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关键词： Hybrid ceramic restorative material   Tooth wear   Treatment outcome  

摘要： Purpose: To evaluate the clinical use of CAD/CAM hybrid ceramics in patients with severe tooth wear. Methods: Forty-nine patients with severe tooth wear underwent prosthetic management with 116 hybrid ceramic restorations. The restorations were evaluated at 1 week and at 3, 6, 12, 18, 24, 30, and 36 months after placement. The amount of wear on the restorations, antagonist teeth, and opposite teeth was compared using digital superimposition analysis. A questionnaire was used to evaluate participants' satisfaction with the restorations. Complications were recorded, and survival rates were estimated using Kaplan-Meier analysis. Results: The clinical performance of the restorations was stable for esthetic, functional, and biological parameters up to 3 years, except for greater changes in "surface and margin staining" and "fracture and retention." There was no significant difference in the amount of progressive wear among the restorations, antagonist teeth, and opposite side teeth until 18 months;however, the wear on the restorations increased gradually up to 36 months. Higher scores and identical satisfaction results were obtained for the chewing efficiency and cleanability during the observation period. The most common complications were restoration dislodgement (5.2%) and partial marginal chipping (4.3% which were clinically repaired. Four restorations (3.4%) were extensively fractured and replaced. The estimated survival rate of the hybrid ceramic restorations at 3 years was 88.0%. Conclusions: The clinical use of hybrid ceramic restorations in patients with severe tooth wear improved chewing efficiency and esthetics, provided adequate resistance for load-bearing, and delivered a stable treatment outcome after functional use.

关键词： FAI   Hip pain   Imaging   Arthroscopy  

摘要： Objective: To characterize different hip morphology phenotypes in individuals with femoroacetabular impingement (FAI) syndrome with cam morphology. Materials and Methods: Supine pelvic anterior-posterior radiographs from 119 hips from 119 individuals diagnosed with FAI syndrome with cam morphology from a RCT were analysed. The lateral center edge angle (LCEA Wiberg center edge angle (W-CEA global retroversion, protrusio acetabuli, and femoral neck shaft angle (FNSA) measures were assessed independently by two raters. Criteria from the Lisbon Agreement on FAI imaging were used to characterize different hip morphology phenotypes based on overcoverage, undercoverage, retroversion and femoral orientation. Radiographic measure's reliability was calculated using intraclass correlation coefficients and kappa statistic. Results: Reliability for all measurements ranged from good to almost perfect agreement. Global retroversion of the acetabulum was percent in 39% of the participants. Based on the W-CEA, 9% of participants had acetabular undercoverage and 9% had overcoverage, while the LCEA identified 5% with undercoverage and 17% with overcoverage. Coxa valga was present in 27% of participants, with only one participant having coxa vara. No participants had protrusio acetabuli. Women had a slightly higher prevalence of coxa valga than men. Conclusion: Close to 40% of patients with FAI syndrome with cam morphology also displayed pincer morphology by acetabular retroversion. The prevalence of pincer morphology, based on the W-CEA and LCEA measures was low, indicating that isolated use of these parameters may lead to underdiagnosis of pincer morphology. The prevalence of hip dysplasia determined by the W-CEA and LCEA measures was low, ranging from 2 to 5%.

关键词： Aerostructural shape optimization   CAD model   CFD   Continuous adjoint   Deep Neural Networks   Machine learning  

摘要： This article presents a gradient-based shape optimization workflow for the aerodynamic and aerostructural design of a civil aircraft, by focusing on the use of machine learning models to replace CAD-related blocks in this workflow. To this end, a Deep Neural Network (DNN), in the form of a two-branch $\lambda$-DNN, replaces the CAD-based parameterization of the aircraft wing shape. The $\lambda$-DNN is trained on a set of snapshots (point clouds) of the aircraft surface for various design variable sets. It reconstructs the wing surface, without having access to the corresponding CAD model. During the optimization, inputs to the $\lambda$-DNN are the nodal coordinates of the baseline geometry and the design vector of each new geometry. The derivatives of surface coordinates with respect to the CAD parameters are computed by differentiating the $\lambda$-DNN. A study that demonstrates the superiority of the $\lambda$-DNN over a standard fully connected neural network is presented. The proposed workflow is used in the aerodynamic and aerostructural optimization of the high aspect ratio wing of the DLR-F25 transport aircraft model. The optimizations target minimum drag, subject to lift and pitching moment constraints. For the aerostructural optimization, thousands of structural constraints are also imposed, by embedding the structural sizing into an aeroelastic optimization loop. The obtained reduction in aircraft’s drag results in significant fuel saving for a typical mission, overall proving that the used $\lambda$-DNN can safely replace the necessary CAD model operations.

关键词： Vascular smooth muscle cells   CAD   Pyrimidine biosynthesis   Ribosome biogenesis   Vascular disease  

摘要：

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  CAD is upregulated in Ang-II-treated VSMCs and ligation-induced neointimal lesions.
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  Silencing CAD inhibits Ang-II-induced VSMC proliferation and migration.
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  CAD promotes ICAM-1 and MMP-9 translation via rRNA synthesis.
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  Targeting CAD mitigates neointima formation in occlusive vascular disease.

关键词： Bonding, Dental   CAD-CAM   Materials, Dental   PMMA   Printing, 3D   Strength, Shear  

摘要： Debonding of denture teeth from denture base resins remains a common clinical complication, particularly with the increasing adoption of digital denture fabrication techniques. Although monolithic CAD/CAM dentures eliminate the tooth–base interface, many digital systems rely on bonding prefabricated or printed teeth to milled or printed denture bases, potentially compromising long-term interfacial durability. This in vitro study evaluated shear bond strength (SBS) and failure characteristics across conventional, additive, subtractive, and monolithic CAD/CAM techniques, and further assessed the influence of thermocycling.

关键词： Complementary alternative practices   CAM   Care providers   Mental health   Cultural sensitivity   Person-centred care   Collaboration  

摘要： Despite the growing interest in complementary healthcare, limited data are available about professionals’ perceptions of collaboration with complementary healthcare providers in mental healthcare. This study aims to gain insight into the feasibility of collaboration between general practitioners and practice nurses and complementary healthcare providers in the Amsterdam Southeast region for persons with mental health concerns.

关键词： Coronary artery disease   Machine intelligence   Heterogeneous ensemble   Classification   Screening tool   Prediction  

摘要： Coronary Artery Disease (CAD) continues to be a major health concern for the Indian population, with CAD patients exhibiting slight or asymptomatic clinical manifestations. This work outlines the proposition of a heterogeneous stacked ensemble machine learning framework, intended to act as a clinical decision support and pre-screening tool for cardiology outpatient department (OPD) patients. The framework was trained on a newly constructed angiography-verified dataset, which was sourced from the Jawaharlal Institute of Postgraduate Medical Education and Research (JIPMER), along with four CAD-related public domain datasets: Cleveland, Statlog, Framingham Heart, and Z-Alizadeh Sani.

关键词： Clinical attachment loss   Dental CAD   Finite element method   Parametric modelling   Periodontal ligament   Tooth generation  

摘要： Finite element analysis is widely used in dental research to investigate the biomechanical behaviour of teeth and surrounding tissues. However, creating simulation-ready models of natural teeth from scan data remains labour-intensive, particularly when structures not captured by intraoral scanning, such as roots and pulp cavities, must be modelled separately. In this study, a rule-based parametric modelling approach for generating simulation-ready tooth models from intraoral scan data was developed. Implemented in Grasshopper 3D, this approach creates complete tooth geometries, including roots and pulp cavities, based on scanned crown surfaces and literature-derived parameters. The parametric design enables variation of tooth attributes and was applied to a right maxillary first premolar to investigate the effects of root length, root number, periodontal ligament (PDL) thickness, PDL material model (linear-elastic and hyperelastic), and clinical attachment loss (CAL) on stress distributions in the alveolar bone and PDL using finite element analysis. Greater CAL led to higher compressive stresses in the alveolar bone and PDL. A higher PDL thickness led to higher compressive and tensile stresses in the alveolar bone. Root length mainly influenced stresses at the root apices in the alveolar bone. Shorter roots led to higher compressive stresses in the PDL. The number of roots affected the stress distribution at the furcation and at the level of the root apices. The hyperelastic PDL model produced near-zero tensile stresses in the PDL. The proposed approach eliminates manual CAD model creation and enables exploration of tooth variants for biomechanical analysis.

关键词： Collaborative CAD   Engineering design   Activity   Systematic literature review   Taxonomy  

摘要： Collaborative Computer-Aided Design (CAD) plays an important role in engineering design by enabling simultaneous multi-user work on design tasks. However, the absence of a unified framework to describe collaborative CAD and associated design activities has resulted in inconsistencies in research findings and challenges in synthesising existing knowledge. This paper aims to develop a taxonomy that describes the usage of collaborative CAD and identifies research opportunities based on the current state of the art in collaborative CAD and related design activities. Using Activity Theory, six top-level taxonomy categories are proposed to structure collaborative CAD activities: Subject, Object, Tools, Community, Division of Labor and Rules. Following the PRISMA methodology, a systematic literature review of collaborative CAD activities was conducted and combined with the grounded theory to derive the third- and second-level taxonomy elements and subcategories. Additionally, five research opportunities that highlight emerging challenges, including the integration of AI tools, the need for interdisciplinary collaboration, and the development of standardised evaluation metrics are identified. The findings have practical implications for researchers, software developers, and educators by providing guidance on future research directions and collaborative CAD tool development. By offering a comprehensive taxonomy based on both the theory and existing literature, and research opportunities, this study contributes to the ongoing evolution of collaborative CAD in engineering design, paving the way for more structured research in this field.

关键词： CAD drawing   SDS-MAE   Swin Transformer   Self-distillation  

摘要： In recent years, the integrity of CAD drawings has become increasingly important in engineering design, construction, and manufacturing. However, due to issues such as scanning, format conversion, and multiple iterative revisions, drawings often suffer from missing or distorted primitives, which severely impact downstream applications. To address this problem, this paper proposes a CAD drawing restoration method based on a Self-Distilled Swin-Masked Autoencoder named as SDS-MAE model. The method integrates Swin Transformer with masked autoencoding and introduces a self-distillation structure with a shared encoder and dual decoders: the student decoder focuses on pixel-level reconstruction, while the teacher decoder provides high-level semantic supervision, enabling the network to capture both local structures and long-range dependencies. In addition, a window-based masking strategy is designed to replace conventional random masking, effectively suppressing shortcut learning and enhancing semantic consistency. Experimental results on the FloorPlanCAD dataset demonstrate that SDS-MAE significantly outperforms baseline methods in terms of Dice Similarity Coefficient, Mean Pixel Accuracy, and Mean Intersection over Union. Ablation studies further validate the effectiveness of the self-distillation mechanism and the window-based masking strategy. These results indicate that SDS-MAE provides a robust and precise solution for CAD drawing restoration and offers strong transferability for downstream applications.