Integrated In-vehicle Monitoring System Using 3D Human Pose Estimation and Seat Belt Segmentation

Recently, along with interest in autonomous vehicles, the importance of monitoring systems for both drivers and passengers inside vehicles has been increasing. This paper proposes a novel in-vehicle monitoring system the combines 3D pose estimation, seat-belt segmentation, and seat-belt status classification networks. Our system outputs various information necessary for monitoring by accurately considering the data characteristics of the in-vehicle environment. Specifically, the proposed 3D pose estimation directly estimates the absolute coordinates of keypoints for a driver and passengers, and the proposed seat-belt segmentation is implemented by applying a structure based on the feature pyramid. In addition, we propose a classification task to distinguish between normal and abnormal states of wearing a seat belt using results that combine 3D pose estimation with seat-belt segmentation. These tasks can be learned simultaneously and operate in real-time. Our method was evaluated on a private dataset we newly created and annotated. The experimental results show that our method has significantly high performance that can be applied directly to real in-vehicle monitoring systems.Comment: AAAI 2022 workshop AI for Transportation accepte

Video-Based Stylized Rendering using Frame Difference

In this paper, we suggest video based stylized rendering using frame difference. Stylized rendering using video frame has a temporal problem that occurs a difference between the previous and current frame. To reduce the temporal problem, we generate reference maps using temporal frame difference in correction and rendering steps. A correction method using reference maps can be reduced flickering effect caused by frame difference between the previous and current frame. We use a background map, an average map, and a quadtree-based summed area table as reference maps. Among these reference maps, the method using quadtree based summed area table can completely remove a flickering and popping effect. Also, a post-blurring method using bilateral filtering can be represented smooth, stylized rendering by removing unnecessary noise. Suggested stylized rendering system can be used in various fields such as visual art, advertisement, game and movie for stylized image contents generation

Biocontrol potential of Chitinophaga flava HK235 producing antifungal-related peptide chitinocin

Botrytis cinerea is a necrotrophic fungal pathogen with an extremely broad host range, causing significant economic losses in agricultural production. In this study, we discovered a culture filtrate of bacterial strain HK235, which was identified as Chitinophaga flava, exhibiting high levels of antifungal activity against B. cinerea. From the HK235 culture filtrate, we isolated a new antimicrobial peptide molecule designated as chitinocin based on activity-guided fractionation followed by characterization of the amino acid composition and spectroscopic analyses. The HK235 culture filtrate and chitinocin completely inhibited both conidial germination and mycelial growth of B. cinerea at a concentration of 20% and 200 μg/mL, respectively. In addition to antibiosis against B. cinerea, the active compound chitinocin had a broad antifungal and antibacterial activity in vitro. When tomato plants were treated with the culture filtrate and chitinocin, the treatment strongly reduced the development of gray mold disease in a concentration-dependent manner compared to the untreated control. Here, considering the potent antifungal property in vitro and in vivo, we present the biocontrol potential of C. flava HK235 for the first time

Lightweight Monocular Depth Estimation via Token-Sharing Transformer

Depth estimation is an important task in various robotics systems and applications. In mobile robotics systems, monocular depth estimation is desirable since a single RGB camera can be deployable at a low cost and compact size. Due to its significant and growing needs, many lightweight monocular depth estimation networks have been proposed for mobile robotics systems. While most lightweight monocular depth estimation methods have been developed using convolution neural networks, the Transformer has been gradually utilized in monocular depth estimation recently. However, massive parameters and large computational costs in the Transformer disturb the deployment to embedded devices. In this paper, we present a Token-Sharing Transformer (TST), an architecture using the Transformer for monocular depth estimation, optimized especially in embedded devices. The proposed TST utilizes global token sharing, which enables the model to obtain an accurate depth prediction with high throughput in embedded devices. Experimental results show that TST outperforms the existing lightweight monocular depth estimation methods. On the NYU Depth v2 dataset, TST can deliver depth maps up to 63.4 FPS in NVIDIA Jetson nano and 142.6 FPS in NVIDIA Jetson TX2, with lower errors than the existing methods. Furthermore, TST achieves real-time depth estimation of high-resolution images on Jetson TX2 with competitive results.Comment: ICRA 202

Key Intrinsic Connectivity Networks for Individual Identification With Siamese Long Short-Term Memory

In functional magnetic resonance imaging (fMRI) analysis, many studies have been conducted on inter-subject variability as well as intra-subject reproducibility. These studies indicate that fMRI could have unique characteristics for individuals. In this study, we hypothesized that the dynamic information during 1 min of fMRI was unique and repetitive enough for each subject, so we applied long short-term memory (LSTM) using initial time points of dynamic resting-state fMRI for individual identification. Siamese network is used to obtain robust individual identification performance without additional learning on a new dataset. In particular, by adding a new structure called region of interest–wise average pooling (RAP), individual identification performance could be improved, and key intrinsic connectivity networks (ICNs) for individual identification were also identified. The average performance of individual identification was 97.88% using the test dataset in eightfold cross-validation analysis. Through the visualization of features learned by Siamese LSTM with RAP, ICNs spanning the parietal region were observed as the key ICNs in identifying individuals. These results suggest the key ICNs in fMRI could represent individual uniqueness

Optimization of protoplast regeneration in the model plant Arabidopsis thaliana

Background Plants have a remarkable reprogramming potential, which facilitates plant regeneration, especially from a single cell. Protoplasts have the ability to form a cell wall and undergo cell division, allowing whole plant regeneration. With the growing need for protoplast regeneration in genetic engineering and genome editing, fundamental studies that enhance our understanding of cell cycle re-entry, pluripotency acquisition, and de novo tissue regeneration are essential. To conduct these studies, a reproducible and efficient protoplast regeneration method using model plants is necessary. Results Here, we optimized cell and tissue culture methods for improving protoplast regeneration efficiency in Arabidopsis thaliana. Protoplasts were isolated from whole seedlings of four different Arabidopsis ecotypes including Columbia (Col-0), Wassilewskija (Ws-2), Nossen (No-0), and HR (HR-10). Among these ecotypes, Ws-2 showed the highest potential for protoplast regeneration. A modified thin alginate layer was applied to the protoplast culture at an optimal density of 1 × 106 protoplasts/mL. Following callus formation and de novo shoot regeneration, the regenerated inflorescence stems were used for de novo root organogenesis. The entire protoplast regeneration process was completed within 15 weeks. The in vitro regenerated plants were fertile and produced morphologically normal progenies. Conclusion The cell and tissue culture system optimized in this study for protoplast regeneration is efficient and reproducible. This method of Arabidopsis protoplast regeneration can be used for fundamental studies on pluripotency establishment and de novo tissue regeneration.This work was supported by the Samsung Science and Technology Foundation under Project Number SSTF-BA2001-10

Primary Alveolar Soft Part Sarcoma of the Lung

Alveolar soft part sarcoma (ASPS) is a rare epithelial-like soft tissue sarcoma. The two main sites of its occurrence are the lower extremities in adults and the head and neck in children. Primary pulmonary involvement of this sarcoma, without evidence of soft tissue tumor elsewhere, is very exceptional. We present a case of primary ASPS of the lung in a 42-yr-old woman. A computed tomographic scan of the thorax demonstrated a well-circumscribed, solid tumor located in the right upper lobe. The mass was resected by right upper lobectomy. After 5 months, three metastatic lesions, involving lumbar vertebrae and occipital scalp, were found. Histologically, the tumor consisted of alveolar nests of large polygonal tumor cells, the cytoplasm of which frequently revealed periodic acid-Schiff-positive, diastase-resistant intracytoplasmic rod-like structures. On immunohistochemical staining, the tumor cells were positive only for vimentin and alpha-smooth muscle actin. Ultrastuctural study using electron microscopy revealed characteristic electron-dense, rhomboid intracytoplasmic crystals

Optimization of protoplast regeneration in the model plant Arabidopsis thaliana

Background Plants have a remarkable reprogramming potential, which facilitates plant regeneration, especially from a single cell. Protoplasts have the ability to form a cell wall and undergo cell division, allowing whole plant regeneration. With the growing need for protoplast regeneration in genetic engineering and genome editing, fundamental studies that enhance our understanding of cell cycle re-entry, pluripotency acquisition, and de novo tissue regeneration are essential. To conduct these studies, a reproducible and efficient protoplast regeneration method using model plants is necessary. Results Here, we optimized cell and tissue culture methods for improving protoplast regeneration efficiency in Arabidopsis thaliana. Protoplasts were isolated from whole seedlings of four different Arabidopsis ecotypes including Columbia (Col-0), Wassilewskija (Ws-2), Nossen (No-0), and HR (HR-10). Among these ecotypes, Ws-2 showed the highest potential for protoplast regeneration. A modified thin alginate layer was applied to the protoplast culture at an optimal density of 1 x 10(6) protoplasts/mL. Following callus formation and de novo shoot regeneration, the regenerated inflorescence stems were used for de novo root organogenesis. The entire protoplast regeneration process was completed within 15 weeks. The in vitro regenerated plants were fertile and produced morphologically normal progenies. Conclusion The cell and tissue culture system optimized in this study for protoplast regeneration is efficient and reproducible. This method of Arabidopsis protoplast regeneration can be used for fundamental studies on pluripotency establishment and de novo tissue regeneration.Y

Epigallocatechin-3-gallate protects toluene diisocyanate-induced airway inflammation in a murine model of asthma

AbstractEpigallocatechin-3-gallate (EGCG), a major form of tea catechin, has anti-allergic properties. To elucidate the anti-allergic mechanisms of EGCG, we investigated its regulation of matrix metalloproteinase (MMP-9) expression in toluene diisocyanate (TDI)-inhalation lung tissues as well as TNF-α and Th2 cytokine (IL-5) production in BAL fluid. Compared with untreated asthmatic mice those administrated with EGCG had significantly reduced asthmatic reaction. Also, increased reactive oxygen species (ROS) generation by TDI inhalation was diminished by administration of EGCG in BAL fluid. These results suggest that EGCG regulates inflammatory cell migration possibly by suppressing MMP-9 production and ROS generation, and indicate that EGCG may be useful as an adjuvant therapy for bronchial asthma