Another angle on contact lens surface analysis

Purpose: Dynamic contact angle (DCA) methods have advantages over other contact angle methodologies, not least that they can provide more than single contact angle values. Here we illustrate the use of DCA analysis to provide “fingerprint” characterisation of contact lens surfaces, and the way that different materials change in the early stages of wear. Method: The DCA method involves attaching to a microbalance weighted strips cut from a lens. The strips are then cyclically inserted into and removed from an aqueous solution. Conventionally, readings of force taken from linear portions of the resultant dipping curves are translated into advancing (CAa) and receding contact (CAr) angles. Additionally, analysis of the force versus immersion profile provides a “fingerprint” characterisation of the state of the lens surface. Results: CAa and CAr values from DCA traces provide a useful means of differentiating gross differences in hydrophilicity and molecular mobility of surfaces under particular immersion and emersion conditions, such as dipping rate and dwell times. Typical values for etafilcon A (CAa:63.1; CAr:37) and balafilcon B (CAa:118.4; CAr:36.4) illustrate this. Surface modifications induced in lens manufacture are observed to produce not only changes in these value, which may be small, but also changes in the DCA “fingerprint” (slope, undulations, length of plateau). Interestingly, similar changes are induced in the first few hours of lens wear with some lens-patient combinations. Conclusions: Although single parameter contact angles are useful for material characterisation, information of potential clinical interest can be obtained from more detailed analysis of DCA traces.

Generalized methods and solvers for noise removal from piecewise constant signals. I. Background theory

Removing noise from piecewise constant (PWC) signals is a challenging signal processing problem arising in many practical contexts. For example, in exploration geosciences, noisy drill hole records need to be separated into stratigraphic zones, and in biophysics, jumps between molecular dwell states have to be extracted from noisy fluorescence microscopy signals. Many PWC denoising methods exist, including total variation regularization, mean shift clustering, stepwise jump placement, running medians, convex clustering shrinkage and bilateral filtering; conventional linear signal processing methods are fundamentally unsuited. This paper (part I, the first of two) shows that most of these methods are associated with a special case of a generalized functional, minimized to achieve PWC denoising. The minimizer can be obtained by diverse solver algorithms, including stepwise jump placement, convex programming, finite differences, iterated running medians, least angle regression, regularization path following and coordinate descent. In the second paper, part II, we introduce novel PWC denoising methods, and comparisons between these methods performed on synthetic and real signals, showing that the new understanding of the problem gained in part I leads to new methods that have a useful role to play.

Synthesis and characterization of some carbon based nanostructures

The aim of present paper is to present the latest results on investigations of the carbon thin film deposited by Thermionic Vacuum Arc (TVA) method and laser pyrolysis. X-ray photoelectron spectroscopy (XPS) and X-ray generated Auger electron spectroscopy (XAES) were used to determine composition and sp2 to sp3 ratios in the outer layers of the film surfaces. The analyses were conducted in a Thermoelectron ESCALAB 250 electron spectrometer equipped with a hemispherical sector energy analyser. Monochromated Al K X-radiation was employed for the XPS examination, at source excitation energy of 15 KeV and emission current of 20 mA. Analyzer pass energy of 20 eV with step size of 0.1 eV and dwell time of 100 ms was used throughout. © 2010 SPIE.