GCN-RL Circuit Designer: Transferable Transistor Sizing with Graph Neural Networks and Reinforcement Learning

Automatic transistor sizing is a challenging problem in circuit design due to the large design space, complex performance trade-offs, and fast technological advancements. Although there has been plenty of work on transistor sizing targeting on one circuit, limited research has been done on transferring the knowledge from one circuit to another to reduce the re-design overhead. In this paper, we present GCN-RL Circuit Designer, leveraging reinforcement learning (RL) to transfer the knowledge between different technology nodes and topologies. Moreover, inspired by the simple fact that circuit is a graph, we learn on the circuit topology representation with graph convolutional neural networks (GCN). The GCN-RL agent extracts features of the topology graph whose vertices are transistors, edges are wires. Our learning-based optimization consistently achieves the highest Figures of Merit (FoM) on four different circuits compared with conventional black-box optimization methods (Bayesian Optimization, Evolutionary Algorithms), random search, and human expert designs. Experiments on transfer learning between five technology nodes and two circuit topologies demonstrate that RL with transfer learning can achieve much higher FoMs than methods without knowledge transfer. Our transferable optimization method makes transistor sizing and design porting more effective and efficient.Comment: Accepted to the 57th Design Automation Conference (DAC 2020); 6 pages, 8 figure

Design of Pseudo-Command Restricted Controller for Tailless Unmanned Aerial Vehicles Based on Attainable Moment Set

This work investigates the pseudo-command restricted problem for tailless unmanned aerial vehicles with snake-shaped maneuver flight missions. The main challenge of designing such a pseudo-command restricted controller lies in the fact that the necessity of control allocation means it will be difficult to provide a precise envelope of pseudo-command to the flight controller; designing a compensation system to deal with insufficient capabilities beyond this envelope is another challenge. The envelope of pseudo-command can be expressed by attainable moment sets, which leave some open problems, such as how to obtain the attainable moment sets online and how to reduce the computational complexity of the algorithm, as well as how to ensure independent control allocation and the convexity of attainable moments sets. In this article, an innovative algorithm is proposed for the calculation of attainable moment sets, which can be implemented by fitting wind tunnel data into a function to solve the problems presented above. Furthermore, the algorithm is independent of control allocation and can be obtained online. Moreover, based on the above attainable moment sets algorithm, a flight performance assurance system is designed, which not only guarantees that the command is constrained within the envelope so that its behavior is more predictable, but also supports adaptive compensation for the pseudo-command restricted controller. Finally, the effectiveness of the AMS algorithm and the advantages of the pseudo-command restricted control system are validated through two sets of independent simulations

Incremental Backstepping Sliding-Mode Trajectory Control for Tailless Aircraft with Stability Enhancer

This paper presents an incremental backstepping sliding-mode (IBS) controller for trajectory control of a tailless aircraft with unknown disturbances and model uncertainties. The proposed controller is based on a nonlinear dynamic model of the tailless aircraft. A stability enhancer (SE) that limits both the rate and amplitude of the virtual control input is proposed. The stability enhancer consists of two layers. When the virtual control input approaches the edge, the first layer SE would be activated to modify the trajectory tracking error; when the virtual control input exceeds the edge, the second layer SE would reduce the control gains to make sure the virtual control input drops within the edge as soon as possible. With the help of SE, the incremental control method could be extended to outer-loop control without considering the dynamics of the inner-loop system. In addition, an adaptive estimator for state derivatives is proposed, together with IBS, allowing the controller to show excellent robustness. Finally, two simulations are presented. The first simulation shows that the system is insensitive to external disturbances and model uncertainties, and the effectiveness of SE is proved in the second simulation

FF-RRT*: a sampling-improved path planning algorithm for mobile robots against concave cavity obstacle

Abstract The slow convergence rate and large cost of the initial solution limit the performance of rapidly exploring random tree star (RRT*). To address this issue, this paper proposes a modified RRT* algorithm (defined as FF-RRT*) that creates an optimal initial solution with a fast convergence rate. An improved hybrid sampling method is proposed to speed up the convergence rate by decreasing the iterations and overcoming the application limitation of the original hybrid sampling method towards concave cavity obstacle. The improved hybrid sampling method combines the goal bias sampling strategy and random sampling strategy, which requires a few searching time, resulting in a faster convergence rate than the existing method. Then, a parent node is created for the sampling node to optimize the path. Finally, the performance of FF-RRT* is validated in four simulation environments and compared with the other algorithms. The FF-RRT* shortens 32% of the convergence time in complex maze environment and 25% of the convergence time in simple maze environment compared to F-RRT*. And in a complex maze with a concave cavity obstacle, the average convergence time of Fast-RRT* in this environment is 134% more than the complex maze environment compared to 12% with F-RRT* and 34% with FF-RRT*. The simulation results show that FF-RRT* possesses superior performance compared to the other algorithms, and also fits with a much more complex environment

A Multiobjective Incremental Control Allocation Strategy for Tailless Aircraft

To address the control allocation problem caused by the redundant arrangement of control surfaces with nonlinear effectiveness for tailless aircraft, a novel multiobjective incremental control allocation (MICA) strategy is proposed. Firstly, the incremental nonlinear control allocation (INCA) method together with the active set quadratic programming algorithm is adopted to precisely allocate the virtual control commands. Secondly, a series of normalized objective functions in the form of increment are designed. Combining these functions by means of linear weighted sum, an incremental multiobjective function is constructed. Then, an improved nondominated sorting genetic algorithm (INSGA) is introduced to offline determine a set of weights that best meets the requirements of each flight phase. In this way, the dependence on subjective experience is minimized based on the theory of Pareto optimal. Meanwhile, the huge computational burden that the intelligent optimization algorithm brings can also be avoided. Finally, combined with the nonlinear dynamic inversion (NDI) control method, a closed-loop validation for the effectiveness of this control allocation strategy is carried out on the tailless aircraft model

Mesenchymal Stem Cell Therapy Using Human Umbilical Cord in a Rat Model of Autoimmune-Induced Premature Ovarian Failure

Premature ovarian failure (POF) is one of the principal causes of female infertility, and although its causes are complex and diverse, autoimmune deficiency may be involved. Human umbilical cord mesenchymal stem cells (UCMSCs) can be used for tissue regeneration and repair. Therefore, the present study was designed to determine the role of UCMSCs in immune factor-induced POF in rats. In this study, different concentrations of UCMSCs were injected into induced POF rats. Ovarian functions were examined by evaluating the estrus cycle, follicular morphology, hormonal secretion, and the proliferation and apoptosis of granulosa cells. Our results showed that the estrus cycle of rats returned to normal and follicular development was significantly improved after transplantation of UCMSCs. In addition, serum concentrations of 17-estradiol (E2), progesterone (P4), and anti-Müllerian hormone (AMH) increased significantly with treatment. Transplantation of UCMSCs also reduced the apoptosis of granulosa cells and promoted the proliferation of granulosa cells. All of these improvements were dose dependent. Furthermore, the results of related gene expression showed that transplanted human UCMSCs upregulated the expression of Bcl-2, AMH, and FSHR in the ovary of POF rats and downregulated the expression of caspase-3. These results further validated the potential mechanisms of promoting the release of cell growth factors and enhancing tissue regeneration and provide a theoretical basis for the clinical application of stem cells in the treatment of premature ovarian failure

Porcine Viperin protein inhibits the replication of classical swine fever virus (CSFV) in vitro

Abstract Background Classical swine fever virus (CSFV) is the causative pathogen of Classical swine fever (CSF), a highly contagious disease of swine. Viperin is one of the hundreds of interferon-stimulated genes (ISGs), and possesses a wide range of antiviral activities. The aim of this study was to explore whether porcine Viperin has the anti-CSFV activity. Method The influences of CSFV infection on Viperin expression and Newcastle disease virus (NDV)/Pseudorabies virus (PRV)-induced Viperin expression were examined in 3D4/21 cells and porcine peripheral blood mononuclear cells (PBMCs). Porcine Viperin gene was amplified to generate cell line PK-Vi over-expressing Viperin. CSFV was inoculated in the cell lines and viral load was detected by qRT-PCR, virus titration and Western blot. The influence of Viperin expression on CSFV binding, entry and release in the cells was also examined. The co-localization of Viperin with CSFV and its proteins (E2, NS5B) was determined by confocal laser scanning microscopy test. Co-IP assay was performed to check the interaction of Viperin with CSFV proteins. Results CSFV infection could not induce Viperin expression in vitro while significantly inhibiting NDV/PRV-induced Viperin expression at 12, 24 and 48 h post infection (hpi; P < 0.05). The proliferation of CSFV in PK-Vi was significantly inhibited at 24, 48 and 72 hpi (P < 0.05), comparing with control cells (PK-C1 expressing EGFP). Virus in both cell culture supernatants and cell pellets were reduced equally. CSFV binding and entry in the cells were not interfered by Viperin expression. These results indicated its anti-CSFV function occurred during the genome and/or protein synthesis step. Confocal laser scanning microscopy test showed the Viperin-EGFP protein co-localized with CSFV E2 protein in CSFV infected PK-Vi cells. Further experiments indicated that Viperin protein co-localized with E2 and NS5B proteins of CSFV in the transfected 293 T cells. Furthermore, Co-IP assay confirmed the interaction of Viperin with E2 protein, but not NS5B. Conclusion Porcine Viperin effectively inhibited CSFV replication in vitro, potentially via the interaction of Viperin with CSFV E2 protein in cytoplasm. The results provided foundation for further studies of the interaction of Viperin with CSFV and other viruses

Lianhua Qingke ameliorates lipopolysaccharide‐induced lung injury by inhibiting neutrophil extracellular traps formation and pyroptosis

Abstract LHQK is a patented Traditional Chinese Medicine (TCM) which is clinically used for acute tracheobronchitis, cough, and other respiratory diseases. Recent studies have proved that LHQK exhibits excellent clinical efficacy in the treatment of acute lung injury (ALI). However, the corresponding mechanisms remain largely unexplored. In this study, we investigated the effects and the underlying mechanisms of LHQK on lipopolysaccharide (LPS)‐induced ALI in mice. The pathological examination, inflammatory cytokines assessments, and mucus secretion evaluation indicated that administration of LHQK ameliorated LPS‐induced lung injury, and suppressed the secretion of Muc5AC and pro‐inflammatory cytokines (IL‐6, TNF‐α, and IL‐1β) in plasma and BALF. Furthermore, the results of cell‐free DNA level showed that LHQK significantly inhibited LPS‐induced NETs formation. Western blot revealed that LHQK effectively inhibited LPS‐triggered pyroptosis in the lung. In addition, RNA‐Seq data analysis, relatively bioinformatic analysis, and network pharmacology analysis revealed that LHQK and relative components may play multiple protective functions in LPS‐induced ALI/acute respiratory distress syndrome (ARDS) by regulating multiple targets directly or indirectly related to NETs and pyroptosis. In conclusion, LHQK can effectively attenuate lung injury and reduce lung inflammation by inhibiting LPS‐induced NETs formation and pyroptosis, which may be regulated directly or indirectly by active compounds of LHQK