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2,967 results for “secondary”
Secondary Volcanic Atmospheres II: The Importance of Kinetics Results
<p>Data used to produce plots for the paper "Growth and Evolution of Secondary Volcanic Atmospheres: II. The Importance of Kinetics", submitted to JGR: Planets.</p>
h5ad files of secondary fibroblast analysis
<p>h5ad files of secondary fibroblast analysis. For each dataset the nomenclature is</p> <p>NAME_YEAR_CONDITION_ORGANISM_X.h5</p> <p>The X parameter can be of 4 types:</p> <p>- Nothing: it is the raw adata file with all cells.</p> <p>- processed: it contains all cell types, and it has been processed.</p> <p>- fb_processed: same file, but with fibroblast cells only.</p> <p>- fb_robust: same as fb_processed, but with the definitive cell type annotation.</p>
The impact of secondary channels on the wetting properties of interconnected hydrophobic nanopores
<p>Data from Molecular Dynamics simulations.</p> <p>Files ending in .xyz are trajectory files and relate to total or partical simulation trajectories. The normal sintax is eqX.xyz where X is the imposed filling of the main cavity. </p> <p>Files ending in .dat are the "measurement" files and are the files required to compute the free energy from the simulation data. The normal sintax is eqX.dat where X is the imposed filling of the main cavity. </p> <p>Files ending in .data are LAMMPS output files. The normal sintax is eqX.data where X is the imposed filling of the main cavity. </p> <p>Other auxiliary files exist, but they are part of the analysis of the data and can be reconstructed with just the above mentioned files.</p> <p>The simulation data for specific configurations of the system is separated in different zipped files (either .tar.gz or .zip). 2A.tar.gz, 4A.tar.gz, 6A.tar.gz, 10.zip and 12.zip correspond to the configurations of lateral channels corresponding to 0.2, 0.4, 0.6,1 and 1.2 nm respectively. empty.zip and no.zip correspond to the configurations where the lateral channels where forcefully left empty (by evacuating the 6 lateral pores) and to the simple cylindrical pore with no lateral channels. all.zip, edges.zip and middle.zip correspond to the configurations of cavities with water molecules on all channel sites, only the external rings and in the middle ring, as described in the supplementary note 7.</p>
ConforMine Molecular Dynamics Data: Conformational Variability, Secondary Structure Propensities and Molecular Dynamics Simulations
<pre>This dataset contains all the data used to calculate Conformational Variability (ConVa) and Conformational Propensities as well as to train ConforMine. Each directory one level below this document contains another readme for further explanation on the contained data. The following information can be found in this dataset: </pre> <ul> <li>ConforMine_MD_training_sequences.fasta: FASTA file with the amino acid sequences of all used proteins.</li> <li>simulations (directory): Contains all the raw data derived from the MD simulations.</li> <li>ConforMine_training_MD_dihedrals (directory): Contains .xvg files with the dihedral angles of each amino acid at each step of the MD simulation.</li> <li>ConforMine_training_data_conformational_variability (directory): Contains the Conformational Variability values for all amino acids. Each file contains all ConVa values for a whole protein. The data is provided in .csv and .npy format.</li> <li>ConforMine_training_data_conformational_propensities (directory): Contains the Conformational Propensities values for all amino acids. Each file contains all propensities for a whole protein. The data is provided in .csv and .npy format.</li> </ul>
Data for: The influence of vegetation structure on secondary diaspore dispersal by wind
<p><span>The role of vegetation structure in relation to wind speed and diaspore attributes on secondary diaspore dispersal by wind has not </span><span>been empirically studied</span><span>. </span><span>Here, we investigated secondary dispersal by wind of diaspores placed in </span><span>12</span><span> different kinds of vegetation</span><span> and bare land</span><span>. The experiments were conducted in a wind tunnel using a range of wind speeds and diaspores that differed in mass and kind of appendages. </span><span>The explanations of wind speed, diaspore attribute</span><span>s</span><span>, vegetation coverage, life-form, vertical </span><span>pattern </span><span>and horizontal pattern for diaspore dispersal capacity were 6.67~10.40%, 16.13~20.53%, </span><span>6.227~</span><span>24.64%, 0.10%, 0.74%, and 0.10%, respectively. </span><span>Compared with wind speed and diaspore attributes, vegetation coverage contributed the most to diaspore dispersal capacity when vegetation coverage was low (</span><span><10% in our study). However</span><span>, but with a high (10-30%) coverage, vegetation coverage was the least influential factor in secondary diaspore dispersal by wind. V</span><span>egetation coverage </span><span>significantly </span><span>interact</span><span>ed with</span> <span>vegetation life-form, horizontal pattern and vertical pattern </span><span>on affecting</span><span> diaspore dispersal capacity. </span><span>Thus,</span><span> the most influential factor determining secondary diaspore dispersal by wind is vegetation coverage.</span></p>
Nanoscale chemical characterization of secondary protein structure of F-Actin using mid-infrared photoinduced force microscopy (PiF-IR)
<p>Raw data for manuscript for special issue in Spectrochimica Acta related to ECSBM 2022</p> <p> </p>
h5ad files of secondary fibroblast analysis [HUMAN DATASETS]
<p>h5ad files of secondary fibroblast analysis [HUMAN DATASETS]. For each dataset the nomenclature is</p> <p>NAME_YEAR_CONDITION_ORGANISM_X.h5</p> <p>The X parameter can be of 4 types:</p> <p>- Nothing: it is the raw adata file with all cells.</p> <p>- processed: it contains all cell types, and it has been processed.</p> <p>- fb_processed: same file, but with fibroblast cells only.</p> <p>- fb_robust: same as fb_processed, but with the definitive cell type annotation.</p> <p>It also includes the adata file associated with the cellxgene object: https://cellxgene.cziscience.com/collections/3c4f0970-7614-43de-beb7-6128b3cb74ed</p>
FIG. 12 in Analysis of lichen secondary chemistry doubled the number of Cetrelia W.L. Culb. & C.F. Culb. species (Parmeliaceae, lichenised Ascomycota) in Hungary
FIG. 12. — Altitudinal distribution of Cetrelia W.L.Culb.& C.F.Culb.species in Hungary.
FIG. 9 in Analysis of lichen secondary chemistry doubled the number of Cetrelia W.L. Culb. & C.F. Culb. species (Parmeliaceae, lichenised Ascomycota) in Hungary
FIG. 9. — Distribution of Cetrelia monachorum (Zahlbr.) W.L. Culb. & C.F. Culb. in Hungary.
FIG. 8 in Analysis of lichen secondary chemistry doubled the number of Cetrelia W.L. Culb. & C.F. Culb. species (Parmeliaceae, lichenised Ascomycota) in Hungary
FIG. 8. — Distribution of Cetrelia chicitae (W.L.Culb.) W.L. Culb.& C.F. Culb.in Hungary.
Prevalence Of Sickle Cell Trait and Needs Assessment Forfor Uptake of Sickle Cell Screening Among Secondary School Students in Kampala City, Uganda
<p>This study aimed to determine the burden of SCT and factors influencing uptake of screening services among secondary school students in Uganda. Data was collected using semi-structured questionnaires and analyzed using descriptive statistics and logistic regression.</p> <p> </p>
Light-demanding tree species are more susceptible to lianas than shade-tolerant tree species in a subtropical secondary forest
<ol> <li> <span>Tree-tree competition has been widely studied as a mechanism responsible for maintaining forest plant species diversity</span><span>.</span><span> Other common plant types, such as lianas, may influence tree species competition. Previous studies reported the negative effects of lianas on trees; however, variation in susceptibility to lianas among tree species and the species-specificity of liana species for tree hosts remain unclear. If lianas have species-specific interactions with trees, based either on tree or liana species identity, then lianas may influence tree-tree interactions by altering tree species-specific competitiveness. </span> </li> <li> <span>We surveyed 5,676 lianas</span><span> (DBH </span><span>≥ </span><span>0.5 cm</span><span>)</span><span> and </span><span>61,538 trees </span><span>(DBH </span><span>≥ </span><span>1 cm</span><span>)</span><span> in a 12-ha subtropical secondary forest</span><span> plot to assess </span><span>liana-tree interactions</span><span>.</span><span> We</span><span> tested </span><span>variation among the 20 most common tree species in their </span><span>susceptibility to lianas,</span><span> including whether light-demanding and shade-tolerant tree species differed. </span><span>We</span><span> quantified liana-tree network structure and</span><span> evaluated the specificity between the 20 most common tree species and the 15 most common liana species. </span><span>We expected that: (1) </span><span>tree species would vary in their susceptibility to lianas, and the extent of this </span><span>variation</span><span> would be predicted by tree shade-tolerance; and (2) </span><span>liana species would have distinct species-specific interactions with host trees. </span> </li> <li> <span>Tree species differed greatly in their susceptibility to lianas, with some tree species accumulating many more lianas than others. Light-demanding tree species particularly had greater susceptibility to lianas than shade-tolerant tree species. Both the liana-tree network structure and the interaction </span><span>intensity</span><span> between the 15 liana species and 20 tree species showed distinct specialization of liana-tree interactions. </span> </li> <li><span><em>Synthesis</em>. Variation in tree species' susceptibility to lianas implies that lianas may alter tree species-specific competitive abilities by disproportionately affecting some tree species more than others. In contrast to studies in neotropical forests, light-demanding tree species were more susceptible to lianas than shade-tolerant tree species, suggesting that lianas could reduce light-demanding tree performance in this forest. The distinct species specialization between liana and tree species suggests that increases in the relative abundance of liana species, which is occurring in many forests, may alter the tree community by reducing the relative abundance of preferred host tree species. </span></li> </ol>
Data from: Predicting regional carbon price in China based on multi-factor HKELM by combining secondary decomposition and ensemble learning
<p class="MsoNormal"><span>Accurately predicting carbon price is crucial for risk avoidance in the carbon financial market. In light of the complex characteristics of the regional carbon price in China, this paper proposes a model to forecast carbon price based on the multi-factor hybrid kernel-based extreme learning machine (HKELM) by combining secondary decomposition and ensemble learning. Variational mode decomposition (VMD) is first used to decompose the carbon price into several modes, and range entropy is then used to reconstruct these modes. The multi-factor HKELM optimized by the sparrow search algorithm is used to forecast the reconstructed subsequences, where the main external factors innovatively selected by maximum information coefficient and historical time-series data on carbon prices are both considered as input variables to the forecasting model. Following this, the improved complete ensemble-based empirical mode decomposition with adaptive noise and range entropy are respectively used to decompose and reconstruct the residual term generated by VMD. Finally, the nonlinear ensemble learning method is introduced to determine the predictions of residual term and final carbon price. In the empirical analysis of Guangzhou market, the root mean square error (RMSE), mean absolute error (MAE) and mean absolute percentage error (MAPE) of the model are 0.1716, 0.1218 and 0.0026, respectively. The proposed model outperforms other comparative models in predicting accuracy. The work here extends the research on forecasting theory and methods of predicting the carbon price.</span></p>
Dataset, Sea spray as a secondary source of organochlorine persistent organic pollutants
<p>The dataset contains concentration of organochlorine persistent organic pollutants, metal and metalloids and hydrogen and oxygen isotopes in snow and sea water samples. All snow samples have been collected within one month during spring 2019 and 2021, in the vicinity of the Polish Polar Station, Svalbard. <br> The dataset is part of a project funded by the Polish National Science Centre project no. NCN 2017/26/D/ST10/00630, RiS ID 11108.</p>
Fungicide-free management of Alternaria leaf blotch and fruit spot on apple indicates Alternaria spp. as secondary colonizer
<p>Raw data of the article: <strong>"Fungicide-free management of Alternaria leaf blotch and fruit spot on apple indicates <em>Alternaria spp</em>. as secondary colonizer"</strong>, DOI: 10.1038/s41598-023-35448-2</p> <p>-->see Read Me file</p>
APPENDIX 13 in Detangling the effects of patch attributes on bryophyte diversity in fragmented subtropical secondary forests - a case study of land-bridge islands
APPENDIX 13. — Islands with multi-long branched appearance in the Thousand Island Lake, China.
A novel preclinical secondary pharmacology resource illuminates target-adverse drug reaction associations of marketed drugs - Supplementary Material
<p>All Supplementary materials and source data for the manuscript.</p> <p>The reported analyses and results can be reproduced via the described IPython notebooks which can be found under www.github.com/Novartis/SPD</p>
Changes in nitrogen and phosphorus availability driven by secondary succession in temperate forests shape soil fungal communities and function
<p><span>Soil fungal community plays an important role in forest ecosystems, and forest secondary succession is a crucial driver of soil fungal community. However, the driving factors of fungal community and function during temperate forest succession and their potential impact on succession processes are poorly understood. In this study, we investigated the dynamics of the soil fungal community in three temperate forest secondary successional stages (shrublands, coniferous forests, and deciduous broadleaf forests) using high-throughput DNA sequencing coupled with functional prediction via the FUNGuild database. We found that fungal community richness, α-diversity, and evenness decreased significantly during the succession process. Soil available phosphorus and nitrate</span> <span>nitrogen decreased significantly after initial succession occurred, and redundancy analysis showed that both were significant predictors of soil fungal community structure. Among functional groups, fungal saprotrophs as well as pathotrophs represented by plant pathogens were significantly enriched in the early-successional stage, while fungal symbiotrophs represented by ectomycorrhiza were significantly increased in the late-successional stage. The abundance of both saprotroph and pathotroph fungal guilds was positively correlated with soil nitrate</span> <span>nitrogen and available phosphorus content. Ectomycorrhizal fungi were negatively correlated with nitrate</span> <span>nitrogen and available phosphorus content and positively correlated with ammonium</span> <span>nitrogen content.</span> <span>These results indicated that the dynamics of fungal community and function reflected the changes in nitrogen and phosphorus availability caused by the secondary succession of temperate forests. The fungal plant pathogen accumulated in the early-successional stage and ectomycorrhizal fungi accumulated in the late-successional stage may have a potential role in promoting forest succession. These findings contribute to a better understanding of the response of soil fungal communities to the secondary forest succession process and highlight the importance of fungal communities during temperate forest succession.</span></p>
Data from: Estimating potential global sources and secondary spread of freshwater invasions under historical and future climates
<p>Aim: We employ a climate-matching method to evaluate potential source regions of freshwater invasive species to an introduced region and their potential secondary spread under historical and future climates.</p> <p>Location: Global source regions, with primary introductions to the Laurentian Great Lakes and secondary introductions throughout North America</p> <p>Methods: We conducted a climate-match analysis using the CLIMATE algorithm to estimate global source freshwater ecoregions under historical and future climates with an ensemble of general circulation models for climate change scenario SSP5-8.5. Given existing research, we use a climate match of ≥ 71.7% between ecoregions to indicate climatic conditions that will not inhibit the survival of introduced freshwater organisms. Further, we estimate the secondary spread of freshwater invaders to the ecoregions of North America under historical and future climates.</p> <p>Results: We identified 54 global freshwater ecoregions with a climate match ≥ 71.7% to the recipient Laurentian Great Lakes under historical climatic conditions and 11 additional ecoregions were predicted to exceed the threshold under climate change. Three of the 11 ecoregions were located in South America, a continent where no matches existed under historical climates and eight were located in the southern United States, southern Europe, Japan, and New Zealand. Further, we identify 34 North American ecoregions of potential secondary spread of freshwater invasions from the Great Lakes under historical climatic conditions, and five ecoregions were predicted to exceed the threshold under climate change.</p> <p>Main conclusion: We provide a climate-match method that can be employed to assess the sources and spread of freshwater invasions under historical and future climate scenarios. Our climate-match method predicted increases in climate match between the recipient region and several potential source regions, and changes in areas of potential spread under climate change. The identified ecoregions are candidates for detailed biosecurity risk assessments and related management actions. The identified ecoregions are candidates for detailed biosecurity risk assessments and related management actions.</p>
Data from: "Multiscale variability in nutrients and secondary metabolites in a bat-dispersed neotropical fruit"
<p>Original data and R code accompanying our paper in <em>Ecology & Evolution</em> by Gelambi M. & Whitehead, S. R. (2023). </p> <p>Ripe fleshy fruits contain not only nutrients but also a diverse array of many secondary metabolites. Nutrients serve as a reward for mutualists, whereas defensive metabolites protect the fruit against pests and predators. The composition of these chemical traits is highly variable, both across different plants and even within repeating structures on the same individual plant. This intraspecific and intraindividual variation has important fitness consequences for both plants and animals, yet patterns of variation and covariation in nutrients and secondary metabolites are not well understood, especially at smaller scales. Here, we investigate the multiscale variation and covariation between nutrients and defensive metabolites in <em>Piper sancti-felicis </em>ripe fruits. Means and variances of sugars, proteins, phenolics, and alkenylphenols vary greatly among plants, and at least 50% of the trait variation occurs at the intraindividual level. Also, we found that proteins, but not sugars, were correlated with phenolics and alkenylphenols at multiple scales, suggesting trait variation in protein content may be more constrained than sugars. Our findings emphasize the importance of examining patterns across scales and provide the groundwork to better understand how complex patterns of variation and covariation in nutrients and defensive metabolites shape ecological interactions surrounding fruits.</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.