Nanoparticle has pulled in expanding consideration with the developing enthusiasm for nanotechnology which hold potential as essential segments for development applications. In the present work, a copper nanoparticle is manufactured as a suspension in distilled water by beating a bulk copper target with laser source (532 nm wavelength, 10 ns pulse duration and 10 Hz repletion rate) via method. UV- visible absorption spectra and AFM analysis has been done to observe the effect of repetition rate for the pulsation of laser. Copper nanoparticles (Cu-NPs) were successfully synthesized with green color. The Cu- NPs have very high purity because the preparation was managed in aqueous media to eliminate ambient contaminations.  Absorption

The current study is concerned with investigating the difficulties that Iraqi EFL learners of English may face when translating English collective nouns. Such collective nouns as committee, government, , jury , Parliament , etc. are considered singular when the concept of the unity as a group is emphasized , but when the concept of the individuals or numbers is emphasized they are treated as plural. A sample of twenty undergraduate students have been selected randomly to translate certain English collective nouns in some selected political texts in order to find out the difficulties they might face in rendering them into Arabic. It is hypothesized that most of the testees have used the singular form rather than the plural ignoring the

       In this paper, we focus on designing feed forward neural network (FFNN) for solving Mixed Volterra – Fredholm Integral Equations (MVFIEs) of second kind in 2–dimensions. in our method, we present a multi – layers model consisting of a hidden layer which has five hidden units (neurons) and one linear output unit. Transfer function (Log – sigmoid) and training algorithm (Levenberg – Marquardt) are used as a sigmoid activation of each unit. A comparison between the results of numerical experiment and the analytic solution of some examples has been carried out in order to justify the efficiency and the accuracy of our method.

_{Reading is an interactive process that goes on between the reader and the text, resulting in comprehension. The text presents letters, words, sentences, and paragraphs that encode meaning. The reader uses knowledge, skills, and strategies to determine what that meaning is. Reading comprehension is much more than decoding; it results when the reader knows which skills and strategies are appropriate for the type oftext, and understands how to apply them to accomplish the reading purpose.Reading comprehension is important because without it reading is nothing more than tracking symbols on a page with your eyes and sounding them out leaving the reader with no information. Instead of promoting traditional approaches, reading should be ta}

This research aims to choose the appropriate  probability ‎ distribution  ‎‏‎ to the reliability‎        analysis‎ for  an   item through ‎ collected data for operating and stoppage  time of  the case  study.

    Appropriate choice for .probability distribution   is when  the data look to be on or  close the form fitting line for probability plot and test the data  for  goodness of fit .

     Minitab’s 17 software  was used ‎  for this  purpose after  arranging collected data and setting it in the the program‎.

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Production of fatty acid esters (biodiesel) from oleic acid and 2-ethylhexanol using sulfated zirconia as solid catalyst for the production of biodiesel was investigated in this work.

       The parameters studied were temperature of reaction (100 to 130°C), molar ratio of alcohol to free fatty acid (1:1 to 3:1), concentration of catalyst (0.5 to 3%wt), mixing speed (500 to 900 rpm) and types of sulfated zirconia (i.e modified, commercial, prepared  catalyst according to literature and reused catalyst). The results show the best conversion to biodiesel was 97.74% at conditions of 130°C, 3:1, 2wt% and 650 rpm using modified catalyst respectively. Also, modified c

Abstract This research scrutinizes the impact of external magnetic field strength variations on plasma jet parameters to enhance its performance and flexibility. Plasma jets are widely used for their high thermal and kinetic energy in both medical and industrial fields. The study employs optical emission spectroscopy to measure electron temperature, electron density, and plasma frequency in a plasma jet subjected to varying magnetic field strengths (25, 50, 100, 150, and 250 mT). The results indicate that a stronger magnetic field results in higher electron temperature (1.485 to 1.991 eV), electron density (5.405 × 1017 to 7.095 × 1017), and plasma frequency 7.382 × 1012 to 8.253 × 1012 Hz. As well as the research investigates the influ

Background: The excess mortality associated with
rheumatoid arthritis is largely due to
cardiovascular disease. Rheumatoid arthritis is of
primary importance in atherogenesis. The intimamedia thickness of extracranial carotid arteries is a
measurable index of the presence of
atherosclerosis.
Objective: To assess carotid intima-media
thickness in rheumatoid arthritis by Doppler
ultrasound.
Methods: Fifty two Iraqi patients with rheumatoid
arthritis were studied and compared with another
fifty two, healthy individuals matched for age and
sex as a control group. Full history was taken and
complete clinical examination was done for all
individuals in both groups. Rheumatoid arthritis
diagnosis was

Abstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization