Development of nitrogen-enriched carbon materials by the subtraction method for formaldehyde adsorption

2021 ◽  
Vol 24 ◽  
pp. 101038
Author(s):  
Changqing Su ◽  
Keke Liu ◽  
Jun Guo ◽  
Weiwu Ma ◽  
Hailong Li ◽  
...  
Keyword(s):  
Carbon Materials ◽  
Subtraction Method ◽  
Formaldehyde Adsorption

Three-dimensional distribution of ribulose-1, 5-bisphosphate carboxylase/oxygemase during the early development of proplastids in dark-grown Euglena cells transferred to an inorganic medium

1990 ◽  
Vol 48 (3) ◽  
pp. 906-907
Author(s):  
Tomoko Ehara ◽  
Shuji Sumida ◽  
Tetsuaki Osafune ◽  
Eiji Hase
Keyword(s):  
Cell Suspension ◽  
Euglena Gracilis ◽  
Carbon Materials ◽  
Three Dimensional ◽  
Peripheral Region ◽  
Plastid Development ◽  
Bisphosphate Carboxylase ◽  
Inorganic Medium ◽  
Ribulose 1 ◽  
Dimensional Distribution

As shown previously, Euglena cells grown in Hutner’s medium in the dark without agitation accumulate wax as well as paramylum, and contain proplastids showing no internal structure except for a single prothylakoid existing close to the envelope. When the cells are transferred to an inorganic medium containing ammonium salt and the cell suspension is aerated in the dark, the wax was oxidatively metabolized, providing carbon materials and energy 23 for some dark processes of plastid development. Under these conditions, pyrenoid-like structures (called “pro-pyrenoids”) are formed at the sites adjacent to the prolamel larbodies (PLB) localized in the peripheral region of the proplastid. The single prothylakoid becomes paired with a newly formed prothylakoid, and a part of the paired prothylakoids is extended, with foldings, in to the “propyrenoid”. In this study, we observed a concentration of RuBisCO in the “propyrenoid” of Euglena gracilis strain Z using immunoelectron microscopy.

Multiple vehicles detection and tracking for intelligent transport systems using machine learning approaches

2019 ◽  
Vol 70 (3) ◽  
pp. 214-224
Author(s):  
Bui Ngoc Dung ◽  
Manh Dzung Lai ◽  
Tran Vu Hieu ◽  
Nguyen Binh T. H.
Keyword(s):  
Machine Learning ◽  
Gaussian Mixture ◽  
Research Field ◽  
Transport Systems ◽  
Learning Approaches ◽  
Subtraction Method ◽  
Intelligent Transport Systems ◽  
Intelligent Transport ◽  
Detection And Tracking ◽  
Multiple Vehicles

Video surveillance is emerging research field of intelligent transport systems. This paper presents some techniques which use machine learning and computer vision in vehicles detection and tracking. Firstly the machine learning approaches using Haar-like features and Ada-Boost algorithm for vehicle detection are presented. Secondly approaches to detect vehicles using the background subtraction method based on Gaussian Mixture Model and to track vehicles using optical flow and multiple Kalman filters were given. The method takes advantages of distinguish and tracking multiple vehicles individually. The experimental results demonstrate high accurately of the method.

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