Generation and characterization of air micro-bubbles in highly hydrophobic capillaries

The generation of air microbubbles in microfluidic systems or in capillaries could be of great interest for transportation (single cell analysis, organite transportation) or for liquid compartmentation. The physicochemical characterization of air bubbles and a better understanding of the process leading to bubble generation during electrophoresis is also interesting in a theoretical point of view. In this work, the generation of microbubbles on hydrophobic Glaco™ coated capillaries has been studied in water-based electrolyte. Air bubbles were generated at the detection window and the required experimental parameters for microbubbles generation have been identified. Generated bubbles migrated against the electroosmotic flow, as would do strongly negatively charged solutes, under constant electric field. They have been characterized in terms of dimensions, electrophoretic mobility, and apparent charge.     

Multistrain edge‐based compartmental model on networks

Multistrain diseases, which are infected through individual contacts, pose severe public health threat nowadays. In this paper, we build competitive and mutative two‐strain edge‐based compartmental models using probability generation function (PGF) and pair approximation (PA). Both of them are ordinary differential equations. Their basic reproduction numbers and final size formulas are explicitly derived. We show that the formula gives a unique positive final epidemic size when the reproduction number is larger than unity. We further consider competitive and mutative multistrain diseases spreading models and compute their basic reproduction numbers. We perform numerical simulations that show some dynamical properties of the competitive and mutative two‐strain models.     

Laser control of magneto-polaron in transition metal dichalcogenides triangular quantum well

We study the dynamic of magneto-polaron condensate in monolayer two dimensional (2D) transition metal dichalcogenides (TMDs) materials of 2H types in triangular quantum well potential. Within both the quantum mechanical Schrödinger approach (QMSA) and the improved Wigner-Brillouin theory (IWBT), Landau energies levels (LELs) are derived. We have shown that the magneto-polaron condensation is enhanced in monolayer MoSe₂ compared to MoS₂, WS₂ and WSe₂. We derive various levels by increasing a magnetic field and laser parameter. We show that the quantum confinement lifts the degeneracy of the Landau levels (LLs) resulting in an anticrossing and crossing. The dephasing effect due to the quantum well potential's parameter plays an important role in the magneto-polaron energy corrections, which are also affected by the amplitude of the laser field. The system presents Stückelberg oscillations which is important for practical applications.     

角锥棱镜谐振腔激光模式模拟研究

为了探究角锥棱镜谐振腔激光模式,以角锥-平面镜腔为例,将角锥棱镜等效为衍射光栅,考虑角锥镜棱宽在谐振腔中的衍射效应以及二面角误差引起的附加相位分布对谐振腔激光模式的影响,在光学谐振腔理论的基础上,建立了求解本征模式的理论分析模型.采用快速傅里叶法数值模拟不同腔长、角锥镜棱宽和二面角误差情况下该无源谐振腔激光输出模式分布情况.结果表明,在腔长30 cm、角锥镜棱宽小于75μm、二面角误差在-10′~5′之间时,可实现光斑完整的圆形分布输出模式,且有较好的光束质量;棱宽不小于0.4 mm,二面角误差在-40′~10′之间时,光斑为TEM 03阶横模,光场呈六瓣分布;当角锥镜棱宽为0.4 mm、二面角误差为3′,腔长从30~90 cm范围内增加时,该谐振腔输出的激光模式从TEM 03转换成TEM 10.     

Rapid and label-free classification of pathogens based on light scattering,reduced power spectral features and support vector machine

The rapid identification of pathogens is crucial in controlling the food quality and safety. The proposed system for the rapid and label-free identification of pathogens is based on the principle of laser scattering from the bacterial microbes. The clinical prototype consists of three parts: the laser beam, photodetectors, and the data acquisition system. The bacterial testing sample was mixed with 10 mL distilled water and placed inside the machine chamber. When the bacterial microbes pass by the laser beam, the scattering of light occurs due to variation in size, shape, and morphology. Due to this reason, different types of pathogens show their unique light scattering patterns. The photo-detectors were arranged at the surroundings of the sample at different angles to collect the scattered light. The photodetectors convert the scattered light intensity into a voltage waveform. The waveform features were acquired by using the power spectral characteristics, and the dimensionality of extracted features was reduced by applying minimal-redundancy-maximal-relevance criterion (mRMR). A support vector machine (SVM) classifier was developed by training the selected power spectral features for the classification of three different bacterial microbes. The resulting average identification accuracies of E. faecalis, E. coli and S. aureus were 99%, 87%, and 94%, respectively. The overall experimental results yield a higher accuracy of 93.6%, indicating that the proposed device has the potential for label-free identification of pathogens with simplicity, rapidity, and cost-effectiveness.     

An experimental method for eliminating effect of rigid out-of-plane motion on 2D-DIC

The out-of-plane motion is one of the most important factors that affect the precision of two-dimensional digital image correlation (2D-DIC). In this paper, a novel solution is presented to improve conventional 2D-DIC by eliminating the effect of out-of-plane motion, including translation and rotation. Firstly, an experimental technique using two projected laser strips is proposed to measure the out-of-plane motion of a planar specimen. A theoretical model is then established to predict the pseudostrains caused by out-of-plane motion based on the pin-hole imaging model. Using the measured out-of-plane displacement, the captured deformed images used in 2D-DIC are amended to eliminate the effect of out-of-plane motion by the theoretical model. Finally, two experiments were conducted to validate the effectiveness of the proposed method. Results indicate that application of the proposed method can effectively eliminate the errors caused by out-of-plane motion.