Spectral Peaks Research Articles

Optimization of stacked Fabry-Perot cavities for VO2-based broadband adaptive thermal radiators

The performance of an adaptive thermal radiator (ATR) for temperature regulation depends on its ability to modulate spectral emissivity across a broad wavelength range. For a single cavity, we found that the tunable, thermal emissivity from 2-30 µm is maximized using a spacer material with low n and k, such as BaF2 . However, a single cavity produces a narrowband peak in the spectral emissivity. Stacking multiple cavities introduces additional resonances that create high-temperature spectral emissivity peaks. Here, we designed cavities composed of VO2 and BaF2 to have different resonant wavelengths to demonstrate a broadband response across the infrared spectrum out to ∼30 µm. In this work, we find that up to three cavities increases the tunable thermal emissivity with negligible changes from additional cavities.

Programmable spectral peak generation by a mode-locked Er-fiber laser with an intracavity LCOS-SLM filter.

Applying intracavity spectral phase and/or intensity modulation to a mode-locked laser can control the state of circulating pulses in the cavity and produce unique and useful pulse outputs. In this study, a mode-locked Er-doped fiber laser with an intracavity high-resolution liquid crystal-on-silicon spatial light modulator (LCOS-SLM) spectral filter was developed, and programmable narrow linewidth spectral peak generation directly from the oscillator was demonstrated. Furthermore, by simultaneously controlling the intracavity group delay dispersion (GDD), the generation of 20 spectral peaks with a linewidth of 100 pm over a bandwidth of 17 nm was demonstrated. Spectral modulation also affects the temporal waveform, and burst-like pulse trains with intra-burst repetition rates up to 252 GHz were observed.

Spectra of solar shallow-water waves from bright point observations

Rossby waves, large-scale meandering patterns drifting in longitude, detected in the Sun, were recently shown to a play a crucial role in understanding “seasons” of space weather. Unlike Earth's purely classical atmospheric Rossby waves, the solar counterparts are strongly magnetized and most likely originate in the tachocline. Because of their deeper origin, detecting these magnetized Rossby waves is a challenging task that relies on careful observations of long-lived longitudinally drifting magnetic patterns at the surface and above. Here, we have utilized 3 years of global, synchronous observations of coronal bright point densities to obtain empirical signatures of dispersion relations that can be attributed to the simulated waves in the tachocline. By tracking the bright point densities at selected latitudes, we computed their wave-numbertimes frequency spectra. Wave-numbertimes frequency spectra were computed utilizing the Wheeler-Kiladis method. This method has been extensively used in the identification of equatorial waves in Earth's atmosphere by highlighting spectral peaks in the wave-numbertimes frequency space. Our results are compatible with the predictions of magneto-Rossby waves with typical periods of several months and inertio-gravity waves with typical periods of a few weeks, depending on the background magnetic field's strength and stratification at the convection zone base. Our analysis suggests that magnetized Rossby waves originate from the tachocline toroidal field of lesssim 15 kG. Global observations of bright points over extended periods will allow us to better constrain the stratification and magnetic field strength in the tachocline.

Machine Learning-Assisted Surface-Enhanced Raman Spectroscopy Detection for Environmental Applications: A Review.

Surface-enhanced Raman spectroscopy (SERS) has gained significant attention for its ability to detect environmental contaminants with high sensitivity and specificity. The cost-effectiveness and potential portability of the technique further enhance its appeal for widespread application. However, challenges such as the management of voluminous quantities of high-dimensional data, its capacity to detect low-concentration targets in the presence of environmental interferents, and the navigation of the complex relationships arising from overlapping spectral peaks have emerged. In response, there is a growing trend toward the use of machine learning (ML) approaches that encompass multivariate tools for effective SERS data analysis. This comprehensive review delves into the detailed steps needed to be considered when applying ML techniques for SERS analysis. Additionally, we explored a range of environmental applications where different ML tools were integrated with SERS for the detection of pathogens and (in)organic pollutants in environmental samples. We sought to comprehend the intricate considerations and benefits associated with ML in these contexts. Additionally, the review explores the future potential of synergizing SERS with ML for real-world applications.

JPOST environment accelerates the reuse and reanalysis of public proteome mass spectrometry data.

jPOST (https://jpostdb.org/) comprises jPOSTrepo (https://repository.jpostdb.org/) (over 2000 projects), a repository for proteome mass spectrometry data, the reanalysis of raw proteome data based on a standardised protocol using UniScore, and jPOSTdb (https://globe.jpostdb.org/) (over 600 datasets), a database that integrates the reanalysed data. The jPOST reanalysis protocol rescores MS/MS spectra using a new scale, UniScore, to evaluate the extent to which the spectral peaks correspond to the amino acid sequences identified by search engines. However, the metadata registered in the repository database is insufficient for conducting the reanalysis. To address this issue, the Japanese Proteomics Society launched a data journal, the Journal of Proteome Data and Methods (JPDM), which accepts data descriptor articles detailing metadata that can be reanalysed. Within jPOST, raw proteome data is reanalysed based on the metadata described in the JPDM data descriptor articles, utilising UniScore. The reanalysed data is deposited in jPOSTdb, and a link to the JPDM articles is added to jPOSTrepo. These reanalysis accelerations within the jPOST environment will promote FAIR data principles and open science.

The Proteomics Standards Initiative Standardized Formats for Spectral Libraries and Fragment Ion Peak Annotations: mzSpecLib and mzPAF.

Mass spectral libraries are collections of reference spectra, usually associated with specific analytes from which the spectra were generated, that are used for further downstream analysis of new spectra. There are many different formats used for encoding spectral libraries, but none have undergone a standardization process to ensure broad applicability to many applications. As part of the Human Proteome Organization Proteomics Standards Initiative (PSI), we have developed a standardized format for encoding spectral libraries, called mzSpecLib (https://psidev.info/mzSpecLib). It is primarily a data model that flexibly encodes metadata about the library entries using the extensible PSI-MS controlled vocabulary and can be encoded in and converted between different serialization formats. We have also developed a standardized data model and serialization for fragment ion peak annotations, called mzPAF (https://psidev.info/mzPAF). It is defined as a separate standard, since it may be used for other applications besides spectral libraries. The mzSpecLib and mzPAF standards are compatible with existing PSI standards such as ProForma 2.0 and the Universal Spectrum Identifier. The mzSpecLib and mzPAF standards have been primarily defined for peptides in proteomics applications with basic small molecule support. They could be extended in the future to other fields that need to encode spectral libraries for nonpeptidic analytes.

Recursive-RARE-based three-dimensional parameter estimation of near-field source considering amplitude attenuation

This paper addresses the issue for near-field (NF) localization considering amplitude attenuation, proposing a recursive rank-reduction (RARE) method for three-dimensional (3-D) parameter estimation of NF sources incident on a symmetrical cross array. The proposed method constructs several one-dimensional (1-D) spectral peak search estimators to obtain two-dimensional angle and range parameters. Initially, using the received data from symmetrical array elements in one axis, a 1-D spectral peak search estimator is constructed. The origins of two types of pseudo peaks within this estimator are analyzed, and then, corresponding pseudo peaks removal methods, namely the initial screening method and the recursive RARE method, are presented to obtain the estimate of the first angle parameter. Subsequently, the estimated results are fed into another 1-D spectral peak search estimator constructed from the original received data to obtain the range parameter. Finally, the same process is applied to the other axis to obtain the second angle and range parameters, followed by a parameter matching operation for 3-D parameters. Compared to existing NF source localization methods, the proposed method more effectively eliminates pseudo peaks, and demonstrates superior parameter estimation performance under conditions of small number of snapshots and low signal-to-noise ratio, as validated by several simulation results.

Complexation of Trivalent Lanthanides with Hexaalkyl Nitrilotriacetamides into Methylimidazolium-Based Ionic Liquids: Spectroscopic, Electrochemical, Calorimetric, and Theoretical Insights.

Exothermic, spontaneous inner-sphere complexation of trivalent lanthanides with N,N,N',N',N″,N″-hexaalkyl-substituted nitrilotriacetamides (HRNTAs) into 1-hexyl-3-methylimidazolium-bis(trifluoromethylsulfonyl)imide (C6mim NTf2) is reported with a predominant presence of ML and ML2 complexes having complexation constants, β1Eu 3.10 ± 0.02 ,β1Nd 2.67 ± 0.03 and β2Eu 5.22 ± 0.04, β2Nd 4.95 ± 0.02, respectively, for the n-butyl-substituted HRNTA (HBNTA); while those for the n-hexyl derivative (HHNTA) are β1Eu 4.27 ± 0.03, β1Nd 3.71 ± 0.03 and β2Eu 7.70 ± 0.03, β2Nd 7.18 ± 0.04, respectively. HHNTA shows better complexing ability; whereas the stronger complexation of the Nd3+ over Eu3+ is attributed to the lanthanide contraction. Furthermore, the nature of the ionic liquid also influences the extent of complexation with the trend: C4mim NTf2 > C6mim NTf2 > C8mim NTf2, which follows the order of their dielectric constants. Judd-Ofelt parameters were calculated from photoluminescence data to get an idea about the symmetry of the Eu3+ complexes. Electrochemical investigations give diffusion coefficient values of 1.17 × 10-7 and 8.26 × 10-8 cm2/s for the Eu3+ complexes of HBNTA and HHNTA, respectively. Changes in the spectral characteristics and peak positions are evidenced in the FTIR spectra on the complexation of Eu3+ with the HRNTA ligands in C6mim NTf2. Structure optimization for the complexes was performed by DFT computations.

Looking at the Modern to Better Understand the Ancient: Is It Possible to Differentiate Mars Pigments from Archaeological Ochres?

This article offers a discussion of the possibility of distinguishing ochres from Mars pigments. The discussion addresses technological, archaeological, and artistic aspects. Natural earth pigments such as ochres, siennas, and umbers have been widely used from the Paleolithic to the present day and still find wide application despite the development of synthetic iron oxide pigment synthesis processes, called Mars pigments. The potential ability of today’s analytical techniques to distinguish between two classes of pigments of the same color with very similar chemical composition—but perhaps sufficient for reliable recognition—is also discussed. The paper begins by addressing the proper use of the terms “ochres” and “Mars pigments” and their accurate identification in artworks. It reviews the literature on the chemical–mineralogical characterization of yellow and red iron pigments and analyzes pigment catalogs to understand how companies distinguish ochres from Mars pigments. An experimental analysis using External Reflection Infrared Spectroscopy (FTIR-ER) compared painting samples made with natural ochres and Mars pigments, confirming the literature findings and suggesting future research directions. Key differences such as hematite in yellow ochres and specific spectral peaks in red ochres support the potential of FTIR-ER spectroscopy as a noninvasive tool for distinguishing pigments, especially for fragile artifacts and archaeological applications.

Developments in Localized Surface Plasmon Resonance

AbstractLocalized surface plasmon resonance (LSPR) is a nanoscale phenomenon associated with noble metal nanostructures that has long been studied and has gained considerable interest in recent years. These resonances produce sharp spectral absorption and scattering peaks, along with strong electromagnetic near-field enhancements. Over the past decade, advancements in the fabrication of noble metal nanostructures have propelled significant developments in various scientific and technological aspects of LSPR. One notable application is the detection of molecular interactions near the nanoparticle surface, observable through shifts in the LSPR spectral peak. This document provides an overview of this sensing strategy. Given the broad and expanding scope of this topic, it is impossible to cover every aspect comprehensively in this review. However, we aim to outline major research efforts within the field and review a diverse array of relevant literature. We will provide a detailed summary of the physical principles underlying LSPR sensing and address some existing inconsistencies in the nomenclature used. Our discussion will primarily focus on LSPR sensors that employ metal nanoparticles, rather than on those utilizing extended, fabricated structures. We will concentrate on sensors where LSPR acts as the primary mode of signal transduction, excluding hybrid strategies like those combining LSPR with fluorescence. Additionally, our examination of biological LSPR sensors will largely pertain to label-free detection methods, rather than those that use metal nanoparticles as labels or as means to enhance the efficacy of a label. In the subsequent section of this review, we delve into the analytical theory underpinning LSPR, exploring its physical origins and its dependency on the material properties of noble metals and the surrounding refractive index. We will discuss the behavior of both spherical and spheroidal particles and elaborate on how the LSPR response varies with particle aspect ratio. Further, we detail the fundamentals of nanoparticle-based LSPR sensing. This includes an exploration of single-particle and ensemble measurements and a comparative analysis of scattering, absorption, and extinction phenomena. The discussion will extend to how these principles are applied in practical sensing scenarios, highlighting the key experimental approaches and measurement techniques.

Vortex light field microscopy: 3D spectral single-molecule imaging with a twist

3D single-molecule imaging reveals nanoscale structures in cell volumes but is limited by the need for spectrally distinct fluorophores. We address this limitation with vortex light field microscopy (VLFM), a 3D spectral single-molecule localization technique with 25 nm spatial and 3 nm spectral precision over a 4 µm depth of field. By modifying our previous single-molecule light field microscope with an azimuthally oriented prism array, we generated spectral disparity orthogonal to axial disparity, enabling simultaneous spatial and spectral localization on a single detector. We demonstrate VLFM with four-color 3D single-particle tracking and two-color 3D dSTORM imaging in fixed cells, successfully identifying dyes with spectral peaks just 15 nm apart. This shows VLFM’s potential for enhancing spatial biology workflows requiring highly multiplexed imaging.

Investigating chloride-induced corrosion in reinforced concrete structures using Laser-Induced Breakdown Spectroscopy

Reinforced concrete structures face significant annual expenditures in combating rebar corrosion, with chloride penetration identified as a major contributor. This study employs laser-induced breakdown spectroscopy (LIBS) to quantitatively predict the chloride-induced corrosion rate in such structures. Eighty samples, characterized by known chloride content (ranging from 0% to 1.0%), underwent controlled corrosion processes with predetermined degrees measured as bar weight loss. The investigation included two cement types, Type I and Type V, along with samples incorporating pozzolanic materials (FA, SF, and GGBFS,) in addition to plain OPC samples. LIBS was subsequently employed to detect chlorine presence in each concrete sample, recording the corresponding intensity of the chlorine line. After the initial data acquisition, peak analysis was performed to identify the dominant spectral peaks, ensuring that the most relevant signals were isolated. Following this, the intensity of the chloride emission line from the LIBS spectrum was recorded and correlated with its corresponding chloride signal, establishing a quantitative relationship between the LIBS output and chloride presence. A model was then developed to link the LIBS signal intensity to its corresponding chloride concentration in the sample. In parallel, the corrosion rate associated with each specific chloride concentration was measured and then linked to the LIBS-derived chloride concentrations, creating a framework that ties the LIBS output to the actual rebar degradation within the concrete. Comparisons with previous studies demonstrated superior conformity of the developed models. The study also presents optimized parameters for the LIBS setup. Notably, results indicated a high correlation between LIBS intensity and chloride concentration, with the developed model accurately predicting the degree of corrosion.

Evaluation of Norm-Constrained Capon Method on Improving Doppler Peak Localization of Antenna-Arrayed High-Frequency Coastal Radar

Abstract Antenna-arrayed high-frequency coastal radar is widely used to monitor the ocean and obtain metocean parameters such as sea surface current, sea wave height, and surface wind. However, the accuracy of these parameters can be significantly influenced by the spectral width and Doppler velocity of the sea echo signals across azimuthal directions, and insufficient spectrum resolution increases uncertainties in the estimates of spectral width and Doppler velocity. To address this, we demonstrate an alternative approach to beamforming by utilizing the norm-constrained Capon (NC-Capon) method to enhance the Doppler spectral resolution and improve the localization accuracy of the spectral peaks. The efficacy of the NC-Capon method is exemplified through an application to a coastal radar dataset collected from 16 receiving channels, operated at a central frequency of 27.75 MHz. A comparative investigation of the NC-Capon beamforming method with the conventional Fourier beamforming method showed that the widths of the spectral peaks at different range cells and azimuthal angles are noticeably improved at lower signal-to-noise ratio (SNR) conditions. Given this, the NC-Capon beamforming method exhibits more robustness to noise and could effectively enhance the concentration of the radar sea echo signals in the Doppler frequency spectrum, thereby reducing the uncertainties of the spectral width and Doppler/radial velocity of the first-order sea echoes. These characteristics are substantiated by the comparative analysis of spectral parameters between the two beamforming methods across various ranges, beamforming angles, and SNR levels. Finally, the computed radial velocities are benchmarked against in situ measurements obtained from a bottom-mounted acoustic current profiler to confirm the validity of the NC-Capon method. Significance Statement We have recently implemented a high-frequency coastal radar equipped with an antenna array to monitor metocean variables within the offshore waters adjacent to Taichung Harbor in Taiwan. Our study focuses on enhancing the Doppler spectral resolution of radar sea echoes by employing an adaptive beamforming technique known as the norm-constrained Capon method. In comparison with the traditional linear beamforming approach, the norm-constrained Capon method demonstrates superior noise resilience. We anticipate that the norm-constrained Capon method holds promise as a dependable approach for refining the accuracy of metocean parameters obtained from antenna-arrayed high-frequency coastal radar systems.

ULTRASONIC INTERROGATION TECHNIQUE FOR DETECTING HATCH ANGLE VARIATIONS IN ADDITIVE MANUFACTURING BY PHONONIC LATTICE STRUCTURES

Abstract Additive Manufacturing/3D Printing (AM/3DP) has revolutionized part production by enabling the creation of intricate internal structures and complex geometries from diverse materials directly from digital design files. Among powder-based metal AM/3DP methods, Selective Laser Melting (SLM) is widely used in advanced applications such as biomedical devices and aerospace parts. Despite considerable progress in AM/3DP and SLM, at present, challenges in print quality persist, and vast resources for post-production quality assessment are allocated. The quality of SLM prints is influenced by various process and design parameters, such as the accuracy of hatch angle deposition, laser intensity/power, scanning speed of the laser beam, print line spacing, layer depth, printing chamber conditions, and the material's physical and chemical properties. Direct ultrasonic Non-Destructive Evaluation (NDE) offers comprehensive internal inspection and real-time data acquisition ability; however, in AM/3DP it faces severe limitations due to a build's intricate internal and external geometric features. In the current study, we present a Phononic Crystal Artifact (PCA)-based real-time ultrasonic NDE quality monitoring framework and show offline its utility in detecting and evaluating hatch angle variations, a critical process parameter. A PCA is substantially simpler and smaller than the actual build but represents its critical geometric and structural intricacies and mechanical properties. The current offline study demonstrates that hatch angle variations can be monitored from ultrasonic responses' spectral modal frequency peaks and wave dispersion relations.

The Early Radio Afterglow of Short GRB 230217A

We present the radio afterglow of short gamma-ray burst (GRB) 230217A, which was detected less than 1 day after the gamma-ray prompt emission with the Australia Telescope Compact Array (ATCA) and the Karl G. Jansky Very Large Array. The ATCA rapid-response system automatically triggered an observation of GRB 230217A following its detection by the Neil Gehrels Swift Observatory and began observing the event just 32 minutes postburst at 5.5 and 9 GHz for 7 hr. Dividing the 7 hr observation into three time-binned images allowed us to obtain radio detections with logarithmic central times of 1, 2.8, and 5.2 hr postburst, the first of which represents the earliest radio detection of any GRB to date. The decline of the light curve is consistent with reverse shock emission if the observing bands are below the spectral peak and not affected by synchrotron self-absorption. This makes GRB 230217A the fifth short GRB (SGRB) with radio detections attributed to a reverse shock at early times (<1 day postburst). Following brightness temperature arguments, we have used our early radio detections to place the highest minimum Lorentz factor ( Γmin>50 at ∼1 hr) constraints on a GRB in the radio band. Our results demonstrate the importance of rapid radio follow-up observations with long integrations and good sensitivity for detecting the fast-evolving radio emission from SGRBs and probing their reverse shocks.

Coconut Testa Flour Sub-Fractions: Correlation Between FTIR Spectral Data and α-Glucosidase Inhibitory Activities.

Fourier-transform infrared spectroscopy (FTIR) serves as a rapid analytical technique to characterize food specimens chemically. The purpose of this study was to investigate the potential of FTIR combined with multivariate statistics to detect Alpha-glucosidase (Alpha-glu) inhibitory activities of a non-cereal flour-like coconut testa flour (CTF). CTF of five distinct local cultivars was sequentially extracted with hexane, ethyl acetate (EtOAc), and methanol (MeOH) to assay the Alpha-glu inhibitory activity. FTIR spectra of CTF extracts were obtained within the range of 4000-500 cm-1 and the prominent spectral peaks obtained for both hexane and EtOAc extracts were roughly similar but some additional peaks were observed in EtOAc extracts representing phenolic constituents. The major absorbance peaks found in MeOH extracts were primarily indicative of the occurrence of the hydroxyl group associated with carbohydrates and phenolic compounds. The multivariate predictive models developed using partial least squares (PLS) and orthogonal partial least squares (OPLS) regression analyses indicated a strong correlation between Alpha-glu inhibitory activity and spectral data. Models developed for the spectral regions 3700-2800 cm-1 and 1800-500 cm-1 exerted the highest regression coefficients with the lowest root mean square errors. In OPLS regression analysis, the model obtained with third-derivative spectral data was identified as the best, exhibiting the highest regression coefficients and the lowest root mean square errors. Both PLS and OPLS regression analyses indicated a potential correlation of Alpha-glu inhibitory activity with FTIR spectral regions. Notably, OPLS models offered enhanced interpretability of the model parameters. This study suggests that the application of multivariate regression analysis of FTIR spectral data on coconut-based products could help to detect Alpha-glu inhibitory activities.

A high precision vital signs detection method based on millimeter wave radar

Millimeter wave (mmWave) radar technology has potential applications in vital signs detection and medicine. In order to minimize the influence of human micro-movements and respiratory harmonics on heart rate estimation, the vital signs detection method based on mmWave radar is studied in this paper. First, we use median filtering to eliminate baseline drift caused by human micromotion. Next, a differential recursive least squares multiple classification (DR-MUSIC) algorithm is proposed based on the combination of recursive least squares-based adaptive filter (RLS) and multiple signal classification (MUSIC) algorithm. This algorithm effectively suppresses respiratory harmonics and separates respiratory and heartbeat signals. Finally, heart rate value can be precisely estimated using spectral peak search. We invite a number of people to participate in the experiment, which demonstrate that the method successfully suppresse the impact of respiratory harmonics at low SNR. The error rate between the estimated heart rate and the reference heart rate is only 1.69% to 2.61%, which is significantly better than the existing algorithms.

Impact of multi-frequency ultrasound processing with different treatment times on the structural quality of frozen wheat dough

This study investigates the effects of multi-frequency ultrasound treatment on the quality of frozen dough. We analyzed frozen wheat dough comprehensively for texture, viscosity, rheology, and structural quality characteristics under multi-frequency ultrasound (20 kHz, 20/40 kHz, and 20/40/60 kHz) with different treatment times (10, 20, and 30 mins). The dough treated with multi-frequency ultrasound increased elasticity and reduced hardness. Scanning electron microscopy revealed that 20/40/60 kHz for 30 min minimized freezing-induced morphological damage, decreased the tan δ in rheological analysis, and led to higher pasting and gelatinization enthalpy in starch granules, resulting in a more cohesive structure and lower free water content. Frozen dough hardness decreased by 52.1 %, which is associated with the control frozen dough with ultrasound frequency and duration changes. The spectral peaks in wheat flour frozen dough treated with single, dual, and tri-frequency ultrasound had the same forms and positions as the control samples but were arranged in an orderly manner. This study demonstrates the potential of multi-frequency ultrasound to enhance the quality of wheat frozen dough by mitigating freezing-induced deteriorations, offering a promising approach to improving the processing of frozen dough.

Comparison of On-Sky Wavelength Calibration Methods for Integral Field Spectrograph

With advancements in technology, scientists are delving deeper in their explorations of the universe. Integral field spectrograph (IFS) play a significant role in investigating the physical properties of supermassive black holes at the centers of galaxies, the nuclei of galaxies, and the star formation processes within galaxies, including under extreme conditions such as those present in galaxy mergers, ultra-low-metallicity galaxies, and star-forming galaxies with strong feedback. IFS transform the spatial field into a linear field using an image slicer and obtain the spectra of targets in each spatial resolution element through a grating. Through scientific processing, two-dimensional images for each target band can be obtained. IFS use concave gratings as dispersion systems to decompose the polychromatic light emitted by celestial bodies into monochromatic light, arranged linearly according to wavelength. In this experiment, the working environment of a star was simulated in the laboratory to facilitate the wavelength calibration of the space integral field spectrometer. Tools necessary for the calibration process were also explored. A mercury–argon lamp was employed as the light source to extract characteristic information from each pixel in the detector, facilitating the wavelength calibration of the spatial IFS. The optimal peak-finding method was selected by contrasting the center of weight, polynomial fitting, and Gaussian fitting methods. Ultimately, employing the 4FFT-LMG algorithm to fit Gaussian curves enabled the determination of the spectral peak positions, yielding wavelength calibration coefficients for a spatial IFS within the range of 360 nm to 600 nm. The correlation of the fitting results between the detector pixel positions and corresponding wavelengths was &gt;99.99%. The calibration accuracy during wavelength calibration was 0.0067 nm, reaching a very high level.

Spatiotemporal patterns in a 2D lattice of Hindmarsh–Rose neurons induced by high-amplitude pulses

We present numerical results for the effects of influence by high-amplitude periodic pulse series on a network of nonlocally coupled Hindmarsh–Rose neurons with 2D geometry of the topology. We consider the case when the pulse amplitude is larger than the amplitude of oscillations in the autonomous network for a wide range of pulse frequencies. An initial regime in the network is a spiral wave chimera. We show that the effects of external influence strongly depend on a balance between the pulse frequency and frequencies of the spectral peaks of the autonomous network. Except for the destructive role of the pulses, when they lead to loss of stability of the initial regime, we have also revealed a constructive role. We have found for the first time the emergence of a new type of multi-front spiral waves, when the wavefront represents a set of several close fronts, and the wave dynamics are significantly different from common spiral waves: neurons oscillate independently to the wave rotation, the rotation velocity is in many times less than for the common spiral wave, etc. We have also discovered several types of cluster spatiotemporal structures induced by the pulses.