A discussion about the repercussions of the exchange rate on the behavior of stock markets became one of the basic principles of financial economics. The Istanbul Stock Exchange , considered  one of the fastest financial markets growing in the region, driven by solid economic activity, for a diversified economy  which classified as one of the the fastest growing economies in the world. However, the aforementioned market witnessed sharp fluctuations in the past few months, coinciding with the continuous fluctuations in the exchange rate of the Turkish lira, posing a serious challenge to the economic and investment environment in a c

The current study examined the effect of different sample sizes to detect the Item differential functioning (DIF). The study has used three different sizes of the samples (300, 500, 1000), as well as to test a component of twenty polytomous items, where each item has five categories. They were used Graded Response Model as a single polytomous item response theory model to estimate items and individuals’ parameters. The study has used the Mantel-Haenszel (MH) way to detect (DIF) through each case for the different samples. The results of the study showed the inverse relationship between the sample size and the number of items, which showed a differential performer.

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.

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

        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

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

     This paper develops the work of Mary Florence et.al. on centralizer of semiprime semirings and presents reverse centralizer of semirings with several propositions and lemmas. Also introduces the notion of dependent element and free actions on semirings with some results of free action of centralizer and reverse centralizer on semiprime semirings and some another mappings.

 In this work, the preparation of some new oxazolidine and thiazolidine derivatives has been conducted. This was done over two steps; the first step included the synthesis of Schiff bases A1-A5 in 72-88% yields by the condensation of isonicotinic acid hydrazide and aldehydes. The second step includes the cyclization of derivatives A1-A5 with glycolic acid and thioglycolic acid to obtain the desired products, oxazolidine derivatives B1-B5 (44-60% yields) and thiazolidine derivatives C1-C5 (41-61% yields), respectively. The structure of the prepared compounds was characterized using FT-IR, 1H NMR, and 13C NMR spectroscopy. Some of the produced compounds were tested for antioxidant properties.  

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