Mesoporous silica (MPS) nanoparticle was prepared as carriers for drug delivery systems by sol–gel method from sodium silicate as inexpensive precursor of silica and Cocamidopropyl betaine (CABP) as template. The silica particles were characterized by SEM, TEM, AFM, XRD, and N2adsorption–desorption isotherms. The results show that the MPS particle in the nanorange (40-80 nm ) with average diameter equal to 62.15 nm has rods particle morphology, specific surface area is 1096.122 m2/g, pore volume 0.900 cm3/g, with average pore diameter 2.902 nm, which can serve as efficient carriers for drugs. The adsorption kinetic of Ciprofloxacin (CIP) drug was studied and the data were analyzed and found to match well with pseudo-first order kinetic model. The CIP drug-loaded mesoporous silica (CIP-mSiO2) nanoparticles has capacity of about 16.3 mg drug/ mg mSiO2 were achieved, and capable of releasing 26% and 98.6% of their drug content after 90 min in water and PBS solution(pH,7.4) respectively. In-vitro controlled release studies of CIP in Simulated Body Fluid were carried out under stirring conditions. A study on release kinetics and mechanism using Koresmeyer-Pepps model, first order kinetic, and kopcha model shows that the Korsmeyer-Peppas and Kopcha models, both conform more closely to the release data.
Azo ligand 11-(4-methoxyphenyl azo)-6-oxo-5,6-dihydro-benzo[4,5] imidazo[1,2-c] quinazoline-9-carboixylic acid was derived from 4-methoxyaniline and 6-oxo-5,6-dihydro-benzo[4,5]imidazo[1,2-c]quinazoline-9-carboxylic acid. The presence of azo dye was identified by elemental analysis and spectroscopic methods (FT-IR and UV-Vis). The compounds formed have been identified by using atomic absorption in flame, FT.IR, UV-Vis spectrometry magnetic susceptibility and conductivity. In order to evaluate the antibacterial efficiency of ligand and its complexes used in this study three species of bacteria were also examined. Ligand and its complexes showed good bacterial efficiencies. From the obtained data, an octahedral geometry was proposed for all p
... Show MoreThe alluvial fan of Mandali located between latitude 30˚45’00” N longitude 45˚30’00” E in east of Diyala Governorate, Iraq. Thirty-five wells were identified in the study area with average depth of 84 m and estimated area of 21550 ha. A three-dimensional conceptual model was prepared by using GMS program. From wells cross sections, four geological layers have been identified. The hydraulic conductivity of these layers was calculated for steady state condition, where the water levels for nine wells distributed over the study area were observed at same time. Afterward, PEST facility in the GMS was used to estimate the aquifer hydraulic characteristics. Other characteristics such as storage coefficient and specific yield have
... Show MoreIn globalization, the world became open area to competition for the attractive of investment, and the abilities of each country to win the confidence of investors depend upon the preparation to optimize circumstances. The competitiveness is an essential means of expanding the capacity of developed to coexist in an international environment characterized by globalization. While competition describes the market structure, the behavior of investors and business, competitiveness is interested in the evaluation of business performance or countries and compare them in the conditions of competition available in these markets. Regarding Malaysia, which is depend on FDI-Export- Led Growth strategy, it has taking on diffe
... Show MoreDetecting protein complexes in protein-protein interaction (PPI) networks is a challenging problem in computational biology. To uncover a PPI network into a complex structure, different meta-heuristic algorithms have been proposed in the literature. Unfortunately, many of such methods, including evolutionary algorithms (EAs), are based solely on the topological information of the network rather than on biological information. Despite the effectiveness of EAs over heuristic methods, more inherent biological properties of proteins are rarely investigated and exploited in these approaches. In this paper, we proposed an EA with a new mutation operator for complex detection problems. The proposed mutation operator is formulate
... Show MoreGas-lift technique plays an important role in sustaining oil production, especially from a mature field when the reservoirs’ natural energy becomes insufficient. However, optimally allocation of the gas injection rate in a large field through its gas-lift network system towards maximization of oil production rate is a challenging task. The conventional gas-lift optimization problems may become inefficient and incapable of modelling the gas-lift optimization in a large network system with problems associated with multi-objective, multi-constrained, and limited gas injection rate. The key objective of this study is to assess the feasibility of utilizing the Genetic Algorithm (GA) technique to optimize t
The investigation of machine learning techniques for addressing missing well-log data has garnered considerable interest recently, especially as the oil and gas sector pursues novel approaches to improve data interpretation and reservoir characterization. Conversely, for wells that have been in operation for several years, conventional measurement techniques frequently encounter challenges related to availability, including the lack of well-log data, cost considerations, and precision issues. This study's objective is to enhance reservoir characterization by automating well-log creation using machine-learning techniques. Among the methods are multi-resolution graph-based clustering and the similarity threshold method. By using cutti
... Show More
Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob
... Show More