HALO is a novel aspect language introducing a logic-based pointcut language which combines history-based pointcuts and “escape ” conditions for interacting with the base language. This combination is difficult to support when escape conditions access context exposed by “future ” join points

. There has been much debate in recent decades as to what fraction of ionizing photons from star forming regions in the Galactic disk escape into the halo. The recent detection of the Magellanic Stream in optical line emission at the CTIO 4m and the AAT 3.9m telescopes may now provide the strongest

Abstract. There has been much debate in recent decades as to what fraction of ionizing photons from star forming regions in the Galactic disk escape into the halo. The recent detection of the Magellanic Stream in optical line emission at the CTIO 4m and the AAT 3.9m telescopes may now provide

that the clustering amplitude of halos depends not only on halo mass, but also on various secondary variables such as halo formation time and concentration; these dependences are collectively termed "assembly bias." Using a modified Fisher matrix formalism, we explore whether these secondary variables have

Context. Future observations of CMB anisotropies will be able to probe high multipole regions of the angular power spectrum, corresponding to a resolution of a few arcminutes. Dust emission from merging haloes is one of the foregrounds that will affect such very small scales. Aims. We estimate

to the nova. Such a model also improves agreement with the data at larger angles, and illustrates the sensitivity of X-ray scattering halos to the presence of lineof-sight density fluctuations. The observations therefore do not require a population of micron-sized dust grains. Future observations by Chandra

to the nova. Such a model also improves agreement with the data at larger angles, and illustrates the sensitivity of X-ray scattering halos to the location of the dust. The observations therefore do not require a population of micron-sized dust grains. Future observations by Chandra and XMM-Newton of X

between invariable and variable during evolution) can be modeled using an i.i.d. process The i.i.d. assumption allows one to readily compute P(D ͦ T, ) by identifying this with the product of the probabilities of evolving each particular site. Occasionally, more intricate models have been proposed

offering an opportunity to experiment with various strategic options proposed and implemented in the past and to understand the various scenarios created under laboratory conditions. Such experimentation helps to explain the variability of the patterns experienced in the past while also pointing toward

amplitude of halos depends not only on halo mass, but also on various secondary variables such as halo formation time and concentration; these dependences are collectively termed “assembly bias. ” Using a modified Fisher matrix formalism, we explore whether these secondary variables have a significant