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Biotin is an important factor affecting the performance of glutamate fermentation by biotin auxotrophic Corynebacterium glutamicum and glutamate is over-produced only when initial biotin content is controlled at suitable levels or initial biotin is excessive but with Tween 40 addition during fermentation. The transcription levels of key enzymes at pyruvate, isocitrate and α-ketoglutarate metabolic nodes, as well as transport protein (TP) of glutamate were investigated under the conditions of varied biotin contents and Tween 40 supplementation. When biotin was insufficient, the genes encoding key enzymes and TP were down-regulated in the early production phase, in particular, the transcription level of isocitrate dehydrogenase (ICDH) which was only 2% of that of control. Although the cells' morphology transformation and TP level were not affected, low transcription level of ICDH led to lower final glutamate concentration (64 g/L). When biotin was excessive, the transcription levels of key enzymes were at comparable levels as those of control with ICDH as an exception, which was only 3-22% of control level throughout production phase. In this case, little intracellular glutamate accumulation (1.5 mg/g DCW) and impermeable membrane resulted in non glutamate secretion into broth, even though the quantity of TP was more than 10-folds of control level. Addition of Tween 40 when biotin was excessive stimulated the expression of all key enzymes and TP, intracellular glutamate content was much higher (10-12 mg/g DCW), and final glutamate concentration reached control level (75-80 g/L). Hence, the membrane alteration and TP were indispensable in glutamate secretion. Biotin and Tween 40 influenced the expression level of ICDH and glutamate efflux, thereby influencing glutamate production.

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Recent advances in computer science and electronics have greatly expanded the capabilities of unmanned aerial vehicles (UAV) in both defense and civil applications, such as moving ground object tracking. Due to the uncertainties of the application environments and objects’ motion, it is difficult to maintain the tracked object always within the sensor coverage area by using a single UAV. Hence, it is necessary to deploy a group of UAVs to improve the robustness of the tracking. This paper investigates the problem of tracking ground moving objects with a group of UAVs using gimbaled sensors under flight dynamic and collision-free constraints. The optimal cooperative tracking path planning problem is solved using an evolutionary optimization technique based on the framework of chemical reaction optimization (CRO). The efficiency of the proposed method was demonstrated through a series of comparative simulations. The results show that the cooperative tracking paths determined by the newly developed method allows for longer sensor coverage time under flight dynamic restrictions and safety conditions.

The knowledge of DNA-binding proteins would help to understand the functions of proteins better in cellular biological processes. Research on the prediction of DNA-binding proteins can promote the research of drug proteins and computer acidified drugs. In recent years, methods based on machine learning are usually used to predict proteins. Although great predicted performance can be achieved via current methods, researchers still need to invest more research in terms of the improvement of predicted performance. In this study, the prediction of DNA-binding proteins is studied from the perspective of evolutionary information and the support vector machine method. One machine learning model for predicting DNA-binding proteins based on evolutionary features by using Chou’s 5-step rule is put forward. The results show that great predicted performance is obtained on benchmark dataset PDB1075 and independent dataset PDB186, achieving the accuracy of 86.05% and 75.30%, respectively. Thus, the method proposed is comparable to a certain degree, and it may work even better than other methods to some extent.