Bayesian generalised ensemble Markov chain Monte Carlo

Bayesian generalised ensemble (BayesGE) is a new method that addresses two major drawbacks of standard Markov chain Monte Carlo algorithms for inference in high-dimensional probability models: inapplicability to estimate the partition function, and poor mixing properties. BayesGE uses a Bayesian approach to iteratively update the belief about the density of states (distribution of the log likelihood under the prior) for the model, with the dual purpose of enhancing the sampling efficiency and make the estimation of the partition function tractable. We benchmark BayesGE on Ising and Potts systems and show that it compares favourably to existing state-of-the-art methods.JF acknowledge funding from the Danish Council for Independent Research | Natural Sciences. ZG acknowledge funding from EPSRC EP/I036575/1 and Google.This is the author accepted manuscript. It is currently under an indefinite embargo pending publication by Microtome Publishing

Towards 3D structure prediction of large RNA molecules: an integer programming framework to insert local 3D motifs in RNA secondary structure

Motivation: The prediction of RNA 3D structures from its sequence only is a milestone to RNA function analysis and prediction. In recent years, many methods addressed this challenge, ranging from cycle decomposition and fragment assembly to molecular dynamics simulations. However, their predictions remain fragile and limited to small RNAs. To expand the range and accuracy of these techniques, we need to develop algorithms that will enable to use all the structural information available. In particular, the energetic contribution of secondary structure interactions is now well documented, but the quantification of non-canonical interactions—those shaping the tertiary structure—is poorly understood. Nonetheless, even if a complete RNA tertiary structure energy model is currently unavailable, we now have catalogues of local 3D structural motifs including non-canonical base pairings. A practical objective is thus to develop techniques enabling us to use this knowledge for robust RNA tertiary structure predictors

Dealing with the difficult student in emergency medicine

Dealing with a student who is perceived as difficult to work with or teach is inevitable in any academic physician's career. This paper will outline the basic categories of these difficulties pertinent to Emergency Medicine rotations in order to facilitate appropriate identification of problems. Strategies for evaluation and reporting of the difficult student are presented. Remediation, based on the type of difficulty, is addressed. Timeliness of reporting, evaluation, and feedback are invaluable to allow for appropriate assessment of the outcome of the remediation plan

Potentials of Mean Force for Protein Structure Prediction Vindicated, Formalized and Generalized

Understanding protein structure is of crucial importance in science, medicine and biotechnology. For about two decades, knowledge based potentials based on pairwise distances -- so-called "potentials of mean force" (PMFs) -- have been center stage in the prediction and design of protein structure and the simulation of protein folding. However, the validity, scope and limitations of these potentials are still vigorously debated and disputed, and the optimal choice of the reference state -- a necessary component of these potentials -- is an unsolved problem. PMFs are loosely justified by analogy to the reversible work theorem in statistical physics, or by a statistical argument based on a likelihood function. Both justifications are insightful but leave many questions unanswered. Here, we show for the first time that PMFs can be seen as approximations to quantities that do have a rigorous probabilistic justification: they naturally arise when probability distributions over different features of proteins need to be combined. We call these quantities reference ratio distributions deriving from the application of the reference ratio method. This new view is not only of theoretical relevance, but leads to many insights that are of direct practical use: the reference state is uniquely defined and does not require external physical insights; the approach can be generalized beyond pairwise distances to arbitrary features of protein structure; and it becomes clear for which purposes the use of these quantities is justified. We illustrate these insights with two applications, involving the radius of gyration and hydrogen bonding. In the latter case, we also show how the reference ratio method can be iteratively applied to sculpt an energy funnel. Our results considerably increase the understanding and scope of energy functions derived from known biomolecular structures

Profiling strugglers in a graduate-entry medicine course at Nottingham: a retrospective case study

Background 10-15% of students struggle at some point in their medicine course. Risk factors include weaker academic qualifications, male gender, mental illness, UK ethnic minority status, and poor study skills. Recent research on an undergraduate medicine course provided a toolkit to aid early identification of students likely to struggle, who can be targeted by established support and study interventions. The present study sought to extend this work by investigating the number and characteristics of strugglers on a graduate-entry medicine (GEM) programme. Methods A retrospective study of four GEM entry cohorts (2003–6) was carried out. All students who had demonstrated unsatisfactory progress or left prematurely were included. Any information about academic, administrative, personal, or social difficulties, were extracted from their course progress files into a customised database and examined. Results 362 students were admitted to the course, and 53 (14.6%) were identified for the study, of whom 15 (4.1%) did not complete the course. Students in the study group differed from the others in having a higher proportion of 2ii first degrees, and scoring less well on GAMSAT, an aptitude test used for admission. Within the study group, it proved possible to categorise students into the same groups previously reported (struggler throughout, pre-clinical struggler, clinical struggler, health-related struggler, borderline struggler) and to identify the majority using a number of flags for early difficulties. These flags included: missed attendance, unsatisfactory attitude or behaviour, health problems, social/family problems, failure to complete immunity status checks, and attendance at academic progress committee. Conclusions Problems encountered in a graduate-entry medicine course were comparable to those reported in a corresponding undergraduate programme. A toolkit of academic and non-academic flags of difficulty can be used for early identification of many who will struggle, and could be used to target appropriate support and interventions

Medical students' personal experience of high-stakes failure:case studies using interpretative phenomenological analysis

Abstract (provisional): Background Failing a high-stakes assessment at medical school is a major event for those who go through the experience. Students who fail at medical school may be more likely to struggle in professional practice, therefore helping individuals overcome problems and respond appropriately is important. There is little understanding about what factors influence how individuals experience failure or make sense of the failing experience in remediation. The aim of this study was to investigate the complexity surrounding the failure experience from the student’s perspective using interpretative phenomenological analysis (IPA). Methods The accounts of 3 medical students who had failed final re-sit exams, were subjected to in-depth analysis using IPA methodology. IPA was used to analyse each transcript case-by-case allowing the researcher to make sense of the participant’s subjective world. The analysis process allowed the complexity surrounding the failure to be highlighted, alongside a narrative describing how students made sense of the experience. Results The circumstances surrounding students as they approached assessment and experienced failure at finals were a complex interaction between academic problems, personal problems (specifically finance and relationships), strained relationships with friends, family or faculty, and various mental health problems. Each student experienced multi-dimensional issues, each with their own individual combination of problems, but experienced remediation as a one-dimensional intervention with focus only on improving performance in written exams. What these students needed to be included was help with clinical skills, plus social and emotional support. Fear of termination of the their course was a barrier to open communication with staff. Conclusions These students’ experience of failure was complex. The experience of remediation is influenced by the way in which students make sense of failing. Generic remediation programmes may fail to meet the needs of students for whom personal, social and mental health issues are a part of the picture

Early identification of first-year students at risk of dropping out of high-school entry medical school: the usefulness of teachers' ratings of class participation

Dropping out from undergraduate medical education is costly for students, medical schools, and society in general. Therefore, the early identification of potential dropout students is important. The contribution of personal features to dropout rates has merited exploration. However, there is a paucity of research on aspects of student experience that may lead to dropping out. In this study, underpinned by theoretical models of student commitment, involvement, and engagement, we explored the hypothesis of using inferior participation as an indicator of a higher probability of dropping out in year 1. Class participation was calculated as an aggregate score based on teachers' daily observations in class. The study used a longitudinal dataset of six cohorts of high-school entry students (N = 709, 67% females) in one medical school with an annual intake of 120 students. The findings confirmed the initial hypothesis and showed that lower scores of class participation in year 1 added predictive ability to pre-entry characteristics (Pseudo-R2 raised from 0.22 to 0.28). Even though the inclusion of course failure in year 1 resulted in higher explanatory power than participation in class (Pseudo-R2 raised from 0.28 to 0.63), ratings of class participation may be advantageous to anticipate dropout identification, as those can be collected prior to course failure. The implications for practice are that teachers' ratings of class participation can play a role in indicating medical students who may eventually drop out. We conclude that the scores of class participation can contribute to flagging systems for the early detection of student dropouts.(undefined)info:eu-repo/semantics/acceptedVersio

Joining the dots: Conditional pass and programmatic assessment enhances recognition of problems with professionalism and factors hampering student progress

<p>Abstract</p> <p>Background</p> <p>Programmatic assessment that looks across a whole year may contribute to better decisions compared with those made from isolated assessments alone. The aim of this study is to describe and evaluate a programmatic system to handle student assessment results that is aligned not only with learning and remediation, but also with defensibility. The key components are standards based assessments, use of "Conditional Pass", and regular progress meetings.</p> <p>Methods</p> <p>The new assessment system is described. The evaluation is based on years 4-6 of a 6-year medical course. The types of concerns staff had about students were clustered into themes alongside any interventions and outcomes for the students concerned. The likelihoods of passing the year according to type of problem were compared before and after phasing in of the new assessment system.</p> <p>Results</p> <p>The new system was phased in over four years. In the fourth year of implementation 701 students had 3539 assessment results, of which 4.1% were Conditional Pass. More in-depth analysis for 1516 results available from 447 students revealed the odds ratio (95% confidence intervals) for failure was highest for students with problems identified in more than one part of the course (18.8 (7.7-46.2) p < 0.0001) or with problems with professionalism (17.2 (9.1-33.3) p < 0.0001). The odds ratio for failure was lowest for problems with assignments (0.7 (0.1-5.2) NS). Compared with the previous system, more students failed the year under the new system on the basis of performance during the year (20 or 4.5% compared with four or 1.1% under the previous system (p < 0.01)).</p> <p>Conclusions</p> <p>The new system detects more students in difficulty and has resulted in less "failure to fail". The requirement to state conditions required to pass has contributed to a paper trail that should improve defensibility. Most importantly it has helped detect and act on some of the more difficult areas to assess such as professionalism.</p

Outlook for inverse design in nanophotonics

Recent advancements in computational inverse design have begun to reshape the landscape of structures and techniques available to nanophotonics. Here, we outline a cross section of key developments at the intersection of these two fields: moving from a recap of foundational results to motivation of emerging applications in nonlinear, topological, near-field and on-chip optics.Comment: 13 pages, 6 figure