This paper discloses the development of a recursive mathematical model for radiotherapy which predicts future position of the lung tumor based on the current and past tumor position measurements. Four adaptation algorithms have been applied to train the model coefficients so as to achieve 1[mm] prediction error in 1[s] ahead prediction. Numerical evaluation has been performed for 9 different lung tumor trajectories and the models are successfully trained to achieve the required precision for all dataset. Analyzing the results indicate that SHARF algorithm gives the smallest prediction error for relatively wide-bandwidth lung motion which might be partly affected by the heartbeat, whereas SHSER algorithm fits the best for tumor motions mainly dominated by the respiration of the patients.

The number of osteoporotic patient is in a tendency to increase now. Therefore, we must take mesures against osteoporosis. The study to prevent bone rarefaction by controlling vibration stimulation appropriately without using a therapeutic dug is conducted. However, the suitable condition for vibration is unknown because vibration properties of the bone is not clear. In this report, we suggest the bone vibration analysis model that considered the influence that the soft tissue around the bones of lower limb gives to bone vibration. And we identified the validity of the analysis model by comparing the analysis result and the experimental result. We conclude that this analysis model has reformability because this model catches the tendency of experimental result．

A two-dimensional ultrasonic-measurement-integrated (2D-UMI) blood flow analysis system was developed for easy acquisition of an intravascular hemodynamics, which feeds back Doppler velocity obtained by an ultrasonic measurement to a numerical blood flow simulation for clinical application. In previous study, ultrasonic measurement and 2D-UMI analysis were performed to clarify the analysis accuracy for real flow field, and the reproducibility of 2D-UMI analysis for real flow field was confirmed by comparison of velocity profile between 2D-UMI and 3D-CFD analysis results corresponding to an experimental flow. However, the analysis accuracy of 2D-UMI analysis for real flow has not been examined, and its spatiotemporal variation is important in evaluation of errors due to noise specific to ultrasonic measurement. The aim of this study was to clarify spatiotemporal variation characteristics of analysis accuracy of each velocity component obtained in 2D-UMI analysis. Comparisons of Doppler velocity V and (u, v) velocity profiles between measurement data, 2D-UMI, and 3D-CFD analyses results were performed, and their spatiotemporal variations were discussed. As a result, it was clarified that spatial variation of Doppler velocity error for frame-averaged measurement data became large when feedback gain is too large, and that of velocity vector error for 3D-CFD analysis result became smaller with increasing feedback gain. Temporal variations of Doppler velocity V, u, and v velocity profile became larger with increasing feedback gain, and it is considered that the analysis result for KV^* = 110 which the time variation is small and the velocity profile is smooth while reproducing the velocity profile of 3D-CFD analysis is close to an actual flow field.

Serious accidents have happened in many cases caused by the decrease of arousal level, and it is known that the arousal level decreases due to driving and simple tasks, such as an easy calculatation. System to accurately evaluate arousal level in real time in order to prevent such accidents is required. In this paper, we examined whether the parameters of the mathematical model could be used as a method to evaluate the arousal level. The modified Duffing oscillator was proposed as a mathematical model to perform simplified parameters identification. It was applied to EEG data, which is obtained by EEG acquisition experimentation in relaxed states and concentrated state. As a result of the parameters identification in theta band, alpha band, beta band, and 4-30 Hz band, it is shown that t h e parameter B is repeating increase and decrease with time progress of each experiment. A result of investigating a correlation between conventional arousal level and parameter B shows a significant correlation. It is suggested that the parameter B of the modified Duffing oscillator is related to the conventional arousal level and it can calculate the arousal level in real time since this evaluation method of arousal level does not require to analyze each band.

A mathematical model of the learning system based on signaling networks in living cells has been proposed. It is well known that a living body has the ability to adapt to environment, and each cell consisting the body may have the same ability. According to various researches in biochemical field, it is expected that the sensors perceiving surroundings are membrane proteins, and the actuators in cells are actin filaments. But the controller for actuators and adaption mechanism of cells has not been understood. When an extracellular signaling molecule activates a protein located on the cell membrane, this protein triggers a biochemical chain in the cell. The network of chemical action is the system which determines the response of the cell to extracellular stimuli. This “signaling network” is expected to work as adaptive control system in living cells. A similar network known as a neural network has ability of learning and its mathematical model has been applied to various fields such as control, pattern recognition, etc. An actual neural network in living body uses electric signals, but the signaling network uses diffusion of various molecules to transmit information. In this paper, a mathematical model of the signaling network having different mechanism from neural networks has been proposed. The model has been applied to nonlinear mapping problem and it shows ability as a learning system. Moreover, a learning ability for time series has been introduced by time delay mechanism to the present mathematical model.

Four kinds of nonlinear oscillators, which include a Duffing oscillator and a van der Pol oscillator, are employed to analyze the brain wave in an epilepsy model rat. Extracting time series data with alpha frequency bands from 8 to 13Hz from the frequency analysis window setting in brain waves, we determine each parameter for nonlinear oscillator, we found that the outbreak of abnormality induces an extreme reduction of the term related to nonlinearity and the input terms increase with the growth of the epileptic wave.

Focal brain cooling can suppress epileptic discharges (EDs) in the cerebral cortex and also suppress frequency spectral powers in the EDs with temperature-dependent effect. The objective of this paper is to investigate the dependence of the cooling rate on the EDs suppression with experiments using 4 epilepsy model rats. The cortical surface of the rats was cooled to 16^oC, and time condition for brain cooling from initial temperature to 16^oC was set at 30, 60, 100 and 200 sec respectively. Obtained ECoG data were divided for 4 frequency bands (δ(0.5-4Hz), θ(4-8Hz), α(8-13Hz), β(13-30Hz)) to elucidate the effect of change in the frequency band of EDs depending on the cooling rate. The power spectral during cooling of each condition were compared to the power spectral of pure EDs (non-cooling state). Our results demonstrated that the suppression of EDs have a cooling rate dependency, and all of the frequency band in the EDs are smaller when the cooling rate is slower. These findings could contribute to elucidation of the mechanism of suppression EDs.

Chemical-free vegetable is a kind of brand-name products in agriculture field. However, it is hard to control plant growth without plant growth regulators. In order to cultivate plants without them, physical stresses are attractive candidates for a plant growth control. Therefore, we proposed a plant growth control system by exposing ultrasound for plant factory with artificial light. In particular, we observed the growth of red leaf lettuces after roots of them exposed to ultrasound. To develop our concept, we fabricated the red leaf lettuce hydroponic cultivation device with ultrasound transducer in the plant growth chamber. The transducer was driven with 10-50 V_p-p at 28 kHz. We prepared saplings of red leaf lettuce cultivated for 2 weeks and cultivated them in the fabricated cultivation device for 2 weeks. Results show that root length and leaf numbers when exposed to ultrasound with 30 V_p-p were statistically longer and higher than those without ultrasound exposure. Meanwhile, root length and leaf numbers when exposed to ultrasound with 50 V_p-p were statistically shorter and lower. These results indicate that our plant hydroponic cultivation device achieves the growth control of plant using ultrasound. Such a technique may facilitate plant growth control without a plant growth regulator in a plant factory, beneficial for future agriculture applications.