The hydrochloric acid-catalyzed hydrothermal pretreatment of brown seaweed residues (Laminaria japonica) was optimized with respect to three operating factors: temperature, time, and the concentration of HCl, using response surface methodology (RSM). In order to confirm the significance of the quadratic model, an analysis of variance was performed, which resulted in an F-value of 11.09. Therefore, the regression model was highly significant. Additionally, the pareto chart was used to contrast the absolute values of the standardized effects. Response surface and contour plots were used to illustrate a surface with a maximum. The perturbation plot showed the sensitivity of the reducing sugars yield to the independent factors. Under the reaction conditions of 142 °C, 9 °C, 18.6 min, and 0.1 N HCl concentration, the experimental yield of 113.0 mg/g and the predicted yield of 107.5 mg/g were obtained.
Enzymatic saccharification of Laminaria japonica seaweed biomass was optimized by four independent factors (enzyme dose, hydrolysis time, pH, and temperature) using response surface methodology (RSM). To confirm the significance of the quadratic model, an analysis of variance (ANOVA) was performed, and the F-value of 8.76 showed that the regression model was highly significant (≤0.1%). In the accuracy study, average recoveries were in the range of 97.00% to 98.32%. The optimum experimental conditions were an enzyme dose of 8.2%, a hydrolysis time of 26 h, a pH of 4.1, and a temperature of 43°C. Temperature was the most important factor in the enzymatic saccharification. A relatively low temperature and short hydrolysis time were shown to improve the yield of reducing sugars.
Recently, drones have been widely used in education and industry. In this paper, we propose a navigation and control algorithm to develop unmanned drones quickly. To limit the proposed framework, we analysed the existing drone solution and simulation framework. We also used Hardware-in-the-Loop (HIL) simulation for rapid development. HIL will simulate physical systems that interface with embedded control equipment on real-time hardware. The code generated in this process can be experimented on a hardware device so that the control performance of the drones can be verified without draining the drones in the outdoor environment. Using the proposed method, you save time and money on drone development while providing stability.
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