Squeaky Wheel Optimization

We describe a general approach to optimization which we term `Squeaky Wheel' Optimization (SWO). In SWO, a greedy algorithm is used to construct a solution which is then analyzed to find the trouble spots, i.e., those elements, that, if improved, are likely to improve the objective function score. The results of the analysis are used to generate new priorities that determine the order in which the greedy algorithm constructs the next solution. This Construct/Analyze/Prioritize cycle continues until some limit is reached, or an acceptable solution is found. SWO can be viewed as operating on two search spaces: solutions and prioritizations. Successive solutions are only indirectly related, via the re-prioritization that results from analyzing the prior solution. Similarly, successive prioritizations are generated by constructing and analyzing solutions. This `coupled search' has some interesting properties, which we discuss. We report encouraging experimental results on two domains, scheduling problems that arise in fiber-optic cable manufacturing, and graph coloring problems. The fact that these domains are very different supports our claim that SWO is a general technique for optimization

Effect of a collector bag for measurement of postpartum blood loss after vaginal delivery: cluster randomised trial in 13 European countries

Objective To evaluate the effectiveness of the systematic use of a transparent plastic collector bag to measure postpartum blood loss after vaginal delivery in reducing the incidence of severe postpartum haemorrhage

Stabilization of Tollmien-Schlichting Waves by Mode Interaction

Decreasing skin friction in boundary layers attached to aircraft wings can have an impact in both fuel consumption and pollutant production, which are becoming crucial to reduce operation costs and meet environmental regulations, respectively. Skin friction in turbulent boundary layers is about ten times that of laminar boundary layers. Thus, an obvious method to reduce friction drag is to delay transition to turbulence, which is a fairly involved process in real aircraft wings [J98]. Transition sis promoted either by Tollmien—Schlichting (TS) and Klebanov (K) modes [K94], with the former playing an essential role. Various methods (e.g., suction [SG00,ZLB04], wave cancellation [WAA01,LG06]) have been proposed to reduce TS modes in laminar boundary layers. Mode interaction methods have been successfully used in fluid systems to control related instabilities, such as the Rayleigh—Taylor instability [LMV01]. Here, we present some recent results on using these methods to control TS modes in a compressible, 2D boundary layer over a flat plate at zero incidence. A given unstable TS mode can be stabilized by coupling its spatial evolution with that of a second selected stable TS mode, in such a way that the stable mode takes energy from the unstable one and gives a stable coupled evolution of both modes. The coupling device is a wavetrain in the boundary layer, with appropriate wavenumber and frequency, which can be created by an array of oscillators on the wall, and promotes both (i) parametric coupling between the stable and unstable TS modes and (ii) a mean flow that is also stabilizing. Three differences with wave cancelation methods are relevant. Namely, (a) nonlinear terms play an essential role in the process; (b) the unstable TS mode is stabilized (its growth rate is decreased), not just canceled; and (c) stabilization does not depend on the phase of the incoming wave, which implies that active control is not necessary

Active adaptive conservation of threatened species in the face of uncertainty

Adaptive management has a long history in the natural resource management literature, but despite this, few practitioners have developed adaptive strategies to conserve threatened species. Active adaptive management provides a framework for valuing learning by measuring the degree to which it improves long-run management outcomes. The challenge of an active adaptive approach is to find the correct balance between gaining knowledge to improve management in the future and achieving the best short-term outcome based on current knowledge. We develop and analyze a framework for active adaptive management of a threatened species. Our case study concerns a novel facial tumor disease affecting the Australian threatened species Sarcophilus harrisii: the Tasmanian devil. We use stochastic dynamic programming with Bayesian updating to identify the management strategy that maximizes the Tasmanian devil population growth rate, taking into account improvements to management through learning to better understand disease latency and the relative effectiveness of three competing management options. Exactly which management action we choose each year is driven by the credibility of competing hypotheses about disease latency and by the population growth rate predicted by each hypothesis under the competing management actions. We discover that the optimal combination of management actions depends on the number of sites available and the time remaining to implement management. Our approach to active adaptive management provides a framework to identify the optimal amount of effort to invest in learning to achieve long-run conservation objectives

Description and field performance of the Walker Branch throughfall displacement experiment: 1993--1996

The authors are conducting a large-scale manipulative field experiment in an upland oak forest on the Walker Branch Watershed in eastern Tennessee to identify important ecosystem responses that might result from future precipitation changes. The manipulation of soil water content is being implemented by a gravity-driven transfer of throughfall from one 6400-m{sup 2} treatment plot to another. Throughfall is intercepted in {approx}1850 subcanopy troughs suspended above the forest floor of the dry plot and transferred by gravity flow across an ambient plot for subsequent distribution onto the wet treatment plot. Soil water content is being monitored at two depths with time domain reflectometers at 310 sampling locations across the site. The experimental system is able to produce statistically significant differences in soil water content in years having both dry and wet conditions. Maximum soil water content differentials between wet and dry plots in the 0- to 0.35-m horizon were 8 to 10% during summers with abundant precipitation and 3 to 5% during drought periods. Treatment impacts on soil water potential were restricted to the surface soil layer. Comparisons of pre- and post-installation soil and litter temperature measurements showed the ability of the experimental design to produce changes in soil water content and water potential without creating large artifacts in the forest understory environment

Progress in Classical and Quantum Variational Principles

We review the development and practical uses of a generalized Maupertuis least action principle in classical mechanics, in which the action is varied under the constraint of fixed mean energy for the trial trajectory. The original Maupertuis (Euler-Lagrange) principle constrains the energy at every point along the trajectory. The generalized Maupertuis principle is equivalent to Hamilton's principle. Reciprocal principles are also derived for both the generalized Maupertuis and the Hamilton principles. The Reciprocal Maupertuis Principle is the classical limit of Schr\"{o}dinger's variational principle of wave mechanics, and is also very useful to solve practical problems in both classical and semiclassical mechanics, in complete analogy with the quantum Rayleigh-Ritz method. Classical, semiclassical and quantum variational calculations are carried out for a number of systems, and the results are compared. Pedagogical as well as research problems are used as examples, which include nonconservative as well as relativistic systems

Nitrogen Increases Early-Stage and Slows Late-Stage Decomposition Across Diverse Grasslands

To evaluate how increased anthropogenic nutrient inputs alter carbon cycling in grasslands, we conducted a litter decomposition study across 20 temperate grasslands on three continents within the Nutrient Network, a globally distributed nutrient enrichment experiment We determined the effects of addition of experimental nitrogen (N), phosphorus (P) and potassium plus micronutrient (Kμ) on decomposition of a common tree leaf litter in a long-term study (maximum of 7 years; exact deployment period varied across sites). The use of higher order decomposition models allowed us to distinguish between the effects of nutrients on early- versus late-stage decomposition. Across continents, the addition of N (but not other nutrients) accelerated early-stage decomposition and slowed late-stage decomposition, increasing the slowly decomposing fraction by 28% and the overall litter mean residence time by 58%. Synthesis. Using a novel, long-term cross-site experiment, we found widespread evidence that N enhances the early stages of above-ground plant litter decomposition across diverse and widespread temperate grassland sites but slows late-stage decomposition. These findings were corroborated by fitting the data to multiple decomposition models and have implications for N effects on soil organic matter formation. For example, following N enrichment, increased microbial processing of litter substrates early in decomposition could promote the production and transfer of low molecular weight compounds to soils and potentially enhance the stabilization of mineral-associated organic matter. By contrast, by slowing late-stage decomposition, N enrichment could promote particulate organic matter (POM) accumulation. Such hypotheses deserve further testing