Background: The repair of bone defects remains a major clinical orthopaedic challenge. Bone is a highly vascularised tissue reliant on the close spatial and temporal connection between blood vessels and bone cells to maintain skeletal integrity. Angiogenesis thus plays a pivotal role in skeletal development and bone fracture repair. The role of angiogenic and osteogenic factors in the adaptive response and interaction of osteoblasts and endothelial cells during the multi step process of bone development and repair will be highlighted in this study. This study aimed to identify the role of local exogenous vascular endothelial growth factor in bone healing and to analyze the expression of VEGF by immunohistochemistry in created bone defect after application with different biomaterials in a rat model. Materials and methods: In this experimental study eighteen male Albino rats, weighing (300-400) gram, aged (6-8) months were used and maintained under control conditions of temperature, drinking and food consumption. The animals were subjected for a surgical operation of medial sides of both tibiae bone ( right side was considered as experimental site ,while left be the control one), in control group the bone defect treated with local application of 1µm of normal saline, while experimental treated with local application of 1µm of VEGF .The rats were sacrificed at 3,7,10 days after surgery(six rats for each period). Bone healing was histologically examined with immunohistochemical localization of VEGF Results: Bone defect treated with local application of VEGF shows an early osteoid tissue deposition with high cell count for osteoblast, osteocyte and osteoclast. Immunohistochemical evaluation for VEGF by stromal cells, reported to be higher with significant difference in VEGF group in comparison to control. Conclusion: The study illustrated that low application of VEGF could be an effective therapeutic expression for bone injuries; these data are promising for a possible future clinical usage.
This research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.
The current research is interested in the objective study of revitalizing the religious sites and the extent to which they achieve the pragmatic and semantic ends, because they are derived from history and civilization and have a clear impact over the recipient. The research question is (what are the techniques of developing the spaces of the religious shrines in accordance with revitalizing the interior spaces within them?).
The research aims at determining the weak and strong points in the process of revitalizing the interior spaces in the religious shrines.
The theoretical framework consists of two parts: the first addressed the revitalization in the interior design, and the second addressed the religious shrines and th
Objectives: To assess pregnant women’s knowledge regarding syphilisand to find out the relationship between women’s knowledge regarding syphilis infection and demographic and reproductive variables. Methodology: A descriptive analytical study of non probable (purposive sample) of 250 pregnant women during their different gestational ages for the period (October 2nd to April 25th 2013) by using questionnaire format consists of demographic variables and items of women's knowledge regarding syphilis who are visiting primary health care centers in Al-Kharkh and Al-Rrusafa in Baghdad city. The coefficient relia
The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre
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In this paper, we investigate the automatic recognition of emotion in text. We perform experiments with a new method of classification based on the PPM character-based text compression scheme. These experiments involve both coarse-grained classification (whether a text is emotional or not) and also fine-grained classification such as recognising Ekman’s six basic emotions (Anger, Disgust, Fear, Happiness, Sadness, Surprise). Experimental results with three datasets show that the new method significantly outperforms the traditional word-based text classification methods. The results show that the PPM compression based classification method is able to distinguish between emotional and nonemotional text with high accuracy, between texts invo
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Background: Client satisfaction with the immunization service is used to evaluate the quality of the admitted service and at the same time it affects the goodness of the health care outcome.
Objectives: This study assessed the satisfaction with immunization services offered to children and factors affecting this satisfaction.
Methods: Exit interviews for clients were conducted in Baghdad, Al-Karkh in a representative sample of primary health care centers to assess clients’ satisfaction with immunization services. Clients are companions of children encountered at study settings.
Results: Among the 253 respondent clients, 183 (72.3%) reflected satisfaction with the immunization
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E-Learning packages are content and instructional methods delivered on a computer
(whether on the Internet, or an intranet), and designed to build knowledge and skills related to
individual or organizational goals. This definition addresses: The what: Training delivered
in digital form. The how: By content and instructional methods, to help learn the content.
The why: Improve organizational performance by building job-relevant knowledge and
skills in workers.
This paper has been designed and implemented a learning package for Prolog Programming
Language. This is done by using Visual Basic.Net programming language 2010 in
conjunction with the Microsoft Office Access 2007. Also this package introduces several
fac