Enhanced Acetone-Sensing Properties of PEI Thin Film by GO-NH2 Functional Groups Modification at Room Temperature

The functional groups of organic gas-sensing materials play a crucial role in adsorbing specific gas molecules, which is significant to the sensing performances of gas sensor. In this work, amido-graphene oxide (GO-NH2) loaded poly(ethyleneimine) (PEI) composite thin film (PEI/GO-NH2) with abundant amino functional groups -NH2 was successfully prepared on quartz crystal microbalance (QCM) by a combined spraying and drop coating method for acetone detection at room temperature (25°C). The morphological, spectrographic and acetone-sensing properties of composite film were investigated. The results demonstrated that a wrinkled surface morphology was formed and the ratio of nucleophilic -NH2 was increased for PEI/GO-NH2 composite film. Meanwhile, the composite film sensor possessed excellent acetone-sensing performances, and its sensitivity was about 4.2 times higher than that of pure PEI one owing to the increased -NH2 groups. This study reveals the important role of absorbing favorable functional groups and provides a novel method for the rational design and construction of acetone-sensing materials

The Research of Air Combat Intention Identification Method Based on BiLSTM + Attention

In the process of air combat intention identification, expert experience and traditional algorithm are relied on to analyze enemy aircraft combat intention in a single moment, but the identification time and accuracy are not excellent. In this paper, from the dynamic attributes of an airspace fighter air combat target and the dynamic and time series changing characteristics of the battlefield environment, we introduce the bidirectional long short-term memory neural network (BiLSTM + Attention) intention identification method based on the attention mechanism for air combat intention identification. In this method, five kinds of state parameters, including target maneuver type, distance, flight velocity, altitude and heading angle, were taken as datasets. The BiLSTM + Attention was used to extract enemy aircraft intention features. By introducing attention mechanism, the weight coefficients of characteristic states corresponding to air combat victories were corrected. Finally, it was input into the SoftMax function to obtain the category of the enemy’s intention. Experimental results showed that the proposed method can effectively identify enemy aircraft in the case of high complexity, multidimensional and large amount of data. Compared with bidirectional long short-term memory (BiLSTM), long short-term memory (LSTM), long short-term memory based on attention mechanisms (LSTM + Attention) and support vector machine (SVM) classification, the proposed method had higher accuracy and lower loss value

Association between Polymorphism of Exportin-5 and Susceptibility to Lead Poisoning in a Chinese Population

Lead (Pb) is one of the major contaminants in many industries, and imposes hazardous effects on multiple human organs and systems. Studies have shown that lead is able to induce the alteration of microRNA (miRNA) expression in serum and organs. In this study we investigated whether polymorphisms in miRNA-regulating genes were associated with the risk of lead exposure. We genotyped seven single-nucleotide polymorphisms (SNPs) in 113 lead-sensitive and 113 lead-resistant lead-related Chinese workers by Taqman analysis. The lead-sensitive group showed a significantly higher blood lead level (BLL) than the resistant group based on unconditional logistic regression results. One SNP in XPO5 extron (rs2257082) was significantly associated with lead-poisoning (p = 0.022, odds rate (OR) = 1.63, 95% confidence interval (CI) = 1.07–2.47 in the C allele compared to the T allele). There were no significant associations between the other six SNPs and the blood lead levels. Therefore, polymorphism rs2257082 could be used to distinguish lead-resistant and lead-susceptible populations, and to develop more specific and accurate preventions