High performance self-consolidating concrete HP-SCC is one of the most complex types of concrete which have the capacity to consolidated under its own weight, have excellent homogeneity and high durability. This study aims to focus on the possibility of using industrial by-products like Silica fumes SF in the preparation of HP-SCC enhanced with discrete steel fibers (DSF) and monofilament polypropylene fibers (PPF). From experimental results, it was found that using DSF with volume fraction of 0.50 %; a highly improvements were gained in the mechanical properties of HP-SCC. The compressive strength, splitting tensile strength, flexural strength and elastic modulus improved about 65.7 %, 70.5 %, 41.7 % and 80.3 % at 28 days age, respectively

Background: Even the wide use of dental implants, still there is a proportion of implants are failed due to infection. Much considerable attention has been paid to modify the implant surface. Coating of dental implant with a biocomposite material of suitable properties can improve osseointegration. And this is the main concern of this study. The aim of present study was to evaluate the use of a biocomposite coating of dental implant with (ceramic nano Al2O3 and metalic AgNo3) on the bond strength at bone – implant interface and tissue reaction. Materials and methods: A total number of forty-eight screws, CpTi dental implant used in this study. Half of these screws were coated with a biocomposite material of nano (Al2O3and AgNo3), thi

Palladium nanoparticles are produced by Polyol method. The characterization of the Pd nanoparticle has been conducted by various techniques such as SEM and AFM. The results of Pd powder showed that the particle size is directly proportional to the temperature and the reaction time. The optimum conditions for obtaining minimum nanoparticles size are 45 oC reaction temperature and 60 min reaction time and the smaller particle size achieved is equal to 25 nm. The optical limiting of smaller size nanoparticles has been studied. The palladium nanoparticles appear to be attractive candidates for optical limiting applications.

The current research was conducted to report the synthesis of alumina powder from Iraqi kaolin. The kaolin was transformed to metakaolin by calcinations at temperature 800 °C for three hours. Then the calcined kaolin was treated with (1.5 M) from H2SO4 for 6 hours to form Al2(SO4)3.12H2O solution. The precipitate was dried at 80oC for 10 hours and calcinations at different temperatures for two hours. The samples which result was characterized by X–Ray diffraction (XRD) and X–Ray fluorescence (XRF). The results indicate to the crystalline hydrate aluminum sulfate for the sample that be as – synthesis and when calcinations at 600 oC transformed into aluminum sulfate phase. The phases of alumina which we obtain consisted of a gamma a

This work was conducted to study the ability of locally prepared Zeolite NaY for the reduction of sulfur compounds from Iraqi natural gas by a continuous mode adsorption unit. Zeolite Y was hydrothermally synthesized using abundant kaolin clay as aluminum precursor. Characterization was made using chemical analysis, XRD and BET surface area. Results of the adsorption experiments showed that zeolite Y is an active adsorbent for removal H2S from natural gas and other gas streams. The effect of temperature was found inversely related to the removal efficiency. Increasing bed height was found to increase the removal efficiency at constant flow rate of natural gas. The adsorption capacity was evaluated and its maximum uptake was 5.345 mg H2S/g z

The faujasite type Y zeolite catalyst was prepared from locally available kaolin. For prepared faujasite type NaY zeolite X-ray, FT-IR, BET pore volume and surface area, and silica/ alumina were determined. The Xray and FT-IR show the compatibility of prepared catalyst with the general structure of standard zeolite Y. BET test shows that the surface area and pore volume of prepared catalyst were 360 m2 /g and 0.39 cm3 /g respectively.
The prepared faujasite type NaY zeolite modified by exchanging sodium ion with ammonium ion using ammonium nitrate and then ammonium ion converted to hydrogen ion. The maximum sodium ion exchange with ammonium ion was 53.6%. The catalytic activity of prepared faujasite type NaY, NaNH4Y and NaHY zeolites

This work was conducted to study the ability of locally prepared Zeolite NaY for the reduction of sulfur compounds from Iraqi natural gas by a continuous mode adsorption unit. Zeolite Y was hydrothermally synthesized using abundant kaolin clay as aluminum precursor. Characterization was made using chemical analysis, XRD and BET surface area. Results of the adsorption experiments showed that zeolite Y is an active adsorbent for removal H2S from natural gas and other gas streams. The effect of temperature was found inversely related to the removal efficiency. Increasing bed height was found to increase the removal efficiency at constant flow rate of natural gas. The adsorption capacity was evaluated and its maximum uptake was 5.345 mg H2S/g z

Abstract: E2F6 is a member of the E2F family of transcription factors involved in regulation of a wide variety of genes through both activation and repression. E2F6 has been reported as overexpressed in breast cancers but whether or not this is important for tumor development is unclear. We first checked E2F6 expression in tumor cDNAs and the protein level in a range of breast cancer cell lines. RNA interference-mediated depletion was then used to assess the importance of E2F6 expression in cell lines with regard to cell cycle profile using fluorescence-activated cell sorting and a cell survival assay using (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT). The overexpression of E2F6 was confirmed in breast tumor cDNA samp

This paper includes an experimental study of hydrogen mass flow rate and inlet hydrogen pressure effect on the fuel cell performance. Depending on the experimental results, a model of fuel cell based on artificial neural networks is proposed. A back propagation learning rule with the log-sigmoid activation function is adopted to construct neural networks model. Experimental data resulting from 36 fuel cell tests are used as a learning data. The hydrogen mass flow rate, applied load and inlet hydrogen pressure are inputs to fuel cell model, while the current and voltage are outputs. Proposed model could successfully predict the fuel cell performance in good agreement with actual data. This work is extended to developed fuel cell feedback