scholarly journals G-RMSD: Root Mean Square Deviation Based Method for Three-dimensional Molecular Similarity Determination

2020 ◽  
Author(s):  
Tomonori Fukutani ◽  
Kohei Miyazawa ◽  
Satoru Iwata ◽  
Hiroko Satoh
Keyword(s):  
Root Mean Square ◽  
Root Mean Square Deviation ◽  
Molecular Similarity ◽  
Three Dimensional ◽  
Mean Square ◽  
Mean Square Deviation

The Study on Three-Dimensional Roughness of Machined Surface in High Speed Milling of SiCp/Al Composites

2011 ◽  
Vol 188 ◽  
pp. 179-183 ◽  
Author(s):  
Yang Jun Wang ◽  
M. Zhou ◽  
Y.H. Zhao
Keyword(s):  
Root Mean Square ◽  
Root Mean Square Deviation ◽  
High Speed ◽  
Three Dimensional ◽  
Roughness Parameter ◽  
Cutting Parameters ◽  
Mean Square ◽  
Mean Square Deviation ◽  
Machined Surface ◽  
High Speed Milling

For the purpose of investigating the effect on surface micro-topography of cutting parameters in high speed milling of SiCp/Al Composites, the high speed milling experiments were performed .The machined surface was measured by Taylor Hobson roughness tester and OLS3000 Confocal Laser Scanning Microscope. The acquired surface data was dealt with the three-dimensional roughness method. The three-dimensional root-mean-square deviation of the surface Sq and two-dimensional root-mean-square deviation Rq were compared. The effects of cutting parameters on three-dimensional roughness parameter were also investigated. The results showed that both feed rate and depth of cut have a little effect on the value of three-dimensional roughness parameter，and the cutting speed is the main affecting factor.

scholarly journals G-RMSD: Root Mean Square Deviation Based Method for Three-dimensional Molecular Similarity Determination

2020 ◽  
Author(s):  
Tomonori Fukutani, ◽  
kohei Miyazawa ◽  
Satoru Iwata ◽  
Hiroko Satoh
Keyword(s):  
Root Mean Square ◽  
Root Mean Square Deviation ◽  
Three Dimensional ◽  
Valence Bond ◽  
Optimization Method ◽  
Molecular Structures ◽  
Mean Square ◽  
Mean Square Deviation ◽  
Atomic Structures ◽  
Structure Search

<div>We present the Generalized Root Mean Square Deviation (G-RMSD) method. G-RMSD is an optimization method to calculate the minimal RMSD value of two atomic structures by optimal superimposition. The method is not restricted to systems with an equal number of atoms or a unique atom matching and can handle any type of chemical structure, including transition states and non-valence bond structures. It requires only Cartesian coordinates for the structures, but can also include further information, i.e. atom and bond types. Applications of G-RMSD to the classification of alpha-D-glucose conformers and 3D partial structure search using a dataset containing equilibrium (EQ), dissociation channel (DC), and transition state (TS) structures are demonstrated. We find that G-RMSD allows for a successful classification and mapping for a wide variety of molecular structures.</div><div><br></div>

scholarly journals G-RMSD: Root Mean Square Deviation Based Method for Three-dimensional Molecular Similarity Determination

2020 ◽  
Author(s):  
Tomonori Fukutani, ◽  
kohei Miyazawa ◽  
Satoru Iwata ◽  
Hiroko Satoh
Keyword(s):  
Root Mean Square ◽  
Root Mean Square Deviation ◽  
Three Dimensional ◽  
Valence Bond ◽  
Optimization Method ◽  
Molecular Structures ◽  
Mean Square ◽  
Mean Square Deviation ◽  
Atomic Structures ◽  
Structure Search

<div>We present the Generalized Root Mean Square Deviation (G-RMSD) method. G-RMSD is an optimization method to calculate the minimal RMSD value of two atomic structures by optimal superimposition. The method is not restricted to systems with an equal number of atoms or a unique atom matching and can handle any type of chemical structure, including transition states and non-valence bond structures. It requires only Cartesian coordinates for the structures, but can also include further information, i.e. atom and bond types. Applications of G-RMSD to the classification of alpha-D-glucose conformers and 3D partial structure search using a dataset containing equilibrium (EQ), dissociation channel (DC), and transition state (TS) structures are demonstrated. We find that G-RMSD allows for a successful classification and mapping for a wide variety of molecular structures.</div><div><br></div>

Three-Dimensional Analysis of Nasal Symmetry following Primary Correction of Unilateral Cleft Lip Nasal Deformity

2017 ◽  
Vol 54 (6) ◽  
pp. 715-719 ◽  
Author(s):  
Olivia E. Linden ◽  
Helena O. Taylor ◽  
Sivabalan Vasudavan ◽  
Margaret E. Byrne ◽  
Curtis K. Deutsch ◽  
...  
Keyword(s):  
Root Mean Square ◽  
Root Mean Square Deviation ◽  
Cleft Lip ◽  
Three Dimensional ◽  
Mean Square ◽  
Mean Square Deviation ◽  
Cleft Lip Palate ◽  
And Control ◽  
Tip Rhinoplasty ◽  
Normal Controls

Objective To evaluate nasal symmetry using three-dimensional photogrammetry following primary tip rhinoplasty with or without an internal splint in patients with unilateral complete cleft lip/palate. Design We captured three-dimensional images of patients with unilateral complete cleft lip/palate who underwent nasolabial repair by rotation-advancement of the lip and primary tip rhinoplasty, either with or without an internal resorbable splint, and normal control subjects. We assessed nasal symmetry by identifying the plane of maximum symmetry and the root-mean-square deviation between native and reflected surfaces. Patients/Participants We imaged 38 controls and 38 subjects with repaired unilateral complete cleft lip/palate (20 with, 18 without an internal splint). Results Nasal asymmetry root-mean-square deviation clustered between 0.19 and 0.50 mm (median = 0.24 ± 0.08 mm) for controls; whereas, those with repaired unilateral complete cleft lip/palate ranged from 0.4 to 1.5 mm (median = 0.75 ± 0.40 mm). Although root-mean-square deviation ranges overlapped, patients with repaired unilateral complete cleft lip/palate had significantly greater asymmetry than controls ( P < .001). We found no difference in asymmetry between patients with or without an internal splint ( P = .5). Conclusions Three-dimensional photogrammetry was used to successfully compare symmetry among different patient and control groups. Although “normal” nasal symmetry was attained in some patients following cleft lip/nasal repair, most had persistent asymmetry compared with normal controls. Placement of a resorbable internal splint did not improve symmetry in patients with unilateral complete cleft lip/palate.

scholarly journals GNINA 1.0: molecular docking with deep learning

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Andrew T. McNutt ◽  
Paul Francoeur ◽  
Rishal Aggarwal ◽  
Tomohide Masuda ◽  
Rocco Meli ◽  
...  
Keyword(s):  
Molecular Docking ◽  
Root Mean Square ◽  
Root Mean Square Deviation ◽  
Computational Cost ◽  
Scoring Function ◽  
Binding Pocket ◽  
Protein Docking ◽  
Mean Square ◽  
Mean Square Deviation ◽  
Autodock Vina

AbstractMolecular docking computationally predicts the conformation of a small molecule when binding to a receptor. Scoring functions are a vital piece of any molecular docking pipeline as they determine the fitness of sampled poses. Here we describe and evaluate the 1.0 release of the Gnina docking software, which utilizes an ensemble of convolutional neural networks (CNNs) as a scoring function. We also explore an array of parameter values for Gnina 1.0 to optimize docking performance and computational cost. Docking performance, as evaluated by the percentage of targets where the top pose is better than 2Å root mean square deviation (Top1), is compared to AutoDock Vina scoring when utilizing explicitly defined binding pockets or whole protein docking. Gnina, utilizing a CNN scoring function to rescore the output poses, outperforms AutoDock Vina scoring on redocking and cross-docking tasks when the binding pocket is defined (Top1 increases from 58% to 73% and from 27% to 37%, respectively) and when the whole protein defines the binding pocket (Top1 increases from 31% to 38% and from 12% to 16%, respectively). The derived ensemble of CNNs generalizes to unseen proteins and ligands and produces scores that correlate well with the root mean square deviation to the known binding pose. We provide the 1.0 version of Gnina under an open source license for use as a molecular docking tool at https://github.com/gnina/gnina.

Fast collocation for Moho estimation from GOCE gravity data: the Iran case study

2020 ◽  
Vol 221 (1) ◽  
pp. 651-664
Author(s):  
H Heydarizadeh Shali ◽  
D Sampietro ◽  
A Safari ◽  
M Capponi ◽  
A Bahroudi
Keyword(s):  
Root Mean Square ◽  
Root Mean Square Deviation ◽  
Seismic Data ◽  
Active Faults ◽  
Earth’S Crust ◽  
Arabian Plate ◽  
Moho Depth ◽  
Mean Square ◽  
Mean Square Deviation ◽  
Earth's Crust

SUMMARY The study of the discontinuity between crust and mantle beneath Iran is still an open issue in the geophysical community due to its various tectonic features created by the collision between the Iranian and Arabian Plate. For instance in regions such as Zagros, Alborz or Makran, despite the number of studies performed, both by exploiting gravity or seismic data, the depth of the Moho and also interior structure is still highly uncertain. This is due to the complexity of the crust and to the presence of large short wavelength signals in the Moho depth. GOCE observations are capable and useful products to describe the Earth’s crust structure either at the regional or global scale. Furthermore, it is plausible to retrieve important information regarding the structure of the Earth’s crust by combining the GOCE observations with seismic data and considering additional information. In the current study, we used as observation a grid of second radial derivative of the anomalous gravitational potential computed at an altitude of 221 km by means of the space-wise approach, to study the depth of the Moho. The observations have been reduced for the gravitational effects of topography, bathymetry and sediments. The residual gravity has been inverted accordingly to a simple two-layer model. In particular, this guarantees the uniqueness of the solution of the inverse problem which has been regularized by means of a collocation approach in the frequency domain. Although results of this study show a general good agreement with seismically derived depths with a root mean square deviation of 6 km, there are some discrepancies under the Alborz zone and also Oman sea with a root mean square deviation up 10 km for the former and an average difference of 3 km for the latter. Further comparisons with the natural feature of the study area, for instance, active faults, show that the resulting Moho features can be directly associated with geophysical and tectonic blocks.

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