Evaluating the Effects of Replacing Alfalfa with Broussonetia papyrifera Branch/Leaf Powder on Growth and Serum Indicators in Dezhou Donkeys.

The purpose of this experiment was to study the apparent digestibility and the effects of Broussonetia papyrifera (BP) branch/leaf powder supplementation on growth performance and serum indicators in donkeys. The results showed that the apparent digestibility of dry matter (DM), crude protein (CP), crude fiber (CF), neutral detergent fiber (NDF), acidic detergent fiber (ADF), and digestible energy content (DE) of BP branch/leaf powder were 51.88%, 67.27%, 64.86%, 49.59%, 54.73%, 40.87%, and 6.37 MJ/kg, respectively. The average daily gain (ADG) in the 20% group was significantly higher than in the 0% and 30% groups. The serum albumin (ALB) levels in the 0% and 10% groups were significantly higher than those in the 20% and 30% groups, while the serum globulin (GLB) content in the 10% group was significantly lower than in the other groups. The 20% group showed decreased serum triglyceride (TG) levels compared to the other groups. Both the 20% and 30% groups exhibited lower total cholesterol (TC) levels and increased alanine aminotransferase (ALT) compared to the 0% and 10% groups and higher serum lactate dehydrogenase (LDH) levels than the 10% group. The 30% group had higher serum immunoglobulin A (IgA) levels than the other groups, while all three BP branch/leaf powder groups had lower serum tumor necrosis factor (TNF-α) levels than the 0% group. There was a gradual increase in serum total antioxidant capacity (T-AOC) with the increasing amount of BP branch/leaf powder added. In conclusion, the optimal supplemental proportion of BP branch/leaf powder in the diet is 20%. Furthermore, BP branch/leaf powder can improve growth performance, serum immune indices, and antioxidant capacity in Dezhou donkeys.

Development of a Three-Dimensional Nerve Stretch Growth Device towards an Implantable Neural Interface.

Because of rising traumatic accidents and diseases, the number of patients suffering from nerve injury is increasing. Without effective rehabilitation therapy, the patients will get motor or sensory function losses or even a lifelong disability. As for amputees, neural interface technology can be used to splice nerves and electrical wires together in a way that allows them to control an artificial limb as if it was a natural extension of the body. However, the means the need for an autologous nerve to stimulate axonal regeneration and extension into target tissues, which are limited by the supply of donor nerves. Based on the principle of mechanical force regulating axon growth, in this paper, we developed a three-dimensional nerve stretch growth device for an implantable neural interface. The device consists of three motors controlled by single chip microcomputer and some mechanical parts. The stability and reliability of the device were tested. Then, we used neurons derived from human pluripotent stem cells by small chemical molecules to explore the optimal three-dimensional stretch culture parameters. Furthermore, we found that the axons were intact through 10 rotations per day and 1 mm of horizontal pulling per day. The results of this research will provide convenience for patients treated through an implantable neural interface.

Novel Approach for the Recognition and Prediction of Multi-Function Radar Behaviours Based on Predictive State Representations.

The extensive applications of multi-function radars (MFRs) have presented a great challenge to the technologies of radar countermeasures (RCMs) and electronic intelligence (ELINT). The recently proposed cognitive electronic warfare (CEW) provides a good solution, whose crux is to perceive present and future MFR behaviours, including the operating modes, waveform parameters, scheduling schemes, etc. Due to the variety and complexity of MFR waveforms, the existing approaches have the drawbacks of inefficiency and weak practicability in prediction. A novel method for MFR behaviour recognition and prediction is proposed based on predictive state representation (PSR). With the proposed approach, operating modes of MFR are recognized by accumulating the predictive states, instead of using fixed transition probabilities that are unavailable in the battlefield. It helps to reduce the dependence of MFR on prior information. And MFR signals can be quickly predicted by iteratively using the predicted observation, avoiding the very large computation brought by the uncertainty of future observations. Simulations with a hypothetical MFR signal sequence in a typical scenario are presented, showing that the proposed methods perform well and efficiently, which attests to their validity.