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5,530 results for “informal”
Supporting Information: Toward learned chemical perception of force field typing rules
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Hindlimb muscle spindles inform preparatory forelimb coordination prior to landing in toads
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A three-year building operational performance dataset for informing energy efficiency
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McMurdo Sound, Antarctica: Cape Armitage, sponge abundance and cover and photo ID information for 1968 and 2010
In 2010 we had the opportunity to revisit historical transects and experiments set up by Dayton et al. in the 1960s, 70s, and 80s. Using the SCINI ROV we were able to revisit sites we had dived previously, including some deeper sites that are no longer diveable by current United States Antarctic Program policies. Revisiting these sites enabled us to study and document long-term changes in benthic biota at McMurdo Sound, Antarctica. These are data on sponge abundance and percent cover collected in 1968 and 2010. We are making these data available to researchers for future observations of community change in the nearly pristine environment of the Ross Sea, Antarctica.
Permafrost soil database with information on site, topography, geomorphology, hydrology, soil stratigraphy, soil carbon, ground ice isotopes, and vegetation at thermokarst features near Toolik and Noatak River, 2009-2013
This database contains soil and permafrost stratigraphy associated with thermokarst features near Toolik Lake and the Noatak River collected by Torre Jorgenson and Andrew Balser during summers 2009-2011. The Access Database has main data tables (tbl_) for site (environmental), soil stratigraphy, soil physical data, soil chemical data, soil isotopes (ground ice), soil radiocarbon dates, topography and bathymetry, and vegetation cover. The site data includes information of location, observers, geomorphology, topography, hydrology, soil summary characteristics, pH and EC, soil classification, and vegetation cover by species. Soil stratigrapy has information on soil texture and ground ice. Soil physical and chemical data includes lab data on bulk density, moisture, carbon, and nitrogen. The database has 37 reference tables (REF_) that have codes and descriptions for variables used in site, soil stratigraphy, and vegetation cover tables.
Seedling planting information: Interactive Effects of Fertility and Distribution on Plant Community Diversity and Structure
There are four levels of nitrogen, corresponding to treatments A, C, F and G in E001, applied at the same time as in that experiment. For a description of fertilizer added to E052, see file fertilization details. There are four levels of soil disturbance designated 1, 2, 3 and 4. Level 1: undisturbed Level 2: 1 pass with a 7 HP Honda rear-tined rototiller with the elevator set to till to a depth of 9 inches Level 3: 2 passes or however many required to produce about 50% bare ground Level 4: 3 passes or however many required to produce 100% bare ground. This requires 3 passes in some plots but 5 or 6 in others. In addition, all woody vegetation not destroyed by tilling is cut at the base. Rototilling is applied in late April. Each fertilization treatment receives each disturbance treatment, for a total of sixteen treatments. There are four replicates of each of the sixteen treatments. In addition, the four extreme ends (lowest N, lowest disturbance; highest N, lowest disturbance, etc. ) are replicated an additional ten times. Treatments are applied in a completely randomized design. Each of the 104 plots is 5m x 5m. Measurements taken at E052 will include: 1) species abundances, 2) community biomass allocation to leaves/roots/stems/flowers, 3) above and below ground net primary production and 4) rates of nitrogen mineralization. For a list of treatments, see the treatment layouts in file trmte52. The plots in E052 are enclosed by a fence to exclude mammalian herbivores. Galvanized welded-wire hardware cloth with 6mm x 6mm openings was buried to a depth of 50cm. Additional hardware cloth extends 60cm above the ground and poultry netting extends to 2m above the ground. In 1990, ten plots of each of four treatments (N1D1, N1D4, N4D1, N4D4, where N is the level of nitrogen added and D is the disturbance treatment) were randomly selected for the competition experiment. The above and belowground effects of neighbors on transplanted grass seedlings were measured using three
Information Based Behavioural Intervention Study (Guildford case)
<p>iSCAPE Dataset Reference No. = DS_PD_014, DS_PD_019</p> <p>Following datasets are acquired/generated during the implementation of behavioural intervention study in Guildford:</p> <ol> <li>Participant's detailed activity-travel diary </li> <li>Introductory and Followup questionnaire responses</li> </ol>
Supporting Information for "Terrestrial bow shock parameters from MMS measurements: dependence on upstream and downstream time ranges"
<p>Summary plots and parameter tables for each of the 51 shocks analyzed in the statistical study "Terrestrial bow shock parameters from MMS measurements: dependence on upstream and downstream time ranges."</p>
Supporting Information for Synthesis of elaborate benzofuran-2-carboxamide derivatives through a combination of 8-aminoquinoline directed C–H arylations and transamidations.revised
<p>Supporting Information for Synthesis of elaborate benzofuran-2-carboxamide derivatives through a combination of 8-aminoquinoline directed C–H arylations and transamidations.</p>
Supplementary Information to: Increasing the spatial resolution of cloud property retrievals from Meteosat SEVIRI by use of its high–resolution visible channel: Evaluation of candidate approaches with MODIS observations
<p>This repository contains the Python programmes and datasets used for</p> <p>the research described in the following paper:<br> https://doi.org/10.5194/amt-2019-334</p> <p>It has been prepared as supplementary information to the final paper.<br> <br> Note that the actual Cloud Property Retrieval (CPP) which would be<br> required for full reproducability of the results cannot be made<br> available by the authors, that the code included here is based on Python2, and that<br> paths to the dataset have to be adapted in the code.<br> <br> The repository consists of three separate parts/directories:<br> <br> * method: Python routines for generating the cloud property retrieval<br> input based on the Meteosat and MODIS data<br> <br> * analysis: Python routines for analysing the different experiments<br> from the CPP outputs, producing the figures and calculating the<br> comparison statistics<br> <br> * datasets: the various input and output datasets used for the<br> analyses of the paper</p>
Offres d'emploi en Suisse romande dans le domaine de l'information documentaire en 2019
<p>Les données ont été collectées sur Swiss-Lib en 2019. Voir l'onglet documentation du fichier Excel pour plus d'informations.</p>
MOTIVE - tiMe-OpTimized contextual Information flow on unmanned VEhicles project experimental results
<p>The experimentation data were collected during the 6th Fed4FIRE+ Open Call (https://www.fed4fire.eu/) using the mobile nodes of the w-iLab.t (link) testbed. During this Open Call we proposed to evaluate the performance of an optimization model for temporal control of the transmission of messages from an IoT mobile device. This mechanism is based on a network condition model that transits from favourable to adverse conditions and vice versa. All these transitions are monitored and validated through our system (change detection and optimal stopping). If a network is performing properly then the transmission control can be relaxed to exploit available resources.The main contribution of MOTIVE is to apply a sequential decision-making process (DMP) on IoT devices that leverages the on-line derived network statistics to efficiently control their telemetry measurements transmission.</p> <p>Our data collected from the experimentation using the testbed's devices consists of network related information, packet error rate and latency. We collected data from a completely functional mobile node that operates in a saturated network and five mobile nodes in the same circumstances. Saturated conditions were generated by data produced by twenty static sensors for the duration of the each experiment. On each run we collected more than 2 * 105 samples. The comparative assessment we did was based on five different policies of decision making: i) no-policy model, ii) the heuristic threshold based model in which the transmission of the messages is paused when a specific threshold of quality network is below a threshold, iii) TOCP model which overviews the quality of network in normal mode and gets in pausing mode when a change is detected; the pausing period lasts for a specific threshold and then it is activated again, iv) TOCP-DRP and the v) fair TOCP-DRP which enters in pausing mode if a change is indicated by TOCP decision making model.</p> <p>The datasets include the packet error rate and the latency of each device, for each experiment, and the critical areas found during the experiments (most saturated areas).</p> <p>The datatset includes for each scenario(experiment) the participating devices and the Latency and Packet Error Rate(PER) per policy( NoPolicy, Heuristic, TOCP, TOCPDRP, TOCPDRPFAIR), apart from scenarioA(single node) where only four policies are present, since the TOCPDRPFAIR applies with more that one participating nodes.</p>
Figs. 1–2. Macrosiphum glawatz. 1 in New Macrosiphum Passerini (Hemiptera: Aphididae) Information From Western North America, Including One New Species And One New Synonymy
Figs. 1–2. Macrosiphum glawatz. 1, Head capsule and antennal segments I of aptera, dorsum. 2, Head capsule and antennal segments I of aptera, ventral surface.
Figs. 17–20. Macrosiphum mentzeliae. 17, Aptera a.s. III. 18, Alata a.s. III. 19 in New Macrosiphum Passerini (Hemiptera: Aphididae) Information From Western North America, Including One New Species And One New Synonymy
Figs. 17–20. Macrosiphum mentzeliae. 17, Aptera a.s. III. 18, Alata a.s. III. 19, Siphunculus of aptera. 20, Siphunculus of alata.
Figs. 5–8. Macrosiphum glawatz. 5, Aptera a.s. III. 6, Alata a.s. III. 7 in New Macrosiphum Passerini (Hemiptera: Aphididae) Information From Western North America, Including One New Species And One New Synonymy
Figs. 5–8. Macrosiphum glawatz. 5, Aptera a.s. III. 6, Alata a.s. III. 7, Siphunculus of aptera. 8, Siphunculus of alata.
Figs. 15–16. Macrosiphum mentzeliae. 15 in New Macrosiphum Passerini (Hemiptera: Aphididae) Information From Western North America, Including One New Species And One New Synonymy
Figs. 15–16. Macrosiphum mentzeliae. 15, Head capsule and antennal segments I of alata, dorsum. 16, Head capsule and antennal segments I of alata, ventral surface.
Process Mining from Information-Seeking Conversations
<p>Synthetic dataset and event logs for the paper 'Process Mining from Information-Seeking Conversations' submitted to WCCI 2020. </p>
Supplementary material 2 from: Chapman AD, Belbin L, Zermoglio PF, Wieczorek J, Morris PJ, Nicholls M, Rees ER, Veiga AK, Thompson A, Saraiva AM, James SA, Gendreau C, Benson A, Schigel D (2020) Developing Standards for Improved Data Quality and for Selecting Fit for Use Biodiversity Data. Biodiversity Information Science and Standards 4: e50889. https://doi.org/10.3897/biss.4.50889
Use cases were collected using a number of methods to maximise responses. Lead authors of papers published using data accessed via the Atlas of Living Australia (ALA) were contacted and asked to contribute their research data use cases, and a number of papers describing fitness for use determination were sent to the ALA Data Quality group. Fitness for use and quality check information from these papers were extracted and transferred to the use case library. These are the results of those surveys.
Supplementary material 4 from: Chapman AD, Belbin L, Zermoglio PF, Wieczorek J, Morris PJ, Nicholls M, Rees ER, Veiga AK, Thompson A, Saraiva AM, James SA, Gendreau C, Benson A, Schigel D (2020) Developing Standards for Improved Data Quality and for Selecting Fit for Use Biodiversity Data. Biodiversity Information Science and Standards 4: e50889. https://doi.org/10.3897/biss.4.50889
Description and specifications for the tests following the conventions of the Fitness For Use Framework. This supplement is a copy of https://github.com/tdwg/bdq/blob/master/tg2/core/TG2_tests.csv as of commit 941e774 2019-Aug-20.
Supplementary material 3 from: Chapman AD, Belbin L, Zermoglio PF, Wieczorek J, Morris PJ, Nicholls M, Rees ER, Veiga AK, Thompson A, Saraiva AM, James SA, Gendreau C, Benson A, Schigel D (2020) Developing Standards for Improved Data Quality and for Selecting Fit for Use Biodiversity Data. Biodiversity Information Science and Standards 4: e50889. https://doi.org/10.3897/biss.4.50889
Counts of occurrence records in 2019-04-15 snapshot of GBIF-mediated data that fit the three categories of expected responses for each of the event date-related validation tests.
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.