Experimental and theoretical study of the infrared spectra of BrHI- and BrDI-

Gas phase vibrational spectra of BrHI- and BrDI- have been measured from 6 to 17 mum (590-1666 cm-1) using tunable infrared radiation from the free electron laser for infrared experiments in order to characterize the strong hydrogen bond in these species. BrHI-.Ar and BrDI-.Ar complexes were produced and mass selected, and the depletion of their signal due to vibrational predissociation was monitored as a function of photon energy. Additionally, BrHI- and BrDI- were dissociated into HBr (DBr) and I- via resonant infrared multiphoton dissociation. The spectra show numerous transitions, which had not been observed by previous matrix studies. New ab initio calculations of the potential-energy surface and the dipole moment are presented and are used in variational ro-vibrational calculations to assign the spectral features. These calculations highlight the importance of basis set in the simulation of heavy atoms such as iodine. Further, they demonstrate extensive mode mixing between the bend and the H-atom stretch modes in BrHI- and BrDI- due to Fermi resonances. These interactions result in major deviations from simple harmonic estimates of the vibrational energies. As a result of this new analysis, previous matrix-isolation spectra assignments are reevaluated. (C) 2004 American Institute of Physics.

Nonlinear system identification using particle swarm optimisation tuned radial basis function models

A novel particle swarm optimisation (PSO) tuned radial basis function (RBF) network model is proposed for identification of non-linear systems. At each stage of orthogonal forward regression (OFR) model construction process, PSO is adopted to tune one RBF unit's centre vector and diagonal covariance matrix by minimising the leave-one-out (LOO) mean square error (MSE). This PSO aided OFR automatically determines how many tunable RBF nodes are sufficient for modelling. Compared with the-state-of-the-art local regularisation assisted orthogonal least squares algorithm based on the LOO MSE criterion for constructing fixed-node RBF network models, the PSO tuned RBF model construction produces more parsimonious RBF models with better generalisation performance and is often more efficient in model construction. The effectiveness of the proposed PSO aided OFR algorithm for constructing tunable node RBF models is demonstrated using three real data sets.

Particle swarm optimization aided orthogonal forward regression for unified data modeling

We propose a unified data modeling approach that is equally applicable to supervised regression and classification applications, as well as to unsupervised probability density function estimation. A particle swarm optimization (PSO) aided orthogonal forward regression (OFR) algorithm based on leave-one-out (LOO) criteria is developed to construct parsimonious radial basis function (RBF) networks with tunable nodes. Each stage of the construction process determines the center vector and diagonal covariance matrix of one RBF node by minimizing the LOO statistics. For regression applications, the LOO criterion is chosen to be the LOO mean square error, while the LOO misclassification rate is adopted in two-class classification applications. By adopting the Parzen window estimate as the desired response, the unsupervised density estimation problem is transformed into a constrained regression problem. This PSO aided OFR algorithm for tunable-node RBF networks is capable of constructing very parsimonious RBF models that generalize well, and our analysis and experimental results demonstrate that the algorithm is computationally even simpler than the efficient regularization assisted orthogonal least square algorithm based on LOO criteria for selecting fixed-node RBF models. Another significant advantage of the proposed learning procedure is that it does not have learning hyperparameters that have to be tuned using costly cross validation. The effectiveness of the proposed PSO aided OFR construction procedure is illustrated using several examples taken from regression and classification, as well as density estimation applications.

Radial basis function classifier construction using particle swarm optimisation aided orthogonal forward regression

We develop a particle swarm optimisation (PSO) aided orthogonal forward regression (OFR) approach for constructing radial basis function (RBF) classifiers with tunable nodes. At each stage of the OFR construction process, the centre vector and diagonal covariance matrix of one RBF node is determined efficiently by minimising the leave-one-out (LOO) misclassification rate (MR) using a PSO algorithm. Compared with the state-of-the-art regularisation assisted orthogonal least square algorithm based on the LOO MR for selecting fixednode RBF classifiers, the proposed PSO aided OFR algorithm for constructing tunable-node RBF classifiers offers significant advantages in terms of better generalisation performance and smaller model size as well as imposes lower computational complexity in classifier construction process. Moreover, the proposed algorithm does not have any hyperparameter that requires costly tuning based on cross validation.

Induced random fields in the LiHoxY1-xF4 quantum ising magnet in a transverse magnetic field

The LiHoxY1-xF4 magnetic material in a transverse magnetic field Bxx̂ perpendicular to the Ising spin direction has long been used to study tunable quantum phase transitions in a random disordered system. We show that the Bx-induced magnetization along the x̂ direction, combined with the local random dilution-induced destruction of crystalline symmetries, generates, via the predominant dipolar interactions between Ho3+ ions, random fields along the Ising ẑ direction. This identifies LiHoxY1-xF4 in Bx as a new random field Ising system. The random fields explain the rapid decrease of the critical temperature in the diluted ferromagnetic regime and the smearing of the nonlinear susceptibility at the spin-glass transition with increasing Bx and render the Bx-induced quantum criticality in LiHoxY1-xF4 likely inaccessible.

Supramolecular structures of enzyme clusters

The structural characterization of subtilisin mesoscale clusters, which were previously shown to induce supramolecular order in biocatalytic self-assembly of Fmocdipeptides, was carried out by synchrotron small-angle X-ray, dynamic, and static light scattering measurements. Subtilisin molecules self-assemble to form supramolecular structures in phosphate buffer solutions. Structural arrangement of subtilisin clusters at 55 degrees Centigrade was found to vary systematically with increasing enzyme concentration. Static light scattering measurements showed the cluster structure to be consistent with a fractal-like arrangement, with fractal dimension varying from 1.8 to 2.6 with increasing concentration for low to moderate enzyme concentrations. This was followed by a structural transition around the enzyme concentration of 0.5 mg mL-1 to more compact structures with significantly slower relaxation dynamics, as evidenced by dynamic light scattering measurements. These concentration-dependent supramolecular enzyme clusters provide tunable templates for biocatalytic self-assembly.

Tuning thermal properties and microphase separation in aliphatic polyester ABA copolymers

Four alkyl substituted β-lactones were investigated as monomers in ring opening polymerisation to produce a family of poly(3-hydroxyalkanoate)s. Homopolymers were synthesised using a robust aluminium salen catalyst, resulting in polymers with low dispersity (Đ < 1.1) and predictable molecular weights. ABA triblock copolymers were prepared using poly(L-lactic acid) as the A block and the aforementioned poly(3-hydroxyalkanoate) as the B block via a sequential addition method. Characterisation of these copolymers determined they were well controlled with low dispersities and predictable molecular weight. DSC analysis determined copolymers prepared from β-butyrolactone or β-valerolactone yielded polymers with tunable and predictable thermal properties. Copolymers prepared from β-heptanolactone yielded a microphase separated material as indicated by SAXS, with two distinct Tgs. The polymers could be readily cast into flexible films and their improved tensile properties were explored.

Enantiomeric conformation controls rate and yield of photoinduced electron transfer in DNA sensitized by Ru(II) Dipyridophenazine complexes

Photosensitized oxidation of guanine is an important route to DNA damage. Ruthenium polypyridyls are very useful photosensitizers as their reactivity and DNA-binding properties are readily tunable. Here we show a strong difference in the reactivity of the two enantiomers of [Ru(TAP)2(dppz)]2+, by using time-resolved visible and IR spectroscopy. This reveals that the photosensitized one-electron oxidation of guanine in three oligonucleotide sequences proceeds with similar rates and yields for bound delta-[Ru(TAP)2(dppz)]2+, whereas those for the lambda enantiomer are very sensitive to base sequence. It is proposed that these differences are due to preferences of each enantiomer for different binding sites in the duplex.