The increased use of hybrid PET /CT scanners combining detailed anatomical information along withfunctional data has benefits for both diagnostic and therapeutic purposes. This presented study is to makecomparison of cross sections to produce 18F , 82Sr and68Ge via different reactions with particle incident energy up to 60 MeV as a part of systematic studies on particle-induced activations on enriched natNe, natRb, natGa 18O,85Rb, and 69Ga targets, theoretical calculation of production yield, calculation of requiredtarget and suggestion of optimum reaction to produce: Fluorine-18 , Strontium-82 andGermanium-68 touse in Hybrid Machines PET/CT Scanners.

ZnO organic hybrid junction (electroluminescence EL device) was fabricated using phase segregation method. ZnO-nanoparticle (NPs) was prepared as a colloidal by self–assembly method of Zinc acetate solution with KOH solution. Nanoparticle is employed to form organic-inorganic hybrid film and generate white light emission, while N,N’–diphenyl-N,N’ –bis(3-methylphenyl)-1,1’-biphenyl 4,4’-diamine (TPD) and polymethyl methacrylate (PMMA) are adopted as the organic matrices. ZnO NPs was used to fabricate TPD: PMMA: ZnO NPs hybrid junction device. The photoluminescence (PL) and electroluminescence (EL) spectra of the TPD: PMMA: ZnO NPs hybrid device provided a broad emission band covering entirely the visible spectrum (∼350-∼700

Regression testing is a crucial phase in the software development lifecycle that makes sure that new changes/updates in the software system don’t introduce defects or don’t affect adversely the existing functionalities. However, as the software systems grow in complexity, the number of test cases in regression suite can become large which results into more testing time and resource consumption. In addition, the presence of redundant and faulty test cases may affect the efficiency of the regression testing process. Therefore, this paper presents a new Hybrid Framework to Exclude Similar & Faulty Test Cases in Regression Testing (ETCPM) that utilizes automated code analysis techniques and historical test execution data to

<p>Combating the COVID-19 epidemic has emerged as one of the most promising healthcare the world's challenges have ever seen. COVID-19 cases must be accurately and quickly diagnosed to receive proper medical treatment and limit the pandemic. Imaging approaches for chest radiography have been proven in order to be more successful in detecting coronavirus than the (RT-PCR) approach. Transfer knowledge is more suited to categorize patterns in medical pictures since the number of available medical images is limited. This paper illustrates a convolutional neural network (CNN) and recurrent neural network (RNN) hybrid architecture for the diagnosis of COVID-19 from chest X-rays. The deep transfer methods used were VGG19, DenseNet121

چکیده

کشورعراق مرزهای زمینی ایران دارد که علاوه بر این ، مشترکات وروابط متعدد اقتصادی ،سیاسی، فرهنگی ودينى ميان هر دو ملت می باشند . عراق بعلت موقعیت جغرافیایی ونزدیکی به ایران سهم بیشتری برای ورود واژه های فارسی به لهجه ی خود داشت ، علاوه بر این رویدادهای سیاسی متقابل قدیم و جدید میان دو کشور سبب ورود بسیاری از لغات فارسی به لهجه ی عراقی شد که کاربرد این لغات هم اکنون در لهجه ی عراقی آشکار است ، ای

The new bidentate Schiff base ligand namely [(E)-N1-(4-methoxy benzylidene) benzene-1, 2-diamine] was prepared from condensation of 4-Methoxy benzaldehyde with O-Phenylene diamine at 1:1 molar ratio in ethanol as a solvent in presence of drops of 48% HBr. The structure of ligand (L) was characterized by, FT-IR, U.V-Vis., 1H-, 13C- NMR spectrophotometer, melting point and elemental microanalysis C.H.N. Metal complexes of the ligand (L) in general molecular formula [M(L)3], where M= Mn(II), Co(II), Ni(II),Cu(II) and Hg(II); L=(C14H14N2O) in ratio (1:3)(Metal:Ligand) were synthesized and characterized by Atomic absorption, FT- IR, U.V-Vis. spectra, molar conductivity, chloride content, melting point and magnetic susceptibility from the above d