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200 results for “endpoints”
watercourse_100mseg: the Flemish watercourses represented by 100-meter line segments and corresponding downstream endpoints
<p>The data source <code>watercourse_100mseg</code> is derived from the raw data source '<a href="https://doi.org/10.5281/zenodo.4420904">watercourses</a>'. It represents all officially known watercourses of the Flemish Region as line segments of <strong>100 m</strong> (or < 100 m, for the most upstream segment of a watercourse). The data source can be used as a base layer of statistical <strong>population units</strong> (line segments) and corresponding anchor points, in the design of monitoring and research of watercourses.</p> <p>The data source is a GeoPackage with <strong>two spatial layers</strong>:</p> <ul> <li> <p><code>watercourse_100mseg_lines</code>: the line segments;</p> </li> <li> <p><code>watercourse_100mseg_points</code>: the corresponding downstream endpoints ('downstream' as defined in <code>watercourses</code>).</p> </li> </ul> <p>The coordinate reference system is 'Belge 72 / Belgian Lambert 72' (EPSG-code <a href="https://epsg.io/31370">31370</a>). Both layers have the same number of rows, and they share the same <strong>attributes</strong>:</p> <ul> <li><code>rank</code>: a unique, incremental number for each segment/endpoint. It just reflects the downstream-to-upstream order of segments within each original line.</li> <li><code>vhag_code</code>: the VHAG code from the raw <code>watercourses</code> data source. It distinguishes the different watercourses, so it is common to all segments/points that belong to the same watercourse.</li> </ul> <p>This version was derived from version '<code>watercourses_20200807</code>' (<a href="https://doi.org/10.5281/zenodo.4420905">Zenodo DOI</a>) as follows:</p> <ol> <li> <p>each line ('watercourse') of <code>watercourses</code> is split into segments of 100 m, where the remaining segment of < 100 m (per original line) is situated most upstream. For this step, the direction of the lines has been reverted (in <code>watercourses</code> the direction is from upstream to downstream). A unique rank number is assigned to each segment, as well as the VHAG code from the corresponding line in <code>watercourses</code>.</p> </li> <li> <p>the downstream endpoint of each segment is located, and assigned the same attributes (<code>rank</code> and <code>vhag_code</code>).</p> </li> </ol> <p>See R and GRASS code in the GitHub repository <a href="https://github.com/inbo/n2khab-preprocessing/tree/6b1d8f7/src/generate_watercourse_100mseg">'n2khab-preprocessing' at commit 6b1d8f7</a> for the creation from the <code>watercourses</code> data source.</p> <p>A reading function to return the data source in a standardized way into the R environment is provided by the R-package <a href="https://inbo.github.io/n2khab/">n2khab</a>.</p>
Madrid Grid Area Buildings + Reachable Endpoints for Given RF Transmitter Location and Parameters, with and without RISs Installation.
<p>1- The obstacles_save folder contains arrays defining the vertices locations (x,y) of buildings in the considered area in Madrid Grid.</p> <p>A transmitter is placed at the center of a square at location [600, 900]. Possible receiver (or relay trasnceivers) locations are defined as the vertices (i.e., corners) of buildings (from previous list). The goal of the simulation is to find how many hops are needed to reach, if possible, each location from the previously mentioned list of vertices, assuming a maximum allowed path loss value of 90 dB between any two consecutive hops. </p> <p>2- The arrays in no_ris specify the vertices reachable within N sucessive hops, when no RIS is installed in the area.</p> <p>3- Similarly, the arrays in double_ris give the coordinates of vertices reachable with N hops when a two RISs are installed in the middle square(as shown in related paper).</p> <p>The RIS beamforming gain is 20 dB (in Table 1 in the paper the gain should be 20 not 15 dB).</p>
Pesticide ecotoxicology Tier 1 endpoints database
<p>The database was developed under the contract CT/EFSA/PPR/2010/03 with the purpose to provide a compilation in IUCLID 5.2 of ecotoxicological endpoints of the active substances and plant protection products (PPPs). It was developed to support the revision of guidance documents on aquatic and terrestrial ecotoxicology. The database for all Tier 1 studies where higher tier studies we also available in the dossier submitted under Directive 91/414/EEC for aquatic organisms, bees, non target arthropods, non target plants and soil organisms. The variables include report metadata, active substance, species tested, description of the experimental conditions and endpoint values (e.g LC50, NOEC, EC50, ER50) according to OECD harmonised templates for Effects on biotic systems. The database includes data extraction for 5745 ecotoxicological endpoint and 1625 risk assessment endpoints.</p> <p>The Format XML export from IUCLID 5.2. with author names removed. XSD is included. The study was outsourced after a procurement procedure.</p>
Basic tools for deriving photolysis endpoints for soil photo-transformation products in groundwater
<p>This spreadsheet has been designed to determine input parameters for consideration of the photolysis pathway in FOCUS-PELMO 5.5.3 and subsequent versions. It should be used alongside the EFSA scientific guidance on “Soil phototransformation products in groundwater – consideration, parameterisation and simulation in the exposure assessment of plant protection products”.</p> <p>The tools in the spreadsheet allow to identify the relevant grid points in the solar database 'AGRI4CAST', to retrieve irradiance values for the relevant grid points and for the period of the study from the 'AGRI4CAST' database via a spatial interpolation of the irradiance values (this can also be used for other solar databases besides 'AGRI4CAST'). Furthermore, the tools enable to convert the irradiance from kWh/m², kJ/m² or J/cm² into W/m², to perform a time-step normalisation for field studies, and to compare the normalised k<sub>fast</sub> values from different field studies.</p>
Data from: Impacts of weathered microplastic ingestion on gastrointestinal microbial communities and health endpoints in fathead minnows (Pimephales promelas)
<p>Microplastics are a ubiquitous presence in the world's aquatic environments and their threat to aquatic biota is poorly understood, especially in freshwater ecosystems. In the environment, microbial biofilms can form on the surface of microplastics, and these plastics have the potential to adsorb harmful toxins. Because lab-based studies on microplastics are often conducted with clean polymers, in ecologically unrealistic conditions and concentrations, the impact of these weathered microplastics on aquatic organisms in ecologically realistic conditions is still unclear. To help address the need for ecologically relevant microplastic exposure data, we incubated 500 μm polyethylene microplastic beads in Muskegon Lake, Michigan, USA and used them to conduct a 28-day ingestion study with male and female fathead minnows (<em>Pimephales promelas</em>). We examined the effects of microplastic ingestion on the fish gut microbial community along with hepatic gene expression and health parameters. We found that microplastic ingestion had statistically significant impacts on growth in male fathead minnows. Microplastic treatment did not significantly alter the beta diversity of the gut microbial community for either males or females, but there were clear differences between sexes and over time, indicating that these factors may outweigh the impacts of microplastic ingestion on beta diversity in the gut. The expression of immune response genes was not altered in males. It did, however, cause some changes to alpha diversity metrics in both sexes and there were several differentially abundant taxa among treatments. These data suggest that microplastic ingestion has health effects, but these effects may be sex specific across certain species and they are likely not being solely driven by changes in gut microbial communities.</p>
Conformance Assessment of Architectural Design Decisions on API Endpoint Designs Derived from Domain Models: Dataset and Code
<p>This is the dataset and related code artifact for the article "Conformance Assessment of Architectural Design Decisions on API Endpoint Designs Derived from Domain Models".</p> <p><strong>Abstract of the article:</strong></p> <p>Domain-driven design (DDD) is commonly used, especially in enterprise systems, to design microservices. A crucial aspects of microservice design is API design, which includes the design of API endpoints. In particular, we studied link mapping, API operation design, and resource segregation as API endpoint design issues that are linked to domain model design. Based on Architectural Design Decisions (ADD) studied in a prior empirical study on the interrelation of DDD and APIs, we suggest a new approach for the automated assessment of conformance to ADD options. This approach aims to support the continuous analysis of API endpoint designs. The approach suggests automated detectors to detect ADD options selected in a given API endpoint design, as well as an assessment scoring scheme based on our empirical results. For evaluation of our results, we first manually created a ground truth for 12 cases in a multi-case study, and then compared the results of our automated detectors to the ground truth for each of those cases.</p>
Dataset to the article "Omnidirectional endpoint force control through Functional Electrical Stimulation" by Marek Sierotowicz and Claudio Castellini
<p>The present .zip files contains the anonimized datasets of a static force output control test facilitated through FES.</p> <p>In addition, the DataExtraction MATLAB code is meant to provide the synchronisation offsets for the logs.</p> <p>The data is sampled from 3 anonymized participants, who all signed informed consent forms.</p> <p>The experiment was carried out in compliance with the standards of the Declaration of Helsinki, and was approved by the ethical committee of the Friedrich-Alexander Universität Erlangen-Nürnberg (approval ID 22-304-S).</p> <p> </p>
LOGiC - Lapatinib Optimization Study in ErbB2 (HER2) Positive Gastric Cancer: A Phase III Global, Blinded Study Designed to Evaluate Clinical Endpoints and Safety of Chemotherapy Plus Lapatinib
ClinicalTrials.gov study NCT00680901. IPD Sharing: YES. Countries: 23. Publications: 2.
Data from: Impacts of weathered microplastic ingestion on gastrointestinal microbial communities and health endpoints in fathead minnows (Pimephales promelas)
Open the record for dataset details and reuse information.
Endpoint gastruloid-on-microraft analysis (EGOMRA)
Open the record for dataset details and reuse information.
Database specific for the pesticide active substance and their metabolites, comprising the main genotoxicity endpoints
<p>In 2014, EFSA has commissioned the compilation of a database specific for the pesticide residues including active substances and their metabolites, which comprises different genotoxicity endpoints, i.e. point mutations, structural and numerical chromosome aberrations, and DNA damage.</p> <p>Data collection on individual genotoxicity studies has been retrieved from regulatory toxicological reports (Draft or Renewal Assessment Reports, i.e. DARs or RARs, respectively) as provided by the Rapporteur Member State (RMS) during the pesticide peer review process at European Level. The final EFSA conclusion on the overall genotoxic potential of active substance or metabolites taking into account all available information is not included in the database. </p> <p>The database contains identity and genotoxicity information on more than 290 active substances and some of their metabolites.</p> <p>The database represents a practical tool to complement in-silico tools i.e. QSAR (Quantitative structure–activity relationship models), grouping and read across for prediction of the genotoxicity hazard of the pesticides residues, and it supposes to enlarge the chemical domains for their application.</p> <p><strong>Format: xls; contact: data.collection@efsa.europa.eu, pesticides.ppr@efsa.europa.eu </strong></p> <p><br> <strong>DISCLAIMER</strong><br> Without prejudice to the legal notice applicable to EFSA's website available here, the following legal notice applies to the Pesticide genotoxicity database and any documents, data or information contained therein. Users are advised to read this legal notice carefully before accessing, using or reading any document, data or information made available in this context, or making any other use of the Database.<br> The Pesticide genotoxicity database is a compilation of chemical and genotoxicity information on active substances and some of their metabolites. The database contains the results of individual studies as initially assessed by the Rapporteur member state (RMS) and reported in the respective Draft assessment reports (DARs) or Renewal Assessment Reports (RARs). The final EFSA Conclusions on the respective active substances are available to the public on the EFSA Journal. The database includes the data that was available at the moment of compilation of the database (December 2016) and will be updated on a regular basis by including or deleting of information as a result of renewal procedure of active substances (Regulation (EU) No 1107/2009). <br> EFSA makes no representations or warranties about the accuracy or suitability of any document, information, data provided in the Database. In case of discrepancy between the data provided in the original scientific output (DARs/RARs) and that in this database, preference shall be given to the former.<br> This database does not disclose any commercially sensitive or otherwise confidential information. Unless otherwise stated, the owners of the data compiled in this database are the applicants under Regulation (EU) No 1107/2009, and by acceiding the Database you acknowledge that agreement for reuse of these data should be sought from them.<br> The information provided in the Database and related materials are not intended to constitute advice of any kind or the rendering of consulting, or other professional services of any kind. Acceding the Database does not establish any contractual relationship with EFSA. Users are advised to consult with an attorney, food consultant or other professional to determine what may be best for your individual needs.<br> By acceding the Database, you also acknowledge that the documents, data or information made available by EFSA may contain inaccuracies or errors. The content of the information provided is for your information and use only. It may be subject to change at any time and without prior notice by EFSA.</p>
Novel Endpoint Characterization Factors for Life Cycle Impact Assessment of Terrestrial Acidification
<p>This repository contains Excel files with the characterization factorsand the soil response factors for the publication entitled "Novel Endpoint Characterization Factors for Life Cycle Impact Assessment of Terrestrial Acidification", published in the "Journal of Ecological Indicators" .<br><br></p> <p>Content:</p> <p><strong>Datasets.zip</strong> is an folder containing the following Excel files: </p> <ul> <li><strong>CF_Terrestrial_Acidification_2024-08-01.xlsx</strong> with the following sheets <ul> <li><em>Dataframe</em> gathering terrestrial acidification marginal endpoint CF [PDF.yr/kg_emitted] values at country level (with the world average value), for 3 acidifying substances (NOx, NHx, SOx) at global and regional impact scales (with and without the inclusion of the Global Extinction Probability - GEP - respectively)</li> <li><em>Calc Info</em> summing up calculation informations</li> <li><em>Calc Table</em> registering input parameters used to run the calculations leading to the <em>Dataframe</em> sheet (substance used, original and adapted resolutions for emission and deposition compartments, resolutions for each CF components and spatial transformations, GEP normalization method)</li> </ul> </li> <li><strong>RF_NO3_2024-03-27.xlsx</strong> with the following sheet:<br> <ul> <li><em>RFs</em> containing the soil response values [(molH+ / L).(yr / kg_dep)] at ecoregion level (referred to as "idTarget") for a marginal increase of 10% in NO3 deposition rate. It also gathers the intermediate results leading the final RFs (sustances' deposition rates, reference and post-deposition increase pHs) </li> </ul> </li> <li><strong>RF_NH4_2024-03-25.xlsx</strong> with the following sheet:<br> <ul> <li><em>RFs</em> containing the soil response values [(molH+ / L).(yr / kg_dep)] at ecoregion level (referred to as "idTarget") for a marginal increase of 10% in NH4 deposition rate. It also gathers the intermediate results leading the final RFs (sustances' deposition rates, reference and post-deposition increase pHs)</li> </ul> </li> <li><strong>RF_SO4_2024-03-25.xlsx</strong> with the following sheet:<br> <ul> <li><em>RFs</em> containing the soil response values [(molH+ / L).(yr / kg_dep)] at ecoregion level (referred to as "idTarget") for a marginal increase of 10% in SO4 deposition rate. It also gathers the intermediate results leading the final RFs (sustances' deposition rates, reference and post-deposition increase pHs)</li> </ul> </li> </ul>
Conformance Assessment of Architectural Design Decisions on the Mapping of Domain Model Elements to APIs and API Endpoints: Dataset and Code
<p>This is the dataset and related code artifact for the article "Conformance Assessment of Architectural Design Decisions on the Mapping of Domain Model Elements to APIs and API Endpoints".</p> <p><strong>Abstract of the article:</strong></p> <p> Microservice APIs are often identified and designed based on Domain-Driven Design (DDD). To help in the continuous analysis of mappings of domain model elements to APIs and API endpoints, we aim to automate the assessment of conformance to Architectural Design Decision (ADD) options. The ADDs, their decision options, and relevant decision drivers studied in this paper originate from an empirical study on the mapping of domain model elements to APIs and API endpoints in practice. We propose automated detectors to detect the decision options of the ADDs taken in a given microservice API model, and an assessment scoring scheme based on the empirical knowledge codified in the ADDs. We evaluate our work, by first manually creating a ground truth for 14 cases in a multi-case study, and then comparing the results of our automated detectors to the ground truth for each of the 14 cases. In the cases we were able to identify 86\% of the decision points correctly, and a statistical analysis of our data shows only a negligible effect size for differences to the ground truth.</p>
Informing upper extremity rehabilitation through endpoint kinematics of the functional reaching movement after stroke
<p>Background. Stroke is a leading contributor to upper limb disability. Current assessments of motor ability are at best subjective estimates. Rehabilitation could be more effective when informed by an individual's specific capacities rather than diagnostic observation. This study characterizes sub-movements of interest during functional reach-to-target tasks with endpoint analysis.\newline<br> <br> Methods. Using Fugl-Meyer (FM) scores and reach capacities, stroke survivors were placed in either mild or severe impairment groups. Individual completed sets of reach-to-target tasks over two visits. The averaged reach curve for each subject was analyzed for angular orientation and velocity profile. The Procrustes method of statistical shape analysis was modified to identify reaching sub-movements that were incongruous to control sub-movements.\newline</p> <p>Findings. Reach-to-target curves were investigated for 15 individuals with mild impairment (FM <span class="math-tex">\(52 \pm 9\)</span>) and 14 individuals with severe impairment (FM <span class="math-tex">\(16 \pm 7\)</span>). The endpoint kinematic analysis found that individuals with severe impairment demonstrate lower peak velocities (centimeters per second) [<span class="math-tex">\(28.5 \pm 17.3 , 80.3 \pm 29.5\)</span>] which occurred sooner in the movement (milliseconds) [<span class="math-tex">\(36.81 \pm 27.0, 59.6 \pm 14.8\)</span>]. The mild group demonstrated variability in orientation in the medial-lateral space, and movement initiation that was congruous to healthy movement. The severe impairment group demonstrated variability in orientation in every axis and showed incongruous initiation and completion behaviors, with some comparable movement in between. \newline<br> <br> Interpretation. Endpoint analysis is a valuable option for clinicians to inform physiotherapy. In addition to kinematic metrics such as orientation and velocity, sub-movements that are comparable to healthy movement can be identified in both mild and severe impairment.</p>
Reproducibility Report for the paper "Vibration signal-assisted endpoint detection for long-stretch, ultraprecision polishing processes"
<p>This reproducibility report includes the datasets and computer code used for reproducing the results in the paper, Jin, Bukkapatnam, Hayes, and Ding, 2023, “Vibration signal-assisted endpoint detection for long-stretch, ultraprecision polishing processes,” <em>ASME Transactions, Journal of Manufacturing Science and Engineering</em>, Vol.145, pp. 061007.</p>
VITAL-DEP: Depression Endpoint Prevention in the VITamin D and OmegA-3 TriaL
ClinicalTrials.gov study NCT01696435. IPD Sharing: Not stated. Countries: 1. Publications: 9.
Survival Endpoints in Women Treated for Metastatic Breast Cancer: Contribution of Real-life Databases
ClinicalTrials.gov study NCT03676257. IPD Sharing: NO. Countries: 1. Publications: 1.
Best Clinical Endpoints That Likely Induce Worse Prognosis in Interstitial Lung Diseases
ClinicalTrials.gov study NCT03400839. IPD Sharing: NO. Countries: 1. Publications: 1.
A Study to Assess Objective Endpoint Measurements of Response in Bacterial Skin Infections
ClinicalTrials.gov study NCT01283581. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Immune-checkpoint Inhibitors and Surrogate Endpoints in Cancer Trials (SURROGATE-ICI)
ClinicalTrials.gov study NCT03963518. IPD Sharing: NO. Countries: 1. Publications: 2.
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.