Sensing Subjective Well-being from Social Media

Subjective Well-being(SWB), which refers to how people experience the quality of their lives, is of great use to public policy-makers as well as economic, sociological research, etc. Traditionally, the measurement of SWB relies on time-consuming and costly self-report questionnaires. Nowadays, people are motivated to share their experiences and feelings on social media, so we propose to sense SWB from the vast user generated data on social media. By utilizing 1785 users' social media data with SWB labels, we train machine learning models that are able to "sense" individual SWB from users' social media. Our model, which attains the state-by-art prediction accuracy, can then be used to identify SWB of large population of social media users in time with very low cost.Comment: 12 pages, 1 figures, 2 tables, 10th International Conference, AMT 2014, Warsaw, Poland, August 11-14, 2014. Proceeding

Adherence to secondary stroke prevention strategies - Results from the German stroke data bank

Only very limited data are available concerning patient adherence to antithrombotic medication intended to prevent a recurrent stroke. Reduced adherence and compliance could significantly influence the effects of any stroke prevention strategies. This study from a large stroke data bank provides representative data concerning the rate of stroke victims adhering to their recommended preventive medication. During a 2-year period beginning January 1, 1998, all patients with acute stroke or TIA in 23 neurological departments with an acute stroke unit were included in the German Stroke Data Bank. Data were collected prospectively, reviewed, validated and processed in a central data management unit. Only 12 centers with a follow-up rate of 80% or higher were included in this evaluation. 3,420 patients were followed up after 3 months, and 2,640 patients were followed up one year after their stroke. After one year, 96% of all patients reported still adhere to at least one medical stroke prevention strategy. Of the patients receiving aspirin at discharge, 92.6% reported to use that medication after 3 months and 84% after one year, while 81.6 and 61.6% were the respective figures for clopidogrel, and 85.2 and 77.4% for oral anticoagulation. Most patients who changed medication switched from aspirin to clopidogrel. Under the conditions of this observational study, adherence to stroke prevention strategies is excellent. The highest adherence rate is noticed for aspirin and oral anticoagulation. After one year, very few patients stopped taking stroke preventive medication. Copyright (C) 2003 S. Karger AG, Basel

Local and global properties of conformally flat initial data for black hole collisions

We study physical properties of conformal initial value data for single and binary black hole configurations obtained using conformal-imaging and conformal-puncture methods. We investigate how the total mass M_tot of a dataset with two black holes depends on the configuration of linear or angular momentum and separation of the holes. The asymptotic behavior of M_tot with increasing separation allows us to make conclusions about an unphysical ``junk'' gravitation field introduced in the solutions by the conformal approaches. We also calculate the spatial distribution of scalar invariants of the Riemann tensor which determine the gravitational tidal forces. For single black hole configurations, these are compared to known analytical solutions. Spatial distribution of the invariants allows us to make certain conclusions about the local distribution of the additional field in the numerical datasets

Dynamical mean-field equations for strongly interacting fermionic atoms in a potential trap

We derive a set of dynamical mean-field equations for strongly interacting fermionic atoms in a potential trap across a Feshbach resonance. Our derivation is based on a variational ansatz, which generalizes the crossover wavefunction to the inhomogeneous case, and the assumption that the order parameter is slowly varying over the size of the Cooper pairs. The equations reduce to a generalized time-dependent Gross-Pitaevskii equation on the BEC side of the resonance. We discuss an iterative method to solve these mean-field equations, and present the solution for a harmonic trap as an illustrating example to self-consistently verify the approximations made in our derivation.Comment: replaced with the published versio

Accurate Evolutions of Orbiting Binary Black Holes

We present a detailed analysis of binary black hole evolutions in the last orbit and demonstrate consistent and convergent results for the trajectories of the individual bodies. The gauge choice can significantly affect the overall accuracy of the evolution. It is possible to reconcile certain gauge-dependent discrepancies by examining the convergence limit. We illustrate these results using an initial data set recently evolved by Brügmann et al. [Phys. Rev. Lett. 92, 211101 (2004)]. For our highest resolution and most accurate gauge, we estimate the duration of this data set's last orbit to be approximately 59MADM

Classification of Stabilometric Time-Series Using an Adaptive Fuzzy Inference Neural Network System

Stabilometry is a branch of medicine that studies balance-related human functions. The analysis of stabilometric-generated time series can be very useful to the diagnosis and treatment balance-related dysfunctions such as dizziness. In stabilometry, the key nuggets of information in a time series signal are concentrated within definite time periods known as events. In this study, a feature extraction scheme has been developed to identify and characterise the events. The proposed scheme utilises a statistical method that goes through the whole time series from the start to the end, looking for the conditions that define events, according to the experts¿ criteria. Based on these extracted features, an Adaptive Fuzzy Inference Neural Network (AFINN) has been applied for the classification of stabilometric signals. The experimental results validated the proposed methodology

Microwave-induced excess quasiparticles in superconducting resonators measured through correlated conductivity fluctuations

We have measured the number of quasiparticles and their lifetime in aluminium superconducting microwave resonators. The number of excess quasiparticles below 160 mK decreases from 72 to 17 $\mu$m$^{-3}$ with a 6 dB decrease of the microwave power. The quasiparticle lifetime increases accordingly from 1.4 to 3.5 ms. These properties of the superconductor were measured through the spectrum of correlated fluctuations in the quasiparticle system and condensate of the superconductor, which show up in the resonator amplitude and phase respectively. Because uncorrelated noise sources vanish, fluctuations in the superconductor can be studied with a sensitivity close to the vacuum noise