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Evaluation of First Reaction to Neoadjuvant Wide spread Treatments within Triple-Negative Breast Cancer Using Amide Proton Transfer-weighted Compound Exchange Saturation Move MRI: An airplane pilot Study.
Herein, the flatband of a W1N2 crystal is theoretically investigated. It is revealed that the flatband can be well-described by a tight-binding model of the N12 skeleton, where the dispersion of the flatband is governed by both the ppσ bonding strength (Vppσ) and the ppπ bonding strength (Vppπ) between the nearest-neighbor N atoms. It is also found that the proper strength of the ppπ bonding between neighboring N atoms plays a prime role in the formation of the flatband. In addition, when the compound is doped with holes, the electrons at the flatband are fully polarized, showing a ferromagnetic character. This behavior has a weak correlation with the on-site Coulomb interaction U. Moreover, several three-dimensional compounds possessing flatbands in the whole k space are predicted.In this article, we implement a recently developed non-equilibrium chemical kinetics model [N. Singh and T. Schwartzentruber, J. Chem. Phys. 152, 224302 (2020)] based on ab initio simulation data and perform verification studies. Direct molecular simulation data are used to verify the predictive capabilities of the model. Using the model, dominant physics, such as the need for a rotational energy equation, and the quantitative role of non-Boltzmann effects are identified. Based on the analysis and reasonable assumptions, a simplified model for implementation into large-scale computational fluid dynamic simulations is proposed. Without incurring additional computational cost, the model can be used in existing flow solvers to analyze hypersonic flows.Nucleation during solidification in multi-component alloys is a complex process that comprises competition between different crystalline phases as well as chemical composition and ordering. Here, we combine transition interface sampling with an extensive committor analysis to investigate the atomistic mechanisms during the initial stages of nucleation in Ni3Al. The formation and growth of crystalline clusters from the melt are strongly influenced by the interplay between three descriptors the size, crystallinity, and chemical short-range order of the emerging nuclei. We demonstrate that it is essential to include all three features in a multi-dimensional reaction coordinate to correctly describe the nucleation mechanism, where, in particular, the chemical short-range order plays a crucial role in the stability of small clusters. The necessity of identifying multi-dimensional reaction coordinates is expected to be of key importance for the atomistic characterization of nucleation processes in complex, multi-component systems.The nonlinear optical properties of hybrid systems composed of a silver nanosphere and an open-ended finite-sized armchair single-walled carbon nanotube (SWCNT) are systematically investigated by the hybrid time-dependent Hartree-Fock (TDHF)/finite difference time domain (FDTD) approach, which combines the real-time TDHF approach for the molecular electronic dynamics with the classical computational electrodynamics approach, the FDTD, for solving Maxwell's equations. The high order harmonic generation (HHG) spectra of SWCNTs are studied as a function of the intensity (I0) and frequency (ω0) of the incident field, and SWCNTs length as well. It is found that the near field generated by a Ag nanoparticle has an overall enhancement to the molecular HHG in all the energy range, and it extends the HHG spectra to high energy. The inhomogeneity of the near field results in the appearance of even-order harmonics, and their corresponding spectral intensities are sensitive to ω0, therefore the near field's gradient. When ω0 is far away from the frequency of plasmon resonance of the silver nanosphere (ωc), the interference between the incident and scattering light beams extends the spectral range and makes the HHG spectra more sensitive to I0, while at ω0 = ωc, the impact of the interference on the spectra is negligible.For particles diffusing in a potential, detailed balance guarantees the absence of net fluxes at equilibrium. Here, we show that the conventional detailed balance condition is a special case of a more general relation that works when the diffusion occurs in the presence of a distributed sink that eventually traps the particle. We use this relation to study the lifetime distribution of particles that start and are trapped at specified initial and final points. It turns out that when the sink strength at the initial point is nonzero, the initial and final points are interchangeable, i.e., the distribution is independent of which of the two points is initial and which is final. In other words, this conditional trapping time distribution possesses forward-backward symmetry.Over the last few decades, computational tools have been instrumental in understanding the behavior of materials at the nano-meter length scale. Until recently, these tools have been dominated by two levels of theory quantum mechanics (QM) based methods and semi-empirical/classical methods. The former are time-intensive but accurate and versatile, while the latter methods are fast but are significantly limited in veracity, versatility, and transferability. Recently, machine learning (ML) methods have shown the potential to bridge the gap between these two chasms due to their (i) low cost, (ii) accuracy, (iii) transferability, and (iv) ability to be iteratively improved. In this work, we further extend the scope of ML for atomistic simulations by capturing the temperature dependence of the mechanical and structural properties of bulk platinum through molecular dynamics simulations. GX15070 We compare our results directly with experiments, showcasing that ML methods can be used to accurately capture large-scale materials phenomena that are out of reach of QM calculations. We also compare our predictions with those of a reliable embedded atom method potential. We conclude this work by discussing how ML methods can be used to push the boundaries of nano-scale materials research by bridging the gap between QM and experimental methods.Molecular dynamics (MD) simulations of explicit representations of fluorescent dyes attached via a linker to a protein allow, e.g., probing commonly used approximations for dye localization and/or orientation or modeling Förster resonance energy transfer. However, setting up and performing such MD simulations with the AMBER suite of biomolecular simulation programs has remained challenging due to the unavailability of an easy-to-use set of parameters within AMBER. Here, we adapted the AMBER-DYES parameter set derived by Graen et al. [J. Chem. Theory Comput. 10, 5505 (2014)] into "AMBER-DYES in AMBER" to generate a force field applicable within AMBER for commonly used fluorescent dyes and linkers attached to a protein. In particular, the computationally efficient graphics processing unit (GPU) implementation of the AMBER MD engine can now be exploited to overcome sampling issues of dye movements. The implementation is compatible with state-of-the-art force fields such as GAFF, GAFF2, ff99SB, ff14SB, lipid17, and GLYCAM_06j, which allows simulating post-translationally modified proteins and/or protein-ligand complexes and/or proteins in membrane environments.
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