This study synthesized polyacetal from the reaction of polyvinyl alcohol with para-nitrobenzaldehyde. Polyacetal/polyvinylpyrrolidone polymer blends were prepared using solution casting. Gold nanoparticles (AuNPs) and silver nanoparticles (AgNPs) were biosynthesized using onion peel extract as the reducing agent. Nanocomposites were fabricated by blending polyacetal/PVP with AuNPs and AgNPs at different ratios. XRD and FESEM characterized the AuNPs and AgNPs. FTIR, FESEM, TGA, and DSC characterized the polyacetal, polymer blends, and nanocomposites. DSC and TGA confirmed the improved thermal stability of the polymer blends and nanocomposites. Nanocomposites demonstrated higher efficacy in inhibiting lung cancer cell lines compared t

The present research deals with studying the formal variations for the Quranic calligraphy at the beginning of Islam , as being regarded from the original Arabic calligraphies which were developed later till they became as they are now, where the calligraphers in pushing for simulating these original calligraphies and knowing the methods of their writing by the calligraphers at that time.That helped in enriching and developing the aesthetic and designing valuesFor these calligraphies, as being calligraphic achievements represent transmission resulted from the objective, aesthetic and indicative vision in producing the verses according to a certain form. This has a clear impact in tendency to the technical, aesthetic and expressing develo

The current study aims to

1) identify the prevalent Enneagram personality types and the academic self among the sixth-grade students of the distinguished secondary schools; 2) the differences of relationship between the Enneagram personality types and the academic self-concept based on gender; 3) identify the correlation between the Enneagram personality types and the academic self-concept; and 4) identify the contribution of each type of personality types to the academic self-concept. To this end, two instrument were used to collect the data: Riso-Hudson’s scale,1995 was administered to measure enneagram types which had translated to the Arabic language by ( al-yassery,2004), the other instrument was

Biological activity of the carotenoids which are produced fromchemically-mutaed local isolate of Rhodotorula mucilaginosawas studied. The results showed variation of inhibition activity of caritenoids against different types of pathogenic bacteria include, Staph aureus, E. coli, B. subtilis and Salmo. typh., the number declined from 2×107cell/ml to 2×104, 5×104, 2×105, 9×105 cell/ml respectively after 24hour. The produced carotenoids from alocal mutant Rhodotorula mucilaginosa revealed an antioxidant activity as free radical removal of 85.6%. Carotinoides revealed a highest stability in petroleum ether solvent for 30 days at room temperature. It found that the pigment was more stability in sesame oil compared with sun flower and coc

Photonic Crystal Fiber (PCF) based on the Surface Plasmon Resonance (SPR) effect has been proposed to detect polluted water samples. The sensing characteristics are illustrated using the finite element method. The right hole of the right side of PCF core has been coated with chemically stable gold material to achieve the practical sensing approach. The performance parameter of the proposed sensor is investigated in terms of wavelength sensitivity, amplitude sensitivity, sensor resolution, and linearity of the resonant wavelength with the variation of refractive index of analyte. In the sensing range of 1.33 to 1.3624, maximum sensitivities of 1360.2 nm ∕ RIU and 184 RIU⁻¹ are achieved with the high sensor resolutions of 7

The aim of this paper is to approximate multidimensional functions by using the type of Feedforward neural networks (FFNNs) which is called Greedy radial basis function neural networks (GRBFNNs). Also, we introduce a modification to the greedy algorithm which is used to train the greedy radial basis function neural networks. An error bound are introduced in Sobolev space. Finally, a comparison was made between the three algorithms (modified greedy algorithm, Backpropagation algorithm and the result is published in [16]).

In this article we  study a single stochastic process model for the evaluate the assets pricing and stock.,On of the models le'vy . depending on the so –called Brownian subordinate as it has been depending on the so-called Normal Inverse Gaussian (NIG). this article aims as the estimate that the parameters of his model using my way (MME,MLE) and then employ those  estimate of the parameters is the study of stock returns and evaluate asset pricing for both the united Bank and Bank of North which their data were taken from the Iraq stock Exchange.

which showed the results to a preference MLE on MME based on the standard of comparison the average square e

Blockchain is an innovative technology that has gained interest in all sectors in the era of digital transformation where it manages transactions and saves them in a database. With the increasing financial transactions and the rapidly developed society with growing businesses many people looking for the dream of a better financially independent life, stray from large corporations and organizations to form startups and small businesses. Recently, the increasing demand for employees or institutes to prepare and manage contracts, papers, and the verifications process, in addition to human mistakes led to the emergence of a smart contract. The smart contract has been developed to save time and provide more confidence while dealing, as well a

     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