Controversy on the Free Energy of Formation of CaO Additional Evidence in Support of Thermochemical Data

The standard free energies of formation of CaO derived from a variety of high-temperature equilibrium measurements made by seven groups of experimentalists are significantly different from those given in the standard compilations of thermodynamic data. Indirect support for the validity of the compiled data comes from new solid-state electrochemical measurements using single-crystal CaF2 and SrF2 as electrolytes. The change in free energy for the following reactions are obtained: CaO + MgF2 --> MgO + CaF2 Delta G degrees = -68,050 -2.47 T(+/-100) J mol(-1) SrO + CaF2 --> SrF2 + CaO Delta G degrees = -35,010 + 6.39 T (+/-80) J mol(-1) The standard free energy changes associated with cell reactions agree with data in standard compilations within +/- 4 kJ mol(-1). The results of this study do not support recent suggestions for a major revision in thermodynamic data for CaO.

Prediction of Candidate Primary Immunodeficiency Disease Genes Using a Support Vector Machine Learning Approach

Screening and early identification of primary immunodeficiency disease (PID) genes is a major challenge for physicians. Many resources have catalogued molecular alterations in known PID genes along with their associated clinical and immunological phenotypes. However, these resources do not assist in identifying candidate PID genes. We have recently developed a platform designated Resource of Asian PDIs, which hosts information pertaining to molecular alterations, protein-protein interaction networks, mouse studies and microarray gene expression profiling of all known PID genes. Using this resource as a discovery tool, we describe the development of an algorithm for prediction of candidate PID genes. Using a support vector machine learning approach, we have predicted 1442 candidate PID genes using 69 binary features of 148 known PID genes and 3162 non-PID genes as a training data set. The power of this approach is illustrated by the fact that six of the predicted genes have recently been experimentally confirmed to be PID genes. The remaining genes in this predicted data set represent attractive candidates for testing in patients where the etiology cannot be ascribed to any of the known PID genes.

Quality of support for multicasting over mobile ad-hoc networks

An ad hoc network is composed of mobile nodes without any infrastructure. Recent trends in applications of mobile ad hoc networks rely on increased group oriented services. Hence multicast support is critical for ad hoc networks. We also need to provide service differentiation schemes for different group of users. An efficient application layer multicast (APPMULTICAST) solution suitable for low mobility applications in MANET environment has been proposed in [10]. In this paper, we present an improved application layer multicast solution suitable for medium mobility applications in MANET environment. We define multicast groups with low priority and high priority and incorporate a two level service differentiation scheme. We use network layer support to build the overlay topology closer to the actual network topology. We try to maximize Packet Delivery Ratio. Through simulations we show that the control overhead for our algorithm is within acceptable limit and it achieves acceptable Packet Delivery Ratio for medium mobility applications.

Classification of magnetic resonance brain images using wavelets as input to support vector machine and neural network

In this paper. we propose a novel method using wavelets as input to neural network self-organizing maps and support vector machine for classification of magnetic resonance (MR) images of the human brain. The proposed method classifies MR brain images as either normal or abnormal. We have tested the proposed approach using a dataset of 52 MR brain images. Good classification percentage of more than 94% was achieved using the neural network self-organizing maps (SOM) and 98% front support vector machine. We observed that the classification rate is high for a Support vector machine classifier compared to self-organizing map-based approach.

A course for teaching design research methodology

Design research informs and supports practice by developing knowledge to improve the chances of producing successful products.Training in design research has been poorly supported. Design research uses human and natural/technical sciences, embracing all facets of design; its methods and tools are adapted from both these traditions. However, design researchers are rarely trained in methods from both the traditions. Research in traditional sciences focuses primarily on understanding phenomena related to human, natural, or technical systems. Design research focuses on supporting improvement of such systems, using understanding as a necessary but not sufficient step, and it must embrace methods for both understanding reality and developing support for its improvement. A one-semester, postgraduate-level, credited course that has been offered since 2002, entitled Methodology for Design Research, is described that teaches a methodology for carrying out research into design. Its steps are to clarify research success; to understand relevant phenomena of design and how these influence success; to use this to envision design improvement and develop proposals for supporting improvement; to evaluate support for its influence on success; and, if unacceptable, to modify, support, or improve the understanding of success and its links to the phenomena of design. This paper highlights some major issues about the status of design research and describes how design research methodology addresses these. The teaching material, model of delivery, and evaluation of the course on methodology for design research are discussed.

Electron diffraction structure analysis: structural research with low-quality diffraction data

Electron Diffraction Structure Analysis (EDSA) with data from standard selected-area electron diffraction (SAED) is still the method of choice for structure determination of nano-sized single crystals. The recently determined heavy atom structure α-Ti2Se (Albe & Weirich, 2003) is used as an example to illustrate the developed procedure for structure determination from two-dimensionally SAED data via direct methods and kinematical least-squares refinement. Despite the investigated crystallite had a relatively large effective thickness of about 230 Å as determined from dynamical calculations, the obtained structural model from SAED data was found in good agreement with the result from an earlier single crystal X-ray study (Weirich, Pöttgen & Simon, 1996). Arguments, which support the validity of the used quasi-kinematical approach, are given in the text. The influences of dynamical and secondary scattering on the quality of the data and the structure solution are discussed. Moreover, the usefulness of first-principles calculations for verifying the results from EDSA is demonstrated by two examples, whereas one of the structures was unattainable by conventional X-ray diffraction.

Recent Research in Structural Health Monitoring

Roctest Group believes in the importance of maintaining a close contact with the scientific community active in fields close to our activities domains, in particular smart structures, structural engineering, sensing and fiber optic sensors. These contacts allow Roctest SMARTEC Telemac to remain at the front of scientific progress and to contribute to the diffusion of the monitoring culture worldwide. Our research and development team actively contributes in the research community, attending conferences and regularly publishing in the scientific literature. we support academic research by participating in joint research projects and by regularly welcoming graduate and undergraduate students for stages and exchange programs.

External support and innovation performance of SMEs in Bangalore: Role of firm level factors

This paper probes the role of internal factors in SMEs in obtaining external support and achieving innovation performance in the context of auto component, electronics and machine tool industries of Bangalore in India. Using step-wise logistic regression analysis, the study found that only if SMEs have internal technical competence in terms of technically qualified entrepreneur, an exclusive design centre, and innovate more frequently, they will be able to obtain external support. Further using step-wise multiple regression the study concluded that SMEs which have come up to implement innovative ideas or exploit market opportunities and which have obtained external support with technically qualified entrepreneurs are able to exhibit better innovation performance.