Search Results (48)

Microalgal amendments can improve soil structure by regulating extracellular polymeric substances (EPSs). However, the mechanisms underlying this process in red soils (characterized by high clay content and susceptibility to acidification) under different farming practices remain unclear. This study examined how Chlorella vulgaris (C. vulgaris) amendment influences EPS composition to enhance soil aggregate stability under arable land and rice paddy farming. A five-month pot experiment using a completely randomized design was conducted to investigate the effects of Chlorella vulgaris amendment on soils cultivated with Pennisetum × sinese and rice, two economically important crops commonly grown in South China. At the end of the experiment, Chlorella vulgaris amendment substantially increased both the mean weight diameter (MWD) and geometric mean diameter (GMD) of soil aggregates under both farming systems. Excitation–emission matrix (EEM) fluorescence spectroscopy revealed distinct changes in soil EPS components between the two farming types. Under arable land farming, humic-like and protein-like EPSs were dominant in Chlorella vulgaris-amended treatments, with fluorescence intensities more than doubling compared to the control. Conversely, under rice paddy farming, soil fulvic acid was the main component and showed a moderate increase. Partial least squares path modeling (PLS-PM) demonstrated that protein-like and humic-like EPSs had the strongest direct effects on aggregate stability in arable land red soil, while fulvic acid was the key factor in rice paddy red soil. The present study demonstrates that Chlorella vulgaris amendment improves aggregate stability in red soils through farming-specific, EPS-mediated pathways, providing a quantitative framework for researchers and land managers seeking to apply microalgal amendments for red soil enhancement and sustainable land management. Full article

Let $\mathcal{Z}$ be a graph of order n with m edges. Let $A_{ag}\left(\mathcal{Z}\right)$ represents the arithmetic–geometric matrix of $\mathcal{Z}$. The eigenvalues of the matrix $A_{ag}\left(\mathcal{Z}\right)$ are called the arithmetic–geometric eigenvalues, and the eigenvalue with the largest modulus is called the arithmetic–geometric spectral radius of $\mathcal{Z}$. The sum of the absolute values of the arithmetic–geometric eigenvalues is called the arithmetic–geometric energy of $\mathcal{Z}$. In this paper, we establish sharp upper and lower bounds for the AM-GM spectral radius in terms of various graph parameters and provide a complete characterization of the extremal graphs that attain these bounds. Additionally, we derive new bounds for the AM-GM energy of a graph and identify the corresponding extremal structures. In both contexts, our results significantly improve upon several existing bounds reported in the literature. Full article

Accurate mapping of localization error distribution is essential for assessing passive sensor systems and guiding sensor placement. However, conventional analytical methods like the Geometrical Dilution of Precision (GDOP) rely on idealized error models, failing to capture the complex, heterogeneous error distributions typical of real-world environments. To overcome this challenge, we propose a novel data-driven framework that reconstructs high-fidelity localization error maps from sparse observations in TDOA-based systems. Specifically, we model the error distribution as a tensor and formulate the reconstruction as a tensor completion problem. A key innovation is our physics-informed regularization strategy, which incorporates prior knowledge from the analytical error covariance matrix into the tensor factorization process. This allows for robust recovery of the complete error map even from highly incomplete data. Experiments on a real-world dataset validate the superiority of our approach, showing an accuracy improvement of at least 27.96% over state-of-the-art methods. Full article

Accurate measurement of luminous flux from solid-state light sources typically requires spectroradiometric equipment or integrating spheres. This work investigates a compact alternative based on a fiber-coupled RGB photodiode system and develops the optical, spectral, and geometric foundations required to obtain traceable flux estimates from reduced-channel measurements. The system under study comprises an LED with known spectral power distribution (SPD), optical head, optical fiber, a protective sensor window, and a photodiode matrix type sensor. A complete end-to-end analysis of the optical path is presented, including geometric coupling efficiency, fiber transmission and angular redistribution, Fresnel losses in the sensor window, and the mosaic structure of the sensor. Additional effects such as fiber–sensor alignment, fiber-facet tilt, air gaps, and LED placement tolerances are quantified and incorporated into a formal uncertainty budget. Using the manufacturer-supplied SPD of the reference LED together with the measured R, G, and B channel responsivity functions of the sensor, a calibration-based mapping is established to reconstruct photopic luminous flux from the three-channel outputs. These results demonstrate that, with appropriate modeling and calibration of all optical stages, a fiber-coupled RGB photodiode mosaic can provide practical and scientifically meaningful luminous-flux estimation for white LEDs, offering a portable and cost-effective alternative to conventional photometric instrumentation in mid-accuracy applications. Further optimization of computation speed can enable fully integrated measurement systems in resource-constrained environments. Full article

This contribution presents an integrated methodological pipeline for digital documentation and virtual reconstruction of large-scale urban archaeological excavations, developed through the Amba Aradam case study (Metro C line, Rome). The excavation revealed a 2nd-century A.D. military complex extending over 4770 m² at depths reaching 20 m, documented through multiple photogrammetric campaigns (2016–2018) as structures were progressively excavated and removed. We established an empirically validated texture density standard (1.26 mm²/texel) for photorealistic digital replicas suitable for immersive HMD and desktop exploration, with an explicit texture density calculation formula ensuring reproducibility. The temporal integration workflow merged 3D snapshots acquired across three excavation campaigns while maintaining geometric and chromatic consistency. Semantic documentation, through the extended matrix framework, recorded Virtual Stratigraphic Units linking archaeological evidence, comparative sources, and interpretative reasoning (paradata) for transparent virtual reconstruction. The complete pipeline, implemented through open-source 3DSC 1.4 and EMtools add-ons for Blender and Metashape v0.9 (available on GitHub), addresses specific challenges of documenting complex stratigraphic contexts within active construction environments where in situ preservation is not feasible. The spatial integration of the digital replica with previous archaeological data illuminated the urban evolution of Rome’s military topography during the 2nd–3rd centuries A.D., demonstrating the essential role of advanced digital documentation in contemporary urban archaeology. Full article

This study introduces a refined multi-scale micromechanical framework for analyzing C/C-SiC ceramic matrix composites (CMCs) using a dedicated Parametric High-Fidelity Method of Cells (PHFGMCs). A three-level geometric model is constructed from scanning electron microscope (SEM) micrographs and computed tomography (CT) scans. Specialized dual micro-meso nested PHFGMCs are employed to accurately generate the effective properties and spatial distributions of local stress fields in the highly heterogeneous microstructure of an 8-harness C/C-SiC representative volume element (RVE). The proposed refined framework recognizes the different micro- and meso-scales, ranging from the carbon fiber and amorphous carbon matrix to intra-yarn segmentation and weave regions. All are nested in a complete 8-harness architecture. The refined PHFGMC analyses showed good agreement between predicted mechanical properties and experimental data for C/C-SiC. The model’s ability to resolve local spatial deformation in the complex microstructure of C/C-SiC CMCs is demonstrated. These findings highlight the need for a refined multi-scale analysis that captures microstructural complexity and constituent interactions influencing both macroscopic and local responses in C/C-SiC CMCs. The proposed PHFGMC-based framework provides a robust theoretical and computational foundation for the future integration of nonlinear and progressive damage models within C/C-SiC CMC material systems. Full article

Infrared thermography non-destructive testing technology has been widely used in the defect detection of composite structures due to its advantages, including non-contact operation, rapidity, low cost, and high precision. In this study, a laser-line scanning system combined with an infrared thermography was developed, along with a corresponding dynamic sequence image reconstruction method, enabling rapid localization of surface damages. Then, high-precision quantitative characterization of defect morphology in reconstructed images was achieved by integrating an edge gradient detection algorithm. The reconstruction method was validated through finite element simulations and experimental studies. The results demonstrated that the laser-line scanning thermography effectively enables both rapid localization of surface damages and precise quantitative characterization of their morphology. Experimental measurements of ceramic materials indicate that the relative error in detecting crack width is about 6% when the crack is perpendicular to the scanning direction, and the relative error gradually increases when the angle between the crack and the scanning direction decreases. Additionally, an alumina ceramic plate with micrometer-width cracks is inspected by the continuous laser-line scanning thermography. The morphology detection results are completely consistent with the actual morphology. However, limited by the spatial resolution of the thermal imager in the experiment, the quantitative identification of the crack width cannot be carried out. Finally, the proposed method is also effective for detecting surface damage of wrinkles in ceramic matrix composites. It can localize damage and quantify its geometric features with an average relative error of less than 3%, providing a new approach for health monitoring of large-scale ceramic matrix composite structures. Full article

The size and flexibility of offshore turbine blades manufactured from composite materials have continuously increased in recent years. In this context, accurate and efficient aeroelastic analyses are important for designing and safely assessing long, flexible blades. Existing linear beam models need to be revised to offer accurate estimates of the geometric nonlinear effects triggered by large displacements. Nonlinear, geometrically exact beam models that have already been extensively used for the above purpose are generally difficult to converge and inefficient. We propose a novel co-rotational beam model for the nonlinear analysis of wind turbine blades. The method adopts vector complement to resolve rotation vector singularity problems. A complete anisotropic cross-sectional stiffness matrix and Timoshenko beam elements are introduced to capture full coupling effects. The method also considers the anisotropy and taper effects caused by the non-uniformity of chord length and material distributions. We established the nonlinear aeroelastic model of the DTU 10 MW turbine, and the results showed that the taper effect dramatically reduced the blade torsion angle by up to 31.44% under rated wind speed. Meanwhile, static beam experiments demonstrate that the accuracy error of the current method is only 1.78%, which is significantly lower than the 17.8% error of the conventional finite element beam method. Full article

This research advances steady state analysis and cost optimization of the M/M/1/N single vacation queueing system with setup time, working vacation, and working breakdown. The server works at a lower service rate instead of stopping work completely during both the vacation period and breakdown period—a key distinction from traditional vacation and breakdown strategies, where the server typically halts operations entirely. The setup time exists between the idle period and the regular busy period. The finite quasi birth-and-death process of this queueing system model is established. The stationary probability vector of the system is calculated using the matrix geometric method. Performance measures, such as output variance, availability, throughput rate, and stationary probabilities, are obtained using the theory of the fundamental matrix and covariance matrix. A cost optimization model based on system performance measures is established. The sparrow search algorithm is adopted to solve the cost optimization model. Through numerical experiments, the influences of system parameters on system performance measures and cost optimization function are analyzed, and the efficiency of the sparrow search algorithm for solving the cost optimization model is verified. The experimental results affirm the effectiveness and practicability of the proposed method, which provides a better theoretical basis for the practical application of the queueing system in communication engineering and production systems. Full article

The oxidative coupling of methyl chloride (CH₃Cl) to vinyl chloride (C₂H₃Cl) (MCTV) represents a promising yet challenging direct conversion route for C₂H₃Cl production. In this study, a novel catalyst, cristobalite silica, supported Na₂WO₄ nanoclusters, was fabricated by calcining an intermediate composite composed by β-zeolite and sodium tungstate (Na₂WO₄). The pore structure of this β-zeolite possesses a regular shape and suitable size distribution, providing an accurate geometric matching effect for Na₂WO₄ to homogeneously distribute in the entire β-zeolite matrix with high loading. Accordingly, the excellent dispersity of Na₂WO₄ nanocluster active sites is well maintained even after calcining at 750 °C, and the microporous β-zeolite matrix is completely converted to dense cristobalite phase silica after the calcination. The high-loading and well-dispersed Na₂WO₄ nanocluster leads to a superior performance in MCTV with a CH₃Cl conversion of 81.5%, a C₂H₃Cl selectivity of 42.4%, and a C₂H₃Cl yield of 34.6%. Notably, the catalyst exhibits remarkable stability during the catalytic process. Full article

In the context of 3D geometric reconstruction from sequential inverse synthetic aperture radar (ISAR) images, the accurate scatterer trajectory association is a critical step. Aiming at the above problem, an enhanced scatterer trajectory association method is proposed by designing a modified label Gaussian mixture probability hypothesis density (ML-GM-PHD) filtering algorithm. The algorithm commences by constructing a general motion model for scatterers across sequential ISAR images, followed by an in-depth analysis of their motion characteristics. Subsequently, the actual projected positions and measurements of the scattering centers of the observed target are treated as random finite sets, which allows us to reformulate the scatterer trajectory association into a maximum a posteriori (MAP) estimation problem. After that, a ML-GM-PHD filtering algorithm is proposed to realize the scatterer trajectory association. Furthermore, the proposed method is applied to ISAR images in both the forward and reverse directions, enabling the fusion of trajectories from opposing directions to bolster the completeness of the scatterer trajectories. Finally, the factorization method is performed on the scatterer trajectory matrix to implement the 3D geometry reconstruction of the scattering centers in the observed target. Experimental results based on random points and electromagnetic data verify the effectiveness and performance priority of the proposed algorithm. Full article

Wavefront shaping is a well-known method of restoring a focus deep within scattering media by manipulating the incident light. However, the achievable focus enhancement depends on and is limited by the optical and geometrical properties of the medium. These properties contribute to the number of linearly independent transmission channels for light propagating through the turbid medium. Correlations occur when the number of incident waves coupled into the scattering medium exceeds this finite number of transmission channels. This paper investigates the wavefront shaping of such correlated electric fields. The influence of the observed correlations persists even though the average electric field distribution at positions in the focal plane follows a circular complex Gaussian. We show that correlations of the transmitted electric fields reduce the achievable intensity enhancement, even deep in the turbid medium. The investigations are carried out using a Monte Carlo algorithm. It is based on the speckle statistics of independent waves and introduces correlations of neighbouring electric fields via a Cholesky decomposition of the covariance matrix. Additional investigations include scenarios where the electric fields are not completely randomized, such as for ballistic or insufficiently scattered light. Significant contributions from such little-scattered light are observed to reduce the intensity enhancement further. Data from simulations solving Maxwell’s equations are compared with the results obtained from the Monte Carlo simulations for validation throughout this paper. Full article

A new formalism is introduced that makes it possible to elucidate the physical and geometric content of quantum space–time. It is based on the Minimum Group Representation Principle (MGRP). Within this framework, new results for entanglement and geometrical/topological phases are found and implemented in cosmological and black hole space–times. Our main results here are as follows: (i) We find the Berry phases for inflation and for the cosmological perturbations and express them in terms of the observables, such as the spectral scalar and tensor indices, $n_S$ and $n_T$, and the tensor-to-scalar ratio r. The Berry phase for de Sitter inflation is imaginary with the sign describing the exponential acceleration. (ii) The pure entangled states in the minimum group (metaplectic) $Mp\left(n\right)$ representation for quantum de Sitter space–time and black holes are found. (iii) For entanglement, the relation between the Schmidt type representation and the physical states of the $Mp\left(n\right)$ group is found: This is a new non-diagonal coherent state representation complementary to the known Sudarshan diagonal one. (iv) Mean value generators of $Mp\left(2\right)$ are related to the adiabatic invariant and topological charge of the space–time, (matrix element of the transition $-\infty <t<\infty$). (v) The basic even and odd n-sectors of the Hilbert space are intrinsic to the quantum space–time and its discrete levels (in particular, continuum for $n\to \infty$), they do not require any extrinsic generation process such as the standard Schrodinger cat states, and are entangled. (vi) The gravity or cosmological domains on one side and another of the Planck scale are entangled. Examples: The quantum primordial trans-Planckian de Sitter vacuum and the classical late de Sitter vacuum today; the central quantum gravity region and the external classical gravity region of black holes. The classical and quantum dual gravity regions of the space–time are entangled. (vii) The general classical-quantum gravity duality is associated with the Metaplectic $Mp\left(n\right)$ group symmetry which provides the complete full covering of the phase space and of the quantum space–time mapped from it. Full article

In the process of using structured light technology to obtain indoor point clouds, due to the limited field of view of the device, it is necessary to obtain multiple point clouds of different wall surfaces. Therefore, merging the point cloud is necessary to acquire a complete point cloud. However, due to issues such as the sparse geometric features of the wall point clouds and the high similarity of multiple point clouds, the merging effect of point clouds is poor. In this paper, we leverage artificially enhanced features to improve the accuracy of registration in this scenario. Firstly, we design feature markers and present their layout criteria. Then, the feature information of the marker is extracted based on the Color Signature of Histograms of OrienTations (Color-SHOT) descriptor, and coarse registration is realized through the second-order similarity measure matrix. After that, precise registration is achieved using the Iterative Closest Point (ICP) method based on markers and overlapping areas. Finally, the global error of the point cloud registration is optimized by loop error averaging. Our method enables the high-precision reconstruction of integrated home design scenes lacking significant features at a low cost. The accuracy and validity of the method were verified through comparative experiments. Full article

In order to improve the simulation efficiency under the premise of ensuring the fidelity of synthetic aperture radar (SAR) simulation images, we propose a BVH-assisted fast SAR image simulation method based on spatial segmentation. The beam scanning model is established based on RD imaging geometric relation, and the bounding volume hierarchy (BVH) algorithm is used to assist in obtaining the time-varying latticed radiation and shadow areas within the radar beam, combining them with the real-time position of the sensors to complete the simulation of the electromagnetic (EM) wave transmission. The ray tracing algorithm is used to calculate the multiple backscatter fields of EM waves, including various material properties of the target surface. The SAR spatial traversal is adopted to spatially segment the latticed radiation area, and the compute unified device architecture (CUDA) kernel function is designed using the echo matrix cell method to make each cell of the target echo matrix as a subfield of the backscattering field, and the position of the echo matrix cell is traversed to obtain the target backscattering field. The target simulated echo is processed by the range Doppler (RD) imaging algorithm to obtain the SAR-simulated image. The simulation results show that compared with a CPU single-thread simulation, the simulation speed of the proposed method is significantly improved, and the SAR simulation image has high structural similarity with the real image, which fully verifies the effectiveness of the proposed method. Full article