An artificial neural network predictor for tropospheric surface duct phenomena

International audienceIn this work, an artificial neural network (ANN) model is developed and used to predict the presence of ducting phenomena for a specific time, taking into account ground values of atmospheric pressure, relative humidity and temperature. A feed forward backpropagation ANN is implemented, which is trained, validated and tested using atmospheric radiosonde data from the Helliniko airport, for the period from 1991 to 2004. The network's quality and generality is assessed using the Area Under the Receiver Operating Characteristics (ROC) Curves (AUC), which resulted to a mean value of about 0.86 to 0.90, depending on the observation time. In order to validate the ANN results and to evaluate any further improvement options of the proposed method, the problem was additionally treated using Least Squares Support Vector Machine (LS-SVM) classifiers, trained and tested with identical data sets for direct performance comparison with the ANN. Furthermore, time series prediction and the effect of surface wind to the presence of tropospheric ducts appearance are discussed. The results show that the ANN model presented here performs efficiently and gives successful tropospheric ducts predictions

NELIOTA: The wide-field, high-cadence lunar monitoring system at the prime focus of the Kryoneri telescope

We present the technical specifications and first results of the ESA-funded, lunar monitoring project "NELIOTA" (NEO Lunar Impacts and Optical TrAnsients) at the National Observatory of Athens, which aims to determine the size-frequency distribution of small Near-Earth Objects (NEOs) via detection of impact flashes on the surface of the Moon. For the purposes of this project a twin camera instrument was specially designed and installed at the 1.2 m Kryoneri telescope utilizing the fast-frame capabilities of scientific Complementary Metal-Oxide Semiconductor detectors (sCMOS). The system provides a wide field-of-view (17.0' $\times$ 14.4') and simultaneous observations in two photometric bands (R and I), reaching limiting magnitudes of 18.7 mag in 10 sec in both bands at a 2.5 signal-to-noise level. This makes it a unique instrument that can be used for the detection of NEO impacts on the Moon, as well as for any astronomy projects that demand high-cadence multicolor observations. The wide field-of-view ensures that a large portion of the Moon is observed, while the simultaneous, high-cadence, monitoring in two photometric bands makes possible, for the first time, the determination of the temperatures of the impacts on the Moon's surface and the validation of the impact flashes from a single site. Considering the varying background level on the Moon's surface we demonstrate that the NELIOTA system can detect NEO impact flashes at a 2.5 signal-to-noise level of ~12.4 mag in the I-band and R-band for observations made at low lunar phases ~0.1. We report 31 NEO impact flashes detected during the first year of the NELIOTA campaign. The faintest flash was at 11.24 mag in the R-band (about two magnitudes fainter than ever observed before) at lunar phase 0.32. Our observations suggest a detection rate of $1.96 \times 10^{-7}$ events $km^{-2} h^{-1}$.Comment: Accepted for publication in A&

TooManyEyes: Super-recogniser directed identification of target individuals on CCTV

For the current research, a ‘Spot the Face in a Crowd Test’ (SFCT) comprising six video clips depicting target-actors and multiple bystanders was loaded on TooManyEyes, a bespoke multi-media platform adapted here for the human-directed identification of individuals in CCTV footage. To test the utility of TooManyEyes, police ‘super-recognisers’ (SRs) who may possess exceptional face recognition ability, and police controls attempted to identify the target-actors from the SFCT. As expected, SRs correctly identified more target-actors; with higher confidence than controls. As such, the TooManyEyes system provides a useful platform for uploading tests for selecting police or security staff for CCTV review deploymen

On the Influence of Pulse Shapes on Ionization Probability

We investigate analytical expressions for the upper and lower bounds for the ionization probability through ultra-intense shortly pulsed laser radiation. We take several different pulse shapes into account, including in particular those with a smooth adiabatic turn-on and turn-off. For all situations for which our bounds are applicable we do not find any evidence for bound-state stabilization.Comment: 21 pages LateX, 10 figure

On the absence of bound-state stabilization through short ultra-intense fields

We address the question of whether atomic bound states begin to stabilize in the short ultra-intense field limit. We provide a general theory of ionization probability and investigate its gauge invariance. For a wide range of potentials we find an upper and lower bound by non-perturbative methods, which clearly exclude the possibility that the ultra intense field might have a stabilizing effect on the atom. For short pulses we find almost complete ionization as the field strength increases.Comment: 34 pages Late

Ionization Probabilities through ultra-intense Fields in the extreme Limit

We continue our investigation concerning the question of whether atomic bound states begin to stabilize in the ultra-intense field limit. The pulses considered are essentially arbitrary, but we distinguish between three situations. First the total classical momentum transfer is non-vanishing, second not both the total classical momentum transfer and the total classical displacement are vanishing together with the requirement that the potential has a finite number of bound states and third both the total classical momentum transfer and the total classical displacement are vanishing. For the first two cases we rigorously prove, that the ionization probability tends to one when the amplitude of the pulse tends to infinity and the pulse shape remains fixed. In the third case the limit is strictly smaller than one. This case is also related to the high frequency limit considered by Gavrila et al.Comment: 16 pages LateX, 2 figure

Multiphoton detachment of electrons from negative ions

A simple analytical solution for the problem of multiphoton detachment from negative ions by a linearly polarized laser field is found. It is valid in the wide range of intensities and frequencies of the field, from the perturbation theory to the tunneling regime, and is applicable to the excess-photon as well as near-threshold detachment. Practically, the formulae are valid when the number of photons is greater than two. They produce the total detachment rates, relative intensities of the excess-photon peaks, and photoelectron angular distributions for the hydrogen and halogen negative ions, in agreement with those obtained in other, more numerically involved calculations in both perturbative and non-perturbative regimes. Our approach explains the extreme sensitivity of the multiphoton detachment probability to the asymptotic behaviour of the bound-state wave function. Rapid oscillations in the angular dependence of the $n$-photon detachment probability are shown to arise due to interference of the two classical trajectories which lead to the same final state after the electron emerges at the opposite sides of the atom when the field is close to maximal.Comment: 27 pages, Latex, and PostScript figures fig1.ps, fig2.ps, fig3.ps, accepted for publication in Phys. Rev.

An expression signature of the angiogenic response in gastrointestinal neuroendocrine tumours: correlation with tumour phenotype and survival outcomes.

BACKGROUND: Gastroenteropancreatic neuroendocrine tumours (GEP-NETs) are heterogeneous with respect to biological behaviour and prognosis. As angiogenesis is a renowned pathogenic hallmark as well as a therapeutic target, we aimed to investigate the prognostic and clinico-pathological role of tissue markers of hypoxia and angiogenesis in GEP-NETs. METHODS: Tissue microarray (TMA) blocks were constructed with 86 tumours diagnosed from 1988 to 2010. Tissue microarray sections were immunostained for hypoxia inducible factor 1α (Hif-1α), vascular endothelial growth factor-A (VEGF-A), carbonic anhydrase IX (Ca-IX) and somatostatin receptors (SSTR) 1–5, Ki-67 and CD31. Biomarker expression was correlated with clinico-pathological variables and tested for survival prediction using Kaplan–Meier and Cox regression methods. RESULTS: Eighty-six consecutive cases were included: 51% male, median age 51 (range 16–82), 68% presenting with a pancreatic primary, 95% well differentiated, 51% metastatic. Higher grading (P=0.03), advanced stage (P<0.001), high Hif-1α and low SSTR-2 expression (P=0.03) predicted for shorter overall survival (OS) on univariate analyses. Stage, SSTR-2 and Hif-1α expression were confirmed as multivariate predictors of OS. Median OS for patients with SSTR-2+/Hif-1α-tumours was not reached after median follow up of 8.8 years, whereas SSTR-2-/Hif-1α+ GEP-NETs had a median survival of only 4.2 years (P=0.006). CONCLUSION: We have identified a coherent expression signature by immunohistochemistry that can be used for patient stratification and to optimise treatment decisions in GEP-NETs independently from stage and grading. Tumours with preserved SSTR-2 and low Hif-1α expression have an indolent phenotype and may be offered less aggressive management and less stringent follow up

Canonicalizing Knowledge Base Literals

Ontology-based knowledge bases (KBs) like DBpedia are very valuable resources, but their usefulness and usability is limited by various quality issues. One such issue is the use of string literals instead of semantically typed entities. In this paper we study the automated canonicalization of such literals, i.e., replacing the literal with an existing entity from the KB or with a new entity that is typed using classes from the KB. We propose a framework that combines both reasoning and machine learning in order to predict the relevant entities and types, and we evaluate this framework against state-of-the-art baselines for both semantic typing and entity matching