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#spectroscopy β€” Public Fediverse posts

Live and recent posts from across the Fediverse tagged #spectroscopy, aggregated by home.social.

  1. πŸ“£ I'm planning to organize an online series of webinars/workshops, focused on #chemometrics and #MachineLearning for #spectroscopy (using #Python )

    I'd like it to be beginner-friendly and informal.

    πŸ†“ Free registration

    πŸ›οΈ Tutorial and research talks (including guest speakers and workshop sessions)

    πŸ“… Monthly or fortnightly schedule

    πŸ’» Fully online

    If it sound like you may be interested, please read more and register your interest here
    nirpyresearch.com/nirpy-webina

    #Webinar

  2. πŸ“£ I'm planning to organize an online series of webinars/workshops, focused on #chemometrics and #MachineLearning for #spectroscopy (using #Python )

    I'd like it to be beginner-friendly and informal.

    πŸ†“ Free registration

    πŸ›οΈ Tutorial and research talks (including guest speakers and workshop sessions)

    πŸ“… Monthly or fortnightly schedule

    πŸ’» Fully online

    If it sound like you may be interested, please read more and register your interest here
    nirpyresearch.com/nirpy-webina

    #Webinar

  3. πŸ“£ I'm planning to organize an online series of webinars/workshops, focused on #chemometrics and #MachineLearning for #spectroscopy (using #Python )

    I'd like it to be beginner-friendly and informal.

    πŸ†“ Free registration

    πŸ›οΈ Tutorial and research talks (including guest speakers and workshop sessions)

    πŸ“… Monthly or fortnightly schedule

    πŸ’» Fully online

    If it sound like you may be interested, please read more and register your interest here
    nirpyresearch.com/nirpy-webina

    #Webinar

  4. πŸ“£ I'm planning to organize an online series of webinars/workshops, focused on #chemometrics and #MachineLearning for #spectroscopy (using #Python )

    I'd like it to be beginner-friendly and informal.

    πŸ†“ Free registration

    πŸ›οΈ Tutorial and research talks (including guest speakers and workshop sessions)

    πŸ“… Monthly or fortnightly schedule

    πŸ’» Fully online

    If it sound like you may be interested, please read more and register your interest here
    nirpyresearch.com/nirpy-webina

    #Webinar

  5. πŸ“£ I'm planning to organize an online series of webinars/workshops, focused on #chemometrics and #MachineLearning for #spectroscopy (using #Python )

    I'd like it to be beginner-friendly and informal.

    πŸ†“ Free registration

    πŸ›οΈ Tutorial and research talks (including guest speakers and workshop sessions)

    πŸ“… Monthly or fortnightly schedule

    πŸ’» Fully online

    If it sound like you may be interested, please read more and register your interest here
    nirpyresearch.com/nirpy-webina

    #Webinar

  6. If your #spectroscopy dataset is small, deterministic data subdivision into training and test sets may be the way to go πŸ”¬

    The SPXY algorithm is an extension of the Kennard-Stone method that selects training samples to maximize coverage of both spectra (X) and response variable (Y) at the same time.

    Here's a primer, with a #Python implementation for #NIR spectroscopy.

    nirpyresearch.com/spxy-algorit

    #Chemometrics #MachineLearning

  7. If your #spectroscopy dataset is small, deterministic data subdivision into training and test sets may be the way to go πŸ”¬

    The SPXY algorithm is an extension of the Kennard-Stone method that selects training samples to maximize coverage of both spectra (X) and response variable (Y) at the same time.

    Here's a primer, with a #Python implementation for #NIR spectroscopy.

    nirpyresearch.com/spxy-algorit

    #Chemometrics #MachineLearning

  8. If your #spectroscopy dataset is small, deterministic data subdivision into training and test sets may be the way to go πŸ”¬

    The SPXY algorithm is an extension of the Kennard-Stone method that selects training samples to maximize coverage of both spectra (X) and response variable (Y) at the same time.

    Here's a primer, with a #Python implementation for #NIR spectroscopy.

    nirpyresearch.com/spxy-algorit

    #Chemometrics #MachineLearning

  9. If your #spectroscopy dataset is small, deterministic data subdivision into training and test sets may be the way to go πŸ”¬

    The SPXY algorithm is an extension of the Kennard-Stone method that selects training samples to maximize coverage of both spectra (X) and response variable (Y) at the same time.

    Here's a primer, with a #Python implementation for #NIR spectroscopy.

    nirpyresearch.com/spxy-algorit

    #Chemometrics #MachineLearning

  10. If your #spectroscopy dataset is small, deterministic data subdivision into training and test sets may be the way to go πŸ”¬

    The SPXY algorithm is an extension of the Kennard-Stone method that selects training samples to maximize coverage of both spectra (X) and response variable (Y) at the same time.

    Here's a primer, with a #Python implementation for #NIR spectroscopy.

    nirpyresearch.com/spxy-algorit

    #Chemometrics #MachineLearning

  11. Cells under the spotlight reveal their inner secrets

    All living things are made of cells, and the molecular machinery within them is imperative to survival. Different…
    #NewsBeep #News #Science #CA #Canada #Cell #Nutrients #Protein #Proteome #Proteomics #Ramanspectroscopy #research #RNA #Spectroscopy #students
    newsbeep.com/ca/633294/

  12. Timing And Style Of Tectonic Assembly And Exhumation Of The Mchugh Complex Within The Chugach-Kodiak Accretionary Wedge, Alaska
    --
    doi.org/10.1029/2025TC009004 <-- shared paper
    --
    discoveryalert.com.au/chugach- <-- shared technical article
    --
    [this paper is WAY over my head in terms of the nuance of structural geology, but still fascinating; further, I have to say: these are TRULY gorgeous, well-designed & presented, and useful geologic maps, cross-sections, annotated photographs and other visualisations (I am jealous of that level of skill, in the BEST of ways!)]
    #geology #structuralgeology #fieldwork #geologic #mapping #KenaiPeninsula #McHughComplex #tectonics #underplating #faulting #subduction #erosion #Exhumation #ChugachKodiak #AccretionaryWedge #Alaska #coast #coastal #mineralogy #transects #crosssections #model #modeling #sampling #spectroscopy #accretionary #accretionarymargin #plateboundary #trench #interpretation #peneplanation #forearc

  13. Dumb NMR question. Why don't we see splitting from 35Cl or 37Cl in the solvent signal when we run either 1H or 13C NMR? Is it being decoupled as with {1H}13C or does it have something to do with the gyromagnetic ratio or???? #NMR #coupling #decoupling #spectroscopy #chemistry #chemchat #help

  14. I learnt about the "entropy of the derivative" or delentropy from the paper linked.

    The idea is that the standard formula for information entropy doesn't distinguish between permutations. The entropy formula βˆ’βˆ‘p(x)logp(x) depends on p(x) which, absent any extra information about a signal, is estimated by the histogram of that signal.

    Now, if we do a random permutation of the values of the signal, the histogram doesn't change, so the entropy doesn't change. To find an 'entropy metric' that accounts for that we need to go to the second order, calculating the entropy of the signal derivative.

    The delentropy is sensitive to the actual shape of a signal or spectrum, not only the distribution of its values.

    arxiv.org/abs/1609.01117

    #physics #SignalProcessing #spectroscopy

  15. It took a while, but I'm finally back to writing my blog 😎

    The first installment for 2026 is an easy introduction to calculating information #entropy for optical spectra (or for any signal, really).

    In my blog, I focus on #data analysis (#chemometrics, machine learning) applied to optical and near-infrared #spectroscopy Smoothing, or denoising, is one of the most common steps to work with spectroscopy data, and information entropy can be used as a criterion to guide the smoothing process.

    Better still, the entropy of the derivative of a signal can help with that, because it accounts for the shape of the signal more naturally.

    Read more at nirpyresearch.com/information-

    #MachineLearning #NIR #Physics

  16. It took a while, but I'm finally back to writing my blog 😎

    The first installment for 2026 is an easy introduction to calculating information #entropy for optical spectra (or for any signal, really).

    In my blog, I focus on #data analysis (#chemometrics, machine learning) applied to optical and near-infrared #spectroscopy Smoothing, or denoising, is one of the most common steps to work with spectroscopy data, and information entropy can be used as a criterion to guide the smoothing process.

    Better still, the entropy of the derivative of a signal can help with that, because it accounts for the shape of the signal more naturally.

    Read more at nirpyresearch.com/information-

    #MachineLearning #NIR #Physics

  17. It took a while, but I'm finally back to writing my blog 😎

    The first installment for 2026 is an easy introduction to calculating information #entropy for optical spectra (or for any signal, really).

    In my blog, I focus on #data analysis (#chemometrics, machine learning) applied to optical and near-infrared #spectroscopy Smoothing, or denoising, is one of the most common steps to work with spectroscopy data, and information entropy can be used as a criterion to guide the smoothing process.

    Better still, the entropy of the derivative of a signal can help with that, because it accounts for the shape of the signal more naturally.

    Read more at nirpyresearch.com/information-

    #MachineLearning #NIR #Physics

  18. It took a while, but I'm finally back to writing my blog 😎

    The first installment for 2026 is an easy introduction to calculating information #entropy for optical spectra (or for any signal, really).

    In my blog, I focus on #data analysis (#chemometrics, machine learning) applied to optical and near-infrared #spectroscopy Smoothing, or denoising, is one of the most common steps to work with spectroscopy data, and information entropy can be used as a criterion to guide the smoothing process.

    Better still, the entropy of the derivative of a signal can help with that, because it accounts for the shape of the signal more naturally.

    Read more at nirpyresearch.com/information-

    #MachineLearning #NIR #Physics

  19. It took a while, but I'm finally back to writing my blog 😎

    The first installment for 2026 is an easy introduction to calculating information #entropy for optical spectra (or for any signal, really).

    In my blog, I focus on #data analysis (#chemometrics, machine learning) applied to optical and near-infrared #spectroscopy Smoothing, or denoising, is one of the most common steps to work with spectroscopy data, and information entropy can be used as a criterion to guide the smoothing process.

    Better still, the entropy of the derivative of a signal can help with that, because it accounts for the shape of the signal more naturally.

    Read more at nirpyresearch.com/information-

    #MachineLearning #NIR #Physics