The 27th British liquid crystal society annual meeting 2013, Cambridge

Attending the British Liquid Crystal Society’s (BLCS) Annual Meeting was a formative experience in my days as a PhD student, starting way back in the 1990s. At that time, this involved travelling to (to me) exotic parts of the United Kingdom, such as Reading, Oxford or Manchester, away from Southampton where I was based. Some postdoctoral years in a different country followed, and three BLCS Meetings were missed, until in 1997 and 1998, I was able to attend again, in Southampton and Leeds, respectively. Not much had changed from my student days, the size and the format were still about the same, many of the leading characters were still around, and the closing talk would still be given by John Lydon. Well, at some point, I got myself a proper academic job on the Continent and stopped attending BLCS Annual Meetings altogether. The fond memories of my youth started to fade. Were the Meetings still on? It seemed so, as old friends and acquaintances would occasionally recount attending them, and even winning prizes at them. But, it all seemed rather remote now. Until, that is, it came to pass that the 27th BLCS Meeting would be held in Selwyn College, Cambridge, just down (or up, depending on how you look at it) the road from the Isaac Newton Institute, where I was spending part of my sabbatical leave. The opportunity to resume attendance could not be missed. A brief e-mail exchange with the organisers, and a cheque to cover the fee, duly secured this. And thus, it was with trepidation that I approached my first BLCS Annual Meeting in more than a decade.

Chronic liver disease staging classification based on ultrasound, clinical and laboratorial data

In this work the identification and diagnosis of various stages of chronic liver disease is addressed. The classification results of a support vector machine, a decision tree and a k-nearest neighbor classifier are compared. Ultrasound image intensity and textural features are jointly used with clinical and laboratorial data in the staging process. The classifiers training is performed by using a population of 97 patients at six different stages of chronic liver disease and a leave-one-out cross-validation strategy. The best results are obtained using the support vector machine with a radial-basis kernel, with 73.20% of overall accuracy. The good performance of the method is a promising indicator that it can be used, in a non invasive way, to provide reliable information about the chronic liver disease staging.

Diffuse liver disease classification from ultrasound surface characterization, clinical and laboratorial data

In this work liver contour is semi-automatically segmented and quantified in order to help the identification and diagnosis of diffuse liver disease. The features extracted from the liver contour are jointly used with clinical and laboratorial data in the staging process. The classification results of a support vector machine, a Bayesian and a k-nearest neighbor classifier are compared. A population of 88 patients at five different stages of diffuse liver disease and a leave-one-out cross-validation strategy are used in the classification process. The best results are obtained using the k-nearest neighbor classifier, with an overall accuracy of 80.68%. The good performance of the proposed method shows a reliable indicator that can improve the information in the staging of diffuse liver disease.

An insight into dapsone co-crystals: sulfones as participants in supramolecular interactions

Agência Financiadora: Fundação para a Ciência e a Tecnologia - Pest-OE/QUI/UI0100/2013; PTDC/CTM-BPC/122447/2010; RECI/QEQ-QIN/0189/2012; SFRH/BPD/78854/2011

Optical nonlinearity in Tandem SI-C photodetectors

The behavior of tandem pin heterojunctions based on a-SiC: H alloys is investigated under different optical and electrical bias conditions. The devices are optimized to act as optically selective wavelength filters. Depending on the device configuration (optical gaps, thickness, sequence of cells in the stack structure) and on the applied voltage (positive or negative) and optical bias (wavelength, intensity, frequency) it is possible to combine the wavelength discrimination function with the self amplification of the signal. This wavelength nonlinearity allows the amplification or the rejection of a weak signal-impulse. The device works as an active tunable optical filter for wavelength selection and can be used as an add/drop multiplexer (ADM) which enables data to enter and leave an optical network bit stream without having to demultiplex the stream. Results show that, even under weak transient input signals, the background wavelength controls the output signal. This nonlinearity, due to the transient asymmetrical light penetration of the input channels across the device together with the modification on the electrical field profile due to the optical bias, allows tuning an input channel without demultiplexing the stream. This high optical nonlinearity makes the optimized devices attractive for the amplification of all optical signals. Transfer characteristics effects due to changes in steady state light, control d.c. voltage and applied light pulses are presented. Based on the experimental results and device configuration an optoelectronic model is developed. The transfer characteristics effects due to changes in steady state light, dc control voltage or applied light pulses are simulated and compared with the experimental data. A good agreement was achieved.

O sistema de controlo interno nas instituições financeiras

Mestrado em Auditoria