Determining the Socially Optimal Recycling Rate

What municipal recycling rate is socially optimal? One credible answer would consider the recycling rate that minimizes the overall social costs of managing municipal waste. Such social costs are comprised of all budgetary costs and revenues associated with operating municipal waste and recycling programs, all costs to recycling households associated with preparing and storing recyclable materials for collection, all external disposal costs associated with waste disposed at landfills or incinerators, and all external benefits associated with the provision of recycled materials that foster environmentally efficient production processes. This paper discusses how to estimate these four components of social cost to then estimate the optimal recycling rate. (C) 2013 Elsevier B.V. All rights reserved.

The Socially Optimal Recycling Rate: Evidence from Japan

This paper estimates the average social cost of municipal waste management as a function of the recycling rate. Social costs include all municipal costs and revenues, costs to recycling households to prepare materials estimated with an original method, external disposal costs, and external recycling benefits. Results suggest average social costs are minimized with recycling rates well below observed and mandated levels in Japan. Cost-minimizing municipalities are estimated to recycle less than the optimal rate. These results are robust to changes in the components of social costs, indicating that Japan and perhaps other developed countries may be setting inefficiently high recycling goals. (C) 2014 Elsevier Inc. All rights reserved.

A Closed-Form Solution for the Optimal Time Evolution of an Exponentially Decaying Signal with Thermal Noise

The signal-to-noise ratio of a monoexponentially decaying signal exhibits a maximum at an evolution time of approximately 1.26 T-2. It has previously been thought that there is no closed-form solution to express this maximum. We report in this note that this maximum can be represented in a specific, analytical closed form in terms of the negative real branch of an inverse function known as the Lambert W function. The Lambert function is finding increasing use in the solution of problems in a variety of areas in the physical sciences. (C) 2014 Wiley Periodicals, Inc.

Towards optimal treatment with growth hormone in short children and adolescents: evidence and theses

Treatment with growth hormone (GH) has become standard practice for replacement in GH-deficient children or pharmacotherapy in a variety of disorders with short stature. However, even today, the reported adult heights achieved often remain below the normal range. In addition, the treatment is expensive and may be associated with long-term risks. Thus, a discussion of the factors relevant for achieving an optimal individual outcome in terms of growth, costs, and risks is required. In the present review, the heterogenous approaches of treatment with GH are discussed, considering the parameters available for an evaluation of the short- and long-term outcomes at different stages of treatment. This discourse introduces the potential of the newly emerging prediction algorithms in comparison to other more conventional approaches for the planning and evaluation of the response to GH. In rare disorders such as those with short stature, treatment decisions cannot easily be deduced from personal experience. An interactive approach utilizing the derived experience from large cohorts for the evaluation of the individual patient and the required decision-making may facilitate the use of GH. Such an approach should also lead to avoiding unnecessary long-term treatment in unresponsive individuals.

Ultrasonographic-guided ilioinguinal/iliohypogastric nerve block in pediatric anesthesia: what is the optimal volume?

Recently, our study group demonstrated the usefulness of ultrasonographic guidance in ilioinguinal/iliohypogastric nerve blocks in children. As a consequence, we designed a follow-up study to evaluate the optimal volume of local anesthetic for this regional anesthetic technique. Using a modified step-up-step-down approach, with 10 children in each study group, a starting dose of 0.2 mL/kg of 0.25% levobupivacaine was administered to perform an ilioinguinal/iliohypogastric nerve block under ultrasonographic guidance. After each group of 10 patients, the results were analyzed, and if all blocks were successful, the volume of local anesthetic was decreased by 50%, and a further 10 patients were enrolled into the study. Failure to achieve a 100% success rate within a group subjected patients to an automatic increase of half the previous volume reduction to be used in the subsequent group. Using 0.2 and 0.1 mL/kg of 0.25% levobupivacaine, the success rate was 100%. With a volume of 0.05 mL/kg of 0.25% levobupivacaine, 4 of 10 children received additional analgesia because of an inadequate block. Therefore, according to the protocol, the amount was increased to 0.075 mL/kg of 0.25% levobupivacaine, where the success rate was again 100%. We conclude that ultrasonographic guidance for ilioinguinal/iliohypogastric nerve blocks in children allowed a reduction of the volume of local anesthetic to 0.075 mL/kg.

A Fully Bayesian Approach for Combining Multilevel Failure Information in Fault Tree Quantification and Corresponding Optimal Resource Allocation

This paper presents a fully Bayesian approach that simultaneously combines basic event and statistically independent higher event-level failure data in fault tree quantification. Such higher-level data could correspond to train, sub-system or system failure events. The full Bayesian approach also allows the highest-level data that are usually available for existing facilities to be automatically propagated to lower levels. A simple example illustrates the proposed approach. The optimal allocation of resources for collecting additional data from a choice of different level events is also presented. The optimization is achieved using a genetic algorithm.

The Optimal Confidence Region for a Random Parameter

Under a two-level hierarchical model, suppose that the distribution of the random parameter is known or can be estimated well. Data are generated via a fixed, but unobservable realization of this parameter. In this paper, we derive the smallest confidence region of the random parameter under a joint Bayesian/frequentist paradigm. On average this optimal region can be much smaller than the corresponding Bayesian highest posterior density region. The new estimation procedure is appealing when one deals with data generated under a highly parallel structure, for example, data from a trial with a large number of clinical centers involved or genome-wide gene-expession data for estimating individual gene- or center-specific parameters simultaneously. The new proposal is illustrated with a typical microarray data set and its performance is examined via a small simulation study.