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Abstract Interface engineering is pivotal for enhancing the performance and stability of devices with layered structures, including solar cells, electronic devices, and electrochemical systems. Incorporating the interfacial dipole between the bulk layers effectively modulates the energy level difference at the interface and does not significantly influence adjacent layers overall. However, interfaces can drastically affect adjoining layers in ultrathin devices, which are essential for next‐generation electronics with high integrity, excellent performance, and low power consumption. In particular, the interfacial effect is pronounced in ultrathin semiconductors, which have a weak electric field screening effect. Herein, the substantial interfacial impact on the ultrathin silicon is shown, the p‐ to n‐type inversion of the semiconductor solely through the deposition of a self‐assembled monolayer (SAM) without external bias. The effects of SAMs with different interfacial dipoles are investigated by using Hall measurement and surface analytic techniques, such as UPS, XPS, and KPFM. Furthermore, the lateral electronic junction of the ultrathin silicon is engineered by the regioselective deposition of SAMs with opposite dipoles, and the device exhibits rectification behavior. When the interfacial dipole of SAM is manipulated, the rectification ratio changes sensitively, and thus the fabricated diode shows potential to be developed as a sensing platform.

The propagation test of lithium-ion battery pack was conducted in an environment of air and insulating oil. The test results showed the difference in the phenomenon in which fire propagation to surrounding cells, when a cell composing a battery pack is thermal runaway in two environments. The temperature of the cells in the battery pack was measured during propagation test. A cycle test was also conducted to check whether there was an abnormality in cell performance immersed in insulating oil. The residual capacity and internal resistance, insulation resistance data of the cell are presented in the two environments.

FINEX process, which utilizes hydrogen (H2) as a part of reductants, has emerged as an environmentally sustainable ironmaking process to meet the upcoming carbon-neutral era. In the H2-enriched atmosphere, local slag holdup in the carbonaceous particle bed may increase due to the increased melting temperature of slags by the rapid reduction of iron oxide and the resulting lower wettability of the carbonaceous materials by liquid slag. In-situ SiC formation on the carbon surface gains much attention as a method to reduce the slag holdup. In this study, as a fundamental study, we investigated the SiC formation on the surface of a graphite substrate under a CO-H2-SiO gas environment at 1873 K. It was found that as the partial pressure of H2 increased, the penetration depth of a SiC layer formed on the graphite surface increased, and the surface roughness became enhanced. A reaction rate analysis revealed that the H2-CO gas mixture accelerated the SiC formation on the graphite surface compared to the N2-CO gas mixture. This effect was attributed to the high bimolecular diffusivity of H2-CO. Our results demonstrate that under a CO-H2-SiO gas environment, the fast diffusion of H2 gas through micropores in the graphite significantly enhances the formation of SiC on the graphite surface. The results obtained in this study show that the acceleration of SiC formation under an H2-enriched atmosphere would improve the wettability of molten slag and reduce the slag holdup in the FINEX process.

This paper proposes a visual map-based position and heading estimation system that is invariant to image rotation and consistent over time, which is achieved by exploiting the radial and azimuthal distributions of semantic segments. To characterize the specific position and heading, a novel concept termed “visual semantic context” is applied, which collects semantics in a polar-coordinated fashion in collaboration with measures of discrepancy. The system then matches visual semantic contexts: one from a semantically segmented aerial image aided by deep learning technology and others from a semantics-labeled database. Two-stage minimization alleviates the expensive computation of an exhaustive search. The first stage marginalizes the heading and coarsely searches for positions. At the same time, the Kolmogorov–Smirnov test significantly reduces the search domain by rejecting unlikely candidates, and the second stage refines the estimates. Numerical experiments show that the proposed algorithm fixes the position and heading, is invariant to image rotation, and is also robust to imprecise scale information.

Background: While efforts have been made to differentiate fall risk in older adults using wearable devices and clinical methodologies, technologies are still infancy. We applied a decision tree (DT) algorithm using inertial measurement unit (IMU) sensor data and clinical measurements to generate high performance classification models of fall risk of older adults. Objects: This study aims to develop a classification model of fall risk using IMU data and clinical measurements in older adults. Methods: Twenty-six older adults were assessed and categorized into high and low fall risk groups. IMU sensor data were obtained while walking from each group, and features were extracted to be used for a DT algorithm with the Gini index (DT1) and the Entropy index (DT2), which generated classification models to differentiate high and low fall risk groups. Model’s performance was compared and presented with accuracy, sensitivity, and specificity. Results: Accuracy, sensitivity and specificity were 77.8%, 80.0%, and 66.7%, respectively, for DT1; and 72.2%, 91.7%, and 33.3%, respectively, for DT2. Conclusion: Our results suggest that the fall risk classification using IMU sensor data obtained during gait has potentials to be developed for practical use. Different machine learning techniques involving larger data set should be warranted for future research and development.

Abstract Ionovoltaics is a breakthrough concept in energy conversion that harnesses water motion with ion dynamics to generate electrical energy. This phenomenon is based on the interaction between the nanoscopic ionic behavior at the solid–liquid interface and the flow of electrons in a semiconductor electrode. Ionovoltaic research aims to present the most rational and convincing mechanism for the much‐debated principle of energy conversion by water motion through a deeper understanding of solid–liquid interfacial phenomena and to discuss the potential to transform related fields through the development of enabling technologies such as novel energy harvesters, interfacial analysis tools, and bio/chemical sensors. Furthermore, efforts to develop high‐efficiency ionovoltaic device powered by small water droplets indicate a potential contribution to the advancement of green energy systems that complement solar and wind power generation and address environmental pollution and energy shortages. This review paper explores the evolution of energy harvesting technologies using water motion, with a particular focus on ionovoltaics as an emerging field. By establishing the fundamentals, this study investigates solid–liquid interfaces, semiconductor properties, and natural water motion‐driven ionovoltaic phenomena and also highlights that extensive research on complex ion/interface phenomena can have practical applications in diverse industrial fields.

Background: Despite fall prevention strategies suggested by researchers, falls are still a major health concern in older adults. Understanding factors that differentiate successful versus unsuccessful balance recovery may help improve the prevention strategies. Objects: The purpose of this review was to identify biomechanical factors that differentiate successful versus unsuccessful balance recovery in the event of a fall. Methods: The literature was searched through Google Scholar and PubMed. The following keywords were used: ‘falls,‘ ‘protective response,‘ ‘protective strategy,’ ‘automated postural response,’ ‘slips,’ ‘trips,’ ‘stepping strategy,‘ ‘muscle activity,’ ‘balance recovery,‘ ‘successful balance recovery,‘ and ‘failed balance recovery.’ Results: A total of 64 articles were found and reviewed. Most of studies included in this review suggested that kinematics during a fall was important to recover balance successfully. To be successful, appropriate movements were required, which governed by several things depending on the direction and characteristics of the fall. Studies also suggested that lower limb muscle activity and joint moments were important for successful balance recovery. Other factors associated with successful balance recovery included fall direction, age, appropriate protective strategy, overall health, comorbidity, gait speed, sex and anticipation of the fall. Conclusion: This review discusses biomechanical factors related to successful versus unsuccessful balance recovery to help understand falls. Our review should help guide future research, or improve prevention strategies in the area of fall and injuries in older adults.

BackgroundEarly screening of elderly individuals who are at risk of dementia allows timely medical interventions to prevent disease progression. The portable and low-cost electroencephalography (EEG) technique has the potential to serve it.ObjectiveWe examined prefrontal EEG and event-related potential (ERP) variables in association with the predementia stages of Alzheimer’s disease (AD).MethodsOne hundred elderly individuals were recruited from the GARD cohort. The participants were classified into four groups according to their amyloid beta deposition (A+ or A−) and neurodegeneration status (N+ or N−): cognitively normal (CN; A−N−, n = 27), asymptomatic AD (aAD; A + N−, n = 15), mild cognitive impairment (MCI) with AD pathology (pAD; A+N+, n = 16), and MCI with non-AD pathology (MCI(−); A−N+, n = 42). Prefrontal resting-state eyes-closed EEG measurements were recorded for five minutes and auditory ERP measurements were recorded for 8 min. Three variables of median frequency (MDF), spectrum triangular index (STI), and positive-peak latency (PPL) were employed to reflect EEG slowing, temporal synchrony, and ERP latency, respectively.ResultsDecreasing prefrontal MDF and increasing PPL were observed in the MCI with AD pathology. Interestingly, after controlling for age, sex, and education, we found a significant negative association between MDF and the aAD and pAD stages with an odds ratio (OR) of 0.58. Similarly, PPL exhibited a significant positive association with these AD stages with an OR of 2.36. Additionally, compared with the MCI(-) group, significant negative associations were demonstrated by the aAD group with STI and those in the pAD group with MDF with ORs of 0.30 and 0.42, respectively.ConclusionSlow intrinsic EEG oscillation is associated with MCI due to AD, and a delayed ERP peak latency is likely associated with general cognitive impairment. MCI individuals without AD pathology exhibited better cortical temporal synchronization and faster EEG oscillations than those with aAD or pAD.SignificanceThe EEG/ERP variables obtained from prefrontal EEG techniques are associated with early cognitive impairment due to AD and non-AD pathology. This result suggests that prefrontal EEG/ERP metrics may serve as useful indicators to screen elderly individuals’ early stages on the AD continuum as well as overall cognitive impairment.

Abstract Herein, the direct growth of polar orthorhombic phase in Hf0.5Zr0.5O2 (HZO) thin films is reported using Pulsed Laser Deposition (PLD). The growth of HZO onto a preheated (700 °C) silicon substrate mimics the rapid thermal annealing, which allows the formation of smaller crystallites (~9.7 nm) with large surface energy leading to the stabilization of metastable orthorhombic phase. Unlike atomic layer deposition (ALD) of HZO, PLD is more advantageous for depositing highly crystalline thin films through optimized parameters, such as laser fluence and background gas pressure. Further, the PLD-HZO is integrated with HfO2 dielectric and the resulting gate stacks have been used in the bottom gate FET architecture-‘Si//PLD-HZO/HfO2/MoS2//Ti/Au’. The NCFETs have yielded a sub-thermionic subthreshold swing (SS for = 33.03 ± 8.7 mV/dec. and SS rev = 36.4 ± 7.7 mV/dec.) and a negligible hysteresis (~28 mV), which is capable in realizing low power integrated digital/analog circuits.

The sintering process is a thermal agglomeration process, and it is accompanied by chemical reactions. In this process, a mixture of iron ore fines, flux, and coal particles is heated to about 1300 °C–1480 °C in a sinter bed. The strength and reducibility properties of iron ore sinter are obtained by liquid phase sintering. The silico-ferrite of calcium and aluminum (SFCA) is the main bonding phase found in modern iron ore sinters. Since the physicochemical and crystallographic properties of the SFCA are affected by the chemical composition and mineral phases of iron ores, a crystallographic understanding of iron ores and sintered ore is important to enhance the quality of iron ore sinter. Scrap and by-products from steel mills are expected to be used in the iron ore sintering process as recyclable resources, and in such a case, the crystallographic properties of iron ore sinter will be affected using these materials. The objective of this paper is to present a short review on research related to mineral phases and structural properties of iron ore and sintered ore.

BACKGROUND AND OBJECTIVE: Neuromyelitis optica (NMO) is an inflammatory demyelinating disorder of the central nervous system with a relapsing and remitting course. We aimed to identify factors associated with the time to next attack, including the effect of the natural disease course and the diverse treatment regimens, by applying a longitudinal statistical analysis to the individual attacks of each patient. METHODS: In total, 184 acute attacks among 58 patients with either NMO or NMO spectrum disorder with anti-aquaporin-4 antibody were assessed retrospectively. Patient demographics, clinical characteristics at each attack, and type of treatment during inter-attack periods were assessed. The dependent variable was defined as the time from each attack to the next attack (inter-attack interval). An exponential accelerated failure time model with shared gamma frailty was adapted for statistical analysis. RESULTS: A multivariable analysis revealed that the time from each attack to the next attack in NMO increased independently by 1.31 times (95% confidence interval (CI), 1.02-1.67; p = 0.035) with each additional cumulative attack experienced, by 5.34 times (95% CI, 1.57-18.13; p = 0.007) with combined azathioprine treatment and continued oral prednisolone, and by 4.26 times (95% CI, 1.09-16.61; p = 0.037) with rituximab treatment. CONCLUSION: The time to next attack in NMO can increase naturally in the later stages of the disease as the number of cumulative attacks increases. Nevertheless, both combined azathioprine treatment with continued oral prednisolone and rituximab treatment were also associated with a longer time to next attack, independently of the natural disease course of NMO.