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4,486 results for “emergency”
S71 | CECSCREEN | HBM4EU CECscreen: Screening List for Chemicals of Emerging Concern Plus Metadata and Predicted Phase 1 Metabolites
<p>This is the collection associated with list S71 CECSCREEN HBM4EU CECscreen: Screening List for Chemicals of Emerging Concern Plus Metadata and Predicted Phase 1 Metabolites<strong> </strong>on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>CECScreen is part of the HBM4EU project (coord. UBA) > WP16 "emerging chemicals" (lead INRA, JP Antignac/L Debrauwer) > Task 16.1 (lead IRAS, J Vlanderen / R Vermeulen) > Main contributor (J Meijer) > Involved Partners (M Lamoree, T Hamers, S Hutinet, A, Covaci, C Huber, M Krauss, DI Walker, EL Schymanski). Further details in Meijer et al (2021) DOI: <a href="https://doi.org/10.1016/j.envint.2021.106511">10.1016/j.envint.2021.106511</a>. Dataset DOI: <a href="https://doi.org/10.5281/zenodo.3956586">10.5281/zenodo.3956586</a>.</p> <p>Update 23/7/2020 (v0.1.1): updated MetFrag files to remove elements causing errors (Os, Pd, Ag, Be). Update 8 Nov 2022 (v0.1.2) removed new lines in several synonyms as detected at BioHackEU22.</p>
Labels for Emergency Response Imagery from Hurricane Barry, Delta, Dorian, Florence, Ida, Isaias, Laura, Michael, Sally, Zeta, and Tropical Storm Gordon
<p>The csv files contain human-generated labels for Emergency Response Imagery collected by US National Oceanic and Atmospheric Administration (NOAA) after Hurricane Barry, Delta, Dorian, Florence, Ida, Isaias, Laura, Michael, Sally, Zeta, and Tropical Storm Gordon. All authors contributed to labeling the imagery. All labeling was done with an open-source labeling tool (Rafique et al., 2020).</p> <p>All csv files provide the userID (the ID of the anonymous labeler), the NOAA flight, the NOAA image, and 6 labels — allWater (if the image was all water), devType (if the image had buildings/development), washoverType (if the image had washover deposits), dmgType (if the image showed damage to built environment), impactType (if the labeler could identify the coastal impact, using the Storm Impact Scale from Sallenger, 2000), and terrainType (the type of physical environment).</p> <p>Images labeled here correspond to multiple NOAA flights — all listed in the csv file for each jpeg image. These jpeg images can be downloaded directly from NOAA (https://storms.ngs.noaa.gov/) or using Moretz et al. (2020a, 2020b).</p> <p>There are three csv files:</p> <p>ReleaseData_10172022.csv has 10,237 labels for 4250 images. These labels were generated by coastal scientists. The csv also contains the Latitude and Longitude of the image center (from NOAA).</p> <p>ReleaseDataQuads.csv has 400 labels for 100 images. These labels were generated by coastal scientists. The images labeled in this set correspond to original NOAA images that have been split into quadrants. Splitting images was done with ImageMagick. The command used to split the images was:</p> <p>`magick mogrify -crop 2x2@ +repage -path ../quadrants *.jpg`</p> <p>The naming convention corresponds to the image quarter — the *-0.jpg is upper left, *-1.jpg is upper right, *-2.jpg is lower left, and *-3.jpg is the lower right.</p> <p>ReleaseDataNCE.csv has 400 labels for 100 images. These images were labeled by non-coastal scientists. Note that the 100 images were also labeled by coastal scientists — those labels can be found in ReleaseData_v3.csv.</p> <p>There is another companion dataset to this, with slightly different labels (Goldstein et al., 2020).</p> <p>A zip file of images is also provided for demonstration purposes (images.zip). These are resized copies made with imagemagick, with the longest dimension set at 2000 pixels ( `mogrify -resize 2000x2000`). For full size images, please download the jpegs directly from NOAA.</p>
City of Seattle, Seattle Public Utilities, Bull Trout Fry Emergence Trapping 2023-current, Cedar River Municipal Watershed, King County, WA
Chester Morse Lake is managed for drinking water supply for the City of Seattle by Seattle Public Utilities (SPU). The reservoir was created in 1915 upon the completion of Masonry Dam, which raised the natural level of Cedar Lake from 1,538 feet to normal operational levels between 1,550 and 1,554 feet, with a maximum refill level of 1,565 feet. Construction of the dam removed several miles of potential stream spawning, incubation, and rearing habitat for an adfluvial population of bull trout, a species listed as threatened under the U.S. Endangered Species Act. The reservoir fluctuates widely across operational elevations during fall and winter storms. During reservoir refill in springtime, however, the reservoir will be continuously filled until reaching peak elevation (1,560 -1,565 feet) terminally inundating habitat where bull trout had previously spawned and embryos and alevins continue to develop in the streambed. Embryo incubation and fry emergence timing data are required to improve SPU's understanding of frequency and magnitude of operational impacts to bull trout embryos developing in stream habitats affected by reservoir inundation. This information enables empirically-based estimates for the number of embryos in the streambed vulnerable to impacts of inundation during fall and winter storms, which is an intermittent impact period for embryos; and reservoir refill, which is a terminal impact period for embryos. Between two and six hand-driven redd egg pocket water quality monitoring wells and quarantine fences (to avoid additional spawning and superimposition) were deployed near primary egg pockets the week of redd observation. Temperature and dissolved oxygen data were recorded in wells and weekly logger downloads informed biologists of incubation conditions (temperature and oxygen) and accumulated temperature units (ATU). Upon reaching approximately 500 ATU, fry emergence traps were deployed over quarantined redds and subsequently, cod ends were sampled
Harmful algal bloom and aquatic weeds data from the Sacramento-San Joaquin Delta, collected to evaluate the impact of the 2021 Temporary Urgency Change Order and Emergency Drought Barrier
Condition 8 of the June 2021 Temporary Urgency Change Order for the Central Valley Project (CVP) and State Water Project (SWP) requires a special study of harmful algal blooms (HABs) in the Sacramento–San Joaquin Delta (Delta) and the spread of submersed aquatic vegetation (SAV), and floating aquatic vegetation (FAV), also referred to as “aquatic weeds”. A report on the study was submitted to the State Water Resources Control Board on June 1, 2022. This data package contains all publicly available data used in the report, including visual cyanobacteria reports, cyanotoxin data, water quality, nutrients, flow/hydrodynamics, chlorophyll-a concentrations, temperature, coverage of SAV and FAV, use of herbicides, and human populations. Many of these data were derived from other datasets, though some were collected specifically for this study
Developmental change in prefrontal cortex recruitment supports the emergence of value-guided memory
Open the record for dataset details and reuse information.
Salvaging the Internet Hate Machine: Using the discourse of extremist online subcultures to identify emergent extreme speech
<p>This dataset accompanies a paper submitted to the WebSci 20 conference. In this paper, we present a lexicon of 'extreme speech' that may be used to detect hate speech and extreme speech on online platforms. We outline a cross-disciplinary research protocol through which this lexicon is initially extracted from a corpus of 3,335,265 posts from 4chan's /pol/ sub-forum using a hybrid method comprising word2vec modeling and subsequent snowballing of nearest neighbours of a small initial expert seed list of extreme language. The choice of corpus is significant, as 4chan is a space of rapid language innovation and obscure extreme vernacular, complicating generalised approaches. Our lexicon detects significantly more extreme posts within a corpus from a more mainstream platform (Reddit) than another popular lexicon, Hatebase, with similar accuracy. Our lexicon and the method of its creation thus provide a contribution to the study of the toxicity of online subcultures similar to 4chan, as well as more mainstream platforms. As we demonstrate, the lexicon allows for more effective detecting of extreme speech in these spaces. This method and the lexicon have further been made available through an open-source web tool for the study of online social platforms, 4CAT. The computational methods and lexicon on offer here can thus be used by a wide academic audience, fostering interdisciplinary approaches to the study of online hate and extreme speech. </p> <p>The dataset comprises the following items:</p> <ul> <li>The 4chan corpus from which the extreme speech lexicon was generated (posts from /pol/, 1 October 2019 - 1 November 2019)</li> <li>The Reddit corpus used to verify and test the lexicon (posts from the_donald, theredpill, politics and chapotraphouse, 1 October 2019 - 1 November 2019)</li> <li>The word2vec model from which the extreme speech lexicon was generated</li> <li>The extreme speech lexicon that was generated</li> </ul>
Data from: A FAIR and modular image-based workflow for knowledge discovery in the emerging field of imageomics
<p>Data and results from the Imageomics Workflow. These include data files from the Fish-AIR repository (https://fishair.org/) for purposes of reproducibility and outputs from the application-specific imageomics workflow contained in the Minnow_Segmented_Traits repository (https://github.com/hdr-bgnn/Minnow_Segmented_Traits).</p> <p>Fish-AIR:<br> This is the dataset downloaded from Fish-AIR, filtering for Cyprinidae and the Great Lakes Invasive Network (GLIN) from the Illinois Natural History Survey (INHS) dataset. These files contain information about fish images, fish image quality, and path for downloading the images. The data download ARK ID is dtspz368c00q. (2023-04-05). The following files are unaltered from the Fish-AIR download. We use the following files:</p> <p>extendedImageMetadata.csv: A CSV file containing information about each image file. It has the following columns: ARKID, fileNameAsDelivered, format, createDate, metadataDate, size, width, height, license, publisher, ownerInstitutionCode. Column definitions are defined https://fishair.org/vocabulary.html and the persistent column identifiers are in the meta.xml file.</p> <p>imageQualityMetadata.csv: A CSV file containing information about the quality of each image. It has the following columns: ARKID, license, publisher, ownerInstitutionCode, createDate, metadataDate, specimenQuantity, containsScaleBar, containsLabel, accessionNumberValidity, containsBarcode, containsColorBar, nonSpecimenObjects, partsOverlapping, specimenAngle, specimenView, specimenCurved, partsMissing, allPartsVisible, partsFolded, brightness, <br> uniformBackground, onFocus, colorIssue, quality, resourceCreationTechnique. Column definitions are defined https://fishair.org/vocabulary.html and the persistent column identifiers are in the meta.xml file.</p> <p>multimedia.csv: A CSV file containing information about image downloads. It has the following columns: ARKID, parentARKID, accessURI, createDate, modifyDate, fileNameAsDelivered, format, scientificName, genus, family, batchARKID, batchName, license, source, ownerInstitutionCode. Column definitions are defined https://fishair.org/vocabulary.html and the persistent column identifiers are in the meta.xml file.</p> <p>meta.xml: A XML file with the metadata about the column indices and URIs for each file contained in the original downloaded zip file. This file is used in the fish-air.R script to extract the indices for column headers.</p> <p>The outputs from the Minnow_Segmented_Traits workflow are:</p> <p>sampling.df.seg.csv: Table with tallies of the sampling of image data per species during the data cleaning and data analysis. This is used in Table S1 in Balk et al. </p> <p>presence.absence.matrix.csv: The Presence-Absence matrix from segmentation, not cleaned. This is the result of the combined outputs from the presence.json files created by the rule “create_morphological_analysis”. The cleaned version of this matrix is shown as Table S3 in Balk et al.</p> <p>heatmap.avg.blob.png and heatmap.sd.blob.png: Heatmaps of average area of biggest blob per trait (heatmap.avg.blob.png) and standard deviation of area of biggest blob per trait (heatmap.sd.blob.png). These images are also in Figure S3 of Balk et al.</p> <p>minnow.filtered.from.iqm.csv: Filtered fish image data set after filtering (see methods in Balk et al. for filter categories).</p> <p>burress.minnow.sp.filtered.from.iqm.csv: Fish image data set after filtering and selecting species from Burress et al. 2017.</p>
Synthetic Dataset of Emergency Healthcare Services
<p>Synthetic dataset of emergency services comprised of several CSV files that we have generated using a simulation software. This dataset is open for public use; please cite our work if used in research or applications.</p> <p>## File Overview</p> <ol> <li>**CheckBloodPressure.csv** - (9 KB): Contains blood pressure Server records of patients.</li> <li>**CheckPatientType.csv** - (19 KB): Identifies the type of each patient (e.g., 1 or 3).</li> <li>**Fill_Information.csv** - (2 KB): Fill information records for new patients.</li> <li>**MedicalRecord1.csv** - (10 KB): Medical record dataset for patient type 1.</li> <li>**MedicalRecord2.csv** - (4 KB): Medical record dataset for patient type 2.</li> <li>**MedicalRecord3.csv** - (2 KB): Medical record dataset for patient type 3.</li> <li>**MedicalRecord4.csv** - (13 KB): Medical record dataset for patient type 4.</li> <li>**OutPatientDepartment.csv** - (18 KB): Data related to the satisfaction and length of stay of an given patient.</li> <li>**Triage.csv** - (13 KB): Data related to the triage process.</li> <li>**README.txt** - (4 KB): Documentation of the dataset, including structure, metadata, and usage.</li> </ol> <p> </p> <p>## Common Fields Across Files</p> <ol> <li>**Patient ID** *(Integer)*: Unique identifier for each patient.</li> <li>**Patient Type** *(Integer)*: Classification of patient (e.g., 1, 4).</li> <li>**Medical Records Arrival Time** *(DateTime)*: Timestamp of the patient's first arrival in the medical record department.</li> <li>**Exiting Time** *(DateTime)*: Timestamp when the patient exits a Server.</li> <li>**Waiting Time (min)** *(Real)*: Total waiting time before being attended to.</li> <li>**Resource Used** *(String)*: Resource (e.g., Operator) allocated to the patient.</li> <li>**Utilization %** *(Real)*: Utilization rate of the resource as a percentage.</li> <li>**Queue Count Before Processing** *(Integer)*: Number of patients in the queue before processing begins.</li> <li>**Queue Count After Processing** *(Integer)*: Number of patients in the queue after processing ends.</li> <li>**Queue Difference** *(Integer)*: Difference between the before and after queue counts.</li> <li>**Length of Stay (min)** *(Real)*: Total time spent in the simulation by the patient.</li> <li>**LOS without Queues (min)** *(Real)*: Length of stay excluding any queuing time.</li> <li>**Satisfaction %** *(Real)*: Patient satisfaction rating based on their experience.</li> <li>**New Patient?** *(String)*: Indicates if this is a new patient or a returning one.</li> </ol> <p>Ferreira, M. (2024). Synthetic Dataset of Emergency Healthcare Services [Data set]. Zenodo. https://doi.org/10.5281/zenodo.14212812</p> <p> </p>
Volunteer kinematics from emergency lateral maneuvers, taken from van Rooij et al, 2013
<p>This data was extracted by the author as part of the OSCCAR project from the publication: </p> <p>Van Rooij, L., Elrofai, H., Philippens, M. M. G. M., & Daanen, H. A. M. (2013). Volunteer kinematics and reaction in lateral emergency maneuver tests. Stapp car crash journal, 57, 313 </p> <p>It is being made available to aid in the validation of Human Body Models.</p> <p>If you use this data, please cote the original paper.</p> <p>A model is available on request from the author of this upload, at Siemens Industry Software Netherlands BV. Modelling information regarding the experimental setup is also available in the public OSCCAR deliverable D3.2.</p>
S91| CECTOYS | Chemicals of Emerging Concern (CECs) in plastic toys
<p>This is the collection associated with list S91 CECTOYS, List of Chemicals of Emerging Concern (CECs) found in plastic toys on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p> </p> <p>A compiled list of 126 Chemicals of Emerging Concern (CECs) found in plastic toys described in Aurisano et. al DOI: 10.1016/j.envint.2020.106194. The list is categorized into four (as seen in CECTOYS_notes.txt) based on being included in regulatory lists of concern as well as reported hazard index (HI) and child cancer risk (CCR) based criteria.</p> <p>Structural identifiers and mapping to DTXSID provided by ECI.</p> <p> </p>
Data and script for "On the emergence of ecosystem decay: a critical assessment of patch area effects across spatial scales"
<p>Data and R script necessary to replicate the results of Riva et al. 2024 ("On the emergence of ecosystem decay: a critical assessment of patch area effects across spatial scales"; minor revisions, Biological Conservation).</p>
Emergency management/Natural Hazards: annotated tweets
<p>A set of annotated tweets related to natural hazards and emergency management.</p> <p>Information available for each tweet:</p> <p>- tweet id</p> <p>- boolean flags about its content: floods;storms;landslides;snow;infrastructures;affected individuals;caution advice;donations & volunteering;emotional support;other info;panic</p> <p> </p>
S12 | NORMANEWS | NormaNEWS for Retrospective Screening of New Emerging Contaminants
<p>This is the collection associated with list S12 NormaNEWS on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/?q=suspect-list-exchange">https://www.norman-network.com/?q=suspect-list-exchange</a></p> <p>S12</p> <p>NORMANEWS</p> <p><strong>NormaNEWS for Retrospective Screening of New Emerging Contaminants</strong></p> <p>NormaNEWS <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/031017Update/NormaNEWS_V4_26042017_wDTXSIDs.csv">CSV</a>, <a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/031017Update/NormaNEWS_V4_26042017_wDTXSIDs.xlsx">XLSX</a> (3/10/2017)</p> <p>CompTox <a href="https://comptox.epa.gov/dashboard/chemical_lists/normanews">NORMANEWS List</a></p> <p><a href="https://www.norman-network.com/sites/default/files/files/suspectListExchange/NormaNEWS_V4_InChIKeys.txt">NormaNEWS InChIKeys</a> (8/05/2017)</p> <p><a href="http://www.norman-network.com/?q=node/244">NormaNEWS</a> list provided by Nikiforos Alygizakis, Saer Samanipour and Kevin Thomas.</p> <p>Alygizakis et al 2018, DOI: 10.1021/acs.est.8b00365</p>
Neutrophil and emergency granulopoietic drivers of sepsis immune suppression and an extreme response to infection
<p>The dysregulated host response to infection leading to organ dysfunction is highly heterogeneous. It is currently poorly delineated by sepsis as a clinical syndromic classification, thus confounding immunotherapy trials. Here we establish the pathophysiology and potential therapeutic targets of a specific extreme response to infection state (sepsis response signature SRS1), characterised by immune compromise and poor outcome. We first derive a whole blood single-cell multi-omic atlas of the sepsis response (2727,993 cells, n=39), finding an increase in IL1R2+ immature neutrophils in SRS1, which we confirmed by CyTOF and RNA-sequencing (n=53). We next uncovered high activity of neutrophil STAT3 gene expression programs in SRS1, which were shared across multiple infectioius disease settings (n=1044) irrespective of the clinical definition of the patient cohorts. We observed elevated plasma G-CSF and IL-6 in SRS1, suggesting heightened emergency granulopoiesis (EG). We therefore characterised patient and healthy control hematopoietic stem cells (HSCs) using single-cell RNA/chromatin accessibility multi-omics (29,366 cells, n=27), identifying SRS1-specific EG transcriptional skewing, together with STAT3 and EG master regulator CEBPB epigenetic signatures. Our findings establish a common cellular axis present across extreme responses to infection, reveal its hematopoietic origin, and nominate G-CSF and IL-6 as potential therapeutic targets for the SRS1 state.</p> <p> </p> <p>The present data deposit includes processed and quality-controlled data tables for:</p> <p>1. Whole blood leukocytes profiled with the BD Rhapsody platform in a cohort of 39 sepsis patients (RNA and protein count matrices, as well as their accompanying metadata table)</p> <p>2. Circulating HSCs in blood profiled with the 10X multiomics platform in a cohort of 27 sepsis patients (RNA and ATAC-seq count matrices, as well as their accompanying metadata tables)</p>
Cell metadata for "The emergent landscape of the mouse gut endoderm at single-cell resolution"
<p>Cell metadata for the data published in "The emergent landscape of the mouse gut endoderm at single-cell resolution"</p> <p> </p>
2021-2022 West False River Emergency Drought Barrier water quality, flow, and fish monitoring
To manage the critically low 2021 water supply for beneficial uses, DWR installed the temporary emergency drought barrier (EDB) on West False River in the Sacramento–San Joaquin Delta (Delta), approximately 5 miles south of Rio Vista, California, in Contra Costa County in June 2021. To monitor the effectiveness and impacts of the EBD, a monitoring program was initiated to track changes in hydrodynamics, water quality, fish, harmful algal blooms, and aquatic weeds in the vicinity of the EDB. The EDB was left in place during the winter of 2021-2022 and removed in fall of 2022. This data set includes all data collected as part of that monitoring program and subsets of ongoing monitoring programs that were used in the final effectiveness report for the EDB.
Seedling emergence and biomass data of nine dryland plant species characterizing the impact of soil residual auxin herbicide across two soil types and water pulse events on greenhouse growth; Las Cruces, New Mexico, Spring 2021.
Synthetic-auxin herbicides are often used to control woody plants and aid in grassland restoration. Seed-based restoration is common alongside herbicide applications and there may be unintended effects of these herbicides on dryland plant species at the seed and seedling stages. Additionally, abiotic conditions at the time of herbicide application may influence herbicide-soil-plant interactions. We conducted a greenhouse study to examine the effects of a common shrub-control herbicide mix and its interaction with soil type and a post-herbicide water pulse on common desert plant seeds and seedlings. In this greenhouse study, we found that a subset of species responded negatively to soil residual herbicide activity of a mixture of aminopyralid, clopyralid, and triclopyr at the seed and seedling stages. Species sensitive to soil herbicide residues were primarily shrub and forb species that are often the target species of herbicide applications for woody plant control, such as Prosopis glandulosa (honey mesquite) and Larrea tridentata (creosote bush). However, two shrub species (Atriplex canescens [four-wing saltbush] and Yucca elata [soaptree yucca]) and one perennial grass species (Digitaria californica [Arizona cottontop]), which are used in dryland restoration projects, were found to be particularly sensitive to soil residual herbicide activity. Thus, if using these herbicides to control woody plants and restore herbaceous vegetation via active seeding or relying on the in situ seed bank, considerations should be given to what species are used in the seed mix, what species are already present in the soil seed bank, and other details of the circumstances of herbicide application.
STREAMS Project: Emergent landscape patterns in stream ecosystem processes resulting from groundwater/surface water interactions
This Data Set is hosted by the Luquillo LTER Program (LUQ) and owned by a LUQ's investigator. Our primary objective is to understand the linkage between surface-subsurface water interactions and ecosystem processes in neotropical lowland streams over an extended time frame (>25 yrs). Proposed research will occur at La Selva Biological Reserve in Costa Rica, which is owned and operated by the Organization for Tropical Studies In tectonically active regions of Central America, it is common for solute-rich groundwater to emerge at gradient breaks within the complex volcanic topography of mountains and foothills which intergrade with the coastal plain. These groundwaters can significantly influence solute chemistry and related ecological and ecosystem-level processes in receiving surface waters. Many solute-rich groundwaters are associated with underlying volcanic activity which has altered the chemistry of receiving streams throughout Central America. Geothermally-modified groundwaters, surfacing at the gradient break between the Central Mountain range and the coastal plain at La Selva Biological Station, have high levels of P (up to 400 mg SRP L-1) and other solutes (Ca, Cl, Mg, SO4) but are not elevated in temperature. Spatial patterns in stream solute chemistry are determined by geomorphic features of the volcanic landscape that include: upland lavas drained by P-poor streams; a gradient break (~50 m.a.s.l.), at or near where P-rich springs emerge; and lowland alluvial areas drained by streams that are both P-rich and P-poor depending on whether they receive the input of solute-rich springs. Our project is the first to determine long-term effects of nutrient enrichment in a detrital-based stream within the wet tropics. We will continue to build upon our long-term(1988-present) data set on stream solute chemistry, which is the only one that we are aware of for lowland primary rainforest of Central America. The proposed project will build on 18 years of past resear
Data for the paper Lemoine, Gmel, Foster, Marmet, Studer (2020). Multiple trajectories of alcohol use and the development of alcohol use disorder: do Swiss men mature-out of problematic alcohol use during emerging adulthood? Plos One. https://doi.org/10.1371/journal.pone.0220232
<p>Data for the paper Lemoine, Gmel, Foster, Marmet, Studer (2020). Multiple trajectories of alcohol use and the development of alcohol use disorder: do Swiss men mature-out of problematic alcohol use during emerging adulthood?</p> <p>Plos One. <a href="https://doi.org/10.1371/journal.pone.0220232">https://doi.org/10.1371/journal.pone.0220232</a></p> <p>Please refer to the paper for further information about the data.</p> <p> </p> <p>The dataset contains all data needed to reproduce the results in the above cited paper. Variable description and labels can be found in the codebook. For further information on the instruments used please refer to the paper.</p> <p>The dataset contains data for three waves that was collected between September 2010 and March 2018 in Switzerland by the C-SURF study (<a href="http://www.c-surf.ch/">www.c-surf.ch</a>). Participants were on average 20 years old at wave 1, 21 at wave 2 and 25 at wave 3 when they answered the questionnaires. The final sample size used in the paper is 4746 after excluding those that did not reply to a questionnaire or to a variable of interest for the main analysis.</p> <p>The research protocol for this study was approved by the Human Research Ethics Committee of the Canton Vaud (Protocol No. 15/07). Data collection was funded by the Swiss National Science Foundation (FN 33CSC0-122679, FN 33CS30_139467, FN 33CS30_148493).</p>
S62 | NORMANEWS2 | NormaNEWS2: Retrospective Screening of New Emerging Contaminants
<p>This is the collection associated with list S62 NORMANEWS2 on the NORMAN Suspect List Exchange.</p> <p><a href="https://www.norman-network.com/nds/SLE/">https://www.norman-network.com/nds/SLE/</a></p> <p>List of suspects provided by many contributors to <a href="https://www.norman-network.net/?q=node/327">NormaNEWS2</a>, collated by Kevin Thomas and colleagues at UQ.</p> <p>The Norman Early Warning System (NormaNEWS) is a collaborative activity aimed at members active in non-target analysis. The concept of NormaNEWS is that when one group identifies a new contaminant of emerging concern identification criteria are sent to other members of the group who use retrospective analysis techniques to check their own samples. This way we can rapidly establish the occurrence of newly identified compounds of emerging concern across Europe and beyond. NormaNEWS is lead by Kevin Thomas at NIVA (Norway) / University of Queensland (Australia) as part of the <a href="http://www.normandata.eu/?q=node/252"><strong>Non-target screening cross-working group activity</strong></a> of the NORMAN network.</p> <p><strong>What is NormaNEWS and how does it work</strong></p> <p>The first round of the collaborative NormaNEWS joint activity in 2016 successfully demonstrated the usefulness of the retrospective screening of high resolution mass spectrometric data in establishing the spatial and temporal occurrence of newly identified compounds of emerging concern. The results of this pilot study are presented in <a href="https://pubs.acs.org/doi/abs/10.1021/acs.est.8b00365?journalCode=esthag">Alygizakis <em>et al.</em>, ES&T, DOI: 10.1021/acs.est.8b00365</a>. The list of contaminants screened can be found on the <a href="http://www.norman-network.com/?q=node/236">NORMAN Suspect Exchange</a> and the <a href="https://comptox.epa.gov/dashboard/chemical_lists/normanews">CompTox Chemistry Dashboard</a>.</p> <p>To build on the first study, the NORMAN network has decided to launch NormaNEWS 2 as part of the activities of the <a href="http://www.normandata.eu/?q=node/252">NTS Cross-Working Group Activity</a> (<a href="http://www.norman-network.net/sites/default/files/files_private/JoinProgramme2018/NORMAN%20JPA%202018_final_Feb2018.pdf">NORMAN JPA 2018</a> and NORMAN JPA 2019).</p> <p>In NormaNEWS 2 we wish to further develop this approach to cover many more contaminants of emerging concern, include a broader range of matrices, and significantly increase temporal and spatial coverage.</p> <p>While NORMAN members are encouraged to participate in NormaNEWS, laboratories outside the NORMAN network are also welcome to participate. </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.