Current decomposition in asymmetrical, unbalanced three-phasesystems under nonsinusoidal conditions

The most attractive theories found in the literature for the representation of the electrical systems under nonsinusoidal conditions can be divided to a great extent into those operating in the time domain and those operating in the frequency domain. When three-phase systems are concerned, the time-domain approach is mainly due to Akagi and Nabae under the name of “instantaneous power theory” or “p-q theory” and is based on the Park transformation. The frequency-domain approach is mainly due to Czarnecki. At a first reading, these two theories seem to be quite different. This paper shows how the application of some interesting properties of the Park transformation leads to a unified approach to the harmonic and sequence components and hence allows derivation of the frequency-domain current decomposition proposed by Czarnecki in a more straightforward way. Moreover, an extension of this decomposition to the case of asymmetrical supply voltages is considered     

Discussion groups with chronic psychotics in the context of community therapy]

The paper describes the Authors clinical experience of "discussion groups" with psychotic patients. Attention is focused on the problems arising from the community therapy context, the general layout of the setting, the definition of objectives and methods, and in particular the attitude of group leaders.     

Catalyst fragmentation during propylene polymerization: Part I. The effects of grain size and structure

Fragmentation of support/catalyst particles during propylene polymerization in the gas phase is analyzed via a mathematical model including energy and mass transfer with chemical reaction processes. The rupture phenomenon is considered specifically by the model, and evaluated as it proceeds in time, Two different regions are recognized in the polymerizing particle at fragmentation time: an inner core resembling the original solid support/catalyst structure, and an external set of layers where most of the polymerization occurs. Model predictions concerning the effects of fragmentation on polymerization are discussed. The influence of different degrees of fragmentation on thermal runaways and monomer availability at active sites located inside the support/catalyst/polymer complex is shown. Monomer concentration profiles inside the growing particles are explained in terms of the combined fragmentation-polymerization interaction. Results show a strong influence of catalyst structure on critical phenomena during early polymerization stages, and suggest the possibility of controlling critical parameters via the definition of fragment structure at catalyst preparation time.     

A new approach of data clustering using a flock of agents

This paper presents a new bio-inspired algorithm (FClust) that dynamically creates and visualizes groups of data. This algorithm uses the concepts of a flock of agents that move together in a complex manner with simple local rules. Each agent represents one data. The agents move together in a 2D environment with the aim of creating homogeneous groups of data. These groups are visualized in real time, and help the domain expert to understand the underlying structure of the data set, like for example a realistic number of classes, clusters of similar data, isolated data. We also present several extensions of this algorithm, which reduce its computational cost, and make use of a 3D display. This algorithm is then tested on artificial and real-world data, and a heuristic algorithm is used to evaluate the relevance of the obtained partitioning.     

A Memristive Nanoparticle/Organic Hybrid Synapstor for Neuroinspired Computing

A large effort is devoted to the research of new computing paradigms associated with innovative nanotechnologies that should complement and/or propose alternative solutions to the classical Von Neumann/CMOS (complementary metal oxide semiconductor) association. Among various propositions, spiking neural network (SNN) seems a valid candidate. i) In terms of functions, SNN using relative spike timing for information coding are deemed to be the most effective at taking inspiration from the brain to allow fast and efficient processing of information for complex tasks in recognition or classification. ii) In terms of technology, SNN may be able to benefit the most from nanodevices because SNN architectures are intrinsically tolerant to defective devices and performance variability. Here, spike‐timing‐dependent plasticity (STDP), a basic and primordial learning function in the brain, is demonstrated with a new class of synapstor (synapse‐transistor), called nanoparticle organic memory field‐effect transistor (NOMFET). This learning function is obtained with a simple hybrid material made of the self‐assembly of gold nanoparticles and organic semiconductor thin films. Beyond mimicking biological synapses, it is also demonstrated how the shape of the applied spikes can tailor the STDP learning function. Moreover, the experiments and modeling show that this synapstor is a memristive device. Finally, these synapstors are successfully coupled with a CMOS platform emulating the pre‐ and postsynaptic neurons, and a behavioral macromodel is developed on usual device simulator.     

Prediction of the pipe buckling by using broadening factor with distributed Brillouin fiber sensors

We successfully measured longitudinal strains in two full-scale steel pipe specimens subjected to loading combinations of internal pressure, axial tensile force and bending moments undergoing local buckling under controlled laboratory conditions. Carbon-coated fibers, for the first time, and standard communication fibers were used. By using the broadening factor of the Brillouin spectrum width, we can successfully predict the location and progression sequence of buckling patterns, prior their visual detection in the laboratory. The broadening factor processing time is more efficient than multiple-peak fitting of the Brillouin spectrum method. Thus, it is capable of proving real-time deformation progression in structural health monitoring applications. High strength carbon-coated fibers are found to be superior to standard communication fibers in two respects: they provide more accurate readings and are able to measure significantly larger strains.     

Regularizing common spatial patterns to improve BCI designs: unified theory and new algorithms

One of the most popular feature extraction algorithms for brain-computer interfaces (BCI) is common spatial patterns (CSPs). Despite its known efficiency and widespread use, CSP is also known to be very sensitive to noise and prone to overfitting. To address this issue, it has been recently proposed to regularize CSP. In this paper, we present a simple and unifying theoretical framework to design such a regularized CSP (RCSP). We then present a review of existing RCSP algorithms and describe how to cast them in this framework. We also propose four new RCSP algorithms. Finally, we compare the performances of 11 different RCSP (including the four new ones and the original CSP), on electroencephalography data from 17 subjects, from BCI competition datasets. Results showed that the best RCSP methods can outperform CSP by nearly 10% in median classification accuracy and lead to more neurophysiologically relevant spatial filters. They also enable us to perform efficient subject-to-subject transfer. Overall, the best RCSP algorithms were CSP with Tikhonov regularization and weighted Tikhonov regularization, both proposed in this paper.     

Interaction of specialized cardiac conduction system with antiarrhythmic drugs: a simulation study

The use of antiarrhythmic drugs is common to treat heart rhythm disorders. Computational modeling and simulation are promising tools that could be used to investigate the effects of specific drugs on cardiac electrophysiology. In this paper, we study the multiscale effects of dofetilide, a drug that blocks IKr, from cellular to organ level paying special attention to its effect on heart structures, in particular the specialized cardiac conduction system (CCS). We include a model of the CCS in a patient-specific anatomical ventricular model and study the drug effects in simulations with and without a CCS. Results confirmed the expected effects of dofetilide at cellular level, increasing the action potential duration, and at organ level, prolonging the QT segment. Notable differences are shown between models with and without the CCS on action potential duration distributions. These techniques show the importance of heart heterogeneity and the global effects of the interaction of drugs with cardiac structures.     

Sputtered metal lift-off for grating fabrication on InP based optical devices

Sputtered metal gratings have been realized using lift-off process based on bilayer resist electron beam lithography (EBL). The lithography mask is composed of PMMA (poly(methylméthacrylate)) layer deposited under HSQ (hydrogen silsesquioxane) inorganic resist. EBL is performed in HSQ, whereas PMMA is used to ease final lift-off. We demonstrate the possibility of patterning by lift-off metals with different sputtering yields and deposition conditions. Gratings with period of 200 nm and filling factor of 50% are obtained.