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“…Philosophers like to fill in the X with something exotic like a bat or a dolphin, or even an Artificial Intelligence, while poets tend to fill it with something else, equally exotic, namely themselves. For the diffident and introspective author of A Rushed Quality and Bodying Forth, the X, while definitely human, is perhaps someone in general, equally distant from and equally intimate with both the writer and the reader in the very moment of their eponymous activity. …”

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“…Gender equality and the environment are treated as cross-cutting issues in all DAC peer reviews in recognition of their importance in development co-operation. …”

“…This report asseses gender equality and women's empowerment in the Austrian labour market. …”

“…Kann suggests that the founders committed themselves in theory to the democratic proposition that all men were created free and equal and could not be governed without their own consent, but that they in no way believed that "all men" could be trusted with equal liberty, equal citizenship, or equal authority. …”

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Conectar con la versión electrónica

Tabla de Contenidos: “…Corrective Justice-based Moral Reasoning -- 7.2.4. The Theory of Equality and Corrective Justice -- 7.2.5. Virtue Ethics and Moral Reasoning -- 7.2.6. …”

Tabla de Contenidos: “…4.3.1 - Newton-Raphson algorithm -- 4.3.2 - Expectation-maximization algorithm -- 4.4 - Approximation of random effects in linear mixed models -- 4.4.1 - Best linear unbiased prediction -- 4.4.2 - Shrinkage and reliability -- 4.5 - Hypothesis testing on variance component G -- 4.6 - Empirical illustrations: linear mixed models with REML -- 4.6.1 - Linear mixed model on effectiveness of acupuncture treatment on PCL score -- 4.6.2 - Linear mixed model on marital status and disability among older Americans -- 4.7 - Summary -- Chapter 5 - Patterns of residual covariance structure -- 5.1 - Residual covariance pattern models with equal spacing -- 5.1.1 - Compound symmetry (CS) -- 5.1.2 - Unstructured pattern (UN) -- 5.1.3 - Autoregressive structures - AR(1) and ARH(1) -- 5.1.4 - Toeplitz structures - TOEP and TOEPH -- 5.2 - Residual covariance pattern models with unequal time intervals -- 5.2.1 - Spatial power model - SP(POW) -- 5.2.2 - Spatial exponential model - SP(EXP) -- 5.2.3 - Spatial Gaussian model - SP(GAU) -- 5.2.4 - Hybrid residual covariance model -- 5.3 - Comparison of covariance structures -- 5.4 - Scaling of time as a classification factor -- 5.4.1 - Scaling approaches for classification factors -- 5.4.2 - Coding schemes of time as a classification factor -- 5.5 - Least squares means, local contrasts, and local tests -- 5.5.1 - Least squares means -- 5.5.2 - Local contrasts and local tests -- 5.6 - Empirical illustrations: estimation of two linear regression models -- 5.6.1 - Linear regression model on effectiveness of acupuncture treatment on PCL score -- 5.6.2 - Linear regression model on marital status and disability severity among older Americans -- 5.7 - Summary -- Chapter 6 - Residual and influence diagnostics -- 6.1 - Residual diagnostics -- 6.1.1 - Types of residuals in linear regression models…”

Tabla de Contenidos: “…5.5.1 Distribution-Free Two-Sided Prediction Intervals to Contain at Least k of m Future Observations -- 5.5.2 Distribution-Free One-Sided Prediction Bounds to Exceed or Be Exceeded by at Least k of m Future Observations -- Bibliographic Notes -- Chapter 6 Statistical Intervals for a Binomial Distribution -- Objectives and Overview -- 6.1 Introduction -- 6.1.1 The Binomial Distribution -- 6.1.2 Other Distributions and Related Notation -- 6.1.3 Notation for Data and Inference -- 6.1.4 Binomial Distribution Statistical Interval Properties -- 6.1.5 Two Examples, Motivation, and a Caution -- 6.2 Confidence Intervals for the Actual Proportion Nonconforming in the Sampled Distribution -- 6.2.1 Preliminaries -- 6.2.2 The Conservative Method -- 6.2.3 The Wald (Normal Theory) Approximate Method -- 6.2.4 The Agresti--Coull Adjusted Wald-Approximation Method -- 6.2.5 The Jeffreys Approximate Method -- 6.2.6 Comparisons and Recommendations -- 6.3 Confidence Interval for the Proportion of Nonconforming Units in a Finite Population -- 6.3.1 The Conservative Method -- 6.3.2 Large-Population Approximate Method -- 6.4 Confidence Intervals for the Probability that The Number of Nonconforming Units in a Sample is Less than or Equal to (or Greater Than) a Specified Number -- 6.5 Confidence Intervals for the Quantile of the Distribution of the Number of Nonconforming Units -- 6.5.1 Two-Sided Confidence Interval for yp -- 6.5.2 One-Sided Confidence Bounds for yp -- 6.6 Tolerance Intervals and One-Sided Tolerance Bounds for the Distribution of the Number of Nonconforming Units -- 6.6.1 One-Sided Lower Tolerance Bound for a Binomial Distribution -- 6.6.2 One-Sided Upper Tolerance Bound for a Binomial Distribution -- 6.6.3 Two-Sided Tolerance Interval for a Binomial Distribution -- 6.6.4 Calibrating Tolerance Intervals…”

Tabla de Contenidos: “…Gains from Trade -- 2.1 Theory of Comparative Advantage -- 2.2 Factor Price Equalization -- 2.3 Other Benefits of Free Trade -- 3. …”

Tabla de Contenidos: “…8.2.2 Universal Theme Behind Human Action-Reaction Processes -- 8.2.3 Human Action-Reaction Process: Never Equal and Opposite -- 8.3 Iterative Convergence for Optimization -- 8.4 Knowledge Machine Programming for a Given Objective -- Conclusions -- Appendix 8 A -- References -- 9 Frustums of Artificial Behavior -- 9.1 Introduction -- 9.1.1 Artificial Knowledge -- 9.1.2 Mechanized Generation of Knowledge -- 9.2 Frustums and Their Volume -- 9.3 The Degeneration of Knowledge -- 9.4 Content-Based Internet Knowledge Filters -- 9.5 General Deployment of Knowledge Filters -- Conclusions -- References -- 10 Computer-Aided Knowledge Design and Validation -- 10.1 Introduction -- 10.2 Major Procedural Steps -- 10.2.1 Fragment the Input Seminal Body of Knowledge Bok -- 10.2.2 Internet-Based Dds/Loc Search for Classification of Vfs, *S, Nos -- 10.2.2.1 Determine and list nos, Vfs, and *S of bok, local, and internet -- 10.2.2.2 Compare NOs, VFs, and *s of bok, local, and internet -- 10.2.2.3 Filtering of NOs, VFs, *s, and concepts that tie them -- 10.2.2.4 Rationality and contextual check of NOs, VFs, and *s -- 10.2.2.5 Scoring and quality based on internet KB's -- 10.2.2.6 Evaluate and grade the inputs -- 10.2.2.7 Threshold limits and probabilities -- 10.3 Blend and Process Input, Local, and Internet Knowledge -- 10.3.1 Relax Nos, Relax Vfs, and Relax *S -- 10.3.2 Iterative Techniques for the Computer-Based Solutions -- 10.3.3 Iterative Convergence of Parameters Within Micro Kels -- 10.4 Generate Newly Synthesized Knowledge - Bok' -- 10.4.1 Relaxation of Attributes, Attributes of Attributes -- 10.4.2 Machine-Based Reassembly of Newly Designed Knowledge - Bok' -- 10.4.3 Verify the Validity of the Newly Designed Knowledge - Bok' -- 10.5 Rationality and Scoring of New Knowledge - Bok' -- 10.6 Machine Configurations…”

Tabla de Contenidos: “…Solution -- Example 2 -- Solution -- Example 3 -- Solution -- Example 4 -- Solution -- 7.4.1 The law of sines -- Example 1 -- Solution -- 7.4.2 The law of cosines -- Example 1 -- Solution -- 7.4 EXERCISES -- CHAPTER 7 REVIEW EXERCISES -- 8 - Matrices, Determinants, and Vectors -- INTRODUCTION -- 8.1 MATRICES -- Example 1 -- Solution -- Example 2 -- Solution -- Outline placeholder -- Outline placeholder -- 8.1.1 Operations with matrices and their properties -- 8.1.1.1 Equality of matrices -- Example 1 -- Solution -- 8.1.1.2 Addition of matrices -- 8.1.1.3 Subtraction of matrices -- Example 1 -- Solution -- 8.1.1.4 Additive identity matrix (zero matrix) -- Example 1 -- 8.1.1.5 Additive inverse (negative) matrix -- Example 1 -- 8.1.1.6 Commutative property of matrix addition -- Example 1 -- 8.1.1.7 Associative property of matrix addition -- Example 1 -- 8.1.1.8 Product of constant (scalar) and a matrix -- Example 1 -- 8.1.1.9 Product of two matrices -- Example 1 -- 8.1.1.10 Multiplicative identity matrix -- Example 1 -- 8.1.1.11 Multiplicative inverse matrix -- Example 1 -- Solution -- Method 1 -- Method 2 -- 8.1.1.12 Transpose of a matrix -- Example 1 -- 8.1.1.13 Symmetric matrix -- Example 1 -- 8.1 EXERCISES -- 8.2 DETERMINANTS -- Example 1 -- Solution -- Example 2 -- Solution -- Example 3 -- Solution -- Example 4 -- Solution -- Example 5 -- Solution -- 8.2 EXERCISES -- 8.3 VECTORS -- Example 1 -- Solution -- 8.3.1 Vector operations -- Example 1 -- Solution -- Example 2 -- Solution -- 8.3.2 Standard unit vectors -- Example 1 -- Solution -- Example 2 -- Solution -- Example 3 -- Solution -- 8.3.3 The dot product -- Example 1 -- Solution -- Example 2 -- Solution -- Example 3 -- Solution -- Example 4 -- Solution -- Example 5 -- Solution -- 8.3.4 Work -- Example 1 -- Solution -- Example 2 -- Solution -- 8.3 EXERCISES -- CHAPTER 8 REVIEW EXERCISES…”

Tabla de Contenidos: “…-- Conventions Used in This Book -- Comments and Questions -- Acknowledgments -- Queries -- 1.1 Specify Query Criteria at Runtime -- Problem -- Solution -- Discussion -- 1.2 Using a Form-Based Parameter Query -- Problem -- Solution -- Discussion -- 1.3 Limit the Items in One Combo Box Based on the Selected Item in Another -- Problem -- Solution -- Discussion -- See Also -- 1.4 Make Formatted Date Columns Sort Correctly in a Crosstab Query -- Problem -- Solution -- Discussion -- 1.5 Group Mailing Labels by Address -- Problem -- Solution -- Discussion -- See Also -- 1.6 Use a Field in One Table to Update a Field in Another Table -- Problem -- Solution -- Discussion -- 1.7 Use a VBA Variable to Filter a Query -- Problem -- Solution -- Discussion -- See Also -- 1.8 Use a Query to Retrieve a Random Set of Rows -- Problem -- Solution -- Discussion -- 1.9 Create a Query That Will Show Aging of Receivables -- Problem -- Solution -- Discussion -- See Also -- 1.10 Create a Join That's Based on a Comparison Other than Equality -- Problem -- Solution -- Discussion -- 1.11 Create a Query to Combine Data from Two Tables with Similar Structures -- Problem -- Solution -- Discussion -- 1.12 Create a Combo Box That Allows a User to Select N/A -- Problem -- Solution…”

Tabla de Contenidos: “…. -- 10 -- Challenges -- To educate communities in solidarity, equality, environmental importance, and green habits (as reuse, recycling and self-made skills)…”