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2,373 results for “working”
Working Memory and Reward in Children with and without Attention Deficit Hyperactivity Disorder (ADHD)
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Differential brain mechanisms of selection and maintenance of information during working memory (MEG data)
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Working Memory and Reward in Adults
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CoHERE Work Package 5 Survey of free time activities amongst Latvian schoolchildren
<p>The quantitative survey «Youth and leisure time activities, informal education and cultural heritage» was carried out as part of Work Package 5 (Education, heritage and identities) of 'Critical Heritages: Performing and presenting identities in Europe' (https://research.ncl.ac.uk/cohere/researchstrands/). This Work Package develops best practices in the production and transmission of European heritages and identities within two sectors that face challenges in an age of immigration and globalization, namely education and cultural heritage production. It explores how European identity is shaped through formal and informal learning situations both in and outside the classroom with the purpose of enhancing school curricula and informal learning at heritage sites by integrating innovative technologies and including multicultural perspectives.</p> <p>The target group: youth (age 16 to 19) from secondary schools and professional education schools in Latvia </p> <p>Sample size: 1047. Time period: December 2017 – March 2018.</p> <p>Method: a self-administered questionnaire.</p> <p>The aim of the survey is to examine how cultural heritage shape different identities in Europe, representing ideas of place, history, traditions and sense of belonging.</p> <p>Tasks of the survey:<br> 1) to get information about leisure time activities of the youth and their participation in different informal education activities;<br> 2) to examine youth opinion about the role of cultural heritage and their involvement in safeguarding cultural heritage;<br> 3) to analyse the role of cultural heritage in formation of local, national and European identities of the young people.</p>
CoHERE Work Package 3 Survey of Inhabitants of Baltic Countries on Song and Dance Celebrations
<p>Part of Work Package 3 for the 'Critical Heritages' research project ( https://research.ncl.ac.uk/cohere/researchstrands/#WP3%20Cultural%20forms%20and%20expressions%20of%20identity%20in%20Europe ).</p> <p>One of the key case studies in CoHERE Work Package 3 has been the Song and Dance Celebration tradition in the Baltic states (included in the UNESCO list as a masterpiece of the oral and intangible heritage of humanity in 2003). The case study reveals several aspects of this festival: cultural, economic, social dimensions and governance. Through examining different aspects of this festival tradition and everyday practices it responds to several objectives of the WP3. Being a key social and cultural event in three Baltic countries, it provides a ground for debates on how performative practices and festivals can contribute to identity construction and transformation, developing sense of belonging, serve as platform for where heritage practices of different social groups can meet.</p>
How to measure work functions from aqueous solutions - data
<p>Data set pertaining to the article "How to measure work functions from aqueous solutions", <a href="https://doi.org/10.1039/D3SC01740K" target="_blank" rel="noopener">https://doi.org/10.1039/D3SC01740K</a> (Chemical Science <strong>14</strong>, 9574-9588 (2023)). A new protocol for energy referencing of photoemission data from liquids (<a href="https://doi.org/10.1039/D1SC01908B" target="_blank" rel="noopener">https://doi.org/10.1039/D1SC01908B</a>, Chemical Science <strong>12</strong>, 10558-10582 (2021)) is refined towards determining work functions from liquids.<br><br></p> <p>Files with extension .h5 are hdf5-files structured according to the NeXus v2020.10 standard using the NXmpes user contributed format suggested by the Fairmat consortium, see<br>https://www.nexusformat.org/<br>https://fairmat-experimental.github.io/nexus-fairmat-proposal/50433d9039b3f33299bab338998acb5335cd8951/mpes-structure.html<br>A few extensions specific to liquid jet-experiments were added to the standard, and are explained in the notes-group on the top level of each file.<br>NeXus data files can be opened with any software capable of opening hdf5-structured files. The following viewers are adapted to the specifics of the NeXus data format:<br>* nexpy (distributed with python)<br>* https://h5web.panosc.eu/h5wasm (web-based NeXus viewer maintained by the European Photon and Neutron Open Science Cloud-consortium)</p> <p>In each NeXus file-entry, two types of spectra are included:<br>1. Sweep-averaged spectra, integrated over the non-dispersive coordinate of our detector ('data').<br>2. As-measured data ('raw').</p> <p>Files with extension .txt are tab-separated ascii-files.</p> <p><br>The following files are provided:</p> <p>Photoemission data pertaining to solute measurements and reference measurements using a gold wire:<br>'Figure 3.h5'<br>'Figure 4.h5'<br>'Figure S1.h5'<br>'Figure S2.h5'<br>Kinetic energies are presented as measured. The scale offset of our spectrometer, determined as E_kin(corrected) = E_kin(measured) + 0.224 eV for data sets 'Figure 3.h5', 'Figure 4.h5' ,'Figure S2.h5', has not been taken into account.</p> <p>Numeric representations of the analysis results shown in the article's figures in graphical form:<br>'Figure 5.txt'<br>'Figure 6B.txt'<br>'Figure 7.txt'<br>'Figure S4B.txt'<br>'Figure S5.txt'</p> <p>In case you have any questions regarding this data set please contact: Uwe Hergenhahn, uhe@fhi.mpg.de .</p>
CETAF-DiSSCo/COVID19-TAF biodiversity-related knowledge hub working group: indexed biotic interactions and review summary
<p>This data publication originated as part of developing a biodiversity-related knowledge hub on COVID-19 via COVID19-TAF - Communities Taking Action (https://cetaf.org/covid19-taf-communities-taking-action), a community-rooted initiative raised jointly by the Consortium of European Taxonomic Facilitaties (CETAF, https://cetaf.org) and Distributed Systems of Scientific Collections (DiSSCo, https://www.dissco.eu/).</p> <p>This archive contains the biodiversity datasets of interest identified in period 14 April-6 October 2020 through COVID19-TAF activities and subsequently indexed by Global Biotic Interactions (GloBI, https://globalbioticinteractions.org). GloBI provides open access to finding species interaction data (e.g., predator-prey, pollinator-plant, virus-host, parasite-host) by combining existing open datasets using open source software.</p> <p>These identified datasets (see references and reviews below) add to a growing collection of open species interaction datasets already indexed by GloBI. So, this data publication only includes a small subset of indexed datasets and include only datasets that were added as a direct consequence of COVID19-TAF activities of the biodiversity-related knowledge hub working group.</p> <p>If you have questions or comments about this publication, please open an issue at https://github.com/ParasiteTracker/tpt-reporting or contact the authors by email.</p> <p>Funding:<br> The creation of this archive was made possible in part by reporting software developed as part of the National Science Foundation award "Collaborative Research: Digitization TCN: Digitizing collections to trace parasite-host associations and predict the spread of vector-borne disease," Award numbers DBI:1901932 and DBI:1901926 . Also, this material is based upon work supported by the National Science Foundation under Grant No. DGE-1545433 .</p> <p>References:<br> Jorrit H. Poelen, James D. Simons and Chris J. Mungall. (2014). Global Biotic Interactions: An open infrastructure to share and analyze species-interaction datasets. Ecological Informatics. https://doi.org/10.1016/j.ecoinf.2014.08.005.</p> <p>GloBI Data Review Report</p> <p>Datasets under review:<br> - Geiselman, Cullen K. & Sarah Younger. 2020. Bat Eco-Interactions Database. www.batbase.org accessed via https://github.com/globalbioticinteractions/batbase/archive/9c65cfeee1a054f9db8cd8bf6892017fd1b3c840.zip on 2020-10-04T22:53:45.576Z<br> - Geiselman, Cullen K. and Tuli I. Defex. 2015. Bat Eco-Interactions Database. www.batplant.org accessed via https://github.com/globalbioticinteractions/batplant/archive/a2e1b57052244d5251d17e96ea61f58bea88975e.zip on 2020-10-04T22:54:28.727Z<br> - Daniel Becker, Gregory F Albery, Anna R Sjodin, Timothee Poisot, Tad Dallas, Evan A. Eskew, Maxwell J. Farrell, Sarah Guth, Barbara A Han, Nancy B Simmons, Colin J Carlson. 2020. Predicting wildlife hosts of betacoronaviruses for SARS-CoV-2 sampling prioritization. bioRxiv 2020.05.22.111344; doi: https://doi.org/10.1101/2020.05.22.111344 accessed via https://github.com/globalbioticinteractions/becker2020/archive/47c6ad28e1c5058f3c13ca69a59fdf21229e8d7f.zip on 2020-10-04T22:54:46.723Z<br> - Chen L, Liu B, Yang J, Jin Q, 2014. DBatVir: the database of bat-associated viruses. Database (Oxford). 2014:bau021. doi:10.1093/database/bau021 accessed via https://github.com/globalbioticinteractions/dbatvir/archive/a906d76e362484d3ca1edbe9683f672838ab70b0.zip on 2020-10-04T22:56:13.913Z<br> - Chen L, Liu B, Wu Z, Jin Q, Yang J, 2017. DRodVir: A resource for exploring the virome diversity in rodents. J Genet Genomics. 44(5):259-264. accessed via https://github.com/globalbioticinteractions/drodvir/archive/0346c0e8d4d66c6400e9965bd6a6aeed24cd7586.zip on 2020-10-04T23:06:04.368Z<br> - Agosti, Donat. 2020. Transcription of Linné, C. von, 1758. Systema naturae per regna tria naturae secundum classes, ordines, genera, species, cum characteribus, differentiis, synonymis, locis. Available at: http://dx.doi.org/10.5962/bhl.title.542 . accessed via https://github.com/globalbioticinteractions/linnaeus1758/archive/a818060080fa04a88dac6df1ae5b897304ae8877.zip on 2020-10-05T00:46:04.852Z<br> - Mollentze, Nardus, & Streicker, Daniel G. (2019). Viral zoonotic risk is homogenous among taxonomic orders of mammalian and avian reservoir hosts (Version 1.0.0) [Data set]. Zenodo. http://doi.org/10.5281/zenodo.3516613 accessed via https://github.com/globalbioticinteractions/mollentze2019/archive/ad12dc74d03c3d992618f16c37cafb7f7ffd9d01.zip on 2020-10-05T00:50:55.878Z<br> - Eneida L. Hatcher, Sergey A. Zhdanov, Yiming Bao, Olga Blinkova, Eric P. Nawrocki, Yuri Ostapchuck, Alejandro A. Schäffer, J. Rodney Brister, Virus Variation Resource – improved response to emergent viral outbreaks, Nucleic Acids Research, Volume 45, Issue D1, January 2017, Pages D482–D490, https://doi.org/10.1093/nar/gkw1065 . accessed via https://github.com/globalbioticinteractions/ncbi-virus/archive/531a8d743d7adcf1153a19087e5d3c5b76750e3e.zip on 2020-10-05T00:53:53.646Z<br> - Olival, K. J., Hosseini, P. R., Zambrana-Torrelio, C., Ross, N., Bogich, T. L., & Daszak, P. (2017). Host and viral traits predict zoonotic spillover from mammals. Nature, 546(7660), 646–650. doi:10.1038/nature22975 accessed via https://github.com/globalbioticinteractions/olival2017/archive/f61070a5339d0e6c6e76d7eb4e2102decb52317d.zip on 2020-10-05T00:56:43.356Z<br> - Pensoft Darwin Core Archives with associateTaxa columns accessed via https://github.com/globalbioticinteractions/pensoft-dwca/archive/ee8831a2a391203f4fa8c05a0ddd927202b234bf.zip on 2020-10-05T00:56:51.868Z<br> - Pensoft Darwin Core Archives available via Integrated Publication Toolkit accessed via https://github.com/globalbioticinteractions/pensoft-ipt/archive/4ad4b47978324681289e36f8c2b247b1bcc97b1a.zip on 2020-10-05T00:58:01.912Z<br> - De Rojas M, Doña J, Dimov I (2020) A comprehensive survey of Rhinonyssid mites (Mesostigmata: Rhinonyssidae) in Northwest Russia: New mite-host associations and prevalence data. Biodiversity Data Journal 8: e49535. https://doi.org/10.3897/BDJ.8.e49535 accessed via https://github.com/globalbioticinteractions/pensoft-table/archive/3488e0397ca4e083d5eca6949951e426a75713e3.zip on 2020-10-05T00:58:03.647Z<br> - Marcus Guidoti, Tatiana Ruschel, Donat Agosti. 2020. Corona virus related biotic associations manually extracted from literature. Plazi. accessed via https://github.com/globalbioticinteractions/plazi-covid19/archive/326578b0d9f974760dcd2e962d86636a6487a6c0.zip on 2020-10-05T00:58:08.025Z<br> - Shaw, LP, Wang, AD, Dylus, D, et al. The phylogenetic range of bacterial and viral pathogens of vertebrates. Mol Ecol. 2020; 29: 3361– 3379. https://doi.org/10.1111/mec.15463 accessed via https://github.com/globalbioticinteractions/shaw2020/archive/bb9ab857b7fdbb4e931752d01b43d37b3ada77cf.zip on 2020-10-05T01:05:23.554Z<br> - OpenBiodiv. 2020. Annotated biotic interaction tables from Pensoft publications. accessed via https://github.com/pensoft/pensoft-interaction-tables/archive/bb7d1dc9f2eba220a61502e06e6114053fd30788.zip on 2020-10-05T03:03:23.372Z<br> - Quentin J. Groom. 2020. Bat interation data manually extracted from literature. accessed via https://github.com/qgroom/batinterations/archive/70108945f9014aa0ac1db920191867f7e151c793.zip on 2020-10-05T03:04:11.533Z</p> <p>Generated on:<br> 2020-10-06</p> <p>by:<br> GloBI's Elton 0.10.2<br> (see https://github.com/globalbioticinteractions/elton).</p> <p> </p> <p>Note that all files ending with .tsv are files formatted<br> as UTF8 encoded tab-separated values files.</p> <p>https://www.iana.org/assignments/media-types/text/tab-separated-values</p> <p><br> Included in this review archive are:</p> <p>README:<br> This file.</p> <p>review_summary.tsv:<br> Summary across all reviewed collections of total number of distinct review comments.</p> <p>review_summary_by_collection.tsv:<br> Summary by reviewed collection of total number of distinct review comments.</p> <p>indexed_interactions_by_collection.tsv:<br> Summary of number of indexed interaction records by institutionCode and collectionCode.</p> <p>review_comments.tsv.gz:<br> All review comments by collection.</p> <p>indexed_interactions_full.tsv.gz:<br> All indexed interactions for all reviewed collections.</p> <p>indexed_interactions_simple.tsv.gz:<br> All indexed interactions for all reviewed collections selecting only sourceInstitutionCode, sourceCollectionCode, sourceCatalogNumber, sourceTaxonName, interactionTypeName and targetTaxonName.</p> <p>datasets_under_review.tsv:<br> Details on the datasets under review.</p> <p>elton.jar:<br> Program used to update datasets and generate the review reports and associated indexed interactions.</p> <p><br> datasets.zip:<br> source datasets collected by elton in process of executing the generate_report.sh script.</p> <p>generate_report.sh:<br> program used to generate the report</p> <p>generate_report.log:<br> log file generated as part of running the generate_report.sh script</p>
Working time, energy throughput and value added embodied in production, consumption and trade by subsectors for the US, the EU, China and rest of the world (2011)
<p>This repository contains the data needed to reproduce the results in:</p> <p>Pérez-Sánchez, L., Velasco-Fernández, R., Giampietro, M., The international division of labor and embodied working time in trade for the US, the EU and China, Ecological Economics. <a href="http://doi.org/10.1016/j.ecolecon.2020.106909">https://doi.org/10.1016/j.ecolecon.2020.1069097</a></p> <p>Sources of data are specified in the dataset (under tab "references")</p> <p> </p>
Synthesized anthropometric data for the German working-age population
<p>The anthropometric datasets presented here are virtual datasets. The unweighted virtual dataset was generated using a synthesis and subsequent validation algorithm (Ackermann et al., 2023). The underlying original dataset used in the algorithm was collected within a regional epidemiological public health study in northeastern Germany (SHIP, see Völzke et al., 2022). Important details regarding the collection of the anthropometric dataset within SHIP (e.g. sampling strategy, measurement methodology & quality assurance process) are discussed extensively in the study by Bonin et al. (2022).</p><p>To approximate nationally representative values for the German working-age population, the virtual dataset was weighted with reference data from the first survey wave of the Study on health of adults in Germany (DEGS1, see Scheidt-Nave et al., 2012). Two different algorithms were used for the weighting procedure: (1) iterative proportional fitting (IPF), which is described in more detail in the publication by Bonin et al. (2022), and (2) a nearest neighbor approach (1NN), which is presented in the study by Kumar and Parkinson (2018). Weighting coefficients were calculated for both algorithms and it is left to the practitioner which coefficients are used in practice. Therefore, the weighted virtual dataset has two additional columns containing the calculated weighting coefficients with IPF ("WeightCoef_IPF") or 1NN ("WeightCoef_1NN"). Unfortunately, due to the sparse data basis at the distribution edges of SHIP compared to DEGS1, values underneath the 5th and above the 95th percentile should be considered with caution.</p><p>In addition, the following characteristics describe the weighted and unweighted virtual datasets: According to ISO 15535, values for "BMI" are in [kg/m2], values for "Body mass" are in [kg], and values for all other measures are in [mm]. Anthropometric measures correspond to measures defined in ISO 7250-1. Offset values were calculated for seven anthropometric measures because there were systematic differences in the measurement methodology between SHIP and ISO 7250-1 regarding the definition of two bony landmarks: the acromion and the olecranon. Since these seven measures rely on one of these bony landmarks, and it was not possible to modify the SHIP methodology regarding landmark definitions, offsets had to be calculated to obtain ISO-compliant values. In the presented datasets, two columns exist for these seven measures. One column contains the measured values with the landmarking definitions from SHIP, and the other column (marked with the suffix "_offs") contains the calculated ISO-compliant values (for more information concerning the offset values see Bonin et al., 2022). The sample size is N = 5000 for the male and female subsets. The original SHIP dataset has a sample size of N = 1152 (women) and N = 1161 (men). Due to this discrepancy between the original SHIP dataset and the virtual datasets, users may get a false sense of comfort when using the virtual data, which should be mentioned at this point. In order to get the best possible representation of the original dataset, a virtual sample size of N = 5000 is advantageous and has been confirmed in pre-tests with varying sample sizes, but it must be kept in mind that the statistical properties of the virtual data are based on an original dataset with a much smaller sample size.</p>
Simultaneously Enhanced Tenacity, Rupture Work, and Thermal Conductivity of Carbon Nanotubes Fibers by Raising Effective Tube Portion
<p>Although individual carbon nanotubes (CNTs) are superior as constituents to polymer chains, the mechanical and thermal properties of CNT fibers (CNTFs) remain inferior to synthetic fibers due to the failure of embedding CNTs effectively in superstructures. Conventional techniques resulted in a mild improvement of target properties while achieving parity at best on others. Here, a Double-Drawing technique is developed to rearrange the constituent CNTs in both mesoscale and nanoscale morphology. Consequently, the mechanical and thermal properties of the resulting CNTFs can simultaneously reach their highest performances with specific strength ~3.30 N/tex, work of rupture ~70 J/g, and thermal conductivity ~354 W/m/K, despite starting from low-crystallinity materials (<em>I</em><sub>G</sub>:<em>I</em><sub>D</sub>~5). The processed CNTFs are more versatile than comparable carbon fiber, Zylon and Dyneema. Based on evidence of load transfer efficiency on individual CNTs measured with In-Situ-Stretching-Raman, we find the main contributors to property enhancements are the increasing of the effective tube contribution, in addition to the known optimization on CNTs alignment and stacking.</p>
EEG Data for: "Cortical oscillations and entrainment in speech processing during working memory load"
<p>This repository contains EEG and audio data used and described in:</p> <p><strong>Hjortkjær, J, Märcher-Rørsted, J, Fuglsang, SA, Dau, T (2018). Cortical oscillations and entrainment in speech processing during working memory load. European Journal of Neuroscience. </strong><strong>doi</strong><strong>:10.1111/ejn.13855</strong></p> <p>Please cite this article when using the data</p> <p> </p> <p>The MAT-files contain the aligned EEG and audio data for each subject (N=22). The envelopes of the speech audio (without noise) have been extracted as described in the paper. Each file (data_N.mat) contains a Matlab struct in the format of the Fieldtrip toolbox containing the following fields:</p> <p> </p> <p>data.trial: EEG and audio data for all 40 trials [channels x timepoints]</p> <ul> <li>channels 1-64: scalp EEG</li> <li>channel 65: left mastoid electrode</li> <li>channel 66: right mastoid electrode</li> <li>channel 67: horizontal EOG</li> <li>channel 68: vertical EOG for left eye</li> <li>channel 69: vertical EOG for right eye</li> <li>channel 70: audio envelopes</li> </ul> <p>data.trialinfo: Experimental condition in each trial</p> <ul> <li>1 = low noise, 1-back</li> <li>2 = low noise, 2-back</li> <li>3 = high noise, 1-back</li> <li>4 = high noise, 2-back</li> </ul> <p>data.time: Sample indices for each trial in seconds</p> <p>data.label: Name of each channel in data.trial</p> <p>data.fsample: EEG/audio sampling rate in Hz (128)</p>
Works by Hans Christian Andersen
<p>A selection of printed works by Hans Christian Andersen. The selection consists of 163 tales plus 6 novels and one file (in JSON-format) with metadata. Most files are flat txt-files, in UTF-8-format. Beware of the Danish special characters æ, ø, ö and the like. One file is in another format: metadataNotesTalesNovels.json . The JSON file is used in the program Intertext developed by Douglas Duhaime and Peter Leonard, see https://dhlab.yale.edu/projects/intertext/ and https://github.com/YaleDHLab/intertext -</p> <p>Update for version 1.0.1: I have added a zip-file with all 170 files.</p>
Quantitative electronic structure and work-function changes of liquid water induced by solute - data
<p>Data set pertaining to the article "Quantitative electronic structure and work-function changes of liquid water induced by solute" | Physical Chemistry Chemical Physics, 24, 1310 (2022).</p> <p>Files with extension .h5 are hdf5-files structured according to the NeXus standard v2022.07 using the NXmpes user contributed format suggested by the Fairmat consortium, see<br> https://www.nexusformat.org/<br> https://fairmat-experimental.github.io/nexus-fairmat-proposal/50433d9039b3f33299bab338998acb5335cd8951/mpes-structure.html<br> A few extensions specific to liquid jet-experiments were added to the standard, and are explained in the notes-group on the top level of each file.<br> NeXus data files can be opened with any software capable of opening hdf5-structured files. The following viewers are adapted to the specifics of the NeXus data format:<br> * nexpy (distributed with python)<br> * https://h5web.panosc.eu/h5wasm (web-based NeXus viewer maintained by the European Photon and Neutron Open Science Cloud-consortium)</p> <p>In each NeXus file-entry, two types of spectra are shown:<br> 1. Sweep-averaged spectra, integrated over the non-dispersive coordinate of our detector ('data').<br> 2. As-measured data ('raw').</p> <p>Files with extension .txt are comma-separated ascii-files.<br> The following files are provided:</p> <p>Photoemission data pertaining to solute measurements using the cut-off as energy reference:<br> NaI_data.h5<br> tbai_data.h5</p> <p>Biased spectra were typically recorded in the following order:<br> [cut-off (fine), cut-off (coarse), (valence band)*(N repeats)]*(M repeats)<br> To avoid the saving of overly complex hdf5-files, these data were saved in a different order, namely:<br> [cut-off (fine)*(M repeats), cut-off (coarse)*(M repeats), (valence band)*(N*M repeats)].</p> <p>Numeric representations of the traces shown in the article's figures:<br> Figure_1a-data.txt<br> Figure_1b-data.txt<br> Figure_2a-data.txt<br> Figure_2b-data.txt<br> Figure_2c-data.txt<br> Figure_3-data.txt<br> Figure_4-data.txt<br> Figure_5a-data.txt<br> Figure_5b-data.txt<br> Figure_6a-data.txt<br> Figure_6b-data.txt<br> Figure_6c-data.txt<br> Figure_7_diff_spectra-data.txt<br> Figure_8-data.txt</p> <p>Traces shown in several figures are included only in the data file pertaining to the figure in which they occur first.</p> <p> </p> <p>Contact: Uwe Hergenhahn, uhe@fhi.mpg.de .</p>
Piano sonatas and Beethoven works in Hans Georg Nägelis catalogues
<p>This dataset (in two csv files) collects the references to piano sonatas, and to works by Ludwig van Beethoven, in the catalogues published by Hans Georg Nägeli as a bookseller in Zurich between 1792 and 1805.</p> <p>The data was used by the author in his paper "Hans Georg Nägeli as Publisher and Bookseller of Piano Music", presented at the conference <a href="https://www.hkb-interpretation.ch/beethoven2020">Beethoven and the Piano</a>, 4–7 November 2020.</p> <p>The printed version of the article is at present in preparation.</p>
Visual working memory: Study one Task fMRI and Behavioural response
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Visual working memory: Study two Task fMRI and Behavioural response
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UWB-IODA project, Work package 1: IR-UWB optimized pulses
<p>The data files contain optimized UWB waveforms using B-spline functions. The spectral efficiency of each waveform is maximized under the constraint of the spectral mask defined by the FCC/ECC regulation authorities.</p>
STROBE checklist for a set of scientific works about COVID-19
<p>STROBE checklist for a set of scientific works about COVID-19. This dataset is the result of the expert-based assessment carried out in <a href="https://arxiv.org/abs/2004.06179">arXiv:2004.06179</a>.</p>
Supplementary material (aggregated data set): Egeler, G.-A. & Baur, P. (2020). Menüwahl in der Hochschulmensa: Fleisch oder Vegi? Ergebnisse eines 12-wöchigen Feldexperiments (NOVANIMAL Working Paper No. 5). ZHAW. https://doi.org/10.21256/zhaw-1405
<p><strong>Meal choice at two university canteens in a field experiment during 12 weeks: aggregated menu sales data</strong></p> <p>How do canteen visitors respond to a revised offer of meat-based and plant-based meals? Selected innovations were simultaneously implemented and tested in a trans­disciplinary field experiment in two university canteens over a 12-week period in the autumn semester 2017. Throughout this time, the meat dishes and ‘veg-meals’ (ovo-lacto-vegetarian and vegan meals) were randomly distributed among the three menu lines, the veg-meals were not marketed and advertised as such and the previous vegetarian menu line was abolished. Weeks where the usual number of meat dishes were on offer (the ‘base weeks’) alternated with weeks where the share of veg-meals was increased (the ‘intervention weeks’). <br> The field experiment did not have a negative impact on the number of meals sold or the turnover compared to the two previous years. Women choose meat dishes less often than men. This connection applies in the base weeks and intervention weeks, in all age groups, among both students and among staff. Remarkably, the share of (non-labelled) vegan dishes is comparable for women and men over all age groups, independent of university affiliation (student, staff). Authentic vegan dishes were particularly welcome. Veg-meals could also be sold on the more expensive menu line. There was a better correlation between meal choice, eating habits and attitudes (health, environment, animal welfare, social aspects) than expected. <br> One quarter of canteen visitors show ‘veg-oriented’ eating habits and three quarters thereof ‘meat-oriented’ eating habits. Only a minority of potential visitors eat regularly at the canteen, and those who do exhibit meat-oriented eating habits more often. We conclude, therefore, that the canteen’s usual menu offer is primarily aimed at visitors with meat-oriented eating habits at lunchtime. The most typical visitors to the canteen are male students who select meat dishes.<br> It has been shown, therefore, that the simultaneous changes in supply have worked. Veg-meals are preferred, particularly by women and those prone to flexitarian eating habits; however, also the canteen visitors with meat-oriented eating habits chose veg-meals during the intervention weeks. Catering in canteens has the great potential to expand the range of veg-meals at the expense of meat dishes, provided that the culinary quality is of a high enough standard and meals are not offered as vegetarian or vegan. The question arises as to whether canteens are not missing an economic opportunity if they only offer traditional meat dishes? Canteens are perfectly suited as real-world laboratories in which innovations for sustainable catering can be tried out. The field experiment in the two university canteens is a start; further experiments are needed.</p> <p><strong>The data set contains more than <em>26'000</em> aggregated menu sales. The analyses and results are summarized in the working paper No. 5 <a href="https://doi.org/10.21256/zhaw-1405">https://doi.org/10.21256/zhaw-1405</a></strong></p> <p>The corresponding scripts are: </p> <p>- <a href="http://doi.org/10.5281/zenodo.4034686">10.5281/zenodo.4034686</a></p> <p>- <a href="http://doi.org/10.5281/zenodo.4034698">10.5281/zenodo.4034698</a></p> <p>- <a href="http://doi.org/10.5281/zenodo.4244258">10.5281/zenodo.4244258</a> (newer Version)</p> <p>For more information visit the <a href="http://novanimal.ch">novanimal.ch</a> website.</p>
Analyses of the works of art and events related to Erkki Kurenniemi's Electronic Musical Instruments (EKIS)
<p>This speadsheet includes data related to analyses of works of art and events related to the Erkki Kurenniemi's electronic musical instruments. The data set produced as a part of the PhD project "User Stories of Erkki Kurenniemi’s Electronic Musical Instruments" by Mikko Ojanen.</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.