1,488 research outputs found

    Interview with K.A. Hays

    No full text
    K.A. Hays’ most recent book is Anthropocene Lullaby (February 2022, Carnegie Mellon). She is the author of three prior books of poetry: Windthrow (2017), Early Creatures, Native Gods (2012) and Dear Apocalypse (2009). Her poems appear widely in journals and have been selected for two editions of Best American Poetry. Born in Phoenixville, Pennsylvania, she earned an MFA from Brown University. She teaches Creative Writing at Bucknell University in Lewisburg, PA, and directs the Bucknell Seminar for Undergraduate Poets, a 3-week all-expenses paid summer writing retreat and conference for undergraduate poets from any university or college in the United States

    Skin-Friction Measurements on Mathematically Generated Roughness in a Turbulent Channel Flow

    No full text
    Engineering systems are affected by surface roughness, however, predicting frictional drag has proven to be challenging. The present work takes a systematic approach by generating and manufacturing surfaces roughness where surface statistics, such as rms, skewness and power-spectral density can be controlled. The frictional drag on these surfaces is measured in a turbulent channel flow facility

    International Research Roundtable “History of the Kazakh Statehood. On the 80th Anniversary of the Famous Researcher K.A. Pischulina” (December 24, 2014) »

    No full text
    This article contains a brief description of the International research confe­rence. The author gives a brief description of the papers presented at the conference. The following reports were presented at the conference: K.Z. Uskenbay. “The Kazakh Statehood during the Late Middle Ages in the Scientific Biography of K.A. Pishchulina”; A. Daulethan. “Formation of Kazakh Culture in the Era of the Mongol Uluses (13th–16th centuries)”; N. Kenzheahmet. “The Kazakh Kha­nate in the Chinese Sources (15th–16th centuries)”; I.M. Mirgaleev. “Activities of the Centre for Research on the Golden Horde History (Sh.Marjani Institute of History, Academy of Sciences of the Republic of Tatarstan) Aimed at Studying New Sources”; K.U. Torlanbaeva. “Ancient and Medieval Kazakhstan in Migration Processes”; Zh.Zh. Zhenis. “Continuity of Statehood and Traditional Worldview in the Empire of Genghis Khan”; A.P. Ermuhamedova. “The Oghuz Role in World History”; N.A. Atygaev. “Early Stage in the History of Kazakh Khanate in the Works of K.A. Pischulina”

    Редже траєкторії кварк-глюонних мішків

    No full text
    Using an exactly solvable statistical model, we discuss the equation of state of large/heavy and short-living bags of the quark gluon plasma (QGP).We argue that the large width of the QGP bags explains not only the observed deficit in the number of hadronic resonances, but also clarifies the reason why the heavy QGP bags cannot be directly observed even as metastable states in the hadronic phase. Also the Regge trajectories of large and heavy QGP bags are established both in vacuum and in a strongly interacting medium. It is shown that, at high temperatures, the average mass and width of the QGP bags behave in accordance with the upper bound of the Regge trajectory asymptotics (the linear asymptotics), whereas, for temperatures below Tн=2 (Tн is the Hagedorn temperature), they obey the lower bound of the Regge trajectory asymptotics (the square root one). Thus, for T Tн=2, these bags demonstrate the standard Regge behavior consistent with the string models.Використовуючи точний розв’язок статистичної моделi, обговорено рiвняння стану великих/важких i короткоживучих мiшкiв кварк-глюонної плазми (КГП). Наведено аргументи того, що велика ширина мiшкiв КГП не тiльки пояснює дефiцит кiлькостi адронних резонансiв, але й причину того, що важкi мiшки КГП не можуть безпосередньо спостерiгатися навiть як метастабiльнi стани в адроннiй фазi. Також знайдено Редже траєкторiї великих i важких мiшкiв КГП як у вакуумi, так i в сильновзаємодiючому середовищi. Доведено, що за високих температур середня маса i ширина мiшкiв КГП пiдкорюються верхнiй границi асимптотики траєкторiї Редже (лiнiйна асимптотика), тодi як для температур, нижчих за Tн=2 (Tн – температура Хагедорна), вони пiдкорюються нижнiй границi асимптотики траєкторiй Редже (асимптотика кореня квадратного). Таким чином, для T Tн=2 цi мiшки демонструють стандартну Редже поведiнку, яка узгоджується з моделями струн.The research made in this work was supported in part by the Program “Fundamental Properties of Physical Systems under Extreme Conditions” of the Division of of Physics and Astronomy of the National Academy of Science of Ukraine. K.A.B. acknowledges the partial support by the Fundamental Research State Fund of Ukraine, Agreement No F28/335-2009 for the Bilateral project FRSF (Ukraine) – RFBR (Russia)

    Редже траєкторії кварк-глюонних мішків

    No full text
    Using an exactly solvable statistical model, we discuss the equation of state of large/heavy and short-living bags of the quark gluon plasma (QGP).We argue that the large width of the QGP bags explains not only the observed deficit in the number of hadronic resonances, but also clarifies the reason why the heavy QGP bags cannot be directly observed even as metastable states in the hadronic phase. Also the Regge trajectories of large and heavy QGP bags are established both in vacuum and in a strongly interacting medium. It is shown that, at high temperatures, the average mass and width of the QGP bags behave in accordance with the upper bound of the Regge trajectory asymptotics (the linear asymptotics), whereas, for temperatures below Tн=2 (Tн is the Hagedorn temperature), they obey the lower bound of the Regge trajectory asymptotics (the square root one). Thus, for T Tн=2, these bags demonstrate the standard Regge behavior consistent with the string models.Використовуючи точний розв’язок статистичної моделi, обговорено рiвняння стану великих/важких i короткоживучих мiшкiв кварк-глюонної плазми (КГП). Наведено аргументи того, що велика ширина мiшкiв КГП не тiльки пояснює дефiцит кiлькостi адронних резонансiв, але й причину того, що важкi мiшки КГП не можуть безпосередньо спостерiгатися навiть як метастабiльнi стани в адроннiй фазi. Також знайдено Редже траєкторiї великих i важких мiшкiв КГП як у вакуумi, так i в сильновзаємодiючому середовищi. Доведено, що за високих температур середня маса i ширина мiшкiв КГП пiдкорюються верхнiй границi асимптотики траєкторiї Редже (лiнiйна асимптотика), тодi як для температур, нижчих за Tн=2 (Tн – температура Хагедорна), вони пiдкорюються нижнiй границi асимптотики траєкторiй Редже (асимптотика кореня квадратного). Таким чином, для T Tн=2 цi мiшки демонструють стандартну Редже поведiнку, яка узгоджується з моделями струн.The research made in this work was supported in part by the Program “Fundamental Properties of Physical Systems under Extreme Conditions” of the Division of of Physics and Astronomy of the National Academy of Science of Ukraine. K.A.B. acknowledges the partial support by the Fundamental Research State Fund of Ukraine, Agreement No F28/335-2009 for the Bilateral project FRSF (Ukraine) – RFBR (Russia)

    Empirical Research and Modeling of Longitudinal Driving Behavior Under Adverse Conditions

    No full text
    Adverse conditions (emergency situations, adverse weather conditions, freeway incidents) have been shown to have a substantial impact on traffic flow operations. It is however unclear to what extent the conditions impact longitudinal driving behavior and what the determinants of these changes in driving behavior are. Furthermore, it is not yet clear how these changes in driving behavior can best be modeled. To this end we performed three extensive driving simulator experiments intended to investigate the influence of emergency situations, adverse weather conditions and freeway incidents on empirical longitudinal driving behavior as well as driver workload. Furthermore we determined the influence of these conditions on parameter values and model performance of an often used car-following model, i.e., the Intelligent Driver Model (Treiber et al., 2000). We also determined changes in the position of so-called action points in a psycho-spacing model and took some first steps towards the development of a new stochastic car following model based on a Bayesian network modeling approach.Transport & PlanningCivil Engineering and Geoscience
    corecore