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413 results for “structural changes”
Dataset of "From Gas to Solution: The Changing Neutral Structure of Proline Upon Solvation"
Liquid-jet photoelectron spectroscopy (LJ-PES) and electronic-structure theory were employed to investigate the chemical and structural properties of the amino acid L-proline in aqueous solution for its three ionized states (protonated, zwitterionic, deprotonated). This is the first PES study of this amino acid in its most biologically relevant environment. Proline's structure in the aqueous phase under neutral conditions is zwitterionic, distinctly different from the non-ionic neutral form in the gas phase. By analyzing the carbon 1s and nitrogen 1s core-levels as well as the valence spectra of aqueous-phase proline, we found that the electronic structure is dominated by the protonation state of each constituent molecular site (the carboxyl and amine) with small yet noticeable interference across the molecule. The site-specific nature of the core-level spectra enables probing of individual molecular constituents. The valence photoelectron spectra are more difficult to interpret because of overlapping signals of proline with the solvent and pH-adjusting agents (HCl and NaOH). Yet we are able to reveal subtle effects of specific (hydrogen-bonding) interaction with the solvent on the electronic structure. We also demonstrate that the relevant conformational space is much smaller for aqueous-phase proline than it is for its gas phase analogue. This study suggests that caution must be taken when comparing photoelectron spectra for gaseous and aqueous-phase molecules, particularly if those molecules are readily protonated / deprotonated in solution.
Data supporting the study "An organic crystalline state in ageing atmospheric aerosol proxies: spatially resolved structural changes in levitated fatty acid particles" by Milsom et al. (2021))
<p>Data supporting the figures and findings presented in the study <strong>"An organic crystalline state in ageing atmospheric aerosol proxies: spatially resolved structural changes in levitated fatty acid particles" by Milsom et al. (2021), <em>Atmos. Chem. Phys..</em></strong></p>
Quantitative electronic structure and work-function changes of liquid water induced by solute - data
<p>Data set pertaining to the article "Quantitative electronic structure and work-function changes of liquid water induced by solute" | Physical Chemistry Chemical Physics, 24, 1310 (2022).</p> <p>Files with extension .h5 are hdf5-files structured according to the NeXus standard v2022.07 using the NXmpes user contributed format suggested by the Fairmat consortium, see<br> https://www.nexusformat.org/<br> https://fairmat-experimental.github.io/nexus-fairmat-proposal/50433d9039b3f33299bab338998acb5335cd8951/mpes-structure.html<br> A few extensions specific to liquid jet-experiments were added to the standard, and are explained in the notes-group on the top level of each file.<br> NeXus data files can be opened with any software capable of opening hdf5-structured files. The following viewers are adapted to the specifics of the NeXus data format:<br> * nexpy (distributed with python)<br> * https://h5web.panosc.eu/h5wasm (web-based NeXus viewer maintained by the European Photon and Neutron Open Science Cloud-consortium)</p> <p>In each NeXus file-entry, two types of spectra are shown:<br> 1. Sweep-averaged spectra, integrated over the non-dispersive coordinate of our detector ('data').<br> 2. As-measured data ('raw').</p> <p>Files with extension .txt are comma-separated ascii-files.<br> The following files are provided:</p> <p>Photoemission data pertaining to solute measurements using the cut-off as energy reference:<br> NaI_data.h5<br> tbai_data.h5</p> <p>Biased spectra were typically recorded in the following order:<br> [cut-off (fine), cut-off (coarse), (valence band)*(N repeats)]*(M repeats)<br> To avoid the saving of overly complex hdf5-files, these data were saved in a different order, namely:<br> [cut-off (fine)*(M repeats), cut-off (coarse)*(M repeats), (valence band)*(N*M repeats)].</p> <p>Numeric representations of the traces shown in the article's figures:<br> Figure_1a-data.txt<br> Figure_1b-data.txt<br> Figure_2a-data.txt<br> Figure_2b-data.txt<br> Figure_2c-data.txt<br> Figure_3-data.txt<br> Figure_4-data.txt<br> Figure_5a-data.txt<br> Figure_5b-data.txt<br> Figure_6a-data.txt<br> Figure_6b-data.txt<br> Figure_6c-data.txt<br> Figure_7_diff_spectra-data.txt<br> Figure_8-data.txt</p> <p>Traces shown in several figures are included only in the data file pertaining to the figure in which they occur first.</p> <p> </p> <p>Contact: Uwe Hergenhahn, uhe@fhi.mpg.de .</p>
A Dataset for detecting Change Coupling and Structural Dependencies.
<p><strong>Introduction</strong></p> <p>This repository hosts the results of runs evaluating the first developments of prototype tool for detecting Change Coupling and Structural Dependencies in the context of cyber-physical-systems(CPS). This tool analyzes the projects' code repository history and uses rule mining to detect logistical couplings, it also analyzes the source code to detect which of those changes have additional structural dependencies. </p> <p> </p> <p>The two datasets are the result from the analysis of two popular GitHub CPS projects:</p> <ul> <li>Eclipse Concierge (Java) — a small-footprint implementation of the OSGi Core Specification optimized for mobile and embedded devices.<sup>1</sup></li> <li>PX4 — a flight control solution for drones, that also contains a Drone Middleware Platform, providing drivers and middleware to run drones <sup>2</sup></li> </ul> <p>The datasets were generated by running a change coupling and structural dependencies analyzer, that is a prototype under development. The resulting raw data is available under the <code>project_results/Proj_Name</code> folder. Additionally, in the folder <code>notebooks </code>the user can find examples of how to easily query the functionality offered by the visualization and analytics libraries (in folder <code>analytics)</code>.</p> <p> </p> <p>[1] https://github.com/eclipse/concierge</p> <p>[2] https://github.com/PX4/PX4-Autopilot</p>
Data used in the article: "Climate change impacts the vertical structure of marine ecosystem thermal ranges"
<p>This dataset is used in the manuscript "Climate change impacts the vertical structure of marine ecosystem thermal ranges" accepted in Nature Climate Change 2022.</p>
From Gas to Solution: The Changing Neutral Structure of Proline Upon Solvation - data
<p>Data set pertaining to the manuscript "From Gas to Solution: The Changing Neutral Structure of Proline Upon Solvation", submitted for peer review.</p> <p>In this work, Liquid-jet photoelectron spectroscopy (LJ-PES) and electronic-structure theory were employed to investigate the chemical and structural properties of the amino acid L-proline in aqueous solution for its three ionized states (protonated, zwitterionic, deprotonated). Experimental data were recorded by photoemission spectroscopy from a liquid jet source using synchrotron radiation. The data set documents the experimentally recorded spectra, including the proline photoelectron spectra and spectra of the zero energy cut-off, that were used to calibrate the binding energy scale.</p> <p>Files with extension .h5 are hdf5-files structured according to the NeXus standard, see the<br>NeXus Data Format definition (v2024.02), https://manual.nexusformat.org/index.html<br>NXmpes expansion for FAIRmat data (v.2024.07), https://fairmat-nfdi.github.io/nexus_definitions/classes/contributed_definitions/NXmpes.html<br>NXmpes_liquid expansion to NXmpes (v.2024.07), https://fairmat-nfdi.github.io/nexus_definitions/mpes-liquid/classes/contributed_definitions/NXmpes_liquid.html<br>NeXus data files can be opened with any software capable of opening hdf5-structured files. The following viewers are adapted to the specifics of the NeXus data format:<br>* nexpy (distributed with python)<br>* https://h5web.panosc.eu/h5wasm (web-based NeXus viewer maintained by the European Photon and Neutron Open Science Cloud-consortium)</p> <p>In each NeXus file-entry, two types of spectra are shown:<br>1. Sweep-averaged spectra, integrated over the non-dispersive coordinate of our detector ('data'). <br>2. As-measured data ('raw').</p> <p>If you use these data for your scientific work we kindly ask you to send us an electronic version or the citation of your work.</p> <p>Contact: Uwe Hergenhahn, uhe@fhi.mpg.de .</p>
Result data related to "Bersalli et al. (2023) -- Most industrialised countries have peaked carbon dioxide emissions during economic crises through strengthened structural change"
<p>This repository contains the result data of our study investigating the relationship between emission peaks and economic crises. The repository contains mainly two datasets:</p> <ul> <li>multiplicative-contributions.csv / .nc</li> <li>prepost-growth-rates.csv / .nc</li> </ul> <p>Both datasets exist in CSV and NetCDF file format for convenience. The dataset <em>multiplicative-contributions</em> contains year-to-year change factors of GDP, population, energy-intensity, and carbon-intensity for every country in our study. The dataset <em>prepost-growth-rates</em> contains growth over a multi-year period pre- and post- crisis for each country and each crises in our study.</p>
Result data related to "Bersalli et al. (2024): Economic crises as critical junctures for policy and structural changes towards decarbonization – the cases of Spain and Germany"
<p>Result data related to "Bersalli et al (2024): Economic crises as critical junctures for policy and structural changes towards decarbonization – the cases of Spain and Germany". The following files are included:</p> <ul> <li>"Energy policy 2020-21 Germany-Spain.xlsx": Policy measures supporting clean energy during the Covid-19 pandemic in Germany and Spain. Data from <a href="http://energypolicytracker.org/">EnergyPolicyTracker.org</a>, amended by the authors.</li> <li> "factors.csv": Time series of emissions, population, GDP, energy intensity, and carbon intensity. Data derived from BP and Eurostat.</li> <li>"multiplicative-contribution-factors.csv": Time series of relative growth in the factors.</li> <li>"relative-cumulative-contribution-factors.csv": Time series of cumulative relative growth in the factors.</li> <li>"periods.csv": Relative growth in the factors during the global financial and COVID19 crises and before (pre) and after (post) the global financial crisis.</li> </ul>
Dataset Changes in structure and assembly of a species-rich soil natural community with contrasting nutrient availability upon establishment of a plant-beneficial Pseudomonas in the wheat rhizosphere
<p>This dataset is related to the paper "<strong>Changes in structure and assembly of a species-rich soil natural community with contrasting nutrient availability upon establishment of a plant-beneficial <em>Pseudomonas </em>in the wheat rhizosphere</strong>" (Garrido-Sanz et al., 2023, doi: 10.1186/s40168-023-01660-5) and contains the data obtained from bacterial competition asays and plant-growth measurements.</p> <p>Sequencing data used in this study has been deposited in the NCBI Sequence Read Archive (RSA) under the BioProject accession number <a href="https://www.ncbi.nlm.nih.gov/bioproject/PRJNA948847">PRJNA948847</a>.</p> <p>The R script used to analyze the data generated in the paper is available at <a href="https://github.com/dgarrs/Pprotegens_proliferation_NatComs">GitHub </a>and <a href="https://doi.org/10.5281/zenodo.8322086">Zenodo</a>.</p>
Virgin Islands National Park: Coral Reef: Decadal-scale changes in community structure from 1987 to 2011
These time series data sample percent cover of Scleractinian corals by genus measured from photo quadrats. Percent cover is given for each quadrat, each site, each year from 1987 to 2011. Counts of juvenile corals conducted in situ and small colonies less than 4 cm diameter are pooled from all sites. Supplementary data include in situ seawater temperature daily mean from 1989 to 2011. These data were used to create the figures in Edmunds, P.J., 2013, Decadal-scale changes in the community structure of coral reefs in St. John, US Virgin Islands, Marine ecology Progress Series. doi:10.3354/meps10424
Data from "Behavioral flexibility is associated with changes in structure and function distributed across a frontal cortical network in macaques"
<p>DATA FILES from the study below:</p> <p><strong><a href="https://www.biorxiv.org/content/10.1101/603530v1">Behavioral flexibility is associated with changes in structure and function distributed across a frontal cortical network in macaques</a></strong></p> <p>Jérôme Sallet, MaryAnn P Noonan, Adam Thomas, Jill X O’Reilly, Jesper Anderson, Georgios KPapageorgiou, Franz X Neubert, Bashir Ahmed, Jackson Smith, Andrew H Bell, Mark J Buckley, LéaRoumazeilles, Steven Cuell, Mark E Walton, Kristine Krug, Rogier B Mars, Matthew FS Rushworth</p> <p>bioRxiv 603530; doi: <a href="https://doi.org/10.1101/603530">https://doi.org/10.1101/603530</a></p> <p>*.nii.gz files could be opened with FSLeyes -<a href="https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLeyes)">https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSLeyes)</a></p> <p>Dara are also available from : https://www.jeromesallet.org/data-ofc-reversal-learning</p>
Figure 3 in Seasonal changes in the population structure of dominant planktonic copepods collected using a sediment trap moored in the western Arctic Ocean
Figure 3. Seasonal changes in sea ice concentration, surface chl. a (from satellite) and total mass flux (a), and daylight hours (b) at St. NAPt from October 2010 to September 2012.
Figure 8 in Seasonal changes in the population structure of dominant planktonic copepods collected using a sediment trap moored in the western Arctic Ocean
Figure 8. Seasonal changes in sea ice concentration, daylight hours, chl. a, and total mass flux from January to December (upper panel). The ecological characteristics of the five dominant copepods (lower panel). The open and solid bars indicate the high abundance and reproductive periods for each species, respectively.
Data, Sensitivity of 21st-century projected ocean new production changes to idealized biogeochemical model structure
<p>Data for reproducing figures in journal article submitted to Biogeosciences in December 2020.</p> <p>Data generated from global 1-degree simulations of the CESM in an ocean-ice configuration.</p> <p>NP model by Brett. See 10.5281/zenodo.4361705 for code for NP model and to use this dataset to recreate paper figures.</p>
Fig. 4 in Changes In The Structure Of Nest Complexes Of The Red Wood Ants Formica Rufa And F. Polyctena (Hymenoptera, Formicidae) In Urban Forests
Fig. 4. Degradation of the Formica rufa complex No. 1 (Feofaniya) in terms of average height (4, A) and diameter (4, B) under conditions of intensive construction and recreation; 4, С, D — diameter and height near the nest complex of F. polyctena No. 4 (surroundings of the Observatory), under conditions of felling of the shrub layer and processing of fallen trunks and branches into wood chips.
Figure 4 in Changes In The Structure Of Nest Complexes Of The Red Wood Ants Formica Rufa And F. Polyctena (Hymenoptera, Formicidae) In Urban Forests
Figure 4 shows the degradation trends for the nest complexes of F. rufa No. 1 (4, A, B), F. polyctena No. 4 (4, C, D). For F. rufa No. 1, there was a sharp decrease in the average diameter of anthills in 2014, and on the contrary, an increase since 2015 (fig. 4, A). In 2016, this indicator remained at approximately the same level, and in 2021 it decreased again. In 2022, this nest complex
Fig. 1 in Changes In The Structure Of Nest Complexes Of The Red Wood Ants Formica Rufa And F. Polyctena (Hymenoptera, Formicidae) In Urban Forests
Fig. 1. Location of nest complexes of Formica rufa (diamonds), F. polyctena (triangles) on the territory of the city of Kyiv (Ukraine). The city limits are marked by a red line, the forest areas by dark grey. The numbers correspond to the serial number of each complex.
Рис. 2. Изменение виΑового богатства и таксономической структуры зонаΛьных фаун прямокрыΛых северо-востока Русской равнины. Fig. 2. Changes in species richness and taxonomic structure of Orthoptera fauna of the Russian Plain. in Fauna and landscape-zonal distribution of Orthoptera in the Komi Republic (Russia)
Рис. 2. Изменение виΑового богатства и таксономической структуры зонаΛьных фаун прямокрыΛых северо-востока Русской равнины. Fig. 2. Changes in species richness and taxonomic structure of Orthoptera fauna of the Russian Plain.
Figure 2 in Tracking of spatial changes in the structure of the zooplankton community according to multiple abiotic factors along a hypersaline lagoon
Figure 2. Variation of multiple factors (temperature, salinity, oxygen (mg.L-1), and pH) in each collection station over the sampled months of 2010 and 2011.
Figure 1 in Tracking of spatial changes in the structure of the zooplankton community according to multiple abiotic factors along a hypersaline lagoon
Figure 1. Map of the coast of the state of Rio de Janeiro pointing out the 8 sampling stations of the Araruama lagoon.
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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.