Two Experiments in Dissipative Systems of Many Degrees of Freedom

我们从多自由度耗散系统中选择了两个典型的实验。一个是在封闭的小室内进行的热湍流实验。二是体外培养神经元网络。通过使用低普朗特数流体汞，在瑞利-贝纳德构型中产生了发达的热湍流。得到的瑞利数（Ra）为10^<11>，盒内雷诺数为5x，这是目前已有的低普朗特数流体实验室实验中最高的数值，与其他流体的最高数值相兼容。在热湍流中发现了一种两层边界层倒转的新状态，即粘性边界层完全包含在热边界层中。尽管有这种反转，但发现胞内净热输运（努塞尔数，Nu）与Ra^<0.29>成正比，这与理论预测相矛盾，即当两个边界层反转时，Nu与Ra^<1/2>成正比。我们得出观测状态是热湍流的渐近状态。我们从18天大鼠胚胎中培养神经元。神经元网络在玻璃基板上再生。采用钙敏感荧光染料和共聚焦显微镜，测定和分析了神经元钙浓度活性的动态变化。我们发现了三种类型的神经网络同步放电；(1)周期(2)非周期(3)传播同步模式。我们还提出了一种新的多点神经活动时间序列分析方法。它使我们能够识别不同的神经元簇，它们以不同的同步模式放电。

We chose two typical experiments from Dissipative Systems with many degrees of freedom.The one is an experiment on developed thermal turbulence in a closed cell. The second is cultured neuron network in vitro.1. Developed thermal turbulence is created in Rayleigh-Benard configuration by using a low Prandtl number fluid, mercury. Achieved Rayleigh number (Ra) is 10^<11> and Reynolds number of the box is 5x which is the highest value among ever existing laboratory experiments for low Prandtl number fluid and compatible with the highest one for other fluid. We found a new state in thermal turbulence in which two boundary layers are inverted, i.e. viscous boundary layer is totally included within thermal boundary layer. In spite of this inversion, net heat transport across the cell (Nusselt number, Nu) was found to be proportional to Ra^<0.29> which contradicts to the theoretical prediction that Nu is proportional to Ra^<1/2> when two boundary layers are inverted. We concluded that the observed state is the asymptotic state of thermal turbulence.2. We made cultures of neurons from 1 8days rat embryos. Network of neurons are regenerated on a glass substrate. By using Ca sensitive fluorescent dye and confocal microscope, dynamics of Ca concentration activity in neurons are measured and analyzed. We found three types of synchronous firing of neural network ; (1) Periodic (2)Non-periodic (3) Propagating synfiring pattern. We also proposed a new way of analyzing multi-point time series of neural activities. It enabled us to identify different clusters of neurons firing with different synchronous modes.