Scaling-up Early Learning in Ethiopia: Exploring the Potential of O-Class

SDG Target 4.2 identifies ‘pre-primary education’ as a strategy to strengthen school readiness and contribute to the quality and outcomes of education, which is supported by the powerful evidence from evaluation research. The challenge faced by many countries is to deliver the proven potential of well-planned, quality programmes to scale. This working paper summarises Ethiopia’s growing commitment to pre-primary education and reports recent Young Lives engagement with the Ministry of Education in Ethiopia and other partners to support scale-up. Ethiopia’s most recent ambitious targets for early learning have been set out in the Fifth Education Sector Development Programme (ESDP V 2015), with pre-primary classes (known as O-Class) within primary schools being seen as the most rapid route to scale-up. The paper reports on the progress and the challenges in delivering ambitious targets. We report key findings from exploratory fieldwork on two key themes, namely the response of Regional Education Bureaus in planning, financing, management and ensuring human capacity for scale-up; and the potential of Ethiopia’s Colleges of Teacher Education to supply sufficient trained teachers to work with young children, especially in the rapidly expanding O- Classes. The final section draws on parallel experiences of other countries, notably Grade R in South Africa, and reports on six key challenges for scale-up; equity; age-appropriateness; cross- sectoral coordination; capacity building; and research and evidence. Other key challenges go beyond the scope of this working paper, notably the models for governance and financing that can deliver quality early education for all. While Ethiopia’s initiative to scale-up O-Class is a welcome indicator of policy commitment to SDG Target 4.2, we conclude that there is a risk that low quality pre-primary programmes will not deliver on the potential of early childhood education and that children (especially poor children) will be the losers

Using a Medical Thesaurus to Predict Query Difficulty

International audienceEstimating query performance is the task of predicting the quality of results returned by a search engine in response to a query. In this paper, we focus on pre-retrieval prediction methods for the medical domain. We propose a novel predictor that exploits a thesaurus to as- certain how difficult queries are. In our experiments, we show that our predictor outperforms the state-of-the-art methods that do not use a thesaurus

Dexmedetomidine improves success of paediatric MRI sedation

OBJECTIVE: To improve success rates of children requiring sedation for MRI. METHODS: Audits of sedation success for children attending planned MRI using three different approaches: (1) National Institute for Health and Care Excellence (NICE) guidance (chloral hydrate if <15 kg and oral midazolam if ≥15 kg), (2) Chloral hydrate for all patients, (3) Chloral hydrate±intranasal dexmedetomidine if <15 kg and intranasal dexmedetomidine alone if ≥15 kg. RESULTS: 74 patients had 85 MRI scan attempts. Overall success rates were significantly higher when using intranasal dexmedetomidine compared with following NICE guidance (81% vs 52% p=0.017). Dexmedetomidine performed better than oral midazolam for the same indication (76% vs 33% p=0.026). The side effect profile for dexmedetomidine was as reported in larger studies. CONCLUSIONS: Intranasal dexmedetomidine is an effective alternative to oral midazolam for sedation for MRI and as a rescue medication where chloral hydrate has been ineffective

Conventional versus automated measurement of blood pressure in primary care patients with systolic hypertension: randomised parallel design controlled trial

Objective To compare the quality and accuracy of manual office blood pressure and automated office blood pressure using the awake ambulatory blood pressure as a gold standard

An effective mesh strategy for CFD modelling of polymer electrolyte membrane fuel cells

Computational fluid dynamics (CFD) is a major tool in PEM fuel cell research. Typical three-dimensional PEM fuel cell models involve more than 106 mesh elements. This makes the computation very intense and necessitates a methodology to mesh the computational domain that can keep the number of elements to a minimum while maintaining good accuracy. In this study, the effect of computational mesh in each direction on the accuracy of the solution is investigated in a systematic way. It is found that the mesh in different directions has a different degree of influence on the solution suggesting that the mesh in one direction can be coarser than the other. The proposed mesh strategy is capable of greatly reducing the number of mesh elements, hence computation time, while preserving the characteristics of important flow-field variables. Moreover, it is applicable to a wide range of cell sizes and flow-field configurations and should be used as a guideline for mesh generation

Hypsometry and Volume of the Arctic Ocean and Its Constituent Seas

This paper presents an analysis of the Arctic Ocean and its constituent seas for seafloor area distribution versus depth and ocean volume. The bathymetry from the International Bathymetric Chart of the Arctic Ocean (IBCAO) is used together with limits defining this ocean and its constituent seas from the International Hydrographic Organization (IHO) as well as redefined limits constructed to confine the seas to the shallow shelves. IBCAO is a bathymetric grid model with a resolution of 2.5 x 2.5 km, which significantly improved the portrayal of the Arctic Ocean seafloor through incorporation of newly released bathymetric data including echo soundings from U.S. and British navies, scientific nuclear submarine cruises, and icebreaker cruises. This analysis of seafloor area and ocean volume is the first for the Arctic Ocean based on this new and improved portrayal of the seafloor as represented by IBCAO. The seafloor area and volume are calculated for different depths starting from the present sea level and progressing in increments of 10 m to a depth of 500 m and in increments of 50 m from 550 m down to the deepest depth within each of the analyzed seas. Hypsometric curves expressed as simple histograms of the frequencies in different depth bins and depth plotted against cumulative area for each of the analyzed seas are presented. The area and volume calculations show that the entire IHO-defined Arctic Ocean makes up 4.3% of the total ocean area but only 1.4% of the volume. Furthermore, the IHO Arctic Ocean is the shallowest (mean depth 1201 m) of all the major oceans and their adjacent seas. The continental shelf area, from the coasts out to the shelf break, make up as much as 52.9% of the total area in the Arctic Ocean, defined in this work as consisting of the oceanic deep Arctic Ocean Basin; the broad continental shelves of the Barents, Kara, Laptev, East Siberian, Chukchi, and Beaufort Seas; the White Sea; and the narrow continental shelf off both the Canadian Arctic Archipelago and northern Greenland. This result indicates that the Arctic Ocean has significantly larger continental shelves compared with all the other oceans, where previous studies show that the proportion of shelves, from the coasts out to the foot of the continental slopes, only ranges between about 9.1 and 17.7%. Furthermore, the derived hypsometric curves show that most of the Arctic Ocean shelf seas besides the Barents Sea, Beaufort Sea, and the shelf off northern Greenland have a similar shape, with the largest seafloor area between 0 and 50 m. The East Siberian and Laptev seas, in particular, show area distributions concentrated in this shallow depth range, and together with the Chukchi Sea they form a large flat shallow shelf province composing as much as 22% of the entire Arctic Ocean area but only 1% of the volume. This implies that the circulation in the Arctic Ocean might be very sensitive to eustatic sea level changes. One of the aims with this work is to make up-to-date high-resolution area and volume calculations for the Arctic Ocean at various depths available for download

Deep learning cardiac motion analysis for human survival prediction

Motion analysis is used in computer vision to understand the behaviour of moving objects in sequences of images. Optimising the interpretation of dynamic biological systems requires accurate and precise motion tracking as well as efficient representations of high-dimensional motion trajectories so that these can be used for prediction tasks. Here we use image sequences of the heart, acquired using cardiac magnetic resonance imaging, to create time-resolved three-dimensional segmentations using a fully convolutional network trained on anatomical shape priors. This dense motion model formed the input to a supervised denoising autoencoder (4Dsurvival), which is a hybrid network consisting of an autoencoder that learns a task-specific latent code representation trained on observed outcome data, yielding a latent representation optimised for survival prediction. To handle right-censored survival outcomes, our network used a Cox partial likelihood loss function. In a study of 302 patients the predictive accuracy (quantified by Harrell's C-index) was significantly higher (p < .0001) for our model C=0.73 (95$\%$ CI: 0.68 - 0.78) than the human benchmark of C=0.59 (95$\%$ CI: 0.53 - 0.65). This work demonstrates how a complex computer vision task using high-dimensional medical image data can efficiently predict human survival

The information sources and journals consulted or read by UK paediatricians to inform their clinical practice and those which they consider important: a questionnaire survey

Background: Implementation of health research findings is important for medicine to be evidence-based. Previous studies have found variation in the information sources thought to be of greatest importance to clinicians but publication in peer-reviewed journals is the traditional route for dissemination of research findings. There is debate about whether the impact made on clinicians should be considered as part of the evaluation of research outputs. We aimed to determine first which information sources are generally most consulted by paediatricians to inform their clinical practice, and which sources they considered most important, and second, how many and which peer-reviewed journals they read. Methods: We enquired, by questionnaire survey, about the information sources and academic journals that UK medical paediatric specialists generally consulted, attended or read and considered important to their clinical practice. Results: The same three information sources – professional meetings & conferences, peerreviewed journals and medical colleagues – were, overall, the most consulted or attended and ranked the most important. No one information source was found to be of greatest importance to all groups of paediatricians. Journals were widely read by all groups, but the proportion ranking them first in importance as an information source ranged from 10% to 46%. The number of journals read varied between the groups, but Archives of Disease in Childhood and BMJ were the most read journals in all groups. Six out of the seven journals previously identified as containing best paediatric evidence are the most widely read overall by UK paediatricians, however, only the two most prominent are widely read by those based in the community. Conclusion: No one information source is dominant, therefore a variety of approaches to Continuing Professional Development and the dissemination of research findings to paediatricians should be used. Journals are an important information source. A small number of key ones can be identified and such analysis could provide valuable additional input into the evaluation of clinical research outputs

Combining classifiers for robust PICO element detection

<p>Abstract</p> <p>Background</p> <p>Formulating a clinical information need in terms of the four atomic parts which are Population/Problem, Intervention, Comparison and Outcome (known as PICO elements) facilitates searching for a precise answer within a large medical citation database. However, using PICO defined items in the information retrieval process requires a search engine to be able to detect and index PICO elements in the collection in order for the system to retrieve relevant documents.</p> <p>Methods</p> <p>In this study, we tested multiple supervised classification algorithms and their combinations for detecting PICO elements within medical abstracts. Using the structural descriptors that are embedded in some medical abstracts, we have automatically gathered large training/testing data sets for each PICO element.</p> <p>Results</p> <p>Combining multiple classifiers using a weighted linear combination of their prediction scores achieves promising results with an <it>f</it>-measure score of 86.3% for P, 67% for I and 56.6% for O.</p> <p>Conclusions</p> <p>Our experiments on the identification of PICO elements showed that the task is very challenging. Nevertheless, the performance achieved by our identification method is competitive with previously published results and shows that this task can be achieved with a high accuracy for the P element but lower ones for I and O elements.</p

Exile Vol. XXXIV No. 2

ARTWORK The Race and the Load by Rhonwen Churchill (cover) Population 6 by Rory Herbster 5 Untitled by Itar 9 Untitled by Itar 17 Untitled by Itar 25 Floating Nude by Shelley Dicerson 27 Valley of Fire, New Mexico by Pam Schilling 33 Untitled by Rhonwen churchill 39 Merely Players by Rhonwen Churchill 43 Newark at Night by Rob Myers 55 Torso II by Shelley Dickerson 57 Untitled by Don Jacobs 61 Serenade by Jenny Smith 65 FICTION Untitled by Lauren Williams 11-15 A Subtle Change in the Flowers by Zach Smith 30-32 Documenting Secrets by Laura Munson 47-52 POETRY Ars Poetica by David Zivan 3 Jesse James In Wax by Itar 4 Catechism by Jennie Dawes 7 Silent State by Cam Martin 8 Red Rock Mound by Itar 16 Almost There by Chris Hanson 19 In Memory by Kent Lambert 20-23 Driving Cross-Country by David Zivan 24 Yoga At Sunrise by Itar 35-36 His Photograph by Debra Benko 37 Appalachian Spring by Jennie Dawes 38 My Proposal by Liza Jones 41 Spheres of Influence by Zach Smith 42 The Eros Motel by Cam Martin 45 A Sacrificial Science by Jen Druley 46 Bird\u27s-Eye View by Itar 53 Driving by David Zivan 54 Mobile Home In The Sky by Itar 59-60 The Cleaving by Amy Judge 63 She Kent Lambert 64 CONTRIBUTOR NOTES 67 Editorial decision is shared equally among the Editorial Board members. - title pag