Subthreshold Periodic Signal Detection by Bounded Noise-Induced Resonance in the FitzHugh–Nagumo Neuron

Neurons can detect weak target signals from complex background signals through stochastic resonance (SR) and vibrational resonance (VR) mechanisms. However, random phase variation of rapidly fluctuating background signals is generally ignored in classical VR or SR studies. Here, the rapidly fluctuating background signals are modeled by bounded noise with random rapidly fluctuating phase derived from Wiener process. Then, the influences of bounded noise on the weak signal detection are discussed in the FitzHugh–Nagumo (FHN) neuron. Numerical results reveal the occurrence of bounded noise-induced single- and biresonance as well as a transition between them. Randomness in phase can enhance the adaptability of neurons, but at the cost of signal detection performance so that neurons can work in more complex environments with a wider frequency range. More interestingly, bounded noise with appropriate parameters can not only optimize information transmission but also simultaneously reduce energy consumption. Finally, the potential mechanism of bounded noise is explained

A Rapid and Efficient Strategy for Quality Control of Clinopodii herba Encompassing Optimized Ultrasound-Assisted Extraction Coupled with Sensitive Variable Wavelength Detection

Clinopodii herba is a folk herbal medicine for treatments of hemorrhagic disorders. However, there is not even a quantitative standard for clinopodii herba deposited in the Chinese Pharmacopoeia. The development of a strategy for rapid and efficient extraction and simultaneous detection of multiple components in clinopodii herba is therefore of great value for its quality evaluation. Here, a variable wavelength strategy was firstly applied to quantity multiple components by segmental monitoring by UHPLC with diode array detector following ultrasound-assisted extraction. The parameters of ultrasound-assisted extraction were optimized using single factor optimization experiments and response surface methodology by a Box–Behnken design combined with overall desirability. Subsequently, a rapid, efficient, and sensitive method was applied for simultaneous determination of eleven compounds, which represented the major and main types of components in clinopodii herba. Moreover, the performance of the validated method was successfully applied for the quality control of various batches of clinopodii herba and provided sufficient supporting data for the optimum harvest time. The Box-Behnken-optimized ultrasound-assisted extraction coupled with variable wavelength detection strategy established in this work not only improves the quality control of clinopodii herba, but also serves as a powerful approach that can be extended to quality evaluation of other traditional Chinese medicines