Search Results (352)

Advancing hydropower development is crucial for supporting China’s “Dual Carbon” strategy and ensuring energy security. A key safety challenge in this endeavor is the stability of arch dam abutments under the combined action of high in situ stress and reservoir water loads. This study addresses this issue by proposing an integrated methodology that links detailed geological characterization, in situ stress quantification, and mechanical stability analysis. Using the Guxue high-arch dam as a case study, we first established a three-dimensional geological model to identify controlling discontinuities and delineate potential sliding blocks. A finite difference model was then developed to simulate the in situ geo-stress field and operational water pressures. Through stress tensor transformation, the stress state on potential slip surfaces was accurately determined, and safety factors were calculated based on the Mohr–Coulomb strength criterion. The results show that the critical left and right abutment rock blocks exhibit safety factors of 1.30 and 1.24, respectively, meeting design specifications while indicating a relatively lower safety margin on the right bank. The proposed approach, grounded in precise stress analysis, provides a reliable framework for assessing abutment stability under complex loading conditions, offering practical support for the safety evaluation and targeted reinforcement of high-arch dam projects in similar geological settings. Full article

Eutectic alloys stand out for their ability to combine high strength and good ductility; a behaviour rooted in their characteristic two-phase microstructure—lamellar or globular—formed at a constant solidification temperature that minimizes segregation and suppresses brittle phases. Their low interfacial energy limits microcrack propagation, while interfacial sliding and dislocation blocking at phase boundaries enhance both strength and toughness. In this work, we investigate how controlled microstructural modifications influence the behaviour of the eutectic high-entropy alloy AlCoCrFeNi2.1, composed of B2 (Ni–Al-rich) and L12 (Co–Fe–Ni-rich) phases. Because these phases exhibit distinct mechanical responses, microconstituent morphology becomes a design parameter. Powder metallurgy is the only processing route capable of providing the level of microstructural control required in this study. It preserves the rapidly solidified eutectic architecture of gas-atomised powders while allowing its intentional transformation during consolidation. Two strategies were implemented: (i) tuning the thermal–electrical input in Spark Plasma Sintering (SPS) and Electrical Resistance Sintering (ERS), and (ii) engineering the particle size distribution, including a bimodal design that enhances surface-energy-driven morphological transitions. SPS enables a gradual lamellar-to-globular evolution, whereas ERS induces ultrafast transformations governed by current intensity. The bimodal PSD significantly accelerates globularisation at lower energy input. EBSD-KAM (Electron Backscatter Diffraction—Kernel Average Misorientation) mapping identifies the lamellar B2 phase as metastable and highly strained, while globular B2 domains show reduced dislocation density. Nanoindentation confirms that intrinsic phase properties remain unchanged, whereas microhardness scales with morphology and lamellar spacing. These results demonstrate that the macroscopic mechanical response is governed by microstructure, establishing powder metallurgy as a uniquely powerful pathway for microstructure-driven design in eutectic HEAs. Full article

The Taranto Landslide Complex (TLC) is a multi-episode submarine mass-failure system developed along the Apulian continental margin (Gulf of Taranto, northern Ionian Sea) between ~200 and ~900 m water depth. High-resolution multibeam bathymetry and chirp seismostratigraphy were integrated to map five partially overlapping Quaternary mass transport deposits (MTD1–MTD5) and quantify their geometry, conservative volumes, and first-order kinematics. Consistent morphometric parameters indicate mobilities (H/L) and angles of reach typical of continental-slope failures, whereas conservative volumes range between ~0.02–0.35 km³. A depth-averaged sliding-block approach yields bounds on peak velocity and travel time compatible with rapid emplacement. Cross-cutting relationships and post-failure sediment drapes constrain two principal phases of slope instability, expressed as time windows rather than fixed ages. This study develops a framework that integrates uniform morphometric, volumetric, and kinematic features with seismostratigraphy to reconstruct the evolution and relative mobility of multi-episode submarine landslide complexes. The proposed workflow provides a transferable framework for preliminary geohazard assessment on continental margins where repeated slope failure interacts with tectonic and sedimentary forcing. Full article

This study evaluates the stability of slopes supported by mechanically stabilized earth walls under combined hydrostatic and seismic loading conditions. Limit equilibrium, pseudo-static methods and permanent displacement approaches, including the Newmark rigid block method as well as coupled and decoupled techniques, are employed to assess the static and seismic performance of the soil slope under investigation. Parametric analyses are conducted using the Slide2 software package (Version 9.041) and verified against geotechnical design criteria to examine the effects of groundwater level and seismic intensity on factors of safety, failure mechanisms, and seismic-induced displacements of the slope. Results based on multiple strong ground motion records indicate that elevated water tables and hydrostatic pressures behind the wall, up to levels near the wall toe, do not significantly increase the failure potential or slope displacement. This behavior is attributed to the MSE wall acting as a rigid stabilizing system that enhances overall slope stability. Full article

Phase-change materials of the Ge–Sb–Te (GST) system are promising for non-volatile memory and programmable photonics owing to their reversible amorphous–crystalline transitions. Among these materials, GeSb₄Te₇ stands out for its optimal balance of thermal stability, switching speed, and energy efficiency. The properties of GST materials are critically dependent on structural defects, particularly germanium vacancies that occur during synthesis and operation. Using density functional theory, we demonstrate that Ge vacancies and Ge–Sb intermixing significantly influence the electronic and optical properties of GeSb₄Te₇. Positive binding energies reveal vacancy clustering tendencies, which systematically reduce p-type degeneracy and widen the band gap (from 0.47 to 0.67 eV at a 2.7% vacancy concentration). Consequently, the metallic optical response in the visible range diminishes, as reflected in the less negative real dielectric function. Furthermore, we extend our investigation to the fundamental building block of this material system, the GeSb₂Te₄ monolayer. By studying controlled interlayer displacements of Ge and Te atoms in an otherwise stoichiometric slab, we elucidate the switching mechanism in the two-dimensional limit. The pristine monolayer exhibits semiconducting behavior with an indirect band gap of 0.74 eV, while layer sliding induces a semiconductor-to-metal transition accompanied by pronounced changes in the optical absorption spectrum. The asymmetric energy barrier (1.69 eV forward, 0.60 eV reverse) suggests favorable reversible switching via structural distortions alone, without requiring chemical modifications. The obtained results, spanning from defective bulk crystals to structurally distorted monolayers, are important for the targeted optimization of GST material properties in memory devices, optical elements, and emerging nanoscale phase-change applications. Full article

Synthetic aperture radar (SAR) imaging is highly vulnerable to radio-frequency interference (RFI) in complex electromagnetic environments, which can introduce structured artifacts and obscure targets in single-look complex (SLC) products. Most existing suppression methods rely on separability along a single dimension or require interference-specific parameter tuning, limiting robustness under multidimensional coupling and strong scatterers. We propose a range-domain sliding-window local tensorization that rearranges SLC data into localized range–azimuth–block-index tensors to better expose multi-mode correlations. On this representation, an energy-guided tensor CUR low-rank projector is embedded into an alternating-projection scheme that alternates complex-valued soft-thresholding for the sparse scene-plus-noise term and CUR-based projection for the structured RFI term. The cleaned SLC image is obtained by de-tensorizing the estimated RFI component and subtracting it from the input SLC. Experiments on semi-synthetic data, where controlled RFI is superimposed on real SLC scenes, and on real Sentinel-1 SLC data containing RFI demonstrate improved Pearson correlation coefficient (PCC) and perceptual image quality while preserving target signatures and scene textures, particularly under strong interference and strong coupling. The proposed approach provides a practical SLC-domain RFI mitigation tool for post-focusing SAR products without requiring explicit interference parameterization. Full article

Graphene, a 2D carbon allotrope with a hexagonal atomic structure, exhibits an exceptionally low friction coefficient of approximately 0.004, making it a superior alternative to traditional lubricants. This research investigates the performance of graphene as an additive in oil-based lubricants. Experimental trials will be conducted using a block-on-ring (B-o-R) setup involving a steel rod pressed against a rotating steel ring under a fixed load. By varying the sliding velocities, the study will map the Stribeck curve across the boundary (BL), mixed (ML), and hydrodynamic (HL) lubrication regimes. Furthermore, the lubricant’s durability under extreme pressure will be assessed via Timken testing. The study identified 0.08 wt.% as the optimal concentration for PAO8, achieving a 21.25% friction reduction in the boundary regime. Furthermore, graphene as an additive mitigated wear volume by up to 90% under extreme pressure conditions (1.3 GPa), whereas epoxidized soybean oil proved to be highly effective as a base lubricant without additional nano-additives. Full article

Additive manufacturing is increasingly adopted for the industrial production of small series of functional components, particularly in thermoplastic strand extrusion processes such as Fused Filament Fabrication. This transition relies on technological advances addressing key process limitations, including dimensional instability, weak interlayer bonding, extrusion defects, moisture sensitivity, and insufficient melting. Process monitoring therefore focuses on early defect detection to minimize failed builds and costs, while ultimately enabling process optimization and adaptive control to mitigate defects during fabrication. For this purpose, a data processing pipeline for monitoring Optical Coherence Tomography images acquired in Fused Filament Fabrication is introduced. Convolutional neural networks are used for the automatic classification of tomographic cross-sections. A dataset of tomographic images passes semi-automatic labeling, preprocessing, model training and evaluation. A sliding window detects outlier regions in the tomographic cross-sections, while masks suppress peripheral noise, enabling label generation based on outlier ratios. Data are split into training, validation, and test sets using block-based partitioning to limit leakage. The classification model employs a ResNet-V2 architecture with BottleneckV2 modules. Hyperparameters are optimized, with N = 2, K = 2, dropout 0.5, and learning rate 0.001 yielding best performance. The model achieves 0.9446 accuracy and outperforms EfficientNet-B0 and VGG16 in accuracy and efficiency. Full article

Rockfall hazard assessment and mitigation design relies heavily on three-dimensional trajectory modeling, in which the coefficient of restitution (COR) is a governing parameter controlling rebound, energy dissipation, and runout distance. In practice, COR values are commonly selected from generalized tables based on slope material type, introducing significant epistemic uncertainty and limiting predictive accuracy. This study presents a comparative evaluation of large-scale field rockfall experiments and 3-D numerical simulations conducted at a former aggregate quarry in Boise, Idaho, to assess the performance of tabulated restitution coefficients. Concrete blocks of controlled shape (spheres, cubes, and rectangular prisms) and mass (17–68 kg) were instrumented with inertial sensors and released from two slope configurations. High-resolution UAV-based LiDAR was used to reconstruct slope geometry, while dynamic cone penetrometer and friction tests were performed to characterize spatial variability in slope material stiffness. These data were incorporated into RocFall3 to simulate block trajectories using spatially varying COR values. Initial models assuming zero rotational velocity and tabulated COR ranges failed to reproduce observed runout distances, dispersion patterns, and modes of motion, particularly for non-spherical blocks. Incorporating field-measured initial rotational velocities significantly improved agreement between modeled and observed trajectories, by correcting the unrealistic sliding mode of motion previously observed. However, quantitative discrepancies in deposition and dispersion persisted, highlighting limitations associated with simplified slope geometry and the loss of small-scale surface features during LiDAR surface reconstruction. The results demonstrate that restitution behavior is strongly shape-dependent and that realistic initial conditions are essential for physically meaningful simulations. The findings underscore the need for site-specific, material-informed approaches to COR estimation and for improved integration of high-fidelity field data into physics-based rockfall models. Full article

Introduction: Pancreatic ductal adenocarcinoma (PDAC) represents one of the most aggressive, heterogeneous, and lethal malignancies in humans. Mismatch repair (MMR) proteins constitute a fundamental component of the DNA mismatch repair pathway, which is responsible for correcting replication-associated errors, including incorrect base pairings and small insertions or deletions. This study aims to evaluate the immunohistochemical expression of MSH2, MSH6, MLH1, and PMS2 in resected PDAC and to analyze their association with pTNM stage, perineural and lymphovascular invasion, HER2 and HER3 expression, and tumor volume. Methods: A cohort of 106 patients with currative intent Whipple procedure was evaluated, their corresponding paraffin blocks and slides were analyzed using tissue microarray. Immunohistochemical analysis of MLH1, PMS2, MSH2, and MSH6 was performed. Patients were grouped based on MMR expression profiles: isolated MutS loss (MSH2/MSH6), and isolated MutL loss (MLH1/PMS2). Results: Among the 106 subjects evaluated, 13 (12.3%) exhibited isolated MutS complex loss and 16 (15.1%) showed MutL complex loss. A total of 7 patients (6.6%) demonstrated concurrent loss of all four MMR proteins, representing a pattern suggestive of MMR deficiency MSI-H. These ones were significantly younger (median 56 vs. 64 years, p = 0.0492) and had distinct T-stage distribution (p = 0.0237). Two intermediate subgroups were identified: five patients with isolated MutL loss and one patient with isolated MutS loss. HER3 positivity was observed in 3/5 of the intermediate MutL cases and HER2 positivity in only one. Conclusions: MMR deficiency and potential MSI-H status were identified to be relevant prognostic biomarkers for pancreatic cancer patients, with MSI-H patients displaying a younger age and distinct tumor features. Full article

Injection mold design is a repetitive and time-consuming process with common individual tasks related to each other. This study presents the development of an automatic computer-aided design (CAD) tool for basic injection molds with complete modeling and no other interaction by the user after inserting the part, built on the SolidWorks Application Programming Interface 2022 (API) and Visual Basic for Applications 7.1 2012(VBA). The tool combines user input forms and supplier catalog data as inputs in an algorithm to automatically generate mold structures, cavity blocks, runner system, ejection system and straight drilled cooling channels without further manual modeling. Three case studies with one-, two-, and four-cavity molds demonstrate the approach. The results show that complete mold assemblies can be produced in less than 10 min rather than hours while maintaining standard component dimensions. Although the present version applies to rule-based geometric placement rather than thermal or injection process optimization, it provides a framework for future integration of more complex mold structures and functions such as slides, hot runner system, unscrewing geometries, conformal cooling, heat-transfer-based design, family molds and machine selection. This work demonstrates how API-driven automation can reduce design time, standardize layouts, and lay the groundwork for next-generation injection mold development. Full article

Wear, a critical factor governing the performance and durability of mechanical systems, is typically characterized using point-contact and line-contact test configurations. However, it remains unclear whether the wear trends observed in one test configuration would be observed in the other configuration under the same nominal conditions. In this study, ball-on-disk (ASTM G99) and block-on-ring (ASTM G77) tests were conducted under an identical maximum Hertzian contact stress and sliding speed, using the same material pair and lubricating oil, to clarify which contact configuration exhibits more wear and why. The results show that, under the same Hertzian contact stress, the line-contact configuration exhibits a specific wear rate two orders of magnitude higher than the point-contact configuration, despite exhibiting a lower and more stable coefficient of friction. The disk wear is negligible and the ball shows only mild material loss, whereas the line-contact system displays wear rates several orders of magnitude higher, with the rotating ring contributing the dominant share of the total wear. White-light interferometry and scanning electron microscopy observations reveal directional, groove-dominated surface morphologies on the ball and disk, while wear on the block is confined to edge-localized regions and the worn ring surface has smooth, polished morphology. Energy-dispersive X-ray spectroscopy confirms that a Zn- and P-rich tribofilm forms exclusively on the ring surface. Finite element analysis shows stress amplification at the finite line-contact edges, explaining the observed wear severity. These results demonstrate that matching Hertzian contact stress alone is insufficient to ensure comparable wear behavior between point and line contacts. Full article

Frequent extreme rainfall events in northwestern China have made loess–mudstone composite slopes highly susceptible to progressive failure, posing serious threats to infrastructure and public safety. This study investigates the deformation–failure mechanisms and evolutionary characteristics of such slopes under rainfall infiltration by integrating indoor physical model tests with long-term SBAS-InSAR time-series deformation monitoring. The physical model experiments reveal pronounced hydro-mechanical heterogeneity within the composite slope: surface fissures act as preferential flow paths, the mudstone interface exerts a significant water-blocking effect, and hydrological responses differ markedly between shallow and deep layers. The wetting front exhibits a distinct dual-layer migration pattern, characterized by rapid lateral expansion in the shallow layer and delayed advancement in the deep layer. Rainfall infiltration induces a progressive failure process, evolving from toe infiltration softening and mid-slope local erosion to differential crest erosion and ultimately overall sliding, forming a typical failure pattern of frontal creeping, central shearing, and rear tensile deformation. SBAS-InSAR results indicate that the natural landslide experienced a similar long-term progressive evolution, developing from shallow, localized deformation to deep-seated and slope-wide acceleration under multi-year rainfall. Despite differences in spatial deformation patterns influenced by natural microtopography, the failure stages and dominant deformation zones identified by both approaches show strong consistency. The combined results demonstrate that rainfall-induced suction decay, interface softening, pore water pressure accumulation, and stress redistribution jointly control the progressive instability of loess–mudstone slopes. This study highlights the effectiveness of integrating physical modeling and InSAR monitoring for elucidating rainfall-induced landslide mechanisms and provides scientific insights for hazard assessment and mitigation in composite-structure slopes. Full article

Deception detection with low-channel wearable EEG requires protocols that generalize across people while remaining practical for portable devices. Using the public LieWaves dataset (27 subjects recorded with a five-channel Emotiv Insight headset), we evaluate to what extent five-channel head-mounted EEG can support lie–truth discrimination under both subject-independent and subject-dependent evaluations. For the subject-independent setting, we train a compact Residual Network with Squeeze-and-Excitation blocks (ResNet-SE) model on raw overlapping windows with focal loss, light data augmentation, and grouped cross-validation by subject; out-of-fold window probabilities are averaged per session and converted to labels using a single decision threshold estimated from the cross-validated session scores. For the subject-dependent setting, we adopt an overlapping short-window Residual Temporal Convolutional Network with Squeeze-and-Excitation and Attention (Res-TCN-SE-Attention) model that fuses raw EEG with discrete wavelet transform (DWT)-based spectral and handcrafted band-power and Hjorth features, using an 80/10/10 split at the recording/session level (stratified by session label), so that all windows from a given session are assigned to a single subset; because each subject contributes two sessions, the same subject may still appear across subsets via different sessions. The subject-independent model attains 66.70% session-level accuracy with an AUC of 0.58 on unseen subjects, underscoring the difficulty of person-independent generalization from low-channel wearable EEG. Because practical deployment requires generalization to previously unseen individuals, we treat the subject-independent evaluation as the primary estimate of real-world generalization. In contrast, the subject-dependent pipeline reaches 99.94% window-level accuracy under the overlapping sliding-window (OSW) setting with a session-disjoint split (no session contributes windows to more than one subset). This near-ceiling performance reflects the optimistic nature of subject-dependent evaluation with highly overlapping windows, even when avoiding within-session train–test overlap, and should not be interpreted as a meaningful indicator of deception-detection capability under realistic deployment constraints. These results suggest limited, above-chance separability between lie and truth sessions in LieWaves using a five-channel wearable EEG under the studied protocol; however, performance remains far from deployment-ready and is strongly shaped by evaluation design. Explicit reporting of both protocols, together with clear rules for windowing, aggregation, and threshold selection, supports more reproducible and comparable benchmarking. Full article

Granite residual soil (GRS) is highly susceptible to water-induced softening, posing significant risks of slope instability and collapse. Conventional impermeable grouting often exacerbates these hazards by blocking groundwater drainage. This study investigates the efficacy of a permeable water-reactive polyurethane (PWPU) in stabilizing GRS, aiming to resolve the conflict between mechanical reinforcement and hydraulic conductivity. Uniaxial compression tests were conducted on specimens with varying initial water contents (5%, 10%, and 15%) and PWPU contents (5%, 10%, and 15%). To reveal the multi-scale failure mechanism, synchronous acoustic emission (AE) monitoring and digital image correlation (DIC) were employed, complemented by scanning electron microscopy (SEM) for microstructural characterization. Results indicate that PWPU treatment significantly enhances soil ductility, shifting the failure mode from brittle fracturing to strain-hardening, particularly at higher moisture levels where failure strains exceeded 30%. This enhancement is attributed to the formation of a flexible polymer network that acts as a micro-reinforcement system to restrict particle sliding and dissipate strain energy. An optimal PWPU content of 10% yielded a maximum compressive strength of 4.5 MPa, while failure strain increased linearly with polymer dosage. SEM analysis confirmed the formation of a porous, reticulated polymer network that effectively bonds soil particles while preserving permeability. The synchronous monitoring quantitatively bridged the gap between internal micro-crack evolution and macroscopic strain localization, with AE analysis revealing that tensile cracking accounted for 79.17% to 96.35% of the total failure events. Full article