1,453 research outputs found

    Tájökológiai Lapok 21.

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    Glioblastoma cell fate is differentially regulated by the microenvironments of the tumor bulk and infiltrative margin

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    Glioblastoma (GBM) recurrence originates from invasive margin cells that escape surgical debulking, but to what extent these cells resemble their bulk counterparts remains unclear. Here, we generated three immunocompetent somatic GBM mouse models, driven by subtype-associated mutations, to compare matched bulk and margin cells. We find that, regardless of mutations, tumors converge on common sets of neural-like cellular states. However, bulk and margin have distinct biology. Injury-like programs associated with immune infiltration dominate in the bulk, leading to the generation of lowly proliferative injured neural progenitor-like cells (iNPCs). iNPCs account for a significant proportion of dormant GBM cells and are induced by interferon signaling within T cell niches. In contrast, developmental-like trajectories are favored within the immune-cold margin microenvironment resulting in differentiation toward invasive astrocyte-like cells. These findings suggest that the regional tumor microenvironment dominantly controls GBM cell fate and biological vulnerabilities identified in the bulk may not extend to the margin residuum

    Synthetic Aperture Radar (SAR) Meets Deep Learning

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    This reprint focuses on the application of the combination of synthetic aperture radars and depth learning technology. It aims to further promote the development of SAR image intelligent interpretation technology. A synthetic aperture radar (SAR) is an important active microwave imaging sensor, whose all-day and all-weather working capacity give it an important place in the remote sensing community. Since the United States launched the first SAR satellite, SAR has received much attention in the remote sensing community, e.g., in geological exploration, topographic mapping, disaster forecast, and traffic monitoring. It is valuable and meaningful, therefore, to study SAR-based remote sensing applications. In recent years, deep learning represented by convolution neural networks has promoted significant progress in the computer vision community, e.g., in face recognition, the driverless field and Internet of things (IoT). Deep learning can enable computational models with multiple processing layers to learn data representations with multiple-level abstractions. This can greatly improve the performance of various applications. This reprint provides a platform for researchers to handle the above significant challenges and present their innovative and cutting-edge research results when applying deep learning to SAR in various manuscript types, e.g., articles, letters, reviews and technical reports

    Set-based state estimation and fault diagnosis using constrained zonotopes and applications

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    This doctoral thesis develops new methods for set-based state estimation and active fault diagnosis (AFD) of (i) nonlinear discrete-time systems, (ii) discrete-time nonlinear systems whose trajectories satisfy nonlinear equality constraints (called invariants), (iii) linear descriptor systems, and (iv) joint state and parameter estimation of nonlinear descriptor systems. Set-based estimation aims to compute tight enclosures of the possible system states in each time step subject to unknown-but-bounded uncertainties. To address this issue, the present doctoral thesis proposes new methods for efficiently propagating constrained zonotopes (CZs) through nonlinear mappings. Besides, this thesis improves the standard prediction-update framework for systems with invariants using new algorithms for refining CZs based on nonlinear constraints. In addition, this thesis introduces a new approach for set-based AFD of a class of nonlinear discrete-time systems. An affine parametrization of the reachable sets is obtained for the design of an optimal input for set-based AFD. In addition, this thesis presents new methods based on CZs for set-valued state estimation and AFD of linear descriptor systems. Linear static constraints on the state variables can be directly incorporated into CZs. Moreover, this thesis proposes a new representation for unbounded sets based on zonotopes, which allows to develop methods for state estimation and AFD also of unstable linear descriptor systems, without the knowledge of an enclosure of all the trajectories of the system. This thesis also develops a new method for set-based joint state and parameter estimation of nonlinear descriptor systems using CZs in a unified framework. Lastly, this manuscript applies the proposed set-based state estimation and AFD methods using CZs to unmanned aerial vehicles, water distribution networks, and a lithium-ion cell.Comment: My PhD Thesis from Federal University of Minas Gerais, Brazil. Most of the research work has already been published in DOIs 10.1109/CDC.2018.8618678, 10.23919/ECC.2018.8550353, 10.1016/j.automatica.2019.108614, 10.1016/j.ifacol.2020.12.2484, 10.1016/j.ifacol.2021.08.308, 10.1016/j.automatica.2021.109638, 10.1109/TCST.2021.3130534, 10.1016/j.automatica.2022.11042

    Musiktheorie als interdisziplinäres Fach: 8. Kongress der Gesellschaft für Musiktheorie Graz 2008

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    Im Oktober 2008 fand an der Universität für Musik und darstellende Kunst Graz (KUG) der 8. Kongress der Gesellschaft für Musiktheorie (GMTH) zum Thema »Musiktheorie als interdisziplinäres Fach« statt. Die hier vorgelegten gesammelten Beiträge akzentuieren Musiktheorie als multiperspektivische wissenschaftliche Disziplin in den Spannungsfeldern Theorie/Praxis, Kunst/Wissenschaft und Historik/Systematik. Die sechs Kapitel ergründen dabei die Grenzbereiche zur Musikgeschichte, Musikästhetik, zur Praxis musikalischer Interpretation, zur kompositorischen Praxis im 20. und 21. Jahrhundert, zur Ethnomusikologie sowie zur Systematischen Musikwissenschaft. Insgesamt 45 Aufsätze, davon 28 in deutscher, 17 in englischer Sprache, sowie die Dokumentation einer Podiumsdiskussion zeichnen in ihrer Gesamtheit einen höchst lebendigen und gegenwartsbezogenen Diskurs, der eine einzigartige Standortbestimmung des Fachs Musiktheorie bietet.The 8th congress of the Gesellschaft für Musiktheorie (GMTH) took place in October 2008 at the University for Music and Dramatic Arts Graz (KUG) on the topic »Music Theory and Interdisciplinarity«. The collected contributions characterize music theory as a multi-faceted scholarly discipline at the intersection of theory/practice, art/science and history/system. The six chapters explore commonalties with music history, music aesthetics, musical performance, compositional practice in twentieth- and twenty-first-century music, ethnomusicology and systematic musicology. A total of 45 essays (28 in German, 17 in English) and the documentation of a panel discussion form a vital discourse informed by contemporaneous issues of research in a broad number of fields, providing a unique overview of music theory today. A comprehensive English summary appears at the beginning of all contributions

    Towards a Peaceful Development of Cyberspace - Challenges and Technical Measures for the De-escalation of State-led Cyberconflicts and Arms Control of Cyberweapons

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    Cyberspace, already a few decades old, has become a matter of course for most of us, part of our everyday life. At the same time, this space and the global infrastructure behind it are essential for our civilizations, the economy and administration, and thus an essential expression and lifeline of a globalized world. However, these developments also create vulnerabilities and thus, cyberspace is increasingly developing into an intelligence and military operational area – for the defense and security of states but also as a component of offensive military planning, visible in the creation of military cyber-departments and the integration of cyberspace into states' security and defense strategies. In order to contain and regulate the conflict and escalation potential of technology used by military forces, over the last decades, a complex tool set of transparency, de-escalation and arms control measures has been developed and proof-tested. Unfortunately, many of these established measures do not work for cyberspace due to its specific technical characteristics. Even more, the concept of what constitutes a weapon – an essential requirement for regulation – starts to blur for this domain. Against this background, this thesis aims to answer how measures for the de-escalation of state-led conflicts in cyberspace and arms control of cyberweapons can be developed. In order to answer this question, the dissertation takes a specifically technical perspective on these problems and the underlying political challenges of state behavior and international humanitarian law in cyberspace to identify starting points for technical measures of transparency, arms control and verification. Based on this approach of adopting already existing technical measures from other fields of computer science, the thesis will provide proof of concepts approaches for some mentioned challenges like a classification system for cyberweapons that is based on technical measurable features, an approach for the mutual reduction of vulnerability stockpiles and an approach to plausibly assure the non-involvement in a cyberconflict as a measure for de-escalation. All these initial approaches and the questions of how and by which measures arms control and conflict reduction can work for cyberspace are still quite new and subject to not too many debates. Indeed, the approach of deliberately self-restricting the capabilities of technology in order to serve a bigger goal, like the reduction of its destructive usage, is yet not very common for the engineering thinking of computer science. Therefore, this dissertation also aims to provide some impulses regarding the responsibility and creative options of computer science with a view to the peaceful development and use of cyberspace
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