Multi-group Population Research Articles

Modeling and Optimal Control for Resource Allocation in the Epidemic Monitoring of a Multi-group Population

Modeling and Optimal Control for Resource Allocation in the Epidemic Monitoring of a Multi-group Population

Homogeneity Test of Multi-Sample Covariance Matrices in High Dimensions

In this paper, a new test statistic based on the weighted Frobenius norm of covariance matrices is proposed to test the homogeneity of multi-group population covariance matrices. The asymptotic distributions of the proposed test under the null and the alternative hypotheses are derived, respectively. Simulation results show that the proposed test procedure tends to outperform some existing test procedures.

JMA: Nature-Inspired Java Macaque Algorithm for Optimization Problem

In recent years, optimization problems have been intriguing in the field of computation and engineering due to various conflicting objectives. The complexity of the optimization problem also dramatically increases with respect to a complex search space. Nature-Inspired Optimization Algorithms (NIOAs) are becoming dominant algorithms because of their flexibility and simplicity in solving the different kinds of optimization problems. Hence, the NIOAs may be struck with local optima due to an imbalance in selection strategy, and which is difficult when stabilizing exploration and exploitation in the search space. To tackle this problem, we propose a novel Java macaque algorithm that mimics the natural behavior of the Java macaque monkeys. The Java macaque algorithm uses a promising social hierarchy-based selection process and also achieves well-balanced exploration and exploitation by using multiple search agents with a multi-group population, male replacement, and learning processes. Then, the proposed algorithm extensively experimented with the benchmark function, including unimodal, multimodal, and fixed-dimension multimodal functions for the continuous optimization problem, and the Travelling Salesman Problem (TSP) was utilized for the discrete optimization problem. The experimental outcome depicts the efficiency of the proposed Java macaque algorithm over the existing dominant optimization algorithms.

Multi-fluid modelling of bubbly channel flows with an adaptive multi-group population balance method

Mass, momentum, and energy transfer in bubbly flows strongly depends on the bubble’s size distribution, which determines the contact area between the interacting phases. Characterization of bubble sizes in polydisperse flows requires empirical modelling of sub-grid physical mechanisms such as break-up and coalescence. In the present work an adaptive multiple size-group (A-MuSiG) method is incorporated into the Eulerian multiphase solver available in Simcenter STAR-CCM+ in order to model polydisperse bubbly flows in horizontal and vertical channels. The disperse phasespace is discretized into multiple size-groups each represented by its own size, number-density, and velocity field. The diameter of the bubbles in each of the size-groups varies in time and space, dynamically adapting to the local flow conditions. The interphase momentum transfer between the continuous phase and polydisperse bubbles is modelled through drag, virtual mass, turbulent dispersion, and lift forces. For modelling sub-grid bubble break-up and coalescence processes, different phenomenological kernels are evaluated. The empirical parameters of the adopted kernels are calibrated in two steps. The initial stage of the analysis considers experimental channel flows at low Reynolds number and zero-gravity conditions, under which the bubble size distribution is solely dependent on coalescence. As part of the second phase of the evaluation, additional parametric simulations in turbulent channel flows are performed in order to calibrate the break-up models, assuming the coalescence scaling constants derived in the previous step. The obtained results demonstrate that in flows with high turbulent mixing the ensuing bubble dynamics are strongly coupled to the internal properties of the population, which in turn influence the developing multiphase interactions in a transient manner.

The Group-Level Consequences of Sexual Conflict in Multigroup Populations

In typical sexual conflict scenarios, males best equipped to exploit females are favored locally over more prudent males, despite reducing female fitness. However, local advantage is not the only relevant form of selection. In multigroup populations, groups with less sexual conflict will contribute more offspring to the next generation than higher conflict groups, countering the local advantage of harmful males. Here, we varied male aggression within-and between-groups in a laboratory population of water striders and measured resulting differences in local population growth over a period of three weeks. The overall pool fitness (i.e., adults produced) of less aggressive pools exceeded that of high aggression pools by a factor of three, with the high aggression pools essentially experiencing no population growth over the course of the study. When comparing the fitness of individuals across groups, aggression appeared to be under stabilizing selection in the multigroup population. The use of contextual analysis revealed that overall stabilizing selection was a product of selection favoring aggression within groups, but selected against it at the group-level. Therefore, this report provides further evidence to show that what evolves in the total population is not merely an extension of within-group dynamics.

Intergenerational transmission of women’s educational attainment in South Korea

Abstract Using a multi-group population projection model, this study examines implications of educational mobility and differential demographic rates on changing women's educational distribution in South Korea. This article focuses on implications of a differential population renewal process on educational mobility, which has not been extensively examined in previous studies of social mobility. My findings suggest, first, that differential demographic rates have no substantial influence on educational distribution, because of substantial educational mobility. Second, that intergenerational association and structural change matter in long run, with stronger intergenerational association and more structural change leading to increases in women's level of education. Finally, that educational mobility and differential fertility are interdependent processes that jointly influence differential population replacement, but fertility gap between education groups would have to be unreasonably large to be influential, due to extraordinarily high educational mobility in South Korea. (ProQuest: ... denotes formulae omitted.) 1. Introduction: Demography and social mobility This study examines intergenerational transmission of women's educational attainment in South Korea as a process jointly determined by educational mobility, differential fertility, and differential mortality. Most previous studies on social mobility have focused on intergenerational association in socioeconomic outcomes (e.g., education and occupation) based on existing parent-offspring dyads. Departing from this approach, this study examines implications of differential demographic rates, intergenerational association, and structural change between generations for transmission of socioeconomic status across generations as a whole. First, approach in most previous research has not fully examined how differential reproductive behaviors affect social mobility. Research in social mobility has applied a variety of statistical models, such as path analysis and structural equation models for status attainment process (Blau and Duncan 1967; Hauser, Tsai, and Sewell 1983), log-linear models for intergenerational occupational mobility (Erikson and Goldthorpe 1992; Hout 1984, 1988), and schooling progression-ratio models for educational attainment (Mare 1981; Shavit and Blossfeld 1993). All these models aim at estimating net intergenerational association in socioeconomic outcomes after controlling for potential confounders and change in marginal distributions. Although this approach demonstrates how offspring's socioeconomic outcomes depend on parental socioeconomic status, implications of socioeconomic differentials in demographic behaviors for status transmission have not been widely studied. This is unfortunate, because intergenerational transmission of socioeconomic status is intrinsically the process by which a socioeconomically differentiated population reproduces itself (Mare 1997: 265). Such recognition is not new - demographic models for social mobility were developed as early as 1950s. Prais (1955) adopted a stable population theory to study social mobility, showing that occupational distributions approach a stable-equivalent state independent of initial state when mobility rates remain constant over time. Although Prais recognized possible complications due to demographic processes, his model did not take into account differential fertility and mortality (Prais 1955: 80). Matras published a series of papers that incorporated differential demographic processes into social mobility. He applied Prais's model (1955) using empirical data (Matras 1960), incorporated differential fertility by occupation (Matras 1961), and examined effect of fertility timing on population distribution in later periods (Matras 1967). These studies applied a multi-group population projection that assumes constant mobility and differential reproduction rates over a long period of time. …

Why we talk?: altruism and multilevel selection in the origin of language

Talking entails costs of production and time, although some of the information sent to hearers will be of value to them in general. We believe that the matter of why we talk at all is a key question for the origin of language, and the answer will shed some light on the mystery of human identity. This article focuses on altruism in communication, and aims to demonstrate evolutionary scenarios based on multilevel selection. We constructed a computational model to examine these scenarios. The evolutionary experiments showed that in the case of an unstructured population, a linguistic system hardly emerged due to the dynamics between interpretable utterance that imposes a penalty and correct interpretation that yields a reward, which is similar to prey-predator dynamics. However, in the case of a multigroup population, a linguistic system emerged owing to multilevel selection among the groups. In addition, the probability of success in conversation was higher in a group in more severe environmental conditions. This result supports Bickerton's hypothesis based on the ecological gap between human ancestors and other ape species.

The concept of group heritability

This paper investigates the role of the concept of group heritability in group selection theory, in relation to the well-known distinction between ‘type 1’ and ‘type 2’ group selection (‘GS1’ and ‘GS2’). I argue that group heritability is required for the operation of GS1 but not GS2, despite what a number of authors have claimed. I offer a numerical example of the evolution of altruism in a multi-group population which demonstrates that a group heritability coefficient of zero is perfectly compatible with the successful operation of group selection in the GS2 sense. A diagnosis of why group heritability has wrongly been regarded as necessary for GS2 is suggested.

The critical vaccination fraction for heterogeneous epidemic models

Given a population with m heterogeneous subgroups, a method is developed for determining minimal vaccine allocations to prevent an epidemic by setting the reproduction number to 1. The framework is sufficiently general to apply to several epidemic situations, such as SIR, SEIR and SIS models with vital dynamics. The reproduction number is the largest eigenvalue of the linearized system round the local point of equilibrium of the model. Using the Perron–Frobenius theorem, an exact method for generating solutions is given and the threshold surface of critical vaccine allocations is shown to be a compact, connected subset of a regular ( m−1)-dimensional manifold. Populations with two subgroups are examined in full. The threshold curves are either hyperbolas or straight lines. Explicit conditions are given as to when threshold elimination is achievable by vaccinating just one or two groups in a multi-group population and expressions for the critical coverage are derived. Specific reference is made to an influenza A model. Separable or proportionate mixing is also treated. Conditions are conjectured for convexity of the threshold surface and the problem of minimizing the amount of vaccine used while remaining on the threshold surface is discussed.

The Evolution of Cooperation in Structured Populations

The present paper analyses the evolution of costly cooperation in a multi-group population. Building on insights first developed in modern biology the idea of viscous population equilibria is introduced (a population is said to be viscous when a (sub)population of players is spatially or genetically clustered). A simple model then analyses how the combined effect of viscosity within multiple subgroups and different levels of between-group segregation influences the evolution of cooperation. The results suggest that a key issue in the evolution of cooperation is the shifting balance between the need to protect cooperators and propagation of the tendency to cooperate.

Why People Punish Defectors: Weak Conformist Transmission can Stabilize Costly Enforcement of Norms in Cooperative Dilemmas

In this paper, we present a cultural evolutionary model in which norms for cooperation and punishment are acquired via two cognitive mechanisms: (1) payoff-biased transmission—a tendency to copy the most successful individual; and (2) conformist transmission—a tendency to copy the most frequent behavior in the population. We first show that if a finite number of punishment stages is permitted (e.g. two stages of punishment occur if some individuals punish people who fail to punish non-cooperators), then an arbitrarily small amount of conformist transmission will stabilize cooperative behavior by stabilizing punishment at some n -th stage. We then explain how, once cooperation is stabilized in one group, it may spread through a multi-group population via cultural group selection. Finally, once cooperation is prevalent, we show how prosocial genes favoring cooperation and punishment may invade in the wake of cultural group selection.

A mixed model method to predict QTL-cluster effects using trait and marker information in a multi-group population.

In this study, a mixed model method using trait phenotype and marker information was developed for genetic evaluation of animals in a crossbred population originated from several founder genetic groups. The situation in which a cluster of QTLs is located in a particular chromosome region and is marked by two flanking markers is considered. With this method, the conditional expectation of the identity-by-descent proportion for the QTL-cluster marked and the genetic variances and covariances, given genetic group and marker information, are properly taken into account. The structure of segregation variance used in this method is different from that in the case of a single QTL marked. The current method provides best linear unbiased estimation of the relevant fixed effects and best linear unbiased prediction of the additive effects for the QTL-cluster marked and of the additive effects of the remaining polygenes. A small numerical example is given to illustrate the current prediction procedure.

On the simultaneous distribution of size and costs of an epidemic in a closed multigroup population

A multitype stochastic epidemic model in which the infectivities and susceptibilities differ between subgroups is considered. To each infected are associated random effects of the infection, such as the development of a subsequent disease and the length of the infectivity period. Sums of the corresponding random variables are called costs of the epidemic. The asymptotic simultaneous distribution of the size and costs of large epidemics is derived.

Epidemiology and Social Networks:

The spread of a disease through human populations can be significantly altered by patterned networks of social contact. Largely in response to AIDS, the way in which social networks channel disease has recently become the focus of a sustained modeling effort in epidemiology. The challenge has been to develop a general framework capable of representing both simple and arbitrarily complicated mixing structures, and of solving the matching problem in a non-equilibrium multi-group population. This work is reviewed here. A recent contribution from network analysis links log-linear models of contact structure to diffusion equations for transmission. This framework is described in detail, and some applications to the spread of AIDS are described. The results show that careful analysis of structured mixing can reveal significant features of an epidemic that would otherwise be missed.

A log-linear modeling framework for selective mixing

Nonrandom mixing can significantly alter the diffusion path of an infectious disease such as AIDS that requires intimate contact. Recent attempts to model this effect have sought a general framework capable of representing both simple and arbitrarily complicated mixing structures, and of solving the balancing problem in a nonequilibrium multigroup population. Log-linear models are proposed here as a general framework for solving the first problem. This approach offers several additional benefits: The parameters used to govern the mixing have a simple, intuitive interpretation, the framework provides a statistically sound basis for the estimation of these parameters from mixing-matrix data, and the resulting estimates are easily integrated into compartmental models for diffusion. A modified selection model is proposed to solve the second problem of generalizing the selection process to nonequilibrium populations. The distribution of contacts under this model is derived and is found to satisfy the assumptions of statistical inference for log-linear models. Together these techniques provide an integrated and flexible framework for modeling the role of selective mixing in the spread of disease.

A gonorrhea model treating sensitive and resistant strains in a multigroup population

In recent years gonorrhea infection with antibiotic-resistant strains, especially PPNG, has become a significant public health problem. Drawing on the gonorrhea model of Lajmanovich and Yorke, a multigroup model that embraces both resistant and sensitive strains of the organism is introduced. It is shown that, like the Lajmanovich and Yorke (single-strain) model, in the general case the sensitive-resistant model has a unique globally asymptotic equilibrium. As a function of the interplay between contact rates, cure rates, and reversion rates, the equilibrium can lead to endemic infection with sensitive infection only, resistant infection only, or both, or to elimination of sensitive and resistant infection.