Low-Frequency Oscillations in Global Simulations of Black Hole Accretion

We have identified the presence of large-scale, low-frequency dynamo cycles in a long-duration, global, magnetohydrodynamic (MHD) simulation of black hole accretion. Such cycles had been seen previously in local shearing box simulations, but we discuss their evolution over 1,500 inner disk orbits of a global pi/4 disk wedge spanning two orders of magnitude in radius and seven scale heights in elevation above/below the disk midplane. The observed cycles manifest themselves as oscillations in azimuthal magnetic field occupying a region that extends into a low-density corona several scale heights above the disk. The cycle frequencies are ten to twenty times lower than the local orbital frequency, making them potentially interesting sources of low-frequency variability when scaled to real astrophysical systems. Furthermore, power spectra derived from the full time series reveal that the cycles manifest themselves at discrete, narrow-band frequencies that often share power across broad radial ranges. We explore possible connections between these simulated cycles and observed low-frequency quasi-periodic oscillations (LFQPOs) in galactic black hole binary systems, finding that dynamo cycles have the appropriate frequencies and are located in a spatial region associated with X-ray emission in real systems. Derived observational proxies, however, fail to feature peaks with RMS amplitudes comparable to LFQPO observations, suggesting that further theoretical work and more sophisticated simulations will be required to form a complete theory of dynamo-driven LFQPOs. Nonetheless, this work clearly illustrates that global MHD dynamos exhibit quasi-periodic behavior on timescales much longer than those derived from test particle considerations.Comment: Version accepted to The Astrophysical Journal, 8 pages, 7 figure

Development and measurement properties of the AxEL (attitude toward education and advice for low-back-pain) questionnaire

Introduction: Clinician time and resources may be underutilised if the treatment they offer does not match patient expectations and attitudes. We developed a questionnaire (AxEL-Q) to guide clinicians toward elements of first-line care that are pertinent to their patients with low back pain. Methods: We used guidance from the COSMIN consortium to develop the questionnaire and evaluated it in a sample of people with low back pain of any duration. Participants were recruited from the community, were over 18 years and fluent in English. Statements that represented first-line care were identified. Semantic scales were used to measure attitude towards these statements. These items were combined to develop the questionnaire draft. Construct validity was evaluated with exploratory factor analysis and hypotheses testing, comparing to the Back Beliefs Questionnaire and modified Pain Self-Efficacy Questionnaire. Reliability was evaluated and floor and ceiling effects calculated. Results: We recruited 345 participants, and had complete data for analysis for 313 participants. The questionnaire draft was reduced to a 3-Factor questionnaire through exploratory factor analysis. Factor 1 comprised 9 items and evaluated Attitude toward staying active, Factor 2 comprised 4 items and evaluated Attitude toward low back pain being rarely caused by a serious health problem, Factor 3 comprised 4 items and evaluated Attitude toward not needing to know the cause of back pain to manage it effectively. There was a strong inverse association between each factor and the Back Beliefs Questionnaire and a moderate positive association with the modified Pain Self-Efficacy Questionnaire. Each independent factor demonstrated acceptable internal consistency; Cronbach α Factor 1 = 0.92, Factor 2 = 0.91, Factor 3 = 0.90 and adequate interclass correlation coefficients; Factor 1 = 0.71, Factor 2 = 0.73, Factor 3 = 0.79. Conclusion: This study demonstrates acceptable construct validity and reliability of the AxEL-Q, providing clinicians with an insight into the likelihood of patients following first-line care at the outset

A multi-analysis approach for estimating regional health impacts from the 2017 Northern California wildfires

Smoke impacts from large wildfires are mounting, and the projection is for more such events in the future as the one experienced October 2017 in Northern California, and subsequently in 2018 and 2020. Further, the evidence is growing about the health impacts from these events which are also difficult to simulate. Therefore, we simulated air quality conditions using a suite of remotely-sensed data, surface observational data, chemical transport modeling with WRF-CMAQ, one data fusion, and three machine learning methods to arrive at datasets useful to air quality and health impact analyses. To demonstrate these analyses, we estimated the health impacts from smoke impacts during wildfires in October 8–20, 2017, in Northern California, when over 7 million people were exposed to Unhealthy to Very Unhealthy air quality conditions. We investigated using the 5-min available GOES-16 fire detection data to simulate timing of fire activity to allocate emissions hourly for the WRF-CMAQ system. Interestingly, this approach did not necessarily improve overall results, however it was key to simulating the initial 12-hr explosive fire activity and smoke impacts. To improve these results, we applied one data fusion and three machine learning algorithms. We also had a unique opportunity to evaluate results with temporary monitors deployed specifically for wildfires, and performance was markedly different. For example, at the permanent monitoring locations, the WRF-CMAQ simulations had a Pearson correlation of 0.65, and the data fusion approach improved this (Pearson correlation = 0.95), while at the temporary monitor locations across all cases, the best Pearson correlation was 0.5. Overall, WRF-CMAQ simulations were biased high and the geostatistical methods were biased low. Finally, we applied the optimized PM2.5 exposure estimate in an exposure-response function. Estimated mortality attributable to PM2.5 exposure during the smoke episode was 83 (95% CI: 0, 196) with 47% attributable to wildland fire smoke. Implications: Large wildfires in the United States and in particular California are becoming increasingly common. Associated with these large wildfires are air quality and health impact to millions of people from the smoke. We simulated air quality conditions using a suite of remotely-sensed data, surface observational data, chemical transport modeling, one data fusion, and three machine learning methods to arrive at datasets useful to air quality and health impact analyses from the October 2017 Northern California wildfires. Temporary monitors deployed for the wildfires provided an important model evaluation dataset. Total estimated regional mortality attributable to PM2.5 exposure during the smoke episode was 83 (95% confidence interval: 0, 196) with 47% of these deaths attributable to the wildland fire smoke. This illustrates the profound effect that even a 12-day exposure to wildland fire smoke can have on human health

Local Simulations of Instabilities in Relativistic Jets I: Morphology and Energetics of the Current-Driven Instability

We present the results of a numerical investigation of current-driven instability in magnetized jets. Utilizing the well-tested, relativistic magnetohydrodynamic code Athena, we construct an ensemble of local, co-moving plasma columns in which initial radial force balance is achieved through various combinations of magnetic, pressure, and rotational forces. We then examine the resulting flow morphologies and energetics to determine the degree to which these systems become disrupted, the amount of kinetic energy amplification attained, and the non-linear saturation behaviors. Our most significant finding is that the details of initial force balance have a pronounced effect on the resulting flow morphology. Models in which the initial magnetic field is force-free deform, but do not become disrupted. Systems that achieve initial equilibrium by balancing pressure gradients and/or rotation against magnetic forces, however, tend to shred, mix, and develop turbulence. In all cases, the linear growth of current-driven instabilities is well-represented by analytic models. CDI-driven kinetic energy amplification is slower and saturates at a lower value in force-free models than in those that feature pressure gradients and/or rotation. In rotating columns, we find that magnetized regions undergoing rotational shear are driven toward equipartition between kinetic and magnetic energies. We show that these results are applicable for a large variety of physical parameters, but we caution that algorithmic decisions (such as choice of Riemann solver) can affect the evolution of these systems more than physically motivated parameters.Comment: 18 pages, 23 figures. Accepted to MNRAS and in press, with only minor revisions from original submitted versio

The gut of the finch: uniqueness of the gut microbiome of the Galápagos vampire finch

Background: Darwin’s finches are a clade of 19 species of passerine birds native to the Galápagos Islands, whose biogeography, specialized beak morphologies, and dietary choices—ranging from seeds to blood—make them a classic example of adaptive radiation. While these iconic birds have been intensely studied, the composition of their gut microbiome and the factors influencing it, including host species, diet, and biogeography, has not yet been explored. Results: We characterized the microbial community associated with 12 species of Darwin’s finches using high-throughput 16S rRNA sequencing of fecal samples from 114 individuals across nine islands, including the unusual blood-feeding vampire finch (Geospiza septentrionalis) from Darwin and Wolf Islands. The phylum-level core gut microbiome for Darwin’s finches included the Firmicutes, Gammaproteobacteria, and Actinobacteria, with members of the Bacteroidetes at conspicuously low abundance. The gut microbiome was surprisingly well conserved across the diversity of finch species, with one exception—the vampire finch—which harbored bacteria that were either absent or extremely rare in other finches, including Fusobacterium, Cetobacterium, Ureaplasma, Mucispirillum, Campylobacter, and various members of the Clostridia—bacteria known from the guts of carnivorous birds and reptiles. Complementary stable isotope analysis of feathers revealed exceptionally high δ15N isotope values in the vampire finch, resembling top marine predators. The Galápagos archipelago is also known for extreme wet and dry seasons, and we observed a significant seasonal shift in the gut microbial community of five additional finch species sampled during both seasons. Conclusions: This study demonstrates the overall conservatism of the finch gut microbiome over short (< 1 Ma) divergence timescales, except in the most extreme case of dietary specialization, and elevates the evolutionary importance of seasonal shifts in driving not only species adaptation, but also gut microbiome composition

An X-Ray-Selected Sample of Candidate Black Holes in Dwarf Galaxies

We present a sample of hard X-ray-selected candidate black holes (BHs) in 19 dwarf galaxies. BH candidates are identified by cross-matching a parent sample of ~44,000 local dwarf galaxies (M* = 3 × 10 9 M☉, z < 0.055) with the Chandra Source Catalog and subsequently analyzing the original X-ray data products for matched sources. Of the 19 dwarf galaxies in our sample, eight have X-ray detections reported here for the first time. We find a total of 43 point-like hard X-ray sources with individual luminosities L2-10 keV ~ 10 37 - 10 40 erg s-1. Hard X-ray luminosities in this range can be attained by stellar-mass X-ray binaries (XRBs) and by massive BHs accreting at low Eddington ratio. We place an upper limit of 53% (10/19) on the fraction of galaxies in our sample hosting a detectable hard X-ray source consistent with the optical nucleus, although the galaxy center is poorly defined in many of our objects. We also find that 42% (8/19) of the galaxies in our sample exhibit statistically significant enhanced hard X-ray emission relative to the expected galaxy-wide contribution from low-mass and high-mass XRBs, based on the [data] star formation rate relation defined by more massive and luminous systems. For the majority of these X-ray-enhanced dwarf galaxies, the excess emission is consistent with (but not necessarily due to) a nuclear X-ray source. Follow-up observations are necessary to distinguish between stellar-mass XRBs and active galactic nuclei powered by more massive BHs. In any case, our results support the notion that X-ray-emitting BHs in low-mass dwarf galaxies may have had an appreciable impact on reionization in the early universe

Scalable production of large quantities of defect-free few-layer graphene by shear exfoliation in liquids

To progress from the laboratory to commercial applications, it will be necessary to develop industrially scalable methods to produce large quantities of defect-free graphene. Here we show that high-shear mixing of graphite in suitable stabilizing liquids results in large-scale exfoliation to give dispersions of graphene nanosheets. X-ray photoelectron spectroscopy and Raman spectroscopy show the exfoliated flakes to be unoxidized and free of basal-plane defects. We have developed a simple model that shows exfoliation to occur once the local shear rate exceeds 10(4) s(-1). By fully characterizing the scaling behaviour of the graphene production rate, we show that exfoliation can be achieved in liquid volumes from hundreds of millilitres up to hundreds of litres and beyond. The graphene produced by this method performs well in applications from composites to conductive coatings. This method can be applied to exfoliate BN, MoS2 and a range of other layered crystals