Model-order selection in Zernike polynomial expansion of corneal surfaces using the efficient detection criterion

Corneal-height data are typically measured with videokeratoscopes and modeled using a set of orthogonal Zernike polynomials. We address the estimation of the number of Zernike polynomials, which is formalized as a model-order selection problem in linear regression. Classical information-theoretic criteria tend to overestimate the corneal surface due to the weakness of their penalty functions, while bootstrap-based techniques tend to underestimate the surface or require extensive processing. In this paper, we propose to use the efficient detection criterion (EDC), which has the same general form of information-theoretic-based criteria, as an alternative to estimating the optimal number of Zernike polynomials. We first show, via simulations, that the EDC outperforms a large number of information-theoretic criteria and resampling-based techniques. We then illustrate that using the EDC for real corneas results in models that are in closer agreement with clinical expectations and provides means for distinguishing normal corneal surfaces from astigmatic and keratoconic surfaces.

Decoration of active sites to create bimetallic surfaces and its implication for electrochemical processes

The creation of electrocatalysts based on noble metals has received a significant amount of research interest due to their extensive use as fuel cell catalysts and electrochemical sensors. There have been many attempts to improve the activity of these metals through creating nanostructures, as well as post-synthesis treatments based on chemical, electrochemical, sonochemical and thermal approaches. In many instances these methods result in a material with active surface states, which can be considered to be adatoms or clusters of atoms on the surface that have a low lattice co-ordination number making them more prone to electrochemical oxidation at a wide range of potentials that are significantly less positive than those of their bulk metal counterparts. This phenomenon has been termed pre-monolayer oxidation and has been reported to occur on a range of metallic surfaces. In this work we present findings on the presence of active sites on Pd that has been: evaporated as a thin film; electrodeposited as nanostructures; as well as commercially available Pd nanoparticles supported on carbon. Significantly, advantage is taken of the low oxidation potential of these active sites whereby bimetallic surfaces are created by the spontaneous deposition of Ag from AgNO3 to generate Pd/Ag surfaces. Interestingly this approach does not increase the surface area of the original metal but has significant implications for its further use as an electrode material. It results in the inhibition or promotion of electrocatalytic activity which is highly dependent on the reaction of interest. As a general approach the decoration of active catalytic materials with less active metals for a particular reaction also opens up the possibility of investigating the role of the initially present active sites on the surface and identifying the degree to which they are responsible for electrocatalytic activity.

Controlling whole blood activation and resultant clot properties by carboxyl and alkyl functional groups on material surfaces : a possible therapeutic approach for enhancing bone healing

Most research virtually ignores the important role of a blood clot in supporting bone healing. In this study, we investigated the effects of surface functional groups carboxyl and alkyl on whole blood coagulation, complement activation and blood clot formation. We synthesised and tested a series of materials with different ratios of carboxyl (–COOH) and alkyl (–CH3, –CH2CH3 and –(CH2)3CH3) groups. We found that surfaces with –COOH/–(CH2)3CH3 induced a faster coagulation activation than those with –COOH/– CH3 and –CH2CH3, regardless of the –COOH ratios. An increase in –COOH ratios on –COOH/–CH3 and –CH2CH3 surfaces decreased the rate of coagulation activation. The pattern of complement activation was entirely similar to that of surface-induced coagulation. All material coated surfaces resulted in clots with thicker fibrin in a denser network at the clot/material interface and a significantly slower initial fibrinolysis when compared to uncoated glass surfaces. The amounts of platelet-derived growth factor-AB (PDGF-AB) and transforming growth factor-b (TGF-b1) released from an intact clot were higher than a lysed clot. The release of PDGF-AB was found to be correlated with the fibrin density. This study demonstrated that surface chemistry can significantly influence the activation of blood coagulation and complement system, resultant clot structure, susceptibility to fibrinolysis as well as release of growth factors, which are important factors determining the bone healing process.

The BAD project: data mining, database and prediction of protein adsorption on surfaces

Protein adsorption at solid-liquid interfaces is critical to many applications, including biomaterials, protein microarrays and lab-on-a-chip devices. Despite this general interest, and a large amount of research in the last half a century, protein adsorption cannot be predicted with an engineering level, design-orientated accuracy. Here we describe a Biomolecular Adsorption Database (BAD), freely available online, which archives the published protein adsorption data. Piecewise linear regression with breakpoint applied to the data in the BAD suggests that the input variables to protein adsorption, i.e., protein concentration in solution; protein descriptors derived from primary structure (number of residues, global protein hydrophobicity and range of amino acid hydrophobicity, isoelectric point); surface descriptors (contact angle); and fluid environment descriptors (pH, ionic strength), correlate well with the output variable-the protein concentration on the surface. Furthermore, neural network analysis revealed that the size of the BAD makes it sufficiently representative, with a neural network-based predictive error of 5% or less. Interestingly, a consistently better fit is obtained if the BAD is divided in two separate sub-sets representing protein adsorption on hydrophilic and hydrophobic surfaces, respectively. Based on these findings, selected entries from the BAD have been used to construct neural network-based estimation routines, which predict the amount of adsorbed protein, the thickness of the adsorbed layer and the surface tension of the protein-covered surface. While the BAD is of general interest, the prediction of the thickness and the surface tension of the protein-covered layers are of particular relevance to the design of microfluidics devices.

Some surface profiles of a strip after plane-strain indentation by rigid bodies with serrated surfaces

This paper is concerned with the surface profiles of a strip after rigid bodies with serrated (saw-teeth) surfaces indent the strip and are subsequently removed. Plane-strain conditions are assumed. This has application in roughness transfer of final metal forming process. The effects of the semi-angle of the teeth, the depth of indentation and the friction on the contact surface on the profile are considered.