Magnetic field suppression in collision-less shocks generated during the expansion of a dense plasma into a rarefied medium

A two-dimensional numerical study of the expansion of a dense plasma through a more rarefied one is reported. The electrostatic ion-acoustic shock, which is generated during the expansion, accelerates the electrons of the rarefied plasma inducing a superthermal population which reduces electron thermal anisotropy. The Weibel instability is therefore not triggered and no self-generated magnetic fields are observed, in contrast with published theoretical results dealing with plasma expansion into vacuum. © The Author(s) 2013.

XUV spectroscopic characterization of warm dense aluminum plasmas generated by the free-electron-laser FLASH

We report on experiments aimed at the generation and characterization of solid density plasmas at the free-electron laser FLASH in Hamburg. Aluminum samples were irradiated with XUV pulses at 13.5 nm wavelength (92 eV photon energy). The pulses with duration of a few tens of femtoseconds and pulse energy up to 100 mu J are focused to intensities ranging between 10(13) and 10(17) W/cm(2). We investigate the absorption and temporal evolution of the sample under irradiation by use of XUV and optical spectroscopy. We discuss the origin of saturable absorption, radiative decay, bremsstrahlung and atomic and ionic line emission. Our experimental results are in good agreement with simulations.

Beaming of High-Order Harmonics Generated from Laser-Plasma Interactions

Beam divergences of high-order extreme ultraviolet harmonics from intense laser interactions with steep plasma density gradients are studied through experiment and Fourier analysis of the harmonic spatial phase. We show that while emission due to the relativistically oscillating mirror mechanism can be explained by ponderomotive surface denting, in agreement with previous results, the divergence of the emission due to the coherent wake emission mechanism requires a combination of the dent phase and an intrinsic emission phase. The temporal dependence of the divergences for both mechanisms is highlighted while it is also shown that the coherent wake emission divergence can be small in circumstances where the phase terms compensate each other. © 2013 American Physical Society.

Time to get a move on:Overcoming bradykinetic movement in Parkinson's disease with artificial sensory guidance generated from biological motion

Paradoxical kinesia describes the motor improvement in Parkinson's disease (PD) triggered by the presence of external sensory information relevant for the movement. This phenomenon has been puzzling scientists for over 60 years, both in neurological and motor control research, with the underpinning mechanism still being the subject of fierce debate. In this paper we present novel evidence supporting the idea that the key to understanding paradoxical kinesia lies in both spatial and temporal information conveyed by the cues and the coupling between perception and action. We tested a group of 7 idiopathic PD patients in an upper limb mediolateral movement task. Movements were performed with and without a visual point light display, travelling at 3 different speeds. The dynamic information presented in the visual point light display depicted three different movement speeds of the same amplitude performed by a healthy adult. The displays were tested and validated on a group of neurologically healthy participants before being tested on the PD group. Our data show that the temporal aspects of the movement (kinematics) in PD can be moderated by the prescribed temporal information presented in a dynamic environmental cue. Patients demonstrated a significant improvement in terms of movement time and peak velocity when executing movement in accordance with the information afforded by the point light display, compared to when the movement of the same amplitude and direction was performed without the display. In all patients we observed the effect of paradoxical kinesia, with a strong relationship between the perceptual information prescribed by the biological motion display and the observed motor performance of the patients. © 2013 Elsevier B.V. All rights reserved.

Identifying cell class specific losses from serially generated electroretinogram components

Purpose. Processing of information through the cellular layers of the retina occurs in a serial manner. In the electroretinogram (ERG), this complicates interpretation of inner retinal changes as dysfunction may arise from "upstream" neurons or may indicate a direct loss to that neural generator. We propose an approach that addresses this issue by defining ERG gain relationships.

Methods. Regression analyses between two serial ERG parameters in a control cohort of rats are used to define gain relationships. These gains are then applied to two models of retinal disease.

Results. The PIIIamp to PIIamp gain is unity whereas the PIIamp to pSTRamp and PIIamp to nSTRamp gains are greater than unity, indicating "amplification" (P <0.05). Timing relationships show amplification between PIIIit to PIIit and compression for PIIit to pSTRit and PIIit to nSTRit, (P <0.05). Application of these gains to ?-3-deficiency indicates that all timing changes are downstream of photoreceptor changes, but a direct pSTR amplitude loss occurs (P <0.05). Application to diabetes indicates widespread inner retinal dysfunction which cannot be attributed to outer retinal changes (P <0.05).

Conclusions. This simple approach aids in the interpretation of inner retinal ERG changes by taking into account gain characteristics found between successive ERG components of normal animals.

A multi-output two-stage locally regularized model construction method using the extreme learning machine

This paper investigates the construction of linear-in-the-parameters (LITP) models for multi-output regression problems. Most existing stepwise forward algorithms choose the regressor terms one by one, each time maximizing the model error reduction ratio. The drawback is that such procedures cannot guarantee a sparse model, especially under highly noisy learning conditions. The main objective of this paper is to improve the sparsity and generalization capability of a model for multi-output regression problems, while reducing the computational complexity. This is achieved by proposing a novel multi-output two-stage locally regularized model construction (MTLRMC) method using the extreme learning machine (ELM). In this new algorithm, the nonlinear parameters in each term, such as the width of the Gaussian function and the power of a polynomial term, are firstly determined by the ELM. An initial multi-output LITP model is then generated according to the termination criteria in the first stage. The significance of each selected regressor is checked and the insignificant ones are replaced at the second stage. The proposed method can produce an optimized compact model by using the regularized parameters. Further, to reduce the computational complexity, a proper regression context is used to allow fast implementation of the proposed method. Simulation results confirm the effectiveness of the proposed technique. © 2013 Elsevier B.V.

Quantum and classical properties of the fields generated by two interlinked second-order non-linear interactions

We consider two interlinked non-linear interactions occurring simultaneously in a single chi((2)) crystal. Classical and quantum working regimes are considered and their peculiar properties analysed. In particular, we describe an experiment, realized in the classical regime, that verifies the holographic nature of the process, and predict, for the quantum regime, the generation of a fully inseparable tripartite Gaussian state of light that can be used to support a general 1--> 2 continuous variable telecloning protocol.

ivlewbel: Uses heteroscedasticity to estimate mismeasured and endogenous regressor models

GMM estimation of triangular systems using heteroscedasticity based instrumental variables as in Lewbel (2012).

Learning from time series:Supervised Aggregative Feature Extraction

Many modeling problems require to estimate a scalar output from one or more time series. Such problems are usually tackled by extracting a fixed number of features from the time series (like their statistical moments), with a consequent loss in information that leads to suboptimal predictive models. Moreover, feature extraction techniques usually make assumptions that are not met by real world settings (e.g. uniformly sampled time series of constant length), and fail to deliver a thorough methodology to deal with noisy data. In this paper a methodology based on functional learning is proposed to overcome the aforementioned problems; the proposed Supervised Aggregative Feature Extraction (SAFE) approach allows to derive continuous, smooth estimates of time series data (yielding aggregate local information), while simultaneously estimating a continuous shape function yielding optimal predictions. The SAFE paradigm enjoys several properties like closed form solution, incorporation of first and second order derivative information into the regressor matrix, interpretability of the generated functional predictor and the possibility to exploit Reproducing Kernel Hilbert Spaces setting to yield nonlinear predictive models. Simulation studies are provided to highlight the strengths of the new methodology w.r.t. standard unsupervised feature selection approaches. © 2012 IEEE.

Viability of Pseudomonas aeruginosa in cough aerosols generated by persons with cystic fibrosis

Background Person-to-person transmission of respiratory pathogens, including Pseudomonas aeruginosa, is a challenge facing many cystic fibrosis (CF) centres. Viable P aeruginosa are contained in aerosols produced during coughing, raising the possibility of airborne transmission.

Methods Using purpose-built equipment, we measured viable P aeruginosa in cough aerosols at 1, 2 and 4 m from the subject (distance) and after allowing aerosols to age for 5, 15 and 45 min in a slowly rotating drum to minimise gravitational settling and inertial impaction (duration). Aerosol particles were captured and sized employing an Anderson Impactor and cultured using conventional microbiology. Sputum was also cultured and lung function and respiratory muscle strength measured.

Results Nineteen patients with CF, mean age 25.8 (SD 9.2) years, chronically infected with P aeruginosa, and 10 healthy controls, 26.5 (8.7) years, participated. Viable P aeruginosa were detected in cough aerosols from all patients with CF, but not from controls; travelling 4 m in 17/18 (94%) and persisting for 45 min in 14/18 (78%) of the CF group. Marked inter-subject heterogeneity of P aeruginosa aerosol colony counts was seen and correlated strongly (r=0.73-0.90) with sputum bacterial loads. Modelling decay of viable P aeruginosa in a clinic room suggested that at the recommended ventilation rate of two air changes per hour almost 50 min were required for 90% to be removed after an infected patient left the room.

Conclusions: Viable P aeruginosa in cough aerosols travel further and last longer than recognised previously, providing additional evidence of airborne transmission between patients with CF.

Cough-generated aerosols of Pseudomonas aeruginosa and other Gram-negative bacteria from patients with cystic fibrosis

BACKGROUND: Pseudomonas aeruginosa is the most common bacterial pathogen in patients with cystic fibrosis (CF). Current infection control guidelines aim to prevent transmission via contact and respiratory droplet routes and do not consider the possibility of airborne transmission. It was hypothesised that subjects with CF produce viable respirable bacterial aerosols with coughing.

METHODS: A cross-sectional study was undertaken of 15 children and 13 adults with CF, 26 chronically infected with P aeruginosa. A cough aerosol sampling system enabled fractioning of respiratory particles of different sizes and culture of viable Gram-negative non-fermentative bacteria. Cough aerosols were collected during 5 min of voluntary coughing and during a sputum induction procedure when tolerated. Standardised quantitative culture and genotyping techniques were used.

RESULTS: P aeruginosa was isolated in cough aerosols of 25 subjects (89%), 22 of whom produced sputum samples. P aeruginosa from sputum and paired cough aerosols were indistinguishable by molecular typing. In four cases the same genotype was isolated from ambient room air. Approximately 70% of viable aerosols collected during voluntary coughing were of particles <or=3.3 microm aerodynamic diameter. P aeruginosa, Burkholderia cenocepacia, Stenotrophomonas maltophilia and Achromobacter xylosoxidans were cultivated from respiratory particles in this size range. Positive room air samples were associated with high total counts in cough aerosols (p = 0.003). The magnitude of cough aerosols was associated with higher forced expiratory volume in 1 s (r = 0.45, p = 0.02) and higher quantitative sputum culture results (r = 0.58, p = 0.008).

CONCLUSION: During coughing, patients with CF produce viable aerosols of P aeruginosa and other Gram-negative bacteria of respirable size range, suggesting the potential for airborne transmission.