A new ligand [N-(4-methoxy benzoyl amino)-thioxo methyl ] leucine (MBL) was prepared from the reaction of (4-methoxy benzoyl isothiocyanate with leucine acid in molar ratio (l:l), it was characterized by elemental analysis (C.H.N.S), FT-IR, UV-Vis, 1H and 13C-NMR. The complexes of the bivalent ions (Mn, Fe, Co, Ni, Cu, Zn, Cd and Hg ) have been prepared and characterized too. The structural was established by elemental analysis (C.H.N.S), FT-IR, UV-Vis spectra, conductivity measurements atomic absorption and magnetic susceptibility and determination of molar ration (M:L). The complexes showed characteristic behavior of tetrahedral geometry around the metal ions except with (Cu) complex showed square planer.

       In recent years, the attention of researchers has increased of semi-parametric regression models, because it is possible to integrate the parametric and non-parametric regression models in one and then form a regression model has the potential to deal with the cruse of dimensionality in non-parametric models that occurs through the increasing of explanatory variables. Involved in the analysis and then decreasing the accuracy of the estimation. As well as the privilege of this type of model with flexibility in the application field compared to the parametric models which comply with certain conditions such as knowledge of the distribution of errors or the parametric models may

Background: While warfarin and direct oral anticoagulants (DOACs) are used to manage thromboembolic events, they possess several features that impact adherence. Objective: To assess medication adherence and self-efficacy in patients receiving warfarin or DOAC treatment. Methods: A cross-sectional study was performed at Ibn Al-Bitar Hospital in Baghdad from December 2022 to May 2023 on patients receiving either warfarin or DOACs. The Arabic version of the Adherence to Refills and Medications Scale (ARMS) questionnaire and the Self-Efficacy for Managing Chronic Disease 6-Item Scale (SES6C) questionnaire were used to assess adherence and self-efficacy. Results: 181 patients were enrolled in the study, of whom 56.9% received warfarin an

داء المشوكات الكيسي (CE) هو مرض وبائي يسبب مرضًا خطيرًا وخسائر اقتصادية في معظم بلدان العالم. MiRNAs هي عامل جيني ضروري لتنظيم الاستجابة المناعية من خلال قدرته على التدخل في التعبير الخلوي ؛ واحد هذه الحوامض النووية الدقيقة -146 أ. هدفت الدراسة الحالية تقييم إذا كان بإمكاننا استخدام microRNA 146a كمؤشر حيوي للكشف عن    CEو تحديد العلاقة بين التعبير الجيني microRNA 146a و IL-17 في مرضى CE.حيث اشتملت الدراسة على 50 مريضًا من CE تم إد

The paper is concerned with the state and proof of the existence theorem of a unique solution (state vector) of couple nonlinear hyperbolic equations (CNLHEQS) via the Galerkin method (GM) with the Aubin theorem. When the continuous classical boundary control vector (CCBCV) is known, the theorem of existence a CCBOCV with equality and inequality state vector constraints (EIESVC) is stated and proved, the existence theorem of a unique solution of the adjoint couple equations (ADCEQS) associated with the state equations is studied. The Frcéhet derivative derivation of the "Hamiltonian" is obtained. Finally the necessary theorem (necessary conditions "NCs") and the sufficient theorem (sufficient conditions" SCs") for optimality of the stat

This study was conducted in the poultry field of the College of Agricultural Engineering Sciences / University of Baghdad for the period from 10/15/2021 to 11/25/2021 in order to show the effect of adding different levels of Ganoderma lucidum to broiler diets on physiological traits and indicators of fat oxidation in meat. In it, 200 unsexed (Ross 308) chicks of one-day-old breed were used, with a starting weight of (40) g. The chicks were distributed and randomly divided into four treatments, with 50 birds for each treatment. One treatment included five replicates (10 birds/repeat) and the experiment treatments were T1, T2, T3, and T4. The percentages of adding reishi mushrooms were 0, 0.5, 1, and 1.5 g/kg of feed, respectively. Th

Precise forecasting of pore pressures is crucial for efficiently planning and drilling oil and gas wells. It reduces expenses and saves time while preventing drilling complications. Since direct measurement of pore pressure in wellbores is costly and time-intensive, the ability to estimate it using empirical or machine learning models is beneficial. The present study aims to predict pore pressure using artificial neural network. The building and testing of artificial neural network are based on the data from five oil fields and several formations. The artificial neural network model is built using a measured dataset consisting of 77 data points of Pore pressure obtained from the modular formation dynamics tester. The input variables