Dissolved Argon Changes the Rate of Diffusion in Room Temperature Ionic Liquids: Effect of the Presence and Absence of Argon and Nitrogen on the Voltammetry of Ferrocene

This work explores the effects of argon and nitrogen, two electrochemically and chemically inert gases frequently used in sample preparation of room temperature ionic liquid (RTIL) solutions, on the eelectrochemical characterization of ferrocene (Fc) dissolved in the RTIL 1-ethyl-3-methylimidazolium bis(trifluoromethanesulfonyl)imide ([C(2)mim][NTf2]). Remarkably, chronoamperometrically determined diffusion coefficients of Fc in [C(2)mim][NTf2] are found to increase from 4.8 (+/- 0.2) x 10(-11) m(2) s(-1) under vacuum conditions to 6.6 (+/- 0.5) x 10(-11) m(2) s(-1) in an atmosphere of 1 atm Ar. In contrast, exposing a vacuum-purified sample to an atmosphere of 1 atm N-2 resulted in no significant change in the measured diffusion coefficient of Fc. The effect of dissolved argon on diffusion transport is unexpected and has implications in electrochemistry and elsewhere. Fc was found to volatilize under vacuum conditions. We propose, however, that evacuation of the cell by vacuum prior to electrochemical measurements being carried out is the only way to ensure that no contamination of the sample occurs, and use of an in situ method of determining the diffusion coefficient and concentration of Fc dispells,any ambiguity associated with Fc depletion by vacuum.

The effect of temperature and strain rate on the deformation behaviour, structure development and properties of biaxially stretched PET-clay nanocomposites.

The inclusion of a synthetic fluoromica clay in PET affects its processability via biaxial stretching and stretching temperature (95 °C and 102 °C) and strain rate (1 s-1 and 2 s-1) influence the structuring and properties of the stretched material. The inclusion of clay has little effect on the temperature operating window for the PET–clay but it has a major effect on deformation behaviour which will necessitate the use of much higher forming forces during processing. The strain hardening behaviour of both the filled and unfilled materials is well correlated with tensile strength and tensile modulus. Increasing the stretching temperature to reduce stretching forces has a detrimental effect on clay exfoliation, mechanical and O2 barrier properties. Increasing strain rate has a lesser effect on the strain hardening behaviour of the PET–clay compared with the pure PET and this is attributed to possible adiabatic heating in the PET–clay sample at the higher strain rate. The Halpin–Tsai model is shown to accurately predict the modulus enhancement of the PET–clay materials when a modified particle modulus rather than nominal clay modulus is used.

The empirical metallicity dependence of the mass-loss rate of O- and early B-type stars

We present a comprehensive study of the observational dependence of the mass-loss rate in stationary stellar winds of hot massive stars on the metal content of their atmospheres. The metal content of stars in the Magellanic Clouds is discussed, and a critical assessment is given of state-of-the-art mass-loss determinations of OB stars in these two satellite systems and the Milky-Way. Assuming a power-law dependence of mass loss on metal content,. M. Z(m), and adopting a theoretical relation between the terminal flow velocity and metal content, v(infinity). Z(0.13) (Leitherer et al. 1992, ApJ, 401, 596), we find m = 0.83 +/- 0.16 for non-clumped outflows from an analysis of the wind momentum luminosity relation (WLR) for stars more luminous than 105.2 L circle dot. Within the errors, this result is in agreement with the prediction m = 0.69 +/- 0.10 by Vink et al. (2001, A& A, 369, 574). Absolute empirical values for the mass loss, based on Ha and ultraviolet (UV) wind lines, are found to be a factor of two higher than predictions in this high luminosity regime. If this difference is attributed to inhomogeneities in the wind, and this clumping does not impact the predictions, this would imply that luminous O and early-B stars have clumping factors in their Ha and UV line forming regions of about a factor of four. For lower luminosity stars, the winds are so weak that their strengths can generally no longer be derived from optical spectral lines (essentially Ha) and one must currently rely on the analysis of UV lines. We confirm that in this low-luminosity domain the observed Galactic WLR is found to be much steeper than expected from theory (although the specific sample is rather small), leading to a discrepancy between UV mass-loss rates and the predictions by a factor 100 at luminosities of L similar to 10(4.75) L circle dot, the origin of which is unknown. We emphasize that even if the current mass-loss rates of hot luminous stars would turn out to be overestimated as a result of wind clumping, but the degree of clumping would be rather independent of metallicity, the scalings derived in this study are expected to remain correct.

A comparison between star formation rate diagnostics and rate of core collapse supernovae within 11 Mpc

Aims. The core collapse supernova rate provides a strong lower limit for the star formation rate (SFR). Progress in using it as a cosmic SFR tracer requires some confidence that it is consistent with more conventional SFR diagnostics in the nearby Universe. This paper compares standard SFR measurements based on H alpha, far ultraviolet (FUV) and total infrared (TIR) galaxy luminosities with the observed core collapse supernova rate in the same galaxy sample. The comparison can be viewed from two perspectives. Firstly, by adopting an estimate of the minimum stellar mass to produce a core collapse supernova one can determine a SFR from supernova numbers. Secondly, the radiative SFR can be assumed to be robust and then the supernova statistics provide a constrain on the minimum stellar mass for core collapse supernova progenitors.

Toward Characterization Of The Type IIP Supernova Progenitor Population: A Statistical Sample Of Light Curves From Pan-STARRS1

In recent years, wide-field sky surveys providing deep multi-band imaging have presented a new path for indirectly characterizing the progenitor populations of core-collapse supernovae (SN): systematic light curve studies. We assemble a set of 76 grizy-band Type IIP SN light curves from Pan-STARRS1, obtained over a constant survey program of 4 years and classified using both spectroscopy and machine learning-based photometric techniques. We develop and apply a new Bayesian model for the full multi-band evolution of each light curve in the sample. We find no evidence of a sub-population of fast-declining explosions (historically referred to as "Type IIL" SNe). However, we identify a highly significant relation between the plateau phase decay rate and peak luminosity among our SNe IIP. These results argue in favor of a single parameter, likely determined by initial stellar mass, predominantly controlling the explosions of red supergiants. This relation could also be applied for supernova cosmology, offering a standardizable candle good to an intrinsic scatter of 0.2 mag. We compare each light curve to physical models from hydrodynamic simulations to estimate progenitor initial masses and other properties of the Pan-STARRS1 Type IIP SN sample. We show that correction of systematic discrepancies between modeled and observed SN IIP light curve properties and an expanded grid of progenitor properties, are needed to enable robust progenitor inferences from multi-band light curve samples of this kind. This work will serve as a pathfinder for photometric studies of core-collapse SNe to be conducted through future wide field transient searches.

The effects of lichen cover upon the rate of solutional weathering of limestone

The contribution of lichens to the biomodification of limestone surfaces is an area of conflict within bioweathering studies, with some researchers suggesting a protective effect induced by lichen coverage and others a deteriorative effect induced by the same organisms.Data are reported demonstrating the potential role of endolithic lichen, in particular of Bagliettoa baldensis, in the active protection of Carboniferous limestone surfaces from rainfall-induced solutional weathering. During a 12-month microcatchment exposure period in the west of Northern Ireland, average dissolutional losses of calciumare greater from a lichen-free limestone surface compared with a predominantly endolithic lichen-covered surface by just under 1.25 times. During colderwintermonths, the lichen free surface experiences calcium loss almost 1.5 times greater than the lichen-covered surface. Using extrapolation to upscale from the micro-catchment sample scale, for the year of sample exposure, the rate of calcium loss is 1.001 g m−2 a−1 from lichen-covered limestone surfaces and 1.228 gm−2 a−1 from lichen-free bare limestone surfaces. This research has implications for our understanding of karst environments, the contribution of lichens to karren development and the conservation of lichen-colonised dimension stone within a cultural setting.

The ejected mass distribution of Type Ia supernovae: a significant rate of non-Chandrasekhar-mass progenitors

The ejected mass distribution of Type Ia supernovae (SNe Ia) directly probes progenitor evolutionary history and explosion mechanisms, with implications for their use as cosmological probes. Although the Chandrasekhar mass is a natural mass scale for the explosion of white dwarfs as SNe Ia, models allowing SNe Ia to explode at other masses have attracted much recent attention. Using an empirical relation between the ejected mass and the light-curve width, we derive ejected masses Mej and 56Ni masses MNi for a sample of 337 SNe Ia with redshifts z <0.7 used in recent cosmological analyses. We use hierarchical Bayesian inference to reconstruct the joint Mej-MNi distribution, accounting for measurement errors. The inferred marginal distribution of Mej has a long tail towards sub-Chandrasekhar masses, but cuts off sharply above 1.4 M⊙. Our results imply that 25-50 per cent of normal SNe Ia are inconsistent with Chandrasekhar-mass explosions, with almost all of these being sub-Chandrasekhar mass; super-Chandrasekhar-mass explosions make up no more than 1 per cent of all spectroscopically normal SNe Ia. We interpret the SN Ia width-luminosity relation as an underlying relation between Mej and MNi, and show that the inferred relation is not naturally explained by the predictions of any single known explosion mechanism.

Obesity markers and blood pressure in a sample of Portuguese children and adolescents.

Little information exists regarding the effect of several obesity markers on blood pressure (BP) levels in youth. Transverse study including 2494 boys and 2589 girls. Height, weight and waist were measured according to the international criteria and body fat (BF) by bioimpedance. BP was measured by an automated device. Hypertension was defined using sex-specific, age-specific and height-specific observation-points. Body mass index (BMI) and waist were positively related with systolic blood pressure (SBP) and diastolic blood pressure (DBP) and heart rate in both sexes, whereas the relationships with BF were less consistent. Stepwise linear regression analysis showed that BMI was positively related with SBP and DBP in both sexes, whereas BF was negatively related with SBP in both sexes and with heart rate in boys only; finally, waist was positively related with SBP in boys and heart rate in girls. Age and heart rate-adjusted values of SBP and DBP increased with BMI: for SBP, 117+/-1, 123+/-1 and 124+/-1 mmHg in normal, overweight and obese boys, respectively; corresponding values for girls were 111+/-1, 114+/-1 and 116+/-2 mmHg (mean+/-SE, P<0.001). Overweight and obese boys had an odds ratio for being hypertensive of 2.26 (95% confidence interval: 1.79-2.86) and 3.36 (2.32-4.87), respectively; corresponding values for girls were 1.58 (confidence interval 1.25-1.99) and 2.31 (1.53-3.50). BMI, not BF or waist, is consistently and independently related to BP levels in children; overweight and obesity considerably increase the risk of hypertension.

Finite-Sample Simulation-Based Inference in VAR Models with Applications to Order Selection and Causality Testing

Statistical tests in vector autoregressive (VAR) models are typically based on large-sample approximations, involving the use of asymptotic distributions or bootstrap techniques. After documenting that such methods can be very misleading even with fairly large samples, especially when the number of lags or the number of equations is not small, we propose a general simulation-based technique that allows one to control completely the level of tests in parametric VAR models. In particular, we show that maximized Monte Carlo tests [Dufour (2002)] can provide provably exact tests for such models, whether they are stationary or integrated. Applications to order selection and causality testing are considered as special cases. The technique developed is applied to quarterly and monthly VAR models of the U.S. economy, comprising income, money, interest rates and prices, over the period 1965-1996.

Speech sample estimation from composite zerocrossings and encoding via adaptive switching of transforms

This thesis investigates the potential use of zerocrossing information for speech sample estimation. It provides 21 new method tn) estimate speech samples using composite zerocrossings. A simple linear interpolation technique is developed for this purpose. By using this method the A/D converter can be avoided in a speech coder. The newly proposed zerocrossing sampling theory is supported with results of computer simulations using real speech data. The thesis also presents two methods for voiced/ unvoiced classification. One of these methods is based on a distance measure which is a function of short time zerocrossing rate and short time energy of the signal. The other one is based on the attractor dimension and entropy of the signal. Among these two methods the first one is simple and reguires only very few computations compared to the other. This method is used imtea later chapter to design an enhanced Adaptive Transform Coder. The later part of the thesis addresses a few problems in Adaptive Transform Coding and presents an improved ATC. Transform coefficient with maximum amplitude is considered as ‘side information’. This. enables more accurate tfiiz assignment enui step—size computation. A new bit reassignment scheme is also introduced in this work. Finally, sum ATC which applies switching between luiscrete Cosine Transform and Discrete Walsh-Hadamard Transform for voiced and unvoiced speech segments respectively is presented. Simulation results are provided to show the improved performance of the coder

Bayesian sample size for exploratory clinical trials incorporating historical data

This paper presents a simple Bayesian approach to sample size determination in clinical trials. It is required that the trial should be large enough to ensure that the data collected will provide convincing evidence either that an experimental treatment is better than a control or that it fails to improve upon control by some clinically relevant difference. The method resembles standard frequentist formulations of the problem, and indeed in certain circumstances involving 'non-informative' prior information it leads to identical answers. In particular, unlike many Bayesian approaches to sample size determination, use is made of an alternative hypothesis that an experimental treatment is better than a control treatment by some specified magnitude. The approach is introduced in the context of testing whether a single stream of binary observations are consistent with a given success rate p(0). Next the case of comparing two independent streams of normally distributed responses is considered, first under the assumption that their common variance is known and then for unknown variance. Finally, the more general situation in which a large sample is to be collected and analysed according to the asymptotic properties of the score statistic is explored. Copyright (C) 2007 John Wiley & Sons, Ltd.

Affective disorder in the parents of a clinic sample of children with anxiety disorders

Background: Family history studies in adults reveal strong familiality for the anxiety disorders with some specificity. The aim of the current study was to establish whether there was an elevated rate of anxiety disorders in the parents of children with anxiety disorders, and whether there was intergenerational specificity in the form of disorder. Methods: The mental state of a clinic sample of 85 children with anxiety disorder and their parents was systematically assessed, together with a comparison sample of 45 children with no current disorder and their parents. Results: Compared to the rate of anxiety disorder amongst parents of comparison children, the rate of current anxiety disorder in mothers of anxious children was significantly raised, as was the lifetime rate of anxiety disorder for both mothers and fathers. The mothers of children with generalised anxiety disorder, social phobia, specific phobia and separation anxiety disorder all had raised lifetime rates of the corresponding disorder, but also raised rates of others disorders. Limitations: Only 60% of the fathers of the anxious children were assessed. Conclusions: Strong familiality of anxiety disorders was confirmed, especially between child and maternal anxiety disorder. All child anxiety disorders were associated with several forms of anxiety disorder in the mother. Some specificity in the form of anxiety disorder in the child and the mother was apparent for social phobia and separation anxiety disorder. The findings have implications for the management of child anxiety. (c) 2006 Elsevier B.V. All rights reserved.

A family study of co-morbidity between generalized social phobia and generalized anxiety disorder in a non-clinic sample

Background: High rates of co-morbidity between Generalized Social Phobia (GSP) and Generalized Anxiety Disorder (GAD) have been documented. The reason for this is unclear. Family studies are one means of clarifying the nature of co-morbidity between two disorders. Methods: Six models of co-morbidity between GSP and GAD were investigated in a family aggregation study of 403 first-degree relatives of non-clinical probands: 37 with GSP, 22 with GAD, 15 with co-morbid GSP/GAD, and 41 controls with no history of GSP or GAD. Psychiatric data were collected for probands and relatives. Mixed methods (direct and family history interviews) were utilised. Results: Primary contrasts (against controls) found an increased rate of pure GSP in the relatives of both GSP probands and co-morbid GSP/GAD probands, and found relatives of co-morbid GSP/GAD probands to have an increased rate of both pure GAD and comorbid GSP/GAD. Secondary contrasts found (i) increased GSP in the relatives of GSP only probands compared to the relatives of GAD only probands; and (ii) increased GAD in the relatives of co-morbid GSP/GAD probands compared to the relatives of GSP only probands. Limitations: The study did not directly interview all relatives, although the reliability of family history data was assessed. The study was based on an all-female proband sample. The implications of both these limitations are discussed. Conclusions: The results were most consistent with a co-morbidity model indicating independent familial transmission of GSP and GAD. This has clinical implications for the treatment of patients with both disorders. (C) 2006 Elsevier B.V. All fights reserved.

A Double-threshold GARCH Model for the French Franc/Deutschmark exchange rate

This paper combines and generalizes a number of recent time series models of daily exchange rate series by using a SETAR model which also allows the variance equation of a GARCH specification for the error terms to be drawn from more than one regime. An application of the model to the French Franc/Deutschmark exchange rate demonstrates that out-of-sample forecasts for the exchange rate volatility are also improved when the restriction that the data it is drawn from a single regime is removed. This result highlights the importance of considering both types of regime shift (i.e. thresholds in variance as well as in mean) when analysing financial time series.

Bicorrelations and cross-bicorrelations as non-linearity tests and tools for exchange rate forecasting

This paper proposes and implements a new methodology for forecasting time series, based on bicorrelations and cross-bicorrelations. It is shown that the forecasting technique arises as a natural extension of, and as a complement to, existing univariate and multivariate non-linearity tests. The formulations are essentially modified autoregressive or vector autoregressive models respectively, which can be estimated using ordinary least squares. The techniques are applied to a set of high-frequency exchange rate returns, and their out-of-sample forecasting performance is compared to that of other time series models