A Novel artificial neural network (ANN) model was constructed for calibration of a multivariate model for simultaneously quantitative analysis of the quaternary mixture composed of carbamazepine, carvedilol, diazepam, and furosemide. An eighty-four mixing formula where prepared and analyzed spectrophotometrically. Each analyte was formulated in six samples at different concentrations thus twentyfour samples for the four analytes were tested. A neural network of 10 hidden neurons was capable to fit data 100%. The suggested model can be applied for the quantitative chemical analysis for the proposed quaternary mixture.

Identifying breast cancer utilizing artificial intelligence technologies is valuable and has a great influence on the early detection of diseases. It also can save humanity by giving them a better chance to be treated in the earlier stages of cancer. During the last decade, deep neural networks (DNN) and machine learning (ML) systems have been widely used by almost every segment in medical centers due to their accurate identification and recognition of diseases, especially when trained using many datasets/samples. in this paper, a proposed two hidden layers DNN with a reduction in the number of additions and multiplications in each neuron. The number of bits and binary points of inputs and weights can be changed using the mask configuration

      The study was conducted for the detection of Aflatoxin B1(AFB1) in the serum and urine of 42 early and middle childhood patients (26 male and  16 female ) with renal function disease, liver function disease, in additional to atrophy in the growth and other symptoms depending on the information within consent obtained from each patient, in addition to 8 children, apparently healthy, as  the control. The technique of HPLC was used for the detection of AFB1 from all samples. The results showed that out of 42 patient children, 19 (45.2%) gave positive detection of AFB1 in the serum among all age groups patients with a mean of 0.88 ng/ml and a range of (0.12-3.04) ng/ml. This was compared with the cont

Ebastine (EBS) is a non-sedating antihistamine with a long duration of action. This drug has predominantly hydrophobic property causing a low solubility and low bioavailability. Surface solid dispersions (SSD) is an effective technique for improving the solubility and dissolution rate of poorly soluble drugs by using hydrophilic water insoluble carriers.

The present study aims to enhance the solubility and dissolution rate of EBS by using surface solid dispersion technique. Avicel® PH101, Avicel® PH 102, croscarmellose sodium(CCS) and sodium starch glycolate(SSG) were used as water insoluble hydrophilic carriers.

The SSD formulations of EBS were prepared by the solvent evaporation method in different drug:  carrier

Ethanol as a solvent, a precursor of titanium isopropoxide and a stabilizer of either hydrochloric acid or ammonium hydroxide was used to prepare a titanium dioxide aqueous solution. The aqueous solutions with different values of pH and the morphology of the resultant reaction of the nanoparticles of titanium dioxide were investigated. The X-ray diffraction showed that at low temperatures and with acidic solutions, rutile structures are more favorable to grow on titanium dioxide synthesized, while at low and average temperatures and with base solutions, anatase phase is more pronounced. The crystalline form and the re-confirmation of the crystallite size growth were observed by the scanning electron microscopy. The atomic force micr

Engineered geopolymer composite (EGC) is a high-performance material with enhanced mechanical and durability capabilities. Ground granulated blast furnace slag (GGBFS) and silica fume (SF) are common binder materials in producing EGC. However, due to the scarcity and high cost of these materials in some countries, sustainable alternatives are needed. This research focused on producing eco-friendly EGC made of cheaper and more common pozzolanic waste materials that are rich in aluminum and silicon. Rice husk ash (RHA), granite waste powder (GWP), and volcanic pumice powder (VPP) were used as partial substitutions (10–50%) of GGBFS in EGC. The effects of these wastes on workability, unit weight, compressive strength, tensile strengt