204 research outputs found
Logic Attention Based Neighborhood Aggregation for Inductive Knowledge Graph Embedding
Knowledge graph embedding aims at modeling entities and relations with
low-dimensional vectors. Most previous methods require that all entities should
be seen during training, which is unpractical for real-world knowledge graphs
with new entities emerging on a daily basis. Recent efforts on this issue
suggest training a neighborhood aggregator in conjunction with the conventional
entity and relation embeddings, which may help embed new entities inductively
via their existing neighbors. However, their neighborhood aggregators neglect
the unordered and unequal natures of an entity's neighbors. To this end, we
summarize the desired properties that may lead to effective neighborhood
aggregators. We also introduce a novel aggregator, namely, Logic Attention
Network (LAN), which addresses the properties by aggregating neighbors with
both rules- and network-based attention weights. By comparing with conventional
aggregators on two knowledge graph completion tasks, we experimentally validate
LAN's superiority in terms of the desired properties.Comment: Accepted by AAAI 201
Laser Controlled Manipulation of Microbubbles on a Surface with Silica-Coated Gold Nanoparticle Array
Microbubble generation and manipulation play critical roles in diverse applications such as microfluidic mixing, pumping, and microrobot propulsion. However, existing methods are typically limited to lateral movements on customized substrates or rely on specific liquids with particular properties or designed concentration gradients, thereby hindering their practical applications. To address this challenge, this paper presents a method that enables robust vertical manipulation of microbubbles. By focusing a resonant laser on hydrophilic silica-coated gold nanoparticle arrays immersed in water, plasmonic microbubbles are generated and detach from the substrates immediately upon cessation of laser irradiation. Using simple laser pulse control, it can achieve an adjustable size and frequency of bubble bouncing, which is governed by the movement of the three-phase contact line during surface wetting. Furthermore, it demonstrates that rising bubbles can be pulled back by laser irradiation induced thermal Marangoni flow, which is verified by particle image velocimetry measurements and numerical simulations. This study provides novel insights into flexible bubble manipulation and integration in microfluidics, with significant implications for various applications including mixing, drug delivery, and the development of soft actuators.</p
Direct Laser Writing of Surface Micro-Domes by Plasmonic Bubbles
Plasmonic microbubbles produced by laser irradiated gold nanoparticles (GNPs)
in various liquids have emerged in numerous innovative applications. The
nucleation of these bubbles inherently involves rich phenomena. In this paper,
we systematically investigate the physicochemical hydrodynamics of plasmonic
bubbles upon irradiation of a continuous wave (CW) laser on a GNP decorated
sample surface in ferric nitrate solution. Surprisingly, we observe the direct
formation of well-defined micro-domes on the sample surface. It reveals that
the nucleation of a plasmonic bubble is associated with the solvothermal
decomposition of ferric nitrate in the solution. The plasmonic bubble acts as a
template for the deposition of iron oxide nanoparticles. It first forms a rim,
then a micro-shell, which eventually becomes a solid micro-dome. Experimental
results show that the micro-dome radius Rd exhibits an obvious dependence on
time t, which can be well interpreted theoretically. Our findings reveal the
rich phenomena associated with plasmonic bubble nucleation in a thermally
decomposable solution, paving a plasmonic bubble-based approach to fabricate
three dimensional microstructures by using an ordinary CW laser
Adaptive Backstepping Control for Air-Breathing Hypersonic Vehicles with Input Nonlinearities
This paper addresses the control problem of air-breathing hypersonic vehicles subject to input nonlinearities, aerodynamic uncertainties and flexible modes. An adaptive backstepping controller and a dynamic inverse controller are developed for the altitude subsystem and the velocity subsystem, respectively, where the former eliminates the problem of “explosion of terms” inherent in backstepping control. Moreover, a modified smooth inverse of the dead-zone is proposed to compensate for the dead-zone effects and reduce the computational burden. Based on this smooth inverse, an input nonlinear pre-compensator is designed to handle input saturation and dead-zone nonlinearities, which leads to a simpler control design for the altitude subsystem subject to these two input nonlinearities. It is proved that the proposed controllers can guarantee that all closed-loop signals are bounded and the tracking errors converge to an arbitrarily small residual set. Simulation results are carried out to demonstrate the effectiveness of the proposed control scheme
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