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694 results for “stiffness”
Stiffness of randomly sampled stainless steel frames under gravity and gravity plus wind load scenarios
<p>Data was generated using the general purpose finite element software ABAQUS and performing advanced nonlinear analyses. The database is comprised of vertical and lateral system stiffness values corresponding to different random samples of six different nominal stainless steel frames under gravity and gravity plus wind load combinations. The values of the random variable assignments are given for each case. </p> <p>The full details of the finite element model can be found in: Arrayago, I.; Rasmussen, K.J.R. Reliability of stainless steel frames designed using the Direct Design Method in serviceability limit states. Journal of Constructional Steel Research 196, 107425, 2022. DOI: https://doi.org/10.1016/j.jcsr.2022.107425</p> <p>The data included in the dataset corresponds to the vertical & lateral stiffness of each frame under different load conditions.</p> <p>Although the data has been generated using the finite element software ABAQUS, no special software is required to read or interpret the data.</p>
Cisplatin enhances cell stiffness and decreases invasiveness rate in prostate cancer cells by actin accumulation: Confocal and atomic force microscopy
<p><strong>Summary</strong></p> <p>Dataset of imaging data related to the publication Raudenska, M., Kratochvilova, M., Vicar, T., Gumulec, J., Balvan, J., Polanska, H. Pribyl, J. & Masarik, M.:Cisplatin enhances cell stiffness and decreases invasiveness rate in prostate cancer cells by actin accumulation. <em>Scientific Reports </em><strong>2019, </strong>9, 1660</p> <p>This dataset includes image data of <em>atomic force microcopy</em> (Young modulus) and <em>confocal microscopy</em>(staining of F-actin and β-tubulin) of prostate cell lines PNT1A, 22Rv1, and PC-3. </p> <p><strong>Materials and Methods</strong></p> <p><em>Cells, cell culture conditions</em></p> <p>Cells confluent up to 50–60% were washed with a FBS-free medium and treated with a fresh medium with FBS and required antineoplastic drug concentration (IC50 concentration for the particular cell line). The cells were treated with 93 µM (PC-3), 38 µM (PNT1A), and 24 µM (22Rv1) of cisplatin (Sigma-Aldrich, St. Louis, Missouri), respectively. IC50 concentrations used for treatment with docetaxel (Sigma-Aldrich, St. Louis, Missouri) were 200nM for PC-3, 70nM for PNT1A, and 150nM for 22Rv1. </p> <p><em>Long-term zinc (II) treatment of cell cultures</em></p> <p>Cells were cultivated in the constant presence of zinc(II) ions. Concentrations of zinc(II) sulphate in the medium were increased gradually by small changes of 25 or 50 µM. The cells were cultivated at each concentration no less than one week before harvesting and their viability was checked before adding more zinc. This process was used to select zinc resistant cells naturally and to ensure better accumulation of zinc within the cells (accumulation of zinc is usually poor during the short-term treatment of prostate cancer cells). Total time of the cultivation of cell lines in the zinc(II)-containing media exceeded one year. Resulting concentrations of zinc(II) in the media (IC50 for the particular cell line) were 50 µM for the PC-3 cell line, 150 µM for the PNT1A cell line, and 400 µM for the 22Rv1 cell line. The concentrations of zinc(II) in the media and FBS were taken into account. </p> <p><em>Actin and tubulin staining</em></p> <p>β-tubulin was labeled with anti- β tubulin antibody [EPR1330] (ab108342) at a working dilution of 1/300. The secondary antibody used was Alexa Fluor® 555 donkey anti-rabbit (ab150074) at a dilution of 1/1000. Actin was labeled with Alexa Fluor™ 488 Phalloidin (A12379, Invitrogen); 1 unit per slide. For mounting Duolink® In Situ Mounting Medium with DAPI (DUO82040) was used. The cells were fixed in 3.7% paraformaldehyde and permeabilized using 0.1% Triton X-100. </p> <p><em>Confocal microscopy</em></p> <p>The microscopy of samples was performed at the Institute of Biophysics, Czech Academy of Sciences, Brno, Czech Republic. Leica DM RXA microscope (equipped with DMSTC motorized stage, Piezzo z-movement, MicroMax CCD camera, CSU-10 confocal unit and 488, 562, and 714 nm laser diodes with AOTF) was used for acquiring detailed cell images (100× oil immersion Plan Fluotar lens, NA 1.3). Total 50 Z slices was captured with Z step size 0.3 μm.</p> <p><em>Atomic force microscopy</em></p> <p>We used the bioAFM microscope JPK NanoWizard 3 (JPK, Berlin, Germany) placed on the inverted optical microscope Olympus IX‑81 (Olympus, Tokyo, Japan) equipped with the fluorescence and confocal module, thus allowing a combined experiment (AFM‑optical combined images). The maximal scanning range of the AFM microscope in X‑Y‑Z range was 100‑100‑15 µm. The typical approach/retract settings were identical with a 15 μm extend/retract length, Setpoint value of 1 nN, a pixel rate of 2048 Hz and a speed of 30 µm/s. The system operated under closed-loop control. After reaching the selected contact force, the cantilever was retracted. The retraction length of 15 μm was sufficient to overcome any adhesion between the tip and the sample and to make sure that the cantilever had been completely retracted from the sample surface. Force‑distance (FD) curve was recorded at each point of the cantilever approach/retract movement. AFM measurements were obtained at 37°C (Petri dish heater, JPK) with force measurements recorded at a pulling speed of 30 µm/s (extension time 0.5 sec).</p> <p>The Young's modulus (E) was calculated by fitting the Hertzian‑Sneddon model on the FD curves measured as force maps (64x64 points) of the region containing either a single cell or multiple cells. JPK data evaluation software was used for the batch processing of measured data. The adjustment of the cantilever position above the sample was carried out under the microscope by controlling the position of the AFM‑head by motorized stage equipped with Petri dish heater (JPK) allowing precise positioning of the sample together with a constant elevated temperature of the sample for the whole period of the experiment. Soft uncoated AFM probes HYDRA-2R-100N (Applied NanoStructures, Mountain View, CA, USA), i.e. silicon nitride cantilevers with silicon tips are used for stiffness studies because they are maximally gentle to living cells (not causing mechanical stimulation). Moreover, as compared with coated cantilevers, these probes are very stable under elevated temperatures in liquids – thus allowing long-time measurements without nonspecific changes in the measured signal.</p> <p><em>Image analysis</em></p> <p>Fluorescence microscopy data were analyzed in ImageJ 1.52h and Python 3.7.1 as follows: cells were manually segmented using actin fluorescence channel, two regions were created for analysis: whole cell and cell periphery, lining a 4 μm thick region around cell border and including most of periphery actin cytoskeleton. In these two regions following parameters were measured for both actin and tubulin fluorescence: Integrated intensity, median intensity, and following regions were measured to describe cell morphology: Cell area, Maximum caliper (max feret diameter), roundness, and aspect ratio. Moreover, stress fibers were manually segmented in every cell and following parameters were measured: number of fibers per cell, feret angle of fiber, integrated intensity, fiber length, mean intensity. Next, a standard deviation of feret angles of individual fibers was calculated relatively to mean of feret angle using a circstd function from scipy package for Python.</p> <p><strong>Identification of files</strong></p> <p><em>Microscopy data</em></p> <p>Files are separated into individual zip files. The dataset of <em>confocal microscopy </em>is separated based on treatments: untreated control, docetaxel-treated cells, cisplatin-treated cells, zinc-treated cells. Filenames actin_tubulin_Zstack_cisplatin.zip, actin_tubulin_Zstack_untreated_control.zip, actin_tubulin_Zstack_zinc.zip, actin_tubulin_Zstack_docetaxel.zip. Files included in these ZIP archives are named as follows: "cellline_treatment_FOV". Files are 3-layer 16bit tiff files with layer sequence as follows: F-Actin (Phalloidin)/b-tubulin/Hoechst 33342. The dataset contains 242 FOVs of three cell line types/three treatments + one control, files are Z-stacks made of 50 slices.</p> <p>The dataset of <em>atomic force microscopy </em>(AFM) is included in one ZIP archive "AFM_YoungModulus_SetpointHeight.zip", which includes data on Young modulus and Setpoint Height of cell lines 22Rv1, PNT1A and PC-3 and treatments zinc, docetaxel, cisplatin (+control), i.e. identical like for confocal microscopy. The file naming is as follows: "AFM_cellline_treatment_FOV_Youngmodulus.tif" for Young modulus and "AFM_cellline_treatment_FOV_setpointheight.tif" for setpoint height. The data are filtered 32-bit tiff images, where the pixel value correspond to cell stiffness (young modulus) in Pa or setpoint height in m.</p> <p><em>Confocal microscopy analysis files</em></p> <p>Following files are csv tables including image analysis of actin/tubulin staining captured by confocal microscope:</p> <p>Cytoskeleton_fluo_analysis_Cell_Cell_periphery_morphology.csv: table includes analyzed data for actin and tubulin staining in following cellular regions: cell, cell periphery. Standard ImageJ parameters regarding intensity and morphology included.</p> <p>Cytoskeleton_fluo_analysis_Fibers.csv: table includes results of manual segmentation and consequent analysis of actin stres fibers in the cells. Apart from standard ImageJ parameters, also number of stress fibers per cell and standard deviation of fiber angle relative to the cell mean angle (for details see methods) are included.</p>
Stiffness Moduli Modelling and Prediction in Four-Point Bending of Asphalt Mixtures: A Machine Learning-Based Framework within Weave-UNISONO 2021 project, NCN project No 2021/03/Y/ST8/00079, and GACR project GA22-04047K
<div><strong>Summary:</strong></div> <div>Two selected mixtures were thoroughly investigated in an experimental trial carried out by means of a four-point bending test (4PBT) apparatus. The mixtures were prepared using spilite aggregate, a conventional 50/70 penetration grade bitumen, and limestone filler. Their stiffness moduli (SM) were determined while samples were exposed to 11 loading frequencies (from 0.1 to 50 Hz) and 4 testing temperatures (from 0 to 30 °C). Observations were recorded and used to develop a machine learning (ML) model. The main scope was the prediction of the stiffness moduli based on the volumetric properties and testing conditions of the corresponding mixtures, which would provide the advantage of reducing the laboratory efforts required to determine them.</div> <div> </div> <div><strong>The dataset includes:</strong></div> <div>Characteristics of bituminous binder, CSV raw data</div> <div> <ul> <li>bituminous binder.csv</li> </ul> </div> <div>Grading curves of tested asphalt mixtures</div> <ul> <li>AML16 Grading curves.csv</li> <li>AMP22 Grading curves.csv</li> </ul> <div>Volumetric characterizations of AML16 and AMP22 mixtures</div> <ul> <li>AML16 Volumetric characterizations.csv</li> <li>AMP22 Volumetric characterizations.csv</li> </ul> <div>Outcomes of the 4PBT experimental trial carried out on AML16 and AMP22 mixtures</div> <ul> <li>AML16 Stiffness Modulus 4PB.csv</li> <li>AMP22 Stiffness Modulus 4PB.csv</li> </ul>
Quantifying local stiffness and forces in soft biological tissues using droplet optical microcavities
<p>Dataset for publication Quantifying local stiffness and forces in soft biological tissues using droplet optical microcavities</p>
Pneumatic elastostatics of multi-functional inflatable lattices: Realization of extreme specific stiffness with active modulation and deployability
<p>Supplementary codes and data: Elastostatics of multi-functional inflatable lattices: Realization of extreme specific stiffness with active modulation and deployability</p>
Design of experiment (DOE) used in the study: Lightweight design of variable-stiffness imperfection-insensitive cylinders enabled by continuous tow shearing and machine learning
<p>There are five input variables that are changed for this design of experiment (DOE) within the following range:</p> <p><span class="math-tex">\(\begin{eqnarray} 0.05 \leq r_{CTS} \leq 0.20 \nonumber \\ 1 \leq n \leq 12 \nonumber \\ 0 \leq {c_2}_{ratio} \leq 1 \\ 0 \leq \theta_1 \leq 75 \nonumber \\ 0 \leq \theta_2 \leq 75 \nonumber \end{eqnarray}\)</span></p> <p>For the sake of simplicity, these variables are respectively called v1, v2, v3, v4, v5.</p> <p>The DOE consist of 2000 points created with Latin Hyper-cube Sampling, as available in the LHS toolbox (Carnell, R. lhs: Latin Hypercube Samples, 2021. R package version 1.1.3.).</p> <p>The outputs evaluated with this design of experiment (DOE) are the critical buckling load $P_{critical}$, $b_{factor}$ obtained with Koiter's asymptotic approach, and the mass.</p>
Text-fig. 7. SEM (a) and SRXTM (b–e) images of Miranthus kvacekii sp. nov.; Mira locality, Portugal. a: Lateral view of flower bud showing corolla lobes extending beyond calyx; note surface of pedicel, calyx and corolla with small equiaxial epidermal cells and indumentum of densely spaced, short stiff trichomes. b, c: Longitudinal sections through floral bud in two directions perpendicular to each other (a, orthoslice yz1024; b, orthoslice xz0950) showing corolla (co), calyx (ca), stamens (st) and semi-inferior ovary with thin ovary wall (ow) and central mushroom-shaped globose placenta (pl) bearing numerous ovules (ov). d, e: Transverse sections through floral bud above placenta (d, orthoslice xy0915; e, orthoslice xy1095) showing calyx (ca), corolla (co), ovary wall (ow) and ovules (ov); yellow outlines indicate the positions of anthers (d) and filaments (e); orange outlines indicate the position of three of the possible staminodes. Specimen, Mira 100-S170157 (a–e, holotype). Scale bars = 600 µm (a–c), 300 µm (d, e). in Early Flowers Of Primuloid Ericales From The Late Cretaceous Of Portugal And Their Ecological And Phytogeographic Implications
Text-fig. 7. SEM (a) and SRXTM (b–e) images of Miranthus kvacekii sp. nov.; Mira locality, Portugal. a: Lateral view of flower bud showing corolla lobes extending beyond calyx; note surface of pedicel, calyx and corolla with small equiaxial epidermal cells and indumentum of densely spaced, short stiff trichomes. b, c: Longitudinal sections through floral bud in two directions perpendicular to each other (a, orthoslice yz1024; b, orthoslice xz0950) showing corolla (co), calyx (ca), stamens (st) and semi-inferior ovary with thin ovary wall (ow) and central mushroom-shaped globose placenta (pl) bearing numerous ovules (ov). d, e: Transverse sections through floral bud above placenta (d, orthoslice xy0915; e, orthoslice xy1095) showing calyx (ca), corolla (co), ovary wall (ow) and ovules (ov); yellow outlines indicate the positions of anthers (d) and filaments (e); orange outlines indicate the position of three of the possible staminodes. Specimen, Mira 100-S170157 (a–e, holotype). Scale bars = 600 µm (a–c), 300 µm (d, e).
Survival-associated cellular response maintained in pancreatic ductal adenocarcinoma (PDAC) switched between soft and stiff 3D microgel culture
<div> <div> <div> <div> <p>Pancreatic ductal adenocarcinoma (PDAC) accounts for about 90% of all pancreatic cancer cases. Five-year survival rates have remained below 12% since the 1970s, in part due to the difficulty in detection before metastasis (migration and invasion into neighboring organs and glands). Mechanical memory is a concept that has emerged over the past decade that may provide a path towards understanding how invading PDAC cells "remember" the mechanical properties of their diseased ("stiff," elastic modulus, E ≈ 10 kPa) microenvironment even whilst invading a healthy ("soft," E ≈ 1 kPa) microenvironment. Here, we investigated the role of mechanical priming by culturing a dilute suspension of PDAC (FG) cells within a 3D, rheologically tunable microgel platform from hydrogels with tunable mechanical properties. We conducted a suite of acute (short-term) priming studies where we cultured PDAC cells in either a soft (E ≈ 1 kPa) or stiff (E ≈ 10 kPa) environment for 6 h, then removed and placed them into a new soft or stiff 3D environment for another 18 h. Following these steps, we conducted RNA-seq analyses to quantify gene expression. Initial priming in 3D culture showed persistent gene expression for the duration of the study, regardless of the subsequent environments (stiff or soft). Stiff 3D culture was associated with the down-regulation of tumor suppressors (LATS1, BCAR3, CDKN2C ), as well as the up-regulation of cancer-associated genes (RAC3). Immunofluorescence staining (BCAR3, RAC3) further supported the persistence of this cellular response, with BCAR3 upregulated in soft culture, and RAC3 upregulated in stiff-primed culture. Stiff-primed genes were stratified against patient data found in The Cancer Genome Atlas (TCGA). Upregulated genes in stiff-primed 3D culture were associated with decreased survival in patient data, suggesting a link between patient survival and mechanical priming.</p> </div> </div> </div> </div>
Data for "Nonlinear Trapping Stiffness of Mid-Air Single-Axis Acoustic Levitators"
<p>Data associated with the manuscript entitled "Nonlinear Trapping Stiffness of Mid-Air Single-Axis Acoustic Levitators".</p>
Dataset: Decay of Torsional Stiffness of RC U-shaped Walls When Subjected Simultaneously to In-Plane Loading
<p>Reinforced concrete U-shaped walls are a popular construction choice, commonly used to resist the lateral loads from wind and earthquakes. When subjected to earthquake ground motions, it is likely that these structural elements will not only bend in flexure but twist due to asymmetries of the building plan layout and the location of the shear center outside of the section. This research investigates the dependency of the torsional stiffness of U-shaped walls on the in-plane translational displacement demands using novel experimental evidence and advanced numerical models. The experimental results show that for a given flexural position, the torsional stiffness decreases with increasing in-plane translational displacement. Furthermore, the numerical and experimental results indicate that when the wall is centered the torsional stiffness degrades at the same rate at the translational stiffness of the walls. Thus, the torsional stiffness of a U-shaped wall as a function of ductility can be estimated using the translational secant stiffness. The numerical results also show that the torsional stiffness increases as a function of the axial load ratio of the wall. The experimental and numerical dataset from this research investigation can be downloaded from a publicly accessible repository.</p>
Data of "Effect of sample dimensions on the stiffness of PA12 Lattice materials fabricated using Powder Bed Fusion"
<div> </div> <div> <pre>Data related to the publication (we would be grateful if you could cite the paper in the case in which you are using the data) title = "Effect of sample dimensions on the stiffness of PA12 Lattice materials fabricated using Powder Bed Fusion", journal = "Additive Manufacturing", pages = " ", year = "2024", issn = "", doi = "https://doi.org/10.1016/j.addma.2024.104382", author = "L. Cobian, E. Maire, J. Adrien, U. Freitas, J.P. Fernandez-Blazquez, M.A. Monclus, J. Segurado"</pre> <p>This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 862015</p> </div>
Data set accompanying the paper "Effective cell membrane tension is independent of polyacrylamide substrate stiffness"
<p>This data set contains the data presented in the publication "Effective cell membrane tension is independent of polyacrylamide substrate stiffness". It consists of optical tweezers data and traction force microscopy data of 3T3 fibroblasts and Xenopus retinal ganglion cells on several different substrates.</p>
Substrate stiffness reduces particle uptake by epithelial cells and macrophages in a size-dependent manner through mechanoregulation
<p>Cells continuously exert forces on their environment and respond to changes in mechanical forces by altering their behavior. Many pathologies such as cancer and fibrosis are hallmarked by dysregulation in the extracellular matrix, driving aberrant behavior through mechanotransduction pathways. We demonstrate that substrate stiffness can be used to regulate cellular endocytosis of particles in a size-dependent fashion. Culture of A549 epithelial cells and J774A.1 macrophages on polystyrene/glass (stiff) and polydimethylsiloxane (soft) substrates indicated that particle uptake is increased up to six times for A549 and two times for macrophages when cells are grown in softer environments. Furthermore, we altered surface characteristics through the attachment of submicron-sized particles as a method to locally engineer substrate stiffness and topography. To investigate the biomechanical changes which occurred within adherent epithelial cells, i.e. characterization of A549 cell spreading and focal adhesion maturation. Consequently, decreasing substrate rigidity and particle-based topography lead to a reduction of focal adhesion size. Moreover, expression levels of Yes-associated protein were found to correlate with the degree of particle endocytosis. A thorough appreciation of the mechanical cues may lead to improved solutions to optimize nanomedicine approaches for treatment of cancer and other diseases with abnormal mechanosignaling.</p>
Equilibrated Kremer-Grest polymer melts of M=500 linear chains with Z=100 entanglements for varying chain stiffness.
<p>Kremer-Grest model polymer melts of highly entangled linear chains. Each melt has approximately 500 chains of Z=100 entanglements each. Systems have been generated for integer and half-integer stiffness kappa=-2.0 to 6.0. System sizes range from 8M to 2M beads.</p> <p>For details regarding the equilibration process and the Kremer-Grest polymer model see C. Svaneborg & R. Everaers ""Multiscale equilibration of highly entangled isotropic model polymer melts" J. Chem. Phys. 158, 054903 (2023) <a href="https://doi.org/10.1063/5.0123431">https://doi.org/10.1063/5.0123431</a></p> <p>Filenames denote the kappa<value> used when equilibrating the melt as well as the number of entanglements Z<number> and the number of molecules M<number>. The files are in ASCII format in the format of a LAMMPS data files. (https://lammps.sandia.gov) The semantics is self-explanatory, sections contains id, molecule, unwrapped coordinates of all beads, as well as bond and angular interactions between all beads.</p> <p>We acknowledge that part of the results of this research was obtained using the PRACE Research Infrastructure resource Joliot-Curie SKL based in France at GENCI@CEA. Computing facilities were provided by the eScience Center at the University of Southern Denmark and financed by the Faculty of Science.</p> <p>Please cite as:</p> <p>@article{MultiscaleEquilibrationHighlyEntangledIsotropicModelPolymerMelts,<br> author = {Svaneborg,Carsten and Everaers,Ralf },<br> title = {Multiscale equilibration of highly entangled isotropic model polymer melts},<br> journal = {J. Chem. Phys.},<br> volume = {158},<br> number = {5},<br> pages = {054903},<br> year = {2023},<br> doi = {10.1063/5.0123431},</p> <p> URL = {https://doi.org/10.1063/5.0123431}</p> <p>}<br> </p> <pre>@misc{EquilibratedKGMeltsZ100, author = {Svaneborg,Carsten and Everaers,Ralf}, title = {Equilibrated Kremer-Grest polymer melts of M=500 linear chains with Z=100 entanglements for varying chain stiffness.}, month = feb, year = 2023, publisher = {Zenodo}, version = {1.0}, doi = {10.5281/zenodo.7319837}, url = {https://doi.org/10.5281/zenodo.7319837} }</pre>
Reassessing variations in the small-strain stiffness of London Clay
<p>Supplementary dataset for "Reassessing variations in the small-strain stiffness of London Clay" Le, Standing and Potts (2023), Géotechnique. https://doi.org/10.1680/jgeot.21.00292</p> <p> </p> <p> </p>
Stiffness transitions in new walls post-cell division differ between Marchantia polymorpha gemmae and Arabidopsis thaliana leaves
<p>Plant morphogenesis is governed by the mechanics of the cell wall–a stiff and thin polymeric box that encloses the cells. The cell wall is a highly dynamic composite material. New cell walls are added during cell division. As the cells continue to grow, the properties of cell walls are modulated to undergo significant changes in shape and size without breakage. Spatial and temporal variations in cell wall mechanical properties have been observed. However, how they<br> relate to cell division remains an outstanding question. Here we combine time-lapse imaging with local mechanical measurements via atomic force microscopy to systematically map the cell wall’s age and growth, with their stiffness. We make use of two systems, <em>M. polymorpha</em> gemmae, and <em>A. thaliana</em> leaves. We first characterise the growth and cell division of <em>M. polymorpha</em> gemmae. We then demonstrate that cell division in <em>M. polymorpha</em> gemmae results in<br> the generation of a temporary stiffer and slower growing new wall. In contrast, this transient phenomenon is absent in <em>A. thaliana</em> leaves. We provide evidence that this different temporal behaviour has a direct impact on the local cell geometry via changes in the junction angle. These results are expected to pave the way for developing more realistic plant morphogenetic models and to advance the study into the impact of cell division on tissue growth.</p>
Analysis of Effective Stiffness and Anisotropy of AC 16 Asphalt Mixture within NCN project Weave-UNISONO 2021, project No 2021/03/Y/ST8/00079
<p><strong>Summary</strong>:</p> <p>The internal structure of the AC 16 (asphalt concrete mixture) was divided into the mortar phase and the mineral aggregate phase. Static creep tests using the Bending Beam Rheometer were conducted for the mortar phase to fit the rheological model. The aggregate arrangement and orientation were analysed using ImageJ software for the mineral phase. The Finite Element Method (FEM using ABACUS software) meshes were prepared based on images with an assumption of plane strain in 2D formulation. Using the FEM model, the tension/compression tests using selected characteristic directions were conducted, and the effective constrained stiffness moduli were estimated.</p> <p><strong>The dataset includes:</strong></p> <ul> <li>TIFF input and output image of AC16 lateral surface, txt output results file <ul> <li>xz_AC_16 lateral surface_areas colour.tiff</li> <li>xz_AC_16 lateral surface.tiff</li> <li>xz_AC_16 lateral surface ImageJ - results.txt</li> </ul> </li> <li>grey TIFF image for plot profile <ul> <li>grey image for plot profile.tif</li> </ul> </li> <li>BBR test results, CSV raw data <ul> <li>sample 1 mortar.csv</li> <li>sample 2 mortar.csv</li> </ul> </li> <li>Input images: scan in xy plane and scan in xz plane <ul> <li>xy_AC_16 mel-dol.tif</li> <li>xy_AC_16.tif</li> <li>xy_AC_16 ImageJ - results.txt</li> <li>xz_AC_16 mel_dol.tif</li> <li>xz_AC_16.tif</li> <li>xz_AC_16 ImageJ - results.txt</li> </ul> </li> <li>Abaqus Input Files – horizontal and vertical tension <ul> <li>xy_AC_16_horizontal_tension.txt</li> <li>xy_AC_16_vertical_tension.txt</li> <li>xz_yz_AC_16_horizontal_tension.txt</li> <li>xz_yz_AC_16_vertical_tension.txt</li> </ul> </li> </ul>
Study of Effects of Sacubitril/Valsartan vs. Enalapril on Aortic Stiffness in Patients With Mild to Moderate HF With Reduced Ejection Fraction
ClinicalTrials.gov study NCT02874794. IPD Sharing: YES. Countries: 1. Publications: 5.
Pneumatic elastostatics of multi-functional inflatable lattices: Realization of extreme specific stiffness with active modulation and deployability
Open the record for dataset details and reuse information.
Data and simulation model files for: Variable-stiffness morphing wheel inspired by the surface tension of a liquid drop
Open the record for dataset details and reuse information.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
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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
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