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Assessment of the Salivary level of Sphingosine kinases-1 in periodontitis and its correlation with periodontal parameters
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One of the key molecules in the conversion of sphingosine to sphingosine-1- phosphate is SPHK-1, also known as Sphingosine Kinase 1 (SPHK-1). Sphingosine-1-phosphate (S1P) is a lipid that acts as a signaling molecule and plays an essential role in inflammatory and immunomodulatory responses. S1P has recently been identified as a mediator and a biomarker in inflammatory bone diseases such as osteoporosis and inflammatory osteolysis based on the biological effects of S1P in osteoclastic and osteoblastic cells and immune cells. According to recent research, S1P may play a role in the pathogenesis of periodontitis, an inflammatory bone-destructive condition. This study assesses the salivary level SPHK-1 in periodontitis and its correlation with periodontal parameters. The study sample consisted of 65 participants, both males and females. It was divided into three groups: the first group, the Healthy Control group (15 Subjects). The second group, Periodontitis Stage II (25 Subjects), and the third group, Periodontitis Stage III (25 Subjects). Collection of whole unstimulated salivary samples from all participants was carried out, followed by an examination of clinical periodontal parameters (plaque index, probing pocket depth, bleeding on probing, and clinical attachment level). Then, radiographs confirmed the staging of periodontitis. Collected saliva was subjected to biomarker analysis using an enzymelinked immunosorbent assay (ELISA) to detect the SPHK-1 level. This study found an increase in the mean SPHK-1 level with increased severity of periodontitis with a significant difference. In addition, positive weak correlations were found between the salivary SPHK-1 and the clinical periodontal parameters (PLI, BOP, PPD, CAL). The study demonstrated that the salivary SPHK-1 level can be helpful to monitor periodontal disease progression. Keywords: Periodontitis, Saliva, Sphingosine -1 phosphate, Sphingosine kinase1.

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Publication Date
Wed Oct 26 2022
Journal Name
Petroleum Science And Technology
Building 3D geological model using non-uniform gridding for Mishrif reservoir in Garraf oilfield
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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Developing an Immune Negative Selection Algorithm for Intrusion Detection in NSL-KDD data Set
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With the development of communication technologies for mobile devices and electronic communications, and went to the world of e-government, e-commerce and e-banking. It became necessary to control these activities from exposure to intrusion or misuse and to provide protection to them, so it's important to design powerful and efficient systems-do-this-purpose. It this paper it has been used several varieties of algorithm selection passive immune algorithm selection passive with real values, algorithm selection with passive detectors with a radius fixed, algorithm selection with passive detectors, variable- sized intrusion detection network type misuse where the algorithm generates a set of detectors to distinguish the self-samples. Practica

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Publication Date
Thu Dec 01 2022
Journal Name
Advances In Cancer Biology - Metastasis
CX3CL1 as potential immunotherapeutic tool for bone metastases in lung cancer: A preclinical study
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Publication Date
Mon Dec 14 2020
Journal Name
Baghdad Science Journal
Smart Flow Steering Agent for End-to-End Delay Improvement in Software-Defined Networks
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Publication Date
Fri May 01 2015
Journal Name
Journal Of The Faculty Of Medicine
Gentamycin injection in disc space during lumbar discectomy (aiming to prevent post - operative discitis)
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AW Ali T, Journal of the Faculty of Medicine, 2015 - Cited by 3

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Publication Date
Wed Aug 10 2011
Journal Name
Ibn Al- Haitham J. For Pure & Appl. S Ci.
A Complete (k,r)-Cap in PG(3,p) Over Galois Field GF(4)
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The aim of t his p aper is t o const ruct t he (k,r)-caps in t he p rojective 3-sp ace PG(3,p ) over Galois field GF(4). We found t hat t he maximum comp let e (k,2)-cap which is called an ovaloid, exist s in PG(3,4) when k = 13. Moreover t he maximum (k,3)-cap s, (k,4)-cap s and (k,5)-caps.

Publication Date
Mon Jan 01 2018
Journal Name
Communications In Computer And Information Science
Automatically Recognizing Emotions in Text Using Prediction by Partial Matching (PPM) Text Compression Method
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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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Publication Date
Mon Jan 01 2024
Journal Name
Fifth International Conference On Applied Sciences: Icas2023
A modified Mobilenetv2 architecture for fire detection systems in open areas by deep learning
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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%.

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Publication Date
Fri Oct 31 2025
Journal Name
Mathematical Modelling Of Engineering Problems
Heterogeneous Traffic Management in SDN-Enabled Data Center Network Using Machine Learning-SPIKE Model
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Software-Defined Networking (SDN) has evolved network management by detaching the control plane from the data forwarding plane, resulting in unparalleled flexibility and efficiency in network administration. However, the heterogeneity of traffic in SDN presents issues in achieving Quality of Service (QoS) demands and efficiently managing network resources. SDN traffic flows are often divided into elephant flows (EFs) and mice flows (MFs). EFs, which are distinguished by their huge packet sizes and long durations, account for a small amount of total traffic but require disproportionate network resources, thus causing congestion and delays for smaller MFs. MFs, on the other hand, have a short lifetime and are latency-sensitive, but they accou

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Publication Date
Sun Aug 01 2021
Journal Name
Bulletin Of Electrical Engineering And Informatics
A critical success factors for software project manager in GVTs within covid-19 pandemic
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The covid-19 pandemic sweeping the world and has rendered a large proportion of the workforce as they are unable to commute to work. This has resulted in employees and employers seeking alternative work arrangements, including the software industry. Then comes the need for the global market and international presence of many companies to implement the global virtual teams (GVTs). GVTs members are gradually engaged in globalized business environments across space, time and organizational boundaries via information and communication technologies. Despite the advancement of technology, the project managers are still facing many challenges in communication. Hense, to become a successful project manager still a big challenge for them. This study

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