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.
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
A Ligand (ECA) methyl 2-((1-cyano-2-ethoxy-2-oxoethyl)diazenyl)benzoate with metals of (Co2+, Ni2+, Cu2+) were prepared and characterization using H-NMR, atomic absorption spectroscopy, ultra violet (UV) visible, magnetic moments measurements, bioactivity, and Molar conductivity measurements in soluble ethanol. Complexes have been prepared using a general formula which was suggested as [M (ECA)2] Cl2, where M = (Cobalt(II), Nickel(II) and Copper(II), the geometry shape of the complexes is octahedral.
This research aims to removes dyes from waste water by adsorption using banana peels. The conduct experiment done by banana powder and banana gel to compare between them and find out which one is the most efficient in adsorption. Studying the effects different factors on adsorption material and calculate the best removal efficiency to get rid of the methylene blue dye (MB).
Feature selection (FS) constitutes a series of processes used to decide which relevant features/attributes to include and which irrelevant features to exclude for predictive modeling. It is a crucial task that aids machine learning classifiers in reducing error rates, computation time, overfitting, and improving classification accuracy. It has demonstrated its efficacy in myriads of domains, ranging from its use for text classification (TC), text mining, and image recognition. While there are many traditional FS methods, recent research efforts have been devoted to applying metaheuristic algorithms as FS techniques for the TC task. However, there are few literature reviews concerning TC. Therefore, a comprehensive overview was systematicall
... Show MoreThis article showcases the development and utilization of a side-polished fiber optic sensor that can identify altered refractive index levels within a glucose solution through the investigation of the surface Plasmon resonance (SPR) effect. The aim was to enhance efficiency by means of the placement of a 50 nm-thick layer of gold at the D-shape fiber sensing area. The detector was fabricated by utilizing a silica optical fiber (SOF), which underwent a cladding stripping process that resulted in three distinct lengths, followed by a polishing method to remove a portion of the fiber diameter and produce a cross-sectional D-shape. During experimentation with glucose solution, the side-polished fiber optic sensor revealed an adept detection
... Show More<p>Vehicular ad-hoc networks (VANET) suffer from dynamic network environment and topological instability that caused by high mobility feature and varying vehicles density. Emerging 5G mobile technologies offer new opportunities to design improved VANET architecture for future intelligent transportation system. However, current software defined networking (SDN) based handover schemes face poor handover performance in VANET environment with notable issues in connection establishment and ongoing communication sessions. These poor connectivity and inflexibility challenges appear at high vehicles speed and high data rate services. Therefore, this paper proposes a flexible handover solution for VANET networks by integrating SDN and
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