The study is concern on determine the type of Candida spp.in leukemia patients that were infected with oral candidiasis as a result to their immune suppression (weekend immune system) due to their submission to radiation and chemotherapy treatment. The result showed that the most common isolates were C. guillermondii 19 which represent 31.66% of cases, then followed by C. itermedia 11 which represent 18.3%, while the less common isolates were for C. zeylamodes 3 which represent 5%.

We have investigated twenty five patients with type-2 diabetes mellitus aged (35-60) years and fifteen healthy persons as control group to detect Anti-Helicobacter pylori IgG antibody. All studied groups were carried out to measure fasting blood sugar, anti- Glutamic acid decarboxylase (GAD), anti-? islets cells antibody by IFAT, Anti-H. pylori IgG antibody by ELISA technique. There was significant elevation in the concentration of fasting blood sugar than in control group (P < 0.05), the patients had negative results for anti-GAD antibody and anti- ? islets cells antibody, there were significant differences (P < 0.05) of anti-H. pylori IgG antibody in 28 % of patients had type-2 diabetes than control group. This lead to suggestion that typ

All the prepared metal complexes of Pt (IV), Au(III), Rh (III), Co (II) and V(IV) with new ligand sodium [5-(p-nitro phenyl)-/4-phenyl-1,2,4-triazole-3-dithiocarbamato hydrazide] (TRZ.DTC) have been synthesized and characterized in solid state by using flame atomic absorption, elemental analysis C.H.N.S, FT-IR ,UV-Vis Spectroscopy, conductivity and magnetic susceptibility measurements. The nature of the complexes formed in ethanolic solution has been studied following the molar ratio method also was studied stability constant and found to be stable in molar ratio1:1 of VL (IV) and CoL(II) while Pt(IV), Au(III) and Rh(III) complexes stable in molar ratio 1:2 as well as the molar absorptivity for these complexes were calculated. From the prev

This study aims to characterize traumatic spinal cord injury (TSCI) neurophysiologically using an intramuscular fine-wire electromyography (EMG) electrode pair. EMG data were collected from an agonist-antagonist pair of tail muscles of Macaca fasicularis, pre- and post-lesion, and for a treatment and control group. The EMG signals were decomposed into multi-resolution subsets using wavelet transforms (WT), then the relative power (RP) was calculated for each individual reconstructed EMG sub-band. Linear mixed models were developed to test three hypotheses: (i) asymmetrical volitional activity of left and right side tail muscles (ii) the effect of the experimental TSCI on the frequency content of the EMG signal, (iii) and the effect

These days, it is crucial to discern between different types of human behavior, and artificial intelligence techniques play a big part in that.  The characteristics of the feedforward artificial neural network (FANN) algorithm and the genetic algorithm have been combined to create an important working mechanism that aids in this field. The proposed system can be used for essential tasks in life, such as analysis, automation, control, recognition, and other tasks. Crossover and mutation are the two primary mechanisms used by the genetic algorithm in the proposed system to replace the back propagation process in ANN. While the feedforward artificial neural network technique is focused on input processing, this should be based on the proce

   The aim of this study is to investigate the kinetics of copper removal from aqueous solutions using an electromembrane extraction (EME) system. To achieve this, a unique electrochemical cell design was adopted comprising two glass chambers, a supported liquid membrane (SLM), a graphite anode, and a stainless-steel cathode. The SLM consisted of a polypropylene flat membrane infused with 1-octanol as a solvent and bis(2-ethylhexyl) phosphate (DEHP) as a carrier. The impact of various factors on the kinetics constant rate was outlined, including the applied voltage, initial pH of the donor phase solution, and initial copper concentration. The results demonstrated a significant influence of the applied voltage on enhancing the rate of c

This paper proposes an on-line adaptive digital Proportional Integral Derivative (PID) control algorithm based on Field Programmable Gate Array (FPGA) for Proton Exchange Membrane Fuel Cell (PEMFC) Model. This research aims to design and implement Neural Network like a digital PID using FPGA in order to generate the best value of the hydrogen partial pressure action (PH₂) to control the stack terminal output voltage of the (PEMFC) model during a variable load current applied. The on-line Particle Swarm Optimization (PSO) algorithm is used for finding and tuning the optimal value of the digital PID-NN controller (kp, ki, and kd) parameters that improve the dynamic behavior of the closed-loop digital control fue