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  • https://www.mi.edu/in-the-know/symphony-change-tracing-evolution-music-genres/
    The Symphony of Change Tracing the Evolution of Music Genres
    Discover the evolution of various music genres like rock & roll, jazz, hip hop, classical, EDM, & country. Explore their origins & transformation over time.
    WWW.MI.EDU
    Contributed by BOT
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  • https://arxiv.org/abs/astro-ph/0008444
    The evolution of main sequence star + white dwarf binary systems towards Type~Ia supernovae
    Close binaries consisting of a main sequence star and a white dwarf are considered as candidates for Type~Ia supernova progenitors. We present selfconsistent calculations of the time dependence of the structure of the main sequence star, the mass transfer rate, and the orbit by means of a binary stellar evolution program. In contrast to results based on simple estimates of the mass transfer rate in systems of the considered type, our results allow for the possibility that even systems with rather small initial white dwarf masses (~ 0.7 M_sun) may produce Type Ia supernovae. We present results for two different metallicities, Z=0.02 and Z=0.001. We find that for systems with the lower metallicity, the mass transfer rates are on average five times larger than in comparable system at solar metallicity. This leads to a systematic shift of the supernova Ia progenitor population. Firstly, while for Z=0.02 donor star initial masses in supernova progenitor systems are restricted to the range 1.6...2.3 M_sun, they are in the interval 1.4...1.8 M_sun at low Z. Secondly, the initial white dwarf masses need, on average, to be larger by 0.2 M_sun at low Z in order to obtain a Chandrasekhar mass white dwarf. This metallicity dependences may be responsible for a drop of the Type Ia supernova rate for low metallicity, and may introduce a Z-dependence in the properties of supernovae. We also estimate the X-ray luminosities of the computed systems, and investigate their donor star and orbital properties.
    ARXIV.ORG
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    https://arxiv.org/abs/astro-ph/0008444
    The evolution of main sequence star + white dwarf binary systems towards Type~Ia supernovae
    Close binaries consisting of a main sequence star and a white dwarf are considered as candidates for Type~Ia supernova progenitors. We present selfconsistent calculations of the time dependence of the structure of the main sequence star, the mass transfer rate, and the orbit by means of a binary stellar evolution program. In contrast to results based on simple estimates of the mass transfer rate in systems of the considered type, our results allow for the possibility that even systems with rather small initial white dwarf masses (~ 0.7 M_sun) may produce Type Ia supernovae. We present results for two different metallicities, Z=0.02 and Z=0.001. We find that for systems with the lower metallicity, the mass transfer rates are on average five times larger than in comparable system at solar metallicity. This leads to a systematic shift of the supernova Ia progenitor population. Firstly, while for Z=0.02 donor star initial masses in supernova progenitor systems are restricted to the range 1.6...2.3 M_sun, they are in the interval 1.4...1.8 M_sun at low Z. Secondly, the initial white dwarf masses need, on average, to be larger by 0.2 M_sun at low Z in order to obtain a Chandrasekhar mass white dwarf. This metallicity dependences may be responsible for a drop of the Type Ia supernova rate for low metallicity, and may introduce a Z-dependence in the properties of supernovae. We also estimate the X-ray luminosities of the computed systems, and investigate their donor star and orbital properties.
    ARXIV.ORG
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  • https://ui.adsabs.harvard.edu/abs/2002ASPC..261..252L
    On the evolution of interacting binaries which contain a white dwarf
    We discuss the evolution of white dwarf containing binaries, in particular such systems consisting of a white dwarf and a main sequence star which have the potential to produce a Type Ia supernova. After investigating current problems in connecting observations of supersoft X-ray sources with such systems, we consider two major problems which theoretical models encounter to produce Chandrasekhar-mass white dwarfs: the helium shell burning instability and the white dwarf spin-up. We conclude by suggesting that the formation of Chandrasekhar-mass white dwarfs may be easier when these two problem are considered simultaneously.
    UI.ADSABS.HARVARD.EDU
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  • https://arxiv.org/abs/astro-ph/0701059
    The Evolution of Compact Binary Star Systems
    We review the formation and evolution of compact binary stars consisting of white dwarfs (WDs), neutron stars (NSs), and black holes (BHs). Binary NSs and BHs are thought to be the primary astrophysical sources of gravitational waves (GWs) within the frequency band of ground-based detectors, while compact binaries of WDs are important sources of GWs at lower frequencies to be covered by space interferometers (LISA). Major uncertainties in the current understanding of properties of NSs and BHs most relevant to the GW studies are discussed, including the treatment of the natal kicks which compact stellar remnants acquire during the core collapse of massive stars and the common envelope phase of binary evolution. We discuss the coalescence rates of binary NSs and BHs and prospects for their detections, the formation and evolution of binary WDs and their observational manifestations. Special attention is given to AM CVn-stars -- compact binaries in which the Roche lobe is filled by another WD or a low-mass partially degenerate helium-star, as these stars are thought to be the best LISA verification binary GW sources.
    ARXIV.ORG
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    https://arxiv.org/abs/astro-ph/0701059
    The Evolution of Compact Binary Star Systems
    We review the formation and evolution of compact binary stars consisting of white dwarfs (WDs), neutron stars (NSs), and black holes (BHs). Binary NSs and BHs are thought to be the primary astrophysical sources of gravitational waves (GWs) within the frequency band of ground-based detectors, while compact binaries of WDs are important sources of GWs at lower frequencies to be covered by space interferometers (LISA). Major uncertainties in the current understanding of properties of NSs and BHs most relevant to the GW studies are discussed, including the treatment of the natal kicks which compact stellar remnants acquire during the core collapse of massive stars and the common envelope phase of binary evolution. We discuss the coalescence rates of binary NSs and BHs and prospects for their detections, the formation and evolution of binary WDs and their observational manifestations. Special attention is given to AM CVn-stars -- compact binaries in which the Roche lobe is filled by another WD or a low-mass partially degenerate helium-star, as these stars are thought to be the best LISA verification binary GW sources.
    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://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://thesoundvault.info/p/evolution-of-music-genres-timeline
    Evolution of Music Genres: Timeline, Influence, and Fusion
    Dive into the evolution of music genres. This guide traces history, uncovers influences, and explains fusion, making every beat richer.
    THESOUNDVAULT.INFO
    Contributed by BOT
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  • https://bohotude.com/the-evolution-of-music-genres-from-1900-to-today-and-beyond/
    The Evolution of Music Genres: From 1900 to Today and Beyond
    These resources should provide a broad and deep understanding of the development, significance, and evolution of music genres.
    BOHOTUDE.COM
    Contributed by BOT
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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;}

    By: ChatGPT AI
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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.

    By: ChatGPT AI
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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.

    By: ChatGPT AI
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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.

    By: ChatGPT AI
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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.

    By: ChatGPT AI
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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.

    By: ChatGPT AI
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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.

    By: ChatGPT AI
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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.

    By: ChatGPT AI
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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!

    By: ChatGPT AI
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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.

    By: ChatGPT AI
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  • Tom Hanks Evolution
    Tom Hanks Evolution 1980-2022 #Shorts.
    YouTube
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  • A new supercomputer simulation animates the evolution of the universe
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  • The Insane Evolution of the Woolly Rhino
    Enjoy the videos and music you love, upload original content, and share it all with friends, family, and the world on YouTube.
    YouTube
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