In order to study the antitumoral effect of Selaginella tamariscina extracts, the cytotoxicities to human histiocytic leukemia cells (U937) and lymphocyte were measured by MTT method. The water extract of Selaginella tamariscina was partitioned into chloroform (CHCl₃), ethylacetate (EtAc), n-butanol (BuOH) and water (H₂O), successively. CHCl₃, EtAc and BuOH fractions of Selaginella tamariscina showed the cytotoxicity to the U937 cells but they had no effect on the cytotoxicity of lymphocyte under the same conditions. The tumor-specific cytotoxicity of Selaginella tamariscina fractions might have been attributed to their genotoxic effect on actively proliferating cells. The expression of p53 tumor suppressor gene was then evaluated by northern blotting. The increased expression of p53 was induced by Selaginella ramariscina fraction V but no expression of p53 was induced by CHCl₃, EtAc, and BuOH fractions of Selaginella tamariscina. These results suggested that the increased expression of p53 induced by Selaginella tamariscina water extract (fraction V) should be required for the cytotoxicity on U937 and the other fractions of Selaginella tamariscina mediated the U937 disruption.

For effective human-robot interaction, robots need to understand the current situation context well, but also the robots need to transfer its understanding to the human participant in efficient way. The most convenient way to deliver robot’s understanding to the human participant is that the robot expresses its understanding using voice and natural language. Recently, the artificial intelligence for video understanding and natural language process has been developed very rapidly especially based on deep learning. Thus, this paper proposes robot vision to audio description method using deep learning. The applied deep learning model is a pipeline of two deep learning models for generating natural language sentence from robot vision and generating voice from the generated natural language sentence. Also, we conduct the real robot experiment to show the effectiveness of our method in human-robot interaction.

The purpose of this study is to develop a motion generation technique based on a double inverted pendulum model (DIPM) that learns and reproduces humanoid robot (or virtual human) motions while keeping its balance in a pattern similar to a human. DIPM consists of a cart and two inverted pendulums, connected in a serial. Although the structure resembles human upper- and lower-body, the balancing motion in DIPM is different from the motion that human does. To do this, we use the motion capture data to obtain the reference motion to keep the balance in the existence of external force. By an optimization technique minimizing the difference between the motion of DIPM and the reference motion, control parameters of the proposed method were learned in advance. The learned control parameters are re-used for the control signal of DIPM as input of linear quadratic regulator that generates a similar motion pattern as the reference. In order to verify this, we use virtual human experiments were conducted to generate the motion that naturally balanced.

The use of human mesenchymal stem cells (hMSCs) in cell-based therapy has attracted extensive interest in the field of regenerative medicine, and it shows applications to numerous incurable diseases. hMSCs show several superior properties for therapeutic use compared to other types of stem cells. Different cell types are discussed in terms of their advantages and disadvantages, with focus on the characteristics of hMSCs. hMSCs can proliferate readily and produce differentiated cells that can substitute for the targeted affected tissue. To maximize the therapeutic effects of hMSCs, a substantial number of these cells are essential, requiring extensive ex vivo cell expansion. However, hMSCs have a limited lifespan in an in vitro culture condition. The senescence of hMSCs is a double-edged sword from the viewpoint of clinical applications. Although their limited cell proliferation potency protects them from malignant transformation after transplantation, senescence can alter various cell functions including proliferation, differentiation, and migration, that are essential for their therapeutic efficacy. Numerous trials to overcome the limited lifespan of mesenchymal stem cells are discussed.

본 연구의 목적은 조선 시대 사상가이며 대학자인 남명의 인간관계를 분석하여 유아기 대인관계교육의 내용 및 방법을 고찰하는 데 있다. 연구 결과 남명의 인간관계는 역할과 도리를 다하는 인간관계, 상대방을 존중하는 인간관계, 마음과 행동을 중시하는 인간관계를 실천한 것으로 분석되어졌다. 남명의 인간관계 실천이 유아기 대인관계교육에 주는 시사점은 덕의 함양과 근본을 갖춘 지식, 그리고 사회ᆞ교육적 가치의 강조이며, 이를 생활에서 실천화하는 방법을 강조한 것으로 나타났다.

MFG-E8 (Milk fat globule-epidermal growth factor VIII), also called lactadherin or BA46, SED1 is a glycoprotein found in milk and mammary epithelial cells, it is a major protein component associated with milk fat globule membrane. Previously, our study showed that expression of MFG-E8 is gradually increased with hepatic differentiation of human embryonic stem cells (hESCs). Therefore, we hypothesized that MFG-E8 would be an early cancer stem cell marker, which may predict cancer progression. Our results showed that MFG-E8 was expressed in various human cancer cell lines such as HepG2, Hep3B, and Huh7. Production and secretion of the MFG-E8 were also confirmed in the conditioned media of those three cell lines using enzyme-linked immunosorbent assay. Next, we analyzed the MFG-E8 expression in 11 clinical cases of cholangiocellular carcinoma (CC) and 33 cases of hepatocellular carcinoma (HCC) by immunohistochemistry and examined the potential correlation with β-catenin and AFP, which are known cancer markers. According to hitological criteria, the progression of HCC and CC was evaluated and classified into high, low, metastatic, and well-, moderate-, poor-differentiated, respectively. Statistical analysis indicated that incidence of both HCC and CC is significantly associated with male compared to female (P<0.05). Tumor size also has positive correlation with age (r2=08948). Our immunohistochemistry data showed that MFG-E8 was expressed both HCC and CC tissue. Interestingly, the MFG-E8 expression was significantly increased with cancer progression (P<0.05) in both cases. Additionally, b-cateninexpression was increased and its localization was changed from membrane to cytoplasm and nucleus with the degree of HCC. Likely b-catenin, AFP was also increased with the degree of HCC but it was not correlated with severalty of CC. Importantly, both AFP and b-catenin were highly co-localized with MFG-E8 in HCC. These results suggest that MFG-E8 may have important physiological roles and its expression in HCC and CC would be considered as an important prognostic factor.

People have expected a humanoid robot to move as naturally as a human being does. The natural movements of humanoid robot may provide people with safer physical services and communicate with persons through motions more correctly. This work presented a methodology to generate the natural motions for a humanoid robot, which are converted from human motion capture data. The methodology produces not only kinematically mapped motions but dynamically mapped ones. The kinematical mapping reflects the human-likeness in the converted motions, while the dynamical mapping could ensure the movement stability of whole body motions of a humanoid robot. The methodology consists of three processes: (a) Human modeling, (b) Kinematic mapping and (c) Dynamic mapping. The human modeling based on optimization gives the ZMP (Zero Moment Point) and COM (Center of Mass) time trajectories of an actor. Those trajectories are modified for a humanoid robot through the kinematic mapping. In addition to modifying the ZMP and COM trajectories, the lower body (pelvis and legs) motion of the actor is then scaled kinematically and converted to the motion available to the humanoid robot considering dynamical aspects. The KIST humanoid robot, Mahru, imitated a dancing motion to evaluate the methodology, showing the good agreement in the motion.

We have proposed modeling methods of mariners' standard behavior for collision avoidance by analyzing mariners' recognition process in a previous study. As a subsequent study, the aim of this study is to build a model of mariners' execution process which is one of six processes in the condition of collision avoidance. In this study, thus, the structure of mariners' information processing on the process of taking avoiding actions is described and the relation between mariners' behavior and necessary factors in the process is analyzed. And then we have built a model of mariners' standard behavior for execution process based on the characteristics of mariners in ship-handling, which are obtained from the international collaborative research on human factors. It is tried to define the contents of execution process based on the standard behavior of mariners for collision avoidance and to formulate information processing of mariners.

This paper deals with a tangible interface system that introduces robot as remote avatar. It is focused on a new method which makes a robot imitate human arm motions captured from a remote space. Our method is functionally divided into two parts: capturing human motion and adapting it to robot. In the capturing part, we especially propose a modified potential function of metaballs for the real-time performance and high accuracy. In the adapting part, we suggest a geometric scaling method for solving the structural difference between a human and a robot. With our method, we have implemented a tangible interface and showed its speed and accuracy test.

본 연구에서는 환자들의 일상생활 동안 움직임 이상을 관찰하기 위한 인체동작 무선계측 기술을 개 발하였다. 기술개발에 사용한 도구는 버클리대학에서 개발한 MICA, TinyOS, nesC를 이용하여 무선신호 감지, 소프트웨어 플랫폼, 그리고 임베디드 프로그래밍을 위한 도구로 사용하였다. 실험을 위해 개발된 장비를 인체의 가슴부위에 부착하고 움직임 동작인 앉기, 서기, 눕기 데이터를 획득하여 PDA로 무선전 송하여 저장하고 처리하여 그래프로 보여준다. 보여진 결과는 인체동작을 구속이나 제한 없이 기록할 수 있게 된다. 본 연구의 결과는 환자의 움직임 이상과 일상생활동작을 관찰하는 데 사용될 수 있을 것 이다.

We've investigated the characteristics on mariner's behavior in the collision situation through a full-mission ship handling simulator and considered that it's necessary to model the standard avoiding behavior of mariners in order to apply the obtained results more widely and effectively. Thus we described the contents of standard avoiding behavior taken by mariners in the collision situation and established the concept of the standard model based on human factors for collision avoidance in a previous study. As a following study, this paper is to propose the method of modeling on mariners' standard behavior for collision avoidance by analyzing the contents of mariner's information processing and the related factors using regression analysis. As a result, we confirmed the influence of relating factors to avoiding behavior in mariner's deciding decisions and proposed the modeling method of mariners' standard behavior for collision avoidance with a example of recognition model.

Human factors have been considered the primary reason of marine accidents. Especially, the collision between vessels is mostly mused by human behavior. However, there have not been many researches to clarify the reason of marine accidents mused by human factors quantitatively. In order to understand human factors and to enhance safe navigation systematically, using a full mission ship-handling simulator, we've investigated the characteristics of avoiding behavior taken by mariners. Further in order to apply the characteristics more widely and effectively, it's necessary to formulate the standard behavior for ship-handling in the condition of collision avoidance. Is this study, therefore, we intended to propose the concept to model the mariner's standard behavior on the handling of collision avoidance as the first step. As a result, we confirmed the contents of information processing in ship-handling that mariner's generally taking to avoid collision.

현재의 게임은 단순한 공학적 산물의 개념을 뛰어넘어 디지털화된 오락문화요 생활문화로 인식되고 있다. 이에 인간의 개인적, 사회적 욕망과 욕구에 대한 정확한 분석은 게임을 디자인하는데 있어서 좀 더 과학적인 근간을 제공해 줄 수 있을 것이다. 인간의 근원적인 욕망과 그에 대한 보상을 위한 활동에 대한 연구는 이미 오래전부터 심리학자들을 중심으로 이루어져 왔다. 이를 바탕으로 플레이어가 게임에서 얻고자하는 바와 그에 대한 보상에 대하여 연구하였다.