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Fig. 2 in New information on ornithopod dinosaurs from the Late Jurassic of Portugal
Fig. 2. Cranial material of Dryosauridae indet. from the Lourinhã municipality, Portugal, Lourinhã Formation, Kimmeridgian–Tithonian. A. ML 1851, parietal in dorsal (A1, A3) and ventral (A2, A4) views. B. ML 768, dentary in lateral (B1), dashed frame indicates area with foramina, dorsal (B2), medial (B3) and ventral (B4) views, detail of dentary tooth (B5).
COVID information commons archive
<p>The COVID Information Commons (CIC) is an open website portal and community to facilitate knowledge-sharing and collaboration across various COVID research efforts, funded by the <a href="https://beta.nsf.gov/funding/initiatives/convergence-accelerator" target="_blank" rel="noopener">NSF Convergence Accelerator</a> and the <a href="https://beta.nsf.gov/tip/latest" target="_blank" rel="noopener">NSF Technology, Innovation and Partnerships Directorate</a>. The CIC serves as an open resource for researchers, students, and decision-makers from academia, government, not-for-profits and industry to identify collaboration opportunities, to leverage each other's research findings, and to accelerate the most promising research to mitigate the broad societal impacts of the COVID-19 pandemic.</p> <p>The CIC was developed as a collaborative proposal led by the <a href="http://nebigdatahub.org/" target="_blank" rel="noopener">Northeast Big Data Innovation Hub</a>, hosted by Columbia University, in collaboration with the <a href="https://midwestbigdatahub.org/" target="_blank" rel="noopener">Midwest Big Data Innovation Hub</a>, <a href="https://southbigdatahub.org/" target="_blank" rel="noopener">South Big Data Innovation Hub</a>, and <a href="https://www.westbigdatahub.org/" target="_blank" rel="noopener">West Big Data Innovation Hub</a>. It was funded by the NSF Convergence Accelerator (<a href="https://www.nsf.gov/awardsearch/showAward?AWD_ID=2028999&HistoricalAwards=false" target="_blank" rel="noopener">NSF #2028999</a>) in May 2020 and launched in July 2020. The initial focus of the CIC website was on the 723 NSF-funded COVID Rapid Response Research (RAPID) projects funded in 2020. The CIC-E: COVID Information Commons Extension for Pandemic Recovery project was proposed and funded in 2021 (<a href="https://www.nsf.gov/awardsearch/showAward?AWD_ID=2139391&HistoricalAwards=false" target="_blank" rel="noopener">NSF #2139391</a>) by the <a href="https://covidinfocommons.datascience.columbia.edu/content/project-team">CIC project team</a> with the goal to increase researcher collaboration across NSF and NIH awardees and with global collaborators, as we continue to combat the novel coronavirus, and glean learnings for future uses of innovations developed for COVID response and recovery, including potential insights which can be leveraged for future pandemics.</p> <p>The CIC extension launched on June 30, 2022 increasing the corpus of awards from just NSF to include NIH-funded COVID related awards, both present and past, through all funding vehicles, in pertinent areas of COVID research, response and recovery. The CIC-extension provides more opportunity for multi-agency and multidisciplinary research collaboration as all the Principal Investigators (PIs) for awards in the CIC are invited to present their research and collaborate on CIC Research Lighting Talk Webinars and Collaboration Sessions.</p>
List of information objects of Northern Cluster in OneNet project
<p>List of information objects includes in CSV format the names and descriptions of role-to-role data exchanges referred to in the use cases of OneNet Northern cluster.</p> <p>The context of usage of the information objects in business use case and system use cases can be found here: <a href="https://onenet-project.eu/wp-content/uploads/2023/10/D7.2_OneNet_v1.0.pdf">https://onenet-project.eu/wp-content/uploads/2023/10/D7.2_OneNet_v1.0.pdf</a>,<a href="https://onenet-project.eu/wp-content/uploads/2023/05/OneNet_D7.3_v1.0-1.pdf"> https://onenet-project.eu/wp-content/uploads/2023/05/OneNet_D7.3_v1.0-1.pdf</a>,<a href="https://onenet-project.eu/wp-content/uploads/2022/12/OneNet_D7.4_v.1.0.pdf">https://onenet-project.eu/wp-content/uploads/2022/12/OneNet_D7.4_v.1.0.pdf</a></p>
Supporting Information
<p><span>Datasets supporting the analysis and conclusions for the research "</span><strong><span>Evaluation of CO<sub>2</sub> Hydrate Saturation in Porous Core Experiments Using Medical CT Images"</span></strong><span>.</span></p>
Developmental isoform diversity in the human neocortex informs neuropsychiatric risk mechanisms
<p>RNA splicing is highly prevalent in the brain and has strong links to neuropsychiatric disorders, yet the role of cell-type-specific splicing or transcript-isoform diversity during human brain development has not been systematically investigated. Here, we leveraged single-molecule long-read sequencing to deeply profile the full-length transcriptome of the germinal zone (GZ) and cortical plate (CP) regions of the developing human neocortex at tissue and single-cell resolution. We identified 214,516 unique isoforms, of which 72.6% are novel (unannotated in Gencode-v33), and uncovered a substantial contribution of transcript-isoform diversity, regulated by RNA binding proteins, in defining cellular identity in the developing neocortex. We leveraged this comprehensive isoform-centric gene annotation to re-prioritize thousands of rare de novo risk variants and elucidate genetic risk mechanisms for neuropsychiatric disorders.</p>
Detailed information on cost and sale prices on Polish pig market in the period 2017-mid2022
<p>The database contains detailed information on costs and sale prices of piglets and finishers on Polish martket in the period January 2017 - July 2022. The prices of cereals used for feeding are taken from the average monthly data of the Ministry of Agriculture and the daily stock exchange quotations of Agrolok. The remaining operational costs (veterinary costs, utilities, labor, and transport) were assumed at a constant average level established on the basis of the reference methodological publication of the Danish research and development organization called “Seges Innovation” (2022) and a manual on pig farming (Pawłowski, 2020). The same sources were used to determine the optimal feeding model, which is important for calculating feed costs. Assumptions for calculating feed cost, the cost of falls, labor costs in piglet and finisher production, as well as piglet transportation costs are presented in the excel sheet.</p>
Local optima network metrics from the IEEE CEC 2024 paper "Information flow and Laplacian dynamics on local optima networks"
<p>Local optima network metrics from the IEEE CEC 2024 paper "Information flow and Laplacian dynamics on local optima networks". </p> <p>There are two CSV files: one for each of the two iterated local search confgurations used to construct the networks (low or high). In each file, a row contains information about one QAPLIB instance. Easch row contains all the metrics computed for the associated LON and also algorithm performance data on the instance. </p>
Data, code, and supplementary information for Hyracoid locus identification
<p>Serially homologous elements pose an identification problem in fragmentary records, particularly those of vertebrate fossils. Examples include individual vertebrae in the vertebral column and teeth in a tooth row. Until an isolated element can be accurately attributed to a specific position within its series, multiple lines of ecological and evolutionary research cannot be conducted. However, varying levels of differentiability between loci, and varying patterns of differentiation across clades, make it impossible to develop a single set of diagnostic traits for any particular set of serial homologs, particularly mammalian molars. Here, we test the utility of a set of classification criteria for distinguishing molar tooth positions of hyraxes (Mammalia, Afrotheria, Hyracoidea), which have been considered indistinguishable in previous taxonomic studies. As part of the test, we evaluate the degree to which between-locus variation is conservative in this taxon, which would strengthen the predictive power of proposed traits even in cases where species identity is unknown. Suitable tests for hypotheses of conservatism in categorical traits did not exist, to our knowledge, and we, therefore, explored the behavior of previously developed metrics, Borges et al.'s δ, to assess conservatism in contrast to the phylogenetic signal produced by Brownian motion. This metric shows some promise but the nature of resulting distributions makes tests difficult to interpret, indicating a line of potential future methods improvement. We used a linear morphometric characterization of shape to validate the candidate traits. In the case of hyracoid molars, relatively simple ratios of linear measurements have strong discriminatory power despite evolutionary variation in between-locus differences. Overall, new or understudied taxa are likely to have lower molar loci differentiable by their relative length and talonid vs. trigonid width.</p>
Supplementary Information for Chemical Properties of the Southeast Asian Haze from Indonesian Peatland Fires
<p>This repository contains supplementary information (SI-1 and SI-2) related to the article entitled "Chemical Properties of the Southeast Asian Haze from Indonesian Peatland Fires" published in Global Environmental Research (GER, Volume 27, No.1, Pages 37–48, Year 2023, <a href="https://doi.org/10.57466/ger.27.1_37" target="_blank" rel="noopener">https://doi.org/10.57466/ger.27.1_37</a>). SI-1 contains the newly created dataset used in GER and SI-2 contains supplementary documents for Sections 4 and 6 as well as tables and figures referred to but not included in the main article of GER.</p>
Improving distribution models of sparsely-documented disease vectors by incorporating information on related species via joint modeling
<p>A necessary component of understanding vector-borne disease risk is the accurate characterization of the distributions of their vectors. Species distribution models have been successfully applied to data-rich species but may produce inaccurate results for sparsely-documented vectors. In light of global change, vectors that are currently not well-documented could become increasingly important, requiring tools to predict their distributions. One way to achieve this could be to leverage data on related species to inform the distribution of a<strong> </strong>sparsely-documented vector based on the assumption that the environmental niches of related species are not independent. Relatedly, there is a natural dependence of the spatial distribution of a disease on the spatial dependence of its vector. Here, we propose to exploit these correlations by fitting a hierarchical model jointly to data on multiple vector species and their associated human diseases to improve distribution models of sparsely-documented species. To demonstrate this approach, we evaluated the ability of twelve models—which differed in their pooling of data from multiple vector species and inclusion of disease data—to improve distribution estimates of sparsely-documented vectors. We assessed our models on two simulated data sets, which allowed us to generalize our results and examine their mechanisms. We found that when the focal species is sparsely documented, incorporating data on related vector species reduces uncertainty and improves accuracy by reducing overfitting. When data on vector species are already incorporated, disease data only marginally improve model performance. However, when data on other vectors are not available, disease data can improve model accuracy and reduce overfitting and uncertainty. We then assessed the approach on empirical data on ticks and tick-borne diseases in Florida and found that incorporating data on other vector species improved model performance. This study illustrates the value of exploiting correlated data via joint modeling to improve distribution models of data-limited species.</p>
Dispilio. Supplementary Information for Maczkowski et al., Absolute dating of the European Neolithic using the 5259 BC rapid 14C excursion
<p>Supplementary Material for the paper "Absolute dating of the European Neolithic using the 5259 BC rapid 14C excursion":</p> <p> </p> <p><strong>Supplementary Information</strong> includes OxCal code, wiggle-matching output, photographs of the Neolithic juniper wood samples analysed, photographs of the tree-ring sampling for annual radiocarbon, photographs of modern tree-ring analogues, supplementary text on the data presented in the article, as well as the tree-ring width measurements in Heidelberg format (.fh).</p> <p><strong>Supplementary Data 1-2 </strong>includes spreadsheets with all the new raw radiocarbon data presented in the article, the associated uncertainties and ring numbers.</p> <p><strong>Supplementary Data 3</strong> includes the R code and the source data used for the generation of Figures 3 and 5 in the main article text, as well as the OxCal code used for the wiggle-matching of annual 14C in OxCal as presented in Fiugre 5</p> <p>The latest version of the Supplementary Material is just an expanded version of the first, files have been renamed according to editorial guidlines, few extra figures, OxCal code, and extra information added after the review process. No changes were made to any of the data published online in the initial version of the Supplementary Material.</p> <p> </p> <p>File renaming from last version:</p> <p>Supplementary Material = Supplementary Information</p> <p>Supplementary Material S1 = Supplementary Note 1</p> <p>Supplementary Material S2 = Supplementary Figures</p> <p>Supplementary Material S3 = Supplementary Note 2</p> <p>Supplementary Table T1 = Supplementary Data 1-2</p> <p>Supplementary Material S4 = Supplementary Data 3</p> <p> </p>
F I G U R E 3 in Biological information on a rare pelagic fish, black ruff Centrolophus niger, caught in Icelandic waters: Distribution, feeding, and otoliths
F I G U R E 3 Images of the proximal and distal sides of the right and left otoliths from black ruff Centrolophus niger (Gmelin, 1789). Scale bar and the plane at which the length and width of the otolith were measured are shown.
F I G U R E 1 in Biological information on a rare pelagic fish, black ruff Centrolophus niger, caught in Icelandic waters: Distribution, feeding, and otoliths
F I G U R E 1 Three specimens of black fish (Centrolophus niger) caught during the International Ecosystem Summer Survey of the Nordic Seas in 2021. Specimens were photographed prior to freezing. Photograph by James Kennedy.
F I G U R E 8 Total length v in Biological information on a rare pelagic fish, black ruff Centrolophus niger, caught in Icelandic waters: Distribution, feeding, and otoliths
F I G U R E 8 Total length v. (a) total weight, (b) fork length, and (c) standard length for black ruff Centrolophus niger (Gmelin, 1789) from the current and previous studies. The origin of the previous data is indicated in the legend. (a) Nonlinear and (b, c) linear regression models are shown. Note that total weight corresponds to frozen weight for measurements in the current study, whereas for previous studies, corresponds to the weight given in the respective study.
F I G U R E 2 in Biological information on a rare pelagic fish, black ruff Centrolophus niger, caught in Icelandic waters: Distribution, feeding, and otoliths
F I G U R E 2 Location of sampling stations of the Icelandic component of the International Ecosystem Summer Survey of the Nordic Seas 2009–2021. Stations where black ruff Centrolophus niger (Gmelin, 1789) were caught are shown in Black. The main surface currents in the Northeast Atlantic are shown in the final panel; the cold East Greenland current (green) and the warm Atlantic current (red) (Blindheim & Østerhus, 2005).
F I G U R E 7 Total length v in Biological information on a rare pelagic fish, black ruff Centrolophus niger, caught in Icelandic waters: Distribution, feeding, and otoliths
F I G U R E 7 Total length v. (a) frozen weight, (b) fork length, (c) and standard length and frozen weight v. (d) thawed weight for black ruff Centrolophus niger (Gmelin, 1789). (a) Nonlinear and (b–d) linear regression models are shown (a–d) as well as x = y line (d).
F I G U R E 4 in Biological information on a rare pelagic fish, black ruff Centrolophus niger, caught in Icelandic waters: Distribution, feeding, and otoliths
F I G U R E 4 Temperature profiles from the CTD probe at each station of the Icelandic part of the International Ecosystem Summer Survey of the Nordic Seas (IESSNS) where black ruff Centrolophus niger (Gmelin, 1789) were caught.
Information and questionnaire associated with GENEActiv accelerometer files collected in Vanuatu during FALAH project (non-anonymized information)
<p>Questionnaire and additional restricted participant information of the following datasets:</p> <p><a title="GENEActiv accelerometer files collected in Vanuatu during FALAH project (non-anonymized version - first part)" href="https://doi.org/10.5281/zenodo.14043547" target="_blank" rel="noopener">GENEActiv accelerometer files collected in Vanuatu during FALAH project (non-anonymized version - first part)</a><br><a title="GENEActiv accelerometer files collected in Vanuatu during FALAH project (non-anonymized version - second part)" href="https://doi.org/10.5281/zenodo.14089527" target="_blank" rel="noopener">GENEActiv accelerometer files collected in Vanuatu during FALAH project (non-anonymized version - second part)</a><br><a title="GENEActiv accelerometer files collected in Vanuatu during FALAH project (anonymized version - first part)" href="https://doi.org/10.5281/zenodo.14043331" target="_blank" rel="noopener">GENEActiv accelerometer files collected in Vanuatu during FALAH project (anonymized version - first part)</a><br><a title="GENEActiv accelerometer files collected in Vanuatu during FALAH project (anonymized version - second part)" href="https://doi.org/10.5281/zenodo.14089477" target="_blank" rel="noopener">GENEActiv accelerometer files collected in Vanuatu during FALAH project (anonymized version - second part)</a></p> <p>Participant characteristics: 13 to 17 years old students.</p> <p>Number of participants: 72.</p> <p>Year of the study: 2023.</p> <p>Place of the study: Vanuatu.</p>
Supplementary Information for "Performance evaluation of adaptive introgression classification methods"
<p>Supplementary information : supplementary figures and tables from "<em>Performance evaluation of adaptive introgression classification methods</em>", Romieu <em>et al., </em>2024 manuscript. ROC values, curves and score value by non-AI windows type for various demographic scenarios.</p>
Replication Data for: Beyond the Dailey-Townes model: chemical information from the electric field gradient
<p>This dataset collects the unprocessed (= outputs from calculations) results discussed in the paper entitled "Beyond the Dailey-Townes model: chemical information from the electric field gradient" by G. Fabbro, J. Pototschnig, and T. Saue.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.