PASSPORT-seq: A Novel High-Throughput Bioassay to Functionally Test Polymorphisms in Micro-RNA Target Sites

Next-generation sequencing (NGS) studies have identified large numbers of genetic variants that are predicted to alter miRNA-mRNA interactions. We developed a novel high-throughput bioassay, PASSPORT-seq, that can functionally test in parallel 100s of these variants in miRNA binding sites (mirSNPs). The results are highly reproducible across both technical and biological replicates. The utility of the bioassay was demonstrated by testing 100 mirSNPs in HEK293, HepG2, and HeLa cells. The results of several of the variants were validated in all three cell lines using traditional individual luciferase assays. Fifty-five mirSNPs were functional in at least one of three cell lines (FDR ≤ 0.05); 11, 36, and 27 of them were functional in HEK293, HepG2, and HeLa cells, respectively. Only four of the variants were functional in all three cell lines, which demonstrates the cell-type specific effects of mirSNPs and the importance of testing the mirSNPs in multiple cell lines. Using PASSPORT-seq, we functionally tested 111 variants in the 3' UTR of 17 pharmacogenes that are predicted to alter miRNA regulation. Thirty-three of the variants tested were functional in at least one cell line

Study on the Reasonable Smoke Exhaust Rate of the Crossrange Exhaust Duct in Double-layer Shield Tunnel

AbstractThe research on the concentrated smoke extraction system of crossrange exhaust duct in double-layer shield tunnel is still very lack in the world. This paper is on the smoke extraction system of double-layer shield tunnel. It will provide the supports and references for the smoke control of tunnel fire and the determination of related technical parameters in the design of tunnel fire ventilation and smoke extraction, so it has important scientific value, practical significance and application prospects. This paper bases on the tunnel project of Slender West Lake in Yangzhou. By using the method of combining theory and numerical simulation, a conclusion can be drawn that the reasonable smoke exhaust rate of the upper tunnel is 140 m3/s

Interfacial Properties of Bilayer and Trilayer Graphene on Metal Substrates

One popular approach to prepare graphene is to grow them on transition metal substrates via chemical vapor deposition. By using the density functional theory with dispersion correction, we systematically investigate for the first time the interfacial properties of bilayer (BLG) and trilayer graphene (TLG) on metal substrates. Three categories of interfacial structures are revealed. The adsorption of B(T)LG on Al, Ag, Cu, Au, and Pt substrates is a weak physisorption, but a band gap can be opened. The adsorption of B(T)LG on Ti, Ni, and Co substrates is a strong chemisorption, and a stacking-insensitive band gap is opened for the two uncontacted layers of TLG. The adsorption of B(T)LG on Pd substrate is a weaker chemisorption, with a band gap opened for the uncontacted layers. This fundamental study also helps for B(T)LG device study due to inevitable graphene/metal contact.Comment: 1 table, 8 figure

Crystal Structure Manipulation of the Exchange Bias in an Antiferromagnetic Film

Exchange bias is one of the most extensively studied phenomena in magnetism, since it exerts a unidirectional anisotropy to a ferromagnet (FM) when coupled to an antiferromagnet (AFM) and the control of the exchange bias is therefore very important for technological applications, such as magnetic random access memory and giant magnetoresistance sensors. In this letter, we report the crystal structure manipulation of the exchange bias in epitaxial hcp Cr2O3 films. By epitaxially growing twined (10-10) oriented Cr2O3 thin films, of which the c axis and spins of the Cr atoms lie in the film plane, we demonstrate that the exchange bias between Cr2O3 and an adjacent permalloy layer is tuned to in-plane from out-of-plane that has been observed in (0001) oriented Cr2O3 films. This is owing to the collinear exchange coupling between the spins of the Cr atoms and the adjacent FM layer. Such a highly anisotropic exchange bias phenomenon is not possible in polycrystalline films.Comment: To be published in Scientific Reports, 12 pages, 6 figure

An improved LSTM-Seq2Seq-based forecasting method for electricity load

Power load forecasting has gained considerable research interest in recent years. The power load is vulnerable to randomness and uncertainty during power grid operations. Therefore, it is crucial to effectively predict the electric load and improve the accuracy of the prediction. This study proposes a novel power load forecasting method based on an improved long short-term memory (LSTM) neural network. Thus, an long short-term memory neural network model is established for power load forecasting, which supports variable-length inputs and outputs. The conventional convolutional neural network (CNN) and recurrent neural network (RNN) cannot reflect the sequence dependence between the output labels. Therefore, the LSTM-Seq2Seq prediction model was established by combining the sequence-to-sequence (Seq2Seq) structure with that of the long short-term memory model to improve the prediction accuracy. Four prediction models, i.e., long short-term memory, deep belief network (DBN), support vector machine (SVM), and LSTM-Seq2Seq, were simulated and tested on two different datasets. The results demonstrated the effectiveness of the proposed LSTM-Seq2Seq method. In the future, this model can be extended to more prediction application scenarios