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In order to master the distribution law of each layer state of the ion exchange resin in the EDI membrane block, this paper firstly analyzed the working principles and characteristics of the migration failure layer, exchange stability layer and hydrolysis protection layer of EDI ion exchange resin. Then, the effects of influent conductivity and operating current on the layer state distribution were tested through experiments. The results showed that the thickness of the hydrolytic protection layer was negatively correlated with the influent conductivity and positively correlated with the operating current. The hydrolysis protection layer was the key point to ensure the quality of product water from EDI membrane block. When the influent conductivity was less than 10 µS/cm (25 ℃), the ratio of the hydrolytic protective layer thickness to the thickness of the whole resin layer was ≥11.43%, which could well ensure that the conductivity of product water from EDI membrane block was

Purposes Exploration of anode materials with excellent electrochemical properties is essential to improve the performance of sodium ion batteries (SIBs). High-entropy oxides (HEO), with their unique structural characteristics, tailorable chemical composition, and tunable functional properties, have drawn increasing interest in the fields of environmental science and renewable energy technology. However, when HEO are directly used as anode materials for SIBs, a problem of agglomeration limits the electrochemical performance. In general, carbon nanotubes (CNT) are used to optimize battery performance because of their high electrical conductivity and good mechanical stability. Methods Spinel-type high-entropy oxide (FeCoNiCuMn)3O4/CNT composites (HEO/CNT) with space group Fd-3m have been synthesized through hydrothermal treatment followed by annealing method. Findings As the anode material in SIBs, at a current density of 0.5 A/g, HEO/CNT has a reversible capacity of 231 mAh/g after 200 cycles. Additionally, the HEO/CNT exhibits high reversible capacities of 363.3, 350, 341.1, 310.2, and 290.2 mAh/g at the current densities 0.1, 0.2, 0.5, 1, and 2 A/g, respectively. In situ X-ray diffraction analysis has been employed to reveal that the sodium ion storage process is a result of a combined Na＋ intercalation and conversion reaction between Na＋ and HEO/CNT. Conclusions Thanks to the “high entropy effect” of the high entropy oxide/carbon material, the volume change of the active material is mitigated during the charge/discharge process. Therefore, HEO/CNT is expected to be an electrode material with good sodium storage performance. This work provides a new template strategy for the application of high entropy materials.

Iron metabolism is considered to play the principal role in sepsis, but the key iron metabolism-related genetic signatures are unclear. In this study, we analyzed and identified the genetic signatures related to the iron-metabolism in sepsis by using a bioinformatics analysis of four transcriptomic datasets from the GEO database. A total of 21 differentially expressed iron metabolism-related signatures were identified including 9 transporters, 8 enzymes, and 4 regulatory factors. Among them, lipocalin 2 was found to have the highest diagnostic value as its expression showed significant differences in all the comparisons including sepsis vs healthy controls, sepsis vs non-sepsis diseases, and mild forms vs severe forms of sepsis. Besides, the cytochrome P450 gene CYP1B1 also showed diagnostic values for sepsis from the non-sepsis diseases. The CYP4V2, LTF, and GCLM showed diagnostic values for distinguishing the severe forms from mild forms of sepsis. Our analysis identified 21 sepsis-associated iron metabolism-related genetic signatures, which may represent diagnostic and therapeutic biomarkers of sepsis, and will improve our understanding of the molecular mechanism underlying the occurrence of sepsis.

In view of problems of coal and gas outburst prediction algorithm based on support vector machine(SVM) that prediction accuracy and reliability are not high, classification of nonlinear data is not considered when selecting kernel function, and extraction effect of influence factors of coal and gas outburst with nonlinear distribution is poor, a coal and gas outburst prediction algorithm which combines improved particle swarm optimization (IPSO) algorithm with Powell algorithm(IPSO-Powell) to optimize SVM was proposed. Firstly, main control factors of coal and gas outburst, namely initial velocity of gas emission, gas pressure, mining depth, gas content and failure type of coal body is extracted through grey correlation analysis and used as input samples of the algorithm. Then, IPSO algorithm is used to improve precocious convergence of particle swarm optimization (PSO), and Powell algorithm is used to search the local optimal solution, the penalty coefficient and Gaussian kernel function parameters of the SVM algorithm are optimized, the optimal parameter combination of SVM is obtained. Finally, the main control factors of coal and gas outburst are input to the SVM for classification , and compared with the actual test set classification results to achieve coal and gas outburst prediction. The simulation results show that compared with the SVM algorithm, GA-SVM algorithm and PSO-SVM algorithm, the application of IPSO-Powell optimized SVM algorithm for coal and gas outburst prediction has higher prediction accuracy, and improves the computational efficiency of the SVM solution process, which can meet the accuracy and reliability requirement of coal and gas outburst prediction with an accuracy rate of 95.9%.

Incremental localization algorithm is a distributed localization method with excellent characteristics for wireless network. However, its estimated result is generally influenced by the heteroscedasticity arising from cumulative errors and the collineation among anchor nodes. We have proposed a novel incremental localization algorithm with consideration to cumulative errors and collinearity among anchors. Using iteratively reweighted and regularized method, the algorithm reduces the influences of errors accumulation and avoids collinearity problem between anchors. Simulation experiment results show that compared with the previous incremental localization algorithms, the proposed algorithm obtains a localization solution which not only has high accuracy but also high stability. Therefore, the proposed algorithm is suitable for different deployment environments and has high adaptability.

C26H28N10O4Zn, monoclinic, C2/c (no. 15), a = 14.507(4) Å, b = 16.776(5) Å, c = 12.151(3) Å, β = 108.596(4)°, V = 2802.8(13) Å3, Z = 4, Rgt(F) = 0.0258, wRref(F2) = 0.0719, T = 293(2) K.

C12H14N7O9Sm, monoclinic, P21/c (no. 14), a = 16.770(3) Å, b = 7.7185(16) Å, c = 15.165(3) Å, β = 108.409(3)°, V = 1862.5(7) Å3, Z = 4, Rgt(F) = 0.0262, wRref(F2) = 0.0672, T = 296(2) K.

Biogenesis of organelles requires targeting of a subset of proteins to specific subcellular domains by signal peptides or mechanisms controlling mRNA localization and local translation. How local distribution and translation of specific mRNAs for organelle biogenesis is achieved remains elusive and likely to be dependent on the cellular context. Here we identify Trinucleotide repeat containing-6a (Tnrc6a), a component of the miRNA pathway, distinctively localized to apical granules of differentiating airway multiciliated cells (MCCs) adjacent to centrioles. In spite of being enriched in TNRC6A and the miRNA-binding protein AGO2, they lack enzymes for mRNA degradation. Instead, we found these apical granules enriched in components of the mRNA translation machinery and newly synthesized proteins suggesting that they are specific hubs for target mRNA localization and local translation in MCCs. Consistent with this, Tnrc6a loss of function prevented formation of these granules and led to a broad reduction, rather than stabilization of miRNA targets. These included downregulation of key genes involved in ciliogenesis and was associated with defective multicilia formation both in vivo and in primary airway epithelial cultures. Similar analysis of Tnrc6a disruption in yolk sac showed stabilization of miRNA targets, highlighting the potential diversity of these mechanisms across organs.

Stellite 6 was deposited by laser cladding on a P91 substrate with energy inputs of 1 kW (P91-1) and 1.8 kW (P91–1.8). The chemical compositions, microstructures and surface roughnesses of these coatings were characterized by atomic absorption spectroscopy, scanning electron microscopy and atomic force microscopy. The microhardness of the coatings was measured and the wear mechanism of the coatings was evaluated using a pin-on-plate (reciprocating) wear testing machine. The results showed less cracking and pore development for Stellite 6 coatings applied to the P91 steel substrate with the lower heat input (P91–1). Further, the Stellite coating for P91-1 was significantly harder than that obtained for P91–1.8. The wear test results indicated that the weight loss for P91–1 was much lower than for P91–1.8. The surface topography data indicated that the surface roughness for P91-1 was much lower than for P91–1.8. The measurements of dilution and carbon content showed that P91–1 has lower dilution and higher concentration of carbon than P91–1.8. It is concluded that the lower hardness of the coating for P91–1.8, together with the softer underlying substrate structure, markedly reduced the wear resistance of the Stellite 6 coating and the lower hardness of the coating for P91-1.8 was due to higher level of dilution and lower concentration of carbon.