Search Results (53)

Background: Entrustable professional activities (EPAs) are increasingly used in competency-based assessment, but evidence remains limited for nursing workplace-based assessment (WBA) systems that can capture learning trajectories while providing defensible reliability for programmatic decisions. Objective: The objective of this study is to develop a respiratory nursing EPA framework and clinically validate core EPAs using longitudinal WBA data, including performance progression, attainment patterns, and reliability requirements based on generalizability (G) theory and decision (D) studies. Methods: This study included two phases: (1) EPA framework development using evidence synthesis and a two-round Delphi consultation and (2) longitudinal clinical validation using WBA data. In the validation phase, 30 respiratory nurses were assessed by five trained raters over 12 weeks on four core EPAs (EPA1, EPA2, EPA5, and EPA11) using a 1–5 entrustment scale (attainment defined as a score ≥ 4). Learning trajectories were modeled using a negative exponential function (learning speed indexed by β0). Reliability was evaluated using a crossed-facet G-study framework (person × rater × occasion) with mixed-effects modeling, and D-studies were used to identify minimal rater–occasion configurations meeting EP² thresholds. Results: In the Delphi phase, 21 experts completed both rounds (100% response rate), with high authority coefficients (Cr = 0.841 and 0.843) and significant inter-expert agreement (Kendall’s W = 0.504 and 0.532; both p < 0.01), yielding a final 13-item respiratory nursing EPA framework. In the validation phase, 1392 core EPA assessments were analyzed, and event-level attainment ranged from 72.5% to 89.1%. Learning speeds were heterogeneous (β0 = 0.038–0.156), with the fastest improvement in EPA11 and the slowest in EPA2. In the G-study, residual variance accounted for 65.05% of the total variance, followed by person (18.21%) and occasion/week (10.13%) effects, and the main effect on rater was small (0.14%). Under the observed protocol (five raters and approximately four ratings/week), reliability reached acceptable levels (G = 0.792; EP² = 0.712). The minimum D-study configurations were one rater × 11 ratings/week for EP² ≥ 0.70 (EP² = 0.703) and two raters × 12 ratings/week for EP² ≥ 0.80 (EP² = 0.812). Conclusions: The respiratory nursing EPA framework showed strong expert-consensus support and promising longitudinal clinical validation evidence. A core EPA-based WBA approach demonstrated developmental sensitivity and acceptable dependability under feasible sampling plans, supporting its use for structured competency assessment and progression monitoring in respiratory nursing training. Full article

High-index silicon surfaces provide anisotropic step networks, reconstruction states, and facet-adjacent geometries that can modify the first stages of III–V heteroepitaxy. This critical review examines GaAs/AlGaAs growth on Si$\left(hhl\right)$ surfaces, with emphasis on the coupled roles of substrate orientation, surface preparation, first-monolayer initiation, and molecular beam epitaxy kinetics. The central viewpoint is that high-index Si can act as an active interfacial template: its anisotropy can bias early nucleation, relaxation, and faceting pathways before any intentional lithographic patterning is introduced. The discussion is anchored in two recent GaAs/Si studies. The first is a matched-condition benchmark comparing Si(001), Si(113), Si(111), and Si(331) under Ga-first and As-first initiation. The second is a Si(331) case study in which Ga pre-exposure followed by low-rate GaAs nucleation yields laterally ordered nanocorrugation/faceting and measurable in-plane optical anisotropy under the explored conditions. Surface-science precedents from adsorbate-induced reconstructions provide additional context for treating the first atomic layer as a meaningful growth variable. These studies point to a broader opportunity: using high-index Si$\left(hhl\right)$ surfaces to link interface chemistry, anisotropic morphology, structural relaxation, and optical response within a common framework for GaAs/Si integration. Full article

High-sensitivity detection of formaldehyde is critically important for environmental protection and public health. Zinc oxide (ZnO) is a widely used core material for chemiresistive gas sensors; however, its conventional low-index facets suffer from a limited number of active sites, creating a bottleneck for further sensitivity enhancement. To overcome this limitation, this study pioneers the application of the highly reactive ZnO $\left[20\overline{2}1\right]$ high-index polar surface for formaldehyde detection. By leveraging its unique stepped atomic configuration and unprecedented density of coordination-unsaturated active sites, we systematically investigate the formaldehyde adsorption behavior and the underlying sensing mechanism using first-principles calculations based on density functional theory (DFT). The pristine ZnO $\left[20\overline{2}1\right]$ surface exhibits intrinsic metallic character. At a coverage of 1 monolayer (ML), the most stable G1 configuration achieves an adsorption energy of −1.54 eV per CH₂O molecule. Within a 2 × 1 supercell, formaldehyde adopts both associative and dissociative adsorption modes. At a lower coverage, formaldehyde forms a stable bidentate structure through dual C–O and Zn–O bonding interactions. Electronic structure analysis reveals significant orbital hybridization and interfacial charge redistribution upon adsorption. Notably, associative adsorption opens a bandgap of 0.04 eV at the Fermi level, inducing a metal-to-semiconductor transition. In contrast, dissociative adsorption results in pronounced n-type doping, thereby elucidating the microscopic origin of the resistivity decrease observed in ZnO-based sensors. Overall, this work highlights the structural advantages of high-index facets and demonstrates for the first time the superior formaldehyde adsorption capability of the ZnO $\left[20\overline{2}1\right]$ facet, providing robust theoretical guidance for the rational design of next-generation, high-performance gas-sensing materials. Full article

Radar is critical for urban security against Unmanned Aerial Vehicles (UAVs), yet signal occlusion caused by dense buildings and complex urban structures remains a major challenge for coverage assessment. Existing approaches commonly rely on 2D maps or 2.5D Digital Surface Models (DSMs), which have difficulty representing vertical facades, vegetation, bridges, overhanging structures, and void spaces. These geometric limitations can introduce errors in radar occlusion determination and direct-path power-density estimation. Full 3D ray-tracing methods offer high fidelity, but their multi-path modeling and material-parameter requirements can be costly for large oblique photogrammetric city meshes. To address this problem, this paper proposes the Visible Radar Power-Density Field (VRPF), a 3D radar power-density field computation framework based on high-resolution oblique photogrammetric models. The method constructs a reusable spatial index for large numbers of triangular facets and performs two-stage occlusion queries: rapid Axis-Aligned Bounding Box (AABB) pruning followed by ray-triangle intersection tests. Together, these components enable efficient direct-path power-density calculation while accounting for line-of-sight occlusion in complex urban scenes. Qualitative and quantitative experiments show that VRPF better preserves occlusion boundaries around building edges, vegetation, and elevated structures than DSM-based baselines. VRPF also requires less time for repeated occlusion queries than a conventional 3D BVH ray-casting baseline while maintaining highly consistent radar-signal occlusion determinations. With 32 threads, VRPF computes power density for ${10}^8$ target points in 5.92 s, about $2.66\times$ faster than the 1 m DSM method. These results indicate that VRPF provides a practical balance between geometric fidelity and computational efficiency for direct-path radar power-density assessment with urban geometric occlusion. Full article

Traditional treatment strategies for Type 2 diabetes (T2D) adopt a “one-size-fits-all” approach, limiting individual effectiveness. This study presents an explainable, data-driven framework for multi-treatment and single-treatment selection of SGLT2 inhibitors (SGLT2-i) and DPP-4 inhibitors (DPP4-i) based on patient-specific health characteristics. Our approach evaluates treatment effectiveness across four outcomes—glycosylated hemoglobin (HbA1c), low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, and body mass index (BMI)—to enable individualized treatment recommendations. The multi-treatment model, based on multi-output regression, achieved an R² score of 0.44 and an RMSE of 5.58, identifying benefit subgroups for SGLT2-i and DPP4-i across all outcomes. Integrated with SHapley Additive exPlanations (SHAP) analysis, the model offers insights into the factors influencing treatment effects. The single-treatment selection algorithm achieved an accuracy of 0.47 and an F1 score of 0.46, showing a higher average treatment effect with SGLT2-i on all outcomes, notably in the reduction in HbA1c, LDL, and BMI and a modest increase in HDL. While DPP4-i demonstrated beneficial effects on HbA1c, LDL, and HDL, it was associated with an increase in BMI. These findings highlight the benefits of a multi-faceted, patient-centered precision medicine approach for T2D management, enabling treatment strategies that address individual health needs beyond HbA1c. Full article

The catalytic reduction of 4-nitrophenol (4-NP) requires highly efficient and cost-effective materials, making Mn-Ni nanostructures a promising candidate. In this study, Mn-Ni nanoparticles with distinct morphologies (specifically spheres, stars, and core–shell structures) were synthesized by tuning the precursor composition. The structural and optical properties of the synthesized catalysts were characterized via electron microscopy and UV-Vis spectroscopy. Kinetic evaluations of the 4-NP reduction demonstrated that the core–shell architecture yielded the highest catalytic activity, outperforming both the star-shaped and spherical nanoparticles. Furthermore, the high-index facets at the tips of the nanostars appeared to have contributed to enhanced catalytic activity by providing additional active surface sites for the reduction process. Ultimately, this work suggests that structural morphology and interfacial interactions play important roles in determining catalytic performance, rather than absolute surface area, providing valuable insights into the design of future bimetallic catalysts. Full article

Electrolysis of seawater is considered a green route for hydrogen generation; however, its practical application is limited by strong electrode corrosion and slow OER kinetics in chloride-rich media. Herein, we report a crystal-facet engineering strategy to construct nickel hydroxide with a parallel array structure on nickel foil (denoted as Ni(OH)₂/NFPA, where NFPA represents nickel foil with parallel array) via a facile two-step etching-hydrothermal method. Structural characterization confirms the formation of high-index Ni(220) surfaces and well-aligned hydroxide nanostripes, which promote more favorable bubble–electrode interactions and contribute to improved interfacial stability. Owing to its characteristic parallel array configuration, Ni(OH)₂/NFPA exhibits outstanding OER performance in alkaline electrolyte, delivering a low overpotential of 256 mV at 10 mA·cm⁻² together with a Tafel slope as small as 74.9 mV·dec⁻¹, surpassing commercial RuO₂ and disordered Ni(OH)₂ nanosheets. The optimized electrode also delivers remarkable durability, maintaining stable operation for 48 h at 100 mA·cm⁻² even under harsh alkaline seawater conditions at 80 °C. Bubble dynamics analysis reveals that the ordered array morphology produces a superaerophobic surface, enabling rapid detachment of oxygen bubbles and ensuring efficient mass transport. This study highlights facet-controlled construction of parallel nanoarrays as a promising approach to improve catalytic efficiency, corrosion resistance, and bubble management in seawater electrolysis, offering useful implications for the rational design of high-performance electrodes for practical hydrogen production. Full article

The Normalized Difference Vegetation Index (NDVI) is a fundamental metric for monitoring terrestrial ecosystem dynamics and assessing ecological responses to climate change. However, uncertainties persist across NDVI products, and a comprehensive assessment of their consistency is lacking. This study conducts a multi-faceted evaluation of three NDVI products, GIMMS V1.2 NDVI (NDVI_3g+), PKU GIMMS NDVI (NDVI_pku), and MODIS NDVI (NDVI_mod), to elucidate their performance across ecosystem applications. Our analysis encompasses a comparative analysis of NDVI values, trends, sensitivity to root-zone soil moisture (RSM), and performance in tracking photosynthesis benchmarked against solar-induced chlorophyll fluorescence (SIF). Our results reveal that NDVI_3g+ deviates notably from NDVI_pku and NDVI_mod over cold climates and Evergreen Broadleaf Forest (EBF). Additionally, NDVI_3g+ exhibits significant global browning, in contrast to the significant greening observed for NDVI_pku and NDVI_mod. Although their responses to RSM are generally uncertain, consistent positive responses appear in Drylands, with NDVI_mod showing the highest sensitivity. Additionally, the three NDVI products have high seasonality consistency with SIF, except over EBF, and NDVI_pku and NDVI_3g+ achieve the highest and lowest overall anomaly consistency with SIF, respectively. Furthermore, converting NDVI_3g+, NDVI_pku, and NDVI_mod to the corresponding kernel NDVIs improves seasonality consistency with SIF across 85% of the globe. Full article

Background: Although evidence-based practice is widely promoted in nursing, direct care nurses remain underrepresented in research activities. This study aimed to assess nurses’ attitudes toward research, their perceptions of the organizational research environment, and their levels of involvement, as well as identify key barriers and facilitators to engagement within a comprehensive healthcare system. This study also explored how racial and ethnic diversity within the nursing workforce may shape research engagement and contribute new perspectives to the field. Methods: A cross-sectional electronic survey was administered to registered nurses across 10 hospitals in a Northeast U.S. health system. The survey instrument assessed research attitudes, environment, involvement (past, present, future), and demographics. Descriptive and inferential statistics, including matched-pairs t-tests, were used to analyze responses. Results: Of 7655 invited nurses, 1094 responses were analyzed. Respondents were predominantly female (88.5%), White (56.8%), and employed full-time (87.1%) as clinical staff nurses (77.3%). While 54.8% had completed a formal research course (mainly within the past 1–3 years), informal research and statistics training were uncommon (17.4% and 5.4%, respectively). Nurses reported highly positive attitudes toward research (composite M = 2.15, SD = 0.51), especially its role in guiding practice, professional growth, and education. However, actual involvement was low. The most common current activities included practice change based on research (20.7%) and participation in committees (18.8%). Anticipated future engagement increased substantially, particularly in collaboration (+21.3%), committee participation (+20.6%), and IRB submission (+18.2%). The research environment was perceived as under-resourced, particularly in terms of protected time, funding, and mentorship. Statistically significant gaps were observed between perceived present and desired future supports (p < 0.01 for all 15 items). The Research Awareness Index revealed high rates of uncertainty about available resources (e.g., 66.1% did not know if internal funding existed). Conclusions: Nurses demonstrate strong positive attitudes and a desire to engage in research, including more advanced roles. Yet structural and informational barriers, particularly a lack of protected time, mentorship, and awareness of existing supports, limit participation. Investments in infrastructure, communication, and accessible development pathways are needed to translate nurses’ readiness into active research engagement. Implications: Institutions should prioritize making research support more visible and navigable while investing in mentorship, protected time, and user-friendly infrastructure. Addressing both facets will empower a highly motivated nursing workforce to engage in and lead practice-relevant research. Full article

Background and Objectives: In the present study, distinct subgroups of older adults with chronic low back pain (LBP) were identified using cluster analysis based on the five dimensions of the EQ-5D-5L. Using detailed profiles of how chronic LBP affects various facets of health-related quality of life (HRQoL), differences in frailty levels across these subgroups were investigated in this study. Materials and Methods: This retrospective study included patients ≥ 60 years of age who visited the pain clinic at a tertiary hospital between March 2022 and February 2023. HRQoL was assessed using the EQ-5D-5L, and frailty was evaluated via the Frailty Phenotype Questionnaire. Hierarchical cluster analysis using the WARD method with squared Euclidean distance was conducted on the EQ-5D-5L dimensions to identify subgroups. Differences in frailty, demographics, and clinical data across clusters were analyzed. Results: Among 837 older adults with chronic LBP, four distinct clusters were identified based on a cluster analysis of the EQ-5D-5L dimensions. Cluster 1 exhibited high levels of pain/discomfort and anxiety/depression, and cluster 2 had severe mobility limitations and pain/discomfort but low anxiety/depression. Cluster 3 showed balanced scores across all dimensions, and cluster 4 had severe pain/discomfort but good mobility. Significant differences were observed among the clusters in pain intensity, EQ Visual Analogue Scale (EQ-VAS) and EQ-5D-5L index scores, and frailty status. Cluster 1 had the highest pain scores and lowest EQ-VAS, and frailty was most prevalent in cluster 2 (28.5%) and least in cluster 4 (13.3%). Conclusions: The results of the present study emphasize the complexity of chronic LBP in older adults by identifying distinct clusters. Cluster analysis identified four unique profiles, with significant frailty differences across the clusters. These findings emphasize the importance of personalized management strategies tailored to specific patient profiles to enhance treatment effectiveness and improve frailty status. Full article

Silicon (Si) and silicon carbide (SiC) are second- and third-generation semiconductor materials with excellent properties that are particularly suitable for applications in scenarios such as high temperature, high voltage, and high frequency. Si/SiC wafers face warpage and bending problems during production, which can seriously affect subsequent processing. Fast, accurate, and comprehensive detection of thickness, thickness variation, and flatness (including bow and warpage) of SiC and Si wafers is an industry-recognized challenge. Frequency scanning interferometry (FSI) can synchronize the upper and lower surfaces and thickness information of transparent parallel thin wafers, but it is still affected by multiple interfacial harmonic reflections, reflectivity asymmetry, and phase modulation uncertainty when measuring SiC thin wafers, which leads to thickness calculation errors and face reconstruction deviations. To this end, this paper proposes a high-precision facet reconstruction method for SiC/Si structures, which combines harmonic spectral domain decomposition, refractive index gradient constraints, and partitioning optimization strategy, and introduces interferometric signal “oversampling” and weighted fusion of multiple sets of data to effectively suppress higher-order harmonic interferences, and to enhance the accuracy of phase resolution. The multi-layer iterative optimization model further enhances the measurement accuracy and robustness of the system. The flatness measurement system constructed based on this method can realize the simultaneous acquisition of three-dimensional top and bottom surfaces on 6-inch Si/SiC wafers, and accurately reconstruct the key parameters, such as flatness, warpage, and thickness variation (TTV). A comparison with the Corning Tropel FlatMaster commercial system shows that this method has high consistency and good applicability. Full article

The exploration of the coupling trend between urban agglomeration development (UAD) and land surface temperature (LST) expansion is of great significance, and it is of scientific value for the regulation of the thermal environment of urban agglomerations, the optimization of urban spatial planning, and the achievement of sustainable urban development. This study employs an array of remote sensing datasets from multiple sources—employing a multi-faceted approach encompassing an overall coupling situation analysis model, a coordination and evaluation system, a geographically weighted spatial autocorrelation algorithm, and landscape pattern quantification indicators—to explore the mutual feedback mechanism and spatial coupling characterization of LST and UAD in the Guanzhong Plain Urban Agglomeration (GZPUA). The results of the study can provide data support for urban spatial planning and thermal environment regulation. The results indicate the following findings: (1) In the GZPUA, the nighttime light (NTL) and land surface temperature (LST) centroids show a significant tendency toward approaching one another, with a spatial offset decreasing from 45.0 km to 9.1 km at the end, indicating a strengthening trend in the photothermal system’s coupling synergy. (2) The coordination of light and heat in the study area exhibits significant non-equilibrium development, with a dynamic trend of urban development space shifting towards the southwest. It confirms the typical regional response law of rapid urbanization. (3) The Moran’s I index of the photothermal system in the study area increased from 0.289 to 0.335, an increase of 15.9%. The proportion of “high–high” (H-H)/“low–low” (L-L)-type regions with clustering distribution of cold and hot spots reaches 58.01%, and their spatial continuity characteristics are significantly enhanced, indicating a significant trend of spatial structural integration between urban heat island effect and construction land expansion. Full article

The pursuit of high-quality higher education in ethnic minority regions is of paramount importance in the contemporary era. As China advances towards its distinctive model of higher education modernization, the imperative for a robust evaluation framework for higher education modernization becomes increasingly evident. Achieving synchronized educational modernization across all ethnic groups is not only a persistent and evolving facet of the historical national strategy of “Four Modernizations in Synchronization” but also a critical milestone and salient indicator of concurrent progress in higher education modernization across ethnic minority regions in the present context. From 2012 to 2020, the nation executed a nine-year strategic plan aimed at revitalizing higher education in the central and western regions. This study, employing literature analysis and grounded in the five core functions of universities, utilizes a comprehensive dataset spanning a decade (2012 to 2021) to construct a bespoke evaluation index system for the modernization of higher education in ethnic minority regions. Through quantitative assessments, this study evaluates the trajectory of modernization in higher education development in these regions over the past decade, thereby offering indirect insights into the efficacy of the national initiative to rejuvenate higher education in the central and western regions. The findings indicate a fluctuating yet upward trend in the overall level of higher education development across the eight ethnic minority regions. Nevertheless, substantial disparities persist when compared with other provinces. Notably, Tibet and Guizhou have demonstrated significant growth, with respective growth rates of 5.533 and 4.341. Moreover, an in-depth analysis leveraging the grey GM(1,1) prediction model projects the future developmental trajectories of higher education in ethnic minority regions. To ensure the sustainable advancement of higher education in ethnic minority regions, supplementary policy interventions are indispensable. This entails fostering a conducive environment of resonance and coordinated development between ethnic economies and higher education, thereby nurturing a harmonious relationship that propels progress. Full article

As the effects of climate change progressively worsen, many scientists are concerned over the expanding geographic range and impact of forest-defoliating insects. Many are currently pointing to this form of disturbance becoming a key focus of remote sensing research in the coming decades; however, the available body of research remains lacking. This study investigated the viability of detecting and quantifying damage caused to a managed Scots pine forest in central Poland by insect defoliation disturbance using high-resolution multispectral satellite imagery. Observed leaf area index (LAI) values were compared to frass observations (insect detritus) to assess the relationship between LAI and defoliating insect activity across a single life cycle of A. posticalis Mats. Across four managed plots, four vegetative indices (NDVI, GNDVI, EVI, and MSAVI2) were calculated using multispectral satellite imagery from a PlanetScope (PSB.SD instrument) satellite system. Then, 1137 point-sampled digital number (DN) values were extracted from each index, and a correlation analysis compared each to 40 ground-observed LAI data points. LAI was modeled on the basis of NDVI values. Three models were assessed for their performance in predicting LAI. They were fit using a variety of regression techniques and assessed using several goodness-of-fit measures. A relationship between observed LAI and frass observations was found to be statistically significant (p-value = 0.000303). NDVI was found to be the correlated LAI values (rho = 0.612). Model 3, which was based on concepts of the Beer–Lambert law, resulted in the most robust predictions of LAI. All parameters were found to be significant post fitting of the model using a nonlinear least squares method. Despite the success of the Beer’s law model in predicting LAI, detection of A. posticalis damage was not achieved. This was predominately due to issues of resolution and plot condition, among others. The results of this analysis address many interesting facets of remote sensing analysis and challenge the commonly held view of the impeachability of these methods. Full article

We systematically investigated the morphology-controlled synthesis of Cu₂O micro-nano crystals, especially under surfactant-free conditions, targeting a simple, rapid, and morphologically controllable preparation strategy for polyhedral Cu₂O micro-nano crystals. By systematically investigating the effects of NaOH concentration, types of reducing agents, and copper salt precursors on crystal growth, precise control over the morphology of Cu₂O crystals under surfactant-free conditions was achieved. This method can rapidly prepare variously faceted Cu₂O crystals under mild conditions (70 °C, 7 min), including regular polyhedra with low-index facets exposure including cubes, octahedra and rhombic dodecahedra, as well as more complex polyhedra with high-index facets exposure such as 18-faceted, 26-faceted, 50-faceted and 74-faceted crystals. NaOH concentration is found to be the key factor in controlling Cu₂O crystal morphology: as the concentration of NaOH increases, the morphology of Cu₂O crystals gradually transforms from cubes that fully expose the {100} faces to regular polyhedra that expose the {110}, {111} faces, and even other high-index faces, ultimately presenting octahedra that fully expose the {111} faces. Additionally, Cu₂O crystals with unique morphologies such as hollow cubes and 18-faceted with {110} face etched can be obtained by introducing surfactants or prolonging reaction durations. This work provides new insights into the morphology control of Cu₂O crystals and establishes foundation in acquiring distinct Cu₂O polyhedra in a facile manner for their application in catalysis, optoelectronics, sensing, and energy conversion fields. Full article