UKIRT Widefield Infrared Survey for H2

We perform an unbiased search for outflows from YSOs along the Galactic Plane (GP). Our data has been taken as part of the UWISH2 survey (Froebrich et al. 2011). It uses as tracer the 1-0S(1) emission line of H2, and here we focus on a continuous 33 square degree sized region in Serpens and Aquila. We identify 130 outflows from which 94% are new discoveries. Thus, we increased the number of known MHOs by a factor of 15 in this area (Ioannidis & Froebrich 2012). The flux completeness limit for the flows is 3?10-18Wm-2. Typically, the known flows occupy the bright end of the flux distribution. Our survey thus increases the known integrated 1-0S(1) H2 flux from outflows only by a factor of two. We are able to assign possible driving sources to half of the outflows. Brighter MHOs are more likely to have a source candidate assigned to them

Kernel-based Inference of Functions over Graphs

The study of networks has witnessed an explosive growth over the past decades with several ground-breaking methods introduced. A particularly interesting -- and prevalent in several fields of study -- problem is that of inferring a function defined over the nodes of a network. This work presents a versatile kernel-based framework for tackling this inference problem that naturally subsumes and generalizes the reconstruction approaches put forth recently by the signal processing on graphs community. Both the static and the dynamic settings are considered along with effective modeling approaches for addressing real-world problems. The herein analytical discussion is complemented by a set of numerical examples, which showcase the effectiveness of the presented techniques, as well as their merits related to state-of-the-art methods.Comment: To be published as a chapter in `Adaptive Learning Methods for Nonlinear System Modeling', Elsevier Publishing, Eds. D. Comminiello and J.C. Principe (2018). This chapter surveys recent work on kernel-based inference of functions over graphs including arXiv:1612.03615 and arXiv:1605.07174 and arXiv:1711.0930

Laboratory Mouse Models for the Human Genome-Wide Associations

The agnostic screening performed by genome-wide association studies (GWAS) has uncovered associations for previously unsuspected genes. Knowledge about the functional role of these genes is crucial and laboratory mouse models can provide such information. Here, we describe a systematic juxtaposition of human GWAS-discovered loci versus mouse models in order to appreciate the availability of mouse models data, to gain biological insights for the role of these genes and to explore the extent of concordance between these two lines of evidence. We perused publicly available data (NHGRI database for human associations and Mouse Genome Informatics database for mouse models) and employed two alternative approaches for cross-species comparisons, phenotype- and gene-centric. A total of 293 single gene-phenotype human associations (262 unique genes and 69 unique phenotypes) were evaluated. In the phenotype-centric approach, we identified all mouse models and related ortholog genes for the 51 human phenotypes with a comparable phenotype in mice. A total of 27 ortholog genes were found to be associated with the same phenotype in humans and mice, a concordance that was significantly larger than expected by chance (p<0.001). In the gene-centric approach, we were able to locate at least 1 knockout model for 60% of the 262 genes. The knockouts for 35% of these orthologs displayed pre- or post-natal lethality. For the remaining non-lethal orthologs, the same organ system was involved in mice and humans in 71% of the cases (p<0.001). Our project highlights the wealth of available information from mouse models for human GWAS, catalogues extensive information on plausible physiologic implications for many genes, provides hypothesis-generating findings for additional GWAS analyses and documents that the concordance between human and mouse genetic association is larger than expected by chance and can be informative

Adding flexibility to multi-tenant networks

Cloud computing has been experiencing sharp development over the last years, leading to an increased demand for application migration to the cloud. Cloud providers, in an effort to attract more customers and earn their confidence, offer to tenants the illusion of an isolated network, exposing familiar abstractions. At the same time, creating this illusion poses challenging problems for the providers, as one tenant's traffic may interfere with another's in complicated, unpredictable ways. First, new challenges have arisen in administering access-control rules (ACLs). On the one hand, installing ACLs at the server is incompatible with bare-metal support and introduces unnecessary performance overhead. On the other hand, offloading the most popular ACLs on the limited hardware memory in Top-of-Rack (ToR) switches should not be conducted naïvely, as the existence of wildcard rules presents inter-rule dependencies that must be respected. Second, tenants' demands have evolved beyond requesting hardware resources; for instance, tenants may require bandwidth provisions between their resources or optimized access to a specific cloud service, e.g., a Mail server or a Database. Cloud providers have not adequately adapted to these expanding demands, therefore elevating hardware resources to "first class citizens," as non-hardware constraints are not considered during resource allocation, instead they are applied afterwards. In this thesis we propose two architectures that facilitate cloud providers in managing their shared network resources in a flexible way. First, we demonstrate virtual flow tables, a ToR architecture that handles ACLs using a two-level memory hierarchy. The most popular ACLs are stored in the limited hardware memory, respecting any dependencies between wildcard rules, while the ToR's supervisor engine maintains access to the entire ACL rule-set. Second, we present a two-tiered architecture for scheduling cloud resources, consisting of a resource-agnostic scheduling layer and a resource-specific enforcement layer. Network resources and constraints are taken into consideration during resource scheduling, instead of afterwards, while resource provisioning, as well as general network-management policies, are delegated to the resource-specific tier

Near-infrared H2 and continuum survey of extended green objects. II. Complete census for the northern Galactic plane

We discuss 94 Extended Green Objects (EGOs) in the northern Galactic plane cataloged by Cyganowski et al., based on near-infrared narrow H2 (2.122 μm) and continuum observations from the United Kingdom Infrared Telescope. This data set is three times larger than the one in our previous study and is unbiased by preselection. As discussed in the previous paper, the morphologies of the 4.5 μm emission generally resemble those of the near-infrared continuum, but are different from those of the H2 emission. Of our sample, only 28% of EGOs with H2 emission show similar morphologies between 4.5 μm and H2 emission. These results suggest that the 4.5 μm emission mainly comes from scattered continuum from the embedded young stellar objects, and partially from H2 emission. About half of EGOs are associated with H2 outflows, if the H 2 outflow incompleteness is considered. The H2 outflow detection rate for EGOs with K-band detections (61%) is significantly higher than for those without K-band detections (36%). This difference may be due to the fact that both H2 and K-band emissions are associated with outflows, i.e., H2 emission and K-band continuum are associated with shocks and outflow cavities, respectively. We also compared the correlation between the H2 outflows and Class I 44 GHz methanol masers from the literature. The methanol masers can be located upstream or downstream of the H2 outflows and some bright H2 spots or outflows are not associated with methanol masers, suggesting that methanol masers and H 2 emission trace different excitation conditions. © 2013. The American Astronomical Society. All rights reserved.