Toward the next generation of research into small area effects on health : a synthesis of multilevel investigations published since July 1998.

To map out area effects on health research, this study had the following aims: (1) to inventory multilevel investigations of area effects on self rated health, cardiovascular diseases and risk factors, and mortality among adults; (2) to describe and critically discuss methodological approaches employed and results observed; and (3) to formulate selected recommendations for advancing the study of area effects on health. Overall, 86 studies were inventoried. Although several innovative methodological approaches and analytical designs were found, small areas are most often operationalised using administrative and statistical spatial units. Most studies used indicators of area socioeconomic status derived from censuses, and few provided information on the validity and reliability of measures of exposures. A consistent finding was that a significant portion of the variation in health is associated with area context independently of individual characteristics. Area effects on health, although significant in most studies, often depend on the health outcome studied, the measure of area exposure used, and the spatial scale at which associations are examined

Sensitivity Analysis of List Scheduling Heuristics

When jobs have to be processed on a set of identical parallel machines so as to minimize the makespan of the schedule, list scheduling rules form a popular class of heuristics. The order in which jobs appear on the list is assumed here to be determined by the relative size of their processing times; well known special cases are the LPT rule and the SPT rule, in which the jobs are ordered according to non-increasing and non-decreasing processing time respectively. When one of the job processing times is gradually increased, the schedule produced by a list scheduling rule will be affected in a manner reflecting its sensitivity to data perturbations. We analyze this phenomenon and obtain analytical support for the intuitively plausible notion that the sensitivity of a list scheduling rule increases with the quality of the schedule produced

A genetic algorithm for the one-dimensional cutting stock problem with setups

This paper investigates the one-dimensional cutting stock problem considering two conflicting objective functions: minimization of both the number of objects and the number of different cutting patterns used. A new heuristic method based on the concepts of genetic algorithms is proposed to solve the problem. This heuristic is empirically analyzed by solving randomly generated instances and also practical instances from a chemical-fiber company. The computational results show that the method is efficient and obtains positive results when compared to other methods from the literature. © 2014 Brazilian Operations Research Society

Recurrent governance challenges in the implementation and alignment of flood risk management strategies: a review

In Europe increasing flood risks challenge societies to diversify their Flood Risk Management Strategies (FRMSs). Such a diversification implies that actors not only focus on flood defence, but also and simultaneously on flood risk prevention, mitigation, preparation and recovery. There is much literature on the implementation of specific strategies and measures as well as on flood risk governance more generally. What is lacking, though, is a clear overview of the complex set of governance challenges which may result from a diversification and alignment of FRM strategies. This paper aims to address this knowledge gap. It elaborates on potential processes and mechanisms for coordinating the activities and capacities of actors that are involved on different levels and in different sectors of flood risk governance, both concerning the implementation of individual strategies and the coordination of the overall set of strategies. It identifies eight overall coordination mechanisms that have proven to be useful in this respect

Modeling and Analysis of the Molecular Basis of Pain in Sensory Neurons

Intracellular calcium dynamics are critical to cellular functions like pain transmission. Extracellular ATP plays an important role in modulating intracellular calcium levels by interacting with the P2 family of surface receptors. In this study, we developed a mechanistic mathematical model of ATP-induced P2 mediated calcium signaling in archetype sensory neurons. The model architecture, which described 90 species connected by 162 interactions, was formulated by aggregating disparate molecular modules from literature. Unlike previous models, only mass action kinetics were used to describe the rate of molecular interactions. Thus, the majority of the 252 unknown model parameters were either association, dissociation or catalytic rate constants. Model parameters were estimated from nine independent data sets taken from multiple laboratories. The training data consisted of both dynamic and steady-state measurements. However, because of the complexity of the calcium network, we were unable to estimate unique model parameters. Instead, we estimated a family or ensemble of probable parameter sets using a multi-objective thermal ensemble method. Each member of the ensemble met an error criterion and was located along or near the optimal trade-off surface between the individual training data sets. The model quantitatively reproduced experimental measurements from dorsal root ganglion neurons as a function of extracellular ATP forcing. Hypothesized architecture linking phosphoinositide regulation with P2X receptor activity explained the inhibition of P2X-mediated current flow by activated metabotropic P2Y receptors. Sensitivity analysis using individual and the whole system outputs suggested which molecular subsystems were most important following P2 activation. Taken together, modeling and analysis of ATP-induced P2 mediated calcium signaling generated qualitative insight into the critical interactions controlling ATP induced calcium dynamics. Understanding these critical interactions may prove useful for the design of the next generation of molecular pain management strategies

Integration of P2Y receptor-activated signal transduction pathways in G protein-dependent signalling networks

The role of nucleotides in intracellular energy provision and nucleic acid synthesis has been known for a long time. In the past decade, evidence has been presented that, in addition to these functions, nucleotides are also autocrine and paracrine messenger molecules that initiate and regulate a large number of biological processes. The actions of extracellular nucleotides are mediated by ionotropic P2X and metabotropic P2Y receptors, while hydrolysis by ecto-enzymes modulates the initial signal. An increasing number of studies have been performed to obtain information on the signal transduction pathways activated by nucleotide receptors. The development of specific and stable purinergic receptor agonists and antagonists with therapeutical potential largely contributed to the identification of receptors responsible for nucleotide-activated pathways. This article reviews the signal transduction pathways activated by P2Y receptors, the involved second messenger systems, GTPases and protein kinases, as well as recent findings concerning P2Y receptor signalling in C6 glioma cells. Besides vertical signal transduction, lateral cross-talks with pathways activated by other G protein-coupled receptors and growth factor receptors are discussed

A framework to assess quality and uncertainty in disaster loss data

There is a growing interest in the systematic and consistent collection of disasterloss data for different applications. Therefore, the collected data must follow a set oftechnical requirements to guarantee its usefulness. One of those requirements is theavailability of a measure of the uncertainty in the collected data to express its quality for agiven purpose. Many of the existing disaster loss databases do not provide such uncertainty/qualitymeasures due to the lack of a simple and consistent approach to expressuncertainty. After reviewing existing literature on the subject, a framework to express theuncertainty in disaster loss data is proposed. This framework builds on an existinguncertainty classification that was updated and combined with an existing method for datacharacterization. The proposed approach is able to establish a global score that reflects theoverall uncertainty in a certain loss indicator and provides a measure of its quality