell firing in monkeys trained to perform a manual random tracking task in addition to circular tracking and center-out reach. Random tracking provides for extensive coverage of kinematic workspaces. Direction and speed errors are significantly greater during random than circular tracking. Cross-correlation analyses comparing hand and target velocity profiles show that hand velocity lags target velocity during random tracking. Correlations between simple spike firing from 120 Purkinje cells and hand position, velocity, and speed were evaluated with linear regression models including a time constant, τ, as a measure of the firing lead/lag relative to the kinematic parameters. Across the population, velocity accounts for the majority of simple spike firing variability (63 ± 30% of Radj2), followed by position (28 ± 24% of Radj2) and speed (11 ± 19% of Radj2). Simple spike firing often leads hand kinematics. Comparison of regression models based on averaged vs. nonaveraged firing and kinematics reveals lower Radj2 values for nonaveraged data; however, regression coefficients and τ values are highly similar. Finally, for most cells, model coefficients generated from random tracking accurately estimate simple spike firing in either circular tracking or center-out reach. These findings imply that the cerebellum controls movement kinematics, consistent with a forward internal model that predicts upcoming limb kinematics. PMID:21795616

In defence of model-based inference in phylogeography

PubMed Central

Beaumont, Mark A.; Nielsen, Rasmus; Robert, Christian; Hey, Jody; Gaggiotti, Oscar; Knowles, Lacey; Estoup, Arnaud; Panchal, Mahesh; Corander, Jukka; Hickerson, Mike; Sisson, Scott A.; Fagundes, Nelson; Chikhi, Lounès; Beerli, Peter; Vitalis, Renaud; Cornuet, Jean-Marie; Huelsenbeck, John; Foll, Matthieu; Yang, Ziheng; Rousset, Francois; Balding, David; Excoffier, Laurent

2017-01-01

Recent papers have promoted the view that model-based methods in general, and those based on Approximate Bayesian Computation (ABC) in particular, are flawed in a number of ways, and are therefore inappropriate for the analysis of phylogeographic data. These papers further argue that Nested Clade Phylogeographic Analysis (NCPA) offers the best approach in statistical phylogeography. In order to remove the confusion and misconceptions introduced by these papers, we justify and explain the reasoning behind model-based inference. We argue that ABC is a statistically valid approach, alongside other computational statistical techniques that have been successfully used to infer parameters and compare models in population genetics. We also examine the NCPA method and highlight numerous deficiencies, either when used with single or multiple loci. We further show that the ages of clades are carelessly used to infer ages of demographic events, that these ages are estimated under a simple model of panmixia and population stationarity but are then used under different and unspecified models to test hypotheses, a usage the invalidates these testing procedures. We conclude by encouraging researchers to study and use model-based inference in population genetics. PMID:29284924

Dynamic multipopulation and density dependent evolutionary games related to replicator dynamics. A metasimplex concept.

PubMed

Argasinski, Krzysztof

2006-07-01

This paper contains the basic extensions of classical evolutionary games (multipopulation and density dependent models). It is shown that classical bimatrix approach is inconsistent with other approaches because it does not depend on proportion between populations. The main conclusion is that interspecific proportion parameter is important and must be considered in multipopulation models. The paper provides a synthesis of both extensions (a metasimplex concept) which solves the problem intrinsic in the bimatrix model. It allows us to model interactions among any number of subpopulations including density dependence effects. We prove that all modern approaches to evolutionary games are closely related. All evolutionary models (except classical bimatrix approaches) can be reduced to a single population general model by a simple change of variables. Differences between classic bimatrix evolutionary games and a new model which is dependent on interspecific proportion are shown by examples.

Model of Yield Response of Corn to Plant Population and Absorption of Solar Energy

PubMed Central

Overman, Allen R.; Scholtz, Richard V.

2011-01-01

Biomass yield of agronomic crops is influenced by a number of factors, including crop species, soil type, applied nutrients, water availability, and plant population. This article is focused on dependence of biomass yield (Mg ha−1 and g plant−1) on plant population (plants m−2). Analysis includes data from the literature for three independent studies with the warm-season annual corn (Zea mays L.) grown in the United States. Data are analyzed with a simple exponential mathematical model which contains two parameters, viz. Ym (Mg ha−1) for maximum yield at high plant population and c (m2 plant−1) for the population response coefficient. This analysis leads to a new parameter called characteristic plant population, xc = 1/c (plants m−2). The model is shown to describe the data rather well for the three field studies. In one study measurements were made of solar radiation at different positions in the plant canopy. The coefficient of absorption of solar energy was assumed to be the same as c and provided a physical basis for the exponential model. The three studies showed no definitive peak in yield with plant population, but generally exhibited asymptotic approach to maximum yield with increased plant population. Values of xc were very similar for the three field studies with the same crop species. PMID:21297960

Controlling the light shift of the CPT resonance by modulation technique

NASA Astrophysics Data System (ADS)

Tsygankov, E. A.; Petropavlovsky, S. V.; Vaskovskaya, M. I.; Zibrov, S. A.; Velichansky, V. L.; Yakovlev, V. P.

2017-12-01

Motivated by recent developments in atomic frequency standards employing the effect of coherent population trapping (CPT), we propose a theoretical framework for the frequency modulation spectroscopy of the CPT resonances. Under realistic assumptions we provide simple yet non-trivial analytical formulae for the major spectroscopic signals such as the CPT resonance line and the in-phase/quadrature responses. We discuss the influence of the light shift and, in particular, derive a simple expression for the displacement of the resonance as a function of modulation index. The performance of the model is checked against numerical simulations, the agreement is good to perfect. The obtained results can be used in more general models accounting for light absorption in the thick optical medium.

Evolutionary dynamics of general group interactions in structured populations

NASA Astrophysics Data System (ADS)

Li, Aming; Broom, Mark; Du, Jinming; Wang, Long

2016-02-01

The evolution of populations is influenced by many factors, and the simple classical models have been developed in a number of important ways. Both population structure and multiplayer interactions have been shown to significantly affect the evolution of important properties, such as the level of cooperation or of aggressive behavior. Here we combine these two key factors and develop the evolutionary dynamics of general group interactions in structured populations represented by regular graphs. The traditional linear and threshold public goods games are adopted as models to address the dynamics. We show that for linear group interactions, population structure can favor the evolution of cooperation compared to the well-mixed case, and we see that the more neighbors there are, the harder it is for cooperators to persist in structured populations. We further show that threshold group interactions could lead to the emergence of cooperation even in well-mixed populations. Here population structure sometimes inhibits cooperation for the threshold public goods game, where depending on the benefit to cost ratio, the outcomes are bistability or a monomorphic population of defectors or cooperators. Our results suggest, counterintuitively, that structured populations are not always beneficial for the evolution of cooperation for nonlinear group interactions.

Active-to-absorbing-state phase transition in an evolving population with mutation.

PubMed

Sarkar, Niladri

2015-10-01

We study the active to absorbing phase transition (AAPT) in a simple two-component model system for a species and its mutant. We uncover the nontrivial critical scaling behavior and weak dynamic scaling near the AAPT that shows the significance of mutation and highlights the connection of this model with the well-known directed percolation universality class. Our model should be a useful starting point to study how mutation may affect extinction or survival of a species.

The Evaluation of Teachers' Job Performance Based on Total Quality Management (TQM)

ERIC Educational Resources Information Center

Shahmohammadi, Nayereh

2017-01-01

This study aimed to evaluate teachers' job performance based on total quality management (TQM) model. This was a descriptive survey study. The target population consisted of all primary school teachers in Karaj (N = 2917). Using Cochran formula and simple random sampling, 340 participants were selected as sample. A total quality management…

Exact Interval Estimation, Power Calculation, and Sample Size Determination in Normal Correlation Analysis

ERIC Educational Resources Information Center

Shieh, Gwowen

2006-01-01

This paper considers the problem of analysis of correlation coefficients from a multivariate normal population. A unified theorem is derived for the regression model with normally distributed explanatory variables and the general results are employed to provide useful expressions for the distributions of simple, multiple, and partial-multiple…

EVALUATING EFFECTS OF LOW QUALITY HABITATS ON REGIONAL GROWTH IN PEOMYCUS LEUCOPUS: INSIGHTS FROM FIELD-PARAMETERIZED SPATIAL MATRIX MODELS.

EPA Science Inventory

Due to complex population dynamics and source-sink metapopulation processes, animal fitness sometimes varies across landscapes in ways that cannot be deduced from simple density patterns. In this study, we examine spatial patterns in fitness using a combination of intensive fiel...

Disturbance-mediated competition between perennial plants along a resource supply gradient

Treesearch

J. Stephen Brewer

2011-01-01

Traditional views of ecological disturbance emphasize the role that physical disturbances play in reducing competition between populations and maintaining species coexistence. I present an alternative view that employs a simple Lotka–Volterra model to demonstrate how disturbance resistance, disturbance resilience and resource storage can increase competition between...

Characterization and Scaling of Black Carbon Aerosol Concentration with City Population Based on In-Situ Measurements and Analysis

NASA Astrophysics Data System (ADS)

Paredes-Miranda, G.; Arnott, W. P.; Moosmuller, H.

2010-12-01

The global trend toward urbanization and the resulting increase in city population has directed attention toward air pollution in megacities. A closely related question of importance for urban planning and attainment of air quality standards is how pollutant concentrations scale with city population. In this study, we use measurements of light absorption and light scattering coefficients as proxies for primary (i.e., black carbon; BC) and total (i.e., particulate matter; PM) pollutant concentration, to start addressing the following questions: What patterns and generalizations are emerging from our expanding data sets on urban air pollution? How does the per-capita air pollution vary with economic, geographic, and meteorological conditions of an urban area? Does air pollution provide an upper limit on city size? Diurnal analysis of black carbon concentration measurements in suburban Mexico City, Mexico, Las Vegas, NV, USA, and Reno, NV, USA for similar seasons suggests that commonly emitted primary air pollutant concentrations scale approximately as the square root of the urban population N, consistent with a simple 2-d box model. The measured absorption coefficient Babs is approximately proportional to the BC concentration (primary pollution) and thus scales with the square root of population (N). Since secondary pollutants form through photochemical reactions involving primary pollutants, they scale also with square root of N. Therefore the scattering coefficient Bsca, a proxy for PM concentration is also expected to scale with square root of N. Here we present light absorption and scattering measurements and data on meteorological conditions and compare the population scaling of these pollutant measurements with predictions from the simple 2-d box model. We find that these basin cities are connected by the square root of N dependence. Data from other cities will be discussed as time permits.

Modeling influenza-like illnesses through composite compartmental models

NASA Astrophysics Data System (ADS)

Levy, Nir; , Michael, Iv; Yom-Tov, Elad

2018-03-01

Epidemiological models for the spread of pathogens in a population are usually only able to describe a single pathogen. This makes their application unrealistic in cases where multiple pathogens with similar symptoms are spreading concurrently within the same population. Here we describe a method which makes possible the application of multiple single-strain models under minimal conditions. As such, our method provides a bridge between theoretical models of epidemiology and data-driven approaches for modeling of influenza and other similar viruses. Our model extends the Susceptible-Infected-Recovered model to higher dimensions, allowing the modeling of a population infected by multiple viruses. We further provide a method, based on an overcomplete dictionary of feasible realizations of SIR solutions, to blindly partition the time series representing the number of infected people in a population into individual components, each representing the effect of a single pathogen. We demonstrate the applicability of our proposed method on five years of seasonal influenza-like illness (ILI) rates, estimated from Twitter data. We demonstrate that our method describes, on average, 44% of the variance in the ILI time series. The individual infectious components derived from our model are matched to known viral profiles in the populations, which we demonstrate matches that of independently collected epidemiological data. We further show that the basic reproductive numbers (R 0) of the matched components are in range known for these pathogens. Our results suggest that the proposed method can be applied to other pathogens and geographies, providing a simple method for estimating the parameters of epidemics in a population.

The Puzzlingly Small Ca II Triplet Absorption in Elliptical Galaxies

NASA Astrophysics Data System (ADS)

Saglia, R. P.; Maraston, Claudia; Thomas, Daniel; Bender, Ralf; Colless, Matthew

2002-11-01

We measure the central values (within Re/8) of the Ca II triplet line indices CaT* and CaT and the Paschen index PaT at 8600 Å for a 93% complete sample of 75 nearby early-type galaxies with BT<12 mag and Vgal<2490 km s-1. We find that the values of CaT* are constant to within 5% over the range of central velocity dispersions 100 km s-1<=σ<=340 km s-1, while the PaT (and CaT) values are mildly anticorrelated with σ. Using simple and composite stellar population models, we show the following: (1) The measured CaT* and CaT are lower than expected from simple stellar population (SSP) models with Salpeter initial mass functions (IMFs) and with metallicities and ages derived from optical Lick (Fe, Mg, and Hβ) indices. Uncertainties in the calibration, the fitting functions, and the SSP modeling taken separately cannot explain the discrepancy. On average, the observed PaT values are within the range allowed by the models and the large uncertainties in the fitting functions. (2) The steepening of the IMF at low masses required to lower the CaT* and CaT indices to the observed values is incompatible with the measured FeH index at 9916 Å and the dynamical mass-to-light ratios of elliptical galaxies. (3) Composite stellar populations with a low-metallicity component reduce the disagreement, but rather artificial metallicity distributions are needed. Another explanation may be that calcium is indeed underabundant in elliptical galaxies.

Games among relatives revisited.

PubMed

Allen, Benjamin; Nowak, Martin A

2015-08-07

We present a simple model for the evolution of social behavior in family-structured, finite sized populations. Interactions are represented as evolutionary games describing frequency-dependent selection. Individuals interact more frequently with siblings than with members of the general population, as quantified by an assortment parameter r, which can be interpreted as "relatedness". Other models, mostly of spatially structured populations, have shown that assortment can promote the evolution of cooperation by facilitating interaction between cooperators, but this effect depends on the details of the evolutionary process. For our model, we find that sibling assortment promotes cooperation in stringent social dilemmas such as the Prisoner's Dilemma, but not necessarily in other situations. These results are obtained through straightforward calculations of changes in gene frequency. We also analyze our model using inclusive fitness. We find that the quantity of inclusive fitness does not exist for general games. For special games, where inclusive fitness exists, it provides less information than the straightforward analysis. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spread of a disease and its effect on population dynamics in an eco-epidemiological system

NASA Astrophysics Data System (ADS)

Upadhyay, Ranjit Kumar; Roy, Parimita

2014-12-01

In this paper, an eco-epidemiological model with simple law of mass action and modified Holling type II functional response has been proposed and analyzed to understand how a disease may spread among natural populations. The proposed model is a modification of the model presented by Upadhyay et al. (2008) [1]. Existence of the equilibria and their stability analysis (linear and nonlinear) has been studied. The dynamical transitions in the model have been studied by identifying the existence of backward Hopf-bifurcations and demonstrated the period-doubling route to chaos when the death rate of predator (μ1) and the growth rate of susceptible prey population (r) are treated as bifurcation parameters. Our studies show that the system exhibits deterministic chaos when some control parameters attain their critical values. Chaotic dynamics is depicted using the 2D parameter scans and bifurcation analysis. Possible implications of the results for disease eradication or its control are discussed.

Testing the uniqueness of mass models using gravitational lensing

NASA Astrophysics Data System (ADS)

Walls, Levi; Williams, Liliya L. R.

2018-06-01

The positions of images produced by the gravitational lensing of background-sources provide insight to lens-galaxy mass distributions. Simple elliptical mass density profiles do not agree well with observations of the population of known quads. It has been shown that the most promising way to reconcile this discrepancy is via perturbations away from purely elliptical mass profiles by assuming two super-imposed, somewhat misaligned mass distributions: one is dark matter (DM), the other is a stellar distribution. In this work, we investigate if mass modelling of individual lenses can reveal if the lenses have this type of complex structure, or simpler elliptical structure. In other words, we test mass model uniqueness, or how well an extended source lensed by a non-trivial mass distribution can be modeled by a simple elliptical mass profile. We used the publicly-available lensing software, Lensmodel, to generate and numerically model gravitational lenses and “observed” image positions. We then compared “observed” and modeled image positions via root mean square (RMS) of their difference. We report that, in most cases, the RMS is ≤0.05‧‧ when averaged over an extended source. Thus, we show it is possible to fit a smooth mass model to a system that contains a stellar-component with varying levels of misalignment with a DM-component, and hence mass modelling cannot differentiate between simple elliptical versus more complex lenses.

Analysis of bacterial migration. 2: Studies with multiple attractant gradients

DOE Office of Scientific and Technical Information (OSTI.GOV)

Strauss, I.; Frymier, P.D.; Hahn, C.M.

1995-02-01

Many motile bacteria exhibit chemotaxis, the ability to bias their random motion toward or away from increasing concentrations of chemical substances which benefit or inhibit their survival, respectively. Since bacteria encounter numerous chemical concentration gradients simultaneously in natural surroundings, it is necessary to know quantitatively how a bacterial population responds in the presence of more than one chemical stimulus to develop predictive mathematical models describing bacterial migration in natural systems. This work evaluates three hypothetical models describing the integration of chemical signals from multiple stimuli: high sensitivity, maximum signal, and simple additivity. An expression for the tumbling probability for individualmore » stimuli is modified according to the proposed models and incorporated into the cell balance equation for a 1-D attractant gradient. Random motility and chemotactic sensitivity coefficients, required input parameters for the model, are measured for single stimulus responses. Theoretical predictions with the three signal integration models are compared to the net chemotactic response of Escherichia coli to co- and antidirectional gradients of D-fucose and [alpha]-methylaspartate in the stopped-flow diffusion chamber assay. Results eliminate the high-sensitivity model and favor the simple additivity over the maximum signal. None of the simple models, however, accurately predict the observed behavior, suggesting a more complex model with more steps in the signal processing mechanism is required to predict responses to multiple stimuli.« less

Use of a simple pharmacokinetic model to study the impact of breast-feeding on infant and toddler body burdens of PCB 153, BDE 47, and DDE.

PubMed

Lorber, Matthew; Toms, Leisa-Maree L

2017-10-01

Several studies have examined the role of breast milk consumption in the buildup of environmental chemicals in infants, and have concluded that this pathway elevates infant body burdens above what would occur in a formula-only diet. Unique data from Australia provide an opportunity to study this finding using simple pharmacokinetic (PK) models. Pooled serum samples from infants in the general population provided data on PCB 153, BDE 47, and DDE at 6-month increments from birth until 4 years of age. General population breast-feeding scenarios for Australian conditions were crafted and input into a simple PK model which predicted infant serum concentrations over time. Comparison scenarios of background exposures to characterize formula-feeding were also crafted. It was found that the models were able to replicate the rise in measured infant body burdens for PCB 153 and DDE in the breast-feeding scenarios, while the background scenarios resulted in infant body burdens substantially below the measurements. The same was not true for BDE 47, however. Both the breast-feeding and background scenarios substantially underpredicted body burden measurements. Two possible explanations were offered: that exposure to higher BDE congeners would debrominate and form BDE 47 in the body, and/or, a second overlooked exposure pathway for PBDEs might be the cause of high infant and toddler body burdens. This pathway was inhalation due to the use of PBDEs as flame retardants in bedding materials. More research to better understand and quantify this pathway, or other unknown pathways, to describe infant and toddler exposures to PBDEs is needed. Published by Elsevier Ltd.

Benchmarking novel approaches for modelling species range dynamics

PubMed Central

Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H.; Moore, Kara A.; Zimmermann, Niklaus E.

2016-01-01

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species’ range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species’ response to climate change but also emphasise several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches operational for large numbers of species. PMID:26872305

Benchmarking novel approaches for modelling species range dynamics.

PubMed

Zurell, Damaris; Thuiller, Wilfried; Pagel, Jörn; Cabral, Juliano S; Münkemüller, Tamara; Gravel, Dominique; Dullinger, Stefan; Normand, Signe; Schiffers, Katja H; Moore, Kara A; Zimmermann, Niklaus E

2016-08-01

Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches operational for large numbers of species. © 2016 John Wiley & Sons Ltd.

Quantitative investigations of the epidemiology of phocine distemper virus (PDV) in European common seal populations.

PubMed

Grenfell, B T; Lonergan, M E; Harwood, J

1992-04-20

This paper uses simple mathematical models to examine the long-term dynamic consequences of the 1988 epizootic of phocine distemper virus (PDV) infection in Northern European common seal populations. In a preliminary analysis of single outbreaks of infection deterministic compartmental models are used to estimate feasible ranges for the transmission rate of the infection and the level of disease-induced mortality. These results also indicate that the level of transmission in 1988 was probably sufficient to eradicate the infection throughout the Northern European common seal populations by the end of the first outbreak. An analysis of longer-term infection dynamics, which takes account of the density-dependent recovery of seal population levels, corroborates this finding. It also indicates that a reintroduction of the virus would be unlikely to cause an outbreak on the scale of the 1988 epizootic until the seal population had recovered for at least 10 years. The general ecological implications of these results are discussed.

A Biologically Informed, Mechanistic Model of Desert Shrub Population Dynamics Bearing on Arid Landscape Evolution

NASA Astrophysics Data System (ADS)

Worman, Stacey; Furbish, David; Fathel, Siobhan

2014-05-01

In arid landscapes, desert shrubs individually and collectively modify how sediment is transported (e.g by wind, overland-flow, and rain-splash). Addressing how desert shrubs modify landscapes on geomorphic timescales therefore necessitates spanning multiple shrub lifetimes and accounting for how processes affecting shrub dynamics on these longer timescales (e.g. fire, grazing, drought, and climate change) may in turn impact sediment transport. To fulfill this need, we present a mechanistic model of the spatiotemporal dynamics of a desert-shrub population that uses a simple accounting framework and tracks individual shrubs as they enter, age, and exit the population (via recruitment, growth, and mortality). Our model is novel insomuch as it (1) features a strong biophysical foundation, (2) mimics well-documented aspects of how shrub populations respond to changes in precipitation, and (3) possesses the process granularity appropriate for use in geomorphic simulations. In a complimentary abstract (Fathel et al. 2014), we demonstrate the potential of this biological model by coupling it to a physical model of rain-splash sediment transport: We mechanistically reproduce the empirical observation that the erosion rate of a hillslope decreases as its vegetation coverage increases and we predict erosion rates under different climate-change scenarios.

Han's model parameters for microalgae grown under intermittent illumination: Determined using particle swarm optimization.

PubMed

Pozzobon, Victor; Perre, Patrick

2018-01-21

This work provides a model and the associated set of parameters allowing for microalgae population growth computation under intermittent lightning. Han's model is coupled with a simple microalgae growth model to yield a relationship between illumination and population growth. The model parameters were obtained by fitting a dataset available in literature using Particle Swarm Optimization method. In their work, authors grew microalgae in excess of nutrients under flashing conditions. Light/dark cycles used for these experimentations are quite close to those found in photobioreactor, i.e. ranging from several seconds to one minute. In this work, in addition to producing the set of parameters, Particle Swarm Optimization robustness was assessed. To do so, two different swarm initialization techniques were used, i.e. uniform and random distribution throughout the search-space. Both yielded the same results. In addition, swarm distribution analysis reveals that the swarm converges to a unique minimum. Thus, the produced set of parameters can be trustfully used to link light intensity to population growth rate. Furthermore, the set is capable to describe photodamages effects on population growth. Hence, accounting for light overexposure effect on algal growth. Copyright © 2017 Elsevier Ltd. All rights reserved.

Application of network methods for understanding evolutionary dynamics in discrete habitats.

PubMed

Greenbaum, Gili; Fefferman, Nina H

2017-06-01

In populations occupying discrete habitat patches, gene flow between habitat patches may form an intricate population structure. In such structures, the evolutionary dynamics resulting from interaction of gene-flow patterns with other evolutionary forces may be exceedingly complex. Several models describing gene flow between discrete habitat patches have been presented in the population-genetics literature; however, these models have usually addressed relatively simple settings of habitable patches and have stopped short of providing general methodologies for addressing nontrivial gene-flow patterns. In the last decades, network theory - a branch of discrete mathematics concerned with complex interactions between discrete elements - has been applied to address several problems in population genetics by modelling gene flow between habitat patches using networks. Here, we present the idea and concepts of modelling complex gene flows in discrete habitats using networks. Our goal is to raise awareness to existing network theory applications in molecular ecology studies, as well as to outline the current and potential contribution of network methods to the understanding of evolutionary dynamics in discrete habitats. We review the main branches of network theory that have been, or that we believe potentially could be, applied to population genetics and molecular ecology research. We address applications to theoretical modelling and to empirical population-genetic studies, and we highlight future directions for extending the integration of network science with molecular ecology. © 2017 John Wiley & Sons Ltd.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kim, K. S.; Nakae, L. F.; Prasad, M. K.

Here, we solve a simple theoretical model of time evolving fission chains due to Feynman that generalizes and asymptotically approaches the point model theory. The point model theory has been used to analyze thermal neutron counting data. This extension of the theory underlies fast counting data for both neutrons and gamma rays from metal systems. Fast neutron and gamma-ray counting is now possible using liquid scintillator arrays with nanosecond time resolution. For individual fission chains, the differential equations describing three correlated probability distributions are solved: the time-dependent internal neutron population, accumulation of fissions in time, and accumulation of leaked neutronsmore » in time. Explicit analytic formulas are given for correlated moments of the time evolving chain populations. The equations for random time gate fast neutron and gamma-ray counting distributions, due to randomly initiated chains, are presented. Correlated moment equations are given for both random time gate and triggered time gate counting. There are explicit formulas for all correlated moments are given up to triple order, for all combinations of correlated fast neutrons and gamma rays. The nonlinear differential equations for probabilities for time dependent fission chain populations have a remarkably simple Monte Carlo realization. A Monte Carlo code was developed for this theory and is shown to statistically realize the solutions to the fission chain theory probability distributions. Combined with random initiation of chains and detection of external quanta, the Monte Carlo code generates time tagged data for neutron and gamma-ray counting and from these data the counting distributions.« less

Analytical model for minority games with evolutionary learning

NASA Astrophysics Data System (ADS)

Campos, Daniel; Méndez, Vicenç; Llebot, Josep E.; Hernández, Germán A.

2010-06-01

In a recent work [D. Campos, J.E. Llebot, V. Méndez, Theor. Popul. Biol. 74 (2009) 16] we have introduced a biological version of the Evolutionary Minority Game that tries to reproduce the intraspecific competition for limited resources in an ecosystem. In comparison with the complex decision-making mechanisms used in standard Minority Games, only two extremely simple strategies ( juveniles and adults) are accessible to the agents. Complexity is introduced instead through an evolutionary learning rule that allows younger agents to learn taking better decisions. We find that this game shows many of the typical properties found for Evolutionary Minority Games, like self-segregation behavior or the existence of an oscillation phase for a certain range of the parameter values. However, an analytical treatment becomes much easier in our case, taking advantage of the simple strategies considered. Using a model consisting of a simple dynamical system, the phase diagram of the game (which differentiates three phases: adults crowd, juveniles crowd and oscillations) is reproduced.

Using Spin to Understand the Formation of LIGO and Virgo’s Black Holes

NASA Astrophysics Data System (ADS)

Farr, Ben; Holz, Daniel E.; Farr, Will M.

2018-02-01

With the growing number of binary black hole (BBH) mergers detected by the Advanced LIGO and Virgo detectors, it is becoming possible to constrain the properties of the underlying population and better understand the formation of these systems. Black hole (BH) spin orientations are one of the cleanest discriminators of formation history, with BHs in dynamically formed binaries in dense stellar environments expected to have spins distributed isotropically, in contrast to isolated populations where stellar evolution is expected to induce spins preferentially aligned with the orbital angular momentum. In this work, we propose a simple, model-agnostic approach to characterizing the spin properties of LIGO/Virgo’s BBH population. Using measurements of the effective spin of the binaries, we introduce a simple parameter to quantify the fraction of the population that is isotropically distributed, regardless of the spin magnitude distribution of the population. Once the orientation characteristics of the population have been determined, we show how measurements of effective spin can be used to directly constrain the BH spin magnitude distribution. We find that most effective spin measurements are too small to be informative, with the first four events showing a slight preference for a population with alignment, with an odds ratio of 1.2. We argue that it will be possible to distinguish symmetric and anti-symmetric populations at high confidence with tens of additional detections, although mixed populations may take significantly longer to disentangle. We also derive BH spin magnitude distributions from LIGO’s first four BBHs under the assumption of aligned or isotropic populations.

Learning Natural Selection in 4th Grade with Multi-Agent-Based Computational Models

NASA Astrophysics Data System (ADS)

Dickes, Amanda Catherine; Sengupta, Pratim

2013-06-01

In this paper, we investigate how elementary school students develop multi-level explanations of population dynamics in a simple predator-prey ecosystem, through scaffolded interactions with a multi-agent-based computational model (MABM). The term "agent" in an MABM indicates individual computational objects or actors (e.g., cars), and these agents obey simple rules assigned or manipulated by the user (e.g., speeding up, slowing down, etc.). It is the interactions between these agents, based on the rules assigned by the user, that give rise to emergent, aggregate-level behavior (e.g., formation and movement of the traffic jam). Natural selection is such an emergent phenomenon, which has been shown to be challenging for novices (K16 students) to understand. Whereas prior research on learning evolutionary phenomena with MABMs has typically focused on high school students and beyond, we investigate how elementary students (4th graders) develop multi-level explanations of some introductory aspects of natural selection—species differentiation and population change—through scaffolded interactions with an MABM that simulates predator-prey dynamics in a simple birds-butterflies ecosystem. We conducted a semi-clinical interview based study with ten participants, in which we focused on the following: a) identifying the nature of learners' initial interpretations of salient events or elements of the represented phenomena, b) identifying the roles these interpretations play in the development of their multi-level explanations, and c) how attending to different levels of the relevant phenomena can make explicit different mechanisms to the learners. In addition, our analysis also shows that although there were differences between high- and low-performing students (in terms of being able to explain population-level behaviors) in the pre-test, these differences disappeared in the post-test.

A simple expression for quantifying bacterial chemotaxis using capillary assay data: application to the analysis of enhanced chemotactic responses from growth-limited cultures.

PubMed

Ford, R M; Lauffenburger, D A

1992-05-01

An individual cell-based mathematical model of Rivero et al. provides a framework for determining values of the chemotactic sensitivity coefficient chi 0, an intrinsic cell population parameter that characterizes the chemotactic response of bacterial populations. This coefficient can theoretically relate the swimming behavior of individual cells to the resulting migration of a bacterial population. When this model is applied to the commonly used capillary assay, an approximate solution can be obtained for a particular range of chemotactic strengths yielding a very simple analytical expression for estimating the value of chi 0, [formula: see text] from measurements of cell accumulation in the capillary, N, when attractant uptake is negligible. A0 and A infinity are the dimensionless attractant concentrations initially present at the mouth of the capillary and far into the capillary, respectively, which are scaled by Kd, the effective dissociation constant for receptor-attractant binding. D is the attractant diffusivity, and mu is the cell random motility coefficient. NRM is the cell accumulation in the capillary in the absence of an attractant gradient, from which mu can be determined independently as mu = (pi/4t)(NRM/pi r2bc)2, with r the capillary tube radius and bc the bacterial density initially in the chamber. When attractant uptake is significant, a slightly more involved procedure requiring a simple numerical integration becomes necessary. As an example, we apply this approach to quantitatively characterize, in terms of the chemotactic sensitivity coefficient chi 0, data from Terracciano indicating enhanced chemotactic responses of Escherichia coli to galactose when cultured under growth-limiting galactose levels in a chemostat.

Mass and Environment as Drivers of Galaxy Evolution: Simplicity and its Consequences

NASA Astrophysics Data System (ADS)

Peng, Yingjie

2012-01-01

The galaxy population appears to be composed of infinitely complex different types and properties at first sight, however, when large samples of galaxies are studied, it appears that the vast majority of galaxies just follow simple scaling relations and similar evolutional modes while the outliers represent some minority. The underlying simplicities of the interrelationships among stellar mass, star formation rate and environment are seen in SDSS and zCOSMOS. We demonstrate that the differential effects of mass and environment are completely separable to z 1, indicating that two distinct physical processes are operating, namely the "mass quenching" and "environment quenching". These two simple quenching processes, plus some additional quenching due to merging, then naturally produce the Schechter form of the galaxy stellar mass functions and make quantitative predictions for the inter-relationships between the Schechter parameters of star-forming and passive galaxies in different environments. All of these detailed quantitative relationships are indeed seen, to very high precision, in SDSS, lending strong support to our simple empirically-based model. The model also offers qualitative explanations for the "anti-hierarchical" age-mass relation and the alpha-enrichment patterns for passive galaxies and makes some other testable predictions such as the mass function of the population of transitory objects that are in the process of being quenched, the galaxy major- and minor-merger rates, the galaxy stellar mass assembly history, star formation history and etc. Although still purely phenomenological, the model makes clear what the evolutionary characteristics of the relevant physical processes must in fact be.

Does lake size matter? Combining morphology and process modeling to examine the contribution of lake classes to population-scale processes

USGS Publications Warehouse

Winslow, Luke A.; Read, Jordan S.; Hanson, Paul C.; Stanley, Emily H.

2014-01-01

With lake abundances in the thousands to millions, creating an intuitive understanding of the distribution of morphology and processes in lakes is challenging. To improve researchers’ understanding of large-scale lake processes, we developed a parsimonious mathematical model based on the Pareto distribution to describe the distribution of lake morphology (area, perimeter and volume). While debate continues over which mathematical representation best fits any one distribution of lake morphometric characteristics, we recognize the need for a simple, flexible model to advance understanding of how the interaction between morphometry and function dictates scaling across large populations of lakes. These models make clear the relative contribution of lakes to the total amount of lake surface area, volume, and perimeter. They also highlight the critical thresholds at which total perimeter, area and volume would be evenly distributed across lake size-classes have Pareto slopes of 0.63, 1 and 1.12, respectively. These models of morphology can be used in combination with models of process to create overarching “lake population” level models of process. To illustrate this potential, we combine the model of surface area distribution with a model of carbon mass accumulation rate. We found that even if smaller lakes contribute relatively less to total surface area than larger lakes, the increasing carbon accumulation rate with decreasing lake size is strong enough to bias the distribution of carbon mass accumulation towards smaller lakes. This analytical framework provides a relatively simple approach to upscaling morphology and process that is easily generalizable to other ecosystem processes.

Using a new high resolution regional model for malaria that accounts for population density and surface hydrology to determine sensitivity of malaria risk to climate drivers

NASA Astrophysics Data System (ADS)

Tompkins, Adrian; Ermert, Volker; Di Giuseppe, Francesca

2013-04-01

In order to better address the role of population dynamics and surface hydrology in the assessment of malaria risk, a new dynamical disease model been developed at ICTP, known as VECTRI: VECtor borne disease community model of ICTP, TRIeste (VECTRI). The model accounts for the temperature impact on the larvae, parasite and adult vector populations. Local host population density affects the transmission intensity, and the model thus reproduces the differences between peri-urban and rural transmission noted in Africa. A new simple pond model framework represents surface hydrology. The model can be used on with spatial resolutions finer than 10km to resolve individual health districts and thus can be used as a planning tool. Results of the models representation of interannual variability and longer term projections of malaria transmission will be shown for Africa. These will show that the model represents the seasonality and spatial variations of malaria transmission well matching a wide range of survey data of parasite rate and entomological inoculation rate (EIR) from across West and East Africa taken in the period prior to large-scale interventions. The model is used to determine the sensitivity of malaria risk to climate variations, both in rainfall and temperature, and then its use in a prototype forecasting system coupled with ECMWF forecasts will be demonstrated.

Development of Simple Sequence Repeats (SSR) markers in Setaria italica (Poaceae) and cross-amplification in related species.

PubMed

Lin, Heng-Sheng; Chiang, Chih-Yun; Chang, Song-Bin; Kuoh, Chang-Sheng

2011-01-01

Foxtail millet is one of the world's oldest cultivated crops. It has been adopted as a model organism for providing a deeper understanding of plant biology. In this study, 45 simple sequence repeats (SSR) markers of Setaria italica were developed. These markers showing polymorphism were screened in 223 samples from 12 foxtail millet populations around Taiwan. The most common dinucleotide and trinucleotide repeat motifs are AC/TG (84.21%) and CAT (46.15%). The average number of alleles (N(a)), the average heterozygosities observed (H(o)) and expected (H(e)) are 3.73, 0.714, 0.587, respectively. In addition, 24 SSR markers had shown transferability to six related Poaceae species. These new markers provide tools for examining genetic relatedness among foxtail millet populations and other related species. It is suitable for germplasm management and protection in Poaceae.

Development of Simple Sequence Repeats (SSR) Markers in Setaria italica (Poaceae) and Cross-Amplification in Related Species

PubMed Central

Lin, Heng-Sheng; Chiang, Chih-Yun; Chang, Song-Bin; Kuoh, Chang-Sheng

2011-01-01

Foxtail millet is one of the world’s oldest cultivated crops. It has been adopted as a model organism for providing a deeper understanding of plant biology. In this study, 45 simple sequence repeats (SSR) markers of Setaria italica were developed. These markers showing polymorphism were screened in 223 samples from 12 foxtail millet populations around Taiwan. The most common dinucleotide and trinucleotide repeat motifs are AC/TG (84.21%) and CAT (46.15%). The average number of alleles (Na), the average heterozygosities observed (Ho) and expected (He) are 3.73, 0.714, 0.587, respectively. In addition, 24 SSR markers had shown transferability to six related Poaceae species. These new markers provide tools for examining genetic relatedness among foxtail millet populations and other related species. It is suitable for germplasm management and protection in Poaceae. PMID:22174636

Common inputs in subthreshold membrane potential: The role of quiescent states in neuronal activity

NASA Astrophysics Data System (ADS)

Montangie, Lisandro; Montani, Fernando

2018-06-01

Experiments in certain regions of the cerebral cortex suggest that the spiking activity of neuronal populations is regulated by common non-Gaussian inputs across neurons. We model these deviations from random-walk processes with q -Gaussian distributions into simple threshold neurons, and investigate the scaling properties in large neural populations. We show that deviations from the Gaussian statistics provide a natural framework to regulate population statistics such as sparsity, entropy, and specific heat. This type of description allows us to provide an adequate strategy to explain the information encoding in the case of low neuronal activity and its possible implications on information transmission.

Testing Modeling Assumptions in the West Africa Ebola Outbreak

NASA Astrophysics Data System (ADS)

Burghardt, Keith; Verzijl, Christopher; Huang, Junming; Ingram, Matthew; Song, Binyang; Hasne, Marie-Pierre

2016-10-01

The Ebola virus in West Africa has infected almost 30,000 and killed over 11,000 people. Recent models of Ebola Virus Disease (EVD) have often made assumptions about how the disease spreads, such as uniform transmissibility and homogeneous mixing within a population. In this paper, we test whether these assumptions are necessarily correct, and offer simple solutions that may improve disease model accuracy. First, we use data and models of West African migration to show that EVD does not homogeneously mix, but spreads in a predictable manner. Next, we estimate the initial growth rate of EVD within country administrative divisions and find that it significantly decreases with population density. Finally, we test whether EVD strains have uniform transmissibility through a novel statistical test, and find that certain strains appear more often than expected by chance.

A Biologically Constrained, Mathematical Model of Cortical Wave Propagation Preceding Seizure Termination

PubMed Central

González-Ramírez, Laura R.; Ahmed, Omar J.; Cash, Sydney S.; Wayne, C. Eugene; Kramer, Mark A.

2015-01-01

Epilepsy—the condition of recurrent, unprovoked seizures—manifests in brain voltage activity with characteristic spatiotemporal patterns. These patterns include stereotyped semi-rhythmic activity produced by aggregate neuronal populations, and organized spatiotemporal phenomena, including waves. To assess these spatiotemporal patterns, we develop a mathematical model consistent with the observed neuronal population activity and determine analytically the parameter configurations that support traveling wave solutions. We then utilize high-density local field potential data recorded in vivo from human cortex preceding seizure termination from three patients to constrain the model parameters, and propose basic mechanisms that contribute to the observed traveling waves. We conclude that a relatively simple and abstract mathematical model consisting of localized interactions between excitatory cells with slow adaptation captures the quantitative features of wave propagation observed in the human local field potential preceding seizure termination. PMID:25689136

Designing instruction to support mechanical reasoning: Three alternatives in the simple machines learning environment

NASA Astrophysics Data System (ADS)

McKenna, Ann Frances

2001-07-01

Creating a classroom environment that fosters a productive learning experience and engages students in the learning process is a complex endeavor. A classroom environment is dynamic and requires a unique synergy among students, teacher, classroom artifacts and events to achieve robust understanding and knowledge integration. This dissertation addresses this complex issue by developing, implementing, and investigating the simple machines learning environment (SIMALE) to support students' mechanical reasoning and understanding. SIMALE was designed to support reflection, collaborative learning, and to engage students in generative learning through multiple representations of concepts and successive experimentation and design activities. Two key components of SIMALE are an original web-based software tool and hands-on Lego activities. A research study consisting of three treatment groups was created to investigate the benefits of hands-on and web-based computer activities on students' analytic problem solving ability, drawing/modeling ability, and conceptual understanding. The study was conducted with two populations of students that represent a diverse group with respect to gender, ethnicity, academic achievement and social/economic status. One population of students in this dissertation study participated from the Mathematics, Engineering, and Science Achievement (MESA) program that serves minorities and under-represented groups in science and mathematics. The second group was recruited from the Academic Talent Development Program (ATDP) that is an academically competitive outreach program offered through the University of California at Berkeley. Results from this dissertation show success of the SIMALE along several dimensions. First, students in both populations achieved significant gains in analytic problem solving ability, drawing/modeling ability, and conceptual understanding. Second, significant differences that were found on pre-test measures were eliminated on post-test measures. Specifically, female students scored significantly lower than males on the overall pre-tests but scored as well as males on the same post-test measures. MESA students also scored significantly lower than ATDP students on pre-test measures but both populations scored equally well on the post-tests. This dissertation has therefore shown the SIMALE to support a collaborative, reflective, and generative learning environment. Furthermore, the SIMALE clearly contributes to students' mechanical reasoning and understanding of simple machines concepts for a diverse population of students.

Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance

PubMed Central

Hong, Ha; Solomon, Ethan A.; DiCarlo, James J.

2015-01-01

To go beyond qualitative models of the biological substrate of object recognition, we ask: can a single ventral stream neuronal linking hypothesis quantitatively account for core object recognition performance over a broad range of tasks? We measured human performance in 64 object recognition tests using thousands of challenging images that explore shape similarity and identity preserving object variation. We then used multielectrode arrays to measure neuronal population responses to those same images in visual areas V4 and inferior temporal (IT) cortex of monkeys and simulated V1 population responses. We tested leading candidate linking hypotheses and control hypotheses, each postulating how ventral stream neuronal responses underlie object recognition behavior. Specifically, for each hypothesis, we computed the predicted performance on the 64 tests and compared it with the measured pattern of human performance. All tested hypotheses based on low- and mid-level visually evoked activity (pixels, V1, and V4) were very poor predictors of the human behavioral pattern. However, simple learned weighted sums of distributed average IT firing rates exactly predicted the behavioral pattern. More elaborate linking hypotheses relying on IT trial-by-trial correlational structure, finer IT temporal codes, or ones that strictly respect the known spatial substructures of IT (“face patches”) did not improve predictive power. Although these results do not reject those more elaborate hypotheses, they suggest a simple, sufficient quantitative model: each object recognition task is learned from the spatially distributed mean firing rates (100 ms) of ∼60,000 IT neurons and is executed as a simple weighted sum of those firing rates. SIGNIFICANCE STATEMENT We sought to go beyond qualitative models of visual object recognition and determine whether a single neuronal linking hypothesis can quantitatively account for core object recognition behavior. To achieve this, we designed a database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior. PMID:26424887

Endogenous technological and population change under increasing water scarcity

NASA Astrophysics Data System (ADS)

Pande, S.; Ertsen, M.; Sivapalan, M.

2013-11-01

The ancient civilization in the Indus Valley civilization dispersed under extreme dry conditions; there are indications that the same holds for many other ancient societies. Even contemporary societies, such as the one in Murrumbidgee river basin in Australia, have started to witness a decline in overall population under increasing water scarcity. Hydroclimatic change may not be the sole predictor of the fate of contemporary societies in water scarce regions and many critics of such (perceived) hydroclimatic determinism have suggested that technological change may ameliorate the effects of increasing water scarcity and as such counter the effects of hydroclimatic changes. To study the role of technological change on the dynamics of coupled human-water systems, we develop a simple overlapping-generations model of endogenous technological and demographic change. We model technological change as an endogenous process that depends on factors such as the investments that are (endogenously) made in a society, the (endogenous) diversification of a society into skilled and unskilled workers, a society's patience in terms of its present consumption vs. future consumption, production technology and the (endogenous) interaction of all of these factors. In the model the population growth rate is programmed to decline once consumption per capita crosses a "survival" threshold. This means we do not treat technology as an exogenous random sequence of events, but instead assume that it results (endogenously) from societal actions. The model demonstrates that technological change may indeed ameliorate the effects of increasing water scarcity but typically it does so only to a certain extent. It is possible that technological change may allow a society to escape the effect of increasing water scarcity, leading to a (super)-exponential rise in technology and population. However, such cases require the rate of success of investment in technological advancement to be high. In other more realistic cases of technological success, we find that endogenous technology change only helps to delay the peak of population size before it inevitably starts to decline. While the model is a rather simple model of societal development, it is shown to be capable of replicating patterns of technological and population changes. It is capable of replicating the pattern of declining consumption per capita in presence of growth in aggregate production. It is also capable of replicating an exponential population rise, even under increasing water scarcity. The results of the model suggest that societies that declined or are declining in the face of extreme water scarcity may have done so due to slower rate of success of investment in technological advancement. The model suggests that the population decline occurs after a prolonged decline in consumption per capita, which in turn is due to the joint effect of initially increasing population and increasing water scarcity. This is despite technological advancement and increase in aggregate production. We suggest that declining consumption per capita despite technological advancement and increase in aggregate production may serve as a useful predictor of upcoming decline in contemporary societies in water scarce basins.

Submillimeter Galaxy Number Counts and Magnification by Galaxy Clusters

NASA Astrophysics Data System (ADS)

Lima, Marcos; Jain, Bhuvnesh; Devlin, Mark; Aguirre, James

2010-07-01

We present an analytical model that reproduces measured galaxy number counts from surveys in the wavelength range of 500 μm-2 mm. The model involves a single high-redshift galaxy population with a Schechter luminosity function that has been gravitationally lensed by galaxy clusters in the mass range 1013-1015 M sun. This simple model reproduces both the low-flux and the high-flux end of the number counts reported by the BLAST, SCUBA, AzTEC, and South Pole Telescope (SPT) surveys. In particular, our model accounts for the most luminous galaxies detected by SPT as the result of high magnifications by galaxy clusters (magnification factors of 10-30). This interpretation implies that submillimeter (submm) and millimeter surveys of this population may prove to be a useful addition to ongoing cluster detection surveys. The model also implies that the bulk of submm galaxies detected at wavelengths larger than 500 μm lie at redshifts greater than 2.

The implications of variable remigration intervals for the assessment of population size in marine turtles.

PubMed

Hays, G C

2000-09-21

Sea turtles nest on sandy beaches and tend to show high fidelity to specific nesting areas, but, despite this fidelity, the inter-annual variation in nesting numbers may be large. This variation may reflect the fact that turtles do not usually nest in consecutive years. Here, theoretical models are developed in which the interval between successive nesting years (the remigration interval) reflects conditions encountered on the feeding grounds, with good feeding years leading to a reduction in the remigration interval and vice versa. These simple models produce high levels of inter-annual variation in nesting numbers with, on occasion, almost no turtles nesting in some years even when the population is large and stable. The implications for assessing the size of sea turtle populations are considered. Copyright 2000 Academic Press.

Social Information Links Individual Behavior to Population and Community Dynamics.

PubMed

Gil, Michael A; Hein, Andrew M; Spiegel, Orr; Baskett, Marissa L; Sih, Andrew

2018-05-07

When individual animals make decisions, they routinely use information produced intentionally or unintentionally by other individuals. Despite its prevalence and established fitness consequences, the effects of such social information on ecological dynamics remain poorly understood. Here, we synthesize results from ecology, evolutionary biology, and animal behavior to show how the use of social information can profoundly influence the dynamics of populations and communities. We combine recent theoretical and empirical results and introduce simple population models to illustrate how social information use can drive positive density-dependent growth of populations and communities (Allee effects). Furthermore, social information can shift the nature and strength of species interactions, change the outcome of competition, and potentially increase extinction risk in harvested populations and communities. Copyright © 2018 Elsevier Ltd. All rights reserved.

Simple diffusion can support the pitchfork, the flip bifurcations, and the chaos

NASA Astrophysics Data System (ADS)

Meng, Lili; Li, Xinfu; Zhang, Guang

2017-12-01

In this paper, a discrete rational fration population model with the Dirichlet boundary conditions will be considered. According to the discrete maximum principle and the sub- and supper-solution method, the necessary and sufficient conditions of uniqueness and existence of positive steady state solutions will be obtained. In addition, the dynamical behavior of a special two patch metapopulation model is investigated by using the bifurcation method, the center manifold theory, the bifurcation diagrams and the largest Lyapunov exponent. The results show that there exist the pitchfork, the flip bifurcations, and the chaos. Clearly, these phenomena are caused by the simple diffusion. The theoretical analysis of chaos is very imortant, unfortunately, there is not any results in this hand. However, some open problems are given.

Generation of multicellular tumor spheroids by the hanging-drop method.

PubMed

Timmins, Nicholas E; Nielsen, Lars K

2007-01-01

Owing to their in vivo-like characteristics, three-dimensional (3D) multicellular tumor spheroid (MCTS) cultures are gaining increasing popularity as an in vitro model of tumors. A straightforward and simple approach to the cultivation of these MCTS is the hanging-drop method. Cells are suspended in droplets of medium, where they develop into coherent 3D aggregates and are readily accessed for analysis. In addition to being simple, the method eliminates surface interactions with an underlying substratum (e.g., polystyrene plastic or agarose), requires only a low number of starting cells, and is highly reproducible. This method has also been applied to the co-cultivation of mixed cell populations, including the co-cultivation of endothelial cells and tumor cells as a model of early tumor angiogenesis.

The role of strength defects in shaping impact crater planforms

NASA Astrophysics Data System (ADS)

Watters, W. A.; Geiger, L. M.; Fendrock, M.; Gibson, R.; Hundal, C. B.

2017-04-01

High-resolution imagery and digital elevation models (DEMs) were used to measure the planimetric shapes of well-preserved impact craters. These measurements were used to characterize the size-dependent scaling of the departure from circular symmetry, which provides useful insights into the processes of crater growth and modification. For example, we characterized the dependence of the standard deviation of radius (σR) on crater diameter (D) as σR ∼ Dm. For complex craters on the Moon and Mars, m ranges from 0.9 to 1.2 among strong and weak target materials. For the martian simple craters in our data set, m varies from 0.5 to 0.8. The value of m tends toward larger values in weak materials and modified craters, and toward smaller values in relatively unmodified craters as well as craters in high-strength targets, such as young lava plains. We hypothesize that m ≈ 1 for planforms shaped by modification processes (slumping and collapse), whereas m tends toward ∼ 1/2 for planforms shaped by an excavation flow that was influenced by strength anisotropies. Additional morphometric parameters were computed to characterize the following planform properties: the planform aspect ratio or ellipticity, the deviation from a fitted ellipse, and the deviation from a convex shape. We also measured the distribution of crater shapes using Fourier decomposition of the planform, finding a similar distribution for simple and complex craters. By comparing the strength of small and large circular harmonics, we confirmed that lunar and martian complex craters are more polygonal at small sizes. Finally, we have used physical and geometrical principles to motivate scaling arguments and simple Monte Carlo models for generating synthetic planforms, which depend on a characteristic length scale of target strength defects. One of these models can be used to generate populations of synthetic planforms which are very similar to the measured population of well-preserved simple craters on Mars.

On the joint bimodality of temperature and moisture near stratocumulus cloud tops

NASA Technical Reports Server (NTRS)

Randall, D. A.

1983-01-01

The observed distributions of the thermodynamic variables near stratocumulus top are highly bimodal. Two simple models of sub-grid fractional cloudiness motivated by this observed bimodality are examined. In both models, certain low order moments of two independent, moist-conservative thermodynamic variables are assumed to be known. The first model is based on the assumption of two discrete populations of parcels: a warm-day population and a cool-moist population. If only the first and second moments are assumed to be known, the number of unknowns exceeds the number of independent equations. If the third moments are assumed to be known as well, the number of independent equations exceeds the number of unknowns. The second model is based on the assumption of a continuous joint bimodal distribution of parcels, obtained as the weighted sum of two binormal distributions. For this model, the third moments are used to obtain 9 independent nonlinear algebraic equations in 11 unknowns. Two additional equations are needed to determine the covariance within the two subpopulations. In case these two internal covariance vanish, the system of equations can be solved analytically.

A statistical approach to quasi-extinction forecasting.

PubMed

Holmes, Elizabeth Eli; Sabo, John L; Viscido, Steven Vincent; Fagan, William Fredric

2007-12-01

Forecasting population decline to a certain critical threshold (the quasi-extinction risk) is one of the central objectives of population viability analysis (PVA), and such predictions figure prominently in the decisions of major conservation organizations. In this paper, we argue that accurate forecasting of a population's quasi-extinction risk does not necessarily require knowledge of the underlying biological mechanisms. Because of the stochastic and multiplicative nature of population growth, the ensemble behaviour of population trajectories converges to common statistical forms across a wide variety of stochastic population processes. This paper provides a theoretical basis for this argument. We show that the quasi-extinction surfaces of a variety of complex stochastic population processes (including age-structured, density-dependent and spatially structured populations) can be modelled by a simple stochastic approximation: the stochastic exponential growth process overlaid with Gaussian errors. Using simulated and real data, we show that this model can be estimated with 20-30 years of data and can provide relatively unbiased quasi-extinction risk with confidence intervals considerably smaller than (0,1). This was found to be true even for simulated data derived from some of the noisiest population processes (density-dependent feedback, species interactions and strong age-structure cycling). A key advantage of statistical models is that their parameters and the uncertainty of those parameters can be estimated from time series data using standard statistical methods. In contrast for most species of conservation concern, biologically realistic models must often be specified rather than estimated because of the limited data available for all the various parameters. Biologically realistic models will always have a prominent place in PVA for evaluating specific management options which affect a single segment of a population, a single demographic rate, or different geographic areas. However, for forecasting quasi-extinction risk, statistical models that are based on the convergent statistical properties of population processes offer many advantages over biologically realistic models.

A Pictorial Version of the RIASEC Scales of the Personal Globe Inventory

ERIC Educational Resources Information Center

Enke, Serena

2009-01-01

Holland's theory of six work personalities has become a staple of vocational psychology, providing a robust and simple model for understanding the structure of vocational interests. Though Holland's types provide a common vocabulary for vocational psychologists working with a variety of populations, until this point there has not been a measure of…

Modeling sandhill crane population dynamics

USGS Publications Warehouse

Johnson, D.H.

1979-01-01

The impact of sport hunting on the Central Flyway population of sandhill cranes (Grus canadensis) has been a subject of controversy for several years. A recent study (Buller 1979) presented new and important information on sandhill crane population dynamics. The present report is intended to incorporate that and other information into a mathematical model for the purpose of assessing the long-range impact of hunting on the population of sandhill cranes.The model is a simple deterministic system that embodies density-dependent rates of survival and recruitment. The model employs four kinds of data: (1) spring population size of sandhill cranes, estimated from aerial surveys to be between 250,000 and 400,000 birds; (2) age composition in fall, estimated for 1974-76 to be 11.3% young; (3) annual harvest of cranes, estimated from a variety of sources to be about 5 to 7% of the spring population; and (4) age composition of harvested cranes, which was difficult to estimate but suggests that immatures were 2 to 4 times as vulnerable to hunting as adults.Because the true nature of sandhill crane population dynamics remains so poorly understood, it was necessary to try numerous (768 in all) combinations of survival and recruitment functions, and focus on the relatively few (37) that yielded population sizes and age structures comparable to those extant in the real population. Hunting was then applied to those simulated populations. In all combinations, hunting resulted in a lower asymptotic crane population, the decline ranging from 5 to 54%. The median decline was 22%, which suggests that a hunted sandhill crane population might be about three-fourths as large as it would be if left unhunted. Results apply to the aggregate of the three subspecies in the Central Flyway; individual subspecies or populations could be affected to a greater or lesser degree.

The Impact of Different Sources of Fluctuations on Mutual Information in Biochemical Networks

PubMed Central

Chevalier, Michael; Venturelli, Ophelia; El-Samad, Hana

2015-01-01

Stochastic fluctuations in signaling and gene expression limit the ability of cells to sense the state of their environment, transfer this information along cellular pathways, and respond to it with high precision. Mutual information is now often used to quantify the fidelity with which information is transmitted along a cellular pathway. Mutual information calculations from experimental data have mostly generated low values, suggesting that cells might have relatively low signal transmission fidelity. In this work, we demonstrate that mutual information calculations might be artificially lowered by cell-to-cell variability in both initial conditions and slowly fluctuating global factors across the population. We carry out our analysis computationally using a simple signaling pathway and demonstrate that in the presence of slow global fluctuations, every cell might have its own high information transmission capacity but that population averaging underestimates this value. We also construct a simple synthetic transcriptional network and demonstrate using experimental measurements coupled to computational modeling that its operation is dominated by slow global variability, and hence that its mutual information is underestimated by a population averaged calculation. PMID:26484538

Genotype imputation in a coalescent model with infinitely-many-sites mutation

PubMed Central

Huang, Lucy; Buzbas, Erkan O.; Rosenberg, Noah A.

2012-01-01

Empirical studies have identified population-genetic factors as important determinants of the properties of genotype-imputation accuracy in imputation-based disease association studies. Here, we develop a simple coalescent model of three sequences that we use to explore the theoretical basis for the influence of these factors on genotype-imputation accuracy, under the assumption of infinitely-many-sites mutation. Employing a demographic model in which two populations diverged at a given time in the past, we derive the approximate expectation and variance of imputation accuracy in a study sequence sampled from one of the two populations, choosing between two reference sequences, one sampled from the same population as the study sequence and the other sampled from the other population. We show that under this model, imputation accuracy—as measured by the proportion of polymorphic sites that are imputed correctly in the study sequence—increases in expectation with the mutation rate, the proportion of the markers in a chromosomal region that are genotyped, and the time to divergence between the study and reference populations. Each of these effects derives largely from an increase in information available for determining the reference sequence that is genetically most similar to the sequence targeted for imputation. We analyze as a function of divergence time the expected gain in imputation accuracy in the target using a reference sequence from the same population as the target rather than from the other population. Together with a growing body of empirical investigations of genotype imputation in diverse human populations, our modeling framework lays a foundation for extending imputation techniques to novel populations that have not yet been extensively examined. PMID:23079542

An energy budget agent-based model of earthworm populations and its application to study the effects of pesticides

PubMed Central

Johnston, A.S.A.; Hodson, M.E.; Thorbek, P.; Alvarez, T.; Sibly, R.M.

2014-01-01

Earthworms are important organisms in soil communities and so are used as model organisms in environmental risk assessments of chemicals. However current risk assessments of soil invertebrates are based on short-term laboratory studies, of limited ecological relevance, supplemented if necessary by site-specific field trials, which sometimes are challenging to apply across the whole agricultural landscape. Here, we investigate whether population responses to environmental stressors and pesticide exposure can be accurately predicted by combining energy budget and agent-based models (ABMs), based on knowledge of how individuals respond to their local circumstances. A simple energy budget model was implemented within each earthworm Eisenia fetida in the ABM, based on a priori parameter estimates. From broadly accepted physiological principles, simple algorithms specify how energy acquisition and expenditure drive life cycle processes. Each individual allocates energy between maintenance, growth and/or reproduction under varying conditions of food density, soil temperature and soil moisture. When simulating published experiments, good model fits were obtained to experimental data on individual growth, reproduction and starvation. Using the energy budget model as a platform we developed methods to identify which of the physiological parameters in the energy budget model (rates of ingestion, maintenance, growth or reproduction) are primarily affected by pesticide applications, producing four hypotheses about how toxicity acts. We tested these hypotheses by comparing model outputs with published toxicity data on the effects of copper oxychloride and chlorpyrifos on E. fetida. Both growth and reproduction were directly affected in experiments in which sufficient food was provided, whilst maintenance was targeted under food limitation. Although we only incorporate toxic effects at the individual level we show how ABMs can readily extrapolate to larger scales by providing good model fits to field population data. The ability of the presented model to fit the available field and laboratory data for E. fetida demonstrates the promise of the agent-based approach in ecology, by showing how biological knowledge can be used to make ecological inferences. Further work is required to extend the approach to populations of more ecologically relevant species studied at the field scale. Such a model could help extrapolate from laboratory to field conditions and from one set of field conditions to another or from species to species. PMID:25844009

Phenomenological network models: Lessons for epilepsy surgery.

PubMed

Hebbink, Jurgen; Meijer, Hil; Huiskamp, Geertjan; van Gils, Stephan; Leijten, Frans

2017-10-01

The current opinion in epilepsy surgery is that successful surgery is about removing pathological cortex in the anatomic sense. This contrasts with recent developments in epilepsy research, where epilepsy is seen as a network disease. Computational models offer a framework to investigate the influence of networks, as well as local tissue properties, and to explore alternative resection strategies. Here we study, using such a model, the influence of connections on seizures and how this might change our traditional views of epilepsy surgery. We use a simple network model consisting of four interconnected neuronal populations. One of these populations can be made hyperexcitable, modeling a pathological region of cortex. Using model simulations, the effect of surgery on the seizure rate is studied. We find that removal of the hyperexcitable population is, in most cases, not the best approach to reduce the seizure rate. Removal of normal populations located at a crucial spot in the network, the "driver," is typically more effective in reducing seizure rate. This work strengthens the idea that network structure and connections may be more important than localizing the pathological node. This can explain why lesionectomy may not always be sufficient. © 2017 The Authors. Epilepsia published by Wiley Periodicals, Inc. on behalf of International League Against Epilepsy.

Computer simulation of vasectomy for wolf control

USGS Publications Warehouse

Haight, R.G.; Mech, L.D.

1997-01-01

Recovering gray wolf (Canis lupus) populations in the Lake Superior region of the United States are prompting state management agencies to consider strategies to control population growth. In addition to wolf removal, vasectomy has been proposed. To predict the population effects of different sterilization and removal strategies, we developed a simulation model of wolf dynamics using simple rules for demography and dispersal. Simulations suggested that the effects of vasectomy and removal in a disjunct population depend largely on the degree of annual immigration. With low immigration, periodic sterilization reduced pup production and resulted in lower rates of territory recolonization. Consequently, average pack size, number of packs, and population size were significantly less than those for an untreated population. Periodically removing a proportion of the population produced roughly the same trends as did sterilization; however, more than twice as many wolves had to be removed than sterilized. With high immigration, periodic sterilization reduced pup production but not territory recolonization and produced only moderate reductions in population size relative to an untreated population. Similar reductions in population size were obtained by periodically removing large numbers of wolves. Our analysis does not address the possible effects of vasectomy on larger wolf populations, but it suggests that the subject should be considered through modeling or field testing.

Causes and consequences of complex population dynamics in an annual plant, Cardamine pensylvanica

DOE Office of Scientific and Technical Information (OSTI.GOV)

Crone, E.E.

1995-11-08

The relative importance of density-dependent and density-independent factors in determining the population dynamics of plants has been widely debated with little resolution. In this thesis, the author explores the effects of density-dependent population regulation on population dynamics in Cardamine pensylvanica, an annual plant. In the first chapter, she shows that experimental populations of C. pensylvanica cycled from high to low density in controlled constant-environment conditions. These cycles could not be explained by external environmental changes or simple models of direct density dependence (N{sub t+1} = f[N{sub t}]), but they could be explained by delayed density dependence (N{sub t+1} = f[N{submore » t}, N{sub t+1}]). In the second chapter, she shows that the difference in the stability properties of population growth models with and without delayed density dependence is due to the presence of Hopf as well as slip bifurcations from stable to chaotic population dynamics. She also measures delayed density dependence due to effects of parental density on offspring quality in C. pensylvanica and shows that this is large enough to be the cause of the population dynamics observed in C. pensylvanica. In the third chapter, the author extends her analyses of density-dependent population growth models to include interactions between competing species. In the final chapter, she compares the effects of fixed spatial environmental variation and variation in population size on the evolutionary response of C. pensylvanica populations.« less

Entropy, Ergodicity, and Stem Cell Multipotency

NASA Astrophysics Data System (ADS)

Ridden, Sonya J.; Chang, Hannah H.; Zygalakis, Konstantinos C.; MacArthur, Ben D.

2015-11-01

Populations of mammalian stem cells commonly exhibit considerable cell-cell variability. However, the functional role of this diversity is unclear. Here, we analyze expression fluctuations of the stem cell surface marker Sca1 in mouse hematopoietic progenitor cells using a simple stochastic model and find that the observed dynamics naturally lie close to a critical state, thereby producing a diverse population that is able to respond rapidly to environmental changes. We propose an information-theoretic interpretation of these results that views cellular multipotency as an instance of maximum entropy statistical inference.

Analytical Model for Mars Crater-Size Frequency Distribution

NASA Astrophysics Data System (ADS)

Bruckman, W.; Ruiz, A.; Ramos, E.

2009-05-01

We present a theoretical and analytical curve that reproduces essential features of the frequency distributions vs. diameter of the 42,000 impact craters contained in Barlow's Mars Catalog. The model is derived using reasonable simple assumptions that allow us to relate the present craters population with the craters population at each particular epoch. The model takes into consideration the reduction of the number of craters as a function of time caused by their erosion and obliteration, and this provides a simple and natural explanation for the presence of different slopes in the empirical log-log plot of number of craters (N) vs. diameter (D). A mean life for martians craters as a function of diameter is deduced, and it is shown that this result is consistent with the corresponding determination of craters mean life based on Earth data. Arguments are given to suggest that this consistency follows from the fact that a crater mean life is proportional to its volumen. It also follows that in the absence of erosions and obliterations, when craters are preserved, we would have N ∝ 1/D^{4.3}, which is a striking conclusion, since the exponent 4.3 is larger than previously thought. Such an exponent implies a similar slope in the extrapolated impactors size-frequency distribution.

Endogenous technological and demographic change under increasing water scarcity

NASA Astrophysics Data System (ADS)

Pande, S.; Ertsen, M.; Sivapalan, M.

2013-12-01

Many ancient civilizations such as the Indus Valley civilization dispersed under extreme dry conditions. Even contemporary societies such as the one in Murrumbidgee river basin, Australia, have started to witness a decline in overall population under increasing water scarcity. Skeptics of hydroclimatic determinism have often cautioned against the use of hydroclimatic change as the sole predictor of the fate of contemporary societies in water scarce regions by suggesting that technological change may ameliorate the effects of increasing water scarcity. We here develop a simple overlapping generations model of endogenous technological and demographic change. It models technological change not as an exogenous random sequence of events but as an endogenous process (as is widely accepted in contemporary literature) that depends on factors such as the investments that are (endogenously) made in a society, the endogenous diversification of a society into skilled and unskilled workers, individuals' patience in terms of its present consumption versus future consumption, the production technology and the (endogenous) interaction of these factors. The population growth rate is modeled to decline once consumption per capita crosses a ';survival' threshold. The model demonstrates that technological change may ameliorate the effects of increasing water scarcity but only to a certain extent in many cases. It is possible that technological change may allow a society to escape the effect of increasing water society, leading to an exponential rise in technology and population. However, such cases require that the rate of success of investment in technological advancement is high. In other more realistic cases of technological success, we find that endogenous technology change has an effect delaying the peak of population before it starts to decline. While the model is a rather simple model of societal growth, it is capable of replicating (not to scale) patterns of technological change (proxies of which in ancient technology include irrigation canals, metal tools, and the use of horses for labor while in contemporary societies its proxies may be the advent of drip irrigation, increasing reservoir storage capacity etc) and population change. It is capable of replicating the pattern of declining consumption per capita in presence of growth in aggregate production. It is also capable of modeling the exponential population rise even under increasing water scarcity. The results of the model suggest, as one of the many other possible explanations, that ancient societies that declined in the face of extreme water scarcity may have done so due to slower rate of success of investment in technological advancement. The model suggests that the population decline occurs after a prolonged decline in consumption per capita, which in turn is due to the joint effect of initially increasing population and increasing water scarcity. This is despite technological advancement and increase in aggregate production. Thus declining consumption per capita despite technological advancement and increase in aggregate production may serve as a useful predictor of upcoming decline in contemporary societies in water scarce basins.

Boom and bust in continuous time evolving economic model

NASA Astrophysics Data System (ADS)

Mitchell, L.; Ackland, G. J.

2009-08-01

We show that a simple model of a spatially resolved evolving economic system, which has a steady state under simultaneous updating, shows stable oscillations in price when updated asynchronously. The oscillations arise from a gradual decline of the mean price due to competition among sellers competing for the same resource. This lowers profitability and hence population but is followed by a sharp rise as speculative sellers invade the large un-inhabited areas. This cycle then begins again.

A new approach to estimate parameters of speciation models with application to apes.

PubMed

Becquet, Celine; Przeworski, Molly

2007-10-01

How populations diverge and give rise to distinct species remains a fundamental question in evolutionary biology, with important implications for a wide range of fields, from conservation genetics to human evolution. A promising approach is to estimate parameters of simple speciation models using polymorphism data from multiple loci. Existing methods, however, make a number of assumptions that severely limit their applicability, notably, no gene flow after the populations split and no intralocus recombination. To overcome these limitations, we developed a new Markov chain Monte Carlo method to estimate parameters of an isolation-migration model. The approach uses summaries of polymorphism data at multiple loci surveyed in a pair of diverging populations or closely related species and, importantly, allows for intralocus recombination. To illustrate its potential, we applied it to extensive polymorphism data from populations and species of apes, whose demographic histories are largely unknown. The isolation-migration model appears to provide a reasonable fit to the data. It suggests that the two chimpanzee species became reproductively isolated in allopatry approximately 850 Kya, while Western and Central chimpanzee populations split approximately 440 Kya but continued to exchange migrants. Similarly, Eastern and Western gorillas and Sumatran and Bornean orangutans appear to have experienced gene flow since their splits approximately 90 and over 250 Kya, respectively.

App Usage Factor: A Simple Metric to Compare the Population Impact of Mobile Medical Apps

PubMed Central

Wyatt, Jeremy C

2015-01-01

Background One factor when assessing the quality of mobile apps is quantifying the impact of a given app on a population. There is currently no metric which can be used to compare the population impact of a mobile app across different health care disciplines. Objective The objective of this study is to create a novel metric to characterize the impact of a mobile app on a population. Methods We developed the simple novel metric, app usage factor (AUF), defined as the logarithm of the product of the number of active users of a mobile app with the median number of daily uses of the app. The behavior of this metric was modeled using simulated modeling in Python, a general-purpose programming language. Three simulations were conducted to explore the temporal and numerical stability of our metric and a simulated app ecosystem model using a simulated dataset of 20,000 apps. Results Simulations confirmed the metric was stable between predicted usage limits and remained stable at extremes of these limits. Analysis of a simulated dataset of 20,000 apps calculated an average value for the app usage factor of 4.90 (SD 0.78). A temporal simulation showed that the metric remained stable over time and suitable limits for its use were identified. Conclusions A key component when assessing app risk and potential harm is understanding the potential population impact of each mobile app. Our metric has many potential uses for a wide range of stakeholders in the app ecosystem, including users, regulators, developers, and health care professionals. Furthermore, this metric forms part of the overall estimate of risk and potential for harm or benefit posed by a mobile medical app. We identify the merits and limitations of this metric, as well as potential avenues for future validation and research. PMID:26290093

Optimized O'Neill/Glaser Model for Human Population of Space and its Impact on Survival Probabilities

NASA Technical Reports Server (NTRS)

Curreri, Peter A.

2010-01-01

Two contemporary issues foretell a shift from our historical Earth based industrial economy and habitation to a solar system based society. The first is the limits to Earth's carrying capacity, that is the maximum number of people that the Earth can support before a catastrophic impact to the health of the planet and human species occurs. The simple example of carrying capacity is that of a bacterial colony in a Petri dish with a limited amount of nutrient. The colony experiences exponential population growth until the carrying capacity is reached after which catastrophic depopulation often results. Estimates of the Earth s carrying capacity vary between 14 and 40 billion people. Although at current population growth rates we may have over a century before we reach Earth s carrying limit our influence on climate and resources on the planetary scale is becoming scientifically established. The second issue is the exponential growth of knowledge and technological power. The exponential growth of technology interacts with the exponential growth of population in a manner that is unique to a highly intelligent species. Thus, the predicted consequences (world famines etc.) of the limits to growth have been largely avoided due to technological advances. However, at the mid twentieth century a critical coincidence occurred in these two trends humanity obtained the technological ability to extinguish life on the planetary scale (by nuclear, chemical, biological means) and attained the ability to expand human life beyond Earth. This paper examines an optimized O Neill/Glaser model (O Neill 1975; Curreri 2007; Detweiler and Curreri 2008) for the economic human population of space. Critical to this model is the utilization of extraterrestrial resources, solar power and spaced based labor. A simple statistical analysis is then performed which predicts the robustness of a single planet based technological society versus that of multiple world (independent habitats) society.

Optimized O'Neill/Glaser Model for Human Population of Space and its Impact on Survival Probabilities

NASA Technical Reports Server (NTRS)

Curreri, Peter A.

2010-01-01

Two contemporary issues foretell a shift from our historical Earth based industrial economy and habitation to a solar system based society. The first is the limits to Earth s carrying capacity, that is the maximum number of people that the Earth can support before a catastrophic impact to the health of the planet and human species occurs. The simple example of carrying capacity is that of a bacterial colony in a Petri dish with a limited amount of nutrient. The colony experiences exponential population growth until the carrying capacity is reached after which catastrophic depopulation often results. Estimates of the Earth s carrying capacity vary between 14 and 40 billion people. Although at current population growth rates we may have over a century before we reach Earth s carrying limit our influence on climate and resources on the planetary scale is becoming scientifically established. The second issue is the exponential growth of knowledge and technological power. The exponential growth of technology interacts with the exponential growth of population in a manner that is unique to a highly intelligent species. Thus, the predicted consequences (world famines etc.) of the limits to growth have been largely avoided due to technological advances. However, at the mid twentieth century a critical coincidence occurred in these two trends humanity obtained the technological ability to extinguish life on the planetary scale (by nuclear, chemical, biological means) and attained the ability to expand human life beyond Earth. This paper examines an optimized O Neill/Glaser model (O Neill 1975; Curreri 2007; Detweiler and Curreri 2008) for the economic human population of space. Critical to this model is the utilization of extraterrestrial resources, solar power and spaced based labor. A simple statistical analysis is then performed which predicts the robustness of a single planet based technological society versus that of multiple world (independent habitats) society.

Optimized O'Neill/Glaser Model for Human Population of Space and its Impact on Survival Probabilities

NASA Technical Reports Server (NTRS)

Curreri, Peter A.

2010-01-01

Two contemporary issues foretell a shift from our historical Earth based industrial economy and habitation to a solar system based society. The first is the limits to Earth s carrying capacity, that is the maximum number of people that the Earth can support before a catastrophic impact to the health of the planet and human species occurs. The simple example of carrying capacity is that of a bacterial colony in a Petri dish with a limited amount of nutrient. The colony experiences exponential population growth until the carrying capacity is reached after which catastrophic depopulation often results. Estimates of the Earth s carrying capacity vary between 14 and 40 billion people. Although at current population growth rates we may have over a century before we reach Earth s carrying limit our influence on climate and resources on the planetary scale is becoming scientifically established. The second issue is the exponential growth of knowledge and technological power. The exponential growth of technology interacts with the exponential growth of population in a manner that is unique to a highly intelligent species. Thus, the predicted consequences (world famines etc.) of the limits to growth have been largely avoided due to technological advances. However, at the mid twentieth century a critical coincidence occurred in these two trends humanity obtained the technological ability to extinguish life on the planetary scale (by nuclear, chemical, biological means) and attained the ability to expand human life beyond Earth. This paper examines an optimized O'Neill/Glaser model (O Neill 1975; Curreri 2007; Detweiler and Curreri 2008) for the economic human population of space. Critical to this model is the utilization of extraterrestrial resources, solar power and spaced based labor. A simple statistical analysis is then performed which predicts the robustness of a single planet based technological society versus that of multiple world (independent habitats) society.

A high resolution spatial population database of Somalia for disease risk mapping.

PubMed

Linard, Catherine; Alegana, Victor A; Noor, Abdisalan M; Snow, Robert W; Tatem, Andrew J

2010-09-14

Millions of Somali have been deprived of basic health services due to the unstable political situation of their country. Attempts are being made to reconstruct the health sector, in particular to estimate the extent of infectious disease burden. However, any approach that requires the use of modelled disease rates requires reasonable information on population distribution. In a low-income country such as Somalia, population data are lacking, are of poor quality, or become outdated rapidly. Modelling methods are therefore needed for the production of contemporary and spatially detailed population data. Here land cover information derived from satellite imagery and existing settlement point datasets were used for the spatial reallocation of populations within census units. We used simple and semi-automated methods that can be implemented with free image processing software to produce an easily updatable gridded population dataset at 100 × 100 meters spatial resolution. The 2010 population dataset was matched to administrative population totals projected by the UN. Comparison tests between the new dataset and existing population datasets revealed important differences in population size distributions, and in population at risk of malaria estimates. These differences are particularly important in more densely populated areas and strongly depend on the settlement data used in the modelling approach. The results show that it is possible to produce detailed, contemporary and easily updatable settlement and population distribution datasets of Somalia using existing data. The 2010 population dataset produced is freely available as a product of the AfriPop Project and can be downloaded from: http://www.afripop.org.

A high resolution spatial population database of Somalia for disease risk mapping

PubMed Central

2010-01-01

Background Millions of Somali have been deprived of basic health services due to the unstable political situation of their country. Attempts are being made to reconstruct the health sector, in particular to estimate the extent of infectious disease burden. However, any approach that requires the use of modelled disease rates requires reasonable information on population distribution. In a low-income country such as Somalia, population data are lacking, are of poor quality, or become outdated rapidly. Modelling methods are therefore needed for the production of contemporary and spatially detailed population data. Results Here land cover information derived from satellite imagery and existing settlement point datasets were used for the spatial reallocation of populations within census units. We used simple and semi-automated methods that can be implemented with free image processing software to produce an easily updatable gridded population dataset at 100 × 100 meters spatial resolution. The 2010 population dataset was matched to administrative population totals projected by the UN. Comparison tests between the new dataset and existing population datasets revealed important differences in population size distributions, and in population at risk of malaria estimates. These differences are particularly important in more densely populated areas and strongly depend on the settlement data used in the modelling approach. Conclusions The results show that it is possible to produce detailed, contemporary and easily updatable settlement and population distribution datasets of Somalia using existing data. The 2010 population dataset produced is freely available as a product of the AfriPop Project and can be downloaded from: http://www.afripop.org. PMID:20840751

Development of feedforward receptive field structure of a simple cell and its contribution to the orientation selectivity: a modeling study.

PubMed

Garg, Akhil R; Obermayer, Klaus; Bhaumik, Basabi

2005-01-01

Recent experimental studies of hetero-synaptic interactions in various systems have shown the role of signaling in the plasticity, challenging the conventional understanding of Hebb's rule. It has also been found that activity plays a major role in plasticity, with neurotrophins acting as molecular signals translating activity into structural changes. Furthermore, role of synaptic efficacy in biasing the outcome of competition has also been revealed recently. Motivated by these experimental findings we present a model for the development of simple cell receptive field structure based on the competitive hetero-synaptic interactions for neurotrophins combined with cooperative hetero-synaptic interactions in the spatial domain. We find that with proper balance in competition and cooperation, the inputs from two populations (ON/OFF) of LGN cells segregate starting from the homogeneous state. We obtain segregated ON and OFF regions in simple cell receptive field. Our modeling study supports the experimental findings, suggesting the role of synaptic efficacy and the role of spatial signaling. We find that using this model we obtain simple cell RF, even for positively correlated activity of ON/OFF cells. We also compare different mechanism of finding the response of cortical cell and study their possible role in the sharpening of orientation selectivity. We find that degree of selectivity improvement in individual cells varies from case to case depending upon the structure of RF field and type of sharpening mechanism.

Population Pharmacokinetics of Busulfan in Pediatric and Young Adult Patients Undergoing Hematopoietic Cell Transplant: A Model-Based Dosing Algorithm for Personalized Therapy and Implementation into Routine Clinical Use

PubMed Central

Long-Boyle, Janel; Savic, Rada; Yan, Shirley; Bartelink, Imke; Musick, Lisa; French, Deborah; Law, Jason; Horn, Biljana; Cowan, Morton J.; Dvorak, Christopher C.

2014-01-01

Background Population pharmacokinetic (PK) studies of busulfan in children have shown that individualized model-based algorithms provide improved targeted busulfan therapy when compared to conventional dosing. The adoption of population PK models into routine clinical practice has been hampered by the tendency of pharmacologists to develop complex models too impractical for clinicians to use. The authors aimed to develop a population PK model for busulfan in children that can reliably achieve therapeutic exposure (concentration-at-steady-state, Css) and implement a simple, model-based tool for the initial dosing of busulfan in children undergoing HCT. Patients and Methods Model development was conducted using retrospective data available in 90 pediatric and young adult patients who had undergone HCT with busulfan conditioning. Busulfan drug levels and potential covariates influencing drug exposure were analyzed using the non-linear mixed effects modeling software, NONMEM. The final population PK model was implemented into a clinician-friendly, Microsoft Excel-based tool and used to recommend initial doses of busulfan in a group of 21 pediatric patients prospectively dosed based on the population PK model. Results Modeling of busulfan time-concentration data indicates busulfan CL displays non-linearity in children, decreasing up to approximately 20% between the concentrations of 250–2000 ng/mL. Important patient-specific covariates found to significantly impact busulfan CL were actual body weight and age. The percentage of individuals achieving a therapeutic Css was significantly higher in subjects receiving initial doses based on the population PK model (81%) versus historical controls dosed on conventional guidelines (52%) (p = 0.02). Conclusion When compared to the conventional dosing guidelines, the model-based algorithm demonstrates significant improvement for providing targeted busulfan therapy in children and young adults. PMID:25162216

TESTING STELLAR POPULATION SYNTHESIS MODELS WITH SLOAN DIGITAL SKY SURVEY COLORS OF M31's GLOBULAR CLUSTERS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Peacock, Mark B.; Zepf, Stephen E.; Maccarone, Thomas J.

2011-08-10

Accurate stellar population synthesis models are vital in understanding the properties and formation histories of galaxies. In order to calibrate and test the reliability of these models, they are often compared with observations of star clusters. However, relatively little work has compared these models in the ugriz filters, despite the recent widespread use of this filter set. In this paper, we compare the integrated colors of globular clusters in the Sloan Digital Sky Survey (SDSS) with those predicted from commonly used simple stellar population (SSP) models. The colors are based on SDSS observations of M31's clusters and provide the largestmore » population of star clusters with accurate photometry available from the survey. As such, it is a unique sample with which to compare SSP models with SDSS observations. From this work, we identify a significant offset between the SSP models and the clusters' g - r colors, with the models predicting colors which are too red by g - r {approx} 0.1. This finding is consistent with previous observations of luminous red galaxies in the SDSS, which show a similar discrepancy. The identification of this offset in globular clusters suggests that it is very unlikely to be due to a minority population of young stars. The recently updated SSP model of Maraston and Stroembaeck better represents the observed g - r colors. This model is based on the empirical MILES stellar library, rather than theoretical libraries, suggesting an explanation for the g - r discrepancy.« less

Bottleneck Effect on Evolutionary Rate in the Nearly Neutral Mutation Model

PubMed Central

Araki, H.; Tachida, H.

1997-01-01

Variances of evolutionary rates among lineages in some proteins are larger than those expected from simple Poisson processes. This phenomenon is called overdispersion of the molecular clock. If population size N is constant, the overdispersion is observed only in a limited range of 2Nσ under the nearly neutral mutation model, where σ represents the standard deviation of selection coefficients of new mutants. In this paper, we investigated effects of changing population size on the evolutionary rate by computer simulations assuming the nearly neutral mutation model. The size was changed cyclically between two numbers, N(1) and N(2) (N(1) > N(2)), in the simulations. The overdispersion is observed if 2N(2)σ is less than two and the state of reduced size (bottleneck state) continues for more than ~0.1/u generations, where u is the mutation rate. The overdispersion results mainly because the average fitnesses of only a portion of populations go down when the population size is reduced and only in these populations subsequent advantageous substitutions occur after the population size becomes large. Since the fitness reduction after the bottleneck is stochastic, acceleration of the evolutionary rate does not necessarily occur uniformly among loci. From these results, we argue that the nearly neutral mutation model is a candidate mechanism to explain the overdispersed molecular clock. PMID:9335622

A case-mix classification system for explaining healthcare costs using administrative data in Italy.

PubMed

Corti, Maria Chiara; Avossa, Francesco; Schievano, Elena; Gallina, Pietro; Ferroni, Eliana; Alba, Natalia; Dotto, Matilde; Basso, Cristina; Netti, Silvia Tiozzo; Fedeli, Ugo; Mantoan, Domenico

2018-03-04

The Italian National Health Service (NHS) provides universal coverage to all citizens, granting primary and hospital care with a copayment system for outpatient and drug services. Financing of Local Health Trusts (LHTs) is based on a capitation system adjusted only for age, gender and area of residence. We applied a risk-adjustment system (Johns Hopkins Adjusted Clinical Groups System, ACG® System) in order to explain health care costs using routinely collected administrative data in the Veneto Region (North-eastern Italy). All residents in the Veneto Region were included in the study. The ACG system was applied to classify the regional population based on the following information sources for the year 2015: Hospital Discharges, Emergency Room visits, Chronic disease registry for copayment exemptions, ambulatory visits, medications, the Home care database, and drug prescriptions. Simple linear regressions were used to contrast an age-gender model to models incorporating more comprehensive risk measures aimed at predicting health care costs. A simple age-gender model explained only 8% of the variance of 2015 total costs. Adding diagnoses-related variables provided a 23% increase, while pharmacy based variables provided an additional 17% increase in explained variance. The adjusted R-squared of the comprehensive model was 6 times that of the simple age-gender model. ACG System provides substantial improvement in predicting health care costs when compared to simple age-gender adjustments. Aging itself is not the main determinant of the increase of health care costs, which is better explained by the accumulation of chronic conditions and the resulting multimorbidity. Copyright © 2018. Published by Elsevier B.V.

Variations of anthropogenic CO2 in urban area deduced by radiocarbon concentration in modern tree rings.

PubMed

Rakowski, Andrzej Z; Nakamura, Toshio; Pazdur, Anna

2008-10-01

Radiocarbon concentration in the atmosphere is significantly lower in areas where man-made emissions of carbon dioxide occur. This phenomenon is known as Suess effect, and is caused by the contamination of clean air with non-radioactive carbon from fossil fuel combustion. The effect is more strongly observed in industrial and densely populated urban areas. Measurements of carbon isotope concentrations in a study area can be compared to those from areas of clear air in order to estimate the amount of carbon dioxide emission from fossil fuel combustion by using a simple mathematical model. This can be calculated using the simple mathematical model. The result of the mathematical model followed in this study suggests that the use of annual rings of trees to obtain the secular variations of 14C concentration of atmospheric CO2 can be useful and efficient for environmental monitoring and modeling of the carbon distribution in local scale.

Improving cerebellar segmentation with statistical fusion

NASA Astrophysics Data System (ADS)

Plassard, Andrew J.; Yang, Zhen; Prince, Jerry L.; Claassen, Daniel O.; Landman, Bennett A.

2016-03-01

The cerebellum is a somatotopically organized central component of the central nervous system well known to be involved with motor coordination and increasingly recognized roles in cognition and planning. Recent work in multiatlas labeling has created methods that offer the potential for fully automated 3-D parcellation of the cerebellar lobules and vermis (which are organizationally equivalent to cortical gray matter areas). This work explores the trade offs of using different statistical fusion techniques and post hoc optimizations in two datasets with distinct imaging protocols. We offer a novel fusion technique by extending the ideas of the Selective and Iterative Method for Performance Level Estimation (SIMPLE) to a patch-based performance model. We demonstrate the effectiveness of our algorithm, Non- Local SIMPLE, for segmentation of a mixed population of healthy subjects and patients with severe cerebellar anatomy. Under the first imaging protocol, we show that Non-Local SIMPLE outperforms previous gold-standard segmentation techniques. In the second imaging protocol, we show that Non-Local SIMPLE outperforms previous gold standard techniques but is outperformed by a non-locally weighted vote with the deeper population of atlases available. This work advances the state of the art in open source cerebellar segmentation algorithms and offers the opportunity for routinely including cerebellar segmentation in magnetic resonance imaging studies that acquire whole brain T1-weighted volumes with approximately 1 mm isotropic resolution.

Is cooperation viable in mobile organisms? Simple Walk Away rule favors the evolution of cooperation in groups

PubMed Central

Aktipis, C. Athena

2011-01-01

The evolution of cooperation through partner choice mechanisms is often thought to involve relatively complex cognitive abilities. Using agent-based simulations I model a simple partner choice rule, the ‘Walk Away’ rule, where individuals stay in groups that provide higher returns (by virtue of having more cooperators), and ‘Walk Away’ from groups providing low returns. Implementing this conditional movement rule in a public goods game leads to a number of interesting findings: 1) cooperators have a selective advantage when thresholds are high, corresponding to low tolerance for defectors, 2) high thresholds lead to high initial rates of movement and low final rates of movement (after selection), and 3) as cooperation is selected, the population undergoes a spatial transition from high migration (and a many small and ephemeral groups) to low migration (and large and stable groups). These results suggest that the very simple ‘Walk Away’ rule of leaving uncooperative groups can favor the evolution of cooperation, and that cooperation can evolve in populations in which individuals are able to move in response to local social conditions. A diverse array of organisms are able to leave degraded physical or social environments. The ubiquitous nature of conditional movement suggests that ‘Walk Away’ dynamics may play an important role in the evolution of social behavior in both cognitively complex and cognitively simple organisms. PMID:21666771

A cellular automata model for population expansion of Spartina alterniflora at Jiuduansha Shoals, Shanghai, China

NASA Astrophysics Data System (ADS)

Huang, Hua-mei; Zhang, Li-quan; Guan, Yu-juan; Wang, Dong-hui

2008-03-01

Biological invasion has received considerable attention recently because of increasing impacts on local ecosystems. Expansion of Spartina alterniflora, a non-native species, on the intertidal mudflats of Jiuduansha Shoals at the Yangtze River Estuary is a prime example of a spatially-structured invasion in a relatively simple habitat, for which strategic control efforts can be modeled and applied. Here, we developed a Cellular Automata (CA) model, in conjunction with Remote Sensing and Geographical Information Systems, to simulate the expanding process of S. alterniflora for a period of 8 years after being introduced to the new shoals, and to study the interactions between spatial pattern and ecosystem processes for the saltmarsh vegetation. The results showed that the CA model could simulate the population dynamics of S. alterniflora and Phragmites australis on the Jiuduansha Shoals successfully. The results strongly support the hypothesis of space pre-emption as well as range expansion with simple advancing wave fronts for these two species. In the Yangtze River Estuary, the native species P. australis shares the same niche with the exotic species S. alterniflora. However, the range expansion rate of P. australis was much slower than that of S. alterniflora. With the accretion of the Jiuduansha Shoals due to the large quantity of sediments deposited by the Yangtze River, a rapid range expansion of S. alterniflora is predicted to last for a long period into future. This study indicated the potential for this approach to provide valuable insights into population and community ecology of invasive species, which could be very important for wetland biodiversity conservation and resource management in the Yangtze River Estuary and other such impacted areas.

Complex and unexpected dynamics in simple genetic regulatory networks

NASA Astrophysics Data System (ADS)

Borg, Yanika; Ullner, Ekkehard; Alagha, Afnan; Alsaedi, Ahmed; Nesbeth, Darren; Zaikin, Alexey

2014-03-01

One aim of synthetic biology is to construct increasingly complex genetic networks from interconnected simpler ones to address challenges in medicine and biotechnology. However, as systems increase in size and complexity, emergent properties lead to unexpected and complex dynamics due to nonlinear and nonequilibrium properties from component interactions. We focus on four different studies of biological systems which exhibit complex and unexpected dynamics. Using simple synthetic genetic networks, small and large populations of phase-coupled quorum sensing repressilators, Goodwin oscillators, and bistable switches, we review how coupled and stochastic components can result in clustering, chaos, noise-induced coherence and speed-dependent decision making. A system of repressilators exhibits oscillations, limit cycles, steady states or chaos depending on the nature and strength of the coupling mechanism. In large repressilator networks, rich dynamics can also be exhibited, such as clustering and chaos. In populations of Goodwin oscillators, noise can induce coherent oscillations. In bistable systems, the speed with which incoming external signals reach steady state can bias the network towards particular attractors. These studies showcase the range of dynamical behavior that simple synthetic genetic networks can exhibit. In addition, they demonstrate the ability of mathematical modeling to analyze nonlinearity and inhomogeneity within these systems.

Modeling the lung: Design and development of tissue engineered macro- and micro-physiologic lung models for research use.

PubMed

Nichols, Joan E; Niles, Jean A; Vega, Stephanie P; Argueta, Lissenya B; Eastaway, Adriene; Cortiella, Joaquin

2014-09-01

Respiratory tract specific cell populations, or tissue engineered in vitro grown human lung, have the potential to be used as research tools to mimic physiology, toxicology, pathology, as well as infectious diseases responses of cells or tissues. Studies related to respiratory tract pathogenesis or drug toxicity testing in the past made use of basic systems where single cell populations were exposed to test agents followed by evaluations of simple cellular responses. Although these simple single-cell-type systems provided good basic information related to cellular responses, much more can be learned from cells grown in fabricated microenvironments which mimic in vivo conditions in specialized microfabricated chambers or by human tissue engineered three-dimensional (3D) models which allow for more natural interactions between cells. Recent advances in microengineering technology, microfluidics, and tissue engineering have provided a new approach to the development of 2D and 3D cell culture models which enable production of more robust human in vitro respiratory tract models. Complex models containing multiple cell phenotypes also provide a more reasonable approximation of what occurs in vivo without the confounding elements in the dynamic in vivo environment. The goal of engineering good 3D human models is the formation of physiologically functional respiratory tissue surrogates which can be used as pathogenesis models or in the case of 2D screening systems for drug therapy evaluation as well as human toxicity testing. We hope that this manuscript will serve as a guide for development of future respiratory tract model systems as well as a review of conventional models. © 2014 by the Society for Experimental Biology and Medicine.

Simple versus complex models of trait evolution and stasis as a response to environmental change

NASA Astrophysics Data System (ADS)

Hunt, Gene; Hopkins, Melanie J.; Lidgard, Scott

2015-04-01

Previous analyses of evolutionary patterns, or modes, in fossil lineages have focused overwhelmingly on three simple models: stasis, random walks, and directional evolution. Here we use likelihood methods to fit an expanded set of evolutionary models to a large compilation of ancestor-descendant series of populations from the fossil record. In addition to the standard three models, we assess more complex models with punctuations and shifts from one evolutionary mode to another. As in previous studies, we find that stasis is common in the fossil record, as is a strict version of stasis that entails no real evolutionary changes. Incidence of directional evolution is relatively low (13%), but higher than in previous studies because our analytical approach can more sensitively detect noisy trends. Complex evolutionary models are often favored, overwhelmingly so for sequences comprising many samples. This finding is consistent with evolutionary dynamics that are, in reality, more complex than any of the models we consider. Furthermore, the timing of shifts in evolutionary dynamics varies among traits measured from the same series. Finally, we use our empirical collection of evolutionary sequences and a long and highly resolved proxy for global climate to inform simulations in which traits adaptively track temperature changes over time. When realistically calibrated, we find that this simple model can reproduce important aspects of our paleontological results. We conclude that observed paleontological patterns, including the prevalence of stasis, need not be inconsistent with adaptive evolution, even in the face of unstable physical environments.

A regional-scale, high resolution dynamical malaria model that accounts for population density, climate and surface hydrology.

PubMed

Tompkins, Adrian M; Ermert, Volker

2013-02-18

The relative roles of climate variability and population related effects in malaria transmission could be better understood if regional-scale dynamical malaria models could account for these factors. A new dynamical community malaria model is introduced that accounts for the temperature and rainfall influences on the parasite and vector life cycles which are finely resolved in order to correctly represent the delay between the rains and the malaria season. The rainfall drives a simple but physically based representation of the surface hydrology. The model accounts for the population density in the calculation of daily biting rates. Model simulations of entomological inoculation rate and circumsporozoite protein rate compare well to data from field studies from a wide range of locations in West Africa that encompass both seasonal endemic and epidemic fringe areas. A focus on Bobo-Dioulasso shows the ability of the model to represent the differences in transmission rates between rural and peri-urban areas in addition to the seasonality of malaria. Fine spatial resolution regional integrations for Eastern Africa reproduce the malaria atlas project (MAP) spatial distribution of the parasite ratio, and integrations for West and Eastern Africa show that the model grossly reproduces the reduction in parasite ratio as a function of population density observed in a large number of field surveys, although it underestimates malaria prevalence at high densities probably due to the neglect of population migration. A new dynamical community malaria model is publicly available that accounts for climate and population density to simulate malaria transmission on a regional scale. The model structure facilitates future development to incorporate migration, immunity and interventions.

A regional-scale, high resolution dynamical malaria model that accounts for population density, climate and surface hydrology

PubMed Central

2013-01-01

Background The relative roles of climate variability and population related effects in malaria transmission could be better understood if regional-scale dynamical malaria models could account for these factors. Methods A new dynamical community malaria model is introduced that accounts for the temperature and rainfall influences on the parasite and vector life cycles which are finely resolved in order to correctly represent the delay between the rains and the malaria season. The rainfall drives a simple but physically based representation of the surface hydrology. The model accounts for the population density in the calculation of daily biting rates. Results Model simulations of entomological inoculation rate and circumsporozoite protein rate compare well to data from field studies from a wide range of locations in West Africa that encompass both seasonal endemic and epidemic fringe areas. A focus on Bobo-Dioulasso shows the ability of the model to represent the differences in transmission rates between rural and peri-urban areas in addition to the seasonality of malaria. Fine spatial resolution regional integrations for Eastern Africa reproduce the malaria atlas project (MAP) spatial distribution of the parasite ratio, and integrations for West and Eastern Africa show that the model grossly reproduces the reduction in parasite ratio as a function of population density observed in a large number of field surveys, although it underestimates malaria prevalence at high densities probably due to the neglect of population migration. Conclusions A new dynamical community malaria model is publicly available that accounts for climate and population density to simulate malaria transmission on a regional scale. The model structure facilitates future development to incorporate migration, immunity and interventions. PMID:23419192

A general stochastic model for sporophytic self-incompatibility.

PubMed

Billiard, Sylvain; Tran, Viet Chi

2012-01-01

Disentangling the processes leading populations to extinction is a major topic in ecology and conservation biology. The difficulty to find a mate in many species is one of these processes. Here, we investigate the impact of self-incompatibility in flowering plants, where several inter-compatible classes of individuals exist but individuals of the same class cannot mate. We model pollen limitation through different relationships between mate availability and fertilization success. After deriving a general stochastic model, we focus on the simple case of distylous plant species where only two classes of individuals exist. We first study the dynamics of such a species in a large population limit and then, we look for an approximation of the extinction probability in small populations. This leads us to consider inhomogeneous random walks on the positive quadrant. We compare the dynamics of distylous species to self-fertile species with and without inbreeding depression, to obtain the conditions under which self-incompatible species can be less sensitive to extinction while they can suffer more pollen limitation. © Springer-Verlag 2011

A simple rule for the costs of vigilance: empirical evidence from a social forager.

PubMed Central

Cowlishaw, Guy; Lawes, Michael J.; Lightbody, Margaret; Martin, Alison; Pettifor, Richard; Rowcliffe, J. Marcus

2004-01-01

It is commonly assumed that anti-predator vigilance by foraging animals is costly because it interrupts food searching and handling time, leading to a reduction in feeding rate. When food handling does not require visual attention, however, a forager may handle food while simultaneously searching for the next food item or scanning for predators. We present a simple model of this process, showing that when the length of such compatible handling time Hc is long relative to search time S, specifically Hc/S > 1, it is possible to perform vigilance without a reduction in feeding rate. We test three predictions of this model regarding the relationships between feeding rate, vigilance and the Hc/S ratio, with data collected from a wild population of social foragers (samango monkeys, Cercopithecus mitis erythrarchus). These analyses consistently support our model, including our key prediction: as Hc/S increases, the negative relationship between feeding rate and the proportion of time spent scanning becomes progressively shallower. This pattern is more strongly driven by changes in median scan duration than scan frequency. Our study thus provides a simple rule that describes the extent to which vigilance can be expected to incur a feeding rate cost. PMID:15002768

Aerosol Light Absorption and Scattering Assessments and the Impact of City Size on Air Pollution

NASA Astrophysics Data System (ADS)

Paredes-Miranda, Guadalupe

The general problem of urban pollution and its relation to the city population is examined in this dissertation. A simple model suggests that pollutant concentrations should scale approximately with the square root of city population. This model and its experimental evaluation presented here serve as important guidelines for urban planning and attainment of air quality standards including the limits that air pollution places on city population. The model was evaluated using measurements of air pollution. Optical properties of aerosol pollutants such as light absorption and scattering plus chemical species mass concentrations were measured with a photoacoustic spectrometer, a reciprocal nephelometer, and an aerosol mass spectrometer in Mexico City in the context of the multinational project "Megacity Initiative: Local And Global Research Observations (MILAGRO)" in March 2006. Aerosol light absorption and scattering measurements were also obtained for Reno and Las Vegas, NV USA in December 2008-March 2009 and January-February 2003, respectively. In all three cities, the morning scattering peak occurs a few hours later than the absorption peak due to the formation of secondary photochemically produced aerosols. In particular, for Mexico City we determined the fraction of photochemically generated secondary aerosols to be about 75% of total aerosol mass concentration at its peak near midday. The simple 2-d box model suggests that commonly emitted primary air pollutant (e.g., black carbon) mass concentrations scale approximately as the square root of the urban population. This argument extends to the absorption coefficient, as it is approximately proportional to the black carbon mass concentration. Since urban secondary pollutants form through photochemical reactions involving primary precursors, in linear approximation their mass concentration also should scale with the square root of population. Therefore, the scattering coefficient, a proxy for particulate matter mass concentration, is also expected to scale the same way. Experimental data for five cities: Mexico City, Mexico; Las Vegas and Reno, NV, USA; Beijing, China; and Delhi, India (the data for the last two cities were obtained from the literature); are in reasonable accord with the model. The scaling relation provided by the model may be considered a useful metric depending on the assumption that specific city conditions (such as latitude, altitude, local meteorological conditions, degree of industrialization, population density, number of cars per capita, city shape, etc.) vary randomly, independent of city size. While more detailed studies (including data from more cities) are needed, we believe that this relatively weak dependence of the pollution concentration on the city population might help to explain why the worsening of urban air quality does not directly lead to a decrease in the rate of growth in city population.

Allee effect from parasite spill-back.

PubMed

Krkošek, Martin; Ashander, Jaime; Frazer, L Neil; Lewis, Mark A

2013-11-01

The exchange of native pathogens between wild and domesticated animals can lead to novel disease threats to wildlife. However, the dynamics of wild host-parasite systems exposed to a reservoir of domesticated hosts are not well understood. A simple mathematical model reveals that the spill-back of native parasites from domestic to wild hosts may cause a demographic Allee effect in the wild host population. A second model is tailored to the particulars of pink salmon (Oncorhynchus gorbuscha) and salmon lice (Lepeophtheirus salmonis), for which parasite spill-back is a conservation and fishery concern. In both models, parasite spill-back weakens the coupling of parasite and wild host abundance-particularly at low host abundance-causing parasites per host to increase as a wild host population declines. These findings show that parasites shared across host populations have effects analogous to those of generalist predators and can similarly cause an unstable equilibrium in a focal host population that separates persistence and extirpation. Allee effects in wildlife arising from parasite spill-back are likely to be most pronounced in systems where the magnitude of transmission from domestic to wild host populations is high because of high parasite abundance in domestic hosts, prolonged sympatry of domestic and wild hosts, a high transmission coefficient for parasites, long-lived parasite larvae, and proximity of domesticated populations to wildlife migration corridors.

How many Laysan Teal Anas laysanensis are on Midway Atoll? Methods for monitoring abundance after reintroduction

USGS Publications Warehouse

Reynolds, Michelle H.; Courtot, Karen; Hatfield, Jeffrey

2017-01-01

Wildlife managers often request a simple approach to monitor the status of species of concern. In response to that need, we used eight years of monitoring data to estimate population size and test the validity of an index for monitoring accurately the abundance of reintroduced, endangered Laysan Teal Anas laysanensis. The population was established at Midway Atoll in the Hawaiian archipelago after 42 wild birds were translocated from Laysan Island during 2004–2005. We fitted 587 birds with unique markers during 2004–2015, recorded 21,309 sightings until March 2016, and conducted standardised survey counts during 2007–2015. A modified Lincoln-Petersen mark-resight estimator and ANCOVA models were used to test the relationship between survey counts, seasonal detectability, and population abundance. Differences were found between the breeding and non-breeding seasons in detection and how maximum counts recorded related to population estimates. The results showed strong, positive correlations between the seasonal maximum counts and population estimates. The ANCOVA models supported the use of standardised bi-monthly counts of unmarked birds as a valid index to monitor trends among years within a season at Midway Atoll. The translocated population increased to 661 adult and juvenile birds (95% CI = 608–714) by 2010, then declined by 38% between 2010 and 2012 after the Toˉhoku Japan earthquake-generated tsunami inundated 41% of the atoll and triggered an Avian Botulism type C Clostridium botulinum outbreak. Following another severe botulism outbreak during 2015, the population experienced a 37% decline. Data indicated that the Midway Atoll population, like the founding Laysan Island population, is susceptible to catastrophic population declines. Consistent standardised monitoring using simple counts, in place of mark-recapture and resightings surveys, can be used to evaluate population status over the long-term. We estimate there were 314–435 Laysan Teal (95% CI for population estimate; point estimate = 375 individuals) at Midway Atoll in 2015; c. 50% of the global population. In comparison, the most recent estimate for numbers on Laysan Island was of 339 individuals in 2012 (95% CI = 265–413). We suggest that this approach can be used to validate a survey index for any marked, reintroduced resident wildlife population.

Complex discrete dynamics from simple continuous population models.

PubMed

Gamarra, Javier G P; Solé, Ricard V

2002-05-01

Nonoverlapping generations have been classically modelled as difference equations in order to account for the discrete nature of reproductive events. However, other events such as resource consumption or mortality are continuous and take place in the within-generation time. We have realistically assumed a hybrid ODE bidimensional model of resources and consumers with discrete events for reproduction. Numerical and analytical approaches showed that the resulting dynamics resembles a Ricker map, including the doubling route to chaos. Stochastic simulations with a handling-time parameter for indirect competition of juveniles may affect the qualitative behaviour of the model.

Endogenous technological and demographic change under increasing water scarcity

NASA Astrophysics Data System (ADS)

Pande, Saket; Ertsen, Maurits; Sivapalan, Murugesu

2014-05-01

The ancient civilization in the Indus Valley civilization dispersed under extreme dry conditions; there are indications that the same holds for many other ancient societies. Even contemporary societies, such as the one in Murrumbidgee river basin in Australia, have started to witness a decline in overall population under increasing water scarcity. Hydroclimatic change may not be the sole predictor of the fate of contemporary societies in water scarce regions and many critics of such (perceived) hydroclimatic determinism have suggested that technological change may ameliorate the effects of increasing water scarcity and as such counter the effects of hydroclimatic changes. To study the role of technological change on the dynamics of coupled human-water systems, we develop a simple overlapping-generations model of endogenous technological and demographic change. We model technological change as an endogenous process that depends on factors such as the investments that are (endogenously) made in a society, the (endogenous) diversification of a society into skilled and unskilled workers, a society's patience in terms of its present consumption vs. future consumption, production technology and the (endogenous) interaction of all of these factors. In the model the population growth rate is programmed to decline once consumption per capita crosses a "survival" threshold. This means we do not treat technology as an exogenous random sequence of events, but instead assume that it results (endogenously) from societal actions. The model demonstrates that technological change may indeed ameliorate the effects of increasing water scarcity but typically it does so only to a certain extent. It is possible that technological change may allow a society to escape the effect of increasing water scarcity, leading to a (super)-exponential rise in technology and population. However, such cases require the rate of success of investment in technological advancement to be high. In other more realistic cases of technological success, we find that endogenous technology change only helps to delay the peak of population size before it inevitably starts to decline. While the model is a rather simple model of societal development, it is shown to be capable of replicating patterns of technological and population changes. It is capable of replicating the pattern of declining consumption per capita in presence of growth in aggregate production. It is also capable of replicating an exponential population rise, even under increasing water scarcity. The results of the model suggest that societies that declined or are declining in the face of extreme water scarcity may have done so due to slower rate of success of investment in technological advancement. The model suggests that the population decline occurs after a prolonged decline in consumption per capita, which in turn is due to the joint effect of initially increasing population and increasing water scarcity. This is despite technological advancement and increase in aggregate production. We suggest that declining consumption per capita despite technological advancement and increase in aggregate production may serve as a useful predictor of upcoming decline in contemporary societies in water scarce basins.

Modeling the Pre-Industrial Roots of Modern Super-Exponential Population Growth

PubMed Central

Stutz, Aaron Jonas

2014-01-01

To Malthus, rapid human population growth—so evident in 18th Century Europe—was obviously unsustainable. In his Essay on the Principle of Population, Malthus cogently argued that environmental and socioeconomic constraints on population rise were inevitable. Yet, he penned his essay on the eve of the global census size reaching one billion, as nearly two centuries of super-exponential increase were taking off. Introducing a novel extension of J. E. Cohen's hallmark coupled difference equation model of human population dynamics and carrying capacity, this article examines just how elastic population growth limits may be in response to demographic change. The revised model involves a simple formalization of how consumption costs influence carrying capacity elasticity over time. Recognizing that complex social resource-extraction networks support ongoing consumption-based investment in family formation and intergenerational resource transfers, it is important to consider how consumption has impacted the human environment and demography—especially as global population has become very large. Sensitivity analysis of the consumption-cost model's fit to historical population estimates, modern census data, and 21st Century demographic projections supports a critical conclusion. The recent population explosion was systemically determined by long-term, distinctly pre-industrial cultural evolution. It is suggested that modern globalizing transitions in technology, susceptibility to infectious disease, information flows and accumulation, and economic complexity were endogenous products of much earlier biocultural evolution of family formation's embeddedness in larger, hierarchically self-organizing cultural systems, which could potentially support high population elasticity of carrying capacity. Modern super-exponential population growth cannot be considered separately from long-term change in the multi-scalar political economy that connects family formation and intergenerational resource transfers to wider institutions and social networks. PMID:25141019

Coin hoards speak of population declines in Ancient Rome

PubMed Central

Turchin, Peter; Scheidel, Walter

2009-01-01

In times of violence, people tend to hide their valuables, which are later recovered unless the owners had been killed or driven away. Thus, the temporal distribution of unrecovered coin hoards is an excellent proxy for the intensity of internal warfare. We use this relationship to resolve a long-standing controversy in Roman history. Depending on who was counted in the early Imperial censuses (adult males or the entire citizenry including women and minors), the Roman citizen population of Italy either declined, or more than doubled, during the first century BCE. This period was characterized by a series of civil wars, and historical evidence indicates that high levels of sociopolitical instability are associated with demographic contractions. We fitted a simple model quantifying the effect of instability (proxied by hoard frequency) on population dynamics to the data before 100 BCE. The model predicts declining population after 100 BCE. This suggests that the vigorous growth scenario is highly implausible. PMID:19805043

Social inheritance can explain the structure of animal social networks

PubMed Central

Ilany, Amiyaal; Akçay, Erol

2016-01-01

The social network structure of animal populations has major implications for survival, reproductive success, sexual selection and pathogen transmission of individuals. But as of yet, no general theory of social network structure exists that can explain the diversity of social networks observed in nature, and serve as a null model for detecting species and population-specific factors. Here we propose a simple and generally applicable model of social network structure. We consider the emergence of network structure as a result of social inheritance, in which newborns are likely to bond with maternal contacts, and via forming bonds randomly. We compare model output with data from several species, showing that it can generate networks with properties such as those observed in real social systems. Our model demonstrates that important observed properties of social networks, including heritability of network position or assortative associations, can be understood as consequences of social inheritance. PMID:27352101

A circular model for song motor control in Serinus canaria

PubMed Central

Alonso, Rodrigo G.; Trevisan, Marcos A.; Amador, Ana; Goller, Franz; Mindlin, Gabriel B.

2015-01-01

Song production in songbirds is controlled by a network of nuclei distributed across several brain regions, which drives respiratory and vocal motor systems to generate sound. We built a model for birdsong production, whose variables are the average activities of different neural populations within these nuclei of the song system. We focus on the predictions of respiratory patterns of song, because these can be easily measured and therefore provide a validation for the model. We test the hypothesis that it is possible to construct a model in which (1) the activity of an expiratory related (ER) neural population fits the observed pressure patterns used by canaries during singing, and (2) a higher forebrain neural population, HVC, is sparsely active, simultaneously with significant motor instances of the pressure patterns. We show that in order to achieve these two requirements, the ER neural population needs to receive two inputs: a direct one, and its copy after being processed by other areas of the song system. The model is capable of reproducing the measured respiratory patterns and makes specific predictions on the timing of HVC activity during their production. These results suggest that vocal production is controlled by a circular network rather than by a simple top-down architecture. PMID:25904860

Evolution of the rate of biological aging using a phenotype based computational model.

PubMed

Kittas, Aristotelis

2010-10-07

In this work I introduce a simple model to study how natural selection acts upon aging, which focuses on the viability of each individual. It is able to reproduce the Gompertz law of mortality and can make predictions about the relation between the level of mutation rates (beneficial/deleterious/neutral), age at reproductive maturity and the degree of biological aging. With no mutations, a population with low age at reproductive maturity R stabilizes at higher density values, while with mutations it reaches its maximum density, because even for large pre-reproductive periods each individual evolves to survive to maturity. Species with very short pre-reproductive periods can only tolerate a small number of detrimental mutations. The probabilities of detrimental (P(d)) or beneficial (P(b)) mutations are demonstrated to greatly affect the process. High absolute values produce peaks in the viability of the population over time. Mutations combined with low selection pressure move the system towards weaker phenotypes. For low values in the ratio P(d)/P(b), the speed at which aging occurs is almost independent of R, while higher values favor significantly species with high R. The value of R is critical to whether the population survives or dies out. The aging rate is controlled by P(d) and P(b) and the amount of the viability of each individual is modified, with neutral mutations allowing the system more "room" to evolve. The process of aging in this simple model is revealed to be fairly complex, yielding a rich variety of results. 2010 Elsevier Ltd. All rights reserved.

Time Evolving Fission Chain Theory and Fast Neutron and Gamma-Ray Counting Distributions

DOE PAGES

Kim, K. S.; Nakae, L. F.; Prasad, M. K.; ...

2015-11-01

Here, we solve a simple theoretical model of time evolving fission chains due to Feynman that generalizes and asymptotically approaches the point model theory. The point model theory has been used to analyze thermal neutron counting data. This extension of the theory underlies fast counting data for both neutrons and gamma rays from metal systems. Fast neutron and gamma-ray counting is now possible using liquid scintillator arrays with nanosecond time resolution. For individual fission chains, the differential equations describing three correlated probability distributions are solved: the time-dependent internal neutron population, accumulation of fissions in time, and accumulation of leaked neutronsmore » in time. Explicit analytic formulas are given for correlated moments of the time evolving chain populations. The equations for random time gate fast neutron and gamma-ray counting distributions, due to randomly initiated chains, are presented. Correlated moment equations are given for both random time gate and triggered time gate counting. There are explicit formulas for all correlated moments are given up to triple order, for all combinations of correlated fast neutrons and gamma rays. The nonlinear differential equations for probabilities for time dependent fission chain populations have a remarkably simple Monte Carlo realization. A Monte Carlo code was developed for this theory and is shown to statistically realize the solutions to the fission chain theory probability distributions. Combined with random initiation of chains and detection of external quanta, the Monte Carlo code generates time tagged data for neutron and gamma-ray counting and from these data the counting distributions.« less

Factors influencing the output of rural cataract surgical facilities in China: the SHARP study.

PubMed

Chen, Tingting; Jin, Ling; Zhou, Zhongqiang; Huang, Yiwen; Yan, Xixi; Liu, Tianyu; Ong, Ee Lin; Liu, Bin; Huang, Wenyong; Iezzi, Beatrice; He, Mingguang; Friedman, David S; Congdon, Nathan G

2015-02-03

To identify factors associated prospectively with increased cataract surgical rate (CSR) in rural Chinese hospitals. Annual cataract surgical output was obtained at baseline and 24 months later from operating room records at 42 rural, county-level hospitals. Total local CSR (cases/million population/y), and proportion of CSR from hospital and local competitors were calculated from government records. Hospital administrators completed questionnaires providing demographic and professional information, and annual clinic and outreach screening volume. Independent cataract surgeons provided clinical information and videotapes of cases for grading by two masked experts using the Ophthalmology Surgical Competency Assessment Rubric (OSCAR). Uncorrected vision was recorded for 10 consecutive cataract cases at each facility, and 10 randomly-identified patients completed hospital satisfaction questionnaires. Total value of international nongovernmental development organization (INGDO) investment in the previous three years and demographic information on hospital catchment areas were obtained. Main outcome was 2-year percentage change in hospital CSR. Among the 42 hospitals (median catchment population 530,000, median hospital CSR 643), 78.6% (33/42) were receiving INGDO support. Median change in hospital CSR (interquartile range) was 33.3% (-6.25%, 72.3%). Predictors of greater increase in CSR included higher INGDO investment (P = 0.02, simple model), reducing patient dissatisfaction (P = 0.03, simple model), and more outreach patient screening (P = 0.002, simple and multiple model). Outreach cataract screening was the strongest predictor of increased surgical output. Government and INGDO investment in screening may be most likely to enhance output of county hospitals, a major goal of China's Blindness Prevention Plan. Copyright 2015 The Association for Research in Vision and Ophthalmology, Inc.

Factors affecting the abundance and distribution of European starlings at the San Joaquin Experimental Range

Treesearch

Kathryn L. Purcell; Jared Verner; Sylvia R. Mori

2002-01-01

We examined population trends and factors related to the abundance and presence of European starlings (Sturnus vulgaris) at the San Joaquin Experimental Range in the foothills of the western Sierra Nevada, 31 km east of Madera, California. Starlings first appeared there in low numbers in the late 1960s and are now abundant breeders. Simple models...

Hands-On! Living in the Biosphere: Production, Pattern, Population, and Diversity. Developing Active Learning Module on the Human Dimensions of Global Change.

ERIC Educational Resources Information Center

Brown, Dwight

Biogeography examines questions of organism inventory and pattern, organisms' interactions with the environment, and the processes that create and change inventory, pattern, and interactions. This learning module uses time series maps and simple simulation models to illustrate how human actions alter biological productivity patterns at local and…

Application of the urban mixing-depth concept to air pollution problems

Treesearch

Peter W. Summers

1977-01-01

A simple urban mixing-depth model is used to develop an indicator of downtown pollution concentrations based on emission strength, rural temperature lapse rate, wind speed, city heat input, and city size. It is shown that the mean annual downtown suspended particulate levels in Canadian cities are proportional to the fifth root of the population. The implications of...

Representation of limb kinematics in Purkinje cell simple spike discharge is conserved across multiple tasks.

PubMed

Hewitt, Angela L; Popa, Laurentiu S; Pasalar, Siavash; Hendrix, Claudia M; Ebner, Timothy J

2011-11-01

Encoding of movement kinematics in Purkinje cell simple spike discharge has important implications for hypotheses of cerebellar cortical function. Several outstanding questions remain regarding representation of these kinematic signals. It is uncertain whether kinematic encoding occurs in unpredictable, feedback-dependent tasks or kinematic signals are conserved across tasks. Additionally, there is a need to understand the signals encoded in the instantaneous discharge of single cells without averaging across trials or time. To address these questions, this study recorded Purkinje cell firing in monkeys trained to perform a manual random tracking task in addition to circular tracking and center-out reach. Random tracking provides for extensive coverage of kinematic workspaces. Direction and speed errors are significantly greater during random than circular tracking. Cross-correlation analyses comparing hand and target velocity profiles show that hand velocity lags target velocity during random tracking. Correlations between simple spike firing from 120 Purkinje cells and hand position, velocity, and speed were evaluated with linear regression models including a time constant, τ, as a measure of the firing lead/lag relative to the kinematic parameters. Across the population, velocity accounts for the majority of simple spike firing variability (63 ± 30% of R(adj)(2)), followed by position (28 ± 24% of R(adj)(2)) and speed (11 ± 19% of R(adj)(2)). Simple spike firing often leads hand kinematics. Comparison of regression models based on averaged vs. nonaveraged firing and kinematics reveals lower R(adj)(2) values for nonaveraged data; however, regression coefficients and τ values are highly similar. Finally, for most cells, model coefficients generated from random tracking accurately estimate simple spike firing in either circular tracking or center-out reach. These findings imply that the cerebellum controls movement kinematics, consistent with a forward internal model that predicts upcoming limb kinematics.

Vaccine effects on heterogeneity in susceptibility and implications for population health management

USGS Publications Warehouse

Langwig, Kate E.; Wargo, Andrew R.; Jones, Darbi R.; Viss, Jessie R.; Rutan, Barbara J.; Egan, Nicholas A.; Sá-Guimarães, Pedro; Min Sun Kim,; Kurath, Gael; Gomes, M. Gabriela M.; Lipsitch, Marc; Bansal, Shweta; Pettigrew, Melinda M.

2017-01-01

Heterogeneity in host susceptibility is a key determinant of infectious disease dynamics but is rarely accounted for in assessment of disease control measures. Understanding how susceptibility is distributed in populations, and how control measures change this distribution, is integral to predicting the course of epidemics with and without interventions. Using multiple experimental and modeling approaches, we show that rainbow trout have relatively homogeneous susceptibility to infection with infectious hematopoietic necrosis virus and that vaccination increases heterogeneity in susceptibility in a nearly all-or-nothing fashion. In a simple transmission model with an R0 of 2, the highly heterogeneous vaccine protection would cause a 35 percentage-point reduction in outbreak size over an intervention inducing homogenous protection at the same mean level. More broadly, these findings provide validation of methodology that can help to reduce biases in predictions of vaccine impact in natural settings and provide insight into how vaccination shapes population susceptibility.

Rhythmic behavior in a two-population mean-field Ising model

NASA Astrophysics Data System (ADS)

Collet, Francesca; Formentin, Marco; Tovazzi, Daniele

2016-10-01

Many real systems composed of a large number of interacting components, as, for instance, neural networks, may exhibit collective periodic behavior even though single components have no natural tendency to behave periodically. Macroscopic oscillations are indeed one of the most common self-organized behavior observed in living systems. In the present paper we study some dynamical features of a two-population generalization of the mean-field Ising model with the scope of investigating simple mechanisms capable to generate rhythms in large groups of interacting individuals. We show that the system may undergo a transition from a disordered phase, where the magnetization of each population fluctuates closely around zero, to a phase in which they both display a macroscopic regular rhythm. In particular, there exists a region in the parameter space where having two groups of spins with inter- and intrapopulation interactions of different strengths suffices for the emergence of a robust periodic behavior.

Assortative mating and mutation diffusion in spatial evolutionary systems

NASA Astrophysics Data System (ADS)

Paley, C. J.; Taraskin, S. N.; Elliott, S. R.

2010-04-01

The influence of spatial structure on the equilibrium properties of a sexual population model defined on networks is studied numerically. Using a small-world-like topology of the networks as an investigative tool, the contributions to the fitness of assortative mating and of global mutant spread properties are considered. Simple measures of nearest-neighbor correlations and speed of spread of mutants through the system have been used to confirm that both of these dynamics are important contributory factors to the fitness. It is found that assortative mating increases the fitness of populations. Quick global spread of favorable mutations is shown to be a key factor increasing the equilibrium fitness of populations.

Stochastic recruitment leads to symmetry breaking in foraging populations

NASA Astrophysics Data System (ADS)

Biancalani, Tommaso; Dyson, Louise; McKane, Alan

2014-03-01

When an ant colony is faced with two identical equidistant food sources, the foraging ants are found to concentrate more on one source than the other. Analogous symmetry-breaking behaviours have been reported in various population systems, (such as queueing or stock market trading) suggesting the existence of a simple universal mechanism. Past studies have neglected the effect of demographic noise and required rather complicated models to qualitatively reproduce this behaviour. I will show how including the effects of demographic noise leads to a radically different conclusion. The symmetry-breaking arises solely due to the process of recruitment and ceases to occur for large population sizes. The latter fact provides a testable prediction for a real system.

Malthusian dynamics in a diverging Europe: Northern Italy, 1650-1881.

PubMed

Fernihough, Alan

2013-02-01

Recent empirical research questions the validity of using Malthusian theory in preindustrial England. Using real wage and vital rate data for the years 1650-1881, I provide empirical estimates for a different region: Northern Italy. The empirical methodology is theoretically underpinned by a simple Malthusian model, in which population, real wages, and vital rates are determined endogenously. My findings strongly support the existence of a Malthusian economy wherein population growth decreased living standards, which in turn influenced vital rates. However, these results also demonstrate how the system is best characterized as one of weak homeostasis. Furthermore, there is no evidence of Boserupian effects given that increases in population failed to spur any sustained technological progress.

Growth dynamics and the evolution of cooperation in microbial populations

NASA Astrophysics Data System (ADS)

Cremer, Jonas; Melbinger, Anna; Frey, Erwin

2012-02-01

Microbes providing public goods are widespread in nature despite running the risk of being exploited by free-riders. However, the precise ecological factors supporting cooperation are still puzzling. Following recent experiments, we consider the role of population growth and the repetitive fragmentation of populations into new colonies mimicking simple microbial life-cycles. Individual-based modeling reveals that demographic fluctuations, which lead to a large variance in the composition of colonies, promote cooperation. Biased by population dynamics these fluctuations result in two qualitatively distinct regimes of robust cooperation under repetitive fragmentation into groups. First, if the level of cooperation exceeds a threshold, cooperators will take over the whole population. Second, cooperators can also emerge from a single mutant leading to a robust coexistence between cooperators and free-riders. We find frequency and size of population bottlenecks, and growth dynamics to be the major ecological factors determining the regimes and thereby the evolutionary pathway towards cooperation.

Ordering structured populations in multiplayer cooperation games

PubMed Central

Peña, Jorge; Wu, Bin; Traulsen, Arne

2016-01-01

Spatial structure greatly affects the evolution of cooperation. While in two-player games the condition for cooperation to evolve depends on a single structure coefficient, in multiplayer games the condition might depend on several structure coefficients, making it difficult to compare different population structures. We propose a solution to this issue by introducing two simple ways of ordering population structures: the containment order and the volume order. If population structure is greater than population structure in the containment or the volume order, then can be considered a stronger promoter of cooperation. We provide conditions for establishing the containment order, give general results on the volume order, and illustrate our theory by comparing different models of spatial games and associated update rules. Our results hold for a large class of population structures and can be easily applied to specific cases once the structure coefficients have been calculated or estimated. PMID:26819335

Reionization Models Classifier using 21cm Map Deep Learning

NASA Astrophysics Data System (ADS)

Hassan, Sultan; Liu, Adrian; Kohn, Saul; Aguirre, James E.; La Plante, Paul; Lidz, Adam

2018-05-01

Next-generation 21cm observations will enable imaging of reionization on very large scales. These images will contain more astrophysical and cosmological information than the power spectrum, and hence providing an alternative way to constrain the contribution of different reionizing sources populations to cosmic reionization. Using Convolutional Neural Networks, we present a simple network architecture that is sufficient to discriminate between Galaxy-dominated versus AGN-dominated models, even in the presence of simulated noise from different experiments such as the HERA and SKA.

Synchronisation of chaos and its applications

NASA Astrophysics Data System (ADS)

Eroglu, Deniz; Lamb, Jeroen S. W.; Pereira, Tiago

2017-07-01

Dynamical networks are important models for the behaviour of complex systems, modelling physical, biological and societal systems, including the brain, food webs, epidemic disease in populations, power grids and many other. Such dynamical networks can exhibit behaviour in which deterministic chaos, exhibiting unpredictability and disorder, coexists with synchronisation, a classical paradigm of order. We survey the main theory behind complete, generalised and phase synchronisation phenomena in simple as well as complex networks and discuss applications to secure communications, parameter estimation and the anticipation of chaos.

Some queuing network models of computer systems

NASA Technical Reports Server (NTRS)

Herndon, E. S.

1980-01-01

Queuing network models of a computer system operating with a single workload type are presented. Program algorithms are adapted for use on the Texas Instruments SR-52 programmable calculator. By slightly altering the algorithm to process the G and H matrices row by row instead of column by column, six devices and an unlimited job/terminal population could be handled on the SR-52. Techniques are also introduced for handling a simple load dependent server and for studying interactive systems with fixed multiprogramming limits.

The simcyp population based simulator: architecture, implementation, and quality assurance.

PubMed

Jamei, Masoud; Marciniak, Steve; Edwards, Duncan; Wragg, Kris; Feng, Kairui; Barnett, Adrian; Rostami-Hodjegan, Amin

2013-01-01

Developing a user-friendly platform that can handle a vast number of complex physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) models both for conventional small molecules and larger biologic drugs is a substantial challenge. Over the last decade the Simcyp Population Based Simulator has gained popularity in major pharmaceutical companies (70% of top 40 - in term of R&D spending). Under the Simcyp Consortium guidance, it has evolved from a simple drug-drug interaction tool to a sophisticated and comprehensive Model Based Drug Development (MBDD) platform that covers a broad range of applications spanning from early drug discovery to late drug development. This article provides an update on the latest architectural and implementation developments within the Simulator. Interconnection between peripheral modules, the dynamic model building process and compound and population data handling are all described. The Simcyp Data Management (SDM) system, which contains the system and drug databases, can help with implementing quality standards by seamless integration and tracking of any changes. This also helps with internal approval procedures, validation and auto-testing of the new implemented models and algorithms, an area of high interest to regulatory bodies.

Estimating population trends with a linear model

USGS Publications Warehouse

Bart, Jonathan; Collins, Brian D.; Morrison, R.I.G.

2003-01-01

We describe a simple and robust method for estimating trends in population size. The method may be used with Breeding Bird Survey data, aerial surveys, point counts, or any other program of repeated surveys at permanent locations. Surveys need not be made at each location during each survey period. The method differs from most existing methods in being design based, rather than model based. The only assumptions are that the nominal sampling plan is followed and that sample size is large enough for use of the t-distribution. Simulations based on two bird data sets from natural populations showed that the point estimate produced by the linear model was essentially unbiased even when counts varied substantially and 25% of the complete data set was missing. The estimating-equation approach, often used to analyze Breeding Bird Survey data, performed similarly on one data set but had substantial bias on the second data set, in which counts were highly variable. The advantages of the linear model are its simplicity, flexibility, and that it is self-weighting. A user-friendly computer program to carry out the calculations is available from the senior author.

Characteristics of pattern formation and evolution in approximations of Physarum transport networks.

PubMed

Jones, Jeff

2010-01-01

Most studies of pattern formation place particular emphasis on its role in the development of complex multicellular body plans. In simpler organisms, however, pattern formation is intrinsic to growth and behavior. Inspired by one such organism, the true slime mold Physarum polycephalum, we present examples of complex emergent pattern formation and evolution formed by a population of simple particle-like agents. Using simple local behaviors based on chemotaxis, the mobile agent population spontaneously forms complex and dynamic transport networks. By adjusting simple model parameters, maps of characteristic patterning are obtained. Certain areas of the parameter mapping yield particularly complex long term behaviors, including the circular contraction of network lacunae and bifurcation of network paths to maintain network connectivity. We demonstrate the formation of irregular spots and labyrinthine and reticulated patterns by chemoattraction. Other Turing-like patterning schemes were obtained by using chemorepulsion behaviors, including the self-organization of regular periodic arrays of spots, and striped patterns. We show that complex pattern types can be produced without resorting to the hierarchical coupling of reaction-diffusion mechanisms. We also present network behaviors arising from simple pre-patterning cues, giving simple examples of how the emergent pattern formation processes evolve into networks with functional and quasi-physical properties including tensionlike effects, network minimization behavior, and repair to network damage. The results are interpreted in relation to classical theories of biological pattern formation in natural systems, and we suggest mechanisms by which emergent pattern formation processes may be used as a method for spatially represented unconventional computation.

Intelligent systems in the context of surrounding environment.

PubMed

Wakeling, J; Bak, P

2001-11-01

We investigate the behavioral patterns of a population of agents, each controlled by a simple biologically motivated neural network model, when they are set in competition against each other in the minority model of Challet and Zhang. We explore the effects of changing agent characteristics, demonstrating that crowding behavior takes place among agents of similar memory, and show how this allows unique "rogue" agents with higher memory values to take advantage of a majority population. We also show that agents' analytic capability is largely determined by the size of the intermediary layer of neurons. In the context of these results, we discuss the general nature of natural and artificial intelligence systems, and suggest intelligence only exists in the context of the surrounding environment (embodiment).

Relation of the runaway avalanche threshold to momentum space topology

NASA Astrophysics Data System (ADS)

McDevitt, Christopher J.; Guo, Zehua; Tang, Xian-Zhu

2018-02-01

The underlying physics responsible for the formation of an avalanche instability due to the generation of secondary electrons is studied. A careful examination of the momentum space topology of the runaway electron population is carried out with an eye toward identifying how qualitative changes in the momentum space of the runaway electrons is correlated with the avalanche threshold. It is found that the avalanche threshold is tied to the merger of an O and X point in the momentum space of the primary runaway electron population. Such a change of the momentum space topology is shown to be accurately described by a simple analytic model, thus providing a powerful means of determining the avalanche threshold for a range of model assumptions.

Understanding diversity–stability relationships: towards a unified model of portfolio effects

PubMed Central

Thibaut, Loïc M; Connolly, Sean R; He, Fangliang

2013-01-01

A major ecosystem effect of biodiversity is to stabilise assemblages that perform particular functions. However, diversity–stability relationships (DSRs) are analysed using a variety of different population and community properties, most of which are adopted from theory that makes several restrictive assumptions that are unlikely to be reflected in nature. Here, we construct a simple synthesis and generalisation of previous theory for the DSR. We show that community stability is a product of two quantities: the synchrony of population fluctuations, and an average species-level population stability that is weighted by relative abundance. Weighted average population stability can be decomposed to consider effects of the mean-variance scaling of abundance, changes in mean abundance with diversity and differences in species' mean abundance in monoculture. Our framework makes explicit how unevenness in the abundances of species in real communities influences the DSR, which occurs both through effects on community synchrony, and effects on weighted average population variability. This theory provides a more robust framework for analysing the results of empirical studies of the DSR, and facilitates the integration of findings from real and model communities. PMID:23095077

Econometric studies of urban population density: a survey.

PubMed

Mcdonald, J F

1989-01-01

This paper presents the 1st reasonably comprehensive survey of empirical research of urban population densities since the publication of the book by Edmonston in 1975. The survey summarizes contributions to empirical knowledge that have been made since 1975 and points toward possible areas for additional research. The paper also provides a brief interpretative intellectual history of the topic. It begins with a personal overview of research in the field. The next section discusses econometric issues that arise in the estimation of population density functions in which density is a function only of a distance to the central business district of the urban area. Section 4 summarizes the studies of a single urban area that went beyond the estimation of simple distance-density functions, and Section 5 discusses studies that sought to explain the variations across urban areas in population density patterns. McDonald refers to the standard theory of urban population density throughout the paper. This basic model is presented in the textbook by Mills and Hamilton and it is assumed that the reader is familiar with the model.

Inference of population splits and mixtures from genome-wide allele frequency data.

PubMed

Pickrell, Joseph K; Pritchard, Jonathan K

2012-01-01

Many aspects of the historical relationships between populations in a species are reflected in genetic data. Inferring these relationships from genetic data, however, remains a challenging task. In this paper, we present a statistical model for inferring the patterns of population splits and mixtures in multiple populations. In our model, the sampled populations in a species are related to their common ancestor through a graph of ancestral populations. Using genome-wide allele frequency data and a Gaussian approximation to genetic drift, we infer the structure of this graph. We applied this method to a set of 55 human populations and a set of 82 dog breeds and wild canids. In both species, we show that a simple bifurcating tree does not fully describe the data; in contrast, we infer many migration events. While some of the migration events that we find have been detected previously, many have not. For example, in the human data, we infer that Cambodians trace approximately 16% of their ancestry to a population ancestral to other extant East Asian populations. In the dog data, we infer that both the boxer and basenji trace a considerable fraction of their ancestry (9% and 25%, respectively) to wolves subsequent to domestication and that East Asian toy breeds (the Shih Tzu and the Pekingese) result from admixture between modern toy breeds and "ancient" Asian breeds. Software implementing the model described here, called TreeMix, is available at http://treemix.googlecode.com.

Simple model for lambda-doublet propensities in bimolecular reactions

NASA Technical Reports Server (NTRS)

Bronikowski, Michael J.; Zare, Richard N.

1990-01-01

A simple geometric model is presented to account for lambda-doublet propensities in bimolecular reactions A + BC - AB + C. It applies to reactions in which AB is formed in a pi state, and in which the unpaired molecular orbital responsible for lambda-doubling arises from breaking the B-C bond. The lambda-doublet population ratio is predicted to be 2:1 provided that: (1) the motion of A in the transition state determines the plane of rotation of AB; (2) the unpaired pi orbital lying initially along the B-C bond may be resolved into a projection onto the AB plane of rotation and a projection perpendicular to this plane; (3) there is no preferred geometry for dissociation of ABC. The 2:1 lambda-doublet ratio is the 'unconstrained dynamics prior' lambda-doublet distribution for such reactions.

Development of a simple and low cost microbioreactor for high-throughput bioprocessing.

PubMed

Rahman, Pattanathu K S M; Pasirayi, Godfrey; Auger, Vincent; Ali, Zulfiqur

2009-02-01

A simple microbioreactor for high-throughput bioprocessing made from low cost polymer polytetrafluoroethylene (PTFE) tubes with a working volume of 1.5 ml is described. We have developed a microfluidic system that handles a small population of cells of a model microorganism, Pseudomonas aeruginosa DS10-129. Under the conditions of the microbioreactor, the organism produced extracellular secondary metabolites by using nutrient broth modified with glycerol. Pyocyanins were isolated from the fermented medium as a metabolite of interest. Antibiotic properties of pyocyanin were effective against a number of microorganisms such as Staphylococcus aureus, S. epidermis, Bacillus subtilis, Micrococcus luteus and Saccharomyces cerevisiae. Batch fermentation of the model organism in the microbioreactor was compared to shake-flask and conventional bench fermenter methods. Results obtained from the microbioreactor compared favourably with the conventional processes.

A Probabilistic Model for Cushing's Syndrome Screening in At-Risk Populations: A Prospective Multicenter Study.

PubMed

León-Justel, Antonio; Madrazo-Atutxa, Ainara; Alvarez-Rios, Ana I; Infantes-Fontán, Rocio; Garcia-Arnés, Juan A; Lillo-Muñoz, Juan A; Aulinas, Anna; Urgell-Rull, Eulàlia; Boronat, Mauro; Sánchez-de-Abajo, Ana; Fajardo-Montañana, Carmen; Ortuño-Alonso, Mario; Salinas-Vert, Isabel; Granada, Maria L; Cano, David A; Leal-Cerro, Alfonso

2016-10-01

Cushing's syndrome (CS) is challenging to diagnose. Increased prevalence of CS in specific patient populations has been reported, but routine screening for CS remains questionable. To decrease the diagnostic delay and improve disease outcomes, simple new screening methods for CS in at-risk populations are needed. To develop and validate a simple scoring system to predict CS based on clinical signs and an easy-to-use biochemical test. Observational, prospective, multicenter. Referral hospital. A cohort of 353 patients attending endocrinology units for outpatient visits. All patients were evaluated with late-night salivary cortisol (LNSC) and a low-dose dexamethasone suppression test for CS. Diagnosis or exclusion of CS. Twenty-six cases of CS were diagnosed in the cohort. A risk scoring system was developed by logistic regression analysis, and cutoff values were derived from a receiver operating characteristic curve. This risk score included clinical signs and symptoms (muscular atrophy, osteoporosis, and dorsocervical fat pad) and LNSC levels. The estimated area under the receiver operating characteristic curve was 0.93, with a sensitivity of 96.2% and specificity of 82.9%. We developed a risk score to predict CS in an at-risk population. This score may help to identify at-risk patients in non-endocrinological settings such as primary care, but external validation is warranted.

A simple, physiologically-based model of sea turtle remigration intervals and nesting population dynamics: Effects of temperature.

PubMed

Neeman, Noga; Spotila, James R; O'Connor, Michael P

2015-09-07

Variation in the yearly number of sea turtles nesting at rookeries can interfere with population estimates and obscure real population dynamics. Previous theoretical models suggested that this variation in nesting numbers may be driven by changes in resources at the foraging grounds. We developed a physiologically-based model that uses temperatures at foraging sites to predict foraging conditions, resource accumulation, remigration probabilities, and, ultimately, nesting numbers for a stable population of sea turtles. We used this model to explore several scenarios of temperature variation at the foraging grounds, including one-year perturbations and cyclical temperature oscillations. We found that thermally driven resource variation can indeed synchronize nesting in groups of turtles, creating cohorts, but that these cohorts tend to break down over 5-10 years unless regenerated by environmental conditions. Cohorts were broken down faster at lower temperatures. One-year perturbations of low temperature had a synchronizing effect on nesting the following year, while high temperature perturbations tended to delay nesting in a less synchronized way. Cyclical temperatures lead to cyclical responses both in nesting numbers and remigration intervals, with the amplitude and lag of the response depending on the duration of the cycle. Overall, model behavior is consistent with observations at nesting beaches. Future work should focus on refining the model to fit particular nesting populations and testing further whether or not it may be used to predict observed nesting numbers and remigration intervals. Copyright © 2015 Elsevier Ltd. All rights reserved.

Empirical evidence that metabolic theory describes the temperature dependency of within-host parasite dynamics.

PubMed

Kirk, Devin; Jones, Natalie; Peacock, Stephanie; Phillips, Jessica; Molnár, Péter K; Krkošek, Martin; Luijckx, Pepijn

2018-02-01

The complexity of host-parasite interactions makes it difficult to predict how host-parasite systems will respond to climate change. In particular, host and parasite traits such as survival and virulence may have distinct temperature dependencies that must be integrated into models of disease dynamics. Using experimental data from Daphnia magna and a microsporidian parasite, we fitted a mechanistic model of the within-host parasite population dynamics. Model parameters comprising host aging and mortality, as well as parasite growth, virulence, and equilibrium abundance, were specified by relationships arising from the metabolic theory of ecology. The model effectively predicts host survival, parasite growth, and the cost of infection across temperature while using less than half the parameters compared to modeling temperatures discretely. Our results serve as a proof of concept that linking simple metabolic models with a mechanistic host-parasite framework can be used to predict temperature responses of parasite population dynamics at the within-host level.

Empirical evidence that metabolic theory describes the temperature dependency of within-host parasite dynamics

PubMed Central

Jones, Natalie; Peacock, Stephanie; Phillips, Jessica; Molnár, Péter K.; Krkošek, Martin; Luijckx, Pepijn

2018-01-01

The complexity of host–parasite interactions makes it difficult to predict how host–parasite systems will respond to climate change. In particular, host and parasite traits such as survival and virulence may have distinct temperature dependencies that must be integrated into models of disease dynamics. Using experimental data from Daphnia magna and a microsporidian parasite, we fitted a mechanistic model of the within-host parasite population dynamics. Model parameters comprising host aging and mortality, as well as parasite growth, virulence, and equilibrium abundance, were specified by relationships arising from the metabolic theory of ecology. The model effectively predicts host survival, parasite growth, and the cost of infection across temperature while using less than half the parameters compared to modeling temperatures discretely. Our results serve as a proof of concept that linking simple metabolic models with a mechanistic host–parasite framework can be used to predict temperature responses of parasite population dynamics at the within-host level. PMID:29415043

Evaluating targeted interventions via meta-population models with multi-level mixing.

PubMed

Feng, Zhilan; Hill, Andrew N; Curns, Aaron T; Glasser, John W

2017-05-01

Among the several means by which heterogeneity can be modeled, Levins' (1969) meta-population approach preserves the most analytical tractability, a virtue to the extent that generality is desirable. When model populations are stratified, contacts among their respective sub-populations must be described. Using a simple meta-population model, Feng et al. (2015) showed that mixing among sub-populations, as well as heterogeneity in characteristics affecting sub-population reproduction numbers, must be considered when evaluating public health interventions to prevent or control infectious disease outbreaks. They employed the convex combination of preferential within- and proportional among-group contacts first described by Nold (1980) and subsequently generalized by Jacquez et al. (1988). As the utility of meta-population modeling depends on more realistic mixing functions, the authors added preferential contacts between parents and children and among co-workers (Glasser et al., 2012). Here they further generalize this function by including preferential contacts between grandparents and grandchildren, but omit workplace contacts. They also describe a general multi-level mixing scheme, provide three two-level examples, and apply two of them. In their first application, the authors describe age- and gender-specific patterns in face-to-face conversations (Mossong et al., 2008), proxies for contacts by which respiratory pathogens might be transmitted, that are consistent with everyday experience. This suggests that meta-population models with inter-generational mixing could be employed to evaluate prolonged school-closures, a proposed pandemic mitigation measure that could expose grandparents, and other elderly surrogate caregivers for working parents, to infectious children. In their second application, the authors use a meta-population SEIR model stratified by 7 age groups and 50 states plus the District of Columbia, to compare actual with optimal vaccination during the 2009-2010 influenza pandemic in the United States. They also show that vaccination efforts could have been adjusted month-to-month during the fall of 2009 to ensure maximum impact. Such applications inspire confidence in the reliability of meta-population modeling in support of public health policymaking. Published by Elsevier Inc.

DESCARTES' RULE OF SIGNS AND THE IDENTIFIABILITY OF POPULATION DEMOGRAPHIC MODELS FROM GENOMIC VARIATION DATA.

PubMed

Bhaskar, Anand; Song, Yun S

2014-01-01

The sample frequency spectrum (SFS) is a widely-used summary statistic of genomic variation in a sample of homologous DNA sequences. It provides a highly efficient dimensional reduction of large-scale population genomic data and its mathematical dependence on the underlying population demography is well understood, thus enabling the development of efficient inference algorithms. However, it has been recently shown that very different population demographies can actually generate the same SFS for arbitrarily large sample sizes. Although in principle this nonidentifiability issue poses a thorny challenge to statistical inference, the population size functions involved in the counterexamples are arguably not so biologically realistic. Here, we revisit this problem and examine the identifiability of demographic models under the restriction that the population sizes are piecewise-defined where each piece belongs to some family of biologically-motivated functions. Under this assumption, we prove that the expected SFS of a sample uniquely determines the underlying demographic model, provided that the sample is sufficiently large. We obtain a general bound on the sample size sufficient for identifiability; the bound depends on the number of pieces in the demographic model and also on the type of population size function in each piece. In the cases of piecewise-constant, piecewise-exponential and piecewise-generalized-exponential models, which are often assumed in population genomic inferences, we provide explicit formulas for the bounds as simple functions of the number of pieces. Lastly, we obtain analogous results for the "folded" SFS, which is often used when there is ambiguity as to which allelic type is ancestral. Our results are proved using a generalization of Descartes' rule of signs for polynomials to the Laplace transform of piecewise continuous functions.

DESCARTES’ RULE OF SIGNS AND THE IDENTIFIABILITY OF POPULATION DEMOGRAPHIC MODELS FROM GENOMIC VARIATION DATA1

PubMed Central

Bhaskar, Anand; Song, Yun S.

2016-01-01

The sample frequency spectrum (SFS) is a widely-used summary statistic of genomic variation in a sample of homologous DNA sequences. It provides a highly efficient dimensional reduction of large-scale population genomic data and its mathematical dependence on the underlying population demography is well understood, thus enabling the development of efficient inference algorithms. However, it has been recently shown that very different population demographies can actually generate the same SFS for arbitrarily large sample sizes. Although in principle this nonidentifiability issue poses a thorny challenge to statistical inference, the population size functions involved in the counterexamples are arguably not so biologically realistic. Here, we revisit this problem and examine the identifiability of demographic models under the restriction that the population sizes are piecewise-defined where each piece belongs to some family of biologically-motivated functions. Under this assumption, we prove that the expected SFS of a sample uniquely determines the underlying demographic model, provided that the sample is sufficiently large. We obtain a general bound on the sample size sufficient for identifiability; the bound depends on the number of pieces in the demographic model and also on the type of population size function in each piece. In the cases of piecewise-constant, piecewise-exponential and piecewise-generalized-exponential models, which are often assumed in population genomic inferences, we provide explicit formulas for the bounds as simple functions of the number of pieces. Lastly, we obtain analogous results for the “folded” SFS, which is often used when there is ambiguity as to which allelic type is ancestral. Our results are proved using a generalization of Descartes’ rule of signs for polynomials to the Laplace transform of piecewise continuous functions. PMID:28018011

Change-in-ratio methods for estimating population size

USGS Publications Warehouse

Udevitz, Mark S.; Pollock, Kenneth H.; McCullough, Dale R.; Barrett, Reginald H.

2002-01-01

Change-in-ratio (CIR) methods can provide an effective, low cost approach for estimating the size of wildlife populations. They rely on being able to observe changes in proportions of population subclasses that result from the removal of a known number of individuals from the population. These methods were first introduced in the 1940’s to estimate the size of populations with 2 subclasses under the assumption of equal subclass encounter probabilities. Over the next 40 years, closed population CIR models were developed to consider additional subclasses and use additional sampling periods. Models with assumptions about how encounter probabilities vary over time, rather than between subclasses, also received some attention. Recently, all of these CIR models have been shown to be special cases of a more general model. Under the general model, information from additional samples can be used to test assumptions about the encounter probabilities and to provide estimates of subclass sizes under relaxations of these assumptions. These developments have greatly extended the applicability of the methods. CIR methods are attractive because they do not require the marking of individuals, and subclass proportions often can be estimated with relatively simple sampling procedures. However, CIR methods require a carefully monitored removal of individuals from the population, and the estimates will be of poor quality unless the removals induce substantial changes in subclass proportions. In this paper, we review the state of the art for closed population estimation with CIR methods. Our emphasis is on the assumptions of CIR methods and on identifying situations where these methods are likely to be effective. We also identify some important areas for future CIR research.

Teaching Population Growth Using Cultures of Vinegar Eels, "Turbatrix aceti" (Nematoda)

ERIC Educational Resources Information Center

Wallace, Robert L.

2005-01-01

A simple laboratory exercise is presented that follows the population growth of the common vinegar eel, "Turbatrix aceti" (Nematoda), in a microcosm using a simple culture medium. It lends itself to an exercise in a single semester course. (Contains 4 figures.)

COMPARING MID-INFRARED GLOBULAR CLUSTER COLORS WITH POPULATION SYNTHESIS MODELS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barmby, P.; Jalilian, F. F.

2012-04-15

Several population synthesis models now predict integrated colors of simple stellar populations in the mid-infrared bands. To date, the models have not been extensively tested in this wavelength range. In a comparison of the predictions of several recent population synthesis models, the integrated colors are found to cover approximately the same range but to disagree in detail, for example, on the effects of metallicity. To test against observational data, globular clusters (GCs) are used as the closest objects to idealized groups of stars with a single age and single metallicity. Using recent mass estimates, we have compiled a sample ofmore » massive, old GCs in M31 which contain enough stars to guard against the stochastic effects of small-number statistics, and measured their integrated colors in the Spitzer/IRAC bands. Comparison of the cluster photometry in the IRAC bands with the model predictions shows that the models reproduce the cluster colors reasonably well, except for a small (not statistically significant) offset in [4.5] - [5.8]. In this color, models without circumstellar dust emission predict bluer values than are observed. Model predictions of colors formed from the V band and the IRAC 3.6 and 4.5 {mu}m bands are redder than the observed data at high metallicities and we discuss several possible explanations. In agreement with model predictions, V - [3.6] and V - [4.5] colors are found to have metallicity sensitivity similar to or slightly better than V - K{sub s}.« less

Predictive Analytics In Healthcare: Medications as a Predictor of Medical Complexity.

PubMed

Higdon, Roger; Stewart, Elizabeth; Roach, Jared C; Dombrowski, Caroline; Stanberry, Larissa; Clifton, Holly; Kolker, Natali; van Belle, Gerald; Del Beccaro, Mark A; Kolker, Eugene

2013-12-01

Children with special healthcare needs (CSHCN) require health and related services that exceed those required by most hospitalized children. A small but growing and important subset of the CSHCN group includes medically complex children (MCCs). MCCs typically have comorbidities and disproportionately consume healthcare resources. To enable strategic planning for the needs of MCCs, simple screens to identify potential MCCs rapidly in a hospital setting are needed. We assessed whether the number of medications used and the class of those medications correlated with MCC status. Retrospective analysis of medication data from the inpatients at Seattle Children's Hospital found that the numbers of inpatient and outpatient medications significantly correlated with MCC status. Numerous variables based on counts of medications, use of individual medications, and use of combinations of medications were considered, resulting in a simple model based on three different counts of medications: outpatient and inpatient drug classes and individual inpatient drug names. The combined model was used to rank the patient population for medical complexity. As a result, simple, objective admission screens for predicting the complexity of patients based on the number and type of medications were implemented.

On the context-dependent scaling of consumer feeding rates.

PubMed

Barrios-O'Neill, Daniel; Kelly, Ruth; Dick, Jaimie T A; Ricciardi, Anthony; MacIsaac, Hugh J; Emmerson, Mark C

2016-06-01

The stability of consumer-resource systems can depend on the form of feeding interactions (i.e. functional responses). Size-based models predict interactions - and thus stability - based on consumer-resource size ratios. However, little is known about how interaction contexts (e.g. simple or complex habitats) might alter scaling relationships. Addressing this, we experimentally measured interactions between a large size range of aquatic predators (4-6400 mg over 1347 feeding trials) and an invasive prey that transitions among habitats: from the water column (3D interactions) to simple and complex benthic substrates (2D interactions). Simple and complex substrates mediated successive reductions in capture rates - particularly around the unimodal optimum - and promoted prey population stability in model simulations. Many real consumer-resource systems transition between 2D and 3D interactions, and along complexity gradients. Thus, Context-Dependent Scaling (CDS) of feeding interactions could represent an unrecognised aspect of food webs, and quantifying the extent of CDS might enhance predictive ecology. © The Authors. Ecology Letters published by CNRS and John Wiley & Sons Ltd.

Estimating tuberculosis incidence from primary survey data: a mathematical modeling approach.

PubMed

Pandey, S; Chadha, V K; Laxminarayan, R; Arinaminpathy, N

2017-04-01

There is an urgent need for improved estimations of the burden of tuberculosis (TB). To develop a new quantitative method based on mathematical modelling, and to demonstrate its application to TB in India. We developed a simple model of TB transmission dynamics to estimate the annual incidence of TB disease from the annual risk of tuberculous infection and prevalence of smear-positive TB. We first compared model estimates for annual infections per smear-positive TB case using previous empirical estimates from China, Korea and the Philippines. We then applied the model to estimate TB incidence in India, stratified by urban and rural settings. Study model estimates show agreement with previous empirical estimates. Applied to India, the model suggests an annual incidence of smear-positive TB of 89.8 per 100 000 population (95%CI 56.8-156.3). Results show differences in urban and rural TB: while an urban TB case infects more individuals per year, a rural TB case remains infectious for appreciably longer, suggesting the need for interventions tailored to these different settings. Simple models of TB transmission, in conjunction with necessary data, can offer approaches to burden estimation that complement those currently being used.

Admixture, Population Structure, and F-Statistics.

PubMed

Peter, Benjamin M

2016-04-01

Many questions about human genetic history can be addressed by examining the patterns of shared genetic variation between sets of populations. A useful methodological framework for this purpose isF-statistics that measure shared genetic drift between sets of two, three, and four populations and can be used to test simple and complex hypotheses about admixture between populations. This article provides context from phylogenetic and population genetic theory. I review how F-statistics can be interpreted as branch lengths or paths and derive new interpretations, using coalescent theory. I further show that the admixture tests can be interpreted as testing general properties of phylogenies, allowing extension of some ideas applications to arbitrary phylogenetic trees. The new results are used to investigate the behavior of the statistics under different models of population structure and show how population substructure complicates inference. The results lead to simplified estimators in many cases, and I recommend to replace F3 with the average number of pairwise differences for estimating population divergence. Copyright © 2016 by the Genetics Society of America.

Predominance of Movement Speed Over Direction in Neuronal Population Signals of Motor Cortex: Intracranial EEG Data and A Simple Explanatory Model

PubMed Central

Hammer, Jiří; Pistohl, Tobias; Fischer, Jörg; Kršek, Pavel; Tomášek, Martin; Marusič, Petr; Schulze-Bonhage, Andreas; Aertsen, Ad; Ball, Tonio

2016-01-01

How neuronal activity of motor cortex is related to movement is a central topic in motor neuroscience. Motor-cortical single neurons are more closely related to hand movement velocity than speed, that is, the magnitude of the (directional) velocity vector. Recently, there is also increasing interest in the representation of movement parameters in neuronal population activity, such as reflected in the intracranial EEG (iEEG). We show that in iEEG, contrasting to what has been previously found on the single neuron level, speed predominates over velocity. The predominant speed representation was present in nearly all iEEG signal features, up to the 600–1000 Hz range. Using a model of motor-cortical signals arising from neuronal populations with realistic single neuron tuning properties, we show how this reversal can be understood as a consequence of increasing population size. Our findings demonstrate that the information profile in large population signals may systematically differ from the single neuron level, a principle that may be helpful in the interpretation of neuronal population signals in general, including, for example, EEG and functional magnetic resonance imaging. Taking advantage of the robust speed population signal may help in developing brain–machine interfaces exploiting population signals. PMID:26984895

An area-level model of vehicle-pedestrian injury collisions with implications for land use and transportation planning.

PubMed

Wier, Megan; Weintraub, June; Humphreys, Elizabeth H; Seto, Edmund; Bhatia, Rajiv

2009-01-01

There is growing awareness among urban planning, public health, and transportation professionals that design decisions and investments that promote walking can be beneficial for human and ecological health. Planners need practical tools to consider the impact of development on pedestrian safety, a key requirement for the promotion of walking. Simple bivariate models have been used to predict changes in vehicle-pedestrian injury collisions based on changes in traffic volume. We describe the development of a multivariate, area-level regression model of vehicle-pedestrian injury collisions based on environmental and population data in 176 San Francisco, California census tracts. Predictor variables examined included street, land use, and population characteristics, including commute behaviors. The final model explained approximately 72% of the systematic variation in census-tract vehicle-pedestrian injury collisions and included measures of traffic volume, arterial streets without transit, land area, proportion of land area zoned for neighborhood commercial and residential-neighborhood commercial uses, employee and resident populations, proportion of people living in poverty and proportion aged 65 and older. We have begun to apply this model to predict area-level change in vehicle-pedestrian injury collisions associated with land use development and transportation planning decisions.

A stochastic step model of replicative senescence explains ROS production rate in ageing cell populations.

PubMed

Lawless, Conor; Jurk, Diana; Gillespie, Colin S; Shanley, Daryl; Saretzki, Gabriele; von Zglinicki, Thomas; Passos, João F

2012-01-01

Increases in cellular Reactive Oxygen Species (ROS) concentration with age have been observed repeatedly in mammalian tissues. Concomitant increases in the proportion of replicatively senescent cells in ageing mammalian tissues have also been observed. Populations of mitotic human fibroblasts cultured in vitro, undergoing transition from proliferation competence to replicative senescence are useful models of ageing human tissues. Similar exponential increases in ROS with age have been observed in this model system. Tracking individual cells in dividing populations is difficult, and so the vast majority of observations have been cross-sectional, at the population level, rather than longitudinal observations of individual cells.One possible explanation for these observations is an exponential increase in ROS in individual fibroblasts with time (e.g. resulting from a vicious cycle between cellular ROS and damage). However, we demonstrate an alternative, simple hypothesis, equally consistent with these observations which does not depend on any gradual increase in ROS concentration: the Stochastic Step Model of Replicative Senescence (SSMRS). We also demonstrate that, consistent with the SSMRS, neither proliferation-competent human fibroblasts of any age, nor populations of hTERT overexpressing human fibroblasts passaged beyond the Hayflick limit, display high ROS concentrations. We conclude that longitudinal studies of single cells and their lineages are now required for testing hypotheses about roles and mechanisms of ROS increase during replicative senescence.

A Stochastic Step Model of Replicative Senescence Explains ROS Production Rate in Ageing Cell Populations

PubMed Central

Lawless, Conor; Jurk, Diana; Gillespie, Colin S.; Shanley, Daryl; Saretzki, Gabriele; von Zglinicki, Thomas; Passos, João F.

2012-01-01

Increases in cellular Reactive Oxygen Species (ROS) concentration with age have been observed repeatedly in mammalian tissues. Concomitant increases in the proportion of replicatively senescent cells in ageing mammalian tissues have also been observed. Populations of mitotic human fibroblasts cultured in vitro, undergoing transition from proliferation competence to replicative senescence are useful models of ageing human tissues. Similar exponential increases in ROS with age have been observed in this model system. Tracking individual cells in dividing populations is difficult, and so the vast majority of observations have been cross-sectional, at the population level, rather than longitudinal observations of individual cells. One possible explanation for these observations is an exponential increase in ROS in individual fibroblasts with time (e.g. resulting from a vicious cycle between cellular ROS and damage). However, we demonstrate an alternative, simple hypothesis, equally consistent with these observations which does not depend on any gradual increase in ROS concentration: the Stochastic Step Model of Replicative Senescence (SSMRS). We also demonstrate that, consistent with the SSMRS, neither proliferation-competent human fibroblasts of any age, nor populations of hTERT overexpressing human fibroblasts passaged beyond the Hayflick limit, display high ROS concentrations. We conclude that longitudinal studies of single cells and their lineages are now required for testing hypotheses about roles and mechanisms of ROS increase during replicative senescence. PMID:22359661

Rock size-frequency distributions on Mars and implications for Mars Exploration Rover landing safety and operations

NASA Astrophysics Data System (ADS)

Golombek, M. P.; Haldemann, A. F. C.; Forsberg-Taylor, N. K.; DiMaggio, E. N.; Schroeder, R. D.; Jakosky, B. M.; Mellon, M. T.; Matijevic, J. R.

2003-10-01

The cumulative fractional area covered by rocks versus diameter measured at the Pathfinder site was predicted by a rock distribution model that follows simple exponential functions that approach the total measured rock abundance (19%), with a steep decrease in rocks with increasing diameter. The distribution of rocks >1.5 m diameter visible in rare boulder fields also follows this steep decrease with increasing diameter. The effective thermal inertia of rock populations calculated from a simple empirical model of the effective inertia of rocks versus diameter shows that most natural rock populations have cumulative effective thermal inertias of 1700-2100 J m-2 s-0.5 K-1 and are consistent with the model rock distributions applied to total rock abundance estimates. The Mars Exploration Rover (MER) airbags have been successfully tested against extreme rock distributions with a higher percentage of potentially hazardous triangular buried rocks than observed at the Pathfinder and Viking landing sites. The probability of the lander impacting a >1 m diameter rock in the first 2 bounces is <3% and <5% for the Meridiani and Gusev landing sites, respectively, and is <0.14% and <0.03% for rocks >1.5 m and >2 m diameter, respectively. Finally, the model rock size-frequency distributions indicate that rocks >0.1 m and >0.3 m in diameter, large enough to place contact sensor instruments against and abrade, respectively, should be plentiful within a single sol's drive at the Meridiani and Gusev landing sites.

Regime, phase and paradigm shifts: making community ecology the basic science for fisheries

PubMed Central

Mangel, Marc; Levin, Phillip S.

2005-01-01

Modern fishery science, which began in 1957 with Beverton and Holt, is ca. 50 years old. At its inception, fishery science was limited by a nineteenth century mechanistic worldview and by computational technology; thus, the relatively simple equations of population ecology became the fundamental ecological science underlying fisheries. The time has come for this to change and for community ecology to become the fundamental ecological science underlying fisheries. This point will be illustrated with two examples. First, when viewed from a community perspective, excess production must be considered in the context of biomass left for predators. We argue that this is a better measure of the effects of fisheries than spawning biomass per recruit. Second, we shall analyse a simple, but still multi-species, model for fishery management that considers the alternatives of harvest regulations, inshore marine protected areas and offshore marine protected areas. Population or community perspectives lead to very different predictions about the efficacy of reserves. PMID:15713590

Comparative evaluation of human heat stress indices on selected hospital admissions in Sydney, Australia.

PubMed

Goldie, James; Alexander, Lisa; Lewis, Sophie C; Sherwood, Steven

2017-08-01

To find appropriate regression model specifications for counts of the daily hospital admissions of a Sydney cohort and determine which human heat stress indices best improve the models' fit. We built parent models of eight daily counts of admission records using weather station observations, census population estimates and public holiday data. We added heat stress indices; models with lower Akaike Information Criterion scores were judged a better fit. Five of the eight parent models demonstrated adequate fit. Daily maximum Simplified Wet Bulb Globe Temperature (sWBGT) consistently improved fit more than most other indices; temperature and heatwave indices also modelled some health outcomes well. Humidity and heat-humidity indices better fit counts of patients who died following admission. Maximum sWBGT is an ideal measure of heat stress for these types of Sydney hospital admissions. Simple temperature indices are a good fallback where a narrower range of conditions is investigated. Implications for public health: This study confirms the importance of selecting appropriate heat stress indices for modelling. Epidemiologists projecting Sydney hospital admissions should use maximum sWBGT as a common measure of heat stress. Health organisations interested in short-range forecasting may prefer simple temperature indices. © 2017 The Authors.

A simple method for finding explicit analytic transition densities of diffusion processes with general diploid selection.

PubMed

Song, Yun S; Steinrücken, Matthias

2012-03-01

The transition density function of the Wright-Fisher diffusion describes the evolution of population-wide allele frequencies over time. This function has important practical applications in population genetics, but finding an explicit formula under a general diploid selection model has remained a difficult open problem. In this article, we develop a new computational method to tackle this classic problem. Specifically, our method explicitly finds the eigenvalues and eigenfunctions of the diffusion generator associated with the Wright-Fisher diffusion with recurrent mutation and arbitrary diploid selection, thus allowing one to obtain an accurate spectral representation of the transition density function. Simplicity is one of the appealing features of our approach. Although our derivation involves somewhat advanced mathematical concepts, the resulting algorithm is quite simple and efficient, only involving standard linear algebra. Furthermore, unlike previous approaches based on perturbation, which is applicable only when the population-scaled selection coefficient is small, our method is nonperturbative and is valid for a broad range of parameter values. As a by-product of our work, we obtain the rate of convergence to the stationary distribution under mutation-selection balance.

A Simple Method for Finding Explicit Analytic Transition Densities of Diffusion Processes with General Diploid Selection

PubMed Central

Song, Yun S.; Steinrücken, Matthias

2012-01-01

The transition density function of the Wright–Fisher diffusion describes the evolution of population-wide allele frequencies over time. This function has important practical applications in population genetics, but finding an explicit formula under a general diploid selection model has remained a difficult open problem. In this article, we develop a new computational method to tackle this classic problem. Specifically, our method explicitly finds the eigenvalues and eigenfunctions of the diffusion generator associated with the Wright–Fisher diffusion with recurrent mutation and arbitrary diploid selection, thus allowing one to obtain an accurate spectral representation of the transition density function. Simplicity is one of the appealing features of our approach. Although our derivation involves somewhat advanced mathematical concepts, the resulting algorithm is quite simple and efficient, only involving standard linear algebra. Furthermore, unlike previous approaches based on perturbation, which is applicable only when the population-scaled selection coefficient is small, our method is nonperturbative and is valid for a broad range of parameter values. As a by-product of our work, we obtain the rate of convergence to the stationary distribution under mutation–selection balance. PMID:22209899

Blue Stragglers in Clusters and Integrated Spectral Properties of Stellar Populations

NASA Astrophysics Data System (ADS)

Xin, Yu; Deng, Licai

Blue straggler stars are the most prominent bright objects in the colour-magnitude diagram of a star cluster that challenges the theory of stellar evolution. Star clusters are the closest counterparts of the theoretical concept of simple stellar populations (SSPs) in the Universe. SSPs are widely used as the basic building blocks to interpret stellar contents in galaxies. The concept of an SSP is a group of coeval stars which follows a given distribution in mass, and has the same chemical property and age. In practice, SSPs are more conveniently made by the latest stellar evolutionary models of single stars. In reality, however, stars can be more complicated than just single either at birth time or during the course of evolution in a typical environment. Observations of star clusters show that there are always exotic objects which do not follow the predictions of standard theory of stellar evolution. Blue straggler stars (BSSs), as discussed intensively in this book both observationally and theoretically, are very important in our context when considering the integrated spectral properties of a cluster, or a simple stellar population. In this chapter, we are going to describe how important the contribution of BSSs is to the total light of a cluster.

How Random Is Social Behaviour? Disentangling Social Complexity through the Study of a Wild House Mouse Population

PubMed Central

Perony, Nicolas; Tessone, Claudio J.; König, Barbara; Schweitzer, Frank

2012-01-01

Out of all the complex phenomena displayed in the behaviour of animal groups, many are thought to be emergent properties of rather simple decisions at the individual level. Some of these phenomena may also be explained by random processes only. Here we investigate to what extent the interaction dynamics of a population of wild house mice (Mus domesticus) in their natural environment can be explained by a simple stochastic model. We first introduce the notion of perceptual landscape, a novel tool used here to describe the utilisation of space by the mouse colony based on the sampling of individuals in discrete locations. We then implement the behavioural assumptions of the perceptual landscape in a multi-agent simulation to verify their accuracy in the reproduction of observed social patterns. We find that many high-level features – with the exception of territoriality – of our behavioural dataset can be accounted for at the population level through the use of this simplified representation. Our findings underline the potential importance of random factors in the apparent complexity of the mice's social structure. These results resonate in the general context of adaptive behaviour versus elementary environmental interactions. PMID:23209394

Simple Learned Weighted Sums of Inferior Temporal Neuronal Firing Rates Accurately Predict Human Core Object Recognition Performance.

PubMed

Majaj, Najib J; Hong, Ha; Solomon, Ethan A; DiCarlo, James J

2015-09-30

To go beyond qualitative models of the biological substrate of object recognition, we ask: can a single ventral stream neuronal linking hypothesis quantitatively account for core object recognition performance over a broad range of tasks? We measured human performance in 64 object recognition tests using thousands of challenging images that explore shape similarity and identity preserving object variation. We then used multielectrode arrays to measure neuronal population responses to those same images in visual areas V4 and inferior temporal (IT) cortex of monkeys and simulated V1 population responses. We tested leading candidate linking hypotheses and control hypotheses, each postulating how ventral stream neuronal responses underlie object recognition behavior. Specifically, for each hypothesis, we computed the predicted performance on the 64 tests and compared it with the measured pattern of human performance. All tested hypotheses based on low- and mid-level visually evoked activity (pixels, V1, and V4) were very poor predictors of the human behavioral pattern. However, simple learned weighted sums of distributed average IT firing rates exactly predicted the behavioral pattern. More elaborate linking hypotheses relying on IT trial-by-trial correlational structure, finer IT temporal codes, or ones that strictly respect the known spatial substructures of IT ("face patches") did not improve predictive power. Although these results do not reject those more elaborate hypotheses, they suggest a simple, sufficient quantitative model: each object recognition task is learned from the spatially distributed mean firing rates (100 ms) of ∼60,000 IT neurons and is executed as a simple weighted sum of those firing rates. Significance statement: We sought to go beyond qualitative models of visual object recognition and determine whether a single neuronal linking hypothesis can quantitatively account for core object recognition behavior. To achieve this, we designed a database of images for evaluating object recognition performance. We used multielectrode arrays to characterize hundreds of neurons in the visual ventral stream of nonhuman primates and measured the object recognition performance of >100 human observers. Remarkably, we found that simple learned weighted sums of firing rates of neurons in monkey inferior temporal (IT) cortex accurately predicted human performance. Although previous work led us to expect that IT would outperform V4, we were surprised by the quantitative precision with which simple IT-based linking hypotheses accounted for human behavior. Copyright © 2015 the authors 0270-6474/15/3513402-17$15.00/0.

A simple model for prediction postpartum PTSD in high-risk pregnancies.

PubMed

Shlomi Polachek, Inbal; Dulitzky, Mordechai; Margolis-Dorfman, Lilia; Simchen, Michal J

2016-06-01

This study aimed to examine the prevalence and possible antepartum risk factors of complete and partial post-traumatic stress disorder (PTSD) among women with complicated pregnancies and to define a predictive model for postpartum PTSD in this population. Women attending the high-risk pregnancy outpatient clinics at Sheba Medical Center completed the Edinburgh Postnatal Depression Scale (EPDS) and a questionnaire regarding demographic variables, history of psychological and psychiatric treatment, previous trauma, previous childbirth, current pregnancy medical and emotional complications, fears from childbirth, and expected pain. One month after delivery, women were requested to repeat the EPDS and complete the Post-traumatic Stress Diagnostic Scale (PDS) via telephone interview. The prevalence rates of postpartum PTSD (9.9 %) and partial PTSD (11.9 %) were relatively high. PTSD and partial PTSD were associated with sadness or anxiety during past pregnancy or childbirth, previous very difficult birth experiences, preference for cesarean section in future childbirth, emotional crises during pregnancy, increased fear of childbirth, higher expected intensity of pain, and depression during pregnancy. We created a prediction model for postpartum PTSD which shows a linear growth in the probability for developing postpartum PTSD when summing these seven antenatal risk factors. Postpartum PTSD is extremely prevalent after complicated pregnancies. A simple questionnaire may aid in identifying at-risk women before childbirth. This presents a potential for preventing or minimizing postpartum PTSD in this population.

Formation of the high-energy ion population in the earth's magnetotail: spacecraft observations and theoretical models

NASA Astrophysics Data System (ADS)

Artemyev, A. V.; Vasko, I. Y.; Lutsenko, V. N.; Petrukovich, A. A.

2014-10-01

We investigate the formation of the high-energy (E ∈ [20,600] keV) ion population in the earth's magnetotail. We collect statistics of 4 years of Interball / Tail observations (1995-1998) in the vicinity of the neutral plane in the magnetotail region (X <-17 RE, |Y| ≤ 20 RE in geocentric solar magnetospheric (GSM) system). We study the dependence of high-energy ion spectra on the thermal-plasma parameters (the temperature Ti and the amplitude of bulk velocity vi) and on the magnetic-field component Bz. The ion population in the energy range E ∈ [20,600] keV can be separated in the thermal core and the power-law tail with the slope (index) ~ -4.5. Fluxes of the high-energy ion population increase with the growth of Bz, vi and especially Ti, but spectrum index seems to be independent on these parameters. We have suggested that the high-energy ion population is generated by small scale transient processes, rather than by the global reconfiguration of the magnetotail. We have proposed the relatively simple and general model of ion acceleration by transient bursts of the electric field. This model describes the power-law energy spectra and predicts typical energies of accelerated ions.

A Resolution to the Blue Whiting (Micromesistius poutassou) Population Paradox?

PubMed Central

Pointin, Fabien; Payne, Mark R.

2014-01-01

We provide the strongest evidence to date supporting the existence of two independent blue whiting (Micromesistius poutassou (Risso, 1827)) populations in the North Atlantic. In spite of extensive data collected in conjunction with the fishery, the population structure of blue whiting is poorly understood. On one hand, genetic, morphometric, otolith and drift modelling studies point towards the existence of two populations, but, on the other hand, observations of adult distributions point towards a single population. A paradox therefore arises in attempting to reconcile these two sets of information. Here we analyse 1100 observations of blue whiting larvae from the Continuous Plankton Recorder (CPR) from 1948–2005 using modern statistical techniques. We show a clear spatial separation between a northern spawning area, in the Rockall Trough, and a southern one, off the Porcupine Seabight. We further show a difference in the timing of spawning between these sites of at least a month, and meaningful differences in interannual variability. The results therefore support the two-population hypothesis. Furthermore, we resolve the paradox by showing that the acoustic observations cited in support of the single-population model are not capable of resolving both populations, as they occur too late in the year and do not extend sufficiently far south to cover the southern population: the confusion is the result of a simple observational artefact. We conclude that blue whiting in the North Atlantic comprises two populations. PMID:25184302

SUBMILLIMETER GALAXY NUMBER COUNTS AND MAGNIFICATION BY GALAXY CLUSTERS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lima, Marcos; Jain, Bhuvnesh; Devlin, Mark

2010-07-01

We present an analytical model that reproduces measured galaxy number counts from surveys in the wavelength range of 500 {mu}m-2 mm. The model involves a single high-redshift galaxy population with a Schechter luminosity function that has been gravitationally lensed by galaxy clusters in the mass range 10{sup 13}-10{sup 15} M{sub sun}. This simple model reproduces both the low-flux and the high-flux end of the number counts reported by the BLAST, SCUBA, AzTEC, and South Pole Telescope (SPT) surveys. In particular, our model accounts for the most luminous galaxies detected by SPT as the result of high magnifications by galaxy clustersmore » (magnification factors of 10-30). This interpretation implies that submillimeter (submm) and millimeter surveys of this population may prove to be a useful addition to ongoing cluster detection surveys. The model also implies that the bulk of submm galaxies detected at wavelengths larger than 500 {mu}m lie at redshifts greater than 2.« less

Stochastic Spatial Models in Ecology: A Statistical Physics Approach

NASA Astrophysics Data System (ADS)

Pigolotti, Simone; Cencini, Massimo; Molina, Daniel; Muñoz, Miguel A.

2018-07-01

Ecosystems display a complex spatial organization. Ecologists have long tried to characterize them by looking at how different measures of biodiversity change across spatial scales. Ecological neutral theory has provided simple predictions accounting for general empirical patterns in communities of competing species. However, while neutral theory in well-mixed ecosystems is mathematically well understood, spatial models still present several open problems, limiting the quantitative understanding of spatial biodiversity. In this review, we discuss the state of the art in spatial neutral theory. We emphasize the connection between spatial ecological models and the physics of non-equilibrium phase transitions and how concepts developed in statistical physics translate in population dynamics, and vice versa. We focus on non-trivial scaling laws arising at the critical dimension D = 2 of spatial neutral models, and their relevance for biological populations inhabiting two-dimensional environments. We conclude by discussing models incorporating non-neutral effects in the form of spatial and temporal disorder, and analyze how their predictions deviate from those of purely neutral theories.

Stochastic Spatial Models in Ecology: A Statistical Physics Approach

NASA Astrophysics Data System (ADS)

Pigolotti, Simone; Cencini, Massimo; Molina, Daniel; Muñoz, Miguel A.

2017-11-01

Ecosystems display a complex spatial organization. Ecologists have long tried to characterize them by looking at how different measures of biodiversity change across spatial scales. Ecological neutral theory has provided simple predictions accounting for general empirical patterns in communities of competing species. However, while neutral theory in well-mixed ecosystems is mathematically well understood, spatial models still present several open problems, limiting the quantitative understanding of spatial biodiversity. In this review, we discuss the state of the art in spatial neutral theory. We emphasize the connection between spatial ecological models and the physics of non-equilibrium phase transitions and how concepts developed in statistical physics translate in population dynamics, and vice versa. We focus on non-trivial scaling laws arising at the critical dimension D = 2 of spatial neutral models, and their relevance for biological populations inhabiting two-dimensional environments. We conclude by discussing models incorporating non-neutral effects in the form of spatial and temporal disorder, and analyze how their predictions deviate from those of purely neutral theories.

Genealogical and evolutionary inference with the human Y chromosome.

PubMed

Stumpf, M P; Goldstein, D B

2001-03-02

Population genetics has emerged as a powerful tool for unraveling human history. In addition to the study of mitochondrial and autosomal DNA, attention has recently focused on Y-chromosome variation. Ambiguities and inaccuracies in data analysis, however, pose an important obstacle to further development of the field. Here we review the methods available for genealogical inference using Y-chromosome data. Approaches can be divided into those that do and those that do not use an explicit population model in genealogical inference. We describe the strengths and weaknesses of these model-based and model-free approaches, as well as difficulties associated with the mutation process that affect both methods. In the case of genealogical inference using microsatellite loci, we use coalescent simulations to show that relatively simple generalizations of the mutation process can greatly increase the accuracy of genealogical inference. Because model-free and model-based approaches have different biases and limitations, we conclude that there is considerable benefit in the continued use of both types of approaches.

Modeling eating behaviors: The role of environment and positive food association learning via a Ratatouille effect.

PubMed

Murillo, Anarina L; Safan, Muntaser; Castillo-Chavez, Carlos; Phillips, Elizabeth D Capaldi; Wadhera, Devina

2016-08-01

Eating behaviors among a large population of children are studied as a dynamic process driven by nonlinear interactions in the sociocultural school environment. The impact of food association learning on diet dynamics, inspired by a pilot study conducted among Arizona children in Pre-Kindergarten to 8th grades, is used to build simple population-level learning models. Qualitatively, mathematical studies are used to highlight the possible ramifications of instruction, learning in nutrition, and health at the community level. Model results suggest that nutrition education programs at the population-level have minimal impact on improving eating behaviors, findings that agree with prior field studies. Hence, the incorporation of food association learning may be a better strategy for creating resilient communities of healthy and non-healthy eaters. A Ratatouille effect can be observed when food association learners become food preference learners, a potential sustainable behavioral change, which in turn, may impact the overall distribution of healthy eaters. In short, this work evaluates the effectiveness of population-level intervention strategies and the importance of institutionalizing nutrition programs that factor in economical, social, cultural, and environmental elements that mesh well with the norms and values in the community.

Medaka: a promising model animal for comparative population genomics

PubMed Central

Matsumoto, Yoshifumi; Oota, Hiroki; Asaoka, Yoichi; Nishina, Hiroshi; Watanabe, Koji; Bujnicki, Janusz M; Oda, Shoji; Kawamura, Shoji; Mitani, Hiroshi

2009-01-01

Background Within-species genome diversity has been best studied in humans. The international HapMap project has revealed a tremendous amount of single-nucleotide polymorphisms (SNPs) among humans, many of which show signals of positive selection during human evolution. In most of the cases, however, functional differences between the alleles remain experimentally unverified due to the inherent difficulty of human genetic studies. It would therefore be highly useful to have a vertebrate model with the following characteristics: (1) high within-species genetic diversity, (2) a variety of gene-manipulation protocols already developed, and (3) a completely sequenced genome. Medaka (Oryzias latipes) and its congeneric species, tiny fresh-water teleosts distributed broadly in East and Southeast Asia, meet these criteria. Findings Using Oryzias species from 27 local populations, we conducted a simple screening of nonsynonymous SNPs for 11 genes with apparent orthology between medaka and humans. We found medaka SNPs for which the same sites in human orthologs are known to be highly differentiated among the HapMap populations. Importantly, some of these SNPs show signals of positive selection. Conclusion These results indicate that medaka is a promising model system for comparative population genomics exploring the functional and adaptive significance of allelic differentiations. PMID:19426554

Biophysical model of prokaryotic diversity in geothermal hot springs.

PubMed

Klales, Anna; Duncan, James; Nett, Elizabeth Janus; Kane, Suzanne Amador

2012-02-01

Recent studies of photosynthetic bacteria living in geothermal hot spring environments have revealed surprisingly complex ecosystems with an unexpected level of genetic diversity. One case of particular interest involves the distribution along hot spring thermal gradients of genetically distinct bacterial strains that differ in their preferred temperatures for reproduction and photosynthesis. In such systems, a single variable, temperature, defines the relevant environmental variation. In spite of this, each region along the thermal gradient exhibits multiple strains of photosynthetic bacteria adapted to several distinct thermal optima, rather than a single thermal strain adapted to the local environmental temperature. Here we analyze microbiology data from several ecological studies to show that the thermal distribution data exhibit several universal features independent of location and specific bacterial strain. These include the distribution of optimal temperatures of different thermal strains and the functional dependence of the net population density on temperature. We present a simple population dynamics model of these systems that is highly constrained by biophysical data and by physical features of the environment. This model can explain in detail the observed thermal population distributions, as well as certain features of population dynamics observed in laboratory studies of the same organisms. © 2012 American Physical Society

Hydrogeomorphology explains acidification-driven variation in aquatic biological communities in the Neversink Basin, USA

USGS Publications Warehouse

Harpold, Adrian A.; Burns, Douglas A.; Walter, M.T.; Steenhuis, Tammo S.

2013-01-01

Describing the distribution of aquatic habitats and the health of biological communities can be costly and time-consuming; therefore, simple, inexpensive methods to scale observations of aquatic biota to watersheds that lack data would be useful. In this study, we explored the potential of a simple “hydrogeomorphic” model to predict the effects of acid deposition on macroinvertebrate, fish, and diatom communities in 28 sub-watersheds of the 176-km2 Neversink River basin in the Catskill Mountains of New York State. The empirical model was originally developed to predict stream-water acid neutralizing capacity (ANC) using the watershed slope and drainage density. Because ANC is known to be strongly related to aquatic biological communities in the Neversink, we speculated that the model might correlate well with biotic indicators of ANC response. The hydrogeomorphic model was strongly correlated to several measures of macroinvertebrate and fish community richness and density, but less strongly correlated to diatom acid tolerance. The model was also strongly correlated to biological communities in 18 sub-watersheds independent of the model development, with the linear correlation capturing the strongly acidic nature of small upland watersheds (2). Overall, we demonstrated the applicability of geospatial data sets and a simple hydrogeomorphic model for estimating aquatic biological communities in areas with stream-water acidification, allowing estimates where no direct field observations are available. Similar modeling approaches have the potential to complement or refine expensive and time-consuming measurements of aquatic biota populations and to aid in regional assessments of aquatic health.

Household's willingness to pay for heterogeneous attributes of drinking water quality and services improvement: an application of choice experiment

NASA Astrophysics Data System (ADS)

Dauda, Suleiman Alhaji; Yacob, Mohd Rusli; Radam, Alias

2015-09-01

The service of providing good quality of drinking water can greatly improve the lives of the community and maintain a normal health standard. For a large number of population in the world, specifically in the developing countries, the availability of safe water for daily sustenance is none. Damaturu is the capital of Yobe State, Nigeria. It hosts a population of more than two hundred thousand, yet only 45 % of the households are connected to the network of Yobe State Water Corporation's pipe borne water services; this has led people to source for water from any available source and thus, exposed them to the danger of contracting waterborne diseases. In order to address the problem, Yobe State Government has embarked on the construction of a water treatment plant with a capacity and facility to improve the water quality and connect the town with water services network. The objectives of this study are to assess the households' demand preferences of the heterogeneous water attributes in Damaturu, and to estimate their marginal willingness to pay, using mixed logit model in comparison with conditional logit model. A survey of 300 households randomly sampled indicated that higher education greatly influenced the households' WTP decisions. The most significant variable from both of the models is TWQ, which is MRS that rates the water quality from the level of satisfactory to very good. 219 % in simple model is CLM, while 126 % is for the interaction model. As for MLM, 685 % is for the simple model and 572 % is for the interaction model. Estimate of MLM has more explanatory powers than CLM. Essentially, this finding can help the government in designing cost-effective management and efficient tariff structure.

Domain learning naming game for color categorization.

PubMed

Li, Doujie; Fan, Zhongyan; Tang, Wallace K S

2017-01-01

Naming game simulates the evolution of vocabulary in a population of agents. Through pairwise interactions in the games, agents acquire a set of vocabulary in their memory for object naming. The existing model confines to a one-to-one mapping between a name and an object. Focus is usually put onto name consensus in the population rather than knowledge learning in agents, and hence simple learning model is usually adopted. However, the cognition system of human being is much more complex and knowledge is usually presented in a complicated form. Therefore, in this work, we extend the agent learning model and design a new game to incorporate domain learning, which is essential for more complicated form of knowledge. In particular, we demonstrate the evolution of color categorization and naming in a population of agents. We incorporate the human perceptive model into the agents and introduce two new concepts, namely subjective perception and subliminal stimulation, in domain learning. Simulation results show that, even without any supervision or pre-requisition, a consensus of a color naming system can be reached in a population solely via the interactions. Our work confirms the importance of society interactions in color categorization, which is a long debate topic in human cognition. Moreover, our work also demonstrates the possibility of cognitive system development in autonomous intelligent agents.

Domain learning naming game for color categorization

PubMed Central

2017-01-01

Naming game simulates the evolution of vocabulary in a population of agents. Through pairwise interactions in the games, agents acquire a set of vocabulary in their memory for object naming. The existing model confines to a one-to-one mapping between a name and an object. Focus is usually put onto name consensus in the population rather than knowledge learning in agents, and hence simple learning model is usually adopted. However, the cognition system of human being is much more complex and knowledge is usually presented in a complicated form. Therefore, in this work, we extend the agent learning model and design a new game to incorporate domain learning, which is essential for more complicated form of knowledge. In particular, we demonstrate the evolution of color categorization and naming in a population of agents. We incorporate the human perceptive model into the agents and introduce two new concepts, namely subjective perception and subliminal stimulation, in domain learning. Simulation results show that, even without any supervision or pre-requisition, a consensus of a color naming system can be reached in a population solely via the interactions. Our work confirms the importance of society interactions in color categorization, which is a long debate topic in human cognition. Moreover, our work also demonstrates the possibility of cognitive system development in autonomous intelligent agents. PMID:29136661

Do You See What I See? Exploring the Consequences of Luminosity Limits in Black Hole-Galaxy Evolution Studies

NASA Astrophysics Data System (ADS)

Jones, Mackenzie L.; Hickox, Ryan C.; Mutch, Simon J.; Croton, Darren J.; Ptak, Andrew F.; DiPompeo, Michael A.

2017-07-01

In studies of the connection between active galactic nuclei (AGNs) and their host galaxies, there is widespread disagreement on some key aspects of the connection. These disagreements largely stem from a lack of understanding of the nature of the full underlying AGN population. Recent attempts to probe this connection utilize both observations and simulations to correct for a missed population, but presently are limited by intrinsic biases and complicated models. We take a simple simulation for galaxy evolution and add a new prescription for AGN activity to connect galaxy growth to dark matter halo properties and AGN activity to star formation. We explicitly model selection effects to produce an “observed” AGN population for comparison with observations and empirically motivated models of the local universe. This allows us to bypass the difficulties inherent in models that attempt to infer the AGN population by inverting selection effects. We investigate the impact of selecting AGNs based on thresholds in luminosity or Eddington ratio on the “observed” AGN population. By limiting our model AGN sample in luminosity, we are able to recreate the observed local AGN luminosity function and specific star formation-stellar mass distribution, and show that using an Eddington ratio threshold introduces less bias into the sample by selecting the full range of growing black holes, despite the challenge of selecting low-mass black holes. We find that selecting AGNs using these various thresholds yield samples with different AGN host galaxy properties.

Structures of Neural Correlation and How They Favor Coding

PubMed Central

Franke, Felix; Fiscella, Michele; Sevelev, Maksim; Roska, Botond; Hierlemann, Andreas; da Silveira, Rava Azeredo

2017-01-01

Summary The neural representation of information suffers from “noise”—the trial-to-trial variability in the response of neurons. The impact of correlated noise upon population coding has been debated, but a direct connection between theory and experiment remains tenuous. Here, we substantiate this connection and propose a refined theoretical picture. Using simultaneous recordings from a population of direction-selective retinal ganglion cells, we demonstrate that coding benefits from noise correlations. The effect is appreciable already in small populations, yet it is a collective phenomenon. Furthermore, the stimulus-dependent structure of correlation is key. We develop simple functional models that capture the stimulus-dependent statistics. We then use them to quantify the performance of population coding, which depends upon interplays of feature sensitivities and noise correlations in the population. Because favorable structures of correlation emerge robustly in circuits with noisy, nonlinear elements, they will arise and benefit coding beyond the confines of retina. PMID:26796692

Neutral evolution of mutational robustness

PubMed Central

van Nimwegen, Erik; Crutchfield, James P.; Huynen, Martijn

1999-01-01

We introduce and analyze a general model of a population evolving over a network of selectively neutral genotypes. We show that the population’s limit distribution on the neutral network is solely determined by the network topology and given by the principal eigenvector of the network’s adjacency matrix. Moreover, the average number of neutral mutant neighbors per individual is given by the matrix spectral radius. These results quantify the extent to which populations evolve mutational robustness—the insensitivity of the phenotype to mutations—and thus reduce genetic load. Because the average neutrality is independent of evolutionary parameters—such as mutation rate, population size, and selective advantage—one can infer global statistics of neutral network topology by using simple population data available from in vitro or in vivo evolution. Populations evolving on neutral networks of RNA secondary structures show excellent agreement with our theoretical predictions. PMID:10449760

Optimal quality control of bakers' yeast fed-batch culture using population dynamics.

PubMed

Dairaku, K; Izumoto, E; Morikawa, H; Shioya, S; Takamatsu, T

1982-12-01

An optimal quality control policy for the overall specific growth rate of bakers' yeast, which maximizes the fermentative activity in the making of bread, was obtained by direct searching based on the mathematical model proposed previously. The mathematical model had described the age distribution of bakers' yeast which had an essential relationship to the ability of fermentation in the making of bread. The mathematical model is a simple aging model with two periods: Nonbudding and budding. Based on the result obtained by direct searching, the quality control of bakers' yeast fed-batch culture was performed and confirmed to be experimentally valid.

The penny pusher: a cellular model of lens growth.

PubMed

Shi, Yanrong; De Maria, Alicia; Lubura, Snježana; Šikić, Hrvoje; Bassnett, Steven

2014-12-16

The mechanisms that regulate the number of cells in the lens and, therefore, its size and shape are unknown. We examined the dynamic relationship between proliferative behavior in the epithelial layer and macroscopic lens growth. The distribution of S-phase cells across the epithelium was visualized by confocal microscopy and cell populations were determined from orthographic projections of the lens surface. The number of S-phase cells in the mouse lens epithelium fell exponentially, to an asymptotic value of approximately 200 cells by 6 months. Mitosis became increasingly restricted to a 300-μm-wide swath of equatorial epithelium, the germinative zone (GZ), within which two peaks in labeling index were detected. Postnatally, the cell population increased to approximately 50,000 cells at 4 weeks of age. Thereafter, the number of cells declined, despite continued growth in lens dimensions. This apparently paradoxical observation was explained by a time-dependent increase in the surface area of cells at all locations. The cell biological measurements were incorporated into a physical model, the Penny Pusher. In this simple model, cells were considered to be of a single type, the proliferative behavior of which depended solely on latitude. Simulations using the Penny Pusher predicted the emergence of cell clones and were in good agreement with data obtained from earlier lineage-tracing studies. The Penny Pusher, a simple stochastic model, offers a useful conceptual framework for the investigation of lens growth mechanisms and provides a plausible alternative to growth models that postulate the existence of lens stem cells. Copyright 2015 The Association for Research in Vision and Ophthalmology, Inc.

Hospice care in a commercial preferred provider organization population in Tennessee.

PubMed

Coulter, Steven L; Melvin, Terry; Carden, J Payne; Mathis, Rick S

2015-03-01

This study was undertaken to examine two aspects of care at the end of life. First, we wanted to see whether the cost savings demonstrated repeatedly in the US Medicare hospice population would also be observed in a commercial population in Tennessee. They were. The second primary interest we had was whether there were certain medical services that seemed to presage death. We found four categories of services that profoundly increase in number as the end of life is approached: primary care, hospital-based specialist, non-hospital based specialist, and oncologist services. It is hoped that these findings could lead to a simple predictive model based on readily available claims data to help identify candidates for Hospice Care earlier. © The Author(s) 2013.

Phobic, panic, and major depressive disorders and the five-factor model of personality.

PubMed

Bienvenu, O J; Nestadt, G; Samuels, J F; Costa, P T; Howard, W T; Eaton, W W

2001-03-01

This study investigated five-factor model personality traits in anxiety (simple phobia, social phobia, agoraphobia, and panic disorder) and major depressive disorders in a population-based sample. In the Baltimore Epidemiologic Catchment Area Follow-up Study, psychiatrists administered the Schedules for Clinical Assessment in Neuropsychiatry to 333 adult subjects who also completed the Revised NEO Personality Inventory. All of the disorders except simple phobia were associated with high neuroticism. Social phobia and agoraphobia were associated with low extraversion. In addition, lower-order facets of extraversion, agreeableness, and conscientiousness were associated with certain disorders (i.e., low positive emotions in panic disorder; low trust and compliance in certain phobias; and low competence, achievement striving, and self-discipline in several disorders). This study emphasizes the utility of lower-order personality assessments and underscores the need for further research on personality/psychopathology etiologic relationships.

Simple spatial scaling rules behind complex cities.

PubMed

Li, Ruiqi; Dong, Lei; Zhang, Jiang; Wang, Xinran; Wang, Wen-Xu; Di, Zengru; Stanley, H Eugene

2017-11-28

Although most of wealth and innovation have been the result of human interaction and cooperation, we are not yet able to quantitatively predict the spatial distributions of three main elements of cities: population, roads, and socioeconomic interactions. By a simple model mainly based on spatial attraction and matching growth mechanisms, we reveal that the spatial scaling rules of these three elements are in a consistent framework, which allows us to use any single observation to infer the others. All numerical and theoretical results are consistent with empirical data from ten representative cities. In addition, our model can also provide a general explanation of the origins of the universal super- and sub-linear aggregate scaling laws and accurately predict kilometre-level socioeconomic activity. Our work opens a new avenue for uncovering the evolution of cities in terms of the interplay among urban elements, and it has a broad range of applications.

Impact of committed individuals on vaccination behavior

NASA Astrophysics Data System (ADS)

Liu, Xiao-Tao; Wu, Zhi-Xi; Zhang, Lianzhong

2012-11-01

We study how the presence of committed vaccinators, a small fraction of individuals who consistently hold the vaccinating strategy and are immune to influence, impact the vaccination dynamics in well-mixed and spatially structured populations. For this purpose, we develop an epidemiological game-theoretic model of a flu-like vaccination by integrating an epidemiological process into a simple agent-based model of adaptive learning, where individuals (except for those committed ones) use anecdotal evidence to estimate costs and benefits of vaccination. We show that the committed vaccinators, acting as “steadfast role models” in the populations, can efficiently avoid the clustering of susceptible individuals and stimulate other imitators to take vaccination, hence contributing to the promotion of vaccine uptake. We substantiate our findings by making comparative studies of our model on a full lattice and on a randomly diluted one. Our work is expected to provide valuable information for decision-making and design more effective disease-control strategy.

A general consumer-resource population model

USGS Publications Warehouse

Lafferty, Kevin D.; DeLeo, Giulio; Briggs, Cheryl J.; Dobson, Andrew P.; Gross, Thilo; Kuris, Armand M.

2015-01-01

Food-web dynamics arise from predator-prey, parasite-host, and herbivore-plant interactions. Models for such interactions include up to three consumer activity states (questing, attacking, consuming) and up to four resource response states (susceptible, exposed, ingested, resistant). Articulating these states into a general model allows for dissecting, comparing, and deriving consumer-resource models. We specify this general model for 11 generic consumer strategies that group mathematically into predators, parasites, and micropredators and then derive conditions for consumer success, including a universal saturating functional response. We further show how to use this framework to create simple models with a common mathematical lineage and transparent assumptions. Underlying assumptions, missing elements, and composite parameters are revealed when classic consumer-resource models are derived from the general model.

Spread of epidemic disease on networks

NASA Astrophysics Data System (ADS)

Newman, M. E.

2002-07-01

The study of social networks, and in particular the spread of disease on networks, has attracted considerable recent attention in the physics community. In this paper, we show that a large class of standard epidemiological models, the so-called susceptible/infective/removed (SIR) models can be solved exactly on a wide variety of networks. In addition to the standard but unrealistic case of fixed infectiveness time and fixed and uncorrelated probability of transmission between all pairs of individuals, we solve cases in which times and probabilities are nonuniform and correlated. We also consider one simple case of an epidemic in a structured population, that of a sexually transmitted disease in a population divided into men and women. We confirm the correctness of our exact solutions with numerical simulations of SIR epidemics on networks.

Relation of the runaway avalanche threshold to momentum space topology

DOE PAGES

McDevitt, Christopher J.; Guo, Zehua; Tang, Xian -Zhu

2018-01-05

Here, the underlying physics responsible for the formation of an avalanche instability due to the generation of secondary electrons is studied. A careful examination of the momentum space topology of the runaway electron population is carried out with an eye toward identifying how qualitative changes in the momentum space of the runaway electrons is correlated with the avalanche threshold. It is found that the avalanche threshold is tied to the merger of an O and X point in the momentum space of the primary runaway electron population. Such a change of the momentum space topology is shown to be accuratelymore » described by a simple analytic model, thus providing a powerful means of determining the avalanche threshold for a range of model assumptions.« less

Relation of the runaway avalanche threshold to momentum space topology

DOE Office of Scientific and Technical Information (OSTI.GOV)

McDevitt, Christopher J.; Guo, Zehua; Tang, Xian -Zhu

Here, the underlying physics responsible for the formation of an avalanche instability due to the generation of secondary electrons is studied. A careful examination of the momentum space topology of the runaway electron population is carried out with an eye toward identifying how qualitative changes in the momentum space of the runaway electrons is correlated with the avalanche threshold. It is found that the avalanche threshold is tied to the merger of an O and X point in the momentum space of the primary runaway electron population. Such a change of the momentum space topology is shown to be accuratelymore » described by a simple analytic model, thus providing a powerful means of determining the avalanche threshold for a range of model assumptions.« less

Biophysics, environmental stochasticity, and the evolution of thermal safety margins in intertidal limpets.

PubMed

Denny, M W; Dowd, W W

2012-03-15

As the air temperature of the Earth rises, ecological relationships within a community might shift, in part due to differences in the thermal physiology of species. Prediction of these shifts - an urgent task for ecologists - will be complicated if thermal tolerance itself can rapidly evolve. Here, we employ a mechanistic approach to predict the potential for rapid evolution of thermal tolerance in the intertidal limpet Lottia gigantea. Using biophysical principles to predict body temperature as a function of the state of the environment, and an environmental bootstrap procedure to predict how the environment fluctuates through time, we create hypothetical time-series of limpet body temperatures, which are in turn used as a test platform for a mechanistic evolutionary model of thermal tolerance. Our simulations suggest that environmentally driven stochastic variation of L. gigantea body temperature results in rapid evolution of a substantial 'safety margin': the average lethal limit is 5-7°C above the average annual maximum temperature. This predicted safety margin approximately matches that found in nature, and once established is sufficient, in our simulations, to allow some limpet populations to survive a drastic, century-long increase in air temperature. By contrast, in the absence of environmental stochasticity, the safety margin is dramatically reduced. We suggest that the risk of exceeding the safety margin, rather than the absolute value of the safety margin, plays an underappreciated role in the evolution of thermal tolerance. Our predictions are based on a simple, hypothetical, allelic model that connects genetics to thermal physiology. To move beyond this simple model - and thereby potentially to predict differential evolution among populations and among species - will require significant advances in our ability to translate the details of thermal histories into physiological and population-genetic consequences.

Coupled Socio-Environmental Changes Triggered Indigenous Aymara Depopulation of the Semiarid Andes of Tarapacá-Chile during the Late 19th-20th Centuries.

PubMed

Lima, Mauricio; Christie, Duncan A; Santoro, M Calogero; Latorre, Claudio

2016-01-01

Socio-economic and environmental changes are well known causes of demographic collapse of agrarian cultures. The collapse of human societies is a complex phenomenon where historical and cultural dimensions play a key role, and they may interact with the environmental context. However, the importance of the interaction between socio-economic and climatic factors in explaining possible breakdowns in Native American societies has been poorly explored. The aim of this study is to test the role of socio-economic causes and rainfall variability in the collapse suffered by the Aymara people of the semiarid Andean region of Tarapacá during the period 1820-1970. Our motivation is to demonstrate that simple population dynamic models can be helpful in understanding the causes and relative importance of population changes in Andean agro-pastoral societies in responses to socio-environmental variability. Simple logistic models that combine the effects of external socio-economic causes and past rainfall variability (inferred from Gross Domestic Product [GDP] and tree-rings, respectively) were quite accurate in predicting the sustained population decline of the Aymara people. Our results suggest that the depopulation in the semiarid Tarapacá province was caused by the interaction among external socio-economic pressures given by the economic growth of the lowlands and demands for labor coupled with a persistent decline in rainfall. This study constitutes an example of how applied ecological knowledge, in particular the application of the logistic equation and theories pertaining to nonlinear population dynamics and exogenous perturbations, can be used to better understand major demographic changes in human societies.

Coupled Socio-Environmental Changes Triggered Indigenous Aymara Depopulation of the Semiarid Andes of Tarapacá-Chile during the Late 19th-20th Centuries

PubMed Central

Lima, Mauricio; Christie, Duncan A.; Santoro, M. Calogero; Latorre, Claudio

2016-01-01

Socio-economic and environmental changes are well known causes of demographic collapse of agrarian cultures. The collapse of human societies is a complex phenomenon where historical and cultural dimensions play a key role, and they may interact with the environmental context. However, the importance of the interaction between socio-economic and climatic factors in explaining possible breakdowns in Native American societies has been poorly explored. The aim of this study is to test the role of socio-economic causes and rainfall variability in the collapse suffered by the Aymara people of the semiarid Andean region of Tarapacá during the period 1820–1970. Our motivation is to demonstrate that simple population dynamic models can be helpful in understanding the causes and relative importance of population changes in Andean agro-pastoral societies in responses to socio-environmental variability. Simple logistic models that combine the effects of external socio-economic causes and past rainfall variability (inferred from Gross Domestic Product [GDP] and tree-rings, respectively) were quite accurate in predicting the sustained population decline of the Aymara people. Our results suggest that the depopulation in the semiarid Tarapacá province was caused by the interaction among external socio-economic pressures given by the economic growth of the lowlands and demands for labor coupled with a persistent decline in rainfall. This study constitutes an example of how applied ecological knowledge, in particular the application of the logistic equation and theories pertaining to nonlinear population dynamics and exogenous perturbations, can be used to better understand major demographic changes in human societies. PMID:27560499

Persistence in a Two-Dimensional Moving-Habitat Model.

PubMed

Phillips, Austin; Kot, Mark

2015-11-01

Environmental changes are forcing many species to track suitable conditions or face extinction. In this study, we use a two-dimensional integrodifference equation to analyze whether a population can track a habitat that is moving due to climate change. We model habitat as a simple rectangle. Our model quickly leads to an eigenvalue problem that determines whether the population persists or declines. After surveying techniques to solve the eigenvalue problem, we highlight three findings that impact conservation efforts such as reserve design and species risk assessment. First, while other models focus on habitat length (parallel to the direction of habitat movement), we show that ignoring habitat width (perpendicular to habitat movement) can lead to overestimates of persistence. Dispersal barriers and hostile landscapes that constrain habitat width greatly decrease the population's ability to track its habitat. Second, for some long-distance dispersal kernels, increasing habitat length improves persistence without limit; for other kernels, increasing length is of limited help and has diminishing returns. Third, it is not always best to orient the long side of the habitat in the direction of climate change. Evidence suggests that the kurtosis of the dispersal kernel determines whether it is best to have a long, wide, or square habitat. In particular, populations with platykurtic dispersal benefit more from a wide habitat, while those with leptokurtic dispersal benefit more from a long habitat. We apply our model to the Rocky Mountain Apollo butterfly (Parnassius smintheus).

Application of models to conservation planning for terrestrial birds in North America

USGS Publications Warehouse

Fitzgerald, Jane A.; Thogmartin, Wayne E.; Dettmers, Randy; Jones, Tim; Rustay, Christopher; Ruth, Janet M.; Thompson, Frank R.; Will, Tom; Millspaugh, Joshua J.; Thompson, Frank R.

2009-01-01

Partners in Flight (PIF), a public–private coalition for the conservation of land birds, has developed one of four international bird conservation plans recognized under the auspices of the North American Bird Conservation Initiative (NABCI). Partners in Flight prioritized species most in need of conservation attention and set range-wide population goals for 448 species of terrestrial birds. Partnerships are now tasked with developing spatially explicit estimates of the distribution, and abundance of priority species across large ecoregions and identifying habitat acreages needed to support populations at prescribed levels. The PIF Five Elements process of conservation design identifies five steps needed to implement all bird conservation at the ecoregional scale. Habitat assessment and landscape characterization describe the current amounts of different habitat types and summarize patch characteristics, and landscape configurations that define the ability of a landscape to sustain healthy bird populations and are a valuable first step to describing the planning area before pursuing more complex species-specific models. Spatially linked database models, landscape-scale habitat suitability models, and statistical models are viable alternatives for predicting habitat suitability or bird abundance across large planning areas to help assess conservation opportunities, design landscapes to meet population objectives, and monitor change in habitat suitability or bird numbers over time.Bird conservation in the United States is a good example of the use of models in large-scale wildlife conservation planning because of its geographic extent, focus on multiple species, involvement of multiple partners, and use of simple to complex models. We provide some background on the recent development of bird conservation initiatives in the United States and the approaches used for regional conservation assessment and planning. We focus on approaches being used for landscape characterization and assessment, and bird population response modeling.

The assumption of equilibrium in models of migration.

PubMed

Schachter, J; Althaus, P G

1993-02-01

In recent articles Evans (1990) and Harrigan and McGregor (1993) (hereafter HM) scrutinized the equilibrium model of migration presented in a 1989 paper by Schachter and Althaus. This model used standard microeconomics to analyze gross interregional migration flows based on the assumption that gross flows are in approximate equilibrium. HM criticized the model as theoretically untenable, while Evans summoned empirical as well as theoretical objections. HM claimed that equilibrium of gross migration flows could be ruled out on theoretical grounds. They argued that the absence of net migration requires that either all regions have equal populations or that unsustainable regional migration propensities must obtain. In fact some moves are inter- and other are intraregional. It does not follow, however, that the number of interregional migrants will be larger for the more populous region. Alternatively, a country could be divided into a large number of small regions that have equal populations. With uniform propensities to move, each of these analytical regions would experience in equilibrium zero net migration. Hence, the condition that net migration equal zero is entirely consistent with unequal distributions of population across regions. The criticisms of Evans were based both on flawed reasoning and on misinterpretation of the results of a number of econometric studies. His reasoning assumed that the existence of demand shifts as found by Goldfarb and Yezer (1987) and Topel (1986) invalidated the equilibrium model. The equilibrium never really obtains exactly, but economic modeling of migration properly begins with a simple equilibrium model of the system. A careful reading of the papers Evans cited in support of his position showed that in fact they affirmed rather than denied the appropriateness of equilibrium modeling. Zero net migration together with nonzero gross migration are not theoretically incompatible with regional heterogeneity of population, wages, or amenities.

Establishment probability in newly founded populations.

PubMed

Gusset, Markus; Müller, Michael S; Grimm, Volker

2012-06-20

Establishment success in newly founded populations relies on reaching the established phase, which is defined by characteristic fluctuations of the population's state variables. Stochastic population models can be used to quantify the establishment probability of newly founded populations; however, so far no simple but robust method for doing so existed. To determine a critical initial number of individuals that need to be released to reach the established phase, we used a novel application of the "Wissel plot", where -ln(1 - P0(t)) is plotted against time t. This plot is based on the equation P(0)t=1-c(1)e(-ω(1t)), which relates the probability of extinction by time t, P(0)(t), to two constants: c(1) describes the probability of a newly founded population to reach the established phase, whereas ω(1) describes the population's probability of extinction per short time interval once established. For illustration, we applied the method to a previously developed stochastic population model of the endangered African wild dog (Lycaon pictus). A newly founded population reaches the established phase if the intercept of the (extrapolated) linear parts of the "Wissel plot" with the y-axis, which is -ln(c(1)), is negative. For wild dogs in our model, this is the case if a critical initial number of four packs, consisting of eight individuals each, are released. The method we present to quantify the establishment probability of newly founded populations is generic and inferences thus are transferable to other systems across the field of conservation biology. In contrast to other methods, our approach disaggregates the components of a population's viability by distinguishing establishment from persistence.

Reduced Order Models Via Continued Fractions Applied to Control Systems,

DTIC Science & Technology

1980-09-01

a simple * model of a nuclear reactor power generator [20, 21]. The heat generating process of a nuclear reactor is dependent upon the mechanism...called fission (a fragmentation of matter). The power generated by this process is directly related to the population of neutrons, n~t) and can be...150) 6(t ()n~t) - c(t) (151) where 6k(t) 6 kc(t)-an(t) (152) The variable 6k(t) is the input to the process and is given the name "reactivity". It is

A novel risk score model for prediction of contrast-induced nephropathy after emergent percutaneous coronary intervention.

PubMed

Lin, Kai-Yang; Zheng, Wei-Ping; Bei, Wei-Jie; Chen, Shi-Qun; Islam, Sheikh Mohammed Shariful; Liu, Yong; Xue, Lin; Tan, Ning; Chen, Ji-Yan

2017-03-01

A few studies developed simple risk model for predicting CIN with poor prognosis after emergent PCI. The study aimed to develop and validate a novel tool for predicting the risk of contrast-induced nephropathy (CIN) in patients undergoing emergent percutaneous coronary intervention (PCI). 692 consecutive patients undergoing emergent PCI between January 2010 and December 2013 were randomly (2:1) assigned to a development dataset (n=461) and a validation dataset (n=231). Multivariate logistic regression was applied to identify independent predictors of CIN, and established CIN predicting model, whose prognostic accuracy was assessed using the c-statistic for discrimination and the Hosmere Lemeshow test for calibration. The overall incidence of CIN was 55(7.9%). A total of 11 variables were analyzed, including age >75years old, baseline serum creatinine (SCr)>1.5mg/dl, hypotension and the use of intra-aortic balloon pump(IABP), which were identified to enter risk score model (Chen). The incidence of CIN was 32(6.9%) in the development dataset (in low risk (score=0), 1.0%, moderate risk (score:1-2), 13.4%, high risk (score≥3), 90.0%). Compared to the classical Mehran's and ACEF CIN risk score models, the risk score (Chen) across the subgroup of the study population exhibited similar discrimination and predictive ability on CIN (c-statistic:0.828, 0.776, 0.853, respectively), in-hospital mortality, 2, 3-years mortality (c-statistic:0.738.0.750, 0.845, respectively) in the validation population. Our data showed that this simple risk model exhibited good discrimination and predictive ability on CIN, similar to Mehran's and ACEF score, and even on long-term mortality after emergent PCI. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

From innervation density to tactile acuity: 1. Spatial representation.

PubMed

Brown, Paul B; Koerber, H Richard; Millecchia, Ronald

2004-06-11

We tested the hypothesis that the population receptive field representation (a superposition of the excitatory receptive field areas of cells responding to a tactile stimulus) provides spatial information sufficient to mediate one measure of static tactile acuity. In psychophysical tests, two-point discrimination thresholds on the hindlimbs of adult cats varied as a function of stimulus location and orientation, as they do in humans. A statistical model of the excitatory low threshold mechanoreceptive fields of spinocervical, postsynaptic dorsal column and spinothalamic tract neurons was used to simulate the population receptive field representations in this neural population of the one- and two-point stimuli used in the psychophysical experiments. The simulated and observed thresholds were highly correlated. Simulated and observed thresholds' relations to physiological and anatomical variables such as stimulus location and orientation, receptive field size and shape, map scale, and innervation density were strikingly similar. Simulated and observed threshold variations with receptive field size and map scale obeyed simple relationships predicted by the signal detection model, and were statistically indistinguishable from each other. The population receptive field representation therefore contains information sufficient for this discrimination.

Bacterial finite-size effects for population expansion under flow

NASA Astrophysics Data System (ADS)

Toschi, Federico; Tesser, Francesca; Zeegers, Jos C. H.; Clercx, Herman J. H.; Brunsveld, Luc

2016-11-01

For organisms living in a liquid ecosystem, flow and flow gradients have a dual role as they transport nutrient while, at the same time, dispersing the individuals. In absence of flow and under homogeneous conditions, the growth of a population towards an empty region is usually described by a reaction-diffusion equation. The effect of fluid flow is not yet well understood and the interplay between transport of individuals and growth opens a wide scenario of possible behaviors. In this work, we study experimentally the dynamics of non-motile E. coli bacteria colonies spreading inside rectangular channels, in PDMS microfluidic devices. By use of a fluorescent microscope we analyze the dynamics of the population density subjected to different co- and counter-flow conditions and shear rates. A simple model incorporating growth, dispersion and drift of finite size beads is able to explain the experimental findings. This indicates that models based on the Fisher-Kolmogorov-Petrovsky-Piscounov equation (FKPP) may have to be supplemented with bacterial finite-size effects in order to be able to accurately reproduce experimental results for population spatial growth.

Simple graph models of information spread in finite populations

PubMed Central

Voorhees, Burton; Ryder, Bergerud

2015-01-01

We consider several classes of simple graphs as potential models for information diffusion in a structured population. These include biases cycles, dual circular flows, partial bipartite graphs and what we call ‘single-link’ graphs. In addition to fixation probabilities, we study structure parameters for these graphs, including eigenvalues of the Laplacian, conductances, communicability and expected hitting times. In several cases, values of these parameters are related, most strongly so for partial bipartite graphs. A measure of directional bias in cycles and circular flows arises from the non-zero eigenvalues of the antisymmetric part of the Laplacian and another measure is found for cycles as the value of the transition probability for which hitting times going in either direction of the cycle are equal. A generalization of circular flow graphs is used to illustrate the possibility of tuning edge weights to match pre-specified values for graph parameters; in particular, we show that generalizations of circular flows can be tuned to have fixation probabilities equal to the Moran probability for a complete graph by tuning vertex temperature profiles. Finally, single-link graphs are introduced as an example of a graph involving a bottleneck in the connection between two components and these are compared to the partial bipartite graphs. PMID:26064661

Climate change impact assessment on food security in Indonesia

NASA Astrophysics Data System (ADS)

Ettema, Janneke; Aldrian, Edvin; de Bie, Kees; Jetten, Victor; Mannaerts, Chris

2013-04-01

As Indonesia is the world's fourth most populous country, food security is a persistent challenge. The potential impact of future climate change on the agricultural sector needs to be addressed in order to allow early implementation of mitigation strategies. The complex island topography and local sea-land-air interactions cannot adequately be represented in large scale General Climate Models (GCMs) nor visualized by TRMM. Downscaling is needed. Using meteorological observations and a simple statistical downscaling tool, local future projections are derived from state-of-the-art, large-scale GCM scenarios, provided by the CMIP5 project. To support the agriculture sector, providing information on especially rainfall and temperature variability is essential. Agricultural production forecast is influenced by several rain and temperature factors, such as rainy and dry season onset, offset and length, but also by daily and monthly minimum and maximum temperatures and its rainfall amount. A simple and advanced crop model will be used to address the sensitivity of different crops to temperature and rainfall variability, present-day and future. As case study area, Java Island is chosen as it is fourth largest island in Indonesia but contains more than half of the nation's population and dominates it politically and economically. The objective is to identify regions at agricultural risk due to changing patterns in precipitation and temperature.

Signatures of criticality arise from random subsampling in simple population models.

PubMed

Nonnenmacher, Marcel; Behrens, Christian; Berens, Philipp; Bethge, Matthias; Macke, Jakob H

2017-10-01

The rise of large-scale recordings of neuronal activity has fueled the hope to gain new insights into the collective activity of neural ensembles. How can one link the statistics of neural population activity to underlying principles and theories? One attempt to interpret such data builds upon analogies to the behaviour of collective systems in statistical physics. Divergence of the specific heat-a measure of population statistics derived from thermodynamics-has been used to suggest that neural populations are optimized to operate at a "critical point". However, these findings have been challenged by theoretical studies which have shown that common inputs can lead to diverging specific heat. Here, we connect "signatures of criticality", and in particular the divergence of specific heat, back to statistics of neural population activity commonly studied in neural coding: firing rates and pairwise correlations. We show that the specific heat diverges whenever the average correlation strength does not depend on population size. This is necessarily true when data with correlations is randomly subsampled during the analysis process, irrespective of the detailed structure or origin of correlations. We also show how the characteristic shape of specific heat capacity curves depends on firing rates and correlations, using both analytically tractable models and numerical simulations of a canonical feed-forward population model. To analyze these simulations, we develop efficient methods for characterizing large-scale neural population activity with maximum entropy models. We find that, consistent with experimental findings, increases in firing rates and correlation directly lead to more pronounced signatures. Thus, previous reports of thermodynamical criticality in neural populations based on the analysis of specific heat can be explained by average firing rates and correlations, and are not indicative of an optimized coding strategy. We conclude that a reliable interpretation of statistical tests for theories of neural coding is possible only in reference to relevant ground-truth models.

Positive feedback in the transition from sexual reproduction to parthenogenesis.

PubMed

Schwander, Tanja; Vuilleumier, Séverine; Dubman, Janie; Crespi, Bernard J

2010-05-07

Understanding how new phenotypes evolve is challenging because intermediate stages in transitions from ancestral to derived phenotypes often remain elusive. Here we describe and evaluate a new mechanism facilitating the transition from sexual reproduction to parthenogenesis. In many sexually reproducing species, a small proportion of unfertilized eggs can hatch spontaneously ('tychoparthenogenesis') and develop into females. Using an analytical model, we show that if females are mate-limited, tychoparthenogenesis can result in the loss of males through a positive feedback mechanism whereby tychoparthenogenesis generates female-biased sex ratios and increasing mate limitation. As a result, the strength of selection for tychoparthenogenesis increases in concert with the proportion of tychoparthenogenetic offspring in the sexual population. We then tested the hypothesis that mate limitation selects for tychoparthenogenesis and generates female-biased sex ratios, using data from natural populations of sexually reproducing Timema stick insects. Across 41 populations, both the tychoparthenogenesis rates and the proportions of females increased exponentially as the density of individuals decreased, consistent with the idea that low densities of individuals result in mate limitation and selection for reproductive insurance through tychoparthenogenesis. Our model and data from Timema populations provide evidence for a simple mechanism through which parthenogenesis can evolve rapidly in a sexual population.

Homogenization of Large-Scale Movement Models in Ecology

USGS Publications Warehouse

Garlick, M.J.; Powell, J.A.; Hooten, M.B.; McFarlane, L.R.

2011-01-01

A difficulty in using diffusion models to predict large scale animal population dispersal is that individuals move differently based on local information (as opposed to gradients) in differing habitat types. This can be accommodated by using ecological diffusion. However, real environments are often spatially complex, limiting application of a direct approach. Homogenization for partial differential equations has long been applied to Fickian diffusion (in which average individual movement is organized along gradients of habitat and population density). We derive a homogenization procedure for ecological diffusion and apply it to a simple model for chronic wasting disease in mule deer. Homogenization allows us to determine the impact of small scale (10-100 m) habitat variability on large scale (10-100 km) movement. The procedure generates asymptotic equations for solutions on the large scale with parameters defined by small-scale variation. The simplicity of this homogenization procedure is striking when compared to the multi-dimensional homogenization procedure for Fickian diffusion,and the method will be equally straightforward for more complex models. ?? 2010 Society for Mathematical Biology.

Random-growth urban model with geographical fitness

NASA Astrophysics Data System (ADS)

Kii, Masanobu; Akimoto, Keigo; Doi, Kenji

2012-12-01

This paper formulates a random-growth urban model with a notion of geographical fitness. Using techniques of complex-network theory, we study our system as a type of preferential-attachment model with fitness, and we analyze its macro behavior to clarify the properties of the city-size distributions it predicts. First, restricting the geographical fitness to take positive values and using a continuum approach, we show that the city-size distributions predicted by our model asymptotically approach Pareto distributions with coefficients greater than unity. Then, allowing the geographical fitness to take negative values, we perform local coefficient analysis to show that the predicted city-size distributions can deviate from Pareto distributions, as is often observed in actual city-size distributions. As a result, the model we propose can generate a generic class of city-size distributions, including but not limited to Pareto distributions. For applications to city-population projections, our simple model requires randomness only when new cities are created, not during their subsequent growth. This property leads to smooth trajectories of city population growth, in contrast to other models using Gibrat’s law. In addition, a discrete form of our dynamical equations can be used to estimate past city populations based on present-day data; this fact allows quantitative assessment of the performance of our model. Further study is needed to determine appropriate formulas for the geographical fitness.

Bistability, non-ergodicity, and inhibition in pairwise maximum-entropy models

PubMed Central

Grün, Sonja; Helias, Moritz

2017-01-01

Pairwise maximum-entropy models have been used in neuroscience to predict the activity of neuronal populations, given only the time-averaged correlations of the neuron activities. This paper provides evidence that the pairwise model, applied to experimental recordings, would produce a bimodal distribution for the population-averaged activity, and for some population sizes the second mode would peak at high activities, that experimentally would be equivalent to 90% of the neuron population active within time-windows of few milliseconds. Several problems are connected with this bimodality: 1. The presence of the high-activity mode is unrealistic in view of observed neuronal activity and on neurobiological grounds. 2. Boltzmann learning becomes non-ergodic, hence the pairwise maximum-entropy distribution cannot be found: in fact, Boltzmann learning would produce an incorrect distribution; similarly, common variants of mean-field approximations also produce an incorrect distribution. 3. The Glauber dynamics associated with the model is unrealistically bistable and cannot be used to generate realistic surrogate data. This bimodality problem is first demonstrated for an experimental dataset from 159 neurons in the motor cortex of macaque monkey. Evidence is then provided that this problem affects typical neural recordings of population sizes of a couple of hundreds or more neurons. The cause of the bimodality problem is identified as the inability of standard maximum-entropy distributions with a uniform reference measure to model neuronal inhibition. To eliminate this problem a modified maximum-entropy model is presented, which reflects a basic effect of inhibition in the form of a simple but non-uniform reference measure. This model does not lead to unrealistic bimodalities, can be found with Boltzmann learning, and has an associated Glauber dynamics which incorporates a minimal asymmetric inhibition. PMID:28968396

From cultural traditions to cumulative culture: parameterizing the differences between human and nonhuman culture.

PubMed

Kempe, Marius; Lycett, Stephen J; Mesoudi, Alex

2014-10-21

Diverse species exhibit cultural traditions, i.e. population-specific profiles of socially learned traits, from songbird dialects to primate tool-use behaviours. However, only humans appear to possess cumulative culture, in which cultural traits increase in complexity over successive generations. Theoretically, it is currently unclear what factors give rise to these phenomena, and consequently why cultural traditions are found in several species but cumulative culture in only one. Here, we address this by constructing and analysing cultural evolutionary models of both phenomena that replicate empirically attestable levels of cultural variation and complexity in chimpanzees and humans. In our model of cultural traditions (Model 1), we find that realistic cultural variation between populations can be maintained even when individuals in different populations invent the same traits and migration between populations is frequent, and under a range of levels of social learning accuracy. This lends support to claims that putative cultural traditions are indeed cultural (rather than genetic) in origin, and suggests that cultural traditions should be widespread in species capable of social learning. Our model of cumulative culture (Model 2) indicates that both the accuracy of social learning and the number of cultural demonstrators interact to determine the complexity of a trait that can be maintained in a population. Combining these models (Model 3) creates two qualitatively distinct regimes in which there are either a few, simple traits, or many, complex traits. We suggest that these regimes correspond to nonhuman and human cultures, respectively. The rarity of cumulative culture in nature may result from this interaction between social learning accuracy and number of demonstrators. Copyright © 2014 Elsevier Ltd. All rights reserved.

Bistability, non-ergodicity, and inhibition in pairwise maximum-entropy models.

PubMed

Rostami, Vahid; Porta Mana, PierGianLuca; Grün, Sonja; Helias, Moritz

2017-10-01

Pairwise maximum-entropy models have been used in neuroscience to predict the activity of neuronal populations, given only the time-averaged correlations of the neuron activities. This paper provides evidence that the pairwise model, applied to experimental recordings, would produce a bimodal distribution for the population-averaged activity, and for some population sizes the second mode would peak at high activities, that experimentally would be equivalent to 90% of the neuron population active within time-windows of few milliseconds. Several problems are connected with this bimodality: 1. The presence of the high-activity mode is unrealistic in view of observed neuronal activity and on neurobiological grounds. 2. Boltzmann learning becomes non-ergodic, hence the pairwise maximum-entropy distribution cannot be found: in fact, Boltzmann learning would produce an incorrect distribution; similarly, common variants of mean-field approximations also produce an incorrect distribution. 3. The Glauber dynamics associated with the model is unrealistically bistable and cannot be used to generate realistic surrogate data. This bimodality problem is first demonstrated for an experimental dataset from 159 neurons in the motor cortex of macaque monkey. Evidence is then provided that this problem affects typical neural recordings of population sizes of a couple of hundreds or more neurons. The cause of the bimodality problem is identified as the inability of standard maximum-entropy distributions with a uniform reference measure to model neuronal inhibition. To eliminate this problem a modified maximum-entropy model is presented, which reflects a basic effect of inhibition in the form of a simple but non-uniform reference measure. This model does not lead to unrealistic bimodalities, can be found with Boltzmann learning, and has an associated Glauber dynamics which incorporates a minimal asymmetric inhibition.

Genetic diversity of Pinus nigra Arn. populations in Southern Spain and Northern Morocco revealed by inter-simple sequence repeat profiles.

PubMed

Rubio-Moraga, Angela; Candel-Perez, David; Lucas-Borja, Manuel E; Tiscar, Pedro A; Viñegla, Benjamin; Linares, Juan C; Gómez-Gómez, Lourdes; Ahrazem, Oussama

2012-01-01

Eight Pinus nigra Arn. populations from Southern Spain and Northern Morocco were examined using inter-simple sequence repeat markers to characterize the genetic variability amongst populations. Pair-wise population genetic distance ranged from 0.031 to 0.283, with a mean of 0.150 between populations. The highest inter-population average distance was between PaCU from Cuenca and YeCA from Cazorla, while the lowest distance was between TaMO from Morocco and MA Sierra Mágina populations. Analysis of molecular variance (AMOVA) and Nei's genetic diversity analyses revealed higher genetic variation within the same population than among different populations. Genetic differentiation (Gst) was 0.233. Cuenca showed the highest Nei's genetic diversity followed by the Moroccan region, Sierra Mágina, and Cazorla region. However, clustering of populations was not in accordance with their geographical locations. Principal component analysis showed the presence of two major groups-Group 1 contained all populations from Cuenca while Group 2 contained populations from Cazorla, Sierra Mágina and Morocco-while Bayesian analysis revealed the presence of three clusters. The low genetic diversity observed in PaCU and YeCA is probably a consequence of inappropriate management since no estimation of genetic variability was performed before the silvicultural treatments. Data indicates that the inter-simple sequence repeat (ISSR) method is sufficiently informative and powerful to assess genetic variability among populations of P. nigra.

Genetic Diversity of Pinus nigra Arn. Populations in Southern Spain and Northern Morocco Revealed By Inter-Simple Sequence Repeat Profiles †

PubMed Central

Rubio-Moraga, Angela; Candel-Perez, David; Lucas-Borja, Manuel E.; Tiscar, Pedro A.; Viñegla, Benjamin; Linares, Juan C.; Gómez-Gómez, Lourdes; Ahrazem, Oussama

2012-01-01

Eight Pinus nigra Arn. populations from Southern Spain and Northern Morocco were examined using inter-simple sequence repeat markers to characterize the genetic variability amongst populations. Pair-wise population genetic distance ranged from 0.031 to 0.283, with a mean of 0.150 between populations. The highest inter-population average distance was between PaCU from Cuenca and YeCA from Cazorla, while the lowest distance was between TaMO from Morocco and MA Sierra Mágina populations. Analysis of molecular variance (AMOVA) and Nei’s genetic diversity analyses revealed higher genetic variation within the same population than among different populations. Genetic differentiation (Gst) was 0.233. Cuenca showed the highest Nei’s genetic diversity followed by the Moroccan region, Sierra Mágina, and Cazorla region. However, clustering of populations was not in accordance with their geographical locations. Principal component analysis showed the presence of two major groups—Group 1 contained all populations from Cuenca while Group 2 contained populations from Cazorla, Sierra Mágina and Morocco—while Bayesian analysis revealed the presence of three clusters. The low genetic diversity observed in PaCU and YeCA is probably a consequence of inappropriate management since no estimation of genetic variability was performed before the silvicultural treatments. Data indicates that the inter-simple sequence repeat (ISSR) method is sufficiently informative and powerful to assess genetic variability among populations of P. nigra. PMID:22754321

Estimating tuberculosis incidence from primary survey data: a mathematical modeling approach

PubMed Central

Chadha, V. K.; Laxminarayan, R.; Arinaminpathy, N.

2017-01-01

SUMMARY BACKGROUND: There is an urgent need for improved estimations of the burden of tuberculosis (TB). OBJECTIVE: To develop a new quantitative method based on mathematical modelling, and to demonstrate its application to TB in India. DESIGN: We developed a simple model of TB transmission dynamics to estimate the annual incidence of TB disease from the annual risk of tuberculous infection and prevalence of smear-positive TB. We first compared model estimates for annual infections per smear-positive TB case using previous empirical estimates from China, Korea and the Philippines. We then applied the model to estimate TB incidence in India, stratified by urban and rural settings. RESULTS: Study model estimates show agreement with previous empirical estimates. Applied to India, the model suggests an annual incidence of smear-positive TB of 89.8 per 100 000 population (95%CI 56.8–156.3). Results show differences in urban and rural TB: while an urban TB case infects more individuals per year, a rural TB case remains infectious for appreciably longer, suggesting the need for interventions tailored to these different settings. CONCLUSIONS: Simple models of TB transmission, in conjunction with necessary data, can offer approaches to burden estimation that complement those currently being used. PMID:28284250

Dependence of the Population on the Temperature in the Boltzmann Distribution: A Simple Relation Involving the Average Energy

ERIC Educational Resources Information Center

Angeli, Celestino; Cimiraglia, Renzo; Dallo, Federico; Guareschi, Riccardo; Tenti, Lorenzo

2013-01-01

The dependence on the temperature of the population of the "i"th state, "P"[subscript "i"], in the Boltzmann distribution is analyzed by studying its derivative with respect to the temperature, "T." A simple expression is found, involving "P"[subscript "i"], the energy of the state,…

A Large Stellar Evolution Database for Population Synthesis Studies. I. Scaled Solar Models and Isochrones

NASA Astrophysics Data System (ADS)

Pietrinferni, Adriano; Cassisi, Santi; Salaris, Maurizio; Castelli, Fiorella

2004-09-01

We present a large and updated stellar evolution database for low-, intermediate-, and high-mass stars in a wide metallicity range, suitable for studying Galactic and extragalactic simple and composite stellar populations using population synthesis techniques. The stellar mass range is between ~0.5 and 10 Msolar with a fine mass spacing. The metallicity [Fe/H] comprises 10 values ranging from -2.27 to 0.40, with a scaled solar metal distribution. The initial He mass fraction ranges from Y=0.245, for the more metal-poor composition, up to 0.303 for the more metal-rich one, with ΔY/ΔZ~1.4. For each adopted chemical composition, the evolutionary models have been computed without (canonical models) and with overshooting from the Schwarzschild boundary of the convective cores during the central H-burning phase. Semiconvection is included in the treatment of core convection during the He-burning phase. The whole set of evolutionary models can be used to compute isochrones in a wide age range, from ~30 Myr to ~15 Gyr. Both evolutionary models and isochrones are available in several observational planes, employing an updated set of bolometric corrections and color-Teff relations computed for this project. The number of points along the models and the resulting isochrones is selected in such a way that interpolation for intermediate metallicities not contained in the grid is straightforward; a simple quadratic interpolation produces results of sufficient accuracy for population synthesis applications.We compare our isochrones with results from a series of widely used stellar evolution databases and perform some empirical tests for the reliability of our models. Since this work is devoted to scaled solar chemical compositions, we focus our attention on the Galactic disk stellar populations, employing multicolor photometry of unevolved field main-sequence stars with precise Hipparcos parallaxes, well-studied open clusters, and one eclipsing binary system with precise measurements of masses, radii, and [Fe/H] of both components. We find that the predicted metallicity dependence of the location of the lower, unevolved main sequence in the color magnitude diagram (CMD) appears in satisfactory agreement with empirical data. When comparing our models with CMDs of selected, well-studied, open clusters, once again we were able to properly match the whole observed evolutionary sequences by assuming cluster distance and reddening estimates in satisfactory agreement with empirical evaluations of these quantities. In general, models including overshooting during the H-burning phase provide a better match to the observations, at least for ages below ~4 Gyr. At [Fe/H] around solar and higher ages (i.e., smaller convective cores) before the onset of radiative cores, the selected efficiency of core overshooting may be too high in our model, as well as in various other models in the literature. Since we also provide canonical models, the reader is strongly encouraged to always compare the results from both sets in this critical age range.

Vaccine Effects on Heterogeneity in Susceptibility and Implications for Population Health Management

PubMed Central

Wargo, Andrew R.; Jones, Darbi R.; Viss, Jessie R.; Rutan, Barbara J.; Egan, Nicholas A.; Sá-Guimarães, Pedro; Kim, Min Sun; Kurath, Gael; Gomes, M. Gabriela M.

2017-01-01

ABSTRACT Heterogeneity in host susceptibility is a key determinant of infectious disease dynamics but is rarely accounted for in assessment of disease control measures. Understanding how susceptibility is distributed in populations, and how control measures change this distribution, is integral to predicting the course of epidemics with and without interventions. Using multiple experimental and modeling approaches, we show that rainbow trout have relatively homogeneous susceptibility to infection with infectious hematopoietic necrosis virus and that vaccination increases heterogeneity in susceptibility in a nearly all-or-nothing fashion. In a simple transmission model with an R0 of 2, the highly heterogeneous vaccine protection would cause a 35 percentage-point reduction in outbreak size over an intervention inducing homogenous protection at the same mean level. More broadly, these findings provide validation of methodology that can help to reduce biases in predictions of vaccine impact in natural settings and provide insight into how vaccination shapes population susceptibility. PMID:29162706

Prey-producing predators: the ecology of human intensification.

PubMed

Efferson, Charles

2008-01-01

Economic growth theory and theoretical ecology represent independent traditions of modeling aggregate consumer-resource systems. Both focus on different but equally important forces underlying the dynamics of human societies. Though the two traditions have unknowingly converged in some ways, they each have curious conventions from the perspective of the other. These conventions are reviewed, and two separate modeling frameworks that integrate the two traditions in a simple and straightforward fashion are developed and analyzed. The resulting models represent a consumer species (e.g. humans) that both produces and consumes its resources and then reproduces biologically according to the consumption of its resources. Depending on the balance between production, consumption, and reproduction, the models can exhibit stagnant behavior, like some predator-prey models, or growth, like many mutualism and economic growth models. When growth occurs, in the long term it takes one of two forms. Either resources per capita grow and the human population size converges to a constant, which may be zero, or resources per capita converge to a constant and the human population grows. The difference depends on initial conditions and the particular mix of biological conditions and human technology.

M13-Tailed Simple Sequence Repeat (SSR) Markers in Studies of Genetic Diversity and Population Structure of Common Oat Germplasm.

PubMed

Onyśk, Agnieszka; Boczkowska, Maja

2017-01-01

Simple Sequence Repeat (SSR) markers are one of the most frequently used molecular markers in studies of crop diversity and population structure. This is due to their uniform distribution in the genome, the high polymorphism, reproducibility, and codominant character. Additional advantages are the possibility of automatic analysis and simple interpretation of the results. The M13 tagged PCR reaction significantly reduces the costs of analysis by the automatic genetic analyzers. Here, we also disclose a short protocol of SSR data analysis.

Simple predictive model for Early Childhood Caries of Chilean children.

PubMed

Fierro Monti, Claudia; Pérez Flores, M; Brunotto, M

2014-01-01

Early Childhood Caries (ECC), in both industrialized and developing countries, is the most prevalent chronic disease in childhood and it is still a health public problem, affecting mainly populations considered as vulnerable, despite being preventable. The purpose of this study was to obtain a simple predictive model based on risk factors for improving public health strategies for ECC prevention for 3-5 year-old children. Clinical, environmental and psycho-socio-cultural data of children (n=250) aged 3-5 years, of both genders, from the Health Centers, were recorded in a Clinical History and Behavioral Survey. 24% of children presented behavioral problems (bizarre behavior was the main feature observed as behavioral problems). The variables associated to dmf ?4 were: bad children temperament (OR=2.43 [1.34, 4.40]) and home stress (OR=3.14 [1.54, 6.41]). It was observed that the model for male gender has higher accuracy for ECC (AUC= 78%, p-value=0.000) than others. Based on the results, we proposed a model where oral hygiene, sugar intake, male gender, and difficult temperament are main factors for predicting ECC. This model could be a promising tool for cost-effective early childhood caries control.

State-space models’ dirty little secrets: even simple linear Gaussian models can have estimation problems

NASA Astrophysics Data System (ADS)

Auger-Méthé, Marie; Field, Chris; Albertsen, Christoffer M.; Derocher, Andrew E.; Lewis, Mark A.; Jonsen, Ian D.; Mills Flemming, Joanna

2016-05-01

State-space models (SSMs) are increasingly used in ecology to model time-series such as animal movement paths and population dynamics. This type of hierarchical model is often structured to account for two levels of variability: biological stochasticity and measurement error. SSMs are flexible. They can model linear and nonlinear processes using a variety of statistical distributions. Recent ecological SSMs are often complex, with a large number of parameters to estimate. Through a simulation study, we show that even simple linear Gaussian SSMs can suffer from parameter- and state-estimation problems. We demonstrate that these problems occur primarily when measurement error is larger than biological stochasticity, the condition that often drives ecologists to use SSMs. Using an animal movement example, we show how these estimation problems can affect ecological inference. Biased parameter estimates of a SSM describing the movement of polar bears (Ursus maritimus) result in overestimating their energy expenditure. We suggest potential solutions, but show that it often remains difficult to estimate parameters. While SSMs are powerful tools, they can give misleading results and we urge ecologists to assess whether the parameters can be estimated accurately before drawing ecological conclusions from their results.

ZFIRE: using Hα equivalent widths to investigate the in situ initial mass function at z ˜ 2

NASA Astrophysics Data System (ADS)

Nanayakkara, Themiya; Glazebrook, Karl; Kacprzak, Glenn G.; Yuan, Tiantian; Fisher, David; Tran, Kim-Vy; Kewley, Lisa J.; Spitler, Lee; Alcorn, Leo; Cowley, Michael; Labbe, Ivo; Straatman, Caroline; Tomczak, Adam

2017-07-01

We use the ZFIRE (http://zfire.swinburne.edu.au) survey to investigate the high-mass slope of the initial mass function (IMF) for a mass-complete (log_{10({M}_*/M_{⊙})˜ 9.3}) sample of 102 star-forming galaxies at z ˜ 2 using their Hα equivalent widths (Hα EWs) and rest-frame optical colours. We compare dust-corrected Hα EW distributions with predictions of star formation histories (SFHs) from pegase.2 and starburst synthetic stellar population models. We find an excess of high Hα EW galaxies that are up to 0.3-0.5 dex above the model-predicted Salpeter IMF locus and the Hα EW distribution is much broader (10-500 Å) than can easily be explained by a simple monotonic SFH with a standard Salpeter-slope IMF. Though this discrepancy is somewhat alleviated when it is assumed that there is no relative attenuation difference between stars and nebular lines, the result is robust against observational biases, and no single IMF (I.e. non-Salpeter slope) can reproduce the data. We show using both spectral stacking and Monte Carlo simulations that starbursts cannot explain the EW distribution. We investigate other physical mechanisms including models with variations in stellar rotation, binary star evolution, metallicity and the IMF upper-mass cut-off. IMF variations and/or highly rotating extreme metal-poor stars (Z ˜ 0.1 Z⊙) with binary interactions are the most plausible explanations for our data. If the IMF varies, then the highest Hα EWs would require very shallow slopes (Γ > -1.0) with no one slope able to reproduce the data. Thus, the IMF would have to vary stochastically. We conclude that the stellar populations at z ≳ 2 show distinct differences from local populations and there is no simple physical model to explain the large variation in Hα EWs at z ˜ 2.

Language competition in a population of migrating agents.

PubMed

Lipowska, Dorota; Lipowski, Adam

2017-05-01

Influencing various aspects of human activity, migration is associated also with language formation. To examine the mutual interaction of these processes, we study a Naming Game with migrating agents. The dynamics of the model leads to formation of low-mobility clusters, which turns out to break the symmetry of the model: although the Naming Game remains symmetric, low-mobility languages are favored. High-mobility languages are gradually eliminated from the system, and the dynamics of language formation considerably slows down. Our model is too simple to explain in detail language competition of migrating human communities, but it certainly shows that languages of settlers are favored over nomadic ones.

The effects of sunspots on solar irradiance

NASA Technical Reports Server (NTRS)

Hudson, H. S.; Silva, S.; Woodard, M.; Willson, R. C.

1982-01-01

It is pointed out that the darkness of a sunspot on the visible hemisphere of the sun will reduce the solar irradiance on the earth. Approaches are discussed for obtaining a crude estimate of the irradiance deficit produced by sunspots and of the total luminosity reduction for the whole global population of sunspots. Attention is given to a photometric sunspot index, a global measure of spot flux deficit, and models for the compensating flux excess. A model is shown for extrapolating visible-hemisphere spot areas to the invisible hemisphere. As an illustration, this extrapolation is used to calculate a very simple model for the reradiation necessary to balance the flux deficit.

Language competition in a population of migrating agents

NASA Astrophysics Data System (ADS)

Lipowska, Dorota; Lipowski, Adam

2017-05-01

Influencing various aspects of human activity, migration is associated also with language formation. To examine the mutual interaction of these processes, we study a Naming Game with migrating agents. The dynamics of the model leads to formation of low-mobility clusters, which turns out to break the symmetry of the model: although the Naming Game remains symmetric, low-mobility languages are favored. High-mobility languages are gradually eliminated from the system, and the dynamics of language formation considerably slows down. Our model is too simple to explain in detail language competition of migrating human communities, but it certainly shows that languages of settlers are favored over nomadic ones.

Using Massive Star Clusters in Merger Remnants To Provide Reference Colors of Intermediate-Age Stellar Populations

NASA Astrophysics Data System (ADS)

Goudfrooij, Paul

2009-07-01

Much current research in cosmology and galaxy formation relies on an accurate interpretation of colors of galaxies in terms of their evolutionary state, i.e., in terms of ages and metallicities. One particularly important topic is the ability to identify early-type galaxies at "intermediate" ages { 500 Myr - 5 Gyr}, i.e., the period between the end of star formation and half the age of the universe. Currently, integrated-light studies must rely on population synthesis models which rest upon spectral libraries of stars in the solar neighborhood. These models have a difficult time correctly incorporating short-lived evolutionary phases such as thermally pulsing AGB stars, which produce up to 80% of the flux in the near-IR in this age range. Furthermore, intermediate-age star clusters in the Local Group do not represent proper templates against which to calibrate population synthesis models in this age range, because their masses are too low to render the effect of stochastic fluctuations due to the number of bright RGB and AGB stars negligible. As a consequence, current population synthesis models have trouble reconciling the evolutionary state of high-redshift galaxies from optical versus near-IR colors. We propose a simple and effective solution to this issue, namely obtaining high-quality EMPIRICAL colors of massive globular clusters in galaxy merger remnants which span this important age range. These colors should serve as relevant references, both to identify intermediate-age objects in the local and distant universe and as calibrators for population synthesis modellers.

Do You See What I See? Exploring the Consequences of Luminosity Limits in Black Hole–Galaxy Evolution Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jones, Mackenzie L.; Hickox, Ryan C.; DiPompeo, Michael A.

In studies of the connection between active galactic nuclei (AGNs) and their host galaxies, there is widespread disagreement on some key aspects of the connection. These disagreements largely stem from a lack of understanding of the nature of the full underlying AGN population. Recent attempts to probe this connection utilize both observations and simulations to correct for a missed population, but presently are limited by intrinsic biases and complicated models. We take a simple simulation for galaxy evolution and add a new prescription for AGN activity to connect galaxy growth to dark matter halo properties and AGN activity to starmore » formation. We explicitly model selection effects to produce an “observed” AGN population for comparison with observations and empirically motivated models of the local universe. This allows us to bypass the difficulties inherent in models that attempt to infer the AGN population by inverting selection effects. We investigate the impact of selecting AGNs based on thresholds in luminosity or Eddington ratio on the “observed” AGN population. By limiting our model AGN sample in luminosity, we are able to recreate the observed local AGN luminosity function and specific star formation-stellar mass distribution, and show that using an Eddington ratio threshold introduces less bias into the sample by selecting the full range of growing black holes, despite the challenge of selecting low-mass black holes. We find that selecting AGNs using these various thresholds yield samples with different AGN host galaxy properties.« less

Population dynamics in the presence of quasispecies effects and changing environments

NASA Astrophysics Data System (ADS)

Forster, Robert Burke

2006-12-01

This thesis explores how natural selection acts on organisms such as viruses that have either highly error-prone reproduction or face variable environmental conditions or both. By modeling population dynamics under these conditions, we gain a better understanding of the selective forces at work, both in our simulations and hopefully also in real organisms. With an understanding of the important factors in natural selection we can forecast not only the immediate fate of an existing population but also in what directions such a population might evolve in the future. We demonstrate that the concept of a quasispecies is relevant to evolution in a neutral fitness landscape. Motivated by RNA viruses such as HIV, we use RNA secondary structure as our model system and find that quasispecies effects arise both rapidly and in realistically small populations. We discover that the evolutionary effects of neutral drift, punctuated equilibrium and the selection for mutational robustness extend to the concept of a quasispecies. In our study of periodic environments, we consider the tradeoffs faced by quasispecies in adapting to environmental change. We develop an analytical model to predict whether evolution favors short-term or long-term adaptation and validate our model through simulation. Our results bear directly on the population dynamics of viruses such as West Nile that alternate between two host species. More generally, we discover that a selective pressure exists under these conditions to fuse or split genes with complementary environmental functions. Lastly, we study the general effects of frequency-dependent selection on two strains competing in a periodic environment. Under very general assumptions, we prove that stable coexistence rather than extinction is the likely outcome. The population dynamics of this system may be as simple as stable equilibrium or as complex as deterministic chaos.

Dark matter and MOND dynamical models of the massive spiral galaxy NGC 2841

NASA Astrophysics Data System (ADS)

Samurović, S.; Vudragović, A.; Jovanović, M.

2015-08-01

We study dynamical models of the massive spiral galaxy NGC 2841 using both the Newtonian models with Navarro-Frenk-White (NFW) and isothermal dark haloes, as well as various MOND (MOdified Newtonian Dynamics) models. We use the observations coming from several publicly available data bases: we use radio data, near-infrared photometry as well as spectroscopic observations. In our models, we find that both tested Newtonian dark matter approaches can successfully fit the observed rotational curve of NGC 2841. The three tested MOND models (standard, simple and, for the first time applied to another spiral galaxy than the Milky Way, Bekenstein's toy model) provide fits of the observed rotational curve with various degrees of success: the best result was obtained with the standard MOND model. For both approaches, Newtonian and MOND, the values of the mass-to-light ratios of the bulge are consistent with the predictions from the stellar population synthesis (SPS) based on the Salpeter initial mass function (IMF). Also, for Newtonian and simple and standard MOND models, the estimated stellar mass-to-light ratios of the disc agree with the predictions from the SPS models based on the Kroupa IMF, whereas the toy MOND model provides too low a value of the stellar mass-to-light ratio, incompatible with the predictions of the tested SPS models. In all our MOND models, we vary the distance to NGC 2841, and our best-fitting standard and toy models use the values higher than the Cepheid-based distance to the galaxy NGC 2841, and the best-fitting simple MOND model is based on the lower value of the distance. The best-fitting NFW model is inconsistent with the predictions of the Λ cold dark matter cosmology, because the inferred concentration index is too high for the established virial mass.

ECOLOGICAL THEORY. A general consumer-resource population model.

PubMed

Lafferty, Kevin D; DeLeo, Giulio; Briggs, Cheryl J; Dobson, Andrew P; Gross, Thilo; Kuris, Armand M

2015-08-21

Food-web dynamics arise from predator-prey, parasite-host, and herbivore-plant interactions. Models for such interactions include up to three consumer activity states (questing, attacking, consuming) and up to four resource response states (susceptible, exposed, ingested, resistant). Articulating these states into a general model allows for dissecting, comparing, and deriving consumer-resource models. We specify this general model for 11 generic consumer strategies that group mathematically into predators, parasites, and micropredators and then derive conditions for consumer success, including a universal saturating functional response. We further show how to use this framework to create simple models with a common mathematical lineage and transparent assumptions. Underlying assumptions, missing elements, and composite parameters are revealed when classic consumer-resource models are derived from the general model. Copyright © 2015, American Association for the Advancement of Science.

A Predictive Model for Readmissions Among Medicare Patients in a California Hospital.

PubMed

Duncan, Ian; Huynh, Nhan

2017-11-17

Predictive models for hospital readmission rates are in high demand because of the Centers for Medicare & Medicaid Services (CMS) Hospital Readmission Reduction Program (HRRP). The LACE index is one of the most popular predictive tools among hospitals in the United States. The LACE index is a simple tool with 4 parameters: Length of stay, Acuity of admission, Comorbidity, and Emergency visits in the previous 6 months. The authors applied logistic regression to develop a predictive model for a medium-sized not-for-profit community hospital in California using patient-level data with more specific patient information (including 13 explanatory variables). Specifically, the logistic regression is applied to 2 populations: a general population including all patients and the specific group of patients targeted by the CMS penalty (characterized as ages 65 or older with select conditions). The 2 resulting logistic regression models have a higher sensitivity rate compared to the sensitivity of the LACE index. The C statistic values of the model applied to both populations demonstrate moderate levels of predictive power. The authors also build an economic model to demonstrate the potential financial impact of the use of the model for targeting high-risk patients in a sample hospital and demonstrate that, on balance, whether the hospital gains or loses from reducing readmissions depends on its margin and the extent of its readmission penalties.

Magnetopause modeling - Flux transfer events and magnetosheath quasi-trapped distributions

NASA Technical Reports Server (NTRS)

Speiser, T. W.; Williams, D. J.

1982-01-01

Three-dimensional distribution functions for energetic ions are studied numerically in the magnetosphere, through the magnetopause, and in the magnetosheath using a simple one-dimensional quasi-static model and ISEE 1 magnetopause crossing data for November 10, 1977. Quasi-trapped populations in the magnetosheath observed near flux transfer events (FTEs) are investigated, and it is shown that the population in the sheath appears to sandwich the FTE distributions. These quasi-trapped distributions are due to slow, large pitch angle, outward moving particles left behind by the outward rush of the ions more field-aligned at the time the flux was opened. It is found that sheath convective flows can map along the connected flux tube without drastically changing the distribution function, and results suggest that localized tangential fields above the upper limit may exist.

Partial differential equation techniques for analysing animal movement: A comparison of different methods.

PubMed

Wang, Yi-Shan; Potts, Jonathan R

2017-03-07

Recent advances in animal tracking have allowed us to uncover the drivers of movement in unprecedented detail. This has enabled modellers to construct ever more realistic models of animal movement, which aid in uncovering detailed patterns of space use in animal populations. Partial differential equations (PDEs) provide a popular tool for mathematically analysing such models. However, their construction often relies on simplifying assumptions which may greatly affect the model outcomes. Here, we analyse the effect of various PDE approximations on the analysis of some simple movement models, including a biased random walk, central-place foraging processes and movement in heterogeneous landscapes. Perhaps the most commonly-used PDE method dates back to a seminal paper of Patlak from 1953. However, our results show that this can be a very poor approximation in even quite simple models. On the other hand, more recent methods, based on transport equation formalisms, can provide more accurate results, as long as the kernel describing the animal's movement is sufficiently smooth. When the movement kernel is not smooth, we show that both the older and newer methods can lead to quantitatively misleading results. Our detailed analysis will aid future researchers in the appropriate choice of PDE approximation for analysing models of animal movement. Copyright © 2017 Elsevier Ltd. All rights reserved.

A First-Principles Model of Early Evolution: Emergence of Gene Families, Species, and Preferred Protein Folds

PubMed Central

Zeldovich, Konstantin B; Chen, Peiqiu; Shakhnovich, Boris E; Shakhnovich, Eugene I

2007-01-01

In this work we develop a microscopic physical model of early evolution where phenotype—organism life expectancy—is directly related to genotype—the stability of its proteins in their native conformations—which can be determined exactly in the model. Simulating the model on a computer, we consistently observe the “Big Bang” scenario whereby exponential population growth ensues as soon as favorable sequence–structure combinations (precursors of stable proteins) are discovered. Upon that, random diversity of the structural space abruptly collapses into a small set of preferred proteins. We observe that protein folds remain stable and abundant in the population at timescales much greater than mutation or organism lifetime, and the distribution of the lifetimes of dominant folds in a population approximately follows a power law. The separation of evolutionary timescales between discovery of new folds and generation of new sequences gives rise to emergence of protein families and superfamilies whose sizes are power-law distributed, closely matching the same distributions for real proteins. On the population level we observe emergence of species—subpopulations that carry similar genomes. Further, we present a simple theory that relates stability of evolving proteins to the sizes of emerging genomes. Together, these results provide a microscopic first-principles picture of how first-gene families developed in the course of early evolution. PMID:17630830

A first-principles model of early evolution: emergence of gene families, species, and preferred protein folds.

PubMed

Zeldovich, Konstantin B; Chen, Peiqiu; Shakhnovich, Boris E; Shakhnovich, Eugene I

2007-07-01

In this work we develop a microscopic physical model of early evolution where phenotype--organism life expectancy--is directly related to genotype--the stability of its proteins in their native conformations-which can be determined exactly in the model. Simulating the model on a computer, we consistently observe the "Big Bang" scenario whereby exponential population growth ensues as soon as favorable sequence-structure combinations (precursors of stable proteins) are discovered. Upon that, random diversity of the structural space abruptly collapses into a small set of preferred proteins. We observe that protein folds remain stable and abundant in the population at timescales much greater than mutation or organism lifetime, and the distribution of the lifetimes of dominant folds in a population approximately follows a power law. The separation of evolutionary timescales between discovery of new folds and generation of new sequences gives rise to emergence of protein families and superfamilies whose sizes are power-law distributed, closely matching the same distributions for real proteins. On the population level we observe emergence of species--subpopulations that carry similar genomes. Further, we present a simple theory that relates stability of evolving proteins to the sizes of emerging genomes. Together, these results provide a microscopic first-principles picture of how first-gene families developed in the course of early evolution.

Inequality measures for wealth distribution: Population vs individuals perspective

NASA Astrophysics Data System (ADS)

Pascoal, R.; Rocha, H.

2018-02-01

Economic inequality is, nowadays, frequently perceived as following a growing trend with impact on political and religious agendas. However, there is a wide range of inequality measures, each of which pointing to a possibly different degree of inequality. Furthermore, regardless of the measure used, it only acknowledges the momentary population inequality, failing to capture the individuals evolution over time. In this paper, several inequality measures were analyzed in order to compare the typical single time instant degree of wealth inequality (population perspective) to the one obtained from the individuals' wealth mean over several time instants (individuals perspective). The proposed generalization of a simple addictive model, for limited time average of individual's wealth, allows us to verify that the typically used inequality measures for a given snapshot instant of the population significantly overestimate the individuals' wealth inequality over time. Moreover, that is more extreme for the ratios than for the indices analyzed.

Data-poor management of African lion hunting using a relative index of abundance.

PubMed

Edwards, Charles T T; Bunnefeld, Nils; Balme, Guy A; Milner-Gulland, E J

2014-01-07

Sustainable management of terrestrial hunting requires managers to set quotas restricting offtake. This often takes place in the absence of reliable information on the population size, and as a consequence, quotas are set in an arbitrary fashion, leading to population decline and revenue loss. In this investigation, we show how an indirect measure of abundance can be used to set quotas in a sustainable manner, even in the absence of information on population size. Focusing on lion hunting in Africa, we developed a simple algorithm to convert changes in the number of safari days required to kill a lion into a quota for the following year. This was tested against a simulation model of population dynamics, accounting for uncertainties in demography, observation, and implementation. Results showed it to reliably set sustainable quotas despite these uncertainties, providing a robust foundation for the conservation of hunted species.

Simultaneous modeling of habitat suitability, occupancy, and relative abundance: African elephants in Zimbabwe

USGS Publications Warehouse

Martin, Julien; Chamaille-Jammes, Simon; Nichols, James D.; Fritz, Herve; Hines, James E.; Fonnesbeck, Christopher J.; MacKenzie, Darryl I.; Bailey, Larissa L.

2010-01-01

The recent development of statistical models such as dynamic site occupancy models provides the opportunity to address fairly complex management and conservation problems with relatively simple models. However, surprisingly few empirical studies have simultaneously modeled habitat suitability and occupancy status of organisms over large landscapes for management purposes. Joint modeling of these components is particularly important in the context of management of wild populations, as it provides a more coherent framework to investigate the population dynamics of organisms in space and time for the application of management decision tools. We applied such an approach to the study of water hole use by African elephants in Hwange National Park, Zimbabwe. Here we show how such methodology may be implemented and derive estimates of annual transition probabilities among three dry-season states for water holes: (1) unsuitable state (dry water holes with no elephants); (2) suitable state (water hole with water) with low abundance of elephants; and (3) suitable state with high abundance of elephants. We found that annual rainfall and the number of neighboring water holes influenced the transition probabilities among these three states. Because of an increase in elephant densities in the park during the study period, we also found that transition probabilities from low abundance to high abundance states increased over time. The application of the joint habitat–occupancy models provides a coherent framework to examine how habitat suitability and factors that affect habitat suitability influence the distribution and abundance of organisms. We discuss how these simple models can further be used to apply structured decision-making tools in order to derive decisions that are optimal relative to specified management objectives. The modeling framework presented in this paper should be applicable to a wide range of existing data sets and should help to address important ecological, conservation, and management problems that deal with occupancy, relative abundance, and habitat suitability.

Geography and end use drive the diversification of worldwide winter rye populations.

PubMed

Parat, Florence; Schwertfirm, Grit; Rudolph, Ulrike; Miedaner, Thomas; Korzun, Viktor; Bauer, Eva; Schön, Chris-Carolin; Tellier, Aurélien

2016-01-01

To meet the current challenges in human food production, improved understanding of the genetic diversity of crop species that maximizes the selection efficacy in breeding programs is needed. The present study offers new insights into the diversity, genetic structure and demographic history of cultivated rye (Secale cereale L.). We genotyped 620 individuals from 14 global rye populations with a different end use (grain or forage) at 32 genome-wide simple sequence repeat markers. We reveal the relationships among these populations, their sizes and the timing of domestication events using population genetics and model-based inference with approximate Bayesian computation. Our main results demonstrate (i) a high within-population variation and genetic diversity, (ii) an unexpected absence of reduction in diversity with an increasing improvement level and (iii) patterns suggestive of multiple domestication events. We suggest that the main drivers of diversification of winter rye are the end use of rye in two early regions of cultivation: rye forage in the Mediterranean area and grain in northeast Europe. The lower diversity and stronger differentiation of eastern European populations were most likely due to more intensive cultivation and breeding of rye in this region, in contrast to the Mediterranean region where it was considered a secondary crop or even a weed. We discuss the relevance of our results for the management of gene bank resources and the pitfalls of inference methods applied to crop domestication due to violation of model assumptions and model complexity. © 2015 John Wiley & Sons Ltd.

A stochastic model for the probability of malaria extinction by mass drug administration.

PubMed

Pemberton-Ross, Peter; Chitnis, Nakul; Pothin, Emilie; Smith, Thomas A

2017-09-18

Mass drug administration (MDA) has been proposed as an intervention to achieve local extinction of malaria. Although its effect on the reproduction number is short lived, extinction may subsequently occur in a small population due to stochastic fluctuations. This paper examines how the probability of stochastic extinction depends on population size, MDA coverage and the reproduction number under control, R c . A simple compartmental model is developed which is used to compute the probability of extinction using probability generating functions. The expected time to extinction in small populations after MDA for various scenarios in this model is calculated analytically. The results indicate that mass drug administration (Firstly, R c must be sustained at R c  < 1.2 to avoid the rapid re-establishment of infections in the population. Secondly, the MDA must produce effective cure rates of >95% to have a non-negligible probability of successful elimination. Stochastic fluctuations only significantly affect the probability of extinction in populations of about 1000 individuals or less. The expected time to extinction via stochastic fluctuation is less than 10 years only in populations less than about 150 individuals. Clustering of secondary infections and of MDA distribution both contribute positively to the potential probability of success, indicating that MDA would most effectively be administered at the household level. There are very limited circumstances in which MDA will lead to local malaria elimination with a substantial probability.

Sustainability, collapse and oscillations in a simple World-Earth model

NASA Astrophysics Data System (ADS)

Nitzbon, Jan; Heitzig, Jobst; Parlitz, Ulrich

2017-07-01

The Anthropocene is characterized by close interdependencies between the natural Earth system and the global human society, posing novel challenges to model development. Here we present a conceptual model describing the long-term co-evolution of natural and socio-economic subsystems of Earth. While the climate is represented via a global carbon cycle, we use economic concepts to model socio-metabolic flows of biomass and fossil fuels between nature and society. A well-being-dependent parametrization of fertility and mortality governs human population dynamics. Our analysis focuses on assessing possible asymptotic states of the Earth system for a qualitative understanding of its complex dynamics rather than quantitative predictions. Low dimension and simple equations enable a parameter-space analysis allowing us to identify preconditions of several asymptotic states and hence fates of humanity and planet. These include a sustainable co-evolution of nature and society, a global collapse and everlasting oscillations. We consider different scenarios corresponding to different socio-cultural stages of human history. The necessity of accounting for the ‘human factor’ in Earth system models is highlighted by the finding that carbon stocks during the past centuries evolved opposing to what would ‘naturally’ be expected on a planet without humans. The intensity of biomass use and the contribution of ecosystem services to human well-being are found to be crucial determinants of the asymptotic state in a (pre-industrial) biomass-only scenario without capital accumulation. The capitalistic, fossil-based scenario reveals that trajectories with fundamentally different asymptotic states might still be almost indistinguishable during even a centuries-long transient phase. Given current human population levels, our study also supports the claim that besides reducing the global demand for energy, only the extensive use of renewable energies may pave the way into a sustainable future.

Mid-infrared Integrated-light Photometry Of LMC Star Clusters

NASA Astrophysics Data System (ADS)

Pessev, Peter; Goudfrooij, P.; Puzia, T.; Chandar, R.

2008-03-01

Massive star clusters (Galactic Globular Clusters and Populous Clusters in the Magellanic Clouds) are the best available approximation of Simple Stellar Populations (SSPs). Since the stellar populations in these nearby objects are studied in details, they provide fundamental age/metallicity templates for interpretation of the galaxy properties, testing and calibration of the SSP Models. Magellanic Cloud clusters are particularly important since they populate a region of the age/metallicity parameter space that is not easily accessible in our Galaxy. We present the first Mid-IR integrated-light measurements for six LMC clusters based on our Spitzer IRAC imaging program. Since we are targeting a specific group of intermediate-age clusters, our imaging goes deeper compared to SAGE-LMC survey data. We present a literature compilation of clusters' properties along with multi-wavelength integrated light photometry database spanning from the optical (Johnson U band) to the Mid-IR (IRAC Channel 4). This data provides an important empirical baseline for the interpretation of galaxy colors in the Mid-IR (especially high-z objects whose integrated-light is dominated by TP-AGB stars emission). It is also a valuable tool to check the SSP model predictions in the intermediate-age regime and provides calibration data for the next generation of SSP models.

Evolution of social versus individual learning in a subdivided population revisited: comparative analysis of three coexistence mechanisms using the inclusive-fitness method.

PubMed

Kobayashi, Yutaka; Ohtsuki, Hisashi

2014-03-01

Learning abilities are categorized into social (learning from others) and individual learning (learning on one's own). Despite the typically higher cost of individual learning, there are mechanisms that allow stable coexistence of both learning modes in a single population. In this paper, we investigate by means of mathematical modeling how the effect of spatial structure on evolutionary outcomes of pure social and individual learning strategies depends on the mechanisms for coexistence. We model a spatially structured population based on the infinite-island framework and consider three scenarios that differ in coexistence mechanisms. Using the inclusive-fitness method, we derive the equilibrium frequency of social learners and the genetic load of social learning (defined as average fecundity reduction caused by the presence of social learning) in terms of some summary statistics, such as relatedness, for each of the three scenarios and compare the results. This comparative analysis not only reconciles previous models that made contradictory predictions as to the effect of spatial structure on the equilibrium frequency of social learners but also derives a simple mathematical rule that determines the sign of the genetic load (i.e. whether or not social learning contributes to the mean fecundity of the population). Copyright © 2013 Elsevier Inc. All rights reserved.

Emerging category representation in the visual forebrain hierarchy of pigeons (Columba livia).

PubMed

Azizi, Amir Hossein; Pusch, Roland; Koenen, Charlotte; Klatt, Sebastian; Bröcker, Franziska; Thiele, Samuel; Kellermann, Janosch; Güntürkün, Onur; Cheng, Sen

2018-06-06

Recognizing and categorizing visual stimuli are cognitive functions vital for survival, and an important feature of visual systems in primates as well as in birds. Visual stimuli are processed along the ventral visual pathway. At every stage in the hierarchy, neurons respond selectively to more complex features, transforming the population representation of the stimuli. It is therefore easier to read-out category information in higher visual areas. While explicit category representations have been observed in the primate brain, less is known on equivalent processes in the avian brain. Even though their brain anatomies are radically different, it has been hypothesized that visual object representations are comparable across mammals and birds. In the present study, we investigated category representations in the pigeon visual forebrain using recordings from single cells responding to photographs of real-world objects. Using a linear classifier, we found that the population activity in the visual associative area mesopallium ventrolaterale (MVL) distinguishes between animate and inanimate objects, although this distinction is not required by the task. By contrast, a population of cells in the entopallium, a region that is lower in the hierarchy of visual areas and that is related to the primate extrastriate cortex, lacked this information. A model that pools responses of simple cells, which function as edge detectors, can account for the animate vs. inanimate categorization in the MVL, but performance in the model is based on different features than in MVL. Therefore, processing in MVL cells is very likely more abstract than simple computations on the output of edge detectors. Copyright © 2018. Published by Elsevier B.V.

Long-Distance Dispersal Shaped Patterns of Human Genetic Diversity in Eurasia

PubMed Central

Alves, Isabel; Arenas, Miguel; Currat, Mathias; Sramkova Hanulova, Anna; Sousa, Vitor C.; Ray, Nicolas; Excoffier, Laurent

2016-01-01

Most previous attempts at reconstructing the past history of human populations did not explicitly take geography into account or considered very simple scenarios of migration and ignored environmental information. However, it is likely that the last glacial maximum (LGM) affected the demography and the range of many species, including our own. Moreover, long-distance dispersal (LDD) may have been an important component of human migrations, allowing fast colonization of new territories and preserving high levels of genetic diversity. Here, we use a high-quality microsatellite data set genotyped in 22 populations to estimate the posterior probabilities of several scenarios for the settlement of the Old World by modern humans. We considered models ranging from a simple spatial expansion to others including LDD and a LGM-induced range contraction, as well as Neolithic demographic expansions. We find that scenarios with LDD are much better supported by data than models without LDD. Nevertheless, we show evidence that LDD events to empty habitats were strongly prevented during the settlement of Eurasia. This unexpected absence of LDD ahead of the colonization wave front could have been caused by an Allee effect, either due to intrinsic causes such as an inbreeding depression built during the expansion or due to extrinsic causes such as direct competition with archaic humans. Overall, our results suggest only a relatively limited effect of the LGM contraction on current patterns of human diversity. This is in clear contrast with the major role of LDD migrations, which have potentially contributed to the intermingled genetic structure of Eurasian populations. PMID:26637555

Multiple Imputation in Two-Stage Cluster Samples Using The Weighted Finite Population Bayesian Bootstrap.

PubMed

Zhou, Hanzhi; Elliott, Michael R; Raghunathan, Trivellore E

2016-06-01

Multistage sampling is often employed in survey samples for cost and convenience. However, accounting for clustering features when generating datasets for multiple imputation is a nontrivial task, particularly when, as is often the case, cluster sampling is accompanied by unequal probabilities of selection, necessitating case weights. Thus, multiple imputation often ignores complex sample designs and assumes simple random sampling when generating imputations, even though failing to account for complex sample design features is known to yield biased estimates and confidence intervals that have incorrect nominal coverage. In this article, we extend a recently developed, weighted, finite-population Bayesian bootstrap procedure to generate synthetic populations conditional on complex sample design data that can be treated as simple random samples at the imputation stage, obviating the need to directly model design features for imputation. We develop two forms of this method: one where the probabilities of selection are known at the first and second stages of the design, and the other, more common in public use files, where only the final weight based on the product of the two probabilities is known. We show that this method has advantages in terms of bias, mean square error, and coverage properties over methods where sample designs are ignored, with little loss in efficiency, even when compared with correct fully parametric models. An application is made using the National Automotive Sampling System Crashworthiness Data System, a multistage, unequal probability sample of U.S. passenger vehicle crashes, which suffers from a substantial amount of missing data in "Delta-V," a key crash severity measure.

Multiple Imputation in Two-Stage Cluster Samples Using The Weighted Finite Population Bayesian Bootstrap

PubMed Central

Zhou, Hanzhi; Elliott, Michael R.; Raghunathan, Trivellore E.

2017-01-01

Multistage sampling is often employed in survey samples for cost and convenience. However, accounting for clustering features when generating datasets for multiple imputation is a nontrivial task, particularly when, as is often the case, cluster sampling is accompanied by unequal probabilities of selection, necessitating case weights. Thus, multiple imputation often ignores complex sample designs and assumes simple random sampling when generating imputations, even though failing to account for complex sample design features is known to yield biased estimates and confidence intervals that have incorrect nominal coverage. In this article, we extend a recently developed, weighted, finite-population Bayesian bootstrap procedure to generate synthetic populations conditional on complex sample design data that can be treated as simple random samples at the imputation stage, obviating the need to directly model design features for imputation. We develop two forms of this method: one where the probabilities of selection are known at the first and second stages of the design, and the other, more common in public use files, where only the final weight based on the product of the two probabilities is known. We show that this method has advantages in terms of bias, mean square error, and coverage properties over methods where sample designs are ignored, with little loss in efficiency, even when compared with correct fully parametric models. An application is made using the National Automotive Sampling System Crashworthiness Data System, a multistage, unequal probability sample of U.S. passenger vehicle crashes, which suffers from a substantial amount of missing data in “Delta-V,” a key crash severity measure. PMID:29226161

A Population Genetic Signal of Polygenic Adaptation

PubMed Central

Berg, Jeremy J.; Coop, Graham

2014-01-01

Adaptation in response to selection on polygenic phenotypes may occur via subtle allele frequencies shifts at many loci. Current population genomic techniques are not well posed to identify such signals. In the past decade, detailed knowledge about the specific loci underlying polygenic traits has begun to emerge from genome-wide association studies (GWAS). Here we combine this knowledge from GWAS with robust population genetic modeling to identify traits that may have been influenced by local adaptation. We exploit the fact that GWAS provide an estimate of the additive effect size of many loci to estimate the mean additive genetic value for a given phenotype across many populations as simple weighted sums of allele frequencies. We use a general model of neutral genetic value drift for an arbitrary number of populations with an arbitrary relatedness structure. Based on this model, we develop methods for detecting unusually strong correlations between genetic values and specific environmental variables, as well as a generalization of comparisons to test for over-dispersion of genetic values among populations. Finally we lay out a framework to identify the individual populations or groups of populations that contribute to the signal of overdispersion. These tests have considerably greater power than their single locus equivalents due to the fact that they look for positive covariance between like effect alleles, and also significantly outperform methods that do not account for population structure. We apply our tests to the Human Genome Diversity Panel (HGDP) dataset using GWAS data for height, skin pigmentation, type 2 diabetes, body mass index, and two inflammatory bowel disease datasets. This analysis uncovers a number of putative signals of local adaptation, and we discuss the biological interpretation and caveats of these results. PMID:25102153

A primer on the study of transitory dynamics in ecological series using the scale-dependent correlation analysis.

PubMed

Rodríguez-Arias, Miquel Angel; Rodó, Xavier

2004-03-01

Here we describe a practical, step-by-step primer to scale-dependent correlation (SDC) analysis. The analysis of transitory processes is an important but often neglected topic in ecological studies because only a few statistical techniques appear to detect temporary features accurately enough. We introduce here the SDC analysis, a statistical and graphical method to study transitory processes at any temporal or spatial scale. SDC analysis, thanks to the combination of conventional procedures and simple well-known statistical techniques, becomes an improved time-domain analogue of wavelet analysis. We use several simple synthetic series to describe the method, a more complex example, full of transitory features, to compare SDC and wavelet analysis, and finally we analyze some selected ecological series to illustrate the methodology. The SDC analysis of time series of copepod abundances in the North Sea indicates that ENSO primarily is the main climatic driver of short-term changes in population dynamics. SDC also uncovers some long-term, unexpected features in the population. Similarly, the SDC analysis of Nicholson's blowflies data locates where the proposed models fail and provides new insights about the mechanism that drives the apparent vanishing of the population cycle during the second half of the series.

Rapid contemporary evolution and clonal food web dynamics

PubMed Central

Jones, Laura E.; Becks, Lutz; Ellner, Stephen P.; Hairston, Nelson G.; Yoshida, Takehito; Fussmann, Gregor F.

2009-01-01

Character evolution that affects ecological community interactions often occurs contemporaneously with temporal changes in population size, potentially altering the very nature of those dynamics. Such eco-evolutionary processes may be most readily explored in systems with short generations and simple genetics. Asexual and cyclically parthenogenetic organisms such as microalgae, cladocerans and rotifers, which frequently dominate freshwater plankton communities, meet these requirements. Multiple clonal lines can coexist within each species over extended periods, until either fixation occurs or a sexual phase reshuffles the genetic material. When clones differ in traits affecting interspecific interactions, within-species clonal dynamics can have major effects on the population dynamics. We first consider a simple predator–prey system with two prey genotypes, parametrized with data from a well-studied experimental system, and explore how the extent of differences in defence against predation within the prey population determine dynamic stability versus instability of the system. We then explore how increased potential for evolution affects the community dynamics in a more general community model with multiple predator and multiple prey genotypes. These examples illustrate how microevolutionary ‘details’ that enhance or limit the potential for heritable phenotypic change can have significant effects on contemporaneous community-level dynamics and the persistence and coexistence of species. PMID:19414472

Evaluating Spatial Interaction Models for Regional Mobility in Sub-Saharan Africa

PubMed Central

Wesolowski, Amy; O’Meara, Wendy Prudhomme; Eagle, Nathan; Tatem, Andrew J.; Buckee, Caroline O.

2015-01-01

Simple spatial interaction models of human mobility based on physical laws have been used extensively in the social, biological, and physical sciences, and in the study of the human dynamics underlying the spread of disease. Recent analyses of commuting patterns and travel behavior in high-income countries have led to the suggestion that these models are highly generalizable, and as a result, gravity and radiation models have become standard tools for describing population mobility dynamics for infectious disease epidemiology. Communities in Sub-Saharan Africa may not conform to these models, however; physical accessibility, availability of transport, and cost of travel between locations may be variable and severely constrained compared to high-income settings, informal labor movements rather than regular commuting patterns are often the norm, and the rise of mega-cities across the continent has important implications for travel between rural and urban areas. Here, we first review how infectious disease frameworks incorporate human mobility on different spatial scales and use anonymous mobile phone data from nearly 15 million individuals to analyze the spatiotemporal dynamics of the Kenyan population. We find that gravity and radiation models fail in systematic ways to capture human mobility measured by mobile phones; both severely overestimate the spatial spread of travel and perform poorly in rural areas, but each exhibits different characteristic patterns of failure with respect to routes and volumes of travel. Thus, infectious disease frameworks that rely on spatial interaction models are likely to misrepresent population dynamics important for the spread of disease in many African populations. PMID:26158274

A Simple Model of Population Vulnerability during Crisis Relocation.

DTIC Science & Technology

1983-01-01

NUMBERS 1801 N. Beauregard Street Work Unit 4112C Alexandria, VA 22311 11. CONTROLLING OFFICE NAME AND ADDRESS 12. REPORT DATE Federal Emergency Management... control of movement within the risk areas can be achieved, the time of exposure to attack while in transit can be minimized. Host Areas The prime...highways can be controlled , then flow can be maintained along them with a reasonable degree of confidence. The capacity of an interstate highway for

The prevalence of incidental simple ovarian cysts >or= 3 cm detected by transvaginal sonography in early pregnancy.

PubMed

Glanc, Phyllis; Brofman, Nicole; Salem, Shia; Kornecki, Anat; Abrams, Jason; Farine, Dan

2007-06-01

To determine the prevalence of simple ovarian cysts of >or= 3 cm diameter detected by transvaginal sonography (TVS) in a population of asymptomatic women in early pregnancy. We conducted a retrospective review of 10,830 consecutive women presenting prior to 14 weeks' gestational age (GA) for early dating TVS. The records of all women with simple cysts >or= 3 cm in diameter were included. The study population was divided into five groups by GA: >or= 6 weeks; 6.1-8 weeks; 8.1-10 weeks; 10.1-12 weeks; and 12.1-14 weeks. A simple cyst >or= 3 cm in diameter was present in 4.9% of women at >or= 6 weeks' gestation, in 5.1% between 6.1 and 8 weeks, in 5.3% between 8.1 and 10 weeks, in 3.2% between 10.1. and 12 weeks, and in 1.5% between 12 and 14 weeks. Overall, a simple cyst >or= 3 cm was present in 516 women (4.8%). Prior to 10 weeks, 5.1% had simple cysts >or= 3 cm, dropping to 2.7% after 10 weeks, a statistically significant decrease (P<0.0001). Between 10.1 weeks and 12 weeks, the prevalence dropped to 3.2%, and then to 1.5% in the 12.1-14 week group. This investigation provides reference data on the prevalence of detecting simple ovarian cysts >or= 3 cm by TVS in an asymptomatic early pregnancy population. A progressive decline in the frequency of detecting simple ovarian cysts >or= 3 cm begins after 10 weeks' gestational age.

Computer based experimental studies of the Fry method of strain analysis on 2- and 3- dimensional grain populations

DOE Office of Scientific and Technical Information (OSTI.GOV)

Longiaru, S.; Bhattacharyya, T.

1985-01-01

Inherent in Fry's (1979) all-object separation method of strain analysis are the subtle conditions that 1) the grains or phenocrysts being counted are of equal diameter and 2) that the true centers of such grains lie within the plane of measurement. When such conditions are met, the technique yields accurate, easily interpreted voids within all-object separation (AOS) plots for both deformed and non-deformed populations. Natural grain or phenocryst populations generally do not conform to these limitation and practical application of the technique from either a cut rock surface or thin section often yields diffuse patterns that are not easily interpreted.more » The authors examine the effect of grain size variation and grain/matrix ratio on AOS diagrams developed from computer generated spherical grain populations constructed in both two and three dimensions. They employ a random number generator and simple fitting algorithm to develop grain populations with known statistical parameters. Such control allows for the modeling of many types of natural grain size populations such as fluvial sandstones, porphyritic ash flow tuffs, augen gneisses, etc. They show that significant grain size variation in a two dimensional population contributes substantial noise in to the AOS diagram and that an additional level of noise is encountered when dealing with slices through populations modeled in three dimensions. Some of this noise can be eliminated by rigorous sampling of only subsets of the total grain population.« less

Can simple rules control development of a pioneer vertebrate neuronal network generating behavior?

PubMed

Roberts, Alan; Conte, Deborah; Hull, Mike; Merrison-Hort, Robert; al Azad, Abul Kalam; Buhl, Edgar; Borisyuk, Roman; Soffe, Stephen R

2014-01-08

How do the pioneer networks in the axial core of the vertebrate nervous system first develop? Fundamental to understanding any full-scale neuronal network is knowledge of the constituent neurons, their properties, synaptic interconnections, and normal activity. Our novel strategy uses basic developmental rules to generate model networks that retain individual neuron and synapse resolution and are capable of reproducing correct, whole animal responses. We apply our developmental strategy to young Xenopus tadpoles, whose brainstem and spinal cord share a core vertebrate plan, but at a tractable complexity. Following detailed anatomical and physiological measurements to complete a descriptive library of each type of spinal neuron, we build models of their axon growth controlled by simple chemical gradients and physical barriers. By adding dendrites and allowing probabilistic formation of synaptic connections, we reconstruct network connectivity among up to 2000 neurons. When the resulting "network" is populated by model neurons and synapses, with properties based on physiology, it can respond to sensory stimulation by mimicking tadpole swimming behavior. This functioning model represents the most complete reconstruction of a vertebrate neuronal network that can reproduce the complex, rhythmic behavior of a whole animal. The findings validate our novel developmental strategy for generating realistic networks with individual neuron- and synapse-level resolution. We use it to demonstrate how early functional neuronal connectivity and behavior may in life result from simple developmental "rules," which lay out a scaffold for the vertebrate CNS without specific neuron-to-neuron recognition.

Evolution in leaps: The punctuated accumulation and loss of cultural innovations

PubMed Central

Kolodny, Oren; Creanza, Nicole; Feldman, Marcus W.

2015-01-01

Archaeological accounts of cultural change reveal a fundamental conflict: Some suggest that change is gradual, accelerating over time, whereas others indicate that it is punctuated, with long periods of stasis interspersed by sudden gains or losses of multiple traits. Existing models of cultural evolution, inspired by models of genetic evolution, lend support to the former and do not generate trajectories that include large-scale punctuated change. We propose a simple model that can give rise to both exponential and punctuated patterns of gain and loss of cultural traits. In it, cultural innovation comprises several realistic interdependent processes that occur at different rates. The model also takes into account two properties intrinsic to cultural evolution: the differential distribution of traits among social groups and the impact of environmental change. In our model, a population may be subdivided into groups with different cultural repertoires leading to increased susceptibility to cultural loss, whereas environmental change may lead to rapid loss of traits that are not useful in a new environment. Taken together, our results suggest the usefulness of a concept of an effective cultural population size. PMID:26598675

Evolution in leaps: The punctuated accumulation and loss of cultural innovations.

PubMed

Kolodny, Oren; Creanza, Nicole; Feldman, Marcus W

2015-12-08

Archaeological accounts of cultural change reveal a fundamental conflict: Some suggest that change is gradual, accelerating over time, whereas others indicate that it is punctuated, with long periods of stasis interspersed by sudden gains or losses of multiple traits. Existing models of cultural evolution, inspired by models of genetic evolution, lend support to the former and do not generate trajectories that include large-scale punctuated change. We propose a simple model that can give rise to both exponential and punctuated patterns of gain and loss of cultural traits. In it, cultural innovation comprises several realistic interdependent processes that occur at different rates. The model also takes into account two properties intrinsic to cultural evolution: the differential distribution of traits among social groups and the impact of environmental change. In our model, a population may be subdivided into groups with different cultural repertoires leading to increased susceptibility to cultural loss, whereas environmental change may lead to rapid loss of traits that are not useful in a new environment. Taken together, our results suggest the usefulness of a concept of an effective cultural population size.

Mobile elements reveal small population size in the ancient ancestors of Homo sapiens.

PubMed

Huff, Chad D; Xing, Jinchuan; Rogers, Alan R; Witherspoon, David; Jorde, Lynn B

2010-02-02

The genealogies of different genetic loci vary in depth. The deeper the genealogy, the greater the chance that it will include a rare event, such as the insertion of a mobile element. Therefore, the genealogy of a region that contains a mobile element is on average older than that of the rest of the genome. In a simple demographic model, the expected time to most recent common ancestor (TMRCA) is doubled if a rare insertion is present. We test this expectation by examining single nucleotide polymorphisms around polymorphic Alu insertions from two completely sequenced human genomes. The estimated TMRCA for regions containing a polymorphic insertion is two times larger than the genomic average (P < <10(-30)), as predicted. Because genealogies that contain polymorphic mobile elements are old, they are shaped largely by the forces of ancient population history and are insensitive to recent demographic events, such as bottlenecks and expansions. Remarkably, the information in just two human DNA sequences provides substantial information about ancient human population size. By comparing the likelihood of various demographic models, we estimate that the effective population size of human ancestors living before 1.2 million years ago was 18,500, and we can reject all models where the ancient effective population size was larger than 26,000. This result implies an unusually small population for a species spread across the entire Old World, particularly in light of the effective population sizes of chimpanzees (21,000) and gorillas (25,000), which each inhabit only one part of a single continent.

AORTIC COARCTATION: RECENT DEVELOPMENTS IN EXPERIMENTAL AND COMPUTATIONAL METHODS TO ASSESS TREATMENTS FOR THIS SIMPLE CONDITION

PubMed Central

LaDisa, John F.; Taylor, Charles A.; Feinstein, Jeffrey A.

2010-01-01

Coarctation of the aorta (CoA) is often considered a relatively simple disease, but long-term outcomes suggest otherwise as life expectancies are decades less than in the average population and substantial morbidity often exists. What follows is an expanded version of collective work conducted by the authors’ and numerous collaborators that was presented at the 1st International Conference on Computational Simulation in Congenital Heart Disease pertaining to recent advances for CoA. The work begins by focusing on what is known about blood flow, pressure and indices of wall shear stress (WSS) in patients with normal vascular anatomy from both clinical imaging and the use of computational fluid dynamics (CFD) techniques. Hemodynamic alterations observed in CFD studies from untreated CoA patients and those undergoing surgical or interventional treatment are subsequently discussed. The impact of surgical approach, stent design and valve morphology are also presented for these patient populations. Finally, recent work from a representative experimental animal model of CoA that may offer insight into proposed mechanisms of long-term morbidity in CoA is presented. PMID:21152106

Size-density scaling in protists and the links between consumer-resource interaction parameters.

PubMed

DeLong, John P; Vasseur, David A

2012-11-01

Recent work indicates that the interaction between body-size-dependent demographic processes can generate macroecological patterns such as the scaling of population density with body size. In this study, we evaluate this possibility for grazing protists and also test whether demographic parameters in these models are correlated after controlling for body size. We compiled data on the body-size dependence of consumer-resource interactions and population density for heterotrophic protists grazing algae in laboratory studies. We then used nested dynamic models to predict both the height and slope of the scaling relationship between population density and body size for these protists. We also controlled for consumer size and assessed links between model parameters. Finally, we used the models and the parameter estimates to assess the individual- and population-level dependence of resource use on body-size and prey-size selection. The predicted size-density scaling for all models matched closely to the observed scaling, and the simplest model was sufficient to predict the pattern. Variation around the mean size-density scaling relationship may be generated by variation in prey productivity and area of capture, but residuals are relatively insensitive to variation in prey size selection. After controlling for body size, many consumer-resource interaction parameters were correlated, and a positive correlation between residual prey size selection and conversion efficiency neutralizes the apparent fitness advantage of taking large prey. Our results indicate that widespread community-level patterns can be explained with simple population models that apply consistently across a range of sizes. They also indicate that the parameter space governing the dynamics and the steady states in these systems is structured such that some parts of the parameter space are unlikely to represent real systems. Finally, predator-prey size ratios represent a kind of conundrum, because they are widely observed but apparently have little influence on population size and fitness, at least at this level of organization. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.

How Does a Divided Population Respond to Change?

PubMed Central

Qubbaj, Murad R.; Muneepeerakul, Rachata; Aggarwal, Rimjhim M.; Anderies, John M.

2015-01-01

Most studies on the response of socioeconomic systems to a sudden shift focus on long-term equilibria or end points. Such narrow focus forgoes many valuable insights. Here we examine the transient dynamics of regime shift on a divided population, exemplified by societies divided ideologically, politically, economically, or technologically. Replicator dynamics is used to investigate the complex transient dynamics of the population response. Though simple, our modeling approach exhibits a surprisingly rich and diverse array of dynamics. Our results highlight the critical roles played by diversity in strategies and the magnitude of the shift. Importantly, it allows for a variety of strategies to arise organically as an integral part of the transient dynamics—as opposed to an independent process—of population response to a regime shift, providing a link between the population's past and future diversity patterns. Several combinations of different populations' strategy distributions and shifts were systematically investigated. Such rich dynamics highlight the challenges of anticipating the response of a divided population to a change. The findings in this paper can potentially improve our understanding of a wide range of socio-ecological and technological transitions. PMID:26161859

How Does a Divided Population Respond to Change?

PubMed

Qubbaj, Murad R; Muneepeerakul, Rachata; Aggarwal, Rimjhim M; Anderies, John M

2015-01-01

Most studies on the response of socioeconomic systems to a sudden shift focus on long-term equilibria or end points. Such narrow focus forgoes many valuable insights. Here we examine the transient dynamics of regime shift on a divided population, exemplified by societies divided ideologically, politically, economically, or technologically. Replicator dynamics is used to investigate the complex transient dynamics of the population response. Though simple, our modeling approach exhibits a surprisingly rich and diverse array of dynamics. Our results highlight the critical roles played by diversity in strategies and the magnitude of the shift. Importantly, it allows for a variety of strategies to arise organically as an integral part of the transient dynamics--as opposed to an independent process--of population response to a regime shift, providing a link between the population's past and future diversity patterns. Several combinations of different populations' strategy distributions and shifts were systematically investigated. Such rich dynamics highlight the challenges of anticipating the response of a divided population to a change. The findings in this paper can potentially improve our understanding of a wide range of socio-ecological and technological transitions.

Race differences: modeling the pharmacodynamics of rosuvastatin in Western and Asian hypercholesterolemia patients

PubMed Central

Yang, Juan; Li, Lu-jin; Wang, Kun; He, Ying-chun; Sheng, Yu-cheng; Xu, Ling; Huang, Xiao-hui; Guo, Feng; Zheng, Qing-shan

2011-01-01

Aim: To evaluate race differences in the pharmacodynamics of rosuvastatin in Western and Asian hypercholesterolemia patients using a population pharmacodynamic (PPD) model generated and validated using published clinical efficacy trials. Methods: Published studies randomized trials with rosuvastatin treatment for at least 4 weeks in hypercholesterolemia patients were used for model building and validation. Population pharmacodynamic analyses were performed to describe the dose-response relationship with the mean values of LDL-C reduction (%) from dose-ranging trials using NONMEM software. Baseline LDL-C and race were analyzed as the potential covariates. Model robustness was evaluated using the bootstrap method and the data-splitting method, and Monte Carlo simulation was performed to assess the predictive performance of the PPD model with the mean effects from the one-dose trials. Results: Of the 36 eligible trials, 14 dose-ranging trials were used in model development and 22 one-dose trials were used for model prediction. The dose-response of rosuvastatin was successfully described by a simple Emax model with a fixed E0, which provided a common Emax and an approximate twofold difference in ED50 for Westerners and Asians. The PPD model was demonstrated to be stable and predictive. Conclusion: The race differences in the pharmacodynamics of rosuvastatin are consistent with those observed in the pharmacokinetics of the drug, confirming that there is no significant difference in the exposure-response relationship for LDL-C reduction between Westerners and Asians. The study suggests that for a new compound with a mechanism of action similar to that of rosuvastatin, its efficacy in Western populations plus its pharmacokinetics in bridging studies in Asian populations may be used to support a registration of the new compound in Asian countries. PMID:21151159

Race differences: modeling the pharmacodynamics of rosuvastatin in Western and Asian hypercholesterolemia patients.

PubMed

Yang, Juan; Li, Lu-jin; Wang, Kun; He, Ying-chun; Sheng, Yu-cheng; Xu, Ling; Huang, Xiao-hui; Guo, Feng; Zheng, Qing-shan

2011-01-01

To evaluate race differences in the pharmacodynamics of rosuvastatin in Western and Asian hypercholesterolemia patients using a population pharmacodynamic (PPD) model generated and validated using published clinical efficacy trials. Published studies randomized trials with rosuvastatin treatment for at least 4 weeks in hypercholesterolemia patients were used for model building and validation. Population pharmacodynamic analyses were performed to describe the dose-response relationship with the mean values of LDL-C reduction (%) from dose-ranging trials using NONMEM software. Baseline LDL-C and race were analyzed as the potential covariates. Model robustness was evaluated using the bootstrap method and the data-splitting method, and Monte Carlo simulation was performed to assess the predictive performance of the PPD model with the mean effects from the one-dose trials. Of the 36 eligible trials, 14 dose-ranging trials were used in model development and 22 one-dose trials were used for model prediction. The dose-response of rosuvastatin was successfully described by a simple E(max) model with a fixed E(0), which provided a common E(max) and an approximate twofold difference in ED(50) for Westerners and Asians. The PPD model was demonstrated to be stable and predictive. The race differences in the pharmacodynamics of rosuvastatin are consistent with those observed in the pharmacokinetics of the drug, confirming that there is no significant difference in the exposure-response relationship for LDL-C reduction between Westerners and Asians. The study suggests that for a new compound with a mechanism of action similar to that of rosuvastatin, its efficacy in Western populations plus its pharmacokinetics in bridging studies in Asian populations may be used to support a registration of the new compound in Asian countries.

A simple approach to lifetime learning in genetic programming-based symbolic regression.

PubMed

Azad, Raja Muhammad Atif; Ryan, Conor

2014-01-01

Genetic programming (GP) coarsely models natural evolution to evolve computer programs. Unlike in nature, where individuals can often improve their fitness through lifetime experience, the fitness of GP individuals generally does not change during their lifetime, and there is usually no opportunity to pass on acquired knowledge. This paper introduces the Chameleon system to address this discrepancy and augment GP with lifetime learning by adding a simple local search that operates by tuning the internal nodes of individuals. Although not the first attempt to combine local search with GP, its simplicity means that it is easy to understand and cheap to implement. A simple cache is added which leverages the local search to reduce the tuning cost to a small fraction of the expected cost, and we provide a theoretical upper limit on the maximum tuning expense given the average tree size of the population and show that this limit grows very conservatively as the average tree size of the population increases. We show that Chameleon uses available genetic material more efficiently by exploring more actively than with standard GP, and demonstrate that not only does Chameleon outperform standard GP (on both training and test data) over a number of symbolic regression type problems, it does so by producing smaller individuals and it works harmoniously with two other well-known extensions to GP, namely, linear scaling and a diversity-promoting tournament selection method.

THE SPATIAL STRUCTURE OF MONO-ABUNDANCE SUB-POPULATIONS OF THE MILKY WAY DISK

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bovy, Jo; Rix, Hans-Walter; Liu Chao

2012-07-10

The spatial, kinematic, and elemental-abundance structure of the Milky Way's stellar disk is complex, and has been difficult to dissect with local spectroscopic or global photometric data. Here, we develop and apply a rigorous density modeling approach for Galactic spectroscopic surveys that enables investigation of the global spatial structure of stellar sub-populations in narrow bins of [{alpha}/Fe] and [Fe/H], using 23,767 G-type dwarfs from SDSS/SEGUE, which effectively sample 5 kpc < R{sub GC} < 12 kpc and 0.3 kpc {approx}< |Z| {approx}< 3 kpc. We fit models for the number density of each such ([{alpha}/Fe] and [Fe/H]) mono-abundance component, properlymore » accounting for the complex spectroscopic SEGUE sampling of the underlying stellar population, as well as for the metallicity and color distributions of the samples. We find that each mono-abundance sub-population has a simple spatial structure that can be described by a single exponential in both the vertical and radial directions, with continuously increasing scale heights ( Almost-Equal-To 200 pc to 1 kpc) and decreasing scale lengths (>4.5 kpc to 2 kpc) for increasingly older sub-populations, as indicated by their lower metallicities and [{alpha}/Fe] enhancements. That the abundance-selected sub-components with the largest scale heights have the shortest scale lengths is in sharp contrast with purely geometric 'thick-thin disk' decompositions. To the extent that [{alpha}/Fe] is an adequate proxy for age, our results directly show that older disk sub-populations are more centrally concentrated, which implies inside-out formation of galactic disks. The fact that the largest scale-height sub-components are most centrally concentrated in the Milky Way is an almost inevitable consequence of explaining the vertical structure of the disk through internal evolution. Whether the simple spatial structure of the mono-abundance sub-components and the striking correlations between age, scale length, and scale height can be plausibly explained by satellite accretion or other external heating remains to be seen.« less

Complex dynamics of selection and cellular memory in adaptation to a changing environment

NASA Astrophysics Data System (ADS)

Kussell, Edo; Lin, Wei-Hsiang

We study a synthetic evolutionary system in bacteria in which an antibiotic resistance gene is controlled by a stochastic on/off switching promoter. At the population level, this system displays all the basic ingredients for evolutionary selection, including diversity, fitness differences, and heritability. At the single cell level, physiological processes can modulate the ability of selection to act. We expose the stochastic switching strains to pulses of antibiotics of different durations in periodically changing environments using microfluidics. Small populations are tracked over a large number of periods at single cell resolution, allowing the visualization and quantification of selective sweeps and counter-sweeps at the population level, as well as detailed single cell analysis. A simple model is introduced to predict long-term population growth rates from single cell measurements, and reveals unexpected aspects of population dynamics, including cellular memory that acts on a fast timescale to modulate growth rates. This work is supported by NIH Grant No. R01-GM097356.

Optimal solutions for a bio mathematical model for the evolution of smoking habit

NASA Astrophysics Data System (ADS)

Sikander, Waseem; Khan, Umar; Ahmed, Naveed; Mohyud-Din, Syed Tauseef

In this study, we apply Variation of Parameter Method (VPM) coupled with an auxiliary parameter to obtain the approximate solutions for the epidemic model for the evolution of smoking habit in a constant population. Convergence of the developed algorithm, namely VPM with an auxiliary parameter is studied. Furthermore, a simple way is considered for obtaining an optimal value of auxiliary parameter via minimizing the total residual error over the domain of problem. Comparison of the obtained results with standard VPM shows that an auxiliary parameter is very feasible and reliable in controlling the convergence of approximate solutions.

Measurement techniques for analysis of fission fragment excited gases

NASA Technical Reports Server (NTRS)

Schneider, R. T.; Carroll, E. E.; Davis, J. F.; Davie, R. N.; Maguire, T. C.; Shipman, R. G.

1976-01-01

Spectroscopic analysis of fission fragment excited He, Ar, Xe, N2, Ne, Ar-N2, and Ne-N2 have been conducted. Boltzmann plot analysis of He, Ar and Xe have indicated a nonequilibrium, recombining plasma, and population inversions have been found in these gases. The observed radiating species in helium have been adequately described by a simple kinetic model. A more extensive model for argon, nitrogen and Ar-N2 mixtures was developed which adequately describes the energy flow in the system and compares favorably with experimental measurements. The kinetic processes involved in these systems are discussed.

Reticulated origin of domesticated emmer wheat supports a dynamic model for the emergence of agriculture in the fertile crescent.

PubMed

Civáň, Peter; Ivaničová, Zuzana; Brown, Terence A

2013-01-01

We used supernetworks with datasets of nuclear gene sequences and novel markers detecting retrotransposon insertions in ribosomal DNA loci to reassess the evolutionary relationships among tetraploid wheats. We show that domesticated emmer has a reticulated genetic ancestry, sharing phylogenetic signals with wild populations from all parts of the wild range. The extent of the genetic reticulation cannot be explained by post-domestication gene flow between cultivated emmer and wild plants, and the phylogenetic relationships among tetraploid wheats are incompatible with simple linear descent of the domesticates from a single wild population. A more parsimonious explanation of the data is that domesticated emmer originates from a hybridized population of different wild lineages. The observed diversity and reticulation patterns indicate that wild emmer evolved in the southern Levant, and that the wild emmer populations in south-eastern Turkey and the Zagros Mountains are relatively recent reticulate descendants of a subset of the Levantine wild populations. Based on our results we propose a new model for the emergence of domesticated emmer. During a pre-domestication period, diverse wild populations were collected from a large area west of the Euphrates and cultivated in mixed stands. Within these cultivated stands, hybridization gave rise to lineages displaying reticulated genealogical relationships with their ancestral populations. Gradual movement of early farmers out of the Levant introduced the pre-domesticated reticulated lineages to the northern and eastern parts of the Fertile Crescent, giving rise to the local wild populations but also facilitating fixation of domestication traits. Our model is consistent with the protracted and dispersed transition to agriculture indicated by the archaeobotanical evidence, and also with previous genetic data affiliating domesticated emmer with the wild populations in southeast Turkey. Unlike other protracted models, we assume that humans played an intuitive role throughout the process.

Supporting Fisheries Management by Means of Complex Models: Can We Point out Isles of Robustness in a Sea of Uncertainty?

PubMed Central

Gasche, Loïc; Mahévas, Stéphanie; Marchal, Paul

2013-01-01

Ecosystems are usually complex, nonlinear and strongly influenced by poorly known environmental variables. Among these systems, marine ecosystems have high uncertainties: marine populations in general are known to exhibit large levels of natural variability and the intensity of fishing efforts can change rapidly. These uncertainties are a source of risks that threaten the sustainability of both fish populations and fishing fleets targeting them. Appropriate management measures have to be found in order to reduce these risks and decrease sensitivity to uncertainties. Methods have been developed within decision theory that aim at allowing decision making under severe uncertainty. One of these methods is the information-gap decision theory. The info-gap method has started to permeate ecological modelling, with recent applications to conservation. However, these practical applications have so far been restricted to simple models with analytical solutions. Here we implement a deterministic approach based on decision theory in a complex model of the Eastern English Channel. Using the ISIS-Fish modelling platform, we model populations of sole and plaice in this area. We test a wide range of values for ecosystem, fleet and management parameters. From these simulations, we identify management rules controlling fish harvesting that allow reaching management goals recommended by ICES (International Council for the Exploration of the Sea) working groups while providing the highest robustness to uncertainties on ecosystem parameters. PMID:24204873

Supporting fisheries management by means of complex models: can we point out isles of robustness in a sea of uncertainty?

PubMed

Gasche, Loïc; Mahévas, Stéphanie; Marchal, Paul

2013-01-01

Ecosystems are usually complex, nonlinear and strongly influenced by poorly known environmental variables. Among these systems, marine ecosystems have high uncertainties: marine populations in general are known to exhibit large levels of natural variability and the intensity of fishing efforts can change rapidly. These uncertainties are a source of risks that threaten the sustainability of both fish populations and fishing fleets targeting them. Appropriate management measures have to be found in order to reduce these risks and decrease sensitivity to uncertainties. Methods have been developed within decision theory that aim at allowing decision making under severe uncertainty. One of these methods is the information-gap decision theory. The info-gap method has started to permeate ecological modelling, with recent applications to conservation. However, these practical applications have so far been restricted to simple models with analytical solutions. Here we implement a deterministic approach based on decision theory in a complex model of the Eastern English Channel. Using the ISIS-Fish modelling platform, we model populations of sole and plaice in this area. We test a wide range of values for ecosystem, fleet and management parameters. From these simulations, we identify management rules controlling fish harvesting that allow reaching management goals recommended by ICES (International Council for the Exploration of the Sea) working groups while providing the highest robustness to uncertainties on ecosystem parameters.

Simple model for vibration-translation exchange at high temperatures: effects of multiquantum transitions on the relaxation of a N2 gas flow behind a shock.

PubMed

Aliat, A; Vedula, P; Josyula, E

2011-02-01

In this paper a simple model is proposed for computation of rate coefficients related to vibration-translation transitions based on the forced harmonic oscillator theory. This model, which is developed by considering a quadrature method, provides rate coefficients that are in very good agreement with those found in the literature for the high temperature regime (≳10,000 K). This model is implemented to study a one-dimensional nonequilibrium inviscid N(2) flow behind a plane shock by considering a state-to-state approach. While the effects of ionization and chemical reactions are neglected in our study, our results show that multiquantum transitions have a great influence on the relaxation of the macroscopic parameters of the gas flow behind the shock, especially on vibrational distributions of high levels. All vibrational states are influenced by multiquantum processes, but the effective number of transitions decreases inversely according to the vibrational quantum number. For the initial conditions considered in this study, excited electronic states are found to be weakly populated and can be neglected in modeling. Moreover, the computing time is considerably reduced with the model described in this paper compared to others found in the literature. ©2011 American Physical Society

A Simple Plasma Retinol Isotope Ratio Method for Estimating β-Carotene Relative Bioefficacy in Humans: Validation with the Use of Model-Based Compartmental Analysis.

PubMed

Ford, Jennifer Lynn; Green, Joanne Balmer; Lietz, Georg; Oxley, Anthony; Green, Michael H

2017-09-01

Background: Provitamin A carotenoids are an important source of dietary vitamin A for many populations. Thus, accurate and simple methods for estimating carotenoid bioefficacy are needed to evaluate the vitamin A value of test solutions and plant sources. β-Carotene bioefficacy is often estimated from the ratio of the areas under plasma isotope response curves after subjects ingest labeled β-carotene and a labeled retinyl acetate reference dose [isotope reference method (IRM)], but to our knowledge, the method has not yet been evaluated for accuracy. Objectives: Our objectives were to develop and test a physiologically based compartmental model that includes both absorptive and postabsorptive β-carotene bioconversion and to use the model to evaluate the accuracy of the IRM and a simple plasma retinol isotope ratio [(RIR), labeled β-carotene-derived retinol/labeled reference-dose-derived retinol in one plasma sample] for estimating relative bioefficacy. Methods: We used model-based compartmental analysis (Simulation, Analysis and Modeling software) to develop and apply a model that provided known values for β-carotene bioefficacy. Theoretical data for 10 subjects were generated by the model and used to determine bioefficacy by RIR and IRM; predictions were compared with known values. We also applied RIR and IRM to previously published data. Results: Plasma RIR accurately predicted β-carotene relative bioefficacy at 14 d or later. IRM also accurately predicted bioefficacy by 14 d, except that, when there was substantial postabsorptive bioconversion, IRM underestimated bioefficacy. Based on our model, 1-d predictions of relative bioefficacy include absorptive plus a portion of early postabsorptive conversion. Conclusion: The plasma RIR is a simple tracer method that accurately predicts β-carotene relative bioefficacy based on analysis of one blood sample obtained at ≥14 d after co-ingestion of labeled β-carotene and retinyl acetate. The method also provides information about the contributions of absorptive and postabsorptive conversion to total bioefficacy if an additional sample is taken at 1 d. © 2017 American Society for Nutrition.

Brain State Effects on Layer 4 of the Awake Visual Cortex

PubMed Central

Zhuang, Jun; Bereshpolova, Yulia; Stoelzel, Carl R.; Huff, Joseph M.; Hei, Xiaojuan; Alonso, Jose-Manuel

2014-01-01

Awake mammals can switch between alert and nonalert brain states hundreds of times per day. Here, we study the effects of alertness on two cell classes in layer 4 of primary visual cortex of awake rabbits: presumptive excitatory “simple” cells and presumptive fast-spike inhibitory neurons (suspected inhibitory interneurons). We show that in both cell classes, alertness increases the strength and greatly enhances the reliability of visual responses. In simple cells, alertness also increases the temporal frequency bandwidth, but preserves contrast sensitivity, orientation tuning, and selectivity for direction and spatial frequency. Finally, alertness selectively suppresses the simple cell responses to high-contrast stimuli and stimuli moving orthogonal to the preferred direction, effectively enhancing mid-contrast borders. Using a population coding model, we show that these effects of alertness in simple cells—enhanced reliability, higher gain, and increased suppression in orthogonal orientation—could play a major role at increasing the speed of cortical feature detection. PMID:24623767

Inference for finite-sample trajectories in dynamic multi-state site-occupancy models using hidden Markov model smoothing

USGS Publications Warehouse

Fiske, Ian J.; Royle, J. Andrew; Gross, Kevin

2014-01-01

Ecologists and wildlife biologists increasingly use latent variable models to study patterns of species occurrence when detection is imperfect. These models have recently been generalized to accommodate both a more expansive description of state than simple presence or absence, and Markovian dynamics in the latent state over successive sampling seasons. In this paper, we write these multi-season, multi-state models as hidden Markov models to find both maximum likelihood estimates of model parameters and finite-sample estimators of the trajectory of the latent state over time. These estimators are especially useful for characterizing population trends in species of conservation concern. We also develop parametric bootstrap procedures that allow formal inference about latent trend. We examine model behavior through simulation, and we apply the model to data from the North American Amphibian Monitoring Program.

The GREAT-ER model in China: Evaluating the risk of both treated and untreated wastewater discharges and a consideration to the future.

NASA Astrophysics Data System (ADS)

Jackson, Benjamin; Jones, Kevin; Sweetman, Andrew

2016-04-01

As a result of rapid economic development, the production and usage of chemicals in China has risen significantly. This has resulted in China's environment becoming degraded. The Chinese government has attempted to ease these problems with significant investment towards upgrading the wastewater network. These efforts have initially focused upon large cities; progressing towards smaller populations within the most recent 5 year plan. However rural populations were largely overlooked, ~90% of rural settlements do not have treatment facilities for their wastewater. The next (13th) five year plan is a great opportunity to improve upon wastewater infrastructure. This transition is particularly important and it is essential for the government to prioritise settlements to provide treatment facilities and to improve water quality in receiving waters. This study focuses upon the use of a catchment model in order make progress towards this goal. A reliable model which can capture the complexity of the catchment is needed, but one without complexity in itself, in order for it to be developed and validated without an excessive requirement for data. The Geo-referenced Regional Exposure Assessment Tool for European Rivers (GREAT-ER) model is a catchment-scale stochastic-deterministic GIS model. It is primarily used for higher-tier chemical risk assessment. Emissions are from point source only and are calculated based upon population and calculated emission rates per capita. Dilution and transportation are determined using low-flow statistics within each stretch; calculated based upon catchment soil and topographic properties. Removal of the contaminant can occur prior to emission and in-stream. The lowest tier methodology applies a simple 1st-order removal rate and a flat percentage removal for in-stream and sewage treatment work removal respectively. The data requirements are relatively low, although still challenging for many situations. Many authors have reported reasonable agreement between modelled and observed concentrations. Unlike many other water quality models, GREAT-ER is relatively simple to setup and use. This provides value for catchment managers, and for chemical end-users and manufacturers alike. As of yet, GREAT-ER has not been used in Chinese catchments, but there is much potential. Our study involves the creation and validation of a model for the Dongjiang catchment, South China. The Dongjiang catchment is a highly populated area, draining into Guangzhou and the Pearl River delta. The catchment area is 25,325 km2 (above Boluo gauging station), of which approximately 90% resides in Guangdong Province. The downstream section of the catchment is densely populated, whilst upstream there is a more significant rural population. This study focuses upon chemical ingredients found in personal care products and pharmaceuticals and the potential risk they may impose upon the catchment. The relative impact of rural discharges has also been examined along with the potential effect of a range of future wastewater upgrade scenarios. The model has been validated with measurement data collected over a number of sampling campaigns. We believe that this study provides insights into the challenges faced by China as it drives to improve water quality.

Using energy budgets to combine ecology and toxicology in a mammalian sentinel species

NASA Astrophysics Data System (ADS)

Desforges, Jean-Pierre W.; Sonne, Christian; Dietz, Rune

2017-04-01

Process-driven modelling approaches can resolve many of the shortcomings of traditional descriptive and non-mechanistic toxicology. We developed a simple dynamic energy budget (DEB) model for the mink (Mustela vison), a sentinel species in mammalian toxicology, which coupled animal physiology, ecology and toxicology, in order to mechanistically investigate the accumulation and adverse effects of lifelong dietary exposure to persistent environmental toxicants, most notably polychlorinated biphenyls (PCBs). Our novel mammalian DEB model accurately predicted, based on energy allocations to the interconnected metabolic processes of growth, development, maintenance and reproduction, lifelong patterns in mink growth, reproductive performance and dietary accumulation of PCBs as reported in the literature. Our model results were consistent with empirical data from captive and free-ranging studies in mink and other wildlife and suggest that PCB exposure can have significant population-level impacts resulting from targeted effects on fetal toxicity, kit mortality and growth and development. Our approach provides a simple and cross-species framework to explore the mechanistic interactions of physiological processes and ecotoxicology, thus allowing for a deeper understanding and interpretation of stressor-induced adverse effects at all levels of biological organization.

Protoplanetary disc `isochrones' and the evolution of discs in the M˙-Md plane

NASA Astrophysics Data System (ADS)

Lodato, Giuseppe; Scardoni, Chiara E.; Manara, Carlo F.; Testi, Leonardo

2017-12-01

In this paper, we compare simple viscous diffusion models for the disc evolution with the results of recent surveys of the properties of young protoplanetary discs. We introduce the useful concept of 'disc isochrones' in the accretion rate-disc mass plane and explore a set of Monte Carlo realization of disc initial conditions. We find that such simple viscous models can provide a remarkable agreement with the available data in the Lupus star forming region, with the key requirement that the average viscous evolutionary time-scale of the discs is comparable to the cluster age. Our models produce naturally a correlation between mass accretion rate and disc mass that is shallower than linear, contrary to previous results and in agreement with observations. We also predict that a linear correlation, with a tighter scatter, should be found for more evolved disc populations. Finally, we find that such viscous models can reproduce the observations in the Lupus region only in the assumption that the efficiency of angular momentum transport is a growing function of radius, thus putting interesting constraints on the nature of the microscopic processes that lead to disc accretion.

Stochastic oscillations in models of epidemics on a network of cities

NASA Astrophysics Data System (ADS)

Rozhnova, G.; Nunes, A.; McKane, A. J.

2011-11-01

We carry out an analytic investigation of stochastic oscillations in a susceptible-infected-recovered model of disease spread on a network of n cities. In the model a fraction fjk of individuals from city k commute to city j, where they may infect, or be infected by, others. Starting from a continuous-time Markov description of the model the deterministic equations, which are valid in the limit when the population of each city is infinite, are recovered. The stochastic fluctuations about the fixed point of these equations are derived by use of the van Kampen system-size expansion. The fixed point structure of the deterministic equations is remarkably simple: A unique nontrivial fixed point always exists and has the feature that the fraction of susceptible, infected, and recovered individuals is the same for each city irrespective of its size. We find that the stochastic fluctuations have an analogously simple dynamics: All oscillations have a single frequency, equal to that found in the one-city case. We interpret this phenomenon in terms of the properties of the spectrum of the matrix of the linear approximation of the deterministic equations at the fixed point.

Portrait of a small population of boreal toads (Anaxyrus boreas)

USGS Publications Warehouse

Muths, Erin; Scherer, Rick D.

2011-01-01

Much attention has been given to the conservation of small populations, those that are small because of decline, and those that are naturally small. Small populations are of particular interest because ecological theory suggests that they are vulnerable to the deleterious effects of environmental, demographic, and genetic stochasticity as well as natural and human-induced catastrophes. However, testing theory and developing applicable conservation measures for small populations is hampered by sparse data. This lack of information is frequently driven by computational issues with small data sets that can be confounded by the impacts of stressors. We present estimates of demographic parameters from a small population of Boreal Toads (Anaxyrus boreas) that has been surveyed since 2001 by using capture-recapture methods. Estimates of annual adult survival probability are high relative to other Boreal Toad populations, whereas estimates of recruitment rate are low. Despite using simple models, clear patterns emerged from the analyses, suggesting that population size is constrained by low recruitment of adults and is declining slowly. These patterns provide insights that are useful in developing management directions for this small population, and this study serves as an example of the potential for small populations to yield robust and useful information despite sample size constraints.

Towards a Population Synthesis Model of Objects formed by Self-Gravitating Disc Fragmentation and Tidal Downsizing

NASA Astrophysics Data System (ADS)

Forgan, Duncan; Rice, Ken

2013-07-01

Recently, the gravitational instability (GI) model of giant planet and brown dwarf formation has been revisited and recast into what is often referred to as the "tidal downsizing" hypothesis. The fragmentation of self-gravitating protostellar discs into gravitationally bound embryos - with masses of a few to tens of Jupiter masses, at semi major axes above 30 - 40 AU - is followed by a combination of grain sedimentation inside the embryo, radial migration towards the central star and tidal disruption of the embryo's upper layers. The properties of the resultant object depends sensitively on the timescales upon which each process occurs. Therefore, GI followed by tidal downsizing can theoretically produce objects spanning a large mass range, from terrestrial planets to giant planets and brown dwarfs. Whether such objects can be formed in practice, and what proportions of the observed population they would represent, requires a more involved statistical analysis. We present a simple population synthesis model of star and planet formation via GI and tidal downsizing. We couple a semi-analytic model of protostellar disc evolution to analytic calculations of fragmentation, initial embryo mass, grain growth and sedimentation, embryo migration and tidal disruption. While there are key pieces of physics yet to be incorporated, it represents a first step towards a mature statistical model of GI and tidal downsizing as a mode of star and planet formation. We show results from four runs of the population synthesis model, varying the opacity law and the strength of migration, as well as investigating the effect of disc truncation during the fragmentation process.

Equilibrium population dynamics when mating is by mutual choice based on age.

PubMed

Alpern, Steve; Katrantzi, Ioanna; Ramsey, David

2014-06-01

We consider a steady state model of mutual mate choice in which an individual's mate preferences depend on his/her age, and the preferences are over the ages of prospective mates of the opposite sex. We present a discrete time (and age) model corresponding to successive mating seasons. Males are fertile for m periods (corresponding to 'age' i=1 to m) and females for n≤m periods (they have ages j=1 to n), which is all that distinguishes the sexes. Although we can deal with arbitrary preferences, we concentrate on a simple fertility model where the common utility to a male age i and female age j who mate is the number K=min(m-i+1,n-j+1) of future periods of joint fertility. The incoming sex ratio R of age 1 males to age 1 females is given exogenously. In each period individuals are randomly (non assortatively) matched and form a mated couple by mutual consent; otherwise they go into the next period unmated and older. We derive properties of equilibrium threshold acceptance strategies and establish the existence of time-invariant age distributions. Our methods determine the age distribution of couples at marriage (mating) and the population sex ratio (OSR) at equilibrium. Since this can be determined empirically in a population, our model can be used to rule out most systems of age preferences (those not consistent with the observed distribution). This extends earlier models of mutual choice with one dimensional types of Alpern and Reyniers [1999. Strategic mating with homotypic preferences. J. Theor. Biol. 198, 71-88; 2005. Strategic mating with common preferences. J. Theor. Biol. 237, 337-354] where individuals sought, respectively, individuals with similar or high types, but in those models an individual's type was fixed over time. Under the simple fertility model, at equilibrium the maximum age of an acceptable partner is increasing in the age of the searcher. Our results relate to discussions in the literature regarding optimal parental age differences, age-related mate preferences, and to mate choice in general. We believe our model will be used as a tool in future investigations in these areas. Copyright © 2013 Elsevier Inc. All rights reserved.

Drift as a mechanism for cultural change: an example from baby names.

PubMed Central

Hahn, Matthew W; Bentley, R Alexander

2003-01-01

In the social sciences, there is currently no consensus on the mechanism by which cultural elements come and go in human society. For elements that are value-neutral, an appropriate null model may be one of random copying between individuals in the population. We show that the frequency distributions of baby names used in the United States in each decade of the twentieth century, for both males and females, obey a power law that is maintained over 100 years even though the population is growing, names are being introduced and lost every decade and large changes in the frequencies of specific names are common. We show that these distributions are satisfactorily explained by a simple process in which individuals randomly copy names from each other, a process that is analogous to the infinite-allele model of population genetics with random genetic drift. By its simplicity, this model provides a powerful null hypothesis for cultural change. It further explains why a few elements inevitably become highly popular, even if they have no intrinsic superiority over alternatives. Random copying could potentially explain power law distributions in other cultural realms, including the links on the World Wide Web. PMID:12952655

The role of parasites in the dynamics of a reindeer population.

PubMed Central

Albon, S D; Stien, A; Irvine, R J; Langvatn, R; Ropstad, E; Halvorsen, O

2002-01-01

Even though theoretical models show that parasites may regulate host population densities, few empirical studies have given support to this hypothesis. We present experimental and observational evidence for a host-parasite interaction where the parasite has sufficient impact on host population dynamics for regulation to occur. During a six year study of the Svalbard reindeer and its parasitic gastrointestinal nematode Ostertagia gruehneri we found that anthelminthic treatment in April-May increased the probability of a reindeer having a calf in the next year, compared with untreated controls. However, treatment did not influence the over-winter survival of the reindeer. The annual variation in the degree to which parasites depressed fecundity was positively related to the abundance of O. gruehneri infection the previous October, which in turn was related to host density two years earlier. In addition to the treatment effect, there was a strong negative effect of winter precipitation on the probability of female reindeer having a calf. A simple matrix model was parameterized using estimates from our experimental and observational data. This model shows that the parasite-mediated effect on fecundity was sufficient to regulate reindeer densities around observed host densities. PMID:12184833

SLiM 2: Flexible, Interactive Forward Genetic Simulations.

PubMed

Haller, Benjamin C; Messer, Philipp W

2017-01-01

Modern population genomic datasets hold immense promise for revealing the evolutionary processes operating in natural populations, but a crucial prerequisite for this goal is the ability to model realistic evolutionary scenarios and predict their expected patterns in genomic data. To that end, we present SLiM 2: an evolutionary simulation framework that combines a powerful, fast engine for forward population genetic simulations with the capability of modeling a wide variety of complex evolutionary scenarios. SLiM achieves this flexibility through scriptability, which provides control over most aspects of the simulated evolutionary scenarios with a simple R-like scripting language called Eidos. An example SLiM simulation is presented to illustrate the power of this approach. SLiM 2 also includes a graphical user interface for simulation construction, interactive runtime control, and dynamic visualization of simulation output, facilitating easy and fast model development with quick prototyping and visual debugging. We conclude with a performance comparison between SLiM and two other popular forward genetic simulation packages. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Non-Boltzmann Modeling for Air Shock-Layer Radiation at Lunar-Return Conditions

NASA Technical Reports Server (NTRS)

Johnston, Christopher O.; Hollis, Brian R.; Sutton, Kenneth

2008-01-01

This paper investigates the non-Boltzmann modeling of the radiating atomic and molecular electronic states present in lunar-return shock-layers. The Master Equation is derived for a general atom or molecule while accounting for a variety of excitation and de-excitation mechanisms. A new set of electronic-impact excitation rates is compiled for N, O, and N2+, which are the main radiating species for most lunar-return shock-layers. Based on these new rates, a novel approach of curve-fitting the non-Boltzmann populations of the radiating atomic and molecular states is developed. This new approach provides a simple and accurate method for calculating the atomic and molecular non-Boltzmann populations while avoiding the matrix inversion procedure required for the detailed solution of the Master Equation. The radiative flux values predicted by the present detailed non-Boltzmann model and the approximate curve-fitting approach are shown to agree within 5% for the Fire 1634 s case.

A computational approach to animal breeding.

PubMed

Berger-Wolf, Tanya Y; Moore, Cristopher; Saia, Jared

2007-02-07

We propose a computational model of mating strategies for controlled animal breeding programs. A mating strategy in a controlled breeding program is a heuristic with some optimization criteria as a goal. Thus, it is appropriate to use the computational tools available for analysis of optimization heuristics. In this paper, we propose the first discrete model of the controlled animal breeding problem and analyse heuristics for two possible objectives: (1) breeding for maximum diversity and (2) breeding a target individual. These two goals are representative of conservation biology and agricultural livestock management, respectively. We evaluate several mating strategies and provide upper and lower bounds for the expected number of matings. While the population parameters may vary and can change the actual number of matings for a particular strategy, the order of magnitude of the number of expected matings and the relative competitiveness of the mating heuristics remains the same. Thus, our simple discrete model of the animal breeding problem provides a novel viable and robust approach to designing and comparing breeding strategies in captive populations.

Synthetic Quorum Sensing and Induced Aggregation in Model Microcapsule Colonies with Repressilator Feedback

NASA Astrophysics Data System (ADS)

Shum, Henry; Yashin, Victor; Balazs, Anna

We model a system of synthetic microcapsules that communicate chemically by releasing nanoparticles or signaling molecules. These signaling species bind to receptors on the shells of capsules and modulate the target shell's permeability, thereby controlling nanoparticle release from the target capsule. Using the repressilator regulatory network motif, whereby three species suppress the production of the next in a cyclic fashion, we show that large amplitude oscillations in nanoparticle release can emerge when many capsules are close together. This exemplifies quorum sensing, which is the ability of cells to gauge their population density and collectively initiate a new behavior once a critical density is reached. We present a physically realizable model in which the oscillations exhibited in crowded populations induce aggregation of the microcapsules, mimicking complex biological behavior of the slime mold Dictyostelium discoideum with only simple, synthetic components. We also show that the clusters can be dispersed and reformed repeatedly and controllably by addition of chemical stimuli, demonstrating possible applications in creating reconfigurable or programmable materials.

Homogenization analysis of invasion dynamics in heterogeneous landscapes with differential bias and motility.

PubMed

Yurk, Brian P

2018-07-01

Animal movement behaviors vary spatially in response to environmental heterogeneity. An important problem in spatial ecology is to determine how large-scale population growth and dispersal patterns emerge within highly variable landscapes. We apply the method of homogenization to study the large-scale behavior of a reaction-diffusion-advection model of population growth and dispersal. Our model includes small-scale variation in the directed and random components of movement and growth rates, as well as large-scale drift. Using the homogenized model we derive simple approximate formulas for persistence conditions and asymptotic invasion speeds, which are interpreted in terms of residence index. The homogenization results show good agreement with numerical solutions for environments with a high degree of fragmentation, both with and without periodicity at the fast scale. The simplicity of the formulas, and their connection to residence index make them appealing for studying the large-scale effects of a variety of small-scale movement behaviors.

Scaling in sensitivity analysis

USGS Publications Warehouse

Link, W.A.; Doherty, P.F.

2002-01-01

Population matrix models allow sets of demographic parameters to be summarized by a single value 8, the finite rate of population increase. The consequences of change in individual demographic parameters are naturally measured by the corresponding changes in 8; sensitivity analyses compare demographic parameters on the basis of these changes. These comparisons are complicated by issues of scale. Elasticity analysis attempts to deal with issues of scale by comparing the effects of proportional changes in demographic parameters, but leads to inconsistencies in evaluating demographic rates. We discuss this and other problems of scaling in sensitivity analysis, and suggest a simple criterion for choosing appropriate scales. We apply our suggestions to data for the killer whale, Orcinus orca.

Demographic and genetic consequences of disturbed sex determination.

PubMed

Wedekind, Claus

2017-09-19

During sex determination, genetic and/or environmental factors determine the cascade of processes of gonad development. Many organisms, therefore, have a developmental window in which their sex determination can be sensitive to, for example, unusual temperatures or chemical pollutants. Disturbed environments can distort population sex ratios and may even cause sex reversal in species with genetic sex determination. The resulting genotype-phenotype mismatches can have long-lasting effects on population demography and genetics. I review the theoretical and empirical work in this context and explore in a simple population model the role of the fitness v yy of chromosomally aberrant YY genotypes that are a consequence of environmentally induced feminization. Low v yy is mostly beneficial for population growth. During feminization, low v yy reduces the proportion of genetic males and hence accelerates population growth, especially at low rates of feminization and at high fitness costs of the feminization itself (i.e. when feminization would otherwise not affect population dynamics much). When sex reversal ceases, low v yy mitigates the negative effects of feminization and can even prevent population extinction. Little is known about v yy in natural populations. The available models now need to be parametrized in order to better predict the long-term consequences of disturbed sex determination.This article is part of the themed issue 'Adult sex ratios and reproductive decisions: a critical re-examination of sex differences in human and animal societies'. © 2017 The Author(s).

Anomalous evolution of Ar metastable density with electron density in high density Ar discharge

DOE Office of Scientific and Technical Information (OSTI.GOV)

Park, Min; Chang, Hong-Young; You, Shin-Jae

2011-10-15

Recently, an anomalous evolution of argon metastable density with plasma discharge power (electron density) was reported [A. M. Daltrini, S. A. Moshkalev, T. J. Morgan, R. B. Piejak, and W. G. Graham, Appl. Phys. Lett. 92, 061504 (2008)]. Although the importance of the metastable atom and its density has been reported in a lot of literature, however, a basic physics behind the anomalous evolution of metastable density has not been clearly understood yet. In this study, we investigated a simple global model to elucidate the underlying physics of the anomalous evolution of argon metastable density with the electron density. Onmore » the basis of the proposed simple model, we reproduced the anomalous evolution of the metastable density and disclosed the detailed physics for the anomalous result. Drastic changes of dominant mechanisms for the population and depopulation processes of Ar metastable atoms with electron density, which take place even in relatively low electron density regime, is the clue to understand the result.« less

Integrating individual movement behaviour into dispersal functions.

PubMed

Heinz, Simone K; Wissel, Christian; Conradt, Larissa; Frank, Karin

2007-04-21

Dispersal functions are an important tool for integrating dispersal into complex models of population and metapopulation dynamics. Most approaches in the literature are very simple, with the dispersal functions containing only one or two parameters which summarise all the effects of movement behaviour as for example different movement patterns or different perceptual abilities. The summarising nature of these parameters makes assessing the effect of one particular behavioural aspect difficult. We present a way of integrating movement behavioural parameters into a particular dispersal function in a simple way. Using a spatial individual-based simulation model for simulating different movement behaviours, we derive fitting functions for the functional relationship between the parameters of the dispersal function and several details of movement behaviour. This is done for three different movement patterns (loops, Archimedean spirals, random walk). Additionally, we provide measures which characterise the shape of the dispersal function and are interpretable in terms of landscape connectivity. This allows an ecological interpretation of the relationships found.

Application of a Simple Model to Predict Environmental Radionuclide Levels and Consequential Dose Rates on the South Welsh Coast, U.K.

NASA Astrophysics Data System (ADS)

Halliwell, C. M.; McKay, W. A.

1994-02-01

The impact of liquid effluent discharges, from both existing nuclear power stations and from a possible future pressurized water reactor (PWR), on the levels of radioactivity in Welsh Severn coastal waters has been addressed in this study through the use of a simple box model. If a PWR was in operation at Hinkley Point, and assuming that the existing discharges into the estuary remained the same as in 1989, the levels of the most radiologically significant radionuclide, 137Cs, in seawater along the Welsh shoreline are predicted to increase by 7% (inner estuary), 7% (Welsh outer estuary) and 5% (inner channel) and in sediment by 0·3, 1·3 and 2% respectively. The radiation dose rate from 137Cs to members of the coastal population alone would show only a marginal increase due to these changes, and would remain less than 1% of the internationally recognized limit.

Phasic Firing in Vasopressin Cells: Understanding Its Functional Significance through Computational Models

PubMed Central

MacGregor, Duncan J.; Leng, Gareth

2012-01-01

Vasopressin neurons, responding to input generated by osmotic pressure, use an intrinsic mechanism to shift from slow irregular firing to a distinct phasic pattern, consisting of long bursts and silences lasting tens of seconds. With increased input, bursts lengthen, eventually shifting to continuous firing. The phasic activity remains asynchronous across the cells and is not reflected in the population output signal. Here we have used a computational vasopressin neuron model to investigate the functional significance of the phasic firing pattern. We generated a concise model of the synaptic input driven spike firing mechanism that gives a close quantitative match to vasopressin neuron spike activity recorded in vivo, tested against endogenous activity and experimental interventions. The integrate-and-fire based model provides a simple physiological explanation of the phasic firing mechanism involving an activity-dependent slow depolarising afterpotential (DAP) generated by a calcium-inactivated potassium leak current. This is modulated by the slower, opposing, action of activity-dependent dendritic dynorphin release, which inactivates the DAP, the opposing effects generating successive periods of bursting and silence. Model cells are not spontaneously active, but fire when perturbed by random perturbations mimicking synaptic input. We constructed one population of such phasic neurons, and another population of similar cells but which lacked the ability to fire phasically. We then studied how these two populations differed in the way that they encoded changes in afferent inputs. By comparison with the non-phasic population, the phasic population responds linearly to increases in tonic synaptic input. Non-phasic cells respond to transient elevations in synaptic input in a way that strongly depends on background activity levels, phasic cells in a way that is independent of background levels, and show a similar strong linearization of the response. These findings show large differences in information coding between the populations, and apparent functional advantages of asynchronous phasic firing. PMID:23093929

Positive feedback in the transition from sexual reproduction to parthenogenesis

PubMed Central

Schwander, Tanja; Vuilleumier, Séverine; Dubman, Janie; Crespi, Bernard J.

2010-01-01

Understanding how new phenotypes evolve is challenging because intermediate stages in transitions from ancestral to derived phenotypes often remain elusive. Here we describe and evaluate a new mechanism facilitating the transition from sexual reproduction to parthenogenesis. In many sexually reproducing species, a small proportion of unfertilized eggs can hatch spontaneously (‘tychoparthenogenesis’) and develop into females. Using an analytical model, we show that if females are mate-limited, tychoparthenogenesis can result in the loss of males through a positive feedback mechanism whereby tychoparthenogenesis generates female-biased sex ratios and increasing mate limitation. As a result, the strength of selection for tychoparthenogenesis increases in concert with the proportion of tychoparthenogenetic offspring in the sexual population. We then tested the hypothesis that mate limitation selects for tychoparthenogenesis and generates female-biased sex ratios, using data from natural populations of sexually reproducing Timema stick insects. Across 41 populations, both the tychoparthenogenesis rates and the proportions of females increased exponentially as the density of individuals decreased, consistent with the idea that low densities of individuals result in mate limitation and selection for reproductive insurance through tychoparthenogenesis. Our model and data from Timema populations provide evidence for a simple mechanism through which parthenogenesis can evolve rapidly in a sexual population. PMID:20071382

Linkage disequilibrium analysis in young populations: Pseudo-vitamin D-deficiency rickets and the founder effect in French Canadians

DOE Office of Scientific and Technical Information (OSTI.GOV)

Labuda, M.; Glorieux, F.H.; Labuda, D.

1996-09-01

Pseudo-vitamin D-deficiency rickets (PDDR) was mapped close to D12S90 and between proximal D12S312 and distal (D12S305, D12S104) microsatellites that were subsequently found on a single YAC clone. Analysis of a complex haplotype in linkage disequilibrium (LD) with the disease discriminated among distinct founder effects in French Canadian populations in Acadia and in Charlevoix-Saguenay-Lac-Saint-Jean (Ch-SLSJ), as well as an earlier one in precolonial Europe. A simple demographic model suggested the historical age of the founder effect in Ch-SLSJ to be {approximately}12 generations. The corresponding LD data are consistent with this figure when they are analyzed within the framework of Luria-Delbruck model,more » which takes into account the population growth. Population sampling due to a limited number of first settlers and the rapid demographic expansion appear to have played a major role in the founding of PDDR in Ch-SLSJ and, presumably, other genetic disorders endemic to French Canada. Similarly, the founder effect in Ashkenazim, coinciding with their early settlement in medieval Poland and subsequent expansion eastward, could explain the origin of frequent genetic diseases in this population. 48 refs., 5 figs., 2 tabs.« less

A macroevolutionary explanation for energy equivalence in the scaling of body size and population density.

PubMed

Damuth, John

2007-05-01

Across a wide array of animal species, mean population densities decline with species body mass such that the rate of energy use of local populations is approximately independent of body size. This "energetic equivalence" is particularly evident when ecological population densities are plotted across several or more orders of magnitude in body mass and is supported by a considerable body of evidence. Nevertheless, interpretation of the data has remained controversial, largely because of the difficulty of explaining the origin and maintenance of such a size-abundance relationship in terms of purely ecological processes. Here I describe results of a simulation model suggesting that an extremely simple mechanism operating over evolutionary time can explain the major features of the empirical data. The model specifies only the size scaling of metabolism and a process where randomly chosen species evolve to take resource energy from other species. This process of energy exchange among particular species is distinct from a random walk of species abundances and creates a situation in which species populations using relatively low amounts of energy at any body size have an elevated extinction risk. Selective extinction of such species rapidly drives size-abundance allometry in faunas toward approximate energetic equivalence and maintains it there.

Using Approximate Bayesian Computation to Probe Multiple Transiting Planet Systems

NASA Astrophysics Data System (ADS)

Morehead, Robert C.

2015-08-01

The large number of multiple transiting planet systems (MTPS) uncovered with Kepler suggest a population of well-aligned planetary systems. Previously, the distribution of transit duration ratios in MTPSs has been used to place constraints on the distributions of mutual orbital inclinations and orbital eccentricities in these systems. However, degeneracies with the underlying number of planets in these systems pose added challenges and make explicit likelihood functions intractable. Approximate Bayesian computation (ABC) offers an intriguing path forward. In its simplest form, ABC proposes from a prior on the population parameters to produce synthetic datasets via a physically-motivated model. Samples are accepted or rejected based on how close they come to reproducing the actual observed dataset to some tolerance. The accepted samples then form a robust and useful approximation of the true posterior distribution of the underlying population parameters. We will demonstrate the utility of ABC in exoplanet populations by presenting new constraints on the mutual inclination and eccentricity distributions in the Kepler MTPSs. We will also introduce Simple-ABC, a new open-source Python package designed for ease of use and rapid specification of general models, suitable for use in a wide variety of applications in both exoplanet science and astrophysics as a whole.

HIV Treatment and Prevention: A Simple Model to Determine Optimal Investment.

PubMed

Juusola, Jessie L; Brandeau, Margaret L

2016-04-01

To create a simple model to help public health decision makers determine how to best invest limited resources in HIV treatment scale-up and prevention. A linear model was developed for determining the optimal mix of investment in HIV treatment and prevention, given a fixed budget. The model incorporates estimates of secondary health benefits accruing from HIV treatment and prevention and allows for diseconomies of scale in program costs and subadditive benefits from concurrent program implementation. Data sources were published literature. The target population was individuals infected with HIV or at risk of acquiring it. Illustrative examples of interventions include preexposure prophylaxis (PrEP), community-based education (CBE), and antiretroviral therapy (ART) for men who have sex with men (MSM) in the US. Outcome measures were incremental cost, quality-adjusted life-years gained, and HIV infections averted. Base case analysis indicated that it is optimal to invest in ART before PrEP and to invest in CBE before scaling up ART. Diseconomies of scale reduced the optimal investment level. Subadditivity of benefits did not affect the optimal allocation for relatively low implementation levels. The sensitivity analysis indicated that investment in ART before PrEP was optimal in all scenarios tested. Investment in ART before CBE became optimal when CBE reduced risky behavior by 4% or less. Limitations of the study are that dynamic effects are approximated with a static model. Our model provides a simple yet accurate means of determining optimal investment in HIV prevention and treatment. For MSM in the US, HIV control funds should be prioritized on inexpensive, effective programs like CBE, then on ART scale-up, with only minimal investment in PrEP. © The Author(s) 2015.

A Method for Obtaining Large Populations of Synchronized Caenorhabditis elegans Dauer Larvae.

PubMed

Ow, Maria C; Hall, Sarah E

2015-01-01

The C. elegans dauer is an attractive model with which to investigate fundamental biological questions, such as how environmental cues are sensed and are translated into developmental decisions through a series of signaling cascades that ultimately result in a transformed animal. Here we describe a simple method of using egg white plates to obtain highly synchronized purified dauers that can be used in downstream applications requiring large quantities of dauers or postdauer animals.

The Geographic Distribution, Ownership, Prices, and Scope of Practice at Retail Clinics

PubMed Central

Rudavsky, Rena; Pollack, Craig Evan; Mehrotra, Ateev

2009-01-01

BACKGROUND As a new model of care in the United States (US), retail clinics have generated much interest. Located physically within a retail store, they provide simple acute and preventive care services for a fixed price and without an appointment. OBJECTIVE To describe where retail clinics have opened in the US, their ownership structure, scope of practice, prices, acceptance of insurance, and the fraction of the population that lives within a short driving distance of a clinic. DESIGN Cross-sectional descriptive study SAMPLE All retail clinics operating in the US as of August 2008 MEASUREMENTS Population living within five and ten-minute driving distances of a retail clinic RESULTS In August 2008, 42 operators ran 982 clinics in 33 states; 88.4% were located in urban areas. An estimated 13.4% and 35.8% of the US urban population lives within a five-minute and ten-minute driving distance respectively from a retail clinic. The proportion of the population that lives close to a retail clinic is higher than 50 percent in some cities such as Nashville (56.7% five-minute, 93.7% ten-minute) and Minneapolis-St. Paul, MN (50.9%, 96.0%). The majority of retail clinic operators (25, 59.5%) are hospital chains and/or physician groups, but they only operate 11.4% of the clinics nationally. Simple acute conditions, skin conditions, and immunizations make up the majority of retail clinics’ limited scope of practice. Across operators, those without insurance paid on average $78 for a sore throat visit and $63 for an adult tetanus booster vaccine. In a random sample of clinics, we found that 97% accepted private insurance, 93% accepted Medicare fee-for-service, and 60% accepted some form of Medicaid. LIMITATIONS Geographic access is only one of many factors that influence whether an individual visits a retail clinic CONCLUSIONS Retail clinics can provide care for simple acute conditions and immunizations for a significant segment of the urban US population. PRIMARY FUNDING California Healthcare Foundation PMID:19721019

The Anthropocene Generalized: Evolution of Exo-Civilizations and Their Planetary Feedback.

PubMed

Frank, A; Carroll-Nellenback, Jonathan; Alberti, M; Kleidon, A

2018-05-01

We present a framework for studying generic behaviors possible in the interaction between a resource-harvesting technological civilization (an exo-civilization) and the planetary environment in which it evolves. Using methods from dynamical systems theory, we introduce and analyze a suite of simple equations modeling a population which consumes resources for the purpose of running a technological civilization and the feedback those resources drive on the state of the host planet. The feedbacks can drive the planet away from the initial state the civilization originated in and into domains that are detrimental to its sustainability. Our models conceptualize the problem primarily in terms of feedbacks from the resource use onto the coupled planetary systems. In addition, we also model the population growth advantages gained via the harvesting of these resources. We present three models of increasing complexity: (1) Civilization-planetary interaction with a single resource; (2) Civilization-planetary interaction with two resources each of which has a different level of planetary system feedback; (3) Civilization-planetary interaction with two resources and nonlinear planetary feedback (i.e., runaways). All three models show distinct classes of exo-civilization trajectories. We find smooth entries into long-term, "sustainable" steady states. We also find population booms followed by various levels of "die-off." Finally, we also observe rapid "collapse" trajectories for which the population approaches n = 0. Our results are part of a program for developing an "Astrobiology of the Anthropocene" in which questions of sustainability, centered on the coupled Earth-system, can be seen in their proper astronomical/planetary context. We conclude by discussing the implications of our results for both the coupled Earth system and for the consideration of exo-civilizations across cosmic history. Key Words: Anthropocene-Astrobiology-Civilization-Dynamical system theory-Exoplanets-Population dynamics. Astrobiology 18, 503-518.

PROM7: 1D modeler of solar filaments or prominences

NASA Astrophysics Data System (ADS)

Gouttebroze, P.

2018-05-01

PROM7 is an update of PROM4 (ascl:1306.004) and computes simple models of solar prominences and filaments using Partial Radiative Distribution (PRD). The models consist of plane-parallel slabs standing vertically above the solar surface. Each model is defined by 5 parameters: temperature, density, geometrical thickness, microturbulent velocity and height above the solar surface. It solves the equations of radiative transfer, statistical equilibrium, ionization and pressure equilibria, and computes electron and hydrogen level population and hydrogen line profiles. Moreover, the code treats calcium atom which is reduced to 3 ionization states (Ca I, Ca II, CA III). Ca II ion has 5 levels which are useful for computing 2 resonance lines (H and K) and infrared triplet (to 8500 A).

Exploring the effect of power law social popularity on language evolution.

PubMed

Gong, Tao; Shuai, Lan

2014-01-01

We evaluate the effect of a power-law-distributed social popularity on the origin and change of language, based on three artificial life models meticulously tracing the evolution of linguistic conventions including lexical items, categories, and simple syntax. A cross-model analysis reveals an optimal social popularity, in which the λ value of the power law distribution is around 1.0. Under this scaling, linguistic conventions can efficiently emerge and widely diffuse among individuals, thus maintaining a useful level of mutual understandability even in a big population. From an evolutionary perspective, we regard this social optimality as a tradeoff among social scaling, mutual understandability, and population growth. Empirical evidence confirms that such optimal power laws exist in many large-scale social systems that are constructed primarily via language-related interactions. This study contributes to the empirical explorations and theoretical discussions of the evolutionary relations between ubiquitous power laws in social systems and relevant individual behaviors.

Self-organization in Balanced State Networks by STDP and Homeostatic Plasticity

PubMed Central

Effenberger, Felix; Jost, Jürgen; Levina, Anna

2015-01-01

Structural inhomogeneities in synaptic efficacies have a strong impact on population response dynamics of cortical networks and are believed to play an important role in their functioning. However, little is known about how such inhomogeneities could evolve by means of synaptic plasticity. Here we present an adaptive model of a balanced neuronal network that combines two different types of plasticity, STDP and synaptic scaling. The plasticity rules yield both long-tailed distributions of synaptic weights and firing rates. Simultaneously, a highly connected subnetwork of driver neurons with strong synapses emerges. Coincident spiking activity of several driver cells can evoke population bursts and driver cells have similar dynamical properties as leader neurons found experimentally. Our model allows us to observe the delicate interplay between structural and dynamical properties of the emergent inhomogeneities. It is simple, robust to parameter changes and able to explain a multitude of different experimental findings in one basic network. PMID:26335425

The big challenges in modeling human and environmental well-being.

PubMed

Tuljapurkar, Shripad

2016-01-01

This article is a selective review of quantitative research, historical and prospective, that is needed to inform sustainable development policy. I start with a simple framework to highlight how demography and productivity shape human well-being. I use that to discuss three sets of issues and corresponding challenges to modeling: first, population prehistory and early human development and their implications for the future; second, the multiple distinct dimensions of human and environmental well-being and the meaning of sustainability; and, third, inequality as a phenomenon triggered by development and models to examine changing inequality and its consequences. I conclude with a few words about other important factors: political, institutional, and cultural.

Size-assortative mating and sexual size dimorphism are predictable from simple mechanics of mate-grasping behavior

PubMed Central

2010-01-01

Background A major challenge in evolutionary biology is to understand the typically complex interactions between diverse counter-balancing factors of Darwinian selection for size assortative mating and sexual size dimorphism. It appears that rarely a simple mechanism could provide a major explanation of these phenomena. Mechanics of behaviors can predict animal morphology, such like adaptations to locomotion in animals from various of taxa, but its potential to predict size-assortative mating and its evolutionary consequences has been less explored. Mate-grasping by males, using specialized adaptive morphologies of their forelegs, midlegs or even antennae wrapped around female body at specific locations, is a general mating strategy of many animals, but the contribution of the mechanics of this wide-spread behavior to the evolution of mating behavior and sexual size dimorphism has been largely ignored. Results Here, we explore the consequences of a simple, and previously ignored, fact that in a grasping posture the position of the male's grasping appendages relative to the female's body is often a function of body size difference between the sexes. Using an approach taken from robot mechanics we model coercive grasping of females by water strider Gerris gracilicornis males during mating initiation struggles. We determine that the male optimal size (relative to the female size), which gives the males the highest grasping force, properly predicts the experimentally measured highest mating success. Through field sampling and simulation modeling of a natural population we determine that the simple mechanical model, which ignores most of the other hypothetical counter-balancing selection pressures on body size, is sufficient to account for size-assortative mating pattern as well as species-specific sexual dimorphism in body size of G. gracilicornis. Conclusion The results indicate how a simple and previously overlooked physical mechanism common in many taxa is sufficient to account for, or importantly contribute to, size-assortative mating and its consequences for the evolution of sexual size dimorphism. PMID:21092131

Measuring the transmission dynamics of a sexually transmitted disease

PubMed Central

Ryder, Jonathan J.; Webberley, K. Mary; Boots, Michael; Knell, Robert J.

2005-01-01

Sexually transmitted diseases (STDs) occur throughout the animal kingdom and are generally thought to affect host population dynamics and evolution very differently from other directly transmitted infectious diseases. In particular, STDs are not thought to have threshold densities for persistence or to be able to regulate host population density independently; they may also have the potential to cause host extinction. However, these expectations follow from a theory that assumes that the rate of STD spread depends on the proportion (rather than the density) of individuals infected in a population. We show here that this key assumption (“frequency dependence”), which has not previously been tested in an animal STD system, is invalid in a simple and general experimental model. Transmission of an STD in the two-spot ladybird depended more on the density of infected individuals in the study population than on their frequency. We argue that, in this system, and in many other animal STDs in which population density affects sexual contact rate, population dynamics may exhibit some characteristics that are normally reserved for diseases with density-dependent transmission. PMID:16204382

Thermal and energetic constraints on ectotherm abundance: A global test using lizards

USGS Publications Warehouse

Buckley, L.B.; Rodda, G.H.; Jetz, W.

2008-01-01

Population densities of birds and mammals have been shown to decrease with body mass at approximately the same rate as metabolic rates increase, indicating that energetic needs constrain endotherm population densities. In ectotherms, the exponential increase of metabolic rate with body temperature suggests that environmental temperature may additionally constrain population densities. Here we test simple bioenergetic models for an ecologically important group of ectothermic vertebrates by examining 483 lizard populations. We find that lizard population densities decrease as a power law of body mass with a slope approximately inverse to the slope of the relationship between metabolic rates and body mass. Energy availability should limit population densities. As predicted, environmental productivity has a positive effect on lizard density, strengthening the relationship between lizard density and body mass. In contrast, the effect of environmental temperature is at most weak due to behavioral thermoregulation, thermal evolution, or the temperature dependence of ectotherm performance. Our results provide initial insights into how energy needs and availability differentially constrain ectotherm and endotherm density across broad spatial scales. ?? 2008 by the Ecological Society of America.

Thermal and energetic constraints on ectotherm abundance: a global test using lizards.

PubMed

Buckley, Lauren B; Rodda, Gordon H; Jetz, Walter

2008-01-01

Population densities of birds and mammals have been shown to decrease with body mass at approximately the same rate as metabolic rates increase, indicating that energetic needs constrain endotherm population densities. In ectotherms, the exponential increase of metabolic rate with body temperature suggests that environmental temperature may additionally constrain population densities. Here we test simple bioenergetic models for an ecologically important group of ectothermic vertebrates by examining 483 lizard populations. We find that lizard population densities decrease as a power law of body mass with a slope approximately inverse to the slope of the relationship between metabolic rates and body mass. Energy availability should limit population densities. As predicted, environmental productivity has a positive effect on lizard density, strengthening the relationship between lizard density and body mass. In contrast, the effect of environmental temperature is at most weak due to behavioral thermoregulation, thermal evolution, or the temperature dependence of ectotherm performance. Our results provide initial insights into how energy needs and availability differentially constrain ectotherm and endotherm density across broad spatial scales.

Invasion and Persistence of Infectious Agents in Fragmented Host Populations

PubMed Central

Jesse, Marieke; Mazzucco, Rupert; Dieckmann, Ulf; Heesterbeek, Hans; Metz, Johan A. J.

2011-01-01

One of the important questions in understanding infectious diseases and their prevention and control is how infectious agents can invade and become endemic in a host population. A ubiquitous feature of natural populations is that they are spatially fragmented, resulting in relatively homogeneous local populations inhabiting patches connected by the migration of hosts. Such fragmented population structures are studied extensively with metapopulation models. Being able to define and calculate an indicator for the success of invasion and persistence of an infectious agent is essential for obtaining general qualitative insights into infection dynamics, for the comparison of prevention and control scenarios, and for quantitative insights into specific systems. For homogeneous populations, the basic reproduction ratio plays this role. For metapopulations, defining such an ‘invasion indicator’ is not straightforward. Some indicators have been defined for specific situations, e.g., the household reproduction number . However, these existing indicators often fail to account for host demography and especially host migration. Here we show how to calculate a more broadly applicable indicator for the invasion and persistence of infectious agents in a host metapopulation of equally connected patches, for a wide range of possible epidemiological models. A strong feature of our method is that it explicitly accounts for host demography and host migration. Using a simple compartmental system as an example, we illustrate how can be calculated and expressed in terms of the key determinants of epidemiological dynamics. PMID:21980339

A Physics-Inspired Mechanistic Model of Migratory Movement Patterns in Birds.

PubMed

Revell, Christopher; Somveille, Marius

2017-08-29

In this paper, we introduce a mechanistic model of migratory movement patterns in birds, inspired by ideas and methods from physics. Previous studies have shed light on the factors influencing bird migration but have mainly relied on statistical correlative analysis of tracking data. Our novel method offers a bottom up explanation of population-level migratory movement patterns. It differs from previous mechanistic models of animal migration and enables predictions of pathways and destinations from a given starting location. We define an environmental potential landscape from environmental data and simulate bird movement within this landscape based on simple decision rules drawn from statistical mechanics. We explore the capacity of the model by qualitatively comparing simulation results to the non-breeding migration patterns of a seabird species, the Black-browed Albatross (Thalassarche melanophris). This minimal, two-parameter model was able to capture remarkably well the previously documented migration patterns of the Black-browed Albatross, with the best combination of parameter values conserved across multiple geographically separate populations. Our physics-inspired mechanistic model could be applied to other bird and highly-mobile species, improving our understanding of the relative importance of various factors driving migration and making predictions that could be useful for conservation.

Predicting regional variations in mortality from motor vehicle crashes.

PubMed

Clark, D E; Cushing, B M

1999-02-01

To show that the previously-observed inverse relationship between population density and per-capita mortality from motor vehicle crashes can be derived from a simple mathematical model that can be used for prediction. The authors proposed models in which the number of fatal crashes in an area was directly proportional to the population and also to some power of the mean distance between hospitals. Alternatively, these can be parameterized as Weibull survival models. Using county and state data from the U.S. Census, the authors fitted linear regression equations on a logarithmic scale to test the validity of these models. The southern states conformed to a different model from the other states. If an indicator variable was used to distinguish these groups, the resulting model accounted for 74% of the variation from state to state (Alaska excepted). After controlling for mean inter-hospital distance, the southern states had a per-capita mortality 1.37 times that of the other states. Simply knowing the mean distance between hospitals in a region allows a fiarly accurate estimate of its per-capita mortality from vehicle crashes. After controlling for this factor, vehicle crash mortality per capita is higher in the southern states, for reasons yet to be explained.

Sexual Reproduction in a Simple Growth Population Model

NASA Astrophysics Data System (ADS)

Lemos, Carlos Gentil Oro; Santos, Marcio

2012-05-01

One of the most important characteristics in the survival of a species is related to the kind of reproduction responsible for the offspring generation. However, only in the last years the role played by sexual reproduction has been investigated. Then, for a better understanding of this kind of process we introduce, in this work, a surface reaction model that describes the role of the sexual reproduction. In our model two different elements of the species, representing male and female, can interact to reproduce a new element. The sex of this new element is chosen with a given probability and in order to take into account the mortality rate we introduce another kind of individual. The value of the spatial density of this element remains constant during the time evolution of the system. The model is studied using Monte Carlo simulations and mean field approximation. Depending on the values of the control parameters of the model, the system can attain two stationary states: In one of them the population survives and in the other it can be extinguished. Besides, accordingly to our results, the phase diagram of the model shows a discontinuous transition between these two states.

A scoring model for predicting advanced colorectal neoplasia in a screened population of asymptomatic Japanese individuals.

PubMed

Sekiguchi, Masau; Kakugawa, Yasuo; Matsumoto, Minori; Matsuda, Takahisa

2018-01-22

Risk stratification of screened populations could help improve colorectal cancer (CRC) screening. Use of the modified Asia-Pacific Colorectal Screening (APCS) score has been proposed in the Asia-Pacific region. This study was performed to build a new useful scoring model for CRC screening. Data were reviewed from 5218 asymptomatic Japanese individuals who underwent their first screening colonoscopy. Multivariate logistic regression was used to investigate risk factors for advanced colorectal neoplasia (ACN), and a new scoring model for the prediction of ACN was developed based on the results. The discriminatory capability of the new model and the modified APCS score were assessed and compared. Internal validation was also performed. ACN was detected in 225 participants. An 8-point scoring model for the prediction of ACN was developed using five independent risk factors for ACN (male sex, higher age, presence of two or more first-degree relatives with CRC, body mass index of > 22.5 kg/m 2 , and smoking history of > 18.5 pack-years). The prevalence of ACN was 1.6% (34/2172), 5.3% (127/2419), and 10.2% (64/627) in participants with scores of < 3, ≥ 3 to < 5, and ≥ 5, respectively. The c-statistic of the scoring model was 0.70 (95% confidence interval, 0.67-0.73) in both the development and internal validation sets, and this value was higher than that of the modified APCS score [0.68 (95% confidence interval, 0.65-0.71), P = 0.03]. We built a new simple scoring model for prediction of ACN in a Japanese population that could stratify the screened population into low-, moderate-, and high-risk groups.

A model of interval timing by neural integration.

PubMed

Simen, Patrick; Balci, Fuat; de Souza, Laura; Cohen, Jonathan D; Holmes, Philip

2011-06-22

We show that simple assumptions about neural processing lead to a model of interval timing as a temporal integration process, in which a noisy firing-rate representation of time rises linearly on average toward a response threshold over the course of an interval. Our assumptions include: that neural spike trains are approximately independent Poisson processes, that correlations among them can be largely cancelled by balancing excitation and inhibition, that neural populations can act as integrators, and that the objective of timed behavior is maximal accuracy and minimal variance. The model accounts for a variety of physiological and behavioral findings in rodents, monkeys, and humans, including ramping firing rates between the onset of reward-predicting cues and the receipt of delayed rewards, and universally scale-invariant response time distributions in interval timing tasks. It furthermore makes specific, well-supported predictions about the skewness of these distributions, a feature of timing data that is usually ignored. The model also incorporates a rapid (potentially one-shot) duration-learning procedure. Human behavioral data support the learning rule's predictions regarding learning speed in sequences of timed responses. These results suggest that simple, integration-based models should play as prominent a role in interval timing theory as they do in theories of perceptual decision making, and that a common neural mechanism may underlie both types of behavior.

A complex speciation–richness relationship in a simple neutral model

PubMed Central

Desjardins-Proulx, Philippe; Gravel, Dominique

2012-01-01

Speciation is the “elephant in the room” of community ecology. As the ultimate source of biodiversity, its integration in ecology's theoretical corpus is necessary to understand community assembly. Yet, speciation is often completely ignored or stripped of its spatial dimension. Recent approaches based on network theory have allowed ecologists to effectively model complex landscapes. In this study, we use this framework to model allopatric and parapatric speciation in networks of communities. We focus on the relationship between speciation, richness, and the spatial structure of communities. We find a strong opposition between speciation and local richness, with speciation being more common in isolated communities and local richness being higher in more connected communities. Unlike previous models, we also find a transition to a positive relationship between speciation and local richness when dispersal is low and the number of communities is small. We use several measures of centrality to characterize the effect of network structure on diversity. The degree, the simplest measure of centrality, is the best predictor of local richness and speciation, although it loses some of its predictive power as connectivity grows. Our framework shows how a simple neutral model can be combined with network theory to reveal complex relationships between speciation, richness, and the spatial organization of populations. PMID:22957181

Estimating the impact of oyster restoration scenarios on transient fish production

USGS Publications Warehouse

McCoy, Elizabeth; Borrett, Stuart R.; LaPeyre, Megan K.; Peterson, Bradley J.

2017-01-01

Oyster reef restoration projects are increasing in number both to enhance oyster density and to retain valuable ecosystem services provided by oyster reefs. Although some oyster restoration projects have demonstrated success by increasing density and biomass of transient fish, it still remains a challenge to quantify the effects of oyster restoration on transient fish communities. We developed a bioenergetics model to assess the impact of selected oyster reef restoration scenarios on associated transient fish species. We used the model to analyze the impact of changes in (1) oyster population carrying capacity; (2) oyster population growth rate; and (3) diet preference of transient fish on oyster reef development and associated transient fish species. Our model results indicate that resident fish biomass is directly affected by oyster restoration and oyster biomass, and oyster restoration can have cascading impacts on transient fish biomass. Furthermore, the results highlight the importance of a favorable oyster population growth rate during early restoration years, as it can lead to rapid increases in mean oyster biomass and biomass of transient fish species. The model also revealed that a transient fish's diet solely dependent on oyster reef-derived prey could limit the biomass of transient fish species, emphasizing the importance of habitat connectivity in estuarine areas to enhance transient fish species biomass. Simple bioenergetics models can be developed to understand the dynamics of a system and make qualitative predictions of management and restoration scenarios.

Degeneracy-Driven Self-Structuring Dynamics in Selective Repertoires

PubMed Central

Atamas, Sergei P.; Bell, Jonathan

2013-01-01

Numerous biological interactions, such as interactions between T cell receptors or antibodies with antigens, interactions between enzymes and substrates, or interactions between predators and prey are often not strictly specific. In such less specific, or “sloppy,” systems, referred to here as degenerate systems, a given unit of a diverse resource (antigens, enzymatic substrates, prey) is at risk of being recognized and consumed by multiple consumers (lymphocytes, enzymes, predators). In this study, we model generalized degenerate consumer-resource systems of Lotka–Volterra and Verhulst types. In the degenerate systems of Lotka–Volterra, there is a continuum of types of consumer and resource based on variation of a single trait (characteristic, or preference). The consumers experience competition for a continuum of resource types. This non-local interaction system is modeled with partial differential-integral equations and shows spontaneous self-structuring of the consumer population that depends on the degree of interaction degeneracy between resource and consumer, but does not mirror the distribution of resource. We also show that the classical Verhulst (i.e. logistic) single population model can be generalized to a degenerate model, which shows qualitative behavior similar to that in the degenerate Lotka–Volterra model. These results provide better insight into the dynamics of selective systems in biology, suggesting that adaptation of degenerate repertoires is not a simple “mirroring” of the environment by the “fittest” elements of population. PMID:19337776

Degeneracy-driven self-structuring dynamics in selective repertoires.

PubMed

Atamas, Sergei P; Bell, Jonathan

2009-08-01

Numerous biological interactions, such as interactions between T cell receptors or antibodies with antigens, interactions between enzymes and substrates, or interactions between predators and prey are often not strictly specific. In such less specific, or "sloppy," systems, referred to here as degenerate systems, a given unit of a diverse resource (antigens, enzymatic substrates, prey) is at risk of being recognized and consumed by multiple consumers (lymphocytes, enzymes, predators). In this study, we model generalized degenerate consumer-resource systems of Lotka-Volterra and Verhulst types. In the degenerate systems of Lotka-Volterra, there is a continuum of types of consumer and resource based on variation of a single trait (characteristic, or preference). The consumers experience competition for a continuum of resource types. This non-local interaction system is modeled with partial differential-integral equations and shows spontaneous self-structuring of the consumer population that depends on the degree of interaction degeneracy between resource and consumer, but does not mirror the distribution of resource. We also show that the classical Verhulst (i.e. logistic) single population model can be generalized to a degenerate model, which shows qualitative behavior similar to that in the degenerate Lotka-Volterra model. These results provide better insight into the dynamics of selective systems in biology, suggesting that adaptation of degenerate repertoires is not a simple "mirroring" of the environment by the "fittest" elements of population.

Human judgment vs. quantitative models for the management of ecological resources.

PubMed

Holden, Matthew H; Ellner, Stephen P

2016-07-01

Despite major advances in quantitative approaches to natural resource management, there has been resistance to using these tools in the actual practice of managing ecological populations. Given a managed system and a set of assumptions, translated into a model, optimization methods can be used to solve for the most cost-effective management actions. However, when the underlying assumptions are not met, such methods can potentially lead to decisions that harm the environment and economy. Managers who develop decisions based on past experience and judgment, without the aid of mathematical models, can potentially learn about the system and develop flexible management strategies. However, these strategies are often based on subjective criteria and equally invalid and often unstated assumptions. Given the drawbacks of both methods, it is unclear whether simple quantitative models improve environmental decision making over expert opinion. In this study, we explore how well students, using their experience and judgment, manage simulated fishery populations in an online computer game and compare their management outcomes to the performance of model-based decisions. We consider harvest decisions generated using four different quantitative models: (1) the model used to produce the simulated population dynamics observed in the game, with the values of all parameters known (as a control), (2) the same model, but with unknown parameter values that must be estimated during the game from observed data, (3) models that are structurally different from those used to simulate the population dynamics, and (4) a model that ignores age structure. Humans on average performed much worse than the models in cases 1-3, but in a small minority of scenarios, models produced worse outcomes than those resulting from students making decisions based on experience and judgment. When the models ignored age structure, they generated poorly performing management decisions, but still outperformed students using experience and judgment 66% of the time. © 2016 by the Ecological Society of America.

Scaling laws describe memories of host-pathogen riposte in the HIV population.

PubMed

Barton, John P; Kardar, Mehran; Chakraborty, Arup K

2015-02-17

The enormous genetic diversity and mutability of HIV has prevented effective control of this virus by natural immune responses or vaccination. Evolution of the circulating HIV population has thus occurred in response to diverse, ultimately ineffective, immune selection pressures that randomly change from host to host. We show that the interplay between the diversity of human immune responses and the ways that HIV mutates to evade them results in distinct sets of sequences defined by similar collectively coupled mutations. Scaling laws that relate these sets of sequences resemble those observed in linguistics and other branches of inquiry, and dynamics reminiscent of neural networks are observed. Like neural networks that store memories of past stimulation, the circulating HIV population stores memories of host-pathogen combat won by the virus. We describe an exactly solvable model that captures the main qualitative features of the sets of sequences and a simple mechanistic model for the origin of the observed scaling laws. Our results define collective mutational pathways used by HIV to evade human immune responses, which could guide vaccine design.

Simple anthropometrics are more correlated with health variables than are estimates of body composition in Yup'ik people.

PubMed

Bray, Maria; Pomeroy, Jeremy; Knowler, William C; Bersamin, Andrea; Hopkins, Scarlett; Brage, Søren; Stanhope, Kimber; Havel, Peter J; Boyer, Bert B

2013-09-01

To (1) evaluate the relationships between several indices of obesity with obesity-related risk factors; (2) compare the accuracy of body composition estimates derived from anthropometry and bioimpedance analysis (BIA) to estimates of body composition assessed by doubly-labeled water (DLW); and (3) establish equations for estimating fat mass (FM), fat-free mass (FFM), and percent body fat (PBF) in Yup'ik people. Participants included 1,056 adult Yup'ik people from 11 communities in Southwestern Alaska. In a sub-study of 30 participants, we developed population-specific linear regression models for estimating FM, FFM, and PBF from anthropometrics, age, sex, and BIA against criterion measures derived from total body water assessed with DLW. These models were then used with the population cohort and we analyzed the relationships between obesity indices and several health-related and disease status variables: (1) fasting plasma lipids, (2) glucose, (3) HbA1c, (4) adiponectin, (5) blood pressure, (6) diabetes (DM), and (7) cerebrocoronary vascular disease (CCVD) which includes stroke and heart disease. The best model for estimating FM in the sub-study used only three variables-sex, waist circumference (WC), and hip circumference and had multiple R(2) = 0.9730. FFM and PBF were calculated from FM and body weight. WC and other anthropometrics were more highly correlated with a number of obesity-related risk factors than were direct estimates of body composition. Body composition in Yup'ik people can be accurately estimated from simple anthropometrics. Copyright © 2012 The Obesity Society.

Simple Anthropometrics Are More Correlated with Health Variables than Are Estimates of Body Composition in Yup’ik People

PubMed Central

Bray, Maria; Pomeroy, Jeremy; Knowler, William C.; Bersamin, Andrea; Hopkins, Scarlett; Brage, Søren; Stanhope, Kimber; Havel, Peter J.; Boyer, Bert B.

2012-01-01

We aimed to: 1) evaluate the relationships between several indices of obesity with obesity-related risk factors; 2) compare the accuracy of body composition estimates derived from anthropometry and bioimpedance analysis (BIA) to estimates of body composition assessed by doubly-labeled water (DLW); and 3) establish equations for estimating fat mass (FM), fat-free mass (FFM), and percent body fat (PBF) in Yup’ik Eskimo people. Participants included 1056 adult Yup’ik People from 11 communities in Southwestern Alaska. In a substudy of 30 participants, we developed population-specific linear regression models for estimating FM, FFM, and PBF from anthropometrics, age, sex, and BIA against criterion measures derived from total body water assessed with DLW. These models were then used with the population cohort and we analyzed the relationships between obesity indices and several health-related and disease status variables: 1. fasting plasma lipids, 2. glucose, 3. HbA1c, 4. adiponectin, 5. blood pressure, 6) diabetes (DM), and 7) cerebrocoronary vascular disease (CCVD) which includes stroke and heart disease. The best model for estimating FM in the substudy used only three variables – sex, waist circumference (WC), and hip circumference and had multiple R2=0.9730. FFM and PBF were calculated from FM and body weight. WC and other anthropometrics were more highly correlated with a number of obesity-related risk factors than were direct estimates of body composition. We conclude that body composition in Yup’ik People can be accurately estimated from simple anthropometrics. PMID:23666898

Long-Distance Dispersal Shaped Patterns of Human Genetic Diversity in Eurasia.

PubMed

Alves, Isabel; Arenas, Miguel; Currat, Mathias; Sramkova Hanulova, Anna; Sousa, Vitor C; Ray, Nicolas; Excoffier, Laurent

2016-04-01

Most previous attempts at reconstructing the past history of human populations did not explicitly take geography into account or considered very simple scenarios of migration and ignored environmental information. However, it is likely that the last glacial maximum (LGM) affected the demography and the range of many species, including our own. Moreover, long-distance dispersal (LDD) may have been an important component of human migrations, allowing fast colonization of new territories and preserving high levels of genetic diversity. Here, we use a high-quality microsatellite data set genotyped in 22 populations to estimate the posterior probabilities of several scenarios for the settlement of the Old World by modern humans. We considered models ranging from a simple spatial expansion to others including LDD and a LGM-induced range contraction, as well as Neolithic demographic expansions. We find that scenarios with LDD are much better supported by data than models without LDD. Nevertheless, we show evidence that LDD events to empty habitats were strongly prevented during the settlement of Eurasia. This unexpected absence of LDD ahead of the colonization wave front could have been caused by an Allee effect, either due to intrinsic causes such as an inbreeding depression built during the expansion or due to extrinsic causes such as direct competition with archaic humans. Overall, our results suggest only a relatively limited effect of the LGM contraction on current patterns of human diversity. This is in clear contrast with the major role of LDD migrations, which have potentially contributed to the intermingled genetic structure of Eurasian populations. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Cardiovascular and other causes of death as a function of lifestyle habits in a quasi extinct middle-aged male population. A 50-year follow-up study.

PubMed

Menotti, Alessandro; Puddu, Paolo Emilio; Maiani, Giuseppe; Catasta, Giovina

2016-05-01

To relate major causes of death with lifestyle habits in an almost extinct male middle-aged population. A 40-59 aged male population of 1712 subjects was examined and followed-up for 50 years. Baseline smoking habits, working physical activity and dietary habits were related to 50 years mortality subdivided into 12 simple and 3 composite causes of death by Cox proportional hazard models. Duration of survival was related to the same characteristics by a multiple linear regression model. Death rate in 50 years was of 97.5%. Out of 12 simple groups of causes of death, 6 were related to smoking habits, 3 to physical activity and 4 to dietary habits. Among composite groups of causes of death, hazard ratios (and their 95% confidence limits) of never smokers versus smokers were 0.68 (0.57-0.81) for major cardiovascular diseases; 0.65 (0.52-0.81) for all cancers; and 0.72 (0.64-0.81) for all-cause deaths. Hazard ratios of vigorous physical activity at work versus sedentary physical activity were 0.63 (0.49-0.80) for major cardiovascular diseases; 1.01 (0.72-1.41) for all cancers; and 0.76 (0.64-0.90) for all-cause deaths. Hazard ratios of Mediterranean Diet versus non-Mediterranean Diet were 0.68 (0.54-0.86) for major cardiovascular diseases; 0.54 (0.40-0.73) for all cancers; and 0.67 (0.57-0.78) for all-cause deaths. Expectancy of life was 12 years longer for men with the 3 best behaviors than for those with the 3 worst behaviors. Some lifestyle habits are strongly related to lifetime mortality. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Inferring Fitness Effects from Time-Resolved Sequence Data with a Delay-Deterministic Model

PubMed Central

Nené, Nuno R.; Dunham, Alistair S.; Illingworth, Christopher J. R.

2018-01-01

A common challenge arising from the observation of an evolutionary system over time is to infer the magnitude of selection acting upon a specific genetic variant, or variants, within the population. The inference of selection may be confounded by the effects of genetic drift in a system, leading to the development of inference procedures to account for these effects. However, recent work has suggested that deterministic models of evolution may be effective in capturing the effects of selection even under complex models of demography, suggesting the more general application of deterministic approaches to inference. Responding to this literature, we here note a case in which a deterministic model of evolution may give highly misleading inferences, resulting from the nondeterministic properties of mutation in a finite population. We propose an alternative approach that acts to correct for this error, and which we denote the delay-deterministic model. Applying our model to a simple evolutionary system, we demonstrate its performance in quantifying the extent of selection acting within that system. We further consider the application of our model to sequence data from an evolutionary experiment. We outline scenarios in which our model may produce improved results for the inference of selection, noting that such situations can be easily identified via the use of a regular deterministic model. PMID:29500183

The galaxy clustering crisis in abundance matching

NASA Astrophysics Data System (ADS)

Campbell, Duncan; van den Bosch, Frank C.; Padmanabhan, Nikhil; Mao, Yao-Yuan; Zentner, Andrew R.; Lange, Johannes U.; Jiang, Fangzhou; Villarreal, Antonio

2018-06-01

Galaxy clustering on small scales is significantly underpredicted by sub-halo abundance matching (SHAM) models that populate (sub-)haloes with galaxies based on peak halo mass, Mpeak. SHAM models based on the peak maximum circular velocity, Vpeak, have had much better success. The primary reason for Mpeak-based models fail is the relatively low abundance of satellite galaxies produced in these models compared to those based on Vpeak. Despite success in predicting clustering, a simple Vpeak-based SHAM model results in predictions for galaxy growth that are at odds with observations. We evaluate three possible remedies that could `save' mass-based SHAM: (1) SHAM models require a significant population of `orphan' galaxies as a result of artificial disruption/merging of sub-haloes in modern high-resolution dark matter simulations; (2) satellites must grow significantly after their accretion; and (3) stellar mass is significantly affected by halo assembly history. No solution is entirely satisfactory. However, regardless of the particulars, we show that popular SHAM models based on Mpeak cannot be complete physical models as presented. Either Vpeak truly is a better predictor of stellar mass at z ˜ 0 and it remains to be seen how the correlation between stellar mass and Vpeak comes about, or SHAM models are missing vital component(s) that significantly affect galaxy clustering.

Adjusting for overdispersion in piecewise exponential regression models to estimate excess mortality rate in population-based research.

PubMed

Luque-Fernandez, Miguel Angel; Belot, Aurélien; Quaresma, Manuela; Maringe, Camille; Coleman, Michel P; Rachet, Bernard

2016-10-01

In population-based cancer research, piecewise exponential regression models are used to derive adjusted estimates of excess mortality due to cancer using the Poisson generalized linear modelling framework. However, the assumption that the conditional mean and variance of the rate parameter given the set of covariates x i are equal is strong and may fail to account for overdispersion given the variability of the rate parameter (the variance exceeds the mean). Using an empirical example, we aimed to describe simple methods to test and correct for overdispersion. We used a regression-based score test for overdispersion under the relative survival framework and proposed different approaches to correct for overdispersion including a quasi-likelihood, robust standard errors estimation, negative binomial regression and flexible piecewise modelling. All piecewise exponential regression models showed the presence of significant inherent overdispersion (p-value <0.001). However, the flexible piecewise exponential model showed the smallest overdispersion parameter (3.2 versus 21.3) for non-flexible piecewise exponential models. We showed that there were no major differences between methods. However, using a flexible piecewise regression modelling, with either a quasi-likelihood or robust standard errors, was the best approach as it deals with both, overdispersion due to model misspecification and true or inherent overdispersion.

How pattern formation in ring networks of excitatory and inhibitory spiking neurons depends on the input current regime.

PubMed

Kriener, Birgit; Helias, Moritz; Rotter, Stefan; Diesmann, Markus; Einevoll, Gaute T

2013-01-01

Pattern formation, i.e., the generation of an inhomogeneous spatial activity distribution in a dynamical system with translation invariant structure, is a well-studied phenomenon in neuronal network dynamics, specifically in neural field models. These are population models to describe the spatio-temporal dynamics of large groups of neurons in terms of macroscopic variables such as population firing rates. Though neural field models are often deduced from and equipped with biophysically meaningful properties, a direct mapping to simulations of individual spiking neuron populations is rarely considered. Neurons have a distinct identity defined by their action on their postsynaptic targets. In its simplest form they act either excitatorily or inhibitorily. When the distribution of neuron identities is assumed to be periodic, pattern formation can be observed, given the coupling strength is supracritical, i.e., larger than a critical weight. We find that this critical weight is strongly dependent on the characteristics of the neuronal input, i.e., depends on whether neurons are mean- or fluctuation driven, and different limits in linearizing the full non-linear system apply in order to assess stability. In particular, if neurons are mean-driven, the linearization has a very simple form and becomes independent of both the fixed point firing rate and the variance of the input current, while in the very strongly fluctuation-driven regime the fixed point rate, as well as the input mean and variance are important parameters in the determination of the critical weight. We demonstrate that interestingly even in "intermediate" regimes, when the system is technically fluctuation-driven, the simple linearization neglecting the variance of the input can yield the better prediction of the critical coupling strength. We moreover analyze the effects of structural randomness by rewiring individual synapses or redistributing weights, as well as coarse-graining on the formation of inhomogeneous activity patterns.

How pattern formation in ring networks of excitatory and inhibitory spiking neurons depends on the input current regime

PubMed Central

Kriener, Birgit; Helias, Moritz; Rotter, Stefan; Diesmann, Markus; Einevoll, Gaute T.

2014-01-01

Pattern formation, i.e., the generation of an inhomogeneous spatial activity distribution in a dynamical system with translation invariant structure, is a well-studied phenomenon in neuronal network dynamics, specifically in neural field models. These are population models to describe the spatio-temporal dynamics of large groups of neurons in terms of macroscopic variables such as population firing rates. Though neural field models are often deduced from and equipped with biophysically meaningful properties, a direct mapping to simulations of individual spiking neuron populations is rarely considered. Neurons have a distinct identity defined by their action on their postsynaptic targets. In its simplest form they act either excitatorily or inhibitorily. When the distribution of neuron identities is assumed to be periodic, pattern formation can be observed, given the coupling strength is supracritical, i.e., larger than a critical weight. We find that this critical weight is strongly dependent on the characteristics of the neuronal input, i.e., depends on whether neurons are mean- or fluctuation driven, and different limits in linearizing the full non-linear system apply in order to assess stability. In particular, if neurons are mean-driven, the linearization has a very simple form and becomes independent of both the fixed point firing rate and the variance of the input current, while in the very strongly fluctuation-driven regime the fixed point rate, as well as the input mean and variance are important parameters in the determination of the critical weight. We demonstrate that interestingly even in “intermediate” regimes, when the system is technically fluctuation-driven, the simple linearization neglecting the variance of the input can yield the better prediction of the critical coupling strength. We moreover analyze the effects of structural randomness by rewiring individual synapses or redistributing weights, as well as coarse-graining on the formation of inhomogeneous activity patterns. PMID:24501591

Geographical parthenogenesis and population genetic structure in the alpine species Ranunculus kuepferi (Ranunculaceae).

PubMed

Cosendai, A-C; Wagner, J; Ladinig, U; Rosche, C; Hörandl, E

2013-06-01

Geographical parthenogenesis describes the enigmatic phenomenon that asexual organisms have larger distribution areas than their sexual relatives, especially in previously glaciated areas. Classical models suggest temporary advantages to asexuality in colonization scenarios because of uniparental reproduction and clonality. We analyzed population genetic structure and self-fertility of the plant species Ranunculus kuepferi on 59 populations from the whole distribution area (European Alps, Apennines and Corsica). Amplified fragment length polymorphisms (AFLPs) and five microsatellite loci revealed individual genotypes for all populations and mostly insignificant differences between diploid sexuals and tetraploid apomicts in all measures of genetic diversity. Low frequencies of private AFLP fragments/simple sequence repeat alleles, and character incompatibility analyses suggest that facultative recombination explains best the unexpectedly high genotypic diversity of apomicts. STRUCTURE analyses using AFLPs revealed a higher number of partitions and a stronger geographical subdivision for diploids than for tetraploids, which contradicts expectations of standard gene flow models, but indicates a reduction of genetic structure in asexuals. Apomictic populations exhibited high admixture near the sexual area, but appeared rather uniform in remote areas. Bagging experiments and analyses of pollen tube growth confirmed self-fertility for pollen-dependent apomicts, but self-sterility for diploid sexuals. Facultative apomixis combines advantages of both modes of reproduction: uniparental reproduction allows for rapid colonization of remote areas, whereas facultative sexuality and polyploidy maintains genetic diversity within apomictic populations. The density dependence of outcrossing limits range expansions of sexual populations.

Geographical parthenogenesis and population genetic structure in the alpine species Ranunculus kuepferi (Ranunculaceae)

PubMed Central

Cosendai, A-C; Wagner, J; Ladinig, U; Rosche, C; Hörandl, E

2013-01-01

Geographical parthenogenesis describes the enigmatic phenomenon that asexual organisms have larger distribution areas than their sexual relatives, especially in previously glaciated areas. Classical models suggest temporary advantages to asexuality in colonization scenarios because of uniparental reproduction and clonality. We analyzed population genetic structure and self-fertility of the plant species Ranunculus kuepferi on 59 populations from the whole distribution area (European Alps, Apennines and Corsica). Amplified fragment length polymorphisms (AFLPs) and five microsatellite loci revealed individual genotypes for all populations and mostly insignificant differences between diploid sexuals and tetraploid apomicts in all measures of genetic diversity. Low frequencies of private AFLP fragments/simple sequence repeat alleles, and character incompatibility analyses suggest that facultative recombination explains best the unexpectedly high genotypic diversity of apomicts. STRUCTURE analyses using AFLPs revealed a higher number of partitions and a stronger geographical subdivision for diploids than for tetraploids, which contradicts expectations of standard gene flow models, but indicates a reduction of genetic structure in asexuals. Apomictic populations exhibited high admixture near the sexual area, but appeared rather uniform in remote areas. Bagging experiments and analyses of pollen tube growth confirmed self-fertility for pollen-dependent apomicts, but self-sterility for diploid sexuals. Facultative apomixis combines advantages of both modes of reproduction: uniparental reproduction allows for rapid colonization of remote areas, whereas facultative sexuality and polyploidy maintains genetic diversity within apomictic populations. The density dependence of outcrossing limits range expansions of sexual populations. PMID:23403961

Genetic Variation and Population Differentiation in a Medical Herb Houttuynia cordata in China Revealed by Inter-Simple Sequence Repeats (ISSRs)

PubMed Central

Wei, Lin; Wu, Xian-Jin

2012-01-01

Houttuynia cordata is an important traditional Chinese herb with unresolved genetics and taxonomy, which lead to potential problems in the conservation and utilization of the resource. Inter-simple sequence repeat (ISSR) markers were used to assess the level and distribution of genetic diversity in 226 individuals from 15 populations of H. cordata in China. ISSR analysis revealed low genetic variations within populations but high genetic differentiations among populations. This genetic structure probably mainly reflects the historical association among populations. Genetic cluster analysis showed that the basal clade is composed of populations from Southwest China, and the other populations have continuous and eastward distributions. The structure of genetic diversity in H. cordata demonstrated that this species might have survived in Southwest China during the glacial age, and subsequently experienced an eastern postglacial expansion. Based on the results of genetic analysis, it was proposed that as many as possible targeted populations for conservation be included. PMID:22942696

Genetic variation and population differentiation in a medical herb Houttuynia cordata in China revealed by inter-simple sequence repeats (ISSRs).

PubMed

Wei, Lin; Wu, Xian-Jin

2012-01-01

Houttuynia cordata is an important traditional Chinese herb with unresolved genetics and taxonomy, which lead to potential problems in the conservation and utilization of the resource. Inter-simple sequence repeat (ISSR) markers were used to assess the level and distribution of genetic diversity in 226 individuals from 15 populations of H. cordata in China. ISSR analysis revealed low genetic variations within populations but high genetic differentiations among populations. This genetic structure probably mainly reflects the historical association among populations. Genetic cluster analysis showed that the basal clade is composed of populations from Southwest China, and the other populations have continuous and eastward distributions. The structure of genetic diversity in H. cordata demonstrated that this species might have survived in Southwest China during the glacial age, and subsequently experienced an eastern postglacial expansion. Based on the results of genetic analysis, it was proposed that as many as possible targeted populations for conservation be included.

A large-scale survey of genetic copy number variations among Han Chinese residing in Taiwan

PubMed Central

Lin, Chien-Hsing; Li, Ling-Hui; Ho, Sheng-Feng; Chuang, Tzu-Po; Wu, Jer-Yuarn; Chen, Yuan-Tsong; Fann, Cathy SJ

2008-01-01

Background Copy number variations (CNVs) have recently been recognized as important structural variations in the human genome. CNVs can affect gene expression and thus may contribute to phenotypic differences. The copy number inferring tool (CNIT) is an effective hidden Markov model-based algorithm for estimating allele-specific copy number and predicting chromosomal alterations from single nucleotide polymorphism microarrays. The CNIT algorithm, which was constructed using data from 270 HapMap multi-ethnic individuals, was applied to identify CNVs from 300 unrelated Han Chinese individuals in Taiwan. Results Using stringent selection criteria, 230 regions with variable copy numbers were identified in the Han Chinese population; 133 (57.83%) had been reported previously, 64 displayed greater than 1% CNV allele frequency. The average size of the CNV regions was 322 kb (ranging from 1.48 kb to 5.68 Mb) and covered a total of 2.47% of the human genome. A total of 196 of the CNV regions were simple deletions and 27 were simple amplifications. There were 449 genes and 5 microRNAs within these CNV regions; some of these genes are known to be associated with diseases. Conclusion The identified CNVs are characteristic of the Han Chinese population and should be considered when genetic studies are conducted. The CNV distribution in the human genome is still poorly characterized, and there is much diversity among different ethnic populations. PMID:19108714

Visualizing diurnal population change in urban areas for emergency management.

PubMed

Kobayashi, Tetsuo; Medina, Richard M; Cova, Thomas J

2011-01-01

There is an increasing need for a quick, simple method to represent diurnal population change in metropolitan areas for effective emergency management and risk analysis. Many geographic studies rely on decennial U.S. Census data that assume that urban populations are static in space and time. This has obvious limitations in the context of dynamic geographic problems. The U.S. Department of Transportation publishes population data at the transportation analysis zone level in fifteen-minute increments. This level of spatial and temporal detail allows for improved dynamic population modeling. This article presents a methodology for visualizing and analyzing diurnal population change for metropolitan areas based on this readily available data. Areal interpolation within a geographic information system is used to create twenty-four (one per hour) population surfaces for the larger metropolitan area of Salt Lake County, Utah. The resulting surfaces represent diurnal population change for an average workday and are easily combined to produce an animation that illustrates population dynamics throughout the day. A case study of using the method to visualize population distributions in an emergency management context is provided using two scenarios: a chemical release and a dirty bomb in Salt Lake County. This methodology can be used to address a wide variety of problems in emergency management.

IVGTT-based simple assessment of glucose tolerance in the Zucker fatty rat: Validation against minimal models.

PubMed

Morettini, Micaela; Faelli, Emanuela; Perasso, Luisa; Fioretti, Sandro; Burattini, Laura; Ruggeri, Piero; Di Nardo, Francesco

2017-01-01

For the assessment of glucose tolerance from IVGTT data in Zucker rat, minimal model methodology is reliable but time- and money-consuming. This study aimed to validate for the first time in Zucker rat, simple surrogate indexes of insulin sensitivity and secretion against the glucose-minimal-model insulin sensitivity index (SI) and against first- (Φ1) and second-phase (Φ2) β-cell responsiveness indexes provided by C-peptide minimal model. Validation of the surrogate insulin sensitivity index (ISI) and of two sets of coupled insulin-based indexes for insulin secretion, differing from the cut-off point between phases (FPIR3-SPIR3, t = 3 min and FPIR5-SPIR5, t = 5 min), was carried out in a population of ten Zucker fatty rats (ZFR) and ten Zucker lean rats (ZLR). Considering the whole rat population (ZLR+ZFR), ISI showed a significant strong correlation with SI (Spearman's correlation coefficient, r = 0.88; P<0.001). Both FPIR3 and FPIR5 showed a significant (P<0.001) strong correlation with Φ1 (r = 0.76 and r = 0.75, respectively). Both SPIR3 and SPIR5 showed a significant (P<0.001) strong correlation with Φ2 (r = 0.85 and r = 0.83, respectively). ISI is able to detect (P<0.001) the well-recognized reduction in insulin sensitivity in ZFRs, compared to ZLRs. The insulin-based indexes of insulin secretion are able to detect in ZFRs (P<0.001) the compensatory increase of first- and second-phase secretion, associated to the insulin-resistant state. The ability of the surrogate indexes in describing glucose tolerance in the ZFRs was confirmed by the Disposition Index analysis. The model-based validation performed in the present study supports the utilization of low-cost, insulin-based indexes for the assessment of glucose tolerance in Zucker rat, reliable animal model of human metabolic syndrome.

Disease-induced mortality in density-dependent discrete-time S-I-S epidemic models.

PubMed

Franke, John E; Yakubu, Abdul-Aziz

2008-12-01

The dynamics of simple discrete-time epidemic models without disease-induced mortality are typically characterized by global transcritical bifurcation. We prove that in corresponding models with disease-induced mortality a tiny number of infectious individuals can drive an otherwise persistent population to extinction. Our model with disease-induced mortality supports multiple attractors. In addition, we use a Ricker recruitment function in an SIS model and obtained a three component discrete Hopf (Neimark-Sacker) cycle attractor coexisting with a fixed point attractor. The basin boundaries of the coexisting attractors are fractal in nature, and the example exhibits sensitive dependence of the long-term disease dynamics on initial conditions. Furthermore, we show that in contrast to corresponding models without disease-induced mortality, the disease-free state dynamics do not drive the disease dynamics.

Parameter Estimation in Epidemiology: from Simple to Complex Dynamics

NASA Astrophysics Data System (ADS)

Aguiar, Maíra; Ballesteros, Sebastién; Boto, João Pedro; Kooi, Bob W.; Mateus, Luís; Stollenwerk, Nico

2011-09-01

We revisit the parameter estimation framework for population biological dynamical systems, and apply it to calibrate various models in epidemiology with empirical time series, namely influenza and dengue fever. When it comes to more complex models like multi-strain dynamics to describe the virus-host interaction in dengue fever, even most recently developed parameter estimation techniques, like maximum likelihood iterated filtering, come to their computational limits. However, the first results of parameter estimation with data on dengue fever from Thailand indicate a subtle interplay between stochasticity and deterministic skeleton. The deterministic system on its own already displays complex dynamics up to deterministic chaos and coexistence of multiple attractors.

Stochastic epidemic outbreaks: why epidemics are like lasers

NASA Astrophysics Data System (ADS)

Schwartz, Ira B.; Billings, Lora

2004-05-01

Many diseases, such as childhood diseases, dengue fever, and West Nile virus, appear to oscillate randomly as a function of seasonal environmental or social changes. Such oscillations appear to have a chaotic bursting character, although it is still uncertain how much is due to random fluctuations. Such bursting in the presence of noise is also observed in driven lasers. In this talk, I will show how noise can excite random outbreaks in simple models of seasonally driven outbreaks, as well as lasers. The models for both population dynamics will be shown to share the same class of underlying topology, which plays a major role in the cause of observed stochastic bursting.

Improving the Rank Precision of Population Health Measures for Small Areas with Longitudinal and Joint Outcome Models

PubMed Central

Athens, Jessica K.; Remington, Patrick L.; Gangnon, Ronald E.

2015-01-01

Objectives The University of Wisconsin Population Health Institute has published the County Health Rankings since 2010. These rankings use population-based data to highlight health outcomes and the multiple determinants of these outcomes and to encourage in-depth health assessment for all United States counties. A significant methodological limitation, however, is the uncertainty of rank estimates, particularly for small counties. To address this challenge, we explore the use of longitudinal and pooled outcome data in hierarchical Bayesian models to generate county ranks with greater precision. Methods In our models we used pooled outcome data for three measure groups: (1) Poor physical and poor mental health days; (2) percent of births with low birth weight and fair or poor health prevalence; and (3) age-specific mortality rates for nine age groups. We used the fixed and random effects components of these models to generate posterior samples of rates for each measure. We also used time-series data in longitudinal random effects models for age-specific mortality. Based on the posterior samples from these models, we estimate ranks and rank quartiles for each measure, as well as the probability of a county ranking in its assigned quartile. Rank quartile probabilities for univariate, joint outcome, and/or longitudinal models were compared to assess improvements in rank precision. Results The joint outcome model for poor physical and poor mental health days resulted in improved rank precision, as did the longitudinal model for age-specific mortality rates. Rank precision for low birth weight births and fair/poor health prevalence based on the univariate and joint outcome models were equivalent. Conclusion Incorporating longitudinal or pooled outcome data may improve rank certainty, depending on characteristics of the measures selected. For measures with different determinants, joint modeling neither improved nor degraded rank precision. This approach suggests a simple way to use existing information to improve the precision of small-area measures of population health. PMID:26098858

Multimethod, multistate Bayesian hierarchical modeling approach for use in regional monitoring of wolves.

PubMed

Jiménez, José; García, Emilio J; Llaneza, Luis; Palacios, Vicente; González, Luis Mariano; García-Domínguez, Francisco; Múñoz-Igualada, Jaime; López-Bao, José Vicente

2016-08-01

In many cases, the first step in large-carnivore management is to obtain objective, reliable, and cost-effective estimates of population parameters through procedures that are reproducible over time. However, monitoring predators over large areas is difficult, and the data have a high level of uncertainty. We devised a practical multimethod and multistate modeling approach based on Bayesian hierarchical-site-occupancy models that combined multiple survey methods to estimate different population states for use in monitoring large predators at a regional scale. We used wolves (Canis lupus) as our model species and generated reliable estimates of the number of sites with wolf reproduction (presence of pups). We used 2 wolf data sets from Spain (Western Galicia in 2013 and Asturias in 2004) to test the approach. Based on howling surveys, the naïve estimation (i.e., estimate based only on observations) of the number of sites with reproduction was 9 and 25 sites in Western Galicia and Asturias, respectively. Our model showed 33.4 (SD 9.6) and 34.4 (3.9) sites with wolf reproduction, respectively. The number of occupied sites with wolf reproduction was 0.67 (SD 0.19) and 0.76 (0.11), respectively. This approach can be used to design more cost-effective monitoring programs (i.e., to define the sampling effort needed per site). Our approach should inspire well-coordinated surveys across multiple administrative borders and populations and lead to improved decision making for management of large carnivores on a landscape level. The use of this Bayesian framework provides a simple way to visualize the degree of uncertainty around population-parameter estimates and thus provides managers and stakeholders an intuitive approach to interpreting monitoring results. Our approach can be widely applied to large spatial scales in wildlife monitoring where detection probabilities differ between population states and where several methods are being used to estimate different population parameters. © 2016 Society for Conservation Biology.

Strain memory of 2D and 3D rigid inclusion populations in viscous flows - What is clast SPO telling us?

NASA Astrophysics Data System (ADS)

Stahr, Donald W.; Law, Richard D.

2014-11-01

We model the development of shape preferred orientation (SPO) of a large population of two- and three-dimensional (2D and 3D) rigid clasts suspended in a linear viscous matrix deformed by superposed steady and continuously non-steady plane strain flows to investigate the sensitivity of clasts to changing boundary conditions during a single or superposed deformation events. Resultant clast SPOs are compared to one developed by an identical initial population that experienced a steady flow history of constant kinematic vorticity and reached an identical finite strain state, allowing examination of SPO sensitivity to deformation path. Rotation paths of individual triaxial inclusions are complex, even for steady plane strain flow histories. It has been suggested that the 3D nature of the system renders predictions based on 2D models inadequate for applied clast-based kinematic vorticity gauges. We demonstrate that for a large population of clasts, simplification to a 2D model does provide a good approximation to the SPO predicted by full 3D analysis for steady and non-steady plane strain deformation paths. Predictions of shape fabric development from 2D models are not only qualitatively similar to the more complex 3D analysis, but they display the same limitations of techniques based on clast SPO commonly used as a quantitative kinematic vorticity gauge. Our model results from steady, superposed, and non-steady flow histories with a significant pure shearing component at a wide range of finite strain resemble predictions for an identical initial population that experienced a single steady simple shearing deformation. We conclude that individual 2D and 3D clasts respond instantaneously to changes in boundary conditions, however, in aggregate, the SPO of a population of rigid inclusions does not reflect the late-stage kinematics of deformation, nor is it an indicator of the unique 'mean' kinematic vorticity experienced by a deformed rock volume.

A minimum stochastic model evaluating the interplay between population density and drift for species coexistence

NASA Astrophysics Data System (ADS)

Guariento, Rafael Dettogni; Caliman, Adriano

2017-02-01

Despite the general acknowledgment of the role of niche and stochastic process in community dynamics, the role of species relative abundances according to both perspectives may have different effects regarding coexistence patterns. In this study, we explore a minimum probabilistic stochastic model to determine the relationship of populations relative and total abundances with species chances to outcompete each other and their persistence in time (i.e., unstable coexistence). Our model is focused on the effects drift (i.e., random sampling of recruitment) under different scenarios of selection (i.e., fitness differences between species). Our results show that taking into account the stochasticity in demographic properties and conservation of individuals in closed communities (zero-sum assumption), initial population abundance can strongly influence species chances to outcompete each other, despite fitness inequalities between populations, and also, influence the period of coexistence of these species in a particular time interval. Systems carrying capacity can have an important role in species coexistence by exacerbating fitness inequalities and affecting the size of the period of coexistence. Overall, the simple stochastic formulation used in this study demonstrated that populations initial abundances could act as an equalizing mechanism, reducing fitness inequalities, which can favor species coexistence and even make less fitted species to be more likely to outcompete better-fitted species, and thus to dominate ecological communities in the absence of niche mechanisms. Although our model is restricted to a pair of interacting species, and overall conclusions are already predicted by the Neutral Theory of Biodiversity, our main objective was to derive a model that can explicitly show the functional relationship between population densities and community mono-dominance odds. Overall, our study provides a straightforward understanding of how a stochastic process (i.e., drift) may affect the expected outcome based on species selection (i.e., fitness inequalities among species) and the resulting outcome regarding unstable coexistence among species.

Multi-agent Simulations of Population Behavior: A Promising Tool for Systems Biology.

PubMed

Colosimo, Alfredo

2018-01-01

This contribution reports on the simulation of some dynamical events observed in the collective behavior of different kinds of populations, ranging from shape-changing cells in a Petri dish to functionally correlated brain areas in vivo. The unifying methodological approach, based upon a Multi-Agent Simulation (MAS) paradigm as incorporated in the NetLogo™ interpreter, is a direct consequence of the cornerstone that simple, individual actions within a population of interacting agents often give rise to complex, collective behavior.The discussion will mainly focus on the emergence and spreading of synchronous activities within the population, as well as on the modulation of the collective behavior exerted by environmental force-fields. A relevant section of this contribution is dedicated to the extension of the MAS paradigm to Brain Network models. In such a general framework some recent applications taken from the direct experience of the author, and exploring the activation patterns characteristic of specific brain functional states, are described, and their impact on the Systems-Biology universe underlined.

Evolutionary Dynamics and Diversity in Microbial Populations

NASA Astrophysics Data System (ADS)

Thompson, Joel; Fisher, Daniel

2013-03-01

Diseases such as flu and cancer adapt at an astonishing rate. In large part, viruses and cancers are so difficult to prevent because they are continually evolving. Controlling such ``evolutionary diseases'' requires a better understanding of the underlying evolutionary dynamics. It is conventionally assumed that adaptive mutations are rare and therefore will occur and sweep through the population in succession. Recent experiments using modern sequencing technologies have illuminated the many ways in which real population sequence data does not conform to the predictions of conventional theory. We consider a very simple model of asexual evolution and perform simulations in a range of parameters thought to be relevant for microbes and cancer. Simulation results reveal complex evolutionary dynamics typified by competition between lineages with different sets of adaptive mutations. This dynamical process leads to a distribution of mutant gene frequencies different than expected under the conventional assumption that adaptive mutations are rare. Simulated gene frequencies share several conspicuous features with data collected from laboratory-evolved yeast and the worldwide population of influenza.

Cloud Geospatial Analysis Tools for Global-Scale Comparisons of Population Models for Decision Making

NASA Astrophysics Data System (ADS)

Hancher, M.; Lieber, A.; Scott, L.

2017-12-01

The volume of satellite and other Earth data is growing rapidly. Combined with information about where people are, these data can inform decisions in a range of areas including food and water security, disease and disaster risk management, biodiversity, and climate adaptation. Google's platform for planetary-scale geospatial data analysis, Earth Engine, grants access to petabytes of continually updating Earth data, programming interfaces for analyzing the data without the need to download and manage it, and mechanisms for sharing the analyses and publishing results for data-driven decision making. In addition to data about the planet, data about the human planet - population, settlement and urban models - are now available for global scale analysis. The Earth Engine APIs enable these data to be joined, combined or visualized with economic or environmental indicators such as nighttime lights trends, global surface water, or climate projections, in the browser without the need to download anything. We will present our newly developed application intended to serve as a resource for government agencies, disaster response and public health programs, or other consumers of these data to quickly visualize the different population models, and compare them to ground truth tabular data to determine which model suits their immediate needs. Users can further tap into the power of Earth Engine and other Google technologies to perform a range of analysis from simple statistics in custom regions to more complex machine learning models. We will highlight case studies in which organizations around the world have used Earth Engine to combine population data with multiple other sources of data, such as water resources and roads data, over deep stacks of temporal imagery to model disease risk and accessibility to inform decisions.

Simplified risk assessment of noise induced hearing loss by means of 2 spreadsheet models.

PubMed

Lie, Arve; Engdahl, Bo; Tambs, Kristian

2016-11-18

The objective of this study has been to test 2 spreadsheet models to compare the observed with the expected hearing loss for a Norwegian reference population. The prevalence rates of the Norwegian and the National Institute for Occupational Safety and Health (NIOSH) definitions of hearing outcomes were calculated in terms of sex and age, 20-64 years old, for a screened (with no occupational noise exposure) (N = 18 858) and unscreened (N = 38 333) Norwegian reference population from the Nord-Trøndelag Hearing Loss Study (NTHLS). Based on the prevalence rates, 2 different spreadsheet models were constructed in order to compare the prevalence rates of various groups of workers with the expected rates. The spreadsheets were then tested on 10 different occupational groups with varying degrees of hearing loss as compared to a reference population. Hearing of office workers, train drivers, conductors and teachers differed little from the screened reference values based on the Norwegian and the NIOSH criterion. The construction workers, miners, farmers and military had an impaired hearing and railway maintenance workers and bus drivers had a mildly impaired hearing. The spreadsheet models give a valid assessment of the hearing loss. The use of spreadsheet models to compare hearing in occupational groups with that of a reference population is a simple and quick method. The results are in line with comparable hearing thresholds, and allow for significance testing. The method is believed to be useful for occupational health services in the assessment of risk of noise induced hearing loss (NIHL) and the preventive potential in groups of noise-exposed workers. Int J Occup Med Environ Health 2016;29(6):991-999. This work is available in Open Access model and licensed under a CC BY-NC 3.0 PL license.

The Impact of Prophage on the Equilibria and Stability of Phage and Host

NASA Astrophysics Data System (ADS)

Yu, Pei; Nadeem, Alina; Wahl, Lindi M.

2017-06-01

In this paper, we present a bacteriophage model that includes prophage, that is, phage genomes that are incorporated into the host cell genome. The general model is described by an 18-dimensional system of ordinary differential equations. This study focuses on asymptotic behaviour of the model, and thus the system is reduced to a simple six-dimensional model, involving uninfected host cells, infected host cells and phage. We use dynamical system theory to explore the dynamic behaviour of the model, studying in particular the impact of prophage on the equilibria and stability of phage and host. We employ bifurcation and stability theory, centre manifold and normal form theory to show that the system has multiple equilibrium solutions which undergo a series of bifurcations, finally leading to oscillating motions. Numerical simulations are presented to illustrate and confirm the analytical predictions. The results of this study indicate that in some parameter regimes, the host cell population may drive the phage to extinction through diversification, that is, if multiple types of host emerge; this prediction holds even if the phage population is likewise diverse. This parameter regime is restricted, however, if infecting phage are able to recombine with prophage sequences in the host cell genome.

An inverse approach to constraining strain and vorticity using rigid clast shape preferred orientation data

NASA Astrophysics Data System (ADS)

Davis, Joshua R.; Giorgis, Scott

2014-11-01

We describe a three-part approach for modeling shape preferred orientation (SPO) data of spheroidal clasts. The first part consists of criteria to determine whether a given SPO and clast shape are compatible. The second part is an algorithm for randomly generating spheroid populations that match a prescribed SPO and clast shape. In the third part, numerical optimization software is used to infer deformation from spheroid populations, by finding the deformation that returns a set of post-deformation spheroids to a minimally anisotropic initial configuration. Two numerical experiments explore the strengths and weaknesses of this approach, while giving information about the sensitivity of the model to noise in data. In monoclinic transpression of oblate rigid spheroids, the model is found to constrain the shortening component but not the simple shear component. This modeling approach is applied to previously published SPO data from the western Idaho shear zone, a monoclinic transpressional zone that deformed a feldspar megacrystic gneiss. Results suggest at most 5 km of shortening, as well as pre-deformation SPO fabric. The shortening estimate is corroborated by a second model that assumes no pre-deformation fabric.

A stochastic cellular automata model of tautomer equilibria

NASA Astrophysics Data System (ADS)

Bowers, Gregory A.; Seybold, Paul G.

2018-03-01

Many chemical substances, including drugs and biomolecules, exist in solution not as a single species, but as a collection of tautomers and related species. Importantly, each of these species is an independent compoundwith its own specific biochemical and physicochemical properties. The species interconvert in a dynamic and often complicated manner, making modelling the overall species composition difficult. Agent-based cellular automata models are uniquely suited to meet this challenge, allowing the equilibria to be simulated using simple rulesand at the same time capturing the inherent stochasticity of the natural phenomenon. In the present example a stochastic cellular automata model is employed to simulate the tautomer equilibria of 9-anthrone and 9-anthrol in the presence of their common anion. The observed KE of the 9-anthrone ⇌ 9-anthrol tautomerisation along with the measured tautomer pKa values were used to model the equilibria at pH values 4, 7 and 10. At pH 4 and 7, the anthrone comprises >99% of the total species population, while at pH 10the anthrone and the anion each represent just under half of the total population. The advantages of the cellular automata approach over the customary coupled differential equation approach are discussed.

The transition between immune and disease states in a cellular automaton model of clonal immune response

NASA Astrophysics Data System (ADS)

Bezzi, Michele; Celada, Franco; Ruffo, Stefano; Seiden, Philip E.

1997-02-01

In this paper we extend the Celada-Seiden (CS) model of the humoral immune response to include infections virus and killer T cells (cellular response). The model represents molecules and cells with bitstrings. The response of the system to virus involves a competition between the ability of the virus to kill the host cells and the host's ability to eliminate the virus. We find two basins of attraction in the dynamics of this system, one is identified with disease and the other with the immune state. There is also an oscillating state that exists on the border of these two stable states. Fluctuations in the population of virus or antibody can end the oscillation and drive the system into one of the stable states. The introduction of mechanisms of cross-regulation between the two responses can bias the system towards one of them. We also study a mean field model, based on coupled maps, to investigate virus-like infections. This simple model reproduces the attractors for average populations observed in the cellular automaton. All the dynamical behavior connected to spatial extension is lost, as is the oscillating feature. Thus the mean field approximation introduced with coupled maps destroys oscillations.

Model-based reasoning for system and software engineering: The Knowledge From Pictures (KFP) environment

NASA Technical Reports Server (NTRS)

Bailin, Sydney; Paterra, Frank; Henderson, Scott; Truszkowski, Walt

1993-01-01

This paper presents a discussion of current work in the area of graphical modeling and model-based reasoning being undertaken by the Automation Technology Section, Code 522.3, at Goddard. The work was initially motivated by the growing realization that the knowledge acquisition process was a major bottleneck in the generation of fault detection, isolation, and repair (FDIR) systems for application in automated Mission Operations. As with most research activities this work started out with a simple objective: to develop a proof-of-concept system demonstrating that a draft rule-base for a FDIR system could be automatically realized by reasoning from a graphical representation of the system to be monitored. This work was called Knowledge From Pictures (KFP) (Truszkowski et. al. 1992). As the work has successfully progressed the KFP tool has become an environment populated by a set of tools that support a more comprehensive approach to model-based reasoning. This paper continues by giving an overview of the graphical modeling objectives of the work, describing the three tools that now populate the KFP environment, briefly presenting a discussion of related work in the field, and by indicating future directions for the KFP environment.

Simplified large African carnivore density estimators from track indices.

PubMed

Winterbach, Christiaan W; Ferreira, Sam M; Funston, Paul J; Somers, Michael J

2016-01-01

The range, population size and trend of large carnivores are important parameters to assess their status globally and to plan conservation strategies. One can use linear models to assess population size and trends of large carnivores from track-based surveys on suitable substrates. The conventional approach of a linear model with intercept may not intercept at zero, but may fit the data better than linear model through the origin. We assess whether a linear regression through the origin is more appropriate than a linear regression with intercept to model large African carnivore densities and track indices. We did simple linear regression with intercept analysis and simple linear regression through the origin and used the confidence interval for ß in the linear model y  =  αx  + ß, Standard Error of Estimate, Mean Squares Residual and Akaike Information Criteria to evaluate the models. The Lion on Clay and Low Density on Sand models with intercept were not significant ( P  > 0.05). The other four models with intercept and the six models thorough origin were all significant ( P  < 0.05). The models using linear regression with intercept all included zero in the confidence interval for ß and the null hypothesis that ß = 0 could not be rejected. All models showed that the linear model through the origin provided a better fit than the linear model with intercept, as indicated by the Standard Error of Estimate and Mean Square Residuals. Akaike Information Criteria showed that linear models through the origin were better and that none of the linear models with intercept had substantial support. Our results showed that linear regression through the origin is justified over the more typical linear regression with intercept for all models we tested. A general model can be used to estimate large carnivore densities from track densities across species and study areas. The formula observed track density = 3.26 × carnivore density can be used to estimate densities of large African carnivores using track counts on sandy substrates in areas where carnivore densities are 0.27 carnivores/100 km 2 or higher. To improve the current models, we need independent data to validate the models and data to test for non-linear relationship between track indices and true density at low densities.

Black Hole Safari: Tracking Populations and Hunting Big Game

NASA Astrophysics Data System (ADS)

McConnell, N. J.

2013-10-01

Understanding the physical connection, or lack thereof, between the growth of galaxies and supermassive black holes is a key challenge in extragalactic astronomy. Dynamical studies of nearby galaxies are building a census of black hole masses across a broad range of galaxy types and uncovering statistical correlations between galaxy bulge properties and black hole masses. These local correlations provide a baseline for studying galaxies and black holes at higher redshifts. Recent measurements have probed the extremes of the supermassive black hole population and introduced surprises that challenge simple models of black hole and galaxy co-evolution. Future advances in the quality and quantity of dynamical black hole mass measurements will shed light upon the growth of massive galaxies and black holes in different cosmic environments.

Purification of human induced pluripotent stem cell-derived neural precursors using magnetic activated cell sorting.

PubMed

Rodrigues, Gonçalo M C; Fernandes, Tiago G; Rodrigues, Carlos A V; Cabral, Joaquim M S; Diogo, Maria Margarida

2015-01-01

Neural precursor (NP) cells derived from human induced pluripotent stem cells (hiPSCs), and their neuronal progeny, will play an important role in disease modeling, drug screening tests, central nervous system development studies, and may even become valuable for regenerative medicine treatments. Nonetheless, it is challenging to obtain homogeneous and synchronously differentiated NP populations from hiPSCs, and after neural commitment many pluripotent stem cells remain in the differentiated cultures. Here, we describe an efficient and simple protocol to differentiate hiPSC-derived NPs in 12 days, and we include a final purification stage where Tra-1-60+ pluripotent stem cells (PSCs) are removed using magnetic activated cell sorting (MACS), leaving the NP population nearly free of PSCs.

On S.N. Bernstein's derivation of Mendel's Law and 'rediscovery' of the Hardy-Weinberg distribution.

PubMed

Stark, Alan; Seneta, Eugene

2012-04-01

Around 1923 the soon-to-be famous Soviet mathematician and probabilist Sergei N. Bernstein started to construct an axiomatic foundation of a theory of heredity. He began from the premise of stationarity (constancy of type proportions) from the first generation of offspring. This led him to derive the Mendelian coefficients of heredity. It appears that he had no direct influence on the subsequent development of population genetics. A basic assumption of Bernstein was that parents coupled randomly to produce offspring. This paper shows that a simple model of non-random mating, which nevertheless embodies a feature of the Hardy-Weinberg Law, can produce Mendelian coefficients of heredity while maintaining the population distribution. How W. Johannsen's monograph influenced Bernstein is discussed.