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1,561 results for “institution”
San Francisco Estuary Institute Phytoplankton eDNA and Toxin Monitoring, San Francisco Bay, CA, 2014-2023
From late 2014-present, San Francisco Estuary Institute has conducted molecular monitoring of phytoplankton in partnership with the US Geological Survey from several stations stretching from Rio Vista in the North Delta to the Lower South Bay, past the Dumbarton Bridge. These samples have been analyzed for 18S eDNA data in partnership with Timothy Otten at Bend Genetics, targeting the V7 region. The included dataset covers the 2014-2023 period, including data up to 2022, conducted with an Illumina MISEQ platform, and from 2022-2023 using a NEXTSEQ platform, which enabled much greater sampling depth. Two sets of taxonomic assignments are included in this data release, one using the Silva database, and the other using the PR2 database, two of the leading sources of phytoplankton taxonomic data aiding in assignments of OTUs to taxa. Raw sequence data will also be uploaded to NCBI for comparison. Data collection continues and this release will be updated as new time periods are added.
Dataset on surface peat stoichiometry and physical properties in boreal undrained peatlands in Finland, Natural Resources Institute Finland (Luke) and Geological Survey of Finland (GTK)
<p><strong>Dataset on surface peat stoichiometry and physical properties in boreal undrained peatlands in Finland </strong></p><p><strong>Creators: </strong>Larmola T, Anttila J, Turunen J, Laine-Petäjäkangas A, Ovaskainen J, Laatikainen M </p><p>The dataset consists of peat properties in a subset of 16 undrained peatland sites (32 peat samples) in Geological Survey of Finland (GTK) national peatland inventory. These sites were sampled between 2002 and 2017 and the subset selected from GTK peat sample archives. These 16 sites represented two pine-<i>Sphagnum-</i> dominated site types (IR, KR) and two treeless sedge fen types (VSN, RhSN) all in 4 replicates and sampled in 2 depths 20-40, 40-60cm). </p><p><strong>Peat analyses</strong> The peat samples were analyzed for C:H:N:S and ash concentration with Leco 628 CHNS analyzer following standard SFS EN13039 with FINAS accredited adjustments JOK3023. The dry matter content was analyzed after drying the sample at 105 ℃ and ash content based on loss on ignition at 550 ℃. The O concentration was determined by difference: %O = 100 - % (ash + total C + N + H + S).</p><p><strong>Stoichiometric calculations</strong>The O concentration was determined by difference: %O = 100 - % (ash + total C + N + H + S). Atomic ratios of C:N, H:C and O:C were calculated based on the individual sample mass values. The C oxidation state (Cox), the oxidative ratio (OR), and the degree of unsaturation (DU) were calculated following equations in the study by Masiello et al. (2008). The analyses are described in more detail in Turunen et al. (manuscript). </p><p>Related datasets used in the same publication are:</p><p>Larmola T, Anttila J, Alm J Dataset on surface peat stoichiometry and physical properties in boreal forestry-drained peatlands in Finland</p><p>Turunen J. (2023). Surface peat data, Geological Survey of Finland (Version 1) [Data set]. Zenodo. <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.5281%2Fzenodo.8434148&data=05%7C01%7Cluke.tuula.larmola%40valtion.mail.onmicrosoft.com%7Cc48ffad4c0e341d0fa5808dbcaff0289%7C7c14dfa4c0fc47259f0476a443deb095%7C0%7C0%7C638326968887189768%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=AyYOxR7Mas2ef8y3wI7oCrzHWSyqBzt%2FJB0CMN%2BJUiU%3D&reserved=0">https://doi.org/10.5281/zenodo.8434148</a></p><p> </p><p><strong>Data column description </strong></p><p>ID - Site identifier</p><p>site - undrained peatland (UDP) for all rows</p><p>ncoord - North coordinate (latitude), degrees.</p><p>depth - Sampling depth. 20: 0-20 cm, 40: 20-40cm, 60: 40-60cm.</p><p>type - Site type classification according to the Finnish peatland site type system.</p><p>origin - UDP site type. I: treed peatland (peat typically Sphagnum-wood), II: treeless peatland (or sparsely treed, peat typically Sphagnum-sedge)</p><p>type_num - Nutrient level according to site type. 1 is the most nutrient rich and 4 is the least.</p><p>Cmol - Molar carbon concentration in the sample</p><p>Hmol - Molar hydrogen concentration in the sample</p><p>Nmol - Molar nitrogen concentration in the sample</p><p>Omol - Molar oxygen concentration in the sample</p><p>Smol - Molar sulphur concentration in the sample</p><p>bd - Bulk density, kg/m3</p><p>cox - C oxidation state</p><p>or - Oxidative ratio</p><p>du - Degree of unsaturation</p><p>hc - H:C ratio</p><p>cn - C:N ratio</p><p>oc - O:C ratio</p><p><strong>References</strong></p><p>Masiello CA, Gallagher ME, Randerson JT, Deco RM, Chadwick OA (2008) Evaluating two experimental approaches for measuring ecosystem carbon oxidation state and oxidative ratio, Journal of Geophysical Research 113, G03010, <a href="https://doi.org/10.1029/2007JG000534">https://doi.org/10.1029/2007JG000534</a></p><p>Turunen J, Anttila J, Laine-Petäjäkangas A, Ovaskainen J, Laatikainen M, Alm J, Larmola T 2023. Impacts of forestry drainage on surface peat stoichiometry and physical properties in boreal peatlands in Finland. <i>manuscript.</i></p>
Dataset on surface peat stoichiometry and physical properties in boreal forestry-drained peatlands in Finland, Natural Resources Institute Finland
<p><strong>Dataset on surface peat stoichiometry and physical properties in boreal forestry-drained peatlands in Finland</strong></p><p><strong>Creators: Larmola T, Anttila J, Alm J </strong></p><p>The dataset consists of peat properties in a subsample of 30 drained peatland forests in Finland selected from the permanent sample plots of the 8th National Forest Inventory (systematic sample of plots on drained peatland forests, e.g., Hotanen et al. 2006). The subsample included equally different site types of forestry-drained peatlands of those parts of Finland where drainage for forestry is economically viable (Latitude 60-66 ºN, annual temperature sum > 750 dd). </p><p><strong>The site selection criteria</strong> were average peat layer thickness of over 20 cm, no clear-cut areas, site drained before 1995 and ditching had detectably altered hydrology or vegetation. <strong>Peat analyses</strong> Finnish Forest Research Institute (now Natural Resources Institute Finland) sampled peat cores with a box corer in 2002, samples were analysed for bulk density, archived and remaining samples at depths 20-30, 30-40 cm (total of 58) were analysed in 2021. The peat samples were analyzed for C:H:N:S and ash concentration with Leco 628 CHNS analyzer following standard SFS EN13039 with FINAS accredited adjustments JOK3023. The dry matter content was analyzed after drying the sample at 105 ℃ and ash content based on loss on ignition at 550 ℃. </p><p><strong>Stoichiometric calculations</strong>The O concentration was determined by difference: %O = 100 - % (ash + total C + N + H + S). Atomic ratios of C:N, H:C and O:C were calculated based on the individual sample mass values. The C oxidation state (Cox), the oxidative ratio (OR), and the degree of unsaturation (DU) were calculated following equations in the study by Masiello et al. (2008). The analyses are described in more detail in Turunen et al. (manuscript). </p><p>Related datasets used in the same publication are:</p><p>Larmola, T. Anttila J, Turunen J, Laine-Petäjäkangas A, Ovaskainen J, Laatikainen M Dataset on surface peat stoichiometry and physical properties in boreal undrained peatlands in Finland, Natural Resources Institute Finland (Version 1) [Dataset]. Zenodo. doi.org/<strong>10.5281/zenodo.10068486</strong></p><p>Turunen J. (2023). Surface peat data, Geological Survey of Finland (Version 1) [Data set]. Zenodo. <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fdoi.org%2F10.5281%2Fzenodo.8434148&data=05%7C01%7Cluke.tuula.larmola%40valtion.mail.onmicrosoft.com%7Cc48ffad4c0e341d0fa5808dbcaff0289%7C7c14dfa4c0fc47259f0476a443deb095%7C0%7C0%7C638326968887189768%7CUnknown%7CTWFpbGZsb3d8eyJWIjoiMC4wLjAwMDAiLCJQIjoiV2luMzIiLCJBTiI6Ik1haWwiLCJXVCI6Mn0%3D%7C3000%7C%7C%7C&sdata=AyYOxR7Mas2ef8y3wI7oCrzHWSyqBzt%2FJB0CMN%2BJUiU%3D&reserved=0">https://doi.org/10.5281/zenodo.8434148</a></p><p> </p><p><strong>Data column description</strong></p><p>ID - Site identifier</p><p>site - Forestry-drained peatland (FDP) for all rows</p><p>ncoord - North coordinate (latitude), degrees.</p><p>depth - Sampling depth. 30: 20-30 cm, 40: 30-40cm, avg: average of both depths.</p><p>type - Site type classification according to the Finnish peatland site type system.</p><p>origin – Origin of the FDP site type at undrained state. I: treed peatland (peat typically Sphagnum-wood), II: treeless peatland (or sparsely treed, peat typically Sphagnum-sedge)</p><p>type_num - Nutrient level according to site type. 1 is the most nutrient rich and 4 is the least.</p><p>Cmol - Molar carbon concentration in the sample</p><p>Hmol - Molar hydrogen concentration in the sample</p><p>Nmol - Molar nitrogen concentration in the sample</p><p>Omol - Molar oxygen concentration in the sample</p><p>Smol - Molar sulphur concentration in the sample</p><p>bd - Bulk density, kg/m3</p><p>cox - C oxidation state</p><p>or - Oxidative ratio</p><p>du - Degree of unsaturation</p><p>hc - H:C ratio</p><p>cn - C:N ratio</p><p>oc - O:C ratio</p><p>n - Number of samples. 2 for averages from both depths, 1 for all other rows.</p><p> </p><p><strong>References</strong></p><p>Hotanen JP, Maltamo M, Reinikainen A (2006) Canopy stratification in peatland forests in Finland. Silva Fennica 40:53–82.</p><p>Masiello CA, Gallagher ME, Randerson JT, Deco RM, Chadwick OA (2008) Evaluating two experimental approaches for measuring ecosystem carbon oxidation state and oxidative ratio, Journal of Geophysical Research 113, G03010, <a href="https://doi.org/10.1029/2007JG000534">https://doi.org/10.1029/2007JG000534</a></p><p>Turunen J, Anttila J, Laine-Petäjäkangas A, Ovaskainen J, Laatikainen M, Alm J, Larmola T 2023. Impacts of forestry drainage on surface peat stoichiometry and physical properties in boreal peatlands in Finland. <i>manuscript.</i></p><p> </p>
Liquid Chromatography - Tandem Mass Spectrometry (LC-MS/MS) and Gas Chromatography - Mass Spectrometry (GC-MS) Reference Libraries from Global Natural Products Social Molecular Networking (GNPS) and National Institute of Standards and Technology (NIST) WebBook Processed for Spectral Library Matching
<div>In order to obtain a high-quality LC-MS/MS reference database for spectral library matching, we selected 22 high-quality GNPS tandem mass spectrometry databases generated under the positive ion mode. Further preprocessing similar to Huber et al involving mass-to-charge (m/z) and intensity filtering yields the database found in the file LCMS_GNPS_reference_library.csv which contains 14,705 electrospray ionization (ESI) mass spectra, each of which corresponds to a unique compound. The NIST WebBook database was used to construct GC-MS database contained in the file GCMS_NIST_WebBook.csv. This database contains 23,721 electron ionization (EI) mass spectra, each of which corresponds to a unique non-hyphenated Chemical Abstract Service (CAS) Registry Number.</div> <div> </div> <div>Both LC-MS/MS and GC-MS databases are organized into three columns: one for the identifier, one for the m/z values, and one for the intensity values. For example, if spectrum A has 20 ion fragments, then there will be 20 rows corresponding to spectrum A in the corresponding database with the identifier A repeated 20 times with the corresponding m/z and intensity values.</div>
GESIS - Leibniz Institute for the Social Sciences data access categories
<p>Replication code for extracting and analysing data access categories from the oai-pmh feed provided by the GESIS - Leibniz Institute for the Social Sciences DBK data catalogue. The code utilises the dc_oai-de feed to extract metadata about objects in the data catalogue, this is then edited to retain and summarise information on the four data access categories used by the archive. The oai-pmh metadata is available from GESIS under a CC0 licence.</p> <p>The .csv files extracted from the oai-pmh feed and edited to correct for missing records is also included for replication.</p>
S70 | EISUSGCEIMS | Environmental Institute GC-EI-MS suspect list
<p>This is the collection associated with list S70 EISUSGCEIMS Environmental Institute GC-EI-MS suspect list on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>GC-EI-MS suspect list of Environmental Institute. Provided by Peter Oswald, Nikiforos Alygizakis, Martina Oswaldova, Jaroslav Slobodnik. Dataset DOI: <a href="https://doi.org/10.5281/zenodo.3894827">10.5281/zenodo.3894827</a>.</p>
12S metabarcoding reference data from the Research Institute for Nature and Forest (INBO)
<p>This dataset contains metabarcoding reference data with 12S sequences from fish and other vertebrates for Teleo and Riaz primers suited for use with the <a href="https://git.metabarcoding.org/obitools/obitools/wikis/home/">OBITools</a> package.</p> <p><strong>Files</strong><br>- <strong>all_seqs_INBO_riaz_amplified.fasta</strong>: reference data for Riaz marker<br>- <strong>all_seqs_INBO_Valentini_teleo_amplified.fasta</strong>: reference data for Teleo marker<br>- <strong>species_INBO_riaz.csv</strong>: species for which reference data is included in Riaz dataset<br>- <strong>species_INBO_teleo.csv</strong>: species for which reference data is included in Teleo dataset</p>
Experimental data aquisition of the U-LEAF Linear Fresnel Collector of the Cyprus Institute
<p>The file contains the experimental data for 50+ (non continuous) days of operation of the <a title="Linear Fresnel Reflector of the Cyprus Institute" href="https://energy.cyi.ac.cy/facilities/fresnel/">LFR</a> at the Cyprus Institute. This is a csv file type. The data set is divided in several columns: </p> <ul> <li><strong>Date</strong>: Year, Month, Day, Hours, Minutes, Seconds <em>as per the aquisition time-steps of the Master PLC of the Linear Fresnel Collector<br></em></li> <li><strong>Solar position</strong>: Azimuth of the sun (Azimuth =0 at South), Elevation of the sun (0 from the horizon) <em>calculated based on NOAA algorithm fitting the Master PLC aquisition time-steps for the location of the Linear Fresnel collector <br></em></li> <li><strong>IAM (Incidence Angle Modifiers)</strong>: calculated from ray tracing software (Tonatiuh) <em> based on PLC aquisition steps</em></li> <li><strong>DNI (Direct Normal Irradiance):</strong> as measured by the pyrheliometer (LP Pyhre 16 AC with EKO STR 21G tracker)</li> <li><strong>Weather station data</strong>: Ambient Temperature, Pressure, GHI, Humidity, Wind velocity (<em>Davis Vantage pro 2</em>)</li> <li><strong>Reflectometry data</strong> as measured several time per week and interpolated in between (<em>D&S Portable Specular Reflectometer Model 15R-USB</em>)</li> <li><strong>Absorber measurements</strong>: measured inlet, measured outlet and average calculated temperatures <em>in the absorber as the the aquisition of the PLCs (TC MISURE E CONTROLLI PT100, Class 1/3)</em></li> <li><strong>Heat transfer Fluid characteristics</strong>: Cp and Density, Massflow obtained from the volumetric flow (Prowirl F200, 7F2B25, DN25 1"), Power absorbed <em>as calculated based on the Duratherm 450 datasheet</em></li> </ul> <p>The date is set by the aquisition by the master PLC that registers the date, the volumetric flowrate of the HTF, the inlet temperature and the outlet temperature. </p> <p>They are 4 data base merged together:</p> <ul> <li>The master PLC </li> <li>The weather station</li> <li>DNI</li> <li>Reflectometer</li> </ul> <p>The available data matches periods of time when the 4 database had data registered. Time-steps vary between 15 seconds and 30 seconds. </p> <p>For more information you can send an email to a.montenon@cyi.ac.cy</p>
Raw Data for Mapping Repositories and their Institutional Open Science Policies in Asia
<p>Persistent Identifiers (PIDs), particularly Digital Object Identifiers (DOIs), are crucial for establishing a robust and globally accessible research infrastructure. In Asia, a diverse array of research outputs and resources are produced and published in repositories. However, a significant number of these repositories, and outputs remain undiscoverable in global registries and aggregators. <br><br>These three datasets provides comprehensive information on the adoption of repositories, Open Access mandates, and DOIs adoption in Asian countries. It includes detailed records from different registry sources and repository platforms.<br><br>You can read the full report titled 'Mapping Repositories and their Institutional Open Science Policies in Asia' at <a href="https://doi.org/10.5281/zenodo.12566244">https://doi.org/10.5281/zenodo.12566244</a></p>
Raw Data for Mapping Repositories and their Institutional Open Science Policies in the Middle East and North Africa (MENA)
<div> <p>Persistent Identifiers (PIDs), particularly Digital Object Identifiers (DOIs), are crucial for establishing a robust and globally accessible research infrastructure. In the Middle East and North Africa (MENA) region, a diverse array of research outputs and resources are produced and published in repositories. However, a significant number of these repositories, and outputs remain undiscoverable in global registries and aggregators. <br><br>These three datasets provides comprehensive information on the adoption of repositories, Open Access mandates, and DOIs adoption in MENA countries. It includes detailed records from different registry sources and repository platforms.<br><br>You can read the full report titled 'Mapping Repositories and their Institutional Open Science Policies in MENA' at <a href="https://doi.org/10.5281/zenodo.11370031">https://doi.org/10.5281/zenodo.11370031</a></p> </div>
Quality evaluation criteria, best practices, and assessment systems for Institutional Publishing Service Providers (IPSPs): dataset
<p>The dataset contains tabular information on the elements of best practice in scholarly publishing found in a set of documents (high-level recommendations and principles, indexation criteria and specific assessment guidelines used on the national and institutional levels). The set of documents subject to analysis (58 items) were identified by the DIAMAS project team members (bibliographic metadata are provided in IPSP-best-practice-documents.xml and IPSP-best-practice-documents.ris).</p> <p>The dataset was compiled by the DIAMAS project team using an analysis matrix that included the general information about the documents (title, issuing entity, scope and purpose, etc.) and the the seven core components of scholarly publishing identified in the Diamond Open Access Action Plan (2022) and revised by the DIAMAS project team.</p> <p>More information about the data collection methodology can be found in the report D3.1 IPSP Best Practices Quality evaluation criteria, best practices, and assessment systems for Institutional Publishing Service Providers (IPSPs) (<a href="https://doi.org/10.5281/zenodo.7859172">https://doi.org/10.5281/zenodo.7859172</a>), which is based on this dataset.</p> <p> </p> <p><strong>****Dataset contents****</strong></p> <p>IPSPs_best-practices-overview.csv</p> <p>IPSPs_best-practices-overview.ods</p> <p>IPSP-best-practice-documents.xml</p> <p>IPSP-best-practice-documents.ris</p> <p>README.txt</p> <p> </p> <p><strong>****Column headers and field types***</strong></p> <p>Title (original) (text)</p> <p>Title (English) (text)</p> <p>Publication date (date, DD/MM/YY)</p> <p>Last accessed (date, DD/MM/YY)</p> <p>URL (text-web address)</p> <p>Scope (text, controlled)</p> <p>Type of document (text, controlled)</p> <p>Original language (text)</p> <p>Other languages (text)</p> <p>Entity issuing the document (text)</p> <p>Entity responsible for the assessment (text)</p> <p>Scope of the assessment (text, controlled)</p> <p>Scope of assessment: region or country (text)</p> <p>Disciplines’ coverage (text)</p> <p>Periodicity of the assessment (text)</p> <p>Reassessment frequency? If yes: periodicity (text)</p> <p>Benefits linked to the assessment (text)</p> <p>(1) Funding (text)</p> <p>(2) Ownership and governance (text)</p> <p>(3) Open science practices (text)</p> <p>(4) Editorial quality, editorial management and research integrity (text)</p> <p>(5) Technical service efficiency (text)</p> <p>(6) Visibility (including indexation), communication, marketing and impact (text)</p> <p>(7) Diversity, Equity and Inclusion (text)</p>
Institutional Dimensions of Restoring Everglades Water Quality -Interview Notes (FCE), September 2014-July 2015
These data were compiled through semi-structured and open-ended interviews as part of the Institutional Dimensions of Restoring Everglades Water Quality research project. The notes represent responses from farmers, agricultural extension agents, state and federal government officials, private water consultants, and nonprofit officials involved in the implementation of the Everglades Forever Act regulations. These mandate that farms in the Everglades Agricultural Area implement best management practices to reduce phosphorus enrichment. Since the regulations started in 1994, water quality has steadily improved. The research sought to explain why the regulations have been effective.
Questionnaire for the self-assessment of digital preservation activities in institutional research repositories
<p>This dataset includes a questionnaire designed to enable institutional repository managers to conduct a self-assessment of their digital preservation strategies and activities. It consists of 46 evaluation criteria extracted and modified from the NDSA Levels of Digital Preservation and ISO 16363:2017 standards. The questionnaire is provided in queXML format, facilitating its import into various survey applications</p> <p> </p>
Room Impulse Response Dataset: Niels Bohr Institute - Auditorium A
<h1>Dataset description</h1> <p>This dataset is comprised of acoustic Room Impulse Response (RIR) measurements using different measurement equipment at the iconic Auditorium A, in the Niels Bohr Institute, Copenhagen. The measurements were carried out during the days July 22<sup>nd</sup> & 23<sup>rd</sup>, 2023.</p> <p>The dataset includes:</p> <ul> <li><strong><em>rir_NBI_line.h5</em></strong> – Sequential measurements over a line using a robotic arm (UR5, Universal Robots) for microphone positioning.</li> <li><strong><em>rir_NBI_em32.h5</em></strong> – Distributed RIRs measured with the 32-channel spherical microphone array Eigenmike (em32, mh Acoustics).</li> <li><strong><em>rir_NBI_em32.sofa – </em></strong>SOFA format of the previous file.</li> </ul> <h2>The room</h2> <p>The Auditorium has a volume of approximately 126 m3 and is roughly rectangular with a tilted floor for the audience. The room was fully furnished with classroom equipment when measured. On one side wall, there are several interspaced windows.</p> <p>The reverberation time in octave bands is:</p> <table> <tbody> <tr> <td> <p>F (Hz)</p> </td> <td> <p>32</p> </td> <td> <p>63</p> </td> <td> <p>126</p> </td> <td> <p>250</p> </td> <td> <p>500</p> </td> <td> <p>1k</p> </td> <td> <p>2k</p> </td> <td> <p>4k</p> </td> <td> <p>8k</p> </td> <td> <p>16k</p> </td> </tr> <tr> <td> <p>T30 (s)</p> </td> <td> <p>0.75</p> </td> <td> <p>0.74</p> </td> <td> <p>0.61</p> </td> <td> <p>0.72</p> </td> <td> <p>0.80</p> </td> <td> <p>0.88</p> </td> <td> <p>1.03</p> </td> <td> <p>1.05</p> </td> <td> <p>0.85</p> </td> <td> <p>0.58</p> </td> </tr> </tbody> </table> <h2>The measurements</h2> <p>All measurements were obtained using an exponential sweep covering the frequencies 20-20k Hz. The specific duration of the sweep varies with the measurement setup and can be found in the corresponding file. The sampling rate is 48 kHz.</p> <p>The source is a two-way loudspeaker (BM6, Dynaudio), and its position was kept constant throughout the entire measurement campaign. The remaining equipment utilised was an audio interface (Fireface UCX, RME), a loudspeaker amplifier, a microphone amplifier (Nexus, B&K).</p> <p>The atmospheric conditions for each set of measurements are included in the corresponding file.</p> <h1>Related publications</h1> <p>This dataset is linked to the publication:</p> <ul> <li>Figueroa-Duran A. & Fernandez-Grande E., <em>Reconstruction of reverberant sound fields over large spatial domains. </em>In <em>J. Acoust. Soc. Am. (2025), </em><a href="https://doi.org/10.1121/10.0034833" target="_blank" rel="noopener">https://doi.org/10.1121/10.0034833</a></li> </ul> <h1>Contact</h1> <p>For any questions, please address them to <strong><em>anfig@dtu.dk</em></strong>.</p>
Omnibus Poll Ukraine - July 2023 (Ilko Kucheriv Democratic Initiatives Foundation + Kyiv International Institute of Sociology) – Random-sample questionnaire-based representative poll
This data collection offers a representative omnibus survey of the Ukrainian population, living in territories controlled by the Ukrainian government without ongoing armed hostilities. The survey was conducted by the Ilko Kucheriv Democratic Initiatives Foundation together with the Kyiv International Institute of Sociology from 03 to 17 July 2023. A description of the methodology is given on p.2 of the "selected results" file, which is part of this data collection. The poll covers the following thematic fields: jobs + entrepreneurship, corruption, economic situation, healthcare sector, war, people under Russian occupation. This data collection contains the original survey data. The SPSS file (.sav) is the original file provided by the Ilko Kucheriv Democratic Initiatives Foundation. It has been exported into an Excel file. The content of the respective xlsx-file should be identical with the original sav-file. The sav-file contains the questions and answer options of the original questionnaire in Ukrainian. The original questionnaire and an English translation are also included in this data collection as separate pdf-files. Additionally, the data collection contains one file with "selected results" which document some major results of the survey in the form of a analytical summaries and descriptive statistics and another file with a clarification concerning the interpretation of question 5.24 about the president's "personal responsibility" for corruption in the country. These files are in Ukrainian only. New in version 1.1: An English translation of the questionnaire has been added under "files".
Version 4.2 (20230306) of the MALDI-ToF Mass Spectrometry Database for Identification and Classification of Highly Pathogenic Microorganisms from the Robert Koch-Institute (RKI)
<p><em>(Version </em>20230306<em>, </em>btmsp files modified May 31, 2023, additional taxonomic information added Dec 27, 2024<em>) </em></p> <p>Version 4.2 (20230306) of the RKI MALDI-ToF mass spectra database represents the third update of the original database (version 20161027, <a href="http://doi.org/10.5281/zenodo.163517">https://doi.org/10.5281/zenodo.163517</a>). The RKI Database v.4.2 now contains a total of 11055 MALDI-ToF mass spectra from 1601 microbial strains of highly pathogenic (i.e. biosafety level 3, BSL-3) bacteria such as <em>Bacillus anthracis</em>, <em>Brucella melitensis</em>, <em>Yersinia pestis</em>, <em>Burkholderia mallei / pseudomallei</em> and <em>Francisella tularensis</em> as well as a selection of spectra of their close and distant relatives. The database can be used as a reference for the diagnosis of BSL-3 bacteria using proprietary and free software packages for MALDI-ToF MS-based microbial identification. The spectral data are provided as a zip archive (<a href="https://zenodo.org/records/14562231/files/zenodo%20db%20230306.zip?download=1&preview=1">zenodo db 230306.zip</a>) containing the original mass spectra in their native data format (Bruker Daltonics). Please refer to the pdf file (<a href="https://zenodo.org/records/14562231/files/230306-ZENODO-Metadata.pdf?download=1&preview=1">230306-ZENODO-Metadata.pdf</a>) for information on cultivation conditions, sample preparation and details of the spectra acquisition. Please do not try to print this document (>1600 pages!).</p> <p>Version 20230306 of the RKI database contains for the first time files in the <em>btmsp</em> format (e.g. <a href="https://zenodo.org/records/14562231/files/2023-May-23-Bacillus-RKI-Database-568.btmsp?download=1&preview=1">2023-May-23-Bacillus-RKI-Database-568.btmsp </a> <a href="https://zenodo.org/api/files/35e90a0c-653d-4ba4-bf93-50b2bd80d073/2023-May-23-Bacillus-RKI-Database-570.btmsp"> </a>and others). These files were generated using the MALDI Biotyper software (Bruker Daltonics) and contain a total of 1601 main spectra (msp) from the BSL-3 database in the proprietary data format of the MALDI Biotyper software. *.<em>btmsp </em>files can be imported and used for identification with this software solution. Please refer to the manufacturer's manual for details on importing <em>btmsp </em>files. Note that the btmsp file available in database version 4 is broken and cannot be imported.</p> <p>The pkf files (<a href="https://zenodo.org/records/14562231/files/230306_ZENODO_30Peaks_0.75.pkf?download=1&preview=1">230306_ZENODO_30Peaks_0.75.pkf</a>, <a href="https://zenodo.org/records/14562231/files/230306_ZENODO_45Peaks_0.75.pkf?download=1&preview=1">230306_ZENODO_45Peaks_0.75.pkf</a>) represent two versions of the MS peak list data in a Matlab compatible format. The latter data can be imported into MicrobeMS, a free Matlab-based software solution developed at the RKI. MicrobeMS can be used for the identification of microorganisms by MALDI-ToF MS and is available at <a href="https://wiki-ms.microbe-ms.com">https://wiki-ms.microbe-ms.com</a>.</p> <p>The Excel file <a href="https://zenodo.org/records/14562231/files/Taxonomy%20information%20-%20RKI%20MALDI-ToF%20MS%20database%20of%20HPB%20at%20ZENODO%20v.4.xlsx?download=1&preview=1">Taxonomy information - RKI MALDI-ToF MS database of HPB at ZENODO v.4.xlsx</a> contains additional taxonomic information such as a detailed list of bacterial MALDI-ToF mass spectra (sheet #1), overviews on the number of spectra per strain, species or bacterial genus (sheet #2), numbers of strains per species, or genus (sheet #3), etc.</p> <p>The RKI mass spectrometry database is updated regularly.</p> <p>The author would like to thank the following individuals for providing microbial strains and species or mass spectra thereof. Without their help, this work would not have been possible.</p> <ul> <li><strong>Wolfgang Beyer</strong> - University of Hohenheim, Faculty of Agricultural Sciences, Stuttgart, Germany</li> <li><strong>Guido Werner</strong> - Robert Koch-Institute, Nosocomial Pathogens and Antibiotic Resistances (FG13), Wernigerode, Germany</li> <li><strong>Alejandra Bosch</strong> - CINDEFI, CONICET-CCT La Plata, Facultad de Ciencias Exactas, Universidad Nacional de La Plata, La Plata, Buenos Aires, Argentina</li> <li><strong>Michal Drevinek</strong> - National Institute for Nuclear, Biological and Chemical Protection, Milin, Czech Republic</li> <li><strong>Roland Grunow, Daniela Jacob, Silke Klee, Susann Dupke </strong>and <strong>Holger Scholz</strong> - Robert Koch-Institute, Highly Pathogenic Microorganisms (ZBS2), Berlin, Germany</li> <li><strong>Jörg Rau </strong>- Chemisches und Veterinäruntersuchungsamt Stuttgart, Fellbach, Germany</li> <li><strong>Jens Jacob</strong> - Robert Koch-Institute, Hospital Hygiene, Infection Prevention and Control (FG14), Berlin, Germany</li> <li><strong>Martin Mielke</strong> - Robert Koch-Institute, Department 1 - Infectious Diseases, Berlin, Germany</li> <li><strong>Monika Ehling-Schulz</strong> - Functional Microbiology, Institute of Microbiology, University of Veterinary Medicine, Vienna, Austria</li> <li><strong>Armand Paauw</strong> - Department of Medical Microbiology, CBRN protection, Universitair Medisch Centrum Utrecht, TNO, Rijswijk, The Netherlands</li> <li><strong>Herbert Tomaso</strong><strong> </strong>– Friedrich-Löffler-Institut (FLI), Federal Research Institute for Animal Health, Jena, Germany</li> <li><strong>Gabriel Karner</strong><strong> </strong>- Karner Düngerproduktion GmbH, Research & Development, Neulengbach, Austria</li> <li><strong>Rainer </strong><strong>Borriss</strong><strong> </strong>- Institute of Marine Biotechnology e.V. (IMaB), Greifswald, Germany</li> <li><strong>Le Thi Thanh Tam</strong><strong> </strong>- Division of Plant Pathology and Phyto-Immunology, Plant Protection Research Institute, Hanoi, Socialist Republic of Vietnam</li> <li><strong>Xuewen</strong><strong> Gao</strong><strong> </strong>- College of Plant Protection, Nanjing Agricultural University, Key Laboratory of Integrated Management of Crop Diseases and Pests, Nanjing, People’s Republic of China</li> </ul> <p>For a detailed description of the database see: Lasch, P., Beyer, W., Bosch, A. <em>et al.</em> A MALDI-ToF mass spectrometry database for identification and classification of highly pathogenic bacteria. <em>Sci Data</em> <strong>12</strong>, 187 (2025). <a href="https://doi.org/10.1038/s41597-025-04504-z">https://doi.org/10.1038/s41597-025-04504-z</a></p>
Development of MeV TOF-SIMS capillary microprobe at the Ruđer Bošković Institute in Zagreb
<p>New Time-of-flight Secondary Ion Mass Spectrometry (TOF SIMS) setup using MeV heavy ions for the excitation is developed at the Ruđer Bošković Institute accelerator facility. To focus heavy MeV ions to micron dimensions, conical glass capillary is used instead of quadrupole magnetic lenses. The setup uses a continuous primary beam where START signal for TOF is obtained from the PIN diode placed behind the thin transmission sample. Results showing measured energy spectra for several primary heavy ions are presented and compared with theoretical simulations. . The first mass spectra obtained with the new setup using reflectron-type TOF analyzer are given together with the mass and spatial resolution values of the new setup. </p>
A private house in 'Marea'/Philoxenite transformed into a monastic institution and other Christian hybrid buildings in the Mareotis region - additional illustrations
<p>Set of three documents on potsherds (ostraca) has been found in Philoxenite (Egypt). All three of the ostraca, M200249 (= Document A), M200250 (= Document B), and M200251 (= Document C) are preserved in their entirety, in the sense that the sherds, meant to serve as the canvas for the documents, were not broken when they were thrown out into the rubbish pit in the piscina.</p> <p>The photos uploaded here provide supplementary material for an article discussing the content of these ostraca. </p> <p> </p>
The institutional perspective on informal housing
<p><strong>Coordinador del Seminario:</strong> Carlos A. Navarrete Ulloa.<br> <strong>Expositor</strong>: Luis Adolfo Ortega Granados</p> <p><strong>Comité Ejecutivo PRONACE-Vivienda</strong><br> Fernando Córdova Canela, Centro Universitario de Arte, Arquitectura y Diseño, Universidad de Guadalajara (UdeG). Francisco Javier Porras Sánchez, Instituto de Investigaciones Dr. José María Luis Mora.<br> Gabriel Castañeda Nolasco, Universidad Autónoma de Chiapas (UNACH). Carlos A. Navarrete Ulloa, Centro Universitario de Tonalá, (UdeG).</p> <p>Exposición realizada en el marco del PRONACE Vivienda en el cual se comenta la lectura:</p> <p>Dekel. T. (2020) The Institutional Perspective on Informal Housing. Habitat International, 106, 102287 https://doi.org/10.1016/j.habitatint.2020.102287</p>
Story Map of the AI Ethics Lab of the Austrian Institute of Technology (AIT)
<p>The Co-Change Lab at AIT, the Austrian Institute of Technology, focuses on addressing the promises and challenges associated with research work on and the application of machine learning and artificial intelligence. An interdisciplinary team of social and data scientists is working on AI ethics.</p>
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