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525 results for “Displace”
FIGURE 2 in Characterization of a monophylum Echinocletodes, its exclusion from Ancorabolinae (Copepoda, Harpacticoida), and displacement of E. bodini and E. walvisi to Cletodes, including the description of two new species
FIGURE 2. Echinocletodes voightae sp. nov., female. A. A1, B. A2, C. GF, D. FR (right). All scale bars: 50 µm.
FIGURE 13 in Characterization of a monophylum Echinocletodes, its exclusion from Ancorabolinae (Copepoda, Harpacticoida), and displacement of E. bodini and E. walvisi to Cletodes, including the description of two new species
FIGURE 13. Cletodes meyerorum sp. nov. A. P3 female, B. P4 female, C. P3 enp male. Scale bar: 50 µm.
FIGURE 15 in Characterization of a monophylum Echinocletodes, its exclusion from Ancorabolinae (Copepoda, Harpacticoida), and displacement of E. bodini and E. walvisi to Cletodes, including the description of two new species
FIGURE 15. Cletodes meyerorum sp. nov., male. A. Habitus dorsal, B. A1. Scale bars: A. 100 µm, B. 50 µm.
FIGURE 8 in Characterization of a monophylum Echinocletodes, its exclusion from Ancorabolinae (Copepoda, Harpacticoida), and displacement of E. bodini and E. walvisi to Cletodes, including the description of two new species
FIGURE 8. Cletodes meyerorum sp. nov., female. A. Habitus lateral, arrows showing cuticular spikes, B. Habitus dorsal. Scale bars: 100 µm.
FIGURES 10–15 in Mature larva of Stenichnus godarti (Latreille) (Coleoptera: Staphylinidae, Scydmaeninae): redescription, hypothesis of displaced epicranial suture and alternative interpretation of homology between chaetotaxic structures
FIGURES 10–15. Larva of Stenichnus godarti. Head in dorsal (10) and ventral (11) views; left (12) and right (13) antenna in dorsal view; right (14) and left (15) maxilla in ventral view. Abbreviations: Ag, antennal gland; An1–3, antennomere I–III; Cd, cardo; Da, dorsoanterior seta; De, dorsoepicranial seta; Df, dorsofrontal seta; Dl, dorsolateral seta; Dp, dorsoposterior seta; Es, frontal arm of epicranial suture; Est, epicranial stem; L, lateral seta; l, lentiform structure; La, labral anterior seta; Ma, mala; Md. mandible; MdS, mandibular seta; Mn, mentum; Mxp1–3, maxillary palpomere II–III; Ptp, posterior tentorial pit; SA, sensory appendage; Smn, submentum; sol, solenidion; St, stemma; Stp, stipes; V, ventral seta; Va, ventroanterior seta; Vl, ventrolateral seta.
The two-year InSAR postseismic displacements of the 2021 Maduo earthquake
<p>This dataset includes the two-year east-west and vertical postseismic displacements of the 22nd May 2021 Maduo earthquake from InSAR based on the ascending and descending Sentinel-1 SAR data.</p>
DISPLACE-2024 Dataset
<p>Inspired by the previous session of DISPLACE 2023 challenge, we have launched the DISPLACE 2024 challenge (https://displace2024.github.io/). Compared to the first DISPLACE challenge, the current challenge includes an additional track on automatic speech recognition (ASR) in code-switched multi-accent conversational scenarios along with speaker and language diarization tracks. <strong>We release supervised data for exploring new directions on multilingual multispeaker, multi accent conversational data</strong>. To the best of our knowledge, no publicly available dataset matches the diverse characteristics observed in the DISPLACE dataset, including code-mixing/switching, natural overlaps, reverberation, and noise. For this challenge, a natural multi-lingual, multi-speaker conversational dataset will be distributed for development and evaluation purposes. There will be no training data given and the participants will be free to use any resource for training the models. The challenge reflects the theme of Interspeech 2024 - "Speech and Beyond" in its true sense.<br><br><br><br>The dataset can be obtained by orgainisers by sending the request form and duly signed the terms and condtions<br><br><strong>Link for registration for obtaining the data : <a href="https://forms.gle/PcewWwYtVDwjZwg99" target="_blank" rel="noopener">Registration Link</a></strong></p>
Job Displacement, Unemployment Benefits and Domestic Violence
<p>This is the replication package for the empirical analysis in Sonia Bhalotra, Diogo Britto, Paolo Pinotti and Breno Sampaio "Job Displacement, Unemployment Benefits and Domestic Violence" to be published in the Review of Economic Studies. All instruction for the package can be found in the doc file Readme.docx.</p>
500-yr Projections of Thwaites Glacier, Antarctica, with MALI, including glacial isostatic adjustment: no elastic displacement
<p>This archive contains a subset of results reproducing the material presented in the manuscript "Stabilizing effect of bedrock uplift on retreat of Thwaites Glacier, Antarctica, at centennial timescales" by Cameron Book, et al. This archive only includes results for the simulations with elastic displacement in the GIA model disabled. These results are briefly discussed in the first paragraph of section 'Factors controlling feedbacks between glacier retreat and bedrock uplift'. The main results from the manuscript are in a separate archive. Questions should be directed to Matt Hoffman (mhoffman@lanl.gov).</p> <p>This archive contains the following directories:</p> <p>|-- N1_no_elastic<br> |-- N2_no_elastic<br> |-- N3_no_elastic<br> `-- N4_no_elastic</p> <p>The individual runs have the following corresponence to the manuscript, but<br> with the elastic displacement disabled:<br> N1=TYP<br> N2=BEST2<br> N3=VLV-THIN<br> N4=VLV</p> <p>Within each run directory, are the following model output files:<br> globalStats.nc: MALI global, scalar time-series<br> output_*.nc: MALI spatial output fields, separated by century</p>
Tide-induced 3D displacement fields at Rutford Ice Stream, West Antarctica
<p>Tide-induced 3D displacement fields at Rutford Ice Stream, West Antarctica</p>
Data from: Analysis on Conveying of Miniature and Microparts on a Platform Subjected to Sinusoidal Displacement Cycles with Controlled Dry Friction
<p>Data from the paper "Analysis on Conveying of Miniature and Microparts on a Platform Subjected to Sinusoidal Displacement Cycles with Controlled Dry Friction" <a href="https://doi.org/10.5755/j02.mech.28195">https://doi.org/10.5755/j02.mech.28195</a></p> <p>This paper presents a novel method for conveying of miniature and microparts on a subjected to sinusoidal displacement cycles in the horizontal direction when the effective coefficient of dry friction between the part and the platform is periodically being controlled. Hereby, the required dynamic directionality is achieved via the system asymmetry created by periodic alteration of the effective coefficient of dry friction between the micropart and the platform. A mathematical model of conveying process is developed and solved numerically to determine the influence of frictional properties, friction control and sinusoidal excitation parameters on the conveying process characteristics. It was found that the velocity and direction of conveying can be easily controlled in a wide range by changing the phase shift between the function of the ef-fective dry friction coefficient and the function of horizon-tal sinusoidal displacement cycles as well as the duration of effective dry friction coefficient reduction. To test the theoretical findings in practise, an experimental setup for micropart conveying with controlled dry friction was created and build. The experimental results revealed the functional capabilities of the proposed method for micropart conveying by demonstrating how the velocity, direction and step size are controlled by regulating the parameters of friction control and sinusoidal excitation.<br> The proposed method can be practically used in conveying, feeding, manipulation and assembly systems for miniature and microparts in the mechatronics, electronic and other industries.</p>
Data and script for "Sensitivity of Precipitation Displacement of a Simulated MCS to the Changes in Land Surface Conditions"
<p>This is a placeholder for Data and script for ""<strong>Sensitivity of Precipitation Displacement of a Simulated MCS to the Changes in Land Surface Condition" submitted to JGR-atmosphere.</strong></p>
Sexual dimorphism in an adaptive radiation: Does intersexual niche differentiation result in ecological character displacement?
<p>Evolutionary radiations are one plausible explanation for the rich biodiversity on Earth. Adaptive radiations are the most studied form of evolutionary radiations and ecological opportunity has been identified as one factor permitting them. Competition among individuals is supposedly highest in populations of conspecifics. Divergent modes of resource use might minimize trophic overlap, and thus intersexual competition, resulting in ecological character displacement between sexes. However, the role of intersexual differentiation in speciation processes is insufficiently studied. The few studies available suggest that sexual niche differentiation exists in adaptive radiations, but their role within the radiation, and the extent of differentiation within the organism itself, remains largely unexplored. Here, we test the hypothesis that multiple morphological structures are affected by sexual niche differentiation in "roundfin" <i>Telmatherina</i>, the first case where sexual niche differentiation was demonstrated in an adaptive fish radiation. We show that sexes of two of the three morphospecies differ in several structural components of the head, all of these are likely adaptive. Sexual differentiation is linked to the respective morphospecies-specific ecology and affects several axes of variation. Trait variation translates into different feeding modes, processing types and habitat usages that add to interspecific variation in all three morphospecies. Intrasexual selection, i.e. male-male competition, may contribute to variation in some of the traits, but appears unlikely in internal structures which are invisible for other individuals. We conclude that intersexual variation adds to the adaptive diversity of roundfins, and might play a key role in minimizing intersexual competition in emerging radiations.</p>
Data for: Relationships between reproductive character displacement in genital morphology and the population-level cost of interspecific mating: Implications for the Templeton effect
<p><span>Natural selection against maladaptive interspecific reproductive interactions may cause greater divergence in mating traits between sympatric populations than between allopatric populations in a pair of species, known as reproductive character displacement (RCD), evidence for the lock-and-key hypothesis of genital evolution. However, the relative importance of various processes contributing to RCD in genital morphology (e.g., reinforcement, reproductive interference, and population filtering or the Templeton effect) is not clear. Here, we examined hypotheses for RCD in genital morphology, with a special focus on the Templeton effect (which predicts that only highly differentiated populations can exist in sympatry). We examined population-level fitness costs in interspecific mating between <em>Carabus maiyasanus</em> and <em>C. iwawakianus</em> with RCD in genital morphology. A mating experiment using populations with various degrees of RCD in genital morphology showed no evidence for consistently lower interspecific mating costs in <em>C. maiyasanus</em> populations in contact with displacement in genital morphology than in remote populations, contrary to the predictions of the Templeton effect. Alternatively, interspecific mating costs varied among populations. Observed relationships between the sizes of genital parts concerning isolation and interspecific mating costs across populations suggested that population-level fitness costs do not necessarily decrease during the process leading to RCD. Our results provide insight into ecological and evolutionary processes during secondary contact in closely related species.</span></p>
Surface displacement measurements and fault slip models for the 1997 Mw 7.2 Zirkuh earthquake
<p><strong>Source models of the 1997 Mw 7.2 Zirkuh earthquake inferred from InSAR and optical correlation displacement field </strong></p> <p><strong>Introduction</strong></p> <p>We provide the InSAR and optical correlation displacement fields of the 1997 Mw 7.2 Zirkuh earthquake (NE Iran).<br> The InSAR data have been processed by Sudhaus and Jonsson (2011) and the optical correlation data by Marchandon et al. (2017). <br> We also provide the different fault slip models for the earthquake inferred from these data and published in Marchandon et al. (2017). <br> Finally, we include the source code of the genetic algorithm used in Marchandon et al. (2017) to infer the uniform slip models of the Zirkuh earthquake.<br> This genetic algorithm (Sudhaus and Jonsson, 2011) allows estimating the geometry and a uniform slip value for each segment of the fault. The Abiz fault, that broke during the Zirkuh earthquake, <br> is a complex structure with many fault strike variations that requires 16 segments to be properly modelled. Thus, a penalty function is implemented to constrain the algorithm to sample models<br> with limited dip angle fluctuations between neighboring segments (Sudhaus and Jonsson, 2011). The rupture is modelled as a dislocation embedded in an elastic half-space (Okada, 1992). </p> <p>For further information about the data, the method and the model results, see Marchandon et al. (2017). </p> <p><strong>Content</strong></p> <p>Data: InSAR data, optical Correlation data, weighting matrix files in .mat format, matlab script to plot the data. <br> Fault: Abiz fault segment locations file in .mat format and matlab script to plot the fault.<br> Scripts: All scripts needed to run the Non-linear optimization.<br> Models: Fault slip models for the Zirkuh earthquake and matlab script to plot them. </p> <p><strong>References</strong></p> <p>Sudhaus, H., and S. Jonsson (2011), Source model for the 1997 Zirkuh earthquake (Mw=7.2) in Iran derived from JERS and ERS InSAR observations, Geophysical Journal International, <br> 185(2), 676–692, doi:10.1111/j.1365-246X.2011.04973.x.</p> <p>Marchandon, M., Vergnolle M., Sudhaus, H., and Cavalié., O., (2017) Fault geometry and slip distribution at depth of the 1997 Mw 7.2 Zirkuh earthquake: <br> contribution of near-field displacement data, accepted with minor revisions at Journal of Geophysical Research: Solid Earth. </p> <p>Okada, Y. (1992), Internal deformation due to shear and tensite faults in a half-space, Bulletin of Seismological Society of America, pp. 1018–1040.</p> <p> </p>
Supplementary material for "Can the anisotropic hydraulic conductivity of an aquifer be determined using surface displacement data? A case study"
<p>Supplementary material for ”Can the anisotropic hydraulic conductivity of an aquifer be determined using surface displacement data? A case study".</p> <p>The <a href="https://github.com/sonasalehian/AHC-Poroelastic-Model.git" target="_blank" rel="noopener">AHC-Poroelastic-Model</a> codes from repository is included in the AHC-Poroelastic-Model-main.zip file.</p>
The postseismic GPS displacements at different time windows following the 2024 M7.5 Noto Peninsula, Japan Earthquake
<p>The postseismic GPS displacements at different time windows following the 2024 M7.5 Noto Peninsula, Japan Earthquake.</p> <p>This data is based on the GPS time series from Nevada Geodetic Laboratory (NGL <span>http://geodesy.unr.edu/ )</span>.</p> <p>The format of data is:</p> <p>Time, lon, lat, dn, de, du, sign, sige, sigu</p>
Ground ice contents and InSAR displacements from Adventdalen, Svalbard.
<p>The file contains ground ice content measurements of the active layer and uppermost permafrost from 12 coring sites in Adventdalen, Svalbard. The frozen sediment cores were collected in April 2023. Further, the file includes InSAR displacement timeseries for the thawing seasons 2021 and 2023 and the ALT of 2023 at the coring sites.</p>
Inversion of GNSS-based 3D Displacement for Daily Terrestrial Water Storage Changes under the 2023 Beijing-Tianjin-Hebei Heavy Rain in China
<p>The data and code for "Inversion of GNSS-based 3D Displacement for Daily TerrestriaI Water Storage Changes under the 2023 Beijing-Tianjin-Hebei Heavy Rain in China".</p> <p>Including:</p> <p>I. the GNSS and water level dataset;</p> <p>II, the codes for Inversion of GNSS for mass loads.</p>
Digital image correlation displacements and strains around a growing fatigue crack in an AA2024-T3 aluminium alloy
<p>This repository contains the data used in the research article:</p> <p>Strohmann, Melching, Paysan, Dietrich, Requena, Breitbarth. Next generation fatigue crack growth experiments of aerospace materials. <em>Scientific Reports</em>, 2024, <a href="https://doi.org/10.1038/s41598-024-63915-x" target="_blank" rel="noopener">https://doi.org/10.1038/s41598-024-63915-x</a>.</p> <p> </p> <p><strong>General Description</strong><br>The dataset contains digital image correlation (DIC) data of a growing fatigue crack in an AA2024-T3 alloy. For the experiment, two independent DIC measurement devices were used – a global full-field DIC and a local microscopic DIC. Thus, the dataset consists of two main directories. One for the 3D DIC data ("global_3d_dic") and a second one for the 2D microscopic DIC data ("local_2d_dic"). Both of these are described and connected by rich metadata.<br>The 3D DIC data directory contains two subdirectories (a "Nodemaps" directory and a "Connections" directory). Both of them contain 797 '.txt'-files. The "Nodemaps" give the DIC results (i.e. coordinates, displacement and strains) for every timestep throughout the experiment. These are usually maximum, minimum, and mean load of a certain load cycle. However, for few crack lengths, we obtained DIC data for a higher number (ca. 100) of images within one load cycle. The nodemaps' format and structure is optimized for data processing in the open-source Python package <a title="CrackPy" href="https://doi.org/10.5281/zenodo.10990494" target="_blank" rel="noopener">CrackPy</a>. The last integer number of each filename can be interpreted as a 'timestep' throughout the experiment. The "Connection" files represent the connections of the DIC facet center coordinates. These are necessary to export the "Nodemap" data to any mesh like dataset, e.g. for VTK. <br>The 2D microscopic DIC directory contains 3 subdirectories ("80", "90", "95") for predefined positions with respect to the specimen coordinate system. For each location, a number of DIC data are stored, again within two subdirectories "Nodemaps" and "Connections" as '.txt'-files. For the 2D DIC data, the last integer of each name cannot be correlated to a timestep. Instead, we provide a descriptive file "local_2d_microscopic_coordinates_by_nodemaps.csv" linking each and every "Nodemap"-file to its respective coordinates and timestep (i.e. the load cycles).</p> <p>To describe the data, we distinguish between<br>1. Higher-level metadata - these data contain information about the experiment and material. The data do not change between timesteps and are given within this description.<br>2. Timestep metadata - these data contain information about one timestep of the experiment and are stored in the header of each "Nodemap"-file.</p> <p> </p> <p><strong>Higher-level Metadata</strong><br>The experiment is described in detail in the reference publication by <a title="Strohmann et al. (2024)" href="https://www.researchsquare.com/article/rs-3128435/v1" target="_blank" rel="noopener">Strohmann et al. (2024)</a> and a summary is given below. Moreover, we provide a dictionary in javascript object notation explaining terms which are used in the higher-level metadata. We use such a dictionary since no standardized ontology is currently available. This dictionary is stored in the main directory as "higher_level_metadata_dictionary.json".</p> <p><em>Material </em><br>A commercially available AA2024-T3 aluminum alloy was tested in L-T orientation, i.e. rolling direction, L, parallel to the load axis. The specimen had a width W = 160 mm cut from a rolled sheet of 2 mm.</p> <p><em>Digital image correlation</em><br>For 3D DIC, we used a GOM Aramis 12M system with a facet size of 20 x 20 pixels and a 16 pixels facet distance. One facet, therefore, covers ~0.614 x 0.614 mm². For the 2D microscopic DIC we captured images using a Zeiss STEMI 206C light optical microscope (LOM), equipped with a Basler a2A5320-23µmPro global shutter CMOS camera. One image has a size of 10.2 x 5.7 mm², 5328 x 3040 Pixels and a facet size of 40x40 pixels (distance of facet center points 30 pixels). The LOM was mounted to a robotic arm, a KUKA lbr Iiwa Cobot.</p> <p><em>Fatigue crack growth</em><br>We used a standard uniaxial servo-hydraulic testing rig. We applied a cyclic load ranging from Fmin = 4.5 kN to Fmax = 15 kN, i.e. R=Fmin/Fmax = 0.3. Throughout the experiment, we measured the crack length using direct current potential drop (DCPD).</p> <p><em>Image acquisition during fatigue crack growth</em><br>We acquired reference images for the DIC calculations before the experiment. For the global DIC, this is simply an image of the unloaded specimen. For the local microscopic DIC, the reference images are acquired in a checker board pattern with an overlap of 70 %. The depth of focus was calibrated for each image individually following (see <a title="Paysan et al. (2023)" href="https://doi.org/10.1007/s11340-023-00964-9" target="_blank" rel="noopener">Paysan et al. (2023)</a>). Images were acquired every 0.5 mm of crack extension at minimum, maximum and 0.5(Fmax- Fmin).</p> <p> </p> <p><strong>Timestep Metadata</strong><br>The timestep-wise metadata is stored in the individual DIC output files, "Nodemaps". We explain the terms used in a second dictionary, "timestep_level_metadata_dictionary.json". For all DIC data, we stored all data coming from the machine controller, i.e. number of cycles, force, displacement of the cylinder and also potential and crack length calculated from the potential as well as current values for back face strain gauges at both back faces of the MT specimen. In addition, for the local microscopic DIC data, we also store the current location of the center point of the image with respect to the global coordinate system provided by the current position of the robot carrying the LOM.</p>
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Allen Brain Atlas
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International Brain Laboratory public data
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OpenNeuro
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