Journal title Wasit Journal for Pure sciences Indexing Online ISSN Print ISSN 2790-5241 2790-5233 Frequency 4 issues per year DOI prefix 10.31185 Editor in Chief Managing Editor Prof. Dr. Ali Khalaf Hussain , College of Education for Pure Science, Wasit University, Iraq Email: alhachamia@uowasit.edu.iq Prof. Dr. Abdul Hadi M.Alaidi, College of Computer Science and IT, Wasit University, Iraq Email: alaidi@uowasit.edu.iq Organized by Wasit University - College of Computer Science and IT Citation Analysis <a href="https://www.scopus.com/results/results.uri?s=REF%28%22wasit+journal+for+pure+science%22+OR+%22Wasit+J.+Pure+Sci.%22+OR+%22+Wasit+J+Pure+sci%22+OR+%22Wasit+J.+Pure+Sci.%22+OR+%22Wasit+Journal+of+Pure+sciences%22+OR+%22+Wasit+J+Pure+Sci%22+OR+%22+Wasit+J+Pure+Sci%22+OR+%22+Wasit+J.+Pure+Sci.%22+OR+%22+Wasit+J.+Pure+Sci.%22%29&limit=10&origin=searchhistory&sort=plf-f&src=s&sot=b&sdt=b&sessionSearchId=2cd33205ae7d7106b9940c3e5d8db675">Scopus | Google Scholar Acceptance Rate: 40% Review Speed: 90 days Before submission, You have to make sure that your paper is prepared using the WJPS paper Template, or Latex Template has been carefully proofread and polished, and conformed to the author's guidelines. Online Submissions Do you already have a username/password for WJPS? GO TO LOGIN Need a username/password? GO TO REGISTRATION Registration and login are required to submit items online and check current submissions' status.
Therapeutic Effect of Myostatin/Activin Blockage and Dietary Restriction in Modulation of Platelet Activation Markers of Progeroid Mouse Model
Aging-related decline in hematopoietic and platelet function is a hallmark of DNA repair deficiency syndromes, yet the impact of metabolic and pharmacological interventions on platelet biology in this context remains unclear. This study addresses this gap by investigating whether dietary restriction (DR) and myostatin/activin blockade through soluble Activin Receptor Type IIB (sActRIIB) can modulate platelet activation markers—GPIbα and P-Selectin—in a progeroid mouse model (Ercc1Δ/-). While DNA repair-deficient mice exhibited significantly reduced GPIbα expression compared to wild-type controls, sActRIIB treatment showed a modest, though non-significant, improvement. In contrast, DR alone or combined with sActRIIB had negligible effects. P-Selectin levels remained unchanged between mutant and control mice; however, sActRIIB treatment significantly suppressed its expression, indicating a potential anti-inflammatory effect. These findings suggest that myostatin/activin pathway inhibition may offer a partial therapeutic benefit in modulating platelet activation in progeroid models, whereas dietary restriction appears insufficient. It is important to conduct further studies to investigate specific, combinatorial application in the restoration of platelet homeostasis in DNA repair-deficient aging diseases.
Copyright (c) 2026 khalid Alyodawi https://creativecommons.org/licenses/by/4.0
Some Properties of a Subclass Involving Close - to - Convex of Univalent and Multivalent Functions
Our work included studying some subclasses of functions (univalent - multivalent) that are close to convex. which is divide into two parts. First part, we discussed the properties of parameter estimates, the implication relation, distortion theorem, and the radius of convexity of functions a subclass of univalent. Second part of this article, we discuss the same properties for subclasses of multivalent functions defined using the Salagen operator in the unit disc.
Copyright (c) 2026 Nada Mohammed Abbas Abbas https://creativecommons.org/licenses/by/4.0
Assessment of the impact of lipopolysaccharide from multidrug-resistant proteus on the expression of ZapA and UreR virulence genes of Proteus mirabilis
Proteus mirabilis is an opportunistic pathogen implicated in urinary tract infections, with virulence largely attributed to factors such as ZapA, a metalloprotease, and UreR, a regulator of urease activity. Lipopolysaccharides [LPS] are a vital ingredient of the outing Gram-negative bacteria membranes, functioning in both structural integrity and pathogenesis. However, the role of endogenous LPS for expressing the genes of virulence factors in P. mirabilis remains unclear. This study objected to assess the LPS extract from P. mirabilis on the expression of ZapA and UreR genes within P. mirabilis cells. LPS was isolated from cultured P. mirabilis using a hot phenol-water extraction method and applied to fresh bacterial cultures on different levels. Entire RNA was obscure, and expressing the ZapA and UreR quantified via qRT-PCR, with 16S rRNA used as the internal control. Comparative analysis between treated and untreated groups had achieved to investigate the LPS exposure on the target genes. Exposure to extracted LPS significantly led to an upregulation of ZapA and UreR genes expression. These findings suggest LPS may act as an autocrine or paracrine signaling molecule modulating virulence gene expression in P. mirabilis. The results demonstrate that LPS derived from P. mirabilis can modulate the core virulence-associating gene expression, ZapA and UreR, potentially influencing the pathogenicity of P. mirabilis.
Copyright (c) 2026 Abeer Gazaa, Najeeb Hussen https://creativecommons.org/licenses/by/4.0
Drug–Drug Interactions in Outpatient Private Clinic Settings vs. Hospital Settings: A Systematic Review and Comparative Analysis
Drug–drug interactions (DDIs) are a major source of adverse drug events (ADEs) that are potentially preventable in the healthcare system worldwide. The present literature lacks a comparative and rigorous synthesis. The objective of our study was to systematically identify, appraise and synthesize evidence on the prevalence, severity, types, and management outcomes of DDIs occurring between the private clinic and hospital settings, and the factors that contribute to the occurrence of DDIs at the patient and system levels are the objective of our study. PubMed, Scopus, Web of Science and Google Scholar were used for literature search from January 2015 to May 2026. Direct or indirect comparative data on DDIs in private clinic versus hospital outpatient or inpatient setting was required for eligibility. Using the Newcastle–Ottawa Scale (NOS) as well as Cochrane RoB 2.0, risk of bias was determined. Narrative synthesis and data extraction in tables were conducted. Forty-two studies (n ≈ 2.1 million patient records) were included. The prevalence of DDI varied from 10.3%–67.4% in settings. The rates of clinically severe DDIs were significantly higher in hospital than in private clinics (mean 28.4% vs. 15.7%) due to the higher prevalence of multimorbidity and older age of inpatients. The detection rate for DDI, pharmacist interventions and integration of CDSS were much lower at private clinics. The conclusion reported that the DDI are common, clinically important, and occur in unique ways in both settings. Patient complexity results in higher severity DDIs in hospitals, while structural limitations in private clinics result in under-detection. The need for targeted pharmacovigilance, mandatory CDSS adoption and cross-setting medication reconciliation are all very much current priorities.
Copyright (c) 2026 Sarhan Rashid Sarhan, Asmaa Kadhim, Hasanain A.J. Gharban, Saranraj Pazhani https://creativecommons.org/licenses/by/4.0
Entropy Analysis of Cryptographic Keys Using Machine Learning
The strength of cryptography key is the basic ingredient of safe information systems, and it directs the strength of encryption algorithms towards attacks. Evaluation methods that rely on entropy measures alone, e.g. Shannon entropy or min-entropy, show any signs of subtle structure patterns or biases in weak keys. In this paper, a machine learning-based framework of a thorough analysis and classification of cryptographic keys are proposed. The model combines entropy values with statistical characteristics-such as variance, runs, autocorrelation-as well as assessment of various supervised learning models, such as Logistic Regression, K-Nearest Neighbors (KNN), Support Vector machines (SVM) and Random Forest classifier. Experiments performed on a synthetic dataset of 10,000 keys (128-bits and 256 bits) indicate that ensemble-based models especially Random Forest have better accuracy of more than 99 percent, demonstrate stability in a noisy environment as well as generalization between various sizes of keys. Further tests, such as ablation tests, cross-validation sensibility tests, and tests of importance of features prove the paramount importance of integrating entropy and statistical features in order to do successful key classification. The offered solution has been suggested as a scalable, automated, and trustworthy method of cryptographic key strength analysis, and its possible usage is related to security-sensitive systems and mechanisms of key generators.
Copyright (c) 2026 Zamen Abood Ramadaan https://creativecommons.org/licenses/by/4.0
Adaptive Federated Learning Framework for Fair and Privacy-Preserving Educational Analytics
The rapid digitalization of educational environments has led to the large-scale generation of student-related data from online learning platforms, intelligent tutoring systems, and virtual classrooms. While such data enable advanced predictive analytics and personalized learning, they also raise critical concerns related to data privacy, fairness, and ethical use. To address these challenges, this paper proposes an Adaptive Federated Learning (AFL) framework for fair and privacy-preserving educational analytics. Unlike conventional centralized learning approaches, the proposed framework allows multiple educational institutions to collaboratively train predictive models without sharing raw student data. Moreover, AFL incorporates a fairness-aware adaptive aggregation mechanism that dynamically adjusts client contributions based on both local predictive performance and fairness indicators. This strategy improves model robustness and reduces demographic bias under heterogeneous and potentially adversarial data distributions. The effectiveness of the proposed framework is evaluated on three publicly available educational datasets—Student Performance, Predict Students’ Dropout and Academic Success, and the Open University Learning Analytics Dataset (OULAD)—under both normal and label-flipping attack scenarios. Experimental results demonstrate that AFL achieves performance comparable to centralized models while consistently improving fairness and resilience against adversarial behavior. These findings highlight the potential of AFL as a trustworthy and ethically aligned solution for decentralized educational data analytics.
Copyright (c) 2026 Hussein Nasrawi https://creativecommons.org/licenses/by/4.0
Fermat Operational Matrix for Solving Nonlinear Fractional Differential Equations Using Spectral Galerkin Method
This paper presents a truncated series of Fermat polynomials as a quick and effective way to solve fractional differential equations numerically. The suggested method converts the fractional differential equation with its beginning conditions into a set of algebraic equations. This transformation is achieved by using the Galerkin spectral technique in conjunction with the matrix of operations for fractional-order derivatives according to Caputo's definition of Fermat polynomials. The precision, efficiency, and stability of the suggested approach are illustrated through a series of numerical examples. The results also show excellent compatibility with exact solutions even when the exact solution is non-polynomial. In addition, comparisons with previously reported methods confirm the higher performance and reliability of the current strategy.
Copyright (c) 2026 Abdullah Hussein, Ali Khalaf Hussain Al-Hachami https://creativecommons.org/licenses/by/4.0
Molecular Diversity and Antimicrobial Resistance in Clinical Pseudomonas aeruginosa Isolates Associated with Virulence and Biofilm Formation
ABSTRACT: Pseudomonas aeruginosa is a dangerous opportunistic pathogen responsible for a share of nosocomial infections that are often fatal with high morbidity. Its bizarre adaptability, inherent mechanisms of resistance, and capability for biofilm formation significantly contribute to its persistence and complicate effective treatment [1, 2]. The study found the prevalence of P. aeruginosa among broad clinical isolates, assessed its biofilm forming capabilities, mapped the distribution of key virulence genes (lasB, toxA, algD, pvdA) and determined its antibiotic susceptibility profiles. Researchers collected 94 proven P. aeruginosa isolates from a range of clinical sources such as respiratory tract infections, burns, wounds, surgical site infections and catheters. Results presented that the isolates had a strong ability to form biofilms, with most of them showing moderate to strong biofilm production. Moreover, a important presence of virulence genes was renowned among the isolates, exactly lasB (86.2%) and toxA (79.8%). Antibiotic susceptibility testing showed diverse levels of resistance, with Cefotaxime (46.7%) and Aztreonam (30.7%) being the maximum resistant. Polymyxin B (4.0%) was still very effective. These results demonstration how complicated P. aeruginosa is as a pathogen and how significant it is to keep an eye on it and come up with new ways to treat it because it is resistant to many drugs.
Copyright (c) 2026 Haider M. Ali Awad https://creativecommons.org/licenses/by/4.0
Sustainable Green for the Synthesis of TiO₂ Nanoparticles Using Solanum Melongena Extract
In this study, a sustainable and environmentally benign methodology was developed for the synthesis of titanium dioxide (TiO₂) nanoparticles utilizing Solanum melongena (eggplant) extract as a natural reducing and stabilizing agent. The proposed biosynthetic route was intentionally designed to substitute conventional chemical pathways that commonly involve hazardous precursors and high-energy consumption. The synthesized TiO₂ nanomaterials were subjected to comprehensive structural and morphological characterization through X-ray diffraction (XRD), field-emission scanning electron microscopy (FE-SEM), and Fourier-transform infrared spectroscopy (FTIR). XRD patterns verified the formation of a highly crystalline anatase phase with an estimated mean crystallite size of approximately 13.6 nm. The FE-SEM micrographs revealed nearly spherical to quasi-spherical morphologies with an average particle diameter of about 29 nm, indicating that the bio mediated process enabled controlled nucleation and moderate particle-size homogeneity. The FTIR spectra exhibited characteristic Ti–O–Ti stretching vibrations together with residual phytochemical functional groups originating from the eggplant extract, confirming their involvement as surface-capping species that enhanced nanoparticle stability. In addition to the structural investigation, the electrical sensing performance of the TiO₂ nanomaterials toward DNA molecules was evaluated at ambient temperature. A comparative analysis between uncalcined and calcined (400 °C) TiO₂ samples demonstrated a pronounced improvement in sensitivity following calcination. The thermally treated TiO₂ displayed enhanced electrical conductivity, increased surface activity, and improved crystallinity, achieving DNA-sensing sensitivities in the range of 45–70%, compared with 12–18% for the uncalcined samples. The observed enhancement is attributed to the generation of oxygen vacancies and the phase transformation from amorphous to anatase, which collectively facilitated more efficient charge transfer across the TiO₂–biomolecule interface.
Copyright (c) 2026 Samah Abbas Jihad Alrubaee, Haider J. Hassan https://creativecommons.org/licenses/by/4.0
Bayesian Estimation For The Odd Chen–Gamma Distribution Under Asymmetric Loss Functions
In this study, a new two-parameter lifetime distribution called the Odd Chen–Gamma distribution is proposed. The probability density function, cumulative distribution function, reliability function, and several important statistical properties of this distribution are derived. Bayesian analysis is performed using two prior functions for the unknown shape parameter: the exponential (informative) prior and a hypothetical prior. The Bayesian estimator of the shape parameter is obtained under two asymmetric loss functions, namely the De-Groot and the Al-Bayyati loss function. A simulation study is conducted to evaluate the performance of the Bayesian estimators by examining their mean squared errors under different parameter values and various sample sizes.
Copyright (c) 2026 Fatima Mutair Ajil, Awatif Rezzoky Al-Dubaicy https://creativecommons.org/licenses/by/4.0
This paper introduces a new class of functions, termed δ-continuous functions, and investigates their fundamental characterizations and properties. Particular attention is given to their connections with other well-known classes of functions in topology and functional analysis. δ-1-continuity, viewed as a natural extension of classical continuity, provides a broader framework that captures settings where standard continuity may be insufficient. This generalization proves especially relevant in the study of spaces with distinctive structural features or in abstract mathematical contexts. The findings not only enrich the theory of generalized continuity but also highlight the potential applications of δ-1-continuous functions in advancing mathematical analysis.
Copyright (c) 2025 Zahraa Mohsen, Ali Khalaf Hussain https://creativecommons.org/licenses/by/4.0
Cobalt-60 Nuclear Source Decay and Gamma Photon Dose Delivery in Radiosurgery: A Radiobiological Comparison of Single- and Multi-Session Irradiation for meningioma
Gamma Knife radiosurgery (GKRS) using Cobalt-60 sources has found wide application in the treatment of intracranial meningiomas because it is used to deliver highly conformal dose distributions with steep gradients. This study was aimed at performing a radiobiological comparison of single-session and multi-session meningioma cases by including dose rate decay, sublethal damage repair, and analytical modeling of probabilistic outcomes. Methods: One hundred intracranial meningioma cases were studied (single-session, 50 cases; multi-session, 50 cases) in this prospective study at Ghazi Alharriri Gamma Knife Center, Medical Complex, Baghdad, Iraq, between January 2025 and March 2026. Dosimetric parameters and beam-on time were extracted, and radiobiological calculations were made in accordance with the linear-quadratic model. BED, EQD2, dose-rate-corrected BED, and Lea-Catcheside repair factor (G) were calculated. Tumor control probability (TCP) as well as normal tissue complication probability (NTCP) were estimated using logistic and Lyman-Kutcher-Burman models, respectively. The statistical comparisons were performed with independent t-tests. Results: Multi-session treatments demonstrated significantly lower effective dose rates and higher beam-on times (p < 0.01), reflecting time-dependent Cobalt-60 decay effects. Single-session radiosurgery yielded higher BED and EQD2 (p < 0.0001); however, TCP remained comparable between groups (p = 0.312), indicating a dose–response plateau. NTCP was significantly reduced in the multi-session group (p = 0.021). A strong inverse correlation was observed between dose rate and repair factor (r = −0.62, p < 0.001), while beam-on time was negatively correlated with NTCP (r = −0.41, p = 0.01). Conclusion: Time-dependent dose delivery significantly influences radiobiological response in GKSRS. Multi-session treatment achieves equivalent tumor control with improved normal tissue sparing, supporting its role as a physics-optimized strategy for meningioma management.
Copyright (c) 2026 Lubna mahmood https://creativecommons.org/licenses/by/4.0
Luminescent Zinc-Based Metal-Organic Frameworks for Fast and Selective Optical Detection of Pharmaceutical Pollutants in Aqueous Solution
This paper reports the development of luminescent zinc-based metal-organic frameworks (MOFs) as optical sensors for monitoring pharmaceutical pollutants in water specifically diclofenac and ibuprofen. The MOFs were synthesized under solvothermal conditions and exhibited crystalline, microporous structures with strong fluorescent properties, enabling analyte-induced quenching for sensitively detection. Under optimized conditions a rapid response was realized in 2 min with high selectivity towards common interferents. Stern -Volmer analysis revealed that they behaved in a linear manner and their detection limits were 0.8 µg/L and 2.1 µg/L when using diclofenac and ibuprofen respectively. Recovery tests in tap, river and wastewater sample produced 92-106% recovery values which prove to be effective. The sensors have been found to be stable with a 90 % performance when they were used repeatedly. These findings demonstrate luminescent MOFs as high-quality, reusable sensors in seconds of environmental surveillance of new pharmaceutical pollutants.
Copyright (c) 2026 Mohammed Rashid Znad, Mohammad Reza Khakzad https://creativecommons.org/licenses/by/4.0
Fake Instagram Account Detection Using Single and Stacking Ensemble Models on Integrated Static and Temporal Features
This research examines the detection of fake Instagram accounts by comparing single machine learning classifiers with a stacking ensemble model applied to integrated static and temporal features. A dataset of 7,594 accounts was collected over five months using multiple scraping tools, ensuring a balanced representation of real and fake profiles. Key behavioral, engagement, and account-level features were extracted to capture users’ activity patterns. Among the individual classifiers, Random Forest achieved the highest performance; however, the stacking ensemble model outperformed all single models, reaching an accuracy of 0.9888 with superior precision, recall, and F-measure values. The findings demonstrate that integrating temporal metrics with ensemble learning significantly enhances detection accuracy and provides a more reliable approach for identifying fraudulent accounts on social media platforms.
Copyright (c) 2026 Samar Sadeq Hassoun, Nahla A. Flayh https://creativecommons.org/licenses/by/4.0
On Unitary Quasi-Square Equivalence and Related Classes of Operators
This paper introduces and systematically investigates the notion of unitary quasi-square equivalence for bounded linear operators on Hilbert spaces. This equivalence relation, defined through the unitary equivalence of operator squares, provides a classification that preserves essential spectral and structural properties while capturing higher-order similarities not detectable through classical unitary equivalence. We establish that this relation defines a genuine equivalence relation and explore its connections with fundamental operator classes including square normal operators, <!-- [if gte msEquation 12]><m:oMath><m:r><m:rPr><m:nor/></m:rPr>n</m:r></m:oMath><![endif]--> <!-- [if gte vml 1]><v:shapetype id="_x0000_t75" coordsize="21600,21600" o:spt="75" o:preferrelative="t" path="m@4@5l@4@11@9@11@9@5xe" filled="f" stroked="f"> <v:stroke joinstyle="miter"/> <v:formulas> <v:f eqn="if lineDrawn pixelLineWidth 0"/> <v:f eqn="sum @0 1 0"/> <v:f eqn="sum 0 0 @1"/> <v:f eqn="prod @2 1 2"/> <v:f eqn="prod @3 21600 pixelWidth"/> <v:f eqn="prod @3 21600 pixelHeight"/> <v:f eqn="sum @0 0 1"/> <v:f eqn="prod @6 1 2"/> <v:f eqn="prod @7 21600 pixelWidth"/> <v:f eqn="sum @8 21600 0"/> <v:f eqn="prod @7 21600 pixelHeight"/> <v:f eqn="sum @10 21600 0"/> </v:formulas> <v:path o:extrusionok="f" gradientshapeok="t" o:connecttype="rect"/> <o:lock v:ext="edit" aspectratio="t"/> </v:shapetype><v:shape id="_x0000_i1025" type="#_x0000_t75" style='width:5.4pt; height:12pt'> <v:imagedata src="file:///C:/Users/Zpc/AppData/Local/Temp/msohtmlclip1/01/clip_image001.png" o:title="" chromakey="white"/> </v:shape><![endif]--> -quasi-normal operators, hyponormal operators, and various isometric structures. Our main contributions include complete characterization of spectral invariants preserved under this equivalence, demonstration of preservation theorems for advanced operator classes and their <!-- [if gte msEquation 12]><m:oMath><m:sSup><m:sSupPr><m:ctrlPr></m:ctrlPr></m:sSupPr><m:e><m:r><m:rPr><m:nor/></m:rPr>C</m:r></m:e><m:sup><m:r><m:rPr><m:nor/></m:rPr>∗</m:r></m:sup></m:sSup></m:oMath><![endif]--> <!-- [if gte vml 1]><v:shape id="_x0000_i1025" type="#_x0000_t75" style='width:9.6pt;height:12pt'> <v:imagedata src="file:///C:/Users/Zpc/AppData/Local/Temp/msohtmlclip1/01/clip_image003.png" o:title="" chromakey="white"/> </v:shape><![endif]--> -algebraic structure, applications to concrete operator families, and development of decomposition theorems revealing the canonical structure of equivalence classes. The theory developed provides a tool for operator classification with applications to invariant subspace problems, similarity theory, and the structural analysis of non-normal operators.
Copyright (c) 2026 Victor Wanjala https://creativecommons.org/licenses/by/4.0
Immunohistochemical Evaluation of Ki-67 and Galectin-3 as a Diagnostic marker for Thyroid Carcinoma in Wasit Province
Thyroid Cancer is a malignant tumor that arises from the cells of the thyroid gland. Biomarkers can help detect thyroid cancer before obvious clinical symptoms appear, improving early diagnosis. Therefore, the purpose of this study was to assess the role of Ki-67 and Galactin-3 (Gal-3) proteins as a biomarker for thyroid cancer diagnosis and to ascertain how these proteins relate to the type and stage of the tumor. This study includes forty formalin-fixed, paraffin-embedded thyroid carcinoma tissue samples were collected from the archives of Histopathology Department at Al-Karama Teaching Hospital in Wasit Governorate, Iraq which diagnosed by a specialist physician. The streptavidin-peroxidase method was used for immunohistochemical staining. Gal-3 expression was evaluated based on staining intensity and the distribution of positive cells, whereas K-67 expression was evaluated based on the proportion of positively stained nuclei. The mean age of the patients was 44.85 ± 10.3 years, with ages ranging from 24 to 72. Males made about 15% of cases, with women making up the bulk (85%). The most prevalent histological pattern was papillary thyroid carcinoma (85%), which was followed by multifocal papillary thyroid cancer (15%). Stage I diagnoses accounted for 80% of cases, whilst stage II diagnoses made up 20%. 65% of cases had elevated Ki-67 protein levels, which were strongly correlated with the type and stage of the tumor. In 70% of cases, especially papillary thyroid carcinoma, galectin-3 protein levels were substantially positive. They also demonstrated a statistically significant link with the type and stage of the tumor. The findings suggest that Gal-3 and Ki-67 are useful markers for thyroid cancer diagnosis. While Gal-3 may be a crucial diagnostic marker for distinguishing malignant thyroid cancers, Ki-67 shows tumor growth activity and may suggest its aggressiveness.
Copyright (c) 2026 Saja Hussain Delfy https://creativecommons.org/licenses/by/4.0
Hybrid CNN–LSTM Framework for DDoS Detection in 5G-Enabled IoT Environments
The increasing deployment of 5G-based Internet of Things (IoT) infrastructure brings about unparalleled opportunities and the exacerbated threat of malicious Distributed Denial-of-Service (DDoS) attacks. Conventional signature-based or static rule-based intrusion detection systems are still inadequate for the dynamic and high-volume traffic in such systems. In order to address these issues, in this paper, we propose a hybrid model with CNN and LSTM. The network features spatial correlations, which are captured by the CNN layers, and the LSTM units learn sequential dependencies for detecting attack behavior evolution. Experimental evaluations performed on the CICDDoS2019 and BoT-IoT datasets show how each module helps, leading to an overall detection accuracy of more than 99% and low false positive rates, and classification latency in real time, 19.5 ms for CICDDoS2019 and 13.6 ms for BoT-IoT), comparisons to relevant existing machine and deep learning baselines establish the trade-off made between accuracy, scalability and practical deployment efficiency. The results show that the proposed model is a suitable and practical choice for protecting 5G-enabled IoT systems against DDoS attacks.
Copyright (c) 2026 Noor Alyassiri, Mohammed Mahdi Salih Altufaili, Fatima Adel Nama https://creativecommons.org/licenses/by/4.0
On Nano g-Connectedness Via Graph with Medical Application
The importance of nano-topology via graphs lies in its ability to represent data within a small yet meaningful topological framework, which enhances the accuracy of classification and decision-making, and supports comparison and categorization. This makes any model applicable in various fields such as healthcare and data analysis. The main objective of this paper is to introduce a new concept of nano-connectivity, called nano-g connectedness via graph. Which defined as the disjoint union of any pair of open sets. We also present a new application to identify the main factors contributing to atherosclerosis.
Copyright (c) 2026 Ahmed Hussien Nasir, Nisreen Abd Alokbi https://creativecommons.org/licenses/by/4.0
Interleukin-6 Dynamics in Host Immune Response: A Cross-Species Study in Humans and Camels During Coronavirus Infections
This study investigates the role of interleukin-6 (IL-6) as a key pro-inflammatory cytokine in coronavirus-infected humans and camels. A total of 75 serum samples from each species were analyzed using ELISA. The results revealed a significant elevation of IL-6 levels in infected individuals compared to controls (P<0.0001), indicating a strong inflammatory response. Notably, this is the first study to quantify IL-6 protein levels in dromedary camels during natural coronavirus infection, addressing a gap in camel immunology. The findings underscore IL-6 as a critical biomarker of inflammation across species. Further research is warranted to explore its mechanistic role in disease severity.
Copyright (c) 2026 Ibrahim Hasan, Hussein A. Mohamed, Rasha M. Othman https://creativecommons.org/licenses/by/4.0
A Continuum Model Based on SIR Equations for Epidemic Spread Analysis
To comprehend how epidemics develop and assess the efficacy of medical treatments, infectious disease modeling is crucial. The SIR model, which separates the population into susceptible, infected, and recovered groups, is one example of the mathematical and statistical models that scientists and policymakers use to describe the dynamics of infection transmission among individuals within a society. These models may also be expanded to incorporate other components, such vaccination, alterations in social behavior, and the results of medical treatments. This work focuses on analyzing the spread of Oropouche fever using the SEIR model with a protective factor that simulates the impact of interventions. The results demonstrate how interventions contribute to reducing the number of infections and delaying the peak of the epidemic. The work also examines the use of the SIRD model in two versions: the classic (without vaccination) and the modified (with vaccination). The numerical results clearly demonstrate the role of vaccination in reducing morbidity and mortality rates, highlighting the importance of mathematical modeling in designing effective strategies to combat epidemics.
Copyright (c) 2026 Alhusna Baqir, Ali Hussein Shuaa https://creativecommons.org/licenses/by/4.0
Solving Linear Programming Problems Using Sensitivity Analysis and Heptagonal Ranking Function
This research presents an integrated approach that combines sensitivity analysis with fuzzy logic to address uncertainty in operations research models. The study focuses on the right-hand side (RHS) of constraints as a key parameter subject to variation. To capture this uncertainty, a symmetric heptagonal fuzzy membership function is proposed, where the seven representative values are governed by a single weight parameter (r). A corresponding fuzzy ranking function is developed to transform the fuzzy outcomes into comparable crisp values. The methodology is applied to two illustrative linear programming examples drawn from textbooks, covering both maximization and minimization problems. The results demonstrate that the fuzzy ranking approach, particularly under specific weight configurations, provides more robust and realistic solutions than traditional sensitivity analysis. These findings confirm the effectiveness of integrating fuzzy logic into sensitivity analysis for enhancing decision-making in linear programming under uncertainty.
Copyright (c) 2026 Aya Safaa Fadhil, Iden Hassan Al-kanani https://creativecommons.org/licenses/by/4.0
Fabrication of a Nanocarbon-Reinforced Nanoclay Membrane for Purification of Drinking Water Contaminated with Escherichia coli
Ultrafiltration systems are considered clean and environmentally acceptable for removing bacteria and contaminants from drinking water. This study used poly sulfone polymer (PSU), DMF, Kaolinite Nanoclay with carbon nanoparticles synthesized from date seeds using reverse-phase technology. In this case, the performance of an ultrafiltration (UF) membrane was improved. Carbon nanoparticles (0, 0.025, 0.050, and 0.075%) were examined, and the polymer concentration was maintained at 17%. The membrane was tested for its ability to remove Escherichia coli from contaminated drinking water. FTIR, AFM, SEM, and EDX tests were used to characterize the membrane composition and structure. As the carbon nanoparticle concentrations varied, the membrane's morphology changed. Various factors were also studied, such as the membrane's ability to remove bacteria from drinking water. The synthesis of membrane (nanofilm) was confirmed using FTIR which conformed presence of active groups responsible for the synthesis process. AFM show revealed an array of homogeneous particles with a regular surface, SEM show a smooth spherical appearance with a diameter range of the particles between 27.69-63.74 nm, EDX spectra shown the main components of the extract were carbon (C), and oxygen (O), , with percentages of 64.8%, and 24%, respectively. The presence of minor components such as Al, Si, S, and Cl with percentages of 0.6% , 0.7% , 8.7%, and 0.3%, respectively. The results of removing contaminated bacteria from drinking water using membranes indicated significant statistical differences (P≤0.05) between the membranes. The efficiency of the membranes was in the following order: F4>F3>F2>F1 compared with sampled without treatments. The study demonstrated that the fabricated nanoclay membrane reinforced with nanocarbon exhibited high efficiency in removing Escherichia coli from contaminated drinking water.
Copyright (c) 2026 Batool Sh. Razij, Mohammed M. Sharqi, Mazin A. Alalousi https://creativecommons.org/licenses/by/4.0
Real-Time Lightweight Emotional Face Recognition Framework Based on CNN Algorithms
In this study, emotional face recognition uses the CNN algorithm. CNN is employed because of its ability to process local tissue and high-resolution connections. This design is planned to authenticate emotion scores for real-time and user-friendly implementations. The preliminary work begins in the neighboring part of the study. Software is utilized to preprocess the data in this study. A CNN model is created using a framework. The process consists of three phases: preprocessing, classifying, and evaluating data. The system was tested on several datasets. The lightweight CNN's performance for training and testing images showed approximately 88.67%. The performance of the system was also compared with existing methods. The research highlights the CNN model's ability to provide state-of-the-art performance in real-time applications, with potential implications for medical and safety applications. However, limitations such as data imbalance and a lack of multimodal approaches were identified for future exploration.
Copyright (c) 2024 Suryanti Awang, MOHAMMED AHMED TALAB https://creativecommons.org/licenses/by/4.0
Fractional Diffusion Equations Solved via Log–Laplace Residual Power Series
In this paper, fractional diffusion equations of Caputo-Hadamard presented as interesting classes of fractional differential equations have not studied before. For the first time, the solution to a diffusion equation of this type was calculated. Therefore, it is considered a new addition to the diffusion equation with the presence of this form of fractional derivatives, with its initial conditions. Additionally, this paper presents a suitable Laplace logarithmic formula for the given fractional equation, derived from the generalized Laplace formula and its established conditions. This also relies on the formula for the fractional derivative as a transformation. The first time this type of fractional derivative was established, it helped in finding an approximate formula for the solution. The residual power series method used is effective in solving many fractional equations and was even more effective when used with the Laplace logarithmic formula. The Log(t+1) –Laplace residual power series method combines the two concepts, formulating and evaluating the method, shown that from any changing of the values of the parameters involving in formulation of derivative as well as the values of fractional order which found in tables and figures for illustrative examples which illustrates the presented method.
Copyright (c) 2025 Ali Zeki, Sameer Qasim Hasan https://creativecommons.org/licenses/by/4.0
Marine Predator Optimized BiLSTM Framework for Real-Time Intrusion Detection in IoT Environments
The rapid expansion and interconnectivity of Internet of Things (IoT) environments have intensified the risk of advanced cyber-attacks, necessitating the development of intelligent and resource-efficient Intrusion Detection Systems (IDS). This study introduces a novel hybrid IDS framework that integrates the Marine Predators Algorithm (MPA) with a Bidirectional Long Short-Term Memory (BiLSTM) network to enhance both detection accuracy and computational efficiency. Within the proposed model, MPA is employed for feature selection and hyperparameter optimization, thereby refining the learning dynamics of the BiLSTM architecture. Experimental evaluations conducted on two benchmark IoT datasets, CICIoT2023 and TON_IoT, demonstrate that the MPA-BiLSTM model consistently achieves detection accuracies exceeding 99.5%, while maintaining low inference latency and minimal memory consumption—characteristics that ensure suitability for real-time edge deployment. Additionally, SHAP-based explainability mechanisms are integrated to provide interpretability of feature importance, thereby fostering transparency and trust in the decision-making process. The results confirm that the synergistic integration of MPA with BiLSTM significantly improves both predictive performance and operational efficiency, establishing the proposed framework as a scalable and practical solution for IoT security.
Copyright (c) 2025 Huda Kadhum Ayoob, Haneen Hasan Hadi Rubaye, Sarah Hayder Hashim https://creativecommons.org/licenses/by/4.0
Experimental Analysis of Random Forest and LSTM Models for Optimizing CPU Efficiency in Cloud Computing
Cloud computing provides scalable and on-demand computational resources; nevertheless, effective utilization of the CPU is a critical issue because insufficient provisioning can result in higher latency and increased energy consumption. This research aims to measure, assess, and optimize CPU performance in cloud systems through the use of two machine learning models, namely, Random Forest (RF) and Long Short-Term Memory (LSTM), and subsequently using the Multi-Objective Grey Wolf Optimizer (MOGWO) to optimize the hyperparameters of the models to predict time series. The models were evaluated on the Google 2019 cluster trace using common metrics (Accuracy, Precision, Recall, and F1). The experimental findings demonstrate that optimization using MOGWO is an effective method for enhancing the performance of the models. Specifically, the accuracy of the Random Forest model increased from 65.15% to 89.70%, while the LSTM model improved from 95.02% to 98.60%, with consistent gains in precision, recall, and F1-score. These results verify the usefulness of the optimized models in forecasting the patterns of CPU usage and optimizing the use of CPU in cloud computing systems.
Copyright (c) 2025 Sajjad Adnan Ajeel, Sundos A. Hameed https://creativecommons.org/licenses/by/4.0
Characterization of Group of Invertible Elements of Six Index Zero Completely Primary Finite Rings of Characteristic p
The study of finite extension of Galois rings in the recent past have given rise to commutative completely primary finite rings that have attracted much attention as they have yielded important results towards classification of finite rings into well-known structures. In this paper, we give a construction of a class of completely primary finite ring<!-- [if gte vml 1]><v:shapetype id="_x0000_t75" coordsize="21600,21600" o:spt="75" o:preferrelative="t" path="m@4@5l@4@11@9@11@9@5xe" filled="f" stroked="f"> <v:stroke joinstyle="miter"/> <v:formulas> <v:f eqn="if lineDrawn pixelLineWidth 0"/> <v:f eqn="sum @0 1 0"/> <v:f eqn="sum 0 0 @1"/> <v:f eqn="prod @2 1 2"/> <v:f eqn="prod @3 21600 pixelWidth"/> <v:f eqn="prod @3 21600 pixelHeight"/> <v:f eqn="sum @0 0 1"/> <v:f eqn="prod @6 1 2"/> <v:f eqn="prod @7 21600 pixelWidth"/> <v:f eqn="sum @8 21600 0"/> <v:f eqn="prod @7 21600 pixelHeight"/> <v:f eqn="sum @10 21600 0"/> </v:formulas> <v:path o:extrusionok="f" gradientshapeok="t" o:connecttype="rect"/> <o:lock v:ext="edit" aspectratio="t"/> </v:shapetype><v:shape id="_x0000_i1031" type="#_x0000_t75" alt="" style='width:16pt; height:16pt;mso-width-percent:0;mso-height-percent:0;mso-width-percent:0; mso-height-percent:0' o:ole=""> <v:imagedata src="file:////Users/hadi/Library/Group%20Containers/UBF8T346G9.Office/TemporaryItems/msohtmlclip/clip_image001.wmz" o:title=""/> </v:shape><![endif]--> <!-- [if gte mso 9]><xml> <o:OLEObject Type="Embed" ProgID="Equation.DSMT4" ShapeID="_x0000_i1031" DrawAspect="Content" ObjectID="_1819869786"> </o:OLEObject> </xml><![endif]-->of characteristic<!-- [if gte vml 1]><v:shape id="_x0000_i1030" type="#_x0000_t75" alt="" style='width:16pt;height:13pt;mso-width-percent:0; mso-height-percent:0;mso-width-percent:0;mso-height-percent:0' o:ole=""> <v:imagedata src="file:////Users/hadi/Library/Group%20Containers/UBF8T346G9.Office/TemporaryItems/msohtmlclip/clip_image003.wmz" o:title=""/> </v:shape><![endif]--> <!-- [if gte mso 9]><xml> <o:OLEObject Type="Embed" ProgID="Equation.DSMT4" ShapeID="_x0000_i1030" DrawAspect="Content" ObjectID="_1819869787"> </o:OLEObject> </xml><![endif]-->whose subsets of zero divisors <!-- [if gte vml 1]><v:shape id="_x0000_i1029" type="#_x0000_t75" alt="" style='width:31pt;height:20pt; mso-width-percent:0;mso-height-percent:0;mso-width-percent:0; mso-height-percent:0' o:ole=""> <v:imagedata src="file:////Users/hadi/Library/Group%20Containers/UBF8T346G9.Office/TemporaryItems/msohtmlclip/clip_image005.wmz" o:title=""/> </v:shape><![endif]--> <!-- [if gte mso 9]><xml> <o:OLEObject Type="Embed" ProgID="Equation.DSMT4" ShapeID="_x0000_i1029" DrawAspect="Content" ObjectID="_1819869788"> </o:OLEObject> </xml><![endif]--> satisfy the condition <!-- [if gte vml 1]><v:shape id="_x0000_i1028" type="#_x0000_t75" alt="" style='width:150pt;height:23pt; mso-width-percent:0;mso-height-percent:0;mso-width-percent:0; mso-height-percent:0' o:ole=""> <v:imagedata src="file:////Users/hadi/Library/Group%20Containers/UBF8T346G9.Office/TemporaryItems/msohtmlclip/clip_image007.wmz" o:title=""/> </v:shape><![endif]--> <!-- [if gte mso 9]><xml> <o:OLEObject Type="Embed" ProgID="Equation.DSMT4" ShapeID="_x0000_i1028" DrawAspect="Content" ObjectID="_1819869789"> </o:OLEObject> </xml><![endif]-->. The ring <!-- [if gte vml 1]><v:shape id="_x0000_i1027" type="#_x0000_t75" alt="" style='width:12pt;height:13pt;mso-width-percent:0; mso-height-percent:0;mso-width-percent:0;mso-height-percent:0' o:ole=""> <v:imagedata src="file:////Users/hadi/Library/Group%20Containers/UBF8T346G9.Office/TemporaryItems/msohtmlclip/clip_image009.wmz" o:title=""/> </v:shape><![endif]--> <!-- [if gte mso 9]><xml> <o:OLEObject Type="Embed" ProgID="Equation.DSMT4" ShapeID="_x0000_i1027" DrawAspect="Content" ObjectID="_1819869790"> </o:OLEObject> </xml><![endif]-->is constructed over its subring <!-- [if gte vml 1]><v:shape id="_x0000_i1026" type="#_x0000_t75" alt="" style='width:79pt;height:22pt; mso-width-percent:0;mso-height-percent:0;mso-width-percent:0; mso-height-percent:0' o:ole=""> <v:imagedata src="file:////Users/hadi/Library/Group%20Containers/UBF8T346G9.Office/TemporaryItems/msohtmlclip/clip_image011.wmz" o:title=""/> </v:shape><![endif]--> <!-- [if gte mso 9]><xml> <o:OLEObject Type="Embed" ProgID="Equation.DSMT4" ShapeID="_x0000_i1026" DrawAspect="Content" ObjectID="_1819869791"> </o:OLEObject> </xml><![endif]--> as an idealization of the <!-- [if gte vml 1]><v:shape id="_x0000_i1025" type="#_x0000_t75" alt="" style='width:15pt;height:18pt;mso-width-percent:0;mso-height-percent:0; mso-width-percent:0;mso-height-percent:0' o:ole=""> <v:imagedata src="file:////Users/hadi/Library/Group%20Containers/UBF8T346G9.Office/TemporaryItems/msohtmlclip/clip_image013.wmz" o:title=""/> </v:shape><![endif]--> <!-- [if gte mso 9]><xml> <o:OLEObject Type="Embed" ProgID="Equation.DSMT4" ShapeID="_x0000_i1025" DrawAspect="Content" ObjectID="_1819869792"> </o:OLEObject> </xml><![endif]-->- modules. A thorough determination and classification of the structure of the group of invertible elements using fundamental theorem of finitely generated abelian groups is given.
Copyright (c) 2025 Hezron Were, Mr. Nicholas Waweru, Dr. Edward Njuguna, Dr. John Matuya https://creativecommons.org/licenses/by/4.0
Comparison Between Different Probability Distributions for Modeling Exchange Rate Volatility Behavior in Oil Countries for the Period 1990 – 2022
this study examines the distributional properties of exchange rate volatility for major oil-exporting developing economies from 1990-2022. Three probability distributions [ Normal, Fr'echet, and Log Normal] are compared using moment method and maximum likelihood approaches.The Bayesian information criterion (BIC) and the Akaike information criterion (AIC) are used to assess goodness-of-fit. The results indicate that the Normal distribution tends to provide the greatest fit for many countries [Iraq, Kuwait, Libya, Iran, Algeria, Oman, and Bahrain]. The Log Normal distribution is found to be optimal for[ Saudi Araia, Qatar, and Egypt] , while the Fr'echet distribution fits best only for United Arab Emirates. This analysis provides insights into the underlying distributional characteristics of exchange rate returns in these countries, which can inform appropriate model selection for volatility forecasting and risk management applications . The research adds to existing literature by conducting a entire distributional comparison across a broader set of oil- exporting developing economies over an extended time.
Copyright (c) 2025 Awatif Al-Dubaicy https://creativecommons.org/licenses/by/4.0
Synthesis, Characterization and Study of Liquid Crystal Behavior of Linear-Shaped Mesogens Containing Cyano and Alkyl as a Terminal Groups
A novel series of liner-shaped liquid crystalline compounds containing thiazolidine-2,4-dione moieties with cyano and alkyl as terminal groups were synthesized and characterized. The molecular design incorporated a thiazolidine-2,4-dione unit linked to flexible alkyl chains via Knoevenagel condensation, yielding mesogens with varying terminal lengths. Structural confirmation was achieved through FT-IR, ¹H-NMR, and mass spectrometry. Mesomorphic properties were investigated using polarized optical microscopy (POM) and differential scanning calorimetry (DSC). All compounds [V] 4,5,6,8 exhibit liquid crystal properties, while, compound [V]3 do not show mesomorphic behavior. Odd-even effects were observed in transition temperatures, highlighting the influence of alkyl chain length on mesophase stability.
Copyright (c) 2025 Hassan Jabori, Nisreen H. Karam https://creativecommons.org/licenses/by/4.0
Indirect Spectrophotometric Determination of Nitrate Ion in Groundwater Using an Organic Reagent
Low river water levels in summer and low rainfall in winter have led to desertification, leading to widespread use of groundwater in many areas of Iraq, especially in the southern and central regions. Groundwater is considered an alternative solution to address desertification, but in reality, many health problems have emerged due to the ions present in groundwater, which cause numerous diseases. Among these ions studied in this research is the nitrate ion (NO3⁻). This spectroscopic method was proposed to determine the concentration of nitrate ions in groundwater. Eriochrome Black T (EBT) colorimetric detector was used as a spectroscopic detector after complexing the detector with silver nitrate to determine the nitrate ion in groundwater. Several parameters and optimal conditions for this reaction were studied, and the assessment of nitrate levels was found to be consistent with the linear equation of the Beer-Lambert law in the range of 0.5–5.0 mg/L at a wavelength of (530) nm. When plotting the calibration curve, good linearity was recorded (R2 = 0.9979). The limits of detection (LOD) and quantification (LOQ) of the method were determined to be 0.269 and 0.816 mg/L, respectively, based on the standard deviation values. The precision measured in terms of relative standard deviation (RSD) over the specified time period at five concentration levels was less than 6.7%. The recovery rate was satisfactory, ranging from 96 to 103, Sandell's sensitivity equal to (0.0263) μg.cm-2. The rationale for using spectrophotometric methods lies in their simplicity of operation, low cost, and applicability in laboratories with limited resources, as opposed to more advanced techniques such as HPLC or LC-MS. Based on these results, the method was approved for the determination of nitrate ions.
Copyright (c) 2025 Ryadh mohammed https://creativecommons.org/licenses/by/4.0