1.

Record Nr.

UNINA9911019636103321

Titolo

Chemistry and technology of surfactants / / edited by Richard J. Farn

Pubbl/distr/stampa

Oxford ; ; Ames, Iowa, : Blackwell Pub., 2006

ISBN

9786610748273

9781280748271

1280748273

9780470988596

0470988592

9781405171793

1405171790

Descrizione fisica

1 online resource (338 p.)

Altri autori (Persone)

FarnRichard J

Disciplina

541/.33

Soggetti

Surface chemistry

Surface active agents

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Note generali

Description based upon print version of record.

Nota di bibliografia

Includes bibliographical references and index.

Nota di contenuto

Chemistry and Technology of Surfactants; Contents; Contributors; Preface; Glossary; 1 What Are Surfactants?; 1.1 History and applications of surfactants; 1.1.1 Introduction; 1.1.2 Properties and other criteria influencing surfactant choice; 1.1.3 Surfactant applications; 1.1.4 Conclusion; Appendix: Application guide; 1.2 Surfactant market overview: importance in different industries; 1.2.1 Introduction; 1.2.2 Consumer; 1.2.3 Industrial; 2 The Basic Theory; 2.1 Molecular structure of surfactants; 2.2 Surface activity; 2.2.1 Surface tension; 2.2.2 Interfacial tension

2.2.3 Surface and interfacial tension reduction2.2.4 Test methods for surface and interfacial tension measurements; 2.3 Self-assembled surfactant aggregates; 2.3.1 Micelles and critical micelle concentration; 2.3.2 Aggregate structures and shapes; 2.4 Adsorption of surfactants at surfaces; 2.4.1 Adsorption at liquid-gas and liquid-liquid interfaces; 2.4.2 Adsorption at liquid-solid interface; Acknowledgement; References; 3 Applied Theory of Surfactants; 3.1 Introduction; 3.2 Detergency; 3.2.1 Fundamental processes; 3.2.2 Basic formulae of



detergents and cleansers

3.2.3 Adsorption at the solid-liquid interface3.2.4 Surface tension and wetting; 3.2.5 Interplay of surfactants with other detergent ingredients; 3.3 Phase behaviour of surfactants; 3.3.1 Introduction; 3.3.2 Surfactant phases; 3.3.3 Impact of the phase behaviour on detergency; 3.4 Emulsions; 3.4.1 Introduction; 3.4.2 Emulsion types; 3.4.3 Breakdown of emulsions; 3.5 Foaming and defoaming; 3.5.1 Introduction; 3.5.2 Stabilising effects in foams; 3.5.3 Correlation of foamability with interfacial parameters; 3.5.4 Foam control; 3.6 Rheology of surfactant solutions; 3.6.1 Introduction

3.6.2 Rheological terms3.6.3 Rheological behaviour of monomeric solutions and non-interacting micelles; 3.6.4 Entanglement networks of rod-like micelles; 3.6.5 The rheological behaviour of bilayer phases; References; 4 Anionic Surfactants; 4.1 Sulphonates; 4.1.1 Alkylbenzene sulphonates; 4.1.2 a-Olefin sulphonates; 4.1.3 Paraffin sulphonates; 4.1.4 Sulphonated methyl esters; 4.1.5 Sulphonated fatty acids; 4.1.6 Sulphosuccinates; 4.2 Sulphates; 4.2.1 Alkyl sulphates; 4.2.2 Alkyl ether sulphates; 4.3 Phosphate esters; 4.4 Carboxylates; 4.4.1 Soap; 4.4.2 Ether carboxylates

4.4.3 Acyl sarcosinates4.4.4 Alkyl phthalamates; 4.4.5 Isethionates; 4.4.6 Taurates; References; 5 Non-ionic Surfactants; 5.1 Introduction; 5.2 General alkoxylation reactions; 5.3 Alkyl phenol ethoxylates; 5.4 Fatty alcohol ethoxylates; 5.5 Polyoxethylene esters of fatty acids; 5.6 Methyl ester ethoxylates; 5.7 Polyalkylene oxide block co-polymers; 5.8 Amine ethoxylates; 5.9 Fatty alkanolamides; 5.10 Amine oxides; 5.11 Esters of polyhydric alcohols and fatty acids; 5.12 Glycol esters; 5.13 Glycerol esters; 5.14 Polyglycerol esters; 5.15 Anhydrohexitol esters

5.16 Polyoxyalkylene polyol esters

Sommario/riassunto

Surfactants are used throughout industry as components in a huge range of formulated products or as effect chemicals in the production or processing of other materials. A detailed understanding of the basis of their activity is required by all those who use surfactants, yet the new graduate or postgraduate chemist or chemical engineer will generally have little or no experience of how and why surfactants work.  Chemistry & Technology of Surfactants is aimed at new graduate or postgraduate level chemists and chemical engineers at the beginning their industrial careers and those in l



2.

Record Nr.

UNINA9910957758803321

Autore

Moraga Paula

Titolo

Geospatial health data : modeling and visualization with R-INLA and Shiny / / Paula Moraga

Pubbl/distr/stampa

Boca Raton : , : CRC Press, , 2020

ISBN

1-000-73215-0

1-000-73203-7

0-429-34182-2

Edizione

[1st ed.]

Descrizione fisica

1 online resource (295 pages)

Collana

Chapman & Hall/CRC biostatistics series

Disciplina

614.42

Soggetti

Medical mapping

Lingua di pubblicazione

Inglese

Formato

Materiale a stampa

Livello bibliografico

Monografia

Nota di contenuto

Cover -- Half Title -- Title Page -- Copyright Page -- Dedication -- Table of Contents -- Preface -- About the author -- I: Geospatial health data and INLA -- 1: Geospatial health -- 1.1 Geospatial health data -- 1.2 Disease mapping -- 1.3 Communication of results -- 2: Spatial data and R packages for mapping -- 2.1 Types of spatial data -- 2.1.1 Areal data -- 2.1.2 Geostatistical data -- 2.1.3 Point patterns -- 2.2 Coordinate reference systems -- 2.2.1 Geographic coordinate systems -- 2.2.2 Projected coordinate systems -- 2.2.3 Setting Coordinate Reference Systems in R -- 2.3 Shapefiles -- 2.4 Making maps with -- 2.4.1 ggplot2 -- 2.4.2 leaflet -- 2.4.3 mapview -- 2.4.4 tmap -- 3: Bayesian inference and INLA -- 3.1 Bayesian inference -- 3.2 Integrated nested Laplace approximation -- 4: The R-INLA package -- 4.1 Linear predictor -- 4.2 The inla() function -- 4.3 Priors specification -- 4.4 Example -- 4.4.1 Data -- 4.4.2 Model -- 4.4.3 Results -- 4.5 Control variables to compute approximations -- II: Modeling and visualization -- 5: Areal data -- 5.1 Spatial neighborhood matrices -- 5.2 Standardized incidence ratio -- 5.3 Spatial small area disease risk estimation -- 5.3.1 Spatial modeling of lung cancer in Pennsylvania -- 5.4 Spatio-temporal small area disease risk estimation -- 5.5 Issues with areal data -- 6: Spatial modeling of areal data. Lip cancer in Scotland -- 6.1 Data and map -- 6.2 Data preparation -- 6.2.1 Adding data to map -- 6.3 Mapping SIRs -- 6.4



Modeling -- 6.4.1 Model -- 6.4.2 Neighborhood matrix -- 6.4.3 Inference using INLA -- 6.4.4 Results -- 6.5 Mapping relative risks -- 6.6 Exceedance probabilities -- 7: Spatio-temporal modeling of areal data. Lung cancer in Ohio -- 7.1 Data and map -- 7.2 Data preparation -- 7.2.1 Observed cases -- 7.2.2 Expected cases -- 7.2.3 SIRs -- 7.2.4 Adding data to map -- 7.3 Mapping SIRs.

7.4 Time plots of SIRs -- 7.5 Modeling -- 7.5.1 Model -- 7.5.2 Neighborhood matrix -- 7.5.3 Inference using INLA -- 7.6 Mapping relative risks -- 8: Geostatistical data -- 8.1 Gaussian random fields -- 8.2 Stochastic partial differential equation approach -- 8.3 Spatial modeling of rainfall in ParanĂ¡, Brazil -- 8.3.1 Model -- 8.3.2 Mesh construction -- 8.3.3 Building the SPDE model on the mesh -- 8.3.4 Index set -- 8.3.5 Projection matrix -- 8.3.6 Prediction data -- 8.3.7 Stack with data for estimation and prediction -- 8.3.8 Model formula -- 8.3.9 inla() call -- 8.3.10 Results -- 8.3.11 Projecting the spatial field -- 8.4 Disease mapping with geostatistical data -- 9: Spatial modeling of geostatistical data. Malaria in The Gambia -- 9.1 Data -- 9.2 Data preparation -- 9.2.1 Prevalence -- 9.2.2 Transforming coordinates -- 9.2.3 Mapping prevalence -- 9.2.4 Environmental covariates -- 9.3 Modeling -- 9.3.1 Model -- 9.3.2 Mesh construction -- 9.3.3 Building the SPDE model on the mesh -- 9.3.4 Index set -- 9.3.5 Projection matrix -- 9.3.6 Prediction data -- 9.3.7 Stack with data for estimation and prediction -- 9.3.8 Model formula -- 9.3.9 inla() call -- 9.4 Mapping malaria prevalence -- 9.5 Mapping exceedance probabilities -- 10: Spatio-temporal modeling of geostatistical data. Air pollution in Spain -- 10.1 Map -- 10.2 Data -- 10.3 Modeling -- 10.3.1 Model -- 10.3.2 Mesh construction -- 10.3.3 Building the SPDE model on the mesh -- 10.3.4 Index set -- 10.3.5 Projection matrix -- 10.3.6 Prediction data -- 10.3.7 Stack with data for estimation and prediction -- 10.3.8 Model formula -- 10.3.9 inla() call -- 10.3.10 Results -- 10.4 Mapping air pollution predictions -- III: Communication of results -- 11: Introduction to R Markdown -- 11.1 R Markdown -- 11.2 YAML -- 11.3 Markdown syntax -- 11.4 R code chunks -- 11.5 Figures -- 11.6 Tables -- 11.7 Example.

12: Building a dashboard to visualize spatial data with flexdashboard -- 12.1 The R package flexdashboard -- 12.1.1 R Markdown -- 12.1.2 Layout -- 12.1.3 Dashboard components -- 12.2 A dashboard to visualize global air pollution -- 12.2.1 Data -- 12.2.2 Table using DT -- 12.2.3 Map using leaflet -- 12.2.4 Histogram using ggplot2 -- 12.2.5 R Markdown structure. YAML header and layout -- 12.2.6 R code to obtain the data and create the visualizations -- 13: Introduction to Shiny -- 13.1 Examples of Shiny apps -- 13.2 Structure of a Shiny app -- 13.3 Inputs -- 13.4 Outputs -- 13.5 Inputs, outputs and reactivity -- 13.6 Examples of Shiny apps -- 13.6.1 Example -- 13.6.2 Example -- 13.7 HTML content -- 13.8 Layouts -- 13.9 Sharing Shiny apps -- 14: Interactive dashboards with flexdashboard and Shiny -- 14.1 An interactive dashboard to visualize global air pollution -- 15: Building a Shiny app to upload and visualize spatio-temporal data -- 15.1 Shiny -- 15.2 Setup -- 15.3 Structure of app.R -- 15.4 Layout -- 15.5 HTML content -- 15.6 Read data -- 15.7 Adding outputs -- 15.7.1 Table using DT -- 15.7.2 Time plot using dygraphs -- 15.7.3 Map using leaflet -- 15.8 Adding reactivity -- 15.8.1 Reactivity in dygraphs -- 15.8.2 Reactivity in leaflet -- 15.9 Uploading data -- 15.9.1 Inputs in ui to upload a CSV file and a shapefile -- 15.9.2 Uploading CSV file in server() -- 15.9.3 Uploading shapefile in server() -- 15.9.4 Accessing the data and the map -- 15.10 Handling missing inputs -- 15.10.1 Requiring input files to be available using req() -- 15.10.2 Checking data are uploaded before creating the map -- 15.11



Conclusion -- 16: Disease surveillance with SpatialEpiApp -- 16.1 Installation -- 16.2 Use of SpatialEpiApp -- 16.2.1 'Inputs' page -- 16.2.2 'Analysis' page -- 16.2.3 'Help' page -- Appendix -- A: R installation and packages used in the book.

A.1 Installing R and RStudio -- A.2 Installing R packages -- A.3 Packages used in the book -- Bibliography -- Index.

Sommario/riassunto

"This book shows how to model disease risk and quantify risk factors using areal and geostatistical data. It also shows how to create interactive maps of disease risk and risk factors, and describes how to build interactive dashboards and Shiny web applications that facilitate the communication of insights to collaborators and policy makers"--