Fuzzy multi-category proximal support vector classification via generalized eigenvalues

Given a dataset, where each point is labeled with one of M labels, we propose a technique for multi-category proximal support vector classification via generalized eigenvalues (MGEPSVMs). Unlike Support Vector Machines that classify points by assigning them to one of M disjoint half-spaces, here points are classified by assigning them to the closest of M non-parallel planes that are close to their respective classes. When the data contains samples belonging to several classes, classes often overlap, and classifiers that solve for several non-parallel planes may often be able to better resolve test samples. In multicategory classification tasks, a training point may have similarities with prototypes of more than one class. This information can be used in a fuzzy setting. We propose a fuzzy multi-category classifier that utilizes information about the membership of training samples, to improve the generalization ability of the classifier. The desired classifier is obtained by using one-from-rest (OFR) separation for each class, i.e. 1: M -1 classification. Experimental results demonstrate the efficacy of the proposed classifier over MGEPSVMs.     

Structure‐Guided Discovery of Antitubercular Agents That Target the Gyrase ATPase Domain

In this study we explored the pharmaceutically underexploited ATPase domain of DNA gyrase (GyrB) as a potential platform for developing novel agents that target Mycobacterium tuberculosis. In this effort a combination of ligand‐ and structure‐based pharmacophore modeling was used to identify structurally diverse small‐molecule inhibitors of the mycobacterial GyrB domain based on the crystal structure of the enzyme with a pyrrolamide inhibitor (PDB ID: 4BAE ). Pharmacophore modeling and subsequent in vitro screening resulted in an initial hit compound 5 [(E)‐5‐(5‐(2‐(1H‐benzo[d]imidazol‐2‐yl)‐2‐cyanovinyl)furan‐2‐yl)isophthalic acid; IC₅₀=4.6±0.1 μm ], which was subsequently tailored through a combination of molecular modeling and synthetic chemistry to yield the optimized lead compound 24 [(E)‐3‐(5‐(2‐cyano‐2‐(5‐methyl‐1H‐benzo[d]imidazol‐2‐yl)vinyl)thiophen‐2‐yl)benzoic acid; IC₅₀=0.3±0.2 μm ], which was found to display considerable in vitro efficacy against the purified GyrB enzyme and potency against the H₃₇Rv strain of M. tuberculosis. Structural handles were also identified that will provide a suitable foundation for further optimization of these potent analogues.     

Convenient and efficient syntheses of 4-hydroxy-2(E)-nonenal and 4-oxo-2(E)-nonenal

Lipid peroxidation products 4-hydroxy-2(E)-nonenal (HNE) and 4-oxo-2(E)-nonenal (ONE) were conveniently synthesized using Wittig and Horner-Wardsworth-Emmons (HWE) reaction. Wittig or HWE reaction between an easily prepared phosphorane or phosphonate with glyoxal dimethyl acetal gave a protected 4-oxo-2(E)-nonenal. Hydrolysis gave 4-oxo-2(E)-nonenal, whereas reduction followed by hydrolysis gave 4-hydroxy-2(E)-nonenal.     

Multi-category laplacian least squares twin support vector machine

In this paper, we have formulated a Laplacian Least Squares Twin Support Vector Machine called Lap-LST-KSVC for semi-supervised multi-category k-class classification problem. Similar to Least Squares Twin Support Vector Machine for multi-classification(LST-KSVC), Lap-LST-KSVC, evaluates all the training samples into “1-versus-1-versus-rest” classification paradigm, so as to generate ternary output {?1, 0, +1}. Experimental results prove the efficacy of the proposed method over other inline Laplacian Twin Support Vector Machine(Lap-TWSVM) in terms of classification accuracy and computational time.     

Imidazolium‐Based Ionic Liquid as Modulator of Physicochemical Properties of Cationic,Anionic, Nonionic,and Gemini Surfactants

The aggregation morphology of 2 cationic surfactants (cetyldimethylethanolammonium bromide and cetyldiethylethanolammonium bromide), an anionic surfactant (sodium dodecylbenzenesulfonate), a nonionic surfactant (Triton X‐100), and 2 gemini surfactants (16‐4‐16,2Br^?[butanediyi‐1,4‐bis(dimethyldohexylammonium bromide)] and 16‐6‐16,2Br^?[hexanediyi‐1,6‐bis(dimethyldohexylammonium bromide)]) in the presence of the ionic liquid (IL) 1‐ethyl‐3‐methylimidazoliumbromide [Emim][Br] is studied using various techniques such as surface tension, conductivity, and UV–visible and fluorescence spectroscopy. Increasing the concentration of [Emim][Br] results in a decrease in the critical micelle concentration (CMC) value of the surfactants. Various interfacial properties, namely the surface excess concentration (Г_max), minimum area per molecule at the air–water interface (A_min)_, and surface pressure at the CMC (π_cmc), as well as the thermodynamic parameters such as free energy of the given air/water interface (), Gibbs free energy of micelle formation (), Gibbs free energy of micellization per alkyl tail (), Gibbs energy of transfer (), and standard free energy of adsorption () were also investigated. The aggregation number (N_agg) was determined by the fluorescence method. It was observed that N_agg decreased with increasing weight‐percent of the IL.     

Power flow model/calculation for power systems with multiple FACTS controllers

This paper presents a new procedure for steady state power flow calculation of power systems with multiple flexible AC transmission system (FACTS) controllers. The focus of this paper is to show how the conventional power flow calculation method can systematically be modified to include multiple FACTS controllers. Newton–Raphson method of iterative solution is used for power flow equations in polar coordinate. The impacts of FACTS controllers on power flow is accommodated by adding new entries and modifying some existing entries in the linearized Jacobian equation of the same system with no FACTS controllers. Three major FACTS controllers (STATic synchronous COMpensator (STATCOM), static synchronous series compensator (SSSC), and unified power flow controller (UPFC)) are studied in this paper. STATCOM is modeled in voltage control mode. SSSC controls the active power of the link to which it is connected. The UPFC controls the active and the reactive power flow of the link while maintaining a constant voltage at one of the buses. The modeling approach presented in this paper is tested on the 9-bus western system coordinating council (WSCC) power system and implemented using MATLAB software package. The numerical results show the robust convergence of the presented procedure.     

Effects of Essential Oil Vapour Treatment on the Postharvest Disease Control and Different Defence Responses in Two Mango (<Emphasis Type="Italic">Mangifera indica</Emphasis> L.) Cultivars

The purpose of this study was to investigate the inhibitory effect of essential oils (thyme, clove and cinnamon) in vapour phase against the major fungal diseases of mango in vitro and in vivo. Thyme oil vapour (5 μL/Petri plate) completely inhibited the mycelial growth of Colletotrichum gloeosporioides and Lasiodiplodia theobromae under in vitro condition. Thyme oil vapour at 66.7 μL L^?1 significantly reduced artificially inoculated C. gloeosporioides and L. theobromae in mangoes for 4 days. GC/MS analysis revealed thymol, eugenol and benzofuran, 3-methyl as the dominant compounds in thyme, clove and cinnamon oils, respectively. The activities of defence and antioxidant enzymes including peroxidase, chitinase, phenylalanine ammonia-lyase, β-1,3-glucanase, catalase and superoxide dismutase were enhanced by thyme oil (66.7 μL L^?1) treatment and also help to maintain the phenolic content. Hence, postharvest thyme oil vapour treatment may prove to be an alternative means of controlling disease in mangoes.     

Extraction,separation and characterisation of sesame oil lignan for nutraceutical applications

Nutraceutical aspects of sesame oil (SO) are well reported. However, an efficient process for commercial production has not yet been reported. In this study we have aimed at separating lignans from SO aiming at use as nutraceuticals. SO was subjected to sequential extraction with methanol under selected conditions of temperature (70 °C), time (100 min) and solvent:oil ratio (1:1). Under the optimised conditions, the yields of pooled methanolic extract concentrate and residual oil were 10.09 ± 1.0 g and 89.2 ± 1.0 g, respectively. On HPLC analysis, the methanol concentrate showed a total lignan content of 9.32 ± 0.19% (6.54 ± 0.12% sesamin and 2.78 ± 0.31% sesamolin). The concentrate was subjected to low temperature crystallization (4 °C) for the separation of lignan crystals and 51% of the lignans in the oil with 94.4% purity. The crystal-removed methanolic concentrate was saponified and purified; the total lignan content (sesamin and sesamolin) in the unsaponifiable matter (USM) was 64%.The distribution of sesamin and sesamolin in the purified USM was in the proportion 46:54, unlike that in the pure crystals (84:16). Lipid classes (triglycerides, TG; free fatty acids, FFA; diglycerides, DG; monoglycerides, MG; polar lipid, PL) in SO, methanolic extract concentrate and residual oil were separated using thin-layer chromatography (TLC). The amounts of lipid classes were determined by relating the total area of the fatty acid peaks to the area of the peak for internal standard (methyl heptadecanoate), using gas chromatography (GC). The process reported here describes a simple and less cumbersome procedure to produce lignans with high yield and purity for nutraceutical applications.     

Parameters Optimization using Fuzzy Rule Based Multi-Objective Genetic Algorithm for an Event Based Rainfall-Runoff Model

The calibration of an event based rainfall-runoff model for steam flow forecasting is challenging because, it is difficult to measure the parameters physically on the field for each rainfall event. In the present study, Fuzzy rule based Multi-objective Genetic Algorithm (MGA) is developed to optimize the infiltration and roughness parameters of an event based rainfall-runoff model. Nash Sutcliffe Efficiency (NSE), Coefficient of Determination (R²) and transformed volume difference (f(V)) are used as the objective functions of the MGA and all Pareto optimal solutions are identified using Nondominated Sorting method. As three objective functions are included in the calibration, the number of Pareto optimal solutions are also increases and hence, the optimization problem now becomes a decision making problem. Therefore, to select the best solution from all Pareto optimal solutions, a Fuzzy Rule-Based Model (FRBM) is developed to get alternative values of each Pareto optimal solution. First, the Fuzzy rule based MGA is developed by integrating the FRBM with the MGA. Then the Fuzzy rule based MGA is integrated with an event based runoff model. The developed Fuzzy-MGA based runoff model is tested on three different watersheds and the simulation results of Fuzzy-MGA based runoff model are compared with observed data and previous study results. From the simulated events of three watersheds using Fuzzy-MGA based runoff model, it is observed that the mean percentage error in any criteria (i.e. volume of runoff, peak runoff, and time to peak) of the developed model for a watershed is less than 16.33%. It is also noted that the developed Fuzzy-MGA based runoff model is able to produce hydrographs that are much closer to the measured hydrographs.