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Satellite clock bias is the key factor affecting the accuracy of the single point positioning of a global navigation satellite system. The traditional model back propagation (BP) neural network is prone to local optimum problems. This paper presents a prediction model and algorithm for the clock bias of the BP neural network based on the optimization of the mind evolutionary algorithm (MEA), which is used to optimize the initial weights and thresholds of the BP neural network. The accuracy of the comparison between clock bias data is verified with and without one-time difference processing. Compared with grey model (GM (1,1)) and BP neural network, this paper discusses the advantages and general applicability of this method from different constellation satellites, different atomic clock type satellites, and the amount of modeling data. The accuracy of the grey model (GM(1,1)), BP, and MEA-BP models for satellite clock bias prediction is analyzed and the root mean square error, range difference error, and the mean of the clock bias data compared. The results demonstrate that the prediction accuracy of the three satellites significantly increased after one-time difference processing and that they have good stability. The prediction accuracy of four sessions of 2 h, 3 h, 6 h, and 12 h obtained using the MEA-BP model was better than 0.74, 0.80, 1.12, and 0.87 ns, respectively. The MEA-BP model has a specific degree of improvement in the prediction accuracy of the different sessions. Additionally, the prediction accuracy of different models has a specific relationship with the length of the original modeling sequence, of which BP model is the most affected, and MEABP is relatively less affected by the length of the modeling sequence, indicating that the MEA-BP model has strong anti-interference ability. [ABSTRACT FROM AUTHOR]

Cylinder- and bamboo-shaped boron nitride nanotubes (BNNTs) have been synthesized in large scale via a facile chemical vapor reaction route using ammonia borane as a precursor. The structure and chemical composition of the as-synthesized BNNTs are extensively characterized by X-ray diffraction, scanning electron microscopy, high-resolution transmission electron microscopy, and selected-area electron diffraction. The cylinder-shaped BNNTs have an average diameter of about 100 nm and length of hundreds of microns, while the bamboo-shaped BNNTs are 100-500 nm in diameter with length up to tens of microns. The formation mechanism of the BNNTs has been explored on the basis of our experimental observations and a growth model has been proposed accordingly. Ultraviolet-visible and cathodoluminescence spectroscopic analyses are performed on the BNNTs. Strong ultraviolet emissions are detected on both morphologies of BNNTs. The band gap of the BNNTs are around 5.82 eV and nearly unaffected by tube morphology. There exist two intermediate bands in the band gap of BNNTs, which could be distinguishably assigned to structural defects and chemical impurities. [ABSTRACT FROM AUTHOR]

Managing the wastewater discharged from oil and shale gas fields is a big challenge, because this kind of wastewater is normally polluted by high contents of both oils and salts. Conventional pressure-driven membranes experience little success for treating this wastewater because of either severe membrane fouling or incapability of desalination. In this study, we designed a new nanocomposite forward osmosis (FO) membrane for accomplishing simultaneous oil/water separation and desalination. This nanocomposite FO membrane is composed of an oil-repelling and salt-rejecting hydrogel selective layer on top of a graphene oxide (GO) nanosheets infused polymeric support layer. The hydrogel selective layer demonstrates strong underwater oleophobicity that leads to superior anti-fouling capability under various oil/water emulsions, and the infused GO in support layer can significantly mitigate internal concentration polarization (ICP) through reducing FO membrane structural parameter by as much as 20%. Compared with commercial FO membrane, this new FO membrane demonstrates more than three times higher water flux, higher removals for oil and salts (>99.9% for oil and >99.7% for multivalent ions) and significantly lower fouling tendency when investigated with simulated shale gas wastewater. These combined merits will endorse this new FO membrane with wide applications in treating highly saline and oily wastewaters. [ABSTRACT FROM AUTHOR]