The coupling between the solar wind and proton fluxes at GEO

The relationship between the solar wind and the proton flux at geosynchronous Earth orbit (GEO) is investigated using the error reduction ratio (ERR) analysis. The ERR analysis is able to search for the most appropriate inputs that control the evolution of the system. This approach is a black box method and is able to derive a mathematical model of a system from input-output data. This method is used to analyse eight energy ranges of the proton flux at GEO from 80 keV to 14.5 MeV. The inputs to the algorithm were solar wind velocity, density and pressure; the Dst index; the solar energetic proton (SEP) flux; and a function of the interplanetary magnetic field (IMF) tangential magnitude and clock angle. The results show that for lowest five energy channels (80 to 800 keV) the GEO proton fluxes are controlled by the solar wind velocity with a lag of two to three days. However, above 350 keV, the SEP fluxes, accounts for a significant portion of the GEO proton flux variance. For the highest three energy channels (0.74 to 14.5 MeV), the SEPs account for the majority of the ERR. The results also show an anisotropy of protons with gyrocenters inside GEO and outside GEO, where the protons inside GEO are controlled partly by the Dst index and also an IMF-clock angle function. © 2013 Author(s)

Modelling and Prediction of Global Magnetic Disturbance in Near-Earth Space: a Case Study for Kp Index using NARX Models

Severe geomagnetic disturbances can be hazardous for mod-ern technological systems. The reliable forecast of parameters related to thestate of the magnetosphere can facilitate the mitigation of adverse effects ofspace weather. This study is devoted to the modeling and forecasting of theevolution of the Kp index related to global geomagnetic disturbances. Through-out this work the Nonlinear AutoRegressive with eXogenous inputs (NARX)methodology is applied. Two approaches are presented: i) a recursive slid-ing window approach, and ii) a direct approach. These two approaches arestudied separately and are then compared to evaluate their performances.It is shown that the direct approach outperforms the recursive approach, butboth tend to produce predictions slightly biased from the true values for lowand high disturbances

Prominence-cavity regions observed using SWAP 174A filtergrams and simultaneous eclipse flash spectra

Images from the SWAP (Proba 2 mission) taken at 174A in the Fe IX/X lines are compared to simultaneous slitless flash spectra taken during the last solar total eclipse of July, 11th 2010. Many faint low excitation emission lines together with the HeI and HeII Paschen Alpha chromospheric lines are recorded on eclipse spectra where regions of limb prominences are obtained with space-borne imagers. We consider a deep flash spectrum obtained by summing 80 individual spectra to show the intensity modulations of the continuum. Intensity depressions are observed around the prominences in both eclipse and SWAP images. The prominence cavities are interpreted as a relative depression of plasma density, produced inside the corona surrounding the prominences. Photometric measurements are shown at different scales and different, spectrally narrow, intervals for both the prominences and the coronal background.Comment: 22 pages, 14 figures, accepted to publish in Sol. Phy

Construction of radial basis function networks with diversified topologies

In this review we bring together some of our recent work from the angle of the diversified RBF topologies, including three different topologies; (i) the RBF network with tunable nodes; (ii) the Box-Cox output transformation based RBF network (Box-Cox RBF); and (iii) the RBF network with boundary value constraints (BVC-RBF). We show that the modified topologies have some advantages over the conventional RBF topology for specific problems. For each modified topology, the model construction algorithms have been developed. These proposed RBF topologies are respectively aimed at enhancing the modelling capabilities of; (i)flexible basis function shaping for improved model generalisation with the minimal model;(ii) effectively handling some dynamical processes in which the model residuals exhibit heteroscedasticity; and (iii) achieving automatic constraints satisfaction so as to incorporate deterministic prior knowledge with ease. It is shown that it is advantageous that the linear learning algorithms, e.g. the orthogonal forward selection (OFS) algorithm based leave-one-out (LOO) criteria, are still applicable as part of the proposed algorithms

Data derived NARMAX Dst model

The NARMAX OLS-ERR methodology is applied to identify a mathematical model for the dynamics of the Dst index. The NARMAX OLS-ERR algorithm, which is widely used in the field of system identification, is able to identify a mathematical model for a wide class of nonlinear systems using input and output data. Solar wind-magnetosphere coupling functions, derived from analytical or data based methods, are employed as the inputs to such models and the outputs are geomagnetic indices. The newly deduced coupling function, p1/2V4/3BTsin6(θ/2), has been implemented as an input to model the Dst dynamics. It was shown that the identified model has a very good forecasting ability, especially with the geomagnetic storms

Utility of incorporating a gene-based lung cancer risk test on uptake and adherence in a community-based lung cancer screening pilot study

Based on the results of randomized control trials, screening for lung cancer using computed tomography (CT) is now widely recommended. However, adherence to screening remains an issue outside the clinical trial setting. This study examines the utility of biomarker-based risk assessment on uptake and subsequent adherence in a community screening study.In a single arm pilot study, current or former smokers > 50 years old with 20 + pack year history were recruited following local advertising. One hundred and fifty seven participants volunteered to participate in the study that offered an optional gene-based lung cancer risk assessment followed by low-dose CT according to a standardised screening protocol.All 157 volunteers who attended visit 1 underwent the gene-based risk assessment comprising of a clinical questionnaire and buccal swab. Of this group, 154 subsequently attended for CT screening (98%) and were followed prospectively for a median of 2.7 years. A participant’s adherence to screening was influenced by their baseline lung cancer risk category, with overall adherence in those with a positive scan being significantly greater in the “very high” risk group compared to “moderate” and “high” risk categories (71% vs 52%, Odds ratio = 2.27, 95% confidence interval of 1.02–5.05, P = 0.047). Those in the “moderate” risk group were not different to those in the “high” risk group (52% and 52%, P > 0.05).In this proof-of-concept study, personalised gene-based lung cancer risk assessment was well accepted, associated with a 98% uptake for screening and increased adherence for those in the highest risk group