Narrow Results

This article describes a complex network model whose weights are proportional to the difference between uniformly distributed "fitness" values assigned to the nodes. It is shown both analytically and experimentally that the strength density (i.e., the weighted node degree) for this model, called derivative complex networks, follows a power law with exponent γ<1 if the fitness has an upper limit and γ>1 if the fitness has no upper limit but a positive lower limit. Possible implications for neuronal networks topology and dynamics are also discussed.

We propose a new mechanism leading to scale-free networks which is based on the presence of an intrinsic character of a vertex called fitness. In our model, a vertex i is assigned a fitness x_i, drawn from a given probability distribution function f(x). During network evolution, with rate p we add a vertex j of fitness x_j and connect to an existing vertex i of fitness x_i selected preferentially to a linking probability function g(x_i, x_j) which depends on the fitnesses of the two vertices involved and, with rate 1 - p we create an edge between two already existed vertices with fitnesses x_i and x_j, with a probability also preferential to the connection function g(x_i, x_j). For the proper choice of g, the resulting networks have generalized power-laws, irrespective of the fitness distribution of vertices.

Evolutionary graph theory was recently proposed by Lieberman et al. in 2005. In the previous papers about evolutionary graphs (EGs), the fitness of the residents in the EGs is in general assumed to be unity, and the fitness of a mutant is assumed to be a constant r. We aim to extend EG to general cases in this paper, namely, the fitness of a mutant is heavily dependent upon frequency. The corresponding properties for these new EGs are analyzed, and the fixation probability is obtained for large population.

Evolutionary graph theory (EGT) is recently proposed by Lieberman et al. in 2005. EGT is successful for explaining biological evolution and some social phenomena. It is extremely important to consider the time of fixation for EGT in many practical problems, including evolutionary theory and the evolution of cooperation. This study characterizes the time to asymptotically reach fixation.

The population dynamics for predator and prey environments have been studied extensively, and several major mathematical models have been introduced to quantify this. The situation becomes more complex, however, when the prey incorporates preservation strategies for survival. One of the most interesting approaches here is the use of mimicry of prey which are unacceptable to the predator, to avoid being consumed. Here we develop a Markov chain model of interactions between a predator and a prey population comprising unpalatable models, general mimics and specific mimics. This incorporates a simple stochastic procedure for the predator, enabling modifiable behavior to be modeled. We calculate equilibrium consumption probabilities and introduce a fitness measure for each type of prey. Finally, by taking into account the population size of each type of prey, we extend the previously reported notion of a predator benefit function for this more complex situation and provide various mathematical forms of optimal benefit for the predator under selected scenarios of biological importance.

Facilitating the company's competitive advantage building as well as enhancing its financial performance, the fitness between one company's technology strategy and its corporate strategy plays a significant role of ensuring the deployment of the company's technological capability and technological resources. In order to analyze the factors which influence the fitness between a company's technological capabilities and its corporate strategy, this study introduces four factors based on the former relevant studies. They are the external environment, top management, firm's technological resources and the organizational convergence ability. Moreover, this study has creatively utilized technology attitude, product innovation and process innovation as three indicators to measure the studying object: the fitness between a company's technology strategy and corporate strategy. After empirical research, a model is constructed, with all the detailed influencing factors and their functional mechanism included. Finally, the limitations and future expectations are discussed.

Fundamental questions posed in classical genetics since early 20th century are still fundamental in today post genomic age. What has changed is the availability of huge amount of molecular genetics information on a broad spectrum of species and a more powerful and rich methodological approach, particularly that one based on statistical mechanics and dynamical system theory which is providing unprecedented prediction power. Here we focus on the behavior of basic life forms such as bacteria and viruses which have small genomes and short generation times. We show that central issues of the evolutionary theory, i.e. how genotype, phenotype and fitness are related, the effect of positive and negative natural selection, the specie formation could be described by simple models which allow predictions and validation using experimental data.

Despite the growing popularity in recent years of elliptical exercise (EE), little is known regarding the loadings applied to the body during EE. Since overloading to the body may lead to early fatigue of the muscles and increase the incidence of overuse injuries, such information is necessary for safe use of the elliptical trainer (ET) as a fitness tool. The current study aimed to determine the typical patterns and loading rates of the measured pedal reaction forces (PRF), and to quantify their differences from those during level walking, and the effects of pedaling rate. Fifteen male adults performed level walking and EE while 3D marker data, right PRFs and ground reaction forces (GRF) were measured. The parameters of the ET were set for two different pedal rates: 50 rpm and 70 rpm. For each pedal rate, the parameters were set to match the variables measured during level walking, with a mean step length of 55% leg length and no workload. During early stance the vertical PRF was smaller than the GRF, while the medial and posterior PRF were greater. PRFs also occurred during swing. Loading rates around heelstrike during EE were all smaller than those during walking. The medial, anterior and posterior PRF, as well as the medial and vertial loading rates increased with increasing pedal rates. The basic force patterns of EE and the effects of pedal rate were established in order to determine the true potential for such instrumentation in locomotion analysis. The results will be helpful for future related studies.

Facilitating the company’s competitive advantage building as well as enhancing its financial performance, the fitness between one company’s technology strategy and its corporate strategy plays a significant role of ensuring the deployment of the company’s technological capability and technological resources. In order to analyze the factors which influence the fitness between a company’s technological capabilities and its corporate strategy, this study introduces four factors based on the former relevant studies. They are the external environment, top management, firm’s technological resources and the organizational convergence ability. Moreover, this study has creatively utilized technology attitude, product innovation and process innovation as three indicators to measure the studying object: the fitness between a company’s technology strategy and corporate strategy. After empirical research, a model is constructed, with all the detailed influencing factors and their functional mechanism included. Finally, the limitations and future expectations are discussed.

The evolution of fitness is central to evolutionary theory, yet few experimental systems allow us to track its evolution in genetically and environmentally relevant contexts. Reverse evolution experiments allow the study of the evolutionary return to ancestral phenotypic states, including fitness. This in turn permits well-defined tests for the dependence of adaptation on evolutionary history and environmental conditions. In the experiments described here, 20 populations of heterogeneous evolutionary histories were returned to their common ancestral environment for 50 generations, and were then compared with both their immediate differentiated ancestors and populations which had remained in the ancestral environment. One measure of fitness returned to ancestral levels to a greater extent than other characters did. The phenotypic effects of reverse evolution were also contingent on previous selective history. Moreover, convergence to the ancestral state was highly sensitive to environmental conditions. The phenotypic plasticity of fecundity, a character directly selected for, evolved during the experimental time frame. Reverse evolution appears to force multiple, diverged populations to converge on a common fitness state through different life-history and genetic changes.