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11,198 results for “organ”
Raw data files associated with the paper "Beyond generalists: the Brassicaceae pollen specialist Osmia brevicornis as a prospective model organism when exploring pesticide risk to bees"
<p>These are the raw data CSV files associated with the results described in the paper "Beyond generalists: the Brassicaceae pollen specialist Osmia brevicornis as a prospective model organism when exploring pesticide risk to bees".</p> <p>By Sara Hellström, Verena Strobl, Lars Straub, Wilhelm H. A. Osterman, Robert J. Paxton, Julia Osterman</p>
Nuclear Genome Organization in Fungi: From Gene folding to Rabl Chromosomes
<p>We discuss the current knowledge on the fungal genome organization, from the association of chromosomes within the nucleus to topological structures at individual genes and the genetic factors required for the hierarchical organization. Chromosome conformation capture followed by high-throughput sequencing (Hi-C) has elucidated how fungal genomes are globally organized in Rabl configuration where centromere or telomere bundles are associated with opposite faces of the nuclear envelope. Here, we explore the presence, in fungal taxa, of the typical proteins associated with genome organization in eukaryotes.</p>
Photoinduced Electron Transfer in Multicomponent Truxene- Quinoxaline Metal−Organic Frameworks
<ul> <li><strong>Data type</strong>: Experimental spectroscopic measurements</li> <li>Files are with filename extensions: <strong>DSC</strong>, <strong>DAT</strong>, <strong>txt</strong></li> <li>Information on <strong>origin of the data</strong>:</li> </ul> <ul> <li>EPR spectroscopic measurements with filename extensions <strong>DSC</strong>, <strong>DTA.</strong></li> <li>EPR spectra are exported as <strong>txt</strong> files in ASCII format.</li> </ul> <ul> <li>X-band CW-EPR spectroscopic measurements were generated by EMX spectrometer equipped with SHQ cavity produced by Bruker.</li> <li><strong>If the dataset includes multiple files that relate to each other:</strong> <ul> <li>Files in <strong>ARACAT_WP4_20200825_ULEI_03_60min_MUF77_OME_100K </strong>folder includes X-band CW-EPR spectroscopic measurements; original data are in DTA/DSC and txt formats.</li> </ul> </li> <li><strong>Information on</strong>: <ul> <li>specialized abbreviations: <strong>MUF7_OME – </strong>NC-MUF-7_dbc-dpq-OMe MOF, <strong>MUF7_OME – </strong>MUF-7_dbc-dpq-OMe MOF, <strong>MUF7_dpq – </strong>MUF-7_dbc-dpq MOF<strong> MUF77_paq – </strong>MUF-7_dbc-paq MOF</li> <li>_100K – measured at 10 K</li> <li>definitions of variables: <strong>Magnetic field, Temperature.</strong></li> <li>units of measurement: <strong>Gauss (G), K, degree (°), milliTesla (mT)</strong>.</li> </ul> </li> </ul>
Synthesis of Phenol-Tagged Ruthenium Alkylidene Olefin Metathesis Catalysts for Robust Immobilisation Inside Met-al-Organic Framework Support
<p>Data confirming the structure of the new compounds obtained within the project, published in <em>Catalysts</em> <strong>2023</strong>, <em>13</em>(2), 297; <a href="https://doi.org/10.3390/catal13020297">https://doi.org/10.3390/catal13020297</a></p> <p>The research was supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 860322 for the ITN-EJD “Coordination Chemistry Inspires Molecular Catalysis” (CCIMC) and by the National Science Centre, Poland (OPUS grant 2017/27/B/ST5/00941).</p>
Carbon-specific remineralization rates of small and large organic particles in the North Atlantic
<p>This repository provides the carbon-specific remineralization rates of small and large organic particles in the North Atlantic which were calculated by using BGC-Argo observations of backscatter (a proxy of particulate organic carbon, POC) and dissolved oxygen. Details are given in the following article:</p> <p>Wang, B. and Fennel, K. (2022), Biogeochemical-Argo data suggest significant contributions of small particles to the vertical carbon flux in the subpolar North Atlantic. Limnol Oceanogr, 67: 2405-2417. <a href="https://doi.org/10.1002/lno.12209">https://doi.org/10.1002/lno.12209</a></p>
Bielefeld Molecular Organic Glasses (BIMOG) Database
<p>The Bielefeld Molecular Organic Glasses (BIMOG) Database is based on a compiled dataset of experimental glass transition temperatures (Tg). The BIMOG database is the basis for our machine learning model for predicting the glass transition temperature of molecular organic compounds. For this purpose, we extended the previously unpublished data set from <a href="https://dx.doi.org/10.1039/C1CP22617G"><strong>Koop et al. 2011</strong></a> with further data from the literature. All experimental data are listed with their respecitve source.</p> <p>Further information is provided here: <strong><a href="https://tgml.chemie.uni-bielefeld.de">https://tgml.chemie.uni-bielefeld.de</a></strong></p> <p>To expand the database, we welcome the submission of further experimental data from the community. To do so, please follow this <a href="https://tgml.chemie.uni-bielefeld.de/submit_data"><strong>link</strong></a>.</p>
Raw data from Cao et al. (2023) "Electron exchange capacity of pyrogenic dissolved organic matter (DOM): Complementarity of square-wave voltammetry in DMSO and mediated chronoamperometry in water"
<p>Measured and fitted data from square-wave voltammetry (SWV) in DMSO for electron exchange capacities (EECs) of pyrogenic natural organic matter (pyDOM) and natural organic matter (NOM) standards. </p> <p>From Cao, H., A. S. Pavitt, J. M. Hudson, P. G. Tratnyek, and W. Xu. 2023. Electron exchange capacity of pyrogenic dissolved organic matter (DOM): Complementarity of square-wave voltammetry in DMSO and mediated chronoamperometry in water. Environ. Sci. Proc. Impacts: ASAP. [10.1039/d3em00009e]</p> <p>The manuscript reports electron accepting capacity (EAC), electron donating capacity (EDC), and electron exchange capacities (EECs) measured with a new method involving square-wave voltammetry in an aprotic solvent (dimethyl sulfoxide, DMSO). The measurement method, fitting of peak areas, and conversion of peak areas to EECs are described in the main text and supporting information of the manuscript.</p> <p>Here we provide the original measured data, baseline corrected data used in the peak fitting, and fitted peak area data that were used to obtain the final EEC values. The data are provided in one .xlsx file that contains multiple tabs: (i) a table of contents, (ii) a summary of the final fitting results, and (iii) tabs numbered R1-R40 containing raw measured data for each pyDOM/NOM sample.</p> <p>The data provided here should be sufficient to replicate and verify all of the analysis described in the manuscript. If you use these data, please cite this Zenodo record (DOI 10.5281/zenodo.7747020) and the original manuscript (DOI: 10.1039/d3em00009e).</p>
ELABORATION OF THE ITALIAN PORTION OF THE GLOBAL SOIL ORGANIC CARBON MAP (GSOCMAP)
<p>The Global Soil Organic Carbon map (GSOCmap) published by the Food and Agriculture Organization<br> constitutes a baseline estimation of soil organic carbon stock (CS, ton ha–1) from 0 to 30 cm, on a grid at 30 arc-seconds<br> resolution (approximately 1 x 1 km). It has been produced for the Italian territory by the Italian Soil Partnership (ISP): a<br> national hub of institutions dealing with soils, either academic/research institutions, and regional soil services (RSS). The<br> RSS are the main soil data owners in Italy and play a central role in the elaboration of policies for soil management. The<br> RSS adhering to the ISP are: Calabria, Campania, Emilia Romagna, Friuli Venezia Giulia, Liguria, Lombardia, Marche,<br> Piemonte, Puglia, Sicilia, Toscana, and Veneto. A national soil database is maintained by the Consiglio per la Ricerca e<br> l'Analisi dell'Economia Agraria (CREA). The RSS contributed with soil data, with mean density of 1 point per 50 square<br> kilometres, selecting data analysed for soil organic carbon content (SOC, dag kg-1), which were representative and well<br> distributed for the following environmental covariates: land use, geomorphology, and climate. The data were selected inbetween<br> 1990 al 2013. This was necessary in order to exclude the effect of the new soil protection policies of the Rural<br> Development Programme 2014-2020. For the RSS not included in the ISP, the data were selected from the national soil<br> database. 6748 point data were finally selected. SOC values obtained with the Springer and Klee and flash combustion<br> elemental analyser methods were retained for elaborations, because the 2 methods, were found to give statistically<br> equivalent results. SOC values obtained with Walkey and Black method were, instead, corrected with an empirical factor<br> of 1.3. 2292 of the 6748 point data had also measured bulk density (BD, Mg m–3). Pedotransfer functions were calibrated<br> to estimate BD were measured BD were missing, with the following as auxiliary variables: land use, soil regions, texture,<br> and SOC. The carbon stock (CS, ton ha–1) was calculated by multiplying: 0.3 (m) * SOC (dag kg-1) * fine earth fraction (1 -<br> skeletal content expressed as daL m–3) * BD (Mg m–3). CS of the first 30 cm depth was calculated as depth-weighted<br> average. A spatial statistics method was used for the CS interpolation. The following auxiliary variables were used: soil<br> regions, soil subregions, Corine land cover 2006, lithology, soils affected by natural constrains (gleyic, histic, vertic,<br> coarse, shallow, arenic, sodic, and acid), sand content, silt content, 30-m aster-DEM, distance from coast, distance from<br> relieves, soil aridity index, annual mean precipitations, mean annual air temperature, soil inorganic carbon, and soil<br> depth. For the soil region of Po valley, the land units at 1:250,000 scale were also used. The interpolation method was a<br> general linear regression for the soil regions of Po valley, and a radial basis function for the remaining Italian territory.<br> The 6748 point data were divided, by spatial random sampling, into 10 subsets. Ten interpolations were produced, each<br> time leaving out 1/10 of the dataset. Average (fig. 1), standard deviation and confidence intervals of these 10<br> interpolations were calculated. Mean Absolute Errors (MAE) and Root Mean Squared Errors (RMSE) were respectively<br> 25.5 and 36.4 Mg/ha.</p> <p>A.85 Italy Map source: Country submission Point data Number of samples: 6748 Sampling period: 1990-2013 SOC analysis method: SOC values obtained with the Springer and Klee and ’flash combustion elemental analyser’ methods were retained for elaborations. Uncorrected values obtained by the Walkey and Black method were corrected with an empirical linear equation, based on previous studies and as recommended by the Italian official methods. BD analysis method: Undisturbed sampling, core method and pit method Mapping method Mapping method details: Neural Networks and GLM, according to soil region Validation statistics: Mean Error (ME) of the prediction is 1.688 Mg/ha, MAE 25.57 Mg/ha, Root Mean Squared Error (RMSE) is 36.24 Mg/ha. Contact Data Holder: Research centre for agriculture and environment Contact: CREA Consiglio per la ricerca in agricoltura e l’analisi dell’economia agraria edoardo.costantini@crea.gov.it</p>
Inverse design of metal-organic frameworks for direct air capture of CO2 via deep reinforcement learning
<p>The combination of several interesting characteristics makes metal-organic frameworks (MOFs) a highly sought-after class of nanomaterials for a broad range of applications like gas storage and separation, catalysis, drug delivery, and so on. However, the ever-expanding and nearly infinite chemical space of MOFs makes it extremely challenging to identify the most optimal materials for a given application. In this work, we present a novel approach using deep reinforcement learning for the inverse design of MOFs, our motivation being designing promising materials for the important environmental application of direct air capture of CO2 (DAC). We demonstrate that the reinforcement learning framework can successfully design MOFs with critical characteristics important for DAC. Our top-performing structures populate two separate subspaces of the MOF chemical space: the subspace with high CO2 heat of adsorption and the subspace with preferential adsorption of CO2 from humid air, with few structures having both characteristics. Our model can thus serve as an essential tool for the rational design and discovery of materials for different target properties and applications.</p>
Temperature-Dependent THz Properties and Emission of Organic Crystal BNA
<p>This dataset is accompanying the paper "Temperature-Dependent THz Properties and Emission of Organic Crystal BNA"</p> <p><strong>General data acquisition:</strong></p> <p>The data was acquired with a modified Menlo Tera K-15 THz-TDS, consisting of a photoconductive emitter/receiver and four off-axis-parabolic mirrors (OAP). The second and third OAP, focusing and collecting the THz, are with a longer focus length to have enough space for the cryostat (Janis ST-100), which is equipped with 3 mm z-cut quartz windows for entry and exit of the THz beam. The delay line offers delays up to 1600 ps but the range was restricted to cut out the reflections from the z-cut quartz windows. Instead of averaging with Menlo’s own software ScanControl, each single trace is read out. 10 000 traces are saved for each unique measurement condition (crystal orientation, temperature) and saved in a single HDF-5 file. HDF-5 is an efficient (binary), cross-platform data format and can be read easily by i.e. Python or Matlab.</p> <p> </p> <p><strong>The structure is as follows:</strong></p> <p><strong>raw_data </strong></p> <p>The folder raw_data contains four folders. The folder “dark” contains a single file since this is independent of crystal orientation and temperature of the cryostat. For this measurement, the THz beam was blocked but all electronics, selected delay range etc. kept the same, to measure the noise-floor of the system.</p> <p>The folder reference was captured with the cryostat incl. windows, vacuum and crystal holder in place. Even though there should be no change in the transfer function by changing the temperature (due to the large aperture of the crystal holder), we still recorded reference traces for each temperature.</p> <p>The folder “BNA_orientation_001” contains the data with the organic crystal BNA in vertical orientation (<001>).</p> <p>The folder “BNA_orientation_100” contains the data with the organic crystal BNA in horizontal orientation (<100>).</p> <p><strong>averaged_corrected_data</strong></p> <p>The folder “averaged_corrected_data” reduces the large amount of raw data due to averaging. The program “Correct@TDS” (developed in the group of Dr. Romain Peretti, Terahertz Photonics Group @ IEMN - CNRS (UMR 8520), publication in preparation), is used to fit specific correction parameters for the delay, dilatation, amplitude noise and periodic sampling. The mean data is saved for each temperature in a text file called “mean.txt”. The other output of “Correct@TDS” is diagnostic information about the correction parameters and about the standard deviation in frequency- and time-domain.</p> <p><strong>extracted_n_alpha</strong></p> <p>The folder “extracted_n_alpha” contains the refractive index, absorption coefficient and more in a single HDF-5 file, extracted by the program phoeniks (<a href="https://github.com/TimVog/phoeniks">https://github.com/TimVog/phoeniks</a>), which is developed in our group. All results for the paper are saved in the internal folder structure of the HDF-5 file (for crystal orientation and temperature).</p> <p>The folder “nelly” shows the extraction of n and alpha done with Nelly [1] (<a href="https://github.com/YaleTHz/nelly">https://github.com/YaleTHz/nelly</a>) for the vertical orientation, which was used for the supplementary document.</p> <p> </p> <p>[1] Nelly: A User-Friendly and Open-Source Implementation of Tree-Based Complex Refractive Index Analysis for Terahertz Spectroscopy</p> <p>Uriel Tayvah, Jacob A. Spies, Jens Neu, and Charles A. Schmuttenmaer</p> <p>Analytical Chemistry 2021 93 (32), 11243-11250</p> <p>DOI: 10.1021/acs.analchem.1c02132</p> <p> </p>
Emission of volatile organic compounds from residential biomass burning and their rapid chemical transformations.
<p>Volatile Organic Compounds (VOCs) were monitored during the Ioannina 2022/23 winter campaign, in north-east Greece. The campaign was carried out between December 6th, 2021, and January 10th, 2022. Nitrogen oxides, carbon monoxide, carbon dioxide, methane, PM10 and Black carbon were also monitored, as well as meteorological variables. Ioannina is nested within the Dinaric mountains and suffers from intense winter pollution events, due to the topology which traps the pollution over the city. The instruments deployed included a Proton Transfer Time-of-Flight Mass Spectrometry (PTR-ToF-MS 4000 – Ionicon GmbH, Austria), a greenhouse gas monitor (G2301 – Picarro Inc., USA), a suite of carbon monoxide, ozone, nitrogen oxide analyzers (APMA-360, APNA-360 and APOA-360 – Horiba Ltd., Japan), a PM10 monitor (F-701-20 – DURAG, Germany), an aethalometer (AE33 – Magee Scientific, USA) and a weather station. Radiation, historical temperature data from the University of Ioannina, and PMF analysis results are also submitted.</p>
Seasonal controls override forest harvesting effects on the composition of dissolved organic matter mobilized from boreal forest soil organic horizons
<p>Dataset comprised of nutrient fluxes (DOC, TDN, NH4, TDN and SRP), optical parameters related to DOM composition (SUVA, spectral slopes and slope ratio), pH, and other nutrient and elemental ratios for passive pan lysimeters installed across terrestrial sites in Pynn's Brook, Newfoundland.</p>
Data_Schönauer et al. (2023)_Root and branch hydraulic functioning and trait coordination across organs in drought-deciduous and evergreen tree species of a subtropical highland forest
<p>Data used in</p> <p>Schönauer, M., Hietz, P., Schuldt, B., and Rewald, B. (2023). Root and branch hydraulic functioning and trait coordination across organs in drought-deciduous and evergreen tree species of a subtropical highland forest. Frontiers in plant science 14, 1127292. doi: 10.3389/fpls.2023.1127292</p>
Gridded global organic matter reactivity (RCM parameter a, in years)
<p>Gridded data product for the globally extrapolated RCM parameter a (in yrs) and its respective reactivity k (in 1/yrs from k = nu/a). This represents a combination of the two datasets presented in the main text in Fig. 9. The deep-sea extrapolation uses data from Seiter, Hensen, and Zabel (2005), while the shallow ocean (SFD<1000m) uses data from Jørgensen, Wenzhöfer, Egger, and Glud (2022). The area South-Est of Australia remains empty as in Seiter et al. (2005) and for reasons given in the main text.</p>
Universal microbial reworking of dissolved organic matter along environmental gradients
<p>Soils are losing increasing amounts of carbon annually to freshwaters as dissolved organic matter (DOM), which, if degraded, can increasingly offset their carbon sink capacity. DOM is more susceptible to degradation closer to its source and becomes increasingly dominated by the same (i.e., universal), difficult-to-degrade compounds as degradation proceeds. However, the processes underlying DOM degradation across environments are poorly understood. Here we found DOM changed similarly along soil-aquatic gradients irrespective of differences in environmental conditions. Using ultrahigh-resolution mass spectrometry, we tracked DOM along soil depths and hillslope positions in forest headwater catchments and related its composition to soil microbiomes and physico-chemical conditions. Along depths and hillslopes, carbohydrate-like and unsaturated hydrocarbon-like compounds increased in abundance-weighted mass, suggestive of microbial reworking of plant material. More than half of the variation in the abundance of these compounds was related to the expression of genes essential for degrading plant-derived carbohydrates. Our results implicate continuous microbial reworking in shifting DOM towards universal compounds in soils. By synthesising data from the land-to-ocean continuum, we suggest these processes can be generalised across ecosystems and spatiotemporal scales. Such general degradation patterns can be leveraged to predict DOM composition and its downstream reactivity along environmental gradients to inform management of soil-to-stream carbon losses.</p>
Model output from CAABA/MECCA study "Development of a multiphase chemical mechanism to improve secondary organic aerosol formation in CAABA/MECCA (version 4.7.0)"
<p>This dataset includes the main data obtained during the study "Development of a multiphase chemical mechanism to improve secondary organic aerosol formation in CAABA/MECCA (version 4.7.0)" (DOI:10.5194/gmd-2023-102). The updated model code can be found at zenodo.org (DOI:10.5281/zenodo.7944174). The data can be used to replicate the results shown in the manuscript. Contained are results produced by the updated CAABA/MECCA (version 4.7.0) and reference data from CAABA/MECCA version 4.5.5. In version 4.7.0, new biogenic and anthropogenic species are introduced to the model (limonene and long-chained alkanes) with refined multiphase chemistry, while new reaction pathways are added for existing compounds (isoprene, benzene and IEPOX). The output is generated to evaluate model results in terms of temperature- and NOx-dependency.</p>
Dataset for "Blue-shift photoconversion of near-infrared fluorescent proteins for labeling and tracking in living cells and organisms"
<p>Dataset that supports the observation, characterization and application of the blue-shift photoconversion of the near infrared proteins, miRFPs, reported in the manuscript: "Blue-shift photoconversion of near-infrared fluorescent proteins for labeling and tracking in living cells and organisms". The data references to the specific figures and graphs in the manuscript.</p>
Geographic range size and species morphology determines the organization of sponge host-guest interaction networks across tropical coral reefs (Raw data)
<p>Datasets for the analysis developed in the Article "<em><strong>Geographic range size and species morphology determines the organization of sponge host-guest interaction networks across tropical coral reefs</strong></em>". For more information, please refer to the original publication.</p> <p>Network_Structural_Index_&_SpogeTraits.csv <- Structural Index for the sponge-dwelling fauna network, sponge accumulated area and sponges’ morphology.</p> <p>NWTA_CoralReefs_Sponges_ interactions.csv <- Relationship between host sponges and guest fauna in the Northwester Atlantic coral reefs</p> <p>NWTA_CoralReefs_Sponge_reacords.csv <- Sponge species incidence records in the Northwester Atlantic coral reefs</p> <p>sponges_morphological_description.csv <- Sponge morphological standardization</p> <p>Network.html <- Interactive sponge-dwelling fauna network</p> <p>Enjoy!<br> </p>
Global Multi-organizations ERGM
<p>Above are the datasets that are used in my essay 'Spatial Characteristics and Determinants of Inter-Organizational Cooperation in the Global Network'.</p>
Dataset for 'Organic Electrochemical Transistors Printed from Degradable Materials as Disposable Biochemical Sensors'
<p>This data set contains the data collected during the FNS project Green Piezo (Grant no. 179064) in association with the publication entitled “Organic Electrochemical Transistors Printed from Degradable Materials as Disposable Biochemical Sensors”.</p> <p>This work aims to study the fabrication of organic electrochemical transistors using more environmentally-friendly materials, in particular carbon contacts and polylactic acid (PLA) as substrate. Organic electrochemical transistors (or OECTs) offer applications in biosensing, for example for point-of-care devices. We use a combination of additive manufacturing methods (screen printing and inkjet printing) to manufacture these transistors and solve the issues with fabricating them on a low-temperature substrate such as PLA. We also assess these transistors as disposable sensors for the detection of various ion concentrations as well as glucose. The data that was collected in the frame of this work is present in this repository. More information about the contents of the dataset is present in the included README files.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.