The aim of the research is to examine the multiple intelligence test item selection based on Howard Gardner's MI model using the Generalized Partial Estimation Form, generalized intelligence. The researcher adopted the scale of multiple intelligences by Kardner, it consists of (102) items with eight sub-scales. The sample consisted of (550) students from Baghdad universities, Technology University, al-Mustansiriyah university, and Iraqi University for the academic year (2019/2020). It was verified assumptions theory response to a single (one-dimensional, local autonomy, the curve of individual characteristics, speed factor and application), and analysis of the data according to specimen partial appreciation of the generalized, and limits

This research began by explaining its variables and dimensions especially the digital gap, which the authors explained it elaborately beginning with the concept, the reasons blind its emergence of its measurement, and how to treat it. The authors supposed the potentiality of relying on enforcing knowledge in general and the groups suffer from this gap in particular, especially the targeted knowledge to treat its subject.

As enforcing knowledge usually depends on some strategies or choices of organizational orientation among them is learning and training from one side, and communication, as an indicating factor for organizational effectiveness as the authors refer from the other side.

Kamel, S.H., R.F. Al-Jassani and H.A. Al-Shammari. 2022. Effects of Pseudomonas fluorescens, Bacillus thuringiensis tenebrionis Isolates and Biologically Synthesized Silver Nanoparticles on Cellulase Enzyme Activity in Workers' Digestive System of the Termite Microcerotermes diversus Silv. Arab Journal of Plant Protection, 40(4): 315-324. https://doi.org/10.22268/AJPP-40.4.315324 The purpose of this study was to investigate the effect of different bacterial isolates of P. fluorescens and B. t. tenebrionis and silver nanoparticles on the activity of the cellulase enzyme in termites' middle digestive system and its role in glucose release by treating cellulose media with bacterial strains and nanoparticles. Ultraviolet spectroscopy re

Glassy carbon electrode (GCE) was modified with carbon nanotubes CNT and C60 by attachment and solution evaporation techniques, respectively. CNT/Li+/GCE and C60/Li+/GCE were prepared by modifying CNT/GCE and C60/GCE in Li+ solution via cyclic voltammetry (CV) potential cycling. The sensing characteristics of the modified film electrodes, demonstrated in this study for interference of Mn2+ in different heavy metals ion esp. Hg2+, Cd2+ and Cu2+. The interfering effect was investigated that exert positive interference on the redox peaks of Mn2+. The modification of GCE with nano materials and Li+ act an enhancement for the redox current peaks to observe the effect of interference for Mn2+ in 1:1 ratio with different heavy metals ion.

The development of new cephalosporins with improved activity against resistant microbes, such as, MRSA (methicillin resistant Staph. aureus), P. aeruginosa, is of high potential. Chemical synthesis of two new series of thiadiazole linked to cysteine (series 1) and cephalosporins containing thiadiazole linked to cysteine through disulfide bond (series 2) were achieved. The chemical structures of the synthesized compounds were confirmed using spectral (FT-IR, ¹H-NMR) and elemental microanalysis. The incorporation of privileged chemical moieties, such as, thiadiazole, Schiff base, cysteine and sulfonamide, has been found to have great contribution to the antimicrobial activities. Compounds of series 1 (1

This paper proposes a new structure of the hybrid neural controller based on the identification model for nonlinear systems. The goal of this work is to employ the structure of the Modified Elman Neural Network (MENN) model into the NARMA-L2 structure instead of Multi-Layer Perceptron (MLP) model in order to construct a new hybrid neural structure that can be used as an identifier model and a nonlinear controller for the SISO linear or nonlinear systems. Weight parameters of the hybrid neural structure with its serial-parallel configuration are adapted by using the Back propagation learning algorithm. The ability of the proposed hybrid neural structure for nonlinear system has achieved a fast learning with minimum number

We propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). St

In this present work, [4,4`-(biphenyl-4,4`-diylbis(azan-1-yl-1-ylidene))bis(methan-1-yl-1-ylidene)bis(2-methoxyphenl)(A1),4,4`-(biphenyl-4,4`-diylbis(azan-1-yl-1-ylidene))bis(methan-1-yl-1-ylidene)diphenol(A2),1,1`-(biphenyl-4,4`-diylbis(azan-1-yl-1-ylidene))bis(methan-1-yl-1-ylidene) dinaphthalen-2-ol (A3)]C.S was prepared in 3.5% NaCl. Corrosion prevention at (293-323) K has been studied by using electrochemical measurements. It shows that the utilized inhibitors are of mixed type based on the polarization curves. The results indicated that the inhibition efficiency changes were used with a change according to the functional groups on the benzene ring and through the electrochemical technique. Temperature increases with corrosion current