The Coronal Analysis of SHocks and Waves (CASHeW) Framework

Coronal Bright Fronts (CBF) are large-scale wavelike disturbances in the solar corona, related to solar eruptions. They are observed in extreme ultraviolet (EUV) light as transient bright fronts of finite width, propagating away from the eruption source. Recent studies of individual solar eruptive events have used EUV observations of CBFs and metric radio type II burst observations to show the intimate connection between low coronal waves and coronal mass ejection (CME)-driven shocks. EUV imaging with the Atmospheric Imaging Assembly(AIA) instrument on the Solar Dynamics Observatory (SDO) has proven particularly useful for detecting CBFs, which, combined with radio and in situ observations, holds great promise for early CME-driven shock characterization capability. This characterization can further be automated, and related to models of particle acceleration to produce estimates of particle fluxes in the corona and in the near Earth environment early in events. We present a framework for the Coronal Analysis of SHocks and Waves (CASHeW). It combines analysis of NASA Heliophysics System Observatory data products and relevant data-driven models, into an automated system for the characterization of off-limb coronal waves and shocks and the evaluation of their capability to accelerate solar energetic particles (SEPs). The system utilizes EUV observations and models written in the Interactive Data Language (IDL). In addition, it leverages analysis tools from the SolarSoft package of libraries, as well as third party libraries. We have tested the CASHeW framework on a representative list of coronal bright front events. Here we present its features, as well as initial results. With this framework, we hope to contribute to the overall understanding of coronal shock waves, their importance for energetic particle acceleration, as well as to the better ability to forecast SEP events fluxes.Comment: Accepted for publication in the Journal of Space Weather and Space Climate (SWSC

Simulation study for the lead time in cancer screening when human lifetime is a competing risk.

PURPOSE: The purpose of this paper is to examine the lead time distribution in cancer screening trials when lifetime is a random variable in order to determine optimal initial age at screening and screening frequency. METHODS: Simulation was used in order to estimate the distribution of the lead time for a hypothetical individual with a future screening schedule. The lifetime distribution used comes from the Social Security Administration\u27s actuarial life tables. The lead time distribution was then calculated based on two different sojourn time distributions (log-logistic and exponential) with four mean sojourn times (2, 5, 10, and 20 years), using three different initial screening ages, to=40, 50, 60, and four different screening frequencies, every six months, every year, every 1.5 years, and every two years for both males and females. RESULTS: Smaller time intervals between screenings yield a smaller probability of no benefit and a greater expected lead time

Formation of molecular oxygen in ultracold O + OH reaction

We discuss the formation of molecular oxygen in ultracold collisions between hydroxyl radicals and atomic oxygen. A time-independent quantum formalism based on hyperspherical coordinates is employed for the calculations. Elastic, inelastic and reactive cross sections as well as the vibrational and rotational populations of the product O2 molecules are reported. A J-shifting approximation is used to compute the rate coefficients. At temperatures T = 10 - 100 mK for which the OH molecules have been cooled and trapped experimentally, the elastic and reactive rate coefficients are of comparable magnitude, while at colder temperatures, T < 1 mK, the formation of molecular oxygen becomes the dominant pathway. The validity of a classical capture model to describe cold collisions of OH and O is also discussed. While very good agreement is found between classical and quantum results at T=0.3 K, at higher temperatures, the quantum calculations predict a larger rate coefficient than the classical model, in agreement with experimental data for the O + OH reaction. The zero-temperature limiting value of the rate coefficient is predicted to be about 6.10^{-12} cm^3 molecule^{-1} s^{-1}, a value comparable to that of barrierless alkali-metal atom - dimer systems and about a factor of five larger than that of the tunneling dominated F + H2 reaction.Comment: 9 pages, 8 figure

The boundary of recruitment: A response

In their commentaries, both Heritage (2016/this issue) and Zinken and Rossi (2016/this issue) provide some context for our concept of and approach to recruitment in terms of previous research into requesting and offering. In doing so, they usefully consider what might be the boundaries of recruitmentwhat might be included and what might not be included or treated as recruitment. We respond here to their suggestions concerning these boundaries

Educational weight loss interventions in obese and overweight adults with type 2 diabetes : a systematic review and meta‐analysis of randomized controlled trials

Aim The worldwide prevalence of type 2 diabetes mellitus is increasing, with most individuals with the disease being overweight or obese. Weight loss can reduce disease‐related morbidity and mortality and weight losses of 10–15 kg have been shown to reverse type 2 diabetes. This review aimed to determine the effectiveness of community‐based educational interventions for weight loss in type 2 diabetes. Methods This is a systematic review and meta‐analysis of randomized controlled trials (RCT) in obese or overweight adults, aged 18–75 years, with a diagnosis of type 2 diabetes. Primary outcomes were weight and/or BMI. CINAHL, MEDLINE, Embase, Scopus and the Cochrane Central Register of Controlled Trials (CENTRAL) were searched from inception to June 2019. Trials were classified into specified a priori comparisons according to intervention type. A pooled standardized mean difference (SMD) (from baseline to follow‐up) and 95% confidence intervals (95% CI) between trial groups (difference‐in‐difference) were estimated through random‐effects meta‐analyses using the inverse variance method. Heterogeneity was quantified using I2 and publication bias was explored visually using funnel plots. Results Some 7383 records were screened; 228 full‐text articles were assessed and 49 RCTs (n = 12 461 participants) were included in this review, with 44 being suitable for inclusion into the meta‐analysis. Pooled estimates of education combined with low‐calorie, low‐carbohydrate meal replacements (SMD = –2.48, 95% CI –3.59, –1.49, I2 = 98%) or diets (SMD = –1.25, 95% CI –2.11, –0.39, I2 = 95%) or low‐fat meal replacements (SMD = –1.15, 95%CI –2.05, –1.09, I2 = 85%) appeared most effective. Conclusion Low‐calorie, low‐carbohydrate meal replacements or diets combined with education appear the most promising interventions to achieve the largest weight and BMI reductions in people with type 2 diabetes

Change point detection in social networksCritical review with experiments

© 2018 Elsevier Inc. Change point detection in social networks is an important element in developing the understanding of dynamic systems. This complex and growing area of research has no clear guidelines on what methods to use or in which circumstances. This paper critically discusses several possible network metrics to be used for a change point detection problem and conducts an experimental, comparative analysis using the Enron and MIT networks. Bayesian change point detection analysis is conducted on different global graph metrics (Size, Density, Average Clustering Coefficient, Average Shortest Path) as well as metrics derived from the Hierarchical and Block models (Entropy, Edge Probability, No. of Communities, Hierarchy Level Membership). The results produced the posterior probability of a change point at weekly time intervals that were analysed against ground truth change points using precision and recall measures. Results suggest that computationally heavy generative models offer only slightly better results compared to some of the global graph metrics. The simplest metrics used in the experiments, i.e. nodes and links numbers, are the recommended choice for detecting overall structural changes