Molecular abundances in the magellanic clouds .1. A multiline study of five cloud cores

Nine H II regions of the LMC were mapped in (CO)-C-13(1-0) and three in (CO)-C-12(1-0) to study the physical properties of the interstellar medium in the Magellanic Clouds. For N113 the molecular core is found to have a peak position which differs from that of the associated H II region by 20 ''. Toward this molecular core the (CO)-C-12 and (CO)-C-13 peak T-MB line temperatures of 7.3 K and 1.2 K are the highest so far found in the Magellanic Clouds. The molecular concentrations associated with N113, N44BC, N159HW, and N214DE in the LMC and LIRS 36 in the SMC were investigated in a variety of molecular species to study the chemical properties of the interstellar medium. I(HCO+)/I(HCN) and I(HCN)/I(HNC) intensity ratios as well as lower limits to the I((CO)-C-13)/I((CO)-O-18) ratio were derived for the rotational 1-0 transitions. Generally, HCO+ is stronger than HCN, and HCN is stronger than HNC. The high relative HCO+ intensities are consistent with a high ionization flux from supernovae remnants and young stars, possibly coupled with a large extent of the HCO+ emission region. The bulk of the HCN arises from relatively compact dense cloud cores. Warm or shocked gas enhances HCN relative to HNC. From chemical model calculations it is predicted that I(HCN)/I(HNC) close to one should be obtained with higher angular resolution (less than or similar to 30 '') toward the cloud cores. Comparing virial masses with those obtained from the integrated CO intensity provides an H-2 mass-to-CO luminosity conversion factor of 1.8 x 10(20) mol cm(-2) (K km s(-1))(-1) for N113 and 2.4 x 10(20) mol cm(-2) (K km s(-1))(-1) for N44BC. This is consistent with values derived for the Galactic disk.

THE EFFECT OF VARYING COSMIC-RAY IONIZATION RATES ON DARK CLOUD CHEMISTRY

We investigate the effects of varying the cosmic ray ionization rate in chemical models of dense interstellar clouds. In the absence of such ionization, a scenario which may be applicable to dark cloud cores, we find that chemi-ionization is able to drive a limited ion-neutral chemistry. Models of clouds in starburst galaxies, which may have enhanced cosmic ray fluxes, are also investigated and enable an upper limit to be derived for the cosmic ray ionization rate in M82. The derived value, which is about 700 times the typical value for Galactic molecular clouds, is in good agreement with that necessary to explain the recent observations of C I in this galaxy.

The VLT-FLAMES survey of massive stars: wind properties and evolution of hot massive stars in the Large Magellanic Cloud

We have studied the optical spectra of a sample of 28 O- and early B-type stars in the Large Magellanic Cloud, 22 of which are associated with the young star forming region N11. Our observations sample the central associations of LH9 and LH10, and the surrounding regions. Stellar parameters are determined using an automated fitting method ( Mokiem et al. 2005), which combines the stellar atmosphere code fastwind ( Puls et al. 2005) with the genetic algorithm based optimisation routine PIKAIA ( Charbonneau 1995). We derive an age of 7.0 +/- 1.0 and 3.0 +/- 1.0 Myr for LH9 and LH10, respectively. The age difference and relative distance of the associations are consistent with a sequential star formation scenario in which stellar activity in LH9 triggered the formation of LH10. Our sample contains four stars of spectral type O2. From helium and hydrogen line fitting we find the hottest three of these stars to be similar to 49- 54 kK ( compared to similar to 45- 46 kK for O3 stars). Detailed determination of the helium mass fraction reveals that the masses of helium enriched dwarfs and giants derived in our spectroscopic analysis are systematically lower than those implied by non-rotating evolutionary tracks. We interpret this as evidence for efficient rotationally enhanced mixing leading to the surfacing of primary helium and to an increase of the stellar luminosity. This result is consistent with findings for SMC stars by Mokiem et al. ( 2006). For bright giants and supergiants no such mass discrepancy is found; these stars therefore appear to follow tracks of modestly or non-rotating objects. The set of programme stars was sufficiently large to establish the mass loss rates of OB stars in this Z similar to 1/2 Z(circle dot) environment sufficiently accurate to allow for a quantitative comparison with similar objects in the Galaxy and the SMC. The mass loss properties are found to be intermediate to massive stars in the Galaxy and SMC. Comparing the derived modified wind momenta D-mom as a function of luminosity with predictions for LMC metallicities by Vink et al. ( 2001) yields good agreement in the entire luminosity range that was investigated, i.e. 5.0

The VLT-FLAMES survey of massive stars: observations centered on the Magellanic Cloud clusters NGC 330, NGC 346, NGC 2004, and the N11 region

We present new observations of 470 stars using the Fibre Large Array Multi-Element Spectrograph ( FLAMES) instrument in fields centered on the clusters NGC330 and NGC346 in the Small Magellanic Cloud (SMC), and NGC2004 and the N11 region in the Large Magellanic Cloud (LMC). A further 14 stars were observed in the N11 and NGC330 fields using the Ultraviolet and Visual Echelle Spectrograph (UVES) for a separate programme. Spectral classifications and stellar radial velocities are given for each target, with careful attention to checks for binarity. In particular, we have investigated previously unexplored regions around the central LH9/LH10 complex of N11, finding similar to 25 new O-type stars from our spectroscopy. We have observed a relatively large number of Be-type stars that display permitted Fe II emission lines. These are primarily not in the cluster cores and appear to be associated with classical Be-type stars, rather than pre main-sequence objects. The presence of the Fe II emission, as compared to the equivalent width of Ha, is not obviously dependent on metallicity. We have also explored the relative fraction of Be- to normal B-type stars in the field-regions near to NGC330 and NGC2004, finding no strong evidence of a trend with metallicity when compared to Galactic results. A consequence of service observations is that we have reasonable time-sampling in three of our FLAMES fields. We find lower limits to the binary fraction of O- and early B-type stars of 23 to 36%. One of our targets (NGC346-013) is especially interesting with a massive, apparently hotter, less luminous secondary component.

A constraints-based resource discovery model for multi-provider cloud environments

Increasingly infrastructure providers are supplying the cloud marketplace with storage and on-demand compute resources to host cloud applications. From an application user's point of view, it is desirable to identify the most appropriate set of available resources on which to execute an application. Resource choice can be complex and may involve comparing available hardware specifications, operating systems, value-added services, such as network configuration or data replication, and operating costs, such as hosting cost and data throughput. Providers' cost models often change and new commodity cost models, such as spot pricing, have been introduced to offer significant savings. In this paper, a software abstraction layer is used to discover infrastructure resources for a particular application, across multiple providers, by using a two-phase constraints-based approach. In the first phase, a set of possible infrastructure resources are identified for a given application. In the second phase, a heuristic is used to select the most appropriate resources from the initial set. For some applications a cost-based heuristic is most appropriate; for others a performance-based heuristic may be used. A financial services application and a high performance computing application are used to illustrate the execution of the proposed resource discovery mechanism. The experimental result shows the proposed model could dynamically select an appropriate set of resouces that match the application's requirements.

Spitzer Space Telescope spectra of post-AGB stars in the large magellanic Cloud-polycyclic aromatic hydrocarbons at low metallicities

This paper reports variations of polycyclic aromatic hydrocarbons (PAHs) features that were found in Spitzer Space Telescope spectra of carbon-rich post-asymptotic giant branch (post-AGB) stars in the Large Magellanic Cloud (LMC). The paper consists of two parts. The first part describes our Spitzer spectral observing programme of 24 stars including post-AGB candidates. The latter half of this paper presents the analysis of PAH features in 20 carbon-rich post-AGB stars in the LMC, assembled from the Spitzer archive as well as from our own programme.We found that five post-AGB stars showed a broad feature with a peak at 7.7 μm, that had not been classified before. Further, the 10-13 μm PAH spectra were classified into four classes, one of which has three broad peaks at 11.3, 12.3 and 13.3 μm rather than two distinct sharp peaks at 11.3 and 12.7 μm, as commonly found in HII regions. Our studies suggest that PAHs are gradually processed while the central stars evolve from post-AGB phase to planetary nebulae, changing their composition before PAHs are incorporated into the interstellar medium. Although some metallicity dependence of PAH spectra exists, the evolutionary state of an object is more significant than its metallicity in determining the spectral characteristics of PAHs for LMC and Galactic post-AGB stars. © 2014 The Authors Published by Oxford University Press on behalf of the Royal Astronomical Society.

The CACTOS Vision of Context-Aware Cloud Topology Optimization and Simulation

Recent advances in hardware development coupled with the rapid adoption and broad applicability of cloud computing have introduced widespread heterogeneity in data centers, significantly complicating the management of cloud applications and data center resources. This paper presents the CACTOS approach to cloud infrastructure automation and optimization, which addresses heterogeneity through a combination of in-depth analysis of application behavior with insights from commercial cloud providers. The aim of the approach is threefold: to model applications and data center resources, to simulate applications and resources for planning and operation, and to optimize application deployment and resource use in an autonomic manner. The approach is based on case studies from the areas of business analytics, enterprise applications, and scientific computing.

Particle-in-cell simulation study of the interaction between a relativistically moving leptonic micro-cloud and ambient electrons

Context. The jets of compact accreting objects are composed of electrons and a mixture of positrons and ions. These outflows impinge on the interstellar or intergalactic medium and both plasmas interact via collisionless processes. Filamentation (beam-Weibel) instabilities give rise to the growth of strong electromagnetic fields. These fields thermalize the interpenetrating plasmas. 

Aims. Hitherto, the effects imposed by a spatial non-uniformity on filamentation instabilities have remained unexplored. We examine the interaction between spatially uniform background electrons and a minuscule cloud of electrons and positrons. The cloud size is comparable to that created in recent laboratory experiments and such clouds may exist close to internal and external shocks of leptonic jets. The purpose of our study is to determine the prevalent instabilities, their ability to generate electromagnetic fields and the mechanism, by which the lepton micro-cloud transfers energy to the background plasma. 

Methods. A square micro-cloud of equally dense electrons and positrons impinges in our particle-in-cell (PIC) simulation on a spatially uniform plasma at rest. The latter consists of electrons with a temperature of 1 keV and immobile ions. The initially charge- and current neutral micro-cloud has a temperature of 100 keV and a side length of 2.5 plasma skin depths of the micro-cloud. The side length is given in the reference frame of the background plasma. The mean speed of the micro-cloud corresponds to a relativistic factor of 15, which is relevant for laboratory experiments and for relativistic astrophysical outflows. The spatial distributions of the leptons and of the electromagnetic fields are examined at several times. 

Results. A filamentation instability develops between the magnetic field carried by the micro-cloud and the background electrons. The electromagnetic fields, which grow from noise levels, redistribute the electrons and positrons within the cloud, which boosts the peak magnetic field amplitude. The current density and the moduli of the electromagnetic fields grow aperiodically in time and steadily along the direction that is anti-parallel to the cloud's velocity vector. The micro-cloud remains conjoined during the simulation. The instability induces an electrostatic wakefield in the background plasma. 

Conclusions. Relativistic clouds of leptons can generate and amplify magnetic fields even if they have a microscopic size, which implies that the underlying processes can be studied in the laboratory. The interaction of the localized magnetic field and high-energy leptons will give rise to synchrotron jitter radiation. The wakefield in the background plasma dissipates the kinetic energy of the lepton cloud. Even the fastest lepton micro-clouds can be slowed down by this collisionless mechanism. Moderately fast charge- and current neutralized lepton micro-clouds will deposit their energy close to relativistic shocks and hence they do not constitute an energy loss mechanism for the shock.

A Lightweight Tool for Anomaly Detection in Cloud Data Centres

Cloud data centres are critical business infrastructures and the fastest growing service providers. Detecting anomalies in Cloud data centre operation is vital. Given the vast complexity of the data centre system software stack, applications and workloads, anomaly detection is a challenging endeavour. Current tools for detecting anomalies often use machine learning techniques, application instance behaviours or system metrics distribu- tion, which are complex to implement in Cloud computing environments as they require training, access to application-level data and complex processing. This paper presents LADT, a lightweight anomaly detection tool for Cloud data centres that uses rigorous correlation of system metrics, implemented by an efficient corre- lation algorithm without need for training or complex infrastructure set up. LADT is based on the hypothesis that, in an anomaly-free system, metrics from data centre host nodes and virtual machines (VMs) are strongly correlated. An anomaly is detected whenever correlation drops below a threshold value. We demonstrate and evaluate LADT using a Cloud environment, where it shows that the hosting node I/O operations per second (IOPS) are strongly correlated with the aggregated virtual machine IOPS, but this correlation vanishes when an application stresses the disk, indicating a node-level anomaly.