Pad-Batch Dyeing of Wool Fabric—Development of an Industrial Process*

This paper describes an industrial procedure developed for the application of dyes of good fastness properties, especially reactive dyes, to wool fabric by a pad-batch technique, following the initial observations (7) that by dyeing from concentrated solutions of urea the rates of diffusion and of reaction of reactive dyes with wool are greatly increased. The chemical and mechanical developments necessary to apply this initial observation under practical dyeing conditions are described.     

Chiral discrimination of basic and hydrophobic molecules by chemical force spectroscopy

Chemical force spectroscopy (CFS) is becoming a powerful technique with which to measure intermolecular forces. The prime advantage over other techniques is the ability to map spatial distribution of ligands on the surface. We have used CFS to explore the binding force of a variety of different chiral molecules in order to understand more about the nature of what is a fundamental aspect of chemical biology and of central importance in pharmacology.     

Controlled modification and direct characterization of multimode-fiber refractive-index profiles

A combination of controlled annealing and characterization by scanning probe microscopy (SPM) is used to demonstrate that the refractive-index proffle of a commercially available silica-based optical fiber can be accurately reconfigured for use as an evanescent field sensor. The process relies on the controlled relocation of the silica glass dopants across the fiber cross section through heat treatment and the accurate measurement of the resulting dopant redistribution with SPM and differential etching techniques. The effect of variable annealing along a length of fiber is to produce a mode transformer to couple light from a laser source into the sensing region of the fiber.     

Effect of powder characteristics on the sinterability of hydroxyapatite powders

The effect of different sintering conditions on the sintered density and microstructure of two different hydroxyapatite (HA) powders was examined. The powder characteristics of a laboratory synthesized HA powder (Lab HA) were low crystallinity, a bimodal particle size distribution, a median particle size of 22 m and a high specific surface area (SSA) of 63 m²/g. By contrast, a commercial calcined HA (commercial HA) was crystalline and had a median particle size of 5 m and a low SSA of 16 m²/g. The different powder characteristics affected the compactability and the sinterability of the two HA powders. Lab HA did not compact as efficiently as commercial HA, resulting in a lower green density, but the onset of sintering of powder compacts of the former was approximately 150 °C lower than the later. The effect of compaction pressure, sintering temperature, time and heating rate on the sintered densities of the two materials was studied. Varying all these sintering conditions significantly affected the sintered density of commercial HA, whereas the sintered density of Lab HA was only affected significantly by increasing the sintering temperature. The Vickers hardness, H_v, of Lab HA was greater than commercial HA for low sintering temperatures, below 1200 °C, whereas for higher sintering temperatures the commercial HA produced ceramics with greater values of hardness. These trends can be related to the sinterability of the two materials.     

Atom pair persistence in disordered materials from fluctuation microscopy

We show that the kinematical theory of fluctuation microscopy for a disordered specimen can be reformulated in terms of an atom pair-pair correlation function. Resolution and coherence are two experimental variables which yield a two-dimensional fluctuation map. This map is a transformation of the pair-pair correlation function, but can be directly interpreted in terms of a pair persistence function (PPF). We show that the PPF reveals the correlation length and structure for a simple paracrystalline model.     

Model Risk for European-Style Stock Index Options

In empirical modeling, there have been two strands for pricing in the options literature, namely the parametric and nonparametric models. Often, the support for the nonparametric methods is based on a benchmark such as the Black-Scholes (BS) model with constant volatility. In this paper, we study the stochastic volatility (SV) and stochastic volatility random jump (SVJ) models as parametric benchmarks against feedforward neural network (FNN) models, a class of neural network models. Our choice for FNN models is due to their well-studied universal approximation properties of an unknown function and its partial derivatives. Since the partial derivatives of an option pricing formula are risk pricing tools, an accurate estimation of the unknown option pricing function is essential for pricing and hedging. Our findings indicate that FNN models offer themselves as robust option pricing tools, over their sophisticated parametric counterparts in predictive settings. There are two routes to explain the superiority of FNN models over the parametric models in forecast settings. These are nonnormality of return distributions and adaptive learning     

Personalising speech-to-speech translation: Unsupervised cross-lingual speaker adaptation for HMM-based speech synthesis

In this paper we present results of unsupervised cross-lingual speaker adaptation applied to text-to-speech synthesis. The application of our research is the personalisation of speech-to-speech translation in which we employ a HMM statistical framework for both speech recognition and synthesis. This framework provides a logical mechanism to adapt synthesised speech output to the voice of the user by way of speech recognition. In this work we present results of several different unsupervised and cross-lingual adaptation approaches as well as an end-to-end speaker adaptive speech-to-speech translation system. Our experiments show that we can successfully apply speaker adaptation in both unsupervised and cross-lingual scenarios and our proposed algorithms seem to generalise well for several language pairs. We also discuss important future directions including the need for better evaluation metrics.