The biosorption of Pb (II), Cd (II), and Hg (II) from simulated aqueous solutions using baker’s yeast biomass was investigated. Batch type experiments were carried out to find the equilibrium isotherm data for each component (single, binary, and ternary), and the adsorption rate constants. Kinetics pseudo-first and second order rate models applied to the adsorption data to estimate the rate constant for each solute, the results showed that the Cd (II), Pb (II), and Hg (II) uptake process followed the pseudo-second order rate model with (R2) 0.963, 0.979, and 0.960 respectively. The equilibrium isotherm data were fitted with five theoretical models. Langmuir model provides the best fitting for the experimental results with (R2) 0.992, 0.9987, and 0.9995 for Cd (II), Pb (II), and Hg (II) respectively. The effect of various influent adsorbates concentrations, and flow rates on the performance of fixed bed adsorber was found for the three heavy metals.
A mathematical model was formulated to describe the breakthrough curves in the fixed bed adsorber for each component. The results show that the mathematical model provides a good description of the adsorption process for Cd (II), Pb (II), and Hg (II) onto fixed bed of baker’s yeast biomass.
This study has applied the theoretical framework of conceptual metaphor theory to the analysis of the source and target domains of metaphors that are used in two English nineteenth century sonnets, both written by contemporaneous female poets. The quantitative and qualitative results of the textual analysis have clearly revealed that Elizabeth Barrett Browning’s sonnet 23 centres around the conceptual mapping of the journey of love and life with that of possession. In contrast, Christina Rossetti’s sonnet Remember tackles the central conceptual mapping of death as a journey in relation to its further experiential connections. In addition, the application of conceptual metaphor theory in identifying the frequencies and densities of metap
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The current research creates an overall relative analysis concerning the estimation of Meixner process parameters via the wavelet packet transform. Of noteworthy presentation relevance, it compares the moment method and the wavelet packet estimator for the four parameters of the Meixner process. In this paper, the research focuses on finding the best threshold value using the square root log and modified square root log methods with the wavelet packets in the presence of noise to enhance the efficiency and effectiveness of the denoising process for the financial asset market signal. In this regard, a simulation study compares the performance of moment estimation and wavelet packets for different sample sizes. The results show that wavelet p
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Uranium concentrations in soil were determined for ten locations in Salahdin governorate using CR-39 track detector, fission fragments track technique was used, the nuclear reaction of nuclear fission fragments obtained by the bombardment of 235U with thermal neutrons from (Am-Be) neutron source with flux (5000n.cm-2.s-1), the concentration values were calculated by a comparison with standard samples. The results of the measurements show that the uranium concentration in soil samples various from 0.42±0.018ppm in Beji province to 0.2±0.014 ppm in Tooz province with an average (0.31±0.08ppm), the values of uranium concentration in all samples are within the permissible limits universally.
<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
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The aim of this research is to assess the validity of Detailed Micro-Modeling (DMM) as a numerical model for masonry analysis. To achieve this aim, a set of load-displacement curves obtained based on both numerical simulation and experimental results of clay masonry prisms loaded by a vertical load. The finite element method was implemented in DMM for analysis of the experimental clay masonry prism. The finite element software ABAQUS with implicit solver was used to model and analyze the clay masonry prism subjected to a vertical load. The load-displacement relationship of numerical model was found in good agreement with those drawn from experimental results. Evidence shows that load-displacement curvefound from the finite element m
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Kidney tumors are of different types having different characteristics and also remain challenging in the field of biomedicine. It becomes very important to detect the tumor and classify it at the early stage so that appropriate treatment can be planned. Accurate estimation of kidney tumor volume is essential for clinical diagnoses and therapeutic decisions related to renal diseases. The main objective of this research is to use the Computer-Aided Diagnosis (CAD) algorithms to help the early detection of kidney tumors that addresses the challenges of accurate kidney tumor volume estimation caused by extensive variations in kidney shape, size and orientation across subjects.
In this paper, have tried to implement an automated segmentati