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Zinc modifies the effect of phyto-oestrogens on osteoblast and osteoclast differentiation in vitro
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Osteoblast and osteoclast activity is disrupted in post-menopausal osteoporosis. Thus, to fully address this imbalance, therapies should reduce bone resorption and promote bone formation. Dietary factors such as phyto-oestrogens and Zn have beneficial effects on osteoblast and osteoclast activity. However, the effect of combinations of these factors has not been widely studied. We therefore examined the effect of coumestrol, daidzein and genistein in the presence or absence of zinc sulphate (Zn) on osteoclast and osteoblast activity. Osteoclast differentiation and bone resorption were significantly reduced by coumestrol (10- 7 m), daidzein (10- 5 m) and genistein (10- 7 m); and this direct anti-osteoclastic action was unaffected by Zn (10- 5 m). In addition, Zn augmented the inhibitory effect of phyto-oestrogens on the osteoblast-derived stimulus for osteoclast formation, significantly reducing the ratio of receptor activator of NF-κB ligand (RANKL)-to-osteoprotegerin mRNA expression in human osteoblast. We then examined the effect of these compounds on osteoblast activity. Mineralisation was enhanced by coumestrol (10- 5 to 10- 7 m), daidzein (10- 5 to 10- 6 m) and genistein (10- 5 m); and Zn significantly augmented this response. Zn and phyto-oestrogens also significantly enhanced alkaline phosphatase activity and Runt-related transcription factor 2 (Runx2) mRNA expression. On the other hand, Zn blunted phyto-oestrogen-induced type I collagen and osteocalcin expression and suppressed coumestrol and daidzein-stimulated osterix expression. Zn may therefore modify the anabolic action of phyto-oestrogens, promoting characteristics associated with early rather than late stages of osteoblast differentiation. Our data suggest that while Zn enhances the anti-osteoclastic effect of phyto-oestrogens, it may limit aspects of their anabolic action on bone matrix formation.

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Publication Date
Fri Jul 05 2019
Journal Name
Digest Journal Of Nanomaterials And Biostructures
Improving sensitivity of In2O3 against NO2 toxic gas by loading tin oxide(Article)
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The paper discusses the structural and optical properties of In2O3 and In2O3-SnO2 gas sensor thin films were deposited on glass and silicon substrates and grown by irradiation of assistant microwave on seeded layer nucleated using spin coating technique. The X-ray diffraction revealed a polycrystalline nature of the cubic structure. Atomic Force Microscopy (AFM) used for morphology analysis that shown the grain size of the prepared thin film is less than 100 nm, surface roughness and root mean square for In2O3 where increased after loading SnO2, this addition is a challenge in gas sensing application. Sensitivity of In2O3 thin film against NO2 toxic gas is 35% at 300oC. Sensing properties were improved after adding Tin Oxide (SnO2) to be mo

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Publication Date
Fri Feb 26 2021
Journal Name
Life-cycle Civil Engineering: Innovation, Theory And Practice
Shear performance of a novel demountable connector for reusable steel-concrete composite structures
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A novel demountable shear connector is proposed to link a concrete slab to steel sections in a way that resulting steel-concrete composite floor is demountable, i.e. it can be easily dismantled at the end of its service life. The proposed connectors consist of two parts: the first part is a hollow steel tube with internal threads at its lower end. The second part is a compatible partially threaded bolted stud. After linking the stud to the steel section, the hollow steel tube can be fastened over the threaded stud, which create a complete demountable shear connector. The connector is suitable for use in both composite bridges and buildings, and using cast in-situ slabs, precast solid slabs, or hollow-core precast slabs. A series of push-off

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Publication Date
Wed Jun 27 2018
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Building Geological Model for Tertiary Reservoir of Exploration Ismail Oil Field, North Iraq
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Geologic modeling is the art of constructing a structural and stratigraphic model of a reservoir from analyses and interpretations of seismic data, log data, core data, etc. ‎[1].

   A static reservoir model typically involves four main stages, these stages are Structural modeling, Stratigraphic modeling, Lithological modeling and Petrophysical modeling ‎[2].

   Ismail field is exploration structure, located in the north Iraq, about 55 km north-west of Kirkuk city, to the north-west of the Bai Hassan field, the distance between the Bai Hassan field and Ismael field is about one kilometer ‎[3].

   Tertiary period reservoir sequences (Main Limestone), which comprise many economica

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Publication Date
Mon Feb 18 2019
Journal Name
Lubricants
Terahertz Time Domain Spectroscopy to Detect Different Oxidation Levels of Diesel Engine Oil
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Diesel engine oil was subjected to thermal oxidization (TO) for six periods of time (0 h, 24 h, 48 h, 72 h, 96 h, and 120 h) and was subsequently characterized by terahertz time domain spectroscopy (THz-TDS). The THz refractive index generally increased with oxidation time. The measurement method illustrated the potential of THz-TDS when a fixed setup with a single cuvette is used. A future miniaturized setup installed in an engine would be an example of a fixed setup. For the refractive index, there were highly significant differences among the oxidation times across most of the 0.3–1.7 THz range.

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Publication Date
Sat Apr 15 2023
Journal Name
Journal Of Robotics
A New Proposed Hybrid Learning Approach with Features for Extraction of Image Classification
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Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

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Publication Date
Sat Feb 19 2022
Journal Name
Intelligent Service Robotics
Dynamic performance of a series elastic actuator with variable stiffness logarithmic spiral spring
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Publication Date
Mon Feb 01 2016
Journal Name
Journal Of Economics And Administrative Sciences
Baghdad City Seasonal Forecasts Of Monthly Chronic Diseases patients Numbers Using SARIMA Models
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    One of the most important problems of IRAQI HEALTH MINISTRY and all healthy instruments in IRAQ is Chronic Diseases because it  have a negative effects on IRAQI population, this is the aim of our study ,to specify the important Chronic diseases which make the population fell weakly, they are six diseases as the IRAQ ministry of health specified (  Diabetes, blood pressure diseases ,Brain diseases ,  Cardiology, Asthma, epilepsy) we got these data from IRAQI HEALTH MINISTRY ,bureau of planning and studies ,for the period 2009-2012,as monthly observations , represent sum of peoples have chronic diseases in Baghdad .

     Our research obj

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Publication Date
Mon Dec 30 2024
Journal Name
Iraqi Journal Of Science
Study of Corrosion Inhibition for Some New Schiff Bases Synthesized from Quinazolinone Derivative
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In this work, new Schiff bases of quinazolinone derivatives (Q1-Q5) were synthesized from methyl anthranilate. The synthesis involved three steps. In the first step, methyl anthranilate was reacted with isothiocyanatobenzene, producing the thiourea derivative K1. The second step entailed reacting K1 with hydrazine hydrate, synthesizing 3-amino-2-(phenylamino) quinazolin-4(3H)-one (K2). The third step involved reaction of K2 with various aromatic aldehydes, yielding the Schiff bases derivatives Q1-Q5. The chemical structures of these compounds were identified by FT-IR,1H NMR and 13C NMR spectroscopy. The newly synthesized derivatives (Q1-Q5) were subjected to rigorous evaluation to assess their efficacy as corrosion inhibitors for ca

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Publication Date
Wed Jul 04 2018
Journal Name
Civil Engineering Journal
Finite Element Analysis of Concrete Beam under Flexural Stresses Using Meso-Scale Model
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Two dimensional meso-scale concrete modeling was used in finite element analysis of plain concrete beam subjected to bending. The plane stress 4-noded quadrilateral elements were utilized to model coarse aggregate, cement mortar. The effect of aggregate fraction distribution, and pores percent of the total area – resulting from air voids entrapped in concrete during placement on the behavior of plain concrete beam in flexural was detected. Aggregate size fractions were randomly distributed across the profile area of the beam. Extended Finite Element Method (XFEM) was employed to treat the discontinuities problems result from double phases of concrete and cracking that faced during the finite element analysis of concrete beam. Crac

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Publication Date
Fri Jan 01 2016
Journal Name
Ieee Access
Towards an Applicability of Current Network Forensics for Cloud Networks: A SWOT Analysis
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In recent years, the migration of the computational workload to computational clouds has attracted intruders to target and exploit cloud networks internally and externally. The investigation of such hazardous network attacks in the cloud network requires comprehensive network forensics methods (NFM) to identify the source of the attack. However, cloud computing lacks NFM to identify the network attacks that affect various cloud resources by disseminating through cloud networks. In this paper, the study is motivated by the need to find the applicability of current (C-NFMs) for cloud networks of the cloud computing. The applicability is evaluated based on strengths, weaknesses, opportunities, and threats (SWOT) to outlook the cloud network. T

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