Been Antkhav three isolates of soil classified as follows: Bacillus G3 consists of spores, G12, G27 led Pal NTG treatment to kill part of the cells of the three isolates varying degrees treatment also led to mutations urged resistance to streptomycin and rifampicin and double mutations

Thermal evaporation method has used for depositing CdTe films
on corning glass slides under vacuum of about 10-5mbar. The
thicknesses of the prepared films are400 and 1000 nm. The prepared
films annealed at 573 K. The structural of CdTe powder and prepared
films investigated. The hopping and thermal energies of as deposited
and annealed CdTe films studied as a function of thickness. A
polycrystalline structure observed for CdTe powder and prepared
films. All prepared films are p-type semiconductor. The hopping
energy decreased as thickness increased, while thermal energy
increased.

Alzheimer’s disease (AD) is an age-related progressive and neurodegenerative disorder, which is characterized by loss of memory and cognitive decline. It is the main cause of disability among older people. The rapid increase in the number of people living with AD and other forms of dementia due to the aging population represents a major challenge to health and social care systems worldwide. Degeneration of brain cells due to AD starts many years before the clinical manifestations become clear. Early diagnosis of AD will contribute to the development of effective treatments that could slow, stop, or prevent significant cognitive decline. Consequently, early diagnosis of AD may also be valuable in detecting patients with dementia who have n

Objective: The study aimed to determine quality of life domains for adult patients with limbs loss and to identify
the association between quality of life domains and demographic characteristics and medical information.
Methodology: A descriptive study was carried out at Baghdad artificial limb center, Al-Salam medical
rehabilitation center, Al-Ghadeer medical rehabilitation center and the rheumatoid and medical rehabilitation
center for the period from September 2007 to April 2008. A purposive ''non- probability'' sample of (200)
patients with limbs loss. Questionnaire form was constructed for the purpose of the study. Data were collected
through the application of the questionnaire and interview technique. Data were a

As they are the smallest functional parts of the muscle, motor units (MUs) are considered as the basic building blocks of the neuromuscular system. Monitoring MU recruitment, de-recruitment, and firing rate (by either invasive or surface techniques) leads to the understanding of motor control strategies and of their pathological alterations. EMG signal decomposition is the process of identification and classification of individual motor unit action potentials (MUAPs) in the interference pattern detected with either intramuscular or surface electrodes. Signal processing techniques were used in EMG signal decomposition to understand fundamental and physiological issues. Many techniques have been developed to decompose intramuscularly detec

In this paper, we characterize the percolation condition for a continuum secondary cognitive radio network under the SINR model. We show that the well-established condition for continuum percolation does not hold true in the SINR regime. Thus, we find the condition under which a cognitive radio network percolates. We argue that due to the SINR requirements of the secondaries along with the interference tolerance of the primaries, not all the deployed secondary nodes necessarily contribute towards the percolation process- even though they might participate in the communication process. We model the invisibility of such nodes using the concept of Poisson thinning, both in the presence and absence of primaries. Invisibility occurs due to nodes

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