Gauss’ law of error revisited in the framework of Sharma-Taneja-Mittal information measure

We reformulate the Gauss’ law of error in presence of correlations which are taken into account by means of a deformed product arising in the framework of the Sharma-Taneja-Mittal measure. Having reviewed the main proprieties of the generalized product and its related algebra, we derive, according to the Maximum Likelihood Principle, a family of error distributions with an asymptotic power-law behavior.      

The Wigner–Yanase information can increase under phase sensitive incoherent operations

We found that the Wigner-Yanase skew information, which has been recently proposed as a measure of coherence in Girolami (2014), can increase under a class of operations which may be interpreted as incoherent following the framework of Baumgratz et al., while being phase sensitive.     

Simultaneous derivatization and air-assisted liquid–liquid microextraction of some aliphatic amines in different aqueous samples followed by gas chromatography-flame ionization detection

The paper presents a new method based on simultaneous derivatization and air-assisted liquid–liquid microextraction (AALLME) for the extraction and preconcentration of some aliphatic amines prior to gas chromatography-flame ionization detection (GC-FID). Primary aliphatic amines are derivatized and extracted simultaneously by a fast reaction with butylchloroformate (derivatization agent/extraction solvent) under mild conditions. The mixture of butylchloroformate and aqueous sample solution is rapidly sucked into a 10-mL glass syringe and then is injected into a test tube with conical bottom and the procedure is repeated seven times. After centrifuging the resulted cloudy solution, the derivatized analytes in the sedimented phase are determined by GC-FID. The influence of main factors on the efficiency of derivatization/extraction procedure is studied. Under the optimal conditions, the enrichment factors (EFs) for aliphatic amines are obtained in the range of 248–360 and limits of detection (LODs) are between 0.30 and 2.6 μg L⁻¹. The obtained extraction recoveries ranged from 50 to 72% and the relative standard deviation (RSD) was less than 4.8% for intra-day (n = 6) and inter-days (n = 4) precision. The method is successfully applied to determine some aliphatic amines in environmental water samples.     

A new approach to pointwise heat kernel upper bounds on doubling metric measure spaces

On doubling metric measure spaces endowed with a strongly local regular Dirichlet form, we show some characterisations of pointwise upper bounds of the heat kernel in terms of global scale-invariant inequalities that correspond respectively to the Nash inequality and to a Gagliardo–Nirenberg type inequality when the volume growth is polynomial. This yields a new proof and a generalisation of the well-known equivalence between classical heat kernel upper bounds and relative Faber–Krahn inequalities or localised Sobolev or Nash inequalities. We are able to treat more general pointwise estimates, where the heat kernel rate of decay is not necessarily governed by the volume growth. A crucial role is played by the finite propagation speed property for the associated wave equation, and our main result holds for an abstract semigroup of operators satisfying the Davies–Gaffney estimates.     

The long‐term extreme price risk measure of portfolio in inventory financing: An application to dynamic impawn rate interval

Different from the short‐term risk measure for traditional financial assets (stocks, bonds, etc.), the key to illiquid inventory portfolio traded in the over‐the‐counter markets is to estimate the long‐term extreme price risk with time varying volatility. In this article, a new long‐term extreme price risk (value at risk and conditional value at risk) measure method for inventory portfolio and an application to dynamic impawn rate interval are proposed. To realize this, we first establish AutoRegressive Moving Average‐Exponential Generalized Autoregressive Conditional Heteroskedasticity‐Extreme Value Theory model and multivariatet‐Copula to depict the autocorrelation, fat tails, and volatility clustering of returns of inventories and the nonlinear dependence structure of inventories. Furthermore, we obtain the long‐term extreme price risk with time varying volatility via Monte Carlo simulation instead of square‐root‐of time rule. The results show that, first, benefits from risk diversification is significant; second, long‐term extreme price risk measure of inventory portfolio via Monte Carlo method outperforms the square‐root‐of time rule; the last is that the dynamic rate interval based on the long‐term price risk is superior to the crude rules of thumb in terms of reducing efficiency loss and improving risk coverage. In summary, this article provides a new quantitative framework for managing the risk of portfolio in inventory financing practice for banks constrained by risk limitation. © 2014 Wiley Periodicals, Inc. Complexity 20: 17–34, 2015     

SiOx encapsulated FeSi2–Si eutectic nanoparticles as durable anode of lithium-ion batteries

Low-cost and high-efficiency production of silicon-based material is the key to improve the energy density of lithium-ion batteries. Herein, we propose a novel structure of FeSi₂–Si eutectic nanoparticles protected by the SiO_x shell. FeSi₂, as a buffer phase can improve the electrochemical stability of the electrode. A SiO_x shell is formed on the surface of the nanoparticles through the passivation process. SiO_x encapsulated FeSi₂–Si eutectic nanoparticles exhibit excellent capacity of 674.9 mAh/g after 500 charge/discharge cycles. The capacity retention rate is above 90% after the stabilization process. This work provides a new nanomaterial design for high performance silicon-based anode materials of lithium-ion batteries.