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5,145 results for “CO₂”
Code and exemplificative data for publication titled: Synaptic inputs to motor neurons underlying muscle co-activation for functionally different tasks have different spectral characteristics.
<p>Code implemented in the publication</p> <p>Titled: Synaptic inputs to motor neurons underlying muscle co-activation for functionally different tasks have different spectral characteristics</p> <p>Authors: Borzelli,D; Vieira,TMM; Botter,A; Gazzoni,M; Lacquaniti,F; d’Avella,A</p> <p>Published in: Journal of Neurophysiology</p> <p>Year: 2024</p> <p>When running the function 'coherenceAnalysis_Borzelli_et_al_JNeurophysiol_2024.m', the code load the firings of the motor units identified during two exemplificative trials performed by a participant, saved in 'data_Borzelli_et_al_JNeurophysiol_2024'. One trial was directed toward an horizontal target of the perturbed block and the other was directed toward a supination target of the baseline block.</p> <p>Then the code calculates the coherence between the MUs identified on the BB and on the TB (cross-muscle coherence) and the cross-muscle coherence after excluding the components synchronized with the norm of the endpoint force.</p> <p>Finally, the code plots the results.</p> <p>This code could easily be modified to compute all the relevant analyses presented in the paper, such as the total within muscle coherence and the within muscle coherences after excluding the components synchronized with the norm of the force or the sum of the firings of the antagonist muscle.</p>
Recent genetic drift in the co-diversified gut bacterial symbionts of laboratory mice
<p>Daniel D. Sprockett (1), Brian A. Dillard (1), Abigail A. Landers (2), Jon G. Sanders (1), Andrew H. Moeller (1,2)*</p> <p>1 Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY 14853, USA<br>2 Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08540, USA<br>*To whom correspondence should be addressed: andrew.moeller@princeton.edu</p> <p> </p> <p><strong>Abstract:</strong></p> <p>Laboratory mice (<em>Mus musculus domesticus</em>) harbor gut bacterial strains that are distinct from those of wild mice but whose evolutionary histories are unclear. Understanding the divergence of laboratory-mouse gut microbiota (LGM) from wild-mouse gut microbiota (WGM) is critical, because LGM and WGM have been previously shown to differentially affect mouse immune-cell proliferation, infection resistance, cancer progression, and ability to model drug outcomes for humans. Here, we show that laboratory mice have retained gut bacterial symbiont lineages that diversified in parallel (co-diversified) with rodent species for > 25 million years, but that LGM strains of these ancestral symbionts have experienced accelerated accumulation of genetic load during the past ~ 120 years of captivity. Compared to closely related WGM strains, co-diversified LGM strains displayed significantly faster genome-wide rates of fixation of nonsynonymous mutations, indicating elevated genetic drift, a difference that was absent in non-co-diversified symbiont clades. Competition experiments in germ-free mice further indicated that LGM strains within co-diversified clades displayed significantly reduced fitness in vivo compared to WGM relatives to an extent not observed within non-co-diversified clades. Thus, stochastic processes (e.g., bottlenecks), not natural selection in the laboratory, have been the predominant evolutionary forces underlying divergence of co-diversified symbiont strains between laboratory and wild house mice. Our results show that gut bacterial lineages conserved in diverse rodent species have acquired novel mutational burdens in laboratory mice, providing an evolutionary rationale for restoring laboratory mice with wild gut bacterial strain diversity.</p>
DMSO-TMP-ACN-H2O Co-solvent Bayesian Optimization with Reproducibility and Gas Analysis via OEMS Data
<p>The zipped files contain the data collected and used for the Bayesian optimization (BO) of Coulombic efficiency (and discharge capacity) from the exploration of 4 co-solvents (dimethyl sulfoxide, trimethyl phosphate, acetonitrile, and water) and 2 salts (lithium perchlorate and LiTFSI).</p> <p>The cycling data and the BO clients are contained in BayesianOptimization.zip.</p> <p>The gas analysis data via online electrochemical mass spectrometry (OEMS) are contained in OEMS_data.zip.</p> <p>The cycling data of select repeats from the BO are contained in Reproducibility_data.zip.</p> <p>These are the raw datafiles. Preprocessing and analysis is not included.</p>
Efficient CO₂ and CH₄ Flux Monitoring in Soil Microcosms Using an Automated Chamber with a Cartesian Robot
Open the record for dataset details and reuse information.
AI4PROFHEALTH - Profession-health status co-occurrence graph statistics
<p>This dataset contains the Pointwise Mutual Information (PMI) values for co-occurrence pairs between different mention categories extracted from two distinct clinical datasets: <strong>MESINESP2</strong> and the <strong>Clinical Case Reports Collection</strong>. PMI is a statistical measure used to assess the strength of association between pairs of entities by comparing their observed co-occurrence to the expected frequency under the assumption of independence.</p> <p>The datasets include PMI values for each co-occurrence pair, derived from the association of professions and clinical concepts, with the aim of identifying potential occupational health risks. By sharing these datasets, we aim to support further research into the relationships between professions and clinical entities, enabling the development of more accurate and targeted occupational health risk models.</p> <p>There is a separate file for each corpus, and each dataset is provided in <strong>CSV format</strong> for easy access and analysis. These files include the PMI values for co-occurrence pairs extracted from the respective corpora, making them suitable for further data analysis.</p> <p><strong>Data Structure:</strong></p> <ul> <li><strong>MESINESP2: <code>mesinesp2_co-occurrence_pmi.zip</code></strong></li> <li><strong>Clinical case reports: <code>clinical_cases_co-occurrence_pmi.zip</code></strong></li> </ul> <p>The repository contains a .zip file for each of the corpus, each containing a .csv file with the co-occurrences between the detected professions and clinical entities. The file has the following columns order:</p> <ul> <li><code><strong>span_mention_1</strong></code>: Mention string (original): profession</li> <li><code><strong>normalized_entity_1</strong></code>: Controlled vocabulary entry for this term</li> <li><code><strong>mention1_category</strong></code>: Semantic class (i.e., NER label)</li> <li><code><strong>mention1_freq</strong></code>: Absolute frequency of this mention entity 1</li> <li><code><strong>span_mention_2</strong></code>:<strong> </strong>Mention string (original): entity 2 (disease, symptom, species, etc.)</li> <li><code><strong>normalized_entity_2</strong></code>: Controlled vocabulary entry for this term</li> <li><code><strong>mention2_category</strong></code>:<strong> </strong>Semantic class (i.e., NER label)</li> <li><code><strong>mention1_freq</strong></code>:<strong> </strong>Absolute frequency of this mention entity 2</li> <li><code><strong>co-occurrence</strong></code>: Number of co-occurrences</li> <li><code><strong>PMID</strong></code>: PMID value</li> </ul> <p><strong>Notes</strong></p> <p>This resource been funded by the Spanish National Proyectos I+D+i 2020 AI4ProfHealth project PID2020-119266RA-I00 (PID2020-119266RA-I0/AEI/10.13039/501100011033).</p> <p><strong>Contact</strong></p> <p>If you have any questions or suggestions, please contact us at:</p> <p>- Miguel Rodríguez Ortega (<miguel [dot] rod [at] bsc [dot] com>)<br>- Martin Krallinger (<krallinger [dot] martin [at] gmail [dot] com>)</p> <p><strong>Additional resources and corpora</strong></p> <p>If you are interested, you might want to check out these corpora and resources:</p> <ul> <li><a href="../records/7116201">MEDDOPROF</a> (Corpus of mentions of professions, occupations and working status and normalization, different document collection with some overlapping documents)</li> <li><a href="https://zenodo.org/records/5602914">MESINESP-2</a> (Corpus of manually indexed records with DeCS /MeSH terms comprising scientific literature abstracts, clinical trials, and patent abstracts, different document collection)</li> </ul> <p> </p>
Dataset on the content of Cu, Ni Cd, Pb, Zn, Ag, Mg, Fe, Co and Ca in the carcass, gastrointestinal tract tissues and the whole body of nestlings of a small passerine bird, the Eurasian Reed Warbler Acrocephalus scirpaceus
<p><span>The data include the description of the age and the </span><span>concentrations of </span><span>Cu, Ni Cd, Pb, Zn, Ag, Mg, Fe, Co and Ca<span> measured in the </span>isolated, emptied gastrointestinal tract, <span>the whole body, and </span>carcass of the each individual nestling of a different age and hence a different stage of <span>post-natal development. The dataset includes also</span> some additional information on the breeding biology of the focal species. </span></p>
AI4PROFHEALTH - Automatic Occupations Gazetteer and Occupations Co-occurrence with Clinical Concepts
<div> <div>This dataset comprises an occupations gazetteer generated with automatically extracted terminology from the Mesinesp2 corpus, a manually annotated corpus in which domain experts have labeled a set of scientific literature, clinical trials, and patent abstracts, as well as clinical case reports. In addition, this dataset also includes the co-occurrences among occupations, and of professions with other clinical concepts that have been extracted automatically, including diseases, procedures, symptoms, species, drugs, and neoplasia morphologies. </div> <br> <div>The repository contains a .zip file for all the results obtained from Mesinesp2 and another for the clinical cases, both containing a .tsv file for the professions gazetteer, one for the professions internal co-occurrence, and one for the professions co-occurrence with other semantic classes:</div> </div> <ul> <li><strong>mesinesp2_profession_gazetteer_and_cooccurrence.zip (Mesinesp2)</strong> <ul> <li>mesinesp2_professions_gazetteer.tsv</li> <li>mesinesp2_professions_cooccurrences.tsv</li> <li>mesinesp2_professions_cooccurrences_with_other_classes.tsv</li> </ul> </li> </ul> <ul> <li><strong>clinicalcases_profession_gazetteer_and_cooccurrence.zip (clinical cases)</strong> <ul> <li>clinicalcases_professions_gazetteer.tsv</li> <li>clinicalcases_professions_cooccurrences.tsv</li> <li>clinicalcases_professions_cooccurrences_with_other_classes.tsv</li> </ul> </li> </ul> <p>The gazetteer is divided into two columns, one with the name of the extracted terms and the other one with their total count.</p> <p>The professions co-occurrences .tsv file is divided into three columns. The first two columns contain the professions that co-occur, and the third column, named "count," indicates the number of co-occurrences calculated at the document level for each pair of detected entities. The professions co-occurrences with other classes .tsv file is structured in a similar manner, where the first column contains professions, the second one the clinical concepts that they co-occur with, the third one the counts of co-occurrences, and the fourth one the class to which the clinical concept belongs.</p> <p><strong>License</strong></p> <p>This work is licensed under a <a href="http://creativecommons.org/licenses/by/4.0/">Creative Commons Attribution 4.0 International License</a>.</p> <p><strong>Contact</strong></p> <p>If you have any questions or suggestions, please contact us at:</p> <p>- Sergi Marsol Torrent (<sergi [dot] marsol [at] bsc [dot] es>)<br>- Martin Krallinger (<krallinger [dot] martin [at] gmail [dot] com>)</p> <p><strong>Additional resources and corpora</strong></p> <p>If you are interested, you might want to check out these corpora and resources:</p> <ul> <li><a href="https://zenodo.org/records/5602914">MESINESP-2</a> (Corpus of manually indexed records with DeCS /MeSH terms comprising scientific literature abstracts, clinical trials, and patent abstracts, different document collection)</li> <li><a href="10.5281/zenodo.5070540" target="_blank" rel="noopener">MEDDOPROF corpus </a></li> <li><a href="https://zenodo.org/record/4720833">Annotation Guidelines</a></li> </ul> <p><strong>Acknowledgements</strong></p> <p>This resource been funded by the Spanish National Proyectos I+D+i 2020 AI4ProfHealth project PID2020-119266RA-I00 (<strong>PID2020-119266RA-I0/AEI/10.13039/501100011033).</strong></p>
Reducing transmission expansion by co-optimizing sizing of wind, solar, storage, and grid connection capacity: Raw Data
<p>This dataset contains all GenX model input and results data relevant to the working paper ‘Reducing transmission expansion by co-optimizing sizing of wind, solar, storage, and grid connection capacity.’ Data for each modeled scenario is contained within a folder in the main directory ('Final_Outputs'), using the naming convention p1_2030_case[number]. Scenarios correspond to the following table:</p> <table> <tbody> <tr> <td><strong>Case Number</strong></td> <td><strong>Scenario</strong></td> <td><strong>VRE Cost</strong></td> <td><strong>Forced Battery Capacity (GW)</strong></td> </tr> <tr> <td>1</td> <td>Fixed Interconnection</td> <td>Low</td> <td>3.75</td> </tr> <tr> <td>2</td> <td>Fixed Interconnection</td> <td>Low</td> <td>5</td> </tr> <tr> <td>3</td> <td>Fixed Interconnection</td> <td>Low</td> <td>7.5</td> </tr> <tr> <td>4</td> <td>Fixed Interconnection</td> <td>Low</td> <td>15</td> </tr> <tr> <td>5</td> <td>Optimized Interconnection</td> <td>Low</td> <td>3.75</td> </tr> <tr> <td>6</td> <td>Optimized Interconnection</td> <td>Low</td> <td>5</td> </tr> <tr> <td>7</td> <td>Optimized Interconnection</td> <td>Low</td> <td>7.5</td> </tr> <tr> <td>8</td> <td>Optimized Interconnection</td> <td>Low</td> <td>15</td> </tr> <tr> <td>9</td> <td>Co-Located Storage</td> <td>Low</td> <td>3.75</td> </tr> <tr> <td>10</td> <td>Co-Located Storage</td> <td>Low</td> <td>5</td> </tr> <tr> <td>11</td> <td>Co-Located Storage</td> <td>Low</td> <td>7.5</td> </tr> <tr> <td>12</td> <td>Co-Located Storage</td> <td>Low</td> <td>15</td> </tr> <tr> <td>13</td> <td>Fixed Interconnection</td> <td>Mid</td> <td>3.75</td> </tr> <tr> <td>14</td> <td>Fixed Interconnection</td> <td>Mid</td> <td>5</td> </tr> <tr> <td>15</td> <td>Fixed Interconnection</td> <td>Mid</td> <td>7.5</td> </tr> <tr> <td>16</td> <td>Fixed Interconnection</td> <td>Mid</td> <td>15</td> </tr> <tr> <td>17</td> <td>Optimized Interconnection</td> <td>Mid</td> <td>3.75</td> </tr> <tr> <td>18</td> <td>Optimized Interconnection</td> <td>Mid</td> <td>5</td> </tr> <tr> <td>19</td> <td>Optimized Interconnection</td> <td>Mid</td> <td>7.5</td> </tr> <tr> <td>20</td> <td>Optimized Interconnection</td> <td>Mid</td> <td>15</td> </tr> <tr> <td>21</td> <td>Co-Located Storage</td> <td>Mid</td> <td>3.75</td> </tr> <tr> <td>22</td> <td>Co-Located Storage</td> <td>Mid</td> <td>5</td> </tr> <tr> <td>23</td> <td>Co-Located Storage</td> <td>Mid</td> <td>7.5</td> </tr> <tr> <td>24</td> <td>Co-Located Storage</td> <td>Mid</td> <td>15</td> </tr> </tbody> </table> <p>The 'fixed interconnection' scenario describes the scenario where the capacity of interconnection for each solar photovoltaic (PV) or wind site is fixed to assumed values. The 'optimized interconnection' scenario enables the model to independently size the renewable energy to interconnection and grid connection capacity. The 'co-located storage' scenario enables any solar PV or wind resource and storage resource to be sited behind a grid connection point while optimizing the interconnection buildout for each site. These scenarios are further explained in the respective working paper. Renewable energy cost sensitivity tags include ‘low’ for assumed low projected VRE and battery costs in 2030 and ‘mid’ for assumed mid projected VRE and battery costs in 2030. Various storage discharge capacities are forced into the system as a percentage of peak demand and range from 3.75-15 GW. Within each case folder, all of the input files (.csv), result files directly outputted by the model (in the 'Results' folder), and setting files (GenX and solver settings in the 'Settings' folder) can be found. All model outputs are described in detail in the GenX documentation. The code can be found on the GenX GitHub repository: https://github.com/GenXProject/GenX.jl. This work has not yet been peer-reviewed.</p>
Supporting Data for "Innovative reforestation mosaics on marginal land in the globally important Mata Atlântica biome can create climate and economic co-benefits"
<p>This data is related to the article "Innovative reforestation mosaics on marginal land in the globally important Mata Atlântica biome can create climate and economic co-benefits."</p>
The effect of body size on co-occurrence patterns within an African carnivore guild
<p>Intraguild interactions among mammalian carnivores are important in shaping carnivore guild composition. Competing species may inhabit different areas and/or being active during different times to reduce the risk of aggressive interactions, but the role of body size in intraguild interactions within carnivore guilds remains largely unknown. We determined spatial and temporal co-occurrence of small, medium-sized and large carnivores of the carnivore guild in central Tuli, Botswana: lion <i>Panthera leo</i>, leopard <i>Panthera pardus</i>, spotted hyena <i>Crocuta crocuta</i>, brown hyena <i>Parahyaena brunnea</i>, black-backed jackal <i>Canis mesomelas</i>, bat-eared fox <i>Otocyon megalotis</i>, African wildcat <i>Felis sylvestris lybica</i>, African civet <i>Civettictis civetta</i>, honey badger <i>Mellivora capensis</i> and small-spotted genet <i>Genetta genetta</i>. We used camera trap data over a 2-year period and quantified the degree of temporal and spatial overlap by comparing activity patterns and calculating Pianka's index respectively. Our results showed that temporal overlap in activity between all carnivore species was high, but complete overlap was possibly reduced by differences in peak activity periods. In addition, low to moderate levels of spatial overlap were found between the different carnivore species, supporting the idea that small carnivore species inhabit different areas than large species to reduce the risk of interference competition. Due to the possible strong competition amongst sympatric carnivores there is a need for more knowledge on co-existence patterns for successful management and conservation of carnivore species, for example when carnivore species are (re)introduced in an area.</p>
Dataset for Co-substituted BiFeO3: thermodynamic, electronic and ferroelectric properties from first principles
<p>Data files related to the publication<em><strong> Co-substituted BiFeO<sub>3</sub>: thermodynamic, electronic and ferroelectric properties from first principles</strong></em>. The paper is yet to be submitted. The dataset includes, (i) VASP input/output files for electronic structure and polarization calculations and (ii) GULP files for the thermodynamic study. </p>
Supplementary material 3 from: Schmidt K, Walz A (2021) Ecosystem-based adaptation to climate change through residential urban green structures: co-benefits to thermal comfort, biodiversity, carbon storage and social interaction. One Ecosystem 6: e65706. https://doi.org/10.3897/oneeco.6.e65706
Mean values of microclimatic parameters between 9am and 9pm, based on measurements in the four courtyards (CY): CY 1: light green, CY 2: dark green, CY 3: orange, CY 4: red
Supplementary material 6 from: Schmidt K, Walz A (2021) Ecosystem-based adaptation to climate change through residential urban green structures: co-benefits to thermal comfort, biodiversity, carbon storage and social interaction. One Ecosystem 6: e65706. https://doi.org/10.3897/oneeco.6.e65706
Results from tree mapping and allometric equations, indicating above-ground biomass and carbon stocks
Supplementary material 5 from: Schmidt K, Walz A (2021) Ecosystem-based adaptation to climate change through residential urban green structures: co-benefits to thermal comfort, biodiversity, carbon storage and social interaction. One Ecosystem 6: e65706. https://doi.org/10.3897/oneeco.6.e65706
Results from habitat mapping and biodiversity scores. Domin values = 1: < 4% cover with few individuals; 2: < 4% with several individuals; 3: < 4% with many individuals; 4: 4–10%; 5: 11–25%; 6: 26–33%; 7: 34–50%; 8: 51–75%; 9: 76–90%; 10: 91–100% cover
FoS Co-occurrence networks related to 103 FoS, and Direct ancestors to emerging topics between 2001~2010
<p>FoS Co-occurrence networks related to 311 Level 0 and 1 FoS, and Direct ancestors to emerging topics between 2000~2010.</p> <p> </p> <p>graphs.7z contains python graph binary files, and Golden dataset.7z contains python list binary files.</p>
Data of the Publication: Master of Chaos and Order:Opposite Microstructures of PCL-co-PGA-co-PLA Accesible by a Single catalyst
<p>NMR, DSC and MALDI-ToF-MS data of the copolymers discussed in the publication "Master of Chaos and Order: Opposite Microstructures of PCL-co-PGA-co-PLA Accessible by a Single Catalyst".</p>
Continuous presence of proto-cereals in Anatolia since 2.3 Ma, and their possible co-evolution with large herbivores and hominins
<p>pollen data from the published paper in Scientific Reports: https://www.nature.com/articles/s41598-021-86423-8</p>
Co-condensation of proteins with single- and double-stranded DNA. Source Data
<p>Source data for: Co-condensation of proteins with single- and double-stranded DNA, PNAS, 2022</p>
Structural Basis for the Inhibition of IAPP Fibril Formation by the Co-Chaperonin Prefoldin - Experimental Data
<p>Experimental data (EM, AFM, BLI, ThT and Cell viability assays, as well as docking models) used for the study :</p> <p><strong>Structural Basis for the Inhibition of IAPP Fibril Formation by the </strong><strong>Co-Chaperonin Prefoldin</strong></p> <p>by Ricarda Törner, Tatsiana Kupreichyk, Lothar Gremer, Elisa Colas Debled, Daphna Fenel, Sarah Schemmert, Pierre Gans<sub>, </sub>Dieter Willbold, Guy Schoehn, Wolfgang Hoyer, Jerome Boisbouvier</p>
Diversification and phylogenetic correlation of functional traits for co-occurring understory species in the Chinese boreal forest
<p><span>Functional traits impact species interactions, community composition, and ecosystem functioning. However, few studies have focused on the diversification and phylogenetic correlation of multiple functional traits over geological time. We conducted phylogenetic comparative analysis for boreal forest understory species in northeast China to examine the diversification and phylogenetic correlation in several functional traits: leaf area (LA), leaf carbon content (LCC), leaf dry matter content (LDMC), leaf nitrogen content (LNC), plant height (PH), and specific leaf area (SLA). Phylogenetic signals showed that there were very low levels of phylogenetic niche conservatism (PNC) in understory leaf-related traits and plant height, suggesting divergence of functional traits for the co-occurring understory species. The disparity through time analyses (DTT) indicated that trait disparities mainly originated during recent divergence events and there were no differences in the observed trait disparities compared to that expected under Brownian motion. Furthermore, we found both positive and negative phylogenetic correlations among the measured functional traits. The very low levels of PNC suggests that these functional traits diverged among co-occurring understory species, and that those species are distantly phylogenetically related. The phylogenetic correlations among traits maybe caused by both positively and negatively correlated adaptions which correspond to resource acquisition strategies. This study provides evidence that divergence in functional traits may reflect understory adaptations to boreal conditions. </span></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.