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.
Propranolol is a nonselective-adrenergic blocker used in the treatment of hypertension, cardiac arrhythmias, and angina pectoris. A significant problem in propranolol therapy is that it undergoes extensive presystemic metabolism after oral administration leading to reduced bioavailability. In this study, two new propranolol derivatives have been designed, synthesized and characterized. These compounds were formed by acylation of propranolol followed by nucleophilic substitution reaction of acylated propranolol, these derivatives were analyzed for IR, CHN, melting points, and evaluated for their lipophilic properties compared with propranolol. The lower partition coefficient of these two derivatives revealed that the prodrug approach may be
... Show MoreReducing global warming potential (GWP) of refrigerants is needed to the decrease of ozone-depleting of refrigeration systems leakages. Refrigerant R1234yf is now used to substitute R134a inside mobile air conditioning systems. Thermodynamic properties of R1234yf are similar to R134a. Also, it has a very low GWP of 4, compared to 1430 for R134a, making it a proper choice for future automobile refrigerants. The purpose of this research is to represent the main operating and performance differences between R1234yf and R134a. Experimental analysis was carried out on the automotive air conditioning system (AACS) with 3 kW nominal capacity, to test and compare the performance of R134a with R1234yf. Experiments were accomplish
... Show MoreIn this paper, the goal of proposed method is to protect data against different types of attacks by unauthorized parties. The basic idea of proposed method is generating a private key from a specific features of digital color image such as color (Red, Green and Blue); the generating process of private key from colors of digital color image performed via the computing process of color frequencies for blue color of an image then computing the maximum frequency of blue color, multiplying it by its number and adding process will performed to produce a generated key. After that the private key is generated, must be converting it into the binary representation form. The generated key is extracted from blue color of keyed image then we selects a c
... Show MoreThe choice of binary Pseudonoise (PN) sequences with specific properties, having long period high complexity, randomness, minimum cross and auto- correlation which are essential for some communication systems. In this research a nonlinear PN generator is introduced . It consists of a combination of basic components like Linear Feedback Shift Register (LFSR), ?-element which is a type of RxR crossbar switches. The period and complexity of a sequence which are generated by the proposed generator are computed and the randomness properties of these sequences are measured by well-known randomness tests.
Face recognition is a crucial biometric technology used in various security and identification applications. Ensuring accuracy and reliability in facial recognition systems requires robust feature extraction and secure processing methods. This study presents an accurate facial recognition model using a feature extraction approach within a cloud environment. First, the facial images undergo preprocessing, including grayscale conversion, histogram equalization, Viola-Jones face detection, and resizing. Then, features are extracted using a hybrid approach that combines Linear Discriminant Analysis (LDA) and Gray-Level Co-occurrence Matrix (GLCM). The extracted features are encrypted using the Data Encryption Standard (DES) for security
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