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Adaptive reconstruction of the heterogeneous scan line ETM+ correction technique
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Publication Date
Sun Jan 01 2023
Journal Name
Chemical Methodologies
Cytotoxicity and Anticancer Effect of Chitosan-Ag NPs-Doxorubicin-Folic Acid Conjugate on Lungs Cell Line
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This study looked at how the synthetic chitosan-AgNPs-Doxorubicin-folic acid combination affected the A549 cell line in terms of cytotoxicity and anticancer activity. By reducing silver nitrate (AgNO3) and biodegradable chitosan, silver nanoparticles were biosynthesized. The produced conjugate was examined by using FT-IR spectroscopy, atomic force microscopy (AFM), and field emission scanning electron microscopy (FE-SEM). The cytotoxicity assay for the viability of A549 cells revealed that the combination of chitosan, AgNPs, doxorubicin, and folic acid decrease cell viability in a dose-determined by method over 48 hours, which direct to a dependent reduce in the activity of A549 cells. The mechanism analysis of the impacted living cells lea

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Publication Date
Fri Nov 03 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences( P-issn 1683 - 3597 E-issn 2521 - 3512)
Synergistic Effects of 2-Deoxy-D-Glucose and Cinnamic Acid with Erlotinib on NSCLC Cell Line
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Background: In spite of all efforts, Non-small cell lung cancer (NSCLC) is a fatal solid tumor with a poor prognosis as of its high metastasis and resistance to present treatments. Tyrosine kinase inhibitors (TKI) such as erlotinib are efficient in treating NSCLC but the emergence of chemoresistance and adverse effects substantially limits their single use. Objective: in this study, the combination treatments of either 2-deoxy-D-glucose (2DG) or cinnamic acid (CINN) with erlotinib (ERL) were tested for their possible synergistic effect on the proliferation and migration capacity of NSCLC cells. Methods: In this study, NSCLC model cell line A549 was used to investigate the effects of single compounds and their combination on cell gro

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Publication Date
Sun Sep 07 2008
Journal Name
Baghdad Science Journal
Chromosomal aberrations and N-ras activation in human larynx carcinoma cell line Hep-2.
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In the present study, cytogenetic and molecular techniques were conducted to detect the chromosomal aneuploidy and the involvement of N and H genes in squamous larynx carcinoma cell line Hep-2.Our results showed that numerical and structural abnormalities were involved in larynx cancer Hep-2.The total number of chromosomes ranging from tripolyploidy in passage187to more than that in passage207.The more frequent chromosomes involved in numerical aberrations were chromosomes1,7,16,17 and 18. Structural chromosomal aberrations were also detected.Deletion of short arm was detected in chromosome 1(del 1p) and the long arm of chromosome 1(del 1q)and 6(del 6q).Gaining on short arms were also recorded in chromosomes 3(3p+) and 12(12p+).At the mole

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Publication Date
Mon Feb 01 2016
Journal Name
Journal Of Engineering
Deterioration Model for Sewer Network Asset Management in Baghdad City (case study Zeppelin line)
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Asset management involves efficient planning of economic and technical performance characteristics of infrastructure systems. Managing a sewer network requires various types of activities so the network can be able to achieve a certain level of performance. During the lifetime of the network various components will start to deteriorate leading to bad performance and can damage the infrastructure. The main objective of this research is to develop deterioration models to provide an assessment tool for determining the serviceability of the sewer networks in Baghdad city the Zeppelin line was selected as a case study, as well as to give top management authorities the appropriate decision making. Different modeling techniques

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Publication Date
Wed Jul 01 2020
Journal Name
Journal Of Engineering
Using Adaptive Neuro Fuzzy Inference System to Predict Rate of Penetration from Dynamic Elastic Properties
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Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal.  The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in

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Publication Date
Wed May 10 2023
Journal Name
Journal Of Engineering
ADAPTIVE CYCLIC PREFIX LENGTH FOR CONVOLUITIONAL CODE OFDM SYSTEM IN FREQUENCY SELECTIVE CHANNEL
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Orthogonal Frequency Division Multiplexing (OFDM) is one of recent years multicarrier modulation used in order to combat the Inter Symbol Interference (ISI) introduced by frequency selective mobile radio channel. The circular extension of the data symbol, commonly referred to as cyclic prefix is one of the key elements in an OFDM transmission scheme. This paper study The influence of the cyclic prefix duration on the BER performance of an OFDM-VCPL (Orthogonal frequency division multiplexing - Variable Cyclic Prefix Length) system and the conventional OFDM system with frame 64-QAM modulation is evaluated by means of computer simulation in a multipath fading channel. The adaptation of CP is done with respect to the delay spread estimation

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Publication Date
Wed Mar 31 2021
Journal Name
Electronics
Adaptive Robust Controller Design-Based RBF Neural Network for Aerial Robot Arm Model
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Aerial Robot Arms (ARAs) enable aerial drones to interact and influence objects in various environments. Traditional ARA controllers need the availability of a high-precision model to avoid high control chattering. Furthermore, in practical applications of aerial object manipulation, the payloads that ARAs can handle vary, depending on the nature of the task. The high uncertainties due to modeling errors and an unknown payload are inversely proportional to the stability of ARAs. To address the issue of stability, a new adaptive robust controller, based on the Radial Basis Function (RBF) neural network, is proposed. A three-tier approach is also followed. Firstly, a detailed new model for the ARA is derived using the Lagrange–d’A

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Publication Date
Thu Jan 11 2018
Journal Name
Al-khwarizmi Engineering Journal
Control on a 2-D Wing Flutter Using an Adaptive Nonlinear Neural Controller
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An adaptive nonlinear neural controller to reduce the nonlinear flutter in 2-D wing is proposed in the paper. The nonlinearities in the system come from the quasi steady aerodynamic model and torsional spring in pitch direction. Time domain simulations are used to examine the dynamic aero elastic instabilities of the system (e.g. the onset of flutter and limit cycle oscillation, LCO). The structure of the controller consists of two models :the modified Elman neural network (MENN) and the feed forward multi-layer Perceptron (MLP). The MENN model is trained with off-line and on-line stages to guarantee that the outputs of the model accurately represent the plunge and pitch motion of the wing and this neural model acts as the identifier. Th

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Publication Date
Fri Jul 01 2016
Journal Name
Journal Of Engineering
An Adaptive Multi-Objective Particle Swarm Optimization Algorithm for Multi-Robot Path Planning
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This paper discusses an optimal path planning algorithm based on an Adaptive Multi-Objective Particle Swarm Optimization Algorithm (AMOPSO) for two case studies. First case, single robot wants to reach a goal in the static environment that contain two obstacles and two danger source. The second one, is improving the ability for five robots to reach the shortest way. The proposed algorithm solves the optimization problems for the first case by finding the minimum distance from initial to goal position and also ensuring that the generated path has a maximum distance from the danger zones. And for the second case, finding the shortest path for every robot and without any collision between them with the shortest time. In ord

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Publication Date
Tue Jul 24 2018
Journal Name
Sensors
Adaptive Windowing Framework for Surface Electromyogram-Based Pattern Recognition System for Transradial Amputees
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Electromyogram (EMG)-based Pattern Recognition (PR) systems for upper-limb prosthesis control provide promising ways to enable an intuitive control of the prostheses with multiple degrees of freedom and fast reaction times. However, the lack of robustness of the PR systems may limit their usability. In this paper, a novel adaptive time windowing framework is proposed to enhance the performance of the PR systems by focusing on their windowing and classification steps. The proposed framework estimates the output probabilities of each class and outputs a movement only if a decision with a probability above a certain threshold is achieved. Otherwise (i.e., all probability values are below the threshold), the window size of the EMG signa

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