Maximum cross-correlated kurtosis-based unsaturated stochastic resonance and its application to bearing fault diagnosis

Considering the random impulses of mechanical noise and the limitations involved while identifying mechanical fault impulse signals via traditional measurement indices of signal-to-noise ratio, which require the characteristic frequency to be known in advance, this study proposes an adaptive unsaturated stochastic resonance method employing maximum cross-correlated kurtosis as the signal detection index. The proposed method combines the features of a cross-correlated coefficient to indicate periodic fault transients and those of spectrum kurtosis to locate these transients in the frequency domain. Actual vibration signals collected from motor and gear bearings subjected to heavy noise are used to demonstrate the effectiveness of the proposed method. Through a coarse tree-based machine learning method, the proposed method is verified to be more suitable for explaining the periodic impulse components of bearing signals, as compared to the ensemble empirical mode decomposition denoising method and unsaturated stochastic resonance using the kurtosis-intercorrelation index.     

原位液相透射电子显微镜及其在 纳米粒子表征方面的应用

近年来,基于透射电子显微技术、微纳加工技术和薄膜制造技术的发展,原位液相透射电子显微技术产生,为构建多种纳米级分辨率尺度下的微实验平台,发展新型纳米表征技术和众多领域的相关研究提供了途径.本文首先介绍了应用于原位液相透射电子显微技术的液体腔设计要求,然后介绍了液体腔的发展和典型的制备工艺,最后综述了近年来液体腔透射电子显微镜在纳米粒子成核和生长方面的应用研究,并探讨了该技术前沿发展面临的机遇和挑战.本文将为提高我国先进纳米表征技术和原子精准构筑技术提供相关讨论和支持.     

Double Gaussian potential stochastic resonance method and its application in centrifugal fan blade crack detection

Stochastic resonance (SR) has been extensively utilized in the field of weak fault signal detection for its characteristic of enhancing weak signals by transferring the noise energy. Aiming at solving the output saturation problem of the classical bistable stochastic resonance (CBSR) system, a double Gaussian potential stochastic resonance (DGSR) system is proposed. Moreover, the output signal-to-noise ratio (SNR) of the DGSR method is derived based on the adiabatic approximation theory to analyze the effect of system parameters on the DGSR method. At the same time, for the purpose of overcoming the drawback that the traditional SNR index needs to know the fault characteristic frequency (FCF), the weighted local signal-to-noise ratio (WLSNR) index is constructed. The DGSR with WLSNR can obtain optimal parameters adaptively, thereby establishing the DGSR system. Ultimately, a DGSR method is proposed and applied in centrifugal fan blade crack detection. Through simulations and experiments, the effectiveness and superiority of the DGSR method are verified.     

RNAGCN: RNA tertiary structure assessment with a graph convolutional network

RNAs play crucial and versatile roles in cellular biochemical reactions. Since experimental approaches of determining their three-dimensional (3D) structures are costly and less efficient, it is greatly advantageous to develop computational methods to predict RNA 3D structures. For these methods, designing a model or scoring function for structure quality assessment is an essential step but this step poses challenges. In this study, we designed and trained a deep learning model to tackle this problem. The model was based on a graph convolutional network (GCN) and named RNAGCN. The model provided a natural way of representing RNA structures, avoided complex algorithms to preserve atomic rotational equivalence, and was capable of extracting features automatically out of structural patterns. Testing results on two datasets convincingly demonstrated that RNAGCN performs similarly to or better than four leading scoring functions. Our approach provides an alternative way of RNA tertiary structure assessment and may facilitate RNA structure predictions. RNAGCN can be downloaded from https://gitee.com/dcw-RNAGCN/rnagcn.     

The induction of PANoptosis in KRAS-mutant pancreatic ductal adenocarcinoma cells by a multispecific platinum complex

Science China Chemistry - Oncogenic KRAS reprograms pancreatic ductal adenocarcinoma (PDAC) cells to a state that is awfully resistant to apoptosis. An alternative coping strategy is to trigger a...     

Polyvinylpyrrolidone and graphene-modified hematite nanoparticles for efficient electrocatalytic oxidation of p-nitrophenol

Journal of Solid State Electrochemistry - Polyvinylpyrrolidone (PVP) and graphene (G)-modified iron oxides (Fe2O3-PVP-G) are prepared by a simple hydrothermal reaction. Their morphology and...     

Bismuth chloride@mesocellular carbon foam nanocomposite cathode materials for rechargeable chloride ion batteries

Chloride ion batteries(CIB) are considered to be one of the most promising energy storage devices. As cathode materials for CIBs, metal chlorides have many advantages, such as high theoretical energy density, abundant elemental resources and ideal discharge voltage plateau. However, the dissolution and huge volume change of metal chlorides during cycling lead to considerable short lifespan, which limits their potential application for CIBs. Herein, the bismuth chloride nanocrystal is confined in...     

Single-atom Fe Embedded Co3S4 for Efficient Electrocatalytic Oxygen Evolution Reaction

Constructing atomically dispersed active sites with densely exposed and dispersed double metal-S_x catalytic sites for favorable OER catalytic activity remains rare and challenging. Herein, we design and construct a Fe₁S_x@Co₃S₄ electrocatalyst with Fe single atoms epitaxially confined in Co₃S₄ nanosheets for catalyzing the sluggish alkaline oxygen evolution reaction(OER). Consequently, in ultralow concentration alkaline solutions(0.1 mol/L KOH), such a catalyst is highly active and robust for OER with low overpotentials of 300 and 333 mV at current densities of 10 and 30 mA/cm², respectively, accompanying long-term stability without significant degradation even for 350 h. In addition, Fe₁S_x@Co₃S₄ shows a turnover frequency(TOF) value of 0.18 s⁻¹, nearly three times that of Co₃S₄(0.07 s⁻¹), suggesting the higher atomic utilization of Fe single atoms. Mössbauer and in-situ Raman spectra confirm that the OER activity of Fe₁S_x@Co₃S₄ origins from a thin catalytic layer of Co(Fe)OOH that interacts with trace-level Fe species in the electrolyte, creating dynamically stable active sites. Combined with experimental characterizations, it suggests that the most active S-coordinated dual-metal site configurations are 2S-bridged (Fe-Co)S₄, in which Co-S and Fe-S moieties are shared with two S atoms, which can strongly regulate the adsorption energy of reaction intermediates, accelerating the OER reaction kinetics.