Effect of microwave heating time on the gel properties of chicken myofibrillar proteins and their formation mechanism

The present work was conducted to illustrate the mechanism of gel formation of myofibrillar proteins (MPs) under different microwave heating times. The results showed that the denaturation enthalpy (ΔH) of the MPs significantly decreased when the heating time increased from 3 to 9 s and then completely disappeared as the heating time progressed, indicating that the MPs gradually denatured and subsequently aggregated with increasing heating time, which was further verified by the changes in the secondary structure, electrophoretic bands, and gel properties (e.g., water holding capacity and textural profiles) of the MPs. Microstructural images indicated that the MP gel formed under 12 s had the most compact network, indicating that extended microwave heating time could induce quality deterioration of MP gels. Moreover, the hydrophobic forces, electrostatic forces, and disulphide bonds of the MPs gradually intensified with increasing microwave heating time, suggesting that both non-covalent and covalent bonds could promote molecular denaturation and subsequent aggregation of MPs. In addition, correlation analysis revealed that the changes in the molecular conformation of MPs induced by different microwave heating times could effectively regulate the formation of MP gels and their related properties.     

Influence of Se and Te substitutions at Tl-site of Tl(Ba,Sr)CaCu2O7 superconductor on the AC susceptibility and electrical properties

The Sr and Ba bearing Tl-1212 phase, Tl(Ba,Sr)CaCu₂O₇ is an interesting superconductor. The Sr only bearing TlSr₂CaCu₂O₇ is not easily prepared in the superconducting form. The Ba only bearing TlBa₂CaCu₂O₇ on the other hand does not show improvement in the transition temperature with elemental substitution. In this work the influence of multivalent Se (non-metal) and Te (metalloid) substitutions at the Tl-site of Tl_1-xM_x(Ba,Sr)CaCu₂O₇ (M = Se or Te) superconductors for x = 0–0.6 was studied. The samples were prepared via the conventional solid-state reaction method. XRD patterns showed a single Tl-1212 phase for x = 0 and 0.1 Se substituted samples. The critical current density at the peak temperature, T_p of the imaginary (χ”) part of the AC susceptibility (χ = χ’ +χ”), J_c-inter(T_p) for all samples was between 15 and 21 A cm⁻². The highest superconducting transition temperature was shown by the x = 0.3 Se-substituted sample (T_c-onset = 104 K, T_c-zero = 89 K, T_cχ’ = 104 K and T_p = 80 K). Te suppressed the superconductivity of Tl-1212 phase. The order of highest transition temperatures are as follows: Tl_1-xTe_x(Ba,Sr)CaCu₂O₇<Tl(Ba,Sr)CaCu₂O₇<Tl_1-xSe_x(Ba,Sr)CaCu₂O₇. This work showed that Se was better than Te in improving the transition temperature and flux pinning of the Tl-1212 phase. The roles of ionic radius of Se and Te on the superconductivity of Tl(Ba,Sr)CaCu₂O₇ are discussed in this paper.     

Maximum likelihood-based adaptive differential evolution identification algorithm for multivariable systems in the state-space form

Parameter estimation plays an important role in the field of system control. This article is concerned with the parameter estimation methods for multivariable systems in the state-space form. For the sake of solving the identification complexity caused by a large number of parameters in multivariable systems, we decompose the original multivariable system into some subsystems containing fewer parameters and study identification algorithms to estimate the parameters of each subsystem. By taking the maximum likelihood criterion function as the fitness function of the differential evolution algorithm, we present a maximum likelihood-based differential evolution (ML-DE) algorithm for parameter estimation. To improve the parameter estimation accuracy, we introduce the adaptive mutation factor and the adaptive crossover factor into the ML-DE algorithm and propose a maximum likelihood-based adaptive differential evolution algorithm. The simulation study indicates the efficiency of the proposed algorithms.     

Control theory for stochastic distributed parameter systems,an engineering perspective

The main purpose of this paper is to survey some recent progresses on control theory for stochastic distributed parameter systems, i.e., systems governed by stochastic differential equations in infinite dimensions, typically by stochastic partial differential equations. We will explain the new phenomenon and difficulties in the study of controllability and optimal control problems for one dimensional stochastic parabolic equations and stochastic hyperbolic equations. In particular, we shall see that both the formulation of corresponding stochastic control problems and the tools to solve them may differ considerably from their deterministic/finite-dimensional counterparts. More importantly, one has to develop new tools, say, the stochastic transposition method introduced in our previous works, to solve some problems in this field.     

A Global Maximum Error Controller Based Nonlinearity Aware TPWL Method for Reducing Nonlinear Systems

Abstract

Model order reduction is a common practice to reduce large order systems so that their simulation and control become easy. Nonlinearity aware trajectory piecewise linear is a variation of trajectory piecewise linearization technique of order reduction that is used to reduce nonlinear systems. With this scheme, the reduced approximation of the system is generated by weighted sum of the linearized and reduced sub-models obtained at certain linearization points on the system trajectory. This scheme uses dynamically inspired weight assignment that makes the approximation nonlinearity aware. Just as weight assignment, the process of linearization points selection is also important for generating faithful approximations. This article uses a global maximum error controller based linearization points selection scheme according to which a state is chosen as a linearization point if the error between a current reduced model and the full order nonlinear system reaches a maximum value. A combination that not only selects linearization points based on an error controller but also assigns dynamic inspired weights is shown in this article. The proposed scheme generates approximations with higher accuracies. This is demonstrated by applying the proposed method to some benchmark nonlinear circuits including RC ladder network and inverter chain circuit and comparing the results with the conventional schemes.     

Maximum Data Generation Rate Routing Protocol Based on Data Flow Controlling Technology for Rechargeable Wireless Sensor Networks

For rechargeable wireless sensor networks, limited energy storage capacity, dynamic energy supply, low and dynamic duty cycles cause that it is unpractical to maintain a fixed routing path for packets delivery permanently from a source to destination in a distributed scenario. Therefore, before data delivery, a sensor has to update its waking schedule continuously and share them to its neighbors, which lead to high energy expenditure for reestablishing path links frequently and low efficiency of energy utilization for collecting packets. In this work, we propose the maximum data generation rate routing protocol based on data flow controlling technology. For a sensor, it does not share its waking schedule to its neighbors and cache any waking schedules of other sensors. Hence, the energy consumption for time synchronization, location information and waking schedule shared will be reduced significantly. The saving energy can be used for improving data collection rate. Simulation shows our scheme is efficient to improve packets generation rate in rechargeable wireless sensor networks.     

Association of solid fuel use with risk of stunting in children living in China

Stunting adversely affects physical and mental outcomes of children. It has not been examined whether household air pollution from solid fuel combustion is a risk factor for stunting in children. In a total of 41,439 children aged 6-17 across China, height was measured using a unified protocol. Multivariable linear regression models and logistic regression models were used to assess the associations of solid fuel use for cooking/heating with stunting in children. Adjusted for covariates, cooking/heating with solid fuel was significantly associated with a lower z-score for height for age and sex (β = −0.21 [−0.32 to −0.09] and −0.17 [−0.31 to −0.03], respectively) and an increased risk of stunting with an estimated ORs of 1.34 [1.07~1.68] and 1.37 [1.02~1.83], respectively. The risk of stunting associated with solid fuel use was statistically significant in high-age children. And the effect was greater on girls than on boys, though the difference was not statistically significant. Our study suggested that Chinese children living in households using solid fuel had a significantly higher risk of stunting than those living in households using cleaner fuel.     

Structures and properties of chicken myofibrillar protein gel induced by microwave heating

Structures and properties of myofibrillar protein gel prepared at different power (300–800 W) were evaluated. Amino acid analysis demonstrated that changes in microwave power did not alter primary structure of gel. However, an increase in microwave power could change higher structures of gel. As microwave power increased, α-helix content decreased and β-sheet content increased. Increased microwave power probably facilitated protein to unfold and expose the internal groups, causing surface hydrophobicity and the formation of disulphide bonds were enhanced, which indicated changes in tertiary and quaternary structures of protein. At 500 W, gel had the best ultrastructure where surface morphology, springiness and water holding capacity reached the optimum. Our findings suggested that microwave at an appropriate power (500 W) could change higher structures of myofibrillar protein gel to achieve desired processing and quality protein gel characteristics.     

Estimation of the Stress-Strength Reliability for Exponentiated Pareto Distribution Using Median and Ranked Set Sampling Methods

In reliability analysis, the stress-strength model is often used to describe the life of a component which has a random strength (X) and is subjected to a random stress (Y). In this paper, we considered the problem of estimating the reliability R=P [Y<X] when the distributions of both stress and strength are independent and follow exponentiated Pareto distribution. The maximum likelihood estimator of the stress strength reliability is calculated under simple random sample, ranked set sampling and median ranked set sampling methods. Four different reliability estimators under median ranked set sampling are derived. Two estimators are obtained when both strength and stress have an odd or an even set size. The two other estimators are obtained when the strength has an odd size and the stress has an even set size and vice versa. The performances of the suggested estimators are compared with their competitors under simple random sample via a simulation study. The simulation study revealed that the stress strength reliability estimates based on ranked set sampling and median ranked set sampling are more efficient than their competitors via simple random sample. In general, the stress strength reliability estimates based on median ranked set sampling are smaller than the corresponding estimates under ranked set sampling and simple random sample methods.     

基于热负荷自动调节的延迟焦化加热炉三点注汽量智能优化

针对国内某炼油厂延迟焦化加热炉三点注汽问题，采用热负荷自动调节的算法进行了研究。运用该模型方法，分析了三点注汽量对加热炉热负荷和炉管结焦系数的影响，发现三点注汽量的改变均会对热负荷和炉管结焦系数产生影响，主要表现为提高注汽量将会提高热负荷，同时降低结焦系数；第1点注汽量和第2点注汽量对热负荷和结焦系数的影响较强，第3点注汽量对热负荷和结焦系数的影响较弱。在实际操作中，加热炉中的结焦程度既不能太强也不能太弱，合适的结焦系数能够保证正常开工周期里炉管不结焦，也能保证瓦斯、注汽量等参数的合理分配。通过对热负荷、注汽量的智能分配，可得到不同原料油加工负荷条件下更加合理的装置运行方案。