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At least 343 records · Page 19

Tightness of the Ising–Kac Model on the Two-Dimensional Torus

We consider the sequence of Gibbs measures of Ising models with Kac interaction defined on a periodic two-dimensional discrete torus near criticality. Using the convergence of the Glauber dynamic proven by Mourrat and Weber (Commun Pure Appl Math 70:717–812, 2017) and a method by Tsatsoulis and Weber employed in ( arXiv:1609.08447 2016), we show tightness for the sequence of Gibbs measures of the Ising–Kac model near criticality and characterise the law of the limit as the Φ{sub 2}{sup 4} measure on the torus. Our result is very similar to the one obtained by Cassandro et al. (J Stat Phys 78(3):1131–1138, 1995) on ℤ{sup 2}, but our strategy takes advantage of the dynamic, instead of correlation inequalities. In particular, our result covers the whole critical regime and does not require the large temperature/large mass/small coupling assumption present in earlier results.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Quantitative Pointwise Estimate of the Solution of the Linearized Boltzmann Equation

We study the quantitative pointwise behavior of the solutions of the linearized Boltzmann equation for hard potentials, Maxwellian molecules and soft potentials, with Grad’s angular cutoff assumption. More precisely, for solutions inside the finite Mach number region (time like region), we obtain the pointwise fluid structure for hard potentials and Maxwellian molecules, and optimal time decay in the fluid part and sub-exponential time decay in the non-fluid part for soft potentials. For solutions outside the finite Mach number region (space like region), we obtain sub-exponential decay in the space variable. The singular wave estimate, regularization estimate and refined weighted energy estimate play important roles in this paper. Our results extend the classical results of Liu and Yu (Commun Pure Appl Math 57:1543–1608, 2004), (Bull Inst Math Acad Sin 1:1–78, 2006), (Bull Inst Math Acad Sin 6:151–243, 2011) and Lee et al. (Commun Math Phys 269:17–37, 2007) to hard and soft potentials by imposing suitable exponential velocity weight on the initial condition.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Quantum Markov States and Quantum Hidden Markov States

In a previous paper (Funct. Anal. Appl., 3 (2015), 205–209), we defined quantum Markov states. Here we recall this definition and present a proof of the results from that paper (which are given there without proofs). We give a definition of a quantum hidden Markov state generated by a function of a quantum Markov process and show how it is related to other definitions of such states. Our definitions work for quantum Markov fields on ℤ{sup N} and on graphs. We consider an example with the Cayley tree.

97 MATHEMATICS AND COMPUTING↗

Accelerated Oxygen Mass Transfer in Copper and Vanadium Oxide-Based MIEC-Redox Membrane

Mixed ionic-electronic conducting (MIEC) membranes have a great potential for use in gas separation technology in the production of pure oxygen for metallurgy, micro- and nanoelectronics, biotechnology, pharmaceutics, etc. Before this happens, an important issue has to be addressed. This issue involves the design of novel MIEC membranes with enhanced oxygen transport. Recently, a concept of thick two-layer solid/liquid composite MIEC-Redox membranes with accelerated diffusion-bubbling oxygen transfer was proposed (see Belousov and Fedorov in ACS Appl Mater Interfaces 10:21794–21798, 2018). These diffusion-bubbling membranes could serve for efficient oxygen separation from air. However, there is no enough fundamental understanding of the mass transport processes involved. This understanding is important for evaluating the potential of MIEC-Redox membranes for practical application. The presented article gives a theory of oxygen mass transfer in two-layer copper and vanadium oxide-based MIEC-Redox membranes. The theory describes both the transport of oxygen ions in the outer layer of the membrane and the nucleation, growth, and transport of oxygen gas bubbles in the inner layer of the membrane. Kinetic regularities of oxygen mass transfer are established. The ways to enhance the productivity of MIEC-Redox membranes are outlined.

36 MATERIALS SCIENCE↗

Gold Nanoparticles (AuNPs) as Reactive Matrix for Detection of Trace Levels of HCN in Air by Laser Desorption/Ionization Mass Spectrometry (LDI-MS)

Under direct laser desorption/ionization mass spectrometric conditions, the irradiation of target spots made of gold nanoparticle residues generates a series of peaks at m/z 197, 394, 591… representing Au{sub n}{sup −} ions (n = 1–3). In contrast, spectra recorded from gold nanoparticles directly mixed with an alkali cyanide exhibited an additional peak at m/z 249, indicating an abundant generation of gaseous [Au(CN){sub 2}]{sup −} ions upon irradiation. The relative intensity of the m/z 249 peak surged when the amount of cyanide in the mixture was increased. Most remarkably, a peak at m/z 249 was observed even from neat AuNPs upon irradiation, if a nearby spot, which was not irradiated, happened to bear a cyanide sample. We postulated that traces of HCN emanating from the headspace of aqueous cyanide solution during the sample-plate preparation is sufficient to convert gold to AuCN, which is subsequently detected as [Au(CN){sub 2}]{sup −}. Further experiments demonstrated that the relative intensity of the m/z 249 peak diminishes exponentially as the AuNP spot becomes more distant from the putative HCN source. Eventually, the method was developed as an efficient procedure to detect HCN or alkali cyanides. Using KCN, the detection limits were determined to be below 10 pg of CN{sup −} per spot. The method also demonstrated that, upon crushing, the seeds or roots of certain fruits and vegetables such as apple, peach, radish, and cassava, but not carrot, release HCN in amounts detectable by this method. .

77 NANOSCIENCE AND NANOTECHNOLOGY↗

A relaxed two-step splitting iteration method for computing PageRank

In this paper, we extend the two-step matrix splitting iteration approach by introducing a new relaxation parameter. The main idea is based on the inner–outer iteration for solving the PageRank problems proposed by Gleich et al. (J Sci Comput 32(1): 349–371, 2010) and Bai (Numer Algebra Cont Optim 2(4): 855–862, 2012) and the two-step splitting iteration presented by Gu et al. (Appl Math Comput 271: 337–343, 2015). The theoretical analysis results show that the proposed method is efficient. Numerical experiments demonstrate that the convergence performances of the method are better than the existing methods.

97 MATHEMATICS AND COMPUTING↗

Jacobian consistency of a one-parametric class of smoothing Fischer–Burmeister functions for SOCCP

The Jacobian consistency of smoothing functions plays an important role for achieving the rapid convergence of Newton methods or Newton-like methods with an appropriate parameter control. In this paper, we study the properties, derive the computable formula for the Jacobian matrix and prove the Jacobian consistency of a one-parametric class of smoothing Fischer–Burmeister functions for second-order cone complementarity problems proposed by Tang et al. (Comput Appl Math 33:655–669, 2014). Then we apply its Jacobian consistency to a smoothing Newton method with the appropriate parameter control presented by Chen et al. (Math Comput 67:519–540, 1998), and show the global convergence and local quadratic convergence of the algorithm for solving the SOCCP under rather weak assumptions.

97 MATHEMATICS AND COMPUTING↗

A new relaxed splitting preconditioner for the generalized saddle point problems from the incompressible Navier–Stokes equations

Based on the modified relaxed splitting (MRS) preconditioner proposed by Fan and Zhu (Appl Math Lett 55:18–26, 2016), a new relaxed splitting preconditioner is proposed for the generalized saddle point problems arising from the incompressible Navier–Stokes equations. The eigenvalue distribution and an upper bound of the degree of the minimal polynomial of the preconditioned matrix are analyzed. Numerical results show that the proposed preconditioner is superior to the MRS preconditioner when they are used as preconditioners to accelerate the convergence rate of the Krylov subspace methods, such as GMRES.

97 MATHEMATICS AND COMPUTING↗

A class of customized proximal point algorithms for linearly constrained convex optimization

In this paper, we propose a class of customized proximal point algorithms for linearly constrained convex optimization problems. The algorithms are implementable, provided that the proximal operator of the objective function is easy to evaluate. We show that, with special setting of the algorithmic scalar, our algorithms contain the customized proximal point algorithm (He et al., Optim Appl 56:559–572, 2013), the linearized augmented Lagrangian method (Yang and Yuan, Math Comput 82:301–329, 2013), the Bregman Operator Splitting algorithm (Zhang et al., SIAM J Imaging Sci 3:253–276, 2010) as special cases. The global convergence and worst-case convergence rate measured by the iteration complexity are established for the proposed algorithms. Numerical results demonstrate that the algorithms work well for a wide range of the scalar.

97 MATHEMATICS AND COMPUTING↗

Similarity solution for a two-phase one-dimensional Stefan problem with a convective boundary condition and a mushy zone model

A two-phase solidification process for a one-dimensional semi-infinite material is considered. It is assumed that it is ensued from a constant bulk temperature present in the vicinity of the fixed boundary, which it is modelled through a convective condition (Robin condition). The interface between the two phases is idealized as a mushy region and it is represented following the model of Solomon, Wilson, and Alexiades. An exact similarity solution is obtained when a restriction on data is verified, and it is analysed the relation between the problem considered here and the problem with a temperature condition at the fixed boundary. Moreover, it is proved that the solution to the problem with the convective boundary condition converges to the solution to a problem with a temperature condition when the heat transfer coefficient at the fixed boundary goes to infinity, and it is given an estimation of the difference between these two solutions. Results in this article complete and improve the ones obtained in Tarzia (Comput Appl Math 9:201–211, 1990).

97 MATHEMATICS AND COMPUTING↗

Numerical study of a smoothing algorithm for the complementarity system over the second-order cone

This paper deals with the complementarity system over the second-order cone (denoted by CSSOC) which contains a wide class of problems. We extend a class of regularized Chen–Harker–Kanzow–Smale smoothing functions studied by Huang and Sun (Appl Math Optim 52:237–262, 2005) for the linear complementarity problem to the CSSOC. Based on this class of functions, we propose a smoothing algorithm for solving the CSSOC. Under weak assumptions, we prove that the proposed algorithm has global and local quadratic convergence. The proposed algorithm is different from existing smoothing algorithms for solving the CSSOC because it adopts a new nonmonotone line search rule. In addition, our algorithm solves a new equation reformulation of the CSSOC. Numerical experiments indicate that the proposed algorithm is quite effective.

97 MATHEMATICS AND COMPUTING↗

Diagonal and circulant or skew-circulant splitting preconditioners for spatial fractional diffusion equations

We propose three new preconditioners: diagonal and optimal-circulant splitting preconditioner, diagonal and skew-circulant splitting preconditioner, and diagonal and optimal-skew-circulant splitting preconditioner for solving the diagonal-plus-Toeplitz linear system discretized from the spatial fractional diffusion equations. Theoretical analysis shows that these three preconditioners can make the eigenvalues of the preconditioned matrices be clustered around 1, especially when the grids of the discretizations are refined. These results coincide with the one about the diagonal and circulant splitting preconditioner constructed recently by Bai et al. (Numer Linear Algebra Appl 24:e2093, 2017). Numerical experiments exhibit that the proposed preconditioners can significantly improve the convergence of the Krylov subspace iteration methods like GMRES and BiCGSTAB, and they outperform the diagonal and circulant splitting preconditioner as well.

97 MATHEMATICS AND COMPUTING↗

Explicit solution for a two-phase fractional Stefan problem with a heat flux condition at the fixed face

A generalized Neumann solution for the two-phase fractional Lamé–Clapeyron–Stefan problem for a semi-infinite material with constant initial temperature and a particular heat flux condition at the fixed face is obtained, when a restriction on data is satisfied. The fractional derivative in the Caputo sense of order α∈(0,1) respect on the temporal variable is considered in two governing heat equations and in one of the conditions for the free boundary. Furthermore, we find a relationship between this fractional free boundary problem and another one with a constant temperature condition at the fixed face and based on that fact, we obtain an inequality for the coefficient which characterizes the fractional phase–change interface obtained in Roscani and Tarzia (Adv Math Sci Appl 24(2):237–249, 2014). We also recover the restriction on data and the classical Neumann solution, through the error function, for the classical two-phase Lamé–Clapeyron–Stefan problem for the case α=1.

97 MATHEMATICS AND COMPUTING↗

Extended Newton-type method for nonlinear functions with values in a cone

In this paper, we consider the problem of finding solutions of nonlinear inclusion problems in Banach space. Using convex optimization techniques introduced by Robinson (Numer Math 19:341–347, 1972), a convergence theorem for Kantorovich-like methods is given, which improves the results of Yamamoto (Jpn J Appl Math 3(2):295–313, 1986; Numer Math 51(5):545–557, 1987) and Robinson (Numer Math 19:341–347, 1972). The result is compared with previously known results. Numerical examples further justify the theoretical results.

97 MATHEMATICS AND COMPUTING↗

Numeric invariants from multidimensional persistence

Topological data analysis is the study of data using techniques from algebraic topology. Often, one begins with a finite set of points representing data and a “filter” function which assigns a real number to each datum. Using both the data and the filter function, one can construct a filtered complex for further analysis. For example, applying the homology functor to the filtered complex produces an algebraic object known as a “one-dimensional persistence module”, which can often be interpreted as a finite set of intervals representing various geometric features in the data. If one runs the above process incorporating multiple filter functions simultaneously, one instead obtains a multidimensional persistence module. Unfortunately, these are much more difficult to interpret. In this article, we analyze the space of multidimensional persistence modules from the perspective of algebraic geometry. First we build a moduli space of a certain subclass of easily analyzed multidimensional persistence modules, which we construct specifically to capture much of the information which can be gained by using multidimensional persistence instead of one-dimensional persistence. Fruthermore, we argue that the global sections of this space provide interesting numeric invariants when evaluated against our subclass of multidimensional persistence modules. Finally, we extend these global sections to the space of all multidimensional persistence modules and discuss how the resulting numeric invariants might be used to study data. This paper extends the results of Adcock et al. (Homol Homotopy Appl 18(1), 381–402, 2016) by constructing numeric invariants from the computation of a multidimensional persistence module as given by Carlsson et al. (J Comput Geom 1(1), 72–100, 2010).

58 GEOSCIENCES↗

Application of HRGS for forensic characterization of uranium oxides, pure uranium metals and uranium alloys

A nondestructive iterative method for uranium-bearing material characterization with HRGS developed earlier in (J. appl. Rad. Isotopes, 166 (2020) 109433) is applied to determine matrix densities and uranium isotope masses of a variety of uranium materials, namely uranium ore, UO 2 and U 3 O 8 powders, fuel elements in the form of UO2 microspheres, uranium metal and uranium alloys. It is shown that U 3 O 8 powders with uranium mass fraction of about 84% can be distinguished from the powders of UO 2 with uranium mass fraction of about 87%; uranium products in the form of liquid or loose powder with matrix density of 0.5-2.0 g/cm 3 can be distinguished from uranium products in the form of compacted fuel elements with matrix density of 6.0-10.0 g/cm 3 and from pure metal uranium and uranium alloys with matrix density of 14.0- 19.0 g/cm 3 . In fuel microspheres based on UO2 the uranium mass fraction 88.02% measured by HRGS is consistent, within the measurement uncertainties, with the results of isotope dilution mass spectrometry 87.76±0.64 % and also is confirmed by X-ray diffraction technique. The uranium mass fraction of the uranium ore estimated as 0.08% by HRGS is consistent, within the measurement uncertainties, with the value 0.09±0.01% determined with WDXRF. Densities of two different uranium metal samples, estimated as 18.42 g/cm 3 and 19.33 g/cm 3 by HRGS are consistent with values 18.24±0.55 g/cm 3 and 18.86±0.59 g/cm 3 , respectively, obtained by the gas pycnometry technique.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Low-mass molecular dynamics simulation: A simple and generic technique to enhance configurational sampling

Highlights: • Reducing atomic masses by 10-fold vastly improves sampling in MD simulations. • CLN025 folded in 4 of 10 × 0.5-μs MD simulations when masses were reduced by 10-fold. • CLN025 folded as early as 96.2 ns in 1 of the 4 simulations that captured folding. • CLN025 did not fold in 10 × 0.5-μs MD simulations when standard masses were used. • Low-mass MD simulation is a simple and generic sampling enhancement technique. - Abstract: CLN025 is one of the smallest fast-folding proteins. Until now it has not been reported that CLN025 can autonomously fold to its native conformation in a classical, all-atom, and isothermal–isobaric molecular dynamics (MD) simulation. This article reports the autonomous and repeated folding of CLN025 from a fully extended backbone conformation to its native conformation in explicit solvent in multiple 500-ns MD simulations at 277 K and 1 atm with the first folding event occurring as early as 66.1 ns. These simulations were accomplished by using AMBER forcefield derivatives with atomic masses reduced by 10-fold on Apple Mac Pros. By contrast, no folding event was observed when the simulations were repeated using the original AMBER forcefields of FF12SB and FF14SB. The results demonstrate that low-mass MD simulation is a simple and generic technique to enhance configurational sampling. This technique may propel autonomous folding of a wide range of miniature proteins in classical, all-atom, and isothermal–isobaric MD simulations performed on commodity computers—an important step forward in quantitative biology.

60 APPLIED LIFE SCIENCES↗

Adiponectin enhances osteogenic differentiation in human adipose-derived stem cells by activating the APPL1-AMPK signaling pathway

Human adipose-derived stem cells (hASCs) are multipotent progenitor cells with multi-lineage differentiation potential including osteogenesis and adipogenesis. While significant progress has been made in understanding the transcriptional control of hASC fate, little is known about how hASC differentiation is regulated by the autocrine loop. The most abundant adipocytokine secreted by adipocytes, adiponectin (APN) plays a pivotal role in glucose metabolism and energy homeostasis. Growing evidence suggests a positive association between APN and bone formation yet little is known regarding the direct effects of APN on hASC osteogenesis. Therefore, this study was designed to investigate the varied osteogenic effects and regulatory mechanisms of APN in the osteogenic commitment of hASCs. We found that APN enhanced the expression of osteoblast-related genes in hASCs, such as osteocalcin, alkaline phosphatase, and runt-related transcription factor-2 (Runx2, also known as CBFa1), in a dose- and time-dependent manner. This was further confirmed by the higher expression levels of alkaline phosphatase and increased formation of mineralization nodules, along with the absence of inhibition of cell proliferation. Importantly, APN at 1 μg/ml was the optimal concentration, resulting in maximum deposition of calcium nodules, and was significant superior to bone morphogenetic protein 2. Mechanistically, we found for the first time that APN increased nuclear translocation of the leucine zipper motif (APPL)-1 as well as AMP-activated protein kinase (AMPK) phosphorylation, which were reversed by pretreatment with APPL1 siRNA. Our results indicate that APN promotes the osteogenic differentiation of hASCs by activating APPL1-AMPK signaling, suggesting that manipulation of APN is a novel therapeutic target for controlling hASC fate. - Highlights: • Adiponectin enhances osteogenic differentiation in human adipose-derived stem cells. • The knock-down of APPL1 block the enhancement of osteogenic differentiation in hASC. • AMPK signaling cascade is activated by adiponectin through APPL1.

60 APPLIED LIFE SCIENCES↗