Orientation coding: a specific deficit in Williams syndrome?

Williams syndrome (WS) is a rare genetic disorder with a unique cognitive profile in which verbal abilities are markedly stronger than visuospatial abilities. This study investigated the claim that orientation coding is a specific deficit within the visuospatial domain in WS. Experiment I employed a simplified version of the Benton Judgement of Line Orientation task and a control, length-matching task. Results demonstrated comparable levels of orientation matching performance in the group with WS and a group of typically developing (TD) controls matched by nonverbal ability, although it is possible that floor effects masked group differences. A group difference was observed in the length-matching task due to stronger performance from the control group. Experiment 2 employed an orientation-discrimination task and a length-discrimination task. Contrary to previous reports, the results showed that individuals with WS were able to code by orientation to a comparable level as that of their matched controls. This demonstrates that, although some impairment is apparent, orientation coding does not represent a specific deficit in WS. Comparison between Experiments I and 2 suggests that orientation coding is vulnerable to task complexity. However, once again, this vulnerability does not appear to be specific to the population with WS, as it was also apparent in the TD controls.

Water adsorption on O-covered Ru{0001}: coverage-dependent change from dissociation to molecular adsorption

When water is coadsorbed with oxygen at coverages above 0.25ML an intact water species is observed in high resolution X-ray photoelectron spectroscopy up to 220 K, which is significantly more stable than intact water on the clean surface. The presence of this species causes a shift in the O 1s binding energy of the pre-adsorbed oxygen, which indicates the formation of hydrogen bonds between the two adsorbates. Low coverages of oxygen induce partial dissociation and recombinative desorption in the same temperature range, which illustrates that desorption temperatures alone cannot be used to determine whether water is molecularly intact or not.

Single trial BCI operation via Wackermann parameters

Accurate single trial P300 classification lends itself to fast and accurate control of Brain Computer Interfaces (BCIs). Highly accurate classification of single trial P300 ERPs is achieved by characterizing the EEG via corresponding stationary and time-varying Wackermann parameters. Subsets of maximally discriminating parameters are then selected using the Network Clustering feature selection algorithm and classified with Naive-Bayes and Linear Discriminant Analysis classifiers. Hence the method is assessed on two different data-sets from BCI competitions and is shown to produce accuracies of between approximately 70% and 85%. This is promising for the use of Wackermann parameters as features in the classification of single-trial ERP responses.

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 statistics of a head-operated force-reflecting rehabilitation robot system

Researchers in the rehabilitation engineering community have been designing and developing a variety of passive/active devices to help persons with limited upper extremity function to perform essential daily manipulations. Devices range from low-end tools such as head/mouth sticks to sophisticated robots using vision and speech input. While almost all of the high-end equipment developed to date relies on visual feedback alone to guide the user providing no tactile or proprioceptive cues, the “low-tech” head/mouth sticks deliver better “feel” because of the inherent force feedback through physical contact with the user's body. However, the disadvantage of a conventional head/mouth stick is that it can only function in a limited workspace and the performance is limited by the user's strength. It therefore seems reasonable to attempt to develop a system that exploits the advantages of the two approaches: the power and flexibility of robotic systems with the sensory feedback of a headstick. The system presented in this paper reflects the design philosophy stated above. This system contains a pair of master-slave robots with the master being operated by the user's head and the slave acting as a telestick. Described in this paper are the design, control strategies, implementation and performance evaluation of the head-controlled force-reflecting telestick system.

Spectro-electrochemical and DFT studies of a planar Cu(II)–phenolate complex active in the aerobic oxidation of primary alcohols

A square-planar compound [Cu(pyrimol)Cl] (pyrimol = 4-methyl-2-N-(2-pyridylmethylene)aminophenolate) abbreviated as CuL–Cl) is described as a biomimetic model of the enzyme galactose oxidase (GOase). This copper(II) compound is capable of stoichiometric aerobic oxidation of activated primary alcohols in acetonitrile/water to the corresponding aldehydes. It can be obtained either from Hpyrimol (HL) or its reduced/hydrogenated form Hpyramol (4-methyl-2-N-(2-pyridylmethyl)aminophenol; H2L) readily converting to pyrimol (L-) on coordination to the copper(II) ion. Crystalline CuL–Cl and its bromide derivative exhibit a perfect square-planar geometry with Cu–O(phenolate) bond lengths of 1.944(2) and 1.938(2) Å. The cyclic voltammogram of CuL–Cl exhibits an irreversible anodic wave at +0.50 and +0.57 V versus ferrocene/ferrocenium (Fc/Fc+) in dry dichloromethane and acetonitrile, respectively, corresponding to oxidation of the phenolate ligand to the corresponding phenoxyl radical. In the strongly donating acetonitrile the oxidation path involves reversible solvent coordination at the Cu(II) centre. The presence of the dominant CuII–L. chromophore in the electrochemically and chemically oxidised species is evident from a new fairly intense electronic absorption at 400–480 nm ascribed to a several electronic transitions having a mixed pi-pi(L.) intraligand and Cu–Cl -> L. charge transfer character. The EPR signal of CuL–Cl disappears on oxidation due to strong intramolecular antiferromagnetic exchange coupling between the phenoxyl radical ligand (L.) and the copper(II) centre, giving rise to a singlet ground state (S = 0). The key step in the mechanism of the primary alcohol oxidation by CuL–Cl is probably the alpha-hydrogen abstraction from the equatorially bound alcoholate by the phenoxyl moiety in the oxidised pyrimol ligand, Cu–L., through a five-membered cyclic transition state.

Synthesis, structure and reactivity of the novel tetratin species bromoheptakis(2,6-diethylphenyl)-cyclotetrastannabutane

Metallation of ArBr (Ar = 2,6-diethylphenyl) with Li powder in diethyl ether, followed by addition of stannous chloride at low temperature does not give the expected oligomeric diarylstannane but an essentially quantitative yield of the novel tetrastannabutane [{SnAr2}3SnArBr]. Some reactions of the new species are reported.

The impact of uncertainty in satellite data on the assessment of flood inundation models

The performance of flood inundation models is often assessed using satellite observed data; however these data have inherent uncertainty. In this study we assess the impact of this uncertainty when calibrating a flood inundation model (LISFLOOD-FP) for a flood event in December 2006 on the River Dee, North Wales, UK. The flood extent is delineated from an ERS-2 SAR image of the event using an active contour model (snake), and water levels at the flood margin calculated through intersection of the shoreline vector with LiDAR topographic data. Gauged water levels are used to create a reference water surface slope for comparison with the satellite-derived water levels. Residuals between the satellite observed data points and those from the reference line are spatially clustered into groups of similar values. We show that model calibration achieved using pattern matching of observed and predicted flood extent is negatively influenced by this spatial dependency in the data. By contrast, model calibration using water elevations produces realistic calibrated optimum friction parameters even when spatial dependency is present. To test the impact of removing spatial dependency a new method of evaluating flood inundation model performance is developed by using multiple random subsamples of the water surface elevation data points. By testing for spatial dependency using Moran’s I, multiple subsamples of water elevations that have no significant spatial dependency are selected. The model is then calibrated against these data and the results averaged. This gives a near identical result to calibration using spatially dependent data, but has the advantage of being a statistically robust assessment of model performance in which we can have more confidence. Moreover, by using the variations found in the subsamples of the observed data it is possible to assess the effects of observational uncertainty on the assessment of flooding risk.