Cairo University

About: Cairo University is a education organization based out in Giza, Egypt. It is known for research contribution in the topics: Population & Medicine. The organization has 33532 authors who have published 55581 publications receiving 792654 citations. The organization is also known as: Fuad I University & King Fuad I University.

Search for new physics in events with same-sign dileptons and b jets in pp collisions at √s=8 TeV

Abstract: A search for new physics is performed using isolated same-sign dileptons with at least two b-quark jets in the final state. Results are based on a 4.98 inverse femtobarn sample of proton-proton collisions at a centre-of-mass energy of 7 TeV collected by the CMS detector. No excess above the standard model background is observed. Upper limits at 95% confidence level are set on the number of events from non-standard-model sources. These limits are used to set constraints on a number of new physics models. Information on acceptance and efficiencies are also provided so that the results can be used to confront additional models in an approximate way.

Chaotic multi-verse optimizer-based feature selection

Abstract: The multi-verse optimizer (MVO) is a new evolutionary algorithm inspired by the concepts of multi-verse theory namely, the white/black holes, which represents the interaction between the universes. However, the MVO has some drawbacks, like any other evolutionary algorithms, such as slow convergence and getting stuck in local optima (maximum or minimum). This paper provides a novel chaotic MVO algorithm (CMVO) to avoid these drawbacks, where chaotic maps are used to improve the performance of MVO algorithm. The CMVO algorithm is applied to solve the feature selection problem, in which five benchmark datasets are used to evaluate the performance of CMVO algorithm. The results of CMVO is compared with standard MVO and two other swarm algorithms. The experimental results show that logistic chaotic map is the best chaotic map that increases the performance of MVO, and also the MVO is better than other swarm algorithms.

Multiobjective Optimization of Earthmoving Operations

Abstract: This paper presents a framework for optimizing earthmoving operations using computer simulation and genetic algorithms. It provides a multiobjective optimization tool geared towards selection of near-optimum fleet configurations. The optimization aims at minimizing time and cost of earthmoving operations. The proposed framework considers factors that influence earthmoving operations including equipment availability and project indirect cost. The simulation process, in the proposed methodology, utilizes discrete event simulation and object oriented modeling. The optimization process uses a recently developed genetic algorithm to search for a near-optimum fleet configuration employing Pareto optimality to account for multiobjective optimization. The algorithm considers a set of qualitative and quantitative variables that influence the production of earthmoving operations. The developed framework supports time.cost tradeoff analysis and can assist users in considering what if scenarios with respect to fleet configurations. A numerical example is presented to illustrate a number of practical features of the proposed framework and to demonstrate its capabilities in selecting near-optimum fleet configurations.

Biophysical studies on chitosan-coated liposomes

Abstract: Liposomes have been used as delivery vehicles for stabilizing drugs, overcoming barriers to cellular and tissue uptake, and for directing their contents toward specific sites in vivo. Chitosan is a biological macromolecule derived from crustacean shells and has several emerging applications in drug development, obesity control, and tissue engineering. In the present work, the interaction between chitosan and dipalmitoyl phosphatidylcholine (DPPC) liposomes was studied by transmission electron microscopy (TEM), zeta potential, solubilization using the nonionic detergent octylglucoside (OG), as well as Fourier transform infrared (FTIR) spectroscopy and viscosity measurements. The coating of DPPC liposomes by a chitosan layer was confirmed by electron microscope images and the zeta potential of liposomes. Coating of liposome by chitosan resulted in an increase in liposomal size by addition of a layer of 92 +/- 27.1 nm. The liposomal zeta potential became increasingly positive as chitosan concentration increased from 0.1 to 0.3% w/v, then it held at a relatively constant value. The amount of detergent needed to completely solubilize the liposomal membrane was increased after coating of liposomes with chitosan, indicating an increased membrane resistance to the detergent and hence a change in the natural membrane permeation properties. In the analysis of FTIR spectra of DPPC, the symmetric and antisymmetric CH(2) (at 2,800-3,000 cm(-1)) bands and the C=O (at 1,740 cm(-1)) stretching band were investigated in the absence and presence of the chitosan. It was concluded that appropriate combining of the liposomal and chitosan characteristics might be utilized for the improvement of the therapeutic efficacy of liposomes as a drug delivery system.