Propagation of an Earth-directed coronal mass ejection in three dimensions

Solar coronal mass ejections (CMEs) are the most significant drivers of adverse space weather at Earth, but the physics governing their propagation through the heliosphere is not well understood. While stereoscopic imaging of CMEs with the Solar Terrestrial Relations Observatory (STEREO) has provided some insight into their three-dimensional (3D) propagation, the mechanisms governing their evolution remain unclear due to difficulties in reconstructing their true 3D structure. Here we use a new elliptical tie-pointing technique to reconstruct a full CME front in 3D, enabling us to quantify its deflected trajectory from high latitudes along the ecliptic, and measure its increasing angular width and propagation from 2-46 solar radii (approximately 0.2 AU). Beyond 7 solar radii, we show that its motion is determined by an aerodynamic drag in the solar wind and, using our reconstruction as input for a 3D magnetohydrodynamic simulation, we determine an accurate arrival time at the Lagrangian L1 point near Earth.Comment: 5 figures, 2 supplementary movie

The development of path integration: combining estimations of distance and heading

Efficient daily navigation is underpinned by path integration, the mechanism by which we use self-movement information to update our position in space. This process is well-understood in adulthood, but there has been relatively little study of path integration in childhood, leading to an underrepresentation in accounts of navigational development. Previous research has shown that calculation of distance and heading both tend to be less accurate in children as they are in adults, although there have been no studies of the combined calculation of distance and heading that typifies naturalistic path integration. In the present study 5-year-olds and 7-year-olds took part in a triangle-completion task, where they were required to return to the startpoint of a multi-element path using only idiothetic information. Performance was compared to a sample of adult participants, who were found to be more accurate than children on measures of landing error, heading error, and distance error. 7-year-olds were significantly more accurate than 5-year-olds on measures of landing error and heading error, although the difference between groups was much smaller for distance error. All measures were reliably correlated with age, demonstrating a clear development of path integration abilities within the age range tested. Taken together, these data make a strong case for the inclusion of path integration within developmental models of spatial navigational processing

Value Iteration for Long-run Average Reward in Markov Decision Processes

Markov decision processes (MDPs) are standard models for probabilistic systems with non-deterministic behaviours. Long-run average rewards provide a mathematically elegant formalism for expressing long term performance. Value iteration (VI) is one of the simplest and most efficient algorithmic approaches to MDPs with other properties, such as reachability objectives. Unfortunately, a naive extension of VI does not work for MDPs with long-run average rewards, as there is no known stopping criterion. In this work our contributions are threefold. (1) We refute a conjecture related to stopping criteria for MDPs with long-run average rewards. (2) We present two practical algorithms for MDPs with long-run average rewards based on VI. First, we show that a combination of applying VI locally for each maximal end-component (MEC) and VI for reachability objectives can provide approximation guarantees. Second, extending the above approach with a simulation-guided on-demand variant of VI, we present an anytime algorithm that is able to deal with very large models. (3) Finally, we present experimental results showing that our methods significantly outperform the standard approaches on several benchmarks

Wide-Scale Analysis of Human Functional Transcription Factor Binding Reveals a Strong Bias towards the Transcription Start Site

We introduce a novel method to screen the promoters of a set of genes with shared biological function, against a precompiled library of motifs, and find those motifs which are statistically over-represented in the gene set. The gene sets were obtained from the functional Gene Ontology (GO) classification; for each set and motif we optimized the sequence similarity score threshold, independently for every location window (measured with respect to the TSS), taking into account the location dependent nucleotide heterogeneity along the promoters of the target genes. We performed a high throughput analysis, searching the promoters (from 200bp downstream to 1000bp upstream the TSS), of more than 8000 human and 23,000 mouse genes, for 134 functional Gene Ontology classes and for 412 known DNA motifs. When combined with binding site and location conservation between human and mouse, the method identifies with high probability functional binding sites that regulate groups of biologically related genes. We found many location-sensitive functional binding events and showed that they clustered close to the TSS. Our method and findings were put to several experimental tests. By allowing a "flexible" threshold and combining our functional class and location specific search method with conservation between human and mouse, we are able to identify reliably functional TF binding sites. This is an essential step towards constructing regulatory networks and elucidating the design principles that govern transcriptional regulation of expression. The promoter region proximal to the TSS appears to be of central importance for regulation of transcription in human and mouse, just as it is in bacteria and yeast.Comment: 31 pages, including Supplementary Information and figure

Testing Yukawa-unified SUSY during year 1 of LHC: the role of multiple b-jets, dileptons and missing E_T

We examine the prospects for testing SO(10) Yukawa-unified supersymmetric models during the first year of LHC running at \sqrt{s}= 7 TeV, assuming integrated luminosity values of 0.1 to 1 fb^-1. We consider two cases: the Higgs splitting (HS) and the D-term splitting (DR3) models. Each generically predicts light gluinos and heavy squarks, with an inverted scalar mass hierarchy. We hence expect large rates for gluino pair production followed by decays to final states with large b-jet multiplicity. For 0.2 fb^-1 of integrated luminosity, we find a 5 sigma discovery reach of m(gluino) ~ 400 GeV even if missing transverse energy, E_T^miss, is not a viable cut variable, by examining the multi-b-jet final state. A corroborating signal should stand out in the opposite-sign (OS) dimuon channel in the case of the HS model; the DR3 model will require higher integrated luminosity to yield a signal in the OS dimuon channel. This region may also be probed by the Tevatron with 5-10 fb^-1 of data, if a corresponding search in the multi-b+ E_T^miss channel is performed. With higher integrated luminosities of ~1 fb^-1, using E_T^miss plus a large multiplicity of b-jets, LHC should be able to discover Yukawa-unified SUSY with m(gluino) up to about 630 GeV. Thus, the year 1 LHC reach for Yukawa-unified SUSY should be enough to either claim a discovery of the gluino, or to very nearly rule out this class of models, since higher values of m(gluino) lead to rather poor Yukawa unification.Comment: 32 pages including 31 EPS figure

Global Development and Climate Change: A Game Theory Approach

The increasing concern with climate change is one of the main issues of our time, and thus we aim to theoretically and mathematically analyse its causes. However our approach follows a different stream of thought, presenting the reasoning and decision-making processes between technical and moral solutions. We have resorted to game theory models in order to demonstrate cooperative and non-cooperative scenarios, ranging from the traditional to the evolutionary within game theory. In doing so we are able to glimpse the development of modern society and a paradigm shift regarding human control over nature and to what extent it is harmful to the sustainability of our environment and the survival of future generations. Merging different fields of knowledge, we present a theoretical-philosophical approach, combined with empirical-mathematical solutions taking into account the agent-based behaviour guided blindly by instrumental rationality

Distinguishing Asthma Phenotypes Using Machine Learning Approaches.

Asthma is not a single disease, but an umbrella term for a number of distinct diseases, each of which are caused by a distinct underlying pathophysiological mechanism. These discrete disease entities are often labelled as asthma endotypes. The discovery of different asthma subtypes has moved from subjective approaches in which putative phenotypes are assigned by experts to data-driven ones which incorporate machine learning. This review focuses on the methodological developments of one such machine learning technique-latent class analysis-and how it has contributed to distinguishing asthma and wheezing subtypes in childhood. It also gives a clinical perspective, presenting the findings of studies from the past 5 years that used this approach. The identification of true asthma endotypes may be a crucial step towards understanding their distinct pathophysiological mechanisms, which could ultimately lead to more precise prevention strategies, identification of novel therapeutic targets and the development of effective personalized therapies

Cosmogenic neutron production at the Sudbury Neutrino Observatory

Neutrons produced in nuclear interactions initiated by cosmic-ray muons present an irreducible background to many rare-event searches, even in detectors located deep underground. Models for the production of these neutrons have been tested against previous experimental data, but the extrapolation to deeper sites is not well understood. Here we report results from an analysis of cosmogenically produced neutrons at the Sudbury Neutrino Observatory. A specific set of observables are presented, which can be used to benchmark the validity of geant4 physics models. In addition, the cosmogenic neutron yield, in units of 10-4 cm2/(g·μ), is measured to be 7.28±0.09(stat)-1.12+1.59(syst) in pure heavy water and 7.30±0.07(stat)-1.02+1.40(syst) in NaCl-loaded heavy water. These results provide unique insights into this potential background source for experiments at SNOLAB

The factor structure and psychometric properties of the Clinical Outcomes in Routine Evaluation - Outcome Measure (CORE-OM) in Norwegian clinical and non-clinical samples

Background The Clinical Outcomes in Routine Evaluation - Outcome Measure (CORE-OM) is a 34-item instrument developed to monitor clinically significant change in out-patients. The CORE-OM covers four domains: well-being, problems/symptoms, functioning and risk, and sums up in two total scores: the mean of All items, and the mean of All non-risk items. The aim of this study was to examine the psychometric properties of the Norwegian translation of the CORE-OM. Methods A clinical sample of 527 out-patients from North Norwegian specialist psychiatric services, and a non-clinical sample of 464 persons were obtained. The non-clinical sample was a convenience sample consisting of friends and family of health personnel, and of students of medicine and clinical psychology. Students also reported psychological stress. Exploratory factor analysis (EFA) was employed in half the clinical sample. Confirmatory (CFA) factor analyses modelling the theoretical sub-domains were performed in the remaining half of the clinical sample. Internal consistency, means, and gender and age differences were studied by comparing the clinical and non-clinical samples. Stability, effect of language (Norwegian versus English), and of psychological stress was studied in the sub-sample of students. Finally, cut-off scores were calculated, and distributions of scores were compared between clinical and non-clinical samples, and between students reporting stress or no stress. Results The results indicate that the CORE-OM both measures general (g) psychological distress and sub-domains, of which risk of harm separates most clearly from the g factor. Internal consistency, stability and cut-off scores compared well with the original English version. No, or only negligible, language effects were found. Gender differences were only found for the well-being domain in the non-clinical sample and for the risk domain in the clinical sample. Current patient status explained differences between clinical and non-clinical samples, also when gender and age were controlled for. Students reporting psychological distress during last week scored significantly higher than students reporting no stress. These results further validate the recommended cut-off point of 1 between clinical and non-clinical populations. Conclusions The CORE-OM in Norwegian has psychometric properties at the same level as the English original, and could be recommended for general clinical use. A cut-off point of 1 is recommended for both genders

Recruitment Constraints in Singapore's Fluted Giant Clam (Tridacna squamosa) Populations - A Dispersal Model Approach

10.1371/journal.pone.0058819PLoS ONE83