917 research outputs found
Integrated context-aware and cloud-based adaptive home screens for android phones
This is the post-print version of this Article. The official published version can be accessed from the link below - Copyright @ 2011 Springer VerlagThe home screen in Android phones is a highly customizable user interface where the users can add and remove widgets and icons for launching applications. This customization is currently done on the mobile device itself and will only create static content. Our work takes the concept of Android home screen [3] one step further and adds flexibility to the user interface by making it context-aware and integrated with the cloud. Overall results indicated that the users have a strong positive bias towards the application and that the adaptation helped them to tailor the device to their needs by using the different context aware mechanisms
The Online Dissemination of NatureâHealth Concepts: Lessons from Sentiment Analysis of Social Media Relating to âNature-Deficit Disorderâ
Evidence continues to grow supporting the idea that restorative environments, green exercise, and nature-based activities positively impact human health. Nature-deficit disorder, a journalistic term proposed to describe the ill effects of people's alienation from nature, is not yet formally recognized as a medical diagnosis. However, over the past decade, the phrase has been enthusiastically taken up by some segments of the lay public. Social media, such as Twitter, with its opportunities to gather "big data" related to public opinions, offers a medium for exploring the discourse and dissemination around nature-deficit disorder and other nature-health concepts. In this paper, we report our experience of collecting more than 175,000 tweets, applying sentiment analysis to measure positive, neutral or negative feelings, and preliminarily mapping the impact on dissemination. Sentiment analysis is currently used to investigate the repercussions of events in social networks, scrutinize opinions about products and services, and understand various aspects of the communication in Web-based communities. Based on a comparison of nature-deficit-disorder "hashtags" and more generic nature hashtags, we make recommendations for the better dissemination of public health messages through changes to the framing of messages. We show the potential of Twitter to aid in better understanding the impact of the natural environment on human health and wellbeing.Tim Taylor and Marco Palomino acknowledge funding from the European Centre for
Environment and Human Health, part of the University of Exeter Medical School, which was partially financed
by the European Regional Development Fund Programme 2007 to 2013 and European Social Fund Convergence
Programme for Cornwall and the Isles of Scilly during the course of this study. Funding for Sara Warber was
provided in part through a UK-US Fulbright Commission Scholarship that supported her studies at the European
Centre for Environment and Human Health, University of Exeter Medical School
Reply to Mistry et al. The Two Substrate Reduction Therapies for Type 1 Gaucher Disease Are Not Equivalent. Comment on âHughes et al. Switching between Enzyme Replacement Therapies and Substrate Reduction Therapies in Patients with Gaucher Disease: Data from the Gaucher Outcome Survey (GOS). J. Clin. Med. 2022, 11, 5158â
Toward a Novel Multilocus Phylogenetic Taxonomy for the Dermatophytes.
Type and reference strains of members of the onygenalean family Arthrodermataceae have been sequenced for rDNA ITS and partial LSU, the ribosomal 60S protein, and fragments of ÎČ-tubulin and translation elongation factor 3. The resulting phylogenetic trees showed a large degree of correspondence, and topologies matched those of earlier published phylogenies demonstrating that the phylogenetic representation of dermatophytes and dermatophyte-like fungi has reached an acceptable level of stability. All trees showed Trichophyton to be polyphyletic. In the present paper, Trichophyton is restricted to mainly the derived clade, resulting in classification of nearly all anthropophilic dermatophytes in Trichophyton and Epidermophyton, along with some zoophilic species that regularly infect humans. Microsporum is restricted to some species around M. canis, while the geophilic species and zoophilic species that are more remote from the human sphere are divided over Arthroderma, Lophophyton and Nannizzia. A new genus Guarromyces is proposed for Keratinomyces ceretanicus. Thirteen new combinations are proposed; in an overview of all described species it is noted that the largest number of novelties was introduced during the decades 1920-1940, when morphological characters were used in addition to clinical features. Species are neo- or epi-typified where necessary, which was the case in Arthroderma curreyi, Epidermophyton floccosum, Lophophyton gallinae, Trichophyton equinum, T. mentagrophytes, T. quinckeanum, T. schoenleinii, T. soudanense, and T. verrucosum. In the newly proposed taxonomy, Trichophyton contains 16 species, Epidermophyton one species, Nannizzia 9 species, Microsporum 3 species, Lophophyton 1 species, Arthroderma 21 species and Ctenomyces 1 species, but more detailed studies remain needed to establish species borderlines. Each species now has a single valid name. Two new genera are introduced: Guarromyces and Paraphyton. The number of genera has increased, but species that are relevant to routine diagnostics now belong to smaller groups, which enhances their identification
Risk information recommendation for engineering workers.
Within any sufficiently expertise-reliant and work-driven domain there is a requirement to understand the similarities between specific work tasks. Though mechanisms to develop similarity models for these areas do exist, in practice they have been criticised within various domains by experts who feel that the output is not indicative of their viewpoint. In field service provision for telecommunication organisations, it can be particularly challenging to understand task similarity from the perspective of an expert engineer. With that in mind, this paper demonstrates a similarity model developed from text recorded by engineerâs themselves to develop a metric directly indicative of expert opinion. We evaluate several methods of learning text representations on a classification task developed from engineers' notes. Furthermore, we introduce a means to make use of the complex and multi-faceted aspect of the notes to recommend additional information to support engineers in the field
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