ABSTRACT
This paper describes the design and implementation of soft sensors to estimate cement fineness. Soft sensors are mathematical models that use available data to provide real-time information on process variables when the information, for whatever reason, is not available by direct measurement. In this application, soft sensors are used to provide information on process variable normally provided by off-line laboratory tests performed at large time intervals. Cement fineness is one of the crucial parameters that define the quality of produced cement. Providing real-time information on cement fineness using soft sensors can overcome limitations and problems that originate from a lack of information between two laboratory tests. The model inputs were selected from candidate process variables using an information theoretic approach. Models based on multi-layer perceptrons were developed, and their ability to estimate cement fineness of laboratory samples was analyzed. Models that had the best performance, and capacity to adopt changes in the cement grinding circuit were selected to implement soft sensors. Soft sensors were tested using data from a continuous cement production to demonstrate their use in real-time fineness estimation. Their performance was highly satisfactory, and the sensors proved to be capable of providing valuable information on cement grinding circuit performance. After successful off-line tests, soft sensors were implemented and installed in the control room of a cement factory. Results on the site confirm results obtained by tests conducted during soft sensor development.
ABSTRACT
Aqueous extract of Clinopodium vulgare L. showed strong antitumour activity when tested in vitro on A2058 (human metastatic melanoma), HEp-2 (epidermoid carcinoma, larynx, human) and L5178Y (mouse lymphoma) cell lines-6 h after treatment disintegration of the nuclei and cell lysis started. Applied at a concentration of 80 microg/ml it reduced the cell survival to 1.0, 5.6 and 6.6%, respectively. The concentrations of aqueous extract inhibiting the growth of A2058, HEp-2 and L5178Y cells by 50% (IC50 values) were calculated to be 20, 10 and 17.8 microg/ml respectively. Two groups of active substances were detected: the first one, probably combining glycosides, influenced adhesion, while the second one caused massive cell vacuolisation. The chloroform extract, which contained ursolic acid and gentriacontan had also cytotoxic, however a little bit weaker effect. All changes observed were irreversible.
