Search Results (20,454)

Soil liquefaction typically occurs during and following earthquakes, although it may also be triggered by non-seismic dynamic loading. While liquefaction is systematically investigated using laboratory element tests, critical field-scale aspects, such as soil fabric and complex boundary conditions, remain challenging to replicate. Consequently, researchers have evaluated field liquefaction through controlled explosive detonations. The primary objective of this study is the numerical simulation of a controlled blast-induced liquefaction test conducted at a silty sand site. An advanced constitutive model was employed to capture the highly non-linear soil behaviour under blast loading. Modelling blast loading is inherently challenging due to extreme near-field deformations, high-frequency accelerations (exceeding 100 Hz), and rapid excess pore water pressure generation on the order of milliseconds. Particular attention is paid to replicating acceleration time histories and Fourier amplitude spectra. Furthermore, computed pore water pressures are validated against experimental transducer data, providing relevant insights into the spatial and temporal development of blast-induced liquefaction. Full article

Background/Objectives: Computational and artificial intelligence (AI)-enabled imaging biomarkers are increasingly being investigated for immunotherapy-response assessment in oral squamous cell carcinoma (OSCC), but the evidence is heterogeneous. This systematic review identified, critically appraised, and synthesized imaging biomarkers used to predict or assess observed immunotherapy response in OSCC. Methods: PubMed/MEDLINE, Embase, and Scopus were searched from inception to 31 July 2026, without language restrictions. The protocol was registered in PROSPERO. Eligible studies evaluated quantitative, radiomic, machine-learning, or related medical-imaging biomarkers against pathological or radiological response. Risk of bias was assessed using design-specific tools, supplemented by a radiomics-specific methodological appraisal. A structured Synthesis Without Meta-analysis was prespecified. Results: Seven reports were included, covering pretreatment prediction, early/on-treatment dynamic assessment, and post-neoadjuvant/preoperative response assessment. Pretreatment-computed tomography and magnetic resonance imaging radiomics showed discriminatory performance, whereas baseline positron emission tomography uptake alone was not consistently associated with pathological response. Longitudinal fibroblast activation protein inhibitor positron emission tomography changes were associated with a major pathological response, and magnetic resonance imaging habitat and longitudinal habitat models showed higher within-study discrimination when combined with clinical information. No computational model had independent external validation specifically in an OSCC population, and no three independent studies were sufficiently comparable for meta-analysis. Conclusions: Computational imaging is promising across several stages of immunotherapy-response assessment. However, based on current evidence, none of the reviewed imaging biomarkers or models can yet be considered ready for routine clinical use. Prospective multicenter OSCC-specific validation and standardized imaging and analytical pipelines are needed to establish generalizability and clinical utility. Full article

Two-box edge girders are widely employed in bridge engineering owing to their superior mechanical properties. However, these girders are susceptible to vortex-induced vibrations (VIVs) due to their blunt configuration. Therefore, it is of great significance to study their VIV performance and specific suppression measures. Wind tunnel tests simultaneously measuring vibration and pressure and computational fluid dynamics (CFD) were performed to investigate the effects of sidewalk railing height and inclination angle on the VIV responses at different wind attack angles. Furthermore, surface pressure distribution, the relationship between distributed aerodynamic lift and the general vortex-excited force (VEF), and flow field characteristics were analyzed to elucidate the VIV suppression mechanism. Results indicate that vertical VIVs occur across all tested wind attack angles, with the most pronounced response observed at α = +5°. Both railing height and inclination angle significantly influence the VIV response, yet their influence patterns are different. Specifically, the VIV amplitude consistently increases with railing height across all wind attack angles, whereas the effect of the inclination angle varies depending on the wind attack angle. The leading and trailing edges of the upper surface and the trailing edge of the lower surface are identified as the critical areas responsible for VIV. The variations in fluctuating pressure coefficient and contribution value with railing configuration are generally consistent with those of the VIV response. Moreover, while the railing configuration does not alter the vortex shedding mode, it significantly modifies the vortex scale and pressure intensity, thereby resulting in distinct VIV responses. Full article

A decline in olfactory ability represents one of the earliest signs of Alzheimer’s disease (AD) and can be valuable information for early diagnosis at the stage of mild cognitive impairment (MCI). Nevertheless, the underlying neurophysiological mechanisms of olfactory impairment have not been systematically studied and, so far, have not been applied to make objective diagnoses using electroencephalography (EEG). To fill this gap, this proof-of-concept study investigates the possibility of using olfactory-evoked EEG complexity to discriminate between healthy subjects (HSs) and MCI patients. To this purpose, a publicly available olfactory oddball EEG-recording dataset was considered. First, a strategy for cleaning the EEG signals was implemented and applied, including exclusion of participants, channels, and epochs affected by substantial artifacts and noise. Then, a dedicated preprocessing pipeline was implemented: in particular, the cleaned signals were partitioned into three temporal intervals according to the stimulus onsets (i.e., pre-stimulus, early post-stimulus, and late post-stimulus periods). For each window of interest, a novel metric—namely, the Multivariate Multiscale Multi-Frequency Entropy (M3FrEn)—was computed across 10 temporal scales. The obtained results showed significant main effects of group and stimulus, as well as a significant group-by-stimulus interaction across all scales, as assessed by linear mixed-effects models. Post hoc analysis revealed a significantly reduced stimulus-related entropy modulation in MCI subjects compared to healthy controls across several early post-stimulus scales, with the strongest effect at scale 6 (adjusted $p=0.0189$, $Hedges’g=-2.88$). An exploratory, fully nested subject-level classification analysis, in which feature selection was performed independently within each cross-validation fold, achieved an accuracy of approximately 92% with all classifiers, consistently relying on the early post-stimulus feature. These preliminary findings suggest that M3FrEn captures olfactory-related EEG alterations in MCI, providing proof-of-concept evidence for its potential as a candidate biomarker. Full article

Landslides are frequent and destructive geological disasters. Accurate landslide identification is essential for post-disaster reconstruction and preventing secondary disasters. Deep learning has shown considerable potential for recognizing landslide objects from remote-sensing images; however, existing models still suffer from insufficient detection accuracy in scenarios with complex backgrounds, blurred boundary localization, sample-class imbalance, and difficulty in balancing detection speed and segmentation accuracy. To address these issues, this study investigates landslide identification in the Great Bend of the Yarlung Zangbo River region using improved deep learning models and heterogeneous optical remote-sensing imagery. (1) By introducing the convolutional block attention module (CBAM) into YOLOv8, 82.79% precision was achieved, and the recall improved by 9.56% compared to the original model, reaching a mean average precision of 75.27% while maintaining computational efficiency, outperforming YOLOv5 and the original YOLOv8. (2) Replacing the cross-entropy loss with Focal Loss in DeepLabV3+ improved the landslide edge segmentation by dynamically adjusting the weights of difficult and easy samples. Compared with the original DeepLabV3+, the precision and recall of the DeepLabV3+-FL semantic-segmentation model were improved by 0.26% and 1.93%, respectively, with the mean pixel accuracy and mean intersection over union reaching 81.76% and 62.59%, respectively. Overall, the two improved models enhanced the accuracy of landslide identification and resistance to interference, demonstrating potential for landslide monitoring and emergency response. Full article

In this paper, we present an algorithmic modeling approach based on Disjunctive Programming using Boolean logic “OR” to solve the Optimal Phasor Measurement Unit Placement (OPP). We propose a framework for modeling the optimal PMU placement subject to disjunctive constraints. A convex objective function is minimized subject to a bilinear equality constraint with a piecewise linear structure. The polynomial constraint constitutes a union of linear segments conceptually analyzed in the two-dimensional continuous space, separating the infeasible from the feasible region. This work investigates the trajectory of iterates from infeasible initial points to stationary solutions and analyzes the convergence behavior using Interior-Point Method (IPM) and Sequential Quadratic Programming (SQP). Our algorithmic model addresses the progress of infeasible and feasible iterates, step computation using line-search and trust-region mechanisms. Combined with second-order correction (SOC) and filter methods, these mechanisms enable the algorithm to maintain a unit primal step, even when starting from an infeasible initial point. Network observability constraints are transformed from a Conjunctive Normal Form (CNF) into a Disjunctive Normal Form (DNF) via Balas’s theory. This geometry transformation reformulates the feasible set into a union of convex affine pieces, effectively eliminating constraint curvature issues. This affine reformulation ensures that gradient-based algorithms maintain a smooth optimization trajectory along a convex local manifold. This trajectory enables the algorithm to preserve the full Newton step, maintaining a superlinear convergence rate. Its underlying piecewise linear convexity inherently enables the gradient-based algorithm to avoid the Maratos effect. Numerical results on IEEE power systems validate the optimization problem. Our framework uses the IEEE-14 bus system to address the high-degree non-convexities. Monte Carlo simulations further enhance the argument that piecewise convexity enables IPM and SQP to converge to binary local minima. Depending on multiple-run initialization, these methods reach the same objective function value. These local minima can be characterized as non-strict optimum points that are structurally symmetric but exhibit unequal basins of attraction. Hence, this geometry-driven formulation enables gradient-based methods to reliably identify binary-valued optimal solutions for the OPP. Full article

The price index of daily commodities is an important indicator of inflation in a country. Adequate modeling of the price index is useful for efficient economic decision-making. Since the exact modeling of the price index is impossible, probabilistic modeling is a suitable alternative for this. The change in the price index of various commodities at different time points is usually dependent, and hence joint modeling is a suitable solution. In this paper, a new family of distributions is proposed for joint modeling of the price index of various Saudi commodities at two different time points and is named as Darwish Bivariate Family of Distributions (DBFDs). Some necessary properties of the family are presented, and some dependence measures are also computed. Conditional distributions for the proposed family are investigated alongside the method for random data generation from any member of the proposed family. The parameter estimation for the proposed family is discussed in general. A specific member of the family, namely the Darwish Bivariate Log-logistic (DBLL) distribution, is studied in detail. Some important properties of the DBLL distribution are presented. The DBLL distribution is used to model the price index of various Saudi commodities. It is found that the proposed DBLL distribution provides a better fit to model the price index in comparison with the other models used in the study. Full article

This study presents a 3D computational fluid dynamics (CFD) investigation of methane and methanol combustion in a medium-speed, large-bore marine spark-ignition engine equipped with a pre-chamber (PC) ignition system. Simulations were performed in ANSYS Forte at 100%, 80%, and 20% engine load. Methane operation with an active PC was used as the reference configuration, while methanol was investigated with both active and passive PC. A preliminary injection-timing analysis was conducted for the active methanol configuration to obtain a near-stoichiometric and sufficiently homogeneous mixture inside the PC at spark timing (ST). The results show that active methanol operation promotes earlier heat release, shorter combustion duration, and higher thermal efficiency than methane operation. The active PC generates stronger turbulent reacting jets and ensures more robust combustion than the passive configuration. Methanol also considerably reduces NO_x emissions because of its lower initial and combustion temperatures. However, active methanol operation increases CO emissions, particularly at low load, because of incomplete oxidation associated with low temperatures, mixture inhomogeneity, and possible spray–wall interaction. The passive PC further reduces NO_x and CO emissions but causes delayed combustion, lower thermal efficiency, higher fuel consumption, and tank-to-wake CO₂ emissions than the active methanol configuration. Full article

Solving problems associated with the efficient distribution and organization of resources has generated increasing interest in the scientific community. One of the most commonly used approaches consists of approximate solution techniques, which have been able to solve complex covering problems within acceptable computational time and cost. One of the benchmarks used to evaluate these approaches is the Set Covering Problem, which is an NP-hard combinatorial optimization problem. Among the techniques that have been investigated, metaheuristics play an important role. These methods are commonly developed for continuous search spaces and, in order to be applied to covering problems, must be modified to operate in discrete domains. This modification presents an important challenge: finding an appropriate transformation method that translates continuous solutions into binary solutions. This issue has been addressed through two main strategies: binarization using two-step schemes, and, in our proposal, the use of repair operators orchestrated according to their performance through an Adaptive Repair Selection Mechanism based on the multi-armed bandit framework. To evaluate our proposal, we selected the Binary Hunger Games Search metaheuristic because the relative quality of each individual determines its hunger level, which in turn regulates the movement of the population and the influence of the best solution found. Infeasible solutions are handled through a set of Tabu Search-based repair operators. Instead of applying a single repair rule throughout the entire execution, the proposed approach dynamically selects among these operators according to their observed contribution during the search. Each repair operator also incorporates Tabu memory to discourage repetitive decisions during feasibility restoration. The experiments were conducted using the classical Beasley benchmark instances for the Set Covering Problem. Full article

Background/Objectives: Stereochemistry can substantially influence the biological activity and pharmaceutical properties of small molecules. This study investigated the stereochemistry-dependent biological activity and chiral recognition of novel naphthylethyl thiourea enantiomers using an integrated biological, chromatographic, and computational approach. Methods: Ten pairs of naphthylethyl thiourea enantiomers were synthesized from enantiomerically pure precursors and characterized. Antiproliferative and antibacterial activity, chiral HPLC behavior on polysaccharide- and protein-based stationary phases, molecular docking, and multivariate relationships were evaluated. Results: Target-dependent enantioselectivity and substituent-dependent activity patterns were observed. All enantiomeric pairs were chromatographically distinguished under at least one condition, and selected compounds showed selector- and mobile-phase-dependent changes in elution order. AGP-based chromatography showed stereoselective recognition for a subset of compounds, while computational analyses provided complementary support for the experimental trends. Conclusions: Stereochemistry and substitution jointly influence biological and chromatographic behavior in this thiourea series. Integrated biological, chromatographic, and computational profiling provides a useful framework for early enantiomer-resolved developability assessment. Full article

Background and Objectives: Magnesium-based biomaterials are increasingly investigated due to their biodegradability, bone-like elastic modulus, and potential osteogenic properties. However, alloy composition may influence degradation behavior and local tissue response. This study aimed to assess and compare the local biocompatibility, degradation characteristics, and bone regenerative response induced by Mg-Zn-Mn-Ca and Mg-Nd-Y-Zr-Zn magnesium alloy powders. Materials and Methods: Two magnesium alloys were evaluated through physicochemical characterization, in vitro osteoblast cytocompatibility and antimicrobial assays, and in vivo testing in Sprague–Dawley rats. Standardized cylindrical defects were created in the medial femoral condyle and filled with either Mg-Nd-Y-Zr-Zn or Mg-Zn-Mn-Ca alloy powders, while untreated defects served as controls. Bone remodeling and defect healing were assessed by micro-computed tomography, allowing three-dimensional qualitative and quantitative evaluation of newly formed bone. Scanning electron microscopy was used to analyze surface morphology and degradation features, while histopathological examination assessed inflammation, osteogenesis, and tissue integration at the implant site. Results: Both magnesium alloy powders showed antimicrobial potency and elicited no cytotoxic effects in vitro, while animal studies revealed progressive biodegradation over time, associated with new bone formation within and around the defect area. Micro-CT analysis demonstrated active bone remodeling in experimental groups, with differences in bone distribution and defect-filling patterns between Mg-Nd-Y-Zr-Zn and Mg-Zn-Mn-Ca implants. SEM revealed alloy-specific degradation morphologies. Histological evaluation showed a moderate early inflammatory response that decreased at later time points, together with ongoing osteogenesis and favorable tissue integration. No severe local adverse reactions or persistent inflammation were observed. Conclusions: Both Mg-Nd-Y-Zr-Zn and Mg-Zn-Mn-Ca alloy powders were locally biocompatible and supported bone regeneration in a rat femoral condyle defect model. Differences in degradation behavior and tissue response emphasize the relevance of alloy composition in developing magnesium-based biomaterials for bone defect treatment. Full article

Background: Injectable bone graft substitutes offer a practical alternative to preformed ceramic scaffolds by adapting to irregular bone defects while preserving osteoconductive properties. This study investigated the in vivo performance of hydroxyapatite/tetracalcium phosphate (HA/TTCP) granules, uncoated or alginate-coated, with or without autologous ovine bone marrow concentrate (oBMC), in a standardized sheep bone defect model. Methods: oBMC was characterized for cellular composition, viability, and recovery. Implanted HA/TTCP formulations were evaluated after 6 and 12 weeks by micro-computed tomography and histomorphometry. Results: Uncoated HA/TTCP granules promoted bone formation, integrating with host bone. Alginate coating improved injectability and handling but influenced granule organization and degradation. Uncoated HA/TTCP + oBMC showed a more favorable response than the coated formulation, with higher bone-to-implant contact (p = 0.004) and bone volume (p = 0.031) at 12 weeks. A modest increase in peri-implant bone volume was observed from 6 to 12 weeks in the HA/TTCP + oBMC group, though this did not retain statistical significance once clustering was accounted for. No significant direct effect of oBMC was observed compared with the cell-free formulation. Conclusions: Injectable HA/TTCP granules + oBMC represent a promising single-step strategy for irregular bone defects, although further coating optimization is needed to preserve biological performance while maximizing handling advantages. Full article

A series of N-phenyl-3-(thiophen-2-yl)acrylamide derivatives were designed and synthesized to investigate the influence of electronic and steric modifications on cytotoxic activity. Although related thiophene-containing acrylamides have been reported, the specific compounds studied in this study have not been previously described. Structural variations were introduced at the para position of the N-phenyl ring (H, CF₃, and OCF₃) and at the 5-position of the thiophene ring (H and CH₃) to enable preliminary structure–activity relationship (SAR) analysis. The target compounds were synthesized via Knoevenagel–Doebner condensation, followed by carbodiimide-mediated amide coupling. The compounds were characterized using nuclear magnetic resonance (NMR) spectroscopy, high-resolution mass spectrometry (HRMS), Fourier-transform infrared (FTIR) spectroscopy, and high-performance liquid chromatography (HPLC). Computational evaluation indicated compliance with Lipinski’s rule of five and the absence of predicted mutagenic, tumorigenic, irritant, and reproductive risks. Cytotoxic activity was determined using the sulforhodamine B (SRB) assay against human breast adenocarcinoma (MCF-7), gastric adenocarcinoma (AGS), colorectal adenocarcinoma (Caco-2), oral squamous cell carcinoma (HSC-3), hepatocellular carcinoma (HepG2) cell lines and non-cancerous human dermal fibroblasts (HDF). Compounds 11 and 16 displayed the most consistent activity, with half-maximal inhibitory concentration (IC₅₀) values of 379, 420, and 265 μM and 272, 256, and 242 μM against AGS, Caco-2, and MCF-7 cells, respectively. MCF-7 cells were the most sensitive model. The most active derivative was compound 16, suggesting that the combination of a 5-methylthiophene moiety and a para-CF₃ substituent may be beneficial within this limited compound series. These findings provide a preliminary evaluation of this scaffold and will help guide future studies on structural modifications. Full article

The pyranoside-into-furanoside (PIF) rearrangement is an uncommon but important process in carbohydrate chemistry. The quantum chemical investigation of the driving force of the recently discovered TfOH-catalyzed ring contraction revealed that it stemmed from the π–π interactions of the phenyl rings in benzoyl-protecting groups. In this study, we focused on the kinetic aspects, which included preliminary 2-O-benzoyl group rotation followed by the protonation of the endo-cyclic O5 atom. Using a combination of DFT and DLPNO-CCSDT methods, we found that in some cases, DFT may not produce adequate energies at the rate-limiting stage of the pyranoside ring opening, presumably due to inadequate modeling of Van der Waals interactions. Predicted rate constants for the PIF rearrangement of the β-O-methyl and β-S-ethyl galactosides were in agreement with NMR kinetic experiments, as the latter reacts significantly slower. The estimated constant for the β-O-phenyl galactoside supports its inability to undergo ring contraction and suggests temperatures of over 400 K for such transformation. The proposed mechanism was additionally confirmed by substituting the triflic acid with the much weaker trifluoroacetic one, which led to a drastic decrease of the reaction rate both in computations and in the experiment. Full article

Background/Objectives: Thrombotic cardiovascular diseases remain a major cause of morbidity and mortality worldwide. Current antithrombotic therapies are limited by insufficient thrombus targeting. This study aimed to develop a fibrin-binding peptide-functionalized, hydrogen peroxide (H₂O₂)-responsive polymeric micelle and to evaluate its physicochemical properties and biological effects under H₂O₂-induced endothelial oxidative stress and preliminary FeCl₃-induced thrombosis conditions. Methods: A fibrin-binding peptide, P2 (VTFIKC), was screened using computer-aided drug design and evaluated through microscale thermophoresis and in vitro thrombus adhesion assays. An all-trans retinoic acid (atRA)-based boronate ester prodrug, BORA, was synthesized to enable H₂O₂-triggered degradation and drug release. BORA was co-assembled with P2-modified Mal-PEG-b-PAsp to prepare P2-Mal-PEG-b-PAsp/BORA micelles. Their physicochemical properties, H₂O₂ responsiveness, H₂O₂-scavenging activity, cytocompatibility, cytoprotective effects, anti-inflammatory activity, and preliminary in vivo efficacy were evaluated. Results: The resulting micelles exhibited a suitable nanoscale size, acceptable cytocompatibility, H₂O₂-responsive changes in particle size distribution, and concentration-dependent H₂O₂-scavenging activity. In H₂O₂-stimulated human umbilical vein endothelial cells, micelle treatment was associated with improved cell viability, lower intracellular ROS-associated fluorescence, and reduced TNF-α and IL-1β concentrations. In a FeCl₃-induced rat carotid artery thrombosis model, P2-Mal-PEG-b-PAsp/BORA micelles altered platelet- and leukocyte-related hematological indices and exhibited preferential accumulation in the thrombotic carotid artery. Conclusions: P2-Mal-PEG-b-PAsp/BORA micelles combine P2-mediated fibrin-binding potential, H₂O₂-responsive release behavior, and H₂O₂-scavenging activity. The findings provide preliminary support for further investigation of this peptide-functionalized nanoplatform. Full article