Search for gravitational waves from Scorpius X-1 in the second Advanced LIGO observing run with an improved hidden Markov model

We present results from a semicoherent search for continuous gravitational waves from the low-mass x-ray binary Scorpius X-1, using a hidden Markov model (HMM) to track spin wandering. This search improves on previous HMM-based searches of LIGO data by using an improved frequency domain matched filter, the J-statistic, and by analyzing data from Advanced LIGO's second observing run. In the frequency range searched, from 60 to 650 Hz, we find no evidence of gravitational radiation. At 194.6 Hz, the most sensitive search frequency, we report an upper limit on gravitational wave strain (at 95% confidence) of h095%=3.47×10-25 when marginalizing over source inclination angle. This is the most sensitive search for Scorpius X-1, to date, that is specifically designed to be robust in the presence of spin wandering. © 2019 American Physical Society

Search for Tensor, Vector, and Scalar Polarizations in the Stochastic Gravitational-Wave Background

The detection of gravitational waves with Advanced LIGO and Advanced Virgo has enabled novel tests of general relativity, including direct study of the polarization of gravitational waves. While general relativity allows for only two tensor gravitational-wave polarizations, general metric theories can additionally predict two vector and two scalar polarizations. The polarization of gravitational waves is encoded in the spectral shape of the stochastic gravitational-wave background, formed by the superposition of cosmological and individually unresolved astrophysical sources. Using data recorded by Advanced LIGO during its first observing run, we search for a stochastic background of generically polarized gravitational waves. We find no evidence for a background of any polarization, and place the first direct bounds on the contributions of vector and scalar polarizations to the stochastic background. Under log-uniform priors for the energy in each polarization, we limit the energy densities of tensor, vector, and scalar modes at 95% credibility to Ω0T<5.58×10-8, Ω0V<6.35×10-8, and Ω0S<1.08×10-7 at a reference frequency f0=25 Hz. © 2018 American Physical Society

Erratum: "A Gravitational-wave Measurement of the Hubble Constant Following the Second Observing Run of Advanced LIGO and Virgo" (2021, ApJ, 909, 218)

[no abstract available

The BioPAX community standard for pathway data sharing

Biological Pathway Exchange (BioPAX) is a standard language to represent biological pathways at the molecular and cellular level and to facilitate the exchange of pathway data. The rapid growth of the volume of pathway data has spurred the development of databases and computational tools to aid interpretation; however, use of these data is hampered by the current fragmentation of pathway information across many databases with incompatible formats. BioPAX, which was created through a community process, solves this problem by making pathway data substantially easier to collect, index, interpret and share. BioPAX can represent metabolic and signaling pathways, molecular and genetic interactions and gene regulation networks. Using BioPAX, millions of interactions, organized into thousands of pathways, from many organisms are available from a growing number of databases. This large amount of pathway data in a computable form will support visualization, analysis and biological discovery. © 2010 Nature America, Inc. All rights reserved

Pathway and Protein Interaction Data: from XML to FDM Database

This paper describes our experience with the first steps towards integrating pathway and protein interaction data with other data sets within the framework of a federated database system based on the functional data model. We have made use of DTD and XML files produced by the BIND project. The DTD provides a specification for information about biomolecular interactions, complexes and pathways, and can be translated semi-automatically to a database schema. The load utility uses metadata derived from this schema to help identify data items of interest when recursively traversing a Prolog tree structure representing the XML data. We also show how derived functions can be used to make explicit those relationships that are present in data sets but which are not fully described in DTD files

Capturing Quantified Constraints in FOL, Through Interaction with a Relationship Graph

As new semantic web standards evolve to allow quantified rules in FOL, we need new ways to capture them from end users in RDFS(XML). We show how to do this against a graphic view of Entities and their Relationships (associated or derived). This even allows inclusion of existential quantifiers in readable fashion. The captured constraint can be tested by generating queries to search for violations in stored data. The constraint can then be automatically revised to exclude specific cases picked out by the user, who is spared worries about proper syntax and boolean connectives

A Mozart implementation of CP(BioNet)

The analysis of biochemical networks consists in studying the interactions between biological entities cooperating in complex cellular processes. To facilitate the expression of analyses and their computation, we introduced CP(BioNet), a constraint programming framework for the analysis of biochemical networks. An Oz-Mozart prototype of CP(BioNet) is described. This prototype consists of the implementation of a new kind of domain variables, graph domain variables, and the implementation of constraint propagators for constraints over graph-domain variables. These new variables and constraints are implemented in Oz and they can then be used like other domain variables in the Oz-Mozart platform. An implementation of a path constraint propagator is described in depth and constrained path finding tests are analysed to assess the tractability of our approach. Finally, an alternative Oz-Mozart data-structure for the graph-domain variables is presented and compared to the first one