The present study aims to explore the effectiveness of a proposed study unit based on the funds of knowledge theory in developing the attitudes towards cultural identity and the proposed study unit. In order to achieve the goal of the study, the two researchers followed the quasi-experimental approach, where the study sample consisted of (28) female students of the fifth-grade at Al-Jeelah Basic Education School, Al-Dakhiliyah Governorate in the Sultanate of Oman. The data were collected by two scales: the first is a scale of attitudes towards cultural identity consisting of (26) items. The second was a scale of attitudes towards the proposed study unit, which consisted of (24) items. The results of the study revealed that the effect of

The present study aimed to investigate the toxic and mutagenic and anti – mutagenic effects of the aqueous extract (5, 10 and 15 mg/kg) of green tea (Camellia sinensis) in modulating the genotoxic effects of mitomycin C (MMC). Albino male mice (Mus musculs) were employed as a biological system and four parameters were performed in vivo; total leucocyte count, mitotic index, chromosomal aberrations and micronucleus formation. The plant extract was evaluated through three types of treatments. In the first, the extract was given alone orally. While the second and third treatment included two types of interactions with MMC; pre – and post – MMC treatments. All treatments were paralleled by negative and positive control

Synthesis of new nucleoside analogues of the type : 3¢ , 3¢ - gem – di – C – nitromethly , expected to have useful application in the chemotherapeutic treatment of AIDS , cancer and microbial infections. The synthesis involved the condensation of the appropriate sugar derivative ( i.e . 3¢ , 3¢ –  gem – di – C – nitromethly – 1–  ribofuranose ) with nitrogen bases , such as , uracil and theophllin following a multi step scheme starting from diacetone golucose (1) (scheme 1) .The prepared compound were identified by spectroscopic methods ; ir , mass , ¹H and ¹³C nmr.

Monaural source separation is a challenging issue due to the fact that there is only a single channel available; however, there is an unlimited range of possible solutions. In this paper, a monaural source separation model based hybrid deep learning model, which consists of convolution neural network (CNN), dense neural network (DNN) and recurrent neural network (RNN), will be presented. A trial and error method will be used to optimize the number of layers in the proposed model. Moreover, the effects of the learning rate, optimization algorithms, and the number of epochs on the separation performance will be explored. Our model was evaluated using the MIR-1K dataset for singing voice separation. Moreover, the proposed approach achi

Abstract 

For sparse system identification,recent suggested algorithms are  -norm Least Mean Square (  -LMS), Zero-Attracting LMS (ZA-LMS), Reweighted Zero-Attracting LMS (RZA-LMS), and p-norm LMS (p-LMS) algorithms, that have modified the cost function of the conventional LMS algorithm by adding a constraint of coefficients sparsity. And so, the proposed algorithms are named  -ZA-LMS, 

This study included the Zakhikhah area in the Al- Anbar desert, which it bounded on the north, east, and west by the Euphrates River and on the south by the Ramadi-Qaim road. Several exploratory field trips were taken to the study area. During this time, a semi-detailed area survey was carried out based on satellite imagery captured by American Land sat-7, topographic maps, and natural vegetation variance. All necessary field tools, including a digital camera and GPS device, were brought to determine the soil type and collect plant samples. All of these visits are planned to cover the entire state of Zakhikhah. All vegetation cover observations, identifying sampling sites and attempting to inventory and collect medicinal plants in t

—Medical images have recently played a significant role in the diagnosis and detection of various diseases. Medical imaging can provide a means of direct visualization to observe through the human body and notice the small anatomical change and biological processes associated by different biological and physical parameters. To achieve a more accurate and reliable diagnosis, nowadays, varieties of computer aided detection (CAD) and computer-aided diagnosis (CADx) approaches have been established to help interpretation of the medical images. The CAD has become among the many major research subjects in diagnostic radiology and medical imaging. In this work we study the improvement in accuracy of detection of CAD system when comb