Effect of cinnamon essential oil dietary supplementation on the growth, fatty acid composition, and meat quality of tilapia.

This study was conducted to investigate the effects of dietary supplementation of 0%, 0.2%, 0.35%, and 0.5% cinnamon essential oil on growth performance, fatty acid, and fillet quality of tilapia (Oreochromis niloticus). The results of growth experiments showed that the weight gain rate linearly and quadratically increased with increasing cinnamon essential oil doses (p < 0.05). The results of fatty acids experiments showed that the addition of essential oil significantly decreased the saturated fatty acids levels from 36.67% to 30.82% and increased the polyunsaturated fatty acids (PUFA) levels from 24.55% to 46.89%; especially, the n - 3 PUFA of 0.5% essential oil treatment showed the highest levels. Moreover, the n - 6 PUFA of 0.2% essential oil treatment were increased from 22.17% to 32.99%. The results of fillet quality experiments showed that the hardness and cohesiveness were linearly and quadratically increased with the increasing essential oil doses on days 4 and 7, respectively. The b* values linearly and quadratically decreased as the doses increased on day 7 (p < 0.05). The total volatile basic nitrogen levels were quadratically decreased with increasing cinnamon essential oil doses on day 7 (p < 0.05). In general, it can be concluded that cinnamon essential oil presented positive effects on the growth, nutritive values, and meat quality in tilapia.

HGR-Net: Hierarchical Graph Reasoning Network for Arbitrary Shape Scene Text Detection.

As a prerequisite step of scene text reading, scene text detection is known as a challenging task due to natural scene text diversity and variability. Most existing methods either adopt bottom-up sub-text component extraction or focus on top-down text contour regression. From a hybrid perspective, we explore hierarchical text instance-level and component-level representation for arbitrarily-shaped scene text detection. In this work, we propose a novel Hierarchical Graph Reasoning Network (HGR-Net), which consists of a Text Feature Extraction Network (TFEN) and a Text Relation Learner Network (TRLN). TFEN adaptively learns multi-grained text candidates based on shared convolutional feature maps, including instance-level text contours and component-level quadrangles. In TRLN, an inter-text graph is constructed to explore global contextual information with position-awareness between text instances, and an intra-text graph is designed to estimate geometric attributes for establishing component-level linkages. Next, we bridge the cross-feed interaction between instance-level and component-level, and it further achieves hierarchical relational reasoning by learning complementary graph embeddings across levels. Experiments conducted on three publicly available benchmarks SCUT-CTW1500, Total-Text, and ICDAR15 have demonstrated that HGR-Net achieves state-of-the-art performance on arbitrary orientation and arbitrary shape scene text detection.

Enhancement of recombinant human serum albumin in transgenic rice cell culture system by cultivation strategy.

Fusion of the sugar-starvation-induced αAmy3 promoter with its signal peptide has enabled secretion of recombinant human serum albumin (rHSA) into the culture medium. To simplify the production process and increase the rHSA yield in rice suspension cells, a one-step strategem without medium change was adopted. The yield of rHSA was increased sixfold by this one-step approach compared with the two-step recombinant protein process, in which a change of the culture medium to sugar-free medium is required. The one-step strategem was applied to check repeated cycle of rHSA production, and the production of rHSA was also higher in each cycle in the one-step, as opposed to the two-step, production process. The use of the one-step process resulted in fewer damaged cells during the cell sugar starvation phase for recombinant protein production. Furthermore, we scaled up the rHSA production in a 2-L airlift and a 2-L stirred tank bioreactor by the one-step approach, and concluded that rHSA can be enriched to 45 mg L(-1) in plant culture commonly used MS medium by the airlift-type bioreactor. Our results suggest that rHSA production can be enriched by this optimized cultivation strategem.