RESUMO
Golden pompano (Trachinotus blochii) is an economically important fish which exhibits sexual size dimorphism and is widely cultivated in the southern seas of China. To evaluate the nutritional composition of T. blochii of different mariculture areas, growth stages, and genders, the moisture, ash, amino acids, and fatty acids in the muscle were measured using national standard biochemical assay. The analysis found 16 kinds of amino acids in the muscle of T. blochii. The EAA contents of fish from Guangdong (GD) and Guangxi (GX) were significantly lower than those of Hainan (HN) and Fujian (FJ) (p < 0.05). The unsaturated fatty acids were higher in T. blochii cultured in HN and FJ (p < 0.05). Within the same sea area, the contents of TAA, EAA, DAA, and PUFA increased with growth in T. blochii, but the differences were not significant (p > 0.05). EAA/TAA and EAA/NEAA conformed to the ideal FAO/WHO model. The AAS, CS, and EAAI scores of amino acids within groups gradually increased with growth. The TAA, EAA and PUFA contents in females were higher than in males (p > 0.05). The slightly higher amounts of amino acids and fatty acids in female T. blochii indicated females had higher nutritional value. In conclusion, the HN and FJ groups, the later growth stages, and the female T. blochii had generally higher nutritional values than their respective counterparts. These results provide fundamental data supporting all-female T. blochii breeding and culture, and optimized marketing body size.
RESUMO
Fish skin color is usually strongly affected by the background color of their environment. The study investigated the effects of five different background colors on the skin color of leopard coral groupers (Plectropomus leopardus). More than 450 juveniles were reared in Blue, Red, Black, White, and Transparent background tanks for 56 days. The paraffin section showed that the skin melanin zone of fish in the White group was smaller, whereas the Black and Red groups (especially Black) were nearly the largest. The apparent skin color of P. leopardus was red on the white background, which darkened in response to the other color backgrounds. The Black group revealed the blackest skin color, followed by the transparent group. Moreover, the White group had the highest L*, a*, and b* values. The melanin content and tyrosinase activity in the dorsal and ventral skin of the Black group were significantly higher than those in the other groups (p < 0.05), and the serum α-MSH level was higher in the Black group as well. The carotenoid and lutein contents showed completely different trends among the experimental groups, as carotenoid content was higher in the Red and White groups, while lutein content was higher in the Transparent group. The expression level of scarb1 was highest in the Blue and White groups, followed by the Transparent group, and lowest in the Black group (p < 0.05). The expression trend of scarb1 was similar to the skin color in different backgrounds, indicating that the background color regulated scarb1 expression level through visual center, then influenced the uptake and transport of carotenoids, then influenced the skin color formation of P. leopardus. Moreover, lighter colors inhibited the formation of melanocytes and had a significant effect on carotenoid and lutein contents. Pigment-related genes were involved in the regulation of fish skin color, and they were affected by background color in P. leopardus. These results indicate that a white background is more conducive to maintaining red skin color in juvenile P. leopardus.
RESUMO
Accurate segmentation of electrocardiogram (ECG) waves is crucial for cardiovascular diseases (CVDs). In this study, a bidirectional hidden semi-Markov model (BI-HSMM) based on the probability distributions of ECG waveform duration was proposed for ECG wave segmentation. Four feature-vectors of ECG signals were extracted as the observation sequence of the hidden Markov model (HMM), and the statistical probability distribution of each waveform duration was counted. Logistic regression (LR) was used to train model parameters. The starting and ending positions of the QRS wave were first detected, and thereafter, bidirectional prediction was employed for the other waves. Forwardly, ST segment, T wave, and TP segment were predicted. Backwardly, P wave and PQ segments were detected. The Viterbi algorithm was improved by integrating the recursive formula of the forward prediction and backward backtracking algorithms. In the QT database, the proposed method demonstrated excellent performance (Acc = 97.98%, F1 score of P wave = 98.37%, F1 score of QRS wave = 97.60%, F1 score of T wave = 97.79%). For the wearable dynamic electrocardiography (DCG) signals collected by the Shandong Provincial Hospital (SPH), the detection accuracy was 99.71% and the F1 of each waveform was above 99%. The experimental results and real DCG signal validation confirmed that the proposed new BI-HSMM method exhibits significant ability to segment the resting and DCG signals; this is conducive to the detection and monitoring of CVDs.
