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Journal articles on the topic 'Competing populations'

Author: Grafiati

Published: 4 June 2021

Last updated: 5 February 2022

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1

César Fassoni, Artur, and Denis Carvalho Braga. "Resilience Analysis for Competing Populations." Bulletin of Mathematical Biology 81, no. 10 (August 30, 2019): 3864–88. http://dx.doi.org/10.1007/s11538-019-00660-7.

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2

Quer, Josep, Christine L. Hershey, Esteban Domingo, John J. Holland, and Isabel S. Novella. "Contingent Neutrality in Competing Viral Populations." Journal of Virology 75, no. 16 (August 15, 2001): 7315–20. http://dx.doi.org/10.1128/jvi.75.16.7315-7320.2001.

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ABSTRACT The replicative fitness of a genetically marked (MARM-C) population of vesicular stomatitis virus was examined in competition assays in BHK-21 cells. In standard fitness assays involving up to eight competition passages of the mixed populations, MARM-C competes equally with the wild type (wt), but very prolonged competitions always led to the wt gaining dominance over MARM-C in a very slowed, nonlinear manner (J. Quer et al., J. Mol. Biol. 264:465–471, 1996). In the present study we show that a number of quite unrelated environmental perturbations, which decreased virus replication during competitions, all led to an accelerated dominance of the wt over MARM-C. These perturbations were (i) the presence of added (or endogenously generated) defective interfering particles, (ii) the presence of the chemical mutagen 5-fluorouracil (5-FU), or (iii) an increase in temperature to 40.5°C. Thus, the “neutral fitness” of the MARM-C population is contingent. We have determined the entire genomic consensus sequence of MARM-C and have identified only six mutations. Clearly, some or all of these mutations allowed the MARM-C quasispecies population to compete equally with wt in a defined constant host environment, but the period of neutrality was shortened when the environment was perturbed during competitions. Interestingly, when four passages of each population were carried out independently in the presence of 5-FU (but in the absence of competition), no significant differences were detected in the fitness changes of wt and MARM-C, nor was there a difference in their subsequent abilities to compete with each other in a standard fitness assay. We propose a model for this contingent neutrality. The conditions employed to generate the MARM-C quasispecies population selected a small number of mutations in the consensus sequence. It appears that the MARM-C quasispecies population has moved into a segment of sequence space in which the average fitness value is neutral but, under environmental stress, beneficial mutations cannot be generated rapidly enough to compete with those being generated concurrently by competing wt virus quasispecies populations.

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3

Scheuring, István, György Károlyi, Zoltán Toroczkai, Tamás Tél, and Áron Péntek. "Competing populations in flows with chaotic mixing." Theoretical Population Biology 63, no. 2 (March 2003): 77–90. http://dx.doi.org/10.1016/s0040-5809(02)00035-7.

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4

Cushing, J. M., Shandelle M. Henson, and Lih-Ing Roeger. "Coexistence of competing juvenile–adult structured populations." Journal of Biological Dynamics 1, no. 2 (April 2007): 201–31. http://dx.doi.org/10.1080/17513750701201372.

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5

Vázquez, Alexei. "Self-organization in populations of competing agents." Physical Review E 62, no. 4 (October 1, 2000): R4497—R4500. http://dx.doi.org/10.1103/physreve.62.r4497.

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6

Charret, I. C., J. N. C. Louzada, and A. T. Costa. "Individual-based model for coevolving competing populations." Physica A: Statistical Mechanics and its Applications 385, no. 1 (November 2007): 249–54. http://dx.doi.org/10.1016/j.physa.2007.06.013.

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7

SACHS, T., A. NOVOPLANSKY, and D. COHEN. "Plants as competing populations of redundant organs." Plant, Cell and Environment 16, no. 7 (September 1993): 765–70. http://dx.doi.org/10.1111/j.1365-3040.1993.tb00498.x.

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8

Boudjellaba, Hafida, and Tewfik Sari. "Stability Loss Delay in Harvesting Competing Populations." Journal of Differential Equations 152, no. 2 (March 1999): 394–408. http://dx.doi.org/10.1006/jdeq.1998.3533.

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9

Papadopoulou, Elena, Evelina Leivada, and Natalia Pavlou. "Acceptability judgments in bilectal populations." Linguistic Variation 14, no. 1 (November 25, 2014): 109–28. http://dx.doi.org/10.1075/lv.14.1.05pap.

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This paper investigates the gradient nature of acceptability judgements and grammatical variants in the bilectal population of Cyprus, by comparatively discussing the findings of two recent experiments on (i) exhaustivity effects in Cypriot Greek clefts and embu ‘it is that’-structures (Leivada et al. 2013) and (ii) clitic placement and how it is affected by lexical and syntactic stimulation (Papadopoulou et al. 2014). The analysis lays emphasis on the intra-dialectal variation observed across speakers’ performance in both experiments. Variation is discussed in relation to socio-syntactic aspects of language use, such as (i) the existence of competing grammars (Tsiplakou 2007, in press) and competing motivations (Grohmann & Leivada 2012, to appear) in bilectal environments such as the one in Cyprus, (ii) the notion of gradience existent within a dialect–standard continuum (e.g. Cornips 2006 for Dutch, Leivada et al. 2013 for Greek), and (iii) syntactic/semantic factors that inform our participants’ performance. Keywords: acceptability judgments; clefts; clitics; Cypriot Greek; gradience; embu; exhaustivity; competing grammars

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10

B., Sivaprakash. "Stability Analysis for Coexistence of Competing Microbial Populations in a Chemostat following Andrew's Growth Model." Journal of Advanced Research in Dynamical and Control Systems 24, no. 4 (March 31, 2020): 255–66. http://dx.doi.org/10.5373/jardcs/v12i4/20201440.

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11

Amado, André, Lenin Fernández, Weini Huang, Fernando F. Ferreira, and Paulo R. A. Campos. "Competing metabolic strategies in a multilevel selection model." Royal Society Open Science 3, no. 11 (November 2016): 160544. http://dx.doi.org/10.1098/rsos.160544.

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The evolutionary mechanisms of energy efficiency have been addressed. One important question is to understand how the optimized usage of energy can be selected in an evolutionary process, especially when the immediate advantage of gathering efficient individuals in an energetic context is not clear. We propose a model of two competing metabolic strategies differing in their resource usage, an efficient strain which converts resource into energy at high efficiency but displays a low rate of resource consumption, and an inefficient strain which consumes resource at a high rate but at low yield. We explore the dynamics in both well-mixed and structured populations. The selection for optimized energy usage is measured by the likelihood that an efficient strain can invade a population of inefficient strains. It is found that the parameter space at which the efficient strain can thrive in structured populations is always broader than observed in well-mixed populations.

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12

Rogers, Tim, Alan J. McKane, and Axel G. Rossberg. "Spontaneous genetic clustering in populations of competing organisms." Physical Biology 9, no. 6 (October 31, 2012): 066002. http://dx.doi.org/10.1088/1478-3975/9/6/066002.

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13

Davydov, A. A., and A. S. Platov. "Optimal exploitation of two competing size-structured populations." Proceedings of the Steklov Institute of Mathematics 287, S1 (November 27, 2014): 49–54. http://dx.doi.org/10.1134/s0081543814090053.

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14

Baier, Gerold, Jesper S. Thomsen, and Erik Mosekilde. "Chaotic Hierarchy in a Model of Competing Populations." Journal of Theoretical Biology 165, no. 4 (December 1993): 593–607. http://dx.doi.org/10.1006/jtbi.1993.1209.

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15

Pinkel, Daniel. "Analytical Description of Mutational Effects in Competing Asexual Populations." Genetics 177, no. 4 (October 18, 2007): 2135–49. http://dx.doi.org/10.1534/genetics.107.075697.

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16

Bayliss, A., and V. A. Volpert. "Patterns for Competing Populations with Species Specific Nonlocal Coupling." Mathematical Modelling of Natural Phenomena 10, no. 6 (2015): 30–47. http://dx.doi.org/10.1051/mmnp/201510604.

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17

Yu, Yumei, Wendi Wang, and Zhengyi Lu. "Global stability of Gompertz model of three competing populations." Journal of Mathematical Analysis and Applications 334, no. 1 (October 2007): 333–48. http://dx.doi.org/10.1016/j.jmaa.2006.12.060.

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18

Pokalyuk, Cornelia, Lisha A. Mathew, Dirk Metzler, and Peter Pfaffelhuber. "Competing islands limit the rate of adaptation in structured populations." Theoretical Population Biology 90 (December 2013): 1–11. http://dx.doi.org/10.1016/j.tpb.2013.08.001.

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19

Tanzy, M. C., V. A. Volpert, A. Bayliss, and M. E. Nehrkorn. "A Nagumo-type model for competing populations with nonlocal coupling." Mathematical Biosciences 263 (May 2015): 70–82. http://dx.doi.org/10.1016/j.mbs.2015.01.014.

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20

Smith, GCS, and IR White. "Competing risk models of stillbirth inform populations but not individuals." BJOG: An International Journal of Obstetrics & Gynaecology 123, no. 7 (February 29, 2016): 1075. http://dx.doi.org/10.1111/1471-0528.13943.

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21

He, Ze-Rong, and Nan Zhou. "Stability for a competing system of hierarchical age-structured populations." International Journal of Biomathematics 13, no. 07 (August 31, 2020): 2050070. http://dx.doi.org/10.1142/s1793524520500709.

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In this paper, we are concerned with the stability for a model in the form of system of integro-partial differential equations, which governs the evolution of two competing age-structured populations. The age-specified environment is incorporated in the vital rates, which displays the hierarchy of ages. By a non-zero fixed-point result, we show the existence of positive equilibria. Some conditions for the stability of steady states are derived by means of semigroup method. Furthermore, numerical experiments are also presented.

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22

Ni, Y. C., H. P. Yin, C. Xu, and P. M. Hui. "Analyzing phase diagrams and phase transitions in networked competing populations." European Physical Journal B 80, no. 2 (March 2011): 233–41. http://dx.doi.org/10.1140/epjb/e2011-10845-3.

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23

Song Mao, Yimin Shi, and Liang Wang. "Exact inference for two exponential populations with competing risks data." Journal of Systems Engineering and Electronics 25, no. 4 (August 2014): 711–20. http://dx.doi.org/10.1109/jsee.2014.00081.

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24

Epifanov, A. V., and V. G. Tsybulin. "Modeling of oscillatory scenarios of the coexistence of competing populations." Biophysics 61, no. 4 (July 2016): 696–704. http://dx.doi.org/10.1134/s0006350916040072.

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25

Rulands, S., T. Reichenbach, and E. Frey. "Threefold way to extinction in populations of cyclically competing species." Journal of Statistical Mechanics: Theory and Experiment 2011, no. 01 (January 27, 2011): L01003. http://dx.doi.org/10.1088/1742-5468/2011/01/l01003.

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26

Whitaker, T. C., and J. Hill. "A comparative analysis of population characteristics of the competing progeny (within UK) of UK elite eventing sires and all competing event horses within the UK." BSAP Occasional Publication 32 (2004): 191–93. http://dx.doi.org/10.1017/s0263967x00041446.

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A greater understanding of the population characteristics of sport horse populations is required to enable potential breed improvement programmes to be formulated correctly and be effective in their outcomes. To date limited research has been conducted into the UK sport horse population.A selected group of progeny (n=339) sired by elite eventing stallions was examined. In the context of this study elite sires were defined as those that were ranked 1-10 by total lifetime points won by competing progeny up to the end of 2000 (British Horse Database, 2000). Comparative analysis was undertaken between the selected group and all competing eventing horses in 2000 (n=9387) (British Horse Database, 2000). Data collected for both groups included, total lifetime points won at eventing and dressage and total lifetime money won at show jumping. Basic descriptive statistics were produced for each data set (Table 1). Product moment correlations were performed for all discipline areas (Table 2). Data transformation was applied using LOG+1(Hassenstein, Roehe, and Kalm, 1996).

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27

Poloczanska, Elvira S., Stephen J. Hawkins, Alan J. Southward, and Michael T. Burrows. "MODELING THE RESPONSE OF POPULATIONS OF COMPETING SPECIES TO CLIMATE CHANGE." Ecology 89, no. 11 (November 2008): 3138–49. http://dx.doi.org/10.1890/07-1169.1.

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28

Segal, B. L., V. A. Volpert, and A. Bayliss. "Pattern formation in a model of competing populations with nonlocal interactions." Physica D: Nonlinear Phenomena 253 (June 2013): 12–22. http://dx.doi.org/10.1016/j.physd.2013.02.006.

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29

Tanzy, M. C., V. A. Volpert, A. Bayliss, and M. E. Nehrkorn. "Stability and pattern formation for competing populations with asymmetric nonlocal coupling." Mathematical Biosciences 246, no. 1 (November 2013): 14–26. http://dx.doi.org/10.1016/j.mbs.2013.09.002.

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30

Sikder, A. "Effects of Parasitism over Two Competing Host Populations Leading to Persistence." Bulletin of Mathematical Biology 61, no. 1 (January 1999): 179–205. http://dx.doi.org/10.1006/bulm.1998.0087.

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31

Kretzschmar, M., R. M. Nisbet, and E. Mccauley. "A Predator-Prey Model for Zooplankton Grazing on Competing Algal Populations." Theoretical Population Biology 44, no. 1 (August 1993): 32–66. http://dx.doi.org/10.1006/tpbi.1993.1017.

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32

Nicholson, Michael D., and Tibor Antal. "Competing evolutionary paths in growing populations with applications to multidrug resistance." PLOS Computational Biology 15, no. 4 (April 15, 2019): e1006866. http://dx.doi.org/10.1371/journal.pcbi.1006866.

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33

Jiang, Luo-Luo, Tao Zhou, Matjaž Perc, Xin Huang, and Bing-Hong Wang. "Emergence of target waves in paced populations of cyclically competing species." New Journal of Physics 11, no. 10 (October 2, 2009): 103001. http://dx.doi.org/10.1088/1367-2630/11/10/103001.

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34

Ardaševa, Aleksandra, Robert A. Gatenby, Alexander R. A. Anderson, Helen M. Byrne, Philip K. Maini, and Tommaso Lorenzi. "Evolutionary dynamics of competing phenotype-structured populations in periodically fluctuating environments." Journal of Mathematical Biology 80, no. 3 (October 22, 2019): 775–807. http://dx.doi.org/10.1007/s00285-019-01441-5.

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Abstract Living species, ranging from bacteria to animals, exist in environmental conditions that exhibit spatial and temporal heterogeneity which requires them to adapt. Risk-spreading through spontaneous phenotypic variations is a known concept in ecology, which is used to explain how species may survive when faced with the evolutionary risks associated with temporally varying environments. In order to support a deeper understanding of the adaptive role of spontaneous phenotypic variations in fluctuating environments, we consider a system of non-local partial differential equations modelling the evolutionary dynamics of two competing phenotype-structured populations in the presence of periodically oscillating nutrient levels. The two populations undergo heritable, spontaneous phenotypic variations at different rates. The phenotypic state of each individual is represented by a continuous variable, and the phenotypic landscape of the populations evolves in time due to variations in the nutrient level. Exploiting the analytical tractability of our model, we study the long-time behaviour of the solutions to obtain a detailed mathematical depiction of the evolutionary dynamics. The results suggest that when nutrient levels undergo small and slow oscillations, it is evolutionarily more convenient to rarely undergo spontaneous phenotypic variations. Conversely, under relatively large and fast periodic oscillations in the nutrient levels, which bring about alternating cycles of starvation and nutrient abundance, higher rates of spontaneous phenotypic variations confer a competitive advantage. We discuss the implications of our results in the context of cancer metabolism.

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35

Yadav, S. K., Sheela Misra, S. S. Mishra, and Shankar Prasad Khanal. "Variance Estimator Using Tri-mean and Inter Quartile Range of Auxiliary Variable." Nepalese Journal of Statistics 1 (December 29, 2017): 83–91. http://dx.doi.org/10.3126/njs.v1i0.18819.

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Background: Whenever the population is large and it is very time taking and costly to take observation on each unit of the population then sampling is the only way to get the appropriate estimate of the population parameter under consideration. Many authors have given many estimators for estimating population variance with greater efficiency.Objective: The objective of the study is to search for more efficient estimator than the competing estimators of population variance of study variable.Materials and Methods: The estimator utilizing information on tri-mean and inter quartile range of auxiliary variable has been is developed. The expressions for the bias and mean squared error (MSE) of the proposed estimator have been derived up to the first order of approximation. A theoretical comparison of the proposed estimator has been made with the competing estimators of population variance.Results: The theoretical findings have been justified with the help of numerical example from some natural populations. It has been found that the proposed estimator is best among the competing estimators of population variance as it has least mean squared error among them.Conclusion: Since the proposed estimator is best among the competing estimator of the population variance, therefore it must be used for the improved estimation of population variance.Nepalese Journal of Statistics, 2017, Vol. 1, 83-91

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36

Misra, O. P., Poonam Sinha, and Chhatrapal Singh. "Dynamics of one-prey two-predator system with square root functional response and time lag." International Journal of Biomathematics 08, no. 03 (April 21, 2015): 1550029. http://dx.doi.org/10.1142/s1793524515500291.

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Animals grouping together is one of the most interesting phenomena in population dynamics and different functional responses as a result of prey–predator forming groups have been considered by many authors in their models. In the present paper we have considered a model for one prey and two competing predator populations with time lag and square root functional response on account of herd formation by prey. It is shown that due to the inclusion of another competing predator, the underlying system without delay becomes more stable and limit cycles do not occur naturally. However, after considering the effect of time lag in the basic system, limit cycles appear in the case of all equilibrium points when delay time crosses some critical value. From the numerical simulation, it is observed that the length of delay is minimum when only prey population survives and it is maximum when all the populations coexist.

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37

Huss, Magnus, Jennifer G. Howeth, Julia I. Osterman, and David M. Post. "Intraspecific phenotypic variation among alewife populations drives parallel phenotypic shifts in bluegill." Proceedings of the Royal Society B: Biological Sciences 281, no. 1787 (July 22, 2014): 20140275. http://dx.doi.org/10.1098/rspb.2014.0275.

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Evolutionary diversification within consumer species may generate selection on local ecological communities, affecting prey community structure. However, the extent to which this niche construction can propagate across food webs and shape trait variation in competing species is unknown. Here, we tested whether niche construction by different life-history variants of the planktivorous fish alewife ( Alosa pseudoharengus ) can drive phenotypic divergence and resource use in the competing species bluegill ( Lepomis macrochirus ). Using a combination of common garden experiments and a comparative field study, we found that bluegill from landlocked alewife lakes grew relatively better when fed small than large zooplankton, had gill rakers better adapted for feeding on small-bodied prey and selected smaller zooplankton compared with bluegill from lakes with anadromous or no alewife. Observed shifts in bluegill foraging traits in lakes with landlocked alewife parallel those in alewife, suggesting interspecific competition leading to parallel phenotypic changes rather than to divergence (which is commonly predicted). Our findings suggest that species may be locally adapted to prey communities structured by different life-history variants of a competing dominant species.

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38

Björnberg, Jakob E., and Erik I. Broman. "Coexistence and Noncoexistence of Markovian Viruses and their Hosts." Journal of Applied Probability 51, no. 01 (March 2014): 191–208. http://dx.doi.org/10.1017/s0021900200010172.

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Examining possibilities for the coexistence of two competing populations is a classic problem which dates back to the earliest ‘predator-prey’ models. In this paper we study this problem in the context of a model introduced in Björnberg et al. (2012) for the spread of a virus infection in a population of healthy cells. The infected cells may be seen as a population of ‘predators’ and the healthy cells as a population of ‘prey’. We show that, depending on the parameters defining the model, there may or may not be coexistence of the two populations, and we give precise criteria for this.

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39

Björnberg, Jakob E., and Erik I. Broman. "Coexistence and Noncoexistence of Markovian Viruses and their Hosts." Journal of Applied Probability 51, no. 1 (March 2014): 191–208. http://dx.doi.org/10.1239/jap/1395771423.

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Examining possibilities for the coexistence of two competing populations is a classic problem which dates back to the earliest ‘predator-prey’ models. In this paper we study this problem in the context of a model introduced in Björnberg et al. (2012) for the spread of a virus infection in a population of healthy cells. The infected cells may be seen as a population of ‘predators’ and the healthy cells as a population of ‘prey’. We show that, depending on the parameters defining the model, there may or may not be coexistence of the two populations, and we give precise criteria for this.

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40

Brandl, Magdalena, Christian Apfelbacher, Annette Weiß, Susanne Brandstetter, and Sebastian Edgar Baumeister. "Incidence Estimation in Post-ICU Populations: Challenges and Possible Solutions When Using Claims Data." Das Gesundheitswesen 82, S 02 (January 28, 2020): S101—S107. http://dx.doi.org/10.1055/a-1082-0777.

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Abstract Background New or worsening cognitive, physical and/or mental health impairments after acute care for critical illness are referred to as “post-intensive care syndrome” (PICS). Little is known about the incidence of its components, since it is challenging to recruit patients after intensive care unit (ICU) treatment for observational studies. Claims data are particularly suited to achieve incidence estimates in difficult-to-recruit groups. However, some limitations remain when using claims data for empirical research on the outcome of ICU treatment. The objective of this article is to describe three challenges and possible solutions for the estimation of the incidence of PICS based on claims data Methodological challenges: The presence of competing risk by death, investigating a syndrome and dealing with interval censoring First, in (post) ICU populations the assumption of independence between the event of interest (diagnosis of PICS component) and the competing event (death) is violated. Competing risk is an event whose occurrence precludes the event of interest to be observed, and in ICU populations, death is a frequent secondary event. Methods that estimate incidence in the presence of competing risks are well-established but have not been applied to the scenario described above. Second, PICS is a complex syndrome and represented by various ICD-10 (International Classification of Diseases, 10th Revision) disease codes. The operationalization of this syndrome (case identification) and the validation of cases are particularly challenging. Third, another major challenge is that the exact date of the event of interest is not available in claims data. It is only known that the event occurred within a certain interval. This feature is called interval censoring. Recently, methods have been developed that address informative censoring due to competing risks in the presence of interval censoring. We will discuss how these methods could be used to tackle the problem when estimating PICS components. Alternatively, it could be possible to assign an exact date for each diagnosis by combining the diagnosis with the exact date of prescriptions of the respective medicines and/or medical services. Conclusion Estimating incidence in post-ICU populations entails various methodological issues when using claims data. Investigators need to be aware of the presence of competing risks. The application of internal validation criteria to operationalize the event of interest is crucial to achieve reliable incidence estimates. The problem of interval censoring can be solved either by statistical methods or by combining information from different sources.

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41

Getz, Wayne M. "Correlative coherence analysis: variation from intrinsic and extrinsic sources in competing populations." Theoretical Population Biology 64, no. 1 (August 2003): 89–99. http://dx.doi.org/10.1016/s0040-5809(03)00026-1.

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42

Lenas, P., N. A. Thomopoulos, D. V. Vayenas, and S. Pavlou. "Oscillations of two competing microbial populations in configurations of two interconnected chemostats." Mathematical Biosciences 148, no. 1 (February 1998): 43–63. http://dx.doi.org/10.1016/s0025-5564(97)10002-5.

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43

Jolles, Etienne, and Olff. "Independent and Competing Disease Risks: Implications for Host Populations in Variable Environments." American Naturalist 167, no. 5 (2006): 745. http://dx.doi.org/10.2307/3844781.

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44

Jolles, Anna E., Rampal S. Etienne, and Han Olff. "Independent and Competing Disease Risks: Implications for Host Populations in Variable Environments." American Naturalist 167, no. 5 (May 2006): 745–57. http://dx.doi.org/10.1086/503055.

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45

Gatto, M. "A general minimum principle for competing populations: Some ecological and evolutionary consequences." Theoretical Population Biology 37, no. 3 (June 1990): 369–88. http://dx.doi.org/10.1016/0040-5809(90)90044-v.

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46

Misra, O. P., Pramod Kushwah, and Chhatrapal Singh Sikarwar. "Dynamical study of native and exotic competing populations: Effects of habitat destruction." Ecological Complexity 17 (March 2014): 46–55. http://dx.doi.org/10.1016/j.ecocom.2013.09.001.

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47

Mukherjee, Debasis. "Impact of predator fear on two competing prey species." Jambura Journal of Biomathematics (JJBM) 2, no. 1 (March 8, 2021): 1–12. http://dx.doi.org/10.34312/jjbm.v2i1.9249.

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Predator-prey interaction is a fundamental feature in the ecological system. The majority of studies have addressed how competition and predation affect species coexistence. Recent field studies on vertebrate has shown that fear of predators can influence the behavioural pattern of prey populations and reduce their reproduction. A natural question arises whether species coexistence is still possible or not when predator induce fear on competing species. Based on the above observation, we propose a mathematical model of two competing prey-one predator system with the cost of fear that affect not only the reproduction rate of both the prey population but also the predation rate of predator. To make the model more realistic, we incorporate intraspecific competition within the predator population. Biological justification of the model is shown through positivity and boundedness of solutions. Existence andstability of different boundary equilibria are discussed. Condition for the existence of coexistence equilibrium point is derived from showing uniform persistence. Local as well as a global stability criterion is developed. Bifurcation analysis is performed by choosing the fear effect as the bifurcation parameter of the model system. The nature of the limit cycle emerging through a Hopf bifurcation is indicated. Numerical experiments are carried out to test the theoretical results obtained from this model.

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48

Liew, Hui. "Transitions among BMI States: A Test of Competing Hypotheses." Obesities 1, no. 1 (December 8, 2020): 1–25. http://dx.doi.org/10.3390/obesities1010001.

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Overweight/obesity and underweight among older adults remain major public health concerns in the United States. This study aims to assess cohort differences in transition among BMI (body mass index) statuses (underweight, normal weight, overweight, and obese) by various cohort and race/ethnicity–gender groups. The empirical work of this study was based on the 1992–2014 Health and Retirement Study (HRS). Multistate life tables (MSLT) were used to assess transitions among different BMI statuses. Results from multistate life tables suggested that the impact of cumulative advantage (disadvantage), persistent inequality, and aging-as-leveler on transition among BMI statuses was shaped along race/ethnicity–gender and cohort lines. Weight management and weight loss strategies should focus on ethnic minorities (i.e., Black and Hispanic populations) and White participants from recent cohorts. Programs aimed at minimizing the negative consequences associated with underweight and weight loss should focus on individuals from earlier cohorts and Black populations.

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KASTNER-MARESCH, ALOIS, and VLASTIMIL KŘIVAN. "MODELLING FOOD PREFERENCES AND VIABILITY CONSTRAINTS." Journal of Biological Systems 03, no. 02 (June 1995): 313–22. http://dx.doi.org/10.1142/s0218339095000290.

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Differential inclusions arising in population biology are analysed and a numerical approach to solve the corresponding initial value problems is proposed. These differential inclusions originate from optimal myopic strategies and from projecting differential equations onto a viability set. We show that such differential inclusions may piecewise be considered either as ordinary differential equations or as differential-algebraic equations with Index 2. The numerical method is based on this observation. Simulations for one population of predators feeding on two populations of prey and for a system of two competing populations whose growth is constrained by a limited resource are given.

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Hunsberger, Eric, Matthew Scott, and Chris Eliasmith. "The Competing Benefits of Noise and Heterogeneity in Neural Coding." Neural Computation 26, no. 8 (August 2014): 1600–1623. http://dx.doi.org/10.1162/neco_a_00621.

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Noise and heterogeneity are both known to benefit neural coding. Stochastic resonance describes how noise, in the form of random fluctuations in a neuron's membrane voltage, can improve neural representations of an input signal. Neuronal heterogeneity refers to variation in any one of a number of neuron parameters and is also known to increase the information content of a population. We explore the interaction between noise and heterogeneity and find that their benefits to neural coding are not independent. Specifically, a neuronal population better represents an input signal when either noise or heterogeneity is added, but adding both does not always improve representation further. To explain this phenomenon, we propose that noise and heterogeneity operate using two shared mechanisms: (1) temporally desynchronizing the firing of neurons in the population and (2) linearizing the response of a population to a stimulus. We first characterize the effects of noise and heterogeneity on the information content of populations of either leaky integrate-and-fire or FitzHugh-Nagumo neurons. We then examine how the mechanisms of desynchronization and linearization produce these effects, and find that they work to distribute information equally across all neurons in the population in terms of both signal timing (desynchronization) and signal amplitude (linearization). Without noise or heterogeneity, all neurons encode the same aspects of the input signal; adding noise or heterogeneity allows neurons to encode complementary aspects of the input signal, thereby increasing information content. The simulations detailed in this letter highlight the importance of heterogeneity and noise in population coding, demonstrate their complex interactions in terms of the information content of neurons, and explain these effects in terms of underlying mechanisms.

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