Groundwater Sensitivity to Climate Variations Across Australia

Groundwater response to climate variations is often pivotal to managing groundwater sustainably. However, this relationship is rarely explicitly examined because of the complexity of surface to subsurface processes and the diverse impacts of multiple drivers, such as groundwater pumping and land use changes. In this paper, we address this challenge by proposing methods to quantify the sensitivity of groundwater level and recharge to temporal climate variability across Australia. Using the HydroSight groundwater hydrograph toolbox we first identify 1,143 out of a total of 4,350 bores as climate-driven, where historically, head was primarily driven by climate variations. Streamflow elasticity measures are then adapted to groundwater to quantify the long-term head and recharge sensitivity. We find that the national median sensitivity of head and recharge to precipitation change are 42 and 0.43 mm mm$^{−1}$, respectively (interquartiles: 20–77 and 0.30–0.55 mm mm$^{−1}$); both of which are ∼8 times that of potential evapotranspiration. Nationally, the results are spatially correlated, suggestive of large-scale effects. The responses of head and recharge appear to be primarily related to climate type and hydrogeology. The more arid the climate, the higher the head sensitivity but the lower the recharge sensitivity. Porous media generally show higher head sensitivity than fractured media due to smaller aquifer specific yield, and again contrarily for that of recharge. These findings contribute to understanding the long-term impact of climate change on groundwater and thus provide valuable insights for sustainable groundwater management

External Validation of a Measurement Tool to Assess Systematic Reviews (AMSTAR)

BACKGROUND: Thousands of systematic reviews have been conducted in all areas of health care. However, the methodological quality of these reviews is variable and should routinely be appraised. AMSTAR is a measurement tool to assess systematic reviews. METHODOLOGY: AMSTAR was used to appraise 42 reviews focusing on therapies to treat gastro-esophageal reflux disease, peptic ulcer disease, and other acid-related diseases. Two assessors applied the AMSTAR to each review. Two other assessors, plus a clinician and/or methodologist applied a global assessment to each review independently. CONCLUSIONS: The sample of 42 reviews covered a wide range of methodological quality. The overall scores on AMSTAR ranged from 0 to 10 (out of a maximum of 11) with a mean of 4.6 (95% CI: 3.7 to 5.6) and median 4.0 (range 2.0 to 6.0). The inter-observer agreement of the individual items ranged from moderate to almost perfect agreement. Nine items scored a kappa of >0.75 (95% CI: 0.55 to 0.96). The reliability of the total AMSTAR score was excellent: kappa 0.84 (95% CI: 0.67 to 1.00) and Pearson's R 0.96 (95% CI: 0.92 to 0.98). The overall scores for the global assessment ranged from 2 to 7 (out of a maximum score of 7) with a mean of 4.43 (95% CI: 3.6 to 5.3) and median 4.0 (range 2.25 to 5.75). The agreement was lower with a kappa of 0.63 (95% CI: 0.40 to 0.88). Construct validity was shown by AMSTAR convergence with the results of the global assessment: Pearson's R 0.72 (95% CI: 0.53 to 0.84). For the AMSTAR total score, the limits of agreement were -0.19+/-1.38. This translates to a minimum detectable difference between reviews of 0.64 'AMSTAR points'. Further validation of AMSTAR is needed to assess its validity, reliability and perceived utility by appraisers and end users of reviews across a broader range of systematic reviews

Parallelizing Training of Deep Generative Models on Massive Scientific Datasets

Training deep neural networks on large scientific data is a challenging task that requires enormous compute power, especially if no pre-trained models exist to initialize the process. We present a novel tournament method to train traditional as well as generative adversarial networks built on LBANN, a scalable deep learning framework optimized for HPC systems. LBANN combines multiple levels of parallelism and exploits some of the worlds largest supercomputers. We demonstrate our framework by creating a complex predictive model based on multi-variate data from high-energy-density physics containing hundreds of millions of images and hundreds of millions of scalar values derived from tens of millions of simulations of inertial confinement fusion. Our approach combines an HPC workflow and extends LBANN with optimized data ingestion and the new tournament-style training algorithm to produce a scalable neural network architecture using a CORAL-class supercomputer. Experimental results show that 64 trainers (1024 GPUs) achieve a speedup of 70.2 over a single trainer (16 GPUs) baseline, and an effective 109% parallel efficiency

Global defects in collagen secretion in a Mia3/TANGO1 knockout mouse

Mia3’s contribution to protein secretion is broader than previously realized—its absence impairs collagen deposition and normal development of cartilage and bone

Exile Vol. XXXV No. 1

ARTWORK Untitled by Eric Whitney (cover) Untitled by Rory Herbster 7 Little Boy by Eric Whitney 45 FICTION Through the Window Pane by Jennifer Read 4 to whom i may concern by Chris Campi 19 For Lack of Sleep by Amy Judge 26 Jonathan by Jim Cox 39 Skin Deep by Eric Whitney 51 NON-FICTION A Theopoetic by Robert Marshall 11 POETRY Clay Pot by Christopher Collette 1 Ars Poetica by Mans Agantyr 2 Bible Thumber by Chris Rynd 6 Play by Amy Judge 9 Satellites by Andrew C. Carinston 10 Music - Love? by Shammon J. Salser 15 Allusion by Rosemary Walsh 17 Self Portrait by Margaret Dawson 18 On Our Way by Lynn Pendleton 21 They called her Mitzi... by Jen Miller 22 Storms of Illusion by Kevin Merriman 23 Beauty by Andrew C. Carington 24 Thoughts of a Husband by Kent Lambert 25 The Music of the Sum by Zach Smith 31 Don\u27t Think by Mary Forsythe 32 Aspiration by Tim Emrick 33 Where We Go Together by Man Angantyr 35 Sunset by Chris Byrd 36 The Child of my Fatalism by Jennifer Peterson 37 Untitled by Kent Lambert 38 Terribly close to being... by Michael Payne 44 Anne Frank\u27s House by Mary Forsythe 47 Invitation by Kevin Merriman 48 Height Protest by Jen Miller 49 Dancer by Bradford Cover 50 Ars Poetica by Amy Judge 55 Editorial decision is shared equally among the Editorial Board members -title page NOTE: The author of the poem Satellites is listed as Andrew C. Carinston in the published table of contents. This is likely a misspelling as there are four instances of an Andrew C. Carington elsewhere in this edition, including the attribution on the page where Satellites is published. NOTE: The author of the poem Where We Go Together is listed as Man Angantyr in the published table of contents. This is likely a misspelling as there are four instances of an Mans Angantyr elsewhere in this edition, including the attribution on the pages where Where We Go Together is published. NOTE: Chris Byrd is listed as the author of the poem Sunset in the published version. However a note in the received version indicates that the author is actually Chris Rynd, whose poem Bible Thumper is also published in this issue. No Chris Byrd is listed among the contributors to this issue. NOTE: The author of the poem Music = Love? is listed as Shammon J. Salser in the published table of contents. This is likely a misspelling. Where Music = Love? appears the author is listed as Shannon J. Salser. The same is true of the contributors section. NOTE: Though the published table of contents is followed here, the poem by Zach Smith that is published on page 31 is listed as The Music of the Sun on page 31

Darwin Core: An Evolving Community-Developed Biodiversity Data Standard

Biodiversity data derive from myriad sources stored in various formats on many distinct hardware and software platforms. An essential step towards understanding global patterns of biodiversity is to provide a standardized view of these heterogeneous data sources to improve interoperability. Fundamental to this advance are definitions of common terms. This paper describes the evolution and development of Darwin Core, a data standard for publishing and integrating biodiversity information. We focus on the categories of terms that define the standard, differences between simple and relational Darwin Core, how the standard has been implemented, and the community processes that are essential for maintenance and growth of the standard. We present case-study extensions of the Darwin Core into new research communities, including metagenomics and genetic resources. We close by showing how Darwin Core records are integrated to create new knowledge products documenting species distributions and changes due to environmental perturbations

Design and Performance of SiPM-Based Readout of PbF\u3csub\u3e2\u3c/sub\u3e Crystals for High-Rate, Precision Timing Applications

We have developed a custom amplifier board coupled to a large-format 16-channel Hamamatsu silicon photomultiplier device for use as the light sensor for the electromagnetic calorimeters in the Muon g - 2 experiment at Fermilab. The calorimeter absorber is an array of lead-fluoride crystals, which produces short-duration Cherenkov light. The detector sits in the high magnetic field of the muon storage ring. The SiPMs selected, and their accompanying custom electronics, must preserve the short pulse shape, have high quantum efficiency, be non-magnetic, exhibit gain stability under varying rate conditions, and cover a fairly large fraction of the crystal exit surface area. We describe an optimized design that employs the new-generation of thru-silicon via devices. The performance is documented in a series of bench and beam tests

LSST: from Science Drivers to Reference Design and Anticipated Data Products

(Abridged) We describe here the most ambitious survey currently planned in the optical, the Large Synoptic Survey Telescope (LSST). A vast array of science will be enabled by a single wide-deep-fast sky survey, and LSST will have unique survey capability in the faint time domain. The LSST design is driven by four main science themes: probing dark energy and dark matter, taking an inventory of the Solar System, exploring the transient optical sky, and mapping the Milky Way. LSST will be a wide-field ground-based system sited at Cerro Pach\'{o}n in northern Chile. The telescope will have an 8.4 m (6.5 m effective) primary mirror, a 9.6 deg$^2$ field of view, and a 3.2 Gigapixel camera. The standard observing sequence will consist of pairs of 15-second exposures in a given field, with two such visits in each pointing in a given night. With these repeats, the LSST system is capable of imaging about 10,000 square degrees of sky in a single filter in three nights. The typical 5$\sigma$ point-source depth in a single visit in $r$ will be $\sim 24.5$ (AB). The project is in the construction phase and will begin regular survey operations by 2022. The survey area will be contained within 30,000 deg$^2$ with $\delta<+34.5^\circ$, and will be imaged multiple times in six bands, $ugrizy$, covering the wavelength range 320--1050 nm. About 90\% of the observing time will be devoted to a deep-wide-fast survey mode which will uniformly observe a 18,000 deg$^2$ region about 800 times (summed over all six bands) during the anticipated 10 years of operations, and yield a coadded map to $r\sim27.5$. The remaining 10\% of the observing time will be allocated to projects such as a Very Deep and Fast time domain survey. The goal is to make LSST data products, including a relational database of about 32 trillion observations of 40 billion objects, available to the public and scientists around the world.Comment: 57 pages, 32 color figures, version with high-resolution figures available from https://www.lsst.org/overvie