Abstract. Anonymity means that the identity of the user performing a certain action is maintained secret. The protocols for ensuring anonymity often use random mechanisms which can be described probabilistically. In this paper we propose a notion of weak probabilistic anonymity, where weak refers to the fact that some amount of probabilistic information may be revealed by the protocol. This information can be used by an observer to infer the likeliness that the action has been performed by a certain user. The aim of this work is to study the degree of anonymity that the protocol can still ensure, despite the leakage of information. We illustrate our ideas by using the example of the dining cryptographers with biased coins. We consider both the cases of nondeterministic and probabilistic users. Correspondingly, we propose two notions of weak anonymity and we investigate their respective dependencies on the biased factor of the coins.

The US Sustainable Remediation Forum (SURF) proposes a nine-step process for conducting and documenting a footprint analysis and life-cycle assessment (LCA) for remediation projects. This guidance is designed to assist remediation practitioners in evaluating the impacts resulting from potential remediation activities so that preventable impacts can be mitigated. Each of the nine steps is flexible and scalable to a full range of remediation projects and to the tools used by remediation practitioners for quantifying environmental metrics. Two fictional case studies are presented to demonstrate how the guidance can be implemented for a range of evaluations and tools. Case-study findings show that greater insight into a study is achieved when the nine steps are followed and additional opportunities are provided to minimize remediation project footprints and create improved sustainable remediation solutions. This guidance promotes a consistent and repeatable process in which all pertinent information is provided in a transparent manner to allow stakeholders to comprehend the intricacies and tradeoffs inherent in a footprint analysis or LCA.For these reasons, SURF recommends that this guidance be used when a footprint analysis or LCA is completed for a remediation project. O c 2011 Wiley Periodicals, Inc. INTRODUCTIONThe remediation industry has successfully cleaned up thousands of sites contaminated with a variety of pollutants using numerous methods. The beneficial intent of these site cleanups is to remediate contaminated media and reduce risks to human health and the environment to acceptable levels. Historically, the activities conducted during cleanups that can impact the environment have not been completely considered or evaluated. Furthermore, potential impacts to human health and ecosystems beyond those typically addressed in human health and ecological risk assessments have not been considered. Externalities, such as societal costs, have not been included in evaluations as well. If these impacts are taken into consideration, some of the negative impacts from remediation activities may be avoided or reduced. Identifying these potential impacts early in remedial planning enables decision makers to maximize opportunities to reduce negative impacts.Sustainability is an emerging and evolving concept used with increasing frequency in today's business world. Every day, corporate decision makers grapple with their company's impact on the environment, natural resources, human health, and society-in addition to tackling questions of economics. Sustainability principles involve balancing 39Guidance for Performing Footprint Analyses and Life-Cycle Assessments for the Remediation Industry three core aspects: environmental, economic, and social. Life-cycle management is a business approach that can be used to target, organize, analyze, and manage information and activities toward continuous improvement along the life cycle. Life-cycle management is about making life-cycle thinking operational for businesses that are striv...

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We study the consequences of positive correlation of beliefs in the design of voting rules in a model with an arbitrary number of voters. We propose a notion of positive correlation, based on the likelihood of agreement of the k‐best alternatives (for any k) of two orders called top‐set (TS) correlation. We characterize the set of ordinal Bayesian incentive compatible (OBIC) (d'Aspremont and Peleg 1988) voting rules with TS‐correlated beliefs and additionally satisfy robustness with respect to local perturbations. We provide an example of a voting rule that satisfies OBIC with respect to all TS‐correlated beliefs. The generally positive results contrast sharply with the negative results obtained for the independent case by [Majumdar and Sen, 2004] and parallel similar results in the auction design model (Crémer and McLean 1988).

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