A Linear-Nonlinear Formulation of Einstein Equations for the Two-Body Problem in General Relativity

A formulation of Einstein equations is presented that could yield advantages in the study of collisions of binary compact objects during regimes between linear-nonlinear transitions. The key idea behind this formulation is a separation of the dynamical variables into i) a fixed conformal 3-geometry, ii) a conformal factor possessing nonlinear dynamics and iii) transverse-traceless perturbations of the conformal 3-geometry.Comment: 7 pages, no figure

Testing Library Specifications by Verifying Conformance Tests

Abstract. Formal specifications of standard libraries are necessary when statically verifying software that uses those libraries. Library specifications must be both correct, accurately reflecting library behavior, and useful, describing library behavior in sufficient detail to allow static verification of client programs. Specification and verification researchers regularly face the question of whether the library specifications we use are correct and useful, and we have collectively provided no good answers. Over the past few years we have created and refined a software engineering process, which we call the Formal CTD Process (FCTD), to address this problem. Although FCTD is primarily targeted toward those who write Java libraries (or specifications for existing Java libraries) using the Java Modeling Language (JML), its techniques are broadly applicable. The key to FCTD is its novel usage of library conformance test suites. Rather than executing the conformance tests, FCTD uses them to measure the correctness and utility of specifications through static verification. FCTD is beginning to see significant use within the JML community and is the cornerstone process of the JML Spec-a-thons, meetings that bring JML researchers and practitioners together for intensive specification writing sessions. This article describes the Formal CTD Process, its use in small case studies, and its broad application to the standard Java class library.

Irrotational binary neutron stars in quasiequilibrium

We report on numerical results from an independent formalism to describe the quasi-equilibrium structure of nonsynchronous binary neutron stars in general relativity. This is an important independent test of controversial numerical hydrodynamic simulations which suggested that nonsynchronous neutron stars in a close binary can experience compression prior to the last stable circular orbit. We show that, for compact enough stars the interior density increases slightly as irrotational binary neutron stars approach their last orbits. The magnitude of the effect, however, is much smaller than that reported in previous hydrodynamic simulations.Comment: 4 pages, 2 figures, revtex, accepted for publication in Phys. Rev.

The Relationship between Behavioural Changes, Cognitive Symptoms, and Functional Disability in Primary Progressive Aphasia: A Longitudinal Study

Background: The contribution of behavioural changes to functional decline is yet to be explored in primary progressive aphasia (PPA). Objectives: (1) investigate functional changes in two PPA variants [semantic (svPPA) and non-fluent (nfvPPA)], at baseline and after 12 months; (2) investigate baseline differences in behavioural changes between groups, and (3) explore predictors of functional decline after a 12-month period. Methods: A longitudinal study involving 29 people with PPA (18 svPPA; 11 nfvPPA) seen annually in Sydney/Australia was conducted. A total of 114 functional and behavioural assessments were included for within-group (repeated-measures ANOVA; annual rate of change; multiple regression analyses) and between-group analyses (pairwise comparisons). Results: Functional profiles in svPPA and nfvPPA were similar in people with up to 5 years of disease duration. Behavioural changes were marked in svPPA patients (stereotypical behaviour and apathy) but did not predict annual rate of change of functional abilities; global cognitive scores at baseline did. Despite mild behavioural changes in nfvPPA (disinhibition, apathy), these were significant predictors of annual rate of functional change. Conclusions: The presentation and interplay of behavioural changes and functional disability differ in svPPA and nfvPPA. These varying factors should be taken into account when considering prognosis, disease management, and selection of outcome measures for interventions

Towards a Realistic Neutron Star Binary Inspiral: Initial Data and Multiple Orbit Evolution in Full General Relativity

This paper reports on our effort in modeling realistic astrophysical neutron star binaries in general relativity. We analyze under what conditions the conformally flat quasiequilibrium (CFQE) approach can generate ``astrophysically relevant'' initial data, by developing an analysis that determines the violation of the CFQE approximation in the evolution of the binary described by the full Einstein theory. We show that the CFQE assumptions significantly violate the Einstein field equations for corotating neutron stars at orbital separations nearly double that of the innermost stable circular orbit (ISCO) separation, thus calling into question the astrophysical relevance of the ISCO determined in the CFQE approach. With the need to start numerical simulations at large orbital separation in mind, we push for stable and long term integrations of the full Einstein equations for the binary neutron star system. We demonstrate the stability of our numerical treatment and analyze the stringent requirements on resolution and size of the computational domain for an accurate simulation of the system.Comment: 22 pages, 18 figures, accepted to Phys. Rev.

Atmospheric Neutrino Oscillations and New Physics

We study the robustness of the determination of the neutrino masses and mixing from the analysis of atmospheric and K2K data under the presence of different forms of phenomenologically allowed new physics in the nu_mu--nu_tau sector. We focus on vector and tensor-like new physics interactions which allow us to treat, in a model independent way, effects due to the violation of the equivalence principle, violations of the Lorentz invariance both CPT conserving and CPT violating, non-universal couplings to a torsion field and non-standard neutrino interactions with matter. We perform a global analysis of the full atmospheric data from SKI together with long baseline K2K data in the presence of nu_mu -> nu_tau transitions driven by neutrino masses and mixing together with sub-dominant effects due to these forms of new physics. We show that within the present degree of experimental precision, the extracted values of masses and mixing are robust under those effects and we derive the upper bounds on the possible strength of these new interactions in the nu_mu--nu_tau sector.Comment: 22 pages, LaTeX file using RevTEX4, 5 figures and 4 tables include

On gravitational waves emitted by an ensemble of rotating neutron stars

We study the possibility to detect the gravitational wave background generated by all the neutron stars in the Galaxy with only one gravitational wave interferometric detector. The proposed strategy consists in squaring the detector's output and searching for a sidereal modulation. The shape of the squared signal is computed for a disk and a halo distribution of neutron stars. The required noise stability of the interferometric detector is discussed. We argue that a possible population of old neutron stars, originating from a high stellar formation rate at the birth of the Galaxy and not emitting as radio pulsars, could be detected by the proposed technique in the low frequency range of interferometric experiments.Comment: 14 pages, 2 PostScript figures, RevTeX, accepted for publication in Physical Review

Brane Big-Bang Brought by Bulk Bubble

We propose an alternative inflationary universe scenario in the context of Randall-Sundrum braneworld cosmology. In this new scenario the existence of extra-dimension(s) plays an essential role. First, the brane universe is initially in the inflationary phase driven by the effective cosmological constant induced by small mismatch between the vacuum energy in the 5-dimensional bulk and the brane tension. This mismatch arises since the bulk is initially in a false vacuum. Then, the false vacuum decay occurs, nucleating a true vacuum bubble with negative energy inside the bulk. The nucleated bubble expands in the bulk and consequently hits the brane, bringing a hot big-bang brane universe of the Randall-Sundrum type. Here, the termination of the inflationary phase is due to the change of the bulk vacuum energy. The bubble kinetic energy heats up the universe. As a simple realization, we propose a model, in which we assume an interaction between the brane and the bubble. We derive the constraints on the model parameters taking into account the following requirements: solving the flatness problem, no force which prohibits the bubble from colliding with the brane, sufficiently high reheating temperature for the standard nucleosynthesis to work, and the recovery of Newton's law up to 1mm. We find that a fine tuning is needed in order to satisfy the first and the second requirements simultaneously, although, the other constraints are satisfied in a wide range of the model parameters.Comment: 20pages, 5figures, some references added, the previous manuscript has been largely improve

A dynamic neural field approach to natural and efficient human-robot collaboration

A major challenge in modern robotics is the design of autonomous robots that are able to cooperate with people in their daily tasks in a human-like way. We address the challenge of natural human-robot interactions by using the theoretical framework of dynamic neural fields (DNFs) to develop processing architectures that are based on neuro-cognitive mechanisms supporting human joint action. By explaining the emergence of self-stabilized activity in neuronal populations, dynamic field theory provides a systematic way to endow a robot with crucial cognitive functions such as working memory, prediction and decision making . The DNF architecture for joint action is organized as a large scale network of reciprocally connected neuronal populations that encode in their firing patterns specific motor behaviors, action goals, contextual cues and shared task knowledge. Ultimately, it implements a context-dependent mapping from observed actions of the human onto adequate complementary behaviors that takes into account the inferred goal of the co-actor. We present results of flexible and fluent human-robot cooperation in a task in which the team has to assemble a toy object from its components.The present research was conducted in the context of the fp6-IST2 EU-IP Project JAST (proj. nr. 003747) and partly financed by the FCT grants POCI/V.5/A0119/2005 and CONC-REEQ/17/2001. We would like to thank Luis Louro, Emanuel Sousa, Flora Ferreira, Eliana Costa e Silva, Rui Silva and Toni Machado for their assistance during the robotic experiment

Shrinking a large dataset to identify variables associated with increased risk of Plasmodium falciparum infection in Western Kenya

Large datasets are often not amenable to analysis using traditional single-step approaches. Here, our general objective was to apply imputation techniques, principal component analysis (PCA), elastic net and generalized linear models to a large dataset in a systematic approach to extract the most meaningful predictors for a health outcome. We extracted predictors for Plasmodium falciparum infection, from a large covariate dataset while facing limited numbers of observations, using data from the People, Animals, and their Zoonoses (PAZ) project to demonstrate these techniques: data collected from 415 homesteads in western Kenya, contained over 1500 variables that describe the health, environment, and social factors of the humans, livestock, and the homesteads in which they reside. The wide, sparse dataset was simplified to 42 predictors of P. falciparum malaria infection and wealth rankings were produced for all homesteads. The 42 predictors make biological sense and are supported by previous studies. This systematic data-mining approach we used would make many large datasets more manageable and informative for decision-making processes and health policy prioritization