The problem of slow learning in primary schools’ pupils is not a local or private one. It is also not related to a certain society other than others or has any relation to a particular culture, it is rather an international problem of global nature. It is one of the well-recognized issues in education field. Additionally, it is regarded as one of the old difficulties to which ancient people gave attention. It is discovered through the process of observing human behaviour and attempting to explain and predict it.
Through the work of the two researchers via frequent visits to primary schools that include special classes for slow learning pupils, in addition to the fact that one of the researcher has a child with slow learning issue, the researcher realized that there is a large number of pupils who suffer slow learning difficulty. The researchers carried out anexploratory experiment on over 20 teachers of special education, concluding that there is about 80% of slow learning pupils suffer from thinking skills deficiency.
The concept of thinking skills as pointed out by Debono (2003) is that they are mental skills that can be improved through exercise and learning. That can be done through preparing situations and creating a suitable system. That should lead to the acquisition og the knowledge and information on the part of the learner. This is supposed to lead the learner to the search for further knowledge of deeper nature, creating good learning. The concept of slow learning, on the other hand, is the child who suffer from a simple retardation qualification or a child of normal brain abilities, but for a certain reason takes a longer time in learning in comparison to his/her peers.
The current study aims at identifying thinking skills for fourth primary grade pupils. The study is limited to the number of 150 pupils of fourth primary grade who suffer from slow learning of male gender only. The researcher prepared a test to measure thinking skills for those pupils.
According to the results of the study the researcher reached a number of conclusions and suggestions.
Immunization is one of the most cost-effective and successful public health applications. The results of immunization are difficult to see as the incidence of disease occurrence is low while adverse effects following the immunization are noticeable, particularly if the vaccine was given to apparently healthy person. High safety expectations of population regarding the vaccines so they are more prone to hesitancy regarding presence of even small risk of adverse events which may lead to loss of pub
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Previous studies indicated that supplementation with antioxidants has a protective effects against oxidative stress–induced damage in type 2 diabetes. In this study we evaluated the antioxidant effects of melatonin on the oxidative stress parameters and microalbuminuria in type 2 DM patients. 30 patients with type 2 DM were treated with 3mg/day melatonin for 90 days. Erythrocytes and plasma MDA and glutathione, fasting plasma glucose, %HbAIC, microalbuminuria, total plasma protein and lipid profile were measured each 30 days and compared with those obtained from 20 healthy controls.
A decrease in MDA levels associated with the elevation in GSH levels were observed, compared with the pre–treatment levels.
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The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow
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In the last few years, the use of artificial neural network analysis has increased, particularly, in geotechnical engineering problems and has demonstrated some success. In this research, artificial neural network analysis endeavors to predict the relationship between physical and mechanical properties of Baghdad soil by making different trials between standard penetration test, liquid limit, plastic limit, plasticity index, cohesion, angle of internal friction, and bearing capacity. The analysis revealed that the changes in natural water content and plastic limit have a great effect on the cohesion of soil and the angle of internal friction, respectively. . On the other hand, the liquid limit has a great impact on the bearing capacity and
... Show MoreThis work discusses the beginning of fractional calculus and how the Sumudu and Elzaki transforms are applied to fractional derivatives. This approach combines a double Sumudu-Elzaki transform strategy to discover analytic solutions to space-time fractional partial differential equations in Mittag-Leffler functions subject to initial and boundary conditions. Where this method gets closer and closer to the correct answer, and the technique's efficacy is demonstrated using numerical examples performed with Matlab R2015a.
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Bigheaded carps (bighead carp, Hypophthalmichthys molitrix, and silver carp, Hypophthalmichthys nobilis) and their hybrids play an important ecological and economic role in their original habitat, while their introduced stocks may pose serious ecological risks. To address questions about the persistence and invasiveness of these fish, we need to better understand their population structures. The genetic structures of bigheaded carp populations inhabiting Lake Balaton and the Tisza River were examined with ten microsatellite markers and a mitochondrial DNA marker (COI). The Lake Balaton stock showed higher genetic diversity compared with the Tisza River stock. Based on hierarchical clustering, the Tisza population was characterized o
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In this work, the adsorption of crystal violet dye from aqueous solution on charcoal and rice husk has been investigated, where the impact of variable factors (contact time; the dosage of adsorbent, pH, temperature, and ionic strength) have been studied. It has been found that charcoal and rice husk have an appropriate adsorption limit with regards to the expulsion of crystal violet dye from fluid arrangements. The harmony adsorption is for all intents and purposes accomplished in 45 min for charcoal and 60 min for rice husk. The amount of crystal violet dye adsorbed (0.4 g of charcoal and 0.5 g of rice husk) increased with an increasing pH and the value of 11 is the best
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Background: Parkinson's disease (PD) is a neurodegenerative aging disease, with idiopathic PD being most common. Gastrointestinal tract disorders (GITD) and microbiota changes may trigger idiopathic PD. Neurotoxins from microbiota can travel from the gut to the brain via the brain-gut axis (BGA), leading to α-syn protein misfolding and dopaminergic neuron death. Methods: The aim of the current study was to investigate the link between PD and GITD by measuring several biochemical and immunological markers in 142 patients. The biochemical markers measured were vitamins B6, B12, and D, calcium, serotonin, ghrelin, dopamine, and α-syn protein. The immunological markers included transforming growth factor-beta (TGF-β), tu
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