Spectral Method Research Articles

2,4-dichloro-6-(1,4,5-triphenyl-1H-imidazol-2-yl) phenol: synthesis, DFT analysis, Molecular docking, molecular dynamics, ADMET properties against COVID-19 main protease (Mpro: 6WCF/6Y84/6LU7)

ABSTRACT New derivatives of 2,4-dichloro-6-(1,4,5-triphenyl-1H-imidazol-2-yl) phenol (DPIP) have been successfully synthesised and characterised using spectral methods such as FT-IR, 1H NMR and 13C NMR. Density functional theory (DFT) approach at B3LYP/6-311 G (d, p) level of theory is used to determine optimised bond parameters and single crystal XRD investigation of related derivatives confirms the structure of DPIP bond parameters. The single crystal XRD measurements and the optimised geometrical parameters produced by the DFT calculation agree well. The FT-IR bands seen in the experiment were attributed to distinct normal modes of the molecule. Frontier molecular orbital computations described the molecule stability, chemical reactivity and charge transfer. Atomic charges determined via Mulliken population analysis on the different DPIP atoms. MEP, which is mapped to the electron density surfaces, has discovered potential reactive sites of the molecule. The reported molecule is used as a potential NLO material since it has a high μβ0 value. Binding affinities were discovered using molecular docking against the COVID-19 major protease (Mpro: 6WCF/6Y84/6LU7). The behaviour of the complex structure formed by the Covid-19 protein under in silico physiological conditions was then confirmed by a 100 ns molecular dynamic simulation which looked at the structure stability over time and revealed a stable conformation and binding pattern in an environment of imidazole derivatives. Furthermore, favourable to moderate anti-viral activity was revealed by an in-silico analysis that anticipated the compound absorption, distribution, metabolism, excretion and toxicity profiles (ADMET).

Spectral Galerkin mode-matching method for applications in photonics

Spectral Galerkin mode-matching method for applications in photonics

Efficient function approximation in enriched approximation spaces

Abstract An enriched approximation space is the span of a conventional basis with a few extra functions included, for example to capture known features of the solution to a computational problem. Adding functions to a basis makes it overcomplete and, consequently, the corresponding discretized approximation problem may require solving an ill-conditioned system. Recent research indicates that these systems can still provide highly accurate numerical approximations under reasonable conditions. In this paper we propose an efficient algorithm to compute such approximations. It is based on the AZ algorithm for overcomplete sets and frames, which simplifies in the case of an enriched basis. In addition, analysis of the original AZ algorithm and of the proposed variant gives constructive insights on how to achieve optimal and stable discretizations using enriched bases. We apply the algorithm to examples of enriched approximation spaces in literature, including a few nonstandard approximation problems and an enriched spectral method for a 2D boundary value problem, and show that the simplified AZ algorithm is indeed stable, accurate and efficient.

Using satellite image data to identify rice varieties through linear spectral unmixing method (case study: Karangjati Sub District, Ngawi Regency)

<p>Remote sensing technology has increasingly emerged as a potent tool for precision agriculture, particularly in facilitating the mapping and monitoring of crops on a large scale. An application of this technology is the identification of different types of rice by analyzing the pixels acquired in satellite images. Regrettably, the pixels in the image have been mixed from different recorded items. Therefore, they have the potential to influence the outcome of the identification. An effective approach to address this problem is to employ the linear spectral unmixing (LSU) technique. The LSU approach quantifies the ratio of pure objects in every pixel of an image by utilizing the spectral value associated with the endmember of the rice variety. The investigation was carried out in the Karangjati District during the generative stage (70 ± DAP) of the rice planting season. The data indicates that the dominant variety is Inpari 32 HDB. The data validation tests, which involved the use of a confusion matrix and Kappa analysis, resulted in an overall accuracy rate of 85.48% and a Kappa analysis score of 70.6%.<strong></strong></p>

Turbulent Rayleigh–Bénard convection in a supercritical [formula omitted]-based binary mixture with cross-diffusion effects

CO2-based binary mixtures are promising in energy engineering to improve efficiencies of thermodynamic cycles where supercritical CO2 prevails. Indeed, under supercritical pressure and transcritical temperature conditions, special thermophysical properties of binary mixtures make the heat transfer process accompanied by enhanced cross-diffusion effects, i.e., the Soret effect and the Dufour effect. Their influences on heat transfer have not been well understood yet. This paper numerically investigates turbulent Rayleigh–Bénard convection in CO2-C2H6 binary mixture. Calculations are performed based on a spectral element method solver considering various temperature differences and pressures. Results indicate that the flow field presents a double-vortex structure. The thickness of the boundary layer is negatively correlated with the flow intensity. Under a positive separation ratio, the concentration gradient induced by cross-diffusion effects enhances buoyancy, which in turn reinforces the natural convection and heat transfer. The enhancement becomes stronger as the critical pressure is approached. Turbulent fluctuations are also strengthened by cross-diffusion effects, except for temperature fluctuations. The unusual reduction in temperature fluctuations is attributed to the increased size of the thermal plume caused by the Dufour effect.

A Machine-Learning-Assisted Classification Algorithm for the Detection of Archaeological Proxies (Cropmarks) Based on Reflectance Signatures

The detection of subsurface archaeological remains using a range of remote sensing methods poses several challenges. Recent studies regarding the detection of archaeological proxies like those of cropmarks highlight the complexity of the phenomenon. In this work, we present three different methods, and associated indices, for identifying stressed reflectance signatures indicating buried archaeological remains, based on a dataset of measured ground spectroradiometric reflectance. Several spectral profiles between the visible and near-infrared parts of the spectrum were taken in a controlled environment in Cyprus during 2011–2012 and are re-used in this study. The first two (spectral) methods are based on a suitable analysis of the spectral signatures in (1) the visible part of the spectrum, in particular in the neighborhood of 570 nm, and (2) the red edge part of the spectrum, in the neighborhood of 730 nm. Machine learning (decision trees) allows for the deduction of suitable wavelengths to focus on in order to formulate the proposed indices and the associated classification criteria (decision boundaries) that can enhance the detection probability of stressed vegetation. Noise in the signal is taken into account by simulating reflectance signatures perturbed by white noise. Applying decision tree classification on the ensemble of simulations and basic statistical analysis, we refine the formulation of the indices and criteria for the noisy signatures. The success rate of the proposed methods is over 90%. The third method rests on the estimation of vegetation/canopy reflectance parameters through inversion of the physical-based PROSAIL reflectance model and the associated classification through machine learning methods. The obtained results provide further insights into the formation of stress vegetation that occurred due to the presence of shallow buried archaeological remains, which are well aligned with physical-based models and existing empirical knowledge. To the best of the authors’ knowledge, this is the first study demonstrating the usefulness of radiative transfer models such as PROSAIL for understanding the formation of cropmarks. Similar studies can support future research directions towards the development of regional remote sensing methods and algorithms if systematic observations are adequately dispersed in space and time.

Differentiation of Polygonatum Cyrtonema Hua from Different Geographical Origins by near-Infrared Spectroscopy with Chemometrics.

The identification of the geographical origin of Polygonatum cyrtonema Hua is of particular importance because the quality and market value of Polygonatum cyrtonema Hua from different production areas are highly variable due to differences in the growing environment and climatic conditions. This study utilized near-infrared spectra (NIR) of Polygonatum cyrtonema Hua (n = 400) to develop qualitative models for effective differentiation of Polygonatum cyrtonema Hua from various regions. The models were produced under different conditions to distinguish the origins distinctly. Ten pre-processing methods have been used to pre-process the original spectra (OS) and to select the most optimal spectral pre-processing method. Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were employed to determine appropriate models. For simplicity, the pretreated full spectrum was calculated by different wavelength selection methods, and the four most significant variables were selected as discriminant indicator variables. The results show that Polygonatum cyrtonema Hua from different regions can be effectively distinguished using spectra from a series of samples analyzed by OPLS-DA. The accuracy of the OPLS-DA model is also satisfactory, with a good differentiation rate. The study findings indicate the feasibility of using spectroscopy in combination with multivariate analysis to identify the geographical origins of Polygonatum cyrtonema Hua. The utilization of near-infrared spectroscopy combined with chemometrics exhibits high efficacy in discerning the provenance of herbal medicines and foods, thereby facilitating quality assurance measures.

Comparison of the cytotoxicity and zebrafish embryo toxicity of insect repellent ingredients: p-Menthane-3,8-diol synthesized by green chemistry from Eucalyptus citriodora and N,N-diethyl-meta-toluamide

Bio-sourced insect repellents are becoming more popular due to their safer applications. Known for its strong fly-repellent property, Cis, trans-para-menthane-3,8-diol (PMD) is the main component of the lemon eucalyptus essential oil and is synthesized from citronellal. In April 2005, US Centers for Disease Control approved two fly repellents that do not contain N,N-diethyl-meta-toluamide (DEET), including PMD. Due to the intentional and pervasive human exposure caused by DEET as insect repellent, concerns have been raised about its toxicological profile and potential harm to people. We hypothesized PMD would have a different toxicological profile than DEET. We synthesized PMD from Eucalyptus citriodora using green chemistry methods and analyzed its structures by 1H-NMR,13C-NMR, and GC/MS spectral methods. We used MTS assay to determine the percentage inhibition of PMD and DEET on keratinocyte (human epidermal keratinocyte [HaCaT]) cells. The xCelligence system was used and followed at real time. Effects of PMD and DEET on zebrafish embryo development were monitored and levels of lipid peroxidation, glutathione-S-transferase (GST), superoxide dismutase (SOD), and acetylcholinesterase (AchE) were evaluated at 72 h post-fertilization using spectrophotometric methods. Our results showed that while DEET inhibited human keratinocyte cell growth, while imporved cell viability and proliferation was exposed in PMD exposed group. In zebrafish embryos, PMD was less toxic in terms of development, oxidant-antioxidant status, and AChE activities than DEET. Based on these results we suggest an efficient method using green chemistry for the synthesis of PMD, which is found to be less toxic in zebrafish embryos and human keratinocyte cells.

Overview on Spectral Analysis Techniques for Gamma Ray Spectrometry

Gamma-ray spectrometry (GRS) is an exploration technology that distinguishes itself from other non-contact sensing technologies because it provides information from 30 to 50 cm below the ground. This technology has evolved through three significant turning points in mapping output. The first turning point, in the 1960s-1970s, was the transition from U concentration maps to weathered zoning maps utilizing K or eTh. The second turning point, occurring from the 1980s to 1990s, was marked by the application of radionuclide mapping to assess radioactive contamination. A third turning point, in the early 2000s, was the development of soil maps for precision agriculture, supported by the free statistics software R. This paper reviews advances in gamma-ray spectrometry spectral analysis since 2000. Traditionally, the gamma-ray spectrum is depicted as a two-dimensional graph with energy on the horizontal axis and counts on the vertical axis. The NASVD and MNF methods, developed around 2000, necessitate a reevaluation of this concept. By conducting principal component analysis of the gamma-ray spectrum in hyperspace, these techniques have unveiled new spectra, such as ground and sky spectra, and have facilitated the removal of noise components from the gamma-ray spectrum. Naturally occurring gamma-ray spectra typically exhibit energies ranging from 0.04 to 3 MeV. Observations from fusion reactors measure energies up to 20 MeV for diagnostics of nuclear plasma. These spectra may yield valuable insights when applied to innovative statistical analysis techniques. A comprehensive spectral analysis method developed in the early 2000s has demonstrated the potential to extract a variety of information beyond window nuclides, previously unexplored. The regression coefficient plots from the PLSR regression model have revealed novel spectral images. This model is set to influence future research on GRS by expanding the number of objectives and covariates. The innovative calibration method for full-spectrum analysis, which assesses different concentration areas, has proven that calibration is achievable even in the absence of a calibration pad. It is expected to become a formidable approach for spectrum analysis in the upcoming period.

Curie point depth, thermal gradient and heat flow along the Ethiopia Rift System and adjacent plateaus using spectral evaluation approach: implications for geothermal resources

The Ethiopia Rift System (ERS) is a section of the East African Rift System within Ethiopia extending from the Afar in the northeast to the Kenya border in the southwest. It is apparent that magmatism and magmatic intrusions influence the crustal shape in the ERS resulting in its thinning and the shallowing of magmatic sources at various locations within it. As a consequence, more than 31 volcanoes hosting hydrothermal structures with a conceivable potential to generate massive quantities of geothermal energy have been identified along the ERS. In this study, we map the Curie Point Depth (CDP) over the ERS based on the analysis of aeromagnetic data extracted from the World Digital Magnetic Anomaly Map. Spectral evaluation method was used to estimate the boundaries (top and bottom) of the magnetized crust. Reduced-to-pole (RTP) aeromagnetic records have been divided into 105 (50% overlap) square blocks of 200 × 200 km size. The Curie temperature (580 °C) of magnetite was used to determine the thermal gradient and the heat drift in the area. The depths obtained for the bottom of the magnetized crust are assumed to correspond to the Curie Depths, where the magnetic layer loses all its magnetization. The determined values of Curie Point Depth, geothermal gradient and heat flow for the 50% overlapped 105 blocks, respectively, range from 8.85 to 55.85 km, 10.38 to 65.54 °C/km and 25.96 to 163.84 mW/m2. Lower CPD (< 20 km) in the ERS was obtained between Mille and Gewane (southwest Afar), between Adama (Nazret) and Yerer (NMER) and between Wendo Genet and Koti (SMER) localities. These areas, showing low CPD, exhibit excessive geothermal gradient and high heat flow all of which indicate the presence of significant geothermal potential.

Alleviated Shifted Gegenbauer Spectral Method for Ordinary and Fractional Differential Equations

This article introduces two numerical methods to address boundary value problems associated with secondorder and fractional differential equations. These methods employ two parameters related to shifted Gegenbauer polynomials as their basis functions. The process involves establishing a differentiation operational matrix for the shifted Gegenbauer polynomials. Subsequently, the initial/boundary value problems for ordinary and fractional differential equations are transformed into a system of equations through the Galerkin, collocation, and tau methods. The convergence analysis is ensured by leveraging theorems pertaining to the shifted Gegenbauer polynomials. To validate the accuracy of the approach, numerous numerical examples are presented.

High-resolution frequency domain decomposition for modal analysis of bridges using train-induced free-vibrations

Modal parameters are structural inherent characteristics that can be applied for revealing performance of railway bridges. Free vibration signals generated by a passage of train are commonly utilized to estimate the modal parameters of railway bridges due to their higher signal-to-noise ratios compared to random vibrations caused by ambient loads. However, since free vibration signals rapidly decay over time, the available free-vibration data is typically short-time. When using the fast Fourier transform-based spectral estimation method for modal identification from short-time vibration data, a phenomenon known as spectral leakage occurs, leading to miss-identification of some structural modes. In this study, the classical frequency domain decomposition (FDD) is improved for modal identification of railway bridges, in which the higher resolution auto-power spectral density (PSD) and cross-PSD functions are calculated through the autoregressive (AR) model-based method. The AR model-based method improves both the smoothness and resolution of the PSD functions compared to the fast Fourier transform technique. These AR model-based PSD functions are then employed in the FDD process to facilitate frequency and mode shape identification while avoiding spurious noise modes. The proposed eigenvalue fitting technique is subsequently utilized to estimate damping ratios. Numerical simulation data as well as vibration data from an actual bridge are analyzed to validate the proposed method, with a comparison made to the Welch’s PSD-based method. The results demonstrate that the modified FDD approach enables more effective identification of structural modes, even in the presence of closely-spaced modes.

On induced subgraph of Cartesian product of paths

AbstractChung et al. constructed an induced subgraph of the hypercube with vertices and with maximum degree smaller than . Subsequently, Huang proved the Sensitivity Conjecture by demonstrating that the maximum degree of such an induced subgraph of hypercube is at least , and posed the question: Given a graph , let be the minimum of the maximum degree of an induced subgraph of on vertices, what can we say about ? In this paper, we investigate this question for Cartesian product of paths , denoted by . We determine the exact values of when by showing that for and , and give a nontrivial lower bound of when by showing that . In particular, when , we have , which is Huang's result. The lower bounds of and are given by using the spectral method provided by Huang.

Development and characterization of fly ash enriched epoxy coatings for corrosion protection in deep sea water

Fly ash (FA) has recently received increasing attention as inexpensive and readily abundant filler for development of epoxy-based anticorrosive coatings. In the present investigation a series of FA enriched epoxy coatings (FECs) has been developed and investigated for their anticorrosive behaviour under immersion in DSW (pH 8.2) over 48 h. The development of FECs was conducted through enrichment of FA ranging 0 to 80 phr (parts of FA per 100 g of epoxy) into epoxy matrix. The formation of FECs was ascertained through spectral, thermal, electrical and microscopic methods. Electrochemical impedance spectra in coherence with DC polarization measurements reveal enhanced corrosion protection efficiency (83 %) of FECs derived at 40 phr enrichment of FA. Enrichment of FA (phr) ranging 40 to 60 has rendered fair (0.01) to moderate (0.05) resistance (mm/year) to FECs against pitting corrosion in DSW. Whereas, FECs derived at 60 phr of FA has shown promising electrical behaviour, moderate heat resistance (TG onset 200 °C with 94.70 % weight residue) with enhanced limiting oxygen index (38.50 %). FECs developed in the present investigation may find their possible applications as anticorrosive coatings sustainable in DSW over 48 h.

Furfuryl-pyridinium-functionalization of flaxseed gum for effective methylene blue removal from aqueous solution

This study describes the modification of flaxseed gum (FSG) via furfural to obtain a furfuryl-pyridinium modified adsorbent (Flax-Py) with improved adsorption characteristics towards methylene blue (MB) versus results obtained for unmodified FSG. Materials characterization was achieved via complementary spectral methods (NMR, XPS, FT-IR, Raman, and XRD) as well as thermogravimetric analysis (TGA) and ζ-potential measurements. Synthetic modification of FSG to yield Flax-Py that led to enriched N-content (2.75 atom-% versus 0.76 atom-% for FSG), and the conversion of furfuryl to pyridinium was incomplete (ca. 50 %), where both moieties were identified. The adsorption isotherms at pH 7 showed that FSG possessed favorably high MB adsorption capacity (ca. 540 mg/g); while Flax-Py was notably lower (167 mg/g). Flax-Py facilitated 100% MB removal at low dye concentrations (1-10 mg/L) versus 50 % MB removal for the FSG bioadsorbent. Further, Flax-Py showed moderate loss of adsorption with MB (ca. 12-16% dye removal) after five regeneration cycles. Flax-Py revealed improved settling characteristics (time, density, gelation, and solubility) that facilitate enhanced phase separation of FSG fractions by circumventing the need for centrifugation. The adsorption mechanism was attributed primarily to H-bonding effects with secondary contributions due to electrostatic interactions (negative ζ-potential above pH 4.2). This study successfully modified FSG to obtain an improved adsorbent (Flax-Py) attaining nearly quantitative MB dye removal at environmentally relevant concentrations (&lt; 15 mg/L).

An approach for fatigue damage estimation under broadband non-Gaussian random loadings based on the Johnson transformation model

Estimating fatigue damage of marine structures using spectral methods under broadband random loadings is a complex and challenging task. In the presence of non-Gaussian loading, the spectral method typically employs the Hermite polynomial model (HPM) to address the non-Gaussianity. However, the applicability of HPM is limited in certain non-Gaussian cases due to the requirement of monotonicity. This paper adopts the Johnson transformation model (JTM) instead of HPM and integrates it with the non-Gaussian TB method (Ding and Chen, 2015) to overcome the constraints in broadband non-Gaussian fatigue estimation. To verify the performance of the new approach, this paper analyses the transformation accuracy of the two models. Additionally, taking the time-domain fatigue damage obtained by the rainflow counting method and the linear damage accumulation rule as a benchmark, this paper compares the fatigue damage estimates obtained from the spectral methods. The comparative assessment encompasses various spectra, S-N curves, and non-Gaussian characteristics. The results indicate the performance of JTM within the non-Gaussian TB method is comparable to HPM in most cases and even surpasses it in hardening non-Gaussian cases. Given the broader applicability of JTM across ranges of skewness and kurtosis, it emerges a superior option for the non-Gaussian TB method in estimating broadband non-Gaussian fatigue damage. Furthermore, the limitations of the proposed approach are discussed.

INVESTIGATION OF ADSORPTION OF BENTONITE SAMPLES WITH IONOGENIC OLIGOMER BY PHYSICO-CHEMICAL METHODS

The adsorption process of natural and modified Co+2-, Ni+2-bentonite samples taken from Dash-Salahli field with ionogenic oligomer modifiers was carried out and studied by x-ray and infrared spectral analysis methods. Important components that ensure the stability of bentonite suspensions are polymers, ions and surfactants. The main goal of the work is to obtain an organic mineral sorbent using an ionogenic oligomer modifier to stabilize polymer-dispersed systems. The most suitable surfactants are substances with a hydrophilic and hydrophobic statistical distribution in the molecule. The prepared sorbent has both cationic and anionic properties and can adsorb various harmful organic substances. As a result of the research, certain changes were observed in the structure of the sorbents. Depending on the ionic radii of substituted metal ions in natural bentonite, weak, medium. strong intensities are observed

Fractional Stochastic Partial Differential Equations: Numerical Advances and Practical Applications—A State of the Art Review

Fractional Stochastic Partial Differential Equations: Numerical Advances and Practical Applications—A State of the Art Review

Construction of Fractional Pseudospectral Differentiation Matrices with Applications

Differentiation matrices are an important tool in the implementation of the spectral collocation method to solve various types of problems involving differential operators. Fractional differentiation of Jacobi orthogonal polynomials can be expressed explicitly through Jacobi–Jacobi transformations between two indexes. In the current paper, an algorithm is presented to construct a fractional differentiation matrix with a matrix representation for Riemann–Liouville, Caputo and Riesz derivatives, which makes the computation stable and efficient. Applications of the fractional differentiation matrix with the spectral collocation method to various problems, including fractional eigenvalue problems and fractional ordinary and partial differential equations, are presented to show the effectiveness of the presented method.

Numerical simulation of Rashba spin–orbit coupling effect on quantum Hall resistivity within tight-binding approximation

A numerical simulation of the effect of Rashba spin–orbit coupling (RSO) on quantum transport properties of electrons confined to a two-dimensional electron gas (2DEG) in the integer quantum Hall regime is presented. The mechanism of quantization and the dependence of the Hall resistivity (HR) on the system built-in and external parameters are studied using the non-equilibrium Green’s function (NEGF) technique. Relevant Green’s functions are computed numerically using spectral decomposition method in combination with recursive techniques. The tight-binding-like representation of the system Hamiltonian including magnetic field is obtained within the finite difference method, using Dirichlet boundary conditions. Corresponding formula linking the Hall resistivity with the transmission function of the system has been derived analytically within the NEGF formalism in a general form, in the sense that the formula can also be used beyond the linear response limit and for nonzero temperatures. In particular, it was shown explicitly that in the presence of the RSO coupling the even- and odd plateaus emerging in the magnetic-field dependence of the quantum Hall resistivity are related to different physical mechanisms.