Numerous blood biomarkers are altered in COVID-19 patients; however, no early biochemical markers are currently being used in clinical practice to predict COVID-19 severity. COVID-19, the most recent pandemic, is caused by the SRS-CoV-2 coronavirus.  The study was aimed to identify patient groups with a high and low risk of developing COVID-19 using a cluster analysis of several biomarkers. 137 women with confirmed SARS CoV-2 RNA testing were collected and analyzed for biochemical profiles. Two-dimensional automated hierarchy clustering of all biomarkers was applied, and patients were sorted into classes. Biochemistry marker variations (Ferritin, lactate dehydrogenase LDH, D-dimer, and C- reactive protein CRP) have split COVID-19 patien

Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

Second language learner may commit many mistakes in the process of second language learning. Throughout the Error Analysis Theory, the present study discusses the problems faced by second language learners whose Kurdish is their native language. At the very stages of language learning, second language learners will recognize the errors committed, yet they would not identify the type, the stage and error type shift in the process of language learning. Depending on their educational background of English as basic module, English department students at the university stage would make phonological, morphological, syntactic, semantic and lexical as well as speech errors. The main cause behind such errors goes back to the cultural differences

 This paper adapted the neural network for the estimating of the direction of arrival (DOA). It uses an unsupervised adaptive neural network with GHA algorithm to extract the principal components that in turn, are used by Capon method to estimate the DOA, where by the PCA neural network we take signal subspace only and use it in Capon (i.e. we will ignore the noise subspace, and take the signal subspace only).

ABSTRACT this paper extends the literature on the elements and effect of financial literacy by investigating the elements of financial literacy and the impact of financial literacy on financial inclusion and savings. This research confirms the results of researches of other economies but exposes some dissimilarities as well. The principal factors of financial literacy are discovered to be government efficiency, educational level, income, economic performance and infrastructure. Both education levels and financial literacy are found to be meaningfully and positively linked to financial inclusion and savings in G20 economies

This document provides an examination of research, on combining orthogonal frequency division multiplexing (OFDM) and optical fibers in communication networks. With the increasing need for data speeds and efficient use of bandwidth experts have been exploring the connection between OFDM, valued for its ability to handle multipath interference and optimize spectral usage and optical fiber technology which provides superior data transmission capabilities with low signal loss and strong protection, against electromagnetic disturbances. The review summarizes discoveries from studies examining the pros and cons of using OFDM, in optical communication networks. It discusses obstacles like fiber nonlinearity, chromatic dispersion and the effects o

Two Schiff bases, namely, 3-(benzylidene amino) -2-thioxo-6-methyl 2,5-dihydropyrimidine-4(3H)-one (LS])and 3-(benzylidene amino)-6-methyl pyrimidine 4(3H, 5H)-dione(LA)as chelating ligands), were used to prepare some complexes of Cr(III), La(III), and Ce(III)] ions. Standard physico-chemical procedures including metal analysis M%, element microanalysis (C.H.N.S) , magnetic susceptibility, conductometric measurements, FT-IR and UV-visible Spectra were used to identify Metal (III) complexes and  Schiff bases (LS) and (LA). According to findings, a [Cr(III) complex] showed six coordinated octahedral geometry, while [La(III), and Ce(III) complexes]were structured with coordination number seven.  Schiff's bases a

The mucilage was isolated from mustard seeds and identification by some different methods like, thermo gravimetric, FTlR., X-ray powdered, proton NMR, FTIR spectra of the three gums contain different functional group in the gums, major peaks  bands noticed were belong to OH (3410.15 – 3010.88) group from hydroxyl group, CH aliphatic (2925-2343.51), C-O (1072.42-1060.85) group and C=O 1743.65, Thermo chemical parameters of mucilage was evaluated  and compared with the standard gums, Results indicated the mucilage was decomposed in 392°C and mass loss 55%, The X ray process found the mucilage had single not sharp peak

This paper explores the feminist voices in Monica Ali’s novel Brick Lane, focusing on the character development of Nazneen as she evolves from a compliant, dependent wife into a self-reliant, empowered individual. The analysis highlights how Nazneen’s journey toward financial independence through her sewing work plays a critical role in her personal transformation. The paper also examines the impact of female support networks on her empowerment, alongside the cultural obstacles she encounters as an immigrant woman living in London. Using feminist theory, this study discusses the complex interplay between culture, gender, and identity, emphasizing the multifaceted nature of women’s empowerment in a diverse cultural setting. Brick Lane

The fetal heart rate (FHR) signal processing based on Artificial Neural Networks (ANN),Fuzzy Logic (FL) and frequency domain Discrete Wavelet Transform(DWT) were analysis in order to perform automatic analysis using personal computers. Cardiotocography (CTG) is a primary biophysical method of fetal monitoring. The assessment of the printed CTG traces was based on the visual analysis of patterns that describing the variability of fetal heart rate signal. Fetal heart rate data of pregnant women with pregnancy between 38 and 40 weeks of gestation were studied. The first stage in the system was to convert the cardiotocograghy (CTG) tracing in to digital series so that the system can be analyzed ,while the second stage ,the FHR time series was t