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1,221 results for “Aggregators”
Archive of aggregate data on work and parenthood
<p>These are aggregate files of labor force participation for mothers, fathers, and women not living with own children. Read ReadMe.txt file first for definitions and codes. Generated using the Current Population Survey monthly files from ipums.org. These files are meant to encourage discussion and analysis of labor force participation of mothers in comparison to fathers and women without own children in their home.</p>
Matrix aggregation of species of Phyla Annelida (Polychaeta), Mollusca, Arthropoda (Decapoda, Stomatopoda, Amphipoda, and Chelicerata), and Echinodermata registered of the Caribbean Sea and Gulf of Mexico region by Ocean Biodiversity Information Systems of the research "Evaluation of the use of Autonomous Reef Monitoring Structures (ARMS) for capturing the biological diversity of two coral reefs in the Yucatán Península, México"
<p>This database consists of an aggregation matrix of species from Ocean Biodiversity Information Systems using as geographic filters the Caribbean Sea region (ID 34287) and the Gulf of Mexico region (ID 34287) nomenclature and hierarchical classification of each Phyla from World Register of Marine Species used for the calculation of average taxonomic distinction of species belonging to the Phyla Annelida (Polychaeta), Mollusca, Arthropoda (Decapoda, Stomatopoda, Amphipoda, and Chelicerata), and Echinodermata associated to Autonomous Reefs Monitoring Structures from the research “Evaluation of the use of Autonomous Reef Monitoring Structures (ARMS) to estimate cryptic diversity in two coral reefs of the Yucatan Península, México”</p> <p><strong>*Corresponding autor: </strong>edlinguerra@gmail.com</p> <p>BIS Ocean Biodiversity Information System. Available online: <a href="http://www.iobis.org/">www.iobis.org</a>.</p> <p>Horton, T.; Gofas, S.; Kroh, A.; Poore, G.C.B.; Read, G.; Rosenberg, G.; Stöhr, S.; Bailly, N.; Boury-Esnault, N.; Brandão, S.N.; et al. Improving nomenclatural consistency: A decade of experience in the World Register of Marine Species. <em>Eur. J. Taxon.</em> <strong>2017</strong>, <em>2017</em>, doi:10.5852/ejt.2017.389.</p> <p><span lang="EN-US">was produced in collaboration with the Biodiversidad Marina de Yucatán project. </span><a href="https://www.bdmy.org.mx/carteles-publicaciones/" target="_blank" rel="noopener">https://www.bdmy.org.mx/,</a> Universidad Nacional Autonoma de México and Escuela Nacional de Estudios Superiores</p>
maximal time of availability of aggregated records
<p>Establish maximal time of availability of the precise versions of records in an aggregating zip archive by publishing SHA256 sums of the archive.</p>
FIGURE. Median network analyses (MNA) of a subset of the C. trilobus aggregate (i.e. those in the clade A from Fig. 11) based on concatenated DNA sequence data from ITS, trnL-trnF and psbJ-petA. Stars and arrow indicate accessions discussed in the text. NI: North Island, SI: South Island. in Five new species of Corybas (Diurideae, Orchidaceae) endemic to New Zealand and phylogeny of the Nematoceras clade
FIGURE. Median network analyses (MNA) of a subset of the C. trilobus aggregate (i.e. those in the clade A from Fig. 11) based on concatenated DNA sequence data from ITS, trnL-trnF and psbJ-petA. Stars and arrow indicate accessions discussed in the text. NI: North Island, SI: South Island.
FIGURE. Bayesian tree of New Zealand spider orchids (Corybas) based on DNA sequence data from ITS, trnL-trnF and psbJ-petA. Major clades are indicated by open bars and capital letters, members of the C. trilobus aggregate are shaded, and posterior probabilities/ bootstrap percentages (≥50) indicated by numbers near each node. NI: North Island, SI: South Island, MCQI: Macquarie Island, CHI: Chatham Island in Five new species of Corybas (Diurideae, Orchidaceae) endemic to New Zealand and phylogeny of the Nematoceras clade
FIGURE. Bayesian tree of New Zealand spider orchids (Corybas) based on DNA sequence data from ITS, trnL-trnF and psbJ-petA. Major clades are indicated by open bars and capital letters, members of the C. trilobus aggregate are shaded, and posterior probabilities/ bootstrap percentages (≥50) indicated by numbers near each node. NI: North Island, SI: South Island, MCQI: Macquarie Island, CHI: Chatham Island
FIGURE. Canonical variate analysis of Corybas hypogaeus, C. obscurus ("darkie"), C. wallii ("triwhite") and two variants of the C. trilobus aggregate ("Rimutaka", "Trotters") in Five new species of Corybas (Diurideae, Orchidaceae) endemic to New Zealand and phylogeny of the Nematoceras clade
FIGURE. Canonical variate analysis of Corybas hypogaeus, C. obscurus ("darkie"), C. wallii ("triwhite") and two variants of the C. trilobus aggregate ("Rimutaka", "Trotters")
AggMapNet: Enhanced and Explainable Low-Sample Omics Deep Learning with Feature-Aggregated Multi-Channel Networks
<p>This data contains the datasets used in the paper "AggMapNet: Enhanced and Explainable Low-Sample Omics Deep Learning with Feature-Aggregated Multi-Channel Networks", each folder is named by the dataset name in the paper</p>
The landscape of circulating platelet aggregates in COVID-19
<p>A characteristic clinical feature of COVID-19 is the frequent incidence of microvascular thrombosis. In fact, COVID-19 autopsy reports have shown widespread thrombotic microangiopathy characterized by extensive diffuse microthrombi within peripheral capillaries and arterioles in lungs, hearts, and other organs, resulting in multiorgan failure. However, the underlying process of COVID-19-associated microvascular thrombosis remains elusive due to the lack of tools to statistically examine platelet aggregation (i.e., the initiation of microthrombus formation) in detail. Here we report the landscape of circulating platelet aggregates in COVID-19 obtained by massive single-cell image-based profiling and temporal monitoring of the blood of COVID-19 patients (n = 110). Surprisingly, our analysis of the big image data shows the anomalous presence of excessive platelet aggregates in nearly 90% of all COVID-19 patients. Furthermore, results indicate strong links between the concentration of platelet aggregates and the severity, mortality, respiratory condition, and vascular endothelial dysfunction level of COVID-19 patients. </p>
Artifacts for [On Rank Aggregating Test Prioritizations]
<p>Artifacts for [On Rank Aggregating Test Prioritizations]<br> =====================================================</p> <pre><code>username: entp password: entp root password: entp</code></pre> <p>Directory structure for [/home/entp/<strong>EnTP</strong>]<br> -----------------------------------------------------------------<br> [<strong>benchmarks</strong>] -> contains the projects/subjects under test used in our study.</p> <p>[<strong>cost_cov_diff</strong>] -> pre-recorded cost (cachegrind's I-Ref count) per test-case. We recorded this precporcessing to avoid fluctuations in costs across different systems, and hence maintain uniformity.</p> <p>[<strong>raw_data_scripts</strong>] -> contains C++ implementation of EnTP, and scripts to generate results (tables, boxplots, .csv, .txt, etc.)</p> <p>[<strong>exp_res_raw</strong>] -> contains pre-recorded experiments results (as .csv files) as reported in the paper. To generate the plots, run [python3 plot.py] from {/home/entp/EnTP/exp_res_raw}. The plots will be generated in .eps format. These precomputed results helps the artifact reviewer save time by generating the plots only, otherwise the whole process (detailed in Makefile's usage) generates a [database] directory of ~400GB (all benchmarks, all combinations, all results even beyond those reported in the paper, + some extra logs) which is very time consuming (~1 month on a standard laptop with 8 cores, 8GB RAM).</p> <p><strong>Makefile</strong>'s usage<br> ---------------------------<br> [Step 1]</p> <pre><code class="language-bash">entp@entp:~/EnTP$ make -s entp_all_[benchmark]</code></pre> <p>Possible values of [benchmark] = {c4, gravity, mlisp, replace, schedule2, space, xc, cf, grep, printtokens, scd, sed, tcas, xxhash, flex, gzip, printtokens2, schedule, slre, totinfo}.</p> <p>example:</p> <pre><code class="language-bash">entp@entp:~/EnTP$ make -s entp_all_slre</code></pre> <p>executes EnTP and state-of-the-arts on the benchmark "slre". Please follow log messages displayed after executing the above command. At the end of the execution, a sub-diretory named [<strong>database</strong>] will store the results for all experiments performed on "slre" for the current system and environment.<br> ...<br> [<em>database/{100, 75, 50, 25}</em>] -> contains experimental results for the consensus budget of top-{100%, 75%, 50%, 25%}.<br> ...</p> <p>(optional)</p> <pre><code class="language-bash">entp@entp:~/EnTP$ make -s entp_all_[benchmark] #other benchmarks</code></pre> <p>[Step 2]</p> <pre><code class="language-bash">entp@entp:~/EnTP$ make -s generate_tabs</code></pre> <p>This will collect data from the newly generated directories and results (at the end of previous step), and generate tables, and .eps plots.</p> <p>Check for results reproduced<br> ---------------------------------------------<br> You can visually compare the .eps plots in {<strong><em>/home/entp/EnTP</em></strong>} with the ones generated in the directory {<strong><em>/home/entp/EnTP/exp_res_raw</em></strong>}.<br> You can also compare the .csv files under these directories for quantitative comparison with some tolerance.</p> <p>(optional)</p> <pre><code class="language-bash">entp@entp:~/EnTP$ make -s destroy_all</code></pre> <p>Cleans up everything!</p>
FIGURE. Thalictrum tsawarungense in the wild (Zayu in Xizang, China, the type locality). A. Habitat. B. Habit. C. Roots. D. Portion of stem. E. Leaf (left: adaxial side; right: abaxial side). F. Leaflet (adaxial side). G. Portion of adaxial side of leaflet. H. Portion of abaxial side of leaflet. I. Flower. J. Sepal (left: adaxial side; right: abaxial side). K. Stamens. L. Carpels. M. Aggregate fruits. N. Achenes (immature). Photographed by Y.P. Zeng. in Thalictrum hengduanshanense and T. longistipitatum (Ranunculaceae), two new species from southeastern Xizang and northwestern Yunnan, China
FIGURE. Thalictrum tsawarungense in the wild (Zayu in Xizang, China, the type locality). A. Habitat. B. Habit. C. Roots. D. Portion of stem. E. Leaf (left: adaxial side; right: abaxial side). F. Leaflet (adaxial side). G. Portion of adaxial side of leaflet. H. Portion of abaxial side of leaflet. I. Flower. J. Sepal (left: adaxial side; right: abaxial side). K. Stamens. L. Carpels. M. Aggregate fruits. N. Achenes (immature). Photographed by Y.P. Zeng.
FIGURE. Thalictrum rostellatum in the wild (Zayu in Xizang, China). A. Habitat. B. Habit. C. Roots. D. Portion of stem. E. Leaf (left: adaxial side; right: abaxial side). F. Leaflet (adaxial side). G. Portion of adaxial side of leaflet. H. Portion of abaxial side of leaflet. I. Flower. J. Sepal (left: adaxial side; right: abaxial side). K. Stamens. L. Carpels. M. Aggregate fruit. N. Achenes (immature). Photographed by Y.P. Zeng. in Thalictrum hengduanshanense and T. longistipitatum (Ranunculaceae), two new species from southeastern Xizang and northwestern Yunnan, China
FIGURE. Thalictrum rostellatum in the wild (Zayu in Xizang, China). A. Habitat. B. Habit. C. Roots. D. Portion of stem. E. Leaf (left: adaxial side; right: abaxial side). F. Leaflet (adaxial side). G. Portion of adaxial side of leaflet. H. Portion of abaxial side of leaflet. I. Flower. J. Sepal (left: adaxial side; right: abaxial side). K. Stamens. L. Carpels. M. Aggregate fruit. N. Achenes (immature). Photographed by Y.P. Zeng.
FIGURE. Specimens of Thalictrum longistipitatum (previously misidentified as T. rostellatum or T. wangii). A. China, Xizang, Zayu, B.S. Li, Z.C. Ni & S.Z. Cheng 7224 (PE); inset: aggregate fruits. B. China, Yunnan, Dêqên, L. Xie & J.F. Mao 136 (PE01569411); inset: aggregate fruits. C. Same locality, L. Xie & J.F. Mao 137 (PE01569412); inset: aggregate fruits. D. Same locality, L. Xie & J.F. Mao 138 (PE01569413); inset: aggregate fruits. in Thalictrum hengduanshanense and T. longistipitatum (Ranunculaceae), two new species from southeastern Xizang and northwestern Yunnan, China
FIGURE. Specimens of Thalictrum longistipitatum (previously misidentified as T. rostellatum or T. wangii). A. China, Xizang, Zayu, B.S. Li, Z.C. Ni & S.Z. Cheng 7224 (PE); inset: aggregate fruits. B. China, Yunnan, Dêqên, L. Xie & J.F. Mao 136 (PE01569411); inset: aggregate fruits. C. Same locality, L. Xie & J.F. Mao 137 (PE01569412); inset: aggregate fruits. D. Same locality, L. Xie & J.F. Mao 138 (PE01569413); inset: aggregate fruits.
FIGURE. Specimens of Thalictrum hengduanshanense (previously misidentified as T. rostellatum or T. wangii). A. China, Xizang, Zayu, Anonymous 75 (HITBC); inset: aggregate fruit (immature). B. China, Yunnan, Dêqên, K.M. Feng 5214 (KUN0690504); inset: aggregate fruit (immature). C. China, Yunnan, Dêqên, L. Xie & J.F. Mao 133 (PE01569465); inset: aggregate fruit. D. China, Yunnan, Weixi, K.M. Feng 4833 (KUN0690086); inset: aggregate fruit. in Thalictrum hengduanshanense and T. longistipitatum (Ranunculaceae), two new species from southeastern Xizang and northwestern Yunnan, China
FIGURE. Specimens of Thalictrum hengduanshanense (previously misidentified as T. rostellatum or T. wangii). A. China, Xizang, Zayu, Anonymous 75 (HITBC); inset: aggregate fruit (immature). B. China, Yunnan, Dêqên, K.M. Feng 5214 (KUN0690504); inset: aggregate fruit (immature). C. China, Yunnan, Dêqên, L. Xie & J.F. Mao 133 (PE01569465); inset: aggregate fruit. D. China, Yunnan, Weixi, K.M. Feng 4833 (KUN0690086); inset: aggregate fruit.
FIGURE. Thalictrum hengduanshanense in the wild (Dêqên in northwestern Yunnan, China, the type locality). A. Habitat. B. Habit. C. Roots. D. Portion of stem. E. Leaf (left: adaxial side; right: abaxial side). F. Leaflet (adaxial side). G. Portion of adaxial side of leaflet. H. Portion of abaxial side of leaflet. I. Flower. J. Sepal (left: adaxial side; right: abaxial side). K. Stamens. L. Carpels. M. Aggregate fruits. N. Achenes (immature). Photographed by Y.P. Zeng. in Thalictrum hengduanshanense and T. longistipitatum (Ranunculaceae), two new species from southeastern Xizang and northwestern Yunnan, China
FIGURE. Thalictrum hengduanshanense in the wild (Dêqên in northwestern Yunnan, China, the type locality). A. Habitat. B. Habit. C. Roots. D. Portion of stem. E. Leaf (left: adaxial side; right: abaxial side). F. Leaflet (adaxial side). G. Portion of adaxial side of leaflet. H. Portion of abaxial side of leaflet. I. Flower. J. Sepal (left: adaxial side; right: abaxial side). K. Stamens. L. Carpels. M. Aggregate fruits. N. Achenes (immature). Photographed by Y.P. Zeng.
FIGURE. Thalictrum wangii in the wild (Lijiang in northwestern Yunnan, China, the type locality). A. Habitat. B. Habit. C. Roots. D. Portion of stem. E. Leaf (left: adaxial side; right: abaxial side). F. Leaflet (adaxial side). G. Portion of adaxial side of leaflet. H. Portion of abaxial side of leaflet. I. Flower. J. Sepal (left: adaxial side; right: abaxial side). K. Stamens. L. Carpels. M. Aggregate fruit. N. Achenes (immature). Photographed by Y.P. Zeng. in Thalictrum hengduanshanense and T. longistipitatum (Ranunculaceae), two new species from southeastern Xizang and northwestern Yunnan, China
FIGURE. Thalictrum wangii in the wild (Lijiang in northwestern Yunnan, China, the type locality). A. Habitat. B. Habit. C. Roots. D. Portion of stem. E. Leaf (left: adaxial side; right: abaxial side). F. Leaflet (adaxial side). G. Portion of adaxial side of leaflet. H. Portion of abaxial side of leaflet. I. Flower. J. Sepal (left: adaxial side; right: abaxial side). K. Stamens. L. Carpels. M. Aggregate fruit. N. Achenes (immature). Photographed by Y.P. Zeng.
Reversal data during aggregation of Myxococcus xanthus
<p>Reversal data of the bacterium Myxococcus xanthus during<br>the formation of aggregates under starvation conditions. The data is<br>separated into two files based on whether an individual bacterium is<br>moving towards or away from the nearest aggregate. Space is measured<br>in micrometers and time in minutes. Each file includes the length of<br>time before the bacteria changes directions, the speed during that<br>period, the distance from the nearest aggregate, the bearing angle<br>with respect to that aggregate, and the local cellular density when a<br>bacterium starts moving in a new direction.<br><br>This data was obtained by processing images from the Welch Lab at<br>Syracuse University. These images are published in "Cell behaviors<br>underlying Myxococcus xanthus aggregate dispersal" (DOI:<br><a href="https://doi.org/10.1128/msystems.00425-23" target="_blank" rel="noopener noreferrer">https://doi.org/10.1128/msystems.00425-23</a>). The associated dataset is<br><a href="../records/8166434" target="_blank" rel="noopener noreferrer">https://<span>zenodo</span>.org/records/8166434</a>.</p>
Intercomparison of Convective-Aggregation States with two Cloud Resolving Models: DATASET
<p>Radiative-Convective Equilibrium (RCE) is an important modeling paradigm for the tropical atmosphere. In this paradigm, cloud clustering can occur spontaneously, affecting the energy budget of the atmosphere. Here, two models, run in RCE, exhibiting this convective aggregation have been compared with each other and with the results of the Radiative-Convective Equilibrium Model Intercomparison Project (RCEMIP). The two models studied, the SAM (System for Atmospheric Modeling) and the ARPS (Advanced Regional Prediction System), are different in the physical and numerical formulation, allowing us to compare the sensitivity to processes related to the phenomenon of convective organization. In General, the two models present similarities in what concerns precipitation, warming, and drying of the atmosphere and anvil cloud area reduction. All these factors are also within the spread of the RCEMIP values. However, the two models differ both in the convective organization feedback and in the degree of organization. SAM is strongly organized and ARPS is weakly organized. SAM achieves convective organization through clouds-radiative feedback and ARPS achieves it through moisture-convection feedback. These differences can be traced back to the interaction between the microphysics and the sub-cloud layer properties. We suggest that when studying climate sensitivity, climate models should include both types of convective organization mechanisms.</p>
Data From: Active sinking particles: Flow and transport dynamics due to sessile suspension feeders on sinking aggregates
<p>Sinking or sedimentation of biological aggregates plays a critical role in carbon sequestration in the ocean and in vertical material fluxes in waste-water treatment plants. In both these contexts, the sinking aggregates are "active," since they are biological hot-spots and are densely colonized by microorganisms including bacteria and sessile protists, some of which generate feeding currents. However, the effect of these feeding currents on the sinking rates, trajectories, and mass transfer to these "active sinking particles," has not previously been studied. Here we use a novel scale-free vertical-tracking microscope (a.k.a. Gravity Machine, Krishnamurthy et al. "Scale-free vertical tracking microscopy." Nature Methods (2020)) to follow model sinking aggregates (agar spheres) with attached protists (<em>Vorticella convallaria</em>), sinking over long distances while simultaneously measuring local flows. We find that activity due to attached \vortc causes significant changes to the flow around aggregates in a dynamic manner and reshapes mass transport boundary layers. Furthermore, we find that activity-mediated local flows along with sinking modify the encounter and plume cross-sections of the aggregate and induce sustained aggregate rotations. Overall our work shows the important role of biological activity in shaping the near-field flows around aggregates with potentially important effects on aggregate fate and material fluxes.</p>
Convolution, aggregation and attention based deep neural networks for accelerating simulations in mechanics [Dataset]
<p>Supplementary data for 'Convolution, aggregation and attention based deep neural networks for accelerating simulations in mechanics'. </p>
FIGURE 3 in Further insights into the Stellaria media aggregate (Caryophyllaceae, Alsinoideae, Alsineae) in Africa: first reports of S. ruderalis in North Africa and S. cupaniana in Tunisia, with nomenclatural notes on the name Alsine cupaniana
FIGURE 3. Stellaria cupaniana in Tunisia. A. Plant habit in one of its natural habitats. B. Summital stems. C. Inflorescence. D. Seed form and shape, scale bar: 1 mm. Photographs by R. El Mokni in Nabeul region (Cap-Bon of Tunisia), 22 March 2021.
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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.