Japanese subject-oriented adverbs in a scope-based theory of adverbs

While English exhibits a clausal-manner alternation that is sensitive to where adverbs occur in clausal structure (e.g., Rudely, John left vs. John left rudely), it has not been clear to what extent Japanese behaves the same way. The present study argues, in the spirit of a scope-based theory of adverb licensing, that there is evidence that the Japanese adverbial system is scope-based similarly to its English counterpart. Focusing on mental attitude adverbs, the paper argues that Ernst’s (2002) generalization holds for Japanese: that subject-oriented adverbs lose their otherwise available clausal readings when pure manner adverbs c-command them in the same clause. The paper also claims that clausal mental attitude adverbs must be clause-mates of Tense, which is not reduced to the scope-based theory

Chapter 6 : Histopathological Studies of Pulpectomy in the Deciduous Teeth of Dogs

A study was performed to examine the impact of resorbable root canal filling material, Vitapex, containing calcium hydroxide and iodoform, on the physiological resorption of its roots, succedaneous permanent tooth buds and periodontal tissues. A total of 14 puppies aged 2-5 months were used; teeth were anesthetized, pulps were extirpated and immediate root canal filling was performed. These procedures were carried out in 53 deciduous teeth with 81 root canals, and contralateral intact teeth were used as controls. The animals were bred for 5 to 60 days and were tracked with radiographical and histological examinations. Results obtained were the following: 1: The form of healing observed after the experimental procedures was divided into 2 groups: those healed either by remaining vital pulp tissue or by the periodontal ligament, with 17 and 29 cases, respectively. 2: The resorption of root canal filling material and the physiological root resorption were almost the same in the majority of cases. 3: The rate of physiological root resorption in the experimental group was slightly delayed compared to that of the control group. 4: The remaining pulp tissue lesions, either in short or long term cases, comprised 5 cases of congestion, 3 cases of hemorrhage, 5 cases of mild inflammation, 11 cases of purulent inflammation, and 1 case of atrophy. 5: Periapical lesions, either in short or long term cases, comprised 6 cases with congestion, 12 cases with mild inflammation, 17 cases with purulent inflammation and 7 cases with pathological alveolar bone resorption. 6: In most cases, the lesions did not significantly affect the permanent tooth buds, except for 6 of 81 cases. 7: Pathological grades obtained in this experiment, in a total of 81 cases, were good in 41 cases (50.6%), fair in 20 cases (24.7%) and a failure in 20 cases (24.7%). 8: The best pathological grades after the experimental procedure were obtained in cases in which the root canal filling material was limited within the canal itself (flush) and in those cases which were underfilled. Overextension of root canal filling should be avoided as much as possible. 9: The relationship between root status and pathological grades showed a slightly lower incidence and favorable results with physiological root resorption compared to those without physiological root resorption. 10: In this study, the use of Vitapex for immediate root canal filling after pulp extirpation in canine deciduous teeth produced good results. Vitality of the remaining pulp and periodontal tissue was restored with subsequent physiological root resorption and without adverse effect on succedaneous permanent tooth buds.Editor, Toshiyuki KawakamiLanguage Editor, David M Carlsonviii, 232 p. ill. (some col.

Runner re-identification from single-view video in the open-world setting

In many sports, player re-identification is crucial for automatic video processing and analysis. However, most of the current studies on player re-identification in multi- or single-view sports videos focus on re-identification in the closed-world setting using labeled image dataset, and player re-identification in the open-world setting for automatic video analysis is not well developed. In this paper, we propose a runner re-identification system that directly processes single-view video to address the open-world setting. In the open-world setting, we cannot use labeled dataset and have to process video directly. The proposed system automatically processes raw video as input to identify runners, and it can identify runners even when they are framed out multiple times. For the automatic processing, we first detect the runners in the video using the pre-trained YOLOv8 and the fine-tuned EfficientNet. We then track the runners using ByteTrack and detect their shoes with the fine-tuned YOLOv8. Finally, we extract the image features of the runners using an unsupervised method using the gated recurrent unit autoencoder model. To improve the accuracy of runner re-identification, we use dynamic features of running sequence images. We evaluated the system on a running practice video dataset and showed that the proposed method identified runners with higher accuracy than one of the state-of-the-art models in unsupervised re-identification. We also showed that our unsupervised running dynamic feature extractor was effective for runner re-identification. Our runner re-identification system can be useful for the automatic analysis of running videos.Comment: 18 pages, 8 figure

Automatic Edge Error Judgment in Figure Skating Using 3D Pose Estimation from a Monocular Camera and IMUs

Automatic evaluating systems are fundamental issues in sports technologies. In many sports, such as figure skating, automated evaluating methods based on pose estimation have been proposed. However, previous studies have evaluated skaters' skills in 2D analysis. In this paper, we propose an automatic edge error judgment system with a monocular smartphone camera and inertial sensors, which enable us to analyze 3D motions. Edge error is one of the most significant scoring items and is challenging to automatically judge due to its 3D motion. The results show that the model using 3D joint position coordinates estimated from the monocular camera as the input feature had the highest accuracy at 83% for unknown skaters' data. We also analyzed the detailed motion analysis for edge error judgment. These results indicate that the monocular camera can be used to judge edge errors automatically. We will provide the figure skating single Lutz jump dataset, including pre-processed videos and labels, at https://github.com/ryota-takedalab/JudgeAI-LutzEdge