In this work, synthesis of conducting polymeric films namely, PVC thin films was carried out containing Schiff base (L) with Cu²⁺, Cr³⁺, Ni²⁺, Co²⁺, in addition to inspecting the possibilities of measuring energy gap values of PVC-L-M with variety metal ions. These new polymeric films (PVC-L-M) were characterized by FTIR spectrophotometry, energy gap and surface morphology. The optical data recorded that the band gap values are influenced by the type of metals. All modified films have a red shift in optical properties in the ultraviolet region. The PVC-L-Co(II) was the lowest value of the optical band gap, 3.1 eV.

Background: Several pathologies of the oral cavity have been associated with stress. Dental students need to gain assorted proficiencies as theoretical knowledge, clinical proficiencies, and interpersonal dexterity which is accompanied with high level of stress. Uric acid is the major antioxidant in saliva. The aim of this study is to assess the dental caries experience among dental students with different levels of dental environment stress in relation to physicochemical characteristics of whole unstimulated saliva.

Materials and Methods: the total sample is composed of 300 dental students (73 males, 227 female) aged 22-23 years old, from collage of dentistry / university of Baghdad, from the 4t

Two different composite materials were prepared by stir casting method of AA 6061 alloy as a matrix reinforced with two addition different ceramic materials Al₂O₃ and B₄C of grain size   20 µm by 2.5, 5, 7.5 and10% in weight. The composite material with aluminum alloy as a matrix possesses a unique mechanical properties such as: high specific strength and hardness, low density, and high resistance to corrosion and friction wear. This composite is widely used in automotive parts space and marine applications.

Pin-on-disc technique was used to calculate the wear rate for each addition of Al₂O₃ and B₄C particles. Rockwell hardness test and

     Pumpkin waste powder was used as a coloring and strengthening filler in epoxy to prepare a natural gelcoat . The Pumpkin powder was mixed with different weight ratios (1, 2, 3, 4, 5, 6, 7, and 8%) to the epoxy matrix to select the best value of powder addition. The effect of the pumpkin particle size on the mechanical properties (impact, flexural, hardness, and wear loss) using two different sizes (2.5 and 1.25 microns) was studied. The impact strength increased from (10.09 KJ/ m²) for neat epoxy to (14.79 KJ/ m²) for epoxy with  1% of micron pumpkin fibers ( MPF) with particle size 2.5 micrometer and (14.21 KJ/ m²) for epoxy with 4% (1.25 MPF), flexural strength increased from (41.94 MPa) for n

        Genotypic detection of some Antibiotics Resistant genes by using polymerase chain reaction (PCR). (20) Isolates of Acinetobacter baumannii that showed resistance to (Ceftaxim, Cefotaxim, Cefepim and Imipenim) were selected. The results showed that 20 isolates of A. baumannii possess the bla-OXA23 like gene, and that all isolates possess this gene with a percentage (100%). With molecular weight 605 bp. The current study showed that A. baumannii isolates carry 100% bla-OXA51like gene when studied with (20) isolates that are resistant to antibiotics (Imipenim Ceftazidime, Cifepime, Cifexime) that belong to this group of β-lactame with molecular weight 382 bp.   Gene exp

In this research work, a simulator with time-domain visualizers and configurable parameters using a continuous time simulation approach with Matlab R2019a is presented for modeling and investigating the performance of optical fiber and free-space quantum channels as a part of a generic quantum key distribution system simulator. The modeled optical fiber quantum channel is characterized with a maximum allowable distance of 150 km with 0.2 dB/km at =1550nm. While, at =900nm and =830nm the attenuation values are 2 dB/km and 3 dB/km respectively. The modeled free space quantum channel is characterized at 0.1 dB/km at =860 nm with maximum allowable distance of 150 km also. The simulator was investigated in terms of the execution of the BB84 p

The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when