Finite-β effects on the radiative thermal instability in magnetized plasmas

The radiative thermal instability is investigated taking into account finite-, or electromagnetic, effects. The two-fluid model for magnetized plasmas together with the Maxwell equations are used to derive a general dispersion relation valid for compressional perturbations with frequency below the electron-cyclotron frequency. The growth rates of the radiative thermal instabilities involving fast magnetosonic flute-like and low-frequency hydromagnetic perturbations are presented.     

The global structure of the pulsar magnetospheres

The model of the pulsar magnetosphere filled with massless charged particles (rest massm=0) is considered. The gas of charged massless particles can be found in two different phases: (1) dynamical phase (DP), when the particles move with nonvanishing energy along some base line, determined by the electromagnetic field only, (2) statical phase (SP), when the particles have vanishing energy =0. The pulsar magnetosphere occurs to be divided into regions of different types: (a) the accelerating regions (DP-regions) containing only DP, (b) the capture regions, containing only SP, (3) leaky capture regions, where DP moves through SP. The leaky capture regions are the active regions, which are responsible for the pulsar radioemission. In the case of oblique magnetic moment the equation for the capture surface has been obtained. The capture region is formed around this surface. Expressions for jumps of the electromagnetic field, the current density and the charge density on the capture region boundary have been obtained. The problem of the pulsar magnetosphere is stated mathematically in the case of oblique magnetic moment and ejection of only electrons.     

A framework of region-based spatial relations for non-overlapping features and its application in object based image analysis

Object based image analysis (OBIA) is an approach increasingly used in classifying high spatial resolution remote sensing images. Object based image classifiers first segment an image into objects (or image segments), and then classify these objects based on their attributes and spatial relations. Numerous algorithms exist for the first step of the OBIA process, i.e. image segmentation. However, less research has been conducted on the object classification part of OBIA, in particular the spatial relations between objects that are commonly used to construct rules for classifying image objects and refining classification results. In this paper, we establish a context where objects are areal (not points or lines) and non-overlapping (we call this “single-valued” space), and propose a framework of binary spatial relations between segmented objects to aid in object classification. In this framework, scale-dependent “line-like objects” and “point-like objects” are identified from areal objects based on their shapes. Generally, disjoint and meet are the only two possible topological relations between two non-overlapping areal objects. However, a number of quasi- topological relations can be defined when the shapes of the objects involved are considered. Some of these relations are fuzzy and thus quantitatively defined. In addition, we define the concepts of line-like objects (e.g. roads) and point-like objects (e.g. wells), and develop the relations between two line-like objects or two point-like objects. For completeness, cardinal direction relations and distance relations are also introduced in the proposed context. Finally, we implement the framework to extract roads and moving vehicles from an aerial photo. The promising results suggest that our methods can be a valuable tool in defining rules for object based image analysis.