Online detection of interturn short-circuit fault in induction motor based on 5th harmonic current tracking using Vold-Kalman filter

In this paper we propose a strategy for real-time detection of interturn short-circuit faults (ISCF) on three-phase induction motor (IM) by using a Vold-Kalman filter (VKF) algorithm. ISCF produce a thermal stress into the stator winding due to large current that flows through the short-circuited turns. Therefore, incipient fault detection is required in order to avoid catastrophic failures such as phase to phase, or phase to ground faults. The strategy is based on an analytical IM model that includes a ISCF fault in any of the phase windings and considering the h-th harmonic in the voltage supply. Based on equivalent electrical circuits with harmonics in sequence components, we propose a strategy for detection of an ISCF on IM by tracking the 5th harmonic current component using a VKF algorithm. The proposed model is experimentally validated using a three-phase IM with modified stator windings to generate ISCF. Also, the IM is feeded by a programmable voltage source to synthesize distorted voltage supply with the 5th harmonic. The results demonstrated that the positive-sequence magnitude for the 5th harmonic current component is a good indicator of the fault severity once it exceeds a threshold limit value, even under load variations and unbalanced voltages

The role of body wall muscles in C. elegans locomotion

Over the past four decades, one of the simplest nervous systems across the animal kingdom, that of the nematode worm C. elegans, has drawn increasing attention. This system is the subject of an intensive concerted effort to understand the behaviour of an entire living animal, from the bottom up and the top down. C. elegans locomotion, in particular, has been the subject of a number of models, but there is as yet no general agreement about the key (rhythm generating) elements. In this paper we investigate the role of one component of the locomotion subsystem, namely the body wall muscles, with a focus on the role of inter-muscular gap junctions. We construct a detailed electrophysiological model which suggests that these muscles function, to a first approximation, as mere actuators and have no obvious rhythm generating role. Furthermore, we show that within our model inter-muscular coupling is too weak to have a significant electrical effect. These results rule out muscles as key generators of locomotion, pointing instead to neural activity patterns. More specifically, the results imply that the reduced locomotion velocity observed in unc-9 mutants is likely to be due to reduced neuronal rather than inter-muscular coupling

Working Paper 06-03 - MODTRIM II : A quarterly model for the Belgian economy

Since 1994 the Federal Planning Bureau has been using the annual version of the econometric model modtrim as a central tool to produce its short-term macroeconomic forecasts. At the origin of the project, and as its name indicates, this annual version was meant to be short-lived and quickly replaced by a quarterly version. Unfortunately, the lack of quarterly national accounts prevented from doing so for several years. In 1998, the Institute for National Accounts published official quarterly accounts for the first time and the construction of the quarterly version of the model started in Spring 2000. On that occasion, the opportunity was taken to reassess all behavioural equations of the model. The more limited availability of quarterly data, in comparison with annual data, implied that a more aggregated version of the accounting framework of the yearly model had to be constructed.

Determining the origin of synchronous multifocal bladder cancer by exome sequencing

Background: Synchronous multifocal tumours are commonly observed in urothelial carcinomas of the bladder. The origin of these physically independent tumours has been proposed to occur by either intraluminal migration (clonal) or spontaneous transformation of multiple cells by carcinogens (field effect). It is unclear which model is correct, with several studies supporting both hypotheses. A potential cause of this uncertainty may be the small number of genetic mutations previously used to quantify the relationship between these tumours. Methods: To better understand the genetic lineage of these tumours we conducted exome sequencing of synchronous multifocal pTa urothelial bladder cancers at a high depth, using multiple samples from three patients. Results: Phylogenetic analysis of high confidence single nucleotide variants (SNV) demonstrated that the sequenced multifocal bladder cancers arose from a clonal origin in all three patients (bootstrap value 100 %). Interestingly, in two patients the most common type of tumour-associated SNVs were cytosine mutations of TpC*dinucleotides (Fisher's exact test p < 10-41), likely caused by APOBEC-mediated deamination. Incorporating these results into our clonal model, we found that TpC*type mutations occurred 2-5× more often among SNVs on the ancestral branches than in the more recent private branches (p < 10-4) suggesting that TpC*mutations largely occurred early in the development of the tumour. Conclusions: These results demonstrate that synchronous multifocal bladder cancers frequently arise from a clonal origin. Our data also suggests that APOBEC-mediated mutations occur early in the development of the tumour and may be a driver of tumourigenesis in non-muscle invasive urothelial bladder cancer. © 2015 Acar et al

Functional renormalization group approach to correlated fermion systems

Numerous correlated electron systems exhibit a strongly scale-dependent behavior. Upon lowering the energy scale, collective phenomena, bound states, and new effective degrees of freedom emerge. Typical examples include (i) competing magnetic, charge, and pairing instabilities in two-dimensional electron systems, (ii) the interplay of electronic excitations and order parameter fluctuations near thermal and quantum phase transitions in metals, (iii) correlation effects such as Luttinger liquid behavior and the Kondo effect showing up in linear and non-equilibrium transport through quantum wires and quantum dots. The functional renormalization group is a flexible and unbiased tool for dealing with such scale-dependent behavior. Its starting point is an exact functional flow equation, which yields the gradual evolution from a microscopic model action to the final effective action as a function of a continuously decreasing energy scale. Expanding in powers of the fields one obtains an exact hierarchy of flow equations for vertex functions. Truncations of this hierarchy have led to powerful new approximation schemes. This review is a comprehensive introduction to the functional renormalization group method for interacting Fermi systems. We present a self-contained derivation of the exact flow equations and describe frequently used truncation schemes. Reviewing selected applications we then show how approximations based on the functional renormalization group can be fruitfully used to improve our understanding of correlated fermion systems.Comment: Review article, final version, 59 pages, 28 figure

Eighth International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI at ECAI 2020)

International audienceProceedings of the 8th International Workshop "What can FCA do for Artificial Intelligence?" (FCA4AI 2020)co-located with 24th European Conference on Artificial Intelligence (ECAI 2020), Santiago de Compostela, Spain, August 29, 202

Workshop Notes of the Seventh International Workshop "What can FCA do for Artificial Intelligence?"

International audienceThese are the proceedings of the seventh edition of the FCA4AI workshop (http://www.fca4ai.hse.ru/) co-located with the IJCAI 2019 Conference in Macao (China). Formal Concept Analysis (FCA) is a mathematically well-founded theory aimed at classification and knowledge discovery that can be used for many purposes in Artificial Intelligence (AI). The objective of the FCA4AI workshop is to investigate two main issues: how can FCA supports various AI activities (knowledge discovery, knowledge engineering, machine learning, data mining, information retrieval, recommendation. . . ), and how can FCA be extended in order to help AI researchers to solve new and complex problems in their domain