ALBERT

Note: Druckausg. ---〉 Mathematical Geosciences

Note: Erscheinungsjahr in Vorlageform:2009

Note: Internetausg. ---〉 Global change biology / Bioenergy

Note: Zugl.: Regensburg, Univ., Diss., 2007

Note: Erscheinungsjahr in Vorlageform:2009

Note: Erscheinungsjahr in Vorlageform:2009

Note: Auch als Internetausg.

Note: Zugl.: Berlin, Freie Univ., Diss., 2008

Note: Contents: PART I GEOLOGICAL AND PALEOECOLOGICAL EVENTS OF THE LATE PLEISTOCENE AND HOLOCENE IN NORTHERN EURASIA. - 1 Geological and Paleoecological Events of the Late Pleistocene along Eurasian Coastal Areas of the Arctic Ocean. - General Upper Pleistocene Stratigraphie Scheme for Northern Eurasia. - Duration of the Mikulino Interglaciation. - Correlation of the Natural Events Correlative with MIS 5d-5a in Northern West Europe and Northwestern Russia. - 2 Late Pleistocene Geologic-Paleoecological Events in the North of European Russia. - Relationship between Land and Sea Areas during the Mikulino Interglacial in Northern Eurasia. - Genetic Types of Continental Sediments. - Marine Sediments of the Boreal Transgression in the North of European Russia. - 3 Main Geologic-Paieoecoioglcal Events of the Late Pleistocene in the North of Western Siberia. - 4 Geologic-Paleoecological Events of the late Pleistocene in the Northern-Siberian Lowland and Taimyr Peninsula. - 5 The Late Glacial Time and Holocene of Northern Eurasia. - 6 Outlines of the Late Pleistocene and Holocene History of the East Arctic Seas. - 7 The Deglaciation Time and Holocene of Northern Eurasia. - PART II MARINE SEDIMENTATION IN THE ARCTIC OCEAN AND SUBARCTIC SEAS. - 8 The Seas of West Subarctic Region. - Geologic and Oceanographic Setting. - History of Sedimentation. - History of Sedimentation Rates. - History of Sedimentation on the Vøring Plateau During the Last 25 ka. - History of Sedimentation at the Continental Margin of Eastern and South-Eastern Greenland During the Last 130 ka. - 9 The Arctic Ocean. - Recent Environment. - Morphostructure, Oceanographic and Sea-Ice Setting, Recent Sediments and Their Mineral Composition. - Facies Variations of Holocene Sediments on the Yermak Plateau (According to Study Data of 〉 63 mkm Fraction). - History of Sedimentation. - History of Sedimentation Rates During the Last 130 ka. - History of Sedimentation on the Yermak Plateau During the Last 190 ka. - Organic-Geochemical Sediment Studies of the Eastern Part of the Central Arctic. - 10 The Western Arctic Seas. - Recent Sedimentation Environment. - The Barents Sea. - The Kara Sea. - Surface Sediments of the Pechora Sea. - Surface Sediments of St. Anna Trough. - Facies Zonality of Surface Sediments in the Eastern Kara Sea. - History of Sedimentation. - Late- and Post-Glacial History of Sedimentation in the Eastern Part of the Barents Sea. - Holocene Sedimentation History in the Southern Novaya Zemlya Trough. - History of Sedimentation in the Pechora Sea During the Late Pleistocene and Holocene. - Light Fraction Mineralogy of the Upper Quaternary Sediments from the Saint Anna Trough and Its Paleoceanographic Interpretation. - Holocene History of Yenisei River Discharge. - Holocene History of Ob River Discharge. - 11 Eastern Arctic Seas. - Recent Sedimentation Environment. - The Laptev Sea. - The East Siberian Sea. - The Chukchi Sea. - History of Sedimentation. - History of Sedimentation in the Laptev Sea During the Late Weichselian to Holocene by Geophysical and Geochemical Data. - Holocene History of the Lena and Other Rivers Discharge in the Laptev Sea. - Organic Geochemical Data About Sedimentation History Along the Continental Slope of the East Siberian Sea During the Last Climatic Cycle. - Preliminary Data About Accumulation of Diatom-Bearing Clayey Silts at the Chukchi Sea Shelf. - 12 Seas of the Eastern Subarctic. - Recent Sedimentation Environment. - History of Sedimentation. - History of Sedimentation in the Deep-Water Part of the Shirshov Ridge (Bering Sea) During the Last Three Marine-Isotope Stages. - History of Sedimentation in the Northern Sea of Okhotsk During the Last 1.1 Ma. - PART III THE LATE PLEISTOCENE PALEOGEOGRAPHIC EVENTS OF NORTHERN EURASIA AND HISTORY OF SEDIMENTATION IN THE SUBARCTIC SEAS AND THE ARCTIC OCEAN IN RELATION TO THE NORTHERN HEMISPHERE GLACIATION DURING THE LAST CLIMATIC CYCLE. - 13 Characteristic Features of the Mikulino Landscapes. - 14 Results of Paleoclimate Studies. - 15 Particularities of Sedimentation Processes Within the Continental Blocks and Marine Basins. - Deglaciation Peculiarities. - Facies Variability during Glaciations, Deglaciations, Interglacials. - Geological History of the Arctic Ocean Sea Ice during the Last 60 ka. - Intercoupling of Atmo-, Hydro-, Cryo-, Bio-, and Lithospheres. - References. - Index.

Note: Inhaltsverzeichnis: Annotation. - Autorenverzeichnis. - Die Blattodea (Insecta) des Paläozoikums, Teil II: Morphogenese der Flügelstrukturen und Phylogenie / Jörg Schneider. - Zur Taxonomie und Biostratigraphie der Conchostraca (Phyllopoda, Crustacea) des Rotliegenden (oberes Karbon bis Perm) im Saar-Nahe-Gebiet (BRD) / Thomas Martens. - Zur Ichnologie der Arthropoda / Harald Walter.

Note: Table of contents --- C. Morelli: The contributions of the International Gravimetric Commission (IGC) to global surface-gravity determinations // pp. 165-177 --- C Kotsakis and M. G. Sideris: Study of the gravity field spectrum in Canada in view of cm-geoid determination // pp. 179-188 --- S.D. Pagiatakis, D. Fraser, K. McEwen, A. K. Goodacre and M. Veronneau: Topographic mass density and gravimetric geoid modelling // pp. 189-194 --- H. Denker and I.N. Tziavos: Investigation of the Molodensky series terms for terrain reduced gravity field data // pp. 195-203 --- S.A. Benhamed Daho and S. Kahlouche: Gravimetry data validation in Algeria // pp. 205-210 --- M. Mojzeš and J. Janák: New gravimetric quasigeoid of Slovakia // pp. 211-217 --- I.N. Tziavos, R. Forsberg and M.G. Sideris : Marine gravity field recovery by combining satellite altimetry and shipborne gravimetry // pp. 219-226 --- G. Fotopopulos, C. Kotsakis and M.G. Sideris: Development and evaluation of a new Canadian geoid model // pp. 227-238 --- C. Jekeli: A further evaluation of the EG M96 geopotential model based on deflections of the vertical // pp. 239-243 --- N.K. Pavlis, C.M. Cox, E.C. Pavlis and F.G. Lemoine: Intercomparison and evaluation of some contemporary global geopotential models // pp. 245-254 --- J.C. Catalao and M.J. Sevilla: Comparison between EGM96 and FCUL96B tailored geopotential model for the north-east Atlantic // pp. 255-259 --- J. Kusche, K.H. Ilk and S. Rudolph: Two-step data analysis for future satellite gravity field solutions: a simulation study // pp. 261-266 --- C. Jekeli: An analysis of geopotential difference determination from satellite-to-satellite tracking // pp. 267-272 --- J. Verdun , R. Bayer , E. Klingelé , M. Cerniar , M. Cocard , A. Geiger and M. Halliday: The Alpine Swiss French Airborne Gravimetry Project (ASFAG Project) // pp. 273-276 --- A. Albertella, F. Migliaccio and F. Sansò: New simulations for the spaceborne gravimetry inversion // pp. 277-283 --- Ch. Reigber, P. Schwintzer and H. Lühr: The CHAMP geopotential mission // pp. 285-289 --- B.D. Tapley and C. Reigber: GRACE: a satellite-to-satellite tracking geopotential mapping mission // pp. 291-291 --- S. Bettadpur, J.R. Kim and B.D. Tapley: Results from simulations studies of the GRACE mission // pp. 293-293 --- M. Aguirre-Martinez and S. Cesare: GOCE mission concept, error derivation and performances // pp. 295-302 --- H. Oberndorfer, R. Orobantu, C. Gerlach, J. Muller, R. Rummel, N. Sneetuw, R. Koop, P. Visser, P. Hoyng, A. Selig and M. Smit: GOCE sensor combination and error analysis // pp. 303-307 --- G. Balmino, F. Perosanz, R. Rummel, N. Sneeuw and H. Sunkel: CHAMP, GRACE and GOCE: mission concepts and simulations // pp. 309-319 --- P. Touboul, E. Willemenot, B. Foulon and V. Josselin: Accelerometers for CHAMP, GRACE and GOCE space missions: synergy and evolution // pp. 321-327 --- Ch. Reigber, F. Barthelmes, H. Greiner-Mai, Th. Gruber, H. Jochmann and J. Wünsch: Temporal gravity field variations from oceanic, atmospheric and inner core mass redistributions and their sensitivity to new gravity missions CHAMP and GRACE // pp. 329-340 --- R. Barzaghi, A. Borghi, L. De Stefani, A. Piatti and G. Venuti: SST estimation using collocation: method refinements and seasonal variability // pp. 341-346 --- R. Blinken and K.R. Koch: Estimation of geoid and sea surface topography from satellite altimetry by the adjoint method // pp. 347-352 --- R. Devoti, V. Luceri, P. Rutigliano, C. Sciarretta and G. Bianco: Time series of low degree zonals obtained analyzing different geodetic satellites // pp. 353-358 --- N.K. Pavlis, C.M. Cox, Y.M. Wang and F.G. Lemoine: Further analyses towards the introduction of ocean circulation model information into geopotential solutions // pp. 359-367 --- O.B. Andersen, P. Knudsen, S. Kenyon and R. Trimmer: Recent improvement in the KMS global marine gravity field // pp. 369-377 --- T. Bašic and M. Brkic: The latest efforts in geoid determination in Croatia // pp. 379-386 --- M. Rentsch, Th. Gruber and M. Anzenhofer: A global grid of high-resolution gravity anomalies based on Geosat and ERS-1 altimetry // pp. 387-394 --- G. Rodríguez, M.J. Sevilla and C. De Toro: Crossover analysis in the Canary-Azores region of ERS-1 altimetric data // pp. 395-401 --- G. Tóth, J. Ádám, I.N. Tziavos and V.D. Andritsanos: Gravimetric geoid computations in Hungary and the sorrounding area // pp. 403-409 --- D. Arabelos, S.D. Spatalas, I.N. Tziavos, M.J. Sevilla, G. Rodriguez, C. De Toro, J. Catalao and J. Calvao: A new high resolution geoid for the Iberian Atlantic continental shelf area // pp. 411-419 --- D. Dreher, M.F. Lalancette and M. Maia: Roughness of the gravity and seafloor topography used to infer geodynamic settings // pp. 421-426 --- O.B. Andersen: Shallow water tidal determination from altimetry - the M4 constituent // pp. 427-437 --- P. Knudsen and O. Andersen: A global high resolution mean sea surface from multi mission satellite altimetry // pp. 439-443 --- P. Holota: A construction of Galerkin’ smatrix in quasi-geoid determination // pp. 445-450 --- M.G. Doufexopoulou and V.N. Pagounis: Investigation of raw variance and variability spectra from non gravimetric geoidal signals // pp. 451-460 --- G. Gerstbach: Inversion of vertical deflection data by the program GREMMO // pp. 461-468 --- C. Braitenberg and M. Zadro: Iterative 3D gravity inversion with integration of seismologic data // pp. 469-475 --- V. Baiocchi, M. Crespi and F. Riguzzi: Mean density map for the Italian region by GIS techniques // pp. 477-482 --- V. Josselin, E. Willemenot and P. Touboul: Digital electronics for electrostatic accelerometers interest for high resolution and in-orbit calibration // pp. 483-486 --- J.M. Brown, T.M. Niebauer and F.J. Klopping: Results from a new interferometric ballistic differential gravity meter // pp. 487-496 --- G. Berrino, G. Cerrutti, G. Corrado, P. De Maria and U. Riccardi: Gravity studies on active Italian volcanoes: a comparison between absolute and relative gravimetry // pp. 497-510 --- Y. Fukuda, T. Sato, Y. Tamura and Y. Aoyama: The effects of sea-surface height variations on the long-period gravity changes // pp. 511-517 --- M. Amalvict, J. Hinderer and J.P. Boy: A comparative analysis between an absolute gravimeter (FG5-206) and a superconducting gravimeter ( GWR CO26) in Strasbourg: new results on calibration and long-term gravity changes // pp. 519-525 --- E. Willemenot, P.Touboul and V. Josselin: Gradiometer calibration and performance verification: GOCE approach // pp. 527-532 --- M.F. Lalancette-Le Quentrec, B. Simon, D. Orseau, N. Florisch, M. Llubes, m. Amalvict and J. Hinderer: Ocean loading and crustal deformation in Bretagne (France ) an experiment involving differential GPS, gravimetry and tide gauges // pp. 533-536 --- Y. Kuroishi: Improvement of Japanese geoid with lD- FFT method and its comparison with altimetry-derived geoid // pp. 537-543 --- N. Kühtreiber: Combining gravity anomalies and deflections of the vertical for a precise Austrian geoid // pp. 545-553 --- M. Kuhn: The influence of different crust models on the gravity field of the Earth // pp. 555-562 --- H.A. Abd-Elmotaal: Comparison among different geoid solutions for the Egyptian south-western desert using FFT technique // pp. 563-569 --- J. Ádám: Difference between geoid undulation and quasigeoid height in Hungary // pp. 571-575 --- C. Braitenberg and M. Zadro: The Grotta Gigante horizontal pendulums - instrumentation and observations // pp. 577-582 --- P. Baldi, G. Casula, J. Hinderer and M. Amalvict: Calibration of a superconducting gravimeter: a comparison between the mass attraction method and the use of FG5 absolute gravity measurements // pp. 583-588 --- L. Biagi, R. De Stefano, F. Sansó and C. Sciarretta: RTC and density variations in the estimation of local geoids // pp. 589-595 --- A. De Bruijne, R. Haagmans and E. De M

Note: Contents: 1 Introduction and examples. - 1.1 Introduction. - 1.2 Why Bayes?. - 1.2.1 Estimating the probability of a rare event. - 1.2.2 Building a predictive model. - 1.3 Where we are going. - 1.4 Discussion and further references. - 2 Belief, probability and exchangeability. - 2.1 Belief functions and probabilities. - 2.2 Events, partitions and Bayes' rule. - 2.3 Independence. - 2.4 Random variables. - 2.4.1 Discrete random variables. - 2.4.2 Continuous random variables. - 2.4.3 Descriptions of distributions. - 2.5 Joint distributions. - 2.6 Independent random variables. - 2.7 Exchangeability. - 2.8 de Finetti's theorem. - 2.9 Discussion and further references. - 3 One-parameter models. - 3.1 The binomial model. - 3.1.1 Inference for exchangeable binary data. - 3.1.2 Confidence regions. - 3.2 The Poisson model. - 3.2.1 Posterior inference . - 3.2.2 Example: Birth rates. - 3.3 Exponential families and conjugate priors. - 3.4 Discussion and further references. - 4 Monte Carlo approximation. - 4.1 The Monte Carlo method. - 4.2 Posterior inference for arbitrary functions. - 4.3 Sampling from predictive distributions. - 4.4 Posterior predictive model checking. - 4.5 Discussion and further references. - 5 The normal model. - 5.1 The normal model. - 5.2 Inference for the mean, conditional on the variance. - 5.3 Joint inference for the mean and variance. - 5.4 Bias, variance and mean squared error. - 5.5 Prior specification based on expectations. - 5.6 The normal model for non-normal data. - 5.7 Discussion and further references. - 6 Posterior approximation with the Gibbs sampler. - 6.1 A semiconjugate prior distribution. - 6.2 Discrete approximations. - 6.3 Sampling from the conditional distributions. - 6.4 Gibbs sampling. - 6.5 General properties of the Gibbs sampler. - 6.6 Introduction to MCMC diagnostics. - 6.7 Discussion and further references. - 7 The multivariate normal model. - 7.1 The multivariate normal density. - 7.2 A semiconjugate prior distribution for the mean. - 7.3 The inverse-Wishart distribution. - 7.4 Gibbs sampling of the mean and covariance. - 7.5 Missing data and imputation. - 7.6 Discussion and further references. - 8 Group comparisons and hierarchical modeling. - 8.1 Comparing two groups. - 8.2 Comparing multiple groups. - 8.2.1 Exchangeability and hierarchical models. - 8.3 The hierarchical normal model. - 8.3.1 Posterior inference. - 8.4 Example: Math scores in U.S. public schools. - 8.4.1 Prior distributions and posterior approximation. - 8.4.2 Posterior summaries and shrinkage. - 8.5 Hierarchical modeling of means and variances. - 8.5.1 Analysis of math score data. - 8.6 Discussion and further references. - 9 Linear regression. - 9.1 The linear regression model. - 9.1.1 Least squares estimation for the oxygen uptake data. - 9.2 Bayesian estimation for a regression model. - 9.2.1 A semiconjugate prior distribution. - 9.2.2 Default and weakly informative prior distributions. - 9.3 Model selection. - 9.3.1 Bayesian model comparison. - 9.3.2 Gibbs sampling and model averaging. - 9.4 Discussion and further references. - 10 Nonconjugate priors and Metropolis-Hastings algorithms. - 10.1 Generalized linear models. - 10.2 The Metropolis algorithm. - 10.3 The Metropolis algorithm for Poisson regression. - 10.4 Metropolis, Metropolis-Hastings and Gibbs. - 10.4.1 The Metropolis-Hastings algorithm. - 10.4.2 Why does the Metropolis-Hastings algorithm work?. - 10.5 Combining the Metropolis and Gibbs algorithms. - 10.5.1 A regression model with correlated errors. - 10.5.2 Analysis of the ice core data. -

Note: Table of Contents 1 Introduction 1.1 Scripting versus Traditional Programming 1.1.1 Why Scripting is Useful in Computational Science 1.1.2 Classification of Programming Languages 1.1.3 Productive Pairs of Programming Languages 1.1.4 Gluing Existing Applications 1.1.5 Scripting Yields Shorter Code 1.1.6 Efficiency 1.1.7 Type-Specification (Declaration) of Variables 1.1.8 Flexible Function Interfaces 1.1.9 Interactive Computing 1.1.10 Creating Code at Run Time 1.1.11 Nested Heterogeneous Data Structures 1.1.12 GUI Programming 1.1.13 Mixed Language Programming 1.1.14 When to Choose a Dynamically Typed Language 1.1.15 Why Python? 1.1.16 Script or Program? 1.2 Preparations for Working with This Book 2 Getting Started with Python Scripting 2.1 A Scientific Hello World Script 2.1.1 Executing Python Scripts 2.1.2 Dissection of the Scientific Hello World Script 2.2 Working with Files and Data 2.2.1 Problem Specification 2.2.2 The Complete Code 2.2.3 Dissection 2.2.4 Working with Files in Memory 2.2.5 Array Computing 2.2.6 Interactive Computing and Debugging 2. 2.7 Efficiency Measurements 2.2.8 Exercises 2.3 Gluing Stand-Alone Applications 2.3.1 The Simulation Code 2.3.2 Using Gnuplot to Visualize Curves 2.3.3 Functionality of the Script 2.3.4 The Complete Code 2.3.5 Dissection 2.3.6 Exercises 2.4 Conducting Numerical Experiments 2.4.1 Wrapping a Loop Around Another Script 2.4.2 Generating an HTML Report 2.4.3 Making Animations 2.4.4 Varying Any Parameter 2.5 File Format Conversion 2.5.1 A Simple Read/Write Script 2.5.2 Storing Data in Dictionaries and Lists 2.5.3 Making a Module with Functions 2.5.4 Exercises 3 Basic Python 3.1 Introductory Topics 3.1.1 Recommended Python Documentation 3.1.2 Control Statements 3.1.3 Running Applications 3.1.4 File Reading and Writing 3.1.5 Output Formatting 3.2 Variables of Different Types 3.2.1 Boolean Types 3.2.2 The None Variable 3.2.3 Numbers and Numerical Expressions 3.2.4 Lists and Tuples 3.2.5 Dictionaries 3.2.6 Splitting and Joining Text 3.2.7 String Operations 3.2.8 Text Processing 3.2.9 The Basics of a Python Class 3.2.10 Copy and Assignment 3.2.11 Determining a Variable's Type 3.2.12 Exercises 3.3 Functions 3.3.1 Keyword Arguments 3.3.2 Doc Strings 3.3.3 Variable Number of Arguments 3.3.4 Call by Reference 3.3.5 Treatment of Input and Output Arguments 3.3.6 Function Objects 3.4 Working with Files and Directories 3.4.1 Listing Files in a Directory 3.4.2 Testing File Types 3.4.3 Removing Files and Directories 3.4.4 Copying and Renaming Files 3.4.5 Splitting Pathnames 3.4.6 Creating and Moving to Directories 3.4.7 Traversing Directory Trees 3.4.8 Exercises 4 Numerical Computing in Python 4.1 A Quick NumPy Primer 4.1.1 Creating Arrays 4.1.2 Array Indexing 4.1.3 Loops over Arrays 4.1.4 Array Computations 4.1.5 More Array Functionality 4.1.6 Type Testing 4.1.7 Matrix Objects 4.1.8 Exercises 4.2 Vectorized Algorithms 4.2.1 From Scalar to Array in Function Arguments 4.2.2 Slicing 4.2.3 Exercises 4.3 More Advanced Array Computing 4.3.1 Random Numbers 4.3.2 Linear Algebra 4.3.3 Plotting 4.3.4 Example: Curve Fitting 4.3.5 Arrays on Structured Grids 4.3.6 File I/O with NumPy Arrays 4.3.7 Functionality in the Numpyutils Module 4.3.8 Exercises 4.4 Other Tools for Numerical Computations 4.4.1 The ScientificPython Package 4.4.2 The SciPy Package 4.4.3 The Python- Matlab Interface 3 4.4.4 Symbolic Computing in Python 4.4.5 Some Useful Python Modules 5 Combining Python with Fortran, C, and C++ 5.1 About Mixed Language Programming 5.1.1 Applications of Mixed Language Programming 5.1.2 Calling C from Python 5.1.3 Automatic Generation of Wrapper Code 5.2 Scientific Hello World Examples 5.2.1 Combining Python and Fortran 5.2.2 Combining Python and C 5.2.3 Combining Python and C++ Functions 5.2.4 Combining Python and C++ Classes 5.2.5 Exercises 5.3 A Simple Computational Steering Example 5.3.1 Modified Time Loop for Repeated Simulations 5.3.2 Creating a P ython Interface 5.3.3 The Steering Python Script 5.3.4 Equipping the Steering Script with a GUI 5.4 Scripting Interfaces to Large Libraries 6 Introduction to GUI Programming 6.1 Scientific Hello World GUI 6.1.1 Introductory Topics 6.1.2 The First Python/Tkinter Encounter 6.1.3 Binding Events 6.1.4 Changing the Layout 6.1.5 The Final Scientific Hello World GUI 6.1.6 An Alternative to Tkinter Variables 6.1.7 About the Pack Command 6.1.8 An Introduction to the Grid Geometry Manager 6.1.9 Implementing a GUI as a Class 6.1.10 A Simple Graphical Function Evaluator 6.1.11 Exercises 6.2 Adding GUis to Scripts 6.2.1 A Simulation and Visualization Script with a GUI 6.2.2 Improving the Layout 6.2.3 Exercises 6.3 A List of Common Widget Operations 6.3.1 Frame 6.3.2 Label 6.3.3 Button 6.3.4 Text Entry 6.3.5 Balloon Help 6.3.6 Option Menu 6.3.7 Slider 6.3.8 Check Button 6.3.9 Making a Simple Megawidget 6.3.10 Menu Bar 6.3.11 List Data 6.3.12 Listbox 6.3.13 Radio Button 6.3.14 Combo Box 6.3.15 Message Box 6.3.16 User-Defined Dialogs 6.3.17 Color-Picker Dialogs 6.3.18 File Selection Dialogs 6.3.19 Toplevel 6.3.20 Some Other Types of Widgets 6.3.21 Adapting Widgets to the User's Resize Actions 6.3.22 Customizing Fonts and Colors 6.3.23 Widget Overview 6.3.24 Exercises 7 Web Interfaces and CGI Programming 7.1 Introductory CGI Scripts 7.1.1 Web Forms and CGI Scripts 7.1.2 Generating Forms in CGI Scripts 7.1.3 Debugging CGI Scripts 7.1.4 A General Shell Script Wrapper for CGI Scripts 7.1.5 Security Issues 7.2 Adding Web Interfaces to Scripts 7.2.1 A Class for Form Parameters 7.2.2 Calling Other Programs 7.2.3 Running Simulations 7.2.4 Getting a CGI Script to Work 7.2.5 Using Web Applications from Scripts 7.2.6 Exercises 8 Advanced Python 8.1 Miscellaneous Topics 8.1.1 Parsing Command-Line Arguments 8.1.2 Platform-Dependent Operations 8.1.3 Run-Time Generation of Code 8.1.4 Exercises 8.2 Regular Expressions and Text Processing 8.2.1 Motivation 8.2.2 Special Characters 8.2.3 Regular Expressions for Real Numbers 8.2.4 Using Groups to Extract Parts of a Text 8.2.5 Extracting Interval Limits 8.2.6 Extracting Multiple Matches 8.2.7 Splitting Text 8.2.8 Pattern-Matching Modifiers 8.2.9 Substitution and Backreferences 8.2.10 Example: Swapping Arguments in Function Calls 8.2.11 A General Substitution Script 8.2.12 Debugging Regular Expressions 8.2.13 Exercises 8.3 Tools for Handling Data in Files 8.3.1 Writing and Reading Python Data Structures 8.3.2 Pickling Objects 8.3.3 Shelving Objects 8.3.4 Writing and Reading Zip and Tar Archive Files 8.3.5 Downloading Internet Files 8.3.6 Binary Input/Output 8.3.7 Exercises 8.4 A Database for NumPy Arrays 8.4.1 The Structure of the Database 8.4.2 Pickling 8.4.3 Formatted ASCII Storage 8.4.4 Shelving 8.4.5 Comparing the Various Techniques 8.5 Scripts Involving Local and Remote Hosts 8.5.1 Secure Shell Commands 8.5.2 Distributed Simulation and Visualization 8.5.3 Client/Server Programming 8.5.4 Threads 8.6 Classes 8.6.1 Class Programming 8.6.2 Checking the Class Type 8.6.3 Private Data 8.6.4 Static Data 8.6.5 Special Attributes 8.6.6 Special Methods 8.6.7 Multiple Inheritance 8.6.8 Using a Class as a C-like Structure 8.6.9 Attribute Access via String Names 8.6.10 New-Style Classes 8.6.11 Implementing Get/Set Functions via Properties 8.6.12 Subclassing Built-in Types 8.6.13 Building Class Interfaces at Run Time 8.6.14 Building Flexible Class Interfaces 8.6.15 Exercises 8.7 Scope of Variables 8.7.1 Global, Local, and Class Variables 8.7.2 Nested Functions 8.7.3 Dictionaries of Variables in Namespaces 8.8 Exceptions 8.8.1 Handling Exceptions 8.8.2 Raising Exceptions 8.9 Iterators 8.9.1 Constructing an Iterator 8.9.2 A Pointwise Grid Iterator 8.9.3 A Vectorized Grid Iterator 8.9.4 Generators 8.

Note: In kyrillischer Schrift

Note: Enthält zwei Werke. Titel des zweiten Werkes: Taxes through the ages : a pictorial history / Ferdinand H. M. Grapperhaus

Note: CONTENTS Abstract Preface Introduction St. Marys River Ice problems Remedial measures Field studies Highlights, trends, and major findings Modifications to boom Maximum forces Ship traffic Characteristics Effect of boom forces Effect on ice Conclusion Literature cited Appendix A: Ice boom forces

Note: CONTENTS Abstract Preface Nomenclature General background The problem Method of solution Results and discussion Conclusions Literature cited Appendix: Evaluation of rn's in equation 25

Note: CONTENTS Abstract Preface Introduction Experiments Test flume facility Experimental apparatus Experimental procedure Results Plastic versus freshwater ice Shoreline forces Boom forces Average shear stress under ice cover Internal forces Discussion Data scatter Summary and conclusions Literature cited Appendix A: Experimental results

Note: CONTENTS Abstract Preface Introduction Test material and test specimens Test material Required dimensions for test specimens Acquisition and preparation of specimens Field core sampling Specimen preparation in the laboratory Application of forces and displacements to uniaxial specimens Compression Tension Squareness imperfections Loading devices Universal testing machine Gas actuator for constant load Weight-and-pulley system for constant tension Equipment for triaxial tests Measurement of force and displacement Force Displacement Readouts and recorders Literature cited Appendix A: Phenolic-resin end caps Appendix B: Compliant platens Appendix C: Theoretical factor for converting overall strain to gauge-length strain indumbbell specimens Appci dix D: Items developed but not used in Phase I Appendix E: Use of the Brazil test

Note: CONTENTS Abstract Preface Introduction Methods and instrumentation Results Drift tracks Pressure data Temperature data Discussion Conclusions Literature cited