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  • https://arxiv.org/abs/1703.03864
    Evolution Strategies as a Scalable Alternative to Reinforcement Learning
    We explore the use of Evolution Strategies (ES), a class of black box optimization algorithms, as an alternative to popular MDP-based RL techniques such as Q-learning and Policy Gradients. Experiments on MuJoCo and Atari show that ES is a viable solution strategy that scales extremely well with the number of CPUs available: By using a novel communication strategy based on common random numbers, our ES implementation only needs to communicate scalars, making it possible to scale to over a thousand parallel workers. This allows us to solve 3D humanoid walking in 10 minutes and obtain competitive results on most Atari games after one hour of training. In addition, we highlight several advantages of ES as a black box optimization technique: it is invariant to action frequency and delayed rewards, tolerant of extremely long horizons, and does not need temporal discounting or value function approximation.
    ARXIV.ORG
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    https://arxiv.org/abs/1703.03864
    Evolution Strategies as a Scalable Alternative to Reinforcement Learning
    We explore the use of Evolution Strategies (ES), a class of black box optimization algorithms, as an alternative to popular MDP-based RL techniques such as Q-learning and Policy Gradients. Experiments on MuJoCo and Atari show that ES is a viable solution strategy that scales extremely well with the number of CPUs available: By using a novel communication strategy based on common random numbers, our ES implementation only needs to communicate scalars, making it possible to scale to over a thousand parallel workers. This allows us to solve 3D humanoid walking in 10 minutes and obtain competitive results on most Atari games after one hour of training. In addition, we highlight several advantages of ES as a black box optimization technique: it is invariant to action frequency and delayed rewards, tolerant of extremely long horizons, and does not need temporal discounting or value function approximation.
    ARXIV.ORG
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  • https://www.thehealthsite.com/topics/coronavirus-evolution/
    coronavirus evolution : Top and Latest News, Articles, Videos and Photo About coronavirus evolution
    Get coronavirus evolution latest news, Article video and Photos on coronavirus evolution Explore latest health updates, news, information from TheHealthSite.com
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  • https://arxiv.org/abs/astro-ph/0307133
    Origin and evolution of neutron star magnetic fields
    This paper intends to give a broad overview of the present knowledge about neutron star magnetic fields, their origin and evolution. An up-to-date overview of the rich phenomenology (encompassing ``classical'' and millisecond radio pulsars, X-ray binaries, ``magnetars'', and ``thermal emitters'') suggests that magnetic fields on neutron stars span at least the range $10^{8-15}$ G, corresponding to a range of magnetic fluxes similar to that found in white dwarfs and upper main sequence stars. The limitations of the observational determinations of the field strength and evidence for its evolution are discussed. Speculative ideas about the possible main-sequence origin of the field (``magnetic strip-tease'') are presented. Attention is also given to physical processes potentially leading to magnetic field evolution.
    ARXIV.ORG
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  • https://ui.adsabs.harvard.edu/abs/1998Geomo..22..325G
    New constraints on the evolution of Carolina Bays from ground-penetrating radar
    Ground-penetrating radar (GPR) data for the Savannah River Site (SRS) in the Upper Coastal Plain of South Carolina, combined with geological, archaeological, and ecological data place new constraints on the evolution of Carolina Bays. Extant SRS bay morphology formed mainly during the Holocene and did not involve migration of bays across the landscape. Multiple periods of bay-rim accretion with intervening intervals of erosion may characterize the longer-term evolution of the bays. Bay evolution, however, did not involve significant modification of the Upland Unit underlying the region. During fluctuating, but generally open water conditions, breaking waves along bay shorelines eroded and transported sediment which was subsequently exposed for deflation during periods of low water. Deflation and transport of sand into standing vegetation along the margin of the bay depression created a rim in the form of a parabolic dune lacking obvious internal stratification. Simultaneously, infilling occurred by shoreline erosion and transport from adjacent elevated surfaces. This, coupled with growth of emergent vegetation, resulted in decreased hydroperiod, wave energy, shoreline modification, and rim accretion. Transport of some rim sediments back into the bays via alluvial and colluvial activity created wedges of infilling sediment during waning stages of evolution. The apparent contradiction of bay orientation with respect to prevailing winds might reflect seasonal changes in water level and wind direction: southwesterly winds during spring high water causes NW-SE elongation of the bays, whereas northwesterly winds during lower water in the fall and winter account for nearshore deflation and rim accretion along the east-southeastern bay margins.
    UI.ADSABS.HARVARD.EDU
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  • https://ui.adsabs.harvard.edu/abs/2018CBio...28E3441G
    Interspecific Gene Flow Shaped the Evolution of the Genus Canis
    Summary. The evolutionary history of the wolf-like canids of the genus Canis has been heavily debated, especially regarding the number of distinct species and their relationships at the population and species level [1-6]. We assembled a dataset of 48 resequenced genomes spanning all members of the genus Canis except the black-backed and side-striped jackals, encompassing the global diversity of seven extant canid lineages. This includes eight new genomes, including the first resequenced Ethiopian wolf (Canis simensis), one dhole (Cuon alpinus), two East African hunting dogs (Lycaon pictus), two Eurasian golden jackals (Canis aureus), and two Middle Eastern gray wolves (Canis lupus). The relationships between the Ethiopian wolf, African golden wolf, and golden jackal were resolved. We highlight the role of interspecific hybridization in the evolution of this charismatic group. Specifically, we find gene flow between the ancestors of the dhole and African hunting dog and admixture between the gray wolf, coyote (Canis latrans), golden jackal, and African golden wolf. Additionally, we report gene flow from gray and Ethiopian wolves to the African golden wolf, suggesting that the African golden wolf originated through hybridization between these species. Finally, we hypothesize that coyotes and gray wolves carry genetic material derived from a "ghost" basal canid lineage.
    UI.ADSABS.HARVARD.EDU
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  • https://ui.adsabs.harvard.edu/abs/1992PhoRe..33..137G
    Evolution of proton pumping ATPases: Rooting the tree of life
    Proton pumping ATPases are found in all groups of present day organisms. The F-ATPases of eubacteria, mitochondria and chloroplasts also function as ATP synthases, i.e., they catalyze the final step that transforms the energy available from reduction/oxidation reactions (e.g., in photosynthesis) into ATP, the usual energy currency of modern cells. The primary structure of these ATPases/ATP synthases was found to be much more conserved between different groups of bacteria than other parts of the photosynthetic machinery, e.g., reaction center proteins and redox carrier complexes. These F-ATPases and the vacuolar type ATPase, which is found on many of the endomembranes of eukaryotic cells, were shown to be homologous to each other; i.e., these two groups of ATPases evolved from the same enzyme present in the common ancestor. (The term eubacteria is used here to denote the phylogenetic group containing all bacteria except the archaebacteria.) Sequences obtained for the plasmamembrane ATPase of various archaebacteria revealed that this ATPase is much more similar to the eukaryotic than to the eubacterial counterpart. The eukaryotic cell of higher organisms evolved from a symbiosis between eubacteria (that evolved into mitochondria and chloroplasts) and a host organism. Using the vacuolar type ATPase as a molecular marker for the cytoplasmic component of the eukaryotic cell reveals that this host organism was a close relative of the archaebacteria. A unique feature of the evolution of the ATPases is the presence of a non-catalytic subunit that is paralogous to the catalytic subunit, i.e., the two types of subunits evolved from a common ancestral gene. Since the gene duplication that gave rise to these two types of subunits had already occurred in the last common ancestor of all living organisms, this non-catalytic subunit can be used to root the tree of life by means of an outgroup; that is, the location of the last common ancestor of the major domains of living organisms (archaebacteria, eubacteria and eukaryotes) can be located in the tree of life without assuming constant or equal rates of change in the different branches. A correlation between structure and function of ATPases has been established for present day organisms. Implications resulting from this correlation for biochemical pathways, especially photosynthesis, that were operative in the last common ancestor and preceding life forms are discussed.
    UI.ADSABS.HARVARD.EDU
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  • https://ui.adsabs.harvard.edu/abs/2007PNAS..104.2271S
    Adaptive genic evolution in the Drosophila genomes
    Determining the extent of adaptive evolution at the genomic level is central to our understanding of molecular evolution. A suitable observation for this purpose would consist of polymorphic data on a large and unbiased collection of genes from two closely related species, each having a large and stable population. In this study, we sequenced 419 genes from 24 lines of Drosophila melanogaster and its close relatives. Together with data from Drosophila simulans, these data reveal the following. (i) Approximately 10% of the loci in regions of normal recombination are much less polymorphic at silent sites than expected, hinting at the action of selective sweeps. (ii) The level of polymorphism is negatively correlated with the rate of nonsynonymous divergence across loci. Thus, even under strict neutrality, the ratio of amino acid to silent nucleotide changes (A:S) between Drosophila species is expected to be 25-40% higher than the A:S ratio for polymorphism when data are pooled across the genome. (iii) The observed A/S ratio between species among the 419 loci is 28.9% higher than the (adjusted) neutral expectation. We estimate that nearly 30% of the amino acid substitutions between D. melanogaster and its close relatives were adaptive. (iv) This signature of adaptive evolution is observable only in regions of normal recombination. Hence, the low level of polymorphism observed in regions of reduced recombination may not be driven primarily by positive selection. Finally, we discuss the theories and data pertaining to the interpretation of adaptive evolution in genomic studies.
    UI.ADSABS.HARVARD.EDU
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  • https://ui.adsabs.harvard.edu/abs/1973Natur.246...96O
    Slightly Deleterious Mutant Substitutions in Evolution
    RECENT advances in molecular genetics have had a great deal of influence on evolutionary theory, and in particular, the neutral mutation-random drift hypothesis of molecular evolution1,2 has stimulated much interest. The concept of neutral mutant substitution in the population by random genetic drift can be extended to include random fixation of very slightly deleterious mutations which have more chance of being selected against than of being selected for3,4. If this class of mutant substitution is important, we can predict that the evolution is rapid in small populations or at the time of speciation5. Here I shall organize the observed facts which indicate that this class is in fact important.
    UI.ADSABS.HARVARD.EDU
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  • https://ui.adsabs.harvard.edu/abs/2002PNAS...9916134O
    Near-neutrality in evolution of genes and gene regulation
    The nearly neutral theory contends that the interaction of drift and selection is important and occurs at various levels, including synonymous and nonsynonymous substitutions in protein coding regions and sequence turnover of regulatory elements. Recent progress of the theory is reviewed, and the interaction between drift and selection is suggested to differ at these different levels. Weak selective force on synonymous changes is stable, whereas its consequence on nonsynonymous changes depends on environmental factors. Selection on differentiation of regulatory elements is even more dependent on environmental factors than on amino acid changes. Of particular significance is the role of drift in the evolution of gene regulation that directly participates in morphological evolution. The range of near neutrality depends on the effective size of the population that is influenced by selected linked loci. In addition to the effective population size, molecular chaperones such as heat shock protein 90 have significant effects on the range of near neutrality.
    UI.ADSABS.HARVARD.EDU
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  • ary-algorithm/

    #include <iostream>
    #include <string>
    #include <vector>
    #include <algorithm>
    #include <random>
    #include <chrono>

    using namespace std;

    // random generator function:
    int myrandom (int i) { return std::rand()%i;}


    int main () {

    // seed the random number generator with a constant value:
    srand( unsigned (time(0)) );

    const string target = "Hello World!"; // target string we are trying to match

    const int populationSize = 500; // population size of our genetic algorithm

    vector<string> population; // vector to store our population of strings

    int generation = 0; // current generation number

    // create a random starting population of strings:

    for (int i=0; i<populationSize; i++) {

    string str;

    for (int j=0; j<target.length(); j++) {

    char c = 97 + rand() % 26; // generate a random lowercase character from 'a' to 'z'

    str += c;

    }

    population.push_back(str); // add the generated string to the population vector

    }

    while (true) { // loop until we find the target string

    cout << "Generation: " << generation++ << endl;

    for (int i=0; i<population.size(); i++) { // loop through each member of the population

    cout << "String: " << population[i] << "\t\tFitness: " << fitness(population[i]) << endl;

    if (population[i] == target) { // check if this member is equal to the target string

    cout << "Target Reached!" << endl;
    return 0; // exit program if target is reached

    }
    }

    vector<string> newPopulation;// create a new empty vector for our new generation of strings

    for (int i=0 ; i<population.size(); i++) {// loop through each member of the current population

    string parent1 = selection(population);// select two parents using tournament selection
    string parent2 = selection(population);

    vector<string> children = crossover(parent1, parent2);// perform crossover between parents and generate two children
    mutation(children[0]);// perform mutation on both children mutation(children[1]); newPopulation.push_back(children[0]);// add both children to the new generation's population newPopulation.push_back(children[1]); } population = newPopulation;// replace old generation's population with the new one } return 0;}

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  • Stellar evolution is the process by which a star changes over the course of time. Depending on the mass of the star, its lifetime can range from a few million years for the most massive to trillions of years for the least massive. During its life, a star will pass through several stages, fusing lighter elements into heavier ones in successive nuclear reactions. These reactions release energy, which allows the star to radiate light and heat into space. As it ages, a star will move through different stages, including main sequence, red giant, and white dwarf. In some cases, stars may even end their lives as supernovae or neutron stars.

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  • Stellar evolution is the process by which a star changes over the course of time. Depending on the mass of the star, its lifetime can range from a few million years for the most massive to trillions of years for the least massive, which is considerably longer than the age of the universe. All stars are born from collapsing clouds of gas and dust, often called nebulae or molecular clouds. Over the course of millions of years, these protostars settle down into a state of equilibrium, becoming what is known as a main-sequence star. Nuclear fusion powers a star for most of its life. Initially the energy is generated by the fusion of hydrogen atoms at the core of the main-sequence star, but as the preponderance of hydrogen gets used up, more and heavier elements are created by fusion processes in layers around the core. The outflow of energy from the core causes it to gradually expand and cool over time, thereby transforming it into a red giant. Stars with at least half to three-quarters of the mass of our Sun will expand further into a supergiant phase before running out of fuel and collapsing into an incredibly dense white dwarf. Stars with greater than three solar masses will continue to collapse until they become dense enough to begin thermonuclear fusion in their cores; these are known as supernovas. Finally, stars that are even more massive will be able to sustain nuclear fusion in their cores even after they collapse, forming neutron stars or black holes depending on their mass and rotation rate.

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  • Stellar evolution is the process by which a star changes over the course of time. Depending on the mass of the star, its lifetime can range from a few million years for the most massive to trillions of years for the least massive. During its life, a star will pass through several stages, such as protostar, main-sequence star, red giant and white dwarf. The more massive stars will also go through supernova and neutron star stages. As it ages, a star's temperature and luminosity will change, and it may also undergo pulsations and mass loss.

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  • Stellar evolution is the process by which a star changes over the course of time. Depending on the mass of the star, its lifetime can range from a few million years for the most massive to trillions of years for the least massive. During its life, a star will pass through several stages, such as a protostar, main-sequence star, red giant and white dwarf. During each stage, different nuclear reactions take place in the core of the star, causing it to heat up or cool down and change in luminosity and size. Eventually, all stars will end their lives by either exploding as supernovae or collapsing into black holes.

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  • Stellar evolution is the process by which a star changes over the course of time. Depending on the mass of the star, its lifetime can range from a few million years for the most massive to trillions of years for the least massive. During its life, a star will pass through various stages, such as protostar, main-sequence star, red giant, and white dwarf. The energy produced by stars comes from nuclear fusion reactions in which hydrogen is converted into helium. As a star ages, it will eventually exhaust its supply of hydrogen fuel and move on to other elements in its core. This process leads to changes in stellar structure and luminosity as well as the eventual death of the star.

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  • Stellar evolution is the process by which a star changes over the course of time. Depending on the mass of the star, its lifetime can range from a few million years for the most massive to trillions of years for the least massive. During its life, a star will pass through various stages, such as a protostar, main-sequence star, red giant, and white dwarf. Each stage is characterized by different properties such as luminosity and temperature. As a star ages, it will also undergo nuclear fusion reactions in its core that produce heavier elements from lighter ones. These heavier elements are then released into space when the star dies, enriching the interstellar medium with new material.

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  • Stellar evolution is the process by which a star changes over the course of time. Depending on the mass of the star, its lifetime can range from a few million years for the most massive to trillions of years for the least massive. During its life, a star will pass through several stages, such as a protostar, main-sequence star, red giant, and white dwarf. As it evolves, a star will undergo nuclear fusion in its core and produce energy in the form of radiation. This radiation will cause the star to expand and contract in size as it moves through different stages of its life cycle.

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  • -of-the-web

    The evolution of the web began in 1989 when Tim Berners-Lee proposed the idea of a global hypertext project. This was the first step towards creating the World Wide Web. In 1991, Berners-Lee and his team at CERN released the first web browser, which allowed users to navigate through documents that were linked together via hypertext. This was the beginning of what we know today as the internet.

    In 1993, Marc Andreessen released Mosaic, which was the first graphical web browser and allowed users to view images and videos on websites. This was a major breakthrough in web technology and led to a surge in internet usage.

    The late 1990s saw a number of important developments in web technology. Netscape Navigator became one of the most popular browsers and HTML 4 was released, which introduced new features such as tables and frames. Java applets also became popular during this time, allowing developers to create interactive websites with dynamic content.

    In 2000, Microsoft released Internet Explorer 6, which became one of the most widely used browsers for many years afterwards. The same year also saw the release of XML, which allowed developers to structure data more effectively than HTML.

    The early 2000s saw a number of important developments in web technology including AJAX (Asynchronous JavaScript And XML), which allowed for faster loading times on websites; CSS (Cascading Style Sheets), which allowed developers to separate content from design; and RSS (Really Simple Syndication), which made it easier for users to keep up with their favorite websites.

    The mid-2000s saw an explosion in social media usage with sites such as Myspace and Facebook becoming hugely popular amongst internet users. This period also saw an increase in mobile device usage with smartphones becoming commonplace by 2010. In response to this trend, responsive design techniques were developed that allowed websites to adapt their layout depending on the device they were being viewed on.

    Today, web technology is constantly evolving with new technologies such as HTML5 being developed all the time. Web development is now much more complex than it was when it first began but it has come a long way since 1989 when Tim Berners-Lee proposed his idea for a global hypertext project!

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  • The first known use of the word "evolution" in English was in 1679, when it was used by Thomas Browne in his book Religio Medici. The term had been used earlier by French philosopher and mathematician René Descartes (1596-1650) and German naturalist and physician Georges-Louis Leclerc, Comte de Buffon (1707-1788). In the 19th century, Charles Darwin popularized the concept of evolution through his work On the Origin of Species. Since then, evolutionary theory has been widely accepted as a scientific explanation for the diversity of life on Earth. Evolutionary biology is now a major field of study, with researchers exploring topics such as genetic drift, natural selection, speciation, and adaptation.

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  • Tom Hanks Evolution
    Tom Hanks Evolution 1980-2022 #Shorts.
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  • A new supercomputer simulation animates the evolution of the universe
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