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The fibromyalgia syndrome (FM) workshop at OMERACT 8 continued the work initiated in the first FM workshop at OMERACT 7 in 2004. The principal objectives were to work toward consensus on core domains for assessment in FM studies, evaluate the performance quality of outcome measures used in a review of recent trials in FM, and discuss the research agenda of the FM working group. An initiative to include the patient perspective on identification and prioritization of domains, consisting of focus groups and a patient Delphi exercise, was completed prior to OMERACT 8. Patient-identified domains were, for the most part, similar to those identified by clinician-investigators in terms of symptoms and relative importance. However, patients identified certain domains, such as stiffness, that were not included by physicians, and emphasized the importance of domains such as dyscognition and impaired motivation. Many of the principal domains agreed upon by the clinician-investigators, patients, and OMERACT participants, including pain, fatigue, sleep, mood, and global measures, have been used in clinical trials and performed well when viewed through the OMERACT filter. The research agenda items reviewed and approved for continued study included development of objective "biomarkers" in FM, development of a responder index for FM, and coordination with the WHO's International Classification of Functioning Disability and Health (ICF) Research Branch and the US National Institutes of Health's Patient Reported Outcome Measures Information System network (PROMIS) to develop improved measures of function, quality of life, and participation. The OMERACT process has provided a framework for identification of key domains to be assessed and a path toward validation and standardization of outcome measures for clinical trials in FM.

Objective: Osteoarthritis (OA) is a chronic and slowly progressive disease for which biomarkers may be able to provide a more rapid indication of therapeutic responses to therapy than is currently available; this could accelerate and facilitate OA drug discovery and development programs. The goal of this document is to provide a summary and guide to the application of in vitro (biochemical and other soluble) biomarkers in the development of drugs for OA and to outline and stimulate a research agenda that will further this goal. Methods: The Biomarkers Working Group representing experts in the field of OA biomarker research from both academia and industry developed this consensus document between 2007 and 2009 at the behest of the Osteoarthritis Research Society International Federal Drug Administration initiative (OARSI FDA initiative). Results: This document summarizes definitions and classification systems for biomarkers, the current outcome measures used in OA clinical trials, applications and potential utility of biomarkers for development of OA therapeutics, the current state of qualification of OA-related biomarkers, pathways for biomarker qualification, critical needs to advance the use of biomarkers for drug development, recommendations regarding practices and clinical trials, and a research agenda to advance the science of OA-related biomarkers. Conclusions: Although many OA-related biomarkers are currently available they exist in various states of qualification and validation. The biomarkers that are likely to have the earliest beneficial impact on clinical trials fall into two general categories, those that will allow targeting of subjects most likely to either respond and/or progress (prognostic value) within a reasonable and manageable time frame for a clinical study (for instance within 1-2 years for an OA trial), and those that provide early feedback for preclinical decision-making and for trial organizers that a drug is having the desired biochemical

Two extensions of the classical scheduling model with two parallel identical machines and a partially ordered set of unit execution time tasks are considered. It is well known that the Coffman-Graham algorithm constructs for this model a so-called ideal schedule: that is, a schedule which is optimal for both makespan and total completion time criteria simultaneously. The question of the existence of such a schedule for the extension of this model, where each task has a release time, has remained open over seneral decades. The paper gives a positive answer to this question and presents the corresponding polynormal-time algorithm.Another straightforward generalisation of the considered classcial model is obtained by the introduction of multiprocessor tasks. It is shown that, despite the fact tha a slightly modified Coffman-Graham algorithm solves the makespan problem with multiprocessor tasks for arbirtary precedence constraints, generally an ideal schedule does not exist and the problem with the criterion of total completion time turns out to be NP-hard ithe strong sense even for in-trees.

In this paper, we consider empty freight car distribution in a scheduled railway system. We analyze the cost structure for the repositioning of empty cars, and conclude that the distribution cost shows an economy-of-scale behavior. In addition to the cost proportional to the number of cars sent from origin to destination, there is a cost related to car-handling operations at yards, which depends on the number of car groups that are handled. Thus, if we can find a transportation pattern in which fewer but larger groups of cars are built, the total distribution cost can be decreased. The objective of the paper is to propose an optimization model that explicitly takes this economy-of-scale effect into account. We use a time-dependent network to describe the possible car movements in time and space, and show how this network can be transformed into a network with fixed costs on links representing movements of cars with identical origin and destination terminals. The resulting optimization model is a capacitated network design model, where each capacity constraint limits the flow on several arcs. We describe a tabu heuristic for solving the model, and present computational results. © 2004 INFORMS.