You Are What You Eat
Emily Crews Splane, Neil E. Rowland, Anaya Mitra in Psychology of Eating, 2019
The theory of evolution attributed to Charles Darwin proposed that species evolve by a very slow process called natural selection. This means that a species will change, over a long time span, if that change allows the individuals or group to exploit or compete for resources better than their ancestors or competitors. These individuals are said to have higher biological fitness because they live to produce more offspring inheriting the fitness traits encoded in their genes. Most scientists are swayed by overwhelming evidence that humans and all living entities past and present are products of natural selection. At the behavioral level, choices and decision making are crucial cognitive manifestations of natural selection, enhancing survival and fitness in a particular environment.
Hugo de Vries (1848–1935)
Krishna Dronamraju in A Century of Geneticists, 2018
To understand the significance of de Vries’s research, it is important to place his investigation in the context of the scientific debates of the period. Charles Darwin’s theory of evolution by natural selection was published in 1859. He held that species evolved or changed in form from generation to generation because some members of the species lived for a longer time than others and were able to produce more offspring than their less fit fellows. In the long run, this would result in a species becoming more like the favored variation and less like the unfavored variations. In his Origin of Species, Darwin did not establish how variations occurred or how they were inherited. Subsequently, the area of heredity and variation became a recognized field of research for biologists interested in evolutionary theory.
Infectious Diseases
Lyle D. Broemeling in Bayesian Analysis of Infectious Diseases, 2021
Microorganisms play the survival game very well indeed, because they adapt far more rapidly than humans as the scene shifts in front of them. Among humans each generation is approximately 20 years, but for bacteria a generation ranges from 20–30 min, and in the case of viruses, a generation is much smaller. Richard Krause, former director of the National Institute of Allergy and Infectious Disease (NIAID) calls this rapidity a millennium in a fortnight. The current director of this agency is Dr. Fauci, who appears with President Trump on the daily briefings of the Coronavirus Task Force. An important aspect of evolution is natural selection, the process by which genetically adapted individuals leave more offspring and in the process transmit more favorable characteristics, and thus operate far more efficiently in the setting of microorganisms. Since these aggregate in large numbers, bacteria and viruses do support a considerable variety in their communities, including mutations that may be expressed when the environment changes. A thimble can contain a billion bacteria, can disappear on Tuesday, and appear in the same quantity on Wednesday.
The Gravitational Pull of Identity: Professional Growth in Sport, Exercise, and Performance Psychologists
Published in Journal of Sport Psychology in Action, 2020
David Tod, Hayley McEwan, Charlotte Chandler, Martin Eubank, Moira Lafferty
Professional evolution may be a more suitable label. Evolution does not imply a single path or endpoint. Instead, evolution focuses on the fit between practitioners and their current professional niches. Individuals ensure sustainable careers when they acquire behaviors and practices that match the demands of the environments they are currently in, or hope to inhabit. Entrepreneurial consultants may create niches to suit their skills. Practitioners wishing to work in the performing arts, for example, benefit from learning the language and cultures associated with musicians, dancers, actors, etc. Evolution is dynamic and ongoing because people and environments continually change. The existing practitioner-setting fit may become obsolete, rendering consultants less effective or able to sustain their careers.
On the life and work of Korbinian Brodmann (1868–1918)
Published in Journal of the History of the Neurosciences, 2019
Thomas Mueller, Uta Kanis-Seyfried
Brodmann and his contemporaries also used the term localization for the morphological part of a topical brain research in the cerebral cortex—that is, for the mapping of the brain. Theodor Meynert (1833–1892) had recognized functional differences of individual regions of the cortex and demanded the description of individual “cortical organs.” Oskar Vogt’s Berlin Institute immediately tied in with Meynert’s cortex organology. Whereas Oskar Vogt and Cécile Vogt studied the myeloarchitectural structure (i.e., the nerve fibers), Brodmann focused on the cellular structure (i.e., cytoarchitectonics). Research to date had described brain convolutions and convolution complexes. A uniform nomenclature was missing. Brodmann’s aim was to obtain a complete picture of the cortex construction and its local modifications in all its parts, and possibly to arrive at a topographical–localizational structure of the cortex surface that could also be used by the clinic. He had realized that the creation of these foundations for more precise topographical–localizational research needed to be preceded by improved information on the principles of cerebral cortex organization: by a comparative anatomical analysis of human and mammal brains. An important prerequisite for this approach was the theory of evolution by Charles Darwin (1809–1882).
An insight into technology diffusion of tractor through Weibull growth model
Published in Journal of Applied Statistics, 2018
Bishal Gurung, K. N. Singh, Ravindra Singh Shekhawat, Md Yeasin
To this end, a very efficient and powerful stochastic optimization technique, viz. GA technique first conceived by John Holland in 1975, can be employed. GA methodology, a computational method to find optimal solution, is capable of rectifying the above limitations. In GA, the parameters form a string, where each string represents a solution to the problem. An objective payoff function is used to measure how well a particular solution solves the problem. Improved solutions are subsequently evolved within a population of chromosomes over a number of generations. The GA algorithm optimizes a problem by iteratively trying to improve a candidate solution with respect to an objective function. GA simulates the evolution of living organisms, where the fittest individual dominates over the weaker ones, by mimicking the biological mechanism of evolution. It combines Darwin’s principle of ‘natural selection’ and ‘survival of the fittest’ with computer-constructed evolution mechanism to select better offspring from the original population. In the GA-literature, mainly two types of procedures are available, viz. Binary-coded GA (BCGA) and Real-coded GA (RCGA). In the former, the coded parameters form a string (chromosome), where each string represents a solution to the problem. Unlike the classical search and optimization methods, GA begins its search with a random set of solutions instead of just one solution. So, GA not only overcomes the traps of local optimization, but also reduces much computational time to find optimum solution [8].
Related Knowledge Centers
- Biodiversity
- Genetic Drift
- Heredity
- Morphology
- Phenotype
- Phenotypic Trait
- Physiology
- Heritability
- Natural Selection
- Fitness