scholarly journals Self-assembly cloning: a rapid construction method for recombinant molecules from multiple fragments

BioTechniques ◽  
2017 ◽  
Vol 62 (1) ◽  
Author(s):  
Akira Matsumoto ◽  
Taichi Q. Itoh
2022 ◽  
Vol 355 ◽  
pp. 02029
Author(s):  
Yimin Du ◽  
Lingling Shi ◽  
Xiang Zhai ◽  
Hanqing Gong ◽  
Zhijing Zhang

The actual product assembly process mainly relies on manual assembly by workers, and the personal experience of workers is difficult to effectively reuse. Ontology as a knowledge management and expression tool is gradually applied in the field of assembly. However, the manual construction of the ontology is time-consuming and labor-intensive, and the automatic construction of the ontology requires a large number of corpora for training, both of which are difficult to obtain a good assembly case ontology. This paper proposes a method in which automatically extracts relevant knowledge from case assembly process files to generates case database and integrates ontology framework of assembly domain to construct ontology. It shows that the accuracy can be guaranteed on the basis of the rapid construction of case ontology. The feasibility of this method is proved by a practical case.


Author(s):  
Mohsen Daghooghi ◽  
Iman Borazjani ◽  
M. Amin Karami ◽  
Ehsan Tarkesh Esfahani

This paper presents self-propelled swimming simulations of a smart foldable structure capable of swimming and self-assembly for rescue or rapid construction missions, e.g., making temporary bridges. The open configuration of the robot is like a wide cross, which undulates like an eel to swim to a given location. Micro Fiber Composites (MFCs) attached to the surface of the foldable robot actuate the surfaces for swimming purpose. Once the robot arrives at the desired locations shape memory alloys will be activated to fold the robot to a box. To optimize the kinematics of the robot to achieve either highest speed or maximize efficiency during locomotion. self-propelled swimming simulations of the robot was carried out by varying two kinematic parameters: the body motion wavelength and the amplitude. The simulations shows that to achieve higher speed, higher wavelengths are more desirable, e.g., wavelength of 0.95L achieved 15% higher swimming speed relative to 0.65L (L is the swimmer’s length). In contrast, to achieve higher efficiency, lower wavelengths (0.65L) and higher undulation amplitude (0.15L) was 14% more efficient than the other swimmer with wavelength 0.95L and amplitude 0.1L.


2017 ◽  
Vol 55 (10) ◽  
pp. 894-899
Author(s):  
S. Tomiyama ◽  
M. Imashioya ◽  
M. Yoshikawa ◽  
H. Ikeya

2014 ◽  
Vol 721 ◽  
pp. 299-302
Author(s):  
Chen Hua Lu ◽  
Meng Jun Song

In order to study how to solve the serial robot kinematics quickly, so we transformed the kinematics coordinate system by Y axis, and the computed results show that transforming the kinematics coordinate system by Y axis could solve the kinematic model quickly and efficiently; the computed results suggest that constructing the redundant coordinate system and transforming the kinematics coordinate system by Y axis could solve the serial robotic kinematics efficiently.


2021 ◽  
Author(s):  
Samuel Schaffter ◽  
Kuan-Lin Chen ◽  
Jackson O'Brien ◽  
Madeline Noble ◽  
Arvind Murugan ◽  
...  

Abstract Engineered far-from-equilibrium synthetic chemical networks that pulse or switch states in response to environmental signals could precisely regulate the kinetics of chemical synthesis or self-assembly pathways. Currently, such networks must be extensively tuned to compensate for the different activities of and unintended reactions between different network chemical elements. Elements with standardized performance would allow rapid construction of networks with designed functions. Here we develop standardized excitable chemical elements, termed genelets, and use them to construct complex in vitro transcriptional networks. We develop a protocol for identifying >15 interchangeable genelet regulatory elements with uniform performance and minimal crosstalk. These elements can be combined to engineer feedforward and feedback modules whose dynamics are predicted by a simple kinetic model. We show modules can be rationally integrated and reorganized into networks that produce tunable temporal pulses and act as multi-state switchable memories. Standardized genelet elements, and the workflow to identify more, should make engineering complex far-from-equilibrium chemical dynamics routine.


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