Towards the development of poly (phenylene sulphide) based nanocomposites with enhanced mechanical, electrical and tribological properties

Novel poly(phenylene sulphide) (PPS) nanocomposites reinforced with an aminated derivative (PPS-NH2) covalently attached to acid-treated single-walled carbon nanotubes (SWCNTs) were prepared via simple melt-blending technique. Their morphology, viscoelastic behaviour, electrical conductivity, mechanical and tribological properties were investigated. Scanning electron microscopy revealed that the grafting process was effective in uniformly dispersing the SWCNTs within the matrix. The storage and loss moduli as a function of frequency increased with the SWCNT content, tending to a plateau in the low-frequency regime. The electrical conductivity of the nanocomposites was considerably enhanced in the range 0.1?0.5 wt% SWCNTs; electrical and rheological percolation thresholds occurred at similar nanotube concentrations. Mechanical tests demonstrated that with only 1.0 wt% SWCNTs the Young's modulus and tensile strength of the matrix improved by 51 and 37%, respectively, without decrement in toughness, ascribed to a very efficient load transfer. A moderate decrease in the friction coefficient and a 75% reduction in wear rate were found for the abovementioned nanotube loading, indicating that PPS-NH2-g-SWCNTs are good tribological additives for thermoplastic polymers. Based on the promising results obtained in this work, it is expected that these nanofillers will be used to develop high-performance thermoplastic/CNT nanocomposites for structural applications.

Combining data mining and ontology engineering to enrich ontologies and linked data

In this position paper, we claim that the need for time consuming data preparation and result interpretation tasks in knowledge discovery, as well as for costly expert consultation and consensus building activities required for ontology building can be reduced through exploiting the interplay of data mining and ontology engineering. The aim is to obtain in a semi-automatic way new knowledge from distributed data sources that can be used for inference and reasoning, as well as to guide the extraction of further knowledge from these data sources. The proposed approach is based on the creation of a novel knowledge discovery method relying on the combination, through an iterative ?feedbackloop?, of (a) data mining techniques to make emerge implicit models from data and (b) pattern-based ontology engineering to capture these models in reusable, conceptual and inferable artefacts.

Preface. The Language of Architecture and Civil Engineering

Preface

Educational Project for the Teaching of Control of Electric Traction Drives

Electric vehicles constitute a multidisciplinary subject that involves disciplines such as automotive, mechanical, electrical and control engineering. Due to this multidisciplinary technical nature, practical teaching methodologies are of special relevance. Paradoxically, in the past, the training of engineers specializing in this area has lacked the practical component represented by field tests, due to the difficulty of accessing real systems. This paper presents an educational project specifically designed for the teaching and training of engineering students with different backgrounds and experience. The teaching methodology focuses on the topology of electric traction drives and their control. It includes two stages, a simulation computer model and a scaled laboratory workbench that comprises a traction electrical drive coupled to a vehicle emulator. With this equipment, the effectiveness of different traction control strategies can be analyzed from the point of view of energy efficiency, robustness, easiness of implementation and acoustic noise.

Peptide design by artificial neural networks and computer-based evolutionary search

A technique for systematic peptide variation by a combination of rational and evolutionary approaches is presented. The design scheme consists of five consecutive steps: (i) identification of a “seed peptide” with a desired activity, (ii) generation of variants selected from a physicochemical space around the seed peptide, (iii) synthesis and testing of this biased library, (iv) modeling of a quantitative sequence-activity relationship by an artificial neural network, and (v) de novo design by a computer-based evolutionary search in sequence space using the trained neural network as the fitness function. This strategy was successfully applied to the identification of novel peptides that fully prevent the positive chronotropic effect of anti-β1-adrenoreceptor autoantibodies from the serum of patients with dilated cardiomyopathy. The seed peptide, comprising 10 residues, was derived by epitope mapping from an extracellular loop of human β1-adrenoreceptor. A set of 90 peptides was synthesized and tested to provide training data for neural network development. De novo design revealed peptides with desired activities that do not match the seed peptide sequence. These results demonstrate that computer-based evolutionary searches can generate novel peptides with substantial biological activity.

Electrical and synaptic properties of embryonic luteinizing hormone-releasing hormone neurons in explant cultures.

Voltage- and ligand-activated channels in embryonic neurons containing luteinizing hormone-releasing hormone (LHRH) were studied by patch-pipette, whole-cell current and voltage clamp techniques. LHRH neurons were maintained in explant cultures derived from olfactory pit regions of embryonic mice. Cells were marked intracellularly with Lucifer yellow following recording. Sixty-two cells were unequivocally identified as LHRH neurons by Lucifer yellow and LHRH immunocytochemistry. The cultured LHRH neurons had resting potentials around -50 mV, exhibited spontaneous discharges generated by intrinsic and/or synaptic activities and contained a time-dependent inward rectifier (Iir). Voltage clamp analysis of ionic currents in the LHRH neuron soma revealed a tetrodotoxin-sensitive Na+ current (INa) and two major types of K+ currents, a transient current (IA), a delayed rectifier current (IK) and low- and high-voltage-activated Ca2+ currents. Spontaneous depolarizing synaptic potentials and depolarizations induced by direct application of gamma-aminobutyrate were both inhibited by picrotoxin or bicuculline, demonstrating the presence of functional gamma-aminobutyrate type A synapses on these neurons. Responses to glutamate were found in LHRH neurons in older cultures. Thus, embryonic LHRH neurons not yet positioned in their postnatal environment in the forebrain contained a highly differentiated repertoire of voltage- and ligand-gated channels.

Mechanical, electrical, and magnetic properties of Ni nanocontacts

The dynamic deformation upon stretching of Ni nanowires as those formed with mechanically controllable break junctions or with a scanning tunneling microscope is studied both experimentally and theoretically. Molecular dynamics simulations of the breaking process are performed. In addition, and in order to compare with experiments, we also compute the transport properties in the last stages before failure using the first-principles implementation of Landauer's formalism included in our transport package ALACANT.

Pollutant Formation During the Thermal Decomposition of Electrical and Electronic Wastes

Paper submitted to the 7th International Symposium on Feedstock Recycling of Polymeric Materials (7th ISFR 2013), New Delhi, India, 23-26 October 2013.

The general deterrence of driving while intoxicated, volume 1, system analysis and computer-based simulation. Final report.

National Highway Traffic Safety Administration, Washington, D.C.