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Microseismic monitoring plays an essential role for reservoir characterization and earthquake disaster monitoring and early warning. The accuracy of the subsurface velocity model directly affects the precision of event localization and subsequent processing. It is challenging for traditional methods to realize efficient and accurate microseismic velocity inversion due to the low signal-to-noise ratio of field data. Deep learning can efficiently invert the velocity model by constructing a mapping relationship from the waveform data domain to the velocity model domain. The predicted and reference values are fitted with mean square error as the loss function. To reduce the feature mismatch between the synthetic and real microseismic data, data augmentation is also performed using correlation and convolution operations. Moreover, a hybrid training strategy is proposed by combining synthetic and augmented data. By testing real microseismic data, the results show that the Unet is capable of high-resolution and robust velocity prediction. The data augmentation method complements more high-frequency components, while the hybrid training strategy fully combines the low-frequency and high-frequency components in the data to improve the inversion accuracy.

Malignant cancer is a devastating disease often associated with a poor clinical prognosis. For decades, modern drug discoveries have attempted to identify potential modulators that can impede tumor growth. Cancer stem cells however are more resistant to therapeutic intervention, which often leads to treatment failure and subsequent disease recurrence. Here in this study, we have developed a specific multi-target drug delivery nanoparticle system against breast cancer stem cells (BCSCs). Therapeutic agents curcumin and salinomycin have complementary functions of limiting therapeutic resistance and eliciting cellular death, respectively. By conjugation of CD44 cell-surface glycoprotein with poly(lactic-co-glycolic acid) (PLGA) nanoparticles that are loaded with curcumin and salinomycin, we investigated the cellular uptake of BCSCs, drug release, and therapeutic efficacy against BCSCs. We determined CD44-targeting co-delivery nanoparticles are highly efficacious against BCSCs by inducing G1 cell cycle arrest and limiting epithelial–mesenchymal transition. This curcumin and salinomycin co-delivery system can be an efficient treatment approach to target malignant cancer without the repercussion of disease recurrence.

A general and efficient aerobic oxidative hydroxylation of arylboronic acids promoted by benzoquinone in water was realized, and provided phenols in 72-95% yields for 20 examples. The main advantages of this protocol are the use of water as solvent in the presence of a catalytic amount of benzoquinone, and metal-free conditions. [ABSTRACT FROM AUTHOR]