Finite-size scaling of heavy-light mesons

We study the finite-size scaling of heavy-light mesons in the static limit. The most relevant effects are due to the pseudo-Goldstone boson cloud. In the HMChPT framework we compute two-point functions of left current densitities as well as pseudoscalar densitites for the cases in which some or all of them lay in the epsilon-regime. As expected, finite volume dependence turns out to be significant in this regime and can be predicted in the effective theory in terms of the infinite-volume low-energy couplings. These results might be relevant for extraction of heavy-light meson properties from lattice simulations.Comment: 7 pages, 2 figures, Contributed to 27th International Symposium on Lattice Field Theory, Beijing, China, 26 - 31 Jul 200

Mapping the geometry of the F4 group

In this paper we present a construction of the compact form of the exceptional Lie group F4 by exponentiating the corresponding Lie algebra f4. We realize F4 as the automorphisms group of the exceptional Jordan algebra, whose elements are 3 x 3 hermitian matrices with octonionic entries. We use a parametrization which generalizes the Euler angles for SU(2) and is based on the fibration of F4 via a Spin(9) subgroup as a fiber. This technique allows us to determine an explicit expression for the Haar invariant measure on the F4 group manifold. Apart from shedding light on the structure of F4 and its coset manifold OP2=F4/Spin(9), the octonionic projective plane, these results are a prerequisite for the study of E6, of which F4 is a (maximal) subgroup.Comment: 50 pages; some typos correcte

Mapping the geometry of the E6 group

In this paper we present a construction for the compact form of the exceptional Lie group E6 by exponentiating the corresponding Lie algebra e6, which we realize as the the sum of f4, the derivations of the exceptional Jordan algebra J3 of dimension 3 with octonionic entries, and the right multiplication by the elements of J3 with vanishing trace. Our parametrization is a generalization of the Euler angles for SU(2) and it is based on the fibration of E6 via a F4 subgroup as the fiber. It makes use of a similar construction we have performed in a previous article for F4. An interesting first application of these results lies in the fact that we are able to determine an explicit expression for the Haar invariant measure on the E6 group manifold.Comment: 30 page

Finite-size scaling for the left-current correlator with non-degenerate quark masses

We study the volume dependence of the left-current correlator with non-degenerate quark masses to next-to-leading order in the chiral expansion. We consider three possible regimes: all quark masses are in the $\epsilon$-regime, all are in the $p$-regime and a mixed-regime where the lighest quark masses satisfy $m_v \Sigma V \leq 1$ while the heavier $m_s \Sigma V \gg 1$. These results can be used to match lattice QCD and the Chiral Effective Theory in a large but finite box in which the Compton wavelength of the lightest pions is of the order of the box size. We consider both the full and partially-quenched results.Comment: 27 pages, 4 figure

Training a machine learning classifier to identify ADHD based on real-world clinical data from medical records

The diagnostic process of attention deficit hyperactivity disorder (ADHD) is complex and relies on criteria sensitive to subjective biases. This may cause significant delays in appropriate treatment initiation. An automated analysis relying on subjective and objective measures might not only simplify the diagnostic process and reduce the time to diagnosis, but also improve reproducibility. While recent machine learning studies have succeeded at distinguishing ADHD from healthy controls, the clinical process requires differentiating among other or multiple psychiatric conditions. We trained a linear support vector machine (SVM) classifier to detect participants with ADHD in a population showing a broad spectrum of psychiatric conditions using anonymized data from clinical records (N = 299 participants). We differentiated children and adolescents with ADHD from those not having the condition with an accuracy of 66.1%. SVM using single features showed slight differences between features and overlapping standard deviations of the achieved accuracies. An automated feature selection achieved the best performance using a combination 19 features. Real-world clinical data from medical records can be used to automatically identify individuals with ADHD among help-seeking individuals using machine learning. The relevant diagnostic information can be reduced using an automated feature selection without loss of performance. A broad combination of symptoms across different domains, rather than specific domains, seems to indicate an ADHD diagnosis

B-meson spectroscopy in HQET at order 1/m

35 pages, 14 tables, 17 figures; Introduction extended and typos corrected. Version accepted for publication in PRDWe present a study of the B spectrum performed in the framework of Heavy Quark Effective Theory expanded to next-to-leading order in 1/m and non-perturbative in the strong coupling. Our analyses have been performed on Nf=2 lattice gauge field ensembles corresponding to three different lattice spacings and a wide range of pion masses. We obtain the Bs-meson mass and hyperfine splittings of the B- and Bs-mesons that are in good agreement with the experimental values and examine the mass difference m_{Bs}-m_B as a further cross-check of our previous estimate of the b-quark mass. We also report on the mass splitting between the first excited state and the ground state in the B and Bs systems

a combined ecological momentary assessment and fMRI study

Regulation of emotions is necessary for successful attainment of short-term and long-term goals. However, over-regulation may also have its costs. In anorexia nervosa (AN), forgoing food intake despite emaciation and endocrine signals that promote eating is an example of “too much” self-control. Here we investigated whether voluntary emotion regulation in AN patients comes with associated disorder-relevant costs. Thirty-five patients with acute AN and thirty-five age-matched healthy controls (HCs) performed an established emotion regulation paradigm during functional magnetic resonance imaging after an overnight fast. The task required reducing emotions induced by positively valenced pictures via distancing. We calculated a neural regulation score from responses recorded in a reward-related brain region of interest (ventral striatum; VS) by subtracting activation measured on “positive distance” trials from that elicited under the “positive watch” (baseline) condition. Complementing the imaging data, we used ecological momentary assessment (EMA) to probe disorder-related rumination and affect six times/day for 2 weeks following the scanning session. The neural regulation score indicating reduced VS activation during emotion regulation was used as a predictor in hierarchical linear models with EMA measures as outcomes. No group differences in neural activity were found for the main contrasts of the task. However, regulation of VS activity was associated with increased body-related rumination and increased negative affect in AN, but not in HC. In line with this finding, correlational analysis with longitudinal BMI measurements revealed a link between greater VS regulation and poorer treatment outcome after 60 and 90 days. Together, these results identify a neural correlate of altered emotion regulation in AN, which seems to be detrimental to psychological well-being and may interfere with recovery

Preserved white matter microstructure in young patients with anorexia nervosa?

A massive but reversible reduction of cortical thickness and subcortical gray matter (GM) volumes in Anorexia Nervosa (AN) has been recently reported. However, the literature on alterations in white matter (WM) volume and microstructure changes in both acutely underweight AN (acAN) and after recovery (recAN) is sparse and results are inconclusive. Here, T1-weighted and diffusion-weighted MRI data in a sizable sample of young and medication-free acAN (n = 35), recAN (n = 32), and age-matched female healthy controls (HC, n = 62) were obtained. For analysis, a well-validated global probabilistic tractography reconstruction algorithm including rigorous motion correction implemented in FreeSurfer: TRACULA (TRActs Constrained by UnderLying Anatomy) were used. Additionally, a clustering algorithm and a multivariate pattern classification technique to WM metrics to predict group membership were applied. No group differences in either WM volume or WM microstructure were detected with standard analysis procedures either in acAN or recAN relative to HC after controlling for the number of performed statistical tests. These findings were not affected by age, IQ, or psychiatric symptoms. While cluster analysis was unsuccessful at discriminating between groups, multivariate pattern classification showed some ability to separate acAN from HC (but not recAN from HC). However, these results were not compatible with a straightforward hypothesis of impaired WM microstructure. The current findings suggest that WM integrity is largely preserved in non-chronic AN. This finding stands in contrast to findings in GM, but may help to explain the relatively intact cognitive performance of young patients with AN and provide the basis for the fast recovery of GM structures. Hum Brain Mapp 37:4069–4083, 2016. © 2016 Wiley Periodicals, Inc

STRAS: a new high time resolution aerosol sampler for PIXE analysis

The joint use of hourly resolution sampling and analyses with accelerated ion beams such as Particle Induced X-ray Emission (PIXE) technique has allowed the measurement of hourly temporal patterns of particulate matter (PM) composition at many sites in different parts of the world. The demand within the scientific community for this type of analysis has been continuously increasing in recent years, but hourly resolution samplers suitable for PIXE analysis are now discontinued and/or suffer from some technical limitations. In this framework, a new hourly sampler, STRAS (Size and Time Resolved Aerosol Sampler), was developed for the collection of PM10, PM2.5 or PM1. It allows automatic sequential sampling of up to 168 hourly samples (1 week), it is mechanically robust, compact, and easily transportable. To increase PIXE sensitivity, each sample is concentrated on a small surface area on a polycarbonate membrane. The comparison between the elemental concentrations retrieved by STRAS samples and samples collected using a standard sequential sampler operated in parallel shows a very good agreement; indeed, if both the samplers use the same kind of membrane, the concentrations of all detected elements are in agreement within 10 %