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In legume nodules, malate is generally considered to provide carbon for both nodule bacteroid respiration and skeletons for NH4+ assimilation. Although it has been suggested that phosphorus (P) deficiency inhibits legume nodule growth through adversely affecting carbon partitioning, the molecular mechanisms underlying malate synthesis and its roles in nodule growth remain largely unknown in soybean (Glycine max). In this study, we found that P deficiency led to a significant decrease of soybean nodule size (fresh weight of individual soybean nodule), accompanying with increased malate concentration. Meanwhile, 16 malate dehydrogenase (GmMDH) members were identified in the soybean genome, and their expression patterns were investigated in soybean nodules in responses to P deficiency. Among them, GmMDH12 was up-regulated by phosphate (Pi) starvation. Enzymatic analysis of GmMDH12 revealed its functions in catalyzing malate synthesis through reduction of oxaloacetate to form malate in vitro. Furthermore, overexpression of GmMDH12 resulted in a significant decrease in nodule size, but a significant increase in concentrations of malate and several carbohydrates in transgenic soybean nodules. Taken together, these results suggest that P deficiency inhibits soybean nodule size due to enhancement of malate synthesis, which is regulated by GmMDH12 transcripts.

Calcium carbonate (CaCO3) was successfully synthesized via the decomposition of calcium bicarbonate (Ca(HCO3)2) solution in the presence of polyethylene glycol with different molecular weights (PEG 6000 and PEG 10000). The semi-quantitative characterization by XRD indicates that calcite is the major phase and vaterite and aragonite are the minor phases at different reaction times. SEM images show that the rhombohedral particle is the dominant morphology, together with some rod-like particles, a few spherical particles and some hierarchical structures, such as snow-shaped particles and spherical particles assembled from slice-like particles. SEM and TEM morphological images reveal that the snow-shaped particle consists of three parts, i.e. the hexagon or spherical center, the trunk and the filling. TEM crystal lattice images and electron diffraction patterns indicate that the trunk is composed of large vaterite crystal(s), while the filling consists of small calcite crystals. Based on the above results, the formation mechanism of snow-shaped particles is also proposed in the present work.

The traditional artificial recognition methods for the blast furnace dust composition have several disadvantages, including a great deal of information to dispose, complex operation, and low working efficiency. In this article, a multifeature analysis method based on comprehensive image-processing techniques was proposed to automatically recognize the blast furnace dust composition. First, the artificial recognition and feature analysis, which included image preprocessing, Harris corner feature, Canny edge feature, and Ruffle feature analysis, was designed to build the template image, so that any unknown dust digital image could be tested. Second, the composition of coke, microvariation pulverized coal, vitric, ash, and iron from dust would be distinguished according to their different range of values based on the multifeature analysis. The method is valid for recognizing the blast furnace dust composition automatically, and it is fast and has a high recognition accuracy.

Harsh environment in Blast Furnace (BF) poses a big challenge for metallurgical industrial radar measurement of burden surface for ore and coke. The improved signal processing algorithm enhances the real-time performance. Antenna is specially designed for continuous stable signal acquirement, high temperature resistance and anti-dust ability. The experiment results illustrate that the single radar meets the accuracy requirement of solid bulk material. A new BF Burden Surface Measuring System is developed for real-time BF 3-D imaging. Distributed 6-radars array mounted on the top of 2500 m 3 BF. A virtual 3-D imaging is achieved with a reconstruction algorithm of 6-radars array according to the actual shape of BF. 3-D imaging system with 6-radars array provides an improved technique for intelligent control of burden distribution during BF iron making process.