CAST: Cross-Attention in Space and Time for Video Action Recognition

Recognizing human actions in videos requires spatial and temporal understanding. Most existing action recognition models lack a balanced spatio-temporal understanding of videos. In this work, we propose a novel two-stream architecture, called Cross-Attention in Space and Time (CAST), that achieves a balanced spatio-temporal understanding of videos using only RGB input. Our proposed bottleneck cross-attention mechanism enables the spatial and temporal expert models to exchange information and make synergistic predictions, leading to improved performance. We validate the proposed method with extensive experiments on public benchmarks with different characteristics: EPIC-KITCHENS-100, Something-Something-V2, and Kinetics-400. Our method consistently shows favorable performance across these datasets, while the performance of existing methods fluctuates depending on the dataset characteristics.Comment: This is an accepted NeurIPS 2023. Project webpage is available at https://jong980812.github.io/CAST.github.io/ Code is available at https://github.com/KHU-VLL/CAS

Market Reaction to the Disclosure of Unfunded Pension Benefit Obligation Write-Off Policies in Japan

This paper investigates whether stock prices react to the corporate disclosures of pension cost write-off policy, and if they do, whether the direction and the magnitude of such reaction are associated with the level of unfunded pension benefit obligation and firm profitability in the Japanese context. The results of the analysis partially support the signaling explanation whereby financially affordable firms with large amount of unfunded obligations are expected to be more likely to adopt shorter term based write-offs, which are rewarded with favorable price reactions

Safe and Efficient Trajectory Optimization for Autonomous Vehicles using B-spline with Incremental Path Flattening

B-spline-based trajectory optimization is widely used for robot navigation due to its computational efficiency and convex-hull property (ensures dynamic feasibility), especially as quadrotors, which have circular body shapes (enable efficient movement) and freedom to move each axis (enables convex-hull property utilization). However, using the B-spline curve for trajectory optimization is challenging for autonomous vehicles (AVs) because of their vehicle kinodynamics (rectangular body shapes and constraints to move each axis). In this study, we propose a novel trajectory optimization approach for AVs to circumvent this difficulty using an incremental path flattening (IPF), a disc type swept volume (SV) estimation method, and kinodynamic feasibility constraints. IPF is a new method that can find a collision-free path for AVs by flattening path and reducing SV using iteratively increasing curvature penalty around vehicle collision points. Additionally, we develop a disc type SV estimation method to reduce SV over-approximation and enable AVs to pass through a narrow corridor efficiently. Furthermore, a clamped B-spline curvature constraint, which simplifies a B-spline curvature constraint, is added to dynamical feasibility constraints (e.g., velocity and acceleration) for obtaining the kinodynamic feasibility constraints. Our experimental results demonstrate that our method outperforms state-of-the-art baselines in various simulated environments. We also conducted a real-world experiment using an AV, and our results validate the simulated tracking performance of the proposed approach.Comment: 14 pages, 21 figures, 4 tables, 3 algorithm

Engineering vacancy and hydrophobicity of two-dimensional TaTe2 for efficient and stable electrocatalytic N2 reduction

Demand for ammonia continues to increase to sustain the growing global population. The direct electrochemical N2 reduction reaction (NRR) powered by renewable electricity offers a promising carbon-neutral and sustainable strategy for manufacturing NH3, yet achieving this remains a grand challenge. Here, we report a synergistic strategy to promote ambient NRR for ammonia production by tuning the Te vacancies (VTe) and surface hydrophobicity of two-dimensional TaTe2 nanosheets. Remarkable NH3 faradic efficiency of up to 32.2% is attained at a mild overpotential, which is largely maintained even after 100 h of consecutive electrolysis. Isotopic labeling validates that the N atoms of formed NH4+ originate from N2. In situ X-ray diffraction indicates preservation of the crystalline structure of TaTe2 during NRR. Further density functional theory calculations reveal that the potential-determining step (PDS) is ∗NH2 + (H+ + e–) → NH3 on VTe-TaTe2 compared with that of ∗ + N2 + (H+ + e–) → ∗N–NH on TaTe2. We identify that the edge plane of TaTe2 and VTe serve as the main active sites for NRR. The free energy change at PDS on VTe-TaTe2 is comparable with the values at the top of the NRR volcano plots on various transition metal surfaces

A K-Means Clustering Algorithm to Determine Representative Operational Profiles of a Ship Using AIS Data

Defining the appropriate functional requirements in the early ship design stage is important in order that costs that are caused by the over- or under-specified functional capabilities do not increase. This paper presents a K-means clustering algorithm for the determination of functional requirements. It uses automatic identification system (AIS) data from a reference ship to determine the representative operational profiles, which can support decision-makers in defining the functional requirements of ships that will be performing similar missions as those of the reference ship. In a case study, we used this method as part of a ship design project, in which the functional requirements of a battery-only electric ship are defined using AIS data from a reference ship. Results indicate that the cost can be reduced by determining the functional requirements using the proposed method

A K-Means Clustering Algorithm to Determine Representative Operational Profiles of a Ship Using AIS Data

Defining the appropriate functional requirements in the early ship design stage is important in order that costs that are caused by the over- or under-specified functional capabilities do not increase. This paper presents a K-means clustering algorithm for the determination of functional requirements. It uses automatic identification system (AIS) data from a reference ship to determine the representative operational profiles, which can support decision-makers in defining the functional requirements of ships that will be performing similar missions as those of the reference ship. In a case study, we used this method as part of a ship design project, in which the functional requirements of a battery-only electric ship are defined using AIS data from a reference ship. Results indicate that the cost can be reduced by determining the functional requirements using the proposed method

H₂ Plasma and PMA Effects on PEALD-Al₂O₃ Films with Different O₂ Plasma Exposure Times for CIS Passivation Layers

In this study, the electrical properties of Al2O3 film were analyzed and optimized to improve the properties of the passivation layer of CMOS image sensors (CISs). During Al2O3 deposition processing, the O2 plasma exposure time was adjusted, and H2 plasma treatment as well as post-metallization annealing (PMA) were performed as posttreatments. The flat-band voltage (Vfb) was significantly shifted (ΔVfb = 2.54 V) in the case of the Al2O3 film with a shorter O2 plasma exposure time; however, with a longer O2 plasma exposure time, Vfb was slightly shifted (ΔVfb = 0.61 V) owing to the reduction in the carbon impurity content. Additionally, the as-deposited Al2O3 sample with a shorter O2 plasma exposure time had a larger number of interface traps (interface trap density, Dit = 8.98 × 1013 eV−1·cm−2). However, Dit was reduced to 1.12 × 1012 eV−1·cm−2 by increasing the O2 plasma exposure time and further reduced after PMA. Consequently, we fabricated an Al2O3 film suitable for application as a CIS passivation layer with a reduced number of interface traps. However, the Al2O3 film with increased O2 plasma exposure time deteriorated owing to plasma damage after H2 plasma treatment, which is a method of reducing carbon impurity content. This deterioration was validated using the C–V hump and breakdown characteristics

Ursodeoxycholic acid may protect from severe acute respiratory syndrome coronavirus 2 Omicron variant by reducing angiotensin‐converting enzyme 2

Abstract The SARS‐CoV‐2 caused COVID‐19 pandemic has posed a global health hazard. While some vaccines have been developed, protection against viral infection is not perfect because of the urgent approval process and the emergence of mutant SARS‐CoV‐2 variants. Here, we employed UDCA as an FXR antagonist to regulate ACE2 expression, which is one of the key pathways activated by SARS‐CoV‐2 Delta variant infection. UDCA is a well‐known reagent of liver health supplements and the only clinically approved bile acid. In this paper, we investigated the protective efficacy of UDCA on Omicron variation, since it has previously been verified for protection against Delta variant. When co‐housing with an Omicron variant‐infected hamster group resulted in spontaneous airborne transmission, the UDCA pre‐supplied group was protected from weight loss relative to the non‐treated group at 4 days post‐infection by more than 5%–10%. Furthermore, UDCA‐treated groups had a 3‐fold decrease in ACE2 expression in nasal cavities, as well as reduced viral expressing genes in the respiratory tract. Here, the data show that the UDCA serves an alternative option for preventive drug, providing SARS‐CoV‐2 protection against not only Delta but also Omicron variant. Our results of this study will help to propose drug‐repositioning of UDCA from liver health supplement to preventive drug of SARS‐CoV‐2 infection

Self-Assembled Monolayer of a Redox-Active Calix[4]arene: Voltammetric Recognition of the Ba^(2+) Ion in Aqueous Media

The Redox-active monolayer of a novel calix[4]arene recognizing redox-inactive ionic species by voltammetry is reported. Calix[4]arene-disulfide-diquinone, which is not only redox-active but is also a highly selective ionophore for the Ba^(2+) ion, spontaneously forms a stable and dense monolayer film on gold. The redox-active calixarene monolayer selectively recognizes Ba^(2+) ion in aqueous media, and the voltammetric signals are proportional to the ionic concentration. A new voltammetric peak can be detected by square-wave voltammetry upon adding a dilute solution containing Ba^(2+) ion having a concentration as low as 1.0 x 10^(-6) M. The Langmuir plot (1/i_(p) vs 1/[Ba^(2+)]) shows a linear slope in the range from 1.0 x 10^(-6) M to 1.0 x 10^(-4) M. This modified electrode does not show any significant interference from alkali and alkaline earth metal ions except for Sr^(2+) and Ca^(2+). Only 100- and 500-fold concentrations of Sr^(2+) and Ca^(2+) ions, respectively, can lead to voltammetric responses comparable to that of Ba^(2+)