Effects of condensation modeling on transient behavior of pressurized water reactors

In simulating pressurized water reactor (PWR) transients with large-scale systems codes such as TRAC and RELAP, the effect of condensation has been recognized as a controlling mechanism in the prediction of plant response. For transients involving contraction of or loss of primary coolant, the rate of condensation (primarily in the pressurizer) controls the system refill characteristics. Several separate but interacting phenomena occur during the process of pressurizer refill: steam compression, system heat losses, thermal stratification or mixing of liquid, and condensation. The relative importance of each of these processes and the degree of interaction between them during different transients is very complex. The existing condensation models do not adequately describe the interplay between these effects and this leads to uncertainties in the predicted system response. Further experimental data and code assessment are required to provide data necessary for improving condensation models. Three examples of transients involving uncertainties introduced by condensation modeling are (1) pressurized thermal shock (PTS) transients, (2) small break loss-of-coolant accidents (SBLOCA), and (3) steam generator tube ruptures (SGTR)

Effects of regional brain volumes on cognition in sickle cell anemia: A developmental perspective

BACKGROUND AND OBJECTIVES: Cognitive difficulties in people with sickle cell anemia (SCA) are related to lower processing speed index (PSI) and working memory index (WMI). However, risk factors are poorly understood so preventative strategies have not been explored. Brain volumes, specifically white matter volumes (WMV) which increases through early adulthood, have been associated with better cognition in healthy typically developing individuals. In patients with SCA, the reduced WMV and total subcortical volumes noted could explain cognitive deficits. We therefore examined developmental trajectories for regional brain volumes and cognitive endpoints in patients with SCA. METHODS: Data from two cohorts, the Sleep and Asthma Cohort and Prevention of Morbidity in SCA, were available. MRI data included T1-weighted axial images, pre-processed before regional volumes were extracted using Free-surfer. PSI and WMI from the Weschler scales of intelligence were used to test neurocognitive performance. Hemoglobin, oxygen saturation, hydroxyurea treatment and socioeconomic status from education deciles were available. RESULTS: One hundred and twenty nine patients (66 male) and 50 controls (21 male) aged 8-64 years were included. Brain volumes did not significantly differ between patients and controls. Compared with controls, PSI and WMI were significantly lower in patients with SCA, predicted by increasing age and male sex, with lower hemoglobin in the model for PSI but no effect of hydroxyurea treatment. In male patients with SCA only, WMV, age and socioeconomic status predicted PSI, while total subcortical volumes predicted WMI. Age positively and significantly predicted WMV in the whole group (patients + controls). There was a trend for age to negatively predict PSI in the whole group. For total subcortical volume and WMI, age predicted decrease only in the patient group. Developmental trajectory analysis revealed that PSI only was significantly delayed in patients at 8 years of age; the rate of development for the cognitive and brain volume data did not differ significantly from controls. DISCUSSION: Increasing age and male sex negatively impact cognition in SCA, with processing speed, also predicted by hemoglobin, delayed by mid childhood. Associations with brain volumes were seen in males with SCA. Brain endpoints, calibrated against large control datasets, should be considered for randomized treatment trials

Imputing biomarker status from RWE datasets — a comparative study

Missing data is a universal problem in analysing Real-World Evidence (RWE) datasets. In RWE datasets, there is a need to understand which features best correlate with clinical outcomes. In this context, the missing status of several biomarkers may appear as gaps in the dataset that hide meaningful values for analysis. Imputation methods are general strategies that replace missing values with plausible values. Using the Flatiron NSCLC dataset, including more than 35,000 subjects, we compare the imputation performance of six such methods on missing data: predictive mean matching, expectation-maximisation, factorial analysis, random forest, generative adversarial networks and multivariate imputations with tabular networks. We also conduct extensive synthetic data experiments with structural causal models. Statistical learning from incomplete datasets should select an appropriate imputation algorithm accounting for the nature of missingness, the impact of missing data, and the distribution shift induced by the imputation algorithm. For our synthetic data experiments, tabular networks had the best overall performance. Methods using neural networks are promising for complex datasets with non-linearities. However, conventional methods such as predictive mean matching work well for the Flatiron NSCLC biomarker dataset

Comparison among five hydrodynamic codes with a diverging-converging nozzle experiment

A realistic open-cycle gas-core nuclear rocket simulation model must be capable of a self-consistent nozzle calculation in conjunction with coupled radiation and neutron transport in three spatial dimensions. As part of the development effort for such a model, five hydrodynamic codes were used to compare with a converging-diverging nozzle experiment. The codes used in the comparison are CHAD, FLUENT, KIVA2, RAMPANT, and VNAP2. Solution accuracy as a function of mesh size is important because, in the near term, a practical three-dimensional simulation model will require rather coarse zoning across the nozzle throat. In the study, four different grids were considered. (1) coarse, radially uniform grid, (2) coarse, radially nonuniform grid, (3) fine, radially uniform grid, and (4) fine, radially nonuniform grid. The study involves code verification, not prediction. In other words, the authors know the solution they want to match, so they can change methods and/or modify an algorithm to best match this class of problem. In this context, it was necessary to use the higher-order methods in both FLUENT and RAMPANT. In addition, KIVA2 required a modification that allows significantly more accurate solutions for a converging-diverging nozzle. From a predictive point of view, code accuracy with no tuning is an important result. The most accurate codes on a coarse grid, CHAD and VNAP2, did not require any tuning. Their main comparison among the codes was the radial dependence of the Mach number across the nozzle throat. All five codes yielded a very similar solution with fine, radially uniform and radially nonuniform grids. However, the codes yielded significantly different solutions with coarse, radially uniform and radially nonuniform grids. For all the codes, radially nonuniform zoning across the throat significantly increased solution accuracy with a coarse mesh. None of the codes agrees in detail with the weak shock located downstream of the nozzle throat, but all the codes indicated the presence of a weak downstream shock

Trialling technologies to reduce hospital in‐patient falls: an agential realist analysis

This paper analyses the 'failure' of a patient safety intervention. Our study was part of an RCT of bed and bedside chair pressure sensors linked to radio pagers to prevent bedside falls in older people admitted to hospital. We use agential realism within science and technology studies to examine the fall and its prevention as a situated phenomenon of knowledge that is made and unmade through intra-actions between environment, culture, humans and technologies. We show that neither the intervention (the pressure sensor system), nor the outcome (fall prevention) could be disentangled from the broader sociomaterial context of the ward, the patients, the nurses and (especially) their work through the RCT. We argue that the RCT design, by virtue of its unacknowledged assumptions, played a part in creating the negative findings. The study also raises wider questions about the kind of subjectivities, agencies and power relations these entanglements might effect and (re)produce in the hospital ward

TEMPy2: a Python library with improved 3D electron microscopy density-fitting and validation workflows

Structural determination of molecular complexes by cryo-EM requires large, often complex processing of the image data that are initially obtained. Here, TEMPy2, an update of the TEMPy package to process, optimize and assess cryo-EM maps and the structures fitted to them, is described. New optimization routines, comprehensive automated checks and workflows to perform these tasks are described

Study protocol: can a school gardening intervention improve children's diets?

BACKGROUND: The current academic literature suggests there is a potential for using gardening as a tool to improve children's fruit and vegetable intake. This study is two parallel randomised controlled trials (RCT) devised to evaluate the school gardening programme of the Royal Horticultural Society (RHS) Campaign for School Gardening, to determine if it has an effect on children's fruit and vegetable intake. METHOD/DESIGN: Trial One will consist of 26 schools; these schools will be randomised into two groups, one to receive the intensive intervention as "Partner Schools" and the other to receive the less intensive intervention as "Associate Schools". Trial Two will consist of 32 schools; these schools will be randomised into either the less intensive intervention "Associate Schools" or a comparison group with delayed intervention. Baseline data collection will be collected using a 24-hour food diary (CADET) to collect data on dietary intake and a questionnaire exploring children's knowledge and attitudes towards fruit and vegetables. A process measures questionnaire will be used to assess each school's gardening activities. DISCUSSION: The results from these trials will provide information on the impact of the RHS Campaign for School Gardening on children's fruit and vegetable intake. The evaluation will provide valuable information for designing future research in primary school children's diets and school based interventions. TRIAL REGISTRATION: ISRCTN11396528