Explore the vast range of titles available.

This study investigates the effects of Ar ion irradiation on the mechanical properties and microstructure of SA508 Grade 3 Class 1 and Class 2 reactor pressure vessel steels. Three different fluence levels of Ar ion irradiation were applied to simulate accelerated irradiation damage conditions. Charpy impact and tensile tests conducted before and after irradiation showed no significant changes in bulk mechanical properties. Stopping and Range of Ions in Matter (SRIM) and Transport of Ions in Matter (TRIM) simulations revealed that Ar ion irradiation produces a shallow penetration depth of approximately 2.5 µm, highlighting the limitations of conventional macro-mechanical testing for evaluating irradiation effects in such a thin surface layer. To overcome this limitation, nano-indentation tests were performed, revealing a clear increase in indentation hardness after irradiation. Transmission electron microscopy (TEM) analysis using STEM–BF imaging confirmed a higher density of irradiation-induced defects in the irradiated specimens. The findings demonstrate that while macro-mechanical properties remain largely unaffected, micro-scale testing methods such as nano-indentation are essential for assessing irradiation-induced hardening in shallowly damaged layers, providing insight into the behavior of SA508 reactor pressure vessel steels under accelerated irradiation conditions.

Two-level systems based on point defects in dielectric oxides offer promising entropy source for random number generators. The random telegraph noise (RTN) generated by the two-level systems is ideal for creating random bit-strings for advanced computing and cryptographic technologies. However, in classical oxide systems, RTN signals often suffer from instability due to undesired defect migration and metastable electronic states. Herein, we present a two-level quantum system based on SrRuO 3 /LaAlO 3 /Nb-doped SrTiO 3 heterostructure, which incorporates two different types of point defects, oxygen vacancies and antisite Ti defects. Temporal electron localization at antisite defects alters the energy levels of nearby oxygen vacancies through instantaneous Coulomb interaction, resulting in two-level current fluctuation across the interface. The RTN-like current signals exhibit high stability at room temperature. We utilize the stable two-level fluctuations to generate random bit-strings and confirm their applicability in practical stochastic machine learning algorithms for image super-resolution. This study provides a guideline for designing reliable entropy sources by exploiting the complementary interactions between cation and anion point defects in oxide-based electronic systems, essential for hardware-based random number generators. Random telegraph noise signals often suffer from low stability. Here, the authors demonstrate a two-level quantum system that incorporates two different types of point defects and produces highly stable random telegraph noise-like current signals.

In this study, we propose a YOLO-based object detection algorithm for the automated and accurate identification of the fifth wave (Wave V) in auditory brainstem response (ABR) graphs. The ABR test plays a critical role in the diagnosis of hearing disorders, with the fifth wave serving as a key marker for clinical assessment. However, conventional manual detection is time-consuming and subject to variability depending on the examiner’s expertise. To address these limitations, we developed a real-time detection method that utilizes a YOLO object detection model applied to ABR graph images. Prior to YOLO training, we employed a U-Net-based preprocessing algorithm to automatically remove existing annotated peaks from the ABR images, thereby generating training data suitable for peak detection. The proposed model was evaluated in terms of precision, recall, and mean average precision (mAP). The experimental results demonstrate that the YOLO-based approach achieves high detection performance across these metrics, indicating its potential as an effective tool for reliable Wave V peak localization in audiological applications.

Persistent surface charge retention in dielectric oxides is critical for a wide range of electronic and energy applications, including charge‐trapping memory devices, triboelectric generators, and supercapacitors. Since charge retention is intrinsically governed by charge diffusion, understanding and controlling the underlying diffusion mechanisms in charge‐storing materials remain significant challenges. Here, ultralong charge retention in epitaxially grown LaAlO3 (LAO) thin films is reported, enabled by anisotropic charge diffusion. The surface accumulation of oxygen vacancies, driven by the internal polar field, effectively suppresses out‐of‐plane electron hopping, allowing ≈90.9% of the initially injected charges to remain on the LAO surface after 180 h, with stable retention persisting for weeks or longer. Time‐resolved Kelvin probe force microscopy and finite‐difference simulations consistently reveal that this retention enhancement arises from diffusion anisotropy induced by surface‐localized defect states in LAO, rather than by isotropic ionic migration. These results provide an effective strategy for designing high‐performance charge storage materials based on polar‐layered oxides, paving the way for durable surface charge‐based electronic and energy devices. Anisotropic charge diffusion in epitaxially grown LAO thin films is reported, which enables ultralong charge retention. Surface‐accumulated oxygen vacancies effectively suppress out‐of‐plane electron hopping, allowing ≈90.9% of the surface charges to remain after a few weeks or longer. Kelvin probe force microscopy and finite‐difference simulations consistently support this mechanism for stable charge retention.

The flashlight sintering characteristics of inkjet-printed nanosized copper ink on paper substrates with varying pattern widths and intervals were studied. The copper nano particles (CNPs) synthesized using vapor self-assembled multilayer (VSAM) method to prevent oxidation, were produced with ink and patterned on a paper substrate through inkjet printing. The width and interval of the Cu patterns were varied from 350 to 550 μm to investigate the flashlight sintering tendency. It was confirmed that the Cu pattern resistivity decreased as the width of the Cu pattern increased, with decreasing interval between the Cu patterns. For the Cu pattern with the largest width and narrowest interval, the lowest specific resistivity was 6.43 × 10 –6 Ω∙m. For auxiliary heating at 80 °C, the lowest resistivity of the Cu pattern was 7.10 × 10 –6 Ω∙m with improved adhesion to the substrate, and this resistivity was 6.2 times lower than that without auxiliary heating. The temperature gradient of the CNP pattern during the flashlight sintering process was predicted using custom made simulation program. Therefore, the experiments and simulations confirmed that the wider the width and the narrower the interval between patterns, the flashlight sintering characteristics improved through higher heat generation by minimizing heat spreading.

Background There are few studies that directly compared different interventions to improve medical students’ clinical reasoning for dermatologic conditions. Objective To investigate the effectiveness of adding practice with reflection and immediate feedback on traditional dermatology electives in improving medical students’ ability in evaluating skin lesions. Methods The participants were fourth-year medical students of Seoul National University College of Medicine, Korea, who were enrolled to take a 2-week dermatology elective course ( n  = 87). Students were assigned to one of the three educational interventions: 2-h training involving 10 written clinical cases (experimental); 1-h lecture and 1-h outpatient clinic (lecture); and 2-h outpatient clinic (no intervention). Before and at the end of rotation, diagnostic accuracy was estimated using 20 written clinical cases with photographs (10 novel cases presented in diagnostic training [training set], 10 cases with diagnoses not included in training [control set]). Results There was a significant interaction effect of intervention×set×time. A post hoc analysis indicated that the students in the experimental group outperformed students in the other two groups only in the training set of the final tests; after completing the 2-week rotation, for the training set, the mean score was higher in the experimental group (7.5 ± 1.3) than in the lecture (5.7 ± 1.6) and no intervention (5.6 ± 1.3) groups, producing an effect size of 1.2 standard deviation (SD) and 1.5 SD, respectively. Conclusion Practicing written clinical cases with reflection and feedback is superior to a lecture-based approach and yields additional benefits to a dermatology elective, thereby enhancing medical students’ ability to accurately diagnose skin lesions. Trial registration ClinicalTrials.gov , NCT03472001 . Registered 21 March 2018.

High-temperature chemical reactions are ubiquitous in (electro) chemical applications designed to meet the growing demands of environmental and energy protection. However, the fundamental understanding and optimization of such reactions are great challenges because they are hampered by the spontaneous, dynamic, and high-temperature conditions. Here, we investigated the roles of metal catalysts (Pd, Ni, Cu, and Ag) in the high-temperature reverse water-gas shift (RWGS) reaction using in-situ surface analyses and density functional theory (DFT) calculations. Catalysts were prepared by the deposition-precipitation method with urea hydrolysis and freeze-drying. Most metals show a maximum catalytic activity during the RWGS reaction (reaching the thermodynamic conversion limit) with formate groups as an intermediate adsorbed species, while Ag metal has limited activity with the carbonate species on its surface. According to DFT calculations, such carbonate groups result from the suppressed dissociation and adsorption of hydrogen on the Ag surface, which is in good agreement with the experimental RWGS results.

This study proposes an effective method to predict technology development from an evolutionary perspective. Product evolution is the result of technological evolution and market selection. A phylogenetic network is the main method to study product evolution. The formation of the dominant design determines the trajectory of technology development. How to predict future dominant design has become a key issue in technology forecasting and new product development. We define the dominant product and use machine learning methods, combined with product evolutionary theory, to construct a Fully Connected Phylogenetic Network dataset to effectively predict the future dominant design.

Guided cracks were successfully generated in an electrode using the concentrated surface stress of a prism-patterned Nafion membrane. An electrode with guided cracks was formed by stretching the catalyst-coated Nafion membrane. The morphological features of the stretched membrane electrode assembly (MEA) were investigated with respect to variation in the prism pattern dimension (prism pitches of 20 μm and 50 μm) and applied strain ( S  ≈ 0.5 and 1.0). The behaviour of water on the surface of the cracked electrode was examined using environmental scanning electron microscopy. Guided cracks in the electrode layer were shown to be efficient water reservoirs and liquid water passages. The MEAs with and without guided cracks were incorporated into fuel cells, and electrochemical measurements were conducted. As expected, all MEAs with guided cracks exhibited better performance than conventional MEAs, mainly because of the improved water transport.

Purpose This paper aims to examine the joint effect of the focal customer’s gender and fellow customer’s gender in influencing voice complaint intentions and intention to convey negative word of mouth (NWOM). Design/methodology/approach Participants were randomly assigned to one of the two dining conditions (same-gender fellow customer vs opposite-gender fellow customer). Their intention to voice a complaint and to spread NWOM were measured after reading a scenario describing a service failure. A 2 (focal customer gender: male vs female) × 2 (fellow customer: same gender vs opposite gender) between-subjects quasi-experimental design was conducted to test the hypotheses. Findings The results demonstrate that female customers’ voice complaint intentions were significantly higher when a fellow customer’s gender was female rather than male. In contrast, regardless of the fellow customer’s gender, no significant differences in voice complaint intentions were found among male customers. The results further indicate that voice complaint intentions mediate the impact of a fellow customer’s gender on intention to spread NWOM among female customers. However, both female and male participants show equally high levels of voice complaint intentions in the context of fine-dining restaurant. Practical implications This study broadens the understanding of customer complaining behavior and also provides insights to practitioners on how to manage customers who are in same- and mixed-gender situations. Originality/value This research extends the literature on agency–communal theory and complaining behaviors by examining the role of a fellow customer’s gender influencing the focal customer’s intentions to voice complaints and to spread NWOM.