A Statistical Study of Photospheric Magnetic Field Changes During 75 Solar Flares

Abrupt and permanent changes of photospheric magnetic fields have been observed during solar flares. The changes seem to be linked to the reconfiguration of magnetic fields, but their origin is still unclear. We carried out a statistical analysis of permanent line-of-sight magnetic field ($B_{\rm LOS}$) changes during 18 X-, 37 M-, 19 C- and 1 B-class flares using data from Solar Dynamics Observatory/Helioseismic and Magnetic Imager. We investigated the properties of permanent changes, such as frequency, areas, and locations. We detected changes of $B_{\rm LOS}$ in 59/75 flares. We find that strong flares are more likely to show changes, with all flares $\ge$ M1.6 exhibiting them. For weaker flares, permanent changes are observed in 6/17 C-flares. 34.3\% of the permanent changes occurred in the penumbra and 18.9\% in the umbra. Parts of the penumbra appeared or disappeared in 23/75 flares. The area where permanent changes occur is larger for stronger flares. Strong flares also show a larger change of flux, but there is no dependence of the magnetic flux change on the heliocentric angle. The mean rate of change of flare-related magnetic field changes is 20.7 Mx cm$^{-2}$ min$^{-1}$. The number of permanent changes decays exponentially with distance from the polarity inversion line. The frequency of the strength of permanent changes decreases exponentially, and permanent changes up to 750 Mx cm$^{-2}$ were observed. We conclude that permanent magnetic field changes are a common phenomenon during flares, and future studies will clarify their relation to accelerated electrons, white light emission, and sunquakes to further investigate their origin.Comment: Piblished in Ap

Bayesian inference for algorithm ranking analysis

The statistical assessment of the empirical comparison of algorithms is an essential step in heuristic optimization. Classically, researchers have relied on the use of statistical tests. However, recently, concerns about their use have arisen and, in many fields, other (Bayesian) alternatives are being considered. For a proper analysis, different aspects should be considered. In this work we focus on the question: what is the probability of a given algorithm being the best? To tackle this question, we propose a Bayesian analysis based on the Plackett-Luce model over rankings that allows several algorithms to be considered at the same tim

Reconstruction and numerical modelling of the abdominal wall. Application to hernia surgery

Routine hernia repair surgery involves the implant of synthetic mesh. However, this proceduremay give rise to several problems causing considerable patient disability. With the aim ofimproving surgical procedures, the healthy and the herniated human abdomen are simulatedusing finite element (FE) simulations. For that purpose, a reconstruction of the physiologicalgeometry of a human abdomen was created using magnetic resonance images. Besides,following the anatomy of the abdomen, the different muscles and aponeurosis were defined.Furthermore, collagen fibres were included in each muscle layer and their passive anisotropicmechanical contribution was modelled within the framework of hyperelasticity. In the FEsimulation of the abdomen, the constraint imposed by the shoulder is applied and an internalpressure of 23 kPa was applied to the interior abdominal wall to reproduce the abdominal loadwhen standing jumping. After generating a hernia in the front of the abdomen, differentprostheses (Surgipro®, Optilene® and Infinit®), modelled using a membrane model, are placedin the defect to simulate the behaviour of the abdomen after the surgical procedure. In thehealthy abdomen, maximal principal stresses (MPS) and displacements (MD) appear in thefront of the belly. On the other hand, once the hernia is created and the mesh is placed, theMD and MPS are higher than those attained in the healthy abdomen. Thus, just after surgery,surgical repair procedure does not fully restore normal physiological conditions and the risk ofhernia recurrence by the suture is high due to the stress concentration

A fully-integrated 180 nm CMOS 1.2 V low-dropout regulator for low-power portable applications

This paper presents the design and postlayout simulation results of a capacitor-less low dropout (LDO) regulator fully integrated in a low-cost standard 180 nm Complementary Metal-Oxide-Semiconductor (CMOS) technology which regulates the output voltage at 1.2 V from a 3.3 to 1.3 V battery over a -40 to 120 degrees C temperature range. To meet with the constraints of system-on-chip (SoC) battery-operated devices, ultralow power (I-q = 8.6 mu A) and minimum area consumption (0.109 mm(2)) are maintained, including a reference voltage V-ref = 0.4 V. It uses a high-gain dynamically biased folded-based error amplifier topology optimized for low-voltage operation that achieves an enhanced regulation-fast transient performance trade-off

A numerical investigation of changes in lens shape during accommodation

The purpose of this study was to investigate how the mechanical properties and geometry of the lens influence the changes in lens shape during accommodation. To do so, ex vivo stretching tests of the isolated lens were simulated via finite element analysis. In these tests, the lens is stretched from the accommodated state to the non-accommodated state. Several key characteristics of the lens were studied: the stiffness gradient of the lens material, the distribution of the capsule thickness, the mechanical properties of the capsule and the material comprising the lens, nucleus and cortex, and the influence of two different age-related lens geometries (17 and 29 y/o subjects). To determine the effects on the changes in lens shape during accommodation, changes in the anterior and posterior radius, the lens and nucleus thicknesses and the equatorial lens diameter were analysed. The results suggest that multiple factors exert statistically significant influences on how the lens changes its shape, but two factors predominate over the rest: the stiffness ratio between the nucleus and cortex and the stiffness of the capsule, specifically the posterior surface

Multi-objectivising Combinatorial Optimisation Problems by means of Elementary Landscape Decompositions

In the last decade, many works in combinatorial optimisation have shown that, due to the advances in multi-objective optimisation, the algorithms from this field could be used for solving single-objective problems as well. In this sense, a number of papers have proposed multi-objectivising single-objective problems in order to use multi-objective algorithms in their optimisation. In this paper, we follow up this idea by presenting a methodology for multi-objectivising combinatorial optimisation prob- lems based on elementary landscape decompositions of their objective function. Under this framework, each of the elementary landscapes obtained from the decomposition is considered as an independent objective function to optimise. In order to illustrate this general methodology, we consider four problems from different domains: the quadratic assignment problem and the linear ordering problem (permutation domain), the 0-1 unconstrained quadratic optimisation problem (binary domain), and the frequency assignment problem (integer domain). We implemented two widely known multi-objective algorithms, NSGA-II and SPEA2, and compared their perfor- mance with that of a single-objective GA. The experiments conducted on a large benchmark of instances of the four problems show that the multi-objective algorithms clearly outperform the single-objective approaches. Furthermore, a discussion on the results suggests that the multi-objective space generated by this decomposition enhances the exploration ability, thus permitting NSGA-II and SPEA2 to obtain better results in the majority of the tested instances.TIN2016-78365R IT-609-1

Low-power 3V single supply lock-in amplifier

In extreme high noise level environments, linear filtering is not a suitable processing method and special techniques for accurately extracting sensor signal information should be considered. An interesting possibility are lock-in amplifiers (LIA), which use the phase sensitive detection technique (PSD) to take out the data signal at a specific reference frequency fo while noise signals at frequencies other than fo are rejected and do not affect significantly the measurement. Current commercial LIAs are expensive, heavy and power consuming devices, which preclude their use in portable sensing systems. Thus, this work analyses the possibility of exporting this technique to low-power low-voltage (LPLV) embedded applications. In particular, the aim is to implement a signal conditioning lock-in architecture suitable for 3V single battery-operated wireless sensor nodes. This implies to re-design all the processing elements in single supply -most reported LIAs are designed using dual power supply- and compatible with the power requirements of a wireless sensor network node. Further, looking for a compact LPLV solution, instead of a traditional sinusoidal input, a square wave input is considered, which can be directly obtained from the embedded microcontroller, thus avoiding blocks like a sinusoidal oscillator or function generator. Figure 1 shows the proposed block diagram and a photograph of the implemented device. Experimental results for signals buried in white noise, flicker noise, interference contamination and common-mode voltage contamination confirm the capability of the proposed solution to recover information from signal to noise ratios down to 24 dB with errors below 6% with an average power consumption of only 5 mW in full operation, being able to process signals with frequencies up to 43 kHz, as shown in Figure 2