Search Results (1,308)

Accurate user-equipment positioning is crucial for the successful deployment of 5G New Radio (NR) networks, particularly in dense urban and vehicular environments where multipath effects and signal blockage frequently compromise GNSS reliability. Building upon the pseudo-signal-word (PSW) paradigm initially developed for low-power wide-area networks, this paper proposes GeoNR-PSW, a novel localization architecture designed for sub-6 GHz (FR1, 2.8 GHz) and mmWave (FR2, 60 GHz) fingerprints from the Raymobtime S007 dataset. GeoNR-PSW encodes 5G channel snapshots into concise PSW sequences and leverages a frozen GPT-2 backbone enhanced by lightweight PSW-Adapters to enable few-shot 3D localization. Despite the limited size of the dataset, the proposed method achieves median localization errors of 5.90 m at FR1 and 3.25 m at FR2. These results highlight the potential of prompt-aligned language models for accurate and scalable 5G positioning with minimal supervision. Full article

This paper proposes an approach to identify interacting objects (IOs) and determine their interaction losses (ILs) using point cloud data from wide-band double-directional channel sounding data. The scattering points (SPs) were identified using the maximum likelihood-based approach applied to the high-resolution path parameters estimated from the channel sounding data, and then IOs were identified via visual inspection of SPs within a 3D point cloud. The proposed approach utilizes all path parameters to calculate the approximate likelihood function for all candidate SPs to determine the SP, regardless of the propagation mechanism. The proposed technique was demonstrated at a suburban residential site with a frequency of 11 GHz. The results show that IOs that are not usually considered in the ray-tracing simulation were identified. Full article

With the development of modern agricultural technology, plant factories have become an important way to achieve efficient and sustainable crop production. Accurate understanding of the light received by plants is the key to improving the light energy utilization efficiency of lamps and ensuring the benefits of plant factories. Ray tracing technology, as one of the key technologies in plant factories, is of great significance to analyze the growing light environment of vegetables. Spinach has high nutritional value and is loved by the public and is one of the main crops grown in plant factories. In this paper, LightTools, TracePro, and Ansys Lumerical FDTD Solution, which are currently mature light environment tracking software in the field of lighting, are selected as the research objects to investigate their performance in simulating the light environment of spinach leaf surfaces under different planting arrangements and different lamp source distances. The results show as follows: Under the rectangular planting arrangement, the leaves received more light, and the plants grew faster. Different planting arrangements of plants had little effect on the simulation effect of the same kind of software, but the simulation effect of the three kinds of software under the same planting arrangement was significantly different, and the difference between the simulated value and the measured value of TracePro was the least. Further, TracePro was used to trace and simulate the leaf surface light conditions of spinach under a rectangular planting arrangement at different lighting distances, and the simulation results showed that there was no significant difference between the software simulation value and the measured value, and the simulation accuracy was the highest when the distance from the light source was 30 cm. Therefore, TracePro software can accurately simulate the light intensity of spinach leaves during the growth process and is most suitable for monitoring the change of light environment of spinach growth in plant factories. Full article

Visibility of the sea plays a significant role in shaping spatial perception, property value, and planning decisions in coastal areas. While traditional GIS-based viewshed analysis provides useful tools for modeling visibility, it remains limited by its 2.5D nature and simplified representations of terrain and vegetation. This study presents a 3D ray-tracing-based method for analyzing water surface visibility using high-resolution LIDAR data and physically based rendering techniques within a fully 3D environment. The methodology allows for realistic modeling of visibility from a human perspective, accounting for complex occlusions caused by buildings, terrain, and vegetation. Unlike conventional GIS tools, the proposed approach identifies visible areas beneath tree canopies and enables vertical exploration of visibility from different elevations and building floors. The method was applied in a case study of the coastal city of Świnoujście, Poland. The resulting viewshed was validated through photographic field verification from observer height (1.7 m), confirming the accuracy of visibility predictions. This research demonstrates the potential of ray-tracing methods in landscape and urban visibility analysis, offering a flexible and perceptually accurate alternative to traditional GIS-based approaches. Future work will focus on quantifying the visible extent of the water surface to support more detailed assessments of visual exposure in planning and conservation context. Full article

The deep-sea convergence zone (CZ) is a critical phenomenon for long-range underwater acoustic propagation. Accurate prediction of its distance, width, and gain is essential for enhancing sonar detection performance. However, conventional ray-tracing models, which assume vertically stratified sound speed profiles (SSPs), fail to account for horizontal sound speed gradients in the mixed layer, leading to significant prediction errors. To address this, we propose a novel ray-tracing model that incorporates horizontally inhomogeneous SSPs in the mixed layer. Our approach combines empirical orthogonal function (EOF) decomposition with the Del Grosso sound speed formula to construct a continuous 3D sound speed field. We further derive a modified ray equation including horizontal gradient terms and solve it using a fourth-order Runge–Kutta method. Simulation and experimental validation in the South China Sea demonstrate that our model reduces the prediction error for the first CZ distance by 2.26%, width by 2.66%, and gain deviation by 5.85% compared to the Bellhop model. These results confirm the effectiveness of our method in improving CZ parameter prediction accuracy. Full article

A new type of vesuvianite jade has recently been discovered in Hanzhong City, Shaanxi Province, China. However, a systematic investigation into its mineralogical characteristics and the origin of its color is currently lacking. In this study, the gemological, mineralogical, and spectroscopic properties of the Hanzhong vesuvianite jade were comprehensively analyzed using a suite of modern analytical techniques, including standard gemological testing, polarizing microscopy, X-ray powder diffraction, Fourier-transform infrared spectroscopy, laser Raman spectroscopy, UV-visible absorption spectroscopy, and X-ray fluorescence spectroscopy. The origin of the jade’s color was also preliminarily investigated. The results indicate that the samples are primarily composed of vesuvianite, with associated minerals including minor amounts of grossular, chlorite, and diopside, and trace amounts of calcite, epidote, chromite, and titanite. The pale green patches consist mainly of chlorite and grossular, the dark green bands are predominantly chlorite, and the dark brown patches are composed of abundant, disseminated microcrystalline chromite intermixed with uvarovite (calcium chromium garnet). The major chemical components of the vesuvianite jade matrix are SiO₂, Al₂O₃, and CaO. Specifically, SiO₂ ranges from 37.01 to 38.54 wt.%, Al₂O₃ from 18.48 to 22.84 wt.%, and CaO from 37.16 to 40.04 wt.%. Minor amounts include MgO (0.76–4.39 wt.%) and FeO_T (total iron expressed as FeO, 0.56–2.09 wt.%). The yellowish-green color of the matrix originates from a combination of ligand-to-metal charge transfer of Fe³⁺, crystal field transitions of Fe³⁺, and intervalence charge transfer between Fe²⁺ and Fe³⁺ in vesuvianite. The emerald-green color of the patches results from the synergistic effect of Fe and Cr; Fe provides a yellowish-green background color, upon which the crystal field transitions of Cr³⁺ (indicated by a doublet at 686/696 nm) impose strong absorption in the red region, resulting in a more vivid green hue. Full article

Sindbis virus (SINV), a prototype of the Alphavirus genus (family Togaviridae), is a globally distributed arbovirus causing febrile rash and debilitating arthritis in humans. Viral structural proteins—capsid (C), E1, and E2—are fundamental to the virion’s architecture, mediating all stages from assembly to host cell entry and pathogenesis, thus representing critical targets for study. This review consolidates the historical and current understanding of SINV structural biology, tracing progress from early microscopy to recent high-resolution cryo-electron microscopy (cryo-EM) and X-ray crystallography. We detail the virion’s precise T = 4 icosahedral architecture, composed of a nucleocapsid core and an outer glycoprotein shell. Key functional roles tied to protein structure are examined: the capsid’s dual capacity as a serine protease and an RNA-packaging scaffold that interacts with the E2 cytoplasmic tail; the E1 glycoprotein’s function as a class II fusion protein driving membrane fusion; and the E2 glycoprotein’s primary role in receptor binding, which dictates cellular tropism and serves as the main antigenic target. Furthermore, we connect these molecular structures to viral evolution and disease, analyzing how genetic variation among SINV genotypes, particularly in the E2 gene, influences host adaptation, immune evasion, and the clinical expression of arthritogenic and neurovirulent disease. In conclusion, the wealth of structural data on SINV offers a powerful paradigm for understanding alphavirus biology. However, critical gaps persist, including the high-resolution visualization of dynamic conformational states during viral entry and the specific molecular determinants of chronic disease. Addressing these challenges through integrative structural and functional studies is paramount. Such knowledge will be indispensable for the rational design of next-generation antiviral therapies and broadly protective vaccines against the ongoing threat posed by SINV and related pathogenic alphaviruses. Full article

Beryl is classified as a cyclosilicate mineral, and its color is primarily determined by the type and oxidation state of trace elements. In this study, natural yellow-green beryl was used as the research subject, and heat treatment experiments were performed at various temperatures under both oxidizing and reducing atmospheres. A combination of analytical techniques, including electron probe microanalysis (EPMA), X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), Raman spectroscopy, and ultraviolet-visible spectroscopy (UV-Vis), were employed to systematically investigate the composition, structure, and chromogenic mechanisms of beryl before and after heat treatment. The experimental results indicate that heat treatment under both atmospheres can lead to the transformation of yellow-green beryl into blue, with 500–600 °C under a reducing atmosphere identified as the optimal treatment condition. With increasing temperature, beryl gradually dehydrates, resulting in a faded blue color and reduced transparency. Even after treatment at 700 °C, no significant changes in unit cell parameters were observed, and both type I and type II water were retained, indicating that the color change is not attributed to crystal structure transformation or phase transitions. The study reveals that the essential mechanism of color modification through heat treatment lies in the valence change between Fe²⁺ and Fe³⁺ occupying channel and octahedral sites. The observed color variation is attributed to changes in absorption band intensity resulting from charge transfers of O²⁻ → Fe³⁺ and Fe²⁺ → Fe³⁺. This study provides theoretical insights and technical references for the color enhancement of beryl through heat treatment. Full article

We propose a novel systematic approach for the deployment optimization of unmanned aerial vehicles (UAVs). In this context, this study focuses on enhancing the coverage of UAV-mounted 6G mobile base stations. The number and placement optimization of UAV-mounted 6G mobile base stations, deployed to support terrestrial base stations during periods of increased population density in a given area, are addressed using a symbolic limited optimal discrete controller synthesis technique. Within the scope of this study, the UAVs’ altitude and attitude behaviors are optimized to ensure the most efficient trajectory toward the designated base station coordinates. Additionally, at their new locations, these behaviors are adjusted to facilitate accurate coverage estimation from the base stations they serve. In the deployment optimization of UAVs, the placement of base stations is determined using received signal strength data obtained through the ray-tracing-based channel modeling technique. The channel model considered critical parameters such as path loss, received power, weather loss, and foliage loss. Final average path loss values of 102.3 dB, 111.7 dB, and 127.4 dB were obtained at the carrier frequencies of 7 GHz, 26 GHz, and 140 GHz, respectively. These findings were confirmed with MATLAB-based ray tracing simulations. Our proposed approach is validated through experimental evaluations, demonstrating superior performance compared to existing methods reported in the literature. Full article

Air-to-air (A2A) communication plays a vital role in low-altitude unmanned aerial vehicle (UAV) networks and demands accurate channel modeling to support system analysis and design. A key challenge in A2A channel modeling lies in extracting reliable cluster characteristics, which are often limited due to the scarcity of measurement data. To overcome this limitation, a cluster characteristic analysis method is proposed for UAV A2A channels in built-up environments. First, we reconstruct virtual urban environments, followed by the acquisition of A2A channel data using ray tracing (RT) techniques. Then, a kernel power density (KPD) clustering algorithm is applied to group the multipath components (MPCs). To enhance the modeling accuracy of intra-cluster angular offsets in both elevation and azimuth domains, a Wasserstein generative adversarial network with gradient penalty (WGAN-GP) is further introduced for generative modeling. A comprehensive analysis is conducted on key cluster characteristics, including the intra-cluster number of MPCs, intra-cluster delay and angular spreads, number of clusters, and angular distributions. The numerical results demonstrate that the proposed WGAN-GP-based approach achieves superior angular fitting accuracy compared to conventional empirical distribution methods. Full article

Aryl diazonium salt chemistry offers a robust and versatile approach for the modification of material surfaces via the covalent immobilization of reactive functional groups under mild conditions. In this study, this strategy was successfully applied to graft the chelating agent 4-(2-pyridylazo)resorcinol (PAR) onto Amberlite XAD-4 resin. Initially, 4-nitrobenzenediazonium tetrafluoroborate (NBDT) was covalently anchored onto the resin surface using hypophosphorous acid as a reducing catalyst to introduce aryl nitro groups. These nitro groups were subsequently reduced to aniline functionalities, enabling diazo coupling with PAR. The successful modification of the resin was confirmed by ATR-FTIR spectroscopy, thermogravimetric analysis (TGA), and X-ray photoelectron spectroscopy (XPS). The synthesized chelating resin exhibited sorption capacities of 0.152, 0.167, and 0.172 mM g⁻¹ for Co(II), Ni(II), and Cu(II), respectively. The functionalized resin was packed into standard SPE cartridges and employed as a selective sorbent for the extraction and preconcentration of trace metals from groundwater samples collected from Dhalamah Valley, Al-Madinah Al-Munawwarah, prior to quantification by inductively coupled plasma mass spectrometry (ICP-MS). These results demonstrate the effectiveness of rapid diazonium-based surface functionalization for the preparation of selective polymeric metal chelators suitable for the extraction of trace metals from complex groundwater matrices. Full article

Acoustic Emission tomography (AET) has the potential to visualize damage in existing structures, contributing to structural health monitoring. Further, AET requires only the arrival times of elastic waves at sensors to identify velocity distributions, as source localization based on ray-tracing is integrated into its algorithm. Thus, AET offers the advantage of easy acquisition of measurement data. However, accurate source localization requires a large number of elastic wave source candidate points, and increasing these candidates significantly raises the computational resource demand. Lagrange Interpolation has the potential to reduce the number of candidate points, optimizing computational resources, and this potential has been validated numerically. In this study, AET incorporating Lagrange Interpolation is applied to identify the velocity distribution in a defective concrete plate, validating its effectiveness using measured wave data. The validation results show that the defect location in the concrete plate is successfully identified using only 36 source candidates, compared to the 121 candidates required in conventional AET. Furthermore, when using 36 source candidates, the percentage error in applying Lagrange Interpolation is 8.4%, which is significantly more accurate than the 25% error observed in conventional AET. Therefore, it is confirmed that AET with Lagrange Interpolation has the potential to identify velocity distributions in existing structures using optimized resources, thereby contributing to the structural health monitoring of concrete infrastructure. Full article

Carbon-based nanocomposites coated with iron oxides were synthesized using a wet impregnation method with thermally annealed coal and an iron nitrate precursor. The influence of the thermal treatment atmosphere (air, vacuum, or nitrogen) on the morphology, structure, and magnetic properties of the nanocomposites was examined by X-ray diffraction, Raman spectroscopy, and transmission electron microscopy. It was found that the vacuum thermal treatment produced carbon-based nanocomposite containing iron oxide with the highest crystallinity, according to XRD analysis, while also inducing the greatest degree of structural defects in the carbon matrix, as evidenced by Raman analysis. Mössbauer spectroscopy confirmed that all thermal treatment methods promote the formation of the hematite phase, which was found to be the only phase formed in the air-treated nanocomposites, whereas traces of magnetite and the formation of Fe(OH)₃ were detected in the vacuum- and nitrogen-treated nanocomposites, respectively. Magnetic characterization revealed that all nanocomposites exhibit ferromagnetic-like behavior, attributed to the weak ferromagnetic nature of hematite. The best magnetic response (highest saturation magnetization with the widest hysteresis loop) was observed in the vacuum-treated nanocomposites. These findings collectively demonstrate that the synthesis atmosphere plays a crucial role in tailoring the structural and magnetic characteristics of carbon-based iron oxide nanocomposites, offering pathways for their optimization in applications such as catalysis, environmental remediation, or sensing technologies. Full article

Silicon carbide (SiC), a wide-bandgap semiconductor, is renowned for its exceptional performance in power electronics and extreme-temperature environments. However, precision low-loss laser slicing of SiC is impeded by energy divergence and crack delamination induced by refractive-index-mismatch interfacial aberrations. This study presents an integrated laser slicing system based on a liquid crystal on silicon spatial light modulator (LCOS-SLM) to address aberration-induced focal elongation and energy inhomogeneity. Through dynamic modulation of the laser wavefront via an inverse ray-tracing algorithm, the system corrects spherical aberrations from refractive index mismatch, thus achieving precise energy concentration at wanted depths. A laser power attenuation model based on interface reflection and the Lambert–Beer law is established to calculate the required laser power at varying processing depths. Experimental results demonstrate that aberration correction reduces focal depth to approximately one-third (from 45 μm to 15 μm) and enhances energy concentration, eliminating multi-layer damage and increasing crack propagation length. Post-correction critical power measurements across depths are consistent with model predictions, with maximum error decreasing from >50% to 8.4%. Verification on a 6-inch N-type SiC ingot shows 90 μm damage thickness, confirming system feasibility for SiC laser slicing. The integrated aberration-correction approach provides a novel solution for high-precision SiC substrate processing. Full article

This work probes the possibility of controlling the morphology of silver crystals through inoculation of trace-level metallic species, building on an industrial-scale cooling process. The obtained crystals are analyzed via X-ray tomography (XRT), dynamic picture analysis, and scanning electron microscopy (SEM). The results reveal assemblages composed of octahedral crystals and triangular platelets. X-ray tomography yields pore size distributions that correlate with Ag% composition. Out of several trace metals tested, cadmium was found to yield a greater number of octahedral morphologies with pronounced twinning, contributing to a fibrous structure. This behavior is consistent with the energetic preference of cadmium atoms to integrate on Ag (111) planes and the limitation of twinning to the (111) planes in FCC metals. Faceting of the interiors of the triangular facets of octahedral crystals is noted in all SEM images of acid-washed samples. These physical features are interpreted as a product of crystal growth and not selective acid etching. The generation of octahedral silver crystals from a molten melt and the presence of faceting are research firsts, such crystal morphologies being previously generated only from aqueous chemical reduction systems. Adding traces of cadmium to primary lead melts is promising for producing silver nanocrystals with desired morphologies. Full article