73 research outputs found

    Subregional DXA-derived vertebral bone mineral measures are stronger predictors of failure load in specimens with lower areal bone mineral density, compared to those with higher areal bone mineral density

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    Measurement of areal bone mineral density (aBMD) in intravertebral subregions may increase the diagnostic sensitivity of dual-energy X-ray absorptiometry (DXA)-derived parameters for vertebral fragility. This study investigated whether DXA-derived bone parameters in vertebral subregions were better predictors of vertebral bone strength in specimens with low aBMD, compared to those with higher aBMD. Twenty-five lumbar vertebrae (15 embalmed and 10 fresh-frozen) were scanned with posteroanterior- (PA) and lateral-projection DXA, and then mechanically tested in compression to ultimate failure. Whole-vertebral aBMD and bone mineral content (BMC) were measured from the PA- and lateral-projection scans and within 6 intravertebral subregions. Multivariate regression was used to predict ultimate failure load by BMC, adjusted for vertebral size and specimen fixation status across the whole specimen set, and when subgrouped into specimens with low aBMD and high aBMD. Adjusted BMC explained a substantial proportion of variance in ultimate vertebral load, when measured over the whole vertebral area in lateral projection (adjusted R2 0.84) and across the six subregions (ROIs 2–7) (adjusted R2 range 0.58–0.78). The association between adjusted BMC, either measured subregionally or across the whole vertebral area, and vertebral failure load, was increased for the subgroup of specimens with identified ‘low aBMD’, compared to those with ‘high aBMD’, particularly in the anterior subregion where the adjusted R2 differed by 0.44. The relative contribution of BMC measured in vertebral subregions to ultimate failure load is greater among specimens with lower aBMD, compared to those with higher aBMD, particularly in the anterior subregion of the vertebral body

    The EC-Earth3 Earth system model for the Coupled Model Intercomparison Project 6

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    The Earth system model EC-Earth3 for contributions to CMIP6 is documented here, with its flexible coupling framework, major model configurations, a methodology for ensuring the simulations are comparable across different high-performance computing (HPC) systems, and with the physical performance of base configurations over the historical period. The variety of possible configurations and sub-models reflects the broad interests in the EC-Earth community. EC-Earth3 key performance metrics demonstrate physical behavior and biases well within the frame known from recent CMIP models. With improved physical and dynamic features, new Earth system model (ESM) components, community tools, and largely improved physical performance compared to the CMIP5 version, EC-Earth3 represents a clear step forward for the only European community ESM. We demonstrate here that EC-Earth3 is suited for a range of tasks in CMIP6 and beyond

    Regional variation in the role of humidity on city-level heat-related mortality

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    The rising humid heat is regarded as a severe threat to human survivability, but the proper integration of humid heat into heat-health alerts is still being explored. Using state-of-the-art epidemiological and climatological datasets, we examined the association between multiple heat stress indicators (HSIs) and daily human mortality in 739 cities worldwide. Notable differences were observed in the long-term trends and timing of heat events detected by HSIs. Air temperature (Tair) predicts heat-related mortality well in cities with a robust negative Tair-relative humidity correlation (CT-RH). However, in cities with near-zero or weak positive CT-RH, HSIs considering humidity provide enhanced predictive power compared to Tair. Furthermore, the magnitude and timing of heat-related mortality measured by HSIs could differ largely from those associated with Tair in many cities. Our findings provide important insights into specific regions where humans are vulnerable to humid heat and can facilitate the further enhancement of heat-health alert systems. © The Author(s) 2024.Q.G., M.H., and T.O. were supported by the Environment Research and Technology Development Fund (JPMEERF23S21120) of the Environmental Restoration and Conservation Agency provided by the Ministry of the Environment of Japan. Q.G. was supported by the Musha Shugyo international travel grants from the School of Engineering, The University of Tokyo. T.O. was supported by the Japan Society for the Promotion of Science (KAKENHI: 21H05002), and the Environment Research and Technology Development Fund of the Environmental Restoration and Conservation Agency of Japan (JPMEERF23S21100). M.N.M. was supported by the European Commission (H2020-MSCA-IF-2020) under REA grant agreement no. 101022870. A.G. was supported by the Medical Research Council-UK (Grant ID: MR/V034162/1) and European Union’s Horizon 2020 Project Exhaustion (Grant ID: 820655). J.K. was supported by the Czech Science Foundation, project 23-06749S. A.M.V.-C. supported by the Swiss National Science Foundation (TMSGI3_211626). V.H. was supported by the European Union’s Horizon 2020 research and innovation program (H2020-MSCA-IF-2020, Grant No.: 101032087). Y.S. was supported by Brain Pool Plus program funded by the Ministry of Science and ICT through the National Research Foundation of Korea (NRF-2021H1D3A2A03097768), and the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (NRF-2023R1A2C1004754)

    Institutional investors and corporate governance

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    We provide a comprehensive overview of the role of institutional investors in corporate governance with three main components. First, we establish new stylized facts documenting the evolution and importance of institutional ownership. Second, we provide a detailed characterization of key aspects of the legal and regulatory setting within which institutional investors govern portfolio firms. Third, we synthesize the evolving response of the recent theoretical and empirical academic literature in finance to the emergence of institutional investors in corporate governance. We highlight how the defining aspect of institutional investors – the fact that they are financial intermediaries – differentiates them in their governance role from standard principal blockholders. Further, not all institutional investors are identical, and we pay close attention to heterogeneity amongst institutional investors as blockholders

    Consistency and discrepancy in the atmospheric response to Arctic sea-ice loss across climate models

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    This is the author accepted manuscript. The final version is available from Springer Nature via the DOI in this recordThe decline of Arctic sea ice is an integral part of anthropogenic climate change. Sea-ice loss is already having a significant impact on Arctic communities and ecosystems. Its role as a cause of climate changes outside of the Arctic has also attracted much scientific interest. Evidence is mounting that Arctic sea-ice loss can affect weather and climate throughout the Northern Hemisphere. The remote impacts of Arctic sea-ice loss can only be properly represented using models that simulate interactions among the ocean, sea ice, land and atmosphere. A synthesis of six such experiments with different models shows consistent hemispheric-wide atmospheric warming, strongest in the mid-to-high-latitude lower troposphere; an intensification of the wintertime Aleutian Low and, in most cases, the Siberian High; a weakening of the Icelandic Low; and a reduction in strength and southward shift of the mid-latitude westerly winds in winter. The atmospheric circulation response seems to be sensitive to the magnitude and geographic pattern of sea-ice loss and, in some cases, to the background climate state. However, it is unclear whether current-generation climate models respond too weakly to sea-ice change. We advocate for coordinated experiments that use different models and observational constraints to quantify the climate response to Arctic sea-ice loss.J.A.S. and R.B. were funded by the Natural Environment Research Council (NE/P006760/1). C.D. acknowledges the National Science Foundation (NSF), which sponsors the National Center for Atmospheric Research. D.M.S. was supported by the Met Office Hadley Centre Climate Programme (GA01101) and the APPLICATE project, which is funded by the European Union’s Horizon 2020 programme. X.Z. was supported by the NSF (ARC#1023592). P.J.K. and K.E.M. were supported by the Canadian Sea Ice and Snow Evolution Network, which is funded by the Natural Science and Engineering Research Council of Canada. T.O. was funded by Environment and Climate Change Canada (GCXE17S038). L.S. was supported by the National Oceanic and Atmospheric Administration’s Climate Program Office
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