Modeling non-thermal emission from stellar bow shocks

Runaway O- and early B-type stars passing throughout the interstellar medium at supersonic velocities and characterized by strong stellar winds may produce bow shocks that can serve as particle acceleration sites. Previous theoretical models predict the production of high energy photons by non-thermal radiative processes, but their efficiency is still debated. We aim to test and explain the possibility of emission from the bow shocks formed by runaway stars traveling through the interstellar medium by using previous theoretical models. We apply our model to AE Aurigae, the first reported star with an X-ray detected bow shock, to BD+43 3654, in which the observations failed in detecting high energy emission, and to the transition phase of a supergiant star in the late stages of its life.From our analysis, we confirm that the X-ray emission from the bow shock produced by AE Aurigae can be explained by inverse Compton processes involving the infrared photons of the heated dust. We also predict low high energy flux emission from the bow shock produced by BD+43 3654, and the possibility of high energy emission from the bow shock formed by a supergiant star during the transition phase from blue to red supergiant.Bow shock formed by different type of runaway stars are revealed as a new possible source of high energy photons in our neighbourhood

Formation of X-ray emitting stationary shocks in magnetized protostellar jets

X-ray observations of protostellar jets show evidence of strong shocks heating the plasma up to temperatures of a few million degrees. In some cases, the shocked features appear to be stationary. They are interpreted as shock diamonds. We aim at investigating the physics that guides the formation of X-ray emitting stationary shocks in protostellar jets, the role of the magnetic field in determining the location, stability, and detectability in X-rays of these shocks, and the physical properties of the shocked plasma. We performed a set of 2.5-dimensional magnetohydrodynamic numerical simulations modelling supersonic jets ramming into a magnetized medium and explored different configurations of the magnetic field. The model takes into account the most relevant physical effects, namely thermal conduction and radiative losses. We compared the model results with observations, via the emission measure and the X-ray luminosity synthesized from the simulations. Our model explains the formation of X-ray emitting stationary shocks in a natural way. The magnetic field collimates the plasma at the base of the jet and forms there a magnetic nozzle. After an initial transient, the nozzle leads to the formation of a shock diamond at its exit which is stationary over the time covered by the simulations (~ 40 - 60 yr; comparable with time scales of the observations). The shock generates a point-like X-ray source located close to the base of the jet with luminosity comparable with that inferred from X-ray observations of protostellar jets. For the range of parameters explored, the evolution of the post-shock plasma is dominated by the radiative cooling, whereas the thermal conduction slightly affects the structure of the shock.Comment: Accepted for publication in Astronomy and Astrophysic

Evaluation of CNN architectures for gait recognition based on optical flow maps

This work targets people identification in video based on the way they walk (\ie gait) by using deep learning architectures. We explore the use of convolutional neural networks (CNN) for learning high-level descriptors from low-level motion features (\ie optical flow components). The low number of training samples for each subject and the use of a test set containing subjects different from the training ones makes the search of a good CNN architecture a challenging task.Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tec

High-resolution error compensation in continuous conduction mode power factor correction stage without current sensor

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. V. M. López-Martín, F. J. Azcondo, and Á. de Castro, "High-resolution error compensation in continuous conduction mode power factor correction stage without current sensor", in 2012 15th International Power Electronics and Motion Control Conference (EPE/PEMC), Novi Sad (Serbia), 2012.Continuous conduction mode power factor correction (PFC) without input current measurement is a step forward with respect to previously proposed PFC digital controllers. Inductance volt-second (vsL) measurement in each switching period enables the estimation of input current, but an accurate compensation of the small errors in the measured vsL is required. Otherwise, they are accumulated over a half-cycle line, leading to an appreciable current distortion. A vsL estimation is proposed, measuring the input (vin) and the the output voltage (vo). Discontinuous conduction mode (DCM) occurs near input line zero crossings, and is also detected by measuring MOSFET vds. This article analyzes the current estimation error caused by errors in the on-time estimation and voltage measurements, and proposes the minimization of vsL errors by cancelling the difference between estimated DCM (TDCMinereb) and real DCM (TDCMin) times with a signal (vdig), generated in the digital device. Therefore, the current estimation is calibrated using digital signals during the operation in DCM. Feedfoward coarse time error compensation is carried out with the measured delay of the drive signal, and then a fine compensation is achieved with a feedback loop that adjusts vdig. Experimental results are shown for a 1 kW boost PFC converter.This work was supported in part by the Spanish Ministry of Science TEC - FEDER 2011-2361

Current error compensation for current-sensorless power factor corrector stage in continuous conduction mode

Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. V. M. Lopez-Martin, F. J. Azcondo, and A. de Castro, "Current error compensation for current-sensorless power factor corrector stage in continuous conduction mode", 2012 IEEE 13th Workshop on Control and Modeling for Power Electronics (COMPEL), Kyoto (Japan), 2012, pp. 1-8A universal digital PFC current-sensorless controller based on control of estimated current is presented. Parasitic elements cause a small difference between the measured input voltage and the voltage across the inductance in a boost converter, which must be taken into account to estimate the input current in a sensorless PFC digital controller. To compensate for the deviation caused by the parasitic elements, and so minimize the current estimation error, the article proposes a digital feedback control technique that cancels the time difference between DCM operation time of the real input current (TinDCM) and the estimated current (TrebDCM). Experimental results, obtained using a boost PFC converter under different conditions, are shown for verification purposes.This work was supported by the Spanish Ministry of Science TEC FEDER 2011-2361

A high-resolution fuel type mapping procedure based on satellite imagery and neural networks: Updating fuel maps for wildfire simulators

A major limitation in the simulation of forest fires involves the proper characterization of the surface vegetation over the study area, based on land cover maps. Unfortunately, these maps may be outdated, with areas where vegetation is either not documented or inaccurately portrayed. These limitations may impair the predictions of wildfire simulators or the design of risk maps and prevention plans. This study proposes a complete procedure for fuel type classification using satellite imagery and fully-connected neural networks. Specifically, our work is based on pixel- based processing cells, generating high-resolution maps. The field study is located in the Northeast of Castilla y Leo ́n, a central Spanish region, and the Rothermel criteria was followed for the fuel classification. The results record an accuracy of close to 78% on the test sets for the two studied settings, improving on the results reported in previous studies and ratifying the robustness of our approach. Additionally, the confusion matrix analysis and the per-class statistics computed confirm good reliability for all fuel types in a cross-validation framework. The predicted maps can be used on wildfire simulators through GIS tools.BERC 2022–2025 PID2019-107685RB-I00 European Regional Development Fund (ERDF) and the Department of Education of the regional government, the Junta of Castilla y Leo ́n, (Grant contract SA089P20); the European Union’s Horizon 2020 – Research and Innovation Framework Program under Grant agreement ID 101036926