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1. |
Record Nr. |
UNICASPUV0927722 |
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Autore |
Mangione, Flavio |
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Titolo |
Le case del fascio in Italia e nelle terre d'Oltremare / Flavio Mangione |
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Pubbl/distr/stampa |
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Roma, : Ministero per i beni e le attività culturali, Direzione generale per gli archivi, 2003 |
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ISBN |
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Descrizione fisica |
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XXII, 513 p. : ill. ; 31 cm. |
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Collana |
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Pubblicazioni degli archivi di Stato |
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Disciplina |
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Soggetti |
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Case del fascio - Architettura |
Case del fascio - Storia |
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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. |
UNINA9910563039503321 |
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Autore |
Schultze Brigitte |
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Titolo |
Der Dialog in F. M. Dostoevskijs "Idiot" / Brigitte Schultze |
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Pubbl/distr/stampa |
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Frankfurt a.M, : PH02, 1974 |
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Edizione |
[1st, New ed.] |
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Descrizione fisica |
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1 online resource (314 p.) : , EPDF |
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Collana |
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Slavistische Beiträge ; 76 |
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Soggetti |
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Literature & literary studies |
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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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Peter Lang GmbH, Internationaler Verlag der Wissenschaften |
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Nota di contenuto |
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Einleitung - Der Roman "Idiot" als Ganzes - Das Sprechverhalten der Romanfiguren - Das Miteinandersprechen in der Romanszene - Der Dialog als zentrales, strukturtragendes Element in "Idiot" |
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Sommario/riassunto |
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In den Romanen von F. M. Dostoevskij nehmen Gesprächsdarstellungen einen auffallend breiten Raum ein. So ist es verständlich, daß in der Dostoevskij-Literatur immer wieder auf das Gewicht und die Bedeutung des interpersonalen Dialogs hingewiesen wird. Eine gründliche und umfassende Untersuchung des interpersonalen Dialogs, der gerade in den fünf großen Romanen Dostoevskijs ein dominantes Merkmal der Darbietungsweise ist, liegt allerdings noch nicht vor. Aufgrund dieser Forschungslage empfiehlt es sich, die Strukturformen und Funktionsmöglichkeiten des interpersonalen Dialogs zunächst nur in einem der großen Prosawerke Dostoevskijs zu untersuchen. Für ein derartiges Vorhaben erscheint "Idiot" besonders geeignet. |
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3. |
Record Nr. |
UNINA9910734821703321 |
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Autore |
Jackson Robert C |
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Titolo |
Evolutionary Dynamics of Malignancy : The Genetic and Environmental Causes of Cancer / / by Robert C. Jackson |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2023 |
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ISBN |
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Edizione |
[1st ed. 2023.] |
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Descrizione fisica |
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1 online resource (271 pages) |
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Disciplina |
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Soggetti |
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Cancer |
Cancer - Animal models |
Cancer - Treatment |
Cancer - Genetic aspects |
Cancer Biology |
Cancer Models |
Cancer Therapy |
Cancer Genetics and Genomics |
Cancer Microenvironment |
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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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Nota di contenuto |
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Chapter 1: Cancer as a Disease of Cell Proliferation -- Chapter 2: Genetic and Chromosomal Instability -- Chapter 3: Cancer as a Disease of Defective Cell Cycle Checkpoint Function -- Chapter 4: The DNA Damage Checkpoint -- Chapter 5: Dynamics of the Spindle Assembly Checkpoint -- Chapter 6: Cancer as a Disease of Complexity: The Dynamics of Drug Resistance -- Chapter 7: Chronic Myeloid Leukaemia: a One-Hit Malignancy -- Chapter 8: Chronic Myelomonocytic Leukaemia: a Three-Hit Malignancy -- Chapter 9: The Cancer Stem Cell and Tumour Progression -- Chapter 10: Evading the antitumour immune response -- Chapter 11: Implications of Evolutionary Dynamics for Cancer Treatment and Prevention -- Chapter 12: In science, all conclusions are provisional. |
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Sommario/riassunto |
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Advances in cancer genomics are transforming our understanding of cancer, and have profound implications for its prevention, diagnosis, and treatment. Evolutionary dynamics suggests that as few as two mutations can cause transformation of normal cells into cancer stem cells. A process of Darwinian selection, involving a further three or more mutations, taking place over a period of years, can then result in progression to a life-threatening tumour. In many cases the immune response can recognise and eliminate the mutant cells, but most advanced tumours have mutations that activate immune checkpoints and enable the tumour to hide from the immune system. For the most hard-to-treat tumours, future progress will require molecular diagnostics to detect cancer-causing mutations in healthy subjects, and new drugs or vaccines that prevent the progression process. Chapters of this book deal with the signalling pathways that control cell division, and changes in these pathways in cancer cells.Three cell cycle checkpoints that are often mutated in cancer are analysed in detail. A discussion of chronic myeloid leukaemia illustrates the role of reactive oxygen species in driving progression from a chronic to an acute condition. A single drug that suppresses reactive oxygen can prevent disease progression and turn an otherwise deadly disease into a condition that can be managed to enable many years of normal life. Another chapter discusses chronic myelomonocytic leukaemia, a disease that involves both genetic and epigenetic change. Tumour progression is discussed as a multi-stage process in which cancer stem cells evolve into genetically unstable, invasive, metastatic, drug-resistant growths. Each of these stages can act as targets for drugs or immunomodulators, but the future of cancer treatment lies in understanding tumour dynamics, and arresting malignancy at the earliest possible stage. Evolutionary dynamics is a primarily mathematical technique, but the target readership will be tumour biologists, clinicians, and drug developers. Computational detail is provided in an online supplement, but the main text emphasises the implications of the dynamics for an understanding of tumour biology and does not require mathematical expertise. |
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4. |
Record Nr. |
UNINA9910920445903321 |
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Autore |
Dornaika Fadi |
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Titolo |
Advances in Data Clustering : Theory and Applications / / edited by Fadi Dornaika, Denis Hamad, Joseph Constantin, Vinh Truong Hoang |
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Pubbl/distr/stampa |
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Singapore : , : Springer Nature Singapore : , : Imprint : Springer, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (225 pages) |
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Altri autori (Persone) |
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HamadDenis |
ConstantinJoseph |
HoangVinh Truong |
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Disciplina |
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Soggetti |
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Data mining |
Artificial intelligence - Data processing |
Information modeling |
Computer vision |
Data Mining and Knowledge Discovery |
Data Science |
Information Model |
Computer Vision |
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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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Nota di contenuto |
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Chapter 1 Classification of Gougerot-Sjögren syndrome Based on Artificial Intelligence -- Chapter 2 Deep learning Classification of Venous Thromboembolism based on Ultrasound imaging -- Chapter 3 Synchronization-Driven Community Detection: Dynamic Frequency Tuning Approach -- Chapter 4 Automatic Evolutionary Clustering for Human Activity Discovery -- Chapter 5 Identification of Correlated factors for Absenteeism of employees using Clustering techniques -- Chapter 6 Multi-view Data Clustering through Consensus Graph and Data Representation Learning -- Chapter 7 Uber’s Contribution to Faster Deep Learning: A Case Study in Distributed Model Training -- Chapter 8 Auto-Weighted Multi-View Clustering with Unified Binary Representation and Deep Initialization -- Chapter 9 Clustering with |
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Adaptive Unsupervised Graph Convolution Network -- Chapter 10 Graph-based Semi-supervised Learning for Multi-view Data Analysis -- Chapter 11 Advancements in Fuzzy Clustering Algorithms for Im-age Processing: A Comprehensive Review and Future Directions -- Chapter 12 Multiview Latent representation learning with feature diversity for clustering. |
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Sommario/riassunto |
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Clustering, a foundational technique in data analytics, finds diverse applications across scientific, technical, and business domains. Within the theme of “Data Clustering,” this book assumes substantial importance due to its indispensable clustering role in various contexts. As the era of online media facilitates the rapid generation of large datasets, clustering emerges as a pivotal player in data mining and machine learning. At its core, clustering seeks to unveil heterogeneous groups within unlabeled data, representing a crucial unsupervised task in machine learning. The objective is to automatically assign labels to each unlabeled datum with minimal human intervention. Analyzing this data allows for categorization and drawing conclusions applicable across diverse application domains. The challenge with unlabeled data lies in defining a quantifiable goal to guide the model-building process, constituting the central theme of clustering. This book presents concepts and different methodologies of data clustering. For example, deep clustering of images, semi-supervised deep clustering, deep multi-view clustering, etc. This book can be used as a reference for researchers and postgraduate students in related research background. |
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