Performance review of locking alleviation methods for continuum ANCF beam elements

Nonlinear Dynamics - The absolute nodal coordinate formulation (ANCF) is a nonlinear finite element approach proposed for the large deformation dynamics analysis of beam- and plate/shell-type...     

Supercritical CO2 Extraction of Triterpenoids from Chaga Sterile Conk of Inonotus obliquus

Triterpenoids are among the bioactive components of Chaga, the sterile conk of the medicinal fungus Inonotus obliquus. Supercritical fluid extraction of Chaga triterpenoids was carried out with supercritical CO₂, while a modified Folch method was used as a comparison. Three temperature-pressure combinations were tested varying between 314–324 K (40–50 °C) and 281–350 bars, using time- and volume-limited extractions. Six triterpenoids were identified with GC-MS and quantified with GC-FID: ergosterol, lanosterol, β-sitosterol, stigmastanol, betulin, and inotodiol. The Folch extraction resulted in recovery of trametenolic acid, which was not extracted by supercritical CO₂. Inotodiol was the major triterpenoid of all the extracts, with a yield of 87–101 mg/100 g and 139 mg/100 g, for SFEs and the Folch method, respectively. The contents of other major triterpenoids, lanosterol and ergosterol, varied in the ranges 59–63 mg/100 g and 17–18 mg/100 g by SFE, respectively. With the Folch method, the yields were 81 mg/100 g and 40 mg/100 g, respectively. The highest recovery of triterpenoids with SFE in relation to Folch was 56% and it was obtained at 324 K (50 °C) and 350 bar, regardless of extraction time or volume of CO₂. The recoveries of lanosterol and stigmastanol were unaffected by SFE conditions. Despite the lower yield, SFE showed several advantages including shorter extraction time and less impact on the environment. This work could be a starting point for further studies on green extraction methods of bioactive triterpenoids from Chaga.     

Introduction and Analysis of a Method for the Investigation of QCD-like Tree Data

The properties of decays that take place during jet formation cannot be easily deduced from the final distribution of particles in a detector. In this work, we first simulate a system of particles with well-defined masses, decay channels, and decay probabilities. This presents the “true system” for which we want to reproduce the decay probability distributions. Assuming we only have the data that this system produces in the detector, we decided to employ an iterative method which uses a neural network as a classifier between events produced in the detector by the “true system” and some arbitrary “test system”. In the end, we compare the distributions obtained with the iterative method to the “true” distributions.     

Probing chromosome structure with dynamic force relaxation

We report measurements of the dynamics of force relaxation in single mitotic chromosomes, following step strains applied with micropipettes of force constant approximately 1 nN/microm. The force relaxes exponentially after an elongation (l/l(0)) to less than 3x native length, with a relaxation time approximately 2 sec. This relaxation time corresponds to an effective viscosity approximately 10(5) times that of water. We experimentally rule out solvent flow into the chromosome as the mechanism for the relaxation time. Instead, the relaxation can be explained in terms of the disentanglement dynamics of approximately 80 kb chromatin loop domains.     

Dynamical properties of a particle in a wave packet: Scaling invariance and boundary crisis

Some dynamical properties present in a problem concerning the acceleration of particles in a wave packet are studied. The dynamics of the model is described in terms of a two-dimensional area preserving map. We show that the phase space is mixed in the sense that there are regular and chaotic regions coexisting. We use a connection with the standard map in order to find the position of the first invariant spanning curve which borders the chaotic sea. We find that the position of the first invariant spanning curve increases as a power of the control parameter with the exponent 2/3. The standard deviation of the kinetic energy of an ensemble of initial conditions obeys a power law as a function of time, and saturates after some crossover. Scaling formalism is used in order to characterise the chaotic region close to the transition from integrability to nonintegrability and a relationship between the power law exponents is derived. The formalism can be applied in many different systems with mixed phase space. Then, dissipation is introduced into the model and therefore the property of area preservation is broken, and consequently attractors are observed. We show that after a small change of the dissipation, the chaotic attractor as well as its basin of attraction are destroyed, thus leading the system to experience a boundary crisis. The transient after the crisis follows a power law with exponent −2.     

Optimal Error Estimate of the Penalty Finite Element Method for the Micropolar Fluid Equations

We present an optimal error estimate of the numerical velocity, pressure, and angular velocity for the fully discrete penalty finite element method of the micropolar equations when the parameters ?, Δ t, and h are sufficiently small. In order to obtain this estimate, we present the time discretization of the penalty micropolar equation that is based on the backward Euler scheme; the spatial discretization of the time discretized penalty micropolar equation is based on a finite elements space pair (X _h , M _h ) that satisfies some approximations properties.     

The <Emphasis Type="Italic">D</Emphasis><Superscript>(−)</Superscript>-Center Energy Spectrum in the Quantum Narrowing in the Presence of a Longitudinal Magnetic Field

The dispersion equation for an electron localized at the D⁰-center in the quantum narrowing in the presence of a magnetic field longitudinal with respect to the axis of constriction is analytically derived within the model of zero-radius potential. It is found that a special feature of the electron spectrum in the quantum narrowing manifests itself in the dependence of the D(−)-state binding energy on the effective constriction length. The evolution of the D(−)-state binding energy with changes in the longitudinal magnetic-field strength is investigated and compared with the case of D(−)-states in quantum wires. __________ Translated from Izvestiya Vysshikh Uchebnykh Zavedenii, Fizika, No. 6, pp. 23–27, June, 2005.     

Extensions of the Fill–Fishkind formula and the infimum – parallel sum relation

Recently, in (Arias ML, Corach G, Maestripieri A. Range additivity, shorted operator and the Sherman–Morrison–Woodburry formula, Linear Algebra Appl. 2015;467), authors gave a generalization of a formula by Fill and Fishkind, regarding the Moore–Penrose inverse of the sum of two matrices, in the setting of arbitrary Hilbert spaces. We consider this formula under some weaker assumptions and derive certain conclusions generalizing the mentioned result. We also extend a formula connecting the infimum of two orthogonal projections and their parallel sum to a formula connecting the star-infimum and the parallel sum of operators which need not be positive, using the concept of parallel sum that was introduced in (Antezana J, Corach G, Stojanoff D. Bilateral shorted operators and parallel sums. Linear Algebra Appl. 2006;414).     

Free energy and entropy production in planar Couette flow far from equilibrium

The macroscopic thermodynamic stability of a system of 108 diatomic molecules undergoing planar Couette flow far from equilibrium is reported. The system is perturbed from the steady state using a nondissipative variable colour field which induces a polarization in the system. It is found that the steady state for the system corresponds to an extremum in the generalized free energy and entropy production. However, while the free energy is always a minimum, the entropy production may be either a minimum or a maximum depending upon the direction of the colour field. These results, for a molecular system, are fundamentally different from those for an equivalent atomic system.     

A continuation approach to mode-finding of multivariate Gaussian mixtures and kernel density estimates

This paper presents a novel method of multi-objective optimization by learning automata (MOLA) to solve complex multi-objective optimization problems. MOLA consists of multiple automata which perform sequential search in the solution domain. Each automaton undertakes dimensional search in the selected dimension of the solution domain, and each dimension is divided into a certain number of cells. Each automaton performs a continuous search action, instead of discrete actions, within cells. The merits of MOLA have been demonstrated, in comparison with a multi-objective evolutionary algorithm based on decomposition (MOEA/D) and non-dominated sorting genetic algorithm II (NSGA-II), on eleven multi-objective benchmark functions and an optimal problem in the midwestern American electric power system which is integrated with wind power, respectively. The simulation results have shown that MOLA can obtain more accurate and evenly distributed Pareto fronts, in comparison with MOEA/D and NSGA-II.