Galvanic corrosion of magnesium alloy AZ91D in contact with an aluminium alloy, steel and zinc

An investigation was carried out into the galvanic corrosion of magnesium alloy AZ91D in contact with zinc, aluminium alloy A380 and 4150 steel. Specially designed test panels were used to measure galvanic currents under salt spray conditions. It was found that the distributions of the galvanic current densities on AZ91D and on the cathodes were different. An insulating spacer between the AZ91D anode and the cathodes could not eliminate galvanic corrosion. Steel was the worst cathode and aluminium the least aggressive to AZ91D. Corrosion products from the anode and cathodes appeared to be able to affect the galvanic corrosion process through an alkalisation, passivation, poisoning effect or shortcut effect. (C) 2003 Elsevier Ltd. All rights reserved.

When vicars meet: A narrow contact zone between morphologically cryptic phylogeographic lineages of the rainforest skink, Carlia rubrigularis

Phylogeographic analyses of the fauna of the Australian wet tropics rainforest have provided strong evidence for long-term isolation of populations among allopatric refugia, yet typically there is no corresponding divergence in morphology. This system provides an opportunity to examine the consequences of geographic isolation, independent of morphological divergence, and thus to assess the broader significance of historical subdivisions revealed through mitochondrial DNA phylogeography. We have located and characterized a zone of secondary contact between two long isolated (mtDNA divergence > 15%) lineages of the skink Carlia rubrigularis using one mitochondrial and eight nuclear (two intron, six microsatellite) markers. This revealed a remarkably narrow (width < 3 km) hybrid zone with substantial linkage disequilibrium and strong deficits of heterozygotes at two of three nuclear loci with diagnostic alleles. Cline centers were coincident across loci. Using a novel form of likelihood analysis, we were unable to distinguish between sigmoidal and stepped cline shapes except at one nuclear locus for which the latter was inferred. Given estimated dispersal rates of 90-133 m x gen(-1/2) and assuming equilibrium, the observed cline widths suggest effective selection against heterozygotes of at least 22-49% and possibly as high as 70%. These observations reveal substantial postmating isolation, although the absence of consistent deviations from Hardy-Weinberg equilibrium at diagnostic loci suggests that there is little accompanying premating isolation. The tight geographic correspondence between transitions in mtDNA and those for nuclear genes and corresponding evidence for selection against hybrids indicates that these morphologically cryptic phylogroups could be considered as incipient species. Nonetheless, we caution against the use of mtDNA phylogeography as a sole criterion for defining species boundaries.

An investigation of contact transmission of methicillin resistant-Staphylococcus aureus

Hand hygiene is critical in the healthcare setting and it is believed that methicillin-resistant Staphylococcus aureus (MRSA), for example, is transmitted from patient to patient largely via the hands of health professionals. A study has been carried out at a large teaching hospital to estimate how often the gloves of a healthcare worker are contaminated with MRSA after contact with a colonized patient. The effectiveness of handwashing procedures to decontaminate the health professionals' hands was also investigated, together with how well different healthcare professional groups complied with handwashing procedures. The study showed that about 17% (9-25%) of contacts between a healthcare worker and a MRSA-colonized patient results in transmission of MRSA from a patient to the gloves of a healthcare worker. Different health professional groups have different rates of compliance with infection control procedures. Non-contact staff (cleaners, food services) had the shortest handwashing times. In this study, glove use compliance rates were 75% or above in all healthcare worker groups except doctors whose compliance was only 27%. (C) 2004 The Hospital Infection Society. Published by Elsevier Ltd. All rights reserved.

Protein contact prediction using patterns of correlation

We describe a new method for using neural networks to predict residue contact pairs in a protein. The main inputs to the neural network are a set of 25 measures of correlated mutation between all pairs of residues in two windows of size 5 centered on the residues of interest. While the individual pair-wise correlations are a relatively weak predictor of contact, by training the network on windows of correlation the accuracy of prediction is significantly improved. The neural network is trained on a set of 100 proteins and then tested on a disjoint set of 1033 proteins of known structure. An average predictive accuracy of 21.7% is obtained taking the best L/2 predictions for each protein, where L is the sequence length. Taking the best L/10 predictions gives an average accuracy of 30.7%. The predictor is also tested on a set of 59 proteins from the CASP5 experiment. The accuracy is found to be relatively consistent across different sequence lengths, but to vary widely according to the secondary structure. Predictive accuracy is also found to improve by using multiple sequence alignments containing many sequences to calculate the correlations. (C) 2004 Wiley-Liss, Inc.

Better prediction of protein contact number using a support vector regression analysis of amino acid sequence

Background: Protein tertiary structure can be partly characterized via each amino acid's contact number measuring how residues are spatially arranged. The contact number of a residue in a folded protein is a measure of its exposure to the local environment, and is defined as the number of C-beta atoms in other residues within a sphere around the C-beta atom of the residue of interest. Contact number is partly conserved between protein folds and thus is useful for protein fold and structure prediction. In turn, each residue's contact number can be partially predicted from primary amino acid sequence, assisting tertiary fold analysis from sequence data. In this study, we provide a more accurate contact number prediction method from protein primary sequence. Results: We predict contact number from protein sequence using a novel support vector regression algorithm. Using protein local sequences with multiple sequence alignments (PSI-BLAST profiles), we demonstrate a correlation coefficient between predicted and observed contact numbers of 0.70, which outperforms previously achieved accuracies. Including additional information about sequence weight and amino acid composition further improves prediction accuracies significantly with the correlation coefficient reaching 0.73. If residues are classified as being either contacted or non-contacted, the prediction accuracies are all greater than 77%, regardless of the choice of classification thresholds. Conclusion: The successful application of support vector regression to the prediction of protein contact number reported here, together with previous applications of this approach to the prediction of protein accessible surface area and B-factor profile, suggests that a support vector regression approach may be very useful for determining the structure-function relation between primary sequence and higher order consecutive protein structural and functional properties.

Contact angle effects on microdroplet deformation using CFD

In this paper we use computational fluid dynamics (CFD) to study the effect of contact angle on droplet shape as it moves through a contraction. A new non-dimensional number is proposed in order to predict situations where the deformed droplet will form a slug in the contraction and thus have the opportunity to interact with the channel wall. It is proposed that droplet flow into a contraction is a useful method to ensure that a droplet will wet a channel surface without a trapped lubrication film, and thus help ensure that a slug will remain attached to the wall downstream of the contraction. We demonstrate that when a droplet is larger than a contraction, capillary and Reynolds numbers, and fluid properties may not be sufficient to fully describe the droplet dynamics through a contraction. We show that, with everything else constant, droplet shape and breakup can be controlled simply by changing the wetting properties of the channel wall. CFD simulations with contact angles ranging from 30 degrees to 150 degrees show that lower contact angles can induce droplet breakup while higher contact angles can form slugs with contact angle dependent shape. Crown Copyright (c) 2005 Published by Elsevier Inc. All rights reserved.

Experimental and analytical study of the effect of contact angle on liquid convective heat transfer in microchannels

In this paper we examine the effect of contact angle (or surface wettability) on the convective heat transfer coefficient in microchannels. Slip flow, where the fluid velocity at the wall is non-zero, is most likely to occur in microchannels due to its dependence on shear rate or wall shear stress. We show analytically that for a constant pressure drop, the presence of slip increases the Nusselt number. In a microchannel heat exchanger we modified the surface wettability from a contact angle of 20 degrees-120 degrees using thin film coating technology. Apparent slip flow is implied from pressure and flow rate measurements with a departure from classical laminar friction coefficients above a critical shear rate of approximately 10,000 s(-1). The magnitude of this departure is dependant on the contact angle with higher contact angles surfaces exhibiting larger pressure drop decreases. Similarly, the non-dimensional heat flux is found to decrease relative to laminar non-slip theory, and this decrease is also a function of the contact angle. Depending on the contact angle and the wall shear rate, variations in the heat transfer rate exceeding 10% can be expected. Thus the contact angle is an important consideration in the design of micro, and even more so, nano heat exchangers. (c) 2006 Elsevier Ltd. All rights reserved.

Predicting residue-wise contact orders in proteins by support vector regression

Background: The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results: We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion: The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.