Nanoparticles generation by laser ablation of a solid target in a liquid environment is an easy method. Cadmium Telluride (CdTe) colloidal nanoparticles have been synthesized by laser ablation Nd:YAG with wavelengths of 1064nm and double frequency at 532 nm, number of pulses 50 pulses, with pulse energy= 620mJ, 700mJ of a solid target CdTe is immersed in double distilled deionized water (DDIW) and in methanol liquid. Influences of the laser energy and different solutions on the formation and optical characterization of the CdTe nanoparticles have been studied using atomic force microscope (AFM) and the UV-Vis absorption. As a results, it leads to the absorbance in UV-Vis spectra of samples prepared in water at laser wavelength of 532nm i

Flurbiprofen (FLB) is chemically 2-(3- fluoro-4-phenyl phenyl) propanoic acid. It is a nonsteroidal anti-inflammatory drug (NSAID) used in the treatment of rheumatoid arthritis and osteoarthritis. Oral administration of this drug is associated with severe gastrointestinal side effects like ulceration and gastrointestinal bleeding. The solution to this problem lies in the fact that topically applied NSAIDs are safer than orally. This study aims to prepare different topical semisolid formulation of FLB as cream base (o/w), (w/o) and gel base using different gel-forming agents in different concentrations. Comparing characterization properties in addition to release and diffusion study for all the prepared formulas to select the best on

The aim of the present study is to formulate floating effervescent microsponge tablet of the narrow absorption window drug, Baclofen (BFN) for controlling drug release and thereby decrease the side effect of the drug. The microsponges of BFN were prepared by non-aqueous emulsion solvent diffusion method (oil in oil emulsion method). The effects of drug: polymer ratio, stirring time and type of Eudragit polymer  on the physical characteristics of microsponges were investigated and characterized for production yield, loading efficiency, particle size, surface morphology, and in vitro drug release from microsponges. The selected microsponge formula was incorporated into the floating effervescent gastro-retentive tablet. The prepared fl

Colloidal silver nanoparticles were prepared by single step green synthesis using aqueous extracts of the leaves of thyme as a function of different molar concentration of AgNO₃ (1,2,3,4 mM(. The Field Emission Scanning Electron Microscopy (FESEM), UV-Visible and X-ray diffraction (XRD) were used to characterize the resultant AgNPs. The surface Plasmon resonance was observed at wavelength of 444 nm. The four intensive peaks of XRD pattern indicate the crystalline nature and the face centered cubic structure of the AgNPs. The average crystallite size of the AgNPs ranged from 18 to 22 nm. The FESEM image illustrated the well dispersion of the AgNPs and the spherical shape of the nanoparticles with a particle size distribution be

This research presents a method for calculating stress ratio to predict fracture pressure gradient. It also, describes a correlation and list ideas about this correlation. Using the data collected from four wells, which are the deepest in southern Iraqi oil fields (3000 to 6000) m and belonged to four oil fields. These wells are passing through the following formations: Y, Su, G, N, Sa, Al, M, Ad, and B. A correlation method was applied to calculate fracture pressure gradient immediately in terms of both overburden and pore pressure gradient with an accurate results. Based on the results of our previous research , the data were used to calculate and plot the effective stresses. Many equations relating horizontal effective stress and vertica

Diagnosing heart disease has become a very important topic for researchers specializing in artificial intelligence, because intelligence is involved in most diseases, especially after the Corona pandemic, which forced the world to turn to intelligence. Therefore, the basic idea in this research was to shed light on the diagnosis of heart diseases by relying on deep learning of a pre-trained model (Efficient b3) under the premise of using the electrical signals of the electrocardiogram and resample the signal in order to introduce it to the neural network with only trimming processing operations because it is an electrical signal whose parameters cannot be changed. The data set (China Physiological Signal Challenge -cspsc2018) was ad

A new and hybrid deep learning-based approach for diagnosing faults in electric vehicle (EV) drive motors is proposed in this article. This article presents a new and hybrid deep learning-based method of diagnosing faults in the drive motors of electric vehicles (EV). In contrast to standard CNNLSTM approaches that depend on SoftMax classification, the introduced framework combines a Random Forest (RF) classifier to enhance the generalization, interpretability, and robustness of fault prediction. Furthermore meant for use on edge computing equipment with IoT integration, the design allows for real-time monitoring in resource-limited settings. The introduced algorithm utilizes a Random Forest (RF) classifier for accurate fault classification

Breast cancer is highlighted in recent research as one of the most prevalent types of cancer. Timely identification is essential for enhancing patient results and decreasing fatality rates. Utilizing computer-assisted detection and diagnosis early on may greatly improve the chances of recovery by accurately predicting outcomes and developing suitable treatment plans. Grading breast cancer properly, especially evaluating nuclear atypia, is difficult owing to faults and inconsistencies in slide preparation and the intricate nature of tissue patterns. This work explores the capability of deep learning to extract characteristics from histopathology photos of breast cancer. The research introduces a new method called SMOTE-based Convolut

The behavior corrosion inhibition of aluminum alloy (Al6061) in acidic (0.1 M HCl) and saline (3.5% NaCl) solutions was investigated in the absence and the presence of expired diclofenac sodium drug (DSD) as a corrosion inhibitor. The influence of temperature and was studied using electrochemical techniques. In addition, scanning electron microscopy (SEM) was used to study the surface morphology. The results showed that DSD acted as a powerful inhibitor in acidic solutions, while a moderate influence was observed with saline one. Maximum inhibition efficiency was 99.99 and 83.32% in acidic and saline solutions at 150 ppm of DSD, respectively. Corrosion current density that obtained using electrochemical technique was increased with temperat