The Coal Mine Accident Causation Model Based on the Hazard Theory

AbstractOn the basis of the summary of the existing research, first of all, the essential factors of coal mine accidents was differentiated and analyzed, and the technology equipment defects was believed to be the essential reasons that affect the coal mine safety. And then using the hazard theory the accident causation in coal mine production system has been divided, and it was believed that coal mine hazard sources consisted of inherent hazards, technology equipment defects and safety management misconducts. On this basis, the coal mine accident causation model on a combination of hazard theory and energy accidental releasing theory was established. Finally, this model was used to analyze the roof-fall accident of Baishui Coal Mine

Dunhuang murals contour generation network based on convolution and self-attention fusion

Dunhuang murals are a collection of Chinese style and national style, forming a self-contained Chinese-style Buddhist art. It has very high historical and cultural value and research significance. Among them, the lines of Dunhuang murals are highly general and expressive. It reflects the character's distinctive character and complex inner emotions. Therefore, the outline drawing of murals is of great significance to the research of Dunhuang Culture. The contour generation of Dunhuang murals belongs to image edge detection, which is an important branch of computer vision, aims to extract salient contour information in images. Although convolution-based deep learning networks have achieved good results in image edge extraction by exploring the contextual and semantic features of images. However, with the enlargement of the receptive field, some local detail information is lost. This makes it impossible for them to generate reasonable outline drawings of murals. In this paper, we propose a novel edge detector based on self-attention combined with convolution to generate line drawings of Dunhuang murals. Compared with existing edge detection methods, firstly, a new residual self-attention and convolution mixed module (Ramix) is proposed to fuse local and global features in feature maps. Secondly, a novel densely connected backbone extraction network is designed to efficiently propagate rich edge feature information from shallow layers into deep layers. Compared with existing methods, it is shown on different public datasets that our method is able to generate sharper and richer edge maps. In addition, testing on the Dunhuang mural dataset shows that our method can achieve very competitive performance

Rh(I)-Catalyzed Enantioselective Hydrogenation of α‑Substituted Ethenylphosphonic Acids

A class of chiral Rh­(I) catalysts containing monodentate phosphorous acid diesters tautomerized from the corresponding secondary phosphine oxides was discovered by serendipitous hydrolysis of phosphoramidite ligands. The evolved catalysts demonstrated unprecedented enantioselectivities (98–99% ee) and high catalytic activities (as low as 0.01 mol% catalyst loading) in asymmetric hydrogenations of a wide variety of α-aryl-/alkyl-substituted ethenylphosphonic acids, providing a facile approach to the corresponding enantiopure phosphonic acids with significant biological importance

Rh(I)-Catalyzed Enantioselective Hydrogenation of α‑Substituted Ethenylphosphonic Acids

A class of chiral Rh­(I) catalysts containing monodentate phosphorous acid diesters tautomerized from the corresponding secondary phosphine oxides was discovered by serendipitous hydrolysis of phosphoramidite ligands. The evolved catalysts demonstrated unprecedented enantioselectivities (98–99% ee) and high catalytic activities (as low as 0.01 mol% catalyst loading) in asymmetric hydrogenations of a wide variety of α-aryl-/alkyl-substituted ethenylphosphonic acids, providing a facile approach to the corresponding enantiopure phosphonic acids with significant biological importance

Rh(I)-Catalyzed Enantioselective Hydrogenation of α‑Substituted Ethenylphosphonic Acids

A class of chiral Rh­(I) catalysts containing monodentate phosphorous acid diesters tautomerized from the corresponding secondary phosphine oxides was discovered by serendipitous hydrolysis of phosphoramidite ligands. The evolved catalysts demonstrated unprecedented enantioselectivities (98–99% ee) and high catalytic activities (as low as 0.01 mol% catalyst loading) in asymmetric hydrogenations of a wide variety of α-aryl-/alkyl-substituted ethenylphosphonic acids, providing a facile approach to the corresponding enantiopure phosphonic acids with significant biological importance

Perfect spin filter and strong current polarization in carbon atomic chain with asymmetrical connecting points

The spin-dependent electron transport properties through a single-carbon atomic chain (SCAC) sandwiched between two-zigzag-graphene-nanoribbon (zGNR) electrodes are investigated by performing first-principles calculations based on the nonequilibrium Green's function (NEGF) approach in combination with spin density functional theory (DFT). Our calculations show that SCAC connecting two zGNRs with asymmetry-contacting points is a perfect spin filter in the transmission function within a large energy range. Moreover, the spin-dependent electron transmission spectra exhibit robust transport polarization characteristics and a strong current polarization behavior (almost 100%) can be found. The microscopic mechanisms are proposed for the spin-related phenomena

RNA-Seq Revealed the Molecular Mechanism of Nutritional Quality Improvement in <i>o16-wx</i> Double-Mutation Maize

The enhancement of the nutritional composition of maize grains could be achieved by the introduction of a mutation with a heightened lysine content. To obtain double-recessive mutant lines for the o16 and wx genes, a molecular-marker-assisted selection technique was used to backcross them into conventional maize lines. The resultant maize was subsequently utilized to explore the molecular mechanism responsible for the maize’s nutritional quality. Based on this, an RNA-seq investigation was conducted using the employing kernels during the development period of maize kernel (18, 28, and 38 DAP) to examine the gene expression involved in amino metabolism. The results revealed that a total of 27 and 34 differentially expressed genes (DEGs) were identified in tryptophan metabolism and lysine metabolism, respectively, across three time periods. In the lysine synthesis pathway, the genes encoding AK, ASD, and DapF were found to be up-regulated at various stages, encouraging lysine synthesis. Conversely, in the lysine degradation pathway, the genes encoding ALDH7A1 and LKR/SDH were down-regulated, suggesting an increase in lysine content. In the process of tryptophan metabolism, the down-regulation of genes encoding TAA and ALDH led to an increase in tryptophan content. In addition, the down-regulation of genes encoding α-zein resulted in a decrease in zein content, thereby enhancing the nutritional quality of maize. These findings hold substantial significance for elucidating the transcriptional-level molecular mechanism, underlying the accumulation of o16 and wx genes to improve maize grain quality, as well as offering valuable insight for the development of biomarkers and gene editing

Dual Optical Frequency Comb Generation with Dual Cascaded Difference Frequency Generation

In this work, we propose a novel dual optical frequency comb (DOFC) generation scheme based on dual cascaded difference frequency generation (DCDFG). Feasible designs are introduced that enable the two sets of cascaded optical waves, initially generated by DCDFG in an aperiodically periodically poled lithium niobate (APPLN) crystal with a pump wave and two signal waves, then transferred to high-order Stokes waves by oscillations of cascaded Stokes waves and the optimization of phase mismatching of each-order DCDFG; finally, a DOFC was constructed. We demonstrate a high-performance DOFC with characteristics of high repetition frequency difference, tunable repetition frequency difference, high flatness, and a tunable spectral distribution range by providing a theoretical framework. We argue that the scheme proposed in this work is promising for achieving a high-quality DOFC

Dual Optical Frequency Comb Generation with Dual Cascaded Difference Frequency Generation

In this work, we propose a novel dual optical frequency comb (DOFC) generation scheme based on dual cascaded difference frequency generation (DCDFG). Feasible designs are introduced that enable the two sets of cascaded optical waves, initially generated by DCDFG in an aperiodically periodically poled lithium niobate (APPLN) crystal with a pump wave and two signal waves, then transferred to high-order Stokes waves by oscillations of cascaded Stokes waves and the optimization of phase mismatching of each-order DCDFG; finally, a DOFC was constructed. We demonstrate a high-performance DOFC with characteristics of high repetition frequency difference, tunable repetition frequency difference, high flatness, and a tunable spectral distribution range by providing a theoretical framework. We argue that the scheme proposed in this work is promising for achieving a high-quality DOFC