Effects of malondialdehyde-induced protein oxidation on the structural characteristics of rice protein

Malondialdehyde (MDA) was selected to represent a secondary by-product of lipid peroxidation during rice ageing. This study aimed to investigate the effects of MDA modification on the structural characteristics of rice protein. The results showed that as MDA concentration increased, rice protein carbonyl and disulphide groups increased, but sulphydryl content decreased. The blue shift of maximum fluorescence peak, the decrease of rice protein intrinsic fluorescence intensity and the reduction of surface hydrophobicity indicated the formation of protein aggregates caused by MDA oxidative modification. The results of molecular weight distribution and particle size distribution showed that MDA modification resulted in the formation of soluble protein aggregates, and the decrease of rice protein solubility indicated that insoluble protein aggregates were formed. Results of protein electrophoresis showed that MDA modification contributed to rice protein aggregation via non-disulphide covalent bonds. The results showed that rice protein gradually aggregated with increasing MDA concentration.     

Achieving Rich and Active Alkaline Hydrogen Evolution Heterostructures via Interface Engineering on 2D 1T‐MoS2 Quantum Sheets

Large‐scale production of hydrogen from water‐alkali electrolyzers is impeded by the sluggish kinetics of hydrogen evolution reaction (HER) electrocatalysts. The hybridization of an acid‐active HER catalyst with a cocatalyst at the nanoscale helps boost HER kinetics in alkaline media. Here, it is demonstrated that 1T–MoS₂ nanosheet edges (instead of basal planes) decorated by metal hydroxides form highly active ${\text{edge}}_{{\text{1T‐MoS}}_{\text{2}}}$/ ${\text{edge}}_{\text{Ni}{(\text{OH})}_{\text{2}}}$ heterostructures, which significantly enhance HER performance in alkaline media. Featured with rich ${\text{edge}}_{{\text{1T‐MoS}}_{\text{2}}}$/ ${\text{edge}}_{\text{Ni}{(\text{OH})}_{\text{2}}}$ sites, the fabricated 1T–MoS₂ QS/Ni(OH)₂ hybrid (quantum sized 1T–MoS₂ sheets decorated with Ni(OH)₂ via interface engineering) only requires overpotentials of 57 and 112 mV to drive HER current densities of 10 and 100 mA cm^?2, respectively, and has a low Tafel slope of 30 mV dec^?1 in 1 m KOH. So far, this is the best performance for MoS₂‐based electrocatalysts and the 1T–MoS₂ QS/Ni(OH)₂ hybrid is among the best‐performing non‐Pt alkaline HER electrocatalysts known. The HER process is durable for 100 h at current densities up to 500 mA cm^?2. This work not only provides an active, cost‐effective, and robust alkaline HER electrocatalyst, but also demonstrates a design strategy for preparing high‐performance catalysts based on edge‐rich 2D quantum sheets for other catalytic reactions.     

Preparation of Silver Nanowires via a Rapid,Scalable and Green Pathway

Rapid synthesis of silver nanowires(Ag NWs) with high quality and a broad processing window is challenging because of the low selectivity of the formation of multiply twinned particles at the nucleation stage for subsequent Ag NWs growth.Herein we report a systematic study of the water-involved heterogeneous nucleation of Ag NWs with high rate(less than 20 min) in a simple and scalable preparation method.Using glycerol as a reducing agent and a solvent with a high boiling point,the reaction is rapidly heated to 210 ℃ in air to synthesize Ag NWs with a very high yield in gram level.It is noted that the addition of a small dose of water plays a key role for obtaining highly pure Ag NWs in high yield,and the optimal water/glycerol ratio is0.25%.After investigating a series of forming factors including reaction temperature and dose of catalysts,the formation kinetics and mechanism of the Ag NWs are proposed.Compared to other preparation methods,our strategy is simple and reproducible.These Ag NWs show a strong Raman enhancement effect for organic molecules on their surface.     

Specific emitter identification for satellite communication using probabilistic neural networks

Electromagnetic signal emitted by satellite communication (satcom) transmitters are used to identify specific individual uplink satcom terminals sharing the common transponder in real environment, which is known as specific emitter identification (SEI) that allows for early indications and warning (I&W) of the targets carrying satcom furnishment and furthermore the real time electromagnetic situation awareness in military operations. In this paper, the authors are the first to propose the identification of specific transmitters of satcom by using probabilistic neural networks (PNN) to reach the goal of target recognition. We have been devoted to the examination by exploring the feasibility of utilizing the Hilbert transform to signal preprocessing, applying the discrete wavelet transform to feature extraction, and employing the PNN to perform the classification of stationary signals. There are a total of 1000 sampling time series with binary phase shift keying (BPSK) modulation originated by five types of satcom transmitters in the test. The established PNNs classifier implements the data testing and finally yields satisfactory accuracy at 8 dB(±1 dB) carrier to noise ratio, which indicates the feasibility of our method, and even the keen insight of its application in military.     

Improved Input and State Estimation for Linear Stochastic Systems with Direct Feedthrough

This paper is concerned with the problem of joint input and state estimation for linear stochastic systems with direct feedthrough. Based on the fact that each unknown input between any two time steps is always bounded, a novel improved algorithm is proposed. Compared with existing results, this algorithm can effectively enhance estimation accuracy. Moreover, the stability of the algorithm is also discussed. Finally, an illustrative example is given to demonstrate the effectiveness of the proposed approach.