25 research outputs found

    Effect of microstructure on the internal hydriding behavior of uranium

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    The Spatial Expansion and Ecological Footprint of Fisheries (1950 to Present)

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    Using estimates of the primary production required (PPR) to support fisheries catches (a measure of the footprint of fishing), we analyzed the geographical expansion of the global marine fisheries from 1950 to 2005. We used multiple threshold levels of PPR as percentage of local primary production to define ‘fisheries exploitation’ and applied them to the global dataset of spatially-explicit marine fisheries catches. This approach enabled us to assign exploitation status across a 0.5° latitude/longitude ocean grid system and trace the change in their status over the 56-year time period. This result highlights the global scale expansion in marine fisheries, from the coastal waters off North Atlantic and West Pacific to the waters in the Southern Hemisphere and into the high seas. The southward expansion of fisheries occurred at a rate of almost one degree latitude per year, with the greatest period of expansion occurring in the 1980s and early 1990s. By the mid 1990s, a third of the world's ocean, and two-thirds of continental shelves, were exploited at a level where PPR of fisheries exceed 10% of PP, leaving only unproductive waters of high seas, and relatively inaccessible waters in the Arctic and Antarctic as the last remaining ‘frontiers.’ The growth in marine fisheries catches for more than half a century was only made possible through exploitation of new fishing grounds. Their rapidly diminishing number indicates a global limit to growth and highlights the urgent need for a transition to sustainable fishing through reduction of PPR

    Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

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    Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

    Lightweight, low cost compositionally complex multiphase alloys with optimized strength, ductility and corrosion resistance: Discovery, design and mechanistic understandings

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    A strategy for designing compositionally complex alloys (CCAs) achieving multiple objectives is articulated. In this specific case, the objectives are low density and cost, along with good strength, ductility, and aqueous corrosion resistance. The present strategy has produced a two-phase material, having a ductile FCC matrix and a L21 intermetallic reinforcing phase. A machine learning algorithm has been trained using attributes of binary phase diagrams as inputs and the existing experimentally informed CCA database as output values, which efficiently predicts the phases which will result from combinations of selected elements. Corrosion resistance is achieved through tailoring the composition such that solute partitioning promotes passivity of both phases. Surprising results of composition optimization, such as preferred levels of Mn and Mo in an Al-Cr-Fe-Mo-Mn-Ni-Ti alloy are presented. While raw material cost, density, corrosion resistance, and stiffness are strong functions of alloy chemistry, the strength and ductility are highly sensitive to microstructure as well. A genetic algorithm is used to optimize a crystal plasticity-based prediction of toughness, defined as the product of ultimate tensile strength and uniform elongation, by varying microstructural attributes. Surprising dependencies of this toughness on the microstructure inputs are highlighted. Experimental results demonstrate the efficacy of the approach
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