Missing black holes in brightest cluster galaxies as evidence for the occurrence of superkicks in nature

We investigate the consequences of superkicks on the population of supermassive black holes (SMBHs) in the Universe residing in brightest cluster galaxies (BCGs). There is strong observational evidence that BCGs grew prominently at late times (up to a factor 2-4 in mass from z=1), mainly through mergers with satellite galaxies from the cluster, and they are known to host the most massive SMBHs ever observed. Those SMBHs are also expected to grow hierarchically, experiencing a series of mergers with other SMBHs brought in by merging satellites. Because of the net linear momentum taken away from the asymmetric gravitational wave emission, the remnant SMBH experiences a kick in the opposite direction. Kicks may be as large as ~5000 Km/s ("superkicks"), pushing the SMBHs out in the cluster outskirts for a time comparable to galaxy-evolution timescales. We predict, under a number of plausible assumptions, that superkicks can efficiently eject SMBHs from BCGs, bringing their occupation fraction down to a likely range 0.9<f<0.99 in the local Universe. Future thirty-meter-class telescopes like ELT and TMT will be capable of measuring SMBHs in hundreds of BCGs up to z=0.2, testing the occurrence of superkicks in nature and the strong-gravity regime of SMBH mergers.Comment: 19 pages, 11 figures, accepted for publication in MNRA

The intersection of race, sexual orientation, socioeconomic status, trans identity, and mental health outcomes

The present study examined patterns in trans individuals’ multiple identities and mental health outcomes. Cluster 1 (socioeconomic and racial privilege; n = 239) was characterized by individuals who identified as trans women or cross-dressers, lesbian, bisexual, or questioning; had associates degrees; reported household incomes of $60,000 or more a year; and were non-Latino White. Cluster 2 (educational privilege; n = 191) was characterized by individuals who identified as trans men or genderqueer, gay, or queer; had a bachelor’s degree; reported household incomes of$10,000 or less a year; and were people of color. There was a pattern of individuals in Cluster 1 who identified with two privileged identities (identifying as White and having higher household incomes), whereas individuals in Cluster 2 identified only formal education as a privilege. Individuals in Cluster 2 reported statistically significant levels of anxiety. Implications of these results for future research and clinical practice are examined.Accepted manuscrip

Graph cluster randomization: network exposure to multiple universes

A/B testing is a standard approach for evaluating the effect of online experiments; the goal is to estimate the `average treatment effect' of a new feature or condition by exposing a sample of the overall population to it. A drawback with A/B testing is that it is poorly suited for experiments involving social interference, when the treatment of individuals spills over to neighboring individuals along an underlying social network. In this work, we propose a novel methodology using graph clustering to analyze average treatment effects under social interference. To begin, we characterize graph-theoretic conditions under which individuals can be considered to be `network exposed' to an experiment. We then show how graph cluster randomization admits an efficient exact algorithm to compute the probabilities for each vertex being network exposed under several of these exposure conditions. Using these probabilities as inverse weights, a Horvitz-Thompson estimator can then provide an effect estimate that is unbiased, provided that the exposure model has been properly specified. Given an estimator that is unbiased, we focus on minimizing the variance. First, we develop simple sufficient conditions for the variance of the estimator to be asymptotically small in n, the size of the graph. However, for general randomization schemes, this variance can be lower bounded by an exponential function of the degrees of a graph. In contrast, we show that if a graph satisfies a restricted-growth condition on the growth rate of neighborhoods, then there exists a natural clustering algorithm, based on vertex neighborhoods, for which the variance of the estimator can be upper bounded by a linear function of the degrees. Thus we show that proper cluster randomization can lead to exponentially lower estimator variance when experimentally measuring average treatment effects under interference.Comment: 9 pages, 2 figure

Opaque Service Virtualisation: A Practical Tool for Emulating Endpoint Systems

Large enterprise software systems make many complex interactions with other services in their environment. Developing and testing for production-like conditions is therefore a very challenging task. Current approaches include emulation of dependent services using either explicit modelling or record-and-replay approaches. Models require deep knowledge of the target services while record-and-replay is limited in accuracy. Both face developmental and scaling issues. We present a new technique that improves the accuracy of record-and-replay approaches, without requiring prior knowledge of the service protocols. The approach uses Multiple Sequence Alignment to derive message prototypes from recorded system interactions and a scheme to match incoming request messages against prototypes to generate response messages. We use a modified Needleman-Wunsch algorithm for distance calculation during message matching. Our approach has shown greater than 99% accuracy for four evaluated enterprise system messaging protocols. The approach has been successfully integrated into the CA Service Virtualization commercial product to complement its existing techniques.Comment: In Proceedings of the 38th International Conference on Software Engineering Companion (pp. 202-211). arXiv admin note: text overlap with arXiv:1510.0142

Debt literacy, financial experiences, and overindebtedness

We analyze a national sample of Americans with respect to their debt literacy, financial experiences, and their judgments about the extent of their indebtedness. Debt literacy is measured by questions testing knowledge of fundamental concepts related to debt and by selfassessed financial knowledge. Financial experiences are the participants’ reported experiences with traditional borrowing, alternative borrowing, and investing activities. Overindebtedness is a self-reported measure. Overall, we find that debt literacy is low: only about one-third of the population seems to comprehend interest compounding or the workings of credit cards. Even after controlling for demographics, we find a strong relationship between debt literacy and both financial experiences and debt loads. Specifically, individuals with lower levels of debt literacy tend to transact in high-cost manners, incurring higher fees and using high-cost borrowing. In applying our results to credit cards, we estimate that as much as one-third of the charges and fees paid by less knowledgeable individuals can be attributed to ignorance. The less knowledgeable also report that their debt loads are excessive or that they are unable to judge their debt position. JEL Classification: D14, D9

Short-term trajectories of workplace bullying and its impact on strain: A latent class growth modeling approach

The aim of this weekly diary study was (a) to identify trajectories of workplace bullying over time and (b) to examine the association of each cluster with strain indicators (i.e., insomnia and anxiety/depression). A sample of 286 employees during 4 weeks of data was used (N occasions = 1,144). Results of latent class growth modeling showed that 3 trajectories could be identified: a nonbullying trajectory, which comprised 90.9% of the sample; an inverted U trajectory; and a delayed increase bullying trajectory; the latter two each had 4.2% of the participants. We found a significant interaction between time and trajectories when predicting insomnia and anxiety/depression, with each strain showing a differential pattern with each trajectory. It seems that the negative effects on insomnia are long-lasting and remain after bullying has already decreased. In the case of anxiety and depression, when bullying decreases strain indicators also decrease. In this study, by examining trajectories of bullying at work over time and their associations with strain, we provide new insights into the temporal dynamics of workplace bullying