ALBERT

Note: Ersch. unregelmäßig , Beiträge teilweise in Englisch

Note: IntroductionMain Assumptions of the Assignment Process -- Definition of Collapse -- Proposing a Range for Fatality Rates in a Collapsed Building -- Assignments of judgment-based fatality rates -- Conclusions. ..

Note: Methodology of Lithium Analytical Chemistry and Isotopic MeasurementsCosmochemistry of Lithium -- Li Partitioning, Diffusion and Associated Isotopic Fractionation: Theoretical and Experimental Insights -- Lithium in the Deep Earth: Mantle and Crustal Systems -- The Surficial Realm: Low Temperature Geochemistry of Lithium..

Note: Part 1 Why Global Cooperation Research 1. The evolution of human cooperation—lessons learned for the future of global governance 2. The behavioral dimension of international cooperation 3. Cooperation in conflict. Ubiquity, limits and potential of working together at the international levelPart 2 Human behavior and cooperation across disciplines 4. The cooperative bias in humans’ biological history 5. Cooperation among humans 6. Can we think of the future? Cognitive barriers to future-oriented decision making 7. Approaching cooperation via complexity 8. The concrete utopia of the gift. A genuine sociological approach to interdisciplinary cooperation theory Part 3 Interdisciplinary approaches to global cooperation 9. The possibilities of global we-identities 10. Diplomatic Cooperation: An evolutionary perspective 11. Cognizing cooperation: clues and cues for institutional design

Note: Thermodynamics and the Earth systemEnergy and entropy -- The first and second law of thermodynamics -- Thermodynamic limits -- Dynamics, structures, and maximization -- Radiation -- Motion -- Hydrologic cycling -- Geochemical cycling -- Land -- Human activity -- The thermodynamic Earth system..

Note: Contents: Part I By Stephen M. Gardiner 1. How Will We be Remembered? ; 2. Betraying the Future ; 3. Who Are We and What Do We Want? ; 4. Justice vs. Extortion Part II By David A. Weisbach ; 5. Introduction to Part II ; 6. Climate Policy and Self-Interest ; 7. The Role of Claims of Justice in Climate Change Policy ; 8. Summing Up ; Part III Responses ; 9. 'The Feasible is Political' ; 10. Weisbach Responds to Gardiner

Note: Contents: 1. Bioeconomy Strategies ; 2. Development of Second-Generation Biorefineries ; 3. Biorefineries: Industry Status and Economics ; 4. Sustainability Considerations for the Future Bioeconomy ; 5. Biomass Supply and Trade Opportunities of Preprocessed Biomass for Power Generation ; 6. Commodity-Scale Biomass Trade and Integration with Other Supply Chains ; 7. Commoditization of Biomass Markets ; 8. Transition Strategies: Resource Mobilization Through Merchandisable Feedstock Intermediates ; Conclusions

Note: Land and Water Resources of Siberia, their Functioning and Ecological StateStatus Report about Understanding, Monitoring and Controlling Landscape Processes in Siberia -- Methods for Monitoring the Chemical Composition of Lake Baikal Water -- Microbiological Monitoring of Lake Baikal -- Developing the Regional Indicator Indexes of Zooplankton for Water Quality Class Determination of Water Bodies in Siberia -- Measuring and Estimating Fluxes of Carbon, Major and Trace Elements to the Arctic Ocean -- Measuring Snowmelt in Siberia: Causes, Process and Consequences -- Estimation of Biomass and Net Primary Production (NPP) in West Siberian Boreal Ecosystems: In-Situ and Remote Sensing Methods -- GIS and Remote Sensing Data Based Methods for Monitoring Water and Soil Objects in the Steppe Biome of Western Siberia -- Significant Siberian Vegetation Change is Inevitably Brought on by the Changing Climate..

Note: Contents: Abstract. - Kurzfassung. - 1 Introduction. - 1.1 Motivation. - 1.2 Scientific questions. - 1.3 Method. - 2 Background and state of the science. - 2.1 The atmospheric aerosol. - 2.1.1 Relevance. - 2.1.2 Aerosol processes. - 2.1.3 Aerosol properties. - 2.2 The influence of ship emissions. - 2.3 Aerosol modeling. - 2.3.1 Selected results. - 2.3.2 Motivation to expand on previous work. - 2.3.3 The computational approach. - 2.3.4 Existing aerosol microphysics submodels. - 2.3.5 MADE3 as a successor of MADE and MADE-in. - 3 The aerosol submodel MADE3. - 3.1 Aerosol characteristics. - 3.1.1 Modes. - 3.1.2 Species. - 3.1.3 Mathematical representation of aerosol characteristics. - 3.2 Aerosol processes. - 3.2.1 Gas–particle partitioning. - 3.2.2 Condensation of H2SO4 and organic vapors. - 3.2.3 New particle formation. - 3.2.4 Coagulation. - 3.2.5 Renaming. - 3.2.6 Aging of insoluble particles. - 4 Box model tests. - 4.1 Model description: MADE vs. MADE3. - 4.2 Model description: PartMC-MOSAIC. - 4.3 Test case scenario. - 4.4 Results: MADE3 vs. MADE. - 4.4.1 Size distributions. - 4.4.2 Composition. - 4.5 Results: MADE3 vs. PartMC-MOSAIC. - 4.5.1 Size distributions. - 4.5.2 Composition. - 4.6 Summary and conclusions. - 5 MADE3 in the atmospheric chemistry general circulation model EMAC. - 5.1 Basic settings. - 5.2 Emissions. - 5.3 Transport. - 5.4 Gas phase chemistry. - 5.5 Cloud formation. - 5.5.1 Stratiform clouds. - 5.5.2 Convective clouds. - 5.6 Cloud and precipitation processing of the aerosol. - 5.7 Wet deposition. - 5.8 Dry deposition. - 5.9 Sedimentation. - 5.10 Optical properties. - 6 Evaluation of simulated tropospheric aerosol properties. - 6.1 Data comparability. - 6.2 The MADE3 aerosol within EMAC. - 6.2.1 Near-surface mass concentrations. - 6.2.2 Vertical distributions. - 6.2.3 Size distributions. - 6.2.4 Aerosol optical depth. - 6.2.5 Global tropospheric burdens and residence times. - 6.2.6 Summary and conclusions. - 6.3 Comparison to MADE. - 6.4 New features of MADE3. - 7 Effects of oceanic ship emissions on atmospheric aerosol particles. - 7.1 Effects of year 2000 emissions. - 7.1.1 Near-surface concentrations. - 7.1.2 Near-surface size distributions. - 7.1.3 Tropospheric burdens. - 7.2 Effects of an idealized fuel sulfur content reduction. - 7.3 Summary and conclusions. - 8 Summary, conclusions, and outlook. - Appendix. - A.1 Particle evolution in the box model study. - A.2 Gas phase chemical mechanism. - A.3 Liquid phase chemical mechanism. - A.4 Mode assignment of cloud residual aerosol. - A.4.1 Terminology. - A.4.2 Basic assumptions. - A.4.3 Algorithm for residual assignment. - A.5 Year 2000 aerosol in EMAC with MADE3. - A.6 Near-surface mass concentration evaluation. - References. - Acronyms, symbols, and species names. - Acronyms. - Symbols. - Tracers and chemical species. - Danksagung.

Note: Why agent-based modelling is useful for economists -- Starting agent-based modelling -- Heterogeneous demand -- Social demand -- Benefits of barter -- The market -- Labour market -- International trade -- Banking -- The tragedy of the commons.

Note: Introduction and overview -- Climate policies in the United States -- Theories of climate policy -- The structural theory applied to the cases -- Causes of climate policies in the fifty states -- Air-pollution and energy policy making in California (the 1940s to the 1980s) -- Climate policy making in California (the 2000s to the present) -- Energy and climate policy making in New York State -- Energy and climate policy making by the federal government -- Conclusions : political opportunities for climate policy in the United States.

Note: Contents: 1 Introduction. - 1.1 Chapter Summary. - 1.2 The Meaning of the Book’s Title. - 1.3 Historical Background. - 1.4 How to Read This Book. - 1.5 Further Reading. - References. - PART 1 BASIC THEORETICAL CONCEPTS. - 2 Discrete-Time Signals and Systems. - 2.1 Chapter Summary. - 2.2 Basic Definitions and Concepts. - 2.3 Discrete-Time Signals: Sequences. - 2.3.1 Basic Sequence Operations. - 2.3.2 Basic Sequences. - 2.3.3 Deterministic and Random Signals. - 2.4 Linear Time-Invariant (LTI) Systems. - 2.4.1 Impulse Response of an LTI System and Linear Convolution. - 2.4.2 An Example of Linear Convolution. - 2.4.3 Interconnections of LTI Systems. - 2.4.4 Effects of Stability and Causality Constraints on the Impulse Response of an LTI System. - 2.4.5 Finite (FIR) and Infinite (IIR) Impulse Response Systems. - 2.4.6 Linear Constant-Coefficient Difference Equation (LCCDE). - 2.4.7 Examples of LCCDE. - 2.4.8 The Solutions of an LCCDE. - 2.4.9 From the LCCDE to the Impulse Response: Examples. - 2.4.10 Eigenvalues and Eigenfunctions of LTI Systems. - References. - 3 Transforms of Discrete-Time Signals. - 3.1 Chapter Summary. - 3.2 z-Transform. - 3.2.1 Examples of z-Transforms and Special Cases. - 3.2.2 Rational z-Transforms. - 3.2.3 Inverse z-Transform. - 3.2.4 The z-Transform on the Unit Circle. - 3.2.5 Selected z-Transform Properties. - 3.2.6 Transfer Function of an LTI System. - 3.2.7 Output Sequence of an LTI System. - 3.2.8 Zeros and Poles: Forms for Rational Transfer Functions. - 3.2.9 Inverse System. - 3.3 Discrete-Time Fourier Transform (DTFT). - 3.3.1 An Example of DTFT Converging in the Mean-Square Sense. - 3.3.2 Line Spectra. - 3.3.3 Inverse DTFT. - 3.3.4 Selected DTFT Properties. - 3.3.5 The DTFT of a Finite-Length Causal Sequence. - 3.4 Discrete Fourier Series (DFS). - 3.4.1 Selected DFS Properties. - 3.4.2 Sampling in the Frequency Domain and Aliasing in the Time Domain. - 3.5 Discrete Fourier Transform (DFT). - 3.5.1 The Inverse DFT in Terms of the Direct DFT. - 3.5.2 Zero Padding. - 3.5.3 Selected DFT Properties. - 3.5.4 Circular Convolution Versus Linear Convolution. - 3.6 Fast Fourier Transform (FFT). - 3.7 Discrete Trigonometric Expansion. - 3.8 Appendix: Mathematical Foundations of Signal Representation. - 3.8.1 Vector Spaces. - 3.8.2 Inner Product Spaces. - 3.8.3 Bases in Vector Spaces. - 3.8.4 Signal Representation by Orthogonal Bases. - 3.8.5 Signal Representation by Standard Bases. - 3.8.6 Frames and Biorthogonal Bases. - 3.8.7 Summary and Complements. - References. - 4 Sampling of Continuous-Time Signals. - 4.1 Chapter Summary. - 4.2 Sampling Theorem. - 4.3 Reconstruction of a Continuous-Time Signal from Its Samples. - 4.4 Aliasing in the Frequency Domain and Anti-Aliasing Filter. - 4.5 The Uncertainty Principle for the Analog Fourier Transform. - 4.6 Support of a Continuous-Time Signal in the Time and Frequency Domains. - 4.7 Appendix: Analog and Digital Frequency Variables. - References. - 5 Spectral Analysis of Deterministic Discrete-Time Signals. - 5.1 Chapter Summary. - 5.2 Issues in Practical Spectral Analysis. - 5.2.1 The Effect of Windowing. - 5.2.2 The Effect of Spectral Sampling. - 5.3 Classical Windows. - 5.4 The Kaiser Window. - 5.5 Energy and Power Signals and Their Spectral Representations. - 5.6 Correlation of Deterministic Discrete-Time Signals. - 5.6.1 Correlation of Energy Signals. - 5.6.2 Correlation of Power Signals. - 5.6.3 Effect of an LTI System on Correlation Properties of Input and Output Signals. - 5.7 Wiener-Khinchin Theorem. - 5.7.1 Energy Signals and Energy Spectrum. - 5.7.2 Power Signals and Power Spectrum. - References. - PART 2 DIGITAL FILTERS. - 6 Digital Filter Properties and Filtering Implementation. - 6.1 Chapter Summary. - 6.2 Frequency-Selective Filters. - 6.3 Real-Causal-Stable-Rational (RCSR) Filters. - 6.4 Amplitude Response. - 6.5 Phase Response. - 6.5.1 Phase Discontinuities and Zero-Phase Response. - 6.5.2 Linear Phase (LP). - 6.5.3 Generalized Linear Phase (GLP). - 6.5.4 Constraints on GLP Filters. - 6.6 Digital Filtering Implementation. - 6.6.1 Direct Forms. - 6.6.2 Transposed-Direct Forms. - 6.6.3 FIR Direct and Transposed-Direct Forms. - 6.6.4 Direct and Transposed-Direct Forms for LP FIR Filters. - 6.6.5 Cascade and Parallel Forms. - 6.7 Zero-Phase Filtering. - 6.8 An Incorrect Approach to Filtering. - 6.9 Filtering After Downsampling. - 6.9.1 Theory of Downsampling. - 6.9.2 An Example of Filtering After Downsampling. - References. - 7 FIR Filter Design. - 7.1 Chapter Summary. - 7.2 Design Process. - 7.3 Specifications of Digital Filters. - 7.3.1 Constraints on the Magnitude Response. - 7.3.2 Constraints on the Phase Response. - 7.4 Selection of Filter Type: IIR or FIR?. - 7.5 FIR-Filter Design Methods and Approximation Criteria. - 7.6 Properties of GLP FIR Filters. - 7.6.1 Factorization of the Zero-Phase Response. - 7.6.2 Zeros of the Transfer Function. - 7.6.3 Another Form of the Adjustable Term. - 7.7 Equiripple FIR Filter Approximations: Minimax Design. - 7.8 Predicting the Minimum Filter Order. - 7.9 MPR Algorithm. - 7.10 Properties of Equiripple FIR Filters. - 7.11 The Minimax Method for Bandpass Filters. - References. - 8 IIR Filter Design. - 8.1 Chapter Summary. - 8.2 Design Process. - 8.3 Lowpass Analog Filters. - 8.3.1 Laplace Transform. - 8.3.2 Transfer Function and Design Parameters. - 8.4 Butterworth Filters. - 8.5 Chebyshev Filters. - 8.5.1 Chebyshev-I Filters. - 8.5.2 Chebyshev-II Filters. - 8.6 Elliptic Filters. - 8.7 Normalized and Non-normalized Filters. - 8.8 Comparison Among the Four Analog Filter Types. - 8.9 From the Analog Lowpass Filter to the Digital One. - 8.9.1 Bilinear Transformation. - 8.9.2 Design Procedure. - 8.9.3 Examples. - 8.10 Frequency Transformations. - 8.10.1 From a Lowpass to a Highpass Filter. - 8.10.2 From a Lowpass to a Bandpass Filter. - 8.10.3 From a Lowpass to a Bandstop Filter . - 8.11 Direct Design of IIR Filters. - 8.12 Appendix. - 8.12.1 Trigonometric Functions with Complex Argument. - 8.12.2 Elliptic Integrals. - 8.12.3 Jacobi Elliptic Functions. - 8.12.4 Landen-Gauss Transformation. - 8.12.5 Elliptic Rational Function. - References. - PART 3 SPECTRAL ANALYSIS. - 9 Statistical Approach to Signal Analysis. - 9.1 Chapter Summary. - 9.2 Preliminary Considerations. - 9.3 Random Variables. - 9.4 Ensemble Averages. - 9.5 Stationary Random Processes and Signals. - 9.6 Ergodicity. - 9.7 Wiener-Khinchin Theorem for Random Signals and Power Spectrum. - 9.8 Cross-Power Spectrum of Two Random Signals. - 9.9 Effect of an LTI System on a Random Signal. - 9.10 Estimation of the Averages of Ergodic Stationary Signals. - 9.10.1 General Concepts in Estimation Theory. - 9.10.2 Mean and Variance Estimation. - 9.10.3 Autocovariance Estimation. - 9.10.4 Cross-Covariance Estimation. - 9.11 Appendix: A Road Map to the Analysis of a Data Record. - References. - 10 Non-Parametric Spectral Methods. - 10.1 Chapter Summary. - 10.2 Power Spectrum Estimation. - 10.3 Periodogram. - 10.3.1 Bias. - 10.3.2 Variance. - 10.3.3 Examples. - 10.3.4 Variance Reduction by Band- and Ensemble-Averaging. - 10.4 Bartlett’s Method. - 10.5 Modified Periodogram. - 10.6 Welch’s Method. - 10.7 Blackman-Tukey Method. - 10.8 Statistical Significance of Spectral Peaks. - 10.9 MultiTaper Method. - 10.10 Estimation of the Cross-Power Spectrum of Two Random Signals. - 10.11 Use of the FFT in Power Spectrum Estimation. - 10.12 Power Spectrum Normalization. - References. - 11 Parametric Spectral Methods. - 11.1 Chapter Summary. - 11.2 Signals with Rational Spectra . - 11.3 Stochastic Models and Processes. - 11.3.1 Autoregressive-Moving Average (ARMA) Model. - 11.3.2 Autoregressive (AR) Model. - 11.3.3 Moving Average (MA) Model. - 11.3.4 How the AR and MA Modeling Approaches Are Theoretically Related. - 11.3.5 First-Order AR and MA Models: White, Red and Blue Noise. - 11.3.6 Higher-Order AR Models. - 11.4 The AR Approach to Spectral Estimation. - 11.5 AR Modeling and Linear Prediction. - 11.6

Note: Beiträge überwiegend deutsch, teilweise englisch

Note: Machine generated contents note:1. Inclusive Developmen t: Debates and Issues -- 2. Inclusive Development and the Burdens of History -- 3. Addressing the Social Deficit in the Wake of Neoliberal Reforms -- 4. Mexico and Indonesia : Politics and Development in Weak States -- 5. Chile : Moving towards Greater Inclusion: From Political Polarization to Consensus -- 6. South Korea : Authoritarianism, Democracy, and the Struggle to Maintain Inclusive Development -- 7. Conclusions: The Politics and Policies of Inclusive Development..