Strives Total Productive Maintenance  to increase the overall effectiveness of the equipment through the early involvement in the design and manufacture of equipment productivity. It also operates in an environment of simultaneous engineering work on the synchronization of activities to take advantage of early information by maintenance engineers, design, operation, and that helps to reduce the faults and facilitate future maintenance tasks.

    Has adopted a search in the theoretical concept of the total maintenance productivity and concurrent engineering activities carried out during which the conjunction a

The (E)-4-chloro-N-(2-(dimethylamino)ethyl)-5-((8-hydroxy quinolin-5-yl)diazenyl)-2-methoxybenzamide azo ligand (L) has been synthesized through the reaction of diazonium salt for 5-amino-4-chloro-N-(2-(dimethylamino) ethyl)-2-methoxybenzamide with 8-hydroxyquinoline and identified azo ligand (L) using spectroscopic studies (FTIR, UV-Vis, 1H and 13CNMR, mass), and micro-elemental analysis (C.H.N). Metal chelates of Co(II), Ni(II), Cu(II), as well as Zn(II) have been completed as well as characterized using mass spectra, flame atomic absorption, elemental analysis (C.H.N), infrared, UV-Vis spectroscopy, as well as conductivity, magnetic measurements. The metal-to-ligand ratio in all complexes, as determined by analytical data, was 1:2 and ex

In the cuurent article, the photophysical properties of 3,6-bis(5-bromothiophen-2-yl)-2,5-bis(2-ethylhexyl)-2,5-dihydropyrrolo[3,4-c]pyrrole-1,4-dione were investigated. The visible absorption bands at 527, 558 and 362 nm in propylene carbonate and the compound was found to be fluorescent in solution and in the plastic film with emission wavelengths between 550- 750 nm. The Stokes Shift of P.C., acetonitrile, diethyl ether, Tetrahydrofuran THF, cyclohexane, dibutyl ether, and dichloromethane DCM  are 734, 836, 668, 601, 601, 719, and 804 cm^-1 in respectively. The Stokes Shift Δ was less in THF and cyclohexane, than the solvents, which indicates that the energy loss is less between the excitation and fluorescence states. The

New Schiff base ligand (E)-6-(2-(4-(dimethylamino)benzylideneamino)-2-(4-hydroxyphenyl)acetamido)-3,3- dimethyl-7-oxo-4-thia-1- azabicyclo[3.2.0]heptane-2-carboxylic acid = (HL) was synthesized via condensation of Amoxicillin and 4(dimethylamino)benzaldehyde in methanol. Figure -1 Polydentate mixed ligand complexes were obtained from 1:1:2 molar ratio reactions with metal ions and HL, 2NA on reaction with MCl2 .nH2O salt yields complexes corresponding to the formulas [M(L)(NA)2Cl],where M=Fe(II),Co(II),Ni(II),Cu(II),and Zn(II), A=nicotinamide .

Background: The association between facial types and dental arches forms has considerable implications in orthodontic diagnosis and treatment planning. The aim was to establish the maxillary and mandibular dental arches width and length in skeletal and dental class II division 1 and class III malocclusion groups, find out the most frequent dental arch form and facial type and the association between them and to check the gender differences. Materials and Methods: Frontal and lateral facial photographs and maxillary and mandibular occlussal photographs for 90 iraqi subjects with age 18-25 years old (45 males and 45 females) divided equally into three groups, the 1st group with class II division 1malocclusion (overjet more than 3mm but less t

In recent years, Bitcoin has become the most widely used blockchain platform in business and finance. The goal of this work is to find a viable prediction model that incorporates and perhaps improves on a combination of available models. Among the techniques utilized in this paper are exponential smoothing, ARIMA, artificial neural networks (ANNs) models, and prediction combination models. The study's most obvious discovery is that artificial intelligence models improve the results of compound prediction models. The second key discovery was that a strong combination forecasting model that responds to the multiple fluctuations that occur in the bitcoin time series and Error improvement should be used. Based on the results, the prediction acc

        Artificial Neural networks (ANN) are powerful and effective tools in time-series applications. The first aim of this paper is to diagnose better and more efficient ANN models (Back Propagation, Radial Basis Function Neural networks (RBF), and Recurrent neural networks) in solving the linear and nonlinear time-series behavior. The second aim is dealing with finding accurate estimators as the convergence sometimes is stack in the local minima. It is one of the problems that can bias the test of the robustness of the ANN in time series forecasting. To determine the best or the optimal ANN models, forecast Skill (SS) employed to measure the efficiency of the performance of ANN models. The mean square error and

Eight different Dichloro(bis{2-[1-(4-R-phenyl)-1H-1,2,3-triazol-4-yl-κN3]pyridine-κN})iron(II) compounds, 2–9, have been synthesised and characterised, where group R=CH3 (L2), OCH3 (L3), COOH (L4), F (L5), Cl (L6), CN (L7), H (L8) and CF3 (L9). The single crystal X-ray structure was determined for the L3 which was complemented with Density Functional Theory calculations for all complexes. The structure exhibits a distorted octahedral geometry, with the two triazole ligands coordinated to the iron centre positioned in the equatorial plane and the two chloro atoms in the axial positions. The values of the FeII/III redox couple, observed at ca. −0.3 V versus Fc/ Fc+ for complexes 2–9, varied over a very small potential range of 0.05 V.