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18,621 results for “development;”
Investigating sediment supply impact on centennial saltmarsh biogeomorphic development with Demeter
<p>This repository contains a series of simulations to investigate the impact of (changing) sediment supply on the long-term biogeomorphic development (200 years) of saltmarshes (4 km<sup>2</sup>). The model used is Demeter (https://doi.org/10.5281/zenodo.7101535). </p> <p>Each simulation output file contains:</p> <ul> <li>yearly bottom elevation maps (resolution of 5 m);</li> <li>yearly vegetation coverage maps (resolution of 5 m);</li> <li>yearly hydroperiod maps (resolution of 5 m);</li> <li>yearly exceeding bottom shear impulse maps (resolution of 5 m);</li> <li>vegetation distribution maps every 5 years (resolution of 50 cm).</li> </ul> <p>Each simulation is also processed to compute channel network characteristics with TidalGeoPro (https://doi.org/10.5281/zenodo.7153257), such as:</p> <ul> <li>maximum upstream channel length along channel network skeleton every 20 years (resolution of 5 m);</li> <li>total upstream channel length within tidal watershed along channel network skeleton every 20 years (resolution of 5 m);</li> <li>tidal watershed surface area along channel network skeleton every 20 years (resolution of 5 m);</li> <li>mean unchanneled path length within tidal watershed along channel network skeleton every 20 years (resolution of 5 m);</li> <li>channel cross-section width, depth and area along channel network skeleton every 20 years (resolution of 5 m);</li> <li>yearly unchanneled path length maps (resolution of 5 m).</li> </ul> <p>If you are interested to use this dataset, or collaborate with the authors, please contact Olivier Gourgue (ogourgue@gmail.com).</p>
List of validated primers of gilthead sea bream (Sparus aurata) and European seabass (DIcentrarchus labrax) developed in PerformFISH project (D2.3)
<p>The document contains all the primers identified for the screening of genes tested for their potential as biomarkers to predict quality performance in gilthead sea bream and European sea bass larvae and juveniles in the context of PERFORMFISH (WP2). The spreadsheet has the following information: Pathway, phisiologic process in which the gene is involved; name of protein that gene produces; gene code; acession nº, code given in the consulted databases and the sequence extracted for primer design; FW and RV primer, forward and reverse primer sequence specific for target gene; melt temperature, optimized temperature that primers work at ; amplicon size, size in base pairs of the product produced with the primers; eff%, efficency of primers; r2; source, the origin of the primers, "in house" or "literature" (including available DOI. Each pair of primers are classified using a "traffic light" system indicating their validation status.</p>
Regional cytoarchitecture of the adult and developing mouse enteric nervous system
<p>The organization and cellular composition of tissues are key determinants of their biological function. In the mammalian gastrointestinal (GI) tract, the enteric nervous system (ENS) intercalates between muscular and epithelial layers of the gut wall and can control GI function independent of central nervous system (CNS) input. As in the CNS, distinct regions of the GI tract are highly specialized and support diverse functions, yet the regional and spatial organization of the ENS remains poorly characterized.<a href="https://www-sciencedirect-com.stanford.idm.oclc.org/science/article/pii/S0960982222013070?via%3Dihub#bib2"><sup>2</sup></a> Cellular arrangements, circuit connectivity patterns, and diverse cell types are known to underpin ENS functional complexity and GI function, but enteric neurons are most typically described only as a uniform meshwork of interconnected ganglia. Here, we present a bird’s eye view of the mouse ENS, describing its previously underappreciated cytoarchitecture and regional variation. We visually and computationally demonstrate that enteric neurons are organized in circumferential neuronal stripes. This organization emerges gradually during the perinatal period, with neuronal stripe formation in the small intestine (SI) preceding that in the colon. The width of neuronal stripes varies throughout the length of the GI tract, and distinct neuronal subtypes differentially populate specific regions of the GI tract, with stark contrasts between SI and colon as well as within subregions of each. This characterization provides a blueprint for future understanding of region-specific GI function and identifying ENS structural correlates of diverse GI disorders.</p>
Sustainable Development Goals (SDG) in citizen science - Dataset
<p>The assignment results of SDGs to CS project descriptions are provided in the following dataset. The analysis was conducted based on data retrieved from the CSTRack database on 2022/09/15. </p> <p>See further detail about the study in D2.2 section 7.3.</p> <p><strong>Content and grouping: </strong></p> <ul> <li> <p>The dataset contains the following details: Platform ID (from which platform the CS project descriptions were retrieved), Project Title (Name of the CS project), SDG assignment results (More details about the assignment technique can be found in D3.2 ‘Web Analytics Toolset and Workbench’ - ESA backend), SDG assignment reported in section 7.2 of D2.2 (which only considered the SDG assignment with the highest similarity).</p> </li> </ul>
Development of a spectral library for the discovery of altered genomic events in Mycobacterium avium associated with virulence using mass spectrometry-based proteogenomic analysis
<p><em>Mycobacterium avium</em> is one of the prominent disease-causing bacteria in humans. It causes lymphadenitis, chronic and extrapulmonary, and disseminated infections in adults, children, and immunocompromised patients. <em>M. avium</em> has ~4,500 predicted protein-coding regions on an average, which can be helpful in discovering several variants at the proteome level. Many of them are potentially associated with virulence, thus identifying such proteins can be a helpful feature in the development of panel-based theranostics. In line with such a long-term goal, we carried out an in-depth proteomic analysis of <em>M. avium</em> with both data-dependent and data-independent acquisition methods. Further, a set of proteogenomic investigations were carried out using the protein database for <em>Mycobacterium tuberculosis,</em> and a genome six-frame translated database and a variant protein database of <em>M. avium</em>. A search of mass spectrometry data analysis against <em>M. avium</em> protein database resulted in the identification of 2,954 proteins. Further, proteogenomic analyses aided in the identification of 1,301 novel peptide sequences and correction of translation start sites for 15 proteins. At the end, we created a spectral library of <em>M. avium</em> proteins including novel genome search-specific peptides and variant peptides detected in this study. We validated the spectral library by a data-independent acquisition of the <em>M. avium</em> proteome. Thus, we present a <em>M. avium </em>spectral library of 29,033 peptide precursors supported by 0.4 million fragment ions for further use by the biomedical community.</p>
Data for Project 'Feasibility, Usability and Acceptance of a Newly Developed Exergame-Based Training Concept for Older Adults with Mild Neurocognitive Disorder - A Pilot Randomized Controlled Trial'
<p>Data for Project 'Feasibility, Usability and Acceptance of a Newly Developed Exergame-Based Training Concept for Older Adults with Mild Neurocognitive Disorder - A Pilot Randomized Controlled Trial' (trial registered at clinicaltrials.gov (<a href="https://clinicaltrials.gov/ct2/show/NCT04996654">NCT04996654</a>; date of registration: 11 July 2021), consisting of:</p> <p>(1) the original and complete data set for all primary outcomes ('Data_Primary-Outcomes_Brain-IT-Pilot-Feasibility-RCT_for-publication.xlsx');</p> <p>(2) the original and complete data set for all secondary outcomes ('Data_Secondary-Outcomes_Brain-IT-Pilot-Feasibility-RCT_for-publication.xlsx');</p> <p>(3) the original and complete data set for all other outcomes (i.e. baseline factors (demographic data, type of usual care interventions) and training heart rate; 'Data_Other-Outcomes_Brain-IT-Pilot-Feasibility-RCT_for-publication.xlsx');</p> <p>(4) folder including the raw and processed heart rate variability (HRV) and electroencephalography (EEG) data for all participants and measurements (HRV-and-EEG_raw-and-processed-data.zip);</p> <p>(5) a corresponding README file including (a) general information, (b) data and file overview, (c) sharing and access information, (d) methodological information, and (e) data-specific information.</p>
Socio-economic development of global river deltas from gridded data
<p>Crop, population, and GDP values in the world's major river deltas, derived from publicly available gridded datasets. </p> <p>v0: Dec. 2022</p> <p>v1: Jan 2023 (added Metadata)</p>
Data associated with "Developing a standardized but extendable framework to increase the findability of infectious disease datasets"
<p><strong>Data associated with "Developing a standardized but extendable framework to increase the findability of infectious disease datasets"</strong></p> <p> </p> <p>Includes:</p> <ul> <li>NIAID Dataset schema</li> <li>NIAID ComputationalTool schema</li> <li>Crosswalk between NIAID schemas and common schemas</li> <li>Survey of Schema.org-compliant repositories</li> </ul> <p><br> The open access movement and scientific reproducibility concerns have led the biomedical research community to embrace efforts to make scientific datasets openly accessible. While many datasets are now available, there are still challenges in ensuring that they are Findable, Accessible, Interoperable, and Reusable (FAIR). To improve the FAIRness of datasets, we evaluated dataset repositories for compliance with Schema.org standards – a collection of standards developed to increase metadata searchability across the internet. Adoption of the Schema.org Dataset standard was highly variable in biomedical research datasets, and the standard omitted many desirable metadata fields. We customized the Schema.org Dataset standard to catalog datasets collected across a Systems Biology research consortium consisting of 15 Centers. We developed a reusable process for creating a schema which is interoperable with other standards, but still extendable and customizable to a particular context. Here, we describe our process along with the associated gains in FAIRness, and discuss ongoing challenges with dataset discoverability – the first step to ensure that the vast amount of open data published by the research community is reused to its maximum value.</p>
Pellet-based fused deposition modeling for the development of soft compliant robotic grippers with integrated
<p>Fused deposition modeling (FDM) has some advantages compared to other additive manufacturing techniques, such as the in situ integration of functional components, like sensors, and recyclability of parts. However, conventional filament-based FDM techniques are limited to thermoplastic elastomers with a Shore hardness above 70 A, thus it has marginal compatibility with soft robotic structures. Due to recently emerging pellet-based FDM printer technology, the fabrication of soft grippers with low Shore hardness has become possible. In this study, styrene based thermoplastic elastomers (TPS) were used to print elastic strips and soft gripper structures down to a Shore hardness of 25 A with an integrated strain sensing element (piezoresistive sensor). Printing on a soft rather than rigid substrate affects the integration of the printed thread on the substrate, because of the softness and relaxation, during the printing softness. It was seen that integrating the sensing element on a substrate with higher Shore hardness decreased the elongation at the point of fracture and the sensitivity of the sensing element. A soft compliant gripper structure with an integrated sensing layer was printed with the TPS-based elastomers successfully, and even due to the complex deformation of the compliant gripper structure, several positions could be detected successfully. Opened and closed position of the gripper, as well as, size recognition of spools of different sizes could be monitored by the piezoresistive printed sensor layer. The most sensitive sensing performance was obtained with the TPS of the lower Shore hardness (25 A), as the value of relative change in resistance was 1, followed by the gripper of Shore hardness 65 A and a relative change in resistance of 0.51. With this study, we demonstrated that pellet-based FDM printers can be used, to print potential soft robotic structures with in-situ integrated sensor structures.</p>
A StackExchange Dataset of Developer Questions Related to Checked-in Secrets in Software Artifacts
<p>Throughout 2021, GitGuardian's monitoring of public GitHub repositories revealed a two-fold increase in the number of secrets (database credentials, API keys, and other credentials) exposed compared to 2020, accumulating more than six million secrets. To our knowledge, the challenges developers face to avoid checked-in secrets are not yet characterized. In our artifact, we provide a dataset containing 779 questions mined from three StackExchange sites asked by developers related to checked-in secrets from three StackExchange sites. In addition, we provide 434 accepted answers provided by the other users of StackExchange to mitigate the challenge of checked-in secrets.</p> <p> </p> <table> <caption>An overview of StackExchange artifact</caption> <thead> <tr> <th scope="col">Field Name</th> <th scope="col">Description</th> </tr> </thead> <tbody> <tr> <td>Id</td> <td>An unique identifier of the question.</td> </tr> <tr> <td>Title</td> <td>The title of the question.</td> </tr> <tr> <td>Body</td> <td>The description of the question.</td> </tr> <tr> <td>Tags</td> <td>The tags related to the question such as "security", "git" and "key-management".</td> </tr> <tr> <td>CreationDate</td> <td>The date when the question is posted.</td> </tr> <tr> <td>Score</td> <td>The count of upvotes in the question.</td> </tr> <tr> <td>ViewCount</td> <td>The number of users who viewed the question.</td> </tr> <tr> <td>AnswerCount</td> <td>The total number of answers posted in the question.</td> </tr> <tr> <td>CommentCount</td> <td>The total number of comments posted in the question.</td> </tr> <tr> <td>FavouriteCount</td> <td>The total number of users who marked the question as favourite.</td> </tr> <tr> <td>ClosedDate</td> <td>The date when the community marked the question as closed. </td> </tr> <tr> <td>URL</td> <td>The url of the question.</td> </tr> <tr> <td>AcceptedAnswerId</td> <td>The unique identifier of the accepted answer for the question.</td> </tr> <tr> <td>Answer</td> <td>The accepted answer of the question.</td> </tr> </tbody> </table>
Datasets of the work named Development of a Low-Cost Smart Sensor GNSS System for Real-Time Positioning and Orientation for Floating Offshore Wind Platform
<pre>- 1_Motion_Simulator/ - IMU_results/ - 20211028101756.csv - 20220114101543.csv - 20220117000000.csv - Rotary_Table/ - 15/ - rover_20220105.nav - rover_20220105.obs - solution_20220105_CAS.log - 360/ - rover_20211221.nav - rover_20211221.obs - solution_20211221_CAS.log - 360-15/ - rover_20220202_CAS.nav - rover_20220202_CAS.obs - solution_20220202_CAS.log - Static_Tests/ - solution_SSRA00CAS0 - solution_SSRA00WHU0 - 2_GNSS_Signal_Simulator/ - platformmov_C1.xtd - platformmov_C2.xtd - platformmov_C3.xtd - TestBetaNoneMov_C1 - TestBetaNoneMov_C1.nav - TestBetaNoneMov_C1.obs - TestBetaNoneMov_C1.ubx - TestBetaNoneMov_C2 - TestBetaNoneMov_C2.nav - TestBetaNoneMov_C2.obs - TestBetaNoneMov_C2.ubx - TestBetaNoneMov_C3 - TestBetaNoneMov_C3.nav - TestBetaNoneMov_C3.obs - TestBetaNoneMov_C3.ubx - 3_Test_Sea/ - 20220503000000.xlsx - solution_28.nav - solution_28.obs - solution_28.ubx Background: {Journal Article using this dataset} 'Development of a Low-Cost Smart Sensor GNSS System for Real-Time Positioning and Orientation for Floating Offshore Wind Platform' Paper DOI: <a href="https://doi.org/10.3390/s23020925">https://doi.org/10.3390/s23020925</a> Abstract: a low-cost smart sensor GNSS system has been developed to provide accurate real-time position and orientation measurements on a floating offshore wind platform. The approach chosen to offer a viable and reliable solution for this application is based on the use of the well-known advantages of the GNSS system as the main driver for enhancing the accuracy of positioning. For this purpose, the data reported in this work are captured through a GNSS receiver operating over multiple frequency bands (L1, L2, L5) and combining signals from different constellations of navigation satellites (GPS, Galileo, and GLONASS), and they are processed through the precise point positioning (PPP) and real-time kinematic (RTK) techniques. Furthermore, aiming to improve global positioning, the processing unit fuses the results obtained with the data acquired through an inertial measurement unit (IMU), reaching final accuracy of a few centimeters. To validate the system designed and developed in this proposal, three different sets of tests were carried out in a (i) rotary table at the laboratory, (ii) GNSS simulator, and (iii) real conditions in an oceanic buoy at sea. The real-time positioning solution was compared to solutions obtained by post-processing techniques in these three scenarios and similar results were satisfactorily achieved. </pre>
Development of a machine learning model for river bedload - Data, Model, and Scripts
<p>This repository for “Development of a machine learning model for river bedload” Hosseiny et. Al (in review at Earth Surface Dynamics) contains the following assets. These assets may need to be modified for your purposes. You are responsible for inspecting these assets and making adjustments as necessary.</p> <p>Assets:</p> <p>1) The trained ANN model described in Hosseiny et al. (in review) as a .zip file named ‘Hosseiny_et_al_trained_ANN.zip’. This contains a folder (BEDLOAD_MODEL_FINAL) which contains the trained ANN Model (saved_model.pb) and associated information related to the input variables and variable weights.</p> <p>2) An accompanying Jupyter notebook named “bedload_ann_example.ipynb” that provides a step-by-step guide for implemented the trained ANN model (Asset 1).</p> <p>3) A .xls file named “Hosseiny et al_Supplemental_Data_Tables.xlsx” which provides the original observations that the model was trained and tested on, the summary statistics of the original input data as a compilation and for individual sites, the model errors associated with training and validation steps, the bedload calculations from the four uncalibrated existing bedload transport models described in the original study and for the ANN for the test data population, associated summary statistics with model output, and additional site-specific calculations of model error.</p>
Dataset for the calibration of the photosynthetic unit (PSU)-model developed at KIT
<p>The presented dataset was used to develop and calibrate (estimate the model parameters) a photosynthetic unit (PSU)-model. The PSU-model and the data were generated at the Institute of Process Engineering in Life Sciences – Bioprocess Engineering of the KIT under the supervision of Prof. Dr.-Ing. Clemens Posten. Please use this data to familiarize yourself with the PSU-model and as an example dataset. If you want to use your own data in this context, organize it like the sample data listed here. As an alternative, you should adapt the model scripts to your data accordingly.</p> <p>Date of data collection: The data were generated as a part of the author’s PhD program between 2018-2022 at Karlsruhe Institute of Technology (KIT).</p>
Geospatial Analysis of Economic Development in kenya by Province
<p>This dataset presents both vector and raster data combinations for pm2.5, elevation, nightlight data, population density, area, and population that can be used to estimate the economic development of Kenya using distribution of banks as a proxy.</p>
Chicken intestinal development is affected by different dietary interventions
<p>These RDS files contain <strong>DESeqDataSet </strong>objects subset into broiler groups of 4, 12 and 33 days post-hatch.<br> These objects are the result of DESeq2::DESeq( … ,betaPrior=FALSE).The .txt-objects contain the normalized sequencing counts per broiler age group. These objects are the result of DESeq2::counts( … , normalized=TRUE). Data was generated using STAR v2.7.9a and DESeq2 v1.34. Metadata is included as Excel file.</p> <p>Sequencing data is deposited at NCBI-SRA under BioProject: PRJNA949454. </p> <p> </p> <p><strong>Study abstract</strong></p> <p>Dirkjan Schokker, Soumya K. Kar, Paul Stege, Norbert Stockhofe, Alex Bossers, Vera Perricone, Annemarie Rebel, Ingrid de Jong</p> <p>Gut health is a prerequisite for broiler welfare. In this study, we investigated the effect of three dietary interventions on small intestinal development in broilers and special emphasis on immunity. Morphometry and immunostaining showed no significant differences in any of the treatments, however, gene expression revealed significant differences in the LPHF and MCFA treatments. Pathway enrichment analysis showed a few main pathways involved in regulation of cellular processes, cell structural processes, and cell protection, as well as a putative link to inflammatory processes. Taken together, these findings suggest that dietary interventions can modulate gut health and functionality in chicken.</p>
Dataset for the article "Development of an integrated socio-hydrological modeling framework for assessing the impacts of shelter location arrangement and human behaviors on flood evacuation processes"
<p>This dataset include the data needed to create the socio-hydrological model to simulate human evacuation processes via a transportation network before a flood hits the residential area. Source code, in JAVA, for generating households in the agent-based model are also provided. </p>
ViF-GTAD: A new Automotive Data Set with Ground Truth for ADAS/AD Development, Testing and Validation
<p>A new dataset for automated driving, which is the subject matter of this paper, identifies and addresses a gap in existing similar perception data sets. While the most state-of-the-art perception data sets primarily focus on provision of various on-board sensor measurements along with the semantic information under various driving conditions, the provided information is often insufficient since the object list and position data provided include unknown and time-varying errors. The current paper and the associated data-set describes the first publicly available perception measurement data that include not only the on-board sensor information from camera, Lidar and radar with semantically classified objects, but also the high precision ground-truth position measurements enabled by the accurate RTK assisted GPS localization systems available on both the ego vehicle and the dynamic target objects. This paper provides insight on the capturing of the data, explicitly explaining the meta data structure and the content, as well as the potential application examples where it has been, and can potentially be, applied and implemented in relation to automated driving and environmental perception systems development, testing and validation.</p>
Data for 'Nature's contributions to people and the Sustainable Development Goals in Nepal'
<p>Title: Data for 'Nature's contributions to people and the Sustainable Development Goals in Nepal'</p> <p>Recommended Citation: Adhikari, B., Prescott, G., Urbach, D., Chettri, N., & Fischer, M. (2022). Nature’s contributions to people and the sustainable development goals in Nepal. Environmental Research Letters. https://doi.org/10.1088/1748-9326/ac8e1e</p> <p>Principal Investigator: Markus Fischer (markus.fischer@ips.unibe.ch)</p> <p>Authors:<br> Biraj Adhikari (biraj.adhikari@ips.unibe.ch, ORCID: 0000-0002-4260-8706)<br> Graham W Prescott (graham.prescott.research@gmail.com, ORCID:0000-0001-5123-514X)<br> Davnah Urbach (davnah.payne@ips.unibe.ch, ORCID: 0000-0001-9170-7834)<br> Nakul Chettri (nakul.chettri@icimod.org, ORCID: 0000-0002-3338-8879)<br> Markus Fischer (markus.fischer@ips.unibe.ch, ORCID: 0000-0002-5589-5900)</p> <p>Date of data collection: November 2020 - August 2021<br> Location of data collection: Kathmandu, Nepal<br> Article title: 'Nature's contributions to people and the Sustainable Development Goals in Nepal'</p> <p>R code available at: https://github.com/biraj-ad/r4dLiteratureReview_GithubRep</p> <p>Data Overview:</p> <p>1. 'Literature_References.csv'<br> List of 119 peer-reviewed journals and 21 grey literature documents used in the review. Each is assigned a unique identifier ("SN Ref") to link it to the other files.</p> <p><br> 2. 'Drivers_and_Trends.csv'<br> The "Quote" column is the text from papers which has information on (i) trends in ecosystems or NCPs, and if available (ii) direct and/or indirect drivers causing the trends.<br> The "Nature" column indicates which ecosystem (Forest, Farmland, Freshwater, Grassland, Others, and Directly to NCP), the "NCP" column indicates which NCP (categorized into 18 categories based on the IPBES classification) the text refers to. The "NCP Category" column indicates whether the said NCP is a regulating, material or non-material NCP. <br> We also categorized direct and indirect drivers based on the IPBES classification (Direct Drivers: Land-use Change, Climate Change, Direct Exploitation, Invasive Alien Species, and Pollution; Indirect Drivers: Institutions and Governance, Demographic and Sociocultural, Economic and Technological). <br> If there were more than one drivers of change for a particular NCP, we have included them in additional columns. In order to avoid multiple counts for trends of a particular NCP, we introduced the "TrendCount" column. For example, columns 3, 4 and 5 refers to the same trend of decreasing WQN, but has 3 Direct Drivers. Therefore, each TrendCount is given a weight of 0.33 so that the total trend adds upto 1.</p> <p>3. 'NCP_to_SDG.csv'<br> The "Quote" Column is the text from papers which has information on which NCP is contributing towards which SDG. "Remarks from text" are the authors' own remarks based on the text and the overall context of the article.<br> The contribution of NCPs are classified as positive or negative, and indicated in the column "Effect (pos/neg)"<br> The "NCP" column indicates which NCP (categorized into 18 categories according to IPBES) the text refers to, while the "Contribution to SDG" column indicates which SDG the NCP is contributing towards.<br> The "Ecosystem" column indicates which ecosystem (Forest, Farmland, Freshwater, Grassland, Others) the NCP is being supplied from.</p> <p>Codes for NCPS:<br> HAB (Habitat Creation and Maintenance), POL (Pollination and dispersal of seeds and other propagules), AIR (Regulation of Air Quality), CLI (Regulation of Climate), WQN (Regulation of Freshwater Quantity, Location, and Timing), WQL (Regulation of Freshwater and Coastal Water Quality), SOI (Formation, Protection, and Decontamination of Soils and Sediments), HAZ (Regulation of Hazards and Extreme Events), ORG (Regulation of Organisms Detrimental to Humans), NRG (Energy), FOD (Food and Feed), MAT (Materials and Assistance), MED (Medicinal, Biochemical, and Genetic Resources), INS (Learning and Inspiration), EXP (Physical and Psychological Experiences), IDE (Supporting Identities), and OPT (Maintenance of Options).</p> <p>4. 'Data_consolidated.xlsx'<br> The above three data files combined into one xlsx document<br> </p> <p> </p> <p> </p>
Occurrence records used to develop a climatic suitability model for emerald ash borer in DDRP
<p>Presence records used to calibrate and validate a climatic suitability model for emerald ash borer in the DDRP platform (Degree-Days, Risk, and Phenological event mapping) (Barker et al. 2023). The first sheet ("Records") of the Excel file provides the range (native or invaded), continent, country, state or province, locality, latitude, and longitude of origin for each record. The "Coords_est" column indicates whether the coordinates were estimated from city- or county-level information (1 = yes, 0 = no). The year in which the record was collected is provided if known. The second sheet of the Excel file ("References") provides a list of references for each record source.</p>
Model output from CAABA/MECCA study "Development of a multiphase chemical mechanism to improve secondary organic aerosol formation in CAABA/MECCA (version 4.7.0)"
<p>This dataset includes the main data obtained during the study "Development of a multiphase chemical mechanism to improve secondary organic aerosol formation in CAABA/MECCA (version 4.7.0)" (DOI:10.5194/gmd-2023-102). The updated model code can be found at zenodo.org (DOI:10.5281/zenodo.7944174). The data can be used to replicate the results shown in the manuscript. Contained are results produced by the updated CAABA/MECCA (version 4.7.0) and reference data from CAABA/MECCA version 4.5.5. In version 4.7.0, new biogenic and anthropogenic species are introduced to the model (limonene and long-chained alkanes) with refined multiphase chemistry, while new reaction pathways are added for existing compounds (isoprene, benzene and IEPOX). The output is generated to evaluate model results in terms of temperature- and NOx-dependency.</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.