A VLT/FLAMES survey for massive binaries in Westerlund 1. IV. Wd1-5 – binary product and a pre-supernova companion for the magnetar CXOU J1647-45?

Context. The first soft gamma-ray repeater was discovered over three decades ago, and was subsequently identified as a magnetar, a class of highly magnetised neutron star. It has been hypothesised that these stars power some of the brightest supernovae known, and that they may form the central engines of some long duration gamma-ray bursts. However there is currently no consenus on the formation channel(s) of these objects. Aims. The presence of a magnetar in the starburst cluster Westerlund 1 implies a progenitor with a mass ≥40 M⊙, which favours its formation in a binary that was disrupted at supernova. To test this hypothesis we conducted a search for the putative pre-SN companion. Methods. This was accomplished via a radial velocity survey to identify high-velocity runaways, with subsequent non-LTE model atmosphere analysis of the resultant candidate, Wd1-5. Results. Wd1-5 closely resembles the primaries in the short-period binaries, Wd1-13 and 44, suggesting a similar evolutionary history, although it currently appears single. It is overluminous for its spectroscopic mass and we find evidence of He- and N-enrichement, O-depletion, and critically C-enrichment, a combination of properties that is difficult to explain under single star evolutionary paradigms. We infer a pre-SN history for Wd1-5 which supposes an initial close binary comprising two stars of comparable (~ 41 M⊙ + 35 M⊙) masses. Efficient mass transfer from the initially more massive component leads to the mass-gainer evolving more rapidly, initiating luminous blue variable/common envelope evolution. Reverse, wind-driven mass transfer during its subsequent WC Wolf-Rayet phase leads to the carbon pollution of Wd1-5, before a type Ibc supernova disrupts the binary system. Under the assumption of a physical association between Wd1-5 and J1647-45, the secondary is identified as the magnetar progenitor; its common envelope evolutionary phase prevents spin-down of its core prior to SN and the seed magnetic field for the magnetar forms either in this phase or during the earlier episode of mass transfer in which it was spun-up. Conclusions. Our results suggest that binarity is a key ingredient in the formation of at least a subset of magnetars by preventing spin-down via core-coupling and potentially generating a seed magnetic field. The apparent formation of a magnetar in a Type Ibc supernova is consistent with recent suggestions that superluminous Type Ibc supernovae are powered by the rapid spin-down of these objects.

Coreferentiality: A New Method for the Hypothesis-Based Analysis of Phenotypes Characterized by Multivariate Data

Many multifactorial biologic effects, particularly in the context of complex human diseases, are still poorly understood. At the same time, the systematic acquisition of multivariate data has become increasingly easy. The use of such data to analyze and model complex phenotypes, however, remains a challenge. Here, a new analytic approach is described, termed coreferentiality, together with an appropriate statistical test. Coreferentiality is the indirect relation of two variables of functional interest in respect to whether they parallel each other in their respective relatedness to multivariate reference data, which can be informative for a complex effect or phenotype. It is shown that the power of coreferentiality testing is comparable to multiple regression analysis, sufficient even when reference data are informative only to a relatively small extent of 2.5%, and clearly exceeding the power of simple bivariate correlation testing. Thus, coreferentiality testing uses the increased power of multivariate analysis, however, in order to address a more straightforward interpretable bivariate relatedness. Systematic application of this approach could substantially improve the analysis and modeling of complex phenotypes, particularly in the context of human study where addressing functional hypotheses by direct experimentation is often difficult.

Adaptation to being at-risk for Huntington's disease and the availability of genetic testing: Application of a stress and coping model

This study examined the utility of a stress/coping model in explaining adaptation in two groups of people at-risk for Huntington's Disease (HD): those who have not approached genetic testing services (non-testees) and those who have engaged a testing service (testees). The aims were (1) to compare testees and non-testees on stress/coping variables, (2) to examine relations between adjustment and the stress/coping predictors in the two groups, and (3) to examine relations between the stress/coping variables and testees' satisfaction with their first counselling session. Participants were 44 testees and 40 non-testees who completed questionnaires which measured the stress/coping variables: adjustment (global distress, depression, health anxiety, social and dyadic adjustment), genetic testing concerns, testing context (HD contact, experience, knowledge), appraisal (control, threat, self-efficacy), coping strategies (avoidance, self-blame, wishful thinking, seeking support, problem solving), social support and locus of control. Testees also completed a genetic counselling session satisfaction scale. As expected, non-testees reported lower self-efficacy and control appraisals, higher threat and passive avoidant coping than testees. Overall, results supported the hypothesis that within each group poorer adjustment would be related to higher genetic testing concerns, contact with HD, threat appraisals, passive avoidant coping and external locus of control, and lower levels of positive experiences with HD, social support, internal locus of control, self-efficacy, control appraisals, problem solving, emotional approach and seeking social support coping. Session satisfaction scores were positively correlated with dyadic adjustment, problem solving and positive experience with HD, and inversely related to testing concerns, and threat and control appraisals. Findings support the utility of the stress/coping model in explaining adaptation in people who have decided not to seek genetic testing for HD and those who have decided to engage a genetic testing service.

Is cannabis a gateway drug? Testing hypotheses about the relationship between cannabis use and the use of other illicit drugs

We outline and evaluate competing explanations of three relationships that have consistently been found between cannabis use and the use of other illicit drugs, namely, ( 1) that cannabis use typically precedes the use of other illicit drugs; and that ( 2) the earlier cannabis is used, and ( 3) the more regularly it is used, the more likely a young person is to use other illicit drugs. We consider three major competing explanations of these patterns: ( 1) that the relationship is due to the fact that there is a shared illicit market for cannabis and other drugs which makes it more likely that other illicit drugs will be used if cannabis is used; ( 2) that they are explained by the characteristics of those who use cannabis; and ( 3) that they reflect a causal relationship in which the pharmacological effects of cannabis on brain function increase the likelihood of using other illicit drugs. These explanations are evaluated in the light of evidence from longitudinal epidemiological studies, simulation studies, discordant twin studies and animal studies. The available evidence indicates that the association reflects in part but is not wholly explained by: ( 1) the selective recruitment to heavy cannabis use of persons with pre-existing traits ( that may be in part genetic) that predispose to the use of a variety of different drugs; ( 2) the affiliation of cannabis users with drug using peers in settings that provide more opportunities to use other illicit drugs at an earlier age; ( 3) supported by socialisation into an illicit drug subculture with favourable attitudes towards the use of other illicit drugs. Animal studies have raised the possibility that regular cannabis use may have pharmacological effects on brain function that increase the likelihood of using other drugs. We conclude with suggestions for the type of research studies that will enable a decision to be made about the relative contributions that social context, individual characteristics, and drug effects make to the relationship between cannabis use and the use of other drugs.

Binary sparse nonnegative matrix factorization

This paper presents a fast part-based subspace selection algorithm, termed the binary sparse nonnegative matrix factorization (B-SNMF). Both the training process and the testing process of B-SNMF are much faster than those of binary principal component analysis (B-PCA). Besides, B-SNMF is more robust to occlusions in images. Experimental results on face images demonstrate the effectiveness and the efficiency of the proposed B-SNMF.

The effects of negative affectivity on self-reported activity limitations in stroke patients:testing the symptom perception, disability and psychosomatic hypotheses

This study investigated whether Negative Affectivity (NA) causes bias in self-report measures of activity limitations or whether NA has a real, non-artifactual association with activity limitations. The Symptom Perception Hypothesis (NA negatively biases self-reporting), Disability Hypothesis (activity limitations cause NA) and Psychosomatic Hypothesis (NA causes activity limitations) were examined longitudinally using both self-report and objective activity limitations measures. Participants were 101 stroke patients and their caregivers interviewed within two weeks of discharge, six weeks later and six months post-discharge. NA and self-report, proxy-report and observed performance activity (walking) limitations were assessed at each interview. NA was associated with activity limitations across measures. Both the Disability and Psychosomatic Hypotheses were supported: initial NA predicted objective activity limitations at six weeks but, additionally, activity limitations at six weeks predicted NA at six months. These results suggest that NA both affects and is affected by activity limitations and does not simply influence reporting.

An autoregressive conditional filtering process to remove intraday seasonal volatility and its application to testing the noisy rational expectations model

We develop a new autoregressive conditional process to capture both the changes and the persistency of the intraday seasonal (U-shape) pattern of volatility in essay 1. Unlike other procedures, this approach allows for the intraday volatility pattern to change over time without the filtering process injecting a spurious pattern of noise into the filtered series. We show that prior deterministic filtering procedures are special cases of the autoregressive conditional filtering process presented here. Lagrange multiplier tests prove that the stochastic seasonal variance component is statistically significant. Specification tests using the correlogram and cross-spectral analyses prove the reliability of the autoregressive conditional filtering process. In essay 2 we develop a new methodology to decompose return variance in order to examine the informativeness embedded in the return series. The variance is decomposed into the information arrival component and the noise factor component. This decomposition methodology differs from previous studies in that both the informational variance and the noise variance are time-varying. Furthermore, the covariance of the informational component and the noisy component is no longer restricted to be zero. The resultant measure of price informativeness is defined as the informational variance divided by the total variance of the returns. The noisy rational expectations model predicts that uninformed traders react to price changes more than informed traders, since uninformed traders cannot distinguish between price changes caused by information arrivals and price changes caused by noise. This hypothesis is tested in essay 3 using intraday data with the intraday seasonal volatility component removed, as based on the procedure in the first essay. The resultant seasonally adjusted variance series is decomposed into components caused by unexpected information arrivals and by noise in order to examine informativeness.

Tests of the Intersensory Redundancy Hypothesis across early postnatal development

The Intersensory Redundancy Hypothesis (IRH; Bahrick & Lickliter, 2000, 2002, 2012) predicts that early in development information presented to a single sense modality will selectively recruit attention to modality-specific properties of stimulation and facilitate learning of those properties at the expense of amodal properties (unimodal facilitation). Vaillant (2010) demonstrated that bobwhite quail chicks prenatally exposed to a maternal call alone (unimodal stimulation) are able to detect a pitch change, a modality-specific property, in subsequent postnatal testing between the familiarized call and the same call with altered pitch. In contrast, chicks prenatally exposed to a maternal call paired with a temporally synchronous light (redundant audiovisual stimulation) were unable to detect a pitch change. According to the IRH (Bahrick & Lickliter, 2012), as development proceeds and the individual's perceptual abilities increase, the individual should detect modality-specific properties in both nonredundant, unimodal and redundant, bimodal conditions. However, when the perceiver is presented with a difficult task, relative to their level of expertise, unimodal facilitation should become evident. The first experiment of the present study exposed bobwhite quail chicks 24 hr after hatching to unimodal auditory, nonredundant audiovisual, or redundant audiovisual presentations of a maternal call for 10min/hr for 24 hours. All chicks were subsequently tested 24 hr after the completion of the stimulation (72 hr following hatching) between the familiarized maternal call and the same call with altered pitch. Chicks from all experimental groups (unimodal, nonredundant audiovisual, and redundant audiovisual exposure) significantly preferred the familiarized call over the pitch-modified call. The second experiment exposed chicks to the same exposure conditions, but created a more difficult task by narrowing the pitch range between the two maternal calls with which they were tested. Chicks in the unimodal and nonredundant audiovisual conditions demonstrated detection of the pitch change, whereas the redundant audiovisual exposure group did not show detection of the pitch change, providing evidence of unimodal facilitation. These results are consistent with predictions of the IRH and provide further support for the effects of unimodal facilitation and the role of task difficulty across early development.

An Autoregressive Conditional Filtering Process to remove Intraday Seasonal Volatility and its Application to Testing the Noisy Rational Expectations Model

We develop a new autoregressive conditional process to capture both the changes and the persistency of the intraday seasonal (U-shape) pattern of volatility in essay 1. Unlike other procedures, this approach allows for the intraday volatility pattern to change over time without the filtering process injecting a spurious pattern of noise into the filtered series. We show that prior deterministic filtering procedures are special cases of the autoregressive conditional filtering process presented here. Lagrange multiplier tests prove that the stochastic seasonal variance component is statistically significant. Specification tests using the correlogram and cross-spectral analyses prove the reliability of the autoregressive conditional filtering process. In essay 2 we develop a new methodology to decompose return variance in order to examine the informativeness embedded in the return series. The variance is decomposed into the information arrival component and the noise factor component. This decomposition methodology differs from previous studies in that both the informational variance and the noise variance are time-varying. Furthermore, the covariance of the informational component and the noisy component is no longer restricted to be zero. The resultant measure of price informativeness is defined as the informational variance divided by the total variance of the returns. The noisy rational expectations model predicts that uninformed traders react to price changes more than informed traders, since uninformed traders cannot distinguish between price changes caused by information arrivals and price changes caused by noise. This hypothesis is tested in essay 3 using intraday data with the intraday seasonal volatility component removed, as based on the procedure in the first essay. The resultant seasonally adjusted variance series is decomposed into components caused by unexpected information arrivals and by noise in order to examine informativeness.

An R-package for the Estimation and Testing of Multiple Covariates and Biomarker Interactions for Survival Data Based on Local Partial Likelihood

When we study the variables that a ffect survival time, we usually estimate their eff ects by the Cox regression model. In biomedical research, e ffects of the covariates are often modi ed by a biomarker variable. This leads to covariates-biomarker interactions. Here biomarker is an objective measurement of the patient characteristics at baseline. Liu et al. (2015) has built up a local partial likelihood bootstrap model to estimate and test this interaction e ffect of covariates and biomarker, but the R code developed by Liu et al. (2015) can only handle one variable and one interaction term and can not t the model with adjustment to nuisance variables. In this project, we expand the model to allow adjustment to nuisance variables, expand the R code to take any chosen interaction terms, and we set up many parameters for users to customize their research. We also build up an R package called "lplb" to integrate the complex computations into a simple interface. We conduct numerical simulation to show that the new method has excellent fi nite sample properties under both the null and alternative hypothesis. We also applied the method to analyze data from a prostate cancer clinical trial with acid phosphatase (AP) biomarker.

Bayesian Dependence Tests for Continuous, Binary and Mixed Continuous-Binary Variables

Tests for dependence of continuous, discrete and mixed continuous-discrete variables are ubiquitous in science. The goal of this paper is to derive Bayesian alternatives to frequentist null hypothesis significance tests for dependence. In particular, we will present three Bayesian tests for dependence of binary, continuous and mixed variables. These tests are nonparametric and based on the Dirichlet Process, which allows us to use the same prior model for all of them. Therefore, the tests are “consistent” among each other, in the sense that the probabilities that variables are dependent computed with these tests are commensurable across the different types of variables being tested. By means of simulations with artificial data, we show the effectiveness of the new tests.

Binary Mixtures of 1-Butyl-1-Methylpyrrolidinium Bis{(trifluoromethyl)Sulfonyl}Imide and Aliphatic Nitrile Solvents As Electrolyte for Electrochemical Double Layer Capacitors (Invited).

Electrochemical double layer capacitors (EDLCs), also known as supercapacitors, are promising energy storage devices, especially when considering high power applications [1]. EDLCs can be charged and discharged within seconds [1], feature high power (10 kW·kg-1) and an excellent cycle life (>500,000 cycles). All these properties are a result of the energy storage process of EDLCs, which relies on storing energy by charge separation instead of chemical redox reactions, as utilized in battery systems. Upon charging, double layers are forming at the electrode/electrolyte interface consisting of the electrolyte’s ions and electric charges at the electrode surface.In state-of-the-art EDLC systems activated carbons (AC) are used as active materials and tetraethylammonium tetrafluoroborate ([Et4N][BF4]) dissolved in organic solvents like propylene carbonate (PC) or acetonitrile (ACN) are commonly used as the electrolyte [2]. These combinations of materials allow operative voltages up to 2.7 V - 2.8 V and an energy in the order of 5 Wh·kg-1[3]. The energy of EDLCs is dependent on the square of the operative voltage, thus increasing the usable operative voltage has a strong effect on the delivered energy of the device [1]. Due to their high electrochemical stability, ionic liquids (ILs) were thoroughly investigated as electrolytes for EDLCs, as well as, batteries, enabling high operating voltages as high as 3.2 V - 3.5 V for the former [2]. While their unique ionic structure allows the usage of neat ILs as electrolyte in EDLCs, ILs suffer from low conductivity and high viscosity increasing the intrinsic resistance and, as a result, a lower power output of the device. In order to overcome this issue, the usage of blends of ionic liquids and organic solvents has been considered a feasible strategy as they combine high usable voltages, while still retaining good transport properties at the same time.In our recent work the ionic liquid 1-butyl-1-methylpyrrolidinium bis{(trifluoromethyl)sulfonyl}imide ([Pyrr14][TFSI]) was combined with two nitrile-based organic solvents, namely butyronitrile (BTN) and adiponitrile (ADN), and the resulting blends were investing regarding their usage in electrochemical double layer capacitors [4,5]. Firstly, the physicochemical properties were investigated, showing good transport properties for both blends, which are similar to the state-of-the-art combination of [Et4N][BF4] in PC. Secondly, the electrochemical properties for EDLC application were studied in depth revealing a high electrochemical stability with a maximum operative voltage as high as 3.7 V. In full cells these high voltage organic solvent based electrolytes have a good performance in terms of capacitance and an acceptable equivalent series resistance at cut-off voltages of 3.2 and 3.5 V. However, long term stability tests by float testing revealed stability issues when using a maximum voltage of 3.5 V for prolonged time, whereas at 3.2 V no such issues are observed (Fig. 1).Considering the obtained results, the usage of ADN and BTN blends with [Pyrr14][TFSI] in EDLCs appears to be an interesting alternative to state-of-the-art organic solvent based electrolytes, allowing the usage of higher maximum operative voltages while having similar transport properties to 1 mol∙dm-3 [Et4N][BF4] in PC at the same time.

Finite Population Inference for Causal Parameters

Thesis (Ph.D.)--University of Washington, 2016-08

A Binary Classifier for Test Case Feasibility Applied to Automatically Generated Tests of Event-Driven Software

Modern software application testing, such as the testing of software driven by graphical user interfaces (GUIs) or leveraging event-driven architectures in general, requires paying careful attention to context. Model-based testing (MBT) approaches first acquire a model of an application, then use the model to construct test cases covering relevant contexts. A major shortcoming of state-of-the-art automated model-based testing is that many test cases proposed by the model are not actually executable. These \textit{infeasible} test cases threaten the integrity of the entire model-based suite, and any coverage of contexts the suite aims to provide. In this research, I develop and evaluate a novel approach for classifying the feasibility of test cases. I identify a set of pertinent features for the classifier, and develop novel methods for extracting these features from the outputs of MBT tools. I use a supervised logistic regression approach to obtain a model of test case feasibility from a randomly selected training suite of test cases. I evaluate this approach with a set of experiments. The outcomes of this investigation are as follows: I confirm that infeasibility is prevalent in MBT, even for test suites designed to cover a relatively small number of unique contexts. I confirm that the frequency of infeasibility varies widely across applications. I develop and train a binary classifier for feasibility with average overall error, false positive, and false negative rates under 5\%. I find that unique event IDs are key features of the feasibility classifier, while model-specific event types are not. I construct three types of features from the event IDs associated with test cases, and evaluate the relative effectiveness of each within the classifier. To support this study, I also develop a number of tools and infrastructure components for scalable execution of automated jobs, which use state-of-the-art container and continuous integration technologies to enable parallel test execution and the persistence of all experimental artifacts.

Defensive role of allelopathic secondary compounds in plants I: testing two independent general hypotheses

This study tests two general and independent hypotheses with the basic assumption that phytoactive secondary compounds produced by plants evolved primarily as plant defences against competitor plant species. The first hypothesis is that the production and main way of release of phytoactive compounds reflect an adaptive response to climatic conditions. Thus, higher phytoactivity by volatile compounds prevails in plants of hot, dry environments, whereas higher phytoactivity by water-soluble compounds is preponderant in plants from wetter environments. The second hypothesis is that synergy between plant phytoactive compounds is widespread, due to the resulting higher energy efficiency and economy of resources. The first hypothesis was tested on germination and early growth of cucumber treated with either water extracts or volatiles from leaves or vegetative shoot tops of four Mediterranean-type shrubs. The second hypothesis was tested on germination of subterranean clover treated with either water extracts of leaves or vegetative shoot tops of one tree and of three Mediterranean-type shrubs or with each of the three fractions obtained from water extracts. Our data do not support either hypotheses. We found no evidence for higher phytoactivity in volatile compounds released by plants that thrive in hot, dry Mediterranean-type environments. We also found no evidence for the predominance of synergy among the constituents of fractions. To the contrary, we found either antagonism or no interaction of effects among allelopathic compounds.