2,540 research outputs found
FORGE enabling FIRE facilities for the eLearning community
International audienceMany engineering students at third-level institutions across the world will not have the advantage of using real-world experimentation equipment, as the infrastructure and resources required for this activity are too expensive. This paper explains how the FORGE (Forging Online Education through FIRE) FP7 project transforms Future Internet Research and Experimentation (FIRE) testbed facilities into educational resources for the eLearning community. This is achieved by providing a framework for remote experimentation that supports easy access and control to testbed infrastructure for students and educators. Moreover, we identify a list of recommendations to support development of eLearning courses that access these facilities and highlight some of the challenges encountered by FORGE
Active galactic nuclei synapses: X-ray versus optical classifications using artificial neural networks
(Abridged) Many classes of active galactic nuclei (AGN) have been defined
entirely throughout optical wavelengths while the X-ray spectra have been very
useful to investigate their inner regions. However, optical and X-ray results
show many discrepancies that have not been fully understood yet. The aim of
this paper is to study the "synapses" between the X-ray and optical
classifications.
For the first time, the new EFLUXER task allowed us to analyse broad band
X-ray spectra of emission line nuclei (ELN) without any prior spectral fitting
using artificial neural networks (ANNs). Our sample comprises 162 XMM-Newton/pn
spectra of 90 local ELN in the Palomar sample. It includes starbursts (SB),
transition objects (T2), LINERs (L1.8 and L2), and Seyferts (S1, S1.8, and S2).
The ANNs are 90% efficient at classifying the trained classes S1, S1.8, and
SB. The S1 and S1.8 classes show a wide range of S1- and S1.8-like components.
We suggest that this is related to a large degree of obscuration at X-rays. The
S1, S1.8, S2, L1.8, L2/T2/SB-AGN (SB with indications of AGN), and SB classes
have similar average X-ray spectra within each class, but these average spectra
can be distinguished from class to class. The S2 (L1.8) class is linked to the
S1.8 (S1) class with larger SB-like component than the S1.8 (S1) class. The L2,
T2, and SB-AGN classes conform a class in the X-rays similar to the S2 class
albeit with larger fractions of SB-like component. This SB-like component is
the contribution of the star-formation in the host galaxy, which is large when
the AGN is weak. An AGN-like component seems to be present in the vast majority
of the ELN, attending to the non-negligible fraction of S1-like or S1.8-like
component. This trained ANN could be used to infer optical properties from
X-ray spectra in surveys like eRosita.Comment: 15 pages, 7 figures, accepted for publication in A&A. Appendix B only
in the full version of the paper here:
https://dl.dropboxusercontent.com/u/3484086/AGNSynapsis_OGM_online.pd
The X-ray nature of the LINER nuclear sources
The analysis of the X-ray data for a sample of 51 LINER nuclei with available
X-ray Chandra imaging is reported. Our aim was to investigate the physical
mechanisms which power LINER nuclear activity. The use of multiwavelenght
information at radio, UV, optical HST and X-ray lead us to conclude that at
least 60% of the LINERs are hosting a low luminosity AGN in their nuclei. This
percentage may be even higher if the Compton-thickness of some nuclei (mostly
with SB-like hard X-ray morphology) is confirmed.Comment: Conference proceedings to appear in "The Central Engine of Active
Galactic Nuclei", ed. L.C. Ho and J.-M. Wang (San Francisco: ASP
Glossina swynnertoni (Diptera: Glossinidae): effective population size and breeding structure estimated by mitochondrial diversity
Nucleotide diversity was examined at mitochondrial COI and r16S2 loci in eight Glossina swynnertoni Austen collections from northern Tanzania and from a culture maintained by the International Atomic Energy Agency. Eighteen composite haplotypes were observed among 149 flies, two of which were common to all samples and 10 were private. Mean haplotype diversity was 0.59 and nucleotide diversity was 0.0013. There were excess singular haplotypes and mutation-drift disequilibrium suggesting that populations had experienced an earlier bottleneck and subsequent expansion. Factorial correspondence analysis showed that haplotype frequencies varied much more temporally (GST = 0.18) than spatially (GST = 0.04). The estimate of effective population size Ne in Tarangire was a harmonic mean ~50 reproductive flies averaged over ~47 generations. The mean rate of gene flow was estimated to be ~5±1 reproducing females per generation but inflated because of mutation-drift disequilibrium arising from likely earlier bottlenecks
Design and validation of a three-instrument toolkit for the assessment of competence in electrocardiogram rhythm recognition
Background: Rapid and accurate interpretation of cardiac arrhythmias by nurses has been linked with safe practice and positive patient outcomes. Although training in electrocardiogram (ECG) rhythm recognition is part of most undergraduate nursing programmes, research continues to suggest that nurses and nursing students lack competence in recognising cardiac rhythms. In order to promote patient safety, nursing educators must develop valid and reliable assessment tools that allow the rigorous assessment of this competence before nursing students are allowed to practise without supervision.
Aim: To develop and psychometrically evaluate a toolkit to holistically assess competence in ECG rhythm recognition.
Methods: Following a convenience sampling technique, 293 nursing students from a nursing faculty in a Spanish university were recruited for the study. The following three instruments were developed and psychometrically tested: a knowledge assessment tool (ECG-KAT), a skills assessment tool (ECG-SAT) and a self-efficacy assessment tool (ECG-SES). Reliability and validity (content, criterion and construct) of these tools were meticulously examined.
Results: A high Cronbach’s alpha coefficient demonstrated the excellent reliability of the instruments (ECG-KAT=0.89; ECG-SAT=0.93; ECG-SES=0.98). An excellent context validity index (S-CVI/Ave>0.94) and very good criterion validity were evidenced for all the tools. Regarding construct validity, principal component analysis revealed that all items comprising the instruments contributed to measure knowledge, skills or self-efficacy in ECG rhythm recognition. Moreover, known-groups analysis showed the tools’ ability to detect expected differences in competence between groups with different training experiences.
Conclusion: The three-instrument toolkit developed showed excellent psychometric properties for measuring competence in ECG rhythm recognition
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