An extension of the Maskit slice for 4-dimensional Kleinian groups

Let $\Gamma$ be a 3-dimensional Kleinian punctured torus group with ccidental parabolic transformations. The deformation space of $\Gamma$ in the group of M\"{o}bius transformations on the 2-sphere is well-known as the Maskit slice of punctured torus groups. In this paper, we study deformations $\Gamma'$ of $\Gamma$ in the group of M\"{o}bius transformations on the 3-sphere such that $\Gamma'$ does not contain screw parabolic transformations. We will show that the space of the deformations is realized as a domain of 3-space $\mathbb{R}^3$, which contains the Maskit slice of punctured torus groups as a slice through a plane. Furthermore, we will show that the space also contains the Maskit slice of fourth-punctured sphere groups as a slice through another plane. Some of another slices of the space will be also studied.Comment: 34 pages, 11 figures. v3: The title is changed and some typo are fixed. To appear in Conform. Geom. dyn. The paper including more clear figures can be downloaded from http://www.math.nagoya-u.ac.jp/~itoken/index.htm

WTC rat has unique characteristics such as resistant to streptozotocin

AbstractBecause we found that WTC rats might be resistant to streptozotocin (STZ), we have elucidated the mechanisms of resistant to the diabetogenic effects of STZ in the WTC rats. Dose response to STZ was evaluated with glucose levels. No significant changes in glucose level to STZ administration were observed in WTC rats. Insulin secretion by suppling glucose was preserved in WTC rats even after STZ administration. Although there was no significant difference in gene expression of both GLUT2 and Kir6.2, which were involved in STZ resistance, between WTC rats and Wistar rats, the expression of metallothionein 2a in pancreas and liver to STZ administration of WTC rats was significantly higher than that of Wistar rats. Moreover, alloxan did not induce diabetes in WTC rats as same as STZ. These results suggest that WTC rats might have powerful antioxidant property to protect β cells in pancreas. Because the STZ-resistant property is very close characteristics to human beings, WTC rats will become a useful animal model in diabetic researches

A part of cholinergic fibers in mouse superior cervical ganglia contain GABA or glutamate

The localizations and functions of glutamate and GABA, the major amino acid neurotransmitters in the central nervous system, are still unclear in the peripheral nervous system. We immunohistochemically double-stained mouse superior cervical ganglia with antibodies for the vesicular acetylcholine transporter (VAchT), GAD65, the vesicular glutamate transporters 1-3 (VGluTs1-3), the marker of the sympathetic preganglionic neuron (SPN), GABAergic, and glutamatergic terminals, respectively. All GAD65-positive terminals showed VAchT-immunoreactivity, indicating that GABAergic fibers originate from SPNs. VGluT2-immunoreactive terminals showing colocalization with VAchT were observed, but VGluT1 and 3 immunoreactive terminals were not. Colocalization of GAD65 and VGluT2 was rarely found. All VGluT2-immunopositive terminals were also immunopositive for neuronal nitric oxide synthase (nNOS), a marker for the subpopulation of the SPNs, while about half of the GABA-immunopositive fibers were immunopositive for nNOS. The origin of these fibers was discussed

Oncogene Surveillance: Differential role of Runx3 and p53

The 3rd International Symposium on Carcinogenic Spiral & International Symposium on Tumor Biology in Kanazawa, [DATE]: January 24(Thu)-25(Fri),2013, [Place]:Kanazawa Excel Hotel Tpkyu, Kanazawa, Japan, [Organizers]:Infection/Inflammation-Assisted Acceleration of the Carcinogenic Spiral and its Alteration through Vector Conversion of the Host Response to Tumors / Scientific Research on Innovative Areas, a MEXT Grant-in Aid Projec

A study of reinforcement learning with knowledge sharing

In this paper, we consider multi-agent system in which every agents have own tasks that differs each other. We propose a method that decreases learning time of reinforcement learning by using the model of environment. In the proposed algorithm, the model is created by sharing the experiences of agents each other. To demonstrate the effectiveness of the proposed method, simulations of a puddle world and experiments of a maze world have been carried out. As a result effective behaviors have been obtained quickly.</p

A study of reinforcement learning with knowledge sharing for distributed autonomous system

Reinforcement learning is one of effective controller for autonomous robots. Because it does not need priori knowledge and behaviors to complete given tasks are obtained automatically be repeating trial and error. However a large number of trials are required to realize complex tasks. So the task that can be obtained using the real robot is restricted to simple ones. Considering these points, various methods that prove the learning cost of reinforcement learning have been proposed. In the method that uses priori knowledge, the methods lose the autonomy that is most important feature of reinforcement learning in applying it to the robots. In the Dyna-Q, that is one of simple and effective reinforcement learning architecture integrating online planning, a model of environment is learned from real experience and by utilizing the model to learn, the learning time is decreased. In this architecture, the autonomy is held, however the model depends on the task, so acquired knowledge of environment cannot be reused to other tasks. In the real world, human beings can learn various behaviors to complete complex tasks without priori knowledge of the tasks. We can try to realize the task in our image without moving our body. After the training in the image, by trying to the real environment, we save time to learn. It means that we have model of environment and we utilize the model to learn. We consider that the key ability that makes the learning process faster is construction of environment model and utilization of it. In this paper, we have proposed a method to obtain an environment model that is independent of the task. And by utilizing the model we have decreased learning time. We consider distributed autonomous agents, and we show that the environment model is constructed quickly by sharing the experience of each agent, even when each agent has own independent task. To demonstrate the effectiveness of the proposed method, we have applied the method to the Q-learning and simulations of a puddle world are carried out. As a result effective behaviors have been obtained quickly. </p