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1. |
Record Nr. |
UNINA9910256159803321 |
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Autore |
Rosa, Franco |
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Titolo |
Il management dell'azienda agraria : guida alle decisioni di pianificazione, controllo, sviluppo / Franco Rosa |
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Descrizione fisica |
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Collana |
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Locazione |
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Collocazione |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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2. |
Record Nr. |
UNISA996201182403316 |
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Autore |
Bybee Keith J. <1965-> |
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Titolo |
Mistaken identity [[electronic resource] ] : the Supreme Court and the politics of minority representation / / Keith J. Bybee |
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Pubbl/distr/stampa |
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Princeton, N.J., : Princeton University Press, c1998 |
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ISBN |
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1-4008-2277-7 |
9786612753589 |
1-282-75358-4 |
1-4008-1116-3 |
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Edizione |
[Core Textbook] |
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Descrizione fisica |
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1 online resource (205 p.) |
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Disciplina |
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Soggetti |
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Minorities - Suffrage - United States |
Proportional representation - United States |
Representative government and representation - United States |
Election districts - United States |
Political questions and judicial power - United States |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Description based upon print version of record. |
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Nota di bibliografia |
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Includes bibliographical references (p. 175-189) and index. |
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Nota di contenuto |
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Front matter -- Contents -- Acknowledgments -- Introduction -- Chapter One. The Voting Rights Act and the Struggle for Meaningful Political Membership -- Chapter Two. The Supreme Court and Representation: Building an Analytical Framework -- Chapter Three. Sound and Fury: Identifying the Role of Political Identity in the Public Debate -- Chapter Four. The Early Cases -- Chapter Five. The Later Cases: The Polarization of Judicial Debate -- Chapter Six. The Possibilities of Legislative Learning -- Appendix Table of Cases -- Reference List -- Index |
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Sommario/riassunto |
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Is it ever legitimate to redraw electoral districts on the basis of race? In its long struggle with this question, the U.S. Supreme Court has treated race-conscious redistricting either as a requirement of political fairness or as an exercise in corrosive racial "as. Cutting through these contradictory positions, Keith Bybee examines the theoretical foundations of the Court's decisions and the ideological controversy those decisions have engendered. He uncovers erroneous assumptions |
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about political identity on both sides of the debate and formulates new terms on which minority representation can be pursued. As Bybee shows, the Court has for the last twenty years encouraged a division between individualist and group concepts of political identity. He demonstrates convincingly that both individualist and group proponents share the misguided notion that political identity is formed prior to and apart from politics itself. According to Bybee, this "mistaken identity" should be abandoned for a more flexible, politically informed understanding of who the "people" really are. Thus, a misdirected debate will be replaced by a more considered discussion in which the people can speak for themselves, even as the Court speaks on their behalf. Engaged in the politics of minority representation, the Court will be able to help citizens articulate and achieve more fruitful forms of political community. |
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3. |
Record Nr. |
UNINA9910427674303321 |
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Titolo |
Thoracic Image Analysis : Second International Workshop, TIA 2020, Held in Conjunction with MICCAI 2020, Lima, Peru, October 8, 2020, Proceedings / / edited by Jens Petersen, Raúl San José Estépar, Alexander Schmidt-Richberg, Sarah Gerard, Bianca Lassen-Schmidt, Colin Jacobs, Reinhard Beichel, Kensaku Mori |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2020 |
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ISBN |
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Edizione |
[1st ed. 2020.] |
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Descrizione fisica |
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1 online resource (X, 166 p. 63 illus., 49 illus. in color.) |
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Collana |
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Image Processing, Computer Vision, Pattern Recognition, and Graphics, , 3004-9954 ; ; 12502 |
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Disciplina |
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Soggetti |
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Computer vision |
Application software |
Computers |
Artificial intelligence |
Computer Vision |
Computer and Information Systems Applications |
Computing Milieux |
Artificial Intelligence |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di contenuto |
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Multi-cavity Heart Segmentation in Non-contrast Non-ECG Gated CT Scans with F-CNN -- 3D Deep Convolutional Neural Network-based Ventilated Lung Segmentation using Multi-nuclear Hyperpolarized Gas MRI -- Lung Cancer Tumor Region Segmentation Using Recurrent 3D-DenseUNet -- 3D Probabilistic Segmentation and Volumetry from 2D Projection Images -- CovidDiagnosis: Deep Diagnosis of Covid-19 Patients using Chest X-rays -- Can We Trust Deep Learning Based Diagnosis? The Impact of Domain Shift in Chest Radiograph Classification -- A Weakly Supervised Deep Learning Framework for COVID-19 CT Detection and Analysis -- Deep Reinforcement Learning for Localization of the Aortic Annulus in Patients with Aortic Dissection -- Functional-Consistent CycleGAN for CT to Iodine Perfusion Map Translation -- MRI to CTA Translation for Pulmonary Artery Evaluation using CycleGANs Trained with Unpaired Data -- Semi-supervised Virtual Regression of Aortic Dissections Using 3D Generative Inpainting -- Registration-Invariant Biomechanical Features for Disease Staging of COPD in SPIROMICS -- Deep Group-wise Variational Diffeomorphic Image Registration. |
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Sommario/riassunto |
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This book constitutes the proceedings of the Second International Workshop on Thoracic Image Analysis, TIA 2020, held in Lima, Peru, in October 2020. Due to COVID-19 pandemic the conference was held virtually. COVID-19 infection has brought a lot of attention to lung imaging and the role of CT imaging in the diagnostic workflow of COVID-19 suspects is an important topic. The 14 full papers presented deal with all aspects of image analysis of thoracic data, including: image acquisition and reconstruction, segmentation, registration, quantification, visualization, validation, population-based modeling, biophysical modeling (computational anatomy), deep learning, image analysis in small animals, outcome-based research and novel infectious disease applications. |
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