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1,604 results for “Acceptance”
"Who Cares?": The Acceptance of Decentralized Wastewater Systems in Regions without Water Problems
<p>Transcripction of focus groups for the paper “Who Cares?”: The Acceptance of Decentralized Wastewater Systems in Regions without Water Problems. <a href="https://doi.org/10.3390/ijerph17239060">https://doi.org/10.3390/ijerph17239060</a> <em>Int. J. Environ. Res. Public Health</em> <strong>2020</strong>, <em>17</em>(23), 9060</p> <p><a href="https://zenodo.org/api/files/0039e4e3-1794-4be8-bb9c-63abf3512695/TRANSCRIPCI%C3%93N%20FOCUS%20GROUP%20ARQUITECTOS.docx">TRANSCRIPCIÓN FOCUS GROUP ARQUITECTOS</a></p> <p><a href="https://zenodo.org/api/files/0039e4e3-1794-4be8-bb9c-63abf3512695/TRANSCRIPCI%C3%93N%20FOCUS%20GROUP%20ECOLOGISTAS.docx">TRANSCRIPCIÓN FOCUS GROUP ECOLOGISTAS.docx </a></p> <p><a href="https://zenodo.org/api/files/0039e4e3-1794-4be8-bb9c-63abf3512695/TRANSCRIPCI%C3%93N%20FOCUS%20GROUP%20POBLACI%C3%93N%20GENERAL%201.docx">TRANSCRIPCIÓN FOCUS GROUP POBLACIÓN GENERAL 1.docx </a><br> <br> <a href="https://zenodo.org/api/files/0039e4e3-1794-4be8-bb9c-63abf3512695/TRANSCRIPCI%C3%93N%20FOCUS%20GROUP%20POBLACI%C3%93N%20GENERAL%202.docx">TRANSCRIPCIÓN FOCUS GROUP POBLACIÓN GENERAL 2.docx </a><br> </p>
Extracted and Anonymised Qualitative Data on Students' Acceptance of an Early Warning System
<p>The data published in this record was adopted in the following study: </p> <p><em><strong>Exploring Higher Education students' experience with AI-powered educational tools: The case of an Early Warning System </strong></em></p> <p>The study analyses the students' experience of an early warning system developed at a fully online university. The study is based on 21 semi-structured interviews that yielded a corpus of 21,761 words, for which a mixed inductive and deductive codification approach was applied after thematic analysis. We focused on 11 themes, 52 subthemes, and 396 coded segments to perform content analysis. Our findings revealed that the students, primarily senior workers with a high-level academic self-efficacy, had little experience with this type of system and low expectations about it. However, a usage experience triggered interest and meaningful reflections on the mentioned tool. Nevertheless, a comparative analysis between disciplines related to Computer Science and Economics showed higher confidence and expectation about the system and artificial intelligence overall by the first group. These results highlight the relevance of supporting students' further experiences and understanding of artificial intelligence systems in education to accept them and mainly to participate in iterative development processes of such tools to achieve quality, relevance, and fairness.</p> <p>The three records attached as part of the dataset include:</p> <p>1- The General CodeTree with exemplar coding excerpts in Spanish<br> 2- Extract of transcriptions in English<br> 3- Full Report in Spanish as extracted from NVIVO, including the extracted codes for the synthesis (1,2) in blue, and the comments made by the two researchers engaged in the interrater agreement.<br> 4- General Content Analysis (Spreadsheet ODS)</p> <p> </p>
Feasibility and acceptability of personalized breast cancer screening (DECIDO Study): A single-arm proof-of-concept trial
<p>The aim of this study was to assess the acceptability and feasibility of offering risk-based breast cancer screening and its integration into regular clinical practice. A single-arm proof-of-concept trial was conducted with a sample of 387 women aged 40–50 years residing in the city of Lleida (Spain). The study intervention consisted of breast cancer risk estimation, risk communication and screening recommendations, and a follow-up. A polygenic risk score with 83 single nucleotide polymorphisms was used to update the Breast Cancer Surveillance Consortium risk model and estimate the 5-year absolute risk of breast cancer. The women expressed a positive attitude towards varying the frequency of breast screening according to individual risk and, especially, more frequently inviting women at higher-than-average risk. A lower intensity screening for women at lower risk was not as welcome, although half of the participants would accept it. Knowledge of the benefits and harms of breast screening was low, especially with regard to false positives and overdiagnosis. The women expressed a high understanding of individual risk and screening recommendations. The participants' intention to participate in risk-based screening and satisfaction at 1-year were very high.</p>
Public Acceptance of Regional Redistribution in Germany: A Survey Experiment on the Perceived Deservingness of Regions
<p>Codebook and data that support the findings of the study "Public Acceptance of Regional Redistribution in Germany: A Survey Experiment on the Perceived Deservingness of Regions" by Jan Gniza and Matthias Wrede. Published in the <em>Journal of Social Policy</em>. For further information on data collection see sheet "Cover" in the codebook.</p>
Data for: Image-based evaluation of beers at an online Pint of Science festival using Projective Mapping, Check-All-That-Apply and Acceptability
<p>Data obtained from n=67 untrained attendants at an outreach Pint of Science festival, online because of the COVID-19 pandemic but usually held at bars. The participants used images of brand logos to evaluate eight beers among the most commonly consumed in Spain. Three sensory analysis techniques were used: Projective Mapping, Acceptability and Check-All-That-Apply (CATA).</p>
DATA: Chatbots in Airport Customer Service – Exploring Use Cases and Technology Acceptance
<p>This dataset (n=191) investigates use cases and technology acceptance of chatbots in airport customer service.</p>
Consider Social Acceptability of Contentious Low-Carbon Energy Technologies
<p>SSH CENTRE (Social Sciences and Humanities for Climate, Energy aNd Transport Research Excellence) is a Horizon Europe project, engaging directly with stakeholders across research, policy, and business (including citizens) to strengthen social innovation, SSH-STEM collaboration, transdisciplinary policy advice, inclusive engagement, and SSH communities across Europe, accelerating the EU’s transition to carbon neutrality. <br>SSH CENTRE is based in a range of activities related to Open Science, inclusivity and diversity – especially with regards Southern and Eastern Europe and different career stages – including: development of novel SSH-STEM collaborations to facilitate the delivery of the EU Green Deal; SSH knowledge brokerage to support regions in transition; and the effective design of strategies for citizen engagement in EU R&I activities. Outputs include action-led agendas and building stakeholder synergies through regular Policy Insight events.<br>This is captured in a high-profile virtual SSH CENTRE generating and sharing best practice for SSH policy advice, overcoming fragmentation to accelerate the EU’s journey to a sustainable future.<br>The documents uploaded here are part of WP2 whereby novel, interdisciplinary teams were provided funding to undertake activities to develop a policy recommendation related to EU Green Deal policy. Each of these policy recommendations, and the activities that inform them, will be written-up as a chapter in an edited book collection. Three books will make up this edited collection - one on climate, one on energy and one on mobility.</p> <p> <br>The present project proposes to conduct a research on social acceptability of three controversial technologies in France: nuclear fusion, agrivoltaics and offshore wind turbines. We review the literature and develop a framework for studying the dynamics of acceptability of these technologies over the entire 2013-2023 period. </p> <p>This file contains:</p> <ul> <li>Appendix 1 : This output uploaded is the literary corpus from the EUROPRESSE database used to carry out the sentimental analysis and the topics modelling</li> <li>Appendix 2 : The scraping results of the corpus from the EUROPRESSE database</li> <li>Appendix 3 : The topic modeling results of the corpus from the EUROPRESSE database</li> <li>Appendix 4 : The sentimental analysis results of the corpus from the EUROPRESSE database</li> <li>Appendix 5 : This file provides a comprehensive analysis of the factors shaping the social acceptability of low-carbon energy technologies in France</li> <li>Appendix 6 : This file sorted the 10 most positive and the 10 most negative articles associated with each low-carbon energy technology</li> </ul>
Dataset: Credit Acceptance Corporation (CACC) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Dataset: World Acceptance Corporation (WRLD) Stock Performance
This dataset provides historical stock market performance data for specific companies. It enables users to analyze and understand the past trends and fluctuations in stock prices over time. This information can be utilized for various purposes such as investment analysis, financial research, and market trend forecasting.
Fig. 3 in Cluster Analysis of Non-conserved Proteins of Trypanosoma cruzi Reference Strains Displays Parity between these Groupings (Peptidemes) and the Consensually Accepted Parasite Lineages
Fig. 3. Phenogram of the peptidemes (P) of eight Trypanosoma cruzi reference strains obtained using the SM coefficient and the UPGMA clustering algorithm, based on data from non-conserved proteins, as seen in SDS-PAGE analysis. The major peptidemes are indicated as mP 1 and mP 2. Their subgroups are identified on the right (P II, P VI, P I), and were numbered following their respective genetic types (TcII, TcVI, TcI), as currently used.
Fig. 1 in Cluster Analysis of Non-conserved Proteins of Trypanosoma cruzi Reference Strains Displays Parity between these Groupings (Peptidemes) and the Consensually Accepted Parasite Lineages
Fig. 1. Total protein profiles of eight Trypanosoma cruzi reference strains separated in 10% SDS-PAGE at 250 V, 25 mA, 90 min, and stained by Coomassie brilliant blue. The position of some conserved proteins is indicated on the right. M: molecular mass markers. (kDa) are indicated on the left.
Fig. 2 in Cluster Analysis of Non-conserved Proteins of Trypanosoma cruzi Reference Strains Displays Parity between these Groupings (Peptidemes) and the Consensually Accepted Parasite Lineages
Fig. 2. Diagrammatic representation of the twenty-two protein bands not shared by all Trypanosoma cruzi reference strains (nonconserved proteins), as visualized in SDS-PAGE. These bands were coded and analyzed by numerical taxonomy procedures. At the top is indicated the number of the major groups they belong, as identified by different approaches. The bands that were exclusive of one or more strains were highlighted with rectangles. M: molecular mass markers. (kDa) are indicated on the left.
Dataset of border control technologies' acceptance from travellers perspective
<p>The dataset is from the METICOS project pilot trials related to the acceptance of border control technologies. Five pilots were conducted at Tallinn Airport, Athens International Airport, Larnaca International Airport, the Moravita Land Border Crossing Point, and Vienna International Airport. The dataset includes data collected via an online questionnaire assessing travelers' acceptance based on demographics, profiles, and perceptions, along with operational information about the border control technologies during their use at the pilot trials.</p>
GAED: Game Acceptance Evaluation Dataset
<p>The Game Acceptance Evaluation Dataset (GAED) contains statistical data aswell training and validation sets used in our experiments on <em>Neural Networks to evaluate Video Games Acceptance</em>.</p> <p>Please consider citing the following references if you found this dataset useful:</p> <p>[1] Augusto de Castro Vieira, Wladmir Cardoso Brandão. Evaluating Acceptance of Video Games using Convolutional Neural Networks for Sentiment Analysis of User Reviews. In Proceedings of the 30th ACM Conference on Hypertext and Social Media. 2019.</p> <p>[2] Augusto de Castro Vieira, Wladmir Cardoso Brandão. GA-Eval: A Neural Network based approach to evaluate Video Games Acceptance. In Proceedings of the 18th Brazilian Symposium on Computer Games and Digital Entertainment. 2019.</p> <p>[3] Augusto de Castro Vieira, Wladmir Cardoso Brandão. (2019). GAED: The Game Acceptance Evaluation Dataset (Version 1.0) [Data set]. Zenodo. </p>
manuscript (atmosphere-3145955) titled: The Black Sea Upwelling System: Analysis on the Western Shallow Waters Authored by: Maria Emanuela Mihailov was accepted in Atmosphere (ISSN 2073-4433) on 15 August 2024
<p>Datasets represents the modelling results for:</p> <p>- Coastal Upwelling Transport Index (CUTI) of the National Oceanic and Administrative Administration’s Environmental Research Division (NOAA-ERD) was used to derive the time series of the coastal upwelling index in four locations on the north-western Black Sea coast. The coastal upwelling index time series was calculated using monthly average wind fields from the European Centre for Medium-Range Weather Forecasts (ECMWFs) reanalysis and MATLAB software to compute the CUTI </p> <p>- The upwelling index (UI) is computed using the CUTI Formula (<span>Bakun Index </span>), defined as CUTI (m3·s−1·100 m−1), representing the volume transport per distance unit of an alongshore section. The sign of Ekman transport is changed to define positive or negative values of UI as a response to upwelling or downwelling favourable winds.<br>To compute the BEUTI, Copernicus Marine Service [1] data are used for dedicated locations.</p> <p>[1] <span>Grégoire,<em> </em>M.;<em> </em>Vandenbulcke,<em> </em>L.;<em> </em>Capet,<em> </em>A.<em> </em>Black<em> </em>Sea<em> </em>Biogeochemical<em> </em>Reanalysis<em> </em>(CMEMS<em> </em>BS-Biogeochemistry)<em> </em>(Version<em> </em>1)<em> </em>set.<em> </em>Copernicus<em> </em>Monitoring<em> </em>Environment<em> </em>Marine<em> </em>Service<em> </em>(CMEMS).<em> </em>2020.<em> </em>Available<em> </em>online:<em> </em>https://marine.copernicus.eu/<em> </em>(accessed<em> </em>on<em> </em>10<em> </em>November<em> </em>2023).</span></p>
Data and analyses for Perkowski et al. (2024) manuscript accepted to AoB Plants: "Symbiotic nitrogen fixation reduces belowground biomass carbon costs of nitrogen acquisition under low, but not high, nitrogen availability"
<p>This repository contains data and scripts for analyses and plots in Perkowski et al. (2024), titled "Symbiotic nitrogen fixation reduces belowground biomass carbon costs of nitrogen acquisition under low, but not high, nitrogen availability".</p> <p>v2.0 updates code and scripts per reviewer comments and is the final release prior to manuscript proofing.</p>
Appendix Figures A.1 - A.15 of the paper "Advanced classification of hot subdwarf binaries using artificial intelligence techniques and Gaia DR3 data". This work has been accepted for publication in the journal Astronomy & Astrphysics (A&A) on September 24, 2024.
<p><strong>Figure captions:</strong></p> <p> </p> <p><strong>Fig. A.1.</strong> Heatmap with the number of common stars (true positives) labeled as binary for the five methods used.</p> <p> </p> <p><strong>Fig. A.2.</strong> Heatmap with the number of common stars (true negatives) labeled as single for the five methods used.</p> <p> </p> <p><strong>Fig. A.3.</strong> Color-magnitude diagrams, showing the 2815 stars of our sample from Sect. 3. Colors indicate the label predictions by SOM (left panel) and CNN (right panel).</p> <p> </p> <p><strong>Fig. A.4.</strong> K-S test comparing radial SOM (black) and CNN (blue).</p> <p> </p> <p><strong>Fig. A.5.</strong> Spectra of the star "LAMOSTJ112914.11+471501.7" (blue color) and in the background (gray color) the 35 stars classified as binary by Solano et al. (2022) with VOSA tools.</p> <p> </p> <p><strong>Fig. A.6.</strong> Spectra of the star "HD14829" (red color) and in the background (gray color) the 53 stars classified as single by Drilling et al. (2013).</p> <p> </p> <p><strong>Fig. A.7.</strong> Spectra of the star "Feige98" (red color) and in the background (gray color) the 53 stars classified as single by Drilling et al. (2013).</p> <p> </p> <p><strong>Fig. A.8.</strong> Spectra of the star "PG0304+184" (red color) and in the background (gray color) the 53 stars classified as single by Drilling et al. (2013).</p> <p> </p> <p><strong>Fig. A.9.</strong> Spectra of the star "PG1510+635" (red color) and in the background (gray color) the 53 stars classified as single by Drilling et al. (2013).</p> <p> </p> <p><strong>Fig. A.10.</strong> Cluster 0 of spectra (blue color) with the other spectra in the background (gray color).</p> <p> </p> <p><strong>Fig. A.11.</strong> Cluster 4 of spectra (brown color) with the other spectra in the background (gray color).</p> <p> </p> <p><strong>Fig. A.12.</strong> Cluster 1 of spectra (yellow color) with the other spectra in the background (gray color).</p> <p> </p> <p><strong>Fig. A.13.</strong> Cluster 3 of spectra (red color) with the other spectra in the background (gray color).</p> <p> </p> <p><strong>Fig. A.14.</strong> Cluster -1 of spectra (pink color) with the other spectra in the background (gray color).</p> <p> </p> <p><strong>Fig. A.15.</strong> Cluster 2 of spectra (green color) with the other spectra in the background (gray color).</p>
Fig. 1 in Confirmed polyphyly, generic recircumscription and typification of Dysoxylum (Meliaceae), with revised disposition of currently accepted species
Fig. 1. Phylogenetic tree based on BI analysis of the four-marker dataset (ITS, ETS, trnL-F, rps15-ycf1) with two runs of six MCMC chains of 50 million generations and corresponding posterior probability values. In square brackets, we provide the previous species names for all newly resurrected genera. Accession numbers in the tree correspond to specimens listed in Appendix 1. A, Clade 10 (green) represents all accessions of Chisocheton referred to as "Ch."; clade 11 (pink) shows all accessions of Prasoxylon referred to as "Pra."; clade 12 (orange) shows all accessions of Anthocarapa referred to as "An.", and Synoum as "Sy."; outgroup (white/no colour) with Trichilia as "Tr.", Cipadessa as "Ci.", Nymania as "Ny." and Turraea as "Tu.". B, Clade 1 (yellow) represents all accessions of Didymocheton referred to as "D."; clade 2 (dark blue) shows Cabralea referred to as "C."; clade 3 (green) represents Aglaieae sensu Pennington & Styles, containing Aglaia referred to as "Ag.", Aphanamixis as "A.", Reinwardtiodendron as "Re.", Lansium as "La.", and Sphaerosacme as "Sph."; clades 4 and 5 (pink) show all accessions of Epicharis referred to as "E."; clades 6 (light blue), 7 (purple) and 8 (red) show all accessions of Dysoxylum s.str. referred to as "Dys.", Pseudocarapa referred to as "Ps.", and Goniocheton referred to as "G.", respectively; clade 9 (orange) with the large parts of 'Guareeae' represents all accessions of Heckeldora referred to as "H.", Guarea as "Gu.", Leplaea as "Le.", Neoguarea as "Neog.", Ruagea as "Ru.", and Turraeanthus as "Tur.".
Barriers & Facilitators of People With Disabilities in Accepting & Adopting Autonomous Shared Mobility Services (Project A5)
<p>Enclosed you will find the data collected during our STRIDE Phase II Extension research project (A5) and a data dictionary.</p>
LiftWEC Social Acceptability Dataset
<p>This document contains LiftWEC’s social acceptability dataset. The dataset consists of interview transcripts sourced from semi-structured discussions conducted by a LiftWEC researcher and a range of stakeholders relevant to the field of marine renewable energy production. Semi-structured interviews were conducted with relevant actors between September and November of 2021. A snowball sampling approach was used for the selection of actors to be interviewed. Beginning with a small population of socio-political actors, this study developed a larger sample by learning from initial participants and identifying others who were relevant to the study. Interviewees were drawn up through a process of mapping, ensuring that a variety of actors holding different roles and located in different European nations engaged with the study and provided insight. Participants were then selected based upon the likelihood of having a detailed understanding of the emerging problems confronting marine renewable energy. Informed by literature, it was decided to categorise actors within three distinct profiles; (i) <em>socio-political actors</em>, (ii) <em>market actors</em>, and (iii) <em>community actors</em>. Three examples of interview transcripts, one from an actor relating to each of the aforementioned profiles, are presented in this dataset.</p> <p>The interviews were designed from the outset to allow for the analysis of debate regarding the social acceptance of novel and emerging marine renewable energy. Interviewees were prompted to discuss their perceptions of the current challenges and opportunities facing marine renewable energy technologies and their experience of how social acceptance issues are managed, and provide recommendations for the future. To support the free development and uptake of individual opinions from a variety of stakeholders, interviews were conducted on a one-to-one basis. A semi-structured interview guideline – an example is presented in section 3 of this dataset – was developed to gather data regarding the specific research objectives of the study. The interview guidelines helped to ensure comparability across interviews, especially across different countries and contexts. The questions that are part of the guideline are open questions, i.e., interview partners did not have fixed options for answering them. This provided interviewees with the possibility of freely choosing which aspect they wanted to put an emphasis or which aspects they wanted to mention. Furthermore, semi-structured interviews enabled the interviewer to spontaneously rephrase or add questions if the answers provided by the interviewee left too much room for interpretation or were not fully clear. All interviews lasted for a duration of between 40 minutes and one hour.</p> <p>This study that these interviews spawned from was conducted in line with the guidelines and standards set by the Queen’s University of Belfast’s Code of Conduct and Integrity in Research and its Policy and Principles on the Ethical Approval of Research. Free and informed consent was obtained from all participants prior to the collection of data from online interviews. All interviewees were provided with a project information sheet and a consent form prior to meeting, and participants were fully briefed on what the research involves. It was also explained how anonymity and confidentiality will be achieved. Permission was also sought for the audio of the meetings to be recorded and participants were made aware of their right to withdraw within one month of data gathering without penalty. Consent was also obtained for the data to be used for research purposes and for future publication. Confidentiality, a hugely important consideration in research, was ensured at all times during the course of the research.</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.