Completely bounded disjointness preserving operators between Fourier algebras

In this paper, we characterize surjective completely bounded disjointness preserving linear operators on Fourier algebras of locally compact amenable groups. We show that such operators are given by weighted homomorphisms induced by piecewise affine proper maps. © 2011 Elsevier Inc.

Thermal conductivities of ionic liquids over the temperature range from 293 K to 353 K

The thermal conductivities of 11 ionic liquids were determined, over the temperature range from 293 K to 353 K, at atmospheric pressure, using an apparatus based on the transient hot-wire method. For each of the ionic liquids studied, the thermal conductivities were found to be between (0.1 and 0.2) W.m(-1).K-1, with a slight decrease observed on increasing temperature. The uncertainty is estimated to be less than +/- 0.002 W.m(-1).K-1. In all cases, a linear equation was found to give a good fit to the data. The effects of water content and chloride content on the thermal conductivities of some of the ionic liquids were investigated. In each case, the thermal conductivities of the water + ionic liquid and chloride + ionic liquid binary mixtures were found to be less than the weighted average of the pure component thermal conductivities. This effect was adequately modeled using the Jamieson correlation. Chloride contamination at typical postsynthesis levels was found to have no significant effect on the thermal conductivities of the ionic liquid studied.

Centennial-scale climate change in Ireland during the Holocene

We examine mid- to late Holocene centennial-scale climate variability in Ireland using proxy data from peatlands, lakes and a speleothem. A high degree of between-record variability is apparent in the proxy data and significant chronological uncertainties are present. However, tephra layers provide a robust tool for correlation and improve the chronological precision of the records. Although we can find no statistically significant coherence in the dataset as a whole, a selection of high-quality peatland water table reconstructions co-vary more than would be expected by chance alone. A locally weighted regression model with bootstrapping can be used to construct a ‘best-estimate’ palaeoclimatic reconstruction from these datasets. Visual comparison and cross-wavelet analysis of peatland water table compilations from Ireland and Northern Britain show that there are some periods of coherence between these records. Some terrestrial palaeoclimatic changes in Ireland appear to coincide with changes in the North Atlantic thermohaline circulation and solar activity. However, these relationships are inconsistent and may be obscured by chronological uncertainties. We conclude by suggesting an agenda for future Holocene climate research in Ireland. ©2013 Elsevier B.V. All rights reserved.

Strudel: A corpus-based semantic model based on properties and types

Computational models of meaning trained on naturally occurring text successfully model human performance on tasks involving simple similarity measures, but they characterize meaning in terms of undifferentiated bags of words or topical dimensions. This has led some to question their psychological plausibility (Murphy, 2002; Schunn, 1999). We present here a fully automatic method for extracting a structured and comprehensive set of concept descriptions directly from an English part-of-speech-tagged corpus. Concepts are characterized by weighted properties, enriched with concept-property types that approximate classical relations such as hypernymy and function. Our model outperforms comparable algorithms in cognitive tasks pertaining not only to concept-internal structures (discovering properties of concepts, grouping properties by property type) but also to inter-concept relations (clustering into superordinates), suggesting the empirical validity of the property-based approach. Copyright © 2009 Cognitive Science Society, Inc. All rights reserved.

Genome scan meta-analysis of schizophrenia and bipolar disorder, part II:Schizophrenia

Schizophrenia is a common disorder with high heritability and a 10-fold increase in risk to siblings of probands. Replication has been inconsistent for reports of significant genetic linkage. To assess evidence for linkage across studies, rank-based genome scan meta-analysis (GSMA) was applied to data from 20 schizophrenia genome scans. Each marker for each scan was assigned to 1 of 120 30-cM bins, with the bins ranked by linkage scores (1 = most significant) and the ranks averaged across studies (R(avg)) and then weighted for sample size (N(sqrt)[affected casess]). A permutation test was used to compute the probability of observing, by chance, each bin's average rank (P(AvgRnk)) or of observing it for a bin with the same place (first, second, etc.) in the order of average ranks in each permutation (P(ord)). The GSMA produced significant genomewide evidence for linkage on chromosome 2q (PAvgRnk

Experimental Evaluations of Elementary Science Programs: A Best-Evidence Synthesis

This article presents a systematic review of research on the achievement outcomes of all types of approaches to teaching science in elementary schools. Study inclusion criteria included use of randomized or matched control groups, a study duration of at least 4 weeks, and use of achievement measures independent of the experimental treatment. A total of 23 studies met these criteria. Among studies evaluating inquiry-based teaching approaches, programs that used science kits did not show positive outcomes on science achievement measures (weighted ES=+0.02 in 7 studies), but inquiry-based programs that emphasized professional development but not kits did show positive outcomes (weighted ES=+0.36 in 10 studies). Technological approaches integrating video and computer resources with teaching and cooperative learning showed positive outcomes in a few small, matched studies (ES=+0.42 in 6 studies). The review concludes that science teaching methods focused on enhancing teachers’ classroom instruction throughout the year, such as cooperative learning and science-reading integration, as well as approaches that give teachers technology tools to enhance instruction, have significant potential to improve science learning.

Validation of a regional Indonesian seas model based on a comparison between model and INSTANT transports

The International Nusantara Stratification and Transport (INSTANT) program measured currents through multiple Indonesian Seas passages simultaneously over a three-year period (from January 2004 to December 2006). The Indonesian Seas region has presented numerous challenges for numerical modelers - the Indonesian Throughflow (ITF) must pass over shallow sills, into deep basins, and through narrow constrictions on its way from the Pacific to the Indian Ocean. As an important region in the global climate puzzle, a number of models have been used to try and best simulate this throughflow. In an attempt to validate our model, we present a comparison between the transports calculated from our model and those calculated from the INSTANT in situ measurements at five passages within the Indonesian Seas (Labani Channel, Lifamatola Passage, Lombok Strait, Ornbai Strait, and Timor Passage). Our Princeton Ocean Model (POM) based regional Indonesian Seas model was originally developed to analyze the influence of bottom topography on the temperature and salinity distributions in the Indonesian seas region, to disclose the path of the South Pacific Water from the continuation of the New Guinea Coastal Current entering the region of interest up to the Lifamatola Passage, and to assess the role of the pressure head in driving the ITF and in determining its total transport. Previous studies found that this model reasonably represents the general long-term flow (seasons) through this region. The INSTANT transports were compared to the results of this regional model over multiple timescales. Overall trends are somewhat represented but changes on timescales shorter than seasonal (three months) and longer than annual were not considered in our model. Normal velocities through each passage during every season are plotted. Daily volume transports and transport-weighted temperature and salinity are plotted and seasonal averages are tabulated.

Trace Element Abundance and Renal Disease

This research investigates the relationship between elevated trace elements in soils, stream sediments and stream water and the prevalence of Chronic Kidney Disease (CKD). The study uses a collaboration of datasets provided from the UK Renal Registry Report (UKRR) on patients with renal diseases requiring treatment including Renal Replacement Therapy (RRT), the soil geochemical dataset for Northern Ireland provided by the Tellus Survey, Geological Survey of Northern Ireland (GSNI) and the bioaccessibility of Potentially Toxic Elements (PTEs) from soil samples which were obtained from the Unified Barge Method (UBM). The relationship between these factors derives from the UKRR report which highlights incidence rates of renal impaired patients showing regional variation with cases of unknown aetiology. Studies suggest a potential cause of the large variation and uncertain aetiology is associated with underlying environmental factors such as the oral bioaccessibility of trace elements in the gastrointestinal tract.
As previous research indicates that long term exposure is related to environmental factors, Northern Ireland is ideally placed for this research as people traditionally live in the same location for long periods of time. Exploratory data analysis and multivariate analyses are used to examine the soil, stream sediments and stream water geochemistry data for a range of key elements including arsenic, lead, cadmium and mercury identified from a review of previous renal disease literature. The spatial prevalence of patients with long term CKD is analysed on an area basis. Further work includes cluster analysis to detect areas of low or high incidences of CKD that are significantly correlated in space, Geographical Weighted Regression (GWR) and Poisson kriging to examine locally varying relationship between elevated concentrations of PTEs and the prevalence of CKD.

Adaptive NormalHedge for robust visual tracking

In this paper, we propose a novel visual tracking framework, based on a decision-theoretic online learning algorithm namely NormalHedge. To make NormalHedge more robust against noise, we propose an adaptive NormalHedge algorithm, which exploits the historic information of each expert to perform more accurate prediction than the standard NormalHedge. Technically, we use a set of weighted experts to predict the state of the target to be tracked over time. The weight of each expert is online learned by pushing the cumulative regret of the learner towards that of the expert. Our simulation experiments demonstrate the effectiveness of the proposed adaptive NormalHedge, compared to the standard NormalHedge method. Furthermore, the experimental results of several challenging video sequences show that the proposed tracking method outperforms several state-of-the-art methods.

Ecological impacts of invasive alien species along temperature gradients: testing the role of environmental matching

Invasive alien species (IAS) can cause substantive ecological impacts, and the role of temperature in mediating these impacts may become increasingly significant in a changing climate. Habitat conditions and physiological optima offer predictive information for IAS impacts in novel environments. Here, using meta-analysis and laboratory experiments, we tested the hypothesis that the impacts of IAS in the field are inversely correlated with the difference in their ambient and optimal temperatures. A meta-analysis of 29 studies of consumptive impacts of IAS in inland waters revealed that the impacts of fishes and crustaceans are higher at temperatures that more closely match their thermal growth optima. In particular, the maximum impact potential was constrained by increased differences between ambient and optimal temperatures, as indicated by the steeper slope of a quantile regression on the upper 25th percentile of impact data compared to that of a weighted linear regression on all data with measured variances. We complemented this study with an experimental analysis of the functional response - the relationship between predation rate and prey supply - of two invasive predators (freshwater mysid shrimp, Hemimysis anomala and Mysis diluviana) across relevant temperature gradients; both of these species have previously been found to exert strong community-level impacts that are corroborated by their functional responses to different prey items. The functional response experiments showed that maximum feeding rates of H. anomala and M. diluviana have distinct peaks near their respective thermal optima. Although variation in impacts may be caused by numerous abiotic or biotic habitat characteristics, both our analyses point to temperature as a key mediator of IAS impact levels in inland waters and suggest that IAS management should prioritize habitats in the invaded range that more closely match the thermal optima of targeted invaders.

Covariance Averaging for Improved Estimation and Portfolio Allocation

We propose a new method for estimating the covariance matrix of a multivariate time series of nancial returns. The method is based on estimating sample covariances from overlapping windows of observations which are then appropriately weighted to obtain the nal covariance estimate. We extend the idea of (model) covariance averaging o ered in the covariance shrinkage approach by means of greater ease of use, exibility and robustness in averaging information over different data segments. The suggested approach does not su er from the curse of dimensionality and can be used without problems of either approximation or any demand for numerical optimization.

Momentum Trading in New York Stock Exchange (NYSE) Energy Stocks

This paper investigates whether the momentum effect exists in the NYSE energy sector. Momentum is defined as the strategy that buys (sells) these stocks that are best (worst) performers, over a pre-specified past period of time (the 'look-back' period), by constructing equally weighted portfolios. Different momentum strategies are obtained by changing the number of stocks included in these portfolios, as well as the look-back period. Next, their performance is compared against two benchmarks: the equally weighted portfolio consisting of most stocks in the NYSE energy index and the market portfolio, and the S&P500 index. The results indicate that the momentum effect is strongly present in the energy sector, and leads to highly profitable portfolios, improving the risk-reward measures and easily outperforming both benchmarks.

Children, Adults, Autonomy and Well-Being

I explore the implications of a view – that children and adults enjoy a markedly different moral and political status, wherein the latter can and should be permitted to make choices as to how they lead their lives, whereas the former should not be permitted to make such choices – for how we think about the relationship between autonomy and welfare, and in particular, in consequence, for how we evaluate paternalism. I discuss the problem of drawing a line and the ‘threshold problem’, and consider how one might, as the UNCRC requires, give a weighted role to the views of the child on matters affecting its own interests.

A population-based study of adverse physical effects following prostate cancer treatments: Results from the PiCTure (Prostate cancer treatment – your experience) study

Background:

Men and clinicians need reliable population based information when making decisions about investigation and treatment of prostate cancer. In the absence of clearly preferred treatments, differences in outcomes become more important.

Aim:

To investigate rates of adverse physical effects among prostate cancer survivors 2-15 years post diagnosis by treatment, and estimate population burden.

Methods:

A cross sectional, postal survey to 6,559 survivors (all ages) diagnosed with primary, invasive prostate cancer (ICD10-C61), identified in Northern Ireland and the Republic of Ireland via cancer registries. Questions included symptoms at diagnosis, treatments received and adverse physical effects (impotence, urinary incontinence, bowel problems, breast changes, libido loss, hot flashes, fatigue) experienced ‘ever’ and ‘current’ i.e. at questionnaire completion. Physical effect levels were weighted by age, country and time since diagnosis for all prostate cancer survivors. Bonferroni corrections were applied to account for multiple comparisons.

Results:

Adjusted response rate 54%, (n=3,348). 75% reported at least one current physical effect (90% ever), with 29% reporting at least three. These varied by treatment. Current impotence was reported by 76% post-prostatectomy, 64% post-external beam radiotherapy with hormone therapy, with average for all survivors of 57%. Urinary incontinence (overall current level: 16%) was highest post-prostatectomy (current 28%, ever 70%). 42% of brachytherapy patients reported no current adverse physical effects; however 43% reported current impotence and 8% current incontinence. Current hot flashes (41%), breast changes (18%) and fatigue (28%) were reported more commonly by patients on hormone therapy.

Conclusions:

This study provides evidence that adverse physical effects following prostate cancer represent a significant public health burden; an estimated 1.6% of men over 45 is a prostate cancer survivor with a current adverse physical effect. This information should facilitate investigation and treatment decision-making and follow-up care of patients.

ZIL: An Energy-Efficient Indoor Localization System Using ZigBee Radio to Detect WiFi Fingerprints

In existing WiFi-based localization methods, smart mobile devices consume quite a lot of power as WiFi interfaces need to be used for frequent AP scanning during the localization process. In this work, we design an energy-efficient indoor localization system called ZigBee assisted indoor localization (ZIL) based on WiFi fingerprints via ZigBee interference signatures. ZIL uses ZigBee interfaces to collect mixed WiFi signals, which include non-periodic WiFi data and periodic beacon signals. However, WiFi APs cannot be identified from these WiFi signals by ZigBee interfaces directly. To address this issue, we propose a method for detecting WiFi APs to form WiFi fingerprints from the signals collected by ZigBee interfaces. We propose a novel fingerprint matching algorithm to align a pair of fingerprints effectively. To improve the localization accuracy, we design the K-nearest neighbor (KNN) method with three different weighted distances and find that the KNN algorithm with the Manhattan distance performs best. Experiments show that ZIL can achieve the localization accuracy of 87%, which is competitive compared to state-of-the-art WiFi fingerprint-based approaches, and save energy by 68% on average compared to the approach based on WiFi interface.