A Dimension-Adaptive Multi-Index Monte Carlo Method Applied to a Model of a Heat Exchanger

We present an adaptive version of the Multi-Index Monte Carlo method, introduced by Haji-Ali, Nobile and Tempone (2016), for simulating PDEs with coefficients that are random fields. A classical technique for sampling from these random fields is the Karhunen-Lo\`eve expansion. Our adaptive algorithm is based on the adaptive algorithm used in sparse grid cubature as introduced by Gerstner and Griebel (2003), and automatically chooses the number of terms needed in this expansion, as well as the required spatial discretizations of the PDE model. We apply the method to a simplified model of a heat exchanger with random insulator material, where the stochastic characteristics are modeled as a lognormal random field, and we show consistent computational savings

The Mock Trial: Revisiting a Valuable Training Strategy

The number of forensic psychiatrists has increased dramatically over the past 40 years. With this welcome development has also come some challenges for educating future generations of practitioners, specifically the greater demands on training programs and the need to divide practice hours among a larger pool of individuals. Junior trainees and experienced practitioners alike can benefit by supplementing work experience with welldesigned, theoretically informed simulations. In this article, the theoretical perspectives of simulation, deliberate practice, and experiential education are discussed and linked to the design of mock trials, a form of simulation used to teach the essential skill of expert testimony. My argument is that, by explicitly linking the mock trial to learning theory, its efficacy and range of application can be increased. I provide recommendations for effective design and application

On supersymmetric interfaces for string theory

We construct the world-sheet interface which preserves space-time supersymmetry in type II superstring theories in the Green-Schwarz formalism. This is an analog of the conformal interface in two-dimensional conformal field theory. We show that a class of the supersymmetric interfaces generates T-dualities of type II theories, and that these interfaces have a geometrical interpretation in the doubled target space. We compute the partition function with a pair of the supersymmetric interfaces inserted, from which we read off the spectrum of the modes coupled to the interfaces and the Casimir energy between them. We also derive the transformation rules under which a set of D-branes is transformed to another by the interface.Comment: 1+23 pages, 1 figure; (v2) added comments, made changes in presentatio

Application of quasi-Monte Carlo methods to PDEs with random coefficients -- an overview and tutorial

This article provides a high-level overview of some recent works on the application of quasi-Monte Carlo (QMC) methods to PDEs with random coefficients. It is based on an in-depth survey of a similar title by the same authors, with an accompanying software package which is also briefly discussed here. Embedded in this article is a step-by-step tutorial of the required analysis for the setting known as the uniform case with first order QMC rules. The aim of this article is to provide an easy entry point for QMC experts wanting to start research in this direction and for PDE analysts and practitioners wanting to tap into contemporary QMC theory and methods.Comment: arXiv admin note: text overlap with arXiv:1606.0661

Hot new directions for quasi-Monte Carlo research in step with applications

This article provides an overview of some interfaces between the theory of quasi-Monte Carlo (QMC) methods and applications. We summarize three QMC theoretical settings: first order QMC methods in the unit cube $[0,1]^s$ and in $\mathbb{R}^s$, and higher order QMC methods in the unit cube. One important feature is that their error bounds can be independent of the dimension $s$ under appropriate conditions on the function spaces. Another important feature is that good parameters for these QMC methods can be obtained by fast efficient algorithms even when $s$ is large. We outline three different applications and explain how they can tap into the different QMC theory. We also discuss three cost saving strategies that can be combined with QMC in these applications. Many of these recent QMC theory and methods are developed not in isolation, but in close connection with applications

A powerful intervention: general practitioners' use of sickness certification in depression

<b>Background</b> Depression is frequently cited as the reason for sickness absence, and it is estimated that sickness certificates are issued in one third of consultations for depression. Previous research has considered GP views of sickness certification but not specifically in relation to depression. This study aimed to explore GPs views of sickness certification in relation to depression.<p></p> <b>Methods</b> A purposive sample of GP practices across Scotland was selected to reflect variations in levels of incapacity claimants and antidepressant prescribing. Qualitative interviews were carried out between 2008 and 2009.<p></p> <b>Results</b> A total of 30 GPs were interviewed. A number of common themes emerged including the perceived importance of GP advocacy on behalf of their patients, the tensions between stakeholders involved in the sickness certification system, the need to respond flexibly to patients who present with depression and the therapeutic nature of time away from work as well as the benefits of work. GPs reported that most patients with depression returned to work after a short period of absence and that it was often difficult to predict which patients would struggle to return to work.<p></p> <b>Conclusions</b> GPs reported that dealing with sickness certification and depression presents distinct challenges. Sickness certificates are often viewed as powerful interventions, the effectiveness of time away from work for those with depression should be subject to robust enquiry

Probable delirium is a presenting symptom of COVID-19 in frail, older adults: a cohort study of 322 hospitalised and 535 community-based older adults

BACKGROUND: Frailty, increased vulnerability to physiological stressors, is associated with adverse outcomes. COVID-19 exhibits a more severe disease course in older, comorbid adults. Awareness of atypical presentations is critical to facilitate early identification. OBJECTIVE: To assess how frailty affects presenting COVID-19 symptoms in older adults. DESIGN: Observational cohort study of hospitalised older patients and self-report data for community-based older adults. SETTINGS: Admissions to St Thomas’ Hospital, London with laboratory-confirmed COVID-19. Community-based data for older adults using the COVID Symptom Study mobile application. SUBJECTS: Hospital cohort: patients aged 65 and over (n = 322); unscheduled hospital admission between 1 March 2020 and 5 May 2020; COVID-19 confirmed by RT-PCR of nasopharyngeal swab. Community-based cohort: participants aged 65 and over enrolled in the COVID Symptom Study (n = 535); reported test-positive for COVID-19 from 24 March (application launch) to 8 May 2020. METHODS: Multivariable logistic regression analysis performed on age-matched samples from hospital and community-based cohorts to ascertain association of frailty with symptoms of confirmed COVID-19. RESULTS: Hospital cohort: significantly higher prevalence of probable delirium in the frail sample, with no difference in fever or cough. Community-based cohort: significantly higher prevalence of possible delirium in frailer, older adults and fatigue and shortness of breath. CONCLUSIONS: This is the first study demonstrating higher prevalence of probable delirium as a COVID-19 symptom in older adults with frailty compared to other older adults. This emphasises need for systematic frailty assessment and screening for delirium in acutely ill older patients in hospital and community settings. Clinicians should suspect COVID-19 in frail adults with delirium

Cross-species gene expression analysis of species specific differences in the preclinical assessment of pharmaceutical compounds

Animals are frequently used as model systems for determination of safety and efficacy in pharmaceutical research and development. However, significant quantitative and qualitative differences exist between humans and the animal models used in research. This is as a result of genetic variation between human and the laboratory animal. Therefore the development of a system that would allow the assessment of all molecular differences between species after drug exposure would have a significant impact on drug evaluation for toxicity and efficacy. Here we describe a cross-species microarray methodology that identifies and selects orthologous probes after cross-species sequence comparison to develop an orthologous cross-species gene expression analysis tool. The assumptions made by the use of this orthologous gene expression strategy for cross-species extrapolation is that; conserved changes in gene expression equate to conserved pharmacodynamic endpoints. This assumption is supported by the fact that evolution and selection have maintained the structure and function of many biochemical pathways over time, resulting in the conservation of many important processes. We demonstrate this cross-species methodology by investigating species specific differences of the peroxisome proliferatoractivator receptor (PPAR) a response in rat and human