Genetic Algorithm-based Adaptive Optimization for Target Tracking in Wireless Sensor Networks

In this paper, we address the problem of genetic algorithm optimization for jointly selecting the best group of candidate sensors and optimizing the quantization for target tracking in wireless sensor networks. We focus on a more challenging problem of how to effectively utilize quantized sensor measurement for target tracking in sensor networks by considering best group of candidate sensors selection problem. The main objective of this paper is twofold. Firstly, the quantization level and the group of candidate sensors selection are to be optimized in order to provide the required data of the target and to balance the energy dissipation in the wireless sensor network. Secondly, the target position is to be estimated using quantized variational filtering (QVF) algorithm. The optimization of quantization and sensor selection are based on the Fast and Elitist Multi-objective Genetic Algorithm (NSGA-II). The proposed multi-objective (MO) function defines the main parameters that may influence the relevance of the participation in cooperation for target tracking and the transmitting power between one sensor and the cluster head (CH). The proposed algorithm is designed to: i) avoid the problem lot of computing times and operation counts, and ii) reduce the communication cost and the estimation error, which leads to a significant reduction of energy consumption and an accurate target tracking. The computation of these criteria is based on the predictive information provided by the QVF algorithm. The simulation results show that the NSGA-II -based QVF algorithm outperforms the standard quantized variational filtering algorithm and the centralized quantized particle filter.     

Quality assessment of refined oil blends during repeated deep frying monitored by SPME–GC–EIMS,GC and chemometrics

The aim of this study was to investigate the effect of the refined palm oil addition (20%) on the fatty acid and sterol compositions of refined olive oil or refined soya bean oil and also to investigate the formation of total polar compounds and volatile compounds in these oil blends during fifty successive deep‐frying sessions of potato fries at 180 °C. The blend of refined olive oil and refined palm oil exhibited a higher chemical stability during the frying process than that of refined soya bean oil and refined palm oil. Indeed, the total polar compounds and volatile compounds formed, especially 2,4‐decadienal, were found to be relatively increased in the refined soya bean oil/refined palm oil blend reaching 36.50% and 46.70%, respectively, after fifty deep‐frying sessions. Moreover, the degradation of linoleic acid and β‐sitosterol was significantly (P < 0.05) observed for the refined soya bean oil/refined palm oil blend. The results have proven that the proper blending of monounsaturated refined olive oil with refined palm oil increases its stability and hence improves the quality of such olive oil during frying process.     

Effects of Trichoderma harzianum on Photosynthetic Characteristics and Fruit Quality of Tomato Plants

The beneficial role of fungi from the Trichoderma genus and its secondary metabolites in promoting plant growth, uptake and use efficiency of macronutrients and oligo/micro-nutrients, activation of plant secondary metabolism and plant protection from diseases makes it interesting for application in environmentally friendly agriculture. However, the literature data on the effect of Trichoderma inoculation on tomato fruit quality is scarce. Commercially used tomato cultivars were chosen in combination with indigenous Trichodrema species previously characterized on molecular and biochemical level, to investigate the effect of Trichoderma on photosynthetic characteristics and fruit quality of plants grown in organic system of production. Examined cultivars differed in the majority of examined parameters. Response of cultivar Gružanski zlatni to Trichoderma application was more significant. As a consequence of increased epidermal flavonols and decreased chlorophyll, the nitrogen balance index in leaves has decreased, indicating a shift from primary to secondary metabolism. The quality of its fruit was altered in the sense of increased total flavonoids content, decreased starch, increased Bioaccumulation Index (BI) for Fe and Cr, and decreased BI for heavy metals Ni and Pb. Higher expression of swolenin gene in tomato roots of more responsive tomato cultivar indicates better root colonization, which correlates with observed positive effects of Trichodrema.     

Finite element modeling and shake-table testing of unidirectional infill masonry walls under out-of-plane dynamic loads

The dynamic out-of-plane response of unreinforced masonry walls is investigated. The study combines analytical, numerical, and experimental methodologies. The paper focuses on structural schemes that involve supporting at the base and the top and yield a unidirectional (one-way) flexural action. First, the modeling concepts for the nonlinear dynamic analysis are discussed and used as a basis for a finite element formulation. The element is based on a first-order shear deformation theory with large displacements, moderate rotations, small strains, material nonlinearity, and a Rayleigh type of viscoelastic damping. The nonlinearities due to cracking and the inelastic response under cyclic compression are introduced through the constitutive model for the mortar. The experimental part includes shake-table testing under different levels of out-of-plane excitation and compressive loading. The experimental results and the numerical model quantify a range of physical phenomena, including the dynamic arching and rocking effects, the coupling of the axial (in the height direction) and the out-of-plane responses, the role of axial loading, and the vulnerability of the masonry construction to dynamic loads. The comparison between the numerical results and the experimental results examines the capabilities of the model and gains insight into the nonlinear dynamics of the masonry wall.     

VELOCITY AND TEMPERATURE DISTRIBUTIONS BETWEEN PARALLEL POROUS PLATES WITH HALL EFFECT AND VARIABLE PROPERTIES

Unsteady hydromagnetic flow and heat transfer between two parallel porous plates is studied with the Hall effect and temperature-dependent properties. The fluid is acted upon by a constant pressure gradient and an external uniform magnetic field, and uniform suction and injection are applied perpendicular to the parallel plates. A numerical solution for the governing nonlinear equations of motion and the energy equation is obtained. The effects of the Hall term and the temperature-dependent viscosity and thermal conductivity on both the velocity and temperature distributions are examined.     

Molecular Mechanisms of Nitric Oxide (NO) Signaling and Reactive Oxygen Species (ROS) Homeostasis during Abiotic Stresses in Plants

Abiotic stressors, such as drought, heavy metals, and high salinity, are causing huge crop losses worldwide. These abiotic stressors are expected to become more extreme, less predictable, and more widespread in the near future. With the rapidly growing human population and changing global climate conditions, it is critical to prevent global crop losses to meet the increasing demand for food and other crop products. The reactive gaseous signaling molecule nitric oxide (NO) is involved in numerous plant developmental processes as well as plant responses to various abiotic stresses through its interactions with various molecules. Together, these interactions lead to the homeostasis of reactive oxygen species (ROS), proline and glutathione biosynthesis, post-translational modifications such as S-nitrosylation, and modulation of gene and protein expression. Exogenous application of various NO donors positively mitigates the negative effects of various abiotic stressors. In view of the multidimensional role of this signaling molecule, research over the past decade has investigated its potential in alleviating the deleterious effects of various abiotic stressors, particularly in ROS homeostasis. In this review, we highlight the recent molecular and physiological advances that provide insights into the functional role of NO in mediating various abiotic stress responses in plants.     

Modulations in Chlorophyll a Fluorescence Based on Intensity and Spectral Variations of Light

Photosynthetic efficiency is significantly affected by both qualitative and quantitative changes during light exposure. The properties of light have a profound effect on electron transport and energy absorption in photochemical reactions. In addition, fluctuations in light intensity and variations in the spectrum can lead to a decrease in photosystem II efficiency. These features necessitate the use of a simple and suitable tool called chlorophyll a fluorescence to study photosynthetic reactions as a function of the aforementioned variables. This research implies that chlorophyll a fluorescence data can be used to determine precise light conditions that help photoautotrophic organisms optimally function.     

Biochemical Characterization of New Gemifloxacin Schiff Base (GMFX-o-phdn) Metal Complexes and Evaluation of Their Antimicrobial Activity against Some Phyto- or Human Pathogens

Four novel ligand-metal complexes were synthesized through the reaction of Fe(III), pleaseCo(II), Zn(II), and Zr(IV) with Schiff base gemifloxacin reacted with ortho-phenylenediamine (GMFX-o-phdn) to investigate their biological activities. Elemental analysis, FT-IR, ¹H NMR, UV-visible, molar conductance, melting points, magnetic susceptibility, and thermal analyses have been carried out for insuring the chelation process. The antimicrobial activity was carried out against Monilinia fructicola, Aspergillus flavus, Penicillium italicum, Botrytis cinerea, Escherichia coli, Bacillus cereus, Pseudomonas fluorescens, and P. aeruginosa. The radical scavenging activity (RSA%) was in vitro evaluated using ABTS method. FT-IR spectra indicated that GMFX-o-phdn chelated with metal ions as a tetradentate through oxygen of carboxylate group and nitrogen of azomethine group. The data of infrared, ¹H NMR, and molar conductivity indicate that GMFX–o-phdn reacted as neutral tetra dentate ligand (N₂O₂) with metal ions through the two oxygen atoms of the carboxylic group (oxygen containing negative charge) and two nitrogen atoms of azomethine group (each nitrogen containing a lone pair of electrons) (the absent of peak corresponding to ν(COOH) at 1715 cm⁻¹, the shift of azomethine group peak from 1633 cm⁻¹ to around 1570 cm⁻¹, the signal at 11 ppm of COOH and the presence of the chloride ions outside the complex sphere). Thermal analyses (TG-DTG/DTA) exhibited that the decaying of the metal complexes exists in three steps with the final residue metal oxide. The obtained data from DTA curves reflect that the degradation processes were exothermic or endothermic. Results showed that some of the studied complexes exhibited promising antifungal activity against most of the tested fungal pathogens, whereas they showed higher antibacterial activity against E. coli and B. cereus and low activity against P. fluorescens and P. aeruginosa. In addition, GMFX-o-phdn and its metal complexes showed strong antioxidant effect. In particular, the parent ligand and Fe(III) complex showed greater antioxidant capacity at low tested concentrations than that of other metal complexes where their IC₅₀ were 169.7 and 164.6 µg/mL, respectively.     

Bayesian methods for time‐varying state and parameter estimation in induction machines

This paper addresses the problem of nonlinear time‐varying state and parameter estimation of induction machines (IMs) on the basis of a third‐order electrical model. The objectives of this paper are threefold. The first objective is to propose the use of an improved particle filter (IPF) with better proposal distribution for nonlinear and non‐Gaussian state and parameter estimation. The second objective is to extend the state and parameter estimation techniques (i.e., extended Kalman filter (EKF), unscented Kalman filter (UKF), particle filter (PF), and IPF) to better handle nonlinear and non‐Gaussian processes without a priori state information, by utilizing a time‐varying assumption of statistical parameters. In this case, the state vector to be estimated at any instant is assumed to follow a Gaussian model, where the expectation and the covariance matrix are both random. The third objective is to compare the performances of EKF, UKF, PF, and IPF in estimating the states of the power process model representing the IM (i.e, the rotor speed, the rotor flux, the stator flux, the rotor resistance, and the magnetizing inductance) and their abilities to estimate some of the key system parameters, which are needed to define the IM process model. The results show that the IPF provides a significant improvement over the PF because, unlike the PF, which depends on the choice of sampling distribution used to estimate the posterior distribution, the IPF yields an optimum choice of the sampling distribution, which also accounts for the observed data. This conclusion is also supported by the experimental results. Copyright © 2014 John Wiley & Sons, Ltd.