Search Results (487)

Periodontitis (PD) is a chronic inflammatory disease characterized by the progressive destruction of periodontal supporting tissues. As one of the most prevalent chronic diseases, PD affects more than 743 million people globally, some with serious systemic health implications. Plaque accumulation constitutes the key driver of periodontitis, initiating host inflammatory cascades and compromising periodontal microbiome equilibrium. Conventional treatment methods, such as scaling and root planing, are limited by a constrained operative field, resulting in blind spots that impede the complete eradication of bacterial biofilms and the modulation of the inflammatory microenvironment. Therefore, employing new therapeutic strategies (e.g., drug delivery systems) is essential. This review focuses on local drug delivery systems for the treatment of PD, including fibers, strips and films, microspheres, gels, nanoparticles, and vesicle systems, to deliver drugs directly into the periodontal pockets, targeting inflammation and providing sustained antibacterial effects while reducing systemic side effects. The characteristics and clinical implications of each type of local drug delivery system are discussed, along with emerging technologies such as 3D printing and nanotechnology. Full article

In size, weight, and power (SWaP)-constrained optical systems, such as spaceborne LiDAR, high-precision centroid localization often relies on focal-plane measurements without dedicated wavefront sensors. Under such conditions, the nonlinear coupling between optical aberrations and sensor noise introduces systematic bias that is difficult to mitigate using conventional centroiding methods. To address this issue, we propose a physics-conditioned feature correction framework based on an aberration-conditioned attention mechanism. A hybrid CNN–Transformer architecture is employed to predict and compensate for systematic centroid bias. Specifically, convolutional layers encode the degraded spot morphology, while a multi-head attention mechanism leverages Seidel aberration coefficients to adaptively modulate spatial features for precise regression. Given the unavailability of absolute ground-truth coordinates in empirical scenarios, a physics-consistent simulation framework based on scalar diffraction theory is constructed to generate synthetic data for supervised learning. Simulation results indicate that the proposed method objectively reduces anisotropic systematic bias, achieving a localization root-mean-square error (RMSE) of 0.011 to 0.021 pixels, and maintains stable sub-pixel accuracy even under a 10% empirical prior perturbation. To evaluate generalization performance and engineering reliability, a wedge-based double-spot platform is developed to verify physical consistency via geometric invariance. Experimental results demonstrate a measured spacing standard deviation (SD) of 0.015 to 0.039 pixels. This validates the framework’s transferability from theoretical simulation to controlled physical measurements, providing an algorithmic foundation for precision optical metrology in hardware-constrained environments. Full article

In engineering practice, additively manufactured (AM) metal and metal alloy structural components, which often contain geometric discontinuities to fulfil functional requirements, are subjected to cyclic service loads. Among the possible loading configurations, far-field Mode I loading is frequently considered as a nominal reference condition. Within this context, a methodology for the fatigue assessment of notched AM Scalmalloy components subjected to Mode I far-field loading is proposed, combining the Strain Energy Density (SED) approach with a multiaxial critical plane-based fatigue criterion. The fatigue assessment is carried out at a verification point whose position is defined as a function of the characteristic length of the SED control volume for Mode I loading, determined through two alternative procedures, and of the surface roughness of the component. The proposed methodology is validated against experimental fatigue data available in the literature for AM Scalmalloy specimens featuring a circumferential semi-circular notch and subjected to Mode I far-field cyclic loading, which induces a locally multiaxial stress state at the notch root, given that the formulation does not rely on material-specific assumptions and could in principle be extended to other notched AM metal and metal alloy components. Full article

Depth conversion of underwater static electric fields refers to a mathematical approach that indirectly determines the distribution of planar electric fields at larger depths using measured planar electric field data obtained from a shallower region with finite depth and limited area. The complicated environment of high-latitude low-temperature sea areas further increases the difficulty of performing practical large-depth measurements of underwater electric fields. Therefore, depth conversion becomes an important technical strategy for overcoming the constraints of field measurements and for comprehensively understanding the distribution of underwater static electric fields of the target. This study begins with the mathematical formulation of the depth conversion problem, solves the related boundary value problem, and develops the corresponding depth conversion method. Subsequently, based on COMSOL simulation data of the underwater static electric field generated by a scaled-down submersible model, numerical analyses are conducted to investigate the effects of factors such as grid discretization, measurement plane dimensions, conversion depth, and data noise on the conversion accuracy. Finally, the reliability of the conversion method is validated in a laboratory environment by simulating a naturally frozen sea area and employing measured underwater static electric field data from the scaled-down submersible model. The results demonstrate that the developed conversion method can effectively achieve extrapolation of the underwater static electric field of the submersible from shallow regions to deeper water. Even when the noise amplitude is nearly twice that of the effective signal and the conversion depth reaches 8 times the outer diameter of the submersible, the relative root mean square error (RRMSE) of the conversion results can still be maintained below 0.10. These findings provide useful references for the advancement of technologies related to underwater electric field characteristic recognition and electric field stealth performance evaluation in high-latitude low-temperature sea areas. Full article

Background/Objectives: Root canal procedures on multi-rooted teeth, including first molars, depend on experience, tactile perception, and anatomical knowledge to avoid perforation in the furcation region. Studies using various methodologies and populations have reported discrepant findings on pulpal floor thickness. No study using micro-computed tomography (Micro-CT), the gold standard, has been conducted on a Black South African sample to evaluate pulpal floor thickness. Methods: In this cross-sectional, descriptive, quantitative study, Micro-CT scans of 91 maxillary and 77 mandibular first molars were reconstructed in 3D and oriented according to a reference plane along the cemento-enamel junction using Avizo software. Measurements were taken from the midpoint of the pulpal chamber floor to the perpendicular point on the furcation. In maxillary molars, an additional measurement between the mesiobuccal and distobuccal roots was taken. The effects of arch, side, age, and sex were assessed. Results: Neither sex, arch, nor side had a significant influence on the pulpal floor thickness. The central mandibular and maxillary pulpal floor thicknesses increased significantly with aging, while the effect on the buccal maxillary pulpal floor thickness was not significant. The mean central mandibular and maxillary pulpal floor thicknesses were 2.66 and 2.83 mm, respectively, while the buccal maxillary pulpal floor thickness was significantly smaller at 2.37 mm. Conclusions: More accurate and repeatable findings compared to the literature could be attributed to the use of Micro-CT, which provides higher resolution images, and to Avizo, which enables precise localization of 3D points. Variations from the literature might also be explained by differences in the age and geographical origin of the samples. Full article

Background/Objectives: The aim of this study was to develop a novel Nasal Spine-Guided Classification for assessing the alveolar vertical extension of the maxillary sinus and to evaluate its anatomical relationship with the roots of the posterior teeth using CBCT in a Saudi subpopulation. Methods: Maxillary sinus pneumatization was measured using cone-beam computed tomography for 380 patients. The assessment was performed along a horizontal plane extending between anterior and posterior nasal spine. In addition, pneumatization was evaluated in edentulous areas, and between the roots of multi-rooted teeth. Maxillary sinus membrane thickness was also measured. The results were expressed as mean, median and interquartile range, and considered statistically significant at a p-value < 0.05. Results: The mean maxillary sinus pneumatization on the left side was 8.8 ± 4.32 mm, and 8.58 ± 4.85 mm on the right side, with no statistically significant difference. The median of pneumatization in the edentulous area and between the roots on left side were 5.1 and 3.8 mm respectively, while on the right side, the median pneumatization was 5.03 and 3.04 mm. In addition, the proximity of the maxillary root apices to the sinus floor revealed a zero distance in 80.49% of the roots on the left side and in 79.48% on the right side. Furthermore, the results indicated no statistically significant association between maxillary sinus membrane thickness and pneumatization in the edentulous area. Conclusions: CBCT analysis revealed a predominance of advanced maxillary sinus pneumatization (Class III) and a high frequency of direct contact between posterior maxillary root apices and the sinus floor in the studied population. Additionally, no significant association was identified between maxillary sinus membrane thickness and sinus pneumatization in edentulous areas. Full article

This article presents the findings of experimental research conducted to assess the stability of the force mode of the UR5e cobot from Universal Robots in the low-force range, from 1 N to 10 N. The set values of the robot’s forces and the physically measured values were verified by an OptoForce Hex six-axis Force/Torque sensor attached to the robot’s wrist, additionally coupled with an end-effector specially designed for research purposes. The results were recorded using proprietary software developed in the LabVIEW environment and a configured test lab station with a UR5e cobot. Three experimental tests were performed, in which the parameters of the effective force were measured while varying (1) the position of the task in the workspace of the robot, (2) the position and the level of force, and (3) the controller parameters of the force mode. The results of the experiments were compiled and presented in tables containing descriptions of, among other parameters, the following: the mean forces and their standard deviation; the mean maximum forces and its standard deviation; the mean root mean square error and its standard deviation; the mean absolute error and its standard deviation; the mean rate of force and its standard deviation; and the mean overshoot and its standard deviation. The findings of Experiment 1 demonstrated that when a setpoint of 10 N was employed, the UR5e cobot yielded an actual mean force ranging from 8.95 N to 13.26 N within the workspace plane. Experiment 2 showed that the average deviation from the set value within the 1–10 N range was approximately 0.38 N, with a maximum deviation of 0.61 N occurring at the limits of the working space. Experiment 3 showed that for the force range of 1–4 N, the best controller settings are Gain = 0.5 and Damping = 0.7; for the force range of 5–7 N: Gain = 1.0 and Damping = 0.6; and for the force range of 8–10 N: Gain = 2.0 and Damping = 0.8. Polynomial regression models were developed for each positioning scenario that can be used when making decisions regarding practical applications of the low-force mode. Full article

We investigate the potential of frequent repeat imagery acquired by the PlanetScope Dove small satellite constellation to overcome temporal and spatial limitations in automated surface topography mapping. While individual PlanetScope Dove stereo pairs produce low-quality Digital Surface Models (DSMs) with large height uncertainties, the high temporal frequency enables multiple DSMs to enhance accuracy through multiple-pair image matching. We present a fully automated SETSM framework by improving the quality of PlanetScope Dove DSMs based on SETSM Multi-Pair Matching Procedure (SETSM MMP). This framework enhances stereo pair quality through an optimized stereo pair selection by sequential conditional filtering and a Weighted Stereo Pair Index (WSPI). A novel inter-plane vertical coregistration, which minimizes scaling errors between single stereo pair DSMs, was developed to improve consistency and accuracy in DSM quality without reference surfaces. Applied to the cloud-obscured Pantasma crater region in Nicaragua, the optimized stereo pair selection automatically selects well-defined stereo pairs. The inter-plane vertical coregistration without existing reference surfaces achieves up to a 43% Root Mean Square Error (RMSE) reduction and 26% improvement in distribution within a 5 m vertical error. DSM quality correlated strongly with tile size, stereo pair convergence angle, asymmetric angle and terrain-dependent scale variability. The proposed framework provides fully automatic, high quality PlanetScope Dove DSMs without Ground Control Points (GCPs). Full article

Parallel iterative schemes are widely used for the simultaneous computation of all distinct roots of nonlinear equations in scientific computing and engineering. While high-order parallel methods can provide substantial acceleration, their practical performance is often dominated by the choice of internal real-valued parameters introduced by correction/acceleration mechanisms, which may strongly affect convergence speed and numerical robustness. Classical parameter-selection strategies—based on analytical sufficient conditions, trial-and-error experimentation, or qualitative dynamical diagnostics (basins of attraction, bifurcation-style inspection, and parameter planes)—are typically problem-dependent, expensive to scale, and difficult to automate reproducibly. In this work, we propose a data-driven framework for systematic parameter optimization based on finite-time contractivity profiling. The approach uses k-nearest neighbors (kNN) micro-series analysis to estimate a proxy profile of the largest Lyapunov exponent (LLE) along the iteration index, summarizing the transient contraction/expansion behavior of the solver trajectories. Two profile-based scores, the minimum score $S_{min}$ and the moment score $S_{\mathrm{mom}}$, are introduced to rank candidate parameter pairs and to construct stability landscapes over $(\alpha ,\beta )$ grids. As a testbed, we apply the framework to a bi-parametric two-step parallel Weierstrass-type scheme and demonstrate that the learned parameter regions yield faster and more reliable convergence than generic or manually tuned choices. Extensive numerical experiments show that the proposed profiling-based optimization consistently improves convergence rate and robustness across the considered nonlinear test problems, providing a scalable and reproducible alternative to heuristic and dynamical-system-based tuning. Full article

Periodontitis is a highly prevalent chronic inflammatory disease initiated by dysbiotic biofilms and sustained by an exaggerated host immune response, for which scaling and root planing (SRP) remains the cornerstone of therapy. However, mechanical debridement alone may be insufficient to fully resolve inflammation in complex cases and in susceptible patients. In this context, natural products and host modulatory strategies have emerged as potential adjunctive therapies owing to their antimicrobial, anti-inflammatory, antioxidant, and immunomodulatory properties. This systematic review and meta-analysis aimed to evaluate the effectiveness of natural products used as adjuncts to SRP on periodontal clinical outcomes. Comprehensive electronic searches were conducted in MEDLINE/PubMed, Scopus, Web of Science, Cochrane CENTRAL, Embase, SciELO, and Google Scholar through December 2025, and randomized controlled clinical trials were included. Ninety studies were eligible for qualitative synthesis, and thirty-three were incorporated into the meta-analysis. The interventions encompassed a broad spectrum of plant-derived, host-modulatory and nutraceutical compounds, including curcumin, resveratrol, propolis, Aloe vera, green tea catechins, and omega-3 fatty acids, administered via local, systemic, or rinse-based approaches. Meta-analytic findings demonstrated that adjunctive natural products significantly enhanced probing pocket depth (PPD) reduction and clinical attachment level (CAL) gain compared with SRP alone, with additional improvements in gingival inflammation and bleeding outcomes; however, substantial heterogeneity was observed among studies. Overall, natural products provide measurable adjunctive benefits to SRP in the management of periodontitis, although further well-designed, standardized, and long-term randomized trials are necessary to support their routine clinical implementation. Full article

The increasing scale and structural flexibility of modern wind turbine rotors have made real-time monitoring and active control of blade tip deflection a critical requirement for ensuring operational safety, particularly regarding blade-tower clearance. Since direct measurement through physical sensors is often impractical due to high costs, installation difficulties and maintenance challenges, this work proposes a data-based framework for out-of-plane blade tip deflection estimation. The approach introduces a systematic and hierarchical input selection framework that evaluates sensor signal groups, ranging from standard SCADA measurements to configurations including auxiliary nacelle/tower sensors and dedicated blade-root instrumentation. By combining Spearman correlation and spectral coherence, the proposed framework ensures consistent representation of key turbine dynamics across all operating regions. This framework provides a structured trade-off between implementation feasibility and estimation fidelity, enabling tailored solutions for applications such as structural health monitoring and safety-critical active control. Compact Feedforward Neural Network (FNN) and Time-Delay Neural Network (TDNN) architectures, whose hyperparameters are optimized via Bayesian optimization, are employed to achieve high estimation accuracy while preserving computational efficiency. Evaluated through high-fidelity aeroelastic simulations of the NREL 5 MW turbine using the industry-standard FAST (Fatigue, Aerodynamics, Structures, and Turbulence) tool across all operating conditions, the approach achieves $R^2=0.894$ using SCADA-only inputs, $R^2=0.973$ when augmented with nacelle and tower-top sensors and a peak fidelity of $R^2=0.989$ using blade-root bending moment data. These results demonstrate that high-fidelity virtual sensing is attainable without blade instrumentation, providing a viable pathway for real-time tip clearance monitoring and fatigue mitigation. This directly enhances the operational resilience of wind energy systems and their contribution to the stability of renewable-dominated power grids. Full article

This study evaluated the biomechanically optimal insertion angle for miniscrew-assisted anterior intrusion by analyzing stress in the periodontal ligament (PDL) and alveolar bone. A three-dimensional finite element model from cone-beam computed tomography (CBCT) data, comprising maxillary bone, anterior dentition, and a bonded orthodontic appliance, and segmented 0.019 × 0.025-inch stainless-steel archwire were used. Titanium miniscrews (1.4 × 6 mm) were placed at 5 mm from the alveolar crest between the lateral incisor and canine. Four insertion angulations relative to the occlusal plane (30°, 60°, 90°, and 120°) were simulated under a 90 g intrusive force. Results demonstrated that while all configurations achieved intrusion with minor labial tipping and maintained miniscrew stability, stress localization was highly angle-dependent: the 90° insertion generated the highest central incisor PDL tensile stress and maximum cortical bone Von Mises stress; the 120° insertion yielded peak canine PDL Von Mises stress and maximum root displacement; and the 60° insertion localized peak stresses within the cancellous bone and the bone–implant interface. Miniscrews remained stable in all scenarios. While all tested miniscrew angulations provided stable anchorage for upper anterior teeth intrusion, the selection of insertion angle critically influenced stress patterns within the supporting tissues. Full article

Background: Numerous plant-derived products have shown notable potential in preclinical studies and traditional use for the management of periodontitis, although clinical studies validating their efficacy remain scarce. The present study investigated the efficacy of a polyherbal phytopreparation as an adjunctive therapy to scaling and root planing (SRP) in patients with periodontitis, and further examined its underlying mechanisms of action, pharmacokinetic behavior, and toxicological profile using in silico approaches. Methods: Eighty patients with moderate periodontitis (stage II, grade A) were randomly assigned to two groups: a control group (n = 40) treated with SRP alone, and an experimental group (n = 40) receiving SRP followed by topical phytotherapeutic treatment with the polyherbal Tinctura paradentoica^®. Efficacy was evaluated using the gingival index, periodontal pocket depth, and cytomorphometric analysis of gingival cells before treatment and one month after. The in silico analysis, guided by HPLC profiling, included MolDock-based docking to assess interactions of bioactive compounds with cyclooxygenase isoforms COX-1 and COX-2 as anti-inflammatory targets, and evaluation of their pharmacokinetic and toxicity properties (ADME/Tox) using SwissADME, ProTox-3.0, and pkCSM. Results: Compared with SRP treatment, the experimental treatment significantly reduced the gingival index and periodontal pocket depth (p < 0.05), as well as the assessed cytomorphometric parameters (nuclear area, perimeter, and Feret’s diameter values) (p < 0.001). Rerank analysis revealed van der Waals-driven isoform selectivity: compact phenolic acids and aglycones favored COX-1, whereas bulky glycosides (e.g., rutin, narcissoside) were optimized for COX-2, with luteolin-7-O-glucoside showing near-balanced engagement. The ADME/Tox analysis indicated generally favorable pharmacokinetic and safety characteristics of phenolic compounds from the phytopreparation, including low systemic absorption and no predicted mutagenicity or skin sensitization potential. Conclusions: The topical application of the polyherbal phytopreparation demonstrated significant potential to enhance the efficacy of conventional SRP therapy by promoting the regression of gingival inflammation in patients with moderate periodontitis, further supported by in silico findings. Full article

Background and aim: Traditional marker-based optical motion capture systems are costly, time-consuming to operate, and constrained by laboratory environments, limiting their broader adoption in clinical practice and naturalistic settings. Markerless motion capture based on a sums-of-Gaussians (SoG) body model is a potential alternative; however, its metrological properties for kinematic assessment during walking and slow running remain insufficiently validated. Using a conventional marker-based Vicon system as the reference, this study evaluated the reliability and concurrent validity of an SoG-based markerless system (MocapGS) for bilateral lower-limb joint range of motion (ROM) during gait. Methods: Thirty-six healthy adults completed self-selected-pace speed walking and slow running tasks while both systems synchronously acquired bilateral lower-limb kinematics. The intraclass correlation coefficient (ICC), standard error of measurement (SEM), SEM percentage (SEM%), minimal detectable change (MDC), MDC percentage (MDC%), and root mean square error (RMSE) were used to assess reliability. Concurrent validity was evaluated using the Pearson correlation coefficient, paired-sample t-tests, and the concordance correlation coefficient (CCC) to compare the ROM. Results: Vicon showed moderate-to-high reliability for ROM in most joints across both tasks. By contrast, the MocapGS achieved acceptable ICC values mainly for the sagittal-plane ROM at the hip and knee. The CCC analysis showed no significant agreement between the two systems. Bland–Altman plots showed systematic biases with spatially heterogeneous random errors. During walking, MocapGS systematically overestimated ROM relative to Vicon at several joint axes; the widest limits of agreement (LOA) occurred at the left knee X-axis and right hip Z-axis. During running, overestimation was consistent across all bilateral joints at the X-axis and the right hip at the Y-axis, while the widest LOA were found at the bilateral hip X-axes. These specific discrepancies highlighted the joint–axis combinations with the greatest measurement variance. In walking, the test–retest reliability of the knee flexion–extension ROM measured by the MocapGS approached that of Vicon; however, the SEM% and MDC% were generally larger for MocapGS than for Vicon. The RMSE exceeded 5 degrees for ROM in most joint planes, especially in the frontal and transverse planes and at distal joints; errors increased further during slow running. Conclusions: MocapGS may be used for coarse monitoring of large-magnitude changes in sagittal-plane kinematics during gait; however, it is currently unlikely to replace Vicon for clinical decision-making or detecting subtle gait changes, and its outputs should be interpreted with caution, particularly for ankle kinematics and non-sagittal-plane motion. Full article

A pixelated instantaneous phase-shifting interferometry (PSI) using a phase-only liquid crystal spatial light modulator (LC-SLM) is developed and experimentally validated. The LC-SLM generates high-frequency spatial phase modulation and introduces pixelated instantaneous phase-shifting between two incident orthogonal linearly polarized beams propagating along the same optical path. A single-frame pixelated phase-shifted interferogram is captured in one exposure, and the wavefront phase is reconstructed subsequently by using the proposed loop retrieval algorithm. In the experimental investigation, an interference region segmentation method based on wavefront-modulated sequential images is firstly developed to realize precise alignment between LC-SLM pixels and CCD pixels. Secondly, based on the PSI setup established, wavefront measurement experiments for system aberration, tilted wavefront and defocused wavefront are performed. Experimental results show that the root-mean-square (RMS) value of the residual wavefront between the retrieved tilted wavefront and its fitting plane is 0.046 λ. Furthermore, the RMS value of the residual wavefront between the defocused wavefront retrieved by the proposed method and the eight-step phase-shifting method is 0.075 λ, which verifies the effectiveness of the proposed approach. This work provides a simple and rapidly deployable solution for single-shot interferometric measurement. Full article