Mentoring student teachers; a vulnerable workplace learning practice

Purpose – The purpose of this paper is to develop an understanding of mentoring as a workplace process. The mentees are post-graduate student teachers hosted in placement schools. The research aims to explore the experiences of key participants in a policy context where the role and scale of school-based teacher training is expanding rapidly. Design/methodology/approach – This is an interpretative case study of mentoring practices assigned to a secondary level initial teacher training partnership, with the mentors being subject teachers working in school departments which host post-graduate student teachers. The case study was investigated over two years and included focus groups, interviews, questionnaires and content analysis. Participants were student teachers, their mentors and both school-based and university-based tutors. Findings – Positive experiences of mentoring are not universal. Mentoring interacts with the required processes of monitoring and reporting and in some cases the power structures associated with these processes conflict with the less performative aspects. However, when mentors are offered evidence of student teachers’ perceptions and theoretical constructs of mentoring as practice they can start to recognise that it can be enhanced. Practical implications- The quality of mentoring in initial teacher education will take on even greater significance in jurisdictions, such as England, where the role of workplace learning is strengthened as a result of changes of government policy. Originality/value – The outcomes of this study will be relevant to policy makers, school-based mentors and system leaders for teacher education – whether school or university based

Implementing Enquiry and Project-based Learning - Revolution or Evolution?

David Leat, Rachel Lofthouse and Ulrike Thomas argue for a more creative perspective on achievement, based on enquiry-based approaches to children's learning. They explore the concept of 'dominant discourse' in education and the need for this to shift from traditional teaching to an emphasis on student questioning and curiosity which lead to "stunning". rather than pre-specified, learning outcomes

The changing immunology of organ transplantation

The engrafted organ becomes a chimera as the recipient's leukocytes station themselves in the transplant. Remarkably, the recipient becomes chimeric as well, in a reverse migration involving immune cells from the graft. Interactions between donor and recipient cells are tolerogenic-a process with implications for the goal of graft acceptance with minimal immunosuppression

MultiBUGS: A Parallel Implementation of the BUGS Modeling Framework for Faster Bayesian Inference

MultiBUGS is a new version of the general-purpose Bayesian modeling software BUGS that implements a generic algorithm for parallelizing Markov chain Monte Carlo (MCMC) algorithms to speed up posterior inference of Bayesian models. The algorithm parallelizes evaluation of the product-form likelihoods formed when a parameter has many children in the directed acyclic graph (DAG) representation; and parallelizes sampling of conditionally-independent sets of parameters. A heuristic algorithm is used to decide which approach to use for each parameter and to apportion computation across computational cores. This enables MultiBUGS to automatically parallelize the broad range of statistical models that can be fitted using BUGS-language software, making the dramatic speed-ups of modern multi-core computing accessible to applied statisticians, without requiring any experience of parallel programming. We demonstrate the use of MultiBUGS on simulated data designed to mimic a hierarchical e-health linked-data study of methadone prescriptions including 425,112 observations and 20,426 random effects. Posterior inference for the e-health model takes several hours in existing software, but MultiBUGS can perform inference in only 28 minutes using 48 computational core

Sea Turtles in the Cancer Risk Landscape: A Global Meta-Analysis of Fibropapillomatosis Prevalence and Associated Risk Factors.

Several cancer risk factors (exposure to ultraviolet-B, pollution, toxins and pathogens) have been identified for wildlife, to form a "cancer risk landscape." However, information remains limited on how the spatiotemporal variability of these factors impacts the prevalence of cancer in wildlife. Here, we evaluated the cancer risk landscape at 49 foraging sites of the globally distributed green turtle (Chelonia mydas), a species affected by fibropapillomatosis, by integrating data from a global meta-analysis of 31 publications (1994-2019). Evaluated risk factors included ultraviolet light exposure, eutrophication, toxic phytoplanktonic blooms, sea surface temperature, and the presence of mechanical vectors (parasites and symbiotic species). Prevalence was highest in areas where nutrient concentrations facilitated the emergence of toxic phytoplankton blooms. In contrast, ultraviolet light exposure and the presence of parasitic and/or symbiotic species did not appear to impact disease prevalence. Our results indicate that, to counter outbreaks of fibropapillomatosis, management actions that reduce eutrophication in foraging areas should be implemented

Residue contacts predicted by evolutionary covariance extend the application of ab initio molecular replacement to larger and more challenging protein folds

For many protein families, the deluge of new sequence information together with new statistical protocols now allow the accurate prediction of contacting residues from sequence information alone. This offers the possibility of more accurate ab initio (non-homology-based) structure prediction. Such models can be used in structure solution by molecular replacement (MR) where the target fold is novel or is only distantly related to known structures. Here, AMPLE, an MR pipeline that assembles search-model ensembles from ab initio structure predictions (`decoys'), is employed to assess the value of contact-assisted ab initio models to the crystallographer. It is demonstrated that evolutionary covariance-derived residue–residue contact predictions improve the quality of ab initio models and, consequently, the success rate of MR using search models derived from them. For targets containing β-structure, decoy quality and MR performance were further improved by the use of a β-strand contact-filtering protocol. Such contact-guided decoys achieved 14 structure solutions from 21 attempted protein targets, compared with nine for simple Rosetta decoys. Previously encountered limitations were superseded in two key respects. Firstly, much larger targets of up to 221 residues in length were solved, which is far larger than the previously benchmarked threshold of 120 residues. Secondly, contact-guided decoys significantly improved success with β-sheet-rich proteins. Overall, the improved performance of contact-guided decoys suggests that MR is now applicable to a significantly wider range of protein targets than were previously tractable, and points to a direct benefit to structural biology from the recent remarkable advances in sequencing

A SAURON study of dwarf elliptical galaxies in the Virgo Cluster: kinematics and stellar populations

Dwarf elliptical galaxies (dEs) are the most common galaxy type in nearby galaxy clusters; even so, many of their basic properties have yet to be quantified. Here we present the results of our study of 4 Virgo dwarf ellipticals obtained with the SAURON integral field unit on the William Herschel Telescope (La Palma, Spain). While traditional long-slit observations are likely to miss more complicated kinematic features, with SAURON we are able to study both kinematics and stellar populations in two dimensions, obtaining a much more detailed view of the mass distribution and star formation histories. What is visible even in such a small sample is that dEs are not a uniform group, not only morphologically, but also as far as their kinematic and stellar population properties are concerned. We find the presence of substructures, varying degrees of flattening and of rotation, as well as differences in age and metallicity gradients. We confirm that two of our galaxies are significantly flattened, yet non-rotating objects, which makes them likely triaxial systems. The comparison between the dwarf and the giant groups shows that dEs could be a low-mass extension of Es in the sense that they do seem to follow the same trends with mass. However, dEs as progenitors of Es seem less likely as we have seen that dEs have much lower abundance ratios.Comment: 8 pages, 6 figures; to appear in the proceedings of the JENAM 2010 Symposium on Dwarf Galaxies (Lisbon, September 9-10, 2010); minor edits and references adde

Growth description for vessel wall adaptation: a thick-walled mixture model of abdominal aortic aneurysm evolution

(1) Background: Vascular tissue seems to adapt towards stable homeostatic mechanical conditions, however, failure of reaching homeostasis may result in pathologies. Current vascular tissue adaptation models use many ad hoc assumptions, the implications of which are far from being fully understood; (2) Methods: The present study investigates the plausibility of different growth kinematics in modeling Abdominal Aortic Aneurysm (AAA) evolution in time. A structurally motivated constitutive description for the vessel wall is coupled to multi-constituent tissue growth descriptions; Constituent deposition preserved either the constituent’s density or its volume, and Isotropic Volume Growth (IVG), in-Plane Volume Growth (PVG), in-Thickness Volume Growth (TVG) and No Volume Growth (NVG) describe the kinematics of the growing vessel wall. The sensitivity of key modeling parameters is explored, and predictions are assessed for their plausibility; (3) Results: AAA development based on TVG and NVG kinematics provided not only quantitatively, but also qualitatively different results compared to IVG and PVG kinematics. Specifically, for IVG and PVG kinematics, increasing collagen mass production accelerated AAA expansion which seems counterintuitive. In addition, TVG and NVG kinematics showed less sensitivity to the initial constituent volume fractions, than predictions based on IVG and PVG; (4) Conclusions: The choice of tissue growth kinematics is of crucial importance when modeling AAA growth. Much more interdisciplinary experimental work is required to develop and validate vascular tissue adaption models, before such models can be of any practical use