3 resultados para principal components analysis (PCA) algorithm

em Helda - Digital Repository of University of Helsinki


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The purpose of this research was to evaluate the special vocational training programme, which aimed at enhancing the pupils with autism spectrum to prepare themselves for work and independent life. The vocational training programme is based on TEACCH (Treatment and Education of Autistic and Related Communication handicapped CHildren), which takes into account the autism spectrum disorders and autistic behaviour. TEACCH is based on the principles of structured teaching, functional teaching and preparation training for work and independent life. The TEACCH has been adapted to Finnish society and the educational system. Treatment programmes were individually designed for each student´s educational needs. There is also an important role for the AAPEP rating scale (Adolescent and Adult Psychoeducational Profile). The AAPEP has been the major tool for planning and following the courses. The AAPEP is an assessment instrument designed by the TEACCH programme, and it is used to provide an evaluation of current and potential skills. The AAPEP contains three scales: a direct observation scale, a home scale and a school / work scale. The AAPEP includes six test variables: vocational skills, independent functions, functional communication, interpersonal behaviour, vocational behaviour and leisure skills; these are evaluated at three levels: pass, emerge and fail. The subjects were 49 students (65% male and 35 % female) with autism spectrum, who have been followed and tested several times, also one year after the vocational training. The design is therefore a longitudinal one. The research data were collected 1997-2004 using the AAPEP rating scales. The teachers have used the AAPEP scales and the codings have been checked by the researcher. The results of the principal component analysis (PCA) suggested that the structure of AAPEP rating scales works quite well as a hypothesis. The factor structure of the scales of the AAPEP was almost the same in these data as in the original publications. The learning-and-changes results showed that learning is a slow process, but that there were also intended changes in several AAPEP areas. The Cohen´s kappa was used as an effect-size measure and the most important result of this research showed that the student´s skills were developing on a school / work scale; vocational skills variable (0,34), vocational behaviour variable (0,28), leisure skills variable (0,26) and on a direct observation scale; interpersonal behaviour variable (0,21). On a home scale skills of some students were developing negatively and also that effect-size was small. The results showed that the students´ vocational skills and vocational behaviour will continue to develop after school in many areas. There were differences between scales. The result of this research shows that the student´s skills were developing significantly in 3 of 48 variables on a direct observation scale and also on a home scale. On a school / work scale student´s skills were developing significantly in 17 of 48 variables. This result implies that students can do the work without extra assistance if there exist continuing supports for the skills after the vocational training. The fully independent life of students will be difficult, because their independent functions, functional communications and leisure skills regressed after the schooling. This seems to indicate that they will not manage their daily life without support. The students and their parents said that the treatment programmes were individually designed for each student s educational needs, and that they were satisfied with the programmes and services. Generally, it can be concluded that vocational special education can be developed for pupils with autistic syndrome and the detailed teaching can be done using TEACCH principles and applying the tool of AAPEP.

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Historical sediment nutrient concentrations and heavy-metal distributions were studied in five embayments in the Gulf of Finland and an adjacent lake. The main objective of the study was to examine the response of these water bodies to temporal changes in human activities. Sediment cores were collected from the sites and dated using 210Pb and 137Cs. The cores were analyzed for total carbon (TC), total nitrogen (TN), total phosphorus (TP), organic phosphorus (OP), inorganic phosphorus (IP), biogenic silica (BSi), loss on ignition (LOI), grain size, Cu, Zn, Al, Fe, Mn, K, Ca, Mg and Na. Principal component analysis (PCA) was used to summarize the trends in the geochemical variables and to compare trends between the different sites. The links between the catchment land use and sediment geochemical data were studied using a multivariate technique of redundancy analysis (RDA). Human activities produce marked geochemical variations in coastal sediments. These variations and signals are often challenging to interpret due to various sedimentological and post-depositional factors affecting the sediment profiles. In general, the sites studied here show significant upcore increases in sedimentation rates, TP and TN concentrations. Also Cu, which is considered to be a good indicator of anthropogenic influence, showed clear increases from 1850 towards the top part of the cores. Based on the RDA-analysis, in the least disturbed embayments with high forest cover, the sediments are dominated by lithogenic indicators Fe, K, Al and Mg. In embayments close to urban settlement, the sediments have high Cu concentrations and a high sediment Fe/Mn ratio. This study suggests that sediment accumulation rates vary significantly from site to site and that the overall sedimentation can be linked to the geomorphology and basin bathymetry, which appear to be the major factors governing sedimentation rates; i.e. a high sediment accumulation rate is not characteristic either to urban or to rural sites. The geochemical trends are strongly site specific and depend on the local geochemical background, basin characteristics and anthropogenic metal and nutrient loading. Of the studied geochemical indicators, OP shows the least monotonic trends in all studied sites. When compared to other available data, OP seems to be the most reliable geochemical indicator describing the trophic development of the study sites, whereas Cu and Zn appear to be good indicators for anthropogenic influence. As sedimentation environments, estuarine and marine sites are more complex than lacustrine basins with multiple sources of sediment input and more energetic conditions in the former. The crucial differences between lacustrine and estuarine/coastal sedimentation environments are mostly related to Fe. P sedimentation is largely governed by Fe redox-reactions in estuarine environments. In freshwaters, presence of Fe is clearly linked to the sedimentation of other lithogenic metals, and therefore P sedimentation and preservation has a more direct linkage to organic matter sedimentation.

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Tiivistelmä ReferatAbstract Metabolomics is a rapidly growing research field that studies the response of biological systems to environmental factors, disease states and genetic modifications. It aims at measuring the complete set of endogenous metabolites, i.e. the metabolome, in a biological sample such as plasma or cells. Because metabolites are the intermediates and end products of biochemical reactions, metabolite compositions and metabolite levels in biological samples can provide a wealth of information on on-going processes in a living system. Due to the complexity of the metabolome, metabolomic analysis poses a challenge to analytical chemistry. Adequate sample preparation is critical to accurate and reproducible analysis, and the analytical techniques must have high resolution and sensitivity to allow detection of as many metabolites as possible. Furthermore, as the information contained in the metabolome is immense, the data set collected from metabolomic studies is very large. In order to extract the relevant information from such large data sets, efficient data processing and multivariate data analysis methods are needed. In the research presented in this thesis, metabolomics was used to study mechanisms of polymeric gene delivery to retinal pigment epithelial (RPE) cells. The aim of the study was to detect differences in metabolomic fingerprints between transfected cells and non-transfected controls, and thereafter to identify metabolites responsible for the discrimination. The plasmid pCMV-β was introduced into RPE cells using the vector polyethyleneimine (PEI). The samples were analyzed using high performance liquid chromatography (HPLC) and ultra performance liquid chromatography (UPLC) coupled to a triple quadrupole (QqQ) mass spectrometer (MS). The software MZmine was used for raw data processing and principal component analysis (PCA) was used in statistical data analysis. The results revealed differences in metabolomic fingerprints between transfected cells and non-transfected controls. However, reliable fingerprinting data could not be obtained because of low analysis repeatability. Therefore, no attempts were made to identify metabolites responsible for discrimination between sample groups. Repeatability and accuracy of analyses can be influenced by protocol optimization. However, in this study, optimization of analytical methods was hindered by the very small number of samples available for analysis. In conclusion, this study demonstrates that obtaining reliable fingerprinting data is technically demanding, and the protocols need to be thoroughly optimized in order to approach the goals of gaining information on mechanisms of gene delivery.