This study investigated the influence of electrolyte composition (sodium hydroxide, silicate) and temperature on Micro-Arc Oxidation (MAO) coatings on Al 6061, focusing on breakdown voltage, microstructure, and infrared emissivity. A systematic factorial design revealed all three factors significantly influenced breakdown voltage and Stage II lifespan. Sodium hydroxide (NaOH) concentration exhibited a complex, non-monotonic effect on IR emissivity and coating growth; its presence generally inhibited growth and reduced emissivity at certain concentrations, while its elimination was critical for optimal performance. Conversely, increasing sodium silicate altered microstructure (e.g., enlarged features, roughened surfaces), boosted silicon content, and consistently enhanced IR emissivity. Without NaOH, silicate concentration had a more pronounced effect on growth, roughness, and IR emissivity than temperature. Notably, we present the first systematic contour maps of the studied properties, revealing temperature's increased influence when NaOH is present. Achieving LWIR emissivity exceeding 90 % on Al 6061 was most effective by eliminating NaOH and maintaining silicate concentrations above 12 g/L, irrespective of temperature.
Background/Objectives: Continuous quality improvement (CQI) requires timely, patient-centered evidence on how people experience healthcare delivery. Structured surveys provide important benchmarks, but their predetermined items may miss emerging or system-specific concerns. This study assesses whether unsolicited online patient reviews can serve as a scalable patient-experience data source for identifying hospital service quality priorities across contrasting healthcare systems. Methods: We analyzed 8247 Google Maps hospital reviews posted in 2024, including 5007 Chinese-language reviews from 24 Taiwanese medical centers and 3240 English-language reviews from 21 large U.S. referral hospitals. Separate language-specific preprocessing pipelines and Latent Dirichlet Allocation (LDA) topic models identified patient-salient service quality dimensions in each country. Cross-lingual semantic mapping then distinguished universal dimensions from system-specific concerns, and star-rating differences across semantically equivalent dimensions were compared. Results: Seven service quality dimensions emerged in each country: five were cross-nationally shared (emergency care, positive care experience, professional medical team, administrative process, and inpatient/treatment care), and each system had two system-specific dimensions. Taiwanese reviews foregrounded service attitude and facility/environment quality, while U.S. reviews foregrounded billing/insurance and clinic systems/access. Ratings for emergency care and administrative process were consistently low across both systems, whereas ratings for the professional medical team were substantially higher in U.S. reviews. Conclusions: Online patient reviews can complement formal patient-experience instruments by revealing actionable CQI priorities that are both universal and context dependent. Emergency care and administrative efficiency represent shared improvement needs across both systems. System-specific interventions include interpersonal training and infrastructure investment in high-utilization single-payer settings, and billing transparency and care coordination in fragmented multi-payer systems. Institutional structures appear to play a more prominent role than cultural factors in shaping which service quality dimensions emerge, though both forces contribute. Established frameworks may inadequately capture system-specific patient concerns.
Consider Laplace's equation in a bounded simply-connected domain S. The harmonic functions in S can be represented by boundary integral equations of the first kind (BIE), which is defined on the domain boundary r (= dS). The unknowns are solved via the source nodes Q on r, and their discrete algorithms are called the conventional boundary integral equation method (BIEM). From the Sobolev extension theory, the harmonic solutions can be extended to a larger simply-connected domain SR with S C SR. We renovate the BIEM by moving the source nodes Q from r to rR, to eliminate the singularity of the BIEM. Their discrete algorithms are simple and straightforward, and called the discrete boundary integral equation method (DBIEM). The main effort of this paper is to explore the error analysis of the DBIEM via Galerkin approaches. An important application of the error analysis is for the method of fundamental solutions (MFS), where the source nodes Q are also located on rR. The error analysis of the MFS in Dou et al. (2020) , Li (2009), Li et al. (2023) is confined to circular/elliptic pseudo-boundaries. The error analysis of the MFS for non-circular/non-elliptic pseudo-boundaries can be obtained from this paper. Since the pseudo-boundary rR is different from the boundary r in the conventional BIEM, the inf-sup lemma is different from that in the boundary element method (BEM). The first work is to prove the new inf-sup lemma. For polygonal domains, when polygonal pseudo-boundaries are chosen, the piecewise interpolation polynomials of low orders are used as in the finite element method (FEM) and the BEM. The error bounds are derived for smooth solutions to achieve the optimal convergence rates. This error analysis is also valid for smooth r, and the constant/linear and linear/quadratic elements may find wide applications. The error analysis can also be applied to the MFS. Numerical experiments are reported to verify the analysis made. This paper is essential to the error analysis of both the DBIEM and the MFS.
The reinforced concrete structures of many bridges and buildings in Taiwan are over 30 years old. Seismic retrofitting of these structures requires an accurate assessment of reinforcement configuration and corrosion conditions to ensure structural safety and seismic performance. In this study, a 1 GHz ground-penetrating radar (GPR) antenna was used to scan reflected signals from single- and double-row reinforcing bars embedded in concrete. Based on established principles reported in previous studies, detailed analyses were conducted, including the use of the approximate circumference method to estimate reinforcing bar dimensions and the determination of spacing between double-row reinforcing bars (6-8 cm). The synthetic aperture focusing technique was first applied to process the original GPR data matrix. Subsequently, physical parameters related to interface diffraction, such as the perimeter S of the reinforcing bar, were extracted using the dielectric constant of the material interface, the calculated power reflection coefficient, and the First Fresnel Zone. These approaches enabled more accurate estimation of reinforcing bar dimensions (e.g., equivalent to #3 bar size) and improved resolution of spacing between double-row reinforcing bars to 3-6 cm. The results demonstrate that using the synthetic aperture focusing technique to process GPR data enhances the ability to determine reinforcing bar dimensions, interpret bar spacing, and improve imaging resolution, thereby providing a reliable reference for the safety assessment of reinforced concrete structures.
Data-driven culture has become a key organisational capability for enhancing innovation and firm performance. This study examines the role of data-driven culture in shaping firm ecosystem scanning, product and process innovation, firm performance, and competitive advantage, as well as its moderating effects on leadership support. We analyse survey data from 293 respondents across more than 80 Vietnamese firms using Partial Least Squares Structural Equation Modelling. The findings indicate that business analytics adoption positively influences data-driven culture and firm ecosystem scanning, which in turn positively affects both product and process innovation. Both innovation types improve firm performance, which subsequently drives competitive advantage. Interestingly, data-driven culture weakens the link between ecosystem scanning and innovation, while leadership support negatively moderates the relationship between product innovation and firm performance. These results highlight the asymmetric roles of data-driven culture and leadership in translating innovation into performance outcomes.
