Identification of multitype branching processes

We solve the problem of constructing an asymptotic global confidence region for the means and the covariance matrices of the reproduction distributions involved in a supercritical multitype branching process. Our approach is based on a central limit theorem associated with a quadratic law of large numbers performed by the maximum likelihood or the multidimensional Lotka--Nagaev estimator of the reproduction law means. The extension of this approach to the least squares estimator of the mean matrix is also briefly discussed. On r\'{e}sout le probl\`{e}me de construction d'une r\'{e}gion de confiance asymptotique et globale pour les moyennes et les matrices de covariance des lois de reproduction d'un processus de branchement multitype et supercritique. Notre approche est bas\'{e}e sur un th\'{e}or\`{e}me de limite centrale associ\'{e} \`{a} une loi forte quadratique v\'{e}rifi\'{e}e par l'estimateur du maximum de vraisemblance ou l'estimateur multidimensionnel de Lotka--Nagaev des moyennes des lois de reproduction. L'extension de cette approche \`{a} l'estimateur des moindres carr\'{e}s de la matrice des moyennes est aussi bri\`{e}vement comment\'{e}e.Comment: Published at http://dx.doi.org/10.1214/009053605000000561 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org

Antifungal activity of methanolic extracts of four Algerian marine algae species

Since ancient times antimicrobial properties of seaweeds have been recognized. In this study, antifungal activity of four species of marine algae of Bejaia coast (Algeria) was explored. This activity was evaluated by agar diffusion method. The minimum inhibitory concentrations were also determined for all the strains. All the extracts used in this study exhibited antifungal activity. The highest inhibiting effect was noted for Rhodomela confervoides (red algae) and Padina pavonica (brown algae), respectively against Candida albicans (diameter of inhibition zone: 24 mm) and Mucor ramaniannus (diameter of inhibition zone: 26 mm) for the first one and Candida albicans (diameter of inhibition zone: 26 mm) for the second one. Aspergillus niger showed resistance against majority of methanolic extracts. The evaluation of minimum inhibitory concentrations showed that extracts of Padina pavonica, Rhodomela confervoides and Ulva lactuca were very efficient against Mucor ramaniannus and Candida albicans. These results suggest that seaweeds collected from Algerian coast present a significant capacity which makes them interesting for screening for natural products.Key words: Marine algae, antifungal activity, methanolic extracts, natural substances

Panton-Valentine leukocidin positive sequence type 80 methicillin-resistant Staphylococcus aureus carrying a staphylococcal cassette chromosome mec type IVc is dominant in neonates and children in an Algiers hospital

Methicillin-resistant Staphylococcus aureus (MRSA) is a major antimicrobial drug-resistant pathogen causing serious infections. It was first detected in healthcare settings, but in recent years it has also become disseminated in the community. Children and young adults are most susceptible to infection by community-acquired (CA) MRSA strains. In this study 25 MRSA isolates implicated in infections of neonates and children admitted to an Algiers hospital during an 18 month period were characterized by molecular methods including staphylococcal cassette chromosome (SCC) mec typing, PCR amplification of pvl genes, pulsed field gel electrophoresis (PFGE) and multilocus sequence typing (MLST). Fifteen out of 25 isolates were from hospital-acquired infections. Twenty-four isolates carried SCCmec type IVc and belonged to the sequence type (ST) 80, one isolate carried SCCmec type II and was ST 39. Twenty-two out of 24 ST80-MRSA-IVc isolates carried pvl genes. Our results suggest that the Panton-Valentine leukocidin positive ST80- MRSA-IVc is the dominant MRSA clone causing disease in neonates and children in Algiers

Phosphoproteome dynamics during mitotic exit in budding yeast

The cell division cycle culminates in mitosis when two daughter cells are born. As cyclin‐dependent kinase (Cdk) activity reaches its peak, the anaphase‐promoting complex/cyclosome (APC/C) is activated to trigger sister chromatid separation and mitotic spindle elongation, followed by spindle disassembly and cytokinesis. Degradation of mitotic cyclins and activation of Cdk‐counteracting phosphatases are thought to cause protein dephosphorylation to control these sequential events. Here, we use budding yeast to analyze phosphorylation dynamics of 3,456 phosphosites on 1,101 proteins with high temporal resolution as cells progress synchronously through mitosis. This reveals that successive inactivation of S and M phase Cdks and of the mitotic kinase Polo contributes to order these dephosphorylation events. Unexpectedly, we detect as many new phosphorylation events as there are dephosphorylation events. These correlate with late mitotic kinase activation and identify numerous candidate targets of these kinases. These findings revise our view of mitotic exit and portray it as a dynamic process in which a range of mitotic kinases contribute to order both protein dephosphorylation and phosphorylation

High-Performance BiCMOS Transimpedance Amplifiers for Fiber-Optic Receivers

High gain, wide bandwidth, low noise, and low-power transimpedance amplifiers based on new BiCMOS common- base topologies have been designed for fiber-optic receivers. In particular a design approach, hereafter called "A more- FET approach", added a new dimension to effectively optimize performance tradeoffs inherent in such circuits. Using conventional silicon 0.8 μm process parameters, simulated performance features of a total-FET transimpedance amplifier operating at 7.2 GHz, which is close to the technology fT of 12 GHz, are presented. The results are superior to those of similar recent designs and comparable to IC designs using GaAs technology. A detailed analysis of the design architecture, including a discussion on the effects of moving toward more FET-based designs is presented

A modular IoT platform for real-time indoor air quality monitoring

The impact of air quality on health and on life comfort is well established. In many societies, vulnerable elderly and young populations spend most of their time indoors. Therefore, indoor air quality monitoring (IAQM) is of great importance to human health. Engineers and researchers are increasingly focusing their efforts on the design of real-time IAQM systems using wireless sensor networks. This paper presents an end-to-end IAQM system enabling measurement of CO2, CO, SO2, NO2, O3, Cl2, ambient temperature, and relative humidity. In IAQM systems, remote users usually use a local gateway to connect wireless sensor nodes in a given monitoring site to the external world for ubiquitous access of data. In this work, the role of the gateway in processing collected air quality data and its reliable dissemination to end-users through a web-server is emphasized. A mechanism for the backup and the restoration of the collected data in the case of Internet outage is presented. The system is adapted to an open-source Internet-of-Things (IoT) web-server platform, called Emoncms, for live monitoring and long-term storage of the collected IAQM data. A modular IAQM architecture is adopted, which results in a smart scalable system that allows seamless integration of various sensing technologies, wireless sensor networks (WSNs) and smart mobile standards. The paper gives full hardware and software details of the proposed solution. Sample IAQM results collected in various locations are also presented to demonstrate the abilities of the system. 2018 by the authors. Licensee MDPI, Basel, Switzerland.Acknowledgments: This publication was made possible by the National Priority Research Program (NPRP) award (NPRP6-600-2-250) from the Qatar National Research Fund (QNRF), a member of the Qatar Foundation. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of QNRF.Scopu

Class-E Amplifier Design Improvements for GSM Frequencies

Efficient power amplifiers are essential in portable battery-operated systems such as mobile phones. Also, the power amplifier (PA) is the most power-consuming building block in the transmitter of a portable system. This paper investigates how the efficiency of the power amplifier (which is beneficial for multiple applications in communcation sector) can be improved by increasing the efficiency of switching mode class E power amplifiers for frequencies of 900 MHz and 1800 MHz. The paper tackles modeling, design improvements and verification through simulation for higher efficiencies. This is the continuation of previous work by the authors. These nonlinear power amplifiers can only amplify constant-envelope RF signals without introducing significant distortion. Mobile systems such as Advanced Mobile Phone System (AMPS) and Global System for Mobile communications (GSM) use modulation schemes which generate constant amplitude RF outputs in order to use efficient but nonlinear power amplifiers. Improvements in designs are suggested and higher efficiencies are achieved, to the tune of 67.1% (for 900 MHz) and 67.0% (1800 MHz)

A real-time early warning seismic event detection algorithm using smart geo-spatial bi-axial inclinometer nodes for Industry 4.0 applications

Earthquakes are one of the major natural calamities as well as a prime subject of interest for seismologists, state agencies, and ground motion instrumentation scientists. The real-time data analysis of multi-sensor instrumentation is a valuable knowledge repository for real-time early warning and trustworthy seismic events detection. In this work, an early warning in the first 1 micro-second and seismic wave detection in the first 1.7 milliseconds after event initialization is proposed using a seismic wave event detection algorithm (SWEDA). The SWEDA with nine low-computation-cost operations is being proposed for smart geospatial bi-axial inclinometer nodes (SGBINs) also utilized in structural health monitoring systems. SWEDA detects four types of seismic waves, i.e., primary (P) or compression, secondary (S) or shear, Love (L), and Rayleigh (R) waves using time and frequency domain parameters mapped on a 2D mapping interpretation scheme. The SWEDA proved automated heterogeneous surface adaptability, multi-clustered sensing, ubiquitous monitoring with dynamic Savitzky-Golay filtering and detection using nine optimized sequential and structured event characterization techniques. Furthermore, situation-conscious (context-aware) and automated computation of short-time average over long-time average (STA/LTA) triggering parameters by peak-detection and run-time scaling arrays with manual computation support were achieved. - 2019 by the authors.Funding: This publication was made possible by the NPRP grant # 8-1781-2-725 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.Scopu

New fast arctangent approximation algorithm for generic real-time embedded applications

Fast and accurate arctangent approximations are used in several contemporary applications, including embedded systems, signal processing, radar, and power systems. Three main approximation techniques are well-established in the literature, varying in their accuracy and resource utilization levels. Those are the iterative coordinate rotational digital computer (CORDIC), the lookup tables (LUTs)-based, and the rational formulae techniques. This paper presents a novel technique that combines the advantages of both rational formulae and LUT approximation methods. The new algorithm exploits the pseudo-linear region around the tangent function zero point to estimate a reduced input arctangent through a modified rational approximation before referring this estimate to its original value using miniature LUTs. A new 2nd order rational approximation formula is introduced for the first time in this work and benchmarked against existing alternatives as it improves the new algorithm performance. The eZDSP-F28335 platform has been used for practical implementation and results validation of the proposed technique. The contributions of this work are summarized as follows: (1) introducing a new approximation algorithm with high precision and application-based flexibility; (2) introducing a new rational approximation formula that outperforms literature alternatives with the algorithm at higher accuracy requirement; and (3) presenting a practical evaluation index for rational approximations in the literature. - 2019 by the authors. Licensee MDPI, Basel, Switzerland.Funding: The publication of this article was funded by the Qatar National Library.Scopu

A real-time early warning seismic event detection algorithm using smart geo-spatial bi-axial inclinometer nodes for Industry 4.0 applications

Earthquakes are one of the major natural calamities as well as a prime subject of interest for seismologists, state agencies, and ground motion instrumentation scientists. The real-time data analysis of multi-sensor instrumentation is a valuable knowledge repository for real-time early warning and trustworthy seismic events detection. In this work, an early warning in the first 1 micro-second and seismic wave detection in the first 1.7 milliseconds after event initialization is proposed using a seismic wave event detection algorithm (SWEDA). The SWEDA with nine low-computation-cost operations is being proposed for smart geospatial bi-axial inclinometer nodes (SGBINs) also utilized in structural health monitoring systems. SWEDA detects four types of seismic waves, i.e., primary (P) or compression, secondary (S) or shear, Love (L), and Rayleigh (R) waves using time and frequency domain parameters mapped on a 2D mapping interpretation scheme. The SWEDA proved automated heterogeneous surface adaptability, multi-clustered sensing, ubiquitous monitoring with dynamic Savitzky-Golay filtering and detection using nine optimized sequential and structured event characterization techniques. Furthermore, situation-conscious (context-aware) and automated computation of short-time average over long-time average (STA/LTA) triggering parameters by peak-detection and run-time scaling arrays with manual computation support were achieved. - 2019 by the authors.Funding: This publication was made possible by the NPRP grant # 8-1781-2-725 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.Scopu