Numerical simulation of dark lanes in post-flare supra-arcade

We integrate the MHD ideal equations to simulate dark void sunwardly moving structures in post--flare supra--arcades. We study the onset and evolution of the internal plasma instability to compare with observations and to gain insight into physical processes and characteristic parameters of these phenomena. The numerical approach uses a finite-volume Harten-Yee TVD scheme to integrate the 1D1/2 MHD equations specially designed to capture supersonic flow discontinuities. The integration is performed in both directions, the sunward radial one and the transverse to the magnetic field. For the first time, we numerically reproduce observational dark voids described in Verwichte et al. (2005). We show that the dark tracks are plasma vacuums generated by the bouncing and interfering of shocks and expansion waves, upstream an initial slow magnetoacoustic shock produced by a localized deposition of energy modeled with a pressure perturbation. The same pressure perturbation produces a transverse to the field or perpendicular magnetic shock giving rise to nonlinear waves that compose the kink--like plasma void structures, with the same functional sunward decreasing phase speed and constancy with height of the period, as those determined by the observations.Comment: Accepted MNRAS, 6 pages, 7 figure

Increasing Competitiveness through the Implementation of Lean Management in Healthcare

The main aim of this paper was two-fold: first, to design a participative methodology that facilitates lean management implementation in healthcare by adopting the action research approach; second, to illustrate the usefulness of this methodology by applying it to the sleep unit of a public hospital in Spain. This methodology proposes the implementation of lean management in its broadest sense: adopting both lean principles and some of its practical tools or practices in order to achieve competitive advantage. The complete service value chain was considered when introducing changes through lean management implementation. This implementation involved training and involving staff in the project (personnel pillar), detecting and analysing "waste" in value chain processes (processes pillar) and establishing control and measurement mechanisms in line with objectives (key performance indicators pillar) and putting in place improvement actions to achieve these objectives. The application of this methodology brought about an improvement in the management of patient flow in terms of effectiveness, efficiency and quality but also an internal transformation towards lean culture

Chapter Machine Learning Techniques to Mitigate Nonlinear Phase Noise in Moderate Baud Rate Optical Communication Systems

Nonlinear phase noise (NLPN) is the most common impairment that degrades the performance of radio-over-fiber networks. The effect of NLPN in the constellation diagram consists of a shape distortion of symbols that increases the symbol error rate due to symbol overlapping when using a conventional demodulation grid. Symbol shape characterization was obtained experimentally at a moderate baud rate (250 MBd) for constellations impaired by phase noise due to a mismatch between the optical carrier and the transmitted radio frequency signal. Machine learning algorithms have become a powerful tool to perform monitoring and to identify and mitigate distortions introduced in both the electrical and optical domains. Clustering-based demodulation assisted with Voronoi contours enables the definition of non-Gaussian boundaries to provide flexible demodulation of 16-QAM and 4+12 PSK modulation formats. Phase-offset and in-phase and quadrature imbalance may be detected on the received constellation and compensated by applying thresholding boundaries obtained from impairment characterization through statistical analysis. Experimental results show increased tolerance to the optical signal-to-noise ratio (OSNR) obtained from clustering methods based on k-means and fuzzy c-means Gustafson-Kessel algorithms. Improvements of 3.2 dB for 16-QAM, and 1.4 dB for 4+12 PSK in the OSNR scale as a function of the bit error rate are obtained without requiring additional compensation algorithms

Absence of Fragmentation in Two-Dimensional Bose-Einstein Condensation

We investigate the possibility that the BEC-like phenomena recently detected on two-dimensional finite trapped systems consist of fragmented condensates. We derive and diagonalize the one-body density matrix of a two-dimensional isotropically trapped Bose gas at finite temperature. For the ideal gas, the procedure reproduces the exact harmonic-oscillator eigenfunctions and the Bose distribution. We use a new collocation-minimization method to study the interacting gas in the Hartree-Fock approximation and obtain a ground-state wavefunction and condensate fraction consistent with those obtained by other methods. The populations of the next few eigenstates increase at the expense of the ground state but continue to be negligible; this supports the conclusion that two-dimensional BEC is into a single state.Comment: 6 pages, 1 figur

Network analysis identifies weak and strong links in a metapopulation system

The identification of key populations shaping the structure and connectivity of metapopulation systems is a major challenge in population ecology. The use of molecular markers in the theoretical framework of population genetics has allowed great advances in this field, but the prime question of quantifying the role of each population in the system remains unresolved. Furthermore, the use and interpretation of classical methods are still bounded by the need for a priori information and underlying assumptions that are seldom respected in natural systems. Network theory was applied to map the genetic structure in a metapopulation system by using microsatellite data from populations of a threatened seagrass, Posidonia oceanica, across its whole geographical range. The network approach, free from a priori assumptions and from the usual underlying hypotheses required for the interpretation of classical analyses, allows both the straightforward characterization of hierarchical population structure and the detection of populations acting as hubs critical for relaying gene flow or sustaining the metapopulation system. This development opens perspectives in ecology and evolution in general, particularly in areas such as conservation biology and epidemiology, where targeting specific populations is crucial

Increased Th17-Related Cytokine Serum Levels in Patients With Multiple Polyps of Unexplained Origin

OBJECTIVES: Most patients with multiple colonic polyps do not have a known genetic or hereditary origin. Our aim was to analyze the presence of inflammatory cytokines and levels of glucose, insulin, and C-reactive protein (CRP) in patients with multiple colonic polyps. METHODS: Eighty-three patients with 10 or more adenomatous or serrated polyps and 53 control people with normal colonoscopy were included. Smoking habits were registered, and glucose, CRP, and basal insulin in the serum/blood were measured. Quantification of IL-2, IL-4, IL-6, IL-10, IL-11, IL-17A, and IL-23 cytokine levels in the serum was performed by a high-sensitivity enzyme-linked immunosorbent assay. RESULTS: Smoking and diabetes were more prevalent in those with colonic polyps than in the control people (67% vs 16%, P = 0.001; 11% vs 2%, P = 0.048). In addition, the cytokine serum levels were higher, i.e., IL-2 (P = 0.001), IL-4 (P = 0.001), IL-6 (P = 0.001), IL-17A (P = 0.001), IL-23 (P = 0.014), and CRP (P = 0.003). Adjusting for sex, smoking, and diabetes in a multivariate analysis, IL-2, IL-4, IL-6, IL-17A, and IL-23 remained independently elevated in cases with multiple polyps. DISCUSSION: These results indicate that immune responses mediated by Th17 cells may be involved in the pathogenesis of multiple colonic polyps

Health Outcome Predictive Evaluation for COVID 19 international registry (HOPE COVID-19), rationale and design

The disease produced by the new coronavirus known as SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus 2), named COVID-19 (Coronavirus Disease-2019) has recently been classified as a pandemic by the World Health Organization (WHO). However, scarce clinical data is available and generally limited to the Chinese population due to the first cases were identified in Wuhan (Hubei, China).This article describes the rationale and design of the HOPE COVID-19 (Health Outcome Predictive Evaluation for COVID 19) registry (ClinicalTrials.gov Identifier: NCT04334291). With an ambispective cohort design, eligible patients are those discharged, deceased or alive, from any hospital center with a confirmed diagnosis or a COVID-19 high suspicion. With a current recruitment of more than 7000 cases, in 46 hospitals in 8 countries, since it is not possible to estimate the sample size based on literature reports, the investigators will try to get the maximum numbers of patients possible. The study primary objective is all cause mortality and aims to characterize the clinical profile of patients infected in order to develop a prognostic clinical score allowing, rapid logistic decision making. As secondary objectives, the analysis of other clinical events, the risk-adjusted influence of treatments and previous comorbidities of patients infected with the disease will be performed.The results of HOPE COVID-19 will contribute to a better understanding of this condition. We aim to describe the management of this condition as well as the outcomes in relation to the therapy chosen, in order to gain insight into improving patient care in the coming months. Clinical Trial registration: ClinicalTrials.gov. Unique identifier: NCT04334291