scholarly journals Nonorthogonal Aerial Optoelectronic Platform Based on Triaxial and Control Method Designed for Image Sensors

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 10
Author(s):  
Quanchao Li ◽  
Shuyan Xu ◽  
Yulei Xu ◽  
Lei Li ◽  
Liu Zhang
Keyword(s):  
Optical Sensors ◽  
Control Method ◽  
Three Dimensional ◽  
Voice Coil Motor ◽  
Image Sensor ◽  
Dimensional Structure ◽  
Internal Space ◽  
Drive Control ◽  
The Stability ◽  
Better Than

A traditional aerial optoelectronic platform consists of inside and outside multilayer gimbals, while an internal gimbal and drive components occupy the internal space where optical sensors are located. In order to improve the replaceability of optical sensors and to increase their available space, this paper introduces a nonorthogonal aerial optoelectronic platform based on three axes; we carried out research on its drive control method. A three-dimensional structure of an aerial optoelectronic platform was designed. A noncontact drive of a linear voice coil motor was introduced, and a drive control scheme of a proportional integral and a disturbance observer was adopted. Finally, simulations and experiments were carried out. Results showed that the aerial optoelectronic platform could effectively release three times the image sensor space, and the servo bandwidth was 60.2 Hz, which was much better than that of traditional two-axis and four-gimbal platforms. The stability accuracy of the system reached 4.9958 micron rad, which was obviously better than that of traditional gimbals. This paper provides a reference for the design of new optoelectronic platforms.

scholarly journals BLASTing away preconceptions in crystallization trials

2019 ◽  
Vol 75 (3) ◽  
pp. 184-192 ◽  
Author(s):  
Gabriel Jan Abrahams ◽  
Janet Newman
Keyword(s):  
Protein Data Bank ◽  
Sequence Similarity ◽  
Three Dimensional ◽  
Protein Sequences ◽  
Protein Molecule ◽  
Data Bank ◽  
Dimensional Structure ◽  
Critical Step ◽  
Quantitative Verification ◽  
Better Than

Crystallization is in many cases a critical step for solving the three-dimensional structure of a protein molecule. Determining which set of chemicals to use in the initial screen is typically agnostic of the protein under investigation; however, crystallization efficiency could potentially be improved if this were not the case. Previous work has assumed that sequence similarity may provide useful information about appropriate crystallization cocktails; however, the authors are not aware of any quantitative verification of this assumption. This research investigates whether, given current information, one can detect any correlation between sequence similarity and crystallization cocktails. BLAST was used to quantitate the similarity between protein sequences in the Protein Data Bank, and this was compared with three estimations of the chemical similarities of the respective crystallization cocktails. No correlation was detected between proteins of similar (but not identical) sequence and their crystallization cocktails, suggesting that methods of determining screens based on this assumption are unlikely to result in screens that are better than those currently in use.

Protein intrachain contact prediction with most interacting residues (MIR)

2014 ◽  
Vol 10 (4) ◽  
Author(s):  
Ruben Acuña ◽  
Zoé Lacroix ◽  
Nikolaos Papandreou ◽  
Jacques Chomilier
Keyword(s):  
Structural Changes ◽  
Hydrophobic Interactions ◽  
Three Dimensional ◽  
Accessible Surface Area ◽  
Dimensional Structure ◽  
Closed Loops ◽  
Folding Process ◽  
Folding Nucleus ◽  
Accessible Surface ◽  
The Stability

AbstractThe transition state ensemble during the folding process of globular proteins occurs when a sufficient number of intrachain contacts are formed, mainly, but not exclusively, due to hydrophobic interactions. These contacts are related to the folding nucleus, and they contribute to the stability of the native structure, although they may disappear after the energetic barrier of transition states has been passed. A number of structure and sequence analyses, as well as protein engineering studies, have shown that the signature of the folding nucleus is surprisingly present in the native three-dimensional structure, in the form of closed loops, and also in the early folding events. These findings support the idea that the residues of the folding nucleus become buried in the very first folding events, therefore helping the formation of closed loops that act as anchor structures, speed up the process, and overcome the Levinthal paradox. We present here a review of an algorithm intended to simulate in a discrete space the early steps of the folding process. It is based on a Monte Carlo simulation where perturbations, or moves, are randomly applied to residues within a sequence. In contrast with many technically similar approaches, this model does not intend to fold the protein but to calculate the number of non-covalent neighbors of each residue, during the early steps of the folding process. Amino acids along the sequence are categorized as most interacting residues (MIRs) or least interacting residues. The MIR method can be applied under a variety of circumstances. In the cases tested thus far, MIR has successfully identified the exact residue whose mutation causes a switch in conformation. This follows with the idea that MIR identifies residues that are important in the folding process. Most MIR positions correspond to hydrophobic residues; correspondingly, MIRs have zero or very low accessible surface area. Alongside the review of the MIR method, we present a new postprocessing method called smoothed MIR (SMIR), which refines the original MIR method by exploiting the knowledge of residue hydrophobicity. We review known results and present new ones, focusing on the ability of MIR to predict structural changes, secondary structure, and the improved precision with the SMIR method.

The Study of Optimal Fuzzy PID-Smith Control Based on Genetic Algorithm

2013 ◽  
Vol 313-314 ◽  
pp. 448-452
Author(s):  
Dian Ting Liu ◽  
Hai Xia Li
Keyword(s):  
Genetic Algorithm ◽  
Simulation Model ◽  
Control Method ◽  
Order System ◽  
Membership Functions ◽  
Fuzzy Pid ◽  
Improved Genetic Algorithm ◽  
Simulation Results ◽  
The Stability ◽  
Better Than

In this paper, the improved genetic algorithm is applied to optimize the quantization factors and the scaling factors of fuzzy control, and the optimized rule table and membership functions is obtained according to certain performances. Then a kind of optimal fuzzy PID-Smith control method based on genetic algorithm is proposed and its simulation model is built in this paper, a second-order system is simulated and analyzed. The results show that requirements of deterministic performances of the new control method are better than the conventional methods through the simulation results in the stability, rapidity and robustness.

Stability Control and Simulation of Wheel-Legged Mobile Robot in Mechanical Engineering

2013 ◽  
Vol 644 ◽  
pp. 123-128
Author(s):  
Ling Yu Sun ◽  
Jian Hua Zhang ◽  
Xiao Jun Zhang
Keyword(s):  
Mobile Robot ◽  
Pid Control ◽  
Control Method ◽  
Three Dimensional ◽  
Stability Domain ◽  
Stability Control ◽  
Terrestrial Environment ◽  
The Stability ◽  
Adaptive Pid Control ◽  
Fuzzy Adaptive

The wheel-legged mobile robot in a complex three-dimensional environment has strong through capacity .Study is very critical for the stability of the control of their body systems. In this paper , based on analysis of the structure of wheel-legged mobile robot designed, the stability is evaluated by the use of (Effective Mass Center) EMC , and the stability domain is established accordingly. A fuzzy adaptive PID control method is created , and verified by ADAMS and MATLAB co-simulation . Simulation results show that the robot in different terrestrial environment, can maintain good stability.

scholarly journals Nanoparticles Mediated Protein Stability in Comparison with Osmolytes: in vivo Approach

2021 ◽  
Vol 33 (6) ◽  
pp. 1433-1438
Author(s):  
R. Verma ◽  
N. Singh ◽  
P. Chaudhuri (Chattopadhyay)
Keyword(s):  
Gold Nanoparticles ◽  
Dihydrofolate Reductase ◽  
Three Dimensional ◽  
Cellular Level ◽  
Dimensional Structure ◽  
Important Group ◽  
Unfolded State ◽  
The Status ◽  
The Stability

The native three-dimensional structure of protein is quite unstable under critical destabilizing conditions. In order to enhance the stability and activity for a proper folded environment of a protein, many stabilizing materials are added such as nanoparticles and osmolytes to an unfolded state of protein. Osmolytes are the important group of molecules which are engaged by the cell as an adaption in the severe conditions. In this communication, a comparative in vivo study is reported for imparting the status of stability and folding ability of zebrafish dihydrofolate reductase (zDHFR) protein with gold nanoparticles and various osmolytes (glycerol, glucose and betain). Present observations revealed that the interaction of gold nanoparticles (AuNPs) with bacteria at the cellular level helps in maintaining the stability of protein more effectively than osmolytes which could be used for many biological and pharmacological approaches although glycerol as an osmolyte also stabilizes the protein at a significant level.

scholarly journals SE-OnionNet: A Convolution Neural Network for Protein–Ligand Binding Affinity Prediction

2021 ◽  
Vol 11 ◽  
Author(s):  
Shudong Wang ◽  
Dayan Liu ◽  
Mao Ding ◽  
Zhenzhen Du ◽  
Yue Zhong ◽  
...  
Keyword(s):  
Neural Network ◽  
Binding Affinity ◽  
Three Dimensional ◽  
Model Performance ◽  
Protein Molecule ◽  
Stochastic Gradient Descent ◽  
Dimensional Structure ◽  
Scoring Functions ◽  
Ligand Complex ◽  
The Stability

Deep learning methods, which can predict the binding affinity of a drug–target protein interaction, reduce the time and cost of drug discovery. In this study, we propose a novel deep convolutional neural network called SE-OnionNet, with two squeeze-and-excitation (SE) modules, to computationally predict the binding affinity of a protein–ligand complex. The OnionNet is used to extract a feature map from the three-dimensional structure of a protein–drug molecular complex. The SE module is added to the second and third convolutional layers to improve the non-linear expression of the network to improve model performance. Three different optimizers, stochastic gradient descent (SGD), Adam, and Adagrad, were also used to improve the performance of the model. A majority of protein–molecule complexes were used for training, and the comparative assessment of scoring functions (CASF-2016) was used as the benchmark. Experimental results show that our model performs better than OnionNet, Pafnucy, and AutoDock Vina. Finally, we chose the macrophage migration inhibitor factor (PDB ID: 6cbg) to test the stability and robustness of the model. We found that the prediction results were not affected by the docking position, and thus, our model is of acceptable robustness.

scholarly journals A Barycenter Control Method for the Bioinspired Forest Chassis Robot on Slope

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Tingting Sui ◽  
Jinhao Liu ◽  
Jianli Wang ◽  
Jianting Zhang
Keyword(s):  
Plantar Pressure ◽  
Control Method ◽  
Vertical Direction ◽  
Vertical Displacement ◽  
Kinematics Simulation ◽  
Standard Normal ◽  
Adjustable Mechanism ◽  
The Stability ◽  
The Relationship ◽  
Better Than

To improve the stability of forestry chassis on the slope, a chassis-installed barycenter adjustable mechanism (BAM) is designed, and the control method of the counterweight is proposed to make the chassis barycenter move suitably to achieve the design purpose. The kinematic analysis of BAM is carried out, and the relationship between the translation, rotation, and vertical displacement of counterweight and the chassis barycenter is calculated. Furthermore, the variation curves obtained in Matlab show the barycenter can translate 100 mm, rotate from 0 to 360 degrees, and lower about 180 mm in the vertical direction. Adams is adopted to complete the kinematics simulation of the chassis, indicating that the control method can effectively adjust the barycenter position. Finally, experiments are carried out under slope conditions to analyze chassis stability by testing plantar pressure. The results show that forest chassis using the barycenter control method helps keep stable on the slope of 15 degrees, much better than standard normal chassis.

scholarly journals Folding membrane proteins by deep transfer learning

2017 ◽  
Author(s):  
Sheng Wang ◽  
Zhen Li ◽  
Yizhou Yu ◽  
Jinbo Xu
Keyword(s):  
Membrane Proteins ◽  
Transfer Learning ◽  
Prediction Accuracy ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Blind Test ◽  
Distance Restraints ◽  
Dimensional Models ◽  
Three Dimensional Models ◽  
Better Than

SummaryComputational elucidation of membrane protein (MP) structures is challenging partially due to lack of sufficient solved structures for homology modeling. Here we describe a high-throughput deep transfer learning method that first predicts MP contacts by learning from non-membrane proteins (non-MPs) and then predicting three-dimensional structure models using the predicted contacts as distance restraints. Tested on 510 non-redundant MPs, our method has contact prediction accuracy at least 0.18 better than existing methods, predicts correct folds for 218 MPs (TMscore>0.6), and generates three-dimensional models with RMSD less than 4Å and 5Å for 57 and 108 MPs, respectively. A rigorous blind test in the continuous automated model evaluation (CAMEO) project shows that our method predicted high-resolution three-dimensional models for two recent test MPs of 210 residues with RMSD ∼2Å. We estimated that our method could predict correct folds for 1,345–1,871 reviewed human multi-pass MPs including a few hundred new folds, which shall facilitate the discovery of drugs targeting at membrane proteins.

scholarly journals Structure elucidation and docking analysis of 5M mutant of T1 lipase Geobacillus zalihae

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0251751
Author(s):  
Siti Nor Hasmah Ishak ◽  
Nor Hafizah Ahmad Kamarudin ◽  
Mohd Shukuri Mohamad Ali ◽  
Adam Thean Chor Leow ◽  
Fairolniza Mohd Shariff ◽  
...  
Keyword(s):  
Amino Acids ◽  
Hydrogen Bonds ◽  
Three Dimensional ◽  
Substrate Preference ◽  
Dynamics Simulation ◽  
Dimensional Structure ◽  
Docking Analysis ◽  
Three Dimensional Structure ◽  
Ion Interactions ◽  
The Stability

5M mutant lipase was derived through cumulative mutagenesis of amino acid residues (D43E/T118N/E226D/E250L/N304E) of T1 lipase from Geobacillus zalihae. A previous study revealed that cumulative mutations in 5M mutant lipase resulted in decreased thermostability compared to wild-type T1 lipase. Multiple amino acids substitution might cause structural destabilization due to negative cooperation. Hence, the three-dimensional structure of 5M mutant lipase was elucidated to determine the evolution in structural elements caused by amino acids substitution. A suitable crystal for X-ray diffraction was obtained from an optimized formulation containing 0.5 M sodium cacodylate trihydrate, 0.4 M sodium citrate tribasic pH 6.4 and 0.2 M sodium chloride with 2.5 mg/mL protein concentration. The three-dimensional structure of 5M mutant lipase was solved at 2.64 Å with two molecules per asymmetric unit. The detailed analysis of the structure revealed that there was a decrease in the number of molecular interactions, including hydrogen bonds and ion interactions, which are important in maintaining the stability of lipase. This study facilitates understanding of and highlights the importance of hydrogen bonds and ion interactions towards protein stability. Substrate specificity and docking analysis on the open structure of 5M mutant lipase revealed changes in substrate preference. The molecular dynamics simulation of 5M-substrates complexes validated the substrate preference of 5M lipase towards long-chain p-nitrophenyl–esters.

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