On the Rebrightenings of Classical Novae during the Early Phase

We report on the spectral evolution of 6 classical novae, V1186 Sco, V2540 Oph, V4745 Sgr, V5113 Sgr, V458 Vul, and V378 Ser, based on the low-resolution spectra obtained at the Fujii-Bisei Observatory and the Bisei Astronomical Observatory, Japan. In the light curves, these 6 novae show several rebrightenings during the early phase lasting ~10 days after the first maximum in fast novae, and ~100 days in slow novae. The early spectra of all of these novae had emission lines with a P-Cygni profile at the maximum brightness. The absorption component of the P-Cygni profiles then disappeared after the maximum, and reappeared when the novae brightened to the next maximum. We suggest that the re-appearance of the absorption component at the rebrightening is attributable to re-expansion of the photosphere after it once shifts sufficiently inside. From the light curves, we found that the time intervals of the rebrightenings of these 6 novae show a similar systematic trend, which is applicable to all types of novae: fast and slow, and Fe II type and hybrid type. Moreover, we note the difference between the spectra at the rebrightenings during the early phase and at the rebrightening in V2362 Cyg, and at the oscillation during the transition phase in V1494 Aql, which means difference of the physical mechanism of the rebrightening during the early phase and the later oscillations.Comment: 11 pages, 15 figures, accepted for publication in PAS

Non-linear Evolution of Matter Power Spectrum in Modified Theory of Gravity

We present a formalism to calculate the non-linear matter power spectrum in modified gravity models that explain the late-time acceleration of the Universe without dark energy. Any successful modified gravity models should contain a mechanism to recover General Relativity (GR) on small scales in order to avoid the stringent constrains on deviations from GR at solar system scales. Based on our formalism, the quasi non-linear power spectrum in the Dvali-Gabadadze-Porratti (DGP) braneworld models and $f(R)$ gravity models are derived by taking into account the mechanism to recover GR properly. We also extrapolate our predictions to fully non-linear scales using the Parametrized Post Friedmann (PPF) framework. In $f(R)$ gravity models, the predicted non-linear power spectrum is shown to reproduce N-body results. We find that the mechanism to recover GR suppresses the difference between the modified gravity models and dark energy models with the same expansion history, but the difference remains large at weakly non-linear regime in these models. Our formalism is applicable to a wide variety of modified gravity models and it is ready to use once consistent models for modified gravity are developed.Comment: 25 pages, 8 figures, comparison to N-body simulations in DGP added, published in PR

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

Spectral Evolution of the Unusual Slow Nova V5558 Sgr

We report on the spectral evolution of the enigmatic, very slow nova V5558 Sgr, based on the low-resolution spectra obtained at the Fujii-Bisei Observatory and the Bisei Astronomical Observatory, Japan during a period of 2007 April 6 to 2008 May 3. V5558 Sgr shows a pre-maximum halt and then several flare-like rebrightenings, which is similar to another very slow nova V723 Cas. In our observations, the spectral type of V5558 Sgr evolved from the He/N type toward the Fe II type during the pre-maximum halt, and then toward the He/N type again. This course of spectral transition was observed for the first time in the long history of the nova research. In the rebrightening stage after the initial brightness maximum, we could identify many emission lines accompanied by a stronger absorption component of the P-Cygni profile at the brightness maxima. We found that the velocity of the P-Cygni absorption component measured from the emission peak decreased at the brightness maxima. Furthermore, we compared the spectra of V5558 Sgr with V723 Cas, and other novae which exhibited several rebrightenings during the early phase.Comment: 8 pages, 7figures, accepted for publication in PAS

Action valuation of on- and off-ball soccer players based on multi-agent deep reinforcement learning

Analysis of invasive sports such as soccer is challenging because the game situation changes continuously in time and space, and multiple agents individually recognize the game situation and make decisions. Previous studies using deep reinforcement learning have often considered teams as a single agent and valued the teams and players who hold the ball in each discrete event. Then it was challenging to value the actions of multiple players, including players far from the ball, in a spatiotemporally continuous state space. In this paper, we propose a method of valuing possible actions for on- and off-ball soccer players in a single holistic framework based on multi-agent deep reinforcement learning. We consider a discrete action space in a continuous state space that mimics that of Google research football and leverages supervised learning for actions in reinforcement learning. In the experiment, we analyzed the relationships with conventional indicators, season goals, and game ratings by experts, and showed the effectiveness of the proposed method. Our approach can assess how multiple players move continuously throughout the game, which is difficult to be discretized or labeled but vital for teamwork, scouting, and fan engagement.Comment: 12 pages, 4 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

Estimation of control area in badminton doubles with pose information from top and back view drone videos

The application of visual tracking to the performance analysis of sports players in dynamic competitions is vital for effective coaching. In doubles matches, coordinated positioning is crucial for maintaining control of the court and minimizing opponents' scoring opportunities. The analysis of such teamwork plays a vital role in understanding the dynamics of the game. However, previous studies have primarily focused on analyzing and assessing singles players without considering occlusion in broadcast videos. These studies have relied on discrete representations, which involve the analysis and representation of specific actions (e.g., strokes) or events that occur during the game while overlooking the meaningful spatial distribution. In this work, we present the first annotated drone dataset from top and back views in badminton doubles and propose a framework to estimate the control area probability map, which can be used to evaluate teamwork performance. We present an efficient framework of deep neural networks that enables the calculation of full probability surfaces. This framework utilizes the embedding of a Gaussian mixture map of players' positions and employs graph convolution on their poses. In the experiment, we verify our approach by comparing various baselines and discovering the correlations between the score and control area. Additionally, we propose a practical application for assessing optimal positioning to provide instructions during a game. Our approach offers both visual and quantitative evaluations of players' movements, thereby providing valuable insights into doubles teamwork. The dataset and related project code is available at https://github.com/Ning-D/Drone_BD_ControlAreaComment: 15 pages, 10 figures, to appear in Multimedia Tools and Application

Predictive World Models from Real-World Partial Observations

Cognitive scientists believe adaptable intelligent agents like humans perform reasoning through learned causal mental simulations of agents and environments. The problem of learning such simulations is called predictive world modeling. Recently, reinforcement learning (RL) agents leveraging world models have achieved SOTA performance in game environments. However, understanding how to apply the world modeling approach in complex real-world environments relevant to mobile robots remains an open question. In this paper, we present a framework for learning a probabilistic predictive world model for real-world road environments. We implement the model using a hierarchical VAE (HVAE) capable of predicting a diverse set of fully observed plausible worlds from accumulated sensor observations. While prior HVAE methods require complete states as ground truth for learning, we present a novel sequential training method to allow HVAEs to learn to predict complete states from partially observed states only. We experimentally demonstrate accurate spatial structure prediction of deterministic regions achieving 96.21 IoU, and close the gap to perfect prediction by 62% for stochastic regions using the best prediction. By extending HVAEs to cases where complete ground truth states do not exist, we facilitate continual learning of spatial prediction as a step towards realizing explainable and comprehensive predictive world models for real-world mobile robotics applications. Code is available at https://github.com/robin-karlsson0/predictive-world-models.Comment: Accepted for IEEE MOST 202

3次元再構成を用いた非骨性距踵骨癒合症の形態学的分析

Background: Resection of talocalcaneal coalitions has generally involved osseous coalitions. We attempted to evaluate the morphology of nonosseous talocalcaneal coalitions. This study aimed to investigate if the calcaneal articular surface area of feet with talocalcaneal coalitions is different than that of normal feet. Methods: Twenty nonosseous talocalcaneal coalition cases with analyzable computed tomography (CT) scans were compared to 20 control cases. Three-dimensional models of the talus and calcaneus were constructed, and the surface areas of the posterior facet (SPF), whole talocalcaneal joint of the calcaneus (SWJ), and coalition site (SCS) of each 3D-CT model were measured. "Calibrated" values of the 2 groups were created to adjust for relative size of the tali and then compared. The preoperative and postoperative AOFAS Ankle-Hindfoot scale was calculated for 9 cases that had undergone single coalition resection. Results: The calibrated SPF and SWJ were significantly greater in the coalition group than in the control group (40% and 12%, respectively). No significant difference was detected between the calibrated (SWJ - SCS) value of the coalition group and the calibrated SWJ value of the control group. The AOFAS scale was improved postoperatively in all 9 cases analyzed. Conclusion: The calcaneal articular surface of nonosseous talocalcaneal coalition feet in our series was larger than that of the normal feet. This study indicates that the total calcaneal articular surface after coalition resection may be comparable to the calcaneal articular surface of normal feet. We suggest that the indication for coalition resection be reconsidered for nonosseous coalition. Level of evidence: Level III, retrospective comparative study.博士（医学）・甲第815号・令和4年3月15日© The Author(s) 2021. Creative Commons Non Commercial CC BY-NC: This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/ open-access-at-sage)

Syntheses of prodelphinidin B1, B2, and B4 and their antitumor activities against human PC-3 prostate cancer cell lines

Total synthesis of prodelphinidin B1, B2, and B4 has been accomplished. The key step is Lewis acid-mediated equimolar condensations between an epigallocatechin and/or a gallocatechin nucleophile and an epigallocatechin and/or a gallocatechin electrophile. The antitumor effects of synthetic prodelphinidin B1-B4 against human PC-3 prostate cancer cell lines have been investigated. These compounds showed significant antitumor effects. Their activity seemed to be little bit stronger than EGCG and prodelphinidin B3, known antitumor agent.ArticleTETRAHEDRON LETTERS. 54(52):7188-7192 (2013)journal articl