The initial composition and structure of microbial community determined the yield and quality of Baijiu during the spontaneous fermentation.

The microbiota during pit mud fermentation is a crucial factor in Baijiu brewing since it determines the yield and flavor. However, the impact of the microbial community during the initial fermentation stage on Baijiu quality remains uncertain. Herein, high-throughput sequencing was employed to investigate the microbial diversities and distribution during Baijiu fermentation in individual pit mud workshops at both initial and late stages.

Femtosecond Yb-doped tapered fiber pulse amplifiers with peak power of over hundred megawatts.

Ultrafast fiber lasers combining high peak power and excellent beam quality in the 1-µm wavelength range have been explored to applications in industry, medicine and fundamental science. Here, we report generation of a high-energy sub 300 fs polarization maintaining fiber chirped pulse amplification (CPA) system by using a Yb-doped large mode area tapered polarization maintaining (PM) optical fiber with the core/cladding diameters of 35/250 µm at the thin end and 56/400 µm at the thick end. The taper fiber design features a confined core for selective gain amplification and multi-layer cladding for enhanced suppression of higher order modes.

Neural Networks-Based Adaptive Control for Nonlinear State Constrained Systems With Input Delay.

This paper addresses the problem of adaptive tracking control for a class of strict-feedback nonlinear state constrained systems with input delay. To alleviate the major challenges caused by the appearances of full state constraints and input delay, an appropriate barrier Lyapunov function and an opportune backstepping design are used to avoid the constraint violation, and the Pade approximation and an intermediate variable are employed to eliminate the effect of the input delay. Neural networks are employed to estimate unknown functions in the design procedure.

Adaptive Control via Neural Output Feedback for a Class of Nonlinear Discrete-Time Systems in a Nested Interconnected Form.

In this paper, an adaptive output feedback control is framed for uncertain nonlinear discrete-time systems. The considered systems are a class of multi-input multioutput nonaffine nonlinear systems, and they are in the nested lower triangular form. Furthermore, the unknown dead-zone inputs are nonlinearly embedded into the systems.

Approximation-Based Adaptive Neural Tracking Control of Nonlinear MIMO Unknown Time-Varying Delay Systems With Full State Constraints.

This paper deals with the tracking control problem for a class of nonlinear multiple input multiple output unknown time-varying delay systems with full state constraints. To overcome the challenges which cause by the appearances of the unknown time-varying delays and full-state constraints simultaneously in the systems, an adaptive control method is presented for such systems for the first time. The appropriate Lyapunov-Krasovskii functions and a separation technique are employed to eliminate the effect of unknown time-varying delays.

Adaptive NN Control Using Integral Barrier Lyapunov Functionals for Uncertain Nonlinear Block-Triangular Constraint Systems.

A neural network (NN) adaptive control design problem is addressed for a class of uncertain multi-input-multi-output (MIMO) nonlinear systems in block-triangular form. The considered systems contain uncertainty dynamics and their states are enforced to subject to bounded constraints as well as the couplings among various inputs and outputs are inserted in each subsystem. To stabilize this class of systems, a novel adaptive control strategy is constructively framed by using the backstepping design technique and NNs.

Atorvastatin protects endothelium by decreasing asymmetric dimethylarginine in dyslipidemia rats.

Background: Asymmetric Dimethylarginine (ADMA) is an inhibitor of endogenous nitric oxide synthase, which is the key synthase for nitric oxide (NO) production. Whether statins could protect endothelium by reducing ADMA concentration is unclear, and whether this effect is associated with the dose of statins usage is also needed further studied.

Methods: Dyslipidemia rat model was produced by giving high-fat and high-cholesterol diet for 8 weeks.

Neural Controller Design-Based Adaptive Control for Nonlinear MIMO Systems With Unknown Hysteresis Inputs.

This paper studies an adaptive neural control for nonlinear multiple-input multiple-output systems in interconnected form. The studied systems are composed of N subsystems in pure feedback structure and the interconnection terms are contained in every equation of each subsystem. Moreover, the studied systems consider the effects of Prandtl-Ishlinskii (PI) hysteresis model.

Reinforcement learning design-based adaptive tracking control with less learning parameters for nonlinear discrete-time MIMO systems.

Based on the neural network (NN) approximator, an online reinforcement learning algorithm is proposed for a class of affine multiple input and multiple output (MIMO) nonlinear discrete-time systems with unknown functions and disturbances. In the design procedure, two networks are provided where one is an action network to generate an optimal control signal and the other is a critic network to approximate the cost function. An optimal control signal and adaptation laws can be generated based on two NNs.