Very large array detection of radio recombination lines from the radio nucleus of NGC 253: Ionization by a weak active galactic nucleus, an obscured super star cluster, or a compact supernova remnant?

We have imaged the H92alpha and H75alpha radio recombination line (RRL) emissions from the starburst galaxy NGC 253 with a resolution of similar to4 pc. The peak of the RRL emission at both frequencies coincides with the unresolved radio nucleus. Both lines observed toward the nucleus are extremely wide, with FWHMs of similar to200 km s(-1). Modeling the RRL and radio continuum data for the radio nucleus shows that the lines arise in gas whose density is similar to10(4) cm(-3) and mass is a few thousand M., which requires an ionizing flux of (6-20) x 10(51) photons s(-1). We consider a supernova remnant (SNR) expanding in a dense medium, a star cluster, and also an active galactic nucleus (AGN) as potential ionizing sources. Based on dynamical arguments, we rule out an SNR as a viable ionizing source. A star cluster model is considered, and the dynamics of the ionized gas in a stellar-wind driven structure are investigated. Such a model is only consistent with the properties of the ionized gas for a cluster younger than similar to10(5) yr. The existence of such a young cluster at the nucleus seems improbable. The third model assumes the ionizing source to be an AGN at the nucleus. In this model, it is shown that the observed X-ray flux is too weak to account for the required ionizing photon flux. However, the ionization requirement can be explained if the accretion disk is assumed to have a big blue bump in its spectrum. Hence, we favor an AGN at the nucleus as the source responsible for ionizing the observed RRLs. A hybrid model consisting of an inner advection-dominated accretion flow disk and an outer thin disk is suggested, which could explain the radio, UV, and X-ray luminosities of the nucleus.

Notes on approximations for turbulent flows with large temperature differences

The diffusion terms in the mean velocity and temperature equations of turbulent flow are analysed to decide when variations of fluid properties can produce appreciable errors. # A theoretical demonstration is given that in the mean-flow continuity equation for a gas the error in assuming constant density is small if the flow is turbulent, even when the temperature variations are large. # Separate discussion is given of the case of local heat sources in turbulence, as large errors can occur there.

Three-dimensional laminar compressible boundary layers with large injection

The effect of large mass injection on the following three-dimensional laminar compressible boundary-layer flows is investigated by employing the method of matched asymptotic expansions: (i) swirling flow in a laminar compressible boundary layer over an axisymmetric surface with variable cross-section and (ii) laminar compressible boundary-layer flow over a yawed infinite wing in a hypersonic flow. The resulting equations are solved numerically by combining the finite-difference technique with quasi-linearization. An increase in the swirl parameter, the yaw angle or the wall temperature is found to be capable of bringing the viscous layer nearer the surface and reducing the effects of massive blowing.

Denaturant mediated unfolding of both native and molten globule states of maltose binding protein are accompanied by large [Delta]Cp's

Maltose binding protein (MBP) is a large, monomeric two domain protein containing 370 amino acids. In the absence of denaturant at neutral pH, the protein is in the native state, while at pH 3.0 it forms a molten globule. The molten globule lacks a tertiary circular dichroism signal but has secondary structure similar to that of the native state. The molten globule binds 8-anilino-1-naphthalene sulfonate (ANS). The unfolding thermodynamics of MBP at both pHs were measured by carrying out a series of isothermal urea melts at temperatures ranging from 274–329 K. At 298 K, values of [Delta]G°, [Delta]Cp, and Cm were 3.1 ± 0.2 kcal mol−1, 5.9 ± 0.8 kcal mol−1 K−1 (15.9 cal (mol-residue)−1 K−1), and 0.8 M, respectively, at pH 3.0 and 14.5 ± 0.4 kcal mol−1, 8.3 ± 0.7 kcal mol−1 K−1 (22.4 kcal (mol-residue)−1 K−1), and 3.3 M, respectively, at pH 7.1. Guanidine hydrochloride denaturation at pH 7.1 gave values of [Delta]G° and [Delta]Cp similar to those obtained with urea. The m values for denaturation are strongly temperature dependent, in contrast to what has been previously observed for small globular proteins. The value of [Delta]Cp per mol-residue for the molten globule is comparable to corresponding values of [Delta]Cp for the unfolding of typical globular proteins and suggests that it is a highly ordered structure, unlike molten globules of many small proteins. The value of [Delta]Cp per mol-residue for the unfolding of the native state is among the highest currently known for any protein.

Dynamic subspace clustering for very large high-dimensional databases

Emerging high-dimensional data mining applications needs to find interesting clusters embeded in arbitrarily aligned subspaces of lower dimensionality. It is difficult to cluster high-dimensional data objects, when they are sparse and skewed. Updations are quite common in dynamic databases and they are usually processed in batch mode. In very large dynamic databases, it is necessary to perform incremental cluster analysis only to the updations. We present a incremental clustering algorithm for subspace clustering in very high dimensions, which handles both insertion and deletions of datapoints to the backend databases.

Mapping of large scale 158 mu m [CII] line emission: Orion A

We present the first results of an observational programme undertaken to map the fine structure line emission of singly ionized carbon ([ CII] 157 : 7409 mum) over extended regions using a Fabry Perot spectrometer newly installed at the focal plane of a 100 cm balloon- borne far- infrared telescope. This new combination of instruments has a velocity resolution of similar to 200 km s(-1) and an angular resolution of 1.'5. During the first flight, an area of 30' x 15' in Orion A was mapped. These observations extend over a larger area than previous observations, the map is fully sampled and the spectral scanning method used enables reliable estimation of the continuum emission at frequencies adjacent to the [ CII] line. The total [ CII] line luminosity, calculated by considering up to 20% of the maximum line intensity is 0.04% of the luminosity of the far- infrared continuum. We have compared the [ CII] intensity distribution with the velocity- integrated intensity distributions of (CO)-C-13(1- 0), CI(1- 0) and CO( 3- 2) from the literature. Comparison of the [ CII], [ CI] and the radio continuum intensity distributions indicates that the largescale [ CII] emission originates mainly from the neutral gas, except at the position of M 43, where no [ CI] emission corresponding to the [ CII] emission is seen. Substantial part of the [ CII] emission from here originates from the ionized gas. The observed line intensities and ratios have been analyzed using the PDR models by Kaufman et al. ( 1999) to derive the incident UV flux and volume density at a few selected positions. The models reproduce the observations reasonably well at most positions excepting the [ CII] peak ( which coincides with the position of theta(1) Ori C). Possible reason for the failure could be the simplifying assumption of a homogeneous plane parallel slab in place of a more complicated geometry.

Regionalization of precipitation in data sparse areas using large scale atmospheric variables - A fuzzy clustering approach

Delineation of homogeneous precipitation regions (regionalization) is necessary for investigating frequency and spatial distribution of meteorological droughts. The conventional methods of regionalization use statistics of precipitation as attributes to establish homogeneous regions. Therefore they cannot be used to form regions in ungauged areas, and they may not be useful to form meaningful regions in areas having sparse rain gauge density. Further, validation of the regions for homogeneity in precipitation is not possible, since the use of the precipitation statistics to form regions and subsequently to test the regional homogeneity is not appropriate. To alleviate this problem, an approach based on fuzzy cluster analysis is presented. It allows delineation of homogeneous precipitation regions in data sparse areas using large scale atmospheric variables (LSAV), which influence precipitation in the study area, as attributes. The LSAV, location parameters (latitude, longitude and altitude) and seasonality of precipitation are suggested as features for regionalization. The approach allows independent validation of the identified regions for homogeneity using statistics computed from the observed precipitation. Further it has the ability to form regions even in ungauged areas, owing to the use of attributes that can be reliably estimated even when no at-site precipitation data are available. The approach was applied to delineate homogeneous annual rainfall regions in India, and its effectiveness is illustrated by comparing the results with those obtained using rainfall statistics, regionalization based on hard cluster analysis, and meteorological sub-divisions in India. (C) 2011 Elsevier B.V. All rights reserved.

Large rapidity gaps survival probabilities at LHC

We calculate the probability of large rapidity gaps in high energy hadronic collisions using a model based on QCD mini-jets and soft gluon emission down into the infrared region. Comparing with other models we find a remarkable agreement among most predictions.

A Randomized Algorithm for Large Scale Support Vector Learning

We propose a randomized algorithm for large scale SVM learning which solves the problem by iterating over random subsets of the data. Crucial to the algorithm for scalability is the size of the subsets chosen. In the context of text classification we show that, by using ideas from random projections, a sample size of O(log n) can be used to obtain a solution which is close to the optimal with a high probability. Experiments done on synthetic and real life data sets demonstrate that the algorithm scales up SVM learners, without loss in accuracy. 1