2,771 research outputs found

    Changing Spatial Discourses of National Identity in Jordan

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    When Jordan was created as a British mandate in 1921, it was a state but not yet a nation. In order to be seen as legitimate rulers of a ‘natural’ national community, the Hashemite monarchy intertwined discourses of national identity and legitimacy in the changing contexts of Arab-Israeli conflicts, radical pan-Arab nationalism, and political Islam. The Jordanian government expressed these discourses by making claims to holy spaces in Jerusalem and (re)constructing various monuments, museums, plazas, and parks in the capital of Amman. However, competing visions of the Jordanian nation also emerged, ranging from nationalist movements that were exclusively Transjordanian to those that identified as Arab nationalist and opposed the monarchy. The struggle to create a unified Jordanian national identity has expressed itself in public spaces as different political and social groups articulated their own visions of what the Jordanian nation should be

    Void Dynamics

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    Cosmic voids are becoming key players in testing the physics of our Universe. Here we concentrate on the abundances and the dynamics of voids as these are among the best candidates to provide information on cosmological parameters. Cai, Padilla \& Li (2014) use the abundance of voids to tell apart Hu \& Sawicki f(R)f(R) models from General Relativity. An interesting result is that even though, as expected, voids in the dark matter field are emptier in f(R)f(R) gravity due to the fifth force expelling away from the void centres, this result is reversed when haloes are used to find voids. The abundance of voids in this case becomes even lower in f(R)f(R) compared to GR for large voids. Still, the differences are significant and this provides a way to tell apart these models. The velocity field differences between f(R)f(R) and GR, on the other hand, are the same for halo voids and for dark matter voids. Paz et al. (2013), concentrate on the velocity profiles around voids. First they show the necessity of four parameters to describe the density profiles around voids given two distinct void populations, voids-in-voids and voids-in-clouds. This profile is used to predict peculiar velocities around voids, and the combination of the latter with void density profiles allows the construction of model void-galaxy cross-correlation functions with redshift space distortions. When these models are tuned to fit the measured correlation functions for voids and galaxies in the Sloan Digital Sky Survey, small voids are found to be of the void-in-cloud type, whereas larger ones are consistent with being void-in-void. This is a novel result that is obtained directly from redshift space data around voids. These profiles can be used to remove systematics on void-galaxy Alcock-Pacinsky tests coming from redshift-space distortions.Comment: 8 pages, 4 figures, to appear in the proceedings of IAU308 Symposium "The Zeldovich Universe

    Methods of Nature: Landscapes from the Gettysburg College Collection

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    Methods of Nature: Landscapes from the Gettysburg College Collection is the third annual exhibition curated by students enrolled in the Art History Methods course. The exhibition is an exciting academic endeavor and incredible opportunity for engaged learning, research, and curatorial experience. The five student curators are Molly Chason ’17, Leah Falk ’18, Shannon Gross ’17, Bailey Harper ’19 and Laura Waters ’19. The selection of artworks in this exhibition includes the depiction of landscape in the nineteenth- and twentieth-century French, American and East Asian cultural traditions in various art forms from traditional media of paintings and prints to utilitarian artifacts of porcelain and a paper folding fan. Landscape paintings in this exhibition are inspired by nature, specific locales and literature. Each object carries a distinctive characteristic, a mood, and an ambience. Collectively, they present a multifaceted view of the landscape in the heart and mind of the artists and intended viewers. [excerpt]https://cupola.gettysburg.edu/artcatalogs/1020/thumbnail.jp

    Extracting respiratory signals from thoracic cone beam CT projections

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    Patient respiratory signal associated with the cone beam CT (CBCT) projections is important for lung cancer radiotherapy. In contrast to monitoring an external surrogate of respiration, such signal can be extracted directly from the CBCT projections. In this paper, we propose a novel local principle component analysis (LPCA) method to extract the respiratory signal by distinguishing the respiration motion-induced content change from the gantry rotation-induced content change in the CBCT projections. The LPCA method is evaluated by comparing with three state-of-the-art projection-based methods, namely, the Amsterdam Shroud (AS) method, the intensity analysis (IA) method, and the Fourier-transform based phase analysis (FT-p) method. The clinical CBCT projection data of eight patients, acquired under various clinical scenarios, were used to investigate the performance of each method. We found that the proposed LPCA method has demonstrated the best overall performance for cases tested and thus is a promising technique for extracting respiratory signal. We also identified the applicability of each existing method.Comment: 21 pages, 11 figures, submitted to Phys. Med. Bio

    A Novel Carrier Loop Based on Adaptive LM-QN Method in GNSS Receivers

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    A well-designed carrier tracking loop in a receiver of the Global Navigation Satellite System (GNSS) is the premise of accurate positioning and navigation in an aircraft-based surveying and mapping system. To deal with the problems of Doppler estimation in high-dynamic maneuvers, the interest on maximum-likelihood estimation (MLE) is increasing among the academic community. Levenberg-Marquardt (LM) method is usually regarded as an effective and promising approach to obtain the solution of MLE, but the computation of Hessian matrix loads a great burden on the algorithm. Besides, a poor performance on convergency in final iterations is the common failing of LM implementations. To solve these problems, an LM method based on Gauss-Newton and a Quasi-Newton (QN) method based on Hessian approximation are derived, making the computation cost of Hessian decline from O(N) to O(1). Then, on the basis of these two methods, a closed carrier loop with adaptive LM-QN algorithm is further proposed which can switch between LM and QN adaptively according to a damping parameter. Besides, an ideal LM with super-linear convergence (SLM) is constructed and proved as a reference of the convergence analysis. Finally, through the analyses and experiments using aircraft data, the improvements on computation cost and convergence are verified. Compared with scalar tracking and vector tracking, results indicate a magnitude increase in the precision of LM-QN loop, even though more computation counts are needed by LM-QN.Peer reviewe
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