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Stimulation of Macrophage Cells Against Cutaneous Leishmaniasis Using Silver Nanoparticles
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Cutaneous leishmaniasis is a disease caused by Leishmania tropica parasite. Current treatments for this parasite are undesirable because of their toxicity, resistance, and high cost. Macrophages are key players against pathogens. Nitric oxide (NO), a molecule produce by immune cells, controls intracellular killing of pathogens during infection. Silver nanoparticles (Ag NPs) demonstrated broad-spectrum activity against various types of infectious diseases. It has the ability to stimulate oxygen species production.  This study aims to analyze the macrophages activation through NO production and estimate the cytotoxicity based on the lactate dehydrogenase (LDH) release upon exposure to L. tropica and Ag NPs. Serially concentrations of Ag NPs were used under two conditions during and following macrophages exposure to L. tropica. MTT assay was used to determine the cytotoxicity of Ag NPs on L. tropica amastigotes during infection of macrophages in vitro. The results showed that by increasing the Ag NPs concentrations, the viability percentage of L. tropica amastigotes decreased and reached to 21.7 ± 0.64 % during infection compared with the control. The 50% inhibitory concentration of Ag NPs on amastigotes was 2.048µg/ml during infection. Moreover, post-phagocytosis study involved the assessment of NO and LDH release by macrophages upon exposure to L. tropica. It have shown that untreated macrophages released low levels of NO while in the presence of Ag NPs, macrophages were activated to produce higher levels of NO under all experimental conditions. On the other hand, macrophages were capable of controlling cytotoxicity and decreasing LDH levels during phagocytosis of L. tropica amastiogotes. Taking together, these findings suggest that Ag NPs can enhance macrophages NO production which provides a method for the identification of Ag NPs ligands with microbicidal and anti-cytotoxic properties against L. tropica pathogens.

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Economics And Administrative Sciences
Finding the best estimation of generalized for failure rates by using Simulation
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The statistical distributions study aimed to obtain on best descriptions  of variable sets phenomena, which each of them got one behavior of that distributions .  The estimation operations study for that distributions considered of important things which could n't canceled in variable behavior study, as result  this research came as trial for reaching to best method for information distribution estimation which is generalized linear failure rate distribution, throughout studying the theoretical sides by depending on statistical posteriori methods  like greatest ability, minimum squares method and Mixing method (suggested method).        

The research

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Publication Date
Fri Sep 30 2011
Journal Name
Al-khwarizmi Engineering Journal
Fuzzy Control of the Robotic Hands Catching Force Using Muscle Wires Actuator
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The aim of this research is controlling the amount of the robotic hand catching force using the artificial muscle wire as an actuator to achieve the desired response of the robotic hand in order to catch different things without destroying or dropping them; where the process is to be similar to that of human hand catching way. The proper selection of the amount of the catching force is achieved through out simulation using the fuzzy control technique. The mechanism of the arrangement of the muscle wires is proposed to achieve good force selections. The results indicate the feasibility of using this proposed technique which mimics human reasoning where as the weight of the caught peace increases, the force increases also with approximatel

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
Simulation and Modelling of Electricity Usage Control and Monitoring System using ThingSpeak
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Renewable energy technology is growing fast especially photovoltaic (PV) system to move the conventional electricity generation and distribution towards smart grid. However, similar to monthly electricity bill, the PV energy producers can only monitor their energy PV generation once a month. Any malfuntion in PV system components may reduce the performance of the system without notice. Thus, developing a real-time monitoring system of PV production is very crucial for early detection. In addition, electricity consumption is also important to be monitored more frequently to increase energy savings awareness among consumers. Hardware based Internet-of-Thing (IoT) monitoring and control system is widely used. However, the implementation of

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Publication Date
Tue Jun 01 2021
Journal Name
Baghdad Science Journal
Improved Image Security in Internet of Thing (IOT) Using Multiple Key AES
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Image is an important digital information that used in many internet of things (IoT) applications such as transport, healthcare, agriculture, military, vehicles and wildlife. etc. Also, any image has very important characteristic such as large size, strong correlation and huge redundancy, therefore, encrypting it by using single key Advanced Encryption Standard (AES) through IoT communication technologies makes it vulnerable to many threats, thus, the pixels that have the same values will be encrypted to another pixels that have same values when they use the same key. The contribution of this work is to increase the security of transferred image. This paper proposed multiple key AES algorithm (MECCAES) to improve the security of the tran

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Detection of Autism Spectrum Disorder Using A 1-Dimensional Convolutional Neural Network
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Autism Spectrum Disorder, also known as ASD, is a neurodevelopmental disease that impairs speech, social interaction, and behavior. Machine learning is a field of artificial intelligence that focuses on creating algorithms that can learn patterns and make ASD classification based on input data. The results of using machine learning algorithms to categorize ASD have been inconsistent. More research is needed to improve the accuracy of the classification of ASD. To address this, deep learning such as 1D CNN has been proposed as an alternative for the classification of ASD detection. The proposed techniques are evaluated on publicly available three different ASD datasets (children, Adults, and adolescents). Results strongly suggest that 1D

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Publication Date
Fri Apr 01 2022
Journal Name
Baghdad Science Journal
Tourism Companies Assessment via Social Media Using Sentiment Analysis
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In recent years, social media has been increasing widely and obviously as a media for users expressing their emotions and feelings through thousands of posts and comments related to tourism companies. As a consequence, it became difficult for tourists to read all the comments to determine whether these opinions are positive or negative to assess the success of a tourism company. In this paper, a modest model is proposed to assess e-tourism companies using Iraqi dialect reviews collected from Facebook. The reviews are analyzed using text mining techniques for sentiment classification. The generated sentiment words are classified into positive, negative and neutral comments by utilizing Rough Set Theory, Naïve Bayes and K-Nearest Neighbor

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Publication Date
Sun Jan 01 2017
Journal Name
Journal Of Petroleum Science And Engineering
Nanoparticles influence on wetting behaviour of fractured limestone formation
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Nanoparticles have gained considerable interest in recent times for oil recovery purposes owing to significant capabilities in wettability alteration of reservoir rocks. Wettability is a key factor controlling displacement efficiency and ultimate recovery of oil. The present study investigates the influence of zirconium (IV) oxide (ZrO2) and nickel (II) oxide (NiO) nanoparticles on the wetting preference of fractured (oil-wet) limestone formations. Wettability was assessed through SEM, AFM and contact angle. The potentials of the nanoparticles to alter oil-wet calcite substrates water wet, was experimentally tested at low nanoparticle concentrations (0.004–0.05 wt%). Quite similar behaviour was observed for both nanoparticles at the same

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Publication Date
Sun Dec 01 2013
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Strategic dimension for theory of constraints and its impact in decision making: بحث تطبيقي في الشركة العامة للصناعات الجلدية
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The research illustrated that the theory of constraints is   "A group of concepts and basics that aim at helping the management in order to determine the difficulties and how to overcome these difficulties through determining the necessary change and how these change can be done efficiently and effectively ".

       The research showed that the theory of constraint including its tools calls for magnifying throughput, constricting the product cycle , determining  the optimal production mix , utilization of scare resources and canceling the idle time , that achieving  throughput  increasing  then  increasing  profit .

      Moreov

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Publication Date
Tue Feb 19 2019
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
Role of the Opportunity Cost in the Overall Economic Development: Applied Study in The General Company for Leather Industries
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This research set to indicate the role of the opportunity cost in the overall economic development (human and social development) by selecting the most appropriate alternative for the growth of the country in exchange for sacrificing profit limits to achieve this growth and development of the country, especially in the present circumstances of the country and after studying the reality of the economic case for him, as the problem lies with don't selecting the best alternative that enhances the gross domestic product, which extends to promote overall economic development and revive the industrial and agricultural sectors, productivity is more like Impotent, versus sacrifice alternative consumption may bring more financially lucrative than

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Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Assessment of image quality of cervical spine complications using Three Magnetic Resonance Imaging Sequences
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Examining and comparing the image quality of degenerative cervical spine diseases through the application of three MRI sequences; the Two-Dimension T2 Weighed Turbo Spin Echo (2D T2W TSE), the Three-Dimension T2 Weighted Turbo Spin Echo (3D T2W TSE), and the T2 Turbo Field Echo (T2_TFE). Thirty-three patients who were diagnosed as having degenerative cervical spine diseases were involved in this study. Their age range was 40-60 years old. The images were produced via a 1.5 Tesla MRI device using (2D T2W TSE, 3D T2W TSE, and T2_TFE) sequences in the sagittal plane. The image quality was examined by objective and subjective assessments. The MRI image characteristics of the cervical spines (C4-C5, C5-C6, C6-C7) showed significant difference

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