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In this paper, we propose a spectrally-resolved titanium dioxide waveguide resonant sensor, modified with a perovskite film. The sensor consists of a prism (N-FK51A), gold (Au), hybrid organic–inorganic halide perovskites, and titanium dioxide layers. The thickness of each layer and the incident angle were optimized based on the Fresnel equations. The refractive index sensitivity of the sensor increased by 32.1% and the figure of merit improved by 60.0% after optimizing the thickness of each layer. The optimized sensor was applied to detect five types of cancer biomarkers (Basal, HeLa, Jurkat, PC12, and MDA-MB-231). Simulation results at an incident angle of 14° demonstrate that the sensor shows excellent performance for the proposed cancer biomarkers, with resonance wavelength shifts ranging from 26 to 44 nm due to differences in the refractive indices between normal cell and cancer cell. These results indicate that the perovskite-modified sensor offers superior sensitivity compared to conventional sensors without the perovskite structure. This enhancement significantly improves the detection performance across various cancer biomarkers. Additionally, by replacing the dense titanium dioxide film with a nanoporous structure in the waveguide layer, which also acts as a biochemical molecule enrichment layer, the detection sensitivity for low-concentration small molecules in solution can be further enhanced. The adsorption sensitivity for small molecules is 90 nm per unit volume fraction. [ABSTRACT FROM AUTHOR]

The apparent enhancement of spectral resolution is one of the attractive features of two-dimensional correlation spectroscopy (2D-COS). Highly overlapped adjacent bands often encountered in one-dimensional spectra may be effectively differentiated and identified by spreading peaks along the second dimension. This differentiating feature or selectivity is especially prominent in asynchronous spectra, where even a slight difference in the variation patterns of overlapped bands in response to a given perturbation results in the generation of cross-peaks. While cross-peaks in asynchronous spectra can identify signals originating from different moieties or bands, they do not effectively specify which regions of spectra actually share the same molecular origin. Overreliance on asynchronous spectra alone risks the potential false negative assessment or lack of sufficient specificity, leading to the failure of classifying signals into a reasonable set of component groups. The combined use of synchronous and asynchronous spectra coupled with the scaling techniques, elimination of anti-correlated negative synchronous peaks, and a robust line shape narrowing method provides a means to achieve both selectivity and specificity for resolution-enhancement of 2D-COS. [ABSTRACT FROM AUTHOR]

Objective. Currently, the task of increasing the spectral solvability of a video stream using modern frame filtering methods is urgent. Various methods of frame filtering are considered and analyzed in the work, and their detailed comparative analysis is carried out. The obtained data contribute to the further development of various materials to increase the spectral resolution of the video stream. Method. A large number of different approaches have been developed in the scientific literature to increase the spectral resolution of a video stream using modern frame filtering methods, and the most basic ones are analyzed in this paper: linear spatial filtering; nonlinear spatial filtering; spatial frequency filtering; filtering using Fourier analysis; filtering based on wavelet analysis. Result. A preliminary systematization of the characteristics of the methods under consideration has been carried out in order to develop new algorithms and implement them to improve image quality, increase detail and clarity of the video stream; various frame filtering methods have been analyzed, contributing to an increase in the spectral resolution of the video stream, and their impact on the quality of video content has been considered; during the analysis, it was found that in order to increase the spectral solvability of the video stream, it is necessary to use a combined filter. The above facts will allow us to further develop methodological recommendations for increasing the spectral solvability of the video stream. Conclusion. The considered approaches to increasing the spectral resolution of a video stream using modern frame filtering methods are preferable when increasing the spectral resolution of images, since they use all the positive aspects of linear, nonlinear and spatial frequency filtering.

Image enhancement is the process of improving the quality of a digital image. Improved image quality is one of the goals of the ongoing effort to improve the information content and interpretability of satellite images. Two sets of remote sensing data were collected for this region: one from the SPOT-4 (2018) satellite and the other from the Enhanced Thematic Mapper Plus (ETM+) Landsat 7 (2020) satellite. This study used two images taken at various spatial resolutions of the same location. Two images are shown here: one with a 30 m spatial resolution and the other with a 5 m resolution with multispectral processing. The results indicate that integrating spatial and spectral resolution using geomatics techniques significantly benefits various applications. Before merging the images, it was root mean square error (RMSE) 11.55 Easting, 5.77 Northing and became 1.52 Easting, 1.45 Northing after merging the images. After implementing the approach, the resulting fusing image exhibits enhanced spatial resolution, and the resulting multispectral image has excellent spatial as well as spectral resolution. Finally, the improved combined image with great spatial and spectral resolution is prepared for analysis and classification. [ABSTRACT FROM AUTHOR]

Infants begin to segment word forms from fluent speech—a crucial task in lexical processing—between 4 and 7 months of age. Prior work has established that infants rely on a variety of cues available in the speech signal (i.e., prosodic, statistical, acoustic‐segmental, and lexical) to accomplish this task. In two experiments with French‐learning 6‐ and 10‐month‐olds, we use a psychoacoustic approach to examine if and how degradation of the two fundamental acoustic components extracted from speech by the auditory system, namely, temporal (both frequency and amplitude modulation) and spectral information, impact word form segmentation. Infants were familiarized with passages containing target words, in which frequency modulation (FM) information was replaced with pure tones using a vocoder, while amplitude modulation (AM) was preserved in either 8 or 16 spectral bands. Infants were then tested on their recognition of the target versus novel control words. While the 6‐month‐olds were unable to segment in either condition, the 10‐month‐olds succeeded, although only in the 16 spectral band condition. These findings suggest that 6‐month‐olds need FM temporal cues for speech segmentation while 10‐month‐olds do not, although they need the AM cues to be presented in enough spectral bands (i.e., 16). This developmental change observed in infants' sensitivity to spectrotemporal cues likely results from an increase in the range of available segmentation procedures, and/or shift from a vowel to a consonant bias in lexical processing between the two ages, as vowels are more affected by our acoustic manipulations. Research Highlights: Although segmenting speech into word forms is crucial for lexical acquisition, the acoustic information that infants' auditory system extracts to process continuous speech remains unknown.We examined infants' sensitivity to spectrotemporal cues in speech segmentation using vocoded speech, and revealed a developmental change between 6 and 10 months of age.We showed that FM information, that is, the fast temporal modulations of speech, is necessary for 6‐ but not 10‐month‐old infants to segment word forms.Moreover, reducing the number of spectral bands impacts 10‐month‐olds' segmentation abilities, who succeed when 16 bands are preserved, but fail with 8 bands. [ABSTRACT FROM AUTHOR]

The uncertainty in estimating the wave spectrum from the records of wave elevation by heave–pitch–roll buoys is studied, considering the effects of the estimation method and the spectral resolution adopted in the process. This investigation utilizes measurements from a wave buoy moored in deep water in the South Atlantic Ocean. First, the spectra are computed using the autocorrelation function and the direct Fourier method. Second, the spectral resolution is tested in terms of degrees of freedom. The degrees of freedom are varied, and the resulting spectra and integrated parameters are computed, showing significant variability. A simple and robust methodology for determining the wave spectrum is suggested, which involves calculating the average energy density in each frequency band. The results of this methodology reduce the variability of the estimated parameters, improving overall accuracy while preserving frequency resolution, which is crucial in complex sea states. Additionally, to demonstrate the feasibility of the implemented approach, the final spectrum is fitted using an empirical model ideal for that type of spectrum. Finally, the performance and the goodness of the fit process for the final averaged curve are checked by widely used statistical metrics, such as R2 = 0.97 and root mean square error = 0.49. [ABSTRACT FROM AUTHOR]

Abstract Increasingly available spaceborne sensors provide unprecedented opportunities for large‐scale, timely and continuous tree species diversity (TSD) monitoring. However, given differences in spectral and spatial resolutions, the choice of sensor is not always straightforward. In this work, we investigated the effects of spatial and spectral resolutions for four spaceborne sensors (RapidEye, Landsat‐8, Sentinel‐2 and PlanetScope) on TSD mapping in an area of approximately 4000 km2 within the Black Forest, Germany. We employed a random forest (RF) regression model to predict Shannon–Wiener diversity based on seven types of spectral heterogeneity metrics (texture, coefficient of variation, Rao's Q, convex hull volume, spectral angle mapper, convex hull area and spectral species diversity) and a full survey dataset from 135 one‐ha sample plots. We compared the RF model's performance across sensors and spatial resolutions. Our results demonstrated that the Sentinel‐2‐based TSD model achieved the highest accuracy (mean R2: 0.477, mean root‐mean‐square error (RMSE): 0.274). The RapidEye‐based TSD model produced lower accuracy (mean R2: 0.346, mean RMSE: 0.303), but it was better than the PlanetScope‐ and Landsat‐based TSD models. The 10 m (for Sentinel‐2 and RapidEye) and 15 m (for PlanetScope) were the best spatial resolutions for predicting TSD. The NIR band was the most favourable spectral band for predicting TSD. Texture metrics and Rao's Q outperformed the other spectral heterogeneity metrics. Our results highlighted that spaceborne optical imagery (especially Sentinel‐2) can be successfully used for large‐scale TSD mapping but that the choice of sensors can significantly affect the resulting mapping accuracy in temperate montane forests.

Abstract Background The proposed research study introduces independent concentration extraction (ICE) as a novel UV–Vis spectrophotometric approach. The approach can be used for extracting the concentration of two analytes with severely overlapped spectra from their binary mixtures. ICE is based on spectral extraction platform involving simple smart successive methods that can directly extract the original zero order spectra of the analytes at their characteristic (λmax). Chlorpheniramine maleate (CPM) and Levocloperastine fendizoate (LCF) are two commonly co-formulated drugs in cough preparations. The combined mixture was used to confirm the validity of the developed ICE tool. Another less green HPTLC was developed for the first time to separate both drugs and help also in confirming the proposed tool. Methods For the simultaneous determination of CPM and LCF, two ecologically friendly techniques were employed. The first approach encompasses the use of the ICE spectrophotometric method that could be successively applied for extracting the concentration of two analytes with severely overlapped unresolved spectra in their binary mixtures. Other complementary methods aiming at original spectral extraction; including spectrum subtraction (SS) and unity subtraction (US) were also successfully employed to resolve the zero order spectra of the combined drugs with all their characteristic features and peaks. The second technique used, a high-performance TLC-densitometric one, was performed on silica plates with silica plates F254 and a mobile phase with a ratio of 3:3:3:1 by volume of toluene, ethanol, acetone, and ammonia as a developing system at 230 nm. Results The presented extraction approach was executed without any optimization steps or sample pretreatment for the simultaneous determination of CPM and LCF. The method was found to be valid for their determination within concentration range of 3.0–30.0 μg mL−1 for both drugs. For HPTLC method, the resulting Rf values of CPM and LCF were 0.37 and 0.78, within concentration ranges of 0.3–4.0 μg/spot and 0.8–10.0 μg/spot, respectively. Greenness assessment of both developed methodologies showed that the HPTLC method is less green than the spectrophotometric method, yet with comparable sustainability when it comes to the used technique. Conclusion The procedures were found to be selective, accurate, and precise for analysis of the studied binary mixture. Furthermore, the environmental impact of the introduced methods was assessed using novel greenness metrics, namely AGREE and Green Analytical Procedure Index (GAPI) to prove their ecological safety. In addition, white analytical chemistry (WAC) evaluation metric was employed to ensure the synergy and coherence of analytical, practical, and ecological attributes.

Background: The proposed research study introduces independent concentration extraction (ICE) as a novel UV–Vis spectrophotometric approach. The approach can be used for extracting the concentration of two analytes with severely overlapped spectra from their binary mixtures. ICE is based on spectral extraction platform involving simple smart successive methods that can directly extract the original zero order spectra of the analytes at their characteristic (λmax). Chlorpheniramine maleate (CPM) and Levocloperastine fendizoate (LCF) are two commonly co-formulated drugs in cough preparations. The combined mixture was used to confirm the validity of the developed ICE tool. Another less green HPTLC was developed for the first time to separate both drugs and help also in confirming the proposed tool. Methods: For the simultaneous determination of CPM and LCF, two ecologically friendly techniques were employed. The first approach encompasses the use of the ICE spectrophotometric method that could be successively applied for extracting the concentration of two analytes with severely overlapped unresolved spectra in their binary mixtures. Other complementary methods aiming at original spectral extraction; including spectrum subtraction (SS) and unity subtraction (US) were also successfully employed to resolve the zero order spectra of the combined drugs with all their characteristic features and peaks. The second technique used, a high-performance TLC-densitometric one, was performed on silica plates with silica plates F254 and a mobile phase with a ratio of 3:3:3:1 by volume of toluene, ethanol, acetone, and ammonia as a developing system at 230 nm. Results: The presented extraction approach was executed without any optimization steps or sample pretreatment for the simultaneous determination of CPM and LCF. The method was found to be valid for their determination within concentration range of 3.0–30.0 μg mL−1 for both drugs. For HPTLC method, the resulting Rf values of CPM and LCF were 0.37 and 0.78, within concentration ranges of 0.3–4.0 μg/spot and 0.8–10.0 μg/spot, respectively. Greenness assessment of both developed methodologies showed that the HPTLC method is less green than the spectrophotometric method, yet with comparable sustainability when it comes to the used technique. Conclusion: The procedures were found to be selective, accurate, and precise for analysis of the studied binary mixture. Furthermore, the environmental impact of the introduced methods was assessed using novel greenness metrics, namely AGREE and Green Analytical Procedure Index (GAPI) to prove their ecological safety. In addition, white analytical chemistry (WAC) evaluation metric was employed to ensure the synergy and coherence of analytical, practical, and ecological attributes. [ABSTRACT FROM AUTHOR]

Spectral features of olivine across the intermediate infrared region (IMIR, 4–8 μm) shift systematically with iron‐magnesium content, enabling determination of olivine composition. Previous IMIR studies have used laboratory data with signal‐to‐noise ratios (SNRs) and spectral resolutions potentially greater than those of data derived from planetary missions. Here we employ a feature fitting algorithm to quantitatively assess the influence of data quality on olivine detection and compositional interpretation from IMIR data of 29 spectra of pure olivine of synthetic, terrestrial, lunar, and Martian origins, as well as 5 spectra of lunar pyroclastic beads measured as bulk samples. First, we demonstrate the effectiveness of the feature fitting algorithm in the interpretation of IMIR olivine spectra, predicting olivine composition with an average error of 6.4 mol% forsterite across all test spectra using laboratory‐quality data. We then extend this analysis to degraded test spectra with reduced SNRs and sampling rates and find a range of data qualities required to predict olivine composition within ±11 Mg# (molar Mg/[Mg + Fe] × 100) for the test spectra explored here. Spectra for the sample most relevant to lunar exploration, an Apollo 74002 drive tube consisting of microcrystalline olivine and glass‐rich pyroclastics, required SNRs ≥ 200 for sampling rates ≤25 nm to predict composition within ±11 Mg# of the sample's true composition. Derived limits on SNRs and sampling rates will serve as valuable inputs for the development of IMIR spectrometers, enabling comprehensive knowledge of olivine composition on the lunar surface. Plain Language Summary: An understanding of olivine composition can reveal the history of large‐ and small‐scale magmatic processes, offering key insights into a planet's thermal and chemical evolution. Here we explore olivine spectra in the intermediate infrared region (IMIR), where systematic trends in olivine's absorption bands are indicative of composition. We degrade laboratory olivine spectra to data qualities that are more realistic of spectrometers used in planetary exploration and derive constraints on the signal‐to‐noise ratio and sampling rates required to accurately predict olivine composition. These constraints will be useful in the development of IMIR spectrometers. Key Points: We use a feature fitting routine to predict olivine composition from degraded spectral data in the intermediate infrared region (4–8 μm)Accurate prediction of olivine composition is observed at data qualities expected of spectrometers designed for space exploration [ABSTRACT FROM AUTHOR]

Increasingly available spaceborne sensors provide unprecedented opportunities for large‐scale, timely and continuous tree species diversity (TSD) monitoring. However, given differences in spectral and spatial resolutions, the choice of sensor is not always straightforward. In this work, we investigated the effects of spatial and spectral resolutions for four spaceborne sensors (RapidEye, Landsat‐8, Sentinel‐2 and PlanetScope) on TSD mapping in an area of approximately 4000 km2 within the Black Forest, Germany. We employed a random forest (RF) regression model to predict Shannon–Wiener diversity based on seven types of spectral heterogeneity metrics (texture, coefficient of variation, Rao's Q, convex hull volume, spectral angle mapper, convex hull area and spectral species diversity) and a full survey dataset from 135 one‐ha sample plots. We compared the RF model's performance across sensors and spatial resolutions. Our results demonstrated that the Sentinel‐2‐based TSD model achieved the highest accuracy (mean R2: 0.477, mean root‐mean‐square error (RMSE): 0.274). The RapidEye‐based TSD model produced lower accuracy (mean R2: 0.346, mean RMSE: 0.303), but it was better than the PlanetScope‐ and Landsat‐based TSD models. The 10 m (for Sentinel‐2 and RapidEye) and 15 m (for PlanetScope) were the best spatial resolutions for predicting TSD. The NIR band was the most favourable spectral band for predicting TSD. Texture metrics and Rao's Q outperformed the other spectral heterogeneity metrics. Our results highlighted that spaceborne optical imagery (especially Sentinel‐2) can be successfully used for large‐scale TSD mapping but that the choice of sensors can significantly affect the resulting mapping accuracy in temperate montane forests. [ABSTRACT FROM AUTHOR]

Multispectral imaging technology has advanced significantly in recent years, allowing single-sensor cameras with multispectral filter arrays to be used in new scene acquisition applications. Our camera, developed as part of the European CAVIAR project, uses an eight-band MSFA to produce mosaic images that can be decomposed into eight sparse images. These sparse images contain only pixels with similar spectral properties and null pixels. A demosaicing process is then applied to obtain fully defined images. However, this process faces several challenges in rendering fine details, abrupt transitions, and textured regions due to the large number of null pixels in the sparse images. Therefore, we propose a sparse image composition method to overcome these challenges by reducing the number of null pixels in the sparse images. To achieve this, we increase the number of snapshots by simultaneously introducing a spatial displacement of the sensor by one to three pixels on the horizontal and/or vertical axes. The set of snapshots acquired provides a multitude of mosaics representing the same scene with a redistribution of pixels. The sparse images from the different mosaics are added together to get new composite sparse images in which the number of null pixels is reduced. A bilinear demosaicing approach is applied to the composite sparse images to obtain fully defined images. Experimental results on images projected onto the response of our MSFA filter show that our composition method significantly improves image spatial resolution and minimizes reconstruction errors while preserving spectral fidelity. [ABSTRACT FROM AUTHOR]

Due to a legacy originating in the limited capability of early computers, the spectroscopic resolution used in Fourier transform infrared spectroscopy and other systems has largely been implemented using only powers of two for more than 50 years. In this study, we investigate debunking the spectroscopic lore of, e.g., using only 2, 4, 8, or 16 cm−1 resolution and determine the optimal resolution in terms of both (i) a desired signal-to-noise ratio and (ii) efficient use of acquisition time. The study is facilitated by the availability of solids and liquids reference spectral data recorded at 2.0 cm−1 resolution and is based on an examination in the 4000–400 cm−1 range of 61 liquids and 70 solids spectra, with a total analysis of 4237 peaks, each of which was also examined for being singlet/multiplet in nature. Of the 1765 liquid bands examined, only 27 had widths <5 cm−1. Of the 2472 solid bands examined, only 39 peaks have widths <5 cm−1. For both the liquid and solid bands, a skewed distribution of peak widths was observed: For liquids, the mean peak width was 24.7 cm−1 but the median peak width was 13.7 cm−1, and, similarly, for solids, the mean peak width was 22.2 cm−1 but the median peak width was 11.2 cm−1. While recognizing other studies may differ in scope and limiting the analysis to only room temperature data, we have found that a resolution to resolve 95% of all bands is 5.7 cm−1 for liquids and 5.3 cm−1 for solids; such a resolution would capture the native linewidth (not accounting for instrumental broadening) for 95% of all the solids and liquid bands, respectively. After decades of measuring liquids and solids at 4, 8, or 16 cm−1 resolution, we suggest that, when accounting only for intrinsic linewidths, an optimized resolution of 6.0 cm−1 will capture 91% of all condensed-phase bands, i.e., broadening of only 9% of the narrowest of bands, but yielding a large gain in signal-to-noise with minimal loss of specificity. [ABSTRACT FROM AUTHOR]

The uncertainty in estimating the wave spectrum from the records of wave elevation by heave–pitch–roll buoys is studied, considering the effects of the estimation method and the spectral resolution adopted in the process. This investigation utilizes measurements from a wave buoy moored in deep water in the South Atlantic Ocean. First, the spectra are computed using the autocorrelation function and the direct Fourier method. Second, the spectral resolution is tested in terms of degrees of freedom. The degrees of freedom are varied, and the resulting spectra and integrated parameters are computed, showing significant variability. A simple and robust methodology for determining the wave spectrum is suggested, which involves calculating the average energy density in each frequency band. The results of this methodology reduce the variability of the estimated parameters, improving overall accuracy while preserving frequency resolution, which is crucial in complex sea states. Additionally, to demonstrate the feasibility of the implemented approach, the final spectrum is fitted using an empirical model ideal for that type of spectrum. Finally, the performance and the goodness of the fit process for the final averaged curve are checked by widely used statistical metrics, such as R2 = 0.97 and root mean square error = 0.49.

Objective: Cochlear implantation of prelingually deaf infants provides auditory input sufficient to develop spoken language; however, outcomes remain variable. Inability to participate in speech perception testing limits testing device efficacy in young listeners. In postlingually implanted adults (aCI), speech perception correlates with spectral resolution an ability that relies independently on frequency resolution (FR) and spectral modulation sensitivity (SMS). The correlation of spectral resolution to speech perception is unknown in prelingually implanted children (cCI). In this study, FR and SMS were measured using a spectral ripple discrimination (SRD) task and were correlated with vowel and consonant identification. It was hypothesized that prelingually deaf cCI would show immature SMS relative to postlingually deaf aCI and that FR would correlate with speech identification. Study Design: Cross‐sectional study. Setting: In‐person, booth testing. Methods: SRD was used to determine the highest spectral ripple density perceived at various modulation depths. FR and SMS were derived from spectral modulation transfer functions. Vowel and consonant identification was measured; SRD performance and speech identification were analyzed for correlation. Results: Fifteen prelingually implanted cCI and 13 postlingually implanted aCI were included. FR and SMS were similar between cCI and aCI. Better FR was associated with better speech identification for most measures. Conclusion: Prelingually implanted cCI demonstrated adult‐like FR and SMS; additionally, FR correlated with speech identification. FR may be a measure of CI efficacy in young listeners. [ABSTRACT FROM AUTHOR]

Dispersive Fourier transform (DFT) has emerged as a powerful technique, enabling the transformation of spectral information from an optical pulse into a temporal waveform. This advancement facilitates the implementation of absorption spectroscopy using a single-pixel photodetector and a pulsed laser, particularly effective when operating on wavelengths near the absorption lines of the gas under study. This paper introduces a DFT-spectrometer employing a mode-locked tunable fiber laser with the central wavelength of 1531.6 nm. We demonstrate fast acquisition NH 3 absorption spectroscopy with a 0.2 nm spectral resolution, achieved through the utilization of the HITRAN database for estimating ammonia concentrations. Alongside the successful demonstration of NH 3 absorption spectroscopy, we explore practical limiting factors influencing the system's performance. Furthermore, we discuss potential avenues for enhancing sensitivity and spectral resolution, aiming to enable more robust and accurate gas sensing applications. [ABSTRACT FROM AUTHOR]

The intensity ratio (αI) and area ratio (αA) obtained using Raman spectroscopy are used widely to characterize the physical properties of gases, fluids, and solids, but the underlying parameters which affect their precision (σαI and σαA) have not been elucidated. We use simulations, experiments, and theoretical analyses to investigate the effects of instrumental performance, analytical conditions, and sample size on σαI and σαA. We identified the parameters which strongly influence σαI: (1) the weaker peak intensity Iw; (2) the ratio of the bandwidth to pixel resolution of the weaker peak Γw/Δxw; (3) the degree of detector saturation; (4) σD2+σR2/σS2 with readout noise σR, dark noise σD, and shot noise σS; (5) drift; and (6) sample size. Theoretical and simulation results show that, when Γw/Δxw ≪ (Γs/Δxs)/αI, increasing Iw or Γw/Δxw by n times can improve σαI by a factor of n. Results showed that σD2+σR2/σS2 is a measure of how much the achievable σαI in the experiment differs from that under ideal analytical conditions (i.e., σD2+σR2≪σS2). When σD2+σR2≪σS2 is not the case (i.e., when Iw is low), reducing σD or σR by decreasing the readout speed, setting a lower charge coupled device (CCD) sensitivity, reducing number of readouts, or narrowing vertical binning width can improve σαI. We demonstrated that evaluations of σαI or σαA based on small sample sizes can engender physically unattainable precision. When the sample size is n = 5, 10, or 20, the average uncertainties of σαI and σαA correspond, respectively, to approximately 30%, 20%, and 15%. Giving an accurate and comparable assessment for σαI and σαA necessitates the reporting of intensity (in units of electrons), bandwidth, Δx, and the sample size. [ABSTRACT FROM AUTHOR]

Satellite sensors like Landsat 8 OLI (L8) and Sentinel-2 MSI (S2) provide valuable multispectral Earth observations that differ in spatial resolution and spectral bands, limiting synergistic use. L8 has a 30 m resolution and a lower revisit frequency, while S2 offers up to a 10 m resolution and more spectral bands, such as red edge bands. Translating observations from L8 to S2 can increase data availability by combining their images to leverage the unique strengths of each product. In this study, a conditional generative adversarial network (CGAN) is developed to perform sensor-specific domain translation focused on green, near-infrared (NIR), and red edge bands. The models were trained on the pairs of co-located L8-S2 imagery from multiple locations. The CGAN aims to downscale 30 m L8 bands to 10 m S2-like green and 20 m S2-like NIR and red edge bands. Two translation methodologies are employed—direct single-step translation from L8 to S2 and indirect multistep translation. The direct approach involves predicting the S2-like bands in a single step from L8 bands. The multistep approach uses two steps—the initial model predicts the corresponding S2-like band that is available in L8, and then the final model predicts the unavailable S2-like red edge bands from the S2-like band predicted in the first step. Quantitative evaluation reveals that both approaches result in lower spectral distortion and higher spatial correlation compared to native L8 bands. Qualitative analysis supports the superior fidelity and robustness achieved through multistep translation. By translating L8 bands to higher spatial and spectral S2-like imagery, this work increases data availability for improved earth monitoring. The results validate CGANs for cross-sensor domain adaptation and provide a reusable computational framework for satellite image translation. [ABSTRACT FROM AUTHOR]

Purpose: Our study aims to compare speech understanding in noise and spectral- temporal resolution skills with regard to the degree of hearing loss, age, hearing aid use experience and gender of hearing aid users. Methods: Our study included sixty-eight hearing aid users aged between 40-70 years, with bilateral mild and moderate symmetrical sensorineural hearing loss. Random gap detection test, Turkish matrix test and spectral-temporally modulated ripple test were implemented on the participants with bilateral hearing aids. The test results acquired were compared statistically according to different variables and the correlations were examined. Results: No statistically significant differences were observed for speech-in-noise recognition, spectral-temporal resolution among older and younger adults in hearing aid users (p>0.05). There wasn’t found a statistically significant difference among test outcomes as regards different hearing loss degrees (p>0.05). Higher performances were obtained in terms of temporal resolution in male participants and participants with more hearing aid use experience (p

Multispectral imaging technology has advanced significantly in recent years, allowing single-sensor cameras with multispectral filter arrays to be used in new scene acquisition applications. Our camera, developed as part of the European CAVIAR project, uses an eight-band MSFA to produce mosaic images that can be decomposed into eight sparse images. These sparse images contain only pixels with similar spectral properties and null pixels. A demosaicing process is then applied to obtain fully defined images. However, this process faces several challenges in rendering fine details, abrupt transitions, and textured regions due to the large number of null pixels in the sparse images. Therefore, we propose a sparse image composition method to overcome these challenges by reducing the number of null pixels in the sparse images. To achieve this, we increase the number of snapshots by simultaneously introducing a spatial displacement of the sensor by one to three pixels on the horizontal and/or vertical axes. The set of snapshots acquired provides a multitude of mosaics representing the same scene with a redistribution of pixels. The sparse images from the different mosaics are added together to get new composite sparse images in which the number of null pixels is reduced. A bilinear demosaicing approach is applied to the composite sparse images to obtain fully defined images. Experimental results on images projected onto the response of our MSFA filter show that our composition method significantly improves image spatial resolution and minimizes reconstruction errors while preserving spectral fidelity.

Recently, considerable efforts have been devoted to the estimation of soil properties using optical payloads mounted on drones or satellites. Nevertheless, many studies focus on diverse pretreatments and modeling techniques, while there continues to be a conspicuous absence of research examining the impact of parameters related to optical remote sensing payloads on predictive performance. The main aim of this study is to evaluate how the spectral resolution and signal-to-noise ratio (SNR) of spectrometers affect the precision of predictions for soil organic matter (SOM) content. For this purpose, the initial soil spectral library was partitioned into to two simulated soil spectral libraries, each of which were individually adjusted with respect to the spectral resolutions and SNR levels. To verify the consistency and generality of our results, we employed four multiple regression models to develop multivariate calibration models. Subsequently, in order to determine the minimum spectral resolution and SNR level without significantly affecting the prediction accuracy, we conducted ANOVA tests on the RMSE and R 2 obtained from the independent validation dataset. Our results revealed that (i) the factors significantly affecting SOM prediction performance, in descending order of magnitude, were the SNR levels > spectral resolutions > estimation models, (ii) no substantial difference existed in predictive performance when the spectral resolution fell within 100 nm, and (iii) when the SNR levels exceeded 15%, altering them did not notably affect the SOM predictive performance. This study is expected to provide valuable insights for the design of future optical remote sensing payloads aimed at monitoring large-scale SOM dynamics. [ABSTRACT FROM AUTHOR]

As spectral resolution increases, the dimension of the Doppler Asymmetric Spatial Heterodyne (DASH) interferometer increases. The existing approach for stably mounting the interferometer is limited to mounting a normal-sized DASH interferometer. In this study, a novel and stable structure is proposed, with its effecti1veness exemplified for a near-infrared (NIR) DASH interferometer. The mathematical model of a flexible structure was established. The parameters of the support structure were optimized by requiring the mechanical stress of the flexible structure and shear stress at the bonding surface to be less than the strength value. The spring constants were optimally designed to adjust natural frequency and minimize stress. The finite element analysis (FEA) results show that the maximum mechanical stress was 65.56 MPa. The maximum shear stress was 3.4 MPa. All stress values had a high safety margin. The mechanical material and adhesive area were optimally designed. Therefore, the thermal resistance of the structure was improved by 7.5 times. The test results indicate that the proposed flexible support structure could satisfy the requirements of the launch environment. The results from FEA and vibration tests were consistent with the model calculation results. Compared to existing structures, the mechanical performance and thermal resistance were improved. [ABSTRACT FROM AUTHOR]

We theoretically investigate the feasibility of using a fiber laser source for high resolution and broadband coherent Raman scattering (CRS) spectroscopy/imaging employing spectral focusing technique. To accomplish this task, we have developed a simulation tool where the laser pulse parameters can be imported directly from any pulse propagation software using split‐step Fourier method to evaluate the spectral resolution and spectral coverage of CRS spectroscopy. Thus, the simulation tool can accommodate optical pulses of arbitrary shape and central wavelength, being also a user‐friendly and versatile open‐source software. We validate the numerical simulation tool by comparing its results with published theoretical and experimental data. We then use the tool to study the feasibility of using an all‐fiber laser source for high resolution CRS spectroscopy in both the C‐H window and the fingerprint region. This tool has a broad scope of applications in multiple fields where CRS spectroscopy is useful such as biomedicine, materials characterization, and biological imaging. [ABSTRACT FROM AUTHOR]

The advancement of ultra-hyperspectral imaging technology, exemplified by the AisaIBIS sensor, has enabled a leap from hyperspectral data (hundreds of bands) to ultra-hyperspectral data (thousands of bands). It provides immense potential for precise ground object recognition within intricate scenes. However, the complexities inherent to features of the ground objects, coupled with the copious redundant information within the ultra-hyperspectral data, pose substantial challenges for accurate object recognition. Therefore, this paper proposed a comprehensive framework to explore the optimal precise classification strategy of ultra-hyperspectral data in complex scenes (12 vegetation and non-vegetation classes). (a) Our investigation delves into the influence of diverse feature subsets and a range of machine learning classifiers on the precision of ground objects recognition. The proposed strategy is up to an overall accuracy of 88.44%, effectively avoiding the curse of dimension, and significantly enhancing the capability to recognize the complex ground objects. (b) Furthermore, based on the simulation of hyperspectral images with different spectral resolutions, we compared the classification results of ultra-hyperspectral data (0.11 nm) and the hyperspectral datasets (10 nm, 5 nm, and 1 nm) by machine learning methods. Compared with the hyperspectral datasets, ultra-hyperspectral data improved the classification accuracy by 5.30–6.38%. This substantiates the pronounced advantages of ultra-hyperspectral data in precision land cover classification. This study provides a valuable reference for the application of ultra-hyperspectral data in recognition of complex ground objects scenes, and urban accurate monitoring. [ABSTRACT FROM AUTHOR]

In a Fourier transform infrared (IR) spectrometer, the Michelson interference signal extrapolation method based on linear prediction is often used to improve spectral resolution. In this method, an autoregressive (AR) model is established for the Michelson interference signal in the spectrometer. Once the AR model parameters are determined, the AR process is predictable. The interference signal can be used to figure out the AR model's parameters. Based on this, the AR model can be used to extrapolate the interference signal to improve the spectral resolution. In this paper, the forward–backward linear prediction total least squares (FB-TLS) method is proposed to estimate the parameters of the AR model. The parameters that are estimated are used to improve the IR spectral resolution. By simulating different order and signal-to-noise ratio situations, the effects of the Burg, the least square, and the FB-TLS parameter estimation methods on spectral resolution enhancement are studied. The simulation results demonstrate that the FB-TLS parameter estimation method can effectively suppress noise and avoid spurious peaks. The experimental results demonstrate that the FB-TLS parameter estimation method is effective for spectral resolution enhancement technology based on linear prediction. When the FB-TLS method is used to enhance NH3 IR spectral resolution from 2 cm−1 to 1 cm−1, the spectral prediction error in the NH3 characteristic band is only 0.21% compared with the measured NH3 spectrum, whose spectral resolution is 1 cm−1. Graphical Abstract This is a visual representation of the abstract. [ABSTRACT FROM AUTHOR]

Modern deterministic polishing processes allow fabrication of x-ray optics with almost any arbitrary aspherical surface shape. Among these optics, the so called "diaboloid"mirror is of special interest. The diaboloid mirror that converts a cylindrical wave to a spherical wave would improve focusing in x-ray beamlines implementing a diffraction element between a parabolic cylinder and a toroidal mirror. The replacement of the toroidal mirror in existing beamlines by the diaboloid mirror would mitigate aberrations. The shape of the diaboloid mirror is usually calculated numerically based on a truncated polynomial solution of the optical path problem. Here, we present an exact analytical solution for the shape of a diaboloid mirror as a function of the conjugate parameters of the mirror placed in a beamline. The derived analytical expressions for the diaboloid mirror in both the canonical and mirror-based coordinate systems are implemented in ray-tracing simulations to verify the beamline performances.

In the field of hyperspectral and multispectral (HS–MS) image fusion, convolutional neural network (CNN) has achieved promising performance. Nevertheless, most networks cannot fully extract the spatial–spectral features from 3-D HS–MS images via vanilla convolution. 3-D-CNN, treating the spatial and spectral dimension at the same weight maybe a solution to this problem. However, this approach ignores the distinctiveness of spatial–spectral features and suffers from high computational complexity. To meet these challenges, a novel architecture called four-stream network (FS-Net) is proposed, which integrates the spatial–spectral feature extraction, and multiscale and multilevel feature fusion into a united framework. First, the simple but effective 2-D spatial feature extractor and spectral feature extractor are designed, which encode the spatial and spectral features of HS–MS images into four groups of feature maps. Next, these four groups of feature maps are fused in pairs, where the output can be seen as the comprehensive representation of input images. Finally, multilevel and multiscale feature fusion strategies helps to recover the HS image at high-spatial-resolution, and thus, simultaneously capture the detail texture and contextual information of the different and complex ground objects. Extensive experiments were conducted on three datasets with various experimental configurations to demonstrate that the proposed FS-Net achieves superior results quantitatively and visually when compared with the state-of-the-art networks.

For convex and sequential effect algebras, we study spectrality in the sense of Foulis. We show that under additional conditions (strong archimedeanity, closedness in norm and a certain monotonicity property of the sequential product), such effect algebra is spectral if and only if every maximal commutative subalgebra is monotone σ -complete. Two previous results on existence of spectral resolutions in this setting are shown to require stronger assumptions. [ABSTRACT FROM AUTHOR]

Open-path Fourier Transform infrared spectroscopy (OP-FTIR) is widely used in polluted gas monitoring. The spectral resolution, as a key parameter of FTIR detection technology, affects the quantitative analysis of gas concentration. In OP-FTIR, the nonlinear least square (NLLS) method based on a synthetic background spectrum is used to quantitatively analyze the gas concentration, and the influence of the spectral resolution is studied. It is found that the influence of the spectral resolution on quantitative gas analysis is related to the full width at half maximum (FWHM) of the gas spectrum. The concentration of gases with different spectral FWHMs were quantitatively analyzed using infrared spectra with different resolutions (1, 2, 4, 8, 16 cm−1). The experimental results show that the relatively optimal spectral resolution for propane (C3H8) with a broad FWHM is 16 cm−1, where the standard deviation is 0.661 and the Allan deviation is only 0.015; the relatively optimal spectral resolution for ethylene (C2H4) with a narrow FWHM is 1 cm−1, where the standard deviation is 0.492 and the Allan deviation is only 0.256. Therefore, for the NLLS quantitative analysis method based on the synthetic background spectrum, which is used in OP-FTIR, gas with a narrow FWHM at high resolutions or gas with a broad FWHM at low resolutions is most effective for performing quantitative analyses. [ABSTRACT FROM AUTHOR]

Dispersive Fourier transform (DFT) has emerged as a powerful technique, enabling the transformation of spectral information from an optical pulse into a temporal waveform. This advancement facilitates the implementation of absorption spectroscopy using a single-pixel photodetector and a pulsed laser, particularly effective when operating on wavelengths near the absorption lines of the gas under study. This paper introduces a DFT-spectrometer employing a mode-locked tunable fiber laser with the central wavelength of 1531.6 nm. We demonstrate fast acquisition NH3 absorption spectroscopy with a 0.2 nm spectral resolution, achieved through the utilization of the HITRAN database for estimating ammonia concentrations. Alongside the successful demonstration of NH3 absorption spectroscopy, we explore practical limiting factors influencing the system’s performance. Furthermore, we discuss potential avenues for enhancing sensitivity and spectral resolution, aiming to enable more robust and accurate gas sensing applications.

Aerosol vertical distribution is decisive and hard to be constrained. It is of great significance for the study of atmospheric climate and environment. Oxygen absorption A-bands (755–775 nm) provide a unique opportunity to acquire vertical aerosol profiles from satellites over a large spatial coverage. To investigate the ability of O2 A-bands in retrieving aerosol vertical distribution, the dependence of retrieval on satellite observation geometry, spectral resolution, signal-to-noise ratio (SNR), size distribution, and a priori knowledge is quantified using information content theory. This work uses the radiative transfer model UNL to simulate four aerosol modes and the instrument noise model. The simulations show that a small scattering angle leads to an increase in the total amount of observed aerosol profile information, with the degrees freedom of signal (DFS) of a single band increasing from 0.4 to 0.85 at high spectral resolution (0.01 nm). The total DFS value of O2 A-bands varies accordingly between 1.2–2.3 to 3.8–5.1 when the spectral resolution increases from 1 nm to 0.01 nm. The spectral resolution has a greater impact on DFS value than the impact from SNR (an improvement of roughly 41–53% resulted from the change in spectral resolution and the SNR led to 13–18%). The retrieval is more sensitive to aerosols with a coarse-dominated mode. The improvement in spectral resolution on information acquisition is demonstrated using the DFS and the posterior error at various previous errors and resolutions. [ABSTRACT FROM AUTHOR]

Abstract The study adopts a number of soil salinity indices by applying geoinformatics techniques in the northeast of the Nile River Delta, based on the different spectral reflectance of soil salinity. The field investigation is carried out by collecting soil samples, and chemically analyzing them in order to compare them with the results of the indices (8 indices), relying on field review so as to capture images indicative of soil salinity and its impact on the land use that is most vulnerable to it, and this is vegetation. This is mainly for the sake of supporting the accuracy of the spectral resolution. It is found that each index relies on different variables of spectral reflectance. Accordingly, the study identifies the most appropriate and effective indices for assessing salinity, both spatially and temporally, in the northeast of the Nile River Delta. This is done through determining the highest degree of correlation between the results of the indices and the results of the chemical analysis of soil samples. Moreover, the study relies on the best indices in determining vegetation, which is EVI, so as to find out the degree to which the vegetation density is affected by soil salinity. This is carried out with the aim of coming up with results that help decision-makers in addressing the problems resulting from soil salinity with the least effort, the lowest cost, and the highest accuracy and realism. المستخلص باللغة العربية اعتمدت الدراسة عدد من أدلة ملوحة التربة عن طريق تطبيق تقنيات الجيوانفورماتيکس شمال شرق دلتا نهر النيل، مستندة على الانعکاسات الطيفية المختلفة لملوحة التربة. وتم التحقق الميداني عن طريق تجميع عينات من التربة وتحليلها کيميائياً، بغرض مقارنتها بنتائج الأدلة (8 مؤشرات)، مع الاعتماد على المراجعة الحقلية لالتقاط الصور المعبرة عن ملوحة التربة وأثارها على أکثر استخدامات الأرض حساسية لها وهو الغطاء النباتي، وذلک لتدعيم دقة التمييز الطيفي. وقد تبين أن کل مؤشر يعتمد على متغيرات مختلفة من الانعکاسات الطيفية، ومن ثم لجأت الدراسة إلى تحديد أفضل المؤشرات المناسبة والفعالة في تقييم الملوحة زمانياً ومکانياً شمال شرق دلتا النيل، وذلک عن طريق تحديد أعلى درجة ارتباط بين نتائج المؤشرات ونتائج التحليل الکيميائي لعينات التربة، کما اعتمدت الدراسة على أفضل المؤشرات في تحديد الغطاء النباتي وهوEVI لمعرفة درجة تأثر کثافة الغطاء النباتي بملوحة التربة، وذلک بهدف الخروج بنتائج تساعد صناع القرار في معالجة المشاکل الناتجة عن ملوحة التربة بأقل جهد وأقل تکلفة وتکون أکثر دقة وواقعية.

As spectral resolution increases, the dimension of the Doppler Asymmetric Spatial Heterodyne (DASH) interferometer increases. The existing approach for stably mounting the interferometer is limited to mounting a normal-sized DASH interferometer. In this study, a novel and stable structure is proposed, with its effecti1veness exemplified for a near-infrared (NIR) DASH interferometer. The mathematical model of a flexible structure was established. The parameters of the support structure were optimized by requiring the mechanical stress of the flexible structure and shear stress at the bonding surface to be less than the strength value. The spring constants were optimally designed to adjust natural frequency and minimize stress. The finite element analysis (FEA) results show that the maximum mechanical stress was 65.56 MPa. The maximum shear stress was 3.4 MPa. All stress values had a high safety margin. The mechanical material and adhesive area were optimally designed. Therefore, the thermal resistance of the structure was improved by 7.5 times. The test results indicate that the proposed flexible support structure could satisfy the requirements of the launch environment. The results from FEA and vibration tests were consistent with the model calculation results. Compared to existing structures, the mechanical performance and thermal resistance were improved.

Imaging spectrometers in a geostationary orbit have unique advantages for various applications ranging from atmospheric to ocean remote sensing. To increase remote sensing range, we developed an ultrawide FOV LWIR imaging spectrometer. We compared several spectrometers and picked the "Offner + center single prism" form, which can simplify the system structure and increase cryogenic adaptability, making it ideal for ultrawide FOV designs. However, to reduce background radiation in LWIR bands, the imaging spectrometer was cooled to 123 K, causing the image plane to deviate from the focal plane. Therefore, we propose a cryogenic refocusing method based on an inclined slit in this paper that employs the full width half maximum (FWHM) of the spectral response function (SRF) as the refocusing evaluation function. By analyzing the effect of deviation on FWHM, the refocusing principle is well explained. The slit is tilted to find the minimal function value, so the deviation amount is calculated using differences in FOVs corresponding to the minimum FWHM at different temperatures. Experiments show that the FWHM is nearly 2.1 pixels after refocusing and that the actual spectral resolution is within 120 nm after spectral calibration. The method reduced the design time and provided references for optical systems experiencing refocusing issues in remote sensing imaging. [ABSTRACT FROM AUTHOR]

Convex blazed gratings, which can effectively broaden the spectral range and improve spectral resolution, have gradually evolved into a crucial optical component for lightweight and compact imaging spectroscopy instruments. Their design, processing, and testing involve multidisciplinary interdisciplinary scientific issues, and they continue to be a major area of research in imaging optics applications. This paper summarizes the effects of various grating groove shapes and structural parameters on the spectral range and diffraction efficiency of convex blazed gratings, after providing a brief introduction to the typical functions and applications of convex blazed gratings. Firstly, the latest progress in typical processing methods for convex blazed gratings is reviewed. It focuses on the current fabrication processes and reviews their capabilities in creating convex blazed gratings from three main types of technologies, namely ultra-precision machining, high-energy density beam processing, and chemically assisted fabrication processes. Secondly, the adaptability of the manufacturing process for convex blazed gratings on different scales is summarized, analyzing the adaptation of current procedures to various grating fabrication scales and their bottlenecks. Finally, the characterization methods and future feasible characterization methods for convex blazed gratings are reviewed. The development trend of efficient and precise preparation of convex blazed gratings is pointed out. [ABSTRACT FROM AUTHOR]

In this study, we propose a method of evaluating the spectral resolution of crossed-asymmetric Czerny-Turner spectrometers by comparing the impact of different slit functions on the optical transfer function, and different slit widths, through simulation and experiments. The results show that, the Gaussian function is suitable for narrower slit widths, such as 25 μm, and the rectangle function or convolution of slit-scattering function with rectangle function is suitable for wider slit widths, such as 50 μm, 150 μm, and 200 μm. The proposed method can provide guidance in the evaluation of spectral resolution in the preliminary optical design process of spectrometers. [ABSTRACT FROM AUTHOR]

A block of an effect algebra is a maximal sub-effect algebra with some kind of compatibility property. Jenča (Australian Math. Soc. 64, 81–98, 2001), shows that every block of a homogeneous effect algebra satisfies the Riesz Decomposition Property (RDP). We establish that in a monotone σ -complete effect algebra, every block is a monotone σ -complete sub-effect algebra with (RDP). This result is used to show a one-to-one relationship between observables and spectral resolutions, as well as for n-dimensional observables and n-dimensional spectral resolutions. This result extends the class of effect algebras where this relationship holds. [ABSTRACT FROM AUTHOR]

A soft- and hardware platform is described for supporting the operation of spectral analysis devices and systems based on tunable semiconductor lasers. The wide spectral range covered by lasers of this type and the versatility of methods for controlling their spectral parameters make it possible to solve various problems within the framework of a single instrumental approach. This includes the most complex tasks of spectral analysis of multicomponent gas mixtures including atmospheric and exhaled air. Main areas of the platform application include IR molecular spectroscopy, chemical technologies, atmospheric pollution control, diagnostics of low-temperature plasma components, biomedical diagnostics. [ABSTRACT FROM AUTHOR]

Image fusion effectively solves the trade-off among spatial resolution, temporal resolution, and spectral resolution of remote sensing sensors. However, most of existing methods focus on the fusion of two of the spatial, temporal, and spectral metrics of remote sensing images. The few spatial–temporal–spectral fusion (STSF) methods available are mainly for fusing Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat images, which are not suitable for the characteristics of the spaceborne hyperspectral images (HSIs) with low temporal resolution, such as Hyperion, ZY-1 02D, and PRISMA. For this purpose, we proposed a novel generalized linear spectral mixing model for STSF (GLMM-STSF). In the method, the GLMM is introduced into the STSF problem, and the temporal variations of images at different times are transferred to the endmember and abundance matrix variations of images for estimation. To the best of our knowledge, for the first time, the STSF task of remote sensing images is handled from the perspective of spectral unmixing. Compared with the existing STSF fusion methods, our method targets the task of fusing spaceborne HSI with low temporal and spatial resolutions with multispectral image (MSI) featured by high temporal and spatial resolutions. Taking the STSF of ZY-1 02D hyperspectral and Sentinel-2 multispectral real datasets as an example, comparisons with related state-of-the-art methods demonstrate that our proposed method achieves superior fusion performance. [ABSTRACT FROM AUTHOR]

Since scanners became a common tool in architecture schools around ten years ago, the tendency has been to record what is there in the built environment in an attempt to discover the interrelationships between spaces obscured by the materiality of building. However, architects are now starting to speculate using these new technologies. Founding member of architecture firms Brrum and servo stockholm, and Professor of Architecture at the KTH School of Architecture, Stockholm, Ulrika Karlsson investigates this through the work conducted by Michael Young, co‐founder of New York‐based practice Young & Ayata. [ABSTRACT FROM AUTHOR]

Spectral analysis is successfully adopted in several fields. However, the requirements and the constraints of the different cases may be so varied that not only the tuning of the analysis parameters but also the choice of the most suitable technique can be a difficult task. For this reason, it is important that a designer of a measurement system for spectral analysis has knowledge about the behaviour of the different techniques with respect to the operating conditions. The case that will be considered is the realization of a numerical instrument for the real-time measurement of the spectral characteristics of a multi-tone signal (amplitude, frequency, and phase). For this purpose, different signal processing techniques can be used, that can be classified as parametric or non-parametric methods. The first class includes those methods that exploit the a priori knowledge about signal parameters, such as the spectral shape of the signal to be processed. Thus, a self-configuring procedure based on a parametric algorithm should include a preliminary evaluation of the number of components. The choice of the right method among several proposals in the literature is fundamental for any designer and, in particular, for the developers of spectral analysis software, for real-time applications and embedded devices where time and reliability constrains are arduous to fulfil. Different aspects should be considered: the desired level of accuracy, the available elaboration resources (memory depth and processing speed), and the signal parameters. The present paper details a comparison of some of the most effective methods available in the literature for the spectral analysis of signals (IFFT-2p, IFFT-3p, and IFFTc, all based on the use of an FFT algorithm, while improving the spectral resolution of the DFT with interpolation techniques and three parametric algorithms—MUSIC, ESPRIT, and IWPA). The methods considered for the comparison will be briefly described, and references to literature will be given for each one of them. Then, their behaviour will be analysed in terms of systematic contribution and uncertainty on the evaluated frequencies of the spectral tones of signals created from superimposed sinusoids and white Gaussian noise. [ABSTRACT FROM AUTHOR]

In this study, an airborne alpha detection system, which consists of a passivated implanted planar silicon (PIPS) detector and an air filter, was developed. A collimator applied to the alpha detection system showed an enhancement in resolution and a degradation in detection efficiency. The resolution and detection efficiency were compared and analyzed to evaluate the performance of the collimator. Thus, the resolution was found to be more important than the efficiency as a determining factor of the detection system performance, from the viewpoint of radionuclide identification. The performance was evaluated on three properties of the collimator: hole shape, hole length, and the ratio between the hole and frame pitches. From the hole shape performance evaluation, a hexagonal collimator showed the highest resolution. Further, the collimator with a hole pitch of 14 mm was found to have the highest resolution while that with a frame pitch of 4–6 mm (i.e., 1.2–1.4 times longer than the hole pitch) showed the highest resolution.

A method to accurately measure the linewidth of short laser pulses at a low repetition rate is demonstrated. Based on the principle of parallel plate equal inclination interference, the linewidth of a short-pulse laser with a low repetition rate is measured by using a Fabry-Pérot (F-P) etalon combined with a CMOS beam profiler. The center of the recorded interference pattern is precisely identified using Hough transformation, and a pixel rotation algorithm is applied to maximise the data collected, transforming two-dimensional image information into one-dimensional spectral information. This algorithm significantly increases the number of data points, improves the spectral resolution, and reduces the error caused by the size of the CMOS pixel size to less than 1 MHz. The influence of the transmission spectrum width (TSW) of the F-P etalon on the measurement results is analyzed, and we demonstrate a reduction in the error introduced by the TSW of the F-P etalon is through deconvolution. This further improves the measurement quality and provides a means by which etalons with a wide TSW can be applied to the measurement of the linewidth of lasers with low pulse energy.

Background Identifying and understanding speech is difficult for individuals with sensorineural hearing loss, especially in noisy environments. Possible causes include less audibility of the signal, impaired temporal resolution, and low selectivity of frequency. The hearing aid is the most common option used to minimize the problems faced by individuals with sensorineural hearing loss. Purpose This article investigates the effects of multichannel and channel-free hearing aid signal processing techniques on spectral-temporal resolution and speech understanding in noise. Research Design An experimental study was used in which the determined tests were applied to the participants. Study Sample Thirty-four individuals with bilateral symmetrical sensorineural hearing loss between the ages of 18 and 70 were included in our study. Data Collection and Analysis Spectral-temporally modulated ripple test, random gap detection test (RGDT), and Turkish matrix test were applied to the participants using multichannel and channel-free hearing aids. All the data obtained were compared statistically in terms of the performances of the hearing aids. Results There was no significant difference between multichannel and channel-free hearing aids for spectral resolution and speech understanding in noise tests (p > 0.05). While there was no significant difference between the two hearing aids for 500 and 4,000 Hz RGDT in temporal resolution measurement (p > 0.05), for 1,000 Hz (p = 0.045), 2,000 Hz (p = 0.046), and composite RGDT (p = 0.001), statistically significant better performances were obtained with the channel-free hearing aids. Conclusion It is thought that faster processing of the incoming signal in the channel-free hearing aids improves the temporal resolution performance. It is predicted that our study findings might help to determine the signal processing technique that will maximize the communication skills of the patients in various conditions. [ABSTRACT FROM AUTHOR]