Irestigation limnological in Bahmanshir River

Bahmanshir River derived from Karoon River and finally connected to Arvandrood that passed from Abadan and then flow into the Persian Gulf. Because of low slope of Bahmanshir River from Ahwaz to Abadan, tidal flow intrusion long distance in Bahmanshir, Arvandrood and Karoon. Sampling from physical and chemical parameters and phytoplankton were done by Nansen sampler, benthic sampling, heavy metals, TOM and grain size sampling were done by grab. Samplings of zooplankton were done by filtering 20 liters water in 100μ mesh size net from middepth of river water. Fish sampling were done by gill net, Trawl net, sobor gill net and stable net with 20, 27, 30, 35, 39, 40 mesh sizes. Physical and Chemical parameters were more similar from station one to four but there were some differences with station five in mouth of river in the sea. Nitrate showed same variations in all studied stations and maximum concentration of nitrite was observed in station five in June and July. The highest value of Total hardness and salinity were observed in station five. The range of pH was 7.2 to 8.5. Cd and Zn were found to be the lowest and the highest concentration in sediments respectively. Annual average following as: Cd < Co < Cu < Pb = Ni < Zn According to ISQGs and river water quality standards, chemical and physical parameters and sediment heavy metals were in acceptable range. Only Cd and Zn values were found higher than acceptable ranges. No significant difference was observed between stations for heavy metal concentrations. In general, 44 phytoplankton species were identified Bacillariophycea (77.74%), Cyanophycea( 10.39%), (Chlorophycae 8.88%) and (Dinophycea 2.99%) were the dominant phytoplankton classes in this study. Shannon index have shown the highest species diversity during one year in January and the lowest was in fourth station. 110 Phytoplankton species composition in Bahmanshir have shown that Bacillariophycea became higher from river to estuary and among zooplanktons Rotifera and Tintinida were the most frequent groups in estuary region with 83% of total abundance. Copepoda, Rotifera and Protozoa (especially Tintinida) were the most frequent zooplankton groups. The highest frequency of zooplankton with 40.6% was observed in the station one in Khoramshahr. 16 macrobenthic groups were identified during the study. Polycheate worms, Isopoda and Oligocheate worms have shown the 83.5%, 5.4% and 3% frequencies respectively. 43 fish species that included in 26 families were identified. Cyprinidae with 12 species and Clupeidae with 2 species were the highest and the lowest species frequencies respectively. Among the identified fish species Hypophthalmichthys molitrix, Barbus esocinus, Crrassius auratus were exotic species and rest of them were local species. Seasonal changes were affected directly by quantitative and qualitative variations in Karoon water and planktonic species composition in estuary region were affected by tidal flow and advances of seawater. Cyprinidae and Barbus geniuses were the most frequent fresh water fish species. Migrant species like Johnius dussumeieri, Acanthophagus latus, Hilsa ilisha were captured in most stations and months, presence of these species is important for reproduction. Fish species of this river have different diet that included soft sediments, planktons, benthos, macroscopic plants, small fishes and shrimps

Unsupervised automated retinal vessel segmentation based on Radon line detector and morphological reconstruction

Abstract Retinal blood vessel segmentation and analysis is critical for the computer‐aided diagnosis of different diseases such as diabetic retinopathy. This study presents an automated unsupervised method for segmenting the retinal vasculature based on hybrid methods. The algorithm initially applies a preprocessing step using morphological operators to enhance the vessel tree structure against a non‐uniform image background. The main processing applies the Radon transform to overlapping windows, followed by vessel validation, vessel refinement and vessel reconstruction to achieve the final segmentation. The method was tested on three publicly available datasets and a local database comprising a total of 188 images. Segmentation performance was evaluated using three measures: accuracy, receiver operating characteristic (ROC) analysis, and the structural similarity index. ROC analysis resulted in area under curve values of 97.39%, 97.01%, and 97.12%, for the DRIVE, STARE, and CHASE‐DB1, respectively. Also, the results of accuracy were 0.9688, 0.9646, and 0.9475 for the same datasets. Finally, the average values of structural similarity index were computed for all four datasets, with average values of 0.9650 (DRIVE), 0.9641 (STARE), and 0.9625 (CHASE‐DB1). These results compare with the best published results to date, exceeding their performance for several of the datasets; similar performance is found using accuracy