On AdS to dS transitions in higher-curvature gravity

We study the possible existence of gravitational phase transitions from AdS to dS geometries in the context of higher-curvature gravities. We use Lanczos-Gauss-Bonnet (LGB) theory with a positive cosmological constant as a toy model. This theory has two maximally symmetric vacua with positive (dS) and negative (AdS) constant curvature. We show that a phase transition from the AdS vacuum to a dS black hole geometry takes place when the temperature reaches a critical value. The transition is produced by nucleation of bubbles of the new phase that expand afterwards. We claim that this phenomenon is not particular to the model under study, and shall also be part of generic gravitational theories with higher-curvature terms.Comment: 12 pages, 3 figures; v2: comments and references adde

Holographic Ward identities for symmetry breaking in two dimensions

We investigate symmetry breaking in two-dimensional field theories which have a holographic gravity dual. Being at large N, the Coleman theorem does not hold and Goldstone bosons are expected. We consider the minimal setup to describe a conserved current and a charged operator, and we perform holographic renormalization in order to find the correct Ward identities describing symmetry breaking. This involves some subtleties related to the different boundary conditions that a vector can have in the three-dimensional bulk. We establish which is the correct prescription that yields, after renormalization, the same Ward identities as in higher dimensions.Comment: 20 pages. v2 comments added. Version to appear in JHE

Foster Parents Plan International

Orang Tua Angka

SUSY Hidden in the Continuum

We study models where the superpartners of the ordinary particles have continuous spectra rather than being discrete states, which can occur when the supersymmetric standard model is coupled to an approximately conformal sector. We show that when superpartners that are well into the continuum are produced at a collider they tend to have long decay chains that step their way down through the continuum, emitting many fairly soft standard model particles along the way, with a roughly spherical energy distribution in the center of mass frame.Comment: 26 pages, 9 figures. Update of Fig.5 and added aknowledgement

A Distributed Approach to System-Level Prognostics

Prognostics, which deals with predicting remaining useful life of components, subsystems, and systems, is a key technology for systems health management that leads to improved safety and reliability with reduced costs. The prognostics problem is often approached from a component-centric view. However, in most cases, it is not specifically component lifetimes that are important, but, rather, the lifetimes of the systems in which these components reside. The system-level prognostics problem can be quite difficult due to the increased scale and scope of the prognostics problem and the relative Jack of scalability and efficiency of typical prognostics approaches. In order to address these is ues, we develop a distributed solution to the system-level prognostics problem, based on the concept of structural model decomposition. The system model is decomposed into independent submodels. Independent local prognostics subproblems are then formed based on these local submodels, resul ting in a scalable, efficient, and flexible distributed approach to the system-level prognostics problem. We provide a formulation of the system-level prognostics problem and demonstrate the approach on a four-wheeled rover simulation testbed. The results show that the system-level prognostics problem can be accurately and efficiently solved in a distributed fashion

AWARE: Platform for Autonomous self-deploying and operation of Wireless sensor-actuator networks cooperating with unmanned AeRial vehiclEs

This paper presents the AWARE platform that seeks to enable the cooperation of autonomous aerial vehicles with ground wireless sensor-actuator networks comprising both static and mobile nodes carried by vehicles or people. Particularly, the paper presents the middleware, the wireless sensor network, the node deployment by means of an autonomous helicopter, and the surveillance and tracking functionalities of the platform. Furthermore, the paper presents the first general experiments of the AWARE project that took place in March 2007 with the assistance of the Seville fire brigades

An Integrated Framework for Model-Based Distributed Diagnosis and Prognosis

Diagnosis and prognosis are necessary tasks for system reconfiguration and fault-adaptive control in complex systems. Diagnosis consists of detection, isolation and identification of faults, while prognosis consists of prediction of the remaining useful life of systems. This paper presents a novel integrated framework for model-based distributed diagnosis and prognosis, where system decomposition is used to enable the diagnosis and prognosis tasks to be performed in a distributed way. We show how different submodels can be automatically constructed to solve the local diagnosis and prognosis problems. We illustrate our approach using a simulated four-wheeled rover for different fault scenarios. Our experiments show that our approach correctly performs distributed fault diagnosis and prognosis in an efficient and robust manner

Semiautomated optical coherence tomography-guided robotic surgery for porcine lens removal.

PurposeTo evaluate semiautomated surgical lens extraction procedures using the optical coherence tomography (OCT)-integrated Intraocular Robotic Interventional Surgical System.SettingStein Eye Institute and Department of Mechanical and Aerospace Engineering, University of California, Los Angeles, USA.DesignExperimental study.MethodsSemiautomated lens extraction was performed on postmortem pig eyes using a robotic platform integrated with an OCT imaging system. Lens extraction was performed using a series of automated steps including robot-to-eye alignment, irrigation/aspiration (I/A) handpiece insertion, anatomic modeling, surgical path planning, and I/A handpiece navigation. Intraoperative surgical supervision and human intervention were enabled by real-time OCT image feedback to the surgeon via a graphical user interface. Manual preparation of the pig-eye models, including the corneal incision and capsulorhexis, was performed by a trained cataract surgeon before the semiautomated lens extraction procedures. A scoring system was used to assess surgical complications in a postoperative evaluation.ResultsComplete lens extraction was achieved in 25 of 30 eyes. In the remaining 5 eyes, small lens pieces (≤1.0 mm3) were detected near the lens equator, where transpupillary OCT could not image. No posterior capsule rupture or corneal leakage occurred. The mean surgical duration was 277 seconds ± 42 (SD). Based on a 3-point scale (0 = no damage), damage to the iris was 0.33 ± 0.20, damage to the cornea was 1.47 ± 0.20 (due to tissue dehydration), and stress at the incision was 0.97 ± 0.11.ConclusionsNo posterior capsule rupture was reported. Complete lens removal was achieved in 25 trials without significant surgical complications. Refinements to the procedures are required before fully automated lens extraction can be realized

A Structural Model Decomposition Framework for Systems Health Management

Systems health management (SHM) is an important set of technologies aimed at increasing system safety and reliability by detecting, isolating, and identifying faults; and predicting when the system reaches end of life (EOL), so that appropriate fault mitigation and recovery actions can be taken. Model-based SHM approaches typically make use of global, monolithic system models for online analysis, which results in a loss of scalability and efficiency for large-scale systems. Improvement in scalability and efficiency can be achieved by decomposing the system model into smaller local submodels and operating on these submodels instead. In this paper, the global system model is analyzed offline and structurally decomposed into local submodels. We define a common model decomposition framework for extracting submodels from the global model. This framework is then used to develop algorithms for solving model decomposition problems for the design of three separate SHM technologies, namely, estimation (which is useful for fault detection and identification), fault isolation, and EOL prediction. We solve these model decomposition problems using a three-tank system as a case study