Malate accumulation has been suggested to balance Al-induced citrate synthesis and efflux in soybean roots. To test this hypothesis, characteristics of Al-induced accumulation and efflux of citrate and malate were compared between two soybean genotypes combining a functional analysis of GmME1 putatively encode a cytosolic NADP-malic enzyme. Similar amounts of citrate were released, and root elongation was equally inhibited before 8 h of Al treatment of Jiyu 70 and Jiyu 62 cultivars. Jiyu 70 began to secrete more citrate and exhibited higher Al resistance than did Jiyu 62 at 12 h. A sustained increase in internal malate and citrate concentrations was observed in Jiyu 70 at 24 h of Al treatment. However, Jiyu 62 decreased its malate concentration at 12 h and its citrate concentration at 24 h of Al treatment. GmME1 localized to the cytoplast and clustered closely with cytosolic malic enzymes AtME2 and SgME1 and was constitutively expressed in the roots. Al treatment induced higher NADP-malic enzyme activities and GmME1 expression levels in Jiyu 70 than in Jiyu 62 within 24 h. Compared with wild-type hairy roots, over-expressing GmME1 in hairy roots (GmME1-OE) produced higher expression levels of GmME1 but did not change the expression patterns of either of the putative citrate transporter genes GmAACT1 and GmFRDL or the malate transporter gene GmALMT1, with or without Al treatment. GmME1-OE showed a higher internal concentration and external efflux of both citrate and malate at 4 h of Al stress. Lighter hematoxylin staining and lower Al contents in root apices of GmME1-OE hairy roots indicated greater Al resistance. Comprehensive experimental results suggest that sustaining Al-induced citrate efflux depends on the malate pool in soybean root apices. GmME1 encodes a cytosolic malic enzyme that contributes to increased internal malate and citrate concentrations and their external efflux to confer higher Al resistance.

Rationally controlled synthesis of transition metal oxide materials for structure-related applications in diverse areas at room temperature and ambient atmosphere remains a challenge. In this article, we propose a facile...

Abstract. With the development of space electronic technology, the space payload operation modes are more and more complex, and manual interpretation is prone to errors for much workload. Generally the space payload's operation modes are reflected by its telemetry data. By analysing the characteristics of the payload telemetry data, it is proposed an automatic analysis method of payload operation modes based on divide-and-conquer clustering. The clustering method combines division and incremental clustering. The principle of the method is introduced and the method is validated using the actual payload telemetry data. Furthermore the improved method is proposed to the problems encountered. Experimental results show that divide-and-conquer clustering method has the feature of calculation simple and classification accurate, when applied to the classification of payload operation modes. Furthermore this method can be applied to the other areas of payload data processing by extending the method.

The fracture surface of con-rod is difficult to be quantitatively described due to its indented macro morphology. Thus, the range of fracture surface defect dimension has no uniform standard. In order to solve this question, 3D software about the digital fracture surface reconstruction was developed by combining the fracture splitting technology of con-rod with reverse engineering, which realized the reproduction of its morphology and completed the real area calculation of the surface. The results show that the fracture surface area processed by fracture splitting is 13.1% larger than that of the plane processed by machining. It represents that the defect dimension range of fracture surface is improved compared to empirical value without reducing the bearing capacity and usability.

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