scholarly journals Dynamical Systems Modeling of Bt Resistant Cornborer Population Dynamics

2019 ◽  
Author(s):  
Jomar F. Rabajante ◽  
Arian J. Jacildo ◽  
Edwin P. Alcantara
Keyword(s):  
Population Dynamics ◽  
Dilution Effect ◽  
Pesticide Resistance ◽  
Initial Population ◽  
Systems Modeling ◽  
Simple Mathematical Model ◽  
Design And Optimization ◽  
Dynamical Systems Modeling ◽  
Control Disease ◽  
Disease Epidemics

SummaryMathematical models provide insights for the design and optimization of strategies to control disease epidemics and evolution of pesticide resistance in crops. Here, we present a simple mathematical model to investigate the population dynamics of non-Bt resistant and Bt resistant cornborers in a field with refuge. In the presence of refuge, it is expected that the population of Bt resistant pests will decline due to the dilution effect (non-Bt resistant cornborers mate with Bt resistant pests). We have found that increasing the refuge size can be effective in reducing Bt resistant pests as long as there exists a relatively huge population of non-Bt resistant cornborers at the start of the simulation. This implies that refuge is useless in inhibiting the evolution of cornborers if a sufficient initial population of non-Bt resistant cornborers is absent.

scholarly journals Population Dynamics Based on Resource Availability & Founding Effects: Live & Computational Models

2016 ◽  
Vol 78 (5) ◽  
pp. 396-403 ◽  
Author(s):  
Samuel Potter ◽  
Rebecca M. Krall ◽  
Susan Mayo ◽  
Diane Johnson ◽  
Kim Zeidler-Watters ◽  
...  
Keyword(s):  
Population Dynamics ◽  
Computer Literacy ◽  
Computational Models ◽  
Computational Simulation ◽  
School Science ◽  
Simulation Software ◽  
High School Science ◽  
Initial Population ◽  
College Level ◽  
Factors Affecting

With the looming global population crisis, it is more important now than ever that students understand what factors influence population dynamics. We present three learning modules with authentic, student-centered investigations that explore rates of population growth and the importance of resources. These interdisciplinary modules integrate biology, mathematics, and computer-literacy concepts aligned with the Next Generation Science Standards. The activities are appropriate for middle and high school science classes and for introductory college-level biology courses. The modules incorporate experimentation, data collection and analysis, drawing conclusions, and application of studied principles to explore factors affecting population dynamics in fruit flies. The variables explored include initial population structure, food availability, and space of the enclosed population. In addition, we present a computational simulation in which students can alter the same variables explored in the live experimental modules to test predictions on the consequences of altering the variables. Free web-based graphing (Joinpoint) and simulation software (NetLogo) allows students to work at home or at school.

scholarly journals A Revisit of Infinite Population Models for Evolutionary Algorithms on Continuous Optimization Problems

2020 ◽  
Vol 28 (1) ◽  
pp. 55-85
Author(s):  
Bo Song ◽  
Victor O.K. Li
Keyword(s):  
Population Dynamics ◽  
Evolutionary Algorithms ◽  
Population Size ◽  
Optimization Problems ◽  
Continuous Optimization ◽  
Analytical Framework ◽  
Population Models ◽  
Initial Population ◽  
Infinite Population ◽  
Continuous Optimization Problems

Infinite population models are important tools for studying population dynamics of evolutionary algorithms. They describe how the distributions of populations change between consecutive generations. In general, infinite population models are derived from Markov chains by exploiting symmetries between individuals in the population and analyzing the limit as the population size goes to infinity. In this article, we study the theoretical foundations of infinite population models of evolutionary algorithms on continuous optimization problems. First, we show that the convergence proofs in a widely cited study were in fact problematic and incomplete. We further show that the modeling assumption of exchangeability of individuals cannot yield the transition equation. Then, in order to analyze infinite population models, we build an analytical framework based on convergence in distribution of random elements which take values in the metric space of infinite sequences. The framework is concise and mathematically rigorous. It also provides an infrastructure for studying the convergence of the stacking of operators and of iterating the algorithm which previous studies failed to address. Finally, we use the framework to prove the convergence of infinite population models for the mutation operator and the [Formula: see text]-ary recombination operator. We show that these operators can provide accurate predictions for real population dynamics as the population size goes to infinity, provided that the initial population is identically and independently distributed.

scholarly journals Hankelet-based dynamical systems modeling for 3D action recognition

2015 ◽  
Vol 44 ◽  
pp. 29-43 ◽  
Author(s):  
Liliana Lo Presti ◽  
Marco La Cascia ◽  
Stan Sclaroff ◽  
Octavia Camps
Keyword(s):  
Dynamical Systems ◽  
Action Recognition ◽  
Systems Modeling ◽  
Dynamical Systems Modeling

scholarly journals Settlement network topology as a factor of rural population dynamics (a case study of Tyumen oblast)

2019 ◽  
pp. 46-62
Author(s):  
A. V. Sheludkov ◽  
M. A. Orlov
Keyword(s):  
Population Dynamics ◽  
Network Topology ◽  
Population Increase ◽  
Initial Population ◽  
Tyumen Oblast ◽  
Network Position ◽  
Network Cluster ◽  
Population Concentration ◽  
Network Pattern

After a brief counter-urbanization of the early 1990s, rural out-migration resumed in Russia. Population concentrates in large settlements, while small and medium-sized towns and villages lose people. The farther rural settlements from regional center the greater the outflow of people. Centripetal tendencies can be mitigated or amplified at local level, where specific conditions of the area come to fore. The authors suggest settlement network pattern as one of such contextual factors, whose effects on population dynamics are still poorly understood. The paper poses two questions: what the effects of settlement network topology on the rate of population concentration are, and how population dynamics in individual settlements depends on their position in settlement network. Based on a case study of Tyumen oblast of Russia the authors investigated population dynamics in 2002–2010 with methods of network, cluster and regression analysis. The authors did not find relationship between density and centralization of settlement network and rate of population concentration. However, the study revealed a significant role, played by the network position in determining individual settlements population increase/decrease. Together with initial population size, the network position explained 23–24% of the variance in population dynamics among the towns and villages of Tyumen oblast. Outside the Tyumen metropolitan area settlements with highest inter-district network centrality grew. It is noteworthy that configuration of the regional settlement network at inter-district level emerged during the period of colonization of Western Siberia in 17–19 centuries. The configuration largely stems from the river network. Thus, even if the factors, which determined settlement network pattern, have lost their force, the settlement pattern itself continues to affect social space.

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