In this study, a low-cost biosorbent, dead mushroom biomass (DMB) granules, was used for investigating the optimum conditions of Pb(II), Cu(II), and Ni(II) biosorption from aqueous solutions. Various physicochemical parameters, such as initial metal ion concentration, equilibrium time, pH value, agitation speed, particles diameter, and adsorbent dosage, were studied. Five mathematical models describing the biosorption equilibrium and isotherm constants were tested to find the maximum uptake capacities: Langmuir, Freundlich, Redlich-Peterson, Sips, and Khan models. The best fit to the Pb(II) and Ni(II) biosorption results was obtained by Langmuir model with maximum uptake capacities of 44.67 and 29.17 mg/g for these two ions, respectively, whereas for Cu(II), the corresponding value was 31.65 mg/g obtained with Khan model. The kinetic study demonstrated that the optimum agitation speed was 400 rpm, at which the best removal efficiency and/or minimum surface mass transfer resistance (MSMTR) was achieved. A pseudo-second-order rate kinetic model gave the best fit to the experimental data (R2 = 0.99), resulting in MSMTR values of 4.69× 10−5, 4.45× 10−6, and 1.12× 10−6 m/s for Pb(II), Cu(II), and Ni(II), respectively. The thermodynamic study showed that the biosorption process was spontaneous and exothermic in nature.
Perchloroethylene (PERC) is commonly used as a dry-cleaning solvent, it is attributed to many deleterious effects in the biological system. The study aimed to investigate the harmful effect associated with PERC exposure among dry-cleaning workers. The study was carried out on 58 adults in two groups. PERC-exposed group; include thirty-two male dry-cleaning workers using PERC as a dry-cleaning solvent and twenty-six healthy non-exposed subjects. History of PERC exposure, use of personal protection equipment (PPE), safety measurement of the exposed group was recorded. Blood sample was taken from each participant for measurement of hematological markers, liver and kidney function tests. The results showed that 28.1% of the workers were usin
... Show MoreIn this work, a magnetic switch was prepared using two typesof ferrofluid materials, the pure ferrofluid and ferrofluid doped with copper nanoparticles (10 nm). The critical magnetic field (Hc) and the state of magnetic saturation (Hs) were studied using three types of laser sources. The main parameters of the magnetic switch measured using pure ferrofluid and He-Ne Laser source were Hc(0.5 mv, 0.4 G), Hs (8.5 mv, 3 G). For the ferrofluid doped with copper nanoparticles were Hc (1 mv, 4 G), Hs (15 mv, 9.6 G), Using green semiconductor laser for the Pure ferrofluid were Hc (0.5 mv, 0.3 G) Hs (15 mv, 2.9 G). While the ferrofluid doped with copper nanoparticles were Hc (0.5 mv, 1 G), Hs (12 mv, 2.8 G) and by using the violet semiconductor l
... Show MoreThe increased use of hybrid PET /CT scanners combining detailed anatomical information along withfunctional data has benefits for both diagnostic and therapeutic purposes. This presented study is to makecomparison of cross sections to produce 18F , 82Sr and68Ge via different reactions with particle incident energy up to 60 MeV as a part of systematic studies on particle-induced activations on enriched natNe, natRb, natGa 18O,85Rb, and 69Ga targets, theoretical calculation of production yield, calculation of requiredtarget and suggestion of optimum reaction to produce: Fluorine-18 , Strontium-82 andGermanium-68 touse in Hybrid Machines PET/CT Scanners.
Two unsupervised classifiers for optimum multithreshold are presented; fast Otsu and k-means. The unparametric methods produce an efficient procedure to separate the regions (classes) by select optimum levels, either on the gray levels of image histogram (as Otsu classifier), or on the gray levels of image intensities(as k-mean classifier), which are represent threshold values of the classes. In order to compare between the experimental results of these classifiers, the computation time is recorded and the needed iterations for k-means classifier to converge with optimum classes centers. The variation in the recorded computation time for k-means classifier is discussed.
Text categorization refers to the process of grouping text or documents into classes or categories according to their content. Text categorization process consists of three phases which are: preprocessing, feature extraction and classification. In comparison to the English language, just few studies have been done to categorize and classify the Arabic language. For a variety of applications, such as text classification and clustering, Arabic text representation is a difficult task because Arabic language is noted for its richness, diversity, and complicated morphology. This paper presents a comprehensive analysis and a comparison for researchers in the last five years based on the dataset, year, algorithms and the accuracy th
... Show MoreIn this research, optical communication coding systems are designed and constructed by utilizing Frequency Shift Code (FSC) technique. Calculations of the system quality represented by signal to noise ratio (S/N), Bit Error Rate (BER),and Power budget are done. In FSC system, the data of Nonreturn- to–zero (NRZ ) with bit rate at 190 kb/s was entered into FSC encoder circuit in transmitter unit. This data modulates the laser source HFCT-5205 with wavelength at 1310 nm by Intensity Modulation (IM) method, then this data is transferred through Single Mode (SM) optical fiber. The recovery of the NRZ is achieved using decoder circuit in receiver unit. The calculations of BER and S/N for FSC system a
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