Variation Of Spectral Features Research Articles

Laboratory Emissivity Spectra of Sulphide-Bearing Samples, New Constraints for the Surface of Mercury: Oldhamite in Mafic Aggregates

Exploration of Mercury will continue in the near future with ESA/JAXA’s BepiColombo mission, which will increase the number and the type of datasets, and it will take advantage of the results from NASA’s MESSENGER (MErcury Surface, Space ENviroment, GEochemistry and Ranging) mission. One of the main discoveries from MESSENGER was the finding of a relatively high abundance of volatiles, and in particular of sulphur, on the surface. This discovery correlates well with the morphological evidence of pyroclastic activity and with features attributable to degassing processes like the hollows. BepiColombo will return compositional results from different spectral ranges and instruments, and, in particular, among them the first results from the orbit of emissivity in the thermal infrared. Here, we investigate the results from the emissivity spectra of different samples between a binary mixture of a volcanic regolith-like for Mercury and oldhamite (CaS). The acquisitions are taken at different temperatures in order to highlight potential shifts due to both mineral variation and temperature dependence on these materials that potentially could be present in hollows. Different absorption features are present for the two endmembers, making it possible to distinguish the oldhamite with respect to the regolith bulk analogue. We show how, in the mixtures, the Christiansen feature is strongly driven by the oldhamite, whereas the Reststrahlen minima are mainly dominated by mafic composition. The spectral contrast is strongly reduced in the mixtures with respect to the endmembers. The variations of spectral features are strong enough to be measured via MERTIS, and the spectral variations are stronger in relation to the mineralogy with respect to temperature dependence.

Unraveling Molecular Composition in Biological Samples-Systematic Evaluation of Statistical Methods for the Analysis of Hyperspectral Raman Data.

Recently, confocal Raman microscopy has gained popularity in biomedical research for studying tissues in healthy and diseased state due to its ability to acquire chemically selective data in a noninvasive approach. However, biological samples, such as brain tissue, are inherently difficult to analyze due to the superposition of molecules in the Raman spectra and low variation of spectral features within the sample. The analysis is further impeded by pathological hallmarks, for example beta-amyloid (Aβ) plaques in Alzheimer's disease, which are often solely characterized by subtle shifts in the respective Raman peaks. To unravel the underlying molecular information, convoluted statistical procedures are inevitable. Unfortunately, such statistical methods are often inadequately described, and most natural scientists lack knowledge of their appropriate use, causing unreproducible results and stagnation in the application of hyperspectral Raman imaging. Therefore, we have set out to provide a comprehensive guide to address these challenges with the example of a complex hyperspectral data set of brain tissue samples with Aβ plaques. Our study encompasses established as well as novel statistical methods, including univariate analysis, principal component analysis, cluster analysis, spectral unmixing, and 2D correlation spectroscopy, and critically compares the outcomes of each analysis. Moreover, we transparently demonstrate the effect of preprocessing decisions like denoising and scaling techniques, providing valuable insights into implications of spectral quality for data evaluation. Thereby, this study provides a comprehensive evaluation of analysis approaches for complex hyperspectral Raman data, laying out a blueprint for elucidating meaningful information from biological samples in chemical imaging.

Heart Rate Detection and Classification from Speech Spectral Features Using Machine Learning

Measurement of vital signs of the human body such as heart rate, blood pressure, body temperature and respiratory rate is an important part of diagnosing medical conditions and these are usually measured using medical equipment. In this paper, we propose to estimate an important vital sign – heart rate from speech signals using machine learning algorithms. Existing literature, observation and experience suggest the existence of a correlation between speech characteristics and physiological, psychological as well as emotional conditions. In this work, we estimate the heart rate of individuals by applying machine learning based regression algorithms to Mel frequency cepstrum coefficients, which represent speech features in the spectral domain as well as the temporal variation of spectral features. The estimated heart rate is compared with actual measurement made using a conventional medical device at the time of recording speech. We obtain estimation accuracy close to 94% between the estimated and actual measured heart rate values. Binary classification of heart rate as ‘normal’ or ‘abnormal’ is also achieved with 100% accuracy. A comparison of machine learning algorithms in terms of heart rate estimation and classification accuracy is also presented. Heart rate measurement using speech has applications in remote monitoring of patients, professional athletes and can facilitate telemedicine.

Revealing the Hidden Diagnostic Clues of Male Infertility from Human Seminal Plasma by Dispersive Solid Phase Extraction and MALDI-TOF MS.

Seminal plasma (SP) mirrors the local pathophysiology of the male reproductive system and represents a non-invasive fluid for the study of infertility. Matrix-Assisted Laser Desorption/Ionization-Time-of-Flight Mass Spectrometry (MALDI-TOF-MS) provides a high-throughput platform to rapidly extrapolate the diagnostic profiles of information-rich patterns. In this study, dispersive solid phase extraction (d-SPE) combined with MALDI-TOF-MS was applied for the first time to the human SP, with the aim of revealing a diagnostic signature for male infertility. Commercially available octadecyl (C18)-, octyl (C8)-bonded silica sorbents and hexagonal mesoporous silica (HMS) were tested and the robustness of MALDI-TOF peptide profiling was evaluated. Best performances were obtained for C18-bonded silica with the highest detection of peaks and the lowest variation of spectral features. To assess the diagnostic potential of the method, C18-bonded silica d-SPE and MALDI-TOF-MS were used to generate enriched endogenous peptide profiles of SP from 15 fertile and 15 non-fertile donors. Principal component analysis (PCA) successfully separated fertile from non-fertile men into two different clusters. An array of seven semenogelin-derived peptides was found to distinguish the two groups, with high statistical significance. These findings, while providing a rapid and convenient route to selectively enrich native components of SP peptidome, strongly reinforce the prominent role of semenogelins in male infertility.

Correlation between surface roughness and spectral features in IR-reflection spectroscopy

Modifications of IR spectral features were reported in the literature when surfaces with diverse morphologies were analysed. In this study, five surfaces at different average roughness (Sa) were created on a massive slice of malachite with the final aim to investigate possible variations of spectral features collected through non-contact infrared reflection spectroscopy. Modifications were investigated as a function of Sa, with five frequency intervals being considered. The spectral acquisition was carried out by two portable spectrometers equipped with specific non-invasive optical heads, operating in External Reflection (ER) and Diffuse Reflection (DR) modes, respectively. A comparison study of the collected spectral profiles is proposed in this work. The analysis of spectra produced by surfaces at different roughness allowed for evaluating the effectiveness of each device in the different spectral ranges. The ER spectra were generally more resolved and cleaner compared to the DR ones. The ER module was able to return spectra whose features - both specular and diffuse - consistently follow the variation of Sa in the investigated spectral ranges. A lack of sensitivity was instead registered when working in DR mode, especially in the frequency intervals where the contribution of the diffuse component dominates the spectra.

Geographic variation of fruit color dimorphism in Viscum coloratum (Kom.) Nakai in Northeast China

Mistletoe, V. coloratum, produces mature fruits of two different colors. To characterize the fruit color dimorphism and its geographic variation, we surveyed 23 populations spanning 10 latitudes in Northeast China and recorded 41 species of host plant, 2896 individual hosts, and 6641 individual fruiting mistletoes. The proportions of different color-morphs were counted in each population. In addition, we examined the variation in spectral features of the two color-morphs within and between populations, finding more red-morphs at high latitudes and more yellow-morphs at low latitudes, instead of the expected 1:1 ratio. A strong correlation was detected between the proportions of color-morphs and latitude of the population. The spectral values of the red-morph fruits were significantly correlated with the latitude of the population, while the yellow-morph showed no such correlation. We propose two unexclusive hypotheses—the food-finding strategies hypothesis and the ecological fitting hypothesis—to explain the maintenance of fruit color dimorphism and geographic variation of patterns in this species.

Raman 18 O-labeling of bacteria in visible and deep UV-ranges.

Raman stable isotope labeling with 2 H, 13 C or 15 N has been reported as an elegant approach to investigate cellular metabolic activity, which is of great importance to reveal the functions of microorganisms in native environments. A new strategy termed Raman 18 O-labeling was developed to probe the metabolic activity of bacteria. Raman 18 O-labeling refers to the combination of Raman microspectroscopy with 18 O-labeling using H218 O. At an excitation wavelength of 532 nm, the incorporation of 18 O into the amide I group of proteins and DNA/RNA bases was observed in Escherichia coli cells, while for an excitation wavelength electronically resonant with DNA or aromatic amino acid absorption at 244 nm 18 O assimilation was detected using chemometric tools rather than visual inspection. Raman 18 O-labeling at 532 nm combined with 2D correlation analysis confirmed the assimilation of 18 O in proteins and nucleic acids and revealed the growth strategy of E. coli cells; they underwent protein synthesis followed by nucleic acid synthesis. Independent cultural replicates at different incubation times corroborated the reproducibility of these results. The variations in spectral features of 18 O-labeled cells revealed changes in physiological information of cells. Hence, Raman 18 O-labeling could provide a powerful tool to identify metabolically active bacterial cells.

Calibration data for simultaneous determination of P-V-X properties of binary and ternary CO2 - CH4 - N2 gas mixtures by Raman spectroscopy over 5–600 bar: Application to natural fluid inclusions

The P-V-X properties of two-component fluid inclusions (FIs) are generally determined from microthermometry data using appropriate thermodynamic models (i.e., VX diagrams) and/or equations of state (EoS). However, some limitations can hamper the applicability of this technique such as the small size, low density or complex composition of the analyzed FI. Raman spectroscopy is known as the best-suited alternative method to microthermometry for the investigation of natural FIs because it can provide simultaneously non-destructive qualitative and possible quantitative analyses after specific calibrations. The present work aims to provide calibration data to directly determine the P-V-X properties of binary or ternary mixtures of CH4, CO2, and N2. The variation of spectral features as a function of composition and pressure (or density) was investigated by using Raman spectroscopy coupled with an improved High-Pressure Optical Cell (HPOC) system and a customized heating-cooling stage. From our experimental data, the relative Raman scattering cross-section (RRSCS) of CH4 (νCH4∗) was demonstrated to be constant at 7.73 ± 0.16 over the investigated range of pressure (5–600 bars) and for any composition. This parameter can thus be used for the determination of composition with an uncertainty of ~0.5 mol%. Several calibration equations were calculated for different PX domains, linking the Fermi diad splitting of CO2 (Δ) or the relative variation of the CH4 peak position (νCH4∗) to the pressure (or density) and composition of CO2-CH4, CH4-N2, and CO2-N2-CH4 mixtures at 22 and 32 °C. The pressure and density of the fluids can henceforth be directly measured from Raman spectra with an uncertainty of ~20 bars and ~0.01 g·cm−3, respectively. Our calibration equations were then validated on natural FIs by comparing the results obtained from Raman and microthermometry. We also interpreted the variation of the peak position of CH4 based on the change of intermolecular interaction. Finally, we discussed the applicability of the obtained calibration data into another laboratory by comparing it with the data of pure CO2 and CH4 published in literature. A small shift between calibration curves implies a systematic error which is perhaps due to the difference in the configuration or the day-to-day deviation of the instruments. Therefore, standards of well-known P-V-X properties should be regularly measured to prevent and to correct any variation or shifting of the instrumental responses.

Soft X-ray Absorption Spectroscopic Investigation of Li(Ni0.8Co0.1Mn0.1)O2 Cathode Materials.

Herein, we report the soft X-ray absorption spectroscopic investigation for Li(Ni0.8Co0.1Mn0.1)O2 cathode material during charging and discharging. These measurements were carried out at the Mn L-, Co L-, and Ni L-edges during various stages of charging and discharging. Both the Mn and Co L-edge spectroscopic measurements reflect the invariance in the oxidation states of Mn and Co ions. The Ni L-edge measurements show the modification of the oxidation state of Ni ions during the charging and discharging process. These studies show that eg states are affected dominantly in the case of Ni ions during the charging and discharging process. The O K-edge measurements reflect modulation of metal–oxygen hybridization as envisaged from the area-ratio variation of spectral features corresponding to t2g and eg states.

Molecular orientation and specificity in the identification of biomolecules via surface enhanced Raman spectroscopy

The orientation dependence of the Raman spectral features of individual protein/biomolecules is studied using surface-enhanced Raman spectroscopy (SERS). Large variation in spectral features mainly in term of peak intensity is observed from small proteins/peptides. We aim to address the question of whether the spectral features of SERS are uniquely determined by the type of protein/molecules or are influenced prominently by factors more than the identity of the molecules such as orientation of molecules relative to the substrate surface. The standard deviation in the intensity of individual Raman peaks diminishes for protein size larger than 13 amino acids. Secondary structure of protein (such as protein-protein interaction) remains unchanged regardless of protein orientation. Numerical simulation studies corroborate the experimental observation in that the SERS spectral features of biomedically relevant protein (of larger than 13 amino acids in size, which represent all human protein types) are not affected by the orientation of amino acids randomly dispersed on SERS-active surfaces. These findings are instrumental to understanding the exceedingly high (label-free) specificity when SERS is used in identifying proteins/peptides as can be found in numerous publications from different research groups in both in vivo and in vitro analyses. It was noted that the spectral position of all Raman peaks assignable to the various amino acids are independent of molecule orientation even though their intensities do vary.

Spectral Analysis of Gravity Waves from Near Space High-Resolution Balloon Data in Northwest China

Using a set of near space high-resolution balloon data released in Hami, Xinjiang, we explored the spectral characteristics of temperature fluctuations and three-dimensional wind field fluctuations. As different from previous studies, which were based on radiosondes, we have increased the height range of spectral analysis to the stratosphere (38 km), which can explore the variation of spectral features with altitude, and can analyze higher wavenumber regions. The results show that horizontal wind field disturbances are isotropic, meridional and zonal winds have relatively consistent spectral structures, while vertical wind fluctuations have completely different spectral structures, which cannot be explained by the existing “universal spectrum” theory. The observed spectrum of horizontal wind field can be explained well by the “wind-shifting” theory. The ratio of spectral kinetic energy to potential energy is approximately constant only in the high wavenumber region but it varies at different height intervals. This study is a necessary extension of the observation for the characteristics of the vertical wavenumber spectrum in northwestern China, and it is also an experimental observation of spectral characteristics using radiosonde data at higher altitudes.

Spatial Residual Blocks Combined Parallel Network for Hyperspectral Image Classification

In hyperspectral image (HSI) classification, there are challenges of the spatial variation in spectral features and the lack of labeled samples. In this paper, a novel spatial residual blocks combined parallel network (SRPNet) is proposed for HSI classification. Firstly, the spatial residual blocks extract spatial features from rich spatial contexts information, which can be used to deal with the spatial variation of spectral signatures. Especially, the skip connection in spatial residual blocks is conducive to the backpropagation of gradients and mitigates the declining-accuracy phenomenon in the deep network. Secondly, the parallel structure is employed to extract spectral features. Spectral feature learning on parallel branches contains fewer independent connection weighs through parameter sharing. Thus, fewer parameters of the network require a lesser number of training samples. Furthermore, the feature fusion is conducted on the multi-scale features from different layers in the spectral feature learning part. Extensive experiments of three representative HSI data sets illustrate the effectiveness of the proposed network.

MIR, VNIR, NIR, and Raman spectra of magnesium chlorides with six hydration degrees: Implication for Mars and Europa

AbstractChloride salts have been identified on the surface of Mars and Europa based on the results from the two soil samples analyzed by Phoenix's wet chemistry laboratory for Mars, as well as some interpretations of the data from the remote sensing for Mars and Europa. To help elucidate our understanding of Mars' and Europa's surface mineral composition and relevant environmental conditions, we studied a series of magnesium chlorides with all six hydration degrees that were synthesized using various laboratory conditions. The identifications of synthesized magnesium chloride hydrates were confirmed using X‐ray diffraction. We took a systematic study of the Raman, mid‐infrared (MIR), visible near‐infrared (VNIR), and near‐infrared (NIR) spectroscopies. We found various spectral features that can be linked to the structural characters of H2O molecules in the six crystal structures. On the basis of those knowledge, we found several trends of spectral feature variations that follow the increase of hydration degree of these magnesium chlorides, which can be used to distinguish them during the planetary exploration missions using the Raman, MIR, NIR, and VNIR spectroscopic techniques. Our data will not only fill the gap in the libraries of planetary spectroscopy but also contribute to the interpretation of Mars' and Europa's current and future exploration data. Specifically, identifying the types of Cl salts (hydrous or anhydrous) within geological context at the surface of Mars and Europa will constrain the current and past processes that they experienced, which can help in understanding the evolutions of these planetary bodies.

Time-dependent spectral-feature variations of stars displaying the B[e] phenomenon

We present an alternative model of V2028 Cyg, a B[e] star of FS CMa type. The star V2028 Cyg is atypical among FS CMa stars due to its composite spectra of B4III and K2II-Ib type. Our modelling of the temporal variability of the Hα line bisectors indicates as the most probable model a geometrically and optically thick disc, which is surrounded by a dusty ring seen almost edge-on. This provides a possibility that the K-spectral component is formed in the disc.

Potential of hyperspectral metrics and classifiers for mapping Brazilian savannas in the rainy and dry seasons

Land cover mapping of savannas in Brazil, a world's hotspot of biodiversity, is still challenging due to the tree cover gradient and the spectral similarity between some vegetation physiognomies. Here, we evaluated the potential of four classifiers (Decision Tree (DT), Random Forest (RF), Spectral Angle Mapper (SAM) and Support Vector Machine (SVM)) for discriminating eight savanna physiognomies in the rainy and dry seasons of the Brasília National Park (BNP). Five sets of Hyperion/Earth Observing One (EO-1) metrics (reflectance, first-order derivative of reflectance; narrow-band vegetation indices (VIs); absorption band parameters; and the combination of these attributes) were tested as input data for each classifier. Before classification, the Correlation-based Feature Selection (CFS) algorithm was applied to reduce data dimensionality. To evaluate the agreement between the classifications of the different techniques, we calculated the Shannon entropy. Finally, Monte Carlo simulation was applied to determine the presence of statistical differences in classifiers and metrics between seasons. The results showed that the greater spectral confusion between the savannas generally observed in the rainy season was compensated by the selection of a greater number of hyperspectral metrics for classification. SVM and RF had the highest overall classification accuracy (OA) and Kappa values in the rainy and dry seasons for each set of metrics. The reflectance and VIs presented better discrimination capability than the absorption band parameters and first-order derivative data. When all metrics were considered in the analysis, gains of 6% and 8% in OA were obtained over the first ranked classifiers and metrics (SVM with reflectance in the rainy season; RF with VIs in the dry season). The lowest Shannon entropy values in the rainy and dry seasons were observed for VIs and reflectance and for physiognomies with larger vegetation cover, while the largest uncertainties were noted in savanna grassland/shrub areas. From the Monte Carlo simulations, differences in Kappa between seasons were not statistically significant for most of the metrics and classifiers at the 99% confidence level. Variations in brightness and VIs, associated with canopy structure, biochemistry and physiology, were therefore more important for classification than variations in spectral features, spectra shape and absorption bands.

Time-dependent spectral-feature variations of stars displaying the B[e] phenomenon

Context. B[e] stars are anomalous objects around which extended circumstellar matter is present. The observed properties of the central star are significantly affected by the surrounding material. Therefore, the use of standard synthetic spectra is disputable in this case and our capability to study these objects is limited. One of the possibilities is to analyse variations of the spectral features. Long-term spectroscopic observations are required for this, but are not found in the literature. For our study we choose the B[e] star HD 50138 of the FS CMa type because of the indication that this star is a post-main-sequence star, although still not highly evolved. Therefore, it can be a good object for testing evolutionary models. Currently, HD 50138 is the most extensively observed FS CMa star which makes it an ideal object for modelling. Our observations fill the gap in the available data.

Near-Infrared K Corrections of Type Ia Supernovae and their Errors

In this paper we use near-infrared (NIR) spectral observations of Type Ia supernovae (SNe Ia) to study the uncertainties inherent in NIR K corrections. To do so, 75 previously published NIR spectra of 33 SNe Ia are employed to determine K-correction uncertainties in the YJHKs passbands as a function of temporal phase and redshift. The resultant K corrections are then fed into an interpolation algorithm that provides mean K corrections as a function of temporal phase and robust estimates of the associated errors. These uncertainties are both statistical and intrinsic—i.e., due to the diversity of spectral features from object to object—and must be included in the overall error budget of cosmological parameters constrained through the use of NIR observations of SNe Ia. Intrinsic variations are likely the dominant source of error for all four passbands at maximum light. Given the present data, the total Y-band K-correction uncertainties at maximum are smallest, amounting to ± 0.04 mag at a redshift of z = 0.08. The J-band K-term errors are also reasonably small (± 0.06 mag), but intrinsic variations of spectral features and noise introduced by telluric corrections in the H-band currently limit its total K-correction errors at maximum to ± 0.10 mag at z = 0.08. Finally, uncertainties in the Ks-band K terms at maximum amount to ± 0.07 mag at this same redshift. These results are largely constrained by the small number of published NIR spectra of SNe Ia, which do not yet allow spectral templates to be constructed as a function of the light curve decline rate.

Two-dimensional (2D) infrared (IR) correlation spectroscopy for dynamic absorption behavior of oleic acid (OA) onto silica gel

Dynamic absorption behavior of oleic acid (OA) onto silica gel was probed by infrared (IR) spectroscopy. Once OA is injected into silica gel placed on a horizontal attenuated total reflectance prism, the silica gel starts to absorb the OA molecules due to the molecular-level interaction based on hydrogen bonding between the COOH of OA and the OH of silica gel. The substantial level of variation of spectral feature is readily observed during the absorption of OA onto silica gel. 2D correlation analysis of the time-dependent IR spectra reveals fine details of absorption dynamics of OA molecules depending on the molecular structure. The predominant absorption of the monomers occurs at the onset of the absorption, and it is then quickly followed by the decrease in the dimers. In other words, the dissociation of the liquid crystals occurs via the disuniting of the tightly packed OA dimers.

Time-dependent spectral-feature variations of stars displaying the B[e] phenomenon

Context. B[e] stars are anomalous objects around which extended circumstellar matter is present. The observed properties of the central star are significantly affected by the surrounding material. Therefore, the use of standard synthetic spectra is disputable in this case and our capability to study these objects is limited. One of the possibilities is to analyse variations of the spectral features. Long-term spectroscopic observations are required for this, but are not found in the literature. For our study we choose the B[e] star HD 50138 of the FS CMa type because of the indication that this star is a post-main-sequence star, although still not highly evolved. Therefore, it can be a good object for testing evolutionary models. Currently, HD 50138 is the most extensively observed FS CMa star which makes it an ideal object for modelling. Our observations fill the gap in the available data.Aims. To describe the variability of HD 50138 we have monitored this star spectroscopically over the last twenty years. To search for the periodicity on short-term scales, series of night-to-night observations were also obtained. We were able to obtain 130 spectra from four different telescopes – 1.06 m at Ritter Observatory (echelle, R ~ 26 000, 32 spectra, 1994-2003), the Perek 2 m telescope at Ondrejov Observatory (slit, R ~ 12 500, 56 spectra, 2004-2013), the 2.12 m telescope at Observatorio Astronomico Nacional San Pedro Martir (echelle, R ~ 18 000, 16 spectra, 2005-2013), and the 0.81 m telescope at Three College Observatory (echelle, R ~ 12 000, 26 spectra, 2013-2014).Methods. We describe and analyse variations of the chosen lines. The measurements of the equivalent widths and radial velocities of the Ha, Hs, and [O?i] ?? 6300, 6364 A lines are presented. The set of obtained spectra allows us to describe the changes on timescales from days to years.Results. The long-term quasi-periodic trend was found in the variations of the Ha equivalent width and confirmed by time dependent studies of the relative flux and equivalent width of the [O?i] 6300 A line and radial velocity of the Ha violet peak. The two long periods of 3000 ± 500and 5000 ± 1000 days were detected there. We were able to catch moving humps in the Ha line, which reveal the rotating media around the star. An analysis of the correlation of equivalent widths, radial velocities, relative fluxes, and V/R ratios for various lines is presented in detail.Conclusions. We describe the spectral variability of HD 50138 over the last twenty years. Based on these data, we determine new restrictions for future modelling. We confirm the quasi-periodic behaviour of the object’s spectral variability, which probably reflects mass transfer in a binary system. This behaviour also supports a recently introduced explanation of the nature of FS CMa stars as post-merger systems.

X-ray absorption spectra of InxGa1−xN alloys with insight from atom-specific simulations

We report N-K--edge x-ray absorption near-edge spectra of a set of In${}_{x}$Ga${}_{1\ensuremath{-}x}$N alloy epilayers with $0.36\ensuremath{\le}x\ensuremath{\le}0.87$, including linear dichroism effects. Careful experimental and data treatment procedures lead to consistent variations of spectral features with In concentration and sample orientation with respect to the direction of linear polarization of the x-ray beam. Insight into the origin of spectral features is provided by a combination of ab initio simulations of the equilibrium structure and atom-by-atom spectral simulations. The relation between the spectral lineshape and the variations in the composition of the first coordination shell and the corresponding local structural distortions is discussed.