Interpreting the time variable RM observed in the core region of the TeV blazar Mrk 421

In this work we interpret and discuss the time variable rotation measure (RM) found, for the first time over a 1-yr period, in the core region of a blazar. These results are based on a one-year, multi-frequency (15, 24, and 43 GHz) Very Long Baseline Array (VLBA) monitoring of the TeV blazar Markarian 421 (Mrk 421). We investigate the Faraday screen properties and its location with respect to the jet emitting region. Given that the 43 GHz radio core flux density and the RM time evolution suggest a similar trend, we explore the possible connection between the RM and the accretion rate. Among the various scenarios that we explore, the jet sheath is the most promising candidate for being the main source of Faraday rotation. During the one-year observing period the RM trend shows two sign reversals, which may be qualitatively interpreted within the context of the magnetic tower models. We invoke the presence of two nested helical magnetic fields in the relativistic jet with opposite helicities, whose relative contribution produce the observed RM values. The inner helical field has the poloidal component ($B_{\rm p}$) oriented in the observer's direction and produces a positive RM, while the outer helical field, with $B_{\rm p}$ in the opposite direction, produces a negative RM. We assume that the external helical field dominates the contribution to the observed RM, while the internal helical field dominates when a jet perturbation arises during the second observing epoch. Being the intrinsic polarization angle parallel to the jet axis, a pitch angle of the helical magnetic field $\phi\gtrsim 70^\circ$ is required. Additional scenarios are also considered to explain the observed RM sign reversals.Comment: 6 pages, 2 figures. Published on MNRA

A Novel Low-Cost Sensor Prototype for Nocturia Monitoring in Older People

Indexación: Scopus.This work was supported in part by CORFO - CENS 16CTTS-66390 through the National Center on Health Information Systems, in part by the National Commission for Scientific and Technological Research (CONICYT) through the program STIC-AMSUD 17STIC-03: ‘‘e-MONITOR âĂŞ Chronic Disease: Ambient Assisted Living and vital teleMONOTORing for e-health,’’ FONDEF ID16I10449 ‘‘Sistema inteligente para la gestión y análisis de la dotación de camas en la red asistencial del sector público,’’ and MEC80170097 ‘‘Red de colaboración científica entre universidades nacionales e internacionales para la estructuración del doctorado y magister en informática médica en la Universidad de Valparaíso.’’ The work of V. H. C. de Albuquerque was supported by the Brazilian National Council for Research and Development (CNPq) under Grant #304315/2017-6.Nocturia is frequently defined as the necessity to get out of bed at least one time during the night to urinate, with each of these episodes being preceded and continued by sleep. Several studies suggest that an increase of nocturia is seen with the onset of age, occurring in around 70% of adults over the age of 70. Its appearance is associated with detrimental quality of life for those who present nocturia, since it leads to daytime sleepiness, cognitive dysfunction, among others. Currently, a voiding diary is necessary for nocturia assessment; these are prone to bias due to their inherent subjectivity. In this paper, we present the design of a low-cost device that automatically detects micturition events. The device obtained 73% in sensibility and 81% in specificity; these results show that systems such as the proposed one can be a valuable tool for the medical team when evaluating nocturia. © 2013 IEEE.https://ieeexplore.ieee.org/document/845445

Berry Phase Quantum Thermometer

We show how Berry phase can be used to construct an ultra-high precision quantum thermometer. An important advantage of our scheme is that there is no need for the thermometer to acquire thermal equilibrium with the sample. This reduces measurement times and avoids precision limitations.Comment: Updated to published version. I. Fuentes previously published as I. Fuentes-Guridi and I. Fuentes-Schulle

Dictionary Learning-based Inpainting on Triangular Meshes

The problem of inpainting consists of filling missing or damaged regions in images and videos in such a way that the filling pattern does not produce artifacts that deviate from the original data. In addition to restoring the missing data, the inpainting technique can also be used to remove undesired objects. In this work, we address the problem of inpainting on surfaces through a new method based on dictionary learning and sparse coding. Our method learns the dictionary through the subdivision of the mesh into patches and rebuilds the mesh via a method of reconstruction inspired by the Non-local Means method on the computed sparse codes. One of the advantages of our method is that it is capable of filling the missing regions and simultaneously removes noise and enhances important features of the mesh. Moreover, the inpainting result is globally coherent as the representation based on the dictionaries captures all the geometric information in the transformed domain. We present two variations of the method: a direct one, in which the model is reconstructed and restored directly from the representation in the transformed domain and a second one, adaptive, in which the missing regions are recreated iteratively through the successive propagation of the sparse code computed in the hole boundaries, which guides the local reconstructions. The second method produces better results for large regions because the sparse codes of the patches are adapted according to the sparse codes of the boundary patches. Finally, we present and analyze experimental results that demonstrate the performance of our method compared to the literature

A novel monitoring system for fall detection in older people

Indexación: Scopus.This work was supported in part by CORFO - CENS 16CTTS-66390 through the National Center on Health Information Systems, in part by the National Commission for Scientific and Technological Research (CONICYT) through the Program STIC-AMSUD 17STIC-03: ‘‘MONITORing for ehealth," FONDEF ID16I10449 ‘‘Sistema inteligente para la gestión y análisis de la dotación de camas en la red asistencial del sector público’’, and in part by MEC80170097 ‘‘Red de colaboración científica entre universidades nacionales e internacionales para la estructuración del doctorado y magister en informática médica en la Universidad de Valparaíso’’. The work of V. H. C. De Albuquerque was supported by the Brazilian National Council for Research and Development (CNPq), under Grant 304315/2017-6.Each year, more than 30% of people over 65 years-old suffer some fall. Unfortunately, this can generate physical and psychological damage, especially if they live alone and they are unable to get help. In this field, several studies have been performed aiming to alert potential falls of the older people by using different types of sensors and algorithms. In this paper, we present a novel non-invasive monitoring system for fall detection in older people who live alone. Our proposal is using very-low-resolution thermal sensors for classifying a fall and then alerting to the care staff. Also, we analyze the performance of three recurrent neural networks for fall detections: Long short-term memory (LSTM), gated recurrent unit, and Bi-LSTM. As many learning algorithms, we have performed a training phase using different test subjects. After several tests, we can observe that the Bi-LSTM approach overcome the others techniques reaching a 93% of accuracy in fall detection. We believe that the bidirectional way of the Bi-LSTM algorithm gives excellent results because the use of their data is influenced by prior and new information, which compares to LSTM and GRU. Information obtained using this system did not compromise the user's privacy, which constitutes an additional advantage of this alternative. © 2013 IEEE.https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=842305

Early warning signals in plant disease outbreaks

Infectious disease outbreaks in plants threaten ecosystems, agricultural crops and food trade. Currently, several fungal diseases are affecting forests worldwide, posing a major risk to tree species, habitats and consequently ecosystem decay. Prediction and control of disease spread are difficult, mainly due to the complexity of the interaction between individual components involved. In this work, we introduce a lattice-based epidemic model coupled with a stochastic process that mimics, in a very simplified way, the interaction between the hosts and pathogen. We studied the disease spread by measuring the propagation velocity of the pathogen on the susceptible hosts. Our quantitative results indicate the occurrence of a critical transition between two stable phases: local confinement and an extended epiphytotic outbreak that depends on the density of the susceptible individuals. Quantitative predictions of epiphytotics are performed using the framework early-warning indicators for impending regime shifts, widely applied on dynamical systems. These signals forecast successfully the outcome of the critical shift between the two stable phases before the system enters the epiphytotic regime. Our study demonstrates that early-warning indicators could be useful for the prediction of forest disease epidemics through mathematical and computational models suited to more specific pathogen–host-environmental interactions. Our results may also be useful to identify a suitable planting density to slow down disease spread and in the future, design highly resilient forests

The Magnetic Electron Ion Spectrometer (MagEIS) Instruments Aboard the Radiation Belt Storm Probes (RBSP) Spacecraft

This paper describes the Magnetic Electron Ion Spectrometer (MagEIS) instruments aboard the RBSP spacecraft from an instrumentation and engineering point of view. There are four magnetic spectrometers aboard each of the two spacecraft, one low-energy unit (20–240 keV), two medium-energy units (80–1200 keV), and a high-energy unit (800–4800 keV). The high unit also contains a proton telescope (55 keV–20 MeV). The magnetic spectrometers focus electrons within a selected energy pass band upon a focal plane of several silicon detectors where pulse-height analysis is used to determine if the energy of the incident electron is appropriate for the electron momentum selected by the magnet. Thus each event is a two-parameter analysis, an approach leading to a greatly reduced background. The physics of these instruments are described in detail followed by the engineering implementation. The data outputs are described, and examples of the calibration results and early flight data presented

The glitch activity of neutron stars

We present a statistical study of the glitch population and the behaviour of the glitch activity across the known population of neutron stars. An unbiased glitch database was put together based on systematic searches of radio timing data of 898 rotation-powered pulsars obtained with the Jodrell Bank and Parkes observatories. Glitches identified in similar searches of 5 magnetars were also included. The database contains 384 glitches found in the rotation of 141 of these neutron stars. We confirm that the glitch size distribution is at least bimodal, with one sharp peak at approximately $20\, \rm{\mu\,Hz}$, which we call large glitches, and a broader distribution of smaller glitches. We also explored how the glitch activity $\dot{\nu}_{\rm{g}}$, defined as the mean frequency increment per unit of time due to glitches, correlates with the spin frequency $\nu$, spin-down rate $|\dot{\nu}|$, and various combinations of these, such as energy loss rate, magnetic field, and spin-down age. It is found that the activity is insensitive to the magnetic field and that it correlates strongly with the energy loss rate, though magnetars deviate from the trend defined by the rotation-powered pulsars. However, we find that a constant ratio $\dot\nu_{\rm{g}}/|\dot\nu| = 0.010 \pm 0.001$ is consistent with the behaviour of all rotation-powered pulsars and magnetars. This relation is dominated by large glitches, which occur at a rate directly proportional to $|\dot{\nu}|$. The only exception are the rotation-powered pulsars with the highest values of $|\dot{\nu}|$, such as the Crab pulsar and PSR B0540$-$69, which exhibit a much smaller glitch activity, intrinsically different from each other and from the rest of the population. The activity due to small glitches also shows an increasing trend with $|\dot\nu|$, but this relation is biased by selection effects.Comment: Accepted for publication in A&