Tabla de Contenidos: “…Billy Beane -- Bill James -- Stats Take Over -- 6 Human Behavior -- Prospect Theory -- Emotional Intelligence -- Neuro-Linguistic Programming -- Trading Tribe -- Curiosity, Not PhDs -- Commitment -- 7 Decision Making -- Occam's Razor -- Fast and Frugal Decision Making -- Innovator's Dilemma -- Process versus Outcome versus Gut -- 8 The Scientific Method -- Critical Thinking -- Linear versus Nonlinear -- Compounding -- 9 Holy Grails -- Buy and Hope -- Warren Buffett -- Losers Average Losers -- Avoiding Stupidity -- 10 Trading Systems -- Risk, Reward, and Uncertainty -- Five Questions -- What Do You Buy or Sell? …”

Tabla de Contenidos: “…Tape building blocks -- 4.1 SAN readiness -- 4.2 LTO tape subsystems -- 4.2.1 Ultrium -- 4.2.2 The IBM LTO Ultrium family of tapes and libraries -- 4.2.3 IBM 3580 Ultrium tape drive -- 4.2.4 IBM 3581 Ultrium tape autoloader -- 4.2.5 IBM 3582 Ultrium Scalable tape library -- 4.2.6 IBM 3583 Ultrium Scalable tape library -- 4.2.7 IBM 3584 UltraScalable tape library -- 4.2.8 IBM 3600 Series LTO tape automation family -- 4.3 IBM TotalStorage MP 3570 and 3575 -- 4.3.1 IBM 3570 drive and autoloader -- 4.3.2 IBM 3575 library -- 4.4 IBM TotalStorage 3590 -- 4.4.1 IBM TotalStorage 3590 tape drives -- 4.4.2 IBM 3590 cartridges -- 4.4.3 IBM 3590 Model A60 ESCON and FICON control unit -- 4.4.4 IBM TotalStorage 3592 tape drives -- 4.4.5 IBM 3592 cartridges -- 4.4.6 IBM TotalStorage 3494 Virtual Tape Server -- 4.5 Digital Linear Tape and SuperDLT -- 4.5.1 IBM 3502 DLT tape library family -- 4.6 Other tape libraries -- 4.7 SAN readiness summary -- Chapter 5. …”

Tabla de Contenidos: “…-- Using DataFrames with MLlib -- Examining the spark-linear-regression.py script -- Getting results -- Spark Streaming and GraphX -- What is Spark Streaming? …”

Tabla de Contenidos: “…Chapter 17: Creating Spatial 3D User Interface Game Objects -- Setting Up a Straight Menu Pointer -- Setting Up Clickable Spatial 3D Buttons -- Setting Up a Spatial Button Group -- Changing the Appearance of Your Spatial Button -- Creating a Spatial Toggle Button -- Creating Spatial Option Buttons -- Interacting Directly with VRTK's Spatial Buttons -- Creating a Spatial Slider -- Hacking Your Straight Spatial Menu Pointer to Interact with Your Slider -- Summary -- Chapter 18: Using Unity's UI Controls with the VRTK -- Downloading and Importing Unity Package Files -- Setting Up the UI Elements 2D Skeletal Menu -- Setting Up a Straight 2D UI Menu Pointer -- Having the 2D UI Menu Pointer Interact with the 2D UI Menu System -- Summary -- Chapter 19: Angular Drives -- Setting Up a Steering Wheel -- Setting Up a Door -- Setting Up a Lever -- Angular Joint Drive and Logic Objects -- Summary -- Chapter 20: Linear Drives -- Setting Up a Drawer -- Setting Up a Push Button -- Summary -- Chapter 21: Tips, Tricks, and Recipes -- Adding Realistic Physical Hands -- Obtaining Haptic Feedback -- Highlighting Interactable Game Objects -- Summary -- Chapter 22: Minigame -- Importing the Base Unity Package -- Setting Up the VRTK Prefabs -- Enabling Obstacle Objects to Attach to the Ball -- Getting the Ball to Roll About Freely -- Spatial Tooltip to Display Countdown Timer -- Setting Up the Countdown Timer and Moment Processor -- Enhancing the Minigame -- Summary -- Index…”

Tabla de Contenidos: “…Cover -- Title Page -- Copyright and Credits -- Packt Upsell -- Contributors -- Table of Contents -- Preface -- Chapter 1: Deep Learning - Architectures and Frameworks -- Deep learning -- Activation functions for deep learning -- The sigmoid function -- The tanh function -- The softmax function -- The rectified linear unit function -- How to choose the right activation function -- Logistic regression as a neural network -- Notation -- Objective -- The cost function -- The gradient descent algorithm -- The computational graph -- Steps to solve logistic regression using gradient descent -- What is xavier initialization? …”

Tabla de Contenidos: “…3.4 Precision of Monte Carlo Method -- 3.4.1 Monitoring Mean and Variance -- 3.4.2 Importance Sampling -- 3.4.3 Correlated Samples -- 3.4.4 Variance Reduction Methods -- 3.5 Markov Chains -- 3.5.1 Markov Processes -- 3.5.2 Discrete Time, Discrete State Space -- 3.5.3 Transition Probability -- 3.5.4 "Sun City" -- 3.5.5 Utility Bills -- 3.5.6 Classification of States -- 3.5.7 Stationary Distribution -- 3.5.8 Reversibility Condition -- 3.5.9 Markov Chains with Continuous State Spaces -- 3.6 Simulation of a Markov Chain -- 3.7 Applications -- 3.7.1 Bank Sizes -- 3.7.2 Related Failures of Car Parts -- References -- 4 Markov Chain Monte Carlo Methods -- 4.1 Markov Chain Simulations for Sun City and Ten Coins -- 4.2 Metropolis-Hastings Algorithm -- 4.3 Random Walk MHA -- 4.4 Gibbs Sampling -- 4.5 Diagnostics of MCMC -- 4.5.1 Monitoring Bias and Variance of MCMC -- 4.5.2 Burn-in and Skip Intervals -- 4.5.3 Diagnostics of MCMC -- 4.6 Suppressing Bias and Variance -- 4.6.1 Perfect Sampling -- 4.6.2 Adaptive MHA -- 4.6.3 ABC and Other Methods -- 4.7 Time-to-Default Analysis of Mortgage Portfolios -- 4.7.1 Mortgage Defaults -- 4.7.2 Customer Retention and Infinite Mixture Models -- 4.7.3 Latent Classes and Finite Mixture Models -- 4.7.4 Maximum Likelihood Estimation -- 4.7.5 A Bayesian Model -- References -- PART II Modeling Dependence -- 5 Statistical Dependence Structures -- 5.1 Introduction -- 5.2 Correlation -- 5.2.1 Pearson's Linear Correlation -- 5.2.2 Spearman's Rank Correlation -- 5.2.3 Kendall's Concordance -- 5.3 Regression Models -- 5.3.1 Heteroskedasticity -- 5.3.2 Nonlinear Regression -- 5.3.3 Prediction -- 5.4 Bayesian Regression -- 5.5 Survival Analysis -- 5.5.1 Proportional Hazards -- 5.5.2 Shared Frailty -- 5.5.3 Multistage Models of Dependence -- 5.6 Modeling Joint Distributions -- 5.6.1 Bivariate Survival Functions -- 5.6.2 Bivariate Normal…”

Tabla de Contenidos: “…-- 15.2 Cats again -- 15.3 Feature scaling -- 15.4 Feature selection and reduction -- 15.5 Clustering -- 15.6 Classification -- 15.7 Linear regression -- 15.8 Concepts of neural networks -- 15.9 Quantum machine learning -- 15.10 Summary -- Appendices -- Appendix A: Tools -- A.1 The operating system command line -- A.2 Installing Python -- A.3 Installing Python modules and packages -- A.4 Installing a virtual environment -- A.5 Installing the Python packages used in this book -- A.6 The Python interpreter -- A.7 IDLE -- A.8 Visual Studio Code -- A.9 Jupyter notebooks -- A.10 Installing and setting up Qiskit -- A.11 The IBM Quantum Composer and Lab -- A.12 Linting -- Appendix B: Staying Current -- B.1 python.org -- B.2 qiskit.org -- B.3 Python expert sites -- B.4 Asking questions and getting answers -- Appendix C: The Complete UniPoly Class -- Appendix D: The Complete Guitar Class Hierarchy -- Appendix E: Notices -- E.1 Photos, images, and diagrams -- E.2 Data -- E.3 Trademarks -- E.4 Python 3 license -- Appendix F: Production Notes…”

Tabla de Contenidos: “…Calculations -- 6.3 Sequential Circuits Vector Joystick Envelope Modulation -- 6.4 Linear Frequency Modulation with LFO or EG -- 6.5 BPM Sync -- 6.6 Quantizing -- 6.7 Ramp Modulation: Fade-in and Fade-out -- 6.8 Pitch Calculation -- 6.9 Pulse-Width Modulation (PWM) -- 6.10 Phase Distortion -- 6.11 Hard Sync -- 6.12 Filter Key Track Modulation -- Bibliography -- 7 Envelope Generators and DCA -- 7.1 Envelope Generator Fundamentals -- 7.2 EG Implementation: Finite State Machine -- 7.3 Digital EG Implementation: Rendering the Output -- 7.4 Biased EG Output -- 7.5 Analog EG Emulation -- 7.6 Synth Module: EnvelopeGenerator -- 7.7 EG Retrigger Modulation -- 7.8 EG Core Programming Notes -- 7.9 The Digitally Controlled Amplifier (DCA) -- 7.10 Exercises -- Bibliography -- 8 Low Frequency Oscillators -- 8.1 Noise Oscillators and Generators -- 8.2 Oscillator Clocking -- 8.3 LFO Waveforms and Rendering Equations -- 8.4 Render Modes -- 8.5 Waveform Shaping -- 8.6 Delay and Fade-in Times -- 8.7 Starting Phase -- 8.8 DC Offset -- 8.9 SynthLFO and Cores -- 8.10 LFO Core Programming Notes -- 8.11 Exercises -- Bibliography -- 9 Wavetable Oscillators -- 9.1 Wavetable Fundamentals: Table Lookup -- 9.2 Wavetable Objects and Database -- 9.3 Wavetable Sources and Database -- 9.4 WTOscillator and Cores -- 9.5 Wavetable Core Programming Notes -- 9.6 Exercises -- Bibliography -- 10 Virtual Analog Oscillators -- 10.1 VA Oscillator Fundamentals -- 10.2 Band Limited Impulse Train (BLIT) -- 10.3 Band Limited Step (BLEP) -- 10.4 Polynomial BLEP Approximation -- 10.5 Choosing the BLEP sinc Source -- 10.6 Other VA Algorithms -- 10.7 BLEP Square Wave -- 10.8 VAOscillator and Core -- 10.9 VA Core Programming Notes -- 10.10 Exercises -- Bibliography -- 11 PCM Sample Playback Oscillators -- 11.1 PCM Sample Playback Modes -- 11.2 PCM Sample Storage -- 11.3 Loading PCM Samples…”

Tabla de Contenidos: “…La distribution du patrimoine est bien plus inégale que celle des revenus. -- 2.2. Inégalités en matière de bien-être -- 2.2.1 On observe des écarts très importants pour diverses dimensions du bien-être. -- 2.2.2. …”

Tabla de Contenidos: “…4 Spending autonomy and public sector performance across levels of government -- Introduction -- Expenditure shares, spending power and fiscal autonomy -- Measuring subnational autonomy through expenditure shares -- Developing spending autonomy indicators -- Defining the indicators -- Levels of government -- Spending power of subnational decision makers -- Questionnaire scope and methodology -- Country questionnaire responses -- Computing spending autonomy indicators -- Spending power in health -- Overall results -- Policy decisions in health care -- Budgeting decisions in health care -- Labour and input decisions in health care -- Output and monitoring decisions in health care -- Comparing responsibilities between different aspects of health spending autonomy -- Spending power in other sectors -- Housing -- Education -- Long-term care -- Transport services -- Extending the indicators: Computing composite indicators with uncertainty -- The effects of decentralisation on service provision -- The non-linear impact of decentralisation in health care -- The impact of decentralisation in other sectors -- Benchmarking and monitoring of public sector performance -- Indicators to measure performance -- Measuring costs -- Composite indicators of performance -- Consumer experience and satisfaction surveys -- Systems to measure and assess performance -- Collegiate systems -- Competitive systems -- The role of "tailored" institutions for evaluation and oversight -- The relevant institutions -- References -- Note -- 5 Digitalisation challenges and opportunities for subnational governments -- Introduction -- Opportunities -- On the revenue side -- Taxation of consumption -- Subnational taxation of incomes -- Property taxes -- User fees -- Promoting voluntary compliance -- On the spending side -- Use of sensors in the delivery of public services…”

Tabla de Contenidos: “…Structures and Structural Design -- The Hierarchy of Structures and Their Components -- Physical Structures -- Cable Structures: Using Cables as the Main Member Type -- Skeletal Structures: Using Beam-Type Members -- Spatial Structures: Using the Membrane/Plate/Shell-Type Members -- Solid Structures: Using the Solid-Type Members -- Mixed Structures: Using One or More of the Basic Element Types -- Structural Members -- Member Cross-Sections -- The Structural Materials -- Designing the Structures -- The Design Objectives and Philosophy-A Historical Overview -- The Role of Building Codes -- Historical Development -- Disaster Resilience and Environmental Sustainability in Building Codes -- Typical Structural Design Process -- Analysis and Design Levels -- Traditional Approaches to Structural Design -- Working Stress Design -- Ultimate Strength Design -- Limit State Design Concept -- Shortcomings of Traditional Building Codes -- From Force-Based to Displacement-Based Design -- The Performance-Based Design -- The Building Blocks of Structural Mechanics -- Basic Concepts and Relationships -- The Concept of Stiffness -- The Structural Equilibrium and Role of Stiffness -- The Nonlinearity of Response and Stiffness -- The Concept of Degree of Freedom (DOF) -- Member Cross-Sections and the DOFs -- DOFs, Deformations, Strains, and Stresses -- Stress Resultants and DOFs -- Linear, Elastic Stiffness Relationships -- Deformations for Applied Actions: Flexibility Relationships -- Restraining Actions for Assumed Deformations -- The Member Stiffness and Cross-Sectional Properties -- Cross-Sectional Analysis and Design -- The Significance of Cross-Sections in Design Process -- Cross-Sectional Analysis…”

Tabla de Contenidos: “…Cover -- Copyright and Credits -- Packt Upsell -- Foreword -- Contributors -- Table of Contents -- Preface -- Chapter 1: Getting Started -- Understanding deep learning -- Perceptron -- Activation functions -- Sigmoid -- The hyperbolic tangent function -- The Rectified Linear Unit (ReLU) -- Artificial neural network (ANN) -- One-hot encoding -- Softmax -- Cross-entropy -- Dropout -- Batch normalization -- L1 and L2 regularization -- Training neural networks -- Backpropagation -- Gradient descent -- Stochastic gradient descent -- Playing with TensorFlow playground -- Convolutional neural network -- Kernel -- Max pooling -- Recurrent neural networks (RNN) -- Long short-term memory (LSTM) -- Deep learning for computer vision -- Classification -- Detection or localization and segmentation -- Similarity learning -- Image captioning -- Generative models -- Video analysis -- Development environment setup -- Hardware and Operating Systems - OS -- General Purpose - Graphics Processing Unit (GP-GPU) -- Computer Unified Device Architecture - CUDA -- CUDA Deep Neural Network - CUDNN -- Installing software packages -- Python -- Open Computer Vision - OpenCV -- The TensorFlow library -- Installing TensorFlow -- TensorFlow example to print Hello, TensorFlow -- TensorFlow example for adding two numbers -- TensorBoard -- The TensorFlow Serving tool -- The Keras library -- Summary -- Chapter 2: Image Classification -- Training the MNIST model in TensorFlow -- The MNIST datasets -- Loading the MNIST data -- Building a perceptron -- Defining placeholders for input data and targets -- Defining the variables for a fully connected layer -- Training the model with data -- Building a multilayer convolutional network -- Utilizing TensorBoard in deep learning -- Training the MNIST model in Keras -- Preparing the dataset -- Building the model…”

Tabla de Contenidos: “…Transforming data into a usable form -- Simple text cleaning -- Removing stop words -- Finding words in text -- Finding and replacing text -- Data imputation -- Subsetting data -- Sorting text -- Data validation -- Validating data types -- Validating dates -- Validating e-mail addresses -- Validating ZIP codes -- Validating names -- Cleaning images -- Changing the contrast of an image -- Smoothing an image -- Brightening an image -- Resizing an image -- Converting images to different formats -- Summary -- Chapter 4: Data Visualization -- Understanding plots and graphs -- Visual analysis goals -- Creating index charts -- Creating bar charts -- Using country as the category -- Using decade as the category -- Creating stacked graphs -- Creating pie charts -- Creating scatter charts -- Creating histograms -- Creating donut charts -- Creating bubble charts -- Summary -- Chapter 5: Statistical Data Analysis Techniques -- Working with mean, mode, and median -- Calculating the mean -- Using simple Java techniques to find mean -- Using Java 8 techniques to find mean -- Using Google Guava to find mean -- Using Apache Commons to find mean -- Calculating the median -- Using simple Java techniques to find median -- Using Apache Commons to find the median -- Calculating the mode -- Using ArrayLists to find multiple modes -- Using a HashMap to find multiple modes -- Using a Apache Commons to find multiple modes -- Standard deviation -- Sample size determination -- Hypothesis testing -- Regression analysis -- Using simple linear regression -- Using multiple regression -- Summary -- Chapter 6: Machine Learning -- Supervised learning techniques -- Decision trees -- Decision tree types -- Decision tree libraries -- Using a decision tree with a book dataset -- Testing the book decision tree -- Support vector machines -- Using an SVM for camping data…”

Tabla de Contenidos: “…Missing It -- Wag the Dog -- The Ethnographic Examples -- Muddying the Waters: The Case of Cassandra -- Missing It: The Case of SSgt Michaels -- Wag the Dog: The Case of Fedor the Troll -- Conclusion -- References -- Chapter 10 Using Neuroimaging to Predict Behavior: An Overview with a Focus on the Moderating Role of Sociocultural Context -- Introduction -- The Brain‐as‐Predictor Approach -- Predicting Individual Behaviors -- Interpreting Associations Between Brain Activation and Behavior -- Predicting Aggregate Out‐of‐Sample Group Outcomes -- Predicting Social Interactions and Peer Influence -- Sociocultural Context -- Future Directions -- Conclusion -- References -- Chapter 11 Social Models from Non-Human Systems -- Emergent Patterns in Groups of Behaviorally Flexible Individuals -- From Bird Motivations to Human Applications -- Game‐Theoretic Model of Frequency‐Dependent Tactic Choice -- Mathematical Model as Behavioral Microscope on Carefully Prepared Birds -- Transferable Insights from Behavioral Games to Human Groups -- Model Systems for Understanding Group Competition -- Social Spiders as Model Systems for Understanding Personality in Groups -- Ants as Model Systems for Understanding the Costs and Benefits of Specialization -- Personality and Specialization: From Nonhuman to Human Groups -- Information Dynamics in Tightly Integrated Groups -- Linear and Nonlinear Recruitment Dynamics -- Herd Behavior and Information Cascades in Ants -- From Ants to Human Decision Support Systems -- Additional Examples: Rationality and Memory -- Conclusions -- Acknowledgments -- References -- Chapter 12 Moving Social‐Behavioral Modeling Forward: Insights from Social Scientists -- Why Do People Do What They Do? …”

Tabla de Contenidos: “…Deconstructing a Sound for Procedural Use -- Scalability -- Modulation/Modifiers for Variation -- Pitch -- Reuse Sounds for Different Sized Sources -- Transformative Reuse -- Pitch Envelopes -- Volume -- One-shot Volume Envelopes -- Looping Volume Envelopes -- Oscillation -- Wavetables -- Parameterization = Interactivity -- Swapping out Sounds with -Branch- -- Parameters to Pitch with &lt -- Set Pitch Multiplier&gt -- -- Parameter-based Crossfades with -Crossfade by Param- -- Using User-defined Curves -- Monitoring Memory and Level Streaming Approaches -- Asset Checking -- Memory Checking -- Level Streaming -- Sound Streaming -- Conclusion -- 03 Music Part A: Quick Start -- Introduction -- Interactive Music Principles -- Playlists -- Level Music, Loops, and Decay Tails -- Decay Tails -- Loop with Integrated Decay -- Play Then Loop -- Looping Manually -- Stingers/Ornamental Forms -- Simple Parallel Forms -- Simple Transitional Forms -- Conclusion -- 04 Music Part B: Basics and Parallel Forms -- Introduction -- Music Basics -- Source Music -- One-shots -- Music for Timed Events -- Ornamental Forms/Stingers -- Parallel Forms -- Switching or Fading Layers (Parallel Forms for Orientation) -- Using Variables to Determine Volume (Parallel Forms for Proximity) -- Linear Variables to Volume -- Curves to Volume -- Mix Automation for Parallel Layers -- Conclusion -- 05 Music Part C: Transitional Forms -- Introduction -- Clunky Transitions -- Nasty -- Crossfades (and When to Use Them) -- Masking Transitions -- Musical Transitions -- Working with Chunks: Measure-based Transitions -- Decay Tails Revisited -- Controlling a Switch -- Transitioning on Measure in Longer Pieces -- Pre-syncs or Ramps -- Aligned Transitions -- Putting It Together -- A Musical Conclusion -- 06 Dialogue -- Introduction -- Randomization -- Better than Random? …”

Tabla de Contenidos: “…Chapter 12 Hybrid Aircraft Aerodynamics and Aerodynamic Design Considerations of Hover-to-Dash Convertible UAVs -- 12.1 Why Hover-to-Dash Conversion is Important -- 12.2 Aircraft Mission Profiles and Sizing Chart Structure -- 12.3 Convertible Coleopter Design, Wind Tunnel and Flight Testing -- 12.4 Future: Convertible QuadCopter Design and Flight Testing -- 12.5 The Extreme: Hover-to-Supersonic Dash Aircraft -- References -- PART II Novel Concepts in Unmanned Aircraft Flight Stability and Control -- 2.1 Fixed-wing (airplanes) -- Chapter 13 Closed-loop Active Flow Control for UAVs -- 13.1 Introduction -- 13.2 Objectives -- 13.3 Actuators -- 13.4 Linear System -- 13.5 Plant Model Identification -- 13.6 Controller Architecture -- 13.7 Conclusions -- Acknowledgement -- References -- Chapter 14 Autonomous Gust Alleviation in UAVs -- 14.1 Introduction -- 14.2 The Composite Spar -- 14.3 The Energy-harvesting and Storage Component -- 14.4 Reduced Energy Control Law -- 14.5 Gust Modelling -- 14.6 Experimental Validation -- 14.7 Performance -- 14.8 Other Considerations -- 14.9 Summary and Discussion -- Acknowledgement -- References -- Chapter 15 Virtual Flight Simulation using Computational Fluid Dynamics -- 15.1 Introduction -- 15.2 Aerodynamic Model for Flight Simulation -- 15.3 Generation of Tabular Aerodynamic Model -- 15.4 Time-accurate CFD for Flight Simulations -- 15.5 Conclusions -- References -- Chapter 16 Flow Structure Modification Using Plasma Actuation for Enhanced UAV Flight Control -- 16.1 Introduction -- 16.2 Aerodynamic Flow Control -- 16.3 Plasma Actuators -- 16.4 Dielectric Barrier Discharge -- 16.5 Experimental Setup -- 16.6 Results and Analysis -- 16.7 Conclusions -- Acknowledgments -- References -- Chapter 17 Constrained Motion Planning and Trajectory Optimization for Unmanned Aerial Vehicles -- 17.1 Introduction…”

Tabla de Contenidos: “…La genèse d'un signe de justice urbain -- L'invention du pilori et de sa peine associée -- Un nouveau mot pour une nouvelle institution -- Un terreau fertile : les rituels d'humiliation publique antérieurs au pilori -- Enquête lexicographique : des mots, une institution -- Flandres, Artois, Picardie, Normandie : espaces et causes d'apparition du pilori -- L'influence des mutations économiques et sociales du XIIe siècle -- Une marque de protection et de propriété du marché -- Une institution au service de la "vengeance commune", des bourgeois ? -- Une distribution inégale des premiers piloris : des lenteurs de Flandre-Hainaut aux succès du Ponthieu -- Des disparités d'implantation dans les grandes villes drapantes -- La transmission de la charte d'Abbeville : des piloris de village pour armer les marchés locaux ? …”

Tabla de Contenidos: “…8.5 Concluding Remarks -- Appendix A (Proofs) -- Appendix B (Tables) -- Acknowledgement -- References -- 9 Mathematical Modeling of Regulation of Sulfur Metabolic Pathways -- 9.1 Introduction -- 9.2 Review of Literature -- 9.3 Materials and Methods -- 9.3.1 Materials -- 9.3.2 Methods -- 9.4 Results -- 9.4.1 KEGG Reported S-biochemical Pathways -- 9.4.2 Construction of S-biochemical Network -- 9.4.3 Model Formulation -- 9.4.4 Steady State Behavior of S-biochemical System -- 9.4.5 Parameter Dependency of the S-biochemical System -- 9.4.6 Initial Condition Dependency of the S-biochemical System -- 9.4.7 Flipping Dynamics of Sulfate and Sulfide -- 9.4.8 Elementary Flux Modes -- 9.5 Conclusion -- References -- 10 Some Results on Quasi-convergence in Gradual Normed linear Spaces -- 10.1 Introduction: Background and Driving Forces -- 10.2 Preliminaries -- 10.3 Main Results -- 10.4 Conclusion -- References -- 11 On Einstein Gyrogroup -- 11.1 Introduction -- 11.2 Preliminaries -- 11.2.1 Gyrogroup and its Main Properties -- 11.2.2 Einstein's Addition of Relativistically Admissible Velocities -- 11.3 Gyrations: Repairing the Breakdown of Classical Laws -- References -- 12 On the Norms of Toeplitz and Hankel Matrices with Balancing and Lucas-balancing Numbers -- 12.1 Introduction -- 12.1.1 Norms and Bounds for Spectral Norm -- 12.2 Main Results -- 12.2.1 Bounds on Norms for Toeplitz Matrices -- 12.2.2 Norms on Hankel Matrices -- 12.3 Numerical Experiments -- 12.4 Concluding Remarks -- Acknowledgment -- References -- 13 Grey Wolf Optimizer for the Design Optimization of a DC-DC Buck Converter -- 13.1 Introduction -- 13.2 Algorithms for Optimization -- 13.2.1 Grey Wolf Optimizer -- 13.2.2 Moth Flame Optimization -- 13.2.3 Particle Swarm Optimization -- 13.2.4 Simulated Annealing -- 13.2.5 Firefly Algorithm…”