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Deep learning has recently been applied to automatically classify the modulation categories of received radio signals without manual experience. However, training deep learning models requires massive volume of data. An insufficient training data will cause serious overfitting problem and degrade the classification accuracy. To cope with small dataset, data augmentation has been widely used in image processing to expand the dataset and improve the robustness of deep learning models. However, in wireless communication areas, the effect of different data augmentation methods on radio modulation classification has not been studied yet. In this paper, we evaluate different data augmentation methods via a state-of-the-art deep learning-based modulation classifier. Based on the characteristics of modulated signals, three augmentation methods are considered, i.e., rotation, flip, and Gaussian noise, which can be applied in both training phase and inference phase of the deep learning-based classifier. Numerical results show that all three augmentation methods can improve the classification accuracy. Among which, the rotation augmentation method outperforms the flip method, both of which achieve higher classification accuracy than the Gaussian noise method. Given only 12.5% of training dataset, a joint rotation and flip augmentation policy can achieve even higher classification accuracy than the baseline with initial 100% training dataset without augmentation. Furthermore, with data augmentation, radio modulation categories can be successfully classified using shorter radio samples, leading to a simplified deep learning model and a shorter classification response time.

The bioaccessibility of polybrominated diphenyl ethers (PBDEs) in indoor dust was estimated by a series of in vitro digestion methods. However, the absorption of PBDEs by intestinal cells after in vitro digestion was seldom studied. In the present study, the bioaccessibility of BDE-28, 47, 99 and 153 in indoor dust was firstly investigated by using the in vitro digestion method. Bioaccessibility in intestinal phase (BDE-28: 24.5–30.1%; BDE-47: 6.99–13.0; BDE-99: 1.61–14.2%; and BDE-153 5.97–24.4%.) was higher than that in gastric phase (BDE-28: 38.3–58.0; BDE-47: 9.62–30.9%; BDE-99: 9.71–24.3%; and BDE-153: 13.8–57.4%). The organic matter contents in indoor dust showed variable influence on the bioaccessibility of PBDEs. For the Caco-2 uptake assay, the BDE-28 showed greatest transport rate from medium to cell (K mc : 0.525 h −1 ), followed by -47, -99 and -153. The K mc of PBDEs was significantly negative correlated with its corresponding K OW value. Similar pattern was found for the maximum uptake flux (J u, max ) and the transport rate from cell to medium (K cm ). The combination of bioacessibility and the absorption factor by Caco-2 cells could be used to estimate human intake of PBDEs via indoor dust would avoid overestimate the health risk.

There is limited information on the BDE-209 relative bioavailability (RBA) of indoor dust and the absorption of BDE-209 after in vitro digestion was seldom studied. In the present study, BDE-209 RBA in 6 household dust samples measured using an in vivo mouse model was compared to BDE-209 bioaccessibility determined using physiologically based extraction test (PBET) and solubility bioaccessibility research consortium method (SBRC) assays. BDE-209 RBA obtained ranged from 45.9 ± 16.1 to 96.0 ± 17.4% and exhibited a significant relationship with PBET gastric phase (r2 = 0.578, p = 0.080), small intestinal phase (r2 = 0.728, p = 0.031) and total BDE-209 bioaccessibility (r2 = 0.728, p = 0.031), which indicated PBET assay can serve as a surrogate to predict BDE-209 RBA to refine human health exposure. In addition, the absorption of BDE-209 by Caco-2 cell line was assessed. With the consideration of the corresponding bioaccessibility and absorption of BDE-209 by Caco-2 cell line, the human daily intake of BDE-209 via dust ingestion for adults and children was much lower than that estimated by total concentration.

Zhenyuan gold deposit is the largest super large gold deposit in the Ailaoshan gold belt, but its precise mineralization age is still lack. Re-Os isotopic age of the auriferous pyrite from the Zhenyuan gold deposit was determined by using a high-resolution inductively coupled plasma mass spectrometry (HR-ICP-MS). The pyrite samples were decomposed in carius tubes, Os was separated by distillation and Re was extracted by acetone, respectively. The results show that the Re-Os isochron age is 229±38 Ma (MSWD=2.0, confidence level is 95%), with an initial 187Os/188Os value of 0.68±0.24 and a corresponding γOs value of 442±91. The Re/Os ratios of the pyrite vary from 40.8 to 100.5. The data suggest that at least one important ore-forming event was occurred during Indosinian epoch, and the ore-forming materials probably derived from mixed sources of crustal and mantle, while the later dominated. The Ailaoshan composite orogen experienced complicated evolutional processes, including formation of Precambrian-Early Paleozoic basement, subduction and orogenesis of Late Paleozoic era, collisional orogenesis of Late Hercynian-Indosinain epoch, and extensional or striking orogenesis of Yanshainan-Cenozoic epoch. The polycycle tectonic evolution and magmatism in this area caused multi-stage and superposition metallization characteristics of the Zhenyuan gold deposit: the mineralization probably occur mainly during the Indosinian collisional orogeny, while the minor gold ores of altered granite-porphyry and altered lamprophyre may be formed in the late superposition metallization.