A CFD study of two-phase frozen flow of air/water through a safety relief valve

The air-water two phase critical flows through a safety relief valve commonly used in the refrigeration industry is examined with particular emphasis on the prediction of the critical mass flowrates using CFD based approaches. The expansion of the gas through the valve and the associated acceleration is coupled to the liquid phase and results in changes to the velocity slip with the possibility of influencing the choking conditions and the magnitude of the critical mass flows. These conditions are poorly reported in the literature for safety valves. This paper presents a study where the ability of established two phase multi-dimensional modelling approaches to predict such conditions are investigated. Comparison with the simplified mixture model will show that this model tends to underestimate mass flowrates for medium to high liquid mass fraction. However, the two fluid model can adequately account for the thermal and mechanical non equilibrium for these complex flow conditions with the use of simplified droplet sizing rules

CFD study of Jet Impingement Test erosion using Ansys Fluent® and OpenFOAM®

The initial aim of this study was to compare OpenFoam and Ansys Fluent in order to verify OpenFoam’s Lagrangian Library and erosion capabilities. However, it was found that previous versions of Fluent have been providing wrong results for the discrete phase and the differences with the latest version (Ansys Fluent 15) are shown. A Submerged Jet Impingement Test is an effective method for studying erosion created by solid particles entrained in a liquid. When considering low particle concentrations a Lagrangian modeling of the particulate phase is a reasonable approach. Proper linkage between OpenFOAM’s Lagrangian library and the solver pimpleFoam for incompressible transient flows allows two-phase simulations to be undertaken for comparison with Ansys Fluent with the aim of verifying OpenFoam’s accuracy. Steady state convergence for the fluid flow is first accomplished and the results are compared, confirming a good agreement between the two packages. A transient simulation was then set up and spherical particles incorporated into the fluid flow. An assessment of the two codes’ discrete phase models was carried out, focusing on the differences between impact angles and velocities yielded at the impingement plate’s surface employing a similar strategy to that outlined first by Hattori et al. (2008) and later by Gnanavelu et al. (2009, 2011). In the comparison of OpenFoam with the latest version of Fluent, the main differences between the injection models are highlighted and the coupling possibilities between phases are taken into consideration. Agreement between trends for both impact angles and velocities is satisfactory when the last version of the commercial package is considered and the average discrepancy between numerical values is very low, verifying OpenFoam’s Lagrangian library. Two different Jet Impingement Test configurations are also compared and the differences highlighted

The Latent Class Structure of ADHD is stable across informants

Previous studies have looked at the structure of attention-deficit/ hyperactivity disorder (ADHD) using latent class analysis (LCA) of Child Behavior Checklist (CBCL) or Diagnostic and Statistical Manual of Mental Disorders (DSM) symptom structure. These studies have identified distinct classes of children with inattentive, hyperactive, or combined subtypes and have used these classes to refine genetic analyses. The objective of the current report is to determine if the latent class structure of ADHD subtypes is consistent across informant using the Conners' Rating Scales (CRS). LCA was applied to CRS forms from mother, father, and teacher reports of 1837, 1329 and 1048 latency aged Dutch twins, respectively. The optimal solution for boys was a 5-class solution for mothers, a 3-class solution for fathers, and a 4-class solution for teachers. For girls, a 4-class solution for mothers and a 3-class for fathers and teachers was optimal. Children placed into a class by one informant had markedly increased odds ratio of being placed into the same or similar class by the other informants. Results from LCA using Dutch twins with the CRS show stability across informants suggesting that more stable phenotypes may be accessible for genotyping using a multi-informant approach

Agreement between two large pan-cancer CRISPR-Cas9 gene dependency data sets.

Genome-scale CRISPR-Cas9 viability screens performed in cancer cell lines provide a systematic approach to identify cancer dependencies and new therapeutic targets. As multiple large-scale screens become available, a formal assessment of the reproducibility of these experiments becomes necessary. We analyze data from recently published pan-cancer CRISPR-Cas9 screens performed at the Broad and Sanger Institutes. Despite significant differences in experimental protocols and reagents, we find that the screen results are highly concordant across multiple metrics with both common and specific dependencies jointly identified across the two studies. Furthermore, robust biomarkers of gene dependency found in one data set are recovered in the other. Through further analysis and replication experiments at each institute, we show that batch effects are driven principally by two key experimental parameters: the reagent library and the assay length. These results indicate that the Broad and Sanger CRISPR-Cas9 viability screens yield robust and reproducible findings

Dysmorphometrics: the modelling of morphological abnormalities

<p>Abstract</p> <p>Background</p> <p>The study of typical morphological variations using quantitative, morphometric descriptors has always interested biologists in general. However, unusual examples of form, such as abnormalities are often encountered in biomedical sciences. Despite the long history of morphometrics, the means to identify and quantify such unusual form differences remains limited.</p> <p>Methods</p> <p>A theoretical concept, called dysmorphometrics, is introduced augmenting current geometric morphometrics with a focus on identifying and modelling form abnormalities. Dysmorphometrics applies the paradigm of detecting form differences as outliers compared to an appropriate norm. To achieve this, the likelihood formulation of landmark superimpositions is extended with outlier processes explicitly introducing a latent variable coding for abnormalities. A tractable solution to this augmented superimposition problem is obtained using Expectation-Maximization. The topography of detected abnormalities is encoded in a dysmorphogram.</p> <p>Results</p> <p>We demonstrate the use of dysmorphometrics to measure abrupt changes in time, asymmetry and discordancy in a set of human faces presenting with facial abnormalities.</p> <p>Conclusion</p> <p>The results clearly illustrate the unique power to reveal unusual form differences given only normative data with clear applications in both biomedical practice & research.</p

CFD study of fluid flow changes with erosion

For the first time, a three dimensional mesh deformation algorithm is used to assess fluid flow changes with erosion. The validation case chosen is the Jet Impingement Test, which was thoroughly analysed in previous works by Hattori et al. (Kenichi Sugiyama and Harada, 2008), Gnanavelu et al. in (Gnanavelu et al., 2009, 2011), Lopez et al. in (Lopez et al., 2015) and Mackenzie et al. in (Mackenzie et al., 2015). Nguyen et al. (2014) showed the formation of a new stagnation area when the wear scar is deep enough by performing a three-dimensional scan of the wear scar after 30 min of jet impingement test. However, in the work developed here, this stagnation area was obtained solely by computational means. The procedure consisted of applying an erosion model in order to obtain a deformed geometry, which, due to the changes in the flow pattern lead to the formation of a new stagnation area. The results as well as the wear scar were compared to the results by Nguyen et al. (2014) showing the same trend. OpenFOAM⃝R was the software chosen for the implementation of the deforming mesh algorithm as well as remeshing of the computational domain after deformation. Different techniques for mesh deformation and approaches to erosion modelling are discussed and a new methodology for erosion calculation including mesh deformation is developed. This new approach is independent of the erosion modelling approach, being applicable to both Eulerian and Lagrangian based equations for erosion calculation. Its different applications such as performance decay in machinery subjected to erosion as well as modelling of natural erosion processes are discussed here

Unsupervised assessment of microarray data quality using a Gaussian mixture model

<p>Abstract</p> <p>Background</p> <p>Quality assessment of microarray data is an important and often challenging aspect of gene expression analysis. This task frequently involves the examination of a variety of summary statistics and diagnostic plots. The interpretation of these diagnostics is often subjective, and generally requires careful expert scrutiny.</p> <p>Results</p> <p>We show how an unsupervised classification technique based on the Expectation-Maximization (EM) algorithm and the naïve Bayes model can be used to automate microarray quality assessment. The method is flexible and can be easily adapted to accommodate alternate quality statistics and platforms. We evaluate our approach using Affymetrix 3' gene expression and exon arrays and compare the performance of this method to a similar supervised approach.</p> <p>Conclusion</p> <p>This research illustrates the efficacy of an unsupervised classification approach for the purpose of automated microarray data quality assessment. Since our approach requires only unannotated training data, it is easy to customize and to keep up-to-date as technology evolves. In contrast to other "black box" classification systems, this method also allows for intuitive explanations.</p

Outcomes following SARS-CoV-2 infection in patients with primary and secondary immunodeficiency in the UK

In March 2020, the United Kingdom Primary Immunodeficiency Network (UKPIN) established a registry of cases to collate the outcomes of individuals with PID and SID following SARS-CoV-2 infection and treatment. A total of 310 cases of SARS-CoV-2 infection in individuals with PID or SID have now been reported in the UK. The overall mortality within the cohort was 17.7% (n = 55/310). Individuals with CVID demonstrated an infection fatality rate (IFR) of 18.3% (n = 17/93), individuals with PID receiving IgRT had an IFR of 16.3% (n = 26/159) and individuals with SID, an IFR of 27.2% (n = 25/92). Individuals with PID and SID had higher inpatient mortality and died at a younger age than the general population. Increasing age, low pre-SARS-CoV-2 infection lymphocyte count and the presence of common co-morbidities increased the risk of mortality in PID. Access to specific COVID-19 treatments in this cohort was limited: only 22.9% (n = 33/144) of patients admitted to the hospital received dexamethasone, remdesivir, an anti-SARS-CoV-2 antibody-based therapeutic (e.g. REGN-COV2 or convalescent plasma) or tocilizumab as a monotherapy or in combination. Dexamethasone, remdesivir, and anti-SARS-CoV-2 antibody-based therapeutics appeared efficacious in PID and SID. Compared to the general population, individuals with PID or SID are at high risk of mortality following SARS-CoV-2 infection. Increasing age, low baseline lymphocyte count, and the presence of co-morbidities are additional risk factors for poor outcome in this cohort

Parsimonious Higher-Order Hidden Markov Models for Improved Array-CGH Analysis with Applications to Arabidopsis thaliana

Array-based comparative genomic hybridization (Array-CGH) is an important technology in molecular biology for the detection of DNA copy number polymorphisms between closely related genomes. Hidden Markov Models (HMMs) are popular tools for the analysis of Array-CGH data, but current methods are only based on first-order HMMs having constrained abilities to model spatial dependencies between measurements of closely adjacent chromosomal regions. Here, we develop parsimonious higher-order HMMs enabling the interpolation between a mixture model ignoring spatial dependencies and a higher-order HMM exhaustively modeling spatial dependencies. We apply parsimonious higher-order HMMs to the analysis of Array-CGH data of the accessions C24 and Col-0 of the model plant Arabidopsis thaliana. We compare these models against first-order HMMs and other existing methods using a reference of known deletions and sequence deviations. We find that parsimonious higher-order HMMs clearly improve the identification of these polymorphisms. Moreover, we perform a functional analysis of identified polymorphisms revealing novel details of genomic differences between C24 and Col-0. Additional model evaluations are done on widely considered Array-CGH data of human cell lines indicating that parsimonious HMMs are also well-suited for the analysis of non-plant specific data. All these results indicate that parsimonious higher-order HMMs are useful for Array-CGH analyses. An implementation of parsimonious higher-order HMMs is available as part of the open source Java library Jstacs (www.jstacs.de/index.php/PHHMM)