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In the European Union nations, and other countries including Japan, Australia and Malaysia, it is a legal requirement that food products containing genetically modified organism (GMO) materials are labelled as such in order that customers may make informed purchasing decisions. For manufacturers and consumers to be confident about these assertions, systems must be in place along the entire food chain which support the co-existence of GM and non GM materials whilst maintaining a strict segregation between the two. This book is an output of a European Union-funded project entitled «Co-Extra: GM and non-GM food and feed supply chains: their Co-Existence and Traceability». The objective of this four year project is to provide practical tools and methods for implementing co-existence that will: enable the co-existence of genetically modified (GM) and non-GM crops enable the segregation and tracing of genetically modified organism (GMO) materials and derived products along the food and feed chains anticipate the future expansion of the use of GMOs The project is designed to foster a robustly science-based debate amongst all of the stakeholders involved in the food and feed chains, and the tools will be assessed not only from a technical point of view but with regard to the economic and legal aspects. It also surveys the GMO-related legal regimes and practices that exist in and beyond the EU. This book examines the practical tools and methods available to implement the co-existence and traceability of GM and non-GM food materials along the entire food and feed chains, as demanded by consumers and by legislation in force in the EU and elsewhere. GM and Non-GM Supply Foods is a source of valuable information for food manufacturers, food research institutions and regulatory bodies internationally.

Mixed modelling is very useful, and easier than you think! Mixed modelling is now well established as a powerful approach to statistical data analysis. It is based on the recognition of random-effect terms in statistical models, leading to inferences and estimates that have much wider applicability and are more realistic than those otherwise obtained. Introduction to Mixed Modelling leads the reader into mixed modelling as a natural extension of two more familiar methods, regression analysis and analysis of variance. It provides practical guidance combined with a clear explanation of the underlying concepts. Like the first edition, this new edition shows diverse applications of mixed models, provides guidance on the identification of random-effect terms, and explains how to obtain and interpret best linear unbiased predictors (BLUPs). It also introduces several important new topics, including the following: Use of the software SAS, in addition to GenStat and R. Meta-analysis and the multiple testing problem. The Bayesian interpretation of mixed models. Including numerous practical exercises with solutions, this book provides an ideal introduction to mixed modelling for final year undergraduate students, postgraduate students and professional researchers. It will appeal to readers from a wide range of scientific disciplines including statistics, biology, bioinformatics, medicine, agriculture, engineering, economics, archaeology and geography. Praise for the first edition: “One of the main strengths of the text is the bridge it provides between traditional analysis of variance and regression models and the more recently developed class of mixed models…Each chapter is well-motivated by at least one carefully chosen example…demonstrating the broad applicability of mixed models in many different disciplines…most readers will likely learn something new, and those previously unfamiliar with mixed models will obtain a solid foundation on this topic.”—Kerrie Nelson University of South Carolina, in American Statistician, 2007

Clearly lays out the issues related to plastics' effects on the environment, while also serving as a practical, non-academic guide for making sustainability decisions about plastics recycling and the newest bio-based plastics Company managers, product developers, policy makers, environmental researchers, and plastics industry engineers are under increasing pressure to find ways of minimizing the environmental footprint of plastic products. This accessible book is designed to help readers understand the life-cycle impacts of various plastics, clarifying the technical research and practical arguments to show when bio-based and recycled plastics might be useful options for reducing the overall energy consumption, greenhouse gas emissions, and waste associated with traditional plastics. Plastics and Sustainability compares traditional fossil fuel-based plastics with bio-based plastics in terms of properties, environmental impacts, and costs – indicating what the most effective approaches could be for using recycled, biodegradable, or various bio-based materials. The book makes objective comparisons between bioplastics and all commonly used plastics, focusing on how they affect production economics, product requirements, and retailer and consumer needs. It incorporates research concerning life-cycle assessment, production techniques, and commercial applications, and presents «green» guidelines about product design, recycling, processing efficiency, and material selection. The book also reports on recent industry developments and commercial trends in an effort to synthesize conclusions that are necessary for finding the right balance between bio-based and fossil-fuel based plastic products. Check out the author's blog at http://www.plastech.biz/blog.

A unified, systematic approach to applying mixed integer programming solutions to integrated scheduling in customer-driven supply chains Supply chain management is a rapidly developing field, and the recent improvements in modeling, preprocessing, solution algorithms, and mixed integer programming (MIP) software have made it possible to solve large-scale MIP models of scheduling problems, especially integrated scheduling in supply chains. Featuring a unified and systematic presentation, Scheduling in Supply Chains Using Mixed Integer Programming provides state-of-the-art MIP modeling and solutions approaches, equipping readers with the knowledge and tools to model and solve real-world supply chain scheduling problems in make-to-order manufacturing. Drawing upon the author's own research, the book explores MIP approaches and examples-which are modeled on actual supply chain scheduling problems in high-tech industries-in three comprehensive sections: Short-Term Scheduling in Supply Chains presents various MIP models and provides heuristic algorithms for scheduling flexible flow shops and surface mount technology lines, balancing and scheduling of Flexible Assembly Lines, and loading and scheduling of Flexible Assembly Systems Medium-Term Scheduling in Supply Chains outlines MIP models and MIP-based heuristic algorithms for supplier selection and order allocation, customer order acceptance and due date setting, material supply scheduling, and medium-term scheduling and rescheduling of customer orders in a make-to-order discrete manufacturing environment Coordinated Scheduling in Supply Chains explores coordinated scheduling of manufacturing and supply of parts as well as the assembly of products in supply chains with a single producer and single or multiple suppliers; MIP models for a single- or multiple-objective decision making are also provided Two main decision-making approaches are discussed and compared throughout. The integrated (simultaneous) approach, in which all required decisions are made simultaneously using complex, monolithic MIP models; and the hierarchical (sequential) approach, in which the required decisions are made successively using hierarchies of simpler and smaller-sized MIP models. Throughout the book, the author provides insight on the presented modeling tools using AMPL® modeling language and CPLEX solver. Scheduling in Supply Chains Using Mixed Integer Programming is a comprehensive resource for practitioners and researchers working in supply chain planning, scheduling, and management. The book is also appropriate for graduate- and PhD-level courses on supply chains for students majoring in management science, industrial engineering, operations research, applied mathematics, and computer science.