Search Results (252)

Landscape quality and the productivity of $\mathit{Rhododendron\; simsii}$ are directly related to the maintenance of ecological functions in the alpine region. The specific relationship between the spatial pattern of colour patches and the visual quality of R. simsii landscape recreational forests has been insufficiently explored. In this study, we constructed a model of the relationship between landscape colour patches and the aesthetic value of such a forest, analysing the key factors driving changes in its landscape quality. A total of 1549 participants were asked to assess 16 groups of landscape photographs. The results showed that variations in perceived aesthetic quality were stimulated by colour patch dynamics and spatial heterogeneity. Utilising structural equation modelling (SEM), we identified key indicators synergistically influencing aesthetic quality, including the area percentage, shape, and distribution of colour patches, which demonstrated strong explanatory power ($R^2$ = 0.83). The SEM also revealed that the red patch area, mean perimeter area ratio, and separation index are critical latent variables with standardised coefficients of 0.54, 0.65, and 0.62, respectively. These findings provide actionable design strategies: (1) optimising chromatic contrast through high-saturation patches, (2) controlling geometric complexity, and (3) improving spatial coherence. These results advance the theoretical framework for landscape aesthetic evaluation and offer practical guidance for landscape recreational forest management. Full article

Helical milling presents a promising alternative to conventional drilling for hole production, offering superior surface quality and improved production efficiency. While this technique has been extensively applied in the aerospace industry, its potential for machining common engineering materials, such as AISI 1045 steel, remains underexplored in the literature. This study addresses this gap by systematically evaluating the influence of key process parameters—cutting speed (V_c), axial depth of cut (a_p), and tool diameter (D_t)—on hole quality attributes, including surface roughness, burr formation, and nominal diameter accuracy. A full factorial experimental design (2³) was employed, coupled with analysis of variance (ANOVA), to quantify the effects and interactions of these parameters. The results reveal that, with a higher V_c, it is possible to reduce surface roughness (R_a) by 30% to 40%, while an increased a_p leads to a 50% increase in R_a. Additionally, D_t emerged as the most critical factor for nominal diameter accuracy, reducing geometrical errors by 1% with a larger D_t. Burr formation was predominantly observed at the lower end of the hole, highlighting challenges specific to this technique. These findings provide valuable insights into optimizing helical milling for low-carbon steels, offering a foundation for broader industrial adoption and further research. Full article

The equator’s unique combination of high humidity and temperature renders optical satellite imagery highly susceptible to persistent cloud cover. In contrast, synthetic aperture radar (SAR) offers a robust alternative due to its ability to penetrate clouds with microwave imaging. This study addresses the challenges of cloud-induced data gaps and cross-sensor geometric biases by proposing an advanced optical and SAR image-matching framework specifically designed for cloud-prone equatorial regions. We use a prompt-driven visual segmentation model with automatic prompt point generation to produce cloud masks that guide cross-modal feature-matching and joint adjustment of optical and SAR data. This process results in a comprehensive digital orthophoto map (DOM) with high geometric consistency, retaining the fine spatial detail of optical data and the all-weather reliability of SAR. We validate our approach across four equatorial regions using five satellite platforms with varying spatial resolutions and revisit intervals. Even in areas with more than 50 percent cloud cover, our method maintains sub-pixel edging accuracy under manual check points and delivers comprehensive DOM products, establishing a reliable foundation for downstream environmental monitoring and ecosystem analysis. Full article

This study investigated the radiation attenuation characteristics of commonly used dental implant materials across an energy spectrum relevant to dental radiology. Two titanium implants were examined, with densities of 4.428 g/cm³ and 4.51 g/cm³, respectively. The first consisted of 90.39% titanium, 5.40% aluminum, and 4.21% vanadium, while the second comprised 58% titanium, 33% oxygen, 7% iron, 1% carbon, and 1% nitrogen. The third material was a zirconia implant (5Y form) composed of 94.75% zirconium dioxide, 5.00% yttrium oxide, and 0.25% aluminum oxide, exhibiting a higher density of 6.05 g/cm³. Monte Carlo simulations (MCNP6) and XCOM data were utilized to estimate photon source parameters, geometric configuration, and interactions with biological materials to calculate the half-value layer, mean free path, and tenth-value layer at varying photon energies. The results indicated that titanium alloys are well suited for low-energy imaging modalities such as CBCT and panoramic radiography due to their reduced artifact production. While zirconia implants demonstrated superior attenuation at higher energies (e.g., CT), their higher density may induce beam-hardening artifacts in low-energy systems. Future research should validate these simulation results through in vitro and clinical imaging and further explore the correlation between material-specific attenuation and CBCT image artifacts. Full article

Coffee has significant economic importance in Brazil, which is the world’s largest exporter of this product. The main focus of this work is to obtain a computational model of coffee branches, using scanning techniques and experimental validation through modal analysis, to understand their mechanical behaviors due to dynamic and static properties. The main mechanical properties of the branches, including specific gravity and elastic modulus, were obtained in the laboratory and used as input parameters for the simulations. Geometric models were obtained by means of three-dimensional scanning and analyzed using the finite element method to predict the static and dynamic behaviors of the branches. The methodology was validated in experimental tests. The results of vibration frequencies obtained in the branches showed variations between simulations and experimental tests ranging from 2% to 20%, and the statistical analysis did not find significant differences. The results demonstrate important indicators for predicting the static and dynamic behaviors of plagiotropic branches of a coffee tree. These results can be considered in vibration analysis for coffee harvesting, which represents a technological advance in the area, since simplified models are usually obtained by geometric coordinates to obtain geometric models of a coffee tree. Full article

Aerosols play a crucial role in air quality, climate regulation, and public health; their timely monitoring is hence fundamental. The aerosol optical depth (AOD) is the parameter used to investigate the spatial–temporal distribution of aerosols from space. Specifically, the AOD retrieved from the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm applied to a Moderate Resolution Imaging Spectroradiometer (MODIS) is suitable for aerosol investigation at a local scale by exploiting its high spatial resolution (1 km × 1 km). In this study, the MAIAC AOD retrieval over Rome (Italy) was validated for the first time, using ground-based data provided by an AERONET station operating in a semi-rural environment close to the city, over a time series from January 2001 to December 2022. Moreover, AOD trends were evaluated in a study area encompassing Rome and its surroundings, characterized by a transition zone between urban and rural environments. The results show a general underestimation of the MAIAC AOD; specifically, the validation process highlighted the less accurate performance of the algorithm under higher aerosol loading and with predominantly coarse mode aerosol. Interesting results were obtained concerning the influence of the geometrical configuration of satellite acquisition on the accuracy of the MAIAC product. In particular, the solar zenith angle, the relative azimuth and the scattering angle between the principal plane of the sun and satellite synergistically influence retrievals. Finally, the spatial distribution of the AOD shows a decreasing trend over the 2001–2022 period and a strong influence of the city of Rome over the whole study area. Full article

X-ray imaging protocols in radiology departments often exhibit variability in exposure parameters and geometric setups, leading to inconsistencies in image quality and potential variations in patient dose. Objectives: This study aimed to harmonise and optimise chest and pelvis X-ray imaging protocols by standardising exposure parameters and geometric setups across departmental systems, minimising radiation dose while ensuring adequate image quality for accurate diagnosis. Methods: The image quality of five pelvic and three chest protocols across different radiographic systems was evaluated both quantitatively and visually. Visual image quality for both chest and pelvis protocols was assessed by radiologists and radiographers using the Visual Grading Analysis (VGA) method. Additionally, the quantitative image quality figure inverse (IQF_inv) metric for all protocols was determined using the CDRAD image quality phantom. Moreover, the patient radiation dose for both chest and pelvis protocols was evaluated using dose area product (DAP) values measured by the systems’ built-in DAP metres. Results: Different quantitative image quality and radiation dose to patients were achieved in various protocol settings for both chest and pelvis examinations, but the visual image quality assessment showed satisfactory image quality for all observers in both the pelvis and chest protocols. The selected protocols for harmonising chest radiography across all imaging systems result in reduced radiation exposure for patients while maintaining adequate image quality compared to the previously used system-specific protocol. Conclusions: The clinical protocol for chest and pelvis radiography has been standardised and optimised in accordance with patient radiation exposure and image quality. This approach aligns with the ALARA (As Low As Reasonably Achievable) principle, ensuring optimal diagnostic information while minimising the radiation risks. Full article

Efficient fruit production, quality improvement, and timely harvesting are essential in olive cultivation, which requires optimised distribution and management of fruiting sites. This study aimed to support sustainable olive crop management by analysing the morphological characteristics of five cultivars (Chemlali, Chetoui, Koroneiki, Meski, and Picholine) under semi-arid Tunisian conditions. Through a detailed architectural analysis, we investigated the relationships between branching patterns, density, distribution of inflorescence and fruit sites, biometric traits (shoot length, internode number, and shoot dimensions), and geometric variability within each cultivar. Three trees per cultivar were analysed across three architectural units. The results showed marked architectural differences, highlighting the need for cultivar-specific strategies in planting, pruning, and orchard management. The distribution of shoots across botanical orders revealed unique branching patterns: Chemlali and Koroneiki showed thinner shoots and higher shoot density, reflecting strong apical dominance and their suitability for hyper-intensive systems. In addition, nonsignificant differences in long shoots’ insertion angles between Meski, Chetoui, and Koroneiki suggest compatibility for co-cultivation, facilitating mechanised maintenance and harvesting. Emphasis on inter-cultivar compatibility and architectural coherence is crucial for orchard design. These findings provide important insights for optimising orchard management practices to improve productivity, fruit quality, and operational efficiency. Full article

With the development of intelligent manufacturing technology, the manufacturing industry is gradually realizing intelligent production. Especially for metal cutting with extremely complex processes, it is of great significance to realize intelligence. Taking the cutting process of aero-engine typical low-rigidity parts as the main line, this article builds an intelligent processing architecture based on a big data platform, which includes customized design of cutting tools, intelligent optimization of cutting parameters, simulation of cutting conditions, and online monitoring and control of cutting processes. At the same time, the realization of related key technologies is explained. Then, this article introduces in detail the intelligent decision-making process based on deep learning, the customized tool design process based on structural features, the simulation process of cutting based on geometric features of parts, as well as the monitoring and control process of Numerical Control (NC) machining based on condition perception. In addition, based on the processing requirements and difficulties of specific parts, formulate a specific intelligent implementation plan under this processing mode. Through the implementation of the above architecture and key technologies, the cutting processing system can automatically optimize the cutting parameters according to real-time working conditions and adjust its own cutting conditions. At the same time, machine tool condition, cutting tool condition, and low-rigidity part condition are real-time monitored to achieve high-precision, efficient, intelligent, and precise cutting of low-rigidity parts. The proposed architecture can provide a reference model for the research and application of intelligent cutting technology for low-rigidity parts. Full article

The combustion behavior and thermal performance of industrial-scale borax pentahydrate (Na₂B₄O₇·5H₂O) melting furnaces remain underexplored despite their critical role in boric oxide (B₂O₃) production, a key input for high-performance manufacturing. This study addressed this gap by employing three-dimensional computational fluid dynamics (CFD) simulations to model two operational natural gas-fired furnaces with distinct burner configurations (four-burner and six-burner systems). The analysis focused on optimizing burner placement, specifically, the axial distance and inclination angle, to enhance thermal uniformity and reduce refractory wall damage caused by aggressive high-temperature borate corrosion. A comprehensive parametric study of twelve burner configurations revealed that tilting the burners at 5–10° significantly improved temperature uniformity while reducing peak wall temperatures and mitigating localized hot spots. The optimal design, incorporating a 10° burner angle and a staggered burner arrangement (Case 11), attained a melt pool temperature of 1831.3 K and a charging average wall temperature of 1812.0 K. These values represent essential benchmarks for maximizing furnace efficiency and operational stability. The modified designs for the four- and six-burner systems led to improved temperature distributions and a notable reduction in maximum wall temperatures, directly contributing to longer maintenance intervals and improved refractory durability. The findings of this study confirm that minor geometrical and angular adjustments in burner placement can yield significant performance gains. The validated CFD approach and proposed design modifications offer a scalable, low-cost strategy for improving combustion efficiency and furnace lifespan in borax processing facilities. Full article

During the continuous casting process, the submerged entry nozzle (SEN) should be maintained at the geometric center of the mold. However, in actual production, factors such as deformation of the tundish bottom and inaccurate positioning of the traversing car occasionally cause SEN offset. SEN offset can make the molten steel flow field in the mold asymmetric, increasing the risks of slag entrainment on the surface of the casting blank and breakout accidents. To evaluate the influence of different SEN offsets on the mold flow field, this study uses a slab continuous casting mold with a cross-section of 920 mm × 200 mm from a specific factory as the research object. Mathematical simulations were used to investigate the influence of SEN offsets (including width-direction and thickness-direction offsets) on the flow behavior of molten steel in the mold. A physical water model at a 1:1 scale was established for verification. Two parameters, the symmetry index (S) and the bias flow index (N), were introduced to quantitatively evaluate the symmetry of the flow field, and the rationality of the liquid-level fluctuation under this flow field was verified using the F-number (proposed by Japanese experts for mold level fluctuation control) from the index model. The results show the following: when the SEN offset in the thickness direction increases from 0 to 50 mm, the longitudinal symmetry index (Sy) of the molten steel flow field in the mold decreases from 0.969 to 0.704—a reduction of 27.4%; the longitudinal bias flow index (Ny) of molten steel level fluctuation increases from 0.007 to 0.186, representing a 25.6-fold increase, and the F-number rises from 4.297 to 8.482; when the SEN offset in the width direction increases from 0 to 20 mm, the transverse-axis symmetry index (Sx) of the flow field decreases gradually from 0.969 to 0.753 at a 20 mm offset, which is a reduction of approximately 22.29%; the transverse-axis bias flow index (Nx) increases from 0.015 to 0.174 at a 20 mm offset—an increase of 10.6 times; and the F-number increases from 4.297 to 5.548. Considering the comprehensive evaluation of horizontal/vertical symmetry indices, bias flow indices, and F-numbers under the two working conditions, the width-direction SEN offset has the most significant impact on the symmetry of the molten steel flow field. Full article

Multi-angle remote sensing observations play an important role in the remote sensing of solar radiation absorbed by land surfaces. Currently, the Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) teams have successively applied the Ross–Li kernel-driven bidirectional reflectance distribution function (BRDF) model to integrate multi-angle observations to produce long time series BRDF model parameter products (MCD43 and VNP43), which can be used for the inversion of various surface parameters and the angle correction of remote sensing data. Even though the MODIS and VIIRS BRDF products originate from sensors and algorithms with similar designs, the consistency between BRDF parameters for different sensors is still unknown, and this likely affects the consistency and accuracy of various downstream parameter inversions. In this study, we applied BRDF model parameter time-series data from the overlapping period of the MODIS and VIIRS services to systematically analyze the temporal and spatial differences between the BRDF parameters and derived indices of the two sensors from the site scale to the region scale in the red band and NIR band, respectively. Then, we analyzed the sensitivity of the BRDF parameters to variations in Normalized Difference Hotspot–Darkspot (NDHD) and examined the spatiotemporal distribution of zero-valued pixels in the BRDF parameter products generated by the constraint method in the Ross–Li model from both sensors, assessing their potential impact on NDHD derivation. The results confirm that among the three BRDF parameters, the isotropic scattering parameters of MODIS and VIIRS are more consistent, whereas the volumetric and geometric-optical scattering parameters are more sensitive and variable; this performance is more pronounced in the red band. The indices derived from the MODIS and VIIRS BRDF parameters were compared, revealing increasing discrepancies between the albedo and typical directional reflectance and the NDHD. The isotropic scattering parameter and the volumetric scattering parameter show responses that are very sensitive to increases in the equal interval of the NDHD, indicating that the differences between the MODIS and VIIRS products may strongly influence the consistency of NDHD estimation. In addition, both MODIS and VIIRS have a large proportion of zero-valued pixels (volumetric and geometric-optical parameter layers), whereas the spatiotemporal distribution of zero-valued pixels in VIIRS is more widespread. While the zero-valued pixels have a minor influence on reflectance and albedo estimation, such pixels should be considered with attention to the estimation accuracy of the vegetation angular index, which relies heavily on anisotropic characteristics, e.g., the NDHD. This study reveals the need in optimizing the Clumping Index (CI)-NDHD algorithm to produce VIIRS CI product and highlights the importance of considering BRDF product quality flags for users in their specific applications. The method used in this study also helps improve the theoretical framework for cross-sensor product consistency assessment and clarify the uncertainty in high-precision ecological monitoring and various remote sensing applications. Full article

The present study aims to prepare a composite via pyrolysis, based on sodium alginate (SA) and a natural clay collected from the eastern region of Morocco, specifically the OUJDA area (C.O.R), for use in the disposal process of emerging pharmaceuticals. The strategy of rapid microwave heating followed by nitrogen calcination at 500 °C was successfully applied to produce the pyrolyzed carbonaceous materials. The removal of paracetamol (PCT) by adsorption on the carbonaceous clay (ca-C.O.R) composite was investigated to determine the effect of operating parameters (initial contaminant concentration, contact time, pH, and temperature) on the efficiency of PCT removal. The nanocomposite was analyzed using various techniques, including the nitrogen gas adsorption–desorption isothermal curve, X-ray diffraction, scanning electron microscopy, and Fourier transform infrared spectroscopy. Three models were used to describe the kinetic adsorption, and it was found that the experimental kinetic data fit well with a pseudo-second-order kinetic model with a coefficient of determination R² close to one, a nonlinear chi-square value close to zero, and a reduced root mean square error RMSE (R² → 1, X² → 0 and lower RMSE). The adsorption was best described by the Sips isotherm. The ca-C.O.R composite achieved a PCT removal efficiency of 91% and a maximum adsorption capacity of 122 mg·g⁻¹ improving on the performance of previous work. Furthermore, the variation in enthalpy (∆H°), Gibbs free energy (∆G°), and entropy (∆S°) indicated that the adsorption is exothermic in nature. The composite has shown promising efficiency for the adsorption of PCT as a model of emergent pollutant from aqueous solutions, making it a viable option for industrial wastewater treatment. Using Density Functional Theory (DFT) along with the 6-31G (d) basis set, the geometric structure of the molecule was determined, and the properties were estimated by analyzing its boundary molecular orbitals. The adsorption energy of PCT on MMT and ca-C.O.R studied using the Monte Carlo (MC) simulation method was −120.3 and −292.5 (kcal·mol⁻¹), respectively, which shows the potential of the two adsorbents for the emerging product. Full article

Co-Cr-based alloys are outstanding materials widely used in applications ranging from engineering to biomedical devices due to their excellent physico-mechanical properties, chemical stability, and biocompatibility. The demand for these alloys is steadily increasing, prompting a shift from conventional fabrication methods, such as casting and subtractive manufacturing, to advanced additive manufacturing (AM) techniques. These modern methods enable the production of complex geometrical shapes with enhanced properties. However, comprehensive information on current trends in 3D printing of Co-Cr-based alloys and their performance in specific applications remains limited. Therefore, the present article addresses this gap by reviewing recent advancements in the AM of Co-Cr-based alloys, offering insights for manufacturers, engineers, and researchers looking to develop optimized products. Key characteristics, including physical, mechanical, tribological, chemical, and biocompatibility properties, are thoroughly discussed, along with their applications, with a focus on potential future developments in this field. The exhaustive outlook of this paper provides a strong basis for future research endeavors in the domain of Co-Cr-alloy part production using AM. Full article

The application of CAD/CAM technologies in modern production has revolutionized manufacturing processes, leading to significant improvements in precision, efficiency, and flexibility. These technologies enable the design and manufacturing of complex geometries with high accuracy, reducing errors and material waste. CAD/CAM integration streamlines workflows, enhances productivity, and facilitates rapid prototyping, accelerating the time-to-market for new products. Additionally, it supports customization and scalability in production, allowing for cost-effective small-batch and large-scale manufacturing. Without a 3D model of the product, it is not possible to use the advantages of applying advanced CAD/CAM technologies. Recognizing 3D models from engineering drawings is essential for modern production, especially for outsourcing companies in fluctuating market conditions, where the production process is organized with 2D workshop drawings on paper. This paper proposes a novel methodology for reconstructing 3D models from 2D engineering drawings, specifically those in DXF file format, leveraging a genetic algorithm. A core component of this approach is the representation of the 2D drawing as a symmetric adjacency matrix. This matrix serves as the foundational data structure for the genetic algorithm, enabling the evolutionary process to effectively optimize the 3D reconstruction. The experimental evaluation, conducted on multiple engineering drawing test cases (including both polyhedral and cylindrical geometries), demonstrated consistent convergence of the proposed GA-based method toward topologically valid and geometrically accurate 3D wireframe models. The approach achieved successful reconstruction in all cases, with fitness scores ranging from 1.1 to 112.2 depending on model complexity, and average execution times from 2 to 100 s. These results confirm the method’s robustness, scalability, and applicability in real-world CAD environments, while establishing a new direction for topology-driven 3D reconstruction using evolutionary computation. Full article