CO excitation in the Seyfert galaxy NGC 34: stars, shock or AGN driven?

We present a detailed analysis of the X-ray and molecular gas emission in the nearby galaxy NGC 34, to constrain the properties of molecular gas, and assess whether, and to what extent, the radiation produced by the accretion onto the central black hole affects the CO line emission. We analyse the CO Spectral Line Energy Distribution (SLED) as resulting mainly from Herschel and ALMA data, along with X-ray data from NuSTAR and XMM-Newton. The X-ray data analysis suggests the presence of a heavily obscured AGN with an intrinsic luminosity of L$_{\rm{1-100\,keV}} \simeq 4.0\times10^{42}$ erg s$^{-1}$. ALMA high resolution data ($\theta \simeq 0.2''$) allows us to scan the nuclear region down to a spatial scale of $\approx 100$ pc for the CO(6-5) transition. We model the observed SLED using Photo-Dissociation Region (PDR), X-ray-Dominated Region (XDR), and shock models, finding that a combination of a PDR and an XDR provides the best fit to the observations. The PDR component, characterized by gas density ${\rm log}(n/{\rm cm^{-3}})=2.5$ and temperature $T=30$ K, reproduces the low-J CO line luminosities. The XDR is instead characterised by a denser and warmer gas (${\rm log}(n/{\rm cm^{-3}})=4.5$, $T =65$ K), and is necessary to fit the high-J transitions. The addition of a third component to account for the presence of shocks has been also tested but does not improve the fit of the CO SLED. We conclude that the AGN contribution is significant in heating the molecular gas in NGC 34.Comment: Accepted for publication in MNRAS. 10 pages, 6 figure

D2D Communications for Large-Scale Fog Platforms: Enabling Direct M2M Interactions

To many, fog computing is considered the next step beyond the current centralized cloud that will support the forthcoming Internet of Things (IoT) revolution. While IoT devices will still communicate with applications running in the cloud, localized fog clusters will appear with IoT devices communicating with application logic running on a proximate fog node. This will add proximity-based machine-to-machine (M2M) communications to standard cloud-computing traffic, and it calls for efficient mobility management for entire fog clusters and energy-efficient communication within them. In this context, long-term evolution-advanced (LTE-A) technology is expected to play a major role as a communication infrastructure that guarantees low deployment costs, native mobility support, and plug-and-play seamless configuration. We investigate the role of LTE-A in future large-scale IoT systems. In particular, we analyze how the recently standardized device-to-device (D2D) communication mode can be exploited to effectively enable direct M2M interactions within fog clusters, and we assess the expected benefits in terms of network resources and energy consumption. Moreover, we show how the fog-cluster architecture, and its localized-communication paradigm, can be leveraged to devise enhanced mobility management, building on what LTE-A already has to offer

CO excitation in the Seyfert galaxy NGC 34: Stars, shock or AGN driven?

We present a detailed analysis of the X-ray and molecular gas emission in the nearby galaxy NGC 34, to constrain the properties of molecular gas, and assess whether, and to what extent, the radiation produced by the accretion on to the central black hole affects the CO line emission. We analyse the CO spectral line energy distribution (SLED) as resulting mainly from Herschel and ALMA data, along with X-ray data from NuSTAR and XMM-Newton. The X-ray data analysis suggests the presence of a heavily obscured active galactic nucleus (AGN) with an intrinsic luminosity of L1-100 keV ≃ 4.0 × 1042 erg s-1. ALMA high-resolution data (θ ≃ 0.2 arcsec) allow us to scan the nuclear region down to a spatial scale of ≈100 pc for the CO(6-5) transition. We model the observed SLED using photodissociation region (PDR), X-ray-dominated region (XDR), and shock models, finding that a combination of a PDR and an XDR provides the best fit to the observations. The PDR component, characterized by gas density log(n/cm-3) = 2.5 and temperature T = 30 K, reproduces the low-J CO line luminosities. The XDR is instead characterized by a denser and warmer gas (log(n/cm-3) = 4.5, T = 65 K), and is necessary to fit the high-J transitions. The addition of a third component to account for the presence of shocks has been also tested but does not improve the fit of the CO SLED. We conclude that the AGN contribution is significant in heating the molecular gas in NGC 34

Safety of AAV Factor IX Peripheral Transvenular Gene Delivery to Muscle in Hemophilia B Dogs

Muscle represents an attractive target tissue for adeno-associated virus (AAV) vector–mediated gene transfer for hemophilia B (HB). Experience with direct intramuscular (i.m.) administration of AAV vectors in humans showed that the approach is safe but fails to achieve therapeutic efficacy. Here, we present a careful evaluation of the safety profile (vector, transgene, and administration procedure) of peripheral transvenular administration of AAV-canine factor IX (cFIX) vectors to the muscle of HB dogs. Vector administration resulted in sustained therapeutic levels of cFIX expression. Although all animals developed a robust antibody response to the AAV capsid, no T-cell responses to the capsid antigen were detected by interferon (IFN)-γ enzyme-linked immunosorbent spot (ELISpot). Interleukin (IL)-10 ELISpot screening of lymphocytes showed reactivity to cFIX-derived peptides, and restimulation of T cells in vitro in the presence of the identified cFIX epitopes resulted in the expansion of CD4+FoxP3+IL-10+ T-cells. Vector administration was not associated with systemic inflammation, and vector spread to nontarget tissues was minimal. At the local level, limited levels of cell infiltrates were detected when the vector was administered intravascularly. In summary, this study in a large animal model of HB demonstrates that therapeutic levels of gene transfer can be safely achieved using a novel route of intravascular gene transfer to muscle

GASP XXIV. The history of abruptly quenched galaxies in clusters

The study of cluster post starburst galaxies gives useful insights on the physical processes quenching the star formation in the most massive environments. Exploiting the MUSE data of the GAs Stripping Phenomena in galaxies (GASP) project, we characterise the quenching history of 8 local cluster galaxies that were selected for not showing emission lines in their fiber spectra. We inspect the integrated colors, the Hb rest frame equivalent widths (EW), star formation histories (SFHs) and luminosity-weighted age (LWA) maps finding no signs of current star formation throughout the disks of these early-spiral/S0 galaxies. All of them have been passive for at least 20 Myr, but their SF declined on different timescales. In most of them the outskirts reached undetectable SFRs before the inner regions (outside-in quenching). Our sample includes three post-starforming galaxies, two passive galaxies and three galaxies with intermediate properties. The first population shows blue colors, deep Hb in absorption (EW>>2.8A), young ages (8.8<log(LW [yr])<9.2). Two of these galaxies show signs of a central SF enhancement before quenching. Passive galaxies have instead red colors, EW(Hb)<2.8A, ages in the range 9.2<log(LWA[yr])<10. Finally, the other galaxies are most likely in transition between a post starforming and passive phase, as they quenched in an intermediate epoch and have not lost all the star forming features yet. The outside-in quenching, the morphology and kinematics of the stellar component, along with the position of these galaxies within massive clusters (sigma_cl=550-950km/s) point to a scenario in which ram pressure stripping has removed the gas, leading to quenching. Only the three most massive galaxies might alternatively have entered the clusters already quenched. These galaxies are therefore at the final stage of the rapid evolution galaxies undergo when they enter the clusters.Comment: 24 pages, 10 figures accepted for publication in Ap

Resource dedication problem in a multi-project environment

There can be different approaches to the management of resources within the context of multi-project scheduling problems. In general, approaches to multiproject scheduling problems consider the resources as a pool shared by all projects. On the other hand, when projects are distributed geographically or sharing resources between projects is not preferred, then this resource sharing policy may not be feasible. In such cases, the resources must be dedicated to individual projects throughout the project durations. This multi-project problem environment is defined here as the resource dedication problem (RDP). RDP is defined as the optimal dedication of resource capacities to different projects within the overall limits of the resources and with the objective of minimizing a predetermined objective function. The projects involved are multi-mode resource constrained project scheduling problems with finish to start zero time lag and non-preemptive activities and limited renewable and nonrenewable resources. Here, the characterization of RDP, its mathematical formulation and two different solution methodologies are presented. The first solution approach is a genetic algorithm employing a new improvement move called combinatorial auction for RDP, which is based on preferences of projects for resources. Two different methods for calculating the projects’ preferences based on linear and Lagrangian relaxation are proposed. The second solution approach is a Lagrangian relaxation based heuristic employing subgradient optimization. Numerical studies demonstrate that the proposed approaches are powerful methods for solving this problem

The Complexity of Flow Expansion and Electrical Flow Expansion

FlowExpansion is a network design problem, in which the input consists of a flow network and a set of candidate edges, which may be added to the network. Adding a candidate incurs given costs. The goal is to determine the cheapest set of candidate edges that, if added, allow the demands to be satisfied. FlowExpansion is a variant of the Minimum-Cost Flow problem with non-linear edge costs. We study FlowExpansion for both graph-theoretical and electrical flow networks. In the latter case this problem is also known as the Transmission Network Expansion Planning problem. We give a structured view over the complexity of the variants of FlowExpansion that arise from restricting, e.g., the graph classes, the capacities, or the number of sources and sinks. Our goal is to determine which restrictions have a crucial impact on the computational complexity. The results in this paper range from polynomial-time algorithms for the more restricted variants over NP-hardness proofs to proofs that certain variants are NP-hard to approximate even within a logarithmic factor of the optimal solution

Joint Power Control and Structural Health Monitoring in Industry 4.0 Scenarios using Eclipse Arrowhead and Web of Things

The integration of legacy IoT ecosystems in Industry 4.0 scenarios requires human effort to adapt single devices. This process would highly benefit from features like device lookup, loose coupling and late binding. In this paper, we tackle the issue of integrating legacy monitoring systems and actuation systems in an industrial scenario, by looking into the Web of Things (WoT) as a communication standard and the Eclipse Arrowhead Framework (AHF) as a service orchestrator. More specifically, we propose a general architectural approach to enable closed-loop automation between the above mentioned legacy systems by leveraging the adaptation of the WoT to the AHF. Then, we develop a rule-based engine that enables the control of the actuation based on sensor values. Finally, we present a proof-of-concept use case where we integrate a Structural Health Monitoring (SHM) scenario with a power control actuation subsystem using the developed component

GASP XXX. The spatially resolved SFR-Mass relation in stripping galaxies in the local universe

The study of the spatially resolved Star Formation Rate-Mass (Sigma_SFR-Sigma_M) relation gives important insights on how galaxies assemble at different spatial scales. Here we present the analysis of the Sigma_SFR-Sigma_M of 40 local cluster galaxies undergoing ram pressure stripping drawn from the GAs Stripping Phenomena in galaxies (GASP) sample. Considering their integrated properties, these galaxies show a SFR enhancement with respect to undisturbed galaxies of similar stellar mass; we now exploit spatially resolved data to investigate the origin and location of the excess. Even on ~1kpc scales, stripping galaxies present a systematic enhancement of Sigma_SFR (~0.35 dex at Sigma_M =108^M_sun/kpc^2) at any given Sigma_M compared to their undisturbed counterparts. The excess is independent on the degree of stripping and of the amount of star formation in the tails and it is visible at all galactocentric distances within the disks, suggesting that the star formation is most likely induced by compression waves from ram pressure. Such excess is larger for less massive galaxies and decreases with increasing mass. As stripping galaxies are characterised by ionised gas beyond the stellar disk, we also investigate the properties of 411 star forming clumps found in the galaxy tails. At any given stellar mass density, these clumps are systematically forming stars at a higher rate than in the disk, but differences are reconciled when we just consider the mass formed in the last few 10^8yr ago, suggesting that on these timescales the local mode of star formation is similar in the tails and in the disks.Comment: 20 pages, 13 figures, accepted for publication in Ap