401 research outputs found

    A critical study of housing and sustainability: a Japanese exemplar

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    Prompt-Guided Zero-Shot Anomaly Action Recognition using Pretrained Deep Skeleton Features

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    This study investigates unsupervised anomaly action recognition, which identifies video-level abnormal-human-behavior events in an unsupervised manner without abnormal samples, and simultaneously addresses three limitations in the conventional skeleton-based approaches: target domain-dependent DNN training, robustness against skeleton errors, and a lack of normal samples. We present a unified, user prompt-guided zero-shot learning framework using a target domain-independent skeleton feature extractor, which is pretrained on a large-scale action recognition dataset. Particularly, during the training phase using normal samples, the method models the distribution of skeleton features of the normal actions while freezing the weights of the DNNs and estimates the anomaly score using this distribution in the inference phase. Additionally, to increase robustness against skeleton errors, we introduce a DNN architecture inspired by a point cloud deep learning paradigm, which sparsely propagates the features between joints. Furthermore, to prevent the unobserved normal actions from being misidentified as abnormal actions, we incorporate a similarity score between the user prompt embeddings and skeleton features aligned in the common space into the anomaly score, which indirectly supplements normal actions. On two publicly available datasets, we conduct experiments to test the effectiveness of the proposed method with respect to abovementioned limitations.Comment: CVPR 202

    Unified Keypoint-based Action Recognition Framework via Structured Keypoint Pooling

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    This paper simultaneously addresses three limitations associated with conventional skeleton-based action recognition; skeleton detection and tracking errors, poor variety of the targeted actions, as well as person-wise and frame-wise action recognition. A point cloud deep-learning paradigm is introduced to the action recognition, and a unified framework along with a novel deep neural network architecture called Structured Keypoint Pooling is proposed. The proposed method sparsely aggregates keypoint features in a cascaded manner based on prior knowledge of the data structure (which is inherent in skeletons), such as the instances and frames to which each keypoint belongs, and achieves robustness against input errors. Its less constrained and tracking-free architecture enables time-series keypoints consisting of human skeletons and nonhuman object contours to be efficiently treated as an input 3D point cloud and extends the variety of the targeted action. Furthermore, we propose a Pooling-Switching Trick inspired by Structured Keypoint Pooling. This trick switches the pooling kernels between the training and inference phases to detect person-wise and frame-wise actions in a weakly supervised manner using only video-level action labels. This trick enables our training scheme to naturally introduce novel data augmentation, which mixes multiple point clouds extracted from different videos. In the experiments, we comprehensively verify the effectiveness of the proposed method against the limitations, and the method outperforms state-of-the-art skeleton-based action recognition and spatio-temporal action localization methods.Comment: CVPR 202

    The methods of using the sword of Shinkage-ryu-kenjutsu and the Contemporary Kendo: The techniques of the body for manipulating a bamboo sword

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    [EN] Nowadays the Japan Kendo Federation guides practitioners to develop mind and body through competing ..

    Genome-wide analysis of aberrant methylation in human breast cancer cells using methyl-DNA immunoprecipitation combined with high-throughput sequencing

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    <p>Abstract</p> <p>Background</p> <p>Cancer cells undergo massive alterations to their DNA methylation patterns that result in aberrant gene expression and malignant phenotypes. However, the mechanisms that underlie methylome changes are not well understood nor is the genomic distribution of DNA methylation changes well characterized.</p> <p>Results</p> <p>Here, we performed methylated DNA immunoprecipitation combined with high-throughput sequencing (MeDIP-seq) to obtain whole-genome DNA methylation profiles for eight human breast cancer cell (BCC) lines and for normal human mammary epithelial cells (HMEC). The MeDIP-seq analysis generated non-biased DNA methylation maps by covering almost the entire genome with sufficient depth and resolution. The most prominent feature of the BCC lines compared to HMEC was a massively reduced methylation level particularly in CpG-poor regions. While hypomethylation did not appear to be associated with particular genomic features, hypermethylation preferentially occurred at CpG-rich gene-related regions independently of the distance from transcription start sites. We also investigated methylome alterations during epithelial-to-mesenchymal transition (EMT) in MCF7 cells. EMT induction was associated with specific alterations to the methylation patterns of gene-related CpG-rich regions, although overall methylation levels were not significantly altered. Moreover, approximately 40% of the epithelial cell-specific methylation patterns in gene-related regions were altered to those typical of mesenchymal cells, suggesting a cell-type specific regulation of DNA methylation.</p> <p>Conclusions</p> <p>This study provides the most comprehensive analysis to date of the methylome of human mammary cell lines and has produced novel insights into the mechanisms of methylome alteration during tumorigenesis and the interdependence between DNA methylome alterations and morphological changes.</p

    A Case of Orbital Xanthogranuloma Treated by Surgical Excision

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    Orbital xanthogranuloma is an uncommon tumor. It is usually associated with a systemic or hematological disease. This report presents a rare case of orbital xanthogranuloma associated with heart disease and thrombocytopenia. A 52-year-old female presented with a bilateral periorbital subcutaneous tumor that had existed for 3 years. Although immunoglobulin levels were within the normal limits, thrombocytopenia, slight anemia and increased levels of C-reactive protein and alkaline phosphatase were observed. The mass was excised successfully. The malar flap elevation technique made it easy to approach the periorbital subcutaneous mass. A histopathological study led to a diagnosis of xanthogranuloma based on the presence of infiltration of histiocytes and Touton-type giant cells
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