Search Results (7,024)

In this study, we used the SERS method for the first time to measure the spectra of four polysaccharide markers of fungal infections: linear β-(1→3)- and β-(1→6)-linked D-glucans, branched mannan of Candida albicans and galactomannan of Aspergillus fumigatus. Aqueous solutions of the polysaccharides were studied in concentrations from 10 pg/mL to 100 μg/mL. The spectra were analyzed using machine learning methods: principal component analysis for data visualization and partial least squares with a ridge regularizer, which were used to construct metrics reflecting the accuracy of substance recognition relative to each other. The spectral changes with varying analyte concentration were observed and stable calibration has been achieved. Subsequent measurements of fungal polysaccharides in the presence of a physiological concentration of human serum albumin (45 mg/mL), used to model blood serum, enabled accurate analyte detection in a clinically relevant concentration range of 10 pg/mL to 100 ng/mL. In this case, the calibration dependence was calculated using the partial least squares method with the L1-regularizer. Blind testing was evaluated using a train-derived applicability-domain criterion based on the disagreement between the model prediction and an independent concentration estimate. Full article

Reliable localization and mapping are critical for intelligent robotic systems operating in dynamic indoor environments, where pedestrians and other moving objects can lead to erroneous feature associations, map contamination, and accumulated trajectory drift. To address these challenges, this study proposes the Boundary-Protected Semantic-Geometric Dynamic-Probability (Boundary-SGDP) framework, an enhanced red–green–blue-depth (RGB-D) visual simultaneous localization and mapping (SLAM) system based on boundary-protected semantic–geometric dynamic-probability estimation. The proposed method combines instance-level semantic priors generated by the YOLO26n-seg detector, a segmentation-oriented model in the You Only Look Once (YOLO) family, and the Segment Anything Model 2 (SAM2) with morphological region decomposition and RGB-D depth-edge detection. Potentially dynamic regions are further divided into dynamic interiors, semantic boundary protection bands, and geometrically informative depth-edge regions. Semantic and geometric cues are integrated to estimate a dynamic score for each feature, which is subsequently propagated to the MapPoint level as a dynamic probability. During pose optimization, these probabilities are used to adaptively adjust the weights of reprojection constraints, thereby reducing the influence of motion-contaminated observations while preserving geometrically valuable features around object boundaries and occlusion regions. Unlike conventional hard semantic masking strategies, Boundary-SGDP provides a soft and adaptive mechanism for handling dynamic observations. Experiments conducted on four dynamic walking sequences from the TUM RGB-D benchmark demonstrate that the proposed method achieves lower absolute and relative trajectory errors than the original ORB-SLAM3 system, while retaining substantially more boundary-related features. The results confirm the effectiveness of semantic–geometric fusion and boundary protection for robust visual localization and mapping in dynamic indoor scenes, and demonstrate the potential of the proposed framework for practical autonomous navigation and intelligent perception applications. Full article

The Standard Model of particle physics has achieved unprecedented success in describing fundamental interactions through the formalism of Quantum Field Theory (QFT), where particles are treated as point-like excitations of underlying fields. In this paper, we introduce an alternative, highly elegant mathematical hypothesis: an effective model that describes particle properties not as fundamental points but as 3D projections of complex topological defects originating in a 4D manifold. By applying the geometry of Kaleidoscopic Iterated Function Systems (KIFS) to a zero-viscosity hydrodynamic framework, we demonstrate a formal isomorphism between standard quantum numbers and 4D fractal attractors. This approach seeks not to replace established phenomenological interactions but rather to offer a complementary geometric lens—a “topological translation”—through which mass generation, spin, and localization can be visualized as emergent properties of higher-dimensional fluid mechanics. Full article

Landscape character change in mountain traditional villages is difficult to assess from a single perspective because roof-material replacement, material–color deviation, and visual exposure vary under complex terrain and settlement configurations. This study develops a multi-source UAV framework for reproducible, spatially explicit assessment of courtyard-scale visual–material integrity (CI), a spatially observable component of landscape character integrity. Using 749 courtyards in nine nationally designated traditional villages in Shangluo, China, the framework integrates UAV orthophotos, 3D mesh models, and point-cloud data to derive material penetration rate (PR), material–color conflict (CC), and standardized visual exposure (VC). PR and CC represent baseline material–color loss, whereas VC is incorporated as an exposure-amplification condition. Formula-structure sensitivity analysis against blinded ratings of 50 sampled courtyards showed that the proposed formulation had the highest rank consistency with expert judgments (Spearman’s ρ = 0.949). The frozen framework also showed a strong association with blinded professional ratings in geographically independent Longnan villages (ρ = 0.912, p < 0.001). XGBoost–SHAP identified courtyard impervious-surface ratio, primary material, and roof form as the leading model-associated predictors of CI variation. The framework supports courtyard-scale CI assessment, priority screening, and repeat-survey reassessment under comparable acquisition conditions. Full article

To compare oculomotor profiles among children wearing orthokeratology, defocus spectacle, and diffusion optics technology lenses in a routine pediatric myopia management setting. This real-world observational study included children who had worn one of the three lens types for approximately one year and had available eye tracking data. Lens type was selected during routine clinical care rather than assigned by the investigators. Oculomotor parameters were compared among lens groups using Kruskal–Wallis tests with false discovery rate correction. One-year spherical equivalent change was examined only in the defocus spectacle and diffusion optics technology groups. Adjusted and exploratory analyses included age, sex, baseline spherical equivalent, baseline axial length, axial elongation, and parental education categories. A total of 134 children were analyzed, including 46 in the orthokeratology group, 49 in the defocus spectacle group, and 39 in the diffusion optics technology group. Significant group differences were observed for microsaccade frequency (FDR adjusted p = 0.00099), peak velocity (FDR adjusted p = 0.00099), latency (FDR adjusted p = 0.00395), fixation disparity (FDR adjusted p = 0.00395), and conjugacy (FDR adjusted p = 0.0274). Saccade frequency and saccade amplitude did not differ significantly. One-year spherical equivalent change did not differ significantly between the defocus spectacle group and the diffusion optics technology group (−0.27 ± 0.43 D vs. −0.34 ± 0.36 D, p = 0.312). No statistically significant correlation was observed between spherical equivalent change and microsaccade frequency in the two spectacle lens groups (Spearman r = −0.231, p = 0.069). Parental education categories showed no consistent association with oculomotor parameters after correction for multiple comparisons. Children wearing different myopia control lenses showed selective differences in oculomotor profiles. Refractive change in the two spectacle lens groups was similar, and the observed oculomotor differences should not be interpreted as direct indicators of myopia control efficacy. Eye tracking may provide complementary information about visual behavior and lens adaptation, but prospective studies with age-balanced designs and longitudinal refractive and axial length outcomes are needed. Full article

Background and Objectives: Reconstruction of extensive acetabular bone defects in revision total hip arthroplasty (THA) remains technically demanding and is associated with a high risk of complications. Custom-made three-dimensional (3D)-printed implants have emerged as a patient-specific option for managing severe bone loss, particularly in Paprosky type 3A and 3B defects. The aim of this multicentre study was to evaluate the early clinical, radiographic, and surgical outcomes following single-stage reconstruction using custom-made 3D-printed acetabular implants. Materials and Methods: This retrospective multicentre study included 62 patients treated between 2021 and 2024 at four orthopaedic departments. All patients had Paprosky type 3A (n = 34) or 3B (n = 28) acetabular defects and underwent reconstruction with custom-made 3D-printed implants. A minimum clinical follow-up of 6 months was required for inclusion. Preoperative computed tomography was used for implant design and surgical planning. Clinical assessment included pain using the Visual Analogue Scale, functional evaluation using the Harris Hip Score and Karnofsky Performance Scale, mobility, range of motion, and use of orthopaedic aids. Radiographic evaluation included plain radiographs and computed tomography. Standardised functional and CT outcome assessments were performed during the first 6 months after surgery, whereas the mean overall follow-up represented subsequent clinical surveillance. Mean follow-up was 27 months. Results: All patients had undergone multiple previous surgical procedures before implantation of the custom-made prosthesis. The interval between primary arthroplasty and implantation of the custom-made implant ranged from 9 to 31 years. During follow-up, improvements in pain, mobility, and functional performance were observed across the entire cohort. The reported functional and CT outcomes refer to the standardised 6-month assessment period. Radiographic evaluation demonstrated satisfactory implant positioning and restoration of hip biomechanics. Progressive radiographic findings suggestive of implant integration were observed during follow-up. The most common complications were postoperative wound-healing disorders and prosthetic dislocation, particularly in patients with more extensive bone defects. Conclusions: Single-stage reconstruction using custom-made 3D-printed implants appears to be a feasible treatment option for patients with Paprosky type 3A and 3B defects, resulting in improvements in pain, mobility, and functional performance. Radiographic assessment suggested stable implant fixation and progressive implant integration during early follow-up. However, postoperative wound-healing disorders, infection, and prosthetic dislocation remain clinically relevant complications, particularly in patients with more extensive bone defects. Further studies with longer follow-up are required to determine long-term implant durability, implant survivorship, and functional outcomes. Full article

Purpose: To compare the clinical and functional outcomes of two successive generations of a trifocal intraocular lens (IOL), the original Liberty 677MY and the optimized Liberty 677CMY. To the best of our knowledge, this is the first head-to-head comparison between two successive generations of any IOL model reported. Methods: This retrospective study included 42 patients (84 eyes) who underwent bilateral phacoemulsification with implantation of either the Liberty 677MY (26 eyes) or the Liberty 677CMY (58 eyes). The primary outcome was postoperative binocular intermediate visual acuity (VA). Secondary outcomes included monocular intermediate VA, monocular and binocular distance and near VA, the proportion of patients or eyes achieving ≤0.1 LogMAR, and defocus curves. Exploratory outcomes included spectacle independence, patient-reported satisfaction (Quality of vision—QoV- and Catquest-9SF), photic phenomena, and intraoperative or postoperative complications. Results: At 3 months, binocular UIVA differed by approximately 0.10 LogMAR in favor of the 677CMY cohort, which was considered clinically significant, although the difference did not reach statistical significance (p = 0.052). Supporting this tendency, monocular UIVA was significantly better with the 677CMY IOL (p = 0.012). Also, a significantly higher percentage of patients and eyes achieved binocular and monocular UIVA ≤ 0.1 LogMAR with the 677CMY IOL (p = 0.025). Defocus curves additionally showed significant between-group differences at intermediate defocus levels (−1.00 and −1.50 D; p < 0.05), favoring the 677CMY cohort. No between-group differences were observed for any distance VA parameter. Binocular near VA and near-vision thresholds were also comparable between groups, although a greater proportion of eyes achieved monocular UNVA ≤ 0.1 LogMAR with the 677CMY IOL (p = 0.016). Spectacle use, overall satisfaction, photic phenomena profile, and postoperative complications were comparable between groups. Conclusions: The optimized Liberty 677CMY exhibited a favorable pattern of intermediate visual performance compared with the 677MY while maintaining comparable distance and near VA and a similar safety profile. These findings suggest potential clinical benefits of the design modifications, although larger prospective studies are warranted to confirm these observations. Full article

Manufacturing companies often register process deviations in operational systems while managing continuous improvement (CI) actions through separate spreadsheets, templates and meeting records. This fragmentation weakens traceability between detection, prioritisation, execution and verification. This paper presents Digital for Continuous Improvement (D4CI), a configurable digital CI system developed from eight literature-derived requirements covering event traceability, detection and escalation rules, transparent assessment, workflow routing, planning, verification and interoperability. The architecture combines data input, relational storage, application logic and user interfaces within a shared information model. Deviations are recorded against process targets or expected conditions, while recurrence criteria consolidate related deviations into occurrences. Impact, Effort and Waste–Cost inputs are stored with the calculated scores and used to recommend an Action for Immediate Improvement, Quick Win or A3 pathway. Planning, execution and verification records remain linked to the originating problem. D4CI was deployed in a metalworking company with established Lean routines and evaluated through implementation records, observation of system use and consolidated feedback. The requirement–function mapping confirmed coverage of the eight design requirements. Deployment evidence indicated centralised problem records, traceable prioritisation criteria, shared visual follow-up of open actions and retrieval of completed CI records. Operational effects require longer observation and comparative performance data. Full article

Background: Enjoyment in sport has emerged as a key psychological factor influencing exercise adherence and cognitive and emotional development. This exploratory study examined pre–post changes in selected cognitive and motor variables over a 15-week observation period and whether average enjoyment during soccer training was associated with cognitive and motor performance indices. Fifty-six players (M = 52; F = 4; age: 9.98 ± 0.70) were observed across 30 soccer training sessions over 15 weeks. Methods: Enjoyment was rated after each session using an emoji-based visual analogue scale, and cognitive performance was assessed before and after the observation period with tablet-based tasks. Results: Pre–post analyses showed significant changes in the Motor Efficiency Test (t55 = 3.15; p = 0.003; Δ = −19.4%; Cohen’s d = 0.42) and FlankTime (W = 1345; p < 0.001; Δ = −8.1%; rank-biserial correlation = 0.68). FlankAcc showed only a nominal, uncorrected distributional change (W = 323; p = 0.015; Δ = 0.0%). Enjoyment was not significantly associated with any of the cognitive or motor performance indices. However, enjoyment scores were clustered toward the upper end of the scale, indicating restricted variability that may have limited the ability to detect associations. Conclusions: These preliminary findings indicate changes in selected cognitive and motor indices over the 15-week observation period, without evidence of direct associations between perceived enjoyment and the cognitive or motor performance indices examined. Full article

This study addresses the design challenges of daily-use smart glasses by proposing a user-centered design and evaluation framework that integrates the KANO model, the Analytic Hierarchy Process (AHP), Fuzzy Comprehensive Evaluation (FCE), and Artificial Intelligence Generated Content (AIGC)-assisted concept generation. User requirements were identified through interviews with 20 participants and user journey map analysis, classified using a KANO questionnaire survey with 309 valid responses, weighted through AHP, and used to guide AI-assisted visual generation based on Low-Rank Adaptation (LoRA) fine-tuning and a ComfyUI workflow. The results show that Functionality and Performance had the highest criterion weight, while multi-scenario mode switching, misoperation recovery, and lightweight structural design were identified as the most critical design attributes. Three design schemes, including a commercial reference product, a conventional 3D-rendered non-AIGC concept, and the proposed AIGC-assisted scheme, were evaluated using FCE. The AIGC-assisted scheme achieved the highest comprehensive score. The study demonstrates that combining quantitative requirement modeling with generative design can support a systematic workflow from user demand identification to design scheme evaluation. The proposed framework provides a practical reference for smart wearable product design and may also inform wearable interface applications in digital cultural heritage and museum interpretation contexts. Full article

This study examines how the vertical spacing of a multi-height 360° camera array affects novel-view synthesis quality in indoor scenes reconstructed with 3D Gaussian splatting (3DGS). Although 3DGS enables high-quality real-time scene representation, its output depends on the geometric arrangement of the input views, which single-lens workflows secure through repeated captures at several heights. A rig of three vertically arranged 360° cameras was evaluated in four indoor spaces differing in ceiling height, structure, and capture path. Three spacing conditions were applied in each space, denoted as Set-L, Set-D, and Set-H. These are ordinal positions within the vertical range each space allows rather than fixed absolute distances, since an identical spacing sits differently in rooms of different scale. The 360° footage was stitched into equirectangular video and reframed into multi-view image sequences, yielding 120 datasets from four spaces × three conditions × ten repeated captures. Novel-view synthesis quality was measured with the PSNR, SSIM, and LPIPS on validation views withheld from training. Because normality and homogeneity of variance were not satisfied, a robust two-way factorial analysis of variance based on 20% trimmed means was used, with robust post hoc comparisons. Spacing, spatial characteristics, and their interaction were significant for all three metrics, so no single spacing was preferable across every space. The wide setting performed best in the low-ceiling repetitive space, the narrow setting in the open space, and the baseline setting in the largest space with variable ceiling height. In one space, comprising stepped, near-symmetric seating, no condition was distinguishable, and dispersion across repeated captures was an order of magnitude larger than elsewhere, indicating that, where a repetitive structure is extensive, the limiting factor is capture stability rather than the choice of spacing. The findings are consistent with a trade-off between vertical viewpoint separation and inter-view overlap, and provide exploratory, space-conditional reference points for indoor 3DGS capture rather than a standardized specification, with relevance to virtual exhibitions, architectural visualization, and digital-twin construction. Full article

Background and Objectives: The rehabilitation of the atrophic posterior maxilla with pterygoid implant presents a significant challenge due to complex regional anatomy and limited visual access. This study aimed to compare the accuracy of a dynamic computer-assisted implant surgery system (dCAIS) for pterygoid implant placement in fully and partially edentulous maxillae using radiographic marker registration (RMR) and markerless tracing registration (MTR), respectively. Materials and Methods: Forty pterygoid implants were retrospectively evaluated in 40 patients, divided into two groups: fully edentulous (n = 20) and partially edentulous (n = 20). Implant placement was performed using a dynamic navigation system (dCAIS), utilizing either bone-anchored mini-screws or tooth-surface tracing as reference points. Accuracy was assessed by superimposing preoperative plans with postoperative cone beam computer tomography (CBCT) scans. Coronal, apical, and angular deviations were measured and analyzed using the Data Science Workbench (version 14). The level of statistical significance was set at α = 0.05 (two-tailed). Results: The mean deviations for fully and partially edentulous maxillae measured 1.24 ± 0.27 mm and 1.40 ± 0.27 mm at the coronal level (p = 0.065), 1.30 ± 0.49 mm and 1.30 ± 0.54 at the apical level (p = 0.995), and 0.72 ± 0.38° and 0.82 ± 0.43° in angular deviation (p = 0.560), respectively. No statistically significant differences were found between the two groups. Notably, mean angular deviation was remarkably low (<1°) in both groups. Conclusions: No statistically significant between-group differences in accuracy were detected in coronal, apical, and angular deviations between the markerless tracing registration method in partially edentulous patients and the bone-anchored radiographic marker registration method in fully edentulous patients. Full article

Accurate forest soil organic carbon (SOC) monitoring is essential for forest soil quality assessment and carbon-sink evaluation. Visible-near-infrared (Vis–NIR) hyperspectral sensing provides rapid and information-rich measurements for SOC prediction, but obtaining sufficiently large labeled soil-spectral datasets remains difficult because field sampling, sample preparation, and reference SOC determination are labor and time intensive. This study developed a latent conditional diffusion-based data augmentation framework for SOC prediction from hyperspectral sensor data. A total of 248 forest red-soil samples from Guangxi, China, were measured using laboratory Vis–NIR reflectance spectroscopy over 350–2500 nm and divided by the Kennard-Stone algorithm into a 174-sample modeling set and a fixed 74-sample validation set. Four generative models, including VAE, GAN, WGAN-GP, and the proposed hyperspectral latent conditional denoising diffusion implicit model (HsDDIM), were evaluated using spectral visualization, t-SNE distributions, maximum mean discrepancy (MMD), Fréchet Inception Distance (FID), and downstream prediction performance. Unlike joint spectral-label generation, HsDDIM treats SOC as an external condition and generates spectra in the latent space under specified SOC conditions; the SOC condition itself is not generated by the diffusion process. Among the compared augmentation strategies, HsDDIM showed the closest distributional agreement with the real spectral samples according to MMD and FID, with values of 0.0806 and 0.5281, respectively. Without augmentation, FD1-SVR achieved the best validation result (R² = 0.83, RMSE = 4.71 g kg⁻¹). After 300% HsDDIM augmentation, 1D-CNN achieved R² = 0.91, RPD = 3.39, and RMSE = 3.40 g kg⁻¹. These results suggest that the SOC-conditioned latent DDIM framework can improve small-sample hyperspectral SOC prediction under the present fixed-validation protocol. Full article

The deployment of real-time three-dimensional (3D) visual perception, continuous spatial sensing, and graphics-intensive multimedia applications on embedded edge devices introduces substantial runtime memory pressure. During execution, these workloads continuously generate small-granularity memory pages, including image buffers, depth maps, rendering caches, intermediate feature tensors, and media buffers. To reduce memory footprint while preserving low processing overhead, this paper proposes a sequence-aware cascaded compression framework for runtime memory pages generated by visual and multimedia workloads. Instead of following the traditional restore-then-recompress path, the proposed framework directly reuses the intermediate sequence representation produced by LZ4. It parses LZ4 sequences into literal and structured stream sequences and applies stream-specific entropy coding using Huffman and Finite State Entropy (FSE) coding. By avoiding full-page restoration and repeated redundancy analysis, the framework preserves lossless reconstruction semantics while reducing compression overhead. Experimental results on real-world runtime memory pages show that the proposed framework reduces compression processing time by 42.10% on average and by up to 52.22%. It also reduces Central Processing Unit (CPU) time by 20.28% on average and peak memory usage by 29.92% on average. Additional validation on a RISC-V edge platform shows that the compression processing time is reduced by up to 64.36%. A 16 MB point-cloud memory sample derived from 3D scan data further shows a 33.16% reduction in compression time. Functional tests on more than 200K mixed-entropy memory pages demonstrate 100% lossless reconstruction and successful detection of corrupted compressed streams. Full article

The increasing complexity of environmental analysis requires new approaches for interactive-scale simulation across indoor and urban spaces. While computational fluid dynamics (CFD) models provide detailed representations of gas dispersion and aerosol transport, they are often computationally intensive for interactive environmental analysis and integration into digital twin platforms. This pilot study presents a GPU-accelerated voxel simulation framework for modeling three-dimensional gas dispersion and aerosol transport using structured voxel representations derived from BIM, LiDAR, GIS, and other 3D built-environment datasets. The framework provides physically informed, CFD-inspired simulation at sub-meter to meter-scale spatial resolutions while maintaining interactive runtime performance suitable for building management, ventilation analysis, environmental monitoring, hazard assessment, and emergency response applications. Transport dynamics are modeled using a discretized advection–diffusion formulation incorporating airflow-driven advection, diffusion, source emissions, and voxel-level sink mechanisms. A key contribution is the development of a voxel-native GPU-parallel computational architecture implemented in Python 3.10.20 using Taichi kernels. Prototype simulations and comparative validation against a benchmark ANSYS Fluent 20.1 simulation demonstrate stable transport behavior, encouraging agreement with the CFD solution, browser-based three-dimensional visualization, and efficient execution on commodity GPU hardware. Experimental scenarios include a voxelized three-story Industry Foundation Classes (IFC) building model comprising approximately 34.5 million active voxels ($582\times 382\times 155$ voxels) and an urban-scale 3D city model spanning approximately $300\times 300\times 150$ m and containing up to 13.9 million active voxels. Simulations containing tens of millions of voxels were completed within minutes on a single consumer-grade GPU, demonstrating the scalability of the framework. These results demonstrate that the proposed framework provides an efficient voxel-based approximation of gas dispersion suitable for interactive environmental analysis and can support future integration with digital twin and AI-assisted environmental simulation systems. Full article