How Accurately Can We Measure the Reconnection Rate E M for the MMS Diffusion Region Event of 11 July 2017?

We investigate the accuracy with which the reconnection electric field E M can be determined from in situ plasma data. We study the magnetotail electron diffusion region observed by National Aeronautics and Space Administration's Magnetospheric Multiscale (MMS) on 11 July 2017 at 22:34 UT and focus on the very large errors in E M that result from errors in an L M N boundary normal coordinate system. We determine several L M N coordinates for this MMS event using several different methods. We use these M axes to estimate E M. We find some consensus that the reconnection rate was roughly E M = 3.2 ± 0.6 mV/m, which corresponds to a normalized reconnection rate of 0.18 ± 0.035. Minimum variance analysis of the electron velocity (MVA-v e), MVA of E, minimization of Faraday residue, and an adjusted version of the maximum directional derivative of the magnetic field (MDD-B) technique all produce reasonably similar coordinate axes. We use virtual MMS data from a particle-in-cell simulation of this event to estimate the errors in the coordinate axes and reconnection rate associated with MVA-v e and MDD-B. The L and M directions are most reliably determined by MVA-v e when the spacecraft observes a clear electron jet reversal. When the magnetic field data have errors as small as 0.5% of the background field strength, the M direction obtained by MDD-B technique may be off by as much as 35°. The normal direction is most accurately obtained by MDD-B. Overall, we find that these techniques were able to identify E M from the virtual data within error bars ≥20%

On your bike! a cross-sectional study of the individual, social and environmental correlates of cycling to school

Background : Active school transport (AST) has declined rapidly in recent decades. While many studies have examined walking, cycling to school has received very little attention. Correlates of cycling are likely to differ to those from walking and cycling enables AST from further distances. This study examined individual, social and environmental factors associated with cycling to school among elementary school-aged children, stratified by gender. Methods : Children (n = 1197) attending 25 Australian primary schools located in high or low walkable neighborhoods, completed a one-week travel diary and a parent/child questionnaire on travel habits and attitudes. Results : Overall, 31.2% of boys and 14.6% of girls cycled &ge; 1 trip/week, however 59.4% of boys and 36.7% of girls reported cycling as their preferred school transport mode. In boys (but not girls), school neighborhood design was significantly associated with cycling: i.e., boys attending schools in neighborhoods with high connectivity and low traffic were 5.58 times more likely to cycle (95% CI 1.11-27.96) and for each kilometer boys lived from school the odds of cycling reduced by 0.70 (95% CI 0.63-0.99). Irrespective of gender, cycling to school was associated with parental confidence in their child\u27s cycling ability (boys: OR 10.39; 95% CI 3.79-28.48; girls: OR 4.03; 95% CI 2.02-8.05), parental perceived convenience of driving (boys: OR 0.42; 95% CI 0.23-0.74; girls: OR 0.40; 95% CI 0.20-0.82); and child\u27s preference to cycle (boys: OR 5.68; 95% CI 3.23-9.98; girls: OR 3.73; 95% CI 2.26-6.17). Conclusion : School proximity, street network connectivity and traffic exposure in school neighborhoods was associated with boys (but not girls) cycling to school. Irrespective of gender, parents need to be confident in their child\u27s cycling ability and must prioritize cycling over driving. <br /

Smolyak's algorithm: A powerful black box for the acceleration of scientific computations

We provide a general discussion of Smolyak's algorithm for the acceleration of scientific computations. The algorithm first appeared in Smolyak's work on multidimensional integration and interpolation. Since then, it has been generalized in multiple directions and has been associated with the keywords: sparse grids, hyperbolic cross approximation, combination technique, and multilevel methods. Variants of Smolyak's algorithm have been employed in the computation of high-dimensional integrals in finance, chemistry, and physics, in the numerical solution of partial and stochastic differential equations, and in uncertainty quantification. Motivated by this broad and ever-increasing range of applications, we describe a general framework that summarizes fundamental results and assumptions in a concise application-independent manner

Temporal networks of face-to-face human interactions

The ever increasing adoption of mobile technologies and ubiquitous services allows to sense human behavior at unprecedented levels of details and scale. Wearable sensors are opening up a new window on human mobility and proximity at the finest resolution of face-to-face proximity. As a consequence, empirical data describing social and behavioral networks are acquiring a longitudinal dimension that brings forth new challenges for analysis and modeling. Here we review recent work on the representation and analysis of temporal networks of face-to-face human proximity, based on large-scale datasets collected in the context of the SocioPatterns collaboration. We show that the raw behavioral data can be studied at various levels of coarse-graining, which turn out to be complementary to one another, with each level exposing different features of the underlying system. We briefly review a generative model of temporal contact networks that reproduces some statistical observables. Then, we shift our focus from surface statistical features to dynamical processes on empirical temporal networks. We discuss how simple dynamical processes can be used as probes to expose important features of the interaction patterns, such as burstiness and causal constraints. We show that simulating dynamical processes on empirical temporal networks can unveil differences between datasets that would otherwise look statistically similar. Moreover, we argue that, due to the temporal heterogeneity of human dynamics, in order to investigate the temporal properties of spreading processes it may be necessary to abandon the notion of wall-clock time in favour of an intrinsic notion of time for each individual node, defined in terms of its activity level. We conclude highlighting several open research questions raised by the nature of the data at hand.Comment: Chapter of the book "Temporal Networks", Springer, 2013. Series: Understanding Complex Systems. Holme, Petter; Saram\"aki, Jari (Eds.

Diffusion-weighted MRI for detecting prostate tumour in men at increased genetic risk.

Background Diffusion-weighted (DW)-MRI is invaluable in detecting prostate cancer. We determined its sensitivity and specificity and established interobserver agreement for detecting tumour in men with a family history of prostate cancer stratified by genetic risk.Methods 51 men with a family history of prostate cancer underwent T2-W + DW-endorectal MRI at 3.0 T. Presence of tumour was noted at right and left apex, mid and basal prostate sextants by 2 independent observers, 1 experienced and the other inexperienced in endorectal MRI. Sensitivity and specificity against a 10-core sampling technique (lateral and medial cores at each level considered together) in men with >2× population risk based on 71 SNP analysis versus those with lower genetic risk scores was established. Interobserver agreement was determined at a subject level.Results Biopsies indicated cancer in 28 sextants in 13/51 men; 32 of 51 men had twice the population risk (>0.25) based on 71 SNP profiling. Sensitivity/specificity per-subject for patients was 90.0%/86.4% (high-risk) vs. 66.7%/100% (low-risk, observer 1) and 60.0%/86.3% (high-risk) vs. 33.3%/93.8% (low-risk, observer 2) with moderate overall inter-observer agreement (kappa = 0.42). Regional sensitivities/specificities for high-risk vs. low-risk for observer 1 apex 72.2%/100% [33.3%/100%], mid 100%/93.1% [100%/97.3%], base 16.7%/98.3% [0%/100%] and for observer 2 apex 36.4%/98.1% [0%/100%], mid 28.6%/96.5% [100%/100%], base 20%/100% [0%/97.3%] were poorer as they failed to detect multiple lesions.Conclusion Endorectal T2W + DW-MRI at 3.0 T yields high sensitivity and specificity for tumour detection by an experienced observer in screening men with a family history of prostate cancer and increased genetic risk

Capture the fracture: a best practice framework and global campaign to break the fragility fracture cycle

Summary The International Osteoporosis Foundation (IOF) Capture the Fracture Campaign aims to support implementation of Fracture Liaison Services (FLS) throughout the world. Introduction FLS have been shown to close the ubiquitous secondary fracture prevention care gap, ensuring that fragility fracture sufferers receive appropriate assessment and intervention to reduce future fracture risk. Methods Capture the Fracture has developed internationally endorsed standards for best practice, will facilitate change at the national level to drive adoption of FLS and increase awareness of the challenges and opportunities presented by secondary fracture prevention to key stakeholders. The Best Practice Framework (BPF) sets an international benchmark for FLS, which defines essential and aspirational elements of service delivery. Results The BPF has been reviewed by leading experts from many countries and subject to beta-testing to ensure that it is internationally relevant and fit-for-purpose. The BPF will also serve as a measurement tool for IOF to award ‘Capture the Fracture Best Practice Recognition’ to celebrate successful FLS worldwide and drive service development in areas of unmet need. The Capture the Fracture website will provide a suite of resources related to FLS and secondary fracture prevention, which will be updated as new materials become available. A mentoring programme will enable those in the early stages of development of FLS to learn from colleagues elsewhere that have achieved Best Practice Recognition. A grant programme is in development to aid clinical systems which require financial assistance to establish FLS in their localities. Conclusion Nearly half a billion people will reach retirement age during the next 20 years. IOF has developed Capture the Fracture because this is the single most important thing that can be done to directly improve patient care, of both women and men, and reduce the spiralling fracture-related care costs worldwide.</p

Validation of T2- and diffusion-weighted magnetic resonance imaging for mapping intra-prostatic tumour prior to focal boost dose-escalation using intensity-modulated radiotherapy (IMRT).

BACKGROUND AND PURPOSE:To assess the diagnostic accuracy and inter-observer agreement of T2-weighted (T2W) and diffusion-weighted (DW) magnetic resonance imaging (MRI) for mapping intra-prostatic tumour lesions (IPLs) for the purpose of focal dose-escalation in prostate cancer radiotherapy. MATERIALS AND METHODS:Twenty-six men selected for radical treatment with radiotherapy were recruited prospectively and underwent pre-treatment T2W+DW-MRI and 5 mm spaced transperineal template-guided mapping prostate biopsies (TTMPB). A 'traffic-light' system was used to score both data sets. Radiologically suspicious lesions measuring ≥0.5 cm3 were classified as red; suspicious lesions 0.2-0.5 cm3 or larger lesions equivocal for tumour were classified as amber. The histopathology assessment combined pathological grade and tumour length on biopsy (red = ≥4 mm primary Gleason grade 4/5 or ≥6 mm primary Gleason grade 3). Two radiologists assessed the MRI data and inter-observer agreement was measured with Cohens' Kappa co-efficient. RESULTS:Twenty-five of 26 men had red image-defined IPLs by both readers, 24 had red pathology-defined lesions. There was a good correlation between lesions ≥0.5 cm3 classified "red" on imaging and "red" histopathology in biopsies (Reader 1: r = 0.61, p < 0.0001, Reader 2: r = 0.44, p = 0.03). Diagnostic accuracy for both readers for red image-defined lesions was sensitivity 85-86%, specificity 93-98%, positive predictive value (PPV) 79-92% and negative predictive value (NPV) 96%. Inter-observer agreement was good (Cohen's Kappa 0.61). CONCLUSIONS:MRI is accurate for mapping clinically significant prostate cancer; diffusion-restricted lesions ≥0.5 cm3 can be confidently identified for radiation dose boosting

Filtration analysis of pedestrian-vehicle interactions for autonomous vehicle control

Interacting with humans remains a challenge for autonomousvehicles (AVs). When a pedestrian wishes to cross the road in front of thevehicle at an unmarked crossing, the pedestrian and AV must competefor the space, which may be considered as a game-theoretic interaction inwhich one agent must yield to the other. To inform development of newreal-time AV controllers in this setting, this study collects and analy-ses detailed, manually-annotated, temporal data from real-world humanroad crossings as they interact with manual drive vehicles. It studies thetemporal orderings (filtrations) in which features are revealed to the ve-hicle and their informativeness over time. It presents a new frameworksuggesting how optimal stopping controllers may then use such data toenable an AV to decide when to act (by speeding up, slowing down, orotherwise signalling intent to the pedestrian) or alternatively, to continueat its current speed in order to gather additional information from newfeatures, including signals from that pedestrian, before acting itself

Predicting pedestrian road-crossing assertiveness for autonomous vehicle control

Autonomous vehicles (AVs) must interact with other road users including pedestrians. Unlike passive environments, pedestrians are active agents having their own utilities and decisions, which must be inferred and predicted by AVs in order to control interactions with them and navigation around them. In particular, when a pedestrian wishes to cross the road in front of the vehicle at an unmarked crossing, the pedestrian and AV must compete for the space, which may be considered as a game-theoretic interaction in which one agent must yield to the other. To inform AV controllers in this setting, this study collects and analyses data from real-world human road crossings to determine what features of crossing behaviours are predictive about the level of assertiveness of pedestrians and of the eventual winner of the interactions. It presents the largest and most detailed data set of its kind known to us, and new methods to analyze and predict pedestrian-vehicle interactions based upon it. Pedestrian-vehicle interactions are decomposed into sequences of independent discrete events. We use probabilistic methods - logistic regression and decision tree regression - and sequence analysis to analyze sets and sub-sequences of actions used by both pedestrians and human drivers while crossing at an intersection, to find common patterns of behaviour and to predict the winner of each interaction. We report on the particular features found to be predictive and which can thus be integrated into game-theoretic AV controllers to inform real-time interactions