Search Results (18,759)

Background: Glioblastoma (GBM) remains the most aggressive primary brain tumor, and intraoperative frozen section analysis is the current standard for rapid histopathological assessment. However, this approach is time-consuming and resource-intensive. Stimulated Raman scattering (SRS) imaging has emerged as a label-free technique enabling near real-time microscopic evaluation of fresh tissue. This study compares the visualization of selected histopathological features in a newly developed intraoperative SRS system with conventional hematoxylin–eosin (HE) staining in confirmed GBM. Methods: Tumor samples from 30 patients with neuropathologically confirmed GBM were analyzed. For each case, both HE-stained frozen sections and SRS-generated virtual HE-like images were prepared from separate portions of the specimen. Twelve neuropathologists with varying levels of experience assessed 60 images according to seven predefined GBM criteria, resulting in 720 image evaluations. Feature detection was analyzed using cluster-adjusted generalized estimating equation models, and interobserver agreement was assessed using Fleiss’ κ. Results: Descriptively, hypercellularity and hypervascularization were identified at similar frequencies in both modalities, whereas pleomorphism, endothelial proliferation, mitotic activity, and necrosis were more often recognized in HE images. In cluster-adjusted analyses, SRS showed significantly lower detection rates for hypercellularity, pleomorphism, endothelial proliferation, and mitotic activity, while no significant difference was observed for hypervascularization, necrosis, or pseudopalisading after false discovery rate correction. Interobserver agreement was feature-dependent and generally higher for HE than SRS, particularly for hypercellularity. Conclusions: In this feature-level analysis of neuropathologically confirmed GBM, SRS imaging provided rapid, label-free morphological information and showed comparable visualization of selected histopathological features, particularly hypervascularization. While conventional HE-stained frozen sections remained superior for certain WHO-defining features, SRS represents a promising intraoperative adjunct that may complement established neuropathological workflows. Further studies including non-tumor tissue and a broader range of glioma grades are needed to determine the full diagnostic accuracy and clinical applicability of this technique. Full article

As modern power systems grow increasingly complex, there is a pressing need for stability analysis methods capable of handling nonlinear dynamics while providing physically meaningful and reliable stability indices. Port-Hamiltonian (PH) frameworks have emerged as strong candidates in this regard, offering inherently stable formulations, energy-consistent representations, and modular plug-and-play scalability. However, the practical deployment of PH-based stability analysis remains hindered by the absence of reliable, high-fidelity parameter identification methods that rely on sensor measurements to capture system dynamics while remaining compatible with PH model structures. This paper addresses that gap by proposing a comprehensive three-stage data-driven identification framework for PH modeling of synchronous generators—the central dynamic component of any power system. While the IEEE Standard 115 provides established procedures for transient parameter identification, it exhibits fundamental limitations when applied to PH modeling, including single-scenario identifiability constraints, noise-sensitive derivative-based formulations that amplify sensor measurement errors, and the inability to decouple generator-internal damping from grid contributions. The proposed framework resolves these limitations through multi-scenario excitation using sensor-acquired voltage and current signals, derivative-free state consistency optimization, and physics-based regularization that enforces PH structure preservation. Complete identification of eight key parameters (H, D, $X_d$, $X_q$, $X_d^{\prime }$, $X_q^{\prime }$, $T_{do}^{\prime }$, $T_{qo}^{\prime }$) is achieved with errors ranging from 1.26% to 9.10%, and validation confirms RMS rotor angle errors below 1.2° and speed errors below 0.15%, demonstrating suitability for transient stability analysis, passivity-based control design, and oscillation damping assessment. Full article

Microbial cutinases are promising biocatalysts for polymer recycling. Here, we investigated the structural basis of catalytic activation in a thermophilic cutinase from Chaetomium thermophilum (CtCut). Differential scanning calorimetry revealed a three-state thermal unfolding pathway (Tm = 66.4 °C and 69.5 °C), indicating hierarchical stability. To capture distinct conformational states while avoiding affinity-tag artifacts, we employed both tag-free and tagged constructs. We determined apo-structures of wild-type and S136A mutant CtCut at 1.7 Å resolution and a complementary inhibitor complex at 2.65 Å. In the apo-state, a chloride ion coordinated the electrostatically pre-organized active site, while the catalytic H204 adopted a solvent-exposed, inactive loop conformation. In the inhibitor complex, p-nitrophenol displaced the chloride, establishing a characteristic oxyanion hole network. Concomitantly, the “lid” loop transitioned to an open state, with H204 exhibiting pronounced conformational heterogeneity across eight independent molecules. These complementary structures provide structural evidence for conformational dynamics of the catalytic lid loop, consistent with the conformational cycling model previously proposed for a mesophilic homolog. Full article

This paper presents a computational study of wave–bathymetry and wave–structure interaction problems using advanced numerical techniques based on high-fidelity, two-phase Navier–Stokes (TpNS) flow and reduced-order, fully nonlinear potential flow models. For high-fidelity simulations, the TpNS equations are discretized using the finite-element method, with free-surface evolution captured through a hybrid level-set (LS) and volume-of-fluid (VOF) formulation. A monolithic, phase-conservative LS equation is introduced to mitigate mass loss and interface smearing, combined with a semi-implicit projection scheme. Hydrodynamic forces are resolved using a high-order, phase-resolving cut finite-element method (CutFEM), which enables the representation of complex solid geometries within a fixed background mesh. An equivalent polynomial of Heaviside and Dirac distributions ensures accurate evaluation of surface and volume integrals. Hence, no explicit generation of cut cell meshes, adaptive quadrature, or local refinement is required. For reduced-order modeling, a fast regularized boundary integral method (RBIM) is employed to solve the fully nonlinear potential flow. Singular and near-singular integrals are treated using a subtract-and-addition technique based on auxiliary functions derived from Stokes’ theorem, allowing direct application of high-order quadrature without conventional boundary element discretization. An arbitrary Lagrangian–Eulerian (ALE) formulation is adopted to enforce free-surface boundary conditions while avoiding excessive mesh distortion. The proposed approaches are applied to investigate highly nonlinear wave transformation over complex bathymetry and wave-induced dynamics of floating structures, including eddy-making damping effects. Numerical results are validated against experimental measurements. These two modeling approaches represent complementary levels of physical fidelity and computational efficiency, and their systematic comparison clarifies the trade-offs between computational accuracy, efficiency, and cost for practical marine problems. Full article

Photonic quantum communication enables secure and high-fidelity information transfer beyond classical limits, with direct relevance to emerging quantum networks operating in free-space environments. While physical-layer models of depolarizing noise, Gamma–Gamma turbulence statistics, entanglement swapping, and decoy-state QKD security bounds are individually well established, prior work typically treats these components in isolation or under fixed network assumptions. In this work, we develop a unified topology-aware analytical framework that simultaneously integrates free-space optical link budgets, turbulence-induced visibility degradation, depolarizing qubit noise, multi-hop entanglement cascade dynamics, teleportation fidelity thresholds, CHSH nonlocality certification, and asymptotic decoy-state secret key rate bounds across star, mesh, and ring graph structures. Rather than introducing new physical channel models, we demonstrate that identical physical links exhibit fundamentally different end-to-end performance once embedded within different network topologies. Mesh architectures minimize visibility cascade through hop-count reduction but incur quadratic hardware scaling. Star topologies minimize link count but concentrate noise and synchronization overhead at the hub. Ring configurations offer linear hardware scaling with multiplicative fidelity degradation. The results establish topology as a first-order design parameter in near-term free-space quantum networks operating without full quantum repeater infrastructures. While motivated by distributed multi-agent architectures, the framework applies broadly to terrestrial, airborne, and satellite-assisted photonic quantum communication systems. Full article

Achieving high-precision force tracking in robotic physical interaction remains challenging in the presence of environmental and dynamic model uncertainties. Conventional impedance control strategies often exhibit excessive force overshoot at contact onset and persistent steady-state errors under uncertain or time-varying interaction conditions. To overcome these limitations, this paper proposes a fuzzy-adaptive sliding-mode impedance control approach. During the initial contact phase, a tracking differentiator (TD) is employed to generate a smooth and dynamically feasible force reference, effectively suppressing impulsive force transients without requiring explicit contact detection. Furthermore, a fuzzy-logic-modulated adaptive law is developed to adjust online the adaptation gains of the impedance controller, thereby asymptotically eliminating steady-state tracking errors while preserving Lyapunov stability. In addition, a composite PD–suboptimal sliding-mode control law is embedded within the impedance loop to enhance robustness against external disturbances while ensuring continuous, chattering-free control action. The proposed architecture requires no prior knowledge of environmental stiffness and is provably robust to model inaccuracies and unstructured disturbance. Simulation and experimental results conducted on a 6-DOF robotic manipulator demonstrate that, under realistic uncertain contact scenarios and in comparison with three benchmark methods, the proposed approach reduces overshoot by 26%, shortens settling time by 30%, and decreases steady-state error by 48%. Full article

Modern-day urban warehouses face exploding large inventory and tight spaces requiring fast, accurate, and safe stocktaking in a narrow aisle in a GPS-denied environment. This paper proposes a complete UAV-enabled framework performing real-time QR code scanning with inventory synchronization through a safety-aware trajectory generation for obtaining collision-free motion. A novel hybrid workflow integrating MATLAB/Simulink R2024b and Unreal Engine is used for dynamics and photorealistic rendering, alongside a real-time warehouse setup using drone cameras and 3D LiDAR coupled with a ground control station and live dashboard. The system in this paper was evaluated by testing with single and multi-UAV models across high-fidelity simulations and experiments. Results demonstrate simulated QR accuracy of approximately 95 to 96%, with experimental validation achieving between 86 and 90.5% due to real-world environmental factors. In experimental and simulation analysis, mean end-to-end latency remained under half a second, trajectory error range between 8 and 10 cm, and safety margins were consistently maintained throughout the test. It was further observed that multi-UAV coordination halved mission time compared to single-drone tests while keeping duplicate reads negligible, indicating a scalable and safe pipeline for industry application. Full article

Background: Immune checkpoint inhibitors (ICIs) targeting the PD-1 axis represent standard second-line therapy for metastatic non-small cell lung cancer (NSCLC). Emerging data suggest that SARS-CoV-2 mRNA vaccines may enhance antitumor immunity through innate immune activation and type I interferon signaling, potentially sensitizing tumors to PD-1 blockade. The clinical impact of patients initiating second-line nivolumab remains unclear. Methods: In this retrospective single-center cohort study, 88 patients with recurrent stage IV NSCLC who received second-line nivolumab between 1 January 2023 and 1 January 2026 were analyzed. Vaccination exposure was defined using a 6-month pre-treatment window prior to nivolumab initiation (T0). Patients were stratified according to receipt of ≥2 versus 0–1 mRNA COVID-19 vaccine doses within the 6 months preceding T0 (n = 45 and n = 43, respectively). The primary endpoint was progression-free survival from nivolumab initiation (PFS2). Survival outcomes were estimated using the Kaplan–Meier method and evaluated using Cox regression models. Results: With a median follow-up of 22.4 months, median PFS2 for the overall cohort was 11.1 months (95% CI, 9.4–15.1). Patients receiving ≥2 mRNA doses had significantly longer PFS2 than those receiving 0–1 dose (14.0 vs. 9.6 months; p = 0.04). In multivariable analysis, ≥2 doses were independently associated with reduced risk of progression or death (aHR 0.52, 95% CI 0.31–0.88; p = 0.01). Non-adenocarcinoma histology and baseline brain metastasis were independently associated with shorter PFS2. Conclusions: Receipt of ≥2 mRNA vaccine doses within 6 months before nivolumab initiation was independently associated with prolonged PFS2 in metastatic NSCLC. Prospective multicenter validation is warranted. Full article

Background: The Mediterranean diet (MedDiet) has been associated with anti-inflammatory effects and potential benefits in several chronic conditions. However, adherence to the MedDiet and its relationship with lifestyle factors and disease severity across different rheumatological diseases remain poorly characterized. Objectives: This study aimed to evaluate differences in MedDiet adherence among patients with rheumatoid arthritis (RA), psoriatic arthritis (PsA), and fibromyalgia (FM), and to explore its association with cardiovascular comorbidities, bowel habits, and disease-related outcomes. Methods: In this monocentric cross-sectional study, adherence to the MedDiet was assessed using the 14-item PREDIMED questionnaire. Self-reported data on sociodemographic characteristics, cardiovascular comorbidities, bowel habits, and dietary behaviors were collected through questionnaires. Disease activity and severity were assessed using validated disease-specific measures. Differences in MedDiet adherence across diagnostic groups were evaluated using non-parametric tests. Multivariable models were performed to examine associations between MedDiet adherence and cardiovascular comorbidities or disease outcomes, adjusting for potential confounders including age, sex, BMI, smoking status, and educational level. Results: A total of 422 participants were included (RA n = 165, PsA n = 85, FM n = 172). Significant differences in MedDiet adherence were observed across diagnostic groups (p < 0.001), with the highest adherence in RA, intermediate values in PsA, and the lowest in FM. Compared with the other groups, a higher proportion of FM participants reported food intolerances (46.5%) and restrictive diets, including lactose-free (34.9%) and gluten-free (15.1%) diets. In the FM group, high adherence to the MedDiet was significantly associated with lower FIQR scores (β = −16.9; 95% CI −32.1 to −1.7; p = 0.01) and lower PDS scores (β = −4.34; 95% CI −7.81 to −0.86; p = 0.01). Sensitivity analyses using the continuous PREDIMED score confirmed these associations. Conclusions: Adherence to the MedDiet differs across rheumatological diseases, with the lowest adherence observed in FM. Higher adherence was associated with lower disease severity and impact in FM. These findings highlight the potential relevance of nutritional counselling in rheumatological diseases and support the need for longitudinal and interventional studies evaluating the role of the MedDiet within multidisciplinary disease management. Full article

Background: Today, it is important to measure livestock water consumption to devise sustainable solutions that consider environmental issues, livestock health requirements and animal welfare. Methods: This longitudinal study measured the water consumption of 66 calves subjected to two feeding diets: a recommended diet as control (CON) and an optimised diet (OPT). Individual measurements were collected daily and summarised on a weekly basis over a 20-week period. The analysis considered the impact of environmental conditions depending on the season of the calf’s birth. Results: Before weaning, calves spontaneously drank significant amounts of water in addition to the water brought by the calf milk replacer (CMR), but there was variability between animals. Water consumption among calves in the OPT group was higher than that among calves in the CON group from week 4 onwards (p = 0.005). At weaning, there was a significant increase in water consumption with a total water intake higher in calves in the OPT group compared to calves in the CON group (118.4 L and 78.9 L; p < 0.001). After weaning, water consumption was correlated with the solid feed intake in our model, which did not include direct fodder other than straw. There were no seasonal effects on water consumption before weaning at 9 weeks, but effects were observed after 13 weeks on the feeding plan (p = 0.008), with higher water consumption among calves born in winter and exposed to warmer temperatures in spring. Over a 20-week period, when calves had reached a weight of 180 kg in the OPT group and 150 kg in the CON group, water consumption had reached 1602 L and 1400 L respectively (p < 0.001). Conclusions: Free access to water should be maintained in calf rearing facilities, as water contributes to concentrated CMR and dry solid feed assimilation and the welfare of calves when the feeding plan remains at a modest level, enabling them to tolerate fluctuating environmental conditions. Full article

The control of surface residual stress is paramount for ensuring the mechanical performance and longevity of machined GH2132 superalloy bolts. However, direct measurement of residual stress remains challenging. This study introduces a novel, efficient approach by establishing a quantitative correlation between Vickers hardness and residual stress based on the energy indentation method. The core hypothesis leverages the principle that residual stress modifies the indentation work; the difference in energy dissipation between stressed and stress-free states provides a direct measure of residual stress. A mathematical model relating hardness (HV) to residual stress (σ) was derived. To validate the model and unravel the underlying microstructural mechanisms, orthogonal cutting experiments were conducted. Comprehensive microstructural characterization using SEM, XRD, and metallography revealed a synchronous relationship between hardness and residual stress. Both properties increased concurrently with greater grain refinement and higher volume fraction/distribution density of carbides and γ’ phases, which impede dislocation motion and introduce micro-strain. The model predictions showed excellent agreement (R² = 92.5%) with X-ray diffraction measurements, confirming its reliability. Furthermore, the influence of cutting parameters (speed V_c, feed f, depth of cut a_p) on residual stress was analyzed. Cutting depth was identified as the most significant factor. An optimal parameter combination (V_c = 20 m × min⁻¹, f = 1 mm × rev⁻¹, a_p = 1.2 mm) was identified to maximize beneficial compressive residual stress, corresponding to the most refined microstructure. This work presents a validated, hardness-based model for residual stress assessment in GH2132 and provides a microstructure-guided pathway for optimizing machining processes to enhance component life. Full article

Phenazine derivatives are promising metal-free chromophores with strong redox and photophysical properties, yet their use in photocatalytic hydrogenation remains limited. Here, we report a homogeneous phenazine-based system for the visible-light-driven hydrogenation of nitroarenes under mild conditions. Using nitrobenzene as a model substrate and triethanolamine as a sacrificial hydrogen source, the photocatalyst achieved aniline yields of up to 81% after 12 h of irradiation at 390 nm. Systematic variation in reaction parameters revealed that catalyst structure, solvent, and light wavelength strongly influence performance. Kinetic analysis indicated that prolonged irradiation reduces overall yield due to the reconversion of reactive intermediates. The system exhibited higher efficiency toward nitroarenes bearing electron-withdrawing groups, while aliphatic nitro compounds underwent only partial reduction. Mechanistic studies using UV–Vis, fluorescence, and EPR spectroscopy confirmed the formation of persistent radical species and supported a stepwise electron and proton transfer mechanism. This work showcases the potential of phenazine-based photocatalysts as metal-free platforms for nitroarene reduction under visible light. Full article

Polymer nanocomposites offer significant potential for improving the strength-to-weight ratio and dynamic behavior of drone blades. This study examines the vibration characteristics of tapered aramid (Kevlar)/epoxy composite blades reinforced with nanocarbon fillers—graphene (2D), multi-walled carbon nanotubes (MWCNTs, 1D), and fullerene (0D)—to determine the most effective filler for enhancing stiffness and operational stability. The laminated blades (300 mm length, 200 mm width, root thickness 13 mm, tip thickness 8 mm) incorporate ply drop-offs and a central honeycomb core. Modeling was performed using classical laminate plate theory integrated with the finite element method (FEM) in MATLAB (R2016a). Under clamped–free–free–free boundary conditions, the study considered rotational speeds of 750–2250 rpm, setting angles of 30–60°, various fiber orientations, and nanofiller contents of 0–10 wt.%. The results indicate that while the setting angle minimally affects natural frequency, it significantly influences damping in modes (1,2) and (2,1). Increasing nanofiller content improves stiffness, with optimal performance observed near 5 wt.%. At 1500 rpm in mode (1,1), MWCNTs provided the greatest enhancement. Overall, MWCNTs exhibited superior stiffness improvement and rotational stability compared to other fillers. Full article

Background: Outcomes with enzalutamide in metastatic castration-resistant prostate cancer (mCRPC) are influenced by tumor burden, disease kinetics, and host factors. We evaluated the relative prognostic impact of metastatic pattern, laboratory markers, and prostate-specific antigen (PSA) dynamics in a real-world cohort. Methods: We retrospectively analyzed 72 patients with mCRPC treated with enzalutamide. Progression-Free Survival (PFS) and Overall Survival (OS) were estimated using the Kaplan–Meier method. Multivariate Cox proportional hazards models were utilized to identify independent predictors of survival, incorporating clinical variables (visceral metastases, bone tumor burden), kinetic parameters (Time to Castration Resistance [TTCR], Time to PSA Nadir [TTN]), and host factors (Charlson Comorbidity Index [CCI], Eastern Cooperative Oncology Group Performance Status (ECOG PS), Systemic Immune-Inflammation Index [SII], HALP score). Results: Visceral metastasis was a dominant predictor of poor outcomes, increasing the risk of death by 4.0-fold (HR: 4.05; 95% CI: 1.84–8.89; p < 0.001). A high skeletal tumor burden (≥5 bone lesions) was identified as a critical threshold, associated with a 5.5-fold increase in mortality risk (HR: 5.53; p < 0.001). Delays in initiating enzalutamide significantly compromised survival, with each 1-month delay increasing the risk of death by 7.3% (HR: 1.07; p = 0.003). While early PSA decline (≥50% at 3 months) did not independently predict OS, a prolonged TTN (>12 months) was associated with superior survival. Notably, host-related factors, including age, CCI, and ECOG PS, were not found to be significantly associated with survival outcomes in this specific dataset. Conclusions: Our preliminary findings suggest that survival in real-world mCRPC patients treated with enzalutamide may be influenced predominantly by intrinsic tumor biology—specifically anatomical extent and resistance kinetics—rather than host frailty or comorbidity burden. However, given the retrospective and single-center nature of this study, these findings should be considered hypothesis-generating and require validation in larger, multi-center cohorts. Host-related variables (including age and CCI) were evaluated but were not retained as independent predictors in the final multivariable model. Early initiation of therapy and monitoring of kinetic markers like TTN and TTCR offer superior prognostic stratification compared to static baseline characteristics. Full article

Vision–language models (VLMs) have demonstrated remarkable performance on a wide range of multimodal reasoning tasks, yet their visual grounding mechanisms remain poorly understood and are often unreliable for fine-grained visual concepts. Existing approaches typically rely on raw attention maps or gradient-based saliency, which provide heuristic explanations but lack a causal interpretation of how visual evidence contributes to model predictions. In this paper, we propose an Information Bottleneck Score (IBS) framework that explicitly quantifies the causal importance of visual patches through interventional analysis. By masking candidate image patches and measuring the induced change in the model prediction, the IBS captures patch-level causal contributions rather than correlation-based signals. We further lift patch-level importance to the attention-head level by aggregating the IBS with text-to-image attention, enabling the identification of a small subset of information-transmitting attention heads responsible for visual grounding. Building on the selected heads, we construct refined importance maps that guide visual cropping in a fully training-free manner. Extensive experiments on multiple detail-sensitive benchmarks, including TextVQA, V*, POPE, and DocVQA, demonstrate consistent improvements in fine-grained visual understanding, while evaluations on general-purpose datasets such as GQA, AOKVQA, and VQAv2 confirm that overall reasoning performance is preserved. Additional ablation studies further validate the effectiveness of each component in the proposed framework. Overall, our work provides a causal perspective on visual grounding in VLMs and offers a model-agnostic, training-free approach for both interpreting and enhancing multimodal reasoning. Full article