Particle systems on flows

We start with a stochastic flow of diffeomorphisms of the space. Particles enter the space at random times and places. Each particle is carried by the flow for some random amount of time. We examine the point process formed by the particles at a fixed time, on the evolution of that point process as time varies, and on the equilibrium law of the point process.     

Bioengineering functional copolymers. III. Synthesis of biocompatible poly[(N‐isopropylacrylamide‐co‐maleic anhydride)‐g‐poly(ethylene oxide)]/poly(ethylene imine) macrocomplexes and their thermostabilization effect on the activity of the enzyme penicillin G acylase

Stimuli‐responsive poly[(N‐isopropylacrylamide‐co‐maleic anhydride)‐g‐poly(ethylene oxide)]/poly(ethylene imine) macrobranched macrocomplexes were synthesized by (1) the radical copolymerization of N‐isopropylacrylamide and maleic anhydride with α,α′‐azobisisobutyronitrile as an initiator in 1,4‐dioxane at 65 °C under a nitrogen atmosphere, (2) the polyesterification (grafting) of prepared poly(N‐isopropylacrylamide‐co‐maleic anhydride) containing less than 20 mol % anhydride units with α‐hydroxy‐ω‐methoxy‐poly(ethylene oxide)s having different number‐average molecular weights (M_n = 4000, 10,000, or 20,000), and (3) the incorporation of macrobranched copolymers with poly(ethylene imine) (M_n = 60,000). The composition and structure of the synthesized copolymer systems were determined by Fourier transform infrared, ¹H and ¹³C NMR spectroscopy, and chemical and elemental analyses. The important properties of the copolymer systems (e.g., the viscosity, thermal and pH sensitivities, and lower critical solution temperature behavior) changed with increases in the molecular weight, composition, and length of the macrobranched hydrophobic domains. These copolymers with reactive anhydride and carboxylic groups were used for the stabilization of penicillin G acylase (PGA). The conjugation of the enzyme with the copolymers significantly increased the thermal stability of PGA (three times at 45 °C and two times at 65 °C). © 2003 Wiley Periodicals, Inc. J Polym Sci Part A: Polym Chem 41: 1580–1593, 2003     

Hyperon production in pp interactions at √s = 53 and 62 GeV

Inclusive measurements of Λ⁰, $\text{Λ}$⁰, Ξ^?, Σ(1385)^±) production in the forward direction at the CERN intersecting storage rings are presented. A signal for simulataneous Λ⁰$\text{Λ}$⁰ production is also observed with total $\text{x > 0.6, 2.3 < M}{}_{\mathrm{<mtext>\Lambda </mtext><mtext>\Lambda </mtext>}}\text{< 2.5}\text{GeV}$ and with a cross section of (1.7 ± 0.2) μb.     

The spin-1 Blume-Capel model with random crystal field on the Bethe lattice

The dependence of the phase diagrams on the random crystal field (RCF) is investigated for the spin-1 Blume-Capel (BC) model on the Bethe lattice. The calculations are carried out in terms of the recursion relations for the coordination number z=4 which corresponds to the square lattice. The model presents tricritical points which are observed at lower negative crystal fields and higher temperatures for higher probabilities p and which vanish at lower p’s. The effect of randomness is illustrated for p=0.5 and shown that it changes the phase diagrams drastically from random to non-random systems. The reentrant behavior is also observed for appropriate p values.     

Thermal entanglement in the XYZ model for a two-qutrit system

The negativity as a measure of thermal entanglement was studied for a two-qutrit spin-1 anisotropic Heisenberg XYZ chain with Dzyaloshinskii-Moriya (DM) interaction in a homogeneous magnetic field in detail. An analytical expression was found for the negativity and then the thermal variations of negativity were investigated in full detail for given values of the DM interaction parameter D_z, the external magnetic field B, the measure of the anisotropy on the xy-plane γ = (J_x − J_y)/(J_x + J_y), a parameter J = (J_x + J_y)/2 and the bilinear interaction parameter J_z along the z-axis.     

Minimizing the probability of lifetime ruin under stochastic volatility

We assume that an individual invests in a financial market with one riskless and one risky asset, with the latter’s price following a diffusion with stochastic volatility. Given the rate of consumption, we find the optimal investment strategy for the individual who wishes to minimize the probability of going bankrupt. To solve this minimization problem, we use techniques from stochastic optimal control.