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11,198 results for “organs”
Cellular composition and circuit organization of mouse locus coeruleus
<p>The locus coeruleus (LC) houses the vast majority of noradrenergic neurons in the brain and regulates many fundamental functions including fight and flight response, attention control, and sleep/wake cycles. While efferent projections of the LC have been extensively investigated, little is known about its local circuit organization. Here, we performed large-scale multi-patch recordings of noradrenergic neurons in adult mouse LC to profile their morpho-electric properties while simultaneously examining their interactions. LC noradrenergic neurons are diverse and could be classified into two major morpho-electric types. While fast excitatory synaptic transmission among LC noradrenergic neurons was not observed in our preparation, these mature LC neurons connected via gap junction at a rate similar to their early developmental stage and comparable to other brain regions. Most electrical connections form between dendrites and are restricted to narrowly spaced pairs or small clusters of neurons of the same type. In addition, more than two electrically coupled cell pairs were often identified across a cohort of neurons from individual multi-cell recording sets that followed a chain-like organizational pattern. The assembly of LC noradrenergic neurons thus follows a spatial and cell type-specific wiring principle that may be imposed by a unique chain-like rule.</p>
True cost accounting of organic and conventional food production
<p>This is the electronic supplementary data for the article "True cost accounting of organic and conventional food production" published in Journal of Cleaner Production (2023), https://doi.org/10.1016/j.jclepro.2023.137134.</p>
Soil organic carbon models need independent time-series validation for reliable prediction
<p>Supplementary Data 1 to the paper: Soil organic carbon models need independent time-series validation for reliable prediction</p> <p>By: Le Noë, J., Manzoni, S., Abramoff, R.Z., Bölscher, T., Bruni, E., Cardinael, R., Ciais, P., Chenu, C., Clivot, H., Derrien, D., Ferchaud, F., Garnier, P., Goll, D., Lashermes, G., Martin, M.P., Rasse, D., Rees, F., Sainte-Marie, J., Salmon, E., Schiedung, M., Schimel, J., Wieder, W.R., Abiven, S., Barré, P., Cécillon, L., Guenet, B.</p>
Dataset for "Single-Step Selective Oxidation of Methane by Iron-Oxo Species in the Metal-Organic Framework MFU-4l"
<p>Dataset belonging to publication "Single-Step Selective Oxidation of Methane by Iron-Oxo Species in the Metal-Organic Framework MFU-4l"</p>
Dataset from: Ultraviolet refractive index values of organic aerosol extracted from deciduous forestry, urban and marine environments
<p>The refractive index values of atmospheric aerosols are required to address the large uncertainties in the magnitude of atmospheric radiative forcing and measurements of the refractive index dispersion with wavelength of particulate matter sampled from the atmosphere are rare over ultraviolet wavelengths. An ultraviolet-optimized spectroscopic system illuminates optically-trapped single particles from a range of tropospheric environments to determine the particle’s optical properties. Aerosol from remote marine, polluted urban, and forestry environments is collected on quartz filters, and the organic fraction is extracted and nebulized to form micron-sized spherical particles. The radius and the real component of refractive index dispersion with wavelength of the optically trapped particles are determined to a precision of 0.001 µm and 0.002 respectively over a near-ultraviolet-visible wavelength range of 0.320–0.480 µm. Remote marine aerosol is observed to have the lowest refractive index (n=1.442 (λ=0.350 µm)), with above-canopy rural forestry aerosol (n=1.462–1.481 (λ=0.350 µm)) and polluted urban aerosol (n=1.444–1.485 (λ=0.350 µm)) showing similar refractive index dispersions with wavelength. In-canopy rural forestry aerosol is observed to have the highest refractive index value (n=1.508 (λ=0.350 µm)). The study presents the first single particle measurements of the dispersion of refractive index with wavelength of atmospheric aerosol samples below wavelengths of 0.350 µm. The Cauchy dispersion equation, commonly used to describe the visible refractive index variation of aerosol particles, is demonstrated to extend to ultraviolet wavelengths below 0.350 µm for the urban, forestry, and atmospheric aerosol water-insoluble extracts from these environments. A 1D radiative-transfer calculation of the difference in top-of-the-atmosphere albedo between atmospheric core-shell mineral aerosol with and without films of this material demonstrates the importance of organic films forming on mineral aerosol.</p> <p>The raw experimental spectra collected and analysed in this study are provided, as well as files for the calibrated wavelengths.</p>
DataSet for "Hybrid Based on Phenazine Conjugated Microporous Polymer as a High-Performance Organic Electrode in Aqueous Electrolytes"
<p>All raw data were obtained directly by the instruments and were then elaborated by us using Origin and/or Excel. All the facilities used, except for the NMR measurements, are present in IMDEA Energy Institute <br> <br> </p>
Hydrobiogeochemical controls on the delivery of dissolved organic matter to boreal headwater streams
<p>Dataset of continuous stream discharge, soil moisture, and hydrographic separation of Upper Horseshoe and Lower Horseshoe stream sites near Pynn's Brook, Newfoundland. Matched to continuous data where available are dissolved organic carbon concentration, absorbance at 254 nm and specific UV absorbance measurements from discrete samples collected via autosampler or grab-sampled.</p>
Upscaling soil organic carbon measurements at the continental scale using multivariate clustering analysis and machine learning
<p><strong>Data Description</strong>:</p> <p>To improve SOC estimation in the United States, we upscaled site-based SOC measurements to the continental scale using multivariate geographic clustering (MGC) approach coupled with machine learning models. First, we used the MGC approach to segment the United States at 30 arc second resolution based on principal component information from environmental covariates (gNATSGO soil properties, WorldClim bioclimatic variables, MODIS biological variables, and physiographic variables) to 20 SOC regions. We then trained separate random forest model ensembles for each of the SOC regions identified using environmental covariates and soil profile measurements from the International Soil Carbon Network (ISCN) and an Alaska soil profile data. We estimated United States SOC for 0-30 cm and 0-100 cm depths were 52.6 + 3.2 and 108.3 + 8.2 Pg C, respectively.</p> <p>Files in collection (32):</p> <p>Collection contains 22 soil properties geospatial rasters, 4 soil SOC geospatial rasters, 2 ISCN site SOC observations csv files, and 4 R scripts</p> <p>gNATSGO TIF files:</p> <p>├── available_water_storage_30arc_30cm_us.tif [30 cm depth soil available water storage]<br> ├── available_water_storage_30arc_100cm_us.tif [100 cm depth soil available water storage]<br> ├── caco3_30arc_30cm_us.tif [30 cm depth soil CaCO3 content]<br> ├── caco3_30arc_100cm_us.tif [100 cm depth soil CaCO3 content]<br> ├── cec_30arc_30cm_us.tif [30 cm depth soil cation exchange capacity]<br> ├── cec_30arc_100cm_us.tif [100 cm depth soil cation exchange capacity]<br> ├── clay_30arc_30cm_us.tif [30 cm depth soil clay content]<br> ├── clay_30arc_100cm_us.tif [100 cm depth soil clay content]<br> ├── depthWT_30arc_us.tif [depth to water table]<br> ├── kfactor_30arc_30cm_us.tif [30 cm depth soil erosion factor]<br> ├── kfactor_30arc_100cm_us.tif [100 cm depth soil erosion factor]<br> ├── ph_30arc_100cm_us.tif [100 cm depth soil pH]<br> ├── ph_30arc_100cm_us.tif [30 cm depth soil pH]<br> ├── pondingFre_30arc_us.tif [ponding frequency]<br> ├── sand_30arc_30cm_us.tif [30 cm depth soil sand content]<br> ├── sand_30arc_100cm_us.tif [100 cm depth soil sand content]<br> ├── silt_30arc_30cm_us.tif [30 cm depth soil silt content]<br> ├── silt_30arc_100cm_us.tif [100 cm depth soil silt content]<br> ├── water_content_30arc_30cm_us.tif [30 cm depth soil water content]<br> └── water_content_30arc_100cm_us.tif [100 cm depth soil water content]</p> <p>SOC TIF files:</p> <p>├──30cm SOC mean.tif [30 cm depth soil SOC]<br> ├──100cm SOC mean.tif [100 cm depth soil SOC]<br> ├──30cm SOC CV.tif [30 cm depth soil SOC coefficient of variation]<br> └──100cm SOC CV.tif [100 cm depth soil SOC coefficient of variation]</p> <p>site observations csv files:</p> <p>ISCN_rmNRCS_addNCSS_30cm.csv 30cm ISCN sites SOC replaced NRCS sites with NCSS centroid removed data</p> <p>ISCN_rmNRCS_addNCSS_100cm.csv 100cm ISCN sites SOC replaced NRCS sites with NCSS centroid removed data</p> <p><br> <strong>Data format</strong>:</p> <p>Geospatial files are provided in Geotiff format in Lat/Lon WGS84 EPSG: 4326 projection at 30 arc second resolution.</p> <p><strong>Geospatial projection</strong>: </p> <pre><code>GEOGCS["GCS_WGS_1984", DATUM["D_WGS_1984", SPHEROID["WGS_1984",6378137,298.257223563]], PRIMEM["Greenwich",0], UNIT["Degree",0.017453292519943295]] (base) [jbk@theseus ltar_regionalization]$ g.proj -w GEOGCS["wgs84", DATUM["WGS_1984", SPHEROID["WGS_1984",6378137,298.257223563]], PRIMEM["Greenwich",0], UNIT["degree",0.0174532925199433]] </code></pre> <p> </p>
Cortical topographic motifs emerge in a self-organized map of object space
<p>The human ventral visual stream has a highly systematic organization of object information, but the causal pressures driving these topographic motifs are highly debated. Here, we use self-organizing principles to learn a topographic representation of the data manifold of a deep neural network representational space. We find that a smooth mapping of this representational space showed many brain-like motifs, with large-scale organization by animacy and real-world object size, supported by mid-level feature tuning, with naturally emerging face- and scene-selective regions. While some theories of the object-selective cortex posit that these differently tuned regions of the brain reflect a collection of distinctly specified functional modules, the present work provides computational support for an alternate hypothesis that the tuning and topography of the object-selective cortex reflects a smooth mapping of a unified representational space.</p>
Data from: Accelerated high-throughput imaging and phenotyping system for small organisms
<p>Studying the complex web of interactions in biological communities requires large multifactorial experiments with sufficient statistical power. Automation tools reduce the time and labor associated with setup, data collection, and analysis in experiments that untangle these webs. We developed tools for high-throughput experimentation (HTE) in duckweeds, small aquatic plants that are amenable to autonomous experimental preparation and image-based phenotyping. We showcase the abilities of our HTE system in a study with 6,000 experimental units grown across 2,000 treatments. These automated tools facilitated the collection and analysis of time-resolved growth data, which revealed finer dynamics of plant-microbe interactions across environmental gradients. Altogether, our HTE system can run experiments with up to 11,520 experimental units and can be adapted for other small organisms.</p>
Dataset for the paper submitted for peer-review with the title "Quantifying heterotrophic bacteria parameters and dissolved organic carbon biodegradability through oxygen data assimilation in a river water quality model"
<p>The proposed dataset is related to the following article submitted for peer review:</p> <p>Hasanyar, M., Flipo, N., Romary, T., Wang, S. (2023), Quantifying heterotrophic bacteria parameters and dissolved organic carbon biodegradability through oxygen data assimilation in a river water quality model, UNDER PEER-REVIEW</p> <p>It consists of command files for the prose-pa0.74 software available here: https://gitlab.com/prose-pa/prose-pa </p> <p>To run the model :</p> <p>1. Compile prose-pa0.74</p> <p>2. Copy the executable in the current directory</p> <p>3. In a terminal launch</p> <p>> ./prose-pa0.74 simulation.COMM test.log</p> <p>The “simulation.COMM” holds the settings for the ProSe-PA simulation related to the paper mentioned in the front head of the current file. </p> <p>The information on different parameters of “simulation.COMM” are included in “bathymetrie”, “Cmds”, “Inflows”, “layers”, “meteo”, “o2_obs”, “param_bio”, “Reaches” and “Singularities” folders.</p> <p>The “bathymetrie” folder holds the geometric information of several cross-sections along the river. </p> <p>The Cmds folder holds the “simulation.COMM” file. </p> <p>The “Inflows” folder the information about the boundary condition inflows to the river such as discharge, concentration of organic carbon, etc.</p> <p>The layer folder holds data of the initial conditions of the model (Table 2 in the article).</p> <p>The “meteo” folder holds the meteorological information.</p> <p>The “o2_obs” folder holds the observed oxygen data needed to do data assimilation. </p> <p>The “param_bio” folder holds information on the physiology of bacteria, phytoplankton, and other model species.</p> <p>The “Reaches” folder holds information about river reaches and their manning coefficient. </p> <p>The “param_range” file holds the variation range of model parameters considered in data assimilation together with their perturbation percentage.</p> <p>The output files are written in $HOME/Outputs folder. It is possible to change it directly in simulation.COMM, last entry “Output_folder”.</p>
Interplay of self-organization of microtubule asters and crosslinking protein condensates Data
<p>Data sets from all figures and supplemental figures for manuscript entitled "Interplay of self-organization of microtubule asters and crosslinking protein condensates" accepted at PNAS Nexus.</p>
Spatial organization of the mouse retina at single cell resolution by MERFISH
<p><strong>Abstract:</strong><br> <br> The visual signal processing in the retina requires the precise organization of diverse neuronal types working in concert. While single-cell omics studies have identified more than 120 different neuronal subtypes in the mouse retina1, little is known about their spatial organization. Here, we generated the first single-cell spatial atlas of the mouse retina using multiplexed error-robust fluorescence in situ hybridization (MERFISH). We profiled over 390,000 cells and identified all major cell types and nearly all subtypes through the integration with reference single-cell RNA sequencing (scRNA-seq) data. Our spatial atlas allowed simultaneous examination of nearly all cell subtypes in the retina, revealing 8 previously unknown displaced amacrine cell subtypes and establishing the first connection between the molecular classification of many cell subtypes and their spatial arrangement. Furthermore, we identified spatially dependent differential gene expression between subtypes, suggesting the possibility of functional tuning of neuronal types based on location.<br> <br> <strong>Data description:</strong><br> 1. VZA105a_integrated_368genes.h5ad<br> This file contains the raw MERFISH count matrix for four samples with 368 gene features. The "sampleid" column represents the unique sample ID, while the "region" column corresponds to the tissue section ID. The "majorclass" and "subclass" columns indicate annotated retinal cell types. Finally, the "center_x" and "center_y" columns provide the coordinates of the cell centers.</p> <p><br> 2. VA45_integrated.h5ad<br> This file contains the raw MERFISH count matrix for six samples with 500 gene features. The "sampleid" column represents the unique sample ID, while the "region" column corresponds to the tissue section ID. The "majorclass" and "subclass" columns indicate annotated retinal cell types. Finally, the "center_x" and "center_y" columns provide the coordinates of the cell centers.<br> <br> 3. merfish_impute.h5ad<br> This file contains the imputed count matrix for ten samples. The "sampleid" column represents the unique sample ID, while the "region" column corresponds to the tissue section ID. The "majorclass" and "subclass" columns indicate annotated retinal cell types. Finally, the "center_x" and "center_y" columns provide the coordinates of the cell centers.<br> </p>
Рис. 1–8. КопуΛятивные органы Zelotes abdurakhmanovi sp. n. (1–6) и Zelotes mikhailovi (7–8). 1–2, 7 – эпигина, вентраΛьно; 3–6, 8 – паΛьпа и буΛьбус самцов: 3 – паΛьпа, вентраΛьно (MA – меΔиаΛьный отросток, E – эмбоΛюс, TA – терминаΛьный отросток), 4 – паΛьпа, ретроΛатераΛьно, 5 – апикаΛьная часть буΛьбуса, ΔорсаΛьно, 6 – буΛьбус, проΛатераΛьно, 8 – буΛьбус, ΔорсаΛьно. Figs 1–8. Copulatory organs of Zelotes abdurakhmanovi sp. n. (1–6) and Zelotes mikhailovi (7–8). 1–2, 7 – epigyne, ventral view; 3–6, 8 – male palp and bulbus: 3 – palp, ventral view (MA – median apohysis, E – embolus, TA – terminal apophysis), 4 – palp, retrolateral view, 5 – apical part of bulbus, dorsal view, 6 – bulbus, prolateral view, 8 – bulbus, dorsal view. in A new species of spiders of the genus Zelotes Gistel, 1848 (Aranei: Gnaphosidae) from the North-East Pre-Caspian region
Рис. 1–8. КопуΛятивные органы Zelotes abdurakhmanovi sp. n. (1–6) и Zelotes mikhailovi (7–8). 1–2, 7 – эпигина, вентраΛьно; 3–6, 8 – паΛьпа и буΛьбус самцов: 3 – паΛьпа, вентраΛьно (MA – меΔиаΛьный отросток, E – эмбоΛюс, TA – терминаΛьный отросток), 4 – паΛьпа, ретроΛатераΛьно, 5 – апикаΛьная часть буΛьбуса, ΔорсаΛьно, 6 – буΛьбус, проΛатераΛьно, 8 – буΛьбус, ΔорсаΛьно. Figs 1–8. Copulatory organs of Zelotes abdurakhmanovi sp. n. (1–6) and Zelotes mikhailovi (7–8). 1–2, 7 – epigyne, ventral view; 3–6, 8 – male palp and bulbus: 3 – palp, ventral view (MA – median apohysis, E – embolus, TA – terminal apophysis), 4 – palp, retrolateral view, 5 – apical part of bulbus, dorsal view, 6 – bulbus, prolateral view, 8 – bulbus, dorsal view.
Рис. 1–10. КопуΛятивные органы и ΔетаΛи строения паΛьп самцов Haplodrassus alexeevi sp. n. (1, 3, 4, 8), H. umbratilis (2, 5, 6, 9) и H. soerenseni (7, 10). 1–2 – паΛьпа, вентраΛьно; 3, 5, 7 – буΛьбус, вентраΛьно; 4, 6 – буΛьбус, вентро-ΛатераΛьно; 8–10 – отросток гоΛени паΛьпы. Масштабные Λинейки 0.2 мм. Figs 1–10. Copulatory organs and details of structure of male palps of Haplodrassus alexeevi sp. n. (1, 3, 4, 8), H. umbratilis (2, 5, 6, 9) and H. soerenseni (7, 10). 1–2 – palp, ventral view; 3, 5, 7 – bulbus, ventral view; 4, 6 – bulbus, ventro-lateral view; 8–10 – tibial apophysis. Scale bars 0.2 mm. in A new species of spiders of the genus Haplodrassus Chamberlin, 1922 (Aranei: Gnaphosidae) from the Northern Pre-Caspian area
Рис. 1–10. КопуΛятивные органы и ΔетаΛи строения паΛьп самцов Haplodrassus alexeevi sp. n. (1, 3, 4, 8), H. umbratilis (2, 5, 6, 9) и H. soerenseni (7, 10). 1–2 – паΛьпа, вентраΛьно; 3, 5, 7 – буΛьбус, вентраΛьно; 4, 6 – буΛьбус, вентро-ΛатераΛьно; 8–10 – отросток гоΛени паΛьпы. Масштабные Λинейки 0.2 мм. Figs 1–10. Copulatory organs and details of structure of male palps of Haplodrassus alexeevi sp. n. (1, 3, 4, 8), H. umbratilis (2, 5, 6, 9) and H. soerenseni (7, 10). 1–2 – palp, ventral view; 3, 5, 7 – bulbus, ventral view; 4, 6 – bulbus, ventro-lateral view; 8–10 – tibial apophysis. Scale bars 0.2 mm.
Reference datasets for consistency tests of GENAPOPOP 1.0 software: a user-friendly software to analyse genetic diversity and structure in partially clonal and selfed polyploid organisms.
<p>Datasets companion of the manuscript entitled GenAPoPop 1.0: a user-friendly software to analyse genetic diversity and structure in partially clonal and selfed polyploid organisms, used to achieve consistency test with Spagedi 1.5 software, and used as reference datasets to demonstrate the new possibilities allowed by GenAPoPop software.</p> <p>Raw datasets used for testing GenAPoPop 1.0, A user-friendly software for easily compute genetic analyses of autopolyploid populations packaged for Linux, MacOS and Windows; Results obtained from Spagedi 1.5 (Hardy & Vekemans 2001) and GenAPoPop1.0.</p> <p>Four pseudo-observed genotyping autotetrapolyploid SNP datasets, corresponding respectively to panmictic (A), highly clonal (B), highly selfed (C) and half-clonal-half-selfed (D) reproductive mode scenario. In all these four scenarios, we simulated two populations of 100 individuals each, connected with a migration rate of 0.01 and mutating at a rate of 0.01, genotyped at 10 SNPs. Datasets were recorded 1000 generations after an initial randomly drawing population with equal allele frequencies.</p> <p>One SNP tetraploid genotyping dataset from two French <em>Ludwigia grandiflora subsp. hexapetala</em> populations (aquatic plant from the Angiosperm clade): two populations in which we collected 75 individuals, each genotyped with 36 SNPs using the Hiplex method allowing confident allele dosage (Delord et al. 2018).</p> <p>One microsatellite tetraploid genotyping dataset on two Aulactinia stella populations (sea-anemone from the Cnidaria phylum), sampled on the coast of the arctic ocean. One population of 21 individuals and one population of 15 individuals, both genotyped with 10 microsatellites.</p> <p>We also report here the consistency tests with GenAlex and Spagedi, results of analyses (GPP tab) on 6300 independant simulations and inferences of the quantitative reproductive modes using the bayesian method on CEMP tab made on 6300 another independant simulations.</p>
Genetic architecture of dispersal behaviour in the post-harvest pest and model organism Tribolium castaneum
<p>Dispersal behaviour is an important aspect of the life-history of animals. However, the genetic architecture of dispersal related traits is often obscure or unknown, even in well studied species.<em> Tribolium castaneum</em> is a globally significant post-harvest pest and established model organism, yet studies of its dispersal have shown ambiguous results and the genetic basis of this behaviour remains unresolved. We combine experimental evolution and agent-based modelling to investigate the number of loci underlying dispersal in <em>T.castaneum</em>, and whether the trait is sex-linked. Our findings demonstrate rapid evolution of dispersal behaviour under selection. We find no evidence of sex-biases in the dispersal behaviour of the offspring of crosses, supporting an autosomal genetic basis of the trait. Moreover, simulated data approximates experimental data under simulated scenarios where the dispersal trait is controlled by one or few loci, but not many loci. Levels of dispersal in experimentally inbred lines, compared with simulations, indicate that a single locus model is not well supported. Taken together, these lines of evidence support an oligogenic architecture underlying dispersal in <em>Tribolium castaneum</em>. These results have implications for applied pest management and for our understanding of the evolution of dispersal in the coleoptera, the world's most species-rich order.</p>
Quantitative research - green organizations and green competencies - Miniatura 5 funded by the National Science Centre in Poland 2021/05/X/HS4/00974
<p>The questionnaire consisted of a general section meant to identify the type of the company, the region of its activity and the average number of employees together with with details of the respondent’s job position. The purpose of the second part of the questionnaire was to define the variables that make it possible to describe the company. These included the following ten: 1) sustainable<br> manufacturing; 2) green human resource management; 3) knowledge and awareness of ecology and sustainability; 4) environmental management; 5) green marketing; 6) environmentally friendly product design; 7) green supply chains; 8) closed-loop waste management; 9) zero waste buildings; 10) minimising the use of resources, including energy. Subsequently, based on the literature devoted to green competences, the questions were divided into four categories: knowledge, skills, attitudes and performance-related managerial skills. A total of 80 concepts were defined that were then assigned to separate categories and evaluated by respondents.<br> 100 manufacturing companies were surveyed (quantitative research). </p> <p>The research was funded by the National Science Centre in Poland 2021/05/X/HS4/00974</p>
Immature leaves are the dominant volatile sensing organs of maize
<p>Plants perceive herbivory induced volatiles and respond to them by upregulating their defenses. So far, the organs responsible for volatile perception remain poorly described. Here, we show that responsiveness to the herbivory induced green leaf volatile (Z)-3-hexenyl acetate (HAC) in terms of volatile emission, transcriptional regulation and jasmonate defense hormone activation is largely constrained to younger maize leaves. Older leaves are much less sensitive to HAC. In a given leaf, responsiveness to HAC is high at immature developmental stages and drops off rapidly during maturation. Responsiveness to the non-volatile elicitor ZmPep3 shows an opposite pattern, demonstrating that this form of hyposmia (i.e. decreased sense of smell) is not due to a general defect in jasmonate defense signaling in mature leaves. Neither stomatal conductance nor leaf cuticle composition explain the unresponsiveness of older leaves to HAC, suggesting perception mechanisms upstream of jasmonate signaling as driving factors. Finally, we show that hyposmia in older leaves is not restricted to HAC, and extends to the full blend of herbivory induced volatiles. In conclusion, our work identifies immature maize leaves as dominant stress volatile sensing organs. The tight spatiotemporal control of volatile perception may facilitate within-plant defense signaling to protect young leaves, and may allow plants with complex architectures to explore the dynamic odor landscapes at the outer periphery of their shoots.</p>
Dataset for "An air-stable Cu(I) metal-organic framework for hydrogen storage"
<p>Dataset for "An air-stable Cu(I) metal-organic framework for hydrogen storage"</p> <p>Raw data set of the electronic structure calculations and inputs for the GCMC calculations relating to above publication.</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.