Quantitative estimation of the cost of parasitic castration in a Helisoma anceps population using a matrix population model.

PubMed

Negovetich, N J; Esch, G W

2008-10-01

Larval trematodes frequently castrate their snail intermediate hosts. When castrated, the snails do not contribute offspring to the population, yet they persist and compete with the uninfected individuals for the available food resources. Parasitic castration should reduce the population growth rate lambda, but the magnitude of this decrease is unknown. The present study attempted to quantify the cost of parasitic castration at the level of the population by mathematically modeling the population of the planorbid snail Helisoma anceps in Charlie's Pond, North Carolina. Analysis of the model identified the life-history trait that most affects lambda, and the degree to which parasitic castration can lower lambda. A period matrix product model was constructed with estimates of fecundity, survival, growth rates, and infection probabilities calculated in a previous study. Elasticity analysis was performed by increasing the values of the life-history traits by 10% and recording the percentage change in lambda. Parasitic castration resulted in a 40% decrease in lambda of H. anceps. Analysis of the model suggests that decreasing the size at maturity was more effective at reducing the cost of castration than increasing survival or growth rates of the snails. The current matrix model was the first to mathematically describe a snail population, and the predictions of the model are in agreement with published research.

Constructing a Covariance Matrix that Yields a Specified Minimizer and a Specified Minimum Discrepancy Function Value.

ERIC Educational Resources Information Center

Cudeck, Robert; Browne, Michael W.

1992-01-01

A method is proposed for constructing a population covariance matrix as the sum of a particular model plus a nonstochastic residual matrix, with the stipulation that the model holds with a prespecified lack of fit. The procedure is considered promising for Monte Carlo studies. (SLD)

Use of an Inverse Method for Time Series to Estimate the Dynamics of and Management Strategies for the Box Jellyfish Carybdea marsupialis.

PubMed

Bordehore, Cesar; Fuentes, Verónica L; Segarra, Jose G; Acevedo, Melisa; Canepa, Antonio; Raventós, Josep

2015-01-01

Frequently, population ecology of marine organisms uses a descriptive approach in which their sizes and densities are plotted over time. This approach has limited usefulness for design strategies in management or modelling different scenarios. Population projection matrix models are among the most widely used tools in ecology. Unfortunately, for the majority of pelagic marine organisms, it is difficult to mark individuals and follow them over time to determine their vital rates and built a population projection matrix model. Nevertheless, it is possible to get time-series data to calculate size structure and densities of each size, in order to determine the matrix parameters. This approach is known as a "demographic inverse problem" and it is based on quadratic programming methods, but it has rarely been used on aquatic organisms. We used unpublished field data of a population of cubomedusae Carybdea marsupialis to construct a population projection matrix model and compare two different management strategies to lower population to values before year 2008 when there was no significant interaction with bathers. Those strategies were by direct removal of medusae and by reducing prey. Our results showed that removal of jellyfish from all size classes was more effective than removing only juveniles or adults. When reducing prey, the highest efficiency to lower the C. marsupialis population occurred when prey depletion affected prey of all medusae sizes. Our model fit well with the field data and may serve to design an efficient management strategy or build hypothetical scenarios such as removal of individuals or reducing prey. TThis This sdfsdshis method is applicable to other marine or terrestrial species, for which density and population structure over time are available.

Organism and population-level ecological models for ...

EPA Pesticide Factsheets

Ecological risk assessment typically focuses on animal populations as endpoints for regulatory ecotoxicology. Scientists at USEPA are developing models for animal populations exposed to a wide range of chemicals from pesticides to emerging contaminants. Modeled taxa include aquatic and terrestrial invertebrates, fish, amphibians, and birds, and employ a wide range of methods, from matrix-based projection models to mechanistic bioenergetics models and spatially explicit population models. not applicable

Tuning stochastic matrix models with hydrologic data to predict the population dynamics of a riverine fish.

PubMed

Sakaris, Peter C; Irwin, Elise R

2010-03-01

We developed stochastic matrix models to evaluate the effects of hydrologic alteration and variable mortality on the population dynamics of a lotic fish in a regulated river system. Models were applied to a representative lotic fish species, the flathead catfish (Pylodictis olivaris), for which two populations were examined: a native population from a regulated reach of the Coosa River (Alabama, USA) and an introduced population from an unregulated section of the Ocmulgee River (Georgia, USA). Size-classified matrix models were constructed for both populations, and residuals from catch-curve regressions were used as indices of year class strength (i.e., recruitment). A multiple regression model indicated that recruitment of flathead catfish in the Coosa River was positively related to the frequency of spring pulses between 283 and 566 m3/s. For the Ocmulgee River population, multiple regression models indicated that year class strength was negatively related to mean March discharge and positively related to June low flow. When the Coosa population was modeled to experience five consecutive years of favorable hydrologic conditions during a 50-year projection period, it exhibited a substantial spike in size and increased at an overall 0.2% annual rate. When modeled to experience five years of unfavorable hydrologic conditions, the Coosa population initially exhibited a decrease in size but later stabilized and increased at a 0.4% annual rate following the decline. When the Ocmulgee River population was modeled to experience five years of favorable conditions, it exhibited a substantial spike in size and increased at an overall 0.4% annual rate. After the Ocmulgee population experienced five years of unfavorable conditions, a sharp decline in population size was predicted. However, the population quickly recovered, with population size increasing at a 0.3% annual rate following the decline. In general, stochastic population growth in the Ocmulgee River was more erratic and variable than population growth in the Coosa River. We encourage ecologists to develop similar models for other lotic species, particularly in regulated river systems. Successful management of fish populations in regulated systems requires that we are able to predict how hydrology affects recruitment and will ultimately influence the population dynamics of fishes.

Effects of uncertainty and variability on population declines and IUCN Red List classifications.

PubMed

Rueda-Cediel, Pamela; Anderson, Kurt E; Regan, Tracey J; Regan, Helen M

2018-01-22

The International Union for Conservation of Nature (IUCN) Red List Categories and Criteria is a quantitative framework for classifying species according to extinction risk. Population models may be used to estimate extinction risk or population declines. Uncertainty and variability arise in threat classifications through measurement and process error in empirical data and uncertainty in the models used to estimate extinction risk and population declines. Furthermore, species traits are known to affect extinction risk. We investigated the effects of measurement and process error, model type, population growth rate, and age at first reproduction on the reliability of risk classifications based on projected population declines on IUCN Red List classifications. We used an age-structured population model to simulate true population trajectories with different growth rates, reproductive ages and levels of variation, and subjected them to measurement error. We evaluated the ability of scalar and matrix models parameterized with these simulated time series to accurately capture the IUCN Red List classification generated with true population declines. Under all levels of measurement error tested and low process error, classifications were reasonably accurate; scalar and matrix models yielded roughly the same rate of misclassifications, but the distribution of errors differed; matrix models led to greater overestimation of extinction risk than underestimations; process error tended to contribute to misclassifications to a greater extent than measurement error; and more misclassifications occurred for fast, rather than slow, life histories. These results indicate that classifications of highly threatened taxa (i.e., taxa with low growth rates) under criterion A are more likely to be reliable than for less threatened taxa when assessed with population models. Greater scrutiny needs to be placed on data used to parameterize population models for species with high growth rates, particularly when available evidence indicates a potential transition to higher risk categories. © 2018 Society for Conservation Biology.

THE INFLUENCE OF MODEL TIME STEP ON THE RELATIVE SENSITIVIY OF POPULATION GROWTH RATE TO REPRODUCTION

EPA Science Inventory

In recent years there has been an increasing interest in using population models in environmental assessments. Matrix population models represent a valuable tool for extrapolating from life stage-specific stressor effects on survival and reproduction to effects on finite populati...

EVALUATION OF THE EFFICACY OF EXTRAPOLATION POPULATION MODELING TO PREDICT THE DYNAMICS OF AMERICAMYSIS BAHIA POPULATIONS IN THE LABORATORY

EPA Science Inventory

An age-classified projection matrix model has been developed to extrapolate the chronic (28-35d) demographic responses of Americamysis bahia (formerly Mysidopsis bahia) to population-level response. This study was conducted to evaluate the efficacy of this model for predicting t...

An Experimental Approach to Mathematical Modeling in Biology

ERIC Educational Resources Information Center

Ledder, Glenn

2008-01-01

The simplest age-structured population models update a population vector via multiplication by a matrix. These linear models offer an opportunity to introduce mathematical modeling to students of limited mathematical sophistication and background. We begin with a detailed discussion of mathematical modeling, particularly in a biological context.…

Tuning stochastic matrix models with hydrologic data to predict the population dynamics of a riverine fish

USGS Publications Warehouse

Sakaris, P.C.; Irwin, E.R.

2010-01-01

We developed stochastic matrix models to evaluate the effects of hydrologic alteration and variable mortality on the population dynamics of a lotie fish in a regulated river system. Models were applied to a representative lotic fish species, the flathead catfish (Pylodictis olivaris), for which two populations were examined: a native population from a regulated reach of the Coosa River (Alabama, USA) and an introduced population from an unregulated section of the Ocmulgee River (Georgia, USA). Size-classified matrix models were constructed for both populations, and residuals from catch-curve regressions were used as indices of year class strength (i.e., recruitment). A multiple regression model indicated that recruitment of flathead catfish in the Coosa River was positively related to the frequency of spring pulses between 283 and 566 m3/s. For the Ocmulgee River population, multiple regression models indicated that year class strength was negatively related to mean March discharge and positively related to June low flow. When the Coosa population was modeled to experience five consecutive years of favorable hydrologic conditions during a 50-year projection period, it exhibited a substantial spike in size and increased at an overall 0.2% annual rate. When modeled to experience five years of unfavorable hydrologic conditions, the Coosa population initially exhibited a decrease in size but later stabilized and increased at a 0.4% annual rate following the decline. When the Ocmulgee River population was modeled to experience five years of favorable conditions, it exhibited a substantial spike in size and increased at an overall 0.4% annual rate. After the Ocmulgee population experienced five years of unfavorable conditions, a sharp decline in population size was predicted. However, the population quickly recovered, with population size increasing at a 0.3% annual rate following the decline. In general, stochastic population growth in the Ocmulgee River was more erratic and variable than population growth in the Coosa River. We encourage ecologists to develop similar models for other lotic species, particularly in regulated river systems. Successful management of fish populations in regulated systems requires that we are able to predict how hydrology affects recruitment and will ultimately influence the population dynamics of fishes. ?? 2010 by the Ecological Society of America.

Bridging the gap between habitat-modeling research and bird conservation with dynamic landscape and population models

Treesearch

Frank R., III Thompson

2009-01-01

Habitat models are widely used in bird conservation planning to assess current habitat or populations and to evaluate management alternatives. These models include species-habitat matrix or database models, habitat suitability models, and statistical models that predict abundance. While extremely useful, these approaches have some limitations.

A metapopulation approach to African lion (Panthera leo) conservation.

PubMed

Dolrenry, Stephanie; Stenglein, Jennifer; Hazzah, Leela; Lutz, R Scott; Frank, Laurence

2014-01-01

Due to anthropogenic pressures, African lion (Panthera leo) populations in Kenya and Tanzania are increasingly limited to fragmented populations. Lions living on isolated habitat patches exist in a matrix of less-preferred habitat. A framework of habitat patches within a less-suitable matrix describes a metapopulation. Metapopulation analysis can provide insight into the dynamics of each population patch in reference to the system as a whole, and these analyses often guide conservation planning. We present the first metapopulation analysis of African lions. We use a spatially-realistic model to investigate how sex-biased dispersal abilities of lions affect patch occupancy and also examine whether human densities surrounding the remaining lion populations affect the metapopulation as a whole. Our results indicate that male lion dispersal ability strongly contributes to population connectivity while the lesser dispersal ability of females could be a limiting factor. When populations go extinct, recolonization will not occur if distances between patches exceed female dispersal ability or if females are not able to survive moving across the matrix. This has profound implications for the overall metapopulation; the female models showed an intrinsic extinction rate from five-fold to a hundred-fold higher than the male models. Patch isolation is a consideration for even the largest lion populations. As lion populations continue to decline and with local extinctions occurring, female dispersal ability and the proximity to the nearest lion population are serious considerations for the recolonization of individual populations and for broader conservation efforts.

A Metapopulation Approach to African Lion (Panthera leo) Conservation

PubMed Central

Dolrenry, Stephanie; Stenglein, Jennifer; Hazzah, Leela; Lutz, R. Scott; Frank, Laurence

2014-01-01

Due to anthropogenic pressures, African lion (Panthera leo) populations in Kenya and Tanzania are increasingly limited to fragmented populations. Lions living on isolated habitat patches exist in a matrix of less-preferred habitat. A framework of habitat patches within a less-suitable matrix describes a metapopulation. Metapopulation analysis can provide insight into the dynamics of each population patch in reference to the system as a whole, and these analyses often guide conservation planning. We present the first metapopulation analysis of African lions. We use a spatially-realistic model to investigate how sex-biased dispersal abilities of lions affect patch occupancy and also examine whether human densities surrounding the remaining lion populations affect the metapopulation as a whole. Our results indicate that male lion dispersal ability strongly contributes to population connectivity while the lesser dispersal ability of females could be a limiting factor. When populations go extinct, recolonization will not occur if distances between patches exceed female dispersal ability or if females are not able to survive moving across the matrix. This has profound implications for the overall metapopulation; the female models showed an intrinsic extinction rate from five-fold to a hundred-fold higher than the male models. Patch isolation is a consideration for even the largest lion populations. As lion populations continue to decline and with local extinctions occurring, female dispersal ability and the proximity to the nearest lion population are serious considerations for the recolonization of individual populations and for broader conservation efforts. PMID:24505385

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.

GAGA: a new algorithm for genomic inference of geographic ancestry reveals fine level population substructure in Europeans.

PubMed

Lao, Oscar; Liu, Fan; Wollstein, Andreas; Kayser, Manfred

2014-02-01

Attempts to detect genetic population substructure in humans are troubled by the fact that the vast majority of the total amount of observed genetic variation is present within populations rather than between populations. Here we introduce a new algorithm for transforming a genetic distance matrix that reduces the within-population variation considerably. Extensive computer simulations revealed that the transformed matrix captured the genetic population differentiation better than the original one which was based on the T1 statistic. In an empirical genomic data set comprising 2,457 individuals from 23 different European subpopulations, the proportion of individuals that were determined as a genetic neighbour to another individual from the same sampling location increased from 25% with the original matrix to 52% with the transformed matrix. Similarly, the percentage of genetic variation explained between populations by means of Analysis of Molecular Variance (AMOVA) increased from 1.62% to 7.98%. Furthermore, the first two dimensions of a classical multidimensional scaling (MDS) using the transformed matrix explained 15% of the variance, compared to 0.7% obtained with the original matrix. Application of MDS with Mclust, SPA with Mclust, and GemTools algorithms to the same dataset also showed that the transformed matrix gave a better association of the genetic clusters with the sampling locations, and particularly so when it was used in the AMOVA framework with a genetic algorithm. Overall, the new matrix transformation introduced here substantially reduces the within population genetic differentiation, and can be broadly applied to methods such as AMOVA to enhance their sensitivity to reveal population substructure. We herewith provide a publically available (http://www.erasmusmc.nl/fmb/resources/GAGA) model-free method for improved genetic population substructure detection that can be applied to human as well as any other species data in future studies relevant to evolutionary biology, behavioural ecology, medicine, and forensics.

A framework for studying transient dynamics of population projection matrix models.

PubMed

Stott, Iain; Townley, Stuart; Hodgson, David James

2011-09-01

Empirical models are central to effective conservation and population management, and should be predictive of real-world dynamics. Available modelling methods are diverse, but analysis usually focuses on long-term dynamics that are unable to describe the complicated short-term time series that can arise even from simple models following ecological disturbances or perturbations. Recent interest in such transient dynamics has led to diverse methodologies for their quantification in density-independent, time-invariant population projection matrix (PPM) models, but the fragmented nature of this literature has stifled the widespread analysis of transients. We review the literature on transient analyses of linear PPM models and synthesise a coherent framework. We promote the use of standardised indices, and categorise indices according to their focus on either convergence times or transient population density, and on either transient bounds or case-specific transient dynamics. We use a large database of empirical PPM models to explore relationships between indices of transient dynamics. This analysis promotes the use of population inertia as a simple, versatile and informative predictor of transient population density, but criticises the utility of established indices of convergence times. Our findings should guide further development of analyses of transient population dynamics using PPMs or other empirical modelling techniques. © 2011 Blackwell Publishing Ltd/CNRS.

Pre-release biological control agent recommendations for swallow-wort (Vincetoxicum spp.) informed by demographic matrix models

USDA-ARS?s Scientific Manuscript database

Weed biological control workers have advocated for the advance assessment of agent efficacy in order to minimize the release of host-specific but ineffective agents. One method involves demographic matrix modeling of target weed populations in order to identify plant life stage transitions that cont...

Matrix Population Model for Estimating Effects from Time-Varying Aquatic Exposures: Technical Documentation

EPA Science Inventory

The Office of Pesticide Programs models daily aquatic pesticide exposure values for 30 years in its risk assessments. However, only a fraction of that information is typically used in these assessments. The population model employed herein is a deterministic, density-dependent pe...

Population models of burrowing mayfly recolonization in Western Lake Erie

USGS Publications Warehouse

Madenjian, C.P.; Schloesser, D.W.; Krieger, K.A.

1998-01-01

Burrowing mayflies, Hexagenia spp. (H. limbata and H. rigida), began recolonizing western Lake Erie during the 1990s. Survey data for mayfly nymph densities indicated that the population experienced exponential growth between 1991 and 1997. To predict the time to full recovery of the mayfly population, we fitted logistic models, ranging in carrying capacity from 600 to 2000 nymphs/m2, to these survey data. Based on the fitted logistic curves, we forecast that the mayfly population in western Lake Erie would achieve full recovery between years 1998 and 2000, depending on the carrying capacity of the western basin. Additionally, we estimated the mortality rate of nymphs in western Lake Erie during 1994 and then applied an age-based matrix model to the mayfly population. The results of the matrix population modeling corroborated the exponential growth model application in that both methods yielded an estimate of the population growth rate, r, in excess of 0.8 yr-1. This was the first evidence that mayfly populations are capable of recolonizing large aquatic ecosystems at rates comparable with those observed in much smaller lentic ecosystems. Our model predictions should prove valuable to managers of power plant facilities along the western basin in planning for mayfly emergences and to managers of the yellow perch (Perca flavescens) fishery in western Lake Erie.

Near-Infrared Collisional Radiative Model for Xe Plasma Electrostatic Thrusters: The Role of Metastable Atoms

DTIC Science & Technology

2009-08-01

the measurements of Jung et al [3], ’BSR’ to the Breit- Pauli B-Spline ft-matrix method, and ’RDW to the relativistic distorted wave method. low...excitation cross sections using both relativistic distorted wave and semi-relativistic Breit- Pauli B-Spline R-matrix methods is presented. The model...population and line intensity enhancement. 15. SUBJECT TERMS Metastable xenon Electrostatic thruster Relativistic Breit- Pauli b-spline matrix

PROJECTING POPULATION-LEVEL RESPONSE OF PURPLE SEA URCHINS TO LEAD CONTAMINATION FOR AN ESTUARINE ECOLOGICAL RISK ASSESSMENT

EPA Science Inventory

As part of an ecological risk assessment case study at the Portsmouth naval Shipyard (PNS), Kittery, Maine, USA, the population level effects of lead exposure to purple sea urchin, Arbacia punctulata, were investigated using a stage-classified matrix population model. The model d...

Inference of Population Structure using Dense Haplotype Data

PubMed Central

Lawson, Daniel John; Hellenthal, Garrett

2012-01-01

The advent of genome-wide dense variation data provides an opportunity to investigate ancestry in unprecedented detail, but presents new statistical challenges. We propose a novel inference framework that aims to efficiently capture information on population structure provided by patterns of haplotype similarity. Each individual in a sample is considered in turn as a recipient, whose chromosomes are reconstructed using chunks of DNA donated by the other individuals. Results of this “chromosome painting” can be summarized as a “coancestry matrix,” which directly reveals key information about ancestral relationships among individuals. If markers are viewed as independent, we show that this matrix almost completely captures the information used by both standard Principal Components Analysis (PCA) and model-based approaches such as STRUCTURE in a unified manner. Furthermore, when markers are in linkage disequilibrium, the matrix combines information across successive markers to increase the ability to discern fine-scale population structure using PCA. In parallel, we have developed an efficient model-based approach to identify discrete populations using this matrix, which offers advantages over PCA in terms of interpretability and over existing clustering algorithms in terms of speed, number of separable populations, and sensitivity to subtle population structure. We analyse Human Genome Diversity Panel data for 938 individuals and 641,000 markers, and we identify 226 populations reflecting differences on continental, regional, local, and family scales. We present multiple lines of evidence that, while many methods capture similar information among strongly differentiated groups, more subtle population structure in human populations is consistently present at a much finer level than currently available geographic labels and is only captured by the haplotype-based approach. The software used for this article, ChromoPainter and fineSTRUCTURE, is available from http://www.paintmychromosomes.com/. PMID:22291602

Demographic Modelling in Weed Biocontrol

USDA-ARS?s Scientific Manuscript database

Demographic matrix modeling of plant populations can be a powerful tool to identify key life stage transitions that contribute the most to population growth of an invasive plant and hence should be targeted for disruption. Therefore, this approach has the potential to guide the pre-release selection...

Using matrix population models to inform biological control management of the wheat stem sawfly, Cephus cinctus

USDA-ARS?s Scientific Manuscript database

Demographic models are a powerful means of identifying vulnerable life stages of pest species and assessing the potential effectiveness of various management approaches in reducing pest population growth and spread. In a biological control context, such models can be used to focus foreign explorati...

Metal Cluster Models for Heterogeneous Catalysis: A Matrix-Isolation Perspective.

PubMed

Hübner, Olaf; Himmel, Hans-Jörg

2018-02-19

Metal cluster models are of high relevance for establishing new mechanistic concepts for heterogeneous catalysis. The high reactivity and particular selectivity of metal clusters is caused by the wealth of low-lying electronically excited states that are often thermally populated. Thereby the metal clusters are flexible with regard to their electronic structure and can adjust their states to be appropriate for the reaction with a particular substrate. The matrix isolation technique is ideally suited for studying excited state reactivity. The low matrix temperatures (generally 4-40 K) of the noble gas matrix host guarantee that all clusters are in their electronic ground-state (with only a very few exceptions). Electronically excited states can then be selectively populated and their reactivity probed. Unfortunately, a systematic research in this direction has not been made up to date. The purpose of this review is to provide the grounds for a directed approach to understand cluster reactivity through matrix-isolation studies combined with quantum chemical calculations. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Constructing stage-structured matrix population models from life tables: comparison of methods

PubMed Central

Diaz-Lopez, Jasmin

2017-01-01

A matrix population model is a convenient tool for summarizing per capita survival and reproduction rates (collectively vital rates) of a population and can be used for calculating an asymptotic finite population growth rate (λ) and generation time. These two pieces of information can be used for determining the status of a threatened species. The use of stage-structured population models has increased in recent years, and the vital rates in such models are often estimated using a life table analysis. However, potential bias introduced when converting age-structured vital rates estimated from a life table into parameters for a stage-structured population model has not been assessed comprehensively. The objective of this study was to investigate the performance of methods for such conversions using simulated life histories of organisms. The underlying models incorporate various types of life history and true population growth rates of varying levels. The performance was measured by comparing differences in λ and the generation time calculated using the Euler-Lotka equation, age-structured population matrices, and several stage-structured population matrices that were obtained by applying different conversion methods. The results show that the discretization of age introduces only small bias in λ or generation time. Similarly, assuming a fixed age of maturation at the mean age of maturation does not introduce much bias. However, aggregating age-specific survival rates into a stage-specific survival rate and estimating a stage-transition rate can introduce substantial bias depending on the organism’s life history type and the true values of λ. In order to aggregate survival rates, the use of the weighted arithmetic mean was the most robust method for estimating λ. Here, the weights are given by survivorship curve after discounting with λ. To estimate a stage-transition rate, matching the proportion of individuals transitioning, with λ used for discounting the rate, was the best approach. However, stage-structured models performed poorly in estimating generation time, regardless of the methods used for constructing the models. Based on the results, we recommend using an age-structured matrix population model or the Euler-Lotka equation for calculating λ and generation time when life table data are available. Then, these age-structured vital rates can be converted into a stage-structured model for further analyses. PMID:29085763

Constructing stage-structured matrix population models from life tables: comparison of methods.

PubMed

Fujiwara, Masami; Diaz-Lopez, Jasmin

2017-01-01

A matrix population model is a convenient tool for summarizing per capita survival and reproduction rates (collectively vital rates) of a population and can be used for calculating an asymptotic finite population growth rate ( λ ) and generation time. These two pieces of information can be used for determining the status of a threatened species. The use of stage-structured population models has increased in recent years, and the vital rates in such models are often estimated using a life table analysis. However, potential bias introduced when converting age-structured vital rates estimated from a life table into parameters for a stage-structured population model has not been assessed comprehensively. The objective of this study was to investigate the performance of methods for such conversions using simulated life histories of organisms. The underlying models incorporate various types of life history and true population growth rates of varying levels. The performance was measured by comparing differences in λ and the generation time calculated using the Euler-Lotka equation, age-structured population matrices, and several stage-structured population matrices that were obtained by applying different conversion methods. The results show that the discretization of age introduces only small bias in λ or generation time. Similarly, assuming a fixed age of maturation at the mean age of maturation does not introduce much bias. However, aggregating age-specific survival rates into a stage-specific survival rate and estimating a stage-transition rate can introduce substantial bias depending on the organism's life history type and the true values of λ . In order to aggregate survival rates, the use of the weighted arithmetic mean was the most robust method for estimating λ . Here, the weights are given by survivorship curve after discounting with λ . To estimate a stage-transition rate, matching the proportion of individuals transitioning, with λ used for discounting the rate, was the best approach. However, stage-structured models performed poorly in estimating generation time, regardless of the methods used for constructing the models. Based on the results, we recommend using an age-structured matrix population model or the Euler-Lotka equation for calculating λ and generation time when life table data are available. Then, these age-structured vital rates can be converted into a stage-structured model for further analyses.

Development and application of a density dependent matrix ...

EPA Pesticide Factsheets

Ranging along the Atlantic coast from US Florida to the Maritime Provinces of Canada, the Atlantic killifish (Fundulus heteroclitus) is an important and well-studied model organism for understanding the effects of pollutants and other stressors in estuarine and marine ecosystems. Matrix population models are useful tools for ecological risk assessment because they integrate effects across the life cycle, provide a linkage between endpoints observed in the individual and ecological risk to the population as a whole, and project outcomes for many generations in the future. We developed a density dependent matrix population model for Atlantic killifish by modifying a model developed for fathead minnow (Pimephales promelas) that has proved to be extremely useful, e.g. to incorporate data from laboratory studies and project effects of endocrine disrupting chemicals. We developed a size-structured model (as opposed to one that is based upon developmental stages or age class structure) so that we could readily incorporate output from a Dynamic Energy Budget (DEB) model, currently under development. Due to a lack of sufficient data to accurately define killifish responses to density dependence, we tested a number of scenarios realistic for other fish species in order to demonstrate the outcome of including this ecologically important factor. We applied the model using published data for killifish exposed to dioxin-like compounds, and compared our results to those using

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.

Continuum-level modelling of cellular adhesion and matrix production in aggregates.

PubMed

Geris, Liesbet; Ashbourn, Joanna M A; Clarke, Tim

2011-05-01

Key regulators in tissue-engineering processes such as cell culture and cellular organisation are the cell-cell and cell-matrix interactions. As mathematical models are increasingly applied to investigate biological phenomena in the biomedical field, it is important, for some applications, that these models incorporate an adequate description of cell adhesion. This study describes the development of a continuum model that represents a cell-in-gel culture system used in bone-tissue engineering, namely that of a cell aggregate embedded in a hydrogel. Cell adhesion is modelled through the use of non-local (integral) terms in the partial differential equations. The simulation results demonstrate that the effects of cell-cell and cell-matrix adhesion are particularly important for the survival and growth of the cell population and the production of extracellular matrix by the cells, concurring with experimental observations in the literature.

Periodic matrix population models: growth rate, basic reproduction number, and entropy.

PubMed

Bacaër, Nicolas

2009-10-01

This article considers three different aspects of periodic matrix population models. First, a formula for the sensitivity analysis of the growth rate lambda is obtained that is simpler than the one obtained by Caswell and Trevisan. Secondly, the formula for the basic reproduction number R0 in a constant environment is generalized to the case of a periodic environment. Some inequalities between lambda and R0 proved by Cushing and Zhou are also generalized to the periodic case. Finally, we add some remarks on Demetrius' notion of evolutionary entropy H and its relationship to the growth rate lambda in the periodic case.

The feasibility and stability of large complex biological networks: a random matrix approach.

PubMed

Stone, Lewi

2018-05-29

In the 70's, Robert May demonstrated that complexity creates instability in generic models of ecological networks having random interaction matrices A. Similar random matrix models have since been applied in many disciplines. Central to assessing stability is the "circular law" since it describes the eigenvalue distribution for an important class of random matrices A. However, despite widespread adoption, the "circular law" does not apply for ecological systems in which density-dependence operates (i.e., where a species growth is determined by its density). Instead one needs to study the far more complicated eigenvalue distribution of the community matrix S = DA, where D is a diagonal matrix of population equilibrium values. Here we obtain this eigenvalue distribution. We show that if the random matrix A is locally stable, the community matrix S = DA will also be locally stable, providing the system is feasible (i.e., all species have positive equilibria D > 0). This helps explain why, unusually, nearly all feasible systems studied here are locally stable. Large complex systems may thus be even more fragile than May predicted, given the difficulty of assembling a feasible system. It was also found that the degree of stability, or resilience of a system, depended on the minimum equilibrium population.

Computational Simulation and Analysis of Mutations: Nucleotide Fixation, Allelic Age and Rare Genetic Variations in Population

ERIC Educational Resources Information Center

Qiu, Shuhao

2015-01-01

In order to investigate the complexity of mutations, a computational approach named Genome Evolution by Matrix Algorithms ("GEMA") has been implemented. GEMA models genomic changes, taking into account hundreds of mutations within each individual in a population. By modeling of entire human chromosomes, GEMA precisely mimics real…

Population demographics, survival, and reporduction: Alaska sea otter research

USGS Publications Warehouse

Monson, Daniel H.; Bodkin, James L.; Doak, D.F.; Estes, James A.; Tinker, M.T.; Siniff, D.B.; Maldini, Daniela; Calkins, Donald; Atkinson, Shannon; Meehan, Rosa

2004-01-01

The fundamental force behind population change is the balance between age-specific survival and reproductive rates. Thus, understanding population demographics is crucial when trying to interpret trends in population change over time. For many species, demographic rates change as the population’s status (i.e., relative to prey resources) varies. Indices of body condition indicative of individual energy reserves can be a useful gauge of population status. Integrated studies designed to measure (1) population trends; (2) current population status; and (3) demographic rates will provide the most complete picture of the factors driving observed population changes. In particular, estimates of age specific survival and reproduction in conjunction with measures of population change can be integrated into population matrix models useful in explaining observed trends. We focus here on the methods used to measure demographic rates in sea otters, and note the importance of comparable methods between studies. Next, we review the current knowledge of the influence of population status on demographic parameters. We end with examples of the power of matrix modeling as a tool to integrate various types of demographic information for detecting otherwise hard to detect changes in demographic parameters.

Evolutionary Games with Randomly Changing Payoff Matrices

NASA Astrophysics Data System (ADS)

Yakushkina, Tatiana; Saakian, David B.; Bratus, Alexander; Hu, Chin-Kun

2015-06-01

Evolutionary games are used in various fields stretching from economics to biology. In most of these games a constant payoff matrix is assumed, although some works also consider dynamic payoff matrices. In this article we assume a possibility of switching the system between two regimes with different sets of payoff matrices. Potentially such a model can qualitatively describe the development of bacterial or cancer cells with a mutator gene present. A finite population evolutionary game is studied. The model describes the simplest version of annealed disorder in the payoff matrix and is exactly solvable at the large population limit. We analyze the dynamics of the model, and derive the equations for both the maximum and the variance of the distribution using the Hamilton-Jacobi equation formalism.

Refining mortality estimates in shark demographic analyses: a Bayesian inverse matrix approach.

PubMed

Smart, Jonathan J; Punt, André E; White, William T; Simpfendorfer, Colin A

2018-01-18

Leslie matrix models are an important analysis tool in conservation biology that are applied to a diversity of taxa. The standard approach estimates the finite rate of population growth (λ) from a set of vital rates. In some instances, an estimate of λ is available, but the vital rates are poorly understood and can be solved for using an inverse matrix approach. However, these approaches are rarely attempted due to prerequisites of information on the structure of age or stage classes. This study addressed this issue by using a combination of Monte Carlo simulations and the sample-importance-resampling (SIR) algorithm to solve the inverse matrix problem without data on population structure. This approach was applied to the grey reef shark (Carcharhinus amblyrhynchos) from the Great Barrier Reef (GBR) in Australia to determine the demography of this population. Additionally, these outputs were applied to another heavily fished population from Papua New Guinea (PNG) that requires estimates of λ for fisheries management. The SIR analysis determined that natural mortality (M) and total mortality (Z) based on indirect methods have previously been overestimated for C. amblyrhynchos, leading to an underestimated λ. The updated Z distributions determined using SIR provided λ estimates that matched an empirical λ for the GBR population and corrected obvious error in the demographic parameters for the PNG population. This approach provides opportunity for the inverse matrix approach to be applied more broadly to situations where information on population structure is lacking. © 2018 by the Ecological Society of America.

Multistate matrix population model to assess the contributions and impacts on population abundance of domestic cats in urban areas including owned cats, unowned cats, and cats in shelters

PubMed Central

Coe, Jason B.

2018-01-01

Concerns over cat homelessness, over-taxed animal shelters, public health risks, and environmental impacts has raised attention on urban-cat populations. To truly understand cat population dynamics, the collective population of owned cats, unowned cats, and cats in the shelter system must be considered simultaneously because each subpopulation contributes differently to the overall population of cats in a community (e.g., differences in neuter rates, differences in impacts on wildlife) and cats move among categories through human interventions (e.g., adoption, abandonment). To assess this complex socio-ecological system, we developed a multistate matrix model of cats in urban areas that include owned cats, unowned cats (free-roaming and feral), and cats that move through the shelter system. Our model requires three inputs—location, number of human dwellings, and urban area—to provide testable predictions of cat abundance for any city in North America. Model-predicted population size of unowned cats in seven Canadian cities were not significantly different than published estimates (p = 0.23). Model-predicted proportions of sterile feral cats did not match observed sterile cat proportions for six USA cities (p = 0.001). Using a case study from Guelph, Ontario, Canada, we compared model-predicted to empirical estimates of cat abundance in each subpopulation and used perturbation analysis to calculate relative sensitivity of vital rates to cat abundance to demonstrate how management or mismanagement in one portion of the population could have repercussions across all portions of the network. Our study provides a general framework to consider cat population abundance in urban areas and, with refinement that includes city-specific parameter estimates and modeling, could provide a better understanding of population dynamics of cats in our communities. PMID:29489854

Multistate matrix population model to assess the contributions and impacts on population abundance of domestic cats in urban areas including owned cats, unowned cats, and cats in shelters.

PubMed

Flockhart, D T Tyler; Coe, Jason B

2018-01-01

Concerns over cat homelessness, over-taxed animal shelters, public health risks, and environmental impacts has raised attention on urban-cat populations. To truly understand cat population dynamics, the collective population of owned cats, unowned cats, and cats in the shelter system must be considered simultaneously because each subpopulation contributes differently to the overall population of cats in a community (e.g., differences in neuter rates, differences in impacts on wildlife) and cats move among categories through human interventions (e.g., adoption, abandonment). To assess this complex socio-ecological system, we developed a multistate matrix model of cats in urban areas that include owned cats, unowned cats (free-roaming and feral), and cats that move through the shelter system. Our model requires three inputs-location, number of human dwellings, and urban area-to provide testable predictions of cat abundance for any city in North America. Model-predicted population size of unowned cats in seven Canadian cities were not significantly different than published estimates (p = 0.23). Model-predicted proportions of sterile feral cats did not match observed sterile cat proportions for six USA cities (p = 0.001). Using a case study from Guelph, Ontario, Canada, we compared model-predicted to empirical estimates of cat abundance in each subpopulation and used perturbation analysis to calculate relative sensitivity of vital rates to cat abundance to demonstrate how management or mismanagement in one portion of the population could have repercussions across all portions of the network. Our study provides a general framework to consider cat population abundance in urban areas and, with refinement that includes city-specific parameter estimates and modeling, could provide a better understanding of population dynamics of cats in our communities.

Functional Response and Matrix Population Model of Podisus nigrispinus (Dallas, 1851) (Hemiptera: Pentatomidae) fed on Chrysomya putoria (Wiedemann, 1818) (Diptera: Calliphoridae) as Alternative Prey.

PubMed

Botteon, V W; Neves, J A; Godoy, W A C

2017-04-01

Among the predators with high potential for use in biological control, the species of the genus Podisus (Hemiptera: Pentatomidae) have received special attention for laboratory rearing, since they feed on different agricultural and forestry pest insects. However, the type of diet offered to insects in the laboratory may affect the viability of populations, expressed essentially by demographic parameters such as survival and fecundity. This study assessed demographic and development aspects in experimental populations of Podisus nigrispinus (Dallas, 1851) fed on larvae of Chrysomya putoria (Wiedemann, 1818) (Diptera: Calliphoridae) as an alternative prey. The demographic parameters fecundity and survival were investigated in life stages of P. nigrispinus with ecological modeling, by applying the Leslie matrix population model, producing histograms of life stages in successive time steps. The functional response of P. nigrispinus was also investigated on seven densities of C. putoria third-instar larvae at 24 and 48 h. The survival of predators that reached adulthood was 65% and the development time from egg to adult was 23.15 days. The predator showed a type III functional response for consumption of C. putoria at 24 and 48 h. The Leslie-matrix simulation of the age structure provided perpetuation of the predator population over time steps and the prey proved to be feasible for use in rearing and maintenance of P. nigrispinus in the laboratory.

EFFECTS OF HABITAT LOSS ON POPULATIONS OF WHITE-FOOTED MICE: MATRIX MODEL PREDICTIONS WITH LANDSCAPE-SCALE PERTURBATION EXPERIMENTS

EPA Science Inventory

Habitat loss is the leading cause of decline in wildlife diversity and abundance throughout the world, and understanding its impacts on animal populations is a critical challenge facing conservation biologists. Population viability analysis (PVA) is a commonly used tool for pred...

Identifying critical life stage transitions for biological control of long-lived perennial Vincetoxicum species

USDA-ARS?s Scientific Manuscript database

Demographic matrix modeling of invasive plant populations can be a powerful tool to identify key life stage transitions for targeted disruption in order to cause population decline. This approach can provide quantitative estimates of reductions in select vital rates needed to reduce population growt...

Integrating info-gap decision theory with robust population management: a case study using the Mountain Plover.

PubMed

van der Burg, Max Post; Tyre, Andrew J

2011-01-01

Wildlife managers often make decisions under considerable uncertainty. In the most extreme case, a complete lack of data leads to uncertainty that is unquantifiable. Information-gap decision theory deals with assessing management decisions under extreme uncertainty, but it is not widely used in wildlife management. So too, robust population management methods were developed to deal with uncertainties in multiple-model parameters. However, the two methods have not, as yet, been used in tandem to assess population management decisions. We provide a novel combination of the robust population management approach for matrix models with the information-gap decision theory framework for making conservation decisions under extreme uncertainty. We applied our model to the problem of nest survival management in an endangered bird species, the Mountain Plover (Charadrius montanus). Our results showed that matrix sensitivities suggest that nest management is unlikely to have a strong effect on population growth rate, confirming previous analyses. However, given the amount of uncertainty about adult and juvenile survival, our analysis suggested that maximizing nest marking effort was a more robust decision to maintain a stable population. Focusing on the twin concepts of opportunity and robustness in an information-gap model provides a useful method of assessing conservation decisions under extreme uncertainty.

Demographic responses of Pinguicula ionantha to prescribed fire: a regression-design LTRE approach.

PubMed

Kesler, Herbert C; Trusty, Jennifer L; Hermann, Sharon M; Guyer, Craig

2008-06-01

This study describes the use of periodic matrix analysis and regression-design life table response experiments (LTRE) to investigate the effects of prescribed fire on demographic responses of Pinguicula ionantha, a federally listed plant endemic to the herb bog/savanna community in north Florida. Multi-state mark-recapture models with dead recoveries were used to estimate survival and transition probabilities for over 2,300 individuals in 12 populations of P. ionantha. These estimates were applied to parameterize matrix models used in further analyses. P. ionantha demographics were found to be strongly dependent on prescribed fire events. Periodic matrix models were used to evaluate season of burn (either growing or dormant season) for fire return intervals ranging from 1 to 20 years. Annual growing and biannual dormant season fires maximized population growth rates for this species. A regression design LTRE was used to evaluate the effect of number of days since last fire on population growth. Maximum population growth rates calculated using standard asymptotic analysis were realized shortly following a burn event (<2 years), and a regression design LTRE showed that short-term fire-mediated changes in vital rates translated into observed increases in population growth. The LTRE identified fecundity and individual growth as contributing most to increases in post-fire population growth. Our analyses found that the current four-year prescribed fire return intervals used at the study sites can be significantly shortened to increase the population growth rates of this rare species. Understanding the role of fire frequency and season in creating and maintaining appropriate habitat for this species may aid in the conservation of this and other rare herb bog/savanna inhabitants.

Metapopulation dynamics of a Burrowing Owl (Speotyto cunicularia) population in Colorado

Treesearch

R. Scott Lutz; David L. Plumpton

1997-01-01

We banded 555 Burrowing Owls (Speotyto cunicularia) either as adults (after hatch year; AHY) or as young of the year (hatch year; HY) and used capture-recapture models to estimate survival and recapture rates and Leslie matrix models to project population growth over time at the 6,900-ha Rocky Mountain Arsenal National Wildlife Refuge (RMANWR),...

Periodic matrix models for seasonal dynamics of structured populations with application to a seabird population.

PubMed

Cushing, J M; Henson, Shandelle M

2018-02-03

For structured populations with an annual breeding season, life-stage interactions and behavioral tactics may occur on a faster time scale than that of population dynamics. Motivated by recent field studies of the effect of rising sea surface temperature (SST) on within-breeding-season behaviors in colonial seabirds, we formulate and analyze a general class of discrete-time matrix models designed to account for changes in behavioral tactics within the breeding season and their dynamic consequences at the population level across breeding seasons. As a specific example, we focus on egg cannibalism and the daily reproductive synchrony observed in seabirds. Using the model, we investigate circumstances under which these life history tactics can be beneficial or non-beneficial at the population level in light of the expected continued rise in SST. Using bifurcation theoretic techniques, we study the nature of non-extinction, seasonal cycles as a function of environmental resource availability as they are created upon destabilization of the extinction state. Of particular interest are backward bifurcations in that they typically create strong Allee effects in population models which, in turn, lead to the benefit of possible (initial condition dependent) survival in adverse environments. We find that positive density effects (component Allee effects) due to increased adult survival from cannibalism and the propensity of females to synchronize daily egg laying can produce a strong Allee effect due to a backward bifurcation.

DEMOGRAPHY AND VIABILITY ANALYSES OF A DIAMONDBACK TERRAPIN POPULATION

EPA Science Inventory

The diamondback terrapin Malaclemys terrapin is a long-lived species with special management requirements, but quantitative analyses to support management are lacking. I analyzed mark-recapture data and constructed an age-classified matrix population model to determine the status...

Demographic projection of high-elevation white pines infected with white pine blister rust: a nonlinear disease model

Treesearch

S. G. Field; A. W. Schoettle; J. G. Klutsch; S. J. Tavener; M. F. Antolin

2012-01-01

Matrix population models have long been used to examine and predict the fate of threatened populations. However, the majority of these efforts concentrate on long-term equilibrium dynamics of linear systems and their underlying assumptions and, therefore, omit the analysis of transience. Since management decisions are typically concerned with the short term (

Implicit assumptions underlying simple harvest models of marine bird populations can mislead environmental management decisions.

PubMed

O'Brien, Susan H; Cook, Aonghais S C P; Robinson, Robert A

2017-10-01

Assessing the potential impact of additional mortality from anthropogenic causes on animal populations requires detailed demographic information. However, these data are frequently lacking, making simple algorithms, which require little data, appealing. Because of their simplicity, these algorithms often rely on implicit assumptions, some of which may be quite restrictive. Potential Biological Removal (PBR) is a simple harvest model that estimates the number of additional mortalities that a population can theoretically sustain without causing population extinction. However, PBR relies on a number of implicit assumptions, particularly around density dependence and population trajectory that limit its applicability in many situations. Among several uses, it has been widely employed in Europe in Environmental Impact Assessments (EIA), to examine the acceptability of potential effects of offshore wind farms on marine bird populations. As a case study, we use PBR to estimate the number of additional mortalities that a population with characteristics typical of a seabird population can theoretically sustain. We incorporated this level of additional mortality within Leslie matrix models to test assumptions within the PBR algorithm about density dependence and current population trajectory. Our analyses suggest that the PBR algorithm identifies levels of mortality which cause population declines for most population trajectories and forms of population regulation. Consequently, we recommend that practitioners do not use PBR in an EIA context for offshore wind energy developments. Rather than using simple algorithms that rely on potentially invalid implicit assumptions, we recommend use of Leslie matrix models for assessing the impact of additional mortality on a population, enabling the user to explicitly define assumptions and test their importance. Copyright © 2017 Elsevier Ltd. All rights reserved.

INDIVIDUAL EFFECTS OF ESTROGENS ON A MARINE FISH, CUNNER (TAUTOGOLABRUS ADSPERSUS), EXTRAPOLATED TO POPULATION LEVEL

EPA Science Inventory

Endocrine disrupting chemicals (EDCs) in the environment may alter the population dynamics of wildlife by affecting reproductive output. This study describes a matrix modeling approach to link laboratory studies on endocrine disruption with potential ecological effects. The exper...

Quantum kinetic expansion in the spin-boson model: Matrix formulation and system-bath factorized initial state.

PubMed

Gong, Zhihao; Tang, Zhoufei; Wang, Haobin; Wu, Jianlan

2017-12-28

Within the framework of the hierarchy equation of motion (HEOM), the quantum kinetic expansion (QKE) method of the spin-boson model is reformulated in the matrix representation. The equivalence between the two formulations (HEOM matrices and quantum operators) is numerically verified from the calculation of the time-integrated QKE rates. The matrix formulation of the QKE is extended to the system-bath factorized initial state. Following a one-to-one mapping between HEOM matrices and quantum operators, a quantum kinetic equation is rederived. The rate kernel is modified by an extra term following a systematic expansion over the site-site coupling. This modified QKE is numerically tested for its reliability by calculating the time-integrated rate and non-Markovian population kinetics. For an intermediate-to-strong dissipation strength and a large site-site coupling, the population transfer is found to be significantly different when the initial condition is changed from the local equilibrium to system-bath factorized state.

The ESS and replicator equation in matrix games under time constraints.

PubMed

Garay, József; Cressman, Ross; Móri, Tamás F; Varga, Tamás

2018-06-01

Recently, we introduced the class of matrix games under time constraints and characterized the concept of (monomorphic) evolutionarily stable strategy (ESS) in them. We are now interested in how the ESS is related to the existence and stability of equilibria for polymorphic populations. We point out that, although the ESS may no longer be a polymorphic equilibrium, there is a connection between them. Specifically, the polymorphic state at which the average strategy of the active individuals in the population is equal to the ESS is an equilibrium of the polymorphic model. Moreover, in the case when there are only two pure strategies, a polymorphic equilibrium is locally asymptotically stable under the replicator equation for the pure-strategy polymorphic model if and only if it corresponds to an ESS. Finally, we prove that a strict Nash equilibrium is a pure-strategy ESS that is a locally asymptotically stable equilibrium of the replicator equation in n-strategy time-constrained matrix games.

Incorporating Temperature-driven Seasonal Variation in Survival, Growth, and Reproduction Models for Small Fish

EPA Science Inventory

Seasonal variation in survival and reproduction can be a large source of prediction uncertainty in models used for conservation and management. A seasonally varying matrix population model is developed that incorporates temperature-driven differences in mortality and reproduction...

Fibrinogen inhibits fibroblast-mediated contraction of collagen

PubMed Central

Nien, Yih-Dar; Han, Yuan-Ping; Tawil, Bill; Chan, Linda S.; Tuan, Tai-Lan; Garner, Warren L.

2008-01-01

Extracellular matrix changes in composition and organization as it transitions from the provisional matrix of the fibrin/platelet plug to collagen scar in healed wounds. The manner in which individual matrix proteins affect these activities is not well established. In this article we describe the interactions of two important extracellular matrix components, fibrin and collagen, using an in vitro model of wound contraction, the fibroblast-populated collagen lattice. We utilized different fibrinogen sources and measured tissue reorganization in floating and tensioned collagen lattices. Our results showed that both fibrin and fibrinogen decreased the contraction of fibroblast populated collagen lattices in a dose-dependent manner. Polymerization of fibrinogen to fibrin using thrombin had no effect on this inhibition. Further, there was no effect due to changes in protein concentration, alternate components of the fibrin sealant, or the enzymatic action of thrombin. These results suggest that the initial stability of the fibrin provisional matrix is due to the fibrin, because this protein appears to inhibit contraction of the matrix. This may be important in the early phases of wound healing when clot stability is vital for hemostasis. Later, as fibrin is replaced by collagen, wound contraction can occur. PMID:12950643

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

Self-emergence of Lexicon Consensus in a Population of Autonomous Agents by Means of Evolutionary Strategies

NASA Astrophysics Data System (ADS)

Maravall, Darío; de Lope, Javier; Domínguez, Raúl

In Multi-agent systems, the study of language and communication is an active field of research. In this paper we present the application of evolutionary strategies to the self-emergence of a common lexicon in a population of agents. By modeling the vocabulary or lexicon of each agent as an association matrix or look-up table that maps the meanings (i.e. the objects encountered by the agents or the states of the environment itself) into symbols or signals we check whether it is possible for the population to converge in an autonomous, decentralized way to a common lexicon, so that the communication efficiency of the entire population is optimal. We have conducted several experiments, from the simplest case of a 2×2 association matrix (i.e. two meanings and two symbols) to a 3×3 lexicon case and in both cases we have attained convergence to the optimal communication system by means of evolutionary strategies. To analyze the convergence of the population of agents we have defined the population's consensus when all the agents (i.e. the 100% of the population) share the same association matrix or lexicon. As a general conclusion we have shown that evolutionary strategies are powerful enough optimizers to guarantee the convergence to lexicon consensus in a population of autonomous agents.

Monocyte activation by smooth muscle cell-derived matrices.

PubMed

Kaufmann, J; Jorgensen, R W; Martin, B M; Franzblau, C

1990-12-01

Mononuclear phagocytes adhere to and penetrate the vessel wall endothelium and contact the subendothelial space prior to the development of the atherosclerotic plaque. In an attempt to model the early events of plaque development we used an elastin-rich, multicomponent, cell-derived matrix from neonatal rat aortic smooth muscle cells as a substratum for monocytes. Using this model, we show that human monocyte morphology and metabolism are markedly altered by the matrix substratum. When a mixed mononuclear cell population is seeded on matrix or plastic, only monocytes adhere to the matrix surface. In contrast, lymphocytes as well as monocytes adhere to the plastic surface. The matrix-adherent monocytes develop large intracellular granules and form extensive clusters of individual cells. Metabolically, these cells develop sodium fluoride resistant non-specific esterase activity and their media contain more growth factor activity and PGE2. Although total protein synthesis is equivalent in both cultures, the matrix contact induces an increase in specific proteins in the media. We also show that a purified alpha-elastin substratum induces some, but not all, of the monocyte changes seen when using the matrix substratum. Using the alpha-elastin substratum, there is selective adhesion of monocytes and increased growth factor activity, however, the cells are morphologically different from the matrix-adherent cells. Thus, the use of the smooth muscle cell-derived matrix, in conjunction with purified matrix components, serves as a model that can provide insight into the mechanisms of monocyte adhesion and stimulation by the matrix environment that exists in vivo. Such mechanisms may be particularly important in atherogenesis.

Joint refinement model for the spin resolved one-electron reduced density matrix of YTiO3 using magnetic structure factors and magnetic Compton profiles data.

PubMed

Gueddida, Saber; Yan, Zeyin; Kibalin, Iurii; Voufack, Ariste Bolivard; Claiser, Nicolas; Souhassou, Mohamed; Lecomte, Claude; Gillon, Béatrice; Gillet, Jean-Michel

2018-04-28

In this paper, we propose a simple cluster model with limited basis sets to reproduce the unpaired electron distributions in a YTiO 3 ferromagnetic crystal. The spin-resolved one-electron-reduced density matrix is reconstructed simultaneously from theoretical magnetic structure factors and directional magnetic Compton profiles using our joint refinement algorithm. This algorithm is guided by the rescaling of basis functions and the adjustment of the spin population matrix. The resulting spin electron density in both position and momentum spaces from the joint refinement model is in agreement with theoretical and experimental results. Benefits brought from magnetic Compton profiles to the entire spin density matrix are illustrated. We studied the magnetic properties of the YTiO 3 crystal along the Ti-O 1 -Ti bonding. We found that the basis functions are mostly rescaled by means of magnetic Compton profiles, while the molecular occupation numbers are mainly modified by the magnetic structure factors.

Spiked Models of Large Dimensional Random Matrices Applied to Wireless Communications and Array Signal Processing

DTIC Science & Technology

2013-12-14

population covariance matrix with application to array signal processing; and 5) a sample covariance matrix for which a CLT is studied on linear...Applications , (01 2012): 1150004. doi: Walid Hachem, Malika Kharouf, Jamal Najim, Jack W. Silverstein. A CLT FOR INFORMATION- THEORETIC STATISTICS...for Multi-source Power Estimation, (04 2010) Malika Kharouf, Jamal Najim, Jack W. Silverstein, Walid Hachem. A CLT FOR INFORMATION- THEORETIC

Maximum Likelihood Estimation in Meta-Analytic Structural Equation Modeling

ERIC Educational Resources Information Center

Oort, Frans J.; Jak, Suzanne

2016-01-01

Meta-analytic structural equation modeling (MASEM) involves fitting models to a common population correlation matrix that is estimated on the basis of correlation coefficients that are reported by a number of independent studies. MASEM typically consist of two stages. The method that has been found to perform best in terms of statistical…

Human salmonellosis: estimation of dose-illness from outbreak data.

PubMed

Bollaerts, Kaatje; Aerts, Marc; Faes, Christel; Grijspeerdt, Koen; Dewulf, Jeroen; Mintiens, Koen

2008-04-01

The quantification of the relationship between the amount of microbial organisms ingested and a specific outcome such as infection, illness, or mortality is a key aspect of quantitative risk assessment. A main problem in determining such dose-response models is the availability of appropriate data. Human feeding trials have been criticized because only young healthy volunteers are selected to participate and low doses, as often occurring in real life, are typically not considered. Epidemiological outbreak data are considered to be more valuable, but are more subject to data uncertainty. In this article, we model the dose-illness relationship based on data of 20 Salmonella outbreaks, as discussed by the World Health Organization. In particular, we model the dose-illness relationship using generalized linear mixed models and fractional polynomials of dose. The fractional polynomial models are modified to satisfy the properties of different types of dose-illness models as proposed by Teunis et al. Within these models, differences in host susceptibility (susceptible versus normal population) are modeled as fixed effects whereas differences in serovar type and food matrix are modeled as random effects. In addition, two bootstrap procedures are presented. A first procedure accounts for stochastic variability whereas a second procedure accounts for both stochastic variability and data uncertainty. The analyses indicate that the susceptible population has a higher probability of illness at low dose levels when the combination pathogen-food matrix is extremely virulent and at high dose levels when the combination is less virulent. Furthermore, the analyses suggest that immunity exists in the normal population but not in the susceptible population.

Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution.

PubMed

Han, Fang; Liu, Han

2017-02-01

Correlation matrix plays a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson's sample correlation matrix. Although Pearson's sample correlation matrix enjoys various good properties under Gaussian models, its not an effective estimator when facing heavy-tail distributions with possible outliers. As a robust alternative, Han and Liu (2013b) advocated the use of a transformed version of the Kendall's tau sample correlation matrix in estimating high dimensional latent generalized correlation matrix under the transelliptical distribution family (or elliptical copula). The transelliptical family assumes that after unspecified marginal monotone transformations, the data follow an elliptical distribution. In this paper, we study the theoretical properties of the Kendall's tau sample correlation matrix and its transformed version proposed in Han and Liu (2013b) for estimating the population Kendall's tau correlation matrix and the latent Pearson's correlation matrix under both spectral and restricted spectral norms. With regard to the spectral norm, we highlight the role of "effective rank" in quantifying the rate of convergence. With regard to the restricted spectral norm, we for the first time present a "sign subgaussian condition" which is sufficient to guarantee that the rank-based correlation matrix estimator attains the optimal rate of convergence. In both cases, we do not need any moment condition.

Climate change threatens polar bear populations: a stochastic demographic analysis.

PubMed

Hunter, Christine M; Caswell, Hal; Runge, Michael C; Regehr, Eric V; Amstrup, Steve C; Stirling, Ian

2010-10-01

The polar bear (Ursus maritimus) depends on sea ice for feeding, breeding, and movement. Significant reductions in Arctic sea ice are forecast to continue because of climate warming. We evaluated the impacts of climate change on polar bears in the southern Beaufort Sea by means of a demographic analysis, combining deterministic, stochastic, environment-dependent matrix population models with forecasts of future sea ice conditions from IPCC general circulation models (GCMs). The matrix population models classified individuals by age and breeding status; mothers and dependent cubs were treated as units. Parameter estimates were obtained from a capture-recapture study conducted from 2001 to 2006. Candidate statistical models allowed vital rates to vary with time and as functions of a sea ice covariate. Model averaging was used to produce the vital rate estimates, and a parametric bootstrap procedure was used to quantify model selection and parameter estimation uncertainty. Deterministic models projected population growth in years with more extensive ice coverage (2001-2003) and population decline in years with less ice coverage (2004-2005). LTRE (life table response experiment) analysis showed that the reduction in lambda in years with low sea ice was due primarily to reduced adult female survival, and secondarily to reduced breeding. A stochastic model with two environmental states, good and poor sea ice conditions, projected a declining stochastic growth rate, log lambdas, as the frequency of poor ice years increased. The observed frequency of poor ice years since 1979 would imply log lambdas approximately - 0.01, which agrees with available (albeit crude) observations of population size. The stochastic model was linked to a set of 10 GCMs compiled by the IPCC; the models were chosen for their ability to reproduce historical observations of sea ice and were forced with "business as usual" (A1B) greenhouse gas emissions. The resulting stochastic population projections showed drastic declines in the polar bear population by the end of the 21st century. These projections were instrumental in the decision to list the polar bear as a threatened species under the U.S. Endangered Species Act.

Climate change threatens polar bear populations: A stochastic demographic analysis

USGS Publications Warehouse

Hunter, C.M.; Caswell, H.; Runge, M.C.; Regehr, E.V.; Amstrup, Steven C.; Stirling, I.

2010-01-01

The polar bear (Ursus maritimus) depends on sea ice for feeding, breeding, and movement. Significant reductions in Arctic sea ice are forecast to continue because of climate warming. We evaluated the impacts of climate change on polar bears in the southern Beaufort Sea by means of a demographic analysis, combining deterministic, stochastic, environment-dependent matrix population models with forecasts of future sea ice conditions from IPCC general circulation models (GCMs). The matrix population models classified individuals by age and breeding status; mothers and dependent cubs were treated as units. Parameter estimates were obtained from a capture-recapture study conducted from 2001 to 2006. Candidate statistical models allowed vital rates to vary with time and as functions of a sea ice covariate. Model averaging was used to produce the vital rate estimates, and a parametric bootstrap procedure was used to quantify model selection and parameter estimation uncertainty. Deterministic models projected population growth in years with more extensive ice coverage (2001-2003) and population decline in years with less ice coverage (2004-2005). LTRE (life table response experiment) analysis showed that the reduction in ?? in years with low sea ice was due primarily to reduced adult female survival, and secondarily to reduced breeding. A stochastic model with two environmental states, good and poor sea ice conditions, projected a declining stochastic growth rate, log ??s, as the frequency of poor ice years increased. The observed frequency of poor ice years since 1979 would imply log ??s ' - 0.01, which agrees with available (albeit crude) observations of population size. The stochastic model was linked to a set of 10 GCMs compiled by the IPCC; the models were chosen for their ability to reproduce historical observations of sea ice and were forced with "business as usual" (A1B) greenhouse gas emissions. The resulting stochastic population projections showed drastic declines in the polar bear population by the end of the 21st century. These projections were instrumental in the decision to list the polar bear as a threatened species under the U.S. Endangered Species Act. ?? 2010 by the Ecological Society of America.

Matrix quality and disturbance frequency drive evolution of species behavior at habitat boundaries.

PubMed

Martin, Amanda E; Fahrig, Lenore

2015-12-01

Previous theoretical studies suggest that a species' landscape should influence the evolution of its dispersal characteristics, because landscape structure affects the costs and benefits of dispersal. However, these studies have not considered the evolution of boundary crossing, that is, the tendency of animals to cross from habitat to nonhabitat ("matrix"). It is important to understand this dispersal behavior, because of its effects on the probability of population persistence. Boundary-crossing behavior drives the rate of interaction with matrix, and thus, it influences the rate of movement among populations and the risk of dispersal mortality. We used an individual-based, spatially explicit model to simulate the evolution of boundary crossing in response to landscape structure. Our simulations predict higher evolved probabilities of boundary crossing in landscapes with more habitat, less fragmented habitat, higher-quality matrix, and more frequent disturbances (i.e., fewer generations between local population extinction events). Unexpectedly, our simulations also suggest that matrix quality and disturbance frequency have much stronger effects on the evolution of boundary crossing than either habitat amount or habitat fragmentation. Our results suggest that boundary-crossing responses are most affected by the costs of dispersal through matrix and the benefits of escaping local extinction events. Evolution of optimal behavior at habitat boundaries in response to the landscape may have implications for species in human-altered landscapes, because this behavior may become suboptimal if the landscape changes faster than the species' evolutionary response to that change. Understanding how matrix quality and habitat disturbance drive evolution of behavior at boundaries, and how this in turn influences the extinction risk of species in human-altered landscapes should help us identify species of conservation concern and target them for management.

Managing American Oystercatcher (Haematopus palliatus) population qrowth by targeting nesting season vital rates

USGS Publications Warehouse

Felton, Shilo K.; Hostetter, Nathan J.; Pollock, Kenneth H.; Simons, Theodore R.

2017-01-01

In populations of long-lived species, adult survival typically has a relatively high influence on population growth. From a management perspective, however, adult survival can be difficult to increase in some instances, so other component rates must be considered to reverse population declines. In North Carolina, USA, management to conserve the American Oystercatcher (Haematopus palliatus) targets component vital rates related to fecundity, specifically nest and chick survival. The effectiveness of such a management approach in North Carolina was assessed by creating a three-stage female-based deterministic matrix model. Isoclines were produced from the matrix model to evaluate minimum nest and chick survival rates necessary to reverse population decline, assuming all other vital rates remained stable at mean values. Assuming accurate vital rates, breeding populations within North Carolina appear to be declining. To reverse this decline, combined nest and chick survival would need to increase from 0.14 to ≤ 0.27, a rate that appears to be attainable based on historical estimates. Results are heavily dependent on assumptions of other vital rates, most notably adult survival, revealing the need for accurate estimates of all vital rates to inform management actions. This approach provides valuable insights for evaluating conservation goals for species of concern.

Contemporary and historic factors influence differently genetic differentiation and diversity in a tropical palm

PubMed Central

da Silva Carvalho, C; Ribeiro, M C; Côrtes, M C; Galetti, M; Collevatti, R G

2015-01-01

Population genetics theory predicts loss in genetic variability because of drift and inbreeding in isolated plant populations; however, it has been argued that long-distance pollination and seed dispersal may be able to maintain gene flow, even in highly fragmented landscapes. We tested how historical effective population size, historical migration and contemporary landscape structure, such as forest cover, patch isolation and matrix resistance, affect genetic variability and differentiation of seedlings in a tropical palm (Euterpe edulis) in a human-modified rainforest. We sampled 16 sites within five landscapes in the Brazilian Atlantic forest and assessed genetic variability and differentiation using eight microsatellite loci. Using a model selection approach, none of the covariates explained the variation observed in inbreeding coefficients among populations. The variation in genetic diversity among sites was best explained by historical effective population size. Allelic richness was best explained by historical effective population size and matrix resistance, whereas genetic differentiation was explained by matrix resistance. Coalescence analysis revealed high historical migration between sites within landscapes and constant historical population sizes, showing that the genetic differentiation is most likely due to recent changes caused by habitat loss and fragmentation. Overall, recent landscape changes have a greater influence on among-population genetic variation than historical gene flow process. As immediate restoration actions in landscapes with low forest amount, the development of more permeable matrices to allow the movement of pollinators and seed dispersers may be an effective strategy to maintain microevolutionary processes. PMID:25873150

Rolling Element Bearing Stiffness Matrix Determination (Presentation)

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

Guo, Y.; Parker, R.

2014-01-01

Current theoretical bearing models differ in their stiffness estimates because of different model assumptions. In this study, a finite element/contact mechanics model is developed for rolling element bearings with the focus of obtaining accurate bearing stiffness for a wide range of bearing types and parameters. A combined surface integral and finite element method is used to solve for the contact mechanics between the rolling elements and races. This model captures the time-dependent characteristics of the bearing contact due to the orbital motion of the rolling elements. A numerical method is developed to determine the full bearing stiffness matrix corresponding tomore » two radial, one axial, and two angular coordinates; the rotation about the shaft axis is free by design. This proposed stiffness determination method is validated against experiments in the literature and compared to existing analytical models and widely used advanced computational methods. The fully-populated stiffness matrix demonstrates the coupling between bearing radial, axial, and tilting bearing deflections.« less

A hybrid mathematical model of solid tumour invasion: the importance of cell adhesion.

PubMed

Anderson, Alexander R A

2005-06-01

In this paper we present a hybrid mathematical model of the invasion of healthy tissue by a solid tumour. In particular we consider early vascular growth, just after angiogenesis has occurred. We examine how the geometry of the growing tumour is affected by tumour cell heterogeneity caused by genetic mutations. As the tumour grows, mutations occur leading to a heterogeneous tumour cell population with some cells having a greater ability to migrate, proliferate or degrade the surrounding tissue. All of these cell properties are closely controlled by cell-cell and cell-matrix interactions and as such the physical geometry of the whole tumour will be dependent on these individual cell interactions. The hybrid model we develop focuses on four key variables implicated in the invasion process: tumour cells, host tissue (extracellular matrix), matrix-degradative enzymes and oxygen. The model is considered to be hybrid since the latter three variables are continuous (i.e. concentrations) and the tumour cells are discrete (i.e. individuals). With this hybrid model we examine how individual-based cell interactions (with one another and the matrix) can affect the tumour shape and discuss which of these interactions is perhaps most crucial in influencing the tumour's final structure.

Development and application of a density dependent matrix population model for Atlantic killifish (Fundulus heteroclitus)

EPA Science Inventory

Ranging along the Atlantic coast from US Florida to the Maritime Provinces of Canada, the Atlantic killifish (Fundulus heteroclitus) is an important and well-studied model organism for understanding the effects of pollutants and other stressors in estuarine and marine ecosystems....

LIKELIHOOD RATIO TESTS OF HYPOTHESES ON MULTIVARIATE POPULATIONS, VOLUME II, TEST OF HYPOTHESIS--STATISTICAL MODELS FOR THE EVALUATION AND INTERPRETATION OF EDUCATIONAL CRITERIA. PART 4.

ERIC Educational Resources Information Center

SAW, J.G.

THIS PAPER DEALS WITH SOME TESTS OF HYPOTHESIS FREQUENTLY ENCOUNTERED IN THE ANALYSIS OF MULTIVARIATE DATA. THE TYPE OF HYPOTHESIS CONSIDERED IS THAT WHICH THE STATISTICIAN CAN ANSWER IN THE NEGATIVE OR AFFIRMATIVE. THE DOOLITTLE METHOD MAKES IT POSSIBLE TO EVALUATE THE DETERMINANT OF A MATRIX OF HIGH ORDER, TO SOLVE A MATRIX EQUATION, OR TO…

The cost effectiveness of acellular dermal matrix in expander-implant immediate breast reconstruction.

PubMed

Krishnan, Naveen M; Chatterjee, Abhishek; Rosenkranz, Kari M; Powell, Stephen G; Nigriny, John F; Vidal, Dale C

2014-04-01

Expander-implant breast reconstruction is often supplemented with acellular dermal matrix (ADM). The use of acellular dermal matrix has allowed for faster, less painful expansions and improved aesthetics, but with increased cost. Our goal was to provide the first cost utility analysis of using acellular dermal matrix in two-stage, expander-implant immediate breast reconstruction following mastectomy. A comprehensive literature review was conducted to identify complication rates for two-stage, expander-implant immediate breast reconstruction with and without acellular dermal matrix. The probabilities of the most common complications were combined with Medicare Current Procedural Terminology reimbursement codes and expert utility estimates to fit into a decision model. The decision model evaluated the cost effectiveness of acellular dermal matrix relative to reconstructions without it. Retail costs for ADM were derived from the LifeCell 2012 company catalogue for Alloderm. The overall complication rates were 30% and 34.5% with and without ADM. The decision model revealed a baseline cost increase of $361.96 when acellular dermal matrix is used. The increase in Quality-Adjusted Life Years (QALYs) is 1.37 in the population with acellular dermal matrix. This yields a cost effective incremental cost-utility ratio (ICUR) of $264.20/QALY. Univariate sensitivity analysis confirmed that using acellular dermal matrix is cost effective even when using retail costs for unilateral and bilateral reconstructions. Our study shows that, despite an increased cost, acellular dermal matrix is a cost effective technology for patients undergoing two-stage, expander-implant immediate breast reconstruction due to its increased utility in successful procedures. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.

A net reproductive number for periodic matrix models.

PubMed

Cushing, J M; Ackleh, A S

2012-01-01

We give a definition of a net reproductive number R (0) for periodic matrix models of the type used to describe the dynamics of a structured population with periodic parameters. The definition is based on the familiar method of studying a periodic map by means of its (period-length) composite. This composite has an additive decomposition that permits a generalization of the Cushing-Zhou definition of R (0) in the autonomous case. The value of R (0) determines whether the population goes extinct (R (0)<1) or persists (R (0)>1). We discuss the biological interpretation of this definition and derive formulas for R (0) for two cases: scalar periodic maps of arbitrary period and periodic Leslie models of period 2. We illustrate the use of the definition by means of several examples and by applications to case studies found in the literature. We also make some comparisons of this definition of R (0) with another definition given recently by Bacaër.

Method for estimating power outages and restoration during natural and man-made events

DOEpatents

Omitaomu, Olufemi A.; Fernandez, Steven J.

2016-01-05

A method of modeling electric supply and demand with a data processor in combination with a recordable medium, and for estimating spatial distribution of electric power outages and affected populations. A geographic area is divided into cells to form a matrix. Within the matrix, supply cells are identified as containing electric substations and demand cells are identified as including electricity customers. Demand cells of the matrix are associated with the supply cells as a function of the capacity of each of the supply cells and the proximity and/or electricity demand of each of the demand cells. The method includes estimating a power outage by applying disaster event prediction information to the matrix, and estimating power restoration using the supply and demand cell information of the matrix and standardized and historical restoration information.

Statistical analysis of latent generalized correlation matrix estimation in transelliptical distribution

PubMed Central

Han, Fang; Liu, Han

2016-01-01

Correlation matrix plays a key role in many multivariate methods (e.g., graphical model estimation and factor analysis). The current state-of-the-art in estimating large correlation matrices focuses on the use of Pearson’s sample correlation matrix. Although Pearson’s sample correlation matrix enjoys various good properties under Gaussian models, its not an effective estimator when facing heavy-tail distributions with possible outliers. As a robust alternative, Han and Liu (2013b) advocated the use of a transformed version of the Kendall’s tau sample correlation matrix in estimating high dimensional latent generalized correlation matrix under the transelliptical distribution family (or elliptical copula). The transelliptical family assumes that after unspecified marginal monotone transformations, the data follow an elliptical distribution. In this paper, we study the theoretical properties of the Kendall’s tau sample correlation matrix and its transformed version proposed in Han and Liu (2013b) for estimating the population Kendall’s tau correlation matrix and the latent Pearson’s correlation matrix under both spectral and restricted spectral norms. With regard to the spectral norm, we highlight the role of “effective rank” in quantifying the rate of convergence. With regard to the restricted spectral norm, we for the first time present a “sign subgaussian condition” which is sufficient to guarantee that the rank-based correlation matrix estimator attains the optimal rate of convergence. In both cases, we do not need any moment condition. PMID:28337068

MATRIX-VBS Condensing Organic Aerosols in an Aerosol Microphysics Model

NASA Technical Reports Server (NTRS)

Gao, Chloe Y.; Tsigaridis, Konstas; Bauer, Susanne E.

2015-01-01

The condensation of organic aerosols is represented in a newly developed box-model scheme, where its effect on the growth and composition of particles are examined. We implemented the volatility-basis set (VBS) framework into the aerosol mixing state resolving microphysical scheme Multiconfiguration Aerosol TRacker of mIXing state (MATRIX). This new scheme is unique and advances the representation of organic aerosols in models in that, contrary to the traditional treatment of organic aerosols as non-volatile in most climate models and in the original version of MATRIX, this new scheme treats them as semi-volatile. Such treatment is important because low-volatility organics contribute significantly to the growth of particles. The new scheme includes several classes of semi-volatile organic compounds from the VBS framework that can partition among aerosol populations in MATRIX, thus representing the growth of particles via condensation of low volatility organic vapors. Results from test cases representing Mexico City and a Finish forrest condistions show good representation of the time evolutions of concentration for VBS species in the gas phase and in the condensed particulate phase. Emitted semi-volatile primary organic aerosols evaporate almost completely in the high volatile range, and they condense more efficiently in the low volatility range.

General Population Job Exposure Matrix Applied to a Pooled Study of Prevalent Carpal Tunnel Syndrome

PubMed Central

Dale, Ann Marie; Zeringue, Angelique; Harris-Adamson, Carisa; Rempel, David; Bao, Stephen; Thiese, Matthew S.; Merlino, Linda; Burt, Susan; Kapellusch, Jay; Garg, Arun; Gerr, Fred; Hegmann, Kurt T.; Eisen, Ellen A.; Evanoff, Bradley

2015-01-01

A job exposure matrix may be useful for the study of biomechanical workplace risk factors when individual-level exposure data are unavailable. We used job title–based exposure data from a public data source to construct a job exposure matrix and test exposure-response relationships with prevalent carpal tunnel syndrome (CTS). Exposures of repetitive motion and force from the Occupational Information Network were assigned to 3,452 active workers from several industries, enrolled between 2001 and 2008 from 6 studies. Repetitive motion and force exposures were combined into high/high, high/low, and low/low exposure groupings in each of 4 multivariable logistic regression models, adjusted for personal factors. Although force measures alone were not independent predictors of CTS in these data, strong associations between combined physical exposures of force and repetition and CTS were observed in all models. Consistent with previous literature, this report shows that workers with high force/high repetition jobs had the highest prevalence of CTS (odds ratio = 2.14–2.95) followed by intermediate values (odds ratio = 1.09–2.27) in mixed exposed jobs relative to the lowest exposed workers. This study supports the use of a general population job exposure matrix to estimate workplace physical exposures in epidemiologic studies of musculoskeletal disorders when measures of individual exposures are unavailable. PMID:25700886

Investigating the effect of chemical stress and resource ...

EPA Pesticide Factsheets

Modeling exposure and recovery of fish and wildlife populations after stressor mitigation serves as a basis for evaluating population status and remediation success. The Atlantic killifish (Fundulus heteroclitus) is an important and well-studied model organism for understanding the effects of pollutants and other stressors in estuarine and marine ecosystems. Herein, we develop a density dependent matrix population model for Atlantic killifish that analyzes both size-structure and age class-structure of the population so that we could readily incorporate output from a dynamic energy budget (DEB) model currently under development. This population modeling approach emphasizes application in conjunction with field monitoring efforts (e.g., through effects-based monitoring programs) and/or laboratory analysis to link effects due to chemical stress to adverse outcomes in whole organisms and populations. We applied the model using data for killifish exposed to dioxin-like compounds, taken from a previously published study. Specifically, the model was used to investigate population trajectories for Atlantic killifish with dietary exposures to 112, 296, and 875 pg/g of dioxin with effects on fertility and survival rates. All effects were expressed relative to control fish. Further, the population model was employed to examine age and size distributions of a population exposed to resource limitation in addition to chemical stress. For each dietary exposure concentration o

Using population models to evaluate management alternatives for Gulf Striped Bass

USGS Publications Warehouse

Aspinwall, Alexander P.; Irwin, Elise R.; Lloyd, M. Clint

2017-01-01

Interstate management of Gulf Striped Bass Morone saxatilis has involved a thirty-year cooperative effort involving Federal and State agencies in Georgia, Florida and Alabama (Apalachicola-Chattahoochee-Flint Gulf Striped Bass Technical Committee). The Committee has recently focused on developing an adaptive framework for conserving and restoring Gulf Striped Bass in the Apalachicola, Chattahoochee, and Flint River (ACF) system. To evaluate the consequences and tradeoffs among management activities, population models were used to inform management decisions. Stochastic matrix models were constructed with varying recruitment and stocking rates to simulate effects of management alternatives on Gulf Striped Bass population objectives. An age-classified matrix model that incorporated stock fecundity estimates and survival estimates was used to project population growth rate. In addition, combinations of management alternatives (stocking rates, Hydrilla control, harvest regulations) were evaluated with respect to how they influenced Gulf Striped Bass population growth. Annual survival and mortality rates were estimated from catch-curve analysis, while fecundity was estimated and predicted using a linear least squares regression analysis of fish length versus egg number from hatchery brood fish data. Stocking rates and stocked-fish survival rates were estimated from census data. Results indicated that management alternatives could be an effective approach to increasing the Gulf Striped Bass population. Population abundance was greatest under maximum stocking effort, maximum Hydrilla control and a moratorium. Conversely, population abundance was lowest under no stocking, no Hydrilla control and the current harvest regulation. Stocking rates proved to be an effective management strategy; however, low survival estimates of stocked fish (1%) limited the potential for population growth. Hydrilla control increased the survival rate of stocked fish and provided higher estimates of population abundances than maximizing the stocking rate. A change in the current harvest regulation (50% harvest regulation) was not an effective alternative to increasing the Gulf Striped Bass population size. Applying a moratorium to the Gulf Striped Bass fishery increased survival rates from 50% to 74% and resulted in the largest population growth of the individual management alternatives. These results could be used by the Committee to inform management decisions for other populations of Striped Bass in the Gulf Region.

Ecotoxicology and spatial modeling in population dynamics: an illustration with brown trout.

PubMed

Chaumot, Arnaud; Charles, Sandrine; Flammarion, Patrick; Auger, Pierre

2003-05-01

We developed a multiregion matrix population model to explore how the demography of a hypothetical brown trout population living in a river network varies in response to different spatial scenarios of cadmium contamination. Age structure, spatial distribution, and demographic and migration processes are taken into account in the model. Chronic or acute cadmium concentrations affect the demographic parameters at the scale of the river range. The outputs of the model constitute population-level end points (the asymptotic population growth rate, the stable age structure, and the asymptotic spatial distribution) that allow comparing the different spatial scenarios of contamination regarding the demographic response at the scale of the whole river network. An analysis of the sensitivity of these end points to lower order parameters enables us to link the local effects of cadmium to the global demographic behavior of the brown trout population. Such a link is of broad interest in the point of view of ecotoxicological management.

Incorporating uncertainty of management costs in sensitivity analyses of matrix population models.

PubMed

Salomon, Yacov; McCarthy, Michael A; Taylor, Peter; Wintle, Brendan A

2013-02-01

The importance of accounting for economic costs when making environmental-management decisions subject to resource constraints has been increasingly recognized in recent years. In contrast, uncertainty associated with such costs has often been ignored. We developed a method, on the basis of economic theory, that accounts for the uncertainty in population-management decisions. We considered the case where, rather than taking fixed values, model parameters are random variables that represent the situation when parameters are not precisely known. Hence, the outcome is not precisely known either. Instead of maximizing the expected outcome, we maximized the probability of obtaining an outcome above a threshold of acceptability. We derived explicit analytical expressions for the optimal allocation and its associated probability, as a function of the threshold of acceptability, where the model parameters were distributed according to normal and uniform distributions. To illustrate our approach we revisited a previous study that incorporated cost-efficiency analyses in management decisions that were based on perturbation analyses of matrix population models. Incorporating derivations from this study into our framework, we extended the model to address potential uncertainties. We then applied these results to 2 case studies: management of a Koala (Phascolarctos cinereus) population and conservation of an olive ridley sea turtle (Lepidochelys olivacea) population. For low aspirations, that is, when the threshold of acceptability is relatively low, the optimal strategy was obtained by diversifying the allocation of funds. Conversely, for high aspirations, the budget was directed toward management actions with the highest potential effect on the population. The exact optimal allocation was sensitive to the choice of uncertainty model. Our results highlight the importance of accounting for uncertainty when making decisions and suggest that more effort should be placed on understanding the distributional characteristics of such uncertainty. Our approach provides a tool to improve decision making. © 2013 Society for Conservation Biology.

Coupling Satellite Data with Species Distribution and Connectivity Models as a Tool for Environmental Management and Planning in Matrix-Sensitive Species.

PubMed

Rödder, Dennis; Nekum, Sven; Cord, Anna F; Engler, Jan O

2016-07-01

Climate change and anthropogenic habitat fragmentation are considered major threats for global biodiversity. As a direct consequence, connectivity is increasingly disrupted in many species, which might have serious consequences that could ultimately lead to the extinction of populations. Although a large number of reserves and conservation sites are designated and protected by law, potential habitats acting as inter-population connectivity corridors are, however, mostly ignored in the common practice of environmental planning. In most cases, this is mainly caused by a lack of quantitative measures of functional connectivity available for the planning process. In this study, we highlight the use of fine-scale potential connectivity models (PCMs) derived from multispectral satellite data for the quantification of spatially explicit habitat corridors for matrix-sensitive species of conservation concern. This framework couples a species distribution model with a connectivity model in a two-step framework, where suitability maps from step 1 are transformed into maps of landscape resistance in step 2 filtered by fragmentation thresholds. We illustrate the approach using the sand lizard (Lacerta agilis L.) in the metropolitan area of Cologne, Germany, as a case study. Our model proved to be well suited to identify connected as well as completely isolated populations within the study area. Furthermore, due to its fine resolution, the PCM was also able to detect small linear structures known to be important for sand lizards' inter-population connectivity such as railroad embankments. We discuss the applicability and possible implementation of PCMs to overcome shortcomings in the common practice of environmental impact assessments.

Coupling Satellite Data with Species Distribution and Connectivity Models as a Tool for Environmental Management and Planning in Matrix-Sensitive Species

NASA Astrophysics Data System (ADS)

Rödder, Dennis; Nekum, Sven; Cord, Anna F.; Engler, Jan O.

2016-07-01

Climate change and anthropogenic habitat fragmentation are considered major threats for global biodiversity. As a direct consequence, connectivity is increasingly disrupted in many species, which might have serious consequences that could ultimately lead to the extinction of populations. Although a large number of reserves and conservation sites are designated and protected by law, potential habitats acting as inter-population connectivity corridors are, however, mostly ignored in the common practice of environmental planning. In most cases, this is mainly caused by a lack of quantitative measures of functional connectivity available for the planning process. In this study, we highlight the use of fine-scale potential connectivity models (PCMs) derived from multispectral satellite data for the quantification of spatially explicit habitat corridors for matrix-sensitive species of conservation concern. This framework couples a species distribution model with a connectivity model in a two-step framework, where suitability maps from step 1 are transformed into maps of landscape resistance in step 2 filtered by fragmentation thresholds. We illustrate the approach using the sand lizard ( Lacerta agilis L.) in the metropolitan area of Cologne, Germany, as a case study. Our model proved to be well suited to identify connected as well as completely isolated populations within the study area. Furthermore, due to its fine resolution, the PCM was also able to detect small linear structures known to be important for sand lizards' inter-population connectivity such as railroad embankments. We discuss the applicability and possible implementation of PCMs to overcome shortcomings in the common practice of environmental impact assessments.

Accuracy of whole-genome prediction using a genetic architecture-enhanced variance-covariance matrix.

PubMed

Zhang, Zhe; Erbe, Malena; He, Jinlong; Ober, Ulrike; Gao, Ning; Zhang, Hao; Simianer, Henner; Li, Jiaqi

2015-02-09

Obtaining accurate predictions of unobserved genetic or phenotypic values for complex traits in animal, plant, and human populations is possible through whole-genome prediction (WGP), a combined analysis of genotypic and phenotypic data. Because the underlying genetic architecture of the trait of interest is an important factor affecting model selection, we propose a new strategy, termed BLUP|GA (BLUP-given genetic architecture), which can use genetic architecture information within the dataset at hand rather than from public sources. This is achieved by using a trait-specific covariance matrix ( T: ), which is a weighted sum of a genetic architecture part ( S: matrix) and the realized relationship matrix ( G: ). The algorithm of BLUP|GA (BLUP-given genetic architecture) is provided and illustrated with real and simulated datasets. Predictive ability of BLUP|GA was validated with three model traits in a dairy cattle dataset and 11 traits in three public datasets with a variety of genetic architectures and compared with GBLUP and other approaches. Results show that BLUP|GA outperformed GBLUP in 20 of 21 scenarios in the dairy cattle dataset and outperformed GBLUP, BayesA, and BayesB in 12 of 13 traits in the analyzed public datasets. Further analyses showed that the difference of accuracies for BLUP|GA and GBLUP significantly correlate with the distance between the T: and G: matrices. The new strategy applied in BLUP|GA is a favorable and flexible alternative to the standard GBLUP model, allowing to account for the genetic architecture of the quantitative trait under consideration when necessary. This feature is mainly due to the increased similarity between the trait-specific relationship matrix ( T: matrix) and the genetic relationship matrix at unobserved causal loci. Applying BLUP|GA in WGP would ease the burden of model selection. Copyright © 2015 Zhang et al.

From individual to population level effects of toxicants in the tubicifid Branchiura sowerbyi using threshold effect models in a Bayesian framework.

PubMed

Ducrot, Virginie; Billoir, Elise; Péry, Alexandre R R; Garric, Jeanne; Charles, Sandrine

2010-05-01

Effects of zinc were studied in the freshwater worm Branchiura sowerbyi using partial and full life-cycle tests. Only newborn and juveniles were sensitive to zinc, displaying effects on survival, growth, and age at first brood at environmentally relevant concentrations. Threshold effect models were proposed to assess toxic effects on individuals. They were fitted to life-cycle test data using Bayesian inference and adequately described life-history trait data in exposed organisms. The daily asymptotic growth rate of theoretical populations was then simulated with a matrix population model, based upon individual-level outputs. Population-level outputs were in accordance with existing literature for controls. Working in a Bayesian framework allowed incorporating parameter uncertainty in the simulation of the population-level response to zinc exposure, thus increasing the relevance of test results in the context of ecological risk assessment.

Modeling Single Well Injection-Withdrawal (SWIW) Tests for Characterization of Complex Fracture-Matrix Systems

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

Cotte, F.P.; Doughty, C.; Birkholzer, J.

2010-11-01

The ability to reliably predict flow and transport in fractured porous rock is an essential condition for performance evaluation of geologic (underground) nuclear waste repositories. In this report, a suite of programs (TRIPOLY code) for calculating and analyzing flow and transport in two-dimensional fracture-matrix systems is used to model single-well injection-withdrawal (SWIW) tracer tests. The SWIW test, a tracer test using one well, is proposed as a useful means of collecting data for site characterization, as well as estimating parameters relevant to tracer diffusion and sorption. After some specific code adaptations, we numerically generated a complex fracture-matrix system for computationmore » of steady-state flow and tracer advection and dispersion in the fracture network, along with solute exchange processes between the fractures and the porous matrix. We then conducted simulations for a hypothetical but workable SWIW test design and completed parameter sensitivity studies on three physical parameters of the rock matrix - namely porosity, diffusion coefficient, and retardation coefficient - in order to investigate their impact on the fracture-matrix solute exchange process. Hydraulic fracturing, or hydrofracking, is also modeled in this study, in two different ways: (1) by increasing the hydraulic aperture for flow in existing fractures and (2) by adding a new set of fractures to the field. The results of all these different tests are analyzed by studying the population of matrix blocks, the tracer spatial distribution, and the breakthrough curves (BTCs) obtained, while performing mass-balance checks and being careful to avoid some numerical mistakes that could occur. This study clearly demonstrates the importance of matrix effects in the solute transport process, with the sensitivity studies illustrating the increased importance of the matrix in providing a retardation mechanism for radionuclides as matrix porosity, diffusion coefficient, or retardation coefficient increase. Interestingly, model results before and after hydrofracking are insensitive to adding more fractures, while slightly more sensitive to aperture increase, making SWIW tests a possible means of discriminating between these two potential hydrofracking effects. Finally, we investigate the possibility of inferring relevant information regarding the fracture-matrix system physical parameters from the BTCs obtained during SWIW testing.« less

A modified dual-level algorithm for large-scale three-dimensional Laplace and Helmholtz equation

NASA Astrophysics Data System (ADS)

Li, Junpu; Chen, Wen; Fu, Zhuojia

2018-01-01

A modified dual-level algorithm is proposed in the article. By the help of the dual level structure, the fully-populated interpolation matrix on the fine level is transformed to a local supported sparse matrix to solve the highly ill-conditioning and excessive storage requirement resulting from fully-populated interpolation matrix. The kernel-independent fast multipole method is adopted to expediting the solving process of the linear equations on the coarse level. Numerical experiments up to 2-million fine-level nodes have successfully been achieved. It is noted that the proposed algorithm merely needs to place 2-3 coarse-level nodes in each wavelength per direction to obtain the reasonable solution, which almost down to the minimum requirement allowed by the Shannon's sampling theorem. In the real human head model example, it is observed that the proposed algorithm can simulate well computationally very challenging exterior high-frequency harmonic acoustic wave propagation up to 20,000 Hz.

Model suggests potential for Porites coral population recovery after removal of anthropogenic disturbance (Luhuitou, Hainan, South China Sea).

PubMed

Zhao, Meixia; Riegl, Bernhard; Yu, Kefu; Shi, Qi; Zhang, Qiaomin; Liu, Guohui; Yang, Hongqiang; Yan, Hongqiang

2016-09-13

Population models are important for resource management and can inform about potential trajectories useful for planning purposes, even with incomplete monitoring data. From size frequency data on Luhuitou fringing reef, Hainan, South China Sea, a matrix population model of massive corals (Porites lutea) was developed and trajectories over 100 years under no disturbance and random disturbances were projected. The model reflects a largely open population of Porites lutea, with low local recruitment and preponderance of imported recruitment. Under no further disturbance, the population of Porites lutea will grow and its size structure will change from predominance of small size classes to large size classes. Therewith, total Porites cover will increase. Even under random disturbances every 10 to 20 years, the Porites population could remain viable, albeit at lower space cover. The models suggest recovery at Luhuitou following the removal of chronic anthropogenic disturbance. Extending the area of coral reef reserves to protect the open coral community and the path of connectivity is advisable and imperative for the conservation of Hainan's coral reefs.

Model suggests potential for Porites coral population recovery after removal of anthropogenic disturbance (Luhuitou, Hainan, South China Sea)

PubMed Central

Zhao, Meixia; Riegl, Bernhard; Yu, Kefu; Shi, Qi; Zhang, Qiaomin; Liu, Guohui; Yang, Hongqiang; Yan, Hongqiang

2016-01-01

Population models are important for resource management and can inform about potential trajectories useful for planning purposes, even with incomplete monitoring data. From size frequency data on Luhuitou fringing reef, Hainan, South China Sea, a matrix population model of massive corals (Porites lutea) was developed and trajectories over 100 years under no disturbance and random disturbances were projected. The model reflects a largely open population of Porites lutea, with low local recruitment and preponderance of imported recruitment. Under no further disturbance, the population of Porites lutea will grow and its size structure will change from predominance of small size classes to large size classes. Therewith, total Porites cover will increase. Even under random disturbances every 10 to 20 years, the Porites population could remain viable, albeit at lower space cover. The models suggest recovery at Luhuitou following the removal of chronic anthropogenic disturbance. Extending the area of coral reef reserves to protect the open coral community and the path of connectivity is advisable and imperative for the conservation of Hainan’s coral reefs. PMID:27622504

Dynamic Remodeling of Microbial Biofilms by Functionally Distinct Exopolysaccharides

PubMed Central

Chew, Su Chuen; Kundukad, Binu; Seviour, Thomas; van der Maarel, Johan R. C.; Yang, Liang; Rice, Scott A.; Doyle, Patrick

2014-01-01

ABSTRACT Biofilms are densely populated communities of microbial cells protected and held together by a matrix of extracellular polymeric substances. The structure and rheological properties of the matrix at the microscale influence the retention and transport of molecules and cells in the biofilm, thereby dictating population and community behavior. Despite its importance, quantitative descriptions of the matrix microstructure and microrheology are limited. Here, particle-tracking microrheology in combination with genetic approaches was used to spatially and temporally study the rheological contributions of the major exopolysaccharides Pel and Psl in Pseudomonas aeruginosa biofilms. Psl increased the elasticity and effective cross-linking within the matrix, which strengthened its scaffold and appeared to facilitate the formation of microcolonies. Conversely, Pel reduced effective cross-linking within the matrix. Without Psl, the matrix becomes more viscous, which facilitates biofilm spreading. The wild-type biofilm decreased in effective cross-linking over time, which would be advantageous for the spreading and colonization of new surfaces. This suggests that there are regulatory mechanisms to control production of the exopolysaccharides that serve to remodel the matrix of developing biofilms. The exopolysaccharides were also found to have profound effects on the spatial organization and integration of P. aeruginosa in a mixed-species biofilm model of P. aeruginosa-Staphylococcus aureus. Pel was required for close association of the two species in mixed-species microcolonies. In contrast, Psl was important for P. aeruginosa to form single-species biofilms on top of S. aureus biofilms. Our results demonstrate that Pel and Psl have distinct physical properties and functional roles during biofilm formation. PMID:25096883

Projecting the Population-level Effects of Mercury on the Common Loon in the Northeast

NASA Astrophysics Data System (ADS)

Evers, D. C.; Mitro, M. G.; Gleason, T. R.

2001-05-01

The Common Loon (Gavia immer) is a top-level predator in aquatic systems and is at risk to mercury contamination. This risk is of particular concern in the Northeast, the region of North America in which loons have the highest mean body concentration of methylmercury (MeHg). We used matrix population models to project the population-level effects of mercury on loons in four states in the Northeast (New York, Vermont, New Hampshire, and Maine) exhibiting different levels of risk to MeHg. Four categories of risk to MeHg (low, moderate, high, and extra high) were established based on MeHg levels observed in loons and associated effects observed at the individual and population levels in the field (e.g., behavior and reproductive success). We parameterized deterministic matrix population models using survival estimates from a 12-year band-resight data set and productivity estimates from a 25-year data set of nesting loon observations in NH. The juvenile loon survival rate was 0.55 (minimum) and 0.63 (maximum) (ages 1-3), and the adult loon survival rate was 0.95 (ages 4-30). The mean age at first reproduction was 7. The mean fertility was 0.26 fledgelings per individual at low to moderate risk; there were 53% fewer fledged young per individual at high to extra high risk. Productivity was weighted by risk for each state. The portion of the breeding population at high to extra high risk was 10% in NY, 15% in VT, 17% in NH, and 28% in ME. We also constructed a stochastic model in which productivity was randomly selected in each time step from the 25 estimates in the NH data set. Model results indicated a negative population growth rate for some states. There was a decreasing trend in population growth rate as the percentage of the loon population at high to extra high risk increased. The stochastic model showed that the population growth rate varied over a range of about 0.05 from year to year, and this range decreased as the percentage of the loon population at high to extra high risk increased. These results suggest that an increase in risk to mercury that effects a change in reproductive success may have a negative population-level effect on loons.

Multilevel selection in a resource-based model.

PubMed

Ferreira, Fernando Fagundes; Campos, Paulo R A

2013-07-01

In the present work we investigate the emergence of cooperation in a multilevel selection model that assumes limiting resources. Following the work by R. J. Requejo and J. Camacho [Phys. Rev. Lett. 108, 038701 (2012)], the interaction among individuals is initially ruled by a prisoner's dilemma (PD) game. The payoff matrix may change, influenced by the resource availability, and hence may also evolve to a non-PD game. Furthermore, one assumes that the population is divided into groups, whose local dynamics is driven by the payoff matrix, whereas an intergroup competition results from the nonuniformity of the growth rate of groups. We study the probability that a single cooperator can invade and establish in a population initially dominated by defectors. Cooperation is strongly favored when group sizes are small. We observe the existence of a critical group size beyond which cooperation becomes counterselected. Although the critical size depends on the parameters of the model, it is seen that a saturation value for the critical group size is achieved. The results conform to the thought that the evolutionary history of life repeatedly involved transitions from smaller selective units to larger selective units.

Cultural interaction and biological distance in postclassic period Mexico.

PubMed

Ragsdale, Corey S; Edgar, Heather J H

2015-05-01

Economic, political, and cultural relationships connected virtually every population throughout Mexico during Postclassic period (AD 900-1520). Much of what is known about population interaction in prehistoric Mexico is based on archaeological or ethnohistoric data. What is unclear, especially for the Postclassic period, is how these data correlate with biological population structure. We address this by assessing biological (phenotypic) distances among 28 samples based upon a comparison of dental morphology trait frequencies, which serve as a proxy for genetic variation, from 810 individuals. These distances were compared with models representing geographic and cultural relationships among the same groups. Results of Mantel and partial Mantel matrix correlation tests show that shared migration and trade are correlated with biological distances, but geographic distance is not. Trade and political interaction are also correlated with biological distance when combined in a single matrix. These results indicate that trade and political relationships affected population structure among Postclassic Mexican populations. We suggest that trade likely played a major role in shaping patterns of interaction between populations. This study also shows that the biological distance data support the migration histories described in ethnohistoric sources. © 2015 Wiley Periodicals, Inc.

Dynamics of the double-crested cormorant population on Lake Ontario

USGS Publications Warehouse

Blackwell, Bradley F.; Stapanian, Martin A.; Weseloh, D.V. Chip

2002-01-01

After nearly 30 years of recolonization and expansion across North America, the double-crested cormorant (Phalacrocorax auritus) occupies the role of a perceived and, in some situations, realized threat to fish stocks and other resources. However, population data necessary to plan, defend, and implement management of this species are few. Our purpose was to gain insight into the relative contribution of various population parameters to the overall rate of population growth and identify data needs critical to improving our understanding of the dynamics of double-crested cormorant populations. We demonstrated the construction of a biologically reasonable representation of cormorant population growth on Lake Ontario (1979-2000) by referencing literature values for fertility, age at first breeding, and survival. These parameters were incorporated into a deterministic stage-classified matrix model. By calculating the elasticity of matrix elements (i.e., statgspecific fertility and survival), we found that cormorant population growth on Lake Ontario was most sensitive to survival of birds about to turn age 3 and older. Finally, we demonstrated how this information could be used to evaluate management scenarios and direct future research by simulating potential environmental effects on fertility and survival, as well as a 5-year egg-oiling program. We also demonstrated that survival of older birds exerts more effective population control than changes in fertility.

Interpretation of light scattering and turbidity measurements in aggregated systems: effect of intra-cluster multiple-light scattering.

PubMed

Soos, Miroslav; Lattuada, Marco; Sefcik, Jan

2009-11-12

In this work we studied the effect of intracluster multiple-light scattering on the scattering properties of a population of fractal aggregates. To do so, experimental data of diffusion-limited aggregation for three polystyrene latexes with similar surface properties but different primary particle diameters (equal to 118, 420, and 810 nm) were obtained by static light scattering and by means of a spectrophotometer. In parallel, a population balance equation (PBE) model, which takes into account the effect of intracluster multiple-light scattering by solving the T-matrix and the mean-field version of T-matrix, was formulated and validated against time evolution of the root mean radius of gyration, , of the zero angle intensity of scattered light, I(0), and of the turbidity, tau. It was found that the mean-field version of the T-matrix theory is able to correctly predict the time evolution of all measured light scattering quantities for all sizes of primary particles without any adjustable parameter. The structure of the aggregates, characterized by fractal dimension, d(f), was independent of the primary particle size and equal to 1.7, which is in agreement with values found in literature. Since the mean-field version of the T-matrix theory used is rather complicated and requires advanced knowledge of cluster structure (i.e., the particle-particle correlation function), a simplified version of the light scattering model was proposed and tested. It was found that within the range of operating conditions investigated, the simplified version of the light scattering model was able to describe with reasonable accuracy the time evolution of all measured light scattering quantities of the cluster mass distribution (CMD) for all three sizes of primary particles and two values of the laser wavelength.

The use of the Dutch Self-Sufficiency Matrix (SSM-D) to inform allocation decisions to public mental health care for homeless people.

PubMed

Lauriks, Steve; de Wit, Matty A S; Buster, Marcel C A; Fassaert, Thijs J L; van Wifferen, Ron; Klazinga, Niek S

2014-10-01

The current study set out to develop a decision support tool based on the Self-Sufficiency Matrix (Dutch version; SSM-D) for the clinical decision to allocate homeless people to the public mental health care system at the central access point of public mental health care in Amsterdam, The Netherlands. Logistic regression and receiver operating characteristic-curve analyses were used to model professional decisions and establish four decision categories based on SSM-D scores from half of the research population (Total n = 612). The model and decision categories were found to be accurate and reliable in predicting professional decisions in the second half of the population. Results indicate that the decision support tool based on the SSM-D is useful and feasible. The method to develop the SSM-D as a decision support tool could be applied to decision-making processes in other systems and services where the SSM-D has been implemented, to further increase the utility of the instrument.

Occupancy dynamics in a tropical bird community: unexpectedly high forest use by birds classified as non-forest species

USGS Publications Warehouse

Ruiz-Gutierrez, Viviana; Zipkin, Elise F.; Dhondt, Andre A.

2010-01-01

1. Worldwide loss of biodiversity necessitates a clear understanding of the factors driving population declines as well as informed predictions about which species and populations are at greatest risk. The biggest threat to the long-term persistence of populations is the reduction and changes in configuration of their natural habitat. 2. Inconsistencies have been noted in the responses of populations to the combined effects of habitat loss and fragmentation. These have been widely attributed to the effects of the matrix habitats in which remnant focal habitats are typically embedded. 3. We quantified the potential effects of the inter-patch matrix by estimating occupancy and colonization of forest and surrounding non-forest matrix (NF). We estimated species-specific parameters using a dynamic, multi-species hierarchical model on a bird community in southwestern Costa Rica. 4. Overall, we found higher probabilities of occupancy and colonization of forest relative to the NF across bird species, including those previously categorized as open habitat generalists not needing forest to persist. Forest dependency was a poor predictor of occupancy dynamics in our study region, largely predicting occupancy and colonization of only non-forest habitats. 5. Our results indicate that the protection of remnant forest habitats is key for the long-term persistence of all members of the bird community in this fragmented landscape, including species typically associated with open, non-forest habitats. 6.Synthesis and applications. We identified 39 bird species of conservation concern defined by having high estimates of forest occupancy, and low estimates of occupancy and colonization of non-forest. These species survive in forest but are unlikely to venture out into open, non-forested habitats, therefore, they are vulnerable to the effects of habitat loss and fragmentation. Our hierarchical community-level model can be used to estimate species-specific occupancy dynamics for focal and inter-patch matrix habitats to identify which species within a community are likely to be impacted most by habitat loss and fragmentation. This model can be applied to other taxa (i.e. amphibians, mammals and insects) to estimate species and community occurrence dynamics in response to current environmental conditions and to make predictions in response to future changes in habitat configurations.

Decoding and optimized implementation of SECDED codes over GF(q)

DOEpatents

Ward, H. Lee; Ganti, Anand; Resnick, David R

2013-10-22

A plurality of columns for a check matrix that implements a distance d linear error correcting code are populated by providing a set of vectors from which to populate the columns, and applying to the set of vectors a filter operation that reduces the set by eliminating therefrom all vectors that would, if used to populate the columns, prevent the check matrix from satisfying a column-wise linear independence requirement associated with check matrices of distance d linear codes. One of the vectors from the reduced set may then be selected to populate one of the columns. The filtering and selecting repeats iteratively until either all of the columns are populated or the number of currently unpopulated columns exceeds the number of vectors in the reduced set. Columns for the check matrix may be processed to reduce the amount of logic needed to implement the check matrix in circuit logic.

Design, decoding and optimized implementation of SECDED codes over GF(q)

DOEpatents

Ward, H Lee; Ganti, Anand; Resnick, David R

2014-06-17

A plurality of columns for a check matrix that implements a distance d linear error correcting code are populated by providing a set of vectors from which to populate the columns, and applying to the set of vectors a filter operation that reduces the set by eliminating therefrom all vectors that would, if used to populate the columns, prevent the check matrix from satisfying a column-wise linear independence requirement associated with check matrices of distance d linear codes. One of the vectors from the reduced set may then be selected to populate one of the columns. The filtering and selecting repeats iteratively until either all of the columns are populated or the number of currently unpopulated columns exceeds the number of vectors in the reduced set. Columns for the check matrix may be processed to reduce the amount of logic needed to implement the check matrix in circuit logic.

Decoding and optimized implementation of SECDED codes over GF(q)

DOEpatents

Ward, H Lee; Ganti, Anand; Resnick, David R

2014-11-18

A plurality of columns for a check matrix that implements a distance d linear error correcting code are populated by providing a set of vectors from which to populate the columns, and applying to the set of vectors a filter operation that reduces the set by eliminating therefrom all vectors that would, if used to populate the columns, prevent the check matrix from satisfying a column-wise linear independence requirement associated with check matrices of distance d linear codes. One of the vectors from the reduced set may then be selected to populate one of the columns. The filtering and selecting repeats iteratively until either all of the columns are populated or the number of currently unpopulated columns exceeds the number of vectors in the reduced set. Columns for the check matrix may be processed to reduce the amount of logic needed to implement the check matrix in circuit logic.

Expert elicitation, uncertainty, and the value of information in controlling invasive species

USGS Publications Warehouse

Johnson, Fred A.; Smith, Brian J.; Bonneau, Mathieu; Martin, Julien; Romagosa, Christina; Mazzotti, Frank J.; Waddle, J. Hardin; Reed, Robert; Eckles, Jennifer Kettevrlin; Vitt, Laurie J.

2017-01-01

We illustrate the utility of expert elicitation, explicit recognition of uncertainty, and the value of information for directing management and research efforts for invasive species, using tegu lizards (Salvator merianae) in southern Florida as a case study. We posited a post-birth pulse, matrix model in which four age classes of tegus are recognized: hatchlings, 1 year-old, 2 year-olds, and 3 + year-olds. This matrix model was parameterized using a 3-point process to elicit estimates of tegu demographic rates in southern Florida from 10 herpetology experts. We fit statistical distributions for each parameter and for each expert, then drew and pooled a large number of replicate samples from these to form a distribution for each demographic parameter. Using these distributions, as well as the observed correlations among elicited values, we generated a large sample of matrix population models to infer how the tegu population would respond to control efforts. We used the concepts of Pareto efficiency and stochastic dominance to conclude that targeting older age classes at relatively high rates appears to have the best chance of minimizing tegu abundance and control costs. We conclude that expert opinion combined with an explicit consideration of uncertainty can be valuable in conducting an initial assessment of what control strategy, effort, and monetary resources are needed to reduce and eventually eliminate the invader. Scientists, in turn, can use the value of information to focus research in a way that not only increases the efficacy of control, but minimizes costs as well.

Population characteristics and the suppression of nonnative Burbot

USGS Publications Warehouse

Klein, Zachary B.; Quist, Michael C.; Rhea, Darren T.; Senecal, Anna C.

2016-01-01

Burbot Lota lota were illegally introduced into the Green River, Wyoming, drainage and have since proliferated throughout the system. Burbot in the Green River pose a threat to native species and to socially, economically, and ecologically important recreational fisheries. Therefore, managers of the Green River are interested in implementing a suppression program for Burbot. We collected demographic data on Burbot in the Green River (summer and autumn 2013) and used the information to construct an age-based population model (female-based Leslie matrix) to simulate the population-level response of Burbot to the selective removal of different age-classes. Burbot in the Green River grew faster, matured at relatively young ages, and were highly fecund compared with other Burbot populations within the species’ native distribution. The age-structured population model, in conjunction with demographic information, indicated that the Burbot population in the Green River could be expected to increase under current conditions. The model also indicated that the Burbot population in the Green River would decline once total annual mortality reached 58%. The population growth of Burbot in the Green River was most sensitive to age-0 and age-1 mortality. The age-structured population model indicated that an increase in mortality, particularly for younger age-classes, would result in the effective suppression of the Burbot population in the Green River.

Analysis of lethal and sublethal impacts of environmental disasters on sperm whales using stochastic modeling.

PubMed

Ackleh, Azmy S; Chiquet, Ross A; Ma, Baoling; Tang, Tingting; Caswell, Hal; Veprauskas, Amy; Sidorovskaia, Natalia

2017-08-01

Mathematical models are essential for combining data from multiple sources to quantify population endpoints. This is especially true for species, such as marine mammals, for which data on vital rates are difficult to obtain. Since the effects of an environmental disaster are not fixed, we develop time-varying (nonautonomous) matrix population models that account for the eventual recovery of the environment to the pre-disaster state. We use these models to investigate how lethal and sublethal impacts (in the form of reductions in the survival and fecundity, respectively) affect the population's recovery process. We explore two scenarios of the environmental recovery process and include the effect of demographic stochasticity. Our results provide insights into the relationship between the magnitude of the disaster, the duration of the disaster, and the probability that the population recovers to pre-disaster levels or a biologically relevant threshold level. To illustrate this modeling methodology, we provide an application to a sperm whale population. This application was motivated by the 2010 Deepwater Horizon oil rig explosion in the Gulf of Mexico that has impacted a wide variety of species populations including oysters, fish, corals, and whales.

Stochastic Evolution Dynamic of the Rock-Scissors-Paper Game Based on a Quasi Birth and Death Process

NASA Astrophysics Data System (ADS)

Yu, Qian; Fang, Debin; Zhang, Xiaoling; Jin, Chen; Ren, Qiyu

2016-06-01

Stochasticity plays an important role in the evolutionary dynamic of cyclic dominance within a finite population. To investigate the stochastic evolution process of the behaviour of bounded rational individuals, we model the Rock-Scissors-Paper (RSP) game as a finite, state dependent Quasi Birth and Death (QBD) process. We assume that bounded rational players can adjust their strategies by imitating the successful strategy according to the payoffs of the last round of the game, and then analyse the limiting distribution of the QBD process for the game stochastic evolutionary dynamic. The numerical experiments results are exhibited as pseudo colour ternary heat maps. Comparisons of these diagrams shows that the convergence property of long run equilibrium of the RSP game in populations depends on population size and the parameter of the payoff matrix and noise factor. The long run equilibrium is asymptotically stable, neutrally stable and unstable respectively according to the normalised parameters in the payoff matrix. Moreover, the results show that the distribution probability becomes more concentrated with a larger population size. This indicates that increasing the population size also increases the convergence speed of the stochastic evolution process while simultaneously reducing the influence of the noise factor.

Stochastic Evolution Dynamic of the Rock-Scissors-Paper Game Based on a Quasi Birth and Death Process.

PubMed

Yu, Qian; Fang, Debin; Zhang, Xiaoling; Jin, Chen; Ren, Qiyu

2016-06-27

Stochasticity plays an important role in the evolutionary dynamic of cyclic dominance within a finite population. To investigate the stochastic evolution process of the behaviour of bounded rational individuals, we model the Rock-Scissors-Paper (RSP) game as a finite, state dependent Quasi Birth and Death (QBD) process. We assume that bounded rational players can adjust their strategies by imitating the successful strategy according to the payoffs of the last round of the game, and then analyse the limiting distribution of the QBD process for the game stochastic evolutionary dynamic. The numerical experiments results are exhibited as pseudo colour ternary heat maps. Comparisons of these diagrams shows that the convergence property of long run equilibrium of the RSP game in populations depends on population size and the parameter of the payoff matrix and noise factor. The long run equilibrium is asymptotically stable, neutrally stable and unstable respectively according to the normalised parameters in the payoff matrix. Moreover, the results show that the distribution probability becomes more concentrated with a larger population size. This indicates that increasing the population size also increases the convergence speed of the stochastic evolution process while simultaneously reducing the influence of the noise factor.

Effect of temperature on the population dynamics of Aedes aegypti

NASA Astrophysics Data System (ADS)

Yusoff, Nuraini; Tokachil, Mohd Najir

2015-10-01

Aedes aegypti is one of the main vectors in the transmission of dengue fever. Its abundance may cause the spread of the disease to be more intense. In the study of its biological life cycle, temperature was found to increase the development rate of each stage of this species and thus, accelerate the process of the development from egg to adult. In this paper, a Lefkovitch matrix model will be used to study the stage-structured population dynamics of Aedes aegypti. In constructing the transition matrix, temperature will be taken into account. As a case study, temperature recorded at the Subang Meteorological Station for year 2006 until 2010 will be used. Population dynamics of Aedes aegypti at maximum, average and minimum temperature for each year will be simulated and compared. It is expected that the higher the temperature, the faster the mosquito will breed. The result will be compared to the number of dengue fever incidences to see their relationship.

Multi-population Genomic Relationships for Estimating Current Genetic Variances Within and Genetic Correlations Between Populations.

PubMed

Wientjes, Yvonne C J; Bijma, Piter; Vandenplas, Jérémie; Calus, Mario P L

2017-10-01

Different methods are available to calculate multi-population genomic relationship matrices. Since those matrices differ in base population, it is anticipated that the method used to calculate genomic relationships affects the estimate of genetic variances, covariances, and correlations. The aim of this article is to define the multi-population genomic relationship matrix to estimate current genetic variances within and genetic correlations between populations. The genomic relationship matrix containing two populations consists of four blocks, one block for population 1, one block for population 2, and two blocks for relationships between the populations. It is known, based on literature, that by using current allele frequencies to calculate genomic relationships within a population, current genetic variances are estimated. In this article, we theoretically derived the properties of the genomic relationship matrix to estimate genetic correlations between populations and validated it using simulations. When the scaling factor of across-population genomic relationships is equal to the product of the square roots of the scaling factors for within-population genomic relationships, the genetic correlation is estimated unbiasedly even though estimated genetic variances do not necessarily refer to the current population. When this property is not met, the correlation based on estimated variances should be multiplied by a correction factor based on the scaling factors. In this study, we present a genomic relationship matrix which directly estimates current genetic variances as well as genetic correlations between populations. Copyright © 2017 by the Genetics Society of America.

Pseudomonas biofilm matrix composition and niche biology

PubMed Central

Mann, Ethan E.; Wozniak, Daniel J.

2014-01-01

Biofilms are a predominant form of growth for bacteria in the environment and in the clinic. Critical for biofilm development are adherence, proliferation, and dispersion phases. Each of these stages includes reinforcement by, or modulation of, the extracellular matrix. Pseudomonas aeruginosa has been a model organism for the study of biofilm formation. Additionally, other Pseudomonas species utilize biofilm formation during plant colonization and environmental persistence. Pseudomonads produce several biofilm matrix molecules, including polysaccharides, nucleic acids, and proteins. Accessory matrix components shown to aid biofilm formation and adaptability under varying conditions are also produced by pseudomonads. Adaptation facilitated by biofilm formation allows for selection of genetic variants with unique and distinguishable colony morphology. Examples include rugose small-colony variants and wrinkly spreaders (WS), which over produce Psl/Pel or cellulose, respectively, and mucoid bacteria that over produce alginate. The well-documented emergence of these variants suggests that pseudomonads take advantage of matrix-building subpopulations conferring specific benefits for the entire population. This review will focus on various polysaccharides as well as additional Pseudomonas biofilm matrix components. Discussions will center on structure–function relationships, regulation, and the role of individual matrix molecules in niche biology. PMID:22212072

How feeling betrayed affects cooperation.

PubMed

Ramazi, Pouria; Hessel, Jop; Cao, Ming

2015-01-01

For a population of interacting self-interested agents, we study how the average cooperation level is affected by some individuals' feelings of being betrayed and guilt. We quantify these feelings as adjusted payoffs in asymmetric games, where for different emotions, the payoff matrix takes the structure of that of either a prisoner's dilemma or a snowdrift game. Then we analyze the evolution of cooperation in a well-mixed population of agents, each of whom is associated with such a payoff matrix. At each time-step, an agent is randomly chosen from the population to update her strategy based on the myopic best-response update rule. According to the simulations, decreasing the feeling of being betrayed in a portion of agents does not necessarily increase the level of cooperation in the population. However, this resistance of the population against low-betrayal-level agents is effective only up to some extend that is explicitly determined by the payoff matrices and the number of agents associated with these matrices. Two other models are also considered where the betrayal factor of an agent fluctuates as a function of the number of cooperators and defectors that she encounters. Unstable behaviors are observed for the level of cooperation in these cases; however, we show that one can tune the parameters in the function to make the whole population become cooperative or defective.

Rapid population growth of a critically endangered carnivore.

PubMed

Grenier, M B; McDonald, D B; Buskirk, S W

2007-08-10

Reintroductions of endangered species are controversial because of high costs and frequent failures. However, the population of black-footed ferrets descended from animals released in Shirley Basin, Wyoming, from 1991 to 1994 has grown rapidly after a decline to a low of five animals in 1997. Beginning around 2000, the population grew rapidly to an estimated 223 (95% confidence interval is 192 to 401) individuals in 2006. Matrix population modeling shows the importance of survival and reproduction during the first year of life, reflecting an uncommon life history for an endangered mammalian carnivore. Recovery of the species may benefit from more opportunistic and widespread releases.

Frequency-dependent population dynamics: effect of sex ratio and mating system on the elasticity of population growth rate.

PubMed

Haridas, C V; Eager, Eric Alan; Rebarber, Richard; Tenhumberg, Brigitte

2014-11-01

When vital rates depend on population structure (e.g., relative frequencies of males or females), an important question is how the long-term population growth rate λ responds to changes in rates. For instance, availability of mates may depend on the sex ratio of the population and hence reproductive rates could be frequency-dependent. In such cases change in any vital rate alters the structure, which in turn, affect frequency-dependent rates. We show that the elasticity of λ to a rate is the sum of (i) the effect of the linear change in the rate and (ii) the effect of nonlinear changes in frequency-dependent rates. The first component is always positive and is the classical elasticity in density-independent models obtained directly from the population projection matrix. The second component can be positive or negative and is absent in density-independent models. We explicitly express each component of the elasticity as a function of vital rates, eigenvalues and eigenvectors of the population projection matrix. We apply this result to a two-sex model, where male and female fertilities depend on adult sex ratio α (ratio of females to males) and the mating system (e.g., polygyny) through a harmonic mating function. We show that the nonlinear component of elasticity to a survival rate is negligible only when the average number of mates (per male) is close to α. In a strictly monogamous species, elasticity to female survival is larger than elasticity to male survival when α<1 (less females). In a polygynous species, elasticity to female survival can be larger than that of male survival even when sex ratio is female biased. Our results show how demography and mating system together determine the response to selection on sex-specific vital rates. Copyright © 2014 Elsevier Inc. All rights reserved.

Multilevel selection in a resource-based model

NASA Astrophysics Data System (ADS)

Ferreira, Fernando Fagundes; Campos, Paulo R. A.

2013-07-01

In the present work we investigate the emergence of cooperation in a multilevel selection model that assumes limiting resources. Following the work by R. J. Requejo and J. Camacho [Phys. Rev. Lett.0031-900710.1103/PhysRevLett.108.038701 108, 038701 (2012)], the interaction among individuals is initially ruled by a prisoner's dilemma (PD) game. The payoff matrix may change, influenced by the resource availability, and hence may also evolve to a non-PD game. Furthermore, one assumes that the population is divided into groups, whose local dynamics is driven by the payoff matrix, whereas an intergroup competition results from the nonuniformity of the growth rate of groups. We study the probability that a single cooperator can invade and establish in a population initially dominated by defectors. Cooperation is strongly favored when group sizes are small. We observe the existence of a critical group size beyond which cooperation becomes counterselected. Although the critical size depends on the parameters of the model, it is seen that a saturation value for the critical group size is achieved. The results conform to the thought that the evolutionary history of life repeatedly involved transitions from smaller selective units to larger selective units.

Ancestral haplotype-based association mapping with generalized linear mixed models accounting for stratification.

PubMed

Zhang, Z; Guillaume, F; Sartelet, A; Charlier, C; Georges, M; Farnir, F; Druet, T

2012-10-01

In many situations, genome-wide association studies are performed in populations presenting stratification. Mixed models including a kinship matrix accounting for genetic relatedness among individuals have been shown to correct for population and/or family structure. Here we extend this methodology to generalized linear mixed models which properly model data under various distributions. In addition we perform association with ancestral haplotypes inferred using a hidden Markov model. The method was shown to properly account for stratification under various simulated scenari presenting population and/or family structure. Use of ancestral haplotypes resulted in higher power than SNPs on simulated datasets. Application to real data demonstrates the usefulness of the developed model. Full analysis of a dataset with 4600 individuals and 500 000 SNPs was performed in 2 h 36 min and required 2.28 Gb of RAM. The software GLASCOW can be freely downloaded from www.giga.ulg.ac.be/jcms/prod_381171/software. francois.guillaume@jouy.inra.fr Supplementary data are available at Bioinformatics online.

First-order transitions and thermodynamic properties in the 2D Blume-Capel model: the transfer-matrix method revisited

NASA Astrophysics Data System (ADS)

Jung, Moonjung; Kim, Dong-Hee

2017-12-01

We investigate the first-order transition in the spin-1 two-dimensional Blume-Capel model in square lattices by revisiting the transfer-matrix method. With large strip widths increased up to the size of 18 sites, we construct the detailed phase coexistence curve which shows excellent quantitative agreement with the recent advanced Monte Carlo results. In the deep first-order area, we observe the exponential system-size scaling of the spectral gap of the transfer matrix from which linearly increasing interfacial tension is deduced with decreasing temperature. We find that the first-order signature at low temperatures is strongly pronounced with much suppressed finite-size influence in the examined thermodynamic properties of entropy, non-zero spin population, and specific heat. It turns out that the jump at the transition becomes increasingly sharp as it goes deep into the first-order area, which is in contrast to the Wang-Landau results where finite-size smoothing gets more severe at lower temperatures.

Concomitant use of the matrix strategy and the mand-model procedure in teaching graphic symbol combinations.

PubMed

Nigam, Ravi; Schlosser, Ralf W; Lloyd, Lyle L

2006-09-01

Matrix strategies employing parts of speech arranged in systematic language matrices and milieu language teaching strategies have been successfully used to teach word combining skills to children who have cognitive disabilities and some functional speech. The present study investigated the acquisition and generalized production of two-term semantic relationships in a new population using new types of symbols. Three children with cognitive disabilities and little or no functional speech were taught to combine graphic symbols. The matrix strategy and the mand-model procedure were used concomitantly as intervention procedures. A multiple probe design across sets of action-object combinations with generalization probes of untrained combinations was used to teach the production of graphic symbol combinations. Results indicated that two of the three children learned the early syntactic-semantic rule of combining action-object symbols and demonstrated generalization to untrained action-object combinations and generalization across trainers. The results and future directions for research are discussed.

Landscape attributes as drivers of the geographical variation in density of Sapajus nigritus Kerr, 1792, a primate endemic to the Atlantic Forest

NASA Astrophysics Data System (ADS)

Hendges, Carla D.; Melo, Geruza L.; Gonçalves, Alberto S.; Cerezer, Felipe O.; Cáceres, Nilton C.

2017-10-01

Neotropical primates are among the most well studied forest mammals concerning their population densities. However, few studies have evaluated the factors that influence the spatial variation in the population density of primates, which limits the possibility of inferences towards this animal group, especially at the landscape-level. Here, we compiled density data of Sapajus nigritus from 21 forest patches of the Brazilian Atlantic Forest. We tested the effects of climatic variables (temperature, precipitation), landscape attributes (number of patches, mean inter-patch isolation distance, matrix modification index) and patch size on the population density using linear models and the Akaike information criterion. Our findings showed that the density of S. nigritus is influenced by landscape attributes, particularly by fragmentation and matrix modification. Overall, moderately fragmented landscapes and those surrounded by matrices with intermediate indexes of temporal modification (i.e., crop plantations, forestry) are related to high densities of this species. These results support the assumptions that ecologically flexible species respond positively to forest fragmentation. However, the non-linear relationship between S. nigritus density and number of patches suggests that even the species that are most tolerant to forest cover changes seem to respond positively only at an intermediate level of habitat fragmentation, being dependent of both a moderate degree of forest cover and a high quality matrix. The results we found here can be a common response to fragmentation for those forest dweller species that are able to use the matrix as complementary foraging sites.

Connectivity, passability and heterogeneity interact to determine fish population persistence in river networks

PubMed Central

Samia, Yasmine; Lutscher, Frithjof; Hastings, Alan

2015-01-01

The movement of fish in watersheds is frequently inhibited by human-made migration barriers such as dams or culverts. The resulting lack of connectivity of spatial subpopulations is often cited as a cause for observed population decline. We formulate a matrix model for a spatially distributed fish population in a watershed, and we investigate how location and other characteristics of a single movement barrier impact the asymptotic growth rate of the population. We find that while population growth rate often decreases with the introduction of a movement obstacle, it may also increase due to a ‘retention effect’. Furthermore, obstacle mortality greatly affects population growth rate. In practice, different connectivity indices are used to predict population effects of migration barriers, but the relation of these indices to population growth rates in demographic models is often unclear. When comparing our results with the dentritic connectivity index, we see that the index captures neither the retention effect nor the influences of obstacle mortality. We argue that structural indices cannot entirely replace more detailed demographic models to understand questions of persistence and extinction. We advocate the development of novel functional indices and characteristics. PMID:26311313

Connectivity, passability and heterogeneity interact to determine fish population persistence in river networks.

PubMed

Samia, Yasmine; Lutscher, Frithjof; Hastings, Alan

2015-09-06

The movement of fish in watersheds is frequently inhibited by human-made migration barriers such as dams or culverts. The resulting lack of connectivity of spatial subpopulations is often cited as a cause for observed population decline. We formulate a matrix model for a spatially distributed fish population in a watershed, and we investigate how location and other characteristics of a single movement barrier impact the asymptotic growth rate of the population. We find that while population growth rate often decreases with the introduction of a movement obstacle, it may also increase due to a 'retention effect'. Furthermore, obstacle mortality greatly affects population growth rate. In practice, different connectivity indices are used to predict population effects of migration barriers, but the relation of these indices to population growth rates in demographic models is often unclear. When comparing our results with the dentritic connectivity index, we see that the index captures neither the retention effect nor the influences of obstacle mortality. We argue that structural indices cannot entirely replace more detailed demographic models to understand questions of persistence and extinction. We advocate the development of novel functional indices and characteristics. © 2015 The Author(s).

Population clustering based on copy number variations detected from next generation sequencing data.

PubMed

Duan, Junbo; Zhang, Ji-Gang; Wan, Mingxi; Deng, Hong-Wen; Wang, Yu-Ping

2014-08-01

Copy number variations (CNVs) can be used as significant bio-markers and next generation sequencing (NGS) provides a high resolution detection of these CNVs. But how to extract features from CNVs and further apply them to genomic studies such as population clustering have become a big challenge. In this paper, we propose a novel method for population clustering based on CNVs from NGS. First, CNVs are extracted from each sample to form a feature matrix. Then, this feature matrix is decomposed into the source matrix and weight matrix with non-negative matrix factorization (NMF). The source matrix consists of common CNVs that are shared by all the samples from the same group, and the weight matrix indicates the corresponding level of CNVs from each sample. Therefore, using NMF of CNVs one can differentiate samples from different ethnic groups, i.e. population clustering. To validate the approach, we applied it to the analysis of both simulation data and two real data set from the 1000 Genomes Project. The results on simulation data demonstrate that the proposed method can recover the true common CNVs with high quality. The results on the first real data analysis show that the proposed method can cluster two family trio with different ancestries into two ethnic groups and the results on the second real data analysis show that the proposed method can be applied to the whole-genome with large sample size consisting of multiple groups. Both results demonstrate the potential of the proposed method for population clustering.

Dust models compatible with Planck intensity and polarization data in translucent lines of sight

NASA Astrophysics Data System (ADS)

Guillet, V.; Fanciullo, L.; Verstraete, L.; Boulanger, F.; Jones, A. P.; Miville-Deschênes, M.-A.; Ysard, N.; Levrier, F.; Alves, M.

2018-02-01

Context. Current dust models are challenged by the dust properties inferred from the analysis of Planck observations in total and polarized emission. Aims: We propose new dust models compatible with polarized and unpolarized data in extinction and emission for translucent lines of sight (0.5 < AV < 2.5). Methods: We amended the DustEM tool to model polarized extinction and emission. We fit the spectral dependence of the mean extinction, polarized extinction, total and polarized spectral energy distributions (SEDs) with polycyclic aromatic hydrocarbons, astrosilicate and amorphous carbon (a-C) grains. The astrosilicate population is aligned along the magnetic field lines, while the a-C population may be aligned or not. Results: With their current optical properties, oblate astrosilicate grains are not emissive enough to reproduce the emission to extinction polarization ratio P353/pV derived with Planck data. Successful models are those using prolate astrosilicate grains with an elongation a/b = 3 and an inclusion of 20% porosity. The spectral dependence of the polarized SED is steeper in our models than in the data. Models perform slightly better when a-C grains are aligned. A small (6%) volume inclusion of a-C in the astrosilicate matrix removes the need for porosity and perfect grain alignment, and improves the fit to the polarized SED. Conclusions: Dust models based on astrosilicates can be reconciled with data by adapting the shape of grains and adding inclusions of porosity or a-C in the astrosilicate matrix.

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...

Modelling the initial phase of an epidemic using incidence and infection network data: 2009 H1N1 pandemic in Israel as a case study

PubMed Central

Katriel, G.; Yaari, R.; Huppert, A.; Roll, U.; Stone, L.

2011-01-01

This paper presents new computational and modelling tools for studying the dynamics of an epidemic in its initial stages that use both available incidence time series and data describing the population's infection network structure. The work is motivated by data collected at the beginning of the H1N1 pandemic outbreak in Israel in the summer of 2009. We formulated a new discrete-time stochastic epidemic SIR (susceptible-infected-recovered) model that explicitly takes into account the disease's specific generation-time distribution and the intrinsic demographic stochasticity inherent to the infection process. Moreover, in contrast with many other modelling approaches, the model allows direct analytical derivation of estimates for the effective reproductive number (Re) and of their credible intervals, by maximum likelihood and Bayesian methods. The basic model can be extended to include age–class structure, and a maximum likelihood methodology allows us to estimate the model's next-generation matrix by combining two types of data: (i) the incidence series of each age group, and (ii) infection network data that provide partial information of ‘who-infected-who’. Unlike other approaches for estimating the next-generation matrix, the method developed here does not require making a priori assumptions about the structure of the next-generation matrix. We show, using a simulation study, that even a relatively small amount of information about the infection network greatly improves the accuracy of estimation of the next-generation matrix. The method is applied in practice to estimate the next-generation matrix from the Israeli H1N1 pandemic data. The tools developed here should be of practical importance for future investigations of epidemics during their initial stages. However, they require the availability of data which represent a random sample of the real epidemic process. We discuss the conditions under which reporting rates may or may not influence our estimated quantities and the effects of bias. PMID:21247949

Structured Modeling and Analysis of Stochastic Epidemics with Immigration and Demographic Effects

PubMed Central

Baumann, Hendrik; Sandmann, Werner

2016-01-01

Stochastic epidemics with open populations of variable population sizes are considered where due to immigration and demographic effects the epidemic does not eventually die out forever. The underlying stochastic processes are ergodic multi-dimensional continuous-time Markov chains that possess unique equilibrium probability distributions. Modeling these epidemics as level-dependent quasi-birth-and-death processes enables efficient computations of the equilibrium distributions by matrix-analytic methods. Numerical examples for specific parameter sets are provided, which demonstrates that this approach is particularly well-suited for studying the impact of varying rates for immigration, births, deaths, infection, recovery from infection, and loss of immunity. PMID:27010993

Structured Modeling and Analysis of Stochastic Epidemics with Immigration and Demographic Effects.

PubMed

Baumann, Hendrik; Sandmann, Werner

2016-01-01

Stochastic epidemics with open populations of variable population sizes are considered where due to immigration and demographic effects the epidemic does not eventually die out forever. The underlying stochastic processes are ergodic multi-dimensional continuous-time Markov chains that possess unique equilibrium probability distributions. Modeling these epidemics as level-dependent quasi-birth-and-death processes enables efficient computations of the equilibrium distributions by matrix-analytic methods. Numerical examples for specific parameter sets are provided, which demonstrates that this approach is particularly well-suited for studying the impact of varying rates for immigration, births, deaths, infection, recovery from infection, and loss of immunity.

Modelling the dynamics of feral alfalfa populations and its management implications.

PubMed

Bagavathiannan, Muthukumar V; Begg, Graham S; Gulden, Robert H; Van Acker, Rene C

2012-01-01

Feral populations of cultivated crops can pose challenges to novel trait confinement within agricultural landscapes. Simulation models can be helpful in investigating the underlying dynamics of feral populations and determining suitable management options. We developed a stage-structured matrix population model for roadside feral alfalfa populations occurring in southern Manitoba, Canada. The model accounted for the existence of density-dependence and recruitment subsidy in feral populations. We used the model to investigate the long-term dynamics of feral alfalfa populations, and to evaluate the effectiveness of simulated management strategies such as herbicide application and mowing in controlling feral alfalfa. Results suggest that alfalfa populations occurring in roadside habitats can be persistent and less likely to go extinct under current roadverge management scenarios. Management attempts focused on controlling adult plants alone can be counterproductive due to the presence of density-dependent effects. Targeted herbicide application, which can achieve complete control of seedlings, rosettes and established plants, will be an effective strategy, but the seedbank population may contribute to new recruits. In regions where roadside mowing is regularly practiced, devising a timely mowing strategy (early- to mid-August for southern Manitoba), one that can totally prevent seed production, will be a feasible option for managing feral alfalfa populations. Feral alfalfa populations can be persistent in roadside habitats. Timely mowing or regular targeted herbicide application will be effective in managing feral alfalfa populations and limit feral-population-mediated gene flow in alfalfa. However, in the context of novel trait confinement, the extent to which feral alfalfa populations need to be managed will be dictated by the tolerance levels established by specific production systems for specific traits. The modelling framework outlined in this paper could be applied to other perennial herbaceous plants with similar life-history characteristics.

EDENetworks: a user-friendly software to build and analyse networks in biogeography, ecology and population genetics.

PubMed

Kivelä, Mikko; Arnaud-Haond, Sophie; Saramäki, Jari

2015-01-01

The recent application of graph-based network theory analysis to biogeography, community ecology and population genetics has created a need for user-friendly software, which would allow a wider accessibility to and adaptation of these methods. EDENetworks aims to fill this void by providing an easy-to-use interface for the whole analysis pipeline of ecological and evolutionary networks starting from matrices of species distributions, genotypes, bacterial OTUs or populations characterized genetically. The user can choose between several different ecological distance metrics, such as Bray-Curtis or Sorensen distance, or population genetic metrics such as FST or Goldstein distances, to turn the raw data into a distance/dissimilarity matrix. This matrix is then transformed into a network by manual or automatic thresholding based on percolation theory or by building the minimum spanning tree. The networks can be visualized along with auxiliary data and analysed with various metrics such as degree, clustering coefficient, assortativity and betweenness centrality. The statistical significance of the results can be estimated either by resampling the original biological data or by null models based on permutations of the data. © 2014 John Wiley & Sons Ltd.

Effects of Hydrogel Stiffness and Extracellular Compositions on Modulating Cartilage Regeneration by Mixed Populations of Stem Cells and Chondrocytes In Vivo.

PubMed

Wang, Tianyi; Lai, Janice H; Yang, Fan

2016-12-01

Cell-based therapies offer great promise for repairing cartilage. Previous strategies often involved using a single cell population such as stem cells or chondrocytes. A mixed cell population may offer an alternative strategy for cartilage regeneration while overcoming donor scarcity. We have recently reported that adipose-derived stem cells (ADSCs) can catalyze neocartilage formation by neonatal chondrocytes (NChons) when mixed co-cultured in 3D hydrogels in vitro. However, it remains unknown how the biochemical and mechanical cues of hydrogels modulate cartilage formation by mixed cell populations in vivo. The present study seeks to answer this question by co-encapsulating ADSCs and NChons in 3D hydrogels with tunable stiffness (∼1-33 kPa) and biochemical cues, and evaluating cartilage formation in vivo using a mouse subcutaneous model. Three extracellular matrix molecules were examined, including chondroitin sulfate (CS), hyaluronic acid (HA), and heparan sulfate (HS). Our results showed that the type of biochemical cue played a dominant role in modulating neocartilage deposition. CS and HA enhanced type II collagen deposition, a desirable phenotype for articular cartilage. In contrast, HS promoted fibrocartilage phenotype with the upregulation of type I collagen and failed to retain newly deposited matrix. Hydrogels with stiffnesses of ∼7-33 kPa led to a comparable degree of neocartilage formation, and a minimal initial stiffness was required to retain hydrogel integrity over time. Results from this study highlight the important role of matrix cues in directing neocartilage formation, and they offer valuable insights in guiding optimal scaffold design for cartilage regeneration by using mixed cell populations.

Patch Size, Functional Isolation, Visibility and Matrix Permeability Influences Neotropical Primate Occurrence within Highly Fragmented Landscapes

PubMed Central

da Silva, Lucas Goulart; Ribeiro, Milton Cezar; Hasui, Érica; da Costa, Carla Aparecida; da Cunha, Rogério Grassetto Teixeira

2015-01-01

Forest fragmentation and habitat loss are among the major current extinction causes. Remaining fragments are mostly small, isolated and showing poor quality. Being primarily arboreal, Neotropical primates are generally sensitive to fragmentation effects. Furthermore, primates are involved in complex ecological process. Thus, landscape changes that negatively interfere with primate population dynamic affect the structure, composition, and ultimately the viability of the whole community. We evaluated if fragment size, isolation and visibility and matrix permeability are important for explaining the occurrence of three Neotropical primate species. Employing playback, we verified the presence of Callicebus nigrifrons, Callithrix aurita and Sapajus nigritus at 45 forest fragments around the municipality of Alfenas, Brazil. We classified the landscape and evaluated the metrics through predictive models of occurrence. We selected the best models through Akaike Selection Criterion. Aiming at validating our results, we applied the plausible models to another region (20 fragments at the neighboring municipality of Poço Fundo, Brazil). Twelve models were plausible, and three were validated, two for Sapajus nigritus (Area and Area+Visibility) and one for Callicebus nigrifrons (Area+Matrix). Our results reinforce the contribution of fragment size to maintain biodiversity within highly degraded habitats. At the same time, they stress the importance of including novel, biologically relevant metrics in landscape studies, such as visibility and matrix permeability, which can provide invaluable help for similar studies in the future and on conservation practices in the long run. PMID:25658108

The role of beetle marks and flower colour on visitation by monkey beetles (hopliini) in the greater cape floral region, South Africa.

PubMed

Van Kleunen, Mark; Nänni, Ingrid; Donaldson, John S; Manning, John C

2007-12-01

A deviation from the classical beetle pollination syndrome of dull-coloured flowers with an unpleasant scent is found in the Greater Cape Floral Region of South Africa. Here, monkey beetles (Scarabaeidae) visit brightly coloured, odourless flowers with conspicuous dark spots and centres (beetle marks). The role of flower colour and markings in attracting monkey beetles is still poorly understood. Artificial model flowers with different marking patterns were used to test the effect of beetle marks on visitation by monkey beetles. To test whether monkey beetles are conditioned to the colour of the local matrix species, model flowers of different colours were placed in populations of three differently coloured species of Iridaceae. Among all three matrix species the presence of dark markings of some kind (either centres or spots) increased visitation rates but the different matrix species differed in whether the effect was due to a dark centre or to dark spots. Monkey beetles were not conditioned for the colour of the matrix species: model colour was not significant in the Hesperantha vaginata and in the Romulea monadelpha matrices, whereas yellow model flowers were preferred over orange ones in the orange-flowered Sparaxis elegans matrix. This study is the first to demonstrate that beetle marks attract pollinating monkey beetles in the Greater Cape Floral Region. In contrast to plants with the classical beetle pollination syndrome that use floral scent as the most important attractant of pollinating beetles, plants with the monkey beetle pollination syndrome rely on visual signals, and, in some areas at least, monkey beetles favour flowers with dark beetle markings over unmarked flowers.

Modelling dynamic fronto-parietal behaviour during minimally invasive surgery--a Markovian trip distribution approach.

PubMed

Leff, Daniel Richard; Orihuela-Espina, Felipe; Leong, Julian; Darzi, Ara; Yang, Guang-Zhong

2008-01-01

Learning to perform Minimally Invasive Surgery (MIS) requires considerable attention, concentration and spatial ability. Theoretically, this leads to activation in executive control (prefrontal) and visuospatial (parietal) centres of the brain. A novel approach is presented in this paper for analysing the flow of fronto-parietal haemodynamic behaviour and the associated variability between subjects. Serially acquired functional Near Infrared Spectroscopy (fNIRS) data from fourteen laparoscopic novices at different stages of learning is projected into a low-dimensional 'geospace', where sequentially acquired data is mapped to different locations. A trip distribution matrix based on consecutive directed trips between locations in the geospace reveals confluent fronto-parietal haemodynamic changes and a gravity model is applied to populate this matrix. To model global convergence in haemodynamic behaviour, a Markov chain is constructed and by comparing sequential haemodynamic distributions to the Markov's stationary distribution, inter-subject variability in learning an MIS task can be identified.

Bayesian Modeling of Prion Disease Dynamics in Mule Deer Using Population Monitoring and Capture-Recapture Data

PubMed Central

Geremia, Chris; Miller, Michael W.; Hoeting, Jennifer A.; Antolin, Michael F.; Hobbs, N. Thompson

2015-01-01

Epidemics of chronic wasting disease (CWD) of North American Cervidae have potential to harm ecosystems and economies. We studied a migratory population of mule deer (Odocoileus hemionus) affected by CWD for at least three decades using a Bayesian framework to integrate matrix population and disease models with long-term monitoring data and detailed process-level studies. We hypothesized CWD prevalence would be stable or increase between two observation periods during the late 1990s and after 2010, with higher CWD prevalence making deer population decline more likely. The weight of evidence suggested a reduction in the CWD outbreak over time, perhaps in response to intervening harvest-mediated population reductions. Disease effects on deer population growth under current conditions were subtle with a 72% chance that CWD depressed population growth. With CWD, we forecasted a growth rate near one and largely stable deer population. Disease effects appear to be moderated by timing of infection, prolonged disease course, and locally variable infection. Long-term outcomes will depend heavily on whether current conditions hold and high prevalence remains a localized phenomenon. PMID:26509806

Computing the structural influence matrix for biological systems.

PubMed

Giordano, Giulia; Cuba Samaniego, Christian; Franco, Elisa; Blanchini, Franco

2016-06-01

We consider the problem of identifying structural influences of external inputs on steady-state outputs in a biological network model. We speak of a structural influence if, upon a perturbation due to a constant input, the ensuing variation of the steady-state output value has the same sign as the input (positive influence), the opposite sign (negative influence), or is zero (perfect adaptation), for any feasible choice of the model parameters. All these signs and zeros can constitute a structural influence matrix, whose (i, j) entry indicates the sign of steady-state influence of the jth system variable on the ith variable (the output caused by an external persistent input applied to the jth variable). Each entry is structurally determinate if the sign does not depend on the choice of the parameters, but is indeterminate otherwise. In principle, determining the influence matrix requires exhaustive testing of the system steady-state behaviour in the widest range of parameter values. Here we show that, in a broad class of biological networks, the influence matrix can be evaluated with an algorithm that tests the system steady-state behaviour only at a finite number of points. This algorithm also allows us to assess the structural effect of any perturbation, such as variations of relevant parameters. Our method is applied to nontrivial models of biochemical reaction networks and population dynamics drawn from the literature, providing a parameter-free insight into the system dynamics.

Calibrating a population-based job-exposure matrix using inspection measurements to estimate historical occupational exposure to lead for a population-based cohort in Shanghai, China

PubMed Central

Koh, Dong-Hee; Bhatti, Parveen; Coble, Joseph B.; Stewart, Patricia A; Lu, Wei; Shu, Xiao-Ou; Ji, Bu-Tian; Xue, Shouzheng; Locke, Sarah J.; Portengen, Lutzen; Yang, Gong; Chow, Wong-Ho; Gao, Yu-Tang; Rothman, Nathaniel; Vermeulen, Roel; Friesen, Melissa C.

2012-01-01

The epidemiologic evidence for the carcinogenicity of lead is inconsistent and requires improved exposure assessment to estimate risk. We evaluated historical occupational lead exposure for a population-based cohort of women (n=74,942) by calibrating a job-exposure matrix (JEM) with lead fume (n=20,084) and lead dust (n=5,383) measurements collected over four decades in Shanghai, China. Using mixed-effect models, we calibrated intensity JEM ratings to the measurements using fixed-effects terms for year and JEM rating. We developed job/industry-specific estimates from the random-effects terms for job and industry. The model estimates were applied to subjects’ jobs when the JEM probability rating was high for either job or industry; remaining jobs were considered unexposed. The models predicted that exposure increased monotonically with JEM intensity rating and decreased 20–50-fold over time. The cumulative calibrated JEM estimates and job/industry-specific estimates were highly correlated (Pearson correlation=0.79–0.84). Overall, 5% of the person-years and 8% of the women were exposed to lead fume; 2% of the person-years and 4% of the women were exposed to lead dust. The most common lead-exposed jobs were manufacturing electronic equipment. These historical lead estimates should enhance our ability to detect associations between lead exposure and cancer risk in future epidemiologic analyses. PMID:22910004

How electronic dynamics with Pauli exclusion produces Fermi-Dirac statistics.

PubMed

Nguyen, Triet S; Nanguneri, Ravindra; Parkhill, John

2015-04-07

It is important that any dynamics method approaches the correct population distribution at long times. In this paper, we derive a one-body reduced density matrix dynamics for electrons in energetic contact with a bath. We obtain a remarkable equation of motion which shows that in order to reach equilibrium properly, rates of electron transitions depend on the density matrix. Even though the bath drives the electrons towards a Boltzmann distribution, hole blocking factors in our equation of motion cause the electronic populations to relax to a Fermi-Dirac distribution. These factors are an old concept, but we show how they can be derived with a combination of time-dependent perturbation theory and the extended normal ordering of Mukherjee and Kutzelnigg for a general electronic state. The resulting non-equilibrium kinetic equations generalize the usual Redfield theory to many-electron systems, while ensuring that the orbital occupations remain between zero and one. In numerical applications of our equations, we show that relaxation rates of molecules are not constant because of the blocking effect. Other applications to model atomic chains are also presented which highlight the importance of treating both dephasing and relaxation. Finally, we show how the bath localizes the electron density matrix.

How Feeling Betrayed Affects Cooperation

PubMed Central

Ramazi, Pouria; Hessel, Jop; Cao, Ming

2015-01-01

For a population of interacting self-interested agents, we study how the average cooperation level is affected by some individuals' feelings of being betrayed and guilt. We quantify these feelings as adjusted payoffs in asymmetric games, where for different emotions, the payoff matrix takes the structure of that of either a prisoner's dilemma or a snowdrift game. Then we analyze the evolution of cooperation in a well-mixed population of agents, each of whom is associated with such a payoff matrix. At each time-step, an agent is randomly chosen from the population to update her strategy based on the myopic best-response update rule. According to the simulations, decreasing the feeling of being betrayed in a portion of agents does not necessarily increase the level of cooperation in the population. However, this resistance of the population against low-betrayal-level agents is effective only up to some extend that is explicitly determined by the payoff matrices and the number of agents associated with these matrices. Two other models are also considered where the betrayal factor of an agent fluctuates as a function of the number of cooperators and defectors that she encounters. Unstable behaviors are observed for the level of cooperation in these cases; however, we show that one can tune the parameters in the function to make the whole population become cooperative or defective. PMID:25922933

The planar cell polarity protein VANGL2 coordinates remodeling of the extracellular matrix.

PubMed

Williams, B Blairanne; Mundell, Nathan; Dunlap, Julie; Jessen, Jason

2012-07-01

Understanding how planar cell polarity (PCP) is established, maintained, and coordinated in migrating cell populations is an important area of research with implications for both embryonic morphogenesis and tumor cell invasion. We recently reported that the PCP protein Vang-like 2 (VANGL2) regulates the endocytosis and cell surface level of membrane type-1 matrix metalloproteinase (MMP14 or MT1-MMP). Here, we further discuss these findings in terms of extracellular matrix (ECM) remodeling, cell migration, and zebrafish gastrulation. We also demonstrate that VANGL2 function impacts the focal degradation of ECM by human cancer cells including the formation or stability of invadopodia. Together, our findings implicate MMP14 as a downstream effector of VANGL2 signaling and suggest a model whereby the regulation of pericellular proteolysis is a fundamental aspect of PCP in migrating cells.

Modeling tradeoffs in avian life history traits and consequences for population growth

USGS Publications Warehouse

Clark, M.E.; Martin, T.E.

2007-01-01

Variation in population dynamics is inherently related to life history characteristics of species, which vary markedly even within phylogenetic groups such as passerine birds. We computed the finite rate of population change (??) from a matrix projection model and from mark-recapture observations for 23 bird species breeding in northern Arizona. We used sensitivity analyses and a simulation model to separate contributions of different life history traits to population growth rate. In particular we focused on contrasting effects of components of reproduction (nest success, clutch size, number of clutches, and juvenile survival) versus adult survival on ??. We explored how changes in nest success or adult survival coupled to costs in other life history parameters affected ?? over a life history gradient provided by our 23 Arizona species, as well as a broader sample of 121 North American passerine species. We further examined these effects for more than 200 passeriform and piciform populations breeding across North America. Model simulations indicate nest success and juvenile survival exert the largest effects on population growth in species with moderate to high reproductive output, whereas adult survival contributed more to population growth in long-lived species. Our simulations suggest that monitoring breeding success in populations across a broad geographic area provides an important index for identifying neotropical migratory populations at risk of serious population declines and a potential method for identifying large-scale mechanisms regulating population dynamics. ?? 2007 Elsevier B.V. All rights reserved.

Linear dimension reduction and Bayes classification

NASA Technical Reports Server (NTRS)

Decell, H. P., Jr.; Odell, P. L.; Coberly, W. A.

1978-01-01

An explicit expression for a compression matrix T of smallest possible left dimension K consistent with preserving the n variate normal Bayes assignment of X to a given one of a finite number of populations and the K variate Bayes assignment of TX to that population was developed. The Bayes population assignment of X and TX were shown to be equivalent for a compression matrix T explicitly calculated as a function of the means and covariances of the given populations.

Modeling the population dynamics of Culex quinquefasciatus (Diptera: Culcidae), along an elevational gradient in Hawaii

USGS Publications Warehouse

Ahumada, Jorge A.; LaPointe, Dennis; Samuel, Michael D.

2004-01-01

We present a population model to understand the effects of temperature and rainfall on the population dynamics of the southern house mosquito, Culex quinquefasciatus Say, along an elevational gradient in Hawaii. We use a novel approach to model the effects of temperature on population growth by dynamically incorporating developmental rate into the transition matrix, by using physiological ages of immatures instead of chronological age or stages. We also model the effects of rainfall on survival of immatures as the cumulative number of days below a certain rain threshold. Finally, we incorporate density dependence into the model as competition between immatures within breeding sites. Our model predicts the upper altitudinal distributions of Cx. quinquefasciatus on the Big Island of Hawaii for self-sustaining mosquito and migrating summer sink populations at 1,475 and 1,715 m above sea level, respectively. Our model predicts that mosquitoes at lower elevations can grow under a broader range of rainfall parameters than middle and high elevation populations. Density dependence in conjunction with the seasonal forcing imposed by temperature and rain creates cycles in the dynamics of the population that peak in the summer and early fall. The model provides a reasonable fit to the available data on mosquito abundance for the east side of Mauna Loa, Hawaii. The predictions of our model indicate the importance of abiotic conditions on mosquito dynamics and have important implications for the management of diseases transmitted by Cx. quinquefasciatus in Hawaii and elsewhere.

The environmental zero-point problem in evolutionary reaction norm modeling.

PubMed

Ergon, Rolf

2018-04-01

There is a potential problem in present quantitative genetics evolutionary modeling based on reaction norms. Such models are state-space models, where the multivariate breeder's equation in some form is used as the state equation that propagates the population state forward in time. These models use the implicit assumption of a constant reference environment, in many cases set to zero. This zero-point is often the environment a population is adapted to, that is, where the expected geometric mean fitness is maximized. Such environmental reference values follow from the state of the population system, and they are thus population properties. The environment the population is adapted to, is, in other words, an internal population property, independent of the external environment. It is only when the external environment coincides with the internal reference environment, or vice versa, that the population is adapted to the current environment. This is formally a result of state-space modeling theory, which is an important theoretical basis for evolutionary modeling. The potential zero-point problem is present in all types of reaction norm models, parametrized as well as function-valued, and the problem does not disappear when the reference environment is set to zero. As the environmental reference values are population characteristics, they ought to be modeled as such. Whether such characteristics are evolvable is an open question, but considering the complexity of evolutionary processes, such evolvability cannot be excluded without good arguments. As a straightforward solution, I propose to model the reference values as evolvable mean traits in their own right, in addition to other reaction norm traits. However, solutions based on an evolvable G matrix are also possible.

Combining dispersal, landscape connectivity and habitat suitability to assess climate-induced changes in the distribution of Cunningham's skink, Egernia cunninghami.

PubMed

Ofori, Benjamin Y; Stow, Adam J; Baumgartner, John B; Beaumont, Linda J

2017-01-01

The ability of species to track their climate niche is dependent on their dispersal potential and the connectivity of the landscape matrix linking current and future suitable habitat. However, studies modeling climate-driven range shifts rarely address the movement of species across landscapes realistically, often assuming "unlimited" or "no" dispersal. Here, we incorporate dispersal rate and landscape connectivity with a species distribution model (Maxent) to assess the extent to which the Cunningham's skink (Egernia cunninghami) may be capable of tracking spatial shifts in suitable habitat as climate changes. Our model was projected onto four contrasting, but equally plausible, scenarios describing futures that are (relative to now) hot/wet, warm/dry, hot/with similar precipitation and warm/wet, at six time horizons with decadal intervals (2020-2070) and at two spatial resolutions: 1 km and 250 m. The size of suitable habitat was projected to decline 23-63% at 1 km and 26-64% at 250 m, by 2070. Combining Maxent output with the dispersal rate of the species and connectivity of the intervening landscape matrix showed that most current populations in regions projected to become unsuitable in the medium to long term, will be unable to shift the distance necessary to reach suitable habitat. In particular, numerous populations currently inhabiting the trailing edge of the species' range are highly unlikely to be able to disperse fast enough to track climate change. Unless these populations are capable of adaptation they are likely to be extirpated. We note, however, that the core of the species distribution remains suitable across the broad spectrum of climate scenarios considered. Our findings highlight challenges faced by philopatric species and the importance of adaptation for the persistence of peripheral populations under climate change.

Interaction times change evolutionary outcomes: Two-player matrix games.

PubMed

Křivan, Vlastimil; Cressman, Ross

2017-03-07

Two most influential models of evolutionary game theory are the Hawk-Dove and Prisoner's dilemma models. The Hawk-Dove model explains evolution of aggressiveness, predicting individuals should be aggressive when the cost of fighting is lower than its benefit. As the cost of aggressiveness increases and outweighs benefits, aggressiveness in the population should decrease. Similarly, the Prisoner's dilemma models evolution of cooperation. It predicts that individuals should never cooperate despite cooperation leading to a higher collective fitness than defection. The question is then what are the conditions under which cooperation evolves? These classic matrix games, which are based on pair-wise interactions between two opponents with player payoffs given in matrix form, do not consider the effect that conflict duration has on payoffs. However, interactions between different strategies often take different amounts of time. In this article, we develop a new approach to an old idea that opportunity costs lost while engaged in an interaction affect individual fitness. When applied to the Hawk-Dove and Prisoner's dilemma, our theory that incorporates general interaction times leads to qualitatively different predictions. In particular, not all individuals will behave as Hawks when fighting cost is lower than benefit, and cooperation will evolve in the Prisoner's dilemma. Copyright © 2017 Elsevier Ltd. All rights reserved.

Free energies from dynamic weighted histogram analysis using unbiased Markov state model.

PubMed

Rosta, Edina; Hummer, Gerhard

2015-01-13

The weighted histogram analysis method (WHAM) is widely used to obtain accurate free energies from biased molecular simulations. However, WHAM free energies can exhibit significant errors if some of the biasing windows are not fully equilibrated. To account for the lack of full equilibration, we develop the dynamic histogram analysis method (DHAM). DHAM uses a global Markov state model to obtain the free energy along the reaction coordinate. A maximum likelihood estimate of the Markov transition matrix is constructed by joint unbiasing of the transition counts from multiple umbrella-sampling simulations along discretized reaction coordinates. The free energy profile is the stationary distribution of the resulting Markov matrix. For this matrix, we derive an explicit approximation that does not require the usual iterative solution of WHAM. We apply DHAM to model systems, a chemical reaction in water treated using quantum-mechanics/molecular-mechanics (QM/MM) simulations, and the Na(+) ion passage through the membrane-embedded ion channel GLIC. We find that DHAM gives accurate free energies even in cases where WHAM fails. In addition, DHAM provides kinetic information, which we here use to assess the extent of convergence in each of the simulation windows. DHAM may also prove useful in the construction of Markov state models from biased simulations in phase-space regions with otherwise low population.

An in vitro assessment of bioaccessibility of arsenicals in rice and the use of this estimate within a probabilistic exposure model.

PubMed

Trenary, Heather R; Creed, Patricia A; Young, Andrea R; Mantha, Madhavi; Schwegel, Carol A; Xue, Jianping; Kohan, Michael J; Herbin-Davis, Karen; Thomas, David J; Caruso, Joseph A; Creed, John T

2012-07-01

In this study, an in vitro synthetic gastrointestinal extraction protocol was used to estimate bioaccessibility of different arsenicals present in 17 rice samples of various grain types that were collected across the United States. The across matrix average for total arsenic was 209 ng/g±153 (\\[xmacr]±2σ). The bioaccessibility estimate produced an across matrix average of 61%±19 (\\[xmacr]±2σ). The across matrix average concentrations of inorganic arsenic (iAs) and dimethylarsinic acid (DMA) were 81 ng/g±67.7 and 41 ng/g±58.1 (\\[xmacr]±2σ), respectively. This distribution of iAs concentrations in rice was combined with the distribution of consumption patterns (from WWEIA) in a Stochastic Human Exposure and Dose Simulator model to estimate population-based exposures. The mean consumption rate for the population as a whole was 15.7 g per day resulting in a 0.98 μg iAs per day exposure. The mean consumption rate for children 1-2 years old was 7 g per day resulting in a 0.48 μg iAs per day exposure. Presystemic biotransformation of DMA in rice was examined using an in vitro assay containing the anaerobic microbiota of mouse cecum. This assay indicated that DMA extracted from the rice was converted to dimethylthioarsinic acid, although a second oxygen-sulfur exchange to produce DMDTA was not observed.

Six-color intravital two-photon imaging of brain tumors and their dynamic microenvironment.

PubMed

Ricard, Clément; Debarbieux, Franck Christian

2014-01-01

The majority of intravital studies on brain tumor in living animal so far rely on dual color imaging. We describe here a multiphoton imaging protocol to dynamically characterize the interactions between six cellular components in a living mouse. We applied this methodology to a clinically relevant glioblastoma multiforme (GBM) model designed in reporter mice with targeted cell populations labeled by fluorescent proteins of different colors. This model permitted us to make non-invasive longitudinal and multi-scale observations of cell-to-cell interactions. We provide examples of such 5D (x,y,z,t,color) images acquired on a daily basis from volumes of interest, covering most of the mouse parietal cortex at subcellular resolution. Spectral deconvolution allowed us to accurately separate each cell population as well as some components of the extracellular matrix. The technique represents a powerful tool for investigating how tumor progression is influenced by the interactions of tumor cells with host cells and the extracellular matrix micro-environment. It will be especially valuable for evaluating neuro-oncological drug efficacy and target specificity. The imaging protocol provided here can be easily translated to other mouse models of neuropathologies, and should also be of fundamental interest for investigations in other areas of systems biology.

Conservation biology for suites of species: Demographic modeling for Pacific island kingfishers

USGS Publications Warehouse

Kesler, D.C.; Haig, S.M.

2007-01-01

Conservation practitioners frequently extrapolate data from single-species investigations when managing critically endangered populations. However, few researchers initiate work with the intent of making findings useful to conservation efforts for other species. We presented and explored the concept of conducting conservation-oriented research for suites of geographically separated populations with similar natural histories, resource needs, and extinction threats. An example was provided in the form of an investigation into the population demography of endangered Micronesian kingfishers (Todiramphus cinnamominus). We provided the first demographic parameter estimates for any of the 12 endangered Pacific Todiramphus species, and used results to develop a population projection matrix model for management throughout the insular Pacific. Further, we used the model for elasticity and simulation analyses with demographic values that randomly varied across ranges that might characterize congener populations. Results from elasticity and simulation analyses indicated that changes in breeding adult survival exerted the greatest magnitude of influence on population dynamics. However, changes in nestling survival were more consistently correlated with population dynamics as demographic rates were randomly altered. We concluded that conservation practitioners working with endangered Pacific kingfishers should primarily focus efforts on factors affecting nestling and breeder survival, and secondarily address fledgling juveniles and helpers. Further, we described how the generalized base model might be changed to focus on individual populations and discussed the potential application of multi-species models to other conservation situations. ?? 2007 Elsevier Ltd. All rights reserved.

Hierarchical spatiotemporal matrix models for characterizing invasions

USGS Publications Warehouse

Hooten, M.B.; Wikle, C.K.; Dorazio, R.M.; Royle, J. Andrew

2007-01-01

The growth and dispersal of biotic organisms is an important subject in ecology. Ecologists are able to accurately describe survival and fecundity in plant and animal populations and have developed quantitative approaches to study the dynamics of dispersal and population size. Of particular interest are the dynamics of invasive species. Such nonindigenous animals and plants can levy significant impacts on native biotic communities. Effective models for relative abundance have been developed; however, a better understanding of the dynamics of actual population size (as opposed to relative abundance) in an invasion would be beneficial to all branches of ecology. In this article, we adopt a hierarchical Bayesian framework for modeling the invasion of such species while addressing the discrete nature of the data and uncertainty associated with the probability of detection. The nonlinear dynamics between discrete time points are intuitively modeled through an embedded deterministic population model with density-dependent growth and dispersal components. Additionally, we illustrate the importance of accommodating spatially varying dispersal rates. The method is applied to the specific case of the Eurasian Collared-Dove, an invasive species at mid-invasion in the United States at the time of this writing.

Hierarchical spatiotemporal matrix models for characterizing invasions

USGS Publications Warehouse

Hooten, M.B.; Wikle, C.K.; Dorazio, R.M.; Royle, J. Andrew

2007-01-01

The growth and dispersal of biotic organisms is an important subject in ecology. Ecologists are able to accurately describe survival and fecundity in plant and animal populations and have developed quantitative approaches to study the dynamics of dispersal and population size. Of particular interest are the dynamics of invasive species. Such nonindigenous animals and plants can levy significant impacts on native biotic communities. Effective models for relative abundance have been developed; however, a better understanding of the dynamics of actual population size (as opposed to relative abundance) in an invasion would be beneficial to all branches of ecology. In this article, we adopt a hierarchical Bayesian framework for modeling the invasion of such species while addressing the discrete nature of the data and uncertainty associated with the probability of detection. The nonlinear dynamics between discrete time points are intuitively modeled through an embedded deterministic population model with density-dependent growth and dispersal components. Additionally, we illustrate the importance of accommodating spatially varying dispersal rates. The method is applied to the specific case of the Eurasian Collared-Dove, an invasive species at mid-invasion in the United States at the time of this writing. ?? 2006, The International Biometric Society.

Sex in an uncertain world: environmental stochasticity helps restore competitive balance between sexually and asexually reproducing populations.

PubMed

Park, A W; Vandekerkhove, J; Michalakis, Y

2014-08-01

Like many organisms, individuals of the freshwater ostracod species Eucypris virens exhibit either obligate sexual or asexual reproductive modes. Both types of individual routinely co-occur, including in the same temporary freshwater pond (their natural habitat in which they undergo seasonal diapause). Given the well-known two-fold cost of sex, this begs the question of how sexually reproducing individuals are able to coexist with their asexual counterparts in spite of such overwhelming costs. Environmental stochasticity in the form of 'false dawn' inundations (where the first hydration is ephemeral and causes loss of early hatching individuals) may provide an advantage to the sexual subpopulation, which shows greater variation in hatching times following inundation. We explore the potential role of environmental stochasticity in this system using life-history data analysis, climate data, and matrix projection models. In the absence of environmental stochasticity, the population growth rate is significantly lower in sexual subpopulations. Climate data reveal that 'false dawn' inundations are common. Using matrix projection modelling with and without environmental stochasticity, we demonstrate that this phenomenon can restore appreciable balance to the system, in terms of population growth rates. This provides support for the role of environmental stochasticity in helping to explain the maintenance of sex and the occurrence of geographical parthenogenesis. © 2014 The Authors. Journal of Evolutionary Biology © 2014 European Society For Evolutionary Biology.

Modelling the effect of urbanization on the transmission of an infectious disease.

PubMed

Zhang, Ping; Atkinson, Peter M

2008-01-01

This paper models the impact of urbanization on infectious disease transmission by integrating a CA land use development model, population projection matrix model and CA epidemic model in S-Plus. The innovative feature of this model lies in both its explicit treatment of spatial land use development, demographic changes, infectious disease transmission and their combination in a dynamic, stochastic model. Heuristically-defined transition rules in cellular automata (CA) were used to capture the processes of both land use development with urban sprawl and infectious disease transmission. A population surface model and dwelling distribution surface were used to bridge the gap between urbanization and infectious disease transmission. A case study is presented involving modelling influenza transmission in Southampton, a dynamically evolving city in the UK. The simulation results for Southampton over a 30-year period show that the pattern of the average number of infection cases per day can depend on land use and demographic changes. The modelling framework presents a useful tool that may be of use in planning applications.

A novel physical eco-hydrological model concept for preferential flow based on experimental applications.

NASA Astrophysics Data System (ADS)

Jackisch, Conrad; van Schaik, Loes; Graeff, Thomas; Zehe, Erwin

2014-05-01

Preferential flow through macropores often determines hydrological characteristics - especially regarding runoff generation and fast transport of solutes. Macropore settings may yet be very different in nature and dynamics, depending on their origin. While biogenic structures follow activity cycles (e.g. earth worms) and population conditions (e.g. roots), pedogenic and geogenic structures may depend on water stress (e.g. cracks) or large events (e.g. flushed voids between skeleton and soil pipes) or simply persist (e.g. bedrock interface). On the one hand, such dynamic site characteristics can be observed in seasonal changes in its reaction to precipitation. On the other hand, sprinkling experiments accompanied by tracers or time-lapse 3D Ground-Penetrating-Radar are suitable tools to determine infiltration patterns and macropore configuration. However, model representation of the macropore-matrix system is still problematic, because models either rely on effective parameters (assuming well-mixed state) or on explicit advection strongly simplifying or neglecting interaction with the diffusive flow domain. Motivated by the dynamic nature of macropores, we present a novel model approach for interacting diffusive and advective water, solutes and energy transport in structured soils. It solely relies on scale- and process-aware observables. A representative set of macropores (data from sprinkling experiments) determines the process model scale through 1D advective domains. These are connected to a 2D matrix domain which is defined by pedo-physical retention properties. Water is represented as particles. Diffusive flow is governed by a 2D random walk of these particles while advection may take place in the macropore domain. Macropore-matrix interaction is computed as dissipation of the advective momentum of a particle by its experienced drag from the matrix domain. Through a representation of matrix and macropores as connected diffusive and advective domains for water transport we open up double domain concepts linking porescale physics to preferential macroscale fingerprints without effective parameterisation or mixing assumptions. Moreover, solute transport, energy balance aspects and lateral heterogeneity in soil moisture distribution are intrinsically captured. In addition, macropore and matrix domain settings may change over time based on physical and stochastic observations. The representativity concept allows scaleability from plotscale to the lower mesoscale.

Developing population models with data from marked individuals

USGS Publications Warehouse

Hae Yeong Ryu,; Kevin T. Shoemaker,; Eva Kneip,; Anna Pidgeon,; Patricia Heglund,; Brooke Bateman,; Thogmartin, Wayne E.; Reşit Akçakaya,

2016-01-01

Population viability analysis (PVA) is a powerful tool for biodiversity assessments, but its use has been limited because of the requirements for fully specified population models such as demographic structure, density-dependence, environmental stochasticity, and specification of uncertainties. Developing a fully specified population model from commonly available data sources – notably, mark–recapture studies – remains complicated due to lack of practical methods for estimating fecundity, true survival (as opposed to apparent survival), natural temporal variability in both survival and fecundity, density-dependence in the demographic parameters, and uncertainty in model parameters. We present a general method that estimates all the key parameters required to specify a stochastic, matrix-based population model, constructed using a long-term mark–recapture dataset. Unlike standard mark–recapture analyses, our approach provides estimates of true survival rates and fecundities, their respective natural temporal variabilities, and density-dependence functions, making it possible to construct a population model for long-term projection of population dynamics. Furthermore, our method includes a formal quantification of parameter uncertainty for global (multivariate) sensitivity analysis. We apply this approach to 9 bird species and demonstrate the feasibility of using data from the Monitoring Avian Productivity and Survivorship (MAPS) program. Bias-correction factors for raw estimates of survival and fecundity derived from mark–recapture data (apparent survival and juvenile:adult ratio, respectively) were non-negligible, and corrected parameters were generally more biologically reasonable than their uncorrected counterparts. Our method allows the development of fully specified stochastic population models using a single, widely available data source, substantially reducing the barriers that have until now limited the widespread application of PVA. This method is expected to greatly enhance our understanding of the processes underlying population dynamics and our ability to analyze viability and project trends for species of conservation concern.

Forecasting the mortality rates of Malaysian population using Heligman-Pollard model

NASA Astrophysics Data System (ADS)

Ibrahim, Rose Irnawaty; Mohd, Razak; Ngataman, Nuraini; Abrisam, Wan Nur Azifah Wan Mohd

2017-08-01

Actuaries, demographers and other professionals have always been aware of the critical importance of mortality forecasting due to declining trend of mortality and continuous increases in life expectancy. Heligman-Pollard model was introduced in 1980 and has been widely used by researchers in modelling and forecasting future mortality. This paper aims to estimate an eight-parameter model based on Heligman and Pollard's law of mortality. Since the model involves nonlinear equations that are explicitly difficult to solve, the Matrix Laboratory Version 7.0 (MATLAB 7.0) software will be used in order to estimate the parameters. Statistical Package for the Social Sciences (SPSS) will be applied to forecast all the parameters according to Autoregressive Integrated Moving Average (ARIMA). The empirical data sets of Malaysian population for period of 1981 to 2015 for both genders will be considered, which the period of 1981 to 2010 will be used as "training set" and the period of 2011 to 2015 as "testing set". In order to investigate the accuracy of the estimation, the forecast results will be compared against actual data of mortality rates. The result shows that Heligman-Pollard model fit well for male population at all ages while the model seems to underestimate the mortality rates for female population at the older ages.

Modeling approaches in avian conservation and the role of field biologists

USGS Publications Warehouse

Beissinger, Steven R.; Walters, J.R.; Catanzaro, D.G.; Smith, Kimberly G.; Dunning, J.B.; Haig, Susan M.; Noon, Barry; Stith, Bradley M.

2006-01-01

This review grew out of our realization that models play an increasingly important role in conservation but are rarely used in the research of most avian biologists. Modelers are creating models that are more complex and mechanistic and that can incorporate more of the knowledge acquired by field biologists. Such models require field biologists to provide more specific information, larger sample sizes, and sometimes new kinds of data, such as habitat-specific demography and dispersal information. Field biologists need to support model development by testing key model assumptions and validating models. The best conservation decisions will occur where cooperative interaction enables field biologists, modelers, statisticians, and managers to contribute effectively. We begin by discussing the general form of ecological models—heuristic or mechanistic, "scientific" or statistical—and then highlight the structure, strengths, weaknesses, and applications of six types of models commonly used in avian conservation: (1) deterministic single-population matrix models, (2) stochastic population viability analysis (PVA) models for single populations, (3) metapopulation models, (4) spatially explicit models, (5) genetic models, and (6) species distribution models. We end by considering their unique attributes, determining whether the assumptions that underlie the structure are valid, and testing the ability of the model to predict the future correctly.

Continuous and Discrete Structured Population Models with Applications to Epidemiology and Marine Mammals

NASA Astrophysics Data System (ADS)

Tang, Tingting

In this dissertation, we develop structured population models to examine how changes in the environmental affect population processes. In Chapter 2, we develop a general continuous time size structured model describing a susceptible-infected (SI) population coupled with the environment. This model applies to problems arising in ecology, epidemiology, and cell biology. The model consists of a system of quasilinear hyperbolic partial differential equations coupled with a system of nonlinear ordinary differential equations that represent the environment. We develop a second-order high resolution finite difference scheme to numerically solve the model. Convergence of this scheme to a weak solution with bounded total variation is proved. We numerically compare the second order high resolution scheme with a first order finite difference scheme. Higher order of convergence and high resolution property are observed in the second order finite difference scheme. In addition, we apply our model to a multi-host wildlife disease problem, questions regarding the impact of the initial population structure and transition rate within each host are numerically explored. In Chapter 3, we use a stage structured matrix model for wildlife population to study the recovery process of the population given an environmental disturbance. We focus on the time it takes for the population to recover to its pre-event level and develop general formulas to calculate the sensitivity or elasticity of the recovery time to changes in the initial population distribution, vital rates and event severity. Our results suggest that the recovery time is independent of the initial population size, but is sensitive to the initial population structure. Moreover, it is more sensitive to the reduction proportion to the vital rates of the population caused by the catastrophe event relative to the duration of impact of the event. We present the potential application of our model to the amphibian population dynamic and the recovery of a certain plant population. In addition, we explore, in details, the application of the model to the sperm whale population in Gulf of Mexico after the Deepwater Horizon oil spill. In Chapter 4, we summarize the results from Chapter 2 and Chapter 3 and explore some further avenues of our research.

Annulus fibrosus functional extrafibrillar and fibrous mechanical behaviour: experimental and computational characterisation.

PubMed

Mengoni, Marlène; Kayode, Oluwasegun; Sikora, Sebastien N F; Zapata-Cornelio, Fernando Y; Gregory, Diane E; Wilcox, Ruth K

2017-08-01

The development of current surgical treatments for intervertebral disc damage could benefit from virtual environment accounting for population variations. For such models to be reliable, a relevant description of the mechanical properties of the different tissues and their role in the functional mechanics of the disc is of major importance. The aims of this work were first to assess the physiological hoop strain in the annulus fibrosus in fresh conditions ( n  = 5) in order to extract a functional behaviour of the extrafibrillar matrix; then to reverse-engineer the annulus fibrosus fibrillar behaviour ( n  = 6). This was achieved by performing both direct and global controlled calibration of material parameters, accounting for the whole process of experimental design and in silico model methodology. Direct-controlled models are specimen-specific models representing controlled experimental conditions that can be replicated and directly comparing measurements. Validation was performed on another six specimens and a sensitivity study was performed. Hoop strains were measured as 17 ± 3% after 10 min relaxation and 21 ± 4% after 20-25 min relaxation, with no significant difference between the two measurements. The extrafibrillar matrix functional moduli were measured as 1.5 ± 0.7 MPa. Fibre-related material parameters showed large variability, with a variance above 0.28. Direct-controlled calibration and validation provides confidence that the model development methodology can capture the measurable variation within the population of tested specimens.

Annulus fibrosus functional extrafibrillar and fibrous mechanical behaviour: experimental and computational characterisation

PubMed Central

Kayode, Oluwasegun; Sikora, Sebastien N. F.; Zapata-Cornelio, Fernando Y.; Gregory, Diane E.; Wilcox, Ruth K.

2017-01-01

The development of current surgical treatments for intervertebral disc damage could benefit from virtual environment accounting for population variations. For such models to be reliable, a relevant description of the mechanical properties of the different tissues and their role in the functional mechanics of the disc is of major importance. The aims of this work were first to assess the physiological hoop strain in the annulus fibrosus in fresh conditions (n = 5) in order to extract a functional behaviour of the extrafibrillar matrix; then to reverse-engineer the annulus fibrosus fibrillar behaviour (n = 6). This was achieved by performing both direct and global controlled calibration of material parameters, accounting for the whole process of experimental design and in silico model methodology. Direct-controlled models are specimen-specific models representing controlled experimental conditions that can be replicated and directly comparing measurements. Validation was performed on another six specimens and a sensitivity study was performed. Hoop strains were measured as 17 ± 3% after 10 min relaxation and 21 ± 4% after 20–25 min relaxation, with no significant difference between the two measurements. The extrafibrillar matrix functional moduli were measured as 1.5 ± 0.7 MPa. Fibre-related material parameters showed large variability, with a variance above 0.28. Direct-controlled calibration and validation provides confidence that the model development methodology can capture the measurable variation within the population of tested specimens. PMID:28879014

A Two-Stage Approach to Missing Data: Theory and Application to Auxiliary Variables

ERIC Educational Resources Information Center

Savalei, Victoria; Bentler, Peter M.

2009-01-01

A well-known ad-hoc approach to conducting structural equation modeling with missing data is to obtain a saturated maximum likelihood (ML) estimate of the population covariance matrix and then to use this estimate in the complete data ML fitting function to obtain parameter estimates. This 2-stage (TS) approach is appealing because it minimizes a…

Modeling the Complex Impacts of Timber Harvests to Find Optimal Management Regimes for Amazon Tidal Floodplain Forests

PubMed Central

Fortini, Lucas B.; Cropper, Wendell P.; Zarin, Daniel J.

2015-01-01

At the Amazon estuary, the oldest logging frontier in the Amazon, no studies have comprehensively explored the potential long-term population and yield consequences of multiple timber harvests over time. Matrix population modeling is one way to simulate long-term impacts of tree harvests, but this approach has often ignored common impacts of tree harvests including incidental damage, changes in post-harvest demography, shifts in the distribution of merchantable trees, and shifts in stand composition. We designed a matrix-based forest management model that incorporates these harvest-related impacts so resulting simulations reflect forest stand dynamics under repeated timber harvests as well as the realities of local smallholder timber management systems. Using a wide range of values for management criteria (e.g., length of cutting cycle, minimum cut diameter), we projected the long-term population dynamics and yields of hundreds of timber management regimes in the Amazon estuary, where small-scale, unmechanized logging is an important economic activity. These results were then compared to find optimal stand-level and species-specific sustainable timber management (STM) regimes using a set of timber yield and population growth indicators. Prospects for STM in Amazonian tidal floodplain forests are better than for many other tropical forests. However, generally high stock recovery rates between harvests are due to the comparatively high projected mean annualized yields from fast-growing species that effectively counterbalance the projected yield declines from other species. For Amazonian tidal floodplain forests, national management guidelines provide neither the highest yields nor the highest sustained population growth for species under management. Our research shows that management guidelines specific to a region’s ecological settings can be further refined to consider differences in species demographic responses to repeated harvests. In principle, such fine-tuned management guidelines could make management more attractive, thus bridging the currently prevalent gap between tropical timber management practice and regulation. PMID:26322896

Modeling the complex impacts of timber harvests to find optimal management regimes for Amazon tidal floodplain forests

USGS Publications Warehouse

Fortini, Lucas B.; Cropper, Wendell P.; Zarin, Daniel J.

2015-01-01

At the Amazon estuary, the oldest logging frontier in the Amazon, no studies have comprehensively explored the potential long-term population and yield consequences of multiple timber harvests over time. Matrix population modeling is one way to simulate long-term impacts of tree harvests, but this approach has often ignored common impacts of tree harvests including incidental damage, changes in post-harvest demography, shifts in the distribution of merchantable trees, and shifts in stand composition. We designed a matrix-based forest management model that incorporates these harvest-related impacts so resulting simulations reflect forest stand dynamics under repeated timber harvests as well as the realities of local smallholder timber management systems. Using a wide range of values for management criteria (e.g., length of cutting cycle, minimum cut diameter), we projected the long-term population dynamics and yields of hundreds of timber management regimes in the Amazon estuary, where small-scale, unmechanized logging is an important economic activity. These results were then compared to find optimal stand-level and species-specific sustainable timber management (STM) regimes using a set of timber yield and population growth indicators. Prospects for STM in Amazonian tidal floodplain forests are better than for many other tropical forests. However, generally high stock recovery rates between harvests are due to the comparatively high projected mean annualized yields from fast-growing species that effectively counterbalance the projected yield declines from other species. For Amazonian tidal floodplain forests, national management guidelines provide neither the highest yields nor the highest sustained population growth for species under management. Our research shows that management guidelines specific to a region’s ecological settings can be further refined to consider differences in species demographic responses to repeated harvests. In principle, such fine-tuned management guidelines could make management more attractive, thus bridging the currently prevalent gap between tropical timber management practice and regulation.

Effects of landscape matrix on population connectivity of an arboreal mammal, Petaurus breviceps.

PubMed

Malekian, Mansoureh; Cooper, Steven J B; Saint, Kathleen M; Lancaster, Melanie L; Taylor, Andrea C; Carthew, Susan M

2015-09-01

Ongoing habitat loss and fragmentation is considered a threat to biodiversity as it can create small, isolated populations that are at increased risk of extinction. Tree-dependent species are predicted to be highly sensitive to forest and woodland loss and fragmentation, but few studies have tested the influence of different types of landscape matrix on gene flow and population structure of arboreal species. Here, we examine the effects of landscape matrix on population structure of the sugar glider (Petaurus breviceps) in a fragmented landscape in southeastern South Australia. We collected 250 individuals across 12 native Eucalyptus forest remnants surrounded by cleared agricultural land or exotic Pinus radiata plantations and a large continuous eucalypt forest. Fifteen microsatellite loci were genotyped and analyzed to infer levels of population differentiation and dispersal. Genetic differentiation among most forest patches was evident. We found evidence for female philopatry and restricted dispersal distances for females relative to males, suggesting there is male-biased dispersal. Among the environmental variables, spatial variables including geographic location, minimum distance to neighboring patch, and degree of isolation were the most important in explaining genetic variation. The permeability of a cleared agricultural matrix to dispersing gliders was significantly higher than that of a pine matrix, with the gliders dispersing shorter distances across the latter. Our results added to previous findings for other species of restricted dispersal and connectivity due to habitat fragmentation in the same region, providing valuable information for the development of strategies to improve the connectivity of populations in the future.

Multi-cut solutions in Chern-Simons matrix models

NASA Astrophysics Data System (ADS)

Morita, Takeshi; Sugiyama, Kento

2018-04-01

We elaborate the Chern-Simons (CS) matrix models at large N. The saddle point equations of these matrix models have a curious structure which cannot be seen in the ordinary one matrix models. Thanks to this structure, an infinite number of multi-cut solutions exist in the CS matrix models. Particularly we exactly derive the two-cut solutions at finite 't Hooft coupling in the pure CS matrix model. In the ABJM matrix model, we argue that some of multi-cut solutions might be interpreted as a condensation of the D2-brane instantons.

The planar cell polarity protein VANGL2 coordinates remodeling of the extracellular matrix

PubMed Central

Williams, B. Blairanne; Mundell, Nathan; Dunlap, Julie; Jessen, Jason

2012-01-01

Understanding how planar cell polarity (PCP) is established, maintained, and coordinated in migrating cell populations is an important area of research with implications for both embryonic morphogenesis and tumor cell invasion. We recently reported that the PCP protein Vang-like 2 (VANGL2) regulates the endocytosis and cell surface level of membrane type-1 matrix metalloproteinase (MMP14 or MT1-MMP). Here, we further discuss these findings in terms of extracellular matrix (ECM) remodeling, cell migration, and zebrafish gastrulation. We also demonstrate that VANGL2 function impacts the focal degradation of ECM by human cancer cells including the formation or stability of invadopodia. Together, our findings implicate MMP14 as a downstream effector of VANGL2 signaling and suggest a model whereby the regulation of pericellular proteolysis is a fundamental aspect of PCP in migrating cells. PMID:23060953

Genetic parameters for milk fatty acids, milk yield and quality traits of a Holstein cattle population reared under tropical conditions.

PubMed

Petrini, J; Iung, L H S; Rodriguez, M A P; Salvian, M; Pértille, F; Rovadoscki, G A; Cassoli, L D; Coutinho, L L; Machado, P F; Wiggans, G R; Mourão, G B

2016-10-01

Information about genetic parameters is essential for selection decisions and genetic evaluation. These estimates are population specific; however, there are few studies with dairy cattle populations reared under tropical and sub-tropical conditions. Thus, the aim was to obtain estimates of heritability and genetic correlations for milk yield and quality traits using pedigree and genomic information from a Holstein population maintained in a tropical environment. Phenotypic records (n = 36 457) of 4203 cows as well as the genotypes for 57 368 single nucleotide polymorphisms from 755 of these cows were used. Covariance components were estimated using the restricted maximum likelihood method under a mixed animal model, considering a pedigree-based relationship matrix or a combined pedigree-genomic matrix. High heritabilities (around 0.30) were estimated for lactose and protein content in milk whereas moderate values (between 0.19 and 0.26) were obtained for percentages of fat, saturated fatty acids and palmitic acid in milk. Genetic correlations ranging from -0.38 to -0.13 were determined between milk yield and composition traits. The smaller estimates compared to other similar studies can be due to poor environmental conditions, which may reduce genetic variability. These results highlight the importance in using genetic parameters estimated in the population under evaluation for selection decisions. © 2016 Blackwell Verlag GmbH.

The Replicator Equation on Graphs

PubMed Central

Ohtsuki, Hisashi; Nowak, Martin A.

2008-01-01

We study evolutionary games on graphs. Each player is represented by a vertex of the graph. The edges denote who meets whom. A player can use any one of n strategies. Players obtain a payoff from interaction with all their immediate neighbors. We consider three different update rules, called ‘birth-death’, ‘death-birth’ and ‘imitation’. A fourth update rule, ‘pairwise comparison’, is shown to be equivalent to birth-death updating in our model. We use pair-approximation to describe the evolutionary game dynamics on regular graphs of degree k. In the limit of weak selection, we can derive a differential equation which describes how the average frequency of each strategy on the graph changes over time. Remarkably, this equation is a replicator equation with a transformed payoff matrix. Therefore, moving a game from a well-mixed population (the complete graph) onto a regular graph simply results in a transformation of the payoff matrix. The new payoff matrix is the sum of the original payoff matrix plus another matrix, which describes the local competition of strategies. We discuss the application of our theory to four particular examples, the Prisoner’s Dilemma, the Snow-Drift game, a coordination game and the Rock-Scissors-Paper game. PMID:16860343

Effects of climate change on an emperor penguin population: analysis of coupled demographic and climate models.

PubMed

Jenouvrier, Stéphanie; Holland, Marika; Stroeve, Julienne; Barbraud, Christophe; Weimerskirch, Henri; Serreze, Mark; Caswell, Hal

2012-09-01

Sea ice conditions in the Antarctic affect the life cycle of the emperor penguin (Aptenodytes forsteri). We present a population projection for the emperor penguin population of Terre Adélie, Antarctica, by linking demographic models (stage-structured, seasonal, nonlinear, two-sex matrix population models) to sea ice forecasts from an ensemble of IPCC climate models. Based on maximum likelihood capture-mark-recapture analysis, we find that seasonal sea ice concentration anomalies (SICa ) affect adult survival and breeding success. Demographic models show that both deterministic and stochastic population growth rates are maximized at intermediate values of annual SICa , because neither the complete absence of sea ice, nor heavy and persistent sea ice, would provide satisfactory conditions for the emperor penguin. We show that under some conditions the stochastic growth rate is positively affected by the variance in SICa . We identify an ensemble of five general circulation climate models whose output closely matches the historical record of sea ice concentration in Terre Adélie. The output of this ensemble is used to produce stochastic forecasts of SICa , which in turn drive the population model. Uncertainty is included by incorporating multiple climate models and by a parametric bootstrap procedure that includes parameter uncertainty due to both model selection and estimation error. The median of these simulations predicts a decline of the Terre Adélie emperor penguin population of 81% by the year 2100. We find a 43% chance of an even greater decline, of 90% or more. The uncertainty in population projections reflects large differences among climate models in their forecasts of future sea ice conditions. One such model predicts population increases over much of the century, but overall, the ensemble of models predicts that population declines are far more likely than population increases. We conclude that climate change is a significant risk for the emperor penguin. Our analytical approach, in which demographic models are linked to IPCC climate models, is powerful and generally applicable to other species and systems. © 2012 Blackwell Publishing Ltd.

Impact of reduced marker set estimation of genomic relationship matrices on genomic selection for feed efficiency in Angus cattle.

PubMed

Rolf, Megan M; Taylor, Jeremy F; Schnabel, Robert D; McKay, Stephanie D; McClure, Matthew C; Northcutt, Sally L; Kerley, Monty S; Weaber, Robert L

2010-04-19

Molecular estimates of breeding value are expected to increase selection response due to improvements in the accuracy of selection and a reduction in generation interval, particularly for traits that are difficult or expensive to record or are measured late in life. Several statistical methods for incorporating molecular data into breeding value estimation have been proposed, however, most studies have utilized simulated data in which the generated linkage disequilibrium may not represent the targeted livestock population. A genomic relationship matrix was developed for 698 Angus steers and 1,707 Angus sires using 41,028 single nucleotide polymorphisms and breeding values were estimated using feed efficiency phenotypes (average daily feed intake, residual feed intake, and average daily gain) recorded on the steers. The number of SNPs needed to accurately estimate a genomic relationship matrix was evaluated in this population. Results were compared to estimates produced from pedigree-based mixed model analysis of 862 Angus steers with 34,864 identified paternal relatives but no female ancestors. Estimates of additive genetic variance and breeding value accuracies were similar for AFI and RFI using the numerator and genomic relationship matrices despite fewer animals in the genomic analysis. Bootstrap analyses indicated that 2,500-10,000 markers are required for robust estimation of genomic relationship matrices in cattle. This research shows that breeding values and their accuracies may be estimated for commercially important sires for traits recorded in experimental populations without the need for pedigree data to establish identity by descent between members of the commercial and experimental populations when at least 2,500 SNPs are available for the generation of a genomic relationship matrix.

On the additive and dominant variance and covariance of individuals within the genomic selection scope.

PubMed

Vitezica, Zulma G; Varona, Luis; Legarra, Andres

2013-12-01

Genomic evaluation models can fit additive and dominant SNP effects. Under quantitative genetics theory, additive or "breeding" values of individuals are generated by substitution effects, which involve both "biological" additive and dominant effects of the markers. Dominance deviations include only a portion of the biological dominant effects of the markers. Additive variance includes variation due to the additive and dominant effects of the markers. We describe a matrix of dominant genomic relationships across individuals, D, which is similar to the G matrix used in genomic best linear unbiased prediction. This matrix can be used in a mixed-model context for genomic evaluations or to estimate dominant and additive variances in the population. From the "genotypic" value of individuals, an alternative parameterization defines additive and dominance as the parts attributable to the additive and dominant effect of the markers. This approach underestimates the additive genetic variance and overestimates the dominance variance. Transforming the variances from one model into the other is trivial if the distribution of allelic frequencies is known. We illustrate these results with mouse data (four traits, 1884 mice, and 10,946 markers) and simulated data (2100 individuals and 10,000 markers). Variance components were estimated correctly in the model, considering breeding values and dominance deviations. For the model considering genotypic values, the inclusion of dominant effects biased the estimate of additive variance. Genomic models were more accurate for the estimation of variance components than their pedigree-based counterparts.

Extinction-effective population index: incorporating life-history variations in population viability analysis.

PubMed

Fujiwara, Masami

2007-09-01

Viability status of populations is a commonly used measure for decision-making in the management of populations. One of the challenges faced by managers is the need to consistently allocate management effort among populations. This allocation should in part be based on comparison of extinction risks among populations. Unfortunately, common criteria that use minimum viable population size or count-based population viability analysis (PVA) often do not provide results that are comparable among populations, primarily because they lack consistency in determining population size measures and threshold levels of population size (e.g., minimum viable population size and quasi-extinction threshold). Here I introduce a new index called the "extinction-effective population index," which accounts for differential effects of demographic stochasticity among organisms with different life-history strategies and among individuals in different life stages. This index is expected to become a new way of determining minimum viable population size criteria and also complement the count-based PVA. The index accounts for the difference in life-history strategies of organisms, which are modeled using matrix population models. The extinction-effective population index, sensitivity, and elasticity are demonstrated in three species of Pacific salmonids. The interpretation of the index is also provided by comparing them with existing demographic indices. Finally, a measure of life-history-specific effect of demographic stochasticity is derived.

A new fracture mechanics model for multiple matrix cracks of SiC fiber reinforced brittle-matrix composites

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

Okabe, T.; Takeda, N.; Komotori, J.

1999-11-26

A new model is proposed for multiple matrix cracking in order to take into account the role of matrix-rich regions in the cross section in initiating crack growth. The model is used to predict the matrix cracking stress and the total number of matrix cracks. The model converts the matrix-rich regions into equivalent penny shape crack sizes and predicts the matrix cracking stress with a fracture mechanics crack-bridging model. The estimated distribution of matrix cracking stresses is used as statistical input to predict the number of matrix cracks. The results show good agreement with the experimental results by replica observations.more » Therefore, it is found that the matrix cracking behavior mainly depends on the distribution of matrix-rich regions in the composite.« less

High resolution tempo-spatial ozone prediction with SVM and LSTM

NASA Astrophysics Data System (ADS)

Gao, D.; Zhang, Y.; Qu, Z.; Sadighi, K.; Coffey, E.; LIU, Q.; Hannigan, M.; Henze, D. K.; Dick, R.; Shang, L.; Lv, Q.

2017-12-01

To investigate and predict the exposure of ozone and other pollutants in urban areas, we utilize data from various infrastructures including EPA, NOAA and RIITS from government of Los Angeles and construct statistical models to conduct ozone concentration prediction in Los Angeles areas at finer spatial and temporal granularity. Our work involves cyber data such as traffic, roads and population data as features for prediction. Two statistical models, Support Vector Machine (SVM) and Long Short-term Memory (LSTM, deep learning method) are used for prediction. . Our experiments show that kernelized SVM gains better prediction performance when taking traffic counts, road density and population density as features, with a prediction RMSE of 7.99 ppb for all-time ozone and 6.92 ppb for peak-value ozone. With simulated NOx from Chemical Transport Model(CTM) as features, SVM generates even better prediction performance, with a prediction RMSE of 6.69ppb. We also build LSTM, which has shown great advantages at dealing with temporal sequences, to predict ozone concentration by treating ozone concentration as spatial-temporal sequences. Trained by ozone concentration measurements from the 13 EPA stations in LA area, the model achieves 4.45 ppb RMSE. Besides, we build a variant of this model which adds spatial dynamics into the model in the form of transition matrix that reveals new knowledge on pollutant transition. The forgetting gate of the trained LSTM is consistent with the delay effect of ozone concentration and the trained transition matrix shows spatial consistency with the common direction of winds in LA area.

An analytical and numerical study of Galton-Watson branching processes relevant to population dynamics

NASA Astrophysics Data System (ADS)

Jang, Sa-Han

Galton-Watson branching processes of relevance to human population dynamics are the subject of this thesis. We begin with an historical survey of the invention of the invention of this model in the middle of the 19th century, for the purpose of modelling the extinction of unusual surnames in France and Britain. We then review the principal developments and refinements of this model, and their applications to a wide variety of problems in biology and physics. Next, we discuss in detail the case where the probability generating function for a Galton-Watson branching process is a geometric series, which can be summed in closed form to yield a fractional linear generating function that can be iterated indefinitely in closed form. We then describe the matrix method of Keyfitz and Tyree, and use it to determine how large a matrix must be chosen to model accurately a Galton-Watson branching process for a very large number of generations, of the order of hundreds or even thousands. Finally, we show that any attempt to explain the recent evidence for the existence thousands of generations ago of a 'mitochondrial Eve' and a 'Y-chromosomal Adam' in terms of a the standard Galton-Watson branching process, or indeed any statistical model that assumes equality of probabilities of passing one's genes to one's descendents in later generations, is unlikely to be successful. We explain that such models take no account of the advantages that the descendents of the most successful individuals in earlier generations enjoy over their contemporaries, which must play a key role in human evolution.

Conserved G-matrices of morphological and life-history traits among continental and island blue tit populations.

PubMed

Delahaie, B; Charmantier, A; Chantepie, S; Garant, D; Porlier, M; Teplitsky, C

2017-08-01

The genetic variance-covariance matrix (G-matrix) summarizes the genetic architecture of multiple traits. It has a central role in the understanding of phenotypic divergence and the quantification of the evolutionary potential of populations. Laboratory experiments have shown that G-matrices can vary rapidly under divergent selective pressures. However, because of the demanding nature of G-matrix estimation and comparison in wild populations, the extent of its spatial variability remains largely unknown. In this study, we investigate spatial variation in G-matrices for morphological and life-history traits using long-term data sets from one continental and three island populations of blue tit (Cyanistes caeruleus) that have experienced contrasting population history and selective environment. We found no evidence for differences in G-matrices among populations. Interestingly, the phenotypic variance-covariance matrices (P) were divergent across populations, suggesting that using P as a substitute for G may be inadequate. These analyses also provide the first evidence in wild populations for additive genetic variation in the incubation period (that is, the period between last egg laid and hatching) in all four populations. Altogether, our results suggest that G-matrices may be stable across populations inhabiting contrasted environments, therefore challenging the results of previous simulation studies and laboratory experiments.

The comparison of automated clustering algorithms for resampling representative conformer ensembles with RMSD matrix.

PubMed

Kim, Hyoungrae; Jang, Cheongyun; Yadav, Dharmendra K; Kim, Mi-Hyun

2017-03-23

The accuracy of any 3D-QSAR, Pharmacophore and 3D-similarity based chemometric target fishing models are highly dependent on a reasonable sample of active conformations. Since a number of diverse conformational sampling algorithm exist, which exhaustively generate enough conformers, however model building methods relies on explicit number of common conformers. In this work, we have attempted to make clustering algorithms, which could find reasonable number of representative conformer ensembles automatically with asymmetric dissimilarity matrix generated from openeye tool kit. RMSD was the important descriptor (variable) of each column of the N × N matrix considered as N variables describing the relationship (network) between the conformer (in a row) and the other N conformers. This approach used to evaluate the performance of the well-known clustering algorithms by comparison in terms of generating representative conformer ensembles and test them over different matrix transformation functions considering the stability. In the network, the representative conformer group could be resampled for four kinds of algorithms with implicit parameters. The directed dissimilarity matrix becomes the only input to the clustering algorithms. Dunn index, Davies-Bouldin index, Eta-squared values and omega-squared values were used to evaluate the clustering algorithms with respect to the compactness and the explanatory power. The evaluation includes the reduction (abstraction) rate of the data, correlation between the sizes of the population and the samples, the computational complexity and the memory usage as well. Every algorithm could find representative conformers automatically without any user intervention, and they reduced the data to 14-19% of the original values within 1.13 s per sample at the most. The clustering methods are simple and practical as they are fast and do not ask for any explicit parameters. RCDTC presented the maximum Dunn and omega-squared values of the four algorithms in addition to consistent reduction rate between the population size and the sample size. The performance of the clustering algorithms was consistent over different transformation functions. Moreover, the clustering method can also be applied to molecular dynamics sampling simulation results.

A prototypic mathematical model of the human hair cycle.

PubMed

Al-Nuaimi, Yusur; Goodfellow, Marc; Paus, Ralf; Baier, Gerold

2012-10-07

The human hair cycle is a complex, dynamic organ-transformation process during which the hair follicle repetitively progresses from a growth phase (anagen) to a rapid apoptosis-driven involution (catagen) and finally a relative quiescent phase (telogen) before returning to anagen. At present no theory satisfactorily explains the origin of the hair cycle rhythm. Based on experimental evidence we propose a prototypic model that focuses on the dynamics of hair matrix keratinocytes. We argue that a plausible feedback-control structure between two key compartments (matrix keratinocytes and dermal papilla) leads to dynamic instabilities in the population dynamics resulting in rhythmic hair growth. The underlying oscillation consists of an autonomous switching between two quasi-steady states. Additional features of the model, namely bistability and excitability, lead to new hypotheses about the impact of interventions on hair growth. We show how in silico testing may facilitate testing of candidate hair growth modulatory agents in human HF organ culture or in clinical trials. Copyright © 2012 Elsevier Ltd. All rights reserved.

Spatial and temporal dynamics of fucoid populations (Ascophyllum nodosum and Fucus serratus): a comparison between central and range edge populations.

PubMed

Araújo, Rita M; Serrão, Ester A; Sousa-Pinto, Isabel; Åberg, Per

2014-01-01

Persistence of populations at range edges relies on local population dynamics and fitness, in the case of geographically isolated populations of species with low dispersal potential. Focusing on spatial variations in demography helps to predict the long-term capability for persistence of populations across the geographical range of species' distribution. The demography of two ecological and phylogenetically close macroalgal species with different life history characteristics was investigated by using stochastic, stage-based matrix models. Populations of Ascophyllum nodosum and Fucus serratus were sampled for up to 4 years at central locations in France and at their southern range limits in Portugal. The stochastic population growth rate (λ(s)) of A. nodosum was lower and more variable in central than in southern sites whilst for F. serratus this trend was reversed with λ(s) much lower and more variable in southern than in central populations. Individuals were larger in central than in southern populations for both species, which was reflected in the lower transition probabilities of individuals to larger size classes and higher probability of shrinkage in the southern populations. In both central and southern populations elasticity analysis (proportional sensitivity) of population growth rate showed that fertility elements had a small contribution to λ(s) that was more sensitive to changes in matrix transitions corresponding to survival. The highest elasticities were found for loop transitions in A. nodosum and for growth to larger size classes in F. serratus. Sensitivity analysis showed high selective pressure on individual growth for both species at both locations. The results of this study highlight the deterministic role of species-specific life-history traits in population demography across the geographical range of species. Additionally, this study demonstrates that individuals' life-transitions differ in vulnerability to environmental variability and shows the importance of vegetative compared to reproductive stages for the long-term persistence of populations.

Dynamic remodeling of microbial biofilms by functionally distinct exopolysaccharides.

PubMed

Chew, Su Chuen; Kundukad, Binu; Seviour, Thomas; van der Maarel, Johan R C; Yang, Liang; Rice, Scott A; Doyle, Patrick; Kjelleberg, Staffan

2014-08-05

Biofilms are densely populated communities of microbial cells protected and held together by a matrix of extracellular polymeric substances. The structure and rheological properties of the matrix at the microscale influence the retention and transport of molecules and cells in the biofilm, thereby dictating population and community behavior. Despite its importance, quantitative descriptions of the matrix microstructure and microrheology are limited. Here, particle-tracking microrheology in combination with genetic approaches was used to spatially and temporally study the rheological contributions of the major exopolysaccharides Pel and Psl in Pseudomonas aeruginosa biofilms. Psl increased the elasticity and effective cross-linking within the matrix, which strengthened its scaffold and appeared to facilitate the formation of microcolonies. Conversely, Pel reduced effective cross-linking within the matrix. Without Psl, the matrix becomes more viscous, which facilitates biofilm spreading. The wild-type biofilm decreased in effective cross-linking over time, which would be advantageous for the spreading and colonization of new surfaces. This suggests that there are regulatory mechanisms to control production of the exopolysaccharides that serve to remodel the matrix of developing biofilms. The exopolysaccharides were also found to have profound effects on the spatial organization and integration of P. aeruginosa in a mixed-species biofilm model of P. aeruginosa-Staphylococcus aureus. Pel was required for close association of the two species in mixed-species microcolonies. In contrast, Psl was important for P. aeruginosa to form single-species biofilms on top of S. aureus biofilms. Our results demonstrate that Pel and Psl have distinct physical properties and functional roles during biofilm formation. Importance: Most bacteria grow as biofilms in the environment or in association with eukaryotic hosts. Removal of biofilms that form on surfaces is a challenge in clinical and industrial settings. One of the defining features of a biofilm is its extracellular matrix. The matrix has a heterogeneous structure and is formed from a secretion of various biopolymers, including proteins, extracellular DNA, and polysaccharides. It is generally known to interact with biofilm cells, thus affecting cell physiology and cell-cell communication. Despite the fact that the matrix may comprise up to 90% of the biofilm dry weight, how the matrix properties affect biofilm structure, maturation, and interspecies interactions remain largely unexplored. This study reveals that bacteria can use specific extracellular polymers to modulate the physical properties of their microenvironment. This in turn impacts biofilm structure, differentiation, and interspecies interactions. Copyright © 2014 Chew et al.

Predictive modelling of the dielectric response of plasmonic substrates: application to the interpretation of ellipsometric spectra

NASA Astrophysics Data System (ADS)

Pugliara, A.; Bayle, M.; Bonafos, C.; Carles, R.; Respaud, M.; Makasheva, K.

2018-03-01

A predictive modelling of plasmonic substrates appropriate to read ellipsometric spectra is presented in this work. We focus on plasmonic substrates containing a single layer of silver nanoparticles (AgNPs) embedded in silica matrices. The model uses the Abeles matrix formalism and is based on the quasistatic approximation of the classical Maxwell-Garnett mixing rule, however accounting for the electronic confinement effect through the damping parameter. It is applied on samples elaborated by: (i) RF-diode sputtering followed by Plasma Enhanced Chemical Vapor Deposition (PECVD) and (ii) Low Energy Ion Beam Synthesis (LE-IBS), and represents situations with increasing degree of complexity that can be accounted for by the model. It allows extraction of the main characteristics of the AgNPs population: average size, volume fraction and distance of the AgNPs layer from the matrix free surface. Model validation is achieved through comparison with results obtained from transmission electron microscopy approving for its applicability. The advantages and limitations of the proposed model are discussed after eccentricity-based statistical analysis along with further developments related to the quality of comparison between the model-generated spectra and the experimentally-recorded ellipsometric spectra.

Conditional random matrix ensembles and the stability of dynamical systems

NASA Astrophysics Data System (ADS)

Kirk, Paul; Rolando, Delphine M. Y.; MacLean, Adam L.; Stumpf, Michael P. H.

2015-08-01

Random matrix theory (RMT) has found applications throughout physics and applied mathematics, in subject areas as diverse as communications networks, population dynamics, neuroscience, and models of the banking system. Many of these analyses exploit elegant analytical results, particularly the circular law and its extensions. In order to apply these results, assumptions must be made about the distribution of matrix elements. Here we demonstrate that the choice of matrix distribution is crucial. In particular, adopting an unrealistic matrix distribution for the sake of analytical tractability is liable to lead to misleading conclusions. We focus on the application of RMT to the long-standing, and at times fractious, ‘diversity-stability debate’, which is concerned with establishing whether large complex systems are likely to be stable. Early work (and subsequent elaborations) brought RMT to bear on the debate by modelling the entries of a system’s Jacobian matrix as independent and identically distributed (i.i.d.) random variables. These analyses were successful in yielding general results that were not tied to any specific system, but relied upon a restrictive i.i.d. assumption. Other studies took an opposing approach, seeking to elucidate general principles of stability through the analysis of specific systems. Here we develop a statistical framework that reconciles these two contrasting approaches. We use a range of illustrative dynamical systems examples to demonstrate that: (i) stability probability cannot be summarily deduced from any single property of the system (e.g. its diversity); and (ii) our assessment of stability depends on adequately capturing the details of the systems analysed. Failing to condition on the structure of dynamical systems will skew our analysis and can, even for very small systems, result in an unnecessarily pessimistic diagnosis of their stability.

An Open-Access Modeled Passenger Flow Matrix for the Global Air Network in 2010

PubMed Central

Huang, Zhuojie; Wu, Xiao; Garcia, Andres J.; Fik, Timothy J.; Tatem, Andrew J.

2013-01-01

The expanding global air network provides rapid and wide-reaching connections accelerating both domestic and international travel. To understand human movement patterns on the network and their socioeconomic, environmental and epidemiological implications, information on passenger flow is required. However, comprehensive data on global passenger flow remain difficult and expensive to obtain, prompting researchers to rely on scheduled flight seat capacity data or simple models of flow. This study describes the construction of an open-access modeled passenger flow matrix for all airports with a host city-population of more than 100,000 and within two transfers of air travel from various publicly available air travel datasets. Data on network characteristics, city population, and local area GDP amongst others are utilized as covariates in a spatial interaction framework to predict the air transportation flows between airports. Training datasets based on information from various transportation organizations in the United States, Canada and the European Union were assembled. A log-linear model controlling the random effects on origin, destination and the airport hierarchy was then built to predict passenger flows on the network, and compared to the results produced using previously published models. Validation analyses showed that the model presented here produced improved predictive power and accuracy compared to previously published models, yielding the highest successful prediction rate at the global scale. Based on this model, passenger flows between 1,491 airports on 644,406 unique routes were estimated in the prediction dataset. The airport node characteristics and estimated passenger flows are freely available as part of the Vector-Borne Disease Airline Importation Risk (VBD-Air) project at: www.vbd-air.com/data. PMID:23691194

An open-access modeled passenger flow matrix for the global air network in 2010.

PubMed

Huang, Zhuojie; Wu, Xiao; Garcia, Andres J; Fik, Timothy J; Tatem, Andrew J

2013-01-01

The expanding global air network provides rapid and wide-reaching connections accelerating both domestic and international travel. To understand human movement patterns on the network and their socioeconomic, environmental and epidemiological implications, information on passenger flow is required. However, comprehensive data on global passenger flow remain difficult and expensive to obtain, prompting researchers to rely on scheduled flight seat capacity data or simple models of flow. This study describes the construction of an open-access modeled passenger flow matrix for all airports with a host city-population of more than 100,000 and within two transfers of air travel from various publicly available air travel datasets. Data on network characteristics, city population, and local area GDP amongst others are utilized as covariates in a spatial interaction framework to predict the air transportation flows between airports. Training datasets based on information from various transportation organizations in the United States, Canada and the European Union were assembled. A log-linear model controlling the random effects on origin, destination and the airport hierarchy was then built to predict passenger flows on the network, and compared to the results produced using previously published models. Validation analyses showed that the model presented here produced improved predictive power and accuracy compared to previously published models, yielding the highest successful prediction rate at the global scale. Based on this model, passenger flows between 1,491 airports on 644,406 unique routes were estimated in the prediction dataset. The airport node characteristics and estimated passenger flows are freely available as part of the Vector-Borne Disease Airline Importation Risk (VBD-Air) project at: www.vbd-air.com/data.

Global Existence Analysis of Cross-Diffusion Population Systems for Multiple Species

NASA Astrophysics Data System (ADS)

Chen, Xiuqing; Daus, Esther S.; Jüngel, Ansgar

2018-02-01

The existence of global-in-time weak solutions to reaction-cross-diffusion systems for an arbitrary number of competing population species is proved. The equations can be derived from an on-lattice random-walk model with general transition rates. In the case of linear transition rates, it extends the two-species population model of Shigesada, Kawasaki, and Teramoto. The equations are considered in a bounded domain with homogeneous Neumann boundary conditions. The existence proof is based on a refined entropy method and a new approximation scheme. Global existence follows under a detailed balance or weak cross-diffusion condition. The detailed balance condition is related to the symmetry of the mobility matrix, which mirrors Onsager's principle in thermodynamics. Under detailed balance (and without reaction) the entropy is nonincreasing in time, but counter-examples show that the entropy may increase initially if detailed balance does not hold.

Invasion-promoting extracellular matrix composition enhances photodynamic therapy response in 3D pancreatic cancer models

NASA Astrophysics Data System (ADS)

Cramer, Gwendolyn M.; El-Hamidi, Hamid; Celli, Jonathan P.

2017-02-01

Pancreatic ductal adenocarcinoma (PDAC) is characterized by extracellular matrix-rich stromal involvement, but it is not clear how ECM properties that affect invasiveness and chemotherapy response influence efficacy of photodynamic therapy (PDT). To disentangle the mechanical and biochemical effects of ECM composition, we measured the effects of various combinations of ECM proteins on growth behavior, invasive potential, and therapeutic response of multicellular 3D pancreatic tumor models. These spheroids were grown in attachment-free conditions before embedding in combinations of rheologically characterized collagen 1 and Matrigel combinations and treated with oxaliplatin chemotherapy and PDT. We find that cells invading from collagen-embedded tumor spheroids, the least rigid ECM substrate described here, displayed better response to PDT than to oxaliplatin chemotherapy. Overall, our results support that ECM-mediated invading PDAC populations remain responsive to PDT in conditions that induce chemoresistance.

Demographic variation across successional stages and their effects on the population dynamics of the neotropical palm Euterpe precatoria.

PubMed

Otárola, Mauricio Fernández; Avalos, Gerardo

2014-06-01

• Premise of the study: Environmental heterogeneity is a strong selective force shaping adaptation and population dynamics across temporal and spatial scales. Natural and anthropogenic gradients influence the variation of environmental and biotic factors, which determine population demography and dynamics. Successional gradients are expected to influence demographic parameters, but the relationship between these gradients and the species life history, habitat requirements, and degree of variation in demographic traits remains elusive.• Methods: We used the palm Euterpe precatoria to test the effect of successional stage on plant demography within a continuous population. We calculated demographic parameters for size stages and performed matrix analyses to investigate the demographic variation within primary and secondary forests of La Selva, Costa Rica.• Key results: We observed differences in mortality and recruitment of small juveniles between primary and secondary forests. Matrix models described satisfactorily the chronosequence of population changes, which were characterized by high population growth rate in disturbed areas, and decreased growth rate in old successional forests until reaching stability.• Conclusions: Different demographic parameters can be expressed in contiguous subpopulations along a gradient of successional stages with important consequences for population dynamics. Demographic variation superimposed on these gradients contributes to generate subpopulations with different demographic composition, density, and ecological properties. Therefore, the effects of spatial variation must be reconsidered in the design of demographic analyses of tropical palms, which are prime examples of subtle local adaptation. These considerations are crucial in the implementation of management plans for palm species within spatially complex and heterogeneous tropical landscapes. © 2014 Botanical Society of America, Inc.

Combining multistate capture-recapture data with tag recoveries to estimate demographic parameters

USGS Publications Warehouse

Kendall, W.L.; Conn, P.B.; Hines, J.E.

2006-01-01

Matrix population models that allow an animal to occupy more than one state over time are important tools for population and evolutionary ecologists. Definition of state can vary, including location for metapopulation models and breeding state for life history models. For populations whose members can be marked and subsequently re-encountered, multistate mark-recapture models are available to estimate the survival and transition probabilities needed to construct population models. Multistate models have proved extremely useful in this context, but they often require a substantial amount of data and restrict estimation of transition probabilities to those areas or states subjected to formal sampling effort. At the same time, for many species, there are considerable tag recovery data provided by the public that could be modeled in order to increase precision and to extend inference to a greater number of areas or states. Here we present a statistical model for combining multistate capture-recapture data (e.g., from a breeding ground study) with multistate tag recovery data (e.g., from wintering grounds). We use this method to analyze data from a study of Canada Geese (Branta canadensis) in the Atlantic Flyway of North America. Our analysis produced marginal improvement in precision, due to relatively few recoveries, but we demonstrate how precision could be further improved with increases in the probability that a retrieved tag is reported.

Do persistently fast-growing juveniles contribute disproportionately to population growth? A new analysis tool for matrix models and its application to rainforest trees.

PubMed

Zuidema, Pieter A; Brienen, Roel J W; During, Heinjo J; Güneralp, Burak

2009-11-01

Plants and animals often exhibit strong and persistent growth variation among individuals within a species. Persistently fast-growing individuals have a higher chance of reaching reproductive size, do so at a younger age, and therefore contribute disproportionately to population growth (lambda). Here we introduce a new approach to quantify this "fast-growth effect." We propose using age-size-structured matrix models in which persistently fast and slow growers are distinguished as they occur in relatively young and old age classes for a given size category. Life-cycle pathways involving fast growth can then be identified, and their contribution to lambda is quantified through loop analysis. We applied this approach to an example species, the tropical rainforest tree Cedrela odorata, that shows persistent growth variation among individuals. Loop analysis showed that juvenile trees reaching the 10-cm diameter class at below-median age contributed twice as much to lambda as slow juvenile growers. Fast growth to larger-diameter categories also contributed disproportionately to lambda. The results were robust to changes in parameter values and life-history trade-offs. These results show that the fast-growth effect can be strong in long-lived species. Persistent growth differences among individuals should therefore be accommodated for in demographic models and life-history studies.

COMADRE: a global data base of animal demography.

PubMed

Salguero-Gómez, Roberto; Jones, Owen R; Archer, C Ruth; Bein, Christoph; de Buhr, Hendrik; Farack, Claudia; Gottschalk, Fränce; Hartmann, Alexander; Henning, Anne; Hoppe, Gabriel; Römer, Gesa; Ruoff, Tara; Sommer, Veronika; Wille, Julia; Voigt, Jakob; Zeh, Stefan; Vieregg, Dirk; Buckley, Yvonne M; Che-Castaldo, Judy; Hodgson, David; Scheuerlein, Alexander; Caswell, Hal; Vaupel, James W

2016-03-01

The open-data scientific philosophy is being widely adopted and proving to promote considerable progress in ecology and evolution. Open-data global data bases now exist on animal migration, species distribution, conservation status, etc. However, a gap exists for data on population dynamics spanning the rich diversity of the animal kingdom world-wide. This information is fundamental to our understanding of the conditions that have shaped variation in animal life histories and their relationships with the environment, as well as the determinants of invasion and extinction. Matrix population models (MPMs) are among the most widely used demographic tools by animal ecologists. MPMs project population dynamics based on the reproduction, survival and development of individuals in a population over their life cycle. The outputs from MPMs have direct biological interpretations, facilitating comparisons among animal species as different as Caenorhabditis elegans, Loxodonta africana and Homo sapiens. Thousands of animal demographic records exist in the form of MPMs, but they are dispersed throughout the literature, rendering comparative analyses difficult. Here, we introduce the COMADRE Animal Matrix Database, an open-data online repository, which in its version 1.0.0 contains data on 345 species world-wide, from 402 studies with a total of 1625 population projection matrices. COMADRE also contains ancillary information (e.g. ecoregion, taxonomy, biogeography, etc.) that facilitates interpretation of the numerous demographic metrics that can be derived from its MPMs. We provide R code to some of these examples. We introduce the COMADRE Animal Matrix Database, a resource for animal demography. Its open-data nature, together with its ancillary information, will facilitate comparative analysis, as will the growing availability of databases focusing on other aspects of the rich animal diversity, and tools to query and combine them. Through future frequent updates of COMADRE, and its integration with other online resources, we encourage animal ecologists to tackle global ecological and evolutionary questions with unprecedented sample size. © 2016 The Authors. Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society.

A multiphase model for tissue construct growth in a perfusion bioreactor.

PubMed

O'Dea, R D; Waters, S L; Byrne, H M

2010-06-01

The growth of a cell population within a rigid porous scaffold in a perfusion bioreactor is studied, using a three-phase continuum model of the type presented by Lemon et al. (2006, Multiphase modelling of tissue growth using the theory of mixtures. J. Math. Biol., 52, 571-594) to represent the cell population (and attendant extracellular matrix), culture medium and porous scaffold. The bioreactor system is modelled as a 2D channel containing the cell-seeded rigid porous scaffold (tissue construct) which is perfused with culture medium. The study concentrates on (i) the cell-cell and cell-scaffold interactions and (ii) the impact of mechanotransduction mechanisms on construct composition. A numerical and analytical analysis of the model equations is presented and, depending upon the relative importance of cell aggregation and repulsion, markedly different cell movement is revealed. Additionally, mechanotransduction effects due to cell density, pressure and shear stress-mediated tissue growth are shown to generate qualitative differences in the composition of the resulting construct. The results of our simulations indicate that this model formulation (in conjunction with appropriate experimental data) has the potential to provide a means of identifying the dominant regulatory stimuli in a cell population.

Approaches for the direct estimation of lambda, and demographic contributions to lambda, using capture-recapture data

USGS Publications Warehouse

Nichols, J.D.; Hines, J.E.

2002-01-01

We first consider the estimation of the finite rate of population increase or population growth rate, lambda sub i, using capture-recapture data from open populations. We review estimation and modelling of lambda sub i under three main approaches to modelling open-population data: the classic approach of Jolly (1965) and Seber (1965), the superpopulation approach of Crosbie & Manly (1985) and Schwarz & Arnason (1996), and the temporal symmetry approach of Pradel (1996). Next, we consider the contributions of different demographic components to lambda sub i using a probabilistic approach based on the composition of the population at time i + 1 (Nichols et al., 2000b). The parameters of interest are identical to the seniority parameters, gamma sub i, of Pradel (1996). We review estimation of gamma sub i under the classic, superpopulation, and temporal symmetry approaches. We then compare these direct estimation approaches for lambda sub i and gamma sub i with analogues computed using projection matrix asymptotics. We also discuss various extensions of the estimation approaches to multistate applications and to joint likelihoods involving multiple data types.

Pros and cons of estimating the reproduction number from early epidemic growth rate of influenza A (H1N1) 2009.

PubMed

Nishiura, Hiroshi; Chowell, Gerardo; Safan, Muntaser; Castillo-Chavez, Carlos

2010-01-07

In many parts of the world, the exponential growth rate of infections during the initial epidemic phase has been used to make statistical inferences on the reproduction number, R, a summary measure of the transmission potential for the novel influenza A (H1N1) 2009. The growth rate at the initial stage of the epidemic in Japan led to estimates for R in the range 2.0 to 2.6, capturing the intensity of the initial outbreak among school-age children in May 2009. An updated estimate of R that takes into account the epidemic data from 29 May to 14 July is provided. An age-structured renewal process is employed to capture the age-dependent transmission dynamics, jointly estimating the reproduction number, the age-dependent susceptibility and the relative contribution of imported cases to secondary transmission. Pitfalls in estimating epidemic growth rates are identified and used for scrutinizing and re-assessing the results of our earlier estimate of R. Maximum likelihood estimates of R using the data from 29 May to 14 July ranged from 1.21 to 1.35. The next-generation matrix, based on our age-structured model, predicts that only 17.5% of the population will experience infection by the end of the first pandemic wave. Our earlier estimate of R did not fully capture the population-wide epidemic in quantifying the next-generation matrix from the estimated growth rate during the initial stage of the pandemic in Japan. In order to quantify R from the growth rate of cases, it is essential that the selected model captures the underlying transmission dynamics embedded in the data. Exploring additional epidemiological information will be useful for assessing the temporal dynamics. Although the simple concept of R is more easily grasped by the general public than that of the next-generation matrix, the matrix incorporating detailed information (e.g., age-specificity) is essential for reducing the levels of uncertainty in predictions and for assisting public health policymaking. Model-based prediction and policymaking are best described by sharing fundamental notions of heterogeneous risks of infection and death with non-experts to avoid potential confusion and/or possible misuse of modelling results.

In vitro and in vivo approaches to study osteocyte biology.

PubMed

Kalajzic, Ivo; Matthews, Brya G; Torreggiani, Elena; Harris, Marie A; Divieti Pajevic, Paola; Harris, Stephen E

2013-06-01

Osteocytes, the most abundant cell population of the bone lineage, have been a major focus in the bone research field in recent years. This population of cells that resides within mineralized matrix is now thought to be the mechanosensory cell in bone and plays major roles in the regulation of bone formation and resorption. Studies of osteocytes had been impaired by their location, resulting in numerous attempts to isolate primary osteocytes and to generate cell lines representative of the osteocytic phenotype. Progress has been achieved in recent years by utilizing in vivo genetic technology and generation of osteocyte directed transgenic and gene deficiency mouse models. We will provide an overview of the current in vitro and in vivo models utilized to study osteocyte biology. We discuss generation of osteocyte-like cell lines and isolation of primary osteocytes and summarize studies that have utilized these cellular models to understand the functional role of osteocytes. Approaches that attempt to selectively identify and isolate osteocytes using fluorescent protein reporters driven by regulatory elements of genes that are highly expressed in osteocytes will be discussed. In addition, recent in vivo studies utilizing overexpression or conditional deletion of various genes using dentin matrix protein (Dmp1) directed Cre recombinase are outlined. In conclusion, evaluation of the benefits and deficiencies of currently used cell lines/genetic models in understanding osteocyte biology underlines the current progress in this field. The future efforts will be directed towards developing novel in vitro and in vivo models that would additionally facilitate in understanding the multiple roles of osteocytes. Copyright © 2012 Elsevier Inc. All rights reserved.

The Use of Surrogate Data in Demographic Population Viability Analysis: A Case Study of California Sea Lions

PubMed Central

2015-01-01

Reliable data necessary to parameterize population models are seldom available for imperiled species. As an alternative, data from populations of the same species or from ecologically similar species have been used to construct models. In this study, we evaluated the use of demographic data collected at one California sea lion colony (Los Islotes) to predict the population dynamics of the same species from two other colonies (San Jorge and Granito) in the Gulf of California, Mexico, for which demographic data are lacking. To do so, we developed a stochastic demographic age-structured matrix model and conducted a population viability analysis for each colony. For the Los Islotes colony we used site-specific pup, juvenile, and adult survival probabilities, as well as birth rates for older females. For the other colonies, we used site-specific pup and juvenile survival probabilities, but used surrogate data from Los Islotes for adult survival probabilities and birth rates. We assessed these models by comparing simulated retrospective population trajectories to observed population trends based on count data. The projected population trajectories approximated the observed trends when surrogate data were used for one colony but failed to match for a second colony. Our results indicate that species-specific and even region-specific surrogate data may lead to erroneous conservation decisions. These results highlight the importance of using population-specific demographic data in assessing extinction risk. When vital rates are not available and immediate management actions must be taken, in particular for imperiled species, we recommend the use of surrogate data only when the populations appear to have similar population trends. PMID:26413746

Framework for analyzing ecological trait-based models in multidimensional niche spaces

NASA Astrophysics Data System (ADS)

Biancalani, Tommaso; DeVille, Lee; Goldenfeld, Nigel

2015-05-01

We develop a theoretical framework for analyzing ecological models with a multidimensional niche space. Our approach relies on the fact that ecological niches are described by sequences of symbols, which allows us to include multiple phenotypic traits. Ecological drivers, such as competitive exclusion, are modeled by introducing the Hamming distance between two sequences. We show that a suitable transform diagonalizes the community interaction matrix of these models, making it possible to predict the conditions for niche differentiation and, close to the instability onset, the asymptotically long time population distributions of niches. We exemplify our method using the Lotka-Volterra equations with an exponential competition kernel.

Population dynamics of long-tailed ducks breeding on the Yukon-Kuskokwim Delta, Alaska

USGS Publications Warehouse

Schamber, Jason L.; Flint, Paul L.; Grand, J. Barry; Wilson, Heather M.; Morse, Julie A.

2009-01-01

Population estimates for long-tailed ducks in North America have declined by nearly 50% over the past 30 years. Life history and population dynamics of this species are difficult to ascertain, because the birds nest at low densities across a broad range of habitat types. Between 1991 and 2004, we collected information on productivity and survival of long-tailed ducks at three locations on the Yukon-Kuskokwim Delta. Clutch size averaged 7.1 eggs, and nesting success averaged 30%. Duckling survival to 30 days old averaged 10% but was highly variable among years, ranging from 0% to 25%. Apparent annual survival of adult females based on mark-recapture of nesting females was estimated at 74%. We combined these estimates of survival and productivity into a matrix-based population model, which predicted an annual population decline of 19%. Elasticities indicated that population growth rate (λ) was most sensitive to changes in adult female survival. Further, the relatively high sensitivity of λ to duckling survival suggests that low duckling survival may be a bottleneck to productivity in some years. These data represent the first attempt to synthesize a population model for this species. Although our analyses were hampered by the small sample sizes inherent in studying a dispersed nesting species, our model provides a basis for management actions and can be enhanced as additional data become available.

Quantifying avian nest survival along an urbanization gradient using citizen- and scientist-generated data.

PubMed

Ryder, Thomas B; Reitsma, Robert; Evans, Brian; Marra, Peter P

2010-03-01

Despite the increasing pace of urbanization little is known about the factors that limit bird populations (i.e., population-level processes) within the urban/suburban land-use matrix. Here, we report rates of nest survival within the matrix of an urban land-use gradient in the greater Washington, D.C., USA, area for five common songbirds using data collected by scientists and citizens as part of a project called Neighborhood Nestwatch. Using program MARK, we modeled the effects of species, urbanization at multiple spatial scales (canopy cover and impervious surface), and observer (citizen vs. scientist) on nest survival of four open-cup and one cavity-nesting species. In addition, artificial nests were used to determine the relative impacts of specific predators along the land-use gradient. Our results suggest that predation on nests within the land-use matrix declines with urbanization but that there are species-specific differences. Moreover, variation in nest survival among species was best explained by urbanization metrics measured at larger "neighborhood" spatial scales (e.g., 1000 m). Trends were supported by data from artificial nests and suggest that variable predator communities (avian vs. mammalian) are one possible mechanism to explain differential nest survival. In addition, we assessed the quality of citizen science data and show that citizens had no negative effect on nest survival and provided estimates of nest survival comparable to Smithsonian biologists. Although birds nesting within the urban matrix experienced higher nest survival, individuals also faced a multitude of other challenges such as contaminants and invasive species, all of which could reduce adult survival.

Generalization of fewest-switches surface hopping for coherences

NASA Astrophysics Data System (ADS)

Tempelaar, Roel; Reichman, David R.

2018-03-01

Fewest-switches surface hopping (FSSH) is perhaps the most widely used mixed quantum-classical approach for the modeling of non-adiabatic processes, but its original formulation is restricted to (adiabatic) population terms of the quantum density matrix, leaving its implementations with an inconsistency in the treatment of populations and coherences. In this article, we propose a generalization of FSSH that treats both coherence and population terms on equal footing and which formally reduces to the conventional FSSH algorithm for the case of populations. This approach, coherent fewest-switches surface hopping (C-FSSH), employs a decoupling of population relaxation and pure dephasing and involves two replicas of the classical trajectories interacting with two active surfaces. Through extensive benchmark calculations of a spin-boson model involving a Debye spectral density, we demonstrate the potential of C-FSSH to deliver highly accurate results for a large region of parameter space. Its uniform description of populations and coherences is found to resolve incorrect behavior observed for conventional FSSH in various cases, in particular at low temperature, while the parameter space regions where it breaks down are shown to be quite limited. Its computational expenses are virtually identical to conventional FSSH.

Sexual selection and population divergence II. Divergence in different sexual traits and signal modalities in field crickets (Teleogryllus oceanicus).

PubMed

Pascoal, Sonia; Mendrok, Magdalena; Wilson, Alastair J; Hunt, John; Bailey, Nathan W

2017-06-01

Sexual selection can target many different types of traits. However, the relative influence of different sexually selected traits during evolutionary divergence is poorly understood. We used the field cricket Teleogryllus oceanicus to quantify and compare how five traits from each of three sexual signal modalities and components diverge among allopatric populations: male advertisement song, cuticular hydrocarbon (CHC) profiles and forewing morphology. Population divergence was unexpectedly consistent: we estimated the among-population (genetic) variance-covariance matrix, D, for all 15 traits, and D max explained nearly two-thirds of its variation. CHC and wing traits were most tightly integrated, whereas song varied more independently. We modeled the dependence of among-population trait divergence on genetic distance estimated from neutral markers to test for signatures of selection versus neutral divergence. For all three sexual trait types, phenotypic variation among populations was largely explained by a neutral model of divergence. Our findings illustrate how phenotypic integration across different types of sexual traits might impose constraints on the evolution of mating isolation and divergence via sexual selection. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Combining dispersal, landscape connectivity and habitat suitability to assess climate-induced changes in the distribution of Cunningham’s skink, Egernia cunninghami

PubMed Central

Stow, Adam J.; Baumgartner, John B.; Beaumont, Linda J.

2017-01-01

The ability of species to track their climate niche is dependent on their dispersal potential and the connectivity of the landscape matrix linking current and future suitable habitat. However, studies modeling climate-driven range shifts rarely address the movement of species across landscapes realistically, often assuming “unlimited” or “no” dispersal. Here, we incorporate dispersal rate and landscape connectivity with a species distribution model (Maxent) to assess the extent to which the Cunningham’s skink (Egernia cunninghami) may be capable of tracking spatial shifts in suitable habitat as climate changes. Our model was projected onto four contrasting, but equally plausible, scenarios describing futures that are (relative to now) hot/wet, warm/dry, hot/with similar precipitation and warm/wet, at six time horizons with decadal intervals (2020–2070) and at two spatial resolutions: 1 km and 250 m. The size of suitable habitat was projected to decline 23–63% at 1 km and 26–64% at 250 m, by 2070. Combining Maxent output with the dispersal rate of the species and connectivity of the intervening landscape matrix showed that most current populations in regions projected to become unsuitable in the medium to long term, will be unable to shift the distance necessary to reach suitable habitat. In particular, numerous populations currently inhabiting the trailing edge of the species’ range are highly unlikely to be able to disperse fast enough to track climate change. Unless these populations are capable of adaptation they are likely to be extirpated. We note, however, that the core of the species distribution remains suitable across the broad spectrum of climate scenarios considered. Our findings highlight challenges faced by philopatric species and the importance of adaptation for the persistence of peripheral populations under climate change. PMID:28873398

Population dynamics of the Concho water snake in rivers and reservoirs

USGS Publications Warehouse

Whiting, M.J.; Dixon, J.R.; Greene, B.D.; Mueller, J.M.; Thornton, O.W.; Hatfield, J.S.; Nichols, J.D.; Hines, J.E.

2008-01-01

The Concho Water Snake (Nerodia harteri paucimaculata) is confined to the Concho–Colorado River valley of central Texas, thereby occupying one of the smallest geographic ranges of any North American snake. In 1986, N. h. paucimaculata was designated as a federally threatened species, in large part because of reservoir projects that were perceived to adversely affect the amount of habitat available to the snake. During a ten-year period (1987–1996), we conducted capture–recapture field studies to assess dynamics of five subpopulations of snakes in both natural (river) and man-made (reservoir) habitats. Because of differential sampling of subpopulations, we present separate results for all five subpopulations combined (including large reservoirs) and three of the five subpopulations (excluding large reservoirs). We used multistate capture–recapture models to deal with stochastic transitions between pre-reproductive and reproductive size classes and to allow for the possibility of different survival and capture probabilities for the two classes. We also estimated both the finite rate of increase (λ) for a deterministic, stage-based, female-only matrix model using the average litter size, and the average rate of adult population change, λ ˆ, which describes changes in numbers of adult snakes, using a direct capture–recapture approach to estimation. Average annual adult survival was about 0.23 and similar for males and females. Average annual survival for subadults was about 0.14. The parameter estimates from the stage-based projection matrix analysis all yielded asymptotic values of λ < 1, suggesting populations that are not viable. However, the direct estimates of average adult λ for the three subpopulations excluding major reservoirs were λ ˆ  =  1.26, SE ˆ(λ ˆ)  =  0.18 and λ ˆ  =  0.99, SE ˆ(λ ˆ)  =  0.79, based on two different models. Thus, the direct estimation approach did not provide strong evidence of population declines of the riverine subpopulations, but the estimates are characterized by substantial uncertainty.

Population pharmacokinetic model of transdermal nicotine delivered from a matrix-type patch.

PubMed

Linakis, Matthew W; Rower, Joseph E; Roberts, Jessica K; Miller, Eleanor I; Wilkins, Diana G; Sherwin, Catherine M T

2017-12-01

Nicotine addiction is an issue faced by millions of individuals worldwide. As a result, nicotine replacement therapies, such as transdermal nicotine patches, have become widely distributed and used. While the pharmacokinetics of transdermal nicotine have been extensively described using noncompartmental methods, there are few data available describing the between-subject variability in transdermal nicotine pharmacokinetics. The aim of this investigation was to use population pharmacokinetic techniques to describe this variability, particularly as it pertains to the absorption of nicotine from the transdermal patch. A population pharmacokinetic parent-metabolite model was developed using plasma concentrations from 25 participants treated with transdermal nicotine. Covariates tested in this model included: body weight, body mass index, body surface area (calculated using the Mosteller equation) and sex. Nicotine pharmacokinetics were best described with a one-compartment model with absorption based on a Weibull distribution and first-order elimination and a single compartment for the major metabolite, cotinine. Body weight was a significant covariate on apparent volume of distribution of nicotine (exponential scaling factor 1.42). After the inclusion of body weight in the model, no other covariates were significant. This is the first population pharmacokinetic model to describe the absorption and disposition of transdermal nicotine and its metabolism to cotinine and the pharmacokinetic variability between individuals who were administered the patch. © 2017 The British Pharmacological Society.

The agroecological matrix as alternative to the land-sparing/agriculture intensification model.

PubMed

Perfecto, Ivette; Vandermeer, John

2010-03-30

Among the myriad complications involved in the current food crisis, the relationship between agriculture and the rest of nature is one of the most important yet remains only incompletely analyzed. Particularly in tropical areas, agriculture is frequently seen as the antithesis of the natural world, where the problem is framed as one of minimizing land devoted to agriculture so as to devote more to conservation of biodiversity and other ecosystem services. In particular, the "forest transition model" projects an overly optimistic vision of a future where increased agricultural intensification (to produce more per hectare) and/or increased rural-to-urban migration (to reduce the rural population that cuts forest for agriculture) suggests a near future of much tropical aforestation and higher agricultural production. Reviewing recent developments in ecological theory (showing the importance of migration between fragments and local extinction rates) coupled with empirical evidence, we argue that there is little to suggest that the forest transition model is useful for tropical areas, at least under current sociopolitical structures. A model that incorporates the agricultural matrix as an integral component of conservation programs is proposed. Furthermore, we suggest that this model will be most successful within a framework of small-scale agroecological production.

Sorption of small molecules in polymeric media

NASA Astrophysics Data System (ADS)

Camboni, Federico; Sokolov, Igor M.

2016-12-01

We discuss the sorption of penetrant molecules from the gas phase by a polymeric medium within a model which is very close in spirit to the dual sorption mode model: the penetrant molecules are partly dissolved within the polymeric matrix, partly fill the preexisting voids. The only difference with the initial dual sorption mode situation is the assumption that the two populations of molecules are in equilibrium with each other. Applying basic thermodynamics principles we obtain the dependence of the penetrant concentration on the pressure in the gas phase and find that this is expressed via the Lambert W-function, a different functional form than the one proposed by dual sorption mode model. The Lambert-like isotherms appear universally at low and moderate pressures and originate from the assumption that the internal energy in a polymer-penetrant-void ternary mixture is (in the lowest order) a bilinear form in the concentrations of the three components. Fitting the existing data shows that in the domain of parameters where the dual sorption mode model is typically applied, the Lambert function, which describes the same behavior as the one proposed by the gas-polymer matrix model, fits the data equally well.

Information matrix estimation procedures for cognitive diagnostic models.

PubMed

Liu, Yanlou; Xin, Tao; Andersson, Björn; Tian, Wei

2018-03-06

Two new methods to estimate the asymptotic covariance matrix for marginal maximum likelihood estimation of cognitive diagnosis models (CDMs), the inverse of the observed information matrix and the sandwich-type estimator, are introduced. Unlike several previous covariance matrix estimators, the new methods take into account both the item and structural parameters. The relationships between the observed information matrix, the empirical cross-product information matrix, the sandwich-type covariance matrix and the two approaches proposed by de la Torre (2009, J. Educ. Behav. Stat., 34, 115) are discussed. Simulation results show that, for a correctly specified CDM and Q-matrix or with a slightly misspecified probability model, the observed information matrix and the sandwich-type covariance matrix exhibit good performance with respect to providing consistent standard errors of item parameter estimates. However, with substantial model misspecification only the sandwich-type covariance matrix exhibits robust performance. © 2018 The British Psychological Society.

Population Fisher information matrix and optimal design of discrete data responses in population pharmacodynamic experiments.

PubMed

Ogungbenro, Kayode; Aarons, Leon

2011-08-01

In the recent years, interest in the application of experimental design theory to population pharmacokinetic (PK) and pharmacodynamic (PD) experiments has increased. The aim is to improve the efficiency and the precision with which parameters are estimated during data analysis and sometimes to increase the power and reduce the sample size required for hypothesis testing. The population Fisher information matrix (PFIM) has been described for uniresponse and multiresponse population PK experiments for design evaluation and optimisation. Despite these developments and availability of tools for optimal design of population PK and PD experiments much of the effort has been focused on repeated continuous variable measurements with less work being done on repeated discrete type measurements. Discrete data arise mainly in PDs e.g. ordinal, nominal, dichotomous or count measurements. This paper implements expressions for the PFIM for repeated ordinal, dichotomous and count measurements based on analysis by a mixed-effects modelling technique. Three simulation studies were used to investigate the performance of the expressions. Example 1 is based on repeated dichotomous measurements, Example 2 is based on repeated count measurements and Example 3 is based on repeated ordinal measurements. Data simulated in MATLAB were analysed using NONMEM (Laplace method) and the glmmML package in R (Laplace and adaptive Gauss-Hermite quadrature methods). The results obtained for Examples 1 and 2 showed good agreement between the relative standard errors obtained using the PFIM and simulations. The results obtained for Example 3 showed the importance of sampling at the most informative time points. Implementation of these expressions will provide the opportunity for efficient design of population PD experiments that involve discrete type data through design evaluation and optimisation.

Temperature dependence of the intensity of the vibration-rotational absorption band ν2 of H2O trapped in an argon matrix

NASA Astrophysics Data System (ADS)

Pitsevich, G.; Doroshenko, I.; Malevich, A..; Shalamberidze, E.; Sapeshko, V.; Pogorelov, V.; Pettersson, L. G. M.

2017-02-01

Using two sets of effective rotational constants for the ground (000) and the excited bending (010) vibrational states the calculation of frequencies and intensities of vibration-rotational transitions for J″ = 0 - 2; and J‧ = 0 - 3; was carried out in frame of the model of a rigid asymmetric top for temperatures from 0 to 40 K. The calculation of the intensities of vibration-rotational absorption bands of H2O in an Ar matrix was carried out both for thermodynamic equilibrium and for the case of non-equilibrium population of para- and ortho-states. For the analysis of possible interaction of vibration-rotational and translational motions of a water molecule in an Ar matrix by 3D Schrödinger equation solving using discrete variable representation (DVR) method, calculations of translational frequencies of H2O in a cage formed after one argon atom deleting were carried out. The results of theoretical calculations were compared to experimental data taken from literature.

A population model of the impact of a rodenticide containing strychnine on Great Basin Gophersnakes (Pituophis catenifer deserticola).

PubMed

Bishop, Christine A; Williams, Kathleen E; Kirk, David A; Nantel, Patrick; Reed, Eric; Elliott, John E

2016-09-01

Strychnine is a neurotoxin and an active ingredient in some rodenticides which are placed in burrows to suppress pocket gopher (Thomomys talpoides) populations in range and crop land in western North America. The population level impact was modelled of the use of strychnine-based rodenticides on a non-target snake species, the Great Basin Gophersnake (Pituophis catenifer deserticola), which is a predator of pocket gopher and a Species at Risk in Canada. Using information on population density, demographics, and movement and habitat suitability for the Gophersnake living in an agricultural valley in BC, Canada, we estimated the impact of the poisoning of adult snakes on the long-term population size. To determine the area where Gophersnakes could be exposed to strychnine, we used vendor records of a rodenticide, and quantified the landcover areas of orchards and vineyards where the compound was most commonly applied. GIS analysis determined the areas of overlap between those agricultural lands and suitable habitats used by Gophersnakes. Stage-based population matrix models revealed that in a low density (0.1/ha) population scenario, a diet of one pocket gopher per year wherein 10 % of them carried enough strychnine to kill an adult snake could cause the loss of 2 females annually from the population and this would reduce the population by 35.3 % in 25 years. Under the same dietary exposure, up to 35 females could die per year in a high density (0.4/ha) population which would result in a loss of 50 % of adults in 25 years.

Clumpak: a program for identifying clustering modes and packaging population structure inferences across K.

PubMed

Kopelman, Naama M; Mayzel, Jonathan; Jakobsson, Mattias; Rosenberg, Noah A; Mayrose, Itay

2015-09-01

The identification of the genetic structure of populations from multilocus genotype data has become a central component of modern population-genetic data analysis. Application of model-based clustering programs often entails a number of steps, in which the user considers different modelling assumptions, compares results across different predetermined values of the number of assumed clusters (a parameter typically denoted K), examines multiple independent runs for each fixed value of K, and distinguishes among runs belonging to substantially distinct clustering solutions. Here, we present Clumpak (Cluster Markov Packager Across K), a method that automates the postprocessing of results of model-based population structure analyses. For analysing multiple independent runs at a single K value, Clumpak identifies sets of highly similar runs, separating distinct groups of runs that represent distinct modes in the space of possible solutions. This procedure, which generates a consensus solution for each distinct mode, is performed by the use of a Markov clustering algorithm that relies on a similarity matrix between replicate runs, as computed by the software Clumpp. Next, Clumpak identifies an optimal alignment of inferred clusters across different values of K, extending a similar approach implemented for a fixed K in Clumpp and simplifying the comparison of clustering results across different K values. Clumpak incorporates additional features, such as implementations of methods for choosing K and comparing solutions obtained by different programs, models, or data subsets. Clumpak, available at http://clumpak.tau.ac.il, simplifies the use of model-based analyses of population structure in population genetics and molecular ecology. © 2015 John Wiley & Sons Ltd.

Table-sized matrix model in fractional learning

NASA Astrophysics Data System (ADS)

Soebagyo, J.; Wahyudin; Mulyaning, E. C.

2018-05-01

This article provides an explanation of the fractional learning model i.e. a Table-Sized Matrix model in which fractional representation and its operations are symbolized by the matrix. The Table-Sized Matrix are employed to develop problem solving capabilities as well as the area model. The Table-Sized Matrix model referred to in this article is used to develop an understanding of the fractional concept to elementary school students which can then be generalized into procedural fluency (algorithm) in solving the fractional problem and its operation.

Nonlinear Fano interferences in open quantum systems: An exactly solvable model

NASA Astrophysics Data System (ADS)

Finkelstein-Shapiro, Daniel; Calatayud, Monica; Atabek, Osman; Mujica, Vladimiro; Keller, Arne

2016-06-01

We obtain an explicit solution for the stationary-state populations of a dissipative Fano model, where a discrete excited state is coupled to a continuum set of states; both excited sets of states are reachable by photoexcitation from the ground state. The dissipative dynamic is described by a Liouville equation in Lindblad form and the field intensity can take arbitrary values within the model. We show that the population of the continuum states as a function of laser frequency can always be expressed as a Fano profile plus a Lorentzian function with effective parameters whose explicit expressions are given in the case of a closed system coupled to a bath as well as for the original Fano scattering framework. Although the solution is intricate, it can be elegantly expressed as a linear transformation of the kernel of a 4 ×4 matrix which has the meaning of an effective Liouvillian. We unveil key notable processes related to the optical nonlinearity and which had not been reported to date: electromagnetic-induced transparency, population inversions, power narrowing and broadening, as well as an effective reduction of the Fano asymmetry parameter.

Genetic association analysis of Osteopontin and Matrix Gla Protein genes polymorphisms with primary knee osteoarthritis in Mexican population.

PubMed

Borgonio-Cuadra, Verónica Marusa; González-Huerta, Norma Celia; Rojas-Toledo, Emma Xochitl; Morales-Hernández, Eugenio; Pérez-Hernández, Nonanzit; Rodríguez-Pérez, José Manuel; Tovilla-Zárate, Carlos Alfonso; González-Castro, Thelma Beatriz; Hernández-Díaz, Yazmín; López-Narváez, María Lilia; Miranda-Duarte, Antonio

2018-05-18

Primary osteoarthritis (OA) is a complex entity in which several loci related to different molecular pathways or classes of molecules are associated with its development as demonstrated through genetic association studies. Genes involved in bone formation and mineralization, such as osteopontin (OPN) and Matrix Gla protein (MGP), could also be related with OA. The aim of this study was to evaluate the association between the genetic variants of OPN and MGP with primary knee osteoarthritis in a Mexican population. A case-control study was conducted in 296 patients with primary knee osteoarthritis and in 354 control subjects. Study groups were assessed radiologically. The rs11730582 of OPN and rs1800802, rs1800801, and rs4236 of MGP were determined by TaqMan allele discrimination assays. The haplotypes of the polymorphisms of MGP were constructed. The association was tested through univariate and multivariate non-conditional logistic regression analyses. The polymorphisms of MGP complied with Hardy-Weinberg (HW) equilibrium. The polymorphisms of OPN and MGP were not significantly associated with primary knee osteoarthritis in the codominant, dominant, and recessive models (p > 0.05). Our study suggests that there are no associations between OPN and MGP polymorphisms with primary knee osteoarthritis in Mexican population.

Hierarchical demographic approaches for assessing invasion dynamics of non-indigenous species: An example using northern snakehead (Channa argus)

USGS Publications Warehouse

Jiao, Y.; Lapointe, N.W.R.; Angermeier, P.L.; Murphy, B.R.

2009-01-01

Models of species' demographic features are commonly used to understand population dynamics and inform management tactics. Hierarchical demographic models are ideal for the assessment of non-indigenous species because our knowledge of non-indigenous populations is usually limited, data on demographic traits often come from a species' native range, these traits vary among populations, and traits are likely to vary considerably over time as species adapt to new environments. Hierarchical models readily incorporate this spatiotemporal variation in species' demographic traits by representing demographic parameters as multi-level hierarchies. As is done for traditional non-hierarchical matrix models, sensitivity and elasticity analyses are used to evaluate the contributions of different life stages and parameters to estimates of population growth rate. We applied a hierarchical model to northern snakehead (Channa argus), a fish currently invading the eastern United States. We used a Monte Carlo approach to simulate uncertainties in the sensitivity and elasticity analyses and to project future population persistence under selected management tactics. We gathered key biological information on northern snakehead natural mortality, maturity and recruitment in its native Asian environment. We compared the model performance with and without hierarchy of parameters. Our results suggest that ignoring the hierarchy of parameters in demographic models may result in poor estimates of population size and growth and may lead to erroneous management advice. In our case, the hierarchy used multi-level distributions to simulate the heterogeneity of demographic parameters across different locations or situations. The probability that the northern snakehead population will increase and harm the native fauna is considerable. Our elasticity and prognostic analyses showed that intensive control efforts immediately prior to spawning and/or juvenile-dispersal periods would be more effective (and probably require less effort) than year-round control efforts. Our study demonstrates the importance of considering the hierarchy of parameters in estimating population growth rate and evaluating different management strategies for non-indigenous invasive species. ?? 2009 Elsevier B.V.

The network level reproduction number for infectious diseases with both vertical and horizontal transmission.

PubMed

Xue, Ling; Scoglio, Caterina

2013-05-01

A wide range of infectious diseases are both vertically and horizontally transmitted. Such diseases are spatially transmitted via multiple species in heterogeneous environments, typically described by complex meta-population models. The reproduction number, R0, is a critical metric predicting whether the disease can invade the meta-population system. This paper presents the reproduction number for a generic disease vertically and horizontally transmitted among multiple species in heterogeneous networks, where nodes are locations, and links reflect outgoing or incoming movement flows. The metapopulation model for vertically and horizontally transmitted diseases is gradually formulated from two species, two-node network models. We derived an explicit expression of R0, which is the spectral radius of a matrix reduced in size with respect to the original next generation matrix. The reproduction number is shown to be a function of vertical and horizontal transmission parameters, and the lower bound is the reproduction number for horizontal transmission. As an application, the reproduction number and its bounds for the Rift Valley fever zoonosis, where livestock, mosquitoes, and humans are the involved species are derived. By computing the reproduction number for different scenarios through numerical simulations, we found the reproduction number is affected by livestock movement rates only when parameters are heterogeneous across nodes. To summarize, our study contributes the reproduction number for vertically and horizontally transmitted diseases in heterogeneous networks. This explicit expression is easily adaptable to specific infectious diseases, affording insights into disease evolution. Copyright © 2013 Elsevier Inc. All rights reserved.

Population viability of Pediocactus bradyi (Cactaceae) in a changing climate.

PubMed

Shryock, Daniel F; Esque, Todd C; Hughes, Lee

2014-11-01

A key question concerns the vulnerability of desert species adapted to harsh, variable climates to future climate change. Evaluating this requires coupling long-term demographic models with information on past and projected future climates. We investigated climatic drivers of population growth using a 22-yr demographic model for Pediocactus bradyi, an endangered cactus in northern Arizona. We used a matrix model to calculate stochastic population growth rates (λs) and the relative influences of life-cycle transitions on population growth. Regression models linked population growth with climatic variability, while stochastic simulations were used to (1) understand how predicted increases in drought frequency and extreme precipitation would affect λs, and (2) quantify variability in λs based on temporal replication of data. Overall λs was below unity (0.961). Population growth was equally influenced by fecundity and survival and significantly correlated with increased annual precipitation and higher winter temperatures. Stochastic simulations increasing the probability of drought and extreme precipitation reduced λs, but less than simulations increasing the probability of drought alone. Simulations varying the temporal replication of data suggested 14 yr were required for accurate λs estimates. Pediocactus bradyi may be vulnerable to increases in the frequency and intensity of extreme climatic events, particularly drought. Biotic interactions resulting in low survival during drought years outweighed increased seedling establishment following heavy precipitation. Climatic extremes beyond historical ranges of variability may threaten rare desert species with low population growth rates and therefore high susceptibility to stochastic events. © 2014 Botanical Society of America, Inc.

Thalamocortical and intracortical laminar connectivity determines sleep spindle properties.

PubMed

Krishnan, Giri P; Rosen, Burke Q; Chen, Jen-Yung; Muller, Lyle; Sejnowski, Terrence J; Cash, Sydney S; Halgren, Eric; Bazhenov, Maxim

2018-06-27

Sleep spindles are brief oscillatory events during non-rapid eye movement (NREM) sleep. Spindle density and synchronization properties are different in MEG versus EEG recordings in humans and also vary with learning performance, suggesting spindle involvement in memory consolidation. Here, using computational models, we identified network mechanisms that may explain differences in spindle properties across cortical structures. First, we report that differences in spindle occurrence between MEG and EEG data may arise from the contrasting properties of the core and matrix thalamocortical systems. The matrix system, projecting superficially, has wider thalamocortical fanout compared to the core system, which projects to middle layers, and requires the recruitment of a larger population of neurons to initiate a spindle. This property was sufficient to explain lower spindle density and higher spatial synchrony of spindles in the superficial cortical layers, as observed in the EEG signal. In contrast, spindles in the core system occurred more frequently but less synchronously, as observed in the MEG recordings. Furthermore, consistent with human recordings, in the model, spindles occurred independently in the core system but the matrix system spindles commonly co-occurred with core spindles. We also found that the intracortical excitatory connections from layer III/IV to layer V promote spindle propagation from the core to the matrix system, leading to widespread spindle activity. Our study predicts that plasticity of intra- and inter-cortical connectivity can potentially be a mechanism for increased spindle density as has been observed during learning.

Genetic structure of cougar populations across the Wyoming basin: Metapopulation or megapopulation

USGS Publications Warehouse

Anderson, C.R.; Lindzey, F.G.; McDonald, D.B.

2004-01-01

We examined the genetic structure of 5 Wyoming cougar (Puma concolor) populations surrounding the Wyoming Basin, as well as a population from southwestern Colorado. When using 9 microsatellite DNA loci, observed heterozygosity was similar among populations (HO = 0.49-0.59) and intermediate to that of other large carnivores. Estimates of genetic structure (FST = 0.028, RST = 0.029) and number of migrants per generation (Nm) suggested high gene flow. Nm was lowest between distant populations and highest among adjacent populations. Examination of these data, plus Mantel test results of genetic versus geographic distance (P ??? 0.01), suggested both isolation by distance and an effect of habitat matrix. Bayesian assignment to population based on individual genotypes showed that cougars in this region were best described as a single panmictic population. Total effective population size for cougars in this region ranged from 1,797 to 4,532 depending on mutation model and analytical method used. Based on measures of gene flow, extinction risk in the near future appears low. We found no support for the existence of metapopulation structure among cougars in this region.

Approaches for the direct estimation of lambda, and demographic contributions to lambda, using capture-recapture data

USGS Publications Warehouse

Nichols, James D.; Hines, James E.

2002-01-01

We first consider the estimation of the finite rate of population increase or population growth rate, u i , using capture-recapture data from open populations. We review estimation and modelling of u i under three main approaches to modelling openpopulation data: the classic approach of Jolly (1965) and Seber (1965), the superpopulation approach of Crosbie & Manly (1985) and Schwarz & Arnason (1996), and the temporal symmetry approach of Pradel (1996). Next, we consider the contributions of different demographic components to u i using a probabilistic approach based on the composition of the population at time i + 1 (Nichols et al., 2000b). The parameters of interest are identical to the seniority parameters, n i , of Pradel (1996). We review estimation of n i under the classic, superpopulation, and temporal symmetry approaches. We then compare these direct estimation approaches for u i and n i with analogues computed using projection matrix asymptotics. We also discuss various extensions of the estimation approaches to multistate applications and to joint likelihoods involving multiple data types.

Population Trend and Elasticities of Vital Rates for Steller Sea Lions (Eumetopias jubatus) in the Eastern Gulf of Alaska: A New Life-History Table Analysis

PubMed Central

Maniscalco, John M.; Springer, Alan M.; Adkison, Milo D.; Parker, Pamela

2015-01-01

Steller sea lion (Eumetopias jubatus) numbers are beginning to recover across most of the western distinct population segment following catastrophic declines that began in the 1970s and ended around the turn of the century. This study makes use of contemporary vital rate estimates from a trend-site rookery in the eastern Gulf of Alaska (a sub-region of the western population) in a matrix population model to estimate the trend and strength of the recovery across this region between 2003 and 2013. The modeled population trend was projected into the future based on observed variation in vital rates and a prospective elasticity analysis was conducted to determine future trends and which vital rates pose the greatest threats to recovery. The modeled population grew at a mean rate of 3.5% per yr between 2003 and 2013 and was correlated with census count data from the local rookery and throughout the eastern Gulf of Alaska. If recent vital rate estimates continue with little change, the eastern Gulf of Alaska population could be fully recovered to pre-decline levels within 23 years. With density dependent growth, the population would need another 45 years to fully recover. Elasticity analysis showed that, as expected, population growth rate (λ) was most sensitive to changes in adult survival, less sensitive to changes in juvenile survival, and least sensitive to changes in fecundity. A population decline could be expected with only a 6% decrease in adult survival, whereas a 32% decrease in fecundity would be necessary to bring about a population decline. These results have important implications for population management and suggest current research priorities should be shifted to a greater emphasis on survival rates and causes of mortality. PMID:26488901

Collagen-coated cellulose sponge: three dimensional matrix for tissue culture of Walker tumor 256.

PubMed

Leighton, J; Justh, G; Esper, M; Kronenthal, R L

1967-03-10

Three-dimensional growth of large populations of cells in vitro has been observed in the interstices of a matrix consisting of collagen-coated cellu lose sponge. The growth of Walker tumor 256 in this composite matrix is com pared with that found in a matrix composed of either cellulose sponge alone or collagen sponge alone. The composite matrix is superior to either one. Collagen coated cellulose sponge may provide a simple tool for the study of social interaction of cells in the formation of organized elementary tissue structures.

Covariance Between Genotypic Effects and its Use for Genomic Inference in Half-Sib Families

PubMed Central

Wittenburg, Dörte; Teuscher, Friedrich; Klosa, Jan; Reinsch, Norbert

2016-01-01

In livestock, current statistical approaches utilize extensive molecular data, e.g., single nucleotide polymorphisms (SNPs), to improve the genetic evaluation of individuals. The number of model parameters increases with the number of SNPs, so the multicollinearity between covariates can affect the results obtained using whole genome regression methods. In this study, dependencies between SNPs due to linkage and linkage disequilibrium among the chromosome segments were explicitly considered in methods used to estimate the effects of SNPs. The population structure affects the extent of such dependencies, so the covariance among SNP genotypes was derived for half-sib families, which are typical in livestock populations. Conditional on the SNP haplotypes of the common parent (sire), the theoretical covariance was determined using the haplotype frequencies of the population from which the individual parent (dam) was derived. The resulting covariance matrix was included in a statistical model for a trait of interest, and this covariance matrix was then used to specify prior assumptions for SNP effects in a Bayesian framework. The approach was applied to one family in simulated scenarios (few and many quantitative trait loci) and using semireal data obtained from dairy cattle to identify genome segments that affect performance traits, as well as to investigate the impact on predictive ability. Compared with a method that does not explicitly consider any of the relationship among predictor variables, the accuracy of genetic value prediction was improved by 10–22%. The results show that the inclusion of dependence is particularly important for genomic inference based on small sample sizes. PMID:27402363

The effect of Fisher information matrix approximation methods in population optimal design calculations.

PubMed

Strömberg, Eric A; Nyberg, Joakim; Hooker, Andrew C

2016-12-01

With the increasing popularity of optimal design in drug development it is important to understand how the approximations and implementations of the Fisher information matrix (FIM) affect the resulting optimal designs. The aim of this work was to investigate the impact on design performance when using two common approximations to the population model and the full or block-diagonal FIM implementations for optimization of sampling points. Sampling schedules for two example experiments based on population models were optimized using the FO and FOCE approximations and the full and block-diagonal FIM implementations. The number of support points was compared between the designs for each example experiment. The performance of these designs based on simulation/estimations was investigated by computing bias of the parameters as well as through the use of an empirical D-criterion confidence interval. Simulations were performed when the design was computed with the true parameter values as well as with misspecified parameter values. The FOCE approximation and the Full FIM implementation yielded designs with more support points and less clustering of sample points than designs optimized with the FO approximation and the block-diagonal implementation. The D-criterion confidence intervals showed no performance differences between the full and block diagonal FIM optimal designs when assuming true parameter values. However, the FO approximated block-reduced FIM designs had higher bias than the other designs. When assuming parameter misspecification in the design evaluation, the FO Full FIM optimal design was superior to the FO block-diagonal FIM design in both of the examples.

Using demography and movement behavior to predict range expansion of the southern sea otter.

USGS Publications Warehouse

Tinker, M.T.; Doak, D.F.; Estes, J.A.

2008-01-01

In addition to forecasting population growth, basic demographic data combined with movement data provide a means for predicting rates of range expansion. Quantitative models of range expansion have rarely been applied to large vertebrates, although such tools could be useful for restoration and management of many threatened but recovering populations. Using the southern sea otter (Enhydra lutris nereis) as a case study, we utilized integro-difference equations in combination with a stage-structured projection matrix that incorporated spatial variation in dispersal and demography to make forecasts of population recovery and range recolonization. In addition to these basic predictions, we emphasize how to make these modeling predictions useful in a management context through the inclusion of parameter uncertainty and sensitivity analysis. Our models resulted in hind-cast (1989–2003) predictions of net population growth and range expansion that closely matched observed patterns. We next made projections of future range expansion and population growth, incorporating uncertainty in all model parameters, and explored the sensitivity of model predictions to variation in spatially explicit survival and dispersal rates. The predicted rate of southward range expansion (median = 5.2 km/yr) was sensitive to both dispersal and survival rates; elasticity analysis indicated that changes in adult survival would have the greatest potential effect on the rate of range expansion, while perturbation analysis showed that variation in subadult dispersal contributed most to variance in model predictions. Variation in survival and dispersal of females at the south end of the range contributed most of the variance in predicted southward range expansion. Our approach provides guidance for the acquisition of further data and a means of forecasting the consequence of specific management actions. Similar methods could aid in the management of other recovering populations.

Comparison on genomic predictions using three GBLUP methods and two single-step blending methods in the Nordic Holstein population

PubMed Central

2012-01-01

Background A single-step blending approach allows genomic prediction using information of genotyped and non-genotyped animals simultaneously. However, the combined relationship matrix in a single-step method may need to be adjusted because marker-based and pedigree-based relationship matrices may not be on the same scale. The same may apply when a GBLUP model includes both genomic breeding values and residual polygenic effects. The objective of this study was to compare single-step blending methods and GBLUP methods with and without adjustment of the genomic relationship matrix for genomic prediction of 16 traits in the Nordic Holstein population. Methods The data consisted of de-regressed proofs (DRP) for 5 214 genotyped and 9 374 non-genotyped bulls. The bulls were divided into a training and a validation population by birth date, October 1, 2001. Five approaches for genomic prediction were used: 1) a simple GBLUP method, 2) a GBLUP method with a polygenic effect, 3) an adjusted GBLUP method with a polygenic effect, 4) a single-step blending method, and 5) an adjusted single-step blending method. In the adjusted GBLUP and single-step methods, the genomic relationship matrix was adjusted for the difference of scale between the genomic and the pedigree relationship matrices. A set of weights on the pedigree relationship matrix (ranging from 0.05 to 0.40) was used to build the combined relationship matrix in the single-step blending method and the GBLUP method with a polygenetic effect. Results Averaged over the 16 traits, reliabilities of genomic breeding values predicted using the GBLUP method with a polygenic effect (relative weight of 0.20) were 0.3% higher than reliabilities from the simple GBLUP method (without a polygenic effect). The adjusted single-step blending and original single-step blending methods (relative weight of 0.20) had average reliabilities that were 2.1% and 1.8% higher than the simple GBLUP method, respectively. In addition, the GBLUP method with a polygenic effect led to less bias of genomic predictions than the simple GBLUP method, and both single-step blending methods yielded less bias of predictions than all GBLUP methods. Conclusions The single-step blending method is an appealing approach for practical genomic prediction in dairy cattle. Genomic prediction from the single-step blending method can be improved by adjusting the scale of the genomic relationship matrix. PMID:22455934

Demographic population model for American shad: will access to additional habitat upstream of dams increase population sizes?

USGS Publications Warehouse

Harris, Julianne E.; Hightower, Joseph E.

2012-01-01

American shad Alosa sapidissima are in decline in their native range, and modeling possible management scenarios could help guide their restoration. We developed a density-dependent, deterministic, stage-based matrix model to predict the population-level results of transporting American shad to suitable spawning habitat upstream of dams on the Roanoke River, North Carolina and Virginia. We used data on sonic-tagged adult American shad and oxytetracycline-marked American shad fry both above and below dams on the Roanoke River with information from other systems to estimate a starting population size and vital rates. We modeled the adult female population over 30 years under plausible scenarios of adult transport, effective fecundity (egg production), and survival of adults (i.e., to return to spawn the next year) and juveniles (from spawned egg to age 1). We also evaluated the potential effects of increased survival for adults and juveniles. The adult female population size in the Roanoke River was estimated to be 5,224. With no transport, the model predicted a slow population increase over the next 30 years. Predicted population increases were highest when survival was improved during the first year of life. Transport was predicted to benefit the population only if high rates of effective fecundity and juvenile survival could be achieved. Currently, transported adults and young are less likely to successfully out-migrate than individuals below the dams, and the estimated adult population size is much smaller than either of two assumed values of carrying capacity for the lower river; therefore, transport is not predicted to help restore the stock under present conditions. Research on survival rates, density-dependent processes, and the impacts of structures to increase out-migration success would improve evaluation of the potential benefits of access to additional spawning habitat for American shad.

Harvesting, predation and competition effects on a red coral population

NASA Astrophysics Data System (ADS)

Abbiati, M.; Buffoni, G.; Caforio, G.; Di Cola, G.; Santangelo, G.

A Corallium rubrum population, dwelling in the Ligurian Sea, has been under observation since 1987. Biometric descriptors of colonies (base diameter, weight, number of polyps, number of growth rings) have been recorded and correlated. The population size structure was obtained by distributing the colonies into diameter classes, each size class representing the average annual increment of diameter growth. The population was divided into ten classes, including a recruitment class. This size structure showed a fairly regular trend in the first four classes. The irregularity of survival in the older classes agreed with field observations on harvesting and predation. Demographic parameters such as survival, growth plasticity and natality coefficients were estimated from the experimental data. On this basis a discrete nonlinear model was implemented. The model is based on a kind of density-dependent Leslie matrix, where the feedback term only occurs in survival of the first class; the recruitment function is assumed to be dependent on the total biomass and related to inhibiting effects due to competitive interactions. Stability analysis was applied to steady-state solutions. Numerical simulations of population evolution were carried out under different conditions. The dynamics of settlement and the effects of disturbances such as harvesting, predation and environmental variability were studied.

Modeling CO2 Storage in Fractured Reservoirs: Fracture-Matrix Interactions of Free-Phase and Dissolved CO2

NASA Astrophysics Data System (ADS)

Oldenburg, C. M.; Zhou, Q.; Birkholzer, J. T.

2017-12-01

The injection of supercritical CO2 (scCO2) in fractured reservoirs has been conducted at several storage sites. However, no site-specific dual-continuum modeling for fractured reservoirs has been reported and modeling studies have generally underestimated the fracture-matrix interactions. We developed a conceptual model for enhanced CO2 storage to take into account global scCO2 migration in the fracture continuum, local storage of scCO2 and dissolved CO2 (dsCO2) in the matrix continuum, and driving forces for scCO2 invasion and dsCO2 diffusion from fractures. High-resolution discrete fracture-matrix models were developed for a column of idealized matrix blocks bounded by vertical and horizontal fractures and for a km-scale fractured reservoir. The column-scale simulation results show that equilibrium storage efficiency strongly depends on matrix entry capillary pressure and matrix-matrix connectivity while the time scale to reach equilibrium is sensitive to fracture spacing and matrix flow properties. The reservoir-scale modeling results shows that the preferential migration of scCO2 through fractures is coupled with bulk storage in the rock matrix that in turn retards the fracture scCO2 plume. We also developed unified-form diffusive flux equations to account for dsCO2 storage in brine-filled matrix blocks and found solubility trapping is significant in fractured reservoirs with low-permeability matrix.

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

Badnell, N. R.; Ballance, C. P.

Modeling the spectral emission of low-charge iron group ions enables the diagnostic determination of the local physical conditions of many cool plasma environments such as those found in H II regions, planetary nebulae, active galactic nuclei, etc. Electron-impact excitation drives the population of the emitting levels and, hence, their emissivities. By carrying-out Breit-Pauli and intermediate coupling frame transformation (ICFT) R-matrix calculations for the electron-impact excitation of Fe{sup 2+}, which both use the exact same atomic structure and the same close-coupling expansion, we demonstrate the validity of the application of the powerful ICFT method to low-charge iron group ions. This ismore » in contradiction to the finding of Bautista et al., who carried-out ICFT and Dirac R-matrix calculations for the same ion. We discuss possible reasons.« less

Functional cartilage repair capacity of de-differentiated, chondrocyte- and mesenchymal stem cell-laden hydrogels in vitro

PubMed Central

Rackwitz, Lars; Djouad, Farida; Janjanin, Sasa; Nöth, Ulrich; Tuan, Rocky S.

2017-01-01

Objective The long-term performance of cell seeded matrix based cartilage constructs depends on (1) the development of sufficient biomechanical properties, and (2) lateral integration with host tissues, both of which require cartilage specific matrix deposition within the scaffold. In this study, we have examined the potential of tissue-engineered cartilage analogs developed using different cell types, i.e., MSCs versus chondrocytes and de-differentiated chondrocytes, in an established “construct in cartilage ring” model. Design Cell-laden constructs of differentiated chondrocytes, de-differentiated chondrocytes after 2, 5 or 8 population doublings, and MSCs were either implanted into a native cartilage ring immediately after fabrication (immature group) or pretreated for 21 days in a transforming growth factor-β3 (TGF-β3) containing medium prior to implantation. After additional culture for 28 days in a serum-free, chemically defined medium, the extent of lateral integration, and biochemical and biomechanical characteristics of the implants as hybrid constructs were assessed. Results The quality of integration, the amount of accumulated cartilage-specific matrix components and associated biomechanical properties were found to be highest when using differentiated chondrocytes. De-differentiation of chondrocytes negatively impacted the properties of the implants, as even two population doublings of the chondrocytes in culture significantly lowered cartilage repair capacity. In contrast, MSCs showed chondrogenic differentiation with TGF-β3 pre-treatment and superior integrational behavior. Conclusions Chondrocyte expansion and de-differentiation impaired the cell response, resulting in inferior cartilage repair in vitro. With TGF-β3 pre-treatment, MSCs were able to undergo sustained chondrogenic differentiation and exhibited superior matrix deposition and integration compared to de-differentiated chondrocytes. PMID:24887551

Efficient Transition Probability Computation for Continuous-Time Branching Processes via Compressed Sensing.

PubMed

Xu, Jason; Minin, Vladimir N

2015-07-01

Branching processes are a class of continuous-time Markov chains (CTMCs) with ubiquitous applications. A general difficulty in statistical inference under partially observed CTMC models arises in computing transition probabilities when the discrete state space is large or uncountable. Classical methods such as matrix exponentiation are infeasible for large or countably infinite state spaces, and sampling-based alternatives are computationally intensive, requiring integration over all possible hidden events. Recent work has successfully applied generating function techniques to computing transition probabilities for linear multi-type branching processes. While these techniques often require significantly fewer computations than matrix exponentiation, they also become prohibitive in applications with large populations. We propose a compressed sensing framework that significantly accelerates the generating function method, decreasing computational cost up to a logarithmic factor by only assuming the probability mass of transitions is sparse. We demonstrate accurate and efficient transition probability computations in branching process models for blood cell formation and evolution of self-replicating transposable elements in bacterial genomes.

Efficient Transition Probability Computation for Continuous-Time Branching Processes via Compressed Sensing

PubMed Central

Xu, Jason; Minin, Vladimir N.

2016-01-01

Branching processes are a class of continuous-time Markov chains (CTMCs) with ubiquitous applications. A general difficulty in statistical inference under partially observed CTMC models arises in computing transition probabilities when the discrete state space is large or uncountable. Classical methods such as matrix exponentiation are infeasible for large or countably infinite state spaces, and sampling-based alternatives are computationally intensive, requiring integration over all possible hidden events. Recent work has successfully applied generating function techniques to computing transition probabilities for linear multi-type branching processes. While these techniques often require significantly fewer computations than matrix exponentiation, they also become prohibitive in applications with large populations. We propose a compressed sensing framework that significantly accelerates the generating function method, decreasing computational cost up to a logarithmic factor by only assuming the probability mass of transitions is sparse. We demonstrate accurate and efficient transition probability computations in branching process models for blood cell formation and evolution of self-replicating transposable elements in bacterial genomes. PMID:26949377

Calculating second derivatives of population growth rates for ecology and evolution

PubMed Central

Shyu, Esther; Caswell, Hal

2014-01-01

1. Second derivatives of the population growth rate measure the curvature of its response to demographic, physiological or environmental parameters. The second derivatives quantify the response of sensitivity results to perturbations, provide a classification of types of selection and provide one way to calculate sensitivities of the stochastic growth rate. 2. Using matrix calculus, we derive the second derivatives of three population growth rate measures: the discrete-time growth rate λ, the continuous-time growth rate r = log λ and the net reproductive rate R0, which measures per-generation growth. 3. We present a suite of formulae for the second derivatives of each growth rate and show how to compute these derivatives with respect to projection matrix entries and to lower-level parameters affecting those matrix entries. 4. We also illustrate several ecological and evolutionary applications for these second derivative calculations with a case study for the tropical herb Calathea ovandensis. PMID:25793101

Forecasting the mortality rates using Lee-Carter model and Heligman-Pollard model

NASA Astrophysics Data System (ADS)

Ibrahim, R. I.; Ngataman, N.; Abrisam, W. N. A. Wan Mohd

2017-09-01

Improvement in life expectancies has driven further declines in mortality. The sustained reduction in mortality rates and its systematic underestimation has been attracting the significant interest of researchers in recent years because of its potential impact on population size and structure, social security systems, and (from an actuarial perspective) the life insurance and pensions industry worldwide. Among all forecasting methods, the Lee-Carter model has been widely accepted by the actuarial community and Heligman-Pollard model has been widely used by researchers in modelling and forecasting future mortality. Therefore, this paper only focuses on Lee-Carter model and Heligman-Pollard model. The main objective of this paper is to investigate how accurately these two models will perform using Malaysian data. Since these models involves nonlinear equations that are explicitly difficult to solve, the Matrix Laboratory Version 8.0 (MATLAB 8.0) software will be used to estimate the parameters of the models. Autoregressive Integrated Moving Average (ARIMA) procedure is applied to acquire the forecasted parameters for both models as the forecasted mortality rates are obtained by using all the values of forecasted parameters. To investigate the accuracy of the estimation, the forecasted results will be compared against actual data of mortality rates. The results indicate that both models provide better results for male population. However, for the elderly female population, Heligman-Pollard model seems to underestimate to the mortality rates while Lee-Carter model seems to overestimate to the mortality rates.

Calculating Path-Dependent Travel Time Prediction Variance and Covariance fro a Global Tomographic P-Velocity Model

NASA Astrophysics Data System (ADS)

Ballard, S.; Hipp, J. R.; Encarnacao, A.; Young, C. J.; Begnaud, M. L.; Phillips, W. S.

2012-12-01

Seismic event locations can be made more accurate and precise by computing predictions of seismic travel time through high fidelity 3D models of the wave speed in the Earth's interior. Given the variable data quality and uneven data sampling associated with this type of model, it is essential that there be a means to calculate high-quality estimates of the path-dependent variance and covariance associated with the predicted travel times of ray paths through the model. In this paper, we describe a methodology for accomplishing this by exploiting the full model covariance matrix and show examples of path-dependent travel time prediction uncertainty computed from SALSA3D, our global, seamless 3D tomographic P-velocity model. Typical global 3D models have on the order of 1/2 million nodes, so the challenge in calculating the covariance matrix is formidable: 0.9 TB storage for 1/2 of a symmetric matrix, necessitating an Out-Of-Core (OOC) blocked matrix solution technique. With our approach the tomography matrix (G which includes Tikhonov regularization terms) is multiplied by its transpose (GTG) and written in a blocked sub-matrix fashion. We employ a distributed parallel solution paradigm that solves for (GTG)-1 by assigning blocks to individual processing nodes for matrix decomposition update and scaling operations. We first find the Cholesky decomposition of GTG which is subsequently inverted. Next, we employ OOC matrix multiplication methods to calculate the model covariance matrix from (GTG)-1 and an assumed data covariance matrix. Given the model covariance matrix, we solve for the travel-time covariance associated with arbitrary ray-paths by summing the model covariance along both ray paths. Setting the paths equal and taking the square root yields the travel prediction uncertainty for the single path.

Modeling the role of quorum sensing in interspecies competition in biofilms

NASA Astrophysics Data System (ADS)

Narla, Avaneesh V.; Wingreen, Ned S.; Borenstein, David B.

Bacteria grow on surfaces in complex immobile communities known as biofilms, composed of cells embedded in an extracellular matrix. Within biofilms, bacteria often communicate, cooperate, and compete within their own species and with other species using Quorum Sensing (QS). QS refers to the process by which bacteria produce, secrete, and subsequently detect small molecules called autoinducers as a way to assess the local population density of their species, or of other species. QS is known to regulate the production of extracellular matrix. We investigated the possible benefit of QS in regulating matrix production to best gain access to a nutrient that diffuses from a source positioned away from the surface on which the biofilm grows. We employed Agent-Based Modeling (ABM), a form of simulation that allows cells to modify their behavior based on local inputs, e.g. nutrient and QS concentrations. We first determined the optimal fixed strategies (that do not use QS) for pairwise competitions, and then demonstrated that simple QS-based strategies can be superior to any fixed strategy. In nature, species can compete by sensing and/or interfering with each other's QS signals, and we explore approaches for targeting specific species via QS-interference. A.V.N. and N.S.W. contributed equally to this project.

Design of UV laser pulses for the preparation of matrix isolated homonuclear diatomic molecules in selective vibrational superposition states.

PubMed

Korolkov, M V; Manz, J

2007-05-07

The preparation of matrix isolated homonuclear diatomic molecules in a vibrational superposition state c0Phie=1,v=0+cjPhie=1,v=j, with large (|c0|2 approximately 1) plus small contributions (|cj|2<1) of the ground v=0 and specific v=j low excited vibrational eigenstates, respectively, in the electronic ground (e=1) state, and without any net population transfer to electronic excited (e>1) states, is an important challenge; it serves as a prerequisite for coherent spin control. For this purpose, the authors investigate two scenarios of laser pulse control, involving sequential or intrapulse pump- and dump-type transitions via excited vibronic states Phiex,k with a dominant singlet or triplet character. The mechanisms are demonstrated by means of quantum simulations for representative nuclear wave packets on coupled potential energy surfaces, using as an example a one-dimensional model for Cl2 in an Ar matrix. A simple three-state model (including Phi1,0, Phi1,j and Phiex,k) allows illuminating analyses and efficient determinations of the parameters of the laser pulses based on the values of the transition energies and dipole couplings of the transient state which are derived from the absorption spectra.

Effects of stand age on the demography of a temperate forest herb in post-agricultural forests.

PubMed

Jacquemyn, Hans; Brys, Rein

2008-12-01

Changes in land use have been shown to have profound effects on forest plant community structure and diversity. Dispersal limitation has been invoked as a major factor hampering colonization of forest plant species, while seed-sowing experiments and performance observations have provided some evidence for recruitment limitation determining forest plant distribution in post-agricultural forests. However, most of these studies were relatively short-term, and very few studies have investigated long-term growth rates of populations occurring in recent and ancient forests. In this study, matrix models using demographic data collected for four consecutive years were used to study the effect of forest age on population dynamics of the temperate forest herb Primula elatior. A life table response experiment (LTRE) and elasticity analysis were used to analyze the effect of forest age on population growth rate (lambda) and to decompose the effect of forest age on lambda into contributions from each matrix element. Population growth increased logarithmically with increasing forest age. Bootstrap analyses showed that populations located in very recent forests (< 50-years-old) had growth rates that were significantly < 1, whereas populations located in forests > 150-years-old had growth rates that were significantly > 1. Summed elasticities for individual growth significantly decreased with increasing forest age, whereas summed elasticities for survival and fertility significantly increased with increasing forest age. The LTRE analysis showed that the increase in lambda with increasing forest age was mainly due to increased seedling and juvenile growth and increased juvenile and adult survival. Our results indicate that past agricultural land use has long-lasting effects on the demography of forest herbs and may provide an additional mechanistic explanation for the poor colonization capacity of many forest herbs in post-agricultural forests.

Synergistic Effects of Temperature and Oxidation on Matrix Cracking in Fiber-Reinforced Ceramic-Matrix Composites

NASA Astrophysics Data System (ADS)

Longbiao, Li

2017-06-01

In this paper, the synergistic effects of temperatrue and oxidation on matrix cracking in fiber-reinforced ceramic-matrix composites (CMCs) has been investigated using energy balance approach. The shear-lag model cooperated with damage models, i.e., the interface oxidation model, interface debonding model, fiber strength degradation model and fiber failure model, has been adopted to analyze microstress field in the composite. The relationships between matrix cracking stress, interface debonding and slipping, fiber fracture, oxidation temperatures and time have been established. The effects of fiber volume fraction, interface properties, fiber strength and oxidation temperatures on the evolution of matrix cracking stress versus oxidation time have been analyzed. The matrix cracking stresses of C/SiC composite with strong and weak interface bonding after unstressed oxidation at an elevated temperature of 700 °C in air condition have been predicted for different oxidation time.

The use of type 1 collagen scaffold containing stromal cell-derived factor-1 to create a matrix environment conducive to partial-thickness cartilage defects repair.

PubMed

Zhang, Wei; Chen, Jialin; Tao, Jiadong; Jiang, Yangzi; Hu, Changchang; Huang, Lu; Ji, Junfeng; Ouyang, Hong Wei

2013-01-01

Despite the presence of cartilage-derived mesenchymal stem cells (C-MSCs) and synovial membrane-derived mesenchymal stem cells (SM-MSCs) populations, partial-thickness cartilage defects, in contrast to the full-thickness defects, are devoid of spontaneous repair capacity. This study aims to create an in situ matrix environment conducive to C-MSCs and SM-MSCs to promote cartilage self-repair. Spontaneous repair with MSCs migration into the defect area was observed in full-thickness defects, but not in partial-thickness defects in rabbit model. Ex vivo and in vitro studies showed that subchondral bone or type 1 collagen (col1) scaffold was more permissive for MSCs adhesion than cartilage or type 2 collagen (col2) scaffold and induced robust stromal cell-derived factors-1 (SDF-1) dependent migration of MSCs. Furthermore, creating a matrix environment with col1 scaffold containing SDF-1 enhanced in situ self-repair of partial-thickness defects in rabbit 6 weeks post-injury. Hence, the inferior self-repair capacity in partial-thickness defects is partially owing to the non-permissive matrix environment. Creating an in situ matrix environment conducive to C-MSCs and SM-MSCs migration and adhesion with col1 scaffold containing SDF-1 can be exploited to improve self-repair capacity of cartilage. Copyright © 2012 Elsevier Ltd. All rights reserved.

Population structure and strong divergent selection shape phenotypic diversification in maize landraces.

PubMed

Pressoir, G; Berthaud, J

2004-02-01

To conserve the long-term selection potential of maize, it is necessary to investigate past and present evolutionary processes that have shaped quantitative trait variation. Understanding the dynamics of quantitative trait evolution is crucial to future crop breeding. We characterized population differentiation of maize landraces from the State of Oaxaca, Mexico for quantitative traits and molecular markers. Qst values were much higher than Fst values obtained for molecular markers. While low values of Fst (0.011 within-village and 0.003 among-villages) suggest that considerable gene flow occurred among the studied populations, high levels of population differentiation for quantitative traits were observed (ie an among-village Qst value of 0.535 for kernel weight). Our results suggest that although quantitative traits appear to be under strong divergent selection, a considerable amount of gene flow occurs among populations. Furthermore, we characterized nonproportional changes in the G matrix structure both within and among villages that are consequences of farmer selection. As a consequence of these differences in the G matrix structure, the response to multivariate selection will be different from one population to another. Large changes in the G matrix structure could indicate that farmers select for genes of major and pleiotropic effect. Farmers' decision and selection strategies have a great impact on phenotypic diversification in maize landraces.

Global solutions to a class of multi-species reaction-diffusion systems with cross-diffusions arising in population dynamics

NASA Astrophysics Data System (ADS)

Wen, Zijuan; Fu, Shengmao

2009-08-01

In this paper, an n-species strongly coupled cooperating diffusive system is considered in a bounded smooth domain, subject to homogeneous Neumann boundary conditions. Employing the method of energy estimates, we obtain some conditions on the diffusion matrix and inter-specific cooperatives to ensure the global existence and uniform boundedness of a nonnegative solution. The globally asymptotical stability of the constant positive steady state is also discussed. As a consequence, all the results hold true for multi-species Lotka-Volterra type competition model and prey-predator model.

High Strain Rate Deformation Modeling of a Polymer Matrix Composite. Part 1; Matrix Constitutive Equations

NASA Technical Reports Server (NTRS)

Goldberg, Robert K.; Stouffer, Donald C.

1998-01-01

Recently applications have exposed polymer matrix composite materials to very high strain rate loading conditions, requiring an ability to understand and predict the material behavior under these extreme conditions. In this first paper of a two part report, background information is presented, along with the constitutive equations which will be used to model the rate dependent nonlinear deformation response of the polymer matrix. Strain rate dependent inelastic constitutive models which were originally developed to model the viscoplastic deformation of metals have been adapted to model the nonlinear viscoelastic deformation of polymers. The modified equations were correlated by analyzing the tensile/ compressive response of both 977-2 toughened epoxy matrix and PEEK thermoplastic matrix over a variety of strain rates. For the cases examined, the modified constitutive equations appear to do an adequate job of modeling the polymer deformation response. A second follow-up paper will describe the implementation of the polymer deformation model into a composite micromechanical model, to allow for the modeling of the nonlinear, rate dependent deformation response of polymer matrix composites.

EvolQG - An R package for evolutionary quantitative genetics

PubMed Central

Melo, Diogo; Garcia, Guilherme; Hubbe, Alex; Assis, Ana Paula; Marroig, Gabriel

2016-01-01

We present an open source package for performing evolutionary quantitative genetics analyses in the R environment for statistical computing. Evolutionary theory shows that evolution depends critically on the available variation in a given population. When dealing with many quantitative traits this variation is expressed in the form of a covariance matrix, particularly the additive genetic covariance matrix or sometimes the phenotypic matrix, when the genetic matrix is unavailable and there is evidence the phenotypic matrix is sufficiently similar to the genetic matrix. Given this mathematical representation of available variation, the \\textbf{EvolQG} package provides functions for calculation of relevant evolutionary statistics; estimation of sampling error; corrections for this error; matrix comparison via correlations, distances and matrix decomposition; analysis of modularity patterns; and functions for testing evolutionary hypotheses on taxa diversification. PMID:27785352

Estimating Allee dynamics before they can be observed: polar bears as a case study.

PubMed

Molnár, Péter K; Lewis, Mark A; Derocher, Andrew E

2014-01-01

Allee effects are an important component in the population dynamics of numerous species. Accounting for these Allee effects in population viability analyses generally requires estimates of low-density population growth rates, but such data are unavailable for most species and particularly difficult to obtain for large mammals. Here, we present a mechanistic modeling framework that allows estimating the expected low-density growth rates under a mate-finding Allee effect before the Allee effect occurs or can be observed. The approach relies on representing the mechanisms causing the Allee effect in a process-based model, which can be parameterized and validated from data on the mechanisms rather than data on population growth. We illustrate the approach using polar bears (Ursus maritimus), and estimate their expected low-density growth by linking a mating dynamics model to a matrix projection model. The Allee threshold, defined as the population density below which growth becomes negative, is shown to depend on age-structure, sex ratio, and the life history parameters determining reproduction and survival. The Allee threshold is thus both density- and frequency-dependent. Sensitivity analyses of the Allee threshold show that different combinations of the parameters determining reproduction and survival can lead to differing Allee thresholds, even if these differing combinations imply the same stable-stage population growth rate. The approach further shows how mate-limitation can induce long transient dynamics, even in populations that eventually grow to carrying capacity. Applying the models to the overharvested low-density polar bear population of Viscount Melville Sound, Canada, shows that a mate-finding Allee effect is a plausible mechanism for slow recovery of this population. Our approach is generalizable to any mating system and life cycle, and could aid proactive management and conservation strategies, for example, by providing a priori estimates of minimum conservation targets for rare species or minimum eradication targets for pests and invasive species.

Estimating Allee Dynamics before They Can Be Observed: Polar Bears as a Case Study

PubMed Central

Molnár, Péter K.; Lewis, Mark A.; Derocher, Andrew E.

2014-01-01

Allee effects are an important component in the population dynamics of numerous species. Accounting for these Allee effects in population viability analyses generally requires estimates of low-density population growth rates, but such data are unavailable for most species and particularly difficult to obtain for large mammals. Here, we present a mechanistic modeling framework that allows estimating the expected low-density growth rates under a mate-finding Allee effect before the Allee effect occurs or can be observed. The approach relies on representing the mechanisms causing the Allee effect in a process-based model, which can be parameterized and validated from data on the mechanisms rather than data on population growth. We illustrate the approach using polar bears (Ursus maritimus), and estimate their expected low-density growth by linking a mating dynamics model to a matrix projection model. The Allee threshold, defined as the population density below which growth becomes negative, is shown to depend on age-structure, sex ratio, and the life history parameters determining reproduction and survival. The Allee threshold is thus both density- and frequency-dependent. Sensitivity analyses of the Allee threshold show that different combinations of the parameters determining reproduction and survival can lead to differing Allee thresholds, even if these differing combinations imply the same stable-stage population growth rate. The approach further shows how mate-limitation can induce long transient dynamics, even in populations that eventually grow to carrying capacity. Applying the models to the overharvested low-density polar bear population of Viscount Melville Sound, Canada, shows that a mate-finding Allee effect is a plausible mechanism for slow recovery of this population. Our approach is generalizable to any mating system and life cycle, and could aid proactive management and conservation strategies, for example, by providing a priori estimates of minimum conservation targets for rare species or minimum eradication targets for pests and invasive species. PMID:24427306

Modelling interactions of toxicants and density dependence in wildlife populations

USGS Publications Warehouse

Schipper, Aafke M.; Hendriks, Harrie W.M.; Kauffman, Matthew J.; Hendriks, A. Jan; Huijbregts, Mark A.J.

2013-01-01

1. A major challenge in the conservation of threatened and endangered species is to predict population decline and design appropriate recovery measures. However, anthropogenic impacts on wildlife populations are notoriously difficult to predict due to potentially nonlinear responses and interactions with natural ecological processes like density dependence. 2. Here, we incorporated both density dependence and anthropogenic stressors in a stage-based matrix population model and parameterized it for a density-dependent population of peregrine falcons Falco peregrinus exposed to two anthropogenic toxicants [dichlorodiphenyldichloroethylene (DDE) and polybrominated diphenyl ethers (PBDEs)]. Log-logistic exposure–response relationships were used to translate toxicant concentrations in peregrine falcon eggs to effects on fecundity. Density dependence was modelled as the probability of a nonbreeding bird acquiring a breeding territory as a function of the current number of breeders. 3. The equilibrium size of the population, as represented by the number of breeders, responded nonlinearly to increasing toxicant concentrations, showing a gradual decrease followed by a relatively steep decline. Initially, toxicant-induced reductions in population size were mitigated by an alleviation of the density limitation, that is, an increasing probability of territory acquisition. Once population density was no longer limiting, the toxicant impacts were no longer buffered by an increasing proportion of nonbreeders shifting to the breeding stage, resulting in a strong decrease in the equilibrium number of breeders. 4. Median critical exposure concentrations, that is, median toxicant concentrations in eggs corresponding with an equilibrium population size of zero, were 33 and 46 μg g−1 fresh weight for DDE and PBDEs, respectively. 5. Synthesis and applications. Our modelling results showed that particular life stages of a density-limited population may be relatively insensitive to toxicant impacts until a critical threshold is crossed. In our study population, toxicant-induced changes were observed in the equilibrium number of nonbreeding rather than breeding birds, suggesting that monitoring efforts including both life stages are needed to timely detect population declines. Further, by combining quantitative exposure–response relationships with a wildlife demographic model, we provided a method to quantify critical toxicant thresholds for wildlife population persistence.

Changes in seasonal climate outpace compensatory density-dependence in eastern brook trout

USGS Publications Warehouse

Bassar, Ronald D.; Letcher, Benjamin H.; Nislow, Keith H.; Whiteley, Andrew R.

2016-01-01

Understanding how multiple extrinsic (density-independent) factors and intrinsic (density-dependent) mechanisms influence population dynamics has become increasingly urgent in the face of rapidly changing climates. It is particularly unclear how multiple extrinsic factors with contrasting effects among seasons are related to declines in population numbers and changes in mean body size and whether there is a strong role for density-dependence. The primary goal of this study was to identify the roles of seasonal variation in climate driven environmental direct effects (mean stream flow and temperature) versus density-dependence on population size and mean body size in eastern brook trout (Salvelinus fontinalis). We use data from a 10-year capture-mark-recapture study of eastern brook trout in four streams in Western Massachusetts, USA to parameterize a discrete-time population projection model. The model integrates matrix modeling techniques used to characterize discrete population structures (age, habitat type and season) with integral projection models (IPMs) that characterize demographic rates as continuous functions of organismal traits (in this case body size). Using both stochastic and deterministic analyses we show that decreases in population size are due to changes in stream flow and temperature and that these changes are larger than what can be compensated for through density-dependent responses. We also show that the declines are due mostly to increasing mean stream temperatures decreasing the survival of the youngest age class. In contrast, increases in mean body size over the same period are the result of indirect changes in density with a lesser direct role of climate-driven environmental change.

Anthropogenic Habitats Facilitate Dispersal of an Early Successional Obligate: Implications for Restoration of an Endangered Ecosystem.

PubMed

Amaral, Katrina E; Palace, Michael; O'Brien, Kathleen M; Fenderson, Lindsey E; Kovach, Adrienne I

2016-01-01

Landscape modification and habitat fragmentation disrupt the connectivity of natural landscapes, with major consequences for biodiversity. Species that require patchily distributed habitats, such as those that specialize on early successional ecosystems, must disperse through a landscape matrix with unsuitable habitat types. We evaluated landscape effects on dispersal of an early successional obligate, the New England cottontail (Sylvilagus transitionalis). Using a landscape genetics approach, we identified barriers and facilitators of gene flow and connectivity corridors for a population of cottontails in the northeastern United States. We modeled dispersal in relation to landscape structure and composition and tested hypotheses about the influence of habitat fragmentation on gene flow. Anthropogenic and natural shrubland habitats facilitated gene flow, while the remainder of the matrix, particularly development and forest, impeded gene flow. The relative influence of matrix habitats differed between study areas in relation to a fragmentation gradient. Barrier features had higher explanatory power in the more fragmented site, while facilitating features were important in the less fragmented site. Landscape models that included a simultaneous barrier and facilitating effect of roads had higher explanatory power than models that considered either effect separately, supporting the hypothesis that roads act as both barriers and facilitators at all spatial scales. The inclusion of LiDAR-identified shrubland habitat improved the fit of our facilitator models. Corridor analyses using circuit and least cost path approaches revealed the importance of anthropogenic, linear features for restoring connectivity between the study areas. In fragmented landscapes, human-modified habitats may enhance functional connectivity by providing suitable dispersal conduits for early successional specialists.

Anthropogenic Habitats Facilitate Dispersal of an Early Successional Obligate: Implications for Restoration of an Endangered Ecosystem

PubMed Central

Amaral, Katrina E.; Palace, Michael; O’Brien, Kathleen M.; Fenderson, Lindsey E.; Kovach, Adrienne I.

2016-01-01

Landscape modification and habitat fragmentation disrupt the connectivity of natural landscapes, with major consequences for biodiversity. Species that require patchily distributed habitats, such as those that specialize on early successional ecosystems, must disperse through a landscape matrix with unsuitable habitat types. We evaluated landscape effects on dispersal of an early successional obligate, the New England cottontail (Sylvilagus transitionalis). Using a landscape genetics approach, we identified barriers and facilitators of gene flow and connectivity corridors for a population of cottontails in the northeastern United States. We modeled dispersal in relation to landscape structure and composition and tested hypotheses about the influence of habitat fragmentation on gene flow. Anthropogenic and natural shrubland habitats facilitated gene flow, while the remainder of the matrix, particularly development and forest, impeded gene flow. The relative influence of matrix habitats differed between study areas in relation to a fragmentation gradient. Barrier features had higher explanatory power in the more fragmented site, while facilitating features were important in the less fragmented site. Landscape models that included a simultaneous barrier and facilitating effect of roads had higher explanatory power than models that considered either effect separately, supporting the hypothesis that roads act as both barriers and facilitators at all spatial scales. The inclusion of LiDAR-identified shrubland habitat improved the fit of our facilitator models. Corridor analyses using circuit and least cost path approaches revealed the importance of anthropogenic, linear features for restoring connectivity between the study areas. In fragmented landscapes, human-modified habitats may enhance functional connectivity by providing suitable dispersal conduits for early successional specialists. PMID:26954014

Convergence of Transition Probability Matrix in CLVMarkov Models

NASA Astrophysics Data System (ADS)

Permana, D.; Pasaribu, U. S.; Indratno, S. W.; Suprayogi, S.

2018-04-01

A transition probability matrix is an arrangement of transition probability from one states to another in a Markov chain model (MCM). One of interesting study on the MCM is its behavior for a long time in the future. The behavior is derived from one property of transition probabilty matrix for n steps. This term is called the convergence of the n-step transition matrix for n move to infinity. Mathematically, the convergence of the transition probability matrix is finding the limit of the transition matrix which is powered by n where n moves to infinity. The convergence form of the transition probability matrix is very interesting as it will bring the matrix to its stationary form. This form is useful for predicting the probability of transitions between states in the future. The method usually used to find the convergence of transition probability matrix is through the process of limiting the distribution. In this paper, the convergence of the transition probability matrix is searched using a simple concept of linear algebra that is by diagonalizing the matrix.This method has a higher level of complexity because it has to perform the process of diagonalization in its matrix. But this way has the advantage of obtaining a common form of power n of the transition probability matrix. This form is useful to see transition matrix before stationary. For example cases are taken from CLV model using MCM called Model of CLV-Markov. There are several models taken by its transition probability matrix to find its convergence form. The result is that the convergence of the matrix of transition probability through diagonalization has similarity with convergence with commonly used distribution of probability limiting method.

Paracrine signaling in a bacterium.

PubMed

López, Daniel; Vlamakis, Hera; Losick, Richard; Kolter, Roberto

2009-07-15

Cellular differentiation is triggered by extracellular signals that cause target cells to adopt a particular fate. Differentiation in bacteria typically involves autocrine signaling in which all cells in the population produce and respond to the same signal. Here we present evidence for paracrine signaling in bacterial populations-some cells produce a signal to which only certain target cells respond. Biofilm formation in Bacillus involves two centrally important signaling molecules, ComX and surfactin. ComX triggers the production of surfactin. In turn, surfactin causes a subpopulation of cells to produce an extracellular matrix. Cells that produced surfactin were themselves unable to respond to it. Likewise, once surfactin-responsive cells commenced matrix production, they no longer responded to ComX and could not become surfactin producers. Insensitivity to ComX was the consequence of the extracellular matrix as mutant cells unable to make matrix responded to both ComX and surfactin. Our results demonstrate that extracellular signaling was unidirectional, with one subpopulation producing a signal and a different subpopulation responding to it. Paracrine signaling in a bacterial population ensures the maintenance, over generations, of particular cell types even in the presence of molecules that would otherwise cause those cells to differentiate into other cell types.

Path-Dependent Travel Time Prediction Variance and Covariance for a Global Tomographic P- and S-Velocity Model

NASA Astrophysics Data System (ADS)

Hipp, J. R.; Ballard, S.; Begnaud, M. L.; Encarnacao, A. V.; Young, C. J.; Phillips, W. S.

2015-12-01

Recently our combined SNL-LANL research team has succeeded in developing a global, seamless 3D tomographic P- and S-velocity model (SALSA3D) that provides superior first P and first S travel time predictions at both regional and teleseismic distances. However, given the variable data quality and uneven data sampling associated with this type of model, it is essential that there be a means to calculate high-quality estimates of the path-dependent variance and covariance associated with the predicted travel times of ray paths through the model. In this paper, we describe a methodology for accomplishing this by exploiting the full model covariance matrix and show examples of path-dependent travel time prediction uncertainty computed from our latest tomographic model. Typical global 3D SALSA3D models have on the order of 1/2 million nodes, so the challenge in calculating the covariance matrix is formidable: 0.9 TB storage for 1/2 of a symmetric matrix, necessitating an Out-Of-Core (OOC) blocked matrix solution technique. With our approach the tomography matrix (G which includes a prior model covariance constraint) is multiplied by its transpose (GTG) and written in a blocked sub-matrix fashion. We employ a distributed parallel solution paradigm that solves for (GTG)-1 by assigning blocks to individual processing nodes for matrix decomposition update and scaling operations. We first find the Cholesky decomposition of GTG which is subsequently inverted. Next, we employ OOC matrix multiplication methods to calculate the model covariance matrix from (GTG)-1 and an assumed data covariance matrix. Given the model covariance matrix, we solve for the travel-time covariance associated with arbitrary ray-paths by summing the model covariance along both ray paths. Setting the paths equal and taking the square root yields the travel prediction uncertainty for the single path.

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.

Geographically weighted regression model on poverty indicator

NASA Astrophysics Data System (ADS)

Slamet, I.; Nugroho, N. F. T. A.; Muslich

2017-12-01

In this research, we applied geographically weighted regression (GWR) for analyzing the poverty in Central Java. We consider Gaussian Kernel as weighted function. The GWR uses the diagonal matrix resulted from calculating kernel Gaussian function as a weighted function in the regression model. The kernel weights is used to handle spatial effects on the data so that a model can be obtained for each location. The purpose of this paper is to model of poverty percentage data in Central Java province using GWR with Gaussian kernel weighted function and to determine the influencing factors in each regency/city in Central Java province. Based on the research, we obtained geographically weighted regression model with Gaussian kernel weighted function on poverty percentage data in Central Java province. We found that percentage of population working as farmers, population growth rate, percentage of households with regular sanitation, and BPJS beneficiaries are the variables that affect the percentage of poverty in Central Java province. In this research, we found the determination coefficient R2 are 68.64%. There are two categories of district which are influenced by different of significance factors.

And the first one now will later be last: Time-reversal in cormack-jolly-seber models

USGS Publications Warehouse

Nichols, James D.

2016-01-01

The models of Cormack, Jolly and Seber (CJS) are remarkable in providing a rich set of inferences about population survival, recruitment, abundance and even sampling probabilities from a seemingly limited data source: a matrix of 1's and 0's reflecting animal captures and recaptures at multiple sampling occasions. Survival and sampling probabilities are estimated directly in CJS models, whereas estimators for recruitment and abundance were initially obtained as derived quantities. Various investigators have noted that just as standard modeling provides direct inferences about survival, reversing the time order of capture history data permits direct modeling and inference about recruitment. Here we review the development of reverse-time modeling efforts, emphasizing the kinds of inferences and questions to which they seem well suited.

Model reduction of nonsquare linear MIMO systems using multipoint matrix continued-fraction expansions

NASA Technical Reports Server (NTRS)

Guo, Tong-Yi; Hwang, Chyi; Shieh, Leang-San

1994-01-01

This paper deals with the multipoint Cauer matrix continued-fraction expansion (MCFE) for model reduction of linear multi-input multi-output (MIMO) systems with various numbers of inputs and outputs. A salient feature of the proposed MCFE approach to model reduction of MIMO systems with square transfer matrices is its equivalence to the matrix Pade approximation approach. The Cauer second form of the ordinary MCFE for a square transfer function matrix is generalized in this paper to a multipoint and nonsquare-matrix version. An interesting connection of the multipoint Cauer MCFE method to the multipoint matrix Pade approximation method is established. Also, algorithms for obtaining the reduced-degree matrix-fraction descriptions and reduced-dimensional state-space models from a transfer function matrix via the multipoint Cauer MCFE algorithm are presented. Practical advantages of using the multipoint Cauer MCFE are discussed and a numerical example is provided to illustrate the algorithms.

A stochastic Markov chain model to describe lung cancer growth and metastasis.

PubMed

Newton, Paul K; Mason, Jeremy; Bethel, Kelly; Bazhenova, Lyudmila A; Nieva, Jorge; Kuhn, Peter

2012-01-01

A stochastic Markov chain model for metastatic progression is developed for primary lung cancer based on a network construction of metastatic sites with dynamics modeled as an ensemble of random walkers on the network. We calculate a transition matrix, with entries (transition probabilities) interpreted as random variables, and use it to construct a circular bi-directional network of primary and metastatic locations based on postmortem tissue analysis of 3827 autopsies on untreated patients documenting all primary tumor locations and metastatic sites from this population. The resulting 50 potential metastatic sites are connected by directed edges with distributed weightings, where the site connections and weightings are obtained by calculating the entries of an ensemble of transition matrices so that the steady-state distribution obtained from the long-time limit of the Markov chain dynamical system corresponds to the ensemble metastatic distribution obtained from the autopsy data set. We condition our search for a transition matrix on an initial distribution of metastatic tumors obtained from the data set. Through an iterative numerical search procedure, we adjust the entries of a sequence of approximations until a transition matrix with the correct steady-state is found (up to a numerical threshold). Since this constrained linear optimization problem is underdetermined, we characterize the statistical variance of the ensemble of transition matrices calculated using the means and variances of their singular value distributions as a diagnostic tool. We interpret the ensemble averaged transition probabilities as (approximately) normally distributed random variables. The model allows us to simulate and quantify disease progression pathways and timescales of progression from the lung position to other sites and we highlight several key findings based on the model.

Joint genome-wide prediction in several populations accounting for randomness of genotypes: A hierarchical Bayes approach. I: Multivariate Gaussian priors for marker effects and derivation of the joint probability mass function of genotypes.

PubMed

Martínez, Carlos Alberto; Khare, Kshitij; Banerjee, Arunava; Elzo, Mauricio A

2017-03-21

It is important to consider heterogeneity of marker effects and allelic frequencies in across population genome-wide prediction studies. Moreover, all regression models used in genome-wide prediction overlook randomness of genotypes. In this study, a family of hierarchical Bayesian models to perform across population genome-wide prediction modeling genotypes as random variables and allowing population-specific effects for each marker was developed. Models shared a common structure and differed in the priors used and the assumption about residual variances (homogeneous or heterogeneous). Randomness of genotypes was accounted for by deriving the joint probability mass function of marker genotypes conditional on allelic frequencies and pedigree information. As a consequence, these models incorporated kinship and genotypic information that not only permitted to account for heterogeneity of allelic frequencies, but also to include individuals with missing genotypes at some or all loci without the need for previous imputation. This was possible because the non-observed fraction of the design matrix was treated as an unknown model parameter. For each model, a simpler version ignoring population structure, but still accounting for randomness of genotypes was proposed. Implementation of these models and computation of some criteria for model comparison were illustrated using two simulated datasets. Theoretical and computational issues along with possible applications, extensions and refinements were discussed. Some features of the models developed in this study make them promising for genome-wide prediction, the use of information contained in the probability distribution of genotypes is perhaps the most appealing. Further studies to assess the performance of the models proposed here and also to compare them with conventional models used in genome-wide prediction are needed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Predicting geographically distributed adult dental decay in the greater Auckland region of New Zealand.

PubMed

Rocha, C M; Kruger, E; Whyman, R; Tennant, M

2014-06-01

To model the geographic distribution of current (and treated) dental decay on a high-resolution geographic basis for the Auckland region of New Zealand. The application of matrix-based mathematics to modelling adult dental disease-based on known population risk profiles to provide a detailed map of the dental caries distribution for the greater Auckland region. Of the 29 million teeth in adults in the region some 1.2 million (4%) are suffering decay whilst 7.2 million (25%) have previously suffered decay and are now restored. The model provides a high-resolution picture of where the disease burden lies geographically and presents to health planners a method for developing future service plans.

Relative Contribution of Matrix Structure, Patch Resources and Management to the Local Densities of Two Large Blue Butterfly Species

PubMed Central

Skórka, Piotr; Nowicki, Piotr; Bonk, Maciej; Król, Wiesław; Szpiłyk, Damian; Woyciechowski, Michal

2016-01-01

The type of matrix, the landscape surrounding habitat patches, may determine the distribution and function of local populations. However, the matrix is often heterogeneous, and its various components may differentially contribute to metapopulation processes at different spatial scales, a phenomenon that has rarely been investigated. The aim of this study was to estimate the relative importance of matrix composition and spatial scale, habitat quality, and management intensity on the occurrence and density of local populations of two endangered large blue butterflies: Phengaris teleius and P. nausithous. Presence and abundance data were assessed over two years, 2011–12, in 100 local patches within two heterogeneous regions (near Kraków and Tarnów, southern Poland). The matrix composition was analyzed at eight spatial scales. We observed high occupancy rates in both species, regions and years. With the exception of area and isolation, almost all of the matrix components contributed to Phengaris sp. densities. The different matrix components acted at different spatial scales (grassland cover within 4 and 3 km, field cover within 0.4 and 0.3 km and water cover within 4 km radii for P. teleius and P. nausithous, respectively) and provided the highest independent contribution to the butterfly densities. Additionally, the effects of a 0.4 km radius of forest cover and a food plant cover on P. teleius, and a 1 km radius of settlement cover and management intensity on P. nausithous densities were observed. Contrary to former studies we conclude that the matrix heterogeneity and spatial scale rather than general matrix type are of relevance for densities of butterflies. Conservation strategies for these umbrella species should concentrate on maintaining habitat quality and managing matrix composition at the most appropriate spatial scales. PMID:28005942

Relative Contribution of Matrix Structure, Patch Resources and Management to the Local Densities of Two Large Blue Butterfly Species.

PubMed

Kajzer-Bonk, Joanna; Skórka, Piotr; Nowicki, Piotr; Bonk, Maciej; Król, Wiesław; Szpiłyk, Damian; Woyciechowski, Michal

2016-01-01

The type of matrix, the landscape surrounding habitat patches, may determine the distribution and function of local populations. However, the matrix is often heterogeneous, and its various components may differentially contribute to metapopulation processes at different spatial scales, a phenomenon that has rarely been investigated. The aim of this study was to estimate the relative importance of matrix composition and spatial scale, habitat quality, and management intensity on the occurrence and density of local populations of two endangered large blue butterflies: Phengaris teleius and P. nausithous. Presence and abundance data were assessed over two years, 2011-12, in 100 local patches within two heterogeneous regions (near Kraków and Tarnów, southern Poland). The matrix composition was analyzed at eight spatial scales. We observed high occupancy rates in both species, regions and years. With the exception of area and isolation, almost all of the matrix components contributed to Phengaris sp. densities. The different matrix components acted at different spatial scales (grassland cover within 4 and 3 km, field cover within 0.4 and 0.3 km and water cover within 4 km radii for P. teleius and P. nausithous, respectively) and provided the highest independent contribution to the butterfly densities. Additionally, the effects of a 0.4 km radius of forest cover and a food plant cover on P. teleius, and a 1 km radius of settlement cover and management intensity on P. nausithous densities were observed. Contrary to former studies we conclude that the matrix heterogeneity and spatial scale rather than general matrix type are of relevance for densities of butterflies. Conservation strategies for these umbrella species should concentrate on maintaining habitat quality and managing matrix composition at the most appropriate spatial scales.

Fast Low-Rank Bayesian Matrix Completion With Hierarchical Gaussian Prior Models

NASA Astrophysics Data System (ADS)

Yang, Linxiao; Fang, Jun; Duan, Huiping; Li, Hongbin; Zeng, Bing

2018-06-01

The problem of low rank matrix completion is considered in this paper. To exploit the underlying low-rank structure of the data matrix, we propose a hierarchical Gaussian prior model, where columns of the low-rank matrix are assumed to follow a Gaussian distribution with zero mean and a common precision matrix, and a Wishart distribution is specified as a hyperprior over the precision matrix. We show that such a hierarchical Gaussian prior has the potential to encourage a low-rank solution. Based on the proposed hierarchical prior model, a variational Bayesian method is developed for matrix completion, where the generalized approximate massage passing (GAMP) technique is embedded into the variational Bayesian inference in order to circumvent cumbersome matrix inverse operations. Simulation results show that our proposed method demonstrates superiority over existing state-of-the-art matrix completion methods.

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

Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change.

PubMed

Bestion, Elvire; Teyssier, Aimeric; Richard, Murielle; Clobert, Jean; Cote, Julien

2015-10-01

Evidence has accumulated in recent decades on the drastic impact of climate change on biodiversity. Warming temperatures have induced changes in species physiology, phenology, and have decreased body size. Such modifications can impact population dynamics and could lead to changes in life cycle and demography. More specifically, conceptual frameworks predict that global warming will severely threaten tropical ectotherms while temperate ectotherms should resist or even benefit from higher temperatures. However, experimental studies measuring the impacts of future warming trends on temperate ectotherms' life cycle and population persistence are lacking. Here we investigate the impacts of future climates on a model vertebrate ectotherm species using a large-scale warming experiment. We manipulated climatic conditions in 18 seminatural populations over two years to obtain a present climate treatment and a warm climate treatment matching IPCC predictions for future climate. Warmer temperatures caused a faster body growth, an earlier reproductive onset, and an increased voltinism, leading to a highly accelerated life cycle but also to a decrease in adult survival. A matrix population model predicts that warm climate populations in our experiment should go extinct in around 20 y. Comparing our experimental climatic conditions to conditions encountered by populations across Europe, we suggest that warming climates should threaten a significant number of populations at the southern range of the distribution. Our findings stress the importance of experimental approaches on the entire life cycle to more accurately predict population and species persistence in future climates.

Live Fast, Die Young: Experimental Evidence of Population Extinction Risk due to Climate Change

PubMed Central

Bestion, Elvire; Teyssier, Aimeric; Richard, Murielle; Clobert, Jean; Cote, Julien

2015-01-01

Evidence has accumulated in recent decades on the drastic impact of climate change on biodiversity. Warming temperatures have induced changes in species physiology, phenology, and have decreased body size. Such modifications can impact population dynamics and could lead to changes in life cycle and demography. More specifically, conceptual frameworks predict that global warming will severely threaten tropical ectotherms while temperate ectotherms should resist or even benefit from higher temperatures. However, experimental studies measuring the impacts of future warming trends on temperate ectotherms' life cycle and population persistence are lacking. Here we investigate the impacts of future climates on a model vertebrate ectotherm species using a large-scale warming experiment. We manipulated climatic conditions in 18 seminatural populations over two years to obtain a present climate treatment and a warm climate treatment matching IPCC predictions for future climate. Warmer temperatures caused a faster body growth, an earlier reproductive onset, and an increased voltinism, leading to a highly accelerated life cycle but also to a decrease in adult survival. A matrix population model predicts that warm climate populations in our experiment should go extinct in around 20 y. Comparing our experimental climatic conditions to conditions encountered by populations across Europe, we suggest that warming climates should threaten a significant number of populations at the southern range of the distribution. Our findings stress the importance of experimental approaches on the entire life cycle to more accurately predict population and species persistence in future climates. PMID:26501958

Apparent mass matrix of standing subjects exposed to multi-axial whole-body vibration.

PubMed

Tarabini, Marco; Solbiati, Stefano; Saggin, Bortolino; Scaccabarozzi, Diego

2016-08-01

This paper describes the experimental characterisation of the apparent mass matrix of eight male subjects in standing position and the identification of nonlinearities under both mono-axial and dual-axis whole-body vibration. The nonlinear behaviour of the response was studied using the conditioned response techniques considering models of increasing complexity. Results showed that the cross-axis terms are comparable to the diagonal terms. The contribution of the nonlinear effects are minor and can be endorsed to the change of modal parameters during the tests. The nonlinearity generated by the vibration magnitude is more evident in the subject response, since magnitude-dependent effects in the population are overlaid by the scatter in the subjects' biometric data. The biodynamic response is influenced by the addition of a secondary vibration axis and, in case of dual-axis vibrations, the overall magnitude has a marginal contribution. Practitioner Summary: We have measured both the diagonal and cross-axis elements of the apparent mass matrix. The effect of nonlinearities and the simultaneous presence of vibration along two axes are smaller than the inter-subject variability.

Existence of solutions of a two-dimensional boundary value problem for a system of nonlinear equations arising in growing cell populations.

PubMed

Jeribi, Aref; Krichen, Bilel; Mefteh, Bilel

2013-01-01

In the paper [A. Ben Amar, A. Jeribi, and B. Krichen, Fixed point theorems for block operator matrix and an application to a structured problem under boundary conditions of Rotenberg's model type, to appear in Math. Slovaca. (2014)], the existence of solutions of the two-dimensional boundary value problem (1) and (2) was discussed in the product Banach space L(p)×L(p) for p∈(1, ∞). Due to the lack of compactness on L1 spaces, the analysis did not cover the case p=1. The purpose of this work is to extend the results of Ben Amar et al. to the case p=1 by establishing new variants of fixed-point theorems for a 2×2 operator matrix, involving weakly compact operators.

Genome-Wide Association Studies with a Genomic Relationship Matrix: A Case Study with Wheat and Arabidopsis

PubMed Central

Gianola, Daniel; Fariello, Maria I.; Naya, Hugo; Schön, Chris-Carolin

2016-01-01

Standard genome-wide association studies (GWAS) scan for relationships between each of p molecular markers and a continuously distributed target trait. Typically, a marker-based matrix of genomic similarities among individuals (G) is constructed, to account more properly for the covariance structure in the linear regression model used. We show that the generalized least-squares estimator of the regression of phenotype on one or on m markers is invariant with respect to whether or not the marker(s) tested is(are) used for building G, provided variance components are unaffected by exclusion of such marker(s) from G. The result is arrived at by using a matrix expression such that one can find many inverses of genomic relationship, or of phenotypic covariance matrices, stemming from removing markers tested as fixed, but carrying out a single inversion. When eigenvectors of the genomic relationship matrix are used as regressors with fixed regression coefficients, e.g., to account for population stratification, their removal from G does matter. Removal of eigenvectors from G can have a noticeable effect on estimates of genomic and residual variances, so caution is needed. Concepts were illustrated using genomic data on 599 wheat inbred lines, with grain yield as target trait, and on close to 200 Arabidopsis thaliana accessions. PMID:27520956

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.

Modeling quorum sensing trade-offs between bacterial cell density and system extension from open boundaries

NASA Astrophysics Data System (ADS)

Marenda, Mattia; Zanardo, Marina; Trovato, Antonio; Seno, Flavio; Squartini, Andrea

2016-12-01

Bacterial communities undergo collective behavioural switches upon producing and sensing diffusible signal molecules; a mechanism referred to as Quorum Sensing (QS). Exemplarily, biofilm organic matrices are built concertedly by bacteria in several environments. QS scope in bacterial ecology has been debated for over 20 years. Different perspectives counterpose the role of density reporter for populations to that of local environment diffusivity probe for individual cells. Here we devise a model system where tubes of different heights contain matrix-embedded producers and sensors. These tubes allow non-limiting signal diffusion from one open end, thereby showing that population spatial extension away from an open boundary can be a main critical factor in QS. Experimental data, successfully recapitulated by a comprehensive mathematical model, demonstrate how tube height can overtake the role of producer density in triggering sensor activation. The biotic degradation of the signal is found to play a major role and to be species-specific and entirely feedback-independent.

Modeling quorum sensing trade-offs between bacterial cell density and system extension from open boundaries.

PubMed

Marenda, Mattia; Zanardo, Marina; Trovato, Antonio; Seno, Flavio; Squartini, Andrea

2016-12-14

Bacterial communities undergo collective behavioural switches upon producing and sensing diffusible signal molecules; a mechanism referred to as Quorum Sensing (QS). Exemplarily, biofilm organic matrices are built concertedly by bacteria in several environments. QS scope in bacterial ecology has been debated for over 20 years. Different perspectives counterpose the role of density reporter for populations to that of local environment diffusivity probe for individual cells. Here we devise a model system where tubes of different heights contain matrix-embedded producers and sensors. These tubes allow non-limiting signal diffusion from one open end, thereby showing that population spatial extension away from an open boundary can be a main critical factor in QS. Experimental data, successfully recapitulated by a comprehensive mathematical model, demonstrate how tube height can overtake the role of producer density in triggering sensor activation. The biotic degradation of the signal is found to play a major role and to be species-specific and entirely feedback-independent.

Robustness of Tomato Quality Evaluation Using a Portable Vis-SWNIRS for Dry Matter and Colour

PubMed Central

Subedi, P. P.; Walsh, K. B.

2017-01-01

The utility of a handheld visible-short wave near infrared spectrophotometer utilising an interactance optical geometry was assessed in context of the noninvasive determination of intact tomato dry matter content, as an index of final ripe soluble solids content, and colouration, as an index of maturation to guide a decision to harvest. Partial least squares regression model robustness was demonstrated through the use of populations of different harvest dates or growing conditions for calibration and prediction. Dry matter predictions of independent populations of fruit achieved R2 ranging from 0.86 to 0.92 and bias from −0.14 to 0.03%. For a CIE a⁎ colour model, prediction R2 ranged from 0.85 to 0.96 and bias from −1.18 to −0.08. Updating the calibration model with new samples to extend range in the attribute of interest and in sample matrix is key to better prediction performance. The handheld spectrometry system is recommended for practical implementation in tomato cultivation. PMID:29333161

Spatial Models for Prediction and Early Warning of Aedes aegypti Proliferation from Data on Climate Change and Variability in Cuba.

PubMed

Ortiz, Paulo L; Rivero, Alina; Linares, Yzenia; Pérez, Alina; Vázquez, Juan R

2015-04-01

Climate variability, the primary expression of climate change, is one of the most important environmental problems affecting human health, particularly vector-borne diseases. Despite research efforts worldwide, there are few studies addressing the use of information on climate variability for prevention and early warning of vector-borne infectious diseases. Show the utility of climate information for vector surveillance by developing spatial models using an entomological indicator and information on predicted climate variability in Cuba to provide early warning of danger of increased risk of dengue transmission. An ecological study was carried out using retrospective and prospective analyses of time series combined with spatial statistics. Several entomological and climatic indicators were considered using complex Bultó indices -1 and -2. Moran's I spatial autocorrelation coefficient specified for a matrix of neighbors with a radius of 20 km, was used to identify the spatial structure. Spatial structure simulation was based on simultaneous autoregressive and conditional autoregressive models; agreement between predicted and observed values for number of Aedes aegypti foci was determined by the concordance index Di and skill factor Bi. Spatial and temporal distributions of populations of Aedes aegypti were obtained. Models for describing, simulating and predicting spatial patterns of Aedes aegypti populations associated with climate variability patterns were put forward. The ranges of climate variability affecting Aedes aegypti populations were identified. Forecast maps were generated for the municipal level. Using the Bultó indices of climate variability, it is possible to construct spatial models for predicting increased Aedes aegypti populations in Cuba. At 20 x 20 km resolution, the models are able to provide warning of potential changes in vector populations in rainy and dry seasons and by month, thus demonstrating the usefulness of climate information for epidemiological surveillance.

Neural patterning of human induced pluripotent stem cells in 3-D cultures for studying biomolecule-directed differential cellular responses.

PubMed

Yan, Yuanwei; Bejoy, Julie; Xia, Junfei; Guan, Jingjiao; Zhou, Yi; Li, Yan

2016-09-15

Appropriate neural patterning of human induced pluripotent stem cells (hiPSCs) is critical to generate specific neural cells/tissues and even mini-brains that are physiologically relevant to model neurological diseases. However, the capacity of signaling factors that regulate 3-D neural tissue patterning in vitro and differential responses of the resulting neural populations to various biomolecules have not yet been fully understood. By tuning neural patterning of hiPSCs with small molecules targeting sonic hedgehog (SHH) signaling, this study generated different 3-D neuronal cultures that were mainly comprised of either cortical glutamatergic neurons or motor neurons. Abundant glutamatergic neurons were observed following the treatment with an antagonist of SHH signaling, cyclopamine, while Islet-1 and HB9-expressing motor neurons were enriched by an SHH agonist, purmorphamine. In neurons derived with different neural patterning factors, whole-cell patch clamp recordings showed similar voltage-gated Na(+)/K(+) currents, depolarization-evoked action potentials and spontaneous excitatory post-synaptic currents. Moreover, these different neuronal populations exhibited differential responses to three classes of biomolecules, including (1) matrix metalloproteinase inhibitors that affect extracellular matrix remodeling; (2) N-methyl-d-aspartate that induces general neurotoxicity; and (3) amyloid β (1-42) oligomers that cause neuronal subtype-specific neurotoxicity. This study should advance our understanding of hiPSC self-organization and neural tissue development and provide a transformative approach to establish 3-D models for neurological disease modeling and drug discovery. Appropriate neural patterning of human induced pluripotent stem cells (hiPSCs) is critical to generate specific neural cells, tissues and even mini-brains that are physiologically relevant to model neurological diseases. However, the capability of sonic hedgehog-related small molecules to tune different neuronal subtypes in 3-D differentiation from hiPSCs and the differential cellular responses of region-specific neuronal subtypes to various biomolecules have not been fully investigated. By tuning neural patterning of hiPSCs with small molecules targeting sonic hedgehog signaling, this study provides knowledge on the differential susceptibility of region-specific neuronal subtypes derived from hiPSCs to different biomolecules in extracellular matrix remodeling and neurotoxicity. The findings are significant for understanding 3-D neural patterning of hiPSCs for the applications in brain organoid formation, neurological disease modeling, and drug discovery. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Mixing times towards demographic equilibrium in insect populations with temperature variable age structures.

PubMed

Damos, Petros

2015-08-01

In this study, we use entropy related mixing rate modules to measure the effects of temperature on insect population stability and demographic breakdown. The uncertainty in the age of the mother of a randomly chosen newborn, and how it is moved after a finite act of time steps, is modeled using a stochastic transformation of the Leslie matrix. Age classes are represented as a cycle graph and its transitions towards the stable age distribution are brought forth as an exact Markov chain. The dynamics of divergence, from a non equilibrium state towards equilibrium, are evaluated using the Kolmogorov-Sinai entropy. Moreover, Kullback-Leibler distance is applied as information-theoretic measure to estimate exact mixing times of age transitions probabilities towards equilibrium. Using empirically data, we show that on the initial conditions and simulated projection's trough time, that population entropy can effectively be applied to detect demographic variability towards equilibrium under different temperature conditions. Changes in entropy are correlated with the fluctuations of the insect population decay rates (i.e. demographic stability towards equilibrium). Moreover, shorter mixing times are directly linked to lower entropy rates and vice versa. This may be linked to the properties of the insect model system, which in contrast to warm blooded animals has the ability to greatly change its metabolic and demographic rates. Moreover, population entropy and the related distance measures that are applied, provide a means to measure these rates. The current results and model projections provide clear biological evidence why dynamic population entropy may be useful to measure population stability. Copyright © 2015 Elsevier Inc. All rights reserved.

Data-Driven Learning of Q-Matrix

PubMed Central

Liu, Jingchen; Xu, Gongjun; Ying, Zhiliang

2013-01-01

The recent surge of interests in cognitive assessment has led to developments of novel statistical models for diagnostic classification. Central to many such models is the well-known Q-matrix, which specifies the item–attribute relationships. This article proposes a data-driven approach to identification of the Q-matrix and estimation of related model parameters. A key ingredient is a flexible T-matrix that relates the Q-matrix to response patterns. The flexibility of the T-matrix allows the construction of a natural criterion function as well as a computationally amenable algorithm. Simulations results are presented to demonstrate usefulness and applicability of the proposed method. Extension to handling of the Q-matrix with partial information is presented. The proposed method also provides a platform on which important statistical issues, such as hypothesis testing and model selection, may be formally addressed. PMID:23926363

Emergence of a new pair-coherent phase in many-body quenches of repulsive bosons

NASA Astrophysics Data System (ADS)

Fischer, Uwe R.; Lee, Kang-Soo; Xiong, Bo

2011-07-01

We investigate the dynamical mode population statistics and associated first- and second-order coherence of an interacting bosonic two-mode model when the pair-exchange coupling is quenched from negative to positive values. It is shown that for moderately rapid second-order transitions, a new pair-coherent phase emerges on the positive coupling side in an excited state, which is not fragmented as the ground-state single-particle density matrix would prescribe it to be.

Forecasting the need for physicians in the United States: the Health Resources and Services Administration's physician requirements model.

PubMed Central

Greenberg, L; Cultice, J M

1997-01-01

OBJECTIVE: The Health Resources and Services Administration's Bureau of Health Professions developed a demographic utilization-based model of physician specialty requirements to explore the consequences of a broad range of scenarios pertaining to the nation's health care delivery system on need for physicians. DATA SOURCE/STUDY SETTING: The model uses selected data primarily from the National Center for Health Statistics, the American Medical Association, and the U.S. Bureau of Census. Forecasts are national estimates. STUDY DESIGN: Current (1989) utilization rates for ambulatory and inpatient medical specialty services were obtained for the population according to age, gender, race/ethnicity, and insurance status. These rates are used to estimate specialty-specific total service utilization expressed in patient care minutes for future populations and converted to physician requirements by applying per-physician productivity estimates. DATA COLLECTION/EXTRACTION METHODS: Secondary data were analyzed and put into matrixes for use in the mainframe computer-based model. Several missing data points, e.g., for HMO-enrolled populations, were extrapolated from available data by the project's contractor. PRINCIPAL FINDINGS: The authors contend that the Bureau's demographic utilization model represents improvements over other data-driven methodologies that rely on staffing ratios and similar supply-determined bases for estimating requirements. The model's distinct utility rests in offering national-level physician specialty requirements forecasts. Images Figure 1 PMID:9018213

Matrix- and plasma-derived peptides promote tissue-specific injury responses and wound healing in diabetic swine.

PubMed

Sheets, Anthony R; Massey, Conner J; Cronk, Stephen M; Iafrati, Mark D; Herman, Ira M

2016-07-02

Non-healing wounds are a major global health concern and account for the majority of non-traumatic limb amputations worldwide. However, compared to standard care practices, few advanced therapeutics effectively resolve these injuries stemming from cardiovascular disease, aging, and diabetes-related vasculopathies. While matrix turnover is disrupted in these injuries, debriding enzymes may promote healing by releasing matrix fragments that induce cell migration, proliferation, and morphogenesis, and plasma products may also stimulate these processes. Thus, we created matrix- and plasma-derived peptides, Comb1 and UN3, which induce cellular injury responses in vitro, and accelerate healing in rodent models of non-healing wounds. However, the effects of these peptides in non-healing wounds in diabetes are not known. Here, we interrogated whether these peptides stimulate healing in a diabetic porcine model highly reminiscent of human healing impairments in type 1 and type 2-diabetes. After 3-6 weeks of streptozotocin-induced diabetes, full-thickness wounds were surgically created on the backs of adult female Yorkshire swine under general anesthesia. Comb1 and UN3 peptides or sterile saline (negative control) were administered to wounds daily for 3-7 days. Following sacrifice, wound tissues were harvested, and quantitative histological and immunohistochemical analyses were performed for wound closure, angiogenesis and granulation tissue deposition, along with quantitative molecular analyses of factors critical for angiogenesis, epithelialization, and dermal matrix remodeling. Comb1 and UN3 significantly increase re-epithelialization and angiogenesis in diabetic porcine wounds, compared to saline-treated controls. Additionally, fluorescein-conjugated Comb1 labels keratinocytes, fibroblasts, and vascular endothelial cells in porcine wounds, and Far western blotting reveals these cell populations express multiple fluorescein-Comb1-interacting proteins in vitro. Further, peptide treatment increases mRNA expression of several pro-angiogenic, epithelializing, and matrix-remodeling factors, importantly including balanced inductions in matrix metalloproteinase-2, -9, and tissue inhibitor of metalloproteinases-1, lending further insight into their mechanisms. Comb1 and UN3 stimulate wound resolution in diabetic Yorkshire swine through upregulation of multiple reparative growth factors and cytokines, especially matrix metalloproteinases and inhibitors that may aid in reversing the proteolytic imbalance characteristic of chronically inflamed non-healing wounds. Together, these peptides should have great therapeutic potential for all patients in need of healing, regardless of injury etiology.

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

Calculating Path-Dependent Travel Time Prediction Variance and Covariance for the SALSA3D Global Tomographic P-Velocity Model with a Distributed Parallel Multi-Core Computer

NASA Astrophysics Data System (ADS)

Hipp, J. R.; Encarnacao, A.; Ballard, S.; Young, C. J.; Phillips, W. S.; Begnaud, M. L.

2011-12-01

Recently our combined SNL-LANL research team has succeeded in developing a global, seamless 3D tomographic P-velocity model (SALSA3D) that provides superior first P travel time predictions at both regional and teleseismic distances. However, given the variable data quality and uneven data sampling associated with this type of model, it is essential that there be a means to calculate high-quality estimates of the path-dependent variance and covariance associated with the predicted travel times of ray paths through the model. In this paper, we show a methodology for accomplishing this by exploiting the full model covariance matrix. Our model has on the order of 1/2 million nodes, so the challenge in calculating the covariance matrix is formidable: 0.9 TB storage for 1/2 of a symmetric matrix, necessitating an Out-Of-Core (OOC) blocked matrix solution technique. With our approach the tomography matrix (G which includes Tikhonov regularization terms) is multiplied by its transpose (GTG) and written in a blocked sub-matrix fashion. We employ a distributed parallel solution paradigm that solves for (GTG)-1 by assigning blocks to individual processing nodes for matrix decomposition update and scaling operations. We first find the Cholesky decomposition of GTG which is subsequently inverted. Next, we employ OOC matrix multiply methods to calculate the model covariance matrix from (GTG)-1 and an assumed data covariance matrix. Given the model covariance matrix we solve for the travel-time covariance associated with arbitrary ray-paths by integrating the model covariance along both ray paths. Setting the paths equal gives variance for that path. Sandia National Laboratories is a multi-program laboratory managed and operated by Sandia Corporation, a wholly owned subsidiary of Lockheed Martin Corporation, for the U.S. Department of Energy's National Nuclear Security Administration under contract DE-AC04-94AL85000.

Distribution of the Determinant of the Sample Correlation Matrix: Monte Carlo Type One Error Rates.

ERIC Educational Resources Information Center

Reddon, John R.; And Others

1985-01-01

Computer sampling from a multivariate normal spherical population was used to evaluate the type one error rates for a test of sphericity based on the distribution of the determinant of the sample correlation matrix. (Author/LMO)

Disease invasion risk in a growing population.

PubMed

Yuan, Sanling; van den Driessche, P; Willeboordse, Frederick H; Shuai, Zhisheng; Ma, Junling

2016-09-01

The spread of an infectious disease may depend on the population size. For simplicity, classic epidemic models assume homogeneous mixing, usually standard incidence or mass action. For standard incidence, the contact rate between any pair of individuals is inversely proportional to the population size, and so the basic reproduction number (and thus the initial exponential growth rate of the disease) is independent of the population size. For mass action, this contact rate remains constant, predicting that the basic reproduction number increases linearly with the population size, meaning that disease invasion is easiest when the population is largest. In this paper, we show that neither of these may be true on a slowly evolving contact network: the basic reproduction number of a short epidemic can reach its maximum while the population is still growing. The basic reproduction number is proportional to the spectral radius of a contact matrix, which is shown numerically to be well approximated by the average excess degree of the contact network. We base our analysis on modeling the dynamics of the average excess degree of a random contact network with constant population input, proportional deaths, and preferential attachment for contacts brought in by incoming individuals (i.e., individuals with more contacts attract more incoming contacts). In addition, we show that our result also holds for uniform attachment of incoming contacts (i.e., every individual has the same chance of attracting incoming contacts), and much more general population dynamics. Our results show that a disease spreading in a growing population may evade control if disease control planning is based on the basic reproduction number at maximum population size.

Holocene population history of the Sabana de Bogotá region, Northern South America: An assessment of the craniofacial shape variation.

PubMed

Delgado, Miguel

2017-02-01

Several authors using multiple and independent lines of evidence investigating the biocultural continuity versus discontinuity in the Sabana de Bogotá region, in the eastern highlands of Colombia, have arrived at contradictory conclusions supporting either scenarios. This study analyzes the craniofacial size and shape variation of diachronic samples from the study region to test distinct population history scenarios that support continuity or, alternatively, divergence. A total of 92 adult skulls belonging to five chronological groups, ranging from c. 10,100 to 350 14 C YBP, were analyzed through Procrustean geometric morphometric techniques. Matrix correlation analysis, multivariate exploratory (PCA, FDA), and evolutionary quantitative genetic methods (R-matrix analysis and β-test) were used to study the diachronic craniofacial shape variation. A model that supports strong evolutionary diversification over the Holocene better explains the patterns of morphological variation observed. At least two periods of significant craniofacial size and shape change were detected: one during the middle to initial late Holocene transition (c. 4,000-3,200 14 C YBP) and other toward the final late Holocene (post-2,000 14 C YBP), which exhibit differences in the pattern and magnitude of cranial divergence. In addition, the differentiation viewed between early and mid-Holocene foragers could mark the initial entry of non-local populations into the region toward the beginnings of the middle Holocene. Distinct to previous investigations the present study supports a more complex regional population history where multiple population contractions/extinctions, dispersals and assimilations along with dietary adaptations took place during the last 10,000 years. These results are in agreement with the archaeological and paleoecological record which suggests marked periods of change rather than temporal stability. © 2016 Wiley Periodicals, Inc.

How Fast Does Darwin's Elephant Population Grow?

PubMed

Podani, János; Kun, Ádám; Szilágyi, András

2018-06-01

In "The Origin of Species," Darwin describes a hypothetical example illustrating that large, slowly reproducing mammals such as the elephant can reach very large numbers if population growth is not affected by regulating factors. The elephant example has since been cited in various forms in a wide variety of books, ranging from educational material to encyclopedias. However, Darwin's text was changed over the six editions of the book, although some errors in the mathematics persisted throughout. In addition, full details of the problem remained hidden in his correspondence with readers of the Origin. As a result, Darwin's example is very often misinterpreted, misunderstood or presented as if it were a fact. We show that the population growth of Darwin's elephant population can be modeled by the Leslie matrix method, which we generalize here to males as well. Darwin's most often cited figure, about 19 million elephants after 750 years is not a typical outcome, actually a very unlikely result under more realistic, although still hypothetical situations. We provide a recursion formula suggesting that Darwin's original model corresponds to a tribonacci series, a proof showing that sex ratio is constant over all age classes, and a derivation of a generating function of the sequence.

Preosteocytes/Osteocytes Have the Potential to Dedifferentiate Becoming a Source of Osteoblasts

PubMed Central

Torreggiani, Elena; Matthews, Brya G.; Pejda, Slavica; Matic, Igor; Horowitz, Mark C.; Grcevic, Danka; Kalajzic, Ivo

2013-01-01

Presently there is no clear evidence for the ability of mature osteogenic lineage cells to dedifferentiate. In order to identify and trace mature osteogenic lineage cells, we have utilized transgenic mouse models in which the dentin matrix protein 1 (Dmp1) promoter drives expression of GFP (active marker) or Cre recombinase (historic label) in preosteocytes/osteocytes. In long bone chip outgrowth cultures, in which cells on the bone surface were enzymatically removed, cells with previous activity of the Dmp1 promoter migrated onto plastic and down-regulated Dmp1-GFP expression. Dmp1Cre-labeled cells from these cultures had the potential to re-differentiate into the osteogenic lineage, while the negative population showed evidence of adipogenesis. We observed numerous Dmp1Cre-labeled osteoblasts on the surface of bone chips following their in vivo transplantation. Our data indicate that cells embedded in bone matrix are motile, and once given access to the extra bony milieu will migrate out of their lacunae. This population of cells is phenotypically and functionally heterogeneous in vitro. Once the preosteocytes/osteocytes leave lacunae, they can dedifferentiate, potentially providing an additional source of functional osteoblasts. PMID:24040401

QCD dirac operator at nonzero chemical potential: lattice data and matrix model.

PubMed

Akemann, Gernot; Wettig, Tilo

2004-03-12

Recently, a non-Hermitian chiral random matrix model was proposed to describe the eigenvalues of the QCD Dirac operator at nonzero chemical potential. This matrix model can be constructed from QCD by mapping it to an equivalent matrix model which has the same symmetries as QCD with chemical potential. Its microscopic spectral correlations are conjectured to be identical to those of the QCD Dirac operator. We investigate this conjecture by comparing large ensembles of Dirac eigenvalues in quenched SU(3) lattice QCD at a nonzero chemical potential to the analytical predictions of the matrix model. Excellent agreement is found in the two regimes of weak and strong non-Hermiticity, for several different lattice volumes.

Individual variation and the resolution of conflict over parental care in penduline tits

PubMed Central

van Dijk, René E.; Székely, Tamás; Komdeur, Jan; Pogány, Ákos; Fawcett, Tim W.; Weissing, Franz J.

2012-01-01

Eurasian penduline tits (Remiz pendulinus) have an unusually diverse breeding system consisting of frequent male and female polygamy, and uniparental care by the male or the female. Intriguingly, 30 to 40 per cent of all nests are deserted by both parents. To understand the evolution of this diverse breeding system and frequent clutch desertion, we use 6 years of field data to derive fitness expectations for males and females depending on whether or not they care for their offspring. The resulting payoff matrix corresponds to an asymmetric Snowdrift Game with two alternative evolutionarily stable strategies (ESSs): female-only and male-only care. This, however, does not explain the polymorphism in care strategies and frequent biparental desertion, because theory predicts that one of the two ESSs should have spread to fixation. Using a bootstrapping approach, we demonstrate that taking account of individual variation in payoffs explains the patterns of care better than a model based on the average population payoff matrix. In particular, a model incorporating differences in male attractiveness closely predicts the observed frequencies of male and female desertion. Our work highlights the need for a new generation of individual-based evolutionary game-theoretic models. PMID:22189404

Individual variation and the resolution of conflict over parental care in penduline tits.

PubMed

van Dijk, René E; Székely, Tamás; Komdeur, Jan; Pogány, Akos; Fawcett, Tim W; Weissing, Franz J

2012-05-22

Eurasian penduline tits (Remiz pendulinus) have an unusually diverse breeding system consisting of frequent male and female polygamy, and uniparental care by the male or the female. Intriguingly, 30 to 40 per cent of all nests are deserted by both parents. To understand the evolution of this diverse breeding system and frequent clutch desertion, we use 6 years of field data to derive fitness expectations for males and females depending on whether or not they care for their offspring. The resulting payoff matrix corresponds to an asymmetric Snowdrift Game with two alternative evolutionarily stable strategies (ESSs): female-only and male-only care. This, however, does not explain the polymorphism in care strategies and frequent biparental desertion, because theory predicts that one of the two ESSs should have spread to fixation. Using a bootstrapping approach, we demonstrate that taking account of individual variation in payoffs explains the patterns of care better than a model based on the average population payoff matrix. In particular, a model incorporating differences in male attractiveness closely predicts the observed frequencies of male and female desertion. Our work highlights the need for a new generation of individual-based evolutionary game-theoretic models.

Application of optimal design methodologies in clinical pharmacology experiments.

PubMed

Ogungbenro, Kayode; Dokoumetzidis, Aristides; Aarons, Leon

2009-01-01

Pharmacokinetics and pharmacodynamics data are often analysed by mixed-effects modelling techniques (also known as population analysis), which has become a standard tool in the pharmaceutical industries for drug development. The last 10 years has witnessed considerable interest in the application of experimental design theories to population pharmacokinetic and pharmacodynamic experiments. Design of population pharmacokinetic experiments involves selection and a careful balance of a number of design factors. Optimal design theory uses prior information about the model and parameter estimates to optimize a function of the Fisher information matrix to obtain the best combination of the design factors. This paper provides a review of the different approaches that have been described in the literature for optimal design of population pharmacokinetic and pharmacodynamic experiments. It describes options that are available and highlights some of the issues that could be of concern as regards practical application. It also discusses areas of application of optimal design theories in clinical pharmacology experiments. It is expected that as the awareness about the benefits of this approach increases, more people will embrace it and ultimately will lead to more efficient population pharmacokinetic and pharmacodynamic experiments and can also help to reduce both cost and time during drug development. Copyright (c) 2008 John Wiley & Sons, Ltd.

An indirect approach to the extensive calculation of relationship coefficients

PubMed Central

Colleau, Jean-Jacques

2002-01-01

A method was described for calculating population statistics on relationship coefficients without using corresponding individual data. It relied on the structure of the inverse of the numerator relationship matrix between individuals under investigation and ancestors. Computation times were observed on simulated populations and were compared to those incurred with a conventional direct approach. The indirect approach turned out to be very efficient for multiplying the relationship matrix corresponding to planned matings (full design) by any vector. Efficiency was generally still good or very good for calculating statistics on these simulated populations. An extreme implementation of the method is the calculation of inbreeding coefficients themselves. Relative performances of the indirect method were good except when many full-sibs during many generations existed in the population. PMID:12270102

A novel patient-derived xenograft model for claudin-low triple-negative breast cancer.

PubMed

Matossian, Margarite D; Burks, Hope E; Bowles, Annie C; Elliott, Steven; Hoang, Van T; Sabol, Rachel A; Pashos, Nicholas C; O'Donnell, Benjamen; Miller, Kristin S; Wahba, Bahia M; Bunnell, Bruce A; Moroz, Krzysztof; Zea, Arnold H; Jones, Steven D; Ochoa, Augusto C; Al-Khami, Amir A; Hossain, Fokhrul; Riker, Adam I; Rhodes, Lyndsay V; Martin, Elizabeth C; Miele, Lucio; Burow, Matthew E; Collins-Burow, Bridgette M

2018-06-01

Triple-negative breast cancer (TNBC) subtypes are clinically aggressive and cannot be treated with targeted therapeutics commonly used in other breast cancer subtypes. The claudin-low (CL) molecular subtype of TNBC has high rates of metastases, chemoresistance and recurrence. There exists an urgent need to identify novel therapeutic targets in TNBC; however, existing models utilized in target discovery research are limited. Patient-derived xenograft (PDX) models have emerged as superior models for target discovery experiments because they recapitulate features of patient tumors that are limited by cell-line derived xenograft methods. We utilize immunohistochemistry, qRT-PCR and Western Blot to visualize tumor architecture, cellular composition, genomic and protein expressions of a new CL-TNBC PDX model (TU-BcX-2O0). We utilize tissue decellularization techniques to examine extracellular matrix composition of TU-BcX-2O0. Our laboratory successfully established a TNBC PDX tumor, TU-BCX-2O0, which represents a CL-TNBC subtype and maintains this phenotype throughout subsequent passaging. We dissected TU-BCx-2O0 to examine aspects of this complex tumor that can be targeted by developing therapeutics, including the whole and intact breast tumor, specific cell populations within the tumor, and the extracellular matrix. Here, we characterize a claudin-low TNBC patient-derived xenograft model that can be utilized for therapeutic research studies.

Application of fiber bridging models to fatigue crack growth in unidirectional titanium matrix composites

NASA Technical Reports Server (NTRS)

Bakuckas, J. G., Jr.; Johnson, W. S.

1992-01-01

Several fiber bridging models were reviewed and applied to study the matrix fatigue crack growth behavior in center notched (0)(sub 8) SCS-6/Ti-15-3 and (0)(sub 4) SCS-6/Ti-6Al-4V laminates. Observations revealed that fatigue damage consisted primarily of matrix cracks and fiber matrix interfacial failure in the (0)(sub 8) SCS-6/Ti-15-3 laminates. Fiber-matrix interface failure included fracture of the brittle reaction zone and cracking between the two carbon rich fiber coatings. Intact fibers in the wake of the matrix cracks reduce the stress intensity factor range. Thus, an applied stress intensity factor range is inappropriate to characterize matrix crack growth behavior. Fiber bridging models were used to determine the matrix stress intensity factor range in titanium metal matrix composites. In these models, the fibers in the wake of the crack are idealized as a closure pressure. An unknown constant frictional shear stress is assumed to act along the debond or slip length of the bridging fibers. The frictional shear stress was used as a curve fitting parameter to available data (crack growth data, crack opening displacement data, and debond length data). Large variations in the frictional shear stress required to fit the experimental data indicate that the fiber bridging models in their present form lack predictive capabilities. However, these models provide an efficient and relatively simple engineering method for conducting parametric studies of the matrix growth behavior based on constituent properties.

A creep cavity growth model for creep-fatigue life prediction of a unidirectional W/Cu composite

NASA Astrophysics Data System (ADS)

Kim, Young-Suk; Verrilli, Michael J.; Halford, Gary R.

1992-05-01

A microstructural model was developed to predict creep-fatigue life in a (0)(sub 4), 9 volume percent tungsten fiber-reinforced copper matrix composite at the temperature of 833 K. The mechanism of failure of the composite is assumed to be governed by the growth of quasi-equilibrium cavities in the copper matrix of the composite, based on the microscopically observed failure mechanisms. The methodology uses a cavity growth model developed for prediction of creep fracture. Instantaneous values of strain rate and stress in the copper matrix during fatigue cycles were calculated and incorporated in the model to predict cyclic life. The stress in the copper matrix was determined by use of a simple two-bar model for the fiber and matrix during cyclic loading. The model successfully predicted the composite creep-fatigue life under tension-tension cyclic loading through the use of this instantaneous matrix stress level. Inclusion of additional mechanisms such as cavity nucleation, grain boundary sliding, and the effect of fibers on matrix-stress level would result in more generalized predictions of creep-fatigue life.

Temperature dependent nonlinear metal matrix laminae behavior

NASA Technical Reports Server (NTRS)

Barrett, D. J.; Buesking, K. W.

1986-01-01

An analytical method is described for computing the nonlinear thermal and mechanical response of laminated plates. The material model focuses upon the behavior of metal matrix materials by relating the nonlinear composite response to plasticity effects in the matrix. The foundation of the analysis is the unidirectional material model which is used to compute the instantaneous properties of the lamina based upon the properties of the fibers and matrix. The unidirectional model assumes that the fibers properties are constant with temperature and assumes that the matrix can be modelled as a temperature dependent, bilinear, kinematically hardening material. An incremental approach is used to compute average stresses in the fibers and matrix caused by arbitrary mechanical and thermal loads. The layer model is incorporated in an incremental laminated plate theory to compute the nonlinear response of laminated metal matrix composites of general orientation and stacking sequence. The report includes comparisons of the method with other analytical approaches and compares theoretical calculations with measured experimental material behavior. A section is included which describes the limitations of the material model.

A creep cavity growth model for creep-fatigue life prediction of a unidirectional W/Cu composite

NASA Technical Reports Server (NTRS)

Kim, Young-Suk; Verrilli, Michael J.; Halford, Gary R.

1992-01-01

A microstructural model was developed to predict creep-fatigue life in a (0)(sub 4), 9 volume percent tungsten fiber-reinforced copper matrix composite at the temperature of 833 K. The mechanism of failure of the composite is assumed to be governed by the growth of quasi-equilibrium cavities in the copper matrix of the composite, based on the microscopically observed failure mechanisms. The methodology uses a cavity growth model developed for prediction of creep fracture. Instantaneous values of strain rate and stress in the copper matrix during fatigue cycles were calculated and incorporated in the model to predict cyclic life. The stress in the copper matrix was determined by use of a simple two-bar model for the fiber and matrix during cyclic loading. The model successfully predicted the composite creep-fatigue life under tension-tension cyclic loading through the use of this instantaneous matrix stress level. Inclusion of additional mechanisms such as cavity nucleation, grain boundary sliding, and the effect of fibers on matrix-stress level would result in more generalized predictions of creep-fatigue life.

Modeling for Matrix Multicracking Evolution of Cross-ply Ceramic-Matrix Composites Using Energy Balance Approach

NASA Astrophysics Data System (ADS)

Longbiao, Li

2015-12-01

The matrix multicracking evolution of cross-ply ceramic-matrix composites (CMCs) has been investigated using energy balance approach. The multicracking of cross-ply CMCs was classified into five modes, i.e., (1) mode 1: transverse multicracking; (2) mode 2: transverse multicracking and matrix multicracking with perfect fiber/matrix interface bonding; (3) mode 3: transverse multicracking and matrix multicracking with fiber/matrix interface debonding; (4) mode 4: matrix multicracking with perfect fiber/matrix interface bonding; and (5) mode 5: matrix multicracking with fiber/matrix interface debonding. The stress distributions of four cracking modes, i.e., mode 1, mode 2, mode 3 and mode 5, are analysed using shear-lag model. The matrix multicracking evolution of mode 1, mode 2, mode 3 and mode 5, has been determined using energy balance approach. The effects of ply thickness and fiber volume fraction on matrix multicracking evolution of cross-ply CMCs have been investigated.

Organizational Models and Mythologies of the American Research University. ASHE 1986 Annual Meeting Paper.

ERIC Educational Resources Information Center

Alpert, Daniel

Features of the matrix model of the research university and myths about the academic enterprise are described, along with serious dissonances in the U.S. university system. The linear model, from which the matrix model evolved, describes the university's structure, perceived mission, and organizational behavior. A matrix model portrays in concise,…

Multi-Length Scale-Enriched Continuum-Level Material Model for Kevlar-Fiber-Reinforced Polymer-Matrix Composites

DTIC Science & Technology

2012-08-03

is unlimited. Multi-Length Scale-Enriched Continuum-Level Material Model for Kevlar ®-Fiber-Reinforced Polymer-Matrix Composites The views, opinions...12211 Research Triangle Park, NC 27709-2211 ballistics, composites, Kevlar , material models, microstructural defects REPORT DOCUMENTATION PAGE 11... Kevlar ®-Fiber-Reinforced Polymer-Matrix Composites Report Title Fiber-reinforced polymer matrix composite materials display quite complex deformation

Shape coexistence and β decay of 70Br within a beyond-mean-field approach

NASA Astrophysics Data System (ADS)

Petrovici, A.

2018-02-01

β -decay properties of the odd-odd N =Z 70Br nucleus are self-consistently explored within the beyond-mean-field complex excited vampir variational model using an effective interaction obtained from a nuclear matter G -matrix based on the charge-dependent Bonn CD potential and an adequate model space. Results on superallowed Fermi β decay of the ground state and Gamow-Teller decay of the 9+ isomer in 70Br correlated with the shape coexistence and mixing effects on the structure and electromagnetic properties of the populated states in the daughter nucleus 70Se are presented and compared with available data.

A Bi-Modal Distribution of ALHA77307 Matrix Olivine: Evidence for Fine-Grained Mixing from Multiple Reservoirs in the CO Formation Zone

NASA Technical Reports Server (NTRS)

Frank, D.; Zolensky, Michael E.; Brearley, A.; Le, L.

2011-01-01

The CO 3.0 chondrite ALHA77307 is thought to be the least metamorphosed of all the CO chondrites [1]. As such, the fine-grained (<30 m) olivine found in its matrix is a valuable resource for investigating the CO formation environment since its compositions should be primary. In the CO matrix, we indeed find a wide range of major element compositions (Fa(0.5-71)). However, more importantly, we find that the olivines make up two compositionally distinct populations (Fa(0.5-5) and Fa(21-71)). Grains from both populations are found within an extremely close proximity and we see no obvious evidence of two distinct lithologies within our samples. Therefore, we conclude that the olivine grains found in the ALHA77307 matrix must have crystallized within two unique formation conditions and were later mixed at a very fine scale during the accretion epoch. Here, we propose a possible explanation based on Cr and Mn concentrations in the olivine.

The Tetrahedral Zamolodchikov Algebra and the {AdS_5× S^5} S-matrix

NASA Astrophysics Data System (ADS)

Mitev, Vladimir; Staudacher, Matthias; Tsuboi, Zengo

2017-08-01

The S-matrix of the {AdS_5× S^5} string theory is a tensor product of two centrally extended su{(2|2)\\ltimes R^2 S-matrices, each of which is related to the R-matrix of the Hubbard model. The R-matrix of the Hubbard model was first found by Shastry, who ingeniously exploited the fact that, for zero coupling, the Hubbard model can be decomposed into two XX models. In this article, we review and clarify this construction from the AdS/CFT perspective and investigate the implications this has for the {AdS_5× S^5} S-matrix.

A job-exposure matrix for use in population based studies in England and Wales.

PubMed Central

Pannett, B; Coggon, D; Acheson, E D

1985-01-01

The job-exposure matrix described has been developed for use in population based studies of occupational morbidity and mortality in England and Wales. The job axis of the matrix is based on the Registrar General's 1966 classification of occupations and 1968 classification of industries, and comprises 669 job categories. The exposure axis is made up of 49 chemical, physical, and biological agents, most of which are known or suspected causes of occupational disease. In the body of the matrix associations between jobs and exposures are graded to four levels. The matrix has been applied to data from a case-control study of lung cancer in which occupational histories were elicited by means of a postal questionnaire. Estimates of exposure to five known or suspected carcinogens (asbestos, chromates, cutting oils, formaldehyde, and inhaled polycyclic aromatic hydrocarbons were compared with those obtained by detailed review of individual occupational histories. When the matrix was used exposures were attributed to jobs more frequently than on the basis of individual histories. Lung cancer was significantly more common among subjects classed by the matrix as having potential exposure to chromates, but neither method of assigning exposures produced statistically significant associations with asbestos or polycyclic aromatic hydrocarbons. Possible explanations for the failure to show a clear effect of these known carcinogens are discussed. The greater accuracy of exposures inferred directly from individual histories was reflected in steeper dose response curves for asbestos, chromates, and polycyclic aromatic hydrocarbons. The improvement over results obtained with the matrix, however, was not great. For occupational data of the type examined in this study, direct exposure estimates offer little advantage over those provided at lower cost by a matrix. PMID:4063222

Three distinct cell populations express extracellular matrix proteins and increase in number during skeletal muscle fibrosis.

PubMed

Chapman, Mark A; Mukund, Kavitha; Subramaniam, Shankar; Brenner, David; Lieber, Richard L

2017-02-01

Tissue extracellular matrix (ECM) provides structural support and creates unique environments for resident cells (Bateman JF, Boot-Handford RP, Lamandé SR. Nat Rev Genet 10: 173-183, 2009; Kjaer M. Physiol Rev 84: 649-98, 2004). However, the identities of cells responsible for creating specific ECM components have not been determined. In striated muscle, the identity of these cells becomes important in disease when ECM changes result in fibrosis and subsequent increased tissue stiffness and dysfunction. Here we describe a novel approach to isolate and identify cells that maintain the ECM in both healthy and fibrotic muscle. Using a collagen I reporter mouse, we show that there are three distinct cell populations that express collagen I in both healthy and fibrotic skeletal muscle. Interestingly, the number of collagen I-expressing cells in all three cell populations increases proportionally in fibrotic muscle, indicating that all cell types participate in the fibrosis process. Furthermore, while some profibrotic ECM and ECM-associated genes are significantly upregulated in fibrotic muscle, the fibrillar collagen gene expression profile is not qualitatively altered. This suggests that muscle fibrosis in this model results from an increased number of collagen I-expressing cells and not the initiation of a specific fibrotic collagen gene expression program. Finally, in fibrotic muscle, we show that these collagen I-expressing cell populations differentially express distinct ECM proteins-fibroblasts express the fibrillar components of ECM, fibro/adipogenic progenitors cells differentially express basal laminar proteins, and skeletal muscle progenitor cells differentially express genes important for the satellite cell. Copyright © 2017 the American Physiological Society.

Three distinct cell populations express extracellular matrix proteins and increase in number during skeletal muscle fibrosis

PubMed Central

Chapman, Mark A.; Mukund, Kavitha; Subramaniam, Shankar; Brenner, David

2017-01-01

Tissue extracellular matrix (ECM) provides structural support and creates unique environments for resident cells (Bateman JF, Boot-Handford RP, Lamandé SR. Nat Rev Genet 10: 173–183, 2009; Kjaer M. Physiol Rev 84: 649–98, 2004). However, the identities of cells responsible for creating specific ECM components have not been determined. In striated muscle, the identity of these cells becomes important in disease when ECM changes result in fibrosis and subsequent increased tissue stiffness and dysfunction. Here we describe a novel approach to isolate and identify cells that maintain the ECM in both healthy and fibrotic muscle. Using a collagen I reporter mouse, we show that there are three distinct cell populations that express collagen I in both healthy and fibrotic skeletal muscle. Interestingly, the number of collagen I-expressing cells in all three cell populations increases proportionally in fibrotic muscle, indicating that all cell types participate in the fibrosis process. Furthermore, while some profibrotic ECM and ECM-associated genes are significantly upregulated in fibrotic muscle, the fibrillar collagen gene expression profile is not qualitatively altered. This suggests that muscle fibrosis in this model results from an increased number of collagen I-expressing cells and not the initiation of a specific fibrotic collagen gene expression program. Finally, in fibrotic muscle, we show that these collagen I-expressing cell populations differentially express distinct ECM proteins—fibroblasts express the fibrillar components of ECM, fibro/adipogenic progenitors cells differentially express basal laminar proteins, and skeletal muscle progenitor cells differentially express genes important for the satellite cell. PMID:27881411

Guidance for the utility of linear models in meta-analysis of genetic association studies of binary phenotypes.

PubMed

Cook, James P; Mahajan, Anubha; Morris, Andrew P

2017-02-01

Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population stratification and relatedness through inclusion of random effects for a genetic relationship matrix. However, the utility of linear (mixed) models in the context of meta-analysis of GWAS of binary phenotypes has not been previously explored. In this investigation, we present simulations to compare the performance of linear and logistic regression models under alternative weighting schemes in a fixed-effects meta-analysis framework, considering designs that incorporate variable case-control imbalance, confounding factors and population stratification. Our results demonstrate that linear models can be used for meta-analysis of GWAS of binary phenotypes, without loss of power, even in the presence of extreme case-control imbalance, provided that one of the following schemes is used: (i) effective sample size weighting of Z-scores or (ii) inverse-variance weighting of allelic effect sizes after conversion onto the log-odds scale. Our conclusions thus provide essential recommendations for the development of robust protocols for meta-analysis of binary phenotypes with linear models.

Epidemic patch models applied to pandemic influenza: contact matrix, stochasticity, robustness of predictions.

PubMed

Lunelli, Antonella; Pugliese, Andrea; Rizzo, Caterina

2009-07-01

Due to the recent emergence of H5N1 virus, the modelling of pandemic influenza has become a relevant issue. Here we present an SEIR model formulated to simulate a possible outbreak in Italy, analysing its structure and, more generally, the effect of including specific details into a model. These details regard population heterogeneities, such as age and spatial distribution, as well as stochasticity, that regulates the epidemic dynamics when the number of infectives is low. We discuss and motivate the specific modelling choices made when building the model and investigate how the model details influence the predicted dynamics. Our analysis may help in deciding which elements of complexity are worth including in the design of a deterministic model for pandemic influenza, in a balance between, on the one hand, keeping the model computationally efficient and the number of parameters low and, on the other hand, maintaining the necessary realistic features.

Post-1500 Population Flows and the Long Run Determinants of Economic Growth and Inequality.

PubMed

Putterman, Louis; Weil, David N

2010-01-01

We construct a matrix showing the share of the year 2000 population in every country that is descended from people in different source countries in the year 1500. Using the matrix to adjust indicators of early development so they reflect the history of a population's ancestors rather than the history of the place they live today greatly improves the ability of those indicators to predict current GDP. The variance of early development history of a country's inhabitants is a good predictor for current inequality, with ethnic groups originating in regions having longer histories of organized states tending to be at the upper end of a country's income distribution.

Association of TCF7L2 Genetic Polymorphisms with Type 2 Diabetes Mellitus in the Uygur Population of China.

PubMed

Yao, Hua; Wang, Zhiqiang; Wang, Tingting; Ma, Yan; Su, Yinxia; Ma, Qi; Wang, Li; Zhu, Jun

2015-09-18

Genetic polymorphisms of the transcription factor 7-like 2 (TCF7L2) gene have been reported to be strongly associated with type 2 diabetes mellitus (T2DM) in Icelandic, Danish and American populations and further replicated in other European populations, African Americans, Mexican Americans, and Asian populations. The aim of the present study was to investigate the association of TCF7L2 gene polymorphisms with T2DM in a Uygur population of China. 877 T2DM patients and 871 controls were selected for the present study. Two single nucleotide polymorphisms (SNPs) (rs12255372 and rs7901695) were genotyped by using matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry. The associations of SNPs and haplotypes with T2DM and linkage disequilibrium (LD) structure of the TCF7L2 gene were analyzed. For total participants and male, the distribution of rs12255372 alleles and the dominant model (Guanine Guanine (GG) genotype vs. Guanine Thymine (GT) genotype + Thymine Thymine (TT) genotype) showed significant difference between T2DM and control subjects (for allele: p = 0.013 and p = 0.002, respectively; for dominant model: p = 0.028 and p = 0.008, respectively). The distribution of rs7901695 alleles and the dominant model (TT genotype vs. Thymine Cytosine (TC) genotype + Cytosine Cytosine (CC) genotype) for total participants and male showed significant difference between T2DM and control subjects (for allele: both p = 0.001; for dominant model: p = 0.006 and p = 0.008, respectively). Our data suggested that the genetic polymorphisms of the TCF7L2 gene were associated with T2DM in the Uygur population of China.

Movement behavior, dispersal, and the potential for localized management of deer in a suburban environment

USGS Publications Warehouse

Porter, W.F.; Underwood, H.B.; Woodard, J.L.

2004-01-01

We examined the potential for localized management of white-tailed deer (Odocoileus virginianus) to be successful by measuring movements, testing site fidelity, and modeling the effects of dispersal. Fifty-nine females were radiomarked and tracked during 1997 through 2000 in Irondequoit, New York, USA, a suburb of Rochester. We constructed home ranges for those deer with A greater than or equal to 18 reclocations/season. Fifty percent minimum convex polygons (MCP) averaged 3.9 (SE = 0.53) ha in the summer and 5.3 (SE = 0.80) ha in the winter. Deer showed strong fidelity to both summer and winter home ranges, and 30 of 31 females showed overlap of summer and winter home ranges. Annual survival was 64%; the major cause of mortality was deer-automobile collisions. Average annual dispersal rates were <15% for yearlings and adults. Using matrix population modeling, we explored the role of female dispersal in sustaining different management objectives in adjacent locales of approximately 1,000 ha. Modeling showed that if female dispersal was 8%, culling would have to reduce annual survival to 58% to maintain a population just under ecological carrying capacity and reduce survival to 42% to keel) the population at one-half carrying capacity. With the same dispersal, contraception Would need to be effective in 32% of females if the population is near carrying capacity and 68% if the population is at one-half of carrying capacity. Movement behavior data and modeling results lend support to the use of a localized approach to management of females that emphasizes neighborhood-scale manipulation of deer populations, but our research suggests that dispersal rates in females could be critical to long-term success.

The relative effects of habitat loss and fragmentation on population genetic variation in the red-cockaded woodpecker (Picoides borealis).

PubMed

Bruggeman, Douglas J; Wiegand, Thorsten; Fernández, Néstor

2010-09-01

The relative influence of habitat loss, fragmentation and matrix heterogeneity on the viability of populations is a critical area of conservation research that remains unresolved. Using simulation modelling, we provide an analysis of the influence both patch size and patch isolation have on abundance, effective population size (N(e)) and F(ST). An individual-based, spatially explicit population model based on 15 years of field work on the red-cockaded woodpecker (Picoides borealis) was applied to different landscape configurations. The variation in landscape patterns was summarized using spatial statistics based on O-ring statistics. By regressing demographic and genetics attributes that emerged across the landscape treatments against proportion of total habitat and O-ring statistics, we show that O-ring statistics provide an explicit link between population processes, habitat area, and critical thresholds of fragmentation that affect those processes. Spatial distances among land cover classes that affect biological processes translated into critical scales at which the measures of landscape structure correlated best with genetic indices. Therefore our study infers pattern from process, which contrasts with past studies of landscape genetics. We found that population genetic structure was more strongly affected by fragmentation than population size, which suggests that examining only population size may limit recognition of fragmentation effects that erode genetic variation. If effective population size is used to set recovery goals for endangered species, then habitat fragmentation effects may be sufficiently strong to prevent evaluation of recovery based on the ratio of census:effective population size alone.

Constructing service-oriented architecture adoption maturity matrix using Kano model

NASA Astrophysics Data System (ADS)

Hamzah, Mohd Hamdi Irwan; Baharom, Fauziah; Mohd, Haslina

2017-10-01

Commonly, organizations adopted Service-Oriented Architecture (SOA) because it can provide a flexible reconfiguration and can reduce the development time and cost. In order to guide the SOA adoption, previous industry and academia have constructed SOA maturity model. However, there is a limited number of works on how to construct the matrix in the previous SOA maturity model. Therefore, this study is going to provide a method that can be used in order to construct the matrix in the SOA maturity model. This study adapts Kano Model to construct the cross evaluation matrix focused on SOA adoption IT and business benefits. This study found that Kano Model can provide a suitable and appropriate method for constructing the cross evaluation matrix in SOA maturity model. Kano model also can be used to plot, organize and better represent the evaluation dimension for evaluating the SOA adoption.

ARMA Cholesky Factor Models for the Covariance Matrix of Linear Models.

PubMed

Lee, Keunbaik; Baek, Changryong; Daniels, Michael J

2017-11-01

In longitudinal studies, serial dependence of repeated outcomes must be taken into account to make correct inferences on covariate effects. As such, care must be taken in modeling the covariance matrix. However, estimation of the covariance matrix is challenging because there are many parameters in the matrix and the estimated covariance matrix should be positive definite. To overcomes these limitations, two Cholesky decomposition approaches have been proposed: modified Cholesky decomposition for autoregressive (AR) structure and moving average Cholesky decomposition for moving average (MA) structure, respectively. However, the correlations of repeated outcomes are often not captured parsimoniously using either approach separately. In this paper, we propose a class of flexible, nonstationary, heteroscedastic models that exploits the structure allowed by combining the AR and MA modeling of the covariance matrix that we denote as ARMACD. We analyze a recent lung cancer study to illustrate the power of our proposed methods.

A review of failure models for unidirectional ceramic matrix composites under monotonic loads

NASA Technical Reports Server (NTRS)

Tripp, David E.; Hemann, John H.; Gyekenyesi, John P.

1989-01-01

Ceramic matrix composites offer significant potential for improving the performance of turbine engines. In order to achieve their potential, however, improvements in design methodology are needed. In the past most components using structural ceramic matrix composites were designed by trial and error since the emphasis of feasibility demonstration minimized the development of mathematical models. To understand the key parameters controlling response and the mechanics of failure, the development of structural failure models is required. A review of short term failure models with potential for ceramic matrix composite laminates under monotonic loads is presented. Phenomenological, semi-empirical, shear-lag, fracture mechanics, damage mechanics, and statistical models for the fast fracture analysis of continuous fiber unidirectional ceramic matrix composites under monotonic loads are surveyed.

MMP-TIMP interactions in cancer invasion: An evolutionary game-theoretical framework.

PubMed

Salimi Sartakhti, Javad; Manshaei, Mohammad Hossein; Sadeghi, Mehdi

2017-01-07

One of the main steps in solid cancers to invade surrounding tissues is degradation of tissue barriers in the extracellular matrix. This operation that leads to initiate, angiogenesis and metastasis to other organs, is essentially consequence of collapsing dynamic balance between matrix metalloproteinases (MMP) and tissue inhibitors of metalloproteinases (TIMP). In this work, we model the MMP-TIMP interaction in both normal tissue and invasive cancer using evolutionary game theory. Our model explains how invasive cancer cells get the upper hand in MMP-TIMP imbalance scenarios. We investigate dynamics of them over time and discuss stable and nonstable states in the population. Numerical simulations presented here provide the identification of key genotypic features in the tumor invasion and a natural description for phenotypic variability. The simulation results are consistent with the experimental results in vitro observations presented in medical literature. Finally, by the provided results the necessary conditions to inhibit cancer invasion or prolong its course are explained. In this way, two therapeutic approaches with respect to how they could meet the required conditions are considered. Copyright © 2016 Elsevier Ltd. All rights reserved.

Collisional transfer of population and orientation in sodium potassium

NASA Astrophysics Data System (ADS)

Wolfe, Christopher Matthew

Collisional spectral satellite lines have been identified in recent optical-optical double resonance (OODR) excitation spectra of the NaK molecule. These satellite lines represent both a transfer of population, and a partial preservation of angular momentum orientation, to a rotational level adjacent to the one directly excited by the pump laser beam. A rate equation model was used to study the intensities of these satellite lines as a function of argon pressure and heat pipe oven temperature, in order to separate the collisional effects of argon and potassium atoms (being the most populous species in the vapor by an order of magnitude over the third most populous). Using a fit of this rate equation model to the data, it was found that collisions between NaK and potassium are more likely to transfer population and destroy orientation than argon collisions, and also more likely to transfer population to rotational levels higher in energy than the one being pumped (i.e. a propensity for positive Delta J collisions). Also, collisions between NaK and argon atoms show a propensity toward even-numbered changes in J. In addition to the above study, an analysis of collisional line broadening and velocity-changes in J-changing collisions was performed, showing potassium has a higher line broadening rate coefficient, as well as a smaller velocity change in J-changing collisions, than argon. A program was also written in Fortran 90/95 which solves the density matrix equations of motion in steady state for a coupled system of 3 (or 4) energy levels with their constituent degenerate magnetic sublevels. The solution to these equations yields the populations of each sublevel in steady state, as well as the laser-induced coherences between each sublevel (which are needed to model the polarization spectroscopy lineshape precisely). Development of an appropriate theoretical model for collisional transfer will yield a more rigorous study of the problem than the empirical rate equation model used in the analysis of our experiment.

A stochastic evolution model for residue Insertion-Deletion Independent from Substitution.

PubMed

Lèbre, Sophie; Michel, Christian J

2010-12-01

We develop here a new class of stochastic models of gene evolution based on residue Insertion-Deletion Independent from Substitution (IDIS). Indeed, in contrast to all existing evolution models, insertions and deletions are modeled here by a concept in population dynamics. Therefore, they are not only independent from each other, but also independent from the substitution process. After a separate stochastic analysis of the substitution and the insertion-deletion processes, we obtain a matrix differential equation combining these two processes defining the IDIS model. By deriving a general solution, we give an analytical expression of the residue occurrence probability at evolution time t as a function of a substitution rate matrix, an insertion rate vector, a deletion rate and an initial residue probability vector. Various mathematical properties of the IDIS model in relation with time t are derived: time scale, time step, time inversion and sequence length. Particular expressions of the nucleotide occurrence probability at time t are given for classical substitution rate matrices in various biological contexts: equal insertion rate, insertion-deletion only and substitution only. All these expressions can be directly used for biological evolutionary applications. The IDIS model shows a strongly different stochastic behavior from the classical substitution only model when compared on a gene dataset. Indeed, by considering three processes of residue insertion, deletion and substitution independently from each other, it allows a more realistic representation of gene evolution and opens new directions and applications in this research field. Copyright © 2010 Elsevier Ltd. All rights reserved.

Micromechanical Modeling of Woven Metal Matrix Composites

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Pindera, Marek-Jerzy

1997-01-01

This report presents the results of an extensive micromechanical modeling effort for woven metal matrix composites. The model is employed to predict the mechanical response of 8-harness (8H) satin weave carbon/copper (C/Cu) composites. Experimental mechanical results for this novel high thermal conductivity material were recently reported by Bednarcyk et al. along with preliminary model results. The micromechanics model developed herein is based on an embedded approach. A micromechanics model for the local (micro-scale) behavior of the woven composite, the original method of cells (Aboudi), is embedded in a global (macro-scale) micromechanics model (the three-dimensional generalized method of cells (GMC-3D) (Aboudi). This approach allows representation of true repeating unit cells for woven metal matrix composites via GMC-3D, and representation of local effects, such as matrix plasticity, yarn porosity, and imperfect fiber-matrix bonding. In addition, the equations of GMC-3D were reformulated to significantly reduce the number of unknown quantities that characterize the deformation fields at the microlevel in order to make possible the analysis of actual microstructures of woven composites. The resulting micromechanical model (WCGMC) provides an intermediate level of geometric representation, versatility, and computational efficiency with respect to previous analytical and numerical models for woven composites, but surpasses all previous modeling work by allowing the mechanical response of a woven metal matrix composite, with an elastoplastic matrix, to be examined for the first time. WCGMC is employed to examine the effects of composite microstructure, porosity, residual stresses, and imperfect fiber-matrix bonding on the predicted mechanical response of 8H satin C/Cu. The previously reported experimental results are summarized, and the model predictions are compared to monotonic and cyclic tensile and shear test data. By considering appropriate levels of porosity, residual stresses, and imperfect fiber-matrix debonding, reasonably good qualitative and quantitative correlation is achieved between model and experiment.

MATRIX-VBS (v1.0): Implementing an Evolving Organic Aerosol Volatility in an Aerosol Microphysics Model

NASA Technical Reports Server (NTRS)

Gao, Chloe Y.; Tsigaridis, Kostas; Bauer, Susanne E.

2017-01-01

The gas-particle partitioning and chemical aging of semi-volatile organic aerosol are presented in a newly developed box model scheme, where its effect on the growth, composition, and mixing state of particles is examined. The volatility-basis set (VBS) framework is implemented into the aerosol microphysical scheme MATRIX (Multiconfiguration Aerosol TRacker of mIXing state), which resolves mass and number aerosol concentrations and in multiple mixing-state classes. The new scheme, MATRIX-VBS, has the potential to significantly advance the representation of organic aerosols in Earth system models by improving upon the conventional representation as non-volatile particulate organic matter, often also with an assumed fixed size distribution. We present results from idealized cases representing Beijing, Mexico City, a Finnish forest, and a southeastern US forest, and investigate the evolution of mass concentrations and volatility distributions for organic species across the gas and particle phases, as well as assessing their mixing state among aerosol populations. Emitted semi-volatile primary organic aerosols evaporate almost completely in the intermediate-volatility range, while they remain in the particle phase in the low-volatility range. Their volatility distribution at any point in time depends on the applied emission factors, oxidation by OH radicals, and temperature. We also compare against parallel simulations with the original scheme, which represented only the particulate and non-volatile component of the organic aerosol, examining how differently the condensed-phase organic matter is distributed across the mixing states in the model. The results demonstrate the importance of representing organic aerosol as a semi-volatile aerosol, and explicitly calculating the partitioning of organic species between the gas and particulate phases.

Stochastic stability in three-player games.

PubMed

Kamiński, Dominik; Miekisz, Jacek; Zaborowski, Marcin

2005-11-01

Animal behavior and evolution can often be described by game-theoretic models. Although in many situations the number of players is very large, their strategic interactions are usually decomposed into a sum of two-player games. Only recently were evolutionarily stable strategies defined for multi-player games and their properties analyzed [Broom, M., Cannings, C., Vickers, G.T., 1997. Multi-player matrix games. Bull. Math. Biol. 59, 931-952]. Here we study the long-run behavior of stochastic dynamics of populations of randomly matched individuals playing symmetric three-player games. We analyze the stochastic stability of equilibria in games with multiple evolutionarily stable strategies. We also show that, in some games, a population may not evolve in the long run to an evolutionarily stable equilibrium.

In vitro model to study the effects of matrix stiffening on Ca2+ handling and myofilament function in isolated adult rat cardiomyocytes

PubMed Central

Najafi, Aref; Fontoura, Dulce; Valent, Erik; Goebel, Max; Kardux, Kim; Falcão‐Pires, Inês; van der Velden, Jolanda

2017-01-01

Key points This paper describes a novel model that allows exploration of matrix‐induced cardiomyocyte adaptations independent of the passive effect of matrix rigidity on cardiomyocyte function.Detachment of adult cardiomyocytes from the matrix enables the study of matrix effects on cell shortening, Ca2+ handling and myofilament function.Cell shortening and Ca2+ handling are altered in cardiomyocytes cultured for 24 h on a stiff matrix.Matrix stiffness‐impaired cardiomyocyte contractility is reversed upon normalization of extracellular stiffness.Matrix stiffness‐induced reduction in unloaded shortening is more pronounced in cardiomyocytes isolated from obese ZSF1 rats with heart failure with preserved ejection fraction compared to lean ZSF1 rats. Abstract Extracellular matrix (ECM) stiffening is a key element of cardiac disease. Increased rigidity of the ECM passively inhibits cardiac contraction, but if and how matrix stiffening also actively alters cardiomyocyte contractility is incompletely understood. In vitro models designed to study cardiomyocyte–matrix interaction lack the possibility to separate passive inhibition by a stiff matrix from active matrix‐induced alterations of cardiomyocyte properties. Here we introduce a novel experimental model that allows exploration of cardiomyocyte functional alterations in response to matrix stiffening. Adult rat cardiomyocytes were cultured for 24 h on matrices of tuneable stiffness representing the healthy and the diseased heart and detached from their matrix before functional measurements. We demonstrate that matrix stiffening, independent of passive inhibition, reduces cell shortening and Ca2+ handling but does not alter myofilament‐generated force. Additionally, detachment of adult cultured cardiomyocytes allowed the transfer of cells from one matrix to another. This revealed that stiffness‐induced cardiomyocyte changes are reversed when matrix stiffness is normalized. These matrix stiffness‐induced changes in cardiomyocyte function could not be explained by adaptation in the microtubules. Additionally, cardiomyocytes isolated from stiff hearts of the obese ZSF1 rat model of heart failure with preserved ejection fraction show more pronounced reduction in unloaded shortening in response to matrix stiffening. Taken together, we introduce a method that allows evaluation of the influence of ECM properties on cardiomyocyte function separate from the passive inhibitory component of a stiff matrix. As such, it adds an important and physiologically relevant tool to investigate the functional consequences of cardiomyocyte–matrix interactions. PMID:28485491

Matrix viscoplasticity and its shielding by active mechanics in microtissue models: experiments and mathematical modeling

NASA Astrophysics Data System (ADS)

Liu, Alan S.; Wang, Hailong; Copeland, Craig R.; Chen, Christopher S.; Shenoy, Vivek B.; Reich, Daniel H.

2016-09-01

The biomechanical behavior of tissues under mechanical stimulation is critically important to physiological function. We report a combined experimental and modeling study of bioengineered 3D smooth muscle microtissues that reveals a previously unappreciated interaction between active cell mechanics and the viscoplastic properties of the extracellular matrix. The microtissues’ response to stretch/unstretch actuations, as probed by microcantilever force sensors, was dominated by cellular actomyosin dynamics. However, cell lysis revealed a viscoplastic response of the underlying model collagen/fibrin matrix. A model coupling Hill-type actomyosin dynamics with a plastic perfectly viscoplastic description of the matrix quantitatively accounts for the microtissue dynamics, including notably the cells’ shielding of the matrix plasticity. Stretch measurements of single cells confirmed the active cell dynamics, and were well described by a single-cell version of our model. These results reveal the need for new focus on matrix plasticity and its interactions with active cell mechanics in describing tissue dynamics.

Matrix viscoplasticity and its shielding by active mechanics in microtissue models: experiments and mathematical modeling

PubMed Central

Liu, Alan S.; Wang, Hailong; Copeland, Craig R.; Chen, Christopher S.; Shenoy, Vivek B.; Reich, Daniel H.

2016-01-01

The biomechanical behavior of tissues under mechanical stimulation is critically important to physiological function. We report a combined experimental and modeling study of bioengineered 3D smooth muscle microtissues that reveals a previously unappreciated interaction between active cell mechanics and the viscoplastic properties of the extracellular matrix. The microtissues’ response to stretch/unstretch actuations, as probed by microcantilever force sensors, was dominated by cellular actomyosin dynamics. However, cell lysis revealed a viscoplastic response of the underlying model collagen/fibrin matrix. A model coupling Hill-type actomyosin dynamics with a plastic perfectly viscoplastic description of the matrix quantitatively accounts for the microtissue dynamics, including notably the cells’ shielding of the matrix plasticity. Stretch measurements of single cells confirmed the active cell dynamics, and were well described by a single-cell version of our model. These results reveal the need for new focus on matrix plasticity and its interactions with active cell mechanics in describing tissue dynamics. PMID:27671239

Making maxillary barbels with a proximal-distal gradient of Wnt signals in matrix-bound mesenchymal cells

PubMed Central

Figueroa, Francisco; Singer, Susan S.; LeClair, Elizabeth E.

2015-01-01

The evolution of specific appendages is made possible by the ontogenetic deployment of general cell signaling pathways. Many fishes, amphibians and reptiles have unique skin appendages known as barbels, which are poorly understood at the cellular and molecular level. In this study, we examine the cell arrangements, cell division patterns, and gene expression profiles associated with the zebrafish maxillary barbel, or ZMB. The earliest cellular organization of the ZMB is an internal whorl of mesenchymal cells in the dermis of the maxilla; there is no epithelial placode, nor any axially-elongated epithelial cells as expected of an apical ectodermal ridge (AER). As the ZMB develops, cells in S-phase are at first distributed randomly throughout the appendage, gradually transitioning to a proliferative population concentrated at the distal end. By observing ZMB ontogenetic stages in a Wnt-responsive transgenic reporter line, TCFsiam, we identified a strongly fluorescent mesenchymal cell layer within these developing appendages. Using an in vitro explant culture technique on developing barbel tissues, we co-localized the fluorescent label in these cells with the mitotic marker EdU. Surprisingly, TCF+ cells showed little proliferation, indicating a slow-cycling subpopulation. Transmission electron microscopy of the ZMB located the TCF+ cells in a single, circumferential layer within the barbel’s matrix core. Morphologically, these cells resemble fibroblasts or osteoblasts; in addition to their matrix-bound location, they are identified by their pancake-shaped nuclei, abundant rough endoplasmic reticulum, and cytoplasmic extensions into the surrounding extracellular matrix. Taken together, these features define a novel mesenchymal cell population in zebrafish, the ‘TCF+ core cells.’ A working model of barbel development is proposed, in which these minimally mitotic mesodermal cells produce collagenous matrix in response to ectodermally-derived Wnt signals deployed in a proximal-distal gradient along the appendage. This documents a novel mechanism of vertebrate appendage outgrowth. Similar genetic signals and cell behaviors may be responsible for the independent and repeated evolution of barbel structures in other fish species. PMID:26492827

State-Space System Realization with Input- and Output-Data Correlation

NASA Technical Reports Server (NTRS)

Juang, Jer-Nan

1997-01-01

This paper introduces a general version of the information matrix consisting of the autocorrelation and cross-correlation matrices of the shifted input and output data. Based on the concept of data correlation, a new system realization algorithm is developed to create a model directly from input and output data. The algorithm starts by computing a special type of correlation matrix derived from the information matrix. The special correlation matrix provides information on the system-observability matrix and the state-vector correlation. A system model is then developed from the observability matrix in conjunction with other algebraic manipulations. This approach leads to several different algorithms for computing system matrices for use in representing the system model. The relationship of the new algorithms with other realization algorithms in the time and frequency domains is established with matrix factorization of the information matrix. Several examples are given to illustrate the validity and usefulness of these new algorithms.

Current evidence on associations between the MMP-7 (-181A>G) polymorphism and digestive system cancer risk.

PubMed

Ke, Pan; Wu, Zhong-De; Wen, Hua-Song; Ying, Miao-Xiong; Long, Huo-Cheng; Qing, Liu-Guo

2013-01-01

Matrix metalloproteinases (MMPs) degrade various components of the extracellular matrix and functional polymorphisms in encoding genes may contribute to genetic susceptibility to many cancers. Up to now, associations between MMP-7 (-181A>G) and digestive system cancer risk have remained inconclusive. To better understand the role of the MMP-7 (-181A>G) genotype in digestive cancer development, we conducted this comprehensive meta-analysis encompassing 3,518 cases and 4,596 controls. Overall, the MMP-7 (-181A>G) polymorphism was associated with higher digestive system cancer risk on homozygote comparison (GG vs. AA, OR=1.21, 95% CI = 1.12-1.60) and in a dominant model (GG/GA vs. AA, OR=1.16, 95% CI =1.03-1.46). On subgroup analysis, this polymorphism was significantly linked to higher risks for gastric cancer (GG vs. AA, OR=1.22, 95% CI = 1.02- 1.46; GA vs. AA, OR=1.82, 95% CI =1.16-2.87; GG/GA vs. AA, OR=1.13, 95% CI =1.01-1.27; GG vs. GA/AA, OR= 1.25, 95% CI = 1.06-2.39. We also observed increased susceptibility to colorectal cancer and esophageal SCC in both homozygote (OR = 1.13, 95% CI = 1.06-1.26) and heterozygote comparisons (OR = 1.45, 95% CI = 1.11-1.91). In the stratified analysis by controls, significant effects were only observed in population-based studies (GA vs. AA, OR=1.16, 95% CI=1.08-1.50; GA/AA vs. GG, OR=1.10, 95% CI=1.01-1.72). According to the source of ethnicity, a significantly increased risk was found among Asian populations in the homozygote model (GG vs. AA, OR=1.40, 95% CI=1.12-1.69), heterozygote model (GA vs. AA, OR=1.26, 95% CI=1.02-1.51), and dominant model (GG/GA vs. AA, OR=1.18, 95% CI=1.08-1.55). Our findings suggest that the MMP-7 (-181A>G) polymorphism may be a risk factor for digestive system cancer, especially among Asian populations.

PREDICTING TWO-DIMENSIONAL STEADY-STATE SOIL FREEZING FRONTS USING THE CVBEM.

USGS Publications Warehouse

Hromadka, T.V.

1986-01-01

The complex variable boundary element method (CVBEM) is used instead of a real variable boundary element method due to the available modeling error evaluation techniques developed. The modeling accuracy is evaluated by the model-user in the determination of an approximative boundary upon which the CVBEM provides an exact solution. Although inhomogeneity (and anisotropy) can be included in the CVBEM model, the resulting fully populated matrix system quickly becomes large. Therefore in this paper, the domain is assumed homogeneous and isotropic except for differences in frozen and thawed conduction parameters on either side of the freezing front. The example problems presented were obtained by use of a popular 64K microcomputer (the current version of the program used in this study has the capacity to accommodate 30 nodal points).

The Impact of Goal Setting and Empowerment on Governmental Matrix Organizations

DTIC Science & Technology

1993-09-01

shared. In a study of matrix management, Eduardo Vasconcellos further describes various matrix structures in the Galbraith model. In a functional...Technology/LAR, Wright-Patterson AFB OH, 1992. Vasconcellos , Eduardo . "A Model For a Better Understanding of the Matrix Structure," IEEE Transactions on...project matrix, the project manager maintains more influence and the structure lies to the right-of center ( Vasconcellos , 1979:58). Different Types of

Efficient system modeling for a small animal PET scanner with tapered DOI detectors.

PubMed

Zhang, Mengxi; Zhou, Jian; Yang, Yongfeng; Rodríguez-Villafuerte, Mercedes; Qi, Jinyi

2016-01-21

A prototype small animal positron emission tomography (PET) scanner for mouse brain imaging has been developed at UC Davis. The new scanner uses tapered detector arrays with depth of interaction (DOI) measurement. In this paper, we present an efficient system model for the tapered PET scanner using matrix factorization and a virtual scanner geometry. The factored system matrix mainly consists of two components: a sinogram blurring matrix and a geometrical matrix. The geometric matrix is based on a virtual scanner geometry. The sinogram blurring matrix is estimated by matrix factorization. We investigate the performance of different virtual scanner geometries. Both simulation study and real data experiments are performed in the fully 3D mode to study the image quality under different system models. The results indicate that the proposed matrix factorization can maintain image quality while substantially reduce the image reconstruction time and system matrix storage cost. The proposed method can be also applied to other PET scanners with DOI measurement.

Method of confidence domains in the analysis of noise-induced extinction for tritrophic population system

NASA Astrophysics Data System (ADS)

Bashkirtseva, Irina; Ryashko, Lev; Ryazanova, Tatyana

2017-09-01

A problem of the analysis of the noise-induced extinction in multidimensional population systems is considered. For the investigation of conditions of the extinction caused by random disturbances, a new approach based on the stochastic sensitivity function technique and confidence domains is suggested, and applied to tritrophic population model of interacting prey, predator and top predator. This approach allows us to analyze constructively the probabilistic mechanisms of the transition to the noise-induced extinction from both equilibrium and oscillatory regimes of coexistence. In this analysis, a method of principal directions for the reducing of the dimension of confidence domains is suggested. In the dispersion of random states, the principal subspace is defined by the ratio of eigenvalues of the stochastic sensitivity matrix. A detailed analysis of two scenarios of the noise-induced extinction in dependence on parameters of considered tritrophic system is carried out.

Asymptotic Linear Spectral Statistics for Spiked Hermitian Random Matrices

NASA Astrophysics Data System (ADS)

Passemier, Damien; McKay, Matthew R.; Chen, Yang

2015-07-01

Using the Coulomb Fluid method, this paper derives central limit theorems (CLTs) for linear spectral statistics of three "spiked" Hermitian random matrix ensembles. These include Johnstone's spiked model (i.e., central Wishart with spiked correlation), non-central Wishart with rank-one non-centrality, and a related class of non-central matrices. For a generic linear statistic, we derive simple and explicit CLT expressions as the matrix dimensions grow large. For all three ensembles under consideration, we find that the primary effect of the spike is to introduce an correction term to the asymptotic mean of the linear spectral statistic, which we characterize with simple formulas. The utility of our proposed framework is demonstrated through application to three different linear statistics problems: the classical likelihood ratio test for a population covariance, the capacity analysis of multi-antenna wireless communication systems with a line-of-sight transmission path, and a classical multiple sample significance testing problem.

Exploring the Association Between Rosacea and Parkinson Disease: A Danish Nationwide Cohort Study.

PubMed

Egeberg, Alexander; Hansen, Peter Riis; Gislason, Gunnar H; Thyssen, Jacob P

2016-05-01

The pathogenesis of rosacea is unclear, but increased matrix metalloproteinase target tissue activity appears to play an important role. Parkinson disease and other neurodegenerative disorders also display increased matrix metalloproteinase activity that contribute to neuronal loss. To investigate the risk of incident (new-onset) Parkinson disease in patients with rosacea. A nationwide cohort study of the Danish population was conducted using individual-level linkage of administrative registers. All Danish citizens 18 years or older from January 1, 1997, to December 31, 2011 (N = 5 472 745), were included. Data analysis was conducted from June 26 to July 27, 2015. The main outcome was a diagnosis of Parkinson disease. Incidence rates (IRs) per 10 000 person-years were calculated, and incidence rate ratios (IRRs) adjusted for age, sex, socioeconomic status, smoking, alcohol abuse, medication, and comorbidity were estimated by Poisson regression models. A total of 5 404 692 individuals were included in the reference population; of these, 22 387 individuals (9812 [43.8%] women; mean [SD] age at diagnosis, 75.9 [10.2] years) received a diagnosis of Parkinson disease during the study period and 68 053 individuals (45 712 [67.2%] women; mean age, 42.2 [16.5] years) were registered as having rosacea. The IRs of Parkinson disease per 10 000 person-years were 3.54 (95% CI, 3.49-3.59) in the reference population and 7.62 (95% CI, 6.78-8.57) in patients with rosacea. The adjusted IRR of Parkinson disease was 1.71 (95%, CI 1.52-1.92) in patients with rosacea compared with the reference population. There was a 2-fold increased risk of Parkinson disease in patients classified as having ocular rosacea (adjusted IRR, 2.03 [95% CI, 1.67-2.48]), and tetracycline therapy appeared to reduce the risk of Parkinson disease (adjusted IRR, 0.98 [95% CI, 0.97-0.99]). Rosacea constitutes an independent risk factor for Parkinson disease. This association could be due to shared pathogenic mechanisms involving elevated matrix metalloproteinase activity. The clinical consequences of this association require further study.

Integrating copper toxicity and climate change to understand extinction risk to two species of pond-breeding anurans.

PubMed

Weir, Scott M; Scott, David E; Salice, Christopher J; Lance, Stacey L

2016-09-01

Chemical contamination is often suggested as an important contributing factor to amphibian population declines, but direct links are rarely reported. Population modeling provides a quantitative method to integrate toxicity data with demographic data to understand the long-term effects of contaminants on population persistence. In this study we use laboratory-derived embryo and larval toxicity data for two anuran species to investigate the potential for toxicity to contribute to population declines. We use the southern toad (Anaxyrus terrestris) and the southern leopard frog (Lithobates sphenocephalus) as model species to investigate copper (Cu) toxicity. We use matrix models to project populations through time and quantify extinction risk (the probability of quasi-extinction in 35 yr). Life-history parameters for toads and frogs were obtained from previously published literature or unpublished data from a long-term (>35 yr) data set. In addition to Cu toxicity, we investigate the role of climate change on amphibian populations by including the probability of early pond drying that results in catastrophic reproductive failure (CRF, i.e., complete mortality of all larval individuals). Our models indicate that CRF is an important parameter for both species as both were unable to persist when CRF probability was >50% for toads or 40% for frogs. Copper toxicity alone did not result in significant effects on extinction risk unless toxicity was very high (>50% reduction in survival parameters). For toads, Cu toxicity and high probability of CRF both resulted in high extinction risk but no synergistic (or greater than additive) effects between the two stressors occurred. For leopard frogs, in the absence of CRF survival was high even under Cu toxicity, but with CRF Cu toxicity increased extinction risk. Our analyses highlight the importance of considering multiple stressors as well as species differences in response to those stressors. Our models were consistently most sensitive to juvenile and adult survival, further suggesting the importance of terrestrial stages to population persistence. Future models will incorporate multiple wetlands with different combinations of stressors to understand if our results for a single wetland result in a population sink within the landscape. © 2016 by the Ecological Society of America.

In vitro model to study the effects of matrix stiffening on Ca2+ handling and myofilament function in isolated adult rat cardiomyocytes.

PubMed

van Deel, Elza D; Najafi, Aref; Fontoura, Dulce; Valent, Erik; Goebel, Max; Kardux, Kim; Falcão-Pires, Inês; van der Velden, Jolanda

2017-07-15

This paper describes a novel model that allows exploration of matrix-induced cardiomyocyte adaptations independent of the passive effect of matrix rigidity on cardiomyocyte function. Detachment of adult cardiomyocytes from the matrix enables the study of matrix effects on cell shortening, Ca 2+ handling and myofilament function. Cell shortening and Ca 2+ handling are altered in cardiomyocytes cultured for 24 h on a stiff matrix. Matrix stiffness-impaired cardiomyocyte contractility is reversed upon normalization of extracellular stiffness. Matrix stiffness-induced reduction in unloaded shortening is more pronounced in cardiomyocytes isolated from obese ZSF1 rats with heart failure with preserved ejection fraction compared to lean ZSF1 rats. Extracellular matrix (ECM) stiffening is a key element of cardiac disease. Increased rigidity of the ECM passively inhibits cardiac contraction, but if and how matrix stiffening also actively alters cardiomyocyte contractility is incompletely understood. In vitro models designed to study cardiomyocyte-matrix interaction lack the possibility to separate passive inhibition by a stiff matrix from active matrix-induced alterations of cardiomyocyte properties. Here we introduce a novel experimental model that allows exploration of cardiomyocyte functional alterations in response to matrix stiffening. Adult rat cardiomyocytes were cultured for 24 h on matrices of tuneable stiffness representing the healthy and the diseased heart and detached from their matrix before functional measurements. We demonstrate that matrix stiffening, independent of passive inhibition, reduces cell shortening and Ca 2+ handling but does not alter myofilament-generated force. Additionally, detachment of adult cultured cardiomyocytes allowed the transfer of cells from one matrix to another. This revealed that stiffness-induced cardiomyocyte changes are reversed when matrix stiffness is normalized. These matrix stiffness-induced changes in cardiomyocyte function could not be explained by adaptation in the microtubules. Additionally, cardiomyocytes isolated from stiff hearts of the obese ZSF1 rat model of heart failure with preserved ejection fraction show more pronounced reduction in unloaded shortening in response to matrix stiffening. Taken together, we introduce a method that allows evaluation of the influence of ECM properties on cardiomyocyte function separate from the passive inhibitory component of a stiff matrix. As such, it adds an important and physiologically relevant tool to investigate the functional consequences of cardiomyocyte-matrix interactions. © 2017 The Authors. The Journal of Physiology published by John Wiley & Sons Ltd on behalf of The Physiological Society.

Fibroblasts and the extracellular matrix in right ventricular disease.

PubMed

Frangogiannis, Nikolaos G

2017-10-01

Right ventricular failure predicts adverse outcome in patients with pulmonary hypertension (PH), and in subjects with left ventricular heart failure and is associated with interstitial fibrosis. This review manuscript discusses the cellular effectors and molecular mechanisms implicated in right ventricular fibrosis. The right ventricular interstitium contains vascular cells, fibroblasts, and immune cells, enmeshed in a collagen-based matrix. Right ventricular pressure overload in PH is associated with the expansion of the fibroblast population, myofibroblast activation, and secretion of extracellular matrix proteins. Mechanosensitive transduction of adrenergic signalling and stimulation of the renin-angiotensin-aldosterone cascade trigger the activation of right ventricular fibroblasts. Inflammatory cytokines and chemokines may contribute to expansion and activation of macrophages that may serve as a source of fibrogenic growth factors, such as transforming growth factor (TGF)-β. Endothelin-1, TGF-βs, and matricellular proteins co-operate to activate cardiac myofibroblasts, and promote synthesis of matrix proteins. In comparison with the left ventricle, the RV tolerates well volume overload and ischemia; whether the right ventricular interstitial cells and matrix are implicated in these favourable responses remains unknown. Expansion of fibroblasts and extracellular matrix protein deposition are prominent features of arrhythmogenic right ventricular cardiomyopathies and may be implicated in the pathogenesis of arrhythmic events. Prevailing conceptual paradigms on right ventricular remodelling are based on extrapolation of findings in models of left ventricular injury. Considering the unique embryologic, morphological, and physiologic properties of the RV and the clinical significance of right ventricular failure, there is a need further to dissect RV-specific mechanisms of fibrosis and interstitial remodelling. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For permissions, please email: journals.permissions@oup.com.

Spreading of Cholera through Surface Water

NASA Astrophysics Data System (ADS)

Bertuzzo, E.; Casagrandi, R.; Gatto, M.; Rodriguez-Iturbe, I.; Rinaldo, A.

2009-12-01

Cholera epidemics are still a major public health concern to date in many areas of the world. In order to understand and forecast cholera outbreaks, one of the most important factors is the role played by the environmental matrix in which the disease spreads. We study how river networks, acting as environmental corridors for pathogens, affect the spreading of cholera epidemics. The environmental matrix in which the disease spreads is constituted by different human communities and their hydrologic interconnections. Each community is characterized by its spatial position, population size, water resources availability and hygiene conditions. By implementing a spatially explicit cholera model we seek the effects on epidemic dynamics of: i) the topology and metrics of the pathogens pathways that connect different communities; ii) the spatial distribution of the population size; and iii) the spatial distributions and quality of surface water resources and public health conditions, and how they vary with population size. The model has been applied to study the space-time evolution of a well documented cholera epidemic occurred in the KwaZulu-Natal province of South Africa. The epidemic lasted for two years and involved about 140,000 confirmed cholera cases. The model does well in reproducing the distribution of the cholera cases during the two outbreaks as well as their spatial spreading. We further extend the model by deriving the speed of propagation of traveling fronts in the case of uniformly distributed systems for different topologies: one and two dimensional lattices and river networks. The derivation of the spreading celerity proves instrumental in establishing the overall conditions for the relevance of spatially explicit models. The conditions are sought by comparison between spreading and disease timescales. Consider a cholera epidemic that starts from a point and spreads throughout a finite size system, it is possible to identify two different timescales: i) the spreading timescale, that is the time needed for the disease to spread and involve all the communities in the system; and ii) the epidemic timescale, defined by the duration of the epidemic in a single community. Our results suggest that in many cases of real-life epidemiological interest, timescales of disease dynamics may trigger outbreaks that significantly depart from the predictions of classical space-implicit compartmental models.

Matrix approach to land carbon cycle modeling: A case study with the Community Land Model.

PubMed

Huang, Yuanyuan; Lu, Xingjie; Shi, Zheng; Lawrence, David; Koven, Charles D; Xia, Jianyang; Du, Zhenggang; Kluzek, Erik; Luo, Yiqi

2018-03-01

The terrestrial carbon (C) cycle has been commonly represented by a series of C balance equations to track C influxes into and effluxes out of individual pools in earth system models (ESMs). This representation matches our understanding of C cycle processes well but makes it difficult to track model behaviors. It is also computationally expensive, limiting the ability to conduct comprehensive parametric sensitivity analyses. To overcome these challenges, we have developed a matrix approach, which reorganizes the C balance equations in the original ESM into one matrix equation without changing any modeled C cycle processes and mechanisms. We applied the matrix approach to the Community Land Model (CLM4.5) with vertically-resolved biogeochemistry. The matrix equation exactly reproduces litter and soil organic carbon (SOC) dynamics of the standard CLM4.5 across different spatial-temporal scales. The matrix approach enables effective diagnosis of system properties such as C residence time and attribution of global change impacts to relevant processes. We illustrated, for example, the impacts of CO 2 fertilization on litter and SOC dynamics can be easily decomposed into the relative contributions from C input, allocation of external C into different C pools, nitrogen regulation, altered soil environmental conditions, and vertical mixing along the soil profile. In addition, the matrix tool can accelerate model spin-up, permit thorough parametric sensitivity tests, enable pool-based data assimilation, and facilitate tracking and benchmarking of model behaviors. Overall, the matrix approach can make a broad range of future modeling activities more efficient and effective. © 2017 John Wiley & Sons Ltd.

Tigers in the Terai: Strong evidence for meta-population dynamics contributing to tiger recovery and conservation in the Terai Arc Landscape.

PubMed

Thapa, Kanchan; Wikramanayake, Eric; Malla, Sabita; Acharya, Krishna Prasad; Lamichhane, Babu Ram; Subedi, Naresh; Pokharel, Chiranjivi Prasad; Thapa, Gokarna Jung; Dhakal, Maheshwar; Bista, Ashish; Borah, Jimmy; Gupta, Mudit; Maurya, Kamlesh K; Gurung, Ghana Shyam; Jnawali, Shant Raj; Pradhan, Narendra Man Babu; Bhata, Shiv Raj; Koirala, Saroj; Ghose, Dipankar; Vattakaven, Joseph

2017-01-01

The source populations of tigers are mostly confined to protected areas, which are now becoming isolated. A landscape scale conservation strategy should strive to facilitate dispersal and survival of dispersing tigers by managing habitat corridors that enable tigers to traverse the matrix with minimal conflict. We present evidence for tiger dispersal along transboundary protected areas complexes in the Terai Arc Landscape, a priority tiger landscape in Nepal and India, by comparing camera trap data, and through population models applied to the long term camera trap data sets. The former showed that 11 individual tigers used the corridors that connected the transboundary protected areas. The estimated population growth rates using the minimum observed population size in two protected areas in Nepal, Bardia National Park and Suklaphanta National Park showed that the increases were higher than expected from growth rates due to in situ reproduction alone. These lines of evidence suggests that tigers are recolonizing Nepal's protected areas from India, after a period of population decline, and that the tiger populations in the transboundary protected areas complexes may be maintained as meta-population. Our results demonstrate the importance of adopting a landscape-scale approach to tiger conservation, especially to improve population recovery and long term population persistence.

Tigers in the Terai: Strong evidence for meta-population dynamics contributing to tiger recovery and conservation in the Terai Arc Landscape

PubMed Central

Wikramanayake, Eric; Malla, Sabita; Acharya, Krishna Prasad; Lamichhane, Babu Ram; Subedi, Naresh; Pokharel, Chiranjivi Prasad; Thapa, Gokarna Jung; Dhakal, Maheshwar; Bista, Ashish; Borah, Jimmy; Gupta, Mudit; Maurya, Kamlesh K.; Gurung, Ghana Shyam; Jnawali, Shant Raj; Pradhan, Narendra Man Babu; Bhata, Shiv Raj; Koirala, Saroj; Ghose, Dipankar; Vattakaven, Joseph

2017-01-01

The source populations of tigers are mostly confined to protected areas, which are now becoming isolated. A landscape scale conservation strategy should strive to facilitate dispersal and survival of dispersing tigers by managing habitat corridors that enable tigers to traverse the matrix with minimal conflict. We present evidence for tiger dispersal along transboundary protected areas complexes in the Terai Arc Landscape, a priority tiger landscape in Nepal and India, by comparing camera trap data, and through population models applied to the long term camera trap data sets. The former showed that 11 individual tigers used the corridors that connected the transboundary protected areas. The estimated population growth rates using the minimum observed population size in two protected areas in Nepal, Bardia National Park and Suklaphanta National Park showed that the increases were higher than expected from growth rates due to in situ reproduction alone. These lines of evidence suggests that tigers are recolonizing Nepal’s protected areas from India, after a period of population decline, and that the tiger populations in the transboundary protected areas complexes may be maintained as meta-population. Our results demonstrate the importance of adopting a landscape-scale approach to tiger conservation, especially to improve population recovery and long term population persistence. PMID:28591175

Adult survival and population growth rate in Colorado big brown bats (Eptesicus fuscus)

USGS Publications Warehouse

O'Shea, T.J.; Ellison, L.E.; Stanley, T.R.

2011-01-01

We studied adult survival and population growth at multiple maternity colonies of big brown bats (Eptesicus fuscus) in Fort Collins, Colorado. We investigated hypotheses about survival using information-theoretic methods and mark-recapture analyses based on passive detection of adult females tagged with passive integrated transponders. We constructed a 3-stage life-history matrix model to estimate population growth rate (??) and assessed the relative importance of adult survival and other life-history parameters to population growth through elasticity and sensitivity analysis. Annual adult survival at 5 maternity colonies monitored from 2001 to 2005 was estimated at 0.79 (95% confidence interval [95% CI] = 0.77-0.82). Adult survival varied by year and roost, with low survival during an extreme drought year, a finding with negative implications for bat populations because of the likelihood of increasing drought in western North America due to global climate change. Adult survival during winter was higher than in summer, and mean life expectancies calculated from survival estimates were lower than maximum longevity records. We modeled adult survival with recruitment parameter estimates from the same population. The study population was growing (?? = 1.096; 95% CI = 1.057-1.135). Adult survival was the most important demographic parameter for population growth. Growth clearly had the highest elasticity to adult survival, followed by juvenile survival and adult fecundity (approximately equivalent in rank). Elasticity was lowest for fecundity of yearlings. The relative importances of the various life-history parameters for population growth rate are similar to those of large mammals. ?? 2011 American Society of Mammalogists.

Local stresses in metal matrix composites subjected to thermal and mechanical loading

NASA Technical Reports Server (NTRS)

Highsmith, Alton L.; Shin, Donghee; Naik, Rajiv A.

1990-01-01

An elasticity solution has been used to analyze matrix stresses near the fiber/matrix interface in continuous fiber-reinforced metal-matrix composites, modeling the micromechanics in question in terms of a cylindrical fiber and cylindrical matrix sheath which is embedded in an orthotropic medium representing the composite. The model's predictions for lamina thermal and mechanical properties are applied to a laminate analysis determining ply-level stresses due to thermomechanical loading. A comparison is made between these results, which assume cylindrical symmetry, and the predictions yielded by a FEM model in which the fibers are arranged in a square array.

Endemic chronic wasting disease causes mule deer population decline in Wyoming.

PubMed

DeVivo, Melia T; Edmunds, David R; Kauffman, Matthew J; Schumaker, Brant A; Binfet, Justin; Kreeger, Terry J; Richards, Bryan J; Schätzl, Hermann M; Cornish, Todd E

2017-01-01

Chronic wasting disease (CWD) is a fatal transmissible spongiform encephalopathy affecting white-tailed deer (Odocoileus virginianus), mule deer (Odocoileus hemionus), Rocky Mountain elk (Cervus elaphus nelsoni), and moose (Alces alces shirasi) in North America. In southeastern Wyoming average annual CWD prevalence in mule deer exceeds 20% and appears to contribute to regional population declines. We determined the effect of CWD on mule deer demography using age-specific, female-only, CWD transition matrix models to estimate the population growth rate (λ). Mule deer were captured from 2010-2014 in southern Converse County Wyoming, USA. Captured adult (≥ 1.5 years old) deer were tested ante-mortem for CWD using tonsil biopsies and monitored using radio telemetry. Mean annual survival rates of CWD-negative and CWD-positive deer were 0.76 and 0.32, respectively. Pregnancy and fawn recruitment were not observed to be influenced by CWD. We estimated λ = 0.79, indicating an annual population decline of 21% under current CWD prevalence levels. A model derived from the demography of only CWD-negative individuals yielded; λ = 1.00, indicating a stable population if CWD were absent. These findings support CWD as a significant contributor to mule deer population decline. Chronic wasting disease is difficult or impossible to eradicate with current tools, given significant environmental contamination, and at present our best recommendation for control of this disease is to minimize spread to new areas and naïve cervid populations.

Endemic chronic wasting disease causes mule deer population decline in Wyoming

PubMed Central

DeVivo, Melia T.; Edmunds, David R.; Kauffman, Matthew J.; Schumaker, Brant A.; Binfet, Justin; Kreeger, Terry J.; Richards, Bryan J.; Schätzl, Hermann M.; Cornish, Todd E.

2017-01-01

Chronic wasting disease (CWD) is a fatal transmissible spongiform encephalopathy affecting white-tailed deer (Odocoileus virginianus), mule deer (Odocoileus hemionus), Rocky Mountain elk (Cervus elaphus nelsoni), and moose (Alces alces shirasi) in North America. In southeastern Wyoming average annual CWD prevalence in mule deer exceeds 20% and appears to contribute to regional population declines. We determined the effect of CWD on mule deer demography using age-specific, female-only, CWD transition matrix models to estimate the population growth rate (λ). Mule deer were captured from 2010–2014 in southern Converse County Wyoming, USA. Captured adult (≥ 1.5 years old) deer were tested ante-mortem for CWD using tonsil biopsies and monitored using radio telemetry. Mean annual survival rates of CWD-negative and CWD-positive deer were 0.76 and 0.32, respectively. Pregnancy and fawn recruitment were not observed to be influenced by CWD. We estimated λ = 0.79, indicating an annual population decline of 21% under current CWD prevalence levels. A model derived from the demography of only CWD-negative individuals yielded; λ = 1.00, indicating a stable population if CWD were absent. These findings support CWD as a significant contributor to mule deer population decline. Chronic wasting disease is difficult or impossible to eradicate with current tools, given significant environmental contamination, and at present our best recommendation for control of this disease is to minimize spread to new areas and naïve cervid populations. PMID:29049389

Endemic chronic wasting disease causes mule deer population decline in Wyoming

USGS Publications Warehouse

DeVivo, Melia T.; Edmunds, David R.; Kauffman, Matthew J.; Schumaker, Brant A.; Binfet, Justin; Kreeger, Terry J.; Richards, Bryan J.; Schatzl, Hermann M.; Cornish, Todd

2017-01-01

Chronic wasting disease (CWD) is a fatal transmissible spongiform encephalopathy affecting white-tailed deer (Odocoileus virginianus), mule deer (Odocoileus hemionus), Rocky Mountain elk (Cervus elaphus nelsoni), and moose (Alces alces shirasi) in North America. In southeastern Wyoming average annual CWD prevalence in mule deer exceeds 20% and appears to contribute to regional population declines. We determined the effect of CWD on mule deer demography using age-specific, female-only, CWD transition matrix models to estimate the population growth rate (λ). Mule deer were captured from 2010–2014 in southern Converse County Wyoming, USA. Captured adult (≥ 1.5 years old) deer were tested ante-mortem for CWD using tonsil biopsies and monitored using radio telemetry. Mean annual survival rates of CWD-negative and CWD-positive deer were 0.76 and 0.32, respectively. Pregnancy and fawn recruitment were not observed to be influenced by CWD. We estimated λ= 0.79, indicating an annual population decline of 21% under current CWD prevalence levels. A model derived from the demography of only CWD-negative individuals yielded; λ = 1.00, indicating a stable population if CWD were absent. These findings support CWD as a significant contributor to mule deer population decline. Chronic wasting disease is difficult or impossible to eradicate with current tools, given significant environmental contamination, and at present our best recommendation for control of this disease is to minimize spread to new areas and naïve cervid populations.

Comparison Of Models Of Metal-Matrix Composites

NASA Technical Reports Server (NTRS)

Bigelow, C. A.; Johnson, W. S.; Naik, R. A.

1994-01-01

Report presents comparative review of four mathematical models of micromechanical behaviors of fiber/metal-matrix composite materials. Models differ in various details, all based on properties of fiber and matrix constituent materials, all involve square arrays of fibers continuous and parallel and all assume complete bonding between constituents. Computer programs implementing models used to predict properties and stress-vs.-strain behaviors of unidirectional- and cross-ply laminated composites made of boron fibers in aluminum matrices and silicon carbide fibers in titanium matrices. Stresses in fiber and matrix constituent materials also predicted.

Unified continuum damage model for matrix cracking in composite rotor blades

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

Pollayi, Hemaraju; Harursampath, Dineshkumar

This paper deals with modeling of the first damage mode, matrix micro-cracking, in helicopter rotor/wind turbine blades and how this effects the overall cross-sectional stiffness. The helicopter/wind turbine rotor system operates in a highly dynamic and unsteady environment leading to severe vibratory loads present in the system. Repeated exposure to this loading condition can induce damage in the composite rotor blades. These rotor/turbine blades are generally made of fiber-reinforced laminated composites and exhibit various competing modes of damage such as matrix micro-cracking, delamination, and fiber breakage. There is a need to study the behavior of the composite rotor system undermore » various key damage modes in composite materials for developing Structural Health Monitoring (SHM) system. Each blade is modeled as a beam based on geometrically non-linear 3-D elasticity theory. Each blade thus splits into 2-D analyzes of cross-sections and non-linear 1-D analyzes along the beam reference curves. Two different tools are used here for complete 3-D analysis: VABS for 2-D cross-sectional analysis and GEBT for 1-D beam analysis. The physically-based failure models for matrix in compression and tension loading are used in the present work. Matrix cracking is detected using two failure criterion: Matrix Failure in Compression and Matrix Failure in Tension which are based on the recovered field. A strain variable is set which drives the damage variable for matrix cracking and this damage variable is used to estimate the reduced cross-sectional stiffness. The matrix micro-cracking is performed in two different approaches: (i) Element-wise, and (ii) Node-wise. The procedure presented in this paper is implemented in VABS as matrix micro-cracking modeling module. Three examples are presented to investigate the matrix failure model which illustrate the effect of matrix cracking on cross-sectional stiffness by varying the applied cyclic load.« less

Optimum 3D Matrix Stiffness for Maintenance of Cancer Stem Cells Is Dependent on Tissue Origin of Cancer Cells

PubMed Central

Jabbari, Esmaiel; Sarvestani, Samaneh K.; Daneshian, Leily; Moeinzadeh, Seyedsina

2015-01-01

Introduction The growth and expression of cancer stem cells (CSCs) depend on many factors in the tumor microenvironment. The objective of this work was to investigate the effect of cancer cells’ tissue origin on the optimum matrix stiffness for CSC growth and marker expression in a model polyethylene glycol diacrylate (PEGDA) hydrogel without the interference of other factors in the microenvironment. Methods Human MCF7 and MDA-MB-231 breast carcinoma, HCT116 colorectal and AGS gastric carcinoma, and U2OS osteosarcoma cells were used. The cells were encapsulated in PEGDA gels with compressive moduli in the 2-70 kPa range and optimized cell seeding density of 0.6x106 cells/mL. Micropatterning was used to optimize the growth of encapsulated cells with respect to average tumorsphere size. The CSC sub-population of the encapsulated cells was characterized by cell number, tumorsphere size and number density, and mRNA expression of CSC markers. Results The optimum matrix stiffness for growth and marker expression of CSC sub-population of cancer cells was 5 kPa for breast MCF7 and MDA231, 25 kPa for colorectal HCT116 and gastric AGS, and 50 kPa for bone U2OS cells. Conjugation of a CD44 binding peptide to the gel stopped tumorsphere formation by cancer cells from different tissue origin. The expression of YAP/TAZ transcription factors by the encapsulated cancer cells was highest at the optimum stiffness indicating a link between the Hippo transducers and CSC growth. The optimum average tumorsphere size for CSC growth and marker expression was 50 μm. Conclusion The marker expression results suggest that the CSC sub-population of cancer cells resides within a niche with optimum stiffness which depends on the cancer cells’ tissue origin. PMID:26168187

Solution to urn models of pairwise interaction with application to social, physical, and biological sciences

NASA Astrophysics Data System (ADS)

Pickering, William; Lim, Chjan

2017-07-01

We investigate a family of urn models that correspond to one-dimensional random walks with quadratic transition probabilities that have highly diverse applications. Well-known instances of these two-urn models are the Ehrenfest model of molecular diffusion, the voter model of social influence, and the Moran model of population genetics. We also provide a generating function method for diagonalizing the corresponding transition matrix that is valid if and only if the underlying mean density satisfies a linear differential equation and express the eigenvector components as terms of ordinary hypergeometric functions. The nature of the models lead to a natural extension to interaction between agents in a general network topology. We analyze the dynamics on uncorrelated heterogeneous degree sequence networks and relate the convergence times to the moments of the degree sequences for various pairwise interaction mechanisms.

Neutron diffraction measurements and modeling of residual strains in metal matrix composites

NASA Technical Reports Server (NTRS)

Saigal, A.; Leisk, G. G.; Hubbard, C. R.; Misture, S. T.; Wang, X. L.

1996-01-01

Neutron diffraction measurements at room temperature are used to characterize the residual strains in tungsten fiber-reinforced copper matrix, tungsten fiber-reinforced Kanthal matrix, and diamond particulate-reinforced copper matrix composites. Results of finite element modeling are compared with the neutron diffraction data. In tungsten/Kanthal composites, the fibers are in compression, the matrix is in tension, and the thermal residual strains are a strong function of the volume fraction of fibers. In copper matrix composites, the matrix is in tension and the stresses are independent of the volume fraction of tungsten fibers or diamond particles and the assumed stress free temperature because of the low yield strength of the matrix phase.

Understanding the Evolution and Stability of the G-Matrix

PubMed Central

Arnold, Stevan J.; Bürger, Reinhard; Hohenlohe, Paul A.; Ajie, Beverley C.; Jones, Adam G.

2011-01-01

The G-matrix summarizes the inheritance of multiple, phenotypic traits. The stability and evolution of this matrix are important issues because they affect our ability to predict how the phenotypic traits evolve by selection and drift. Despite the centrality of these issues, comparative, experimental, and analytical approaches to understanding the stability and evolution of the G-matrix have met with limited success. Nevertheless, empirical studies often find that certain structural features of the matrix are remarkably constant, suggesting that persistent selection regimes or other factors promote stability. On the theoretical side, no one has been able to derive equations that would relate stability of the G-matrix to selection regimes, population size, migration, or to the details of genetic architecture. Recent simulation studies of evolving G-matrices offer solutions to some of these problems, as well as a deeper, synthetic understanding of both the G-matrix and adaptive radiations. PMID:18973631

Effects of Orbital Lifetime Reduction on the Long-Term Earth Satellite Population as Modeled by EVOLVE 4.0

NASA Technical Reports Server (NTRS)

Krisko, Paula H.; Opiela, John N.; Liou, Jer-Chyi; Anz-Meador, Phillip D.; Theall, Jeffrey R.

1999-01-01

The latest update of the NASA orbital debris environment model, EVOLVE 4.0, has been used to study the effect of various proposed debris mitigation measures, including the NASA 25-year guideline. EVOLVE 4.0, which includes updates of the NASA breakup, solar activity, and the orbit propagator models, a GEO analysis option, and non-fragmentation debris source models, allows for the statistical modeling and predicted growth of the particle population >1 mm in characteristic length in LEO and GEO orbits. The initial implementation of this &odel has been to study the sensitivity of the overall LEO debris environment to mitigation measures designed to limit the lifetime of intact objects in LEO orbits. The mitigation measures test matrix for this study included several commonly accepted testing schemes, i.e., the variance of the maximum LEO lifetime from 10 to 50 years, the date of the initial implementation of this policy, the shut off of all explosions at some specified date, and the inclusion of disposal orbits. All are timely studies in that all scenarios have been suggested by researchers and satellite operators as options for the removal of debris from LEO orbits.

Characterizing species interactions to understand press perturbations: What is the community matrix?

USGS Publications Warehouse

Novak, Mark; Yeakel, Justin D.; Noble, Andrew E.; Doak, Daniel F.; Emmerson, Mark; Estes, James A.; Jacob, Ute; Tinker, M. Tim; Wootton, J. Timothy

2016-01-01

The community matrix is among ecology's most important mathematical abstractions, formally encapsulating the interconnected network of effects that species have on one another's populations. Despite its importance, the term `community matrix' has been applied to matrices having differing interpretations. This has hindered the application of theory for understanding community structure and perturbation responses, particularly in the contexts of ecosystem-based management and conservation. Here we clarify the correspondence and distinctions between the Interaction matrix, the Alpha matrix and the Jacobian matrix, terms which are frequently used interchangeably and have numerous synonyms, including the term Community matrix. We illustrate how these matrices correspond to different ways of characterizing interaction strengths, how they permit insights regarding different types of press perturbations of species growth rates or abundances, and how these are related by a simple scaling relationship. Connections to additional interaction strength characterizations encapsulated by the Beta matrix, the Gamma matrix, and the Removal matrix are also discussed. Our synthesis highlights the empirical challenges that remain in using these mathematical tools to understand actual communities.

Micro-mechanics modelling of smart materials

NASA Astrophysics Data System (ADS)

Shah, Syed Asim Ali

Metal Matrix ceramic-reinforced composites are rapidly becoming strong candidates as structural materials for many high temperature and engineering applications. Metal matrix composites (MMC) combine the ductile properties of the matrix with a brittle phase of the reinforcement, leading to high stiffness and strength with a reduction in structural weight. The main objective of using a metal matrix composite system is to increase service temperature or improve specific mechanical properties of structural components by replacing existing super alloys.The purpose of the study is to investigate, develop and implement second phase reinforcement alloy strengthening empirical model with SiCp reinforced A359 aluminium alloy composites on the particle-matrix interface and the overall mechanical properties of the material.To predict the interfacial fracture strength of aluminium, in the presence of silicon segregation, an empirical model has been modified. This model considers the interfacial energy caused by segregation of impurities at the interface and uses Griffith crack type arguments to predict the formation energies of impurities at the interface. Based on this, model simulations were conducted at nano scale specifically at the interface and the interfacial strengthening behaviour of reinforced aluminium alloy system was expressed in terms of elastic modulus.The numerical model shows success in making prediction possible of trends in relation to segregation and interfacial fracture strength behaviour in SiC particle-reinforced aluminium matrix composites. The simulation models using various micro scale modelling techniques to the aluminum alloy matrix composite, strengthenedwith varying amounts of silicon carbide particulate were done to predict the material state at critical points with properties of Al-SiC which had been heat treated.In this study an algorithm is developed to model a hard ceramic particle in a soft matrix with a clear distinct interface and a strain based relationship has been proposed for the strengthening behaviour of the MMC at the interface rather than stress based, by successfully completing the numerical modelling of particulate reinforced metal matrix composites.

Application of mathematical modeling in sustained release delivery systems.

PubMed

Grassi, Mario; Grassi, Gabriele

2014-08-01

This review, presenting as starting point the concept of the mathematical modeling, is aimed at the physical and mathematical description of the most important mechanisms regulating drug delivery from matrix systems. The precise knowledge of the delivery mechanisms allows us to set up powerful mathematical models which, in turn, are essential for the design and optimization of appropriate drug delivery systems. The fundamental mechanisms for drug delivery from matrices are represented by drug diffusion, matrix swelling, matrix erosion, drug dissolution with possible recrystallization (e.g., as in the case of amorphous and nanocrystalline drugs), initial drug distribution inside the matrix, matrix geometry, matrix size distribution (in the case of spherical matrices of different diameter) and osmotic pressure. Depending on matrix characteristics, the above-reported variables may play a different role in drug delivery; thus the mathematical model needs to be built solely on the most relevant mechanisms of the particular matrix considered. Despite the somewhat diffident behavior of the industrial world, in the light of the most recent findings, we believe that mathematical modeling may have a tremendous potential impact in the pharmaceutical field. We do believe that mathematical modeling will be more and more important in the future especially in the light of the rapid advent of personalized medicine, a novel therapeutic approach intended to treat each single patient instead of the 'average' patient.

Active tissue stiffness modulation controls valve interstitial cell phenotype and osteogenic potential in 3D culture.

PubMed

Duan, Bin; Yin, Ziying; Hockaday Kang, Laura; Magin, Richard L; Butcher, Jonathan T

2016-05-01

Calcific aortic valve disease (CAVD) progression is a highly dynamic process whereby normally fibroblastic valve interstitial cells (VIC) undergo osteogenic differentiation, maladaptive extracellular matrix (ECM) composition, structural remodeling, and tissue matrix stiffening. However, how VIC with different phenotypes dynamically affect matrix properties and how the altered matrix further affects VIC phenotypes in response to physiological and pathological conditions have not yet been determined. In this study, we develop 3D hydrogels with tunable matrix stiffness to investigate the dynamic interplay between VIC phenotypes and matrix biomechanics. We find that VIC populated within hydrogels with valve leaflet like stiffness differentiate towards myofibroblasts in osteogenic media, but surprisingly undergo osteogenic differentiation when cultured within lower initial stiffness hydrogels. VIC differentiation progressively stiffens the hydrogel microenvironment, which further upregulates both early and late osteogenic markers. These findings identify a dynamic positive feedback loop that governs acceleration of VIC calcification. Temporal stiffening of pathologically lower stiffness matrix back to normal level, or blocking the mechanosensitive RhoA/ROCK signaling pathway, delays the osteogenic differentiation process. Therefore, direct ECM biomechanical modulation can affect VIC phenotypes towards and against osteogenic differentiation in 3D culture. These findings highlight the importance of the homeostatic maintenance of matrix stiffness to restrict pathological VIC differentiation. We implement 3D hydrogels with tunable matrix stiffness to investigate the dynamic interaction between valve interstitial cells (VIC, major cell population in heart valve) and matrix biomechanics. This work focuses on how human VIC responses to changing 3D culture environments. Our findings identify a dynamic positive feedback loop that governs acceleration of VIC calcification, which is the hallmark of calcific aortic valve disease. Temporal stiffening of pathologically lower stiffness matrix back to normal level, or blocking the mechanosensitive signaling pathway, delays VIC osteogenic differentiation. Our findings provide an improved understanding of VIC-matrix interactions to aid in interpretation of VIC calcification studies in vitro and suggest that ECM disruption resulting in local tissue stiffness decreases may promote calcific aortic valve disease. Copyright © 2016 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

Nonlinear Penalized Estimation of True Q-Matrix in Cognitive Diagnostic Models

ERIC Educational Resources Information Center

Xiang, Rui

2013-01-01

A key issue of cognitive diagnostic models (CDMs) is the correct identification of Q-matrix which indicates the relationship between attributes and test items. Previous CDMs typically assumed a known Q-matrix provided by domain experts such as those who developed the questions. However, misspecifications of Q-matrix had been discovered in the past…

Assessing Fit of Item Response Models Using the Information Matrix Test

ERIC Educational Resources Information Center

Ranger, Jochen; Kuhn, Jorg-Tobias

2012-01-01

The information matrix can equivalently be determined via the expectation of the Hessian matrix or the expectation of the outer product of the score vector. The identity of these two matrices, however, is only valid in case of a correctly specified model. Therefore, differences between the two versions of the observed information matrix indicate…

Platelet-rich fibrin matrix improves wound angiogenesis via inducing endothelial cell proliferation.

PubMed

Roy, Sashwati; Driggs, Jason; Elgharably, Haytham; Biswas, Sabyasachi; Findley, Muna; Khanna, Savita; Gnyawali, Urmila; Bergdall, Valerie K; Sen, Chandan K

2011-11-01

The economic, social, and public health burden of chronic ulcers and other compromised wounds is enormous and rapidly increasing with the aging population. The growth factors derived from platelets play an important role in tissue remodeling including neovascularization. Platelet-rich plasma (PRP) has been utilized and studied for the last four decades. Platelet gel and fibrin sealant, derived from PRP mixed with thrombin and calcium chloride, have been exogenously applied to tissues to promote wound healing, bone growth, hemostasis, and tissue sealing. In this study, we first characterized recovery and viability of as well as growth factor release from platelets in a novel preparation of platelet gel and fibrin matrix, namely platelet-rich fibrin matrix (PRFM). Next, the effect of PRFM application in a delayed model of ischemic wound angiogenesis was investigated. The study, for the first time, shows the kinetics of the viability of platelet-embedded fibrin matrix. A slow and steady release of growth factors from PRFM was observed. The vascular endothelial growth factor released from PRFM was primarily responsible for endothelial mitogenic response via extracellular signal-regulated protein kinase activation pathway. Finally, this preparation of PRFM effectively induced endothelial cell proliferation and improved wound angiogenesis in chronic wounds, providing evidence of probable mechanisms of action of PRFM in healing of chronic ulcers. 2011 by the Wound Healing Society.

Genome-Wide Association Studies with a Genomic Relationship Matrix: A Case Study with Wheat and Arabidopsis.

PubMed

Gianola, Daniel; Fariello, Maria I; Naya, Hugo; Schön, Chris-Carolin

2016-10-13

Standard genome-wide association studies (GWAS) scan for relationships between each of p molecular markers and a continuously distributed target trait. Typically, a marker-based matrix of genomic similarities among individuals ( G: ) is constructed, to account more properly for the covariance structure in the linear regression model used. We show that the generalized least-squares estimator of the regression of phenotype on one or on m markers is invariant with respect to whether or not the marker(s) tested is(are) used for building G,: provided variance components are unaffected by exclusion of such marker(s) from G: The result is arrived at by using a matrix expression such that one can find many inverses of genomic relationship, or of phenotypic covariance matrices, stemming from removing markers tested as fixed, but carrying out a single inversion. When eigenvectors of the genomic relationship matrix are used as regressors with fixed regression coefficients, e.g., to account for population stratification, their removal from G: does matter. Removal of eigenvectors from G: can have a noticeable effect on estimates of genomic and residual variances, so caution is needed. Concepts were illustrated using genomic data on 599 wheat inbred lines, with grain yield as target trait, and on close to 200 Arabidopsis thaliana accessions. Copyright © 2016 Gianola et al.

Statistical Analysis of Q-matrix Based Diagnostic Classification Models

PubMed Central

Chen, Yunxiao; Liu, Jingchen; Xu, Gongjun; Ying, Zhiliang

2014-01-01

Diagnostic classification models have recently gained prominence in educational assessment, psychiatric evaluation, and many other disciplines. Central to the model specification is the so-called Q-matrix that provides a qualitative specification of the item-attribute relationship. In this paper, we develop theories on the identifiability for the Q-matrix under the DINA and the DINO models. We further propose an estimation procedure for the Q-matrix through the regularized maximum likelihood. The applicability of this procedure is not limited to the DINA or the DINO model and it can be applied to essentially all Q-matrix based diagnostic classification models. Simulation studies are conducted to illustrate its performance. Furthermore, two case studies are presented. The first case is a data set on fraction subtraction (educational application) and the second case is a subsample of the National Epidemiological Survey on Alcohol and Related Conditions concerning the social anxiety disorder (psychiatric application). PMID:26294801

The Cauchy Two-Matrix Model, C-Toda Lattice and CKP Hierarchy

NASA Astrophysics Data System (ADS)

Li, Chunxia; Li, Shi-Hao

2018-06-01

This paper mainly talks about the Cauchy two-matrix model and its corresponding integrable hierarchy with the help of orthogonal polynomial theory and Toda-type equations. Starting from the symmetric reduction in Cauchy biorthogonal polynomials, we derive the Toda equation of CKP type (or the C-Toda lattice) as well as its Lax pair by introducing time flows. Then, matrix integral solutions to the C-Toda lattice are extended to give solutions to the CKP hierarchy which reveals the time-dependent partition function of the Cauchy two-matrix model is nothing but the τ -function of the CKP hierarchy. At last, the connection between the Cauchy two-matrix model and Bures ensemble is established from the point of view of integrable systems.

Inference and Analysis of Population Structure Using Genetic Data and Network Theory

PubMed Central

Greenbaum, Gili; Templeton, Alan R.; Bar-David, Shirli

2016-01-01

Clustering individuals to subpopulations based on genetic data has become commonplace in many genetic studies. Inference about population structure is most often done by applying model-based approaches, aided by visualization using distance-based approaches such as multidimensional scaling. While existing distance-based approaches suffer from a lack of statistical rigor, model-based approaches entail assumptions of prior conditions such as that the subpopulations are at Hardy-Weinberg equilibria. Here we present a distance-based approach for inference about population structure using genetic data by defining population structure using network theory terminology and methods. A network is constructed from a pairwise genetic-similarity matrix of all sampled individuals. The community partition, a partition of a network to dense subgraphs, is equated with population structure, a partition of the population to genetically related groups. Community-detection algorithms are used to partition the network into communities, interpreted as a partition of the population to subpopulations. The statistical significance of the structure can be estimated by using permutation tests to evaluate the significance of the partition’s modularity, a network theory measure indicating the quality of community partitions. To further characterize population structure, a new measure of the strength of association (SA) for an individual to its assigned community is presented. The strength of association distribution (SAD) of the communities is analyzed to provide additional population structure characteristics, such as the relative amount of gene flow experienced by the different subpopulations and identification of hybrid individuals. Human genetic data and simulations are used to demonstrate the applicability of the analyses. The approach presented here provides a novel, computationally efficient model-free method for inference about population structure that does not entail assumption of prior conditions. The method is implemented in the software NetStruct (available at https://giligreenbaum.wordpress.com/software/). PMID:26888080

Inference and Analysis of Population Structure Using Genetic Data and Network Theory.

PubMed

Greenbaum, Gili; Templeton, Alan R; Bar-David, Shirli

2016-04-01

Clustering individuals to subpopulations based on genetic data has become commonplace in many genetic studies. Inference about population structure is most often done by applying model-based approaches, aided by visualization using distance-based approaches such as multidimensional scaling. While existing distance-based approaches suffer from a lack of statistical rigor, model-based approaches entail assumptions of prior conditions such as that the subpopulations are at Hardy-Weinberg equilibria. Here we present a distance-based approach for inference about population structure using genetic data by defining population structure using network theory terminology and methods. A network is constructed from a pairwise genetic-similarity matrix of all sampled individuals. The community partition, a partition of a network to dense subgraphs, is equated with population structure, a partition of the population to genetically related groups. Community-detection algorithms are used to partition the network into communities, interpreted as a partition of the population to subpopulations. The statistical significance of the structure can be estimated by using permutation tests to evaluate the significance of the partition's modularity, a network theory measure indicating the quality of community partitions. To further characterize population structure, a new measure of the strength of association (SA) for an individual to its assigned community is presented. The strength of association distribution (SAD) of the communities is analyzed to provide additional population structure characteristics, such as the relative amount of gene flow experienced by the different subpopulations and identification of hybrid individuals. Human genetic data and simulations are used to demonstrate the applicability of the analyses. The approach presented here provides a novel, computationally efficient model-free method for inference about population structure that does not entail assumption of prior conditions. The method is implemented in the software NetStruct (available at https://giligreenbaum.wordpress.com/software/). Copyright © 2016 by the Genetics Society of America.

Mathematical model of water transport in Bacon and alkaline matrix-type hydrogen-oxygen fuel cells

NASA Technical Reports Server (NTRS)

Prokopius, P. R.; Easter, R. W.

1972-01-01

Based on general mass continuity and diffusive transport equations, a mathematical model was developed that simulates the transport of water in Bacon and alkaline-matrix fuel cells. The derived model was validated by using it to analytically reproduce various Bacon and matrix-cell experimental water transport transients.

Take the Red Pill: A New Matrix of Literacy

ERIC Educational Resources Information Center

Brabazon, Tara

2011-01-01

Using "The Matrix" film series as an inspiration, aspiration and model, this article integrates horizontal and vertical models of literacy. My goal is to create a new matrix for media literacy, aligning the best of analogue depth models for meaning making with the rapid scrolling, clicking and moving through the read-write web. To…

Numerical modelling of transdermal delivery from matrix systems: parametric study and experimental validation with silicone matrices.

PubMed

Snorradóttir, Bergthóra S; Jónsdóttir, Fjóla; Sigurdsson, Sven Th; Másson, Már

2014-08-01

A model is presented for transdermal drug delivery from single-layered silicone matrix systems. The work is based on our previous results that, in particular, extend the well-known Higuchi model. Recently, we have introduced a numerical transient model describing matrix systems where the drug dissolution can be non-instantaneous. Furthermore, our model can describe complex interactions within a multi-layered matrix and the matrix to skin boundary. The power of the modelling approach presented here is further illustrated by allowing the possibility of a donor solution. The model is validated by a comparison with experimental data, as well as validating the parameter values against each other, using various configurations with donor solution, silicone matrix and skin. Our results show that the model is a good approximation to real multi-layered delivery systems. The model offers the ability of comparing drug release for ibuprofen and diclofenac, which cannot be analysed by the Higuchi model because the dissolution in the latter case turns out to be limited. The experiments and numerical model outlined in this study could also be adjusted to more general formulations, which enhances the utility of the numerical model as a design tool for the development of drug-loaded matrices for trans-membrane and transdermal delivery. © 2014 Wiley Periodicals, Inc. and the American Pharmacists Association.

An algebraic aspect of Pareto mixture parameter estimation using censored sample: A Bayesian approach.

PubMed

Saleem, Muhammad; Sharif, Kashif; Fahmi, Aliya

2018-04-27

Applications of Pareto distribution are common in reliability, survival and financial studies. In this paper, A Pareto mixture distribution is considered to model a heterogeneous population comprising of two subgroups. Each of two subgroups is characterized by the same functional form with unknown distinct shape and scale parameters. Bayes estimators have been derived using flat and conjugate priors using squared error loss function. Standard errors have also been derived for the Bayes estimators. An interesting feature of this study is the preparation of components of Fisher Information matrix.

Solving large-scale dynamic systems using band Lanczos method in Rockwell NASTRAN on CRAY X-MP

NASA Technical Reports Server (NTRS)

Gupta, V. K.; Zillmer, S. D.; Allison, R. E.

1986-01-01

The improved cost effectiveness using better models, more accurate and faster algorithms and large scale computing offers more representative dynamic analyses. The band Lanczos eigen-solution method was implemented in Rockwell's version of 1984 COSMIC-released NASTRAN finite element structural analysis computer program to effectively solve for structural vibration modes including those of large complex systems exceeding 10,000 degrees of freedom. The Lanczos vectors were re-orthogonalized locally using the Lanczos Method and globally using the modified Gram-Schmidt method for sweeping rigid-body modes and previously generated modes and Lanczos vectors. The truncated band matrix was solved for vibration frequencies and mode shapes using Givens rotations. Numerical examples are included to demonstrate the cost effectiveness and accuracy of the method as implemented in ROCKWELL NASTRAN. The CRAY version is based on RPK's COSMIC/NASTRAN. The band Lanczos method was more reliable and accurate and converged faster than the single vector Lanczos Method. The band Lanczos method was comparable to the subspace iteration method which was a block version of the inverse power method. However, the subspace matrix tended to be fully populated in the case of subspace iteration and not as sparse as a band matrix.

Sparse PCA with Oracle Property.

PubMed

Gu, Quanquan; Wang, Zhaoran; Liu, Han

In this paper, we study the estimation of the k -dimensional sparse principal subspace of covariance matrix Σ in the high-dimensional setting. We aim to recover the oracle principal subspace solution, i.e., the principal subspace estimator obtained assuming the true support is known a priori. To this end, we propose a family of estimators based on the semidefinite relaxation of sparse PCA with novel regularizations. In particular, under a weak assumption on the magnitude of the population projection matrix, one estimator within this family exactly recovers the true support with high probability, has exact rank- k , and attains a [Formula: see text] statistical rate of convergence with s being the subspace sparsity level and n the sample size. Compared to existing support recovery results for sparse PCA, our approach does not hinge on the spiked covariance model or the limited correlation condition. As a complement to the first estimator that enjoys the oracle property, we prove that, another estimator within the family achieves a sharper statistical rate of convergence than the standard semidefinite relaxation of sparse PCA, even when the previous assumption on the magnitude of the projection matrix is violated. We validate the theoretical results by numerical experiments on synthetic datasets.

Sparse PCA with Oracle Property

PubMed Central

Gu, Quanquan; Wang, Zhaoran; Liu, Han

2014-01-01

In this paper, we study the estimation of the k-dimensional sparse principal subspace of covariance matrix Σ in the high-dimensional setting. We aim to recover the oracle principal subspace solution, i.e., the principal subspace estimator obtained assuming the true support is known a priori. To this end, we propose a family of estimators based on the semidefinite relaxation of sparse PCA with novel regularizations. In particular, under a weak assumption on the magnitude of the population projection matrix, one estimator within this family exactly recovers the true support with high probability, has exact rank-k, and attains a s/n statistical rate of convergence with s being the subspace sparsity level and n the sample size. Compared to existing support recovery results for sparse PCA, our approach does not hinge on the spiked covariance model or the limited correlation condition. As a complement to the first estimator that enjoys the oracle property, we prove that, another estimator within the family achieves a sharper statistical rate of convergence than the standard semidefinite relaxation of sparse PCA, even when the previous assumption on the magnitude of the projection matrix is violated. We validate the theoretical results by numerical experiments on synthetic datasets. PMID:25684971

The impact of covariance misspecification in group-based trajectory models for longitudinal data with non-stationary covariance structure.

PubMed

Davies, Christopher E; Glonek, Gary Fv; Giles, Lynne C

2017-08-01

One purpose of a longitudinal study is to gain a better understanding of how an outcome of interest changes among a given population over time. In what follows, a trajectory will be taken to mean the series of measurements of the outcome variable for an individual. Group-based trajectory modelling methods seek to identify subgroups of trajectories within a population, such that trajectories that are grouped together are more similar to each other than to trajectories in distinct groups. Group-based trajectory models generally assume a certain structure in the covariances between measurements, for example conditional independence, homogeneous variance between groups or stationary variance over time. Violations of these assumptions could be expected to result in poor model performance. We used simulation to investigate the effect of covariance misspecification on misclassification of trajectories in commonly used models under a range of scenarios. To do this we defined a measure of performance relative to the ideal Bayesian correct classification rate. We found that the more complex models generally performed better over a range of scenarios. In particular, incorrectly specified covariance matrices could significantly bias the results but using models with a correct but more complicated than necessary covariance matrix incurred little cost.

Modeling extracellular matrix degradation balance with proteinase/transglutaminase cycle.

PubMed

Larreta-Garde, Veronique; Berry, Hugues

2002-07-07

Extracellular matrix mass balance is implied in many physiological and pathological events, such as metastasis dissemination. Widely studied, its destructive part is mainly catalysed by extracellular proteinases. Conversely, the properties of the constructive part are less obvious, cellular neo-synthesis being usually considered as its only element. In this paper, we introduce the action of transglutaminase in a mathematical model for extracellular matrix remodeling. This extracellular enzyme, catalysing intermolecular protein cross-linking, is considered here as a reverse proteinase as far as the extracellular matrix physical state is concerned. The model is based on a proteinase/transglutaminase cycle interconverting insoluble matrix and soluble proteolysis fragments, with regulation of cellular proteinase expression by the fragments. Under "closed" (batch) conditions, i.e. neglecting matrix influx and fragment efflux from the system, the model is bistable, with reversible hysteresis. Extracellular matrix proteins concentration abruptly switches from low to high levels when transglutaminase activity exceeds a threshold value. Proteinase concentration usually follows the reverse complementary kinetics, but can become apparently uncoupled from extracellular matrix concentration for some parameter values. When matrix production by the cells and fragment degradation are taken into account, the dynamics change to sustained oscillations because of the emergence of a stable limit cycle. Transitions out of and into oscillation areas are controlled by the model parameters. Biological interpretation indicates that these oscillations could represent the normal homeostatic situation, whereas the other exhibited dynamics can be related to pathologies such as tumor invasion or fibrosis. These results allow to discuss the insights that the model could contribute to the comprehension of these complex biological events.

Emerging prion disease drives host selection in a wildlife population

USGS Publications Warehouse

Robinson, Stacie J.; Samuel, Michael D.; Johnson, Chad J.; Adams, Marie; McKenzie, Debbie I.

2012-01-01

Infectious diseases are increasingly recognized as an important force driving population dynamics, conservation biology, and natural selection in wildlife populations. Infectious agents have been implicated in the decline of small or endangered populations and may act to constrain population size, distribution, growth rates, or migration patterns. Further, diseases may provide selective pressures that shape the genetic diversity of populations or species. Thus, understanding disease dynamics and selective pressures from pathogens is crucial to understanding population processes, managing wildlife diseases, and conserving biological diversity. There is ample evidence that variation in the prion protein gene (PRNP) impacts host susceptibility to prion diseases. Still, little is known about how genetic differences might influence natural selection within wildlife populations. Here we link genetic variation with differential susceptibility of white-tailed deer to chronic wasting disease (CWD), with implications for fitness and disease-driven genetic selection. We developed a single nucleotide polymorphism (SNP) assay to efficiently genotype deer at the locus of interest (in the 96th codon of the PRNP gene). Then, using a Bayesian modeling approach, we found that the more susceptible genotype had over four times greater risk of CWD infection; and, once infected, deer with the resistant genotype survived 49% longer (8.25 more months). We used these epidemiological parameters in a multi-stage population matrix model to evaluate relative fitness based on genotype-specific population growth rates. The differences in disease infection and mortality rates allowed genetically resistant deer to achieve higher population growth and obtain a long-term fitness advantage, which translated into a selection coefficient of over 1% favoring the CWD-resistant genotype. This selective pressure suggests that the resistant allele could become dominant in the population within an evolutionarily short time frame. Our work provides a rare example of a quantifiable disease-driven selection process in a wildlife population, demonstrating the potential for infectious diseases to alter host populations. This will have direct bearing on the epidemiology, dynamics, and future trends in CWD transmission and spread. Understanding genotype-specific epidemiology will improve predictive models and inform management strategies for CWD-affected cervid populations.

Estimation of Covariance Matrix on Bi-Response Longitudinal Data Analysis with Penalized Spline Regression

NASA Astrophysics Data System (ADS)

Islamiyati, A.; Fatmawati; Chamidah, N.

2018-03-01

The correlation assumption of the longitudinal data with bi-response occurs on the measurement between the subjects of observation and the response. It causes the auto-correlation of error, and this can be overcome by using a covariance matrix. In this article, we estimate the covariance matrix based on the penalized spline regression model. Penalized spline involves knot points and smoothing parameters simultaneously in controlling the smoothness of the curve. Based on our simulation study, the estimated regression model of the weighted penalized spline with covariance matrix gives a smaller error value compared to the error of the model without covariance matrix.

Time-dependent deformation of titanium metal matrix composites

NASA Technical Reports Server (NTRS)

Bigelow, C. A.; Bahei-El-din, Y. A.; Mirdamadi, M.

1995-01-01

A three-dimensional finite element program called VISCOPAC was developed and used to conduct a micromechanics analysis of titanium metal matrix composites. The VISCOPAC program uses a modified Eisenberg-Yen thermo-viscoplastic constitutive model to predict matrix behavior under thermomechanical fatigue loading. The analysis incorporated temperature-dependent elastic properties in the fiber and temperature-dependent viscoplastic properties in the matrix. The material model was described and the necessary material constants were determined experimentally. Fiber-matrix interfacial behavior was analyzed using a discrete fiber-matrix model. The thermal residual stresses due to the fabrication cycle were predicted with a failed interface, The failed interface resulted in lower thermal residual stresses in the matrix and fiber. Stresses due to a uniform transverse load were calculated at two temperatures, room temperature and an elevated temperature of 650 C. At both temperatures, a large stress concentration was calculated when the interface had failed. The results indicate the importance of accuracy accounting for fiber-matrix interface failure and the need for a micromechanics-based analytical technique to understand and predict the behavior of titanium metal matrix composites.

Faces of matrix models

NASA Astrophysics Data System (ADS)

Morozov, A.

2012-08-01

Partition functions of eigenvalue matrix models possess a number of very different descriptions: as matrix integrals, as solutions to linear and nonlinear equations, as τ-functions of integrable hierarchies and as special-geometry prepotentials, as result of the action of W-operators and of various recursions on elementary input data, as gluing of certain elementary building blocks. All this explains the central role of such matrix models in modern mathematical physics: they provide the basic "special functions" to express the answers and relations between them, and they serve as a dream model of what one should try to achieve in any other field.

NLTE steady-state response matrix method.

NASA Astrophysics Data System (ADS)

Faussurier, G.; More, R. M.

2000-05-01

A connection between atomic kinetics and non-equilibrium thermodynamics has been recently established by using a collisional-radiative model modified to include line absorption. The calculated net emission can be expressed as a non-local thermodynamic equilibrium (NLTE) symmetric response matrix. In the paper, this connection is extended to both cases of the average-atom model and the Busquet's model (RAdiative-Dependent IOnization Model, RADIOM). The main properties of the response matrix still remain valid. The RADIOM source function found in the literature leads to a diagonal response matrix, stressing the absence of any frequency redistribution among the frequency groups at this order of calculation.

Birth/birth-death processes and their computable transition probabilities with biological applications.

PubMed

Ho, Lam Si Tung; Xu, Jason; Crawford, Forrest W; Minin, Vladimir N; Suchard, Marc A

2018-03-01

Birth-death processes track the size of a univariate population, but many biological systems involve interaction between populations, necessitating models for two or more populations simultaneously. A lack of efficient methods for evaluating finite-time transition probabilities of bivariate processes, however, has restricted statistical inference in these models. Researchers rely on computationally expensive methods such as matrix exponentiation or Monte Carlo approximation, restricting likelihood-based inference to small systems, or indirect methods such as approximate Bayesian computation. In this paper, we introduce the birth/birth-death process, a tractable bivariate extension of the birth-death process, where rates are allowed to be nonlinear. We develop an efficient algorithm to calculate its transition probabilities using a continued fraction representation of their Laplace transforms. Next, we identify several exemplary models arising in molecular epidemiology, macro-parasite evolution, and infectious disease modeling that fall within this class, and demonstrate advantages of our proposed method over existing approaches to inference in these models. Notably, the ubiquitous stochastic susceptible-infectious-removed (SIR) model falls within this class, and we emphasize that computable transition probabilities newly enable direct inference of parameters in the SIR model. We also propose a very fast method for approximating the transition probabilities under the SIR model via a novel branching process simplification, and compare it to the continued fraction representation method with application to the 17th century plague in Eyam. Although the two methods produce similar maximum a posteriori estimates, the branching process approximation fails to capture the correlation structure in the joint posterior distribution.

Matrix approach to uncertainty assessment and reduction for modeling terrestrial carbon cycle

NASA Astrophysics Data System (ADS)

Luo, Y.; Xia, J.; Ahlström, A.; Zhou, S.; Huang, Y.; Shi, Z.; Wang, Y.; Du, Z.; Lu, X.

2017-12-01

Terrestrial ecosystems absorb approximately 30% of the anthropogenic carbon dioxide emissions. This estimate has been deduced indirectly: combining analyses of atmospheric carbon dioxide concentrations with ocean observations to infer the net terrestrial carbon flux. In contrast, when knowledge about the terrestrial carbon cycle is integrated into different terrestrial carbon models they make widely different predictions. To improve the terrestrial carbon models, we have recently developed a matrix approach to uncertainty assessment and reduction. Specifically, the terrestrial carbon cycle has been commonly represented by a series of carbon balance equations to track carbon influxes into and effluxes out of individual pools in earth system models. This representation matches our understanding of carbon cycle processes well and can be reorganized into one matrix equation without changing any modeled carbon cycle processes and mechanisms. We have developed matrix equations of several global land C cycle models, including CLM3.5, 4.0 and 4.5, CABLE, LPJ-GUESS, and ORCHIDEE. Indeed, the matrix equation is generic and can be applied to other land carbon models. This matrix approach offers a suite of new diagnostic tools, such as the 3-dimensional (3-D) parameter space, traceability analysis, and variance decomposition, for uncertainty analysis. For example, predictions of carbon dynamics with complex land models can be placed in a 3-D parameter space (carbon input, residence time, and storage potential) as a common metric to measure how much model predictions are different. The latter can be traced to its source components by decomposing model predictions to a hierarchy of traceable components. Then, variance decomposition can help attribute the spread in predictions among multiple models to precisely identify sources of uncertainty. The highly uncertain components can be constrained by data as the matrix equation makes data assimilation computationally possible. We will illustrate various applications of this matrix approach to uncertainty assessment and reduction for terrestrial carbon cycle models.

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.

An Analysis of Variance Framework for Matrix Sampling.

ERIC Educational Resources Information Center

Sirotnik, Kenneth

Significant cost savings can be achieved with the use of matrix sampling in estimating population parameters from psychometric data. The statistical design is intuitively simple, using the framework of the two-way classification analysis of variance technique. For example, the mean and variance are derived from the performance of a certain grade…

The anatomy of a (potential) disaster: Volcanoes, behavior, and population viability of the short-tailed albatross (Phoebastria albatrus)

USGS Publications Warehouse

Finkelstein, M.E.; Wolf, S.; Goldman, M.; Doak, D.F.; Sievert, P.R.; Balogh, G.; Hasegawa, H.

2010-01-01

Catastrophic events, either from natural (e.g., hurricane) or human-induced (e.g., forest clear-cut) processes, are a well-known threat to wild populations. However, our lack of knowledge about population-level effects of catastrophic events has inhibited the careful examination of how catastrophes affect population growth and persistence. For the critically endangered short-tailed albatross (Phoebastria albatrus), episodic volcanic eruptions are considered a serious catastrophic threat since approximately 80% of the global population of ???2500 birds (in 2006) currently breeds on an active volcano, Torishima Island. We evaluated how short-tailed albatross population persistence is affected by the catastrophic threat of a volcanic eruption relative to chronic threats. We also provide an example for overcoming the seemingly overwhelming problems created by modelling the population dynamics of a species with limited demographic data by incorporating uncertainty in our analysis. As such, we constructed a stochastic age-based matrix model that incorporated both catastrophic mortality due to volcanic eruptions and chronic mortality from several potential sources (e.g., contaminant exposure, fisheries bycatch) to determine the relative effects of these two types of threats on short-tailed albatross population growth and persistence. Modest increases (1%) in chronic (annual) mortality had a 2.5-fold greater effect on predicted short-tailed albatross stochastic population growth rate (lambda) than did the occurrence of periodic volcanic eruptions that follow historic eruption frequencies (annual probability of eruption 2.2%). Our work demonstrates that periodic catastrophic volcanic eruptions, despite their dramatic nature, are less likely to affect the population viability and recovery of short-tailed albatross than low-level chronic mortality. ?? 2009 Elsevier Ltd.

Continuous fiber ceramic matrix composites for heat engine components

NASA Technical Reports Server (NTRS)

Tripp, David E.

1988-01-01

High strength at elevated temperatures, low density, resistance to wear, and abundance of nonstrategic raw materials make structural ceramics attractive for advanced heat engine applications. Unfortunately, ceramics have a low fracture toughness and fail catastrophically because of overload, impact, and contact stresses. Ceramic matrix composites provide the means to achieve improved fracture toughness while retaining desirable characteristics, such as high strength and low density. Materials scientists and engineers are trying to develop the ideal fibers and matrices to achieve the optimum ceramic matrix composite properties. A need exists for the development of failure models for the design of ceramic matrix composite heat engine components. Phenomenological failure models are currently the most frequently used in industry, but they are deterministic and do not adequately describe ceramic matrix composite behavior. Semi-empirical models were proposed, which relate the failure of notched composite laminates to the stress a characteristic distance away from the notch. Shear lag models describe composite failure modes at the micromechanics level. The enhanced matrix cracking stress occurs at the same applied stress level predicted by the two models of steady state cracking. Finally, statistical models take into consideration the distribution in composite failure strength. The intent is to develop these models into computer algorithms for the failure analysis of ceramic matrix composites under monotonically increasing loads. The algorithms will be included in a postprocessor to general purpose finite element programs.

Producing genome structure populations with the dynamic and automated PGS software.

PubMed

Hua, Nan; Tjong, Harianto; Shin, Hanjun; Gong, Ke; Zhou, Xianghong Jasmine; Alber, Frank

2018-05-01

Chromosome conformation capture technologies such as Hi-C are widely used to investigate the spatial organization of genomes. Because genome structures can vary considerably between individual cells of a population, interpreting ensemble-averaged Hi-C data can be challenging, in particular for long-range and interchromosomal interactions. We pioneered a probabilistic approach for the generation of a population of distinct diploid 3D genome structures consistent with all the chromatin-chromatin interaction probabilities from Hi-C experiments. Each structure in the population is a physical model of the genome in 3D. Analysis of these models yields new insights into the causes and the functional properties of the genome's organization in space and time. We provide a user-friendly software package, called PGS, which runs on local machines (for practice runs) and high-performance computing platforms. PGS takes a genome-wide Hi-C contact frequency matrix, along with information about genome segmentation, and produces an ensemble of 3D genome structures entirely consistent with the input. The software automatically generates an analysis report, and provides tools to extract and analyze the 3D coordinates of specific domains. Basic Linux command-line knowledge is sufficient for using this software. A typical running time of the pipeline is ∼3 d with 300 cores on a computer cluster to generate a population of 1,000 diploid genome structures at topological-associated domain (TAD)-level resolution.

Development of an adaptive harvest management program for Taiga bean geese

USGS Publications Warehouse

Johnson, Fred A.; Alhainen, Mikko; Fox, Anthony D.; Madsen, Jesper

2016-01-01

This report describes recent progress in specifying the elements of an adaptive harvest program for taiga bean goose. It describes harvest levels appropriate for first rebuilding the population of the Central Management Unit and then maintaining it near the goal specified in the AEWA International Single Species Action Plan (ISSAP). This report also provides estimates of the length of time it would take under ideal conditions (no density dependence and no harvest) to rebuild depleted populations in the Western and Eastern Management Units. We emphasize that our estimates are a first approximation because detailed demographic information is lacking for taiga bean geese. Using allometric relationships, we estimated parameters of a thetalogistic matrix population model. The mean intrinsic rate of growth was estimated as r = 0.150 (90% credible interval: 0.120 – 0.182). We estimated the mean form of density dependence as   2.361 (90% credible interval: 0.473 – 11.778), suggesting the strongest density dependence occurs when the population is near its carrying capacity. Based on expert opinion, carrying capacity (i.e., population size expected in the absence of hunting) for the Central Management Unit was estimated as K  87,900 (90% credible interval: 82,000 – 94,100). The ISSAP specifies a population goal for the Central Management Unit of 60,000 – 80,000 individuals in winter; thus, we specified a preliminary objective function as one which would minimize the difference between this goal and population size. Using the concept of stochastic dominance to explicitly account for uncertainty in demography, we determined that optimal harvest rates for 5, 10, 15, and 20-year time horizons were h = 0.00, 0.02, 0.05, and 0.06, respectively. These optima represent a tradeoff between the harvest rate and the time required to achieve and maintain a population size within desired bounds. We recognize, however, that regulation of absolute harvest rather than harvest rate is more practical, but our matrix model does not permit one to calculate an exact harvest associated with a specific harvest rate. Approximate harvests for current population size in the Central Management Unit are 0, 1,200, 2,300, and 3,500 for the 5, 10, 15, and 20-year time horizons, respectively. Populations of taiga bean geese in the Western and Eastern Units would require at least 10 and 13 years, respectively, to reach their minimum goals under the most optimistic of scenarios. The presence of harvest, density dependence, or environmental variation could extend these time frames considerably. Finally, we stress that development and implementation of internationally coordinated monitoring programs will be essential to further development and implementation of an adaptive harvest management program.

Population modelling to compare chronic external radiotoxicity between individual and population endpoints in four taxonomic groups.

PubMed

Alonzo, Frédéric; Hertel-Aas, Turid; Real, Almudena; Lance, Emilie; Garcia-Sanchez, Laurent; Bradshaw, Clare; Vives I Batlle, Jordi; Oughton, Deborah H; Garnier-Laplace, Jacqueline

2016-02-01

In this study, we modelled population responses to chronic external gamma radiation in 12 laboratory species (including aquatic and soil invertebrates, fish and terrestrial mammals). Our aim was to compare radiosensitivity between individual and population endpoints and to examine how internationally proposed benchmarks for environmental radioprotection protected species against various risks at the population level. To do so, we used population matrix models, combining life history and chronic radiotoxicity data (derived from laboratory experiments and described in the literature and the FREDERICA database) to simulate changes in population endpoints (net reproductive rate R0, asymptotic population growth rate λ, equilibrium population size Neq) for a range of dose rates. Elasticity analyses of models showed that population responses differed depending on the affected individual endpoint (juvenile or adult survival, delay in maturity or reduction in fecundity), the considered population endpoint (R0, λ or Neq) and the life history of the studied species. Among population endpoints, net reproductive rate R0 showed the lowest EDR10 (effective dose rate inducing 10% effect) in all species, with values ranging from 26 μGy h(-1) in the mouse Mus musculus to 38,000 μGy h(-1) in the fish Oryzias latipes. For several species, EDR10 for population endpoints were lower than the lowest EDR10 for individual endpoints. Various population level risks, differing in severity for the population, were investigated. Population extinction (predicted when radiation effects caused population growth rate λ to decrease below 1, indicating that no population growth in the long term) was predicted for dose rates ranging from 2700 μGy h(-1) in fish to 12,000 μGy h(-1) in soil invertebrates. A milder risk, that population growth rate λ will be reduced by 10% of the reduction causing extinction, was predicted for dose rates ranging from 24 μGy h(-1) in mammals to 1800 μGy h(-1) in soil invertebrates. These predictions suggested that proposed reference benchmarks from the literature for different taxonomic groups protected all simulated species against population extinction. A generic reference benchmark of 10 μGy h(-1) protected all simulated species against 10% of the effect causing population extinction. Finally, a risk of pseudo-extinction was predicted from 2.0 μGy h(-1) in mammals to 970 μGy h(-1) in soil invertebrates, representing a slight but statistically significant population decline, the importance of which remains to be evaluated in natural settings. Copyright © 2015 Elsevier Ltd. All rights reserved.

Estimating cell populations

NASA Technical Reports Server (NTRS)

White, B. S.; Castleman, K. R.

1981-01-01

An important step in the diagnosis of a cervical cytology specimen is estimating the proportions of the various cell types present. This is usually done with a cell classifier, the error rates of which can be expressed as a confusion matrix. We show how to use the confusion matrix to obtain an unbiased estimate of the desired proportions. We show that the mean square error of this estimate depends on a 'befuddlement matrix' derived from the confusion matrix, and how this, in turn, leads to a figure of merit for cell classifiers. Finally, we work out the two-class problem in detail and present examples to illustrate the theory.

A System Analysis for Determining Alternative Technological Issues for the Future

NASA Technical Reports Server (NTRS)

Magistrale, V. J.; Small, J.

1967-01-01

A systems engineering methodology is provided, by which future technological ventures may be examined utilizing particular national, corporate, or individual value judgments. Three matrix analyses are presented. The first matrix is concerned with the effect of technology on population increase, war, poverty, health, resources, and prejudice. The second matrix explores an analytical technique for determining the relative importance of different areas of technology. The third matrix explores how an individual or corporate entity may determine how its capability may be used for future technological opportunities. No conclusions are presented since primary effort has been placed on the methodology of determining future technological issues.

Novel measures of linkage disequilibrium that correct the bias due to population structure and relatedness.

PubMed

Mangin, B; Siberchicot, A; Nicolas, S; Doligez, A; This, P; Cierco-Ayrolles, C

2012-03-01

Among the several linkage disequilibrium measures known to capture different features of the non-independence between alleles at different loci, the most commonly used for diallelic loci is the r(2) measure. In the present study, we tackled the problem of the bias of r(2) estimate, which results from the sample structure and/or the relatedness between genotyped individuals. We derived two novel linkage disequilibrium measures for diallelic loci that are both extensions of the usual r(2) measure. The first one, r(S)(2), uses the population structure matrix, which consists of information about the origins of each individual and the admixture proportions of each individual genome. The second one, r(V)(2), includes the kinship matrix into the calculation. These two corrections can be applied together in order to correct for both biases and are defined either on phased or unphased genotypes.We proved that these novel measures are linked to the power of association tests under the mixed linear model including structure and kinship corrections. We validated them on simulated data and applied them to real data sets collected on Vitis vinifera plants. Our results clearly showed the usefulness of the two corrected r(2) measures, which actually captured 'true' linkage disequilibrium unlike the usual r(2) measure.

Brief announcement: Hypergraph parititioning for parallel sparse matrix-matrix multiplication

DOE PAGES

Ballard, Grey; Druinsky, Alex; Knight, Nicholas; ...

2015-01-01

The performance of parallel algorithms for sparse matrix-matrix multiplication is typically determined by the amount of interprocessor communication performed, which in turn depends on the nonzero structure of the input matrices. In this paper, we characterize the communication cost of a sparse matrix-matrix multiplication algorithm in terms of the size of a cut of an associated hypergraph that encodes the computation for a given input nonzero structure. Obtaining an optimal algorithm corresponds to solving a hypergraph partitioning problem. Furthermore, our hypergraph model generalizes several existing models for sparse matrix-vector multiplication, and we can leverage hypergraph partitioners developed for that computationmore » to improve application-specific algorithms for multiplying sparse matrices.« less

Clinical outcomes with Biolimus (A9)™ eluting stent, 'BioMatrix' in diabetic patients--interim results from multicenter post market surveillance registry in India.

PubMed

Seth, Ashok; Hiremath, Shirish; Dani, Sameer; Kapoor, Sunil; Jain, R K; Abhaichand, Rajpal; Trivedi, Shailendra; Kaul, Upendra; Patil, Aruna; Khemnar, Bhushan; Rangnekar, Hrishikesh

2013-01-01

The objective of this registry is to establish safety and efficacy of BioMatrix, BioMatrix™-Biolimus A9™ eluting stent in diabetic population in India. Diabetes mellitus is a major predisposing factor for coronary artery disease. Prognosis for diabetic population patients presenting with coronary artery disease who undergo coronary revascularization is inferior to non diabetics and remains an independent risk factor of restenosis, need for revascularization, and overall mortality. Stent thrombosis is a potential complication of first generation, permanent polymer drug-eluting stents. Biodegradable polymer is a good relief in this era and its utility in diabetic patients will be a major advantage for them. 334 patients with diabetes mellitus and requiring angioplasty, implanted with BioMatrix stent were followed at 1, 6, 12 and 24 months who entered in a multicenter registry in India. We analyzed the incidence of major adverse cardiac events (MACE) and stent thrombosis (ST) at 1, 6, 12 and 24 months. The mean age was 58.71 ± 9.2 years, 81% were males, comorbidity index was 1.6 ± 1.02, and 59.1% presented with acute coronary syndrome. The incidence of adverse event rates was: MACE 1.27%. There were no incidences of myocardial infarction (MI) and target vessel revascularization (TVR). Definite stent thrombosis occurred only in 2 patients. In this registry of diabetic population treated with BioMatrixTM-Biolimus A9TM eluting stent (BioMatrix), the reported incidence of MACE and ST were much lower than previously published results. The 1- and 2-year follow-up result supports favorable clinical outcomes of using BioMatrix stents as a suitable alternative to contemporary DES available during PCI in diabetic patients. Copyright © 2013 Cardiological Society of India. Published by Elsevier B.V. All rights reserved.

Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA.

PubMed

Kelly, Brendan J; Gross, Robert; Bittinger, Kyle; Sherrill-Mix, Scott; Lewis, James D; Collman, Ronald G; Bushman, Frederic D; Li, Hongzhe

2015-08-01

The variation in community composition between microbiome samples, termed beta diversity, can be measured by pairwise distance based on either presence-absence or quantitative species abundance data. PERMANOVA, a permutation-based extension of multivariate analysis of variance to a matrix of pairwise distances, partitions within-group and between-group distances to permit assessment of the effect of an exposure or intervention (grouping factor) upon the sampled microbiome. Within-group distance and exposure/intervention effect size must be accurately modeled to estimate statistical power for a microbiome study that will be analyzed with pairwise distances and PERMANOVA. We present a framework for PERMANOVA power estimation tailored to marker-gene microbiome studies that will be analyzed by pairwise distances, which includes: (i) a novel method for distance matrix simulation that permits modeling of within-group pairwise distances according to pre-specified population parameters; (ii) a method to incorporate effects of different sizes within the simulated distance matrix; (iii) a simulation-based method for estimating PERMANOVA power from simulated distance matrices; and (iv) an R statistical software package that implements the above. Matrices of pairwise distances can be efficiently simulated to satisfy the triangle inequality and incorporate group-level effects, which are quantified by the adjusted coefficient of determination, omega-squared (ω2). From simulated distance matrices, available PERMANOVA power or necessary sample size can be estimated for a planned microbiome study. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Large-N and Bethe Ansatz

NASA Astrophysics Data System (ADS)

Jurčo, Branislav

We describe an integrable model, related to the Gaudin magnet, and its relation to the matrix model of Brézin, Itzykson, Parisi and Zuber. Relation is based on Bethe ansatz for the integrable model and its interpretation using orthogonal polynomials and saddle point approximation. Large-N limit of the matrix model corresponds to the thermodynamic limit of the integrable system. In this limit (functional) Bethe ansatz is the same as the generating function for correlators of the matrix models.

Comparison of Damage Models for Predicting the Non-Linear Response of Laminates Under Matrix Dominated Loading Conditions

NASA Technical Reports Server (NTRS)

Schuecker, Clara; Davila, Carlos G.; Rose, Cheryl A.

2010-01-01

Five models for matrix damage in fiber reinforced laminates are evaluated for matrix-dominated loading conditions under plane stress and are compared both qualitatively and quantitatively. The emphasis of this study is on a comparison of the response of embedded plies subjected to a homogeneous stress state. Three of the models are specifically designed for modeling the non-linear response due to distributed matrix cracking under homogeneous loading, and also account for non-linear (shear) behavior prior to the onset of cracking. The remaining two models are localized damage models intended for predicting local failure at stress concentrations. The modeling approaches of distributed vs. localized cracking as well as the different formulations of damage initiation and damage progression are compared and discussed.

Matrix approaches to assess terrestrial nitrogen scheme in CLM4.5

NASA Astrophysics Data System (ADS)

Du, Z.

2017-12-01

Terrestrial carbon (C) and nitrogen (N) cycles have been commonly represented by a series of balance equations to track their influxes into and effluxes out of individual pools in earth system models (ESMs). This representation matches our understanding of C and N cycle processes well but makes it difficult to track model behaviors. To overcome these challenges, we developed a matrix approach, which reorganizes the series of terrestrial C and N balance equations in the CLM4.5 into two matrix equations based on original representation of C and N cycle processes and mechanisms. The matrix approach would consequently help improve the comparability of models and data, evaluate impacts of additional model components, facilitate benchmark analyses, model intercomparisons, and data-model fusion, and improve model predictive power.

Impact of biology knowledge on the conservation and management of large pelagic sharks.

PubMed

Yokoi, Hiroki; Ijima, Hirotaka; Ohshimo, Seiji; Yokawa, Kotaro

2017-09-06

Population growth rate, which depends on several biological parameters, is valuable information for the conservation and management of pelagic sharks, such as blue and shortfin mako sharks. However, reported biological parameters for estimating the population growth rates of these sharks differ by sex and display large variability. To estimate the appropriate population growth rate and clarify relationships between growth rate and relevant biological parameters, we developed a two-sex age-structured matrix population model and estimated the population growth rate using combinations of biological parameters. We addressed elasticity analysis and clarified the population growth rate sensitivity. For the blue shark, the estimated median population growth rate was 0.384 with a range of minimum and maximum values of 0.195-0.533, whereas those values of the shortfin mako shark were 0.102 and 0.007-0.318, respectively. The maturity age of male sharks had the largest impact for blue sharks, whereas that of female sharks had the largest impact for shortfin mako sharks. Hypotheses for the survival process of sharks also had a large impact on the population growth rate estimation. Both shark maturity age and survival rate were based on ageing validation data, indicating the importance of validating the quality of these data for the conservation and management of large pelagic sharks.

Prospective Isolation and Comparison of Human Germinal Matrix and Glioblastoma EGFR+ Populations with Stem Cell Properties.

PubMed

Tome-Garcia, Jessica; Tejero, Rut; Nudelman, German; Yong, Raymund L; Sebra, Robert; Wang, Huaien; Fowkes, Mary; Magid, Margret; Walsh, Martin; Silva-Vargas, Violeta; Zaslavsky, Elena; Friedel, Roland H; Doetsch, Fiona; Tsankova, Nadejda M

2017-05-09

Characterization of non-neoplastic and malignant human stem cell populations in their native state can provide new insights into gliomagenesis. Here we developed a purification strategy to directly isolate EGFR +/- populations from human germinal matrix (GM) and adult subventricular zone autopsy tissues, and from de novo glioblastoma (GBM) resections, enriching for cells capable of binding EGF ligand ( LB EGFR + ), and uniquely compared their functional and molecular properties. LB EGFR + populations in both GM and GBM encompassed all sphere-forming cells and displayed proliferative stem cell properties in vitro. In xenografts, LB EGFR + GBM cells showed robust tumor initiation and progression to high-grade, infiltrative gliomas. Whole-transcriptome sequencing analysis confirmed enrichment of proliferative pathways in both developing and neoplastic freshly isolated EGFR + populations, and identified both unique and shared sets of genes. The ability to prospectively isolate stem cell populations using native ligand-binding capacity opens new doors onto understanding both normal human development and tumor cell biology. Copyright © 2017 The Author(s). Published by Elsevier Inc. All rights reserved.

Effective Perron-Frobenius eigenvalue for a correlated random map

NASA Astrophysics Data System (ADS)

Pool, Roman R.; Cáceres, Manuel O.

2010-09-01

We investigate the evolution of random positive linear maps with various type of disorder by analytic perturbation and direct simulation. Our theoretical result indicates that the statistics of a random linear map can be successfully described for long time by the mean-value vector state. The growth rate can be characterized by an effective Perron-Frobenius eigenvalue that strongly depends on the type of correlation between the elements of the projection matrix. We apply this approach to an age-structured population dynamics model. We show that the asymptotic mean-value vector state characterizes the population growth rate when the age-structured model has random vital parameters. In this case our approach reveals the nontrivial dependence of the effective growth rate with cross correlations. The problem was reduced to the calculation of the smallest positive root of a secular polynomial, which can be obtained by perturbations in terms of Green’s function diagrammatic technique built with noncommutative cumulants for arbitrary n -point correlations.

Demographic origins of skewed operational and adult sex ratios: perturbation analyses of two-sex models.

PubMed

Veran, Sophie; Beissinger, Steven R

2009-02-01

Skewed sex ratios - operational (OSR) and Adult (ASR) - arise from sexual differences in reproductive behaviours and adult survival rates due to the cost of reproduction. However, skewed sex-ratio at birth, sex-biased dispersal and immigration, and sexual differences in juvenile mortality may also contribute. We present a framework to decompose the roles of demographic traits on sex ratios using perturbation analyses of two-sex matrix population models. Metrics of sensitivity are derived from analyses of sensitivity, elasticity, life-table response experiments and life stage simulation analyses, and applied to the stable stage distribution instead of lambda. We use these approaches to examine causes of male-biased sex ratios in two populations of green-rumped parrotlets (Forpus passerinus) in Venezuela. Female local juvenile survival contributed the most to the unbalanced OSR and ASR due to a female-biased dispersal rate, suggesting sexual differences in philopatry can influence sex ratios more strongly than the cost of reproduction.

Evaluating Process Improvement Courses of Action Through Modeling and Simulation

DTIC Science & Technology

2017-09-16

changes to a process is time consuming and has potential to overlook stochastic effects. By modeling a process as a Numerical Design Structure Matrix...13 Methods to Evaluate Process Performance ................................................................15 The Design Structure...Matrix ......................................................................................16 Numerical Design Structure Matrix

Average dispersal success: linking home range, dispersal, and metapopulation dynamics to reserve design.

PubMed

Fagan, William F; Lutscher, Frithjof

2006-04-01

Spatially explicit models for populations are often difficult to tackle mathematically and, in addition, require detailed data on individual movement behavior that are not easily obtained. An approximation known as the "average dispersal success" provides a tool for converting complex models, which may include stage structure and a mechanistic description of dispersal, into a simple matrix model. This simpler matrix model has two key advantages. First, it is easier to parameterize from the types of empirical data typically available to conservation biologists, such as survivorship, fecundity, and the fraction of juveniles produced in a study area that also recruit within the study area. Second, it is more amenable to theoretical investigation. Here, we use the average dispersal success approximation to develop estimates of the critical reserve size for systems comprising single patches or simple metapopulations. The quantitative approach can be used for both plants and animals; however, to provide a concrete example of the technique's utility, we focus on a special case pertinent to animals. Specifically, for territorial animals, we can characterize such an estimate of minimum viable habitat area in terms of the number of home ranges that the reserve contains. Consequently, the average dispersal success framework provides a framework through which home range size, natal dispersal distances, and metapopulation dynamics can be linked to reserve design. We briefly illustrate the approach using empirical data for the swift fox (Vulpes velox).

Demography and population dynamics of the mouse opossum (Thylamys elegans) in semi-arid Chile: seasonality, feedback structure and climate.

PubMed Central

Lima, M.; Stenseth, N. C.; Yoccoz, N. G.; Jaksic, F. M.

2001-01-01

Here we present, to the authors' knowledge for the very first time for a small marsupial, a thorough analysis of the demography and population dynamics of the mouse opossum (Thylamys elegans) in western South America. We test the relative importance of feedback structure and climatic factors (rainfall and the Southern Oscillation Index) in explaining the temporal variation in the demography of the mouse opossum. The demographic information was incorporated into a stage-structured population dynamics model and the model's predictions were compared with observed patterns. The mouse opossum's capture rates showed seasonal (within-year) and between-year variability, with individuals having higher capture rates during late summer and autumn and lower capture rates during winter and spring. There was also a strong between-year effect on capture probabilities. The reproductive (the fraction of reproductively active individuals) and recruitment rates showed a clear seasonal and a between-year pattern of variation with the peak of reproductive activity occuring during winter and early spring. In addition, the fraction of reproductive individuals was positively related to annual rainfall, while population density and annual rainfall positively influenced the recruitment rate. The survival rates were negatively related to annual rainfall. The average finite population growth rate during the study period was estimated to be 1.011 +/- 0.0019 from capture-recapture estimates. While the annual growth rate estimated from the seasonal linear matrix models was 1.026, the subadult and adult survival and maturation rates represent between 54% (winter) and 81% (summer) of the impact on the annual growth rate. PMID:11571053

Development of a cellularly degradable PEG hydrogel to promote articular cartilage extracellular matrix deposition.

PubMed

Sridhar, Balaji V; Brock, John L; Silver, Jason S; Leight, Jennifer L; Randolph, Mark A; Anseth, Kristi S

2015-04-02

Healing articular cartilage remains a significant clinical challenge because of its limited self-healing capacity. While delivery of autologous chondrocytes to cartilage defects has received growing interest, combining cell-based therapies with scaffolds that capture aspects of native tissue and promote cell-mediated remodeling could improve outcomes. Currently, scaffold-based therapies with encapsulated chondrocytes permit matrix production; however, resorption of the scaffold does not match the rate of production by cells leading to generally low extracellular matrix outputs. Here, a poly (ethylene glycol) (PEG) norbornene hydrogel is functionalized with thiolated transforming growth factor (TGF-β1) and cross-linked by an MMP-degradable peptide. Chondrocytes are co-encapsulated with a smaller population of mesenchymal stem cells, with the goal of stimulating matrix production and increasing bulk mechanical properties of the scaffold. The co-encapsulated cells cleave the MMP-degradable target sequence more readily than either cell population alone. Relative to non-degradable gels, cellularly degraded materials show significantly increased glycosaminoglycan and collagen deposition over just 14 d of culture, while maintaining high levels of viability and producing a more widely-distributed matrix. These results indicate the potential of an enzymatically degradable, peptide-functionalized PEG hydrogel to locally influence and promote cartilage matrix production over a short period. Scaffolds that permit cell-mediated remodeling may be useful in designing treatment options for cartilage tissue engineering applications. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The Role of Wildfire, Prescribed Fire, and Mountain Pine Beetle Infestations on the Population Dynamics of Black-Backed Woodpeckers in the Black Hills, South Dakota

PubMed Central

Rota, Christopher T.; Millspaugh, Joshua J.; Rumble, Mark A.; Lehman, Chad P.; Kesler, Dylan C.

2014-01-01

Wildfire and mountain pine beetle infestations are naturally occurring disturbances in western North American forests. Black-backed woodpeckers (Picoides arcticus) are emblematic of the role these disturbances play in creating wildlife habitat, since they are strongly associated with recently-killed forests. However, management practices aimed at reducing the economic impact of natural disturbances can result in habitat loss for this species. Although black-backed woodpeckers occupy habitats created by wildfire, prescribed fire, and mountain pine beetle infestations, the relative value of these habitats remains unknown. We studied habitat-specific adult and juvenile survival probabilities and reproductive rates between April 2008 and August 2012 in the Black Hills, South Dakota. We estimated habitat-specific adult and juvenile survival probability with Bayesian multi-state models and habitat-specific reproductive success with Bayesian nest survival models. We calculated asymptotic population growth rates from estimated demographic rates with matrix projection models. Adult and juvenile survival and nest success were highest in habitat created by summer wildfire, intermediate in MPB infestations, and lowest in habitat created by fall prescribed fire. Mean posterior distributions of population growth rates indicated growing populations in habitat created by summer wildfire and declining populations in fall prescribed fire and mountain pine beetle infestations. Our finding that population growth rates were positive only in habitat created by summer wildfire underscores the need to maintain early post-wildfire habitat across the landscape. The lower growth rates in fall prescribed fire and MPB infestations may be attributed to differences in predator communities and food resources relative to summer wildfire. PMID:24736502

The role of wildfire, prescribed fire, and mountain pine beetle infestations on the population dynamics of black-backed woodpeckers in the black hills, South Dakota.

PubMed

Rota, Christopher T; Millspaugh, Joshua J; Rumble, Mark A; Lehman, Chad P; Kesler, Dylan C

2014-01-01

Wildfire and mountain pine beetle infestations are naturally occurring disturbances in western North American forests. Black-backed woodpeckers (Picoides arcticus) are emblematic of the role these disturbances play in creating wildlife habitat, since they are strongly associated with recently-killed forests. However, management practices aimed at reducing the economic impact of natural disturbances can result in habitat loss for this species. Although black-backed woodpeckers occupy habitats created by wildfire, prescribed fire, and mountain pine beetle infestations, the relative value of these habitats remains unknown. We studied habitat-specific adult and juvenile survival probabilities and reproductive rates between April 2008 and August 2012 in the Black Hills, South Dakota. We estimated habitat-specific adult and juvenile survival probability with Bayesian multi-state models and habitat-specific reproductive success with Bayesian nest survival models. We calculated asymptotic population growth rates from estimated demographic rates with matrix projection models. Adult and juvenile survival and nest success were highest in habitat created by summer wildfire, intermediate in MPB infestations, and lowest in habitat created by fall prescribed fire. Mean posterior distributions of population growth rates indicated growing populations in habitat created by summer wildfire and declining populations in fall prescribed fire and mountain pine beetle infestations. Our finding that population growth rates were positive only in habitat created by summer wildfire underscores the need to maintain early post-wildfire habitat across the landscape. The lower growth rates in fall prescribed fire and MPB infestations may be attributed to differences in predator communities and food resources relative to summer wildfire.

Biological Control of the Chagas Disease Vector Triatoma infestans with the Entomopathogenic Fungus Beauveria bassiana Combined with an Aggregation Cue: Field, Laboratory and Mathematical Modeling Assessment

PubMed Central

Forlani, Lucas; Pedrini, Nicolás; Girotti, Juan R.; Mijailovsky, Sergio J.; Cardozo, Rubén M.; Gentile, Alberto G.; Hernández-Suárez, Carlos M.; Rabinovich, Jorge E.; Juárez, M. Patricia

2015-01-01

Background Current Chagas disease vector control strategies, based on chemical insecticide spraying, are growingly threatened by the emergence of pyrethroid-resistant Triatoma infestans populations in the Gran Chaco region of South America. Methodology and findings We have already shown that the entomopathogenic fungus Beauveria bassiana has the ability to breach the insect cuticle and is effective both against pyrethroid-susceptible and pyrethroid-resistant T. infestans, in laboratory as well as field assays. It is also known that T. infestans cuticle lipids play a major role as contact aggregation pheromones. We estimated the effectiveness of pheromone-based infection boxes containing B. bassiana spores to kill indoor bugs, and its effect on the vector population dynamics. Laboratory assays were performed to estimate the effect of fungal infection on female reproductive parameters. The effect of insect exuviae as an aggregation signal in the performance of the infection boxes was estimated both in the laboratory and in the field. We developed a stage-specific matrix model of T. infestans to describe the fungal infection effects on insect population dynamics, and to analyze the performance of the biopesticide device in vector biological control. Conclusions The pheromone-containing infective box is a promising new tool against indoor populations of this Chagas disease vector, with the number of boxes per house being the main driver of the reduction of the total domestic bug population. This ecologically safe approach is the first proven alternative to chemical insecticides in the control of T. infestans. The advantageous reduction in vector population by delayed-action fungal biopesticides in a contained environment is here shown supported by mathematical modeling. PMID:25969989

Cobimaximal lepton mixing from soft symmetry breaking

NASA Astrophysics Data System (ADS)

Grimus, W.; Lavoura, L.

2017-11-01

Cobimaximal lepton mixing, i.e.θ23 = 45 ° and δ = ± 90 ° in the lepton mixing matrix V, arises as a consequence of SV =V* P, where S is the permutation matrix that interchanges the second and third rows of V and P is a diagonal matrix of phase factors. We prove that any such V may be written in the form V = URP, where U is any predefined unitary matrix satisfying SU =U*, R is an orthogonal, i.e. real, matrix, and P is a diagonal matrix satisfying P2 = P. Using this theorem, we demonstrate the equivalence of two ways of constructing models for cobimaximal mixing-one way that uses a standard CP symmetry and a different way that uses a CP symmetry including μ-τ interchange. We also present two simple seesaw models to illustrate this equivalence; those models have, in addition to the CP symmetry, flavour symmetries broken softly by the Majorana mass terms of the right-handed neutrino singlets. Since each of the two models needs four scalar doublets, we investigate how to accommodate the Standard Model Higgs particle in them.

Modelling the Dynamics of Post-Vaccination Immunity Rate in a Population of Sahelian Sheep after a Vaccination Campaign against Peste des Petits Ruminants Virus

PubMed Central

Lancelot, Renaud; Lesnoff, Matthieu

2016-01-01

Background Peste des petits ruminants (PPR) is an acute infectious viral disease affecting domestic small ruminants (sheep and goats) and some wild ruminant species in Africa, the Middle East and Asia. A global PPR control strategy based on mass vaccination—in regions where PPR is endemic—was recently designed and launched by international organizations. Sahelian Africa is one of the most challenging endemic regions for PPR control. Indeed, strong seasonal and annual variations in mating, mortality and offtake rates result in a complex population dynamics which might in turn alter the population post-vaccination immunity rate (PIR), and thus be important to consider for the implementation of vaccination campaigns. Methods In a context of preventive vaccination in epidemiological units without PPR virus transmission, we developed a predictive, dynamic model based on a seasonal matrix population model to simulate PIR dynamics. This model was mostly calibrated with demographic and epidemiological parameters estimated from a long-term follow-up survey of small ruminant herds. We used it to simulate the PIR dynamics following a single PPR vaccination campaign in a Sahelian sheep population, and to assess the effects of (i) changes in offtake rate related to the Tabaski (a Muslim feast following the lunar calendar), and (ii) the date of implementation of the vaccination campaigns. Results The persistence of PIR was not influenced by the Tabaski date. Decreasing the vaccination coverage from 100 to 80% had limited effects on PIR. However, lower vaccination coverage did not provide sufficient immunity rates (PIR < 70%). As a trade-off between model predictions and other considerations like animal physiological status, and suitability for livestock farmers, we would suggest to implement vaccination campaigns in September-October. This model is a first step towards better decision support for animal health authorities. It might be adapted to other species, livestock farming systems or diseases. PMID:27603710

The genetic variance but not the genetic covariance of life-history traits changes towards the north in a time-constrained insect.

PubMed

Sniegula, Szymon; Golab, Maria J; Drobniak, Szymon M; Johansson, Frank

2018-06-01

Seasonal time constraints are usually stronger at higher than lower latitudes and can exert strong selection on life-history traits and the correlations among these traits. To predict the response of life-history traits to environmental change along a latitudinal gradient, information must be obtained about genetic variance in traits and also genetic correlation between traits, that is the genetic variance-covariance matrix, G. Here, we estimated G for key life-history traits in an obligate univoltine damselfly that faces seasonal time constraints. We exposed populations to simulated native temperatures and photoperiods and common garden environmental conditions in a laboratory set-up. Despite differences in genetic variance in these traits between populations (lower variance at northern latitudes), there was no evidence for latitude-specific covariance of the life-history traits. At simulated native conditions, all populations showed strong genetic and phenotypic correlations between traits that shaped growth and development. The variance-covariance matrix changed considerably when populations were exposed to common garden conditions compared with the simulated natural conditions, showing the importance of environmentally induced changes in multivariate genetic structure. Our results highlight the importance of estimating variance-covariance matrixes in environments that mimic selection pressures and not only trait variances or mean trait values in common garden conditions for understanding the trait evolution across populations and environments. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

Population density, sex ratio, body size and fluctuating asymmetry of Ceroglossus chilensis (Carabidae) in the fragmented Maulino forest and surrounding pine plantations

NASA Astrophysics Data System (ADS)

Henríquez, Paula; Donoso, Denise S.; Grez, Audrey A.

2009-11-01

Habitat fragmentation results in new environmental conditions that may stress resident populations. Such stress may be reflected in demographical or morphological changes in the individuals inhabiting those landscapes. This study evaluates the effects of fragmentation of the Maulino forest on population density, sex ratio, body size, and fluctuating asymmetry (FA) of the endemic carabid Ceroglossus chilensis. Individuals of C. chilensis were collected during 2006 in five locations at Los Queules National Reserve (continuous forest), in five forest fragments and in five areas of surrounding pine plantations (matrix). In each location, once a season, 40 pitfall traps (20 in the centre, 20 in the edge), were opened for 72 h. Population density of C. chilensis was higher in the small fragments than in the pine matrix, with intermediate densities in the continuous forest; sex ratio did not differ significantly from 1:1 in the three habitats. Individuals from the centre of fragments were smaller than those from the centre of continuous forest, and FA did not vary significantly among habitats. These results suggest that small forest fragments maintain dense populations of C. chilensis and therefore they must be considered in conservation strategies. Although the decrease of the body size suggests that small remnants should be connected by managing the structure of the surrounding matrix, facilitating the dispersion of this carabid across the landscape and avoiding possible antagonistic interactions inside small fragments.

MIXOR: a computer program for mixed-effects ordinal regression analysis.

PubMed

Hedeker, D; Gibbons, R D

1996-03-01

MIXOR provides maximum marginal likelihood estimates for mixed-effects ordinal probit, logistic, and complementary log-log regression models. These models can be used for analysis of dichotomous and ordinal outcomes from either a clustered or longitudinal design. For clustered data, the mixed-effects model assumes that data within clusters are dependent. The degree of dependency is jointly estimated with the usual model parameters, thus adjusting for dependence resulting from clustering of the data. Similarly, for longitudinal data, the mixed-effects approach can allow for individual-varying intercepts and slopes across time, and can estimate the degree to which these time-related effects vary in the population of individuals. MIXOR uses marginal maximum likelihood estimation, utilizing a Fisher-scoring solution. For the scoring solution, the Cholesky factor of the random-effects variance-covariance matrix is estimated, along with the effects of model covariates. Examples illustrating usage and features of MIXOR are provided.

Stability of an SAIRS alcoholism model on scale-free networks

NASA Astrophysics Data System (ADS)

Xiang, Hong; Liu, Ying-Ping; Huo, Hai-Feng

2017-05-01

A new SAIRS alcoholism model with birth and death on complex heterogeneous networks is proposed. The total population of our model is partitioned into four compartments: the susceptible individual, the light problem alcoholic, the heavy problem alcoholic and the recovered individual. The spread of alcoholism threshold R0 is calculated by the next generation matrix method. When R0 < 1, the alcohol free equilibrium is globally asymptotically stable, then the alcoholics will disappear. When R0 > 1, the alcoholism equilibrium is global attractivity, then the number of alcoholics will remain stable and alcoholism will become endemic. Furthermore, the modified SAIRS alcoholism model on weighted contact network is introduced. Dynamical behavior of the modified model is also studied. Numerical simulations are also presented to verify and extend theoretical results. Our results show that it is very important to treat alcoholics to control the spread of the alcoholism.

Multivariate Qst–Fst Comparisons: A Neutrality Test for the Evolution of the G Matrix in Structured Populations

PubMed Central

Martin, Guillaume; Chapuis, Elodie; Goudet, Jérôme

2008-01-01

Neutrality tests in quantitative genetics provide a statistical framework for the detection of selection on polygenic traits in wild populations. However, the existing method based on comparisons of divergence at neutral markers and quantitative traits (Qst–Fst) suffers from several limitations that hinder a clear interpretation of the results with typical empirical designs. In this article, we propose a multivariate extension of this neutrality test based on empirical estimates of the among-populations (D) and within-populations (G) covariance matrices by MANOVA. A simple pattern is expected under neutrality: D = 2Fst/(1 − Fst)G, so that neutrality implies both proportionality of the two matrices and a specific value of the proportionality coefficient. This pattern is tested using Flury's framework for matrix comparison [common principal-component (CPC) analysis], a well-known tool in G matrix evolution studies. We show the importance of using a Bartlett adjustment of the test for the small sample sizes typically found in empirical studies. We propose a dual test: (i) that the proportionality coefficient is not different from its neutral expectation [2Fst/(1 − Fst)] and (ii) that the MANOVA estimates of mean square matrices between and among populations are proportional. These two tests combined provide a more stringent test for neutrality than the classic Qst–Fst comparison and avoid several statistical problems. Extensive simulations of realistic empirical designs suggest that these tests correctly detect the expected pattern under neutrality and have enough power to efficiently detect mild to strong selection (homogeneous, heterogeneous, or mixed) when it is occurring on a set of traits. This method also provides a rigorous and quantitative framework for disentangling the effects of different selection regimes and of drift on the evolution of the G matrix. We discuss practical requirements for the proper application of our test in empirical studies and potential extensions. PMID:18245845

On Connected Diagrams and Cumulants of Erdős-Rényi Matrix Models

NASA Astrophysics Data System (ADS)

Khorunzhiy, O.

2008-08-01

Regarding the adjacency matrices of n-vertex graphs and related graph Laplacian we introduce two families of discrete matrix models constructed both with the help of the Erdős-Rényi ensemble of random graphs. Corresponding matrix sums represent the characteristic functions of the average number of walks and closed walks over the random graph. These sums can be considered as discrete analogues of the matrix integrals of random matrix theory. We study the diagram structure of the cumulant expansions of logarithms of these matrix sums and analyze the limiting expressions as n → ∞ in the cases of constant and vanishing edge probabilities.

An integrated workflow for stress and flow modelling using outcrop-derived discrete fracture networks

NASA Astrophysics Data System (ADS)

Bisdom, K.; Nick, H. M.; Bertotti, G.

2017-06-01

Fluid flow in naturally fractured reservoirs is often controlled by subseismic-scale fracture networks. Although the fracture network can be partly sampled in the direct vicinity of wells, the inter-well scale network is poorly constrained in fractured reservoir models. Outcrop analogues can provide data for populating domains of the reservoir model where no direct measurements are available. However, extracting relevant statistics from large outcrops representative of inter-well scale fracture networks remains challenging. Recent advances in outcrop imaging provide high-resolution datasets that can cover areas of several hundred by several hundred meters, i.e. the domain between adjacent wells, but even then, data from the high-resolution models is often upscaled to reservoir flow grids, resulting in loss of accuracy. We present a workflow that uses photorealistic georeferenced outcrop models to construct geomechanical and fluid flow models containing thousands of discrete fractures covering sufficiently large areas, that does not require upscaling to model permeability. This workflow seamlessly integrates geomechanical Finite Element models with flow models that take into account stress-sensitive fracture permeability and matrix flow to determine the full permeability tensor. The applicability of this workflow is illustrated using an outcropping carbonate pavement in the Potiguar basin in Brazil, from which 1082 fractures are digitised. The permeability tensor for a range of matrix permeabilities shows that conventional upscaling to effective grid properties leads to potential underestimation of the true permeability and the orientation of principal permeabilities. The presented workflow yields the full permeability tensor model of discrete fracture networks with stress-induced apertures, instead of relying on effective properties as most conventional flow models do.

LA-ICP-MS depth profile analysis of apatite: Protocol and implications for (U-Th)/He thermochronometry

NASA Astrophysics Data System (ADS)

Johnstone, Samuel; Hourigan, Jeremy; Gallagher, Christopher

2013-05-01

Heterogeneous concentrations of α-producing nuclides in apatite have been recognized through a variety of methods. The presence of zonation in apatite complicates both traditional α-ejection corrections and diffusive models, both of which operate under the assumption of homogeneous concentrations. In this work we develop a method for measuring radial concentration profiles of 238U and 232Th in apatite by laser ablation ICP-MS depth profiling. We then focus on one application of this method, removing bias introduced by applying inappropriate α-ejection corrections. Formal treatment of laser ablation ICP-MS depth profile calibration for apatite includes construction and calibration of matrix-matched standards and quantification of rates of elemental fractionation. From this we conclude that matrix-matched standards provide more robust monitors of fractionation rate and concentrations than doped silicate glass standards. We apply laser ablation ICP-MS depth profiling to apatites from three unknown populations and small, intact crystals of Durango fluorapatite. Accurate and reproducible Durango apatite dates suggest that prolonged exposure to laser drilling does not impact cooling ages. Intracrystalline concentrations vary by at least a factor of 2 in the majority of the samples analyzed, but concentration variation only exceeds 5x in 5 grains and 10x in 1 out of the 63 grains analyzed. Modeling of synthetic concentration profiles suggests that for concentration variations of 2x and 10x individual homogeneous versus zonation dependent α-ejection corrections could lead to age bias of >5% and >20%, respectively. However, models based on measured concentration profiles only generated biases exceeding 5% in 13 of the 63 cases modeled. Application of zonation dependent α-ejection corrections did not significantly reduce the age dispersion present in any of the populations studied. This suggests that factors beyond homogeneous α-ejection corrections are the dominant source of overdispersion in apatite (U-Th)/He cooling ages.

Accuracy of inference on the physics of binary evolution from gravitational-wave observations

NASA Astrophysics Data System (ADS)

Barrett, Jim W.; Gaebel, Sebastian M.; Neijssel, Coenraad J.; Vigna-Gómez, Alejandro; Stevenson, Simon; Berry, Christopher P. L.; Farr, Will M.; Mandel, Ilya

2018-04-01

The properties of the population of merging binary black holes encode some of the uncertain physics underlying the evolution of massive stars in binaries. The binary black hole merger rate and chirp-mass distribution are being measured by ground-based gravitational-wave detectors. We consider isolated binary evolution, and explore how accurately the physical model can be constrained with such observations by applying the Fisher information matrix to the merging black hole population simulated with the rapid binary-population synthesis code COMPAS. We investigate variations in four COMPAS parameters: common-envelope efficiency, kick-velocity dispersion, and mass-loss rates during the luminous blue variable and Wolf-Rayet stellar-evolutionary phases. We find that ˜1000 observations would constrain these model parameters to a fractional accuracy of a few per cent. Given the empirically determined binary black hole merger rate, we can expect gravitational-wave observations alone to place strong constraints on the physics of stellar and binary evolution within a few years. Our approach can be extended to use other observational data sets; combining observations at different evolutionary stages will lead to a better understanding of stellar and binary physics.

Accuracy of inference on the physics of binary evolution from gravitational-wave observations

NASA Astrophysics Data System (ADS)

Barrett, Jim W.; Gaebel, Sebastian M.; Neijssel, Coenraad J.; Vigna-Gómez, Alejandro; Stevenson, Simon; Berry, Christopher P. L.; Farr, Will M.; Mandel, Ilya

2018-07-01

The properties of the population of merging binary black holes encode some of the uncertain physics underlying the evolution of massive stars in binaries. The binary black hole merger rate and chirp-mass distribution are being measured by ground-based gravitational-wave detectors. We consider isolated binary evolution, and explore how accurately the physical model can be constrained with such observations by applying the Fisher information matrix to the merging black hole population simulated with the rapid binary-population synthesis code COMPAS. We investigate variations in four COMPAS parameters: common-envelope efficiency, kick-velocity dispersion and mass-loss rates during the luminous blue variable, and Wolf-Rayet stellar-evolutionary phases. We find that ˜1000 observations would constrain these model parameters to a fractional accuracy of a few per cent. Given the empirically determined binary black hole merger rate, we can expect gravitational-wave observations alone to place strong constraints on the physics of stellar and binary evolution within a few years. Our approach can be extended to use other observational data sets; combining observations at different evolutionary stages will lead to a better understanding of stellar and binary physics.

Further Improvements to Linear Mixed Models for Genome-Wide Association Studies

PubMed Central

Widmer, Christian; Lippert, Christoph; Weissbrod, Omer; Fusi, Nicolo; Kadie, Carl; Davidson, Robert; Listgarten, Jennifer; Heckerman, David

2014-01-01

We examine improvements to the linear mixed model (LMM) that better correct for population structure and family relatedness in genome-wide association studies (GWAS). LMMs rely on the estimation of a genetic similarity matrix (GSM), which encodes the pairwise similarity between every two individuals in a cohort. These similarities are estimated from single nucleotide polymorphisms (SNPs) or other genetic variants. Traditionally, all available SNPs are used to estimate the GSM. In empirical studies across a wide range of synthetic and real data, we find that modifications to this approach improve GWAS performance as measured by type I error control and power. Specifically, when only population structure is present, a GSM constructed from SNPs that well predict the phenotype in combination with principal components as covariates controls type I error and yields more power than the traditional LMM. In any setting, with or without population structure or family relatedness, a GSM consisting of a mixture of two component GSMs, one constructed from all SNPs and another constructed from SNPs that well predict the phenotype again controls type I error and yields more power than the traditional LMM. Software implementing these improvements and the experimental comparisons are available at http://microsoft.com/science. PMID:25387525

Mapping of epistatic quantitative trait loci in four-way crosses.

PubMed

He, Xiao-Hong; Qin, Hongde; Hu, Zhongli; Zhang, Tianzhen; Zhang, Yuan-Ming

2011-01-01

Four-way crosses (4WC) involving four different inbred lines often appear in plant and animal commercial breeding programs. Direct mapping of quantitative trait loci (QTL) in these commercial populations is both economical and practical. However, the existing statistical methods for mapping QTL in a 4WC population are built on the single-QTL genetic model. This simple genetic model fails to take into account QTL interactions, which play an important role in the genetic architecture of complex traits. In this paper, therefore, we attempted to develop a statistical method to detect epistatic QTL in 4WC population. Conditional probabilities of QTL genotypes, computed by the multi-point single locus method, were used to sample the genotypes of all putative QTL in the entire genome. The sampled genotypes were used to construct the design matrix for QTL effects. All QTL effects, including main and epistatic effects, were simultaneously estimated by the penalized maximum likelihood method. The proposed method was confirmed by a series of Monte Carlo simulation studies and real data analysis of cotton. The new method will provide novel tools for the genetic dissection of complex traits, construction of QTL networks, and analysis of heterosis.

Further Improvements to Linear Mixed Models for Genome-Wide Association Studies

NASA Astrophysics Data System (ADS)

Widmer, Christian; Lippert, Christoph; Weissbrod, Omer; Fusi, Nicolo; Kadie, Carl; Davidson, Robert; Listgarten, Jennifer; Heckerman, David

2014-11-01

We examine improvements to the linear mixed model (LMM) that better correct for population structure and family relatedness in genome-wide association studies (GWAS). LMMs rely on the estimation of a genetic similarity matrix (GSM), which encodes the pairwise similarity between every two individuals in a cohort. These similarities are estimated from single nucleotide polymorphisms (SNPs) or other genetic variants. Traditionally, all available SNPs are used to estimate the GSM. In empirical studies across a wide range of synthetic and real data, we find that modifications to this approach improve GWAS performance as measured by type I error control and power. Specifically, when only population structure is present, a GSM constructed from SNPs that well predict the phenotype in combination with principal components as covariates controls type I error and yields more power than the traditional LMM. In any setting, with or without population structure or family relatedness, a GSM consisting of a mixture of two component GSMs, one constructed from all SNPs and another constructed from SNPs that well predict the phenotype again controls type I error and yields more power than the traditional LMM. Software implementing these improvements and the experimental comparisons are available at http://microsoft.com/science.

Further improvements to linear mixed models for genome-wide association studies.

PubMed

Widmer, Christian; Lippert, Christoph; Weissbrod, Omer; Fusi, Nicolo; Kadie, Carl; Davidson, Robert; Listgarten, Jennifer; Heckerman, David

2014-11-12

We examine improvements to the linear mixed model (LMM) that better correct for population structure and family relatedness in genome-wide association studies (GWAS). LMMs rely on the estimation of a genetic similarity matrix (GSM), which encodes the pairwise similarity between every two individuals in a cohort. These similarities are estimated from single nucleotide polymorphisms (SNPs) or other genetic variants. Traditionally, all available SNPs are used to estimate the GSM. In empirical studies across a wide range of synthetic and real data, we find that modifications to this approach improve GWAS performance as measured by type I error control and power. Specifically, when only population structure is present, a GSM constructed from SNPs that well predict the phenotype in combination with principal components as covariates controls type I error and yields more power than the traditional LMM. In any setting, with or without population structure or family relatedness, a GSM consisting of a mixture of two component GSMs, one constructed from all SNPs and another constructed from SNPs that well predict the phenotype again controls type I error and yields more power than the traditional LMM. Software implementing these improvements and the experimental comparisons are available at http://microsoft.com/science.

Three-dimensional finite element modeling of pericellular matrix and cell mechanics in the nucleus pulposus of the intervertebral disk based on in situ morphology.

PubMed

Cao, Li; Guilak, Farshid; Setton, Lori A

2011-02-01

Nucleus pulposus (NP) cells of the intervertebral disk (IVD) have unique morphological characteristics and biologic responses to mechanical stimuli that may regulate maintenance and health of the IVD. NP cells reside as single cell, paired or multiple cells in a contiguous pericellular matrix (PCM), whose structure and properties may significantly influence cell and extracellular matrix mechanics. In this study, a computational model was developed to predict the stress-strain, fluid pressure and flow fields for cells and their surrounding PCM in the NP using three-dimensional (3D) finite element models based on the in situ morphology of cell-PCM regions of the mature rat NP, measured using confocal microscopy. Three-dimensional geometries of the extracellular matrix and representative cell-matrix units were used to construct 3D finite element models of the structures as isotropic and biphasic materials. In response to compressive strain of the extracellular matrix, NP cells and PCM regions were predicted to experience volumetric strains that were 1.9-3.7 and 1.4-2.1 times greater than the extracellular matrix, respectively. Volumetric and deviatoric strain concentrations were generally found at the cell/PCM interface, while von Mises stress concentrations were associated with the PCM/extracellular matrix interface. Cell-matrix units containing greater cell numbers were associated with higher peak cell strains and lower rates of fluid pressurization upon loading. These studies provide new model predictions for micromechanics of NP cells that can contribute to an understanding of mechanotransduction in the IVD and its changes with aging and degeneration.

Numerical simulation of elasto-plastic deformation of composites: evolution of stress microfields and implications for homogenization models

NASA Astrophysics Data System (ADS)

González, C.; Segurado, J.; LLorca, J.

2004-07-01

The deformation of a composite made up of a random and homogeneous dispersion of elastic spheres in an elasto-plastic matrix was simulated by the finite element analysis of three-dimensional multiparticle cubic cells with periodic boundary conditions. "Exact" results (to a few percent) in tension and shear were determined by averaging 12 stress-strain curves obtained from cells containing 30 spheres, and they were compared with the predictions of secant homogenization models. In addition, the numerical simulations supplied detailed information of the stress microfields, which was used to ascertain the accuracy and the limitations of the homogenization models to include the nonlinear deformation of the matrix. It was found that secant approximations based on the volume-averaged second-order moment of the matrix stress tensor, combined with a highly accurate linear homogenization model, provided excellent predictions of the composite response when the matrix strain hardening rate was high. This was not the case, however, in composites which exhibited marked plastic strain localization in the matrix. The analysis of the evolution of the matrix stresses revealed that better predictions of the composite behavior can be obtained with new homogenization models which capture the essential differences in the stress carried by the elastic and plastic regions in the matrix at the onset of plastic deformation.

A Deep Stochastic Model for Detecting Community in Complex Networks

NASA Astrophysics Data System (ADS)

Fu, Jingcheng; Wu, Jianliang

2017-01-01

Discovering community structures is an important step to understanding the structure and dynamics of real-world networks in social science, biology and technology. In this paper, we develop a deep stochastic model based on non-negative matrix factorization to identify communities, in which there are two sets of parameters. One is the community membership matrix, of which the elements in a row correspond to the probabilities of the given node belongs to each of the given number of communities in our model, another is the community-community connection matrix, of which the element in the i-th row and j-th column represents the probability of there being an edge between a randomly chosen node from the i-th community and a randomly chosen node from the j-th community. The parameters can be evaluated by an efficient updating rule, and its convergence can be guaranteed. The community-community connection matrix in our model is more precise than the community-community connection matrix in traditional non-negative matrix factorization methods. Furthermore, the method called symmetric nonnegative matrix factorization, is a special case of our model. Finally, based on the experiments on both synthetic and real-world networks data, it can be demonstrated that our algorithm is highly effective in detecting communities.

Multiscale Modeling of Ceramic Matrix Composites

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Mital, Subodh K.; Pineda, Evan J.; Arnold, Steven M.

2015-01-01

Results of multiscale modeling simulations of the nonlinear response of SiC/SiC ceramic matrix composites are reported, wherein the microstructure of the ceramic matrix is captured. This micro scale architecture, which contains free Si material as well as the SiC ceramic, is responsible for residual stresses that play an important role in the subsequent thermo-mechanical behavior of the SiC/SiC composite. Using the novel Multiscale Generalized Method of Cells recursive micromechanics theory, the microstructure of the matrix, as well as the microstructure of the composite (fiber and matrix) can be captured.

Cost-effective management alternatives for Snake River Chinook salmon: a biological-economic synthesis.

PubMed

Halsing, David L; Moore, Michael R

2008-04-01

The mandate to increase endangered salmon populations in the Columbia River Basin of North America has created a complex, controversial resource-management issue. We constructed an integrated assessment model as a tool for analyzing biological-economic trade-offs in recovery of Snake River spring- and summer-run chinook salmon (Oncorhynchus tshawytscha). We merged 3 frameworks: a salmon-passage model to predict migration and survival of smolts; an age-structured matrix model to predict long-term population growth rates of salmon stocks; and a cost-effectiveness analysis to determine a set of least-cost management alternatives for achieving particular population growth rates. We assessed 6 individual salmon-management measures and 76 management alternatives composed of one or more measures. To reflect uncertainty, results were derived for different assumptions of effectiveness of smolt transport around dams. Removal of an estuarine predator, the Caspian Tern (Sterna caspia), was cost-effective and generally increased long-term population growth rates regardless of transport effectiveness. Elimination of adult salmon harvest had a similar effect over a range of its cost estimates. The specific management alternatives in the cost-effective set depended on assumptions about transport effectiveness. On the basis of recent estimates of smolt transport effectiveness, alternatives that discontinued transportation or breached dams were prevalent in the cost-effective set, whereas alternatives that maximized transportation dominated if transport effectiveness was relatively high. More generally, the analysis eliminated 80-90% of management alternatives from the cost-effective set. Application of our results to salmon management is limited by data availability and model assumptions, but these limitations can help guide research that addresses critical uncertainties and information. Our results thus demonstrate that linking biology and economics through integrated models can provide valuable tools for science-based policy and management.

Cost-effective management alternatives for Snake river chinook salmon: A biological-economic synthesis

USGS Publications Warehouse

Halsing, D.L.; Moore, M.R.

2008-01-01

The mandate to increase endangered salmon populations in the Columbia River Basin of North America has created a complex, controversial resource-management issue. We constructed an integrated assessment model as a tool for analyzing biological-economic trade-offs in recovery of Snake River spring- and summer-run chinook salmon (Oncorhynchus tshawytscha). We merged 3 frameworks: a salmon-passage model to predict migration and survival of smolts; an age-structured matrix model to predict long-term population growth rates of salmon stocks; and a cost-effectiveness analysis to determine a set of least-cost management alternatives for achieving particular population growth rates. We assessed 6 individual salmon-management measures and 76 management alternatives composed of one or more measures. To reflect uncertainty, results were derived for different assumptions of effectiveness of smolt transport around dams. Removal of an estuarine predator, the Caspian Tern (Sterna caspia), was cost-effective and generally increased long-term population growth rates regardless of transport effectiveness. Elimination of adult salmon harvest had a similar effect over a range of its cost estimates. The specific management alternatives in the cost-effective set depended on assumptions about transport effectiveness. On the basis of recent estimates of smolt transport effectiveness, alternatives that discontinued transportation or breached dams were prevalent in the cost-effective set, whereas alternatives that maximized transportation dominated if transport effectiveness was relatively high. More generally, the analysis eliminated 80-90% of management alternatives from the cost-effective set. Application of our results to salmon management is limited by data availability and model assumptions, but these limitations can help guide research that addresses critical uncertainties and information. Our results thus demonstrate that linking biology and economics through integrated models can provide valuable tools for science-based policy and management.

Structural symmetry in evolutionary games.

PubMed

McAvoy, Alex; Hauert, Christoph

2015-10-06

In evolutionary game theory, an important measure of a mutant trait (strategy) is its ability to invade and take over an otherwise-monomorphic population. Typically, one quantifies the success of a mutant strategy via the probability that a randomly occurring mutant will fixate in the population. However, in a structured population, this fixation probability may depend on where the mutant arises. Moreover, the fixation probability is just one quantity by which one can measure the success of a mutant; fixation time, for instance, is another. We define a notion of homogeneity for evolutionary games that captures what it means for two single-mutant states, i.e. two configurations of a single mutant in an otherwise-monomorphic population, to be 'evolutionarily equivalent' in the sense that all measures of evolutionary success are the same for both configurations. Using asymmetric games, we argue that the term 'homogeneous' should apply to the evolutionary process as a whole rather than to just the population structure. For evolutionary matrix games in graph-structured populations, we give precise conditions under which the resulting process is homogeneous. Finally, we show that asymmetric matrix games can be reduced to symmetric games if the population structure possesses a sufficient degree of symmetry. © 2015 The Author(s).

Structural symmetry in evolutionary games

PubMed Central

McAvoy, Alex; Hauert, Christoph

2015-01-01

In evolutionary game theory, an important measure of a mutant trait (strategy) is its ability to invade and take over an otherwise-monomorphic population. Typically, one quantifies the success of a mutant strategy via the probability that a randomly occurring mutant will fixate in the population. However, in a structured population, this fixation probability may depend on where the mutant arises. Moreover, the fixation probability is just one quantity by which one can measure the success of a mutant; fixation time, for instance, is another. We define a notion of homogeneity for evolutionary games that captures what it means for two single-mutant states, i.e. two configurations of a single mutant in an otherwise-monomorphic population, to be ‘evolutionarily equivalent’ in the sense that all measures of evolutionary success are the same for both configurations. Using asymmetric games, we argue that the term ‘homogeneous’ should apply to the evolutionary process as a whole rather than to just the population structure. For evolutionary matrix games in graph-structured populations, we give precise conditions under which the resulting process is homogeneous. Finally, we show that asymmetric matrix games can be reduced to symmetric games if the population structure possesses a sufficient degree of symmetry. PMID:26423436

The Effects of Q-Matrix Design on Classification Accuracy in the Log-Linear Cognitive Diagnosis Model.

PubMed

Madison, Matthew J; Bradshaw, Laine P

2015-06-01

Diagnostic classification models are psychometric models that aim to classify examinees according to their mastery or non-mastery of specified latent characteristics. These models are well-suited for providing diagnostic feedback on educational assessments because of their practical efficiency and increased reliability when compared with other multidimensional measurement models. A priori specifications of which latent characteristics or attributes are measured by each item are a core element of the diagnostic assessment design. This item-attribute alignment, expressed in a Q-matrix, precedes and supports any inference resulting from the application of the diagnostic classification model. This study investigates the effects of Q-matrix design on classification accuracy for the log-linear cognitive diagnosis model. Results indicate that classification accuracy, reliability, and convergence rates improve when the Q-matrix contains isolated information from each measured attribute.

Simulating Cancer Growth with Multiscale Agent-Based Modeling

PubMed Central

Wang, Zhihui; Butner, Joseph D.; Kerketta, Romica; Cristini, Vittorio; Deisboeck, Thomas S.

2014-01-01

There have been many techniques developed in recent years to in silico model a variety of cancer behaviors. Agent-based modeling is a specific discrete-based hybrid modeling approach that allows simulating the role of diversity in cell populations as well as within each individual cell; it has therefore become a powerful modeling method widely used by computational cancer researchers. Many aspects of tumor morphology including phenotype-changing mutations, the adaptation to microenvironment, the process of angiogenesis, the influence of extracellular matrix, reactions to chemotherapy or surgical intervention, the effects of oxygen and nutrient availability, and metastasis and invasion of healthy tissues have been incorporated and investigated in agent-based models. In this review, we introduce some of the most recent agent-based models that have provided insight into the understanding of cancer growth and invasion, spanning multiple biological scales in time and space, and we further describe several experimentally testable hypotheses generated by those models. We also discuss some of the current challenges of multiscale agent-based cancer models. PMID:24793698

Translating effects of inbreeding depression on component vital rates to overall population growth in endangered bighorn sheep.

PubMed

Johnson, Heather E; Mills, L Scott; Wehausen, John D; Stephenson, Thomas R; Luikart, Gordon

2011-12-01

Evidence of inbreeding depression is commonly detected from the fitness traits of animals, yet its effects on population growth rates of endangered species are rarely assessed. We examined whether inbreeding depression was affecting Sierra Nevada bighorn sheep (Ovis canadensis sierrae), a subspecies listed as endangered under the U.S. Endangered Species Act. Our objectives were to characterize genetic variation in this subspecies; test whether inbreeding depression affects bighorn sheep vital rates (adult survival and female fecundity); evaluate whether inbreeding depression may limit subspecies recovery; and examine the potential for genetic management to increase population growth rates. Genetic variation in 4 populations of Sierra Nevada bighorn sheep was among the lowest reported for any wild bighorn sheep population, and our results suggest that inbreeding depression has reduced adult female fecundity. Despite this population sizes and growth rates predicted from matrix-based projection models demonstrated that inbreeding depression would not substantially inhibit the recovery of Sierra Nevada bighorn sheep populations in the next approximately 8 bighorn sheep generations (48 years). Furthermore, simulations of genetic rescue within the subspecies did not suggest that such activities would appreciably increase population sizes or growth rates during the period we modeled (10 bighorn sheep generations, 60 years). Only simulations that augmented the Mono Basin population with genetic variation from other subspecies, which is not currently a management option, predicted significant increases in population size. Although we recommend that recovery activities should minimize future losses of genetic variation, genetic effects within these endangered populations-either negative (inbreeding depression) or positive (within subspecies genetic rescue)-appear unlikely to dramatically compromise or stimulate short-term conservation efforts. The distinction between detecting the effects of inbreeding depression on a component vital rate (e.g., fecundity) and the effects of inbreeding depression on population growth underscores the importance of quantifying inbreeding costs relative to population dynamics to effectively manage endangered populations. ©2011 Society for Conservation Biology.

Climate warming alters effects of management on population viability of threatened species: results from a 30-year experimental study on a rare orchid.

PubMed

Sletvold, Nina; Dahlgren, Johan P; Oien, Dag-Inge; Moen, Asbjørn; Ehrlén, Johan

2013-09-01

Climate change is expected to influence the viability of populations both directly and indirectly, via species interactions. The effects of large-scale climate change are also likely to interact with local habitat conditions. Management actions designed to preserve threatened species therefore need to adapt both to the prevailing climate and local conditions. Yet, few studies have separated the direct and indirect effects of climatic variables on the viability of local populations and discussed the implications for optimal management. We used 30 years of demographic data to estimate the simultaneous effects of management practice and among-year variation in four climatic variables on individual survival, growth and fecundity in one coastal and one inland population of the perennial orchid Dactylorhiza lapponica in Norway. Current management, mowing, is expected to reduce competitive interactions. Statistical models of how climate and management practice influenced vital rates were incorporated into matrix population models to quantify effects on population growth rate. Effects of climate differed between mown and control plots in both populations. In particular, population growth rate increased more strongly with summer temperature in mown plots than in control plots. Population growth rate declined with spring temperature in the inland population, and with precipitation in the coastal population, and the decline was stronger in control plots in both populations. These results illustrate that both direct and indirect effects of climate change are important for population viability and that net effects depend both on local abiotic conditions and on biotic conditions in terms of management practice and intensity of competition. The results also show that effects of management practices influencing competitive interactions can strongly depend on climatic factors. We conclude that interactions between climate and management should be considered to reliably predict future population viability and optimize conservation actions. © 2013 John Wiley & Sons Ltd.

Modeling the Monotonic and Cyclic Tensile Stress-Strain Behavior of 2D and 2.5D Woven C/SiC Ceramic-Matrix Composites

NASA Astrophysics Data System (ADS)

Li, L. B.

2018-05-01

The deformation of 2D and 2.5 C/SiC woven ceramic-matrix composites (CMCs) in monotonic and cyclic loadings has been investigated. Statistical matrix multicracking and fiber failure models and the fracture mechanics interface debonding approach are used to determine the spacing of matrix cracks, the debonded length of interface, and the fraction of broken fibers. The effects of fiber volume fraction and fiber Weibull modulus on the damage evolution in the composites and on their tensile stress-strain curves are analyzed. When matrix multicracking and fiber/matrix interface debonding occur, the fiber slippage relative to the matrix in the debonded interface region of the 0° warp yarns is the main reason for the emergance of stress-strain hysteresis loops for 2D and 2.5D woven CMCs. A model of these loops is developed, and histeresis loops for the composites in cyclic loadings/unloadings are predicted.

Finite-range Coulomb gas models of banded random matrices and quantum kicked rotors

NASA Astrophysics Data System (ADS)

Pandey, Akhilesh; Kumar, Avanish; Puri, Sanjay

2017-11-01

Dyson demonstrated an equivalence between infinite-range Coulomb gas models and classical random matrix ensembles for the study of eigenvalue statistics. We introduce finite-range Coulomb gas (FRCG) models via a Brownian matrix process, and study them analytically and by Monte Carlo simulations. These models yield new universality classes, and provide a theoretical framework for the study of banded random matrices (BRMs) and quantum kicked rotors (QKRs). We demonstrate that, for a BRM of bandwidth b and a QKR of chaos parameter α , the appropriate FRCG model has the effective range d =b2/N =α2/N , for large N matrix dimensionality. As d increases, there is a transition from Poisson to classical random matrix statistics.

Modeling the Tensile Behavior of Cross-Ply C/SiC Ceramic-Matrix Composites

NASA Astrophysics Data System (ADS)

Li, L. B.; Song, Y. D.; Sun, Y. C.

2015-07-01

The tensile behavior of cross-ply C/SiC ceramic-matrix composites (CMCs) at room temperature has been investigated. Under tensile loading, the damage evolution process was observed with an optical microscope. A micromechanical approach was developed to predict the tensile stress-strain curve, which considers the damage mechanisms of transverse multicracking, matrix multicracking, fiber/matrix interface debonding, and fiber fracture. The shear-lag model was used to describe the microstress field of the damaged composite. By combining the shear-lag model with different damage models, the tensile stress-strain curve of cross-ply CMCs corresponding to each damage stage was modeled. The predicted tensile stress-strain curves of cross-ply C/SiC composites agreed with experimental data.

Finite-range Coulomb gas models of banded random matrices and quantum kicked rotors.

PubMed

Pandey, Akhilesh; Kumar, Avanish; Puri, Sanjay

2017-11-01

Dyson demonstrated an equivalence between infinite-range Coulomb gas models and classical random matrix ensembles for the study of eigenvalue statistics. We introduce finite-range Coulomb gas (FRCG) models via a Brownian matrix process, and study them analytically and by Monte Carlo simulations. These models yield new universality classes, and provide a theoretical framework for the study of banded random matrices (BRMs) and quantum kicked rotors (QKRs). We demonstrate that, for a BRM of bandwidth b and a QKR of chaos parameter α, the appropriate FRCG model has the effective range d=b^{2}/N=α^{2}/N, for large N matrix dimensionality. As d increases, there is a transition from Poisson to classical random matrix statistics.

Symmetry Transition Preserving Chirality in QCD: A Versatile Random Matrix Model

NASA Astrophysics Data System (ADS)

Kanazawa, Takuya; Kieburg, Mario

2018-06-01

We consider a random matrix model which interpolates between the chiral Gaussian unitary ensemble and the Gaussian unitary ensemble while preserving chiral symmetry. This ensemble describes flavor symmetry breaking for staggered fermions in 3D QCD as well as in 4D QCD at high temperature or in 3D QCD at a finite isospin chemical potential. Our model is an Osborn-type two-matrix model which is equivalent to the elliptic ensemble but we consider the singular value statistics rather than the complex eigenvalue statistics. We report on exact results for the partition function and the microscopic level density of the Dirac operator in the ɛ regime of QCD. We compare these analytical results with Monte Carlo simulations of the matrix model.

A novel variable selection approach that iteratively optimizes variable space using weighted binary matrix sampling.

PubMed

Deng, Bai-chuan; Yun, Yong-huan; Liang, Yi-zeng; Yi, Lun-zhao

2014-10-07

In this study, a new optimization algorithm called the Variable Iterative Space Shrinkage Approach (VISSA) that is based on the idea of model population analysis (MPA) is proposed for variable selection. Unlike most of the existing optimization methods for variable selection, VISSA statistically evaluates the performance of variable space in each step of optimization. Weighted binary matrix sampling (WBMS) is proposed to generate sub-models that span the variable subspace. Two rules are highlighted during the optimization procedure. First, the variable space shrinks in each step. Second, the new variable space outperforms the previous one. The second rule, which is rarely satisfied in most of the existing methods, is the core of the VISSA strategy. Compared with some promising variable selection methods such as competitive adaptive reweighted sampling (CARS), Monte Carlo uninformative variable elimination (MCUVE) and iteratively retaining informative variables (IRIV), VISSA showed better prediction ability for the calibration of NIR data. In addition, VISSA is user-friendly; only a few insensitive parameters are needed, and the program terminates automatically without any additional conditions. The Matlab codes for implementing VISSA are freely available on the website: https://sourceforge.net/projects/multivariateanalysis/files/VISSA/.

Susceptibility of metallic magnesium implants to bacterial biofilm infections.

PubMed

Rahim, Muhammad Imran; Rohde, Manfred; Rais, Bushra; Seitz, Jan-Marten; Mueller, Peter P

2016-06-01

Magnesium alloys have promising mechanical and biological properties as biodegradable medical implant materials for temporary applications during bone healing or as vascular stents. Whereas conventional implants are prone to colonization by treatment resistant microbial biofilms in which bacteria are embedded in a protective matrix, magnesium alloys have been reported to act antibacterial in vitro. To permit a basic assessment of antibacterial properties of implant materials in vivo an economic but robust animal model was established. Subcutaneous magnesium implants were inoculated with bacteria in a mouse model. Contrary to the expectations, bacterial activity was enhanced and prolonged in the presence of magnesium implants. Systemic antibiotic treatments were remarkably ineffective, which is a typical property of bacterial biofilms. Biofilm formation was further supported by electron microscopic analyses that revealed highly dense bacterial populations and evidence for the presence of extracellular matrix material. Bacterial agglomerates could be detected not only on the implant surface but also at a limited distance in the peri-implant tissue. Therefore, precautions may be necessary to minimize risks of metallic magnesium-containing implants in prospective clinical applications. © 2016 Wiley Periodicals, Inc. J Biomed Mater Res Part A: 104A: 1489-1499, 2016. © 2016 Wiley Periodicals, Inc.

A robust method of computing finite difference coefficients based on Vandermonde matrix

NASA Astrophysics Data System (ADS)

Zhang, Yijie; Gao, Jinghuai; Peng, Jigen; Han, Weimin

2018-05-01

When the finite difference (FD) method is employed to simulate the wave propagation, high-order FD method is preferred in order to achieve better accuracy. However, if the order of FD scheme is high enough, the coefficient matrix of the formula for calculating finite difference coefficients is close to be singular. In this case, when the FD coefficients are computed by matrix inverse operator of MATLAB, inaccuracy can be produced. In order to overcome this problem, we have suggested an algorithm based on Vandermonde matrix in this paper. After specified mathematical transformation, the coefficient matrix is transformed into a Vandermonde matrix. Then the FD coefficients of high-order FD method can be computed by the algorithm of Vandermonde matrix, which prevents the inverse of the singular matrix. The dispersion analysis and numerical results of a homogeneous elastic model and a geophysical model of oil and gas reservoir demonstrate that the algorithm based on Vandermonde matrix has better accuracy compared with matrix inverse operator of MATLAB.

A nonequilibrium model for reactive contaminant transport through fractured porous media: Model development and semianalytical solution

NASA Astrophysics Data System (ADS)

Joshi, Nitin; Ojha, C. S. P.; Sharma, P. K.

2012-10-01

In this study a conceptual model that accounts for the effects of nonequilibrium contaminant transport in a fractured porous media is developed. Present model accounts for both physical and sorption nonequilibrium. Analytical solution was developed using the Laplace transform technique, which was then numerically inverted to obtain solute concentration in the fracture matrix system. The semianalytical solution developed here can incorporate both semi-infinite and finite fracture matrix extent. In addition, the model can account for flexible boundary conditions and nonzero initial condition in the fracture matrix system. The present semianalytical solution was validated against the existing analytical solutions for the fracture matrix system. In order to differentiate between various sorption/transport mechanism different cases of sorption and mass transfer were analyzed by comparing the breakthrough curves and temporal moments. It was found that significant differences in the signature of sorption and mass transfer exists. Applicability of the developed model was evaluated by simulating the published experimental data of Calcium and Strontium transport in a single fracture. The present model simulated the experimental data reasonably well in comparison to the model based on equilibrium sorption assumption in fracture matrix system, and multi rate mass transfer model.

Scale-Dependent Fracture-Matrix Interactions And Their Impact on Radionuclide Transport - Final Report

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

Detwiler, Russell

Matrix diffusion and adsorption within a rock matrix are widely regarded as important mechanisms for retarding the transport of radionuclides and other solutes in fractured rock (e.g., Neretnieks, 1980; Tang et al., 1981; Maloszewski and Zuber, 1985; Novakowski and Lapcevic, 1994; Jardine et al., 1999; Zhou and Xie, 2003; Reimus et al., 2003a,b). When remediation options are being evaluated for old sources of contamination, where a large fraction of contaminants reside within the rock matrix, slow diffusion out of the matrix greatly increases the difficulty and timeframe of remediation. Estimating the rates of solute exchange between fractures and the adjacentmore » rock matrix is a critical factor in quantifying immobilization and/or remobilization of DOE-relevant contaminants within the subsurface. In principle, the most rigorous approach to modeling solute transport with fracture-matrix interaction would be based on local-scale coupled advection-diffusion/dispersion equations for the rock matrix and in discrete fractures that comprise the fracture network (Discrete Fracture Network and Matrix approach, hereinafter referred to as DFNM approach), fully resolving aperture variability in fractures and matrix property heterogeneity. However, such approaches are computationally demanding, and thus, many predictive models rely upon simplified models. These models typically idealize fracture rock masses as a single fracture or system of parallel fractures interacting with slabs of porous matrix or as a mobile-immobile or multi-rate mass transfer system. These idealizations provide tractable approaches for interpreting tracer tests and predicting contaminant mobility, but rely upon a fitted effective matrix diffusivity or mass-transfer coefficients. However, because these fitted parameters are based upon simplified conceptual models, their effectiveness at predicting long-term transport processes remains uncertain. Evidence of scale dependence of effective matrix diffusion coefficients obtained from tracer tests highlights this point and suggests that the underlying mechanisms and relationship between rock and fracture properties are not fully understood in large complex fracture networks. In this project, we developed a high-resolution DFN model of solute transport in fracture networks to explore and quantify the mechanisms that control transport in complex fracture networks and how these may give rise to observed scale-dependent matrix diffusion coefficients. Results demonstrate that small scale heterogeneity in the flow field caused by local aperture variability within individual fractures can lead to long-tailed breakthrough curves indicative of matrix diffusion, even in the absence of interactions with the fracture matrix. Furthermore, the temporal and spatial scale dependence of these processes highlights the inability of short-term tracer tests to estimate transport parameters that will control long-term fate and transport of contaminants in fractured aquifers.« less

On the role of hydrogel structure and degradation in controlling the transport of cell-secreted matrix molecules for engineered cartilage.

PubMed

Dhote, Valentin; Skaalure, Stacey; Akalp, Umut; Roberts, Justine; Bryant, Stephanie J; Vernerey, Franck J

2013-03-01

Damage to cartilage caused by injury or disease can lead to pain and loss of mobility, diminishing one's quality of life. Because cartilage has a limited capacity for self-repair, tissue engineering strategies, such as cells encapsulated in synthetic hydrogels, are being investigated as a means to restore the damaged cartilage. However, strategies to date are suboptimal in part because designing degradable hydrogels is complicated by structural and temporal complexities of the gel and evolving tissue along multiple length scales. To address this problem, this study proposes a multi-scale mechanical model using a triphasic formulation (solid, fluid, unbound matrix molecules) based on a single chondrocyte releasing extracellular matrix molecules within a degrading hydrogel. This model describes the key players (cells, proteoglycans, collagen) of the biological system within the hydrogel encompassing different length scales. Two mechanisms are included: temporal changes of bulk properties due to hydrogel degradation, and matrix transport. Numerical results demonstrate that the temporal change of bulk properties is a decisive factor in the diffusion of unbound matrix molecules through the hydrogel. Transport of matrix molecules in the hydrogel contributes both to the development of the pericellular matrix and the extracellular matrix and is dependent on the relative size of matrix molecules and the hydrogel mesh. The numerical results also demonstrate that osmotic pressure, which leads to changes in mesh size, is a key parameter for achieving a larger diffusivity for matrix molecules in the hydrogel. The numerical model is confirmed with experimental results of matrix synthesis by chondrocytes in biodegradable poly(ethylene glycol)-based hydrogels. This model may ultimately be used to predict key hydrogel design parameters towards achieving optimal cartilage growth. Copyright © 2012 Elsevier Ltd. All rights reserved.

On the role of hydrogel structure and degradation in controlling the transport of cell-secreted matrix molecules for engineered cartilage

PubMed Central

Dhote, Valentin; Skaalure, Stacey; Akalp, Umut; Roberts, Justine; Bryant, Stephanie J.; Vernerey, Franck J.

2012-01-01

Damage to cartilage caused by injury or disease can lead to pain and loss of mobility, diminishing one’s quality of life. Because cartilage has a limited capacity for self-repair, tissue engineering strategies, such as cells encapsulated in synthetic hydrogels, are being investigated as a means to restore the damaged cartilage. However, strategies to date are suboptimal in part because designing degradable hydrogels is complicated by structural and temporal complexities of the gel and evolving tissue along multiple length scales. To address this problem, this study proposes a multi-scale mechanical model using a triphasic formulation (solid, fluid, unbound matrix molecules) based on a single chondrocyte releasing extracellular matrix molecules within a degrading hydrogel. This model describes the key players (cells, proteoglycans, collagen) of the biological system within the hydrogel encompassing different length scales. Two mechanisms are included: temporal changes of bulk properties due to hydrogel degradation, and matrix transport. Numerical results demonstrate that the temporal change of bulk properties is a decisive factor in the diffusion of unbound matrix molecules through the hydrogel. Transport of matrix molecules in the hydrogel contributes both to the development of the pericellular matrix and the extracellular matrix and is dependent on the relative size of matrix molecules and the hydrogel mesh. The numerical results also demonstrate that osmotic pressure, which leads to changes in mesh size, is a key parameter for achieving a larger diffusivity for matrix molecules in the hydrogel. The numerical model is confirmed with experimental results of matrix synthesis by chondrocytes in biodegradable poly(ethylene glycol)-based hydrogels. This model may ultimately be used to predict key hydrogel design parameters towards achieving optimal cartilage growth. PMID:23276516

A study of fiber volume fraction effects in notched unidirectional SCS-6/Ti-15V-3Cr-3Al-3Sn composite. Ph.D. Thesis Final Report

NASA Technical Reports Server (NTRS)

Covey, Steven J.

1993-01-01

Notched unidirectional SCS-6/Ti-15-3 composite of three different fiber volume fractions (vf = 0.15, 0.37, and 0.41) was investigated for various room temperature microstructural and material properties including: fatigue crack initiation, fatigue crack growth, and fracture toughness. While the matrix hardness is similar for all fiber volume fractions, the fiber/matrix interfacial shear strength and matrix residual stress increases with fiber volume fraction. The composite fatigue crack initiation stress is shown to be matrix controlled and occurs when the net maximum matrix stress approaches the endurance limit stress of the matrix. A model is presented which includes residual stresses and presents the composite initiation stress as a function of fiber volume fraction. This model predicts a maximum composite initiation stress at vf approximately 0.15 which agrees with the experimental data. The applied composite stress levels were increased as necessary for continued crack growth. The applied Delta(K) values at crack arrest increase with fiber volume fraction by an amount better approximated using an energy based formulation rather than when scaled linear with modulus. After crack arrest, the crack growth rate exponents for vf37 and vf41 were much lower and toughness much higher, when compared to the unreinforced matrix, because of the bridged region which parades with the propagating fatigue crack. However, the vf15 material exhibited a higher crack growth rate exponent and lower toughness than the unreinforced matrix because once the bridged fibers nearest the crack mouth broke, the stress redistribution broke all bridged fibers, leaving an unbridged crack. Degraded, unbridged behavior is modeled using the residual stress state in the matrix ahead of the crack tip. Plastic zone sizes were directly measured using a metallographic technique and allow prediction of an effective matrix stress intensity which agrees with the fiber pressure model if residual stresses are considered. The sophisticated macro/micro finite element models of the 0.15 and 0.37 fiber volume fractions presented show good agreement with experimental data and the fiber pressure model when an estimated effective fiber/matrix debond length is used.

Data-Driven Learning of Q-Matrix

ERIC Educational Resources Information Center

Liu, Jingchen; Xu, Gongjun; Ying, Zhiliang

2012-01-01

The recent surge of interests in cognitive assessment has led to developments of novel statistical models for diagnostic classification. Central to many such models is the well-known "Q"-matrix, which specifies the item-attribute relationships. This article proposes a data-driven approach to identification of the "Q"-matrix and estimation of…

Heat- and light-induced transformations of Yb trapping sites in an Ar matrix

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

Tao, L.-G.; Lambo, R., E-mail: lambo@mail.ustc.edu.cn; Zhou, X.-G.

2015-11-07

The low-lying electronic states of Yb isolated in a solid Ar matrix grown at 4.2 K are characterized through absorption and emission spectroscopy. Yb atoms are found to occupy three distinct thermally stable trapping sites labeled “red,” “blue,” and “violet” according to the relative positions of the absorption features they produce. Classical simulations of the site structure and relative stability broadly reproduced the experimentally observed matrix-induced frequency shifts and thus identified the red, blue, and violet sites as due to respective single substitutional (SS), tetravacancy (TV), and hexavacancy (HV) occupation. Prolonged excitation of the {sup 1}S → {sup 1}P transitionmore » was found to transfer the Yb population from HV sites into TV and SS sites. The process showed reversibility in that annealing to 24 K predominantly transferred the TV population back into HV sites. Population kinetics were used to deduce the effective rate parameters for the site transformation processes. Experimental observations indicate that the blue and violet sites lie close in energy, whereas the red one is much less stable. Classical simulations identify the blue site as the most stable one.« less

Semiclassical matrix model for quantum chaotic transport with time-reversal symmetry

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

Novaes, Marcel, E-mail: marcel.novaes@gmail.com

2015-10-15

We show that the semiclassical approach to chaotic quantum transport in the presence of time-reversal symmetry can be described by a matrix model. In other words, we construct a matrix integral whose perturbative expansion satisfies the semiclassical diagrammatic rules for the calculation of transport statistics. One of the virtues of this approach is that it leads very naturally to the semiclassical derivation of universal predictions from random matrix theory.

Deformation, Failure, and Fatigue Life of SiC/Ti-15-3 Laminates Accurately Predicted by MAC/GMC

NASA Technical Reports Server (NTRS)

Bednarcyk, Brett A.; Arnold, Steven M.

2002-01-01

NASA Glenn Research Center's Micromechanics Analysis Code with Generalized Method of Cells (MAC/GMC) (ref.1) has been extended to enable fully coupled macro-micro deformation, failure, and fatigue life predictions for advanced metal matrix, ceramic matrix, and polymer matrix composites. Because of the multiaxial nature of the code's underlying micromechanics model, GMC--which allows the incorporation of complex local inelastic constitutive models--MAC/GMC finds its most important application in metal matrix composites, like the SiC/Ti-15-3 composite examined here. Furthermore, since GMC predicts the microscale fields within each constituent of the composite material, submodels for local effects such as fiber breakage, interfacial debonding, and matrix fatigue damage can and have been built into MAC/GMC. The present application of MAC/GMC highlights the combination of these features, which has enabled the accurate modeling of the deformation, failure, and life of titanium matrix composites.

Stress and Damage in Polymer Matrix Composite Materials Due to Material Degradation at High Temperatures

NASA Technical Reports Server (NTRS)

McManus, Hugh L.; Chamis, Christos C.

1996-01-01

This report describes analytical methods for calculating stresses and damage caused by degradation of the matrix constituent in polymer matrix composite materials. Laminate geometry, material properties, and matrix degradation states are specified as functions of position and time. Matrix shrinkage and property changes are modeled as functions of the degradation states. The model is incorporated into an existing composite mechanics computer code. Stresses, strains, and deformations at the laminate, ply, and micro levels are calculated, and from these calculations it is determined if there is failure of any kind. The rationale for the model (based on published experimental work) is presented, its integration into the laminate analysis code is outlined, and example results are given, with comparisons to existing material and structural data. The mechanisms behind the changes in properties and in surface cracking during long-term aging of polyimide matrix composites are clarified. High-temperature-material test methods are also evaluated.

Computational Modeling of Single-Cell Migration: The Leading Role of Extracellular Matrix Fibers

PubMed Central

Schlüter, Daniela K.; Ramis-Conde, Ignacio; Chaplain, Mark A.J.

2012-01-01

Cell migration is vitally important in a wide variety of biological contexts ranging from embryonic development and wound healing to malignant diseases such as cancer. It is a very complex process that is controlled by intracellular signaling pathways as well as the cell’s microenvironment. Due to its importance and complexity, it has been studied for many years in the biomedical sciences, and in the last 30 years it also received an increasing amount of interest from theoretical scientists and mathematical modelers. Here we propose a force-based, individual-based modeling framework that links single-cell migration with matrix fibers and cell-matrix interactions through contact guidance and matrix remodelling. With this approach, we can highlight the effect of the cell’s environment on its migration. We investigate the influence of matrix stiffness, matrix architecture, and cell speed on migration using quantitative measures that allow us to compare the results to experiments. PMID:22995486

The Effect of Fiber Architecture on Matrix Cracking in Sic/sic Cmc's

NASA Technical Reports Server (NTRS)

Morscher, Gregory N.

2005-01-01

Applications incorporating silicon carbide fiber reinforced silicon carbide matrix composites (CMC's) will require a wide range of fiber architectures in order to fabricate complex shape. The stress-strain response of a given SiC/SiC system for different architectures and orientations will be required in order to design and effectively life-model future components. The mechanism for non-linear stress-strain behavior in CMC's is the formation and propagation of bridged-matrix cracks throughout the composite. A considerable amount of understanding has been achieved for the stress-dependent matrix cracking behavior of SiC fiber reinforced SiC matrix systems containing melt-infiltrated Si. This presentation will outline the effect of 2D and 3D architectures and orientation on stress-dependent matrix-cracking and how this information can be used to model material behavior and serve as the starting point foe mechanistic-based life-models.

An A{sub r} threesome: Matrix models, 2d conformal field theories, and 4dN=2 gauge theories

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

Schiappa, Ricardo; Wyllard, Niclas

We explore the connections between three classes of theories: A{sub r} quiver matrix models, d=2 conformal A{sub r} Toda field theories, and d=4N=2 supersymmetric conformal A{sub r} quiver gauge theories. In particular, we analyze the quiver matrix models recently introduced by Dijkgraaf and Vafa (unpublished) and make detailed comparisons with the corresponding quantities in the Toda field theories and the N=2 quiver gauge theories. We also make a speculative proposal for how the matrix models should be modified in order for them to reproduce the instanton partition functions in quiver gauge theories in five dimensions.

Detection of density dependence requires density manipulations and calculation of lambda.

PubMed

Fowler, N L; Overath, R Deborah; Pease, Craig M

2006-03-01

To investigate density-dependent population regulation in the perennial bunchgrass Bouteloua rigidiseta, we experimentally manipulated density by removing adults or adding seeds to replicate quadrats in a natural population for three annual intervals. We monitored the adjacent control quadrats for 14 annual intervals. We constructed a population projection matrix for each quadrat in each interval, calculated lambda, and did a life table response experiment (LTRE) analysis. We tested the effects of density upon lambda by comparing experimental and control quadrats, and by an analysis of the 15-year observational data set. As measured by effects on lambda and on N(t+1/Nt in the experimental treatments, negative density dependence was strong: the population was being effectively regulated. The relative contributions of different matrix elements to treatment effect on lambda differed among years and treatments; overall the pattern was one of small contributions by many different life cycle stages. In contrast, density dependence could not be detected using only the observational (control quadrats) data, even though this data set covered a much longer time span. Nor did experimental effects on separate matrix elements reach statistical significance. These results suggest that ecologists may fail to detect density dependence when it is present if they have only descriptive, not experimental, data, do not have data for the entire life cycle, or analyze life cycle components separately.

Turnover of Village Chickens Undermines Vaccine Coverage to Control HPAI H5N1.

PubMed

Villanueva-Cabezas, J P; Campbell, P T; McCaw, J M; Durr, P A; McVernon, J

2017-02-01

Highly pathogenic avian influenza (HPAI) subtype H5N1 remains an enzootic disease of village chickens in Indonesia, posing ongoing risk at the animal-human interface. Previous modelling showed that the fast natural turnover of chicken populations might undermine herd immunity after vaccination, although actual details of how this effect applies to Indonesia's village chicken population have not been determined. We explored the turnover effect in Indonesia's scavenging and mixed populations of village chickens using an extended Leslie matrix model parameterized with data collected from village chicken flocks in Java region, Indonesia. Population dynamics were simulated for 208 weeks; the turnover effect was simulated for 16 weeks after vaccination in two 'best case' scenarios, where the whole population (scenario 1), or birds aged over 14 days (scenario 2), were vaccinated. We found that the scavenging and mixed populations have different productive traits. When steady-state dynamics are reached, both populations are dominated by females (54.5%), and 'growers' and 'chicks' represent the most abundant age stages with 39% and 38% in the scavenging, and 60% and 25% in the mixed population, respectively. Simulations showed that the population turnover might reduce the herd immunity below the critical threshold that prevents the re-emergence of HPAI H5N1 4-8 weeks (scavenging) and 6-9 weeks (mixed population) after vaccination in scenario 1, and 2-6 weeks (scavenging) and 4-7 weeks (mixed population) after vaccination in scenario 2. In conclusion, we found that Indonesia's village chicken population does not have a unique underlying population dynamic and therefore, different turnover effects on herd immunity may be expected after vaccination; nonetheless, our simulations carried out in best case scenarios highlight the limitations of current vaccine technologies to control HPAI H5N1. This suggests that the improvements and complementary strategies are necessary and must be explored. © 2016 Blackwell Verlag GmbH.

Differential effect of extracellular matrix derived from papillary and reticular fibroblasts on epidermal development in vitro.

PubMed

Janson, David; Rietveld, Marion; Mahé, Christian; Saintigny, Gaëlle; El Ghalbzouri, Abdoelwaheb

2017-06-01

Papillary and reticular fibroblasts have different effects on keratinocyte proliferation and differentiation. The aim of this study was to investigate whether these effects are caused by differential secretion of soluble factors or by differential generation of extracellular matrix from papillary and reticular fibroblasts. To study the effect of soluble factors, keratinocyte monolayer cultures were grown in papillary or reticular fibroblast-conditioned medium. To study the effect of extracellular matrix, keratinocytes were grown on papillary or reticular-derived matrix. Conditioned medium from papillary or reticular fibroblasts did not differentially affect keratinocyte viability or epidermal development. However, keratinocyte viability was increased when grown on matrix derived from papillary, compared with reticular, fibroblasts. In addition, the longevity of the epidermis was increased when cultured on papillary fibroblast-derived matrix skin equivalents compared with reticular-derived matrix skin equivalents. The findings indicate that the matrix secreted by papillary and reticular fibroblasts is the main causal factor to account for the differences in keratinocyte growth and viability observed in our study. Differences in response to soluble factors between both populations were less significant. Matrix components specific to the papillary dermis may account for the preferential growth of keratinocytes on papillary dermis.

Modeling the Stress Strain Behavior of Woven Ceramic Matrix Composites

NASA Technical Reports Server (NTRS)

Morscher, Gregory N.

2006-01-01

Woven SiC fiber reinforced SiC matrix composites represent one of the most mature composite systems to date. Future components fabricated out of these woven ceramic matrix composites are expected to vary in shape, curvature, architecture, and thickness. The design of future components using woven ceramic matrix composites necessitates a modeling approach that can account for these variations which are physically controlled by local constituent contents and architecture. Research over the years supported primarily by NASA Glenn Research Center has led to the development of simple mechanistic-based models that can describe the entire stress-strain curve for composite systems fabricated with chemical vapor infiltrated matrices and melt-infiltrated matrices for a wide range of constituent content and architecture. Several examples will be presented that demonstrate the approach to modeling which incorporates a thorough understanding of the stress-dependent matrix cracking properties of the composite system.

Population Projection. Applications of Linear Algebra to Population Studies. Modules and Monographs in Undergraduate Mathematics and Its Applications. UMAP Module 345.

ERIC Educational Resources Information Center

Keller, Edward L.

This unit, which looks at applications of linear algebra to population studies, is designed to help pupils: (1) understand an application of matrix algebra to the study of populations; (2) see how knowledge of eigen values and eigen vectors is useful in studying powers of matrices; and (3) be briefly exposed to some difficult but interesting…

A Method of Q-Matrix Validation for the Linear Logistic Test Model

PubMed Central

Baghaei, Purya; Hohensinn, Christine

2017-01-01

The linear logistic test model (LLTM) is a well-recognized psychometric model for examining the components of difficulty in cognitive tests and validating construct theories. The plausibility of the construct model, summarized in a matrix of weights, known as the Q-matrix or weight matrix, is tested by (1) comparing the fit of LLTM with the fit of the Rasch model (RM) using the likelihood ratio (LR) test and (2) by examining the correlation between the Rasch model item parameters and LLTM reconstructed item parameters. The problem with the LR test is that it is almost always significant and, consequently, LLTM is rejected. The drawback of examining the correlation coefficient is that there is no cut-off value or lower bound for the magnitude of the correlation coefficient. In this article we suggest a simulation method to set a minimum benchmark for the correlation between item parameters from the Rasch model and those reconstructed by the LLTM. If the cognitive model is valid then the correlation coefficient between the RM-based item parameters and the LLTM-reconstructed item parameters derived from the theoretical weight matrix should be greater than those derived from the simulated matrices. PMID:28611721

Perturbed generalized multicritical one-matrix models

NASA Astrophysics Data System (ADS)

Ambjørn, J.; Chekhov, L.; Makeenko, Y.

2018-03-01

We study perturbations around the generalized Kazakov multicritical one-matrix model. The multicritical matrix model has a potential where the coefficients of zn only fall off as a power 1 /n s + 1. This implies that the potential and its derivatives have a cut along the real axis, leading to technical problems when one performs perturbations away from the generalized Kazakov model. Nevertheless it is possible to relate the perturbed partition function to the tau-function of a KdV hierarchy and solve the model by a genus expansion in the double scaling limit.

Habitat or matrix: which is more relevant to predict road-kill of vertebrates?

PubMed

Bueno, C; Sousa, C O M; Freitas, S R

2015-11-01

We believe that in tropics we need a community approach to evaluate road impacts on wildlife, and thus, suggest mitigation measures for groups of species instead a focal-species approach. Understanding which landscape characteristics indicate road-kill events may also provide models that can be applied in other regions. We intend to evaluate if habitat or matrix is more relevant to predict road-kill events for a group of species. Our hypothesis is: more permeable matrix is the most relevant factor to explain road-kill events. To test this hypothesis, we chose vertebrates as the studied assemblage and a highway crossing in an Atlantic Forest region in southeastern Brazil as the study site. Logistic regression models were designed using presence/absence of road-kill events as dependent variables and landscape characteristics as independent variables, which were selected by Akaike's Information Criterion. We considered a set of candidate models containing four types of simple regression models: Habitat effect model; Matrix types effect models; Highway effect model; and, Reference models (intercept and buffer distance). Almost three hundred road-kills and 70 species were recorded. River proximity and herbaceous vegetation cover, both matrix effect models, were associated to most road-killed vertebrate groups. Matrix was more relevant than habitat to predict road-kill of vertebrates. The association between river proximity and road-kill indicates that rivers may be a preferential route for most species. We discuss multi-species mitigation measures and implications to movement ecology and conservation strategies.

Long-range comparison between genes and languages based on syntactic distances.

PubMed

Colonna, Vincenza; Boattini, Alessio; Guardiano, Cristina; Dall'ara, Irene; Pettener, Davide; Longobardi, Giuseppe; Barbujani, Guido

2010-01-01

To propose a new approach for comparing genetic and linguistic diversity in populations belonging to distantly related groups. Comparisons of linguistic and genetic differences have proved powerful tools to reconstruct human demographic history. Current models assume on both sides that similarities reflect either descent from common ancestry or the balance between isolation and contact. Most linguistic phylogenies are ultimately based on lexical evidence (roughly, words and morphemes with their sounds and meanings). However, measures of lexical divergence are reliable only for closely related languages, thus large-scale comparisons of genetic and linguistic diversity have appeared problematic so far. Syntax (abstract rules to combine words into sentences) appears more measurable, universally comparable, and stable than the lexicon, and hence certain syntactic similarities might reflect deeper linguistic relationships, such as those between distant language families. In this study, we for the first time compared genetic data to a matrix of syntactic differences among selected populations of three continents. Comparing two databases of microsatellite (Short Tandem Repeat) markers and Single Nucleotides Polymorphisms (SNPs), with a linguistic matrix based on the values of 62 grammatical parameters, we show that there is indeed a correlation of syntactic and genetic distances. We also identified a few outliers and suggest a possible interpretation of the overall pattern. These results strongly support the possibility of better investigating population history by combining genetic data with linguistic information of a new type, provided by a theoretically more sophisticated method to assess the relationships between distantly related languages and language families. Copyright © 2010 S. Karger AG, Basel.

Shrinkage estimation of the realized relationship matrix

USDA-ARS?s Scientific Manuscript database

The additive relationship matrix plays an important role in mixed model prediction of breeding values. For genotype matrix X (loci in columns), the product XX' is widely used as a realized relationship matrix, but the scaling of this matrix is ambiguous. Our first objective was to derive a proper ...

Recovering hidden diagonal structures via non-negative matrix factorization with multiple constraints.

PubMed

Yang, Xi; Han, Guoqiang; Cai, Hongmin; Song, Yan

2017-03-31

Revealing data with intrinsically diagonal block structures is particularly useful for analyzing groups of highly correlated variables. Earlier researches based on non-negative matrix factorization (NMF) have been shown to be effective in representing such data by decomposing the observed data into two factors, where one factor is considered to be the feature and the other the expansion loading from a linear algebra perspective. If the data are sampled from multiple independent subspaces, the loading factor would possess a diagonal structure under an ideal matrix decomposition. However, the standard NMF method and its variants have not been reported to exploit this type of data via direct estimation. To address this issue, a non-negative matrix factorization with multiple constraints model is proposed in this paper. The constraints include an sparsity norm on the feature matrix and a total variational norm on each column of the loading matrix. The proposed model is shown to be capable of efficiently recovering diagonal block structures hidden in observed samples. An efficient numerical algorithm using the alternating direction method of multipliers model is proposed for optimizing the new model. Compared with several benchmark models, the proposed method performs robustly and effectively for simulated and real biological data.

General structure of democratic mass matrix of quark sector in E6 model

NASA Astrophysics Data System (ADS)

Ciftci, R.; ćiftci, A. K.

2016-03-01

An extension of the Standard Model (SM) fermion sector, which is inspired by the E6 Grand Unified Theory (GUT) model, might be a good candidate to explain a number of unanswered questions in SM. Existence of the isosinglet quarks might explain great mass difference of bottom and top quarks. Also, democracy on mass matrix elements is a natural approach in SM. In this study, we have given general structure of Democratic Mass Matrix (DMM) of quark sector in E6 model.

Bacterial Biofilms as Complex Communities

NASA Astrophysics Data System (ADS)

Vlamakis, Hera

2010-03-01

Many microbial populations form surface-associated multicellular communities known as biofilms. These multicellular communities are encased in a self-produced extracellular matrix composed of polysaccharides and proteins. Division of labor is a key feature of these communities and different cells serve distinct functions. We have found that in biofilms of the bacterium Bacillus subtilis, different cell types including matrix-producing and sporulating cells coexist and localize to distinct regions within the structured community. We were interested in understanding how these different cell types arise. Using fluorescence reporters under the control of promoters that are specific for distinct cell types we were able to follow the dynamics of differentiation throughout biofilm development. We found that a series of extracellular signals leads to differentiation of distinct cell types during biofilm formation. In addition, we found that extracellular matrix functions as a differentiation signal for timely sporulation within a biofilm and mutants unable to produce matrix were delayed in sporulation. Our results indicate that within a biofilm, cell-cell signaling is directional in that one cell type produces a signal that is sensed by another distinct cell type. Furthermore, once differentiated, cells become resistant to the action of other signaling molecules making it possible to maintain distinct cell populations over prolonged periods.

PACIC Instrument: disentangling dimensions using published validation models.

PubMed

Iglesias, K; Burnand, B; Peytremann-Bridevaux, I

2014-06-01

To better understand the structure of the Patient Assessment of Chronic Illness Care (PACIC) instrument. More specifically to test all published validation models, using one single data set and appropriate statistical tools. Validation study using data from cross-sectional survey. A population-based sample of non-institutionalized adults with diabetes residing in Switzerland (canton of Vaud). French version of the 20-items PACIC instrument (5-point response scale). We conducted validation analyses using confirmatory factor analysis (CFA). The original five-dimension model and other published models were tested with three types of CFA: based on (i) a Pearson estimator of variance-covariance matrix, (ii) a polychoric correlation matrix and (iii) a likelihood estimation with a multinomial distribution for the manifest variables. All models were assessed using loadings and goodness-of-fit measures. The analytical sample included 406 patients. Mean age was 64.4 years and 59% were men. Median of item responses varied between 1 and 4 (range 1-5), and range of missing values was between 5.7 and 12.3%. Strong floor and ceiling effects were present. Even though loadings of the tested models were relatively high, the only model showing acceptable fit was the 11-item single-dimension model. PACIC was associated with the expected variables of the field. Our results showed that the model considering 11 items in a single dimension exhibited the best fit for our data. A single score, in complement to the consideration of single-item results, might be used instead of the five dimensions usually described. © The Author 2014. Published by Oxford University Press in association with the International Society for Quality in Health Care; all rights reserved.

An analysis of the wear behavior of SiC whisker reinforced alumina from 25 to 1200 C

NASA Technical Reports Server (NTRS)

Dellacorte, Christopher

1991-01-01

A model is described for predicting the wear behavior of whisker reinforced ceramics. The model was successfully applied to a silicon carbide whisker reinforced alumina ceramic composite subjected to sliding contact. The model compares the friction forces on the whiskers due to sliding, which act to pull or push them out of the matrix, to the clamping or compressive forces on the whiskers due to the matrix, which act to hold the whiskers in the composite. At low temperatures, the whiskers are held strongly in the matrix and are fractured into pieces during the wear process along with the matrix. At elevated temperatures differential thermal expansion between the whiskers and matrix can cause loosening of the whiskers and lead to pullout during the wear process and to higher wear. The model, which represents the combination of elastic stress analysis and a friction heating analysis, predicts a transition temperature at which the strength of the whiskers equals the clamping force holding them in the matrix. Above the transition the whiskers are pulled out of the matrix during sliding, and below the transition the whiskers are simply fractured. The existence of the transition gives rise to a dual wear mode or mechanism behavior for this material which was observed in laboratory experiments. The results from this model correlate well with experimentally observed behavior indicating that the model may be useful in obtaining a better understanding of material behavior and in making material improvements.

An analysis of the wear behavior of SiC whisker-reinforced alumina from 25 to 1200 C

NASA Technical Reports Server (NTRS)

Dellacorte, Christopher

1993-01-01

A model is described for predicting the wear behavior of whisker reinforced ceramics. The model was successfully applied to a silicon carbide whisker reinforced alumina ceramic composite subjected to sliding contact. The model compares the friction forces on the whiskers due to sliding, which act to pull or push them out of the matrix, to the clamping or compressive forces on the whiskers due to the matrix, which act to hold the whiskers in the composite. At low temperatures, the whiskers are held strongly in the matrix and are fractured into pieces during the wear process along with the matrix. At elevated temperatures differential thermal expansion between the whiskers and matrix can cause loosening of the whiskers and lead to pullout during the wear process and to higher wear. The model, which represents the combination of elastic stress analysis and a friction heating analysis, predicts a transition temperature at which the strength of the whiskers equals the clamping force holding them in the matrix. Above the transition the whiskers are pulled out of the matrix during sliding, and below the transition the whiskers are simply fractured. The existence of the transition gives rise to a dual wear mode or mechanism behavior for this material which was observed in laboratory experiments. The results from this model correlate well with experimentally observed behavior indicating that the model may be useful in obtaining a better understanding of material behavior and in making material improvements.

Minimal Model of Quantum Kinetic Clusters for the Energy-Transfer Network of a Light-Harvesting Protein Complex.

PubMed

Wu, Jianlan; Tang, Zhoufei; Gong, Zhihao; Cao, Jianshu; Mukamel, Shaul

2015-04-02

The energy absorbed in a light-harvesting protein complex is often transferred collectively through aggregated chromophore clusters. For population evolution of chromophores, the time-integrated effective rate matrix allows us to construct quantum kinetic clusters quantitatively and determine the reduced cluster-cluster transfer rates systematically, thus defining a minimal model of energy-transfer kinetics. For Fenna-Matthews-Olson (FMO) and light-havrvesting complex II (LCHII) monomers, quantum Markovian kinetics of clusters can accurately reproduce the overall energy-transfer process in the long-time scale. The dominant energy-transfer pathways are identified in the picture of aggregated clusters. The chromophores distributed extensively in various clusters can assist a fast and long-range energy transfer.

The ability of individuals to assess population density influences the evolution of emigration propensity and dispersal distance.

PubMed

Poethke, Hans Joachim; Gros, Andreas; Hovestadt, Thomas

2011-08-07

We analyze the simultaneous evolution of emigration and settlement decisions for actively dispersing species differing in their ability to assess population density. Using an individual-based model we simulate dispersal as a multi-step (patch to patch) movement in a world consisting of habitat patches surrounded by a hostile matrix. Each such step is associated with the same mortality risk. Our simulations show that individuals following an informed strategy, where emigration (and settlement) probability depends on local population density, evolve a lower (natal) emigration propensity but disperse over significantly larger distances - i.e. postpone settlement longer - than individuals performing density-independent emigration. This holds especially when variation in environmental conditions is spatially correlated. Both effects can be traced to the informed individuals' ability to better exploit existing heterogeneity in reproductive chances. Yet, already moderate distance-dependent dispersal costs prevent the evolution of multi-step (long-distance) dispersal, irrespective of the dispersal strategy. Copyright © 2011 Elsevier Ltd. All rights reserved.

Effect of the fiber-matrix interphase on the transverse tensile strength of the unidirectional composite material

NASA Technical Reports Server (NTRS)

Tsai, H. C.; Arocho, A. M.

1992-01-01

A simple one-dimensional fiber-matrix interphase model has been developed and analytical results obtained correlated well with available experimental data. It was found that by including the interphase between the fiber and matrix in the model, much better local stress results were obtained than with the model without the interphase. A more sophisticated two-dimensional micromechanical model, which included the interphase properties was also developed. Both one-dimensional and two-dimensional models were used to study the effect of the interphase properties on the local stresses at the fiber, interphase and matrix. From this study, it was found that interphase modulus and thickness have significant influence on the transverse tensile strength and mode of failure in fiber reinforced composites.

Rodent malaria-resistant strains of the mosquito, Anopheles gambiae, have slower population growth than -susceptible strains

PubMed Central

Voordouw, Maarten J; Anholt, Bradley R; Taylor, Pam J; Hurd, Hilary

2009-01-01

Background Trade-offs between anti-parasite defence mechanisms and other life history traits limit the evolution of host resistance to parasites and have important implications for understanding diseases such as malaria. Mosquitoes have not evolved complete resistance to malaria parasites and one hypothesis is that anti-malaria defence mechanisms are costly. Results We used matrix population models to compare the population growth rates among lines of Anopheles gambiae that had been selected for resistance or high susceptibility to the rodent malaria parasite, Plasmodium yoelii nigeriensis. The population growth rate of the resistant line was significantly lower than that of the highly susceptible and the unselected control lines, regardless of whether mosquitoes were infected with Plasmodium or not. The lower population growth of malaria-resistant mosquitoes was caused by reduced post blood-feeding survival of females and poor egg hatching. Conclusion With respect to eradicating malaria, the strategy of releasing Plasmodium-resistant Anopheles mosquitoes is unlikely to be successful if the costs of Plasmodium-resistance in the field are as great as the ones measured in this study. High densities of malaria-resistant mosquitoes would have to be maintained by continuous release from captive breeding facilities. PMID:19379508

TRANSPOSABLE REGULARIZED COVARIANCE MODELS WITH AN APPLICATION TO MISSING DATA IMPUTATION

PubMed Central

Allen, Genevera I.; Tibshirani, Robert

2015-01-01

Missing data estimation is an important challenge with high-dimensional data arranged in the form of a matrix. Typically this data matrix is transposable, meaning that either the rows, columns or both can be treated as features. To model transposable data, we present a modification of the matrix-variate normal, the mean-restricted matrix-variate normal, in which the rows and columns each have a separate mean vector and covariance matrix. By placing additive penalties on the inverse covariance matrices of the rows and columns, these so called transposable regularized covariance models allow for maximum likelihood estimation of the mean and non-singular covariance matrices. Using these models, we formulate EM-type algorithms for missing data imputation in both the multivariate and transposable frameworks. We present theoretical results exploiting the structure of our transposable models that allow these models and imputation methods to be applied to high-dimensional data. Simulations and results on microarray data and the Netflix data show that these imputation techniques often outperform existing methods and offer a greater degree of flexibility. PMID:26877823

TRANSPOSABLE REGULARIZED COVARIANCE MODELS WITH AN APPLICATION TO MISSING DATA IMPUTATION.

PubMed

Allen, Genevera I; Tibshirani, Robert

2010-06-01

Missing data estimation is an important challenge with high-dimensional data arranged in the form of a matrix. Typically this data matrix is transposable , meaning that either the rows, columns or both can be treated as features. To model transposable data, we present a modification of the matrix-variate normal, the mean-restricted matrix-variate normal , in which the rows and columns each have a separate mean vector and covariance matrix. By placing additive penalties on the inverse covariance matrices of the rows and columns, these so called transposable regularized covariance models allow for maximum likelihood estimation of the mean and non-singular covariance matrices. Using these models, we formulate EM-type algorithms for missing data imputation in both the multivariate and transposable frameworks. We present theoretical results exploiting the structure of our transposable models that allow these models and imputation methods to be applied to high-dimensional data. Simulations and results on microarray data and the Netflix data show that these imputation techniques often outperform existing methods and offer a greater degree of flexibility.

Implementation of thermal residual stresses in the analysis of fiber bridged matrix crack growth in titanium matrix composites

NASA Technical Reports Server (NTRS)

Bakuckas, John G., Jr.; Johnson, W. Steven

1994-01-01

In this research, thermal residual stresses were incorporated in an analysis of fiber-bridged matrix cracks in unidirectional and cross-ply titanium matrix composites (TMC) containing center holes or center notches. Two TMC were investigated, namely, SCS-6/Timelal-21S laminates. Experimentally, matrix crack initiation and growth were monitored during tension-tension fatigue tests conducted at room temperature and at an elevated temperature of 200 C. Analytically, thermal residual stresses were included in a fiber bridging (FB) model. The local R-ratio and stress-intensity factor in the matrix due to thermal and mechanical loadings were calculated and used to evaluate the matrix crack growth behavior in the two materials studied. The frictional shear stress term, tau, assumed in this model was used as a curve-fitting parameter to matrix crack growth data. The scatter band in the values of tau used to fit the matrix crack growth data was significantly reduced when thermal residual stresses were included in the fiber bridging analysis. For a given material system, lay-up and temperature, a single value of tau was sufficient to analyze the crack growth data. It was revealed in this study that thermal residual stresses are an important factor overlooked in the original FB models.

Creep of Heat-Resistant Composites of an Oxide-Fiber/Ni-Matrix Family

NASA Astrophysics Data System (ADS)

Mileiko, S. T.

2001-09-01

A creep model of a composite with a creeping matrix and initially continuous elastic brittle fibers is developed. The model accounts for the fiber fragmentation in the stage of unsteady creep of the composite, which ends with a steady-state creep, where a minimum possible average length of the fiber is achieved. The model makes it possible to analyze the creep rate of the composite in relation to such parameters of its structure as the statistic characteristics of the fiber strength, the creep characteristics of the matrix, and the strength of the fiber-matrix interface, the latter being of fundamental importance. A comparison between the calculation results and the experimental ones obtained on composites with a Ni-matrix and monocrystalline and eutectic oxide fibers as well as on sapphire fiber/TiAl-matrix composites shows that the model is applicable to the computer simulation of the creep behavior of heat-resistant composites and to the optimization of the structure of such composites. By combining the experimental data with calculation results, it is possible to evaluate the heat resistance of composites and the potential of oxide-fiber/Ni-matrix composites. The composite specimens obtained and tested to date reveal their high creep resistance up to a temperature of 1150°C. The maximum operating temperature of the composites can be considerably raised by strengthening the fiber-matrix interface.

Estimation of Potential Population Level Effects of Contaminants on Wildlife

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

Loar, J.M.

2001-06-11

The objective of this project is to provide DOE with improved methods to assess risks from contaminants to wildlife populations. The current approach for wildlife risk assessment consists of comparison of contaminant exposure estimates for individual animals to literature-derived toxicity test endpoints. These test endpoints are assumed to estimate thresholds for population-level effects. Moreover, species sensitivities to contaminants is one of several criteria to be considered when selecting assessment endpoints (EPA 1997 and 1998), yet data on the sensitivities of many birds and mammals are lacking. The uncertainties associated with this approach are considerable. First, because toxicity data are notmore » available for most potential wildlife endpoint species, extrapolation of toxicity data from test species to the species of interest is required. There is no consensus on the most appropriate extrapolation method. Second, toxicity data are represented as statistical measures (e.g., NOAEL s or LOAELs) that provide no information on the nature or magnitude of effects. The level of effect is an artifact of the replication and dosing regime employed, and does not indicate how effects might increase with increasing exposure. Consequently, slight exceedance of a LOAEL is not distinguished from greatly exceeding it. Third, the relationship of toxic effects on individuals to effects on populations is poorly estimated by existing methods. It is assumed that if the exposure of individuals exceeds levels associated with impaired reproduction, then population level effects are likely. Uncertainty associated with this assumption is large because depending on the reproductive strategy of a given species, comparable levels of reproductive impairment may result in dramatically different population-level responses. This project included several tasks to address these problems: (1) investigation of the validity of the current allometric scaling approach for interspecies extrapolation an d development of new scaling models; (2) development of dose-response models for toxicity data presented in the literature; and (3) development of matrix-based population models that were coupled with dose-response models to provide realistic estimation of population-level effects for individual responses.« less

Coherent Microwave Scattering Model of Marsh Grass

NASA Astrophysics Data System (ADS)

Duan, Xueyang; Jones, Cathleen E.

2017-12-01

In this work, we developed an electromagnetic scattering model to analyze radar scattering from tall-grass-covered lands such as wetlands and marshes. The model adopts the generalized iterative extended boundary condition method (GIEBCM) algorithm, previously developed for buried cylindrical media such as vegetation roots, to simulate the scattering from the grass layer. The major challenge of applying GIEBCM to tall grass is the extremely time-consuming iteration among the large number of short subcylinders building up the grass. To overcome this issue, we extended the GIEBCM to multilevel GIEBCM, or M-GIEBCM, in which we first use GIEBCM to calculate a T matrix (transition matrix) database of "straws" with various lengths, thicknesses, orientations, curvatures, and dielectric properties; we then construct the grass with a group of straws from the database and apply GIEBCM again to calculate the T matrix of the overall grass scene. The grass T matrix is transferred to S matrix (scattering matrix) and combined with the ground S matrix, which is computed using the stabilized extended boundary condition method, to obtain the total scattering. In this article, we will demonstrate the capability of the model by simulating scattering from scenes with different grass densities, different grass structures, different grass water contents, and different ground moisture contents. This model will help with radar experiment design and image interpretation for marshland and wetland observations.

A model to predict thermal conductivity of irradiated U-Mo dispersion fuel

NASA Astrophysics Data System (ADS)

Burkes, Douglas E.; Huber, Tanja K.; Casella, Andrew M.

2016-05-01

Numerous global programs are focused on the continued development of existing and new research and test reactor fuels to achieve maximum attainable uranium loadings to support the conversion of a number of the world's remaining high-enriched uranium fueled reactors to low-enriched uranium fuel. Some of these programs are focused on assisting with the development and qualification of a fuel design that consists of a uranium-molybdenum (U-Mo) alloy dispersed in an aluminum matrix as one option for reactor conversion. Thermal conductivity is an important consideration in determining the operational temperature of the fuel and can be influenced by interaction layer formation between the dispersed phase and matrix and upon the concentration of the dispersed phase within the matrix. This paper extends the use of a simple model developed previously to study the influence of interaction layer formation as well as the size and volume fraction of fuel particles dispersed in the matrix, Si additions to the matrix, and Mo concentration in the fuel particles on the effective thermal conductivity of the U-Mo/Al composite during irradiation. The model has been compared to experimental measurements recently conducted on U-Mo/Al dispersion fuels at two different fission densities with acceptable agreement. Observations of the modeled results indicate that formation of an interaction layer and subsequent consumption of the matrix reveals a rather significant effect on effective thermal conductivity. The modeled interaction layer formation and subsequent consumption of the high thermal conductivity matrix was sensitive to the average dispersed fuel particle size, suggesting this parameter as one of the most effective in minimizing thermal conductivity degradation of the composite, while the influence of Si additions to the matrix in the model was highly dependent upon irradiation conditions.