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Radiation chemistry from basics to applications in material and life sciences /

Table of Contents: “…pt. 1. Primary radiation-induced phenomena -- pt. 2. …”
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Nanofluids and their engineering applications /

Table of Contents: “…Section I Understanding Nanofluids 1. Nanofluids: Preparation Methods and Challenges in Stability [P. …”
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L'état de l'insécurité alimentaire dans le monde.

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Silencing the sounded self : John Cage and the American experimental tradition / by Shultis, Christopher

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Manuel de détermination et de mise en place d'un Système d'information pour la sécurité alimentaire et l'alerte rapide (SISAAR)

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CONTAMINANTS AND CLEAN TECHNOLOGIES

Table of Contents: “…Singh, Preeti Chaturvedi, and Soumya Pandit</P></I><B><P>Chapter 2 </B>Biological Treatment of Sulfate-Rich Wastewater</P><I><P>Ariovaldo Jose da Silva, Bruna Sampaio de Mello, and Arnaldo Sarti</P></I><B><P>Chapter 3 </B>Wetland Plants: Recent Advances in Removal of Pollutants from Contaminated Site</P><I><P>Poonam and Mahesh Kumar</P></I><B><P>Chapter 4 </B>Toxic Contaminants in Herbal Medicines</P><I><P>Bhanu Kumar and Subir Kumar Bose</P></I><B><P>Chapter 5 </B>Toxicity Evaluation of Paper Mill Pollutants Using <I>In Silico </I>Toxicology Approach for Environment Safety</P><I><P>Anil Kumar Singh, Pankaj Chowdhary, and Abhay Raj</P></I><B><P>Chapter 6 </B>Effect of Arsenic on Human Health and Its Removal through Physiochemical Techniques</P><I><P>Vishvas Hare, Pankaj Chowdhary, Siddarth Boudh, Anil Kumar Singh, Sujata Mani, and Amit Kumar</P></I><B><P>Chapter 7 </B>Synthesis, Characterization, and Remediation Application of Iron Oxide Nanoparticles</P><I><P>Sandhya Singh, Gaurav Hitkari, and Gulam Abbas</P></I><B><P>Chapter 8 </B>Dyes: Industrial Applications and Toxicity Profile</P><I><P>Sujata Mani and Pankaj Chowdhary</P></I><B><P>Chapter 9 </B>Importance of Bacterial Biofilm in Bioremediation</P><I><P>Rishi Pramod Babu, Soumya Pandit , Namita Khanna, Pankaj Chowdhary, Abhilasha Singh Mathuriya, and Elvis Fosso-Kankeu</P></I><B><P></B> </P><B><P>Chapter 10 </B>Arsenic: Threat to Water as Well as Soil</P><I><P>Kiran Gupta, Alka Srivastava, and Amit Kumar</P></I><B><P>Chapter 11 </B>Aquatic Plants as Effective Phytoremediators of Heavy Metals</P><I><P>Sandip Singh Bhatti, Sartaj Ahmad Bhat, and Jaswinder Singh</P></I><B><P>Chapter 12 </B>Biodiesel as a Renewable Energy Source: An Alternative to Conventional Fuel</P><I><P>Siddharth Boudh, Surabhi Zainith, Pankaj Chowdhary, and Sandhya Mishra</P></I><B><P>Chapter 13 </B>Phytoremediation of Heavy Metals-Polluted Soil</P><I><P>Amjad Ali, Di Guo, Amanullah Mahar, Fazli Wahid, Parimala Gnana Soundari Arockiam Jeyasundar, Muhammad Azeem,</P><P>Ronghua Li, and Zengqiang Zhang</P></I><B><P>Chapter 14 </B>Advanced Nanofiltration Membranes for Wastewater Treatment</P><I><P>Oluranti Agboola, Samuel E. …”
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Inflammatory diseases of blood vessels

Table of Contents: “…Machine generated contents note: List of Contributors Preface Section I. Biology of Blood Vessels and Mechanisms of Vascular Inflammation 1. …”
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L'université en réseau : Les 25 ans de l'Université du Québec / by Ferretti, Lucia

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Statistical disclosure control

Table of Contents: “…Machine generated contents note: Preface vii Acknowledgements ix 1 Introduction 1 1.1 Concepts and Definitions 2 1.1.1 Disclosure 2 1.1.2 Statistical disclosure control 2 1.1.3 Tabular data 3 1.1.4 Microdata 3 1.1.5 Risk and utility 4 1.2 An approach to Statistical Disclosure Control 6 1.3 The chapters of the handbook 8 2 Ethics, Principles, Guidelines and Regulations, a general background 9 2.1 Introduction 9 2.2 Ethical codes and the new ISI code 9 2.2.1 ISI Declaration on Professional Ethics 10 2.2.2 New ISI Declaration on Professional Ethics 10 2.2.3 European Statistics Code of Practice 14 2.3 UNECE Principles and guidelines 14 2.4 Laws 17 2.4.1 Committee on Statistical Confidentiality 18 2.4.2 European Statistical System Committee 18 3 Microdata 21 3.1 Introduction 21 3.2 Microdata Concepts 22 3.2.1 Stage 1: Assess need for confidentiality protection 22 3.2.2 Stage 2: Key characteristics and uses of microdata 24 3.2.3 Stage 3: Disclosure risk 27 3.2.4 Stage 4: Protection methods 29 3.2.5 Stage 5: Implementation 30 3.3 Definitions of disclosure 32 3.3.1 Definitions of disclosure scenarios 33 3.4 Definitions of Disclosure Risk 34 3.4.1 Disclosure risk for categorical quasi-identifiers 35 3.4.2 Disclosure risk for continuous quasi-identifiers 37 3.5 Estimating Re-identification Risk 39 3.5.1 Individual risk based on the sample: threshold rule 39 3.5.2 Estimating individual risk using sampling weights 39 3.5.3 Estimating individual risk by Poisson model 42 3.5.4 Further models that borrow information from other sources 43 3.5.5 Estimating per record risk via heuristics 44 3.5.6 Assessing risk via record linkage 45 3.6 Non-Perturbative Microdata Masking 45 3.6.1 Sampling 46 3.6.2 Global recoding 46 3.6.3 Top and bottom coding 47 3.6.4 Local suppression 47 3.7 Perturbative Microdata Masking 48 3.7.1 Additive noise masking 48 3.7.2 Multiplicative noise masking 52 3.7.3 Microaggregation 54 3.7.4 Data swapping and rank swapping 66 3.7.5 Data shuffling 66 3.7.6 Rounding 67 3.7.7 Resampling 67 3.7.8 PRAM 67 3.7.9 MASSC 71 3.8 Synthetic and Hybrid Data 71 3.8.1 Fully synthetic data 72 3.8.2 Partially synthetic data 77 3.8.3 Hybrid data 79 3.8.4 Pros and cons of synthetic and hybrid data 88 3.9 Information Loss in Microdata 91 3.9.1 Information loss measures for continuous data 92 3.9.2 Information loss measures for categorical data 99 3.10 Release of multiple files from the same microdata set 101 3.11 Software 102 3.11.1 _-ARGUS 102 3.11.2 sdcMicro 103 3.11.3 IVEware 106 3.12 Case Studies 106 3.12.1 Microdata files at Statistics Netherlands 106 3.12.2 The European Labour Force Survey Microdata for Research Purposes 108 3.12.3 The European Structure of Earnings Survey Microdata for Research Purposes 111 3.12.4 NHIS Linked Mortality Data Public Use File, USA 117 3.12.5 Other real case instances 119 4 Magnitude tabular data 121 4.1 Introduction 121 4.1.1 Magnitude Tabular Data: Basic Terminology 121 4.1.2 Complex tabular data structures: hierarchical and linked tables 122 4.1.3 Risk Concepts 124 4.1.4 Protection Concepts 127 4.1.5 Information Loss Concepts 127 4.1.6 Implementation: Software, Guidelines and Case Study 127 4.2 Disclosure Risk Assessment I: Primary Sensitive Cells 128 4.2.1 Intruder Scenarios 128 4.2.2 Sensitivity rules 129 4.3 Disclosure Risk Assessment II: Secondary risk assessment 140 4.3.1 Feasibility Interval 141 4.3.2 Protection Level 142 4.3.3 Singleton and multi cell disclosure 143 4.3.4 Risk models for hierarchical and linked tables 144 4.4 Non-Perturbative Protection Methods 145 4.4.1 Global Recoding 145 4.4.2 The Concept of Cell Suppression 145 4.4.3 Algorithms for Secondary Cell Suppression 146 4.4.4 Secondary Cell Suppression in Hierarchical and Linked Tables 149 4.5 Perturbative Protection Methods 151 4.5.1 A pre-tabular method: Multiplicative Noise 152 4.5.2 A Post-tabular Method: Controlled Tabular Adjustment 153 4.6 Information Loss Measures for Tabular Data 153 4.6.1 Cell Costs for Cell Suppression 153 4.6.2 Cell Costs for CTA 154 4.6.3 Information Loss Measures to Evaluate the Outcome of Table Protection 155 4.7 Software for Tabular Data Protection 155 4.7.1 Empirical comparison of cell suppression algorithms 156 4.8 Guidelines: Setting up an efficient table model systematically 160 4.8.1 Defining Spanning Variables 161 4.8.2 Response Variables and Mapping Rules 162 4.9 Case Studies 164 4.9.1 Response Variables and Mapping Rules of the Case Study 164 4.9.2 Spanning Variables of the Case Study 165 4.9.3 Analysing the Tables of the Case Study 165 4.9.4 Software Issues of the Case Study 167 5 Frequency tables 169 5.1 Introduction 169 5.2 Disclosure risks 169 5.3 Methods 176 5.4 Post-tabular methods 178 5.4.1 Cell Suppression 178 5.4.2 ABS Cell Perturbation 179 5.4.3 Rounding 179 5.5 Information loss 184 5.6 Software 186 5.6.1 Introduction 186 5.7 Case Studies 188 5.7.1 UK Census 188 5.7.2 Australian and New Zealand Censuses 190 6 Data Access Issues 193 6.1 Introduction 193 6.2 Research Data Centres 193 6.3 Remote Execution 194 6.4 Remote Access 195 6.5 Licensing 196 6.6 Guidelines on output checking 196 6.6.1 Introduction 196 6.6.2 General approach 197 6.6.3 Rules for output checking 199 6.6.4 Organizational/procedural aspects of output checking 208 6.6.5 Researcher training 215 6.7 Additional issues concerning data access 218 6.7.1 Examples of disclaimers 218 6.7.2 Output description 218 6.8 Case Studies 219 6.8.1 The U.S. …”
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L'université en réseau : Les 25 ans de l'Université du Québec / by Ferretti, Lucia

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Cometh the hour / by Archer, Jeffrey

Cometh the hour / by Archer, Jeffrey

Multicriteria decision aid and artificial intelligence links, theory and applications / by Doumpos, Michael

Table of Contents: “…s Method 7.5 Discussion 7.6 Conclusion References Part Four Multiobjective Optimization 8 Interactive Approaches Applied to Multiobjective Evolutionary Algorithms 8.1 Introduction 8.1.1 Methods Analyzed in this Chapter 8.2 Basic Concepts and Notation 8.2.1 Multiobjective Optimization Problems 8.2.2 Classical Interactive Methods 8.3 MOEAs Based on Reference Point Methods 8.3.1 A Weighted Distance Metric 8.3.2 Light Beam Search Combined with NSGA-II 8.3.3 Controlling the Accuracy of the Pareto Front Approximation 8.3.4 Light Beam Search Combined with PSO 8.3.5 A Preference Relation Based on a Weighted Distance Metric 8.3.6 The Chebyshev Preference Relation 8.4 MOEAs Based on Value Function Methods 8.4.1 Progressive Approximation of a Value Function 8.4.2 Value Function by Ordinal Regression 8.5 Miscellaneous Methods 8.5.1 Desirability Functions 8.6 Conclusions and Future Work References 9 Generalized DEA and Computational Intelligence in Multiple Criteria Decision Making 9.1 Introduction 9.2 Generalized Data Envelopment Analysis 9.2.1 Basic DEA Models: CCR, BCC and FDH Models 9.2.2 GDEA Model 9.3 Generation of Pareto Optimal Solutions using Generalized DEA and Computational Intelligence 9.3.1 GDEA in Fitness Evaluation 9.3.2 GDEA in Deciding the Parameters of Multi-objective PSO 9.3.3 Expected Improvement for Multi-objective Optimization Using GDEA 9.4 Summary References 10 Fuzzy Multiobjective Optimization 10.1 Introduction 10.2 Solution Concepts for Multiobjective Programming 10.3 Interactive Multiobjective Linear Programming 10.4 Fuzzy Multiobjective Linear Programming 10.5 Interactive Fuzzy Multiobjective Linear Programming 10.6 Interactive Fuzzy Multiobjective Linear Programming with Fuzzy Parameters 10.7 Interactive Fuzzy Stochastic Multiobjective Linear Programming 10.8 Related Works and Applications References Part Five Applications in Management and Engineering 11 MCDA & Agents: Supporting Effective Resource Federation in Virtual Organizations 11.1 Introduction 11.2 The Intuition of Multiple Criteria Decision Aid in Multi-agent Systems 11.3 Resource Federation Applied 11.3.1 Describing the Problem in a Cloud Computing Context 11.3.2 Problem Modeling 11.3.3 Assessing Agents' Value Function for Resource Federation 11.4 An Illustrative Example 11.5 Conclusions References 12 Fuzzy AHP Using Type II Fuzzy Sets: An Application to Warehouse Location Selection 12.1 Introduction 12.2 Multicriteria Selection 12.2.1 The ELECTRE (&Eacute;limination Et Choix Traduisant la Realite) Method 12.2.2 PROMETHEE (Preference Ranking Organization Method for Enrichment Evaluations) 12.2.3 TOPSIS (Technique for Order Preference by Similarity to Ideal Situation) 12.2.4 The WSM (Weighted Sum Model) Method 12.2.5 MAUT (Multi-attribute Utility Theory) 12.2.6 AHP (Analytic Hierarchy Process) 12.3 Literature Review on Fuzzy AHP 12.4 Buckley's Type-1 Fuzzy AHP 12.5 Type-2 Fuzzy Sets 12.6 Type-2 Fuzzy AHP 12.7 An Application: Warehouse Location Selection 12.8 Conclusion References 13 Applying Genetic Algorithms to Optimize Energy Efficiency in Buildings 13.1 Introduction 13.2 State-of-the-Art Review 13.3 An Example Case Study 13.3.1 Basic Principles and Problem Definition 13.3.2 Decision Variables 13.3.3 Decision Criteria 13.3.4 Decision Model 13.4 Development and Application of a Genetic Algorithm for the Example Case Study 13.4.1 Development of the Genetic Algorithm 13.4.2 Application of the Genetic Algorithm, Analysis of Results and Discussion 13.5 Conclusions References 14 Nature-Inspired Intelligence for Pareto Optimality Analysis in Portfolio Optimization 14.1 Introduction 14.2 Literature Review 14.3 Methodological Issues 14.4 Pareto Optimal Sets in Portfolio Optimization 14.4.1 Pareto Efficiency 14.4.2 Mathematical Formulation of the Portfolio Optimization Problem 14.5 Computational Results 14.5.1 Experimental Setup 14.5.2 Efficient Frontier 14.6 Conclusion References Index.…”
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Design and fabrication of self-powered micro-harvesters : rotating and vibrated micro-power systems / by Pan, C. T., Hwang, Y. M., Lin, Liwei, Chen, Yingzhong

Table of Contents: “…Machine generated contents note: About the Authors xi Preface xiii Acknowledgments xv 1 Introduction 1 1.1 Background 1 1.2 Energy Harvesters 2 1.2.1 Piezoelectric ZnO Energy Harvester 3 1.2.2 Vibrational Electromagnetic Generators 3 1.2.3 Rotary Electromagnetic Generators 4 1.2.4 NFES Piezoelectric PVDF Energy Harvester 4 1.3 Overview 5 2 Design and Fabrication of Flexible Piezoelectric Generators Based on ZnO Thin Films 7 2.1 Introduction 7 2.2 Characterization and Theoretical Analysis of Flexible ZnO-Based Piezoelectric Harvesters 10 2.2.1 Vibration Energy Conversion Model of Film-Based Flexible Piezoelectric Energy Harvester 10 2.2.2 Piezoelectricity and Polarity Test of Piezoelectric ZnO Thin Film 12 2.2.3 Optimal Thickness of PET Substrate 15 2.2.4 Model Solution of Cantilever Plate Equation 15 2.2.5 Vibration-Induced Electric Potential and Electric Power 18 2.2.6 Static Analysis to Calculate the Optimal Thickness of the PET Substrate 19 2.2.7 Model Analysis and Harmonic Analysis 21 2.2.8 Results of Model Analysis and Harmonic Analysis 23 2.3 The Fabrication of Flexible Piezoelectric ZnO Harvesters on PET Substrates 27 2.3.1 Bonding Process to Fabricate UV-Curable Resin Lump Structures on PET Substrates 27 2.3.2 Near-Field Electro-Spinning with Stereolithography Technique to Directly Write 3D UV-Curable Resin Patterns on PET Substrates 29 2.3.3 Sputtering of Al and ITO Conductive Thin Films on PET Substrates 29 2.3.4 Deposition of Piezoelectric ZnO Thin Films by Using RF Magnetron Sputtering 31 2.3.5 Testing a Single Energy Harvester under Resonant and Non-Resonant Conditions 34 2.3.6 Application of ZnO/PET-Based Generator to Flash Signal LED Module 39 2.3.7 Design and Performance of a Broad Bandwidth Energy Harvesting System 40 2.4 Fabrication and Performance of Flexible ZnO/SUS304-Based Piezoelectric Generators 48 2.4.1 Deposition of Piezoelectric ZnO Thin Films on Stainless Steel Substrates 48 2.4.2 Single-Sided ZnO/SUS304-Based Flexible Piezoelectric Generator 50 2.4.3 Double-Sided ZnO/SUS304-Based Flexible Piezoelectric Generator 51 2.4.4 Characterization of ZnO/SUS304-Based Flexible Piezoelectric Generators 52 2.4.5 Structural and Morphological Properties of Piezoelectric ZnO Thin Films on Stainless Steel Substrates 54 2.4.6 Analysis of Adhesion of ZnO Thin Films on Stainless Steel Substrates 56 2.4.7 Electrical Properties of Single-Sided ZnO/SUS304-Based Flexible Piezoelectric Generator 59 2.4.8 Characterization of Double-Sided ZnO/SUS304-Based Flexible Piezoelectric Generator: Analysis and Modification of Back Surface of SUS304 61 2.4.9 Electrical Properties of Double-Sided ZnO/SUS304-Based Piezoelectric Generator 63 2.5 Summary 66 References 67 3 Design and Fabrication of Vibration-Induced Electromagnetic Microgenerators 71 3.1 Introduction 71 3.2 Comparisons between MCTG and SMTG 74 3.2.1 Magnetic Core-Type Generator (MCTG) 74 3.2.2 Sided Magnet-Type Generator (SMTG) 76 3.3 Analysis of Electromagnetic Vibration-Induced Microgenerators 76 3.3.1 Design of Electromagnetic Vibration-Induced Microgenerators 77 3.3.2 Analysis Mode of the Microvibration Structure 78 3.3.3 Analysis Mode of Magnetic Field 81 3.3.4 Evaluation of Various Parameters of Power Output 84 3.4 Analytical Results and Discussion 88 3.4.1 Analysis of Bending Stress within the Supporting Beam of the Spiral Microspring 90 3.4.2 Finite Element Models for Magnetic Density Distribution 93 3.4.3 Power Output Evaluation 97 3.5 Fabrication of Microcoil for Microgenerator 103 3.5.1 Microspring and Induction Coil 103 3.5.2 Microspring and Magnet 105 3.6 Tests and Experiments 106 3.6.1 Measurement System 106 3.6.2 Measurement Results and Discussion 107 3.6.3 Comparison between Measured Results and Analytical Values 110 3.7 Conclusions 112 3.7.1 Analysis of Microgenerators and Vibration Mode and Simulation of the Magnetic Field 112 3.7.2 Fabrication of LTCC Microsensor 112 3.7.3 Measurement and Analysis Results 113 3.8 Summary 113 References 114 4 Design and Fabrication of Rotary Electromagnetic Microgenerator 117 4.1 Introduction 117 4.1.1 Piezoelectric, Thermoelectric, and Electrostatic Generators 119 4.1.2 Vibrational Electromagnetic Generators 119 4.1.3 Rotary Electromagnetic Generators 120 4.1.4 Generator Processes 121 4.1.5 Lithographie Galvanoformung Abformung Process 122 4.1.6 Winding Processes 123 4.1.7 LTCC 123 4.1.8 Printed Circuit Board Processes 124 4.1.9 Finite-Element Simulation and Analytical Solutions 126 4.2 Case 1: Winding Generator 126 4.2.1 Design 127 4.2.2 Analytical Formulation 132 4.2.3 Simulation 134 4.2.4 Fabrication Process 138 4.2.5 Results and Discussion (1) 139 4.2.6 Results and Discussion (2) 142 4.3 Case 2: LTCC Generator 146 4.3.1 Simulation 147 4.3.2 Analytical Theorem of Microgenerator Electromagnetism 148 4.3.3 Simplification 152 4.3.4 Analysis of Vector Magnetic Potential 153 4.3.5 Analytical Solutions for Power Generation 154 4.4 Fabrication 157 4.4.1 LTCC Process 157 4.4.2 Magnet Process 159 4.4.3 Measurement Set-up 160 4.5 Results and Discussion 162 4.5.1 Design 162 4.5.2 Analytical Solutions 168 4.5.3 Fabrication 170 References 178 5 Design and Fabrication of Electrospun PVDF Piezo-Energy Harvesters 183 5.1 Introduction 183 5.2 Fundamentals of Electrospinning Technology 187 5.2.1 Introduction to Electrospinning 187 5.2.2 Alignment and Assembly of Nanofibers 190 5.3 Near-Field Electrospinning 191 5.3.1 Introduction and Background 191 5.3.2 Principles of Operation 194 5.3.3 Process and Experiment 196 5.3.4 Summary 202 5.4 Continuous NFES 202 5.4.1 Introduction and Background 202 5.4.2 Principles of Operation 202 5.4.3 Controllability and Continuity 205 5.4.4 Process Characterization 208 5.4.5 Summary 211 5.5 Direct-Write Piezoelectric Nanogenerator 211 5.5.1 Introduction and Background 211 5.5.2 Polyvinylidene Fluoride 212 5.5.3 Theoretical Studies for Realization of Electrospun PVDF Nanofibers 213 5.5.4 Electrospinning of PVDF Nanofibers 216 5.5.5 Detailed Discussion of Process Parameters 219 5.5.6 Experimental Realization of PVDF Nanogenerator 223 5.5.7 Summary 241 5.6 Materials, Structure, and Operation of Nanogenerator with Future Prospects 241 5.6.1 Material and Structural Characteristics 241 5.6.2 Operation of Nanogenerator 243 5.6.3 Summary and Future Prospects 248 5.7 Case Study: Large-Array Electrospun PVDF Nanogenerators on a Flexible Substrate 248 5.7.1 Introduction and Background 248 5.7.2 Working Principle 249 5.7.3 Device Fabrication 249 5.7.4 Experimental Results 251 5.7.5 Summary 252 5.8 Conclusion 253 5.8.1 Near-Field Electrospinning 253 5.8.2 Continuous Near-Field Electrospinning 254 5.8.3 Direct-Write Piezoelectric PVDF 254 5.9 Future Directions 255 5.9.1 NFES Integrated Nanofiber Sensors 255 5.9.2 NFES One-Dimensional Sub-Wavelength Waveguide 256 5.9.3 NFES Biological Applications 257 5.9.4 Direct-Write Piezoelectric PVDF Nanogenerators 258 References 258 Index 265.…”
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CRYPTO WARS the fight for privacy in the digital age. by Jarvis, Craig

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Semiconductor laser engineering, reliability and diagnostics a practical approach to high power and single mode devices / by Epperlein, Peter W.

Table of Contents: “…Machine generated contents note: Dedication Preface About the Author PART I: DIODE LASER ENGINEERING Overview 1. Basic Diode Laser Engineering Principles Introduction 1.1. …”
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Web scalability for startup engineers : tips & techniques for scaling your Web application / by Ejsmont, Artur

Law, Privacy and Surveillance in Canada in the Post-Snowden Era /

Table of Contents: “…Obar -- Forgotten surveillance : covert human intelligence sources in Canada in a post-9/11 world / Steve Hewitt -- Foreign intelligence in an inter-networked world : time for a re-evaluation / Tamir Israel -- Lawful illegality : what Snowden has taught us about the legal infrastructure of the surveillance state / Lisa M. …”
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Law, Privacy and Surveillance in Canada in the Post-Snowden Era /

Table of Contents: “…Obar -- Forgotten surveillance : covert human intelligence sources in Canada in a post-9/11 world / Steve Hewitt -- Foreign intelligence in an inter-networked world : time for a re-evaluation / Tamir Israel -- Lawful illegality : what Snowden has taught us about the legal infrastructure of the surveillance state / Lisa M. …”
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Understanding aerodynamics arguing from the real physics / by McLean, Doug, 1943-

Table of Contents: “…10.6 Integrated forces and the components of drag 10.7 Solution visualization 10.8 Things a user should know about any CFD code before running it References.…”
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