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Clinical use of tumor necrosis factor-alpha inhibitors in Iraq: a review of their documented efficacy, safety, and associated genetics
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This comprehensive review examines the efficacy and safety of tumor necrosis factor-alpha (TNF-α) inhibitors in treating various autoimmune diseases, and focuses on their application in Iraqi patients. Elevated TNF-α levels are linked to autoimmune disorders, leading to the development of anti-TNF-α therapies such as infliximab, etanercept, adalimumab, certolizumab pegol, and golimumab, which have gained FDA approval for conditions like psoriasis, in¬flammatory bowel disease, ankylosing spondylitis, and rheumatoid arthritis. While these therapies demonstrate sig¬nificant therapeutic benefits, including improved quality of life and disease management, they also carry risks, such as increased susceptibility to infections and potential malignancies. The review highlights the variable patient re¬sponses to TNF-α inhibitors, influenced by pharmacokinetic and pharmacodynamic factors as well as genetic varia¬tions. The rise of anti-drug antibodies and inadequate drug concentrations are common challenges observed, empha¬sizing the need for therapeutic drug monitoring. Safety profiles of TNF-α inhibitors are generally favorable, but adverse effects (including infections and infusion reactions) have been reported. Genetic factors, such as polymorphisms in the TNF-α gene, may also play a role in the treatment responsiveness and adverse effects, suggesting the potential for personalized medicine approaches. While TNF-α inhibitors effectively manage autoimmune diseases in Iraqi pa¬tients, further research is warranted in order to optimize treatment strategies, assess long-term safety, and explore genetic influences on therapy outcomes. The findings underscore the importance of individualized treatment plans so as to enhance the efficacy and minimize the risks associated with these biologic therapies.

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Publication Date
Sat Jan 01 2022
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Increasing validation accuracy of a face mask detection by new deep learning model-based classification
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During COVID-19, wearing a mask was globally mandated in various workplaces, departments, and offices. New deep learning convolutional neural network (CNN) based classifications were proposed to increase the validation accuracy of face mask detection. This work introduces a face mask model that is able to recognize whether a person is wearing mask or not. The proposed model has two stages to detect and recognize the face mask; at the first stage, the Haar cascade detector is used to detect the face, while at the second stage, the proposed CNN model is used as a classification model that is built from scratch. The experiment was applied on masked faces (MAFA) dataset with images of 160x160 pixels size and RGB color. The model achieve

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Publication Date
Tue Aug 31 2021
Journal Name
Inmateh Agricultural Engineering
DETERMINING THE EFFICIENCY OF A SMART SPRAYING ROBOT FOR CROP PROTECTION USING IMAGE PROCESSING TECHNOLOGY
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A system was used to detect injuries in plant leaves by combining machine learning and the principles of image processing. A small agricultural robot was implemented for fine spraying by identifying infected leaves using image processing technology with four different forward speeds (35, 46, 63 and 80 cm/s). The results revealed that increasing the speed of the agricultural robot led to a decrease in the mount of supplements spraying and a detection percentage of infected plants. They also revealed a decrease in the percentage of supplements spraying by 46.89, 52.94, 63.07 and 76% with different forward speeds compared to the traditional method.

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Publication Date
Sat Sep 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Removal of Lead Ions from Wastewater by using a Local Adsorbent from Charring Tea Wastes
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   Adsorption of lead ions from wastewater by native agricultural waste, precisely tea waste. After the activation and carbonization of tea waste, there was a substantial improvement in surface area and other physical characteristics which include density, bulk density, and porosity. FTIR analysis indicates that the functional groups in tea waste adsorbent are aromatic and carboxylic. It can be concluded that the tea waste could be a good sorbent for the removal of Lead ions from wastewater. Different dosages of the adsorbents were used in the batch studies. A random series of experiments indicated a removal degree efficiency of lead reaching (95 %) at 5 ppm optimum concentration, with adsorbents R2 =97.75% for tea. Three mo

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Publication Date
Sat Apr 01 2023
Journal Name
Chemical Methodologies
A Novel Design for Gas Sensor of Zinc Oxide Nanostructure Prepared by Hydrothermal Annealing Technique
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Publication Date
Sun Sep 01 2019
Journal Name
Baghdad Science Journal
Common Fixed Point of a Finite-step Iteration Algorithm Under Total Asymptotically Quasi-nonexpansive Maps
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      Throughout this paper, a generic iteration algorithm for a finite family of total asymptotically quasi-nonexpansive maps in uniformly convex Banach space is suggested. As well as weak / strong convergence theorems of this algorithm to a common fixed point are established. Finally, illustrative numerical example by using Matlab is presented.

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Publication Date
Sat Oct 16 2021
Journal Name
Iraqi Journal Of Physics
Numerical analysis of molecules intersystem crossing effect on a passively Q- switched laser pulse characteristics
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The effect of molecules intersystem crossing (Kisc) on characteristics
(energy and duration) of a Passive Q- switched Laser Pulse has been
studied by mathematical description (rate equations model) for
temporal performance of which was used as a saturable absorber
material (passive switch) with laser. The study shows that the energy
and duration pulse are decreasing while the molecules intersystem
crossing into saturable absorber energy levels is increasing.

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Publication Date
Tue Dec 25 2018
Journal Name
Summaries Of Working Papers, Research And Experiments
E-learning at the College of Mass Communication, subject: public relations campaigns as a model
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Publication Date
Sat Apr 30 2022
Journal Name
Eastern-european Journal Of Enterprise Technologies
Improvement of noisy images filtered by bilateral process using a multi-scale context aggregation network
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Deep learning has recently received a lot of attention as a feasible solution to a variety of artificial intelligence difficulties. Convolutional neural networks (CNNs) outperform other deep learning architectures in the application of object identification and recognition when compared to other machine learning methods. Speech recognition, pattern analysis, and image identification, all benefit from deep neural networks. When performing image operations on noisy images, such as fog removal or low light enhancement, image processing methods such as filtering or image enhancement are required. The study shows the effect of using Multi-scale deep learning Context Aggregation Network CAN on Bilateral Filtering Approximation (BFA) for d

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Publication Date
Thu Feb 28 2019
Journal Name
Journal Of Engineering
Numerical Simulation of Unsaturated Soil Water from a Trickle Irrigation System for Sandy Loam Soils
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Trickle irrigation is a system for supplying filtered water and fertilizer directly into the soil and water and it is allowed to dissipate under low pressure in an exact predetermined pattern. An equation to estimate the wetted area of unsaturated soil with water uptake by roots is simulated numerically using the HYDRUS-2D/3D software. In this paper, two soil types, which were different in saturated hydraulic conductivity were used with two types of crops tomato and corn, different values of emitter discharge and initial volumetric soil moisture content were assumed. It was assumed that the water uptake by roots was presented as a continuous sink function and it was introduced into Richard's equation in the unsaturated z

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Publication Date
Sat Apr 01 2023
Journal Name
Baghdad Science Journal
Characterization of a novel pathway for xanthene degradation by the engineered strain Sphingobium yanoikuyae B1DR
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Polyaromatic hydrocarbons (PAHs) are a group of aromatic compounds that contain at least two rings. These compounds are found naturally in petroleum products and are considered the most prevalent pollutants in the environment. The lack of microorganism capable of degrading some PAHs led to their accumulation in the environment which usually causes major health problems as many of these compounds are known carcinogens. Xanthene is one of the small PAHs which has three rings. Many xanthene derivatives are useful dyes that are used for dyeing wood and cosmetic articles. However, several studies have illustrated that these compounds have toxic and carcinogenic effects. The first step of the bacterial degradation of xanthene is conducted by d

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