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Screening strategy modification based on personalized breast cancer risk stratification and its implementation in the national guidelines – pilot study
No full textMixed-Precision Iterative Refinement using Tensor Cores on GPUs to Accelerate Solution of Linear Systems
No full textDouble-precision floating-point arithmetic (FP64) has been the de facto standard for engineering and scientific simulations for several decades. Problem complexity and the sheer volume of data coming from various instruments and sensors motivate researchers to mix and match various approaches to optimize compute resources, including different levels of floating-point precision. In recent years, machine learning has motivated hardware support for half precision floating-point arithmetic. A primary challenge in high-performance computing is to leverage reduced precision and mixed-precision hardware. We show how the FP16/FP32 Tensor Cores on NVIDIA GPUs can be exploited to accelerate the solution of linear systems of equations Ax = b without sacrificing numerical stability. On the NVIDIA Quadro GV100 (Volta) GPU, we achieve a 4×–5× performance increase and 5× better energy efficiency versus the standard FP64 implementation while maintaining an FP64 level of numerical stability
“A CATALYST FOR ACTION”: FACTORS FOR IMPLEMENTING CLINICAL RISK PREDICTION MODELS OF INFECTION IN HOME CARE SETTINGS
No full textObjective: To outline how a clinical risk prediction model for identifying patients at risk of infection is perceived by home care nurses, and to inform how the output of the model could be integrated into clinical workflow. Materials and Methods: A qualitative study using semi-structured interviews with 50 home care nurses. Interviews explored nurses’ perceptions of clinical risk prediction models, their experiences using them in practice, and what elements are important for the implementation of a clinical risk prediction model focusing on infection. Interviews were audio-taped and transcribed, with data evaluated using thematic analysis.Results: Two themes were derived from the data; 1) Informing nursing practice, which outlined how a clinical risk prediction model could inform nurse clinical judgment and be used to modify their care plan interventions and 2) Operationalising the score, which summarized how the clinical risk prediction model could be incorporated in home care settings.Discussion: The findings indicate that home care nurses would find a clinical risk prediction model for infection useful, as long as it provided both context around the reasons why a patient was deemed to be at high risk and provided some guidance for action. Conclusion: It is important to evaluate the potential feasibility and acceptability of a clinical risk prediction model, to inform the intervention design and implementation strategy. The results of this study can provide guidance for the development of the clinical risk prediction tool as an intervention for integration in home care settings.<br/
Transition from viscous fingering to capillary fingering: application of GPU-based fully-implicit dynamic pore-network modelling
No full textImmiscible two-phase flow through porous materials exhibits different invasion patterns controlled by dynamic conditions, competition between the viscous and capillary forces and the contrast between the fluids viscosities. Two distinct invasion patterns are viscous and capillary fingering. While the first one happens under unfavorable viscosity ratios at high injection rates, the second one happens when the viscous forces are very small compared to the capillary forces. Depending on whether the invasion is under the capillary fingering or viscous fingering regime, the remaining oil saturation and the effective permeability of the fluids can significantly change. The contribution of the present work has two key aspects: a) it addresses how the remaining saturation changes at different flow rates (i.e. capillary numbers) for different unfavourable viscosity ratios in a three-dimensional system; b) it presents a new dynamic pore-network model using the fully-implicit scheme which has been enhanced by the graphic processing unit (GPU) parallel computing. Additionally, the model has been carefully validated against micromodel experiments in both time and space, which to our best knowledge has not been reported in such details in the literature. The results of the validated 3D dynamic pore-network model demonstrate that remaining saturation at the breakthrough time as a non-monotonic trend with the imposed capillary number
Sustainability or sustainable infrastructure?:Using sustainability discourse to construct a motorway.
No full textWestConnex is a 33km, A$16.8bn motorway under construction in Sydney. It is promoted by the state government as an example of excellent ‘sustainable infrastructure’. We explore the use of sustainability discourse to explain how a motorway corporation, established by a state government committed to building infrastructure that could later be privatized, engaged with an organization that redefined the notion of sustainability and then presented this definition and approach to justify their motorway construction practices as sustainable
Forest fire induces short term shifts in soil food webs with consequences for carbon cycling
No full textWe tested for fire-induced (5-6 years post fire) changes in the structure and functioning of the soil food web along a 3000 km north-south transect across European Russia, spanning all major forest types in the northern hemisphere outside the tropics. The total biomass of the detrital food web, including microbes and invertebrates, was not affected by fire. However, fire reduced the biomass of microfauna, but had no impact on mesofauna or macrofauna. Fire also reduced rates of carbon (C) mobilisation by soil biota. Our results demonstrate that fire-induced shifts in soil food webs have significant short-term effects on forest soil C cycling, but that these effects vary across forest types and geographic locations
Laser spectroscopy of neutron-rich 207;208Hg isotopes: Illuminating the kink and odd-even staggering in charge radii across the N = 126 shell closure
No full textAnabolism of Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) by Cupriavidus necator DSM 545 from Spent Coffee Grounds Oil
No full textOil extracted from spent coffee grounds (SCG) [yield 16.8 % (w/w)] was discovered to be a highly suitable carbon substrate for the biosynthesis of poly(3-hydroxybutyrate-co-3-hydroxyvalerate) [P(3HB-co-3HV)] copolymers by Cupriavidus necator DSM 545 in the absence of any traditional 3HV precursors. Cells cultivated in a 3 L bioreactor (batch) reached a total biomass concentration of 8.9 g L−1 with a P(3HB-co-3HV) (6.8 mol% 3HV) content of 89.6 % (w/w). In contrast, cells grown on sunflower oil reached a total biomass concentration of 9.4 g L−1 with a P(3HB-co-3HV) (0.2 mol% 3HV) content of 88.1 % (w/w). It is proposed that the organism could synthesize 3HV monomers from succinyl CoA, an intermediate of the tricarboxylic acid (TCA) cycle, via the succinate-propionate metabolic pathway
External validation of five scores to predict stroke-associated pneumonia and the role of selected blood biomarkers
No full textBackground and Purpose: Several clinical scoring systems as well as biomarkers have been proposed to predict Stroke-associated pneumonia (SAP). We aimed to externally and competitively validate SAP scores and hypothesized that 5 selected biomarkers would improve performance of these scores.Methods: We pooled the clinical data of two acute stroke studies with identical data assessment: STRAWINSKI and PREDICT. Biomarkers (ultrasensitive Procalcitonin; mid-regional pro-Adrenomedullin; mid-regional pro-atrionatriuretic peptide; ultrasensitive Copeptin; C-terminal pro Endothelin) were measured from hospital admission serum samples. A literature search wasperformed to identify SAP prediction scores. We then calculated multivariate regression models with the individual scores and the biomarkers. Areas under receiver-operating characteristic curves (AUROC) were used to compare discrimination of these scores and models.Results: The combined cohort consisted of 683 cases, of which 573 had available backup samples to perform the biomarker analysis. Literature search identified 9 SAP prediction scores. Our dataset enabled us to calculate 5 of these scores. The scores had AUROC of 0.543-0.651 for physiciandetermined SAP, 0.574-0.685 for probable and 0.689-0.811 for definite SAP according to Pneumonia In Stroke ConsEnSus (PISCES) group criteria. Multivariate models of the scores with biomarkers improved virtually all predictions, but mostly in the range of an AUROC delta of 0.05.Conclusion: All SAP prediction scores identified patients who would develop SAP with fair to strong capabilities, with better discrimination when stricter criteria for SAP diagnosis were applied. The selected biomarkers provided only limited added predictive value, currently not warranting addition of these markers to prediction models