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  1. Free, publicly-accessible full text available May 1, 2023
  2. Rapid progress in machine learning offers new opportunities for the automated analysis of multidimensional NMR spectra ranging from protein NMR to metabolomics applications. Most recently, it has been demonstrated how deep neural networks (DNN) designed for spectral peak picking are capable of deconvoluting highly crowded NMR spectra rivaling the facilities of human experts. Superior DNN-based peak picking is one of a series of critical steps during NMR spectral processing, analysis, and interpretation where machine learning is expected to have a major impact. In this perspective, we lay out some of the unique strengths as well as challenges of machine learningmore »approaches in this new era of automated NMR spectral analysis. Such a discussion seems timely and should help define common goals for the NMR community, the sharing of software tools and standardization of protocols, and calibrate expectations. It will also help prepare for an NMR future where machine learning and artificial intelligence tools will be common place.« less
    Free, publicly-accessible full text available April 1, 2023
  3. Abstract Magnetic fields have an important role in the evolution of interstellar medium and star formation 1,2 . As the only direct probe of interstellar field strength, credible Zeeman measurements remain sparse owing to the lack of suitable Zeeman probes, particularly for cold, molecular gas 3 . Here we report the detection of a magnetic field of +3.8 ± 0.3 microgauss through the H  I narrow self-absorption (HINSA) 4,5 towards L1544 6,7 —a well-studied prototypical prestellar core in an early transition between starless and protostellar phases 8–10 characterized by a high central number density 11 and a low central temperature 12 . Amore »combined analysis of the Zeeman measurements of quasar H  I absorption, H  I emission, OH emission and HINSA reveals a coherent magnetic field from the atomic cold neutral medium (CNM) to the molecular envelope. The molecular envelope traced by the HINSA is found to be magnetically supercritical, with a field strength comparable to that of the surrounding diffuse, magnetically subcritical CNM despite a large increase in density. The reduction of the magnetic flux relative to the mass, which is necessary for star formation, thus seems to have already happened during the transition from the diffuse CNM to the molecular gas traced by the HINSA. This is earlier than envisioned in the classical picture where magnetically supercritical cores capable of collapsing into stars form out of magnetically subcritical envelopes 13,14 .« less
    Free, publicly-accessible full text available January 6, 2023
  4. Free, publicly-accessible full text available November 1, 2022
  5. The analysis of nuclear magnetic resonance (NMR) spectra for the comprehensive and unambiguous identification and characterization of peaks is a difficult, but critically important step in all NMR analyses of complex biological molecular systems. Here, we introduce DEEP Picker, a deep neural network (DNN)-based approach for peak picking and spectral deconvolution which semi-automates the analysis of two-dimensional NMR spectra. DEEP Picker includes 8 hidden convolutional layers and was trained on a large number of synthetic spectra of known composition with variable degrees of crowdedness. We show that our method is able to correctly identify overlapping peaks, including ones that aremore »challenging for expert spectroscopists and existing computational methods alike. We demonstrate the utility of DEEP Picker on NMR spectra of folded and intrinsically disordered proteins as well as a complex metabolomics mixture, and show how it provides access to valuable NMR information. DEEP Picker should facilitate the semi-automation and standardization of protocols for better consistency and sharing of results within the scientific community.« less
    Free, publicly-accessible full text available October 1, 2022
  6. Context. The carbon monoxide (CO) molecular line at around 46655 Å in solar infrared spectra is often used to investigate the dynamic behavior of the cold heart of the solar atmosphere, i.e., sunspot oscillation, especially at the sunspot umbra. Aims. We investigated sunspot oscillation at Doppler velocities of the CO 7-6 R67 and 3-2 R14 lines that were measured by the Cryogenic Infrared Spectrograph (CYRA), as well as the line profile of Mg  II k line that was detected by the Interface Region Imaging Spectrograph (IRIS). Methods. A single Gaussian function is applied to each CO line profile to extractmore »the line shift, while the moment analysis method is used for the Mg  II k line. Then the sunspot oscillation can be found in the time–distance image of Doppler velocities, and the quasi-periodicity at the sunspot umbra are determined from the wavelet power spectrum. Finally, the cross-correlation method is used to analyze the phase relation between different atmospheric levels. Results. At the sunspot umbra, a periodicity of roughly 5 min is detected at the Doppler velocity range of the CO 7-6 R67 line that formed in the photosphere, while a periodicity of around 3 min is discovered at the Doppler velocities of CO 3-2 R14 and Mg  II k lines that formed in the upper photosphere or the temperature minimum region and the chromosphere. A time delay of about 2 min is measured between the strong CO 3-2 R14 line and the Mg  II k line. Conclusions. Based on the spectroscopic observations from the CYRA and IRIS, the 3 min sunspot oscillation can be spatially resolved in the Doppler shifts. It may come from the upper photosphere or the temperature minimum region and then propagate to the chromosphere, which might be regarded as a propagating slow magnetoacoustic wave.« less