Automated Prediction of CMEs Using Machine Learning of CME – Flare Associations

Machine-learning algorithms are applied to explore the relation between significant flares and their associated CMEs. The NGDC flares catalogue and the SOHO/LASCO CME catalogue are processed to associate X and M-class flares with CMEs based on timing information. Automated systems are created to process and associate years of flare and CME data, which are later arranged in numerical-training vectors and fed to machine-learning algorithms to extract the embedded knowledge and provide learning rules that can be used for the automated prediction of CMEs. Properties representing the intensity, flare duration, and duration of decline and duration of growth are extracted from all the associated (A) and not-associated (NA) flares and converted to a numerical format that is suitable for machine-learning use. The machine-learning algorithms Cascade Correlation Neural Networks (CCNN) and Support Vector Machines (SVM) are used and compared in our work. The machine-learning systems predict, from the input of a flare’s properties, if the flare is likely to initiate a CME. Intensive experiments using Jack-knife techniques are carried out and the relationships between flare properties and CMEs are investigated using the results. The predictive performance of SVM and CCNN is analysed and recommendations for enhancing the performance are provided.     

Geochronology of anthropogenic pollutants in riparian wetland sediments of the Lippe River (Germany)

Anthropogenic pollutants were determined in a dated sediment core, collected from a riparian wetland of the Lippe River (Ruhr district, Germany). The historical trend in heavy metals, polycyclic aromatic hydrocarbons, organochlorines, polychlorinated biphenyls and linear alkylbenzenes as well as more recent contaminants such as industrial additives, organotins, synthetic musks, methyltriclosan and some other compounds were determined for the time period between 1930 and 1986. Emission sources, information on technical production and usage, as well as on the individual pollution pathways, with appropriate environmental stability, were considered in the interpretation of the sediment contamination over the past 50 years.Contaminants were analysed and interpreted according to two different criteria: (a) the origin of the main contaminants as related to mining and industrial activities as well as municipal sewage and agricultural effluents and (b) the pollution history. Due to a significant appearance of formerly missing contaminants in sediments deposited since 1970, we suggest classifying contaminants as either common (predating 1970) or modern (postdating 1970).In summary, the study provided a comprehensive reconstruction of the pollution history of the Lippe River system.     

Global-Mode Analysis of Full-Disk Data from the <Emphasis Type="Italic">Michelson Doppler Imager</Emphasis> and the <Emphasis Type="Italic">Helioseismic and Magnetic Imager</Emphasis>

Building upon our previous work, in which we analyzed smoothed and subsampled velocity data from the Michelson Doppler Imager (MDI), we extend our analysis to unsmoothed, full-resolution MDI data. We also present results from the Helioseismic and Magnetic Imager (HMI), in both full resolution and processed to be a proxy for the low-resolution MDI data. We find that the systematic errors that we saw previously, namely peaks in both the high-latitude rotation rate and the normalized residuals of odd \(a\)-coefficients, are almost entirely absent in the two full-resolution analyses. Furthermore, we find that both systematic errors seem to depend almost entirely on how the input images are apodized, rather than on resolution or smoothing. Using the full-resolution HMI data, we confirm our previous findings regarding the effect of using asymmetric profiles on mode parameters, and also find that they occasionally result in more stable fits. We also confirm our previous findings regarding discrepancies between 360-day and 72-day analyses. We further investigate a six-month period previously seen in \(f\)-mode frequency shifts using the low-resolution datasets, this time accounting for solar-cycle dependence using magnetic-field data. Both HMI and MDI saw prominent six-month signals in the frequency shifts, but we were surprised to discover that the strongest signal at that frequency occurred in the mode coverage for the low-resolution proxy. Finally, a comparison of mode parameters from HMI and MDI shows that the frequencies and \(a\)-coefficients agree closely, encouraging the concatenation of the two datasets.     

2MASS near-infrared photometry of symbiotic stars

We present Two Micron All Sky Survey photometry for 216 symbiotic and possible symbiotic stars. This represents the most comprehensive near-infrared photometry for these sources which has been published to date. The results are used to define the statistics of S- and D-type stars; to investigate the photometric properties of Magellanic S-type symbiotics; and to define the possible evolution of D-type symbiotics within the J − H / H − K _S colour plane. It appears that the colours of D-type symbiotics are consistent with differing mass-loss rates d M /d t , provided that the grains have a silicate-like composition, and maximum temperatures of the order of ∼800 K.     

A Long-Term Forecast Model of Spring Runoff: The Case of the Belaya River

Doklady Earth Sciences - The results of long-term forecasting of the spring runoff in the Belaya River basin based on the water-balance model are presented. The structure and parameters of the...