Note: Intro -- Urheberrecht -- Titelblatt -- 1. Geschichtliches -- 2. Kunst und Technik -- 3. Funktionsprinzip der Junghans Mysterieuse -- 3.1 Mathematische Berechnung der Schwingpendeluhren -- 4. Die Uhr der Junghans Mysterieuse -- 4.1 "Amerikanische" Produktion -- 4.2 Das Uhrengehäuse -- 4.3 Die Zifferblätter -- 4.4 Farbgebung der Uhren -- 4.5 Das Räderwerk -- 4.6 Die Zugfeder -- 5. Die Kunstgussfiguren -- 5.1 Herstellung und Material der Kunstgussfiguren -- 5.2 Die Figuren -- 6. Variationen und Kombinationen -- 7. Original und Fälschungen -- 7.1 Gefälschte Uhren -- 8.2 Gefälschte Figuren -- 7.3 Marriagen -- 8. Wert der Mysterieusen von Junghans -- 9. Reparatur / Restaurierung -- 9.1 Das Uhrwerk -- 9.2 Das Uhrengehäuse -- 9.3 Die Trägerfigur -- 10. Regulierung -- 10.1 Korrektur der Auflagestifte -- 10.2 Einstellen des Ruhezustandes -- 10.3 Einstellung des Ankers -- 10.4 Einstellen des Pendelgewichts -- 11. Die Junghans Kataloge mit Schwingpendeluhren -- 11.1 1910 -- 11.2 1911 -- 11.3 1912 -- 11.4 1913 -- 11.5 1914 -- 11.6 1922 -- 11.7 1923 -- 11.8 1925 -- 11.9 1926 -- 11.10 1927 -- 11.11 1929 -- 11.12 1930 -- 11.13 1931 -- 11.14 1932 -- 11.15 1933 -- 11.16 1934 -- 11.17 1935 -- 11.18 1937 / 1938 -- 12. Mysterieusen in Museen -- 12.1 Museum der Firma Junghans in Schramberg: -- 12.2 Stadtmuseum Schramberg: -- 12.3 Musée D'Haute Doubs, Morteau, Frankreich: -- 12.4 Musee D'Horlogerie, Le Locle, Schweiz -- 12.5 Internationales Uhrenmuseum La-Chaux- de-Fonds, Schweiz -- 13. Literatur.

Note: Intro -- Preface -- Contents -- Contributors -- Chapter 1: Nanoscale Structure of Biomass -- 1.1 Introduction -- 1.2 General Plant Anatomy and Plant Cell Wall Structure -- 1.2.1 Corn Stover -- 1.2.2 Switchgrass -- 1.2.3 Poplar -- 1.3 Cellulose, Hemicelluloses, and Lignin -- 1.4 Pretreatment -- 1.5 Enzyme Hydrolysis -- 1.6 Conclusion -- References -- Chapter 2: Depolymerization of Cellulosic Biomass Catalyzed by Activated Carbons -- 2.1 Introduction -- 2.2 Hydrolysis of Cellulose by Activated Carbons -- 2.2.1 Catalytic Activities of Carbons -- 2.2.2 Mix-Milling for the Hydrolysis of Cellulose by Activated Carbon -- 2.2.3 Combination of Activated Carbon and Trace Hydrochloric Acid -- 2.3 Mechanistic Study of the Hydrolysis of Cellulose by Activated Carbon -- 2.3.1 Elementary Steps of Hydrolytic Reactions -- 2.3.2 Adsorption of Cellulosic Molecules on Activated Carbon -- 2.3.3 Hydrolysis of Glycosidic Bonds by Oxygenated Groups -- 2.3.4 Proposed Reaction Mechanism -- 2.4 Summary -- References -- Chapter 3: Advances in the Conversion of Short-Chain Carbohydrates: A Mechanistic Insight -- 3.1 Introduction -- 3.2 New Platform Chemicals from Three-Carbon Sugars -- 3.2.1 Lewis Acid-Catalyzed Synthesis of Lactic Acid or Alkyl Lactates -- 3.2.2 Direct Conversion of Glycerol to Lactic Acid or Its Esters -- 3.2.3 Hydrogenation of Trioses to 1,2-Propylene Glycol -- 3.3 The Chemistry of Tetroses: Rare Sugars to High-Value Chemicals -- 3.3.1 Catalytic Synthesis of Functional C4-α-Hydroxy Esters -- 3.3.2 Role of New C4-α-Hydroxy Esters in the Biopolymer Industry -- 3.3.3 Isomerization of Tetroses in Aqueous Media -- 3.3.4 Hydrogenation of Tetroses -- 3.4 Valorization of C2-Sugars -- 3.4.1 Synthesis of C4-α-Hydroxy Esters from Glycolaldehyde -- 3.4.2 Lewis Acid-Catalyzed Conversion of Glyoxal to Glycolic Acid. , 3.5 Prebiotic Mechanisms as Inspiration for the Selective Bottom-Up Synthesis of Carbohydrates -- 3.6 Cross Coupling of Small Carbohydrates -- 3.7 Summary, Conclusions, Outlook -- References -- Chapter 4: Differentiation of the Coordination Chemistry of Metal Chlorides in Catalytic Conversion of Glucose in Ionic Liquids -- 4.1 Introduction -- 4.2 Analytical Techniques Applied to Characterize Carbohydrate Conversions to 5-HMF -- 4.3 Equilibrium Anomer Distribution, Reaction Pathway, and Kinetics in Glucose Hydrothermal Conversion -- 4.4 Metal Halide Catalyzed Glucose Conversion to 5-HMF -- 4.5 Mechanistic Pathway in Aldose-Ketose Isomerization: Hydride Transfer by Binuclear Complexes Based on DFT and EXAFS Study -- 4.6 Differentiation of Metal Chloride Catalysts by In Situ Far-Infrared Spectroscopy: Effect of Oxygen Sources on the Coordination Chemistry and on Catalysis -- 4.6.1 The Introduction of Far-Infrared Spectroscopy (FIR) -- 4.6.2 The Application of FIR in Glucose Conversion Catalyzed by Metal Chlorides in 1-Butyl-3-Methylimidazolium Chloride ([BMIM]Cl) -- 4.6.3 The Coordination Characteristics of Metal Chlorides in Glucose Conversion to 5-HMF in [BMIM]Cl -- 4.6.4 The Mechanism of Metal Chlorides in the Process of Glucose Conversion -- 4.6.5 The Coordination Characteristic of Metal Atoms to the Hydroxyl Oxygen -- 4.6.6 The Coordination Characteristic of Metal Atoms to the Ketonic Oxygen -- 4.6.7 The Coordination Characteristic of Metal Atoms to the Oxygen Atoms of 5-HMF and Water -- 4.6.8 Correlation of the Coordination Chemistry of Metal Chlorides with Their Catalytic Performance in Glucose Conversion -- References -- Chapter 5: Base-Catalyzed Reactions in Biomass Conversion: Reaction Mechanisms and Catalyst Deactivation -- 5.1 Introduction -- 5.2 Transesterification -- 5.2.1 Transesterification Catalysts and Reaction Mechanisms. , 5.2.2 Transesterification Catalyst Deactivation -- 5.3 Aldol Condensation -- 5.3.1 Acetone Self-Condensation -- 5.3.1.1 Acetone Self-Condensation Catalysts and Reaction Mechanism -- Acetone Self-Condensation in the Liquid Phase -- Acetone Self-Condensation in Gas Phase -- 5.3.1.2 Acetone Self-Condensation Catalyst Deactivation -- 5.3.2 Alcohol Condensation: Guerbet Reaction -- 5.3.2.1 Ethanol Condensation Catalysts and Reaction Mechanism -- 5.3.2.2 Ethanol Condensation Catalyst Deactivation -- 5.3.3 Condensation of Cellulose-Derived Aldehydes -- 5.3.3.1 Aldehyde Condensation Catalysts and Reaction Mechanisms -- 5.3.3.2 Aldehyde Condensation Catalyst Deactivation -- 5.4 Ketonization -- 5.4.1 Acetic Acid Ketonization Catalysts and Reaction Mechanism -- 5.4.2 Acetic Acid Ketonization Catalyst Deactivation -- References -- Chapter 6: Progress in the Development of Mesoporous Solid Acid and Base Catalysts for Converting Carbohydrates into Platform Chemicals -- 6.1 Introduction -- 6.2 Catalytic Conversion of Fructose and Glucose Over Solid Acid or Base Catalysts -- 6.2.1 Dehydration of Fructose into HMF -- 6.2.1.1 Silica-Based Solid Acid Catalyst -- 6.2.1.2 Carbon-Based Solid Acid Catalysts -- 6.2.1.3 Zeolite-Based Solid Acid Catalysts -- 6.2.1.4 Ion-Exchange Resin Solid Acid Catalysts -- 6.2.1.5 Ionic Liquid-Based Solid Acid Catalysts -- 6.2.1.6 Metal Oxide-Based Solid Acid Catalyst -- 6.2.1.7 Heteropoly Acid Solid Acid Catalysts -- 6.2.2 Isomerization of Glucose to Fructose -- 6.2.3 Dehydration of Glucose to HMF -- 6.2.3.1 Metal Oxide-Based Catalysts -- 6.2.3.2 Zeolite-Based Catalysts -- 6.2.3.3 Carbon-Based Catalysts and Other Bifunctional Catalysts -- 6.2.3.4 Binary Solid Acid and Base Catalyst -- 6.3 Conversion of Cellulose Over Solid Acid Catalyst -- 6.3.1 Hydrolysis of Cellulose into Monosaccharide or Polysaccharides. , 6.3.1.1 Sulfated Carbon Catalysts -- 6.3.1.2 Silica-Based Solid Acid Catalysts -- 6.3.1.3 Metal Oxide-Based Solid Acid Catalysts -- 6.3.2 Glycosidation of Cellulose to Alkyl Glucosides -- 6.4 Concluding Remarks -- References -- Chapter 7: Catalytic Oxidation Pathways for the Production of Carboxylic Acids from Biomass -- 7.1 Introduction -- 7.2 Oxidation of Glycerol -- 7.2.1 Oxidation of Glycerol to Dihydroxyacetone -- 7.2.2 Oxidation of Glycerol to Glyceric Acid -- 7.2.3 Oxidation of Glycerol to Lactic Acid -- 7.3 Oxidation of HMF, Furfural, and Glyoxal -- 7.3.1 Selective Oxidation of 5-Hydroxymethylfurfural (HMF) -- 7.3.2 Selective Oxidation of Furfural -- 7.3.3 Selective Oxidation of Glyoxal into Glyoxylic Acid -- 7.4 Oxidation of Sugars into Chemicals -- 7.4.1 Selective Oxidation of Glucose to Gluconic Acid -- 7.4.2 Selective Oxidation of Other Pentoses or Hexoses to Aldonic Acids -- 7.5 Oxidation of Cellulose into Carboxylic Acids -- References -- Chapter 8: New Reaction Schemes for the Production of Biomass-Based Chemicals Created by Selective Catalytic Hydrogenolysis: Catalysts with Noble Metal and Tungsten -- 8.1 Introduction -- 8.2 Addition Effect Common to Group 6-7 Metal Oxides -- 8.2.1 Rh-W Catalysts and the Differences to Rh-Re and Rh-Mo Catalysts -- 8.2.2 Ir-Based Catalysts -- 8.3 The Unique Addition Effect of Tungsten -- 8.3.1 Pd-W Catalysts for the Partial C-O Hydrogenolysis of Diols -- 8.3.2 Pt-W Catalysts for the Hydrogenolysis of Glycerol to 1,3-Propanediol -- 8.4 Conclusions -- References -- Chapter 9: Mechanism and Kinetic Analysis of the Hydrogenolysis of Cellulose to Polyols -- 9.1 Introduction -- 9.2 Cellulose Hydrogenolysis to Sugar Alcohols -- 9.2.1 Catalysts and Reaction Mechanisms -- 9.2.2 Reaction Kinetics -- 9.3 Cellulose Hydrogenolysis to Ethylene Glycol and 1,2-Propylene Glycol -- 9.3.1 Catalysts and Reaction Mechanism. , 9.3.2 Reaction Kinetics -- 9.4 Outlook -- References.

Note: Cover -- Proteome Informatics -- Acknowledgements -- Contents -- Chapter 1 - Introduction to Proteome Informatics -- 1.1 Introduction -- 1.2 Principles of LC-MS/MS Proteomics -- 1.2.1 Protein Fundamentals -- 1.2.2 Shotgun Proteomics -- 1.2.3 Separation of Peptides by Chromatography -- 1.2.4 Mass Spectrometry -- 1.3 Identification of Peptides and Proteins -- 1.4 Protein Quantitation -- 1.5 Applications and Downstream Analysis -- 1.6 Proteomics Software -- 1.6.1 Proteomics Data Standards and Databases -- 1.7 Conclusions -- Acknowledgements -- References -- Section I - Protein Identification -- Chapter 2 - De novo Peptide Sequencing -- 2.1 Introduction -- 2.2 Manual De novo Sequencing -- 2.3 Computer Algorithms -- 2.3.1 Search Tree Pruning -- 2.3.2 Spectrum Graph -- 2.3.3 PEAKS Algorithm -- 2.4 Scoring Function -- 2.4.1 Likelihood Ratio -- 2.4.2 Utilization of Many Ion Types -- 2.4.3 Combined Use of Different Fragmentations -- 2.4.4 Machine Learning -- 2.4.5 Amino Acid Score -- 2.5 Computer Software -- 2.5.1 Lutefisk -- 2.5.2 Sherenga -- 2.5.3 PEAKS -- 2.5.4 PepNovo -- 2.5.5 DACSIM -- 2.5.6 NovoHMM -- 2.5.7 MSNovo -- 2.5.8 PILOT -- 2.5.9 pNovo -- 2.5.10 Novor -- 2.6 Conclusion: Applications and Limitations of De novo Sequencing -- 2.6.1 Sequencing Novel Peptides and Detecting Mutated Peptides -- 2.6.2 Assisting Database Search -- 2.6.3 De novo Protein Sequencing -- 2.6.4 Unspecified PTM Characterization -- 2.6.5 Limitations -- Acknowledgements -- References -- Chapter 3 - Peptide Spectrum Matching via Database Search and Spectral Library Search -- 3.1 Introduction -- 3.2 Protein Sequence Databases -- 3.3 Overview of Shotgun Proteomics Method -- 3.4 Collision Induced Dissociation Fragments Peptides in Predictable Ways -- 3.5 Overview of Database Searching -- 3.6 MyriMatch Database Search Engine -- 3.6.1 Spectrum Preparation. , 3.6.2 Peptide Harvesting from Database -- 3.6.3 Comparing Experimental MS/MS with Candidate Peptide Sequences -- 3.7 Accounting for Post-Translational Modifications During Database Search -- 3.8 Reporting of Database Search Peptide Identifications -- 3.9 Spectral Library Search Concept -- 3.10 Peptide Spectral Libraries -- 3.11 Overview of Spectral Library Searching -- 3.12 Pepitome Spectral Library Search Engine -- 3.12.1 Experimental MS2 Spectrum Preparation -- 3.12.2 Library Spectrum Harvesting and Spectrum-Spectrum Matching -- 3.12.3 Results Reporting -- 3.13 Search Results Vary Between Various Database Search Engines and Different Peptide Identification Search Strategies -- 3.14 Conclusion -- References -- Chapter 4 - PSM Scoring and Validation -- 4.1 Introduction -- 4.2 Statistical Scores and What They Mean -- 4.2.1 Statistical Probability p-Values and Multiple Testing -- 4.2.2 Expectation Scores -- 4.2.3 False Discovery Rates -- 4.2.4 q-Values -- 4.2.5 Posterior Error Probability -- 4.2.6 Which Statistical Measure to Use and When -- 4.2.7 Target Decoy Approaches for FDR Assessment -- 4.3 Post-Search Validation Tools and Methods -- 4.3.1 Qvality -- 4.3.2 PeptideProphet -- 4.3.3 Percolator -- 4.3.4 Mass Spectrometry Generating Function -- 4.3.5 Nokoi -- 4.3.6 PepDistiller -- 4.3.7 Integrated Workflow and Pipeline Analysis Tools -- 4.3.8 Developer Libraries -- 4.4 Common Pitfalls and Problems in Statistical Analysis of Proteomics Data -- 4.4.1 Target-Decoy Peptide Assumptions -- 4.4.2 Peptide Modifications -- 4.4.3 Search Space Size -- 4.4.4 Distinct Peptides and Proteins -- 4.5 Conclusion and Future Trends -- References -- Chapter 5 - Protein Inference and Grouping -- 5.1 Background -- 5.1.1 Assignment of Peptides to Proteins -- 5.1.2 Protein Groups and Families -- 5.2 Theoretical Solutions and Protein Scoring. , 5.2.1 Protein Grouping Based on Sets of Peptides -- 5.2.2 Spectral-Focussed Inference Approaches -- 5.2.3 Considerations of Protein Length -- 5.2.4 Handling Sub-Set and Same-Set Proteins within Groups -- 5.2.5 Assignment of Representative or Group Leader Proteins -- 5.2.6 Importance of Peptide Classification to Quantitative Approaches -- 5.2.7 Scoring or Probability Assignment at the Protein-Level -- 5.2.8 Handling "One Hit Wonders" -- 5.3 Support for Protein Grouping in Data Standards -- 5.4 Conclusions -- Acknowledgements -- References -- Chapter 6 - Identification and Localization of Post-Translational Modifications by High-Resolution Mass Spectrometry -- 6.1 Introduction -- 6.2 Sample Preparation Challenges -- 6.3 Identification and Localization of Post-Translational Modifications -- 6.3.1 Computational Challenges -- 6.3.2 Annotation of Modifications -- 6.3.3 Common Post-Translational Modifications Identified by Mass Spectrometry -- 6.3.4 Validation of Results -- 6.4 Conclusion -- Acknowledgements -- References -- Section II - Protein Quantitation -- Chapter 7 - Algorithms for MS1-Based Quantitation -- 7.1 Introduction -- 7.2 Feature Detection and Quantitation -- 7.2.1 Conventional Feature Detection -- 7.2.2 Recent Approaches Based on Sparsity and Mixture Modelling -- 7.3 Chromatogram Alignment -- 7.3.1 Feature-Based Pattern Matching -- 7.3.2 Raw Profile Alignment -- 7.4 Abundance Normalisation -- 7.5 Protein-Level Differential Quantification -- 7.5.1 Statistical Methods -- 7.5.2 Statistical Models Accounting for Shared Peptides -- 7.6 Discussion -- Acknowledgements -- References -- Chapter 8 - MS2-Based Quantitation -- 8.1 MS2-Based Quantification of Proteins -- 8.2 Spectral Counting -- 8.2.1 Implementations -- 8.2.2 Conclusion on Spectrum Counting -- 8.3 Reporter Ion-Based Quantification -- 8.3.1 Identification. , 8.3.2 Reporter Ion Intensities, Interferences and Deisotoping -- 8.3.3 Ratio Estimation and Normalization -- 8.3.4 Implementation -- 8.3.5 Conclusion on Reporter Ion-Based Quantification -- Acknowledgements -- References -- Chapter 9 - Informatics Solutions for Selected Reaction Monitoring -- 9.1 Introduction -- 9.1.1 SRM - General Concept and Specific Bioinformatic Challenges -- 9.1.2 SRM-Specific Bioinformatics Tools -- 9.2 SRM Assay Development -- 9.2.1 Target and Transition Selection, Proteotypic and Quantotypic Peptides -- 9.2.2 Spikes of Isotopically Labeled Peptides and Protein Standards and Additional Assay Development Steps -- 9.2.3 Retention Time Regressions and Retention Time Scheduling -- 9.2.4 Method Generation for MS Acquisitions -- 9.3 System Suitability Assessments -- 9.4 Post-Acquisition Processing and Data Analysis -- 9.4.1 mProphet False Discovery Analysis, Peak Detection and Peak Picking -- 9.4.2 Data Viewing and Data Management: Custom Annotation, Results and Document Grids, Group Comparisons -- 9.4.3 Data Reports, LOD-LOQ Calculations and Statistical Processing, Use of Skyline External Tools -- 9.4.4 Group Comparisons and Peptide & -- Protein Quantification -- 9.4.5 Easy Data Sharing and SRM Resources - Panorama -- 9.5 Post-Translational Modifications and Protein Isoforms or Proteoforms -- 9.6 Conclusion and Future Outlook -- Acknowledgements -- References -- Chapter 10 - Data Analysis for Data Independent Acquisition -- 10.1 Analytical Methods -- 10.1.1 Motivation -- 10.1.2 Background: Other MS Methods -- 10.1.3 DIA Concept -- 10.1.4 Theoretical Considerations -- 10.1.5 Main DIA Methods -- 10.1.5.1 PRM -- 10.1.5.2 MSE/HDMSE/AIF -- 10.1.5.3 PAcIFIC -- 10.1.5.4 SWATH-MS -- 10.1.5.5 MSX -- 10.1.6 Analyte Separation Methods -- 10.2 Data Analysis Methods -- 10.2.1 DIA Data Analysis -- 10.2.2 Untargeted Analysis, Spectrum-Centric. , 10.2.2.1 Signal Clustering -- 10.2.2.2 Pseudo-Spectra Identification -- 10.2.2.3 Peptide and Protein Quantification -- 10.2.3 Targeted Analysis, Chromatogram-Centric -- 10.2.3.1 Retention Time Normalisation -- 10.2.3.2 Chromatogram Extraction -- 10.2.3.3 Peak Group Scoring -- 10.2.3.3.1 Peak Picking.The aim of peak picking is to identify potential peak candidates (points of elution) for each peptide in the fragme... -- 10.2.3.3.2 Peak Scoring.The algorithm next operates on the peak group candidates found in the previous step and computes a set of scores fo... -- 10.2.3.4 Peak Quantification -- 10.2.3.5 Error Rate Estimation -- 10.2.3.6 Alignment -- 10.2.4 FDR -- 10.2.5 Results and Formats -- 10.3 Challenges -- References -- Section III - Open Source Software Environments for Proteome Informatics -- Chapter 11 - Data Formats of the Proteomics Standards Initiative -- 11.1 Introduction -- 11.2 mzML -- 11.2.1 Data Format -- 11.2.2 Software Implementations -- 11.2.3 Current Work -- 11.2.4 Variations of mzML -- 11.3 mzIdentML -- 11.3.1 Data Format -- 11.3.2 Software Implementations -- 11.3.3 Current Work -- 11.4 mzQuantML -- 11.4.1 Data Format -- 11.4.2 Software Implementations -- 11.4.3 Current Work -- 11.5 mzTab -- 11.5.1 Data Format -- 11.5.2 Software Implementations -- 11.5.3 Current Work -- 11.6 TraML -- 11.6.1 Data Format -- 11.6.2 Software Implementations -- 11.7 Other Data Standard Formats Produced by the PSI -- 11.8 Conclusions -- Abbreviations -- Acknowledgements -- References -- Chapter 12 - OpenMS: A Modular, Open-Source Workflow System for the Analysis of Quantitative Proteomics Data -- 12.1 Introduction -- 12.2 Peptide Identification -- 12.3 iTRAQ Labeling -- 12.4 Dimethyl Labeling -- 12.5 Label-Free Quantification -- 12.6 Conclusion -- Acknowledgements -- References -- Chapter 13 - Using Galaxy for Proteomics -- 13.1 Introduction. , 13.2 The Galaxy Framework as a Solution for MS-Based Proteomic Informatics.

Note: Intro -- Page de Titre -- Droits d'Auteur -- Entreprise Régénérative -- Remerciements -- À Propos des Auteurs -- Références.

Note: Intro -- Contents -- Preface -- Dedication -- Chapter 1: Introduction and Brief Summary -- 1.1 Why Seed Clouds? -- 1.2 Approaches and Restrictions to Seeding Clouds -- 1.3 Scientific Basis for Cloud Seeding -- 1.4 The Conduct of Cloud Seeding Operations -- 1.5 How to Initiate a Cloud Seeding Project -- 1.6 Conclusions -- 1.7 References -- Chapter 2: Societal, Environmental, and Economic Aspects -- 2.1 Introduction -- 2.2 Societal Aspects -- 2.2.1 Studies -- 2.2.2 The Diffusion of Innovations and Cloud Seeding -- 2.2.3 Assessing Public Attitudes -- 2.2.4 Assessing Community Dynamics -- 2.2.5 Decision Processes -- 2.2.6 Public Participation Procedures -- 2.3 Environmental Aspects -- 2.3.1 Historical Perspective -- 2.3.2 The Concept of Cumulative Effects -- 2.3.3 Case Study-The Sierra Ecology Project -- 2.3.4 Case Study-Environmental Impact Statement for a Prototype Project -- 2.4 Economic Aspects -- 2.4.1 Deciding the Goal and Scale of Economic Analysis -- 2.4.2 Economic Aspects of Summer Cloud Seeding -- 2.4.3 Economic Aspects of Winter Cloud Seeding -- 2.5 Conclusions -- 2.6 References -- Chapter 3: Legal Aspects of Weather Modification Operations -- 3.1 Introduction -- 3.2 Preoperational Planning -- 3.2.1 Role of Regulatory Entities in States -- 3.2.2 Weather Modification Licenses -- 3.2.3 Weather Modification Permits -- 3.2.4 Impacts of Environmental Laws and Rules -- 3.2.5 Contractual Agreements among Sponsors and Operators -- 3.3 Conducting Operations -- 3.3.1 Operational Control -- 3.3.2 Archival of Data and Information -- 3.3.3 Reporting Procedures -- 3.4 Evaluating Operations -- 3.4.1 Legal Liabilities for Sponsors and Operators -- 3.4.2 Water Rights -- 3.5 Conclusions -- 3 .6 References -- Chapter 4: The Scientific Basis -- 4.1 Introduction -- 4.2 The Natural Production of Precipitation -- 4.2.1 Formation of Cloud Condensate. , 4.2.2 Cloud Initiation and Colloidal Stability -- 4.2.3 Initiation and Evolution of Precipitation -- 4.3 Cloud Seeding to Augment Rainfall -- 4.3.1 Seeding to Enhance the Warm Cloud Process (Hygroscopic Seeding) -- 4.3.2 Seeding to Enhance the Cold Cloud Process (Glaciogenic Seeding) -- 4.3.3 Seeding to Enhance Development of Individual Convective Clouds -- 4.3.4 Expansion of Glaciogenic Seeding Concepts to Mesoscale Systems -- 4.4 The Natural Production of Snowfall -- 4.4.1 Formation of Cloud Condensate -- 4.4.2 Cloud Initiation, Colloidal Stability, and Evolution of Precipitation -- 4.5 Cloud Seeding to Augment Snowfall -- 4.5.1 Snow Augmentation Methods -- 4.5.2 Expansion of Snow Augmentation Concepts to Larger Scales -- 4.6 Technological Advances -- 4.7 Conclusions -- 4.8 References -- Chapter 5: Cloud Seeding Modes, Instrumentation, and Status of Precipitation Enhancement Technology -- 5.1 Introduction -- 5.2 Cloud Seeding Modes -- 5.2.1 Cloud Seeding Agents -- 5.2.2 Delivery Systems -- 5.2.3 Deployment of Cloud Seeding Systems -- 5.3 Instrumentation and Atmospheric Models -- 5.3.1 Real-Time Decision-Making and Monitoring Tools -- 5.3.2 Measurements of Potential Value in Postproject Assessments -- 5.4 Status of Precipitation Enhancement Technology -- 5.4.1 American Society of Civil Engineers -- 5.4.2 Weather Modification Association -- 5.4.3 American Meteorological Society -- 5.4.4 World Meteorological Organization -- 5.5 Conclusions -- 5.6 References -- Chapter 6: How to Implement a Cloud Seeding Program -- 6.1 Introduction -- 6.1.1 Feasibility Study -- 6.1.2 The Factors Governing Implementation -- 6.2 Needs and Goals -- 6.2.1 Origin of Need and Program Justification (Program Sponsors) -- 6.2.2 Political and/or Institutional Mechanisms -- 6.3 The Feasibility Study -- 6.3.1 Feasibility Study Considerations. , 6.3.2 Feasibility Study Technical Considerations -- 6.3.3 Feasibility Study Cost Considerations -- 6.3.4 Statement of Program Expectations (Likelihood of Success) -- 6.4 Program Design -- 6.4.1 Seeding Modes and Agents (Design) -- 6.4.2 The Evaluation Plan -- 6.4.3 Quantification of Findings -- 6.5 Program Control -- 6.5.1 Seeding Decisions -- 6.5.2 Data Collection and Access -- 6.5.3 Seeding Suspension Criteria -- 6.6 Program Management -- 6.7 References -- Chapter 7: Glossary -- Index.

Note: Intro -- Title Page.

Note: Intro -- Inhalt -- 1 Einleitung -- 2 Konzept und Methoden -- 2.1 Dimensionen von Energiedemokratie -- 2.1.1 Beteiligung -- 2.1.2 Eigentum und Besitz -- 2.1.3 Wertschöpfung und Beschäftigung -- 2.1.4 Ökologie und Suffizienz -- 2.1.5 Emanzipation als Politik -- 2.2 Die empirische Methodik -- 2.2.1 Geografische Verteilung der Fallstudien -- 3 Emanzipatorische Energiewenden - 15 Fallstudien -- 3.1 Energiegenossenschaften -- 3.1.1 Spanien -- 3.1.2 Italien -- 3.1.3 Belgien -- 3.1.4 England und Wales -- 3.2 Transitionen in peripherisierten Räumen -- 3.2.1 Frankreich -- 3.2.2 Schottland -- 3.2.3 Deutschland -- 3.2.4 Schweden -- 3.3 Unkonventionelle Projekte -- 4 Einordnung der Ergebnisse -- 4.1 Diskurse, Kapitalfraktionen und Lokalismus -- 4.1.1 Drohende diskursive Vereinnahmung der Energiewende -- 4.1.2 Grüne und graue Kapitalfraktion -- 4.1.3 Lokalismus als Beschränkung oder als Keimform? -- 4.2 Dynamiken der Transition -- 4.2.1 Lokale Nischen als Anfang -- 4.2.2 Horizontale Lernprozesse und Formalisierung -- 4.2.3 Skalierbarkeit - Gute Konzepte verlassen ihre Nische -- 4.2.4 Energiewenden als Herausforderung des Status quo -- 5 Zusammenfassung -- 5.1 Energiedemokratie im Rückblick: Erfreuliche Funde und einige Lücken -- 5.1.1 Beteiligung -- 5.1.2 Eigentum und Besitz -- 5.1.3 Wertschöpfung und Beschäftigung -- 5.1.4 Ökologie und Postwachstum -- 5.1.5 Emanzipation als erfolgreiche Politik -- 6 Ausblick -- 7 Literatur- und Quellenverzeichnis -- Literatur -- Interviews.

Note: Förderkennzeichen BMBF 01MT12012. - Verbund-Nummer 01115985 , Projektleiter ist laut Berichtsblatt Autor , Unterschiede zwischen dem gedruckten Dokument und der elektronischen Ressource können nicht ausgeschlossen werden , Mit deutscher und englischer Zusammenfassung