Al-Nahrain Journal of Science
type: channel
description: Al-Nahrain Journal of Science (ANJS), Republic of Iraq, is a scientific journal published quarterly by the College of Science, Al-Nahrain University in Baghdad. Four issues are published annually in March, June, September, and December. Original research articles are welcomed and considered for publication in ANJS based on a double-blind peer-review process. ANJS has international standard serial numbers (ISSNs) for both electronic (e-ISSN:2663-5461) and printed versions (ISSN: 2663-5453) and each article shall have a digital object identifier (DOI) number once it is accepted for publication. ANJS is also an open access journal which means that publications are available electronically on the journal’s website. The author(s) (or the copyright owner of the work submitted) signs an author publishing agreement in which the contributing authors retain copyright and give the publisher of the Al-Nahrain Journal of science the right to publish the work submitted in its final format after the completion of the review process. The agreement includes the Creative Commons license which will indicate what others can do with the article once it is published. The authors cannot publish their articles in other journals. ANJS is not financially supported by any governmental or non-governmental organization, and it is solely supported by the author's fees. Publication charges apply for all articles submitted to ANJS. Researchers from around the world are welcome to submit their work to ANJS.
publisher: College of Science, Al-Nahrain University
language: en
publication name: Al-Nahrain Journal of Science
issn: 2663-5453
items: Image Fusion for Brain Tumor Diagnosis Using Fractal Weighted Adaptive Dual Channel Neural Network
items: Retention and Selectivity of the Nalidixic Acid and Enoxacin by Hydrophilic Interaction Liquid Chromatography on Various Polar Columns with Different Chain Lengths
items: Impact of Antenatal Steroid Treatment on External Morphological Feature of Newly Born Rats
items: Explainable Machine Learning Models for Mortality Risk Prediction of Crimean-Congo Hemorrhagic Fever in Iraq
items: Study of the Efficiency of the Magnetic Deflector at Various Operation Conditions
items: Syntheses, Characterization, DFT and Molecular Docking of N-(4-chlorophenyl)-1-(4-nitrophenyl) methanimine, (4-chlorophenyl)-1-(4-methoxyphenyl) methanimine and its derivatives
items: Testing Different Models for the Rotation Curve of the Milky Way Using BURT Observations
items: Dispersion Parameters and Electrical Characterization of Cd₁₋ₓCuₓS Thin Films Deposited by Using AACVD Technique
items: Photo-Thermal Conversion of Selective Coatings with Iron and Chromium Powder Additives
items: Ion-Pair Based Dispersive Liquid-Liquid Microextraction for Spectrophotometric Analysis of Carmoisine in Food: A BAGI and AGREE Study
items: CXCL12, CA15-3, and Liver function Tests as Predictors of Liver Metastasis in Breast Cancer
items: AI Based Cognitive and Software Defined Network for Dynamic Management and Security in 6G Networks
items: Methods for Finding Gelfand Pairs in Finite Groups with an Emphasis on Symmetry
items: Some Methods to Estimate the Parameters of IDAL-Distribution (b)
items: Image Augmentation for Passionfruit Disease Classification Using Conditional Generative Adversarial Networks (cGANs)
items: The Length-Biased Wieghted Kpendidum Distribution: Properties and some Real-Life Applications
items: Biochemical changes of alkaline phosphatase in tissue homogenate of the developing femurs in chick embryos after in ovo calcium carbonate nanoparticles inoculation
items: Immunoregulatory Role of miRNA-26 in Modulating IL-32, IL-33, IL-34, and MMP-9 Expression in Rheumatoid Arthritis
items: Comparative Study on Electron Beam Characteristics of a Thermionic Electron Gun for Different Shapes of Wehnelt Cup
items: Evaluation of Forensic Efficiency Parameters of 19 Autosomal STR Markers in a Population Sample of Arabs Residing in Voronezh, Russia
items: Deep Image Segmentation Using Explainable Attention Mechanisms: Applications in Biomedical Imaging
items: Cytotoxic Activity of Secondary Metabioltic Agent Produce by Actinomycetes
items: Extended Inverse Lomax Distribution with Simulation and Application to Crude Birth Rate Data
items: Charge Carrier Mechanism in CdTe/ZnTe Core/Shell Nanocrystals for Photoelectrodes by Laser Ablation Method
items: Quantum Chemical Insights into the Electronic, Vibrational and Thermodynamic Properties of Chloro-Substituted Anisole
items: The Effectiveness of Aspergillus fumigatus and A. niger in Biodegrading Petroleum Derivatives in Contaminated Water
items: Phytochemical and Antibacterial Evaluation of Pterygota Alata Leaf Extracts Against CSOM Bacteria
items: Evaluation of Generating DNA Profile from Keratinous Tissues
items: ARIMA-NN Model for Drugs Sales Forecasting in the United States
items: Study of Charge Density Distributions, Elastic and Inelastic Electron Scattering Form Factors and Size Radii for 24Mg and 28Si Nuclei

Image Fusion for Brain Tumor Diagnosis Using Fractal Weighted Adaptive Dual Channel Neural Network
type: item
description: This research paper proposes a novel image fusion algorithm for assisting effective diagnosis of brain cancers. The method extracts detailed features from source images using a multi-level decomposition strategy that leverages local extrema information. The detailed layers are fused using an Enhanced Weighted Pulse Adaptive Dual Channel Neural Network (EWPADCNN), with fusion weights calculated using the Fractal Dimension with Differential Box Counting (FDDBC) method. In order to preserve low-frequency information, the base layers uses a weighted average method based on pixel significance. Comprehensive tests on 100 slices from four different datasets of brain disorders demonstrates that the proposed approach outperforms current fusion methods in both qualitative and quantitative assessments. These results support the suggested method as an efficient and trustworthy technique for improving brain imaging diagnostic quality. Quantitative evaluation demonstrates average improvements of 41%, 5%, 16%, 23%, 34%, and 4% in terms of AG, H, SF, MI, QABF, and SD metrics, respectively, compared to existing fusion methods.
subject: Mathematics
  topic: section
subject: Image fusion
  topic: keywords
subject: local extrema
  topic: keywords
subject: Enhanced Weighted Pulse
  topic: keywords
subject: Dual Channel Neural Network
  topic: keywords
subject: Fractal Dimension
  topic: keywords
subject: Differential Box Counting
  topic: keywords
subject: Brain imaging
  topic: keywords
subject: Artificial Intelligence and Computer Science
  topic: disciplines
subject: Machine Learning (ML)
  topic: disciplines
subject: Digital Image Processing
  topic: disciplines
creator: Shailaja Mantha
creator: Jatothu Brahmaiah Naik
creator: Kanagala Sateesh Kumar
creator: Rajanidevi
rights: Copyright (c) 2026 Shailaja Mantha, Jatothu Brahmaiah Naik, Kanagala Sateesh Kumar, Rajanidevi https://creativecommons.org/licenses/by/4.0/
date: 2026-03-16
publication date: 2026-03-16
starting page: 150
ending page: 165
doi: 10.22401/

Retention and Selectivity of the Nalidixic Acid and Enoxacin by Hydrophilic Interaction Liquid Chromatography on Various Polar Columns with Different Chain Lengths
type: item
description: This research aims to provide a comprehensive view of the separation mechanisms of HILIC stationary phases in various applications. This study was conducted to understand the retention behavior of nalidixic acid and enoxacin, to show the effect of alkyl chain length on their selectivity, and to develop a simple and sensitive HILIC method for their determination in pharmaceutical formulations. Two lab-made columns (ZIC-HILIC-1 and ZIC-HILIC-3) were used to examine the retention behavior of nalidixic acid and Enoxacin. The retention mechanism in this research was studied by investigating the effect of parameters that affect the selectivity of the separation, which include (acetonitrile content, pH, and buffer concentration). The zwitterionic columns are characterized by their different alkyl spacer chain length, which have been employed to examine the retention behavior of select drugs. The eluent consists of acetonitrile: 10mM acetate buffer (90:10 v/v, pH 4.75) equipped with a UV detector set at 220nm, at a flow rate of 0.75 mL/min. This research developed a ZIC-HILIC method to determine nalidixic acid and enoxacin in pharmaceutical formulations. The technique exhibited linearity in the concentration range (0.1– 6 μg/mL) and 0.1-12 μg/mL for nalidixic acid and Enoxacin, respectively. LOD is 0.070 and 0.04 μg/mL for nalidixic acid, and LOD is 0.080 and 0.060 μg/mL for enoxacin in ZIC-HILIC-1 and ZIC-HILIC-3 columns, respectively.
subject: Mathematics
  topic: section
subject: Enoxacin
  topic: keywords
subject: Nalidixic acid
  topic: keywords
subject: Pharmaceutical formulations
  topic: keywords
subject: Quinolones
  topic: keywords
subject: ZIC-HILIC
  topic: keywords
subject: Chemistry
  topic: disciplines
creator: Bashaer A. Al-phalahy
creator: Raad Radi Karabat
creator: Ali Amer Waheb
creator: Mustafa J. Mohammed
creator: Ashraf Saad Rasheed
rights: Copyright (c) 2025 Bashaer A. Al-phalahy, Raad Radi Karabat, Ali Amer Waheb, Mustafa J. Mohammed, Ashraf Saad Rasheed https://creativecommons.org/licenses/by/4.0/
date: 2025-12-19
publication date: 2025-12-19
starting page: 283
ending page: 291

Impact of Antenatal Steroid Treatment on External Morphological Feature of Newly Born Rats
type: item
description: This paper is about the application of Steroid treatment during pregnancy as practiced in common in practice, in rheumatological and autoimmune diseases, its prolonged use has an adverse effect on fetal growth. The study aimed to assess the effect of prenatal dexamethasone and hydrocortisone treatment on rats' offspring concerning growth parameters, congenital malformation, and survival rate. Sixty pregnant rats were allocated into 12 groups, and administered intraperitoneally either dexamethasone (1mg/kg/day) or hydrocortisone (9 mg/kg/day), and a control group that received normal saline. These were administered in the first week or last week of gestation. Neonatal body weight, length, and gross morphological anomalies were evaluated postnatal at 1 and 15 days. Prenatal dexamethasone treatment in late pregnancy resulted in 27 % neonatal mortality on day 3. Dexamethasone and hydrocortisone significantly reduced body weight and length of neonates compared to the control group, which is more prominent in dexamethasone treatment. However, both glucocorticoids resulted in profound developmental deficits when given in late pregnancy, especially dexamethasone, which causes profound growth retardation and teratogenic effects in neonates. At the same time hydrocortisone has a less severe impact on postnatal malformations and growth retardation. This sheds more light on the timing of steroid administration during the prenatal period, which should be taken into consideration for risk-benefit assessment.
subject: Mathematics
  topic: section
subject: Prenatal glucocorticoids
  topic: keywords
subject: Dexamethasone
  topic: keywords
subject: Hydrocortisone
  topic: keywords
subject: Fetal growth retardation
  topic: keywords
subject: Congenital anomalies
  topic: keywords
creator: Rasha A. Salman
creator: Huda Rashid Kamoona
creator: Ahlem Soussi
rights: Copyright (c) 2025 Rasha A. Salman, Huda Rashid Kamoona, Ahlem Soussi https://creativecommons.org/licenses/by/4.0/
date: 2025-12-15
publication date: 2025-12-15
starting page: 67
ending page: 75

Explainable Machine Learning Models for Mortality Risk Prediction of Crimean-Congo Hemorrhagic Fever in Iraq
type: item
description: In mid-2022, Iraq experienced a massive outbreak of Crimean-Congo hemorrhagic fever (CCHF), resulting in high mortality rates. The outbreak began in Thi-Qar province and subsequently spread to other provinces. This research analyzes data collected from Thi-Qar province to investigate the key factors influencing patient life risk. This is accomplished by collecting a real dataset (HemoIraq24) and conducting a statistical analysis, followed by developing explainable patient outcome prediction models using several machine learning algorithms. The most important factors contributing to the decision of the predicted outcome are obtained using feature importance and SHAP techniques. In addition, a web-based application has been developed based on the best ML prediction model to assist healthcare providers in clinical decision-making. The ML algorithms tested include Decision Trees, Random Forests, Logistic Regression, Gradient Boosting, and K-nearest neighbor. The highest baseline prediction model accuracy achieved is 89%. Feature importance analysis and SHAP are utilized for further feature engineering, causing an enhancement of 3% in prediction accuracy, with up to 8% enhancement in F1 score. It is found that the main factor contributing to the patient outcome is the days in the hospital, which means that the healthcare given in the hospitals is strong enough and can handle the endemic. The dataset can help with future research and is available at: HemoIraq24 Dataset.
subject: Mathematics
  topic: section
subject: Data Analysis
  topic: keywords
subject: Prediction Accuracy
  topic: keywords
subject: Outbreak
  topic: keywords
subject: Feature Importance Analysis
  topic: keywords
subject: Explainable AI
  topic: keywords
subject: Machine learning
  topic: subjects
subject: Computer science
  topic: disciplines
creator: Tiba Zaki Abdulhameed
creator: Rabia Al Mamlook
creator: Haider Ali Hantoosh
creator: Hasnaa Imad Al-Shaikhli
creator: Yasir Younis Majeed
creator: Suhad A. Yousif
creator: Tasnim Gharaibeh
rights: Copyright (c) 2026 Tiba Zaki Abdulhameed, Rabia Al Mamlook, Haider Ali Hantoosh, Hasnaa Imad Al-Shaikhli, Yasir Younis Majeed, Suhad A. Yousif, Tasnim Gharaibeh https://creativecommons.org/licenses/by/4.0/
date: 2026-03-15
publication date: 2026-03-15
starting page: 128
ending page: 149
doi: 10.22401/

Study of the Efficiency of the Magnetic Deflector at Various Operation Conditions
type: item
description: The efficiency of the magnetic deflector for variation operation condition was investigated. The design appears that the possibility of finding the constant characteristics of the deflector which lead to stability in the properties of the electron beam at the image plane despite the change in the properties of the electron source as: the initial beam divergence and the energy. The relation between the value of applied magnetic field on the magnetic deflector and the properties of the electron beam was studied. also the distribution of different value of the energy of the electron beam was studied. The calculation was carried out for different values of the divergence angle. The result showed that the increases in divergence angle dose not result change in the nature of the distribution of energy of the electron beam at image plane, and one can find constant dimensions of the electron beam at image plane even though the electron beams energy was altered, and this results can be achieved by choosing the appropriative values of magnetic field to be applied to the deflector. The calculations showed that the non-linear relation between the amount of the magnetic field and values of the kinetic energy electron beam.
subject: Mathematics
  topic: section
subject: Magnetic deflection system
  topic: keywords
subject: Magnetic deflector
  topic: keywords
subject: Initial angle
  topic: keywords
subject: Electron beam optics
  topic: keywords
subject: Simulation
  topic: keywords
subject: electron optics
  topic: disciplines
creator: Shahad A. Aziz
creator: Oday A. Hussein
rights: Copyright (c) 2025 Shahad A. Aziz, Oday A. Hussein https://creativecommons.org/licenses/by/4.0/
date: 2025-12-15
publication date: 2025-12-15
starting page: 124
ending page: 134

Syntheses, Characterization, DFT and Molecular Docking of N-(4-chlorophenyl)-1-(4-nitrophenyl) methanimine, (4-chlorophenyl)-1-(4-methoxyphenyl) methanimine and its derivatives
type: item
description: The synthesis of numerous chemical compounds relies on imines as a key building ingredient. Several Schiff bases were generated via the acid-catalyzed condensation of aromatic aldehyde derivatives with aniline derivatives. FT-IR, 1HNMR, spectra allowed to identify the products. The ORCA software package was used to obtain the outcome of the Density Functional Theory (DFT) and to comprehend how para substituting impacts the electronic structure of the synthesized compounds. Finally, docking simulation was performed using the Autodock application. At the binding site, the prepared compounds were docked with the 3FYV enzyme.
subject: Mathematics
  topic: section
subject: Imines
  topic: keywords
subject: Schiff bases
  topic: keywords
subject: Molecular Docking
  topic: keywords
subject: DFT
  topic: keywords
subject: theoretical study
  topic: subjects
subject: physical and organic
  topic: disciplines
creator: Asya A. Tawfiq
creator: Omar J. Mahdi
creator: Ahmed H. Hattab
rights: Copyright (c) 2026 Asya A. Tawfiq, Omar J. Mahdi, Ahmed H. Hattab https://creativecommons.org/licenses/by/4.0/
date: 2026-03-16
publication date: 2026-03-16
starting page: 31
ending page: 41
doi: 10.22401/

Testing Different Models for the Rotation Curve of the Milky Way Using BURT Observations
type: item
description: Understanding the rotation curves (RCs) of our Milky Way galaxy represents a main tool to understand its dynamical evolution and the connection between different regions in the galaxy. The present work is intended to test the applicability of three rotation curve models against two datasets, the first being the well-known Sofue data, and the second being the Baghdad University Radio Telescope (BURT) data, both for the HI 21-cm emission line. The tested models are the Time of Events (ToE) model, the Brandt model, and the Navarro-Frenk-White (NFW) model. The fitting results showed that the ToE model provided the best prediction for the experimental data compared to the other two models for both BURT and Sofue data within all regions in the galaxy. The other two models applied slightly well only in the central region, while their results diverge near the edge region. The reduced R2 values that ​​we obtained for BURT and Sofue data are equal to 0.79 and 0.94, respectively. In addition, the ToE model worked as a calibration tool for the BURT data point, which can predict the behavior of the rotation curve and fill in the gaps of the missing points in the observed BURT data.
subject: Mathematics
  topic: section
subject: Galaxy
  topic: keywords
subject: Milky Way
  topic: keywords
subject: Radio Telescope
  topic: keywords
subject: Rotation Curve
  topic: keywords
subject: Time of Events Model
  topic: keywords
subject: Physical Science
  topic: subjects
subject: Astronomy and Astrophysics
  topic: disciplines
creator: Jazeel H. Azeez
creator: Hareth S. Mahdi
creator: Roslan Umar
creator: Kamal M. Abood
rights: Copyright (c) 2026 Jazeel H. Azeez, Hareth S. Mahdi, Roslan Umar, Kamal M. Abood https://creativecommons.org/licenses/by/4.0/
date: 2026-03-16
publication date: 2026-03-16
starting page: 109
ending page: 116
doi: 10.22401/

Dispersion Parameters and Electrical Characterization of Cd₁₋ₓCuₓS Thin Films Deposited by Using AACVD Technique
type: item
description: In this research, an aerosol-assisted chemical vapor deposition (AACVD) was successfully employed to synthesize Cd₁₋ₓCuₓS (0 ≤ x ≤ 1) semiconductor thin films. The structural, morphological, and optical properties of the deposited films were systematically investigated as a function of copper concentration using energy-dispersive X-ray spectroscopy (EDX), scanning electron microscopy (SEM), and UV-Vis spectroscopy. The results demonstrated that the optical behavior of the films is strongly influenced by Cu incorporation. Specifically, an increase in CdS fraction resulted in a decrease in the Urbach energy, whereas the activation energy exhibited a progressive increase with higher CuS content.
subject: Mathematics
  topic: section
subject: Urbach Energy
  topic: keywords
subject: Dispersion Parameters
  topic: keywords
subject: SEM-EDX
  topic: keywords
subject: AACVD
  topic: keywords
subject: physics
  topic: disciplines
creator: Zaid Mohammed Jasim
creator: Nahida B. Hasan
creator: Mohsin K. Al-khaykanee
rights: Copyright (c) 2026 Zaid Mohammed Jasim, Nahida B. Hasan, Mohsin K. Al-khaykanee https://creativecommons.org/licenses/by/4.0/
date: 2026-03-16
publication date: 2026-03-16
starting page: 98
ending page: 108
doi: 10.22401/

Photo-Thermal Conversion of Selective Coatings with Iron and Chromium Powder Additives
type: item
description: This research explores the improvement of solar-to-thermal conversion efficiency in aluminum substrates coated with heat-resistant black paint enhanced by iron (Fe) and chromium (Cr) powders. Aluminum sheets were thoroughly cleaned and coated with a commercial black paint, followed by the application of Fe and Cr powders (both individually and combined) using an air-spraying method to ensure even distribution. The coatings’ morphology and uniformity were examined through optical and scanning electron microscopy, while their elemental makeup was assessed using energy-dispersive X-ray spectroscopy (EDS). The photo-thermal conversion capabilities were tested by exposing the coated substrates to solar radiation, with temperature monitored over time. Reflectance measurements were conducted using a pyrheliometer-like device, and spectral absorptance was analyzed via UV-Vis spectroscopy. The EDS results confirmed the effective incorporation of Fe and Cr into the coatings, with minor cross-contamination likely due to processing. Results show that adding Fe and Cr powders notably changes the surface morphology, increasing roughness and complexity, which enhances light trapping and absorption. Among the coatings, the Fe-modified sample showed the highest solar absorptance (96.23%) and the greatest temperature increase under irradiation, surpassing both the Cr-modified and combined Fe+Cr coatings. UV-Vis analysis revealed that Fe-containing coatings possessed the greatest integrated absorbance, especially within the visible spectrum (500–800 nm), aligning with their superior photo-thermal performance. These results highlight that integrating Fe powder into heat-resistant paint on aluminum substrates is an effective and practical approach to optimize solar-to-thermal energy conversion, offering promising applications in solar thermal collectors.
subject: Mathematics
  topic: section
subject: Solar collectors
  topic: keywords
subject: Coating
  topic: keywords
subject: Photo-thermal effect
  topic: keywords
subject: Optical absorption
  topic: keywords
subject: Nanopowders
  topic: keywords
subject: Solid state physics
  topic: subjects
subject: Renewable energy
  topic: subjects
subject: selective coatings
  topic: subjects
subject: solar-thermal conversion
  topic: subjects
subject: Physics
  topic: disciplines
creator: Mohammed Al-Ameen Amer
creator: Ahmed A. Al-Tabbakh
rights: Copyright (c) 2025 Mohammed Al-Ameen Amer, Ahmed A. Al-Tabbakh https://creativecommons.org/licenses/by/4.0/
date: 2025-12-15
publication date: 2025-12-15
starting page: 173
ending page: 187

Ion-Pair Based Dispersive Liquid-Liquid Microextraction for Spectrophotometric Analysis of Carmoisine in Food: A BAGI and AGREE Study
type: item
description: This paper discusses the identification of a new dispersive Liquid-liquid microextraction method for evaluating carmoisine dye using spectrophotometry. It has been established that Carmoisine dye is an anionic azo food dye used in the food industry in some countries such as Iraq. This method involves the extraction of carmoisine from aqueous solutions using chloroform as the extraction solvent in a DLLME procedure. Parameters influencing the DLLME efficiency, including pH, type and volume of extraction as well as dispersive solvents (chloroform and ethanol), under a centrifugation conditions, were thoroughly optimized to complete extraction conditions. Moreover, the method showed a linear calibration curve in the range of 1.0-10.0 mg/L. The low values of both the limit of quantification (0.297 mg/L) and the limit of detection (0.099 mg/L) indicate a more sensitive DLLME method. The applicability and environmental impact of the developed method were assessed using the Blue Applicability Grade Index (BAGI) and the Analytical Greenness metric (AGREE), yielding scores of 70.0 and 0.55, respectively, indicating a practical method with moderate adherence to green analytic chemistry principles. The optimized DLLME procedure was successfully applied to the determination of carmoisine dye in various food samples.
subject: Mathematics
  topic: section
subject: Microextraction
  topic: keywords
subject: DLLME
  topic: keywords
subject: Carmoisine
  topic: keywords
subject: TTC reagent
  topic: keywords
subject: AGREE
  topic: keywords
subject: BAGI
  topic: keywords
subject: analytical chemistry
  topic: subjects
subject: Analytical chemistry
  topic: disciplines
subject: green chemistry
  topic: disciplines
creator: Araf Ismael Jabbar
creator: Adel Ismael Jabbar
creator: Arwa Mahmoud Hussain
creator: Ruba Fahmi Abbas
creator: Adrián Fuente-Ballesteros
rights: Copyright (c) 2026 Araf Ismael Jabbar, Adel Ismael Jabbar, Arwa Mahmoud Hussain, Ruba Fahmi Abbas, Adrián Fuente-Ballesteros https://creativecommons.org/licenses/by/4.0/
date: 2026-03-16
publication date: 2026-03-16
starting page: 42
ending page: 53
doi: 10.22401/

CXCL12, CA15-3, and Liver function Tests as Predictors of Liver Metastasis in Breast Cancer
type: item
description: Breast cancer liver metastasis (BCLM) is a multi- step process that characterized by the spread of breast cancer cells to the liver. The majority of breast cancer-related deaths are due to metastatic rather than primary breast tumors. CXCL12 is one of the chemokines, small proteins capable of migrating various types of immune cells to the site of inflammation. CXCL12 can affect several cell biological activities, such as migration and proliferation, when it binds to its receptors. The aim of this study is to investigate the predictive value of plasma CXCL12, CA15-3, and some liver-related parameter levels in breast cancer patients with liver metastasis. This study involves 94 women, 25 healthy controls and 69 patients with breast cancer, divided into three subgroups: 26 newly diagnosed women with primary breast cancer, 28 women with non-metastatic breast cancer undergoing chemotherapy, and 15 women with liver metastatic breast cancer. Plasma levels of CXCL12, CA15-3, albumin, ALP, ALT, and AST were measured using absorbance photometry and ELISA assays. The results of the study reveals that the level distributions of CXCL12 (p‎>0.9999) and CA15-3 (p‎>0.9999) showed no significant difference between breast cancer patients with and without liver metastasis. Albumin levels were significantly lower (‎‎p=0.0089) in women with liver metastatic breast cancer compared to those without metastasis. Levels of ALP‎ (p=‎0.0006‎), ALT (‎p=0.0015), and AST (p‎‎<0.0001) were significantly elevated in breast cancer liver metastatic patients compared to patients without metastasis. CXCL12 ‎(AUC, ‎0.5840‎, p=‎0.3788‎)‎ and CA15-3 ‎(AUC, ‎0.5787‎, p=‎0.4099‎)‎ could not serve as reliable discriminatory parameters for liver metastasis. Albumin ‎(AUC, ‎0.7267‎, p=‎0.0176‎) showed a moderate ability to distinguish between BC patients with and without BCLM‎. ALP (AUC, 0.8693, p=0.0001) and AST (AUC, 0.9453, p<0.0001) exhibited the highest diagnostic accuracies for liver metastasis. Together…
subject: Mathematics
  topic: section
subject: Tumors
  topic: keywords
subject: Breast cancer
  topic: keywords
subject: Liver metastasis
  topic: keywords
subject: Chemokine
  topic: keywords
subject: Biochemistry
  topic: disciplines
creator: Baqer A. Altimmime
creator: Farah A. Rashid
creator: Yaala Saady Raof
creator: Omran Mansour
rights: Copyright (c) 2025 Baqer A. Altimmime, Farah A. Rashid, Yaala Saady Raof, Omran Mansour https://creativecommons.org/licenses/by/4.0/
date: 2025-12-15
publication date: 2025-12-15
starting page: 55
ending page: 66

AI Based Cognitive and Software Defined Network for Dynamic Management and Security in 6G Networks
type: item
description: The appearance of the sixth generation (6G) networks introduces new realities of demand towards real-time, scalable and secure communication infrastructures. To respond to such challenges, the overlap of three major technologies is required, namely Cognitive Networks (CN), Artificial Intelligence (AI), and Software-Defined Networking (SDN). Nevertheless, the issue of integration is not simple as the environments of 6G will be heterogeneous, and threats to security will be constantly changing. This paper will suggest a combination of hybrid layered architecture which integrates AI-based analytics, cognitive flexibility and SDN programmability to optimize dynamic network control and advanced security in 6G environments. This architecture styles use of reinforcement learning (RL) and convolutional neural networks (CNN) to enable autonomous decision creation, resource optimization, and detection of threats. The simulation results (obtained with synthetic traffic and attack scenarios) show the improvements compared to the baseline systems are high: 30 percent less latency, 25 percent higher throughput, 20 percent higher energy efficiency, 95 percent DDoS attack detection and 98 percent malware propagation detection accuracies. These results confirm the capabilities of the framework in providing mission critical 6G applications in areas like in healthcare, industries, and smart cities.
subject: Mathematics
  topic: section
subject: 6G Networks
  topic: keywords
subject: Cognitive Networks
  topic: keywords
subject: Artificial Intelligence
  topic: keywords
subject: Software-Defined Networking
  topic: keywords
subject: Dynamic Network Management
  topic: keywords
subject: Zero-Trust Security
  topic: keywords
subject: Reinforcement Learning
  topic: keywords
subject: CNN
  topic: keywords
subject: Network Scalability
  topic: keywords
subject: Computer Science,Networks
  topic: subjects
subject: 6G Networks
  topic: subjects
subject: Cognitive Networks
  topic: subjects
subject: Dynamic Network
  topic: subjects
subject: Computer Science,Networks
  topic: disciplines
creator: Ehsan Qahtan Ahmed
creator: Zainab Haider Ameen
creator: Zahraa A. Jaaz
creator: Maamoun Ahmed
rights: Copyright (c) 2025 Ehsan Qahtan Ahmed, Zainab Haider Ameen, Zahraa A. Jaaz, Maamoun Ahmed https://creativecommons.org/licenses/by/4.0/
date: 2025-12-15
publication date: 2025-12-15
starting page: 226
ending page: 240

Methods for Finding Gelfand Pairs in Finite Groups with an Emphasis on Symmetry
type: item
description: This paper seeks to develop a procedure to identify all pairs within a finite group that are Gelfand, symmetric, and weakly symmetric. With the focus on the projective special linear groups. This leads to a unique class of "strictly weakly symmetric pairs." For the specific case of the projective special linear group PSL(2, p) where p is prime in the range , it is observed that only a single such pair exists.
subject: Mathematics
  topic: section
subject: Gelfand pairs,
  topic: keywords
subject: symmetric
  topic: keywords
subject: weakly symmetric
  topic: keywords
subject: multiplicity-free representations
  topic: keywords
subject: GAP
  topic: keywords
subject:
  topic: subjects
  value: Subjects: Gelfand pairs, symmetric pairs, weakly symmetric pairs, finite groups, representation theory, harmonic analysis, multiplicity-free representations, projective special linear groups, computational group theory, GAP.
subject: Pure Mathematics, Algebra, Representation Theory, Computational Mathematics, Group Theory.
  topic: disciplines
creator: Saad O. Bedaiwi
rights: Copyright (c) 2026 Saad O. Bedaiwi https://creativecommons.org/licenses/by/4.0/
date: 2026-03-16
publication date: 2026-03-16
starting page: 176
ending page: 184
doi: 10.22401/

Some Methods to Estimate the Parameters of IDAL-Distribution (b)
type: item
description: This paper estimates three parameters for a new model called “IDAL Distribution”. This model expands the exponential Weibull distribution by adding a third parameter and studying its characteristics. Several estimation methods, such as maximum likelihood estimation, ordinary least squares estimation, and proposed ordinary least squares methods, have been used to investigate the unknown parameters of the IDAL distribution. The goodness of fit of the proposed distribution is ultimately compared, and the results of the applied approaches are evaluated based on MSE.
subject: Mathematics
  topic: section
subject: IDAL Distribution
  topic: keywords
subject: Estimation methods
  topic: keywords
subject: Maximum likelihood
  topic: keywords
subject: Ordinary least square
  topic: keywords
subject: Ordinary least square suggested
  topic: keywords
subject: mathematics statistics
  topic: disciplines
creator: Alaa M. Hamad
creator: Iden H. Alkanani
rights: Copyright (c) 2025 Alaa M. Hamad, Iden H. Alkanani https://creativecommons.org/licenses/by/4.0/
date: 2025-12-15
publication date: 2025-12-15
starting page: 270
ending page: 282

Image Augmentation for Passionfruit Disease Classification Using Conditional Generative Adversarial Networks (cGANs)
type: item
description: Early and accurate detection of crop diseases is vital for safeguarding food security and improving agricultural productivity, particularly in regions where access to the prognosis and diagnostic tools as well as expert knowledge is remote. This paper presents the first targeted application of class-conditional Generative Adversarial Networks (cGANs) to passionfruit disease detection using the publicly available Makerere Passionfruit dataset, which contains 3,001 labelled images across three classes: Healthy, Brownspot, and Woodiness. We propose a domain-specific augmentation pipeline that integrates progressive growing, spectral normalization, hinge loss, and gradient penalty to generate high-quality, class-specific synthetic images for under-represented disease categories. Experimental results demonstrate that cGAN augmentation significantly enhances minority class recognition. The F1-score for Brownspot improved from 0.72 to 0.78 and for Woodiness from 0.60 to 0.71, raising the macro-average F1-score from 0.76 to 0.80. To validate robustness, the framework is evaluated across multiple architectures, including LeNet, ResNet-18, and MobileNetV2. In each case, cGAN-based augmentation consistently improved macro-F1 scores by 3–5% without reducing overall accuracy, confirming the model-agnostic nature of the approach. These findings establish a novel and practical foundation for AI-powered plant/crop disease detection in realistic field conditions. The framework is computationally efficient and suitable for deployment on mobile or edge devices, making it particularly relevant for low-resource and inaccessible agricultural environments.
subject: Mathematics
  topic: section
subject: Passionfruit disease classification
  topic: keywords
subject: Conditional GAN (cGAN)
  topic: keywords
subject: Image augmentation
  topic: keywords
subject: Deep learning
  topic: keywords
subject: Agricultural AI
  topic: keywords
subject: AI
  topic: disciplines
creator: Khamael Al-Dulaimi
creator: Jasmine Banks
rights: Copyright (c) 2026 Khamael Al-Dulaimi, Jasmine Bank https://creativecommons.org/licenses/by/4.0/
date: 2026-03-16
publication date: 2026-03-16
starting page: 117
ending page: 127
doi: 10.22401/

The Length-Biased Wieghted Kpendidum Distribution: Properties and some Real-Life Applications
type: item
description: The main aim of this paper is to introduce a new class of one-parameter statistical models namely the length-biased weighted Kpendidum distribution. This distribution is a convex combination of three component of Gamma distribution. Some statistical and reliability properties of this distribution are discussed. The maximum likelihood estimation is used to estimate the one-parameter of the presented distribution. Moreover, five real life applications are provided to investigate the effectiveness of the new model in comparison with the Kpendidum distribution and some other one-parameter length-biased weighted models. Additionally, it is shown that in some real-life applications the proposed model gives a better results than some of the two-parameter models. Finally, different statistical measures are used to guarantee the accuracy of this model.
subject: Mathematics
  topic: section
subject: Weighted distribution
  topic: keywords
subject: Kpendidum distribution
  topic: keywords
subject: Length-based distribution
  topic: keywords
subject: Maximum likelihood Estimation
  topic: keywords
subject: Mathematical statistics
  topic: disciplines
creator: Ranen Z. Ahmood
creator: Akram Al-Sabbagh
creator: Haneen A. Ameen
rights: Copyright (c) 2026 Ranen Z. Ahmood, Akram Al-Sabbagh, Haneen A. Ameen https://creativecommons.org/licenses/by/4.0/
date: 2026-03-16
publication date: 2026-03-16
starting page: 166
ending page: 175
doi: 10.22401/

Biochemical changes of alkaline phosphatase in tissue homogenate of the developing femurs in chick embryos after in ovo calcium carbonate nanoparticles inoculation
type: item
description: This study oriented to provide evidences related to effects of calcium carbonate nanoparticles (CCN) on the osteogenesis of the developing femur in chick embryos. The 20 fertilized chick eggs used in this study divided into two a control and experimental groups. The control group of eggs injected with normal saline pre-incubation, while eggs of the experimental group injected with 500 g/mL hydrocolloid of CCN in 0.2 mL volume per egg. The homogenate of the femur obtained from the control and experimental groups show statistically significant variations when comparing the level of alkaline phosphatase in the tissue of the control group at day 13 with that of the experimental group at day 13 and day 14. The alkaline phosphatase level as a marker of bone metabolism in the femur tissue homogenate of the experimental group revealed highly significant increased concentration compared to that of the control group at both day 13 and 14. This characteristic finding is associated with the effect of in-ovo inoculation of CCN on the femur tissue homogenate in pre-hatching chick embryos during osteoid formation and mineralization.
subject: Mathematics
  topic: section
subject: Chick eggs
  topic: keywords
subject: Embryo
  topic: keywords
subject: Calcium carbonate
  topic: keywords
subject: Nanoparticles
  topic: keywords
subject: Femur
  topic: keywords
subject: Osteogenesis
  topic: keywords
subject: Tissue homogenate
  topic: keywords
subject: Alkaline phosphatase
  topic: keywords
subject: chemistry
  topic: disciplines
creator: Lamyaa Hadi
creator: Fatma Ayadi
creator: Hayder Jawad Kadhim
rights: Copyright (c) 2025 Lamyaa Hadi, Fatma Ayadi, Hayder Jawad Kadhim https://creativecommons.org/licenses/by/4.0/
date: 2025-09-15
publication date: 2025-09-15
starting page: 119
ending page: 124

Immunoregulatory Role of miRNA-26 in Modulating IL-32, IL-33, IL-34, and MMP-9 Expression in Rheumatoid Arthritis
type: item
description: Rheumatoid arthritis (RA) is a systemic autoimmune illness marked by abnormal cytokine expression and persistent inflammation. MicroRNAs (miRNAs), particularly miRNA-26, have been implicated in the regulation of inflammatory pathways and show promise as potential biomarkers for RA diagnosis and treatment monitoring. Aim: This study aimed to evaluate miR-26 expression about established clinical markers and pro-inflammatory cytokines, to identify potential predictive markers of treatment response and contribute to more personalized management strategies in RA. Method: 180 participants were enrolled and categorized into three groups: Newly diagnosed RA patients (NDRA), biologically treated RA patients (TRA), and Healthy controls (HC). Each group consisted of 60 Individuals. The miR-26 expression levels were quantified in blood specimens using quantitative real-time PCR (qRT-PCR). Additionally, serum concentrations of interleukins (IL-32, IL-33, IL-34) and matrix metalloproteinase-9 (MMP-9) were quantified using sandwich enzyme-linked immunosorbent assay (ELISA) techniques. Results: Both NDRA and TRA groups exhibited elevated miR-26 expression and significantly increased serum levels of IL-32, IL-33, IL-34, and MMP-9 relative to healthy controls (p < 0.001). The NDRA group showed the highest cytokine and MMP-9 levels, indicating active inflammation, while the TRA group had moderately reduced levels and a greater fold increase in miR-26 expression. IL-33 and MMP-9 demonstrated the most pronounced intergroup differences, suggesting their utility as early diagnostic biomarkers. The reciprocal relationship between miR-26 and inflammatory cytokines indicates a regulatory function of it. MiR-26 expression could be downregulated during the peak of inflammation and partially restored with biotherapy treatment Conclusion: IL-33 and MMP-9 came out as prospective early diagnostic markers. The negative correlation between miR-26 and inflammatory mediators points to a regulatory, an…
subject: Mathematics
  topic: section
subject: miR-26
  topic: keywords
subject: IL-32
  topic: keywords
subject: IL-33
  topic: keywords
subject: IL-34
  topic: keywords
subject: Rheumatoid Arthritis
  topic: keywords
subject: and MMP9
  topic: keywords
subject: miR-26
  topic: subjects
subject: IL-32
  topic: subjects
subject: IL-33
  topic: subjects
subject: IL-34
  topic: subjects
subject: Rheumatoid Arthritis
  topic: subjects
subject: and MMP9
  topic: subjects
subject: Biotechnology
  topic: disciplines
creator: Rawaa AlChalabi
creator: Orooba Al-Hammood
creator: Semaa A. Shaban
creator: Saja Hameed Abbas
rights: Copyright (c) 2025 Rawaa Al-Chalabi, Orooba Al-Hammood, Semaa A. Shaban, Saja Hameed Abbas https://creativecommons.org/licenses/by/4.0/
date: 2025-09-15
publication date: 2025-09-15
starting page: 93
ending page: 104

Comparative Study on Electron Beam Characteristics of a Thermionic Electron Gun for Different Shapes of Wehnelt Cup
type: item
description: This research paper presents a comparative study on the effect of the geometric design of a thermionic electron gun on the quality of the electron beam. Although several studies have been conducted on the thermionic electron gun design. However, the effect of the geometry of the Wehnelt electrode on the performance of the electron gun needs to be investigated through accurate and comparative analysis. Simulations were performed to test three different shapes of Wehnelt electrodes and their effect on electron gun performance behavior of the electron gun in which the characteristics of electron beams for different designs were analyzed with the aid of computer aided simulations. The results showed that the conical shape is the most efficient, producing low emittance (ԑ) and a small crossover diameter (R) of the electron beam. Based on these results, the performance of the electron gun can be improved by selecting an appropriate shape for the Wehnelt electrode, which produces high-quality electron beams.
subject: Mathematics
  topic: section
subject: Electron gun
  topic: keywords
subject: Wehnelt cup
  topic: keywords
subject: Beam emittance
  topic: keywords
subject: Optimization
  topic: keywords
subject: charged particle optics
  topic: disciplines
creator: Roaa T. Abdulla
rights: Copyright (c) 2026 Roaa T. Abdulla https://creativecommons.org/licenses/by/4.0/
date: 2026-03-16
publication date: 2026-03-16
starting page: 90
ending page: 97
doi: 10.22401/

Evaluation of Forensic Efficiency Parameters of 19 Autosomal STR Markers in a Population Sample of Arabs Residing in Voronezh, Russia
type: item
description: The accuracy of DNA profile identification is significantly enhanced by increasing the number of STR markers that are examined. Forensic markers' usefulness depends on the population, necessitating regional studies. This study aims to provide a better understanding of the effectiveness of autosomal STR loci as a forensic tool by comparing the genetic factors found in Arabs living in Voronezh, Russia, to published datasets from other Arab groups. Blood samples were collected from 98 unrelated Arab volunteers. Using a 3130XL Genetic Analyzer, DNA typing was conducted for 19 polymorphic STR loci and the Amelogenin locus with the use of the GOrDIS Plus kit. The analysis revealed a high degree of polymorphism, with the number of alleles per locus ranging from 6 to 36. The highest allele frequency observed was 0.5816 at the TPOX locus. The observed heterozygosity (Ho) and expected heterozygosity (He) values were generally consistent, indicating that the population is largely in Hardy–Weinberg equilibrium (HWE). The forensic parameters demonstrated high discriminatory power: the Power of Discrimination (PD) ranged from 0.813 to 0.962, the Polymorphism Information Content (PIC) from 0.58 to 0.86, and the Power of Exclusion (PE) from 0.388 to 0.689. High Ho was observed at FGA and D21S11 loci (87.76% and 87.8%, respectively), while TPOX showed the lowest Ho (63.27%).In conclusion, the Analysis of Molecular Variance (AMOVA) and pairwise FST analysis indicated that Arabs residing in Voronezh, Russia, show strong genetic similarities with Arab populations in Europe and Arab countries. These findings underscore the robustness of the selected STR markers for forensic applications within this population and contribute valuable data to the global forensic genetic database.
subject: Mathematics
  topic: section
subject: STR
  topic: keywords
subject: TPOX locus
  topic: keywords
subject: Genetic diversity
  topic: keywords
subject: Arab populations
  topic: keywords
subject: forensic dna
  topic: disciplines
creator: Jaber M. M. T.
creator: Mohammed M. Al-Zubaidi
creator: Miriam Jasim Shehab
creator: Zahraa Mustafa AL-Jumaa
creator: Nisred Klichkhanov
rights: Copyright (c) 2025 Jaber M. M. T., Mohammed M. Al-Zubaidi, Miriam Jasim Shehab, Zahraa Mustafa AL-Jumaa, Nisred Klichkhanov https://creativecommons.org/licenses/by/4.0/
date: 2025-12-15
publication date: 2025-12-15
starting page: 33
ending page: 43

Deep Image Segmentation Using Explainable Attention Mechanisms: Applications in Biomedical Imaging
type: item
description: Correct and discernible segmentation of an image is an important part of biomedical imaging, especially when anatomical structures and pathological regions are identified. Although deep learning architectures, like U-Net and its variants, have performed well, their lack of interpretability, transparency and contextual reasoning has limited their clinical adoption. This research helps to overcome the most important issue of high-performance medical segmentation by introducing a new explainable framework that combines convolutional encoders with transformer-based decoders and dual attention mechanisms. There are three aspects of this work, based on the following objectives. (1) To boost the performance of segmentation by means of hybrid local-global feature modelling; (2) To bring about clarity through visual explanation tools; and (3) To conduct clinical viability checks through expert assessments. The architecture proposed includes CBAM for fine spatial and channel attention and combines Grad-CAM++ and SHAP for local and global explainability. Such modules make it possible for clinicians to view the decision paths of models and establish trust in automated outputs. Experiments in two datasets, which were publicly available, were performed: ISIC 2018 for skin lesion segmentation and BraTS 2021 for brain tumor segmentation. The quantitative results show that the suggested method is better than several strong baseline models, such as U-Net, Attention U-Net, and TransUNet, delivering Dice scores of 0.902 and 0.895 on ISIC and BraTS datasets, respectively. Visual comparisons and expert confirmation validate the clinical plausibility of the predicted masks and demonstrate the potential worth of the explainability in high-stakes healthcare conditions. On the whole, this work provides a prudent, precise and explainable deep learning approach toward medical image segmentation and offers ample room for scientific integration and trust-conscious implementation in diagnostics w…
subject: Mathematics
  topic: section
subject: Biomedical Image Segmentation XAI Transformer-CNN Hybrid
  topic: keywords
subject: XAI
  topic: keywords
subject: Attention Mechanisms
  topic: keywords
subject: Transformer-CNN Hybrid
  topic: keywords
subject: Grad-CAM++
  topic: keywords
subject: SHAP
  topic: keywords
subject: Skin Lesion Analysis
  topic: keywords
subject: Brain Tumor Segmentation
  topic: keywords
subject: Clinical Decision Support
  topic: keywords
subject: Deep Learning Interpretability
  topic: keywords
subject: Biomedical Image Segmentation
  topic: subjects
subject: image processing
  topic: subjects
subject: Deep Learning
  topic: subjects
subject: computer science
  topic: disciplines
creator: Hanaa M. Mushgil
creator: Farah Saad Al-Mukhtar
creator: Ehsan Qahtan Ahmed
creator: Khairiyah Saeed Abduljabbar
rights: Copyright (c) 2025 Hanaa M. Mushgil, Farah Saad Al-Mukhtar, Ehsan Qahtan Ahmed, Khairiyah Saeed Abduljabbar https://creativecommons.org/licenses/by/4.0/
date: 2025-12-15
publication date: 2025-12-15
starting page: 241
ending page: 258

Cytotoxic Activity of Secondary Metabioltic Agent Produce by Actinomycetes
type: item
description: In this work, total of 50 samples of different soil types (sandy, loomy, clayey, and river deposits) were collected randomly. The physico-chemical properties such as pH, soil temperature and electrical conductivity of the soil samples were studied and analysed Soil characteristics all were within the limits of growth and reproduction of Actinomycetes. Of the 50 soil samples, only 35 were sourced to obtain 18 colonies, were suspected to be Actinomycetes. These isolates were purified by sub culturing more than one time on International Streptomyces project-2 agar (ISP-2),the pigmentation of the selected colonies exhibited a spectrum of colors ,including shades of white, cream, gray, green ,black to yellow. These isolates were identified by culture properties which showed that they were Gram positive varieties of aerial mycelia and substrate mycelia and spore chain formation. By the third day of incubation, the isolate had attained the stationary phase of its growth cycle.at maximum OD 0.619nm. Extraction of Extracellular secondary metabolites from Each of the Actinomycetes by ethyl acetate. According to the quantity of the product and the speed of its production, 3 isolates (NI- RS 15, AM - AG 18 and MA-CL2) were selected to complete the study. All extracts with high solubility with water, had melting point range 287ºC- 300°C and were powder in natural. Chemical Characterization of secondary metabolites were as follow λ max ranged from 274 nm to 320 nm FTR show several bands of absorption as functional chemical group and HPLC clearly sharp peaks that appeared at 2.1 - 9.9 minutes which indicated a very well separated. The cytotoxicity of extracts were assessed by MTT on normal cell line was which inhibited cells range from 9.9-13.9% in 200 μg / mL.
subject: Mathematics
  topic: section
subject: Actinomycetes
  topic: keywords
subject: FTR
  topic: keywords
subject: HPLC
  topic: keywords
subject: Secondary Metabolites
  topic: keywords
subject: UV-visible spectroscopy
  topic: keywords
subject: microbiology
  topic: disciplines
subject: antibiotic
  topic: disciplines
creator: Istbraq Abbas Hassan
creator: Yazi Abdullah Jassim
creator: Noor Salman Kadhim Al-Khafaji
rights: Copyright (c) 2026 Istbraq Abbas Hassan, Yazi Abdullah Jassim, Noor Salman Kadhim Al-Khafaji https://creativecommons.org/licenses/by/4.0/
date: 2026-03-16
publication date: 2026-03-16
starting page: 61
ending page: 79
doi: 10.22401/

Extended Inverse Lomax Distribution with Simulation and Application to Crude Birth Rate Data
type: item
description: This paper presents a flexible extended version of the inverse Lomax (EVIL) distribution with four parameters and different shapes of the hazard function. It is developed within the framework of the truncated Rayleigh odd Weibull generator family. Various statistical properties are discussed, including reliability measures, density mixture representation, moments, characteristic and moment-generating functions, quantile function, order statistics, and residual life function with its reversal. The maximum likelihood estimates of unknown parameters are assessed via simulation. The empirical results show that the estimates are reliable and flexible. Furthermore, the EVIL is employed with some competitive distributions to model real-life data concerning the crude birth rate in Iraq. The outcomes of the real data demonstrate that the EVIL outperforms existing inverse Lomax-based models in terms of flexibility and goodness of fit.
subject: Mathematics
  topic: section
subject: Inverse Lomax
  topic: keywords
subject: Reliability Measures
  topic: keywords
subject: Statistical Features
  topic: keywords
subject: Maximum Likelihood
  topic: keywords
subject: Mathematical Statistics
  topic: disciplines
creator: Hadi H. Hadi
creator: Omar A. Hilal
creator: Nadia H. Al-Noor
rights: Copyright (c) 2025 Hadi H. Hadi, Omar A. Hilal, Nadia H. Al-Noor https://creativecommons.org/licenses/by/4.0/
date: 2025-09-15
publication date: 2025-09-15
starting page: 130
ending page: 139

Charge Carrier Mechanism in CdTe/ZnTe Core/Shell Nanocrystals for Photoelectrodes by Laser Ablation Method
type: item
description: Laser ablation in the UV-Vis absorption and emission spectra, as well as the duration increased and the emitted quantum efficiency increased., were used to synthesise and characterise of CdTe/ZnTe core/shell nanocrystals (NCs) or quantum dots (QDs). The dynamics via which carriers decrease and the distribution of excited state carriers were revealed by using ultrafast transient absorption spectroscopy to study the charge carrier process. A broad ground state bleach signal in the core/shell nanocrystals was seen in the transient absorption spectrum upon excitation by a laser pulse (Nd: YAG laser with 150 pulses and 600 mJ of power), which was consistent with the absorption spectra. These photoelectrodes were pre-sensitized by CdTe/ZnTe core/shell NCs that were deposited utilising an FTO/TPD/CdTe-ZnTe/PEDOT: PSS/Ag scaffold of a certain thickness on a transparent mesopous FTO (Fluoride tin oxide). According to PL measurements, the energygap (Eg) of CdTe/ZnTe core/shell NCs is around 2 and 2.5 eV for CdTe-core and ZnTe-shell respectively. A laser ablation-produced CdTe/ZnTe core/shell NCs improved the photoelectrodes' performance by improving the carrier's charge mobility and, therefore, recombination processes inside the NCs along with TPD and PEDOT: PSS polymer ions. A current-voltage (I-V) characteristic, in addition to lighting at 3V, verifies an ideal environment and formation. The surface trapping mechanism was eliminated because of the ZnTe shell's better surface passivation, which considerably slowed down the recombination in the core/shell nanocrystals.
subject: Mathematics
  topic: section
subject: CdTe
  topic: keywords
subject: ZnTe
  topic: keywords
subject: Core/Shell
  topic: keywords
subject: Optical properties
  topic: keywords
subject: Laser ablation
  topic: keywords
subject: Physics
  topic: disciplines
subject: Nano technology
  topic: disciplines
creator: Akeel M. Kadim
creator: Amjed M. Shareef
rights: Copyright (c) 2025 Akeel M. Kadim, Amjed M. Shareef https://creativecommons.org/licenses/by/4.0/
date: 2025-12-15
publication date: 2025-12-15
starting page: 165
ending page: 172

Quantum Chemical Insights into the Electronic, Vibrational and Thermodynamic Properties of Chloro-Substituted Anisole
type: item
description: Anisole, also known as methoxybenzene, is an organic compound with the formula \(CH_{3}OC_{6}H_{5}\). It is a colorless liquid with a sweet, aromatic odor similar to anise seeds and is used as an intermediate in the synthesis of pharmaceuticals, agro-chemicals, and fragrances. This study is about the quantum chemical insight into the Electronic, vibrational, and thermodynamic properties. The study first analyzed the optimized molecular structures and identified different physical properties. The Non-Co-valent Interactions (NCI)-Reduced Density Gradient (RDG) reveal weak hydrogen bonding and strong repulsive interactions. Molecular electrostatic potential mapping shows higher reactivity in chlorine-substituted anisole, with key reactive sites at oxygen, chlorine, and carbon atoms. Anisole has an excitation energy of 5.770 eV and a lower electronegativity of 3.2850 eV, indicating kinetic stability. Para-chloroanisole (PCA) exhibits the lowest energy gap at 5.481 eV and chemical hardness of 2.7405 eV, suggesting high reactivity. The quantum energy levels are observed in the density of States (DOS) spectrum. Due to their electronegative nature, chlorine atoms show positive charges while oxygen atoms, owing to their electron-withdrawing properties, show negative Mulliken charges, respectively, and serve as key reactive sites. In addition to that, Infrared (IR), Raman, and UV-visible spectra reveal different vibration modes and spectral intensities. Thermodynamic functions such as constant pressure (Cp), enthalpy (H), and entropy (S) for all studied molecules increase with temperature.
subject: Mathematics
  topic: section
subject: Anisole
  topic: keywords
subject: Density functional theory
  topic: keywords
subject: Electronic structure
  topic: keywords
subject: Vibrational analysis
  topic: keywords
subject: Thermodynamic parameters
  topic: keywords
subject: Physics
  topic: disciplines
subject: solid state and materials, Physics
  topic: disciplines
creator: Tulsi Ojha
creator: Prakash Man Shrestha
creator: Suresh Prasad Gupta
creator: Krishna Bahadur Rai
rights: Copyright (c) 2025 Tulsi Ojha, Prakash Man Shrestha, Suresh Prasad Gupta, Krishna Bahadur Rai https://creativecommons.org/licenses/by/4.0/
date: 2025-12-15
publication date: 2025-12-15
starting page: 146
ending page: 164

The Effectiveness of Aspergillus fumigatus and A. niger in Biodegrading Petroleum Derivatives in Contaminated Water
type: item
description: Fungi have attracted increasing attention in biodegradation due to their ability to degrade a wide range of substances through a process known as mycodegradation. This study evaluated that Aspergillus niger has a significant effect in biodegrading contaminated water samples. TPH concentrations in water samples before and after treatment with A. nigar ranged from 1,850 to 1,023 μg/l. TPH removal efficiency reached 44.7% with A. niger and 55.05% with A. fumigatus (from1.059 to 0.476 μg/l). The remaining PAHs were analyzed by GC-MS. The 10 not substituted PAHs on the list of important contaminants (EPA 10 PAHs) were the most frequently analyzed PAHs, with concentrations varying from oil to oil. A. fumigatus showed a higher degree of degradation of PAHs compared to A. niger. Treatment unit containing Aspergillus indicates to be effective in removing heavy metals and improving most physical and chemical properties and nutrients in industrial waste waters analyzed.
subject: Mathematics
  topic: section
subject: bioremediation
  topic: keywords
subject: Aspergillus
  topic: keywords
subject: crude oil
  topic: keywords
subject: Gas chromatography
  topic: keywords
subject: Biology
  topic: disciplines
creator: Najwan Abbas Mohammed
rights: Copyright (c) 2026 Najwan Abbas Mohammed https://creativecommons.org/licenses/by/4.0/
date: 2026-03-16
publication date: 2026-03-16
starting page: 80
ending page: 89
doi: 10.22401/

Phytochemical and Antibacterial Evaluation of Pterygota Alata Leaf Extracts Against CSOM Bacteria
type: item
description: The increasing rates of multidrug-resistant (MDR) organisms among patients with chronic suppurative otitis media (CSOM) have caused treatment procedures to become more complex, raising healthcare costs and significantly increasing the time of recovery. Since medicinal plants are the natural repositories for bio-active and secondary metabolites, they are an excellent alternative to antibiotics to combat MDR bacterial strains. This study aims to assess the antibacterial activity and the presence of phytochemicals in the aqueous and methanol leaf extracts of the Indian deciduous tree Pterygota alata against 5 MDR strains of CSOM-causing bacteria: Pseudomonas aeruginosa, Staphylococcus aureus, Escherichia coli, Proteus mirabilis, and Klebsiella pneumoniae. Fresh P. alata leaves were harvested, dried, and extracted with methanol and water. Qualitative and quantitative assessments demonstrated the detection of primary and secondary metabolites. The antibacterial activities were determined using the agar well diffusion method, including minimum inhibitory concentration (MIC), minimum bactericidal concentration (MBC), dose-response, and time-kill studies against CSOM bacterial isolates. Most phytochemicals, except proteins, were present in moderate to high concentrations in aqueous and methanol extracts. The methanol extracts had higher levels of phenolics (85.6 mg/g), flavonoids (42.3 mg/g), tannins (40.8 mg/g), and saponins (36.9 mg/g). Steroids were minimal in both extracts, while alkaloids were moderately present. All extracts showed significant antibacterial activity, particularly the methanol extracts against S. aureus and P. mirabilis (ANOVA, p ≤ 0.05). The effect was concentration-dependent, with rapid bactericidal action observed at higher concentrations. It was further confirmed with one-way ANOVA followed post-hoc Tukey test, there were significant differences among different treatments (p ≤ 0.05), supporting the reliability of the results. Therefore, it can be c…
subject: Mathematics
  topic: section
subject: Pterygota alata
  topic: keywords
subject: Aqueous leaf extracts
  topic: keywords
subject: CSOM causing bacteria
  topic: keywords
subject: Antibacterial efficacy
  topic: keywords
subject: Phytocomeical analysis
  topic: keywords
subject: microbiology
  topic: disciplines
creator: Debidatta Singhsamanta
creator: Shakti Rath
creator: Saumya Ranjan Das
rights: Copyright (c) 2025 Debidatta Singhsamanta, Shakti Rath, Saumya Ranjan Das https://creativecommons.org/licenses/by/4.0/
date: 2025-12-15
publication date: 2025-12-15
starting page: 44
ending page: 54

Evaluation of Generating DNA Profile from Keratinous Tissues
type: item
description: Fragmented DNA samples became serious issue in crime scene and all most result in incomplete DNA profile. Keratinous tissues such as hair and nails contain highly fragmented DNA and could be seen as biological evidence at crime scene. This study aimed to evaluation of generating DNA profile from keratinous tissues. Ten samples (five from hair and five from nails) collected from volunteers. Extraction of DNA was carried out by using PrepFilerTM forensic DNA extraction kit. The quantities of DNA were measured using real-time PCR, while the amplification of eight loci (D13S31, D7S820, D2S1338, D21S11, D16S539, D18S51, CSF1PO, FGA) and amelogenin was performed using the AmpFLSTR™ MiniFiler™ PCR Amplification Kit. The genetic Analyzer 3130 XL system and GeneMapper ID software v.3.2 were used to perform capillary electrophoresis and data analysis. The results indicated that the mean quantities of DNA isolated from hair (3.34 ± 1.7) and the DNA isolated from nails (4.36 ± 3.02). Analysis of MiniFiler results revealed that most of hair samples generated partial DNA profile while all samples of nail produced full profile and the percentage of allele’s appearance for hair samples range between (30%-90%). Whereas, nail samples alleles appearance was 100%. Conclusion, although both nail and hair tissues are subject to DNA fragmentation due to their keratinized structure and cellular composition, nail samples produces more consistent and complete DNA profiles compared to hair samples when analyzed using MiniFiler kit. This is likely attributed to the relatively lower degradation and greater stability of DNA in nails. In contrast, hair samples especially those lacking follicles exhibited a high degree of allele drop-out, particularly in loci with large amplicon sizes.
subject: Mathematics
  topic: section
subject: keratinous tissues
  topic: keywords
subject: crime scene
  topic: keywords
subject: DNA profile
  topic: keywords
subject: Mini-Filer kit
  topic: keywords
subject: forensic , molecular biology
  topic: disciplines
creator: Mohammed M. Al-Zubaidi
creator: Miriam Jasim Sheha
creator: Thoalnoon Younis Salih
creator: Rasha Sadeq Ameen
rights: Copyright (c) 2026 Mohammed M Al-Zubaidi, Miriam Jasim Shehab, Thoalnoon Younis Salih, Rasha Sadeq Ameen https://creativecommons.org/licenses/by/4.0/
date: 2026-03-16
publication date: 2026-03-16
starting page: 54
ending page: 60
doi: 10.22401/

ARIMA-NN Model for Drugs Sales Forecasting in the United States
type: item
description: This study proposes a new version of the Autoregressive Integrated Moving Average (ARIMA) model using Artificial Neural Networks (ANNs) denoted by ARIMA-NN. The new model incorporates a multi-layer perceptron with matrix multiplication within a feed-forward network. The logistic, hyperbolic tangent (tanh), and sigmoid activation functions are used for weight updates in ARIMA-NN. A new forecasting algorithm is proposed, and one-step and multiple-steps forecasting procedures are rigorously analyzed. The proposed model was evaluated against existing forecasting model using performance metrics such as the Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) to assess its effectiveness. The U.S. Census Bureau (www.census.gov) provides a dataset of monthly drug sales spanning ten years (2014-2024), which is utilized in the study. The ARIMA-NN model is applied to generate forecasts for drug sales in the U.S. for the next four years to demonstrate the models' utility and efficacy. All the computations and visualizations are performed using various R packages in version 4.3.2.
subject: Mathematics
  topic: section
subject: ARMA
  topic: keywords
subject: ARIMA
  topic: keywords
subject: ANNs
  topic: keywords
subject: Forecasting
  topic: keywords
subject: Time Series
  topic: keywords
subject: Multi-layer Perceptron
  topic: keywords
subject: Mathematical statistics
  topic: disciplines
creator: Ghadeer Jasim Mohammed Mahdi
creator: Zahraa Ibrahim Al-Share
rights: Copyright (c) 2025 Ghadeer Jasim Mohammed Mahdi, Zahraa Ibrahim Al-Share https://creativecommons.org/licenses/by/4.0/
date: 2025-12-15
publication date: 2025-12-15
starting page: 259
ending page: 269

Study of Charge Density Distributions, Elastic and Inelastic Electron Scattering Form Factors and Size Radii for 24Mg and 28Si Nuclei
type: item
description: Unitary Correlation Operator Method (UCOM) has been used to inspect the ground state properties of 24Mg and 28Si nuclei, such as, charge densities, the root mean square () radii and elastic electron scattering form factors. Inelastic longitudinal electron scattering form factors have been computed for iso scalar or transition ∆T=0 of the () and ( transitions) for the 24Mg and 28Si nuclei. The results of the computations have been discussed, and a comparison of those results with the experimental data has occurred. It was assured that the unitary correlation operator method is suitable for studying the nuclear structure.
subject: Mathematics
  topic: section
subject: Unitary Correlation Operator Method
  topic: keywords
subject: Charge density distribution
  topic: keywords
subject: Elastic and Inelastic Form Factor
  topic: keywords
subject: Nuclear Physics
  topic: disciplines
creator: Zaid M. Abbas
creator: Ghaith N. Flaiyh
rights: Copyright (c) 2025 Zaid M. Abbas, Ghaith N. Flaiyh https://creativecommons.org/licenses/by/4.0/
date: 2025-12-15
publication date: 2025-12-15
starting page: 76
ending page: 82