Spectral representation of the pentagon diagram amplitude

A method developed in two previous papers is used to derive a double spectral representation with Mandelstam boundary for the pentagon diagram amplitude for the production process A B → C D N. Restrictions on the masses and kinematic invariants for which this representation is valid are found and it is discussed how a representation can be obtained for wider ranges of these variables. Finally, a comparison is made with the results of other authors

Double spectral representations of single loop amptitudes with k vertices:k ≥ 4

A method developed in several previous papers is combined with the method of induction to derive double dispersion relations, with Mandelstam boundary, for the class of single loop amplitudes with four or more vertices. The spectral functions are expressed as integral representations and restrictions on the masses and kinematic invariants for which dispersion relations are valid are found. It is also discussed how representations for the low order single loop amplitudes can be obtained for wider ranges of these variables

Theory and computation of covariant Lyapunov vectors

Lyapunov exponents are well-known characteristic numbers that describe growth rates of perturbations applied to a trajectory of a dynamical system in different state space directions. Covariant (or characteristic) Lyapunov vectors indicate these directions. Though the concept of these vectors has been known for a long time, they became practically computable only recently due to algorithms suggested by Ginelli et al. [Phys. Rev. Lett. 99, 2007, 130601] and by Wolfe and Samelson [Tellus 59A, 2007, 355]. In view of the great interest in covariant Lyapunov vectors and their wide range of potential applications, in this article we summarize the available information related to Lyapunov vectors and provide a detailed explanation of both the theoretical basics and numerical algorithms. We introduce the notion of adjoint covariant Lyapunov vectors. The angles between these vectors and the original covariant vectors are norm-independent and can be considered as characteristic numbers. Moreover, we present and study in detail an improved approach for computing covariant Lyapunov vectors. Also we describe, how one can test for hyperbolicity of chaotic dynamics without explicitly computing covariant vectors.Comment: 21 pages, 5 figure

Arrhythmic risk prediction in arrhythmogenic right ventricular cardiomyopathy : external validation of the arrhythmogenic right ventricular cardiomyopathy risk calculator

Aims: Arrhythmogenic right ventricular cardiomyopathy (ARVC) causes ventricular arrhythmias (VAs) and sudden cardiac death (SCD). In 2019, a risk prediction model that estimates the 5-year risk of incident VAs in ARVC was developed (ARVCrisk.com). This study aimed to externally validate this prediction model in a large international multicentre cohort and to compare its performance with the risk factor approach recommended for implantable cardioverter-defibrillator (ICD) use by published guidelines and expert consensus. Methods and results: In a retrospective cohort of 429 individuals from 29 centres in North America and Europe, 103 (24%) experienced sustained VA during a median follow-up of 5.02 (2.05-7.90) years following diagnosis of ARVC. External validation yielded good discrimination [C-index of 0.70 (95% confidence interval-CI 0.65-0.75)] and calibration slope of 1.01 (95% CI 0.99-1.03). Compared with the three published consensus-based decision algorithms for ICD use in ARVC (Heart Rhythm Society consensus on arrhythmogenic cardiomyopathy, International Task Force consensus statement on the treatment of ARVC, and American Heart Association guidelines for VA and SCD), the risk calculator performed better with a superior net clinical benefit below risk threshold of 35%. Conclusion: Using a large independent cohort of patients, this study shows that the ARVC risk model provides good prognostic information and outperforms other published decision algorithms for ICD use. These findings support the use of the model to facilitate shared decision making regarding ICD implantation in the primary prevention of SCD in ARVC

Measurement of B(D_s+ -> mu+ nu_mu)/B(D_s+ -> phi mu+ nu_mu) and Determination of the Decay Constant f_{D_s}

We have observed $23.2 \pm 6.0_{-0.9}^{+1.0}$ purely-leptonic decays of $D_s^+ -> \mu^+ \nu_\mu$ from a sample of muonic one prong decay events detected in the emulsion target of Fermilab experiment E653. Using the $D_s^+ -> \phi \mu^+ \nu_\mu$ yield measured previously in this experiment, we obtain $B(D_s^+ --> \mu^+ \nu_\mu) / B(D_s^+ --> \phi \mu^+ \nu_\mu) =0.16 \pm 0.06 \pm 0.03$. In addition, we extract the decay constant $f_{D_s}=194 \pm 35 \pm 20 \pm 14 MeV$.Comment: 15 pages including one figur

APOSTEL 2.0 recommendations for reporting quantitative optical coherence tomography studies

OBJECTIVE: To update the consensus recommendations for reporting of quantitative optical coherence tomography (OCT) study results, thus revising the previously published Advised Protocol for OCT Study Terminology and Elements (APOSTEL) recommendations. METHODS: To identify studies reporting quantitative OCT results, we performed a PubMed search for the terms “quantitative” and “optical coherence tomography” from 2015 to 2017. Corresponding authors of the identified publications were invited to provide feedback on the initial APOSTEL recommendations via online surveys following the principle of a modified Delphi method. The results were evaluated and discussed by a panel of experts, and changes to the initial recommendations were proposed. A final survey was recirculated among the corresponding authors to obtain a majority vote on the proposed changes. RESULTS: One hundred sixteen authors participated in the surveys, resulting in 15 suggestions, of which 12 were finally accepted and incorporated into an updated 9-point-checklist. We harmonized the nomenclature of the outer retinal layers, added the exact area of measurement to the description of volume scans; we suggested reporting device-specific features. We advised to address potential bias in manual segmentation or manual correction of segmentation errors. References to specific reporting guidelines and room light conditions were removed. The participants’ consensus with the recommendations increased from 80% for the previous APOSTEL version to greater than 90%. CONCLUSIONS: The modified Delphi method resulted in an expert-led guideline (evidence class III, GRADE criteria) concerning study protocol, acquisition device, acquisition settings, scanning protocol, fundoscopic imaging, post-acquisition data selection, post-acquisition analysis, nomenclature and abbreviations, and statistical approach. It will still be essential to update these recommendations to new research and practices regularly