Learning nonlinear dynamics with behavior ordinary/partial/system of the differential equations: looking through the lens of orthogonal neural networks

In this paper, size-dependent dynamic stability of axially loaded functionally graded (FG) composite truncated conical microshells with magnetostrictive facesheets surrounded by nonlinear viscoelastic foundations including a two-parameter Winkler–Pasternak medium augmented via a Kelvin–Voigt viscoelastic approach is analyzed considering nonlinear cubic stiffness. To this purpose, von Karman-type kinematic nonlinearity along with modified couple stress theory of elasticity was applied to third-order shear deformation conical shell theory in the presence of magnetic permeability tensor and magnetic fluxes. The numerical technique of generalized differential quadrature (GDQ) was used for the solution of microstructural-dependent dynamic stability responses of FG composite truncated conical microshells. It was seen that moving from prebuckling to postbuckling domain somehow increased the significance of couple stress type of size dependency on frequency. In addition, within both prebuckling and postbuckling regimes, an increase of material gradient index decreased the importance of couple stress type of size dependency on the frequency of an axially loaded FG composite truncated conical microshell. Furthermore, it was revealed that by applying a positive magnetic field to an axially loaded truncated conical microshell with magnetostrictive facesheets, its frequency at a specific axial load value was increased in prebuckling domain and decreased in postbuckling domain. However, this pattern was reversed by applying a negative magnetic field.

     

Congestion-aware channel assignment for multi-channel wireless mesh networks

In this paper, we propose a distributed congestion-aware channel assignment (DCACA) algorithm for multi-channel wireless mesh networks (MC–WMNs). The frequency channels are assigned according to the congestion measures which indicate the congestion status at each link. Depending on the selected congestion measure (e.g., queueing delay, packet loss probability, and differential backlog), various design objectives can be achieved. Our proposed distributed algorithm is simple to implement as it only requires each node to perform a local search. Unlike most of the previous channel assignment schemes, our proposed algorithm assigns not only the non-overlapped (i.e., orthogonal) frequency channels, but also the partially-overlapped channels. In this regard, we introduce the channel overlapping and mutual interference matrices which model the frequency overlapping among different channels. Simulation results show that in the presence of elastic traffic (e.g., TCP Vegas or TCP Reno) sources, our proposed DCACA algorithm increases the aggregate throughput and also decreases the average packet round-trip compared with the previously proposed Load-Aware channel assignment algorithm. Furthermore, in a congested IEEE 802.11b network setting, compared with the use of three non-overlapped channels, the aggregate network throughput can further be increased by 25% and the average round-trip time can be reduced by more than one half when all the 11 partially-overlapped channels are used.     

A Study on Lateral Control of Autonomous Vehicles via Fired Fuzzy Rules Chromosome Encoding Scheme

In this paper, we propose a novel Fired Rules Chromosomes (FRC) encoding scheme for a fuzzy controller tuned by Genetic Algorithms (GA). The proposed method improves the optimization speed through the reduction of the search space. In addition, an improvement in convergence is demonstrated. The fuzzy controller optimized by the FRC scheme is employed to maintain the lateral position of an autonomous vehicle. The robustness of the controller to parameter variation is studied by Monte-Carlo analysis. Simulation and experimental studies demonstrate the performance of the lateral controller.     

Wavelet PSO‐Based LQR Algorithm for Optimal Structural Control Using Active Tuned Mass Dampers

This study presents a new method to find the optimal control forces for active tuned mass damper. The method uses three algorithms: discrete wavelet transform (DWT), particle swarm optimization (PSO), and linear quadratic regulator (LQR). DWT is used to obtain the local energy distribution of the motivation over the frequency bands. PSO is used to determine the gain matrices through the online update of the weighting matrices used in the LQR controller while eliminating the trial and error. The method is tested on a 10‐story structure subject to several historical pulse‐like near‐fault ground motions. The results indicate that the proposed method is more effective at reducing the displacement response of the structure in real time than conventional LQR controllers.     

Efficient repairing effect of PEG based tri-block copolymer on mechanically damaged PC12 cells and isolated spinal cord

Membrane sealing effects of polymersomes made of tri-block copolymer, PEG-co-FA/SC-co-PEG, (PFSP) were studied on isolated spinal cord strips, PC12 cell lines and artificial bilayer following mechanical impact implemented by aneurism clip, sonication and electric shock, respectively. The homogeneity and size of PFSP, membrane permeability and cell viability were assessed by dynamic light scattering, LDH release and MTT assays. According to the results, the biocompatible, physico-chemical, size, surface charge and amphipathic nature of PFSP polymersome makes it an ideal macromolecule to rapidly reseal damaged membranes of cells in injured spinal cord as well as in culture medium. Compound action potentials recorded from intentionally damaged spinal cord strips incubated with PFSP showed restoration of neural excitability by 82.24 % and conduction velocity by 96.72 % after 5 min that monitored in real time. Thus, they triggered efficient instant and sustained sealing of membrane and reactivation of temporarily inactivated axons. Treatment of ultrasonically damaged PC12 cells by PFSP caused efficient cell membrane repair and led to their increased viability. The optimum effects of PFSP on stabilization and impermeabilizing of the lipid bilayer occurred at the same concentrations applied to the damaged cells and spinal cord fibers and was approved by restoration of membrane conductance and calcein release manifested by NanoDrop technique. The unique physico-chemical characteristics of novel polymersomes introduced here, make them capable to reorganize membrane lipid molecules, reseal the breaches and restore the hydrophobic insulation in spinal cord damaged cells. Thus, they might be considered in the clinical treatment of SCI at early stages.     

Acid esophago-pharyngeal reflux as etiology of hoarseness

BACKGROUND: Gastroesophageal reflux has been implicated in otolaryngologic problems, particularly chronic hoarseness that cannot be attributed to other causes. PATIENTS AND METHODS: To study this relationship between gastroesophageal reflux and chronic hoarseness we used 24-h dual-site ambulatory pH-recordings in 68 patients with chronic hoarseness and laryngeal lesions suggestive of acid irritation. RESULTS: Thirty-eight patients (56%) had evidence of at least one esophago-pharyngeal reflux episode. The mean number of esophago-pharyngeal episodes was 6.7 +/- 12 within 24 hours (range: 1-34 episodes). The mean duration of these episodes was 201 +/- 28 seconds (range: 6 seconds-19.6 minutes). Most patients with esophago-pharyngeal reflux had no evidence of pathologic gastroesophageal reflux. Only 28.9% of the patients with esophago-pharyngeal reflux episodes also had pathologic gastroesophageal phageal reflux, whereas 23.3% of the patients without esophago-pharyngeal reflux had no gastroesophageal reflux disease. The esophago-pharyngeal reflux occurred mainly in the upright position. CONCLUSIONS: Occult esophago-pharyngeal reflux, predominantly in the upright position, appears to be common and severe in patients with chronic hoarseness. Gastroesophageal reflux may be an important factor in the pathogenesis of chronic hoarseness. The causative mechanisms are not clear.     

Model-based fault diagnosis in continuous dynamic systems

Traditional fault detection and isolation methods are based on quantitative models which are sometimes difficult and costly to obtain. In this paper, qualitative bond graph (QBG) reasoning is adopted as the modeling scheme to generate a set of qualitative equations. The QBG method provides a unified approach for modeling engineering systems, in particular, mechatronic systems. An input-output qualitative equation derived from QBG formalism performs continuous system monitoring. Fault diagnosis is activated when a discrepancy is observed between measured abnormal behavior and predicted system behavior. Genetic algorithms (GA's) are then used to search for possible faulty components among a system of qualitative equations. In order to demonstrate the performance of the proposed algorithm, we have tested it on a laboratory scale servo-tank liquid process rig. Results of the proposed model-based fault detection and diagnosis algorithm for the process rig are presented and discussed.