Cold atoms in U(3) gauge potentials

We explore the effects of artificial $U(3)$ gauge potentials on ultracold atoms. We study background gauge fields with both non-constant and constant Wilson loops around plaquettes, obtaining the energy spectra in each case. The scenario of metal-insulator transition for irrational fluxes is also examined. Finally, we discuss the effect of such a gauge potential on the superfluid-insulator transition for bosonic ultracold atoms.Comment: minor typos corrected; journal versio

Cognitive system to achieve human-level accuracy in automated assignment of helpdesk email tickets

Ticket assignment/dispatch is a crucial part of service delivery business with lot of scope for automation and optimization. In this paper, we present an end-to-end automated helpdesk email ticket assignment system, which is also offered as a service. The objective of the system is to determine the nature of the problem mentioned in an incoming email ticket and then automatically dispatch it to an appropriate resolver group (or team) for resolution. The proposed system uses an ensemble classifier augmented with a configurable rule engine. While design of classifier that is accurate is one of the main challenges, we also need to address the need of designing a system that is robust and adaptive to changing business needs. We discuss some of the main design challenges associated with email ticket assignment automation and how we solve them. The design decisions for our system are driven by high accuracy, coverage, business continuity, scalability and optimal usage of computational resources. Our system has been deployed in production of three major service providers and currently assigning over 40,000 emails per month, on an average, with an accuracy close to 90% and covering at least 90% of email tickets. This translates to achieving human-level accuracy and results in a net saving of about 23000 man-hours of effort per annum

Quasi-viscous accretion flow -- I: Equilibrium conditions and asymptotic behaviour

In a novel approach to studying viscous accretion flows, viscosity has been introduced as a perturbative effect, involving a first-order correction in the $\alpha$-viscosity parameter. This method reduces the problem of solving a second-order nonlinear differential equation (Navier-Stokes equation) to that of an effective first-order equation. Viscosity breaks down the invariance of the equilibrium conditions for stationary inflow and outflow solutions, and distinguishes accretion from wind. Under a dynamical systems classification, the only feasible critical points of this "quasi-viscous" flow are saddle points and spirals. A linearised and radially propagating time-dependent perturbation gives rise to secular instability on large spatial scales of the disc. Further, on these same length scales, the velocity evolution equation of the quasi-viscous flow has been transformed to bear a formal closeness with Schr\"odinger's equation with a repulsive potential. Compatible with the transport of angular momentum to the outer regions of the disc, a viscosity-limited length scale has been defined for the full spatial extent over which the accretion process would be viable.Comment: 15 page

Runtime monitoring in continuous deployment by differencing execution behavior model

\u3cp\u3eContinuous deployment techniques support rapid deployment of new software versions. Usually a new version is deployed on a limited scale, its behavior is monitored and compared against the previously deployed version and either the deployment of the new version is broadened, or one reverts to the previous version. The existing monitoring approaches, however, do not capture the differences in the execution behavior between the new and the previously deployed versions. We propose an approach to automatically discover execution behavior models for the deployed and the new version using the execution logs. Differences between the two models are identified and enriched such that spurious differences, e.g., due to logging statement modifications, are mitigated. The remaining differences are visualized as cohesive diff regions within the discovered behavior model, allowing one to effectively analyze them for, e.g., anomaly detection and release decision making. To evaluate the proposed approach, we conducted case study on Nutch, an open source application, and an industrial application. We discovered the execution behavior models for the two versions of applications and identified the diff regions between them. By analyzing the regions, we detected bugs introduced in the new versions of these applications. The bugs have been reported and later fixed by the developers, thus, confirming the effectiveness of our approach.\u3c/p\u3

Runtime monitoring in continuous deployment by differencing execution behavior model

Continuous deployment techniques support rapid deployment of new software versions. Usually a new version is deployed on a limited scale, its behavior is monitored and compared against the previously deployed version and either the deployment of the new version is broadened, or one reverts to the previous version. The existing monitoring approaches, however, do not capture the differences in the execution behavior between the new and the previously deployed versions. We propose an approach to automatically discover execution behavior models for the deployed and the new version using the execution logs. Differences between the two models are identified and enriched such that spurious differences, e.g., due to logging statement modifications, are mitigated. The remaining differences are visualized as cohesive diff regions within the discovered behavior model, allowing one to effectively analyze them for, e.g., anomaly detection and release decision making. To evaluate the proposed approach, we conducted case study on Nutch, an open source application, and an industrial application. We discovered the execution behavior models for the two versions of applications and identified the diff regions between them. By analyzing the regions, we detected bugs introduced in the new versions of these applications. The bugs have been reported and later fixed by the developers, thus, confirming the effectiveness of our approach

An Inducible and Secreted Eukaryote-Like Serine/Threonine Kinase of Salmonella enterica Serovar Typhi Promotes Intracellular Survival and Pathogenesis

Eukaryote-like serine/threonine kinases (eSTKs) constitute an important family of bacterial virulence factors. Genome analysis had predicted putative eSTKs in Salmonella enterica serovar Typhi, although their functional characterization and the elucidation of their role in pathogenesis are still awaited. We show here that the primary sequence and secondary structure of the t4519 locus of Salmonella Typhi Ty2 have all the signatures of eukaryotic superfamily kinases. t4519 encodes a�39-kDa protein (T4519), which shows serine/threonine kinase activities in vitro. Recombinant T4519 (rT4519) is autophosphorylated and phosphorylates the universal substrate myelin basic protein. Infection of macrophages results in decreased viability of the mutant (Ty2�t4519) strain, which is reversed by gene complementation. Moreover, reactive oxygen species produced by the macrophages signal to the bacteria to induce T4519, which is translocated to the host cell cytoplasm. That T4519 may target a host substrate(s) is further supported by the activation of host cellular signaling pathways and the induction of cytokines/chemokines.Finally, the role of T4519 in the pathogenesis of Salmonella Typhi is underscored by the significantly decreased mortality of mice infected with the Ty2�t4519 strain and the fact that the competitive index of this strain for causing systemic infection is 0.25% that of the wild-type strain. This study characterizes the first eSTK of Salmonella Typhi and demonstrates its role in promoting phagosomal survival of the bacteria within macrophages, which is a key determinant of pathogenesis. This, to the best of our knowledge, is the first study to describe the essential role of eSTKs in the in vivo pathogenesis of Salmonella spp