Micro- and Nanostructure Analysis of Vapor-Phase-Grown AlN on Face-to-Face Annealed Sputtered AlN/Nanopatterned Sapphire Substrate Templates.

Micro- and nanostructures in vapor-phase-grown AlN on face-to-face annealed sputtered AlN (FFA Sp-AlN) templates formed on nanopatterned sapphire substrates (NPSS) were comprehensively analyzed using transmission electron microscopy. The comparison between metal-organic vapor-phase epitaxy-grown AlN/FFA Sp-AlN/hole-type NPSS (Sample MOH) and hydride vapor-phase epitaxy-grown AlN/FFA Sp-AlN/cone-type NPSS (Sample HVC) showed apparent differences in the morphology of dislocation propagation, presence of voids, shape of polarity inversion boundaries, and crystal structure on the slope region of NPSS. Notably, cross-sectional and plan-view observations revealed that the quality of FFA Sp-AlN significantly affects the threading dislocation density in the vapor-phase-grown layer. At the slope region of the AlN/NPSS interface, γ-AlON was observed in the MOH sample, while highly misaligned AlN grains were observed in the HVC sample. These characteristic crystal structures affect the occurrence of dislocations via different mechanisms in each sample. This study provides practical information for strategically controlling the micro- and nanostructures formed in AlN/NPSS structures for high-performance AlGaN-based deep-ultraviolet emitters. Supplementary Information: The online version contains supplementary material available at 10.1007/s11664-023-10348-3.

Predictive Rule for Mortality of Inpatients With Escherichia coli Bacteremia: Chi-Square Automatic Interaction Detector Decision Tree Analysis Model.

AIM: A predictive rule for risk factors for mortality due to Escherichia coli (E. coli)bacteremia has not been defined, especially using the chi-square automatic interaction detector (CHAID) decision tree analysis. Here we aimed to create the predictive rule for risk factors for in-hospital mortality due to E. coli bacteremia. METHODS: The outcome of this retrospective cross-sectional survey was death in the hospital due to E. coli bacteremia. Factors potentially predictive of death in the hospital due to E. coli bacteremia were analyzed using the CHAID decision tree analysis. RESULTS: A total of 420 patients (male:female=196:224; mean±standard deviation [SD] age, 75.81±13.13 years) were included in this study. 56 patients (13.3%) died in the hospital. The CHAID decision tree analysis revealed that patients with total protein level ≤5.10 g/dL (incidence, 46.2%), total protein level ≤5.90 g/dL with disturbance of consciousness (incidence, 39.4%), and total protein level >5.90 g/dL with hemoglobin level ≤11.10 g/dL and lactate dehydrogenase level ≥312.0 IU/L (incidence, 42.3%) were included in the high-risk group. CONCLUSIONS: Appropriate preventative therapy should be facilitated in patients with E. coliat a high risk of mortality.