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The study of collective animal behavior, especially in aquatic environments, presents unique challenges and opportunities for understanding movement and interaction patterns in the field of ethology, ecology, and bio-navigation. The Fish Tracking Challenge 2024 (https://ftc-2024.github.io/) introduces a multi-object tracking competition focused on the intricate behaviors of schooling sweetfish. Using the SweetFish dataset, participants are tasked with developing advanced tracking models to accurately monitor the locations of 10 sweetfishes simultaneously. This paper introduces the competition's background, objectives, the SweetFish dataset, and the appraoches of the 1st to 3rd winners and our baseline. By leveraging video data and bounding box annotations, the competition aims to foster innovation in automatic detection and tracking algorithms, addressing the complexities of aquatic animal movements. The challenge provides the importance of multi-object tracking for discovering the dynamics of collective animal behavior, with the potential to significantly advance scientific understanding in the above fields., Comment: 5 pages, 1 figure

The development of a reliable and valid assessment tool of human-automation trust is an important topic. This study aimed to develop a Chinese version of human-automation trust scale (C-HATS) with reasonable reliability and validity based on Lee and See (2004)'s trust model. After three phases of assessments including exploratory factor analysis, item analysis, and confirmatory factor analysis, different dimensions and items were considered for initial and posttask human-automation trust. For post-task trust, the scale had three dimensions and 11 items and reflected Lee and See (2004)'s model, whereas different from Lee and See (2004)'s model, the final scale had 14 items but only two dimensions for initial trust. Nevertheless, for both initial and post-task trust, reasonable reliability and validity of the scale were verified with various consumer automation products. Although further verification is still necessary, the developed C-HATS could be used to effectively assess human-automation trust in the Chinese context., Comment: 26 pages with 3 figures

In this paper, we show that the dynamics of a wide variety of nonlinear systems such as engineering, physical, chemical, biological, and ecological systems, can be simulated or modeled by the dynamics of memristor circuits. It has the advantage that we can apply nonlinear circuit theory to analyze the dynamics of memristor circuits. Applying an external source to these memristor circuits, they exhibit complex behavior, such as chaos and non-periodic oscillation. If the memristor circuits have an integral invariant, they can exhibit quasi-periodic or non-periodic behavior by the sinusoidal forcing. Their behavior greatly depends on the initial conditions, the parameters, and the maximum step size of the numerical integration. Furthermore, an overflow is likely to occur due to the numerical instability in long-time simulations. In order to generate a non-periodic oscillation, we have to choose the initial conditions, the parameters, and the maximum step size, carefully. We also show that we can reconstruct chaotic attractors by using the terminal voltage and current of the memristor. Furthermore, in many memristor circuits, the active memristor switches between passive and active modes of operation, depending on its terminal voltage. We can measure its complexity order by defining the binary coding for the operation modes. By using this coding, we show that in the forced memristor Toda lattice equations, the memristor's operation modes exhibit the higher complexity. Furthermore, in the memristor Chua circuit, the memristor has the special operation modes., Comment: 115 pages, 109 figures

In this paper, we introduce some interesting features of a memristor CNN (Cellular Neural Network). We first show that there is the similarity between the dynamics of memristors and neurons. That is, some kind of flux-controlled memristors can not respond to the sinusoidal voltage source quickly, namely, they can not switch `on' rapidly. Furthermore, these memristors have refractory period after switch `on', which means that it can not respond to further sinusoidal inputs until the flux is decreased. We next show that the memristor-coupled two-cell CNN can exhibit chaotic behavior. In this system, the memristors switch `off' and `on' at irregular intervals, and the two cells are connected when either or both of the memristors switches `on'. We then propose the modified CNN model, which can hold a binary output image, even if all cells are disconnected and no signal is supplied to the cell after a certain point of time. However, the modified CNN requires power to maintain the output image, that is, it is volatile. We next propose a new memristor CNN model. It can also hold a binary output state (image), even if all cells are disconnected, and no signal is supplied to the cell, by memristor's switching behavior. Furthermore, even if we turn off the power of the system during the computation, it can resume from the previous average output state, since the memristor CNN has functions of both short-term (volatile) memory and long-term (non-volatile) memory. The above suspend and resume feature are useful when we want to save the current state, and continue work later from the previous state. Finally, we show that the memristor CNN can exhibit interesting two-dimensional waves, if an inductor is connected to each memristor CNN cell., Comment: 60 pages, 50 figures

A Comment on the Letter by P. Kratzer and M. Scheffler, Phys. Rev. Lett. 88, 036102 (2002)., Comment: 1 page, no figures. Withdrawn because the main claim can be found in another article, cond-mat/0004368

Zhao et al. [Phys.Rev.B 58, 13824 (1998)] depicted several atomic structures of domain boundaries on a Si(111) surface and criticized the article by the present author and the co-workers. I will point out that their criticism is incorrect and their structure models have no consistency., Comment: 2 pages. Physical Review B, to appear

An attempt is made to simulate the homoepitaxial growth of a Si(111) surface by the kinetic Monte Carlo method in which the standard Solid-on-Solid model and the planar model of the (7x7) surface reconstruction are used in combination. By taking account of surface reconstructions as well as atomic deposition and migrations, it is shown that the effect of a coorparative stacking transformation is necessary for a layer growth., Comment: 4 pages, 5 figures. For Fig.1 of this article, please see Fig.2 of Phys.Rev. B56, 3583 (1997). To appear in Phys.Rev.B. (June 1998)

We have performed a series of simulations of clusters of galaxies on the basis of the smoothed particle hydrodynamics technique in a spatially-flat cold dark matter universe with $\Omega=0.3$, $\lambda=0.7$, and H_0=70 km/s/Mpc as one of the most successful representative cosmological scenarios. In particular, we focus on the Sunyaev--Zel'dovich effect in submm and mm bands, and estimate the reliability of the estimates of the global Hubble constant $H_0$ and the peculiar velocity of clusters $v_r$. Our simulations indicate that fractional uncertainties of the estimates of $H_0$ amount to $\sim 20%$ mainly due to the departure from the isothermal and spherical gas density distribution. We find a systematic underestimate bias of $H_0$ by $\sim 20%$ for clusters $z\approx 1$, but not at $z\approx 0$. The gas temperature drop in the central regions of our simulated clusters leads to the underestimate bias of $v_r$ by $\sim 5%$ at $z\approx 0$ and by $\sim 15%$ at $z\approx 1$ in addition to the statistical errors of the comparable amount due to the non-spherical gas profile., Comment: 16 pages, LaTeX, 6 figures and 1 table. Accepted for publication in PASJ, for higher resolution Postscript files, see ftp://ftp.kusastro.kyoto-u.ac.jp/pub/kohji/yis98