Six-converter solar thermionic generator Final report, 10 Jan. 1967 - 31 Mar. 1968

Six converter solar thermionic generato

Simultaneous multi-frequency single-pulse properties of AXP XTE J1810-197

We have used the 76-m Lovell, 94-m equivalent WSRT and 100-m Effelsberg radio telescopes to investigate the simultaneous single-pulse properties of the radio emitting magnetar AXP XTE J1810-197 at frequencies of 1.4, 4.8 and 8.35 GHz during May and July 2006. We study the magnetar's pulse-energy distributions which are found to be very peculiar as they are changing on time-scales of days and cannot be fit by a single statistical model. The magnetar exhibits strong spiky single giant-pulse-like subpulses, but they do not fit the definition of the giant pulse or giant micropulse phenomena. Measurements of the longitude-resolved modulation index reveal a high degree of intensity fluctuations on day-to-day time-scales and dramatic changes across pulse phase. We find the frequency evolution of the modulation index values differs significantly from what is observed in normal radio pulsars. We find that no regular drifting subpulse phenomenon is present at any of the observed frequencies at any observing epoch. However, we find a quasi-periodicity of the subpulses present in the majority of the observing sessions. A correlation analysis indicates a relationship between components from different frequencies. We discuss the results of our analysis in light of the emission properties of normal radio pulsars and a recently proposed model which takes radio emission from magnetars into consideration.Comment: 15 pages, 11 figures, accepted for publication by MNRA

Placing limits on the stochastic gravitational-wave background using European Pulsar Timing Array data

Direct detection of low-frequency gravitational waves ($10^{-9} - 10^{-8}$ Hz) is the main goal of pulsar timing array (PTA) projects. One of the main targets for the PTAs is to measure the stochastic background of gravitational waves (GWB) whose characteristic strain is expected to approximately follow a power-law of the form $h_c(f)=A (f/\hbox{yr}^{-1})^{\alpha}$, where $f$ is the gravitational-wave frequency. In this paper we use the current data from the European PTA to determine an upper limit on the GWB amplitude $A$ as a function of the unknown spectral slope $\alpha$ with a Bayesian algorithm, by modelling the GWB as a random Gaussian process. For the case $\alpha=-2/3$, which is expected if the GWB is produced by supermassive black-hole binaries, we obtain a 95% confidence upper limit on $A$ of $6\times 10^{-15}$, which is 1.8 times lower than the 95% confidence GWB limit obtained by the Parkes PTA in 2006. Our approach to the data analysis incorporates the multi-telescope nature of the European PTA and thus can serve as a useful template for future intercontinental PTA collaborations.Comment: 14 pages, 8 figures, 3 tables, mnras accepte

Publication and patent analysis of European researchers in the field of production technology and manufacturing systems

This paper develops a structured comparison among a sample of European researchers in the field of Production Technology and Manufacturing Systems, on the basis of scientific publications and patents. Researchers are evaluated and compared by a variegated set of indicators concerning (1) the output of individual researchers and (2) that of groups of researchers from the same country. While not claiming to be exhaustive, the results of this preliminary study provide a rough indication of the publishing and patenting activity of researchers in the field of interest, identifying (dis)similarities between different countries. Of particular interest is a proposal for aggregating analysis results by means of maps based on publication and patent indicators. A large amount of empirical data are presented and discusse

Mesoscale modeling of combined aerosol and photo-oxidant processes in the Eastern Mediterranean

International audienceParticulate matter and photo-oxidant processes in the Eastern Mediterranean have been studied using the UAM-AERO mesoscale air quality model in conjunction with the NILU-CTM regional model. Meteorological data were obtained from the RAMS prognostic meteorological model. The modeling domain includes the eastern Mediterranean area between the Greek mainland and the island of Crete. The modeling system is applied to study the atmospheric processes in three periods, i.e. 13?16 July 2000, 26?30 July 2000 and 7?14 January 2001. The spatial and temporal distributions of both gaseous and particulate matter pollutants have been extensively studied together with the identification of major emission sources in the area. The modeling results were compared with field data obtained in the same period. The objective of the current modeling work was mainly to apply the UAM-AERO mesoscale model in the eastern Mediterranean in order to assess the performed field campaigns and determine that the applied mesoscale model is fit for this purpose. Comparison of the modeling results with measured data was performed for a number of gaseous and aerosol species. The UAM-AERO model underestimates the PM10 measured concentrations during summer and winter campaigns. Discrepancies between modeled and measured data are attributed to unresolved particulate matter emissions. Particulate matter in the area is mainly composed by sulphate, sea salt and crustal materials, and with significant amounts of nitrate, ammonium and organics. During winter the particulate matter and oxidant concentrations were lower than the summer values

An ultrawideband patch antenna for UHF detection of partial discharge.

The location of partial discharge (PD) sources by free-space UHF detection is an attractive approach for condition monitoring of high voltage equipment in substations. A low-cost, radiometric, PD wireless sensor network (WSN) has been proposed to provide continuous real-time coverage for an entire substation. A suggested band for UHF PD detection is 0.3 – 1.5 GHz. A novel ultrawideband (UWB) printed monopole antenna is presented here for PD WSN applications

Data-Driven Audio Feature Space Clustering for Automatic Sound Recognition in Radio Broadcast News

This is an Open Access article published by World Scientific Publishing Company. It is distributed under the terms of the Creative Commons Attribution 4.0 (CC-BY) License. Further distribution of this work is permitted, provided the original work is properly cited. T. Theodorou, I. Mpoas, A. Lazaridis, N. Fakotakis, 'Data-Driven Audio Feature Space Clustering for Automatic Sound Recognition in Radio Broadcast News', International Journal on Artificial Intelligence Tools, Vol. 26 (2), April 2017, 1750005 (13 pages), DOI: 10.1142/S021821301750005. © The Author(s).In this paper we describe an automatic sound recognition scheme for radio broadcast news based on principal component clustering with respect to the discrimination ability of the principal components. Specifically, streams of broadcast news transmissions, labeled based on the audio event, are decomposed using a large set of audio descriptors and project into the principal component space. A data-driven algorithm clusters the relevance of the components. The component subspaces are used by sound type classifier. This methodology showed that the k-nearest neighbor and the artificial intelligent network provide good results. Also, this methodology showed that discarding unnecessary dimension works in favor on the outcome, as it hardly deteriorates the effectiveness of the algorithms.Peer reviewe

Iron Age and Anglo-Saxon genomes from East England reveal British migration history

British population history has been shaped by a series of immigrations, including the early Anglo-Saxon migrations after 400 CE. It remains an open question how these events affected the genetic composition of the current British population. Here, we present whole-genome sequences from 10 individuals excavated close to Cambridge in the East of England, ranging from the late Iron Age to the middle Anglo-Saxon period. By analysing shared rare variants with hundreds of modern samples from Britain and Europe, we estimate that on average the contemporary East English population derives 38% of its ancestry from Anglo-Saxon migrations. We gain further insight with a new method, rarecoal, which infers population history and identifies fine-scale genetic ancestry from rare variants. Using rarecoal we find that the Anglo-Saxon samples are closely related to modern Dutch and Danish populations, while the Iron Age samples share ancestors with multiple Northern European populations including Britain