Terpolymerization of Triisopropylsilyl Acrylate,Methyl Methacrylate,and Butyl Acrylate: Reactivity Ratio Estimation

Ternary monomer reactivity ratios of triisopropylsilyl acrylate (SiA), methyl methacrylate (MMA), and n‐butyl acrylate (BA), as common monomers in self‐polishing coatings (SPCs) binders are obtained using experimental data collected from free radical bulk polymerization at 70 °C. Different terpolymerizations at low and medium‐high conversions are performed at optimized feed compositions. Estimations are made using the error‐in‐variables model (EVM) framework, applying the recast form of the Alfrey–Goldfinger (AG) model and a direct numerical integration (DNI) approach to the collected data. Estimations from individual low and medium‐high conversion data are compared to those found with the combined data (full conversion range data). The highest certainty in point estimates are obtained with analysis of the full conversion range data. Furthermore, the reactivity ratios determined from the combined data fall between those found with analysis of individual low and medium‐high conversion data, another corroboration of reliable data collection. Reactivity ratios determined from analysis of the combined data (r_SiA/MMA = 0.4185, r_MMA/SiA = 1.3754, r_SiA/BA = 0.8739, r_BA/SiA = 0.5736, r_BA/MMA = 0.3692, r_MMA/BA = 1.7919) are used in the recast AG model to predict cumulative terpolymer composition as a function of conversion. The experimental data and model prediction show satisfactory agreement.     

Rate constants of the reactions of O(3P) atoms with Br2 and NO2 over the temperature range 220-950 K

The kinetics of the reactions of Br₂ and NO₂ with ground state oxygen atoms have been studied over a wide temperature range, T = 220-950 K, using a low-pressure flow tube reactor coupled with a quadrupole mass spectrometer: O + NO₂ → NO + O₂ (1) and O + Br₂ → Br + BrO (2). The rate constant of reaction (1) was determined under pseudo–first-order conditions, either monitoring the kinetics of O-atom or NO₂ consumption in excess of NO₂ or of the oxygen atoms, respectively: k₁ = (6.1 ± 0.4) × 10⁻¹² exp((155 ± 18)/T) cm³ molecule⁻¹ s⁻¹ (where the uncertainties represent precision at the 2σ level, the estimated total uncertainty on k₁ being 15% at all temperatures). The temperature dependence of k₁, found to be in excellent agreement with multiple previous low-temperature data, was extended to 950 K. The rate constant of reaction (2) determined under pseudo–first-order conditions, monitoring the kinetics of Br₂ consumption in excess of O-atoms, showed upward curvature at low and high temperatures of the study and was fitted with the following three-parameter expression: k₂ = 9.85 × 10⁻¹⁶ T^1.41 exp(543/T) cm³ molecule⁻¹ s⁻¹ at T = (220-950) K, which is recommended from the present study with an independent of temperature conservative uncertainty of 15% on k₂.     

Quantitative estimations of bivariate summation‐integral–type operators

In this paper, we study the approximation properties of bivariate summation‐integral–type operators with two parameters . The present work deals within the polynomial weight space. The rate of convergence is obtained while the function belonging to the set of all continuous and bounded function defined on ([0],∞)(×[0],∞) and function belonging to the polynomial weight space with two parameters, also convergence properties, are studied. To know the asymptotic behavior of the proposed bivariate operators, we prove the Voronovskaya type theorem and show the graphical representation for the convergence of the bivariate operators, which is illustrated by graphics using Mathematica. Also with the help of Mathematica, we discuss the comparison by means of the convergence of the proposed bivariate summation‐integral–type operators and Szász‐Mirakjan‐Kantorovich operators for function of two variables with two parameters to the function. In the same direction, we compute the absolute numerical error for the bivariate operators by using Mathematica and is illustrated by tables and also the comparison takes place of the proposed bivariate operators with the bivariate Szász‐Mirakjan operators in the sense of absolute error, which is represented by table. At last, we study the simultaneous approximation for the first‐order partial derivative of the function.     

Cooling of Al-Cu-Fe-Cr-Ni high entropy alloy with different size

Cooling rate is critical in synthesizing nanoparticles (NPs), which determines the microstructure and the corresponding mechanical, thermal and electrical properties. This research, as the most initiative one, studies microstructure formation of three different sized high entropy alloy (HEA) NPs under three different cooling rates, employing molecular dynamics (MD). Through analysis of potential energy, “common neighbor analysis”, radial distribution function, and also the mean square displacement, it is found that phase transition temperature is independent of HEA NP size, and as cooling rate decrease, more amorphous atoms transform to fcc and hcp orders, which can alternate the mechanical and thermodynamic properties of the final structure. The Cr atoms are found to aggregate into one cluster inside the NP and also try to migrate to the surface of the HEA NP, due to the large diffusivity. This research provides new insights in the size dependency of the nanoparticles, which may motivate more applications in which the strong size dependency is not desirable.     

How vector feeding preference through an infectious host relates to the seasonal transmission rates in a mathematical vector‐host model

Vector‐borne diseases, such as leishmaniasis, dengue, malaria, and yellow fever, transmitted by microparasites show periodic fluctuations in their prevalence. The novelty of this research is to assess the relationship between the vector feeding preference for an infectious host and the annual seasonal transmission through a vector‐host mathematical model. For the first time, numerical simulations illustrate that by increasing the vector feeding preference value in the transmission dynamics, periodic fluctuations accentuate and the endemic equilibrium average increases in vector and host populations. Moreover, increasing the vector feeding preference value, the amplitude strengthens for the infectious host and vector populations. This periodic behavior shows a similar pattern with the Peruvian incidence data from 2000 to 2016 for Andean cutaneous leishmaniasis provided by the Ministry of Health of Peru (MINSA). In addition, using the Floquet theory, the time average method and the linear operator method provides for the first time that the basic reproduction number for a nonautonomous system depends explicitly on the vector feeding preference for the infectious host. The nonautonomous model system shows that is a threshold parameter for the local stability of the disease‐free periodic solution. Therefore, the vector feeding preference is an important factor that should be considered and attended to for future research. Public and veterinary health in Peru and other countries should consider the vector feeding preference for specific host to vector control.     

Synergistic Effects of Pseudocolor Imaging,Differentiation, and Square and Logarithmic Conversion on Accuracy of Quantification of Chemical Characteristics Using Test Strips and Similar Products

Test strips and similar products are highly feasible tools for the rapid and approximate determination of chemical characteristics. Although the application of both the quantitative observation of coloration and regression modeling has recently enabled these products to become quantitative tools, their precision and accuracy may be further improved. In this study, the pseudocolor imaging of the coloration image, derivative spectrophotometry-like differentiation of the coloration values, and logarithmic conversion of the raw and derivative values were compared in terms of the precision and accuracy of the quantitative determination of corrosiveness, glucose, nitrate, and pH using the products. The best regression models for the determination were provided by the combination of pseudocolor imaging and differentiation (nitrate and pH); pseudocolor imaging, differentiation, and square-conversion (corrosiveness); or all of the techniques (glucose). When compared to the use of the original 10 raw coloration variables of red-green-blue, cyan-magenta-yellow-key black, and L*a*b* color models only, the above combinations improved the normalized mean absolute error from 14.8% to 3.09% (corrosiveness), 6.33% to 3.15% (glucose), 7.46% to 4.56% (nitrate), and 3.22% to 0.94% (pH). These achievements were largely attributed to the combination of multiple variables that have non-linear and nonmonotonic relationships with the chemical characteristics.     

Phase segregation of metastable quenched liquid mixtures and the effect of the quenching rate

The effect of the quenching rate on the phase separation of partially miscible liquid mixtures is studied, showing that it may influence the growth rate of single-phase domains. In particular, the phase separation of metastable binary mixtures in the presence of strong emulsifiers appears to be heavily retarded. These effects constitute an important limitation to the phase transition extraction process introduced by the authors in previous works, which is based on the fact that phase separation of unstable mixtures is rapid, even in the presence of surface active compounds.     

Asymptotic analysis for multi-objective sequential stochastic assignment problems

ABSTRACT

We provide an asymptotic analysis of multi-objective sequential stochastic assignment problems (MOSSAP). In MOSSAP, a fixed number of tasks arrive sequentially, with an n-dimensional value vector revealed upon arrival. Each task is assigned to one of a group of known workers immediately upon arrival, with the reward given by an n-dimensional product-form vector. The objective is to maximize each component of the expected reward vector. We provide expressions for the asymptotic expected reward per task for each component of the reward vector and compare the convergence rates for three classes of Pareto optimal policies.     

多种分布下选择后变量显著性分析及其在CEPS数据中的应用

在使用变量选择方法选出模型后,如何评价模型中变量系数的显著性是统计学重点关注的前沿问题之一.文章从适应性Lasso变量选择方法的选择结果出发,在考虑实践中误差分布多样性的前提下,基于选择事件构造了模型保留变量系数的条件检验统计量,并给出了该统计量的一致收敛性质的证明过程.模拟研究显示,在多种误差分布下所提方法均可进一步优化变量选择结果,有较强的实用价值.应用此方法对CEPS学生数据进行了实证分析,最终选取了学生认知能力等10个变量作为影响中学生成绩的主要因素,为相关研究提供了有益的参考.