Summary: The study focused on the role of the educational counselor in schools, as an integral part of the educational system that faces multiple challenges and difficulties. In this context, the counselor’s role becomes crucial in attempting to reduce or eliminate such difficulties, in addition to guiding students in an appropriate manner. Methodes: The study employed a descriptive field approach, using interviews and direct observation as tools to examine the actual role performed by school counselors. Results: The study concluded with several key findings, most notably the numerous challenges faced by counselors, including students’ negative behaviors, school dropouts, and the limited administrative support for counselors’ work. Fu

The activation and reaction energies of the C-C and C-H bonds cleavage in pyrene molecule are calculated applying the Density Functional Theory and 6-311G Gaussian basis. Different values for the energies result for the different bonds, depending on the location of the bond and the structure of the corresponding transition states. The C-C bond cleavage reactions include H atom migration, in many cases, leading to the formation of CH2 groups and H-C≡C- acetylenic fragments. The activation energy values of the C-C reactions are greater than 190.00 kcal/mol for all bonds, those for the C-H bonds are greater than 160.00 kcal/mol. The reaction energy values for the C-C bonds range between 56.497 to 191.503 kcal/mol. As for the C-H cleavage rea

BN Rashid, International Journal of Research in Social Sciences and Humanities, 2019 - Cited by 1

Anew Schiff base (NaHL) has been prepared from the reaction between the salt of amino acid glycine with 2-hydroxy naphthaldehyde. By tridentate Schiff base of (ONO), donors were characterized by using U.V and spectrophotometer techniques. Complexes of Co(II) Ni(II) Cu(II) and Zn(II) ion with the ligand have been prepared, these complexes were identified by infrared, electronic spectral data, elemental analysis, magnetic moments, and molar conductivity measurements. It is concluded from the elemental analysis that all the complexes have (1:2) [metal:ligand] molar ratios, octahedral, with the exception to Zn(II) complex which have (1:1)[metal:ligand] molar ratio.

The effects of T-shaped fins on the improvement of phase change materials (PCM) melting are numerically investigated in vertical triple-tube storage containment. The PCM is held in the middle pipe of a triple-pipe heat exchanger while the heat transfer fluid flows through the internal and external pipes. The dimension effects of the T-shaped fins on the melting process of the PCM are investigated to determine the optimum case. Results indicate that while using T-shaped fins improves the melting performance of the PCM, the improvement potential is mainly governed by the fin’s body rather than the head. Hence, the proposed T-shaped fin did not noticeably improve melting at the bottom of the PCM domain; additionally, a flat fin is ad

A novel azo dye was prepared by reacting the diazonium salt of 3-aminophenol with 8-hydroxyquinoline and subsequently used to prepare a series of Ni+2, Pd+2, Pt+4, and Cu+2 complexes. The ligand structure was characterized via1H-and 13C-nuclear magnetic resonance spectroscopy. The as-synthesized materials were characterized via Fourier-transform infrared, ultraviolet‒visible, and mass spectroscopy, as well as thermo gravimetry, differential scanning calorimetry, and elemental analysis. Conductivity, magnetic susceptibility, and the metal and chloride contents of the complexes were also determined. The ligand exhibited a trigonal geometry, whereas the Cu+2, Pd+2, Pt+4, and Ni+2 complexesexhibited tetrahedral, square planar, octahedral, and

Modified unsaturated polyester (MUPE) was blended with Cellulose (Cls) and with ethyl cellulose (ECls) at ambient conditions in the presence of ethyl methyl ketone peroxide (EMKP) as hardener. The blends containing different weight percentages (5-25 %) of Cls or ECls. Mechanical properties (impact strength, hardness, and bending) and dielectric constant were determined. The results observed that Cls increases the impact strength, hardness, and dielectric constant and decreases the bending of the MUPS, while ECls causes an increase in the three mechanical behaviours and a decrease in the dielectric constant of the MU-PS.

A survey of haemoproteids among the eight species of Iraq rallids were carried out in the
middle, south, and west of Iraq. Two haemoproteods were recorded, Haeomproteus porzanae
(Galli-Valerio, 1907) as a new record for Iraq and the new species H. baghdadensis described
from Fulica atra L. collected in the middle of Iraq.

The new multidentate Schiff-base (E)-6,6′-((1E,1′E)-(ethane-1,2-diylbis(azan-1-yl-1-ylidene))bis(methan-1-yl-ylidene))bis(4-methyl-2-((E)(pyridine-2-ylmethylimino)methyl)phenol) H2L and its polymeric binuclear metal complexes with Cr(III), Mn(II), Fe(II), Co(II), Ni(II), Cu(II), Zn(II), Cd(II) and Hg(II) are reported. The reaction of 2,6-diformyl-4-methyl-phenol with ethylenediamine in mole ratios of 2:1 gave the precursor 3,3′-(1E,1′E)-(ethane-1,2-diylbis(azan-1-yl-1ylidene))bis(methan-1-yl-1-ylidene)bis(2-hydroxy-5-methylbenzaldehyde) W. Condensation of the precursor with 2-(amino-methyl)pyridine in mole ratios of 1:2 gave the new N6O2 multidentate Schiff-base ligand H2L. Upon complex formation, the ligand behaves as a dibasic oct

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class