On growth of spinodal instabilities in nuclear matter-II:asymmetric matter

As an extension of our previous work, the growth of density fluctuations in the spinodal region of charge asymmetric nuclear matter is investigated in the basis of the stochastic mean-field approach in the non-relativistic framework. A complete treatment of density correlation functions are presented by including collective modes and non-collective modes as well.Comment: 20 pages, 6 figures, Accepted by Physical Review

Scalar f0 and a0 mesons in radiative ϕ→K+K−γ decay

AbstractWe study the radiative ϕ→K+K−γ decay within a phenomenological framework by considering the contributions of the f0(980) and a0(980) scalar resonances. We consider the kaon-loop model and the no-structure model to evaluate these contributions and compare the results obtained in two models

Investigations of spinodal dynamics in asymmetric nuclear matter within a stochastic relativistic model

Cataloged from PDF version of article.Early development of spinodal instabilities and density correlation functions in asymmetric nuclear matter are investigated in the stochastic extension of the Walecka-type relativistic mean field including coupling with rho meson. Calculations are performed under typical conditions encountered in heavy-ion collisions and in the crusts of neutron stars. In general, growth of instabilities occur relatively slower for increasing charge asymmetry of matter. At higher densities around rho = 0.4 rho(0) fluctuations grow relatively faster in the quantal description than those found in the semi-classical limit. Typical sizes of early condensation regions extracted from density correlation functions are consistent with those found from dispersion relations of the unstable collective modes

Simple and Effective Augmentation Methods for CSI Based Indoor Localization

Indoor localization is a challenging task. There is no robust and almost-universal approach, in contrast to outdoor environments where GPS is dominant. Recently, machine learning (ML) has emerged as the most promising approach for achieving accurate indoor localization, yet its main challenge is the requirement for large datasets to train the neural networks. The data collection procedure is costly and laborious as the procedure requires extensive measurements and labeling processes for different indoor environments. The situation can be improved by Data Augmentation (DA), which is a general framework to enlarge the datasets for ML, making ML systems more robust and increases their generalization capabilities. In this paper, we propose two simple yet surprisingly effective DA algorithms for channel state information (CSI) based indoor localization motivated by physical considerations. We show that the required number of measurements for a given accuracy requirement may be decreased by an order of magnitude. Specifically, we demonstrate the algorithms' effectiveness by experiments conducted with a measured indoor WiFi measurement dataset: as little as 10% of the original dataset size is enough to get the same performance of the original dataset. We also showed that, if we further augment the dataset with proposed techniques we get better test accuracy more than three-fold

Online randomised controlled trial to improve clinical estimates of survival (ORACLES): study design

Introduction: Clinicians often struggle to recognise whether palliative care patients are imminently dying.1 2 A previous study identified the factors that expert palliative care doctors (with demonstrated prognostic skills) had used to judge the probability of patients dying within 72 hours. / Aim and methods: To evaluate whether an online training resource can teach medical students to formulate survival estimates for palliative care patients that are more similar to experts’ estimates. In this online randomised controlled trial we will recruit 128 students in the penultimate/final year of medical school. Participants are asked to review three series of vignettes describing patients referred to palliative care and provide estimates (0%–100%) about the probability that patients will die within 72 hours. After the first series of vignettes students in the intervention arm are given access to the training resource showing how experts weighted the various symptoms/signs. Participants are asked to complete a second series of vignettes and then a third series after two weeks to assess if any effect has been maintained. Results Students’ survival estimates will be correlated with experts’ estimates to determine the baseline level of agreement and any changes following the intervention. The primary outcome will be the survival estimates provided in the second series of vignettes. Secondary outcomes include the estimates provided at the follow-up the weighting of symptoms/signs and levels of discrimination and consistency. / Conclusion: This study will provide evidence about whether a brief low-cost online training resource can influence how medical students make prognostic decisions in an experimental setting

Growth of spinodal instabilities in nuclear matter. II. Asymmetric matter

As an extension of our previous work, the growth of density fluctuations in the spinodal region of charge asymmetric nuclear matter is investigated in the basis of the stochastic mean-field approach in the nonrelativistic framework. A complete treatment of density correlation functions is presented by including collective modes and noncollective modes. © 2015 American Physical Society

Growth of spinodal instabilities in nuclear matter

Early growth of density fluctuations of nuclear matter in the spinodal region is investigated employing the stochastic mean-field approach. In contrast to the earlier treatments in which only collective modes were included in the calculations, in the present work noncollective modes are also included, thus providing a complete treatment of the density correlation functions. Calculations are carried out for symmetric matter in a nonrelativistic framework using a semiclassical approximation. © 2015 American Physical Society

A FIRST-AND SECOND-ORDER TURBULENCE MODELS IN HYDROGEN NON-PREMIXED FLAME

ABSTRACT The mathematical modelling of turbulent flames is a difficult task due to the intense coupling between turbulent transport processes and chemical kinetics. The model presented within this paper is focused on the turbulence-chemistry interaction. The topic of this study is the numerical simulation of turbulent non-premixed hydrogen flame with different turbulent models in order to invest gate their predictive capability. The two turbulent models are compared: the (k-ε) model with a limited Pope's correction and the Reynolds stress model (RSM). The predictions are validated against experimental data provided by Raman and laser Doppler anemometry (LDA) measurements for a turbulent jet hydrogen-air diffusion flame. The turbulence-chemistry interaction is handled with flame let approach. Simulations of test cases with simple geometries verify the developed model and compare favourably with results of earlier investigations that employed both (k-ε) and RSM closures with the CMC and PDF approache

Collisional Damping of Nuclear Collective Vibrations in a Non-Markovian Transport Approach

A detailed derivation of the collisional widths of collective vibrations is presented in both quantal and semi-classical frameworks by considering the linearized limits of the extended TDHF and the BUU model with a non-Markovian binary collision term. Damping widths of giant dipole and giant quadrupole excitations are calculated by employing an effective Skyrme force, and the results are compared with GDR measurements in Lead and Tin nuclei at finite temperature.Comment: 23 pages, 6 Figure

Protocol for the ORaClES study: An online randomised controlled trial to improve clinical estimates of survival using a training resource for medical students

Copyright © Author(s) (or their employer(s)) 2019. Introduction Clinicians often struggle to recognise when palliative care patients are imminently dying (last 72 hours of life). A previous study identified the factors that expert palliative care doctors (with demonstrated prognostic skills) had used, to form a judgement about which patients were imminently dying. This protocol describes a study to evaluate whether an online training resource showing how experts weighted the importance of various symptoms and signs can teach medical students to formulate survival estimates for palliative care patients that are more similar to the experts' estimates. Methods and analysis This online double-blind randomised controlled trial will recruit at least 128 students in the penultimate or final year of medical school in the UK. Participants are asked to review three series of vignettes describing patients referred to palliative care and provide an estimate about the probability (0%-100%) that each patient will die within 72 hours. After the first series, students randomised to the intervention arm are given access to an online training resource. All participants are asked to complete a second series of vignettes. After 2 weeks, all participants are asked to complete a third series. The primary outcome will be the probability of death estimates (0%-100%) provided by students in the intervention and control arms for the second series of vignettes. Secondary outcomes include the maintenance effect at 2-week follow-up, weighting of individual symptoms and signs, and level of expertise (discrimination and consistency). Ethics and dissemination Approval has been obtained from the UCL Research Ethics Committee (8675/002) and local approvals will be obtained as appropriate. Results will be published in peer-reviewed journals using an open access format and presented at academic conferences. We will also publicise our findings on the Marie Curie website. Trial registration number NCT03360812; Pre-results.Marie Curie I-CAN-CARE Programme grant (MCCC-FPO-16-U); Professor Stone is supported by the Marie Curie Chair’s grant (MCCC-509537)