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One of the most important steps in solid waste management is the selection of an appropriate landfill site. The site selection process requires the evaluation and analysis of several criteria. However, the traditional evaluation method is not sufficient for the site selection process. Geographical information system (GIS) technologies are effectively used in the process of site selection, which is a spatial problem. This article describes a raster GIS-based landfill site selection (LSS) method. This method utilizes a raster-based spatial database in which the factors affect the landfill site selection. The final product in this method is the cost surface map showing pixel-based values of the appropriate areas. Furthermore, this GIS-based LSS method was applied for the evaluation of two landfill sites in Trabzon Province in Turkey, for which the traditional evaluation method for site selection was used. The suitability values on the cost surface map of these two landfills have shown that these sites are not appropriate for a solid waste landfill. In conclusion, it was demonstrated that the method of raster GIS-based site selection gives more effective results than traditional methods.

A 2-D reference map in pI range 3-10 was constructed for the soluble protein fraction of Phanerochaete chrysosporium growing vegetatively under standard conditions. Functional annotation could be made for 517 spots out of 720 that were subjected to MALDI-TOF-MS analysis, according to the specific accession numbers from the P. chrysosporium genomic database. Further analysis of the data revealed 314 distinct ORFs, 118 of which yielded multiple spots on the master gel. Functional classification of the proteins was made according to the eukaryote orthologous groups defined in the organism's genome website. The functional class of PTMs, protein turnover and chaperones was represented with the highest number (63) of the identified ORFs. Six proteins were assigned to the hypothetical proteins and 29 were predicted to have a signal peptide sequence. Subcellular localization predictions were also made for the identified proteins. Of the protein spots detected on the master gel, 380 were found to be probably phosphorylated and 96 of these matched to the identified proteins. The reference map was efficiently used in the identification of the proteins differentially expressed under cadmium and copper stress. Three new ribosomal proteins as well as zinc-containing alcohol dehydrogenase, glucose-6-phosphate isomerase, flavonol/cinnamoyl-CoA reductase, H+-transporting two-sector ATPase, ribosomal protein S7, ribosomal protein S21e, elongation factor EF-1 alpha subunit were demonstrated as the most strongly induced.

No abstract

Rapid population growth, economic development and industrialization have created many problems related to municipal solid waste management (MSWM) in developing countries like Turkey. Solid waste disposal has become mandatory because of increasingly common factors such as global warming and contamination of water resources. In recent years, this situation has revealed the need for effective management of solid waste. Suitable site selection requires evaluation and analysis of multiplefactor. Therefore, it is very important that the design of landfill site selection take into account environmental, economical and sociologicalfactors. In order to do this, the Geographical Information System (GIS) used with Multi Criteria Decision Making (MCDM) techniques is a useful tool for creating a model. One such MCDM is the Spatial-integrated Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). In this study, TOPSIS was applied to integrate environmental, economical and sociological sensitivity into determine alternative solid waste landfill sites for Bursa Province, Turkey. Using the data obtained by comparing the geo-statistics, six of the most suitable landfill areas were determined. In the final stage, as a result of this study, the Kayapa district was identified as the most suitable landfill area.