Power dissipation in nanoscale conductors: classical, semi-classical and quantum dynamics

Modelling Joule heating is a difficult problem because of the need to introduce correct correlations between the motions of the ions and the electrons. In this paper we analyse three different models of current induced heating (a purely classical model, a fully quantum model and a hybrid model in which the electrons are treated quantum mechanically and the atoms are treated classically). We find that all three models allow for both heating and cooling processes in the presence of a current, and furthermore the purely classical and purely quantum models show remarkable agreement in the limit of high biases. However, the hybrid model in the Ehrenfest approximation tends to suppress heating. Analysis of the equations of motion reveals that this is a consequence of two things: the electrons are being treated as a continuous fluid and the atoms cannot undergo quantum fluctuations. A means for correcting this is suggested.

Dynamic pricing model and algorithm for perishable products with fuzzy demand (ABS 2* Journal)

This paper studies the dynamic pricing problem of selling fixed stock of perishable items over a finite horizon, where the decision maker does not have the necessary historic data to estimate the distribution of uncertain demand, but has imprecise information about the quantity demand. We model this uncertainty using fuzzy variables. The dynamic pricing problem based on credibility theory is formulated using three fuzzy programming models, viz.: the fuzzy expected revenue maximization model, a-optimistic revenue maximization model, and credibility maximization model. Fuzzy simulations for functions with fuzzy parameters are given and embedded into a genetic algorithm to design a hybrid intelligent algorithm to solve these three models. Finally, a real-world example is presented to highlight the effectiveness of the developed model and algorithm.

Holding parties responsible at election time: Multi-level, multi-party government and electoral accountability

This paper highlights the crucial role played by party-specific responsibility attributions in performance-based voting. Three models of electoral accountability, which make distinct assumptions regarding citizens' ability to attribute responsibility to distinct governing parties, are tested in the challenging Northern Ireland context - an exemplar case of multi-level multi-party government in which expectations of performance based voting are low. The paper demonstrates the operation of party-attribution based electoral accountability, using data from the 2011 Northern Ireland Assembly Election Study. However, the findings are asymmetric: accountability operates in the Protestant/unionist bloc but not in the Catholic/nationalist bloc. This asymmetry may be explained by the absence of clear ethno-national ideological distinctions between the unionist parties (hence providing political space for performance based accountability to operate) but the continued relevance in the nationalist bloc of ethno-national difference (which limits the scope for performance politics). The implications of the findings for our understanding of the role of party-specific responsibility attribution in performance based models of voting, and for our evaluation of the quality of democracy in post-conflict consociational polities, are discussed. 

The Prenatal Distress Questionnaire:An investigation of factor structure in a high risk population

Background: The Prenatal Distress Questionnaire (PDQ) is a short measure designed to assess specific worries and concerns related to pregnancy. The aim of this study was to confirm the factor structure of the PDQ in a group of pregnant women with a small for gestational age infant (< 10th centile). Methods: The first PDQ assessment for each of 337 pregnant women participating in the Prospective Observational Trial to Optimise paediatric health (PORTO) study was analysed. All women enrolled in the study were identified as having a small for gestational age foetus (< 10th centile), thus representing an 'elevated risk' group. Data were analysed using confirmatory factor analysis (CFA). Three models of the PDQ were evaluated and compared in the current study: a theoretical uni-dimensional measurement model, a bi-dimensional model, and a three-factor model solution. Results: The three-factor model offered the best fit to the data while maintaining sound theoretical grounds(χ² (51df) = 128.52; CFI = 0.97; TLI = 0.96; RMSEA = 0.07). Factor 1 contained items reflecting concerns about birth and the baby, factor 2 concerns about physical symptoms and body image and factor 3 concerns about emotions and relationships. Conclusions: CFA confirmed that the three-factor model provided the best fit, with the items in each factor reflecting the findings of an earlier exploratory data analysis. © 2013 Society for Reproductive and Infant Psychology.

Three-dimensional delayed-detonation models with nucleosynthesis for type ia supernovae

We present results for a suite of 14 three-dimensional, high-resolution hydrodynamical simulations of delayed-detonation models of Type Ia supernova (SN Ia) explosions. This model suite comprises the first set of three-dimensional SN Ia simulations with detailed isotopic yield information. As such, it may serve as a data base for Chandrasekhar-mass delayed-detonation model nucleosynthetic yields and for deriving synthetic observables such as spectra and light curves. We employ aphysically motivated, stochastic model based on turbulent velocity fluctuations and fuel density to calculate in situ the deflagration-to-detonation transition probabilities. To obtain different strengths of the deflagration phase and thereby different degrees of pre-expansion, we have chosen a sequence of initial models with 1, 3, 5, 10, 20, 40, 100, 150, 200, 300 and 1600 (two different realizations) ignition kernels in a hydrostatic white dwarf with a central density of 2.9 × 10 g cm, as well as one high central density (5.5 × 10 g cm) and one low central density (1.0 × 10 g cm) rendition of the 100 ignition kernel configuration. For each simulation, we determined detailed nucleosynthetic yields by postprocessing10 tracer particles with a 384 nuclide reaction network. All delayed-detonation models result in explosions unbinding thewhite dwarf, producing a range of 56Ni masses from 0.32 to 1.11M. As a general trend, the models predict that the stableneutron-rich iron-group isotopes are not found at the lowest velocities, but rather at intermediate velocities (~3000×10 000 km s) in a shell surrounding a Ni-rich core. The models further predict relatively low-velocity oxygen and carbon, with typical minimum velocities around 4000 and 10 000 km s, respectively. © 2012 The Authors. Published by Oxford University Press on behalf of the Royal Astronomical Society.

Three-dimensional pure deflagration models with nucleosynthesis and synthetic observables for type ia supernovae

We investigate whether pure deflagration models ofChandrasekhar-mass carbon-oxygen white dwarf stars can account for one or more subclass of the observed population of Type Ia supernova (SN Ia) explosions. We compute a set of 3D full-star hydrodynamic explosion models, in which the deflagration strength is parametrized using the multispot ignition approach. For each model, we calculate detailed nucleosynthesis yields in a post-processing step with a 384 nuclide nuclear network. We also compute synthetic observables with our 3D Monte Carlo radiative transfer code for comparison with observations. For weak and intermediate deflagration strengths (energy release E {less-than or approximate} 1.1 × 10 erg), we find that the explosion leaves behind a bound remnant enriched with 3 to 10 per cent (by mass) of deflagration ashes. However, we do not obtain the large kick velocities recently reported in the literature. We find that weak deflagrations with E ~ 0.5 × 10 erg fit well both the light curves and spectra of 2002cx-like SNe Ia, and models with even lower explosion energies could explain some of the fainter members of this subclass. By comparing our synthetic observables with the properties of SNe Ia, we can exclude the brightest, most vigorously ignited models as candidates for any observed class of SN Ia: their B-V colours deviate significantly from both normal and 2002cx-like SNe Ia and they are too bright to be candidates for other subclasses.

Synthetic light curves and spectra for three-dimensional delayed-detonation models of type ia supernovae

In a companion paper, Seitenzahl et al. have presented a set of three-dimensional delayed detonation models for thermonuclear explosions of near-Chandrasekhar-mass white dwarfs (WDs). Here,we present multidimensional radiative transfer simulations that provide synthetic light curves and spectra for those models. The model sequence explores both changes in the strength of the deflagration phase (which is controlled by the ignition configuration in our models) and the WD central density. In agreement with previous studies, we find that the strength of the deflagration significantly affects the explosion and the observables. Variations in the central density also have an influence on both brightness and colour, but overall it is a secondary parameter in our set of models. In many respects, the models yield a good match to the observed properties of normal Type Ia supernovae (SNe Ia): peak brightness, rise/decline time-scales and synthetic spectra are all in reasonable agreement. There are, however, several differences. In particular, the models are systematically too red around maximum light, manifest spectral line velocities that are a little too high and yield I-band light curves that do not match observations. Although some of these discrepancies may simply relate to approximations made in the modelling, some pose real challenges to the models. If viewed as a complete sequence, our models do not reproduce the observed light-curve width- luminosity relation (WLR) of SNe Ia: all our models show rather similar B-band decline rates, irrespective of peak brightness. This suggests that simple variations in the strength of the deflagration phase in Chandrasekhar-mass deflagration-to-detonation models do not readily explain the observed diversity of normal SNe Ia. This may imply that some other parameter within the Chandrasekhar-mass paradigm is key to the WLR, or that a substantial fraction of normal SNe Ia arise from an alternative explosion scenario.

Adsorption isotherm models for basic dye adsorption by peat in single and binary component systems

Coloured effluents from textile industries are a problem in many rivers and waterways. Prediction of adsorption capacities of dyes by adsorbents is important in design considerations. The sorption of three basic dyes, namely Basic Blue 3, Basic Yellow 21 and Basic Red 22, onto peat is reported. Equilibrium sorption isotherms have been measured for the three single component systems. Equilibrium was achieved after twenty-one days. The experimental isotherm data were analysed using Langmuir, Freundlich, Redlich-Peterson, Temkin and Toth isotherm equations. A detailed error analysis has been undertaken to investigate the effect of using different error criteria for the determination of the single component isotherm parameters and hence obtain the best isotherm and isotherm parameters which describe the adsorption process. The linear transform model provided the highest R2 regression coefficient with the Redlich-Peterson model. The Redlich-Peterson model also yielded the best fit to experimental data for all three dyes using the non-linear error functions. An extended Langmuir model has been used to predict the isotherm data for the binary systems using the single component data. The correlation between theoretical and experimental data had only limited success due to competitive and interactive effects between the dyes and the dye-surface interactions.

A comparison of a range of models for dispersion in a partially stratified room

A comparative study of models used to predict contaminant dispersion in a partially stratified room is presented. The experiments were carried out in a ventilated test room, with an initially evenly dispersed pollutant. Air was extracted from the outlet in the ceiling of the room at 1 and 3 air changes per hour. A small temperature difference between the top and bottom of the room causes very low air velocities, and higher concentrations, in the lower half of the room. Grid-independent CFD calculations were compared with predictions from a zonal model and from CFD using a very coarse grid. All the calculations show broadly similar contaminant concentration decay rates for the three locations monitored in the experiments, with the zonal model performing surprisingly well. For the lower air change rate, the models predict a less well mixed contaminant distribution than the experimental measurements suggest. With run times of less than a few minutes, the zonal model is around two orders of magnitude faster than coarse-grid CFD and could therefore be used more easily in parametric studies and sensitivity analyses. For a more detailed picture of internal dispersion, a CFD study using coarse and standard grids may be more appropriate.

Comparisons, mental models, and the action effect in judgments of regret

People tend to attribute more regret to a character who has decided to take action and experienced a negative outcome than to one who has decided not to act and experienced a negative outcome. For some decisions, however, this finding is not observed in a between-participants design and thus appears to rely on comparisons between people's representations of action and their representations of inaction. In this article, we outline a mental models account that explains findings from studies that have used within- and between-participants designs, and we suggest that, for decisions with uncertain counterfactual outcomes, information about the consequences of a decision to act causes people to flesh out their representation of the counterfactual states of affairs for inaction. In three experiments, we confirm our predictions about participants' fleshing out of representations, demonstrating that an action effect occurs only when information about the consequences of action is available to participants as they rate the nonactor and when this information about action is informative with respect to judgments about inaction. It is important to note that the action effect always occurs when the decision scenario specifies certain counterfactual outcomes. These results suggest that people sometimes base their attributions of regret on comparisons among different sets of mental models.

Parametric FIR Design of Propagation Loss Filters in Digital Waveguide String Models

One of the attractive features of sound synthesis by physical modeling is the potential to build acoustic-sounding digital instruments that offer more flexibility and different options in its design and control than their real-life counterparts. In order to develop such virtual-acoustic instruments, the models they are based on need to be fully parametric, i.e., all coefficients employed in the model are functions of physical parameters that are controlled either online or at the (offline) design stage. In this letter we show how propagation losses can be parametrically incorporated in digital waveguide string models with the use of zero-phase FIR filters. Starting from the simplest possible design in the form of a three-tap FIR filter, a higher-order FIR strategy is presented and discussed within the perspective of string sound synthesis with digital waveguide models.

Discrete Conditional Phase-type models utilising classification trees: Application to modelling health service capacities

Discrete Conditional Phase-type (DC-Ph) models consist of a process component (survival distribution) preceded by a set of related conditional discrete variables. This paper introduces a DC-Ph model where the conditional component is a classification tree. The approach is utilised for modelling health service capacities by better predicting service times, as captured by Coxian Phase-type distributions, interfaced with results from a classification tree algorithm. To illustrate the approach, a case-study within the healthcare delivery domain is given, namely that of maternity services. The classification analysis is shown to give good predictors for complications during childbirth. Based on the classification tree predictions, the duration of childbirth on the labour ward is then modelled as either a two or three-phase Coxian distribution. The resulting DC-Ph model is used to calculate the number of patients and associated bed occupancies, patient turnover, and to model the consequences of changes to risk status.