Optimal generalized quantum measurements for arbitrary spin systems

Positive operator valued measurements on a finite number of N identically prepared systems of arbitrary spin J are discussed. Pure states are characterized in terms of Bloch-like vectors restricted by a SU(2 J+1) covariant constraint. This representation allows for a simple description of the equations to be fulfilled by optimal measurements. We explicitly find the minimal POVM for the N=2 case, a rigorous bound for N=3 and set up the analysis for arbitrary N.Comment: LateX, 12 page

Diagnosis and modelling of a summer convective storm over Mediterranean Pyrenees

International audienceOver the Mediterranean Pyrenees and near coastal region there is a high frequency of convective storms during summertime. This fact determines a local maximum of precipitation at this season unlike the normal and general minimum over Mediterranean basin. The common synoptic and mesoscale patterns associated to convective phenomena are briefly analyzed and diagnosed with radar imagery, surface pressure and isobaric level fields and surface data. They usually involves a little distant through at medium levels, very weak pressure gradient at the surface and not significant instability, but a preferred Planetary Boundary Layer low-level convergence zones tied to the orography. As a result of this analysis two different kinds of circulations associated to recurrent convergence zones have been recognized: upvalley/upslope winds and sea breezes. High resolution simulations from a Numerical Weather Prediction model for a case study have carried out to analyze the role of the main key components, i.e. the orography, the sea and valley breeze and their influence to generate local convergence zones. Furthermore, the skills of the model to simulate the location and the intensity of the precipitation of these summer Mediterranean storms have been discussed

Predictive learning, prediction errors, and attention: evidence from event-related potentials and eye tracking

Prediction error (‘‘surprise’’) affects the rate of learning: We learn more rapidly about cues for which we initially make incorrect predictions than cues for which our initial predictions are correct. The current studies employ electrophysiological measures to reveal early attentional differentiation of events that differ in their previous involvement in errors of predictive judgment. Error-related events attract more attention, as evidenced by features of event-related scalp potentials previously implicated in selective visual attention (selection negativity, augmented anterior N1). The earliest differences detected occurred around 120 msec after stimulus onset, and distributed source localization (LORETA) indicated that the inferior temporal regions were one source of the earliest differences. In addition, stimuli associated with the production of prediction errors show higher dwell times in an eyetracking procedure. Our data support the view that early attentional processes play a role in human associative learning

Minimal optimal generalized quantum measurements

Optimal and finite positive operator valued measurements on a finite number $N$ of identically prepared systems have been presented recently. With physical realization in mind we propose here optimal and minimal generalized quantum measurements for two-level systems. We explicitly construct them up to N=7 and verify that they are minimal up to N=5. We finally propose an expression which gives the size of the minimal optimal measurements for arbitrary $N$.Comment: 9 pages, Late

Field experimental study of traffic-induced turbulence on highways

This paper is focused on traffic-induced turbulence (TIT) analysis from a field campaign performed in 2011, using ultrasonic anemometers deployed in the M-12 Highways, Madrid (Spain). The study attempts to improve knowledge about the influence of traffic-related parameters on turbulence. Linear relationships between vehicle speed and turbulent kinetic energy (TKE) values are found with coefficients of determination (R2) of 0.75 and 0.55 for the lorry and van respectively. The vehicle-induced fluctuations in the wind components (u', v' and w') showed the highest values for the longitudinal component (v) because of the wake-passing effect. In the analysis of wake produced by moving vehicles it is indicated how the turbulence dissipates in relation to a distance d and height h. The TKE values were found to be higher at the measuring points closer to the surface during the wake analysis.This work was supported by the OASIS Research Project that was co financed by CDTI (Spanish Science and Innovation Ministry) and developed with the Spanish companies: Iridium, OHL Concesiones, Abertis, Sice, Indra, Dragados, OHL, Geocisa, GMV, Asfaltos Augusta, Hidrofersa, Eipsa, PyG, CPS, AEC and Torre de Comares Arquitectos s.l and 16 research centres

Impact of gaps in the asteroseismic characterization of pulsating stars. I. On the efficiency of pre-whitening

It is known that the observed distribution of frequencies in CoRoT and Kepler {\delta} Scuti stars has no parallelism with any theoretical model. Pre-whitening is a widespread technique in the analysis of time series with gaps from pulsating stars located in the classical instability strip such as {\delta} Scuti stars. However, some studies have pointed out that this technique might introduce biases in the results of the frequency analysis. This work aims at studying the biases that can result from pre-whitening in asteroseismology. The results will depend on the intrinsic range and distribution of frequencies of the stars. The periodic nature of the gaps in CoRoT observations, just in the range of the pulsational frequency content of the {\delta} Scuti stars, is shown to be crucial to determine their oscillation frequencies, the first step to perform asteroseismolgy of these objects. Hence, here we focus on the impact of pre-whitening on the asteroseismic characterization of {\delta} Scuti stars. We select a sample of 15 {\delta} Scuti stars observed by the CoRoT satellite, for which ultra-high quality photometric data have been obtained by its seismic channel. In order to study the impact on the asteroseismic characterization of {\delta} Scuti stars we perform the pre-whitening procedure on three datasets: gapped data, linearly interpolated data, and ARMA interpolated data. The different results obtained show that at least in some cases pre-whitening is not an efficient procedure for the deconvolution of the spectral window. therefore, in order to reduce the effect of the spectral window to the minimum it is necessary to interpolate with an algorithm that is aimed to preserve the original frequency content, and not only to perform a pre-whitening of the data.Comment: 27 pages, 47 figures Tables and typos fixe

Teegi: Tangible EEG Interface

We introduce Teegi, a Tangible ElectroEncephaloGraphy (EEG) Interface that enables novice users to get to know more about something as complex as brain signals, in an easy, en- gaging and informative way. To this end, we have designed a new system based on a unique combination of spatial aug- mented reality, tangible interaction and real-time neurotech- nologies. With Teegi, a user can visualize and analyze his or her own brain activity in real-time, on a tangible character that can be easily manipulated, and with which it is possible to interact. An exploration study has shown that interacting with Teegi seems to be easy, motivating, reliable and infor- mative. Overall, this suggests that Teegi is a promising and relevant training and mediation tool for the general public.Comment: to appear in UIST-ACM User Interface Software and Technology Symposium, Oct 2014, Honolulu, United State

Effect of clozapine on immunoglobulin M plasma levels

Clozapine is an atypical antipsychotic medication indicated for the treatment of patients who fail to respond to standard antipsychotic treatment. It possesses immunomodulatory properties and requires regular counts of white blood cells and absolute neutrophils. It has been reported to mediate several effects on humoral immunity, such as altering the levels of antibody-producing cytokines [Hinze-Selch et al. 1998]. Selective immunoglobulin M immunodeficiency (SIgMD) is a rare form of dysgammaglobulinaemia characterized by a selective, low level of immunoglobulin M (IgM) in conjunction with normal T cell numbers and function, and with no other identifiable immunodeficiencies. It can occur as either a primary or secondary condition and displays an estimated prevalence of 0.03%– 3%. Secondary SIgMD can be associated with malignancy, autoimmune disorders, gastrointestinal diseases and/or immunosuppressive treatments [Goldstein et al. 2006]..