Topological flat bands in rhombohedral tetralayer and multilayer graphene on hexagonal boron nitride moire superlattices

We show that rhombohedral four-layer graphene (4LG) nearly aligned with a hexagonal boron nitride (hBN) substrate often develops nearly flat isolated low energy bands with non-zero valley Chern numbers. The bandwidths of the isolated flatbands are controllable through an electric field and twist angle, becoming as narrow as $\sim10~$meV for interlayer potential differences between top and bottom layers of $|\Delta|\approx 10\sim15~$meV and $\theta \sim 0.5^{\circ}$ at the graphene and boron nitride interface. The local density of states (LDOS) analysis shows that the nearly flat band states are associated to the non-dimer low energy sublattice sites at the top or bottom graphene layers and their degree of localization in the moire superlattice is strongly gate tunable, exhibiting at times large delocalization despite of the narrow bandwidth. We verified that the first valence bands' valley Chern numbers are $C^{\nu=\pm1}_{V1} = \pm n$, proportional to layer number for $n$LG/BN systems up to $n = 8$ rhombohedral multilayers

Surface modification through oxide ALD to improve oxygen exchange rate on perovskite surface

Segregation and phase separation on perovskite oxide (ABO3) surface have been considered as a key detrimental factor to the performance of energy conversion devices such as solid oxide/electrolysis cells. Recently, the overcoat of less reducible cations has been suggested as a way to suppress the surface Sr segregation on Sr-containing perovskite oxides. However, the detailed requirements of the coating layer to sufficiently stabilize the perovskite surface hasn’t been systematically investigated yet. In this wok, we fabricate La0.6Sr0.4CoO3 (LSC) thin-film model electrode via pulse layer deposition and observe how the degree of Sr segregation varies with the type and thickness of the overcoat layer. Al2O3 and HfO2 with different thickness are coated on LSC via ALD, and the oxygen exchange rate of both bare and ALD-coated samples is measured via electrical conductivity relaxation. It is found that both Al2O3 and HfO2 layers suppress the Sr segregation only within a narrow thickness range, i.e., 1-2 nm for Al2O3 and 0.2 – 0.4 nm for HfO2, respectively. These observations are discussed with solubility and diffusivity of Al and Hf in the host oxide lattice, providing a critical guideline of a new surface modification method to stabilize the perovskite surface at high temperatures. Please click Additional Files below to see the full abstract

Towards Good Practices for Missing Modality Robust Action Recognition

Standard multi-modal models assume the use of the same modalities in training and inference stages. However, in practice, the environment in which multi-modal models operate may not satisfy such assumption. As such, their performances degrade drastically if any modality is missing in the inference stage. We ask: how can we train a model that is robust to missing modalities? This paper seeks a set of good practices for multi-modal action recognition, with a particular interest in circumstances where some modalities are not available at an inference time. First, we study how to effectively regularize the model during training (e.g., data augmentation). Second, we investigate on fusion methods for robustness to missing modalities: we find that transformer-based fusion shows better robustness for missing modality than summation or concatenation. Third, we propose a simple modular network, ActionMAE, which learns missing modality predictive coding by randomly dropping modality features and tries to reconstruct them with the remaining modality features. Coupling these good practices, we build a model that is not only effective in multi-modal action recognition but also robust to modality missing. Our model achieves the state-of-the-arts on multiple benchmarks and maintains competitive performances even in missing modality scenarios. Codes are available at https://github.com/sangminwoo/ActionMAE.Comment: AAAI 202

Between comments and repeat visit: capturing repeat visitors with a hybrid approach

Purpose Understanding customers' revisiting behavior is highlighted in the field of service industry and the emergence of online communities has enabled customers to express their prior experience. Thus, purpose of this study is to investigate customers' reviews on an online hotel reservation platform, and explores their postbehaviors from their reviews. Design/methodology/approach The authors employ two different approaches and compare the accuracy of predicting customers' post behavior: (1) using several machine learning classifiers based on sentimental dimensions of customers' reviews and (2) conducting the experiment consisted of two subsections. In the experiment, the first subsection is designed for participants to predict whether customers who wrote reviews would visit the hotel again (referred to as Prediction), while the second subsection examines whether participants want to visit one of the particular hotels when they read other customers' reviews (dubbed as Decision). Findings The accuracy of the machine learning approaches (73.23%) is higher than that of the experimental approach (Prediction: 58.96% and Decision: 64.79%). The key reasons of users' predictions and decisions are identified through qualitative analyses. Originality/value The findings reveal that using machine learning approaches show the higher accuracy of predicting customers' repeat visits only based on employed sentimental features. With the novel approach of integrating customers' decision processes and machine learning classifiers, the authors provide valuable insights for researchers and providers of hospitality services

Optimization of Airport Surface Traffic: A Case-Study of Incheon International Airport

This study aims to develop a controllers decision support tool for departure and surface management of ICN. Airport surface traffic optimization for Incheon International Airport (ICN) in South Korea was studied based on the operational characteristics of ICN and airspace of Korea. For surface traffic optimization, a multiple runway scheduling problem and a taxi scheduling problem were formulated into two Mixed Integer Linear Programming (MILP) optimization models. The Miles-In-Trail (MIT) separation constraint at the departure fix shared by the departure flights from multiple runways and the runway crossing constraints due to the taxi route configuration specific to ICN were incorporated into the runway scheduling and taxiway scheduling problems, respectively. Since the MILP-based optimization model for the multiple runway scheduling problem may be computationally intensive, computation times and delay costs of different solving methods were compared for a practical implementation. This research was a collaboration between Korea Aerospace Research Institute (KARI) and National Aeronautics and Space Administration (NASA)

Population-attributable causes of cancer in Korea : obesity and physical inactivity

Changes in lifestyle including obesity epidemic and reduced physical activity influenced greatly to increase the cancer burden in Korea. The purpose of the current study was to perform a systematic assessment of cancers attributable to obesity and physical inactivity in Korea. Gender- and cancer site-specific population-attributable fractions (PAF) were estimated using the prevalence of overweight and obesity in 1992-1995 from a large-scale prospective cohort study, the prevalence of low physical activity in 1989 from a Korean National Health Examination Survey, and pooled relative risk estimates from Korean epidemiological studies. The overall PAF was then estimated using 2009 national cancer incidence data from the Korea Central Cancer Registry. Excess body weight was responsible for 1,444 (1.5%) and 2,004 (2.2%) cancer cases among men and women, respectively, in 2009 in Korea. Among men, 6.8% of colorectal, 2.9% of pancreatic, and 16.0% of kidney cancer was attributable to excess body weight. In women, 6.6% of colorectal, 3.9% of pancreatic, 18.7% of kidney, 8.2% of postmenopausal breast, and 32.7% of endometrial cancer was attributable to excess body weight. Low leisure-time physical activity accounted for 8.8% of breast cancer, whereas the PAF for overall cancer was low (0.1% in men, 1.4% in women). Projections suggest that cancers attributable to obesity will increase by 40% in men and 16% in women by 2020. With a significantly increasing overweight and physically inactive population, and increasing incidence of breast and colorectal cancers, Korea faces a large cancer burden attributable to these risk factors. Had the obese population of Korea remained stable, a large portion of obesity-related cancers could have been avoided. Efficient cancer prevention programs that aim to reduce obesity- and physical inactivity-related health problems are essential in Korea

Operational Characteristics Identification and Simulation Model Verification for Incheon International Airport

Incheon International Airport (ICN) is one of the hub airports in East Asia. Airport operations at ICN have been growing more than 5% per year in the past five years. According to the current airport expansion plan, a new passenger terminal will be added and the current cargo ramp will be expanded in 2018. This expansion project will bring 77 new stands without adding a new runway to the airport. Due to such continuous growth in airport operations and future expansion of the ramps, it will be highly likely that airport surface traffic will experience more congestion, and therefore, suffer from efficiency degradation. There is a growing awareness in aviation research community of need for strategic and tactical surface scheduling capabilities for efficient airport surface operations. Specific to ICN airport operations, a need for A-CDM (Airport - Collaborative Decision Making) or S-CDM(Surface - Collaborative Decision Making), and controller decision support tools for efficient air traffic management has arisen since several years ago. In the United States, there has been independent research efforts made by academia, industry, and government research organizations to enhance efficiency and predictability of surface operations at busy airports. Among these research activities, the Spot and Runway Departure Advisor (SARDA) developed and tested by National Aeronautics and Space Administration (NASA) is a decision support tool to provide tactical advisories to the controllers for efficient surface operations. The effectiveness of SARDA concept, was successfully verified through the human-in-the-loop (HITL) simulations for both spot release and runway operations advisories for ATC Tower controllers of Dallas/Fort Worth International Airport (DFW) in 2010 and 2012, and gate pushback advisories for the ramp controller of Charlotte/Douglas International Airport (CLT) in 2014. The SARDA concept for tactical surface scheduling is further enhanced and is being integrated into NASA's Airspace Technology Demonstration - 2 (ATD-2) project for technology demonstration of Integrated Arrival/Departure/Surface (ADS) operations at CLT. This study is a part of the international research collaboration between KAIA (Korea Agency for Infrastructure Technology Advancement)/KARI (Korea Aerospace Research Institute) and NASA, which is being conducted to validate the effectiveness of SARDA concept as a controller decision support tool for departure and surface management of ICN. This paper presents the preliminary results of the collaboration effort. It includes investigation of the operational environment of ICN, data analysis for identification of the operational characteristics of the airport, construction and verification of airport simulation model using Surface Operations Simulator and Scheduler (SOSS), NASA's fast-time simulation tool

Reproductive and Hormonal Factors Associated with Fatty or Dense Breast Patterns among Korean Women

PURPOSE: Dense breasts have been suggested as a risk factor for breast cancer, but controversy still remains. This study evaluates the association of reproductive and hormonal factors with dense breasts among Korean women. MATERIALS AND METHODS: Using a cross-sectional design, 516 women were recruited and classified for breast density patterns as being either fatty or dense, using the Breast Imaging Reporting and Data System (BI-RADS) of the American College of Radiology. Univariate and multivariate logistic regression models were used for statistical analysis. RESULTS: In univariate logistic regression, older age, higher body mass index, older age at menarche, and oral contraceptive use were associated with more fatty breasts. On the contrary, longer duration of education, alcohol consumption, lower parity, menopause and use of hormone replacement therapy were associated with dense breasts. After adjustment, age and body mass index were inversely associated with breast density (p-value for trend <0.01, respectively), whereas nulliparous and premenopausal status were positively associated. Compared to women who had ≥2 children, nulliparous women had an 11.8-fold increase of dense breasts (p-value for trend <0.01). Compared to postmenopausal women, premenopausal women had 2.4-fold increase of dense breasts (odds ratio, 2.42; 95% confidence interval, 1.36 to 4.32). CONCLUSION: Young age, lower body mass index, lower parity, and premenopausal status were significantly associated with dense breasts in Koreaope

Acid-Sensing Ion Channel 2a (ASIC2a) Promotes Surface Trafficking of ASIC2b via Heteromeric Assembly

Acid-sensing ion channels (ASICs) are proton-activated cation channels that play important roles as typical proton sensors during pathophysiological conditions and normal synaptic activities. Among the ASIC subunits, ASIC2a and ASIC2b are alternative splicing products from the same gene, ACCN1. It has been shown that ASIC2 isoforms have differential subcellular distribution: ASIC2a targets the cell surface by itself, while ASIC2b resides in the ER. However, the underlying mechanism for this differential subcellular localization remained to be further elucidated. By constructing ASIC2 chimeras, we found that the first transmembrane (TM1) domain and the proximal post-TM1 domain (17 amino acids) of ASIC2a are critical for membrane targeting of the proteins. We also observed that replacement of corresponding residues in ASIC2b by those of ASIC2a conferred proton-sensitivity as well as surface expression to ASIC2b. We finally confirmed that ASIC2b is delivered to the cell surface from the ER by forming heteromers with ASIC2a, and that the N-terminal region of ASIC2a is additionally required for the ASIC2a-dependent membrane targeting of ASIC2b. Together, our study supports an important role of ASIC2a in membrane targeting of ASIC2b.1