Field Spectra Research Articles

Hydrothermal Alteration Zones Mapping Using Sentinel 2 MSI and Terra Aster Data in The Uruguay Mine, Minas do Camaquã District

Objective: This work has as main objective to evaluate the usage of data from the Terra ASTER multispectral sensor, as well as data from Sentinel 2 MSI for the identification of hydrothermal alteration zones in the Uruguay Mine. Another objective of this work was to map a not-so-great scale deposit that present a hydrothermal pattern associated in a tropical country. Method: Were applied principal component analysis and entropy analysis technique to the ASTER surface reflectance data and principal components only to the surface reflectance MSI data. The field spectra provided were obtained with the ASD FieldSpec-3 High-Resolution spectroradiometer. The samples collected contained spectral features characteristic of minerals such as ferric chlorite, hematite, goethite and illite (Phengite). Result and Conclusion: The ASTER data resulted in a good radial highlighted pattern at the mine location indicating that the processing was able to map the target spectral patterns. The MSI data were processed to map the ferric minerals and presented a pattern highlighting the mine contours and slopes, demonstrating the possible occurrence of minerals containing the aimed spectral features. The entropy usage as an intensity factor applied to intensity-hue-saturation (IHS) fusion on ASTER data improved the reliability of the results, by highlighting the pixels with deepest absorbance features, reducing the uncertainty associated with the process. The results were considered good since both processes showed correspondence in the location of the mine. Implication of the research: This work contributes for the understanding of spectroscopy analysis of alteration minerals related to copper mineralization, and techniques of remote sensing to map them. Originality/value: Good results of the application of principal component analysis in the studied area and application of entropy concept in spectral analysis.

Grain refinement induced unusually large shape memory effect in lightweight titanium alloy

High-performance and lightweight shape memory alloys (SMAs) play a pivotal role in a variety of cutting-edge fields like aerospace, which however, are still quite difficult to be obtained until now. In the present work, we meticulously develop a novel lightweight Ti-12.5V-3.5Al-1Hf-0.8Fe-0.01B (at.%) SMA, which has a low mass density of ∼4.73 g/cm3. Prominently, distinct from the conventional wisdom in previous studies that is mainly based on eliminating grain boundaries or developing desired texture, we utilize the grain refinement strategy introduced by elaborate thermal-mechanical training, which effectively enables us to achieve exceptional shape memory response and strength-ductility combination simultaneously. It was revealed that a dominant β phase structure is achieved in this newly designed fine-grain SMA, accompanied by some α″ variants penetrating the grain boundaries. Compared to the coarse-grained counterpart, the deformation process becomes more intricate, involving stress-induced martensitic transformation and additional reorientations, which ultimately results in an unusually large recoverable strain up to 9.3 %. Furthermore, the fine-grain structure also contributes to an enhanced specific yield strength up to ∼159 MPa·m³/kg, while maintaining a large tensile ductility of ∼30 %. In light of its impressive structure-function integration and cost efficiency, this new-type SMA would emerge as a promising candidate for various advanced lightweight applications in a broad spectrum of fields.

Towards a robust approach for evidencing quality in higher education learning: The new CALOHEE model

PurposeKey to transnational higher education (HE) cooperation is building trust to allow for seamless recognition of studies. Building on the Tuning Educational Structures initiative (2001) and lessons learnt from the Organisation for Economic Cooperation and Development (OECD)-Assessment of Learning Outcomes in Higher Education (AHELO) feasibility study, this paper offers a sophisticated approach developed by the European Union (EU)-co-financed project Measuring and Comparing Achievements of Learning Outcomes in Europe (CALOHEE). These evidence the quality and relevance of learning by applying transparent and reliable indicators at the overarching and disciplinary levels. The model results allow for transnational diagnostic assessments to identify the strength and weaknesses of degree programmes.Design/methodology/approachThe materials presented have been developed from 2016 to 2023, applying a bottom-up approach involving approximately 150 academics from 20+ European countries, reflecting the full spectrum of academic fields. Based on intensive face-to-face debate and consultation of stakeholders and anchored in academic literature and wide experience.FindingsAs a result, general (overarching) state-of-the-art reference frameworks have been prepared for the associated degree, bachelor, master and doctorate, as well as aligned qualifications reference frameworks and more detailed learning outcomes/assessment frameworks for 11 subject areas, offering a sound basis for quality assurance. As a follow-up, actual assessment formats for five academic fields have been developed to allow for measuring the actual level of learning at the institutional level from a comparative perspective.Originality/valueFrameworks as well as assessment models and items are highly innovative, content-wise as in the strategy of development, involving renown academics finding common ground. Its value is not limited to Europe but has global significance. The model developed, is also relevant for micro-credentials in defining levels of mastery.

A compendium of logarithmic corrections in AdS/CFT

We study the logarithmic corrections to various CFT partition functions in the context of the AdS4/CFT3 correspondence for theories arising on the worldvolume of M2-branes. We utilize four-dimensional gauged supergravity and heat kernel methods and present general expressions for the logarithmic corrections to the gravitational on-shell action and black hole entropy for a number of different supergravity backgrounds. We outline several subtle features of these calculations and contrast them with a similar analysis of logarithmic corrections performed directly in the eleven-dimensional uplift of a given four-dimensional supergravity background. We find results consistent with AdS/CFT provided that the infinite sum over KK modes on the internal space is regularized in a specific manner. This analysis leads to an explicit expression for the logarithmic correction to the Bekenstein-Hawking entropy of large Kerr-Newmann and Reissner-Nordström black holes in AdS4. Our results also have important implications for effective field theory coupled to gravity in AdS4 and for the existence of scale-separated AdS4 vacua in string theory, which come in the form of new constraints on the field content and mass spectrum of matter fields.

Comparison of anomalies in the VLF spectrum of the natural electromagnetic field with data from the seismometer in a landslide-affected area

The data from a permanent monitoring station, based on a sound card as an AD/DA converter and a magnetic loop antenna for continuous recording of electromagnetic field intensities in the Very Low Frequency (VLF) range, were recorded and compared with data from a seismic station based on Raspberry Pi located in a landslide-affected area. The stations operated 24/7 and were placed in a room below ground level. Correlations were observed between seismic signals in the frequency spectrum from 0.1 Hz to 10 Hz (some extending beyond 20 Hz) and anomalies in the electromagnetic field in the VLF range. These anomalies are likely associated with micro-fracturing, piezo-electromagnetic, and triboelectric phenomena within the landslide body, producing relatively weak VLF emissions and a faint seismic signal. A single-component 4.5 Hz 395 Ohm vertical Racotech RGI-20DX geophone with electronic extension to lower frequencies (< 1 Hz) was used with a sampling rate of 100 sps (samples per second). VLF emissions cover almost the entire spectrum from 6 kHz with a peak at 14 kHz to 18 kHz. The received spectrum was divided into following sections: VLF band 4 kHz – 6 kHz; 6 kHz – 8 kHz; 8 kHz – 10 kHz; 10 kHz – 12 kHz; 12 kHz – 14 kHz; 14 kHz – 16 kHz; 16 kHz – 18 kHz. Simultaneously, there were changes in these sections analysed and compared with the seismic record within the same time interval.

Bayesian deep learning for cosmic volumes with modified gravity

Context. The new generation of galaxy surveys will provide unprecedented data that will allow us to test gravity deviations at cosmological scales at a much higher precision than could be achieved previously. A robust cosmological analysis of the large-scale structure demands exploiting the nonlinear information encoded in the cosmic web. Machine-learning techniques provide these tools, but no a priori assessment of the uncertainties. Aims. We extract cosmological parameters from modified gravity (MG) simulations through deep neural networks that include uncertainty estimations. Methods. We implemented Bayesian neural networks (BNNs) with an enriched approximate posterior distribution considering two cases: the first case with a single Bayesian last layer (BLL), and the other case with Bayesian layers at all levels (FullB). We trained both BNNs with real-space density fields and power spectra from a suite of 2000 dark matter-only particle-mesh N-body simulations including MG models relying on MG-PICOLA, covering 256 h−1 Mpc side cubical volumes with 1283 particles. Results. BNNs excel in accurately predicting parameters for Ωm and σ8 and their respective correlation with the MG parameter. Furthermore, we find that BNNs yield well-calibrated uncertainty estimates that overcome the over- and under-estimation issues in traditional neural networks. The MG parameter leads to a significant degeneracy, and σ8 might be one possible explanation of the poor MG predictions. Ignoring MG, we obtain a deviation of the relative errors in Ωm and σ8 by 30% at least. Moreover, we report consistent results from the density field and power spectrum analysis and comparable results between BLL and FullB experiments. This halved the computing time. This work contributes to preparing the path for extracting cosmological parameters from complete small cosmic volumes towards the highly nonlinear regime.

Jovian Magnetosheath Turbulence Driven by Whistler

Jupiter’s magnetosheath is a natural yet complex laboratory for analyzing compressible plasma turbulence. Recent observations by the Juno mission provide a promising opportunity for the first time to reckon the energy cascade rate in the magnetohydrodynamic scales in the vicinity of Jupiter’s space. In the present work, a two-dimensional model is constructed for a whistler wave that is nonlinearly coupled with a wave magnetic field via ion density perturbation. The dynamics of whistler wave propagating in the direction of the magnetic field are derived within the limit of the two-fluid modeling approach. The magnetic field localization along with magnetic field spectra and spectral slope variations are estimated to realize the turbulence generation and energy cascade from large to small scales in the Jovian magnetosheath region. The simulated magnetic field spectrum in the wave number (in the unit of ion inertial length ρ i ) consists of turbulence in the inertial range with a spectral slope of −1.4 and a spectral knee at k ρ i = 1. Subsequently, the spectral slope increases to −2.6 and the spectrum becomes steeper. The simulated magnetic field spectrum in the wave number is further translated into the frequency domain using the whistler wave dispersion relation and by considering the Taylor frozen-in condition. The analytically estimated magnetic field spectrum slopes, i.e., −1.8 and −4.2 at low and high frequencies are further compared with recent Juno mission observations. The comparison further affirms the existence of Kolmogorov scaling, a spectral knee, and steepening in the spectrum at high frequencies. Furthermore, it is found that the two-fluid model can reasonably simulate the turbulence effects in Jovian magnetosheath in terms of magnetic field spectral distribution in wave number and frequency domains.

Unpaired Downscaling of Fluid Flows with Diffusion Bridges

Abstract We present a method to downscale idealized geophysical fluid simulations using generative models based on diffusion maps. By analyzing the Fourier spectra of fields drawn from different data distributions, we show how a diffusion bridge can be used as a transformation between a low resolution and a high resolution dataset, allowing for new sample generation of high-resolution fields given specific low resolution features. The ability to generate new samples allows for the computation of any statistic of interest, without any additional calibration or training. Our unsupervised setup is also designed to downscale fields without access to paired training data; this flexibility allows for the combination of multiple source and target domains without additional training. We demonstrate that the method enhances resolution and corrects context-dependent biases in geophysical fluid simulations, including in extreme events. We anticipate that the same method can be used to downscale the output of climate simulations, including temperature and precipitation fields, without needing to train a new model for each application and providing a significant computational cost savings.

Advancements in EEG Emotion Recognition: Leveraging Multi-Modal Database Integration

This paper addresses the limitations of relying solely on facial expressions for emotion recognition by proposing an advanced approach that emphasizes continuous monitoring of electroencephalography (EEG) signals. Recognizing the potential for deception in facial expressions, our study leverages the growing interest in EEG signals, tapping into advancements in deep learning and machine learning. By optimizing the configuration of EEG electrodes, our approach enhances the accuracy of emotion classification systems, offering a streamlined solution. The proposed multi-input system refines EEG-based emotion recognition efficiency and integrates facial expression analysis to enhance overall system effectiveness. Through the application of brain heat map topographies and facial expression recognition, our system, employing just nine electrodes, outperforms basic emotion recognition setups. Experimental results validate that combining facial expression analysis with EEG signals provides a more comprehensive and accurate understanding of human emotions. This innovative approach holds significance across various sectors, including healthcare, psychology, and human–computer interaction. The paper introduces a novel multi-input system approach, collaboratively fusing two powerful deep learning algorithms: two Convolutional Neural Networks (CNNs). The proposed EEG-based CNN algorithm achieves an efficiency of 87.43%, rising to 91.21% when integrated with the DeepFace CNN. The seamless integration of facial expressions and brain topographies enables the system to efficiently harness abundant information from both modalities, ensuring a thorough comprehension of human emotions. By capitalizing on the combined advantages of analyzing facial expressions and EEG-derived brain topography, this avant-garde technique substantially improves both precision and efficiency in emotion recognition systems. This enhancement establishes a foundation for the introduction of innovative applications across a spectrum of fields.

Influence of pressure and temperature on the magneto-optical properties and Aharonov-Bohm oscillations of a quantum ring

We theoretically investigated the influence of pressure and temperature on the electronic and optical properties of a GaAs /Al0.3Ga0.7As quantum ring, described by a combination of a parabolic potential and an inverse square one, in the presence of the magnetic field. The results reveal a variation with pressure and temperature of the period of Aharonov-Bohm oscillations appearing in the electronic spectra in magnetic field. This period varies nonlinearly with pressure and temperature. In the absorption spectra and refractive index variation at 4 K, we found that with the increment of the magnetic field or of the pressure more transitions are allowed. When no external pressure is applied, the absorption maxima shift to lower energies at increasing magnetic field, but with increasing pressure, the absorption maxima red-shift at intermediate magnetic fields and blue-shift at high fields.

Intermittency as a Consequence of a Stationarity Constraint on the Energy Flux.

In his seminal work on turbulence, Kolmogorov made use of the stationary hypothesis to determine the power density spectrum of the velocity field in turbulent flows. However, to our knowledge, the constraints that stationary processes impose on the fluctuations of the energy flux have never been used in the context of turbulence. Here, we recall that the power density spectra of the fluctuations of the injected power, the dissipated power, and the energy flux have to converge to a common value at vanishing frequency. Hence, we show that the intermittent Gledzer-Ohkitani-Yamada (GOY) shell model fulfills these constraints. We argue that they can be related to intermittency. Indeed, we find that the constraint on the fluctuations of the energy flux implies a relation between the scaling exponents that characterize intermittency, which is verified by the GOY shell model and in agreement with the She-Leveque formula. It also fixes the intermittency parameter of the log-normal model at a realistic value. The relevance of these results for real turbulence is drawn in the concluding remarks.

Spectral imaging of grass species in arid ecosystems of Namibia

Grasslands across the African continent are under pressure from climate change and human activities, particularly in arid ecosystems. From a remote sensing perspective, these ecosystems have not received much scientific attention, especially in Namibia. To address this knowledge gap, various remote sensing methods were implemented using new generation spaceborne imaging spectrometers amongst others. Therefore, this research provides a first methodological approach aimed at mapping and evaluating the distribution of grasslands within two private nature reserves, namely, the NamibRand Nature Reserve (NRNR) and ProNamib Nature Reserve (PNNR) with surrounding farmlands on the edge of Namib Sand Sea. The multi-sensor approach utilizes Mixture Tuned Matched Filtering (MTMF) and incorporated spectral information collected in the field to analyze grasslands. The research involves a sensor comparison of multispectral Sentinel-2 and PlanetScope data, hyperspectral data from Environmental Mapping and Analysis Programme (EnMAP) and PRecursore IperSpettrale della Missione Applicativa (PRISMA) and an additional data fusion product derived from Sentinel-2 and EnMAP imagery based on a Smoothing Filter-based Intensity Modulation Hypersharpening method (SFIM-HS). Additionally, a unique spectral library of collected field spectra was established and inter-species spectral separability and intra-species spectral homogeneity was analyzed. This library presents newly published spectra of individual species. Due to dry initial conditions, the calculated spectral separability of individual grasses is limited, making only a mean endmember feasible for partial unmixing. The validation results of satellite comparison show that data fusion products (R2 = 0.51 with Normalized Difference Vegetation Index (NDVI); R2 = 0.66 with Soil Adjusted Vegetation Index (SAVI)) are more suitable for mapping arid grasslands than multispectral or hyperspectral data (all R2 < 0.35). More research is required and potential methodological adjustments are discussed to further investigate the spatio-temporal dynamics of arid grasslands and to aid conservation efforts in the Greater Sossusvlei-Namib Landscape in line with the United Nations Decade of Restoration.

Exploring the Impact of Meta-Analysis in Scientific Research: A Review

Meta-analysis is a well-established statistical analysis method that aims to analyze the number of different studies which are addressing the same hypothesis. This statistical analysis increases the efficiency of the output and provides us with consensus and significant results. When addressing several datasets, the relevance of the meta-analysis is revealed when some hidden feature or the results are brought up. The available literature also provides us with references to numerous meta-analysis studies in different scientific areas to provide new insight into available research with discoveries and outcomes. In our comprehensive and extensive review study, we will embark upon a thorough investigation into the pivotal role and profound impact of meta-analysis in various fields, encompassing but not limited to bioinformatics, medicine, criminology, ecology, cancer research, education, psychology, pharmaceuticals, food safety, epidemiology, neurodegenerative diseases, diabetes, and hypertension. By immersing ourselves in the intricacies and complexities of these diverse and multifarious subjects, our all-encompassing and in-depth study aims to delve deeply into the very essence of the challenges and opportunities that pervade a vast array of disciplines. From the critical realm of healthcare to the captivating and enthralling realm of social sciences, we seek to unravel the interconnected and interwoven tapestry of issues and possibilities that span across a wide spectrum of scholarly fields.

The impact of shallow waveguides on the spectral characteristics of modulated spectral lines in underwater radiated noise produced by ships

The modulation spectrum line spectrum of undersea radiated noise from ships is a significant characteristic in the identification of ship targets. This research presents an analysis of the impact of waveguide dispersion effect and demodulation bandwidth on the intensity of modulation line spectrum, based on the theoretical framework of square demodulation method. The physical mechanism underlying this influence is derived and discussed. The examination of collected data and numerical simulations demonstrates that the extracted modulated line spectrum intensity in an unobstructed environment effectively utilizes the carrier’s energy and generally does not exhibit any abnormal loss during propagation. However, in a shallow sea dispersive waveguide, as the propagation distance increases, a transimission loss anomaly of over 3dB occurs in the modulated line spectrum. The theoretical derivation yields implications that can offer theoretical backing for the reduction of vibration and noise in underwater targets, extraction of faint signals from high-order line spectra in the distant field, and identification of targets.

Direct numerical simulation of a wall source dispersion in a turbulent channel flow

A comprehensive direct numerical simulation (DNS) is conducted to analyze the turbulent mixing process of a surface source dispersion emitting from the bottom wall in a turbulent channel flow. A comparative analysis of ten test cases has been conducted to examine the turbulent mixing process and its relationship with the source strength. The study involves an examination of the dispersion process in both physical and spectral spaces, which includes an evaluation of statistical moments of the concentration field, pre-multiplied spatial spectra of the velocity and concentration fields, as well as an analysis of the coherent turbulent structures in the flow. Upon normalization by friction concentration, the DNS analysis reveals that the first- and second-order statistical moments of the concentration field remain unaffected by variations in the source strength. Conversely, the relative intensity of concentration fluctuations and the thickness of the concentration boundary layer exhibit significant susceptibility to variations in the source strength. It has been observed that the dispersion process within the channel is significantly influenced by the small-scale eddies in cases where the source strength is not particularly intense. When confronted with high source strength scenarios, analysis of the simulation results establishes that both small- and large-scale eddies are crucial players in the dispersion phenomena, as evinced by a comparison of the pre-multiplied spectra of concentration and velocity fields. Furthermore, hairpin vortices have been recognized as the primary source of turbulence in the dispersal of substances from regions of high shear to the center of the channel.

Directional wave spectrum evolution modelling of ship noise

A new underwater acoustic propagation model that is well suited to modelling ship noise is described. The model describes the spatio-temporal evolution of the directional energy spectrum of a sound field. The governing equation can be thought of as an advection-diffusion equation for spectral energy in phase space (position, angle). Numerical simulations of sound fields excited by both isotropic compact sources and by highly anisotropic ship noise provide confidence that the model works well, with caveats that will be discussed. [Work supported by ONR.]

Numerical investigation of flow past a cylinder using cumulant lattice Boltzmann method

This paper presents simulations of flow past a circular cylinder within the subcritical Reynolds number (Re) range from 3900 to 2 × 105, utilizing the parameterized cumulant lattice Boltzmann model. In this study, a three-dimensional characteristic boundary condition for incompressible flow has been integrated into the lattice Boltzmann method at the outflow boundary to minimize spurious reflection. The flow field, wake statistics, hydrodynamic force, and power spectra results of Re = 3900 from the cumulant lattice Boltzmann model are exhaustively compared with the laboratory data and other numerical models. Relative to other numerical models employing turbulence closure, the cumulant lattice Boltzmann simulations demonstrate enhanced agreement with the experimental data even with relatively coarser grid resolution. The resolution-spanning feature for the cumulant lattice Boltzmann model in turbulent flows, without using explicit turbulence model, aligns with the previous benchmark case studies. The stability-preserving regularization process in the present model is analyzed. Results indicate that the influence of the regularization parameter is mitigated with improved grid resolution. A specific regularization parameter for flow around cylinder simulations is recommended. Variations in flow properties and hydrodynamic forces within the subcritical Reynolds number range of 3900 to 2 × 105 are analyzed. The results confirm that the parameterized cumulant lattice Boltzmann model can accurately simulate practical engineering flows, characterized by complex separation and recirculation, within the subcritical range. Moreover, the computational efficiency and parallel scalability are compared with other numerical methods.

Estimating and Calibrating Markov Chain Sample Error Variance

Markov chain Monte Carlo (MCMC) methods are a powerful and versatile tool with applications spanning a wide spectrum of fields, including Bayesian inference, computational biology, and physics. One of the key challenges in applying MCMC algorithms is to deal with estimation error. The main result in this article is a closed form, non-asymptotic solution for the sample error variance of a single MCMC  estimate. Importantly, this result assumes that the state-space is finite and discrete. We demonstrate with examples how this result can help estimate and calibrate MCMC estimation error variance in the more general case, when the state-space is continuous and/or unbounded.

A Comprehensive Correction of the Gaia DR3 XP Spectra

By combining spectra from the CALSPEC and NGSL, as well as spectroscopic data from the LAMOST Data Release 7 (DR7), we have analyzed and corrected the systematic errors of the Gaia DR3 BP/RP (XP) spectra. The errors depend on the normalized spectral energy distribution (simplified by two independent “colors”) and G magnitude. Our corrections are applicable in the range of approximately −0.5 < BP − RP < 2, 3 < G < 17.5, and E(B − V) < 0.8. To validate our correction, we conduct independent tests by comparisons with the MILES and LEMONY spectra. The results demonstrate that the systematic errors of BP − RP and G have been effectively corrected, especially in the near-ultraviolet. The consistency between the corrected Gaia XP spectra and the MILES and LEMONY is better than 2% in the wavelength range of 336–400 nm and 1% in redder wavelengths. A global absolute calibration is also carried out by comparing the synthetic Gaia photometry from the corrected XP spectra with the corrected Gaia DR3 photometry. Our study opens up new possibilities for using XP spectra in many fields. A Python package is publicly available to do the corrections (doi:10.12149/101375 or https://github.com/HiromonGON/GaiaXPcorrection).

Диагностика неисправностей синхронных генераторов путем компьютерного моделирования внешнего магнитного поля

Currently, the development of non-invasive diagnostic methods for electric machines and especially generators, as the main producers of electric energy, using magnetic field fixation sensors is an urgent scientific and technical task. To solve this problem, research has been conducted to develop a method for troubleshooting a synchronous generator by analyzing an external magnetic field. The article discusses the main issues of computer modeling of an external magnetic field in the FEMM 4.2 system for troubleshooting. Mathematical expressions are given for creating a computer model of a synchronous generator in two-dimensional space, on the basis of which a numerical solution of the external magnetic field is formed using the finite element method. The modeling takes into account the design features of the synchronous generator. The main stages of work in the FEMM 4.2 system are defined. The geometric model of the synchronous generator is imported from the computer-aided design system. The physical properties of all elements of the model are determined by the structural materials of the synchronous generator and the external space. The control program, created on the basis of the algorithm presented in the article, allows you to simulate the rotation of the inductor of a synchronous generator, automate the calculations of the electromagnetic field and display the results. An example of using a computer model of a synchronous generator for troubleshooting by examining an external magnetic field is given. Based on the results of a numerical solution of the external magnetic field, a harmonic analysis of the magnetic induction of a working synchronous generator was carried out. The article shows that a diagnostic sign of static eccentricity of a synchronous generator inductor is the appearance of even harmonics in the magnetic induction spectrum of an external magnetic field Based on the results obtained, the dependence of the growth of even harmonics on the magnitude of the displacement of the inductor of the synchronous generator is determined.