Search Results (79)

The target price for naval equipment orders is driven by the coupling of multidimensional technical and economic factors, exhibiting typical characteristics such as high dimensionality, strong nonlinearity, multicollinearity, and small-sample fluctuations. Traditional cost estimation methods struggle to achieve high-precision fitting and interpretable decision support. To address these issues, this paper constructs an integrated prediction model that combines Boruta–Lasso two-stage feature selection, grid search-optimized CatBoost, and SHAP interpretability analysis. First, the Boruta algorithm is used for rough screening of feature significance, then Lasso regression is applied for sparse fine screening, effectively eliminating redundant features and significantly mitigating multicollinearity; grid search and five-fold repeated cross-validation are employed to optimize CatBoost hyperparameters, while 10 repeated experiments with random seeds are conducted to verify model generalization robustness. SHAP is used to quantify the marginal contribution of features, revealing nonlinear associations and statistical response transition points between core features and price. This study is based on 33 publicly available real data from main combat vessels, from which 198 modeling samples were generated through interpolation-based small-sample data augmentation. The interpolated samples were only used for data augmentation and were not considered independent empirical samples. All core conclusions were validated on the 33 original real samples, and there are no missing values in the dataset. Experimental results show that the proposed model achieved the best individual results on the test set, with a coefficient of determination of R² = 0.8949, root mean square error RMSE = 0.0554, and mean absolute error MAE = 0.0476. Across 10 repeated robustness experiments, the average results were R² = 0.8828, RMSE = 0.0586, and MAE = 0.0529, with overall performance better than comparison models such as XGBoost, random forest, and standard CatBoost. Ablation experiments validated the effectiveness of the two-stage Boruta–Lasso selection strategy in improving model accuracy and stability. SHAP attribution analysis shows that full-load displacement, number of vertical missile launch cells, number of phased array radars, and combat capability are core features highly correlated with price, all showing significant nonlinear positive correlations and clear statistical response transition points. The dataset in this study has no missing values, is entirely constructed based on publicly traceable data, and does not include confidential information such as internal shipyard costs. The findings reflect statistical associations rather than causal effects. However, the sample size and ship-type coverage are limited, so the model’s applicability is somewhat constrained, and its generalization ability needs to be further verified on larger-scale, multi-ship-type independent datasets. This model combines high prediction accuracy, strong robustness, and good interpretability, providing reliable technical support for ship equipment procurement pricing demonstration, full lifecycle cost management, and scientific procurement decision-making. Full article

Additive manufacturing (AM) enables customized, efficient restorative workflows, though the accuracy of 3D-printed restorations may be compromised by polymerization, sintering shrinkage, and post-processing. This study evaluated the geometric accuracy of 3D-printed partial restorations compared with the computer-aided design (CAD) reference. The null hypothesis stated that no significant differences would be found between Varseo Smile Crown^plus (by BEGO, Italy) and IRIXMax (by DWS System, Italy) materials, which are printed and cured with different technologies. A model was prepared for an overlay and designed with a 1.5 mm uniform thickness. Restorations were produced in two groups with two different printing processes: DLP (digital light processing)-printed Varseo Smile Crown^plus and SLA (stereolithography)-printed IRIXMax. Six samples per group were printed at 90° orientation and scanned. Meshes were aligned to the master geometry via pre-alignment and ICP (Iterative Closest Point) registration. Deviations were quantified in CloudCompare using mean, standard deviation (SD), and 90th percentile values. IRIXMax showed the lowest deviations from the ideal geometry, while Varseo Smile Crown^plus exhibited greater variability. Pairwise comparisons found IRIXMax significantly more accurate than Varseo Smile Crown^plus. Color maps confirmed material-specific deviation patterns. IRIXMax provided the highest geometric accuracy. Material-specific calibration is essential for reliable 3D-printed definitive restorations. Full article

Microleakage at the implant–abutment interface represents a potential pathway for bacterial penetration and may contribute to peri-implant inflammation, marginal bone loss, and mechanical complications such as screw loosening. The increasing clinical use of compatible prosthetic abutments as cost-effective alternatives to original components has raised concerns regarding their fit, sealing capacity, and mechanical stability at this interface. The aim of this in vitro study was to evaluate differences in sealing capacity and torque loss between original and non-original abutments in a mixed internal connection implant system and to investigate the applicability of a novel quantitative approach for assessing microleakage based on a hydraulic conductance perfusion system. Nine abutments, including four multi-unit and five screw-retained cementable abutments, were connected to Straumann Bone Level implants at two tightening torques (5 N·cm and 35 N·cm). Microleakage was quantified by measuring fluid transport across the implant–abutment interface using the perfusion system, and removal torque values were recorded after testing. Non-original abutments exhibited significantly greater microleakage than original abutments at both torque levels. Microleakage increased significantly when the installation torque was reduced to 5 N·cm. At the manufacturer-recommended torque, screw-retained cementable abutments demonstrated higher microleakage than multi-unit abutments. Non-original abutments also showed significantly greater torque loss. These findings suggest that original abutments provide improved sealing capacity and mechanical stability at the implant–abutment interface, while the hydraulic conductance perfusion system represents a promising quantitative tool for investigating microleakage. Full article

Spent coffee grounds (SCGs) are abundant byproducts generated during coffee processing that are unsuitable for storage and subsequent value-added utilization owing to their high moisture content and water activity (a_w). This study investigated the effects of different infrared power levels (800, 900, and 1000 W) on drying kinetics, product quality, and energy efficiency to determine the preferred drying parameters for SCGs. The initial moisture content and a_w of SCGs were 63.56% (wet basis) and 0.95, respectively. To enhance mechanistic understanding, the drying data were fitted to four mathematical models, with the Midilli and Page models providing the best fit (R² > 0.99). Drying experiments were conducted under a sample thickness of 0.7 cm and a loading of 500 g, with a final moisture content of <10% as the drying endpoint. The results showed that as infrared power increased, drying time decreased from 30 to 24 min and the drying rate significantly increased from 10.32 to 12.77 g H₂O/min (p < 0.05). The drying process was mainly characterized by a falling-rate period, with the effective moisture diffusivity ranging from 0.97 to 1.15 × 10⁻⁸ m²/s and increasing with rising power, indicating that internal moisture diffusion was the dominant drying mechanism. The final a_w of each treatment group was ≤0.60, indicating good storage stability. Color analysis showed that the color differences in treatments at higher power levels (900 W and 1000 W) were significantly lower than those at lower ones (p < 0.05). While the specific energy consumption (SEC) showed a marginal decrease from 5.80 to 5.68 kWh/kg at higher power, a comprehensive evaluation of drying efficiency, quality characteristics, and energy consumption indicated that 1000 W was the preferred infrared drying power under the conditions employed in this study. These results confirm that infrared drying is an efficient stabilization method with strong potential for rapid stabilization of food processing byproducts. Full article

(1) Purpose: To compare the fabrication accuracy, internal fit, and marginal adaptation of three-unit definitive resin fixed dental prostheses (FDPs) produced by subtractive milling and additive manufacturing. (2) Materials and Methods: A typodont mandible was prepared for a three-unit FDP, with full crown preparations on teeth mandibular left canine and mandibular left second premolar featuring 1 mm chamfer finish lines. The FDP was designed with a 16 mm² connector and a 100 µm cement gap. Two milling materials (Ambarino High-Class, IPS e.max CAD) and two experimental 3D printing hybrid resins (3D-1, 3D-2) were used. All restorations were scanned using an intraoral scanner and compared to the original STL using reverse engineering software for surface trueness and deviation analysis. The internal fit was evaluated using the triple-scan method, while marginal fit was assessed via micro-CT imaging. Statistical analysis was conducted using one-way ANOVA and Kruskal–Wallis tests (α = 0.05). (3) Results: Milled groups demonstrated a lower prevalence of external, marginal, and overall surface deviations (p < 0.001), while 3D-1 exhibited comparable deviations within the internal region with M-E (p = 0.067). Milled groups had average gap values that were similar to 3D-1 (p > 0.08), but significantly lower than 3D-2 (p < 0.002). In marginal adaptation evaluated by micro-CT, the M-A and M-E groups provided significantly lower gaps, while the 3D-1 and 3D-2 groups exhibited wider marginal and axial gaps. (4) Conclusions: These results indicate that while milling remains a more reliable manufacturing method for achieving external and marginal precision, position 3D-1 is a compelling, chairside alternative to milling. Full article

Background and Objectives: Advances in digital dentistry, particularly CAD-CAM, have improved the efficiency and precision of crown design and fabrication. Recently, artificial intelligence (AI)-integrated CAD-CAM systems have enabled automated tooth morphology generation, margin detection, and occlusal analysis, enhancing consistency and accuracy. This systematic review evaluates the accuracy of AI-assisted crown design compared with conventional and CAD-CAM workflows. Materials and Methods: A systematic search was conducted across PubMed/MEDLINE, Scopus, Web of Science, Cochrane, and LILACS for studies published between January 2010 and December 2025 that assessed the marginal fit, internal adaptation, and occlusal contact accuracy of single crowns. Screening, full-text assessment, and data extraction followed Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Methodological quality and risk of bias were evaluated using the Modified CONSORT checklist for in vitro studies and the Joanna Briggs Institute tools for clinical studies. Results: Of 887 records identified, 12 studies met the inclusion criteria. Nine studies showed a moderate risk of bias, two moderate-to-high, and one low-to-moderate. AI-assisted crown design demonstrated clinically acceptable internal fit and marginal adaptation, comparable or superior to CAD-CAM systems. Occlusal contact accuracy was generally comparable to CAD-CAM and technician-designed crowns, though variability was observed across AI models. Conclusions: AI-assisted crown design provides a reliable fit and marginal adaptation, with occlusal accuracy approaching conventional CAD-CAM and technician workflows. While not a replacement for clinical expertise, AI serves as a valuable adjunct, enhancing reproducibility, precision, and overall quality in restorative dentistry. Further standardized clinical studies are needed to validate long-term outcomes and optimize occlusal performance. Full article

Hami melon is a widely consumed fruit worldwide, and its sweetness, characterized by soluble solids content (SSC), is a key indicator of fruit quality and commercial value. In this study, hyperspectral imaging combined with machine learning was systematically applied to develop non-destructive models for SSC prediction in multiple Hami melon varieties. Four varieties, namely ‘Xizhoumi’, ‘Jiashigua’, ‘Jinfenghuang’, and ‘Heimeimao’, with a total of 160 samples, were used as the test materials. Hyperspectral images were collected, and SSC was measured at two pulp positions for each sample (denoted as BRIX1 and BRIX2). After applying preprocessing methods including Standard Normal Variate (SNV) transformation and Savitzky–Golay smoothing, five machine learning models were compared: XGBoost, LightGBM, Random Forest (RF), Support Vector Regression (SVR), and Partial Least Squares Regression (PLSR). Furthermore, an ensemble modeling strategy based on residual predictive deviation (RPD) weighting from the validation set was proposed. The results show that all models could effectively predict SSC, with the ensemble model achieving the best performance: the coefficients of determination (R²) for BRIX1 and BRIX2 were 0.848 and 0.833, the root mean square errors (RMSEs) were 0.992 and 0.899, the Mean Absolute Percentage Errors (MAPEs) were 6.90% and 6.76%, and the RPD values were 2.57 and 2.45, respectively, demonstrating its strong quantitative analysis capability. This performance benefited from three core optimized designs adopted in this study: (1) a multi-cultivar experimental design that verified the stable correlation between sugar-related spectral features and internal SSC across different Hami melon varieties; (2) an RPD-weighted ensemble modeling strategy that balanced the fitting ability and generalization performance of linear and nonlinear models; and (3) a dual-position SSC measurement design that validated the robustness of the model for SSC prediction at different spatial positions in the pulp. This study confirms the feasibility of hyperspectral imaging technology for non-destructive SSC detection in the four tested Hami melon varieties under laboratory-controlled conditions. The proposed ensemble model achieved a marginal but stable improvement in overall prediction accuracy across the tested varieties compared with the optimal single model, providing a preliminary methodological reference and data support for the development of cross-cultivar non-destructive SSC detection models for Hami melon. Full article

Muscular fitness is a key component of health and athletic performance, and isometric strength is a widely used indicator. This study reports an agreement-based validation of the Isometric Strength Measurement Device (ISOMETRO) for upper-limb isometric tension measurements under controlled laboratory conditions. Twenty-one healthy young amateur rock climbers (11 men and 10 women) performed four upper-limb tensile tests (shoulder adduction at 90°, shoulder adduction at 60°, shoulder extension at 90°, and elbow extension at 90°). Agreement with an independent criterion device was evaluated using a force plate, while a series-connected load cell was used as an internal consistency check of the measurement chain. Linear mixed-effects models showed that ISOMETRO strongly predicted force plate values (β = 0.999, SE = 0.002, p < 0.001), with a marginal R² > 0.99. Bland–Altman analysis indicated negligible bias (−0.08 N) and narrow limits of agreement (−4.97 to 4.81 N), and concordance was excellent (CCC ≥ 0.996). The series-connected load cell comparison also showed near-unity agreement (β = 0.998, SE = 0.003, p < 0.001), supporting internal measurement chain integrity. These findings support excellent agreement between ISOMETRO and force plate measurements for upper-limb tensile isometric testing along the vertical axis in young amateur rock climbers under controlled laboratory conditions. However, given the specific sample characteristics and the strictly vertical laboratory configuration, these results should not be generalized to other populations, joint angles, force directions, or non-laboratory environments without further validation. Further studies are needed to confirm performance in more diverse contexts and to establish reliability for repeated-measurement applications. Full article

Background/Objectives: This study compared the marginal fit of CAD/CAM zirconia copings based on digital and conventional impression techniques by using a new method of tooth section examination. Methods: Twenty premolars were prepared for an all-ceramic full crown. Ten conventional impressions using the polyether Impregum and ten digital impressions using the cara TRIOS intraoral scanner were used to fabricate zirconia copings. Slices were prepared by cutting each tooth five times. The marginal fit was microscopically analyzed using seven defined distances at 20 measuring points per tooth. The statistical analyses were carried out by using the Mann–Whitney test and the Kruskal–Wallis test (α = 0.05). Results: The median values for the copings based on the conventional (c) and digital (d) impressions showed significant differences for the internal gap (c: 56 μm (IQR = 22); d: 30 μm (IQR = 13); p < 0.001), horizontal marginal discrepancy (c: 64 μm (IQR = 59); d: 84 μm (IQR = 41); p < 0.001), absolute marginal discrepancy (c: 81 μm (IQR = 40); d: 98 μm (IQR = 50); p < 0.001) and the overextension (c: 63 μm (IQR = 48); d: 89 μm (IQR = 50); p < 0.001). All copings based on digital impressions were overextended. Underextensions only occurred with the conventional impression method with a median value of 40 μm (IQR = 64). For the marginal gap (c: 29 μm (IQR = 27); d: 31 μm (IQR = 22); p = 0.477) and the vertical marginal discrepancy (c: 34 μm (IQR = 32); d: 35 μm (IQR = 40); p = 0.944) no significant differences could be found. Conclusions: Both impression methods are suitable for the fabrication of ceramic copings. The microscopic examination of tooth sections seems to be a suitable in vitro method for the evaluation of the marginal fit of ceramic copings. Full article

(1) Objective: To compare the marginal and internal fit of 3D-printed and milled three-unit fixed dental prostheses (FDPs) made from tetragonal zirconia polycrystal (3Y-TZP). (2) Methods: Three-unit FDPs were designed for a typodont maxillary model with crown preparation for the second premolar and second molar. Nominal cement gap widths were set to 30 µm at the margins and 80 µm internally. A total of 40 FDPs (n = 10/group) differing in wall thickness (w = 0.6/1.0 mm) and support structures (with/without a stiffening frame) were fabricated from 3Y-TZP by 3D printing. A total of 10 milled FDPs with w = 0.6 mm served as a control group. After adhesive cementation on the respective replicated maxillary models, FDPs were sectioned and the cement gap dimension was assessed with a digital microscope. The marginal and internal fit found for the different test groups were compared using non-parametric tests. (3) Results: The best marginal fit—qualified by median/maximum marginal gap width—was given for milled FDPs (79/127 µm vertical; 85/171 µm tangential), whereas the marginal fit of 3D-printed FDPs with w = 0.6 mm and regular support structures was the worst (144/284 µm vertical; 107/198 µm tangential). Use of an additional support frame improved the marginal fit of 3D-printed FDPs, in particular FDPs with w = 0.6 mm (108/197 µm vertical; 87/161 µm tangential). (4) Conclusions: 3D-printed zirconia FDPs showed conditionally comparable marginal and internal fit as their milled counterparts, but with slightly higher scattering. When fabricating thinner 3D-printed FDPs, additional support structures are mandatory to achieve clinically well-fitting restorations. Full article

Objectives: To compare artificial intelligence (AI) crown design with expert or non-AI computer-aided (CAD) design for single-unit tooth and implant-supported crowns across efficiency, marginal and internal fit, morphology and occlusion, and mechanical performance. Materials and Methods: This systematic review was conducted and reported in accordance with PRISMA 2020. PubMed MEDLINE, Scopus, Web of Science, IEEE Xplore, and Dentistry and Oral Sciences Source were searched from 2016 to 2025 with citation chasing. Eligible studies directly contrasted artificial intelligence-generated or artificial intelligence-assisted crown designs with human design in clinical, ex vivo, or in silico settings. Primary outcomes were design time, marginal and internal fit, morphology and occlusion, and mechanical performance. Risk of bias was assessed with ROBINS-I for non-randomized clinical studies, QUIN for bench studies, and PROBAST + AI for computational investigations, with TRIPOD + AI items mapped descriptively. Given heterogeneity in settings and endpoints, a narrative synthesis was used. Results: A total of 14 studies met inclusion criteria, including a clinical patient study, multiple ex vivo experiments, and in silico evaluations. Artificial intelligence design reduced design time by between 40% and 90% relative to expert computer-aided design or manual workflows. Marginal and internal fit for artificial intelligence and human designs were statistically equivalent in multiple comparisons. Mechanical performance matched technician designs in load-to-fracture testing, and modeling indicated stress distributions similar to natural teeth. Overall risk of bias was judged as some concerns across tiers. Conclusions: Artificial intelligence crown design delivers efficiency gains while showing short-term technical comparability across fit, morphology, occlusion, and strength for single-unit crowns in predominantly bench and in silico evidence, with limited patient-level feasibility data. Prospective clinical trials with standardized, preregistered endpoints are needed to confirm durability, generalizability, and patient-relevant outcomes, and to establish whether short-term technical advantages translate into clinical benefit. Full article

This study explains repeat purchase intentions on e-commerce platforms as a problem of fit between what the interface signals (Customer Service Orientation, CSO) and what the system delivers (Internal Service Quality, ISQ). Using survey data from Chinese platform users (N = 605), second-order polynomial models with response-surface analysis (RSA) show that repurchase intention rises when CSO and ISQ increase together, exhibits diminishing returns at high joint levels, and declines as the two diverge. A structural equation model (SEM) provides cross-sectional evidence consistent with mediation via pride in membership; when CSO and ISQ are modeled jointly with pride, CSO shows the larger direct association with repurchase. We also find that trust and security awareness initiatives act as a structural assurance that flattens the CSO–ISQ surface, attenuating both slopes and curvatures. Taken together, the results advance a fit-based account of digital service in which outcomes depend on the alignment of interface signals with executional capability and operate through identity-based pride, with platform-level assurances bounding marginal returns. Managerially, the findings imply prioritizing the closure of CSO–ISQ gaps and reducing execution variance before pursuing further single-dimension upgrades. Full article

Aim: This in vitro study aimed to evaluate the marginal and internal fit of three monolithic CAD/CAM zirconia ceramics with different Y-TZP contents, prepared with chamfer and rounded shoulder finish lines. Methods. Sixty monolithic zirconia crowns were fabricated and divided into three groups (n = 20) based on their yttria content: (1) multilayer zirconia consisting of a dentin layer of 3 mol% yttria-stabilized tetragonal zirconia polycrystal (3Y-TZP) and an incisal layer of 5 mol% partially stabilized zirconia (5Y-PSZ), (2) shade-gradient zirconia fully composed of 3Y-TZP, and (3) shade-gradient zirconia containing 4 mol% partially stabilized zirconia (4Y-PSZ). Each group was further divided into two finish line configurations (chamfer and rounded shoulder). Marginal and internal gaps were measured using the silicone replica technique under a stereomicroscope by a single operator. Data were analyzed using three-way ANOVA followed by Tukey’s post hoc test (α = 0.05). Marginal and internal gaps were assessed using the silicone replica technique under a stereomicroscope by a single operator. Statistical analysis was performed with three-way ANOVA and Tukey’s post hoc test (p < 0.05). Results: The occlusal region exhibited the largest gap values, while the axial region showed the smallest across all groups. Mean marginal and internal gaps were 33.79 µm for chamfer and 43.37 µm for rounded shoulder finish lines. Zirconia with higher Y-TZP content demonstrated significantly greater gap values than those with lower percentages (p < 0.05). Significant interactions were found among finish line design, material type, and measurement region (p < 0.05), with rounded shoulder margins showing larger gaps (p = 0.001). Conclusions: Y-TZP content significantly affects marginal and internal adaptation, with higher percentages associated with increased gap values. Both finish line types produced clinically acceptable fits, although chamfer margins provided superior adaptation. Full article

Retrofitting existing buildings is regarded as a main driver of decarbonization, yet retrofitting activities are lagging behind their ambitious goals. This study explores 86 German construction practitioners’ perceptions of organizational, policy, and social challenges to sustainable retrofitting and how those perceptions relate to age, attitude, and their interaction. The primary analyses used OLS moderation models with HC3-robust standard errors and ordered-logit models, which served as robustness checks. Across outcomes, more pro-environment attitudes were associated with fewer perceived challenges, and older practitioners (41–56+) reported higher barrier perception. The attitude × age interaction results indicate that the protective link of attitude was weaker among older respondents, which was significant for policy and social challenges but only marginal for organizational challenges. The model fit was reasonable, at an Adj. R² between ≈0.56 and 0.72 with acceptable diagnostics. Our results suggest that even motivated professionals can feel constrained, especially among older, senior staff. Practical implications include early tenant engagement to enhance acceptance and foster internal organizational sustainability capacities. Policy instruments such as adult education programmes need to be leveraged to enhance sustainable construction capabilities and reinforce attitudes and behaviours toward sustainable retrofitting. More salient policy communications and guidance can contribute to increasing sustainability orientation and reducing perceived trade-offs with economic goals. Full article