Search Results (562)

Short-range forces enable peridynamics to simulate impact, yet it demands a computationally expensive contact search and includes no intrinsic damping. A significantly more efficient solution is the coupled dual-horizon peridynamics–discrete element method approach, which provides a robust framework for modeling fracture. The peridynamics component handles the nonlocal continuum mechanics capabilities to predict material damage and fracture, while the discrete element method captures discrete particle behavior. Whereas existing peridynamics–discrete element method approaches assign discrete element method particles to many or all surface peridynamics points, the proposed method integrates dual-horizon peridynamics with a single discrete element particle representing each object. Contact forces are computed once per discrete element pair and mapped to overlapping peridynamics points in proportion to shared volume, conserving linear momentum. Benchmark sphere-on-plate impact demonstrates prediction of peak contact force, rebound velocity, and plate deflection within 5% of theoretical results found in the literature, while decreasing neighbour-search cost by more than an order of magnitude. This validated force-transfer mechanism lays the groundwork for future extension to fully resolved fracture and fragmentation. Full article

The increasing integration of artificial intelligence agents (AIAs) based on large language models (LLMs) is transforming many spheres of society. These agents act as human assistants, forming Distributed Intelligent Systems (DISs) and engaging in opinion formation, consensus-building, and collective decision-making. However, complex DIS network topologies introduce significant uncertainty into these processes. We propose a quantum-inspired graph signal processing framework to model collective behavior in a DIS interacting with an external environment represented by an influence matrix (IM). System topology is captured using scale-free and Watts–Strogatz graphs. Two contrasting interaction regimes are considered. In the first case, the internal structure fully aligns with the external influence, as expressed by the commutativity between the adjacency matrix and the IM. Here, a renormalization-group-based scaling approach reveals minimal reservoir influence, characterized by full phase synchronization and coherent dynamics. In the second case, the IM includes heterogeneous negative (antagonistic) couplings that do not commute with the network, producing partial or complete spectral disorder. This disrupts phase coherence and may fragment opinions, except for the dominant collective (Perron) mode, which remains robust. Spectral entropy quantifies disorder and external influence. The proposed framework offers insights into designing LLM-participated DISs that can maintain coherence under environmental perturbations. Full article

This study explores Eastern Orthodox aesthetics through a parallax lens, situating it at the intersection of theology, anthropology, and cultural practice to move beyond the icon-centric discourse. It examines how Orthodox aesthetics, rooted in the theological vision of beauty as divine disclosure, manifests in liturgical ethos, material culture, and secular artistic expression. The analysis draws on Christos Yannaras’ ethos of liturgical art, Chrysostomos Stamoulis’ exercise in philokalic aesthetics, and Timothy Carroll’s ethnographic material ecology of Orthodox Christianity, revealing beauty as an ontological event of communion and transformation. A parallax shift to Dionysis Savvopoulos’ lyrics uncovers an aesthetic eschatology, or an aesthetics of eschatology, where Orthodox themes of resurrection and festivity permeate non-ecclesial Greek culture. Employing a comparative, interdisciplinary methodology, the study integrates theological reflection, ethnographic insights, and cultural analysis. It concludes that Orthodox aesthetics is a dynamic field where beauty, truth, and eschatological hope converge, extending beyond the sanctuary into everyday practices and popular art—“incarnated” in material reality. This transdisciplinary approach reconfigures Orthodox aesthetics as a theological anthropology, offering fresh perspectives on its role in contemporary discourse and its diffusion into the public sphere, while advocating for material culture as a critical lens for future exploration. Full article

This paper proposes a reconstruction framework for estimating the far-field (FF) radiation patterns of large, heavy, or non-rotatable wireless-enabled systems. The method combines a tilted orbital sampling (ToS) strategy with sparse spherical harmonic (SH) expansion, compressed sensing (CS), and convex optimization (CO), thereby linking a mechanically constrained acquisition scheme with a mathematically efficient recovery process. The purpose of this integration is not only to reduce the number of measurements but also to retrieve the radiation information most relevant to Internet of Things (IoT) devices and bulky equipment that cannot be easily rotated within anechoic chambers. The framework is validated on two representative cases: a canonical half-wave dipole and a commercial Wi-Fi-enabled device. In the latter and more challenging case, accurate reconstruction is achieved with fewer than 30 SH coefficients and using less than 20% of the measurements required by a conventional full-sphere scan, with the normalized root-mean-square error remaining below 5%. Although inaccessible angular regions may be partially uncharacterized, such directions are of minor relevance for the intended operational coverage. The resulting SH-based representation can be seamlessly integrated into ray-tracing propagation simulators and electromagnetic optimization workflows, enabling efficient and application-oriented OTA characterization under realistic chamber constraints. Full article

To enhance the field calibration capability of ground-based lunar observation instruments for long-term continuous monitoring and to optimize the stability and traceability of lunar observation data, this manuscript presents the development of a SI traceable Portable Self-calibrating Absolute Radiation Source (PSARS) based on an electrical substitute radiometer. A self-calibrating radiation transfer model has been established. The system features a “+” structure layout centered around an integrating sphere, which ensures uniformity of the light source while improving system integration. Preliminary performance testing results indicate that PSARS achieves excellent radiative planar uniformity and angular uniformity within the targeted area, both exceeding 99%. During the self-calibration cycle of PSARS, the detector demonstrates high measurement stability for the built-in light source. Ultimately, through comparative validation and uncertainty assessment, the self-calibration accuracy of spectral irradiance for PSARS in the 400–1000 nm wavelength range is better than 2%, meeting the demands for high-frequency, high-stability, and high-precision real-time on-site radiometric calibration under ground-based lunar observation field test conditions. This provides technical support for the construction of high-precision lunar models and the widespread application of lunar calibration technologies. Full article

Addressing the urgent need for robust and sustainable catalysts to detoxify nitroaromatic pollutants, this study introduces a novel approach for synthesizing cobalt oxide nanocomposites via pyrolysis of cobalt benzene-1,3,5-tricarboxylate. By integrating porous carbon (PC) and nano silica (NS) supports with Co₃O₄ to form (Co₃O₄/PC) and (Co₃O₄/NS), we achieved precise morphological control, as evidenced by SEM and TEM analysis. SEM revealed 80–500 nm Co₃O₄ microspheres, 300 nm Co₃O₄/PC microfibers, and 2–5 µm Co₃O₄/NS spheres composed of 100 nm nanospheres. TEM further confirmed the presence of ~15 nm nanoparticles. Additionally, FTIR spectra exhibited characteristic Co–O bands at 550 and 650 cm⁻¹, while UV–Vis absorption bands appeared in the range of 450–550 nm, confirming the formation of cobalt oxide structures. Catalytic assays toward p-nitrophenol reduction revealed exceptional kinetics (k = 0.459, 0.405, and 0.384 min⁻¹) and high turnover numbers (TON = 5.1, 6.7, and 6.3 mg 4-NP reduced per mg of catalyst), outperforming most of the recently reported systems. Notably, both supported catalysts retained over 95% activity after two regeneration cycles. These findings not only fill a gap in the development of efficient, regenerable cobalt-based catalysts, but also pave the way for practical applications in environmental remediation. Full article

This study presents an improved UAV-based structure inspection method that integrates advanced 3D modeling and optimized path planning with obstacle avoidance. The system uses Meshroom, an open-source software, to combine multiple sets of 3D point clouds collected by a UAV-mounted 3D camera into a complete 3D model of the structure. Because point cloud data typically contain an overwhelming number of points, they are grouped into smaller sets, each represented by an oriented bounding box (OBB). This step significantly reduces the complexity in path-planning calculations. The UAV, modeled as a flying sphere, initially moves along a straight path from its starting point to a target position. A gradient-based optimization method then adjusts this trajectory to maintain a safe distance between the UAV and the OBBs representing the obstacles. The results show that the proposed method successfully generates safe and efficient UAV flight paths, improving both the accuracy and safety of UAV-based structure inspections. Full article

In additive manufacturing (AM), particularly with AlSi10Mg aluminum alloy produced via Laser Powder Bed Fusion (L-PBF), understanding and detecting defects is crucial for ensuring mechanical integrity. This study evaluates the effectiveness of active thermography as a fast, non-destructive testing (NDT) method for identifying typical L-PBF defects. Artificial defects (cubes, spheres, cylinders with unfused powder) were introduced by varying printing parameters. Their real geometry was assessed via micro-computed tomography (μ-CT), revealing deviations from nominal shapes. Thermographic tests using a laser heat source (≈40 W/cm²) were conducted to examine the detectability of these defects in the highly diffusive material AlSi10Mg. Results highlight both the limitations and potential of thermography as a cost- and time-effective alternative to μ-CT for quantitative inspection. Full article

LED strips are increasingly used as lighting sources in public and private spaces. However, traditional photometric methods, such as integrating spheres, are unsuitable for measuring their light parameters, often resulting in significant errors and requiring expensive instrumentation or calibration. These errors are typically caused by non-uniform illumination of the internal surface or improper internal geometry, especially when measuring LED sources. This article presents the development of a low-cost integrating device specifically designed to measure LED strips’ light parameters. The device is a compact cube with a volume of less than 1.0 m³. It was tested against alternative methods using an integrating sphere and a goniophotometer in a professional photometric laboratory. The verification results confirmed its effectiveness. The device showed the maximum relative error of luminous flux measurement to be around 5% compared with the accurate, expensive goniophotometric method. For colorimetric measurements, the maximum Correlated Color Temperature (CCT) absolute error was about 35 K for an LED strip with a CCT of 4000 K, indicating a difference imperceptible to the human eye. These results demonstrate the device’s proper relevance in the research and development of LED strip-based lighting equipment to improve lighting equipment quality and control processes. The device is easy to replicate, significantly reducing production and transportation costs, making it an excellent solution for companies and research units seeking a cost-effective method for LED strip measurements. Additionally, the device can measure other light sources or luminaires with reasonably small sizes emitting light in only one hemisphere. The device is the basis of a patent application. Full article

In this paper, we first make and discuss a conjecture concerning Newtonian potentials in Euclidean n space which have all their mass on the unit sphere about the origin and are normalized to be one at the origin. The conjecture essentially divides these potentials into subclasses whose criteria for membership is that a given member has its maximum on the closed unit ball at most M and its minimum at least d. It then lists the extremal potential in each subclass, which is conjectured to solve certain extremal problems. In Theorem 1, we show the existence of these extremal potentials. In Theorem 2, we prove an integral inequality on spheres about the origin, involving so-called extremal potentials, which lends credence to the conjecture. Full article

Cancer stem cells (CSCs), a subpopulation of tumor cells endowed with self-renewal capacity, drive cancer initiation and progression. While long non-coding RNAs (lncRNAs) are increasingly recognized as critical regulators of CSC stemness, their specific roles in gastric cancer stem cells (GCSCs) remain poorly understood. This study investigates the functional significance of lncRNA TSPEAR-AS2 in modulating GCSC properties and uncovers its underlying molecular mechanisms. Through integrated whole-transcriptome sequencing, bioinformatics analysis, and validation in 48 paired gastric cancer tissues and adjacent normal tissues, TSPEAR-AS2 was identified as a differentially expressed lncRNA upregulated in both GCSCs and tumor samples. Functional experiments revealed that TSPEAR-AS2 overexpression significantly enhanced GCSC sphere-forming ability, proliferation, cell cycle progression, epithelial–mesenchymal transition (EMT), and expression of stemness markers (CD54, CD44, OCT4, NANOG, and SOX2) while suppressing apoptosis. Conversely, TSPEAR-AS2 knockdown attenuated these malignant phenotypes. In vivo tumorigenicity assays in nude mice further confirmed that TSPEAR-AS2 promotes tumor growth, with overexpression accelerating and knockdown inhibiting tumor formation. Mechanistically, bioinformatics predictions and dual-luciferase reporter assays established TSPEAR-AS2 as a competing endogenous RNA (ceRNA) that sponges miR-15a-5p, thereby derepressing the miR-15a-5p target gene CCND1. Rescue experiments demonstrated that overexpression of miR-15a-5p phenocopied TSPEAR-AS2 knockdown, reducing GCSC stemness, while miR-15a-5p inhibition rescued the effects of TSPEAR-AS2 suppression. Collectively, these findings reveal a novel TSPEAR-AS2/miR-15a-5p/CCND1 regulatory axis that sustains GCSC stemness and tumorigenicity. These results highlight TSPEAR-AS2 as a potential therapeutic target for eradicating gastric cancer stem cells and improving clinical outcomes. Full article

Background: The COVID-19 pandemic exposed major structural deficiencies in global health governance, including stark inequities in vaccine access, intervention timing, and mortality outcomes. While economic resources played a role, the influence of governance performance remains insufficiently examined. This study addresses a significant gap by integrating governance metrics with pandemic response data to assess how governance quality, independent of income level, affected national outcomes. Although the Oxford COVID-19 Government Response Tracker (OxCGRT) dataset has been widely used to document policy responses, this study offers a novel contribution by linking these policy interventions with governance performance and evaluating their joint effect on health outcomes and vaccine equity. Methods: This mixed-methods study combines quantitative analysis of global datasets with a qualitative literature review. Quantitative data were mainly obtained from the Oxford COVID-19 Government Response Tracker (OxCGRT), the World Bank’s Worldwide Governance Indicators (WGIs), and World Bank/WHO databases. A governance performance index was constructed using two WGI components: Government Effectiveness and Regulatory Quality. Countries were grouped into high, medium, or low governance categories. Statistical tests included ANOVA, Kaplan Meier survival analysis, and multivariable OLS regression. The qualitative component reviewed 45 academic and institutional sources on governance performance during COVID-19. Results: Countries with high governance performance had earlier public health interventions, lower mortality, and broader vaccine coverage, independent of income level. Kaplan Meier analysis revealed faster school closures in these countries (p < 0.01). Multivariable regression showed governance remained a significant predictor after adjusting for income and health spending. Qualitative findings highlighted recurring weaknesses in legal enforceability, intergovernmental coordination, and global financing mechanisms. Conclusions: Governance performance had a decisive impact on pandemic outcomes. The COVID-19 crisis revealed the need for robust governance systems capable of responding to complex emergencies that extend beyond the health sector into institutional, economic, and social spheres. Full article

The bond market serves dual roles in fiscal and financial spheres, playing a crucial role in coordinating monetary policy. This paper investigates the impact of quantitative and price-based monetary policies on the liquidity level of China’s bond market. A comprehensive index measuring the liquidity of the local bond market is constructed using a combination weighting method that integrates the entropy method and the coefficient of variation. Employing the time-varying stochastic volatility structure vector autoregression (TVP-SV-SVAR) model on data spanning from 2013 to 2021, this study empirically compares the impulse response of local bond market liquidity to monetary policy shocks. The findings reveal that both types of monetary policy operations exhibit asymmetric, nonlinear, and time-varying impacts on bond market liquidity. Quantitative monetary instruments induce deeper impulse responses, with longer-lasting effects. These conclusions offer insights for monetary policy reforms and bond market development in China. Full article

In this work, we present the procedure to obtain exact spherical shape functions for finite element modeling applications, without resorting to any kind of approximation, for generic prismatic spherical elements and for the case of spherical six-node tri-rectangular and eight-node quadrangular spherical prisms. The proposed spherical shape functions, given in explicit analytical form, are expressed in geographic coordinates, namely colatitude, longitude and distance from the center of the sphere. We demonstrate that our analytical shape functions satisfy all the properties required by this class of functions, deriving at the same time the analytical expression of the Jacobian, which allows us changes in coordinate systems. Within the perspective of volume integration on Earth, entering a variety of geophysical and geodetic problems, as for mass change contribution to gravity, we consider our analytical expression of the shape functions and Jacobian for the six-node tri-rectangular and eight-node quadrangular right spherical prisms as reference volumes to evaluate the volume of generic spherical triangular and quadrangular prisms over the sphere; volume integration is carried out via Gauss–Legendre quadrature points. We show that for spherical quadrangular prisms, the percentage volume difference between the exact and the numerically evaluated volumes is independent from both the geographical position and the depth and ranges from 10⁻³ to lower than 10⁻⁴ for angular dimensions ranging from 1° × 1° to 0.25° × 0.25°. A satisfactory accuracy is attained for eight Gauss–Legendre quadrature points. We also solve the Poisson equation and compare the numerical solution with the analytical solution, obtained in the case of steady-state heat conduction with internal heat production. We show that, even with a relatively coarse grid, our elements are capable of providing a satisfactory fit between numerical and analytical solutions, with a maximum difference in the order of 0.2% of the exact value. Full article

Efficient autonomous exploration in unknown obstacle cluttered environments with interior obstacles remains a challenging task for mobile robots. In this work, we present a novel exploration process for a non-holonomic agent exploring 2D spaces using onboard LiDAR sensing. The proposed method generates velocity commands based on the calculation of the solution of an elliptic Partial Differential Equation with Dirichlet boundary conditions. While solving Laplace’s equation yields collision-free motion towards the free space boundary, the agent may become trapped in regions distant from free frontiers, where the potential field becomes almost flat, and consequently the agent’s velocity nullifies as the gradient vanishes. To address this, we solve a Poisson equation, introducing a source point on the free explored boundary which is located at the closest point from the agent and attracts it towards unexplored regions. The source values are determined by an exponential function based on the shortest path of a Hybrid Visibility Graph, a graph that models the explored space and connects obstacle regions via minimum-length edges. The computational process we apply is based on the Walking on Sphere algorithm, a method that employs Brownian motion and Monte Carlo Integration and ensures efficient calculation. We validate the approach using a real-world platform; an AmigoBot equipped with a LiDAR sensor, controlled via a ROS-MATLAB interface. Experimental results demonstrate that the proposed method provides smooth and deadlock-free navigation in complex, cluttered environments, highlighting its potential for robust autonomous exploration in unknown indoor spaces. Full article