Analyzing laser plasma interferograms with a continuous wavelet transform ridge extraction technique: the method

Laser plasma interferograms are currently analyzed by extraction of the phase-shift map with fast Fourier transform (FFT) techniques [Appl. Opt. 18, 3101 (1985)]. This methodology works well when interferograms are only marginally affected by noise and reduction of fringe visibility, but it can fail to produce accurate phase-shift maps when low-quality images are dealt with. We present a novel procedure for a phase-shift map computation that makes extensive use of the ridge extraction in the continuous wavelet transform (CWT) framework. The CWT tool is flexible because of the wide adaptability of the analyzing basis, and it can be accurate because of the intrinsic noise reduction in the ridge extraction. A comparative analysis of the accuracy performances of them new tool and the FFT-based one shows that the CWT-based tool produces phase maps considerably less noisy and that it can better resolve local inhomogeneties. (C) 2001 Optical Society of America.

Low-pressure solubilities and thermodynamics of solvation of eight gases in 1-butyl-3-methylimidazolium hexafluorophosphate

Experimental values for the solubility of carbon dioxide, ethane, methane, oxygen, nitrogen, hydrogen, argon and carbon monoxide in 1-butyl-3-methylimidazolium hexafluorophosphate, [bmim][PF6] - a room temperature ionic liquid - are reported as a function of temperature between 283 and 343 K and at pressures close to atmospheric. Carbon dioxide is the most soluble and hydrogen is the least soluble of the gases studied with mole fraction solubilities of the order of 10-2 and 10-4, respectively. All the mole fraction solubilities decrease with temperature except for hydrogen for which a maximum is observed at temperatures close to 310 K. From the variation of solubility, expressed as Henry's law constants, with temperature, the partial molar thermodynamic functions of solvation such as the standard Gibbs energy, the enthalpy, and the entropy are calculated. The precision of the experimental data, considered as the average absolute deviation of the Henry's law constants from appropriate smoothing equations, is better than ±1%. © 2005 Elsevier B.V. All rights reserved.

Thermophysical properties, low pressure solubilities and thermodynamics of solvation of carbon dioxide and hydrogen in two ionic liquids based on the alkylsulfate anion

Densities and viscosities of the ionic liquid 1-butyl-3-methylimidazolium octylsulfate, [C4C1Im][C8SO4] were measured as a function of temperature between 313 K and 395 K. Solubilities of hydrogen and carbon dioxide were determined, between 283 K and 343 K, and at pressures close to atmospheric in [C4C1Im][C 8SO4] and in another ionic liquid based on the alkylsulfate anion-1-ethyl-3-methylimidazolium ethylsulfate, [C 2C1Im][C2SO4]. Density and viscosity were measured using a vibrating tube densimeter from Anton Paar and a rheometer from Rheometrics Scientific with accuracies of 10-3 g cm -3 and 1%, respectively. Solubilities were obtained using an isochoric saturation technique and, from the variation of solubility with temperature, the partial molar thermodynamic functions of solvation, such as the standard Gibbs energy, the enthalpy, and the entropy, are calculated. The precision of the experimental data, considered as the average absolute deviation of the Henry's law constants from appropriate smoothing equations, is better than ±1%. © The Royal Society of Chemistry.

The Conditional Phase-type distribution: Graphical Models for Continuous Non-Normal Data:The Conditional Phase-type (C-Ph) distribution:

Conditional Gaussian (CG) distributions allow the inclusion of both discrete and continuous variables in a model assuming that the continuous variable is normally distributed. However, the CG distributions have proved to be unsuitable for survival data which tends to be highly skewed. A new method of analysis is required to take into account continuous variables which are not normally distributed. The aim of this paper is to introduce the more appropriate conditional phase-type (C-Ph) distribution for representing a continuous non-normal variable while also incorporating the causal information in the form of a Bayesian network.

Methylation using dimethylcarbonate catalysed by ionic liquids under continuous flow conditions

The ionic liquid, tributylmethylammonium methylcarbonate, has been employed as a catalytic base for clean N-methylation of indole with dimethylcarbonate. The reaction conditions were optimised under microwave heating to give 100% conversion and 100% selectivity to N-methylindole, and subsequently transferred to a high temperature/high pressure (285 degrees C/150 bar) continuous flow process using a short (3 min) residence time and 2 mol% of the catalyst to efficiently methylate a variety of different amines, phenols, thiophenols and carboxylic acid substrates. The extremely short residence times, versatility, and high selectivity have significant implications for the synthesis of a wide range of pharmaceutical intermediates, as high product throughputs can be obtained via this scalable continuous flow protocol. It has also been shown that the ionic liquid can be generated in situ from tributylamine, which has the net effect of transforming an ineffective stoichiometric base into a highly efficient catalyst for this broad class of reactions.

Microwave-assisted Cu-catalyzed Ullmann ether synthesis in a continuous-flow milli-plant

The combination of milli-scale processing and microwave heating has been investigated for the Cu-catalyzed Ullmann etherification in fine-chemical synthesis, providing improved catalytic activity and selective catalyst heating. Wall-coated and fixed-bed milli-reactors were designed and applied in the Cu-catalyzed Ullmann-type CO coupling of phenol and 4-chloropyridine. In a batch reactor the results show clearly increased yields for the microwave heated process at low microwave powers, whereas high powers and catalyst loadings reduced the benefits of microwave heating. Slightly higher yields were found in the Cu/ZnO wall-coated as compared to the Cu/TiO fixed-bed flow-reactor. The benefit here is that the reaction occurs at the surface of the metal nanoparticles confined within a support film making the nano-copper equally accessible. Catalyst deactivation was mainly caused by Cu oxidation and coke formation; however, at longer process times leaching played a significant role. Catalyst activity could partially be recovered by removal of deposited by-product by means of calcination. After 6h on-stream the reactor productivities were 28.3 and 55.1kgprod/(mR3h) for the fresh Cu/ZnO wall-coated and Cu/TiO fixed-bed reactor, respectively. Comparison of single- and multimode microwaves showed a threefold yield increase for single-mode microwaves. Control of nanoparticles size and loading allows to avoid high temperatures in a single-mode microwave field and provides a novel solution to a major problem for combining metal catalysis and microwave heating. Catalyst stability appeared to be more important and provided twofold yield increase for the CuZn/TiO catalyst as compared to the Cu/TiO catalyst due to stabilized copper by preferential oxidation of the zinc. For this catalyst a threefold yield increase was observed in single-mode microwaves which, to the best of our knowledge, led to a not yet reported productivity of 172kgprod/(mR3h) for the microwave and flow Ullmann CO coupling. © 2012 Elsevier B.V.

Assessing reproducibility of data obtained with instruments based on continuous measurements

Data obtained with any research tool must be reproducible, a concept referred to as reliability. Three techniques are often used to evaluate reliability of tools using continuous data in aging research: intraclass correlation coefficients (ICC), Pearson correlations, and paired t tests. These are often construed as equivalent when applied to reliability. This is not correct, and may lead researchers to select instruments based on statistics that may not reflect actual reliability. The purpose of this paper is to compare the reliability estimates produced by these three techniques and determine the preferable technique. A hypothetical dataset was produced to evaluate the reliability estimates obtained with ICC, Pearson correlations, and paired t tests in three different situations. For each situation two sets of 20 observations were created to simulate an intrarater or inter-rater paradigm, based on 20 participants with two observations per participant. Situations were designed to demonstrate good agreement, systematic bias, or substantial random measurement error. In the situation demonstrating good agreement, all three techniques supported the conclusion that the data were reliable. In the situation demonstrating systematic bias, the ICC and t test suggested the data were not reliable, whereas the Pearson correlation suggested high reliability despite the systematic discrepancy. In the situation representing substantial random measurement error where low reliability was expected, the ICC and Pearson coefficient accurately illustrated this. The t test suggested the data were reliable. The ICC is the preferred technique to measure reliability. Although there are some limitations associated with the use of this technique, they can be overcome.

Emergent thermodynamics in a quenched quantum many-body system

We study the statistics of the work done, the fluctuation relations and the irreversible entropy production in a quantum many-body system subject to the sudden quench of a control parameter. By treating the quench as a thermodynamic transformation we show that the emergence of irreversibility in the nonequilibrium dynamics of closed many-body quantum systems can be accurately characterized. We demonstrate our ideas by considering a transverse quantum Ising model that is taken out of equilibrium by the instantaneous switching of the transverse field.

Gapped Two-Body Hamiltonian for Continuous-Variable Quantum Computation

We introduce a family of Hamiltonian systems for measurement-based quantum computation with continuous variables. The Hamiltonians (i) are quadratic, and therefore two body, (ii) are of short range, (iii) are frustration-free, and (iv) possess a constant energy gap proportional to the squared inverse of the squeezing. Their ground states are the celebrated Gaussian graph states, which are universal resources for quantum computation in the limit of infinite squeezing. These Hamiltonians constitute the basic ingredient for the adiabatic preparation of graph states and thus open new venues for the physical realization of continuous-variable quantum computing beyond the standard optical approaches. We characterize the correlations in these systems at thermal equilibrium. In particular, we prove that the correlations across any multipartition are contained exactly in its boundary, automatically yielding a correlation area law. © 2011 American Physical Society.

The structure of compact disjointness preserving operators on continuous functions

Let T be a compact disjointness preserving linear operator from C0(X) into C0(Y), where X and Y are locally compact Hausdorff spaces. We show that T can be represented as a norm convergent countable sum of disjoint rank one operators. More precisely, T = Snd ?hn for a (possibly finite) sequence {xn }n of distinct points in X and a norm null sequence {hn }n of mutually disjoint functions in C0(Y). Moreover, we develop a graph theoretic method to describe the spectrum of such an operator

Modeling continuous self-report measures of perceived emotion using generalized additive mixed models

Emotion research has long been dominated by the “standard method” of displaying posed or acted static images of facial expressions of emotion. While this method has been useful it is unable to investigate the dynamic nature of emotion expression. Although continuous self-report traces have enabled the measurement of dynamic expressions of emotion, a consensus has not been reached on the correct statistical techniques that permit inferences to be made with such measures. We propose Generalized Additive Models and Generalized Additive Mixed Models as techniques that can account for the dynamic nature of such continuous measures. These models allow us to hold constant shared components of responses that are due to perceived emotion across time, while enabling inference concerning linear differences between groups. The mixed model GAMM approach is preferred as it can account for autocorrelation in time series data and allows emotion decoding participants to be modelled as random effects. To increase confidence in linear differences we assess the methods that address interactions between categorical variables and dynamic changes over time. In addition we provide comments on the use of Generalized Additive Models to assess the effect size of shared perceived emotion and discuss sample sizes. Finally we address additional uses, the inference of feature detection, continuous variable interactions, and measurement of ambiguity.