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.     

Combating Biofilm Associated Infection In Vivo: Integration of Quorum Sensing Inhibition and Photodynamic Treatment based on Multidrug Delivered Hollow Carbon Nitride Sphere

Recently, quorum sensing (QS) inhibitors (QSIs) have been combined with antibiotics to enhance antibiofilm efficacy in vitro and in vivo. However, targeting QS signals alone is not enough to prevent bacterial infections. Drug resistance and recurrence of biofilms makes it difficult to eradicate. Herein, photodynamic therapy (PDT) is selected to unite QSIs and antibiotics. A synergistically antibiofilm system, which combines QSIs, antibiotics, and PDT based on hollow carbon nitride spheres (HCNSs) is envisaged. First, HCNS provides the multidrug delivering ability, enabling QSIs and antibiotics to be released in sequence. Subsequently, multistage releases sensitize bacteria effectively, potentiating the chemotherapeutic effects of the antibiotics. Finally, the integration of QSIs and PDT not only minimizes the possibility of drug resistance, but also overcomes the problem of limited mass and extension of PDT. Even after 48 h of incubation, the bacterial biofilm is obviously inhibited. And its biofilm disperse efficiency exceeds 48% (compared with QSI‐potentiated chemotherapy group) and 40% (compared with PDT group). Besides, the inhibition of the QS system influences phenotypes related to virulence factor production and surface hydrophobicity, which weaken biofilm invasion and formation. Eventually, this system is applied to disperse bacterial biofilm in vivo. Overall, PDT and QS modulation are devoted to eradicate drug resistance and recurrence of the biofilm.     

胶东一体化背景下天然气发展策略研究

大力发展天然气对于促进能源结构优化调整和大气污染防治具有重要意义,是实现"碳达峰""碳中和"的重要路径.借力胶东一体化发展战略的提出,引领胶东五市天然气基础设施协同发展,促进胶东一体化战略在能源领域的实施.     

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.