Massive Dirac particles on the background of charged de-Sitter black hole manifolds

We consider the behavior of massive Dirac fields on the background of a charged de-Sitter black hole. All black hole geometries are taken into account, including the Reissner-Nordstr\"{o}m-de-Sitter one, the Nariai case and the ultracold case. Our focus is at first on the existence of bound quantum mechanical states for the Dirac Hamiltonian on the given backgrounds. In this respect, we show that in all cases no bound state is allowed, which amounts also to the non-existence of normalizable time-periodic solutions of the Dirac equation. This quantum result is in contrast to classical physics, and it is shown to hold true even for extremal cases. Furthermore, we shift our attention on the very interesting problem of the quantum discharge of the black holes. Following Damour-Deruelle-Ruffini approach, we show that the existence of level-crossing between positive and negative continuous energy states is a signal of the quantum instability leading to the discharge of the black hole, and in the cases of the Nariai geometry and of the ultracold geometries we also calculate in WKB approximation the transmission coefficient related to the discharge process.Comment: 19 pages, 11 figures. Macro package: Revtex4. Changes concern mainly the introduction and the final discussion in section VI; moreover, Appendix D on the evaluation of the Nariai transmission integral has been added. References adde

Response of finite-time particle detectors in non-inertial frames and curved spacetime

The response of the Unruh-DeWitt type monopole detectors which were coupled to the quantum field only for a finite proper time interval is studied for inertial and accelerated trajectories, in the Minkowski vacuum in (3+1) dimensions. Such a detector will respond even while on an inertial trajctory due to the transient effects. Further the response will also depend on the manner in which the detector is switched on and off. We consider the response in the case of smooth as well as abrupt switching of the detector. The former case is achieved with the aid of smooth window functions whose width, $T$, determines the effective time scale for which the detector is coupled to the field. We obtain a general formula for the response of the detector when a window function is specified, and work out the response in detail for the case of gaussian and exponential window functions. A detailed discussion of both $T \rightarrow 0$ and $T \rightarrow \infty$ limits are given and several subtlities in the limiting procedure are clarified. The analysis is extended for detector responses in Schwarzschild and de-Sitter spacetimes in (1+1) dimensions.Comment: 29 pages, normal TeX, figures appended as postscript file, IUCAA Preprint # 23/9

Protocol for a mixed-methods exploratory investigation of care following intensive care discharge: the REFLECT study

© Author(s) 2019. Re-use permitted under CC BY. Published by BMJ.INTRODUCTION: A substantial number of patients discharged from intensive care units (ICUs) subsequently die without leaving hospital. It is unclear how many of these deaths are preventable. Ward-based management following discharge from ICU is an area that patients and healthcare staff are concerned about. The primary aim of REFLECT (Recovery Following Intensive Care Treatment) is to develop an intervention plan to reduce in-hospital mortality rates in patients who have been discharged from ICU. METHODS AND ANALYSIS: REFLECT is a multicentre mixed-methods exploratory study examining ward care delivery to adult patients discharged from ICU. The study will be made up of four substudies. Medical notes of patients who were discharged from ICU and subsequently died will be examined using a retrospective case records review (RCRR) technique. Patients and their relatives will be interviewed about their post-ICU care, including relatives of patients who died in hospital following ICU discharge. Staff involved in the care of patients post-ICU discharge will be interviewed about the care of this patient group. The medical records of patients who survived their post-ICU stay will also be reviewed using the RCRR technique. The analyses of the substudies will be both descriptive and use a modified grounded theory approach to identify emerging themes. The evidence generated in these four substudies will form the basis of the intervention development, which will take place through stakeholder and clinical expert meetings. ETHICS AND DISSEMINATION: Ethical approval has been obtained through the Wales Research and Ethics Committee 4 (17/WA/0107). We aim to disseminate the findings through international conferences, international peer-reviewed journals and social media. TRIAL REGISTRATION NUMBER: ISRCTN14658054.Peer reviewedFinal Published versio

Deep Over-sampling Framework for Classifying Imbalanced Data

Class imbalance is a challenging issue in practical classification problems for deep learning models as well as traditional models. Traditionally successful countermeasures such as synthetic over-sampling have had limited success with complex, structured data handled by deep learning models. In this paper, we propose Deep Over-sampling (DOS), a framework for extending the synthetic over-sampling method to exploit the deep feature space acquired by a convolutional neural network (CNN). Its key feature is an explicit, supervised representation learning, for which the training data presents each raw input sample with a synthetic embedding target in the deep feature space, which is sampled from the linear subspace of in-class neighbors. We implement an iterative process of training the CNN and updating the targets, which induces smaller in-class variance among the embeddings, to increase the discriminative power of the deep representation. We present an empirical study using public benchmarks, which shows that the DOS framework not only counteracts class imbalance better than the existing method, but also improves the performance of the CNN in the standard, balanced settings

Interpolating between the Bose-Einstein and the Fermi-Dirac distributions in odd dimensions

We consider the response of a uniformly accelerated monopole detector that is coupled to a superposition of an odd and an even power of a quantized, massless scalar field in flat spacetime in arbitrary dimensions. We show that, when the field is assumed to be in the Minkowski vacuum, the response of the detector is characterized by a Bose-Einstein factor in even spacetime dimensions, whereas a Bose-Einstein as well as a Fermi-Dirac factor appear in the detector response when the dimension of spacetime is odd. Moreover, we find that, it is possible to interpolate between the Bose-Einstein and the Fermi-Dirac distributions in odd spacetime dimensions by suitably adjusting the relative strengths of the detector's coupling to the odd and the even powers of the scalar field. We point out that the response of the detector is always thermal and we, finally, close by stressing the apparent nature of the appearance of the Fermi-Dirac factor in the detector response.Comment: RevTeX, 7 page

Cavity method for quantum spin glasses on the Bethe lattice

We propose a generalization of the cavity method to quantum spin glasses on fixed connectivity lattices. Our work is motivated by the recent refinements of the classical technique and its potential application to quantum computational problems. We numerically solve for the phase structure of a connectivity $q=3$ transverse field Ising model on a Bethe lattice with $\pm J$ couplings, and investigate the distribution of various classical and quantum observables.Comment: 27 pages, 9 figure

Facilitating the driver detection of road surface type by selective manipulation of the steering-wheel acceleration signal

Copyright @ 2012 by Institution of Mechanical Engineers.Previous research has investigated the possibility of facilitating the driver detection of road surface type by means of selective manipulation of the steering-wheel acceleration signal. In previous studies a selective increase in acceleration amplitude has been found to facilitate road-surface-type detection, as has selective manipulation of the individual transient events which are present in the signal. The previous research results have been collected into a first guideline for the optimization of the steering-wheel acceleration signal, and the guideline has been tested in the current study. The test stimuli used in the current study were ten steering-wheel acceleration-time histories which were selected from an extensive database of road test measurements performed by the research group. The time histories, which were all from midsized European automobiles and European roads, were selected such that the widest possible operating envelope could be achieved in terms of the r.m.s. value of the steering acceleration, the kurtosis, the power spectral density function, and the number of transient events present in the signal. The time histories were manipulated by means of the mildly non-stationary mission synthesis algorithm in order to increase, by a factor of 2, both the number and the size of the transient events contained within the frequency interval from 20 Hz to 60Hz. The ensemble, composed of both the unmanipulated and the manipulated time histories, was used to perform a laboratory-based detection task with 15 participants, who were presented the individual stimuli in random order. The participants were asked to state, by answering 'yes' or 'no', whether each stimulus was considered to be from the road surface that was displayed in front of them by means of a large photograph on a board. The results suggest that the selectively manipulated steering-wheel acceleration stimuli produced improved detection for eight of the ten road surface types which were tested, with a maximum improvement of 14 per cent in the case of the broken road surface. The selective manipulation did lead, however, to some degradation in detection for the motorway road stimulus and for the noise road stimulus, thus suggesting that the current guideline is not universally optimal for all road surfaces

Synthesis and characterization of biodegradable lignin nanoparticles with tunable surface properties

Lignin nanoparticles can serve as biodegradable carriers of biocidal actives with minimal environmental footprint. Here we describe the colloidal synthesis and interfacial design of nanoparticles with tunable surface properties using two different lignin precursors, Kraft (Indulin AT) lignin and Organosolv (high-purity lignin). The green synthesis process is based on flash precipitation of dissolved lignin polymer, which enabled the formation of nanoparticles in the size range of 45–250 nm. The size evolution of the two types of lignin particles is fitted on the basis of modified diffusive growth kinetics and mass balance dependencies. The surface properties of the nanoparticles are fine-tuned by coating them with a cationic polyelectrolyte, poly(diallyldimethylammonium chloride). We analyze how the colloidal stability and dispersion properties of these two types of nanoparticles vary as a function of pH and salinities. The data show that the properties of the nanoparticles are governed by the type of lignin used and the presence of polyelectrolyte surface coating. The coating allows the control of the nanoparticles’ surface charge and the extension of their stability into strongly basic regimes, facilitating their potential application at extreme pH conditions