Intermediate-mass-ratio-inspirals in the Einstein Telescope. II. Parameter estimation errors

We explore the precision with which the Einstein Telescope (ET) will be able to measure the parameters of intermediate-mass-ratio inspirals (IMRIs). We calculate the parameter estimation errors using the Fisher Matrix formalism and present results of a Monte Carlo simulation of these errors over choices for the extrinsic parameters of the source. These results are obtained using two different models for the gravitational waveform which were introduced in paper I of this series. These two waveform models include the inspiral, merger and ringdown phases in a consistent way. One of the models, based on the transition scheme of Ori & Thorne [1], is valid for IMBHs of arbitrary spin, whereas the second model, based on the Effective One Body (EOB) approach, has been developed to cross-check our results in the non-spinning limit. In paper I of this series, we demonstrated the excellent agreement in both phase and amplitude between these two models for non-spinning black holes, and that their predictions for signal-to-noise ratios (SNRs) are consistent to within ten percent. We now use these models to estimate parameter estimation errors for binary systems with masses 1.4+100, 10+100, 1.4+500 and 10+500 solar masses (SMs), and various choices for the spin of the central intermediate-mass black hole (IMBH). Assuming a detector network of three ETs, the analysis shows that for a 10 SM compact object (CO) inspiralling into a 100 SM IMBH with spin q=0.3, detected with an SNR of 30, we should be able to determine the CO and IMBH masses, and the IMBH spin magnitude to fractional accuracies of 0.001, 0.0003, and 0.001, respectively. We also expect to determine the location of the source in the sky and the luminosity distance to within 0.003 steradians, and 10%, respectively. We also assess how the precision of parameter determination depends on the network configuration.Comment: 21 pages, 5 figures. One reference corrected in v3 for consistency with published version in Phys Rev

Hierarchically-coupled hidden Markov models for learning kinetic rates from single-molecule data

We address the problem of analyzing sets of noisy time-varying signals that all report on the same process but confound straightforward analyses due to complex inter-signal heterogeneities and measurement artifacts. In particular we consider single-molecule experiments which indirectly measure the distinct steps in a biomolecular process via observations of noisy time-dependent signals such as a fluorescence intensity or bead position. Straightforward hidden Markov model (HMM) analyses attempt to characterize such processes in terms of a set of conformational states, the transitions that can occur between these states, and the associated rates at which those transitions occur; but require ad-hoc post-processing steps to combine multiple signals. Here we develop a hierarchically coupled HMM that allows experimentalists to deal with inter-signal variability in a principled and automatic way. Our approach is a generalized expectation maximization hyperparameter point estimation procedure with variational Bayes at the level of individual time series that learns an single interpretable representation of the overall data generating process.Comment: 9 pages, 5 figure

American Geriatrics Society and National Institute on Aging Bench-to-Bedside conference: sensory impairment and cognitive decline in older adults

This article summarizes the presentations and recommendations of the tenth annual American Geriatrics Society and National Institute on Aging Bench‐to‐Bedside research conference, “Sensory Impairment and Cognitive Decline,” on October 2–3, 2017, in Bethesda, Maryland. The risk of impairment in hearing, vision, and other senses increases with age, and almost 15% of individuals aged 70 and older have dementia. As the number of older adults increases, sensory and cognitive impairments will affect a growing proportion of the population. To limit its scope, this conference focused on sensory impairments affecting vision and hearing. Comorbid vision, hearing, and cognitive impairments in older adults are more common than would be expected by chance alone, suggesting that some common mechanisms might affect these neurological systems. This workshop explored the mechanisms and consequences of comorbid vision, hearing, and cognitive impairment in older adults; effects of sensory loss on the aging brain; and bench‐to‐bedside innovations and research opportunities. Presenters and participants identified many research gaps and questions; the top priorities fell into 3 themes: mechanisms, measurement, and interventions. The workshop delineated specific research questions that provide opportunities to improve outcomes in this growing population.Funding was provided by National Institutes of Health (NIH) Grant U13 AG054139-01. Dr. Whitson's efforts and contributions were supported by R01AG043438, R24AG045050, UH2AG056925, and 5P30AG028716. Dr. Lin's effort and contributions were also supported by R01AG055426, R01HL096812, and R33DC015062. (U13 AG054139-01 - National Institutes of Health (NIH); R01AG043438; R24AG045050; UH2AG056925; 5P30AG028716; R01AG055426; R01HL096812; R33DC015062)Accepted manuscrip

Precise Measures of Orbital Period, Before and After Nova Eruption for QZ Aurigae

For the ordinary classical nova QZ Aurigae (which erupted in 1964), we report 1317 magnitudes from 1912--2016, including four eclipses detected on archival photographic plates from long before the eruption. We have accurate and robust measures of the orbital period both pre-eruption and post-eruption, and we find that the orbital period decreased, with a fractional change of -290.71+-0.28 parts-per-million across the eruption, with the orbit necessarily getting smaller. Further, we find that the light curve outside of eclipses and eruption is flat at near B=17.14 from 1912--1981, whereupon the average light curve starts fading down to B=17.49 with large variability. QZ Aur is a robust counter-example against the Hibernation model for the evolution of cataclysmic variables, where the model requires that all novae have their period increase across eruptions. Large period decreases across eruptions can easily arise from mass imbalances in the ejecta, as are commonly seen in asymmetric nova shells.Comment: MNRAS in press, 24 pages, 5 tables, 6 figure

Spatial Distribution, Temporal Stability, and Yield Loss Estimates for Annual Grasses and Common Ragweed (Ambrosia artimisiifolia) in a Corn/Soybean Production Field Over Nine Years

Weeds generally occur in patches in production fields. Are these patches spatially and temporally stable? Do management recommendations change on the basis of these data? The population density and location of annual grass weeds and common ragweed were examined in a 65-ha corn/soybean production field from 1995 to 2004. Yearly treatment recommendations were developed from field means, medians, and kriging grid cell densities, using the hyperbolic yield loss (YL) equation and published incremental YL values (I ), maximum YL values (A), and YL limits of 5, 10, or 15%. Mean plant densities ranged from 12 to 131 annual grasses m22 and , 1 to 37 common ragweed m22. Median weed densities ranged from 0 to 40 annual grasses m22 and were 0 for common ragweed. The grass I values used to estimate corn YL were 0.1 and 2% and treatment was recommended in only 1 yr when the high I value and either the mean or median density was used. The grass I values used for soybean were 0.7 and 10% and estimated YL was over 10% all years, regardless of I value. The common ragweed I values were 4.5 and 6% for corn and 5.1 and 15.6% for soybean. On the basis of mean densities, fieldwide treatment would have been recommended in 6 of 9 yr but in no years when the median density was used. Recommendations on the basis of grid cell weed density and kriging ranged from . 80% of the field treated for grass weeds in 3 of 4 yr in soybean to , 20% of the field treated for common ragweed in 2002 and 2004 (corn). Grass patches were more stable in time, space, and density than common ragweed patches. Population densities and spatial distribution generally were variable enough so that site-specific information within this field would improve weed management decisions

Spatial Distribution of Macrophages During Callus Formation and Maturation Reveals Close Crosstalk Between Macrophages and Newly Forming Vessels

Macrophages are essential players in the process of fracture healing, acting by remodeling of the extracellular matrix and enabling vascularization. Whilst activated macrophages of M1-like phenotype are present in the initial pro-inflammatory phase of hours to days of fracture healing, an anti-inflammatory M2-like macrophage phenotype is supposed to be crucial for the induction of downstream cascades of healing, especially the initiation of vascularization. In a mouse-osteotomy model, we provide a comprehensive characterization of vessel (CD31+, Emcn+) and macrophage phenotypes (F4/80, CD206, CD80, Mac-2) during the process of fracture healing. To this end, we phenotype the phases of vascular regeneration-the expansion phase (d1-d7 after injury) and the remodeling phase of the endothelial network, until tissue integrity is restored (d14-d21 after injury). Vessels which appear during the bone formation process resemble type H endothelium (CD31hiEmcnhi), and are closely connected to osteoprogenitors (Runx2+, Osx+) and F4/80+ macrophages. M1-like macrophages are present in the initial phase of vascularization until day 3 post osteotomy, but they are rare during later regeneration phases. M2-like macrophages localize mainly extramedullary, and CD206+ macrophages are found to express Mac-2+ during the expansion phase. VEGFA expression is initiated by CD80+ cells, including F4/80+ macrophages, until day 3, while subsequently osteoblasts and chondrocytes are main contributors to VEGFA production at the fracture site. Using Longitudinal Intravital Microendoscopy of the Bone (LIMB) we observe changes in the motility and organization of CX3CR1+ cells, which infiltrate the injury site after an osteotomy. A transient accumulation, resulting in spatial polarization of both, endothelial cells and macrophages, in regions distal to the fracture site, is evident. Immunofluorescence histology followed by histocytometric analysis reveals that F4/80+CX3CR1+ myeloid cells precede vascularization

Classification of intended phoneme production from chronic intracortical microelectrode recordings in speech-motor cortex

This is the published version, also available here: http://dx.doi.org/10.3389/fnins.2011.00065.We conducted a neurophysiological study of attempted speech production in a paralyzed human volunteer using chronic microelectrode recordings. The volunteer suffers from locked-in syndrome leaving him in a state of near-total paralysis, though he maintains good cognition and sensation. In this study, we investigated the feasibility of supervised classification techniques for prediction of intended phoneme production in the absence of any overt movements including speech. Such classification or decoding ability has the potential to greatly improve the quality-of-life of many people who are otherwise unable to speak by providing a direct communicative link to the general community. We examined the performance of three classifiers on a multi-class discrimination problem in which the items were 38 American English phonemes including monophthong and diphthong vowels and consonants. The three classifiers differed in performance, but averaged between 16 and 21% overall accuracy (chance-level is 1/38 or 2.6%). Further, the distribution of phonemes classified statistically above chance was non-uniform though 20 of 38 phonemes were classified with statistical significance for all three classifiers. These preliminary results suggest supervised classification techniques are capable of performing large scale multi-class discrimination for attempted speech production and may provide the basis for future communication prostheses