On the radius of spatial analyticity for the modified Kawahara equation on the line

First, by using linear and trilinear estimates in Bourgain type analytic and Gevrey spaces, the local well‐posedness of the Cauchy problem for the modified Kawahara equation on the line is established for analytic initial data that can be extended as holomorphic functions in a strip around the x‐axis. Next we use this local result and a Gevrey approximate conservation law to prove that global solutions exist. Furthermore, we obtain explicit lower bounds for the radius of spatial analyticity given by , where can be taken arbitrarily small and c is a positive constant.     

Analysis of risk bounds in partially specified additive factor models

The study of worst case scenarios for risk measures (e.g. the Value at Risk) when the underlying risk vector (or portfolio of risks) is not completely specified is a central topic in the literature on robust risk measurement. In this paper we discuss partially specified factor models as introduced in Bernard et al. (2017) in more detail for the class of additive factor models which admit more explicit results. These results allow to describe in more detail the reduction of risk bounds obtainable by this method in dependence on the degree of positive resp. negative dependence induced by the systematic risk factors. The insight may help in applications of this reduction method to get a better qualitative impression on the range of influence of the partially specified factor structure.     

An interview with Sam C. Saunders

Sam C. Saunders, the son of Elizabeth Cundiff and Winston E. Saunders, was born in Richland, OR, on February 24, 1931. The family moved to La Grande, OR, in 1944, where Sam completed high school and two years at Eastern Oregon College. He then received the BSc degree in Mathematics from the University of Oregon, Eugene, OR, in 1952, and he attended the University of Washington, Seattle, WA, receiving a PhD degree under Z. W. Birnbaum. After graduating, he accepted employment at the Boeing Company in its Mathematical Services Unit and, in 1972, a position as a Full Professor at Washington State University, Pullman, WA, from which he retired in 1996.     

Modeling Thioredoxin Reductase-Like Activity with Cyclic Selenenyl Sulfides: Participation of an NH⋅⋅⋅Se Hydrogen Bond through Stabilization of the Mixed Se−S Intermediate

At the redox-active center of thioredoxin reductase (TrxR), a selenenyl sulfide (Se−S) bond is formed between Cys497 and Sec498, which is activated into the thiolselenolate state ([SH,Se⁻]) by reacting with a nearby dithiol motif ([SH^Cys59,SH^Cys64]) present in the other subunit. This process is achieved through two reversible steps: an attack of a cysteinyl thiol of Cys59 at the Se atom of the Se−S bond and a subsequent attack of a remaining thiol at the S atom of the generated mixed Se−S intermediate. However, it is not clear how the kinetically unfavorable second step progresses smoothly in the catalytic cycle. A model study that used synthetic selenenyl sulfides, which mimic the active site structure of human TrxR comprising Cys497, Sec498, and His472, suggested that His472 can play a key role by forming a hydrogen bond with the Se atom of the mixed Se−S intermediate to facilitate the second step. In addition, the selenenyl sulfides exhibited a defensive ability against H₂O₂-induced oxidative stress in cultured cells, which suggests the possibility for medicinal applications to control the redox balance in cells.     

Order-Stability in Complex Biological,Social, and AI-Systems from Quantum Information Theory

This paper is our attempt, on the basis of physical theory, to bring more clarification on the question “What is life?” formulated in the well-known book of Schrödinger in 1944. According to Schrödinger, the main distinguishing feature of a biosystem’s functioning is the ability to preserve its order structure or, in mathematical terms, to prevent increasing of entropy. However, Schrödinger’s analysis shows that the classical theory is not able to adequately describe the order-stability in a biosystem. Schrödinger also appealed to the ambiguous notion of negative entropy. We apply quantum theory. As is well-known, behaviour of the quantum von Neumann entropy crucially differs from behaviour of classical entropy. We consider a complex biosystem S composed of many subsystems, say proteins, cells, or neural networks in the brain, that is, S=(Si). We study the following problem: whether the compound system S can maintain “global order” in the situation of an increase of local disorder and if S can preserve the low entropy while other Si increase their entropies (may be essentially). We show that the entropy of a system as a whole can be constant, while the entropies of its parts rising. For classical systems, this is impossible, because the entropy of S cannot be less than the entropy of its subsystem Si. And if a subsystems’s entropy increases, then a system’s entropy should also increase, by at least the same amount. However, within the quantum information theory, the answer is positive. The significant role is played by the entanglement of a subsystems’ states. In the absence of entanglement, the increasing of local disorder implies an increasing disorder in the compound system S (as in the classical regime). In this note, we proceed within a quantum-like approach to mathematical modeling of information processing by biosystems—respecting the quantum laws need not be based on genuine quantum physical processes in biosystems. Recently, such modeling found numerous applications in molecular biology, genetics, evolution theory, cognition, psychology and decision making. The quantum-like model of order stability can be applied not only in biology, but also in social science and artificial intelligence.     

A health insurance pricing model based on prevalence rates: Application to critical illness insurance

The Italian health insurance market is currently undersized. The paucity of assured data and the discontinuous statistical surveys carried out by the National Institute of Statistics (ISTAT) represent one of the main obstacles to the insurance market development. The paper sets forth a parametric model to estimate technical basis for health insurance policies when data are limited and only aggregated information on mortality and morbidity is available. The probabilistic framework is based on a multiple state continuous and time inhomogeneous Markov model. We provide an estimate of transition intensities from the healthy state to the sickness state when only prevalence rates of sickness are available, according to an extension and modification of the methodology proposed in Olivieri (1996) for Long Term Care insurance. We assume that mortality intensity of both healthy and sick lives is modelled by two independent Gompertz–Makeham models.     

The ASBM-SA turbulence closure: Taking advantage of structure-based modeling in current engineering CFD codes

Structure-based turbulence models (SBM) carry information about the turbulence structure that is needed for the prediction of complex non-equilibrium flows. SBM have been successfully used to predict a number of canonical flows, yet their adoption rate in engineering practice has been relatively low, mainly because of their departure from standard closure formulations, which hinders easy implementation in existing codes. Here, we demonstrate the coupling between the Algebraic Structure-Based Model (ASBM) and the one-equation Spalart–Allmaras (SA) model, which provides an easy route to bringing structure information in engineering turbulence closures. As the ASBM requires correct predictions of two turbulence scales, which are not taken into account in the SA model, Bradshaw relations and numerical optimizations are used to provide the turbulent kinetic energy and dissipation rate. Attention is paid to the robustness and accuracy of the hybrid model, showing encouraging results for a number of simple test cases. An ASBM module in Fortran-90 is provided along with the present paper in order to facilitate the testing of the model by interested readers.     

Molecular dynamics simulation of poly(3‐hexylthiophene) helical structure In Vacuo and in amorphous polymer surrounding

The stability of poly(3‐hexylthiophene) (P3HT) helical structure has been investigated in vacuo and in amorphous polymer surrounding via molecular dynamics‐based simulations at temperatures below and above the P3HT melting point. The results show that the helical chain remains stable at room temperature both in vacuo and in amorphous surrounding, and promptly loses its structure at elevated temperatures. However, the amorphous surrounding inhibits the destruction of the helix at higher temperatures. In addition, it is shown that the electrostatic interactions do not significantly affect the stability of the helical structure. © 2016 Wiley Periodicals, Inc. J. Polym. Sci., Part B: Polym. Phys. 2016 , 54, 2448–2456     

Simulating ion clustering in potassium thiocyanate aqueous solutions with various ion-water models

Using a molecular dynamics simulation technique,we compared several commonly used ion-water models to describe the microscopic structures and dynamics in KSCN aqueous solutions.Results are compared with observations of femtosecond infrared vibrational-energy transfer and anisotropy measurements.The Jorgensen/TIP4P model is found to provide the best reproduction of clustering properties such as percentage of clustered ions,cluster-size distribution,concentration dependence of the water,and ion-rotation time constants.