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585 results for “Goal”
Decentralized Motion Planning with Collision Avoidance for a Team of UAVs under High Level Goals
<p>The video illustrates simulation and experimental results of a team of unmanned aerial vehicles executing Linear Temporal Logic (LTL) tasks. More specifically, given a certain LTL task over predefined regions of interest, each agent derives a high-level plan that satisfies the given task. Then, it executes the plan using a continuous controller that is based on decentralized navigation functions, which also guarantee inter-agent collision avoidance. The video shows one simulation and two experimental scenarios.</p>
In-situ observations of surface Chlorophyll-a (HPLC) in the Western Antarctic Peninsula during 2008-2018 (GOAL-FURG)
<p>This dataset contains observations of in-situ chlorophyll-a (mg/m3) along the Western Antarctic Peninsula from 2008 to 2018. All data included in this dataset were collected by the Brazillian High Latitude Oceanography Group (GOAL), based at the Federal University of Rio Grande (FURG), aboard research vessels from the Brazillian Navy.</p> <p>All chlorophyll-a samples were collected at 5 metres depth. Chlorophyll-a concentration was determined through High Pressure Liquid Chromatography. This dataset has been collected thanks to a 10 year effort of sampling by GOAL in the Western Antarctic Peninsula. As such, many researchers, students, and crew members contributed to this valuable dataset. Therefore, we ask that users acknowledge the use of the dataset.</p> <p>Please consult Ferreira et al. 2024 for more information on how the data was collected and analysed.</p>
Long-term ecological studies' practices and goals for trainees
<p>We created a survey for the other authors in the 2024 <em>Ecology Letters</em> special issue on very long-term ecological studies about their practices and goals for trainees. We received 27 responses from researchers around the world studying a broad range of organisms across ecosystems. In more than half of the responding programs, undergraduate students collect, curate, and analyze data, as well as develop research questions, present at conferences, and contribute to writing scientific papers. Unlike our program, which primarily recruits from one university, other long-term studies often target a variety of institutions (79% of respondents). About half reported targeted recruitment of students from marginalized identities and a similar proportion paid students for their work. Students were slightly more likely to collaborate with a cohort of other students (3.8 in 1-5 Likert scale) and have peer cohort building activities (3.6 in 1-5 Likert scale). When asked to rank the helpful characteristics of long-term studies to undergraduate students, top choices included "links between research, internship, classes", "extensive professional networks", "rich data", and "robust logistics". The rank of "paid salaries" was split, with about a third of the programs ranking it least helpful to students but the other third of programs ranking it either as the first or second most helpful attribute of long-term programs. Based on comments related to funding, the low salary ranking might be associated with student funding opportunities available through university grants or independent fellowships. Overall, this suggests the most impactful transformation long-term studies can make is to advocate for paying trainees in future grant proposals.</p>
Thalamic input to motor cortex facilitates goal-directed action initiation
<p>Data set for: Takahashi N, Moberg S, Zolnik TA, Catanese J, Sachdev RNS, Larkum ME, Jaeger D (2021) Thalamic input to motor cortex facilitates goal-directed action initiation. <em>Current Biology</em> (DOI: <a href="https://doi.org/10.1016/j.cub.2021.06.089">https://doi.org/10.1016/j.cub.2021.06.089</a>) </p> <p>The file named "Takahashi_Data&Code.zip" is a zipped version of a folder "Takahashi_Data&Code", which contains the data analyzed in the study along with the Matlab code used to generate the published figures. To access the data and the code, first unzip the file. Then add the folder with subfolders to the Matlab path. Before running the code (e.g., "PlotData_Fig1.m"), load the related Matlab data file (e.g., "Data_Pharmacology_Fig1.mat") in Workspace. Each code plots the results used in the corresponding figure.</p>
Mu-rhythm modulation associated with the observation and execution of a goal-directed action in healthy toddlers estimated using two different baseline conditions
<p>The database includes mu-rhythm ERD/ERS values elicited by the observation and execution of a goal-directed action in healthy toddlers (N=19). ERD/ERS values has been computed using to different baseline conditions: 1) observation of a black and white static image (BL1) and 2) short period of stillness (BL2).</p> <p>The first sheet of the database refers to action execution (AE) data, whereas the second sheet refers to action observation (AO) data. The database table in each sheet includes for each subject single trial ERD/ERS values (table rows) registered in 7 different scalp sites (table columns) for both BL1 and BL2.</p> <p>The database was used for the statistical analysis of the following paper: Piazza, C.; Visintin, E.; Reni, G.; Montirosso, R. The Effect of Baseline on Toddler Event-Related Mu-Rhythm Modulation. <em>Brain Sci.</em> <strong>2021</strong>, <em>11</em>, 1159. https://doi.org/10.3390/brainsci11091159 (<a href="https://www.mdpi.com/2076-3425/11/9/1159/htm">https://www.mdpi.com/2076-3425/11/9/1159/htm</a>)</p> <p>All the details about data acquisition and preprocessing are reported in the above mentioned publication.</p>
Shared motivations, goals and values in the practice of personal science - Qualitative data set
<p>269 transcribed excerpts coded from 22 interviews to self-researchers for the study "Shared motivations, goals and values in the practice of personal science - A community perspective on self-tracking for empirical knowledge". Interviews with participants were conducted via video conferencing and were based on a list of open-ended questions, separated into key sections around participation and collaboration in personal science. Participants who agreed to be interviewed, gave informed consent in like with the ethics approval by the Inserm Institutional Review Board (IRB) for this study, and regarding this data set, previous agreement in compliance with privacy and anonymity requirements. Academic article based on this dataset: Senabre Hidalgo, E., Ball, M. P., Opoix, M., & Greshake Tzovaras, B. (2022). Shared motivations, goals and values in the practice of personal science: a community perspective on self-tracking for empirical knowledge. <em>Humanities and Social Sciences Communications</em>, <em>9</em>(1), 1-12. <a href="https://doi.org/10.1057/s41599-022-01199-0">https://doi.org/10.1057/s41599-022-01199-0</a></p>
Dataset for Assessing Multi-Dimensional Impacts of Achieving Sustainability Goals by Projecting the Sustainable Agriculture Matrix into the Future
<p>This data repository feeds into the meta-repository setup for post-processing of GCAM-SAM outputs. GitHub link of meta-repository is: <a href="https://github.com/JGCRI/Kyle-etal_2022_EF">https://github.com/JGCRI/Kyle-etal_2022_EF</a> <br> <br> Folders: <br> <strong>model/</strong> is the static version of the model used to simulate 8 scenarios. See the <a href="https://github.com/pkyle/gcam-core/tree/gpk/paper/sam">GitHub GCAM-SAM repository</a> to follow active development of this model. <br> <strong>inputs/</strong> folder contains input datasets and scripts used to prepare files while postprocessing. This is to be used with <a href="https://github.com/JGCRI/Kyle-etal_2022_EF">GitHub post-processing meta-repository</a>. <br> <strong>outdata/</strong> contains <a href="http://github.com/pkyle/gcam-core/tree/gpk/paper/sam">GCAM-SAM</a> output and <a href="http://github.com/JGCRI/Kyle-etal_2022_EF">post-processed</a> output files used to plot figures. <br> <br> Key files: <br> <em><strong>SAM-matrix.dat</strong></em> is the consolidated GCAM-SAM output. Use <em>proj_load.R</em> in the <a href="https://github.com/JGCRI/Kyle-etal_2022_EF">metarepo</a> to read the file. <br> <em><strong>region_vals.csv</strong></em> has all 8 indicators in all 8 scenarios for years 2020 till 2100 on a 10 year time step. <br> <br> Short introduction to the study:</p> <p>In this paper sustainable agriculture matrix (SAM) is estimated to 2100 using Global Change Analysis Model (GCAM). We model combinatorial variations of yield intensification, dietary shift, and greenhouse gas mitigation scenarios. Findings include scenarios having significant tradeoffs across multiple environmental, economic, and social dimensions. Assessment of these multi-dimensional tradeoffs in a consistent framework improves the quality of information for decision-making.<br> <br> Should you have any questions, feel free to reach out Page Kyle at <a href="mailto:pkyle@pnnl.gov">pkyle@pnnl.gov</a>. </p>
The Anthropocene and the Sustainable Development Goals: Key elements in geography higher education? Study Dataset.
<p>The document contains the Dataset of a study "The Anthropocene and the Sustainable Development Goals: Key elements in geography higher education? "</p>
Output data: China's energy-water-land system co-evolution under carbon neutrality goal and climate impacts
<p>Outputs for Wang, J., Duan, Y., Wang, C., 2023. China’s energy-water-land system co-evolution under carbon neutrality goal and climate impacts. (In progress)</p> <p>Folder demeter contains the spatially downscaled land use/land cover datasets.<br> Folder tethys contains the spatially downscaled water withdrawal datasets.</p> <p>The sub-folder names correspond to the scenarios described in the paper.</p> <p>For landcover datasets, land type ratios in each grid are presented. Land types include water, forest, shrub, grass, urban, snow, sparse and crops.</p> <p>For water withdrawal datasets, “wd” = “water withdrawal spatially downscaled”, “twd” = “water withdrawal spatially and temporally downscaled”, “dom”=”domestic/municipal sector”, “elec”=”electricity sector”, ”irr”=”irrigation sector”, “liv”=”livestock sector”, “mfg”=”manufacturing/industry sector”, “min”=”mining/primary energy sector”, “nonag”=”non-agricultural sector”, “total”=”all sectors”.<br> </p>
Resource-Centric Goal Model Slicing for Detecting Feature Interactions
<p>Supplementary materials of the paper entitled:</p> <p>“Resource-Centric Goal Model Slicing for Detecting Feature Interactions”</p> <p>file01 - The features related to the concept of Decline-Mutual-Exclusion.<br> file02 - The features related to the concept of Decline-Produce-and-Use<br> file03 - The features related to the concept of Decline-State-Changing<br> file04 - The features related to the concept of Enhanced-State-Changing<br> file05 - Zoom-features-2022</p>
Sustainable Development Goals (SDGs) in English as a Foreign Language (EFL)
<p>The qualitative mixed-method intervention study, grounded in content analysis and comparative methodology, reveals that incorporating SDGs into teacher training programmes is key since there is a significant direct impact on society. The objective was firstly to create an SDG-based didactic proposal including inquiry-based learning as its pedagogical approach for developing critical thinking. Secondly, to study its effect on participants regarding raising awareness of SDGs and their projection to society as future teachers.</p>
A Patient-Centered Communication Tool (UR-GOAL) Versus Usual Care for Older Patients With Acute Myeloid Leukemia, Their Caregivers, and Their Oncologists
ClinicalTrials.gov study NCT05335369. IPD Sharing: YES. Countries: 1. Publications: 3.
A Study of Eliglustat Tartrate (Genz-112638) in Patients With Gaucher Disease Who Have Reached Therapeutic Goals With Enzyme Replacement Therapy (ENCORE)
ClinicalTrials.gov study NCT00943111. IPD Sharing: Not stated. Countries: 12. Publications: 7.
Goal Achievement After Utilizing an Anti-PCSK9 Antibody in Statin Intolerant Subjects
ClinicalTrials.gov study NCT01375764. IPD Sharing: Not stated. Countries: 8. Publications: 1.
Guys/Girls Opt for Activities for Life Trial (GOAL) to Increase Young Adolescents' Physical Activity and Healthy Eating
ClinicalTrials.gov study NCT04213014. IPD Sharing: YES. Countries: 1. Publications: 2.
Effect of Goal-directed Crystalloid Versus Colloid Administration on Major Postoperative Morbidity
ClinicalTrials.gov study NCT01195883. IPD Sharing: NO. Countries: 2. Publications: 1.
Motivational Interview Intervention to Help Patients Formulate Their Goals for Medical Care in the Emergency Department
ClinicalTrials.gov study NCT03208530. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Goal Oriented Activity for Latinos With Spine Pain
ClinicalTrials.gov study NCT05005416. IPD Sharing: YES. Countries: 1. Publications: 22.
Assessment Study of Three Different Fasting Plasma Glucose Targets in Chinese Patients With Type 2 Diabetes Mellitus (BEYOND III/FPG GOAL)
ClinicalTrials.gov study NCT02545842. IPD Sharing: YES. Countries: 1. Publications: 4.
Goal Achievement After Utilizing an Anti-PCSK9 Antibody in Statin Intolerant Subjects -2
ClinicalTrials.gov study NCT01763905. IPD Sharing: Not stated. Countries: 14. Publications: 11.
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.