Effect of initial surface topography during laser polishing process: Statistical analysis

Surface finish is one of the most important quality characteristics of fabricated components. Laser polishing (LP) is one of the advanced manufacturing surface finishing techniques that has been recently developed and successfully employed for improving surface quality without deteriorating the overall structural form through surface smoothing by melting and redistributing a thin layer of molten material. This paper advances the statistical analysis of the LP process emphasizing aspects of the effect of the initial surface topography. Flat and ground initial surfaces are used for comparative statistical analysis of initial and polished profiles obtained experimentally. Their profile geometries and surface quality characteristics, such as, roughness, were compared and analyzed. In addition, LP process was experimentally investigated as a thermodynamic operator represented by a transfer function and it was examined by means of a coherence function

Preliminary experimental analysis of the surface topography formation during laser polishing H13 tooling steel using statistical characteristics of the surface amplitude distribution

48th SME North American Manufacturing Research Conference, NAMRC 48 (Cancelled due to COVID-19

Effect of transcranial direct current stimulation combined with patient-controlled intravenous morphine analgesia on analgesic use and post-thoracotomy pain. A prospective, randomized, double-blind, sham-controlled, proof-of-concept clinical trial

Background: Transcranial direct current stimulation (tDCS) is used for various chronic pain conditions, but experience with tDCS for acute postoperative pain is limited. This study investigated the effect of tDCS vs. sham stimulation on postoperative morphine consumption and pain intensity after thoracotomy. Methods: This is a single-center, prospective, randomized, double-blind, sham-controlled trial in lung cancer patients undergoing thoracotomy under general anesthesia. All patients received patient-controlled (PCA) intravenous morphine and intercostal nerve blocks at the end of surgery. The intervention group (a-tDCS, n = 31) received anodal tDCS over the left primary motor cortex (C3-Fp2) for 20 min at 1.2 mA, on five consecutive days; the control group (n = 31) received sham stimulation. Morphine consumption, number of analgesia demands, and pain intensity at rest, with movement and with cough were recorded at the following intervals: immediately before (T1), immediately after intervention (T2), then every hour for 4 h (Т3-Т6), then every 6 h (Т7-Т31) for 5 days. We recorded outcomes on postoperative days 1 and 5 and conducted a phone interview inquiring about chronic pain 1 year later (NCT03005548). Results: A total of 62 patients enrolled, but tDCS was prematurely stopped in six patients. Fifty-five patients (27 a-tDCS, 28 sham) had three or more tDCS applications and were included in the analysis. Cumulative morphine dose in the first 120 h after surgery was significantly lower in the tDCS [77.00 (54.00-123.00) mg] compared to sham group [112.00 (79.97-173.35) mg, p = 0.043, Cohen\u27s d = 0.42]. On postoperative day 5, maximum visual analog scale (VAS) pain score with cough was significantly lower in the tDCS group [29.00 (20.00-39.00) vs. 44.50 (30.00-61.75) mm, p = 0.018], and pain interference with cough was 80% lower [10.00 (0.00-30.00) vs. 50.00 (0.00-70.00), p = 0.013]. One year after surgery, there was no significant difference between groups with regard to chronic pain and analgesic use. Conclusion: In lung cancer patients undergoing thoracotomy, three to five tDCS sessions significantly reduced cumulative postoperative morphine use, maximum VAS pain scores with cough, and pain interference with cough on postoperative day 5, but there was no obvious long-term benefit from tDCS

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

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

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

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.Peer reviewe

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

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

Institutional investors and corporate governance

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

Seasonality of mortality under climate change: a multicountry projection study

Data sharing: All data used in our study were obtained from the MCC Collaborative Research Network under a data-sharing agreement and cannot be made publicly available. Researchers can refer to collaborators of the Network, who are listed as coauthors of this Article (primary contact: Antonio Gasparrini, [email protected]), for information on accessing the data for each country. The R code is available on request, and a reproducible example is publicly available on the personal GitHub website of the first author (https://github.com/LinaMadaniyazi).For more on the MCC see https://mccstudy.lshtm.ac.uk/Supplementary Material is available online at: https://www.sciencedirect.com/science/article/pii/S2542519623002693#sec1 .Background: Climate change can directly impact temperature-related excess deaths and might subsequently change the seasonal variation in mortality. In this study, we aimed to provide a systematic and comprehensive assessment of potential future changes in the seasonal variation, or seasonality, of mortality across different climate zones. Methods: In this modelling study, we collected daily time series of mean temperature and mortality (all causes or non-external causes only) via the Multi-Country Multi-City Collaborative (MCC) Research Network. These data were collected during overlapping periods, spanning from Jan 1, 1969 to Dec 31, 2020. We projected daily mortality from Jan 1, 2000 to Dec 31, 2099, under four climate change scenarios corresponding to increasing emissions (Shared Socioeconomic Pathways [SSP] scenarios SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5). We compared the seasonality in projected mortality between decades by its shape, timings (the day-of-year) of minimum (trough) and maximum (peak) mortality, and sizes (peak-to-trough ratio and attributable fraction). Attributable fraction was used to measure the burden of seasonality of mortality. The results were summarised by climate zones. Findings: The MCC dataset included 126 809 537 deaths from 707 locations within 43 countries or areas. After excluding the only two polar locations (both high-altitude locations in Peru) from climatic zone assessments, we analysed 126 766 164 deaths in 705 locations aggregated in four climate zones (tropical, arid, temperate, and continental). From the 2000s to the 2090s, our projections showed an increase in mortality during the warm seasons and a decrease in mortality during the cold seasons, albeit with mortality remaining high during the cold seasons, under all four SSP scenarios in the arid, temperate, and continental zones. The magnitude of this changing pattern was more pronounced under the high-emission scenarios (SSP3-7.0 and SSP5-8.5), substantially altering the shape of seasonality of mortality and, under the highest emission scenario (SSP5-8.5), shifting the mortality peak from cold seasons to warm seasons in arid, temperate, and continental zones, and increasing the size of seasonality in all zones except the arid zone by the end of the century. In the 2090s compared with the 2000s, the change in peak-to-trough ratio (relative scale) ranged from 0·96 to 1·11, and the change in attributable fraction ranged from 0·002% to 0·06% under the SSP5-8.5 (highest emission) scenario. Interpretation: A warming climate can substantially change the seasonality of mortality in the future. Our projections suggest that health-care systems should consider preparing for a potentially increased demand during warm seasons and sustained high demand during cold seasons, particularly in regions characterised by arid, temperate, and continental climates.This study was primarily supported by the Environment Research and Technology Development Fund (grant number JPMEERF20231007) of the Environmental Restoration and Conservation Agency, provided by the Ministry of the Environment of Japan. MH was supported by the Japan Science and Technology Agency as part of the Strategic International Collaborative Research Program (grant number JPMJSC20E4). AG was supported by the UK Medical Research Council (grant number MR/V034162/1) and the EU's Horizon 2020 research project Exhaustion (grant number 820655). AU and JK were supported by the Czech Science Foundation (project 22–24920S). JJKJ was supported by the Academy of Finland (grant number 310372; Global Health Risks Related to Atmospheric Composition and Weather Consortium). FS was supported by the Italian Ministry of University and Research, Department of Excellence project 2023–2027, Rethinking Data Science—Department of Statistics, Computer Science and Applications—University of Florence

Impact of population aging on future temperature-related mortality at different global warming levels

Data availability: All data needed to evaluate the conclusions in the paper are present in the paper and/or the Supplementary Materials. Data were collected within the MCC Collaborative Research Network under a data sharing agreement and cannot be made publicly available.Code availability: A sample of the analysis code is available from https://github.com/CHENlab-Yale/MCC_ProjAging_Temp .Supplementary information is available online at: https://link-springer-com.ezproxytest.brunel.ac.uk/article/10.1038/s41467-024-45901-z#Sec15 .Older adults are generally amongst the most vulnerable to heat and cold. While temperature-related health impacts are projected to increase with global warming, the influence of population aging on these trends remains unclear. Here we show that at 1.5 °C, 2 °C, and 3 °C of global warming, heat-related mortality in 800 locations across 50 countries/areas will increase by 0.5%, 1.0%, and 2.5%, respectively; among which 1 in 5 to 1 in 4 heat-related deaths can be attributed to population aging. Despite a projected decrease in cold-related mortality due to progressive warming alone, population aging will mostly counteract this trend, leading to a net increase in cold-related mortality by 0.1%–0.4% at 1.5–3 °C global warming. Our findings indicate that population aging constitutes a crucial driver for future heat- and cold-related deaths, with increasing mortality burden for both heat and cold due to the aging population.We acknowledge the World Climate Research Programme, which, through its Working Group on Coupled Modeling, coordinated and promoted CMIP6. We thank the climate modeling groups for producing and making available their model output, the Earth System Grid Federation (ESGF) for archiving the data and providing access, and the multiple funding agencies who support CMIP6 and ESGF. K.C. was supported by the Yale Planetary Solutions Project seed grant. A.G., A.S., and S.R. were supported by the European Union’s Horizon 2020 Project Exhaustion grant (820655). A.G. was also supported by the Medical Research Council UK grant (MR/V034162/1). J.M. received funding from the Fundação para a Ciência e a Tecnlogia Grant (SFRH/BPD/115112/2016). A.T. was supported by the MCIN/AEI/10.13039/501100011033 grant (CEX2018-000794-S). A.U. and J.K. were supported by the Czech Science Foundation (22-24920S). F.S. was supported by the Italian Ministry of University and Research (MUR), Department of Excellence project 2023-2027 ReDS ‘Rethinking Data Science’ - Department of Statistics, Computer Science and Applications - University of Florence. MNM. was supported by the European Commission (H2020-MSCA-IF-2020) under REA grant agreement no. 101022870. A.V.C. acknowledges the support of the Swiss National Foundation (TMSGI3_211626). V.H. received funding from the European Union’s Horizon 2020 research and innovation program (Marie Skłodowska-Curie Grant Agreement No.: 101032087)

Global, regional, and national burden of mortality associated with cold spells during 2000–19: a three-stage modelling study

Data sharing: All used data were obtained from the Multi-Country Multi-City (MCC) Collaborative Research Network (https://mccstudy.lshtm.ac.uk/) under a data sharing agreement and cannot be made publicly available. Researchers can refer to MCC participants, who are listed as coauthors of our study, for information on accessing the data for each country.Supplementary Material is available online at: https://www.sciencedirect.com/science/article/pii/S2542519623002772#sec1 .Background: Exposure to cold spells is associated with mortality. However, little is known about the global mortality burden of cold spells. Methods: A three-stage meta-analytical method was used to estimate the global mortality burden associated with cold spells by means of a time series dataset of 1960 locations across 59 countries (or regions). First, we fitted the location-specific, cold spell-related mortality associations using a quasi-Poisson regression with a distributed lag non-linear model with a lag period of up to 21 days. Second, we built a multivariate meta-regression model between location-specific associations and seven predictors. Finally, we predicted the global grid-specific cold spell-related mortality associations during 2000–19 using the fitted meta-regression model and the yearly grid-specific meta-predictors. We calculated the annual excess deaths, excess death ratio (excess deaths per 1000 deaths), and excess death rate (excess deaths per 100 000 population) due to cold spells for each grid across the world. Findings: Globally, 205 932 (95% empirical CI [eCI] 162 692–250 337) excess deaths, representing 3·81 (95% eCI 2·93–4·71) excess deaths per 1000 deaths (excess death ratio), and 3·03 (2·33–3·75) excess deaths per 100 000 population (excess death rate) were associated with cold spells per year between 2000 and 2019. The annual average global excess death ratio in 2016–19 increased by 0·12 percentage points and the excess death rate in 2016–19 increased by 0·18 percentage points, compared with those in 2000–03. The mortality burden varied geographically. The excess death ratio and rate were highest in Europe, whereas these indicators were lowest in Africa. Temperate climates had higher excess death ratio and rate associated with cold spells than other climate zones. Interpretation: Cold spells are associated with substantial mortality burden around the world with geographically varying patterns. Although the number of cold spells has on average been decreasing since year 2000, the public health threat of cold spells remains substantial. The findings indicate an urgency of taking local and regional measures to protect the public from the mortality burdens of cold spells.Australian Research Council, Australian National Health and Medical Research Council, EU's Horizon 2020 Project Exhaustion. This study was supported by the Australian Research Council (DP210102076), the Australian National Health and Medical Research Council (APP2000581) and the EU's Horizon 2020 Project Exhaustion (Grant ID: 820655). YGa and WH were supported by the China Scholarship Council (number 202008110182 and number 202006380055). YGu was supported by the Leader Fellowship (number APP2008813) of the Australian National Health and Medical Research Council. QZ was supported by the Natural Science Foundation of Shandong Province in China (grant ZR2021QH318) and the Shandong Excellent Young Scientists Fund Program (Overseas) (grant 2022HWYQ-055). AG was supported by the European Union's Horizon 2020 Project Exhaustion (Grant ID: 820655). JK and AU were supported by the Czech Science Foundation (project 22-24920S). VH was supported by the European Union's Horizon 2020 Research and Innovation Programme (Marie Skłodowska-Curie Grant Agreement Number 101032087), and SL was supported by an Emerging Leader Fellowship of the Australian National Health and Medical Research Council (number APP2009866)