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In order to reduce the drag torque under high speed conditions, the equivalent radius is introduced into the traditional low speed torque model of a wet clutch with track vehicle, and the calculation model of the drag torque with radial groove is derived. An optimization design model is established with 3 working condition parameters of the clutch and 5 structural parameters of the friction plate as design variables, and the minimum drag torque as the optimization objective. The objective function is solved based on the whale optimization algorithm (WOA) , and the drag torque is reduced by 35.6% after optimization. The dynamic response model of the objective function is established by Simulink software, and the optimization results are verified. The results show that the optimization method is effective and can provide some reference for structural design and parameter optimization of wet clutches.

Oral delivery of insulin exhibits low bioavailability due to the hydrolysis in acidic gastric juice, biodegradation of enzymes, and inefficient penetration through the intestinal mucus and epithelial cell layer. Here, we report a micelle platform to enhance the oral delivery of insulin. Insulin was precipitated by zinc ions to form hydrophobic nanoparticles and subsequently coated with a surfactant polysorbate-80 (Tween-80) to form nanosized micelles (TW-Zn-rhINS). Tween-80 protects the insulin from the degradation of enzymes, meanwhile facilitating the diffusion within mucus and the epithelial cell layer by opening the tight junctions. The micelles were then lyophilized and encapsulated in enteric capsules to overcome acidic hydrolysis in gastric juice. The micelles significantly increased transcellular insulin transport and uptake. The in vivo experiments demonstrated that oral TW-Zn-rhINS micelle capsules (30 IU/kg) decreased the blood glucose of diabetic mice by 58.74% after administration for 6 h, while the postprandial blood glucose dropped by 51.1%. Pharmacokinetics data indicated that the relative oral bioavailability of TW-Zn-rhINS was 7.88%, which was 7.73 times higher than that of insulin. The micelles present a promising platform to enhance the oral bioavailability of insulin, also indicating a potential for oral delivery of protein. [ABSTRACT FROM AUTHOR]

In order to accurately obtain the seedling emergence rate of breeding sunflower and to assess the quality of sowing as well as the merit of sunflower varieties, a method of extracting the sunflower seedling emergence rate using multi-source remote sensing information from unmanned aerial vehicles is proposed. Visible and multispectral images of sunflower seedlings were acquired using a UAV. The thresholding method was used to segment the excess green image of the visible image into vegetation and non-vegetation, to obtain the center point of the vegetation to generate a buffer, and to mask the visible image to achieve weed removal. The components of color models such as the hue–saturation value (HSV), green-relative color space (YCbCr), cyan-magenta-yellow-black (CMYK), and CIELAB color space (L*A*B) models were compared and analyzed. The A component of the L*A*B model was preferred for the optimization of K-means clustering to segment sunflower seedlings and mulch using the genetic algorithm, and the segmentation accuracy was improved by 4.6% compared with the K-means clustering algorithm. All told, 10 geometric features of sunflower seedlings were extracted using segmented images, and 10 vegetation indices and 48 texture features of sunflower seedlings were calculated based on multispectral images. The Pearson's correlation coefficient method was used to filter the three types of features, and the geometric feature set, the vegetation index set, the texture feature set, and the preferred feature set were constructed. The construction of a sunflower plant number estimation model using the crested porcupine optimizer–support vector machine is proposed and compared with the sunflower plant number estimation models constructed based on decision tree regression, BP neural network, and support vector machine regression. The results show that the accuracy of the model based on the preferred feature set is higher than that of the other three feature sets, indicating that feature screening can improve the accuracy and stability of models; assessed using the CPO-SVR model, the accuracy of the preferred feature set was the highest, with an R² of 0.94, an RMSE of 5.16, and an MAE of 3.03. Compared to the SVR model, the value of the R2 is improved by 3.3%, the RMSE decreased by 18.3%, and the MAE decreased by 18.1%. The results of the study can be cost-effective, accurate, and reliable in terms of obtaining the seedling emergence rate of sunflower field breeding. [ABSTRACT FROM AUTHOR]

To identify the mechanism underlying macrosteatosis (MaS)‐related graft failure (GF) in liver transplantation (LT) by multi‐omics network analysis. The transcriptome and metabolome were assayed in graft and recipient plasma in discovery (n = 68) and validation (n = 89) cohorts. Differentially expressed molecules were identified by MaS and GF status. Transcriptional regulatory networks were generated to explore the mechanism for MaS‐related inferior post‐transplant prognosis. The differentially expressed molecules associated with MaS and GF were enriched in ferroptosis and peroxisome‐related pathways. Core features of MaS‐related GF were presented on decreased transferrin and impaired anti‐oxidative capacity dependent upon dysregulation of transcription factors hepatocyte nuclear factor 4A (HNF4A) and hypoxia‐inducible factor 1A (HIF1A). Furthermore, miR‐362‐3p and miR‐299‐5p inhibited transferrin and HIF1A expression, respectively. Lower M2 macrophages but higher memory CD4 T cells were observed in MaS‐related GF cases. These results were validated in clinical specimens and cellular models. Systemic analysis of multi‐omics data depicted a panorama of biological pathways deregulated in MaS‐related GF. Transcriptional regulatory networks centered on transferrin and anti‐oxidant responses were associated with poor MaS graft quality, qualifying as potential targets to improve prognosis of patients after LT. [ABSTRACT FROM AUTHOR]

In this article, a prescribed-time state-feedback stabilization design strategy is proposed for a class of p-norm stochastic nonlinear strict feedback systems. In previous work on prescribed-time stabilization of stochastic systems, only stochastic nonlinear systems with fractional power less than or equal to one are considered. To overcome this problem, we improve the existing method and discuss the issue of prescribed-time stabilization of stochastic nonlinear systems with fractional power is arbitrary positive odd rational number. First, a prescribed-time controller is designed by combining the Lyapunov function with adding a power integrator technique. It should be pointed out that the homogeneous domination approach is adopted when dealing with the nonlinear terms of the system. Then, according to the stochastic prescribed-time stability theorem, it is proved that the designed controller can ensure the closed-loop system is prescribed-time mean-square stable. Finally, three simulation examples are given to investigate the validity of the presented method, in which the last one is an electromechanical system example. [ABSTRACT FROM AUTHOR]

Summary: This article focuses on the fast finite‐time adaptive tracking control for non‐strict feedback stochastic nonlinear systems. Random disturbances with constraints have rarely been considered in previous studies of fast finite‐time stabilization problems. The corresponding extension of the adaptive fast finite‐time stabilization mechanism to stochastic nonlinear systems with full‐state constraints is one of the innovations of this article. First, neural networks and barrier Lyapunov functions are utilized to handle the problems arising from the unknown nonlinear terms and the state constraints, respectively. Second, an adaptive fast finite‐time tracking control scheme for stochastic systems is designed based on the backstepping technique and a fast finite‐time control strategy, which allows all signals of the closed‐loop system to be bounded. Meanwhile, the designed controller guarantees a fast convergence of the tracking error to a small neighborhood of the origin under full‐state constraints. Finally, two examples are given to illustrate the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]