Subleading Shape Functions in Inclusive B Decays

The contributions of subleading shape functions to inclusive decay distributions of B mesons are derived from a systematic two-step matching of QCD current correlators onto soft-collinear and heavy-quark effective theory. At tree-level, the results can be expressed in terms of forward matrix elements of bi-local light-cone operators. Four-quark operators, which arise at O(g^2), are included. Their effects can be absorbed entirely into a redefinition of other shape functions. Our results are in disagreement with some previous studies of subleading shape-function effects in the literature. A numerical analysis of B->X_u+l+nu decay distributions suggests that power corrections are small, with the possible exception of the endpoint region of the charged-lepton energy spectrum.Comment: 22 pages, 2 figures; several typos corrected; version published in JHE

Validation of machine learning-based assessment of major depressive disorder from paralinguistic speech characteristics in routine care

New developments in machine learning-based analysis of speech can be hypothesized to facilitate the long-term monitoring of major depressive disorder (MDD) during and after treatment. To test this hypothesis, we collected 550 speech samples from telephone-based clinical interviews with 267 individuals in routine care. With this data, we trained and evaluated a machine learning system to identify the absence/presence of a MDD diagnosis (as assessed with the Structured Clinical Interview for DSM-IV) from paralinguistic speech characteristics. Our system classified diagnostic status of MDD with an accuracy of 66% (sensitivity: 70%, specificity: 62%). Permutation tests indicated that the machine learning system classified MDD significantly better than chance. However, deriving diagnoses from cut-off scores of common depression scales was superior to the machine learning system with an accuracy of 73% for the Hamilton Rating Scale for Depression (HRSD), 74% for the Quick Inventory of Depressive Symptomatology–Clinician version (QIDS-C), and 73% for the depression module of the Patient Health Questionnaire (PHQ-9). Moreover, training a machine learning system that incorporated both speech analysis and depression scales resulted in accuracies between 73 and 76%. Thus, while findings of the present study demonstrate that automated speech analysis shows the potential of identifying patterns of depressed speech, it does not substantially improve the validity of classifications from common depression scales. In conclusion, speech analysis may not yet be able to replace common depression scales in clinical practice, since it cannot yet provide the necessary accuracy in depression detection. This trial is registered with DRKS00023670

EASIX for Prediction of Outcome in Hospitalized SARS-CoV-2 Infected Patients

Background: The coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and has evoked a pandemic that challenges public health-care systems worldwide. Endothelial cell dysfunction plays a key role in pathophysiology, and simple prognosticators may help to optimize allocation of limited resources. Endothelial activation and stress index (EASIX) is a validated predictor of endothelial complications and outcome after allogeneic stem cell transplantation. Aim of this study was to test if EASIX could predict life-threatening complications in patients with COVID-19. Methods: SARS-CoV-2-positive, hospitalized patients were enrolled onto a prospective non-interventional register study (n=100). Biomarkers were assessed at hospital admission. Primary endpoint was severe course of disease (mechanical ventilation and/or death, V/D). Results were validated in 126 patients treated in two independent institutions. Results: EASIX at admission was a strong predictor of severe course of the disease (odds ratio for a two-fold change 3.4, 95%CI 1.8-6.3, p<0.001), time to V/D (hazard ratio (HR) for a two-fold change 2.0, 95%CI 1.5-2.6, p<0.001) as well as survival (HR for a two-fold change 1.7, 95%CI 1.2-2.5, p=0.006). The effect was retained in multivariable analysis adjusting for age, gender, and comorbidities and could be validated in the independent cohort. At hospital admission EASIX correlated with increased suppressor of tumorigenicity-2, soluble thrombomodulin, angiopoietin-2, CXCL8, CXCL9 and interleukin-18, but not interferon-alpha. Conclusion: EASIX is a validated predictor of COVID19 outcome and an easy-to-access tool to segregate patients in need for intensive surveillance

Association between infectious burden, socioeconomic status, and ischemic stroke

Background and aims: Infectious diseases contribute to stroke risk, and are associated with socioeconomic status (SES). We tested the hypotheses that the aggregate burden of infections increases the risk of ischemic stroke (IS) and partly explains the association between low SES and ischemic stroke. Methods: In a case-control study with 470 ischemic stroke patients and 809 age- and sex-matched controls, randomly selected from the population, antibodies against the periodontal microbial agents Aggregatibacter actinomycetemcomitans and Porphyromonas gingivalis, against Chlamydia pneumonia, Mycoplasma pneumoniae (IgA and IgG), and CagA-positive Helicobacter pylori (IgG) were assessed. Results: IgA seropositivity to two microbial agents was significantly associated with IS after adjustment for SES (OR 1.45 95% CI 1.01-2.08), but not in the fully adjusted model (OR 1.32 95% CI 0.86-2.02). By trend, cumulative IgA seropositivity was associated with stroke due to large vessel disease (LVD) after full adjustment (OR 1.88, 95% CI 0.96e3.69). Disadvantageous childhood SES was associated with higher cumulative seropositivity in univariable analyses, however, its strong impact on stroke risk was not influenced by seroepidemiological data in the multivariable model. The strong association between adulthood SES and stroke was rendered nonsignificant when factors of dental care were adjusted for. Conclusions: Infectious burden assessed with five microbial agents did not independently contribute to ischemic stroke consistently, but may contribute to stroke due to LVD. High infectious burden may not explain the association between childhood SES and stroke risk. Lifestyle factors that include dental negligence may contribute to the association between disadvantageous adulthood SES and stroke. (C) 2016 Elsevier Ireland Ltd. All rights reserved.Peer reviewe

There Goes the Neighborhood? – People‘s Attitudes and the Effects of Immigration to Australia

This paper compares the effects of immigration flows on economic outcomes and crime levels to the public opinion about these effects using individual and regional data for Australia. We employ an instrumental variables strategy to account for non-random location choices of immigrants and find that immigration has no adverse effects on regional unemployment rates, median incomes, or crime levels. This result is in line with the economic effects that people typically expect but does not confirm the public opinion about the contribution of immigration to higher crime levels, suggesting that Australians overestimate the effect of immigration on crime

Dynamical mean-field theory for bosons

We discuss the recently developed bosonic dynamical mean-field (B-DMFT) framework, which maps a bosonic lattice model onto the selfconsistent solution of a bosonic impurity model with coupling to a reservoir of normal and condensed bosons. The effective impurity action is derived in several ways: (i) as an approximation to the kinetic energy functional of the lattice problem, (ii) using a cavity approach, and (iii) by using an effective medium approach based on adding a one-loop correction to the selfconsistently defined condensate. To solve the impurity problem, we use a continuous-time Monte Carlo algorithm based on a sampling of a perturbation expansion in the hybridization functions and the condensate wave function. As applications of the formalism we present finite temperature B-DMFT phase diagrams for the bosonic Hubbard model on a 3d cubic and 2d square lattice, the condensate order parameter as a function of chemical potential, critical exponents for the condensate, the approach to the weakly interacting Bose gas regime for weak repulsions, and the kinetic energy as a function of temperature.Comment: 26 pages, 19 figure

Electroweak Gauge-Boson Production at Small q_T: Infrared Safety from the Collinear Anomaly

Using methods from effective field theory, we develop a novel, systematic framework for the calculation of the cross sections for electroweak gauge-boson production at small and very small transverse momentum q_T, in which large logarithms of the scale ratio M_V/q_T are resummed to all orders. These cross sections receive logarithmically enhanced corrections from two sources: the running of the hard matching coefficient and the collinear factorization anomaly. The anomaly leads to the dynamical generation of a non-perturbative scale q_* ~ M_V e^{-const/\alpha_s(M_V)}, which protects the processes from receiving large long-distance hadronic contributions. Expanding the cross sections in either \alpha_s or q_T generates strongly divergent series, which must be resummed. As a by-product, we obtain an explicit non-perturbative expression for the intercept of the cross sections at q_T=0, including the normalization and first-order \alpha_s(q_*) correction. We perform a detailed numerical comparison of our predictions with the available data on the transverse-momentum distribution in Z-boson production at the Tevatron and LHC.Comment: 34 pages, 9 figure

Complete-Graph Tensor Network States: A New Fermionic Wave Function Ansatz for Molecules

We present a new class of tensor network states that are specifically designed to capture the electron correlation of a molecule of arbitrary structure. In this ansatz, the electronic wave function is represented by a Complete-Graph Tensor Network (CGTN) ansatz which implements an efficient reduction of the number of variational parameters by breaking down the complexity of the high-dimensional coefficient tensor of a full-configuration-interaction (FCI) wave function. We demonstrate that CGTN states approximate ground states of molecules accurately by comparison of the CGTN and FCI expansion coefficients. The CGTN parametrization is not biased towards any reference configuration in contrast to many standard quantum chemical methods. This feature allows one to obtain accurate relative energies between CGTN states which is central to molecular physics and chemistry. We discuss the implications for quantum chemistry and focus on the spin-state problem. Our CGTN approach is applied to the energy splitting of states of different spin for methylene and the strongly correlated ozone molecule at a transition state structure. The parameters of the tensor network ansatz are variationally optimized by means of a parallel-tempering Monte Carlo algorithm

Ab initio study of step formation and self-diffusion on Ag(100)

Using the plane wave pseudopotential method we performed density functional theory calculations on the stability of steps and self-diffusion processes on Ag(100). Our calculated step formation energies show that the {111}-faceted step is more stable than the {110}-faceted step. In accordance with experimental observations we find that the equilibrium island shape should be octagonal very close to a square with predominately {111}-faceted steps. For the (100) surface of fcc metals atomic migration proceeds by a hopping or an exchange process. For Ag(100) we find that adatoms diffuse across flat surfaces preferentially by hopping. Adatoms approaching the close-packed {111}-faceted step edges descend from the upper terrace to the lower level by an atomic exchange with an energy barrier almost identical to the diffusion barrier on flat surface regions. Thus, within our numerical accuracy (approx +- 0.05 eV) there is no additional step-edge barrier to descent. This provides a natural explanation for the experimental observations of the smooth two-dimensional growth in homoepitaxy of Ag(100). Inspection of experimental results of other fcc crystal surfaces indicates that our result holds quite generally.Comment: 10 pages, 9 figures. Submitted to Phys. Rev B (October 31, 1996

EASIX for Prediction of Outcome in Hospitalized SARS-CoV-2 Infected Patients

BackgroundThe coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and has evoked a pandemic that challenges public health-care systems worldwide. Endothelial cell dysfunction plays a key role in pathophysiology, and simple prognosticators may help to optimize allocation of limited resources. Endothelial activation and stress index (EASIX) is a validated predictor of endothelial complications and outcome after allogeneic stem cell transplantation. Aim of this study was to test if EASIX could predict life-threatening complications in patients with COVID-19.MethodsSARS-CoV-2-positive, hospitalized patients were enrolled onto a prospective non-interventional register study (n=100). Biomarkers were assessed at hospital admission. Primary endpoint was severe course of disease (mechanical ventilation and/or death, V/D). Results were validated in 126 patients treated in two independent institutions.ResultsEASIX at admission was a strong predictor of severe course of the disease (odds ratio for a two-fold change 3.4, 95%CI 1.8-6.3, p&lt;0.001), time to V/D (hazard ratio (HR) for a two-fold change 2.0, 95%CI 1.5-2.6, p&lt;0.001) as well as survival (HR for a two-fold change 1.7, 95%CI 1.2-2.5, p=0.006). The effect was retained in multivariable analysis adjusting for age, gender, and comorbidities and could be validated in the independent cohort. At hospital admission EASIX correlated with increased suppressor of tumorigenicity-2, soluble thrombomodulin, angiopoietin-2, CXCL8, CXCL9 and interleukin-18, but not interferon-alpha.ConclusionEASIX is a validated predictor of COVID19 outcome and an easy-to-access tool to segregate patients in need for intensive surveillance