Rather than evidence that humans are an exception among primates, we consider this disparity to be a clue that, in primate evolution, developing a very large body and a very large brain have been mutually excluding strategies, probably because of metabolic reasons".
Hull's idea of science as a process models historical unity after a Darwinian-style pattern of evolution (developing an earlier suggestion by Popper).
Taking these correlations together, the dynamics of the tumour progression offers an opportunity to interfere in the tumour evolution and develop a more customized treatment.
Therefore, a new promising direction in environmental biotechnology is to apply the principles of ecobiotechnology and adaptive laboratory evolution to develop a mixed microbial population, selected to achieve a higher production yield and which would have unique metabolic capacities [ 25], at lower operational costs [ 6, 26].
Ultimately, a new synthesis will be needed in which evolutionary biologists focused on contemporary evolution develop academic programmes jointly with scientists interested in medicine.
Molecular evolution developed as a phylogenetic method for the comparison of DNA sequences and whole genomes; molecular systematics sought to research the evolution of the genetic code as well as the rates of that evolutionary process by comparing similarities and differences between molecules (Dietrich 1998).
This Nativist connection to evolution raises a natural question: why did the resurgence of Nativism have to wait for Chomskyan linguistics; why didn't the theory of evolution, developed more than a half-century earlier, undermine Empiricism and resurrect Nativism?
His most important work, Primitive Culture (1871), influenced in part by Darwin's theory of biological evolution, developed the theory of an evolutionary, progressive relationship from primitive to modern cultures.
Through exposure to science ideas and deeper exploration and explanation of evolution, students can develop a greater knowledge of scientific thinking and evidence, which in turn leads to greater understanding of evolution.
In this paper, we introduce an advanced architecture of K-means clustering-based polynomial Radial Basis Function Neural Networks (p-RBF NNs) designed with the aid of Particle Swarm Optimization (PSO) and Differential Evolution (DE) and develop a comprehensive design methodology supporting their construction.
