Stability and cytotoxicity study of NiFe2O4 nanocomposites synthesized by co-precipitation and subsequent thermal annealing

In this article, NiFe₂O₄ nanoparticles (NPs) were prepared by co-precipitation method with subsequent thermal annealing leading to obtainment NPs with average sizes of 78 nm. Structure and magnetic analysis were performed by X-ray diffraction, transmission electron microscopy, Mössbauer spectroscopy and vibrating sample magnetometry techniques. Stability of NiFe₂O₄ NPs was evaluated in PBS solution during 20 days. The toxicity of prepared NPs was evaluated in vitro using different cancer cell lines: HeLa (cervical cancer cell), PC-3 (prostate cancer cell). Fibroblasts like cells of L929 obtained from subcutaneous adipose tissue of mouse were used as normal cells. Results indicate successful synthesis of NiFe₂O₄ NPs that exhibit low cytotoxicity in concentration range from 1 to 100 μg/ml. Presented physical and biological results indicate the possibility of application investigated magnetic nanoparticles in hyperthermia, targeted drug delivery, magnetic resonance imaging or cell separation.     

Sol-gel synthesis,structural, morphological and magnetic properties of BaTiO3–BiMnO3 solid solutions

In this study, solid solutions of (1-x)BaTiO₃-xBiMnO₃ have been synthesized by an aqueous sol-gel method. It was determined that single-phase compounds can be obtained up to x = 0.6 and with further increase in percentage of BiMnO₃ component additional crystal phases were detected. Perovskite crystal structure was determined for all synthesized compounds regardless of chemical composition. Raman spectra of synthesized solid solutions showed gradual change of the shape with an increase of BiMnO₃ fraction. It was demonstrated that partial substitution of BaTiO₃ by BiMnO₃ led to the drastic growth of grains of the end products. Magnetization measurements showed that all BiMnO₃-containing samples are characterized by paramagnetic behavior. Clear correlation between magnetization values and composition of the materials was observed, magnetization values increased with increasing of BiMnO₃ content in solid solutions.     

三维圆弧型井眼轨道设计模型的拟解析解

为了研究三维圆弧型井眼轨道设计方程组是否存在解析解以及如何有效求解，使用消去法从多元非线性方程组中推导出其中的某个未知数满足一个特征多项式方程，并且证明了该方程组的拟解析解可以由特征多项式方程的实数根和已知设计参数构成的解析公式计算得到；如果极点多项式非恒等于0，则当特征多项式次数不超过5时，如果有解则为解析解，否则为数值解。通过使用C++类实现多项式加减法、乘法的计算方法，提出了多项式实数根的分隔算法、并用二分法快速求解出多项式全部实数根的计算方案。该方法在数学上经严格推导，计算方案简洁、稳健，在三维井眼轨道设计、智能钻井定向控制中具有应用价值。     

Thermodynamic assessment of the Ga–Se–Te system

In this study, the Ga–Te binary system was reassessed by means of the CALPHAD method using a modified lattice stability parameter for Te as well as experimental data for this binary system. The two-sublattice ionic solution model was applied for the liquid phase, and the intermediate phases were described by the sublattice model. A set of self-consistent thermodynamic parameters was optimized for all the phases in the Ga–Te binary system, which reproduced the phase diagram and the thermodynamic properties well. Using the reevaluated Ga–Te system, previously assessed Ga–Se system, and modified Se–Te system, a critical evaluation of the Ga–Se–Te ternary system was performed. The calculated vertical sections, isothermal sections, and liquidus projection agreed reasonably well with the experimental data. Immiscibility in the liquid phase was observed, and the origin of this behavior is discussed from a thermodynamic perspective.     

内热型超声雾化溶液再生系统最优内热量的研究

基于质量守恒、能量守恒定律，建立了内热型超声雾化溶液再生系统（IH-UARS）的再生性能预测模型并进行了充分的实验验证，通过研究不同内热量下IH-UARS的再生性能及其变化规律，寻求系统所需的最佳内热量并明确其可能的影响因素。结果表明：IH-UARS系统存在最优的内热量范围，使其再生系统性能最佳；所需最优内热量随着再生溶液流量增大呈显著的对数增长，但受空气流量的影响较弱；在该研究中的标准工况下，IH-UARS所需最优内热量约为275~350 W。此外研究发现：内热量的增长有益于促进初始浓度较高的溶液进一步浓缩再生，如当IH-UARS中内热量增至800 W时，其初始浓度为36%的溶液比24%的溶液浓度增量指标改善幅度高37%。研究所得结果可对提高溶液再生性能及经济性提供积极参考。     

Power system state estimation using a direct non-iterative method

This paper describes a new method for state estimation of a non-linear AC power system in a non-iterative manner. This method is based on the Kipnis–Shamir relinearization technique that is used to solve over-defined sets of polynomial equations. The technique transforms the equations to a higher dimensional linear space which allows the states to be solved in a non-iterative manner. Given accurate measurements, this new state estimation method provides the same results as traditional iterative state estimation methods, and the proposed method does not require an initial guess of system states nor does it have issues with convergence.     

A Method for Systematic Assessment of Intrinsically Disordered Protein Regions by NMR

Intrinsically disordered proteins (IDPs) that lack stable conformations and are highly flexible have attracted the attention of biologists. Therefore, the development of a systematic method to identify polypeptide regions that are unstructured in solution is important. We have designed an “indirect/reflected” detection system for evaluating the physicochemical properties of IDPs using nuclear magnetic resonance (NMR). This approach employs a “chimeric membrane protein”-based method using the thermostable membrane protein PH0471. This protein contains two domains, a transmembrane helical region and a C-terminal OB (oligonucleotide/oligosaccharide binding)-fold domain (named NfeDC domain), connected by a flexible linker. NMR signals of the OB-fold domain of detergent-solubilized PH0471 are observed because of the flexibility of the linker region. In this study, the linker region was substituted with target IDPs. Fifty-three candidates were selected using the prediction tool POODLE and 35 expression vectors were constructed. Subsequently, we obtained ¹⁵N-labeled chimeric PH0471 proteins with 25 IDPs as linkers. The NMR spectra allowed us to classify IDPs into three categories: flexible, moderately flexible, and inflexible. The inflexible IDPs contain membrane-associating or aggregation-prone sequences. This is the first attempt to use an indirect/reflected NMR method to evaluate IDPs and can verify the predictions derived from our computational tools.     

Adaptive backstepping repetitive learning control design for nonlinear discrete‐time systems with periodic uncertainties

This paper addresses a tracking problem for uncertain nonlinear discrete‐time systems in which the uncertainties, including parametric uncertainty and external disturbance, are periodic with known periodicity. Repetitive learning control (RLC) is an effective tool to deal with periodic unknown components. By using the backstepping procedures, an adaptive RLC law with periodic parameter estimation is designed. The overparameterization problem is overcome by postponing the parameter estimation to the last backstepping step, which could not be easily solved in robust adaptive control. It is shown that the proposed adaptive RLC law without overparameterization can guarantee the perfect tracking and boundedness of the states of the whole closed‐loop systems in presence of periodic uncertainties. In addition, the effectiveness of the developed controller is demonstrated by an implementation example on a single‐link flexible‐joint robot. Copyright © 2014 John Wiley & Sons, Ltd.     

Exact and Approximate Solutions of Thermoelastic Stresses in Functionally Graded Cylinders

Thermoelasticity behavior of functionally graded thick hollow cylinders with power law and exponentially variations of material properties versus radius is studied analytically. Temperature, displacement and thermomechanical stress distributions are obtained and discussed. Approximate homogeneous multilayer semi-analytical method is used successfully with adequate accuracy and finite layers. Different combinations of ceramics and metals are checked out for thermoelastic stresses due to high temperature and internal pressure. We conclude that the approximate method is simple and has appropriate results. The effects of high temperature on the stresses are more important than the high internal pressure.     

The Investigation of the Fractional-View Dynamics of Helmholtz Equations Within Caputo Operator

It is eminent that partial differential equations are extensively meaningful in physics, mathematics and engineering. Natural phenomena are formulated with partial differential equations and are solved analytically or numerically to interrogate the system’s dynamical behavior. In the present research, mathematical modeling is extended and the modeling solutions Helmholtz equations are discussed in the fractional view of derivatives. First, the Helmholtz equations are presented in Caputo’s fractional derivative. Then Natural transformation, along with the decomposition method, is used to attain the series form solutions of the suggested problems. For justification of the proposed technique, it is applied to several numerical examples. The graphical representation of the solutions shows that the suggested technique is an accurate and effective technique with a high convergence rate than other methods. The less calculation and higher rate of convergence have confirmed the present technique’s reliability and applicability to solve partial differential equations and their systems in a fractional framework.