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300 results for “Echo”
data set related to article Echo-time dependency of quantitative susceptibility mapping reproducibility at different magnetic field strengths
<p>This record contains raw date related to article Echo-time dependency of quantitative susceptibility mapping reproducibility at different magnetic field strengths</p>
Echo-CGC: A Communication-Efficient Byzantine-tolerant Distributed Machine Learning Algorithm in Single-Hop Radio Network (video)
Full video presentation of the paper: Echo-CGC: A Communication-Efficient Byzantine-tolerant Distributed Machine Learning Algorithm in Single-Hop Radio Network.<br><br>Appears in Session 2 of the 24th International Conference on Principles of Distributed Systems OPODIS 2020<br><a href="https://opodis2020.unistra.fr">https://opodis2020.unistra.fr</a>
Data from: Acoustic emissions of Sorex unguiculatus (Mammalia: Soricidae): assessing the echo-based orientation hypothesis
Shrew species have been proposed to utilize an echo-based orientation system to obtain additional acoustic information while surveying their environments. This system has been supported by changes in vocal emission rates when shrews encounter different habitats of varying complexity, although detailed acoustic features in this system have not been reported. In this study, behavioral experiments were conducted using the long-clawed shrew (Sorex unguiculatus) to assess this orientation system. Three experimental conditions were set, two of which contained obstacles. Short-click, noisy, and different types of tonal calls in the audible-to-ultrasonic frequency range were recorded under all experimental conditions. The results indicated that shrews emit calls more frequently when they are facing obstacles or exploring the experimental environment. Shrews emitted clicks and several different types of tonal calls while exploring, and modified the use of different types of calls for varying behavior. Furthermore, shrews modified the dominant frequency and duration of squeak calls for different types of obstacles, i.e., plants and acrylic barriers. The vocalizations emitted at short interpulse intervals could not be observed when shrews approached these obstacles. These results are consistent with the echo-based orientation hypothesis according to which shrews use a simple echo-orientation system to obtain information from their surrounding environments, although further studies are needed to confirm this hypothesis.
FIGURE 13 in A description of Echo perornata spec. nov. from Xizang (Tibet), China (Odonata: Calopterygidae)
FIGURE 13. Distribution map showing the known locations for Echo margarita (circle) and E. perornata spec. nov. (triangle).
FIGURE 12 in A description of Echo perornata spec. nov. from Xizang (Tibet), China (Odonata: Calopterygidae)
FIGURE 12. Field photo of Echo m. margarita female taken in Pakhai Tiger Reserve, Arunachal Pradesh, India, by Krushnamegh Kunte.
FIGURES 5–6 in A description of Echo perornata spec. nov. from Xizang (Tibet), China (Odonata: Calopterygidae)
FIGURES 5–6. Echo perornata spec. nov., anal appendages of male; 5) dorsal view; 6) lateral view. Since the appendages are disorted in the teneral holotype specimen, these drawings are reconstructions of the supposed shape.
FIGURES 7–10 in A description of Echo perornata spec. nov. from Xizang (Tibet), China (Odonata: Calopterygidae)
FIGURES 7–10. Penis head, ventral (i.e. when viewed in situ in the male abdomen) and lateral views; 7–8) Echo perornata spec. nov., holotype; 9–10) Echo m. margarita male from Khasia Hills, Meghalaya, India.
Figure 1. Echo incarnata Karsch 1892 in The type material of Calopterygidae in the Museum für Naturkunde in Berlin (Odonata)
Figure 1. Echo incarnata Karsch 1892, synonym of Archineura incarnata (Karsch, 1892); male syntype in coll. MNB (♂ 4a9574), dorsal view.
Data from: A Deep Learning Approach for Fast Muscle Water T2 Mapping with Subject Specific Fat T2 Calibration from Multi-Spin-Echo Acquisitions
<p>This repository contains the imaging data (in NIfTI) and analysis code to reproduce the work presented in <em>"A Deep Learning Approach for Fast Muscle Water T2 Mapping with Subject Specific Fat T2 Calibration from Multi-Spin-Echo Acquisitions"</em> by <strong>Marco Barbieri, Melissa T. Hooijmans, Kevin Moulin, Tyler E. Cork, Daniel B. Ennis, Garry E. Gold, Feliks Kogan and Valentina Mazzoli.</strong></p> <p>Citation: "Barbieri, M., Hooijmans, M.T., Moulin, K. <em>et al.</em> A deep learning approach for fast muscle water T2 mapping with subject specific fat T2 calibration from multi-spin-echo acquisitions. <em>Sci Rep</em> 14, 8253 (2024). https://doi.org/10.1038/s41598-024-58812-2"</p> <p>The source code for setting up the Deep Learning application can be found in the GitHub repository https://github.com/barma7/Deep_Learning_for_Muscle_T2_mapping.git</p>
MRI data of 3D radial multi-echo spin-echo acquisition of the human brain at 3T with and without deliberate motion
<p>Radial 3D multi-echo spin echo acquisition of a human brain acquired with a house made sequence on a Prisma Siemens 3T MRI scanner. </p> <p>The data have been converted in ISMRMRD format. </p> <p>Two raw datasets are available, one with deliberate motion and one without. </p> <p>The sequence allows for retrospective motion correction based on self-navigation. </p> <p>The images can be reconstructed with the code available on Github: https://github.com/nadegecorbin/Reco_MESE_RAD.git</p> <p>Reconstructed images and associated T2 maps are also provided in the folder "Reconstruction".</p> <p>For the motion case, intermediate images are stored in "Motion/Moco/RecoTRImages", the corrected echoes are in "Motion/Moco/RecoEchoes". Echo images without correction are in "Motion/Nomoco/RecoEchoes". </p> <p>For the No motion case, only data without motion correction are reconstructed and are located in "Nomotion/Nomoco/Recoechoes"</p> <p>A manuscript describing the method is under submission. </p> <p> </p>
The study of daytime ionospheric E-region radar echoes simultaneously observed by Qujing VHF radar and multi-ionosondes
<p>Qujing VHF coherent backscatter radar observed from 05:00 - 08:00 UT (13:00-16:00 LT) on 20 June, 2020;</p> <p>Ionosonde data observed on 19, 20, and 21 June 2020 at Huize and Qujing;</p> <p>Fengyun-4A (FY-4A) satellite data observed from 0230 UT to 0730 UT on 20 June, 2020.</p>
Meteor Head Echo Data from Concurrent Data Collect at RISR-N, JRO, and MHO
<p>Contains data from head echoes observed in the CEDAR 2019 concurrent meteor radar data collect on 2019-10-10 and 2019-10-11 from 9:00-13:00 UTC, at the following facilities: AMISR Resolute Bay Incoherent Scatter Radar North (RISR-N), Jicamarca Research Observatory (JRO), and Millstone Hill Observatory (MHO). Data is saved in the .npz format, which requires Python with the Numpy library to read. The data includes head echo detection rates as a function of time at each facility, and raw data for a subset of head echoes that are included in the analysis of a paper submitted to JGR Space Physics.</p>
Echoes of a panacea in progress: Towards a systematic model for understanding and acting on the disorders of Open Access Publishing
<pre>Data used for the production of the article entitled "<strong>Echoes of a panacea in progress:</strong> <strong>Towards a systematic model for understanding and acting on the disorders of Open Access Publishing"</strong></pre>
Ideophonic echo-words and prosaic dvandva compounds in Korean and Japanese
<p>This dataset contains ideophonic echo-words and prosaic dvandva compounds in Korean and Japanese. For Korean data, 118 echo-words and 64 dvandva compounds are extracted from a written corpus of 29,015 Korean ideophones (http://www.hangeul.pe.kr/symbol/words.htm) and Jung’s (1991) comprehensive study on Korean compounds, respectively. For Japanese data, 98 echo-words are compiled from seven ideophonic studies (Ono 2007; Hida and Asada 2002; Yamaguchi 2003; Kakehi et al. 1996; Amanuma 1974; Asano 1978; Hamano 2014), and 107 dvandva compounds are taken from Hayata’s (1977) list of Japanese compounds.</p> <p><strong>Reference</strong></p> <p>Amanuma, Yasushi. ed. 1974. <em>Giongo/gitaigo jiten</em> [A dictionary of mimetic words]. Tokyo: Tokyodo.</p> <p>Asano, Tsuruko. ed. 1978. <em>Giongo/gitaigo jiten</em> [A dictionary of mimetic words]. Tokyo: Kadokawa.</p> <p>Hamano, Shoko. 2014. <em>Nihongo no onomatope</em> [Onomatopeia in Japanese: Sound symbolism and structure]. Tokyo: Kuroshio.</p> <p>Hayata, Teruhiro. 1977. Tsuigo-no on’inkaiso [On phonological hierarchies for binomials]. <em>Bungaku Kenkyu</em> 74: 123-152.</p> <p>Hida, Yoshifumi, and Hideko Asada. 2002. <em>Gendai giongo gitaigo yōhō jiten</em> [A usage dictionary of modern mimetic words]. Tokyo: Tokyodo.</p> <p>Jung, Dong Hwan 1991. Kwuke hapsengeuy uymikwankye yenkwu [A study of semantic relations of compound words in Korean]. PhD diss., Konkuk University.</p> <p>Kakehi, Hisao, Ikuhiro Tamori, and Lawrence Schourup. 1996. <em>Dictionary of iconic expressions in Japanese</em>. 2 vols. Berlin: Mouton de Gruyter.</p> <p>Ono, Masahiro. ed. 2007. <em>Giongo/gitaigo 4500: Nihongo onomatope jiten </em>[4500 mimetic words: A dictionary of Japanese onomatopoeia]. Tokyo: Shogakukan.</p> <p>Yamaguchi, Nakami. ed. 2003. <em>Kurashi no kotoba: Gion/gitaigo jiten</em> [Language of life: A dictionary of mimetic words]. Tokyo: Kodansha.</p>
Date and codes for papar "Manifestation of topological gapless phase in two-dimensional chiral symmetric system through Loschmidt echo"
<p>The date and MATLAB codes of numerical calculations for the papar "Manifestation of topological gapless phase in two-dimensional chiral symmetric system through Loschmidt echo". The codes are runnable in the MATLAB version R2018a. </p>
Data from: Echoes of a distant time: effects of historical processes on contemporary genetic patterns in Galaxias platei in Patagonia
Interpreting the genetic structure of a metapopulation as the outcome of gene flow over a variety of timescales is essential for the proper understanding of how changes in landscape affect biological connectivity. Here we contrast historical and contemporary connectivity in two metapopulations of the freshwater fish Galaxias platei in northern and southernmost Patagonia where paleolakes existed during the Holocene and Pleistocene, respectively. Contemporary gene flow was mostly high and asymmetrical in the northern system while extremely reduced in the southernmost system. Historical migration patterns were high and symmetric in the northern system and high and largely asymmetric in the southern system. Both systems showed a moderate structure with a clear pattern of isolation by distance (IBD). Effective population sizes were smaller in populations with low contemporary gene flow. An approximate Bayesian computation (ABC) approach suggests a late Holocene colonization of the lakes in the northern system and recent divergence of the populations from refugial populations from east and west of the Andes. For the southern system, the ABC approach reveals that some of the extant G. platei populations most likely derive from an ancestral population inhabiting a large Pleistocene paleolake while the rest derive from a higher-altitude lake. Our results suggest that neither historical nor contemporary processes individually fully explain the observed structure and geneflow patterns and both are necessary for a proper understanding of the factors that affect diversity and its distribution. Our study highlights the importance of a temporal perspective on connectivity to analyse the diversity of spatially complex metapopulations.
Non-Conventional TD-NMR Approaches (Spin Diffusion , Solid and Magic Sandwich Echo) for Food Quality
<p>Non-Conventional TD-NMR Approaches (Spin Diffusion , Solid and Magic Sandwich Echo) for Food Quality</p>
Silicon-29 NMR Experimental Datasets from Silicon-29 Echo Train Coherence Lifetimes and Geminal J-Couplings in Network Modified Silicate Glasses
<p>Silicon-29 Phase-Incremented Echo-Train Acquisition Nuclear Magnetic Resonance datasets that are analyzed to obtain the data in the figures of the paper "Silicon-29 Echo Train Coherence Lifetimes and Geminal <sup>2</sup>J-Couplings in Network Modified Silicate Glasses." </p> <p>Details of the csdf dataset format are given in <a href="https://doi.org/10.1371/journal.pone.0225953"><em>PLOS ONE,</em> 15(1): e0225953 (2020)</a>, "Core Scientific Dataset Model: A lightweight and portable model and file format for multi-dimensional scientific data," D. Srivastava, T. Vosegaard, D. Massiot, and P.J. Grandinetti. The data within csdf files can be accessed with the Python package <a href="https://csdmpy.readthedocs.io/en/stable">csdmpy</a>, or other CSDM-compliant software.</p>
Sailbuoy Echo PolarFront EK80 echosounder datasets 2023-08 to 2023-09
<p><strong>Sailbuoy Echo PolarFront EK80 echosounder data 2023-08 to 2023-09</strong></p><p>The Echo was deployed on 18 August 2023 at 29.45E, 77.76N. For further details on deployment, sampling, and piloting, see Buschmann (2023).</p><p>Time coverage: 2023-08-18-T09:11:46Z/2023-09-22T03:17:15Z</p><p><strong>Datasets</strong></p><ol><li>2023-08-18/2023-08-23: <a href="https://doi.org/10.5281/zenodo.10036821">https://doi.org/10.5281/zenodo.10036821</a></li><li>2023-08-24/2023-08-26: <a href="https://doi.org/10.5281/zenodo.10036823">https://doi.org/10.5281/zenodo.10036823</a></li><li>2023-08-27/2023-09-03: <a href="https://doi.org/10.5281/zenodo.10036825">https://doi.org/10.5281/zenodo.10036825</a></li><li>2023-09-04/2023-09-14: <a href="https://doi.org/10.5281/zenodo.10036827">https://doi.org/10.5281/zenodo.10036827</a></li><li>2023-09-15/2023-09-22: <a href="https://doi.org/10.5281/zenodo.10036829">https://doi.org/10.5281/zenodo.10036829</a></li></ol><p><strong>References</strong><br>Akvaplan-niva (2023-10-01). <strong>Sailbuoy Echo PolarFront sensor data.</strong><br>Buschmann H (2023). Glider data sampling for Polar Front mission summer 2023. In: Daase, M. (2023). PolarFront August 2023 Cruise Report (1.0.0). Zenodo. <a href="https://zenodo.org/doi/10.5281/zenodo.10013660">10.5281/zenodo.10013660</a>.<br> </p>
Day 211: Indian Echo Cavern Entrance
3D scan of Indian Echo Cavern entrance in Hummelstown, PA. One of the coolest limestone caves I've visited. (150+ Images, Photo Mode) Created with Polycam Source: Objaverse 1.0 / Sketchfab
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