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14,580 results for “state”
Which multiband factor should you choose for your resting-state fMRI study? The Emory Multiband Dataset
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A derecho climatology over the United States from 2004 to 2021
<p><em>We develop the high-resolution (4 km and hourly) </em><em>observational derecho and derecho-producing mesoscale convective system (MCS) dataset over the United States east of the Rocky Mountains from </em><em>2004 to 2021 by using a </em><em>MCS </em><em>dataset generated by the Python Flexible Object Tracker </em><em>(PyFLEXTRKR) software, bow echoes detected by a semantic segmentation </em><em>convolutional neural network, gust speed</em><em>s from the Integrated Surface Database and the Storm Events Database, and physically based identification criteria.</em></p>
XAlkeneDB: A database illuminating the electronic ground and excited state quantum chemical features of ethene, propene and butene
<div> <div> <div> <p>The dataset associated with this research has been published in <a href="https://pubs.rsc.org/en/content/articlelanding/2024/sc/d4sc04164j" target="_blank" rel="noopener"> Chem. Sci., 2024,15, 15880-15890.</a> Please cite this journal article when using the data.</p> </div> </div> </div>
Bayesian analysis of the equation of state of quantum chromodynamics from a holographic model
<p>Prior and posterior samples obtained from a Bayesian analysis of the equation of state of quantum chromodynamics (QCD) within a holographic Einstein-Maxwell-Dilaton model, constrained by state-of-the art lattice QCD results at a vanishing net density of baryons.</p> <p>Samples contain metadata, model parameters, and model predictions for the location of the QCD critical point.</p> <p>Supplement to <a title="Bayesian location of the QCD critical point from a holographic perspective" href="https://arxiv.org/abs/2309.00579">arXiv:2309.00579</a>.</p>
White Pine Blister Rust (WPBR) Plot Data from the Western United States
As one of North America’s most damaging tree diseases, white pine blister rust (WPBR) is expected to continue to affect high-elevation five-needle (High-5) pine species in the near future. In order to better understand and estimate the risk it poses to white pines, data was compiled from independent studies across the Western U.S. from 1983-2025. This WPBR disease occurrence data includes nearly 6700 points, which were classified into two epidemic types: established or invading, based on the disease intensity value and the amount of time the disease had been present in the area.
Bridging data silos to holistically model plant macrophenology data, Contiguous United States, 2013-2021
Phenological responses to climate change can have dire implications for ecosystem functions. Despite the availability of diverse datasets (e.g., herbarium specimens, community science initiatives, observatory networks, and remote sensing), holistic modeling of plant events across scales remains limited due to fragmented data and disciplinary silos. This is an important topic that has been overdue for attention. Here we use two different plant phenological datasets, herbarium and USA-NPN (includes NEON), to look at the overall flowering period of Acer rubrum between 2013-2021, distributed across the Contiguous United States. We harmonize the data to demonstrate its use to leverage the spatial and biological organizational scales at which these data are captured. Both datasets include phenophase status (presence or absence) across the flowering season (day of year). These harmonized data exemplify their usefulness to holistically model plant phenology using an integrated species distribution model framework, while accounting for the heterogeneity across data types (presence-only, presence-absence). These data can be used to explore general questions about intraspecific synchrony of Acer rubrum flowering phenology across populations, or questions with coarser scales of interest (e.g., community level, global scales).
Summertime methane and carbon dioxide emission rates and associated variables from a national-scale survey of 146 reservoirs in the United States, 2016-2023
Reservoirs are globally important sources of greenhouse gases, but the magnitude of their emissions is highly uncertain. Here we present data for 146 reservoirs from two surveys of reservoir methane and carbon dioxide emissions, one at the regional scale in the midwestern United States and one at the national scale in the conterminous United States, plus data from one reservoir in Washington and another in Puerto Rico. At all reservoirs, ebullitive and diffusive emissions and basic physiochemistry were measured at 15-70 locations during one 22 to 64-hour period during the summers of 2016-2023, with four reservoirs revisited a second time. Concomitant water chemistry measurements were also made at an index site. The dataset is comprised of two geospatial files and seven .csv files containing greenhouse gas emissions, water chemistry, morphology, and other relevant data. These data comprise the largest multi-reservoir emissions dataset ever assembled using consistent measurement methods.
Net Ecosystem Carbon Balance of Grazing Lands across the continental United States, 2013-2023
Grazing lands underpin U.S. beef production, store roughly one-third of global soil organic carbon, deliver multiple ecosystem services, and are closely tied to the prosperity and resilience of rural communities. In this study, we calculated net ecosystem carbon balance (NECB), the net status of grazing lands as a carbon sink or source, by integrating carbon uptake from photosynthesis, and carbon loss through ecosystem respiration, enteric fermentation and manure from livestock. Our objective was to synthesize multiple years of annual NECB of grazing lands measured by eddy covariance towers from 16 pastures across seven USDA Long-term Agroecosystem Research Network (LTAR) sites and enteric fermentation and manure emissions derived from the stocking rates. We evaluated annual NECB against mean annual precipitation (MAP), mean annual temperature (MAT), vegetation, soil, fire history, grazing pressure index (GPI) and fertilization history. We found: (1) grazing lands were a carbon sink or neutral in most sites, and NECB was not significantly different between grasslands and shrublands, mesic and xeric conditions, and fertilized and unfertilized sites; (2) NECB increased with precipitation and temperature, but decreased with a higher GPI; and (3) precipitation, temperature, and GPI interacted such that temperature had a positive effect when MAP was greater than 700 mm and GPI had a negative effect when MAP was less than 1000 mm. Thus, most grazing lands in our study function as a carbon sink unless coupled with water deficit, low temperature, or heavy grazing. NECB is most sensitive to precipitation when water was limited with high interannual variability. Future work to improve our understanding of NECB on grazing lands should directly measure enteric fermentation and ecosystem emissions in different systems and add measurements on carbon loss through wind erosion and leaching.
Carbon Isotope and Ring Width Measurements from Tree Rings of Selected Canopy Species at Six Sites in the Eastern United States
Forest Water Use Efficiency (WUE) is defined as the ratio of carbon uptake per unit water vapor loss via transpiration. Micrometeorological measurements suggest that forest WUE has dramatically increased over the last two decades, in excess of what would be expected from increases in atmospheric carbon dioxide concentrations. Coinciding with observed trends in forest WUE have been marked decreases in acid deposition throughout much of North America and Europe. There is evidence that acid deposition may impact forest WUE, either by altering the availability of nutrients in forest soils or by directly affecting foliar physiology. Changes in WUE could also lead to changes in stream discharge from forested catchments. The hypothesized response of forests to changing levels of acid deposition is not currently considered in the land surface components of global climate models (GCMs). Since carbon dioxide and water vapor are the two most important greenhouse gases, it is vital to accurately model their land-atmosphere exchange. This research uses a catchment-based approach to investigate the effects of changing acid deposition on forest WUE. Tree ring carbon isotopes reconstruct historical WUE time series within six catchments that have been differentially impacted by acid deposition due to distinctions between their underlying bedrock mineralogy and geological histories. The research also capitalizes on experimental treatments that have altered soil biogeochemistry in paired catchment designs (Bear Brook, ME; Hubbard Brook, NH; and Fernow Experimental Forest, WV). Additional watersheds that vary in underlying bedrock chemistry are also used in this research to examine tree-ring WUE time series as natural experiments along a base-cation gradient. These watersheds include Sleepers River, VT; Hubbard Brook, NH; Cone Pond Watershed, NH; and Shenandoah National Park, VA.
CAP LTER weather stations at Papago Park and Lost Dutchman State Park in the greater Phoenix metropolitan area of central Arizona, USA, ongoing since 2010
The CAP LTER maintains two micrometeorological stations (10-m height) in the greater Phoenix metropolitan area, including at Lost Dutchman State Park and near the Desert Botanical Garden at Papago Park. The local terrain at both sites is flat or gently sloping Sonoran desert, and the vegetation canopy consists of patchy coverage of desert shrubs and trees. The dominant vegetation species include bursage (*Ambrosia deltoidea*) and creosote bush (*Larrea tridentata*), while minor species include palo verde (*Parkinsonia microphylla*) and saguaro cactus (*Carnegiea gigantea*). Wind speed and direction, incoming solar radiation, air temperature, relative humidity, and precipitation have been monitored nearly continuously since the fall of 2010. Each variable is measured every 5 seconds and the average (or total for precipitation and total solar radiation) saved to a data logger every 10 minutes.
Pre-Colonial and Modern Tree Data from Nine Northeastern States 1620-2008
The northeastern United States is a predominately-forested region that, like most of the eastern U.S., has undergone a 400-year history of intense logging, land clearance for agriculture, and natural reforestation. This setting affords the opportunity to address a major ecological question: How similar are today’s forests to those existing prior to European colonization? Working throughout a nine-state region spanning Maine to Pennsylvania, we assembled a comprehensive database of archival land-survey records describing the forests at the time of European colonization. We compared these records to modern forest inventory data and described: (1) the magnitude and attributes of forest compositional change, (2) the geography of change and (3) the relationships between change and environmental factors and historical land use. We found that with few exceptions, notably the American chestnut, the same taxa that made up the pre-colonial forest still comprise the forest today, despite ample opportunities for species invasion and loss. Nonetheless, there have been dramatic shifts in the relative abundance of forest taxa. The magnitude of change is spatially clustered at local scales (less than 125-km) but exhibits little evidence of regional-scale gradients. Compositional change is most strongly associated with the historical extent of agricultural clearing. Throughout the region, there has been a broad ecological shift away from late successional taxa, such as beech and hemlock, in favor of early- and mid-successional taxa, such as red maple and poplar. Additionally, the modern forest composition is more homogeneous and less coupled to local climatic controls.
LAGOS - Predicted and observed maximum depth values for lakes in a 17-state region of the U.S.
This dataset includes predicted and observed values of maximum depth for lakes in the upper Midwest and northeast United States. All observed values came from LAGOS ver 1.040.0 (LAke multi-scaled GeOSpatial and temporal database), an integrated database of lake ecosystems (Soranno et al. 2015). LAGOS contains a complete census of lakes great than or equal to 4 ha with corresponding geospatial information for a 17-state region of the U.S., and a subset of the lakes has observational data on morphometry and chemistry. Approximately 40 different sources of data were compiled for this dataset and were mostly generated by government agencies (state, federal, tribal) and universities. Here, observed maximum depth values (n = 8164) were used to train and validate a predictive mixed effects model for lake depth using terrestrial and lake morphology as predictors (Oliver et al., submitted). Predicted values (n = 50 607) generated by the model had a root mean squared error of 7.1 m. This research was supported by the NSF Macrosystem Biology awards 1065786, 1065818, and 1065649.
LAGOS - Lake nitrogen, phosphorus, stoichiometry, and geospatial data for a 17-state region of the U.S.
This dataset includes information about total nitrogen (TN) concentrations, total phosphorus (TP) concentrations, TN:TP stoichiometry, and 12 driver variables that might predict nutrient concentrations and ratios. All observed values came from LAGOSLIMNO v. 1.054.1 and LAGOSGEO v. 1.03 (LAke multi-scaled GeOSpatial and temporal database), an integrated database of lake ecosystems (Soranno et al. 2015). LAGOS contains a complete census of lakes greater than or equal to 4 ha with corresponding geospatial information for a 17-state region of the U.S., and a subset of the lakes has observational data on morphometry and chemistry. Approximately 54 different sources of data were compiled for this dataset and were mostly generated by government agencies (state, federal, tribal) and universities. Here, we compiled chemistry data from lakes with concurrent observations of TN and TP from the summer stratified season (June 15-September 15) in the most recent 10 years of data included in LAGOSLIMNO v. 1.054.1 (2002-2011). We report the median TN, TP and molar TN:TP values for each lake, which was calculated as the grand median of each yearly median value. We also include data for lake and landscape characteristics that might be important controls on lake nutrients, including: land use (agricultural, pasture, row crop, urban, forest), nitrogen deposition, temperature, precipitation, hydrology (baseflow), maximum depth, and the ratio of lake area to watershed area, which is used to approximate residence time. These data were used to identify drivers of lake nutrient stoichiometry at sub-continental and regional scales (Collins et al, submitted). This research was supported by the NSF Macrosystems Biology program (awards EF-1065786 and EF-1065818) and by the NSF Postdoctoral Research Fellowship in Biology (DBI-1401954).
LAGOS-NE v.1.054.1 - Lake water quality time series and geophysical data from a 17-state region of the United States
Time series of mean summer total nitrogen (TN), total phosphorus (TP), stoichiometry (TN:TP) and chlorophyll values from 2913 unique lakes in the Midwest and Northeast United States. Epilimnetic nutrient and chlorophyll observations were derived from the Lake Multi-Scaled Geospatial and Temporal Database LAGOS-NELIMNO version 1.054.1, and come from 54 disparate data sources. These data were used to assess long-term monotonic changes in water quality from 1990-2013, and the potential drivers of those trends (Oliver et al., submitted). Summer was used to approximate the stratified period, which was defined as June 15 to September 15. The median number of observations per summer for a given lake was 2, but ranged from 1 to 83. The rules for inclusion in the database were that, for a given water quality parameter, a lake must have an observation in each period of 1990-2000 and 2001-2011. Additionally, observations must span at least 5 years. Each unique lake with nutrient or chlorophyll data also has supporting geophysical data, including climate, atmospheric deposition, land use, hydrology, and topography derived at the lake watershed (variable prefix “iws”) and HUC 4 (variable prefix “hu4”) scale. Lake-specific characteristics, such as depth and area, are also reported. The geospatial data came from LAGOS-NEGEO version 1.03. For more specific information on how LAGOS-NE was created, see Soranno et al. 2015. Soranno P.A., Bissell E.G., Cheruvelil K.S., Christel S.T., Collins S.M., Fergus C.E., Filstrup C.T., Lapierre J.-F., Lottig N.R., Oliver S.K., Scott C.E., Smith N.J., Stopyak S., Yuan S., Bremigan M.T., Downing J.A., Gries C., Henry E.N., Skaff N.K., Stanley E.H., Stow C.A., Tan P.-N., Wagner T., and Webster K.E. 2015. Building a multi-scaled geospatial temporal ecology database from disparate data sources: fostering open science and data reuse. Gigascience 4: 28. doi: 10.1186/s13742-015-0067-4.
fMRI: resting state and arithmetic task
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Resting state with closed eyes for patients with depression and healthy participants
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Two sessions of resting state with closed eyes for patients with depression in treatment course (NFB, CBT or No treatment groups)
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Modeling an auditory stimulated brain under altered states of consciousness using the generalized ising model
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United States LEMIS wildlife trade data curated by EcoHealth Alliance
<p>Shared here are United States Fish and Wildlife Service (USFWS) Law Enforcement Management Information System (LEMIS) data on wildlife and wildlife product imports into the United States. This data was obtained via Freedom of Information Act (FOIA) requests by EcoHealth Alliance.</p> <p>Data were curated, cleaned, and made accessible via an R package interface: <a href="https://github.com/ecohealthalliance/lemis">https://github.com/ecohealthalliance/lemis</a>.</p> <p>Additionally, a summary of a portion of the data can be found in Smith et al. 2017, <em>EcoHealth </em>(<a href="https://doi.org/10.1007/s10393-017-1211-7">https://doi.org/10.1007/s10393-017-1211-7</a>).</p> <p>l<strong>emis_2000_2014_cleaned.csv</strong>: This file represents the compiled, cleaned LEMIS data from 2000-2014. This data is identical to the version 1.1.0 dataset available through the <strong>lemis </strong>R package.</p> <p><strong>lemis_codes.csv</strong>: Full values for all coded values used in the LEMIS data. Identical to the output from the <strong>lemis </strong>R package function "lemis_codes()".</p> <p><strong>lemis_metadata.csv</strong>: Data fields and field descriptions for all variables in the LEMIS data. Identical to the output from the <strong>lemis </strong>R package function "lemis_metadata()".</p> <p><strong>raw_data.zip</strong>: This archive contains all of the raw LEMIS data files that are processed and cleaned with the code contained in the 'data-raw' subdirectory of the <strong>lemis </strong>R package repository.</p>
Dataset of "Electronic structure and defect states in bismuth and antimony sulphides identified by energy-resolved electrochemical impedance spectroscopy"
Understanding the nature of the defects in the absorber materials, namely point defects, their formation mechanism and the contribution to the properties is essential for the photovoltaic device performance improvement. They are one the reasons why chalcogenide-based solar cells do not yet meet expected high power conversion efficiencies. Here we identify and present energy distribution of defects in Bi2S3 and Sb2S3, and their (SbxBi(100-x))2S3 alloys (with x = 0, 10, 33, 50, 67, 90, 100 at% Sb content) chalcogenides, being explored for emerging photovoltaic applications as they are earth-abundant and highly absorbing in the visible light range. We show that their density of states (DOS) and related parameters can be obtained experimentally by energy-resolved electrochemical impedance spectroscopy (ER-EIS) in a technically simple and quick way, where ER-EIS data are well correlated with theoretical DFT calculations. ER-EIS reveals that in Bi2S3 there are only shallow defects at CBM. In Sb2S3, ER-EIS reveals also midgap states which can be the cause of low electrical conductivity of Sb2S3. We also explain the discrepancy in the reported values of ionisation potentials and the bandgaps of the Bi- and Sb-chalcogenides. Dominant sulphur vacancy defect was identified in Bi- and Sb-chalcogenides whereas in ternary (SbxBi(100-x))2S3 system, merely 10 at.% of Bi transforms the midgap sulphur defects to shallow ones. This provides novel strategy for healing the midgap defects in Sb2S3, which is crucial for boosting the PV performance and tuning the electrical conductivity in Sb2S3.
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.