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#deconvolution

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amen zwa, esq.<p>My son, Ronan, who is double-majoring in <a href="https://mathstodon.xyz/tags/biochemistry" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>biochemistry</span></a> and <a href="https://mathstodon.xyz/tags/physics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>physics</span></a>, is working at Georgetown University in DC this summer, on a <a href="https://mathstodon.xyz/tags/cancer" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>cancer</span></a> research internship. His work focuses on <a href="https://mathstodon.xyz/tags/cell" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>cell</span></a>-type <a href="https://mathstodon.xyz/tags/deconvolution" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>deconvolution</span></a> in spatial <a href="https://mathstodon.xyz/tags/transcriptomics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>transcriptomics</span></a>.</p><p>I know nothing about biology, but I am assisting him with deconvolution. My MathsTodon friends, have you any guidance to offer, either in mathematics or in biology?</p>
Albert Cardona<p><span class="h-card" translate="no"><a href="https://mathstodon.xyz/@NadiaHalidi" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>NadiaHalidi</span></a></span> </p><p>Workshop on True Image Deconvolution, Restoration, and Analysis</p><p>When: March 13th, 2025 – 3 days from now.</p><p>2 hours long: 14:30 - 16:30 CET</p><p>Where: online, via zoom.</p><p>Program: <a href="https://www.crg.eu/en/event/workshop-true-image-deconvolution-restoration-and-analysis" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">crg.eu/en/event/workshop-true-</span><span class="invisible">image-deconvolution-restoration-and-analysis</span></a></p><p>Registration: <a href="https://apps.crg.es/content/internet/events/webforms/workshop-true-image-deconvolution-restoration-and-analysis" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">apps.crg.es/content/internet/e</span><span class="invisible">vents/webforms/workshop-true-image-deconvolution-restoration-and-analysis</span></a></p><p><a href="https://mathstodon.xyz/tags/BioimageAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>BioimageAnalysis</span></a> <a href="https://mathstodon.xyz/tags/PSF" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PSF</span></a> <a href="https://mathstodon.xyz/tags/deconvolution" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>deconvolution</span></a> <a href="https://mathstodon.xyz/tags/ImageProcessing" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ImageProcessing</span></a> <a href="https://mathstodon.xyz/tags/microscopy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>microscopy</span></a></p>
TomKrajci 🇺🇦 🏳️‍🌈 🏳️‍⚧️<p>Three-day old waxing crescent moon - high resolution stack of 180 images.</p><p>(This is a continuation of my learning that started yesterday: <a href="https://universeodon.com/@KrajciTom/113758881213411285" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">universeodon.com/@KrajciTom/11</span><span class="invisible">3758881213411285</span></a> )</p><p>I am quite surprised at how much detail I could extract from the image stack, given that I was imaging through 2-1/2 air masses with a mediocre quality telephoto lens.</p><p>Screenshots 2, 3, and 4 show how the user of the deconvolution software needs to carefully choose the size of the Gaussian deconvolution kernel (expressed as a radius in pixels).</p><p>This image stack has such a high signal to noise ratio that if I boost contrast and brightness, earthshine is clearly visible with decent detail showing maria, highlands, craters, and ejecta rays. </p><p>"Lucky imaging" techniques and software are practically magic for high-resolution imaging.</p><p><a href="https://universeodon.com/tags/NewMexico" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NewMexico</span></a> <a href="https://universeodon.com/tags/Moon" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Moon</span></a> <a href="https://universeodon.com/tags/Infrared" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Infrared</span></a> <a href="https://universeodon.com/tags/Monochrome" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Monochrome</span></a> <a href="https://universeodon.com/tags/Telephoto" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Telephoto</span></a> <a href="https://universeodon.com/tags/Astronomy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Astronomy</span></a> <a href="https://universeodon.com/tags/Astrophotography" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Astrophotography</span></a> <a href="https://universeodon.com/tags/Photography" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Photography</span></a> <a href="https://universeodon.com/tags/BnW" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>BnW</span></a> <a href="https://universeodon.com/tags/Deconvolution" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Deconvolution</span></a> <a href="https://universeodon.com/tags/Math" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Math</span></a> <a href="https://universeodon.com/tags/ImageProcessing" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ImageProcessing</span></a></p>
TomKrajci 🇺🇦 🏳️‍🌈 🏳️‍⚧️<p>New Year, new image processing for sharper moon images.</p><p>Two-day old crescent on the evening of 1 January.</p><p>This is a first attempt at stacking multiple images and then using deconvolution to enhance the finer details.</p><p>I only took a small number of images, but results are promising.</p><p>2nd screen grab shows an analysis of my batch of 31 images. The green line is a plot sorted by image quality and shows that about 20% of my images were of high sharpness...half the images were of medium-low sharpness, and the remaining 30% were pretty bad. (Playing those images in sequence from best to worst was eye opening.)</p><p>In this case I discarded the worst 30% and stacked the remaining images. </p><p>Stacking software: <a href="https://www.autostakkert.com/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="">autostakkert.com/</span><span class="invisible"></span></a></p><p>Then I used deconvolution: <a href="https://greatattractor.github.io/imppg/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">greatattractor.github.io/imppg</span><span class="invisible">/</span></a></p><p><a href="https://en.wikipedia.org/wiki/Richardson%E2%80%93Lucy_deconvolution" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">en.wikipedia.org/wiki/Richards</span><span class="invisible">on%E2%80%93Lucy_deconvolution</span></a></p><p>Next clear night...take many, many images!</p><p><a href="https://universeodon.com/tags/NewMexico" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NewMexico</span></a> <a href="https://universeodon.com/tags/Moon" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Moon</span></a> <a href="https://universeodon.com/tags/Infrared" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Infrared</span></a> <a href="https://universeodon.com/tags/Monochrome" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Monochrome</span></a> <a href="https://universeodon.com/tags/Telephoto" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Telephoto</span></a> <a href="https://universeodon.com/tags/Astronomy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Astronomy</span></a> <a href="https://universeodon.com/tags/Astrophotography" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Astrophotography</span></a> <a href="https://universeodon.com/tags/Photography" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Photography</span></a> <a href="https://universeodon.com/tags/BnW" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>BnW</span></a> <a href="https://universeodon.com/tags/NewYear" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>NewYear</span></a> <a href="https://universeodon.com/tags/Deconvolution" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Deconvolution</span></a> <a href="https://universeodon.com/tags/Math" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Math</span></a> <a href="https://universeodon.com/tags/ImageProcessing" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ImageProcessing</span></a></p>
CellBioNews<p>Improving resolution and reducing noise in <a href="https://scientificnetwork.de/tags/fluorescence" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>fluorescence</span></a> <a href="https://scientificnetwork.de/tags/microscopy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>microscopy</span></a> with ensured fidelity.</p><p><a href="https://scientificnetwork.de/tags/deconvolution" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>deconvolution</span></a> <a href="https://scientificnetwork.de/tags/multi_resolution" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>multi_resolution</span></a></p><p><a href="https://phys.org/news/2024-08-resolution-noise-fluorescence-microscopy-fidelity.html" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">phys.org/news/2024-08-resoluti</span><span class="invisible">on-noise-fluorescence-microscopy-fidelity.html</span></a></p>
Jack Kamm<p>New preprint: Fine-scale cellular deconvolution via generalized maximum entropy on canonical correlation features <a href="https://mastodon.social/tags/singlecell" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>singlecell</span></a> <a href="https://mastodon.social/tags/deconvolution" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>deconvolution</span></a></p><p><a href="https://www.biorxiv.org/content/10.1101/2024.06.07.598010v1" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">biorxiv.org/content/10.1101/20</span><span class="invisible">24.06.07.598010v1</span></a></p>
Moritz Negwer<p>This 3D image stack deconvolution tool looks super useful for <a href="https://mstdn.science/tags/bioimageanalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bioimageanalysis</span></a> </p><p>Deconwolf enables high-performance deconvolution of widefield fluorescence microscopy images<br>Wernersson et al., Nature Methods 2024<br><a href="https://doi.org/10.1038/s41592-024-02294-7" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="ellipsis">doi.org/10.1038/s41592-024-022</span><span class="invisible">94-7</span></a></p><p>Github: <a href="https://github.com/elgw/deconwolf/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">github.com/elgw/deconwolf/</span><span class="invisible"></span></a> <br>Program: <a href="https://deconwolf.fht.org/" rel="nofollow noopener" translate="no" target="_blank"><span class="invisible">https://</span><span class="">deconwolf.fht.org/</span><span class="invisible"></span></a></p><p><a href="https://mstdn.science/tags/microscopy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>microscopy</span></a> <a href="https://mstdn.science/tags/ImageAnalysis" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>ImageAnalysis</span></a> <a href="https://mstdn.science/tags/deconvolution" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>deconvolution</span></a></p>
SVI Huygens<p>Simply combine pixel (co-occurence and correlation) or object-based <a href="https://mstdn.science/tags/colocalization" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>colocalization</span></a> analysis with corrections (like <a href="https://mstdn.science/tags/deconvolution" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>deconvolution</span></a>, crosstalk correction and chromatic aberration) in Huygens Workflow Processor, and increase the reliability of your measurements. Try Huygens at svi.nl</p>
Albert Cardona<p>"Ring Deconvolution Microscopy: An Exact Solution for Spatially-Varying Aberration Correction" by Amit Kohli et al. 2023 <a href="https://arxiv.org/abs/2206.08928" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="">arxiv.org/abs/2206.08928</span><span class="invisible"></span></a></p><p>Claims to solve the spatially-varying problem of deconvolution that makes it so computationally expensive, and with a single calibration image per instrument. Eager to give it a try soon.</p><p><a href="https://mathstodon.xyz/tags/deconvolution" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>deconvolution</span></a> <a href="https://mathstodon.xyz/tags/LSM" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>LSM</span></a> <a href="https://mathstodon.xyz/tags/imaging" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>imaging</span></a> <a href="https://mathstodon.xyz/tags/microscopy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>microscopy</span></a></p>
Daniel Fischer<p>Richardson-Lucy <a href="https://scicomm.xyz/tags/deconvolution" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>deconvolution</span></a> with a spatially Variant point-spread function of <a href="https://scicomm.xyz/tags/Chandra" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Chandra</span></a> - Supernova Remnant <a href="https://scicomm.xyz/tags/CassiopeiaA" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>CassiopeiaA</span></a> as an Example: <a href="https://arxiv.org/abs/2306.13355" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="">arxiv.org/abs/2306.13355</span><span class="invisible"></span></a> -&gt; Image Reconstruction Technique to Enhance the Clarity of High Spatial Resolution Space X-ray Images - Revealing fine structures in Cassiopeia A Supernova Remnant: <a href="https://english.rikkyo.ac.jp/news/2023/dn4ddm0000005dp0.html" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="ellipsis">english.rikkyo.ac.jp/news/2023</span><span class="invisible">/dn4ddm0000005dp0.html</span></a></p>
Dave Tabb<p>How mature are the identification algorithms for top-down <a href="https://mastodon.africa/tags/proteomics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>proteomics</span></a>? If we use two different algorithms on the same data, do we see the same proteoforms? I was recently lucky enough to invest two whole years in top-down <a href="https://mastodon.africa/tags/bioinformatics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bioinformatics</span></a>, courtesy of Julia Chamot-Rooke. Kyowon Jeong invested some serious time to teach me about <a href="https://mastodon.africa/tags/deconvolution" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>deconvolution</span></a>, too! We feature new data from Mowei Zhou for <a href="https://mastodon.africa/tags/phosphorylation" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>phosphorylation</span></a> proteomics.<br><a href="https://doi.org/10.1021/acs.jproteome.2c00673" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="ellipsis">doi.org/10.1021/acs.jproteome.</span><span class="invisible">2c00673</span></a></p>
Digital Science Center (DiSC)<p>Don't miss today's <a href="https://mstdn.science/tags/DiSCourseSeminar" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DiSCourseSeminar</span></a> with <span class="h-card"><a href="https://genomic.social/@Francesca_Finotello" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>Francesca_Finotello</span></a></span> at 12:00 (CEST) at DiSC, Innrain 15, 6020 Innsbruck or on Big Blue Button: <a href="https://webconference.uibk.ac.at/b/car-aab-cxf-o81" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="ellipsis">webconference.uibk.ac.at/b/car</span><span class="invisible">-aab-cxf-o81</span></a></p><p>Topic: Charting Tissue Complexity Through Transcriptomics <a href="https://mstdn.science/tags/Deconvolution" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Deconvolution</span></a></p><p><a href="https://mstdn.science/tags/multiomics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>multiomics</span></a> <a href="https://mstdn.science/tags/bioinformatics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>bioinformatics</span></a></p>
Digital Science Center (DiSC)<p>Join us on Friday, 12:00 (CEST) for another <a href="https://mstdn.science/tags/DiSCourseSeminar" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DiSCourseSeminar</span></a>.</p><p>Topic: Charting Tissue Complexity Through Transcriptomics <a href="https://mstdn.science/tags/Deconvolution" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Deconvolution</span></a></p><p>Speaker: <span class="h-card"><a href="https://genomic.social/@Francesca_Finotello" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>Francesca_Finotello</span></a></span> (DiSC &amp; Molecular Biology).</p><p>Location: Onsite at DiSC or online on Big Blue Button.</p><p>More: <a href="https://www.uibk.ac.at/disc/events/" rel="nofollow noopener" target="_blank"><span class="invisible">https://www.</span><span class="">uibk.ac.at/disc/events/</span><span class="invisible"></span></a></p>
Digital Science Center (DiSC)<p>Our next <a href="https://mstdn.science/tags/DiSCourseSeminar" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>DiSCourseSeminar</span></a> with <span class="h-card"><a href="https://genomic.social/@Francesca_Finotello" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>Francesca_Finotello</span></a></span>, Dept. of Molecular Biology &amp; DiSC <span class="h-card"><a href="https://wisskomm.social/@uniinnsbruck" class="u-url mention" rel="nofollow noopener" target="_blank">@<span>uniinnsbruck</span></a></span>, is scheduled for 5 May, 12:00 (CEST). Her talk is about Charting Tissue Complexity Through Transcriptomics <a href="https://mstdn.science/tags/Deconvolution" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Deconvolution</span></a>!</p><p>Read more here:<br><a href="https://www.uibk.ac.at/disc/event-documents/discourse/discourse_francesca-finotello_05052023.pdf" rel="nofollow noopener" target="_blank"><span class="invisible">https://www.</span><span class="ellipsis">uibk.ac.at/disc/event-document</span><span class="invisible">s/discourse/discourse_francesca-finotello_05052023.pdf</span></a></p>
Daniel Fischer<p>Galaxy image <a href="https://scicomm.xyz/tags/deconvolution" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>deconvolution</span></a> for weak <a href="https://scicomm.xyz/tags/GravitationaLensing" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>GravitationaLensing</span></a> with unrolled plug-and-play ADMM: <a href="https://academic.oup.com/mnrasl/article/522/1/L31/7075894" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="ellipsis">academic.oup.com/mnrasl/articl</span><span class="invisible">e/522/1/L31/7075894</span></a> -&gt; <a href="https://scicomm.xyz/tags/AI" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>AI</span></a> algorithm unblurs the cosmos; tool produces faster, more realistic images than current methods: <a href="https://news.northwestern.edu/stories/2023/03/ai-algorithm-unblurs-the-cosmos/" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="ellipsis">news.northwestern.edu/stories/</span><span class="invisible">2023/03/ai-algorithm-unblurs-the-cosmos/</span></a> and <a href="https://news.northwestern.edu/stories/2023/03/ai-algorithm-unblurs-the-cosmos/?fj=1" rel="nofollow noopener" target="_blank"><span class="invisible">https://</span><span class="ellipsis">news.northwestern.edu/stories/</span><span class="invisible">2023/03/ai-algorithm-unblurs-the-cosmos/?fj=1</span></a></p>
j_bertolotti<p><a href="https://mathstodon.xyz/tags/PhysicsFactlet" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PhysicsFactlet</span></a> <br>If you know the response function of your instrument, you can deconvolve it from your measurement to obtain a much sharper signal. But deconvolution is a dangerous procedure, as small mistakes in the kernel can result in heavy artefacts.<br><a href="https://mathstodon.xyz/tags/Visualization" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Visualization</span></a> <a href="https://mathstodon.xyz/tags/Imaging" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Imaging</span></a> <a href="https://mathstodon.xyz/tags/PointSpreadFunction" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>PointSpreadFunction</span></a> <a href="https://mathstodon.xyz/tags/Deconvolution" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Deconvolution</span></a> <a href="https://mathstodon.xyz/tags/Physics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>Physics</span></a></p>
David Kent, bird of the sea<p>i guess i'll do an <a href="https://mathstodon.xyz/tags/introduction" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>introduction</span></a>. i'm a <a href="https://mathstodon.xyz/tags/statistics" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>statistics</span></a> phd candidate at <a href="https://mathstodon.xyz/tags/cornell" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>cornell</span></a>. i work on non-parametric <a href="https://mathstodon.xyz/tags/deconvolution" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>deconvolution</span></a> (aspirational hashtag) theory and some <a href="https://mathstodon.xyz/tags/FunctionalData" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>FunctionalData</span></a> non-parametric regression stuff too (currently with <a href="https://mathstodon.xyz/tags/astronomy" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>astronomy</span></a> applications; spectroscopy, photometric redshift estimation, etc).</p><p>i'm learning <a href="https://mathstodon.xyz/tags/persian" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>persian</span></a> (سلام! خوبی؟) and <a href="https://mathstodon.xyz/tags/running" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>running</span></a> when i'm not doing stats or <a href="https://mathstodon.xyz/tags/lying" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>lying</span></a> <a href="https://mathstodon.xyz/tags/prone" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>prone</span></a> on the <a href="https://mathstodon.xyz/tags/floor" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>floor</span></a> in <a href="https://mathstodon.xyz/tags/despair" class="mention hashtag" rel="nofollow noopener" target="_blank">#<span>despair</span></a></p>