Aramid pulp treated with imidazolium ionic liquids as a filler in rigid polyurethane bio-foams

This article reports an aramid pulp (AP) treated with two ionic liquids (IL), namely 1-n-butyl-3-methylimidazolium chloride (C₄.Cl) and 1-carboxymethyl-3-methylimidazolium chloride (HO₂C), and its use as a filler in reinforced rigid polyurethane foams (RPUF). The RPUF were incorporated with the treated AP at three weight fractions (c.a. 0.1, 0.5, and 1.0 wt%) and were produced by the free rising method. The results showed that the studied IL promoted a better interaction between the AP and the RPUF system, which increased the overall reactivity, imparting a higher cell anisotropy. This also yielded a positive effect in mechanical properties and thermal stability of the RPUF. Compared to the neat RPUF, outstanding increases of approximately 50 and 20% were achieved in compressive modulus and strength, respectively. In all, the use of IL promoted increased compatibility between matrix and reinforcement, especially that HO₂C IL.     

Selecting linear algebra kernel composition using response time prediction

Numerical linear algebra libraries provide many kernels that can be composed to perform complex computations. For a given computation, there is typically a large number of functionally equivalent kernel compositions. Some of these compositions achieve better response times than others for particular data and when executed on a particular computer architecture. Previous research provides methods to enumerate (a subset of) these kernel compositions. In this work, we study the problem of determining the composition that yields the lowest response time. Our approach is based on a response time prediction for each candidate combination. While this prediction could in principle be obtained using analytical and/or empirical performance models, developing accurate such models is known to be challenging. Instead, we define a feature space that captures salient properties of kernel combinations and predict response time using supervised machine learning. We experiment with a standard set of machine learning algorithms and identify an effective algorithm for our kernel composition selection problem. Using this algorithm, our approach widely outperforms the strategy that would consist in always using the simplest kernel composition and is often close to the fastest kernel compositions among those evaluated. We quantify the potential benefit of our approach if it were to be implemented as part of an interactive computational tool. We find that although the potential benefit is substantial, a limiting factor is the kernel composition enumeration overhead. Copyright © 2014 John Wiley & Sons, Ltd.     

Advanced product planning: a comprehensive process for systemic definition of new product requirements

This paper reports results of research into the definition of requirements for new consumer products––specifically, electro-mechanical products. The research dealt with the derivation of design requirements that are demonstrably aligned with stakeholder needs. The paper describes a comprehensive process that can enable product development teams to deal with statements of product requirements, as originally collected through market research activities, in a systematic and traceable manner from the early, fuzzy front end, stages of the design process. The process described has been based on principles of systems engineering. A case study from its application and evaluation drawn from the power sector is described in this paper. The case study demonstrates how the process can significantly improve product quality planning practices through revision of captured product requirements, analysis of stakeholder requirements and derivation of design requirements. The paper discusses benefits and issues from the use of the process by product development teams, and identifies areas for further research. Finally, the conclusions drawn from the reported research are presented.

Chemical sensor based on a novel capacitive microwave flexible transducer with polymer nanocomposite-carbon nanotube sensitive film

Microsystem Technologies - This study presents the results on the feasibility of a resonant planar chemical capacitive sensor in the microwave frequency range suitable for gas detection and...     

Analysis of Non-Equilibrium Fluctuations In A Ternary Liquid Mixture

From the benchmark values of the diffusion and thermodiffusion coefficients of the tetralin, isobutylbenzene and n-dodecane ternary mixture, and the published optical contrast factors, we have evaluated the theoretical amplitudes of the two composition modes of the refractive-index fluctuations. Shadowgraph experiments have been performed on ground, where the current theory is expected to be correct only for large wave vectors. Two decay times have been observed experimentally. The fastest one being related to the thermal diffusivity of the mixture, while the slower one to mass diffusion. Hence, it has not been possible to distinguish the two eigenvalues of the mass diffusion matrix, a problem also encountered in traditional light-scattering with ternary mixtures of similar-size molecules. Thus, to compare the measured Intermediate Scattering Function with theory, we fix the amplitudes and decay rates to the benchmark values, use the wave number as a fitting parameter, and compare it to the experimental wave number. The good agreement between theory and experiments for the larger wave numbers validates the theory developed for the microgravity conditions.     

A unifying criterion for unsupervised clustering and feature selection

Exploratory data analysis methods are essential for getting insight into data. Identifying the most important variables and detecting quasi-homogenous groups of data are problems of interest in this context. Solving such problems is a difficult task, mainly due to the unsupervised nature of the underlying learning process. Unsupervised feature selection and unsupervised clustering can be successfully approached as optimization problems by means of global optimization heuristics if an appropriate objective function is considered. This paper introduces an objective function capable of efficiently guiding the search for significant features and simultaneously for the respective optimal partitions. Experiments conducted on complex synthetic data suggest that the function we propose is unbiased with respect to both the number of clusters and the number of features.     

A multi-level, multi-theory perspective of information technology implementation

Abstract.  Much of information technology (IT) implementation research has focused on individuals' acceptance of IT by examining their behaviour when faced with new IT and the antecedents of these behaviours. As they are frequently undertaken within a project framework, IT implementations also entail the application of project management practices in order to be successful. Based on the premise that antecedents of lower level theories are frequently determined by the outcomes of a higher level theory, the present paper illustrates how organizational-level decisions, examined from the perspective of economics theories, can help explain the antecedents of project risk management at the project and individual levels. To do so, the paper describes an IT implementation effort which went through three phases; the first two of which were abandoned versions of the same project. An organizational-level analysis of the case from an economics perspective and its project-level analysis from a risk management perspective show how organizational-level decisions influenced the antecedents at the project and individual levels, providing a more complete understanding of the IT implementation in question, an understanding which neither a theory approach nor a level perspective could provide on its own.     

Food vacuole proteome of the malarial parasite Plasmodium falciparum

The Plasmodium falciparum food vacuole (FV) is a lysosome-like organelle where erythrocyte hemoglobin digestion occurs. It is a favorite target in the development of antimalarials. We have used a tandem mass spectrometry approach to investigate the proteome of an FV-enriched fraction and identified 116 proteins. The electron microscopy analysis and the Western blot data showed that the major component of the fraction was the FV and, as expected, the majority of previously known FV markers were recovered. Of particular interest, several proteins involved in vesicle-mediated trafficking were identified, which are likely to play a key role in FV biogenesis and/or FV protein trafficking. Recovery of parasite surface proteins lends support to the cytostomal pathway of hemoglobin ingestion as a FV trafficking route. We have identified 32 proteins described as hypothetical in the databases. This insight into FV protein content provides new clues towards understanding the biological function of this organelle in P. falciparum.