Keywords
Organochlorine Pesticides; Human Breast Milk; Pine Needles; Hasse Diagram Technique; PyHasse software
Location
Session E2: Environmental Modeling of Human Health Effects from Global to Local Scale
Start Date
18-6-2014 9:00 AM
End Date
18-6-2014 10:20 AM
Abstract
In a recently performed monitoring project, 18 OCPs (Organochlorine pesticides) in paired samples of pine needles and human breast milk samples were analysed in different regions in the Taurus Mountains in Turkey. The aim of our data evaluation approach is to find out whether there are conformities between the paired human breast milk and pine needle samples. An appropriate data analysis method to identify such conformities and differences is the discrete mathematical method named Hasse diagram technique. The software package used is the PyHasse software. It comprises several modules, which are of great support in the evaluation of environmental data. In this presentation we applied the main Hasse Diagram Technique Module (mHDCI2_7). the Similarity Analysis, and teh CombiSimilarity7 for the comparison of two data matrices. The new module CombiSimilarity resulted in evidence that needles' and breast milk pollution are similar if taken here from related locations. This means that although we find visible differences in the Hasse diagrams of breast milk samples and needles, the calculations by the new CombiSimilarity tool reveal conformity of the two data sets.
Included in
Civil Engineering Commons, Data Storage Systems Commons, Environmental Engineering Commons, Hydraulic Engineering Commons, Other Civil and Environmental Engineering Commons
Modelling similarities of Endocrine Disruptors in Pine Needles and Human Breast Milk
Session E2: Environmental Modeling of Human Health Effects from Global to Local Scale
In a recently performed monitoring project, 18 OCPs (Organochlorine pesticides) in paired samples of pine needles and human breast milk samples were analysed in different regions in the Taurus Mountains in Turkey. The aim of our data evaluation approach is to find out whether there are conformities between the paired human breast milk and pine needle samples. An appropriate data analysis method to identify such conformities and differences is the discrete mathematical method named Hasse diagram technique. The software package used is the PyHasse software. It comprises several modules, which are of great support in the evaluation of environmental data. In this presentation we applied the main Hasse Diagram Technique Module (mHDCI2_7). the Similarity Analysis, and teh CombiSimilarity7 for the comparison of two data matrices. The new module CombiSimilarity resulted in evidence that needles' and breast milk pollution are similar if taken here from related locations. This means that although we find visible differences in the Hasse diagrams of breast milk samples and needles, the calculations by the new CombiSimilarity tool reveal conformity of the two data sets.
