Carbides or nitrides thin films present materials with good mechanical properties for industrial applications as they can be coatings at low temperatures serve temperature sensitive surfaces. In this work the effect of the C percentage on the mechanical properties represented by the Young modulus (E) of combinatorial magnetron sputtered TiC_x (34%x˂65%) has been studied. The structure of the produced films is TiC independent on the C concentration. The mechanical properties are increased with increasing the C concentration up to 50%, and then decreasing with further C % increasing. These results can be explained by considering the resultant residual stresses.

Background: The microhardness of a composite resin is a vital parameter that is used to determine its clinical behavior. Measuring the microhardness of a composite resin has been used as an indirect method to assess its degree of conversion and extent of polymerization. The purpose of this in vitro study was to evaluate the effect of three curing distances (0, 2, and 4 mm) on the microhardness of the top and bottom surfaces of three types of flowable bulk-fill composite resins (smart dentin replacement, Opus bulk fill flow, and Tetric N). Material and method: Sixty-three specimens from the three types of composite resins (n=21) were fabricated using Teflon mold with a 4mm depth and a 5 mm internal diameter and cured for 20 seconds. For e

A hierarchically porous structured zeolite composite was synthesized from NaX zeolite supported on carbonaceous porous material produced by thermal treatment for plum stones which is an agro-waste. This kind of inorganic-organic composite has an improved performance because bulky molecules can easily access the micropores due to the short diffusion path to the active sites which means a higher diffusion rate. The composite was prepared using a green synthesis method, including an eco-friendly polymer to attach NaX zeolite on the carbon surface by phase inversion. The synthesized composite was characterized using X-ray diffraction spectrometry, Fourier transforms infrared spectroscopy, field emission scanning electron microscopy, energy d

Pot experiment was carried out at the College of Agriculture – Baghdad University during autumn season, 2007. Thirteen treatments were formulated to evaluate the effectiveness of four applications of Phosphorus (0, 60, 60×2 and 120 Kg P. h-1) and three applications of Zinc (0, 25×2 mg Zn. L-1 and 50 mg Zn. Kg soil-1) along with inoculating seeds of bean with strains mixture 889 and 1865 and non-inoculated treatment, on nodulation, yield and protein content in seeds (N%). The results showed that inoculated plants exceeded on non-inoculated one in all the studied characteristics. While, P and Zn, applications at the rate of 60×2 kg/ha and 25×2 mg/L respectively, significantly, increased, nodulation, yield, protein content in se

Objective: Assessment of health problems and identify demographical information to elderly. Methodology:
it is a descriptive study, data were collected by the researchers depended on the direct interview with the
elderly by using the study instrument (questionnaire) as well as review the records of the geriatric.
Results: The majority of study sample (66%) were males and (24.3%) were within age group (70-74) years,
(44.7%) were widows, and (41.7%) did not read and write. This study applied the international classification
of diseases(short-table) in (11) items, which stated that most of the elderly were complaining from
health problems: debility of hearing (80.65%), eczema or allergies (69.35%), debility of vision (66.9

Face recognition and identity verification are now critical components of current security and verification technology. The main objective of this review is to identify the most important deep learning techniques that have contributed to the improvement in the accuracy and reliability of facial recognition systems, as well as highlighting existing problems and potential future research areas. An extensive literature review was conducted with the assistance of leading scientific databases such as IEEE Xplore, ScienceDirect, and SpringerLink and covered studies from the period 2015 to 2024. The studies of interest were related to the application of deep neural networks, i.e., CNN, Siamese, and Transformer-based models, in face recogni