Abstract: A W/O/W type composite emulsion, wherein a W/O type emulsion containing water, an oil ingredient and a lipophilic emulsifier each in a proportion expressed in term of mass ratio falling within a range enclosed with bold lines in FIG. 1 is dispersed in an external aqueous phase with a water-soluble macromolecule blended therein has a sufficient stability, and permits preserving a percent inclusion of medical substances included in an internal aqueous phase of the W/O/W type composite emulsion at a high level. Because of the characteristics, it is now possible to blend in a liquid formulation medical substances having an unfavorable taste or unstable medical substances which have to date hardly been included in liquid formulations with low viscosity, so that the W/O/W type composite emulsion can be utilized for liquid formulations including a liquid formulation for internal application, injections, etc.

Abstract: A W/O/W type composite emulsion, wherein a W/O type emulsion containing water, an oil ingredient and a lipophilic emulsifier each in a proportion expressed in term of mass ratio falling within a range enclosed with bold lines in FIG. 1 is dispersed in an external aqueous phase with a water-soluble macromolecule blended therein has a sufficient stability, and permits preserving a percent inclusion of medical substances included in an internal aqueous phase of the W/O/W type composite emulsion at a high level.

Abstract: In system and method for predicting an occurrence of failure in a machine tool, at least one monitor data (for example, position deviation variable of a tool with respect to a target position of the tool as a result of rotation of a servomotor) which is changed according to an operating situation in a series of working processes in the machine tool is detected, a prediction level of failure against the monitor data is set, the prediction level being set according to the operating situation, a comparison period of time is set according to the series of the working processes, the monitor data detected is compared with the prediction level set during a predetermined one of the series of working processes of the machine tool set as the comparison period of time, a failure prediction signal is output when the value of the monitor data exceeds the prediction level, and the prediction of the occurrence of failure is informed through a CRT on the basis of the received failure prediction signal.