Two-dimensional Spectra Research Articles

Application of wavelet transform in anti-Compton phoswich detector for gamma spectrum

The response of an anti-Compton phoswich detector to gamma rays was investigated using Monte-Carlo method, and the pulses from different crystal cases, including gamma deposition only in the LaBr3(Ce) or CsI(Tl) crystal and coincidence in both crystals, were analyzed. A novel pulse discrimination method for gamma deposition events based on wavelet transform analysis, called SSD (Scale Shape Discrimination), was developed in this study. Compared to the traditional PSD (Pulse Shape Discrimination) method, SSD has the advantage of transforming one-dimensional pulses in the time-domain into two-dimensional time-frequency spectra, providing the more useful features for pulse discrimination. The performances of the Compton suppression and Full-energy peak loss using PSD and SSD methods was studied. The results show that the Compton suppression factor IPSD = 5.12 and ISSD = 5.32, and FEP loss factor PLPSD = 0.0554 and PLSSD = 0.0587. Meanwhile, the influences of the cutoff values for pulse discrimination on the results of I and PL with different method were analyzed.

FT-Raman and FTIR spectroscopy as a tools showing marker of platinum-resistant phenomena in women suffering from ovarian cancer

Platinum-resistant phenomena in ovarian cancer is very dangerous for women suffering from this disease, because reduces the chances of complete recovery. Unfortunately, until now there are no methods to verify whether a woman with ovarian cancer is platinum-resistant. Importantly, histopathology images also were not shown differences in the ovarian cancer between platinum-resistant and platinum-sensitive tissues. Therefore, in this study, Fourier Transform InfraRed (FTIR) and FT-Raman spectroscopy techniques were used to find chemical differences between platinum-resistant and platinum-sensitive ovarian cancer tissues. Furthermore, Principal Component Analysis (PCA) and machine learning methods were performed to show if it possible to differentiate these two kind of tissues as well as to propose spectroscopy marker of platinum-resistant. Indeed, obtained results showed, that in platinum-resistant ovarian cancer tissues higher amount of phospholipids, proteins and lipids were visible, however when the ratio between intensities of peaks at 1637 cm−1 (FTIR) and at 2944 cm−1 (Raman) and every peaks in spectra was calculated, difference between groups of samples were not noticed. Moreover, structural changes visible as a shift of peaks were noticed for C–O–C, C–H bending and amide II bonds. PCA clearly showed, that PC1 can be used to differentiate platinum-resistant and platinum-sensitive ovarian cancer tissues, while two-trace two-dimensional correlation spectra (2T2D-COS) showed, that only in amide II, amide I and asymmetric CH lipids vibrations correlation between two analyzed types of tissues were noticed. Finally, machine learning algorithms showed, that values of accuracy, sensitivity and specificity were near to 100% for FTIR and around 95% for FT-Raman spectroscopy. Using decision tree peaks at 1777 cm−1, 2974 cm−1 (FTIR) and 1714 cm−1, 2817 cm−1 (FT-Raman) were proposed as spectroscopy marker of platinum-resistant.

Accurate Range Modeling for High-Resolution Spaceborne Synthetic Aperture Radar.

Spaceborne synthetic aperture radar (SAR) is an advanced microwave imaging technology that provides all-weather and all-day target information. However, as spaceborne SAR resolution improves, traditional echo signal models based on airborne SAR design become inadequate due to the curved orbit, Earth rotation, and increased propagation distance. In this study, we propose an accurate range model for high-resolution spaceborne SAR by analyzing motion trajectory and Doppler parameters from the perspective of the space geometry of spaceborne SAR. We evaluate the accuracy of existing range models and propose an advanced equivalent squint range model (AESRM) that accurately fits the actual range history and compensates for high-order term errors by introducing third-order and fourth-order error terms while maintaining the simplicity of the traditional model. The proposed AESRM's concise two-dimensional frequency spectrum form facilitates the design of imaging algorithms. Point target simulations confirm the effectiveness of the proposed AESRM, demonstrating significant improvements in fitting accuracy for range histories characterized by nonlinear trajectories. The developed AESRM provides a robust foundation for designing imaging algorithms and enables higher resolution and more accurate radar imaging.

Theory of 2D electronic spectroscopy of water soluble chlorophyll-binding protein (WSCP): Signatures of Chl b derivate.

We investigate how electronic excitations and subsequent dissipative dynamics in the water soluble chlorophyll-binding protein (WSCP) are connected to features in two-dimensional (2D) electronic spectra, thereby comparing results from our theoretical approach with experimental data from the literature. Our calculations rely on third-order response functions, which we derived from a second-order cumulant expansion of the dissipative dynamics involving the partial ordering prescription, assuming a fast vibrational relaxation in the potential energy surfaces of excitons. Depending on whether the WSCP complex containing a tetrameric arrangement of pigments composed of two dimers with weak excitonic coupling between them binds the chlorophyll variant Chl a or Chl b, the resulting linear absorption and circular dichroism spectra and particularly the 2D spectra exhibit substantial differences in line shapes. These differences between Chl a WSCP and Chl b WSCP cannot be explained by the slightly modified excitonic couplings within the two variants. In the case of Chl a WSCP, the assumption of equivalent dimer subunits facilitates a reproduction of substantial features from the experiment by the calculations. In contrast, for Chl b WSCP, we have to assume that the sample, in addition to Chl b dimers, contains a small but distinct fraction of chemically modified Chl b pigments. The existence of such Chl b derivates has been proposed by Pieper et al. [J. Phys. Chem. B 115, 4042 (2011)] based on low-temperature absorption and hole-burning spectroscopy. Here, we provide independent evidence.

Relaxation Editing in NMR Using a New Two-Dimensional Long-Lived Coherence Method for Mixture Analysis.

The exploration of metabolomics and targeted segments of proteins stands as a pivotal facet of Nuclear Magnetic Resonance (NMR) analysis, furnishing valuable insights into molecular architectures and potential therapeutic applications. The issue of spectral congestion frequently presents challenges in ascribing distinct peaks within the confines of both one-dimensional (1D) and two-dimensional (2D) NMR spectra. Numerous strategies have been proposed to resolve specific resonances in NMR spectra differentially. Among these approaches, relaxation editing emerges as a viable solution. In the realm of relaxation phenomena within NMR, Long-Lived States (LLS) and Long-Lived Coherences (LLC) manifest as promising phenomena, offering enhanced relaxation lifetimes in comparison to the traditional longitudinal (T1) and transverse (T2) relaxation times for coupled nuclear spins. Notably, LLC presents a pathway to attenuate uncoupled high-intensity peaks, effectively diminishing their impact. The foundation of this technique rests upon the premise that the relaxation lifetime in the rotating frame (T1ρ) remains smaller than TLLC. In pursuit of refining spectral assignments within complex mixtures, we introduce a new pulse sequence tailored for LLC Total Correlation Spectroscopy (LLC-TOCSY). This demonstrates efficacy in extracting LLC signals within configurations involving multiple coupled spins, thereby decluttering the spectrum and enhancing the accuracy of peak assignments. To validate the effectiveness of this method, a collection of samples was subjected to scrutiny, yielding compelling results.

A Joint Inversion Method Algorithm for T2-Pc two Dimensional NMR based on Logistic Functions

Data processing is a key step in the analysis of nuclear magnetic resonance (NMR) experimental data, and efficient and accurate computer inversion algorithms are the core of the T2-Pc two-dimensional NMR experiment. T2-Pc two-dimensional NMR experiment is an advanced experimental method that characterizes reservoir connectivity through two dimensions: relaxation time and capillary pressure, and can obtain irreducible water saturation under different pressure differences. However, the algorithm currently used for T2-Pc two-dimensional spectrum inversion uses a mutation kernel function, resulting in low accuracy of calculation results. This paper uses the Logistic function as the two-dimensional inversion kernel function, rewrites the inversion algorithm, and obtains more accurate inversion results. Numerical simulations have proven that the T2-Pc two-dimensional map obtained by this method not only has higher resolution, but also has greater applicability in the case of low signal-to-noise ratio and a small number of centrifugal echo groups. Practice has found that the proposed method can reduce the number of centrifugations during the experiment and significantly improve the efficiency of T2-Pc two-dimensional nuclear magnetic resonance experiments.

Boundary Effects Cause False Signals of Range Expansions in Population Genomic Data.

Studying range expansions is central for understanding genetic variation through space and time as well as for identifying refugia and biological invasions. Range expansions are characterized by serial founder events causing clines of decreasing genetic diversity away from the center of origin and asymmetries in the two-dimensional allele frequency spectra. These asymmetries, summarized by the directionality index (ψ), are sensitive to range expansions and persist for longer than clines in genetic diversity. In continuous and finite meta-populations, genetic drift tends to be stronger at the edges of the species distribution in equilibrium populations and populations undergoing range expansions alike. Such boundary effects are expected to affect geographic patterns in genetic diversity and ψ. Here we demonstrate that boundary effects cause high false positive rates in equilibrium meta-populations when testing for range expansions. In the simulations, the absolute value of ψ (|ψ|) in equilibrium data sets was proportional to the fixation index (FST). By fitting signatures of range expansions as a function of ɛ |ψ|/FST and geographic clines in ψ, strong evidence for range expansions could be detected in data from a recent rapid invasion of the cane toad, Rhinella marina, in Australia, but not in 28 previously published empirical data sets from Australian scincid lizards that were significant for the standard range expansion tests. Thus, while clinal variation in ψ is still the most sensitive statistic to range expansions, to detect true signatures of range expansions in natural populations, its magnitude needs to be considered in relation to the overall levels of genetic structuring in the data.

Two-dimensional spectrum characteristics and oil movability study of the shale oil reservoir

Shale oil is mainly stored in the nano–micro-pores of shale in the form of adsorption or in a free state. Among them, only free-state oil is the main contributor to shale oil production under natural elastic energy. Therefore, it is crucial to evaluate the movability of crude oil effectively. In this paper, focusing on the Jurassic shale oil reservoir core in the middle-eastern Sichuan region of China, low-field nuclear magnetic resonance (NMR) technology is used to analyze the basic characteristics of shale oil core samples. Experiments on the low-field NMR one-dimensional and two-dimensional spectrum characteristics of the original core, heat-treated core, and thermogravimetric-treated shale core are carried out. The effects of the TG-MS method, T2 method, and the volatilization of light oil components on the movability of shale oil reservoirs are analyzed, and the movability characteristics of shale oil reservoirs in the middle-eastern Sichuan region are preliminarily clarified. The results show that under thermal treatment, the distribution range of the two-dimensional spectrum of the core oil occurrence area is significantly reduced, and the T1 and T2 distribution ranges are reduced by 10.9% and 60.7%, respectively. According to the TG-MS method, the mobile oil, bound oil, and adsorbed oil account for 74.7%, 8.1%, and 17.2%, respectively. The quantitative calculation of movable oil saturation by NMR combined with heat treatment is 65.6%, which is lower than that calculated using the thermogravimetric method. In order to calculate the movability more accurately, the scale effect between different samples should be considered. This study could provide a theoretical basis for the subsequent shale oil development program.

Two-dimensional nonlinear spectroscopy in the extreme ultraviolet to study dynamics of atomic and molecular gases

We present a two-dimensional (2D) nonlinear four-wave mixing scheme in the extreme ultraviolet (XUV) to investigate ultrafast electronic wave-packets dynamics of multi-electron states in the above-threshold ionization region, using atomic argon and molecular nitrogen as examples. Coherent light sources in the range between 24 and 45 eV is generated by phase-matched cascaded four-wave mixing processes with a collinear configuration of laser fields 800 nm and 1400 nm. Motion of the electrons involving the excited states 3s3p6np (1P10) of argon gas, theF2Σg+ state and the predissociation state C2Σu+ of molecular nitrogen ion N2+ are unravelled through the ‘on-axis’ and ‘off-axis’ features of the two-dimensional spectra. Interpretation of the experimental data is supported by a theoretical dipole control model. Hence, results of this study may be promising for studies of dynamics of electrons in more complex systems.

Impact of astrophysical effects on the dark matter mass constraint with 21 cm intensity mapping

ABSTRACT We present an innovative approach to constraining the non-cold dark matter model using a convolutional neural network (CNN). We perform a suite of hydrodynamic simulations with varying dark matter particle masses and generate mock 21 cm radio intensity maps to trace the dark matter distribution at z = 3 in the postreionization epoch. Our proposed method complements the traditional power-spectrum analysis. We compare the results of the CNN classification between the mock maps with different dark matter masses with those from the two-dimensional power spectrum of the differential brightness temperature map of 21 cm radiation. We find that the CNN outperforms the power spectrum. Moreover, we investigate the impact of baryonic physics on the dark matter model constraint, including star formation, self-shielding of H i gas, and ultraviolet background model. We find that these effects may introduce some contamination in the dark matter constraint, but they are insignificant compared to the system noise of the SKA instruments.

Structuring restricted amorphous molecular chains in the reinforced cellulose film by uniaxial stretching

The construction of the preferred orientation structure by stretching is an efficient strategy to fabricate high-performance cellulose film and it is still an open issue whether crystalline structure or amorphous molecular chain is the key factor in determining the enhanced mechanical performance. Herein, uniaxial stretching with constant width followed by drying in a stretching state was carried out to cellulose hydrogels with physical and chemical double cross-linking networks, achieving high-performance regenerated cellulose films (RCFs) with an impressive tensile strength of 154.5 MPa and an elastic modulus of 5.4 GPa. The hierarchical structure of RCFs during uniaxial stretching and drying was systematically characterized from micro- to nanoscale, including microscopic morphology, crystalline structure as well as relaxation behavior at a molecular level. The two-dimensional correlation spectra of dynamic mechanical analysis and Havriliak-Negami fitting results verified that the enhanced mechanical properties of RCFs were mainly attributed to the stretch-induced tight packing and restricted relaxation of amorphous molecular chains. The new insight concerning the contribution of molecular chains in the amorphous region to the enhancement of mechanical performance for RCFs is expected to provide valuable guidance for designing and fabricating high-performance eco-friendly cellulose-based films.

Observation of Dark States in Two-Dimensional Electronic Spectra of Chlorosomes.

Observations of low-lying dark states in several photosynthetic complexes challenge our understanding of the mechanisms behind their efficient energy transfer processes. Computational models are necessary for providing novel insights into the nature and function of dark states, especially since these are not directly accessible in spectroscopy experiments. Here, we will focus on signatures of dark-type states in chlorosomes, a light-harvesting complex from green sulfur bacteria well-known for uniting a broad absorption band with very efficient energy transfer. In agreement with experiments, our simulations of two-dimensional electronic spectra capture the ultrafast exciton transfer occurring in 100s of femtoseconds within a single chlorosome cylinder. The sub-100 fs process corresponds to relaxation within the single-excitation manifold in a single chlorosome tube, where all initially created populations in the bright exciton states are quickly transferred to dark-type exciton states. Structural inhomogeneities on the local scale cause a redistribution of the oscillator strength, leading to the emergence of these dark-type exciton states, which dominate ultrafast energy transfer. The presence of the dark-type exciton states suppresses energy loss from an isolated chlorosome via fluorescence quenching, as observed experimentally. Our results further question whether relaxation to dark-exciton states is a leading process or merely competes with transfer to the baseplate within the photosynthetic apparatus of green sulfur bacteria.

Rapid simulation of two-dimensional spectra with correlated anisotropic dimensions.

A new algorithm has been developed to simulate two-dimensional (2D) spectra with correlated anisotropic frequencies faster and more accurately than previous methods. The technique uses finite-element numerical integration on the sphere and an interpolation scheme based on the Alderman-Solum-Grant algorithm. This method is particularly useful for numerical calculations of joint probability distribution functions involving quantities with a parametric orientation dependence. The technique's efficiency also allows for practical least-squares fitting of experimental 2D solid-state nuclear magnetic resonance (NMR) datasets. The simulation method is illustrated for select 2D NMR methods, and a least-squares analysis is demonstrated in the extraction of paramagnetic shift and quadrupolar coupling tensors and their relative orientation from the experimental shifting-d echo 2H NMR spectrum of a NiCl2 · 2D2O salt.

Universality of spectral fluctuations in open quantum chaotic systems

Quantum chaotic systems with one-dimensional spectra follow spectral correlations of Orthogonal (OE), Unitary (UE), or Symplectic Ensembles (SE) of random matrices depending on their invariance under time reversal and rotation. In this letter, we study the non-Hermitian and non-unitary ensembles based on the symmetry of matrix elements, viz. ensemble of complex symmetric, complex asymmetric (Ginibre), and self-dual matrices of complex quaternions. The eigenvalues for these ensembles lie in the two-dimensional plane. We show that the fluctuation statistics of these ensembles are universal and quantum chaotic systems belonging to OE, UE, and SE in the presence of a dissipative environment show similar spectral fluctuations. The short-range correlations are studied using spacing ratio and spacing distribution. For long-range correlations, unfolding at a non-local scale is crucial. We describe a generic method to unfold the two-dimensional spectra with non-uniform density and evaluate correlations using number variance. We find that both short-range and long-range correlations are universal. We verify our results with the quantum kicked top in a dissipative environment that can be tuned to exhibit symmetries of OE, UE, and SE in its conservative limit.

Effect of MnO2-biochar composites on promoting humification during chicken manure composting

The present study aimed to accelerate the humification and to investigate how MnO2 modification of biochar (MBC) drives the humus formation during composting with chicken manure. In this study, compared with the control group (CK), the addition of MBC caused an increase in the concentration of both humus and humic acid (HA), with a respective enhancement of 29.1% and 37.2%. In addition, MBC also improved the stability of compost products. Hetero two-dimensional correlation spectra further exhibited that the MBC could alter the formation mechanism of humus fractions during composting. Random forest analysis showed that Microbacterium, Bacteroides, Kroppenstedtia, Gracilibacillus, and Lentibacillus were significantly related to humus formation (P < 0.05). MBC enhanced the absolute abundance of these five genera during composting. The structural equation model further confirmed that these five genera could be indirectly involved in humus formation, through the production of aromatic compounds via secondary metabolism. Additionally, these five genera could directly transform organic components into macromolecular humus structures. Therefore, the increase in these five genera might be a direct response to the acceleration of the humification during MBC composting. These findings demonstrate the potential value of MBC in harmless disposal of hazardous biowastes through composting.HighlightsMnO2 modification of biochar changed the formation mechanism of humus fractions.Key genera involved in humus formation were identified.Among of MnO2 modification of biochar, key genera and humus formation were revealed.Graphical

Identifying Exchangeable Protons in a 1D NMR Spectrum by Spatially Selective Exchange-Editing.

Signals undergoing chemical or conformational exchange in one-dimensional NMR spectra are often identified by deuterium exchange. In order to obtain quantitative information about the dynamic processes involved, one frequently used method is EXchange SpectroscopY (EXSY). To detect all exchange processes, the EXSY experiment requires the acquisition of time-consuming two-dimensional spectra. Here we report a faster alternative, an experiment which uses spatial encoding to extract similar information in a 1D exchange-edited experiment. Thereby, all protons are observed at once, but in different slices of the detection volume. The experiment can be carried out in a single scan to identify exchanging sites in a 1D spectrum by changes in signal intensity indicating exchange processes. If the exchanging partner, for example water is in molar excess the exchange-editing method easily identifies mobile protons by negative signals in the 1D 1H NMR spectrum.

Characterization of Orbital Angular Momentum Beams by Polar Mapping and Fourier Transform

The recognition, decoding and tracking of vortex patterns is of increasing importance in many fields, ranging from the astronomical observations of distant galaxies to turbulence phenomena in liquids or gases. Currently, coherent light beams with orbital angular momentum (OAM) are of particular interest for optical communication, metrology, micro-machining or particle manipulation. One common task is to identify characteristic spiral patterns in pixelated intensity maps at real-world signal-to-noise ratios. A recently introduced combination of polar mapping and Fast Fourier Transform (FFT) was extended to novel sampling configurations and applied to the quantitative analysis of the spiral interference patterns of OAM beams. It is demonstrated that specific information on topological parameters in non-uniform arrays of OAM beams can be obtained from significantly distorted and noisy intensity maps by extracting one- or two-dimensional angular frequency spectra from single or concatenated circular cuts in either spatially fixed or scanning mode. The method also enables the evaluation of the quality of beam shaping and optical transmission. Results of proof-of-principle experiments are presented, resolution limits are discussed, and the potential for applications is addressed.

An Improved NLCS Algorithm Based on Series Reversion and Elliptical Model Using Geosynchronous Spaceborne–Airborne UHF UWB Bistatic SAR for Oceanic Scene Imaging

Geosynchronous spaceborne–airborne (GEO-SA) ultra-high-frequency ultra-wideband bistatic synthetic aperture radar (UHF UWB BiSAR) provides high-precision images for marine and polar environments, which are pivotal in glacier monitoring and sea ice thickness measurement for polar ocean mapping and navigation. Contrasting with traditional high-frequency BiSAR, it faces unique challenges, such as the considerable spatial variability, significant range–azimuth coupling, and vast volumes of echo data, which impede high-resolution image reconstruction. This paper presents an improved bistatic nonlinear chirp scaling (NLCS) algorithm for imaging oceanic scenes with GEO-SA UHF UWB BiSAR. This methodology extends the two-dimensional (2-D) spectrum up to the sixth order via the method of series reversion (MSR) to meet accuracy demands and then employs an elliptical model to elucidate the alterations in the azimuth frequency modulation (FM) rate mismatch. Initially, the imaging geometry and signal model are introduced, and then a separation of bistatic slant ranges based on the configuration is proposed. In addition, during range processing, after eliminating linear range cell migration (RCM), the derivation process for the sixth-order 2-D spectrum is detailed and an improved filter is applied to correct the high-order RCM. Finally, during azimuth processing, the causes of the FM rate mismatch are analyzed, a cubic perturbation function derived from the elliptical model is used for FM rate equalization, and a unified sixth-order filter is applied to complete the azimuth compression. Experimental results with point targets and natural oceanic scenes validate the outstanding efficacy of the proposed NLCS algorithm, particularly in imaging quality enhancements for GEO-SA UHF UWB BiSAR.

Two dimensional parallel sequence spread spectrum for wireless communications

A novel two-dimensional parallel sequence spread spectrum (2D-PSSS) structure for the physical layer of wireless communication systems is introduced. The proposed 2D-PSSS system partitions a data block into two groups of bits, representing the two dimensions. The first dimension represents the selected code from a predefined set of Gold codes. While the second dimension determines a shift value applied to the chosen code. The shifted Gold code will represent the data block. By design, the 2D-PSSS system overcomes the challenge of inter-code interference encountered in conventional PSSS systems without introducing additional computational complexity. Moreover, the 2D-PSSS system offers reduced encoder computational complexity compared to PSSS systems, enhancing its suitability for a wide range of wireless communication applications. The performance of the 2D-PSSS system in terms of bit error rate has been evaluated in additive white Gaussian noise (AWGN) channel and under different fading channel conditions.

Optimal Configuration of Omega-Kappa FF-SAR Processing for Specular and Non-Specular Targets in Altimetric Data: The Sentinel-6 Michael Freilich Study Case

In this study, the full-focusing (FF) algorithm is reviewed with the objective of optimizing it for processing data from different types of surfaces probed in altimetry. In particular, this work aims to provide a set of optimal FF processing parameters for the Sentinel-6 Michael Freilich (S6-MF) mission. The S6-MF satellite carries an advanced radar altimeter offering a wide range of potential FF-based applications which are just beginning to be explored and require prior optimization of this processing. In S6-MF, the Synthetic Aperture Radar (SAR) altimeter acquisitions are known to be aliased in the along-track direction. Depending on the target, aliasing can be tolerated or may be a severe impairment to provide the level of performance expected from FF processing. Another key aspect to consider in this optimization study is the unprecedented resolution of the FF processing, which results in a higher posting rate than the standard SAR processing. This work investigates the relationship between posting rate and noise levels and provides recommendations for optimal algorithm configurations in various scenarios, including transponder, open ocean, and specular targets like sea-ice and inland water scenes. The Omega–Kappa (WK) algorithm, which has demonstrated superior CPU efficiency compared to the back-projection (BP) algorithm, is considered for this study. But, unlike BP, it operates in the Doppler frequency domain, necessitating further precise spectral and time domain settings. Based on the results of this work, real case studies using S6-MF acquisitions are presented. We first compare S6-MF FF radargrams with Sentinel-1 (S1) images to showcase the potential of optimally configured FF processing. For highly specular surfaces such as sea-ice, distinct techniques are employed for lead signature identification. S1 relies on image-based lineic reconstruction, while S6-MF utilizes phase coherency of focalized pulses for lead detection. The study also delves into two-dimensional wave spectra derived from the amplitude modulation of image/radargrams, with a focus on a coastal example. This case is especially intriguing, as it vividly illustrates different sea states characterized by varying spectral peak positions over time.