Narrow Results

Mycobacterium tuberculosis (Mtb), the bacterium responsible for tuberculosis (TB), employs mycolic acids to build its cell wall. This robust structure plays a vital role in protecting the bacterium from external threats and contributes to its resistance against antibiotics. Mycobacterial membrane protein Large 3 (MmpL3), a secondary resistance nodulation division transporter, is essential in mycolic acid biosynthesis, transporting mycolic acid precursors into the periplasm using the proton motive force. Due to its role in bacterial cell wall formation, it is a promising target for new tuberculosis treatments. In this study, starting with 85 known MmPL3 compounds, the artificial intelligence (AI)-assisted tool “Design of Druglike Analogues (DeLA-Drug)” was employed to generate about 15,000 novel molecules. These compounds were then subjected to structure-based high-throughput virtual screening and molecular dynamics (MD) simulations to identify potential novel inhibitors of MmpL3. The binding affinity was obtained by docking the above molecules at the SQ109 binding site in MmPL3, followed by pharmacokinetics and toxicity, which were used to reduce the chemical space. Finally, five ligands were subjected to 100 ns MD simulations to investigate the binding energetics of inhibitors to MmpL3. These compounds demonstrated stable binding and favorable drug-like properties, indicating that they could serve as potential novel inhibitors of MmpL3 for Mtb.

The Piecewise Parabolic Method (PPM) hydrodynamics code and other codes based on the PPM technique have been used extensively for the simulation of astrophysical phenomena. A new version of the PPM hydrodynamics code under development at the Laboratory for Computational Science and Engineering (LCSE) at the University of Minnesota is described. This new code incorporates a version of dynamic local adaptive mesh refinement (AMR) targeted specifically at improving the treatment of shocks and contact discontinuities. This AMR technique is not intended to increase grid resolution in entire regions of the problem for which standard techniques of nonuniform grids and simple grid motion are adequate. Because the AMR is targeted at surfaces within a flow that can develop complex shapes, a cell-by-cell approach to the grid refinement is adopted in order to minimize the number of refined grid cells, with the hope of controlling the computational cost. As a result of this approach, the number of refined cells needed across a given shock or captured contact discontinuity is modest (< 10). Because the PPM method is very complex, ordinarily its wide difference stencil demands that a relatively large number of extra grid cells need to be added to each end of a grid strip, even when adapting to a thin feature of the flow. To avoid the work associated in handling these extra cells, only to conveniently produce valid data in the thin strip of actual interest, we have used intermediate results of the coarse grid calculation in order to eliminate the need for all but two of these extra cells at each end of the refined grid strip. The benefits of this approach will be described through sample results in 2D, and the method for handling the boundaries of the refined grid strips efficiently will be discussed. The data structures in this method are being carefully designed to permit efficient implementation of the algorithm on clusters of shared memory machines, with automatic dynamic balancing of computational loads over the cluster members.

In this paper the two-dimensional Euler equations, with a simple chemical reaction model, are used as the governing equations for the detonation problem. The spatial derivatives are evaluated using the fifth-order WENO scheme, and the third-order TVD Runge-Kutta method is employed for the temporal derivative. The characteristics of the two-dimensional detonation in an argon-diluted mixture of hydrogen and oxygen are investigated using Adaptive Mesh Refinement (AMR) method. From computational accuracy point of view, AMR enables the detonation front to be clearer than the method with basic meshes. From the other point of computational time, AMR also saves about half the time as compared with the case of refining the entire field. It is obvious that AMR not only increases the resolution of local field, but also improves the efficiency of numerical simulation.

In this paper, the anisotropic magnetoresistance (AMR) and electron conductivity of electron gas in presence of the Rashba and Dresselhaus spin-orbit coupling are investigated. Boltzmann equation is solved exactly for low temperature, including electron scattering. Calculations have been performed within the coherent potential approximation. Results of the transport study demonstrate that the AMR enhances as the Rashba strength increases. It is also observed that the AMR depends critically on spin-orbit coupling strength, wave vector and Dresselhaus strength.

In this paper, a CFD parallel adaptive algorithm is self-developed by combining the multi-block Lattice Boltzmann Method (LBM) with Adaptive Mesh Refinement (AMR). The mesh refinement criterion of this algorithm is based on the density, velocity and vortices of the flow field. The refined grid boundary is obtained by extending outward half a ghost cell from the coarse grid boundary, which makes the adaptive mesh more compact and the boundary treatment more convenient. Two numerical examples of the backward step flow separation and the unsteady flow around circular cylinder demonstrate the vortex structure of the cold flow field accurately and specifically.

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• Life of a Scientist at Singapore-MIT Alliance for Research and Technology (SMART)

From historical obscurity, antiferromagnets are recently enjoying revived interest, as antiferromagnetic (AFM) materials may allow the continued reduction in size of spintronic devices. They have the benefit of being insensitive to parasitic external magnetic fields, while displaying high read/write speeds, and thus poised to become an integral part of the next generation of logical devices and memory. They are currently employed to preserve the magnetoresistive qualities of some ferromagnetic based giant or tunnel magnetoresistance systems. However, the question remains how the magnetic states of an antiferromagnet can be efficiently manipulated and detected. Here, we reflect on AFM materials for their use in spintronics, in particular, newly recognized antiferromagnet Mn₂Au with its in-plane anisotropy and tetragonal structure and high Néel temperature. These attributes make it one of the most promising candidates for AFM spintronics thus far with the possibility of architectures freed from the need for ferromagnetic (FM) elements. Here, we discuss its potential for use in ferromagnet-free spintronic devices.

High cost, low response frequency and dynamic time delay are general problems in most of the existing micro magnetic compass (MMC). According to the characteristic of mini-UAV navigation and control system, this paper presents a silicon MEMS-based integrated MMC, determining attitude by both accelerometers and anisotropic magneto resistance (AMR) sensors through estimating the mini-UAV state utilizing the Z-direction gyroscope. On the other hand, the magnetic disturbance around the MMC is calibrated. The experiments show that this MMC, with good collective performance, 0.5° heading accuracy, 1/5 cost and 50Hz response frequency, is able to meet the requirements of extraordinary precision, low cost and real time communication.