Allosteric modulation of the SARS-CoV-2 spike conformation

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infects host cells through binding to angiotensin-converting enzyme 2 (ACE2), which is mediated by the receptor-binding domain (RBD) of the viral spike (S) glycoprotein. Structural data and real-time analysis of conformational dynamics have shown that S can adopt multiple conformations, which mediate the exposure of the ACE2-binding site in the RBD. Here, using single-molecule Förster resonance energy transfer (smFRET) imaging we report the effects of ACE2 and antibody binding on the conformational dynamics of S from the Wuhan-1 strain and the B.1 variant (D614G). We found that antibodies that target diverse epitopes, including those distal to the RBD, stabilize the RBD in a position competent for ACE2 binding. Parallel solution-based binding experiments using fluorescence correlation spectroscopy (FCS) indicated antibody-mediated enhancement of ACE2 binding. These findings inform on novel strategies for therapeutic antibody cocktails.

A Collocated Finite Volume Scheme for High-Performance Simulation of Induced Seismicity in Geo-Energy Applications

We develop a collocated Finite Volume Method (FVM) to study induced seismicity as a result of pore pressure fluctuations. A discrete system is obtained based on a fully-implicit coupled description of flow, elastic deformation, and contact mechanics at fault surfaces on a fully unstructured mesh. The cell-centered collocated scheme leads to convenient integration of the different physical equations, as the unknowns share the same discrete locations on the mesh. Additionally, a multi-point flux approximation is formulated in a general procedure to treat heterogeneity, anisotropy, and cross-derivative terms for both flow and mechanics equations. The resulting system, though flexible and accurate, can lead to excessive computational costs for field-relevant applications. To resolve this limitation, a scalable parallel solution algorithm is developed and presented. Several proof-of-concept numerical tests, including benchmark studies with analytical solutions, are investigated. It is found that the presented method is indeed accurate, stable and efficient; and as such promising for accurate and efficient simulation of induced seismicity.

Building of training sessions in the health-enhancing physical activity

The article analyzes the recommendations for the building of training sessions in the health-enhancing physical activity (HEPA), offers directions for further improvement this process. As you know, the effectiveness of health-enhancing physical activity is determined by the factors: the use of means and methods adequate for age and fitness, the optimal physical load and the peculiarities of its alternation with rest. Ultimately, the implementation of these requirements is carried out through the rational building of various structural elements as microcycles, mesocycles, macrocycles, training session. However, in our opinion, some of the theoretical provisions of the planning of training sessions, in contrast to sports training, have not been sufficiently studied. Research aim is to study the peculiarities of building training sessions in health-enhancing physical activity. Objectives: Analyze of specialists recommendations on the characteristics of the load used in the building of health-enhancing sessions. Study the peculiarities of the building selective and complex sessions. It was found that the recommendations regarding the duration of the training load for building of health-enhancing physical activity are sufficiently developed. However characteristic classification for sports practice is not used when planning the value of loads in separate sessions. This refers to a classification that takes into account the phase of physical performance in which the session was ended. It classification include low, medium, significant and large loads. In our opinion, this negatively affects the quality of planning both sessions and microcycles. It is revealed that there is a need to further improve the building complex training sessions with a consistent solution of tasks and the development of methodological conditions for the use of means and methods in complex training sessions with a parallel solution of tasks.

Large scale simulation of pressure induced phase-field fracture propagation using Utopia

Non-linear phase field models are increasingly used for the simulation of fracture propagation problems. The numerical simulation of fracture networks of realistic size requires the efficient parallel solution of large coupled non-linear systems. Although in principle efficient iterative multi-level methods for these types of problems are available, they are not widely used in practice due to the complexity of their parallel implementation. Here, we present Utopia, which is an open-source C++ library for parallel non-linear multilevel solution strategies. Utopia provides the advantages of high-level programming interfaces while at the same time a framework to access low-level data-structures without breaking code encapsulation. Complex numerical procedures can be expressed with few lines of code, and evaluated by different implementations, libraries, or computing hardware. In this paper, we investigate the parallel performance of our implementation of the recursive multilevel trust-region (RMTR) method based on the Utopia library. RMTR is a globally convergent multilevel solution strategy designed to solve non-convex constrained minimization problems. In particular, we solve pressure-induced phase-field fracture propagation in large and complex fracture networks. Solving such problems is deemed challenging even for a few fractures, however, here we are considering networks of realistic size with up to 1000 fractures.

NUMERICAL IMPLEMENTATION OF A PARALLEL ALGORITHM FOR SOLVING THE PROBLEM OF POLLUTANT TRANSPORT IN A RESERVOIR ON A HIGH-PERFORMANCE COMPUTER SYSTEM

The purpose of this work is to create a software package for a distributed solution of the problem of transporting a pollutant in a reservoir with complex bathymetry and the presence of technological structures. An algorithm has been developed for the parallel solution of the problem of transporting a pollutant (pollutant) in a reservoir on a graphics accelerator controlled by the CUDA (Compute Unified Device Architecture) system; a comparative analysis of the operation of algorithms on a CPU (Central Processing Unit) and on a graphics accelerator GPU (Graphics Processing Unit) made it possible to evaluate their performance. The software implementation of the modules included in the complex is described, the main classes and implemented methods are documented. The results of numerical experiments showed that solving of pollutant transport’s problem based on the CUDA technology is ineffective for small grids (up to 100 ´ 100 computational nodes). In the case of large grids (1000 ´ 1000 computational nodes), the use of CUDA technology reduces the computation time by an order of magnitude. An analysis of the experiments carried out with the developed components of software showed that the maximum value of the ratio of the algorithm operating time that implements the set task of transferring matter in a shallow water on a GPU to the operating time of a similar algorithm on the CPU was 24.92 times, which is achieved on a grid of 1000 ´ 1000 computational nodes. Implementation of methods for decomposition of grid regions is proposed for solving computationally laborious problems of diffusion-convection, including the problem of transporting pollutants in a reservoir with complex bathymetry with technological objects that take into account the architecture and parameters of a MSC (Multiprocessor Computing System) located on the basis of the infrastructure facility of the STU (Scientific and Technological University) “Sirius” (Sochi, Russia). Consideration was made for such a property of a computing system as the time it takes to transmit and receive floating point data. An algorithm for the parallel solution of the task under the control of MPI (Message Passing Interface) technology has been developed, and its efficiency has been assessed. The acceleration values of the proposed algorithm are obtained depending on the number of involved computers (processors) and the size of the computational grid. The maximum number of computers used is 24, the maximum size of the computational grid was 10 000 ´ 10 000 computational nodes. The developed algorithm showed low efficiency for small computational grids (up to 100 ´ 100 computational nodes). In the case of large computational grids ( from 1000  1000 computational nodes), the use of MPI reduces the computation time by several times.

Hyperspectral Parallel Image Compression on Edge GPUs

Edge applications evolved into a variety of scenarios that include the acquisition and compression of immense amounts of images acquired in space remote environments such as satellites and drones, where characteristics such as power have to be properly balanced with constrained memory and parallel computational resources. The CCSDS-123 is a standard for lossless compression of multispectral and hyperspectral images used in on-board satellites and military drones. This work explores the performance and power of 3 families of low-power heterogeneous Nvidia GPU Jetson architectures, namely the 128-core Nano, the 256-core TX2 and the 512-core Xavier AGX by proposing a parallel solution to the CCSDS-123 compressor on embedded systems, reducing development effort, compared to the production of dedicated circuits, while maintaining low power. This solution parallelizes the predictor on the low-power GPU while the entropy encoders exploit the heterogeneous multiple CPU cores and the GPU concurrently. We report more than 4.4 GSamples/s for the predictor and up to 6.7 Gb/s for the complete system, requiring less than 11 W and providing an efficiency of 611 Mb/s/W.

A single inverse-designed photonic structure that performs parallel computing

In the search for improved computational capabilities, conventional microelectronic computers are facing various problems arising from the miniaturization and concentration of active electronics. Therefore, researchers have explored wave systems, such as photonic or quantum devices, for solving mathematical problems at higher speeds and larger capacities. However, previous devices have not fully exploited the linearity of the wave equation, which as we show here, allows for the simultaneous parallel solution of several independent mathematical problems within the same device. Here we demonstrate that a transmissive cavity filled with a judiciously tailored dielectric distribution and embedded in a multi-frequency feedback loop can calculate the solutions of a number of mathematical problems simultaneously. We design, build, and test a computing structure at microwave frequencies that solves two independent integral equations with any two arbitrary inputs and also provide numerical results for the calculation of the inverse of four 5 x 5 matrices.