Comments, with reply, on `Passive equalization of semiconductordiode laser frequency modulation' by S.B. Alexander et al

Some flaws in a recent article by S.B. Alexander et al. (ibid., vol.7, no.1, p.11-23, Jan. 1989) on the theory of equalization of FM response of a laser diode using passive filters are noted. An error has occurred as a result of assuming a constant C as a positive instead of negative. When C is negative and large, the equalization network cannot be realized with passive networks. Also the simulated time waveform shown in the article for the optical frequency of an equalized laser does not show some spikes which are expected theoretically. The spikes occur as a result of an imperfect equalization provided by the proposed passive filters that were realized assuming C as positive. In replying the original author feels that the comments and observations result simply from attempting to extend the simple FM transfer-function model far beyond its limits while trying to introduce unnecessary theoretical rigor     

A comprehensive review on theoretical framework‐based electric vehicle consumer adoption research

Green vehicles, such as electric vehicles (EVs), are getting noteworthy popularity among consumers worldwide. The purpose of this paper is to establish EVs as a feasible long‐term solution for the future of technology in the vehicle industry, which can decrease the current dependency on fossil fuels and also decrease greenhouse gas (GHG) emissions. As a part of long‐term benefits, the adoption of EVs gives environmentally friendly innovation to society. Despite positive environmental implications, the total number of EVs in usage is still inadequate. One of the major causes of this insubstantial adoption of EVs is largely dependent on the perceptions of consumers regarding EVs. However, this particular research study offers an inclusive outline on the existing hurdles for consumer adoption of EVs as well as a framework of the theoretical standpoints that were developed for the adoption behaviour, in addition to considering consumer intentions in the direction of EVs. In this particular study, the researcher found that the literature regarding EV adoption tried to address only the diffusion method of EVs. Whereas this study highlights consumer innovations, which provides a wide insight on consumer emotions to overlook the major aspect in consumer EVs' adoption research. The theme of this particular literature can be implemented in order to better understand the consumers' emotions and behaviour towards the adoption of EVs. The scholars further stated that there is a possible cause for more recent developments within the technological adoption part that can assist to be a standard for upcoming developments. For the last few years, knowledge regarding the problems surrounding the adoption and diffusion of EVs has gained less attention. This study expands this line of research by focusing on making a chance for developing the theoretical frameworks in terms of adding emotions in a psychological perspective where consumer behaviour and ethics are considered. Copyright © 2016 John Wiley & Sons, Ltd.     

Secondary population implementation in multi-objective evolutionary algorithm for scheduling of FMS

Any practical implementation of any multi-objective evolutionary algorithm (MOEA) must include a secondary population composed of all Pareto-optimal solutions found during its search process. Such an implementation with an active participation of solutions from the secondary population into the generational population of the genetic cycle is expected to improve the effectiveness of the MOEA. In this work, two kinds of secondary population, one with set of non-dominated solutions and another with a set of inferior solutions, accrued out of the generation cycles are constructed, and with different combinations of feeding of solutions from these two secondary populations, seven different implementation schemes are designed with an aim of intensifying the convergence and diversification capabilities of the genetic process of MOEA. All the schemes were implemented in a genetic algorithm-based MOEA designed to solve the scheduling problem with dual objectives for a flexible manufacturing system and tested with common experimental data. The performances of the schemes are compared, and the most appropriate implementation scheme is proposed.     

Microstructural and magnetic studies on P/M processed (Nd14.9Dy1.9)(Fe65.0Co8.0Cu1.0Ga1.0Nb0.7) B7.5 alloy

Sintered samples of (Nd_14.9 Dy_1.9) (Fe₆₅ Co₈ Cu_1.0 Ga_1.0 Nb_0.7)B_7.5 were prepared and subjected to stepwise annealing in the temperature range 875 K–675 K. The XRD and metallographic (optical and electron microscopy) studies reveal a multi-phase microstructure with each phase showing different solubility of the alloying additions. This alloy has T _C of 705 K with an intrinsic coercivity of 1000 kA/m and energy product of 250 kJ/m³ at RT. Solubility of Co into the matrix phase and that of Ga and Cu into the Nd-rich grain boundary phase are considered to be the main contributing factors for the significant enhancement in T _C and H _ci respectively of the multi-component alloy when compared to those of ternary NdFeB, wherein H _ci = 720 kA/m and T _C = 585 K.     

A pattern based PSO approach for block matching in motion estimation

Block matching motion estimation is a popular method in developing video coding applications. A new algorithm has been proposed for reducing the number of search points using a pattern based particle swarm optimization (PSO) for motion estimation. The conventional particle swarm optimization has been modified to provide accurate solutions in motion estimation problems. This leads to very low computational cost and good estimation accuracy. Due to the center biased nature of the videos, the proposed approach uses an initial pattern to speed up the convergence of the algorithm. Simulation results show that improvements over other fast block matching motion estimation algorithms could be achieved with 31%～63% of search point reduction, without degradation of image quality.     

Removal of manganese from water by electrocoagulation: Adsorption,kinetics and thermodynamic studies

The present study provides an electrocoagulation process for the removal of manganese (Mn) from water using magnesium as anode and galvanised iron as cathode. The various operating parameters like effect of initial pH, current density, electrode configuration, inter‐electrode distance, coexisting ions and temperature on the removal efficiency of Mn were studied. The results showed that the maximum removal efficiency of 97.2% at a pH of 7.0 was achieved at a current density 0.05 A/dm² with an energy consumption of 1.151 kWhr/m³. Thermodynamic parameters, including the Gibbs free energy, enthalpy and entropy, indicated that the Mn adsorption of water on magnesium hydroxides was feasible, spontaneous and endothermic. The experimental data were fitted with several adsorption isotherm models to describe the electrocoagulation process. The adsorption of Mn preferably fitting the Langmuir adsorption isotherm suggests monolayer coverage of adsorbed molecules. In addition, the adsorption kinetic studies showed that the electrocoagulation process was best described using the second‐order kinetic model at the various current densities. © 2012 Canadian Society for Chemical Engineering     

Hybrid genetic algorithms and line search method for industrial production planning with non-linear fitness function

Many engineering, science, information technology and management optimization problems can be considered as non-linear programming real-world problems where all or some of the parameters and variables involved are uncertain in nature. These can only be quantified using intelligent computational techniques such as evolutionary computation and fuzzy logic. The main objective of this research paper is to solve non-linear fuzzy optimization problem where the technological coefficient in the constraints involved are fuzzy numbers, which was represented by logistic membership functions using the hybrid evolutionary optimization approach. To explore the applicability of the present study, a numerical example is considered to determine the production planning for the decision variables and profit of the company.     

Dynamics of Bacterial Community Structure in the Rhizosphere and Root Nodule of Soybean: Impacts of Growth Stages and Varieties

Bacterial communities in rhizosphere and root nodules have significant contributions to the growth and productivity of the soybean (Glycine max (L.) Merr.). In this report, we analyzed the physiological properties and dynamics of bacterial community structure in rhizosphere and root nodules at different growth stages using BioLog EcoPlate and high-throughput sequencing technology, respectively. The BioLog assay found that the metabolic capability of rhizosphere is in increasing trend in the growth of soybeans as compared to the bulk soil. As a result of the Illumina sequencing analysis, the microbial community structure of rhizosphere and root nodules was found to be influenced by the variety and growth stage of the soybean. At the phylum level, Actinobacteria were the most abundant in rhizosphere at all growth stages, followed by Alphaproteobacteria and Acidobacteria, and the phylum Bacteroidetes showed the greatest change. But, in the root nodules Alphaproteobacteria were dominant. The results of the OTU analysis exhibited the dominance of Bradyrhizobium during the entire stage of growth, but the ratio of non-rhizobial bacteria showed an increasing trend as the soybean growth progressed. These findings revealed that bacterial community in the rhizosphere and root nodules changed according to both the variety and growth stages of soybean in the field.     

Ubiquitin-Specific Protease 29 Regulates Cdc25A-Mediated Tumorigenesis

Cell division cycle 25A (Cdc25A) is a dual-specificity phosphatase that is overexpressed in several cancer cells and promotes tumorigenesis. In normal cells, Cdc25A expression is regulated tightly, but the changes in expression patterns in cancer cells that lead to tumorigenesis are unknown. In this study, we showed that ubiquitin-specific protease 29 (USP29) stabilized Cdc25A protein expression in cancer cell lines by protecting it from ubiquitin-mediated proteasomal degradation. The presence of USP29 effectively blocked polyubiquitination of Cdc25A and extended its half-life. CRISPR-Cas9-mediated knockdown of USP29 in HeLa cells resulted in cell cycle arrest at the G0/G1 phase. We also showed that USP29 knockdown hampered Cdc25A-mediated cell proliferation, migration, and invasion of cancer cells in vitro. Moreover, NSG nude mice transplanted with USP29-depleted cells significantly reduced the size of the tumors, whereas the reconstitution of Cdc25A in USP29-depleted cells significantly increased the tumor size. Altogether, our results implied that USP29 promoted cell cycle progression and oncogenic transformation by regulating protein turnover of Cdc25A.