Understanding Algorithm Performance on an Oversubscribed Scheduling Application

The best performing algorithms for a particular oversubscribed scheduling application, Air Force Satellite Control Network (AFSCN) scheduling, appear to have little in common. Yet, through careful experimentation and modeling of performance in real problem instances, we can relate characteristics of the best algorithms to characteristics of the application. In particular, we find that plateaus dominate the search spaces (thus favoring algorithms that make larger changes to solutions) and that some randomization in exploration is critical to good performance (due to the lack of gradient information on the plateaus). Based on our explanations of algorithm performance, we develop a new algorithm that combines characteristics of the best performers; the new algorithms performance is better than the previous best. We show how hypothesis driven experimentation and search modeling can both explain algorithm performance and motivate the design of a new algorithm

Coping and Management Techniques Used by Chronic Low Back Pain Patients Receiving Treatment From Chiropractors.

OBJECTIVES:The purpose of this study was to describe coping strategies (eg, mechanisms, including self-treatment) that a person uses to reduce pain and its impact on functioning as reported by patients with chronic low back pain who were seen by doctors of chiropractic and how these coping strategies vary by patient characteristics. METHODS:Data were collected from a national sample of US chiropractic patients recruited from chiropractic practices in 6 states from major geographical regions of the United States using a multistage stratified sampling strategy. Reports of coping behaviors used to manage pain during the past 6 months were used to create counts across 6 domains: cognitive, self-care, environmental, medical care, social activities, and work. Exploratory analyses examined counts in domains and frequencies of individual items by levels of patient characteristics. RESULTS:A total of 1677 respondents with chronic low back pain reported using an average of 9 coping behaviors in the prior 6 months. Use of more types of behaviors were reported among those with more severe back pain, who rated their health as fair or poor and who had daily occurrences of pain. Exercise was more frequent among the healthy and those with less pain. Female respondents tended to report using more coping behaviors than men, and Hispanics more than non-Hispanics. CONCLUSION:Persons with chronic back pain were proactive in their coping strategies and frequently used self-care coping strategies like those provided by chiropractors in patient education. In alignment with patients' beliefs that their condition was chronic and lifelong, many patients attempted a wide range of coping strategies to relieve their pain

Comparing the Penman-Monteith equation and a modified Jarvis-Stewart model with an artificial neural network to estimate stand-scale transpiration and canopy conductance

The responses of canopy conductance to variation in solar radiation, vapour pressure deficit and soil moisture have been extensively modelled using a Jarvis-Stewart (JS) model. Modelled canopy conductance has then often been used to predict transpiration using the Penman-Monteith (PM) model. We previously suggested an alternative approach in which the JS model is modified to directly estimate transpiration rather than canopy conductance. In the present study we used this alternative approach to model tree water fluxes from an Australian native forest over an annual cycle. For comparative purposes we also modelled canopy conductance and estimated transpiration via the PM model. Finally we applied an artificial neural network as a statistical benchmark to compare the performance of both models. Both the PM and modified JS models were parameterised using solar radiation, vapour pressure deficit and soil moisture as inputs with results that compare well with previous studies. Both models performed comparably well during the summer period. However, during winter the PM model was found to fail during periods of high rates of transpiration. In contrast, the modified JS model was able to replicate observed sapflow measurements throughout the year although it too tended to underestimate rates of transpiration in winter under conditions of high rates of transpiration. Both approaches to modelling transpiration gave good agreement with hourly, daily and total sums of sapflow measurements with the modified JS and PM models explaining 87% and 86% of the variance, respectively. We conclude that these three approaches have merit at different time-scales. © 2009 Elsevier B.V. All rights reserved

Is productivity of mesic savannas light limited or water limited? Results of a simulation study

A soil-plant-atmosphere model was used to estimate gross primary productivity (GPP) and evapotranspiration (ET) of a tropical savanna in Australia. This paper describes model modifications required to simulate the substantial C4 grass understory together with C3 trees. The model was further improved to include a seasonal distribution of leaf area and foliar nitrogen through 10 canopy layers. Model outputs were compared with a 5-year eddy covariance dataset. Adding the C4 photosynthesis component improved the model efficiency and root-mean-squared error (RMSE) for total ecosystem GPP by better emulating annual peaks and troughs in GPP across wet and dry seasons. The C4 photosynthesis component had minimal impact on modelled values of ET. Outputs of GPP from the modified model agreed well with measured values, explaining between 79% and 90% of the variance and having a low RMSE (0.003-0.281gCm-2day-1). Approximately, 40% of total annual GPP was contributed by C4 grasses. Total (trees and grasses) wet season GPP was approximately 75-80% of total annual GPP. Light-use efficiency (LUE) was largest for the wet season and smallest in the dry season and C4 LUE was larger than that of the trees. A sensitivity analysis of GPP revealed that daily GPP was most sensitive to changes in leaf area index (LAI) and foliar nitrogen (Nf) and relatively insensitive to changes in maximum carboxylation rate (Vcmax), maximum electron transport rate (Jmax) and minimum leaf water potential (ψmin). The modified model was also able to represent daily and seasonal patterns in ET, (explaining 68-81% of variance) with a low RMSE (0.038-0.19mmday-1). Current values of Nf, LAI and other parameters appear to be colimiting for maximizing GPP. By manipulating LAI and soil moisture content inputs, we show that modelled GPP is limited by light interception rather than water availability at this site. © 2011 Blackwell Publishing Ltd

A modified Jarvis-Stewart model for predicting stand-scale transpiration of an Australian native forest

Rates of water uptake by individual trees in a native Australian forest were measured on the Liverpool Plains, New South Wales, Australia, using sapflow sensors. These rates were up-scaled to stand transpiration rate (expressed per unit ground area) using sapwood area as the scalar, and these estimates were compared with modelled stand transpiration. A modified Jarvis-Stewart modelling approach (Jarvis 1976), previously used to calculate canopy conductance, was used to calculate stand transpiration rate. Three environmental variables, namely solar radiation, vapour pressure deficit and soil moisture content, plus leaf area index, were used to calculate stand transpiration, using measured rates of tree water use to parameterise the model. Functional forms for the model were derived by use of a weighted non-linear least squares fitting procedure. The model was able to give comparable estimates of stand transpiration to those derived from a second set of sapflow measurements. It is suggested that short-term, intensive field campaigns where sapflow, weather and soil water content variables are measured could be used to estimate annual patterns of stand transpiration using daily variation in these three environmental variables. Such a methodology will find application in the forestry, mining and water resource management industries where long-term intensive data sets are frequently unavailable. © 2007 Springer Science+Business Media B.V

Onboard Evolution of Understandable Swarm Behaviors

Designing the individual robot rules that give rise to desired emergent swarm behaviors is difficult. The common method of running evolutionary algorithms off‐line to automatically discover controllers in simulation suffers from two disadvantages: the generation of controllers is not situated in the swarm and so cannot be performed in the wild, and the evolved controllers are often opaque and hard to understand. A swarm of robots with considerable on‐board processing power is used to move the evolutionary process into the swarm, providing a potential route to continuously generating swarm behaviors adapted to the environments and tasks at hand. By making the evolved controllers human‐understandable using behavior trees, the controllers can be queried, explained, and even improved by a human user. A swarm system capable of evolving and executing fit controllers entirely onboard physical robots in less than 15 min is demonstrated. One of the evolved controllers is then analyzed to explain its functionality. With the insights gained, a significant performance improvement in the evolved controller is engineered

Expression of voltage-dependent potassium channels in first trimester human placentae

Potassium channel α-subunits encoded by KCNQ1-5 genes form voltage-dependent channels (Kv7), modulated by KCNE1-5 encoded accessory proteins. The aim was to determine KCNQ and KCNE mRNA expression and assess protein expression/localisation of the KCNQ3 and KCNE5 isoforms in first trimester placental tissue. Placentae were obtained from women undergoing elective surgical termination of pregnancy (TOP) at 10 weeks’ (mid TOP) gestations. KCNQ1-5 expression was unchanged during the first trimester. KCNE5 expression increased in mid TOP vs. early TOP samples (P=0.022). This novel study reports mRNA and protein expression of Kv7 channels in first trimester placentae

Loneliness, social relations and health and wellbeing in deprived communities

There is growing policy concern about the extent of loneliness in advanced societies, and its prevalence among various social groups. This study looks at loneliness among people living in deprived communities, where there may be additional barriers to social engagement including low incomes, fear of crime, poor services and transient populations. The aim was to examine the prevalence of loneliness, and also its associations with different types of social contacts and forms of social support, and its links to self-reported health and wellbeing in the population group. The method involved a cross-sectional survey of 4,302 adults across 15 communities, with the data analysed using multinomial logistic regression controlling for sociodemographics, then for all other predictors within each domain of interest. Frequent feelings of loneliness were more common among those who: had contact with family monthly or less; had contact with neighbours weekly or less; rarely talked to people in the neighbourhood; and who had no available sources of practical or emotional support. Feelings of loneliness were most strongly associated with poor mental health, but were also associated with long-term problems of stress, anxiety and depression, and with low mental wellbeing, though to a lesser degree. The findings are consistent with a view that situational loneliness may be the product of residential structures and resources in deprived areas. The findings also show that neighbourly behaviours of different kinds are important for protecting against loneliness in deprived communities. Familiarity within the neighbourhood, as active acquaintance rather than merely recognition, is also important. The findings are indicative of several mechanisms that may link loneliness to health and wellbeing in our study group: loneliness itself as a stressor; lonely people not responding well to the many other stressors in deprived areas; and loneliness as the product of weak social buffering to protect against stressors

Innovation as a Nonlinear Process, the Scientometric Perspective, and the Specification of an "Innovation Opportunities Explorer"

The process of innovation follows non-linear patterns across the domains of science, technology, and the economy. Novel bibliometric mapping techniques can be used to investigate and represent distinctive, but complementary perspectives on the innovation process (e.g., "demand" and "supply") as well as the interactions among these perspectives. The perspectives can be represented as "continents" of data related to varying extents over time. For example, the different branches of Medical Subject Headings (MeSH) in the Medline database provide sources of such perspectives (e.g., "Diseases" versus "Drugs and Chemicals"). The multiple-perspective approach enables us to reconstruct facets of the dynamics of innovation, in terms of selection mechanisms shaping localizable trajectories and/or resulting in more globalized regimes. By expanding the data with patents and scholarly publications, we demonstrate the use of this multi-perspective approach in the case of RNA Interference (RNAi). The possibility to develop an "Innovation Opportunities Explorer" is specified.Comment: Technology Analysis and Strategic Management (forthcoming in 2013