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Fig. 2 in Compositional change in fish assemblages along the Andean piedmont - Llanos floodplain gradient of the río Portuguesa, Venezuela
Fig. 2. DCA ordination of species assemblages at survey sites in three different elevational zones along the longitudinal gradient of the Portuguesa River, Venezuela: Camaguan, 50-100 m (open squares); Middle, 100-150 m (filled circles); and Upper, 150-200 m (open triangles). The three regions were significantly different in assemblage composition (MANOVA, p <0.0001).
Fig.1 in Compositional change in fish assemblages along the Andean piedmont - Llanos floodplain gradient of the río Portuguesa, Venezuela
Fig.1. Map of Venezuela with inset showing locations of survey sites (n=28, filled circles) along the río Portuguesa elevational gradient.
Fig. 3 in Vegetation of Paektu Mt. alpine tundra and changes of species composition in its ecotone
Fig. 3. Numerical classification of 42 relevés (20 ✕ 20m) of alpine tundra and adjacent larch forest vegetation from Paektu Mt. (North Korea). JACCARD's coefficient and β-flexible clustering method was used (β= -0.25). Explanations: see page 7–8.
Fig. 6 in Vegetation of Paektu Mt. alpine tundra and changes of species composition in its ecotone
Fig. 6. Light-park larch forest (Rhododendro aurei-Laricetum olgensis) – ground layer contents species of alpine tundra, e.g. Rhododendron aureum, Bupleurum euphorbioides, and Juniperus sibirica (photo I. Jarolímek).
Fig. 5 in Vegetation of Paektu Mt. alpine tundra and changes of species composition in its ecotone
Fig. 5. Timber-line on Paektu Mt. – contact zone of alpine tundra and light-park larch forest (Rhododendro aurei-Laricetum olgensis) (photo I. Jarolímek).
Figure 8 in Ultrastructure and mineral composition of serpulid tubes (Polychaeta, Annelida)
Figure 8. Pomatoceros triqueter, polished section of the tabula, fine crystal homogeneous structure, treated with 1% acetic acid for 2 min. Abbreviations: cryst, crystals; orgm, organic matrix.
Figure 7. A–B in Ultrastructure and mineral composition of serpulid tubes (Polychaeta, Annelida)
Figure 7. A–B, Serpula crenata, inner tube layer. A, cross section, fresh fracture surface, showing the crystals of irregularly oriented prismatic structure completely embedded into the organic matrix. B, polished cross section, treated with GA solution for 5 min; note that the organic matrix is partially decomposed. C, Marifugia cavatica, longitudinal section, fresh fracture surface, inner mineral irregulary oriented prismatic structure, and inner organic tube layer. D, Spirobranchus giganteus, tube lumen, inner organic layer; note the mesh-like composition of the layer. E, Hydroides dianthus, polished longitudinal section, treated with 1% acetic acid for 2 min, showing transition between irregularly oriented prismatic and lamello-fibrillar structure. F, Laminatubus alvini, polished cross section, treated with 1% acetic acid for 2 min, showing transition between inner irregularly oriented prismatic and outer homogeneous angular crystal structure. Abbreviations: cryst, crystals; exter, exterior; HAC, homogeneous angular crystal structure; IOP, irregularly oriented prismatic structure; LF, lamello-fibrillar structure; orgm, organic matrix; orgl, inner organic layer of the tube.
Figure 5. A–B in Ultrastructure and mineral composition of serpulid tubes (Polychaeta, Annelida)
Figure 5. A–B, Vitreotubus digeronimoi, simple prismatic structure, polished, and treated with GA solution for 5 min. A, cross section. B, longitudinal section. C–D, Pomatoceros triqueter, lamello-fibrillar structure. C, cross section. D, longitudinal section. E–F, Floriprotis sabiuraensis, spherulitic lamello-fibrillar structure, inner tube layer. E, cross section. F, longitudinal section. Samples (C–F) were treated with 1% acetic acid for 2 min. Abbreviations: exter, exterior; ginc, growth increments.
Figure 4. A–B in Ultrastructure and mineral composition of serpulid tubes (Polychaeta, Annelida)
Figure 4. A–B, Protula diomedeae, semi-ordered irregularly oriented prismatic structure. A, cross section. B, longitudinal section. C–D, Pyrgopolon ctenactis, semi-ordered spherulitic irregularly oriented prismatic structure, outer tube layer. C, cross section. D, longitudinal section. E–F, Crucigera websteri, contact of inner tube layer with spherulitic prismatic structure, and third tube layer from outside with lamello-fibrillar structure. E, cross section. F, longitudinal section. All samples were polished and treated with 1% acetic acid for 2 min. Abbreviations: exter, exterior; ginc, growth increments; LF, lamello-fibrillar structure; osh, organic sheet; SPHP, spherulitic prismatic structure.
Figure 3. A–B in Ultrastructure and mineral composition of serpulid tubes (Polychaeta, Annelida)
Figure 3. A–B, Neovermilia falcigera, irregularly oriented platy structure, outer tube layer. A, cross section. B, longitudinal section. C–D, Bathyvermilia langerhansi, homogeneous angular crystal structure, outer tube layer. C, cross section. D, longitudinal section. E–F, Pomatostegus stellatus, homogeneous rounded crystal structure. E, cross section. F, longitudinal section. All samples were polished and treated with 1% acetic acid for 2 min. Abbreviations: exter, exterior.
Figure 2. A–B in Ultrastructure and mineral composition of serpulid tubes (Polychaeta, Annelida)
Figure 2. A–B, Pseudovermilia madracicola, spherulitic irregularly oriented prismatic structure. A, cross section. B, longitudinal section. C–E, Crucigera zygophora. C, transition between irregularly oriented prismatic and spherulitic irregularly oriented prismatic structure in cross section. D, spherulitic irregularly oriented prismatic structure, cross section. E, spherulitic irregularly oriented prismatic structure, longitudinal section. F, Spiraserpula caribensis, spherulitic irregularly oriented prismatic structure. All sections were polished and treated with 1% acetic acid for 2 min. Abbreviations: IOP, irregularly oriented prismatic structure; SIOP, spherulitic irregularly oriented prismatic structure.
Figure 1. A–B in Ultrastructure and mineral composition of serpulid tubes (Polychaeta, Annelida)
Figure 1. A–B, Apomatus globifer, irregularly oriented prismatic structure, polished and treated with GA (see Material & Methods) solution for 5 min. A, cross section. B, longitudinal section. C–E, Marifugia cavatica, polished, and treated with 1% acetic acid for 2 min. C, cross section, two-layered tube with irregularly oriented prismatic structure. D, longitudinal section, outer tube layer, with a low content of homogeneous carbonate cement. E, longitudinal section, inner tube layer, with a high content of homogeneous carbonate cement. F, Semivermilia crenata, irregularly oriented prismatic structure with a high content of homogeneous carbonate cement, polished cross section, treated with GA solution for 5 min. Abbreviations: cryst, crystals; exter, exterior; hc, homogeneous carbonate cement.
Figure 6. A–D in Ultrastructure and mineral composition of serpulid tubes (Polychaeta, Annelida)
Figure 6. A–D, Spirobranchus giganteus, polished, and treated with GA solution for 5 min. A, outer tube layer with oriented fibrillar structure, cross section. B, outer tube layer, oriented fibrillar structure, longitudinal section. C, detail of (B), showing the close-up of the organic sheet. D, outer layer with spherulitic irregularly oriented prismatic structure; note the epitaxial growth of prisms through several organic sheets. E, Ficopomatus enigmaticus, polished longitudinal section, spherulites in irregularly oriented prismatic structure, treated with 1% acetic acid for 2 min. F, Placostegus tridentatus, calcitic spherulite, longitudinal section of the tube with simple prismatic structure. Abbreviations: exter, exterior; ginc, growth increments; osh, organic sheet; pr, prismatic crystals; SPH, spherulite.
Figure 10 in Ultrastructure and mineral composition of serpulid tubes (Polychaeta, Annelida)
Figure 10. Evolution of serpulid tube ultrastructures. Phylogenetic relationships of serpulid genera derived from Kupriyanova et al. (2006), Bayesian majority consensus phylogram of the combined molecular and morphological data set. Numbers denote the presence of the ultrastructures in a particular genus: 1, unoriented structures; 2, semi-oriented structures; 3, oriented prismatic structures; 4, oriented complex structures.
OlSiFaComp : A database for Olea: Olive Self-Incompatibility Flower Allelic Composition
<p><strong>Introduction</strong> : Data on olive cross and selfing studies were numerous and dispersed in literature. Varieties were list in lines, and each line correspond to one data – bag, pollen test, paternity tests, ...To compare data in bags standardization was achieved based on 100 hermaphroditic flowers.</p> <p><strong>Materials and methods</strong> : Data from publications were recorded keeping the name of origin for each variety. Varieties in pair wise combinations in crosses enabled to decipher the S-allele pair (Breton and Bervillé 2012, Farinelli et al. 2014) leading to attribute the PASI pair. The G group (Saumitou-Laprade et al. 2017) was recorded from Mariotti et al. 2021.</p> <p><strong>Results</strong> : The DSI pair and the PASI pair were introduced and sorting data by screening G1xG2 (1 for fruit) and G2xG1 (1) whereas by screening G1xG1 (0) and G2XG2 (0) show that all crosses display fruit. The DSSM reconciles DSI and PASI to explain Self-incompatibility. Selfing was shown appearing when crosses were 1-0 or 0-1, but not when 1-1, whereas some expected 0-0 combinations lead to fruit. Moreover, paternity tests (column embryo) revealed most of the time a father compatible in DSI , but incompatible in PASI, this is due to DS-D, that shows compatible pollen is insufficient.</p> <p>The database is useful to check whether the variety has already been studied for SI. It enables to check the homogeneity of cross data in literature.</p>
Differences in bee community composition between restored and remnant prairies are more strongly linked to forb community differences than landscape differences
<p>1. Grassland restoration is an important tool for conserving bee biodiversity within agricultural landscapes. Restorations foster increases in local bee abundance and α-diversity, however, these measures are insufficient for understanding if remnant communities are being conserved. We compared native bee α-diversity, β-diversity, and community composition between restored and remnant prairies in Minnesota, USA. We then investigated two potential drivers of bee community dissimilarity between restored and remnant prairies: proportion of agricultural land surrounding a restoration and differences in floral community between restored and remnant prairies.</p> <p>2. We selected ten restored prairies that lie along a gradient of increasing agricultural land cover, ranging from 20–85% of surrounding land in agricultural production. We paired each restoration with a nearby prairie remnant and sampled bee and floral communities concurrently in each restoration-remnant pair. We quantified bee and forb α-diversity, community composition, β-diversity, and levels of dissimilarity between restoration-remnant pairs along the gradient of agricultural development. Additionally, we quantified differences in the community weighted mean between restored and remnant prairies for two bee traits, oligolecty and tongue length, to investigate how differences in floral community between restored and remnant prairies may influence bee community composition.</p> <p>3. While bee α-diversity between restored and remnant prairies was similar, bee composition between restorations and remnants were significantly different with restorations being more homogenous than remnants. Differences in bee community composition and β-diversity were not statisticlly related to agricultural landscapes or floral community dissimilarity, however, we found a significantly higher proportion of oligolectic bees in remnant prairies. This difference in oligolectic bees was likely related to the absence of important host plants in restorations<i>.</i></p> <p>4. <i>'Synthesis and application'</i>: Prairie restorations should seek to provide diverse floral resources that are of similar composition to remnant prairies. Specifically, providing important floral host plants for pollen specialist bees could improve restorations' ability to conserve prairie remnant bee communities.</p>
Data for "Training data composition affects performance of protein structure analysis algorithms" by A. Derry, K. A. Carpenter, & R. B. Altman
<p><strong>Description</strong></p> <p>This repository contains all data used in "Training data composition affects performance of protein structure analysis algorithms", published in the Pacific Symposium on Biocomputing 2022 by A. Derry, K. A. Carpenter, & R. B. Altman. </p> <p>The data consists of the following files:</p> <ul> <li>ema_zenodo_data.tar.gz: train, validation, and test splits for Estimation of Model Accuracy task, in LMDB format</li> <li>design_zenodo_data.tar.gz: train, validation, and test splits for Protein Sequence Design task, in JSON format</li> <li>enz_cat_res_zenodo_data.tar.gz: train, validation, and test splits for Catalytic Residue and Enzyme Prediction task, in TF record format</li> </ul> <p>Details on dataset construction can be found in our paper and dataloaders can be found in our <a href="https://github.com/awfderry/ml-structure-bias">Github repo</a>.</p> <p><strong>Reference</strong></p> <p>A. Derry*, K. A. Carpenter*, & R. B. Altman, "Training data composition affects performance of protein structure analysis algorithms", 2021.</p> <p><strong>Dataset References</strong></p> <p>Datasets used were derived from the following works:</p> <p>Kryshtafovych, A., Schwede, T., Topf, M., Fidelis, K., & Moult, J. (2019). Critical assessment of methods of protein structure prediction (CASP)—Round XIII. In <em>Proteins: Structure, Function and Bioinformatics</em> (Vol. 87, Issue 12, pp. 1011–1020). https://doi.org/10.1002/prot.25823</p> <p>Ingraham, J., Garg, V. K., Barzilay, R., & Jaakkola, T. (2019). <em>Generative Models for Graph-Based Protein Design</em>. https://openreview.net/pdf?id=SJgxrLLKOE</p> <p>Furnham, N., Holliday, G. L., de Beer, T. A. P., Jacobsen, J. O. B., Pearson, W. R., & Thornton, J. M. (2014). The Catalytic Site Atlas 2.0: cataloging catalytic sites and residues identified in enzymes. <em>Nucleic Acids Research</em>, <em>42 </em>(Database issue), D485–D489.</p>
Social vulnerability to flooding in Ecuador : input variables, PCA vs Expert composite indices
<p><strong>Social vulnerability indices are used to better understand and predict the consequences of disasters, and support the development of improved disaster management policies. This research specifically supports the Ecuadorian Red Cross in generating a flood-specific social vulnerability index to inform flash flood early action protocol.</strong></p> <p>The dataset presents the results from the analysis of the social vulnerability to flooding in Ecuador, from individual input variables to the composite indices outputs. The results are available at the Parroquia level in Ecuador (admin level 3), for 1032 Parroquia excluding the Galapagos Islands.</p> <ul> <li>The dataset comprises, for each Parroquia, the estimation of <strong>15 variables characterizing the social vulnerability to flooding specific to Ecuador context</strong>. The variables are selected from literature review and consultation with Ecuadorian Red Cross disaster practitioners : <em>Disability, Poverty incidence, Gini Index, Agricultural labor share, Vectorborne disease incidence, Waterborne disease incidence, Social Security affiliation, Education level, Sanitation, Driking water access, Power access, Road travel time, Wall structure, Mobile access and Internet access.</em> All variables are normalized from 0 to 1, directed toward increasing vulnerability, and renamed accordingly.</li> <li>In addition, the <strong>Administrative level names, PCODE, calculated Area, population density,</strong> as well as related <strong>sub-regions</strong> are also referenced.</li> <li>Individual variables are integrated into <strong>composite vulnerability indices</strong>, using two different approaches: i) the Principal Component Analysis approach, using the first component <strong>PCA(n=1) </strong>and the first 5 components <strong>PCA(n=5)</strong> separately ; ii) the <strong>expert judgement weighting</strong> of the variables. The output composite indices, normalized from 0 to 1 are presented in 3 separated columns.</li> </ul> <p> </p>
Local fruit availability and en route wind conditions are poor predictors of bird abundance and composition during fall migration in coastal Yucatán Peninsula
<p>In migratory stopover habitats, bird abundance and composition change on a near daily basis. On any given day, the local bird community should reflect local environmental conditions but also the environments that birds encountered previously along their migratory route. For example, during fall migration, the coast of the Yucatán Peninsula in Mexico receives birds that have just crossed the Gulf of Mexico and their abundance and composition may be associated with regional factors such as wind conditions experienced on previous dates but also local factors such as fruit availability. Thus, we used three data sets to quantify the influence of wind and fruit on near daily variation in bird abundance and composition. Our bird data consists of the number of individuals per species captured using mist nets for two coastal national parks in the Yucatán Peninsula during fall migration in 2016 and 2017. The data is provided daily, as are the "net-hours," i.e., the sum of the hours each net was open summed across nets. Thus, we analyzed bird captures standardized by net-hours. Our fruit data consists of the number of unripe and ripe fruits per species counted on each side of each mist net lane at various points during fall migration. Our wind data consists of the wind costs birds arriving at our sites would have experienced when departing the north coast of the Gulf of Mexico two days prior to their arrival. Wind cost reflects wind speed and direction and it was calculated using the wind.dl_2 function in the rWind package. The wind costs are averaged across the entire US Gulf coastline. We used Moran eigenvector maps to quantify the temporal structure of the bird, wind, and fruit data and we partitioned the variance in the bird data into the components explainable by wind or fruit, the temporal structure of wind or fruit, and temporal structure independent of wind or fruit. After running the analysis, we did not find a strong association between daily changes in bird abundance or community composition with wind conditions and ripe fruit availability. Thus, despite wind and fruit being known to be important to individual birds (influencing stopover duration and departure decisions), their effects might not scale up to be drivers of population and community-level variation.</p>
Experimental investigation of composite materials for sliding friction dampers: data, plots, photos and videos of the tests
<p><strong>Folder DATA</strong></p> <p>This folder contains the data acquired by testing the friction pads M1, M2, M3, M4 and M5 under the following loading protocols:</p> <ul> <li>Linear static loading (M);</li> <li>Cyclic loading with constant amplitude (CA);</li> <li>Cyclic loading with decreasing amplitude at low rate (DA);</li> <li>Cyclic loading with increasing amplitude at low rate (IA);</li> <li>Cyclic loading with increasing amplitude at moderate rate (IA-H);</li> <li>Cyclic loading with increasing amplitude at high rate (IA-HH);</li> <li>Pulse-like loading protocol (PL);</li> <li>Mainshock-aftershock protocol (MS-AS): mainshock (MS), first aftershock (AS1) and second aftershock (AS2).</li> </ul> <p>The data include:</p> <ul> <li><em>Time</em>: time (unit: second);</li> <li><em>F</em>: axial force experienced by the sliding friction damper (unit: kN);</li> <li><em>N_bolt</em>: bolt preload (unit: kN);</li> <li><em>mu</em>: friction coefficient of the considered pad (unit: dimensionless);</li> <li><em>delta</em>: axial displacement experienced by the sliding friction damper (unit: mm);</li> <li><em>Cum. delta</em>: total cumulative displacement experienced by the sliding friction damper (unit: mm);</li> <li><em>Cum. E</em>: total cumulative energy dissipated by the sliding friction damper (unit: kJ);</li> <li><em>max Tin</em>: maximum temperature tracked close to the sliding interface (unit: Celsius);</li> <li><em>Tout</em>: temperature tracked at the surface of the inner slotted plate (unit: Celsius).</li> </ul> <p> The data are organized as follows:</p> <ul> <li>Folder <strong>T100</strong></li> </ul> <p>This folder contains the data acquired under the linear static loading protocol (M) for a tightening torque of 100 Nm. Each EXCEL file <strong>T100_M_Y</strong> saved in the folder <strong>T100</strong> contains the data obtained by testing the friction pad Y (Y = M1, M2, M3, M4, M5) under the loading protocol M.</p> <ul> <li>Folder <strong>T200</strong></li> </ul> <p>This folder contains the data acquired under the linear static loading protocol (M) for a tightening torque of 200 Nm. Each EXCEL file <strong>T200_M_Y</strong> saved in the folder <strong>T200</strong> contains the data obtained by testing the friction pad Y (Y = M1, M2, M3, M4, M5) under the loading protocol M.</p> <ul> <li>Folder <strong>Fs150</strong></li> </ul> <p>This folder contains the data acquired for an expected slip load of 150 kN. Each subfolder <strong>Fs150_X</strong> contains the data obtained under the loading protocol X (X = M, CA, DA, IA, IA-H). Each EXCEL file <strong>Fs150_X_Y</strong> saved in the subfolder <strong>Fs150_X</strong> contains the data obtained by testing the friction pad Y (Y = M1, M2, M3, M4, M5) under the loading protocol X.</p> <ul> <li>Folder <strong>Fs300</strong></li> </ul> <p>This folder contains the data acquired for an expected slip load of 300 kN. Each subfolder <strong>Fs300_X</strong> contains the data obtained under the loading protocol X (X = M, CA, DA, IA, IA-H, IA-HH, PL, MS, AS1, AS2). Each EXCEL file <strong>Fs300_X_Y</strong> saved in the subfolder <strong>Fs300_X </strong>contains the data obtained by testing the friction pad Y (Y = M1, M2, M3, M4, M5) under the loading protocol X.</p> <p><strong>Folder PHOTOS</strong></p> <p>This folder contains the following photos:</p> <ul> <li>Folder <strong>01_FrictionDamper</strong>: photos of the sliding friction damper and its components.</li> <li>Folder <strong>02_Instrumentation</strong>: photos of the instrumentation used for the data acquisition during the experimental campaign.</li> <li>Folder <strong>03_FrictionPads</strong>: <ul> <li>Subfolder <strong>BeforeTesting</strong>: photos of the friction pads before the experimental campaign.</li> <li>Subfolder <strong>AfterTesting</strong>: photos of the friction pads at the end of each loading protocol. The photo <strong>Fs150vs300_X_Y</strong> shows the condition of the pad Y (Y = M1, M2, M3, M4, M5) at the end of the loading protocol X (X = M, CA, DA, IA, IA-H, IA-HH, PL, MS, AS1, AS2) performed for an expected slip load of 150 kN and 300 kN (the pads shown at the top of each photo are those tested for an expected slip load of 150 kN). Similarly, the photo <strong>Fs300_X_Y</strong> shows the condition of the pad Y at the end of the loading protocol X performed for an expected slip load of 300 kN.</li> </ul> </li> <li>Folder <strong>04_Tests</strong>: photos taken from the east and north side of the sliding friction damper during the loading protocols that caused the fracture of the pads <ul> <li>Subfolder <strong>Fs150</strong>: photos taken during the tests conducted for an expected slip load of 150 kN. Each folder <strong>Fs150_X_Y</strong> contains the photos taken by testing the pad Y (Y = M1, M2, M4, M5) during the loading protocol X (X = CA, DA, IA, IA-H).</li> <li>Subfolder <strong>Fs300</strong>: photos taken during the tests conducted for an expected slip load of 300 kN. Each folder <strong>Fs300_X_Y</strong> contains the photos taken by testing the pad Y (Y = M1, M2, M4, M5) during the loading protocol X (X = CA, IA, IA-H). A video was recorded live during the loading protocols IA-HH, PL, MS, AS1 and AS2 (see folder <strong>VIDEOS</strong>).</li> </ul> </li> </ul> <p><strong>Folder PLOTS</strong></p> <p>This folder contains the following MATLAB plots:</p> <ul> <li><em>Force-Disp</em>: axial force – axial displacement response of the sliding friction damper;</li> <li><em>Preload-CumDisp</em>: bolt preload as a function of the total cumulative displacement experienced by the sliding friction damper;</li> <li><em>FrictionCoeff-CumDisp</em>: friction coefficient of the considered pad as a function of the total cumulative displacement experienced by the sliding friction damper;</li> <li><em>Temp-CumDisp</em>: rise in temperature as a function of the total cumulative displacement experienced by the sliding friction damper (the temperature values reported for the expected slip load of 150 kN correspond to “max Tin”, whereas those reported for the expected slip load of 300 kN correspond to “Tout”);</li> <li><em>FrictionCoeff-LoadingHistoryEffect</em>: friction coefficient of the considered pad as a function of the total cumulative displacement experienced by the sliding friction damper under different loading protocols;</li> <li><em>FrictionCoeff-RateEffect</em>: friction coefficient of the considered pad as a function of sliding velocity experienced by the sliding friction damper under different loading protocols;</li> <li><em>FrictionCoeff-TempEffect</em>: friction coefficient of the considered pad as a function of the rise in temperature tracked during different loading protocols;</li> <li><em>FrictionCoeff-PressureDependency</em>: mean and standard deviation of the friction coefficient of the considered pad obtained for different expected slip loads and loading protocols;</li> <li><em>FrictionCoeffStaticDynamic-PressureDependency</em>: mean of the static and dynamic friction coefficient of the considered pad obtained for different expected slip loads and loading protocols.</li> </ul> <p>The MATLAB plots are organized as follows:</p> <ul> <li>Folder <strong>T200</strong></li> </ul> <p>The MATLAB plots saved in this folder illustrate the data obtained by testing the friction pads M1, M2, M3, M4 and M5 under the linear static loading protocol (M) for a tightening torque of 200 Nm.</p> <ul> <li>Folder <strong>Fs150 and Fs300</strong></li> </ul> <p>The MATLAB plots saved in this folder illustrate the data obtained by testing the friction pads M1, M2, M3, M4 and M5 under the considered loading protocol (M, CA, DA, IA, IA-H, IA-HH, PL, MS-AS) for an expected slip load of 150 kN and 300 kN.</p> <p><strong>Folder VIDEOS</strong></p> <p>This folder contains the following videos:</p> <ul> <li>Folder <strong>T100</strong>: videos created from the photos taken during the tests conducted for a tightening torque of 100 Nm under the linear static loading protocol (M). The videos <strong>T100_M_Y_East</strong> and <strong>T100_M_Y_North</strong> show the test conducted on the pad Y (Y = M1, M2, M3, M4, M5) from the east and north side of the sliding friction damper respectively.</li> <li>Folder <strong>T200</strong>: videos created from the photos taken during the tests conducted for a tightening torque of 200 Nm under the linear static loading protocol (M). The videos <strong>T200_M_Y_East</strong> and <strong>T200_M_Y_North</strong> show the test conducted on the pad Y (Y = M1, M2, M3, M4, M5) from the east and north side of the sliding friction damper respectively.</li> <li>Folder <strong>Fs150</strong>: videos created from the photos taken during the tests conducted for an expected slip load of 150 kN. The videos <strong>Fs150_X_Y_East</strong> and <strong>Fs150_X_Y_North</strong> show the loading protocol X (X = M, CA, DA, IA, IA-H) applied to the pad Y (Y = M1, M2, M3, M4, M5) from the east and north side of the sliding friction damper respectively.</li> <li>Folder <strong>Fs300</strong>: videos created from the photos taken during the tests conducted for an expected slip load of 300 kN. The videos <strong>Fs300_X_Y_East</strong> and <strong>Fs300_X_Y_North</strong> show the loading protocol X (X = M, CA, DA, IA, IA-H) applied to the pad Y (Y = M1, M2, M3, M4, M5) from the east and north side of the sliding friction damper respectively. The videos obtained for the loading protocols IA-HH, PL, MS, AS1 and AS2 were recorded live during each test.</li> </ul>
ScienceDex guides
Understand access before you commit
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.