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Preclinical Oral Histology Research: A Retrospective Review Study
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A retrospective study is conducted to identify factors that improve prospective animal studies; contribute to the optimization of animal protection from all unnecessary and preventable damage. Preclinical oral histology research from 2010-2020 is evaluated and 64 studies were reviewed relating to two interventions: bone trauma and surgical incision. The harm-benefit analysis is featured in this study through the application of the recent form of Bateson's Cube. Depending on its three axes, we can assess animal suffering, the likelihood of benefit, and the importance of research. The total number of animals used in the research is 2685. Rats, 51.6%, and rabbits, 48.4%, are the most commonly used animals. Research related to bone healing accounts for about 65.6%, while research related to wound healing 34.4%. The expert panel's estimate of animal suffering revealed that 57.8% had moderate animal suffering; 39.1% had mild suffering, and only 3.1% had severe suffering. Results revealed that hard tissue studies get more citations, 77.88% more than soft tissue-related research. However, the soft tissue studies show more concordance between preclinical and clinical studies. Continual efforts should be made to assure that when animals are involved in research, each study is well-designed, well-analyzed, and clearly published.

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Publication Date
Mon Jan 01 2024
Journal Name
Baghdad Science Journal
Semi-Analytical Assessment of Magneto-Hydrodynamic Nano-Fluid Flow Jeffrey- Hamel Problem
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In this paper, analyzing the non-dimensional Magnesium-hydrodynamics problem Using nanoparticles in Jeffrey-Hamel flow (JHF) has been studied. The fundamental equations for this issue are reduced to a three-order ordinary differential equation. The current project investigated the effect of the angles between the plates, Reynolds number, nanoparticles volume fraction parameter, and magnetic number on the velocity distribution by using analytical technique known as a perturbation iteration scheme (PIS). The effect of these parameters is similar in the converging and diverging channels except magnetic number that it is different in the divergent channel. Furthermore, the resulting solutions with good convergence and high accuracy for the d

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Publication Date
Mon Dec 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
USING SENSITIVITY ANALYSIS IN DETERMINING THE OPTIMAL&EFFICIENT PRODUCTION PLANS IN GREENHOUSES IN ASSOCIATION OF AL-WATAN UNDER CONDITION OF RISK &UNCERTAINTY
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 The objectives of this research are to determine and find out the reality of crops structure of greenhouses in association of Al-Watan  in order to stand on the optimal use of economic resources available for the purpose of reaching a crop structure optimization of the farm that achieves maximize profit and gross and net farm incomes , using the method of linear programming to choose the farm optimal plan with the highest net income , as well as identifying production plans farm efficient with (income - deviation) optimal (E-A) of the Association and derived, which takes into account the margin risk wich derived from each plan using the model( MOTAD), as a model of models of linear programming alternative programming m

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Publication Date
Fri Jan 01 2021
Journal Name
Journal Of Economics And Administrative Sciences
identifying the reasons of electronic smoking spreading (VAPING) in the society with practical application using Analytical Factors
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We have investigated in this research, the contents of the electronic cigarette (Viber) and the emergence of the phenomenon of electronic smoking (vibing) were discussed, although the topic of smoking is one of the oldest topics on which many articles and research have been conducted, electronic smoking has not been studied according to statistical scientific research, we tried in this research to identify the concept of electronic smoking to sample the studied data and to deal with it in a scientific way. This research included conducting a statistical analysis using the factor analysis of a sample taken randomly from some colleges in Bab Al-medium in Baghdad with a size of (70) views where  (КМО) and a (bartlett) tests

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Publication Date
Sun Dec 01 2024
Journal Name
Journal Of The Iraqi Translators Association Translation And Linguistics
COMPARISON OF THE IDEOLOGICAL DISCOURSE OF THE RUSSIAN-UKRAINIAN WAR IN REPORTS FROM NEWS CHANNELS CNN AND RT
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This study conducts a systematic comparative critical discourse analysis of news reports from prominent American (CNN) and Russian (RT) media sources covering the Russia-Ukraine conflict. Utilizing the theoretical frameworks of Norman Fairclough's multidimensional model and Teun van Dijk's socio-cognitive approach, the research examines the underlying ideological assumptions and discursive strategies employed by the two contrasting news channels. Quantitative analysis of discursive techniques and linguistic features provides insights into how each channel selectively utilizes language to convey distinct ideological positions. The findings demonstrate how media discourse constructs and normalizes particular ideological representations of pol

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Publication Date
Tue Nov 01 2022
Journal Name
2022 International Conference On Data Science And Intelligent Computing (icdsic)
An improved Bi-LSTM performance using Dt-WE for implicit aspect extraction
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In aspect-based sentiment analysis ABSA, implicit aspects extraction is a fine-grained task aim for extracting the hidden aspect in the in-context meaning of the online reviews. Previous methods have shown that handcrafted rules interpolated in neural network architecture are a promising method for this task. In this work, we reduced the needs for the crafted rules that wastefully must be articulated for the new training domains or text data, instead proposing a new architecture relied on the multi-label neural learning. The key idea is to attain the semantic regularities of the explicit and implicit aspects using vectors of word embeddings and interpolate that as a front layer in the Bidirectional Long Short-Term Memory Bi-LSTM. First, we

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Publication Date
Wed Aug 17 2022
Journal Name
Aip Conference Proceedings
The effect of using Gaussian, Kurtosis and LogCosh as kernels in ICA on the satellite classification accuracy
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This study focusses on the effect of using ICA transform on the classification accuracy of satellite images using the maximum likelihood classifier. The study area represents an agricultural area north of the capital Baghdad - Iraq, as it was captured by the Landsat 8 satellite on 12 January 2021, where the bands of the OLI sensor were used. A field visit was made to a variety of classes that represent the landcover of the study area and the geographical location of these classes was recorded. Gaussian, Kurtosis, and LogCosh kernels were used to perform the ICA transform of the OLI Landsat 8 image. Different training sets were made for each of the ICA and Landsat 8 images separately that used in the classification phase, and used to calcula

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Publication Date
Sun Apr 01 2018
Journal Name
Construction And Building Materials
Linear viscous approach to predict rut depth in asphalt mixtures
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Rutting in asphalt mixtures is a very common type of distress. It occurs due to the heavy load applied and slow movement of traffic. Rutting needs to be predicted to avoid major deformation to the pavement. A simple linear viscous method is used in this paper to predict the rutting in asphalt mixtures by using a multi-layer linear computer programme (BISAR). The material properties were derived from the Repeated Load Axial Test (RLAT) and represented by a strain-dependent axial viscosity. The axial viscosity was used in an incremental multi-layer linear viscous analysis to calculate the deformation rate during each increment, and therefore the overall development of rutting. The method has been applied for six mixtures and at different tem

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Publication Date
Thu Feb 01 2024
Journal Name
Journal Of Engineering
Predicting Biochemical Oxygen Demand at the Inlet of Al-Rustumiya Wastewater Treatment Plant Using Different Mathematical Techniques
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Water quality planning relies on Biochemical Oxygen Demand BOD. BOD testing takes five days. The Particle Swarm Optimization (PSO) is increasingly used for water resource forecasting. This work designed a PSO technique for estimating everyday BOD at Al-Rustumiya wastewater treatment facility inlet. Al-Rustumiya wastewater treatment plant provided 702 plant-scale data sets during 2012-2022. The PSO model uses the daily data of the water quality parameters, including chemical oxygen demand (COD), chloride (Cl-), suspended solid (SS), total dissolved solids (TDS), and pH, to determine how each variable affects the daily incoming BOD. PSO and multiple linear regression (MLR) findings are compared, and their perfor

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Publication Date
Mon Jun 05 2023
Journal Name
Journal Of Engineering
Simulation and Modeling of Detailed Load flow Analysis for the 400kVA and 132kVA Iraqi Grid
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A load flow program is developed using MATLAB and based on the Newton–Raphson method,which shows very fast and efficient rate of convergence as well as computationally the proposed method is very efficient and it requires less computer memory through the use of sparsing method and other methods in programming to accelerate the run speed to be near the real time.
The designed program computes the voltage magnitudes and phase angles at each bus of the network under steady–state operating conditions. It also computes the power flow and power losses for all equipment, including transformers and transmission lines taking into consideration the effects of off–nominal, tap and phase shift transformers, generators, shunt capacitors, sh

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Publication Date
Mon Sep 16 2024
Journal Name
Plant Protection
In vitro investigation of phytochemical, antioxidant and antimicrobial activities of Harpagophytum procumbens seeds extracts
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Medicinal plants contain bioactive substances that are highly bioavailable in extracts or pure molecules, making them promising for therapeutic applications and precursors for chemo-pharmaceutical semi-synthesis. Harpagophytum procumbens (Devil’s Claw) is widely recognized as one of the most potent therapeutic herbs. This study aimed to extract seeds from H. procumbens using two types of solvents and to assess both qualitative and quantitative aspects of the extracts. The two extracts were evaluated for antibacterial and anti-biofilm activities using agar well diffusion assays against four bacterial isolates and two yeast isolates. Qualitative analysis identified the presence of alkaloids, flavonoids, tannins, saponins, and terpen

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