Biology-oriented drug synthesis (BIODS), in vitro urease inhibitory activity,and in silico studies on ibuprofen derivatives

Molecular Diversity - Novel ibuprofen derivatives 1–19 including ibuprofen hydrazide 1, and substituted thiourea derivatives 2–19 were synthesized and characterized by EI-MS, FAB-MS,...     

Improving the Retrieval of Arabic Web Search Results Using Enhanced k-Means Clustering Algorithm

Traditional information retrieval systems return a ranked list of results to a user’s query. This list is often long, and the user cannot explore all the results retrieved. It is also ineffective for a highly ambiguous language such as Arabic. The modern writing style of Arabic excludes the diacritical marking, without which Arabic words become ambiguous. For a search query, the user has to skim over the document to infer if the word has the same meaning they are after, which is a time-consuming task. It is hoped that clustering the retrieved documents will collate documents into clear and meaningful groups. In this paper, we use an enhanced k-means clustering algorithm, which yields a faster clustering time than the regular k-means. The algorithm uses the distance calculated from previous iterations to minimize the number of distance calculations. We propose a system to cluster Arabic search results using the enhanced k-means algorithm, labeling each cluster with the most frequent word in the cluster. This system will help Arabic web users identify each cluster’s topic and go directly to the required cluster. Experimentally, the enhanced k-means algorithm reduced the execution time by 60% for the stemmed dataset and 47% for the non-stemmed dataset when compared to the regular k-means, while slightly improving the purity.     

A Novel Algebraic Structure of (α,β)-Complex Fuzzy Subgroups

A complex fuzzy set is a vigorous framework to characterize novel machine learning algorithms. This set is more suitable and flexible compared to fuzzy sets, intuitionistic fuzzy sets, and bipolar fuzzy sets. On the aspects of complex fuzzy sets, we initiate the abstraction of (α,β)-complex fuzzy sets and then define -complex fuzzy subgroups. Furthermore, we prove that every complex fuzzy subgroup is an (α,β)-complex fuzzy subgroup and define (α,β)-complex fuzzy normal subgroups of given group. We extend this ideology to define (α,β)-complex fuzzy cosets and analyze some of their algebraic characteristics. Furthermore, we prove that (α,β)-complex fuzzy normal subgroup is constant in the conjugate classes of group. We present an alternative conceptualization of (α,β)-complex fuzzy normal subgroup in the sense of the commutator of groups. We establish the (α,β)-complex fuzzy subgroup of the classical quotient group and show that the set of all (α,β)-complex fuzzy cosets of this specific complex fuzzy normal subgroup form a group. Additionally, we expound the index of -complex fuzzy subgroups and investigate the (α,β)-complex fuzzification of Lagrange’s theorem analog to Lagrange’ theorem of classical group theory.     

A New Group Decision-Making Technique under Picture Fuzzy Soft Expert Information

As an extension of intuitionistic fuzzy sets, the theory of picture fuzzy sets not only deals with the degrees of rejection and acceptance but also considers the degree of refusal during a decision-making process; therefore, by incorporating this competency of picture fuzzy sets, the goal of this study is to propose a novel hybrid model called picture fuzzy soft expert sets by combining picture fuzzy sets with soft expert sets for dealing with uncertainties in different real-world group decision-making problems. The proposed hybrid model is a more generalized form of intuitionistic fuzzy soft expert sets. Some novel desirable properties of the proposed model, namely, subset, equality, complement, union and intersection, are investigated together with their corresponding examples. Two well-known operations AND and OR are also studied for the developed model. Further, a decision-making method supporting by an algorithmic format under the proposed approach is presented. Moreover, an illustrative application is provided for its better demonstration, which is subjected to the selection of a suitable company of virtual reality devices. Finally, a comparison of the initiated method is explored with some existing models, including intuitionistic fuzzy soft expert sets.     

Study of Kinetic Freeze-Out Parameters as a Function of Rapidity in pp Collisions at CERN SPS Energies

We used the blast wave model with the Boltzmann–Gibbs statistics and analyzed the experimental data measured by the NA61/SHINE Collaboration in inelastic (INEL) proton–proton collisions at different rapidity slices at different center-of-mass energies. The particles used in this study were π+, π−, K+, K−, and p¯. We extracted the kinetic freeze-out temperature, transverse flow velocity, and kinetic freeze-out volume from the transverse momentum spectra of the particles. We observed that the kinetic freeze-out temperature is rapidity and energy dependent, while the transverse flow velocity does not depend on them. Furthermore, we observed that the kinetic freeze-out volume is energy dependent, but it remains constant with changing the rapidity. We also observed that all three parameters are mass dependent. In addition, with the increase of mass, the kinetic freeze-out temperature increases, and the transverse flow velocity, as well as kinetic freeze-out volume decrease.     

Average scattered field from a random PEC cylinder buried below a slightly rough surface

Scattering from a perfect electric conducting cylinder with random radius buried below a half space dielectric homogenous interface is studied. The cylindrical wave scattered by cylinder is expanded in terms of plane wave spectrum. Small perturbation method is used to study the interaction of each plane wave with the interface. The zeroth order term yields solution for a flat interface, whereas scattering from a rough surface is given by first-order term. Results are obtained for both TM and TE polarizations. Analytical expressions of the average scattered field are obtained and verified using numerical evaluation. Different scattering scenarios are simulated by varying the distribution of the radius. It is observed that average scattering cross section of an ensemble with normal/uniform distribution is almost equal to that of a cylinder with mean radius.     

Lentivirus-mediated transgene delivery to the hippocampus reveals sub-field specific differences in expression

Background  

In the adult hippocampus, the granule cell layer of the dentate gyrus is a heterogeneous structure formed by neurons of different ages, morphologies and electrophysiological properties. Retroviral vectors have been extensively used to transduce cells of the granule cell layer and study their inherent properties in an intact brain environment. In addition, lentivirus-based vectors have been used to deliver transgenes to replicative and non-replicative cells as well, such as post mitotic neurons of the CNS. However, only few studies have been dedicated to address the applicability of these widespread used vectors to hippocampal cells in vivo. Therefore, the aim of this study was to extensively characterize the cell types that are effectively transduced in vivo by VSVg-pseudotyped lentivirus-based vectors in the hippocampus dentate gyrus.     

Melting Heat in Radiative Flow of Carbon Nanotubes with Homogeneous-Heterogeneous Reactions

The present article provides mathematical modeling for melting heat and thermal radiation in stagnationpoint flow of carbon nanotubes towards a nonlinear stretchable surface of variable thickness. The process of homogeneousheterogeneous reactions is considered. Diffusion coefficients are considered equal for both reactant and autocatalyst.Water and gasoline oil are taken as base fluids. The conversion of partial differential system to ordinary differential system is done by suitable transformations. Optimal homotopy technique is employed for the solutions development of velocity, temperature, concentration, skin friction and local Nusselt number. Graphical results for various values of pertinent parameters are displayed and discussed. Our results indicate that the skin friction coefficient and local Nusselt number are enhanced for larger values of nanoparticles volume fraction.     

Elevations of diffusion anisotropy are associated with hyper-acute stroke: a serial imaging study

Diffusion tensor imaging (DTI) studies of human ischemic stroke within 24 h of symptom onset have reported variable findings of changes in diffusion anisotropy. Serial DTI within 24 h may clarify these heterogeneous results. We characterized longitudinal changes of diffusion anisotropy by analyzing discrete ischemic white matter (WM) and gray matter (GM) regions during the hyperacute (2.5-7 h) and acute (21.5-29 h) scanning phases of ischemic stroke onset in 13 patients. Mean diffusivity (MD), fractional anisotropy (FA) and T2-weighted signal intensity were measured for deep and subcortical WM and deep and cortical GM areas in lesions outlined by a > or =30% decrease in MD. Average reductions of approximately 40% in relative (r) MD were observed in all four brain regions during both the hyperacute and acute phases post stroke. Overall, 9 of 13 patients within 7 h post symptom onset showed elevated FA in at least one of the four tissues, and within the same cohort, 11 of 13 patients showed reduced FA in at least one of the ischemic WM and GM regions at 21.5-29 h after stroke. The fractional anisotropy in the lesion relative to the contralateral side (rFA, mean+/-S.D.) was significantly elevated in some patients in the deep WM (1.10+/-0.11, n=4), subcortical WM (1.13+/-0.14, n=4), deep GM (1.07+/-0.06, n=1) and cortical GM (1.22+/-0.13, n=5) hyperacutely (< or =7 h); however, reductions of rFA at approximately 24 h post stroke were more consistent (rFA= 0.85+/-0.12).