Bubbles in microfluidics—even those that appear to be negligibly small—are pervasive and responsible for the failure of many biological and chemical experiments. For instance, they block current conduction, damage cell membranes, and interfere with detection results. To overcome this unavoidable and intractable problem, researchers have developed various methods for capturing and removing bubbles from microfluidics. Such methods are multifarious and their working principles are very different from each other. In this review, bubble-removing methods are divided into two broad categories: active debubblers (that require external auxiliary equipment) and passive debubblers (driven by natural processes). In each category, three main types of methods are discussed along with their advantages and disadvantages. Among the active debubblers, those assisted by lasers, acoustic generators, and negative pressure pumps are discussed. Among the passive debubblers, those driven by buoyancy, the characteristics of gas–liquid interfaces, and the hydrophilic and hydrophobic properties of materials are discussed. Finally, the challenges and prospects of the bubble-removal technologies are reviewed to refer researchers to microfluidics and inspire further investigations in this field.

This paper concerns the improvement on Proportional-Integration-Derivative (PID) control for standard second-order plus time-delay systems (SOPTD). To achieve higher tracking precision and stronger disturbance rejection, a PID type-ii and type-iii controlloops design method based on the combination of the linear quadratic regulator (LQR) and dominant pole configuration technology is proposed in this paper. The PID type-ii control loop is capable of achieving perfect tracking of step and ramp reference signals with zero steady-state position and velocity error. The PID type-iii control loop is capable of achieving perfect tracking of step, ramp and parabolic reference signals with zero steady-state position, velocity and acceleration error. The effectiveness of the proposed PID type-ii and type-iii controller parameters tuning rules has been demonstrated via simulation of over-damped, critical-damped and under-damped systems. To be specific, compared with the PID type-i control loop, rise time, settling time and disturbance rejection property of the system have been significantly improved while realizing faster reference signal tracking. Finally, the effects of non-dominant pole on the stability and robustness of PID type-ii and PID type-iii closed loop systems have also been discussed.

High control bandwidth is usually restricted in a photoelectric tracking system (PTS) based on a Charge-Couple Device(CCD) with time delay, which hinders a good tracking performance. Generally, a model-based delay-compensation controller called Smith predictor (SP) can help increase the controller gain to promote the bandwidth by separating delay from the control loop. However, the performance promotion is insufficient because the delay still stays in the forward channel which causes errors between output and input. And the increase of the controller gain is still limited due to the effect of model mismatch on stability. In this paper, to solve the problems, a delay-compound-compensation control (DCCC) based on improved SP by trajectory prediction and velocity feedforward is proposed. The additional trajectory prediction is used to further eliminate the effect of delay existing in the forward channel. The additional velocity feedforward is used to further reform the transfer characteristics limited by the controller gain. A Kalman filter-based design method of trajectory prediction is presented and the optimal design principle of feedback and feedforward controllers is given in the face of model mismatch. Experiments demonstrate that the DCCC is valid and could greatly promote the tracking performance in the low frequency.

Calcium is the main mineral responsible for healthy bone growth in infants. Laser-induced breakdown spectroscopy (LIBS) was combined with a variable importance-based long short-term memory (VI-LSTM) for the quantitative analysis of calcium in infant formula powder. First, the full spectra were used to establish PLS (partial least squares) and LSTM models. The R2 and root-mean-square error (RMSE) of the test set (R P 2 and RMSE P ) were 0.1460 and 0.0093 in the PLS method, respectively, and 0.1454 and 0.0091 in the LSTM model, respectively. To improve the quantitative performance, variable selection based on variable importance was introduced to evaluate the contribution of input variables. The variable importance-based PLS (VI-PLS) model had R P 2 and RMSE P of 0.1454 and 0.0091, respectively, whereas the VI-LSTM model had R P 2 and RMSE P of 0.9845 and 0.0037, respectively. Compared with the LSTM model, the number of input variables in the VI-LSTM model was reduced to 276, R P 2 was improved by 114.63%, and RMSE P was reduced by 46.38%. The mean relative error of the VI-LSTM model was 3.33%. We confirm the predictive ability of the VI-LSTM model for the calcium element in infant formula powder. Thus, combining VI-LSTM modeling and LIBS has great potential for the quantitative elemental analysis of dairy products.

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