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This paper presents a novel event camera simulation system fully based on physically based Monte Carlo path tracing with adaptive path sampling. The adaptive sampling performed in the proposed method is based on a statistical technique, hypothesis testing for the hypothesis whether the difference of logarithmic luminances at two distant periods is significantly larger than a predefined event threshold. To this end, our rendering system collects logarithmic luminances rather than raw luminance in contrast to the conventional rendering system imitating conventional RGB cameras. Then, based on the central limit theorem, we reasonably assume that the distribution of the population mean of logarithmic luminance can be modeled as a normal distribution, allowing us to model the distribution of the difference of logarithmic luminance as a normal distribution. Then, using Student's t-test, we can test the hypothesis and determine whether to discard the null hypothesis for event non-occurrence. When we sample a sufficiently large number of path samples to satisfy the central limit theorem and obtain a clean set of events, our method achieves significant speed up compared to a simple approach of sampling paths uniformly at every pixel. To our knowledge, we are the first to simulate the behavior of event cameras in a physically accurate manner using an adaptive sampling technique in Monte Carlo path tracing, and we believe this study will contribute to the development of computer vision applications using event cameras., Comment: 10 pages, 7 figures, Presented at ICCP 2024

We investigate the dose and dose-rate dependence of the mutation frequency caused by artificial radiations with Whack-A-Mole (WAM) model which we have recently proposed. In particular, we pay special attention to the case of long-term and low dose-rate exposure. The results indicate that the dose-rate dependence is successfully described with WAM model and it may replace the so-called DDREF, the concept of which has long been adopted to take account of the difference between the high dose-rate data and the low dose-rate ones. Basic properties of WAM model are discussed emphasizing the dose-rate dependence to demonstrate how the explicit dose-rate dependence built in the model plays a key role. By adopting the parameters that are determined to fit the mega mouse experiments, biological effects of long-term exposure to extremely low dose-rate radiation are discussed. In WAM model, the effects of the long-term exposure show a saturation property, which makes a clear distinction from the LNT hypothesis which predicts a linear increase of the effects with time., Comment: 20 pages, 5 figures, 2 tables, submitted to Journal of Nuclear Science and Technology

We present a novel model to estimate biological effects caused by artificial radiation exposure, Whack-a-mole (WAM) model. It is important to take account of the recovery effects during the time course of the cellular reactions. The inclusion of the dose-rate dependence is essential in the risk estimation of low dose radiation, while nearly all the existing theoretical models relies on the total dose dependence only. By analyzing the experimental data of the relation between the radiation dose and the induced mutation frequency of 5 organisms, mouse, drosophila, chrysanthemum, maize and tradescantia, we found that all the data can be reproduced by WAM model. Most remarkably, a scaling function, which is derived from WAM model, consistently accounts for the observed mutation frequencies of 5 organisms. This is the first rationale to account for the dose rate dependence as well as to give a unified understanding of a general feature of organisms., Comment: 26 pages, 4 figures, 1 table, Journal of the Physical Society of Japan accepted

We develop a kinetic reaction model for cells having irradiated DNA molecules due to ionizing radiation exposure. Our theory simultaneously accounts for the time-dependent reactions of the DNA damage, the DNA mutation, the DNA repair, and the proliferation and apoptosis of cells in a tissue with a minimal set of model parameters. In contrast to existing theories for radiation exposition, we do not assume the relationships between the total dose and the induced mutation frequency. Our theory provides a universal scaling function that reasonably explains the mega-mouse experiments in Ref.[W. L. Russell and E. M. Kelly, Proc. Natl. Acad. Sci. USA. {\bf 79} (1982) 542.] with different dose rates. Furthermore, we have estimated the effective dose rate, which is biologically equivalent to the ionizing effects other than those caused by artificial irradiation. This value is $ 1.11 \times 10^{-3} ~\rm{[Gy/hr]}$, which is significantly larger than the effect caused by natural background radiation., Comment: 12 pages, 3 figures

We propose Radiation Exposure Theory (RET), a mathematical framework to estimate biological damage caused by irradiation. This is an extension of LDM model which was proposed in the paper [Y. Manabe et al.: J. Phys. Soc. Jpn. 81, 104004(2012)]. The theory is based on physical protocol, 'a stimulus and its response'. It takes account of considerable response including mutation, cell death caused by outer stimulus, as well as biological functions such as proliferation, apoptosis and repair. By taking account of biological issues, namely a variety of preventable effects, which is characteristic feature of living object. RET can explain various data which simple LNT does not reproduce. As one of the characteristic features of RET, we propose a scaling law, namely all the data point with different dose rate irradiation are predicted to lie on the universal line if the variables, the biological damage function as a function of time development after artificial irradiation starts are converted to renormalized ones. The above scaling law can be compared with experimental data. We adopt the accumulated experiments performed by so-called mega mouse projects. It is found that their data points are converted into a universal scaling function and are in reasonably agreement with the prediction of RET., Comment: 9 pages, 5 figures, submitted to Phys. Rev. E

We propose LD(Low Dose) model, the extension of LDM model which was proposed in the previous paper [Y. Manabe et al.: J. Phys. Soc. Jpn. 81 (2012) 104004] to estimate biological damage caused by irradiation. LD model takes account of all the considerable effects including cell death effect as well as proliferation, apoptosis, repair. As a typical example of estimation, we apply LD model to the experiment of mutation frequency on the responses induced by the exposure to low levels of ionizing radiation. The most famous and extensive experiments are those summarized by Russell and Kelly [Russell, W. L. & Kelly, E. M: Proc. Natl Acad. Sci. USA 79 (1982) 539-541], which are known as 'Mega-mouse project'. This provides us with important information of the frequencies of transmitted specific-locus mutations induced in mouse spermatogonia stem-cells. It is found that the numerical results of the mutation frequency of mice are in reasonable agreement with the experimental data: the LD model reproduces the total dose and dose rate dependence of data reasonably. In order to see such dose-rate dependence more explicitly, we introduce the dose-rate effectiveness factor (DREF). This represents a sort of preventable effects such as repair, apoptosis and death of broken cells, which are to be competitive with proliferation effect of broken cells induced by irradiation., Comment: subimitting to J. Phys. Soc. Jpn, 32 pages, 8 figures

We propose a mathematical model for estimating biological damage caused by low-dose irradiation. We understand that the Linear Non Threshold (LNT) hypothesis is realized only in the case of no recovery effects. In order to treat the realistic living objects, our model takes into account various types of recovery as well as proliferation mechanism, which may change the resultant damage, especially for the case of lower dose rate irradiation. It turns out that the lower the radiation dose rate, the safer the irradiated system of living object (which is called symbolically "tissue" hereafter) can have chances to survive, which can reproduce the so-called dose and dose-rate effectiveness factor (DDREF)., Comment: 22 pages, 6 Figs, accepted in Journal of the Physical Society of Japan