搜索结果：computer-aided

This in vitro pilot study aimed to determine the impact of two different CBCT fields of view, intraoral scan areas and surgical template sizes on the accuracy of static computer-aided implant surgery. A total of 20 implant sites in the anterior maxilla of 20 polyurethane models of partially edentulous arches were divided into four groups based on CBCT field of view and intraoral scan area. The groups used either a small (40 × 40 mm) or medium field of view (50 × 100 mm), a full-maxilla or partial intraoral scan area and a full or partial surgical guide. CBCT and intraoral scan data were registered for implant planning, and surgical templates (either supported by all the remaining teeth or only by teeth 11 and 23) were designed accordingly. The implants were randomly placed through the template in a fully guided manner. Postoperative surface scans were superimposed on the preoperative planning data to evaluate the angular and spatial deviation between the planned and inserted implants. Descriptive statistics were followed by a non-parametric Kruskal-Wallis test to compare the differences between the groups. No significant differences were found when comparing the effect of the size of field of view, intraoral scan area and surgical template on the accuracy of static computer-aided implant surgery (P > 0.05). Preliminary findings indicate that field of view size, intraoral scan area and surgical template dimensions do not significantly affect the accuracy of static computer-aided implant surgery in the partially edentulous anterior maxilla, supporting the application of As Low As Diagnostically Acceptable being Indication-oriented and Patient-specific principles. The authors declare there are no conflicts of interest relating to this study.

Finishing and polishing protocols can markedly influence the surface quality of computer-aided design-computer-aided manufacturing (CAD-CAM) restorative materials; however, the performance of synthetic diamond abrasives across different microstructures remains unclear. The purpose of this in vitro study was to evaluate the effects of various finishing and polishing procedures on the surface roughness, gloss, and contact angle of 4 CAD-CAM restorative materials. Eighty rectangular specimens (15&#xd7;1.5&#xd7;1.5&#x202f;mm) were prepared from a polymer-infiltrated ceramic (Enamic), ceramic-reinforced composite resin (Cerasmart), fiber-reinforced composite resin (Trinia), and feldspathic ceramic (Vita Mark II). After standardized grinding with 600-, 800-, and 1000-grit silicon carbide papers, specimens were assigned to 4 groups (n=5): control (C), rubber-cup polishing (RC), rubber-cup polishing followed by diamond polishing paste (RC+DP), and rubber-cup polishing followed by synthetic diamond abrasives (RC+SD). Surface roughness (Ra), gloss, and contact angle were measured using a contact profilometer, glossmeter, and drop-shape analyzer, respectively. Data were analyzed using 2-way analysis of variance and the Tukey post hoc test (&#x3b1;=.05). Both polishing procedure and material type significantly affected surface roughness, gloss, and contact angle values (P<.001), with significant interactions between the 2 factors for all parameters. Trinia exhibited the highest roughness and lowest gloss, whereas Cerasmart and Enamic demonstrated smoother surfaces after polishing. The RC+SD protocol generally produced lower Ra values and higher gloss and contact angles compared with RC and RC+DP (P<.001). Finishing and polishing protocols substantially influence the surface quality of CAD-CAM restorative materials. Synthetic diamond abrasives generally produce smoother surfaces, higher gloss, and increased hydrophobicity. Polishing protocols incorporating synthetic diamond abrasives may be considered a reliable approach across different CAD-CAM restorative materials.

Rehabilitation of the anterior region requires careful prosthetic planning in cases of immediate implant placement and loading due to the complexity of prosthetically driven restoration in the esthetic zone. The management of interferences during mandibular excursive movements remains critical. A technique is presented for obtaining four-dimensional (4D) virtual patient data, where the 4D component refers to the integration of real-time mandibular movements using an optical jaw motion tracking system. Cone beam computed tomography records, intraoral and face scanning and dynamic jaw motion tracking data, including border movements, which are obtained from JMA Optic System, are superimposed using Exocad software, while data alignment is achieved using the remaining dentition as reference structures. This report describes a step-by-step method to transfer the digital treatment planning simulation into the patient's mouth using a computer-aided design/computer-aided manufacturing&#xa0;(CAD/CAM)-fabricated surgical guide for implant placement and a digitally designed provisional restoration to facilitate clinical reproduction of the planned prosthetic position, supporting a prosthetically driven approach to anterior implant rehabilitation.

Endodontically Treated Teeth (ETT) have challenges in resisting fracture against occlusal forces. This study aimed to assess the fracture resistance (FR) of endodontically treated premolar teeth restored with an innovative self-adhesive bulk-fill resin-based composite (RBC) (Stela , SDI Limited, Australia), a short-fiber-reinforced composite (SFRC) (EverX flow, GC., Tokyo, Japan), a conventional nanohybrid (RBC) (Filtek Z250 XT, 3M ESPE, St. Paul, MN, USA) , and a Computer-Aided Design/Computer-Aided Manufacturing (CAD/CAM) Lithium Disilicate (Emax, Dentsply Sirona, Bensheim, Germany) Endocrown. For the FR test, 44 human extracted maxillary premolars were included in the study. Endodontic treatment was done, and a single operator prepared standardized mesio&#x2011;occlusal&#x2011;distal (MOD) cavities in the teeth and divided into four groups (n=11) according to the restorative material used. Group (F1): ETT restored with Stela resin-based composite, which was inserted into the cavity as a single 5 mm increment. Group (F2): ETT restored with (EverX Flow) composite,which was packed and light-cured for 20 seconds, leaving a 2 mm occlusal layer to be restored with nanohybrid composite (Filtek Z250 XT). Group (F3): ETT restored with Filtek Z250 XT resin-based composite only. Group (F4): ETT restored with (CAD/CAM Cerec MCXL) Lithium Disilicate endocrown, preparations were scanned with the Omnicam, and restorations were designed using CEREC Premium Software (version 4.4). For direct restoration groups the proximal walls were reconstructed by using a tofflemire matrix retainer and band. All restored teeth were subjected to FR testing using a universal testing machine ( Bluehill Lite Software on an Instron&#xae; / Each specimen's failure load was recorded in Newton). Each specimen was individually mounted on the computer-controlled machine equipped with a 5 kN load cell, with the acrylic block secured to the lower fixed head. Statistical analyses were conducted using SPSS 27&#xae;, GraphPad Prism&#xae;, and Microsoft Excel 2016. Data normality was assessed with the Shapiro-Wilk and Kolmogorov-Smirnov tests, which indicated a nonparametric distribution. Comparison between groups revealed a significant difference (P<0.0001), with Group F4 (Endocrown) demonstrating the highest performance (1427.73 &#xb1; 156.96), compared to all direct restoration materials. In contrast, there were no significant differences among the three direct restoration groups despite slight differences in their means. Group F2 (EverX+Z250, mean: 619.87 &#xb1; 186.41) was higher than Group F1 (Stella, mean: 561.75 &#xb1; 173.74) with P = 1.000, and higher than Group F3 (Z250, mean: 452.22 &#xb1; 202.72) with P = 0.471. Group F1 (Stella) exceeded Group F3 (Z250), but this difference was not statistically significant (P = 0.838). While lithium disilicate endocrowns exhibit superior fracture resistance, direct restorative materials may serve as a clinically acceptable alternative for routine applications. Nevertheless, these findings should be interpreted with caution, given the inherent limitations of the in vitro study design.

To compare computer-aided design/computer-aided manufacturing (CAD/CAM) and 3D-printing fabrication techniques of an interim bridge on marginal fit and fracture resistance. Thirty bridges were divided into two groups according to fabrication technique: Group I (n = 15) by CAD/CAM milling and group II (n = 15) by 3D-printing technology. A typodont model, with the first maxillary molar and premolar, and a missing second premolar, was selected for this study. The prepared master model was digitally scanned. The scans were exported to obtain the final virtual 3D master model, which was then used to fabricate the test models and to design and fabricate the provisional dental prosthesis using CAD/CAM technology (milling and printing). The vertical marginal gap was measured. All groups were subjected to thermocycling, and then the marginal gap was remeasured to analyze the influence of thermomechanical aging on the marginal gap. Then the specimens were loaded for the fracture resistance test. The 3D-printed group demonstrated a higher mean marginal gap compared to the milled group before and after thermocycling. While specific combinations of procedure, surface, and tooth type were affected by thermocycling. For the fracture resistance, the milled group demonstrated substantially higher fracture resistance than the 3D-printed group. The CAD/CAM-milled restoration showed better marginal fit and higher fracture resistance than the 3D-printed restoration in temporary prosthesis, but both groups were within clinically acceptable limits. The thermocycling aging influenced the marginal fit of interim fixed bridges. This study demonstrates that the fabrication technique and thermocycling impact the marginal fit and fracture resistance of interim bridges. The milling technique provides superior marginal fit and fracture resistance; therefore, it is recommended that clinicians prioritize the milling technique to enhance longevity and stability of dental prostheses.

Advances in virtual surgical planning (VSP) and computer-aided design/computer-aided manufacturing continue to transform the management of craniomaxillofacial surgical care. There has been a demonstrable shift toward fully personalized surgical care in postablative head and neck reconstruction, orthognathic and temporomandibular joint surgeries, and in surgery for congenital and acquired anomalies. Surgical management of facial trauma exhibits timing and budgetary challenges that have delayed the adoption of VSP into common practice in the area. This review explores the scope, advantages, and evolution of VSP in craniomaxillofacial trauma, with an emphasis on the authors' institutional integration of VSP in management of facial trauma.

Excessive proliferation of white blood cells (WBCs) in the bone marrow leads to a type of blood cancer known as leukemia. This blood cancer impairs the immune response, and timely detection and diagnosis are crucial for human health. Several manual and automated methods for leukemia diagnosis have emerged recently, with the latter still requiring medical practitioners' attention for leukemia treatment. Microscopy is an essential technique in the diagnosis of leukemia, as it allows examination of blood cells in detail and accurate identification of cancerous cells. But artificial intelligence (AI), especially deep learning, has recently been explored to enhance leukemia detection and classification. This study presents an approach to detect leukemia from microscopic images using a convolutional neural network (CNN). The approach starts with image pre-processing, then enhances the training dataset through data augmentation strategies, increasing the number of image samples from 270 to 1268. The U-Net model is used to segment leukemia and normal cells, allowing for efficient feature extraction from high resolution microscopic images. Then, the ASH dataset is classified using a CNN-based architecture, differentiating between the different subtypes of leukemia. Through 10-fold cross-validation, the proposed model achieves an accuracy rate of 99.06% for binary classification and 98.68% for multi-class classification, with a recall of 96.74%, a precision of 96.83%, and an F1-score of 96.77%&#x2009;&#xb1;&#x2009;1.09%. These results suggest that the proposed model performs similarly to other methods. The framework of microscopic imaging and deep learning in our model shows promise as computer-aided diagnosis of leukemia. But more work is needed to train it on a larger and more diverse dataset. This process can be extended to detect other blood disorders through the inclusion of other deep learning models or potentially investigate robust data augmentation techniques in the future.

Carbon nanotube field-effect transistors (CNT FETs) hold great promise for extending Moore's Law, yet their performance is critically limited by excessive off-state leakage, caused by band-to-band tunneling (BTBT) in narrow bandgap CNT channels. In this work, we overcome this long-standing bottleneck by introducing a co-design strategy that integrates a small-diameter HiPco CNT channel with a novel asymmetric gate architecture. This approach strategically reshapes the channel electrostatics to simultaneously suppress the gate-induced drain leakage (GIDL) effect and preserve excellent carrier transport. The efficacy of this strategy is rigorously validated through calibrated technology computer-aided design (TCAD) simulations for both NMOS and PMOS operation, demonstrating an ultralow off-current of 10 fA/&#xb5;m, an on-current of 1.08 mA/&#xb5;m, and a record on-off ratio of 1.1 &#xd7; 1011 for back-gated CNTFETs at the 90 nm node. The design exhibits outstanding scalability: at the scaled 28 nm node with a supply voltage of 0.7 V, the PMOS device achieves 3 mA/&#xb5;m on-current and 6 pA/&#xb5;m off-current, maintaining an on-off ratio of 5 &#xd7; 108. This work establishes a scalable pathway toward femtoampere-level CNT CMOS, addressing the static power challenge in future nano-electronics.

Precise, highly spatial resolution surface pressure measurement is critical for reliable state assessment of unmanned systems, such as the flight safety of unmanned aerial vehicles. Conventionally, the acquisition of such high-resolution data requires dense, expensive sensing arrays or relies on external computational resources. Here, we introduce a flexible electronic skin featuring a sparse sensing network integrated with in-sensor numerical hyperdimensional computing, thereby facilitating super-resolution sensing and in-sensor learning. This innovative approach processes sparse inputs to produce high-resolution pressure field maps on-device, enabling rapid real-time analysis and precise flight state identification. The numerical hyperdimensional computing enhances the efficiency of in-sensor learning, overcoming the limitations of conventional vector symbolic architectures previously confined to classification tasks. Furthermore, the integration of hyperdimensional computing substantially boosts the performance of the flexible sensing skin. Compared to the computer-aided super-resolution method, our approach reduces power consumption from ~40&#xa0;watts to ~0.09&#xa0;milliwatts, memory usage from ~2274 to ~32 kilobytes, and latency from ~115 to ~10&#xa0;milliseconds, respectively. The achieved super-resolution capability reaches an enhancement factor of 5.517. Compared with conventional high-density sensing arrays, our approach reduces the number of interconnects by 91.5% (using a 4 by 4 array). Last, the developed super-resolution skin is applied in unmanned aerial vehicle flight control.

Quantitative assessment of gigapixel whole slide images remains challenging due to morphological diversity and human intervention during slide acquisition and processing. While AI-assisted diagnostics hold promise for improving healthcare accessibility and quality, practical application is hindered by difficulties in faithfully representing histomorphological heterogeneity and scaling AI models for deployment. Prevailing approaches predominantly rely on weakly supervised algorithms based on homogeneous graph, which typically decouple diagnostic models from the underlying hardware, resulting in lack of an efficient, closed-loop, end-to-end system. Here, we propose a portable integrated system: the Intelligent Pathology Whole-Slide Analyzer (iPathWS analyzer), which embeds a Spectral Heterogeneity Engine Network and interfaces directly with a slide scanner to form a unified platform for WSI inference. The system seamlessly overlays explainable heatmaps onto slides, enabling intuitive AI integration into routine clinical workflows in a closed-loop manner. We validate the effectiveness of the iPathWS analyzer across four distinct classification tasks spanned by three independent pathology datasets, including multi-center crossover studies. Furthermore, the model produces highly detailed and interpretable heatmaps capable of detecting tiny lesions with the size of 188.5&#xd7; 280.2&#x3bc;m&#xb2;, which are often imperceptible by human observers. Overall, the iPathWS Analyzer demonstrates consistent and substantial improvements in diagnostic performance, offering a scalable and robust platform for next-generation computer-aided pathology.

Toileting is a fundamental activity of daily living that presents significant challenges in bed-based care, particularly for individuals with mobility limitations and neurodevelopmental or intellectual disabilities. Despite its importance, assistive toileting has received limited attention at early design and feasibility stages. This study evaluates the technical feasibility of a bed-deployable, plumbing-independent automated toileting concept using simulation-based methods and structured expert appraisal. A mixed-methods approach was employed, including computer-aided design (CAD), quasistatic finite element analysis (FEA), controller timing simulations, and qualitative flow coverage assessments. An interdisciplinary expert panel (n = 15) provided structured feedback on system architecture and technical plausibility. Simulation results indicate that the proposed system architecture can execute the intended operational sequence and integrate key subsystems within a controlled virtual environment. Expert feedback identified design considerations and areas requiring further investigation but does not represent real-world performance or validated outcomes. This study is positioned as a preliminary feasibility investigation and provides a structured, standards-aware framework for early-stage evaluation of assistive toileting systems. Findings are based on simulation and expert perception and do not reflect clinical effectiveness or user outcomes. Future work should include physical prototyping, standardized bench testing, and empirical validation with end users to assess safety, usability, and real-world performance. The Auto Potty prototype provides individuals with autism and physical disabilities greater autonomy and emotional comfort, which can reduce caregiver dependency.Rehabilitation professionals can integrate this technology into home-based and clinical care plans to improve hygiene management and dignity preservation.Simulation-based evaluation offers a safe and cost-effective method for testing assistive devices before large-scale clinical trials.The device&#x2019;s portable and smart features make it suitable for community-based rehabilitation, especially for individuals with limited mobility or access to specialised care.

Maltogenic amylase (AmyM) hydrolyzes starch to produce maltodextrin, thereby retarding bread staling via starch retrogradation inhibition. However, poor thermal stability limits its industrial application in high-temperature baking. In this study, we employed a computer-aided dual strategy to enhance the thermostability of AmyM-M2 (D261G/T288P) from Bacillus stearothermophilus. Flexible regions were identified via AlphaFold3 and Gromacs molecular dynamics (MD) simulations. By integrating MD-guided saturation and virtual screening-assisted mutagenesis, we obtained two highly stable mutants: M2-A138P and M2-F188I. At 70 &#xb0;C, their half-lives extended dramatically from 3 h (parent) to 18 and 36 h, respectively. Baking experiments demonstrated both mutants exhibited superior performance in maintaining bread elasticity and delaying hardening compared to the parent enzyme. MD analysis revealed these mutations improve overall structural stability by restricting thermal fluctuations via enhanced local hydrophobic interactions and conformational rigidity. This rational design strategy provides a feasible scheme for engineering the thermostability of industrial enzymes.