Search Results (37,099)

Recent taxonomic revisions within the family Molidae have clarified the validity and diagnostic characters of the bump-head sunfish Mola alexandrini (Ranzani, 1839), a species historically confused with Mola mola. Despite its circumglobal distribution, confirmed records of M. alexandrini in the Mediterranean Sea remain limited, particularly in the Adriatic Sea. Here, we report the occurrence of an adult female M. alexandrini stranded along the north-western Adriatic coast (Ravenna, Italy) in March 2026. Species identification was assessed through an integrative approach combining external morphology, morphometric measurements, and mitochondrial COI sequencing. The specimen exhibited diagnostic morphological traits consistent with M. alexandrini, including a rounded clavus lacking lobes and back-fold, a deep laterally compressed body, and characteristic coloration patterns. Phylogenetic analysis based on COI sequences clustered the specimen within the M. alexandrini clade, clearly separating it from M. mola. This finding provides further evidence of the occurrence of M. alexandrini in the Adriatic Sea and highlights the importance of combining molecular and morphological approaches to resolve taxonomic uncertainty within the genus Mola. The study also highlights that historical misidentification may have contributed to an underestimation of the occurrence of M. alexandrini in the Mediterranean basin. Full article

Alkali-activated concrete (AAC) offers the advantages of high mechanical strength and excellent corrosion resistance, making it a promising low-carbon material. However, its widespread application in practical engineering is severely limited by the serious issues of high shrinkage and susceptibility to cracking. To address the challenges, this work proposes incorporating superabsorbent polymers (SAPs) into AAC to mitigate its shrinkage problems. A comprehensive investigation is conducted on fresh, mechanical and shrinkage properties of SAP-modified AAC. The underlying shrinkage-mitigating mechanism is revealed through various tests including hydration heat, X-ray diffraction, scanning electron microscope (SEM), and nuclear magnetic resonance (NMR) analysis. Results indicate that SAP prolongs concrete setting times. With SAP addition, the overall porosity and weak interfacial transition zones are increased, leading to decreases in the compressive strength by approximately 6.9–20.2% at 28 d. Both splitting tensile and flexural strengths show varying degrees of improvement. Adding 0.1–0.3% SAP reduces the 3 d autogenous shrinkage by about 33.08–41.14%, and 56 d drying shrinkage by 12.4–32.7%. SAPs act as internal water reservoirs, regulating humidity and reducing AAC’s sensitivity to internal relative humidity. Furthermore, SAPs optimize AAC pore structure distributions, as revealed by SEM and NMR analyses. Given the impact of SAP dosage (0–0.3%), autogenous and drying shrinkage prediction models are respectively established based on CEB-FIP 90 and GL 2000 models, showing superior agreement between predicted results and test data, with all the fitting coefficients over 0.9. Full article

This paper presents a code-based static verification of the FA125 hydraulic drilling rig mast under its governing design load combination. Unlike the previously published dynamic investigation of the same platform, the present work establishes the baseline static load path, identifies the governing structural members, evaluates the local stress state in the mast-to-support connection plates, and computes the effective safety coefficients. The mixed finite element model integrates the lattice mast, the support frame, and the base assembly, utilizing beam elements for the slender load-bearing members and shell elements for the localized plate-type connection regions. The governing load combination encompasses structural self-weight, maximum hook load (14.90 kN), and the reactive torque transmitted by the drilling head (0.50 kNm). The maximum mast-top displacement was limited to 4.75 mm. The critical beam elements were located within the lateral base-support region, developing peak compressive and tensile stresses of 70.08 MPa and 69.21 MPa, respectively. The highest localized shell-level von Mises stress (23.62 MPa) was concentrated within the mast-to-support interface connection plates. The results mathematically confirm that the existing FA125 steel structure satisfies the active design criteria, providing a distinct static reference map required for subsequent structural optimization, lightweighting, and selective material substitution. Full article

Lightweight materials with improved strength characteristics are increasingly required in aerospace, automotive, impact protection, and vibration damping applications to enhance structural efficiency and service life. Although aluminum metal foams have been found to be promising lightweight cellular materials, their load-bearing performance is rather limited, thus limiting their use for high-performance structural applications. The composite metal foams in the present study were produced by CaCO₃ as foaming agent and AA7075 as the base material by gas-releasing particle decomposition method, in which the foaming agent is transformed into CO₂ gas to generate pores during foaming. Cell size distribution analysis, density, and energy-dispersive spectroscopy were used to investigate the composite foams containing 0, 1, 2 and 3 wt.% Si₃N₄, while quasi-static uniaxial compression testing was employed to measure the compressive strength of these foams. Si₃N₄ of 2 wt.% and 3 wt.% resulted in better pore refinement and uniformity of cells, as revealed in the microstructural analysis. The density was raised from 0.21 to 0.61 g/cm³ by reinforcement addition. The compression strength increased from 7.85 to 23.64 MPa, while energy absorption increased from 5.10 to 20.52 MJ/m³ for foams containing 0 and 3 wt.% Si₃N₄, respectively. The yield strength also improved from 4.92 to 15.98 MPa, and the plateau stress from 7.37 to 22.57 MPa. Improved mechanical behavior is due to the following: refinement of pores, thickness of the ligaments, more compact structure, and load transfer in the cellular structure. Full article

Very-high-resolution (VHR) multispectral satellite imagery contains rich semantic information, yet its real-time transmission is constrained by limited satellite-to-ground bandwidth and dynamic channel impairments. Conventional communication schemes prioritize pixel-level reconstruction, resulting in large transmission overhead and poor robustness under unfavorable channel conditions. To address these challenges, an end-to-end task-oriented semantic communication framework for remote sensing downstream recognition tasks, termed Semantic Transmission Architecture for Remote Sensing (STARS), is proposed. To improve transmission efficiency for very-high-resolution remote sensing images with highly redundant background regions, a Semantic Feature Reweighting Module (SFRM) is introduced to dynamically evaluate token-level semantic importance and adaptively allocate transmission resources to task-critical features. Furthermore, vector quantization and a practical digital transmission chain are jointly integrated to achieve efficient semantic compression, while dynamic channel variations are incorporated during training to improve robustness under fading channel conditions. Experimental results on the DOTA dataset demonstrate that STARS consistently outperforms conventional schemes and existing semantic baselines under Rician fading channels, validating the effectiveness of semantic-aware feature allocation for bandwidth-efficient VHR imagery transmission. Full article

Lunar regolith simulant (LRS) geopolymers are promising construction materials for lunar in situ resource utilization, but their brittle behavior and limited crack resistance restrict their structural applications. This study investigated the effect of basalt fiber length on the mechanical properties, failure modes, stress–strain behavior, constitutive relationship, and microstructure of CQU-1 LRS geopolymers. Basalt fiber-reinforced LRS geopolymers were prepared under weak alkali activation and high-temperature curing at 80 °C. The basalt fiber content was fixed at 0.1%, and six fiber lengths of 0, 6, 9, 12, 15, and 18 mm were considered. Compressive and flexural tests were conducted after curing for 1 d and 7 d, and the normalized stress–strain curves were fitted using the Saenz L.P., Carreira D.J., and Zhenhai Guo models. The results showed that basalt fiber length significantly affected the mechanical performance of LRS geopolymers. An appropriate fiber length improved strength, stiffness, ductility, and post-peak load-bearing capacity, whereas excessively short or long fibers weakened the reinforcing effect. The 15 mm fiber group exhibited the best overall performance. After curing for 1 d, its compressive strength reached 2.23 MPa, 49.7% higher than that of the control group, and its elastic modulus increased approximately 2.5-fold. After curing for 7 d, its compressive strength reached 13.44 MPa, 32.0% higher than that of the control group. The Zhenhai Guo model provided the best fit for the stress–strain curves. SEM-EDS analysis showed that basalt fibers improved interfacial bonding and promoted gel enrichment near the fiber–matrix interface. Overall, 15 mm was recommended as the optimal basalt fiber length for CQU-1 LRS geopolymers under the conditions used in this study. Full article

Compression index (Cc) and recompression index (Cur) are essential parameters in one-dimensional consolidation and settlement analysis, yet their direct determination from oedometer testing is time-consuming, costly, and often limited by sparse recompression data. This study develops an interpretable and physically constrained machine-learning framework for the joint prediction of Cc and Cur from four routinely measured index properties: liquid limit (LL), plasticity index (PI), initial void ratio (e), and natural water content (w). A curated subset of 459 natural clay records from the global CLAY/Cc/6/6203 database was used to benchmark single-output and multi-output Random Forest, gradient-boosted tree, and deep neural network models. In addition to conventional random train–test and cross-validation protocols, a leave-one-location-out validation was introduced to evaluate transferability across 81 Country–Location groups. Under the random-split setting, Cc was predicted with moderate-to-good accuracy, with baseline models achieving test R² values of approximately 0.61–0.70 and a geotechnically enriched Random Forest model increasing the test R² to 0.777. Cur was more difficult to predict. Although feature enrichment improved its test R² to 0.507, location-aware validation reduced Cur performance substantially, confirming its stronger dependence on site-specific stress history, fabric, and geological structure. SHAP interpretation identified e and w as the dominant controls on Cc, while Cur exhibited weaker and more diffuse dependence on the available index properties. A physically constrained target transformation based on the bounded ratio of Cur/Cc guaranteed mechanically admissible predictions with Cur < Cc, but did not fully recover the missing information needed for accurate Cur estimation. The proposed constraint is not a governing-equation-based physics-informed model. Rather, it is a mechanically constrained target transformation that preserves the admissible relationship Cur < Cc. The results show that routine index properties can support the useful preliminary prediction of Cc, whereas Cur should be treated as a screening-level estimate unless explicit stress history descriptors are available. Full article

Finite element (FE) modeling is widely used in biomechanical research, enabling computational investigations of anatomical structures. To develop accurate FE models, high-resolution medical imaging such as computed tomography (CT) is essential. However, CT exposes patients to ionizing radiation. Recently, radiation-free three-dimensional zero-echo-time magnetic resonance imaging (3D ZTE MRI) has shown promising results for bone visualization. Therefore, this feasibility study investigated whether 3D ZTE MRI is reliable for creating subject-specific FE models. Human femora from four female subjects were imaged using 3D ZTE MRI. Static FE analyses of the femora were performed in Abaqus/CAE, assuming a biphasic homogenous linear-elastic material. A sensitivity analysis was conducted to evaluate varying bone material properties. After loading with 2000 N, the mean displacement of the femoral head amounted to −1.30 ± 0.26 mm (vertical) and −9.03 ± 2.21 mm (horizontal), while the femoral neck exhibited compressive (inferior: −1366.03 ± 182.70 µm/m) and tensile (superior: 1038.69 ± 135.82 µm/m) strains. Overall, the results demonstrate displacement and strain predictions similar to previous experimental and computational studies based on CT data. Therefore, despite several simplifications, these findings confirm the feasibility of radiation-free 3D ZTE MRI for subject-specific FE modeling, enabling future simultaneous assessment of bone morphology and surrounding soft tissues. Full article

Rigid polyurethane foam was evaluated as a filler material for a tubular railway vehicle energy absorber. Cubic samples cut from a cylindrical PU foam sample with a density of 175 kg/m³ were tested under quasi-static uniaxial compression to determine the material’s compressive response and provide input data for finite element modelling. The experimental results showed a non-linear stress–strain response typical of cellular foams, while samples from the central region of the cylinder exhibited a lower stress response than those from the outer region. An Ogden foam material model was calibrated in Ansys using compression data obtained by experimental tests and then applied to numerical models of three absorber configurations: an empty steel tube, a fully foam-filled steel tube, and a foam-filled tube with an additional concentric steel core. The simulations compared the force–stroke response and absorbed energy of each configuration under quasi-static axial loading through a conical bushing. Over a 60 mm stroke, compared to the empty tube, the fully foam-filled tube absorbed an additional 16% energy and the concentric-core configuration absorbed an additional 9.5%. These results indicate that rigid PU foam filling can improve the quasi-static energy absorption capacity of tubular railway collision absorbers. Full article

In this work, the use of biodiesel derived from Acacia sieberiana (commonly referred to as “Bagaruwa”) seed oil is presented as a potential renewable fuel for compression ignition engines. The biodiesel was produced using transesterification and characterized using Fourier transform infrared spectroscopy (FTIR) and gas chromatography–mass spectrometry (GC–MS). The FTIR analysis confirmed the presence of functional groups, including C=O stretching at 1740 cm⁻¹, and C–O ester bands at 1244 and 1170 cm⁻¹. The GC–MS analysis showed that linoleic acid methyl ester was the dominant compound (54.77%), followed by 11-octadecenoic acid methyl ester (22.91%) and palmitic acid methyl ester (11.71%). The physicochemical properties of biodiesel–diesel blends were evaluated according to the ASTM standards. Increasing the biodiesel content reduced the density, viscosity, cetane number, and calorific value, while the flash point was found to increase. B10 and B15 blends showed the highest density values within ASTM limits. The results indicated that Acacia sieberiana seed oil is a promising non-edible feedstock for sustainable biodiesel production and applications. Full article

Traditional methods for wine bottle packaging leakage detection often suffer from low efficiency, high false-positive rates, or an inability to detect micro-leakages. This paper proposes a near-infrared laser leakage detection system based on tunable diode laser absorption spectroscopy at 1392 nm, combined with a LightGBM machine learning model. The system detects gaseous ethanol vapor escaping from leaking bottles, addressing the spectral interference caused by ambient water vapor. A total of 1410 samples were collected, and each raw 2000-point spectral contour was compressed into a 200-dimensional feature vector through baseline correction, Z-score normalization, and uniform down-sampling. A two-stage hyperparameter optimization strategy yielded the optimal LightGBM configuration with a 5-fold cross-validation. For the binary classification task, the model achieved an AUC of 0.9949 and an inference speed of 0.0058 ms per sample on a CPU, outperforming Random Forest, PLS, and four deep learning models. For the regression task, the model achieved an R² of 0.5854 ± 0.0919. An anti-interference experiment on 422 samples under varying flow rates, temperatures, and commercial wine types confirmed the model’s robustness, achieving an overall accuracy of 0.94 and an alcohol recall of 0.99. To further validate the system under realistic conditions, a simulated micro-leakage test was conducted using a negative-pressure extraction method: 320 samples were collected from artificially damaged commercial wine bottles placed in a custom-built acrylic vacuum chamber that replicates the production line enclosure. The model achieved an accuracy of 0.95 with zero false negatives. The complete detection cycle takes no more than 5 s per bottle, enabling non-destructive, rapid, and online packaging integrity assessment. The results demonstrate that the proposed system provides a low-cost and reliable solution for wine bottle leakage detection suitable for industrial deployment. Full article

Concrete remains the most widely used construction material owing to its affordability, local availability, mechanical performance, durability, and versatility. However, its production has a significant environmental impact, and its service life may be reduced under aggressive exposure conditions, affecting both the functionality and cost of structures. This study presents a sustainability assessment based on a harmonized database of previously developed concrete mixtures, rather than a new experimental campaign. Waste-containing mixtures and their corresponding conventional or reference controls were considered to anchor the comparison to reference concretes, rather than only to the minimum values within the analyzed dataset. The objective was to compare the consistency among sustainability index formulations: K_SB and K_SB,C, associated with the Building Material Sustainability Potential (BMSP), and the Empathetic Added Sustainability Index (EASI). These formulations integrate functional and environmental performance, although they differ in their aggregation approach and in the treatment of economic variables, such as cost and eco-cost. The indicators considered include 28-day compressive strength, carbonation rate, global warming potential (GWP), gross energy requirement (GER), natural raw material consumption (NRMC), eco-cost, and material cost. The results show that mixtures with higher replacement levels of natural aggregates by recycled concrete aggregate and partial replacement of cement by locally sourced ashes exhibited the best integrated performance. The 300/100RCAg mixture stood out, with index values close to 3.43, 3.52, and 3.99, up to approximately four times those of the control. Sensitivity and uncertainty analyses showed that the highest-ranked mixtures generally maintained favorable positions across assessment methods and under ±20% input variability, although some alternatives exhibited substantial method-dependent ranking changes. The results demonstrate that local waste materials can improve concrete sustainability; however, their benefits depend on waste type, conditioning requirements, functional performance, and the selected sustainability assessment method. Full article

Nowadays, alternative cost-effective and environmentally friendly waste materials have gained popularity over conventional chemical additives for the stabilization of weak soil in seasonal freeze–thaw (FT) areas. Molasses, a byproduct of sugar production, is utilized in various sectors; however, there are no studies in the literature concerning the use of molasses in the stabilization of clayey soil under FT cycles. To address this aim, in this study, a series of unconfined compressive strength (UCS) tests were conducted on both unstabilized and stabilized samples with molasses ratios ranging from 4% to 14%, subjected to 0, 5, 10, and 15 FT cycles following 7 and 28 days of curing. The assessment focused on the stress–strain (σ-ε) responses, unconfined compressive strength (q_u), failure strain (ε_f), secant modulus (E₅₀), and failure mode. The results demonstrated that maximum performances appeared with 10% molasses ratios, showing a 1.39–2.62-fold increase in the q_u values. As the curing period increased, the q_u and E₅₀ values increased significantly, while the ε_f values exhibited a diminishing trend. It was also observed that the FT cycles caused a dramatic reduction in the shear strength of unstabilized samples, ranging from approximately 42% to 69%; however, molasses-stabilized samples demonstrated higher resistance. Furthermore, XRD, SEM, and EDX analyses were carried out to investigate the mineralogical, microstructural, and chemical behaviors. Finally, an empirical equation was proposed to predict the q_u of molasses-stabilized soil subjected to FT cycles. Full article

Near-field multistatic radar imaging requires evaluating a nonlinear matched-filter operator over a three-dimensional search region, imposing a prohibitive computational burden on systems utilizing sparse, large-aperture receiver layouts. In this paper, we study a static-target formulation with a known signal envelope and develop a receiver-domain-decomposition for computation burden mitigation. Starting from a maximum-likelihood model, we show that when the temporal waveform is known, the estimation problem reduces to a coherent spatial matched filter formed from time-compressed data. This representation enables a direct comparison between brute-force image formation and an approximation in which the receiver set is partitioned into subapertures, low-resolution subimages are computed on a coarse spatial grid, corrected by a reference phase, interpolated to the fine grid, and coherently aggregated. We derive the matched-filter formulation, provide interpolation-based error bounds under compensated-image smoothness assumptions, and analyze computational complexity. Numerical simulations demonstrate that phase correction substantially smooths low-resolution block images, thereby enabling interpolation. The results also clarify the conditions under which the proposed approximation is accurate and where it is expected to degrade, including insufficient phase compensation, overly aggressive coarse-grid factors, and extended-target interference. Full article

With the continuous advancement of urban renewal and the renovation and utilization of existing buildings, a large number of existing reinforced concrete slender columns face challenges in capacity evaluation. Quick and accurate calculation of their stability capacity, which represents the upper limit of member capacity, holds significant importance. These columns often exhibit plastic characteristics such as concrete cracking and steel yielding. Moreover, the bracing restraint provided by adjacent columns typically falls between that of a sway frame and a non-sway frame, classifying them as elastically restrained sway frame columns. Current design codes lack appropriate effective length factor tables for such columns, while the stiffness degradation induced by material nonlinearity is difficult to quantify accurately. To address these issues, the frame column is isolated from the overall structure and modeled as a rigid compression member system with three springs. The influence of bracing stiffness on the column’s critical load is revealed, leading to a formula for the elastic critical load of elastically restrained sway frame columns. Based on tests of reinforced concrete columns under compression, the influence mechanisms of eccentricity ratio and longitudinal reinforcement ratio on flexural stiffness degradation are elucidated. The obtained elastoplastic stiffness is then integrated into the stability calculation framework for elastically restrained sway frame columns, resulting in a method for determining the elastoplastic stability capacity of reinforced concrete columns that accounts for both geometric and material nonlinearities. This method avoids solving complex transcendental equations and offers a straightforward calculation process, providing a simple and practical hand-calculation tool for evaluating the stability capacity of reinforced concrete columns in existing buildings. Full article