The Keck/OSIRIS Nearby AGN Survey (KONA) I. The Nuclear K-band Properties of Nearby AGN

We introduce the Keck Osiris Nearby AGN survey (KONA), a new adaptive optics-assisted integral-field spectroscopic survey of Seyfert galaxies. KONA permits at ~0.1" resolution a detailed study of the nuclear kinematic structure of gas and stars in a representative sample of 40 local bona fide active galactic nucleus (AGN). KONA seeks to characterize the physical processes responsible for the coevolution of supermassive black holes and galaxies, principally inflows and outflows. With these IFU data of the nuclear regions of 40 Seyfert galaxies, the KONA survey will be able to study, for the first time, a number of key topics with meaningful statistics. In this paper we study the nuclear K-band properties of nearby AGN. We find that the luminosities of the unresolved Seyfert 1 sources at 2.1 microns are correlated with the hard X-ray luminosities, implying that the majority of the emission is non-stellar. The best-fit correlation is logLK = 0.9logL2-10 keV + 4 over 3 orders of magnitude in both K-band and X-ray luminosities. We find no strong correlation between 2.1 microns luminosity and hard X-ray luminosity for the Seyfert 2 galaxies. The spatial extent and spectral slope of the Seyfert 2 galaxies indicate the presence of nuclear star formation and attenuating material (gas and dust), which in some cases is compact and in some galaxies extended. We detect coronal-line emission in 36 galaxies and for the first time in five galaxies. Finally, we find 4/20 galaxies that are optically classified as Seyfert 2 show broad emission lines in the near-IR, and one galaxy (NGC 7465) shows evidence of a double nucleus.Comment: Accepted for publication in ApJ, 19 pages with 18 figure

Multivariate statistical appraisal of regional susceptibility to induced seismicity: application to the Permian Basin, SW United States

Induced earthquake sequences are typically interpreted through causal triggering mechanisms. However, studies of causality rarely consider large regions and why some regions experiencing similar anthropogenic activities remain largely aseismic. Therefore, it can be difficult to forecast seismic hazard at a regional scale. In contrast, multivariate statistical methods allow us to find the combinations of factors that correlate best with seismicity, which can help form the basis of hypotheses that can be subsequently tested with physical models. Whilst strong correlations do not necessarily equate to causality, such a statistical approach is particularly important for large regions with newly emergent seismicity comprising multiple distinct clusters and multi-faceted industrial operations. Recent induced seismicity in the Permian Basin provides an excellent test-bed for multivariate statistical analyses because the main causal industrial and geological factors driving earthquakes in the region remain highly debated. Here, we use logistic regression to retrospectively predict the spatial variation of seismicity across the western Permian Basin. We reproduce the broad distribution of seismicity using a combination of both industrial and geological factors. Our model shows that the proximity to neotectonic faults west of the Delaware Basin is the most important factor that contributes to induced seismicity. The second-most important factor is salt-water disposal at shallow depths, with hydraulic fracturing playing a less dominant role. The higher tectonic stressing, together with a poor correlation between seismicity and large-volume deep salt-water disposal wells indicates a very different mechanism of induced seismicity compared to that in Oklahoma

AFLOW-QHA3P: Robust and automated method to compute thermodynamic properties of solids

Accelerating the calculations of finite-temperature thermodynamic properties is a major challenge for rational materials design. Reliable methods can be quite expensive, limiting their applicability in autonomous high-throughput workflows. Here, the three-phonon quasiharmonic approximation (QHA) method is introduced, requiring only three phonon calculations to obtain a thorough characterization of the material. Leveraging a Taylor expansion of the phonon frequencies around the equilibrium volume, the method efficiently resolves the volumetric thermal expansion coefficient, specific heat at constant pressure, the enthalpy, and bulk modulus. Results from the standard QHA and experiments corroborate the procedure, and additional comparisons are made with the recently developed self-consistent QHA. The three approaches—three-phonon, standard, and self-consistent QHAs—are all included within the open-source ab initio framework aflow, allowing the automated determination of properties with various implementations within the same framework

An interdisciplinary approach to volcanic risk reduction under conditions of uncertainty: a case study of Tristan da Cunha

The uncertainty brought about by intermittent volcanic activity is fairly common at volcanoes worldwide. While better knowledge of any one volcano's behavioural characteristics has the potential to reduce this uncertainty, the subsequent reduction of risk from volcanic threats is only realised if that knowledge is pertinent to stakeholders and effectively communicated to inform good decision making. Success requires integration of methods, skills and expertise across disciplinary boundaries. This research project develops and trials a novel interdisciplinary approach to volcanic risk reduction on the remote volcanic island of Tristan da Cunha (South Atlantic). For the first time, volcanological techniques, probabilistic decision support and social scientific methods were integrated in a single study. New data were produced that (1) established no spatio-temporal pattern to recent volcanic activity; (2) quantified the high degree of scientific uncertainty around future eruptive scenarios; (3) analysed the physical vulnerability of the community as a consequence of their geographical isolation and exposure to volcanic hazards; (4) evaluated social and cultural influences on vulnerability and resilience; and (5) evaluated the effectiveness of a scenario planning approach, both as a method for integrating the different strands of the research and as a way of enabling on-island decision makers to take ownership of risk identification and management, and capacity building within their community. The paper provides empirical evidence of the value of an innovative interdisciplinary framework for reducing volcanic risk. It also provides evidence for the strength that comes from integrating social and physical sciences with the development of effective, tailored engagement and communication strategies in volcanic risk reduction

Optimizing sustainable multimodal distribution networks in the context of carbonpricing, with a case study in the Thai sugar industry

Transportation is a major cause of energy consumption and emissions which can bereduced by optimizing routings and using alternative modes of transport. This paperrelates to the strategic design of multimodal transportation networks. It presents ageneral model of green vehicle routing problems that supports strategic decisionmakingby identifying optimal solutions and provides data on costs and emissions.Three general linear programming models were developed that optimize multimodaldistribution networks that could be applied in many industries. Model I evaluatescarbon emissions; model II assesses carbon emissions and capacity constraints; andmodel III establishes total costs including transportation, handling, storage, fuel andcarbon costs.Thailand is the third largest world sugar exporter in the world and is piloting carbonpricing, which will affect energy intensive industries, including the sugar industry. Themodels are applied using data obtained from a collaborating company. The researchcontributed to practice by informing managerial decisions relating to the export of sugarfrom the factory. This included evaluating the possible use of a dry port with railconnections, which could reduce transportation and carbon costs by 54.3% andfacilitate the building of another factory to increase exports

On the degrees of freedom of a semi-Riemannian metric

A semi-Riemannian metric in a n-manifold has n(n-1)/2 degrees of freedom, i.e. as many as the number of components of a differential 2-form. We prove that any semi-Riemannian metric can be obtained as a deformation of a constant curvature metric, this deformation being parametrized by a 2-for

Amazonian Hydrothermal Alteration Comparing Nakhlite Secondary Mineralogy to Water Rock Reaction Experiments

We report on results from experiments with Mars analog materials under diagenetic conditions. The mineralogical results of our experiments suggest that an important type of fluid alteration in the Amazonian may be short duration (e.g. less than 1 year) events from near neutral, dilute brines, that were able to exchange CO2 either directly, or via ice reservoirs, with the atmosphere

Validating and improving CT ventilation imaging by correlating with ventilation 4D-PET/CT using 68Ga-labeled nanoparticles.

PURPOSE: CT ventilation imaging is a novel functional lung imaging modality based on deformable image registration. The authors present the first validation study of CT ventilation using positron emission tomography with (68)Ga-labeled nanoparticles (PET-Galligas). The authors quantify this agreement for different CT ventilation metrics and PET reconstruction parameters. METHODS: PET-Galligas ventilation scans were acquired for 12 lung cancer patients using a four-dimensional (4D) PET/CT scanner. CT ventilation images were then produced by applying B-spline deformable image registration between the respiratory correlated phases of the 4D-CT. The authors test four ventilation metrics, two existing and two modified. The two existing metrics model mechanical ventilation (alveolar air-flow) based on Hounsfield unit (HU) change (VHU) or Jacobian determinant of deformation (VJac). The two modified metrics incorporate a voxel-wise tissue-density scaling (ρVHU and ρVJac) and were hypothesized to better model the physiological ventilation. In order to assess the impact of PET image quality, comparisons were performed using both standard and respiratory-gated PET images with the former exhibiting better signal. Different median filtering kernels (σm = 0 or 3 mm) were also applied to all images. As in previous studies, similarity metrics included the Spearman correlation coefficient r within the segmented lung volumes, and Dice coefficient d20 for the (0 - 20)th functional percentile volumes. RESULTS: The best agreement between CT and PET ventilation was obtained comparing standard PET images to the density-scaled HU metric (ρVHU) with σm = 3 mm. This leads to correlation values in the ranges 0.22 ≤ r ≤ 0.76 and 0.38 ≤ d20 ≤ 0.68, with r = 0.42 ± 0.16 and d20 = 0.52 ± 0.09 averaged over the 12 patients. Compared to Jacobian-based metrics, HU-based metrics lead to statistically significant improvements in r and d20 (p < 0.05), with density scaled metrics also showing higher r than for unscaled versions (p < 0.02). r and d20 were also sensitive to image quality, with statistically significant improvements using standard (as opposed to gated) PET images and with application of median filtering. CONCLUSIONS: The use of modified CT ventilation metrics, in conjunction with PET-Galligas and careful application of image filtering has resulted in improved correlation compared to earlier studies using nuclear medicine ventilation. However, CT ventilation and PET-Galligas do not always provide the same functional information. The authors have demonstrated that the agreement can improve for CT ventilation metrics incorporating a tissue density scaling, and also with increasing PET image quality. CT ventilation imaging has clear potential for imaging regional air volume change in the lung, and further development is warranted