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关键词： artificial intelligence   fractional flow reserve   coronary artery disease   coronary CT angiography   transcatheter aortic valve replacement  

摘要： Objectives:To explore the diagnostic accuracy and robustness of artificial intelligence (AI)-based fully automated CT-derived fractional flow reserve (CT-FFR) in detecting significant coronary artery disease (CAD) in patients with transcatheter aortic valve replacement (TAVR).Methods:This single-center retrospective study included consecutive patients who underwent TAVR between January 2020 and June 2023. All patients received preoperative coronary CT angiography (CCTA) and invasive coronary angiography (ICA). CT-FFR was evaluated with a fully automated AI-based software. The diagnostic performance of CCTA and CT-FFR for the identification of significant CAD was compared using ICA (>= 70% diameter stenosis) as the reference standard. Patients who underwent post-TAVR CCTA within 3 months were used to calculate CT-FFR values. The post-TAVR CT-FFR calculations were compared with pre-TAVR CT-FFR to evaluate the robustness of the AI-based ***:A total of 77 pre-TAVR patients and 164 vessels were included. Significant CAD was identified by ICA in 18 patients (23.4%). In per-patient analysis, the sensitivity, specificity, positive predictive value, negative predictive value, and diagnostic accuracy were 44.4%, 91.5%, 61.5%, 84.4%, and 80.5% for CCTA and 94.4%, 83.1%, 64.0%, 98.0%, and 85.7% for CT-FFR. The area under the receiver operating characteristic curve of CT-FFR was superior to CCTA (0.83 vs. 0.63, P = 0.001). Thirty-five (45.5%) patients underwent CT-FFR calculations before and after TAVR. There was good agreement between pre- and post-TAVR of CT-FFR values (intraclass correlation coefficient 0.85).Conclusions:AI-based fully automated CT-FFR enables to improve the diagnostic performance of CCTA for the detection of significant CAD pre-TAVR and demonstrates robust stability post-TAVR.

关键词： C4 photosynthesis   CO2 concentrating mechanism   Crassulacean acid metabolism   Ottelia alismoides   PEP carboxylase   photosynthesis   Rubisco   single-cell  

摘要： Many plants maximize photosynthesis by using a CO2-concentrating mechanism (CCM). Based on physiology, the freshwater plant Ottelia alismoides has three CCMs: C4 metabolism (NAD-malic enzyme (NAD-ME) subtype) and bicarbonate-use during the day plus crassulacean acid metabolism (CAM) at night and lacks Kranz anatomy. Here, we combined a range of techniques including analysis of enzyme activity and location, transcriptomics, proteomics and 13C labelling in plants grown at low and high concentrations of CO2 to investigate how these CCMs interact and can be integrated without Kranz anatomy. We showed that, unlike canonical NAD-ME subtypes, malate is the first stable compound, produced by a cytosolic malate dehydrogenase, rather than aspartate produced by aspartate aminotransferase. CAM depends on the nocturnal synthesis and transport of malic acid into the vacuole involving a vacuolar-ATPase and a tonoplast dicarboxylate transporter that are highly expressed at night. These results show that C4 and CAM are compatible within a single cell, thanks to temporal regulation and expression of different isoforms of key enzymes and transporters. They contribute to the growing appreciation of the diversity of CCMs and how different processes can co-occur and be coordinated. This study presents a model that could facilitate future plant engineering.

关键词： Design   visual gestalt   experiment-based design   cognitive load   electroencephalography  

摘要： This study investigates the neural correlates of visual perception elicited by fundamental geometric forms in 3D-CAD models, focusing on curved versus edged configurations. Sixty participants were exposed to controlled 3D visual stimuli while EEG recordings captured brainwave activity across alpha, beta, delta, and theta bands. Results revealed significant modulation in the beta band, with edged designs eliciting higher attentional engagement than curved forms (p < 0.001), whereas delta, theta, and alpha bands showed no substantial differences. These findings suggest that geometric properties (sharpness vs continuity) influence cognitive processing, aligning with Gestalt principles of perceptual organization. The study highlights how simple geometric variations can impact mental effort, attention, and perceptual fluency, offering actionable insights for designers seeking to optimize visual composition. By bridging design theory and neurocognitive evidence, this research advances understanding of how basic visual structures shape user cognition and provides a foundation for integrating brain-based metrics into human-centered design.

关键词： digital dentistry   process mining   CAD   CAM   iteration   dental laboratory   custom abutment  

摘要： Digitalization has reshaped dental laboratory processes through digital tools and artefacts supporting clinician-laboratory collaboration;however, repeated iterations still increase coordination effort and extend delivery times. This study examined how the custom abutment process was executed in a dental laboratory and identified where and why iterations occurred during computer-aided design (CAD) modelling, design verification, and manufacturing preparation. Ten completed orders were selected, and their event log information was analyzed using process mining in Disco, complemented by contextual inquiry with domain practitioners. The analysis reconstructed observed execution from order initiation to delivery and derived a reference representation summarizing the most frequently observed ordering of actions. Across the ten orders analyzed, nine exhibited at least one iteration. Iterations were most frequently observed as returns between CAD modelling and design verification and occurred in four orders, while rescanning occurred in two orders due to insufficient or incompatible initial scan information. Contextual inquiry linked repeated action sequences to changes in digital artefacts and communication exchanges, indicating that iterations were associated with incomplete information or differences in interpretation across roles. The findings show that combining process mining with contextual inquiry enables the identification of iterations and clarifies the conditions under which they emerge.

关键词： zirconia   cold plasma   sandblasting   femtosecond laser   thermal aging   resin cement   bond strength  

摘要： This study aimed to evaluate the individual and combined effects of mechanical, plasma-based, and laser-based surface treatments, along with short- and long-term thermal aging, on the surface morphology, surface energy, and resin cement bond strength of CAD/CAM monolithic zirconia. Significant numerical differences were observed among the treatment groups. Surface roughness increased from 0.22 & micro;m (control) to 0.98 & micro;m after sandblasting, 1.12 & micro;m after sandblasting + plasma, and 1.07 & micro;m after laser treatment, while plasma alone produced a moderate increase (0.31 & micro;m). Wettability improved most notably in the plasma group, where the contact angle decreased to 43.27 degrees compared with 67.00 degrees in the control. The highest shear bond strength after 5000 thermal cycles was recorded in the sandblasting + plasma group (14.80 +/- 1.53 MPa), whereas laser treatment demonstrated the best long-term stability, showing no significant decrease after 10,000 cycles (12.48 -> 12.02 MPa). From a practical perspective, these findings indicate that sandblasting followed by plasma treatment provides high initial bond strength, making it suitable for clinical situations requiring strong immediate adhesion of zirconia restorations. Conversely, femtosecond laser treatment offers superior resistance to aging-related degradation, suggesting its potential value in cases where long-term durability is critical, such as high-stress posterior restorations or patients with parafunctional habits.

关键词： fibula free flap   CAD/CAM   mandibular reconstruction   virtual surgical planning   perioperative efficiency   cost analysis   value-based surgery  

摘要： Background: Computer-aided design and manufacturing (CAD/CAM) technology has been increasingly adopted for mandibular and maxillary reconstruction using fibula free flaps. However, its clinical and economic advantages over the conventional freehand technique remain debated. The objective of this study was to compare perioperative outcomes and institutional costs between CAD/CAM-guided and conventional freehand fibula flap reconstructions. Methods: An ambispective observational study was conducted including patients who underwent mandibular or maxillary reconstruction with an osteocutaneous free fibula flap between 2017 and 2024. Reconstructions were performed either using CAD/CAM-guided virtual surgical planning or the conventional freehand technique. Demographic data, perioperative variables, postoperative outcomes, oncologic margin status, transfusion requirements, and total institutional costs were analyzed. Univariate comparisons were performed between groups, and multivariate linear regression models were used to assess the independent association of CAD/CAM guidance with operative time and hospital length of stay. Results: Fifty-one patients were included (25 CAD/CAM-guided and 26 freehand). CAD/CAM-guided reconstruction was associated with a significantly shorter operative time (542.3 +/- 65.8 vs. 604.9 +/- 79.5 min;p = 0.0036) and a shorter overall hospital stay (19.6 +/- 7.2 vs. 30.6 +/- 26.2 days;p = 0.047) in univariate analysis. The need for perioperative blood transfusion was significantly lower in the CAD/CAM group. No significant differences were observed in ICU stay, flap failure, reintervention rate, or postoperative hemoglobin decrease. Although margin status did not differ significantly between groups, a higher proportion of negative margins was observed in the CAD/CAM cohort. In multivariate analysis adjusting for age and perioperative variables, CAD/CAM guidance remained independently associated with reduced operative time, but not with hospital

摘要： Purpose: To evaluate the accuracy of navigation-assisted arthroscopic osteochondroplasty by focusing on the total volume and location of residual deformities, specifically by assessing the total amount and areas of residual deformities and determining whether residual cam deformities result in simulated residual impingement in postoperative computed tomography (CT)-based computer simulations. Methods: We analyzed pre- and postoperative CT data of patients with cam-type or combined-type femoroacetabular impingement who underwent navigation-assisted arthroscopic osteochondroplasty between November 2022 and May 2024. Preoperative planning included a virtual cam resection simulation to improve internal rotation by 10 degrees. Three-dimensional models were created using Mimics and 3-matic software. Residual volume was calculated as a percentage of the planned resection volume, and residual thickness was quantified using a 3-mm threshold. Postoperative CT simulations at 0 degrees adduction and 90 degrees flexion were used to evaluate residual impingement. Results: Of 26 patients (27 hips) who underwent CT-based navigation-assisted arthroscopic osteochondroplasty, 4 hips were excluded due to congenital hip disorders, missing planning data, or magnification inconsistencies, leaving 23 hips in 22 patients for analysis. The residual volume was 1149.3 (634.6-1427.2) mm3, accounting for 57.1 (37.4-67.6)% of the planned resection volume. Areas with a residual thickness >3 mm accounted for 5.4 (1.7-15.1%). Residual regions were predominantly in the distal lateral area (91.3%) and showed a high concordance with the residual impingement area (kappa = 0.72). The planned resection volume was 2113.0 mm(3) (1576.3-3164.5), and the actual resected volume was 1784.3 mm3 (1283.1-2473.9), showing a significant difference (P = .04). Conclusions: Even with navigational assistance, insufficient cam resection and associated residual impingement may persist. The residual volume comprised 57.1%

关键词： Model-based definition   Model-based enterprise   3D model   CAD   Digital thread   Digital manufacturing  

摘要： The digitalization of manufacturing processes has been largely driven by the evolution of Computer-Aided Design (CAD) software over the past half-century, transitioning from 2D, paper-based drawings to 3D, model-centric environments. Central to this transformation is the concept of the digital thread, which facilitates interconnected and seamless information flows across the product lifecycle. Realizing this vision from an operational perspective requires a robust information carrier capable of storing and transmitting essential information through a consistent data structure. Model-Based Definition (MBD) addresses this need by embedding semantic information directly into 3D CAD models, thereby supporting streamlined information exchange and aiming to replace traditional 2D documentation in Model-Based Enterprise (MBE) environments. Given the prominence and transformative potential of MBD, this study presents a systematic literature review covering two decades of fragmented research across diverse manufacturing processes and domains, offering a structured reference to unify prior efforts and support future implementation. The analysis of 132 systematically selected high-quality references from Scopus, Web of Science, leading software vendors, and national and international standards provides a comprehensive and up-to-date synthesis. By consolidating key findings, this review offers a state-of-the-art overview and outlines a roadmap for adoption in modern intelligent manufacturing systems. Particular attention is given to unmapped areas, establishing a foundation for future research and standardization efforts and highlighting MBD's potential role in strengthening the digital thread across sectors, organizational scales, and geographic regions.

关键词： Delays   FeFETs   Nonvolatile memory   Computer architecture   Time-domain analysis   Energy efficiency   Microprocessors   Computational modeling   Switches   In-memory computing   Ferroelectric FET (FeFET)   in-memory computing   time-domain   nonvolatile memory   content addressable memory   multiply-and-accumulate (MAC)  

摘要： Time-domain nonvolatile in-memory computing (TD-nvIMC) offers a promising pathway to reduce data movement and improve energy efficiency by encoding computation in delay rather than voltage or current. This work presents a fully integrated and reconfigurable TD-nvIMC macro, fabricated in 28 nm CMOS, that combines a ferroelectric FET (FeFET)-based content-addressable memory array, a cascaded delay element chain, and a time-to-digital converter. The architecture supports binary multiply-and-accumulate (MAC) operations using XORand AND-based matching, as well as in-memory Boolean logic and arithmetic functions. Sub-nanosecond MAC resolution is achieved through experimentally demonstrated 550 ps delay steps, representing a 2000 & times;improvement over prior FeFET TD-nvIMC work, enabled by multilevel-state calibration with <= 100 ps resolution. Write-disturb resilience is ensured via isolated triple-well bulks. The proposed macro achieves a measured throughput of 222.2 MOPS/cell and energy efficiency of 1887 TOPS/W at 0.85 V, establishing a viable path toward scalable, energy-efficient TD-nvIMC accelerators.

关键词： Grad-CAM   Explainable AI   Breast cancer   Thermography   Feature selection  

摘要： Dynamic Infrared Thermography (DIT) captures a sequence of thermal images after applying a stimulus to analyze vascular responses, offering greater sensitivity than static methods. However, its clinical application remains limited. To address this, Deep Learning (DL) models have gained attention for extracting spatial and temporal patterns automatically. In this study, we propose an explainable deep temporal modeling framework based on recurrent neural networks (RNN, LSTM, GRU) trained on dynamic thermal imaging (DTI) sequences composed of 20-frame series per patient. The architecture integrates a convolutional neural network (CNN) backbone for feature extraction, followed by Grad-CAM for interpretability, allowing the identification of regions contributing most to the classification decision. Feature selection was performed using both statistical methods (based on temporal variance) and wrapper-based optimization techniques, including genetic algorithms (GA), particle swarm optimization (PSO), and simulated annealing (SA). These subsets were used as input to the recurrent classification models. Model evaluation was performed using repeated five-fold cross-validation. All configurations achieved high classification performance, with accuracy ranging from 94% to 97%, sensitivity from 95% to 98%, and specificity from 93% to 96%. Filtering reduced dimensionality while preserving accuracy, whereas wrapper methods further boosted performance, with RNN-GA reaching 97.03% +/- 0.38%. RNN models consistently outperformed LSTM and GRU variants across all subsets. The main strength of this framework lies in the integration of Grad-CAM-based feature attribution, handcrafted temporal descriptors, and deep sequence modeling, thus enhancing explainability for clinical decision-making. However, a key limitation remains the restricted dataset size.