How may quality asurance systems in food chains include environmental aspects based on life cycle methodology?

The number of Quality Assurance Systems (QAS) for food products is increasing and so is the topics they cover, from traditional intrinsic product characteristics such as percent meat in slaughtered pigs and protein content in milk to food safety issues such as zoonoses and pesticide residues and in some cases aspects of animal welfare. This development is linked to de-mands for risk controlling systems such as HACCP and traceability systems that would allow food safety problems to be traced to a small number of producers or farms. The large retail companies (supermarkets) are an important driving force for this development because of their efforts to build consumer trust in food products and loyalty to the companies own brands. Envi-ronmental characteristics of food products and information on their production methods are be-coming part of some QAS but not mostly in the form of qualitative information e.g. certification that the farmers have used Good Agricultural Practice (GAP). The paper gives examples of this and then discuss this development in relation to LCA based environmental appraisal of food products. The development of quantitative (tools for) environmental appraisal of agriculture and food production is becoming more productoriented improving the possibilities of assessing the regional and global impacts of food production chains and consumption. But these systems building on LCA does not so far seem to be linked with the development of QAS for food. The paper finally discuss the possibilities for linking the food safety related traceability systems and gives an example of on-going work to establish LCA based QAS in a meat processing system

What is a Freestanding Emergency Department? Definitions Differ Across Major United States Data Sources

Introduction: Despite the growing number of freestanding emergency departments (FSED) in the United States (US), FSED definitions differ across major US data sources of healthcare facilities and use. We compare these sources and propose a universal definition of FSED (and its two major types) to improve communications regarding these facilities and their patients.Methods: We collected definitions of FSEDs from 11 national data sources using their websites, email, and telephone communications. For each source, we asked how they define FSEDs, whether being open 24/7 is a requirement to be called an ED, and whether they maintain a dataset of FSEDs.Results: Definitions varied across the data sources. All sources recognize FSEDs in their definitions, regardless of type; only one (the National Health Intervew Survey) does not differentiate them from other EDs. Five of the 11 sources (45%) omit autonomous FSEDs from their definitions and do not separately identify satellite FSEDs from their affiliated hospitals. One source does separately identify satellite FSEDs from their affiliated hospitals, but also omits autonomous FSEDs. Furthermore, three of the 11 sources (27%) do not require being open 24/7, while all others (73%) employ this criterion. Six of the 11 (55%) maintain datasets of FSEDs using their definition.Conclusion: As FSEDs continue to change the landscape of emergency care, it is important that they also be represented in national ED data sources. The current differences in the definition of an FSED make it difficult to provide accurate and longitudinal analysis for these facilities and patients who receive services at these facilities. We propose a universal definition of FSEDs as described by both the American College of Emergency Physicians and the National Emergency Department Inventory. Implementing a standard definition would facilitate a more accurate representation of FSEDs in national data sources and enhance ongoing efforts to improve the quality of emergency care delivered in FSEDs

Benchmarking Utility Clean Energy Deployment: 2016

Benchmarking Utility Clean Energy Deployment: 2016 provides a window into how the global transition toward clean energy is playing out in the U.S. electric power sector. Specifically, it reveals the extent to which 30 of the largest U.S. investor-owned electric utility holding companies are increasingly deploying clean energy resources to meet customer needs.Benchmarking these companies provides an opportunity for transparent reporting and analysis of important industry trends. It fills a knowledge gap by offering utilities, regulators, investors, policymakers and other stakeholders consistent and comparable information on which to base their decisions. And it provides perspective on which utilities are best positioned in a shifting policy landscape, including likely implementation of the U.S. EPA's Clean Power Plan aimed at reducing carbon pollution from power plants

Analyzing the solutions of DEA through information visualization and data mining techniques: SmartDEA framework

Data envelopment analysis (DEA) has proven to be a useful tool for assessing efficiency or productivity of organizations, which is of vital practical importance in managerial decision making. DEA provides a significant amount of information from which analysts and managers derive insights and guidelines to promote their existing performances. Regarding to this fact, effective and methodologic analysis and interpretation of DEA solutions are very critical. The main objective of this study is then to develop a general decision support system (DSS) framework to analyze the solutions of basic DEA models. The paper formally shows how the solutions of DEA models should be structured so that these solutions can be examined and interpreted by analysts through information visualization and data mining techniques effectively. An innovative and convenient DEA solver, SmartDEA, is designed and developed in accordance with the proposed analysis framework. The developed software provides a DEA solution which is consistent with the framework and is ready-to-analyze with data mining tools, through a table-based structure. The developed framework is tested and applied in a real world project for benchmarking the vendors of a leading Turkish automotive company. The results show the effectiveness and the efficacy of the proposed framework

Terminology mining in social media

The highly variable and dynamic word usage in social media presents serious challenges for both research and those commercial applications that are geared towards blogs or other user-generated non-editorial texts. This paper discusses and exemplifies a terminology mining approach for dealing with the productive character of the textual environment in social media. We explore the challenges of practically acquiring new terminology, and of modeling similarity and relatedness of terms from observing realistic amounts of data. We also discuss semantic evolution and density, and investigate novel measures for characterizing the preconditions for terminology mining

Global Employee Engagement Report: A Corporate Responsibility Practitioner's Guide

This is a Corporate Responsibility Practitioner's Guide designed to provide practical information to companies looking to expand their employee engagement programs internationally. The report explores the employee engagement landscape in five countries: China, Brazil, India, South Africa and the United Kingdom. SVCF surveyed existing literature (global and country-specific) and conducted in-depth interviews with 65 corporate and nonprofit practitioners who have direct experience with employee engagement programs in the five countries studied. The report identifies cultural nuances, policies and trends that practitioners should be aware of as they design locally relevant programs

Recent Trends in the Research on National Innovation Systems

In this paper, we give an overview on recent developments in the research on national innovation systems (NIS). Essentially, we identify three development lines of the concept. These are policy-oriented studies that frequently combine the NIS approach with the terminology of corporate benchmarking, contributions to formalize the concept of NIS through descriptive or analytical models, and NIS studies of countries beyond the group of highly industrialized economies. It follows from the analysis of these research trends that the concept has developed in distinctive directions. In international comparisons of innovation systems, heterogeneity in the structure of the systems is only marginally taken into account, an aspect that may reduce the explanatory power of such system-level comparisons. Contrary to this, historically grown organizational and institutional structures are extensively described and considered in NIS studies of industrializing countries, a characteristic which ties up with early studies of national innovation systems.innovation, national innovation systems, comparative studies

Performance of Network and Service Monitoring Frameworks

The efficiency and the performance of anagement systems is becoming a hot research topic within the networks and services management community. This concern is due to the new challenges of large scale managed systems, where the management plane is integrated within the functional plane and where management activities have to carry accurate and up-to-date information. We defined a set of primary and secondary metrics to measure the performance of a management approach. Secondary metrics are derived from the primary ones and quantifies mainly the efficiency, the scalability and the impact of management activities. To validate our proposals, we have designed and developed a benchmarking platform dedicated to the measurement of the performance of a JMX manager-agent based management system. The second part of our work deals with the collection of measurement data sets from our JMX benchmarking platform. We mainly studied the effect of both load and the number of agents on the scalability, the impact of management activities on the user perceived performance of a managed server and the delays of JMX operations when carrying variables values. Our findings show that most of these delays follow a Weibull statistical distribution. We used this statistical model to study the behavior of a monitoring algorithm proposed in the literature, under heavy tail delays distribution. In this case, the view of the managed system on the manager side becomes noisy and out of date