HST/NICMOS Observations of M82

The irregular galaxy M82 is known as the archetypal starburst galaxy. Its proximity (3.5 Mpc) makes this galaxy an ideal laboratory for studying the properties of its starburst. The detailed morphology of the [FeII] 1.644 μm and emission Pa_α (at 1.87 μm) is revealed by the NICMOS images. The peak of the 2.2 μm continuum brightness(evolved population) lies very close to the dynamical centre. Most of the Pa_α emission (which traces the young population) is distributed in a ring of star formation (with a `hole' lacking line emission at the centre of the galaxy). These observations support the scenario in which the starburst in M82 is propagating outwards. It has long been suggested that the [FeII] emission in starburst galaxies can be used as a measure of supernova (SN) activity. M82 shows a large number of radio supernova remnants (SNRs), approximately 50, lying in the plane of the galaxy. The comparison of the positions of the bright compact [FeII] emitting regions with the location of the radio SNRs shows that there is no one-to-one spatial correspondence between the two emissions, suggesting that the radio and [FeII] emissions trace two populations of SNRs with different ages. Young (a few hundred years) SNRs are best traced by their radio emission, whereas the [FeII] stage lasts for at least a few 10⁴ yr. The compact [FeII] sources contribute only some 20 % of the total [FeII] emission observed in M82. However, much of the remaining unresolved [FeII] emission in the plane of the galaxy may arise from SNRs that expanded and merged into a general interstellar medium within a few 10⁴ yr. Presumably, as much as 70% of the total extinction-corrected [FeII]1.644 μm in M82 is associated with SNRs. The extended and diffuse [FeII] component in M82 seems to be related with the superwind above and below the disc of the galaxy. This revised version was published online in July 2006 with corrections to the Cover Date.     

Effects of beta-naphthoflavone on hepatic biotransformation and glutathione biosynthesis in largemouth bass (Micropterus salmoides)

We are investigating the effects of in vivo exposure of prototypical enzyme inducing agents on hepatic biotransformation enzyme expression in largemouth bass (Micropterus salmoides), a predatory game fish found throughout the United States and Canada. The current study targeted those genes involved in biotransformation and oxidative stress that may be regulated by Ah-receptor-dependent pathways. Exposure of bass to beta-naphthoflavone (beta-NF, 66 mg/kg, i.p.) elicited a 7-9-fold increase in hepatic microsomal cytochrome P4501A-dependent ethoxyresorufin O-deethylase (EROD) activities, but did not affect cytosolic GST catalytic activities toward 1-chloro-2,4-dinitrobenzene (CDNB) or 5-androstene-3,17-dione (ADI). Glutathione S-transferase A (GST-A) mRNA expression exhibited a transient, but non-significant increase following exposure to beta-NF, and generally tracked the minimal changes observed in GST-CDNB activities. Expression of the mRNA encoding glutamate-cysteine ligase catalytic subunit (GCLC), the rate-limiting enzyme in glutathione (GSH) biosynthesis, was increased 1.7-fold by beta-NF. Changes in GCLC mRNA expression were paralleled by increases in intracellular GSH. In summary, largemouth bass hepatic CYP1A-dependent and GSH biosynthetic pathways, and to a lesser extent GST, are responsive to exposure to beta-NF.     

A note on first-order normalizations of perturbed Keplerian systems

Techniques are developed to facilitate the transformation of a perturbed Keplerian system into Deláunay normal form at first order. The implicit dependence of the Hamiltonian on 1, the mean anomaly, through the explicit variable f, the true anomaly, or E, the eccentric anomaly, is removed through first order for terms of the form:

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.