Bayesian robustness under a skew-normal class of prior distribution

We develop a global sensitivity analysis to measure the robustness of the Bayesian estimators with respect to a class of prior distributions. This class arises when we consider multiplicative contamination of a base prior distribution. A similar structure was presented by van der Linde [12]. Some particular specifications for this multiplicative contamination class coincide with well known families of skewed distributions. In this paper, we explore the skew-normal multiplicative contamination class for the prior distribution of the location parameter of a normal model. Results of a Bayesian conjugation and expressions for some measures of distance between posterior means and posterior variance are obtained. We also elaborate on the behavior of the posterior means and of the posterior variances through a simulation study.     

Determination of Ti-6242 α and β slip properties using micro-pillar test and computational crystal plasticity

The properties and behaviour of an α−β colony Ti-6242 alloy have been investigated at 20 °C utilising coupled micro-pillar stress relaxation tests and computational crystal plasticity. The β-phase slip strength and intrinsic slip system strain rate sensitivity have been determined, and the β-phase shown to have stronger rate sensitivity than that for the α phase. Close agreement of experimental observations and crystal plasticity predictions of micro-pillar elastic-plastic response, stress relaxation, slip activation in both α and β-phases, and strain localisation within the α−β pillars with differing test strain rate, β morphology, and crystal orientations is achieved, supporting the validity of the properties extracted. The β-lath thickness is found to affect slip transfer across the α−β−α colony, but not to significantly change the nature of the slip localisation when compared to pure α-phase pillars with the same crystallographic orientation. These results are considered in relation to rate-dependent deformation, such as dwell fatigue, in complex multiphase titanium alloys.     

Efficient computation of operator‐type response sensitivities for uncertainty quantification and predictive modeling: illustrative application to a spent nuclear fuel dissolver model

This work honors the 75th birthday of Professor Ionel Michael Navon by presenting original results highlighting the computational efficiency of the adjoint sensitivity analysis methodology for function‐valued operator responses by means of an illustrative paradigm dissolver model. The dissolver model analyzed in this work has been selected because of its applicability to material separations and its potential role in diversion activities associated with proliferation and international safeguards. This dissolver model comprises eight active compartments in which the 16 time‐dependent nonlinear differential equations modeling the physical and chemical processes comprise 619 scalar and time‐dependent model parameters, related to the model's equation of state and inflow conditions. The most important response for the dissolver model is the time‐dependent nitric acid in the compartment furthest away from the inlet, where measurements are available at 307 time instances over the transient's duration of 10.5 h. The sensitivities to all model parameters of the acid concentrations at each of these instances in time are computed efficiently by applying the adjoint sensitivity analysis methodology for operator‐valued responses. The uncertainties in the model parameters are propagated using the above‐mentioned sensitivities to compute the uncertainties in the computed responses. A predictive modeling formalism is subsequently used to combine the computational results with the experimental information measured in the compartment furthest from the inlet and then predict optimal values and uncertainties throughout the dissolver. This predictive modeling methodology uses the maximum entropy principle to construct an optimal approximation of the unknown a priori distribution for the a priori known mean values and uncertainties characterizing the model parameters and the computed and experimentally measured model responses. This approximate a priori distribution is subsequently combined using Bayes' theorem with the “likelihood” provided by the multi‐physics computational models. Finally, the posterior distribution is evaluated using the saddle‐point method to obtain analytical expressions for the optimally predicted values for the parameters and responses of both multi‐physics models, along with corresponding reduced uncertainties. This work shows that even though the experimental data pertains solely to the compartment furthest from the inlet (where the data were measured), the predictive modeling procedure used herein actually improves the predictions and reduces the predicted uncertainties for the entire dissolver, including the compartment furthest from the measurements, because this predictive modeling methodology combines and transmits information simultaneously over the entire phase‐space, comprising all time steps and spatial locations. Copyright © 2016 John Wiley & Sons, Ltd.     

Differences in Salivary Proteins as a Function of PROP Taster Status and Gender in Normal Weight and Obese Subjects

Taste plays an important role in processes such as food choices, nutrition status and health. Salivary proteins contribute to taste sensitivity. Taste reduction has been associated with obesity. Gender influences the obesity predisposition and the genetic ability to perceive the bitterness of 6-n-propylthiouracil (PROP), oral marker for food preferences and consumption. We investigated variations in the profile of salivary proteome, analyzed by HPLC-ESI-MS, between sixty-one normal weight subjects (NW) and fifty-seven subjects with obesity (OB), based on gender and PROP sensitivity. Results showed variations of taste-related salivary proteins between NW and OB, which were differently associated with gender and PROP sensitivity. High levels of Ps-1, II-2 and IB-1 proteins belonging to basic proline rich proteins (bPRPs) and PRP-1 protein belonging to acid proline rich proteins (aPRPs) were found in OB males, who showed a lower body mass index (BMI) than OB females. High levels of Ps-1 protein and Cystatin SN (Cyst SN) were found in OB non-tasters, who had lower BMI than OB super-tasters. These new insights on the role of salivary proteins as a factor driving the specific weight gain of OB females and super-tasters, suggest the use of specific proteins as a strategic tool modifying taste responses related to eating behavior.     

Tunable and highly sensitive temperature sensor based on graphene photonic crystal fiber

Optical fiber temperature sensors have been widely employed in enormous areas ranging from electric power industry, medical treatment, ocean dynamics to aerospace. Recently, graphene optical fiber temperature sensors attract tremendous attention for their merits of simple structure and direct power detecting ability. However, these sensors based on transfer techniques still have limitations in the relatively low sensitivity or distortion of the transmission characteristics, due to the unsuitable Fermi level of graphene and the destruction of fiber structure, respectively. Here, we propose a tunable and highly sensitive temperature sensor based on graphene photonic crystal fiber (Gr-PCF) with the non-destructive integration of graphene into the holes of PCF. This hybrid structure promises the intact fiber structure and transmission mode, which efficiently enhances the temperature detection ability of graphene. From our simulation, we find that the temperature sensitivity can be electrically tuned over four orders of magnitude and achieve up to ～ 3.34×10^-3 dB/(cm·℃) when the graphene Fermi level is ～ 35 meV higher than half the incident photon energy. Additionally, this sensitivity can be further improved by ～ 10 times through optimizing the PCF structure (such as the fiber hole diameter) to enhance the light-matter interaction. Our results provide a new way for the design of the highly sensitive temperature sensors and broaden applications in all-fiber optoelectronic devices.     

Direct and adjoint global stability analysis of turbulent transonic flows over a NACA0012 profile

In this work, various turbulent solutions of the two‐dimensional (2D) and three‐dimensional compressible Reynolds averaged Navier–Stokes equations are analyzed using global stability theory. This analysis is motivated by the onset of flow unsteadiness (Hopf bifurcation) for transonic buffet conditions where moderately high Reynolds numbers and compressible effects must be considered. The buffet phenomenon involves a complex interaction between the separated flow and a shock wave. The efficient numerical methodology presented in this paper predicts the critical parameters, namely, the angle of attack and Mach and Reynolds numbers beyond which the onset of flow unsteadiness appears. The geometry, a NACA0012 profile, and flow parameters selected reproduce situations of practical interest for aeronautical applications. The numerical computation is performed in three steps. First, a steady baseflow solution is obtained; second, the Jacobian matrix for the RANS equations based on a finite volume discretization is computed; and finally, the generalized eigenvalue problem is derived when the baseflow is linearly perturbed. The methodology is validated predicting the 2D Hopf bifurcation for a circular cylinder under laminar flow condition. This benchmark shows good agreement with the previous published computations and experimental data. In the transonic buffet case, the baseflow is computed using the Spalart–Allmaras turbulence model and represents a mean flow where the high frequency content and length scales of the order of the shear‐layer thickness have been averaged. The lower frequency content is assumed to be decoupled from the high frequencies, thus allowing a stability analysis to be performed on the low frequency range. In addition, results of the corresponding adjoint problem and the sensitivity map are provided for the first time for the buffet problem. Finally, an extruded three‐dimensional geometry of the NACA0012 airfoil, where all velocity components are considered, was also analyzed as a Triglobal stability case, and the outcoming results were compared to the previous 2D limited model, confirming that the buffet onset is well detected. Copyright © 2014 John Wiley & Sons, Ltd.     

Synthesis of Stimuli-responsive Nanoparticles by Solution Polymerization

In this study, stimuli-responsive nanoparticles were prepared by solution polymerization. Two synthesis routes are proposed to synthesize the particles, the monomer route and the polymer/monomer route. For the monomer route, pH and thermal sensitive nanoparticles were synthesized from acrylic acid and N-isopropylacrylamide. For the polymer/monomer route, the pH sensitive nanoparticles were synthesized from chitosan and acrylic acid. The effect of reaction time, initiator concentration and agitation rate on the particle size and the size distribution were investigated. The stimuli-responsive nanoparticles could be directly blended with other polymers to prepare stimuli-responsive functional membranes.     

The Copolymerization of Alkenes with Maleic Anhydride

The investigations presented deal with the experimental results of the copolymerization of maleic anhydride (MAn) with alkenes. The course of the reaction is explained by the overall rate of the copolymerization (v _Br), which correlates with the solution viscosity of the copolymer, and the dependence of the v _Br maximum on the mole ratio of the monomers at constant total monomer concentration. The use of solvents with increasing donor power leads to increased complexing of the free MAn molecules and of the MAn radical chain ends. The results demonstrate that, for low 1-alkenes, the addition of the MAn chain radical is the rate-determining step of the copolymerization. As the substituents on the olefinic double bond become larger or the double bond shifts to the 1,2-position, the addition of MAn to the hydrocarbon radical becomes more and more the rate-determining step. On the other hand, an increase of the CT complexation of the MAn polymer radical by use of donor solvents decreases the alkene addition rate.     

基于3,6-二肼基-1,2,4,5-四嗪的两种高氮含能离子盐

本文通过3,6-二肼基-1,2,4,5-四嗪(DHT)分别与高氯酸和硝酸反应得到2种高氮含能离子盐,并通过X-射线单晶衍射技术对它们的结构进行了表征。(DHT)(NO₃)₂(1)属于单斜晶系,C2/c空间群,晶胞参数:a=1.3000(6)nm,b=0.8349(3)nm,c=1.0187(5)nm,β=118.89(5)°,Z=4;(DHT)(ClO₄)₂(2)属于正交晶系,P2₁2₁2空间群,晶胞参数:a=0.9804(4)nm,b=1.0747(4)nm,c=0.5325(2)nm,Z=2。采用DSC和TG-DTG技术研究了这两种含能离子盐的热分解机理,并对这两种含能离子盐的非等温动力学、爆热及感度进行了测试分析。研究表明这两种含能离子盐在敏感型含能材料领域具有潜在的应用前景。