LEADER 00874nam0-22002651i-450- 001 990003865680403321 035 $a000386568 035 $aFED01000386568 035 $a(Aleph)000386568FED01 035 $a000386568 100 $a19960715d2000----km-y0itay50------ba 101 0 $aITA 102 $aIT 200 1 $aFlussi migratori e modelli di sviluppo industriale$eL'esperienza italiana dal dopoguerra agli anni novanta$fdi Marina Murat, Sergio Paba 210 $d2000 225 1 $aMateriali di discussione$fDipartimento di economia politica. Università di Modena$v333 700 1$aMurat,$bMarina$0120092 701 1$aPaba,$bSergio$f<1954- >$0375096 801 0$aIT$bUNINA$gRICA$2UNIMARC 901 $aBK 912 $a990003865680403321 952 $aPaper$fSES 959 $aSES 996 $aFlussi migratori e modelli di sviluppo industriale$9514743 997 $aUNINA LEADER 04770nam 22004693u 450 001 9910453593703321 005 20211005021825.0 010 $a1-119-97286-8 035 $a(CKB)2550000001228494 035 $a(EBL)819229 035 $a(OCoLC)739118492 035 $a(MiAaPQ)EBC819229 035 $a(EXLCZ)992550000001228494 100 $a20160725d2011|||| u|| | 101 0 $aeng 135 $aur|n|---||||| 200 10$aIntroduction to Synchrotron Radiation$b[electronic resource] $eTechniques and Applications 210 $aHoboken $cWiley$d2011 215 $a1 online resource (370 p.) 300 $aDescription based upon print version of record. 311 $a1-119-97287-6 327 $aAn Introduction to Synchrotron Radiation; Contents; Preface; Acknowledgements; 1. Introduction; 1.1 A Potted History of X-rays; 1.2 Synchrotron Sources Over the Last 50 Years; References; 2. The Interaction of X-rays with Matter; 2.1 Introduction; 2.2 The Electromagnetic Spectrum; 2.3 Thomson Scattering; 2.4 Compton Scattering; 2.5 Atomic Scattering Factors; 2.5.1 Scattering From a Cloud of Free Electrons; 2.5.2 Correction Terms for the Atomic Scattering Factor; 2.6 The Refractive Index, Reflection and Absorption; 2.6.1 The Refractive Index; 2.6.2 Refraction and Reflection; 2.6.3 Absorption 327 $a2.7 X-ray Fluorescence and Auger Emission2.7.1 X-ray Fluorescence; 2.7.2 Auger Emission; 2.7.3 Fluorescence or Auger?; 2.8 Concluding Remarks; References; 3. Synchrotron Physics; 3.1 Introduction; 3.2 Overview; 3.3 Radiation From Relativistic Electrons; 3.3.1 Magnetic Deflection Fields; 3.3.2 Radiated Power Loss in Synchrotrons; 3.4 Radio Frequency Power Supply and Bunching; 3.5 Photon Beam Properties; 3.5.1 Flux and Brilliance; 3.5.2 Emittance; 3.5.3 Coherence; 3.5.4 Polarization of Synchrotron Radiation; 3.6 Bending Magnets and Superbends; 3.7 Insertion Devices; 3.7.1 Wigglers 327 $a3.7.2 Worked Example: The SLS Materials Science Beamline Wiggler3.7.3 Undulators; 3.8 Future Sources of Synchrotron Light; 3.8.1 The Energy Recovery Linac; 3.8.2 The Free-Electron Laser; 3.8.3 Tabletop Synchrotrons; 3.9 Concluding Remarks; References; 4. Beamlines; 4.1 Introduction; 4.2 Front End; 4.2.1 Beam-Position Monitors; 4.2.2 Primary Aperture and Front-End Slits; 4.2.3 Low-Energy Filters; 4.3 Primary Optics; 4.3.1 X-ray Mirrors; 4.3.2 Mirror Focal Lengths - The Coddington Equations; 4.3.3 Monochromators; 4.3.4 Focusing Geometry; 4.4 Microfocus and Nanofocus Optics; 4.4.1 Lens Types 327 $a4.5 Beam Intensity Monitors4.6 Detectors; 4.6.1 Photographic Plates; 4.6.2 Scintillator Detectors; 4.6.3 The Point-Spread Function; 4.6.4 Crystal Analysers; 4.6.5 Image Plates and Charge-Coupled Devices; 4.6.6 Pixel and Microstrip Detectors; 4.6.7 Energy-Dispersive Detectors; 4.7 Time-Resolved Experiments; 4.7.1 Avalanche Photodiodes; 4.7.2 Streak Cameras; 4.8 Concluding Remarks; References; 5. Scattering Techniques; 5.1 Introduction; 5.2 Diffraction at Synchrotron Sources; 5.3 Description of Crystals; 5.3.1 Lattices and Bases; 5.3.2 Crystal Planes 327 $a5.3.3 Labelling Crystallographic Planes and Axes5.4 Basic Tenets of X-ray Diffraction; 5.4.1 Introduction; 5.4.2 The Bragg Law and the Reciprocal Lattice; 5.4.3 The Influence of the Basis; 5.4.4 Kinematical and Dynamical Diffraction; 5.5 Diffraction and the Convolution Theorem; 5.5.1 The Convolution Theorem; 5.5.2 Understanding the Structure Factor; 5.6 The Phase Problem and Anomalous Diffraction; 5.6.1 Introduction; 5.6.2 The Patterson Map; 5.6.3 Friedel's Law and Bijvoet Mates; 5.6.4 Anomalous Diffraction; 5.6.5 Direct Methods; 5.7 Types of Crystalline Samples 327 $a5.8 Single Crystal Diffraction 330 $aSince the first use of synchrotron light to investigate the properties of materials half a century ago, it has become increasingly recognized as an invaluable research tool by a broad spectrum of scientists, ranging from physicists and chemists, through molecular biologists and environmental scientists, to geologists and archaeologists. This rising demand for access to synchrotron radiation has also expressed itself in a recent increase in the construction of facilities worldwide to accommodate this diverse and burgeoning user community. 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III N 19$g1$i2002000954060$lle002$o-$pE0.00$q-$rl$s- $t0$u0$v0$w0$x0$y.i10545220$z27-06-02 996 $aJean Cocteau$9222722 997 $aUNISALENTO 998 $ale002$b01-01-00$cm$da $e-$ffre$gfr $h0$i1 LEADER 04742nam 22005535 450 001 9910484234603321 005 20250610110442.0 010 $a3-030-42950-4 024 7 $a10.1007/978-3-030-42950-8 035 $a(CKB)5310000000016735 035 $a(MiAaPQ)EBC6236239 035 $a(DE-He213)978-3-030-42950-8 035 $a(PPN)248595962 035 $a(MiAaPQ)EBC6236095 035 $a(MiAaPQ)EBC29090330 035 $a(EXLCZ)995310000000016735 100 $a20200623d2020 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aNonlinear Conjugate Gradient Methods for Unconstrained Optimization /$fby Neculai Andrei 205 $a1st ed. 2020. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2020. 215 $a1 online resource (515 pages) 225 1 $aSpringer Optimization and Its Applications,$x1931-6828 ;$v158 311 08$a3-030-42949-0 327 $a1. Introduction -- 2. Linear Conjugate Gradient Algorithm -- 3. General Convergence Results for Nonlinear Conjugate Gradient Methods -- 4. Standard Conjugate Gradient Methods -- 5. Acceleration of Conjugate Gradient Algorithms -- 6. Hybrid and Parameterized Conjugate Gradient Methods -- 7. Conjugate Gradient Methods as Modifications of the Standard Schemes -- 8. Conjugate Gradient Methods Memoryless BFGS Preconditioned -- 9. Three-Term Conjugate Gradient Methods -- 10. Other Conjugate Gradient Methods -- 11. Discussion and Conclusions -- References -- Author Index -- Subject Index. 330 $aTwo approaches are known for solving large-scale unconstrained optimization problems?the limited-memory quasi-Newton method (truncated Newton method) and the conjugate gradient method. This is the first book to detail conjugate gradient methods, showing their properties and convergence characteristics as well as their performance in solving large-scale unconstrained optimization problems and applications. Comparisons to the limited-memory and truncated Newton methods are also discussed. Topics studied in detail include: linear conjugate gradient methods, standard conjugate gradient methods, acceleration of conjugate gradient methods, hybrid, modifications of the standard scheme, memoryless BFGS preconditioned, and three-term. Other conjugate gradient methods with clustering the eigenvalues or with the minimization of the condition number of the iteration matrix, are also treated. For each method, the convergence analysis, the computational performances and the comparisons versus other conjugate gradient methods are given. The theory behind the conjugate gradient algorithms presented as a methodology is developed with a clear, rigorous, and friendly exposition; the reader will gain an understanding of their properties and their convergence and will learn to develop and prove the convergence of his/her own methods. Numerous numerical studies are supplied with comparisons and comments on the behavior of conjugate gradient algorithms for solving a collection of 800 unconstrained optimization problems of different structures and complexities with the number of variables in the range [1000,10000]. The book is addressed to all those interested in developing and using new advanced techniques for solving unconstrained optimization complex problems. Mathematical programming researchers, theoreticians and practitioners in operations research, practitioners in engineering and industry researchers, as well as graduate students in mathematics, Ph.D. and master students in mathematical programming, will find plenty of information and practical applications for solving large-scale unconstrained optimization problems and applications by conjugate gradient methods. 410 0$aSpringer Optimization and Its Applications,$x1931-6828 ;$v158 606 $aMathematical optimization 606 $aMathematical models 606 $aOptimization$3https://scigraph.springernature.com/ontologies/product-market-codes/M26008 606 $aMathematical Modeling and Industrial Mathematics$3https://scigraph.springernature.com/ontologies/product-market-codes/M14068 615 0$aMathematical optimization. 615 0$aMathematical models. 615 14$aOptimization. 615 24$aMathematical Modeling and Industrial Mathematics. 676 $a512.5 676 $a512.94 700 $aAndrei$b Neculai$4aut$4http://id.loc.gov/vocabulary/relators/aut$0767620 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910484234603321 996 $aNonlinear Conjugate Gradient Methods for Unconstrained Optimization$92413542 997 $aUNINA