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6,335 results for “direct”
Dung beetles drive direct and indirect changes in ecosystem multifunctionality
<p>This project was funded by the Australian Department of Agriculture, Water and the Environment and Meat and Livestock Australia through Research through the Dung Beetles as Ecosystem Engineers (DBEE) research programme (2018–2022) managed by Charles Sturt University (grant agreement no: RnD4Profit-16-03-016). </p>
Suplementary Material for Direct hydrodynamic measurements at the upper shoreface of a sandy beach in Paraná - Brazil
<p>ADCP data accompanying the manuscript entitled "Direct hydrodynamic measurements at the upper shoreface of a sandy beach in Paraná - Brazil" to be published in Ocean and Coastal Research<strong> (</strong>ISSN (<em>online</em>): 2675-2824)</p>
[Data] Real-time monitoring and quality assurance for laser-based directed energy deposition: integrating co-axial imaging and self-supervised deep learning framework
<p>The experimental setup utilized a co-axial color Charged Couple Device (CCD) camera, integrated into the laser deposition head. This camera operates at a frame rate of 30 frames per second and captures the morphology of the process area. The captured images consist of three RGB channels with a 640 × 480 pixels resolution. To enable the camera to capture the radiation from the process zone, a beam splitter is installed on Precitec's laser applicator head. An optical notch filter within the 650–675 nm range also blocks the laser wavelengths.</p> <p>The dataset consists of four categories that covers the process map of DED process [.rar file].<br>The dataset consist of around 48,000 images that are labelled into 4 categories [P1-P2-P3-P4]. The images correspond to DED process zone captured co-axially<br>The categories are function of linear laser energy deposited. The folder is already split into Train and Test.</p>
Point in the Right Direction
Puerta de Europa, Philip Johnson, 2006 ; Antwerp Port House, Zaha Hadid, 2016; Faculty of History at Cambridge, James Stirling, 1968 Source: Objaverse 1.0 / Sketchfab
Data for: Direct measurement of dynamic attractant gradients reveals breakdown of the Patlak-Keller-Segel chemotaxis model
<p>Chemotactic bacteria not only navigate chemical gradients but also shape their environments by consuming and secreting attractants. Investigating how these processes influence the dynamics of bacterial populations has been challenging because of a lack of experimental methods for measuring spatial profiles of chemoattractants in real-time. Here, we use a fluorescent sensor for aspartate to directly measure bacterially generated chemoattractant gradients during collective migration. Our measurements show that the standard Patlak-Keller-Segel model for collective chemotactic bacterial migration breaks down at high cell densities. To address this, we propose modifications to the model that consider the impact of cell density on bacterial chemotaxis and attractant consumption. With these changes, the model explains our experimental data across all cell densities, offering new insight into chemotactic dynamics. Our findings highlight the significance of considering cell density effects on bacterial behavior and the potential for fluorescent metabolite sensors to shed light on the complex emergent dynamics of bacterial communities.</p>
Data from: Direct propylene epoxidation via water activation over Pd-Pt electrocatalysts
<p>Direct electrochemical propylene epoxidation using water oxidation intermediates presents a sustainable alternative to existing routes that involve hazardous chlorine or peroxide reagents. Here we report an oxidized palladium-platinum alloy catalyst (PdPtO<sub>x</sub>/C), which reaches a Faradaic efficiency of 66±5% toward propylene epoxidation at 50 mA/cm<sup>2</sup> at ambient temperature and pressure. Embedding platinum into the palladium oxide crystal structure stabilized oxidized platinum species, resulting in improved catalyst performance. The reaction kinetics suggest that epoxidation on PdPtO<sub>x</sub>/C proceeds through electrophilic attack by metal-bound peroxo (OO*) intermediates. This work demonstrates an effective strategy for selective electrochemical oxygen-atom transfer from water, without mediators, for diverse oxygenation reactions.</p>
Data from: Sampling origins and directions affect the minimum sampling area in forest plots
<p><span>The minimum sampling area (or minimum area), representing the smallest space </span>that reflects the species composition and characteristics of a plant community, is estimated using species-area relationships (SARs) for designing and managing biodiversity conservation. However, the sampling design's effect on the determination of the minimum area has rarely been systematically evaluated. In this study, we used tree census data from three forest dynamic plots of 25–60 ha in different climatic zones in China to calculate the minimum areas of woody plants in the plots and analyze the effects of species richness and topographic heterogeneity on the areas by changing sampling origins and directions. Our findings reveal that the estimated size of the minimum areas varied significantly with sampling origins and directions, with a difference of approximately 1.5–2 times in forest plots. Topographic heterogeneity affected the minimum area through changes in species composition, while species richness had only a weak impact. These results suggest the importance of considering the sampling origin and direction design when utilizing SARs to estimate the minimum area and species diversity in plant communities, which contributes to a better understanding of vegetation characteristics and the minimum area required for censuses in heterogeneous habitats.</p>
Movies associated with "Direct N-body simulations of satellite formation around small asteroids: insights from DART's encounter with the Didymos system"
<pre>All movies are titled based on the figure in the paper they correspond to and the ID number of the simulation. All movies, except for movie_fig1_fig2_spinup.mp4 are rendered in a rotating, primary-centered frame with a period of 10 hours. This is done to make it easier to watch the satellite accumulate. movie_fig1_fig2_spinup.mp4 is rendered in an inertial frame. The movies are quite long, so we recommend fast-forwarding some of the boring parts :)</pre>
Labelled dataset to classify direct deforestation drivers in Cameroon
<p><strong>Overview</strong></p> <p>This dataset includes the images (visible bands for Landsat-8 or NICFI PlanetScope), auxiliary data (infrared, NCEP, forest gain, OpenStreetMap, SRTM, GFW), and data about forest loss (Global Forest Change) used to train, validate and test a model to classify direct deforestation drivers in Cameroon. </p> <p><strong>Description of the files</strong></p> <ul> <li>'my_examples_landsat_final_detailed.zip': Landsat-8 images, auxiliary data and forest loss data used to train, validate and test a model for a detailed classification of deforestation drivers in Cameroon (15 classes: ‘Oil palm plantation’, ‘Timber plantation’, ‘Fruit plantation (e.g. banana)’, ‘Rubber plantation’, ‘Other large-scale plantation (e.g. tea, sugarcane)’, ‘Grassland/Shrubland’, ‘Small-scale oil palm plantation’, ‘Small-scale maize plantation’, ‘Other small-scale agriculture’, ‘Mining’, ‘Selective logging’, ‘Infrastructure’, ‘Wildfire’, ‘Hunting’, ‘Other’)</li> <li>'my_examples_planet_final_detailed.zip': NICFI PlanetScope images, auxiliary data and forest loss data used to train, validate and test a model for a detailed classification of deforestation drivers in Cameroon (15 classes)</li> <li>'my_examples_landsat_final.zip': Landsat-8 images, auxiliary data and forest loss data used to train, validate and test a model for a classification of deforestation drivers by groups in Cameroon (4 classes: 'Plantation', 'Grassland/Shrubland', 'Smallholder agriculture', 'Other')</li> <li>'my_examples_planet_final.zip': NICFI PlanetScope images, auxiliary data and forest loss data used to train, validate and test a model for a classification of deforestation drivers by groups in Cameroon (4 classes)</li> <li>'my_examples_landsat_detailed_timeseries.zip': Landsat-8 images, auxiliary data and forest loss data used to test a model for a detailed classification of deforestation drivers in Cameroon (15 classes) using multiple images and a time series analysis </li> <li>'my_examples_planet_detailed_timeseries.zip': NICFI PlanetScope images, auxiliary data and forest loss data used to test a model for a detailed classification of deforestation drivers in Cameroon (15 classes) using multiple images and a time series analysis</li> <li> <p>‘labels.zip’: in csv files, the labels for each image in each folder described above (image identified by folder and coordinates or ‘path’) and matches the format of the csv files used as inputs to train, validate and test our classification model</p> <p>For ‘labels.zip’, we have subfolders for Landsat and PlanetScope. Then, for each type of imagery, we have subfolders for ‘detailed’, ‘groups’ and ‘time series’ which correspond to the different ‘my_examples’ folders listed above. </p> <p>For each folder, subfolders named with the coordinates of the centre of the images contain each:<br>• A folder ‘images’, with a sub-folder ‘visible’ containing the PNG RGB image; and a sub-folder ‘infrared’ containing the infrared bands in a NPY file.<br>• A folder ‘auxiliary’ with topographic and forest gain information in a NPY format, OpenStreetMap and peat data in a JSON format, and a sub-folder ‘ncep’ containing all data from NCEP in a NPY format.<br>• The forest loss pickle file delimiting the area of forest loss.</p> </li> </ul> <p><strong>Details about the images</strong></p> <ul> <li> <p>For Landsat-8 data (courtesy of the U.S. Geological Survey), this dataset contains 332x 332 pixels RGB calibrated top-of-atmosphere (TOA) reflectance images pan-sharpened to a 15 m resolution (less than 20% cloud cover)</p> </li> <li> <p>For NICFI PlanetScope data (catalog owner: Planet), this dataset contains 332x 332 pixels monthly RGB composite with a 4.77 m resolution</p> </li> </ul> <p><strong>Details about the auxiliary data</strong></p> <ul> <li>Forest gain from GFC: 30-m resolution, yearly data for 2000-2021, downloaded via Google Earth Engine</li> <li>Near infrared, shortwave infrared 1 and 2 bands from Landsat-8 TOA: 30-m resolution, data every 16 days for 2013-2023, downloaded via Google Earth Engine and selected using the same process as for Landsat-8 RGB images</li> <li> From NCEP Climate Forecast System Version 2 (CFSv2) 6-hourly Products: surface level albedo and volumetric soil moisture content (depths: 0.1 m, 0.4 m, 1.0 m, 2.0m) in 0.01%; radiative fluxes (clear-sky longwave flux downward and upward, clear-sky solar flux downward and upward, direct evaporation from bare soil, longwave and shortwave radiation flux downward and upward, latent, ground and sensible heat net flux), potential evaporation rate, and sublimation in W/m²; humidity (specific, maximum specific, minimum specific) in 10-4 kg/kg; ground level precipitation in 0.1 mm; air pressure at surface level in 10 Pa; wind level (u and v component) in 0.01 m/s, water runoff at surface level in 232.01 kg/ m²; temperature in K: 22264-m resolution, available four times a day for 2011-2023, downloaded directly from the NOAA website and selected the mean of the monthly mean over 5 years before the forest loss event, the monthly maximum over 5 years before the forest loss event, and the monthly minimum over 5 years before the forest loss event for each parameter</li> <li>Closest street and closest city from OpenStreetMap in km: directly downloaded with the Nominatim API</li> <li>Altitude in m, slope and aspect in 0.01° from Shuttle Radar Topography Mission (SRTM): 30-m resolution, measured for 2000, downloaded via Google Earth Engine</li> <li>Presence of peat from GFW: 232-m resolution, measured for 2017, directly downloaded on the GFW website</li> </ul> <p><strong>Details about Global Forest Change</strong></p> <p>For each image, there is a corresponding 'forest_loss_region' .pkl file delimiting a forest loss region polygon from Global Forest Change (GFC). GFC consists of annual maps of forest cover loss with a 30-m resolution. </p> <p><strong>License</strong></p> <p>The NICFI PlanetScope images fall under the same license as the <a href="https://assets.planet.com/docs/Planet_ParticipantLicenseAgreement_NICFI.pdf">NICFI data program license agreement</a> (data in 'my_examples_planet_final.zip', 'my_examples_planet_final_detailed.zip', 'my_examples_planet_detailed_timeseries.zip': subfolders '[coordinates]'>'images'>'visible'). </p> <p><a href="https://wiki.osmfoundation.org/wiki/Licence/Attribution_Guidelines">OpenStreetMap®</a> is open data, licensed under the <a href="https://opendatacommons.org/licenses/odbl/1-0/">Open Data Commons Open Database License (ODbL)</a> by the OpenStreetMap Foundation (OSMF) (data in all 'my_examples' folders: subfolders '[coordinates]'>'auxiliary'>'closest_city.json'/'closest_street.json'). The documentation is licensed under the <a href="https://creativecommons.org/licenses/by-sa/2.0/">Creative Commons Attribution-ShareAlike 2.0 license (CC BY-SA 2.0)</a>.</p> <p>The rest of the data is under a <a href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a>. The data has been transformed following the code that can be found via this link: <a href="https://github.com/aedebus/Cam-ForestNet">https://github.com/aedebus/Cam-ForestNet</a> (in 'prepare_files').</p> <p> </p>
Compressed raw videos for Directed droplet motion along thin fibers
<p>Compressed video of experiments to determine droplet velocities. The videos are at the same scale as the the videos in the supplemental material of the paper "Directed droplet motion along thin fibers". Specifically these videos follow the panels in SI Movie 1. Droplet positions, droplet spans and fiber angles are extracted from these videos. </p>
Data from: Directed and acyclic synaptic connectivity in the human layer 2-3 cortical microcircuit
<p>The computational capabilities of neuronal networks are fundamentally constrained by their specific connectivity. Previous studies of cortical connectivity have been mostly carried out in rodents; however, whether the principles also apply to the evolutionary expanded human cortex is unclear. Here we studied network properties within the human temporal cortex using samples obtained from brain surgery. We analyzed multi-neuron patch-clamp recordings in layer 2-3 pyramidal neurons and identified substantial differences compared to rodents. Reciprocity showed random distribution, synaptic strength was independent from connection probability and connectivity of the supragranular temporal cortex followed a directed and mostly acyclic graph topology. Application of these principles in neuronal models increased the dimensionality of network dynamics suggesting a critical role for cortical computation.</p>
Data used in manuscript Direct CO2 emissions and uptake at neighbourhood scale over the urban area of Beijing
<p>This dataset provides the data used in the manuscript "<em>Direct CO2 emissions and uptake at neighbourhood scale over the urban area of Beijing</em>".</p> <p>The folders are:</p> <p><strong>1. Modelled_CO2_Flux</strong><br> This folder contains a portion of modelled CO2 fluxes generated by SUEWS. Fc is the net CO2 flux, FcPhoto the CO2 uptake by vegetation, FcRespi the CO2 release from soil and vegetation respiration, FcMetab the CO2 emissions from human metabolism, FcBuild the CO2 emissions from the local fuel combustion in buildings. Longitudes and latitudes denote the centroid of grid.<br> <strong>1.1 Fc_annual_2016_g_C_m-2_yr-1.nc</strong> is the annual CO2 fluxes in g C m-2 year-1.<br> <strong> 1.2 Fc_monthly_2016_g_C_m-2_mon-1.nc</strong> is the monthly CO2 fluxes in g C m-2 month-1.<br> <strong>1.3 Fc_annual_2016_g_C_m-2_yr-1.tiff</strong> is the annual Fc (g C m-2 year-1) provided in GeoTiff format.<br> <strong>1.4 6_ring_EPSG4326</strong> contains the ESRI Shapefile defining the study area (with the 6th Ring Road in Beijing as the boundary).</p> <p><strong>2. ModelRun</strong><br> This folder includes SUEWS source code (Järvi et al., 2011; Ward et al., 2016; Järvi et al., 2019) and a model run sample.<br> <strong>2.1 SUEWS_SourceCode</strong> is a folder including SUEWS V2020b source Fortran codes. For detailed descriptions, readers are referred to SUEWS webpage (https://suews.readthedocs.io/en/latest/). Enter "make" through the command line and a SUEWS executive will be built under ".../ModelRun/Release".<br> <strong>2.2 EvaluationRun</strong> is a folder including the SUEWS run for model performance evaluation. To conduct a quick model run to reproduce the results demonstrated in the manuscript, use command line "./SUEWS_V2020b". </p> <p><strong>3. Observations</strong><br> The unit for CO2 flux (Fc) is μmol m-2 s-1 under this folder.<br> <strong>3.1 co2_flux_140m_2016_rm_QC.csv</strong> is the Fc observations after quality control and resampled to hourly resolution.<br> <strong>3.2 Fc_gapfilled_with_MeanDC.csv</strong> is the Fc time series for the year 2016 gap-filled with the Mean Diurnal Cycle method on a seasonal basis.</p> <p> </p> <p>Contact information: zhengyingqi@mail.iap.ac.cn</p> <p><br><strong>[References]</strong><br>Järvi, L., Grimmond, C. S. B., & Christen, A. (2011). The surface urban energy and water balance scheme (SUEWS): Evaluation in Los Angeles and Vancouver. Journal of Hydrology, 411(3-4), 219-237.<br>Ward, H. C., Kotthaus, S., Järvi, L., & Grimmond, C. S. B. (2016). Surface Urban Energy and Water Balance Scheme (SUEWS): development and evaluation at two UK sites. Urban Climate, 18, 1-32.<br>Järvi, L., Havu, M., Ward, H. C., Bellucco, V., McFadden, J. P., Toivonen, T., ... & Grimmond, C. S. B. (2019). Spatial modeling of local‐scale biogenic and anthropogenic carbon dioxide emissions in Helsinki. Journal of Geophysical Research: Atmospheres, 124(15), 8363-8384.</p>
Direct synthesis, characterization, in vitro and in silico studies of simple chalcones as potential antimicrobial and antileishmanial agents
<p>Chalcone represents a vital biosynthetic scaffold owing to its numerous therapeutic effects. The present study was intended to synthesize seventeen chalcone derivatives <strong>(3a-q)</strong> by direct coupling of substituted acetophenones and benzaldehyde. The target chalcones were characterized by spectroscopic analyses followed by their <em>in vitro</em> antimicrobial, and antileishmanial investigations with reference to standard drugs. The majority of the chalcones displayed good to excellent biological activities. Chalcone <strong>3q</strong> (1000 μg/mL) exhibited the most potent antibacterial effect with its zone of inhibition values of 30, 33, and 34 mm versus <em>Staphylococcus aureus,</em> <em>Escherichia coli, and Pseudomonas aeruginosa </em>respectively. The results also confirmed chalcone <strong>3q</strong> to be the most potent versus <em>Leishmania major </em>with the lowest IC<sub>50</sub> value of 0.59±0.12 μg/mL.<em> </em>Chalcone <strong>3i</strong> (500 μg/mL) was noticed to be the most potent antifungal agent with its zone of inhibition being 29 mm against <em>Candida albicans</em>. Computational studies of chalcones <strong>3i </strong>and<strong> 3q</strong> supported the preliminary <em>in vivo</em> results. The existence of the amino moiety and bromine atom on ring-A and methoxy moieties on ring-B caused better biological effects of the chalcones. In brief, the investigations reveal that chalcones (<strong>3i </strong>and<strong> 3q) </strong>can be employed as building blocks<strong> </strong>to discover novel antimicrobial agents.</p>
Idealized wave data in support of Directional Breaking Kinematics Observations from 3D Stereo Reconstruction of Ocean Waves
<p>You will find the WaveWatchIII data output from idealized solutions of Romero 2019, ST4 and ST6</p> <p>Data are in Netcdf format and include metadata.</p> <p>Each file corresponds to a duration-limited solution with constant wind speed of 13 m/s</p>
Diverse Hits in de Novo Molecule Design: A Diversity-based Comparison of Goal-directed Generators
<p>Results for the paper "<strong>Diverse Hits in de Novo Molecule Design: A Diversity-based Comparison of Goal-directed Generators"</strong> in the form of the generated molecules and their associated scores. The relevant code to reproduce and visualize the results can be found at https://github.com/ml-jku/diverse-hits. </p> <p> </p>
Dataset for Direct Chemical Lithography Writing on 2D Materials by Electron Beam Induced Chemical Reactions
<p>The dataset contains all relevant data and figures regarding the Figure 4, S4 and S5 of manuscript "Direct Chemical Lithography Writing on 2D Materials by Electron Beam Induced Chemical Reactions".</p> <p>All Figures are in tiff format and all relevant data are in csv formats. </p> <p>The data in csv format are labelled as specified in the corresping images (e.g. Figure4a.csv file corresponds to data used to plot graphs from Figure4a etc.). </p> <p>Axis labeling and units are always specified at the beginning of individual columns. If more than one curve was plotted from the csv file, the conditions can also be found at the beginning of corresponding columns.</p>
Financial Literacy among Young College Students: Advancements and Future Directions
Open the record for dataset details and reuse information.
Phosphorus Limitation Directly and Indirectly Constrains Tree Photosynthesis and Productivity: Evidence from a Global Meta-Analysis
<p>These dataset contains the source data and the correposnding code for the paper explained above.</p>
WindSightNet: Catalogue of wind speed and direction data from NASA InSight lander on Mars using seismic data
<p>Dataset associated with the publication "WindSightNet: the inter-annual variability of Martian winds retrieved from InSight's seismic data with machine learning" submitted to JGR: Planets.</p> <p>Authors:</p> <p>A. E. Stott, R. F. Garcia, N. Murdoch, D. Mimoun, M. Drilleau, C. Newman, A. Spiga, D. Banfield, M. Lemmon, S. Navarro, L. Mora-Sotomayor, C. Charalambous, W. T. Pike, P. Lognonné, W. B .Banerdt</p> <p>Files containing catalogue of winds produced from the seismic data on the NASA InSight mission using machine learning algorithm produced in above publication. Please refer to this publication for technical details.</p> <p> </p> <p>Contents:</p> <p>WindSightNet.csv - file containing wind speed and direction produced from the WindSightNet neural network based on seismic data</p> <p>TWINS.csv - comparitive wind speed and direction from TWINS wind sensor when available. </p> <p>TWINS data originally available from:</p> <p>J A Manfredi, Insight Auxiliary Payload Sensor Subsystem (APSS) Temperatures and Wind Sensor for Insight (TWINS) Archive Bundle, (2019), https://doi.org/10.17189/1518950</p> <p> </p> <p>Each file contains values for:</p> <p>Wind Speed</p> <p>Wind dir.</p> <p>Sol - number of sol of InSight mission </p> <p>UTC - Coordinated Universal Time of sample</p> <p>LTST - Local True Solar Time of sample</p> <p>L_s - Solar longitude value of sample</p> <p>Time - seconds since UNIX epoch</p> <p>Data is considered to be sampled at a rate of 0.01 Hz when there are no gaps.</p> <p> </p> <p>Example code for plotting paper figures can be found:</p> <p>https://doi.org/10.5281/zenodo.14267939</p>
Examination of 6 and 12 Month Follow-up of Calcium Hydroxide and Calcium Silicate Materials Used in Direct and Indirect Pulp Capping
<p>This dataset includes data evaluating the clinical and radiographic 6 and 12-month treatment success of calcium hydroxide and calcium silicate materials in indirect pulp therapy (IPT) and direct pulp capping (DPC) applications in teeth with deep dentin caries.</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.