Phase Spectra Research Articles

Pu(VI) Oxalate Crystal Structure and Evidence of Photoreduction to Pu(IV) Oxalate.

We report the first crystal structure of a Pu(VI)-oxalate compound. This compound, [PuO2(C2O4)(H2O)]·2(H2O) (1), crystallizes in space group P21/c with a = 5.5993(3) Å, b = 16.8797(12) Å, c = 9.3886(6) Å, and β = 98.713(6)°. It is isostructural with the previously reported U(VI) compound, [UO2(C2O4)(H2O)]·2(H2O). Each plutonyl ion (PuO22+) is coordinated in the equatorial plane by two side-on bidentate oxalates, creating an infinite chain along [001]. A coordinated water molecule and twisting of the oxalates lead to a distorted pentagonal bipyramidal geometry of the Pu. A photochemical degradation was observed for 1, which resulted in the formation of a secondary crystalline phase. The absorption spectrum of this secondary phase confirmed the presence of Pu(IV), but it did not match the spectrum of Pu(C2O4)2·6H2O, which is considered to be the primary product of Pu-oxalate precipitation. While compound 1 has previously been proposed to exist in solution, this is the first time it has been isolated via crystallization. Although redox interactions between Pu and oxalate have been documented in the literature, the present study is the first observation of a photochemical reduction of Pu(VI)-oxalate. As a result, this study has expanded on the limited understanding of the Pu(VI)-oxalate system, which is important for nuclear fuel cycle applications.

CD40 is expressed in the subsets of endothelial cells undergoing partial endothelial-mesenchymal transition in tumor microenvironment.

Tumor progression and metastasis are regulated by endothelial cells undergoing endothelial-mesenchymal transition (EndoMT), a cellular differentiation process in which endothelial cells lose their properties and differentiate into mesenchymal cells. The cells undergoing EndoMT differentiate through a spectrum of intermediate phases, suggesting that some cells remain in a partial EndoMT state and exhibit an endothelial/mesenchymal phenotype. However, detailed analysis of partial EndoMT has been hampered by the lack of specific markers. Transforming growth factor-β (TGF-β) plays a central role in the induction of EndoMT. Here, we showed that inhibition of TGF-β signaling suppressed EndoMT in a human oral cancer cell xenograft mouse model. By using genetic labeling of endothelial cell lineage, we also established a novel EndoMT reporter cell system, the EndoMT reporter endothelial cells (EMRECs), which allow visualization of sequential changes during TGF-β-induced EndoMT. Using EMRECs, we characterized the gene profiles of multiple EndoMT stages and identified CD40 as a novel partial EndoMT-specific marker. CD40 expression was upregulated in the cells undergoing partial EndoMT, but decreased in the full EndoMT cells. Furthermore, single-cell RNA sequencing analysis of human tumors revealed that CD40 expression was enriched in the population of cells expressing both endothelial and mesenchymal cell markers. Moreover, decreased expression of CD40 in EMRECs enhanced TGF-β-induced EndoMT, suggesting that CD40 expressed during partial EndoMT inhibits transition to full EndoMT. The present findings provide a better understanding of the mechanisms underlying TGF-β-induced EndoMT and will facilitate the development of novel therapeutic strategies targeting EndoMT-driven cancer progression and metastasis.

Coherence phase spectrum analyzer for a randomly fluctuated fractional vortex beam

Fractional vortex beams exhibit a higher degree of modulation dimensions than conventional vortices, thus inheriting superior anti-turbulent transmission properties through the incorporation of additional coherence modulation. However, aliasing the mixed modes induced by coherence degradation makes the quantitative measurement of the topological charge in fractional vortex beams challenging. In this study, a coherence phase spectrum was introduced, and experimental demonstrations to quantitatively determine the fractional topological charge of partially coherent fractional vortex beams were performed. By leveraging the four-dimensional measurement of a partially coherent light field, the source coherence function was inversely reconstructed, and fractional topological charges were determined with high precision by extracting the phase spectrum of the coherence function. Laguerre–Gaussian, elliptical Gaussian, and plane-wave-fraction vortex beams with various degrees of coherence were used to demonstrate measurement precision. The proposed method is applicable to X-rays and electron vortices. It has potential applications in optical encryption, high-capacity optical communication, and quantum entanglement.

Exploring the Influence of the Phosphorus-Heteroatom Substitution in Nicotine on Its Electronic and Vibrational Spectroscopic Properties.

The influence of phosphorus substitution of nitrogen in heterocyclic compounds on the vibrational spectroscopy as well as frontier molecular orbitals are analyzed. Nicotine with two nitrogen atoms in its structure is taken as the sample system to be studied computationally. By replacing the nitrogen atom in one or both rings of this molecule with phosphorus, three nicotine derivatives are created. The vibrational circular dichroism and infrared spectra of these four molecules in their monomer state, as well as the assemblies up to trimers are determined. The aforementioned spectra are calculated using static quantum chemical calculations employing a cluster-weighted approach. The calculated gas phase spectra of nicotine are compared to their respective experimental spectra. It is observed that the nicotine derivatives with phosphorus in the methylpyrrolidine ring have considerably different gas phase and bulk phase vibrational circular dichroism spectra when compared to nicotine. The phosphorus substitution reduces the energy gap between the highest occupied molecular orbital and the lowest unoccupied molecular orbital as well as altering the polarizability and reactivity of the investigated molecules.

Synthesis, X-ray diffraction, DFT, and molecular docking studies of isonicotinohydrazide derivative

Abstract The synthesized compound N′-benzylidene-isonicotinohydrazide (N-BINH), was experimentally characterized using XRD and distinguished by using experimental spectroscopic methods. DFT, B3LYP method along with 6-311++G(d,p) basis set were applied to determine the optimal molecular geometry and vibrational wave numbers. Gauge Independent Atomic Orbital (GIAO) method and DFT were used to calculate the chemical shifts for 13C and 1H NMR in chloroform solvent. MEP analysis reveals that the site with an oxygen atom is the most reactive part of the N-BINH molecule. Computed UV–visible spectrum in MeOH and gas phase was generated by using the TD-DFT technique. The investigation also looked at electron localization function properties. Hirshfeld analysis demonstrates the 3D intermolecular interactions of the crystal surface, while fingerprint plots were used to elucidate the 2D interactions. By calculating the electrophilicity index, it was theoretically shown that the titled molecule could be bioactive. Further, molecular docking analysis was used to investigate the biological activity of the N-BINH with four distinct receptors to assess the finest ligand–protein interactions and similarity to the dynamic constituent.

A tunable graphene-based phase-jump inversion plasmonic sensor for ultra-sensitive refractive index sensing over THz frequency

The surface plasmon resonance effect has been previously reported as an essential mechanism for terahertz wave sensing applications. However, due to its structural geometric parameters dependence, either the reconfiguration of the arrays or the realignment of the prism system is required, which always remains one of the challenges limiting practical applications. Here, a graphene-based phase-jump inversion plasmonic sensor (GPPS) operating at a fixed gap and incident angle is established. The optimal wave vector matching between specific analytes and the GPPS can be achieved by adjusting the Fermi level of graphene. On this basis, an ultrahigh sensitivity of 0.488 THz/RIU is achieved under the optimal Fermi level. Remarkably, the comparison between the phase spectra and the reflective amplitude spectra indicates that the phase-based FoM and Q-factor are two orders of magnitude larger than those calculated by amplitude spectra, which could reach 244RIU−1 and 218.5. The unique phase-jump responses on graphene surface plasmon resonance provide new ideas for ultra-sensitivity THz sensing methods.

The spiral phase spectrum of the composite power Gaussian vortex beam in plasma sheath turbulence

This paper establishes an evolution model for the spiral phase spectrum of a composite power Gaussian (CPG) vortex beam in plasma sheath turbulence (PST) based on the Rytov approximation theory and the modified von Karman spectrum. The impact of various parameters, including turbulence and beam attributes, on the spiral phase spectrum of the CPG vortex beam in PST is investigated through numerical simulations. Our numerical results reveal that the spiral phase spectrum of beam exhibits asymmetry which modulated by the structural parameter. Meanwhile, the resistance of the CPG vortex beam against turbulence strengthens as the wavelength increases and the topological charge decreases. The findings also demonstrate that the spiral phase spectrum of the CPG vortex beam incorporates a broader range of modes in isotropic PST compared to anisotropic PST. Furthermore, the impact of PST on the beam is intensified with a higher refractive index undulation variance and a smaller outer scale parameter.

Head-related transfer functions of rabbits within the front horizontal plane

The head-related transfer function (HRTF) describes the direction-dependent acoustic filtering by the head that occurs between a source signal in free-field space and the signal at the tympanic membrane. HRTFs contain information on sound source location via interaural differences of their magnitude or phase spectra and via the shapes of their magnitude spectra. The present study characterized HRTFs for source locations in the front horizontal plane for nine rabbits, which are a species commonly used in studies of the central auditory system. HRTF magnitude spectra shared several features across individuals, including a broad spectral peak at 2.6kHz that increased gain by 12 to 23dB depending on source azimuth; and a notch at 7.6kHz and peak at 9.8kHz visible for most azimuths. Overall, frequencies above 4kHz were amplified for sources ipsilateral to the ear and progressively attenuated for frontal and contralateral azimuths. The slope of the magnitude spectrum between 3 and 5kHz was found to be an unambiguous monaural cue for source azimuths ipsilateral to the ear. Average interaural level difference (ILD) between 5 and 16kHz varied monotonically with azimuth over ±31dB despite a relatively small head size. Interaural time differences (ITDs) at 0.5kHz and 1.5kHz also varied monotonically with azimuth over ±358 μs and ±260 μs, respectively. Remeasurement of HRTFs after pinna removal revealed that the large pinnae of rabbits were responsible for all spectral peaks and notches in magnitude spectra and were the main contribution to high-frequency ILDs (5–16kHz), whereas the rest of the head was the main contribution to ITDs and low-frequency ILDs (0.2–1.5kHz). Lastly, inter-individual differences in magnitude spectra were found to be small enough that deviations of individual HRTFs from an average HRTF were comparable in size to measurement error. Therefore, the average HRTF may be acceptable for use in neural or behavioral studies of rabbits implementing virtual acoustic space when measurement of individualized HRTFs is not possible.

An improved parameter estimation of HFM signals based on IRLS linear fitting of extracted group delay

To address the issue of robust parameter estimation of hyperbolic frequency modulated (HFM) signals under low signal-to-noise ratios (SNRs), an improved algorithm based on iteratively reweighted least squares (IRLS) linear fitting of extracted group delay is proposed. The algorithm includes three main steps. First, a novel method for estimating the frequency distribution range (FDR) of an HFM signal is presented, which involves analyzing the transient features of the amplitude spectrum (AS). Second, the spectrum phase (SP) is unwrapped in the estimated FDR to extract the group delay (GD) of the HFM signal. Last, parameter estimation of the HFM signal is achieved by fitting the GD, which is a linear function of the reciprocal of the frequency, using the IRLS linear fitting method. The simulation results have shown that for SNR ≥ -14 dB, the normalized root mean square errors (NRMSEs) estimated by the proposed estimator are 1.5 dB lower than those estimated by the spectrum phase unwrapping (SPU) estimator, including the starting frequency and period slope. Furthermore, experimental results based on sea trial data have also verified the validity and feasibility of the proposed estimator.

Magnons in the fan phase of anisotropic frustrated antiferromagnets

Elementary excitations spectrum of the fan phase of anisotropic frustrated antiferromagnets is discussed analytically. In the linear spin-wave approximation, the spectrum is determined by the Hamiltonian, including normal, anomalous, and umklapp terms. The latter mix states with momenta which differ by two modulation vectors of the fan structure. This mixing leads to essential rearrangement of the low-energy part of the spectrum, which is shown to consist of a gapless phason branch with linear dispersion and a gapped “optical” branch, which corresponds to the fan structure amplitude oscillations. In the high-energy part of the spectrum, the effect of the umklapps is negligible, and the excitations are similar to the magnons of the fully polarized phase.

Robust small infrared target detection using weighted adaptive ring top-hat transformation

Complex background in infrared images often challenges the accurate detection of small targets. To address this problem, we propose a weighted adaptive ring top-hat transformation (WARTH) for extracting infrared small targets in complex backgrounds. The method utilizes an adaptive ring-shaped structural element (SE) and a target awareness indicator to effectively measure local and global feature information to detect small targets while minimizing false alarms accurately. Firstly, the difference-of-structure tensors (DoST) is designed, and the positive smallest eigenvalue of DoST (PSEDoST) is computed to construct the adaptive ring-shaped SE that captures local feature information for background estimation. Secondly, the image is converted into the Fourier phase spectrum, and a two-stage sliding window filtering technique is designed to generate the target awareness indicator that perceives global feature information of small targets. Finally, the WARTH is defined by fusing the above two measurements, which can further eliminate false alarms and improve the robustness of target detection. The experimental results demonstrate that the WARTH is superior to several advanced methods in terms of false alarm reduction and small target detection in complex backgrounds.

Sensitivity to direction and velocity of fast frequency chirps in the inferior colliculus of awake rabbit

Neurons in the mammalian inferior colliculus (IC) are sensitive to the velocity (speed and direction) of fast frequency chirps contained in Schroeder-phase harmonic complexes (SCHR). However, IC neurons are also sensitive to stimulus periodicity, a prominent feature of SCHR stimuli. Here, to disentangle velocity sensitivity from periodicity tuning, we introduced a novel stimulus consisting of aperiodic random chirps. Extracellular, single-unit recordings were made in the IC of Dutch-belted rabbits in response to both SCHR and aperiodic chirps. Rate-velocity functions were constructed from aperiodic-chirp responses and compared to SCHR rate profiles, revealing interactions between stimulus periodicity and neural velocity sensitivity. A generalized linear model analysis demonstrated that periodicity tuning influences SCHR response rates more strongly than velocity sensitivity. Principal component analysis of rate-velocity functions revealed that neurons were more often sensitive to the direction of lower-velocity chirps and were less often sensitive to the direction of higher-velocity chirps. Overall, these results demonstrate that sensitivity to chirp velocity is common in the IC. Harmonic sounds with complex phase spectra, such as speech and music, contain chirps, and velocity sensitivity would shape IC responses to these sounds.

Correction: Influence of iron insertion in phase and Raman spectra of sol–gel-derived Ruddlesden Popper-type Sr2(Ce1-xFex)O4 (x = 0–1.0) powders

Correction: Influence of iron insertion in phase and Raman spectra of sol–gel-derived Ruddlesden Popper-type Sr2(Ce1-xFex)O4 (x = 0–1.0) powders

Robust infrared small target detection with multi-feature fusion

The performance of the infrared search and track system depends on the robust of the infrared small target detection. In this paper, a novel small target detection with multi-feature fusion is proposed. At first, the salient proposal region is obtained with phase spectrum Fourier transform (PFT). Then, geometric moment is utilized to design an adaptive steerable edges awareness factor, which effectively eliminates the strong edge clutters. Afterwards, we adopt a three-layers local contrast structure and the difference-ration form is introduced to enhance the target and suppress the complex backgrounds. Finally, the adaptive threshold is applied to extract the target in the saliency map. Experiments are conducted on four real IR image sequences, which demonstrate that the proposed method outperforms the comparing methods with various complex backgrounds.

Stochastic simulation of earthquake ground motions based on improved finite-fault model

In the seismic reliability analysis of engineering structures, it is often necessary to adopt stochastic ground motions as inputs. However, the current methods used to generate stochastic samples, such as the spectral representation method, the spectral transfer method, the dynamic source method, the physical source method, and the comprehensive method, etc., are not very convincing since they do not contain the complete information of seismic occurrence and propagation. In this study, an improved finite-fault model for stochastic simulation of ground motions is proposed. Compared to existing stochastic finite-fault model, the improved model considers the propagation law of phase spectrum, local site effect, and the impact of wave velocity on the arrival time of seismic waves. Besides, identification and statistics of model parameters are carried out based on ground motion records. Reasonable samples of stochastic ground motions are then obtained. In addition, parameter sensitivity analysis is conducted to determine critical random variables, which reduces the complexity of stochastic simulation. Simulation results are compared with recorded accelerograms from the 1999 Chi-Chi earthquake. It is shown that the improved stochastic finite-fault model is reliable, and the acceleration response spectra of simulated samples are consistent with those of station records collected at various site classes and the design spectra.

Parameter identification of transformer lumped element network model through genetic algorithm‐based gray‐box modelling technique

AbstractThe lumped element network model has been proven to be an efficient tool for the interpretation of transformer Frequency Response Analysis. However, it is challenging to obtain parameters of the model if transformer design information is unavailable. In such a case, optimisation algorithms can be used for gray‐box model parameter estimation. A methodology is developed by the authors to establish a transformer network model without winding design data, and instead, end‐to‐end open circuit Frequency Response and other terminal test results are utilised; and Genetic Algorithm is applied to approximate the unknown parameters of the model. The modelling approach developed is independent of the unit number of the network model and therefore guarantees the accuracy of optimisation. Furthermore, it can deal with transformers with a complicated winding structure such as interleaved disc type winding. Two single windings, helical and interleaved disc type, and a single‐phase 144/13 kV 60 MVA transformer are used to demonstrate the method. FRA spectra produced by the best estimated gray‐box model and the corresponding white‐box model are compared. The main features in amplitude and phase spectra are well matched, with low values of Relative Standard Deviation, for both single windings and transformer. Estimated electrical parameters show a high consistency with reference values, which are calculated based on winding design data. This validates the methodology and gives confidence to apply grey‐box modelling for FRA interpretation.

Super-resolution imaging through scattering media based on improved triple correlation recursion and deterministic iterative estimation.

Iterative phase retrieval algorithms are commonly used in computational techniques and optimization methods to obtain the reconstruction of objects hidden behind opaque scattering media. However, these methods are susceptible to converging to incorrect local minima, and the calculation results tend to be unstable. In this paper, a triple-correlation-based super-resolution imaging (TCSI) framework is proposed to achieve single-shot imaging of unknown objects hidden behind the scattering medium. The amplitude spectrum of the object is obtained by a speckle correlation (SC) method. Iterative relaxation recursion (IRR) sufficiently extracts object information from the triple correlation (TC) of the speckle patterns, serving as the prior initial guess for the iterative estimation algorithm (IE) to obtain a deterministic phase spectrum. Blur correction (BC) is then applied to the diffraction-limited image to achieve super-resolution imaging. Experimental results demonstrate that the flexible framework could effectively overcome the influence of speckle resolution and outperform traditional methods in terms of performance. Our approach provides a basis for non-invasively visualizing various samples behind scattering media.

Enhancing structural illumination microscopy with hybrid CNN-transformer and dynamic frequency loss

Deep learning techniques have augmented structured illumination microscopy (SIM) imaging by employing convolutional neural networks (CNNs) for the super-resolution reconstruction of SIM images. However, due to the intrinsic shortcomings of CNNs, i.e. limited receptive field and inadaptability to input content, their reconstruction faithfulness and imaging resolution are limited. Recently, another class of neural backbone, Transformer, has shown complementary advantages to CNNs. To this end, this work aims to borrow the recent Transformers to enhance CNN-based SIM reconstruction, thereby fully unleashing the power of neural networks for SIM imaging. Concretely, we first experimentally explore the pros and cons of CNNs and Transformers for SIM reconstruction. Then, we propose a Hybrid CNN-Transformer (HCT) model, to inherit merits of the both. To further encourage the recovery of high frequencies down-modulated by patterned illumination, we also devise a dynamic frequency loss based on the phase spectrum information, helping models focus on hard frequencies adaptively. Experiments on diverse subcellular structures demonstrate that the proposed method can evidently boost SIM reconstruction performance, even under low-light conditions or with fewer raw frames.

Optimal Extraction and Separation of Europium and Samarium from Nitrate Medium Using Binary Mixture of Cyanex 572 and Tertiary Amine Extractants

ABSTRACT Extraction and separation of rare-earth elements (Eu(III) and Sm(III)) from nitrate solutions were studied using Cyanex 572 and Alamine 336 type extractants, as well as their binary mixtures in kerosene. Separate studies were carried out on the parameters that influence the extraction process. According to the slope analysis method, the composition of extracted species in the organic phase is [MNO3A2(HA)2][R3NH.NO3]2(Org). The mixture loading capacity towards Eu(III) and Sm(III), as well as the stripping of their loads from the organic phases, were also tested. After being treated with a NaOH solution, the stripped binary mixture was regenerated. The FT-IR spectra of the binary mixture organic phase, the organic phase loaded with metals, the stripped organic phase, and the regenerated organic phase were identified and compared. The separation method is based on a combined reduction-precipitation process in which europium is reduced to its bivalent state by commercial zinc metal, followed by the precipitation of its sparingly soluble europous sulphate. The developed method was used to separate a synthetic mixture of Eu(III) and Sm(III) from an analogous solution in nitrate medium to that expected from spent nuclear fuel leach liquor. Extraction and separation processes for Eu(III) and Sm(III) were detailed in a flowchart.

Exploring the behavior feature of complex trajectories of ships with Fourier transform processing: a case from fishing vessels

The significant uncertainty and complexity of vessels at sea poses challenges for regulatory bodies in the fishing industry. This paper presents a method for identifying fishing vessel trajectory characteristics involving the Fourier series transform. The model utilizes the Fourier series and Gaussian mixture clustering to address the complexity and uncertainty issues in fishing vessel trajectories. First, the vessel trajectories undergo a process of dimensionality expansion and projection along the temporal axis. The relationship between trajectories and complex plane projection was elucidated in this process. Second, a vessel trajectory identification model involving Fourier transformation was constructed. Subsequently, the phase spectrum was assigned binary values using differentiation, and the phase spectrum characteristics of the transformed trajectories through Fourier transformation were analyzed. Finally, six encoding formats for fishing vessel motion trajectories in phase spectrum encoding are introduced, along with the determination of uncertain vessel motion range through mixed Gaussian clustering. This method has been validated using a dataset comprising 7,000 fishing vessel trajectories collected from the Beidou satellite positioning system. The results demonstrate that the range of uncertain vessel motion was able to be obtained with the assistance of Gaussian mixture clustering, with an 80% probability position of approximately 1,000 m and a 50% probability position of around 2,000 m. Effective identification of fishing vessel operating and navigational states was achieved, leading to the determination of a safety distance for fishing vessels in the range of 1,000m–2,000 m. This research holds important reference value for fishery regulatory agencies in terms of supervising fishing vessels and maintaining a safe navigational distance.