A New Viewpoint Over Reelin Now Made available

Local populations with relational databases have allowed managers and planners of health and social services to use GIS to better run their services (13). In the absence of detailed locational data for individuals accessing health services, as in the case of Entinostat manufacturer Bandar Abbas, population demand is usually summarized at the population-weighted or, more commonly, Geographic Centroids (GC) of such areas (21). Pre-defined stations considered here as patient��s locations referred as the GC (Figure 1). In the absence of individual household locations and population counts, remote sensing technology with high-resolution satellite images, i.e. QuickBird with 60 cm resolution, were used for calculating the number of homes located inside a geographical polygon. Due to the lack of census tracts in Bandar Abbas, the centroids of each geographical polygon containing at least 500 buildings were denoted as GC by using GIS (Figure 1b). We know that summarizing a population of a zone by assuming all live at the centroid may introduce errors in estimation of accessibility (3). Considering this, the points that we have selected as GC in each polygon, have equal traffic accessibility with respect to most of their polygon��s boundary. So, we have tried to minimize the errors. Sixteen GC were located in the territory of Bandar Abbas (Figure 1). Creating buffer zones ��Buffer�� is an area of specified width drawn around one or more map elements (22). In order to calculate health services-to-GC ratio for each GC, the FCA method (20) uses circles of varying radii with straight-line distances (to buffer an arbitrary Euclidean distance based on density of healthcare services) placed at the centroids of geographic polygons (GC) and counts the number of health services within the circles. This method is referred as the coverage method by some authors (14). There are also questions regarding the sensitivity of the health services-to-GC ratios to the size of the radius of the circle used in the floating catchment methodology. In Bandar Abbas, three buffer zones with 500, 1,000 and 2,000m widths were drawn separately around the hospitals. Considering the overlaps of the varying buffer zones, a width of 500m was specified as the optimal radius. Six buffer zones were drawn for hospitals (Figure 2a). Since clinics have lower facilities for patients, three buffer zones were drawn for them (Figure 2b). For hybrid state (hospitals and clinics) six buffer zones were drawn (Figure 2c). Figure 2 Calculation of different types of distances between Geographic Centroids (hypothetical patients) and healthcare services Different types of distances were calculated between healthcare services (hospitals and clinics) and patients (GC) (Figures 3, ?,44 and ?and5).5). The results were used for evaluation of the minimum distance method.