Deep learning is a quite useful and proliferating technique of machine learning. Various applications, such as medical images analysis, medical images processing, text understanding, and speech recognition, have been using deep learning, and it has been providing rather promising results. Both supervised and unsupervised approaches are being used to extract and learn features as well as for the multi-level representation of pattern recognition and classification. Hence, the way of prediction, recognition, and diagnosis in various domains of healthcare including the abdomen, lung cancer, brain tumor, skeletal bone age assessment, and so on, have been transformed and improved significantly by deep learning. By considering a wide range of deep-learning applications, the main aim of this paper is to present a detailed survey on emerging research of deep-learning models for bone age assessment (e.g., segmentation, prediction, and classification). An enormous number of scientific research publications related to bone age assessment using deep learning are explored, studied, and presented in this survey. Furthermore, the emerging trends of this research domain have been analyzed and discussed. Finally, a critical discussion section on the limitations of deep-learning models has been presented. Open research challenges and future directions in this promising area have been included as well.
The present study was done to know the effects of supplementations of vitamin C and E on humoral immune response against Newcastle Disease (ND) and Infectious Bursal Disease (IBD) and on lymphoid organs in broiler birds. One hundred and twenty day old chicks were purchased from a local hatchery and were reared in an open house shed. On day 5 th all the chick divided randomly into 4 groups A, B, C and D (30 birds in each). On the day 5 th and 11 th , the chicks were vaccinated against ND and Disease IBD. Booster doses of both vaccines were given on day 28. The chicks were offered Vitamin E (600 mg l -1 ), Vitamin C (600 mg l -1 ) and Vitamin E+C (300 mg l -1 each), for 5 consecutive days in drinking water on day 5 and 28. Weekly serum Hemagglutination Inhibition (HI) antibody titers against ND virus, total body weight, feed conversion ratio (FCR) and weight of lymphoid organs were recorded until the day 49. Geometric mean HI antibody titers against ND remained maximum in group C. Statistical analysis revealed a non significant (P<0.05) differences among the various treatment groups in weight gain. At day 49, the total weight gain was maximum in group C (2196.0 gm) followed by group A (2155.0 g), group B (2146 g) and group D (2094 gm). The feed conversion ratio was the best in the group B (1.66) followed by group C (1.69) with a non significant difference. From the study, it was concluded that the combined effect of Vitamin E+C was better as compared to separate supplementation of Vitamin E and Vitamin C.
Water scarcity is a universal environmental constraint for agricultural sustainability and production. Two field experiments were accomplished during the 2012 and 2013 growing seasons in two sites: the experimental farm of Suez Canal University, Ismailia and Romana Province, North Sinai, Egypt to evaluate 21 genotypes of maize comprising six inbred lines and their 15 F1 crosses for their drought tolerance. The experiments were arranged as a split-plot design with three replications, where moisture levels (100 and 50% of evapotranspiration) and maize genotypes were allocated to main plots and sub-plots, respectively. Results showed reduction in performance for most measured traits in response to water stress with varying degrees with yield plant-1 being the most affected. Inversely, proline and relative water content and anthesis-silking interval were increased. Correlation results confirmed the reduced grain yield with the increasing anthesis-silking interval, and suggested kernels row-1, relative water content, peroxidase activity and rows ear-1 in Ismailia, and rows ear-1, relative water content, peroxidase activity, kernel weight in Romana were indirect selection criteria for increasing yield in water scarcity environments. Principal component (PC) analysis showed that three PCs having Eigen value >1 explained 70.67 and 70.16%; 69.79 and 71.38% of the total variability among genotypes in control and stress conditions in Ismailia and Romana, respectively. The crosses P1?P3, P4?P6, P3?P5 and P1?P5 were classified as drought tolerant under Ismailia and Romana conditions. On the other hand, P1xP4, P3xP4, and P4 were considered as drought sensitive in Ismailia conditions. In addition, P5, P2?P4, P1?P4 and P5?P6 were the most affected by water deficiency under Romana conditions.
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