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Cholesterol has been used as additive in fish feeds due to the reduced use of fish meal and fish oil. In order to evaluate the effects of dietary cholesterol supplementation (D-CHO-S) on fish physiology, a liver transcriptome analysis was performed following a feeding experiment on turbot and tiger puffer with different levels of dietary cholesterol. The control diet contained 30% fish meal (0% fish oil) without cholesterol supplementation, while the treatment diet was supplemented with 1.0% cholesterol (CHO-1.0). A total of 722 and 581 differentially expressed genes (DEG) between the dietary groups were observed in turbot and tiger puffer, respectively. These DEG were primarily enriched in signaling pathways related to steroid synthesis and lipid metabolism. In general, D-CHO-S downregulated the steroid synthesis in both turbot and tiger puffer. Msmo1, lss, dhcr24, and nsdhl might play key roles in the steroid synthesis in these two fish species. Gene expressions related to cholesterol transport (npc1l1, abca1, abcg1, abcg2, abcg5, abcg8, abcb11a, and abcb11b) in the liver and intestine were also extensively investigated by qRT-PCR. However, the results suggest that D-CHO-S rarely affected the cholesterol transport in both species. The protein-protein interaction (PPI) network constructed on steroid biosynthesis-related DEG showed that in turbot, Msmo1, Lss, Nsdhl, Ebp, Hsd17b7, Fdft1, and Dhcr7 had high intermediary centrality in the dietary regulation of steroid synthesis. In conclusion, in both turbot and tiger puffer, the supplementation of dietary cholesterol inhibits the steroid metabolism but does not affect the cholesterol transport.

Text-based captchas are still widely used by many websites such as Wikipedia and Microsoft despite the emergence of many alternative captchas. Recently, the design of text-based captchas has become more and more complex to resist attacks from automatic cracking programs. However, most of the existing captcha solving methods have certain shortcomings, such as insufficient accuracy, poor generalization performance, and the need for a large number of labeled samples. This study proposes a fast captcha solver that can effectively break text-based captchas with complex security features using a small amount of labeled data. The solver was achieved by constructing a captcha transformation model based on generative adversarial networks to simplify the captcha images before character segmentation and recognition. Results showed that the proposed captcha solver achieved a high success rate of over 96% character accuracy and 74% captcha accuracy for all evaluated schemes. Moreover, the average time to process a single captcha image using a laptop GPU was only 4–8 ms. The effectiveness of this work may encourage captcha designers to reconsider a more secure human–machine distinction mechanism.

The presence of cavitation in the oil film seriously affects the bearing lubrication performance and bearing capacity. Now the research of this phenomenon mostly focuses on the model of Reynolds equation (R-E equation) or Navier-Stokes equation (N-S), the influence of the two computation models is less analyzed, and the effect of noncondensable gas (NCG) mass fraction on the bearing performance is seldom studied. In the manuscript, the cavitation mechanism is studied using the mixed model of three-dimensional N-S equation and Jakobsson-Floberg-Olsson (JFO) condition of two dimensional Reynolds equation, and the influence of rotational speed and NCG mass fraction on the cavitationoil film pressure, and bearing capacity was studied. The results show that the change trend of cavitation with the rotational speed is basically consistent for N-S equation and R-E equation. The bearing capacity calculated by N-S equation is greater than that calculated by R-E equation. The peak pressure and bearing capacity of film can be improved by increasing the NCG mass fraction of lubricant and rotational speed.

Mention-level relation extraction (mRE) plays an important role in extracting relational information from short texts such as those exchanged in a social network. Deep learning (DL) has made remarkable achievements; the main problem encountered with DL in mRE is a lack of training samples. In this paper, we present a design for a quick sample-marking method. First, we construct an uneven noisy labeled data (UNLD) set using a pattern matching algorithm, and then a relabeling framework is put forward for modifying the UNLD. With regard to the accuracy, the recall rates of categories with sufficient samples increased from 0.4 to nearly 1 using the relabeling framework. We have released our code and other resources for further research (https://github.com/curtainsky/UNLD).

Conventional strategies for determining phosphate concentration is limited in efficiency due to the cost, time, and labor that is required in laboratory analysis. Therefore, an on-site and rapid detection sensor for phosphate is urgently needed to characterize phosphate variability in a hydroponic system. Cobalt (Co) is a highly sensitive metal that has shown a selectivity towards phosphate to a certain extent. A disposable phosphate sensor based on the screen-printed electrode (SPE) was developed to exploit the advantages of Co-nanoparticles. A support vector machine regression model was established to predict the concentration of phosphate in the hydroponic solutions. The results showed that Co-nanoparticles improve the detection limit of the sensor in the initial state. Meanwhile, the corrosion of Co-nanoparticles leads to a serious time-drift and instability of the electrodes. On the other hand, the coefficient of variation of the disposable phosphate detection chip is 0.4992%, the sensitivity is 33 mV/decade, and the linear range is 10&minus, 1&ndash, 10&minus, 4.56 mol/L. The R2 and mean square error of the buffer-free sensor in the hydroponic solution are 0.9792 and 0.4936, respectively. In summary, the SPE modified by the Co-nanoparticles is a promising low-cost sensor for on-site and rapid measurement of the phosphate concentration in hydroponic solutions.