Ultrasound and Sonochemistry for Radical Polymerization: Sound Synthesis

The use of ultrasound as an external stimulus for promoting polymerization reactions has received increasing attention in recent years. In this Review article, the fundamental processes that can lead to either the homolytic cleavage of polymer chains, or the sonolysis of solvent (or other) small molecules, under the application of ultrasound are described. These reactions promote the production of reactive radicals, which can be utilized in chain-growth radical polymerizations under the right conditions. A full historical overview of the development of ultrasound-assisted radical polymerization is provided, with special attention given to the recently described systems that are “controlled” by methods of reversible (radical) deactivation. Perspectives are shared on what challenges still remain in polymer sonochemistry, as well as new areas that are yet to be explored.     

Novel perturbation expansion for the Langevin equation

We discuss the randomly driven systemdx/dt= -W(x) +f(t), wheref(t) is a Gaussian random function or stirring force withf(t)f(t)=2(t–t), andW(x) is of the formgx ¹⁺². The parameter is a measure of the nonlinearity of the equation. We show how to obtain the correlation functionsx(t)f(t)···x(t( n)) _f as a power series in. We obtain three terms in the expansion and show how to use Padé approximants to analytically continue the answer in the variable. By using scaling relations, we show how to get a uniform approximation to the equal-time correlation functions valid for allg and.     

Discovering Higher-Order Interactions Through Neural Information Decomposition

If regularity in data takes the form of higher-order functions among groups of variables, models which are biased towards lower-order functions may easily mistake the data for noise. To distinguish whether this is the case, one must be able to quantify the contribution of different orders of dependence to the total information. Recent work in information theory attempts to do this through measures of multivariate mutual information (MMI) and information decomposition (ID). Despite substantial theoretical progress, practical issues related to tractability and learnability of higher-order functions are still largely unaddressed. In this work, we introduce a new approach to information decomposition—termed Neural Information Decomposition (NID)—which is both theoretically grounded, and can be efficiently estimated in practice using neural networks. We show on synthetic data that NID can learn to distinguish higher-order functions from noise, while many unsupervised probability models cannot. Additionally, we demonstrate the usefulness of this framework as a tool for exploring biological and artificial neural networks.     

Increasing the Weight of Minimum Spanning Trees

The problems of computing the maximum increase in the weight of the minimum spanning trees of a graph caused by the removal of a given number of edges, or by finite increases in the weights of the edges, are investigated. For the case of edge removals, the problem is shown to be NP-hard and an Ω(1/log k)-approximation algorithm is presented for it, where (input parameter) k > 1 is the number of edges to be removed. The second problem is studied, assuming that the increase in the weight of an edge has an associated cost proportional to the magnitude of the change. An O(n³m² log(n²/m)) time algorithm is presented to solve it.     

Disordered ground states for classical discrete-state problems in one dimension

It is known that one-dimensional lattice problems with a discrete, finite set of states per site generically have periodic ground states (GSs). We consider slightly less generic cases, in which the Hamiltonian is constrained by either spin (S) or spatial (I) inversion symmetry (or both). We show that such constraints give rise to the possibility ofdisordered GSs over a finite fraction of the coupling-parameter space—that is, without invoking any nongeneric fine tuning of coupling constants, beyond that arising from symmetry. We find that such disordered GSs can arise for many values of the number of statesk at each site and the ranger of the interaction. The Ising (k=2) case is the least prone to disorder:I symmetry allows for disordered GSs (without fine tuning) only forr5, whileS symmetry never gives rise to disordered GSs.     

A comparison of T2*-weighted magnitude and phase imaging for measuring the arterial input function in the rat aorta following intravenous injection of gadolinium contrast agent

The arterial input function (AIF) is important for quantitative MR imaging perfusion experiments employing Gd contrast agents. This study compared the accuracy of T(2)*-weighted magnitude and phase imaging for noninvasive measurement of the AIF in the rat aorta. Twenty-eight in vivo experiments were performed involving simultaneous arterial blood sampling and MR imaging following Gd injection. In vitro experiments were also performed to confirm the in vivo results. At 1.89 T and TE=3 ms, the relationship between changes in 1/T(2)* in blood (estimated from MR signal magnitude) and Gd concentration ([Gd]) was measured to be approximately 19 s(-1) mM(-1), while that between phase and [Gd] was approximately 0.19 rad mM(-1). Both of these values are consistent with previously published results. The in vivo phase data had approximately half as much scatter with respect to [Gd] than the in vivo magnitude data (r(2)=.34 vs. r(2)=.17, respectively). This is likely due to the fact that the estimated change in 1/T(2)* is more sensitive than the phase to a variety of factors such as partial volume effects and T(1) weighting. Therefore, this study indicates that phase imaging may be a preferred method for measuring the AIF in the rat aorta compared to T(2)*-weighted magnitude imaging.     

Experimental implementation of an adiabatic quantum optimization algorithm

We report the realization of a nuclear magnetic resonance computer with three quantum bits that simulates an adiabatic quantum optimization algorithm. Adiabatic quantum algorithms offer new insight into how quantum resources can be used to solve hard problems. This experiment uses a particularly well-suited three quantum bit molecule and was made possible by introducing a technique that encodes general instances of the given optimization problem into an easily applicable Hamiltonian. Our results indicate an optimal run time of the adiabatic algorithm that agrees well with the prediction of a simple decoherence model.     

Arbitrage‐free call option surface construction using regression splines

In this work, we suggest a novel quadratic programming‐based algorithm to generate an arbitrage‐free call option surface. The empirical performance of the proposed method is evaluated using S&P 500 Index call options. Our results indicate that the proposed method provides a more precise fit to observed option prices than other alternative methodologies. Copyright © 2014 John Wiley & Sons, Ltd.     

Synthesis of readily cleavable immobilized 1,10-phenanthroline resins

1,10-Phenanthroline is derivatized and ultimately immobilized on two different polystyrene/divinylbenzene solid supports using convenient methodology. All syntheses are amenable to semiautomatic processing and are scalable for high-throughput screening. A domino copper-catalyzed coupling-cyclization reaction is used to illustrate applicability in catalytic studies.     

Separation of thiosulfate and the polythionates in gold thiosulfate leach solutions by capillary electrophoresis

A technique for the separation of thiosulfate (S(2)O(3) (2-)), polythionates (S(x)O(6) (2-), x = 3 to 5) and the gold(I) thiosulfate complex (Au(S(2)O(3))(2) (3-)) using capillary electrophoresis with simultaneous UV detection at 195 and 214 nm is presented. The five species were separated in under 3 min with a total analysis time of 8 min, using an electrolyte containing 25 mM 2,2-bis(hydroxymethyl)-2,2',2"-nitrilotriethanol (bis-tris) adjusted to pH 6.0 with sulfuric acid and an applied voltage of -30 kV. While the gold(I) thiosulfate complex could be separated from the other analytes of interest under these conditions, the quantification of this complex was not possible due to inconsistent peak areas and peak splitting effects induced by the sulfur-oxygen species in the leach matrix. Detection limits calculated for 3s pressure injection at 50 mbar ranged between 0.5-2 microM. The method was linear over the ranges 40-8000, 10-2000, 10-2000, and 5-2000 microM for thiosulfate, trithionate, tetrathionate, and pentathionate, respectively. The technique was applied successfully to leach liquors containing 0.5 M ammonium thiosulfate, 2 M ammonia, 0.05 M copper sulfate and 20% w/v gold ore, diluted 1:100 prior to analysis.