background: osteoporosis is a metabolic bone disease that affects women more than men, it is characterized by generalizes reduction of bone mineral density (BMD) leaving a fragile weak bone that is liable to fracture, gonial angle index (GAI) is one of the radio-morphometric indices, it has been controversial whether it is related to bone mineral density or ageing or none of them. The aim of study is to evaluate the role of cone beam computed tomography (CBCT) as a screening tool for diagnosis of osteoporosis and age effect in females using gonial angle index. Material and method: 60 females were divided into 3 groups according to age and (BMD) status into: Group1 (non-osteoporosis 20-30 years), Group2 (non-osteoporosis 50years and above), and Group3 (osteoporosis 50years and above), each patient had a CBCT scan, and gonial angle index was measured compared among groups. Results: Gonial angle index showed a significant difference between Group1 and Group2 at p < 0.05, while it showed no significant difference between Group2 and Group3 at p > 0.05. Conclusion: Gonial angle index is significantly affected by age factor while it was not affected by osteoporosis, so it cannot be used as a parameter that can predict bone mineral density status patients
The main parameters and methods influencing the removal of Gentian Violet (GV) dye from aqueous media were investigated using a stachy plant in this study. The surface of the stachy plant was determined using FTIR spectra. Adsorption is influenced by the adsorbent's characteristic groups. The research took into account the usual conditions for GV dye adsorption by the stachy plant, such as the impact of contact time. Mass dosage , after 0.3 g the amount of adsorbed dye declines. Study pH and ionic strength, the results obtained showed that at pH 3 the largest adsorption of (GV) was seen, while at pH 9, the lowest adsorption was observed at 298 K, the adsorption kinetics and equilibrium constants were achieved, and the equ
... Show MoreThe present work aimed to study the efficiency of nanofiltration (NF) and reverse osmosis (RO) process for treatment of heavy metals wastewater contains zinc. In this research, the salt of heavy metals were zinc chloride (ZnCl2) used as feed solution.Nanofiltration and reverse osmosis membranes are made from polyamide as spiral wound module. The parameters studied were: operating time (0 – 70 min), feed concentrations for zinc ions (10 – 300 mg/l), operating pressure (1 – 4 bar).The theoretical results showed, flux of water through membrane decline from 19 to 10.85 LMH with time. Flux decrease from 25.84 to 10.88 LMH with the increment of feed concentration. The raise of pressure, the flux increase for NF and RO membranes.The maximum
... Show MoreIn this study three inorganic nano additives, namely; CaCO3, Al2O3 and SiO2 were used to prepare nanocomposites of unsaturated polyester in order to modify their mechanical properties, i.e. tensile strength, elongation, impact and hardness. The results indicated that all the three additives were effective to improve the mechanical properties up to 4% by weight. The effectiveness of them follows the order : CaCO3 > Al2O3 > SiO2 This is due to their particle size in which CaCO3 (13nm), Al2O3 (20-30nm) and SiO2 (15-20nm).
Biosorpion of lead (Pb), Cadmium (Cd) and Nickl(Ni) by dried biomass of Chara sp. for sample of BMP was used as alternative approach of conventional method. The range of removal percentages was between 92-97%, 70-98.7% and 46.6-96.6% for Pb, Cd and Ni respectively at 3h.Treatment time, with 300-500 mg dried weight from Chara sp. powder at pH 4, with 60 rpm at shaker. FTIR analysis showed the active groups which are responsible for sequestration of heavy metals represented by carboxyl, hydroxyl alkyl, amine and amide. The Biosorption equilibrium experiment for elements showed that the highest sorption percentage for three elements was, Pb 96.6% after 30 minute, for Cd was 100% after 15 minute and 40% to Ni after 75 minute, while the biosorp
... Show MoreIn this work laser detection and tracking system (LDTS) is designed and implemented using a fuzzy logic controller (FLC). A 5 mW He-Ne laser system and an array of nine PN photodiodes are used in the detection system. The FLC is simulated using MATLAB package and the result is stored in a lock up table to use it in the real time operation of the system. The results give a good system response in the target detection and tracking in the real time operation.
A genetic algorithm model coupled with artificial neural network model was developed to find the optimal values of upstream, downstream cutoff lengths, length of floor and length of downstream protection required for a hydraulic structure. These were obtained for a given maximum difference head, depth of impervious layer and degree of anisotropy. The objective function to be minimized was the cost function with relative cost coefficients for the different dimensions obtained. Constraints used were those that satisfy a factor of safety of 2 against uplift pressure failure and 3 against piping failure.
Different cases reaching 1200 were modeled and analyzed using geo-studio modeling, with different values of input variables. The soil wa
Reservoir characterization plays a crucial role in comprehending the distribution of formation properties and fluids within heterogeneous reservoirs. This knowledge is instrumental in constructing an accurate three-dimensional model of the reservoir, facilitating predictions regarding porosity, permeability, and fluid flow distribution. Among the various methods employed for reservoir characterization, the hydraulic flow unit stands out as a widely adopted approach. By effectively subdividing the reservoir into distinct zones, each characterized by unique petrophysical and geological properties, hydraulic flow units enable comprehensive reservoir analysis. The concept of the flow unit is closely tied to the flow zone indicator, a cr
... Show MoreKE Sharquie, HM Al-Hamamy, AA Noaimi, IA Al-Shawi, Journal of the Saudi Society of Dermatology & Dermatologic Surgery, 2011 - Cited by 9
The successful implementation of deep learning nets opens up possibilities for various applications in viticulture, including disease detection, plant health monitoring, and grapevine variety identification. With the progressive advancements in the domain of deep learning, further advancements and refinements in the models and datasets can be expected, potentially leading to even more accurate and efficient classification systems for grapevine leaves and beyond. Overall, this research provides valuable insights into the potential of deep learning for agricultural applications and paves the way for future studies in this domain. This work employs a convolutional neural network (CNN)-based architecture to perform grapevine leaf image classifi
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