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Reflexión entorno a la colaboración y co creación
<p>Coordinador del Seminario: Carlos A. Navarrete Ulloa.<br> Expositor: Luis Adolfo Ortega Granados</p> <p>Comité Ejecutivo PRONACE-Vivienda</p> <ul> <li>Fernando Córdova Canela, Centro Universitario de Arte, Arquitectura y Diseño, Universidad de Guadalajara (UdeG).</li> <li>Francisco Javier Porras Sánchez, Instituto de Investigaciones Dr. José María Luis Mora.</li> <li>Gabriel Castañeda Nolasco, Universidad Autónoma de Chiapas (UNACH).</li> <li>Carlos A. Navarrete Ulloa, Centro Universitario de Tonalá, (UdeG).</li> </ul> <p>Exposición realizada en el marco del PRONACE Vivienda en el cual se comenta la lectura:</p> <p>Lange, C. (2014). Perspectivas estratégicas y miradas tácticas: propuesta de un enfoque reflexivo en torno al desarrollo de grandes proyectos urbanos. Revista De Urbanismo, 16(30), 30–38</p> <p><a href="https://revistaatemus.uchile.cl/index.php/RU/article/view/30887">https://revistaatemus.uchile.cl/index.php/RU/article/view/30887</a></p>
Supplementary material 3 from: Bongard C, Butler K, Fulthorpe R (2013) Investigation of fungal root colonizers of the invasive plant Vincetoxicum rossicum and co-occurring local native plants in a field and woodland area in Southern Ontario. Nature Conservation 4: 55-76. https://doi.org/10.3897/natureconservation.4.3578
Supplementary material 3 from: Bongard C, Butler K, Fulthorpe R (2013) Investigation of fungal root colonizers of the invasive plant Vincetoxicum rossicum and co-occurring local native plants in a field and woodland area in Southern Ontario. Nature Conservation 4: 55-76. https://doi.org/10.3897/natureconservation.4.3578
VEL-Ar trajectory prediction model linear, co-seismic, and post-seismic grids for interpolation
<p>VEL-Ar trajectory prediction model linear, co-seismic, and post-seismic interpolation grids in ASCII format. The generation of these grids is described in http://doi.org/10.1007/s00190-015-0871-8</p>
First-principles prediction of the Co-Al phase diagram including configurational, vibrational and magnetic contributions
<p>Documentation for the Dataset used in the publication entitled "First-principles prediction of the Co–Al phase diagram including configurational, vibrational and magnetic contributions" <br>** These datasets comprise all configurations used in Co-Al system and their formation enthalpies at different temperatures, where configurational, vibrational and magnetic contributions were considered. Hcp Co and fcc Al were used as reference states. **<br>** More details about the methodology can be found in the paper "First-principles prediction of the Co-Al phase diagram including configurational, vibrational and magnetic contributions, Journal of Materials Research and Technology, 2024" **</p> <p>1. bcc-Co-Al.zip<br>- Description: bcc-Co-Al.zip is a compressed folder. It contains Al1-xCox configurations with bcc lattice used to fit the cluster expansion (CE). Each folder contains a POSCAR file that correspons to a configuration. The POSCAR can be opened with Notepad and visualized with VESTA software.</p> <p>2. fcc-Co-Al.zip<br>- Description: fcc-Co-Al.zip is a compressed folder. It contains Al1-xCox configurations with fcc lattice used to fit the CE. Each folder contains a POSCAR file that correspons to a configuration. The POSCAR can be opened with Notepad and visualized with VESTA software.</p> <p>3. hcp-Co-Al.zip<br>- Description: hcp-Co-Al.zip is a compressed folder. It contains Al1-xCox configurations with hcp lattice used to fit the CE. Each folder contains a POSCAR file that correspons to a configuration. The POSCAR can be opened with Notepad and visualized with VESTA software.</p> <p><br>4. Formation enthalpies of bcc-Co-Al.xlsx<br>- Description: Formation enthalpies of bcc lattice in Co-Al system at different temperatures, which includes the effect of lattice vibration and magnetic excitation. Fcc Al and hcp Co were used as reference states.</p> <p>- Variable description by columns:<br> 1-(Folder name) - type: numerical (integer)<br> Description: Each folder name in the bcc-Co-Al.zip corresponds to a configuration.<br> 2- (at. fraction of Co (%)) - type: numerical (float)<br> Description: The atomic fraction of Co in each configuration.<br> 3- (H_f^(conf)(DFT) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 0 K calculated by density functional theory (DFT) following eq.(18) in the paper.<br> 4- (H_f^(conf)(CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 0 K fitted by CE. <br> 6- (at. fraction of Co (%)) - type: numerical (float)<br> Description: The atomic fraction of Co in each configuration.<br> 7- (H_f^(conf+vib+mag)(Cal.) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 400 K calculated by DFT, the bond length vs. bond stiffness relationship and Monte Carlo simulation of the Heisenberg Hamiltonian following eq.(20) in the paper.<br> 8- (H_f^(conf+vib+mag)(CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 400 K fitted by CE. <br> 10- (at. fraction of Co (%)) - type: numerical (float)<br> Description: The atomic fraction of Co in each configuration.<br> 11- (H_f^(conf+vib+mag)(Cal.) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 800 K calculated by DFT, the bond length vs. bond stiffness relationship and Monte Carlo simulation of the Heisenberg Hamiltonian following eq.(20) in the paper.<br> 12- (H_f^(conf+vib+mag)(CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 800 K fitted by CE. <br> 14- (at. fraction of Co (%)) - type: numerical (float)<br> Description: The atomic fraction of Co in each configuration.<br> 15- (H_f^(conf+vib+mag)(Cal.) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 1200 K calculated by DFT, the bond length vs.bond stiffness relationship and Monte Carlo simulation of the Heisenberg Hamiltonian following eq.(20) in the paper.<br> 16- (H_f^(conf+vib+mag)(CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 1200 K fitted by CE.<br> 18- (at. fraction of Co (%)) - type: numerical (float)<br> Description: The atomic fraction of Co in each configuration.<br> 19- (H_f^(conf+vib+mag)(Cal.) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 1600 K calculated by DFT, the bond length vs.bond stiffness relationship and Monte Carlo simulation of the Heisenberg Hamiltonian following eq.(20) in the paper.<br> 20- (H_f^(conf+vib+mag)(CE) (eV/atom)) - type: numerical (float)<br> Description: Formation enthalpy of each configuration at 1600 K fitted by CE.</p> <p><br>5. Formation enthalpies of fcc Co-Al.xlsx<br>- Description: Formation enthalpies of fcc lattice in Co-Al system at different temperatures, which includes the effect of lattice vibration and magnetic excitation. Fcc Al and hcp Co were used as reference states.</p> <p>- Variable descriptions by columns are the same as those of Formation enthalpies of bcc-Co-Al.xlsx.</p> <p><br>6. Formation enthalpies of hcp-Co-Al.xlsx<br>- Description: Formation enthalpies of hcp lattice in Co-Al system at different temperatures, which includes the effect of lattice vibration and magnetic excitation. Fcc Al and hcp Co were used as reference states.</p> <p>- Variable descriptions by columns are the same as those of Formation energies of bcc-Co-Al.xlsx.</p> <p><br>7. ECIs of bcc-Co-Al at different temperatures.txt<br>- Description: ECIs of bcc lattice in Co-Al system from 0 to 2000 K with increment step of 10 K. The ECIs at different temperatures are separated by blank lines. ECIs at 0 K means that only configurational contribution was considered. ECIs at finite temperature means that configurational, vibrational and magnetic contributions were considered.</p> <p><br>8. ECIs of fcc-Co-Al at different temperatures.txt<br>- Description: ECIs of fcc lattice in Co-Al system from 0 to 2000 K with increment step of 10 K. The ECIs at different temperatures are separated by blank lines. ECIs at 0 K means that only configurational contribution was considered. ECIs at finite temperature means that configurational, vibrational and magnetic contributions were considered.</p> <p><br>9. ECIs of hcp-Co-Al at different temperatures.txt<br>- Description: ECIs of hcp lattice in Co-Al system from 0 to 2000 K with increment step of 10 K. The ECIs at different temperatures are separated by blank lines. ECIs at 0 K means that only configurational contribution was considered. ECIs at finite temperature means that configurational, vibrational and magnetic contributions were considered.</p> <p><br>10. Clusters of bcc-Co-Al.txt<br>- Description: Cluster information of bcc lattice in Co-Al system. Each cluster is separated by a blank line. Each cluster contains: multiplicity; Length of the longest pair within the cluster; number of points in cluster; coordinates of point. They are arranged in a row.</p> <p><br>11. Clusters of fcc-Co-Al.txt<br>- Description: Cluster information of fcc lattice in Co-Al system. Each cluster is separated by a blank line. Each cluster contains: multiplicity; Length of the longest pair within the cluster; number of points in cluster; coordinates of point. They are arranged in a row.</p> <p><br>12. Clusters of hcp-Co-Al.txt<br>- Description: Cluster information of hcp lattice in Co-Al system. Each cluster is separated by a blank line. Each cluster contains: multiplicity; Length of the longest pair within the cluster; number of points in cluster; coordinates of point. They are arranged in a row.</p>
RW Aur: 1.3mm continuum and CO isotopologues - ALMA observations
<p>The <strong>self-calibrated ALMA observations at 1.3mm wavelength of the RW Aur</strong>, published in <strong>Kurtovic et al., (2024c)</strong>. These observations are separated by epoch, and classified with the sufix LB or SB for "Long Baselines" and "Short Baselines". Please check the <strong>README.txt</strong> for more details about each file.</p>
Map of Co-Seismic Landslides for the M 7.8 Kaikoura, New Zealand Earthquake
<p>Prepared by the Research Group on Earthquake Geology in Greece (http://eqgeogr.weebly.com/)</p> <p>Version 2 (updated)</p> <p>With the release of new Sentinel-2 images, and other available resources for the M7.8 Kaikoura earthquake, we present an update of the Map of Co-Seismic Landslides and Surfaces Ruptures (As of 27/11/2016). Landslides were mapped using Sentinel-2 satellite images from Copernicus, European Space Agency, dated November and December 2016. Images were visually compared with previous last available S2A images without cloud cover (13 September and 26 October) and landslides and large slope failures were manually mapped. Areas covered by cloud are omitted and shown on map. 5875 landslide sites are shown in the map. A small number of landslides could have been mis-identified due to insufficient resolution of the images, small gaps of cloud cover or for other reasons. Also, re-activated landslides on the central mountainous area were unabled to identify due to imagery restrictions (medium resolution, relief shadows etc). Some local gaps in Sentinel imagery still exist due to cloud cover, but we believe the current map is very close to the major distribution of mass movement effects. Surface ruptures were mapped using Sentinel-2 imagery and approximate position from photos of the post-earthquake aerial surveys of Environment Canterbury Regional Council (http://ecan.govt.nz)</p> <p>KML file contains7355 landslide spots.</p>
Elevation modulates the phenotypic responses to light of four co-occurring Pyrenean forest tree species
<p>Data on plant water potential for seedlings of four Pyrenean tree species planted along an elevation gradient. The dataset contains three files:</p> <ol> <li><strong>Biomass.txt: </strong>Data on plant biomass per fraction (leaf, stem and roots) 4 years after plantation. Included variables:<br> - Piso (factor): elevational stage at which the seedling was planted. Two levels: montane (M) or subalpine (S)<br> - Luz (factor): whether the seedling was plantes at a gap or in the understory. Two levels: gap (O) or understroy (T)<br> - N (numeric): number of plant in that plot<br> - Sp (factor): species. Four levels: BEPE (Betula pendula) / PISY (Pinus sylvestris) / PIUN (Pinus uncinata) / ABAL (Abies alba)<br> - Planta (factor): code to identify uniquely each plant<br> - File (factor): code to identify uniquely each plant<br> - GLI (num): Global Light Index, the amount of irradiance that receives each seedling<br> - Code (factor): code to identify uniquely each plant<br> - PLB (numeric): total plant biomass (g)<br> - LFB (numeric): leaf biomass (g)<br> - STB (numeric): stem biomass (g)<br> - RTB (numeric): root biomass (g)<br> - LMF (numeric): leaf mass fraction (LFB/PLB)<br> - SMF (numeric): stem mass fraction (STB/PLB)<br> - RMF (numeric): root mass fraction (RTB/PLB)<br> - SLA (numeric): specific leaf area<br> - H (numeric): plant height (mm)<br> - D (numeric): plant diameter at root collar (mm)<br> - PB2 (numeric): total plant biomass without considering leaves (g)<br> - SF2 (numeric): stem mass fraction without considering leaves (STB/PB2)<br> - RF2 (numeric): root mass fraction without considering leaves (RTB/PB2)</li> <li><strong>init_biomass.txt:</strong> for biomass at the moment of plantation<br> - Piso (factor): elevational stage at which the seedling was planted. Two levels: montane (M) or subalpine (S)<br> - N (numeric): number of plant<br> - Sp (factor): species. Four levels: BEPE (Betula pendula) / PISY (Pinus sylvestris) / PIUN (Pinus uncinata) / ABAL (Abies alba)<br> - Planta (factor): code to identify uniquely each plant<br> - File (numeric): code to identify uniquely each plant<br> - PB (numeric): total plant biomass (g)<br> - LB (numeric): leaf biomass (g)<br> - SB (numeric): stem biomass (g)<br> - RB (numeric): root biomass (g)</li> <li><strong>WaterPot.txt</strong>: data on plant water potential for seedlings of four Pyrenean tree species planted along an elevation gradient during a period of intense drought<br> - Piso (factor): elevational stage at which the seedling was planted. Two levels: montane (M) or subalpine (S)<br> - Luz (factor): whether the seedling was plantes at a gap or in the understory. Two levels: gap (O) or understroy (T)<br> - N (numeric): number of plant <br> - Parcela (factor): identifier ofthe plot<br> - Sp (factor): species. Four levels: BEPE (Betula pendula) / PISY (Pinus sylvestris) / PIUN (Pinus uncinata) / ABAL (Abies alba)<br> - Estacion (factor): the moment for the measurement. One level: September<br> - GLI (numeric): global light index, the ration of total irradiance received by the plant at the moment of plantation<br> - WPt (numeric): water potential (bars)</li> </ol>
Sentiment analysis of tech media articles using VADER package and co-occurrence analysis
<p><strong>Sentiment analysis of tech media articles using VADER package and co-occurrence analysis</strong></p> <p><strong>Sources</strong>: Above 140k articles (01.2016-03.2019):</p> <ul> <li>Gigaom 0.5%</li> <li>Euractiv 0.9%</li> <li>The Conversation 1.3%</li> <li>Politico Europe 1.3%</li> <li>IEEE Spectrum 1.8%</li> <li>Techforge 4.3%</li> <li>Fastcompany 4.5%</li> <li>The Guardian (Tech) 9.2%</li> <li>Arstechnica 10.0%</li> <li>Reuters 11%</li> <li>Gizmodo 17.5%</li> <li>ZDNet 18.3%</li> <li>The Register 19.5%</li> </ul> <p><strong>Methodology</strong></p> <p>The sentiment analysis has been prepared using VADER*, an open-source lexicon and rule-based sentiment analysis tool. VADER is specifically designed for social media analysis, but can be also applied for other text sources. The sentiment lexicon was compiled using various sources (other sentiment data sets, Twitter etc.) and was validated by human input. The advantage of VADER is that the rule-based engine includes word-order sensitive relations and degree modifiers.</p> <p>As VADER is more robust in the case of shorter social media texts, the analysed articles have been divided into paragraphs. The analysis have been carried out for the social issues presented in the co-occurrence exercise.</p> <p>The process included the following main steps:</p> <ul> <li>The 100 most frequently co-occurring terms are identified for every social issue (using the co-occurrence methodology)</li> <li>The articles containing the given social issue and co-occurring term are identified</li> <li>The identified articles are divided into paragraphs</li> <li>Social issue and co-occurring words are removed from the paragraph</li> <li>The VADER sentiment analysis is carried out for every identified and modified paragraph</li> <li>The average for the given word pair is calculated for the final result</li> </ul> <p>Therefore, the procedure has been repeated for 100 words for all identified social issues.</p> <p>The sentiment analysis resulted in a compound score for every paragraph. The score is calculated from the sum of the valence scores of each word in the paragraph, and normalised between the values -1 (most extreme negative) and +1 (most extreme positive). Finally, the average is calculated from the paragraph results. Removal of terms is meant to exclude sentiment of the co-occurring word itself, because the word may be misleading, e.g. when some technologies or companies attempt to solve a negative issue. The neighbourhood's scores would be positive, but the negative term would bring the paragraph's score down.</p> <p>The presented tables include the most extreme co-occurring terms for the analysed social issue. The examples are chosen from the list of words with 30 most positive and 30 most negative sentiment. The presented graphs show the evolution of sentiments for social issues. The analysed paragraphs are selected the following way:</p> <ul> <li>The articles containing the given social issue are identified</li> <li>The paragraphs containing the social issue are selected for sentiment analysis</li> </ul> <p>*Hutto, C.J. & Gilbert, E.E. (2014). VADER: A Parsimonious Rule-based Model for Sentiment Analysis of Social Media Text. Eighth International Conference on Weblogs and Social Media (ICWSM-14). Ann Arbor, MI, June 2014.</p> <p> </p> <p><strong>Files</strong></p> <p>sentiments_mod11.csv sentiment score based on chosen unigrams</p> <p>sentiments_mod22.csv sentiment score based on chosen bigrams</p> <p>sentiments_cooc_mod11.csv, sentiments_cooc_mod12.csv, sentiments_cooc_mod21.csv, sentiments_cooc_mod22.csv combinations of co-occurrences: unigrams-unigrams, unigrams-bigrams, bigrams-unigrams, bigrams-bigrams</p> <p> </p>
Co-occurrences of trending keywords in popular tech media
<p><strong>Co-occurrences of trending keywords in the tech media (01.2016-03.2019)</strong></p> <p><strong>Sources</strong></p> <ul> <li>Gigaom 0.5%</li> <li>Euractiv 0.9%</li> <li>The Conversation 1.3%</li> <li>Politico Europe 1.3%</li> <li>IEEE Spectrum 1.8%</li> <li>Techforge 4.3%</li> <li>Fastcompany 4.5%</li> <li>The Guardian (Tech) 9.2%</li> <li>Arstechnica 10.0%</li> <li>Reuters 11%</li> <li>Gizmodo 17.5%</li> <li>ZDNet 18.3%</li> <li>The Register 19.5%</li> </ul> <p><strong>Methodology</strong></p> <ul> <li>Exploring the relationship between topics</li> <li>Pairs of terms which are mentioned together in media articles</li> <li>Most trending social issues have been selected (e.g. 'metoo', 'gdpr')</li> <li>The co-occurrence analysis is calculated for pairs consisting of emerging social issues and trending uni/bigrams</li> <li>The number of times the terms appear in articles together with a social issue is divided by the number of times the social issue is mentioned across all articles</li> <li>A single index is constructed for all word pairs by weighted average (taking into account the prevalence of the given source)</li> </ul> <p><strong>Files</strong></p> <p>unigram-unigram co-occurrences: cooc11weighted.csv</p> <p>unigram-bigram co-occurrences: cooc12weighted.csv</p> <p>bigram-unigram co-occurrences: cooc21weighted.csv</p> <p>bigram-bigram co-occurrences: cooc22weighted.csv<br> </p> <p> </p>
Supplementary data files for Manzano-Marín 2020 "No evidence for Wolbachia as a nutritional co-obligate endosymbiont in the aphid Pentalonia nigronervosa"
<p>Supplementary data for Manzano-Marín 2019 "No evidence for Wolbachia as a nutritional co-obligate endosymbiont in the aphid Pentalonia nigronervosa".</p> <p>The data in "supplementary_data.tar.gz" consists of six folders:</p> <p>1) "Buchnera_GenBank_annotation”: GenBank-formatted file of the annotated genes of <em>Buchnera</em> from <em>Pentalonia nigronervosa</em> (BPn).</p> <p>2) "Buchnera_gene_BLAST_search”: Tabular BLAST output files and FASTA-formatted files of the identified <em>Buchnera</em> Bpn genes.</p> <p>3) "P_nigronervosa_blastx_binning”: Tabular BLAST output files and FASTA-formatted files of the <em>Buchnera</em>, <em>Wolbachia</em>, and mitochondrion bins.</p> <p>4) "P_nigronervosa_BOWTIE_map_vs_bins": BAM-formatted alignment files for read libraries vs. <em>Buchnera</em> and <em>Wolbachia</em> bins from <em>Pentalonia nigronervosa</em>.</p> <p>5) "P_nigronervosa_BOWTIE_map_vs_genes": BAM-formatted alignment files for read libraries vs. genes from <em>Buchnera</em> and <em>Wolbachia</em> bin from <em>Pentalonia nigronervosa</em>.</p> <p>6) "P_nigronervosa_SPAdes_assembly": Output files for pooled SPAdes assembly.</p> <p>Also, the filtered and trimmed FASTQ files used for genome assembly can be found in the comrpessed file "read_files_clean.tar.gz".</p>
Al-Ni-Co quasicrystalline melt-spun alloy - microstructure and catalytic properties
<p>This set contains supplementary data for the work: Al-Ni-Co decagonal quasicrystal application as an energy-effective catalyst<br>for phenylacetylene hydrogenation, Sustainable Materials and Technologies 41 (2024) e01055, https://doi.org/10.1016/j.susmat.2024.e01055</p> <p> </p> <p>SEM BSE images present the microstructure of the cross-section of the ribbon.</p> <p>MS_Surf images show the surface of the ribbons acquired using an optical microscope.</p> <p>TEM images were named as follows:</p> <p>ms_ribb - melt-spun ribbon</p> <p>nabh4_ribb - ribbon cleaned with NaBH4 aqueous solution</p> <p>liq_ribb - ribbon recovered after phenylacetylene hydrogenation reaction </p> <p><a href="../api/records/13371995/draft/files/phenylacetylene%20hydrogenation%20reactions.ods/content" target="_blank" rel="noopener noreferrer">phenylacetylene hydrogenation reactions.ods</a> - Reaction course of phenylacetylene hydrogenation reactions with new portions of catalyst. Chemical composition of the reaction mixture was evaluated using the gas chromatography method.</p> <p>XPS spectra were collected for surfaces of ribbons in a melt-spun form and recovered after the phenylacetylene hydrogenation reaction. </p> <p> </p> <p>The material preparation and microstructural analyses were performed at the Institute of Metallurgy and Materials Science of the Polish Academy of Sciences.</p> <p>The experimental procedure for material preparation, instrumentation, data collection and results analysis were described in the work: https://doi.org/10.1016/j.susmat.2024.e01055</p> <p> </p> <p>Preparation of materials: Amelia Zięba</p> <p>TEM images collection (FEI Tecnai G2, ThermoFisher Titan Themis G2 200 Probe Cs-Corrected): Amelia Zięba, Lidia Lityńska-Dobrzyńska</p> <p>SEM images acquisition (FEI E-SEM XL-30): Amelia Zięba</p> <p>Catalytic performance tests: Dorota Duraczyńska</p> <p>XPS study: Mateusz Marzec</p> <p> </p> <p><em><strong>Acknowledgements</strong></em></p> <p><strong><em>The work was financially supported by the National Science Centre (NCN), Poland, project No. 2021/41/N/ST8/02533.</em></strong></p> <p> </p>
Supporting information of a study for the definition and evaluation of a graphical user interface for housing co-design
<p>This dataset is from a study that intends to define, prototype and test a graphical user interface for a housing co-design system. To define the requirements of the interface, we conducted interviews with professionals of architecture, urbanism and social sciences areas, as well as with housing cooperatives and inhabitants of these institutions. An interface solution was prototyped, tested and refined. Then we conducted a heuristic evaluation and a summative evaluation. Such evaluations involved the testing of a high-fidelity prototype, to receive feedback from UX/UI experts, potential users (inhabitants) and architects.</p> <p>S1_File refers to the interview protocol used with the three groups of interviewees. We share the English and Portuguese versions of the interviews with professionals and the original (Portuguese) and translated versions of the remaining ones since these were conducted in Portuguese.</p> <p>S2_File is a dataset reporting the results of the interviews. Each question includes the answers given and the identification (anonymized) of the interviewees who responded to that question.</p> <p>S3_File describes the usability issues identified by the experts during the heuristic evaluation of the high-fidelity prototype. The first page organizes the issues by severity (left) and priority (right). The remaining pages have a table for each issue, including rows for problem designation, heuristic violated, problem description, solution proposal, severity degree, and an image of the interface pointing to the referred issue.</p> <p>S4_File refers to the results of the heuristic evaluation. It includes the identification of each issue, which expert (anonymized) identified such issue, and the heuristic it violates, with the sum of the times each heuristic was violated at the end of each column. At the right, a table presents the consolidation of issues, organized by priority, with columns identifying the issue, severity level, frequency, and priority.</p> <p>S5_File is the script given to potential users to experiment with the interface during the summative evaluation. This script guides the user through the tasks to perform since the prototype does not have all the features functioning.</p> <p>S6_File refers to the questionnaires applied during the summative evaluation with inhabitants. It includes a preliminary questionnaire, a Single Ease Question (SEQ) questionnaire, a System Usability Scale (SUS) questionnaire, and a Graphical User Interface (GUI) questionnaire.</p> <p>S7_File refers to the results of the summative evaluation with inhabitants (potential users).</p> <ul> <li>Page A refers to the preliminary questionnaire with demographic information such as age, gender, education, relationship with digital technologies, etc. Each field corresponds with each inhabitant (anonymised) and the sum and percentage. In the middle, a table presents a summary of the consolidation. In the right possible relations are presented. </li> <li>Page B presents the results of the SEQ questionnaire, identifying the ratings each inhabitant (anonymized) gave each task. A summary of such values is at the right. </li> <li>On page C, the result of each rating for the SUS questionnaire given by each inhabitant (anonymized) is shown. At the bottom is the calculation of the SUS score.</li> <li>Page D presents the GUI questionnaire results for each inhabitant (anonymized), with the average and SD identified for each question. A summary of such results is on the right.</li> <li>Page E holds the notes taken by the researchers based on their observations regarding task performance. The information is organized in tables for each step of each task and includes the completeness, attempts, and time taken for each inhabitant (anonymized) to complete such task. Also, the sum, percentage, average, and SD are registered. Next to each task is a table identifying how many participants accomplished the task at the first attempt.</li> <li>Page F refers to the strong and weak aspects identified by the inhabitants. Strong and weak aspects are identified, as well as which inhabitant (anonymized) has identified them. The sum and percentage are also given. At the right, there is a table with the consolidation of results by combining similar answers. </li> </ul> <p>S8_File refers to the results of the discussion with architects after experiencing the interface. Such results relate to the positive and negative aspects that the architects identified in the interface and its usefulness for architecture. The left table identifies the strong and weak aspects that architects (anonymized) identified and the sum and percentage associated with them. The table on the right consolidates such results, with similar responses combined.</p>
Posterior CO emissions
<p>The dataset provides CO emissions from anthropogenic sources resulting from a global inversion of multispectral CO retrieval profiles (V9J) from the Measurements of Pollution in the Troposphere (MOPITT) presented in Gaubert et al., (2024). The analysis is performed using a quantile-conserving ensemble filter framework (QCEFF), specifically with a bounded normal rank histogram (BNRH) distribution for the prior, using the Data Assimilation Research Testbed (DART). The posterior emissions are derived on the global Community Atmosphere Model with Chemistry (CAM-Chem) model grid at the horizontal resolution is 0.9° latitude by 1.25° longitude. The prior emissions are CAMS-GLOB-ANT version 5.3 (Soulié et al., 2024) and the Fire Inventory from NCAR version 2.5 (Wiedinmyer et al., 2023).</p>
Montserrat Digital Surface Model (1 metre) - March 2019 - Pleiades Photogrammetry (raw, not co-registered)
<p>This tiff file contains a Digital Surface Model (DSM) of the southern portion of Montserrat, Eastern Caribbean, including the Soufrière Hills Volcano. This is the raw DSM, generated via leverage of Pleiades tri-stereo imagery using the DSM-OPT software platform; it has not been co-registered. </p>
Belham River Valley Digital Surface Model (1 metre) - March 2019 - Pleiades Photogrammetry (co-registered)
<p>This tiff contains a Digital Surface Model (DSM) of the Belham River Valley in Montserrat, Eastern Caribbean. This was generated via leverage of Pleiades tri-stereo imagery throught the DSM-OPT software platform. This DSM has been co-registered to a LiDAR DSM (generated in 2010, vertical error 0.15 m) and found to have a vertical error of 2.3 m.</p>
Co-citations Map: Literature review on Learning Ecologies, 1991-2018
<p>The co-citation map was adopted as type of analysis over 85 papers sampled from five scientific databases (pls. cfr: <a href="https://zenodo.org/record/1503775#.W_rUn-hKg2w">Systematic Review on the Research Topic "Learning Ecologies" - Dataset and Analysi</a>s". This was adopted as method to further understand the relationships and advancement of work relating the concept of LE.</p> <p>The software tool to carry out this phase of the study was <a href="http://www.citnetexplorer.nl/ ">Citenet Explorer</a> for the analysis and visualization of co-citations along the period 1999-2018.</p> <p>The total number of citations and the relationships between most cited authors and all authors were extracted from the corpus analyzed (<a href="https://zenodo.org/record/1503775#.W_rUn-hKg2w">Systematic Review on the Research Topic "Learning Ecologies" - Dataset and Analysi</a>s"; a specific dataset was created and the outputs were processed by the specialized software that delivers the bibliometric maps as output.</p> <p>All the instructions to use the two files that compose the dataset requested by the software, as well as the software specifications can be found at CiteNet Explore page: http://www.citnetexplorer.nl/ </p> <p>Finally, the Fig. 7 with the analysis we performed shows the co-citations map, where at a first sight it is possible to see two main groups of nodes or authors cited (X axis) across a timespan (Y axis), and sparse elements at the center and at the beginning of the period (1991). The main and more compact group (also in terms of clusterisation of nodes, which are showed in green) related the publications that cite the seminal work of Barron (2004). These publications are mostly classified as using socio-constructivist theories and are placed in the area of social sciences, while for other categories (such as the methodological approach, research applications and the alignment are more fragmented). There are four seminal works (Abd-El-Khalick & Akerson, 2004; Barron, 2004; T ; Okamoto, Kayama, Inoue, & Cristea, 2002; Toshio Okamoto & Kayama, 2004) to which other papers can be connected. Beyond the mentioned work of Barron, the other three works can be placed in the area of technology (development of eLearning environments) and STEM education, supporting the idea of disciplinary fragmentation.</p>
Measurements of savanna landscap fire emission factors for CO2, CO, CH4 and N2O using a UAV-based sampling methodology
<p>This dataset contains direct measurements of biomass burning emission factors for CO<sub>2</sub>, CO, CH<sub>4</sub> and N<sub>2</sub>O. It includes over 4500 EF bag measurements sampled using an unmanned aerial system (UAS), and measured fuel parameters and fire severity proxies during 129 individual fires. The measurements cover a variety of savanna ecosystems in Brazil, Australia, Botswana, Zambia, South-Africa and Mozambique under different seasonal conditions, sampled over the course of six fire seasons between 2017 and 2022. The table in the included word file explains the individual columns in the excell file. </p> <p> </p>
Two years of CO2 CO and CH4 from The Cyprus Institute at Nicosia, Cyprus
<p>Two years of carbon dioxide (CO2), carbon monoxide (CO) and methane (CH4) concentration measurements, were performed for the first time in the city of Nicosia, Cyprus from 11/02/2020 to 07/09/2022.</p> <p>The dataset is generated from three Picarro G2401s. Property of LSCE (187) and CYI (1172 &1173). They were consecutively installed at the Cyprus Institute, on top of the NTL building, in Nicosia residential area. The dataset was processed by LSCE at Gif-sur-Yvette in France and calibrated against a World Meteorological Organization (WMO) reference scale. </p> <p>The Eastern Mediterranean and Middle East (EMME) region, with its population of more than 400 million, is identified as one of the primary climate “hot spots” worldwide, experiencing adverse impacts ranging from extreme weather events to poor air quality. Projections show that these phenomena are expected to further exacerbate in the coming decades. At central position, lies Cyprus, an island country that receives long-range transported pollution from various anthropogenic and natural sources.</p> <p> </p>
Network data and script accompanying the paper "Operationalizing anthropological theory: four techniques to simplify networks of co-occurring ethnographic codes"
<p>This repository accompanies the paper<a href="https://rdcu.be/dbuhi"> "Operationalizing anthropological theory: four techniques to simplify networks of co-occurring ethnographic codes"</a>, by Cottica et al. It contains:</p> <ol> <li>A data file, containing networks of co-occurrence of ethnographic codes from three ethnographies. Data are pseudonymized (see the paper for details).</li> <li>A script that, when run on the data, produces simplified versions of each network. Simplifications follow four different techniques, described in the paper. Each technique relies on a tuning parameter, so that, for each network and each techniques, the script produces several simplified networks, each one associated with a unique value of the tuning parameter.</li> </ol> <p>The data file format is that of a Tulip perspective. To open, download Tulip (https://tulip.labri.fr), launch it and open the file from within the Tulip GUI.</p> <p>The script file is in Python. To run, open it from within the Tulip IDE first.</p> <p> </p>
UTHSC Publication Research Category (ANZSRC 2020) Co-Occurrence
<p>This data visualization is a bibliometric analysis of University of Tennessee Health Science Center publications for the years 2018-2020. It was created for senior University leadership for the purposes of strategic planning and identifying research areas of strength.</p> <p>Bibliographic data was supplied by Dimensions by Digital Science. The chord graph was created in Tableau and demonstrates relationship pairs of Fields of Research (ANZSRC 2020) categories. Each publication record may be associated with 1+ categories. The graph highlights the frequency of category pairings within a single publication record. I.e. publications categorized as "Immunology" are most commonly also categorized with "Medical Microbiology," indicating overlap in this area of research.</p> <p>This graph was created using instructions from Marc Reid's datavis.blog entry "Creating a Chord Diagram with Tableau Prep and Desktop" (<a href="https://datavis.blog/2020/07/02/creating-chord-diagram-in-tableau/">https://datavis.blog/2020/07/02/creating-chord-diagram-in-tableau/</a>).</p> <p>The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.</p>
ScienceDex guides
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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.