A Markov Chain Monte Carlo approach to the study of massive black hole binary systems with LISA

The Laser Interferometer Space Antenna (LISA) will produce a data stream containing a vast number of overlapping sources: from strong signals generated by the coalescence of massive black hole binary systems to much weaker radiation form sub-stellar mass compact binaries and extreme-mass ratio inspirals. It has been argued that the observation of weak signals could be hampered by the presence of loud ones and that they first need to be removed to allow such observations. Here we consider a different approach in which sources are studied simultaneously within the framework of Bayesian inference. We investigate the simplified case in which the LISA data stream contains radiation from a massive black hole binary system superimposed over a (weaker) quasi-monochromatic waveform generated by a white dwarf binary. We derive the posterior probability density function of the model parameters using an automatic Reversible Jump Markov Chain Monte Carlo algorithm (RJMCMC). We show that the information about the sources and noise are retrieved at the expected level of accuracy without the need of removing the stronger signal. Our analysis suggests that this approach is worth pursuing further and should be considered for the actual analysis of the LISA data.Comment: submitted to cqg as GWDAW-10 conference proceedings, 10 pages, 4 figures, some changes to plots and numerical detail

LISA Response Function and Parameter Estimation

We investigate the response function of LISA and consider the adequacy of its commonly used approximation in the high-frequency range of the observational band. We concentrate on monochromatic binary systems, such as white dwarf binaries. We find that above a few mHz the approxmation starts becoming increasingly inaccurate. The transfer function introduces additional amplitude and phase modulations in the measured signal that influence parameter estmation and, if not properly accounted for, lead to losses of signal-to-noise ratio.Comment: 4 pages, 2 figures, amaldi 5 conference proceeding

Studying the Longest ‘Legal’ U.S. Same-Sex Couples: A Case of Lessons Learned

We review methodological opportunities and lessons learned in conducting a longitudinal, prospective study of same-sex couples with civil unions, recruited from a population-based sample, who were compared with same-sex couples in their friendship circle who did not have civil unions, and heterosexual married siblings and their spouse. At Time 1 (2002), Vermont was the only US state to provide legal recognition similar to marriage to same-sex couples; couples came from other US states and other countries to obtain a civil union. At Time 2 (2005), only one US state had legalized same-sex marriage, and at Time 3 (2013) about half of US states had legalized same-sex marriage, some within weeks of the onset of the Time 3 study. Opportunities included sampling legalized same-sex relationships from a population; the use of heterosexual married couples and same-sex couples not in legalized relationships as comparison samples from within the same social network; comparisons between sexual minority and heterosexual women and men with and without children; improvements in statistical methods for non-independence of data and missing data; and the use of mixed methodologies. Lessons learned included obtaining funding, locating participants over time as technologies changed, and on-going shifts in marriage laws during the study

MCMC Exploration of Supermassive Black Hole Binary Inspirals

The Laser Interferometer Space Antenna will be able to detect the inspiral and merger of Super Massive Black Hole Binaries (SMBHBs) anywhere in the Universe. Standard matched filtering techniques can be used to detect and characterize these systems. Markov Chain Monte Carlo (MCMC) methods are ideally suited to this and other LISA data analysis problems as they are able to efficiently handle models with large dimensions. Here we compare the posterior parameter distributions derived by an MCMC algorithm with the distributions predicted by the Fisher information matrix. We find excellent agreement for the extrinsic parameters, while the Fisher matrix slightly overestimates errors in the intrinsic parameters.Comment: Submitted to CQG as a GWDAW-10 Conference Proceedings, 9 pages, 5 figures, Published Versio

Discrete Model of Ideological Struggle Accounting for Migration

A discrete in time model of ideological competition is formulated taking into account population migration. The model is based on interactions between global populations of non-believers and followers of different ideologies. The complex dynamics of the attracting manifolds is investigated. Conversion from one ideology to another by means of (i) mass media influence and (ii) interpersonal relations is considered. Moreover a different birth rate is assumed for different ideologies, the rate being assumed to be positive for the reference population, made of initially non-believers. Ideological competition can happen in one or several regions in space. In the latter case, migration of non-believers and adepts is allowed; this leads to an enrichment of the ideological dynamics. Finally, the current ideological situation in the Arab countries and China is commented upon from the point of view of the presently developed mathematical model. The massive forced conversion by Ottoman Turks in the Balkans is briefly discussed.Comment: 24 pages, with 5 figures and 52 refs.; prepared for a Special issue of Advances in Complex System

Facing the LISA Data Analysis Challenge

By being the first observatory to survey the source rich low frequency region of the gravitational wave spectrum, the Laser Interferometer Space Antenna (LISA) will revolutionize our understanding of the Cosmos. For the first time we will be able to detect the gravitational radiation from millions of galactic binaries, the coalescence of two massive black holes, and the inspirals of compact objects into massive black holes. The signals from multiple sources in each class, and possibly others as well, will be simultaneously present in the data. To achieve the enormous scientific return possible with LISA, sophisticated data analysis techniques must be developed which can mine the complex data in an effort to isolate and characterize individual signals. This proceedings paper very briefly summarizes the challenges associated with analyzing the LISA data, the current state of affairs, and the necessary next steps to move forward in addressing the imminent challenges.Comment: 4 pages, no figures, Proceedings paper for the TeV Particle Astrophysics II conference held Aug 28-31 at the Univ. of Wisconsi

Incorporating prior knowledge improves detection of differences in bacterial growth rate

BACKGROUND: Robust statistical detection of differences in the bacterial growth rate can be challenging, particularly when dealing with small differences or noisy data. The Bayesian approach provides a consistent framework for inferring model parameters and comparing hypotheses. The method captures the full uncertainty of parameter values, whilst making effective use of prior knowledge about a given system to improve estimation. RESULTS: We demonstrated the application of Bayesian analysis to bacterial growth curve comparison. Following extensive testing of the method, the analysis was applied to the large dataset of bacterial responses which are freely available at the web-resource, ComBase. Detection was found to be improved by using prior knowledge from clusters of previously analysed experimental results at similar environmental conditions. A comparison was also made to a more traditional statistical testing method, the F-test, and Bayesian analysis was found to perform more conclusively and to be capable of attributing significance to more subtle differences in growth rate. CONCLUSIONS: We have demonstrated that by making use of existing experimental knowledge, it is possible to significantly improve detection of differences in bacterial growth rate

Safety and pharmacokinetics of MM-302, a HER2-targeted antibody–liposomal doxorubicin conjugate, in patients with advanced HER2-positive breast cancer: A phase 1 dose-escalation study

BackgroundThis phase 1 dose-escalation trial studied MM-302, a novel HER2-targeted PEGylated antibody-liposomal doxorubicin conjugate, in HER2-positive locally advanced/metastatic breast cancer.MethodsPatients were enrolled in four cohorts: MM-302 monotherapy (8, 16, 30, 40, and 50 mg/m2 every 4 weeks [q4w]); MM-302 (30 or 40 mg/m2 q4w) plus trastuzumab (4 mg/kg q2w); MM-302 (30 mg/m2) plus trastuzumab (6 mg/kg) q3w; MM-302 (30 mg/m2) plus trastuzumab (6 mg/kg) and cyclophosphamide (450 mg/m2) q3w.ResultsSixty-nine patients were treated. The most common adverse events (AEs) were fatigue and nausea. Grade 3/4 AEs of special interest included neutropenia, fatigue, mucosal inflammation, anemia, thrombocytopenia, febrile neutropenia, and palmar-plantar erythrodysesthesia. The MTD was not reached. With MM-302 ≥ 30 mg/m2, overall response rate (ORR) was 13% and median progression-free survival (mPFS) 7.4 months (95% CI: 3·5-10·9) in all arms. In 25 anthracycline-naïve patients, ORR was 28·0% and mPFS 10·9 months (95% CI: 1·8-15·3). Imaging with 64Cu-labeled MM-302 visualized tumor-drug penetrance in tumors throughout the body, including the brain.ConclusionMM-302 monotherapy, in combination with trastuzumab, or trastuzumab plus cyclophosphamide, was well tolerated and showed promising efficacy. The selected phase 2 MM-302 dose was 30 mg/m2 plus 6 mg/kg trastuzumab q3w

Effect of intragastric acid stability of fat emulsions on gastric emptying, plasma lipid profile and postpradial satiety

Fat is often included in common foods as an emulsion of dispersed oil droplets to enhance the organoleptic quality and stability. The intragastric acid stability of emulsified fat may impact on gastric emptying, satiety and plasma lipid absorption. The aim of the present study was to investigate whether, compared with an acid-unstable emulsion, an acid-stable fat emulsion would empty from the stomach more slowly, cause more rapid plasma lipid absorption and cause greater satiety. Eleven healthy male volunteers received on two separate occasions 500 ml of 15% (w/w) [13C]palmitate-enriched olive oil-in-water emulsion meals which were either stable or unstable in the acid gastric environment. MRI was used to measure gastric emptying and the intragastric oil fraction of the meals. Blood sampling was used to measure plasma lipids and visual analogue scales were used to assess satiety. The acid-unstable fat emulsion broke and rapidly layered in the stomach. Gastric emptying of meal volume was slower for the acid-stable fat emulsion (P,0·0001; two-way ANOVA). The rate of energy delivery of fat from the stomach to the duodenum was not different up to t ¼ 110 min. The acid-stable emulsion induced increased fullness (P,0·05), decreased hunger (P,0·0002), decreased appetite (P,0·0001) and increased the concentration of palmitic acid tracer in the chylomicron fraction (P,0·04). This shows that it is possible to delay gastric emptying and increase satiety by stabilising the intragastric distribution of fat emulsions against the gastric acid environment. This could have implications for the design of novel foods

Optimal statistic for detecting gravitational wave signals from binary inspirals with LISA

A binary compact object early in its inspiral phase will be picked up by its nearly monochromatic gravitational radiation by LISA. But even this innocuous appearing candidate poses interesting detection challenges. The data that will be scanned for such sources will be a set of three functions of LISA's twelve data streams obtained through time-delay interferometry, which is necessary to cancel the noise contributions from laser-frequency fluctuations and optical-bench motions to these data streams. We call these three functions pseudo-detectors. The sensitivity of any pseudo-detector to a given sky position is a function of LISA's orbital position. Moreover, at a given point in LISA's orbit, each pseudo-detector has a different sensitivity to the same sky position. In this work, we obtain the optimal statistic for detecting gravitational wave signals, such as from compact binaries early in their inspiral stage, in LISA data. We also present how the sensitivity of LISA, defined by this optimal statistic, varies as a function of sky position and LISA's orbital location. Finally, we show how a real-time search for inspiral signals can be implemented on the LISA data by constructing a bank of templates in the sky positions.Comment: 22 pages, 15 eps figures, Latex, uses iopart style/class files. Based on talk given at the 8th Gravitational Wave Data Analysis Workshop, Milwaukee, USA, December 17-20, 2003. Accepted for publication in Class. Quant. Gra