Superradiant Emission from Coherent Excitons in van Der Waals Heterostructures

Recent advancements in isolation and stacking of layered van der Waals materials have created an unprecedented paradigm for demonstrating varieties of 2D quantum materials. Rationally designed van der Waals heterostructures composed of monolayer transition-metal dichalcogenides (TMDs) and few-layer hBN show several unique optoelectronic features driven by correlations. However, entangled superradiant excitonic species in such systems have not been observed before. In this report, it is demonstrated that strong suppression of phonon population at low temperature results in a formation of a coherent excitonic-dipoles ensemble in the heterostructure, and the collective oscillation of those dipoles stimulates a robust phase synchronized ultra-narrow band superradiant emission even at extremely low pumping intensity. Such emitters are in high demand for a multitude of applications, including fundamental research on many-body correlations and other state-of-the-art technologies. This timely demonstration paves the way for further exploration of ultralow-threshold quantum-emitting devices with unmatched design freedom and spectral tunability.     

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.     

An expert system with temporal reasoning for alarm processing inpower system control centers

The alarm lists presented to control center operators are usually difficult to interpret. The authors present an expert system that processes the alarm lists in Portuguese control centers. This system makes an intelligent synthesis of the available information and presents it in a flexible and structured way. It uses an original approach to deal with temporal reasoning and real-time constraints. The system incorporates an explanation module that enables its use as a tutor for novice operators     

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     

MASCEM: a multiagent system that simulates competitive electricity markets

Around the world, the electricity industry, which has long been dominated by vertically integrated utilities, is experiencing major changes in the structure of its markets and regulations. Owing to new regulations, it's evolving into a distributed industry in which market forces drive electricity's price. The industry is becoming competitive; a market environment is replacing the traditional centralized-operation approach. This transformation is often called the deregulation of the electricity market. MASCEM, a multiagent simulator system, is a valuable framework for evaluating new rules, new behavior, and new participants in the numerous electricity markets that are moving toward liberalization and competition.     

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.     

Pole placement adaptive control with persistent jumps in the plant parameters

In this paper we consider the problem of adaptively stabilizing, and providing step tracking for, an uncertain linear time-varying system. We propose an adaptive pole placement controller which solves the problem for a single-input single-output plant whose parameters switch at a moderate rate among the elements of a compact set. The output feedback controller incorporates an integrator, and its action emulates the behaviour of a pole placement state feedback compensator; the controller is periodic and mildly nonlinear, is easy to implement, is noise tolerant, and tolerates a degree of unmodelled dynamics.     

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.