We analyze the allowed spectrum of electric and magnetic charges carried by dyons in (toroidally compactified) heterotic string theory in four dimensions at arbitrary values of the string coupling constant and θ angle. The spectrum is shown to be invariant under electric-magnetic duality transformation, thereby providing support to the conjecture that this is an exact symmetry in string theory.

We predict that left-handed metamaterials with nonlinear response can support both TEand TM-polarized self-trapped localized beams, or spatial electromagnetic solitons. Such solitons appear as singleand multi-hump beams, being either symmetric or antisymmetric, and they are modified dramatically by the hysteresis-type magnetic nonlinearity and the effective domains of negative magnetic permeabi...

using fe(no3)3.9h2o, co(no3)2.6h2o and mn(no3)2.4h2o the magnetic properties of nanoparticles trimetalic iron - cobalt - manganese, with supported magnesium oxide have been prepared by co-precipitation and solvothermal methods. the prepared samples are characterized by scanning electron microscope (sem), x-ray diffraction (xrd), vibrating sample magnetometer (vsm) and brunaer-emmett-teller (bet...

Aims. We aim to study the 250 μm luminosity function (LF) down to much fainter luminosities than achieved by previous efforts. Methods. We developed a modified stacking method to reconstruct the 250 μm LF using optically selected galaxies from the SDSS survey and Herschel maps of the GAMA equatorial fields and Stripe 82. Our stacking method not only recovers the mean 250 μm luminosities of gala...

Coalition analysis is extended to incorporate uncertain preference into three stability concepts, general metarationality (GMR), symmetric metarationality (SMR), and sequential stability (SEQ) under the paradigm of the graph model for conflict resolution. As a follow-up analysis in the graph model, coalition analysis aims to assess whether equilibriums under individual calculations are vulnerab...

INTRODUCTION In recent years, machine-learning techniques have gained growing popularity in medical image analysis. Temporal brain-state classification is one of the major applications of machine-learning techniques in functional magnetic resonance imaging (fMRI) brain data. This article explores the use of support vector machine (SVM) classification technique with motor-visual activation parad...

The nature of the excess near-infrared emission associatedwith themagneticwhite dwarf commonly known as SDSS 1212 is investigated primarily through spectroscopy, and also via photometry. The inferred low-mass secondary in this system has been previously detected by the emission and variation of H , and the 1–2.5 m spectral data presented here are consistent with the presence of a late L or earl...

Functional magnetic resonance imaging (fMRI) is becoming a forefront brain-computer interface tool. To decipher brain patterns, fast, accurate and reliable classifier methods are needed. The support vector machine (SVM) classifier has been traditionally used. Here we argue that state-of-the-art methods from pattern recognition and machine learning, such as classifier ensembles, offer more accur...

Measurement of the evolution properties of solar flares through their complete cyclic development is crucial in the studies of Solar Physics. From the analysis of solar Hα images, we used Support Vector Machines (SVMs) to automatically detect flares and applied image segmentation techniques to compute their properties. We also present a solution for automatically tracking the apparent separatio...

Despite its diagnostic value and technological availability, (1)H NMR spectroscopic imaging (MRSI) has not found its way into clinical routine yet. Prerequisite for the clinical application is an automated and reliable method for the diagnostic evaluation of MRS images. In the present paper, different approaches to the estimation of tumor probability from MRSI in the prostate are assessed. Two ...