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5,027 results for “Culture”
1830 Map of Land Cover and Cultural Features in Massachusetts
Background and Data Limitations The Massachusetts 1830 map series represents a unique data source that depicts land cover and cultural features during the historical period of widespread land clearing for agricultural. To our knowledge, Massachusetts is the only state in the US where detailed land cover information was comprehensively mapped at such an early date. As a result, these maps provide unusual insight into land cover and cultural patterns in 19th century New England. However, as with any historical data, the limitations and appropriate uses of these data must be recognized: (1) These maps were originally developed by many different surveyors across the state, with varying levels of effort and accuracy. (2) It is apparent that original mapping did not follow consistent surveying or drafting protocols; for instance, no consistent minimum mapping unit was identified or used by different surveyors; as a result, whereas some maps depict only large forest blocks, others also depict small wooded areas, suggesting that numerous smaller woodlands may have gone unmapped in many towns. Surveyors also were apparently not consistent in what they mapped as ‘woodlands’: comparison with independently collected tax valuation data from the same time period indicates substantial lack of consistency among towns in the relative amounts of ‘woodlands’, ‘unimproved’ lands, and ‘unimproveable’ lands that were mapped as ‘woodlands’ on the 1830 maps. In some instances, the lack of consistent mapping protocols resulted in substantially different patterns of forest cover being depicted on maps from adjoining towns that may in fact have had relatively similar forest patterns or in woodlands that ‘end’ at a town boundary. (3) The degree to which these maps represent approximations of ‘primary’ woodlands (i.e., areas that were never cleared for agriculture during the historical period, but were generally logged for wood products) varies considerably from town to town, depending on wheth
Optimizing laboratory cultures of <i>Gammarus fossarum</i> (Crustacea: Amphipoda) as a study organism in environmental sciences and ecotoxicology
<p>Supplemental code and data for Alther, Krähenbühl, Bucher & Altermatt (2022) 'Optimizing laboratory cultures of <em>Gammarus fossarum</em> (Crustacea: Amphipoda) as a study organism in environmental sciences and ecotoxicology' (DOI: 10.1016/j.scitotenv.2022.158730). The repository folder contains three text files and a corresponding R script.</p> <p>Rerunning the analysis and producing figures requires two raw data files: LabdataAK_v6_210616_Daylength_input.txt and Nutrition_Exp_KaplanMeier_v1_input.txt. In order to reproduce the analysis and figures, run 'AmphipodHusbandry_20220919.R'. Make sure that your working directory is the folder containing all data files, easily achieved by (re)starting R (or R Studio) by double-clicking the R script file in the folder. The analysis script will produce all the figures from the paper, organized in a folder 'Results' and a subfolder 'Supplement'. Figures are prepared as pixel graphics (PNG).</p> <p>The R script was tested in R ver. 4.1.1 (Windows 10, version 21H1), 4.1.3 (macOS 11.6), and 4.2.0 (Ubuntu 22.04. Required packages are survival (version 3.2-13 worked), survminer (version 0.4.9 worked), and vioplot (version 0.3.7 worked).</p>
Cross cultural tears: A systematic investigation of the interpersonal effects of emotional crying across different cultural backgrounds
<p>The present project wants to examine the importance of emotional crying as an attachment behaviour and its fundamental role across a number of diverse cultures.</p> <p>Emotional tears are uniquely human and have fascinated scholars across several decades (Vingerhoets, 2013). Some researchers argue that tearful crying played a significant role in the evolution of humankind with regard to social development and solidarity (Walter, 2006). Recent years have seen an increased interest in exploring the interpersonal effects of human tears (see Gračanin, Bylsma, & Vingerhoets, 2018 for a review), with findings that emotional tears foster approach or support behavior (Gračanin, Krahmer, Rinck, & Vingerhoets, 2018) and crying individuals being evaluated as more communal (e.g., Zickfeld, van de Ven, Schubert, & Vingerhoets, 2018). These findings generally fit the hypothesis that emotional tears constitute a social act, promote social bonding and fulfill an attachment function (Nelson, 2005; Bowlby, 1982; Gračanin, Bylsma, et al., 2018; Murube, Murube, & Murube, 1999; Radcliffe-Brown, 1922; Vingerhoets, 2013). The present projects aims to answer the question whether emotional tears present a fundamental form of solidarity and bonding and whether the findings on increased attributions of warmth and higher approach intentions for tearful individuals replicate across a number of diverse contexts.</p> <p><a href="https://osf.io/fj9bd">Published in OSF: https://osf.io/fj9bd</a>.</p> <p>The OPen SCience FRamework also includes:</p> <ul> <li>Data from the pilot study: https://osf.io/txcw3/</li> <li>General information about the translation process (including the Portuguese version https://osf.io/t4cas/),</li> <li>Data management and research protocol (https://osf.io/5bh7m/),</li> <li>Approvals from ethical committees (https://osf.io/v8rqh/),</li> <li>Data and descriptive document of supplementary analyses (https://osf.io/s8ack/),</li> <li>Data and syntax (https://osf.io/x2pks/),</li> <li>Information about stimuli (https://osf.io/x2pks/) </li> </ul>
Greenhouse mixed culture experiment from August 2002 to April 2003 (FCE): Evaluate the effect of salinity and hydroperiod on interspecific mangrove seedlings growth rate (mixed culture) / Morphometric variables
A greenhouse experiment (mixed culture experiment) was performed for 8 months to evaluate the effect of salinity and hydroperiod on seedling growth rates of 2 mangrove species( Laguncularia racemosa and Rizhophora mangle). Data analyses are currently being performed.
BIOLOGICAL DATA in CO2 budget of cultured mussels metabolism in the highly productive Northwest Iberian upwelling system
<p>BIOLOGICAL DATA to estimate the carbon dioxide budget of cultured mussels metabolism in the highly productive Northwest Iberian upwelling system.</p> <p>Álvarez-Salgado et al. (2022) estimate the carbon dioxide and total alkalinity budgets due to the Mediterranean mussels (Mytilus galloprovicialis) growing in suspended culture in a low seston environment such as the Galician Rías (NW Spain). This database contains the biological data needed to estimate the carbon dioxide fluxes and changes in total alkalinity induced by the different biological processes involved in mussel growth. </p> <p>Manuscript available at: <a href="https://doi.org/10.1016/j.scitotenv.2022.157867">https://doi.org/10.1016/j.scitotenv.2022.157867</a></p> <p>Álvarez-Salgado, X.A., Fernández-Reiriz, M.J., Fuentes-Santos, I., Antelo, L.T., Alonso, A.A., Labarta, U., 2022. CO2 budget of cultured mussels metabolism in the highly productive Northwest Iberian upwelling system. Sci. Total Environ. 849, 157867.</p>
Participatory activities good practices in the field of cultural heritage (REACH project)
<p>The REACH repository of good practices comprises over a hundred and twenty records of European and extra European participatory activities in the field of cultural heritage, with an emphasis on small-scale, localised examples, but including also larger collaborative projects and global or distributed online initiatives. Located in over twenty different countries, the activities showcased here cover a wide variety of topics and themes, from urban, rural and institutional heritage to indigenous and minority heritage; from preservation, and management to use and re-use of cultural heritage. This easy-to-use collection of good practices offers professionals, practitioners, researchers and citizens useful information about activities which could be transferred, adapted or replicated in new contexts.</p>
Dataset for 'A Matter of Culture? Conceptualising and Investigating 'Evidence Cultures' within Research on Evidence-Informed Policymaking'
<p><strong><span>Introduction</span></strong><strong><span><br></span></strong><span>This document describes the data collection and datasets used in the manuscript "A Matter of Culture? Conceptualising and Investigating ‘Evidence Cultures’ within Research on Evidence-Informed Policymaking" <span>[1].</span></span></p> <p><strong><span>Data Collection</span></strong></p> <p><span>To construct the citation network analysed in the manuscript, we first designed a series of queries to capture a large sample of literature exploring the relationship between evidence, policy, and culture from various perspectives. Our team of domain experts developed the following queries based on terms common in the literature. These queries search for the terms included in the titles, abstracts, and associated keywords of WoS indexed records (i.e. ‘TS=’). While these are separated below for ease of reading, they combined into a single query via the OR operator in our search. Our search was conducted on the Web of Science’s (WoS) Core Collection through the University of Edinburgh Library subscription on 29/11/2023, returning a total of <strong><u>2,089 records</u></strong>.</span></p> <p><em><span>TS = ((“cultures of evidence” OR “culture of evidence” OR “culture of knowledge” OR “cultures of knowledge” OR “research culture” OR “research cultures” OR “culture of research” OR “cultures of research” OR “epistemic culture” OR “epistemic cultures” OR “epistemic community” OR “epistemic communities” OR “epistemic infrastructure” OR “evaluation culture” OR “evaluation cultures” OR “culture of evaluation” OR “cultures of evaluation” OR “thought style” OR “thought styles” OR “thought collective” OR “thought collectives” OR “knowledge regime” OR “knowledge regimes” OR “knowledge system” OR “knowledge systems” OR “civic epistemology” OR “civic epistemologies”) AND (“policy” OR “policies” OR “policymaking” OR “policy making” OR “policymaker” OR “policymakers” OR “policy maker” OR “policy makers” OR “policy decision” OR “policy decisions” OR “political decision” OR “political decisions” OR “political decision making”))</span></em></p> <p><em><span>OR</span></em></p> <p><em><span>TS = ((“culture” OR “cultures”) AND ((“evidence-based” OR “evidence-informed” OR “evidence-led” OR “science-based” OR “science-informed” OR “science-led” OR “research-based” OR “research-informed” OR “evidence use” OR “evidence user” OR “evidence utilisation” OR “evidence utilization” OR “research use” OR “researcher user” OR “research utilisation” OR “research utilization” OR “research in” OR “evidence in” OR “science in”) NEAR/1 (“policymaking” OR “policy making” OR “policy maker” OR “policy makers”)))</span></em></p> <p><em><span>OR</span></em></p> <p><em><span>TS = ((“culture” OR “cultures”) AND (“scientific advice” OR “technical advice” OR “scientific expertise” OR “technical expertise” OR “expert advice”) AND (“policy” OR “policies” OR “policymaking” OR “policy making” OR “policymaker” OR “policymakers” OR “policy maker” OR “policy makers” OR “political decision” OR “political decisions” OR “political decision making”))<span> </span></span></em></p> <p><em><span>OR</span></em></p> <p><em><span>TS = ((“culture” OR “cultures”) AND (“post-normal science” OR “trans-science” OR “transdisciplinary” OR “transdisiplinarity” OR “science-policy interface” OR “policy sciences” OR “sociology of knowledge” OR “sociology of science” OR “knowledge transfer” OR “knowledge translation” OR “knowledge broker” OR “implementation science” OR “risk society”) AND (“policymaking” OR “policy making” OR “policymaker” OR “policymakers” OR “policy maker” OR “policy makers”))</span></em></p> <p><strong><span>Citation Network Construction</span></strong></p> <p><span>All bibliographic metadata on these 2,089 records were downloaded in five batches in plain text and then merged in R. We then parsed these data into network readable files. All unique reference strings are given unique node IDs. A node-attribute-list (‘CE_Node’) links identifying information of each document with its node ID, including authors, title, year of publication, journal WoS ID, and WoS citations. An edge-list (‘CE_Edge’) records all citations from these documents to their bibliographies – with edges going <em>from</em> a citing document <em>to</em> the cited – using the relevant node IDs. These data were then cleaned by (a) matching DOIs for reference strings that differ but point to the same paper, and (b) manual merging of obvious duplicates caused by referencing errors.</span></p> <p><span>Our initial dataset consisted of 2,089 <em>retrieved</em> documents and 123,772 <em>unretrieved</em> cited documents (i.e. documents that were cited within the publications we retrieved but which were not one of these 2,089 documents). These documents were connected by 157,229 citation links, but ~87% of the documents in the network were cited just once. To focus on relevant literature, we filtered the network to include <em>only</em> documents with at least three citation or reference links. We further refined the dataset by focusing on the main connected component, resulting in 6,650 nodes and 29,198 edges. <strong><u>It is this dataset that we publish here</u></strong>, and it is this network that underpins Figure 1, Table 1, and the qualitative examination of documents (see manuscript for further details). </span></p> <p><span>Our final network dataset contains 1,819 of the documents in our original query (~87% of the original retrieved records), and 4,831 documents not retrieved via our Web of Science search but cited by at least three of the retrieved documents. We then clustered this network by modularity maximization via the Leiden algorithm <span>[2]</span>, detecting 14 clusters with Q=0.59. Citations to documents within the same cluster constitute ~77% of all citations in the network. </span></p> <p><strong><span>Citation Network Dataset Description</span></strong></p> <p><span>We include two network datasets: (i) ‘CE_Node.csv’ that contains 1,819 retrieved documents, 4,831 unretrieved referenced documents, making for a total of 6,650 documents (nodes); (ii)’CE_Edge.csv’ that records citations (edges) between the documents (nodes), including a total of 29,198 citation links. These files can be used to construct a network with many different tools, but we have formatted these to be used in Gephi 0.10<span>[3]</span>. </span></p> <p><strong><span>‘CE_Node.csv’</span></strong><span> is a comma-separate values file that contains two types of nodes: </span></p> <p><span><span>i.<span> </span></span></span><span>Retrieved documents – these are documents captured by our query. These include full bibliographic metadata and reference lists. </span></p> <p><span><span>ii.<span> </span></span></span><span>Non-retrieved documents – these are documents referenced by our retrieved documents but were not retrieved via our query. These only have data contained within their reference string (i.e. first author, journal or book title, year of publication, and possibly DOI). </span></p> <p><span>The columns in the .csv refer to:</span></p> <p><span><span>-<span> </span></span></span><em><span>Id</span></em><span>, the node ID</span></p> <p><span><span>-<span> </span></span></span><em><span>Label</span></em><span>, the reference string of the document</span></p> <p><span><span>-<span> </span></span></span><em><span>DOI</span></em><span>, the DOI for the document, if available</span></p> <p><span><span>-<span> </span></span></span><em><span>WOS_ID</span></em><span>, WoS accession number</span></p> <p><span><span>-<span> </span></span></span><em><span>Authors</span></em><span>, named authors</span></p> <p><span><span>-<span> </span></span></span><em><span>Title</span></em><span>, title of document</span></p> <p><span><span>-<span> </span></span></span><em><span>Document_type</span></em><span>, variable indicating whether a document is an article, review, etc.</span></p> <p><span><span>-<span> </span></span></span><em><span>Journal_book_title, </span></em><span>journal of publication or title of book</span></p> <p><span><span>-<span> </span></span></span><em><span>Publication year</span></em><span>, year of publication.</span></p> <p><span><span>-<span> </span></span></span><em><span>WOS_times_cited</span></em><span>, total Core Collection citations as of 29/11/2023</span></p> <p><span><span>-<span> </span></span></span><em><span>Indegree</span></em><span>, number of <strong><em>within</em></strong> network citations to a given document</span></p> <p><span><span>-<span> </span></span></span><em><span>Cluster</span></em><span>, provides the cluster membership number as discussed in the manuscript (Figure 1)</span></p> <p><strong><span>‘CE_Edge.csv’</span></strong><span> is a comma-separated values file that contains edges (citation links) between nodes (documents) (<em>n</em>=29,198). The columns refer to:</span></p> <p><span><span>-<span> </span></span></span><em><span>Source</span></em><span>, node ID of the <em>citing</em> document</span></p> <p><span><span>-<span> </span></span></span><em><span>Target, </span></em><span>node ID of the <em>cited</em> document</span></p> <p><strong><span>Cluster Analysis</span></strong></p> <p><span>We qualitatively analyse a set of publications from seven of the largest clusters in our manuscript. For this, we calculated the within cluster indegree of nodes, and read through the 10 most cited retrieved documents and 10 most cited unretrieved documents. To generate these lists, sub-graphs for each cluster needed to be generated, and then indegree was measured (i.e. counting the number of citations from papers within a cluster to other papers in that same cluster).</span></p> <p><strong><span>Notes</span></strong></p> <p><a href="https://zenodo.org/records/6615221#_ftnref1"><span>[1]</span></a><span> Bandola-Gill, J., Andersen, N., Leng, R. I., Pattyn, V., & Smith, K. E. (forthcoming). A Matter of Culture? Conceptualising and Investigating ‘Evidence Cultures’ within Research on Evidence-Informed Policymaking. Policy and Society</span></p> <p><a href="https://zenodo.org/records/6615221#_ftnref6"><span>[2]</span></a><span> Traag, V. A., Waltman, L., & van Eck, N. J. (2019). From Louvain to Leiden: guaranteeing well-connected communities. Scientific reports, 9(1), 5233. </span><a href="https://doi.org/10.1038/s41598-019-41695-z"><span>https://doi.org/10.1038/s41598-019-41695-z</span></a></p> <p><a href="https://zenodo.org/records/6615221#_ftnref5"><span>[3]</span></a><span> Bastian, M., Heymann, S., & Jacomy, M. (2009). Gephi: an open source software for exploring and manipulating networks. International AAAI Conference on Weblogs and Social Media. Gephi is available via </span><a href="https://gephi.org/"><span>https://gephi.org/</span></a></p> <p><span> </span></p>
Cross-Cultural Dataset
<p>For researchers and professionals, it is very important to analyze the cross-cultural differences in different disciplines. As the international impact is increasing and international events are becoming popular, the need to develop some automatic methods is significantly increasing. We choose the top 10 daily read newspapers in the world in 2020 and collect the events reported by these newspapers using Event Registry over the time period of 2016-2020. Event Registry. approximately 8000 events belong to each newspaper except Zaman (only 900 events). </p>
Cultural heritage adaptive reuse in Salerno: challenges and solutions. Dataset
<p>Dataset analysed in Pintossi, N., Ikiz Kaya, D., Pereira Roders, A. (2023). Cultural heritage adaptive reuse in Salerno: Challenges and solutions. City, Culture and Society, 100505. https://doi.org/10.1016/j.ccs.2023.100505</p> <ul> <li>Date of data collection: 27/11/2018</li> <li>Geographic location of data collection: Salerno, Italy. The venue of the data collection is <em>Salone dei marmi, Palazzo di Città</em>, via Roma, 84121 Salerno, Italy </li> <li>Activity of data collection: Historic Urban Landscape workshop 2 - Salerno. Held in Salerno, Italy, on 26-27/11/2018</li> <li>Aim of data collection: Multi-scale, participatory identification of challenges entailed in the adaptive reuse of cultural heritage and solutions </li> <li>Methods for collection/generation of data: see the methodology section in Pintossi, N., Ikiz Kaya, D., Pereira Roders, A. (2023). Cultural heritage adaptive reuse in Salerno: Challenges and solutions. City, Culture and Society, 100505. https://doi.org/10.1016/j.ccs.2023.100505</li> <li>Researchers facilitating roundtable discussion and writing down paper version of data: Marco Acri, Gaia Daldanise, Gamze Dane, Cristina Garzillo, Antonia Gravagnuolo, Lu Lu, Nadia Pintossi, and Ruba Saleh</li> <li>Researcher translating to English, transcribing data in the digital tabular dataset, and cleaning the data: Nadia Pintossi</li> <li>Original language of the data: English, Italian, and mix of English and Italian</li> </ul>
Culture-Aware Music Recommendation Dataset
<p><strong>LFM-1b dataset extended by acoustic track features and cultural cues describing users</strong></p> <p> </p> <p>This dataset is based on the LFM-1b dataset (cf. <a href="http://www.cp.jku.at/datasets/LFM-1b/">http://www.cp.jku.at/datasets/LFM-1b/</a>), however, adds acoustic features describing the tracks to the original dataset as well as cultural aspects describing users (taken from Hofstede's six dimension model and the World Happiness Report) on the country-level.</p> <p>For the creation of the dataset, we extract all users for which the original dataset contains country information for. We extract the listening events of these users and match the tracks against the Spotify API to subsequently retrieve the acoustic features of these tracks (cf. [Spotify Audio Feature Description](https://developer.spotify.com/documentation/web-api/reference/object-model/#audio-features-object)). The final dataset contains only events of users with country information and tracks with acoustic features, which can be matched with the country-level data of the World Happiness Report and Hofstede's cultural dimensions to add cultural and socio-economic aspects for users.</p> <p>This new dataset contains</p> <ul> <li>55,190 users</li> <li>3,471,884 tracks including acoustic features</li> <li>351,469,333 listening events of those users for tracks we have obtained acoustic features for</li> <li>Hofstede's cultural dimensions for 47 countries</li> <li>World Happiness Report (WHR) data for 164 countries</li> </ul> <p> </p> <p><strong>Files</strong><br> All files are tab-separated, with no quoting of strings. The dataset contains the following files, whose content we describe in more detail in the following parts.</p> <p>* acoustic_features_lfm_id.tsv: acoustic features for all tracks in the dataset, identified by their LFM track identifier<br> * events.tsv: listening events for all users<br> * hofstede.tsv: Hofstede's cultural dimensions<br> * users.tsv: user metadata<br> * world_happiness_report_2018.tsv: World Happiness Report data</p> <p>For further information on the contents of these files, please cf. the Readme file.</p> <p> </p> <p>Please cite the following paper when using the dataset:<br> Zangerle, E., Pichl, M. and Schedl, M., 2020. User Models for Culture-Aware Music Recommendation: Fusing Acoustic and Cultural Cues. <em>Transactions of the International Society for Music Information Retrieval</em>, 3(1), pp.1–16. DOI: <a href="http://doi.org/10.5334/tismir.37">http://doi.org/10.5334/tismir.37</a></p>
Plant regeneration in leaf culture of Centaurium erythraea Rafn. Part 3: de novo transcriptome assembly and validation of housekeeping genes for studies of in vitro morphogenesis
<p>Six centaury transcriptomes (embryogenic calli, globular somatic embryos, cotyledonary somatic embryos, adventitious buds, leaves and roots of <em>in vitro</em> grown plants) were sequenced and <em>de novo</em> assembled using <a href="https://github.com/trinityrnaseq/trinityrnaseq/wiki">Trinity</a> .</p> <p><a href="https://zenodo.org/api/files/a0546879-e382-4cf9-8185-f188d1a0c5f0/CE_Assembly.tar.gz">CE_Assembly.tar.gz</a> - Centaury referent transcriptome comprises of 160.839 Trinity transcripts grouped in 105.726 Trinity genes.</p> <p><a href="https://zenodo.org/api/files/a0546879-e382-4cf9-8185-f188d1a0c5f0/CE_Assembly_fpkm.tar.gz">CE_Assembly_fpkm.tar.gz</a> - fpkm normalized read counts of the assembled transcripts in the six sequenced centaury tissues.</p> <p><a href="https://zenodo.org/api/files/a0546879-e382-4cf9-8185-f188d1a0c5f0/nt.db_CE_assembly.tar.gz">nt.db_CE_assembly.tar.gz</a> - annotation of assembled transcripts by mapping them against NCBI nucleotide (NT) database using BLASTn . The obtained results were filtered with E-value E ≤ 10<sup>-3</sup>.</p> <p><a href="https://zenodo.org/api/files/a0546879-e382-4cf9-8185-f188d1a0c5f0/swissprot.db_CE_assembly.tar.gz">swissprot.db_CE_assembly.tar.gz</a> - annotation of assembled transcripts by mapping them against NCBI nucleotide (<a href="https://zenodo.org/api/files/a0546879-e382-4cf9-8185-f188d1a0c5f0/swissprot.db_CE_assembly.tar.gz">s</a>wissprot) database using BLASTx . The obtained results were filtered with E-value E ≤ 10<sup>-3</sup>.</p> <p><a href="https://zenodo.org/api/files/a0546879-e382-4cf9-8185-f188d1a0c5f0/pfam30.db_CE_assembly.tar.gz">pfam30.db_CE_assembly.tar.gz</a> - annotation of assembled transcripts by mapping them against Pfam30 domain database using hmmer3. The obtained results were filtered with independent E-value E ≤ 10<sup>-3</sup>.</p>
Deep reinforcement learning for the control of microbial co-cultures in bioreactors
<p>Data for the figures in the paper:<br> <a href="https://www.biorxiv.org/content/10.1101/457366v2">https://www.biorxiv.org/content/10.1101/457366v2</a><br> (in press PLoS Comp Biol.)</p> <p>Abstract:<br> Multi-species microbial communities are widespread in natural ecosystems. When employed for biomanufacturing, engineered synthetic communities have shown increased productivity in comparison with monocultures and allow for the reduction of metabolic load by compartmentalising bioprocesses between multiple sub-populations. Despite these benefits, co-cultures are rarely used in practice because control over the constituent species of an assembled community has proven challenging. Here we demonstrate, in silico, the efficacy of an approach from artificial intelligence – reinforcement learning – for the control of co-cultures within continuous bioreactors. We confirm that feedback via reinforcement learning can be used to maintain populations at target levels, and that model-free performance with bang-bang control can outperform a traditional proportional integral controller with continuous control, when faced with infrequent sampling. Further, we demonstrate that a satisfactory control policy can be learned in one twenty-four hour experiment by running five bioreactors in parallel. Finally, we show that reinforcement learning can directly optimise the output of a co-culture bioprocess. Overall, reinforcement learning is a promising technique for the control of microbial communities.</p>
Cultures of Suntanning in late-19th to mid-20th century Britain
<p>Data collected in the project "Cultures of Suntanning in late 19th to mid-20th century Britain", British Academy Mid-Career Fellowship award number MCFSS22\220038.</p><p>Archive Dataset lists identifying details for all archive resources that were consulted during the project, with a note as to whether data was collected from each source.</p><p>Literary dataset lists identifying details for all literary resources consulted during the project, including digital concordances where used, with a note as to whether data was collected from each source.</p><p>The raw data collected cannot be made open access due to archive/copyright restrictions. The identifying details provide enough supplementary information for researchers to locate these resources.</p>
Phlorest phylogeny derived from Honkola et al. 2013 'Cultural and climatic changes shape the evolutionary history of the Uralic languages'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Honkola T, Vesakoski O, Korhonen K, Lehtinen J, Syrjänen K & Wahlberg N. 2013. Cultural and climatic changes shape the evolutionary history of the Uralic languages. Journal of Evolutionary Biology, 26(6):1244–1253.</p> </blockquote>
Acoustics, Audibility and Political Culture in the House of Commons, 1800-34
<p>This dataset includes the auralization results obtained from the acoustic models of the House of Commons in 1800-34, as part of the research with the homonymous paper submitted in the special issue "Parliamentary History Journal" (first submission September 2023). </p><p>The auralization results represent the perceived result from the acoustic models for the two discussed scenarios (full-occupied and half-full-occupied House of Commons). We present the results from 3 different speakers at 5 listening positions as shown in the images. </p><p>The anechoic sample is an excerpt of Henry Beaufoy's speech to the House of Commons in 1792 on the subject of the slave trade, performed by John Cooper (co-author) in the anechoic chamber at the Audiolab, University of York. The perceived differences and similarities of the recorded/simulated spaces as heard in these audio files help to further verify the results of the acoustic parameters presented in this paper.</p>
Untargeted metabolomics analysis of RPE cells during six month in culture
<p>Primary RPE cell cultures were established with human fetal RPE cells acquired from ScienCell (Cat. No, 6540) seeded at passage 3 (P3) in 12-well Transwell<sup>®</sup> inserts (Corning Inc., Cat. No. CLSS3460) coated with 2% v/v Geltrex<sup>®</sup> matrix (Thermo Fisher Scientific; Cat. No. A1413202). Cells were cultured for a total time of 6 months (25 weeks), following the same protocol as previous works (16,59). Samples were acquired for protein immunolocalization, transcriptomic and metabolomics analysis from independent cell cultures along the total 6 months culture time (specifically at 4, 12, 17 and 25 weeks in culture), collecting 3 biological replicates per type of analysis and time point.<em> </em>Cell metabolites were quenched and extracted using MeOH:H<sub>2</sub>O (80:20, -20ºC) containing a spiked solution of isotopically enriched low molecular mass internal standard<strong>. </strong>Quality control (QC) samples were prepared by creating a pool of equal volumes from each biological replicate and were analyzed after a blank solution every fifth sample to monitor the performance, stability, and reproducibility of the LC-MS run. A liquid chromatography (LC) system 1290 Infinity II (Agilent Technologies) was coupled to an Agilent 6560B Ion Mobility quadrupole-time-of-flight mass spectrometer (IM-QTOF-MS) equipped with an Agilent G1607A dual jetstream ESI source and the MassHunter WorkSation 11.0. A reference solution containing purine and hexakis(1H,1H,3H-tetrafluoropropoxy)phosphazene for mass correction was added using the second ESI source. Chromatographic, ion source and MS conditions were optimized using QCs and selected parameters are shown in Supporting Information. MS analysis was conducted with an untargeted approach, operating the instrument in both positive and negative ionization modes. All samples were analysed in a randomized order. Raw data was processed using the software Profinder B10.00 (Agilent) and refined data were exported as CEF files<strong>. </strong>Data were converted to mzml files using MS convert.</p>
Destruction of the Cultural-Archaeological Landscape in the Gaza Strip
This dataset contains 10 archaeological sites in Gaza strip destroyed during the war 2023-2024. The dataset was compiled by Ministry of Tourism & Antiquities of Palestine (MOTA) team, Dr. Sufyan Deis.
Standard Cross-Cultural Sample of Religion
<p>The Standard Cross-Cultural Sample of Religion is a product of the <a href="https://religiondatabase.org/" rel="nofollow">Database of Religious History (DRH)</a>. The DRH is a qualitative-quantitative encyclopedic database of historical religious data across time and space. Data are contributed to the project by academic <a href="https://religiondatabase.org/landing/about/people/experts" rel="nofollow">experts</a> and overseen by a panel of <a href="https://religiondatabase.org/landing/about/people/editors" rel="nofollow">editors</a>. The data take the form of answers (provided by experts) to a long list of standard questions grounded in time and space.</p> <p>The Standard Cross-Cultural Sample of Religion is “standard” in a different way than its namesake, The Standard Cross-Cultural Sample (SCCS). The SCCS was designed to control for region and cultural relatedness. Because of our mostly bottom-up, expert-driven data gathering method, DRH data is heavily overweighted in certain time/space regions. Analysts will have to control for this as they see fit.</p> <p>On the other hand, DRH data is “standard” in the sense that whatever Group, Place of Text is being portrayed, experts are answering a standardized set of questions, allowing a degree of comparison and quantitative analysis that has simply never been possible before. As the DRH grows, top-down data-gathering pushes will be targeted at underrepresented regions of the world, with the goal of making future versions of the SCCSR more and more comprehensive.</p> <p>The Standard Cross-Cultural Sample of Religion (SCCSR.v2) is provided under CC-BY-4.0 license.</p>
Research compendium for 'Refitting the Context: A Reconsideration of Cultural Change among Early Homo sapiens at Fumane Cave through Blade Break Connections, Spatial Taphonomy, and Lithic Technology'
<div> <h3>Compendium DOI:</h3> <p><a href="../doi/10.5281/zenodo.10965413">https://zenodo.org/doi/10.5281/zenodo.10965413</a> </p> </div> <p>The content available at the above provided URL will reproduce the results as documented in the publication. Instead, the files hosted at <a href="https://github.com/ArmandoFalcucci/Refitting-The-Context">https://github.com/ArmandoFalcucci/Refitting-The-Context</a> represent the developmental versions and might have undergone modifications since the paper's publication.</p> <div> <h3>Maintainer of this repository:</h3> </div> <p>Armando Falcucci (<a href="mailto:armando.falcucci@uni-tuebingen.de">armando.falcucci@uni-tuebingen.de</a>)</p> <div> <h3>Published paper:</h3> </div> <p>Armando Falcucci, Domenico Giusti, Filippo Zangrossi, Matteo De Lorenzi, Letizia Ceregatti, Marco Peresani. Refitting the Context: Revisiting the Aurignacian sequence at Fumane Cave through blade fragment connections, spatial taphonomy, and lithic technology. <em>Journal of Paleolithic Archaeology</em> (2024). DOI: <a href="https://doi.org/10.1007/s41982-024-00203-0" rel="nofollow">10.1007/s41982-024-00203-0</a></p> <div> <h3>Abstract:</h3> </div> <p>High-resolution stratigraphic frameworks are crucial for unraveling the biocultural processes behind the dispersals of Homo sapiens across Europe. Detailed technological studies of lithic assemblages retrieved from multi-stratified sequences allow archaeologists to precisely model the chrono-cultural dynamics of the early Upper Paleolithic. However, it is of paramount importance to verify the integrity of these assemblages before building explanatory models of cultural change. In this study, multiple lines of evidence suggest that the stratigraphic sequence of Fumane Cave in northeastern Italy experienced minor post-depositional reworking, establishing it as a pivotal site for exploring the earliest stages of the Aurignacian. By conducting a systematic search for break connections between blade fragments and applying spatial analysis techniques, we identified three well-preserved areas of the excavation containing assemblages suitable for renewed archaeological investigations. Subsequent technological analyses, incorporating attribute analysis, reduction intensity, and multivariate statistics, have allowed us to discern the spatial organization of the site during the formation of the Protoaurignacian palimpsest A2–A1. Moreover, diachronic comparisons between three successive stratigraphic units prompted us to reject the hypothesis of techno-cultural continuity of the Protoaurignacian in northeastern Italy after the onset of the Heinrich Event 4. Based on the variability of the lithic and osseous artifacts, the most recent assemblage analyzed, D3b alpha, is now ascribed to the Early Aurignacian, aligning the evidence from Fumane with the current understanding of the development of the Aurignacian across Europe. Overall, this study demonstrates the high effectiveness of the break connection method when combined with detailed spatial analysis and lithic technology, providing a methodological tool particularly amenable to be applied to sites excavated in the past with varying degrees of recording accuracy.</p> <div> <h3>Keywords:</h3> </div> <p>Protoaurignacian; Early Aurignacian; Lithics; Refittings; Assemblage integrity; Spatial analysis; Italy</p> <div> <h3>Overview of contents and how to reproduce:</h3> </div> <p>Within this repository, various folders house data (<code>data</code>), code (<code>script</code>), and output files (<code>output</code>) pertinent to the paper. The data folder encompasses the blank and core datasets from the Aurignacian of Fumane Cave and the dataset of the blade fragment connection study. To replicate the results, download the entire repository and employ <code>Refitting-The-Context.Rproj</code> and open the folder <code>script</code>. For ensuring reproducibility, the <code>renv</code> package (v. 1.0.3) was utilized, following the procedures detailed in its vignette. All analyses and visualizations in the paper were conducted using R 4.3.1 on Microsoft Windows 10.0.19045 (64-bit). As the necessary packages are available in the <code>renv</code> folder, they are not explicitly listed here.</p> <div> <h3>Licenses:</h3> </div> <p>Code: <strong>MIT</strong> <a href="http://opensource.org/licenses/MIT" rel="nofollow">http://opensource.org/licenses/MIT</a>, copyright holder: Armando Falcucci (2024).</p> <p>Data and intellectual work: <strong>Creative Commons Attribution 4.0 International License</strong> (<a href="http://creativecommons.org/licenses/by/4.0/" rel="nofollow">http://creativecommons.org/licenses/by/4.0/</a>), copyright holder: the authors (2024).</p>
Land based IMTA culture of abalone (Haliotis tuberculata) juvenile, anemone (Anemona sulcata) and Ulvella lens
<p>France Haliotis implemented a co-culture trial in abalone (Haliotis tuberculata) nursery tanks in a flow through system in order to improve growth and survival of abalone juveniles, reduce amphipods and copepods populations while recycling nutrients</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.