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This study investigated the effect of extrusion ratio on the microstructural evolution and mechanical properties of the as-extruded short carbon fibers (SCFs) reinforced AZ31 alloy composite, and the microstructural development of the composite during extrusion was thoroughly investigated. The dominant dynamic recrystallization (DRX) mechanisms are particle simulated nucleation, continuous DRX, and discontinuous DRX. The addition of SCFs promotes the dynamic recrystallization during hot extrusion. As extrusion ratio increases, the interfacial bonding degree of the composite increases gradually, and the composite with an extrusion ratio of 25:1 exhibits the finest DRXed grains and the best mechanical performance with a yield strength of 171 MPa, an ultimate tensile strength of 258 MPa and an elongation of 6.0%. The enhanced strength is mainly attributed to grain refinement strengthening and dislocation strengthening, which are induced by the DRXed grains and the added SCFs. [ABSTRACT FROM AUTHOR]

Carbonyl compounds cause adverse effect on human health and play important roles in the atmospheric chemical reactions in the troposphere. However, their characteristics and complicated environmental impacts were poorly understood around petrochemical enterprises over North China. In this study, we found that acetone (2.8 ± 1.39 ppbv), acetaldehyde (2.74 ± 1.45 ppbv) and formaldehyde (2.73 ± 1.48 ppbv) were the three most abundant carbonyls, accounting for about 85% of the total concentration of the 15 carbonyls measured in the petrochemical industrial area of Jinan during the winter. The dominant sources of atmospheric carbonyls were vehicle exhaust, petrochemical processes and residential combustion as inferred by the good correlation between carbonyls and primary pollutants such as CO and NOx and the diagnostic ratios of formaldehyde to acetaldehyde (C1/C2, 1.00 ± 0.11). In addition, backward trajectories suggest that air mass transport also contributes to carbonyl compounds. Furthermore, carbonyls showed strong positive correlation with PM2.5, probably due to the promoting effect of carbonyl compounds on atmospheric oxidation capacity (AOC), which in turn makes PM2.5 concentration increase. On the other hand, PM2.5 photochemical aging causes an increase in secondary carbonyls concentration. Overall, the present study indicates considerable impacts of carbonyls on PM2.5 pollution in petrochemical enterprises area and suggests the urgent need for intensive study on the related processes. [ABSTRACT FROM AUTHOR]

We use the concept of negativity to study the entanglement of spin-1/2 and spin-5/2 antiferromagnetic Heisenberg model with an inhomogeneous magnetic field. Analytical conclusions of the model are acquired. It is found that the critical temperature $$T_\mathrm{c}$$ goes up, as the increase of anisotropy parameter $$k$$ . The temperature $$T_\mathrm{c}$$ becomes bigger than the results of spin-1/2 and spin-3/2 Heisenberg XXZ chain for the same value of $$k$$ . And we can gain more entanglement at higher temperature by coordinating the value of inhomogeneity $$b$$ . [ABSTRACT FROM AUTHOR]

Antrodia camphorata is a well-known Chinese medicinal mushroom that protects against diverse health-related conditions. Submerged fermentation of A. camphorata is an alternative choice for the effective production of bioactive metabolites, but the effects of nutrition and environment on mycelial morphology are largely unknown. In this study, we show that A. camphorata American Type Culture Collection 200183 can form arthrospores in the end of liquid fermentation. Different morphologies of A. camphorata in submerged culture were analyzed using scanning electron microscopy. The optimal carbon and nitrogen sources for sporulation were soluble starch and yeast extract. We found that a carbon-to-nitrogen ratio (C/N) of 40:1, MgSO (0.5 g/l), KHPO (3.0 g/l), an initial pH 5.0, and an inoculum size of 1.5 × 10 spores/ml led to maximum production of arthroconidia. Our results will be useful in the regulation and optimization of A. camphorata cultures for efficient production of arthroconidia in submerged culture, which can be used as inocula in subsequent fermentation processes. [ABSTRACT FROM AUTHOR]

Extreme learning machine (ELM) as a new learning algorithm has been proposed for single-hidden layer feed-forward neural networks, ELM can overcome many drawbacks in the traditional gradient-based learning algorithm such as local minimal, improper learning rate, and low learning speed by randomly selecting input weights and hidden layer bias. However, ELM suffers from instability and over-fitting, especially on large datasets. In this paper, a dynamic ensemble extreme learning machine based on sample entropy is proposed, which can alleviate to some extent the problems of instability and over-fitting, and increase the prediction accuracy. The experimental results show that the proposed approach is robust and efficient. [ABSTRACT FROM AUTHOR]

Microbial transformation of glycinonitrile into glycine by nitrile hydrolase is of considerable interest to green chemistry. A novel fungus with high nitrile hydrolase was newly isolated from soil samples and identified as Fusarium oxysporum H3 through 18S ribosomal DNA, 28S ribosomal DNA, and the internal transcribed spacer sequence analysis, together with morphology characteristics. After primary optimization of culture conditions including pH, temperature, carbon/nitrogen sources, inducers, and metal ions, the enzyme activity was greatly increased from 326 to 4,313 U/L. The preferred carbon/nitrogen sources, inducer, and metal ions were glucose and yeast extract, caprolactam, and Cu, Mn, and Fe, respectively. The maximum enzyme formation was obtained when F. oxysporum H3 was cultivated at 30 °C for 54 h with the initial pH of 7.2. There is scanty report about the optimization of nitrile hydrolase production from nitrile-converting fungus. [ABSTRACT FROM AUTHOR]

In this study, alteration in morphology of submergedly cultured Antrodia camphorata ATCC 200183 including arthroconidia, mycelia, external and internal structures of pellets was investigated. Two optimization models namely response surface methodology (RSM) and artificial neural network (ANN) were built to optimize the inoculum size and medium components for intracellular triterpenoid production from A. camphorata. Root mean squares error, R, and standard error of prediction given by ANN model were 0.31%, 0.99%, and 0.63%, respectively, while RSM model gave 1.02%, 0.98%, and 2.08%, which indicated that fitness and prediction accuracy of ANN model was higher when compared to RSM model. Furthermore, using genetic algorithm (GA), the input space of ANN model was optimized, and maximum triterpenoid production of 62.84 mg l was obtained at the GA-optimized concentrations of arthroconidia (1.78 × 10 ml) and medium components (glucose, 25.25 g l; peptone, 4.48 g l; and soybean flour, 2.74 g l). The triterpenoid production experimentally obtained using the ANN-GA designed medium was 64.79 ± 2.32 mg l which was in agreement with the predicted value. The same optimization process may be used to optimize many environmental and genetic factors such as temperature and agitation that can also affect the triterpenoid production from A. camphorata and to improve the production of bioactive metabolites from potent medicinal fungi by changing the fermentation parameters. [ABSTRACT FROM AUTHOR]