Optimizing separation conditions for riboflavin,flavin mononucleotide and flavin adenine dinucleotide in capillary zone electrophoresis with laser-induced fluorescence detection

DNA sequencing is performed in a multiplexed capillary electrophoresis system by UV absorption detection. Four individual electropherograms are obtained by simultaneously running the unlabeled DNA products of the four ddNTP-terminated reactions in the capillary array. The sequence of the template used in the cycle-sequencing reaction can be determined by overlaying the four electropherograms. Two internal standards are employed to adjust for the variance in migration times among the capillaries. After applying the correction algorithm, base calling can be done at a high level of confidence.     

Tris[2‐(1,3‐thiazol‐2‐yl‐κN)‐1H‐benzimidazole‐κN3]zinc(II) dinitrate ethanol hemisolvate monohydrate at 100 K

The Zn^II center in the dicationic complex of the title compound, [Zn(C₁₀H₇N₃S)₃](NO₃)₂·0.5C₂H₅OH·H₂O, is in a distorted octahedral environment with imperfect noncrystallographic C₃ symmetry. Each 2‐(1,3‐thiazol‐2‐yl)‐1H‐benzimidazole ligand coordinates in a bidentate manner, with the Zn—N(imidazole) bond lengths approximately 0.14 Å shorter than the Zn—N(thiazole) bond lengths. Charge‐assisted hydrogen bonds connect cations, anions and water molecules. A lattice void is occupied by an ethanol solvent molecule disordered about a crystallographic inversion center and π‐stacking is observed between one type of symmetry‐related benzene rings.     

Cosmological background solutions and cosmological backreactions

The cosmological backreaction proposal, which attempts to account for observations without a primary dark energy source in the stress-energy tensor, has been developed and discussed by means of different approaches. Here, we focus on the concept of cosmological background solutions in order to develop a framework to study different backreaction proposals.     

Antiferromagnetic Potts Models on the Square Lattice: A High-Precision Monte Carlo Study

We study the antiferromagnetic q-state Potts model on the square lattice for q=3 and q=4, using the Wang–Swendsen–Kotecký (WSK) Monte Carlo algorithm and a powerful finite-size-scaling extrapolation method. For q=3 we obtain good control up to correlation length 5000; the data are consistent with ()=Ae ^{2 p} (1+a ₁ e ^– + ...) as , with p1. The staggered susceptibility behaves as _stagg ^5/3. For q=4 the model is disordered (2) even at zero temperature. In appendices we prove a correlation inequality for Potts antiferromagnets on a bipartite lattice, and we prove ergodicity of the WSK algorithm at zero temperature for Potts antiferromagnets on a bipartite lattice.     

Effect of acidity on the formation of silica–chitosan hybrid materials and thermal conductive property

In this study, the formation of silica–chitosan hybrid materials via sol–gel process under pH values of 2–6 were investigated using N₂ sorption analysis, scanning electron microscopy, transmission electron microscopy, thermal analysis and zeta potential analyzer. The hierarchical structure consisting of meso- and macropore was formed when pH value was higher than 2. Mesopores were formed as the interparticle channels of silica nanoparticles aggregates, whereas macropores were the void between the aggregates (clusters). The clusters size was decreased with increasing the pH value, resulting in the increase of the macroporosity. The thermal conductivity of the products was controlled in the range of 0.06 and 0.13 W m⁻¹ K⁻¹ by varying the product porosity between 88 and 69% (pH 6 and pH 2, respectively).     

Pricing and Hedging Asian Basket Options with Quasi-Monte Carlo Simulations

In this article we consider the problem of pricing and hedging high-dimensional Asian basket options by Quasi-Monte Carlo simulations. We assume a Black–Scholes market with time-dependent volatilities, and we compute the deltas by means of the Malliavin Calculus as an extension of the procedures employed by Kohatsu-Higa and Montero (Physica A 320:548–570, 2003). Efficient path-generation algorithms, such as Linear Transformation and Principal Component Analysis, exhibit a high computational cost in a market with time-dependent volatilities. To face this challenge we then introduce a new and faster Cholesky algorithm for block matrices that makes the Linear Transformation more convenient. We also propose a new-path generation technique based on a Kronecker Product Approximation. Our procedure shows the same accuracy as the Linear Transformation used for the computation of deltas and prices in the case of correlated asset returns, while requiring a shorter computational time. All these techniques can be easily employed for stochastic volatility models based on the mixture of multi-dimensional dynamics introduced by Brigo et al. (2004a, Risk 17(5):97–101, b).