An Intuitive Graphical Query Interface for Protégé Knowledge Bases

Emily is a graphical query engine for Protégé knowledge bases that was developed by the Structural Informatics Group (SIG) at the University of Washington. Currently this application is adapted for a specific knowledge model, the Foundational Model of Anatomy (FMA) [1], but it could readily be generalized for use with other Protégé knowledge bases. In developing the Emily query interface, our intent was to provide a tool that was simple and intuitive to use, like the Queries tab provided with Protégé, but with improved information retrieval capabilities. Although some more advanced query mechanisms exist, currently they are too complicated for non-expert end users. The Algernon tab [2], for example, provides extensive Protégé query capabilities but requires users to learn a query scripting language. We sought to develop a query interface that was intuitive enough for end users to operate, with only minor instruction, yet was powerful enough to gather interesting information from a knowledge base that was not easily attained by browsing alone

Emotion Differentiation as a Protective Factor Against Nonsuicidal Self-Injury in Borderline Personality Disorder

Evidence that nonsuicidal self-injury (NSSI) serves a maladaptive emotion regulation function in borderline personality disorder (BPD) has drawn attention to processes that may increase risk for NSSI by exacerbating negative emotion, such as rumination. However, more adaptive forms of emotion processing, including differentiating broad emotional experiences into nuanced emotion categories, might serve as a protective factoragainst NSSI. Using an experience-sampling diary, the present study tested whether differentiation of negative emotion was associated with lower frequency of NSSI acts and urges in 38 individuals with BPD who reported histories of NSSI. Participants completed a dispositional measure of rumination and a 21-day experience-sampling diary, which yielded an index of negative emotion differentiation and frequency of NSSI acts and urges. A significant rumination by negative emotion differentiation interaction revealed that rumination predicted higher rates of NSSI acts and urges in participants with difficulty differentiating their negative emotions. The results extend research on emotion differentiation into the clinical literature and provide empirical support for clinical theories that suggest emotion identification and labeling underlie strategies for adaptive self-regulation and decreased NSSI risk in BPD

Deviational simulation of phonon transport in graphene ribbons with ab initio scattering

We present a deviational Monte Carlo method for solving the Boltzmann-Peierls equation with ab initio 3-phonon scattering, for temporally and spatially dependent thermal transport problems in arbitrary geometries. Phonon dispersion relations and transition rates for graphene are obtained from density functional theory calculations. The ab initio scattering operator is simulated by an energy-conserving stochastic algorithm embedded within a deviational, low-variance Monte Carlo formulation. The deviational formulation ensures that simulations are computationally feasible for arbitrarily small temperature differences, while the stochastic treatment of the scattering operator is both efficient and exhibits no timestep error. The proposed method, in which geometry and phonon-boundary scattering are explicitly treated, is extensively validated by comparison to analytical results, previous numerical solutions and experiments. It is subsequently used to generate solutions for heat transport in graphene ribbons of various geometries and evaluate the validity of some common approximations found in the literature. Our results show that modeling transport in long ribbons of finite width using the homogeneous Boltzmann equation and approximating phonon-boundary scattering using an additional homogeneous scattering rate introduces an error on the order of 10% at room temperature, with the maximum deviation reaching 30% in the middle of the transition regime.Singapore-MIT Alliance for Research and TechnologyAmerican Society for Engineering Education. National Defense Science and Engineering Graduate FellowshipNational Science Foundation (U.S.). Graduate Research Fellowshi

Practical learning method for multi-scale entangled states

We describe a method for reconstructing multi-scale entangled states from a small number of efficiently-implementable measurements and fast post-processing. The method only requires single particle measurements and the total number of measurements is polynomial in the number of particles. Data post-processing for state reconstruction uses standard tools, namely matrix diagonalisation and conjugate gradient method, and scales polynomially with the number of particles. Our method prevents the build-up of errors from both numerical and experimental imperfections

Statistical comparison of capacity predictions for realistic MIMO channels

Journal ArticleThe impact of antenna polarization on channel capacity is explored in multiple-input, multiple-output (MIMO) systems. An idealized polarization model involving branch power rations (BPR's) and channel cross-coupling is incorporated into channel-specific capacity calculations. Results are compared for several measured channels including line-of-sight (LOS) and non-line-of-sight (NLOS) both indoors and outdoors yielding valuable sensitivity analyses for channel capacity. Virtually all channels achieve perchannel peak capacities of 50% above that of single-input, single-output (SISO) channels and are well suited to opportunistic scheduling. However, systems exclusively dependent on polarization diversity will often exhibit outage capacities of just 10% above SISO capacity and will perform worse than those dependent on additional degrees of freedom