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1,605 results for “1995”

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zenodo36/100

Figure 2 in Systematic list of Genus Megophrys Kuhl and van Hasselt, 1822 (Amphibia: Anura: Megophryidae) in Meghalaya, North-East India with a discussion on the distribution of M. wuliangshanensis Ye and Fei, 1995 in India

Figure 2. Femoral glands of Megophrys major

opencc-by-4.0Dec 2017View details →
zenodo36/100

Figure 1 in Systematic list of Genus Megophrys Kuhl and van Hasselt, 1822 (Amphibia: Anura: Megophryidae) in Meghalaya, North-East India with a discussion on the distribution of M. wuliangshanensis Ye and Fei, 1995 in India

Figure 1. Dorsal view of Megophrys major

opencc-by-4.0Dec 2017View details →
zenodo36/100

Figure 3 in Systematic list of Genus Megophrys Kuhl and van Hasselt, 1822 (Amphibia: Anura: Megophryidae) in Meghalaya, North-East India with a discussion on the distribution of M. wuliangshanensis Ye and Fei, 1995 in India

Figure 3. Dorsal view of Megophrys oropedion

opencc-by-4.0Dec 2017View details →
zenodo36/100

SuperDARN data in netCDF format (1995-Feb)

<p>1995-Feb SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroJul 2022View details →
zenodo36/100

SuperDARN data in netCDF format (1995-Apr)

<p>1995-Apr SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroJul 2022View details →
zenodo36/100

SuperDARN data in netCDF format (1995-Jun)

<p>1995-Jun SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroJul 2022View details →
zenodo36/100

SuperDARN data in netCDF format (1995-Jan)

<p>1995-Jan SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroJul 2022View details →
zenodo36/100

SuperDARN data in netCDF format (1995-May)

<p>1995-May SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroJul 2022View details →
zenodo36/100

SuperDARN data in netCDF format (1995-Mar)

<p>1995-Mar SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroJul 2022View details →
zenodo36/100

SuperDARN data in netCDF format (1995-Jul)

<p>1995-Jul SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroJul 2022View details →
zenodo36/100

SuperDARN data in netCDF format (1995-Aug)

<p>1995-Aug SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroJul 2022View details →
zenodo36/100

SuperDARN data in netCDF format (1995-Sep)

<p>1995-Sep SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroJul 2022View details →
zenodo36/100

SuperDARN data in netCDF format (1995-Nov)

<p>1995-Nov SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroJul 2022View details →
zenodo36/100

SuperDARN data in netCDF format (1995-Oct)

<p>1995-Oct SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroJul 2022View details →
zenodo36/100

SuperDARN data in netCDF format (1995-Dec)

<p>1995-Dec SuperDARN radar data in netCDF format. These files were produced using versions 2.5 and 3.0 of the public FitACF algorithm, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here:&nbsp;https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>

opencc-zeroJul 2022View details →
zenodo36/100

AsiaRiceYield4km: Seasonal Rice Yield in Asia from 1995 to 2015

<p><strong><em>请注意,我们已更新版本,包含两个名为 Version1 和 Version2 的文件!</em></strong></p> <p>第一个文件名为<em><strong>Version1.zip</strong></em>,是<strong><em>之前的版本</em></strong>,其中包含 126 个压缩到单个文件夹中的 .tif 文件。</p> <p><em>该文件支持地球系统科学数据中发表的题为&ldquo; AsiaRiceYield4km:1995 年至 2015 年亚洲季节性水稻产量</em>&rdquo;(https://doi.org/10.5194/essd-15-791-2023)的出版物。</p> <p>以下是<strong><em>Version1.zip</em></strong>的描述:</p> <p><strong><em>吴华清</em></strong>和<strong><em>&nbsp;张静</em></strong>对本文的贡献相同,为共同第一作者。</p> <p>该数据集提供了1995年至2015年亚洲主要稻米生产国4公里网格季节性稻米产量。</p> <p>*** 数据文件为&ldquo;.tif&rdquo;格式</p> <p>*** 时间分辨率:季节性</p> <p>*** 时间范围:1995-2015</p> <p>*** 像素大小:4 公里</p> <p>*** 投影信息:EPSG:4326</p> <p>本数据库使用的地图边界并不意味着我们对任何国家、领土、城市或地区或其当局的法律地位,或对其边界或边界的划定发表任何意见。</p> <p>至于名为<em><strong>Version2.zip</strong></em>的文件,则是<em><strong>更新版本</strong></em>,将<strong><em>东南亚的</em></strong>研究期<strong><em>从 1991 年延长至 2021 年,使用相同的产量估算方法。本次更新由</em></strong><strong><em>程飞</em></strong>进行。&nbsp;</p> <p>以下是<strong><em>Version 2.zip</em></strong>的描述:</p> <p>该数据集提供了1991年至2021年东南亚主要稻米生产国0.05&deg;网格季节性稻米产量。</p> <p>*** 数据文件为&ldquo;.nc&rdquo;格式</p> <p>*** 时间分辨率:季节性</p> <p>*** 时间范围:1991-2021</p> <p>*** 像素大小:0.05&deg;</p> <p>*** 投影信息:EPSG:4326</p>

opencc-by-4.0Aug 2022View details →
zenodo36/100

Survey of India Topo Sheet 64J7 1995 2nd Edition

<p>Survey of India Topo Sheet 64J7 1995 2nd Edition&nbsp;</p>

opencc-by-nc-nd-4.0Jan 2019View details →
zenodo36/100

Binary black-hole simulation SXS:BBH:1995

Simulation of a black-hole binary system evolved by the <a href="https://www.black-holes.org/code/SpEC.html">SpEC code</a>.

opencc-by-4.0Mar 2019View details →
zenodo36/100

Constant Hue Loci Data - Hung and Berns (1995)

<p>This deposit only contains the extracted tabular data from&nbsp;<em>Hung, P.-C., &amp; Berns, R. S. (1995). Determination of constant Hue Loci for a CRT gamut and their predictions using color appearance spaces. Color Research &amp; Application, 20(5), 285&ndash;295. doi:10.1002/col.5080200506</em>, please use the following&nbsp;link or DOI for the original publication.<br> <br> <strong>Source URL</strong>:&nbsp;<a href="https://onlinelibrary.wiley.com/doi/abs/10.1002/col.5080200506">https://onlinelibrary.wiley.com/doi/abs/10.1002/col.5080200506</a><br> <strong>Source DOI</strong>: 10.1002/col.5080200506f</p> <p><strong>Determination of constant Hue Loci for a CRT gamut and their predictions using color appearance spaces</strong></p> <p>A colorimetrically characterized computer‐controlled CRT display was used to determine 24 loci of constant perceived hue for pseudo‐object related stimuli, sampling the display&#39;s interior color gamut at constant lightness and the edge of its gamut at variable lightness. Nine observers performed three replications generating matching data at 132 positions. the constant hue loci were used to evaluate the correlation between perceived hue and hue angle of CIELAB, CIELUV, Hunt, and Nayatani color appearance spaces. the CIELAB, CIELUV, and Hunt spaces exhibited large errors in the region of the blue CRT primary, while the Nayatani and CIELUV spaces produced large errors in the region of the red primary for constant lightness stimuli. Along the edge of the CRT&#39;s color gamut (variable lightness stimuli), all the spaces had a similar trend, large errors in the cyan region. the differences in performance between the four spaces were not statistically significant for the constant lightness stimuli. For the variable lightness stimuli, CIELAB and CIELUV had statistically superior performance in comparison with the Nayatani space and equal performance in comparison with the Hunt space. It was concluded that for imaging applications, a new color appearance space needs to be developed that will produce small hue error artifacts when used for gamut mapping along loci of constant hue angle.</p>

opennotspecifiedAug 2019View details →
zenodo36/100

Fig. 2 in New sites of the endangered Marmaris Salamander, Lyciasalamandra flavimembris (Mutz and Steinfartz 1995), (Caudata: Salamandridae) from Muğla, Turkey

Fig. 2. General view of new site habitats. [A]. Arıcılar, [B,C]. Selimiye [D]. Taşlıca.

opencc-by-4.0Dec 2018View details →

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Allen Brain Atlas

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Last verified 2026-04-30Open record

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dandi-nwb
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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.

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OpenNeuro

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neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record