Mechanical properties of continuous bamboo fiber-reinforced biobased polyamide 11 composites

This study is devoted to the analysis of the properties of continuous bamboo fiber (BF)-reinforced polyamide 11 (PA 11) composites. The SEM observations highlighted continuity between BFs and the polymeric matrix showing a high density of hydrogen bonds. The comparative calorimetric study of the matrix and its composites showed that the crystallinity of PA 11 was not modified by the presence of bamboo fibers. The physical aging observed in PA 11 is no more observed in composites due to physical interactions between PA 11 and BFs. The mechanical properties were investigated by tensile strength and dynamic mechanical analysis. The introduction of BFs enhanced Young's modulus of the matrix by a factor of 10. The presence of BFs also improved the storage shear modulus G′ over the whole temperature range. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47623.     

An enhanced state estimation for linear parabolic PDE systems with mobile sensors

This paper studies an enhanced state estimation problem of distributed parameter processes modeled by a linear parabolic partial differential equation using mobile sensors. The proposed estimation scheme contains a state estimator and the guidance of mobile sensors, where the spatial domain is decomposed into multiple subdomains according to the number of sensors and each sensor is capable of moving within the respective subdomain. The state estimator is desired to make the state estimation error system exponentially stable while providing an performance bound. The mobile sensor guidance is used to enhance the transient performance of the error system. By the Lyapunov direct technique, an integrated design of state estimator and mobile sensor guidance laws is developed in the form of bilinear matrix inequalities (BMIs) to meet the desired design objectives. Moreover, to make the performance bound as small as possible, a suboptimal enhanced state estimation problem is formulated as a BMI optimization one, which can be solved via an iterative linear matrix inequality algorithm. Finally, numerical simulations are given to show the effectiveness of the proposed method.     

A novel hybridized metaheuristic technique in enhancing the diagnosis of cross-sectional dent damaged offshore platform members

Offshore jacket platforms are widely used for oil and gas extraction as well as transportation in shallow to moderate water depth. Tubular cross-sectional elements are used to construct offshore platforms. Tubular cross sections impart higher resistance against hydrodynamic forces and have high torsional rigidity. During operation, the members can be partially or fully damaged due to lateral impacts. The lateral impacts can be due to ship collisions or through the impact of falling objects. The impact forces can weaken some members that influence the overall performance of the platform. This demonstrates an urgent need to develop a framework that can accurately forecast dent depth as well as dent angle of the affected members. This study investigates the use of an adaptive metaheuristics algorithm to provide automatic detection of denting damage in an offshore structure. The damage information includes dent depth and the dent angle. A model is developed in combination with the percentage of the dent depth of the damaged member and is used to assess the performance of the method. It demonstrates that small changes in stiffness of individual damaged bracing members are detectable from measurements of global structural motion.     

基于差动共焦显微技术的微区拉曼光学系统构建与实验研究

研制了一种基于差动共焦显微技术的微区拉曼光学系统装置,对无机样品进行微区拉曼光谱探测。传统显微共焦拉曼光谱技术没有强调系统的定焦能力,而所研制的光学系统装置利用差动共焦曲线过零点与焦点位置精确对应的特性,采用反馈控制技术,具有长时间定焦功能。在微区拉曼散射信号收集时,采用多模光纤空间耦合技术,以光纤代替传统物理探测针孔,提高了环境抗干扰能力,优化了系统结构和装调性能。实验结果表明:该装置具有较高稳定性,可有效探测单壁碳纳米管在1581.510 cm^-1,2708.065 cm^-1特征峰处的拉曼频移及纯物质硫在153.113 cm^-1,219.917 cm^-1,473.322 cm^-1特征峰处的拉曼频移并且实现碳管的单线检测,满足了光谱探测系统装置设计需求。     

Impact of A134 and E218 Amino Acid Residues of Tropomyosin on Its Flexibility and Function

Tropomyosin (Tpm) is one of the major actin-binding proteins that play a crucial role in the regulation of muscle contraction. The flexibility of the Tpm molecule is believed to be vital for its functioning, although its role and significance are under discussion. We choose two sites of the Tpm molecule that presumably have high flexibility and stabilized them with the A134L or E218L substitutions. Applying differential scanning calorimetry (DSC), molecular dynamics (MD), co-sedimentation, trypsin digestion, and in vitro motility assay, we characterized the properties of Tpm molecules with these substitutions. The A134L mutation prevented proteolysis of Tpm molecule by trypsin, and both substitutions increased the thermal stability of Tpm and its bending stiffness estimated from MD simulation. None of these mutations affected the primary binding of Tpm to F-actin; still, both of them increased the thermal stability of the actin-Tpm complex and maximal sliding velocity of regulated thin filaments in vitro at a saturating Ca²⁺ concentration. However, the mutations differently affected the Ca²⁺ sensitivity of the sliding velocity and pulling force produced by myosin heads. The data suggest that both regions of instability are essential for correct regulation and fine-tuning of Ca²⁺-dependent interaction of myosin heads with F-actin.     

Pseudospectral method for assessing stability robustness for linear time-periodic delayed dynamical systems

The article presents a pseudospectral approach to assess the stability robustness of linear time-periodic delay systems, where periodic functions potentially present discontinuities and the delays may also periodically vary in time. The considered systems are subject to linear real-valued time-periodic uncertainties affecting the coefficient matrices, and the presented method is able to fully exploit structure and potential interdependencies among the uncertainties. The assessment of robustness relies on the computation of the pseudospectral radius of the monodromy operator, namely, the largest Floquet multiplier that the system can attain within a given range of perturbations. Instrumental to the adopted novel approach, a solver for the computation of Floquet multipliers is introduced, which results into the solution of a generalized eigenvalue problem which is linear w.r.t. (samples of) the original system matrices. We provide numerical simulations for popular applications modeled by time-periodic delay systems, such as the inverted pendulum subject to an act-and-wait controller, a single-degree-of-freedom milling model and a turning operation with spindle speed variation.     

Dynamic Oscillation via Negative Differential Resistance in Type III Junction Organic/Two-Dimensional and Oxide/Two-Dimensional Transition Metal Dichalcogenide Diodes

Among many of 2D semiconductor-based devices, type III PN junction diodes are given special attentions due to their unique function, negative differential resistance (NDR). However, it has been found uneasy to achieve well-matched type III PN junctions from 2D–2D van der Waals heterojunctions. Here, the authors present other alternatives of type III heterojunctions, using 2D p-MoTe₂/organic n-type dipyrazino[2,3-f:2′,3′-h]quinoxaline-2,3,6,7,10,11-hexacarbonitrile (HAT-CN) and 2D p-WSe₂/n-MoO_x systems. Those junction diodes appear to well-demonstrate static and dynamic NDR behavior via resonant tunneling and electron–hole recombination. Extended to an inverter circuit, p-MoTe₂/n-HAT-CN diode enables multilevel inverter characteristics as monolithically integrated with p-MoTe₂ channel field effect transistor. The same NDR diode shows dynamic LC oscillation behavior under a constant DC voltage, connected to an external inductor. From p-WSe₂/n-MoO_x oxide diode, similar NDR behavior to those of p-MoTe₂/n-HAT-CN is again observed along with LC oscillations. The authors attribute these visible oscillation results to high peak-to-valley current ratios of their organic or oxide/2D heterojunction diodes.     

Neural network-based hybrid models developed for free radical polymerization of styrene

In the present work, the free radical polymerization of styrene is modeled by considering the phenomenology of the process (a simplified model, which does not include the diffusional effects, gel, and glass effects) in combination with an empirical model represented by an artificial neural network. Differential evolution (DE) algorithm, belonging to the class of evolutionary algorithms, is applied for developing the neural models in optimal forms. For improving the results—predicted conversion and molecular weights as function of time, temperature, and initiator concentration—different combinations between phenomenological model and neural network are tested; also, individual and stacked neural networks have been developed for the polymerization process. This methodology based on hybrid models, including neural networks aggregated in stacks, provides accurate results.