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Optimizing genetic prediction: Define-by-run DL approach in DNA sequencing
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Abstract: The utility of DNA sequencing in diagnosing and prognosis of diseases is vital for assessing the risk of genetic disorders, particularly for asymptomatic individuals with a genetic predisposition. Such diagnostic approaches are integral in guiding health and lifestyle decisions and preparing families with the necessary foreknowledge to anticipate potential genetic abnormalities. The present study explores implementing a define-by-run deep learning (DL) model optimized using the Tree-structured Parzen estimator algorithm to enhance the precision of genetic diagnostic tools. Unlike conventional models, the define-by-run model bolsters accuracy through dynamic adaptation to data during the learning process and iterative optimization of critical hyperparameters, such as layer count, neuron count per layer, learning rate, and batch size. Utilizing a diverse dataset comprising DNA sequences fromtwo distinct groups: patients diagnosed with breast cancer and a control group of healthy individuals. The model showcased remarkable performance, with accuracy, precision, recall, F1-score, and area under the curve metrics reaching 0.871, 0.872, 0.871, 0.872, and 0.95, respectively, outperforming previous models. These findings underscore the significant potential of DL techniques in amplifying the accuracy of disease diagnosis and prognosis through DNA sequencing, indicating substantial advancements in personalized medicine and genetic counseling. Collectively, the findings of this investigation suggest that DL presents transformative potential in the landscape of genetic disorder diagnosis and management.

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Early Diagnose Alzheimer's Disease by Convolution Neural Network-based Histogram Features Extracting and Canny Edge
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Alzheimer's disease (AD) increasingly affects the elderly and is a major killer of those 65 and over. Different deep-learning methods are used for automatic diagnosis, yet they have some limitations. Deep Learning is one of the modern methods that were used to detect and classify a medical image because of the ability of deep Learning to extract the features of images automatically. However, there are still limitations to using deep learning to accurately classify medical images because extracting the fine edges of medical images is sometimes considered difficult, and some distortion in the images. Therefore, this research aims to develop A Computer-Aided Brain Diagnosis (CABD) system that can tell if a brain scan exhibits indications of

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Publication Date
Thu Oct 01 2020
Journal Name
Chemical Engineering And Processing - Process Intensification
Cobalt Removal from Simulated Wastewaters Using a Novel Flow-by Fixed Bed Bio-electrochemical Reactor
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Publication Date
Fri Sep 15 2023
Journal Name
Journal Of Optics
Studying of the structural and optical properties of titanium dioxide nanoparticles prepared by chemical method
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Publication Date
Tue Sep 01 2020
Journal Name
Optik
Synthesis of Ag2O films by pulsed laser deposited on porous silicon as gas sensor application
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Publication Date
Tue Nov 01 2022
Journal Name
Heliyon
Removal of copper by Azolla filiculoides and Lemna minor: phytoremediation potential, adsorption kinetics and isotherms
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Publication Date
Sun Dec 04 2011
Journal Name
Baghdad Science Journal
Spectrophotometric determination of micro amount of palladium(II) platinum (II)By using pyrazolone azo resorcinol
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A sensitive and selective method have been developed for the determination of palladium (II)and platinum (II) . A new reagent and two complexes have been prepared in ethanolic solutions .The method is based on the chelation of metal ions with 4-(4?- pyrazolon azo) resorcinol (APAR) to form intense color soluble products, that are stable and have a maximum absorption at 595 nm and at 463 nm and ?max of 1.11×10 4 and.1.35 ×104 Lmole-1cm-1 for Pd(II) Pt(II) respectively. A linear correlation of (1.4 – 0.2) and (3.2 -0.4 ) ppm for pd(II) pt(II) respectively .The stability constants , relative errors , a relative standard deviations for Pd(II) and Pt(II) were 0.40×105 , 0.4×104 L mol-1 ,0.34 - 0.21% and 2.4 – 0.91% respectively.

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Publication Date
Mon Apr 01 2019
Journal Name
Journal Of Engineering
Removal of Methyl Orange from Aqueous Solutions by Adsorption Using Corn Leaves as Adsorbent Material
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A comparative study was done on the adsorption of methyl orange dye (MO) using non-activated and activated corn leaves with hydrochloric acid as an adsorbent material. Scanning electron microscopy (SEM) and Fourier Transform Infrared spectroscopy (FTIR) were utilized to specify the properties of adsorbent material. The effect of several variables (pH, initial dye concentration, temperature, amount of adsorbent and contact time) on the removal efficiency was studied and the results indicated that the adsorption efficiency increases with the increase in the concentration of dye, adsorbent dosage and contact time, while inversely proportional to the increase in pH and temperature for both the treated and untreated corn leaves. The equi

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Publication Date
Sun Oct 21 2018
Journal Name
Iraqi Journal Of Physics
Spectroscopic study the plasma parameters for Pb doped CuO prepared by pulse Nd:YAG laser deposition
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In this work, plasma parameters such as, the electron temperature )Te(, electron density ne, plasma frequency )fp(, Debye length )λD(
and Debye number )ND), have been studied using optical emission spectroscopy technique. The spectrum of plasma with different values of energy, Pb doped CuO at different percentage (X=0.6, 0.7, 0.8) were recorded. The spectroscopic study for these mixing under vacuum with pressure down to P=2.5×10-2 mbar. The results of electron temperature for X=0.6 range (1.072-1.166) eV, for X=0.7 the Te range (1.024-0.855) eV and X=0.8 the Te is (1.033-0.921) eV. Optical properties of CuO:Pb thin films were determined through the optical transmission method using ultraviolet visible spectrophotometer within the ra

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Publication Date
Mon Jun 01 2020
Journal Name
Iop Conference Series: Materials Science And Engineering
Removal of COD from Petroleum refinery Wastewater by Electro-Coagulation Process Using SS/Al electrodes
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Abstract<p>In the present study, the effectiveness of a procedure of electrocoagulation for removing chemical oxygen demand (COD) from the wastewater of petroleum refinery has been evaluated. Aluminum and stainless steel electrodes were used as a sacrificial anode and cathode respectively. The effect of current density (4-20mAcm<sup>−2</sup>), pH (3-11), and NaCl concentration (0-4g/l) on efficiency of removal of chemical oxygen demand was investigated. The results have shown that increasing of current density led to increase the efficiency of COD removal while increasing NaCl concentration resulted in decreasing of COD removal efficiency. Effect of pH was found to be lowering COD re</p> ... Show More
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Publication Date
Sat Oct 01 2022
Journal Name
Journal Of Engineering
Production Load–bearing Concrete Masonry Units by Using Recycled Waste Crushed Clay Bricks; A Review
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There are serious environmental problems in all countries of the world, due to the waste material such as crushed clay bricks (CCB) and in huge quantities resulting from the demolition of buildings. In order to reduce the effects of this problem as well as to preserve natural resources, it is possible to work on recycling (CCB) and to use it in the manufacture of environmentally friendly loaded building units by replacing percentages in coarse aggregate by volume. It can be used as a powder and replacing of percentages in cement by weight and study the effect on the physical and mechanical properties of the concrete and the masonry unit. Evaluation of its performance through workability, dry density, compressive strength, thermal conduct

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