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Evaluation of the Effect of Topical Artemisia dracunculus Administration on Serum Levels of Selected Interleukins and Spleen Index in Imiquimod-Induced Psoriasis in Male Mice Compared to Clobetasol Propionate (Dermovate (R)) Ointment
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Psoriasis is a long-lasting autoimmune disease that is characterized by swollen skin patches. Normally, these skin patches are dark, swollen, itchy and scaly. The single application of the innate TLR7/8 ligand Imiquimod (IMQ) in mice easily induces a dermatitis that closely resembles human psoriasis, critically dependent on the axis of IL-23/IL-17. Artemisia dracunculus prepared as an ointment and has been used topically to mice before imiquimod application. The results of the current study showed that A. dracunculus ointment can significantly reduce psoriasis area and severity index in (A. dracunculus ointment + imiquimod group as compared with both control group and (vehicle ointment + imiquimod) group.

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Publication Date
Fri Dec 25 2009
Journal Name
Wireless Personal Communications
A N-Radon Based OFDM Trasceivers Design and Performance Simulation Over Different Channel Models
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In this paper a new method is proposed to perform the N-Radon orthogonal frequency division multiplexing (OFDM), which are equivalent to 4-quadrature amplitude modulation (QAM), 16-QAM, 64-QAM, 256-QAM, ... etc. in spectral efficiency. This non conventional method is proposed in order to reduce the constellation energy and increase spectral efficiency. The proposed method gives a significant improvement in Bit Error Rate performance, and keeps bandwidth efficiency and spectrum shape as good as conventional Fast Fourier Transform based OFDM. The new structure was tested and compared with conventional OFDM for Additive White Gaussian Noise, flat, and multi-path selective fading channels. Simulation tests were generated for different channels

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Publication Date
Fri May 01 2015
Journal Name
Journal Of Engineering
Cooling Load Calculations For Typical Iraqi Roof And Wall Constructions Using Ashrae's RTS Method
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The present work is an attempt to develop design data for an Iraqi roof and wall constructions using the latest ASHRAE Radiant Time Series (RTS) cooling load calculation method. The work involves calculation of cooling load theoretically by introducing the design data for Iraq, and verifies the results experimentally by field measurements. Technical specifications of Iraqi construction materials are used to derive the conduction time factors that needed in RTS method calculations. Special software published by Oklahoma state university is used to extract the conduction factors according to the technical specifications of Iraqi construction materials.  Good agreement between the average theoretical and measured cooli

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Publication Date
Thu Aug 18 2022
Journal Name
Sustainability
A Sustainable Cold Mix Asphalt Mixture Comprising Paper Sludge Ash and Cement Kiln Dust
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Concerns about the environment, the cost of energy, and safety mean that low-energy cold-mix asphalt materials are very interesting as a potential replacement for present-day hot mix asphalt. The main disadvantage of cold bituminous emulsion mixtures is their poor early life strength, meaning they require a long time to achieve mature strength. This research work aims to study the protentional utilization of waste and by-product materials as a filler in cold emulsion mixtures with mechanical properties comparable to those of traditional hot mix asphalt. Accordingly, cold mix asphalt was prepared to utilize paper sludge ash (PSA) and cement kiln dust (CKD) as a substitution for conventional mineral filler with percentages ranging fro

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Publication Date
Mon Jan 01 2024
Journal Name
Journal Of Engineering
Improving Press Bending Production Quality through Finite Element Simulation: Integration CAD and CAE Approach
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Efficient operations and output of outstanding quality distinguish superior manufacturing sectors. The manufacturing process production of bending sheet metal is a form of fabrication in the industry of manufacture in which the plate is bent using punches and dies to the angle of the work design. Product quality is influenced by plate material selection, which includes thickness, type, dimensions, and material. Because no prior research has concentrated on this methodology, this research aims to determine V-bending capacity limits utilizing the press bending method. The inquiry employed finite element analysis (FEA), along with Solidworks was the tool of choice to develop drawings of design and simulations. The ASTM E290

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Publication Date
Mon Aug 01 2022
Journal Name
Journal Of Structural Engineering
Standard Pushout Tests and Design Rules for a Bolted–Welded Hybrid Demountable Shear Connector
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A bolted–welded hybrid demountable shear connector for use in deconstructable steel–concrete composite buildings and bridges was proposed. The hybrid connector consisted of a partially threaded stud, which was welded on the flange of a steel section, and a machined steel tube with compatible geometry, which was bolted on the stud. Four standard pushout tests according to Eurocode 4 were carried out to assess the shear performance of the hybrid connector. The experimental results show that the initial stiffness, shear resistance, and slip capacity of the proposed connector were higher than those of traditional welded studs. The hybrid connector was a ductile connector, according to Eurocode 4, with slip capacity higher than 6 mm. A nonli

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Publication Date
Wed Aug 25 2021
Journal Name
Caai Transactions On Intelligence Technology
Shoulder girdle recognition using electrophysiological and low frequency anatomical contraction signals for prosthesis control
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Publication Date
Tue Apr 02 2024
Journal Name
Engineering, Technology & Applied Science Research
Two Proposed Models for Face Recognition: Achieving High Accuracy and Speed with Artificial Intelligence
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In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen

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Publication Date
Wed Feb 01 2023
Journal Name
Journal Of Ecological Engineering
Chlorpyrifos Removal from Aqueous Solutions by Emulsion Liquid Membrane – Stability, Extraction, and Stripping Studies
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Publication Date
Mon Jun 05 2023
Journal Name
Al-khwarizmi Engineering Journal
Citric Acid Production: Raw Material, Microbial Production, Fermentation Strategy and Global Market: Critical Review
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Citric acid is an essential ingredient for the manufacture of (12) key industrial chemicals. Citric acid use is increasing steadily with a high annual growth rate as a result of the development of ever more sophisticated applications. Citric acid is widely utilized in the food and pharmaceutical industries due to its low toxicity when compared to other acidulous. Other uses for citric acid can be found in cleaning supplies and detergents. Based on information from a review of the literature, Citric acid production substrates and methods for surface fermentation, submerged fermentation, solid-state fermentation, and international market expansion are all covered in the current review study. Finally, there is still much to learn about the

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Publication Date
Wed Jan 28 2026
Journal Name
F1000research
Enhancing Solar Power Forecasting Accuracy Using HMPCS and Machine Learning Techniques: An Applied Study
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Background Solar irradiance is a nonlinear and intermittent function, which makes accurate forecasting of solar power generation a challenge. The high variability of meteorological conditions is not well represented by conventional atmospheric models, thus hampering forecasting skill and model robustness. In this work, an advanced hybridization of multi-population cuckoo search (HMPCS) algorithm with machine learning (ML) methods is developed to enhance the prediction performance of photovoltaic (PV) power forecasting with more reliability. Methods In this study, a hybrid modeling framework is proposed, called HMPCS–ML framework which captures the global search capacity of HMPCS and predictive power of sophisti

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