An algorithm for diagnosing IgE-mediated food allergy in study participants who do not undergo food challenge.

BACKGROUND: Food allergy diagnosis in clinical studies can be challenging. Oral food challenges (OFC) are time-consuming, carry some risk and may, therefore, not be acceptable to all study participants. OBJECTIVE: To design and evaluate an algorithm for detecting IgE-mediated food allergy in clinical study participants who do not undergo OFC. METHODS: An algorithm for trial participants in the Barrier Enhancement for Eczema Prevention (BEEP) study who were unwilling or unable to attend OFC was developed. BEEP is a pragmatic, multi-centre, randomized-controlled trial of daily emollient for the first year of life for primary prevention of eczema and food allergy in high-risk infants (ISRCTN21528841). We built on the European iFAAM consensus guidance to develop a novel food allergy diagnosis algorithm using available information on previous allergenic food ingestion, food reaction(s) and sensitization status. This was implemented by a panel of food allergy experts blind to treatment allocation and OFC outcome. We then evaluated the algorithm's performance in both BEEP and Enquiring About Tolerance (EAT) study participants who did undergo OFC. RESULTS: In 31/69 (45%) BEEP and 44/55 (80%) EAT study control group participants who had an OFC the panel felt confident enough to categorize children as "probable food allergy" or "probable no food allergy". Algorithm-derived panel decisions showed high sensitivity 94% (95%CI 68, 100) BEEP; 90% (95%CI 72, 97) EAT and moderate specificity 67% (95%CI 39, 87) BEEP; 67% (95%CI 39, 87) EAT. Sensitivity and specificity were similar when all BEEP and EAT participants with OFC outcome were included. CONCLUSION: We describe a new algorithm with high sensitivity for IgE-mediated food allergy in clinical study participants who do not undergo OFC. CLINICAL RELEVANCE: This may be a useful tool for excluding food allergy in future clinical studies where OFC is not conducted

Alexander representation of tangles

A tangle is an oriented 1-submanifold of the cylinder whose endpoints lie on the two disks in the boundary of the cylinder. Using an algebraic tool developed by Lescop, we extend the Burau representation of braids to a functor from the category of oriented tangles to the category of Z[t,t^{-1}]-modules. For (1,1)-tangles (i.e., tangles with one endpoint on each disk) this invariant coincides with the Alexander polynomial of the link obtained by taking the closure of the tangle. We use the notion of plat position of a tangle to give a constructive proof of invariance in this case.Comment: 13 pages, 5 figure

Debris cover and surface melt at a temperate maritime alpine glacier: Franz Josef Glacier, New Zealand

Melt rates on glaciers are strongly influenced by the presence of supraglacial debris, which can either enhance or reduce ablation relative to bare ice. Most recently, Franz Josef Glacier has entered into a phase of strong retreat and downwasting, with the increasing emergence of debris on the surface in the ablation zone. Previously at Franz Josef Glacier, melt has only been measured on bare ice. During February 2012, a network of 11 ablation stakes was drilled into locations of varying supraglacial debris thickness on the lower glacier. Mean ablation rates over 9 days varied over the range 1.2–10.1 cm d−1, and were closely related to debris thickness. Concomitant observations of air temperature allowed the application of a degree-day approach to the calculation of melt rates, with air temperature providing a strong indicator of melt. Degree-day factors (d f) varied over the range 1.1–8.1 mm d−1 °C−1 (mean of 4.4 mm d−1 °C−1), comparable with rates reported in other studies. Mapping of the current debris cover revealed 0.7 km2 of the 4.9 km2 ablation zone surface was debris-covered, with thicknesses ranging 1–50 cm. Based on measured debris thicknesses and d f, ablation on debris-covered areas of the glacier is reduced by a total of 41% which equates to a 6% reduction in melt overall across the entire ablation zone. This study highlights the usefulness of a short-term survey to gather representative ablation data, consistent with numerous overseas ablation studies on debris-covered glaciers

On the Performance Prediction of BLAS-based Tensor Contractions

Tensor operations are surging as the computational building blocks for a variety of scientific simulations and the development of high-performance kernels for such operations is known to be a challenging task. While for operations on one- and two-dimensional tensors there exist standardized interfaces and highly-optimized libraries (BLAS), for higher dimensional tensors neither standards nor highly-tuned implementations exist yet. In this paper, we consider contractions between two tensors of arbitrary dimensionality and take on the challenge of generating high-performance implementations by resorting to sequences of BLAS kernels. The approach consists in breaking the contraction down into operations that only involve matrices or vectors. Since in general there are many alternative ways of decomposing a contraction, we are able to methodically derive a large family of algorithms. The main contribution of this paper is a systematic methodology to accurately identify the fastest algorithms in the bunch, without executing them. The goal is instead accomplished with the help of a set of cache-aware micro-benchmarks for the underlying BLAS kernels. The predictions we construct from such benchmarks allow us to reliably single out the best-performing algorithms in a tiny fraction of the time taken by the direct execution of the algorithms.Comment: Submitted to PMBS1

Metastability of Asymptotically Well-Behaved Potential Games

One of the main criticisms to game theory concerns the assumption of full rationality. Logit dynamics is a decentralized algorithm in which a level of irrationality (a.k.a. "noise") is introduced in players' behavior. In this context, the solution concept of interest becomes the logit equilibrium, as opposed to Nash equilibria. Logit equilibria are distributions over strategy profiles that possess several nice properties, including existence and uniqueness. However, there are games in which their computation may take time exponential in the number of players. We therefore look at an approximate version of logit equilibria, called metastable distributions, introduced by Auletta et al. [SODA 2012]. These are distributions that remain stable (i.e., players do not go too far from it) for a super-polynomial number of steps (rather than forever, as for logit equilibria). The hope is that these distributions exist and can be reached quickly by logit dynamics. We identify a class of potential games, called asymptotically well-behaved, for which the behavior of the logit dynamics is not chaotic as the number of players increases so to guarantee meaningful asymptotic results. We prove that any such game admits distributions which are metastable no matter the level of noise present in the system, and the starting profile of the dynamics. These distributions can be quickly reached if the rationality level is not too big when compared to the inverse of the maximum difference in potential. Our proofs build on results which may be of independent interest, including some spectral characterizations of the transition matrix defined by logit dynamics for generic games and the relationship of several convergence measures for Markov chains

Anakinra treats fulminant myocarditis from Neisseria meningitidis septicaemia and haemophagocytic lymphohistiocytosis: a case report

Background: Fulminant myocarditis is a life-threatening condition characterized by acute cardiac dysfunction requiring pharmacological or mechanical circulatory support. Haemophagocytic lymphohistiocytosis (HLH) is an uncommon state of immune dysregulation and overactivation. Inflammation mediated by interleukin-1 (IL-1) is thought to play a role in the pathogenesis of myocarditis and HLH, and there is some evidence that the IL-1 receptor antagonist Anakinra may play a role in treating both these conditions. Case summary: A 26-year-old previously healthy male presented to the Emergency Department with a 3-day history of malaise, headache, vomiting, diarrhoea, and fever. He was profoundly hypotensive on arrival, diagnosed with septic shock, and commenced on broad-spectrum antibiotics and vasopressors. Blood tests showed lymphopenia, thrombocytopenia, low fibrinogen and elevated high sensitivity troponin T, ferritin, and C-reactive protein. Echocardiography demonstrated severely impaired biventricular systolic function and a diagnosis of fulminant myocarditis was made. His condition deteriorated and he required intubation and additional inotropic support. A diagnosis of HLH was made and he was commenced on Anakinra and Methylprednisolone. His condition improved rapidly thereafter. Polymerase chain reaction testing subsequently confirmed infection with Neisseria meningitidis. Discussion: In this case, fulminant myocarditis and HLH were life-threatening manifestations of meningococcal septicaemia, and the patient’s condition improved rapidly following administration of the IL-1 receptor antagonist Anakinra. These complications should be borne in mind in septic patients with marked haemodynamic instability and multiorgan dysfunction, and treatment with Anakinra should be considered in those who fail to respond to conventional therapy

Tacotron: Towards End-to-End Speech Synthesis

A text-to-speech synthesis system typically consists of multiple stages, such as a text analysis frontend, an acoustic model and an audio synthesis module. Building these components often requires extensive domain expertise and may contain brittle design choices. In this paper, we present Tacotron, an end-to-end generative text-to-speech model that synthesizes speech directly from characters. Given pairs, the model can be trained completely from scratch with random initialization. We present several key techniques to make the sequence-to-sequence framework perform well for this challenging task. Tacotron achieves a 3.82 subjective 5-scale mean opinion score on US English, outperforming a production parametric system in terms of naturalness. In addition, since Tacotron generates speech at the frame level, it's substantially faster than sample-level autoregressive methods.Comment: Submitted to Interspeech 2017. v2 changed paper title to be consistent with our conference submission (no content change other than typo fixes

Maximum Likelihood Estimator for Hidden Markov Models in continuous time

The paper studies large sample asymptotic properties of the Maximum Likelihood Estimator (MLE) for the parameter of a continuous time Markov chain, observed in white noise. Using the method of weak convergence of likelihoods due to I.Ibragimov and R.Khasminskii, consistency, asymptotic normality and convergence of moments are established for MLE under certain strong ergodicity conditions of the chain.Comment: Warning: due to a flaw in the publishing process, some of the references in the published version of the article are confuse