Search Results (978)

Dental implant components are typically fabricated using subtractive manufacturing, often involving metal materials that can be costly, inefficient, and time-consuming. This study explores the use of additive manufacturing (AM) with zirconia for dental implant overdenture bars, focusing on mechanical performance, stress distribution, and fit. Solid and lattice-structured bars were designed in Fusion 360 and produced using LithaCon 210 3Y-TZP zirconia (Lithoz GmbH, Vienna, Austria) on a CeraFab 8500 printer. Post-processing included cleaning, debinding, and sintering. A 3D-printed denture was also fabricated to evaluate fit. Thermography and optical imaging were used to assess adaptation. Custom fixtures were developed for flexural testing, and fracture loads were recorded to calculate stress distribution using finite element analysis (ANSYS R2025). The FEA model assumed isotropic, homogeneous, linear-elastic material behavior. Bars were torqued to 15 Ncm on implant analogs. The average fracture loads were 1.2240 kN (solid, n = 12) and 1.1132 kN (lattice, n = 5), with corresponding stress values of 147 MPa and 143 MPa, respectively. No statistically significant difference was observed (p = 0.578; α = 0.05). The fracture occurred near high-stress regions at fixture support points. All bars demonstrated a clinically acceptable fit on the model; however, further validation and clinical evaluation are still needed. Additively manufactured zirconia bars, including lattice structures, show promise as alternatives to conventional superstructures, potentially offering reduced material use and faster production without compromising mechanical performance. Full article

The integration of AI into online platforms is reshaping consumer experience and behavior. While existing research has largely focused on the role of AI in search services and experience services, few studies have examined the role of AI in the context of credence services. This study fills this gap by investigating an AI-powered preview tool in the context of online medical aesthetic platforms. Specifically, this study investigates how the AI Magic Mirror influences consumer purchase intentions in medical aesthetic services. Using secondary data analysis and two experimental studies, we examine the main effects, as well as mediation and moderation effects. The findings consistently demonstrate that the AI Magic Mirror significantly increases consumer purchase intentions. This relationship is positively mediated by perceived value and negatively mediated by perceived risk. In addition, the main effect is stronger for procedures with higher fit uncertainty and is more pronounced for those with lower popularity. These results provide theoretical insights into AI application in credence service contexts and offer practical implications for the design of AI-enhanced online service platforms. Full article

This longitudinal study examines how perceived brand globalness (PBG) influenced sustainable purchase intentions (SPI) between 2021 and 2024, incorporating factors such as perceived brand quality (PBQ), perceived brand prestige (PBP), brand–cause fit (BCF), and the moderating effect of consumer ethnocentrism (CE). Using survey responses from 415 participants, the study employed partial least squares structural equation modeling (PLS-SEM) via SmartPLS4. The findings reveal that CE emerged as significant in 2024, while PBP’s impact on SPI weakened—suggesting a growing consumer association of prestige with sustainability. Heightened post-pandemic ethical awareness further underscores the importance of brand values. Contrary to earlier research indicating low CE in developing markets, the 2024 results demonstrate an unexpected rise in CE, highlighting its evolving significance. Overall, the study emphasizes the necessity for global brands to adopt sustainable, locally attuned strategies to succeed in developing countries. Full article

The growing interest in probiotic bacteria within the food industry is driven by their recognized health benefits for consumers. However, preserving their therapeutic viability and stability during gastrointestinal transit remains a formidable challenge. Hence, this research aimed to enhance the viability of Lactobacillus reuteri through microencapsulation using a binary polysaccharide mixture composed of low acyl gellan gum (LAG), high acyl gellan gum (HAG), and calcium for the microencapsulation of L. reuteri. To achieve this, the Box–Behnken design was applied, targeting the optimization of L. reuteri microencapsulated to withstand simulated gastrointestinal conditions. The microcapsules were crafted using the internal ionic gelation method, and optimization was performed using response surface methodology (RSM) based on the Box–Behnken design. The model demonstrated robust predictive power, with R² values exceeding 95% and a lack of fit greater than p > 0.05. Under optimized conditions—0.88% (w/v) LAG, 0.43% (w/v) HAG, and 24.44 mM Ca—L. reuteri reached a viability of 97.43% following the encapsulation process. After 4 h of exposure to simulated gastric fluid (SGF) and intestinal fluid (SIF), the encapsulated cells maintained a viable count of 8.02 log CFU/mL. These promising results underscore the potential of biopolymer-based microcapsules, such as those containing LAG and HAG, as an innovative approach for safeguarding probiotics during gastrointestinal passage, paving the way for new probiotic-enriched food products. Full article

The purpose of this study was to examine vegetable consumption and its relationship with lifestyle characteristics among children and adolescents. Data from a health survey administered to a representative sample of 177,091 schoolchildren between the ages of 8 and 17 were employed in this observational, cross-sectional investigation. Physical activity level, screen time, and sleeping patterns were assessed using self-completed questionnaires. Vegetable consumption and dietary habits were analyzed using the Mediterranean Diet Quality Index for Children and Adolescents. Participants consuming vegetables more than once daily were categorized as consumers vs. non-consumers. Physical education teachers measured anthropometric and physical fitness factors. Descriptive statistics and binary logistic regression analysis were conducted, and the odds ratio with the corresponding 95% confidence interval was calculated and adjusted for confounders. Vegetables were consumed once or more times a day by more females than males (25.5% vs. 24.0%, p < 0.001). In both sexes, vegetable consumers slept more, ate healthier, spent less time on screens, and had better anthropometric and aerobic fitness measurements than non-consumers. Healthy eating practices, such as regularly consuming fruits, legumes, nuts, and dairy products, were strongly correlated with vegetable intake. For every one-year increase in age, the odds of being a vegetable consumer decreased by 8% and 10% in boys and girls, respectively. Overweight/obese participants had lower odds of being a vegetable consumer by 20%. Increased screen time, inadequate physical activity, and insufficient sleeping hours decreased the odds of being a vegetable consumer by 22%, 30%, and 25%, respectively (all p-values < 0.001). Overall, a healthier lifestyle profile was associated with higher vegetable intake for both sexes among children and adolescents. Full article

Research concerning green marketing has predominantly focused on consumer behavior. However, aspects such as the extent to which Small and Medium Enterprises (SMEs) embrace green marketing values, their ability to implement the green marketing mix, and the integration of green marketing into their business culture are critically important. This research aims to provide the 4P (product, price, place, and promotion)-focused green marketing literature with a measurement tool to assess how SMEs implement green marketing practices. The study employed a descriptive design and possesses an exploratory nature. Scale development involved two stages: First, analyses were conducted on a pre-test sample of 159 individuals, revealing the initial scale structure. Second, these analyses were repeated on a larger group of 387 participants. The scale was finalized by confirming the consistency of results across both analyses. Statistical Package for the Social Sciences (SPSS) version 24 and Analysis of Moment Structures (AMOS) version 24 were utilized for descriptive statistics and the scale development process. The final validated 12-item scale demonstrates a robust three-factor structure (“Environmental Promotion”, ”Green Packaging”, and ”Green Distribution”), explaining 62.6% of the total variance. The scale exhibits excellent psychometric properties, including high internal consistency (Cronbach’s α = 0.912), strong model fit from Confirmatory Factor Analysis (CFA), and both convergent and discriminant validity, as indicated by an Average Variance Extracted (AVE) value of 0.605. The scale is deemed applicable to larger populations. Full article

Seafood processing byproducts (SB) such as bones and skin can be safely used as food ingredients to increase profitability for the seafood sector and provide nutritional value. An online survey of 716 US adult seafood consumers was conducted to explore SB trial intent, responsiveness to health and safety information, and associated elicited emotions (nine-point Likert scale). Consumers’ SB-elicited emotions were defined as those changing in reported intensity (from a baseline condition) after the delivery of SB-related information (dependent t-tests). As criteria for practical significance, a raw mean difference of >0.2 units was used, and Cohen’s d values were used to classify effect sizes as small, medium, or large. Differences in willingness-to-try, responsiveness to safety and health information, and SB-elicited emotions were found based on self-reported gender and race, with males and Hispanics expressing more openness to SB consumption. SB-elicited emotions were then used to model consumers’ willingness-to-try foods containing SB via logistic regression modeling. Traditional stepwise variable selection was compared to variable selection using raw mean difference > 0.2 units and Cohen’s d > 0.50 constraints for SB-elicited emotions. Resulting models indicated that extrinsic information considered at the point of decision-making determined which emotions were relevant to the response. These new approaches yielded models with increased Akaike Information Criterion (AIC) values (lower values indicate better model fit) but could provide simpler and more practically meaningful models for understanding which emotions drive consumption decisions. Full article

Background: The relationship between genetic diversity and fitness is well understood, but few studies have investigated how behavior influences genetic diversity, or vice versa. We investigated the relationship between feeding behavior (on a pelleted diet) and genetic diversity in pikeperch, a piscivorous species. Methods: A total of 135 juvenile pikeperch from the same stock were grouped into three behavioral groups: pellet consuming, pellet refusing, and cannibalistic. Eighteen microsatellite markers were used to characterize the genetic diversity and structure of individuals. Results: The juveniles were classified into two genetic clusters: one dominated by pellet-consuming individuals and the other by pellet-refusing individuals containing equal proportions of cannibal individuals. Three of the microsatellite markers were under selection, but only one showed significant genetic segregation between the groups. For this marker, the pellet consumption was associated with low fragment length. Individual multilocus heterozygosity was significantly higher in the pellet-refusing group. Conclusions: These results suggest that pellet consumption acts as an uncontrolled selective force during domestication, influencing the genetic variability of domesticated populations. The ability to habituate to pellets has a significant genetic basis. Cannibalism does not affect genetic variability, and the emergence of the trait is independent of the propensity to consume pellets. Full article

Design and use of wearable technology have grown exponentially, particularly in consumer products and service sectors, e.g., healthcare. However, there is a lack of a comprehensive understanding of wearable technology in consumer acceptance. This systematic review utilized a PRISMA on peer-reviewed articles published between 2014 and 2024 and collected on WoS, Scopus, and ScienceDirect. A total of 38 full-text articles were systematically reviewed and analyzed using bibliometric, thematic, and descriptive analysis to understand the technical functions of digital wearable products (DWPs) in consumer acceptance. The findings revealed four key functions: (i) wearable technology, (ii) appearance and design, (iii) biomimetic innovation, and (iv) security and privacy, found in eight types of DWPs, among them smartwatches, medical robotics, fitness devices, and wearable fashions, significantly predicted the customers’ acceptance moderated by the behavioral factors. The review also identified five key outcomes: health and fitness, enjoyment, social value, biomimicry, and market growth. The review proposed a comprehensive acceptance model that combines biomimetic principles and AI-driven features into the technical functions of the technical function model (TAM) while addressing security and privacy concerns. This approach contributes to the extended definition of TAM in wearable technology, offering new pathways for biomimetic research in smart devices and robotics. Full article

In order to elucidate the high-temperature reaction process of solid waste-based high belite sulphoaluminate cement containing residual gypsum in clinker (NHBSAC) and obtain the formation laws of each mineral in clinker, this article studied its high-temperature reaction kinetics. Through QXRD analysis and numerical fitting methods, the formation of C₄A₃$\overline{\mathrm{S}}$, β-C₂S, and CaSO₄ in clinker under different calcination systems was quantitatively characterized, the corresponding high-temperature reaction kinetics models were established, and the reaction activation energies of each mineral were obtained. The results indicate that the content of C₄A₃$\overline{\mathrm{S}}$ and β-C₂S increases with the prolongation of holding time and the increase in calcination temperature, while CaSO₄ is continuously consumed. Under the control mechanism of solid-state reaction, the formation and consumption of minerals follow the kinetic equation. C₄A₃$\overline{\mathrm{S}}$ and β-C₂S satisfy the D₄ equation under diffusion mechanism control, and CaSO₄ satisfies the R₃ equation under interface chemical reaction mechanism control. The activation energy required for mineral formation varies with different temperature ranges. The activation energies required to form C₄A₃$\overline{\mathrm{S}}$ at 1200–1225 °C, 1225–1275 °C, and 1275–1300 °C are 166.28 kJ/mol, 83.14 kJ/mol, and 36.58 kJ/mol, respectively. The activation energies required to form β-C₂S at 1200–1225 °C and 1225–1300 °C are 374.13 kJ/mol and 66.51 kJ/mol, respectively. This study is beneficial for achieving flexible control of the mineral composition of NHBSAC clinker, providing a theoretical basis and practical experience for the preparation of low-carbon cement and the optimization design of its mineral composition. Full article

This study systematically investigates the effects of shell ash (SA) content (0–10%) on early moisture evolution, pore structure, and hydration kinetics in cement paste using LF-NMR and NG-I-D hydration kinetic models. Key findings include the following: (1) Increased SA content significantly alters moisture phase distribution. Low contents (≤8%) consume free water through rapid CaO hydration, promoting C-S-H gel densification. However, 10% SA causes reduced moisture in 0.16–0.4 μm gel micropores (due to hindered ion diffusion) and abrupt increases in 0.63–2.5 μm pores. (2) Porosity first decreases then increases with SA content, reaching minimum values at 3–5% and 8%, respectively. The 10% content induces abnormal porosity growth from localized over-densification following polynomial fitting (R² = 0.966). (3) Krstulovic–Dabic model analysis reveals three consecutive hydration stages: nucleation–growth (NG), phase boundary reaction (I), and diffusion control (D). The NG stage shows the most intense reactions, while the D stage dominates (>60% contribution), with high model fitting accuracy (R² > 0.9). (4) SA delays nucleation/crystal growth, inducing needle-like crystals at 3% content. Mechanical properties exhibit quadratic relationships with SA content, achieving peak compressive strength (18.6% increase vs. control) at 5% SA. This research elucidates SA content thresholds governing hydration kinetics and microstructure evolution, providing theoretical support for low-carbon cementitious material design. Full article

Background: Marker-based motion capture is the current gold standard for three-dimensional (3D) gait analysis. This is a highly technical analysis that is time-consuming, and marker application can trigger anxiety in children. One potential solution is to use markerless camera systems instead. The objective of this study was to compare 3D lower limb gait kinematics in children using both marker-based and markerless motion capture methods. Methods: Ten typically developing children (age 6–13 yrs) completed five barefoot walks at a self-selected speed. A 10-camera marker-based system (Oqus, Qualisys) and a 7-camera markerless system (Miqus, Qualisys) captured synchronised gait data at 85 Hz. Generalised Additive Mixed Models were fitted to the data to identify the random effects of measurement systems, age, and time across the gait cycle. The root-mean-square difference (RMSD) was used to compare the differences between systems. Results: Significant interactions and differences were observed between the marker-based and markerless systems for most joint angles and planes of motion, particularly with regard to time and age. Conclusions: Despite differences across all kinematic profiles, the RMSD in this study was comparable to previously published results. Alternative model definitions and kinematic crosstalk in both systems likely explain the differences. Age differences were not consistent across joint levels, suggesting a larger sample size is required to determine how maturation may affect markerless tracking. Further investigation is required to understand the deviations and differences between systems before implementing markerless technology in a clinical setting. Full article

Monitoring forest structure, diversity, and biomass in restoration areas is both expensive and time-consuming. Metrics derived from digital aerial photogrammetry (DAP) may offer a cost-effective and efficient alternative for monitoring forest restoration. The main objective of this study was to use metrics derived from digital aerial photogrammetry (DAP) point clouds obtained by remotely piloted aircraft (RPA) to estimate aboveground biomass (AGB), species diversity, and structural variables for monitoring restored secondary tropical forest areas. The study was conducted in three active and one passive forest restoration systems located in a secondary forest in Sergipe state, Brazil. A total of 2507 tree individuals from 36 plots (0.0625 ha each) were identified, and their total height (ht) and diameter at breast height (dbh) were measured in the field. Concomitantly with the field inventory, the plots were mapped using an RPA, and traditional height-based point cloud metrics and Fourier transform-derived metrics were extracted for each plot. Regression models were developed to calculate AGB, Shannon diversity index (H′), ht, dbh, and basal area (ba). Furthermore, multivariate statistical analyses were used to characterize AGB and H′ in the different restoration systems. All fitted models selected Fourier transform-based metrics. The AGB estimates showed satisfactory accuracy (R² = 0.88; RMSE = 31.2%). The models for H′ and ba also performed well, with R² values of 0.90 and 0.67 and RMSEs of 24.8% and 20.1%, respectively. Estimates of structural variables (dbh and ht) showed high accuracy, with RMSE values close to 10%. Metrics derived from the Fourier transform were essential for estimating AGB, species diversity, and forest structure. The DAP-RPA-derived metrics used in this study demonstrate potential for monitoring and characterizing AGB and species richness in restored tropical forest systems. Full article

Light curve analysis of W UMa-type contact binary systems using MCMC or MC methods can be time-consuming, primarily because the repeated generation of synthetic light curves tends to be relatively slow during the fitting process. Although various approaches have been proposed to address this issue, their implementation is often challenging due to complexity or uncertain performance. In this study, we introduce the BSN application, whose name is taken from the BSN project. The application is designed for analyzing contact binary system light curves, supporting photometric data, and employing an MCMC algorithm for efficient parameter estimation. The BSN application generates synthetic light curves more than 40 times faster than PHOEBE during the MCMC fitting process. The BSN application enhances light curve analysis with an expanded feature set and a more intuitive interface while maintaining compliance with established scientific standards. In addition, we present the first light curve analyses of four contact binary systems based on the TESS data, utilizing the BSN application version 1.0. We also conducted a light curve analysis using the PHOEBE Python code and compared the resulting outputs. Two of the target systems exhibited asymmetries in the maxima of their light curves, which were appropriately modeled by introducing a cold starspot on one of the components. The estimated mass ratios of these total-eclipse systems place them within the category of low mass ratio contact binary stars. The estimation of the absolute parameters for the selected systems was carried out using the $P-a$ empirical relationship. Based on the effective temperatures and masses of the components, three of the target systems were classified as A-subtype, while TIC 434222993 was identified as a W-subtype system. Full article

Carbon black (CB)-filled rubber has been widely used in engineering. However, its time-dependent behavior, such as creep, is undesirable during the service process. In addition, the long-term creep test is time- and cost-consuming. To this end, the objective of this paper aims to predict the creep behavior from the short-term storage modulus by use of the collocation method. First, the master curve of storage modulus was constructed based on the time–temperature superposition principle (TTSP), and the validation of shift factors was verified by use of the Williams–Landel–Ferry (WLF) equation. Second, the generalized Kelvin model was used to describe the master curve of storage modulus by use of the collocation method, and the corresponding parameters were obtained. Compared with the existing works, the collocation method had the advantages of avoiding the occurrence of waviness of the fitting curve. Lastly, the creep compliance of CB-filled rubber was calculated by substituting the fitting parameters into the creep compliance expression. In order to verify the reliability of the calculation result, the creep tests were carried out. It was obvious that the calculation result is in good agreement with the experimental one with a RMSE value of 0.0055, which means that the calculation result is reliable. Full article