Theory Of Biological Evolution Research Articles

Liberté, déterminisme et neurosciences

Free Will, Determinism and Neuroscience. This contribution aims to show that most recent progress in neuroscience, particularly linked to neural plasticity, permits anthropology where human behavior is characterized by some degree of free will. In a first time, I would like to analyze philosophical stakes of learning mechanisms. I will show that downward causation contradicts reductionist ambition to totally explaining with biology human behavior. In a second time, the possible relations between language and free will will be analyzed. Language permits to respect principle of generalized causality. In a third time, integral determinism in human sciences will be studied. Finally, a conclusion dialogues with indetermination in theories of biological evolution.

The Religious Evolution Theory: The Parallel Religious Evolutions in the Middle East and India

This paper proposes the religious evolution by natural selection adapting to civilizational shifts from technological revolutions, and survival of the fittest. For an example, the parallel religious evolutions by natural selection in the Middle East (Judaism, Christianity, and Islam) and India (Brahmanism, Buddhism, and Hinduism) are through the adaptations to the civilizational shifts from technological revolutions in terms of the Bronze Age, the Iron Age, and the Advanced Iron Age. The civilizational shift from tribal nations with national kings and polytheism during the Bronze Age to a mega empire with one centralized emperor and deity during the Iron Age produces the parallel religious evolutions from theocratic polytheistic Pre-Deuteronomic Judaism to theocratic monotheistic Judaism in the Middle East and from theocratic polytheistic Vedism to theocratic monotheistic Brahmanism in India. The civilizational shift for the rise of ordinary people during the Advanced Iron Age produces the parallel religious evolutions from theocratic monotheistic Judaism to spiritual monotheistic Christianity in the Middle East and from theocratic monotheistic Brahmanism to spiritual monotheistic Buddhism in India. The absorption of Christianity by modified Judaism resulted in Islam to dominate the Middle East, and in parallel, the absorption of Buddhism by Brahmanism resulted in Hinduism to dominate India. As a result, Pre-Deuteronomic Judaism-Judaism-Christianity-Islam in the Middle East is parallel to Vedism-Brahmanism-Buddhism-Hinduism in India. In conclusion, the parallel religious evolutions by natural selection in the Middle East and India are through the adaptations to the civilizational shifts from the technological revolutions. The religious evolution theory is the foundation of religious pluralism as the biological evolution theory is the foundation of biological multi-species. The religion in the coming Intelligence Age is the religious evolution theory which explains the relations among religions, and maintains the original religions and their texts.

On the Possible Beneficial Role for the Regular Use of Potent Mouthwash Solutions as a Preventive Measure for Covid19 Transmission; Invoking the Evolutionary Biology and Game Theory

In vitro studies demonstrated bactericidal and virucidal role for some of the over-the-counter mouthwash solutions. Meanwhile, Game theory and evolutionary biology suggests that inhibiting cooperation -reciprocal altruism- between two organisms can negatively affect their survival, based on a set of relevant publications, it is proposed here that "SARS-COV-2" may be relying on an "accomplice"; be it a certain organism (e.g. bacterial species), or a state of dysbiosis in general. On this premise, the regular use of potent disinfectant, through the repeated reduction in microbial load, may be able to induce a strain sufficient to inhibit reciprocal altruism, and hence halt the progression of the disease, as observed in the majority of those tested positive worldwide, yet with mild or no symptoms. We cite a group of observations related to COVID, that can be justified by the complicit hypothesis, predict a rather preventive than therapeutic advantage, suggestive for a possible role for the regular use of potent mouthwash as an additional control measure in the community level.

Victoria L. Sork—Recipient of the 2020 Molecular Ecology Prize

Victoria L. Sork—Recipient of the 2020 Molecular Ecology Prize

Sensitivity Analysis of Genetic Algorithms for Optimization of Operating Conditions for Protein Production Plants

This work introduces genetic algorithms, which will be investigated and used to perform sensitivity analysis. Genetic algorithms are part of a collection of stochastic optimization algorithms based on the concepts of biological evolutionary theory. This research deals with the problem of the search for optimal investment cost of multiproduct batch chemical plants found in a chemical engineering process with uncertain demand. The aim of this work is to minimize the investment cost and find out the number and size of parallel equipment units in each stage. For this purpose, it is proposed to solve the problem by using Genetics Algorithms (GAs). This GAs consider an effective mixed continuous discrete coding method with a four point crossover operator, which take into account, the uncertainty on the demand using Gaussian process modeling. Experiments indicated that relatively good results could be obtained using 4-point crossover with an applied rate of 0.7 and mutation rate ranged between 0.01 and 0.09 promised to give best performance. The results (number and size of equipment, investment cost, production time (Hi), CPU time and Idle times in plant) obtained by GAs are much more rapidly than mixed integer linear programming. This methodology can help the decision makers and constitutes a very promising framework for finding a set of “good solutions”.

Thomas Aquinas on the Proportionate Causes of Living Species

The principle of proportionate causality is often cited as a cause for concern that Thomistic metaphysics may be irreconcilable with a theory of biological evolution. St. Thomas does hold that for the generation of what he calls perfect animals, a generator of the same species is required. This study clarifies what the proportionate causes of generated organisms are for Thomas, examining his views about spontaneous generation, reproductive generation, and hybridization, while also articulating the roles of both the heavenly bodies and their separate movers as universal causes of generation. This study establishes that Thomas’s assertion of the need for a univocal generator for perfect animals is grounded not in the principle of proportionate causality, but rather in physical and biological doctrines received from Aristotle and in a causal principle that seems reconcilable with biological evolution, namely, that a remote universal cause requires more mediating causes to produce more powerful effects.

Special Issue of Scientia et Fides on Evolution – Introduction

The ongoing debate on the Christian philosophical and theological approach to the theory of biological evolution is multifaceted. It refers to the biblical notion of creation, as well as to some strictly philosophical issues such as the difficulty in defining species and units of evolutionary transitions, the nature of chance, and the classical principle of proportionate causation (saying that an effect cannot exceed its own cause). Moving toward theology, it refers to the distinction between creation ( creatio ) and production ( productio ), and to the notion of secondary causation of creatures in the origin of new forms of organisms – contrasted with the classical assertion that creatures cannot create (even instrumentally).

An Experimental Examination of Demand-Side Preferences for Female and Male National Leaders.

Females constitute a far smaller proportion of political leaders than their proportion in the general population. Leading demand- and supply side explanations for this phenomenon account for some of the variance but leave a great deal unexplained. In an effort to account for additional variance, this research evaluates the issue informed by the biological theory of evolution by natural selection, a foundational explanation for the diversity and function of living organisms. It experimentally assesses how varying types of inter- and intragroup threat–a recurring ancestral problem–affect demand for female and male national leaders. This work analyzes data collected from individuals (N = 826) in the U.S. during the 2012 Cooperative Congressional Election Study. The results suggest the predominant preference for male over female leaders in some contexts may be the non-adaptive and non-functional but lingering outcome of an adaptive preference for physically formidable allies that was shaped by natural selection in ancestral environments.

An Enhanced Genetic Algorithm for Parameter Estimation of Sinusoidal Signals

Estimating the parameters of sinusoidal signals is a fundamental problem in signal processing and in time-series analysis. Although various genetic algorithms and their hybrids have been introduced to the field, the problems pertaining to complex implementation, premature convergence, and accuracy are still unsolved. To overcome these drawbacks, an enhanced genetic algorithm (EGA) based on biological evolutionary and mathematical ecological theory is originally proposed in this study; wherein a prejudice-free selection mechanism, a two-step crossover (TSC), and an adaptive mutation strategy are designed to preserve population diversity and to maintain a synergy between convergence and search ability. In order to validate the performance, benchmark function-based studies are conducted, and the results are compared with that of the standard genetic algorithm (SGA), the particle swarm optimization (PSO), the cuckoo search (CS), and the cloud model-based genetic algorithm (CMGA). The results reveal that the proposed method outperforms the others in terms of accuracy, convergence speed, and robustness against noise. Finally, parameter estimations of real-life sinusoidal signals are performed, validating the superiority and effectiveness of the proposed method.

A New Hope: A better ICM to understand human cognitive architectural variability

How can we best understand human cognitive architectural variability? We believe that the relationships between theories in neurobiology, cognitive science and evolutionary biology posited by evolutionary psychology’s Integrated Causal Model (ICM) has unduly supported various essentialist conceptions of the human cognitive architecture, monomorphic minds (to use Griffiths’ apt phrase), that mask HCA variability, and we propose a different set of relationships between theories in the same domains to support a different, non-essentialist, understanding of HCA variability. To set our case against essentialist theories of HCA variability, we detail the general notion of an ICM and the specific ICM at the heart of evolutionary psychology. We briefly illustrate the type of essentialism fostered by evolutionary psychology’s ICM by showing how it grounds essentialist theories of cognitive gender. We shall not criticize these theories here since the literature is replete with compelling objections to them, but shall instead focus on motivating a replacement ICM to destabilize evolutionary psychology’s ICM wholesale. ICMs usually span larger than the models they support, hence larger than arguments against these models, and one reason the essentialist theories addressed here have the kind of staying power they do is that they are partly supported by the ICM in which they are grounded. In short, we offer “A New Hope” against the essentialist empire. True to the Hollywood trope, this new hope rests on an alliance between a young theory, cognitive network neuroscience, and two older, but still quite young, epistemic rebels: enactive cognitive science and developmental systems theory. Accordingly, we detail and discuss the proposed emerging ICM and test-drive it by sketching the multimorphic view of gender it grounds.

Life-history theory in psychology and evolutionary biology: one research programme or two?

The term ‘life-history theory’ (LHT) is increasingly often invoked in psychology, as a framework for integrating understanding of psychological traits into a broader evolutionary context. Although LHT as presented in psychology papers (LHT-P) is typically described as a straightforward extension of the theoretical principles from evolutionary biology that bear the same name (LHT-E), the two bodies of work are not well integrated. Here, through a close reading of recent papers, we argue that LHT-E and LHT-P are different research programmes in the Lakatosian sense. The core of LHT-E is built around ultimate evolutionary explanation, via explicit mathematical modelling, of how selection can drive divergent evolution of populations or species living under different demographies or ecologies. The core of LHT-P concerns measurement of covariation, across individuals, of multiple psychological traits; the proximate goals these serve; and their relation to childhood experience. Some of the links between LHT-E and LHT-P are false friends. For example, elements that are marginal in LHT-E are core commitments of LHT-P, and where explanatory principles are transferred from one to the other, nuance can be lost in transmission. The methodological rules for what grounds a prediction in theory are different in the two cases. Though there are major differences between LHT-E and LHT-P at present, there is much potential for greater integration in the future, through both theoretical modelling and further empirical research.This article is part of the theme issue ‘Life history and learning: how childhood, caregiving and old age shape cognition and culture in humans and other animals’.

Indonesian Pre-service Biology Teachers’ and Biology Education Professors’ Views on Evolution

Indonesia is a religious country that values local wisdom and customs. Although the characteristics of the Indonesian people may provide novel insight into and distinguished views on the theory of evolution by natural selection, few studies have explored how Indonesians view the theory of biological evolution. Thus, this study aimed to examine the views on evolution of undergraduate students and their professors majoring in biology education. A multiple-case approach was used as the method of this study. Three pre-service biology teachers and three biology education professors were interviewed. The interview results revealed that the six participants embraced creationism without accepting the theory of evolution by natural selection. One intriguing result was that Indonesian professors in this sample tended to see no conflict between evolution and religion. Instead, they believed in seeking harmonization by compartmentalizing evolution and religion. The participants connected their views to the current state of the science curriculum that embraced the idea of harmonization between science and religion. In addition, four categories were found in terms of how the participants approached evolution acceptance and its relation to religion. How the participants negotiated the dilemma between evolution and personal or cultural values is discussed, and suggestions for teaching and learning evolution are presented.

INVESTIGAÇÕES SOBRE O ENSINO DE PALEONTOLOGIA E EVOLUÇÃO NO ENSINO MÉDIO

A Paleontologia atua de forma conjunta com a evolução biológica das espécies, pois fornece evidencias sobre os principais processos evolutivos. Por isso, este estudo teve como objetivo analisar as percepções de estudantes de uma escola pública em São João do Patos/MA, Brasil a respeito do estudo dos fósseis para o entendimento de mudanças evolutivas em populações biológicas. A pesquisa foi desenvolvida com 33 estudantes da 3ª série do Ensino Médio do Centro de Ensino Dr. Paulo Ramos, situada no estado do Maranhão. Como instrumento de coleta de dados, utilizou-se um questionário com perguntas abertas e fechadas de modo a identificar como os estudantes percebiam a dinâmica da Terra, no que se refere ao estudo das rochas, dos fósseis para a compreensão de mecanismos evolutivos. Observou-se que a maioria dos estudantes demonstrava concepção considerada satisfatória sobre a importância dos registros fósseis para o entendimento da teoria da evolução biológica das espécies, evidenciando que o professor da disciplina de Biologia trabalhou os princípios geológicos e paleontológicos para facilitar a compreensão da evolução. Portanto, é preciso trabalhar de forma interdisciplinar esses conceitos provenientes da Geologia, Paleontologia e Evolução, a fim que o aluno possa construir um conhecimento sólido e integrado, contribuindo então, para a consolidação de uma aprendizagem significativa.

Apontamentos sobre a organização do criacionismo e do intelligent design nos EUA e no Brasil

O crescimento das instituições religiosas, especialmente as de denominação cristã no Brasil e no mundo tem contribuído para a disseminação das interpretações religiosas sobre a origem do mundo e os fenômenos naturais e sociais. Nesse contexto a ciência como instrumento de compreensão do mundo perde espaço para as revelações míticas, presentes nas escrituras bíblicas. O criacionismo, como a principal interpretação cristã para a explicação sobre a origem do mundo tem se revigorado na disputa de terreno com a ciência, ao questionar as descobertas científicas, inspiradas na teoria da evolução biológica, eixo norteador das ciências naturais, apresentando alternativas pseudocientíficas para a compreensão da complexa organização do mundo natural. Nesse artigo são apresentados alguns apontamentos sobre a organização do criacionismo e do Intelligent Design nos EUA, berço de sua constituição, e no Brasil, cuja disseminação tem ocupado várias instituições da república.

Antropocentrismo, antropoceno, evolución


 
 
 En este trabajo relevo algunos conceptos particulares que se desarrollaron en distintos campos disciplinares desde fines del siglo XX y principios del siglo XXI, y los coloco en diálogo con la epistemología, para sostener que se puede tematizar una “epistemología del riesgo” con elementos actuales. Así, una serie de nuevos términos fueron generados en diversas áreas científicas y filosóficas desde la década de 1970 hasta el presente para dar cuenta conceptualmente de algunas de las problemáticas propias de nuestra época. Entre ellas podemos encontrar: antropoceno, ecocidio, biocidio, geocidio, defaunación, americanización del mundo, sexta extinción masiva de especies, polución espacial, catástrofes de lesa ambientalidad e impacto antrópico. Estos a su vez, pueden vincularse con la clásica idea de sociedad del miedo. Es posible afirmar que tales términos configuran un panorama epistemológico relativamente reciente y problemático, que se complejiza aún más incorporando el nivel de análisis macro que proporciona la teoría de la (co)evolución biológica. Propongo, entonces, que este panorama puede ser entendido como una nueva epistemología del riesgo antrópico.
 
 

Application of Improved Genetic Programming for Feature Extraction in the Evaluation of Bearing Performance Degradation

In the evaluation of bearing performance degradation, discovering a good HI (Health Indicator) is one of the most crucial parts, because it determines whether a precise result can be obtained in the prediction of remaining useful life. In this paper, GP (Genetic Programming), which is a heuristic iterative search algorithm inspired by the theory of biological evolution, is improved in genetic operation and fitness function, and a feature weighted matrix is used in GP innovatively. The improved GP is applied to discover a HI by fusing multiple features, which is very close to linearity. Furthermore, by optimizing the discovered HIs, an optimization HI is obtained, which has a higher fitness and can get a more precise result in the prediction of RUL. The proposed approach is verified in the experimental data for the entire life of the bearing provided by 2012 IEEE PHM challenge, and a total of three bearings are used in the verification.

An Adaptive Approach to Controlling Parameters and Population Size of Evolutionary Algorithm

Evolutionary algorithm (EA) is a part of evolutionary computing inspired by the theory of biological evolution. Evolutionary algorithms have three parameters that must be defined, namely population size, probability of crossing over, and probability of mutation. The absence of standard rules in setting the value of these parameters becomes a difficulty in utilizing evolutionary algorithms to solve optimization problems so that it can cause early convergence in obtaining local optimum values. This research was conducted to find a way to adjust the value of these parameters by using fuzzy logic to determine the probability of crossing and mutation probability and the method of determining population size based on the best fitness value. This method is called Population Resizing on Fitness Improvement Fuzzy Evolutionary Algorithm (PRoFIFEA). The testing of this method uses the problem of Traveling Salesman Problem (TSP) compared to the standard evolutionary algorithm method which states that the PRoFIFEA method is able to find a more optimal solution.

Research on the optimisation of complex models of large-scale building structures dependent on adaptive grey genetic algorithms

Genetic algorithm (GA) is a bionics algorithm based on the biological evolution theory that has received extensive attention in the field of computer science and optimisation in recent years. This paper analyses and integrates the relevant contents of genetic algorithm and its application in the optimal design of large-scale building structures and analyses and researches briefly several key factors when the genetic algorithm is applied to the optimal design of large-scale building structures, such as mathematical modelling, constraint condition treatment, generation of initial population and selection of control parameters of genetic algorithm. However, because the simple genetic algorithm is only good at global search, and the local search ability is not enough, it will take quite a long time to achieve the real optimal solution. For the shortcomings of simple genetic algorithm, an improved adaptive grey genetic algorithm is proposed in this paper. The example shows that the obtained adaptive genetic algorithm can improve the convergence and calculation speed when the genetic algorithms is applied to structural optimisation design.

Research on the optimisation of complex models of large-scale building structures dependent on adaptive grey genetic algorithms

Genetic algorithm (GA) is a bionics algorithm based on the biological evolution theory that has received extensive attention in the field of computer science and optimisation in recent years. This paper analyses and integrates the relevant contents of genetic algorithm and its application in the optimal design of large-scale building structures and analyses and researches briefly several key factors when the genetic algorithm is applied to the optimal design of large-scale building structures, such as mathematical modelling, constraint condition treatment, generation of initial population and selection of control parameters of genetic algorithm. However, because the simple genetic algorithm is only good at global search, and the local search ability is not enough, it will take quite a long time to achieve the real optimal solution. For the shortcomings of simple genetic algorithm, an improved adaptive grey genetic algorithm is proposed in this paper. The example shows that the obtained adaptive genetic algorithm can improve the convergence and calculation speed when the genetic algorithms is applied to structural optimisation design.

LearnPopGen: An R package for population genetic simulation and numerical analysis.

Here, I briefly present a new R package called learnPopGen that has been designed primarily for the purposes of teaching evolutionary biology, population genetics, and evolutionary theory. Functions of the package can be used to conduct simulations and numerical analyses of a wide range of evolutionary phenomena that would typically be covered in advanced undergraduate through graduate‐level curricula in population genetics or evolution. For instance, learnPopGen functions can be used to visualize gene frequency changes through time under multiple deterministic and stochastic processes, to compute and animate the changes in phenotypic trait values or distributions under natural selection, to numerically analyze and graph the outcome of simple game theory models, and to plot coalescence within a population experiencing genetic drift, along with a number of other things. Functions have been designed to be maximally didactic and frequently employ compelling animated visualizations. Furthermore, it is straightforward to export plots and animations from R in the form of flat or animated graphics, or as videos. For maximum flexibility, students working with the package can run functions directly in R; however, instructors may choose to guide students less adept in the R environment to one of various web interfaces that I have built for a number of the functions of the package and that are already available online.