Background: The objectives of this study are to evaluate the effect of addition of Multi-Wall Carbon Nano Tubes (MWCNTs) of different concentrations (0.05 mg.mL-1,0.25 mg.mL-1,0.5 mg.mL-1and1 mg.mL-1) on dimethyl sulphoxide DMSO and distilled water (DW) on tooth enamel. It intends to evaluate enamel microhardness in (Kg. m-2) pre and post the application of Multi-Wall Carbon Nano Tubes (MWCNTs). Materials and Methods: Thirty specimens prepared for the present study to measure the hardness of the enamel. Results: The results showed that a significant increase in the enamel microhardness for groups 0.05 mg/mL (group B), 0.25 mg/mL (group C), 0.5 mg/mL (group D) and 1 mg/mL (group E) compared with control group (group A) in dimethyl sulphoxi

In this research The study of Multi-level  model (partial pooling model) we consider The partial pooling model which is one Multi-level  models and one of  the Most important models and extensive use and application in the analysis of the data .This Model characterized by the fact that the treatments take hierarchical or structural Form, in this partial pooling models, Full Maximum likelihood FML was used to estimated parameters of partial pooling models (fixed and random ), comparison between the preference of these Models, The application was on the Suspended Dust data in Iraq, The data were for four and a half years .Eight stations were selected randomly  among the stations in Iraq. We use Akaik′s Informa

Protecting information sent through insecure internet channels is a significant challenge facing researchers. In this paper, we present a novel method for image data encryption that combines chaotic maps with linear feedback shift registers in two stages. In the first stage, the image is divided into two parts. Then, the locations of the pixels of each part are redistributed through the random numbers key, which is generated using linear feedback shift registers. The second stage includes segmenting the image into the three primary colors red, green, and blue (RGB); then, the data for each color is encrypted through one of three keys that are generated using three-dimensional chaotic maps. Many statistical tests (entropy, peak signa

A 3D geological model for Mishrif Reservoir in Nasiriyah oil field had been invented "designed" "built". Twenty Five wells namely have been selected lying in Nasiriyah  Governorate in order to build Structural and petrophysical (porosity and water saturation) models represented by a 3D static geological model in three directions .Structural model showed that Nasiriyah oil field represents anticlinal fold its length about 30 km and the width about 10  km, its axis extends toward NW–SE  with structural closure about 65 km . After making zones for Mishrif reservoir, which was divided into 5 zones i.e. (MA zone, UmB 1zone,MmB1 zone ,L.mB1 zone and mB2zone) .Layers were built for each zone depending on petrophysical propertie

Building a 3D geological model from field and subsurface data is a typical task in
geological studies involving natural resource evaluation and hazard assessment. In
this paper a 3D geological model for Asmari Reservoir in Fauqi oil field has been
built using petrel software. Asmari Reservoir belongs to (Oligocene- Lower
Miocene), it represents the second reservoir products after Mishrif Reservoir in Fauqi
field. Five wells namely FQ6, FQ7, FQ15, FQ20, FQ21 have been selected lying in
Missan governorate in order to build Structural and petrophysical (porosity and water
saturation) models represented by a 3D static geological model in three directions
.Structural model shows that Fauqi oil field represents un cylin

In this article, we design an optimal neural network based on new LM training algorithm. The traditional algorithm of LM required high memory, storage and computational overhead because of it required the updated of Hessian approximations in each iteration. The suggested design implemented to converts the original problem into a minimization problem using feed forward type to solve non-linear 3D - PDEs. Also, optimal design is obtained by computing the parameters of learning with highly precise. Examples are provided to portray the efficiency and applicability of this technique. Comparisons with other designs are also conducted to demonstrate the accuracy of the proposed design.

Quantum dots (QDs) of zinc sulfide (ZnS) was prepared by chemical reaction with different potential of hydrogen (pH) and used to fabricate organic quantum dot hybrid junction device. The optical properties of QDs were characterized by ultraviolet-visible (UV-Vis.) and photoluminescence (PL) spectrometer. The results show that the prepared QDs were nanocrystalline with defects formation. The energy gap (E_g)calculated from PL were 3.64, 3.53 and 3.35 eV for pH=8, 10 and 12 respectively. This decreasing of energy gaps is results of the effect the pH solution increases, which in turn leads to the shifted of the PL spectrum toward red shifted, which makes the energy bands at surface states are shallow ban

The effects of using aqueous nanofluids containing covalently functionalized graphene nanoplatelets with triethanolamine (TEA-GNPs) as novel working fluids on the thermal performance of a flat-plate solar collector (FPSC) have been investigated. Water-based nanofluids with weight concentrations of 0.025%, 0.05%, 0.075%, and 0.1% of TEA-GNPs with specific surface areas of 300, 500, and 750 m2/g were prepared. An experimental setup was designed and built and a simulation program using MATLAB was developed. Experimental tests were performed using inlet fluid temperatures of 30, 40, and 50 °C; flow rates of 0.6, 1.0, and 1.4 kg/min; and heat flux intensities of 600, 800, and 1000 W/m2. The FPSC’s efficiency increased as the flow rate and hea