STRUCTURE OF METHYLPHEOPHORBIDE-RCI

he methanolic extract of the cyanobacterium (blue-green alga) Spirulina geitleri has been treated with methanolic acid to convert all chlorophyllous pigments to their methylpheophorbides. Fractionation of the latter from methylpheophorbide a by thin layer chromatography and high pressure liquid chromatography yielded methylpheophorbide-RCI. Its structure has been determined as 132S-hydroxy-20-chloro-methylpheophorbide a by 1H-nuclear magnetic resonance, absorption and circular dichroism spectroscopy, mass spectrometry and by partial synthesis from chlorophyll a. The pigment is isolated from Spirulina geitleri irrespective of the use or omission of chlorinated substances during the isolation procedure

Analisis de los sistemas de trabajo del Sernac alternativas de mejoramiento

141 p.El Servicio Nacional del Consumidor (SERNAC) es un organismo publico dependiente del Ministerio de Economía, Fomento y Reconstrucción cuya finalidad es la de velar por los Derechos y Deberes de los agentes económicos que participan en las relaciones de consumo. Además Orienta, Educa y Entrega información a la comunidad a modo de que exista una mayor información acerca de los Bienes y Servicios que se transan en el mercado, de manera de hacerlo mas transparente y eficiente. La presente Tesis consiste en un estudio acabado y detallado de los Sistemas de Trabajo que actualmente realiza el Sernac, con la finalidad de proponer alternativas de mejoramiento a modo de que la institución cumpla de mejor manera los objetivos que son el propósito fundamental de su creación

Small number enumeration processes of deaf or hard-of-hearing students: A study using eye tracking and artificial intelligence

Students who are deaf or hard-of-hearing (DHH) often show significant difficulties in learning mathematics. Previous studies have reported that students who are DHH lag several years behind in their mathematical development compared to hearing students. As possible reasons, limited learning opportunities due to a lesser incidental exposure to numerical ideas, delays in language and speech development, and further idiosyncratic difficulties of students who are DHH are discussed; however, early mathematical skills and their role in mathematical difficulties of students who are DHH are not explored sufficiently. In this study, we investigate whether students who are DHH differ from hearing students in their ability to enumerate small sets (1-9)-an ability that is associated with mathematical difficulties and their emergence. Based on a study with N = 63 who are DHH and N = 164 hearing students from third to fifth grade attempting 36 tasks, we used eye tracking, the recording of students' eye movements, to qualitatively investigate student enumeration processes. To reduce the effort of qualitative analysis of around 8,000 student enumeration processes (227 students x 36 tasks), we used Artificial Intelligence, in particular, a clustering algorithm, to identify student enumeration processes from the heatmaps of student gaze distributions. Based on the clustering, we found that gaze distributions of students who are DHH and students with normal hearing differed significantly on a group level, indicating differences in enumeration processes, with students who are DHH using advantageous processes (e.g., enumeration at a glance) more often than hearing students. The results indicate that students who are DHH do not lag behind in small number enumeration as compared to hearing students but, rather, appear to perform better than their hearing peers in small number enumeration processes, as well as when conceptual knowledge about the part-whole relationship is involved. Our study suggests that the mathematical difficulties of students who are DHH are not related to difficulties in the small number enumeration, which offers interesting perspectives for further research

Detecting and monitoring change in models

Schaffernicht, M. Facultad de Ciencias Empresariales, Universidad de Talca, Avenida Lircay s/n, Talca, Chile.System dynamics is often brought into connection with a double-loop learning process. Learning has been the object of an increasing number of studies. However, inquiry has focused on using models rather than modeling, and there are huge differences in assessment approaches. If learning changes models then it can be inferred from comparing models. Here it is argued that monitoring learning from modeling is feasible and desirable. One possibility is to conceive of a model as a series of versions and compare their structure. One possible method for comparing model versions is presented