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GENEActiv accelerometer files collected in Vanuatu during FALAH project (anonymized version - first part)
<p><a title="GENEActiv" href="https://activinsights.com/technology/geneactiv/" target="_blank" rel="noopener">GENEActiv</a> accelerometer .csv and .RData files converted with a 1 second epoch from raw GENEActiv .bin files recorded in Vanuatu during <a title="FALAH website" href="https://falah.unc.nc/" target="_blank" rel="noopener">FALAH</a> project. Devices are 60-Hz triaxial accelerometers.</p> <p>This dataset also contains <strong>participantCharacteristics.csv</strong> that povides basic information about participants and <strong>read_a_binFile_share.R</strong> that is a short R code aiming at converting and saving accelerometer data from .bin files in 1 second epoch .csv files (consider the Methods section).</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> <p>The accelerometer .csv and .RData files with a 1 second epoch and extracted from raw .bin files are available in the restricted datasets:</p> <ul> <li><a title="Anonymized dataset (first part)" href="https://doi.org/10.5281/zenodo.14043332" target="_blank" rel="noopener">anonymized version (first part)</a></li> <li><a title="Anonymized dataset (second part)" href="https://doi.org/10.5281/zenodo.14089478" target="_blank" rel="noopener">anonymized version (second part)</a></li> </ul> <p>The accelerometer raw .bin files are available in the restricted datasets:</p> <ul> <li><a title="Non-anonymized dataset (first part)" href="https://doi.org/10.5281/zenodo.14043547" target="_blank" rel="noopener">non-anonymized version (first part)</a></li> <li><a title="Non-anonymized dataset (second part)" href="https://doi.org/10.5281/zenodo.14089527">non-anonymized version (second part)</a></li> </ul> <p>Other participant characteristics (age, place of living, ...) and responses to questionnaires are available in <a title="Information and questionnaire associated with GENEActiv accelerometer files collected in Vanuatu during FALAH project (non-anonymized information)" href="https://doi.org/10.5281/zenodo.14189884" target="_blank" rel="noopener">a restricted non-anonymized dataset</a>.</p>
Project files provided as supporting information to the manuscript "How Communication Pathways Bridge Local and Global Conformations in an IgG4 Antibody: a Molecular Dynamics Study"
<p>June 23, 2021</p> <p>Thomas Tarenzi, Marta Rigoli and Raffaello Potestio</p> <p>==================================</p> <p>The dataset contains the following folders:</p> <p>- contact_area_binding_site: files with the computed surface area, used for the calculation of the contact area between PD-1 and the antibody Fab (Fig. S41).</p> <p>- hbonds_ab-pd1: number of hydrogen bonds between the antigen and the antibody, for each holo cluster (Fig. S41).</p> <p>- mutual_information: matrices with the computed mutual information, for each pair of residues (Fig. S34, S35, S46). The folder contains also the generalized correlation coefficients (Fig. S43) and the correlation scores (Fig. 4, S44, S45), computed from the mutual informations.</p> <p>- networks: communities - for each cluster, each residue is assigned to a community within the interaction network (Fig. S32, S33). betweenness - the values of edge betweenness for each cluster (S30, S31).</p> <p>- output_clustering: each frame of the apo and holo simulations is assigned a cluster index, on the basis of the structural similarity (Fig. S4).</p> <p>- PAD: per-residue values of PAD parameter, for apo and holo systems (Fig. 3, S39).</p> <p>- PCA: principal component analysis for each conformational cluster (Section S2.1).</p> <p>- representative_structures: representative structures for each conformational cluster (Fig. 2).</p> <p>- r_gyr_antibody: radii of gyration of the antibody, for each cluster (Fig. 2).</p> <p>- r_gyr_hinge: radii of gyration of the sole hinge segment, for each cluster (Fig. S36).</p> <p>- RMSD_antibody: distributions of the root-mean-square deviation of the antibody, for each cluster (Fig. S5). </p> <p>- RMSD_antigen: root-mean-square deviation of the antigen PD-1, for each cluster (Fig. S42).</p> <p>- RMSD_binding_site: distributions of the root-mean-square deviation of the residues belonging to the paratope, for each cluster (Fig. S40, S47).</p> <p>- RMSD_matrix: root-mean-square deviation between structures belonging to different pairs of clusters (Fig. S9).</p> <p>- rmsf_antigen: root-mean-square fluctuation of the antigen PD-1, for each cluster (Fig. S42).</p> <p>- rmsf_hinge: difference between the total root-mean-square fluctuations of the two hinge segments, for each cluster (Fig. S38).</p> <p>- salt_bridge: distribution of distances between residues R979 and D1377 (Fig. 4).</p> <p>- sasa_domains: contact area between Fab and Fc antibody domains, for each cluster (Fig. S8).</p> <p>- sasa_hinge: solvent accessible surface area of each hinge segment, for each cluster (Fig. S37).</p>
Data from: Recurrent sublethal warming reduces embryonic survival, inhibits juvenile growth, and alters species distribution projections under climate change
The capacity to tolerate climate change often varies across ontogeny in organisms with complex life cycles. Recently developed species distribution models incorporate traits across life stages; however, these life-cycle models primarily evaluate effects of lethal change. Here, we examine impacts of recurrent sublethal warming on development and survival in ecological projections of climate change. We reared lizard embryos in the laboratory under temperature cycles that simulated contemporary conditions and warming scenarios. We also artificially warmed natural nests to mimic laboratory treatments. In both cases, recurrent sublethal warming decreased embryonic survival and hatchling sizes. Incorporating survivorship results into a mechanistic species distribution model reduced annual survival by up to 24% compared to models that did not incorporate sublethal warming. Contrary to models without sublethal effects, our model suggests that modest increases in developmental temperatures influence species ranges due to effects on survivorship.
Wind and Solar Candidate Project Areas for Princeton REPEAT
<p>This data set contains the GIS data for solar, land-based wind, and offshore wind Candidate Project Areas (CPAs) under base (BLUA). Each record in this dataset represents a “Candidate Project Area” with attributes such as nameplate capacity, annual generation, model region, distance to transmission, etc. The Lawrence Berkeley National Lab MAPRE tools (<a href="https://mapre.lbl.gov/gis-tools/">https://mapre.lbl.gov/gis-tools/</a>) were used to create this dataset, along with input assumptions adapted from Wu et al 2020 (Grace C Wu <em>et al</em> 2020 <em>Environ. Res. Lett.</em> 15 074044) and E. Larson, C. Greig, J. Jenkins, E. Mayfield, A. Pascale, C. Zhang, J. Drossman, R. Williams, S. Pacala, R. Socolow, EJ Baik, R. Birdsey, R. Duke, R. Jones, B. Haley, E. Leslie, K. Paustian, and A. Swan, Net-Zero America: Potential Pathways, Infrastructure, and Impacts, interim report, Princeton University, Princeton, NJ, December 15, 2020.</p> <p><br> What's new in version 2: </p> <ul> <li>Solar: <ul> <li>Prime farmland eligible for utility scale solar development throughout the study area.</li> <li>Solar configuration: single-axis tracking solar assumed per VCE data</li> <li>Additional attributes calculated: <ul> <li>Aspect indicates the compass direction toward which a slope faces, measured in degrees from North in a clockwise direction from 0 to 360. Surface is flat where aspect_min = -1 (Source: https://www.sciencebase.gov/catalog/item/5540ec40e4b0a658d7939628)</li> </ul> </li> </ul> </li> <li>Wind: additional airspace and military exclusions applied <ul> <li>Airfields with arrivals and departures > 1000 buffered by 5 mi</li> <li>Weather radar stations buffered 5 mi</li> <li>NEXRAD radar buffered 3 km</li> <li>Military installations, ranges and training areas buffered 5 mi</li> </ul> </li> <li>Wind: additional attributes calculated: <ul> <li>VFR navigation landmarks (buffered 2 nautical mi)</li> <li>Navaid systems (buffered 8 nautical mi)</li> <li>Special Use Airspace (floor <=1000 ft)</li> </ul> </li> <li>Additional attribute for both solar and wind: <ul> <li>m_landcover indicates landcover type (per USGS NLCD 2016. https://www.mrlc.gov/data/legends/national-land-cover-database-2016-nlcd2016-legend)</li> </ul> </li> </ul> <p>What's new in version 3:</p> <ul> <li>Geographic extent of offshore wind increased farther west</li> </ul>
The Archaeal Proteome Project advances knowledge about archaeal cell biology through comprehensive proteomics
<p>Modern proteomics approaches can explore whole proteomes within a single mass spectrometry (MS) run. However, the enormous amount of MS data generated often remains incompletely analyzed due to a lack of sophisticated bioinformatic tools and expertise needed from a diverse array of fields. In particular, in the field of microbiology, efforts to combine large-scale proteomic datasets have so far largely been missing. Thus, despite their relatively small genomes, the proteomes of most archaea remain incompletely characterized. This in turn undermines our ability to gain a greater understanding of archaeal cell biology.</p> <p>Therefore, we have initiated the Archaeal Proteome Project (ArcPP), a community effort that works towards a comprehensive analysis of archaeal proteomes. Starting with the model archaeon <em>Haloferax volcanii</em>, using state-of-the-art bioinformatic tools, we have:</p> <ul> <li>reanalyzed more than 26 Mio. spectra</li> <li>optimized the analysis using parameter sweeps, multiple search engines implemented in Ursgal, and the combination of results through the combined PEP approach</li> <li>thoroughly controlled false discovery rates for high confidence protein identifications using the picked protein FDR approach and limiting FDR to 0.5%</li> <li>identified more than 45k peptides, corresponding to 3069 proteins (>75% of the proteome) with a median sequence coverage of 55%.</li> <li>analyzed N-terminal protein processing, including N-terminal acetylation and signal peptide cleavage</li> <li>performed a detailed glycoproteomic analysis, identifying >230 glycopeptides corresponding to 45 glycoproteins</li> </ul> <p>Benefiting from the established bioinformatic infrastructure, we will follow up on this analysis focusing on <em>H. volcanii</em> proteogenomics as well as the characterization of additional post-translational modifications. Furthermore, ArcPP will integrate quantitative results obtained from the individual datasets in order to identify common regulatory mechanisms. These studies on the <em>H. volcanii</em> proteome can serve as a blueprint for comprehensive proteomic analyses performed on a diverse range of archaea and bacteria.</p> <p> </p> <p>For further details, please refer to the following publications. Please also cite this work if you use these results for further analyses:</p> <p>Schulze, S., Adams, Z., Cerletti, M. <em>et al.</em> The Archaeal Proteome Project advances knowledge about archaeal cell biology through comprehensive proteomics. <em>Nat Commun</em> <strong>11, </strong>3145 (2020). <a href="https://doi.org/10.1038/s41467-020-16784-7">https://doi.org/10.1038/s41467-020-16784-7</a></p> <p>Schulze, S.; Pfeiffer, F.; Garcia, B.A.; Pohlschroder, M. (2021). Comprehensive glycoproteomics shines new light on the complexity and extent of glycosylation in archaea. <em>PLOS Biol</em>. https://doi.org/10.1371/journal.pbio.3001277</p> <p> </p> <p>An interactive website to explore the combined results can be found at <a href="https://archaealproteomeproject.org/">https://archaealproteomeproject.org/</a></p> <p>Scripts and metadata used for the analysis can be found at <a href="https://github.com/arcpp/ArcPP">https://github.com/arcpp/ArcPP</a></p> <p> </p> <p><strong>Updates version 1.3.0:</strong></p> <p>- includes dataset PXD021827</p> <p><strong>Updates version 1.2.0:</strong></p> <p>- Includes dataset PXD021874<br> - Includes results from a comprehensive glycoproteomic analysis of ArcPP datasets</p> <p><strong>Updates version 1.1.0:</strong><br> - <em>Natrialba magadii</em> results are included in PXD009116.zip</p>
Two decades of annual landscape-scale tree growth and dynamics in old-growth tropical rainforest in the CARBONO Project, La Selva Biological Station, 1997-2018
<p>Here we present the complete data series from a 21-yr study of the annual growth and dynamics of trees, palms and lianas in the old-growth tropical rainforest at the La Selva Biological Station in Costa Rica. These observations were part of the CARBONO Project, a multidisciplinary team study of forest carbon cycling. The project was designed to assess forest processes at the landscape scale by sampling with replication across the within-landscape edaphic heterogeneity typical of tropical forests. Through more than two decades, forest growth and dynamics were assessed annually. The annual time-step used in the CARBONO Project effectively captured forest responses to major disturbances and to interannual and climatic variation. Annual measurements also enhanced the accuracy and long-term consistency of the data. To our knowledge, the resulting records are unique for tropical forests, where the dominant approach to studying the dynamics of a given forest has been to use a single plot and multi-year inter-census intervals. To date these CARBONO Project data have revealed: multi-decadal forest stability in spite of the short-term changes in forest structure resulting from major natural disturbances (e.g., the 1997-1998 Strong El Niño, and the extreme windstorm of May 2018); the dynamics and importance of large trees; and the responses of a major component of ecosystem productivity, aboveground wood production, to interannual and long-term climatic and atmospheric change. These data have also contributed to many remote-sensing studies.</p> <p>The data set consists of annual observations through the period 1997–2018 of the floristics, survival, recruitment, and growth of all woody stems (diameter <u>></u> 10 cm) in a landscape-scale plot network. At completion of the study, the data spanned 6705 individuals and 21 years. The data set is complete and has been through extensive internal checks for quality assurance. Detailed data documentation and an emphasis on measurement repeatability were prioritized through the study. The metadata include an extensive README file describing the data files and the methods, a document detailing the data management and qa/qc, and the scanned original field data-sheets for the 22 annual censuses.</p> <p>We gratefully acknowledge the careful long-term field work and data entry and checking by paraforesters Leonel Campos Otoya and William Miranda Conejo. Logistical support and the long-term protection of the La Selva reserve were provided by the Organization for Tropical Studies. The Ministerio de Ambiente y Energía of Costa Rica granted permits to carry out this study through the years of the study (most recently: Resolución No. 037-2018-ACCVC-PI).</p>
Data from: Consequences of climatic thresholds for projecting fire activity and ecological change
Aim: Ecological properties governed by threshold relationships can exhibit heightened sensitivity to climate, creating an inherent source of uncertainty when anticipating future change. We investigated the impact of threshold relationships on our ability to project ecological change outside the observational record (e.g., the 21st century), using the challenge of predicting late‐Holocene fire regimes in boreal forest and tundra ecosystems. Location: Boreal forest and tundra ecosystems of Alaska. Time period: 850–2100 CE. Major taxa studied: Not applicable. Methods: We informed a set of published statistical models, designed to predict the 30‐year probability of fire occurrence based on climatological normals, with downscaled global climate model data for 850–1850 CE. To evaluate model performance outside the observational record and the implications of threshold relationships, we compared modelled estimates with mean fire return intervals estimated from 29 published lake‐sediment palaeofire reconstructions. To place our results in the context of future change, we evaluate changes in the location of threshold to burning under 21st‐century climate projections. Results: Model–palaeodata comparisons highlight spatially varying accuracy across boreal forest and tundra regions, with variability strongly related to the summer temperature threshold to burning: sites closer to this threshold exhibited larger prediction errors than sites further away from this threshold. Modifying the modern (i.e., 1950–2009) fire–climate relationship also resulted in significant changes in modelled estimates. Under 21st‐century climate projections, increasing proportions of Alaskan tundra and boreal forest will approach and surpass the temperature threshold to burning, with > 50% exceeding this threshold by > 2 °C by 2070–2099. Main conclusions: Our results highlight a high sensitivity of statistical projections to changing threshold relationships and data uncertainty, implying that projections of future ecosystem change in threshold‐governed ecosystems will be accompanied by notable uncertainty. This work also suggests that ecological responses to climate change will exhibit high spatio‐temporal variability as different regions approach and surpass climatic thresholds over the 21st century.
Data and outputs for NESP Project 8.3.1
<p>Data and outputs for <em>NESP Threatened Species Recovery Hub Project 8.3.1: ‘Fire-affected invertebrates: priority species and management response’</em>.</p>
Comparing and Combining Existing and Emerging Data Collection and Modeling Strategies in Support of Signal Control Optimization and Management (Project M2)
<p>For decades, traffic signal management agencies have used signal timing optimization tools combined with fine-tuning of signal timing based on field observations in their updates of time-of-day signal timing plans. These traditional signal optimization methods and tools use very limited amount of data and depend on default values in the signal timing optimization/simulation tools to estimate network performance under different signal optimization strategies. In recent years, new data collection technologies are emerging including high resolution controller data, more advanced detection technologies such as video image detection that are based on vehicle tracking and possible integration with microwave detectors, automatic-vehicle based identification technologies, third party crowdsourcing data, connected vehicles, and connected automated vehicles data. The objective of the proposed study is to propose methods and algorithms to combine data collected from existing and emerging sources with enhanced models and optimization algorithms to optimize and manage signal operations. The results from applying the developed methods and algorithms will be compared with traditional signal timing and optimization methods currently used by transportation agencies. </p>
Demonstaration of the use of Zenodo website to upload data and link it to the PersonalizeAF project
<p>This video demonstarates the use of Zenodo website to upload data and link it to the PersonalizeAF project</p>
Seamless Projections of Global Storm Surge and Ocean Waves under a Warming Climate
<p>This is dataset of global ocean waves and storm surges used in the paper "Seamless Projections of Global Storm Surge and Ocean Waves under a Warming Climate" by Shimura et al. (2022, Geophysical Research Letters).</p> <p>AnnualMaxSSH_SeamlessExperiment.nc contains the global annual maximum storm surge in the seamless experiment.</p> <p>AnnualMaxHs_SeamlessExperiment.nc contains the global annual maximum significant wave heights in the seamless experiment.</p> <p>AnnualMaxHs_TimesliceExperiment_Historical.nc contains the global annual maximum significant wave heights in the time-slice experiment (the historical climate simulations).</p> <p>AnnualMaxHs_TimesliceExperiment_ProjectedFuture.nc contains the global annual maximum significant wave heights in the time-slice experiment (the projected future climate simulations).</p>
Projected impacts of climate and land use changes on the habitat of Atlantic Forest plants in Brazil
<p>Aim:<b> </b>To provide novel evidence on the average impact of climate and land use changes on habitat suitability for tropical plants and to test previous conclusions on the relative importance of these two drivers in shaping future availability of habitat for tropical plant species.</p> <p>Location<b>: </b>Brazil's Atlantic Forest domain.</p> <p>Time period: Plant occurrences recorded between 1960 and 2014. Baseline climate from 1960-2000 and land use from 2015. Projected scenarios of climate for 2041-2060 and land use for 2050.</p> <p>Major taxa studied: Angiosperms.</p> <p>Results: Our results suggest that climate change alone will, surprisingly, have only a modest negative impact on the mean habitat suitability, decreasing it by 2% (median = -5% to -7%, variation associated with scenarios). Land use change alone had a more consistent negative impact on habitat suitability, causing mean and median reductions of 4% to 6%. When the effects of climate and land use are combined, the mean habitat suitability was reduced by 4% (median = -9% to -11%).</p> <p>Main conclusions: The combined impacts of climate and land use changes were substantial, although smaller than expected. Habitat suitability decreased for most species, but it increased substantially for some species, suggesting that the distribution of impacts across species is markedly right skewed. The impacts were typically detrimental to small-ranged species and neutral or beneficial to widespread species. Land use change rather than climate change will likely cause more losses to the habitat of Atlantic Forest plant species within the next several decades.</p>
Code and figure data from "Projections of northern hemisphere extratropical climate underestimate internal variability and hence uncertainty"
<p>Code and figure data from "Projections of northern hemisphere extratropical climate underestimate internal variability and hence uncertainty".</p>
Projected climate risk of aquatic food system benefits
<p>Aquatic foods from marine and freshwater systems are critical to the nutrition, health, livelihoods, economies and culture of billions of people worldwide – but climate-related hazards may compromise their ability to provide these benefits. This analysis estimates national-level aquatic food system climate risk using a fuzzy logic modeling approach that connects climate hazards impacting marine and freshwater capture fisheries and aquaculture to their contributions to sustainable food system outcomes, and vulnerability to losing those contributions. Estimates are presented for a high and a low emissions scenario in three different time windows (2030, 2050, 2090). </p>
Crowdsourcing historical text and data with the Chinese Text Project
<p>Paper presented on Friday 11 June 2021 at the Digital Medievalist Global Symposium <em>The past, present, and future of Digital Medieval Studies</em> for the Asia & Oceania Panel, in the session Engaging in Chinese Literature.</p> <p>The Chinese Text Project (<a href="https://ctext.org">https://ctext.org</a>) is a crowdsourced digital library of premodern Chinese writing, containing over 35 million pages of scanned primary source material and billions of words of transcribed text. In this talk I describe the implementation of a crowdsourced semantic annotation system for these texts, as well as the joint construction of a crowdsourced knowledge graph recording data covering close to 3000 years of Chinese history.</p>
data set regarding to project- Malnutrition, sarcopenia and malnutrition-sarcopenia syndrome in Older Adults with COPD
<p><strong>data set regarding to project- Malnutrition, sarcopenia and malnutrition-sarcopenia syndrome in Older Adults with COPD</strong></p>
Dataset for TC_07.05.01 of VSP product of CROSSBOW project
<p>Dataset for TC_07.05.01 of VSP product of CROSSBOW project</p>
Spine-project/spine-cs-b3: v1
<p>No description provided.</p>
Spine-project/spine-cs-a2: v1
<p>No description provided.</p>
Spine-project/spine-cs-c1: v1
<p>Case Study C1: Market design for integrated energy systems</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.