A Perturbed Self-organizing Multiobjective Evolutionary Algorithm to solve Multiobjective TSP

Travelling Salesman Problem (TSP) is a very important NP-Hard problem getting focused more on these days. Having improvement on TSP, right now consider the multi-objective TSP (MOTSP), broadened occurrence of travelling salesman problem. Since TSP is NP-hard issue MOTSP is additionally a NP-hard issue. There are a lot of algorithms and methods to solve the MOTSP among which Multiobjective evolutionary algorithm based on decomposition is appropriate to solve it nowadays. This work presents a new algorithm which combines the Data Perturbation, Self-Organizing Map (SOM) and MOEA/D to solve the problem of MOTSP, named Perturbed Self-Organizing multiobjective Evolutionary Algorithm (P-SMEA). In P-SMEA Self-Organizing Map (SOM) is used extract neighborhood relationship information and with MOEA/D subproblems are generated and solved simultaneously to obtain the optimal solution. Data Perturbation is applied to avoid the local optima. So by using the P-SMEA, MOTSP can be handled efficiently. The experimental results show that P-SMEA outperforms MOEA/D and SMEA on a set of test instances

Selenium in Diketopyrrolopyrrole-based Polymers: Influence on Electronic Properties and Charge Carrier Mobilities

Cataloged from PDF version of article.Diketopyrrolopyrrole (DPP)-based pi-conjugated copolymers with thiophene have exceptionally high electron mobilities. This paper investigates electronic properties and charge carrier mobilities of selenophene containing analogues. Two new copolymers, with alternating thiophene DPP (TDPP) and selenophene DPP (SeDPP) units, were synthesized. Two side-chains, hexyl (Hex) and triethylene glycol (TEG) were employed, yielding polymers designated as PTDPPSeDPP-Hex and PTDPPSeDPP-TEG. Selenophene systems have smaller band gaps, with concomitant enhancement of the stability of the reduced state. For both polymers, ambipolar mobilities were observed in organic field-effect transistors (OFET). Grazing incidence X-ray diffraction (GIXD) data indicates preferential edge-on orientation of PTDPPSeDPP-TEG, which leads to superior charge transport properties of the TEG substituted polymer, as compared to its Hex analogue. Time-dependent-density functional theory (TDDFT) calculations corroborate the decrease in the optical band gap with the inclusion of selenophene. Ambipolar charge transport is rationalized by exceptionally wide conduction bands. Delta SCF calculations confirm the larger electron affinity, and therefore the greater stability, of the reduced form of the selenophene-containing DPP polymer in presence of chloroform

TONE MAPPING AND IMAGE ENHANCEMENT USING RECURSIVE MEAN SEPARATE HISTOGRAM EQUALIZATION (RMSHE) TECHNIQUE

ABSTRACT This work aims to develop a Novel Image Enhancement technique to enhance contrast and tone of digital imagery. Contrast Enhancement and White Balancing used for Image Enhancement. Contrast Enhancement is achieved by Recursive Mean Separate Histogram Equalization (RMSHE). White Balancing is used for Tonal correction. Parameter such as PSNR, MSE, MAE are calculated to identify the better Histogram Equalization for contrast enhancement. Keywords: contrast enhancement, white balancing, histogram equalization, mean absolute error, mean square error, meak signal to noise ratio, RMSHE

THREE-DIMENSIONAL QUANTITATIVE STRUCTURE–ACTIVITY RELATIONSHIPS MODELING STUDIES OF PHYTOCHEMICALS FROM BRASSICACEAE AS POTENT INHIBITORS AGAINST TUMOR INFLAMMATION

Objective: The aim of this study was to develop a three-dimensional quantitative structure–activity relationships (3D-QSARs) model for studying theinteraction of different phytochemicals with nuclear factor kappa B (NF-ĸB) inducing kinase, a major regulator in tumor inflammation.Methods: Different phytochemicals (ligands) from Brassicaceae were selected and tested for Lipinski's rule of five and further analyzed using interaction studies (docking) to identify the binding site in the target protein. Ligands with best fit were made to pass through ADMET filter, and the nontoxic ligands were selected based on the pIC50 values.Results: The 3D-QSARs of the ligands were designed using comparative molecular field analysis, and glucoraphanin was found to be stable and fit after subjecting for molecular dynamics simulation with annealing studies.Conclusion: Thus, the model may be prospectively used in drug design to find possible inhibitors of NF-ĸB, which plays a key prominent role in cancer inflammation.Keywords: Three-dimensional quantitative structure–activity relationships, Brassica oleracea, Simulation, Annealing, Nuclear factor kappa B kinase

Torsional angle dependence and switching of inner sphere reorganisation energies for electron and hole charge transfer processes involving phenyl substituted diketopyrrolopyrroles; a density functional study

This document is the Accepted Manuscript version of the following article: Jesus Calvo-Castro, Callum J. McHugh, Andrew J. McLean, ‘Torsional angle dependence and switching of inner sphere reorganisation energies for electron and hole transfer processes involving phenyl substituted diketopyrrolopyrroles; a density functional study’, Dyes and Pigments, Vol. 113, pp. 609-617, February 2015. The Version of Record is available online at doi: https://doi.org/10.1016/j.dyepig.2014.09.031. Published by Elsevier.Determination of inner sphere reorganisation energies is important in the development of organic charge mediating materials and electron transfer reactions. In this study, hole and electron inner sphere reorganisation energies, lambda(h) and lambda(e) respectively, have been computed for the first time for a series of structurally related diketopyrrolopyrrole (DPP) molecular motifs. Inner sphere reorganisation energies for self-exchange electron transfer reactions are calculated as being lower than those associated hole transfer processes in model planar phenyl and thiophenyl substituted DPP systems. It is found that lambda(e) lambda(h).Peer reviewedFinal Accepted Versio

Conceptual Framework on Workplace Deviance Behavior: A Review

This article aims to highlight the importance of organizational climate with both destructive and constructive deviance behaviour in different cultural setting with workplace as a common ground. First, we discuss the need for research in workplace deviance especially destructive and constructive deviance behaviour with the review of previous studies from deviance literature. Next, we present the importance of climate and culture with both destructive and constructive deviance by proposing relationship among them with the help of a framework. The presented theoretical framework can be useful for conducting future empirical research. Finally, we present the conclusion and future research in conducting cross-national research with respect to deviance

Approaches in biotechnological applications of natural polymers

Natural polymers, such as gums and mucilage, are biocompatible, cheap, easily available and non-toxic materials of native origin. These polymers are increasingly preferred over synthetic materials for industrial applications due to their intrinsic properties, as well as they are considered alternative sources of raw materials since they present characteristics of sustainability, biodegradability and biosafety. As definition, gums and mucilages are polysaccharides or complex carbohydrates consisting of one or more monosaccharides or their derivatives linked in bewildering variety of linkages and structures. Natural gums are considered polysaccharides naturally occurring in varieties of plant seeds and exudates, tree or shrub exudates, seaweed extracts, fungi, bacteria, and animal sources. Water-soluble gums, also known as hydrocolloids, are considered exudates and are pathological products; therefore, they do not form a part of cell wall. On the other hand, mucilages are part of cell and physiological products. It is important to highlight that gums represent the largest amounts of polymer materials derived from plants. Gums have enormously large and broad applications in both food and non-food industries, being commonly used as thickening, binding, emulsifying, suspending, stabilizing agents and matrices for drug release in pharmaceutical and cosmetic industries. In the food industry, their gelling properties and the ability to mold edible films and coatings are extensively studied. The use of gums depends on the intrinsic properties that they provide, often at costs below those of synthetic polymers. For upgrading the value of gums, they are being processed into various forms, including the most recent nanomaterials, for various biotechnological applications. Thus, the main natural polymers including galactomannans, cellulose, chitin, agar, carrageenan, alginate, cashew gum, pectin and starch, in addition to the current researches about them are reviewed in this article.. }To the Conselho Nacional de Desenvolvimento Cientfíico e Tecnológico (CNPq) for fellowships (LCBBC and MGCC) and the Coordenação de Aperfeiçoamento de Pessoal de Nvíel Superior (CAPES) (PBSA). This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit, the Project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462) and COMPETE 2020 (POCI-01-0145-FEDER-006684) (JAT)

An automated cervical cancer detection scheme using deeply supervised shuffle attention modified convolutional neural network model

Cervical malignant growth is the fourth most typical reason for disease demise in women around the world. In developing countries, women don’t approach sufficient screening methods because of the costly procedures to undergo examination regularly, scarce awareness and lack of access to the medical centre. Recently, deep learning-based radiomic methods have been introduced in differentiating vessel invasion from non-vessel invasion in Cervical Cancer (CC) by multi-parametric Magnetic Resonance Imaging (MRI). However, this model doesn’t produce sufficient results. In this work, the MRI images are initially pre-processed using bilateral filtering. After pre-processing, the image is segmented by modified U-Net model in order to identify the cancerous region. Extraction of deep semantic information from images by using residual blocks in the processes of contractions and expansions. The last layer of the contracting route uses tightly coupled convolutions in the second phase to speed up feature recycling and feature propagation. It was inferred from the observations that the proposed model was effective as a predictive tool for detecting vessel invasions in preoperative early stages of CC. Proposed model produces 94.00% detection accuracy which is better than the other existing methods