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2,885 results for “Transfers”
Data from: Transgenic Aedes aegypti mosquitoes transfer genes into a natural population
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Data from: Coral tentacle elasticity promotes an out-of-phase motion that improves mass transfer
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Data from: Genetic variation in adaptive traits and seed transfer zones for Pseudoroegneria spicata (bluebunch wheatgrass) in the northwestern United States
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Data from: Systematic evaluation of horizontal gene transfer between eukaryotes and viruses
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Effect of surface inhomogeneity of ion exchange membranes on the mass transfer efficiency in pulsed electric field modes
<p>Video 1: Visualization of the vortex structures at the Neosepta AMX membrane surface in the desalination channel of the electrodialysis cell in the DC mode at i = 3.0 ilimLev;</p> <p>Video 2: Visualization of the vortex structures at the Neosepta AMX membrane surface in the desalination channel of the electrodialysis cell in the PEF mode at iav = 3.0 ilimLev (f = 0.5 Hz, α = 1/2);</p> <p>Video 3: Visualization of the vortex structures at the Neosepta AMX membrane surface in the desalination channel of the electrodialysis cell in the PEF mode at iav = 3.0 ilimLev (f = 5.0 Hz, α = 1/2).</p>
Evolution of an insect immune barrier through horizontal gene transfer mediated by a parasitic wasp
<p>Numerical data that underlies tables and graphs (figures 1-7, 9, 10; table 1) and statistics of the PLOS Genetics article from Di Lelio et al., 2019.</p>
Transfer Learning for leveraging computer vision in infrastructure maintenance [extracted features]
<p>Dataset containing features extracted from images taken on single case of infrastructure facility for the purpose of training Transfer Learned CNN classifier. It is meant to be used with KrakN framework (https://github.com/MatZar01/KrakN), published with the research paper.</p>
Fig. 2 in Redescription of Inglisia vitrea Cockerell (Hemiptera, Coccidae) and its transfer to the genus Pseudokermes Cockerell
Fig. 2. Pseudokermes vitreus (Cockerell), adult female. Abbreviations of enlargements: anplt = anal plate; ant = antenna; ar = anal ring; dmic = dorsal microduct; mset = marginal setae; rshs = round-shaped specimen; sp = simple pore; pp = perivulvar pore; spp = spiracular pore; stgsp = stigmatic spine; vmic = ventral microduct; vset = ventral setae; vsbset = ventral submarginal setae; vtd = ventral tubular duct.
Figure 4 from: Xue B, Ding H-B, Yao G, Shao Y-Y, Fan X-J, Tan Y-H (2020) From Polyalthia to Polyalthiopsis (Annonaceae): transfer of species enlarges a previously monotypic genus. PhytoKeys 148: 71-91. https://doi.org/10.3897/phytokeys.148.50929
Figure 4 Polyalthiopsis verrucipes comb. nov. A flowering branch B close-up of adaxial surface of leaf, showing glands C close-up of leaf petiole, showing the transverse striations on dried petiole D lateral view of the flower E adaxial view of the flower F sepal G outer petal H inner petal I stamen J carpel K longitudinal section of the developing carpel, showing two lateral ovules L a dried monocarp M a seed. Drawn by Ding-Han Cui. (A–K from B. Xue & H. B. Ding XB311, IBSC; L, M from C. W. Wang 76321, PE)
Figure 3 from: Xue B, Ding H-B, Yao G, Shao Y-Y, Fan X-J, Tan Y-H (2020) From Polyalthia to Polyalthiopsis (Annonaceae): transfer of species enlarges a previously monotypic genus. PhytoKeys 148: 71-91. https://doi.org/10.3897/phytokeys.148.50929
Figure 3 Morphology of Polyalthiopsis verrucipes comb. nov. A trunk, showing greyish bark B a branch, showing the leaf lamina C adaxial leaf surface, showing the raised midrib D close-up of the abaxial surface of dried leaf, showing glands E petiole with transverse striations when dried F lateral view of the flower G top view of the flower H bottom view of the flower I adaxial and abaxial view of the stamen J carpel K longitudinal section of a developing carpel, showing two developing ovules L developing young fruits M single dried monocarp, showing the two seeds 01187409 (C. W. Wang 76321, PE) N cylindrical seed, showing longitudinal groove around circumference (C. W. Wang 76321, PE). – Photos: A, C–E, I–N, by Bine Xue; B, by Yun-Hong Tan; G–H by Hong-Bo Ding.
Figure 2 from: Xue B, Ding H-B, Yao G, Shao Y-Y, Fan X-J, Tan Y-H (2020) From Polyalthia to Polyalthiopsis (Annonaceae): transfer of species enlarges a previously monotypic genus. PhytoKeys 148: 71-91. https://doi.org/10.3897/phytokeys.148.50929
Figure 2 Morphological comparison between Polyalthiopsis chinensis and P. verrucipesA type specimen of P. chinensis (Qinghai-Xizang Exped. 74-4451, PE) B infloresence of P. chinensis (Qinghai-Xizang Exped. 74-4451, PE) C type specimen of P. verrucipes (C. W. Wang 76321, A) D inflorescence of P. verrucipes (B. Xue & H.B. Ding 311, IBSC) E adaxial leaf surface of P. chinensis (Qinghai-Xizang Exped. 74-4451, KUN) F abaxial leaf surface of P. chinensis (Qinghai-Xizang Exped. 74-4451, KUN) G adaxial leaf surface of P. verrucipes (Yunnan Exped. 9527, KUN) H abaxial leaf surface of P. verrucipes (Yunnan Exped. 9527, KUN).
Figure 1 from: Xue B, Ding H-B, Yao G, Shao Y-Y, Fan X-J, Tan Y-H (2020) From Polyalthia to Polyalthiopsis (Annonaceae): transfer of species enlarges a previously monotypic genus. PhytoKeys 148: 71-91. https://doi.org/10.3897/phytokeys.148.50929
Figure 1 Bayesian 50% majority-rule consensus tree under partitioned models (cpDNA data: matK, ndhF, psbA-trnH, rbcL and trnL-F; 60 taxa) showing Annonaceae subfams. Anaxagoreoideae, Ambavioideae and Annonoideae. Numbers at the nodes indicate Bayesian posterior probabilities and maximum parsimony bootstrap values (> 50%) in that order.
A Deep Learning Based Cardiac Cine Segmentation Framework for Clinicians - Transfer Learning Application to 7T - Additional Data
<p><strong>Automatically Generated Segmentation Masks for Data Science Bowl Cardiac Challenge Data</strong></p> <p>These segmentation masks have been automatically generated with the <a href="https://github.com/baiwenjia/ukbb_cardiac">ukbb_cardiac</a> network by Bai et al. (2018, <a href="https://doi.org/10.1186/s12968-018-0471-x">doi:10.1186/s12968-018-0471-x</a>). In order to reproduce the data cleaning and conversion: download the data from <a href="https://www.kaggle.com/c/second-annual-data-science-bowl/data">Kaggle</a> and follow the data curation and conversion steps outlined in: <a href="https://github.com/chfc-cmi/cmr-seg-tl">cmr-seg-tl</a> and the associated publication (Link to be added).</p> <p>As this is a derived dataset please abide by the data use rules of the original dataset at kaggle and provide proper citation to the original data:</p> <blockquote> <p>The data for the Data Science Bowl is available for research and academic pursuits. Please cite as ‘Data Science Bowl Cardiac Challenge Data’.</p> </blockquote> <p>Please also cite the Bai et al. article for the algorithm and our publication for the data curation.</p>
Data for the parameterization of radiative transfer processes in urban climate models
<p><em>Radiative Transfer</em> <em>Model</em> (RTM) is a key component in microscale building resolving urban climate models (<em>UCM</em>), which are used to simulate the flow within urban area. We use different parameterizations of RTMs in the model system <a href="https://gmd.copernicus.org/articles/13/1335/2020/gmd-13-1335-2020.html">PALM</a> version 6.0 to show how much detail modellers should include in their simulation.</p> <p>We introduce the output PALM model results for two examples: (1) A simplified urban geometry consisting of an urban crossing (UC) and (2) a realistic urban domain located at the town square Ernst-Reuter-Platz in Charlottenburg in Berlin (ER). The netCDF files contain the radiative flux received by each surface in the domains, including the shortwave (direct and diffuse) radiation as well as the longwave radiation. Also, the data set includes the 3D flow variables (<em>u</em>, <em>v</em>, <em>w</em>) and the potential temperature. The model drivers (input data) for both examples are included as well.</p> <p>The data set consists of the following model input/output data:</p> <p>1) Simplified urban domain (UC):</p> <ul> <li>Input driver for the model PALM for UC (UC_model_driver.tar.gz)</li> <li>Radiation fluxes for UC when using RTM_01: radiation for horizontal surfaces (UC_RTM_01.nc)</li> <li>Radiation fluxes for UC when using RTM_02: sky view effect (building shadows) (UC_RTM_02.nc)</li> <li>Radiation fluxes for UC when using RTM_03: vegetation interaction with SW radiation (UC_RTM_03.nc)</li> <li>Radiation fluxes for UC when using RTM_04: receiving radiation from surface emission (UC_RTM_04.nc)</li> <li>Radiation fluxes for UC when using RTM_05: vegetation interaction with LW radiation (UC_RTM_05.nc)</li> <li>Radiation fluxes for UC when using RTM_06: single reflection (UC_RTM_06.nc)</li> <li>Radiation fluxes for UC when using RTM_07: vegetation interaction with reflected radiation (UC_RTM_07.nc)</li> <li>Radiation fluxes for UC when using RTM_08: multiple reflections (UC_RTM_08.nc)</li> <li>3D data for the UC reference case which includes u,v,w,theta</li> </ul> <p>2) Realistic urban domain (ER):</p> <ul> <li>Input driver for the model PALM for ER (ER_model_driver)</li> <li>Radiation fluxes for ER when using RTM_01: radiation for horizontal surfaces (ER_RTM_01.nc)</li> <li>Radiation fluxes for ER when using RTM_02: sky view effect (building shadows) (ER_RTM_02.nc)</li> <li>Radiation fluxes for ER when using RTM_03: vegetation interaction with SW radiation (ER_RTM_03.nc)</li> <li>Radiation fluxes for ER when using RTM_04: receiving radiation from surface emission (ER_RTM_04.nc)</li> <li>Radiation fluxes for ER when using RTM_05: vegetation interaction with LW radiation (ER_RTM_05.nc)</li> <li>Radiation fluxes for ER when using RTM_06: single reflection (ER_RTM_06.nc)</li> <li>Radiation fluxes for ER when using RTM_07: vegetation interaction with reflected radiation (ER_RTM_07.nc)</li> <li>Radiation fluxes for ER when using RTM_08: multiple reflections (ER_RTM_08.nc)</li> <li>3D data for the ER reference case which includes u,v,w,theta</li> </ul> <p>For more information and analysis, please check out the relevant publication in the international journal Geoscientific Model Development: Salim et. al, Importance of radiative transfer processes in urban climate models:A study based on the PALM model system 6.0, submitted to GMD.</p>
Supplementary material 2 from: Datta A, Schweiger O, Kühn I (2020) Origin of climatic data can determine the transferability of species distribution models. NeoBiota 59: 61-76. https://doi.org/10.3897/neobiota.59.36299
Multimodel inference table
Supplementary material 3 from: Datta A, Schweiger O, Kühn I (2020) Origin of climatic data can determine the transferability of species distribution models. NeoBiota 59: 61-76. https://doi.org/10.3897/neobiota.59.36299
R codes
Sub-picosecond to Sub-nanosecond Vibrational Energy Transfer Dynamics in Pentaerythritol Tetranitrate
<p><strong>Experimental Data</strong></p> <p>All data are saved as a .csv file. Each transient .csv file is labeled according to molecule, file contents, polarization, pump laser power, spectrometer grating position, and a date (<em>e.g</em>. PETN_TA_para_1.8mW_11.1um_06Feb2020.csv). The first column contains frequencies (in cm<sup>-1</sup>) while the first row indexes each time delay (in ps). Transient spectra at select time delays are similarly labeled (<em>e.g</em>. PETN_spectra_7.8um_FTIRcorr_07Feb2020.csv) with the same data organization within each file. The select transient spectra shown at 1660 cm-1 were taken from the 6.1 µm "TA" dataset. The static PETN FTIR and 33°C ThDIR spectra are given as two column .csv files: the first column is frequency (in cm<sup>-1</sup>) while the second column is either transmission<br> or <span class="math-tex">\(\Delta \mathrm{OD}\)</span>.</p> <p><strong>Theory Data</strong></p> <p>Included in the data repository are all of the necessary inputs to perform the vibrational analysis using the Phonopy software package. The minimized PETN crystal used in the nite displacement calculations is given as a POSCAR file format to be used in VASP, the enumeration of all displacements used in the first anharmonic expansion is given in disp_fc3.yaml. The collection of all individual VASP calculations into second- and third-order force constants are contained in the .hdf5 files. The remaining files contain all of the details for the Phonopy calculations performed, per-mode population adjustments in the JDOS are achieved by modifying the phono3py/phonon3/triplets.py source code file which is distributed with all versions of the code. Short movies of each IR mode and all phonon modes between 0–800 cm<sup>-1</sup> are presented in .gif format; filenames are either the calculated frequency or, in the case of several modes, the approximate center frequency.</p>
Data for article "Tracking Charge Transfer to Residual Metal Clusters in Conjugated Polymers for Photocatalytic Hydrogen Evolution"
<p>Data presented in the publication "Tracking Charge Transfer to Residual Metal Clusters in Conjugated Polymers for Photocatalytic Hydrogen Evolution", published in the Journal of the American Chemical Society. The published article is available at <a href="https://doi.org/10.1021/jacs.0c06104">https://doi.org/10.1021/jacs.0c06104</a></p>
Rapid Radiative Transfer Model Output Evaluating Cryospheric Surface Emissivities
<p>Rapid Radiative Transfer Model (RRTM) (Mlawer, et al.,1997) output use to evaluate three cryospheric surface emissivities spectrally across three atmospheric profiles. README file attached provides information regarding output format. </p>
Dataset - Copyrights Transfer Agreement
<p>Data kami berasal dari basis data SINTA (2020) dan Scimagojr (Scimagojr,<strong> </strong>2020) dengan total 25 jurnal, terdiri dari 15 jurnal nasional (penerbit berdomisili di Indonesia) dan 10 jurnal luar negeri (penerbit berdomisili di luar Indonesia). </p> <p>Untuk jurnal nasional, kami memilih (1) Sepuluh jurnal yang masuk kategori SINTA 1; (2) Dua jurnal yang masuk SINTA 3, dan (3) Tiga jurnal yang belum masuk daftar SINTA (SINTA 0). Untuk jurnal internasional, kami menggunakan daftar SJR pada kategori <em>Arts and H</em>umanities (3 jurnal teratas), kategori <em>Demography</em> (3 jurnal teratas) dan <em>Earth and P</em>lanetary <em>S</em>ciences (4 jurnal teratas).</p>
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.