A multiwinding modeling method for high frequency transformers and inductors

This paper presents a method to obtain an electric model for transformers and inductors, including both frequency and geometry effects in the windings, which can be linked with existing core models. One-dimensional distributions for magnetic and electric fields are assumed, and from Maxwell's equations an equivalent electric circuit is easily obtained. This equivalent circuit has been included in analog simulators (Spice, AnalogWorkBench, Saber ...), and comparisons between measured and simulated results are shown, both in time domain and in AC sweep, which verify the model accuracy. The model described in this paper allows designers to deal with key issues in the design of high-frequency magnetic components (copper losses, leakage inductance, skin and proximity effects) by using analog simulators, which are usually more familiar to them than finite-element analysis tools.     

Nephelometric study of salivary protein–tannin aggregates

Grape seed procyanidins were fractionated through different degrees of polymerisation, and human saliva was purified and separated into two fractions: one was mostly α‐amylase and the other was essentially proline‐rich proteins (PRPs). The interaction of these proteins with the procyanidin compounds was assayed using nephelometry, and the influence of several factors was investigated, such as degree of polymerisation, pH and concentrations of both protein and tannin. The same experiments were performed with bovine serum albumin (BSA). The amount of insoluble aggregates, resulting from the formation of polyphenol–protein aggregates, increased quickly up to a maximum value which thereafter remained practically unchanged. pH was set at 5.0 for all further assays, since it was the nearest value to that encountered in human saliva (pH 5.6–7.9), where proteins were stable and had a maximum ability to bind and precipitate procyanidin oligomers. These proteins were shown to have a strong affinity for procyanidin oligomers and were unable to resolubilise the polyphenol–protein aggregates when present in excess. PRPs required a much lower content to bind all the tannins (400 µg of procyanidin oligomers) than BSA and especially α‐amylase (48, 60 and 132 µg respectively). The procyanidin's ability to bind PRPs, BSA and α‐amylase increased with its average molecular weight. This ability increased regularly for PRPs up to 4500 Da, whereas the ability to bind the globular proteins decreased beyond 3400 Da. © 2001 Society of Chemical Industry     

Fabry Disease and the Heart: A Comprehensive Review

Fabry disease (FD) is an X-linked lysosomal storage disorder caused by mutations of the GLA gene that result in a deficiency of the enzymatic activity of α-galactosidase A and consequent accumulation of glycosphingolipids in body fluids and lysosomes of the cells throughout the body. GB3 accumulation occurs in virtually all cardiac cells (cardiomyocytes, conduction system cells, fibroblasts, and endothelial and smooth muscle vascular cells), ultimately leading to ventricular hypertrophy and fibrosis, heart failure, valve disease, angina, dysrhythmias, cardiac conduction abnormalities, and sudden death. Despite available therapies and supportive treatment, cardiac involvement carries a major prognostic impact, representing the main cause of death in FD. In the last years, knowledge has substantially evolved on the pathophysiological mechanisms leading to cardiac damage, the natural history of cardiac manifestations, the late-onset phenotypes with predominant cardiac involvement, the early markers of cardiac damage, the role of multimodality cardiac imaging on the diagnosis, management and follow-up of Fabry patients, and the cardiac efficacy of available therapies. Herein, we provide a comprehensive and integrated review on the cardiac involvement of FD, at the pathophysiological, anatomopathological, laboratory, imaging, and clinical levels, as well as on the diagnosis and management of cardiac manifestations, their supportive treatment, and the cardiac efficacy of specific therapies, such as enzyme replacement therapy and migalastat.     

Well-defined polymer precursors synthesized by RAFT polymerization of N,N-dimethylacrylamide/N-acryloxysuccinimide: random and block copolymers

N,N-dimethylacrylamide (DMA) and N-acryloxysuccinimide (NAS) were copolymerized by the reversible addition–fragmentation chain transfer (RAFT) polymerization technique, to obtain random and block copolymer precursors onto which different side-groups may be statistically grafted via the reactive NAS units. These reactive copolymers have interesting applications in various fields such as coatings and paints, water purification and biology. Random poly(DMA-co-NAS) copolymer chains were synthesized with a 75/25 molar ratio, high conversion, an excellent molecular weight (MW) control from 5000 to 130 000 g mol⁻¹, and low polydispersity index (M_w/M_n<1.1). Poly(DMA-b-NAS) block copolymers were synthesized by a two step method, in which a poly(DMA) homopolymer was prepared first and then used as macro-chain transfer agent to polymerize NAS. For example, a poly(DMA-b-NAS) sample was obtained with an average molecular weight of 44 300/7400 g mol⁻¹ corresponding to 447 DMA and 44 NAS units. Such block copolymers had not yet been synthesized by any controlled polymerization technique. They can be used to prepare polymers with exactly the same backbone and an increasing number of different side groups (e.g. hydrophobic, ionic or fluorescent).     

A linear algebra approach to OLAP

Inspired by the relational algebra of data processing, this paper addresses the foundations of data analytical processing from a linear algebra perspective. The paper investigates, in particular, how aggregation operations such as cross tabulations and data cubes essential to quantitative analysis of data can be expressed solely in terms of matrix multiplication, transposition and the Khatri–Rao variant of the Kronecker product. The approach offers a basis for deriving an algebraic theory of data consolidation, handling the quantitative as well as qualitative sides of data science in a natural, elegant and typed way. It also shows potential for parallel analytical processing, as the parallelization theory of such matrix operations is well acknowledged.     

A Closed-Loop Automatic Data-Mining Approach for Preventive Network Monitoring

As telecommunication networks grow in size and complexity, monitoring systems need to scale up accordingly. Alarm data generated in a large network are often highly correlated. These correlations can be explored to simplify the process of network fault management, by reducing the number of alarms presented to the network-monitoring operator. This makes it easier to react to network failures. But in some scenarios, it is highly desired to prevent the occurrence of these failures by predicting the occurrence of alarms before hand. This work investigates the usage of data mining methods to generate knowledge from historical alarm data, and using such knowledge to train a machine learning system, in order to predict the occurrence of the most relevant alarms in the network. The learning system was designed to be retrained periodically in order to keep an updated knowledge base.     

Giant Anomalous Hall and Nernst Conductivities in Magnetic All-d Metal Heusler Alloys

All-d Heuslers are a category of novel compounds combining versatile functionalities such as caloric responses and spintronics with enhanced mechanical properties. Despite the promising transport properties (anomalous Hall (AHC) and anomalous Nernst (ANC) conductivities) shown in the conventional Co₂XY Heuslers with p-d hybridization, the all-d Heuslers with only d-d hybridization open a new horizon to search for new candidates with outstanding transport properties. In this work, the AHC and ANC are evaluated for thermodynamically stable ferro/ferri-magnetic all-d-metal regular Heusler compounds based on high-throughput first-principles calculations. It is observed that quite a few materials exhibit giant AHCs and ANCs, such as cubic Re₂TaMn with an AHC of 2011 S cm^-1, and tetragonal Pt₂CrRh with an AHC of 1966 S cm^-1 and an ANC of 7.50 A m^-1K^-1. Comprehensive analysis on the electronic structure reveals that the high AHC can be attributed to the occurrence of the Weyl nodes or gapped nodal lines in the neighborhood of the Fermi level. The correlations between such transport properties and the number of valence electrons are also thoroughly investigated, which provides a practical guidance to tailor AHC and ANC via chemical doping for transverse thermoelectric applications.     

Slicing for architectural analysis

Current software development often relies on non-trivial coordination logic for combining autonomous services, eventually running on different platforms. As a rule, however, such a coordination layer is strongly woven within the application at source code level. Therefore, its precise identification becomes a major methodological (and technical) problem and a challenge to any program understanding or refactoring process.The approach introduced in this paper resorts to slicing techniques to extract coordination data from source code. Such data are captured in a specific dependency graph structure from which a coordination model can be recovered either in the form of an Orc specification or as a collection of code fragments corresponding to the identification of typical coordination patterns in the system. Tool support is also discussed.