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Single-point mutations in the transmembrane (TM) region of receptor tyrosine kinases (RTKs) can lead to abnormal ligand-independent activation. We use a combination of computational modeling, NMR spectroscopy and cell experiments to analyze in detail the mechanism of how TM domains contribute to the activation of wild-type (WT) PDGFRA and its oncogenic V536E mutant. Using a computational framework, we scan all positions in PDGFRA TM helix for identification of potential functional mutations for the WT and the mutant and reveal the relationship between the receptor activity and TM dimerization via different interfaces. This strategy also allows us design a novel activating mutation in the WT (I537D) and a compensatory mutation in the V536E background eliminating its constitutive activity (S541G). We show both computationally and experimentally that single-point mutations in the TM region reshape the TM dimer ensemble and delineate the structural and dynamic determinants of spontaneous activation of PDGFRA via its TM domain. Our atomistic picture of the coupling between TM dimerization and PDGFRA activation corroborates the data obtained for other RTKs and provides a foundation for developing novel modulators of the pathological activity of PDGFRA.
A stratified liquid with two layers separated by a fast oscillating interface in the case of Raleigh--Taylor instability is considered. The averaged equations are derived, and it is shown that a mushy region of a certain density appears after averaging. The similarity between this fact and the case of unstable jump decay is discussed.
The article investigates one‐dimensional (1D) suspension‐colloidal transport of size distributed particles with particle attachment. A population balance approach is presented for computing the particle transport and capture by porous media. The occupied area of each attached particle is particle‐size dependent. The main model assumption is the retention‐rate dependency of the overall vacancy concentration for all particle sizes. For the first time, we derive an exact averaging (upscaling) procedure resulting in a closed system of large‐scale equations for average concentrations of suspended and retained particles, and of occupied rock surface area. The resulting large‐scale 3x3 system significantly differs from the traditional 2x2 deep bed filtration model. However, the traditional model becomes a particular case that corresponds to an equal occupied area for all particles. The averaging yields the appearance of two empirical suspension and site‐occupation functions, which govern the kinetics of particle retention and site occupation, respectively. 1D flow problems for the averaged equations are essentially non‐linear. However, they allow for exact solutions. We derive novel exact solutions for three 1D problems: continuous injection of particulate colloidal suspension, injection of colloidal suspension bank with particle‐free chase drive, and fines migration induced by high‐rate flows. The analytical model for continuous injection closely matches three series of laboratory tests on nano‐fluid transport.
A novel method of finding and classifying irreducible invariant surfaces of non-autonomous polynomial dynamical systems in the plane is presented. The general structure of irreducible invariant surfaces and their cofactors is found. The complete set of irreducible invariant surfaces for the classical forced Duffing-van der Pol oscillator is obtained. It is proved that the forced Duffing-van der Pol oscillator possesses only one independent generalized Darboux first integral provided that a constraint on the parameters is valid. In other cases generalized Darboux first integrals do not exist. Consequently, the forced Duffing-van der Pol oscillator is not integrable with two independent generalized Darboux first integrals.
We present a nonlocal statistical field theory of a diluted solution of dipolar particles which are capable of forming chain-like clusters in accordance with the ’head-to-tail’ mechanism. As in our previous study [Yu.A. Budkov 2018 J. Phys.: Condens. Matter 30 344001], we model dipolar particles as dimers comprised of oppositely charged point-like groups, separated by fluctuating distance. For the special case of the Yukawa-type distribution function of distance between the charged groups of dipolar particles we obtain an analytical expression for the electrostatic free energy of solution within the random phase approximation. We show that an increase in the association constant leads to a decrease in the absolute value of the electrostatic free energy of solution, preventing its phase separation which is in agreement with the former computer simulations and theoretical results. We obtain a non-linear integro-differential equation for the self-consistent field potential created by the fixed external charges in a solution medium, taking into account the association of dipolar particles. As a consequence of the derived self-consistent field equation, in regime of weak electrostatic interactions, we obtain an analytical expression for the electrostatic potential of the pointlike test ion, surrounded by the chain-like clusters of the dipolar particles. We show that in the mean-field approximation the association does not change the bulk dielectric permittivity of the solution, but increases the solvation radius of the point-like charge, relative to the theory of non-associating dipolar particles.
This book constitutes the refereed proceedings of the 9th International Conference on Optimization and Applications, OPTIMA 2018, held in Petrovac, Montenegro, in October 2018.The 35 revised full papers and the one short paper presented were carefully reviewed and selected from 103 submissions. The papers are organized in topical sections on mathematical programming; combinatorial and discrete optimization; optimal control; optimization in economy, finance and social sciences; applications.
A new method of solubility estimations, applied to sparingly dissolved compounds in supercritical carbon dioxide has been introduced in this paper. The method is based on determination of solubility contributions along the thermodynamic path consisting of sublimation and solvation processes. The contribution of the sublimation process is taken from the experiment, while the free energy of solvation is calculated from the classical density functional theory based on the fundamental measure theory. The parameterization of potential was performed using the Weeks-Chandler-Anderson procedure, where the Lennard-Jones parameters were obtained from the thermodynamics data of solute and solvent critical points. The introduced method can efficiently predict the pressure crossover on solubility curve of sparingly dissolved compounds in supercritical carbon dioxide.
We consider the Wiener algebra A(T^d) of absolutely convergent Fourier series on the d-torus. For phase functions \phi of a certain special form we obtain lower bounds for the A -norms of e^{i\lambda\varphi} as \lambda tends to \infty.
We reply to the comment on our paper by Budkov (2018 J. Phys.: Condens. Matter 30 344001).
We study the stability conditions of the multiserver queueing system in which each customer requires a random number of servers simultaneously. The input flow is supposed to be a regenerative one and service times of a given customer are independent at the occupied servers. The service time has an exponential, phase-type or hyper-exponential distribution. We define an auxiliary service process that is the number of completed services by all m servers under the assumption that there are always customers in the system. Then we construct the sequence of common regeneration points for the regenerative input flow and the auxiliary service process. It allows us to deduce the stability criterion of the model under consideration. It turns out that the stability condition does not depend on the structure of the input flow, only the rate of this process plays a role. Nevertheless the distribution of the service time is a very important factor. We give examples which show that the stability condition can not be expressed in terms of the mean of the service time.
We present a study of viscosities of methane, n-butane and their mixtures by the non-equilibrium molecular dynamics simulations and derivation of semiempirical volume-based mixing rules. The Batchinski equation $\eta = C / (V - b)$ is used to describe the viscosities of pure components, with parameters fitted to reproduce molecular dynamics results. Cubic root, Arrhenius and Batchinski mixing rules are tested for mixtures. The viscosities of pure components used in mixing equations are expressed as functions of volume of component rather than pressure. This allows to apply the mixing rules to metastable and stable liquids, dense supercritical fluids and solutions of gas in liquid. To obtain volumes of components in mixture, molecular dynamics method is used. The mixing rules predictions are compared against direct non-equilibrium molecular dynamics calculations of mixture viscosities. The best agreement with the molecular dynamics data is found when Batchinski mixing is used. The proposed viscosity model predictions are in agreement with the experimental data on viscosities of methane-butane mixtures. The model can be used for the interpretation and interpolation of the experimental data on viscosities of liquids, which is demonstrated on the example of methane + propane system.
Plasmon spectroscopy methods are highly sensitive to the small volumes of material due to subwavelength localization of light increasing light-matter interaction. Recent research has shown a high potential of plasmon quantum generator (spaser) or amplifier (sped) for sensing in the infrared optical region. Trinitrotoluene (TNT) molecules fingerprints are considered as an example. Basing on Lindblad equations, we implement full quantum mechanical theory of graphene plasmon generator to investigate how a small amount of absorbing atoms influences the spectrum of a graphene spaser. We analyze the optimal type of an active medium, the number of active molecules, and the pump level to achieve the highest sensitivity and show that optimized structure is sensitive to dozens of atoms. Our research is useful for the development of near- and mid-IR spectroscopy based on plasmon quantum amplifier.
For the three-frequency quantum resonance oscillator, the reducible case, where its frequencies are integer and at least one pair of frequencies has a nontrivial common divisor, is studied. It is shown how the description of the algebra of symmetries of such an oscillator can be reduced to the irreducible case of pairwise coprime integer frequencies. Polynomial algebraic relations are written, and irreducible representations and coherent states are constructed.
We point out that superconducting quantum computers are prospective for the simulation of the dynamics of spin models far from equilibrium, including nonadiabatic phenomena and quenches. The important advantage of these machines is that they are programmable, so that different spin models can be simulated in the same chip, as well as various initial states can be encoded into it in a controllable way. This opens an opportunity to use superconducting quantum computers in studies of fundamental problems of statistical physics such as the absence or presence of thermalization in the free evolution of a closed quantum system depending on the choice of the initial state as well as on the integrability of the model. In the present paper, we performed proof-of-principle digital simulations of two spin models, which are the central spin model and the transverse-field Ising model, using 5- and 16-qubit superconducting quantum computers of the IBM Quantum Experience. We found that these devices are able to reproduce some important consequences of the symmetry of the initial state for the system’s subsequent dynamics, such as the excitation blockade. However, lengths of algorithms are currently limited due to quantum gate errors. We also discuss some heuristic methods which can be used to extract valuable information from the imperfect experimental data.
The problem of optimal control is formulated for a class of nonlinear objects that can be represented as objects with a linear structure and parameters that depend on the state. The linear structure of the transformed nonlinear system and the quadratic functional of quality allow for the synthesis of optimal control, i.e. parameters of the regulator, move from the need to search for solutions of the Hamilton-Jacobi equation to an equation of the Riccati type with parameters that depend on the state. The main problem of implementing optimal control is related to the problem of finding a solution to such an equation at the pace of object functioning. The paper proposes an algorithmic method of parametric optimization of the regulator. This method is based on the use of the necessary conditions for the optimality of the control system under consideration. The constructed algorithms can be used both to optimize the non-stationary objects themselves, if the corresponding parameters are selected for this purpose, and to optimize the entire managed system by means of the corresponding parametric adjustment of the regulators. The example of drug treatment of patients with HIV is demonstrated the effectiveness of the developed algorithms.
A lot of files and data, in general, are transferred throughout the networks. But the data may be corrupted by intrusions or package loss so, the executable files may be marked as non-executable and violate the local network policy. Thus, it’s necessary to detect such files. In this paper, we present a novel method for detecting broken bytes of a file, so the corrupted files may be detected. Also, the positions of wrong bytes might be helpful in restoring the original file content. This work is devoted to study of modern neural network models applied to detect corrupted bytes of a file problem. Since recurrent neural networks (RNNs) seem to be well suited for such tasks, the main tasks of this work are to analyze the efficiency of popular state-of-the-art RNNs solving the problem mentioned above and to compare results of different models. We use data consisting of the most popular file types collected from the Internet and manually randomly added noise to that data to test our models. An experiment on this data demonstrates the advantages and disadvantages of the considered models.
Researchers face fundamental challenges applying the stochastic geometry framework to analysis of terahertz (THz) communications systems. The two major problems are the principally new propagation model that now includes exponential term responsible for molecular absorption and blocking of THz radiation by the human crowd around the receiver. These phenomena change the probability density function ) of the interference from a single node such that it no longer has an analytical Laplace transform (LT) preventing characterization of the aggregated interference and signal-to-interference ratio (SIR) distributions. The expected use of highly directional antennas at both transmitter and receiver adds to this problem increasing the complexity of modeling efforts. In this paper, we consider Poisson deployment of interferers in ℜ 2 and provide accurate analytical approximations for of interference from a randomly chosen node for blocking and non-blocking cases. We then derive LTs ofs of aggregated interference and SIR. Using the Talbot’s algorithm for inverse transform we provide numerical results indicating that failure to capture atmospheric absorption, blocking or antenna directivity leads to significant modeling errors. Finally, we investigate the response of SIR densities to a wide range of system parameters highlighting the specific effects of THz communications systems. The model developed in this paper can be used as a building block for performance analysis of realistic THz network deployments providing metrics such as outage and coverage probabilities.