An analytical model in the form of a hyperbolic function has been suggested for the axial potential distribution of an electrostatic einzel lens. With the aid of this hyperbolic model the relative optical parameters have been computed and investigated in detail as a function of the electrodes voltage ratio for various trajectories of an accelerated charged-particles beam. The electrodes voltage ratio covered a wide range where the lens may be operated at accelerating and decelerating modes. The results have shown that the proposed hyperbolic field has the advantages of producing low aberrations under various magnification conditions and operational modes. The electrodes profile and their three-dimensional diagram have been determined which showed the possibility of being practically realized.
Hyperprolactinemia is a common endocrine abnormality caused by physiological factors like pregnancy and lactation, drug-induced factors like antipsychotics, pituitary adenomas that secrete prolactin, or stalk compression or section that reduces dopamine inhibition. Dopamine agonists cure most prolactinomas.
To assess response to treatment in micro versus macroprolactinoma.
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The deficiency of potable water resources and energy supply is emerging as a significant and concerning obstacle to sustainable development. Solar and waste heat-powered humidification dehumidification (HDH) desalination systems become essential due to the severe impacts of global warming and water shortages. This problem highlights the need to apply boosted water desalination solutions. Desalination is a capital-intensive process that demands considerable energy, predominantly sourced from fossil fuels worldwide, posing a significant carbon footprint risk. HDH is a very efficient desalination method suitable for remote areas with moderate freshwater requirements for domestic and agricultural usage. Several operational and maintenance conce
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DAIRMD Professor Hayder R. Al-Hamamy, **Professor Adil A. Noaimi, **Dr. Ihsan A. Al-Turfy, IOSR Journal of Dental and Medical Sciences (IOSR-JDMS), 2015
Numerous integral and local electron density’s topological parameters of significant metal-metal and metal-ligand bonding interactions in a trinuclear tetrahydrido cluster [(Cp* Ir) (Cp Ru)2 (μ3-H) (μ-H)3]1 (Cp = η5 -C5Me5), (Cp* = η5 -C5Me4Et) were calculated and interpreted by using the quantum theory of atoms in molecules (QTAIM). The properties of bond critical points such as the delocalization indices δ (A, B), the electron density ρ(r), the local kinetic energy density G(r), the Laplacian of the electron density ∇2ρ(r), the local energy density
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Most Internet-tomography problems such as shared congestion detection depend on network measurements. Usually, such measurements are carried out in multiple locations inside the network and relied on local clocks. These clocks usually skewed with time making these measurements unsynchronized and thereby degrading the performance of most techniques. Recently, shared congestion detection has become an important issue in many computer networked applications such as multimedia streaming and
peer-to-peer file sharing. One of the most powerful techniques that employed in literature is based on Discrete Wavelet Transform (DWT) with cross-correlation operation to determine the state of the congestion. Wavelet transform is used as a de-noisin
A 20 year-old male was admitted with a history of recurrent palpitations from 5 years. Baseline ECG revealed premature ventricular contractions (PVCs) with delta waves. Stress ECG showed short non-sustained Ventricular tachycardia (VT). Echocardiography showed moderate dilation of the left ventricle with mild reduced systolic function and Ejection fraction was estimated to be 42%. Right ventricle was mildly dilated and hypokinetic. Both atria were mildly dilated. The patient referred to CVC for EP study with possible ablation. The ablation of the focus led to complete suppression of the ectopy. Post-procedure ECG and echocardiography showed normalized rhythm and systolic function.
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Discriminant between groups is one of the common procedures because of its ability to analyze many practical phenomena, and there are several methods can be used for this purpose, such as linear and quadratic discriminant functions. recently, neural networks is used as a tool to distinguish between groups.
In this paper the simulation is used to compare neural networks and classical method for classify observations to group that is belong to, in case of some variables that don’t follow the normal distribution. we use the proportion of number of misclassification observations to the all observations as a criterion of comparison.