Throughout the animal kingdom there are species that have two or more phenotypic forms or ‘morphs＇, and many of these are amphibians. In North America, the red-backed salamander Plethodon cinereus can have either a ...Throughout the animal kingdom there are species that have two or more phenotypic forms or ‘morphs＇, and many of these are amphibians. In North America, the red-backed salamander Plethodon cinereus can have either a red dorsal stripe or no dorsal stripe （lead-phase form）, and evidence to date indicates the lead-phase form incurs a greater number of attacks from predators. In a recent collection of 51 P cinereus, blood smears of both color morphs （35 red-stripe, 16 lead-phase） were examined to obtain numbers of circulating leukocytes （via light microscopy）, which can be used to indirectly estimate levels of stress hormones in vertebrates via a ‘hematological stress index＇, which is the ratio between the number of two leukocyte types （neutrophils and lymphocytes）. Our results showed that lead-phase salamanders tended to have greater numbers of circulating neutrophils and lower numbers of circulating lymphocytes than red-stripe morphs, leading to higher average neutrophil-lymphocyte ratios in lead-phase individuals. Since the salamanders were held （refrigerated） for 7 days before sampling, we cannot be certain if this effect is a stress reaction to the captivity or the normal level for this morph. However comparison with two sets of related salamanders that were captured and sampled immediately indicates the red-stripe salamanders were either not stressed from the captivity at all, or their white blood cell distributions had returned to normal after 7 days of captivity. Taken together, our results indicate that lead-phase forms of P. cinereus have higher stress levels than the red-stripe forms, which may be a consequence of their higher exposure to, and/or attacks from, predators. They may also indicate that the lead-phase form is less-suited to captivity than the red-stripe form of this species.展开更多
This paper presents a supervised learning algorithm for retinal vascular segmentation based on classification and regression tree (CART) algorithm and improved adptive bosting (AdaBoost). Local binary patterns (LBP) t...This paper presents a supervised learning algorithm for retinal vascular segmentation based on classification and regression tree (CART) algorithm and improved adptive bosting (AdaBoost). Local binary patterns (LBP) texture features and local features are extracted by extracting,reversing,dilating and enhancing the green components of retinal images to construct a 17-dimensional feature vector. A dataset is constructed by using the feature vector and the data manually marked by the experts. The feature is used to generate CART binary tree for nodes,where CART binary tree is as the AdaBoost weak classifier,and AdaBoost is improved by adding some re-judgment functions to form a strong classifier. The proposed algorithm is simulated on the digital retinal images for vessel extraction (DRIVE). The experimental results show that the proposed algorithm has higher segmentation accuracy for blood vessels,and the result basically contains complete blood vessel details. Moreover,the segmented blood vessel tree has good connectivity,which basically reflects the distribution trend of blood vessels. Compared with the traditional AdaBoost classification algorithm and the support vector machine (SVM) based classification algorithm,the proposed algorithm has higher average accuracy and reliability index,which is similar to the segmentation results of the state-of-the-art segmentation algorithm.展开更多
基金Funding for AKD during this project was provided by the DBWarnell School of Forestry and Natural Resources and a grant from the Morris Animal FoundationSupport for the field word of this project came form an NSF grant (NSF-DEB DEB0542974)
文摘Throughout the animal kingdom there are species that have two or more phenotypic forms or ‘morphs＇, and many of these are amphibians. In North America, the red-backed salamander Plethodon cinereus can have either a red dorsal stripe or no dorsal stripe （lead-phase form）, and evidence to date indicates the lead-phase form incurs a greater number of attacks from predators. In a recent collection of 51 P cinereus, blood smears of both color morphs （35 red-stripe, 16 lead-phase） were examined to obtain numbers of circulating leukocytes （via light microscopy）, which can be used to indirectly estimate levels of stress hormones in vertebrates via a ‘hematological stress index＇, which is the ratio between the number of two leukocyte types （neutrophils and lymphocytes）. Our results showed that lead-phase salamanders tended to have greater numbers of circulating neutrophils and lower numbers of circulating lymphocytes than red-stripe morphs, leading to higher average neutrophil-lymphocyte ratios in lead-phase individuals. Since the salamanders were held （refrigerated） for 7 days before sampling, we cannot be certain if this effect is a stress reaction to the captivity or the normal level for this morph. However comparison with two sets of related salamanders that were captured and sampled immediately indicates the red-stripe salamanders were either not stressed from the captivity at all, or their white blood cell distributions had returned to normal after 7 days of captivity. Taken together, our results indicate that lead-phase forms of P. cinereus have higher stress levels than the red-stripe forms, which may be a consequence of their higher exposure to, and/or attacks from, predators. They may also indicate that the lead-phase form is less-suited to captivity than the red-stripe form of this species.
基金National Natural Science Foundation of China(No.61163010)
文摘This paper presents a supervised learning algorithm for retinal vascular segmentation based on classification and regression tree (CART) algorithm and improved adptive bosting (AdaBoost). Local binary patterns (LBP) texture features and local features are extracted by extracting,reversing,dilating and enhancing the green components of retinal images to construct a 17-dimensional feature vector. A dataset is constructed by using the feature vector and the data manually marked by the experts. The feature is used to generate CART binary tree for nodes,where CART binary tree is as the AdaBoost weak classifier,and AdaBoost is improved by adding some re-judgment functions to form a strong classifier. The proposed algorithm is simulated on the digital retinal images for vessel extraction (DRIVE). The experimental results show that the proposed algorithm has higher segmentation accuracy for blood vessels,and the result basically contains complete blood vessel details. Moreover,the segmented blood vessel tree has good connectivity,which basically reflects the distribution trend of blood vessels. Compared with the traditional AdaBoost classification algorithm and the support vector machine (SVM) based classification algorithm,the proposed algorithm has higher average accuracy and reliability index,which is similar to the segmentation results of the state-of-the-art segmentation algorithm.
