Xuchang University

ABSTRACT The electron spin of nitrogen‐vacancy center and the phonon mode of mechanical resonator are widely adopted to explore information science and technology, in which the preparation of entangled states in a fast and robust manner is of significance. Here we present a scheme for creating an entangled W state by the technique of shortcut to adiabaticity. Two electron spins are magnetically coupled to a common mechanical resonator, and each spin is individually driven by a classical pulse. By encoding the dressed states of the microwave‐driven spin to a logic qubit manifold, we obtain an effective spin‐resonator‐spin system. By suitably engineering the invariant‐based shortcut with constant Rabi rates, one‐step generation of a tripartite entangled state can be realized without the adiabatic constraint. We further analyze the decoherence effects and the robustness against the Rabi rate inaccuracies and timing error. The strategy could provide a promising avenue to generate entangled states with the hybrid system.

Abstract Accurate forecasting of net power load on the public grid for integrated source-grid-load-storage projects is crucial for ensuring the safe and stable operation of power systems. Sudden fluctuations in net load (ramping events) pose significant challenges to grid dispatch. This paper addresses the identification and prediction of net load ramping events by first proposing a definition method based on ramping segments. It identifies ramping events by analyzing the magnitude of power changes between adjacent sampling moments. Then, a CNN-BiLSTM hybrid network is constructed for point prediction and is combined with an adaptive bandwidth kernel density estimation (KDEAB) method to establish an interval prediction model. Finally, the effectiveness of the proposed method is validated through case studies. Experimental results demonstrate that the proposed method can effectively identify net load ramping events. Its interval predictions achieve coverage and confidence levels close to the target, exhibiting good overall prediction performance.

Abstract This study prepared ternary glycyrrhizic acid/rutin/zein (GRZ) complexes (at a zein: GA mass ratio of 1:1) via anti-solvent precipitation at varying pH levels (3.5, 4.5, 6.0). The pH 6.0 complex demonstrated optimal characteristics, featuring the smallest particle size (112 nm) and highest absolute zeta potential (−35.4 mV). Superior rutin encapsulation efficiency was achieved for complexes formed at pH 4.5 and 6.0. All complexes exhibited high physical stability across a pH range of 6.0–8.0, at temperatures up to 85 °C, and in salt concentrations up to 15 mmol/L. Complexes formed at pH 4.5 and 6.0 maintained better re-dispersibility after freeze-drying. FTIR and XRD analyses confirmed the formation of hydrogen bonds and hydrophobic interactions, resulting in an amorphous structure. Notably, GRZ complex incorporation enhanced yogurt coagulation without affecting fermentation kinetics. These findings establish a promising strategy for developing efficient rutin delivery systems with potential for functional food applications.

We propose a three-neuron heterogeneous cyclic Hopfield neural network (het-CHNN) utilizing three different activation functions: the hyperbolic tangent, sine, and cosine functions. The network’s globally uniformly ultimate boundedness is proved theoretically, and its chaotic dynamics are explored through numerical simulations and analog experiments. The numerical results demonstrate that the het-CHNN displays chaotic dynamics and multi-scroll chaotic attractors. Subsequently, the het-CHNN is implemented in an analog circuit, and hardware experiments are performed to verify the previous numerical results. Notably, the het-CHNN successfully resolves the issue of the absence of chaos in a three-neuron CHNN and currently appears to be the simplest three-neuron Hopfield neural network (HNN) that can generate chaos.