Human cytomegalovirus (HCMV) infection is ubiquitous and successfully reactivated in patients with immune dysfunction as in patient with multiple myeloma (MM), causing a wide range of life-threatening diseases. Early detection of HCMV and significant advances in MM management has amended patient outcomes and prolonged survival rates.

The employment of cognitive radio (CR) is critical to the successful development of wireless communications. In this field, especially when using the multiple input multiple output (MIMO) antenna technology, energy consumption is critical. If the principal user (PU) is present, developers can utilize the energy detecting approach to tell. The researchers employed two distinct phases to conduct their research: the intense and accurate sensing stages. After the furious sensing step was completed, the PU user was identified as having a maximum or minimal energy channel. There are two situations in which the proposed algorithm's performance is tested: channels for fading AWGN and Rayleigh. When the proposed methods' simulation results a

Phosphorus (P) is an element that is potatoes require in large amounts. Soil pH is a crucial factor impacting phosphorus availability in potato production. This study was conducted to evaluate the influence of P application rates on the P efficiency for tuber yield, specific gravity, and P uptake. Additionally, the relationship between soil pH and total potato tuber yield was determined. Six rates of P fertilization (0–280 kg P ha−1) were applied at twelve different sites across Northern Maine. Yield parameters were not responsive to P application rates. However, regression analysis showed that soil pH was significantly correlated with total potato tuber yield(R2 = 0.38). Sites with soil pH values < 6 had total tuber yields,

Background: Mini implant stability is primarily related to local bone density; no studies have evaluated bone density related to mini implant placement for orthodontic anchorage between different age groups in the maxilla and the mandible. The present research aims to evaluate side, gender, age, and regional differences in bone density of the alveolar bone at various orthodontic implant sites. Materials and method: Fifty three individuals who were divided into two groups according to their age into: group I (ages 16-20 years) and group II (ages 21-29 years) had subjected to clinical examination, then 64-multislice computed tomography scan data were evaluated and bone density was measured in Hounsfield unit at 102 points (51 in the maxilla

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

     The radio drama is considered to be one of the arts that is discovered after a long period of theater's discovery. Initially , it was the broad framework of the theater's work when radio was broadcasting the shows on the huge theaters. This beginning encouraged many of the radio specialists to correlate plays with radio and make a novice and distinctive type of art. Thus, radio drama made its first step including the following   ( plays, short and long series drama as well as other types of radio arts). Because of the above mentioned , the researcher is stimulating  to study directing techniques to process the radio drama script ( Khata'a play as a sample).

The first chapter deals with the

There has been a growing interest in the use of chaotic techniques for enabling secure communication in recent years. This need has been motivated by the emergence of a number of wireless services which require the channel to provide very low bit error rates (BER) along with information security. This paper investigates the feasibility of using chaotic communications over Multiple-Input Multiple-Output (MIMO) channels by combining chaos modulation with a suitable Space Time Block Code (STBC). It is well known that the use of Chaotic Modulation techniques can enhance communication security. However, the performance of systems using Chaos modulation has been observed to be inferior in BER performance as compared to conventional communication

The growing interest in the use of chaotic techniques for enabling secure communication in recent years has been motivated by the emergence of a number of wireless services which require the service provider to provide low bit error rates (BER) along with information security. This paper investigates the feasibility of using chaotic communications over Multiple-Input-Multiple-Output (MIMO) channels. While the use of Chaotic maps can enhance security, it is seen that the overall BER performance gets degraded when compared to conventional communication schemes. In order to overcome this limitation, we have proposed the use of a combination of Chaotic modulation and Alamouti Space Time Block Code. The performance of Chaos Shift Keying (CSK) wi

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med

      Let S be a commutative ring with identity, and A is an S-module. This paper introduced an important concept, namely strongly maximal submodule. Some properties and many results were proved as well as the behavior of that concept with its localization was studied and shown.