Search Results (634)

Multi-frame fusion is standard for converting frame-by-frame license plate character detections into stable, reliable readings. Character Time-Series Matching (CTM), a leading approach, associates characters across frames using the Hungarian algorithm with a fixed Euclidean distance threshold and a translation-only motion model, reporting 96.7% accuracy on the UFPR-ALPR dataset. In this work, we demonstrate that this high performance is protocol-dependent: when ground-truth static plate crops and pre-segmented tracks are used, CTM performs strongly. However, in real-world scenarios involving moving cameras (such as drone-mounted cameras, helmet-mounted cameras, and mobile platforms) where inter-frame geometry changes dynamically, baseline multi-frame association frameworks that combine fixed spatial gates with unconstrained translation propagation fail. In these cases, temporal fusion provides no benefit and degrades plate recognition performance below the single-frame baseline. Indeed, under its own Intersection over Union (IoU) tracker, this literature method correctly reads only 15.1% of plates in traffic videos recorded with a real moving camera (86 human-verified tracks). To address this vulnerability, we propose Geo-CTM (Geometry-Constrained CTM), an association pipeline integrating height-scaled adaptive matching gates, inter-frame similarity estimation via Random Sample Consensus (RANSAC), transform-guided character coasting, and co-occurrence-constrained duplicate track elimination. Systematic motion-model ablation demonstrates that while the complete association pipeline provides the primary foundation for robustness (raising mean accuracy from 85.40% to over 91.5%), estimating a similarity transform (91.82%) delivers the most physically grounded and identifiable representation on planar plates without estimation degeneration. While our method performs comparably to CTM on ideal data when using the same detector and detections, it minimizes performance loss under geometric distortion conditions where CTM is inadequate. For instance, a statistically significant improvement is achieved under a 0 → 60° perspective change; in real traffic videos, with the tracker held fixed so that the fusion layer is the only variable, performance rises from 15.1% to 26.7% under the IoU tracker of the original system and from 16.3% to 29.1% under ByteTrack ($+11.6$ and $+12.8$ points; exact McNemar $p=0.021$ and $p=0.013$), whereas changing the tracker alone while holding the fusion layer fixed moves accuracy by only 1–2 points and is not statistically significant. Finally, our error taxonomy analysis demonstrates that on the undistorted benchmark all residual errors correspond to zero-evidence cases beyond the reach of decision-level fusion, while under dynamic perspective distortion errors are dominated by association misalignment, highlighting the specific development areas that future performance improvements must target. Full article

Accurate reconstruction of thin-walled marine structures, such as ship hull plates and stiffened panels, via the conventional inverse Finite Element Method (iFEM) is severely limited by strain data scarcity in real-world deployments. Existing augmentation approaches either lack explicit physical constraints or rely on prior knowledge, restricting generality. This paper proposes a self-evolving physics-constrained multi-round strain augmentation framework (SPMR iFEM) that extracts deformation physics, specifically curvature trends, from iFEM-reconstructed displacements using only sparse measurements, without any prior knowledge. This extracted physics serves as a self-evolving reference to guide multi-round strain augmentation, progressively refining the displacement field through controlled steps. The method is demonstrated on two representative transverse deformation modes of ship plates: pure transverse deformation and a complex S-shaped transverse deformation. Quantitative results show that SPMR-iFEM reduces the maximum reconstruction error from 91.73% (conventional iFEM) to −11.68% for pure transverse deformation, and from 228.29% to −22.44% with four rounds and to −47.69% even with a single round for S-shaped deformation. The proposed prior knowledge-free, physics-constrained framework offers a robust shape sensing solution for marine structural health monitoring under data-sparse conditions, with potential for SHM in marine engineering involving complex deformations. Full article

Background: Rehabilitation of the severely atrophic posterior mandible remains challenging when the residual bone height above the inferior alveolar nerve (IAN) is insufficient for conventional implant placement. In such cases, IAN lateralization or transposition may facilitate placement of longer implants and support fixed prosthetic rehabilitation. However, these procedures require careful case selection because of their technical complexity and the risk of neurosensory complications. Objective: This narrative review presents a literature-informed, expert-derived, parameter-based clinical decision framework for preoperative planning of IAN lateralization and transposition in the severely atrophic posterior mandible. Methods: A focused appraisal of the literature was performed to identify anatomical, prosthodontic, and surgical parameters relevant to IAN repositioning. Parameters were selected according to their recurrent relevance to surgical feasibility, implant positioning, procedural safety, and restorative planning, and were integrated with the authors’ clinical experience to develop a structured decision-making framework. No formal risk-of-bias or certainty-of-evidence assessment was performed. Each parameter was assigned an evidence-source category and a threshold status to make its evidentiary basis explicit. Results: The proposed framework organizes treatment planning into three domains: bone-related, prosthodontic, and surgical considerations. Key parameters include residual bone height above the IAN canal, global mandibular height, ridge width, bone density, crown-to-implant ratio, intermaxillary space, ridge angulation, buccal cortical plate thickness, and the three-dimensional course of the IAN. Additional parameters include interforaminal dentition, implant trajectory, canal diameter, bifid canal anatomy, and ridge contour. Collectively, these variables are integrated into a stepwise decision pathway to help determine whether IAN repositioning is appropriate, whether lateralization or transposition is preferable, and when alternative approaches, such as short implants, ridge splitting, or vertical augmentation, may be more suitable. The framework links restorative feasibility and surgical risk to the choice of technique within a single sequential pathway, and reports the evidence basis of each decision point. Conclusions: The proposed framework should not be regarded as a validated clinical decision tool; prospective clinical validation and consensus-based refinement are required before routine clinical implementation. The framework is intended to structure and guide multidisciplinary assessment and discussion of cases; it should not independently determine treatment selection or replace individualized clinical judgment. Full article

Multi-storey solar chimneys are often evaluated using shaft-outlet airflow, which may conceal uneven airflow distribution among floors. A shaft may provide adequate extraction while upper floors receive insufficient air or experience reverse airflow. This study examined the relationship between neutral plane (NP) position and floor-specific airflow to guide adjustments to openings in a nine-storey building with two solar chimneys. Three-dimensional unsteady computational fluid dynamics (CFD) simulations quantified airflow rate and direction on each floor, airflow at the shaft outlet, and NP height. During controlled case screening at a prescribed absorber-plate heat flux of 484.24 W/m², each shaft’s outlet airflow exceeded the combined requirements of its connected floors, although reverse airflow occurred at 2F and 7F–9F. Reducing selected lower-floor opening areas raised the NP from 11.5 to 12.4 m in the west-shaft zone and from 29.2 to 35.9 m in the east-shaft zone, redistributing airflow upward without changing shaft geometry. Across the six evaluated transition-season months, compliance rates were 100% on 1F–7F, 79.2% on 8F, and 0% on 9F. Airflow remained inward on 8F throughout, whereas reverse airflow persisted on 9F. This study demonstrates that joint assessment of NP position alongside shaft-outlet airflow and floor-specific requirements distinguished insufficient extraction from uneven distribution and informed opening adjustments. Within the evaluated building and design space, however, the tested opening-area strategy did not resolve reverse airflow on 9F and would need to be combined with additional measures targeting the upper-floor pressure and airflow path to achieve building-wide compliance. Full article

The integration of complementary sensing modalities provides a basis for accurate crack identification in advanced aircraft structures. In this context, PZT transducers are sensitive to incipient damage through guided-wave interrogation, whereas strain gauges capture quasi-static deformation. Prevailing fusion paradigms, however, encounter an interpretability–adaptability dilemma. Model-based approaches lack robustness to sensor degradation, while data-driven attention methods sacrifice transparency. To resolve this trade-off, an Evidence-guided Attention Neural Network (EANN) is proposed. Its central methodological contribution lies in repositioning Dempster–Shafer (D-S) evidence theory from a terminal fusion operator to an upstream credibility feature extraction module. Evidence-derived credibility features, comprising belief entropy, inter-source similarity, and Kalman-filtered residuals, drive the attention weight optimization and endow the learned channel weights with physically interpretable evidential meaning. Ablation experiments confirm that the observed improvement arises from the interaction between the evidence-guided credibility representation and adaptive attention weighting, with neither component sufficient on its own. The framework fuses quasi-static strain measurements with active piezoelectric guided-wave interrogation, which offers high sensitivity to incipient damage but remains vulnerable to channel degradation. Experiments on aluminum tensile plates and trapezoidal wing skin specimens show that EANN maintains identification accuracy under simulated sensor anomalies and partial failures by attenuating compromised channels without explicit fault detection, providing an uncertainty-aware fusion framework for online structural health monitoring of aerospace structures. Full article

Hotel breakfast buffets combine a visible hospitality encounter with an operating system in which production surplus, buffet returns, and plate waste can arise, yet material and experiential outcomes are usually examined separately. This focused integrative review uses structured narrative synthesis, framework-guided thematic coding, source-to-claim mapping, and design-sensitive critical appraisal to examine 35 publications. Evidence directness and methodological credibility are assessed separately. Three publications paired a quantitative material waste measure with a quantitative experiential or satisfaction measure, but only one directly combined hotel breakfast buffet plate waste with field satisfaction; one concerned a related hotel buffet with intervention-specific experience measures, and one supplied transferable hotel restaurant evidence. The synthesis identifies context-specific support for selected behavioural interventions and setting-proximate operational evidence for measurement and tracking. Forecasting, simulation, and guest-facing digital applications remain dependent on local calibration and field validation. The paper proposes display and replenishment as a material–experiential service operations coupling point, treats abundance cues as an unvalidated sensitising proposition, and presents an evidence-calibrated two-pathway model and context-sensitive F&B decision matrix. The matrix links waste origins, interventions, operational indicators, experience safeguards, context, and illustrative local testing criteria. The framework is a research and local testing heuristic rather than a validated implementation protocol. Full article

Background: School-based sustainable and healthy diet (SHD) interventions often inadequately capture the multidimensional nature of sustainability, with socioeconomic and cultural dimensions frequently underrepresented. While digital interventions can facilitate the integration of multiple SHD components, maintaining user engagement remains a persistent challenge that can compromise intervention effectiveness. Digital serious games represent a promising intervention strategy that can address both limitations by delivering multidimensional SHD content through interactive and engaging learning, while enabling real-time behavioral monitoring. Objectives: To assess the feasibility, as well as the acceptability and user experience of “Sustainable ePlate”, a web-based serious game for multidimensional SHD educational interventions in schools, during school-based sessions. Methods: Sustainable ePlate integrates food-level sustainability indicators into a scaffolded nine-challenge serious game. Challenges are presented through the healthy eating plate structure, while addressing eight food-level sustainability indicators transformed into 1–5 ordinal game scores. A database of 138 food items was developed from publicly available LCA and TCA databases. The game design draws on established learning theories implemented through progressive challenge sequencing, tiered feedback, and social features. Feasibility was assessed in guided school sessions in Northern Greece using the eGameFlow questionnaire and system in-app metrics. Results: The assessment sample comprised n = 59 students from two secondary schools, of whom n = 57 completed the eGameFlow questionnaire. Mean overall enjoyment was 82.54 ± 16.33%. Mean session duration was 22.39 ± 12.68 min. Across all sessions, 6003 food selections were recorded, with 5179 correct and 824 incorrect placements, corresponding to an 86.27% placement accuracy rate. In-app metrics indicated strong technical feasibility, with all sessions completing the full game sequence. Behavioral metrics demonstrated active interaction, characterized by placement interval duration, hesitation times, and high placement accuracy. Conclusions: Sustainable ePlate demonstrated feasibility and a positive user experience as a school-based serious game for multidimensional SHD education, and as a research platform for capturing in-app behavioral metrics. Further studies are required to assess its educational effectiveness in improving knowledge, attitudes, and practices related to sustainable healthy diets through pre–post design interventions. Full article

Accurate detection of sub-millimeter defects in reactor core-plate cotter-pin holes is essential for nuclear safety. However, underwater inspection images often suffer from low signal-to-noise ratios, weak boundary responses, and pseudo-edge interference, resulting in unstable localization of defects. Existing deformable and attention-based detectors remain vulnerable to sampling drift and semantic–boundary inconsistency under such conditions. To address these challenges, an Edge-Geometry-Guided Deformable Detection Network (EGD-Net) is proposed for underwater defect detection. EGD-Net introduces an edge-geometry-constrained deformable sampling mechanism that embeds edge-confidence priors into deformable convolution to improve boundary-aware feature sampling. A cross-level semantic–geometric alignment strategy is designed to enhance the interaction between defect semantics and geometric boundary cues, while a top-down feedback recalibration mechanism improves multi-scale response consistency for weak defects. Experiments on the Core-Plate Pin-Hole Defect (CPHD) dataset demonstrate that EGD-Net achieves the highest AP@[0.5:0.95] on both datasets while maintaining competitive or superior Precision, Recall, and F1-score while reducing engineering center error under a fixed operating point. Performance across the two complementary domains suggests its robustness to variations between coupon images and practical underwater inspection scenes. These results indicate that EGD-Net provides a reliable solution for boundary-sensitive localization of underwater sub-millimeter defects in nuclear inspection. Full article

Background/Objectives: Temporary hemiepiphysiodesis corrects idiopathic genu valgum during growth, but alignment may drift after implant removal. Radiographic alignment to skeletal maturity was evaluated, and factors associated with post-removal rebound were explored. Methods: This single-center longitudinal observational cohort study included 17 patients (31 limbs) treated with tension-band plates. Standing long-leg radiographs were assessed before implantation (t0), at plate removal (t1), and at final follow-up after skeletal maturity (t2). Rebound was defined as a lateral mechanical-axis deviation (MAD) shift of at least 5 mm from t1 to t2. Paired comparisons and exploratory linear regression models were used to assess longitudinal changes and potential predictors of rebound. Results: Mean age was 13.53 ± 1.27 years at t0, 14.67 ± 1.45 years at t1, and 19.64 ± 1.08 years at t2. MAD changed from −15.06 ± 7.32 mm at t0 to 3.65 ± 7.29 mm at t1 and −1.03 ± 7.48 mm at t2. The mean lateral shift after plate removal was 4.68 ± 6.55 mm (p < 0.001). A total of 15 of 31 limbs (48.4%) met the rebound definition. At t2, 29 limbs (93.5%) remained within Stevens zones ±1. Greater residual growth (univariate b = 0.621, p = 0.003) and isolated distal femoral plating (univariate b = 5.534 mm, p = 0.017) were associated with greater lateral drift and remained significant in the multivariable model. Conclusions: Post-removal rebound was frequent but generally modest, with the observed alignment drift predominantly reflecting distal femoral change. Nevertheless, most limbs remained within the central, clinically acceptable Stevens zones at skeletal maturity. These findings support continued radiographic surveillance, particularly following isolated distal femoral correction and in patients with substantial residual growth. Full article

Uneven straw conveying and unstable throwing can reduce the operational performance of rice combine harvesters. To address these problems, an integrated straw conveying and throwing device combining guided conveying with pneumatic throwing was developed. The brachistochrone principle was introduced into the curved-surface design of the diversion plate as a geometry-guided approach to provide a continuous transition between the straw-falling region and the conveying inlet. Based on the motion characteristics of straw in the diversion and throwing regions, a coordinated feeding–acceleration–throwing process was established. The effects of diversion plate angle, blade rotational speed, and blade installation angle on throwing distance and distribution stability were investigated. A computational fluid dynamics model based on the mixture multiphase approach was used to characterize the macroscopic gas–solid flow field and compare airflow organization under different blade installation angles. A Box–Behnken response surface design was subsequently employed to establish regression models for throwing distance and the coefficient of variation in straw distribution, followed by multi-response numerical optimization. The optimal parameter combination consisted of a blade rotational speed of 2500 r/min, a diversion plate angle of 1.25 rad, and a backward blade installation angle of 15°. Under these conditions, the predicted throwing distance and coefficient of variation were 7.89 m and 14.6%, respectively. Validation tests produced throwing distances of 6.94–8.21 m and coefficients of variation of approximately 13%, showing good agreement with the predicted performance. The developed device and optimization results provide a basis for improving the conveying continuity and throwing uniformity of straw-handling systems in combine harvesters. Full article

The genus Glaucium (Papaveraceae), comprising approximately 30 species, is widely distributed across the Mediterranean region, Europe, North Africa, and Central and Southwest Asia. In the flora of Türkiye, the genus is represented by 11 taxa and is commonly known as “boynuzlu gelincik” and “çömlek çatlatan”. The aim of this study is to explore the analgesic and anti-inflammatory properties of Glaucium corniculatum (L.) Rud subsp. refractum (NAB) Cullen, and Glaucium leiocarpum Boiss., which are found in Türkiye and are known for their high alkaloid content. Traditionally, G. leiocarpum has been used for wound care, cuts, bruises, acne, hemorrhoids, headache, and diarrhea, while G. corniculatum subsp. refractum has been employed as an antitussive and for external applications against ocular inflammations. Ethanolic extracts and crude alkaloid fractions from the aerial parts were evaluated in vivo in anti-inflammatory and antinociceptive test models. Anti-inflammatory activity was assessed by the carrageenan-induced paw edema model, while antinociceptive activity was determined using tail-flick and hot-plate tests. G. leiocarpum ethanolic extract (200 mg/kg) showed the highest anti-inflammatory activity, effectively suppressing carrageenan-induced edema (1.58 ± 0.30–1.73 ± 0.51 mL), and displayed the strongest antinociceptive activity, with tail-flick latencies reaching 23.91 ± 2.08 s (90 min) and 22.23 ± 1.97 s (150 min) and hot-plate latencies of 22.27 ± 4.76 s (30 min) and 23.00 ± 4.61 s (90 min). Bioactivity-guided fractionation of the most active extract was carried out using various chromatographic techniques. Thin-layer chromatography (TLC) and high-performance liquid chromatography (HPLC) analyses were employed throughout the isolation process to monitor fractions and determine their phytochemical profiles. As a result, two compounds were obtained and subsequently evaluated for their biological activities. The chemical structures of the isolated compounds were elucidated by spectroscopic methods, including ¹H-NMR, ¹³C-NMR, 2D-NMR, and LC-MS analyses as kaempferol-3-O-glucorhamnoside and quercetin-3-O-glucorhamnoside. Biological activity evaluation demonstrated that these compounds significantly contributed to the observed antinociceptive activity. These findings confirm that Glaucium species are traditionally used and highlight their potential to provide bioactive compounds with anti-inflammatory and pain-relieving effects. Full article

Coronary artery calcification (CAC) is a hallmark of advanced atherosclerosis and a major determinant of procedural complexity during percutaneous coronary intervention (PCI). Once considered a passive consequence of vascular degeneration, CAC is now recognized as an active, highly regulated process driven by inflammation, oxidative stress, extracellular vesicle release, osteogenic differentiation of vascular smooth muscle cells, and biomechanical remodeling. These mechanisms generate a spectrum of calcific phenotypes, ranging from microcalcifications and sheet calcium to nodular calcium and calcified nodules. Calcified nodules represent an advanced fibrocalcific plaque phenotype characterized by fractured calcific plates, luminal calcium protrusion, surface disruption, and variable thrombus formation. They can be characterized using intravascular ultrasound (IVUS), optical coherence tomography (OCT), and hybrid near-infrared spectroscopy–IVUS imaging, and are associated with coronary thrombosis, stent underexpansion, restenosis, target lesion failure, and the need for advanced calcium-modification strategies. A structured literature search of PubMed/MEDLINE, Web of Science Core Collection, and Scopus identified 83 publications published between 2020 and 2026 for inclusion in the narrative synthesis. This narrative review summarizes the biological and biomechaniclam mechanisms of coronary calcification and calcified nodule formation, compares multimodality intravascular imaging criteria, and discusses contemporary imaging-guided PCI strategies, including balloon-based modification, rotational and orbital atherectomy, excimer laser coronary atherectomy, intravascular lithotripsy, and hybrid approaches. By integrating pathobiology, intravascular imaging criteria, and lesion-specific PCI strategies, this review provides a clinically oriented framework for the assessment and management of calcified nodules. Future directions include standardized imaging definitions, prospectively validated morphology-guided treatment algorithms, and computational and artificial intelligence-assisted plaque characterization. Full article

The goal of this work is to develop an optimized framework for ultrasonic guided wave imaging in order to increase the precision of damage localization in planar structures. This work is novel in that it refines the Reconstruction Algorithm for Probabilistic Inspection of Damage (RAPID) by assessing how the scaling factor β affects imaging resolution. To track structural integrity, the technique makes use of a surface-mounted array of twelve piezoelectric transducers (PZT). Numerical simulations were performed on an aluminum plate with through-hole defect in order to assess the performance. To replicate realistic Lamb wave interactions, a finite element model was created using CIVA SHM software (version 2023). MATLAB (version 2022) was used to process the obtained signals in order to produce probabilistic defect distribution maps. The RAPID algorithm, optimized with a scaling factor β = 1.05, achieves relative localization accuracy, according to numerical results. The study provides a solid numerical foundation for further experimental validation by confirming that the suggested configuration detects structural damage. Full article

Large language models (LLMs) are increasingly applied across drug discovery, yet their role in analytical method development to support quality control in cell-based potency assays remains insufficiently explored. This study evaluates whether general-purpose LLMs can assess plate homogeneity and detect spatial bias using a half-maximal effective concentration (EC₅₀) mapping approach implemented in a 96-well cell-based reporter gene assay. Four independent plates were generated by two analysts on different days and analyzed using a conventional spreadsheet workflow and three LLMs (Google Gemini, ChatGPT, and Microsoft Copilot Analyst) under identical prompt conditions. All approaches consistently identified a statistically significant row-wise positional effect with no significant column-wise effects, supported by one-way analysis of variance (ANOVA), confidence-interval summaries, and heat-map visualizations of raw signal and Z-scores. The dominant top-to-bottom signal gradient was reproducible across individual plates and the averaged dataset. While all LLMs reproduced standard plate quality control (QC) metrics, they differed primarily in workflow completeness, responsiveness to iterative prompting, and in the extent to which additional spatial diagnostics were proposed. Overall, these results suggest that general-purpose LLMs can reproduce conventional plate-effect analyses and may serve as practical analytical companions when guided by structured prompts and complete datasets. Full article

X-ray computed laminography (CL) is a promising nondestructive testing technique for plate-type objects and is of great importance in 3D imaging. Nevertheless, its scanning geometry results in a lack of projection data along in-plane directions, causing severe inter-slice aliasing and cone-beam artifacts, especially under sparse-view sampling. To address this challenge, a prior image-guided adaptive-weighted relative total variation (PiAwRTV) algorithm is proposed for sparse-view CL. Based on relative total variation (RTV), PiAwRTV leverages structural information from a high-quality prior image to guide image reconstruction and introduces weights that vary with local image gradients. The reconstruction model incorporates 2D PiAwRTV in the horizontal direction to perform edge-preserving smoothing and 1D PiAwRTV in the vertical direction to suppress inter-slice blurring. An alternating minimization strategy is employed to decompose this optimization problem into three subproblems for iterative solution. Experimental results demonstrate that the proposed algorithm reconstructs key structural features while reducing cone-beam artifacts, significantly improving the imaging quality of sparse-view CL. Full article