Social presence in the 21st Century: an adjustment to the Community of Inquiry framework

The Community of Inquiry framework, originally proposed by Garrison, Anderson and Archer (2000) identifies teaching, social and cognitive presences as central to a successful online educational experience. This article presents the findings of a study conducted in Uruguay between 2007 and 2010. The research aimed to establish the role of cognitive, social and teaching presences in the professional development of 40 English language teachers on Continuous Professional Development (CPD) programmes delivered in blended learning settings. The findings suggest that teaching presence and cognitive presence have themselves 'become social'. The research points to social presence as a major lever for engagement, sense-making and peer support. Based on the patterns identified in the study, this article puts forward an adjustment to the Community of Inquiry framework, which shows social presence as more prominent within the teaching and cognitive constructs than the original version of the framework suggests

Josephson φ\varphi-junctions based on structures with complex normal/ferromagnet bilayer

We demonstrate that Josephson devices with nontrivial phase difference $0<\varphi_g <\pi$ in the ground state can be realized in structures composed from longitudinally oriented normal metal (N) and ferromagnet (F) films in the weak link region. Oscillatory coupling across F-layer makes the first harmonic in the current-phase relation relatively small, while coupling across N-layer provides negative sign of the second harmonic. To derive quantitative criteria for a $\varphi$-junction, we have solved two-dimensional boundary-value problem in the frame of Usadel equations for overlap and ramp geometries of S-NF-S structures. Our numerical estimates show that $\varphi$-junctions can be fabricated using up-to-date technology.Comment: 14 pages, 9 figure

Detectable Changes in The Blood Transcriptome Are Present after Two Weeks of Antituberculosis Therapy

Globally there are approximately 9 million new active tuberculosis cases and 1.4 million deaths annually. Effective antituberculosis treatment monitoring is difficult as there are no existing biomarkers of poor adherence or inadequate treatment earlier than 2 months after treatment initiation. Inadequate treatment leads to worsening disease, disease transmission and drug resistance.To determine if blood transcriptional signatures change in response to antituberculosis treatment and could act as early biomarkers of a successful response.Blood transcriptional profiles of untreated active tuberculosis patients in South Africa were analysed before, during (2 weeks and 2 months), at the end of (6 months) and after (12 months) antituberculosis treatment, and compared to individuals with latent tuberculosis. An active-tuberculosis transcriptional signature and a specific treatment-response transcriptional signature were derived. The specific treatment response transcriptional signature was tested in two independent cohorts. Two quantitative scoring algorithms were applied to measure the changes in the transcriptional response. The most significantly represented pathways were determined using Ingenuity Pathway Analysis.An active tuberculosis 664-transcript signature and a treatment specific 320-transcript signature significantly diminished after 2 weeks of treatment in all cohorts, and continued to diminish until 6 months. The transcriptional response to treatment could be individually measured in each patient.Significant changes in the transcriptional signatures measured by blood tests were readily detectable just 2 weeks after treatment initiation. These findings suggest that blood transcriptional signatures could be used as early surrogate biomarkers of successful treatment response

Consistent as-similar-as-possible non-isometric surface registration

© 2017 The Author(s)Non-isometric surface registration, aiming to align two surfaces with different sizes and details, has been widely used in computer animation industry. Various existing surface registration approaches have been proposed for accurate template fitting; nevertheless, two challenges remain. One is how to avoid the mesh distortion and fold over of surfaces during transformation. The other is how to reduce the amount of landmarks that have to be specified manually. To tackle these challenges simultaneously, we propose a consistent as-similar-as-possible (CASAP) surface registration approach. With a novel defined energy, it not only achieves the consistent discretization for the surfaces to produce accurate result, but also requires a small number of landmarks with little user effort only. Besides, CASAP is constrained as-similar-as-possible so that angles of triangle meshes are preserved and local scales are allowed to change. Extensive experimental results have demonstrated the effectiveness of CASAP in comparison with the state-of-the-art approaches

FAAST: Flow-space Assisted Alignment Search Tool

<p>Abstract</p> <p>Background</p> <p>High throughput pyrosequencing (454 sequencing) is the major sequencing platform for producing long read high throughput data. While most other sequencing techniques produce reading errors mainly comparable with substitutions, pyrosequencing produce errors mainly comparable with gaps. These errors are less efficiently detected by most conventional alignment programs and may produce inaccurate alignments.</p> <p>Results</p> <p>We suggest a novel algorithm for calculating the optimal local alignment which utilises flowpeak information in order to improve alignment accuracy. Flowpeak information can be retained from a 454 sequencing run through interpretation of the binary SFF-file format. This novel algorithm has been implemented in a program named FAAST (Flow-space Assisted Alignment Search Tool).</p> <p>Conclusions</p> <p>We present and discuss the results of simulations that show that FAAST, through the use of the novel algorithm, can gain several percentage points of accuracy compared to Smith-Waterman-Gotoh alignments, depending on the 454 data quality. Furthermore, through an efficient multi-thread aware implementation, FAAST is able to perform these high quality alignments at high speed.</p> <p>The tool is available at <url>http://www.ifm.liu.se/bioinfo/</url></p

FAAST: Flow-space Assisted Alignment Search Tool

<p>Abstract</p> <p>Background</p> <p>High throughput pyrosequencing (454 sequencing) is the major sequencing platform for producing long read high throughput data. While most other sequencing techniques produce reading errors mainly comparable with substitutions, pyrosequencing produce errors mainly comparable with gaps. These errors are less efficiently detected by most conventional alignment programs and may produce inaccurate alignments.</p> <p>Results</p> <p>We suggest a novel algorithm for calculating the optimal local alignment which utilises flowpeak information in order to improve alignment accuracy. Flowpeak information can be retained from a 454 sequencing run through interpretation of the binary SFF-file format. This novel algorithm has been implemented in a program named FAAST (Flow-space Assisted Alignment Search Tool).</p> <p>Conclusions</p> <p>We present and discuss the results of simulations that show that FAAST, through the use of the novel algorithm, can gain several percentage points of accuracy compared to Smith-Waterman-Gotoh alignments, depending on the 454 data quality. Furthermore, through an efficient multi-thread aware implementation, FAAST is able to perform these high quality alignments at high speed.</p> <p>The tool is available at <url>http://www.ifm.liu.se/bioinfo/</url></p

Health and illness beliefs in adults with tuberculosis infection during the COVID-19 pandemic in the UK

BACKGROUND: COVID-19 disrupted the TB prevention programme in the UK, especially for TB infection (TBI) care. We explore whether experience of the COVID-19 pandemic impacted on patients' perceptions of TBI and its treatment. METHODS: Semi-structured interviews were conducted as part of the Research to Improve Detection and Treatment of TBI (RID-TB) programme, exploring perceptual and practical barriers to TBI treatment. Nineteen people diagnosed with TBI were interviewed between August 2020 and April 2021. Recordings were transcribed and analysed using a constant comparative approach, allowing for a dynamic and iterative exploration of themes. Themes are organised using the Perceptions and Practicalities Approach. FINDINGS: Some participants perceived TBI as a risk factor for increased susceptibility to COVID-19, while some thought that treatment for TBI might protect against COVID-19 or mitigate its effects. Adaptations to TB services (e.g., remote follow-up) and integrated practices during the COVID-19 restrictions (e.g., medication being posted) addressed some practical barriers to TBI treatment. However, we identified beliefs about TBI and COVID-19 that are likely to act as barriers to engagement with TBI treatment, including: interpreting service delays as an indication of TBI not being serious enough for treatment and concerns about contracting COVID-19 in TB clinics. INTERPRETATION: COVID-19 and TBI service delays influence people's perceptions and practical barriers to TBI treatment adherence. Failure to address these beliefs may lead to people's concerns about their treatment not being fully addressed. Utilised service adaptations like remote consultations to address practical barriers may be relevant beyond COVID-19

Mean-Field HP Model, Designability and Alpha-Helices in Protein Structures

Analysis of the geometric properties of a mean-field HP model on a square lattice for protein structure shows that structures with large number of switch backs between surface and core sites are chosen favorably by peptides as unique ground states. Global comparison of model (binary) peptide sequences with concatenated (binary) protein sequences listed in the Protein Data Bank and the Dali Domain Dictionary indicates that the highest correlation occurs between model peptides choosing the favored structures and those portions of protein sequences containing alpha-helices.Comment: 4 pages, 2 figure

PUGeo-Net: A Geometry-centric Network for 3D Point Cloud Upsampling

This paper addresses the problem of generating uniform dense point clouds to describe the underlying geometric structures from given sparse point clouds. Due to the irregular and unordered nature, point cloud densification as a generative task is challenging. To tackle the challenge, we propose a novel deep neural network based method, called PUGeo-Net, that learns a $3\times 3$ linear transformation matrix $\bf T$ for each input point. Matrix $\mathbf T$ approximates the augmented Jacobian matrix of a local parameterization and builds a one-to-one correspondence between the 2D parametric domain and the 3D tangent plane so that we can lift the adaptively distributed 2D samples (which are also learned from data) to 3D space. After that, we project the samples to the curved surface by computing a displacement along the normal of the tangent plane. PUGeo-Net is fundamentally different from the existing deep learning methods that are largely motivated by the image super-resolution techniques and generate new points in the abstract feature space. Thanks to its geometry-centric nature, PUGeo-Net works well for both CAD models with sharp features and scanned models with rich geometric details. Moreover, PUGeo-Net can compute the normal for the original and generated points, which is highly desired by the surface reconstruction algorithms. Computational results show that PUGeo-Net, the first neural network that can jointly generate vertex coordinates and normals, consistently outperforms the state-of-the-art in terms of accuracy and efficiency for upsampling factor $4\sim 16$.Comment: 17 pages, 10 figure

Shape Retrieval of Non-rigid 3D Human Models

3D models of humans are commonly used within computer graphics and vision, and so the ability to distinguish between body shapes is an important shape retrieval problem. We extend our recent paper which provided a benchmark for testing non-rigid 3D shape retrieval algorithms on 3D human models. This benchmark provided a far stricter challenge than previous shape benchmarks. We have added 145 new models for use as a separate training set, in order to standardise the training data used and provide a fairer comparison. We have also included experiments with the FAUST dataset of human scans. All participants of the previous benchmark study have taken part in the new tests reported here, many providing updated results using the new data. In addition, further participants have also taken part, and we provide extra analysis of the retrieval results. A total of 25 different shape retrieval methods are compared