Output feedback control of wind energy conversion system involving a doubly fed induction generator

This paper deals with the problem of controlling a wind energy conversion system (WECS) based on the doubly fed induction generator (DFIG), by IGBT‐based back‐to‐back rectifier‐inverter. The goal of control is to maximize wind energy extraction letting the wind turbine rotor operate in a variable‐speed mode. Interestingly, the present study features the achievement of the above energetic goal without resorting to sensors for wind velocity. The control strategy involves: (i) an output feedback non‐linear regulator designed by the backstepping technique and based on the use of a high gain observer; (ii) a sensorless online reference‐speed optimizer designed using the turbine power characteristic to achieve the maximum power point tracking (MPPT) requirement. It is formally shown that the proposed controller actually meets its control objectives. This theoretical result is confirmed by several simulations.     

Attractive Agents Are More Persuasive

Advances in more ubiquitous human–computer interface technologies have resulted in the increased use of virtual agents, thus highlighting the need to understand the impact these artificial entities have on the human user in terms of how the user both perceives and behaves toward these characters. We report the results of an experiment based on the Desert Survival task, where the effect of agent attractiveness on persuasion was tested. The results suggest that the attractive agent was significantly more persuasive in changing the participant's opinion than was the unattractive agent. Furthermore, greater behavioral change was observed when the participant interacted with the attractive agent, in terms of persuasiveness, including the attribution of more positive personality traits toward this agent (the attractiveness stereotype). These findings provide further evidence of the powerful influence of the agent's physical appearance on the human user in an interaction-based context. We conclude by pointing toward future research and potential within the area.     

An agenda-based framework for multi-issue negotiation

This paper presents a new model for multi-issue negotiation under time constraints in an incomplete information setting. The issues to be bargained over can be associated with a single good/service or multiple goods/services. In our agenda-based model, the order in which issues are bargained over and agreements are reached is determined endogenously, as part of the bargaining equilibrium. In this context we determine the conditions under which agents have similar preferences over the implementation scheme and the conditions under which they have conflicting preferences. Our analysis shows the existence of equilibrium even when both players have uncertain information about each other, and each agent's information is its private knowledge. We also study the properties of the equilibrium solution and determine conditions under which it is unique, symmetric, and Pareto-optimal.     

MODM: multi-objective diffusion model for dynamic social networks using evolutionary algorithm

A lot of research efforts have been made to model the diffusion process in social networks that varies from adoption of products in marketing strategies to disease and virus spread. Previously, a diffusion process is usually considered as a single-objective optimization problem, in which different heuristics or approximate algorithms are applied to optimize an objective of spreading single piece of information that captures the notion of diffusion. However, in real social networks individuals simultaneously receive several pieces of information during their communication. Single-objective solutions are inadequate for collective spread of several information pieces. Therefore, in this paper, we propose a Multi-Objective Diffusion Model (MODM) that allows the modeling of complex and nonlinear phenomena of multiple types of information exchange, and calculate the information worth of each individual from different aspects of information spread such as score, influence and diversity. We design evolutionary algorithm to achieve the multi-objectives in single diffusion process. Through extensive experiments on a real world data set, we have observed that MODM leads to a richer and more realistic class of diffusion model compared to a single objective. This signifies the correlation between the importance of each individual and his information processing capability. Our results indicate that some individuals in the network are naturally and significantly better connected in terms of receiving information irrespective of the starting position of the diffusion process.     

Regional observability of Caputo semilinear fractional systems

This article studies the problem of regional observability of an important class of time-fractional evolution systems involving the Caputo time-fractional derivative. The main goal here is to check the regional observability of the considered system in the desired subregion, $\omega$, of the evolution domain, $\mathrm{\Omega }$. We assume that the linear part of the studied system is approximately regionally observable in the desired subregion $\omega$, and we add some reasonable hypotheses on the system's dynamic, $A$, as well as on the nonlinear operator $N$. Then, with the help of all these assumptions, we attempt to reconstruct the initial state of our system in the desired subregion $\omega$. To do that, we propose an extension of the Hilbert uniqueness method (HUM) to semilinear fractional systems. The main advantage of the HUM approach is that it transforms the reconstruction problem into a solvability one, which is more practical. We also present an algorithm for reconstructing the initial state in $\omega$, which leads to some successful numerical simulations.     

The iNKT Cell–Macrophage Axis in Homeostasis and Disease

Invariant natural killer T (iNKT) cells are CD1d-restricted, lipid-reactive T cells that exhibit preponderant immunomodulatory properties. The ultimate protective or deleterious functions displayed by iNKT cells in tissues are known to be partially shaped by the interactions they establish with other immune cells. In particular, the iNKT cell–macrophage crosstalk has gained growing interest over the past two decades. Accumulating evidence has highlighted that this immune axis plays central roles not only in maintaining homeostasis but also during the development of several pathologies. Hence, this review summarizes the reported features of the iNKT cell–macrophage axis in health and disease. We discuss the pathophysiological significance of this interplay and provide an overview of how both cells communicate with each other to regulate disease onset and progression in the context of infection, obesity, sterile inflammation, cancer and autoimmunity.     

Enhancement of bioactivity and bioavailability of curcumin with chitosan based materials

Curcumin (CUR) has been investigated for its poor accessibility to a site of action or absorption and rapid metabolism to cope with the limited medication and cure applications. This article reviews numerous approaches, such as encapsulated surfactant/polymeric micelles, liposomes, micro/nano-spheres, nano-suspensions/composites, nanocomplex, films, and hydrogels for effective transfer of CUR to target sites. Chitosan (CS), and chitosan derivatives have been found to enhance therapeutic efficacy of CUR. CS/modified-CS based alginate, cyclodextrin, starch, dextran sulfate, ZnO, phytosomes, and poly(butyl) cyanoacrylate drug delivery matrices improved bioavailability, prolonged drug loading and permeability, sustained release rate, improved solubility and stability (prevent metabolic degradation) of CUR, consequently promoting various clinical applications. CS based polysaccharide, protein, and metal oxide drug delivery nano formulations advantageously participated to improve biological activities of CUR. We have attempted to summarize these delivery approaches, and reviewed future trends/strategies to permit the introduction of CUR as practical therapeutic drug.     

Synthesis of 1‐Naphthol by a Natural Peroxygenase Engineered by Directed Evolution

There is an increasing interest in enzymes that catalyze the hydroxylation of naphthalene under mild conditions and with minimal requirements. To address this challenge, an extracellular fungal aromatic peroxygenase with mono(per)oxygenase activity was engineered to convert naphthalene selectively into 1‐naphthol. Mutant libraries constructed by random mutagenesis and DNA recombination were screened for peroxygenase activity on naphthalene together with quenching of the undesired peroxidative activity on 1‐naphthol (one‐electron oxidation). The resulting double mutant (G241D‐R257K) obtained from this process was characterized biochemically and computationally. The conformational changes produced by directed evolution improved the substrate's catalytic position. Powered exclusively by catalytic concentrations of H₂O₂, this soluble and stable biocatalyst has a total turnover number of 50 000, with high regioselectivity (97 %) and reduced peroxidative activity.