Thinking strategically about assessment

Drawing upon the literature on strategy formulation in organisations, this paper argues for a focus on strategy as process. It relates this to the need to think strategically about assessment, a need engendered by resource pressures, developments in learning and the demands of external stakeholders. It is argued that in practice assessment strategies are often formed at the level of practice, but that this produces contradiction and confusion at higher levels. Such tensions cannot be managed away, but they can be reflected on and mitigated. The paper suggests a framework for the construction of assessment strategies at different levels of an institution. However, the main conclusion is that the process of constructing such strategies should be an opportunity for learning and reflection, rather than one of compliance

Long-term effectiveness of a digital therapeutic intervention for smoking cessation: a randomized controlled trial

Introduction: The present study evaluated the long-term effectiveness of Quit Genius (QG), an extended digital smoking cessation intervention. Methods: Participants were adult smokers (N=556) recruited between January and November of 2019 via social media and referrals from primary care practices who were given nicotine replacement therapy and randomly assigned to Quit Genius (QG) (n=277), a cognitive behavioral therapy (CBT) based digital intervention or Very Brief Advice (VBA) (n=279), a face-to-face control intervention. Primary analyses (N=530), by intention-to-treat, compared QG and VBA on biochemically verified continuous 7-day abstinence at 4, 26, and 52 weeks post-quit date. Secondary outcomes included sustained abstinence, quit attempts, self-efficacy and mental well-being. Results: Seven-day point prevalence abstinence from weeks 4 through 52 ranged from 27% to nearly 45% among those who received QG, and from 13% to 29% for those in VBA. Continuous 7-day abstinence at 26 and 52 weeks occurred in 27.2% and 22.6% of QG participants, respectively, relative to 16.6% and 13.2% of VBA participants; QG participants were more likely to remain abstinent than those in VBA (Relative Risk [RR]= 1.71, 95% CI 1.17-2.50; p=0.005). Conclusions: This study provides evidence for the long-term effectiveness of an extended digital therapeutic intervention. Implications The long-term effectiveness of digital smoking cessation interventions has not been well-studied. This study established the long-term effectiveness of an extended CBT-based intervention; results may inform implementation of scalable, cost-effective approaches to smoking cessation in the health system

Amenability of groups and GG-sets

This text surveys classical and recent results in the field of amenability of groups, from a combinatorial standpoint. It has served as the support of courses at the University of G\"ottingen and the \'Ecole Normale Sup\'erieure. The goals of the text are (1) to be as self-contained as possible, so as to serve as a good introduction for newcomers to the field; (2) to stress the use of combinatorial tools, in collaboration with functional analysis, probability etc., with discrete groups in focus; (3) to consider from the beginning the more general notion of amenable actions; (4) to describe recent classes of examples, and in particular groups acting on Cantor sets and topological full groups

Generation of Large-Scale Vorticity in a Homogeneous Turbulence with a Mean Velocity Shear

An effect of a mean velocity shear on a turbulence and on the effective force which is determined by the gradient of Reynolds stresses is studied. Generation of a mean vorticity in a homogeneous incompressible turbulent flow with an imposed mean velocity shear due to an excitation of a large-scale instability is found. The instability is caused by a combined effect of the large-scale shear motions (''skew-induced" deflection of equilibrium mean vorticity) and ''Reynolds stress-induced" generation of perturbations of mean vorticity. Spatial characteristics, such as the minimum size of the growing perturbations and the size of perturbations with the maximum growth rate, are determined. This instability and the dynamics of the mean vorticity are associated with the Prandtl's turbulent secondary flows. This instability is similar to the mean-field magnetic dynamo instability. Astrophysical applications of the obtained results are discussed.Comment: 8 pages, 3 figures, REVTEX4, submitted to Phys. Rev.

Patterns of subnet usage reveal distinct scales of regulation in the transcriptional regulatory network of Escherichia coli

The set of regulatory interactions between genes, mediated by transcription factors, forms a species' transcriptional regulatory network (TRN). By comparing this network with measured gene expression data one can identify functional properties of the TRN and gain general insight into transcriptional control. We define the subnet of a node as the subgraph consisting of all nodes topologically downstream of the node, including itself. Using a large set of microarray expression data of the bacterium Escherichia coli, we find that the gene expression in different subnets exhibits a structured pattern in response to environmental changes and genotypic mutation. Subnets with less changes in their expression pattern have a higher fraction of feed-forward loop motifs and a lower fraction of small RNA targets within them. Our study implies that the TRN consists of several scales of regulatory organization: 1) subnets with more varying gene expression controlled by both transcription factors and post-transcriptional RNA regulation, and 2) subnets with less varying gene expression having more feed-forward loops and less post-transcriptional RNA regulation.Comment: 14 pages, 8 figures, to be published in PLoS Computational Biolog

Innovation in assessment: building student confidence in preparation for unfamiliar assessment methods

Innovative assessment methods in which students are active participants promote deeper learning. A group debate and a webfolio were implemented as methods of assessment in the 2015 undergraduate midwifery curriculum, with the assessment tools being evaluated by students. Thematic analysis of the evaluations showed students enjoyed undertaking innovative methods of assessment, they developed confidence and engaged meaningfully with the content to be assessed. Students also commented they developed multiple skills required for future professional practice as a midwife. Thorough preparation of students to undertake an innovative method of assessment however is vital in fostering student confidence

Phase Transitions on Nonamenable Graphs

We survey known results about phase transitions in various models of statistical physics when the underlying space is a nonamenable graph. Most attention is devoted to transitive graphs and trees

FLORA: a novel method to predict protein function from structure in diverse superfamilies

Predicting protein function from structure remains an active area of interest, particularly for the structural genomics initiatives where a substantial number of structures are initially solved with little or no functional characterisation. Although global structure comparison methods can be used to transfer functional annotations, the relationship between fold and function is complex, particularly in functionally diverse superfamilies that have evolved through different secondary structure embellishments to a common structural core. The majority of prediction algorithms employ local templates built on known or predicted functional residues. Here, we present a novel method (FLORA) that automatically generates structural motifs associated with different functional sub-families (FSGs) within functionally diverse domain superfamilies. Templates are created purely on the basis of their specificity for a given FSG, and the method makes no prior prediction of functional sites, nor assumes specific physico-chemical properties of residues. FLORA is able to accurately discriminate between homologous domains with different functions and substantially outperforms (a 2–3 fold increase in coverage at low error rates) popular structure comparison methods and a leading function prediction method. We benchmark FLORA on a large data set of enzyme superfamilies from all three major protein classes (α, β, αβ) and demonstrate the functional relevance of the motifs it identifies. We also provide novel predictions of enzymatic activity for a large number of structures solved by the Protein Structure Initiative. Overall, we show that FLORA is able to effectively detect functionally similar protein domain structures by purely using patterns of structural conservation of all residues