Soft materials including elastomers and hydrogels are playing critical roles in a variety of fields,including bioelectrodes,batteries,supercapacitors,biomedical scaffolds,and solar vapor *** hydrophobic sponges(i.e.,m...
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Soft materials including elastomers and hydrogels are playing critical roles in a variety of fields,including bioelectrodes,batteries,supercapacitors,biomedical scaffolds,and solar vapor *** hydrophobic sponges(i.e.,mechanical robustness,elasticity and macroscopic porous structure)and hydrophilic hydrogels(i.e.,autonomous water absorption and transportation,biocompatibility)within one unit could readily combine the complementary characters from each component,making a number of future research directions and applications *** propose a simple yet effective strategy to construct sponge-hydrogel hybrid structures with robust hydrophobic-hydrophilic *** sponge scaffold imparts the sponges-hydrogel hybrids with desirable mechanical robustness,elasticity and macroscopic *** the other hand,the incorporated hydrogel component endows the hybrids with high water content(98 wt%hydrogel and 2 wt%sponge),superior compatibility,and nanoscale pores allowing for storage and transportation of various chemical and biological *** further demonstrate that the introduction of hydrophilic hydrogel components could effectively improve the liquid absorption capability,blood coagulation rate,hemostatic capacity and hemocompatibility,thus promising as hemostatic agents.
Ferrofluid droplets are of great importance due to their ability to be manipulated by magnetic actuation, enabling progress in various areas, such as nanotechnology, robotics, and optics. Moving, splitting, and mergin...
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In this paper, we present a method to control the UAV to follow the power line with a specific position and orientation based only on the measurement of the magnetic field generated by the current flow in the power li...
Robotic manipulation tasks in dynamic and unstructured environments present significant challenges for traditional control procedures. Deep reinforcement learning (DRL) has appeared as a powerful technique to enable r...
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Recent research on Large Language Models for autonomous driving shows promise in planning and control. However, high computational demands and hallucinations still challenge accurate trajectory prediction and control ...
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The process of educating and learning about the automotive industry is still ongoing, and one of the most effective techniques is the provision of direct practice. Such a system is regarded as effective, albeit with c...
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In a number of industries, including computer graphics, robotics, and medical imaging, three-dimensional reconstruction is essential. In this research, a CNN-based Multi-output and Multi-Task Regressor with deep learn...
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In recent years, cyberattacks against automobiles have exposed significant security threats to in-vehicle networks. The vulnerability of communication signals to malicious interference and manipulation can lead to ser...
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Multi-modal Video Object Segmentation (VOS), including RGB-Thermal, RGB-Depth, and RGB-Event, has garnered attention due to its capability to address challenging scenarios where traditional VOS methods struggle, such ...
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Unmanned aerial vehicles (UAVs) are being increasingly established for autonomous contacted-based inspection of industrial assets, reducing the risk of errors by human operators. However, challenges remain in the navi...
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