Search for gravitational radiation from intermediate mass black hole binaries in data from the second LIGO-Virgo joint science run

This paper reports on an unmodeled, all-sky search for gravitational waves from merging intermediate mass black hole binaries (IMBHB). The search was performed on data from the second joint science run of the LIGO and Virgo detectors (July 2009-October 2010) and was sensitive to IMBHBs with a range up to similar to 200 Mpc, averaged over the possible sky positions and inclinations of the binaries with respect to the line of sight. No significant candidate was found. Upper limits on the coalescence-rate density of nonspinning IMBHBs with total masses between 100 and 450 M-circle dot and mass ratios between 0.25 and 1 were placed by combining this analysis with an analogous search performed on data from the first LIGO-Virgo joint science run (November 2005-October 2007). The most stringent limit was set for systems consisting of two 88 M-circle dot black holes and is equal to 0.12 Mpc(-3) Myr(-1) at the 90% confidence level. This paper also presents the first estimate, for the case of an unmodeled analysis, of the impact on the search range of IMBHB spin configurations: the visible volume for IMBHBs with nonspinning components is roughly doubled for a population of IMBHBs with spins aligned with the binary's orbital angular momentum and uniformly distributed in the dimensionless spin parameter up to 0.8, whereas an analogous population with antialigned spins decreases the visible volume by similar to 20%.

First all-sky search for continuous gravitational waves from unknown sources in binary systems

We present the first results of an all-sky search for continuous gravitational waves from unknown spinning neutron stars in binary systems using LIGO and Virgo data. Using a specially developed analysis program, the TwoSpect algorithm, the search was carried out on data from the sixth LIGO science run and the second and third Virgo science runs. The search covers a range of frequencies from 20 Hz to 520 Hz, a range of orbital periods from 2 to similar to 2,254 h and a frequency-and period-dependent range of frequency modulation depths from 0.277 to 100 mHz. This corresponds to a range of projected semimajor axes of the orbit from similar to 0.6 x 10(-3) ls to similar to 6,500 ls assuming the orbit of the binary is circular. While no plausible candidate gravitational wave events survive the pipeline, upper limits are set on the analyzed data. The most sensitive 95% confidence upper limit obtained on gravitational wave strain is 2.3 x 10(-24) at 217 Hz, assuming the source waves are circularly polarized. Although this search has been optimized for circular binary orbits, the upper limits obtained remain valid for orbital eccentricities as large as 0.9. In addition, upper limits are placed on continuous gravitational wave emission from the low-mass x-ray binary Scorpius X-1 between 20 Hz and 57.25 Hz.

Directed search for gravitational waves from Scorpius X-1 with initial LIGO data

We present results of a search for continuously emitted gravitational radiation, directed at the brightest low-mass x-ray binary, Scorpius X-1. Our semicoherent analysis covers 10 days of LIGO S5 data ranging from 50-550 Hz, and performs an incoherent sum of coherent F-statistic power distributed amongst frequency-modulated orbital sidebands. All candidates not removed at the veto stage were found to be consistent with noise at a 1% false alarm rate. We present Bayesian 95% confidence upper limits on gravitational-wave strain amplitude using two different prior distributions: a standard one, with no a priori assumptions about the orientation of Scorpius X-1; and an angle-restricted one, using a prior derived from electromagnetic observations. Median strain upper limits of 1.3 x 10(-24) and 8 x 10(-25) are reported at 150 Hz for the standard and angle-restricted searches respectively. This proof-of-principle analysis was limited to a short observation time by unknown effects of accretion on the intrinsic spin frequency of the neutron star, but improves upon previous upper limits by factors of similar to 1.4 for the standard, and 2.3 for the angle-restricted search at the sensitive region of the detector.

Polarimetry of the binary PDS 144

Aims. Our goal is to study the circumstellar environment associated with each component of the wide intermediate-mass pre-main sequence binary system PDS 144 using broadband polarimetry. Methods. We present near-infrared (NIR) linear polarimetric observations of PDS 144 gathered with the IAGPOL imaging polarimeter along with the CamIV infrared camera at the Observatorio do Pico dos Dias (OPD). In addition, we re-analyzed OPD archive optical polarization to separate the binary and estimate the interstellar polarization using foreground stars. Results. After discounting the interstellar component, we found that both stars of the binary system are intrinsically polarized. The polarization vectors at optical and NIR bands of both components are aligned with the local magnetic field and the jet axis. These findings indicate an interplay between the interstellar magnetic field and the formation of the binary system. We also found that the PDS 144N is less polarized than its southern companion in the optical. However, in the NIR PDS 144N is more polarized. Our polarization data can only be explained by high inclinations (i greater than or similar to 80 degrees) for the disks of both members. In particular, comparisons of our NIR data with young stellar objects disk models suggest predominantly small grains in the circumstellar environment of PDS 144N. In spite of the different grain types in each component, the infrared spectral indexes indicate a coeval system. We also found evidence of coplanarity between the disks.

Incorporating label dependency into the binary relevance framework for multi-label classification

In multi-label classification, examples can be associated with multiple labels simultaneously. The task of learning from multi-label data can be addressed by methods that transform the multi-label classification problem into several single-label classification problems. The binary relevance approach is one of these methods, where the multi-label learning task is decomposed into several independent binary classification problems, one for each label in the set of labels, and the final labels for each example are determined by aggregating the predictions from all binary classifiers. However, this approach fails to consider any dependency among the labels. Aiming to accurately predict label combinations, in this paper we propose a simple approach that enables the binary classifiers to discover existing label dependency by themselves. An experimental study using decision trees, a kernel method as well as Naive Bayes as base-learning techniques shows the potential of the proposed approach to improve the multi-label classification performance.

Measurements and correlations of the isobaric vapor-liquid equilibria of binary mixtures and excess properties for mixtures containing and alkyl (Methyl, Ethyl) butanoate with an alkane (Heptane, Nonane) at 101.32 kPa.

[EN]In this work, the measurements of the isobaric vapor−liquid equilibrium (VLE) data at 101.32 kPa and the excess molar volumes (vE), obtained at 10 K intervals of temperature in the range (288.15 to 328.15) K, for four binary systems comprised of methyl or ethyl butanoate with two alkanes (heptane and nonane) are presented.

Multiproperty correlation of experimental data of the binaries propyl ethanoate+alkanes (pentane to decane). New experimental information for vapor-liquid equilibrium and mixing properties

[EN]A thermodynamic study is carried out on binary systems composed of propyl ethanoate with six alkanes, from pentane to decane. Vapor pressures of the ester and the isobaric vapor−liquid equilibria of these six mixtures were measured at 101.32 kPa in a small-capacity ebulliometer and also the mixing properties yE = vE,hE over a range of temperatures and at atmospheric pressure. Adequate correlations are drawn for the surfaces yE = yE(x,T) with an interpretation on the behavior of the mixtures and also using cp E data from literature.

Cosmic-Lab: Optical companions to binary Millisecond Pulsars

Millisecond Pulsars (MSPs) are fast rotating, highly magnetized neutron stars. According to the "canonical recycling scenario", MSPs form in binary systems containing a neutron star which is spun up through mass accretion from the evolving companion. Therefore, the final stage consists of a binary made of a MSP and the core of the deeply peeled companion. In the last years, however an increasing number of systems deviating from these expectations has been discovered, thus strongly indicating that our understanding of MSPs is far to be complete. The identification of the optical companions to binary MSPs is crucial to constrain the formation and evolution of these objects. In dense environments such as Globular Clusters (GCs), it also allows us to get insights on the cluster internal dynamics. By using deep photometric data, acquired both from space and ground-based telescopes, we identified 5 new companions to MSPs. Three of them being located in GCs and two in the Galactic Field. The three new identifications in GCs increased by 50% the number of such objects known before this Thesis. They all are non-degenerate stars, at odds with the expectations of the "canonical recycling scenario". These results therefore suggest either that transitory phases should also be taken into account, or that dynamical processes, as exchange interactions, play a crucial role in the evolution of MSPs. We also performed a spectroscopic follow-up of the companion to PSRJ1740-5340A in the GC NGC 6397, confirming that it is a deeply peeled star descending from a ~0.8Msun progenitor. This nicely confirms the theoretical expectations about the formation and evolution of MSPs.

Palaeo wind system reconstruction of the last glacial period over Europe, using high resolution proxy data and model-data-comparison

The atmosphere is a global influence on the movement of heat and humidity between the continents, and thus significantly affects climate variability. Information about atmospheric circulation are of major importance for the understanding of different climatic conditions. Dust deposits from maar lakes and dry maars from the Eifel Volcanic Field (Germany) are therefore used as proxy data for the reconstruction of past aeolian dynamics.rnrnIn this thesis past two sediment cores from the Eifel region are examined: the core SM3 from Lake Schalkenmehren and the core DE3 from the Dehner dry maar. Both cores contain the tephra of the Laacher See eruption, which is dated to 12,900 before present. Taken together the cores cover the last 60,000 years: SM3 the Holocene and DE3 the marine isotope stages MIS-3 and MIS-2, respectively. The frequencies of glacial dust storm events and their paleo wind direction are detected by high resolution grain size and provenance analysis of the lake sediments. Therefore two different methods are applied: geochemical measurements of the sediment using µXRF-scanning and the particle analysis method RADIUS (rapid particle analysis of digital images by ultra-high-resolution scanning of thin sections).rnIt is shown that single dust layers in the lake sediment are characterized by an increased content of aeolian transported carbonate particles. The limestone-bearing Eifel-North-South zone is the most likely source for the carbonate rich aeolian dust in the lake sediments of the Dehner dry maar. The dry maar is located on the western side of the Eifel-North-South zone. Thus, carbonate rich aeolian sediment is most likely to be transported towards the Dehner dry maar within easterly winds. A methodology is developed which limits the detection to the aeolian transported carbonate particles in the sediment, the RADIUS-carbonate module.rnrnIn summary, during the marine isotope stage MIS-3 the storm frequency and the east wind frequency are both increased in comparison to MIS-2. These results leads to the suggestion that atmospheric circulation was affected by more turbulent conditions during MIS-3 in comparison to the more stable atmospheric circulation during the full glacial conditions of MIS-2.rnThe results of the investigations of the dust records are finally evaluated in relation a study of atmospheric general circulation models for a comprehensive interpretation. Here, AGCM experiments (ECHAM3 and ECHAM4) with different prescribed SST patterns are used to develop a synoptic interpretation of long-persisting east wind conditions and of east wind storm events, which are suggested to lead to an enhanced accumulation of sediment being transported by easterly winds to the proxy site of the Dehner dry maar.rnrnThe basic observations made on the proxy record are also illustrated in the 10 m-wind vectors in the different model experiments under glacial conditions with different prescribed sea surface temperature patterns. Furthermore, the analysis of long-persisting east wind conditions in the AGCM data shows a stronger seasonality under glacial conditions: all the different experiments are characterized by an increase of the relative importance of the LEWIC during spring and summer. The different glacial experiments consistently show a shift from a long-lasting high over the Baltic Sea towards the NW, directly above the Scandinavian Ice Sheet, together with contemporary enhanced westerly circulation over the North Atlantic.rnrnThis thesis is a comprehensive analysis of atmospheric circulation patterns during the last glacial period. It has been possible to reconstruct important elements of the glacial paleo climate in Central Europe. While the proxy data from sediment cores lead to a binary signal of the wind direction changes (east versus west wind), a synoptic interpretation using atmospheric circulation models is successful. This shows a possible distribution of high and low pressure areas and thus the direction and strength of wind fields which have the capacity to transport dust. In conclusion, the combination of numerical models, to enhance understanding of processes in the climate system, with proxy data from the environmental record is the key to a comprehensive approach to paleo climatic reconstruction.rn

Implementazione ed analisi di un framework basato su Cloud per la valutazione di algoritmi di data Distribution Management

Il Data Distribution Management (DDM) è un componente dello standard High Level Architecture. Il suo compito è quello di rilevare le sovrapposizioni tra update e subscription extent in modo efficiente. All'interno di questa tesi si discute la necessità di avere un framework e per quali motivi è stato implementato. Il testing di algoritmi per un confronto equo, librerie per facilitare la realizzazione di algoritmi, automatizzazione della fase di compilazione, sono motivi che sono stati fondamentali per iniziare la realizzazione framework. Il motivo portante è stato che esplorando articoli scientifici sul DDM e sui vari algoritmi si è notato che in ogni articolo si creavano dei dati appositi per fare dei test. L'obiettivo di questo framework è anche quello di riuscire a confrontare gli algoritmi con un insieme di dati coerente. Si è deciso di testare il framework sul Cloud per avere un confronto più affidabile tra esecuzioni di utenti diversi. Si sono presi in considerazione due dei servizi più utilizzati: Amazon AWS EC2 e Google App Engine. Sono stati mostrati i vantaggi e gli svantaggi dell'uno e dell'altro e il motivo per cui si è scelto di utilizzare Google App Engine. Si sono sviluppati quattro algoritmi: Brute Force, Binary Partition, Improved Sort, Interval Tree Matching. Sono stati svolti dei test sul tempo di esecuzione e sulla memoria di picco utilizzata. Dai risultati si evince che l'Interval Tree Matching e l'Improved Sort sono i più efficienti. Tutti i test sono stati svolti sulle versioni sequenziali degli algoritmi e che quindi ci può essere un riduzione nel tempo di esecuzione per l'algoritmo Interval Tree Matching.

Comparison of Roadside Crash Injury Metrics using Event Data Recorders

The occupant impact velocity (OIV) and acceleration severity index (ASI) are competing measures of crash severity used to assess occupant injury risk in full-scale crash tests involving roadside safety hardware, e.g. guardrail. Delta-V, or the maximum change in vehicle velocity, is the traditional metric of crash severity for real world crashes. This study compares the ability of the OIV, ASI, and delta-V to discriminate between serious and non-serious occupant injury in real world frontal collisions. Vehicle kinematics data from event data recorders (EDRs) were matched with detailed occupant injury information for 180 real world crashes. Cumulative probability of injury risk curves were generated using binary logistic regression for belted and unbelted data subsets. By comparing the available fit statistics and performing a separate ROC curve analysis, the more computationally intensive OIV and ASI were found to offer no significant predictive advantage over the simpler delta-V.

Secondary collisions revisited: real-world crash data and relationship to crash test criteria

Objectives: Previous research conducted in the late 1980s suggested that vehicle impacts following an initial barrier collision increase severe occupant injury risk. Now over 25years old, the data are no longer representative of the currently installed barriers or the present US vehicle fleet. The purpose of this study is to provide a present-day assessment of secondary collisions and to determine if current full-scale barrier crash testing criteria provide an indication of secondary collision risk for real-world barrier crashes. Methods: To characterize secondary collisions, 1,363 (596,331 weighted) real-world barrier midsection impacts selected from 13years (1997-2009) of in-depth crash data available through the National Automotive Sampling System (NASS) / Crashworthiness Data System (CDS) were analyzed. Scene diagram and available scene photographs were used to determine roadside and barrier specific variables unavailable in NASS/CDS. Binary logistic regression models were developed for second event occurrence and resulting driver injury. To investigate current secondary collision crash test criteria, 24 full-scale crash test reports were obtained for common non-proprietary US barriers, and the risk of secondary collisions was determined using recommended evaluation criteria from National Cooperative Highway Research Program (NCHRP) Report 350. Results: Secondary collisions were found to occur in approximately two thirds of crashes where a barrier is the first object struck. Barrier lateral stiffness, post-impact vehicle trajectory, vehicle type, and pre-impact tracking conditions were found to be statistically significant contributors to secondary event occurrence. The presence of a second event was found to increase the likelihood of a serious driver injury by a factor of 7 compared to cases with no second event present. The NCHRP Report 350 exit angle criterion was found to underestimate the risk of secondary collisions in real-world barrier crashes. Conclusions: Consistent with previous research, collisions following a barrier impact are not an infrequent event and substantially increase driver injury risk. The results suggest that using exit-angle based crash test criteria alone to assess secondary collision risk is not sufficient to predict second collision occurrence for real-world barrier crashes.

A modified test for small-study effects in meta-analyses of controlled trials with binary endpoints

Publication bias and related bias in meta-analysis is often examined by visually checking for asymmetry in funnel plots of treatment effect against its standard error. Formal statistical tests of funnel plot asymmetry have been proposed, but when applied to binary outcome data these can give false-positive rates that are higher than the nominal level in some situations (large treatment effects, or few events per trial, or all trials of similar sizes). We develop a modified linear regression test for funnel plot asymmetry based on the efficient score and its variance, Fisher's information. The performance of this test is compared to the other proposed tests in simulation analyses based on the characteristics of published controlled trials. When there is little or no between-trial heterogeneity, this modified test has a false-positive rate close to the nominal level while maintaining similar power to the original linear regression test ('Egger' test). When the degree of between-trial heterogeneity is large, none of the tests that have been proposed has uniformly good properties.

Quantifying and Comparing the Accuracy of Binary Biomarkers When Predicting a Failure Time Outcome

The positive and negative predictive value are standard measures used to quantify the predictive accuracy of binary biomarkers when the outcome being predicted is also binary. When the biomarkers are instead being used to predict a failure time outcome, there is no standard way of quantifying predictive accuracy. We propose a natural extension of the traditional predictive values to accommodate censored survival data. We discuss not only quantifying predictive accuracy using these extended predictive values, but also rigorously comparing the accuracy of two biomarkers in terms of their predictive values. Using a marginal regression framework, we describe how to estimate differences in predictive accuracy and how to test whether the observed difference is statistically significant.

A Data-Analytic Strategy for Protein-Biomarker Discovery: Profiling of High-Dimensional Proteomic Data for Cancer Detection

With recent advances in mass spectrometry techniques, it is now possible to investigate proteins over a wide range of molecular weights in small biological specimens. This advance has generated data-analytic challenges in proteomics, similar to those created by microarray technologies in genetics, namely, discovery of "signature" protein profiles specific to each pathologic state (e.g., normal vs. cancer) or differential profiles between experimental conditions (e.g., treated by a drug of interest vs. untreated) from high-dimensional data. We propose a data analytic strategy for discovering protein biomarkers based on such high-dimensional mass-spectrometry data. A real biomarker-discovery project on prostate cancer is taken as a concrete example throughout the paper: the project aims to identify proteins in serum that distinguish cancer, benign hyperplasia, and normal states of prostate using the Surface Enhanced Laser Desorption/Ionization (SELDI) technology, a recently developed mass spectrometry technique. Our data analytic strategy takes properties of the SELDI mass-spectrometer into account: the SELDI output of a specimen contains about 48,000 (x, y) points where x is the protein mass divided by the number of charges introduced by ionization and y is the protein intensity of the corresponding mass per charge value, x, in that specimen. Given high coefficients of variation and other characteristics of protein intensity measures (y values), we reduce the measures of protein intensities to a set of binary variables that indicate peaks in the y-axis direction in the nearest neighborhoods of each mass per charge point in the x-axis direction. We then account for a shifting (measurement error) problem of the x-axis in SELDI output. After these pre-analysis processing of data, we combine the binary predictors to generate classification rules for cancer, benign hyperplasia, and normal states of prostate. Our approach is to apply the boosting algorithm to select binary predictors and construct a summary classifier. We empirically evaluate sensitivity and specificity of the resulting summary classifiers with a test dataset that is independent from the training dataset used to construct the summary classifiers. The proposed method performed nearly perfectly in distinguishing cancer and benign hyperplasia from normal. In the classification of cancer vs. benign hyperplasia, however, an appreciable proportion of the benign specimens were classified incorrectly as cancer. We discuss practical issues associated with our proposed approach to the analysis of SELDI output and its application in cancer biomarker discovery.