The Significance of this research comes as a result of the development occurring in various life fields including the field of technical and technological development in the domain of industrial products which are in direct touch with the receiver, and because the study of deletion and addition mechanism didn't Find the Scientific space through researches and Studies. On this basis , the aim of this study is defining the forms of deletion and addition mechanism in designing the industrial product in a way that fits the functional presser . As to the limitations of this study, they involve examples of readymade Turkish House furniture, which is available in Iraqi local markets in Baghdad city 2013. The study included four chapters. The fi

An optical spectroscopic study is reported in this article to study the correlation between the supermassive black hole (SMBH) and the star formation rate (SFR) for a sample of Seyfert galaxies type (I and II). The study focused on 45 galaxy of Seyfert 1, in addition to 45 galaxy of Seyfert 2, where these samples have been selected form different survey of Salon Digital Sky Survey (SDSS). The redshift (z) of these objects were between (0.02 – 0.26). The results of Seyfert 1 galaxies shows that there good correlation between the SMBH and the SFR depending on statistical analysis parameter named Spearman’s Rank Correlation in a factor of (ρ=0.609), as well as the Seyfert 2 galaxies results show a good correlation between the SMBH and

Abstract:

The great expansion of teaching skills requires finding ways and methods to help teachers acquire experiences of all kinds. The researcher found in the subject of the teaching skills for teachers in public and private schools a fertile field for conducting a study that enables the measurement of these skills. Thus, the study aims to identify the skills of teaching lessons for teachers, the difference in teaching lesson skills for teachers according to the years of service, the differences in teaching lesson skills for teachers according to the specialized teachers and non-specialized teachers, the differences in teaching lesson skills for teachers according to the public and private school. The

A novel series of liquid crystalline compounds containing 2,4-thiazolidinedione units with varying terminal alkyl chain lengths was successfully synthesized and characterized. The chemical structures of the synthesized compounds were confirmed by FT-IR, ¹H-NMR, and mass spectrometry. The mesomorphic behavior was investigated using polarized optical microscopy (POM) and differential scanning calorimetry (DSC). Compounds [V]₄, [V]₅, and [V]₆ exhibited enantiotropic nematic phases, while compound [V]₈ displayed a smectic A (SmA) phase. No liquid crystalline behavior was observed for compound [V]₃. The liquid crystalline properties were found to depend on the terminal-to-lateral chain length ratio, molecular geometry, and the nature

Background: The bond strength of root canal sealers to dentin was important for maintaining the integrity of the seal in root canal filling in both static and dynamic situations. In a static situation, it should eliminate any space that allowed the percolation of fluids between the filling and the wall while in a dynamic situation; it was needed to resist dislodgement of the filling during subsequent manipulation. Materials and Methods: Forty mandibular premolars were selected for this study. All canals were instrumented using ProTaper rotary instruments. Instrumentation was done with copious irrigation of 5.25% sodium hypochlorite. Roots were randomly divided into four groups according to the type of cleaning and method of root canal irrig

Empirical and statistical methodologies have been established to acquire accurate permeability identification and reservoir characterization, based on the rock type and reservoir performance. The identification of rock facies is usually done by either using core analysis to visually interpret lithofacies or indirectly based on well-log data. The use of well-log data for traditional facies prediction is characterized by uncertainties and can be time-consuming, particularly when working with large datasets. Thus, Machine Learning can be used to predict patterns more efficiently when applied to large data. Taking into account the electrofacies distribution, this work was conducted to predict permeability for the four wells, FH1, FH2, F