Spectral Sampling Research Articles

Sensitive Spectroscopic Analysis of Biomarkers in Exhaled Breath

We have developed a novel optical setup which is based on a high finesse cavity and absorption laser spectroscopy in the near-IR spectral region. In pilot experiments, spectrally resolved absorption measurements of biomarkers in exhaled breath, such as methane and acetone, were carried out using cavity ring-down spectroscopy (CRDS). With a 172-cm-long cavity, an efficient optical path of ~ 132 km was achieved. The CRDS technique is well suited for such measurements due to its high sensitivity and good spectral resolution. The detection limits for methane of ~ 8 ppbv and acetone of ~ 2.1 ppbv with spectral sampling of 0.005 cm−1 were achieved, which allowed to analyze multicomponent gas mixtures and to observe absorption peaks of 12CH4 and 13CH4. Further improvements of the technique have the potential to realize diagnostics of health conditions based on a multicomponent analysis of breath samples.

A mean-based filter to remove power line harmonic noise from seismic reflection data

Power line harmonic noise generated by power lines during the seismic data acquisition in land and marine seismic surveys generally appears as a single frequency with 50/60Hz (or multiples of these frequencies) and contaminates seismic data leading to complicate the identification of fine details in the data. Commonly applied method during seismic data processing to remove the harmonic noise is classical notch filter (or very narrow band-stop filter), however, it also attenuates all recorded data around the notch frequencies and results in a complete loss of available information which corresponds to fine details in the seismic data.In this study, we introduce an application of the algorithm of iterative trimmed and truncated mean filter method (ITTM) to remove the harmonic noise from seismic data, and here, we name the method as local ITTM (LITTM) since we applied it to the seismic data locally in spectral domain. In this method, an optimal value is iteratively searched depending on a threshold value by trimming and truncating process for the spectral amplitude samples within the specified spectral window. Therefore, the LITTM filter converges to the median, but, there is no need to sort the data as in the case of conventional median filters. On the other hand, the LITTM filtering process doesn't require any reference signal or a precise estimate of the fundamental frequency of the harmonic noise, and only approximate frequency band of the noise within the amplitude spectra is considered. The only required parameter of the method is the width of this frequency band in the spectral domain.The LITTM filter is first applied to synthetic data and then we analyze a real marine dataset to compare the quality of the output after removing the power line noise by classical notch, median and proposed LITTM filters. We observe that the power line harmonic noise is completely filtered out by LITTM filter, and unlike the conventional notch filter, without any damage on the available frequencies around the notch frequency band. It also provides a more balanced amplitude spectrum since it does not produce amplitude notches in the spectrum.

Accurate and rapid detection of soil and fertilizer properties based on visible/near-infrared spectroscopy.

Accurate information of soil macronutrient contents and fertilizer macronutrient contents is the precondition of precision fertilization; however, how to detect soil and fertilizer information rapidly, reliably, and inexpensively remains a great challenge. Visible and near-infrared (VIS/NIR) diffuse reflectance spectroscopy proves to be an effective tool for extensive investigation of soil and fertilizer properties. This study first collected many soil and chemical fertilizer samples and performed both spectral scanning and chemical analysis. During the correlation between the collected VIS/NIR spectra and the measured data, different spectral pretreatment, sample selection, and wavelength optimization methods were applied for improving the accuracy and robustness of the prediction models. After appropriate spectral processing and selection of representative samples, both principal component regression and genetic algorithm (GA) can adequately reduce the number of variables and pick out the characteristic variables, which not only enhanced prediction speed but also greatly improved prediction accuracy. In particular, using GA-based models, organic matter content (OMC), total N and pH value in soil and N, P, and K contents in fertilizer can all be accurately predicted.

Mapping the distribution of iron ore minerals and spatial correlation with environmental variables in hilltop mining areas

The prime contribution of this assignment was to examine the hyperspectral remote sensing, based on iron ore minerals identification using spectral angle mapper (SAM) technique. Correlation analyses between field iron contents and environmental variables (soil, water, and vegetation) have been performed. Spectral feature fitting (SFF) and multi-range spectral feature fitting (MRSFF) methods were used for accuracy assessment in extracting iron ore minerals from Hyperion EO-1 data. Spectral inspections as a reference were used in SAM technique for image classification for iron ore minerals: Hematite (24.26%), Goethite (32.98%) and Desert (42.76). Iron ore minerals classification is justified by the United States Geological Survey (USGS) spectral library and field sample points. The regression analysis of USGS and Hyperion reflectance spectra has shown the moderate positive correlation. The regression analyses between iron ore contents and environmental parameters (soil, water, and vegetation) have shown the moderate negative correlation. The examination was significantly effectual in extracting iron ore minerals: Hematite (SFF RMSE ≤ 0.51 MRSFF RMSE ≤ 0.48), Goethite (SFF RMSE ≤ 0.047 MRSFF RMSE ≤ 0.438) and Desert (SFF RMSE ≤ 0.63 and MRSFF RMSE ≤ 0.50); and the MRSFF RMSE histograms indicate the above result likened to a conventional SFF RMSE. MRSFF RMS error result is best because multiple absorption features typically characterize spectral signatures. This analysis demonstrates the potential applicability of the methodology for iron minerals identification framework and iron minerals impact on environmental parameters.

Correction to: Efficient multiobjective optimization employing Gaussian processes, spectral sampling and a genetic algorithm

This note lists changes to the article by Bradford et al.. A number of figures have moved to the wrong positions, while the references in the text still refer to the correct figure, i.e. a number of figures are now in the wrong section, have the wrong position and have the wrong caption.

Evaluation of spectral libraries and sample preparation for DIA-LC-MS analysis of host cell proteins: A case study of a bacterially expressed recombinant biopharmaceutical protein

Recombinantly expressed biopharmaceutical proteins often undergo a series of purification steps with the aim of removing contaminating material. Depending on the application of the protein, there are various requirements for the degree of purity, but host cell proteins (HCPs) will in general remain in small amounts. LC-MS has emerged as an orthogonal technique, capable of providing detailed information regarding the individual proteins. The aim of this case study was to characterize the HCPs associated with a biopharmaceutical protein, provided by Statens Serum Institut (DK), which is used in the field of tuberculosis and has not previously been studied by LC-MS. The developed method and acquired experiences served to develop a generalized strategy for HCP-characterization in our laboratory. We evaluated the use of different spectral libraries, recorded in data-dependent mode for obtaining the highest HCP coverage, combined with SWATH-based absolute quantification. The accuracy of two label-free absolute quantification strategies was evaluated using stable isotope peptides. Two different sample preparation workflows were evaluated for optimal HCP yield. . The label-free strategy produced accurate quantification across several orders of magnitude, and the calculated purity was found to be in agreement with previously obtained ELISA data.

Efficient multiobjective optimization employing Gaussian processes, spectral sampling and a genetic algorithm

Many engineering problems require the optimization of expensive, black-box functions involving multiple conflicting criteria, such that commonly used methods like multiobjective genetic algorithms are inadequate. To tackle this problem several algorithms have been developed using surrogates. However, these often have disadvantages such as the requirement of a priori knowledge of the output functions or exponentially scaling computational cost with respect to the number of objectives. In this paper a new algorithm is proposed, TSEMO, which uses Gaussian processes as surrogates. The Gaussian processes are sampled using spectral sampling techniques to make use of Thompson sampling in conjunction with the hypervolume quality indicator and NSGA-II to choose a new evaluation point at each iteration. The reference point required for the hypervolume calculation is estimated within TSEMO. Further, a simple extension was proposed to carry out batch-sequential design. TSEMO was compared to ParEGO, an expected hypervolume implementation, and NSGA-II on nine test problems with a budget of 150 function evaluations. Overall, TSEMO shows promising performance, while giving a simple algorithm without the requirement of a priori knowledge, reduced hypervolume calculations to approach linear scaling with respect to the number of objectives, the capacity to handle noise and lastly the ability for batch-sequential usage.

Resolving Dopamine Receptor Dynamics with Spatial, Temporal, and Spectral Sampling

Resolving Dopamine Receptor Dynamics with Spatial, Temporal, and Spectral Sampling

The on-ground calibration performances of the hyperspectral microscope MicrOmega for the Hayabusa-2 mission

The miniaturized near-infrared hyperspectral microscope MicrOmega, on board the MASCOT lander for Hayabusa-2 mission, is designed to perform in situ measurements at the grain scale of the C-type asteroid 1999 JU3 RYUGU. MicrOmega will observe samples with a field of view of a few millimeters with a spatial sampling of 25 μm and acquire near-infrared spectra by illuminating the sample sequentially with different wavelengths from 0.99 to 3.55 μm over two spectral channels with a typical spectral sampling of 20 cm−1. The on-ground calibration of MicrOmega requires a full characterization of the nominal range of operation of the instrument, both spectral (0.99–3.55 μm) and thermal (−40 °C to +40 °C) to derive the radiometric and spectral responses combined into a 4D transfer function to convert raw signal to calibrated reflectance. This specific 4D radiometric reference gives the instrument response according to the pixel location (x,y), the wavelength and the instrument temperature. This paper reports the complex computation of the 4D radiometric reference for the 0.9–2.5 μm channel. In this spectral range, the composition of the grains of a wide variety of minerals with relevance to solar system bodies can be identified through diagnostic spectral features: mafic (pyroxene, olivine…) as well as hydrated and altered minerals that are key phases for the solar system bodies’ exploration.

紧凑型红外成像光谱仪光学设计

To reduce the burden of the working platform, optimize the optical structure and promote the thermal adaption of the imaging spectrometer, an optical design of a compact infrared imaging spectrometer was presented. Due to compactness and aberration correction, the extended polynomial surfaces were utilized in the optical design of the infrared imaging spectrometer with spectral region between 1 m to 3.4 m, optical speed of F/2.86, and spectral sampling of 7.5 nm. The optical system was comprised of a free form three mirror telescope and a plane grating based free form spectrometer. The telescope was semi telecentric for pupil matching with the telecentric spectrometer, free of distortion and able to provide enough imaging space for other modules. The good imaging quality of spectrometer, and spectral distortion correction were achieved, and the tilt of image plane for detector arrangement was improved. The system is analyzed from the diffraction efficiency of the grating, the supressed stray light, as well as the opto-mechanical design of the integrated mirrors, which show it has high engineering feasibility.

空间辐射基准传递不确定性的光谱敏感性分析

空间辐射基准传递不确定性的光谱敏感性分析

Selecting optimal features from Fourier transform infrared spectroscopy for discrete-frequency imaging.

Tissue histology utilizing chemical and immunohistochemical labels plays an important role in biomedicine and disease diagnosis. Recent research suggests that mid-infrared (IR) spectroscopic imaging may augment histology by providing quantitative molecular information. One of the major barriers to this approach is long acquisition time using Fourier-transform infrared (FTIR) spectroscopy. Recent advances in discrete frequency sources, particularly quantum cascade lasers (QCLs), may mitigate this problem by allowing selective sampling of the absorption spectrum. However, DFIR imaging only provides a significant advantage when the number of spectral samples is minimized, requiring a priori knowledge of important spectral features. In this paper, we demonstrate the use of a GPU-based genetic algorithm (GA) using linear discriminant analysis (LDA) for DFIR feature selection. Our proposed method relies on pre-acquired broadband FTIR images for feature selection. Based on user-selected criteria for classification accuracy, our algorithm provides a minimal set of features that can be used with DFIR in a time-frame more practical for clinical diagnosis.

A Statistical Comparison between Photospheric Vector Magnetograms Obtained by SDO/HMI and Hinode/SP

Abstract Since 2010 May 1, we have been able to study (almost) continuously the vector magnetic field in the Sun, thanks to two space-based observatories: the Solar Dynamics Observatory (SDO) and Hinode. Both are equipped with instruments able to measure the Stokes parameters of Zeeman-induced polarization of photospheric line radiation. But the observation modes; the spectral lines; the spatial, spectral, and temporal sampling; and even the inversion codes used to recover magnetic and thermodynamic information from the Stokes profiles are different. We compare the vector magnetic fields derived from observations with the HMI instrument on board SDO with those observed by the SP instrument on Hinode. We have obtained relationships between components of magnetic vectors in the umbra, penumbra, and plage observed in 14 maps of NOAA Active Region 11084. Importantly, we have transformed SP data into observables comparable to those of HMI, to explore possible influences of the different modes of operation of the two instruments and the inversion schemes used to infer the magnetic fields. The assumed filling factor (fraction of each pixel containing a Zeeman signature) produces the most significant differences in derived magnetic properties, especially in the plage. The spectral and angular samplings have the next-largest effects. We suggest to treat the disambiguation in the same way in the data provided by HMI and SP. That would make the relationship between the vector magnetic field recovered from these data stronger, which would favor the simultaneous or complementary use of both instruments.

Solid state structural investigations of the bis(chalcone) compound with single crystal X-ray crystallography, DFT, gamma-ray spectroscopy and chemical spectroscopy methods

A bis(chalcone), (2E,6E)-2,6-bis((E)-3phenylallidene)cyclohexanone, was characterized by 1H NMR, 13C NMR, FTIR, UV-Vis spectroscopy, gamma-ray spectroscopy and single crystal X- ray structural analysis. The optimized molecular structure of the compound is calculated using DFT/B3LYP with 6-31G (d,p) level. The calculated geometrical parameters are in good agreement with the experimental data obtained from our reported X-ray structure. The powder and single crystal compounds were gama-irradiated using clinical electron linear accelerator and 60Co gamma-ray source, respectively. Spectral studies (1H NMR, 13C NMR, FTIR and UV-Vis) of powder chalcone compound were also investigated before and after irradiation. Depending on the irradiation notable changes were observed in spectral features powder sample. Single crystal X-ray diffraction investigation shows that both unirradiated and irradiated single crystal samples crystallizes in a orthorhombic crystal system in the centrosymmetric space group Pbcn and exhibits an C-H..O intramolecular and intermolecular hydrogen bonds. The crystal packing is stabilised by strong intermolecular bifurcate C-H..O hydrogen bonds and π…π stacking interactions. The asymmetric unit of the title compound contains one-half of a molecule. The other half of the molecule is generated with (1-x,y,-3/2-z) symmetry operator. The molecule is almost planar due to having π conjugated system of chalcones. However, irradiated single crystal compound showed significant changes lattice parameters, crystal volume and density. According to results of gamma-ray spectroscopy, radioactive elements of powder compound which are 123Sb(n,g),124Sb,57Fe(g,p),56Mn, 55Mn(g,n), and 54Mn were determined using photoactivation analysis. However, the most intensive gamma-ray energy signals are 124Sb.

Two-dimensional correlation analysis of spectra collected without knowing sampling order

Two-dimensional correlation spectroscopy (2DCOS) without a priori knowledge of meaningful spectral sampling order is considered. Construction of synchronous 2D correlation spectrum does not require the knowledge of sampling order, and disrelation spectrum derived from synchronous spectrum possesses useful features similar to those of asynchronous spectrum. Disrelation analysis may provide enhanced spectral resolution and distinction of bands arising from different sources but not the sequential order of intensity variations. Dataset sampled in an arbitrary or scrambled order may be reassembled into a more structured form by rank ordering the spectra with the intensity of a select band. If there is no meaningful data structure, asynchronous 2D correlation should not be attempted, although synchronous and disrelation spectra may still be useful. The intrinsic ambiguity in the direction of sampling order may sometimes be resolved using additional physical information known about the sample system.

Sensitivity of clay content prediction to spectral configuration of VNIR/SWIR imaging data, from multispectral to hyperspectral scenarios

The use of digital soil mapping, with the help of spectroscopic data, provides a non-destructive and cost-efficient alternative to soil property laboratory measurements. Visible, near-infrared and short wave infrared (VNIR/SWIR, 400–2500nm) hyperspectral imaging is one of the most promising tools for topsoil property mapping. The aim of this study was to test the sensitivity of soil property prediction results to coarsening image spectral resolution. This may offer an analysis of the potential of forthcoming hyperspectral satellite sensors, e.g., HYPerspectral X IMagery (HYPXIM) or Environmental Mapping and Analysis Program (EnMAP), and existing multispectral sensors, e.g., SENTINEL-2 Multispectral Sensor Instrument (MSI) or LANDSAT-8 Operational Land Imager (OLI), for soil properties mapping. This study used VNIR/SWIR hyperspectral airborne data acquired by the AISA-DUAL sensor (initial spectral and spatial resolutions of approximately 5nm and 5m, respectively) over a 300km2 Mediterranean rural region. Ten spectral configurations were built and divided in the following two groups: i) six spectral configurations corresponding to simulated sensors with regular spectral resolution from 5nm to 200nm (i.e., the Full Width at Half Maximum (FWHM) remains constant throughout the considered spectral domain; this includes the simulation of the forthcoming HYPXIM and EnMAP hyperspectral satellites) and ii) four spectral configurations corresponding to existing multispectral sensors with irregular spectral resolution (i.e., the FWHM differs from spectral sampling interval; Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), SENTINEL-2 MSI, LANDSAT-7 Enhanced Thematic Mapper (ETM+) and LANDSAT-8 OLI). The soil property studied in this paper is the clay content, defined as the percentage of granulometric fraction finer than 2μm by weight of the soil, which will be estimated using the partial least squares regression method. Our results showed that i) spectral configurations with regular spectral resolutions from 5 to 100nm provided similar and good clay content prediction performances (R2val>0.7 and RPIQ>3) and allowed clay mapping with correct short-scale variations, ii) the spectral configuration with a regular spectral resolution of 200nm provided unsatisfactory clay content prediction performance (R2val≃0.01 and RPIQ≃1.65) and iii) the ASTER sensor was the only existing multispectral sensor that provided both correct performance of clay content estimation (R2val≃0.8 and RPIQ≃3.72) and correct clay mapping. Therefore, clay mapping by the ASTER multispectral data should be pursued while awaiting the launch of forthcoming hyperspectral satellite sensors (e.g., HYPXIM and EnMAP), which will be good candidates for future large clay mapping campaigns over bare soils.

Composition and structure of fresh ammonia clouds on Jupiter based on quantitative analysis of Galileo/NIMS and New Horizons/LEISA spectra

Ammonia gas has long been assumed to be the main source of condensables for the upper cloud layer on Jupiter, but distinctive spectral features associated with ammonia have been seen only rarely. Since both ammonia and NH4SH absorb in the 3 µm region, and widespread absorption in the 3 µm region was present (Sromovsky and Fry, 2010), identification of the 2 µm absorption feature of NH3 provided an opportunity to clearly establish its presence in Jovian clouds. Baines et al. (2002) succeeded in finding in Near Infrared Mapping Spectrometer (NIMS) observations one feature that had both 2 µm and 3 µm absorption, and many which were known to have absorption at 2.73 µm. They named these Spectrally Identifiable Ammonia Clouds (SIACs). They also argued that these were fresh ammonia clouds that would eventually succumb to some process that would obscure their absorption features. Detection of many more of the 2 µm features was later achieved by New Horizon’s Linear Etalon Imaging Spectral Array (LEISA) instrument, which provided both the spatial and spectral resolution needed to identify these features. Here we report on the first quantitative modeling that uses NIMS spectra over a broad (1–5.2 µm) spectral range and LEISA spectra over a much narrower (1.25–2.5 µm) spectral range to constrain the cloud structure and composition of these rare cloud features and compare them to background clouds. We find that the absorption signature at 2 µm, which is well characterized in LEISA spectra, is relatively subtle and easily matched by model clouds containing spherical particles of ammonia ice with radii of 2–4 µm. The NIMS spectra, which cover both reflected sunlight as well as thermal emission regions are more difficult to model with cloud materials plausibly present in Jupiter’s atmosphere. The best signal/noise spectra obtained from NIMS provide a relatively sparse sampling of the spectrum, which does not establish the detailed shape of the 3 µm absorption region. NIMS SIAC spectra with much denser spectral sampling are limited by much higher noise levels that degrade the features that are key to identifying cloud composition. The structure which best matches the wide range NIMS SIAC spectra contains two overlapping NH3 clouds with a bi-modal size distribution over an optically thick NH4SH cloud. The bi-modal distribution may be a result of modeling non-spherical, possibly fractal aggregate, particles with spheres.

Hyperspectral radiative transfer modeling to explore the combined retrieval of biophysical parameters and canopy fluorescence from FLEX – Sentinel-3 tandem mission multi-sensor data

The FLuorescence EXplorer (FLEX) satellite mission, selected as ESA's 8th Earth Explorer, has been designed for the measurement of sun-induced fluorescence (F) spectra emitted by plants. This will be accomplished through a multi-sensor approach by placing it in a common orbit in tandem with the Sentinel-3 (S3) mission, which will have two optical sensors on board, OLCI (Ocean and Land Colour Instrument) and SLSTR (Sea and Land Surface Temperature Radiometer) to complement FLEX. These S3 instruments will be used in combination with the imaging spectrometers on board FLEX to provide data useful for atmospheric correction of FLEX data. However, a fully synergetic approach, i.e. by exploiting the spectral and directional information from all tandem mission instruments together, is an attractive alternative which is explored in this paper. By employing all combined top-of-atmosphere (TOA) spectral radiance data, one can (i) characterize the relevant optical properties of the atmosphere, (ii) retrieve biophysical canopy properties including the associated reflectance anisotropy, and (iii) retrieve a more accurate and consistent canopy F.Regarding retrieval methods, Fraunhofer Line Depth (FLD) and Spectral Fitting (SF) are well-known techniques applied to hyperspectral data. Both methods depend on a high spectral resolution and assume a Lambertian (isotropic) canopy reflectance. However, most vegetation canopies are non-Lambertian. This implies that, in particular when ignoring the anisotropic surface reflection, substantial retrieval errors can occur due to the interaction between atmospheric absorption bands and surface reflectance anisotropy. In this paper, a novel method based on spectral radiative transfer (RT) modeling is proposed, in which coupled RT models are used to simulate TOA radiance spectra. These are then matched with ‘measured’ spectra in order to retrieve surface fluorescence, along with a suite of biophysical parameters, by model inversion through optimization. By applying coupled RT models of the soil-leaf-canopy and the surface-atmosphere systems, TOA radiance spectra can be simulated for all optical sensors of this tandem mission. In this way, complex effects due to surface reflectance anisotropy and the spectral sampling by the various instruments, which are difficult to compensate for in the end products, are properly taken into account by their incorporation in the forward modeling. Next, by model inversion of TOA radiance data via optimization, the most accurate F retrievals can be achieved in a consistent manner, along with important canopy level biophysical parameters that may help interpret the F spectrum, such as chlorophyll content and leaf area index (LAI). The potential of this approach has been explored in a numerical experiment, and the results are presented in this paper. We find that, with the assumed well-characterized and plausible FLEX/S3 instrument performances, the simultaneous retrieval of biophysical canopy parameters and F spectra would be possible with a remarkable accuracy, provided the correct atmospheric characterization is available.

Vowel contrasts relative to schwa: Effects of utterance-level fundamental frequency

The purpose of this study is to characterize the potential effects of utterance-level fundamental frequency (F0) on the acoustic contrasts of vowels as expressed relative to the mid-central vowel schwa. This is a follow-up to a previous study [Kuo, J. Acoust. Soc. Am. 141, 3840 (2017)] based on a hypothesis of schwa as a speaker-defined reference for vowel contrasts. The hypothesized reference schwa is made up of the averaged first and second formant (F1 and F2) frequencies from many tokens of schwa produced by a given speaker. Motivated by the potential interactions among F0, spectral sampling, and articulation, the present study evaluates the effects, if any, of utterance-level F0 on vowel contrasts relative to schwa. Utterance-level F0 is measured for breath groups at the sentence level. Vowel contrasts are expressed as the Euclidean distances between vowels and the reference schwa in the F1-F2 space. Specifically, two questions are of interest. First, are the Euclidean distances between vowels and the reference schwa impacted by the utterance-level F0? Second, does utterance-level F0 affect the variability of schwa productions, and thus influencing the makeup of the reference schwa? Findings will be discussed within the framework of the acoustic theory of speech production.

Mira Variable Stars from LAMOST DR4 Data: Emission Features, Temperature Types, and Candidate Selection

Based on an extensive spectral study of a photometrically confirmed sample of Mira variables, we find a relationship between relative Balmer emission-line strength and spectral temperature of O-rich Mira stars. The $F_{\rm H\delta}/F_{\rm H\gamma}$ flux ratio increases from less than unity to five as stars cool down from M0 to M10, which is likely driven by increasing TiO absorption above the deepest shock-emitting regions. We also discuss the relationship between the equivalent widths of the Balmer emission lines and the photometric luminosity phase of our Mira sample stars. Using our 291 Mira spectra as templates for reference, 191 Mira candidates are newly identified from the LAMOST DR4 catalog. We summarize the criteria adopted to select Mira candidates based on emission-line indices and molecular absorption bands. This enlarged spectral sample of Mira variables has the potential to contribute significantly to our knowledge of the optical properties of Mira stars and will facilitate further studies of these late-type, long-period variables.