Distributed Prognostics based on Structural Model Decomposition

Within systems health management, prognostics focuses on predicting the remaining useful life of a system. In the model-based prognostics paradigm, physics-based models are constructed that describe the operation of a system and how it fails. Such approaches consist of an estimation phase, in which the health state of the system is first identified, and a prediction phase, in which the health state is projected forward in time to determine the end of life. Centralized solutions to these problems are often computationally expensive, do not scale well as the size of the system grows, and introduce a single point of failure. In this paper, we propose a novel distributed model-based prognostics scheme that formally describes how to decompose both the estimation and prediction problems into independent local subproblems whose solutions may be easily composed into a global solution. The decomposition of the prognostics problem is achieved through structural decomposition of the underlying models. The decomposition algorithm creates from the global system model a set of local submodels suitable for prognostics. Independent local estimation and prediction problems are formed based on these local submodels, resulting in a scalable distributed prognostics approach that allows the local subproblems to be solved in parallel, thus offering increases in computational efficiency. Using a centrifugal pump as a case study, we perform a number of simulation-based experiments to demonstrate the distributed approach, compare the performance with a centralized approach, and establish its scalability. Index Terms-model-based prognostics, distributed prognostics, structural model decomposition ABBREVIATION

Linking basin-scale and pore-scale gas hydrate distribution patterns in diffusion-dominated marine hydrate systems

The goal of this study is to computationally determine the potential distribution patterns of diffusion-driven methane hydrate accumulations in coarse-grained marine sediments. Diffusion of dissolved methane in marine gas hydrate systems has been proposed as a potential transport mechanism through which large concentrations of hydrate can preferentially accumulate in coarse-grained sediments over geologic time. Using one-dimensional compositional reservoir simulations, we examine hydrate distribution patterns at the scale of individual sand layers (1-20 m thick) that are deposited between microbially active fine-grained material buried through the gas hydrate stability zone (GHSZ). We then extrapolate to two-dimensional and basin-scale three-dimensional simulations, where we model dipping sands and multilayered systems. We find that properties of a sand layer including pore size distribution, layer thickness, dip, and proximity to other layers in multilayered systems all exert control on diffusive methane fluxes toward and within a sand, which in turn impact the distribution of hydrate throughout a sand unit. In all of these simulations, we incorporate data on physical properties and sand layer geometries from the Terrebonne Basin gas hydrate system in the Gulf of Mexico. We demonstrate that diffusion can generate high hydrate saturations (upward of 90%) at the edges of thin sands at shallow depths within the GHSZ, but that it is ineffective at producing high hydrate saturations throughout thick (greater than 10 m) sands buried deep within the GHSZ. Furthermore, we find that hydrate in fine-grained material can preserve high hydrate saturations in nearby thin sands with burial

Spatially explicit species distribution models: A missed opportunity in conservation planning?

Aim: Systematic conservation planning is vital for allocating protected areas given the spatial distribution of conservation features, such as species. Due to incomplete species inventories, species distribution models (SDMs) are often used for predicting species habitat suitability and species probability of occurrence. Currently, SDMs mostly ignore spatial dependencies in species and predictor data. Here, we provide a comparative evaluation of how accounting for spatial dependencies, that is, autocorrelation, affects the delineation of optimized protected areas. Location: Southeast Australia, Southeast U.S. Continental Shelf, Danube River Basin. Methods: We employ Bayesian spatially explicit and non-spatial SDMs for terrestrial, marine and freshwater species, using realm-specific planning unit shapes (grid, hexagon and subcatchment, respectively). We then apply the software gurobi to optimize conservation plans based on species targets derived from spatial and non-spatial SDMs (10% 50% each to analyse sensitivity), and compare the delineation of the plans. Results: Across realms and irrespective of the planning unit shape, spatially explicit SDMs (a) produce on average more accurate predictions in terms of AUC, TSS, sensitivity and specificity, along with a higher species detection probability. All spatial optimizations meet the species conservation targets. Spatial conservation plans that use predictions from spatially explicit SDMs (b) are spatially substantially different compared to those that use non-spatial SDM predictions, but (c) encompass a similar amount of planning units. The overlap in the selection of planning units is smallest for conservation plans based on the lowest targets and vice versa. Main conclusions: Species distribution models are core tools in conservation planning. Not surprisingly, accounting for the spatial characteristics in SDMs has drastic impacts on the delineation of optimized conservation plans. We therefore encourage practitioners to consider spatial dependencies in conservation features to improve the spatial representation of future protected areas. © 2019 The Authors. Diversity and Distributions Published by John Wiley and Sons LtdThis study was funded by the European Union’s Horizon 2020 research and innovation programme under grant agreement No. 642317. SDL has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska‐Curie grant agreement No. 748625, and SCJ from the German Federal Ministry of Education and Research (BMBF) for the “GLANCE” project (Global Change Effects in River Ecosystems; 01 LN1320A). We wish to thank Gwen Iacona and two anonymous referees for their constructive comments on an earlier version of the manuscript

H-alpha Kinematics of the SINGS Nearby Galaxies Survey. II

This is the second part of an H-alpha kinematics follow-up survey of the Spitzer Infrared Nearby Galaxies Survey (SINGS) sample. The aim of this program is to shed new light on the role of baryons and their kinematics and on the dark/luminous matter relation in the star forming regions of galaxies, in relation with studies at other wavelengths. The data for 37 galaxies are presented. The observations were made using Fabry-Perot interferometry with the photon-counting camera FaNTOmM on 4 different telescopes, namely the Canada-France-Hawaii 3.6m, the ESO La Silla 3.6m, the William Herschel 4.2m, and the Observatoire du mont Megantic 1.6m telescopes. The velocity fields are computed using custom IDL routines designed for an optimal use of the data. The kinematical parameters and rotation curves are derived using the GIPSY software. It is shown that non-circular motions associated with galactic bars affect the kinematical parameters fitting and the velocity gradient of the rotation curves. This leads to incorrect determinations of the baryonic and dark matter distributions in the mass models derived from those rotation curves.Comment: 18 pages, 5 figures, 4 tables. Accepted for publication in MNRAS. All high-res. figures are available at http://www.astro.umontreal.ca/fantomm/singsII

Temporal Trends and Factors Associated with Bisphosphonate Discontinuation and Restart

Adverse events related to long-term use of bisphosphonates have raised interest in temporary drug discontinuation. Trends in bisphosphonate discontinuation and restart, as well factors associated with these decisions, are not fully understood at a population level. We investigated temporal trends of bisphosphonate discontinuation from 2010 to 2015 and identified factors associated with discontinuation and restart of osteoporosis therapy. Our cohort consisted of long-term bisphosphonate users identified from 2010 to 2015 Medicare data. We defined discontinuation as 6512\u2009months without bisphosphonate prescription claims. We used conditional logistic regression to compare factors associated with alendronate discontinuation or osteoporosis therapy restart in the 120-day period preceding discontinuation or restart referent to the 120-day preceding control periods. Among 73,800 long-term bisphosphonate users, 59,251 (80.3%) used alendronate, 6806 (9.2%) risedronate, and 7743 (10.5%) zoledronic acid, exclusively. Overall, 26,281 (35.6%) discontinued bisphosphonates for at least 12\u2009months. Discontinuation of bisphosphonates increased from 1.7% in 2010, reaching a peak of 14% in 2012 with levels plateauing through 2015. The factors most strongly associated with discontinuation of alendronate were: benzodiazepine prescription (adjusted odds ratio [aOR] = 2.5; 95% confidence interval [CI] 2.1, 3.0), having a dual-energy X-ray absorptiometry (DXA) scan (aOR = 1.8; 95% CI 1.7, 2.0), and skilled nursing facility care utilization (aOR = 1.8; 95% CI 1.6, 2.1). The factors most strongly associated with restart of osteoporosis therapy were: having a DXA scan (aOR = 9.9; 95% CI 7.7, 12.6), sustaining a fragility fracture (aOR = 2.8; 95% CI 1.8, 4.5), and an osteoporosis or osteopenia diagnosis (aOR = 2.5; 95% CI 2.0, 3.1). Our national evaluation of bisphosphonate discontinuation showed that an increasing proportion of patients on long-term bisphosphonate therapy discontinue medications. The factors associated with discontinuation of alendronate were primarily related to worsening of overall health status, whereas traditional factors associated with worsening bone health were associated with restarting osteoporosis medication. \ua9 2019 American Society for Bone and Mineral Research

Atomic and Molecular Gas Components in Spiral Galaxies of the Virgo Cluster

Based on two models, we investigate the molecular-to-atomic gas ratio in Virgo cluster galaxies in comparison with field galaxies. We show that the enhanced metallicity for cluster members and the ram pressure stripping of atomic gas from the disk periphery cannot fully explain the observed gas component ratios. The additional environmental factors affecting the interstellar medium and leading to an increase in the molecular gas fraction should be taken into account for cluster galaxies.Comment: 11 pages, 4 figure

Beyond Volume: The Impact of Complex Healthcare Data on the Machine Learning Pipeline

From medical charts to national census, healthcare has traditionally operated under a paper-based paradigm. However, the past decade has marked a long and arduous transformation bringing healthcare into the digital age. Ranging from electronic health records, to digitized imaging and laboratory reports, to public health datasets, today, healthcare now generates an incredible amount of digital information. Such a wealth of data presents an exciting opportunity for integrated machine learning solutions to address problems across multiple facets of healthcare practice and administration. Unfortunately, the ability to derive accurate and informative insights requires more than the ability to execute machine learning models. Rather, a deeper understanding of the data on which the models are run is imperative for their success. While a significant effort has been undertaken to develop models able to process the volume of data obtained during the analysis of millions of digitalized patient records, it is important to remember that volume represents only one aspect of the data. In fact, drawing on data from an increasingly diverse set of sources, healthcare data presents an incredibly complex set of attributes that must be accounted for throughout the machine learning pipeline. This chapter focuses on highlighting such challenges, and is broken down into three distinct components, each representing a phase of the pipeline. We begin with attributes of the data accounted for during preprocessing, then move to considerations during model building, and end with challenges to the interpretation of model output. For each component, we present a discussion around data as it relates to the healthcare domain and offer insight into the challenges each may impose on the efficiency of machine learning techniques.Comment: Healthcare Informatics, Machine Learning, Knowledge Discovery: 20 Pages, 1 Figur

Molecular gas in NUclei of GAlaxies (NUGA). XI. A complete gravity torque map of NGC4579: new clues on bar evolution

We create a complete gravity torque map of the disk of the LINER/Seyfert 1.9 galaxy NGC4579. We quantify the efficiency of angular momentum transport and search for signatures of secular evolution in the fueling process from r~15kpc down to the inner r~50pc around the Active Galactic Nucleus (AGN). We use both the 1-0 and 2-1 line maps of CO obtained with the Plateau de Bure Interferometer (PdBI) as part of the NUclei of Galaxies-(NUGA)-project. We derive the stellar potential from a NIR (K band) wide field image of the galaxy. The K-band image, which reveals a stellar bar, together with a high resolution HI map of NGC4579 obtained with the Very Large Array (VLA), allow us to extend the gravity torque analysis to the outer disk. The bulk of the gas response traced by the CO PdBI maps follows the expected gas flow pattern induced by the bar potential in the presence of two Inner Lindblad Resonances (ILR). We also detect an oval distortion in the inner r~200pc of the K-band image. The oval is not aligned with the large-scale bar, a signature of dynamical decoupling. The morphology of the outer disk suggests that the neutral gas is currently piling up in a pseudo-ring formed by two winding spiral arms that are morphologically decoupled from the bar structure. In the outer disk, the decoupling of the spiral allows the gas to efficiently produce net gas inflow on intermediate scales. The corotation barrier seems to be overcome due to secular evolution processes. The gas in the inner disk is efficiently funneled by gravity torques down to r~300pc. Closer to the AGN, the two m=2 modes (bar and oval) act in concert to produce net gas inflow down to r~50pc, providing a clear smoking gun evidence of fueling with associated short dynamical time-scales.Comment: Submitted for publication in A&A. 21 pages, 21 figure

Gravitational stability and dynamical overheating of stellar disks of galaxies

We use the marginal stability condition for galactic disks and the stellar velocity dispersion data published by different authors to place upper limits on the disk local surface density at two radial scalelengths $R=2h$. Extrapolating these estimates, we constrain the total mass of the disks and compare these estimates to those based on the photometry and color of stellar populations. The comparison reveals that the stellar disks of most of spiral galaxies in our sample cannot be substantially overheated and are therefore unlikely to have experienced a significant merging event in their history. The same conclusion applies to some, but not all of the S0 galaxies we consider. However, a substantial part of the early type galaxies do show the stellar velocity dispersion well in excess of the gravitational stability threshold suggesting a major merger event in the past. We find dynamically overheated disks among both seemingly isolated galaxies and those forming pairs. The ratio of the marginal stability disk mass estimate to the total galaxy mass within four radial scalelengths remains within a range of 0.4---0.8. We see no evidence for a noticeable running of this ratio with either the morphological type or color index.Comment: 25 pages, 5 figures, accepted to Astronomy Letter