The Protection of Subjects in Human Research rule by the USEPA, including the establishment of the Human Studies Review Board (HSRB), has resulted in changes to both study design and study evaluation processes, particularly with respect to ethical considerations. Non-Dietary Human Exposure andRisk Assessment is a compilation of the presentations given in a symposium of the same name at the 238th ACS National Meeting in Washington D.C. The purpose of the symposium was to provide a forum for scientists from industry, academia, and government to share investigative methods used to generate data for use in non-dietary human risk assessments and to share methodology for performing and evaluating those assessments.
This compilation is intended to provide the reader with a concise overview of the current status of both the scientific and regulatory aspects of non-dietary human exposure and risk assessment as applied to pesticides. It is the hope of the editors that it will also be the starting point for discussions leading to the further refinement of study and risk assessment design, data evaluation, and regulatory harmonization.
Three major areas are covered in this symposium edition. The first area is regulatory issues including the development of the Protection of Subjects in Human Research rule and the HSRB, statistical procedures involved in designing human exposure studies, handling of the data generated in those studies, and quality assurance processes related to worker exposure studies. The second area, study design, includes processes for the identification and recruitment of volunteers for human exposure studies, overviews of several studies that have been recently performed, the development of procedures for evaluating the resulting data by Regulatory Agencies, and efforts towards international cooperation in the generation and use of exposure data. The final area, methodology, includes examples of the development of methods for the analysis of samples generated in non-dietary human exposure studies with particular emphasis on the use of hyphenated techniques and the development of a model for determining greenhouse exposures that is currently being used in Europe.

Risk model validation is an emerging and important area of research, and has arisen because of Basel I and II. These regulatory initiatives require trading institutions and lending institutions to compute their reserve capital in a highly analytic way, based on the use of internal risk models. It is part of the regulatory structure that these risk models be validated both internally and externally, and there is a great shortage of information as to best practise. Editors Christodoulakis and Satchell collect papers that are beginning to appear by regulators, consultants, and academics, to provide the first collection that focuses on the quantitative side of model validation. The book covers the three main areas of risk: Credit Risk and Market and Operational Risk.
*Risk model validation is a requirement of Basel I and II
*The first collection of papers in this new and developing area of research
*International authors cover model validation in credit, market, and operational risk

For a long time, conventional reliability analyses have been oriented towards selecting the more reliable system and preoccupied with maximising the reliability of engineering systems. On the basis of counterexamples however, we demonstrate that selecting the more reliable system does not necessarily mean selecting the system with the smaller losses from failures! As a result, reliability analyses should necessarily be risk-based, linked with the losses from failures.
Accordingly, a theoretical framework and models are presented which form the foundations of the reliability analysis and reliability allocation linked with the losses from failures.
An underlying theme in the book is the basic principle for a risk-based design: the larger the cost of failure associated with a component, the larger its minimum necessary reliability level. Even identical components should be designed to different reliability levels if their failures are associated with different losses.
According to a classical definition, the risk of failure is a product of the probability of failure and the cost given failure. This risk measure however cannot describe the risk of losses exceeding a maximum acceptable limit. Traditionally the losses from failures have been 'accounted for' by the average production availability (the ratio of the actual production capacity and the maximum production capacity). As demonstrated in the book by using a simple counterexample, two systems with the same production availability can be characterised by very different losses from failures.
As an alternative, a new aggregated risk measure based on the cumulative distribution of the potential losses has been introducedand the theoretical framework for risk analysis based on the concept potential losses has also been developed. This new risk measure incorporates the uncertainty associated with the exposure to losses and the uncertainty in the consequences given the exposure. For repairable systems with complex topology, the distribution of the potential losses can be revealed by simulating the behaviour of systems during their life-cycle. For this purpose, fast discrete event-driven simulators are presented capable of tracking the potential losses for systems with complex topology, composed of a large number of components. The simulators are based on new, very efficient algorithms for system reliability analysis of systems comprising thousands of components.
An important theme in the book are the generic principles and techniques for reducing technical risk. These have been classified into three major categories: preventive (reducing the likelihood of failure), protective (reducing the consequences from failure) and dual (reducing both, the likelihood and the consequences from failure). Many of these principles (for example: avoiding clustering of events, deliberately introducing weak links, reducing sensitivity, introducing changes with opposite sign, etc.) are discussed in the reliability literature for the first time.
Significant space has been allocated to component reliability. In the last chapter of the book, several applications are discussed of a powerful equation which constitutes the core of a new theory of locally initiated component failure by flaws whose number is a random variable.
This book has been written with the intention to fill two big gaps in the reliability and riskliterature: the risk-based reliability analysis as a powerful alternative to the traditional reliability analysis and the generic principles for reducing technical risk. I hope that the principles, models and algorithms presented in the book will help to fill these gaps and make the book useful to reliability and risk-analysts, researchers, consultants, students and practising engineers.
- Offers a shift in the existing paradigm for conducting reliability analyses.
- Covers risk-based reliability analysis and generic principles for reducing risk.
- Provides a new measure of risk based on the distribution of the potential losses from failure as well as the basic principles for risk-based design.
- Incorporates fast algorithms for system reliability analysis and discrete-event simulators.
- Includes the probability of failure of a structure with complex shape expressed with a simple equation.

Literary Nonfiction. Philosophy. Economics & Statistics. Translated from the German by Karen Leeder. Acclaimed poet, essayist, and cultural critic Hans Magnus Enzensberger takes a fresh, sobering look at our faith in statistics, our desire to predict the future, and our dependence on fortuitousness. Tracing the interface between chance and probability in medical diagnostics, risk models, economics, and the fluctuations of financial markets, FATAL NUMBERS goes straight to the heart of what it means to live, plan, and make decisions in a globalized, digitized, hyperlinked, science-driven, and uncertain world. Foreword by Gerd Gigerenzer. Illustrations by David Fried.

This book is written to empower risk professionals to turn analytics and models into deployable solutions with minimal IT intervention. Corporations, especially financial institutions, must show evidence of having quantified credit, market and operational risks. They have databases but automating the process to translate data into risk parameters remains a desire.Modelling is done using software with output codes not readily processed by databases. With increasing acceptance of open-source languages, database vendors have seen the value of integrating modelling capabilities into their products. Nevertheless, deploying solutions to automate processes remains a challenge. While not comprehensive in dealing with all facets of risks, the author aims to develop risk professionals who will be able to do just that.