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Sapienza University of Rome

Sapienza University of Rome

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586 Projects, page 1 of 118
  • Funder: European Commission Project Code: 340172
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  • Funder: European Commission Project Code: 101059918
    Funder Contribution: 188,590 EUR

    ROMAVANTGARDE aims to reveal a particular phenomenon in the history of music: the effervescence of avant-garde networks in Rome during the 1960s. This phenomenon saw the first steps of influential figures to come: Frederic Rzewski, Alvin Curran, and Ennio Morricone. But it is also of particular interest as it involved a large number of artists from varied national and cultural horizons, connected diverse institutions (schools, bars, religious establishments), and saw the encounter of various genres (art music, jazz, and popular music) to create original repertoires. As a consequence, this is an ideal case to show how art music creation—despite the enduring paradigm of the individual genius—is a collective phenomenon involving human, but also nonhuman actors (institutions, artifacts, ideas). To do so, ROMAVANTGARDE will draw specifically on Actor-Network Theory (ANT), but also on Social Network Analysis (SNA). Through this case study, ROMAVANTGARDE aims to advance knowledge on the history of twentieth-century music and to reveal Rome as a cosmopolitan city actively participating in the construction of the European musical landscape. At the same time, It aims to further research on creativity and to encourage the recent exchanges between network theories and music studies. This project will be undertaken in Sapienza University of Rome, a reputed university for research in the history of music. Sapienza is also the ideal institution to carry out research in the city’s libraries and archives and to carry out the collection of testimonies before witnesses disappear. Professor Emanuele Senici, an internationally renowned music historian with extensive experience in the history of modern and Roman music, will supervise this project. This experience is thus expected to have a profound impact on my training, scientific maturity, and reputation and to place me in good stead to qualify for a tenure-track position in Europe.

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  • Funder: European Commission Project Code: 301363
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  • Funder: European Commission Project Code: 101041885
    Overall Budget: 1,496,290 EURFunder Contribution: 1,496,290 EUR

    Humans are particularly rhythmic animals. Why did the human sense of rhythm develop? Many hypotheses try to explain the origins of our acoustic rhythm capacities, but few are empirically tested, compared, and comparatively investigated. This project searches for the evolutionary roots of human rhythmicity, breaking new ground through three concerted approaches. First, I zoom in on key rhythmic properties: isochrony, an even occurrence of events in time, and meter, a relative accentuation of events. Second, I compare hypotheses on rhythm origins, selecting the most relevant ones to music and speech and testing them against each other. Third, I target rhythm precursors in other species as predicted by these alternative hypotheses. I test four hypotheses, which propose that 1) gait or 2) breathing control, and the ability to 3) learn new sounds or 4) sing in a chorus are evolutionary precursors to human rhythm. I will use different measures including behavior, electrophysiology, gait tracking, breathing, and computational modeling to test whether the four features above predict rhythmic capacities. Comparative animal work is needed to test whether similar evolutionary pressures lead to similar rhythmic traits. I will collect data from humans and four more species. I will test seals, displaying vocal learning, and porpoises; both mammals have developed breathing control. I will also test siamangs, displaying rhythmic locomotion, and indris; both primates naturally sing in choruses, a rare trait in non-human mammals. Finding rhythm in other species will provide a test bench to reconstruct the origins of human rhythm. Resting on my background in bioacoustics and mathematics, the project expands in new challenging directions, such as neurophysiology of marine mammals, automated gait analyses, and biomusicology. In brief, I will show which species have rhythm, and why humans evolved to be such chatty, rhythmic creatures.

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  • Funder: European Commission Project Code: 101040600
    Overall Budget: 1,462,710 EURFunder Contribution: 1,462,710 EUR

    Earthquakes and tectonic fault slip are among the most hazardous and unpredictable natural phenomena. Fluids play a key role in tectonic faulting and recent research suggests that fluids are central in both human induced seismicity and the mode of fault slip, ranging from episodic tremor and slip to slow earthquakes. However, the lack of accessibility to earthquake faults and the complexity of physical processes has limited our ability to develop holistic models for hydromechanical coupling in fault zones. Geophysical observations have the potential for illuminating precursors to failure for the spectrum of tectonic faulting, however we lack key laboratory data to connect these observations with predictive, physics-based models. The ambitious goal of HYQUAKE is to build a physically based framework to understand and predict fluid pressure induced fault slip for a range of fault motion, from aseismic creep to destructive earthquakes. The HYQUAKE approach is interdisciplinary and at the frontier of laboratory earthquake physics, seismology and data/computer science, with the goal of providing unprecedented quantitative constraints on the key physical processes that couple fault friction, the dynamics of strain localization and fluid flow controlling earthquakes and fault slip behavior. Specifically, I will build a research program around unusually well controlled rock deformation experiments tightly connected to numerical models of faulting. HYQUAKE will integrate lab data on fault zone elastic properties, frictional rheology, and hydromechanical parameters using state-of-the-art experimental equipment built within the project with machine learning to forecast labquake. Details of deformation processes, fluid flow, and fault failure will be imaged using novel acoustic techniques. These data will set the stage for the upscaling of laboratory observations to the prediction of natural faulting by coupling physics-based machine learning with 3D hydro-mechanical models.

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