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1. |
Record Nr. |
UNINA9910790288603321 |
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Titolo |
Fast food / / edited by Justin Healey |
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Pubbl/distr/stampa |
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Thirroul, NSW, : Spinney Press, 2012 |
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ISBN |
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Descrizione fisica |
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1 online resource (60 pages) : colour illustrations |
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Collana |
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Issues in society ; ; v. 343 |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Convenience foods |
Nutrition |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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Nota di contenuto |
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Chapter 1. Fast food and nutrition -- Chapter 2. Junk food marketing to children |
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Sommario/riassunto |
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Australians spend about a third of their weekly household food budget on food prepared outside the home. These meals tend to be fast food and take-away, which are often high in saturated fats, salt and sugar. Excessive consumption of fast food contributes to obesity, heart disease and a range of other conditions. 'Junk food' should only be eaten occasionally, this includes potato chips, soft drinks, chocolates and sweets, cakes, and take-away food like fried chicken, pizza, hotdogs, fries and hamburgers. Fast Food is a helpful guide to better informed dietary choices, and features detailed advice on the nutritional contents of Australia's major fast food products, including kilojoule counts, portion sizes and packaging information. What are the healthy alternatives to fast food? Should the government introduce traffic light labelling, or even a 'fat tax'? This book also examines the debate over food marketing to children. Should Australia ban junk food advertising aimed at children, who so often resort to 'pester power'? In a nation where a quarter of the population is now obese, are Australians finally fed up with junk food marketing that targets children? |
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2. |
Record Nr. |
UNINA9910877813003321 |
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Autore |
Jutten Christian |
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Titolo |
Source Separation in Physical-Chemical Sensing |
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Pubbl/distr/stampa |
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Newark : , : John Wiley & Sons, Incorporated, , 2023 |
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©2024 |
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ISBN |
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9781119137276 |
1119137276 |
9781119137290 |
1119137292 |
9781119137252 |
111913725X |
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Edizione |
[1st ed.] |
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Descrizione fisica |
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1 online resource (417 pages) |
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Collana |
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Altri autori (Persone) |
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DuarteLeonardo Tomazeli |
MoussaouiSaïd |
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Disciplina |
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Soggetti |
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Chemical detectors |
Blind source separation |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Intro -- Table of Contents -- Title Page -- Copyright -- About the Editors -- List of Contributors -- Foreword -- Preface -- Notation -- 1 Overview of Source Separation -- 1.1 Introduction -- 1.2 The Problem of Source Separation -- 1.3 Statistical Methods for Source Separation -- 1.4 Source Separation Problems in Physical-Chemical Sensing -- 1.5 Source Separation Methods for Chemical-Physical Sensing -- 1.6 Organization of the Book -- References -- Notes -- 2 Optimization -- 2.1 Introduction to Optimization Problems -- 2.2 Majorization-Minimization Approaches -- 2.3 Primal‐Dual Methods -- 2.4 Application to NMR Signal Restoration -- 2.5 Conclusion -- References -- Notes -- 3 Non‐negative Matrix Factorization -- 3.1 Introduction -- 3.2 Geometrical Interpretation of NMF and the Non‐negative Rank -- 3.3 Uniqueness and Admissible Solutions of NMF -- 3.4 Non‐negative Matrix Factorization Algorithms -- 3.5 Applications of NMF in Chemical Sensing. Two Examples of Reducing Admissible Solutions -- 3.6 |
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Conclusions -- References -- 4 Bayesian Source Separation -- 4.1 Introduction -- 4.2 Overview of Bayesian Source Separation -- 4.3 Statistical Models for the Separation in the Linear Mixing -- 4.4 Statistical Models and Separation Algorithms for Nonlinear Mixtures -- 4.5 Some Practical Issues on Algorithm Implementation -- 4.6 Applications to Case Studies in Chemical Sensing -- 4.7 Conclusion -- Appendix 4.AImplementation of Function postsourcesrnd via Metropolis-Hasting Algorithm -- References -- Notes -- 5 Geometrical Methods - Illustration with Hyperspectral Unmixing -- 5.1 Introduction -- 5.2 Hyperspectral Sensing -- 5.3 Hyperspectral Mixing Models -- 5.4 Linear HU Problem Formulation -- 5.5 Dictionary‐Based Semiblind HU -- 5.6 Minimum Volume Simplex Estimation -- 5.7 Applications -- 5.8 Conclusions -- References -- Notes. |
6 Tensor Decompositions: Principles and Application to Food Sciences -- 6.1 Introduction -- 6.2 Tensor Decompositions -- 6.3 Constraints in Decompositions -- 6.4 Coupled Decompositions -- 6.5 Algorithms -- 6.6 Applications -- References -- Notes -- Index -- End User License Agreement. |
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Sommario/riassunto |
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"With the advent of more affordable, higher resolution or innovative data acquisition techniques, chemical analysis has been using progressively advanced signal and image processing tools. Indeed, both specialities (analytical chemistry and signal processing) share similar values of best practice in carrying out identifications and comprehensive characterizations, be they of chemical samples or of numerical data. Signal and image processing, for instance, often breaks down data into atoms, molecules, with specific decompositions and priors, as common in chemistry. Many problems in chemical engineering can be addressed with classical or advanced methods of signal and image processing, through topics such as chemical analysis leading to PARAFAC/tensor methods, hyper spectral imaging, ion-sensitive sensors, artificial noise, chromatography, mass spectrometry, TEP imaging, etc."-- |
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