Modern statistical techniques offer a range of methodologies for modelling time series data, with conditional and unconditional approaches providing complementary insights that enhance overall model accuracy. This article introduced a modified ARIMA model employing conditional and unconditional parameter estimates. The methodology for the new model based on novel methods is provided. The prediction process, one and two steps ahead, is covered in detail, and a novel algorithm is presented. The best model is picked based on various measurement criteria, such as coefficient of determination (R2), root mean squared error (RMSE), and mean absolute scaled error (MASE). The suggested model is applied to a monthly petrol sales dataset (Jan

The current work aims to evaluate the association between genetic mutations in thymidylate synthetase (TYMS gene in exon1 and partial regions of promotor and intron 1 [877 bp, 657,220–658,096 bp]) and the therapeutic outcomes for rheumatoid arthritis (RA) Iraqi patients. An observational cross-sectional study involving 95 RA patients with established RA patients based on their methotrexate treatment responsiveness. Genetic sequencing of the TYMS gene was performed for all patients according to the instruction manuals of the sequencing company (Macrogen Inc. Geumchen, South Korea). Four polymorphisms were identified by sequencing 95 randomly selected patients in the noncoding region of TYMS

An optical spectroscopic study is reported in this article to study the correlation between the supermassive black hole (SMBH) and the star formation rate (SFR) for a sample of Seyfert galaxies type (I and II). The study focused on 45 galaxy of Seyfert 1, in addition to 45 galaxy of Seyfert 2, where these samples have been selected form different survey of Salon Digital Sky Survey (SDSS). The redshift (z) of these objects were between (0.02 – 0.26). The results of Seyfert 1 galaxies shows that there good correlation between the SMBH and the SFR depending on statistical analysis parameter named Spearman’s Rank Correlation in a factor of (ρ=0.609), as well as the Seyfert 2 galaxies results show a good correlation between the SMBH

An optical spectroscopic study is reported in this article to study the correlation between the supermassive black hole (SMBH) and the star formation rate (SFR) for a sample of Seyfert galaxies type (I and II). The study focused on 45 galaxy of Seyfert 1, in addition to 45 galaxy of Seyfert 2, where these samples have been selected form different survey of Salon Digital Sky Survey (SDSS). The redshift (z) of these objects were between (0.02 – 0.26). The results of Seyfert 1 galaxies shows that there good correlation between the SMBH and the SFR depending on statistical analysis parameter named Spearman’s Rank Correlation in a factor of (ρ=0.609), as well as the Seyfert 2 galaxies results show a good correlation between the SMBH and

Accurate pore and fracture pressure detection is a major step in successful drilling operations design. The overestimation of these parameters absolutely leads to serious problems throughout and after well drilling. This study is concerned with the characterization and analysis of the most significant diagenetic processes that degrade or improve the reservoir characteristics of the Mauddud Formation in the Badra oil field. The primary goal of this research is to estimate the pore pressure and fracture pressure using well logging data by Techlog 2015 software in order to assess the impact on the estimation of the mud weight window (MWW). The estimated values of formation pressures are then analyzed according to different diagenetic p

      The alterations in glyoxylate reductase and hydroxy-pyruvate reductase concentrations in the sera and the genetic alterations associated with calcium oxalate kidney stones in Iraqi patients were not studied previously so this study aimed to focus on these points. This study included 80 subjects; they were 50 patients with calcium oxalate stones compared to 30 apparently healthy controls. Biochemical investigations for kidney functions (creatinine, urea, and uric acid), were performed on the sera of both groups. Also, complete blood count, random blood sugar, and blood group tests. Furthermore, urine had been collected for General Urine Examination to visualize oxalate crystals in the urine of the patient. Also, the GRHPR

Odontogenic cysts and tumors often form hard and soft structures that resemble odontogenesis. It is well known that amyloid is produced in Pindborg tumors; however, it is still debatable whether it is also formed in other odontogenic tumors and cysts. This study aimed to detect the presence of amyloid in different odontogenic cysts and tumors in correlation to matrix proteins secreted during enamel formation; namely amelogenin and odontogenic ameloblast‐associated protein.

There are numerous bidirectional interactions between the reproductive system and the liver. Sex steroids regulate metabolic health through signaling effects in both peripheral and central metabolic tissues, including adipose tissue, liver, skeletal muscle, and brain, and have a role in the etiology of structural and functional liver diseases. Blood samples were obtained from 90 healthy women (control group) and 90 women that have hormonal changes (patients’ group). The levels of reproductive hormones (follicle stimulation hormone/FSH, luteinizing hormone/LH, estradiol/E2, progesterone/P4) were measured by using fully automated Cobas E411, whereas those of liver enzymes (alanine transaminase /ALT, aspartate aminotransferase/AST, a

Face recognition and identity verification are now critical components of current security and verification technology. The main objective of this review is to identify the most important deep learning techniques that have contributed to the improvement in the accuracy and reliability of facial recognition systems, as well as highlighting existing problems and potential future research areas. An extensive literature review was conducted with the assistance of leading scientific databases such as IEEE Xplore, ScienceDirect, and SpringerLink and covered studies from the period 2015 to 2024. The studies of interest were related to the application of deep neural networks, i.e., CNN, Siamese, and Transformer-based models, in face recogni