Spectral Mapping Research Articles

Automated Cough Sound Analysis for Detecting Childhood Pneumonia.

Pneumonia is one of the leading causes of death in children. Prompt diagnosis and treatment can help prevent these deaths, particularly in resource poor regions where deaths due to pneumonia are highest. Clinical symptom-based screening of childhood pneumonia yields excessive false positives, highlighting the necessity for additional rapid diagnostic tests. Cough is a prevalent symptom of acute respiratory illnesses and the sound of a cough can indicate the underlying pathological changes resulting from respiratory infections. In this study, we propose a fully automated approach to evaluate cough sounds to distinguish pneumonia from other acute respiratory diseases in children. The proposed method involves cough sound denoising, cough sound segmentation, and cough sound classification. The denoising algorithm utilizes multi-conditional spectral mapping with a multilayer perceptron network while the segmentation algorithm detects cough sounds directly from the denoised audio waveform. From the segmented cough signal, we extract various handcrafted features and feature embeddings from a pretrained deep learning network. A multilayer perceptron is trained on the combined feature set for detecting pneumonia. The method we propose is evaluated using a dataset comprising cough sounds from 173 children diagnosed with either pneumonia or other acute respiratory diseases. On average, the denoising algorithm improved the signal-to-noise ratio by 44%. Furthermore, a sensitivity and specificity of 91% and 86%, respectively, is achieved in cough segmentation and 82% and 71%, respectively, in detecting childhood pneumonia using cough sounds alone. This demonstrates its potential as a rapid diagnostic tool, such as using smartphone technology.

Further Properties of an Operator Commuting with an Injective Quasi-Nilpotent Operator

In (Aiena et al., Math. Proc. R. Irish Acad. 122A(2):101–116, 2022), it has been shown that a bounded linear operator T∈L(X)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$T\\in L(X)$$\\end{document}, defined on an infinite-dimensional complex Banach space X, for which there exists an injective quasi-nilpotent operator that commutes with it, has a very special structure of the spectrum. In this paper, we show that we have much more: if a such quasi-nilpotent operator does exist, then some of the spectra of T originating from B-Fredholm theory coalesce. Further, the spectral mapping theorem holds for all the B-Weyl spectra. Finally, the generalized version of Weyl type theorems hold for T assuming that T is of polaroid type. Our results apply to the operators that belong to the commutant of Volterra operators.

AFSleepNet: Attention-based multi-view feature fusion framework for pediatric sleep staging.

The widespread prevalence of sleep problems in children highlights the importance of timely and accurate sleep staging in the diagnosis and treatment of pediatric sleep disorders. However, most existing sleep staging methods rely on one-dimensional raw polysomnograms or two-dimensional spectrograms, which omit critical details due to single-view processing. This shortcoming is particularly apparent in pediatric sleep staging, where the lack of a specialized network fails to meet the needs of precision medicine. Therefore, we introduce AFSleepNet, a novel attention-based multi-view feature fusion network tailored for pediatric sleep analysis. The model utilizes multimodal data (EEG, EOG, EMG), combining one-dimensional convolutional neural networks to extract time-invariant features and bidirectional-long-short-term memory to learn the transition rules among sleep stages, as well as employing short-time Fourier transform to generate two-dimensional spectral maps. This network employs a fusion method with self-attention mechanism and innovative pre-training strategy. This strategy can maintain the feature extraction capabilities of AFSleepNet from different views, enhancing the robustness of the multi-view model while effectively preventing model overfitting, thereby achieving efficient and accurate automatic sleep stage analysis. A "leave-one-subject-out" cross-validation on CHAT and clinical datasets demonstrated the excellent performance of AFSleepNet, with mean accuracies of 87.5% and 88.1%, respectively. Superiority over existing methods improves the accuracy and reliability of pediatric sleep staging.

MONITORING OF WATER BODIES AND RECLAIMED LANDS AFFECTED BY WARFARE USING SATELLITE DATA

The paper presents the results of monitoring the state of water bodies and reclaimed lands affected by warfare using remote sensing methods and in-situ surveys. On the example of the flooding of the floodplain of the Irpin river by the waters of the Kyiv reservoir as a result of the destruction of the culvert structure, as well as the flooding of the floodplain of the Dnipro river near village Otradokamyanka after the explosion of the Kakhovska hydro power plant (HPP), the change in the area of inundation was calculated based on spectral index maps and surface classification using Sentinel-2 L2A imagery. On the base of Sentinel-2 L2A images, maps of SAVI and NDWI indices were obtained. They revealed the places of soil cover by sediments and the increase of the area of water bodies. Monitoring of reclaimed lands affected by warfare was carried out in the floodplain of the Irpin river on the Irpin Drainage and Moistening System during three time intervals: before the war in 2019; during the fighting in the spring of 2022 and a year after the end of military actions. Studies have shown a significant prevalence of waterlogged areas in the present time, which confirms the destruction of drainage network.The calculated values of the NDVI index turned out to be too high for agricultural crops, which indicates that the lands is overgrown with shrubs. Based on the results of the conducted monitoring, the territory was classified according to the degree of its damage by shell craters. Based on the results of the studies, it is recommended to monitor water bodies and reclaimed lands that have been affected by the war using images of different spatial resolution, a complex of spectral indices, a combination of image bands and in-situ surveys.

Raman spectral mapping reveal molecular changes in cellulose aging induced by ultraviolet and extreme ultraviolet radiation

Raman spectral mapping reveal molecular changes in cellulose aging induced by ultraviolet and extreme ultraviolet radiation

The discovery of a z = 0.7092 OH megamaser with the MIGHTEE survey

ABSTRACT We present the discovery of the most distant OH megamaser (OHM) to be observed in the main lines, using data from the MeerKAT International Giga-Hertz Tiered Extragalactic Exploration (MIGHTEE) survey. At a newly measured redshift of z = 0.7092, the system has strong emission in both the 1665 MHz (L ≈ 2500 L⊙) and 1667 MHz (L ≈ 4.5 × 104 L⊙) transitions, with both narrow and broad components. We interpret the broad line as a high-velocity-dispersion component of the 1667 MHz transition, with velocity v ∼ 330 km s−1 with respect to the systemic velocity. The host galaxy has a stellar mass of M⋆ = 2.95 × 1010 M⊙ and a star formation rate of SFR = 371 M⊙ yr−1, placing it ∼1.5 dex above the main sequence for star-forming galaxies at this redshift, and can be classified as an ultraluminous infrared galaxy. Alongside the optical imaging data, which exhibit evidence for a tidal tail, this suggests that the OHM arises from a system that is currently undergoing a merger, which is stimulating star formation and providing the necessary conditions for pumping the OH molecule to saturation. The OHM is likely to be lensed, with a magnification factor of ∼2.5, and perhaps more if the maser emitting region is compact and suitably offset relative to the centroid of its host galaxy’s optical light. This discovery demonstrates that spectral line mapping with the new generation of radio interferometers may provide important information on the cosmic merger history of galaxies.

Learning Degradation-Robust Spatiotemporal Frequency-Transformer for Video Super-Resolution.

Video Super-Resolution (VSR) aims to restore high-resolution (HR) videos from low-resolution (LR) videos. Existing VSR techniques usually recover HR frames by extracting pertinent textures from nearby frames with known degradation processes. Despite significant progress, grand challenges remain to effectively extract and transmit high-quality textures from high-degraded low-quality sequences, such as blur, additive noises, and compression artifacts. This work proposes a novel degradation-robust Frequency-Transformer (FTVSR++) for handling low-quality videos that carry out self-attention in a combined space-time-frequency domain. First, video frames are split into patches and each patch is transformed into spectral maps in which each channel represents a frequency band. It permits a fine-grained self-attention on each frequency band so that real visual texture can be distinguished from artifacts. Second, a novel dual frequency attention (DFA) mechanism is proposed to capture the global and local frequency relations, which can handle different complicated degradation processes in real-world scenarios. Third, we explore different self-attention schemes for video processing in the frequency domain and discover that a "divided attention" which conducts joint space-frequency attention before applying temporal-frequency attention, leads to the best video enhancement quality. Extensive experiments on three widely-used VSR datasets show that FTVSR++ outperforms state-of-the-art methods on different low-quality videos with clear visual margins. Code and pre-trained models are available at https://github.com/researchmm/FTVSR.

ALMA-IMF. VIII. Combination of Interferometric Continuum Images with Single-dish Surveys and Structural Analysis of Six Protoclusters

We present the combination of ALMA-IMF and single-dish continuum images from the MUSTANG-2 Galactic Plane Survey (MGPS90) at 3 mm and the Bolocam Galactic Plane Survey (BGPS) at 1 mm. Six and 10 out of the 15 ALMA-IMF fields are combined with MGPS90 and BGPS, respectively. The combination is made via the feathering technique. We used the dendrogram algorithm throughout the combined images, and performed further analysis in the six fields with the combination in both bands (G012.80, W43-MM1, W43-MM2, W43-MM3, W51-E, W51-IRS2). In these fields, we calculated spectral index maps and used them to separate regions dominated by dust or free–free emission, and then performed further structural analysis. We report the basic physical parameters of the dust-dominated (column densities, masses) and ionized (emission measures, hydrogen ionization photon rates) structures. We also searched for multiscale relations in the dust-dominated structures across the analyzed fields, finding that the fraction of mass in dendrogram leaves (which we label leaf mass efficiency (LME)) as a function of molecular gas column density follows a similar trend: a rapid, exponential-like growth, with maximum values approaching 100% in most cases. The observed behavior of the LME with the gas column is tentatively interpreted as an indicator of large star formation activity within the ALMA-IMF protoclusters. W51-E and G012.80 stand out as cases with comparatively large and reduced potential for further star formation, respectively.

Probing the non-thermal physics of stellar bow shocks using radio observations

Context. Massive runaway stars produce bow shocks in the interstellar medium. Recent observations revealed radio emission from a few of these objects, but the origin of this radiation remains poorly understood. Aims. We aim to interpret this radio emission and assess under which conditions it could be either thermal (free–free) or non-thermal (synchrotron), and how to use the observational data to infer physical properties of the bow shocks. Methods. We used an extended non-thermal emission model for stellar bow shocks for which we incorporated a consistent calculation of the thermal emission from the forward shock. We fitted this model to the available radio data (spectral and intensity maps), including largely unexplored data at low frequencies. In addition, we used a simplified one-zone model to estimate the gamma-ray emission from particles escaping the bow shocks. Results. We can only explain the radio data from the best sampled systems (BD+43°3654 and BD+60°2522) assuming a hard electron energy distribution below ∼1 GeV, a high efficiency of conversion of (shocked) wind kinetic power into relativistic electrons (∼1 − 5%), and a relatively high magnetic-to-thermal pressure ratio of ηB ∼ 0.2. In the other systems, the interpretation of the observed flux density is more ambiguous, although a non-thermal scenario is also favoured. We also show how complementary observations at other frequencies can allow us to place stronger constraints in the model. We also estimated the gamma-ray fluxes from the HII regions around the bow shocks of BD+43°3654 and BD+60°2522, and obtained luminosities at GeV energies of ∼1033 erg s−1 and 1032 erg s−1, respectively, under reasonable assumptions. Conclusions. Stellar bow shocks can potentially be very efficient particle accelerators. This work provides multi-wavelength predictions of their emission and demonstrates the key role of low-frequency radio observations in unveiling particle acceleration processes. The prospects of detections with next-generation observatories such as SKA and ngVLA are very promising. Finally, BD+43°3654 may be detected in GeV in the near future, while bow shocks in general may turn out to be non-negligible sources of (at least leptonic) low-energy cosmic rays.

PHYSICAL PROPERTIES AND KINEMATICS OF DENSE CORES ASSOCIATED WITH REGIONS OF MASSIVE STAR FORMATION FROM THE SOUTHERN SKY

The results of spectral observations in the \( \sim {\kern 1pt} 84{\kern 1pt} - {\kern 1pt} 92\) GHz frequency range of six objects from the southern sky having dense cores and associated with massive star and star cluster forming regions are presented. The observations are carried out with the MOPRA-22m radio telescope. Within the framework of the local thermodynamic equilibrium (LTE) approximation, column densities and abundances of the H13CN, H13CO+, HN13C, HC3N, c-C3H2, SiO, CH3C2H and CH3CN molecules are calculated. Kinetic temperatures (\( \sim 30{\kern 1pt} - {\kern 1pt} 50\) K), sizes of emission regions (\( \sim 0.2{\kern 1pt} - {\kern 1pt} 3.1\) pc) and virial mass esimates (\( \sim 70{\kern 1pt} - {\kern 1pt} 4600{\kern 1pt} {{M}_{ \odot }}\)) are obtained. The linewidths in the three cores decrease with increasing distance from the center. Four cores exhibit asymmetry in the profiles of the optically thick HCO+(1–0) and HCN(1–0) lines, indicating the presence of systematic motions in the line of sight. In two cases, the asymmetry can be caused by contraction of gas. The model HCO+(1–0) and H13CO+(1–0) spectral maps obtained within the non-LTE spherically symmetric model are fitted into observed ones. Radial density (\( \propto {\kern 1pt} {{r}^{{ - 1.6}}}\)), turbulent velocity (\( \propto {\kern 1pt} {{r}^{{ - 0.2}}}\)) and contraction velocity (\( \propto {\kern 1pt} {{r}^{{0.5}}}\)) profiles in the G268.42–0.85 core are obtained. The contraction velocity radial profile differs from expected both in the case of free fall of gas onto a protostar (\({{r}^{{ - 0.5}}}\)), and in the case of global core collapse (contraction velocity does not depend on distance). A discussion of the results obtained is provided.

VLT/MUSE Characterization of Dimorphos Ejecta from the DART Impact

We have observed the Didymos-Dimorphos binary system with the MUSE integral field unit spectrograph mounted at the Very Large Telescope before and after DART impact and captured the ensuing ejecta cone, debris cloud, and tails at subarcsecond resolutions. We targeted the Didymos system over 11 nights from 2022 September 26 to October 25 and utilized both narrow- and wide-field observations with and without adaptive optics, respectively. We took advantage of the spectral–spatial coupled measurements and produced both white-light images and spectral maps of the dust reflectance. We identified and characterized numerous dust features, such as the ejecta cone, spirals, wings, clumps, and tails. We found that the base of the sunward edge of the wings, from October 3 to 19, is consistent with maximum grain sizes on the order of 0.05–0.2 mm and that the earliest detected clumps have the highest velocities, on the order of ;10 m s−1. We also see that three clumps in narrow-field mode (8″ × 8″) exhibit redder colors and slower speeds, around 0.09 m s−1, than the surrounding ejecta, likely indicating that the clump is composed of larger, slower grains. We measured the properties of the primary tail and resolved and measured the properties of the secondary tail earlier than any other published study, with first retrieval on October 3. Both tails exhibit similarities in curvature and relative flux; however, the secondary tail appears thinner, which may be caused by lower-energy ejecta and possibly a low-energy formation mechanism such as secondary impacts.

A Bayesian deep learning framework for reliable fault diagnosis in wind turbine gearboxes under various operating conditions

Vibration-based fault diagnostics combined with deep learning approaches has promising applications in detecting and diagnosing faults in wind turbine gearboxes. Specifically when time series vibration data is transformed to a 2-dimensional cyclic spectral coherence maps, the accuracy of deep neural networks in classifying faults increases. Nevertheless, standard deep learning techniques are vulnerable to inaccurate predictions when tested with new data originating from unseen faults or unusual operating conditions. To address some of these shortcomings in the context of wind turbine gearboxes, this paper investigates fault diagnostics using Bayesian convolutional neural network which provide accurate results with uncertainty bounds reducing wrong overconfident classifications. The performance of Bayesian and standard neural networks is compared using a simulation-based dataset of acceleration signals generated from a multibody dynamic model of a 5 MW wind turbine. The framework proposed in this paper has relevance to fault detection and diagnosis in other rotating machinery applications.

Noise Reduction Method for the Vibration Signal of Reactor CRDM Based on CEEMDAACN-SK

The reactor control rod drive mechanism (CRDM) controls the startup, shutdown and power of the reactor; it is one of the key pieces of equipment to ensure the normal operation of the reactor. CRDM is complex, mainly composed of stator, rotor, bearing, roller, etc. The characteristic analysis of the vibration monitoring signal is one of the important methods of the CRDM state evaluation. In view of the characteristics of large noise interference and the difficulty in analyzing the vibration monitoring signal of CRDM, this paper proposes a noise reduction method for the vibration signal of CRDM based on complete ensemble empirical mode decomposition with adaptive amplitude correction noise and spectral kurtosis (CEEMDAACN-SK), which can deeply reduce the vibration signal of CRDM. Firstly, the proposed CEEMDAACN algorithm is used to decompose the vibration signal of CRDM to obtain multiple intrinsic mode functions (IMF). Then, the spectral kurtosis of each IMF component is analyzed to obtain the spectral kurtosis map of each IMF component, which is compared with the spectral kurtosis map of the original signal. Finally, the denoising reconstruction of the signal is carried out to obtain the final denoising signal. Through experimental analysis, the performance of the proposed CEEMDAACN-SK denoising algorithm is better than the complete ensemble empirical mode decomposition with adaptive noise and spectral kurtosis (CEEMDAN-SK) algorithm in terms of results. The method proposed in this paper can be applied not only to the vibration signal noise reduction of CRDM, but also to other equipment and fields, such as nuclear power main circulation pump and the chemical industry.

C ii] Spectral Mapping of the Galactic Wind and Starbursting Disk of M82 with SOFIA

M82 is an archetypal starburst galaxy in the local Universe. The central burst of star formation, thought to be triggered by M82's interaction with other members in the M81 group, is driving a multiphase galaxy-scale wind away from the plane of the disk that has been studied across the electromagnetic spectrum. Here, we present new velocity-resolved observations of the [C ii] 158 μm line in the central disk and the southern outflow of M82 using the upGREAT instrument on board SOFIA. We also report the first detections of velocity-resolved (ΔV = 10 km s−1) [C ii] emission in the outflow of M82 at projected distances of ≈1–2 kpc south of the galaxy center. We compare the [C ii] line profiles to observations of CO and H i and find that likely the majority (>55%) of the [C ii] emission in the outflow is associated with the neutral atomic medium. We find that the fraction of [C ii] actually outflowing from M82 is small compared to the bulk gas outside the midplane (which may be in a halo or tidal streamers), which has important implications for observations of [C ii] outflows at higher redshift. Finally, by comparing the observed ratio of the [C ii] and CO intensities to models of photodissociation regions, we estimate that the far-ultraviolet (FUV) radiation field in the disk is ∼103.5 G 0, in agreement with previous estimates. In the outflow, however, the FUV radiation field is 2–3 orders of magnitudes lower, which may explain the high fraction of [C ii] arising from the neutral medium in the wind.

Exploration of ecological environment construction and development paths in towns and cities by applying time series data

Abstract This paper explores the interaction mechanism between urbanization and the ecological environment based on the unique correlation between urbanization and the ecological environment. BISE and Savizky-Golay algorithms are combined to establish the time series data, and for the characteristic curves of the EVI time response of the land cover, the spectral angle mapping method is combined with the minimum distance method to form the spectral angle-minimum distance classification method. The application of time series data involves calculating the time and spatial change of urban land cover and analyzing the evolution of urban ecological environment elements. Based on the temporal and spatial consistency test and land cover analysis of urban ecological environment construction, as well as the development of urbanization construction, relevant development paths are proposed. The comprehensive score of new urbanization in the four districts and one city of Hengyang City is concentrated towards 1.6, indicating that the level of economic development and the construction of new urbanization have reached coupling at different levels, respectively.

Mixing nanoparticles in a ProCell type spouted bed

Mixing nanoparticles is critical in various industries, including pharmaceuticals, solar, and nanotechnology. When different nanopowders are mixed, hetero-aggregates consisting of hetero-contacts are formed, facilitating the exchange of charge, mass and moments between particles of different materials. This research paper presents a novel approach for mixing nanoparticles using special spouted bed equipment to produce hetero-aggregates. The paper explores the potential of special spouted bed equipment for mixing nanoparticles. High-velocity opposed inlet air streams in this equipment result in high gas-solid contact efficiency and enhanced particle circulation, which contribute to the breakage of aggregates and promote the mixing process. The study investigates the aggregate breakage and mixing quality in produced hetero-aggregates. Experimental results demonstrate that the special spouted bed equipment enables efficient mixing of nanoparticles, leading to higher dispersion in hetero-aggregates with many hetero-contacts. The modified homogeneity of mixing method is utilized to quantify the mixing inside the single hetero-aggregates. Visual confirmation of the assessed values of mixing quality is provided by EDX spectral mapping.

Microstructural Evaluation of the Mineralized Apical Barrier Induced by a Calcium Hydroxide Paste Containing Iodoform: A Case Report

IntroductionA 65-year-old man had nonsurgical retreatment using an iodoform and calcium hydroxide paste in a maxillary left canine with persistent apical periodontitis. An apical mineralized barrier (AMB) was observed 3-months postoperatively. Unfortunately, the tooth was extracted due to a cementum tear. This provided an opportunity to analyze the AMB histologically, as there is a lack of previous reports on its microstructure. MethodsAfter extraction and removal of the granulation tissue from the root surface, the canine was processed, and observed using micro–computed tomography (μCT) and light microscopy. Thereafter, the specimen was resin-embedded specimen was evaluated by scanning electron microscopy, micro–X-ray fluorescence spectroscopy and Raman spectroscopy to understand the mechanism and nature of the AMB formation during apical healing. ResultsNonsurgical retreatment was clinically successful based on the absence of clinical symptoms of apical periodontitis and the radiographic presence of an AMB. The AMB was opaque and could be readily differentiated from dentin under a light microscope. Micro–computed tomography analysis revealed that the AMB had the same mineral density as dentin. Scanning electron microscopy revealed that the AMB had two distinct layers based on the size of the calcified particles. Elemental mapping using micro–X-ray fluorescence spectroscopy showed that the localization of calcium and phosphorus differed between AMB and other areas of biomineralization. Raman spectral mapping revealed that the surface layer of the AMB consisted of collagen, calcium carbonate, and hydroxyapatite. ConclusionsThis study explored new analytical methods for elucidating the apical wound-healing process and the nature of the mineralized repair. The findings provided detailed information on the AMB highlighting a bilaminar structure with high calcium components higher on the inside and a brightness similar to cementum not dentin and the presence of hydroxyapatite.

Lightweight Transformer with Transposed-attention for Hyperspectral Unmixing

Hyperspectral unmixing primarily involves accurately estimating the end members and abundances from mixed pixels in hyperspectral images. In our task, we design a transposed-attention mechanism in the lightweight Transformer to capture the effective information between channels to provide better performance and faster computing speed. We compare the proposed model with those of the CyCU, FCLS, and DHTN methods. The quantitative and qualitative results indicate that our method outperforms the quality of endmember spectral and abundance maps and has a competitive advantage in calculation speed.

New Insights on 30 Dor B Revealed by High-quality Multiwavelength Observations

The supernova remnant (SNR) 30 Dor B is associated with the H ii region ionized by the OB association LH99. The complex interstellar environment has made it difficult to study the physical structure of this SNR. We have used Hubble Space Telescope Hα images to identify SNR shocks and deep Chandra X-ray observations to detect faint diffuse emission. We find that 30 Dor B hosts three zones with very different X-ray surface brightnesses and nebular kinematics that are characteristic of SNRs in different interstellar environments and/or evolutionary stages. The ASKAP 888 MHz map of 30 Dor B shows counterparts to all X-ray emission features except the faint halo. The ASKAP 888 and 1420 MHz observations are used to produce a spectral index map, but its interpretation is complicated by the background thermal emission and the pulsar PSR J0537−6910's flat spectral index. The stellar population in the vicinity of 30 Dor B indicates a continuous star formation in the past 8–10 Myr. The observed very massive stars in LH99 cannot be coeval with the progenitor of 30 Dor B’s pulsar. Adopting the pulsar’s spin-down timescale, 5000 yr, as the age of the SNR, the X-ray shell would be expanding at ∼4000 km s−1 and the post-shock temperature would be 1–2 orders of magnitude higher than that indicated by the X-ray spectra. Thus, the bright central region of 30 Dor B and the X-ray shell requires two separate SN events, and the faint diffuse X-ray halo perhaps other older SN events.

Electron-to-nuclear spectral mapping via dynamic nuclear polarization.

We report on a strategy to indirectly read out the spectrum of an electronic spin via polarization transfer to nuclear spins in its local environment. The nuclear spins are far more abundant and have longer lifetimes, allowing for repeated polarization accumulation in them. Subsequent nuclear interrogation can reveal information about the electronic spectral density of states. We experimentally demonstrate the method by reading out the ESR spectrum of nitrogen vacancy center electrons in diamond via readout of lattice 13C nuclei. Spin-lock control on the 13C nuclei yields a significantly enhanced signal-to-noise ratio for the nuclear readout. Spectrally mapped readout presents operational advantages in being background-free and immune to crystal orientation and optical scattering. We harness these advantages to demonstrate applications in underwater magnetometry. The physical basis for the "one-to-many" spectral map is itself intriguing. To uncover its origin, we develop a theoretical model that maps the system dynamics, involving traversal of a cascaded structure of Landau-Zener anti-crossings, to the operation of a tilted "Galton board." This work points to new opportunities for "ESR-via-NMR" in dilute electronic systems and in hybrid electron-nuclear quantum memories and sensors.