The morphology of decorated amyloid fibers is controlled by the conformation and position of the displayed protein.

Self-assembled structures capable of mediating electron transfer are an attractive scientific and technological goal. Therefore, systematic variants of SH3-Cytochrome b(562) fusion proteins were designed to make amyloid fibers displaying heme-b(562) electron transfer complexes. TEM and AFM data show that fiber morphology responds systematically to placement of b(562) within the fusion proteins. UV-vis spectroscopy shows that, for the fusion proteins under test, only half the fiber-borne b(562) binds heme with high affinity. Cofactor binding also improves the AFM imaging properties and changes the fiber morphology through changes in cytochrome conformation. Systematic observations and measurements of fiber geometry suggest that longitudinal registry of subfilaments within the fiber, mediated by the interaction and conformation of the displayed proteins and their interaction with surfaces, gives rise to the observed morphologies, including defects and kinks. Of most interest is the role of small molecule modulation of fiber structure and mechanical stability. A minimum complexity model is proposed to capture and explain the fiber morphology in the light of these results. Understanding the complex interplay between these factors will enable a fiber design that supports longitudinal electron transfer.

Extending noise robust structured support vector machines to larger vocabulary tasks

This paper describes a structured SVM framework suitable for noise-robust medium/large vocabulary speech recognition. Several theoretical and practical extensions to previous work on small vocabulary tasks are detailed. The joint feature space based on word models is extended to allow context-dependent triphone models to be used. By interpreting the structured SVM as a large margin log-linear model, illustrates that there is an implicit assumption that the prior of the discriminative parameter is a zero mean Gaussian. However, depending on the definition of likelihood feature space, a non-zero prior may be more appropriate. A general Gaussian prior is incorporated into the large margin training criterion in a form that allows the cutting plan algorithm to be directly applied. To further speed up the training process, 1-slack algorithm, caching competing hypothesis and parallelization strategies are also proposed. The performance of structured SVMs is evaluated on noise corrupted medium vocabulary speech recognition task: AURORA 4. © 2011 IEEE.

Hierarchical electrohydrodynamic structures for surface-enhanced Raman scattering.

Surface enhanced Raman scattering (SERS) is a well-established spectroscopic technique that requires nanoscale metal structures to achieve high signal sensitivity. While most SERS substrates are manufactured by conventional lithographic methods, the development of a cost-effective approach to create nanostructured surfaces is a much sought-after goal in the SERS community. Here, a method is established to create controlled, self-organized, hierarchical nanostructures using electrohydrodynamic (HEHD) instabilities. The created structures are readily fine-tuned, which is an important requirement for optimizing SERS to obtain the highest enhancements. HEHD pattern formation enables the fabrication of multiscale 3D structured arrays as SERS-active platforms. Importantly, each of the HEHD-patterned individual structural units yield a considerable SERS enhancement. This enables each single unit to function as an isolated sensor. Each of the formed structures can be effectively tuned and tailored to provide high SERS enhancement, while arising from different HEHD morphologies. The HEHD fabrication of sub-micrometer architectures is straightforward and robust, providing an elegant route for high-throughput biological and chemical sensing.

A comparison of the value of viscosity for several water models using Poiseuille flow in a nano-channel.

The viscosity-temperature relation is determined for the water models SPC/E, TIP4P, TIP4P/Ew, and TIP4P/2005 by considering Poiseuille flow inside a nano-channel using molecular dynamics. The viscosity is determined by fitting the resulting velocity profile (away from the walls) to the continuum solution for a Newtonian fluid and then compared to experimental values. The results show that the TIP4P/2005 model gives the best prediction of the viscosity for the complete range of temperatures for liquid water, and thus it is the preferred water model of these considered here for simulations where the magnitude of viscosity is crucial. On the other hand, with the TIP4P model, the viscosity is severely underpredicted, and overall the model performed worst, whereas the SPC/E and TIP4P/Ew models perform moderately.

The retrieval of structured design rationale for the re-use of design knowledge with an integrated representation

Design knowledge can be acquired from various sources and generally requires an integrated representation for its effective and efficient re-use. Though knowledge about products and processes can illustrate the solutions created (know-what) and the courses of actions (know-how) involved in their creation, the reasoning process (know-why) underlying the solutions and actions is still needed for an integrated representation of design knowledge. Design rationale is an effective way of capturing that missing part, since it records the issues addressed, the options considered, and the arguments used when specific design solutions are created and evaluated. Apart from the need for an integrated representation, effective retrieval methods are also of great importance for the re-use of design knowledge, as the knowledge involved in designing complex products can be huge. Developing methods for the retrieval of design rationale is very useful as part of the effective management of design knowledge, for the following reasons. Firstly, design engineers tend to want to consider issues and solutions before looking at solid models or process specifications in detail. Secondly, design rationale is mainly described using text, which often embodies much relevant design knowledge. Last but not least, design rationale is generally captured by identifying elements and their dependencies, i.e. in a structured way which opens the opportunity for going beyond simple keyword-based searching. In this paper, the management of design rationale for the re-use of design knowledge is presented. The retrieval of design rationale records in particular is discussed in detail. As evidenced in the development and evaluation, the methods proposed are useful for the re-use of design knowledge and can be generalised to be used for the retrieval of other kinds of structured design knowledge. © 2012 Elsevier Ltd. All rights reserved.

Color photometric stereo for multicolored surfaces

We present a multispectral photometric stereo method for capturing geometry of deforming surfaces. A novel photometric calibration technique allows calibration of scenes containing multiple piecewise constant chromaticities. This method estimates per-pixel photometric properties, then uses a RANSAC-based approach to estimate the dominant chromaticities in the scene. A likelihood term is developed linking surface normal, image intensity and photometric properties, which allows estimating the number of chromaticities present in a scene to be framed as a model estimation problem. The Bayesian Information Criterion is applied to automatically estimate the number of chromaticities present during calibration. A two-camera stereo system provides low resolution geometry, allowing the likelihood term to be used in segmenting new images into regions of constant chromaticity. This segmentation is carried out in a Markov Random Field framework and allows the correct photometric properties to be used at each pixel to estimate a dense normal map. Results are shown on several challenging real-world sequences, demonstrating state-of-the-art results using only two cameras and three light sources. Quantitative evaluation is provided against synthetic ground truth data. © 2011 IEEE.

The retrieval of structured design knowledge

Design rationale is an effective way of capturing knowledge, since it records the issues addressed, the options considered, and the arguments used when specific decisions are made during the design process. Design rationale is generally captured by identifying elements and their dependencies, i.e. in a structured way. Current retrieval methods focus mainly on either the classification of rationale or on keyword-based searches of records. Keyword-based retrieval is reasonably effective as the information in design rationale records is mainly described using text. However, most of the current keyword-based retrieval methods discard the implicit structures of these records, resulting either in poor precision of retrieval or in isolated pieces of information that are difficult to understand. This ongoing research aims to go beyond keyword-based retrieval by developing methods and tools to facilitate the provision of useful design knowledge in new design projects. Our first step is to understand the structured information derived from the relationship between lumps of text held in different nodes in the design rationale captured via a software tool currently used in industry, and study how this information can be utilised to improve retrieval performance. Specifically, methods for utilising various structured information are developed and implemented on a prototype keyword-based retrieval system developed in our earlier work. The implementation and evaluation of these methods shows that the structured information can be utilised in a number of ways, such as filtering the results and providing more complete information. This allows the retrieval system to present results that are easy to understand, and which closely match designers' queries. Like design rationale, other methods for representing design knowledge also in essence involve structured information and thus the methods proposed can be generalised to be adapted and applied for the retrieval of other kinds of design knowledge. Copyright © 2002-2012 The Design Society. All rights reserved.

Defects Detection and Assessment in Concrete Surfaces

Aside from cracks, the impact of other surface defects, such as air pockets and discoloration, can be detrimental to the quality of concrete in terms of strength, appearance and durability. For this reason, local and national codes provide standards for quantifying the quality impact of these concrete surface defects and owners plan for regular visual inspections to monitor surface conditions. However, manual visual inspection of concrete surfaces is a qualitative (and subjective) process with often unreliable results due to its reliance on inspectors’ own criteria and experience. Also, it is labor intensive and time-consuming. This paper presents a novel, automated concrete surface defects detection and assessment approach that addresses these issues by automatically quantifying the extent of surface deterioration. According to this approach, images of the surface shot from a certain angle/distance can be used to automatically detect the number and size of surface air pockets, and the degree of surface discoloration. The proposed method uses histogram equalization and filtering to extract such defects and identify their properties (e.g. size, shape, location). These properties are used to quantify the degree of impact on the concrete surface quality and provide a numerical tool to help inspectors accurately evaluate concrete surfaces. The method has been implemented in C++ and results that validate its performance are presented.