Catchment hydrology, resources, economics and management (ChREAM): Integrated modelling of rural land use & farm income impacts of the WFD and its potential non-market benefits

The paper outlines a programme of research funded under the Rural Economy and Land Use (RELU) programme. The proposed research will examine the likely effects of the Water Framework Directive (WFD) in terms of both its impacts upon the farming sector and the non-market benefits it may generate. From an agricultural perspective the WFD will impose a substantial extension of controls upon diffuse pollution from farms. A major objective of the research will be to assess the likely response and consequent economic costs to an already fragile farming sector. This objective will be addressed via a highly interdisciplinary methodology combining hydrological and other physical sciences with quantitative and qualitative socio-economic analyses to generate an integrated hydrological-economic model of farm activities and incomes. This will dynamically link farm local and regional activities to water standards, allowing feedback loops to indicate the impacts of altering farm activity and changing water quality targets. Model parameters and response scenarios will initially be established via quantitative estimation and then refined through a series of farm attitude and behaviour surveys. This cost-effectiveness analysis will be complemented by an assessment of the benefits arising from the WFD and an aggregation and equity analysis of the distribution of both costs and benefits. Planned deliverables include assessments of the impact of alternative WFD implementation strategies allowing policy makers to inspect effects upon farmer and the wider community at a variety of spatial scales

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

The epidemiology and outcomes of invasive \u3ci\u3eCandida\u3c/i\u3e infections among organ transplant recipients in the United States: results of the Transplant-Associated Infection Surveillance Network (TRANSNET)

Background: Invasive candidiasis (IC) is a common cause of mortality in solid organ transplant recipients (OTRs), but knowledge of epidemiology in this population is limited. Method: The present analysis describes data from 15 US centers that prospectively identified IC from nearly 17 000 OTRs. Analyses were undertaken to determine predictors of infection and mortality. Results: A total of 639 cases of IC were identified. The most common species was Candida albicans (46.3%), followed by Candida glabrata (24.4%) and Candida parapsilosis (8.1%). In 68 cases \u3e1 species was identified. The most common infection site was bloodstream (44%), followed by intra-abdominal (14%). The most frequently affected allograft groups were liver (41.1%) and kidney (35.3%). All-cause mortality at 90 days was 26.5% for all species and was highest for Candida tropicalis (44%) and C. parapsilosis (35.2%). Non-white race and female gender were more commonly associated with non-albicans species. A high rate of breakthrough IC was seen in patients receiving antifungal prophylaxis (39%). Factors associated with mortality include organ dysfunction, lung transplant, and treatment with a polyene antifungal. The only modifiable factor identified was choice of antifungal drug class based upon infecting Candida species. Conclusion: These data highlight the common and distinct features of IC in OTRs

Food insecurity, school absenteeism and educational attainment of adolescents in Jimma Zone Southwest Ethiopia: a longitudinal study

<p>Abstract</p> <p>Background</p> <p>Food insecurity not only affects physical growth and health of children but also their intellectual development, school attendance and academic performance. However, most evidences are based on studies in high income countries. Although food insecurity is common in Ethiopia, to what extent it affects school attendance and educational attainment of adolescents is not explored. We hypothesized that food insecure adolescents would be more likely to be absent from school and have lower grades attained after 1 year compared to their food secure peers.</p> <p>Methods</p> <p>We used data from 2009 adolescents in the age group of 13-17 years from two consecutive surveys of a five year longitudinal family study in Southwest Ethiopia. A stratified random sampling was used to select participants. Regression analyses were used to compare school absenteeism and the highest grade attained after 1 year of follow-up in food secure and insecure adolescents. The analysis was adjusted for demographic factors, reported illness and workload.</p> <p>Results</p> <p>Significantly more (33.0%) food insecure adolescents were absent from school compared with their food secure peers (17.8%, P < 0.001). Multivariable logistic regression analyses showed that after adjusting for gender, place of residence and gender of the household head, adolescent food insecurity [OR 1.77 (1.34-2.33)], severe household food insecurity [OR 1.62 (1.27-2.06)], illness during the past one month before the survey [OR 2.26 (1.68-3.06)], the highest grade aspired to be completed by the adolescent [OR 0.92 (0.88-0.96)], and the number of days that the adolescent had to work per week [OR 1.16 (1.07-1.26)] were independent predictors of school absenteeism. Similarly after controlling for household income and gender of the household head, adolescent food insecurity(P < 0.001), severe household food insecurity(P < 0.001), illness during the last month(P < 0.001) and rural residence(P < 0.001) were inversely associated with highest grade attained, while age of the adolescent(P < 0.001), the highest grade intended to be completed(P < 0.001) and residence in semi urban area(P < 0.001) were positively associated with the highest grade attained.</p> <p>Conclusions</p> <p>Adolescent and household food insecurity are positively associated with school absenteeism and a lower educational attainment. Programs aiming to achieve universal access to primary education in food insecure environments should integrate interventions to ensure food security of adolescents.</p

A search for new physics in central exclusive production using the missing mass technique with the CMS detector and the CMS-TOTEM precision proton spectrometer

A generic search is presented for the associated production of a Z boson or a photon with an additional unspecified massive particle X, pp → pp + Z/γ + X, in proton-tagged events from proton–proton collisions at √s = 13 TeV, recorded in 2017 with the CMS detector and the CMS-TOTEM precision proton spectrometer. The missing mass spectrum is analysed in the 600–1600 GeV range and a fit is performed to search for possible deviations from the background expectation. No significant excess in data with respect to the background predictions has been observed. odelindependent upper limits on the visible production cross section of pp → pp + Z/γ + X are set

Portable Acceleration of CMS Computing Workflows with Coprocessors as a Service

A preprint version of the article is available at: arXiv:2402.15366v2 [physics.ins-det], https://arxiv.org/abs/2402.15366 . Comments: Replaced with the published version. Added the journal reference and the DOI. All the figures and tables can be found at https://cms-results.web.cern.ch/cms-results/public-results/publications/MLG-23-001 (CMS Public Pages). Report numbers: CMS-MLG-23-001, CERN-EP-2023-303.Data Availability: No datasets were generated or analyzed during the current study.Computing demands for large scientific experiments, such as the CMS experiment at the CERN LHC, will increase dramatically in the next decades. To complement the future performance increases of software running on central processing units (CPUs), explorations of coprocessor usage in data processing hold great potential and interest. Coprocessors are a class of computer processors that supplement CPUs, often improving the execution of certain functions due to architectural design choices. We explore the approach of Services for Optimized Network Inference on Coprocessors (SONIC) and study the deployment of this as-a-service approach in large-scale data processing. In the studies, we take a data processing workflow of the CMS experiment and run the main workflow on CPUs, while offloading several machine learning (ML) inference tasks onto either remote or local coprocessors, specifically graphics processing units (GPUs). With experiments performed at Google Cloud, the Purdue Tier-2 computing center, and combinations of the two, we demonstrate the acceleration of these ML algorithms individually on coprocessors and the corresponding throughput improvement for the entire workflow. This approach can be easily generalized to different types of coprocessors and deployed on local CPUs without decreasing the throughput performance. We emphasize that the SONIC approach enables high coprocessor usage and enables the portability to run workflows on different types of coprocessors.SCOAP3. Open access funding provided by CERN (European Organization for Nuclear Research

The epidemiology and outcomes of invasive \u3ci\u3eCandida\u3c/i\u3e infections among organ transplant recipients in the United States: results of the Transplant-Associated Infection Surveillance Network (TRANSNET)

Background: Invasive candidiasis (IC) is a common cause of mortality in solid organ transplant recipients (OTRs), but knowledge of epidemiology in this population is limited. Method: The present analysis describes data from 15 US centers that prospectively identified IC from nearly 17 000 OTRs. Analyses were undertaken to determine predictors of infection and mortality. Results: A total of 639 cases of IC were identified. The most common species was Candida albicans (46.3%), followed by Candida glabrata (24.4%) and Candida parapsilosis (8.1%). In 68 cases \u3e1 species was identified. The most common infection site was bloodstream (44%), followed by intra-abdominal (14%). The most frequently affected allograft groups were liver (41.1%) and kidney (35.3%). All-cause mortality at 90 days was 26.5% for all species and was highest for Candida tropicalis (44%) and C. parapsilosis (35.2%). Non-white race and female gender were more commonly associated with non-albicans species. A high rate of breakthrough IC was seen in patients receiving antifungal prophylaxis (39%). Factors associated with mortality include organ dysfunction, lung transplant, and treatment with a polyene antifungal. The only modifiable factor identified was choice of antifungal drug class based upon infecting Candida species. Conclusion: These data highlight the common and distinct features of IC in OTRs

{Search for direct production of GeV-scale resonances decaying to a pair of muons in proton-proton collisions at s \sqrt{s} = 13 TeV}

A search for direct production of low-mass dimuon resonances is performed using = 13 TeV proton-proton collision data collected by the CMS experiment during the 2017–2018 operation of the CERN LHC with an integrated luminosity of 96.6 fb−1. The search exploits a dedicated high-rate trigger stream that records events with two muons with transverse momenta as low as 3 GeV but does not include the full event information. The search is performed by looking for narrow peaks in the dimuon mass spectrum in the ranges of 1.1–2.6 GeV and 4.2–7.9 GeV. No significant excess of events above the expectation from the standard model background is observed. Model-independent limits on production rates of dimuon resonances within the experimental fiducial acceptance are set. Competitive or world’s best limits are set at 90% confidence level for a minimal dark photon model and for a scenario with two Higgs doublets and an extra complex scalar singlet (2HDM+S). Values of the squared kinetic mixing coefficient ε2 in the dark photon model above 10−6 are excluded over most of the mass range of the search. In the 2HDM+S, values of the mixing angle sin(θH) above 0.08 are excluded over most of the mass range of the search with a fixed ratio of the Higgs doublets vacuum expectation tan β = 0.5