The V-model of service quality: An African case study

This paper aims to introduce and demonstrate a new model for service quality that separates out the measurement of service quality in ways grounded in psychological theory and methodological symmetry.A review of experience in service quality management suggests that new approaches are needed. By seeking a way of managing service at different levels, with symmetry between data collection and data analysis, a model is presented that has more potential applicability and flexibility than is found in traditional models

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Skidmore, Owings & Merrill LLP : architecture and urbanism 1995-2000

263 hlm., bibl., ill., indexs, 34 c

The master architect series IV : Dominique Perrault

236hlm.;bib.;ill

SURROGATE MODEL OPTIMIZATION OF A ‘MICRO CORE’ PWR FUEL ASSEMBLY ARRANGEMENT USING DEEP LEARNING MODELS

This paper investigates the applicability of surrogate model optimization (SMO) using deep learning regression models to automatically embed knowledge about the objective function into the optimization process. This paper demonstrates two deep learning SMO methods for calculating simple neutronics parameters. Using these models, SMO returns results comparable with those from the early stages of direct iterative optimization. However, for this study, the cost of creating the training set outweighs the benefits of the surrogate models

QUANTUM ANNEALING OPTIMIZATION OF A HEURISTIC SURROGATE MODEL FOR PWR FUEL LOADING

An efficient fuel arrangement must be generated by PWR operators every 6–18 months. This complex problem has been extensively researched with two broad approaches, heuristic and stochastic methods, becoming accepted. This initial study qualitatively introduces the concept of encoding full-core PWR fuel loading patterns in a form suitable for quantum annealing. The concepts of adiabatic quantum computers and quantum annealing are introduced, and a surrogate model encoding of a set of heuristics for loading pattern design produced in a form suitable for use in present-day quantum annealers. The simulated results show significant similarity to benchmark loading patterns

QUANTUM ANNEALING OPTIMIZATION OF A HEURISTIC SURROGATE MODEL FOR PWR FUEL LOADING

An efficient fuel arrangement must be generated by PWR operators every 6–18 months. This complex problem has been extensively researched with two broad approaches, heuristic and stochastic methods, becoming accepted. This initial study qualitatively introduces the concept of encoding full-core PWR fuel loading patterns in a form suitable for quantum annealing. The concepts of adiabatic quantum computers and quantum annealing are introduced, and a surrogate model encoding of a set of heuristics for loading pattern design produced in a form suitable for use in present-day quantum annealers. The simulated results show significant similarity to benchmark loading patterns

Transport use, health and health inequalities: The impact of measures to reduce the spread of COVID-19

This paper looks at how transport use changed in Scotland between 23 March 2020 (the start of lockdown) and 6 September 2020 (phase 3 of eased restrictions). It looks at how these changes could affect health and health inequalities and makes recommendations for future action