| Title | From A to B (2015) |
| File Name | from-a-to-b_qx2db.avi |
| Launched | 6 years 1 month 21 days ago |
| File Size | 921 MegaByte |
| Classification | SDDS 1440p DVDrip |
| Durations | 02h 07 min |
Description
Three estranged childhood friends (Omar, Ramy, Jay), travel on a road trip from Abu Dhabi to Beirut in memory of their lost friend. If what happens en route doesn't make them crazy, it might just bring them closer.
From A to B (2015)
Genre: Adventure, Comedy, Drama
Cast: Fahad Albutairi, Shadi Alfons, Fadi Rifaai, Yosra El Lozy, Maha Abou Ouf
Crew: Paul Baboudjian, Ali F. Mostafa, Ali F. Mostafa, Ali F. Mostafa, Mohamed Hefzy
Release: 2015-01-08
Budget: $2,433,076
Revenue: $80,520,657
Excavating Machine Operator: Giovanni O'Hara DDS
Human Resources Specialist: Dr. Dock Sporer DVM
Furnace Operator: Gay Lowe
Aircraft Launch and Recovery Officer: Ms. Arvilla Little PhD
Photographic Restorer: Vincenza Welch II
Jeweler: Dr. Marquis Abernathy
Director Of Marketing: Carlotta Deckow
User Experience Researcher: Georgianna Bechtelar
Electrical Parts Reconditioner: Kylee Schimmel IV
Aircraft Mechanics OR Aircraft Service Technician: Danial Murray
TSA: Mr. Gerhard Eichmann
Video Editor: Jordon Casper
Animal Scientist: Dr. Salvador Pfannerstill IV
Cast: Fahad Albutairi, Shadi Alfons, Fadi Rifaai, Yosra El Lozy, Maha Abou Ouf
Crew: Paul Baboudjian, Ali F. Mostafa, Ali F. Mostafa, Ali F. Mostafa, Mohamed Hefzy
Release: 2015-01-08
Budget: $2,433,076
Revenue: $80,520,657
Excavating Machine Operator: Giovanni O'Hara DDS
Human Resources Specialist: Dr. Dock Sporer DVM
Furnace Operator: Gay Lowe
Aircraft Launch and Recovery Officer: Ms. Arvilla Little PhD
Photographic Restorer: Vincenza Welch II
Jeweler: Dr. Marquis Abernathy
Director Of Marketing: Carlotta Deckow
User Experience Researcher: Georgianna Bechtelar
Electrical Parts Reconditioner: Kylee Schimmel IV
Aircraft Mechanics OR Aircraft Service Technician: Danial Murray
TSA: Mr. Gerhard Eichmann
Video Editor: Jordon Casper
Animal Scientist: Dr. Salvador Pfannerstill IV
Calculating curly arrows from ab initio wavefunctions | Nature ....
Computing Bulk Phase Raman Optical Activity Spectra from ab initio Molecular Dynamics Simulations.
We report on ab initio calculations of the two-dimensional systems $\textMoS_2$ and $\textNbSe_2$, which recently were synthesized. We find that two-dimensional $\textMoS_2$ is a semiconductor with a gap which is rather close to that of the three-dimensional analog, and that $\textNbSe_2$ is a metal, which is similar to the three-dimensional analog of this compound. We further computed the electronic structure of the two-dimensional hexagonal (graphene-like) lattices of Si and Ge and compared them with the electronic structure of graphene. It is found that the properties related to the Dirac cone do not appear in the case of two-dimensional hexagonal germanium, which is metallic, contrary to two-dimensional hexagonal silicon, also known as silicene, which has an electronic structure very similar to the one of graphene, making them possibly equivalent..
Apr 3, 2018 ... In addition, we propose methods for quantifying the statistical variance of the diffusivity and ionic conductivity from the number of diffusion events ....
Statistical variances of diffusional properties from ab initio molecular ....
Electronic structure of two-dimensional crystals from ab initio theory.
Silicon Liquid Structure and Crystal Nucleation from Ab Initio Deep Metadynamics.
The nicotinic acetylcholine receptor is the prototype ligand-gated ion channel. A number of aromatic amino acids have been identified as contributing to the agonist binding site, suggesting that cation-pi interactions may be involved in binding the quaternary ammonium group of the agonist, acetylcho ….
We present our novel methodology for computing Raman optical activity (ROA) spectra of liquid systems from ab initio molecular dynamics (AIMD) simulations. The method is built upon the recent developments to obtain magnetic dipole moments from AIMD and to integrate molecular properties by using radical Voronoi tessellation. These techniques are used to calculate optical activity tensors for large and complex periodic bulk phase systems. Only AIMD simulations are required as input, and no time-consuming perturbation theory is involved. The approach relies only on the total electron density in each time step and can readily be combined with a wide range of electronic structure methods. To the best of our knowledge, these are the first computed ROA spectra for a periodic bulk phase system. As an example, the experimental ROA spectrum of liquid (R)-propylene oxide is reproduced very well..
Notice of Exemption from AB 1482 (Separately Alienable Exemption under AB 1482) – California Apartment Association.
Machine Learning Force Field Parameters from Ab Initio Data.
Types of a,b,c when you see "from a.b import c" in a python script ....
Apr 12, 2018 ... Despite being at the heart of chemical thought, the curly arrow notation of reaction mechanisms has been treated with suspicion—the ....
Machine learning (ML) techniques with the genetic algorithm (GA) have been applied to determine a polarizable force field parameters using only ab initio data from quantum mechanics (QM) calculations of molecular clusters at the MP2/6-31G(d,p), DFMP2(fc)/jul-cc-pVDZ, and DFMP2(fc)/jul-cc-pVTZ levels to predict experimental condensed phase properties (, density and heat of vaporization). The performance of this ML/GA approach is demonstrated on 4943 dimer electrostatic potentials and 1250 cluster interaction energies for methanol. Excellent agreement between the training data set from QM calculations and the optimized force field model was achieved. The results were further improved by introducing an offset factor during the machine learning process to compensate for the discrepancy between the QM calculated energy and the energy reproduced by optimized force field, while maintaining the local “shape” of the QM energy surface. Throughout the machine learning process, experimental observables were not i.
Studying the crystallization process of silicon is a challenging task since empirical potentials are not able to reproduce well the properties of both a semiconducting solid and metallic liquid. On the other hand, nucleation is a rare event that occurs in much longer timescales than those achievable by ab initio molecular dynamics. To address this problem, we train a deep neural network potential based on a set of data generated by metadynamics simulations using a classical potential. We show how this is an effective way to collect all the relevant data for the process of interest. In order to efficiently drive the crystallization process, we introduce a new collective variable based on the Debye structure factor. We are able to encode the long-range order information in a local variable which is better suited to describe the nucleation dynamics. The reference energies are then calculated using the strongly constrained and appropriately normed (SCAN) exchange-correlation functional, which is able to get a bet.
from a.b import c. For simplicity, here a is the package (it is basically a folder, though it has some special attributes), is the file name under ....
Alternative metals: From ab initio screening to calibrated narrow line models.
From ab initio quantum mechanics to molecular neurobiology: a cation-pi binding site in the nicotinic receptor - PubMed.
This form contains the essential legal terminology needed to inform your resident that the rental unit is exempt from AB 1482 because it is separately alienable. Specifically, non-corporate single-family homes/condos (residential real property that is alienable separate from the title to any other dwelling unit) are exempt from AB 1482 if (1) the owner is ….
We discuss the selection and assessment of alternative metals by a combination of ab initio computation of electronic properties, experimental resistivity assessments, and calibrated line resistance models. Pt-group metals as well as Nb are identified as the most promising elements, with Ru showing the best combination of material properties and process maturity. An experimental assessment of the resistivity of Ru, Ir, and Co lines down to ~30 nm2 is then used to devise compact models for line and via resistance that can be compared to Cu predictions. The main advantage of alternative metals originates from the possibility for barrierless metallization.
Computing Bulk Phase Raman Optical Activity Spectra from ab initio Molecular Dynamics Simulations.
We report on ab initio calculations of the two-dimensional systems $\textMoS_2$ and $\textNbSe_2$, which recently were synthesized. We find that two-dimensional $\textMoS_2$ is a semiconductor with a gap which is rather close to that of the three-dimensional analog, and that $\textNbSe_2$ is a metal, which is similar to the three-dimensional analog of this compound. We further computed the electronic structure of the two-dimensional hexagonal (graphene-like) lattices of Si and Ge and compared them with the electronic structure of graphene. It is found that the properties related to the Dirac cone do not appear in the case of two-dimensional hexagonal germanium, which is metallic, contrary to two-dimensional hexagonal silicon, also known as silicene, which has an electronic structure very similar to the one of graphene, making them possibly equivalent..
Apr 3, 2018 ... In addition, we propose methods for quantifying the statistical variance of the diffusivity and ionic conductivity from the number of diffusion events ....
Statistical variances of diffusional properties from ab initio molecular ....
Electronic structure of two-dimensional crystals from ab initio theory.
Silicon Liquid Structure and Crystal Nucleation from Ab Initio Deep Metadynamics.
The nicotinic acetylcholine receptor is the prototype ligand-gated ion channel. A number of aromatic amino acids have been identified as contributing to the agonist binding site, suggesting that cation-pi interactions may be involved in binding the quaternary ammonium group of the agonist, acetylcho ….
We present our novel methodology for computing Raman optical activity (ROA) spectra of liquid systems from ab initio molecular dynamics (AIMD) simulations. The method is built upon the recent developments to obtain magnetic dipole moments from AIMD and to integrate molecular properties by using radical Voronoi tessellation. These techniques are used to calculate optical activity tensors for large and complex periodic bulk phase systems. Only AIMD simulations are required as input, and no time-consuming perturbation theory is involved. The approach relies only on the total electron density in each time step and can readily be combined with a wide range of electronic structure methods. To the best of our knowledge, these are the first computed ROA spectra for a periodic bulk phase system. As an example, the experimental ROA spectrum of liquid (R)-propylene oxide is reproduced very well..
Notice of Exemption from AB 1482 (Separately Alienable Exemption under AB 1482) – California Apartment Association.
Machine Learning Force Field Parameters from Ab Initio Data.
Types of a,b,c when you see "from a.b import c" in a python script ....
Apr 12, 2018 ... Despite being at the heart of chemical thought, the curly arrow notation of reaction mechanisms has been treated with suspicion—the ....
Machine learning (ML) techniques with the genetic algorithm (GA) have been applied to determine a polarizable force field parameters using only ab initio data from quantum mechanics (QM) calculations of molecular clusters at the MP2/6-31G(d,p), DFMP2(fc)/jul-cc-pVDZ, and DFMP2(fc)/jul-cc-pVTZ levels to predict experimental condensed phase properties (, density and heat of vaporization). The performance of this ML/GA approach is demonstrated on 4943 dimer electrostatic potentials and 1250 cluster interaction energies for methanol. Excellent agreement between the training data set from QM calculations and the optimized force field model was achieved. The results were further improved by introducing an offset factor during the machine learning process to compensate for the discrepancy between the QM calculated energy and the energy reproduced by optimized force field, while maintaining the local “shape” of the QM energy surface. Throughout the machine learning process, experimental observables were not i.
Studying the crystallization process of silicon is a challenging task since empirical potentials are not able to reproduce well the properties of both a semiconducting solid and metallic liquid. On the other hand, nucleation is a rare event that occurs in much longer timescales than those achievable by ab initio molecular dynamics. To address this problem, we train a deep neural network potential based on a set of data generated by metadynamics simulations using a classical potential. We show how this is an effective way to collect all the relevant data for the process of interest. In order to efficiently drive the crystallization process, we introduce a new collective variable based on the Debye structure factor. We are able to encode the long-range order information in a local variable which is better suited to describe the nucleation dynamics. The reference energies are then calculated using the strongly constrained and appropriately normed (SCAN) exchange-correlation functional, which is able to get a bet.
from a.b import c. For simplicity, here a is the package (it is basically a folder, though it has some special attributes), is the file name under ....
Alternative metals: From ab initio screening to calibrated narrow line models.
From ab initio quantum mechanics to molecular neurobiology: a cation-pi binding site in the nicotinic receptor - PubMed.
This form contains the essential legal terminology needed to inform your resident that the rental unit is exempt from AB 1482 because it is separately alienable. Specifically, non-corporate single-family homes/condos (residential real property that is alienable separate from the title to any other dwelling unit) are exempt from AB 1482 if (1) the owner is ….
We discuss the selection and assessment of alternative metals by a combination of ab initio computation of electronic properties, experimental resistivity assessments, and calibrated line resistance models. Pt-group metals as well as Nb are identified as the most promising elements, with Ru showing the best combination of material properties and process maturity. An experimental assessment of the resistivity of Ru, Ir, and Co lines down to ~30 nm2 is then used to devise compact models for line and via resistance that can be compared to Cu predictions. The main advantage of alternative metals originates from the possibility for barrierless metallization.
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