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In order to study the similarities and differences of mechanical and internal fine view of the structure between artificial sandstone and deep coal seam roof sandstone, artificial sandstone of different material proportions and deep roof sandstone in No. 12 Coal Mine of Pingmei Company were measured by a series of tests, including acoustic wave velocity test, uniaxial compression test, CT scanning, and high-pressure mercury injection test. The experimental results show that the greater the particle size and the higher the mass ratio of the quartz sand, the greater the elastic modulus of the artificial sandstone. For the artificial sandstone, aggregate and pore structure are uniform distribution, both the porosity and permeability are negatively correlated with the mass fraction of clay. The elastic modulus of roof sandstone is between large-grained and coarse-grained artificial sandstone, and the density distribution of rock mass is more discrete. The permeability and pore radius distribution are 1 to 2 orders of magnitude smaller than that of artificial sandstone. Comparison results show that artificial sandstone can better simulate on mechanical properties of deep roof sandstone, and on the pore structure artificial sandstone and deep roof sandstone has bigger difference.

Camellia oleifera oil (CO oil) extracted from C. oleifera seeds has a 2300-year consumption history in China. However, there is relatively little research regarding its non-edible uses. This study determined the physicochemical properties of CO oil extracted via direct pressing, identified its main components using GC-MS, and evaluated its antioxidant, moisturizing, and anti-inflammatory activities. The results revealed that CO oil's acid, peroxide, iodine, and saponification values were 1.06 ± 0.031 mg/g, 0.24 ± 0.01 g/100 g, 65.14 ± 8.22 g/100 g, and 180.41 ± 5.60 mg/g, respectively. CO oil's tocopherol, polyphenol, and squalene contents were 82.21 ± 9.07 mg/kg, 181.37 ± 3.76 mg/kg, and 53.39 ± 6.58 mg/kg, respectively; its unsaturated fatty acid (UFA) content was 87.44%, and its saturated fatty acid (SFA) content was 12.56%. CO oil also demonstrated excellent moisture retention properties, anti-inflammatory effects, and certain free radical scavenging. A highly stable CO oil emulsion with competent microbiological detection was developed using formulation optimization. Using CO oil in the emulsion significantly improved the formulation's antioxidant and moisturizing properties compared with those of the emulsion formulation that did not include CO oil. The prepared emulsion was not cytotoxic to cells and could reduce cells' NO content; therefore, it may have potential nutritional value in medicine and cosmetics. [ABSTRACT FROM AUTHOR]

As a significant source of anthropogenic greenhouse gas emissions, the municipal solid waste sector's greenhouse gas emission mode remains unknown, hampering effective decision-making on possible greenhouse gas emission reductions. Rapid urbanization and economic growth have resulted in massive volumes of municipal solid trash. As a result, identifying emission reduction routes for municipal solid waste treatment is critical. In this research, we investigate the potential of municipal solid waste treatment methods in lowering greenhouse gas (GHG) emissions in Shenzhen, a typical Chinese major city. The results showed that the combined treatment of 58% incineration, 2% landfill, and 40% anaerobic digestion (AD) had the lowest greenhouse gas emissions of about 5.91 million tons under all scenarios. The implementation of waste sorting and anaerobic digestion treatment of organic municipal solid waste after separate collection can reduce greenhouse gas emissions by simply increasing the incineration ratio. [ABSTRACT FROM AUTHOR]

The rate of the total electron content (TEC)change index (ROTI)can be regarded as an effective indicator of the level of ionospheric scintillation, in particular in low and high latitude regions. An accurate prediction of the ROTI is essential to reduce the impact of the ionospheric scintillation on earth observation systems, such as the global navigation satellite systems. However, it is difficult to predict the ROTI with high accuracy because of the complexity of the ionosphere. In this study, advanced machine learning methods have been investigated for ROTI prediction over a station at high-latitude in Canada. These methods are used to predict the ROTI in the next 5 minutes using the data derived from the past 15 minutes at the same location. Experimental results show that the method of the bidirectional gated recurrent unit network (BGRU)outperforms the other six approaches tested in the research. It is also confirmed that the RMSEs of the predicted ROTI using the BGRU method in all four seasons of 2017 are less than 0.05 TECU/min. It is demonstrated that the BGRU method exhibits a high level of robustness in dealing with abrupt solar activities.