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The Value of Ultrasonography in The Diagnosis and Evaluation of Early Therapeutic Response of Cervical Tuberculous Lymphadenitis
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ABSTRACT Background: Tuberculosis is a worldwide infectious disease in spite of advancement in health care system. Tuberculous lymphadenitis is the most prevalent form of extra pulmonary tuberculosis with predilection of cervical lymph nodes. Objectives: To evaluate the reliability of grey scale ultrasonography together with color Doppler in the diagnosis of cervical tuberculous lymph adenitis and evaluation of early therapeutic response. Subjects and methods:From July 2015 to May 2016 in Al-Karama teaching hospital /Kut city- Wasit-Iraq, 25 patients (14 males and 11 females) with ages range from (6-50) years. Ultrasonography examination was done for all patients and grey scale criteria (distribution, size, shape, echogenicity, echogenic hilum, intranodal necrosis and ancillary features) and vascular distribution were recorded to help in tuberculous lymphadenitis diagnosis. Excisional biopsy was done to confirm the diagnosis histopathologically. After chemotherapy the Patients were followed up after 46 days of treatment, again the grey scale criteria were recorded and compared with the 1st reading. Results: Ultrasonography could identify 88% of the patients (22/25) as having cervical tuberculous lymphadenitis while histopathology proved that only 80% of patients really have the disease. This mean that ultrasonography had good sensitivity (100%), specificity (60%) and accuracy (90%) with no false negative and 8% false positive.In following up the patients, grey scale ultrasonography criteria showed a significant difference for the same patients before and after 46 days of treatment. Conclusions: Ultrasonography was found to play a paramount role in detection, localization and delineation of cervical tuberculous lymph nodes hence grey scale and color Doppler are reliable in diagnosis of the disease and the evaluation of therapeutic response of the patients.

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Publication Date
Mon Jun 30 2025
Journal Name
Modern Sport
Visual Tracking and its Relationship to Dynamic Visual Acuity Among National Youth Foil Fencing Team Athletes
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Publication Date
Sun Aug 01 2021
Journal Name
Journal Of Physics: Conference Series
EEG Motor-Imagery BCI System Based on Maximum Overlap Discrete Wavelet Transform (MODWT) and cubic SVM
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Abstract<p>Communication of the human brain with the surroundings became reality by using Brain- Computer Interface (BCI) based mechanism. Electroencephalography (EEG) being the non-invasive method has become popular for interaction with the brain. Traditionally, the devices were used for clinical applications to detect various brain diseases but with the advancement in technologies, companies like Emotiv, NeuoSky are coming up with low cost, easily portable EEG based consumer graded devices that can be used in various application domains like gaming, education etc as these devices are comfortable to wear also. This paper reviews the fields where the EEG has shown its impact and the way it has p</p> ... Show More
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Publication Date
Mon Mar 11 2019
Journal Name
Baghdad Science Journal
Developing Load Balancing for IoT - Cloud Computing Based on Advanced Firefly and Weighted Round Robin Algorithms
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The evolution of the Internet of things (IoT) led to connect billions of heterogeneous physical devices together to improve the quality of human life by collecting data from their environment. However, there is a need to store huge data in big storage and high computational capabilities.   Cloud computing can be used to store big data.  The data of IoT devices is transferred using two types of protocols: Message Queuing Telemetry Transport (MQTT) and Hypertext Transfer Protocol (HTTP). This paper aims to make a high performance and more reliable system through efficient use of resources. Thus, load balancing in cloud computing is used to dynamically distribute the workload across nodes to avoid overloading any individual r

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Publication Date
Sun May 01 2022
Journal Name
Optical Fiber Technology
Optical fiber sensor network integrating SAC-OCDMA and cladding modified optical fiber sensors coated with nanomaterial
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Publication Date
Fri Jun 29 2018
Journal Name
Journal Of Engineering
Improving Water Use Efficiency and Water Productivity for Okra Crop by using Subsurface Water Retention Technology
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Utilizing the modern technologies in agriculture such as subsurface water retention techniques were developed to improve water storage capacities in the root zone depth. Moreover, this technique was maximizing the reduction in irrigation losses and increasing the water use efficiency. In this paper, a polyethylene membrane was installed within the root zone of okra crop through the spring growing season 2017 inside the greenhouse to improve water use efficiency and water productivity of okra crop. The research work was conducted in the field located in the north of Babylon Governorate in Sadat Al Hindiya Township seventy-eight kilometers from Baghdad city. Three treatments plots were used for the comparison using surface

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Publication Date
Wed Mar 01 2023
Journal Name
Al-khwarizmi Engineering Journal
A Methodology for Evaluating and Scheduling Preventive Maintenance for a Thermo-Electric Unit Using Artificial Intelligence
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Flow-production systems whose pieces are connected in a row may not have maintenance scheduling procedures fixed because problems occur at different times (electricity plants, cement plants, water desalination plants). Contemporary software and artificial intelligence (AI) technologies are used to fulfill the research objectives by developing a predictive maintenance program. The data of the fifth thermal unit of the power station for the electricity of Al Dora/Baghdad are used in this study. Three stages of research were conducted. First, missing data without temporal sequences were processed. The data were filled using time series hour after hour and the times were filled as system working hours, making the volume of the data relativel

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Publication Date
Fri Oct 20 2023
Journal Name
Bmc Endocrine Disorders
Dietary caffeine intake is associated with favorable metabolic profile among apparently healthy overweight and obese individuals
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Abstract<sec> <title>Background

Recent studies have revealed some conflicting results about the health effects of caffeine. These studies are inconsistent in terms of design and population and source of consumed caffeine. In the current study, we aimed to evaluate the possible health effects of dietary caffeine intake among overweight and obese individuals.

Methods

In this cross-sectional study, 488 apparently healthy individuals with overweight and obesity were participated. Dietary intake was assessed by a Food Frequency Questionnaire (FFQ) and

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Publication Date
Wed Apr 01 2020
Journal Name
Medico-legal Update
Knowledge and protective health behaviors concerning risk factors for coronary heart disease among baghdad university students
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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Physics
Producing Hydrogen Energy Using Cr2O3-TNFs Nanocomposite with Animal (Chitosan) Extract via Ultrasonic and Hydrothermal Techniques
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In this study, an efficient photocatalyst for dissociation of water was prepared and studied. The chromium oxide (Cr2O3) with Titanium dioxide (TiO2) nanofibers (Cr2O3-TNFs) nanocomposite with (chitosan extract) were synthesized using ecologically friendly methods such as ultrasonic and hydrothermal techniques; such TiO2 exhibits nanofibers (TNFs) shape struct

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Publication Date
Fri Apr 14 2023
Journal Name
Journal Of Big Data
A survey on deep learning tools dealing with data scarcity: definitions, challenges, solutions, tips, and applications
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Abstract<p>Data scarcity is a major challenge when training deep learning (DL) models. DL demands a large amount of data to achieve exceptional performance. Unfortunately, many applications have small or inadequate data to train DL frameworks. Usually, manual labeling is needed to provide labeled data, which typically involves human annotators with a vast background of knowledge. This annotation process is costly, time-consuming, and error-prone. Usually, every DL framework is fed by a significant amount of labeled data to automatically learn representations. Ultimately, a larger amount of data would generate a better DL model and its performance is also application dependent. This issue is the main barrier for</p> ... Show More
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