Tabla de Contenidos: “…. -- NOTES -- REFERENCES -- 4 The Patient Population -- INCIDENCE AND PREVALENCE -- COMPOSITION OF THE ESRD POPULATION -- MORTALITY ISSUES -- Unadjusted Mortality -- Adjusted Mortality -- Subgroup Mortality -- STATE AND REGIONAL MORTALITY DATA -- CROSS-NATIONAL MORTALITY DATA -- PROJECTIONS TO THE YEAR 20006 -- NOTES -- REFERENCES -- 5 The ESRD Patient Population: Special Groups -- PEDIATRIC PATIENTS -- ELDERLY ESRD PATIENTS -- DIABETIC PATIENTS -- HYPERTENSIVE PATIENTS -- Hypertension in the United States -- Relationship Between Hypertension and Hypertensive ESRD -- Epidemiology of ESRD Attributed to Hypertension…”

“…Cross-border integration intensified following the opening of a fixed-link bridge/tunnel in 2000. …”

Tabla de Contenidos: “…10.3.2 Post-Filters 257 -- 10.3.3 Post-Filter Types 257 -- 10.3.4 Estimating Post-Filters with Machine Learning 259 -- 10.3.5 Post-Filter Design Based on Spatial Parameters 259 -- References 261 -- 11 Cross-Spectrum-Based Post-Filter Utilizing Noisy and Robust Beamformers 265 /Symeon Delikaris-Manias and Ville Pulkki -- 11.1 Introduction 265 -- 11.2 Notation and Signal Model 267 -- 11.2.1 Virtual Microphone Design Utilizing Pressure Microphones 268 -- 11.3 Estimation of the Cross-Spectrum-Based Post-Filter 269 -- 11.3.1 Post-Filter Estimation Utilizing Two Static Beamformers 270 -- 11.3.2 Post-Filter Estimation Utilizing a Static and an Adaptive Beamformer 272 -- 11.3.3 Smoothing Techniques 277 -- 11.4 Implementation Examples 279 -- 11.4.1 Ideal Conditions 279 -- 11.4.2 Prototype Microphone Arrays 281 -- 11.5 Conclusions and Further Remarks 283 -- 11.6 Source Code 284 -- References 287 -- 12 Microphone-Array-Based Speech Enhancement Using Neural Networks /Pasi Pertila 291 -- 12.1 Introduction 291 -- 12.2 Time–Frequency Masks for Speech Enhancement Using Supervised Learning 293 -- 12.2.1 Beamforming with Post-Filtering 293 -- 12.2.2 Overview of Mask Prediction 294 -- 12.2.3 Features for Mask Learning 295 -- 12.2.4 Target Mask Design 297 -- 12.3 Artificial Neural Networks 298 -- 12.3.1 Learning the Weights 299 -- 12.3.2 Generalization 301 -- 12.3.3 Deep Neural Networks 305 -- 12.4 Mask Learning: A Simulated Example 305 -- 12.4.1 Feature Extraction 306 -- 12.4.2 Target Mask Design 306 -- 12.4.3 Neural Network Training 307 -- 12.4.4 Results 308 -- 12.5 Mask Learning: A Real-World Example 310 -- 12.5.1 Brief Description of the Third CHiME Challenge Data 310 -- 12.5.2 Data Processing and Beamforming 312 -- 12.5.3 Description of Network Structure, Features, and Targets 312 -- 12.5.4 Mask Prediction Results and Discussion 314 -- 12.5.5 Speech Enhancement Results 316 -- 12.6 Conclusions 318 -- 12.7 Source Code 318 -- 12.7.1 Matlab Code for Neural-Network-Based Sawtooth Denoising Example 318.…”

Tabla de Contenidos: “…3.3.3.2 Game Perspective: How to Play Nash in Alternation -- 3.3.3.3 Cross Fertilization Between Game and Mathematical Perspectives -- 3.4 Variational Rationality: How Human Dynamics Work? …”

Tabla de Contenidos: “…Growth Rates in the Postwar Period -- CROSS-COUNTRY DIFFERENCES IN GROWTH ACCOUNTING RATES -- SUMMARY -- KEY TERMS -- REVIEW QUESTIONS -- PROBLEMS -- DATA ANALYSIS PROBLEMS -- Chapter 6 Appendix THE ALGEBRA OF THE SOLOW GROWTH MODEL -- SOLVING FOR THE STEADY STATE -- SUMMARY AND RESULTS -- REVIEW QUESTIONS AND PROBLEMS -- Chapter 6 Web Appendix THE GOLDEN RULE LEVEL OF THE CAPITAL-LABOR RATIO -- Chapter 7 DRIVERS OF GROWTH: TECHNOLOGY, POLICY, AND INSTITUTIONS -- PREVIEW -- TECHNOLOGY AS A PRODUCTION INPUT -- Technology Versus Conventional Production Inputs -- Technology and Excludability -- POLICIES TO PROMOTE PRODUCTIVITY -- Building Infrastructure -- Increasing Human Capital -- POLICY AND PRACTICE: Government Measures to Increase Human Capital -- Encouraging Research and Development -- INSTITUTIONS AND PROPERTY RIGHTS -- The Legal System and Property Rights -- Geography, the Legal System, and Economic Growth -- Obstacles to Effective Property Rights -- POLICY AND PRACTICE: The World Bank's Doing Business -- POLICY AND PRACTICE: Does Foreign Aid Work? …”

Tabla de Contenidos: “…Elasticity Along a Linear Demand Curve -- Total Revenue and Elasticity -- Your Expenditure and Your Elasticity -- More Elasticities of Demand -- Income Elasticity of Demand -- Cross Elasticity of Demand -- Elasticity of Supply -- Calculating the Elasticity of Supply -- The Factors That Influence the Elasticity of Supply -- Economics in Action -- Economics in the News -- Worked Problem -- Summary -- Key Points -- Key Terms -- Study Plan Problems and Applications -- Additional Problems and Applications -- Chapter 5 ◆ Efficiency And Equity -- Resource Allocation Methods -- Market Price -- Command -- Majority Rule -- Contest -- First-Come, First-Served -- Lottery -- Personal Characteristics -- Force -- Benefit, Cost, and Surplus -- Demand, Willingness to Pay, and Value -- Individual Demand and Market Demand -- Consumer Surplus -- Supply and Marginal Cost -- Supply, Cost, and Minimum Supply-Price -- Individual Supply and Market Supply -- Producer Surplus -- Is the Competitive Market Efficient? …”

Tabla de Contenidos: “…Calculating Price Elasticity of Demand -- Inelastic and Elastic Demand -- The Factors that Influence the Elasticity of Demand -- Elasticity Along a Linear Demand Curve -- Total Revenue and Elasticity -- Your Expenditure And Your Elasticity -- More Elasticities Of Demand -- Income Elasticity Of Demand -- Cross Elasticity Of Demand -- Elasticity of Supply -- Calculating the Elasticity of Supply -- The Factors That Influence the Elasticity of Supply -- Economics in Action -- Economics in the News -- Worked Problem -- Summary -- Key Points -- Key Terms -- Study Plan Problems and Applications -- Additional Problems and Applications -- Chapter 5 Economics in the News and Equity -- Resource Allocation Methods -- Market Price -- Command -- Majority Rule -- Contest -- First-Come, First-Served -- Lottery -- Personal Characteristics -- Force -- Benefit, Cost, and Surplus -- Demand, Willingness to Pay, and Value -- Individual Demand and Market Demand -- Consumer Surplus -- Supply and Marginal Cost -- Supply, Cost, and Minimum Supply-Price -- Individual Supply and Market Supply -- Producer Surplus -- Is the Competitive Market Efficient? …”

Tabla de Contenidos: “…Rewrapping instead of state changing -- Computing Spearman rank-order correlation -- Polymorphism and type-pattern matching -- Summary -- Chapter 8: The Itertools Module -- Working with the infinite iterators -- Counting with count() -- Counting with float arguments -- Re-iterating a cycle with cycle() -- Repeating a single value with repeat() -- Using the finite iterators -- Assigning numbers with enumerate() -- Running totals with accumulate() -- Combining iterators with chain() -- Partitioning an iterator with groupby() -- Merging iterables with zip_longest() and zip() -- Filtering with compress() -- Picking subsets with islice() -- Stateful filtering with dropwhile() and takewhile() -- Two approaches to filtering with filterfalse() and filter() -- Applying a function to data via starmap() and map() -- Cloning iterators with tee() -- The itertools recipes -- Summary -- Chapter 9: More Itertools Techniques -- Enumerating the Cartesian product -- Reducing a product -- Computing distances -- Getting all pixels and all colors -- Performance analysis -- Rearranging the problem -- Combining two transformations -- Permuting a collection of values -- Generating all combinations -- Recipes -- Summary -- Chapter 10: The Functools Module -- Function tools -- Memoizing previous results with lru_cache -- Defining classes with total ordering -- Defining number classes -- Applying partial arguments with partial() -- Reducing sets of data with the reduce() function -- Combining map() and reduce() -- Using the reduce() and partial() functions -- Using the map() and reduce() functions to sanitize raw data -- Using the groupby() and reduce() functions -- Summary -- Chapter 11: Decorator Design Techniques -- Decorators as higher-order functions -- Using the functools update_wrapper() functions -- Cross-cutting concerns -- Composite design -- Preprocessing bad data…”