Spectroscopic properties and electronic structures of 17-electron half-sandwich ruthenium acetylide complexes, [Ru(CCAr)(L2)Cp′]+ (Ar=phenyl, p-tolyl, 1-naphthyl, 9-anthryl; L2=(PPh3)2, Cp′=Cp; L2=dppe; Cp′=Cp∗)

A series of half-sandwich bis(phosphine) ruthenium acetylide complexes [Ru(C CAr)(L-2)Cp'] (Ar = phenyl, p-tolyl, 1-naphthyl, 9-anthryl; L2 = (PPh3)(2), Cp' = Cp; L-2 = dppe; Cp' = Cp*) have been examined using electrochemical and spectroelectrochemical methods. One-electron oxidation of these complexes gave the corresponding radical cations [Ru(C CAr)(L2)Cp'](+). Those cations based on Ru(dppe)Cp*, or which feature a para-tolyl acetylide substituent, are more chemically robust than examples featuring the Ru(PPh3)(2)Cp moiety, permitting good quality UV-Vis-NIR and IR spectroscopic data to be obtained using spectroelectrochemical methods. On the basis of TD DFT calculations, the low energy (NIR) absorption bands in the experimental electronic spectra for most of these radical cations are assigned to transitions between the beta-HOSO and beta-LUSO, both of which have appreciable metal d and ethynyl pi character. However, the large contribution from the anthryl moiety to the frontier orbitals of [Ru(C CC14H9)(L2)CP'](+) suggests compounds containing this moiety should be described as metal-stabilised anthryl radical cations.

Rhenium-to-benzoylpyridine and rhenium-to-bipyridine MLCT excited states offac-[Re(Cl)(4-benzoylpyridine)2(CO)3] andfac-[Re(4-benzoylpyridine)(CO)3(bpy)]+: a time-resolved spectroscopic and spectroelectrochemical study

The lowest allowed electronic transition of fac-[Re(Cl)(CO)(3)(bopy)(2)] (bopy = 4-benzoylpyridine) has a Re --> bopy MLCT character, as revealed by UV-vis and stationary resonance Raman spectroscopy. Accordingly, the lowest-lying, long-lived, excited state is Re --> bopy (MLCT)-M-3. Electronic depopulation of the Re(CO)(3) unit and population of a bopy pi* orbital upon excitation are evident by the upward shift of v(Cequivalent toO) vibrations and a downward shift of the ketone v(C=O) vibration, respectively, seen in picosecond time-resolved IR spectra. Moreover, reduction of a single bopy ligand in the (MLCT)-M-3 excited state is indicated by time-resolved visible and resonance Raman (TR3) spectra that show features typical of bopy(.-). In contrast, the lowest allowed electronic transition and lowest-lying excited state of a new complex fac-[Re(bopy)(CO)(3)(bpy)](+) (bpy = 2,2'-bipyridine) have been identified as Re --> bpy MLCT with no involvement of the bopy ligand, despite the fact that the first reduction of this complex is bopy-localized, as was proven spectroelectrochemically. This is a rare case in which the localizations of the lowest MLCT excitation and the first reduction are different. (MLCT)-M-3 excited states of both fac-[Re(Cl)(CO)(3)(bopy)(2)] and fac-[Re(bopy)(CO)(3)(bpy)](+) are initially formed vibrationally hot. Their relaxation is manifested by picosecond dynamic shifts of v(Cequivalent toO) IR bands. The X-ray structure of fac-[Re(bopy)(CO)(3)(bpy)](PF6CH3CN)-C-. has been determined.

Simplified parameter adaptive control

A simple parameter adaptive controller design methodology is introduced in which steady-state servo tracking properties provide the major control objective. This is achieved without cancellation of process zeros and hence the underlying design can be applied to non-minimum phase systems. As with other self-tuning algorithms, the design (user specified) polynomials of the proposed algorithm define the performance capabilities of the resulting controller. However, with the appropriate definition of these polynomials, the synthesis technique can be shown to admit different adaptive control strategies, e.g. self-tuning PID and self-tuning pole-placement controllers. The algorithm can therefore be thought of as an embodiment of other self-tuning design techniques. The performances of some of the resulting controllers are illustrated using simulation examples and the on-line application to an experimental apparatus.

On the principal eigenvalue of a Robin problem with a large parameter

We study the asymptotic behaviour of the principal eigenvalue of a Robin (or generalised Neumann) problem with a large parameter in the boundary condition for the Laplacian in a piecewise smooth domain. We show that the leading asymptotic term depends only on the singularities of the boundary of the domain, and give either explicit expressions or two-sided estimates for this term in a variety of situations.

Parameter estimation based on stacked regression and evolutionary algorithms

A new parameter-estimation algorithm, which minimises the cross-validated prediction error for linear-in-the-parameter models, is proposed, based on stacked regression and an evolutionary algorithm. It is initially shown that cross-validation is very important for prediction in linear-in-the-parameter models using a criterion called the mean dispersion error (MDE). Stacked regression, which can be regarded as a sophisticated type of cross-validation, is then introduced based on an evolutionary algorithm, to produce a new parameter-estimation algorithm, which preserves the parsimony of a concise model structure that is determined using the forward orthogonal least-squares (OLS) algorithm. The PRESS prediction errors are used for cross-validation, and the sunspot and Canadian lynx time series are used to demonstrate the new algorithms.

Performance analysis of near-far resistant CDMA detectors-influence of system parameter estimation errors

Little has been reported on the performance of near-far resistant CDMA detectors in the presence of system parameter estimation errors (SPEEs). Starting with the general mathematical model of matched filters, the paper examines the effects of three classes of SPEEs, i.e., time-delay, carrier phase, and carrier frequency errors, on the performance (BER) of an emerging type of near-far resistant coherent DS/SSMA detector, i.e., the linear decorrelating detector. For comparison, the corresponding results for the conventional detector are also presented. It is shown that the linear decorrelating detector can still maintain a considerable performance advantage over the conventional detector even when some SPEEs exist.

Analysis of spectroscopic measurements of leaf water content at terahertz frequencies using linear transforms

We provide a unified framework for a range of linear transforms that can be used for the analysis of terahertz spectroscopic data, with particular emphasis on their application to the measurement of leaf water content. The use of linear transforms for filtering, regression, and classification is discussed. For illustration, a classification problem involving leaves at three stages of drought and a prediction problem involving simulated spectra are presented. Issues resulting from scaling the data set are discussed. Using Lagrange multipliers, we arrive at the transform that yields the maximum separation between the spectra and show that this optimal transform is equivalent to computing the Euclidean distance between the samples. The optimal linear transform is compared with the average for all the spectra as well as with the Karhunen–Loève transform to discriminate a wet leaf from a dry leaf. We show that taking several principal components into account is equivalent to defining new axes in which data are to be analyzed. The procedure shows that the coefficients of the Karhunen–Loève transform are well suited to the process of classification of spectra. This is in line with expectations, as these coefficients are built from the statistical properties of the data set analyzed.

A hybrid data assimilation scheme for model parameter estimation: application to morphodynamic modelling

We present a novel algorithm for joint state-parameter estimation using sequential three dimensional variational data assimilation (3D Var) and demonstrate its application in the context of morphodynamic modelling using an idealised two parameter 1D sediment transport model. The new scheme combines a static representation of the state background error covariances with a flow dependent approximation of the state-parameter cross-covariances. For the case presented here, this involves calculating a local finite difference approximation of the gradient of the model with respect to the parameters. The new method is easy to implement and computationally inexpensive to run. Experimental results are positive with the scheme able to recover the model parameters to a high level of accuracy. We expect that there is potential for successful application of this new methodology to larger, more realistic models with more complex parameterisations.

Dynamic integrated system optimization and parameter estimation for discrete time optimal control of nonlinear systems

An algorithm for solving nonlinear discrete time optimal control problems with model-reality differences is presented. The technique uses Dynamic Integrated System Optimization and Parameter Estimation (DISOPE), which achieves the correct optimal solution in spite of deficiencies in the mathematical model employed in the optimization procedure. A version of the algorithm with a linear-quadratic model-based problem, implemented in the C+ + programming language, is developed and applied to illustrative simulation examples. An analysis of the optimality and convergence properties of the algorithm is also presented.

Model predictive control using dynamic integrated system optimisation and parameter estimation (DISOPE)

DISOPE is a technique for solving optimal control problems where there are differences in structure and parameter values between reality and the model employed in the computations. The model reality differences can also allow for deliberate simplification of model characteristics and performance indices in order to facilitate the solution of the optimal control problem. The technique was developed originally in continuous time and later extended to discrete time. The main property of the procedure is that by iterating on appropriately modified model based problems the correct optimal solution is achieved in spite of the model-reality differences. Algorithms have been developed in both continuous and discrete time for a general nonlinear optimal control problem with terminal weighting, bounded controls and terminal constraints. The aim of this paper is to show how the DISOPE technique can aid receding horizon optimal control computation in nonlinear model predictive control.

Production of pH-responsive microparticles by spray drying: investigation of experimental parameter effects on morphological and release properties

During spray drying, emphasis is placed on process optimisation to generate favourable particle morphological and flow properties. The effect of the initial feed solution composition on the drug release from the prepared microparticles is rarely considered. We investigated the effects of solvent composition, feed solution concentration and drug-loading on sodium salicylate, hydrocortisone and triamcinolone release from spray dried Eudragit L100 microparticles. Eudragit L100 is a pH-responsive polymer whose dissolution threshold is pH 6 so dissolution testing of the prepared microparticles at pH 5 and 1.2 illustrated non-polymer controlled burst release. Increasing the water content of the initial ethanolic feed solution significantly reduced hydrocortisone burst release at pH 5, as did reducing the feed solution concentration. These findings caution that changes in feed solution concentration or solvent composition not only affect particles’ morphological characteristics but can also negatively alter their drug release properties. This work also illustrate that drug-free microparticles can have different morphological properties to drug-loaded microparticles. Therefore, process optimisation needs to be carried out using drug-loaded systems. Depending on the physicochemical properties of the encapsulated API, drug-loading can affect the polymer solubility in the initial feed solution with consequent impact on microparticles morphological and release properties.