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249 results for “letters”
Photographs of Queen Elizabeth I's French letters in the National Library of Russia
<p>These are photographs of the manuscripts of French letters by Queen Elizabeth I of England, held by the <a href="http://nlr.ru/eng">National Library of Russia</a> (NLR) in Saint Petersburg. There are twenty-four letters, and they belong to the Dubrovsky collection. The shelfmark of the manuscript volume is Fr. F. v. XIV No. 6.</p> <p>These images were taken by the NLR, and rights for their publication were granted to the Research Unit for Variation, Contacts and Change in English (<a href="https://varieng.helsinki.fi/">VARIENG</a>) at the University of Helsinki, Finland.</p> <p>This release accompanies an online edition of the letters of Queen Elizabeth I in NLR, Fr. F. v. XIV No. 6. The letters were edited by Guillaume Coatalen, and the images were edited to be IIIF-compliant by Samuli Kaislaniemi. The full reference of the edition, one part of which is a gallery of these images using an IIIF image viewer, is:</p> <ul> <li>Coatalen, Guillaume & Samuli Kaislaniemi (eds). 2021. <em>Queen Elizabeth I's French Letters in the National Library of Russia</em> (Studies in Variation, Contacts and Change in English 21). Helsinki: VARIENG. <a href="https://varieng.helsinki.fi/series/volumes/21/">https://varieng.helsinki.fi/series/volumes/21/</a></li> </ul> <p>All the images are released under a Creative Commons Attribution-NonCommercial 4.0 International license. <a href="https://creativecommons.org/licenses/by-nc/4.0/">https://creativecommons.org/licenses/by-nc/4.0/</a></p> <p>There are 57 images in total, which come in two formats: the original TIFF files, and converted JPG images of the same resolution. As the TIFF files are so large, the JPGs were created to be used in the online edition in order to reduce the use of server space and bandwidth. The images have been bundled into zip files.</p> <p>The image names follow the numbering of the letters in the edition (Coatalen & Kaislaniemi). These numbers differ from archival itemisation: in the manuscript volume, the letters have been pencilled with numbers 3–26. These archival item numbers have also been included in the image names. For example, the first image is named, "Letter 01 - No 3 - fol.1r". "Letter 1" is the number of the letter in the edition; "No 3" is the archival item number; and "fol.1r" means the image is of the recto of the first leaf of the manuscript letter.</p>
Digital Glossary of Sinhala Prakrit (version 2.0), letters N to Z
<p>Digital Glossary of Sinhala Prakrit (version 2.0), letters N to Z</p>
Digital Glossary of Sinhala Prakrit (version 2.0), letters A to M
<p>Digital Glossary of Sinhala Prakrit (version 2.0), letters A to M</p>
Hand-written letters classification measurement data
<p><span>Deep neural networks with applications from computer vision to medical diagnosis<sup>1-5</sup> are commonly implemented using clock-based processors<sup>6-14</sup>, where computation speed is mainly limited by the clock frequency and the memory access time. In the optical domain, despite </span><span>advances in photonic computation<sup>15-17</sup>, the lack of scalable on-chip optical nonlinearity and the loss of photonic devices limit the scalability of optical deep networks. </span><span>Here we report the first integrated end-to-end photonic deep neural network (PDNN) that performs sub-nanosecond image classification through direct processing of the optical waves impinging on the on-chip pixel array as they propagate through layers of neurons. Within each neuron, linear computation is performed optically and the nonlinear activation function is realised opto-electronically, enabling a classification time of under 570 ps, which is comparable with a single clock-cycle of state-of-the-art digital platforms. A uniformly distributed supply light provides the same per-neuron optical output range enabling </span><span>scalability to large-scale PDNNs.</span> <span>Two- and four-class classification of handwritten letters with accuracies of higher than 93.8% and 89.8% are demonstrated, </span><span>respectively. </span><span>Direct clock-less processing of optical data eliminates analogue-to-digital conversion and the requirement for a large memory module, enabling </span><span>faster and more energy-efficient neural networks for the next generations of deep learning systems.</span></p>
The datasets for the paper "Spatial and temporal distribution of lobate scarps in the lunar south polar region: Evidence for latitudinal variation of scarp geometry, kinematics and formation ages, continuous tectonic activity in the last 100 million years and seismically safe south pole Artemis human landing site" Geophysical Research Letters.
<p>This dataset provides the original data that were used for preparing the illustrations, figures and tables.</p>
Dataset for "Multidecadal regime shifts in North Pacific subtropical mode water formation in a coupled atmosphere-ocean-sea ice model" by Kim et al., 2022 in Geophysical Research Letters
<p>Kiel Climate Model pre-industrial simulation data used in the Geophysical Research Letters publication titled “Multidecadal regime shifts in North Pacific subtropical mode water formation in a coupled atmosphere-ocean-sea ice model” by Kim et al., 2022</p>
CEA research letter supplementary material
<p><strong><strong>Diagnosing pediatric mild acute Food Protein-Induced Enterocolitis Syndrome. Proposal of new criteria.</strong></strong></p> <p><strong>Table 1 - Capacity of interception of mild acute FPIES by the previous considered criteria and the new criteria</strong></p>
Zonal mean of primary production and carbon export in the Southern Ocean (Huang and Fassbender, 2023, Geophysical Research Letters)
<p>This dataset contains zonal means of primary production, export potential of distinct biogenic carbon pools, particle sinking flux, and particle export efficiency in the Southern Ocean. See more details in the relevant publication of Huang and Fassbender (2023, Geophysical Research Letters).</p> <p> </p>
8 letters to C.P. Tiele, 1868-1886
<p>These are 8 letters to C.P. Tiele, a Dutch proffesor of Theology at Leiden University in the 19th century. This was the result of a student project mostly intended to gain experience for the minor Digital Humanities at the University of Leiden.</p>
200 Synthetic Epilepsy Clinic letters Markup annotation outputs as CSV files
<p>We have produced 200 synthetic epilepsy clinic letters which were annotated using Markup Annotation Tool with the annotation files (.ann and JSON formats) uploded previously : https://doi.org/10.5281/zenodo.8356494. Here we are making available annotation outputs for each entity extracted as a separate CSV file. These outputs can be directly compared with outputs created by ExECTv2 when processing the 200 synthetic letters. </p>
Model data and figure code for results and figures in the manuscript submitted to Geophysical Research Letters "Hysteresis of the Antarctic ice sheet with a coupled ice sheet climate model"
<p>This folder contains the model data and figure code for results and figures in the manuscript submitted to Geophysical Research Letters "Hysteresis of the Antarctic ice sheet with a coupled ice sheet climate model"</p> <p>The code for plotting the figures is the notebook Plot_figures.ipynb</p> <p>Fig1/simulation_output/ : Model output necessary for plotting the first figure </p> <p>The last timestep of each simulation is provided. There is one file for 1D variables (ice volume, ice volume above flotation), and one file for 2D variables (ice sheet thickness for instance).</p> <ul> <li><span>melt_insoPI_output/ : melt branch, pre-industrial insolation. Results for different CO2 levels</span></li> <li><span>growth_insoPI_output/ : growth branch, pre-industrial insolation. Results for different CO2 levels</span></li> <li><span>melt_insoMAX_output/ : melt branch, maximum insolation. Results for different CO2 levels</span></li> <li><span>growth_insoMIN_output/ : growth branch, minimum insolation. Results for different CO2 levels</span></li> </ul> <p><span>compute_SLR_equivalent.py : code to compute the ice sheet volume in SLRe based on model output</span></p> <p><span>Fig1/SLR_files/ : contains the equilibrium ice sheet volume of the different simulations according to the CO2 level</span></p> <p> </p> <p>Fig2/simulation_output/ : Model output necessary for plotting the second figure </p> <p>The last timestep of each simulation is provided. </p> <ul> <li><span>melt_insoPI_enhancedmelt_albfb/ : melt branch, pre-industrial insolation, enhanced melt and albedo feedback. Results for different CO2 levels</span></li> <li><span>growth_insoPI_enhancedmelt_albfb/ : growth branch, pre-industrial insolation, enhanced melt and albedo feedback. Results for different CO2 levels</span></li> <li><span>melt_insoPI_enhancedmelt_fixedalb/ : melt branch, pre-industrial insolation, enhanced melt, no albedo feedback. Results for different CO2 levels</span></li> <li><span>growth_insoPI_enhancedmelt_fixedalb/: growth branch, pre-industrial insolation, enhanced melt, no albedo feedback. Results for different CO2 levels</span></li> </ul> <p><span>compute_SLR_equivalent.py : code to compute the ice sheet volume in SLRe based on model output</span></p> <p><span>Fig2/SLR_files/ : contains the equilibrium ice sheet volume of the different simulations according to the CO2 level</span></p> <p> </p> <p><span>Fig3/simulation_output/ : Model output necessary for plotting the third figure </span></p> <ul> <li><span>1xCO2_nocoupling/ : simulation with pre-industrial CO2 levels and insolation and no coupling to the ice sheet model</span></li> <li><span>8xCO2_nocoupling/ : simulation with 8xpiCO2 (pre-industrial CO2) levels, pre-industrial insolation and no coupling to the ice sheet model</span></li> <li><span>8xCO2_transient_albfb/ : quasi transient simulation, 8xpiCO2 levels, pre-industrial insolation, coupling with the ice sheet model </span></li> <li><span>8xCO2_transient_fixedalb/ : quasi transient simulation, 8xpiCO2 levels, pre-industrial insolation, coupling with the ice sheet model excluding the albedo-melt feedback</span></li> </ul> <p> </p>
Letters of Stone: a podcast interview with Steve Robins
<p>A blog entry of an interview conducted with Steve Robins, the writer of the book- Letters of Stone: From Nazi Germany to South Africa (Penguin Books, 2016<br> </p>
Correction to "Detecting distortions of peripherally presented letter stimuli under crowded conditions"
<p>We discovered a bug in the code producing radial frequency distortions for our paper</p> <p>Wallis, T. S. A., Tobias, S., Bethge, M., & Wichmann, F. A. (2017). Detecting distortions of peripherally presented letter stimuli under crowded conditions. Attention, Perception, & Psychophysics. https://doi.org/10.3758/s13414-016-1245-x</p> <p>In this correction, we fixed the bug, remeasured data for Experiment 1 from the paper, and found that our substantive conclusions remain.</p>
FIGURE 11. Letter from A.E. Wade, February 1960 in Contributions to a history of New Zealand lichenology 5*. James Murray (1923-1961) †
FIGURE 11. Letter from A.E. Wade, February 1960 (James Murray correspondence, OTA) [Photo: D.J. Galloway]
FIGURE. Maximum clade credibility tree of a post-burnin Bayesian analysis (100 million generations), based on nuclear (agt1, ETS, g3pdh, phyC, rpb2) and plastid (atpB–rbcL, matK, rps16, ycf1 pos. 1113-2103, ycf1 pos. 4492-5440) data. Above the branches, Bayesian posterior probabilities (PP) and maximum-likelihood bootstrap support (BS) are shown (PP/BS). The scale bar below the tree shows the branch length for 0.004 substitutions per nucleotide position. Capital letters at the branches are referred to in the tree description. in Re-evaluation of the Amazonian Hylaeaicum (Bromeliaceae: Bromelioideae) based on neglected morphological traits and molecular evidence
FIGURE. Maximum clade credibility tree of a post-burnin Bayesian analysis (100 million generations), based on nuclear (agt1, ETS, g3pdh, phyC, rpb2) and plastid (atpB–rbcL, matK, rps16, ycf1 pos. 1113-2103, ycf1 pos. 4492-5440) data. Above the branches, Bayesian posterior probabilities (PP) and maximum-likelihood bootstrap support (BS) are shown (PP/BS). The scale bar below the tree shows the branch length for 0.004 substitutions per nucleotide position. Capital letters at the branches are referred to in the tree description.
FIGURE. Bayesian tree of New Zealand spider orchids (Corybas) based on DNA sequence data from ITS, trnL-trnF and psbJ-petA. Major clades are indicated by open bars and capital letters, members of the C. trilobus aggregate are shaded, and posterior probabilities/ bootstrap percentages (≥50) indicated by numbers near each node. NI: North Island, SI: South Island, MCQI: Macquarie Island, CHI: Chatham Island in Five new species of Corybas (Diurideae, Orchidaceae) endemic to New Zealand and phylogeny of the Nematoceras clade
FIGURE. Bayesian tree of New Zealand spider orchids (Corybas) based on DNA sequence data from ITS, trnL-trnF and psbJ-petA. Major clades are indicated by open bars and capital letters, members of the C. trilobus aggregate are shaded, and posterior probabilities/ bootstrap percentages (≥50) indicated by numbers near each node. NI: North Island, SI: South Island, MCQI: Macquarie Island, CHI: Chatham Island
Supplementary tables for Geophysical Research Letters_2022GL101947
<p>Data associated with the publication " Evolutionary stasis during the Mesoproterozoic Columbia-Rodinia supercontinent transition"</p>
Datasets, scripts and Jupyter Notebook for "Two distinct magma storage regions at Ambrym volcano detected by satellite geodesy", Geophysical Research Letters
<p>This repository includes scripts and files necessary to create Figure 1 (<strong>S1.zip </strong>and <strong>plot_TS_Ambrym_2019_2022.py</strong>) in "Two distinct magma storage regions at Ambrym volcano detected by satellite geodesy", <em>Geophysical Research Letters</em>. We also include the Jupyter Notebook used to run the EnKF data assimilation (<strong>enkf_notebook.zip) </strong>and produce Figures 2 and 3. The Jupyter Notebook and files used to produce Figure 4b,c can be found on <a href="http://github.com/tshreve/jupyterNBs/">GitHub</a>.</p> <p>This version corrects a bug in the code used to plot the cross-sections in Figure 3 with <strong>enkf_notebook.zip</strong>.</p>
Dataset for MNRAS Letter: The stellar thermal wind as a consequence of oblateness
<p>This dataset contains temperature anomalies published as figure 2 and table 1 of the MNRAS Letter: The stellar thermal wind as a consequence of oblateness. This dataset also contains the entropy anomalies (not discussed in the paper), the rotation rate and its derivatives (computed from the <a href="https://zenodo.org/record/8171573">Howe 2023 dataset</a>), and the interpolated model S profiles (computed from the dataset at J. Christensen-Dalsgaard's <a href="https://users-phys.au.dk/jcd/solar_models/">personal website</a>). For more information, see the README.pdf document. </p>
Dataset for paper "Equatorial Pacific sea-air CO2 exchange modulated by upper ocean circulation during the last deglaciation" submittted to Geophysical Research Letters
<p>Data of the <em>p</em>CO<sub>2</sub> and ∆<em>p</em>CO<sub>2_sw-atm</sub> from <em>G. ruber</em> 𝛿<sup>11</sup>B, 𝛿<sup>11</sup>B of <em>G. sacculifer</em>, 𝛿<sup>18</sup>O of <em>G. ruber</em> and <em>P. obliquiloculata</em>, ∆𝛿<sup>18</sup>O<sub>P-G</sub>, bulk 𝛿<sup>15</sup>N in core MD10-3340 (0º31.0’S, 128º43.5’E, water depth 1094 m), and upper Ocean Heat Content (OHC) in the Western Equatorial Pacific (WEP).</p>
ScienceDex guides
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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.