Mt. Carmel Shade Structure

The Mt. Carmel Shade Structure incorporated the efforts of students practicing Architectural Engineering and Construction Management disciplines. The project consisted of designing, engineering and constructing a steel frame structure for the benefit of Mt. Carmel Church and its associated preschool

An Application of Gaussian Process Modeling for High-order Accurate Adaptive Mesh Refinement Prolongation

We present a new polynomial-free prolongation scheme for Adaptive Mesh Refinement (AMR) simulations of compressible and incompressible computational fluid dynamics. The new method is constructed using a multi-dimensional kernel-based Gaussian Process (GP) prolongation model. The formulation for this scheme was inspired by the GP methods introduced by A. Reyes et al. (A New Class of High-Order Methods for Fluid Dynamics Simulation using Gaussian Process Modeling, Journal of Scientific Computing, 76 (2017), 443-480; A variable high-order shock-capturing finite difference method with GP-WENO, Journal of Computational Physics, 381 (2019), 189-217). In this paper, we extend the previous GP interpolations and reconstructions to a new GP-based AMR prolongation method that delivers a high-order accurate prolongation of data from coarse to fine grids on AMR grid hierarchies. In compressible flow simulations special care is necessary to handle shocks and discontinuities in a stable manner. To meet this, we utilize the shock handling strategy using the GP-based smoothness indicators developed in the previous GP work by A. Reyes et al. We demonstrate the efficacy of the GP-AMR method in a series of testsuite problems using the AMReX library, in which the GP-AMR method has been implemented

Should We Be Confident in Published Research? A Case Study of Confidence Interval Reporting in Health Education and Behavior Research

Confidence intervals (CIs) have been highlighted as “the best” reporting device when reporting statistical findings. However, researchers often fail to maximize the utility of CIs in research. We seek to (a) present a primer on CIs; (b) outline reporting practices of health researchers; and (c) discuss implications for statistical best practice reporting in social science research. Approximately 1,950 peer-reviewed articles were examined from six health education, promotion, and behavior journals. We recorded: (a) whether the author(s) reported a CI; (b) whether the author(s) reported a CI estimate width, either numerical or visual; and (c) whether an associated effect size was reported alongside the CI. Of the 1,245 quantitative articles in the final sample, 46.5% (n = 580) reported confidence interval use; , and 518 provided numerical/visual interval estimates. Of the articles reporting CIs, 383 (64.2%) articles reported a CI with an associated effect size, meeting the American Psychological Association’s (APA) recommendation for statistical reporting best-practice. Health education literature demonstrates inconsistent statistical reporting practices, and falls short in employing best practices and consistently outlining the minimum expectations recommended by APA. In an effort to maximize utility and implications of health education, promotion, and behavior research, future investigations should provide comprehensive information regarding research findings

Unique safety features and licensing requirements of the NuScale small modular reactor

Small modular reactors (SMR) offer a novel approach to the construction and operation of nuclear power plants. The NuScale VOYGR™ plant uses a simplified SMR design that is based on proven light-water reactor technology with substantial improvements in nuclear safety. It consists of a 250 MWt reactor core housed with other primary system components in an integral reactor pressure vessel surrounded by a steel containment vessel, all of which is immersed in a large pool of water that also serves as the ultimate heat sink. At the core of the NuScale safety case are three primary safety systems: the decay heat removal system, the emergency core cooling system, and the containment. The ability of the NuScale Power Module (NPM) passive safety systems to remove core decay heat for an unlimited duration is demonstrated through analysis of a beyond-design-basis extended loss of AC power with no replenishment of water to the ultimate heat sink or operator actions. The NuScale methodology to evaluate an indefinite loss of AC power uses the proprietary NRELAP5 systems analysis computer code. Analysis results show that the reactor coolant system liquid level above the core is maintained and that containment pressure remains below the vessel design pressure. Once full passive air cooling is established, containment pressure and temperature will decrease over time with decreasing core decay heat. NuScale received standard design approval in September 2020 and design certification in January 2023 for its 50 MWe NPM configured as a 12 module plant. NuScale is currently seeking standard design approval to increase its core power to 250 MWt, nominally 77 MWe per module, in a 6-module plant (VOYGR™-6) configuration. The high-level safety of NuScale’s SMR technology is foundational to a new standard of nuclear power plant resilience

The Climate-system Historical Forecast Project: providing open access to seasonal forecast ensembles from centers around the globe

Fil: Tompkins, Adrian M.. The Abdus Salam; ItaliaFil: Ortiz de Zarate, Maria Ines. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Centre National de la Recherche Scientifique; FranciaFil: Saurral, Ramiro Ignacio. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Centre National de la Recherche Scientifique; FranciaFil: Vera, Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Centro de Investigaciones del Mar y la Atmósfera. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Centro de Investigaciones del Mar y la Atmósfera; Argentina. Centre National de la Recherche Scientifique; FranciaFil: Saulo, Andrea Celeste. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Ministerio de Defensa. Secretaria de Planeamiento. Servicio Meteorológico Nacional; ArgentinaFil: Merryfield, William J.. Canadian Centre for Climate Modelling and Analysis; CanadáFil: Sigmond, Michael. Canadian Centre for Climate Modelling and Analysis; CanadáFil: Lee, Woo Sung. Canadian Centre for Climate Modelling and Analysis; CanadáFil: Baehr, Johanna. Universitat Hamburg; AlemaniaFil: Braun, Alain. Météo-France; FranciaFil: Amy Butler. National Ocean And Atmospheric Administration; Estados UnidosFil: Déqué, Michel. Météo-France; FranciaFil: Doblas Reyes, Francisco J.. Institució Catalana de Recerca i Estudis Avancats; España. Barcelona Supercomputing Center - Centro Nacional de Supercomputacion; EspañaFil: Gordon, Margaret. Met Office; Reino UnidoFil: Scaife, Adam A.. University of Exeter; Reino UnidoFil: Yukiko Imada. Japan Meteorological Agency. Meteorological Research Institute. Climate Research Department; JapónFil: Masayoshi Ishii. Japan Meteorological Agency. Meteorological Research Institute. Climate Research Department; JapónFil: Tomoaki Ose. Japan Meteorological Agency. Meteorological Research Institute. Climate Research Department; JapónFil: Kirtman, Ben. University of Miami; Estados UnidosFil: Kumar, Arun. National Ocean And Atmospheric Administration; Estados UnidosFil: Müller, Wolfgang A.. Max-Planck-Institut für Meteorologie; AlemaniaFil: Pirani, Anna. Université Paris-Saclay; FranciaFil: Stockdale, Tim. European Centre for Medium-Range Weather; Reino UnidoFil: Rixen, Michel. World Meteorological Organization. World Climate Research Programme; SuizaFil: Yasuda, Tamaki. Japan Meteorological Agency. Climate Prediction Division; Japó

Treatment time and circadian genotype interact to influence radiotherapy side-effects. A prospective European validation study using the REQUITE cohort

Breast cancer; Circadian rhythm; RadiotherapyCáncer de mama; Ritmo circadiano; RadioterapiaCàncer de mama; Ritme circadià; RadioteràpiaBackground Circadian rhythm impacts broad biological processes, including response to cancer treatment. Evidence conflicts on whether treatment time affects risk of radiotherapy side-effects, likely because of differing time analyses and target tissues. We previously showed interactive effects of time and genotypes of circadian genes on late toxicity after breast radiotherapy and aimed to validate those results in a multi-centre cohort. Methods Clinical and genotype data from 1690 REQUITE breast cancer patients were used with erythema (acute; n=340) and breast atrophy (two years post-radiotherapy; n=514) as primary endpoints. Local datetimes per fraction were converted into solar times as predictors. Genetic chronotype markers were included in logistic regressions to identify primary endpoint predictors. Findings Significant predictors for erythema included BMI, radiation dose and PER3 genotype (OR 1.27(95%CI 1.03-1.56); P < 0.03). Effect of treatment time effect on acute toxicity was inconclusive, with no interaction between time and genotype. For late toxicity (breast atrophy), predictors included BMI, radiation dose, surgery type, treatment time and SNPs in CLOCK (OR 0.62 (95%CI 0.4-0.9); P < 0.01), PER3 (OR 0.65 (95%CI 0.44-0.97); P < 0.04) and RASD1 (OR 0.56 (95%CI 0.35-0.89); P < 0.02). There was a statistically significant interaction between time and genotypes of circadian rhythm genes (CLOCK OR 1.13 (95%CI 1.03-1.23), P < 0.01; PER3 OR 1.1 (95%CI 1.01-1.2), P < 0.04; RASD1 OR 1.15 (95%CI 1.04-1.28), P < 0.008), with peak time for toxicity determined by genotype. Interpretation Late atrophy can be mitigated by selecting optimal treatment time according to circadian genotypes (e.g. treat PER3 rs2087947C/C genotypes in mornings; T/T in afternoons). We predict triple-homozygous patients (14%) reduce chance of atrophy from 70% to 33% by treating in mornings as opposed to mid-afternoon. Future clinical trials could stratify patients treated at optimal times compared to those scheduled normally.EU-FP7