Adhesion, friction, and deformation of ion-beam-deposited boron nitride films

The tribological properties and mechanical strength of boron nitride films were investigated. The BN films were predominantly amorphous and nonstoichiometric and contained small amounts of oxides and carbides. It was found that the yield pressure at full plasticity, the critical load to fracture, and the shear strength of interfacial adhesive bonds (considered as adhesion) depended on the type of metallic substrate on which the BN was deposited. The harder the substrate, the greater the critical load and the adhesion. The yield pressures of the BN film were 12 GPa for the 440C stainless steel substrate, 4.1 GPa for the 304 stainless steel substrate, and 3.3 GPa for the titanium substrate

A Heuristic-Dynamic-programming-Based Power System Stabilizer for a Turbogenerator in a Single-Machine Power System

Power system stabilizers (PSSs) are used to generate supplementary control signals for the excitation system in order to damp the low-frequency power system oscillations. To overcome the drawbacks of a conventional PSS (CPSS), numerous techniques have been proposed in the literature. Based on the analysis of existing techniques, a novel design based on heuristic dynamic programming (HDP) is presented in this paper. HDP, combining the concepts of dynamic programming and reinforcement learning, is used in the design of a nonlinear optimal power system stabilizer. Results show the effectiveness of this new technique. The performance of the HDP-based PSS is compared with the CPSS and the indirect-adaptive-neurocontrol-based PSS under small and large disturbances. In addition, the impact of different discount factors in the HDP PSS\u27s performance is presented

A Heuristic Dynamic Programming Based Power System Stabilizer for a Turbogenerator in a Single Machine Power System

Power system stabilizers (PSS) are used to generate supplementary control signals for the excitation system in order to damp the low frequency power system oscillations. To overcome the drawbacks of conventional PSS (CPSS), numerous techniques have been proposed in the literature. Based on the analysis of existing techniques, a novel design of power system stabilizer (PSS) based on heuristic dynamic programming (HDP) is proposed in this paper. HDP combining the concepts of dynamic programming and reinforcement learning is used in the design of a nonlinear optimal power system stabilizer. The proposed HDP based PSS is evaluated against the conventional power system stabilizer and indirect adaptive neurocontrol based PSS under small and large disturbances in a single machine infinite bus power system setup. Results are presented to show the effectiveness of this new technique

Online Identification of Turbogenerator\u27s Dynamics using a Neuro-Identifier

The increasing complexity of modern power systems highlights the need for effective system identification techniques for the successful control of power system. This paper proposes a robust continually online trained neuroidentifier to predict the outputs of turbogenerator - terminal voltage and speed deviation. The inputs to the neuro-identifier are the changes of the plant\u27s outputs and plant\u27s inputs. It overcomes the drawback of calculating deviation signals from reference signals for different operating points in previous work. Simulation results show that the neuro-identifier can provide accurate identification under different operating conditions. Furthermore, the neuro-identifier can learn the dynamics of the system in a short period of time, which makes it suitable for use with an online adaptive controller for the control of turbogenerators

Memristor-Based HTM Spatial Pooler with On-Device Learning for Pattern Recognition

This article investigates hardware implementation of hierarchical temporal memory (HTM), a brain-inspired machine learning algorithm that mimics the key functions of the neocortex and is applicable to many machine learning tasks. Spatial pooler (SP) is one of the main parts of HTM, designed to learn the spatial information and obtain the sparse distributed representations (SDRs) of input patterns. The other part is temporal memory (TM) which aims to learn the temporal information of inputs. The memristor, which is an appropriate synapse emulator for neuromorphic systems, can be used as the synapse in SP and TM circuits. In this article, a memristor-based SP (MSP) circuit structure is designed to accelerate the execution of the SP algorithm. The presented MSP has properties of modeling both the synaptic permanence and the synaptic connection state within a single synapse, and on-device and parallel learning. Simulation results of statistic metrics and classification tasks on several real-world datasets substantiate the validity of MSP

Zinc-finger domains of the transcriptional repressor KLF15 bind multiple sites in rhodopsin and IRBP promoters including the CRS-1 and G-rich repressor elements

BACKGROUND: In the retina, many of the genes that encode components of the visual transduction cascade and retinoid recycling are exclusively expressed in photoreceptor cells and show highly stereotyped temporal and spatial expression patterns. Multiple transcriptional activators of photoreceptor-specific genes have been identified, but little is known about negative regulation of gene expression in the retina. We recently identified KLF15, a member of the Sp/Krüppel-like Factor family of zinc-finger containing transcription factors, as an in vitro repressor of the promoters of the photoreceptor-specific genes rhodopsin and IRBP/Rbp3. To gain further insight into the mechanism of KLF15-mediated regulation of gene expression, we have characterized the binding characteristics and specificity of KLF15's DNA binding domains and defined the KLF15 binding sites in the rhodopsin and IRBP promoters. RESULTS: In EMSA and DNAseI footprinting assays, a KLF15-GST fusion protein containing the C-terminal zinc-finger domains (123 amino acids) showed zinc-dependent and sequence-specific binding to a 9 bp consensus sequence containing a core CG/TCCCC. Both the bovine rhodopsin and IRBP promoters contained multiple KLF15 binding sites that included the previously identified CRS-1 and G-rich repressor elements. KLF15 binding sites were highly conserved between the bovine, human, chimp and dog rhodopsin promoters, but less conserved in rodents. KLF15 reduced luciferase expression by bRho130-luc (containing 4 KLF15 sites) and repressed promoter activation by CRX (cone rod homeobox) and/or NRL (neural retina leucine zipper), although the magnitude of the reduction was smaller than previously reported for a longer bRho225-luc (containing 6 KFL15 sites). CONCLUSION: KLF15 binds to multiple 9 bp consensus sites in the Rhodospin and IRBP promoters including the CRS-1 and G-rich repressor elements. Based on the known expression pattern of KLF15 in non-photoreceptor cells, we hypothesize an in vivo role for KLF15 in repressing photoreceptor-specific gene expression in the inner retina

Human cortical perfusion and the arterial pulse: a near-infrared spectroscopy study

BACKGROUND: The pulsatile nature of the arterial pulse induces a pulsatile perfusion pattern which can be observed in human cerebral cortex with non-invasive near-infrared spectroscopy. The present study attempts to establish a quantitative relation between these two events, even in situations of very weak signal-to-noise ratio in the cortical perfusion signal. The arterial pulse pattern was extracted from the left middle finger by means of plethesmographic techniques. Changes in cortical perfusion were detected with a continuous-wave reflectance spectrophotometer on the scalp overlying the left prefrontal cortex. Cross-correlation analysis was performed to provide evidence for a causal relation between the arterial pulse and relative changes in cortical total hemoglobin. In addition, the determination of the statistical significance of this relation was established by the use of phase-randomized surrogates. RESULTS: The results showed statistically significant cross correlation between the arterial and perfusion signals. CONCLUSIONS: The approach designed in the present study can be utilized for a quantitative and continuous assessment of the perfusion states of the cerebral cortex in experimental and clinical settings even in situations of extremely low signal-to-noise ratio

Feedback Linearization Based Power System Stabilizer Design with Control Limits

In power system controls, simplified analytical models are used to represent the dynamics of power system and controller designs are not rigorous with no stability analysis. One reason is because the power systems are complex nonlinear systems which pose difficulty for analysis. This paper presents a feedback linearization based power system stabilizer design for a single machine infinite bus power system. Since practical operating conditions require the magnitude of control signal to be within certain limits, the stability of the control system under control limits is also analyzed. Simulation results under different kinds of operating conditions show that the controller design not only can damp the power system oscillations very well but can also minimize the impact on the terminal voltage. In addition, the Brunovsky Canonical form of the power system model presented in this paper can be used for other forms of controller design

Extended Kalman Filter based Resilient Formation Tracking Control of Multiple Unmanned Vehicles Via Game-Theoretical Reinforcement Learning

In This Paper, We Discuss the Resilient Formation Tracking Control Problem of Multiple Unmanned Vehicles (MUV). a Dynamic Leader-Follower Distributed Control Structure is Utilized to Optimize the Performance of the Formation Tracking. for the Follower of the MUV, the Leader is a Cooperative Unmanned Vehicle, and the Target of Formation Tracking is a Non-Cooperative Unmanned Vehicle with a Nonlinear Trajectory. Therefore, an Extended Kalman Filter (EKF) Observer is Designed to Estimate the State of the Target. Then the Leader of the MUV is Adjusted Dynamically According to the State of the Target. in Order to Describe the Interactions between the Follower and Dynamic Leader, a Stackelberg Game Model is Constructed to Handle the Hierarchical Decision Problems. at the Lower Layer, Each Follower Responds by Observing the Leader\u27s Strategy, and the Potential Game is Used to Prove a Nash Equilibrium among All Followers. at the Upper Layer, the Dynamic Leader Makes Decisions Depending on the Response of All Followers to Reaching the Stackelberg Equilibrium. Moreover, the Stackelberg-Nash Equilibrium of the Designed Game Theoretical Model is Proven. a Novel Reinforcement Learning-Based Algorithm is Designed to Achieve the Stackelberg-Nash Equilibrium of the Game. Finally, the Effectiveness of the Method is Verified by a Variety of Formation Tracking Simulation Experiments