Survey on roof movement of the gangue backfill working face

This paper studied the roof movement characteristics of LW1302N-1 with gangue backfill mining in Shandong Xinjulong Company of China. The monitoring of roof subsidence of the gob and bearing stress of filled gangue was carried out by using the roof subsidence and gangue loading monitoring system. From data analysis, the result shows that: (1) Gob roof subsidence can be divided into six stages including slow subsidence, fast subsidence, very fast subsidence, subsidence slowing down, subsidence speeding up and subsidence becoming slow. (2) Filled gangue loading period can be divided into four stages including slow increasing resistance, fast increasing strength, strengthening and continuing increasing resistance, Similarly, the gob roof movement consists of four steps such as immediate roof caving, central roof flexure, main roof fracturing, and high strata flexure. (3) The immediate roof is 3.1 times the thickness of equal mining height, and the main roof is 2.7 times the thickness of equal mining height. The research results provide a reference to the analysis of the characteristics of overlying strata structure and roof movement for gangue backfill mining in deep coal mines

Chemical and Electrochemical Studies of Cl\u3csub\u3e2\u3c/sub\u3eFeS\u3csub\u3e2\u3c/sub\u3eMS\u3csub\u3e2\u3c/sub\u3eFeCl\u3csub\u3e2\u3c/sub\u3e\u3csup\u3e\u3cem\u3en\u3c/em\u3e-\u3c/sup\u3e Clusters [M = Mo (n = \u3cem\u3e2\u3c/em\u3e), W (\u3cem\u3en\u3c/em\u3e = 2), V (\u3cem\u3en\u3c/em\u3e = 3)]

The electrochemistry and spectroelectrochemistry of [Cl2FeS2MS2FeCl2]n- clusters (where n = 2 for M = Mo and W and n = 3 for M = V; Ia, Ib, and Ic, respectively) and the dimetal complex [Cl2FeS2MoS2]2- (IIIa) were examined in order to characterize the structures and properties of the one-electron-reduced complexes. A stable reduction product for Ia was observed spectroelectrochemically at −1.05 V, which could be oxidized back to the starting complex. Reduction at more negative potentials caused complete bleaching of the spectrum, and the starting complex could not be obtained by reoxidation. Similar behavior was observed for the tungsten complex, Ib, but the dimetal complex [Cl2FeS2WS2]2- was formed upon reoxidation. Chemical and electrochemical reduction of Ia and Ib both led to the same products (IIa and IIb), but by different mechanisms. Borohydride reduction of Ia and Ib led to the initial formation of the dimetal complex, while the electrochemical reduction of Ia proceeded by way of the formation of [Cl2FeS2MoS2FeCl2]3-. Spectral changes were observed in the reduction of Ic, but they were not reversible. Resonance Raman spectroscopy of the reduced complexes was carried out in order to characterize the reduction product. Two polarized bands in the sulfur bridging region were observed in the resonance Raman spectra of electrochemically and chemically generated IIa and IIb. The relative intensities of these bands were dependent upon the excitation frequency. Reduction of Ic led to the loss of all resonance Raman bands. Reduction of IIIa gave rise to a complex (IVa) that was spectrally quite similar to IIa. These results, along with the previously reported result that the reduction complex was diamagnetic, indicate that the complex IIa is a dimeric species. The most likely structure consistent with these data is a Mo2Fe2S4 cubane structure

Integrated transcriptome analysis reveals miRNA-mRNA crosstalk in laryngeal squamous cell carcinoma.

Next generation sequencing (NGS) has proven to be a powerful tool in delineating myriads of molecular subtypes of cancer, as well as in revealing accumulation of genomic mutations throughout cancer progression. Whole genome microRNA (miRNA) and mRNA expression profiles were obtained from patients with laryngeal squamous cell carcinoma (LSCC) using deep sequencing technology, and were analyzed by utilizing integrative computational approaches. A large number of protein-coding and non-coding genes were detected to be differentially expressed, indicating a functional switch in LSCC cells. A total of 127 mutated genes were detected to be significantly associated with ectoderm and epidermis development. Eleven miRNAs were found to be differentially expressed, including a potential cancer suppressor miRNA, mir-34c, which was dramatically down-regulated. Integrated analysis of mRNA and miRNA transcriptomes further revealed correlated dynamics among 11 miRNAs and 138 targeted genes, forming a highly dynamical co-regulation network response to LSCC development

A PCA and ELM Based Adaptive Method for Channel Equalization in MFL Inspection

Magnetic flux leakage (MFL) as an efficient method for pipeline flaw detection plays important role in pipeline safety. This nondestructive test technique assesses the health of the buried pipeline. The signal is gathered by an array of hall-effect sensors disposed at the magnetic neutral plane of a pair of permanent magnet in the pipeline inspection gauge (PIG) clinging to the inner surface of the pipe wall. The magnetic flux measured by the sensors reflects the health condition of the pipe. The signal is influenced by not only the condition of the pipe, but also by the lift-off value of the sensors and various properties of electronic component. The consistency of the position of the sensors is almost never satisfied and each sensor measures differently. In this paper, a new scheme of channel equalization is proposed for MFL signal in order to correct sensor misalignments, which eventually improves accuracy of defect characterization. The algorithm proposed in this paper is adaptive to the effects of error on the disposition of the sensor due to manufacturing imperfections and movements of the sensors. The algorithm is tested by data acquired from an experimental pipeline. The results show the effectiveness of the proposed algorithm

Detection and Genetic Analysis of Porcine Bocavirus

Porcine Bocavirus (PBoV) has been reported to be associated with postweaning multisystemic wasting syndrome and pneumonia in pigs. In this study, a survey was conducted to evaluate the prevalence of PBoV in slaughter pigs, sick pigs, asymptomatic pigs and classical swine fever virus (CSFV) eradication plan herds in five provinces of China (Henan, Liaoning, Shandong, Hebei and Tianjin) by means of PCR targeting NS1 gene of PBoV. Among the total of 403 tissue samples, 11.41% were positive for PBoV. The positive rates of spleen (20.75%) and inguinal lymph node (27.18%) are higher than those of other organs. PCR products of twenty PBoV positive samples from slaughter pigs were sequenced for phylogenetic analysis. The result revealed that PBoV could be divided into 6 groups (PBoV-a~PBoV-f). All PBoV sequenced in this study belong to PBoV-a–PBoV-d with 90.1% to 99% nucleotide identities. Our results exhibited significant genetic diversity of PBoV and suggested a complex prevalence of PBoV in Chinese swine herds. Whether this diversity of PBoV has a significance to pig production or even public health remains to be further studied

An Adaptive Fuzzy Min-Max Neural Network Classifier Based on Principle Component Analysis and Adaptive Genetic Algorithm

A novel adaptive fuzzy min-max neural network classifier called AFMN is proposed in this paper. Combined with principle component analysis and adaptive genetic algorithm, this integrated system can serve as a supervised and real-time classification technique. Considering the loophole in the expansion-contraction process of FMNN and GFMN and the overcomplex network architecture of FMCN, AFMN maintains the simple architecture of FMNN for fast learning and testing while rewriting the membership function, the expansion and contraction rules for hyperbox generation to solve the confusion problems in the hyperbox overlap region. Meanwhile, principle component analysis is adopted to finish dataset dimensionality reduction for increasing learning efficiency. After training, the confidence coefficient of each hyperbox is calculated based on the distribution of samples. During classifying procedure, utilizing adaptive genetic algorithm to complete parameter optimization for AFMN can also fasten the entire procedure than traversal method. For conditions where training samples are insufficient, data core weight updating is indispensible to enhance the robustness of classifier and the modified membership function can adjust itself according to the input varieties. The paper demonstrates the performance of AFMN through substantial examples in terms of classification accuracy and operating speed by comparing it with FMNN, GFMN, and FMCN