A radiation-like era before inflation

We show that the semiclassical approximation to the Wheeler-DeWitt equation for the minisuperspace of a minimally coupled scalar field in the spatially flat de Sitter Universe prompts the existence of an initial power-law evolution driven by non-adiabatic terms from the gravitational wavefunction which act like radiation. This simple model hence describes the onset of inflation from a previous radiation-like expansion during which the cosmological constant is already present but subleading.Comment: LaTeX, 8 pages, no figures; final version to be published in JCA

The Operator Product Expansion for Wilson Loops and Surfaces in the Large N Limit

The operator product expansion for ``small'' Wilson loops in {\cal N}=4, d=4 SYM is studied. The OPE coefficients are calculated in the large N and g_{YM}^2 N limit by exploiting the AdS/CFT correspondence. We also consider Wilson surfaces in the (0,2), d=6 superconformal theory. In this case, we find that the UV divergent terms include a term proportional to the rigid string action.Comment: 22 pages LaTeX2e, using utarticle.cls (included) and AMS-LaTeX macro

Bosonic Quadratic Actions for 11D Supergravity on AdS_7/4 x S_4/7

We determine from 11D supergravity the quadratic bulk action for the physical bosonic fields relevant for the computation of correlation functions of normalized chiral operators in D=6, N=(0,2) and D=3, N=8 supersymmetric CFT in the large N limit, as dictated by the AdS/CFT duality conjecture.Comment: 16 pages, Plain TeX, no figures, requires AMS font files amssym.def and amssym.tex, a few typos correcte

Correlation Functions of Operators and Wilson Surfaces in the d=6, (0,2) Theory in the Large N Limit

We compute the two and three-point correlation functions of chiral primary operators in the large N limit of the (0,2), d=6 superconformal theory. We also consider the operator product expansion of Wilson surfaces in the (0,2) theory and compute the OPE coefficients of the chiral primary operators at large N from the correlation functions of surfaces.Comment: 34 pages, using utarticle.cls (included), array.sty, amsmath.sty, amsfonts.sty, latexsym.sty, epsfig. Bibtex style: utphys.bst (.bbl file included

Financial intermediation and growth : causality and causes without outliers

In a seminal paper, Levine et al. (J Monet Econ 46:31–77, 2000) provide cross-sectional evidence showing that financial development has pos- itive average impact on long-run growth, using a sample of 71 countries. We argue that the evidence is sensitive to the presence of outliers.info:eu-repo/semantics/publishedVersio

Quantifying atrial anatomy uncertainty from clinical data and its impact on electro-physiology simulation predictions

Patient-specific computational models of structure and function are increasingly being used to diagnose disease and predict how a patient will respond to therapy. Models of anatomy are often derived after segmentation of clinical images or from mapping systems which are affected by image artefacts, resolution and contrast. Quantifying the impact of uncertain anatomy on model predictions is important, as models are increasingly used in clinical practice where decisions need to be made regardless of image quality. We use a Bayesian probabilistic approach to estimate the anatomy and to quantify the uncertainty about the shape of the left atrium derived from Cardiac Magnetic Resonance images. We show that we can quantify uncertain shape, encode uncertainty about the left atrial shape due to imaging artefacts, and quantify the effect of uncertain shape on simulations of left atrial activation times

Entanglement entropy of Wilson surfaces from bubbling geometries in M-theory

We consider solutions of eleven-dimensional supergravity constructed in [1,2] that are half-BPS, locally asymptotic to $AdS_7\times S^4$ and are the holographic dual of heavy Wilson surfaces in the six-dimensional $(2,0)$ theory. Using these bubbling solutions we calculate the holographic entanglement entropy for a spherical entangling surface in the presence of a planar Wilson surface. In addition, we calculate the holographic stress tensor and, by evaluating the on-shell supergravity action, the expectation value of the Wilson surface operator.Comment: 42 pages, 4 figures, v2: minor modification

Predicting Atrial Fibrillation Recurrence by Combining Population Data and Virtual Cohorts of Patient-Specific Left Atrial Models.

BACKGROUND: Current ablation therapy for atrial fibrillation is suboptimal, and long-term response is challenging to predict. Clinical trials identify bedside properties that provide only modest prediction of long-term response in populations, while patient-specific models in small cohorts primarily explain acute response to ablation. We aimed to predict long-term atrial fibrillation recurrence after ablation in large cohorts, by using machine learning to complement biophysical simulations by encoding more interindividual variability. METHODS: Patient-specific models were constructed for 100 atrial fibrillation patients (43 paroxysmal, 41 persistent, and 16 long-standing persistent), undergoing first ablation. Patients were followed for 1 year using ambulatory ECG monitoring. Each patient-specific biophysical model combined differing fibrosis patterns, fiber orientation maps, electrical properties, and ablation patterns to capture uncertainty in atrial properties and to test the ability of the tissue to sustain fibrillation. These simulation stress tests of different model variants were postprocessed to calculate atrial fibrillation simulation metrics. Machine learning classifiers were trained to predict atrial fibrillation recurrence using features from the patient history, imaging, and atrial fibrillation simulation metrics. RESULTS: We performed 1100 atrial fibrillation ablation simulations across 100 patient-specific models. Models based on simulation stress tests alone showed a maximum accuracy of 0.63 for predicting long-term fibrillation recurrence. Classifiers trained to history, imaging, and simulation stress tests (average 10-fold cross-validation area under the curve, 0.85±0.09; recall, 0.80±0.13; precision, 0.74±0.13) outperformed those trained to history and imaging (area under the curve, 0.66±0.17) or history alone (area under the curve, 0.61±0.14). CONCLUSION: A novel computational pipeline accurately predicted long-term atrial fibrillation recurrence in individual patients by combining outcome data with patient-specific acute simulation response. This technique could help to personalize selection for atrial fibrillation ablation

Postdischarge symptoms and rehabilitation needs in survivors of COVID‐19 infection: A cross‐sectional evaluation

Background: There is currently very limited information on the nature and prevalence of post‐COVID‐19 symptoms after hospital discharge. Methods: A purposive sample of 100 survivors discharged from a large University hospital were assessed 4 to 8 weeks after discharge by a multidisciplinary team of rehabilitation professionals using a specialist telephone screening tool designed to capture symptoms and impact on daily life. EQ‐5D‐5L telephone version was also completed. Results: Participants were between 29 and 71 days (mean 48 days) postdischarge from hospital. Thirty‐two participants required treatment in intensive care unit (ICU group) and 68 were managed in hospital wards without needing ICU care (ward group). New illness‐related fatigue was the most common reported symptom by 72% participants in ICU group and 60.3% in ward group. The next most common symptoms were breathlessness (65.6% in ICU group and 42.6% in ward group) and psychological distress (46.9% in ICU group and 23.5% in ward group). There was a clinically significant drop in EQ5D in 68.8% in ICU group and in 45.6% in ward group. Conclusions: This is the first study from the United Kingdom reporting on postdischarge symptoms. We recommend planning rehabilitation services to manage these symptoms appropriately and maximize the functional return of COVID‐19 survivors