• Animal cells and systems
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• v.8 no.2
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• pp.77-80
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• 2004

To investigate the effect of host egg color dimorphism on the vinous-throated parrotbill (Paradoxornis webbianus) - common cuckoo (Cuculus canorus) interactions, we monitored breeding nests of vinous-throated parrotbills, and conducted model egg experiments, using two colors: white and blue. Of the 190 nests examined in this study, cuckoo parasitism occurred at 10 nests (8 blue and 2 white egg clutches, respectively), and only blue cuckoo eggs were found. This frequency was similar to the egg-color ratio of all host nests found (151 blue and 39 white egg clutches). Vinous-throated parrotbills showed high rejection rate towards both cuckoo eggs and model ones. There was a significant difference in rejection rates towards mimetic (blue) and non-mimetic (white) eggs in blue egg clutches. Mimetic eggs put in nests took significantly longer to be rejected than non-mimetic ones. The most common rejection method used by the hosts was egg ejection (puncture-ejection). The costs of ejecting non-mimetic eggs tended to be lower than those of ejecting mimetic eggs. These results indicate that egg-color dimorphism in this species favors the individuals having white egg clutches in terms of higher rejection rate and lower ejection costs of the parasitic eggs. This study also suggests that egg-color dimorphism of the vinous-throated parrotbill decreases the effect of cuckoo parasitism on host populations.

• International Journal of Industrial Entomology and Biomaterials
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• v.8 no.1
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• pp.51-59
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• 2004

Phylogenetic relationships were analyzed among bumblebees using a portion of mitochondrial (mt) 16S ribosomal RNA (16S rRNA). Eight species of true bumblebees and one species of cuckoo bumblebee (Bombini, Apidae), collected from Korea were included in the analysis. Also, one species of true bumblebee imported from several foreign countries for pollination was included. The length of mt 16S rRNA sequence ranged from 496 bp to 508 bp and sequence divergence ranged from 1.4％ (7 bp) to 15.49％ (77bp). As expected, a high A＋T content was observed (78.5％ on average). According to the phylogeny tree derived from parsimony and maximum likelihood analysis, a monphyletic Bombus species, excluding a single cuckoo bumblebee, Psithyrus coreanus, was obtained, but the bootstrap estimate at the node supporting the monophyletic group was very weak (40％ or 46％), suggesting a very close relationship of the cuckoo bumblebee to the true bumblebee. Within Bombus species belonging to identical subgenera subgeneric specific clustering was formed with high bootstrap values, implying validity of the subgeneric names of each species: Pyrobombus for B. ardens and B. modeatus; Megabombus for B. consobrinus wittenburgi and B. koreanus; and Bombus s. str. for B. ignitus, B. hypocrita sapporoensis, and B. terrestris.

• Journal of Electrical Engineering and Technology
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• v.10 no.4
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• pp.1899-1909
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• 2015

Glaucoma is one of the most common causes of blindness which is caused by increase of fluid pressure in the eye which damages the optic nerve and eventually causing vision loss. An automated technique to diagnose glaucoma disease can reduce the physicians’ effort in screening of Glaucoma in a person through the fundal retinal images. In this paper, optimal hyper analytic wavelet transform for Glaucoma detection technique from fundal retinal images is proposed. The optimal coefficients for transformation process are found out using the hybrid GSO-Cuckoo search algorithm. This technique consists of pre-processing module, optimal transformation module, feature extraction module and classification module. The implementation is carried out with MATLAB and the evaluation metrics employed are accuracy, sensitivity and specificity. Comparative analysis is carried out by comparing the hybrid GSO with the conventional GSO. The results reported in our paper show that the proposed technique has performed well and has achieved good evaluation metric values. Two 10- fold cross validated test runs are performed, yielding an average fitness of 91.13% and 96.2% accuracy with CGD-BPN (Conjugate Gradient Descent- Back Propagation Network) and Support Vector Machines (SVM) respectively. The techniques also gives high sensitivity and specificity values. The attained high evaluation metric values show the efficiency of detecting Glaucoma by the proposed technique.