“One does not simply categorize a meme”: A dual classification system for visual-textual internet memes

Internet memes are a popular and long-standing genre of discourse on social media platforms, used to express everything from emotional states to political opinions. Dancygier and Vandelanotte (2017) define internet memes as intertextual, multimodal discourses that combine text with images. In order to capture and compare these rapidly-changing discourses, we propose a descriptive dual classification system for memes with two components: meme composition and multimodal quality. Meme composition categorizes memes by their structure—beyond the individual images they employ—and thus explains how memes recontextualize images and text to create new meanings. Multimodal quality serves to describe the way(s) that the text interacts with the image in the meme: as a caption, label, and/or utterance. Combining one meme composition with one or more multimodal qualities classifies an individual meme structurally and provides a basis for explaining its intertextuality, modality, and meaning-making. We apply the dual classification system to English language data collected in its naturally-occurring context on the social media platform Instagram from 2019 to 2021. Analysis of these data shows that the dual classification system is a flexible and robust approach which provides a vocabulary for discussing the creative agency exerted by meme creators in a wide range of communities. We argue that the dual classification system affords researchers the ability to study memes linguistically across a variety of platforms and over time

The Effectiveness of Technology-Mediated Dance Interventions and Their Impact on Psychosocial Factors in Older Adults: A Systematic Review and Meta-Analysis

Background: Engaging in physical activity contributes to healthy aging; however, adherence to exercise programs is often low among older adults. Technology-mediated dance systems, which can be used at home, and dance as a way of keeping physically active have been receiving attention as a means of not only enabling physical activity among older people but may also address key psychosocial factors that are amenable to change. Objectives: To assess the effectiveness of technology-mediated dance interventions and their impact on psychosocial factors in older adults (aged 65 or older). Methods: A systematic review of randomized controlled trials from January 2000 to February 2017 using key search terms. Two independent reviewers screened articles using predetermined selection criteria. Risk of bias of selected articles was assessed in accordance with the Cochrane guidelines. Results: From an overall 264 articles, six articles (ve studies) were found, which assessed the impact of technology-mediated dance interventions on psychosocial factors in older adults. Studies' quality ratings were low, with exception of one study that was considered of moderate quality. None of the studies considered psychosocial factors as primary outcomes. Secondary outcomes assessed fear of falling, depression, and training enjoyment, but no study showed evidence of an effective impact on these variables. The meta-analysis revealed low quality evidence that there was little or no difference above that of the comparison groups for fear of falling (standardized mean difference [SMD] −0.02, 95% condence interval [CI] −0.37 to 0.33; P = 0.91; ve trials). Similarly, there was little or no difference on depression (SMD −0.06, 95% CI −0.59 to 0.47; P = 0.83; three trials). Conclusion: Existing evidence to support the effectiveness of technology-mediated dance interventions and their impact on psychosocial factors in older adults is weak and with a high risk for bias. The ndings of this review may inform future, more rigorous research in the area

Spread of Hepatitis C Virus among European Injection Drug Users Infected with HIV: A Phylogenetic Analysis

To describe the spread of hepatitis C virus (HCV) among HCV/human immunodeficiency virus (HIV)-coinfected injection drug users (IDUs), the molecular epidemiology of HCV was studied among 108 IDUs from 7 European countries. Phylogenetic analysis based on the NS5B region showed great sequence variation of HCV within each country and no clear phylogenetic clustering by geographic region. The most prevalent subtypes were 1a and 3a, but the percentage of genotype 4 was also relatively high, ranging from 7% in northern Europe to 24% in southern Europe. Genotype 4 consisted mainly of subtype 4d and has entered the majority of the IDU populations studied. The significantly lower evolutionary distances within subtype 4d suggest that this subtype may have entered the European IDU population relatively recently. In conclusion, HCV exchange between European IDU populations has occurred on a large scale, and, overall, country-specific clustering for HCV was less than that shown for HI

Low hepatitis B testing among migrants:a cross-sectional study in a UK city

BACKGROUND: In 2012, hepatitis B virus (HBV) testing of people born in a country with a prevalence of ≥2% was recommended in the UK. Implementation of this recommendation requires an understanding of prior HBV testing practice and coverage, for which there are limited data. AIM: To estimate the proportion of migrants tested for HBV and explore GP testing practices and barriers to testing. DESIGN AND SETTING: A cross-sectional study of (a) migrants for whom testing was recommended under English national guidance, living in Bristol, and registered with a GP in 2006–2013, and (b) GPs practising in Bristol. METHOD: NHS patient demographic data and HBV laboratory surveillance data were linked. A person was defined as ‘HBV-tested’ if a laboratory result was available. An online GP survey was undertaken, using a structured questionnaire. RESULTS: Among 82 561 migrants for whom HBV testing was recommended, 9627 (12%) were ‘HBV-tested’. The HBV testing coverage was: Eastern Africa 20%; Western Africa 15%; South Eastern Asia 9%; Eastern Asia 5%. Of 19 GPs, the majority did not use guidelines to inform HBV testing in migrants and did not believe routine testing of migrants was indicated; 12/17 GPs stated that workload and lack of human, and financial resources were the most significant barriers to increased testing. CONCLUSION: The majority of migrants to a multicultural UK city from medium-/high-prevalence regions have no evidence of HBV testing. Much greater support for primary care in the UK and increased GP awareness of national guidance are required to achieve adherence to current testing guidance

The EMBL Nucleotide Sequence Database

The EMBL Nucleotide Sequence Database (http://www.ebi.ac.uk/embl), maintained at the European Bioinformatics Institute (EBI) near Cambridge, UK, is a comprehensive collection of nucleotide sequences and annotation from available public sources. The database is part of an international collaboration with DDBJ (Japan) and GenBank (USA). Data are exchanged daily between the collaborating institutes to achieve swift synchrony. Webin is the preferred tool for individual submissions of nucleotide sequences, including Third Party Annotation (TPA) and alignments. Automated procedures are provided for submissions from large-scale sequencing projects and data from the European Patent Office. New and updated data records are distributed daily and the whole EMBL Nucleotide Sequence Database is released four times a year. Access to the sequence data is provided via ftp and several WWW interfaces. With the web-based Sequence Retrieval System (SRS) it is also possible to link nucleotide data to other specialist molecular biology databases maintained at the EBI. Other tools are available for sequence similarity searching (e.g. FASTA and BLAST). Changes over the past year include the removal of the sequence length limit, the launch of the EMBLCDSs dataset, extension of the Sequence Version Archive functionality and the revision of quality rules for TPA data

EMBL Nucleotide Sequence Database: developments in 2005

The EMBL Nucleotide Sequence Database () at the EMBL European Bioinformatics Institute, UK, offers a comprehensive set of publicly available nucleotide sequence and annotation, freely accessible to all. Maintained in collaboration with partners DDBJ and GenBank, coverage includes whole genome sequencing project data, directly submitted sequence, sequence recorded in support of patent applications and much more. The database continues to offer submission tools, data retrieval facilities and user support. In 2005, the volume of data offered has continued to grow exponentially. In addition to the newly presented data, the database encompasses a range of new data types generated by novel technologies, offers enhanced presentation and searchability of the data and has greater integration with other data resources offered at the EBI and elsewhere. In stride with these developing data types, the database has continued to develop submission and retrieval tools to maximise the information content of submitted data and to offer the simplest possible submission routes for data producers. New developments, the submission process, data retrieval and access to support are presented in this paper, along with links to sources of further information

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Learning biophysically-motivated parameters for alpha helix prediction

<p>Abstract</p> <p>Background</p> <p>Our goal is to develop a state-of-the-art protein secondary structure predictor, with an intuitive and biophysically-motivated energy model. We treat structure prediction as an optimization problem, using parameterizable cost functions representing biological "pseudo-energies". Machine learning methods are applied to estimate the values of the parameters to correctly predict known protein structures.</p> <p>Results</p> <p>Focusing on the prediction of alpha helices in proteins, we show that a model with 302 parameters can achieve a Q_{<it>α </it>}value of 77.6% and an SOV_{<it>α </it>}value of 73.4%. Such performance numbers are among the best for techniques that do not rely on external databases (such as multiple sequence alignments). Further, it is easier to extract biological significance from a model with so few parameters.</p> <p>Conclusion</p> <p>The method presented shows promise for the prediction of protein secondary structure. Biophysically-motivated elementary free-energies can be learned using SVM techniques to construct an energy cost function whose predictive performance rivals state-of-the-art. This method is general and can be extended beyond the all-alpha case described here.</p