Characteristic of polysaccharides from Flammulina velutipes in vitro digestion under salivary,simulated gastric and small intestinal conditions and fermentation by human gut microbiota

In this study, in vitro digestion and fermentation of Flammulina velutipes -derived polysaccharides (FVP) were investigated. It was found that FVP mainly consisted of 48.45% glucose, 15.40% mannose, 14.60% xylose, 11.80% fucose and 9.90% galactose. The -human saliva, simulated gastric and small intestinal juices conditions did not break down the FVP. Based on in vitro fermentation tests, FVP modulated the composition of gut microbiota by elevating the amounts of Bifidobacteriaceae and Bacteroidaceae and reducing the numbers of genera Lachnospiraceae and Enterococcaceae. Meanwhile, FVP affected the synthesis of short-chain fatty acids derived from gut microbiota.     

Stream-Based Data Sampling Mechanism for Process Object

Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive data sampling mechanism to find a ppropriate d ata t o m odeling. F irst o f all, we use concept drift to make the partition of the life cycle of process object. Then, entity community detection is proposed to find changes. Finally, we propose stream-based real-time optimization of data sampling. Contributions of this paper are concept drift, community detection, and stream-based real-time computing. Experiments show the effectiveness and feasibility of our proposed adaptive data sampling mechanism for process object.     

Use of heat-moisture treated maize starch to modify the properties of wheat flour and the quality of noodles

Waxy, normal and high-amylose maize starches were subjected to heat-moisture treatment (HMT) and then added to wheat flour (WF) in different ratios (1%, 5% and 10%). The properties of blends and their cooked noodles were studied to investigate the effects of HMT starches. The incorporation of HMT starch in WF led to an increase in swelling power, peak viscosity and breakdown and to a decrease in setback, thus inhibiting retrogradation, hence enhancing resultant noodle softness. Compared to the same addition ratio of native starch to WF, HMT starch led to higher tensile strength and extensibility in resultant noodles. WF with added HMT starch had higher resistant starch than with native starch. This study showed that addition of HMT maize starch has potential to bring nutritional benefits. However, it is necessary to select the proper blending ratio and amylose content of starch to add, in consideration of its effect on noodle quality.     

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.     

Low-temperature synthesis of SiC nanowires with Ni catalyst

SiC nano wires were fabricated on the silicon substrate dipped with a layer of Ni catalyst at 900 ℃ by gas pressure annealing processing. The morphologies and crystal structures were determined by scanning electron microscopy(SEM), transmission electron microscopy(TEM)and X-ray diffraction(XRD). The results show that the assynthesized nanowires are β-SiC single crystalline with diameter range of 50-100 nm, and length of tens of micron by directly annealing at 900 ℃. The SiC nano wires grow along the [111] direction with highly uniform morphology. And the possible growth mechanism of SiC nano wires is proposed.The present work provides an efficient strategy for the production of high-quality SiC nano wires.     

Fabrication strategies and application fields of novel 2D Ti3C2Tx (MXene) composite hydrogels: A mini-review

Ti₃C₂T_x (MXene), a new kind of 2D ceramic nanosheets, is receiving more and more attention in the fields of medicine, biology, energy, electronics, etc. However, the preparation and application of MXene in hydrogel is still in its infancy period. Here, we review the latest progress (after 2018) related to MXene hydrogels in time. Aiming at the key issue of the dispersion stability of MXene in hydrogel systems, the preparation strategy, mechanism, advantages and disadvantages of MXene hydrogels are sorted out in detail, and the potential application prospects of MXene composite hydrogel are introduced. Finally, future viewpoints are put forward for the dispersion stability challenges that need solving in the design of MXene hydrogel.     

Study of haze emission efficiency based on new co-opetition data envelopment analysis

As haze intensifies in China, controlling haze emission has become the country's top priority for environmental protection. Because haze moves across different regions, it is necessary to develop a data envelopment analysis (DEA) model underpinned by both competition and cooperation to evaluate the haze emission efficiency in different provinces. This study innovatively adopts the spatial econometrics to construct the co-opetition matrices of Chinese provinces, then builds the co-opetition DEA model to evaluate the haze emission efficiency of them, and finally uses the haze data of 2015 as an example to assess the applicability of the model. The results of the study include the following: First, compared with the traditional CCR (A. Charnes & W. W. Cooper & E. Rhodes) model, this study constructs the co-opetition DEA cross-efficiency model that integrates haze's feature of cross-border moving; thus, it is more in line with the reality of haze emission and movement. Second, compared with the efficiency value gained from the CCR model, the haze emission efficiency values for Tianjin and Guangdong, two decision-making units, register greater variance when using the DEA model. The reason might lie in that they have a different spatial transportation relationship with their surrounding provinces. Third, the haze emission efficiency of provinces, according to the evaluation based on the co-opetition DEA method, varies greatly: Those with high efficiency are mostly inland provinces with slow economic growth and adverse climatic conditions, whereas many of the provinces with low efficiency are located in the relatively prosperous East China. The specific co-opetition DEA model constructed in this study enriches the research on the DEA model, which can be applied to the emission efficiency evaluation of similar pollutants around the world and can contribute empirical support to the haze reducing efforts of the government with its empirical results.     

Wear mechanism of a novel AlSiMgAl2O4Al2O3 composite used in the low vessel of an RH secondary refining furnace

A novel AlSiMgAl₂O₄Al₂O₃ composite brick was prepared and evaluated in the low vessel of an RH (the initials of Ruhrstahl and Hereaeus) secondary refining furnace; it was characterized by X-ray diffraction, scanning electron microscopy, and energy-dispersive spectroscopy. The results show that after use, the AlSiMgAl₂O₄Al₂O₃ composite has a functional gradient with an erosion zone–reinforced zone–original zone phase distribution, in which the phases in the erosion zone (0–1.8?cm) are a Mg-hercynite spinel solid solution, α-Al₂O₃, and minor amount of Al₃Fe₅O₁₂. Furthermore, the phases in the reinforced zone (1.8–5.0?cm) are γ-AlON, 21RSiAlON, SiC, Mg_0.388Al_2.408O₄, and α-Al₂O₃; i.e., the Al and Si in the composite are completely converted into non-oxide reinforced phases. Finally, the phases in the original zone (>5.0?cm) show no change. The reaction mechanism is as follows. During operation, a Mg-hercynite spinel solid solution is formed in the erosion zone due to a reaction between MgAl₂O₄ and FeO from a refinery operation. Therefore, the slag erosion of the material is improved. The Al and Si metals undergo active oxidation, and 21RSiAlON flakes are subsequently formed from the products of the metastable Al₂O(g), SiO(g), and N₂(g) in the ambient. The γ-AlON is formed by a carbothermal reduction nitridation of the α-Al₂O₃ and residual active carbon from the resin binder. The 21RSiAlON and γ-AlON reinforce the composite brick and improve its high temperature performance accordingly. Its service life is 110% that of the magnesia-chrome bricks used in the same period. The reaction model was also established.