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 twenty four 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.

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.

The current study designed to determine the effect of Glucosamine sulfate on the liver tissue of Albino mice .the study included (40)mice divided in to 4 groups(control group had distilled water orally ).The other groups treated with(1000,2000,3000)ml/k .respectively for 8 week .the liver have been taken from dissected animal for microscopic preparation to study the histological changes .Frequently histopathologicale changes appeared in the liver tissue of the exposure groups during (4-8)week .This changes depends on (Dose and Time ). The effects were Congestion ,Infiltration ,Swelling ,Vaculation ,Hyalinization , Amyloid and Necrosis.

Background: The mechanical properties of 3D-printed denture base resins are crucial factors for determining the quality and performance of dentures inside a patient’s mouth. Tensile strength and diametral compressive strength are two properties that could play significant roles in assessing the suitability of a material. Although they measure different aspects of material behavior, a conceptual link exists between them in terms of overall material strength and resilience. Aim: This study aims to investigate the correlation between tensile strength and diametral compressive strength after incorporating 2% ZrO2 nanoparticles (NPs) by weight into 3D-printed denture base resin. Methods: A total of 40 specimens (20 dumbbell-shaped and

: Clobetasol propionate (CP) is a potent corticosteroid used for skin conditions but often causes side effects due its systemic absorption. To improve its solubility and reduce it side effects (like skin irritation, skin atrophy, hypopigmentation and steroidal acne), Microsponge (Msg) has been employed as a unique three-dimensional particle that can encapsulate hydrophilic and lipophilic drugs. This study aims to develop and evaluate CP Msg-loaded hydrogels. Two Clobetasol-loaded ethylcellulose-based Msg formulas were prepared using the quasi-emulsion solvent diffusion method, then they were incorporated into Carbopol hydrogel. Two ratios of Carbopol 940 (1% and 1.5% w/w) were used. The prepared hydrogel were assessed for appearance, pH, dr

Nanocomposite was prepared using unsaturated polyester (UP) resin as a matrix and graphene nanoparticles as a reinforcement material in six percentage weights (0, 0.1, 0.2, 0.3, 1 and 1.5%). Mechanical, calorimetric and thermal studies were performed on the (UP) resin/graphene nanocomposite. All tests showed a clear improvement of all mechanical properties examined (hardness, flexural strength (F.S), impact strength (I.S) and tensile strength (T.S)) with increasing graphene percentage. In addition, the temperature of glass transition and thermal conductivity of this composite increased with increasing graphene content.

In this research, optical communication coding systems are designed and constructed by utilizing Frequency Shift Code (FSC) technique. Calculations of the system quality represented by signal to noise ratio (S/N), Bit Error Rate (BER),and Power budget are done. In FSC system, the data of Nonreturn- to–zero (NRZ ) with bit rate at 190 kb/s was entered into FSC encoder circuit in transmitter unit. This data modulates the laser source HFCT-5205 with wavelength at 1310 nm by Intensity Modulation (IM) method, then this data is transferred through Single Mode (SM) optical fiber. The recovery of the NRZ is achieved using decoder circuit in receiver unit. The calculations of BER and S/N for FSC system a

The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient com