Separation of Mixtures of Rutin and Quercetin: Evaluating the Productivity of Preparative Chromatography

The flavonoid rutin is present in significant amounts in the flower buds of Sophora japonica L. It offers numerous desired pharmacological effects. Under certain extraction conditions quercetin is found as a hydrolysis product which needs to be separated from rutin. This paper describes the application of liquid chromatography to solve this task. Based on the determination of adsorption equilibrium constants and column efficiencies, the productivity of the separation process is estimated, and scale-up considerations are presented. A comparison with alternatively directly crystallizing rutin from raw extracts is also reported.     

Dynamic Assembly of Cascade Enzymes by the Shape Transformation of a DNA Scaffold (Adv. Funct. Mater. 15/2023)

Within cells, the close spatial arrangement of cascade enzymes facilitates the channeling of intermediates and enhances cascade reaction efficiency. Reconfigurable DNA nanostructures, owing to their structural controllability and precise spatial addressability, are promising tools for mimicking such processes. In this study, a 3D DNA origami scaffold, with a dynamic shape transformation from its open boat form to a closed hexagonal prism induced by toehold-mediated strand displacement, is designed to investigate the enzyme cascade reaction of xylose reductase and xylitol dehydrogenase from D-xylose metabolic pathway. Enzymes are assembled on the DNA scaffold in its open state, which is subsequently closed by the assistance of DNA sequence-specific closing keys. The enzyme cascade efficiency is much higher in the static encapsulated closed state than in the open state due not only to the enzyme proximity but also the environmental factors of 3D DNA structure. These results provide novel insights into controlling enzyme cascade reactions by inducing the shape transformation of DNA nanostructures and how environmental factors affect the action of multi-enzyme complexes in the cell.     

Dynamic event-triggered distributed interval functional observers for interconnected systems

In this paper, we design dynamic event-triggered interval functional observers (FOs) for interconnected systems comprising $M$ $(M\ge 2)$ subsystems where each subsystem is subject to nonlinearities and output disturbances. Our design method consists of two main steps. First, we design decentralized dynamic event-triggered mechanisms (ETMs) which use only locally measured output information. We then consider the design of distributed interval FOs by using the newly proposed ETMs. Their existence conditions are established and formulated in terms of linear programming. We also derive a bound on the estimated error vector and show that this bound is the smallest. Thus, this ensures that the unknown linear functional state vector can be estimated within an upper and lower bound of its true value by the designed interval observers. Finally, we apply the obtained results to design dynamic event-triggered interval observers for linear functions of the state vectors of an $N$-machine power system.     

Model-free hierarchical control with fractional-order sliding surface for multisection web machines

Due to the nonlinearities and dynamical properties of multisection web machines, it is essential to accomplish an appropriate mathematical model as well as design a compatible control scheme. A generalized fully driven web winding model is constructed taking unpredictable changes of moment of inertia and radius of rolls into consideration. In this article, a fractional-order sliding surface algorithm-based hierarchical control frame is applied to multisection web machines to deal with matched and mismatched uncertainties and disturbances. In addition, the Radius Basis Function neural network is deployed to estimate necessary system dynamics and the proposed control scheme taking advantage of first-order low-pass filters to produce virtual control signals without complicated calculation and attenuate the explosion of terms phenomenon. Finally, the semi-global stability of the entire system is determined using Lyapunov's stability theory. The simulation results are presented to clarify the superior performance of robust control algorithm and approximation law in the presence of nonideal elements.     

Substitution of V5+ in BiVO4 with Ni2+ and the Improved Photocatalytic Degradation of Crystal Violet Under White LED Light Irradiation

The effects of the substitution of V⁵⁺ with Ni²⁺ at the corresponding sites in BiVO₄ on the crystal structures, optical properties, and photocatalytic efficiency of BiVO₄ was investigated. Ni²⁺ cations doped at the V⁵⁺ sites in BiVO₄ was confirmed by X-ray diffraction, Raman, X-ray photoelectron spectroscopy, ultraviolet–visible diffuse reflectance spectra, and photoluminescence spectra. Ni-doped BiVO₄ exhibited excellent degradation of crystal violet (CV) compared with the bare BiVO₄. For optimal Ni²⁺ doping of 5%, the degradation rate of CV, which reached about 95% within 180 min of LED light irradiation, was obtained. Ni doping can introduce advantageous defect states that significantly increase the separation and diffusion efficiency of the photo-induced charge carriers, thereby boosting the photocatalytic activity of crystal structures.

     

Adaptive neural network hierarchical sliding mode control for six degrees of freedom overhead crane

This paper presents an effective control method for three-dimensional (3D) overhead cranes with six degrees of freedom (DOF). Two payload swings and an axial payload oscillation should be minimized besides driving the bridge, trolley, and hoisting drum to bring the payload to the desired position in space. First, a novel 3D-6DOF crane model is developed, where the sixth degree of freedom is axial cargo oscillation that has never been considered in previous studies. A controller is then designed using the hierarchical sliding mode control method. Moreover, a radial basis function neural network (RBFNN) is used to approximate the system's unknown dynamic model accurately. According to the Lyapunov principle, a control law and an updated law for the neural network's weight matrices are designed to ensure the stability of the closed-loop system. Simulation results on Matlab software show the proposed approach's effectiveness, such as smaller swing, minor axial oscillation, and precise position as desired.