Consensus in nonlinear multi-agent systems with nonidentical nodes and sampled-data control

This paper primarily discusses the leader-following consensus problem in nonlinear second-order multi-agent systems with nonidentical nodes. Sampled-data-based protocols are applied to reach consensus. Both delay-free and input-delay protocols are proposed. Based on the Lyapunov functional approach and linear matrix inequality (LMI) method, sufficient criteria are obtained to guarantee quasi-consensus for nonlinear heterogeneous multi-agent systems. All the heterogeneous followers can track the leader within a bounded range. Furthermore, the error systems between the leader and each follower eventually converge to a convergence domain that depends on the heterogeneity among the dynamics of the agents. Additionally, leader-following consensus can also be reached as the heterogeneity vanishes. Finally, numerical simulations are provided to illustrate the theoretical results.     

EEG rhythm/channel selection for fuzzy rule-based alertness state characterization

The aim of the paper is to automatically select the optimal EEG rhythm/channel combinations capable of classifying human alertness states. Four alertness states were considered, namely ‘engaged’, ‘calm’, ‘drowsy’ and ‘asleep’. The features used in the automatic selection are the energies associated with the conventional rhythms, \(\delta , \theta , \alpha , \beta\) and \(\gamma\), extracted from overlapping windows of the different EEG channels. The selection process consists of two stages. In the first stage, the optimal brain regions, represented by sets of EEG channels, are selected using a simple search technique based on support vector machine (SVM), extreme learning machine (ELM) and LDA classifiers. In the second stage, a fuzzy rule-based alertness classification system (FRBACS) is used to identify, from the previously selected EEG channels, the optimal features and their supports. The IF–THEN rules used in FRBACS are constructed using a novel differential evolution-based search algorithm particularly designed for this task. Each alertness state is represented by a set of IF–THEN rules whose antecedent parts contain EEG rhythm/channel combination. The selected spatio-frequency features were found to be good indicators of the different alertness states, as judged by the classification performance of the FRBACS that was found to be comparable to those of the SVM, ELM and LDA classifiers. Moreover, the proposed classification system has the advantage of revealing simple and easy to interpret decision rules associated with each of the alertness states.

     

The microRNA-202 as a Diagnostic Biomarker and a Potential Tumor Suppressor

MicroRNA-202 (miR-202) is a member of the highly conserved let-7 family that was discovered in Caenorhabditis elegans and recently reported to be involved in cell differentiation and tumor biology. In humans, miR-202 was initially identified in the testis where it was suggested to play a role in spermatogenesis. Subsequent research showed that miR-202 is one of the micro-RNAs that are dysregulated in different types of cancer. During the last decade, a large number of investigations has fortified a role for miR-202 in cancer. However, its functions can be double-edged, depending on context they may be tumor suppressive or oncogenic. In this review, we highlight miR-202 as a potential diagnostic biomarker and as a suppressor of tumorigenesis and metastasis in several types of tumors. We link miR-202 expression levels in tumor types to its involved upstream and downstream signaling molecules and highlight its potential roles in carcinogenesis. Three well-known upstream long non-coding-RNAs (lncRNAs); MALAT1, NORAD, and NEAT1 target miR-202 and inhibit its tumor suppressive function thus fueling cancer progression. Studies on the downstream targets of miR-202 revealed PTEN, AKT, and various oncogenes such as metadherin (MTDH), MYCN, Forkhead box protein R2 (FOXR2) and Kirsten rat sarcoma virus (KRAS). Interestingly, an upregulated level of miR-202 was shown by most of the studies that estimated its expression level in blood or serum of cancer patients, especially in breast cancer. Reduced expression levels of miR-202 in tumor tissues were found to be associated with progression of different types of cancer. It seems likely that miR-202 is embedded in a complex regulatory network related to the nature and the sensitivity of the tumor type and therapeutic (pre)treatments. Its variable roles in tumorigenesis are mediated in part thought its oncogene effectors. However, the currently available data suggest that the involved signaling pathways determine the anti- or pro-tumorigenic outcomes of miR-202’s dysregulation and its value as a diagnostic biomarker.     

The Improvement of the Quality of Raffinate Obtained from Solvent Extraction of Lubricating Oils

Abstract

Vacuum distillates of an Egyptian crude oil were subjected to solvent extraction process applying N-methyl-2-pyrrolidone (NMP) and furfural as dearomatization solvents. The study shows that the extraction solvent together with the temperature and solvent-to-oil ratio have a significant effect on the yield and quality of produced lubricating oils. The optimum temperature for extracting light waxy distillates with NMP is 55°C at the solvent-to-feed ratio 2:1. These conditions are appropriate to remove the major portion of aromatics from the raffinate. The apparent activation energy (Ea), enthalpy (ΔH*), entropy (ΔS*), and free energy of activation (ΔG*) were calculated for the solvent dearomatization process.     

Secondary side post regulator for improving cross regulation and reducing standby power consumption

The quest for improved energy savings is driving research into power converter high-efficiency operation under extremely light-load conditions. The use of multiple output converters to satisfy circuit needs and cost requirements adds additional complication to the standby mode power-consumption problem. This is due to the difficulty of satisfying both good cross-regulation under various load conditions as well as high efficiency in the standby mode simultaneously; because topologies that exhibit a good cross-regulation performance, such as resonant converters, generally have a poor efficiency problem under extremely light-loads. A secondary side post regulator (SSPR) is proposed to reduce the standby power consumption and to improve the cross-regulation performance of single- controller multiple-output channel power converters. It is capable of reducing the power consumption of the power converter as well as the SSPR. The SSPR is analysed using its operational principles and small signal models. A 110?W experimental prototype was built to verify the standby power consumption and cross-regulation performance using the proposed SSPR.     

Theoretical bounds for the bit error rate for SAC OCDMA balanced detectors with multiple photodiodes

Photonic Network Communications - In this paper, we derive the theoretical lower and upper bounds for bit error rate (BER) for spectral amplitude coding OCDMA balanced detector (BD) employing...     

Subharmonic synchronous and hybrid mode-locking of a monolithic DBR laser operating at millimeter-wave frequencies

A detailed comparison of subharmonic synchronous and subharmonic hybrid mode-locking of a monolithic distributed Bragg reflector (DBR) laser operating at 33 GHz is presented. Optical injection at the 20th subharmonic frequency (1.65 GHz) has produced a locking range of 10 MHz with negligible amplitude modulation. In comparison, electrical injection at the 4th subharmonic frequency (5.83 GHz) has shown higher levels of amplitude modulation and a narrower locking range (4 MHz). While subharmonic hybrid mode-locking remains a simple and cost effective solution for the generation of low timing jitter high-repetition rate optical pulse trains, subharmonic synchronous mode-locking shows superior performance with regard to reduced amplitude modulation and larger locking range.     

Discrete-time implementation of high-gain observers for numerical differentiation

High-gain observers have been used in non-linear control to estimate derivatives of the output. In this paper, we study discrete-time implementation of high-gain observers and their use as numerical differentiators, in noise-free as well as noisy measurements. We show that discretization using the bilinear transformation method gives better results than other discretization methods. We also show that many of the available numerical differentiators are special cases of the bilinear discrete-time equivalents of full-order or reduced-order high-gain observers.