Evolution of pore structure, submaceral composition and produced gases of two Chinese coals during thermal treatment

This research was funded by the Research Program for Excellent Doctoral Dissertation Supervisor of Beijing (grant no. YB20101141501), the Fundamental Research Funds for Central Universities (grant no. 35832015136) and Key Project of Coal-based Science and Technology in Shanxi Province-CBM accumulation model and reservoir evaluation in Shanxi province (grant no. MQ2014-01).Peer reviewedPostprin

Magnetic Borophenes from an Evolutionary Search

A computational methodology based on ab initio evolutionary algorithms and spin-polarized density functional theory was developed to predict two-dimensional magnetic materials. Its application to a model system borophene reveals an unexpected rich magnetism and polymorphism. A metastable borophene with nonzero thickness is an antiferromagnetic semiconductor from first-principles calculations, and can be further tuned into a half-metal by finite electron doping. In this borophene, the buckling and coupling among three atomic layers are not only responsible for magnetism, but also result in an out-of-plane negative Poisson\u27s ratio under uniaxial tension, making it the first elemental material possessing auxetic and magnetic properties simultaneously

PLUG: Leveraging Pivot Language in Cross-Lingual Instruction Tuning

Instruction tuning has remarkably advanced large language models (LLMs) in understanding and responding to diverse human instructions. Despite the success in high-resource languages, its application in lower-resource ones faces challenges due to the imbalanced foundational abilities of LLMs across different languages, stemming from the uneven language distribution in their pre-training data. To tackle this issue, we propose pivot language guided generation (PLUG), an approach that utilizes a high-resource language, primarily English, as the pivot to enhance instruction tuning in lower-resource languages. It trains the model to first process instructions in the pivot language, and then produce responses in the target language. To evaluate our approach, we introduce a benchmark, X-AlpacaEval, of instructions in 4 languages (Chinese, Korean, Italian, and Spanish), each annotated by professional translators. Our approach demonstrates a significant improvement in the instruction-following abilities of LLMs by 29% on average, compared to directly responding in the target language alone. Further experiments validate the versatility of our approach by employing alternative pivot languages beyond English to assist languages where LLMs exhibit lower proficiency

Optimization of Fermentation Medium for the Production of Atrazine Degrading Strain Acinetobacter

Statistical experimental designs provided by statistical analysis system (SAS) software were applied to optimize the fermentation medium composition for the production of atrazine-degrading Acinetobacter sp. DNS32 in shake-flask cultures. A “Plackett-Burman Design” was employed to evaluate the effects of different components in the medium. The concentrations of corn flour, soybean flour, and K2HPO4 were found to significantly influence Acinetobacter sp. DNS32 production. The steepest ascent method was employed to determine the optimal regions of these three significant factors. Then, these three factors were optimized using central composite design of “response surface methodology.” The optimized fermentation medium composition was composed as follows (g/L): corn flour 39.49, soybean flour 25.64, CaCO3 3, K2HPO4 3.27, MgSO4 ·7H2O 0.2, and NaCl 0.2. The predicted and verifiable values in the medium with optimized concentration of components in shake flasks experiments were 7.079×108 CFU/mL and 7.194×108 CFU/mL, respectively. The validated model can precisely predict the growth of atrazine-degraing bacterium, Acinetobacter sp. DNS32

Protective Effects of Total Flavones of Elaeagnus rhamnoides

The aim was to evaluate the protective effects of total flavones of Elaeagnus rhamnoides (L.) A. Nelson (TFE) against vascular endothelial injury in blood stasis model rats and explore the potential mechanisms preliminarily. The model of blood stasis rat model with vascular endothelial injury was induced by subcutaneous injection of adrenaline combined with ice-water bath. Whole blood viscosity (WBV), histological examination, and prothrombin time (PT), activated partial thromboplastin time (APTT), and fibrinogen (FIB) were measured. Meanwhile, the levels of Thromboxane B2 (TXB2), 6-keto-PGF1α, von Willebrand factor (vWF), and thrombomodulin (TM) were detected. In addition, Quantitative Real-Time PCR (qPCR) was performed to identify PI3K, Erk2, Bcl-2, and caspase-3 gene expression. The results showed that TFE can relieve WBV, increase PT and APTT, and decrease FIB content obviously. Moreover, TFE might significantly downregulate the levels of TXB2, vWF, and TM in plasma and upregulate the level of 6-keto-PGF1α in plasma. Expressions of PI3K and Bcl-2 were increased and the expression of caspase-3 was decreased by TFE pretreatment in the rat model. Consequently, the study suggested that TFE may have the potential against vascular endothelial injury in blood stasis model rats induced by a high dose of adrenaline with ice-water bath