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Neutrophil / Lymphocyte Ratio is not Correlated with Disease Activity in Rheumatoid Arthritis Patients
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Rheumatoid arthritis is a chronic systemic inflammatory disease. Inflammation leads to joint damage and increases the risk of cardiovascular diseases. Neutrophil lymphocyte ratio (NLR) is a measure of inflammation in many diseases. Therefore, we aimed to evaluate the usefulness of NLR to detect inflammation in RA, and its correlation to RA disease activity indices and some hematological parameters. A cross-sectional study involving 24 patients with active rheumatoid arthritis (RA) who are using MTX participated in this study. All patients were clinically evaluated using disease activity score of 28 joints (DAS28) and simplified disease activity index (SDAI), whereas functional disability was assessed by health assessment questionnaire disability index (HAQDI); Moreover, blood specimen of each patient was used for measuring erythrocyte sedimentation rate (ESR), C – reactive protein (CRP), rheumatoid factor (RF), hemoglobin (Hb), white blood cells (WBC) count, platelets and red blood cells (RBCs) count, and NLR ratio.NLR was positively correlated with ESR and inversely correlated with Hb, but it didn’t show any correlation with other clinical and laboratory parameters. In conclusion NLR is less correlated with inflammation and not suitable to monitor disease activity in RA patients using MTX.

Keywords: Rheumatoid arthritis, Inflammation, Neutrophil lymphocyte ratio.

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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
Forecasting Cryptocurrency Market Trends with Machine Learning and Deep Learning
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Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The

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Publication Date
Fri Jan 01 2021
Journal Name
Egyptian Journal Of Chemistry
Microstructure and Dielectric Properties of Polyaniline Doped with Copper Nanoparticles
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Polyaniline (PANI) has been prepared by the oxidation method in order to fabricate it with various concentrations of copper nanoparticles (CuNPs) which produced using the reduction method. Various techniques have characterized pure PANI and PANI doped CuNPs composites, such as fourier transform infrared spectroscopy (FT-IR), X-ray diffraction spectroscopy (XRD), field emission scanning electron microscopy (FE-SEM) and energy dispersive X-ray spectroscopy (EDS), which were provided important information about the structure and morphology of the fabricated polymer nanocomposites. The properties of dielectric permittivity (έ), dielectric loss (ἔ) and electrical conductivity (σ_AC) properties were studied at room temperature versus a range

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Publication Date
Mon Dec 07 2020
Journal Name
Egyptian Journal Of Chemistry
Microstructure and Dielectric Properties of Polyaniline Doped with Copper Nanoparticles
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Publication Date
Mon Dec 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Comparison between some of linear classification models with practical application
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Linear discriminant analysis and logistic regression are the most widely used in multivariate statistical methods for analysis of data with categorical outcome variables .Both of them are appropriate for the development of linear  classification models .linear discriminant analysis has been that the data of explanatory variables must be distributed multivariate normal distribution. While logistic regression no assumptions on the distribution of the explanatory data. Hence ,It is assumed that logistic regression is the more flexible and more robust method in case of violations of these assumptions.

In this paper we have been focus for the comparison between three forms for classification data belongs

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Publication Date
Thu Sep 01 2022
Journal Name
Iraqi Journal Of Physics
Electrical Properties of PAN/PMMA Blends Doped with Lithium Salts
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         Polymer blended electrolytes of various concentrations of undoped PAN/PMMA (80/20, 75/25, 70/30, 65/35 and 60/40 wt%) and doped with lithium salts (LiCl, Li2SO4H2O, LiNO3, Li2CO3) at 20% wt have been prepared by the solution casting method using dimethylformamide as a solvent. The electrical conductivity has been carried out using an LCR meter. The results showed that the highest ionic conductivity was 2.80x10-7 (Ω.cm)-1 and 1.05x10-1 (Ω.cm)-1 at 100 kHz frequency at room temperature for undoped (60% PAN + 40% PMMA) and (80% PAN + 20% PMMA) doped with 20%wt Li2CO3 composite blends, respect

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Publication Date
Sun Feb 25 2024
Journal Name
Baghdad Science Journal
Qin Seal Script Character Recognition with Fuzzy and Incomplete Information
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The dependable and efficient identification of Qin seal script characters is pivotal in the discovery, preservation, and inheritance of the distinctive cultural values embodied by these artifacts. This paper uses image histograms of oriented gradients (HOG) features and an SVM model to discuss a character recognition model for identifying partial and blurred Qin seal script characters. The model achieves accurate recognition on a small, imbalanced dataset. Firstly, a dataset of Qin seal script image samples is established, and Gaussian filtering is employed to remove image noise. Subsequently, the gamma transformation algorithm adjusts the image brightness and enhances the contrast between font structures and image backgrounds. After a s

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Publication Date
Tue Dec 01 2015
Journal Name
Chemical Engineering Science
Airlift bioreactor for biological applications with microbubble mediated transport processes
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Publication Date
Sat Dec 24 2022
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Characterization of Alginate with Natural Polymers Combination for Drug Encapsulation
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Alginate is one of the natural biopolymers that is widely used for drug formulations, combination of alginate with other polymers, such as gum acacia, pectin, and carrageenan can increase mechanical strength, therefore, can reduce leakage of the encapsulated active pharmaceutical ingredient from the polymer matrix. Interaction of alginate and these polymers can occur via intermolecular hydrogen bonds causing synergism, which is determined from the viscosity of polymer mixture.

Alginate was combined with gum acacia/pectin/carrageenan in different blending ratios (100:0, 75:25, 50:50, 25:75, and 0:100) with and without addition of CaCl2. The synergism effect is obtained from the design of experimental (DoE), and calculati

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Publication Date
Mon Jan 01 2024
Journal Name
Nonlinear Functional Analysis And Applications
NEW SEVEN-PARAMETER MITTAG-LEFFLER FUNCTION WITH CERTAIN ANALYTIC PROPERTIES
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In this paper, a new seven-parameter Mittag-Leffler function of a single com-plex variable is proposed as a generalization of the standard Mittag-Leffler function, certain generalizations of Mittag-Leffler function, hypergeometric function and confluent hypergeometric function. Certain essential analytic properties are mainly discussed, such as radius of convergence, order, type, differentiation, Mellin-Barnes integral representation and Euler transform in the complex plane. Its relation to Fox-Wright function and H-function is also developed.

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Publication Date
Tue Jun 01 2021
Journal Name
2021 Ieee/cvf Conference On Computer Vision And Pattern Recognition Workshops (cvprw)
Alps: Adaptive Quantization of Deep Neural Networks with GeneraLized PositS
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