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1,197 results for “FLEXIBILITY”
Fig. 11 in Revision of the flexible crinoid genus Ammonicrinus and a new hypothesis on its life mode
Fig. 11. The lecanocrinid species Ammonicrinus kerdreoletensis Le Menn and Jaouen, 2003 (GIK−2121) from Vireux−Molhain (locality 12, Appendix 1), France, lower Eifelian (Middle Devonian); lateral view of long mesistele, proxistele and huge cup (arrow) on matrix. Scale bar 10 mm.
Fig. 10. The lecanocrinid species Ammonicrinus sulcatus from locality 1 in Revision of the flexible crinoid genus Ammonicrinus and a new hypothesis on its life mode
Fig. 10. The lecanocrinid species Ammonicrinus sulcatus from locality 1 (A–G, I–Q) and 2 (H) (see Appendix 1). A–D. Facet views of GIK−2104–2107, showing nodular tubercles and spine−tubercles on exterior flanks of the columnals of the mesistele. E. Facet view (E1) and view of the exterior flank of a specimen (E2) (GIK−2108), showing tubercles and spine−tubercles on exterior flank of the columnal of the mesistele. F. Facet view of a specimen (GIK−2109), showing tubercles and spine−tubercles on exterior flank of the columnal of the mesistele. G. Facet view of a strongly sculptured columnal (GIK−2110) of the distal−most mesistele, showing connection to the dististele. H. Facet view of a columnal of the distal−most mesistele (GIK−2111), showing long LCEE and connection to the dististele. I. Facet view of a columnal of the distal−most mesistele (GIK−2112), showing relatively long LCEE and connection to the dististele. J. Interior view of a distal−most, barrel−like columnal of the mesistele (GIK−2113) with LCEE. K. Interior view of a distal−most, barrel−like columnal of the mesistele (GIK−2114), with partly preserved LCEE. L. Facet view of a juvenile distal columnal of the mesistele (GIK−2115) with nodular tubercles on exterior flank and on LCEE. M–N. Juvenile columnals of the proximal mesistele in facet views, showing well developed nodes on exterior flanks. M. GIK−2116. N. GIK−2117. O. Facet view of a juvenile distal columnal of the mesistele (GIK−2118) with nodular tubercles on exterior flank and on LCEE. P. Lateral view (P1) and view of the exterior flank (P2) of the partly preserved mesistele (GIK−2119); the specimen shows nodular tubercles, spine−tubercles and a few partly preserved spines (arrow). Q. Facet view (Q1) and lateral view (Q2) of a cracked, coiled mesistele (GIK−2120), showing several tuberculated and concave ossicles of the cup (arrows). Scale bars 10 mm.
Fig. 15 in Revision of the flexible crinoid genus Ammonicrinus and a new hypothesis on its life mode
Fig. 15. Schematic sketches of different LCEE of the mesistele in uncoiled (above) and coiled positions (below), indicating evolution of perfecting the crown−encasing in coiled position by modifying the extensions form Emsian to Givetian. A. Lateral view of Ammonicrinus kerdreoletensis Le Menn and Jaouen, 2003, showing similar shaped columnals with very short LCEE; thus, the crown is laterally nearly unprotected in coiled position. B. Lateral view of Ammonicrinus wanneri Springer, 1926, with lengthened LCEE of the similar shaped columnals, which lattice−like guarded the crown in coiled position. C. Lateral view of Ammonicrinus sulcatus Kongiel, 1958, showing smaller columnals of the mesistele, which are interconnected with longer ones and afford lateral density of the coiled stem. D. Lateral view of Ammonicrinus doliiformis Wolburg, 1938a (for 1937), showing regularly or irregularly arranged columnals with longer and shorter LCEE, which were interconnected with several columnals showing broadened convex and concave extensions that could interlock in coiled position.
Fig. 6 in Flexibility is everything: prey capture throughout the seasonal habitat switches in the smooth newt Lissotriton vulgaris
Fig. 6 First (a) and second (b) phase of the tongue prehension mode shown in Fig. 4a. The time axes are normalized to percentages of corresponding phase duration. Both phases can, therefore, be directly compared to the kinematic profiles shown in Fig. 4. Note the striking similarities of movement patterns of the second phase (b) and the aquatic feeding patterns shown in Fig. 4a, b, c
Fig. 5 in Flexibility is everything: prey capture throughout the seasonal habitat switches in the smooth newt Lissotriton vulgaris
Fig. 5 Significant correlation plots of kinematic variables. The feeding modes are color*coded: blue (a, b) suction feeding in the aquatic stage, liVWt brown (c, d), jaw prehension in the aquatic stage, and Vreen (e–l)
Data Access Made Easy: flexible, on the fly data standardization and processing (for research automatic weather stations)
<pre>Automatic Weather Stations (AWS) deployed in the context of research projects provide very valuable data thanks to the flexibility they offer in term of measured meteorological parameters, choice of sensors and quick deployment and redeployment. However this flexibility is a challenge in terms of metadata and data management. Traditional approaches based on networks of standard stations can not accommodate these needs and often no tools are available to manage these research AWS, leading to wasted data periods because of difficult data reuse, low reactivity in identifying potential measurement problems, and lack of metadata to document what happened. The Data Access Made Easy (DAME) effort is our answer to these challenges. At its core, it relies on the mature and flexible open source MeteoIO meteorological pre-processing library. It was originally developed as a flexible data processing engine for the needs of numerical models consuming meteorological data and further developed as a data standardization engine for the Global Cryosphere Watch (GCW) of the World Meteorological Organization (WMO). For each AWS, a single configuration file describes how to read and parse the data, defines a mapping between the available fields and a set of standardized names and provides relevant Attribute Conventions Dataset Discovery (ACDD) metadata fields, if necessary on a per input file basis. Low level data editing is also available, such as excluding a given sensor, swapping sensors or merging data from another AWS, for any given time period. Moreover an arbitrary number of filters can be applied on each meteorological parameter, restricted to specific time periods if required. This allows to describe the whole history of an AWS within a single configuration file and to deliver a single, consistent, standardized output file possibly spanning many years, many input data files and many changes both in format and available sensors. Finally, all configuration files are versionned in order to document their history. A web interface has been developed that allows data owners to manage the configuration files for their stations, refresh their data at regular intervals, inspect the data QA log files and allow on-demand data generation. The same interface allows other users to request data on-demand for any time period.<br><br>This presentation and software has received funding from the World Meteorological Organization under grant agreement No. 29539/2022-1.9 as well as the European Union’s Horizon 2020 research and innovation program under grant agreement No. 101003472 (Arctic Passion). It has also been supported by the WSL/SLF over many years and projects.</pre>
Hydrology and trophic flexibility structure alpine stream food webs in the Teton Range, Wyoming, USA
<p>Data and code necessary to replicate the findings from the manuscript titled "Hydrology and trophic flexibility structure alpine stream food webs in the Teton Range, Wyoming, USA".</p> <p><span>Abstract:</span><strong><span> </span></strong><span>Understanding biotic interactions and how they vary across habitats is important for assessing the vulnerability of communities to climate change. Receding glaciers in high mountain areas can lead to the hydrologic homogenization of streams and reduce habitat heterogeneity, which are predicted to drive declines in regional diversity and imperil endemic species. However, little is known about food web structure in alpine stream habitats, particularly among streams fed by different hydrologic sources (e.g., glaciers or snowfields). We used gut content and stable isotope analyses to characterize food web structure of alpine macroinvertebrate communities in streams fed by glaciers, subterranean ice, and seasonal snowpack in the Teton Range, Wyoming, USA. Specifically, we sought to: (1) assess community resource use among streams fed by different hydrologic sources; (2) explore how variability in resource use relates to feeding strategies; and (3) identify which environmental variables influenced resource use within communities. Average taxa diet differed among all hydrologic sources, and food webs in subterranean ice-fed streams were largely supported by the gold alga <em>Hydrurus</em>. This finding bolsters a hypothesis that streams fed by subterranean ice may provide key habitat for cold-water species under climate change by maintaining a longer growing season for this high-quality food resource. While a range of environmental variables associated with hydrologic source (e.g., stream temperature) were related to diet composition, hydrologic source categories explained the most variation in diet composition models. Less variable diets within versus among streams suggests high trophic flexibility, which was further supported by high levels of omnivory. This inherent trophic flexibility may bolster alpine stream communities against future changes in resource availability as the mountain cryosphere fades. Ultimately, our results expand understanding of the habitat requirements for imperiled alpine taxa while empowering predictions of their vulnerability under climate change.</span></p>
Dataset: Structural Health Monitoring of a Flexible Wing
<p>This Zenodo entry contains the experimental data underlying the journal article Noise-robust Modal Parameter Identification and Damage Assessment for Aero-structures, in preparation. The document XB-2_SHM_Dataset.pdf serves as the explanatory note for the data contained in SHM_XB2.mat</p>
Data input for the RegMex model experiment on the power system and flexible sector coupling
<p>This file provides the input data used in the power system flexibility model experiment performed within the RegMex project. Comprehensive information about the project can be found in the project report [Lechtenböhmer2018] (in German, see link in the file). In the experiment performed with the data documented here, three scenarios were considered, labelled "Import", "Decentralized" and "Offshore". This file contains the input for all scenarios. All further information on the model and scenario configuration is available from the project report. Many technology parameter have been derived as own assumptions within previous projects, relying on different sources. Details can be found in the cited PhD and masters theses. In the experiment, Germany was modelled with 18 regions reflecting the transmission grid operator zones (see map in the file).</p>
Inhibitory control, exploration behaviour and manipulated ecological context are associated with foraging flexibility in the great tit
<p class="MsoCommentText">Organisms are constantly under selection to respond effectively to diverse, sometimes rapid, changes in their environment, but not all individuals are equally plastic in their behaviour. Although cognitive processes and personality are expected to influence individual behavioural plasticity, the effects reported are highly inconsistent, which we hypothesise is because ecological context is usually not considered.</p> <p class="MsoCommentText">We explored how one type of behavioural plasticity, foraging flexibility, was associated with inhibitory control (assayed using a detour-reaching task) and exploration behaviour in a novel environment (a trait closely linked to the fast-slow personality axis). We investigated how these effects varied across two experimentally manipulated ecological contexts, food value and predation risk.</p> <p class="MsoCommentText">In the first phase of the experiment, we trained great tits <i>Parus major</i> to retrieve high value (preferred) food that was hidden in sand so that this became the familiar food source. In the second phase, we offered them the same familiar hidden food at the same time as a new alternative option that was visible on the surface, which was either high or low value, and under either high or low perceived predation risk. Foraging flexibility was defined as the proportion of choices made during four minute trials that were for the new alternative food source.</p> <p>Our assays captured consistent differences among individuals in foraging flexibility. Inhibitory control was associated with foraging flexibility - birds with high inhibitory control were more flexible when the alternative food was high value, suggesting they inhibited the urge to select the familiar food and instead selected the new food option. Exploration behaviour also predicted flexibility – fast explorers were more flexible, supporting the information gathering hypothesis. This tendency was especially strong under high predation risk, suggesting risk aversion also influenced the observed flexibility because fast explorers are risk prone and the new unfamiliar food was perceived to be the risky option. Thus, both behaviours predicted flexibility, and these links were at least partly dependent on ecological conditions.</p> <p class="MsoCommentText">Our results demonstrate that an executive cognitive function (inhibitory control) and a behavioural assay of a well-known personality axis are both associated with individual variation in the plasticity of a key functional behaviour. That their effects on foraging flexibility were primarily observed as interactions with food value or predation risk treatments also suggests that the population level consequences of some behavioural mechanisms may only be revealed across key ecological conditions.</p>
Supplementary material for: RSAT variation-tools: An accessible and flexible framework to predict the impact of regulatory variants on transcription factor binding
<p>Supplementary Material for the Article</p> <p>Santana-Garcia, W., Rocha-Acevedo, M., Ramirez-Navarro, L., Mbouamboua, Y., Thieffry, D., Thomas-Chollier, M., Contreras-Moreira, B., van Helden, J., Medina-Rivera, A., 2019. RSAT variation-tools: An accessible and flexible framework to predict the impact of regulatory variants on transcription factor binding. Comput. Struct. Biotechnol. J. 17, 1415–1428.</p> <p> </p>
Supplementary Data for AGouTI - flexible Annotation of Genomic and Transcriptomic Intervals
<p>The data allows to replicate the use-case scenario described in the manuscript "AGouTI - flexible Annotation of Genomic and Transcriptomic Intervals" by Jan G. Kosiński and Marek Żywicki.</p>
De novo modelling of HEV replication polyprotein: Five-domain breakdown and involvement of flexibility in functional regulation - DATASET
<p>All models used for the paper "De novo modelling of HEV replication polyprotein: Five-domain breakdown and involvement of flexibility in functional regulation".</p>
Artifact for Paper ParaQooba: A Fast and Flexible Framework for Parallel and Distributed QBF Solving
<p>The artifact for the paper "ParaQooba: A Fast and Flexible Framework for Parallel and Distributed QBF Solving" submitted to the <a href="https://tacas.info/artifacts-23.php">TACAS2023 artifact evaluation</a>.</p> <p>We thank the reviewers for their comments and added the missing dependencies to this revised version. No other parts have been changed.</p>
The evolution of dynamic and flexible courtship displays that reveal individual quality
Abstract Sexual selection is a major force shaping morphological and behavioral diversity. Existing theory focuses on courtship display traits such as morphological ornaments whose costs and benefits are assumed be to fixed across individuals' lifetimes. In contrast, empirically observed displays are often inherently dynamic, as vividly illustrated by the acrobatic dances, loud vocalizations, and vigorous motor displays involved in courtship behavior across a broad range of taxa. One empirically observed form of display flexibility occurs when signalers adjust their courtship investment based on the number of rival signalers. The predictions of established sexual selection theory cannot readily be extended to such displays because display expression varies between courtship events, such that any given display may not reliably reflect signaler quality. We thus lack an understanding of how dynamic displays coevolve with sexual preferences and how signalers should tactically adjust their display investment across multiple courtship opportunities. To address these questions, we extended an established model of the coevolution of a female sexual preference and a male display trait to allow for flexible, dynamic displays. We find that such a display can coevolve with a sexual preference away from their naturally selected optima, though display intensity is a weaker signal of male quality than for non-flexible displays. Furthermore, we find that males evolve to decrease their display investment when displaying alongside more rivals. This research represents a first step towards generalizing the findings of sexual selection theory to account for the ubiquitous dynamism of animal courtship. Significance statement Animal courtship displays are typically costly for survival: songs attract predators; dances are exhausting; extravagant plumage is cumbersome. Because of the trade-off between mating benefits and survival costs, displaying individuals often vary their displays across time, courting more intensely when the potential benefit is higher or the cost is lower. Despite the ubiquity of such adjustment in nature, existing theory cannot account for how this flexibility might affect the coevolution of displays with sexual preferences, nor for the patterns of tactical display adjustment that might result, because those models treat displays as static, with fixed costs and benefits. Generalizing a well-studied model of sexual selection, we find that a static display and a flexible display can evolve under similar conditions. Our model predicts that courtship should be less intense when more competitors are present.
Replication package for the study "Digital Sufficiency in Flexible Work"
<p>This dataset is published for transparency and open data purposes, as part of the work "<em>'We are always on, is that really necessary?' Exploring the Path to Digital Sufficiency in Flexible Work</em>" published at <a href="https://conf.researchr.org/home/ict4s-2023">ICT4S 2023</a> conference.</p> <p><strong>The study:</strong></p> <p>We conducted three focus groups with a total of 11 participants, inside two different companies. Our aim was to investigate the notion of digital sufficiency in the context of flexible work.</p> <p><strong>Content:</strong></p> <ul> <li><em>Preliminary interview guide.pdf</em>: the interview guide containing the questions for the preliminary interview</li> <li><em>Focus group slides.pdf</em>: the slides presented to the participants of the three focus groups</li> <li><em>Focus group participant print-outs.pdf</em>: the sheets distributed to the participants of the three focus groups, for individual note-taking</li> <li><em>Codebook.xlsx</em>: the codes extracted (with the help of the software <a href="http://www.saturateapp.com">Saturate</a>) from the transcripts of the three focus groups: <ul> <li>tab <em>CODEBOOK</em>: the codes, sorted by three levels and by research question, along with their definition and a description on when the code is applicable,</li> <li>tab <em>Code Count</em>: the number of occurrence of each code in the transcripts,</li> <li>tab <em>Clustering Tactics</em>: the thematic analysis performed on the codes with level 1 "tactic". Corresponds to the Table III in the paper</li> </ul> </li> </ul> <p>For privacy reason, all names are removed and the transcript and audio recording are not part of this replication package.</p>
U.S. building energy efficiency and flexibility as an electric grid resource (Data and Code)
<p><strong>* New in Version 2.1 *</strong></p> <ul> <li> <p>All residential measure savings shapes data (<strong>Latest_Res_Shapes.zip</strong> and residential measures in <strong>Latest_BM_Shapes.zip</strong>) were updated to correct post-processing errors present in version 2.</p> </li> <li> <p>The raw baseline-case data that are used in Scout to estimate sector-level baseline hourly loads (file <a href="https://github.com/trynthink/scout/blob/master/supporting_data/tsv_data/tsv_load.gz">tsv_load</a>) are now included in this data resource (see files <strong>Latest_Res_Baselines.zip</strong> and <strong>Latest_Com_Baselines.zip</strong>).</p> </li> <li> <p>Additional residential measure run documentation is available (<a href="https://github.com/NREL/resstock/blob/e2a98b7345d5c453ba35341b70af2f8859dd22fe/GEB_Potential.yml">here</a> for all except water heating efficiency plus flexibility (EE+DF) measure and <a href="https://github.com/NREL/resstock/blob/9611d92388e1e23466c9dc451e115c21321b4012/GEB_Potential_v2.5.0_appl_ee_dr.yml">here</a> for the water heating EE+DF measure).</p> </li> <li>A guide to reading and/or preparing savings shapes CSVs is available <a href="https://scout-bto.readthedocs.io/_/downloads/en/latest/pdf/">in the Scout documentation</a>, p. 36. The documentation also summarizes the net system load conditions that measures with flexibility (DF) characteristics respond to (Table 1, p. 37).</li> </ul> <p><strong>* New in Version 2 *</strong></p> <p>All hourly savings shapes CSV files that support the original <a href="https://doi.org/10.1016/j.joule.2021.06.002">analysis</a> have been updated to reflect the following improvements:</p> <ul> <li> <p>Generate residential data using ResStock v2.5.0 and commercial data using DOE Commercial Prototypes generated with OpenStudio v3.3.0.</p> </li> <li> <p>Residential and commercial measures with flexibility (DF) features respond to updated grid conditions (net peak/low load periods) that are consistent with projections from the EIA 2022 Annual Energy Outlook (AEO) “Low renewables cost” <a href="https://www.eia.gov/outlooks/aeo/tables_side_xls.php">side case</a>.</p> </li> <li> <p>Residential baseline loads and load savings are now distinguished by three building types (single family, multi family, and mobile homes).</p> </li> </ul> <p>Updated savings shape CSVs are organized into three ZIP files that may be separately downloaded depending on user interests:</p> <p><strong>Latest_BM_Shapes.zip</strong> includes only the subset of savings shape CSVs needed to execute the <a href="https://doi.org/10.5281/zenodo.3158929">Scout Benchmark Scenarios</a>.</p> <p><strong>Latest_Res_Shapes.zip</strong> includes all residential savings shape CSVs.</p> <p><strong>Latest_Com_Shapes.zip</strong> includes all commercial savings shape CSVs.</p> <p>Baseline load shapes in Scout have also been updated based on the same versions of ResStock and the DOE Commercial Prototypes, and peak/take period impact calculations have been updated to reflect the 2022 AEO system conditions. These updated data are contained in <a href="https://github.com/trynthink/scout/releases/tag/v0.8">Scout v0.8</a> (see ./supporting_data/tsv_data).</p> <p><br> <strong>Summary of Original Data Files</strong></p> <p>These data underpin an analysis of the near- and long-term technical potential bulk power grid resource offered by best available U.S. building efficiency and flexibility measures. Using multiple openly-available modeling frameworks supported by the U.S. Department of Energy, including <a href="https://scout.energy.gov/">Scout</a>, <a href="https://resstock.nrel.gov/">ResStock</a>, and the <a href="https://www.energycodes.gov/development/commercial/prototype_models">Commercial Building Prototype Models</a>, we pair bottom-up simulations of measures' building-level impacts with regional representations of the building stock and its projected electricity use to estimate the impacts of multiple building efficiency and flexibility scenarios on hourly regional system loads across the contiguous U.S. in 2030 and 2050. We find that demand-side management via building efficiency and flexibility could avoid up to nearly ⅓ of annual fossil-fired generation and ½ of fossil-fired capacity additions after 2020.<strong> </strong>Results are reported at both the national and regional scales and are disaggregated by building type and end use, facilitating a quantitative understanding of the role that buildings as a whole and specific building technologies or operational approaches can play in the future evolution of the U.S. electricity system.</p> <p>The four ZIP files that make up this data record are interpreted as follows:</p> <p><strong>Measure_Data.zip: </strong>Includes the Scout energy conservation measure (ECM) JSON definitions that were used to generate the main baseline and efficient/flexible scenario results ("Baseline_Measures" and "Efficiency_Flexibility_Measures", respectively), as well as side cases that assess the sensitivity of results to higher levels of variable renewable penetration ("High_RE_Sensitivity_Analysis") and a high degree of building load electrification ("High_Electrification_Measures"). Each measure set includes supporting 8760 load savings shapes in the sub-folder "Savings_Shapes". Additional details about defining and interpreting Scout measures with time-sensitive analysis features are available <a href="https://scout-bto.readthedocs.io/en/latest/tutorials.html#time-sensitive-valuation">here</a>.</p> <p><strong>Results_Data.zip: </strong>Includes the main and side case results data. Baseline-case outcomes, which are consistent with the <a href="https://www.eia.gov/outlooks/archive/aeo19/">EIA 2019 Annual Energy Outlook</a>, are stored in "Baseline_Loads". Efficient/flexible scenario results are stored in "Efficiency_Flexibility_Measure_Impacts_Individual" and "Efficiency_Flexibility_Measure_Impacts_Portfolio," respectively, where the former includes results for individual measures in our analysis without considering any interactions across measures, and the latter includes results for aggregations of energy efficiency (EE), demand flexibility (DF), and efficiency and flexibility (EE+DF) portfolios that do consider interactions across measures in each portfolio. Results for the high electrification side case are stored in the "High_Electrification" sub-folder in the EE+DF case only. Results for the high renewable sensitivity analysis are stored in "High_RE_Sensitivity_Analysis", and residential and commercial 8760 savings shape outcomes for each of the EE, DF, and EE+DF measure portfolios and five of the 2019 EIA Electricity Market Module (EMM) <a href="https://www.eia.gov/outlooks/aeo/nems/documentation/archive/pdf/m068(2018).pdf">regions</a> (p.6) of focus are stored in "Sector_Level_8760s".</p> <p><strong>Source_Code.zip: </strong>Includes the source code needed to translate the measure inputs provided in "Measures_Data.zip" into the outputs provided in "Results_Data.zip". The core set of files required to execute the main analysis results is stored in "Base_Code_Package", while variants to certain files in the core package needed to execute the high renewable sensitivity and high electrification side cases are stored in "Code_Variants". In general, the process of running an analysis is as described in the Scout <a href="https://scout-bto.readthedocs.io/en/latest/quick_start_guide.html">Quick Start Guide</a>; however, the file "ecm_prep_batch.py" should be substituted for "ecm_prep.py" and the file "run_batch.py" should be substituted for "run.py". These batch files execute multiple versions of "ecm_prep.py" and "run.py" that are tailored to generate individual measure and whole portfolio results for annual, net peak summer and winter, and net off-peak summer and winter metrics (individual measures: "ecm_prep.json," "ecm_prep_spa," "ecm_prep_wpa," "ecm_prep_sta," "ecm_prep_wta"; whole portfolio: "ecm_results.json," "ecm_results_spa.json," "ecm_results_wpa.json," and "ecm_results_sta.json," and "ecm_results_wta.json"). Results for the side cases are generated by replacing the versions of the "ecm_prep" and "run" files included in the "Base_Code_Package" folder with those in the "Code_Variants" folder. Sector-level 8760 shapes are generated using the "--sect_shapes" command line option as described <a href="https://scout-bto.readthedocs.io/en/latest/tutorials.html#sector-level-hourly-energy-loads">here</a>. See Scout's <a href="https://scout-bto.readthedocs.io/en/latest/tutorials.html#local-execution-tutorials">Local Execution Tutorials</a> for more details on how to develop Scout inputs and outputs.</p> <p><strong>Supporting_Data.zip: </strong>Includes supplemental data files provided by EIA that describe key inputs and outputs to the <a href="https://www.eia.gov/outlooks/aeo/nems/documentation/archive/pdf/m068(2018).pdf">Electricity Market Module</a> in the AEO 2019 run of the National Energy Modeling System ("EIA EMM Data (AEO 2019)"), as well as raw EnergyPlus outputs that were used to develop the baseline Scout hourly load shape file found in "./Source_Code/Base_Code_Package/supporting_data/tsv_data/tsv_load.json". </p>
openENTRANCE - Case Study 7 - Power-to-Heat Demand Flexibility: Results
<p>In case study 7 of the openENTRANCE project, Plan4EU, an electricity dispatch model for Europe, is soft-linked to the Flexibility Function, an indirect demand response model, via Frigg, a novel framework for integrating realistic demand response in energy system analysis. This modelling setup is applied to analyse the role of power-to-heat demand flexibility (end-consumer demand response and heat storage) in the Danish electricity system of 2050. This dataset contains results as presented in the related project report.</p>
Data from: Prospection of potential actions during visual working memory starts early, is flexible, and predicts behavior.
<p>Raw data (EEG and behavior) reported in the manuscript "Prospection of potential actions in visual working memory starts early, is flexible, and predicts behavior" by Rose Nasrawi, Sage E.P. Boettcher, and Freek van Ede</p>
Flexibility, Alcohol Misuse, and Excitation
ClinicalTrials.gov study NCT06634771. IPD Sharing: YES. Countries: 1. Publications: 32.
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.