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188 results for “content analysis”
Data from: Dietary partitioning among three cryptobentic reef fish mesopredators revealed by visual analysis, metabarcoding of gut content, and stable isotope analysis
<p>Understanding how mesopredators partition their diet and the identity of consumed prey can assist in understanding the ecological role predators and prey play in ecosystem trophodynamics. Here, we assessed the diet of three common coral reef mesopredators; <em>Pseudochromis flavivertex</em>, <em>Pseudochromis fridmani</em>, and <em>Pseudochromis olivaceus</em> from the family Pseudochromidae, commonly known as dottybacks, using a combination of i) visual stomach content analysis, ii) stomach content DNA metabarcoding (18S, COI), and iii) stable isotope analysis (δ<sup>15</sup>N, δ<sup>13</sup>C). In addition, <em>P. flavivertex</em> is found in two distinct color morphs in the Red Sea, providing an opportunity to analyze intra-morph differences. These techniques revealed partitioning in the dietary composition and resource use among species. Arthropods comprised the main dietary component of <em>P. flavivertex</em> (18S > 60%; COI > 10%), and <em>P. olivaceus</em> (18S = 57.2%) while <em>P. fridmani</em> ingested predominantly mollusks (18S = 51.3%, COI = 24.6%). Despite being small predators, microplastics were found in the gut content of some of these fishes. Stable isotope analysis showed differences in species' isotopic niche breadth and trophic position. <em>Pseudochromis olivaceus</em> presented the largest isotopic niche (SEA<sub>C</sub> = 1.61‰<sup>2</sup>), while <em>P. fridmani</em> showed the smallest isotopic niche (SEA<sub>C</sub> = 0.45‰<sup>2</sup>) among species. Although the two techniques used for stomach content analysis did not show differences in the diet within color morphs of <em>P. flavivertex</em>, they differed in the isotopic niche and resource use. Despite our limited sampling, our findings provide evidence of species-specific differences in the trophic ecology of dottybacks and demonstrate their important role as predators of cryptic invertebrates and small fishes. This study highlights the importance of combining several approaches (short-term: visual analysis and DNA metabarcoding; and long-term: isotope analysis) when assessing the feeding habits of coral reef fish, as they provide complementary information necessary to delimit their niches and understand the role that small mesopredators play in coral reef ecosystems.</p>
Genome content flat files for comparative genomic analysis of seadragons and relatives
<p>Seadragons are widely recognized for their derived and novel traits. Research and conservation efforts involving these unique fish species and their relatives have been hindered by a lack of genomic resources. From this project we present full, annotated genomes of leafy and weedy seadragons, which help uncover surprising features of gene family and genome architecture evolution that likely relate to extreme phenotypic traits in seadragons, pipefishes, and seahorses. These genomes are important research resources for the Syngnathidae, a diverse, morphologically exceptional group of vertebrates, and for comparative genomic study of vertebrates in general.</p>
Content Analysis on System Dynamics Modelling Application in Agriculture
<p>The data is a compilation of journal articles retrieved from three databases - Scopus, Web of Science, and Science Direct, using this Boolean search string: ("system dynamics" OR "systems thinking" OR "causal loop diagram") AND ("Agri*" OR "Food" OR "Crop" OR "Meat" OR "Animal" OR "Livestock")). </p>
A content analysis of Vietnam online news about a pentavaent vaccine in the EPI
<p>This includes two files:</p> <p>-One dataset includes details about the online newspaper articles about Quinvaxem, a 5-in-1 vaccine used in Expanded Programme on Immunization in Vietnam. It includes the names of articles, publication dates and original webpages which the author retrieved the articles from. </p> <p>- The coding framework used for categorizing articles. This was built based on codebooks used in previous studies about vaccine media analysis. It was piloted and tested for interrater reliability. </p>
Content analysis of Spanish Defense institutions' NATO eFP social media messages (2017-2022)
<p>Content analysis of Spanish Defense institutions' social media messages about the NATO Enhanced Forward Forward (eFP) mission on Facebook, Twitter (X), Instagram and YouTube (2017-2022).</p>
Fig 2 in Ontogeny and stomach content analysis of Bagrus bayad (Forskal, 1977) in Zobe reservoir, Katsina, Nigeria
Fig 2. Percentage weight of various food item in stomach content of Bagrus bayad in Zobe dam.
Picture this, power politics in international aid: A visual content analysis of the 2014 Ebola epidemic in West Africa, Dataset
<p>Literature on framing of the African continent is rich, however, similar framing literature on international actors in Africa is significantly under explored. This study investigated the visual frames through which Chinese, French, and U.S. newspapers engaged in nation branding by portraying international aid during the 2014 Ebola outbreak in West Africa. Data from the <em>People’s Daily</em>, <em>Le Monde</em>, and <em>The New York Times</em> showed that while Western coverage was negatively toned on frames of medical aid and culture, Chinese coverage was more positively toned on frames of medical aid and the military. Such findings contribute to scholarly understandings of visual media framing as functions of political power struggles and nation branding. </p>
Charter School Websites: A Physical Education and Physical Activity Content Analysis
<p>Excel file for data set associated with analysis of 520 California elementary charter school websites' mentioning of physical education and physical activity opportunities.</p>
Content analysis of a sample of images about climate change on Twitter
<p>We carried out a content analysis of images (photographs, illustrations and graphics) posted on Twitter, during five randomly selected weeks between 28 November 2019 and 29 November 2020. The random process of selecting five weeks, performed using the website random.org, yielded the following weeks: 3, 11, 22, 32 and 45. These weeks correspond to the following dates:</p> <p>Week 3: from 11 to 17 November 2019</p> <p>Week 11: from 6 to 12 January 2020</p> <p>Week 22: from 23 to 29 March 2020</p> <p>Week 32: from 8 to 14 June 2020</p> <p>Week 45: from 7 to 13 September 2020</p> <p>The sample was selected using the Twitter API (twitter.com) by selecting the “top tweets” that included photos or videos and were posted during the periods mentioned. The sample was chosen on 30 January 2021. We considered that the time interval between the tweet dates and the date the sample was chosen allowed enough time for each image to reach its full interaction potential.</p> <p>The searches carried out using the Twitter API were as follows:</p> <p>1. “climate change” since:2019-11-25 until:2019-11-17 filter:media</p> <p>2. “climate change” since:2020-01-12 until:2020-01-06 filter:media</p> <p>3. “climate change” since:2020-03-29 until:2020-03-23 filter:media</p> <p>4. “climate change” since:2020-06-14 until:2020-06-08 filter:media</p> <p>5. “climate change” since:2019-09-13 until:2019-09-07 filter:media</p> <p>Each of these searches yielded a result of between 90 and 100 tweets. The results were saved on a spreadsheet and all of the fixed images were selected (photographs, graphs, illustrations, etc.). When several images appeared on the same post, we considered each one of them independently. Besides the images, we saved the following information for each tweet: date, user, number of likes, number of retweets, number of comments and text associated with each tweet. The interactions (number of likes, number of retweets and number of comments) were considered indicators of interest in the content of the message and therefore an indication of the potential of that image (along with the text associated) to foster public involvement in climate change.</p> <p>Of the 419 total images included in the initial sample, 39 contained text only (the image showed only a sign, press cutting or similar), so these were excluded, leaving a final sample (n) of 380 images.</p> <p><em>Coding</em></p> <p>After putting the selected images in chronological order in a database, we developed the codebook based on examples from previous studies. To classify the types of images, we used the classification system proposed by O’Neill (2017) for the most common images in traditional media:</p> <p>- Identifiable people: i.e. politicians, businesspeople and celebrities.</p> <p>- Non-identifiable people.</p> <p>- Impacts of climate change: i.e. episodes of extreme weather, ice melting, desertification and endangered animal species.</p> <p>- Energy, emissions and pollution: i.e. factory smokestacks, renewable energy sources and traffic.</p> <p>- Protests: i.e. demonstrations and other protest actions.</p> <p>- Scientific images: i.e. graphics on greenhouse gas emissions and maps of global warming.</p> <p>- Other images.</p> <p>Basing our work on the principles outlined by Climate Visuals (2018), we propose seven factors that lend effectiveness to images as a means to foster climate change engagement:</p> <p>- Showing real people, avoiding staged images. Images that show people expressing identifiable emotions are especially effective. Politicians, due to their low credibility and the fact that they’re perceived as not being authentic, are not very effective.</p> <p>- Telling stories. Images that tell a story by themselves, especially the newest ones, tend to be more effective at fostering public involvement.</p> <p>- Showing the causes of climate change on the appropriate scale. For example, showing a gridlocked motorway could be more effective than showing a single driver. Images that show individual behaviour (such as eating meat) can trigger defensive reactions and may not be effective.</p> <p>- Showing powerful climate impacts. For example, floods and the effects of extreme weather, which can have a huge emotional impact.</p> <p>- Showing solutions. The levels of involvement and the ideology determine the response to the images. However, images that show “solutions” to climate change tend to generate positive emotions.</p> <p>- Establishing local connections. It’s a good idea to use images that connect climate change with a local environment. However, at the same time, they should connect with the problem on a global level.</p> <p>- Showing people who are directly affected. Although images of protests tend to generate scepticism among most observers, protests by people who are directly affected by climate change are usually perceived as more authentic and emotionally moving.</p> <p> </p> <p> </p>
Content Analysis Data set
<p><strong>Assessment of the Global Healthcare Industry during COVID-19 pandemic: A Content Analysis Approach</strong></p>
Contents of Supplemental Table S15 of the gradient analysis of Mesotaenium endlicherianum
<p>Contents of the large Supplemental Table S15 of the study "Environmental gradients reveal stress hubs predating plant terrestrialization"</p>
Dietary adaptations along the Northern limit of distribution: What does the smooth snake (Coronella austriaca) eat in Norway? Metabarcoding of stomach content and visual analysis of faeces
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Data from: Spider webs, stable isotopes and molecular gut content analysis: multiple lines of evidence support trophic niche differentiation in a community of Hawaiian spiders
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Data from: To pool or not to pool: Pooled metabarcoding does not affect estimates of prey diversity in spider gut content analysis
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Genome content flat files for comparative genomic analysis of seadragons and relatives
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Identification of potential western bean cutworm (<em>Striacosta albicosta</em>) predators in field corn through molecular gut-content analysis
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Data from: Dietary partitioning among three cryptobentic reef fish mesopredators revealed by visual analysis, metabarcoding of gut content, and stable isotope analysis
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A content analysis of Vietnam online news about a pentavaent vaccine in the EPI
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Arthropod food webs in the foreland of a retreating Greenland glacier: Integrating molecular gut content analysis with Structural Equation Modelling
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Data file: a qualitative social media content analysis of the Dutch #breakthesilence campaign on negative and traumatic experiences of labour and birth
<p>Data file with typed out quotes from the Dutch #breakthesilence campaign analysed for the study 'Left powerless: a qualitative social media content analysis of the Dutch #breakthesilence campaign on negative and traumatic experiences of labour and birth'.</p>
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.