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Great Britain Accessibility Indicators 2023 (AI23)
<p><strong>Overview</strong></p> <p>Accessibility indicators measure the ease of reaching valuable destinations (Levinson and Wu 2020). The current dataset, Great Britain Accessibility Indicators 2023 (AI23), provides small-area indicators to key services such as health, education, employment, and urban centres.</p> <p>This dataset is an updated and expanded version of the the <a href="https://zenodo.org/records/8037156">Public Transport Accessibility Indicators for Great Britain 2022</a> (PTAI22) dataset (available at: https://zenodo.org/records/8037156, and described at: https://www.nature.com/articles/s41597-023-02890-w) (J. Rafael Verduzco Torres and McArthur 2024).</p> <p>In particular, the AI23 dataset provides a suite of ready-to-use accessibility indicators by public transport,<br>bicycle, and on foot to employment, general practices (GPs), hospitals, pharmacies, parks and gardens,<br>primary and secondary schools, supermarkets, main urban centres, and urban sub-centres. These indicators<br>are available for 42,000 small area units across Great Britain (GB), specifically at the Lower Super Output<br>Area (LSOA) level in England and Wales, and the Data Zone (DZ) level in Scotland. It includes active modes, specifically walking and cycling, in addition to public transport.</p> <p>A full data descriptor is available <a href="https://osf.io/preprints/socarxiv/qb9j4_v1">here</a> (URL: https://osf.io/preprints/socarxiv/qb9j4_v1) (Verduzco Torres & McArthur, 2024b).</p> <p> </p> <p><strong>Records</strong></p> <table> <tbody> <tr> <td> <p><strong>Variable</strong></p> </td> <td> <p><strong>Description </strong></p> </td> </tr> <tr> <td> <p><strong>geo_code</strong></p> </td> <td> <p>2011 LSOA/DZ geo-code of origin</p> </td> </tr> <tr> <td> <p><strong>mode</strong></p> </td> <td> <p>Mode of transport used for the indicators, values: 'pt' = public transport, 'bicycle', 'walk'</p> </td> </tr> <tr> <td> <p><strong>time_of_day</strong></p> </td> <td> <p>Time of departure, values: 'am' = 7 a.m., 'pm' = 9 p.m. Available for public transport only.</p> </td> </tr> <tr> <td> <p><strong>access_<NAME OF SERVICE>_15</strong></p> </td> <td> <p>Cumulative accessibility: Number of services of type k within 15 minutes</p> </td> </tr> <tr> <td> <p><strong>access_<NAME OF SERVICE>_30</strong></p> </td> <td> <p>Cumulative accessibility: Number of services of type k within 30 minutes</p> </td> </tr> <tr> <td> <p><strong>access_<NAME OF SERVICE>_45</strong></p> </td> <td> <p>Cumulative accessibility: Number of services of type k within 45 minutes</p> </td> </tr> <tr> <td> <p><strong>access_<NAME OF SERVICE>_60</strong></p> </td> <td> <p>Cumulative accessibility: Number of services of type k within 60 minutes</p> </td> </tr> <tr> <td> <p><strong>access_<NAME OF SERVICE>_75</strong></p> </td> <td> <p>Cumulative accessibility: Number of services of type k within 75 minutes</p> </td> </tr> <tr> <td> <p><strong>access_<NAME OF SERVICE>_90</strong></p> </td> <td> <p>Cumulative accessibility: Number of services of type k within 90 minutes</p> </td> </tr> <tr> <td> <p><strong>access_<NAME OF SERVICE>_105</strong></p> </td> <td> <p>Cumulative accessibility: Number of services of type k within 105 minutes</p> </td> </tr> <tr> <td> <p><strong>access_<NAME OF SERVICE>_120</strong></p> </td> <td> <p>Cumulative accessibility: Number of services of type k within 120 minutes</p> </td> </tr> <tr> <td> <p><strong>access_<NAME OF SERVICE>_15_pct</strong></p> </td> <td> <p>Relative cumulative accessibility: Number of services of type k within 15 minutes. In percent, from 0 to 100.</p> </td> </tr> <tr> <td> <p><strong>access_<NAME OF SERVICE>_30_pct</strong></p> </td> <td> <p>Relative cumulative accessibility: Number of services of type k within 30 minutes. In percent, from 0 to 100.</p> </td> </tr> <tr> <td> <p><strong>access_<NAME OF SERVICE>_45_pct</strong></p> </td> <td> <p>Relative cumulative accessibility: Number of services of type k within 45 minutes. In percent, from 0 to 100.</p> </td> </tr> <tr> <td> <p><strong>access_<NAME OF SERVICE>_60_pct</strong></p> </td> <td> <p>Relative cumulative accessibility: Number of services of type k within 60 minutes. In percent, from 0 to 100.</p> </td> </tr> <tr> <td> <p><strong>access_<NAME OF SERVICE>_75_pct</strong></p> </td> <td> <p>Relative cumulative accessibility: Number of services of type k within 75 minutes. In percent, from 0 to 100.</p> </td> </tr> <tr> <td> <p><strong>access_<NAME OF SERVICE>_90_pct</strong></p> </td> <td> <p>Relative cumulative accessibility: Number of services of type k within 90 minutes. In percent, from 0 to 100.</p> </td> </tr> <tr> <td> <p><strong>access_<NAME OF SERVICE>_105_pct</strong></p> </td> <td> <p>Relative cumulative accessibility: Number of services of type k within 105 minutes. In percent, from 0 to 100.</p> </td> </tr> <tr> <td> <p><strong>access_<NAME OF SERVICE>_120_pct</strong></p> </td> <td> <p>Relative cumulative accessibility: Number of services of type k within 120 minutes. In percent, from 0 to 100.</p> </td> </tr> <tr> <td> <p><strong>nearest_<NAME OF SERVICE></strong></p> </td> <td> <p>Travel time in minutes to the nearest service of type k</p> </td> </tr> </tbody> </table> <p> </p> <p><strong>Citation</strong></p> <p>If you use this dataset or part of it, you are encouraged to use the following citation:</p> <div> <div>1. J Rafael Verduzco Torres, & David McArthur. (2024). Great Britain Accessibility Indicators 2023 (AI23) (Version 2023) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.14778265</div> <div>2. Verduzco Torres, J. R., & McArthur, D. P. (2024). Public transport accessibility indicators to urban and regional services in Great Britain. <em>Scientific Data</em>, <em>11</em>(1). <a href="https://doi.org/10.1038/s41597-023-02890-w">https://doi.org/10.1038/s41597-023-02890-w</a></div> <div>3. Verduzco Torres, J. R., & McArthur, D. P. (2024a). <em>Great Britain Accessibility Indicators 2023: Data descriptor</em>. OSF. <a href="https://doi.org/10.31235/osf.io/qb9j4">https://doi.org/10.31235/osf.io/qb9j4</a></div> </div> <pre><code><br>@article{VerduzcoTorres2024,<br> title = {Public Transport Accessibility Indicators to Urban and Regional Services in {{Great Britain}}},<br> author = {Verduzco Torres, J. Rafael and McArthur, David Philip},<br> year = {2024},<br> month = jan,<br> journal = {Scientific Data},<br> volume = {11},<br> number = {1},<br> pages = {53},<br> publisher = {{Nature Publishing Group}},<br> doi = {10.1038/s41597-023-02890-w},<br> urldate = {2024-01-15},<br> }<br> @article{VerduzcoTorres2024a,<br> title = {Great {{Britain Accessibility Indicators}} 2023: {{Data}} Descriptor},<br> shorttitle = {Great {{Britain Accessibility Indicators}} 2023},<br> author = {Verduzco Torres, Jose Rafael and McArthur, David Philip},<br> date = {2024-03-23},<br> eprinttype = {OSF},<br> doi = {10.31235/osf.io/qb9j4},<br> url = {https://osf.io/qb9j4},<br> urldate = {2024-03-25}<br>} </code></pre> <p> </p> <p> </p>
FI GU R E 3 Maximum likelihood phylogenetic tree of the Hyalospheniformes with a focus on Apodera, Alocodera, and Padaungiella based on COI gene sequences. Bootstrap values (bs) and Bayesian posterior probabilities (p.p.) are indicated respectively between branches. COI sequences from genera other than Apodera were retrieved from GenBank in Superficially described and ignored for 92 years, rediscovered and emended: Apodera angatakere (Amoebozoa: Arcellinida: Hyalospheniformes) is a new flagship testate amoeba taxon from Aotearoa (New Zealand)
FI GU R E 3 Maximum likelihood phylogenetic tree of the Hyalospheniformes with a focus on Apodera, Alocodera, and Padaungiella based on COI gene sequences. Bootstrap values (bs) and Bayesian posterior probabilities (p.p.) are indicated respectively between branches. COI sequences from genera other than Apodera were retrieved from GenBank
SIRIUS Project - comparative dataset on socio-cultural, political and legal indicators
<p>This is an ad hoc dataset on socio-economic, cultural, political and legal indicators on migration covering all SIRIUS countries (Czech Republic, Denmark, Finland, Greece, Italy, Switzerland, United Kingdom), created by retrieving and systematizing a number of indicators available in the most relevant databases.</p> <p>The dataset has been created as part of the work package 2 of the SIRIUS Project "Skills and Integration of Migrants, Refugees and Asylum Applicants in European Labour markets". The work package, titled “Legal barriers and enablers”, examined the legal and institutional framework of migration and asylum, integrated with critical insights on the cultural and socio-economic environment of the SIRIUS countries. </p> <p><strong>Acknowledgments and disclaimers</strong><br> This research was conducted under the Horizon 2020 project ‘SIRIUS’ (770515).<br> The sole responsibility of this publication lies with the author. The European Union is not responsible for any use that may be made of the information contained therein.</p>
nal; E', F', internal, G'-J', Pal. 1341 (peripheral 8); G', H', external; I', J', internal; K'-N', Pal. 1343 (peripheral 9); K', L', external; M', N', internal; O'-R', Pal. 1345 (peripheral 10); O', P', external; Q', R', internal; S'-V', Pal. 1348 (peripheral 11); S', T', external; U', V', internal views; W', reconstruction of carapace Thick lines correspond to scute sulci, dotted lines denote plate sutures, and oblique lines indicate missing plate portions. Abbreviations: Ce, cervical; co, costal; Ma, marginal; ne, neural; nu, nuchal; per, peripheral; Pl, pleural; py, pygal; sp, suprapygal; Spr, supracaudal; Ve, vertebral. Scale bars: A-V', 1 cm; W', 2.5 cm. in Fossil turtles from the early Miocene localities of Mokrá-Quarry (Burdigalian, MN4), South Moravian Region, Czech Republic
nal; E', F', internal, G'-J', Pal. 1341 (peripheral 8); G', H', external; I', J', internal; K'-N', Pal. 1343 (peripheral 9); K', L', external; M', N', internal; O'-R', Pal. 1345 (peripheral 10); O', P', external; Q', R', internal; S'-V', Pal. 1348 (peripheral 11); S', T', external; U', V', internal views; W', reconstruction of carapace Thick lines correspond to scute sulci, dotted lines denote plate sutures, and oblique lines indicate missing plate portions. Abbreviations: Ce, cervical; co, costal; Ma, marginal; ne, neural; nu, nuchal; per, peripheral; Pl, pleural; py, pygal; sp, suprapygal; Spr, supracaudal; Ve, vertebral. Scale bars: A-V', 1 cm; W', 2.5 cm.
sal; W, visceral; X-Z, Pal. 1308 (costal 5); X, Y, dorsal; Z, visceral; A'-C', Pal. 1309 (costal 6); A', B', dorsal; C', visceral; D'-F', Pal. 1310 (costal 8); D', E', dorsal; F', visceral; G'-J', Pal. 1312 (peripheral 1); G', H', dorsal; I', J', visceral; K'-N', Pal. 1313 (peripheral 7); K', L', dorsal; M', N', visceral; O'-R', Pal. 1314 (peripheral 8); O', P', dorsal; Q', R', visceral views; S', reconstruction of carapace. Thick lines indicate to scute sulci, dotted lines sutures and oblique lines denote missing plate portions. Abbreviations: Ce, cervical; co, costal; Ma, marginal; ne, neural; nu, nuchal; per, peripheral; Pl, pleural; py, pygal; sp, suprapygal; Ve, vertebral. Scale bars: 1 cm. in Fossil turtles from the early Miocene localities of Mokrá-Quarry (Burdigalian, MN4), South Moravian Region, Czech Republic
sal; W, visceral; X-Z, Pal. 1308 (costal 5); X, Y, dorsal; Z, visceral; A'-C', Pal. 1309 (costal 6); A', B', dorsal; C', visceral; D'-F', Pal. 1310 (costal 8); D', E', dorsal; F', visceral; G'-J', Pal. 1312 (peripheral 1); G', H', dorsal; I', J', visceral; K'-N', Pal. 1313 (peripheral 7); K', L', dorsal; M', N', visceral; O'-R', Pal. 1314 (peripheral 8); O', P', dorsal; Q', R', visceral views; S', reconstruction of carapace. Thick lines indicate to scute sulci, dotted lines sutures and oblique lines denote missing plate portions. Abbreviations: Ce, cervical; co, costal; Ma, marginal; ne, neural; nu, nuchal; per, peripheral; Pl, pleural; py, pygal; sp, suprapygal; Ve, vertebral. Scale bars: 1 cm.
Data and codes related to the article: Renard et al. A Hidden Climate Indices Modeling Framework for Multi-Variable Space-Time Data. Water Resources Research.
<p>This package contains data and codes related to the article:</p> <p>B. Renard, M. Thyer, D. McInerney, D. Kavetski, M. Leonard and S. Westra. A Hidden Climate Indices Modeling Framework for Multi-Variable Space-Time Data. <em>Water Resources Research</em>.</p> <p><strong>R scripts</strong></p> <p>The main computations of the paper have been performed using a computing code named <a href="https://github.com/STooDs-tools">STooDs</a>, which is called using the bash script launchpad.sh.</p> <p>The R scripts in this package only perform pre-processing (create configuration files) and post-processing (analyze results) steps.</p> <ul> <li>Funk.R: a set of functions called by other scripts.</li> <li>1_defineModel.R: define the model to be inferred and create STooDs configuration files in <em>dataset_XXX/runs.</em></li> <li>2_analyzeResults.R: analyze the outputs of STooDs runs.</li> <li>3_crossValidation.R: analyze the outputs of cross-validation experiments in <em>dataset_XV</em> and <em>dataset_XV_1971-1990</em>.</li> </ul> <p><strong>Data</strong></p> <p>Data for the 3 cases (full dataset and 2 cross-validation experiments) are located in folders <em>dataset_XXX/data</em>.</p> <ul> <li>dat.txt: raw dataset in text format.</li> <li>dataset.RData: dataset in RData format.</li> <li>DMI.txt, NINO.txt, SAM.txt: 3 standard climate indices.</li> <li>spaceP.txt, spaceQ.txt, spaceT.txt: properties of Precipitation (P), Streamflow (Q) and Temperature (T) stations.</li> <li>[only for cross-validation experiments] validation.RData: left-out data used for validation.</li> </ul> <p> </p> <p> </p>
Fig. 1 in Five Trophically-transmitted Parasites from Adult Arctic Lampreys Lethenteron camtschaticum (Petromyzontiformes: Petromyzontidae): Biological Indicators of the Host's Marine Life as a Predator
Fig. 1. Endoparasites from adult Arctic lampreys Lethenteron camtschaticum (Tilesius, 1811) from the Ishikari River, Hokkaido. A, Brachyphallus crenatus (Rudolphi, 1802); B, Lecithaster gibbosus (Rudolphi, 1802); C, Nybelinia surmenicola (Okada in Dollfus, 1929); D, metabasal armature of a tentacle of N. surmenicola; E, tetraphyllidean plerocercoid; F, male specimen of Bolbosoma sp.; G, female specimen of Bolbosoma sp. Scale bars: A–B, 500 µm; C, E–G, 2 mm; D, 50 µm.
Fig. 3 in Impact Of Coastal Wetland Restoration Strategies In The Chongming Dongtan Wetlands, China: Waterbird Community Composition As An Indicator
Fig. 3. Densities of Charadriidae (a), Anatidae (b), Ardeidae (c), and Laridae (d) among autumn, winter and spring in four sites. Error bars represent ±1 SE.
Fig. 3 in Hrabeiella Periglandulata (Annelida: "Polychaeta") Do Apparent Differences In Chaetal Ultrastructure Indicate The Existence Of Several Species In Europe?
Fig. 3. Hrabeiellaperiglandulata, chaetae, SEMmicrograph (thewormswerefixedinetha- nol, thespecimenfromSpainfixedinBouinsolution): A = anteriorpartofbodywiththree rowsofchaetaeofaspecimenfromBakonyMts, Hungary (ventro-lateralview), B = lateral chaetaeinthesecondrow (specimenfromBrno, CzechRepublic), C = chaetaeinthesecond row (ventralview, specimenfromVěncováhora (locustypicus), CzechRepublic), D = cha-
Fig. 1 in Hrabeiella Periglandulata (Annelida: "Polychaeta") Do Apparent Differences In Chaetal Ultrastructure Indicate The Existence Of Several Species In Europe?
Fig. 1. Distributionof Hrabeiellaperiglandulata inEuropebasedonrecordspreviouslypublished (circles) orreportedinthisstudy (squares).
Fig. 4 in Hrabeiella Periglandulata (Annelida: "Polychaeta") Do Apparent Differences In Chaetal Ultrastructure Indicate The Existence Of Several Species In Europe?
Fig. 4. SEMmicrographsof Hrabeiellaperiglandulata chaetaeshowingadifferentshape (the wormswerefixedonlyinethanol): A = LateralchaetaeofaspecimenfromHungary. B = Lateralchaetaeinthethirdrowofaspecimenfromnorth-westernCzechia. C = Ventral chaetaeofthelastrowsofaspecimenfromHungary (BakonyMts). D = Chaetaeinthefifth
Capturing features of hourly-resolution energy models through statistical annual indicators
<p>Dear colleagues,</p> <p>This is the official repository of the Task 7.4 of H2020 Locomotion project. Feel free to use our data by citing this work and comment about our work by referencing the main authors of it. The article explaining this work is under revision. it will be referenced as soon as posible.</p> <p><strong>Python scripts </strong>("create_inputs.txt" and "run_simulations.txt") creates the input files for EnergyPLAN. The second one runs iteratively EnergyPLAN to generate the outputs of combinations (which are saved in the "EU_Iterate_case.xlsx" file). Hourly distributions of demands and supply technologies are contained in the RAR file ("EUdist.rar") and "EU_start_v2_noFlex.txt" initialize the starting configuration of the European energy system. Those files are required to run EnergyPLAN. The <strong>PowerPoint file</strong> ("EnergyPLAN_instructions.pptx") explains the procedure to carry out the runs of combinations in Python/Excel.</p> <p>In case you couldn't properly do the combinations, the<strong> Excel file</strong> ("EU.xlsx") saves this information, so the steps of the approach could be followed from this point with the Excel file. We have used Power Query (Excel) to prepare the data for the next step of building the regression models.</p> <p>The <strong>Matlab file (</strong>"CreateRegressionModels.m"<strong>)</strong> automatically generates the regression models for the European region of WILIAM (official model of the Locomotion project).</p> <p>Best regards,</p> <p>Gonzalo.</p>
Donor Age and Red Cell Age Contribute to the Variance in Lorrca Indices in Healthy Donors for Next Generation Ektacytometry: A Pilot Study
<p>This dataset refers to the article "Donor Age and Red Cell Age Contribute to the Variance in Lorrca Indices in Healthy Donors for Next Generation Ektacytometry: A Pilot Study" Front. Physiol. 12:639722 2021</p> <p>DOI: 10.3389/fphys.2021.639722</p>
Global indicators framework for socially responsible research and innovation (RRI): How to monitor public and researcher perspectives (Supplemental material)
<p>This data upload provides a detailed account of indicators that can be used to measure RRI progress around the world against the UNESCO Recommendation for Science and Scientific Researchers at the level of individual researchers and public opinion. This data upload provides supplemental material for an article in Open Research Europe entitled, 'Global indicators framework for socially responsible research and innovation (RRI): How to monitor public and researcher perspectives'.</p> <p>Abstract for main article:</p> <p>As calls for more socially responsible research and innovation (RRI) policies and practices grow more insistent, the need for high quality indicators that can be used to evaluate progress is becoming increasingly important. Given the global nature of science, such indicators need to be relevant to countries across all world regions. Moreover, the methodological quality of indicators is critical to provide a strong foundation for long-term comparative measurement of the impacts of different kinds of policy intervention. There is a practical challenge in this effort relating to the uneven mechanisms for data collection and analysis available in different countries. There is also a geopolitical challenge in gaining buy-in from countries with very different, and sometimes competing, agendas. Here, the 2017 UNESCO-led Recommendation on Science and Scientific Researchers is highlighted as an existing vehicle that can enable cooperation on globally comparative measurement of socially responsible research and innovation. In particular, the quadrennial monitoring of the implementation of this wide-ranging global policy instrument that has been ratified by 195 countries affords a unique opportunity to add value for these countries by linking RRI to the 2017 Recommendation while establishing benchmark indicators for RRI more generally. As a practical and methodological contribution to the global community of science and innovation policymakers, researchers and research and innovation stakeholders committed to socially responsible research, this report contains specific, detailed survey questions and response options focusing on the public opinion and individual researchers’ level of measurement. It provides details of sources of benchmark survey data that have readily available open data that can be used to benchmark the development of socially responsible research and innovation over time from the vantage points of the public and researchers around the world. The aim of this kind of indicators framework is to enable evidence-based practice in socially responsible research and innovation. Robust and practical RRI measurement on a global scale can reduce the risk that well-intentioned but ill-conceived RRI policy and practice interventions create undetected, unchecked, and unreformed negative impacts in practice.</p>
Fig. 1. Maps showing the localities where adeonid bryozoans were collected. A. Collecting localities around Japan. Gray arrows indicate warm currents, the unfilled arrow indicates the cold current. B in Diversity and distribution of adeonid bryozoans (Cheilostomata: Adeonidae) in Japanese waters
Fig. 1. Maps showing the localities where adeonid bryozoans were collected. A. Collecting localities around Japan. Gray arrows indicate warm currents, the unfilled arrow indicates the cold current. B. Enlargement from previous, showing the localities around Sagami Bay, Sagami Sea, and Hachijo-jima Island. C. Enlargement from map A, showing the localities along the Nansei Islands, from Tanegashima to Okinawa.
An estimation of the absolute number of axons indicates that human cortical areas are sparsely connected
<p>This is a collection of preprocessed data and standalone Matlab analysis code for the PLoS: Biology article of the same name, <a href="https://doi.org/10.1371/journal.pbio.3001575">https://doi.org/10.1371/journal.pbio.3001575</a>. The primary processed diffusion MRI connectivity data was reported and previous distributed in our eNeuro article <a href="http://doi.org/10.1523/ENEURO.0416-20.2020">https://doi.org/10.1523/ENEURO.0416-20.2020</a>. The replication dataset was reported and previous distributed by Arnatkeviciute et al. 2021, Nature Communications (<a href="http://doi.org/10.1038/s41467-021-24306-2">https://doi.org/10.1038/s41467-021-24306-2</a>). Please cite these publications when using relevant code or data. Files with the .mat extension are Matlab v7.3 data files. The raw imaging data from which these files were derived are available from <a href="https://db.humanconnectome.org/">https://db.humanconnectome.org</a>.</p>
Tool for the selection of indicators for agriculture sustainability assessment
<p>This is a preliminary version of the Excel-based tool that is being developed within the Working Group of the Crop diversification cluster on Multi-criteria Assessment and Sustainability Indicators (MCA & SI cluster WG). The tool has the aim to assist different end-users in the selection of sustainability indicators tailored to assess the impacts and effects of crop diversification. Currently this preliminary version contains only the indicators developed by the DiverIMPACTS and DiverFARMING projects (2 out 5 projects of Crop diversification cluster).</p> <p>The tool is composed by three sheets: 1) the “Selection” sheet for querying the database and obtaining the results; 2) the “Database” sheet where all indicators of the cluster projects are reported; 3) the “SAFA_HierachicalClassification” sheet with the description of the SAFA framework, and the items identified for the indicators of the cluster projects reported in the database.</p>
Data: Spatio-temporal prediction of soil moisture using soil maps, topographic indices and SMAP retrievals
<p><strong>Data used in:</strong></p> <p>Schönauer, M., Prinz, R., Väätäinen, K., Astrup, R., Pszenny, D., Lindeman, H., et al. (2022). Spatiotemporal prediction of soil moisture using soil maps, topographic indices and SMAP retrievals. <em>International Journal of Applied Earth Observation and Geoinformation</em>, 102730. doi: 10.1016/j.jag.2022.102730</p>
Beethoven's Indications of Tempo and Expression
<p><strong>Database: Beethoven’s Indications of Tempo and Expression</strong></p> <p>This data set was created during 2012-2016 as a tool for my doctorate research on Beethoven’s tempo indications at the University of Manchester. It provides an unprecedented overview of Beethoven’s entire published oeuvre, both with opus numbers and without, by documenting the time signature, tempo indication, indicators of expression, and metronome marks for each individual section of each piece. This data set has been used for my doctoral project and its spin-off publications to achieve the following objectives:</p> <p>The first objective was to create an understanding of how Beethoven thought about tempo through the consideration of the surviving documentary evidence. This was achieved by combining the theoretical principles of tempo that Beethoven was familiar with and subscribed to earlier in his life and observing how these principles played out in the context of his entire oeuvre. Here, Beethoven’s own metronome marks served as benchmarks of the indicative speeds, with the later editorial speeds by Czerny, Moscheles, and Holz also being considered relevant in the absence of authoritative indications. (Admittedly, subsequent research has somewhat complicated the connection between these later editorial indications and Beethoven's practices.) The result is not only a detailed overview of how Beethoven used different combinations of note values, metres, and tempo indications to indicate the desired speed — or, in a small number of cases, how he used this system inconsistently or erroneously — but also exposed a number of longstanding errors in the literature. A relevant example of the latter is the metronome mark for the <em>Schreckensfanfare</em> that opens the last movement of the Ninth Symphony. The sources for this metronome mark show a discrepancy that in all literature had hitherto been resolved in favour of dotted minim = 66, but using the database I have been able to show that a reading of dotted minim = 96 is actually more plausible in the context of Beethoven's use.</p> <p> The second objective was to provide some overview of how Beethoven used expressive indications, and what they may have intended to convey. This was achieved by studying the definitions of the different expressive indications that Beethoven used (<em>dolce</em>, <em>espressivo</em>, <em>cantabile</em>, etc.), as well as the specific contexts in which these expressions occur within Beethoven’s oeuvre. This was originally planned to be the secondary focus of my doctoral project, but it was ultimately excised from my thesis for reasons of space, and has since been the focus of an independent study. </p> <p> </p> <p><strong>About the database</strong></p> <p>The database consists of four different layers, which in the file represented as individual worksheets. <strong>Opus numbers</strong> contains all of the opus numbers and WoO numbers of the compositions included in the database. In order to not overcomplicate the data, the same variable <em>Opus</em> has been used for Opus numbers and WoO numbers, with the former using 1-138 and the latter 1001-1158. Not included are arrangements made of Beethoven’s works without his involvement or works that are clearly spurious, such as the arrangements opp. 63-4 and the canon WoO 162, respectively. In cases of opus number being used multiple times, such opus 81 or 121, rather than use letters to indicate the different versions as is most common, this dataset represents these as a decimal number (i.e. 72,1; 81,2, etc.). Also included are the place and publisher of the first edition used to obtain the indications in the rest of the dataset, as well as any relevant comments on the publication.</p> <p> The worksheet <strong>Movements</strong> breaks the opus numbers down into individual pieces, and adds the variables <em>Number</em>, <em>Work title</em>, and <em>Movement</em>, as well as another layer of commentary. The most useful worksheet is <strong>Sections</strong>, which includes the <em>Time Signature</em>, <em>Tempo Markings</em>, <em>Metronome Mark</em>, and localised <em>Indicators of Tempo and Expression</em>. (Should the note values in the metronome marks not display correctly on your computer, please install the Bach Font.) Using Microsoft Excel’s Filter and Sort feature, it is possible to get a complete overview of Beethoven’s uses of these elements for all works included in the database. There is also a <em>Sorting number</em> which can be used to bring the records back into the original order.</p> <p> </p> <p> </p> <p>This database has been used as a research tool in the preparation of the following publications:</p> <p> </p> <p>Noorduin, Marten, <em>Beethoven’s Tempo Indications</em>, PhD thesis, University of Manchester, 2016. <a href="https://www.escholar.manchester.ac.uk/uk-ac-man-scw:302884">https://www.escholar.manchester.ac.uk/uk-ac-man-scw:302884</a></p> <p> </p> <p>——————— , ‘Re-examining Czerny’s and Moscheles’s Metronome Marks for Beethoven’s Piano Sonatas’, <em>Nineteenth-Century Music Review</em>, 15/2 (August 2018), 209–235. <a href="https://doi.org/10.1017/s1479409817000027">https://doi.org/10.1017/s1479409817000027</a></p> <p> </p> <p>——————— , ‘The Metronome Marks for Beethoven’s Ninth Symphony in Context’, <em>Early Music</em>, 49/1 (February 2021), 129–145. <a href="https://doi.org/10.1093/em/caab005">https://doi.org/10.1093/em/caab005</a></p> <p> </p> <p>——————— , ‘Beethoven’s Indicators of Expression in his Piano Works’, in <em>Beethoven and the Piano</em> (Musikforschung der Hochschule der Künste Bern), ed. Leonardi Miucci, Claudio Bacciagaluppi, Daniel Allenbach and Martin Skamletz (Edition Argus, 2023), pp. 118-136. <a href="https://doi.org/10.26045/kp64-6180-006">https://doi.org/10.26045/kp64-6180-006</a></p> <p> </p> <p>——————— , ‘Transcending Slowness in Beethoven’s Late Works’, in <em>Manchester Beethoven Studies</em>, ed. Barry Cooper and Matthew Pilcher (Manchester University Press, 2023), pp. 214-43. <a href="https://doi.org/10.7765/9781526155696.00015" target="_blank" rel="noopener">https://doi.org/10.7765/9781526155696.00015</a></p> <p> </p> <p>The above list is continuously updated. Users of this database are kindly invited to notify me at martennoorduin@gmail.com with comments, questions, or to add their publications to the above list.</p> <p> </p> <p> </p> <p>Marten Noorduin, Berlin, August 2023.</p>
Chloroplast redox state changes indicate cell-to-cell signalling during the hypersensitive response
<p>We performed detailed spatiotemporal analysis of chloroplast redox response to potato virus Y (PVY) infection in resistant <em>Ny</em><em>‐</em><em>1</em>-gene-bearing potato and its transgenic counterpart with impaired SA accumulation and compromised resistance. We found that the chloroplasts are highly oxidized in the cells adjacent to the cell death zone at different stages after virus inoculation in both genotypes. This hypothesis is further supported by highly induced formation of stroma filled tubules that extend from chloroplasts (stromules) in the cells adjacent to signalling cells. This dataset s a deposit of all the raw microscopy images of the study, plus the relevant metadata in ISA-tab compliant folder structure. </p> <p>After receiving reviews, we have made an additional experiment using a ROS inhibitor. The raw and processed data for this is in a separate file: _S_chlROS_inhibitor.zip</p> <p><br> <br> </p> <p><strong>Additional information about the microscopy images in this data deposit </strong></p> <ol> <li>Images of which name ends with <strong>ch00/ch01/ch02</strong> are maximum projections from Z-stacks for each ROI for each of three channels: chlorophyll fluorescence (ch00), GFP fluorescence after excitation with 405 nm laser line (ch01) and GFP fluorescence after excitation with 488 laser line (ch02), exported from Leica LAS X software.</li> <li>Only mesophyll cells are included in z-stack, except for the experiments with GFP-tagged PVY where additional z-stacks including both mesophyll and epidermal cells were produced ( »_2« added in the image name, see images with the comment »epidermal cells included in z-stack« in S_PhenodataRedox).</li> <li>Images of which name ends with <strong>ch00.tif</strong> and <strong>ch00.tif_ratio</strong> are analysed images, obtained using in-house Matlab script. These images were obtained by the analysis of ch00/ch01/ch02 images with the following steps: conversion to grayscale, filtering out pixels of low intensity, conversion to binary format using spatial adaptive thresholding, a round or erosion and dilation to remove single pixel noise around the chloroplasts, followed by size-based segmentation of individual chloroplasts. The ratios of fluorescence intensities 405/488 were then calculated for each pixel belonging to the chloroplast masks obtained in the previous step. Results were calculated per image (normalized to the fraction of pixels belonging to chloroplasts) and per individual chloroplast in each image.</li> <li>In the experiments with GFP-tagged PVY, due to high background signal in the cell death zone as a result of virus derived GFP fluorescence, signal in the 488 channel and 405/488 ratio (images named »scaled 488« and »405/488 in chloroplasts« in ch00.tif_ratio) in the cell death zone are not accurate.</li> <li>Figures of which name ends with <strong>ch00.tif_spatial_ROI1/ROI2</strong> show the 405/488 ratios in ROI1 or ROI2, determined for each pixel inside chloroplast masks for each Bin. See Image analysis in Methods for details.</li> <li>Experiment names and image names correspond to the names in S_PhenodataRedox. Details regarding experimental set-up and transgenic lines used are specified in S_PhenodataRedox.</li> </ol> <p>The Zenodo_reanalysis.zip file contains processed microscopic images in a new red/blue colormap. </p>
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