Abstract

The current research aims to identify the typical effect of Flower and Coscroft on expressive performance and the development of lateral thinking among literary fifth-grade students. To achieve the research objective, the researcher chose a sample of (90) female students from the fifth literary grade, with two experimental groups and a control group. The research groups are of six subjects. The research found that the two experimental groups have more expressive performance than the control group. Students of the first experimental group outperformed the students of the second experimental group in expressive performance and lateral thinking tests. In light of the findings of the research, the researcher

Objective(s): To evaluate teachers’ performance of counseling for pupils with Attention Deficit and Hyperactivity Disorder, to identify the relationship between Teachers’ Performance of Counselling for Pupils with Attention Deficit and Hyperactivity Disorder and their demographic.

Methodology: A quasi-experimental (pre-posttest) design was carried out to evaluate teachers’ performance of counseling for pupils with Attention Deficit and Hyperactivity Disorder, at Al-Firdous mixed primary School and to find out the association between teachers' performance about Attention Deficit and Hyperactivity Disorder and their socio-demographic characteristic. The study was started from 18th September 2

Background: Stroke defined by diminished cerebral blood flow, results in brain damage and neurological impairments. It often leads to considerable difficulties, such as limited mobility and compromised hand function, usually manifesting as a weakening in the ability to open and shut the hand. Objective: The study evaluates the differences between opening and closing hands when utilizing a soft robot. Methods: The study was conducted in the Mosul Specialist Rehabilitation Center which involved 68 participants, all over 20 years old, with visual impairments. The Iranian Clinical Trials Registry and Ministry of Planning approved the study, The Fugl-Meyer Assessment for Upper Extremity Action Research Arm Test, and Arm Motor Ability Test were

The physical, mechanical, electrical and thermal properties containing (Viscosity, curing, adhesion force, Tensile strength, Lap shear strength, Resistively, Electrical conductivity and flammability) of adhesive material that prepared from Nitrocellulose reinforced with graphite particles and aluminum streat. A comparison is made between the properties of adhesive material with varying percentage of graphite powder (0%, 25%, 30%, 35%, 40%) to find out the effect of reinforcement on the adhesive material. The ability of property an electrical was studied through the measurement of conductivity a function of temperature varying. The results of comparison have clearly shown that the increasing of conten

Thermomechanical analysis (TMA) and differential scanning calorimetry (DSC) are used to investigate the effect of molding and annealing of polyester on the behavior of thermal expansion and crystallization since these factors play role in the reprocessing or recycling of the polymer. The dynamic mode of the TMA provides enhanced characterization information about the polyester since it separates the transitions into reversible and irreversible signals, and also reveals the progress of the amorphous regions as the polyester loses strength with the increasing temperature approaching melting. Slow cooling after annealing brings crystallization that may be attributed to molecular chain straightening due to orientation.

Global concerns are rising due to complications associated with the use of chemical agents and antibiotic resistance. Consequently, research focus has shifted towards the quest for effective agents of biological origin. The aim of the present study was to assess the antioxidant and antimicrobial potentials of aqueous and organic extracts derived from various parts of Alcea kurdica. Different parts of A. kurdica were obtained and prepared into leaf, flower and root powders. The powders were extracted with aqueous and organic solvents. The antimicrobial activity of these extracts was assessed against bacterial pathogens using the agar well-diffusion assay. Additionally, the antioxidant effects of the extracts were evaluated using the

        Peroxidase is a class of oxidation-reduction reaction enzyme that is useful for accelerating many oxidative reactions that protect cells from the harmful effects of free radicals. Peroxidase is found in many common sources like plants, animals and microbes and have extensive uses in numerous industries such as industrial, medical and food processing. In this study, P. aeruginosa was harvested to utilize and study its peroxidases. P. aeruginosa was isolated from a burn patient, and the isolate was verified as P. aeruginosa using staining techniques, biochemical assay, morphological, and a sensitivity test. The gram stain and biochemical test result show rod pink gram-ne

Heterocyclic systems, which are essential in medicinal chemistry due to their promising cytotoxic activity, are one of the most important families of organic molecules found in nature or produced in the laboratory. As a result of coupling N-(4-nitrophenyl)-3-oxo-butanamide (3) using thiourea, indole-3-carboxaldehyde, or piperonal, the pyrimidine derivatives (5a and 5b) were produced. Furthermore, pyrimidine 9 was synthesized by reacting thiophene-2-carboxaldehyde with ethyl cyanoacetate and urea with potassium carbonate as a catalyst. The chalcones 11a and 11b were synthesized by reacting equal molar quantities of 1-naphthaldehy

     Deep learning (DL) plays a significant role in several tasks, especially classification and prediction. Classification tasks can be efficiently achieved via convolutional neural networks (CNN) with a huge dataset, while recurrent neural networks (RNN) can perform prediction tasks due to their ability to remember time series data. In this paper, three models have been proposed to certify the evaluation track for classification and prediction tasks associated with four datasets (two for each task). These models are CNN and RNN, which include two models (Long Short Term Memory (LSTM)) and GRU (Gated Recurrent Unit). Each model is employed to work consequently over the two mentioned tasks to draw a road map of deep learning mod