Spectral Structure Research Articles

Filling the gap of phonation in reptiles: First record of oral emission of the worm lizard, Amphisbaena alba

AbstractSo far, the phonation among worm lizards (Amphisbaenia) was virtually unknown, but herein we present for the first time a loud and clear record of sound emission by an amphisbaenian and its acoustic parameters. We observed an adult female of Amphisbaena alba emitting a high‐pitched sound, able to be heard a few meters away by a human ear. The sound was emitted with the mouth wide open and consisted of a short well‐defined note, presenting harmonics and frequency modulation. Based on the context of display and the body posture of the individual, we suggest that the oral emission of A. alba may be considered a defensive sound emission. However, based on the spectral structure of emission within hearing acuity reported for the species, we cannot disregard the possibility that this sound might act in communication with conspecifics. Beyond raising possible defensive and intra‐specific communication roles for the sound emissions of worm lizards, our findings contribute to the understanding of acoustic communication in tetrapods through the analysis of sounds produced by these fossorial reptiles.

Shpol’skii effect: new interpretation for the nature of the spectral multiplet structure and Bethe-splitting

New approach to the interpretation of the multiplet structure in the Shpol’skii spectra based on the symmetry consideration of the impurity molecule and crystal matrix is proposed. The reasons and peculiarities of doublet structure formation in the spectra of molecules without inversion center and highly symmetric molecules are considered. It is shown that the structure of electron density distribution in the naphthalene molecule causes a doubly degenerate of the electronic level of its ground state. The calculated data are compared with the experimental results. The main research stages and directions in the field of narrow-line spectroscopy of organic molecules are marked.

Spectrum, bifurcation and hypersurfaces of prescribed k-th mean curvature in Minkowski space

By bifurcation and topological methods, we study the existence/nonexistence and multiplicity of one-sign or nodal solutions of the following k-th mean curvature problem in Minkowski spacetime r N − k v ′ 1 − v ′ 2 k ′ = λ N C N k r N − 1 H k ( r , v ) in ( 0 , R ) , | v ′ | < 1 in ( 0 , R ) , v ′ ( 0 ) = v ( R ) = 0 . As a previous step, we investigate the spectral structure of its linearized problem at zero. Moreover, we also obtain a priori bounds and the asymptotic behaviors of solutions with respect to λ.

Skolem and positivity completeness of ergodic Markov chains

We consider the following Markov Reachability decision problems that view Markov Chains as Linear Dynamical Systems: given a finite, rational Markov Chain, source and target states, and a rational threshold, does the probability of reaching the target from the source at the nth step: (i) equal the threshold for some n? (ii) cross the threshold for some n? (iii) cross the threshold for infinitely many n? These problems are respectively known to be equivalent to the Skolem, Positivity, and Ultimate Positivity problems for Linear Recurrence Sequences (LRS), number-theoretic problems whose decidability has been open for decades. We present an elementary reduction from LRS Problems to Markov Reachability Problems that improves the state of the art as follows. (a) We map LRS to ergodic (irreducible and aperiodic) Markov Chains that are ubiquitous, not least by virtue of their spectral structure, and (b) our reduction maps LRS of order k to Markov Chains of order k+1: a substantial improvement over the previous reduction that mapped LRS of order k to reducible and periodic Markov chains of order 4k+5. This contribution is significant in view of the fact that the number-theoretic hardness of verifying Linear Dynamical Systems can often be mitigated by spectral assumptions and restrictions on order.

A spectral and spatial transformer for hyperspectral remote sensing image super-resolution

ABSTRACT Due to the generally low spatial resolution of hyperspectral images (HSIs), early multispectral images lacked corresponding panchromatic bands, and as a result, fusion methods could not be used to enhance resolution. Many researchers have proposed various image super-resolution methods to address these limitations. However, these methods still suffered from issues, such as inadequate feature representation, lack of spectral feature representation, and high computational cost and inefficiency. To address these challenges, a spectral and spatial transformer (SST) algorithm for hyperspectral remote sensing image super-resolution is introduced. This algorithm uses a spatial transformer structure to extract the spatial features between the image pixels and a spectral transformer structure to extract the spectral features within the image pixels. The integration of these two components is applied to HSI super-resolution. After comparative experiments with currently advanced methods on three publicly available hyperspectral datasets, the results consistently show that our algorithm has better performance in both spectral fidelity and spatial restoration. Furthermore, our proposed algorithm was applied to real-world super-resolution experiments in the region of China's Ruoergai National Park, and subsequently, pixel-based classification was conducted on the super-resolution images, the results indicate that our algorithm could also be applied to future remote sensing interpretation tasks.

Exciting space-time surface plasmon polaritons by irradiating a nanoslit structure.

Space-time (ST) wave packets are propagation-invariant pulsed optical beams that travel freely in dielectrics at a tunable group velocity without diffraction or dispersion. Because ST wave packets maintain these characteristics even when only one transverse dimension is considered, they can realize surface-bound waves (e.g., surface plasmon polaritons at a metal-dielectric interface, which we call ST-SPPs) that have the same unique characteristics as their freely propagating counterparts. However, because the spatiotemporal spectral structure of ST-SPPs is key to their propagation invariance on the metal surface, their excitation methodology must be considered carefully. Using finite-difference time-domain simulations, we show that an appropriately synthesized ST wave packet in free space can be coupled to an ST-SPP via a single nanoscale slit inscribed in the metal surface. Our calculations confirm that this excitation methodology yields surface-bound ST-SPPs that are localized in all dimensions (and can thus be considered as plasmonic "bullets"), which travel rigidly at the metal-dielectric interface without diffraction or dispersion at a tunable group velocity.

Effect of multiply excited states to the EUV emission from yttrium-like tin

The spectral emission rate of yttrium-like tin (Sn11+) is investigated as the typical ion, which has a strong emission of extreme ultra-violet (EUV) light near the wavelength of 13.5 nm. The energy level structure of the tin ion is investigated using the non-relativesitic configuration average model to calculate the population in the local thermodynamic equilibrium, and the spectral structure of the unresolved transition array that has EUV emission is investigated based on the calculated atomic data using the HULLAC code. It is shown that the broad main peak is accompanied by the tail structure for shorter and longer wavelengths, which arises from multiply and inner-shell excited levels. The emission channels that significantly contribute to the spectrum are determined from a convergence analysis. The excited states below the ionization limit with a large population are shown to have a significant contribution to the emission.

VLA FRAMEx. I. Wideband Radio Properties of the AGN in NGC 4388

We present the first results from Karl G. Jansky Very Large Array (VLA) observations as a part of the Fundamental Reference Active Galactic Nucleus (AGN) Monitoring Experiment, a program to understand the relationship between AGN accretion physics and wavelength-dependent position as a function of time. With this VLA survey, we investigate the radio properties from a volume-complete sample of 25 hard X-ray-selected AGNs using the VLA in its wideband mode. We observed the targets in the A-array configuration at 4–12 GHz with all polarization products. In this work, we introduce our calibration and imaging methods for this survey, and we present our results and analysis for the radio-quiet AGN NGC 4388. We calibrated and imaged these data using the multiterm, multifrequency synthesis imaging algorithm to determine its spatial, spectral, and polarization structure across a continuous 4–12 GHz band. In the AGN, we measure a broken power law spectrum with α = − 0.06 below a break frequency of 7.3 GHz and α = − 0.34 above. We detect polarization at subarcsecond resolution across both the AGN and a secondary radio knot. We compare our results to ancillary data and find that the VLA radio continuum is likely due to AGN winds interacting with the local interstellar medium that gets resolved away at subparsec spatial scales as probed by the Very Long Baseline Array. A well-known ionization cone to the southwest of the AGN appears likely to be projected material onto the underside of the disk of the host galaxy.

The first spatio-spectral Bayesian imaging of SN1006 in X-rays

Supernovae (SNs) are an important source of energy in the interstellar medium. Young remnants of supernovae (SNRs) exhibit peak emission in the X-ray region, making them interesting objects for X-ray observations. In particular, the supernova remnant SN1006 is of great interest due to its historical record, proximity, and brightness. Thus, it has been studied with a number of X-ray telescopes. Improving X-ray imaging of this and other remnants is an important but challenging task, as it often requires multiple observations with different instrument responses to image the entire object. Here, we use Chandra observations to demonstrate the capabilities of Bayesian image reconstruction using information field theory (IFT). Our objective is to reconstruct denoised, deconvolved, and spatio-spectral resolved images from X-ray observations and to decompose the emission into different morphologies, namely, diffuse and point-like. Further, we aim to fuse data from different detectors and pointings into a mosaic and quantify the uncertainty of our result. By utilizing prior knowledge on the spatial and spectral correlation structure of the diffuse emission and point sources, this method allows for the effective decomposition of the signal into these two components. In order to accelerate the imaging process, we introduced a multi-step approach, in which the spatial reconstruction obtained for a single energy range is used to derive an informed starting point for the full spatio-spectral reconstruction. We applied this method to 11 Chandra observations of SN1006 from 2008 and 2012, providing a detailed, denoised, and decomposed view of the remnant. In particular, the separated view of the diffuse emission ought to provide new insights into the complex, small-scale structures in the center of the remnant and at the shock front profiles. For example, our analysis reveals sharp X-ray flux increases by up to two orders of magnitude at the shock fronts of SN1006.

Localization and spectral structure in two-dimensional quasicrystal potentials

Localization and spectral structure in two-dimensional quasicrystal potentials

Performance study on a novel greenhouse cover structure with beam split and heat control function

Based on the principle of spacing prism, a novel greenhouse cover plate with beam split and heat control function is proposed. The visible light needed for plant growth transmits into the greenhouse and near-infrared radiation is absorbed to reduce the internal temperature. The target is to design a greenhouse cover plate that can not only reduces the temperature of greenhouse, but also reduces the energy consumption of greenhouses cooling system in summer. The relative position and size of the heat-absorbing plate are obtained through theoretical calculations. Based on the Monte Carlo light tracking principle, optical software is used to optimize the operating mode of the heat-absorbing plate. The relationship between air flow, efficiency and outlet temperature are analyzed by CFD numerical simulations. The integrating box is designed on principle of integrating ball, which is used to test this device's transmission and thermal characteristics. The test results are compared with double-layer vacuum glass under actual weather conditions. The results show that the transmission rate of spectral temperature control cover structure (STCCS) is about 60 % in the morning and afternoon, but it is lower at noon, approximately 47.32 %. Based on the thermal characteristic experiment results, it can be known that the average inside temperature of the STCCS box is decreased by 3.16 °C compared with the double-layer vacuum glass, and the thermal load is reduced by 21 %.

Evolution of weak, homogeneous turbulence with rotation and stratification

This article concerns the time-evolution, spectral structure and scaling of weak turbulence subject to rotation and stable stratification. The flow is expressed as a combination of particular solutions, referred to as modes, of the linearised governing equations without viscosity or diffusion. Modes are of two types: oscillatory ones which represent inertial-gravity waves and time-independent ones that express a non-propagating (NP) component of the flow. The presence of the NP component, which plays an active role in the dynamics apart from in the case of pure rotation, renders wave-turbulence analysis problematic because the NP mode is non-dispersive. Equations are derived for the time evolution of the modal amplitudes, evolution which is due to nonlinearity and visco-diffusion. Subsequent analysis assumes that one or other (or both) of the Rossby and Froude numbers is small (weak turbulence). Given this assumption, the NP component is found to evolve independently of the wave one and a numerical scheme, similar to, though significantly different from classical direct numerical simulation, is used to determine its time evolution. The treatment of the wave component assumes its amplitude is large compared with the NP one, otherwise there are seemingly intractable difficulties of closure in the analysis. Given this further assumption, the wave component decouples from the NP one. Evolution equations for the wave spectra are derived using wave-turbulence analysis and are integrated numerically. As might be expected, these equations indicate that nonlinear coupling of wave modes is dominated by resonances. Results are given for both the NP and wave components.

SSC-SFN: spectral-spatial non-local segment federated network for hyperspectral image classification with limited labeled samples

ABSTRACT Hyperspectral image (HSI) classification methods based on deep learning (DL) have performed well in numerous investigations. Although many modified superpixel-wise neural networks are utilized to enhance spatial information, their ability to mine spectral information in graph structures is insufficient. Moreover, single classifier approaches are unable to extract adequate spatial and spectral information simultaneously. For the classification of large-scale research areas, many works have relied on the use of a large number of labeled samples, leading to low efficiency and weak generalization. To address these issues, an effective spectral-spatial HSI classification approach based on spectral-spatial non-local segment federated network (SSC-SFN) was developed in this study. In this framework, deconvolution is employed to recover the data size, while the lost spatial information is replaced by up-pooling. The spectral dimensional features are updated through the generation of non-Euclidean graph structures and the non-local segment smoothing technique. The convolutional neural network and graph convolutional network techniques are coupled to exploit the available spectral and spatial structure information fully. Extensive experimental results obtained using four public benchmark datasets show that the classification accuracy of SSC-SFN can exceed 90% for large-scale HSIs with limited samples.

Anthemis tricolor Containing Unusual Totarol with Cytotoxic and Acetylcholinesterase-Inhibitory Activity.

Anthemis tricolor is an endemic species of Cyprus, and there is very limited information on its chemistry and pharmacological activities. The study aims to identify the in-vitro cytotoxic and acetylcholinesterase activities of Anthemis tricolor. The compounds responsible for the activities were also identified. Potent extracts of A. tricolor were subjected to preparative isolation and spectral structure determination studies. The chloroform extract contained many components, and due to the small quantity of extract available, enough pure compound(s) cannot be obtained for structure determination studies, though the n-hexane extract afforded two known compounds, totarol (1) and taraxasterol (2). The structures of the compounds (1 and 2) were determined by 1 H and 13 C NMR experiments. The pure compounds were also tested for their acetylcholinesterase inhibitory properties. For compound 1, the IC50 value was found to be 87.88 μg/mL. However, no inhibition was seen for 2. Anthemis tricolor was established to be a valuable source of pharmacologically active compounds and requires further studies.

Efficacy of the Ionic Liquid 1,4-Bis(carboxymethyl)piperazine-1,4-diium Chloride as a Catalyst for Xanthenes/Acridines Synthesis: Spectral Characterization, X-ray Structure, and Nematicidal Activity

In this research paper, a straightforward and efficient approach for synthesizing the 1,4-bis(carboxymethyl)piperazine-1,4-diium chloride [BCMPZ][2Cl] ionic liquid salt (IL) catalyst is introduced. The morphology, thermal stability, and functionality of the synthesized [BCMPZ][2Cl] IL were characterized using spectroscopic, electron microscopy, and thermal analysis. A density functional theory (DFT) study, including infrared spectroscopy (IR), powder X-ray diffraction (PXRD), Thermogravimetric analysis (TGA), and scanning electron microscopy with energy-dispersive X-ray spectroscopy (SEM with EDX), were employed. The well-characterized ionic liquid (IL) assisted as a catalyst in the synthesis reaction involving aldehydes, dimidone, and arylamine to yield 1,8-dioxo-octahydroxanthene and 1,8-dioxo-9-aryl-10-aryl-decahydroacridine derivatives (3a-i and 4a-b) with high yields, getting up to 97%. The structure of the synthesized molecules was confirmed through various physicochemical techniques, including 1H and 13C NMR, IR, elemental analysis, and MS. X-ray single crystal diffraction techniques were also used to elucidate the geometry of one of the synthesized molecules (3f). The heterogeneous catalyst (IL) used in the synthesis of the molecules was successfully recycled and reused without additional treatment of purification. The synthesized xanthines were found to inhibit nematode activity, thus they may act as potential nematicides for crop protection. The present study also identified five different compounds that were effective against Meloidogyne incognita. Compound 3a reduced nematode egg hatching by 65% at a concentration of 2000 ppm, which was the highest efficacy in tested compounds. Compound 3c had a mortality rate of 80% against nematodes. Overall, the developed method has many advantages, including fast reaction time, economic efficiency, and minimal catalyst loading, making it a promising method for future research in the field of heterocycle synthesis and crop protection.

Enhanced 3-D asynchronous correlation data preprocessing method for Raman spectroscopy of Chinese handmade paper

We have developed a novel 3D asynchronous correlation method (3D-ACM) designed for the classification and identification of Chinese handmade paper samples using Raman spectra and machine learning. The 3D-ACM approach involves two rounds of tensor product and Hilbert transform operations. In the tensor product process, the outer product of the spectral data from different samples within the same category is computed, establishing inner connections among all samples within that category. The Hilbert transform introduces a 90-degree phase shift, resulting in a true three-dimensional spectral data structure. This expansion significantly increases the number of equivalent frequency points and samples within each category. This enhancement substantially boosts spectral resolution and reveals more hidden information within the spectral data. To maximize the potential of 3D-ACM, we employed six machine learning models: principal component analysis (PCA) with linear regression (LR), support vector machine (SVM) with LR, k-Nearest Neighbors (KNN), random forest (RF), and convolutional neural network (CNN). When applied to the 3D-ACM data preprocessing method, R-squared values of PLS-LR, KNN, RF and CNN supervised models, approached or equaled 1. This indicates exceptional performance comparable to unsupervised models like PCA. 3D-ACM stands as a versatile mathematical technique not confined to spectral data. It also eliminates the necessity for additional experimental setups or external control conditions, distinct from traditional two-dimensional correlation spectroscopy. Moreover, it preserves the original experimental data, setting it apart from conventional data preprocessing methods. This positions 3D-ACM as a promising tool for future material classification and identification in conjunction with machine learning.

High-dimensional inference of radio interferometer beam patterns I: parametric model of the HERA beams

ABSTRACT Accurate modelling of the primary beam is an important but difficult task in radio astronomy. For high dynamic range problems such as 21 cm intensity mapping, small modelling errors in the sidelobes, and spectral structure of the beams can translate into significant systematic errors. Realistic beams exhibit complex spatial and spectral structure, presenting a major challenge for beam measurement and calibration methods. In this paper series, we present a Bayesian framework to infer per-element beam patterns from the interferometric visibilities for large arrays with complex beam structure, assuming a particular (but potentially uncertain) sky model and calibration solution. In this first paper, we develop a compact basis for the beam so that the Bayesian computation is tractable with high-dimensional sampling methods. We use the Hydrogen Epoch of Reionization Array (HERA) as an example, verifying that the basis is capable of describing its single-element E-field beam (i.e. without considering array effects like mutual coupling) with a relatively small number of coefficients. We find that 32 coefficients per feed, incident polarization, and frequency, are sufficient to give percent-level and $\sim$10 per cent errors in the mainlobe and sidelobes, respectively, for the current HERA Vivaldi feeds, improving to $\sim 0.1{{\ \rm per\ cent}}$ and $\sim 1{{\ \rm per\ cent}}$ for 128 coefficients.

Detecting Fast Radio Bursts with Spectral Structure Using the Continuous Forward Algorithm

Detecting fast radio bursts (FRBs) with frequency-dependent intensity remains a challenge, as existing search algorithms do not account for the spectral shape, potentially leading to nondetections. We propose a novel detection statistic, which we call the Kalman detector, that improves the sensitivity of FRB signal detection by incorporating spectral shape information. The detection statistic is based on an optimal matched filter, marginalizing over all possible intensity functions, weighted by a random walk probability distribution, considering some decorrelation bandwidth. Our analysis of previously detected FRBs demonstrates that the Kalman score provides a comparable yet independent source of information for bursts with significant spectral structure, and the sensitivity improvement is of the order 0%–200% with a median improvement of 20%. We also applied the Kalman detector to existing data from FRB 20201124A and detected two new repeat bursts that were previously missed. Furthermore, we suggest a practical implementation for real-time surveys by employing a low significance soft-trigger from initial flux integration-based detection algorithms. The Kalman detector has the potential to significantly enhance FRB detection capabilities and enable new insights into the spectral properties of these enigmatic astrophysical phenomena.

Laser monitoring of stress conditions of plants

Based on our own research and analysis of existing methods for monitoring vegetation cover, the advantages of laser remote sensing have been proven. Preliminary experiments were carried out on such simplified models as extracts of pigments that play a major role in the photographic processes of interest to us. These models were chlorophyll fractions “a” and “b” extracted from plant leaves. These measurements made it possible to state that by selective excitation of fluorescence in preparations from acetone solutions of chlorophyll, it is possible to identify certain effects caused by differences in the groups and configurations of pigments inherent in their native state in the photosynthetic apparatus. Measurements carried out on plants subject to mineral stress showed that cotton grown under conditions without the addition of basic nutrients such as potassium, nitrogen and phosphorus to the substrate shows a lower fluorescence yield compared to control plants grown under normal mineral nutrition. At the same time, the dynamics of changes in the spectral characteristics of plants subject to water stress showed the opposite pattern. On the sixth day after stopping watering, when signs of wilting began to appear, the fluorescence output increased by 30% compared to control plants. As a result, these two competing processes make it difficult to unambiguously diagnose the real state from the integrated fluorescence output. However, the spectral shape turned out to be more informative than the integral fluorescence output. Therefore, to most accurately identify the state of the plant, an analysis of the spectral structure of the fluorescent response was chosen

Integration of Spatial Spectral Structure with Improved Local Density for Hyperspectral Image Band Selection Method

Integration of Spatial Spectral Structure with Improved Local Density for Hyperspectral Image Band Selection Method