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7,195 results for “SET”
The current and future distribution of the yellow fever mosquito (Aedes aegypti) on Madeira Island [data set].
<p><strong>Additional data for manuscript:</strong> "The current and future distribution of the yellow fever mosquito (<em>Aedes aegypti</em>) on Madeira Island" published in PLOS Neglected Tropical Diseases by José Maurício Santos, César Capinha, Jorge Rocha, Carla Alexandra Sousa.</p> <p><strong>Corresponding authors:</strong> José Maurício Santos (josemauriciosantos@campus.ul.pt) & César Capinha (cesarcapinha@campus.ul.pt).</p> <p> </p> <p> </p> <p> </p>
Data set for "1/f Noise Characterization of Bilayer MoS2 Field-Effect Transistors on Paper with Inkjet-Printed Contacts and hBN Dielectrics"
<p>Data set of the experimental results presented in the article "1/f Noise Characterization of Bilayer MoS2 Field-Effect Transistors on Paper with Inkjet-Printed Contacts and hBN Dielectrics" published in Advanced Electronics Materials.</p>
Data set for "Inkjet-printed low-dimensional materials-based complementary electronic circuits on paper"
<p>Data set of the experimental results presented in the article "Inkjet-printed low-dimensional materials-based complementary electronic circuits on paper" published in npj-2D Materials and applications.</p>
Data: set for "Low-voltage 2D materials-based printed field-effect transistors for integrated digital and analog electronics on paper"
<p>The file reports the raw data of Figure 2, Figure 3 and Figure 4 of the manuscript. Data shown in Figure 2 represent the electrical characterization of the MoS<sub>2</sub> FETs with inkjet-printed silver contacts. Figure 2a is a typical transfer characteristic measured as a function of the gate voltage for a drain voltage of 2.0 V; Figure 2b is a typical output characteristic measured at different gate voltages (from V<sub>GS</sub> = 0.0 V to V<sub>GS</sub> = 1.75 V, steps of 0.25 V). Figure 3 represents the electrical characterization of the MoS<sub>2</sub> FETs with inkjet-printed graphene contacts. In particular, a typical transfer characteristic curve measured as a function of the gate voltage for a drain voltage of 2.5 V is shown and a typical output characteristic curves measured at increasing gate voltages (from V<sub>GS</sub> = 0.0 V to V<sub>GS</sub> = 1.75 V, steps of 0.25 V) are reported in Figure 3b and Figure 3c, respectively. Logic gates and current mirror based on MoS2 FETs with inkjet-printed silver contact are presented in Figure 4. Figure 4c shows the output voltage (left axis) and the voltage gain (right axis) of the inverter gate as a function of the input voltage; Figure 4f the output voltage of the NAND gate as a function of the input states (V<sub>IN1</sub>, V<sub>IN2</sub>). Voltage bias is 5 V for both the inverter and the NAND gate; and Figure 4i g the output current of the current mirror as a function of the output voltage for two different values of the reference current.The file reports the raw data of Figure 2, Figure 3 and Figure 4 of the manuscript. Data shown in Figure 2 represent the electrical characterization of the MoS<sub>2</sub> FETs with inkjet-printed silver contacts. Figure 2a is a typical transfer characteristic measured as a function of the gate voltage for a drain voltage of 2.0 V; Figure 2b is a typical output characteristic measured at different gate voltages (from V<sub>GS</sub> = 0.0 V to V<sub>GS</sub> = 1.75 V, steps of 0.25 V). Figure 3 represents the electrical characterization of the MoS<sub>2</sub> FETs with inkjet-printed graphene contacts. In particular, a typical transfer characteristic curve measured as a function of the gate voltage for a drain voltage of 2.5 V is shown and a typical output characteristic curves measured at increasing gate voltages (from V<sub>GS</sub> = 0.0 V to V<sub>GS</sub> = 1.75 V, steps of 0.25 V) are reported in Figure 3b and Figure 3c, respectively. Logic gates and current mirror based on MoS2 FETs with inkjet-printed silver contact are presented in Figure 4. Figure 4c shows the output voltage (left axis) and the voltage gain (right axis) of the inverter gate as a function of the input voltage; Figure 4f the output voltage of the NAND gate as a function of the input states (V<sub>IN1</sub>, V<sub>IN2</sub>). Voltage bias is 5 V for both the inverter and the NAND gate; and Figure 4i g the output current of the current mirror as a function of the output voltage for two different values of the reference current.</p>
Data set of 1D model runs, CTRL and ICE runs, associated with "Underestimation of oceanic carbon uptake in the Arctic Ocean: Ice melt as predictor of the sea ice carbon pump"
<p>Dataset of one-dimensional runs for investigation on the sea ice carbon pump. Associated with Sect. 3.1 and 4.1 of manuscript "Underestimation of oceanic carbon uptake in the Arctic Ocean: Ice melt as predictor of the sea ice carbon pump".</p>
Antipredator behaviors in urban settings: Ecological experimentation powered by citizen science
<p><span>1. Animal behaviors are often modified in urban settings due to changes in species assemblages and interactions. The ability of prey to respond to a predator is a critical behavior, but </span><span>urban populations may experience altered predation pressure, food supplementation, and other human-mediated disturbances that modify their responsiveness to predation risk and promote habituation.</span></p> <p><span>2. Citizen-science programs generally focus on the collection and analysis of observational data (e.g., bird checklists), but there has been increasing interest in the engagement of citizen scientists for ecological experimentation.</span></p> <p><span>3. Our goal was to implement a behavioral experiment in which citizen scientists recorded antipredator behaviors in wild birds occupying urban areas. In North America, increasing populations of Accipiter hawks have colonized suburban and urban areas and regularly prey upon birds that frequent backyard bird feeders. This scenario, of an increasingly common avian predator hunting birds near human dwellings, offers a unique opportunity to characterize antipredator behaviors within urban passerines. </span></p> <p><span>4. For two winters, we engaged citizen scientists in Chicago, IL, USA to deploy a playback experiment and record antipredator behaviors in backyard birds. If backyard birds maintained their antipredator behaviors, we hypothesized that birds would decrease foraging behaviors and increase vigilance in response to a predator cue (hawk playback) but that these responses would be mediated by flock size, presence of sentinel species, body size, tree cover, and amount of surrounding urban area. </span></p> <p><span>5. Using a randomized control–treatment design, citizen scientists at 15 sites recorded behaviors from 3,891 individual birds representing 22 species. Birds were more vigilant and foraged less during the playback of a hawk call, and these responses were strongest for individuals within larger flocks and weakest in larger-bodied birds. We did not find effects of sentinel species, tree cover, or urbanization. </span></p> <p><span>6. By deploying a behavioral experiment, we found that backyard birds inhabiting urban landscapes largely maintained antipredator behaviors of increased vigilance and decreased foraging in response to predator cues. Experimentation in citizen science poses challenges (e.g., observation bias, sample size limitations, reduced complexity in protocol design), but unlike programs focused solely on observational data, experimentation allows researchers to disentangle the complex factors underlying animal behavior and species interactions. </span></p>
Quantitative 3D OPT and LSFM datasets of pancreata from mice with streptozotocin-induced diabetes: Sample data sets
<p><span>Mouse models for streptozotocin (STZ) induced diabetes probably represent the most widely used systems for preclinical diabetes research, owing to the compound's toxic effect on pancreatic ß-cells. However, a comprehensive view of pancreatic β-cell mass distribution subject to STZ administration is lacking. Previous assessments have largely relied on the extrapolation of stereological sections, which provide limited 3D-spatial and quantitative information. This data descriptor presents multiple ex vivo tomographic optical image data sets of the full β-cell mass distribution in mice subject to single high and multiple low doses of STZ administration, and in glycaemia recovered mice. The data further include information about structural features, such as individual islet β-cell volumes, spatial coordinates, and shape as well as signal intensities for both insulin and GLUT2. Together, they provide the most comprehensive anatomical record of the effects of STZ administration on the islet of Langerhans in mice. As such, this data descriptor may serve as reference material to facilitate the planning, use and (re)interpretation of this widely used disease model.</span></p>
A mule deer's movements in the summer of 2016 in Wyoming, USA, and a set of associated environmental layers
<p>These are the data associated with the paper "Defining Null Expectations for Animal Site Fidelity" by Picardi et al. The file muledeer_summer2016.rds is a data frame containing GPS tracking data for one individual mule deer during the summer of 2016 in Wyoming, USA. The file env_stack_issa.tiff is a raster stack containing environmental layers for the landscape where the mule deer was located. The layers in the stack are, in order: distance to roads (meters), distance to streams, rivers, or water bodies (meters), elevation (meters), slope (degrees), aspect (), topographic position index, terrain ruggedness index, roughness, percent tree cover, and forage biomass. </p>
Bumblebees retrieve only the ordinal ranking of foraging options when comparing memories obtained in distinct settings
<p><span>Are animals' preferences determined by absolute memories for options (e.g. reward sizes) or by their remembered ranking (better/worse)? The only studies examining this question suggest humans and starlings utilise memories for both absolute and relative information. We show that bumblebees' learned preferences are based only on memories of ordinal comparisons. A series of experiments showed that after learning to discriminate pairs of different flowers by sucrose concentration, bumblebees preferred flowers (in novel pairings) with 1) higher ranking over equal absolute reward, 2) higher ranking over higher absolute reward, and 3) identical qualitative ranking but different quantitative ranking equally. Bumblebees used absolute information in order to rank different flowers. However, additional experiments revealed that, even when ranking information was absent (i.e. bees learned one flower at a time), memories for absolute information were lost or could no longer be retrieved after at most one hour. Our results illuminate a divergent mechanism for bees (compared to starlings and humans) of learned preferences that may have arisen from different adaptations to their natural environment.</span></p>
Formatted Public GWAS Summary Statistics for 16 Traits and LD pruned SNP sets
<p>This data set includes 16 files with formatted GWAS summary statistic and a csv file gwas_info.csv. The csv provides the original download link and publication for each study. The data in this repository were created by downloading raw summary statistics for each study and processing them using Joe Marcus' GWAS pipeline (https://github.com/jhmarcus/gwass). The resulting data set have consistent allele orientation and column headers making them convenient for analysis. We use them in an MR analysis of pairs of GWAS traits described in Section 2.3 of Morrison et al (2019) (https://www.biorxiv.org/content/10.1101/682237v3) and here https://jean997.github.io/cause/gwas_pairs.html.</p> <p>New Sep 2022: I have added LD pruned SNP sets for each pair of traits.For each exposure/outcome pair, the set of snps in</p> <p>snps_<exposure>__<outcome>.txt</p> <p>were generated by LD pruning using LD estimated using LD Shrink (available https://zenodo.org/record/1464357/) at a threshold of r^2 < 0.1. LD pruning was performed using the ld_prune function in the cause R package (github.com/jean997/cause). These are the SNP sets used in the analysis in the paper</p>
Data set associated with a research on nephrotoxicity of gasoline fumes in male albino rat: A mechanism-based approach study
<p>Few studies have reported nephrotoxicity of gasoline fumes in animals, but none of the findings has been fully ascertained and the mechanism underlying the observed toxicity still remains unknown. In this study, we present insights into the potential mechanism underlying the nephrotoxicity of gasoline fumes in 72 adult male albino rats. This study showed for the first time that accumulation of gasoline residues and metabolites in the kidney of exposed animal could potentially result in the generation of ROS capable of inducing renal dysfunction. The dataset uploaded are associated with this study. </p>
WhichDog: A crowdsourced dataset including candidate set-based labelling
<p>A dataset with crowdsourced labels for aggregation and supervised classification.<br> It contains 400 images of dogs from the Stanford Dogs dataset (http://vision.stanford.edu/aditya86/ImageNetDogs/). Images of dogs that belong to 32 different breeds (classes) are included. Annotators were asked to provide two types of labelling: full labelling (each labeler is allowed to provide a single label for each image) and candidate labelling (each labeler is allowed to provide a set of candidate labels for each image). It includes a total of 61227 annotations (30628 full and 30599 candidate) obtained from a set of 1028 different labelers.</p> <p>The labels were collected through the online crowdsourcing platform Amazon mTurk thanks to funds provided by the Basque Government through the Elkartek program (KK-2018/00071). The assignments were designed as sequences of 64 images that were given to the annotators. Each image in the sequence was provided together with a specific subset of possible labels (with the number of options ranging from 4 to 32), and a instruction for the annotator to perform a specific type of labelling (full or candidate). Each labeler performed at least one assignment. Not all the labelers completed the 64 annotations in their assignments.<br> <br> The file 'whichdog.zip' contains a folder ('images') with the 400 images of dogs, a text file ('breed_names.txt') that indicates the names of the different breeds and their assigned label (a number in the interval from 0 to 31) and a CSV file ('whichdog_all_annots.csv') that contains the information about the annotations. Each row of the CSV file represents a single annotation, and each column shows:<br> - image_id: ID number of the image.<br> - is_candidate: indicates whether the requested labelling is full (0) or candidate (1).<br> - labeler_id: ID number of the labeler.<br> - time: time employed by the labeler to perform the annotation.<br> - answer: label or set of labels provided by the labeler as annotation.<br> - options: subset of possible labels shown to the labeler.<br> - assignment_id: ID number of the assignment<br> - sequence_point: number that indicates the point of the sequence of images of the assignment in which the annotation was provided.<br> - class: ground truth label of the image.</p>
The OpenMRG data set
<p><strong>Overview</strong></p> <p>Data for the article "OpenMRG: Open data from Microwave links, Radar, and Gauges for rainfall quantification in Gothenburg, Sweden" (Andersson et al. 2022, Earth Syst. Sci. Data, 14, 5411–5426, <a href="https://doi.org/10.5194/essd-14-5411-2022">https://doi.org/10.5194/essd-14-5411-2022</a>)</p> <p>OpenMRG consists of data from 364 bi-directional commercial microwave links (CML, 10s resolution, true coordinates), one C-band radar composite, and 11 rainfall gauges covering Gothenburg, Sweden during June-August 2015. More details on the data structure and files the are provided in readme.txt. </p> <p>We acknowledge the indispensable support for this work by Hi3G Access AB (providing access to the CML network), Göteborgs Stad – Kretslopp och Vatten (providing the City network data), Ericsson AB (gathering CML data), and the Swedish Meteorological and Hydrological Institute (providing the SMHI gauge and radar data). We also thank Lei Bao, Anna Jacobsson, Christina Larsson, Mohamed Mustafa, Mikael Riedel, Johan Selin, Victor Näslund, and Johan Thuresson for valuable technical contributions and discussion.</p> <p>This work was carried out in the context of the projects MEMO (financed by Vinnova, dnr: 2017-03297), FutureCityFlow (financed by Vinnova, dnr: 2019-04701), and Urban skyfallsinformation (financed by the Swedish Ministry of the Environment and Energy, grant 1:10 for climate adaptation).</p> <p><strong>Versions</strong></p> <p>1.1: revised data set pertaining to the ESSD article by Andersson et al. 2022 (<a href="https://doi.org/10.5194/essd-14-5411-2022">https://doi.org/10.5194/essd-14-5411-2022</a>). These revisions were made on recommendation by the reviewers and include changing variable names and adding more variables to the data set. <br> 1.0: Initial data set, used in ESSD preprint.</p>
Classification Data set : Land Cover Classification with Gaussian Processes using spatio-spectro-temporal features
<p>Classification data set (train, validation, test) from the study area based on 27 tiles on the south of the France. Data set are provided for each eco-climatic region. The size corresponds to the data set DS-A. Only one random pixel sampling is provided: seed 0. This data set was used to train Gaussian Processes, Random Forest, Multilayer Perceptron and Lightweight Temporal Self-Attention models.</p> <p>For further details see section VI-A-1 of the pre-print article "Land Cover Classification with Gaussian Processes using spatio-spectro-temporal features ". This article is available <a href="https://hal.archives-ouvertes.fr/hal-03781332">here</a>.</p> <p>The implementation of the models is available in the <a href="https://gitlab.cesbio.omp.eu/belletv/land_cover_southfrance_gp">open source repository</a>.</p>
IG receptor germline set for species: Mouse subgroup: A/J set_name: A/J IGLV
<p>Germline Reference set published on the Open Germline Receptor Database (OGRDB)</p>
IG receptor germline set for species: Mouse subgroup: 129S1/SvImJ set_name: 129S1/SvImJ IGKV
<p>IG Germline Reference set published on the Open Germline Receptor Database (OGRDB)</p>
IG receptor germline set for species: Mouse subgroup: C3H/HeJ set_name: C3H/HeJ IGKV
<p>Germline Reference set published on the Open Germline Receptor Database (OGRDB)</p>
IG receptor germline set for species: Mouse subgroup: BALB/c set_name: BALB/c IGH
<p>Germline Reference set published on the Open Germline Receptor Database (OGRDB)</p>
IG receptor germline set for species: Mouse subgroup: AKR/J set_name: AKR/J IGKV
<p>Germline Reference set published on the Open Germline Receptor Database (OGRDB)</p>
IG receptor germline set for species: Mouse subgroup: AKR/J set_name: AKR/J IGLV
<p>Germline Reference set published on the Open Germline Receptor Database (OGRDB)</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.