[An approach for segmentation of X-ray angiographic image based on region-growing and structure inferring].

We presented a new method for vessel segmentation and vascular structure recognition for coronary angiographic images. During vessel segmentation, a new vessel function was proposed to attain vessel feature map. Then the region growing algorithm was implemented with an automatic selection of seed point, extraction of main vessel branch, and vessel detail repairing. In the algorithm of vascular structure recognition, a fuzzy operator was used, which can detect the structures of vascular segments, bifurcations, crosses, and tips. The experimental results indicated that there was about 5 percent larger vessel region which was extracted by the proposed segmentation method than that by the simple region growing algorithm, and several thinner vessels were resumed from the lower gray region. The results also indicated that the fuzzy operator could correctly infer the simulative and real vessel structure with 100% and 90.59% correctness rate on the average, respectively.

Effect of ultrasonic treatment on the quality of Mianning ham.

This paper investigates the optimal process for ultrasonic desalination of Mianning ham. The study analyzed various factors such as ultrasonic treatment time, temperature, and power to determine their impact on the rate of desalination of hams. A single factor test was conducted to study the rate of desalination. Further, A Box-Behnken experimental design was used to evaluate the effect of Mianning ham desalination. The design examined the impacts of ultrasound on the physicochemical properties, texture, and sensory of the ham. Response surface processing group underwent oral processing to determine the optimal ultrasonic treatment conditions with the highest acceptance level. The results show that the best conditions were: ultrasonic time 84.56 min, ultrasonic temperature 40.35°C, and ultrasonic power 150.85 W. The average desalination rate of the ham under the optimal conditions was 25.93% ± 0.69%, and the hardness was 4.48 N ± 0.62 N. Overall, this process significantly improved the desalination rate, texture, and sensory quality of Mianning ham, providing solid theoretical support for desalination processing at the back end of ham.

The tiger genome and comparative analysis with lion and snow leopard genomes.

Tigers and their close relatives (Panthera) are some of the world's most endangered species. Here we report the de novo assembly of an Amur tiger whole-genome sequence as well as the genomic sequences of a white Bengal tiger, African lion, white African lion and snow leopard. Through comparative genetic analyses of these genomes, we find genetic signatures that may reflect molecular adaptations consistent with the big cats' hypercarnivorous diet and muscle strength. We report a snow leopard-specific genetic determinant in EGLN1 (Met39>Lys39), which is likely to be associated with adaptation to high altitude. We also detect a TYR260G>A mutation likely responsible for the white lion coat colour. Tiger and cat genomes show similar repeat composition and an appreciably conserved synteny. Genomic data from the five big cats provide an invaluable resource for resolving easily identifiable phenotypes evident in very close, but distinct, species.