Shortwave infrared hyperspectral imaging as a novel method to elucidate multi-phase dolomitization, recrystallization, and cementation in carbonate sedimentary rocks

Carbonate rocks undergo low-temperature, post-depositional changes, including mineral precipitation, dissolution, or recrystallisation (diagenesis). Unravelling the sequence of these events is time-consuming, expensive, and relies on destructive analytical techniques, yet such characterization is essential to understand their post-depositional history for mineral and energy exploitation and carbon storage. Conversely, hyperspectral imaging offers a rapid, non-destructive method to determine mineralogy, while also providing compositional and textural information. It is commonly employed to differentiate lithology, but it has never been used to discern complex diagenetic phases in a largely monomineralic succession. Using spatial-spectral endmember extraction, we explore the efficacy and limitations of hyperspectral imaging to elucidate multi-phase dolomitization and cementation in the Cathedral Formation (Western Canadian Sedimentary Basin). Spectral endmembers include limestone, two replacement dolomite phases, and three saddle dolomite phases. Endmember distributions were mapped using Spectral Angle Mapper, then sampled and analyzed to investigate the controls on their spectral signatures. The absorption-band position of each phase reveals changes in %Ca (molar Ca/(Ca + Mg)) and trace element substitution, whereas the spectral contrast correlates with texture. The ensuing mineral distribution maps provide meter-scale spatial information on the diagenetic history of the succession that can be used independently and to design a rigorous sampling protocol.

Alveolar Backing in 3-Year-Old Children With and Without Repaired Cleft Palate: Preliminary Findings Related to Cleft Type and History of Otitis Media

Objective The purpose of this preliminary study was to determine if cleft type and/or history of otitis media with effusion (OM) contribute to backing of /t/ and/or /s/ in young children with and without repaired cleft palate (CP). Method Participants were 39 children ( M age = 36 months, range: 34–41). Ten children had repaired unilateral cleft lip and palate (CLP), nine had repaired CP only, 12 had no clefts but histories of OM, and eight were typically developing (TD) without clefts or OM history. All children were video- and audio-recorded during administration of the Goldman-Fristoe Test of Articulation–Third Edition (GFTA-3). Standard scores of articulation, frequency of alveolar backing, and first spectral moments of the /t/−/k/ and /s/−/ʃ/ phonetic contrasts were obtained. Results Children with CLP had lower GFTA-3 scores than both TD ( p = .012) and OM ( p = .001) groups. Fisher's exact test showed that significantly more children with CLP backed alveolar targets, mostly /s/, than children with CP ( p = .020). Children with CLP also had (a) reduced /t/−/k/ spectral difference compared to TD children ( p = .016) and (b) reduced /s/−/ʃ/ spectral difference compared to both children with CP ( p = .010) and children with OM ( p = .018). Children with OM had reduced /t/−/k/ spectral difference compared to TD children ( p = .009). Conclusions Cleft type contributes to alveolar backing and reduced spectral contrast of /s/−/ʃ/ in 3-year-old children with repaired CP. History of OM affects spectral contrast of /t/−/k/ in noncleft children. Etiology and clinical implications of alveolar backing are discussed.

An Analysis of the Impact of Spectral Contrast Feature in Speech Emotion Recognition

Feature extraction is an integral part in speech emotion recognition. Some emotions become indistinguishable from others due to high resemblance in their features, which results in low prediction accuracy. This paper analyses the impact of spectral contrast feature in increasing the accuracy for such emotions. The RAVDESS dataset has been chosen for this study. The SAVEE dataset, CREMA-D dataset and JL corpus dataset were also used to test its performance over different English accents. In addition to that, EmoDB dataset has been used to study its performance in the German language. The use of spectral contrast feature has increased the prediction accuracy in speech emotion recognition systems to a good degree as it performs well in distinguishing emotions with significant differences in arousal levels, and it has been discussed in detail.<div> </div>

Spectral Contrasts of Short Wind Waves in Artificial Slicks from the Sea Surface Photographs

Purpose. The aim of the work is to evaluate the contrasts between the two-dimensional spectra of the short wind waves on a clean sea surface and on the surface covered by a thin film of vegetable oil. The contrast angular dependence, which is still not understood, is of particular interest. The study is intended to widen the base of empirical notions of wave suppression on the surfactant films in field conditions. Its results may be useful both for theoretical modeling the short wind wave spectra, and for developing the methods for remote monitoring of the ocean. Methods and Results. The contrasts were assessed by analyzing the sea surface photographs taken from the Platform of the Black Sea hydrophisical subsatellite polygon (Katsiveli) during the specialized experiments aimed at obtaining artificial slicks using vegetable oil spills. The applied in the study simple method for estimating the contrasts is based on the assumptions of a linear relationship between the brightness and the sea surface slope, and of the invariability of the brightness – slope transfer function at transition from a clean sea surface to a slick. In contrast to the previously applied methods, this approach makes it possible to obtain the contrasts varying both in wavenumber and direction. Obtaining the estimates of the shortest wave characteristics usually constitutes the utmost technical difficulty. In the work, the spectral contrasts are evaluated for the wind waves whose lengths are from ~ 20 to ~ 1 cm. Conclusions. At moderate wind speeds (6–8 m/s), the obtained contrasts increase monotonically with the wavenumber up to the values ~ 10. Under calm conditions (wind speed 0.5 m/s), the spectral contrast maximum (~ 30–50) is observed at the wavenumber peak ~ 100 rad/m that is qualitatively confirmed by the estimates from a string wave gauge. These results are consistent with the previous measurements performed by the other authors. The two-dimensional contrast distributions are anisotropic with the maximum in the direction perpendicular to the wind one. At moderate winds, the anisotropy increases with growth of a wavenumber.

Spectral Contrasts of Short Wind Waves in Artificial Slicks from the Sea Surface Photographs

Purpose. The aim of the work is to evaluate the contrasts between the two-dimensional spectra of the short wind waves on a clean sea surface and on the surface covered by a thin film of vegetable oil. The contrast angular dependence, which is still not understood, is of particular interest. The study is intended to widen the base of empirical notions of wave suppression on the surfactant films in field conditions. Its results may be useful both for theoretical modeling the short wind wave spectra, and for developing the methods for remote monitoring of the ocean. Method and Results. The contrasts were assessed by analyzing the sea surface photographs taken from the Platform of the Black Sea hydrophisical subsatellite polygon (Katsiveli) during the specialized experiments aimed at obtaining artificial slicks using vegetable oil spills. The applied in the study simple method for estimating the contrasts is based on the assumptions of a linear relationship between the brightness and the sea surface slope, and of the invariability of the brightness – slope transfer function at transition from a clean sea surface to a slick. In contrast to the previously applied methods, this approach makes it possible to obtain the contrasts varying both in wavenumber and direction. Obtaining the estimates of the shortest wave characteristics usually constitutes the utmost technical difficulty. In the work, the spectral contrasts are evaluated for the wind waves whose lengths are from ~ 20 to ~ 1 cm. Conclusions. At moderate wind speeds (6–8 m/s), the obtained contrasts increase monotonically with the wavenumber up to the values ~ 10. Under calm conditions (wind speed 0.5 m/s), the spectral contrast maximum (~ 30–50) is observed at the wavenumber peak ~ 100 rad/m that is qualitatively confirmed by the estimates from a string wave gauge. These results are consistent with the previous measurements performed by the other authors. The two-dimensional contrast distributions are anisotropic with the maximum in the direction perpendicular to the wind one. At moderate winds, the anisotropy increases with growth of a wavenumber.

An Efficacy of Spectral Features with Boosted Decision Tree Algorithm for Automatic Heart Sound Classification

This research work aims to classify the audio signals received from heart into normal/abnormal. The heart sound perceived has been referred as phonocardiogram (PCG) signals. An attempt has been made to identify a set of features that provide more accurate results for classifying PCG under designated categories using a variant of decision tree algorithm. After applying 6th order butter worth band-pass filter on PCG signals, the new features, viz. Tonnetz, Spectral contrast, and Chroma have been extracted. Further, XGBOOST, a variant of the decision tree has been used for classifying unsegmented PCG signals. The benchmark datasets, PhysioNet 2016, and PASCAL 2011 have been taken for validating the proposed methodology presented here. PhysioNet 2016 is comprised of sub-datasets, viz. A–F which contain a total of 3,240 PCG recordings, whereas the PASCAL 2011 contains 415 heart sound signals. The proposed approach considers a new feature set in conjunction with the existing ones; and it has resulted in mean accuracy, sensitivity, and specificity scores as 95.2, 94.22 and 96.18 respectively.

Detection of Fire Smoke Plumes Based on Aerosol Scattering Using VIIRS Data over Global Fire-Prone Regions

Smoke from fires significantly influences climate, weather, and human health. Fire smoke is traditionally detected using an aerosol index calculated from spectral contrast changes. However, such methods usually miss thin smoke plumes. It also remains challenging to accurately separate smoke plumes from dust, clouds, and bright surfaces. To improve smoke plume detections, this paper presents a new scattering-based smoke detection algorithm (SSDA) depending mainly on visible and infrared imaging radiometer suite (VIIRS) blue and green bands. The SSDA is established based on the theory of Mie scattering that occurs when the diameter of an atmospheric particulate is similar to the wavelength of the scattered light. Thus, smoke commonly causes Mie scattering in VIIRS blue and green bands because of the close correspondence between smoke particulate diameters and the blue/green band wavelengths. For developing the SSDA, training samples were selected from global fire-prone regions in North America, South America, Africa, Indonesia, Siberia, and Australia. The SSDA performance was evaluated against the VIIRS aerosol detection product and smoke detections from the ultraviolet aerosol index using manually labeled fire smoke plumes as a benchmark. Results show that the SSDA smoke detections are superior to existing products due chiefly to the improved ability of the algorithm to detect thin smoke and separate fire smoke from other surface types. Moreover, the SSDA smoke distribution pattern exhibits a high spatial correlation with the global fire density map, suggesting that SSDA is capable of detecting smoke plumes of fires in near real-time across the globe.