As an ideal method to manipulate biological particles, the dielectrophoresis (DEP) technique has been widely used in clinical diagnosis, disease treatment, drug development, immunoassays, cell sorting, etc. This review summarizes the research in the field of bioparticle manipulation based on DEP techniques. Firstly, the basic principle of DEP and its classical theories are introduced in brief; Secondly, a detailed introduction on the DEP technique used for bioparticle manipulation is presented, in which the applications are classified into five fields: capturing bioparticles to specific regions, focusing bioparticles in the sample, characterizing biomolecular interaction and detecting microorganism, pairing cells for electrofusion and separating different kinds of bioparticles; Thirdly, the effect of DEP on bioparticle viability is analyzed; Finally, the DEP techniques are summarized and future trends in bioparticle manipulation are suggested.

Most of the recent progresses on visual question answering are based on recurrent neural networks (RNNs) with attention. Despite the success, these models are often timeconsuming and having difficulties in modeling long range dependencies due to the sequential nature of RNNs. We propose a new architecture, Positional Self-Attention with Coattention (PSAC), which does not require RNNs for video question answering. Specifically, inspired by the success of self-attention in machine translation task, we propose a Positional Self-Attention to calculate the response at each position by attending to all positions within the same sequence, and then add representations of absolute positions. Therefore, PSAC can exploit the global dependencies of question and temporal information in the video, and make the process of question and video encoding executed in parallel. Furthermore, in addition to attending to the video features relevant to the given questions (i.e., video attention), we utilize the co-attention mechanism by simultaneously modeling “what words to listen to” (question attention). To the best of our knowledge, this is the first work of replacing RNNs with selfattention for the task of visual question answering. Experimental results of four tasks on the benchmark dataset show that our model significantly outperforms the state-of-the-art on three tasks and attains comparable result on the Count task. Our model requires less computation time and achieves better performance compared with the RNNs-based methods. Additional ablation study demonstrates the effect of each component of our proposed model.

Artificial muscles possess a vast potential in accelerating the development of robotics, exoskeletons, and prosthetics. Although a variety of emerging actuator technologies are reported, they suffer from several issues, such as high driving voltages, large hysteresis, and water intolerance. Here, a liquid metal artificial muscle (LMAM) is demonstrated, based on the electrochemically tunable interfacial tension of liquid metal to mimic the contraction and extension of muscles. The LMAM can work in different solutions with a wide range of pH (0–14), generating actuation strains of up to 87% at a maximum extension speed of 15 mm s−1. More importantly, the LMAM only needs a very low driving voltage of 0.5 V. The actuating components of the LMAM are completely built from liquids, which avoids mechanical fatigue and provides actuator linkages without mechanical constraints to movement. The LMAM is used for developing several proof‐of‐concept applications, including controlled displays, cargo deliveries, and reconfigurable optical reflectors. The simplicity, versatility, and efficiency of the LMAM are further demonstrated by using it to actuate the caudal fin of an untethered bionic robotic fish. The presented LMAM has the potential to extend the performance space of soft actuators for applications from engineering fields to biomedical applications.

sphere to roll. [3] Robots based on rolling locomotion have relatively high velocity and flexibility, with simple and compact structures that can readily alter their direction of moving. [4] Various actuators have been demonstrated for altering the CG of rolling robots, such as motors, shapememory alloys, and pneumatic actuators. [5] Gallium-based liquid-metal (LM) alloys such as eutectic gallium indium (EGaIn, m.pt. 15.5 °C) and gallium indium tin (Galinstan, m.pt. −19 °C) have been attracting more attention from researchers in recent years. The unique physical/chemical properties of LM, such as high thermal/electrical conductivity, extreme flexibility, and their ability to form a thin oxide shell when exposed to oxygen [6] has many applications; they include making chip cooling systems, [7] forming 3D structures, [8] fabricating flexible electronic components, [9] and producing 2D nanomaterials. [9b,c] Moreover, LM droplets may also be used when forming innovative actuators that can be manipulated by using electrical, magnetic, chemical, and optical mechanisms, [10] making them useful for microfluidics [11] and robotics. [12] However, LM must first be coated or mixed with ferromagnetic microparticles, catalysts, or aluminum strips in order to actuate LM droplets via magnetic, optical, or chemical methods. This may significantly affect the intrinsic properties and compromise the liquidity of LM. Alternatively, actuating LM droplets via an electrical approach can result in high-speed locomotion with almost no effect on the properties of LM. This is achieved by inducing an interfacial tension gradient along the surface of an LM droplet with the application of exterior electric fields. [13] Nevertheless, previous studies show that robotic systems driven by this type of locomotion are only possible within a solution, [13,14] which limits the scope of integrating LM as the core of an actuator to form a more complex system. On this basis, we have been impelled to investigate an innovative method that can harness the actuation of LM droplets to enable a more complex robotic system to have locomotion outside a liquid environment.In this paper, we report on the design and investigation of a wheeled robot that contains an EGaIn LM droplet and electrolyte within an enclosed system, and such an enclosed system is used as the core of the driving module that will enable a robot to have locomotion outside a liquid environment. An LM droplet that is controlled by a pair of electrodes powers this driving module. When applying a voltage to the electrodes, the confined LM droplet is actuated within the electrolyte and consequently, alters the CG of the wheeled robot The controlled actuation of gallium liquid-metal (LM) alloys has presented new and exciting opportunities for constructing mobile robots with structural flexibility. However, the locomotion of current LM-based actuators often relies on inducing a gradient of interfacial tension on the LM surface within electrolytes, which limits their application outside a liqui...