Background Alloys with the addition of zirconium and niobium eliminate the adverse effects of aluminum and vanadium on the nervous system, the possibility of metallosis and the initiation of diseases (including cancers or Alzheimer›s disease). In addition, they have better corrosion resistance, and a Young›s modulus value similar to longitudinal bone tissue. Therefore, only choosing appropriate materials does not guarantee proper functioning of the implants, the surfaces of the implants also have to be suitable to meet the requirements. The laser surface hardening process modifies the surface properties by imparting microstructural changes, whereas surface remelting induces changes in the surface topography, roughness, wettability and w

This research focuses on improvement of the corrosion behaviour of commercial pure titanium (Ti) grade II when exposed to Hank’s solution through different surface treatments. The disc shape of titanium samples were constructed to be divided according to their surface treatment. The first experimental group the Ti sample was exposed to computer numerical control (CNC) fiber laser machine. Whereas, the other experimental group the Ti sample was only coated with Polyetherketon keton (PEKK) by using carbon dioxide (CO2) laser technique while the last experimental group the Ti sample was treated with CNC fiber laser followed by PEKK coating by using CO2 laser technique. All were compared with the untreated control group. The electrochemical a

CD-nanosponges were prepared by crosslinking B-CD with diphenylcarbonate (DPC) using ultrasound assisted technique. 5-FU was incorporated with NS by freeze drying, and the phase solubility study, complexation efficiency (CE) entrapment efficiency were performed. Also, the particle morphology was studied using SEM and AFM. The in-vitro release of 5-FU from the prepared nanosponges was carried out in 0.1N HCl.

5-FU nanosponges particle size was in the nano size. The optimum formula showed a particle size of (405.46±30) nm, with a polydispersity index (PDI) (0.328±0.002) and a negative zeta potential (-18.75±1.8). Also the drug entrapment efficiency varied with the CD: DPC molar ratio from 15.6 % to 30%. The SEM an

In this paper we proposed a new method for selecting a smoothing parameter in kernel estimator to estimate a nonparametric regression function in the presence of missing values. The proposed method is based on work on the golden ratio and Surah AL-E-Imran in the Qur'an. Simulation experiments were conducted to study a small sample behavior. The results proved the superiority the proposed on the competition method for selecting smoothing parameter.

Sodium Dodecyle Sulphate (CH3(CH2)11SO4-Na+) solution was used as a secondary oil recovery by using a lab Model shown in figure-1. The effect of (solution concentration, temperature and salinity) on interfacial tension figure-2 and figure-3 and figure-4 respectively. The best values of these three variables, were taken (those values that give the lowest interfacial tension). Porosity, saturation, permeability were determined in the lab depending on Darcy law. Primary oil recovery was displaced by water until no more oil is obtained then sodium dodecyle sulphate solution was injected. The total oil recovery was 94.8% or 85.7% of the residual oil (secondary oil recovery) figure-5. This method was applied on Iraqi oil field and it gave resu

    The main purpose of the work is to apply a new method, so-called LTAM, which couples the Tamimi and Ansari iterative method (TAM) with the Laplace transform (LT). This method involves solving a problem of non-fatal disease spread in a society that is assumed to have a fixed size during the epidemic period. We apply the method to give an approximate analytic solution to the nonlinear system of the intended model. Moreover, the absolute error resulting from the numerical solutions and the ten iterations of LTAM approximations of the epidemic model, along with the maximum error remainder, were calculated by using MATHEMATICA® 11.3 program to illustrate the effectiveness of the method.

          The primary objective of this paper is to improve a biometric authentication and classification model using the ear as a distinct part of the face since it is unchanged with time and unaffected by facial expressions. The proposed model is a new scenario for enhancing ear recognition accuracy via modifying the AdaBoost algorithm to optimize adaptive learning. To overcome the limitation of image illumination, occlusion, and problems of image registration, the Scale-invariant feature transform technique was used to extract features. Various consecutive phases were used to improve classification accuracy. These phases are image acquisition, preprocessing, filtering, smoothing, and feature extraction. To assess the proposed