A fast and elitist multiobjective genetic algorithm: NSGA-II

Multi-objective evolutionary algorithms (MOEAs) that use non-dominated sorting and sharing have been criticized mainly for: (1) their O(MN³) computational complexity (where M is the number of objectives and N is the population size); (2) their non-elitism approach; and (3) the need to specify a sharing parameter. In this paper, we suggest a non-dominated sorting-based MOEA, called NSGA-II (Non-dominated Sorting Genetic Algorithm II), which alleviates all of the above three difficulties. Specifically, a fast non-dominated sorting approach with O(MN²) computational complexity is presented. Also, a selection operator is presented that creates a mating pool by combining the parent and offspring populations and selecting the best N solutions (with respect to fitness and spread). Simulation results on difficult test problems show that NSGA-II is able, for most problems, to find a much better spread of solutions and better convergence near the true Pareto-optimal front compared to the Pareto-archived evolution strategy and the strength-Pareto evolutionary algorithm - two other elitist MOEAs that pay special attention to creating a diverse Pareto-optimal front. Moreover, we modify the definition of dominance in order to solve constrained multi-objective problems efficiently. Simulation results of the constrained NSGA-II on a number of test problems, including a five-objective, seven-constraint nonlinear problem, are compared with another constrained multi-objective optimizer, and the much better performance of NSGA-II is observed     

Effects of extracts of spices on rumen methanogenesis,enzyme activities and fermentation of feeds in vitro

BACKGROUND: An experiment was conducted to study the effects of boiling water, methanol and ethanol extracts (0, 0.25 and 0.50 mL) of seeds of Foeniculum vulgare (fennel), flower buds of Syzygium aromaticum (clove), bulbs of Allium sativum (garlic), bulbs of Allium cepa (onion) and roots of Zingiber officinalis (ginger) on rumen methanogenesis, fibrolytic enzyme activities and fermentation characteristics in vitro. RESULTS: Ethanol and methanol extracts of fennel, clove and garlic at 0.50 mL and clove at 0.25 mL inhibited (P < 0.05) methane production. Carboxymethylcellulase activity was reduced (P < 0.05) by ethanol and methanol extracts (0.50 mL) of fennel and clove (0.25 and 0.50 mL). The extracts of clove reduced (0.25 and 0.50 mL) xylanase and acetylesterase activities, and the fennel extract (0.50 mL) reduced (P < 0.05) xylanase activity. However, the extracts of garlic (0.50 mL) increased (P < 0.05) acetylesterase activity. Concentrations of volatile fatty acids were reduced (P < 0.05) by the extracts of garlic and onion. The extracts of garlic caused a decrease (P < 0.05) in acetate:propionate ratio (A:P) at 0.50 mL, whereas A:P was increased (P < 0.05) by the inclusion of 0.50 mL extracts of clove. Methanol and ethanol extracts of clove decreased (P < 0.05) in vitro organic matter degradability. Extracts (0.50 mL) of clove decreased (P < 0.05) the numbers of total protozoa, small entodiniomorphs and holotrichs, whereas extracts of onion, ginger and garlic enhanced (P < 0.05) protozoal numbers (both entodiniomorphs and holotrichs). CONCLUSION: Ethanol and methanol extracts of fennel and garlic have potential to inhibit rumen methanogenesis without adversely affecting rumen fermentation. Copyright © 2009 Society of Chemical Industry     

Synthesis and Anti-Cancer Activity of New Pyrazolinyl-Indole Derivatives: Pharmacophoric Interactions and Docking Studies for Identifying New EGFR Inhibitors

Newly designed series of indole-containing pyrazole analogs, pyrazolinylindoles, were synthesized, and their structures were confirmed based on the spectral data of the ¹H NMR, ¹³C NMR, and HR-MS analyses. Preliminary anti-cancer activity testings were carried out by the National Cancer Institute, United States of America (NCI, USA). Compounds HD02, HD05, and HD12 demonstrated remarkable cytotoxic activities against nine categories of cancer types based cell line panels which included leukemia, colon, breast, melanoma, lungs, renal, prostate, CNS, and ovarian cancer cell lines. The highest cytotoxic effects were exhibited by the compounds HD02 [1-(5-(1-H-indol-3-yl)-3-(p-tolyl)-4,5-dihydro-1H-pyrazol-1-yl)-2-phenylethanone], HD05 [1-(3-(4-chlorophenyl)-5-(1H-indol-3-yl)-4,5-dihydro-1H-pyrazol-1-yl)-2-phenoxyethanone], and HD12 [(3-(4-chlorophenyl)-5-(1H-indol-3-yl)-4,5-dihydro-1H-pyrazol-1-yl)(pyridin-4-yl)methanone] against some of the 56 types of NCI-based cell lines in different panels. Compound HD05 showed the maximum range of cancer cell growth inhibitions against all categories of the cell lines in all nine panels. On average, in comparison to the referral standard, imatinib, at a dose level of 10 µM, the HD05 showed significant activity against leukemia in the range of 78.76%, as compared to the imatinib at 9% of cancer cells’ growth inhibitions. Molecular docking simulation studies were performed in silico on the epidermal growth factor receptor (EGFR) tyrosine kinase, in order to validate the activity.     

Efficient Update of Indexes for Dynamically Changing Web Documents

Recent work on incremental crawling has enabled the indexed document collection of a search engine to be more synchronized with the changing World Wide Web. However, this synchronized collection is not immediately searchable, because the keyword index is rebuilt from scratch less frequently than the collection can be refreshed. An inverted index is usually used to index documents crawled from the web. Complete index rebuild at high frequency is expensive. Previous work on incremental inverted index updates have been restricted to adding and removing documents. Updating the inverted index for previously indexed documents that have changed has not been addressed. In this paper, we propose an efficient method to update the inverted index for previously indexed documents whose contents have changed. Our method uses the idea of landmarks together with the diff algorithm to significantly reduce the number of postings in the inverted index that need to be updated. Our experiments verify that our landmark-diff method results in significant savings in the number of update operations on the inverted index.     

Change point detection for compositional multivariate data

Change point detection algorithms have numerous applications in areas of medical condition monitoring, fault detection in industrial processes, human activity analysis, climate change detection, and speech recognition. We consider the problem of change point detection on compositional multivariate data (each sample is a probability mass function), which is a practically important sub-class of general multivariate data. While the problem of change-point detection is well studied in univariate setting, and there are few viable implementations for a general multivariate data, the existing methods do not perform well on compositional data. In this paper, we propose a parametric approach for change point detection in compositional data. Moreover, using simple transformations on data, we extend our approach to handle any general multivariate data. Experimentally, we show that our method performs significantly better on compositional data and is competitive on general data compared to the available state of the art implementations.

     

Tactical approaches for alleviating distance in global softwaredevelopment

To overcome the problem of distance in global software development, various managers are experimenting and quickly adjusting their tactical approaches. We discuss some emerging approaches and explain their motivations from conceptual and practical perspectives. The most intuitive approach for alleviating distance is to apply communication technologies, but this is not our focus. Rather, we examine tactics that go beyond communication technologies, tactics aimed at reducing intensive collaboration, national and organizational cultural differences, and temporal distance     

Optimisation of Detergent Ingredients for Stain Removal Using Statistical Modelling

Artificially soiled test fabrics are widely used to study the cleaning performance of detergents formulations. In this study, artificial soiled cotton test fabrics were prepared in the laboratory using carbon black as a model soil. Design of experiments was used to optimise the concentration of detergent ingredients for stain removal. A multi‐factorial analysis of variance was used to model the effect of sodium dodecylbenzene sulfonate, nonylphenol ethoxylate, sodium silicate, sodium citrate and sodium carbonate as builders on soil removal. A colourimetric evaluation using the CIELAB system was used to measure soil removal. In general, performance increases with increasing concentration of surfactant, silicate and soda ash.     

Electrochemical treatment of cotton textile-based dyeing effluent

The electrochemical treatment (ECT) of textile wastewater was carried out in a 1.5 dm³ electrolyte batch reactor using iron electrodes. With the four plate configurations, a current density (CD) of 89.2 A/m² and a pH value of 8.5 were found to be optimal, at which maximum reduction in chemical oxygen demand (COD) and colour achieved were 86% and 79%, respectively. Loss of 0.0666 kg/m³ iron electrode and 18.44 kWh/m³ power consumption was observed during ECT with a maximum COD reduction of 79%. The settling characteristics of electrochemically treated effluents as well as the characteristics of foam and residue were also analysed.