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 Assist. 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.
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.
Keywords: Cloud computing, CPU efficiency, Random Forest, LSTM, machine learning, resource optimization, performance prediction, time-series analysis.
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.
Completely Primary Finite Rings, Group of Invertible Elements, Six Index Zero
Copyright (c) 2025 Hezron Were, Mr. Nicholas Waweru, Dr. Edward Njuguna, Dr. John Matuya 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.
liquid crystal, heterocyclic, Nematic phase, Smectic phase
Copyright (c) 2025 Hassan Jabori, Nisreen H. Karam https://creativecommons.org/licenses/by/4.0
Total Italian Domination: Structural Results on Middle Graphs of Standard Families
If we have graph , an Italian dominating function (IDF) is defined as a mapping satisfying the condition, if for any vertex must be have neighbor there is no fewer than 1 vertex to be or no fewer than 2 vertices where The weight of a (IDF) is the sum of all these functions for all vertices . And the minimum weight selected from overall (IDF) of and indicated by A total Italian dominating function (TIDF) is an (IDF) if the collection of non-zero elements, each of which is contiguous to at least one non-zero element. A minimum weight of any (TIDF) is referred to as a total Italian domination number indicated by . We commenced the study of (TIDF) of graph and the graph can be issued by add a new vertex between every two old vertices in and draw the edges between every two added vertices provided that there exist common vertex binds them, we called middle graph of . For selected standard graph families. The accurate numerical values of these graph-related parameters were established. We determined these parameters' exact values.
Italian domination, total Italian domination, Middle graph
Copyright (c) 2025 Maryam ALTABATABAII https://creativecommons.org/licenses/by/4.0
Computational Approaches to Studying Reaction Mechanisms and Transition States in Quantum Chemistry
The Computational chemistry plays a crucial role in understanding reaction mechanisms and transition states at the atomic level. Quantum mechanical methods, particularly Density Functional Theory (DFT), provide insights into electronic structures, energy landscapes, and reaction kinetics. This study explores computational techniques such as Transition State Theory (TST), the Nudged Elastic Band (NEB) method, and post-Hartree-Fock approaches to identify reaction pathways and energy barriers. Molecular Dynamics (MD) simulations further examine reaction dynamics over time under various conditions. This analysis of model reactions highlights key transition states and activation energies, demonstrating that DFT-based methods balance computational efficiency and accuracy. NEB simulations effectively mapped minimum energy paths, while TST calculations provided reliable reaction rate constants. The integration of time-dependent DFT (TD-DFT) enabled the study of excited-state reaction dynamics, crucial for photochemical processes. These findings confirm that quantum mechanical simulations can accurately describe chemical transformations, aiding in the design of novel catalysts, materials, and pharmaceuticals.
Computational Chemistry, Reaction mechanisms, Transition states, Density Functional Theory (DFT).
Copyright (c) 2025 Sarah Badri Jasim, Khalidah H. M. Al Furaiji, Asam Hussein Ali https://creativecommons.org/licenses/by/4.0
AI in Medical Imaging & Diagnostics: review
ABSTRACT: The application of artificial intelligence (AI) has transformed medical diagnostics for the better with the adoption and evolution of radiology, histopathology, clinical laboratory testing, robotic surgery, and expert systems. The implementation of deep learning algorithms using AI, such as Convolutional Neural Networks (CNNs), Vision Transformers (ViTs), and Generative Adversarial Networks (GANs), have outperformed humans in the analysis of medical images, tumor categorization, and biomarker detection. AI powered biopsy systems, which are a type of robotic assisted diagnostics, have improved the accuracy and reduced the invasiveness of the procedure, which in return, enables for better detection of diseases at earlier stages. The use of pipetting robots and automated blood analyzers for AI powered automation of clinical lab diagnostics improves the speed and volume of diagnostic assays while reducing the rate of human error. Additionally, AI powered expert systems, like OncoKB for the analysis of genetic mutations and deep mind’s AlphaFold for predicting protein structures, are advancing precision oncology and personalized medicine by offering non-biased treatment suggestions. The issues that impede the further integration of AI in diagnostics include data diversity, model generalization, obtaining legal certification, and the absence of XAI which would heighten clinician acceptance. To overcome these barriers, there needs to be standard validation frameworks, federated learning for privacy-centric AI training, and multimodal AI that incorporates medical images, genomic data, and EHRs. Emerging directions in self-supervised learning (SSL), active AI robotics, and human-machine interaction will likely improve the precision of diagnoses, automate clinical processes, and expand healthcare access around the world. This review outlines the role of AI in transforming medical diagnostics while analyzing existing obstacles, emerging possibilities, and recommendations for AI in clinical decision support systems.
Artificial Intelligence (AI), Medical Diagnostics, Deep Learning, Computer-Aided Diagnosis (CAD), Convolutional Neural Networks (CNNs), Vision Transformers (ViTs), Explainable AI (XAI), Generative Adversarial Networks (GANs), Robotic-Assisted Biopsy, Precision Oncology, Automated Blood Analyzers, Digital Pathology.
Copyright (c) 2025 Saif Hameed Abbood Al-Waeli1, Haza Nuzly bin Abdul Hameed https://creativecommons.org/licenses/by/4.0
The relationship between the presence of Prevotella intermedia and Porphyromonas gingivalis and increased severity of gingivitis
ABSTRACT: The study aimed to analyze the relationship between the presence of P.intermedia and P.gingivalis and the increased severity of gingivitis. The results are consistent with previous studies that demonstrated the multiplicity of periodontal pathogens and their varying prevalence according to geographical, genetic, and environmental criteria, confirming that the use of molecular analysis techniques such as polymerase chain reaction provides high accuracy in detecting disease-causing bacteria and contributes to a deeper understanding of how the presence of these microbes is associated with the clinical development of gingivitis and periodontitis.
Keywords: P. gingivalis, P. intermedia, Real-Time Quantitative Polymerase Chain Reaction
Copyright (c) 2025 Hodaa Qassim, Rana Salih Al-Taweel https://creativecommons.org/licenses/by/4.0
Numerical Simulation of a Nonlinear Predator-Prey System with Robin Boundary Conditions
This study presents a numerical simulation of a nonlinear predator-prey system described by a reaction-diffusion model within a convex, open domain, subject to Robin boundary conditions. The Finite Element Method (FEM) is employed to discretize and solve the system, offering a practical approach to capture the spatiotemporal dynamics of predator-prey interactions. Furthermore, an error estimation is derived to evaluate the accuracy of the numerical approximation in comparison to the exact continuous solution. The results confirm the reliability and efficiency of the proposed numerical scheme, particularly in handling the complexities introduced by the Robin boundary conditions.
Copyright (c) 2025 Ghassan Al-Juaifri, Huda Al-Maliky https://creativecommons.org/licenses/by/4.0
Assessment of Testosterone Levels in Tobacco Smokers, Dependence Over the Long Term with Some Haemato-Biochemical Parameters
Smoking is considered a pervasive global concern, negatively affecting health and resulting in several diseases, causing millions of fatalities annually. The purpose of this research was to determine how blood smokers' testosterone levels, blood parameters, renal function, cholesterol, triglycerides, and liver enzymes were affected by heavy and chronic tobacco use. Participants (n =60) were obtained from a population cohort of men in Al-Ramadi city aged 20-63 years , Smokers (n=30) have been addicted to smoking for 10 years or more with number of 15-40 cigarette/ day . The subjects answered a detailed survey on their health, therapy or drug intake, and other symptoms or disease. The sex hormone, RBC Count, Hb, HCT, MCV, MCH, MCHC, WBC Count, Platelets, renal function, lipid profiles, ALP,AST and ALT were measured. Our findings have shown a substantial statistical difference in blood total testosterone levels (p < 0.001) among chronic smokers and non-smokers, with lower levels observed in the former group. 1.653±0.097 and 5.980±0.195 respectively , Cigarette smoking adversely affects Haematological parameters ( count of red blood cell , hemoglobin, hematocrit, mean corpuscular volume, mean corpuscular haemoglobin concentration, total leukocyte count) demonstrated a statistically significant increase (p < 0.05). No significance variations are observed on mean corpuscular haemoglobin and platelets (p > 0.05). The findings indicated a highly substantial increase in the levels of urea and creatinine (p<0.001), Furthermore lipid and liver enzymes it was also revealed that it a highly significant elevated (p< 0.001). Therefore, the current investigation indicates detrimental consequences of prolonged smoking on testosterone level in serum , hematological variables , moreover smoking are a risk factor for kidney disorders indicated by urea and creatinine , dyslipidemia was found including change in total cholesterol and triglyceride finally liver enzymes abnormalities were recorded in our study including ALP,AST and ALT in the addicted smokers
Tobacco smoking, Testosterone, Blood parameters, Renal function, Cholesterol, liver function
Copyright (c) 2025 Nbaa Mutea Abid Al Alh , Asmaa Wajeh Jumaa, Nagam Khudhair https://creativecommons.org/licenses/by/4.0
Recurrent Neural Network Optimized by Grasshopper for Accurate Audio Data-Based Diagnosis of Parkinson's Disease
Proposed here is a speech-based diagnostic framework for detecting Parkinson's disease that utilizes a Long Short-Term Memory neural network and the Grasshopper Optimization Algorithm. The framework aims to improve the detection of PD while ensuring accurate and efficient classification of speech-based signals. Incorporated within the system is a dimensionality reduction technique called Linear Discriminant Analysis. This approach allows the system to optimally utilize the features extracted from the given speech signal while ensuring that all the conditions necessary for successful classification are met. The LSTM neural network serves as the core deep learning model for this framework. It is trained on the speech signals produced by both healthy individuals and those with PD, allowing it to detect the class of a given speech signal based on the conditions necessary for successful classification. We assess the suggested technique on two speech datasets that are publicly available: NeuroVoz, a Castilian-Spanish body of work, and EWA-DB, a database in the Slovak language. The classification accuracy of our model on NeuroVoz is 99.45%, while on EWA-DB it is 99.71%. Moreover, these results exceed those from several contemporary approaches that were also tested on these two datasets. We interpret our results as strong evidence that uniting deep learning with nature-inspired optimization does yield an effective tool for providing, in a non-invasive way, a diagnosis of early-stage Parkinson's across diverse linguistic contexts.
Grasshopper Optimization Algorithm (GOA)
Copyright (c) 2025 Saif Wali Ali Alsudani, Ghassan Khudair Saud https://creativecommons.org/licenses/by/4.0
Evaluation of ADH4 gene expression and hematological parameters as biomarkers for the pathogenesis of ITP in the pediatric
This study investigates the role of the ADH4 gene expression and hematological biomarkers in the pathogenesis of Immune Thrombocytopenic Purpura (ITP) in pediatric patients. The study involved 100 children, 50 with ITP and 50 healthy controls, to evaluate blood parameters and ADH4 gene expression. Results showed the mean white blood cell (WBC) count was significantly lower in ITP patients (8.11 ± 0.73) compared to controls (11.94 ± 0.69), Similarly, lymphocyte counts were significantly reduced in ITP patients (3.29 ± 0.43) versus controls (5.65 ± 0.42), The platelet count was markedly lower in ITP patients (26.18 ± 2.77) compared to controls (277.40 ± 10.74), On the contrary, The results show there was a non-significant difference between ITP patients and healthy individuals according to both neutrophil count and hemoglobin (Hb) levels (P < 0.05), while, ADH4 gene expression was significantly higher in ITP patients shown The mean 13.29, 1.00 between the ITP patients and Control respectively, suggesting its involvement in immune dysregulation. These findings highlight the potential of the ADH4 gene and some hematological parameter as a biomarker and therapeutic target in ITP, emphasizing the need for personalized treatment approaches
Copyright (c) 2025 Hayder Dawood saleem, Muthana Ibrahim Maleek https://creativecommons.org/licenses/by/4.0
A Study of a New Class of Meromorphic Univalent Functions Through Subordination Applications
In this research, I wanted to create a new beautiful class defined by subordination and the integral operator and the combination between them and I named it so that I inferred results from the geometric properties of this nice class in terms of studying the radius of convexity and estimating the coefficient and other new results. I also presented the previous information related to the distinguished researchers who before me studied the subordination and the integral operator that I used in my beautiful research.
Meromorphic Functions, Integral Operator, Coefficient Bounds, Radii of Starlikeness, Convolution
Copyright (c) 2025 Hazha Zirar Hussain https://creativecommons.org/licenses/by/4.0
Evaluation of Decision Tree and Support Vector Machine Classifiers in Comparison for Flood Prediction
Protection from floods is one of the most significant activities aimed at risk reduction. Flood prediction and disaster preparedness have relevance for reducing the association between floods and people and infrastructure. The goal of this study was to find out how well the Support Vector Machine (SVM) and Decision Tree classifiers work at predicting flooding based on different environmental and infrastructure factors. Data collection had been done through gathering 140 samples with a total of 21 variables where analysis had been done in order to identify significant contributory factors: topography, urbanization, and climate change. The results show that an SVM model was capable of achieving an accuracy of 91%, while the Decision Tree classifier did much better at an accuracy of 95%. The decision tree model was also more precise in flood prediction (1.00) and recall for non-flood cases (1.00), while for both models, the recall for flood cases was the same (0.88). This indicates that both the models had some false negatives for floods. The current study focuses more on machine learning applications and disaster readiness in flood risk assessment for better and more effective mitigation.
: Flood Prediction, Machine Learning, Support Vector Machine, Decision Tree, Disaster Preparedness
Copyright (c) 2025 Suha Abdullah https://creativecommons.org/licenses/by/4.0
Morphological Description of the Pancreas in Indian Roller Coracias benghalensis (Linnaeus, 1758)
The current study aimed to determine the morphological description of the pancreas in the Indian Roller Coracias benghalensis (Linnaeus, 1758). In this study 15-10 adult live birds were used, which were anesthetized with chloroform and then dissected and the pancreatic gland was removed, then the samples were fixed with fixative solutions. The morphological examination revealed that the Indian roller bird's pancreas is rounded and long, and is a pale pink color. It is found on the lower right side of the body cavity and it has three lobes: the ventral lobe, the dorsal lobe, and the splenic lobe. The ventral lobe was the longest and largest cylindrical lobe and extends within the mesenteric tissue of the duodenal loop. While the dorsal lobe appears flat and lay parallel to the descending arm of the duodenum, the splenic lobe appears in the form of a small volume pear-shaped lobe extending from the center of the dorsal part of the ventral lobe towards the spleen
Bird, Coracias benghalensis, Indian Roller, Morphological description, Pancreas.
Copyright (c) 2025 Haneen Saad Khamas, Intidhar Mohammed Mnati https://creativecommons.org/licenses/by/4.0
Eight-Figure Pattern for Enhancing the Searching Process of Grey Wolf Optimization (Eight-GWO)
Evolutionary algorithms suffer significantly from a stack at the local optima. This paper proposes a new strategy that detects when the search gets stuck in a local optimum and then switches to a more dynamic approach to escape. The proposed model is based on simulating eight pattern movements and embedded with a Grey Wolf Optimizer algorithm (GWO). It is called the Eight-Figure Grey Wolf Optimizer (Eight-GWO). The proposed model combines two phases: regular search when searching progresses over time while the second phase, searching by eight patterns when the algorithm reaches stuck. The Eight-pattern updates the gray position based on the sin and cos function. The proposed Eight-GWO on the 24 functions of the CEC2005 benchmark suite and compared its results with both the standard GWO and Particle Swarm Optimization (PSO). The experiments result show the proposed Eight-GWO gets better results than GWO and PSO where it achieved the best results on 80% of the test functions. The proposed Eight-GWO runs 23% faster than the original GWO and 44% faster than PSO.
Copyright (c) 2025 Lec. Ali Hakem Alsaeedi, Suha Muhammed Hadi, Yarub Alazzawi, Emad Badry Badry https://creativecommons.org/licenses/by/4.0
Medical Image Segmentation Based on Hybrid Deep Learning Techniques
ABSTRACT: Medical image segmentation is an integral component of computer-aided treatment planning and diagnosis, enabling accurate analysis of abnormalities and anatomical structures. In this paper, a novel U-Net and transformer encoder-based hybrid deep learning architecture is developed to advance precision and speed in medical image segmentation. The U-Net architecture, for its remarkable capability to capture local details, is integrated in synergy with a transformer encoder, whose power is in capturing data's long-range dependencies. The synergy between such capabilities makes the resultant hybrid architecture robust for segmentation in diverse medical imaging modalities. The approach is rigorously compared on publicly available datasets, including brain MRI, Chest X-Rays, and ISIC, and is shown to have better Dice coefficients than current state-of-the-art. The synergy between U-Net and transformer components, in addition to better segmentation, is shown to result in computational savings, thus becoming efficient for clinical application. The result demonstrates the capability of such a hybrid architecture to advance diagnostic precision and contribute to enhanced treatment planning in clinical settings. The work is in alignment with growing literature on using advanced deep learning to overcome challenging medical image analysis problems, ultimately leading to enhanced clinical outcomes through accurate and reliable tools for segmentation.
Copyright (c) 2025 Mohammed Abdulameer Aljanabi , Noor Abd Alrazak Shnain https://creativecommons.org/licenses/by/4.0
Intelligent Cyber-Attack Detection in IoT Networks Using IDAOA-Based Wrapper Feature Selection
ABSTRACT: In the realm of cybersecurity, the increasing sophistication of cyber-attacks demands the creation of sophisticated intrusion detection systems (IDS) designed to accurately detect and counteract threats in real-time. This study presents an innovative framework that integrates the Improved Dynamic Arithmetic Optimization Algorithm (IDAOA) with a Bagging technique to enhance the performance of intelligent cyber intrusion detection systems. The IDAOA serves as a wrapper-based feature selection method, optimizing the identification of the most impactful features while balancing local exploration and global exploitation. The Bagging technique further strengthens the classification phase by combining predictions from multiple classifiers, effectively addressing issues of class imbalance and improving overall system robustness. Evaluation of the proposed system using the NSL-KDD dataset demonstrates its superior performance, achieving an accuracy of 99.45%, significantly outperforming state-of-the-art approaches. These findings underscore the potential of intelligent optimization and ensemble learning techniques in advancing cybersecurity for IoT networks.
Copyright (c) 2025 Mohammed Abdullah, Ryna Svyd https://creativecommons.org/licenses/by/4.0
Quantum-Inspired Temporal Synchronization in Dynamic Mesh Networks: A Non-Local Approach to Latency Optimization
This paper presents a novel method for achieving temporal synchronization in Network-on-Chip (NoC) architectures, using optimization techniques derived from quantum mechanics. We provide a non-local temporal coordination framework to optimize network latency in dynamic mesh networks using quantum principles such as entanglement and superposition. A specialized router design using quantum-inspired control units incorporates the Quantum-Inspired Temporal Coordination Algorithm (QTCA) and Non-Local State Synchronization Protocol (NSSP), which are essential components of the proposed architecture. The experimental results indicate that the 16x16 mesh network significantly outperforms conventional route strategies. Latency is diminished by 31.2%, the network saturation threshold is enhanced by 37.8%, and packet loss is decreased by 76.3%. Notwithstanding a minor 8.2% increase in logic overhead and a 5.7% rise in power usage, the framework sustains robust phase coherence (0.92 local, 0.87 non-local). The results demonstrate that next-generation NoC designs might gain from temporal synchronization influenced by quantum computing, particularly in addressing performance and scalability challenges in complex multi-core systems.
Mesh Networks, Network-on-Chip, Quantum-Inspired Computing, Time Synchronization, Non-Local Correlation
Copyright (c) 2025 Yousri Sabah https://creativecommons.org/licenses/by/4.0
A diagnostic study of Cryptosporidiosis in the bile of some ruminant’s species in Wasit Province, Iraq
The current study aimed to determine the prevalence of Cryptosporidium spp. in gallbladder fluid samples collected from cattle and sheep in Wasit Governorate, Iraq. Using the modified Ziehl-Neelsen stain technique,the presence of oocysts of the parasite was confirmed microscopically, showing spherical forms that ranged in color from pink to bright red. A total of 300 samples (150 from cattle and 150 from sheep) were examined between July 1, 2024, and October 30, 2024. The results revealed an infection rate of 30% in cattle and 8% in sheep. Additionally, younger animals, particularly calves under one year of age, exhibited higher infection rates due to weaker immune systems and overcrowded rearing conditions. The results also showed no significant difference in infection rates between rural and urban areas for both cattle and sheep, indicating common environmental risk factors such as water contamination and poor waste management. Statistical analysis revealed that infection rates varied with age, with younger animals being more susceptible. These findings emphasize the need to raise health awareness among farmers,improve livestock management practices, and implement advanced diagnostic techniques to reduce the spread of Cryptosporidium spp. This study contributes to the understanding of the epidemiology of cryptosporidiosis in livestock and highlights its potential as a zoonotic disease.
Cryptosporidium, Cattle, Cow, Sheep, Microscopic examination
Copyright (c) 2025 Yasmin Ghani https://creativecommons.org/licenses/by/4.0
Efficiency of spraying with spirulina and variety on the growth of bean plant under drip irrigation system
The utilization of bio-stimulants in agricultural settings has emerged as a potentially fruitful technique for enhancing the development and production of crops. Microalgae extracts are a form of bio-stimulant that has recently garnered much attention. These extracts are well-known for their high metabolic activity, bioactive chemicals, and capacity to boost plant growth and development. The experiment aimed to determine the efficiency of Spirulina platensis extracts by foliar spraying on bean plants. The experiments were carried out in the autumn of 2023 in Diyala Governorate to study the efficiency of spraying with spirulina extract and its physiological effect on bean plant growth. The experiment was carried out in RCBD design with three replications, using four concentrations of spirulina (0, 0.25, 0.50, and 1.0) % and two varieties of bean plants ( Barcelona and luz de otono). The results showed a superiority concentration of 1.0% in all studied traits. Which record in 73.28 cm,51,43 SPAD,1.41,42.03 g/ plant,3.90%,0.156%, and 1.41% for the high plant, chlorophyll index, leaf area index, dry matter, N%, P%, and K% respectively, Barcelona variety superiority in all characteristics except leaf area index (LAI). The results also showed that the binary interaction between spray and variety significantly affected the studied factors.
Copyright (c) 2025 Intesar Kareem Abdulhassan https://creativecommons.org/licenses/by/4.0
Article Review: Advancements in Veterinary Histopathology: Linking Tissue Pathology to Clinical Outcomes
stressors. Histopathologists in veterinary pathology are therefore engaged in examining tissue alterations resulting from the direct or indirect influence of diseases on cells, tissues, organs, and/or body systems. Such microscopic alterations are collectively considered as 'lesions,' and the terminology used to describe these changes is unique to histopathology. Although mainly involved in Histopathology comprises the study of morphological changes occurring in tissues and organs during various pathological conditions or following exposure to chemicals, drugs, and other environmental diagnostic work, the veterinary histopathologist often plays a substantial role in understanding the pathogenesis of an individual case or collection of cases and may contribute to fundamental studies of the etiology and pathogenesis of a wide range of diseases affecting different species of animals. In review, where the aim is to understand why and how a disease develops, the broad term "anatomical pathology" is used.
Copyright (c) 2025 Samer Fadhail https://creativecommons.org/licenses/by/4.0
Antimicrobial Activities of Chitosan and Nanochitosan Against Aerobic Infection in Wound
In this study aerobic bacteria were isolated from wound and burn samples taken from diabetic foot patient at Al-Salam Teaching Hospital. chitosan, which comes from insects and arthropods, were employed as an antibacterial agent.it binds to negatively charged bacterial cell wall, producing damage and alterations in permeability. The concentration0f 1% was discovered to be the most efficient against aerobic bacterial infections. The degree of deacetylation, which directly effects the positive charge density, has significant effect on the antibacterial activity of chitosan and its derivatives.
pseudomonas aeroginosa; chitosan; nanochitosan ,Antibacterial activity; The degree of deacetylation
Copyright (c) 2025 wafaa mohson https://creativecommons.org/licenses/by/4.0
Effect of an amount of extra food on the dynamics of a food -web model with modified Holling type II functional response
<a href="https://wjps.uowasit.edu.iq/index.php/wjps/This paper deals with studding the effect of an amount of additional food supplies on the dynamic interaction of three species food-web, the species are, prey, intermediate predators and top predators. The top predator species predate both prey species and intermediate predator species according to extended Holling type II functional response for two prey species. Firstly it is proved that the model solutions are bounded under certain condition. All biological possible steady states are explored, and their local stability is analyzed based on the sample parameters. Critical values that make the occurrence of Hopf-bifurcation of the model near intermediate predators-free and top predator-free steady states are determined. Finally, with the help of MATLAB, it is performed numerical simulations to support the evidence of the analytical results regarding to stability and Hopf- bifurcation , Further it is observed that when the amount of extra food increases, the dynamics of the model may induced a transition from the a stability situation to the state where populations oscillate periodically.">This paper deals with studding the effect of an amount of additional food supplies on the dynamic interaction of three species food-web, the species are, prey, intermediate predators and top predators. The top predator species predate both prey species and intermediate predator species according to extended Holling type II functional response for two prey species. Firstly it is proved that the model solutions are bounded under certain condition. All biological possible steady states are explored, and their local stability is analyzed based on the sample parameters. Critical values that make the occurrence of Hopf-bifurcation of the model near intermediate predators-free and top predator-free steady states are determined. Finally, with the help of MATLAB, it is performed numerical simulations to support the evidence of the analytical results regarding to stability and Hopf- bifurcation , Further it is observed that when the amount of extra food increases, the dynamics of the model may induced a transition from the a stability situation to the state where populations oscillate periodically.
Food web, Extra food, Functional response, Stability analysis, Hopf-bifurcation
Copyright (c) 2025 Arkan Mustafa https://creativecommons.org/licenses/by/4.0
Synthesis, Characterization & Biological Activity Assessment of a New Oxadiazole Derivative Based on Nicotinic Hydrazide and Using It for Extraction of Ni and Co from Aqueous Solutions
In a recent study, a novel chemical generated from 1,3,4-oxadiazole was synthesized by mixing transition metals with nicotinic hydrazide using their water-dissolved chloride salts. To determine the chemical properties of the bonds and their chains, H1-NMR, FT-IR, and mass spectrometry(MS) methods were used. In addition, conduction sensitivity measurements were performed. The size of the inhibitory zone for Candida Kruse, Candida albicans, Pseudomonas aeruginosa, and Staphylococcus aureus, was assessed after generated complexe was tested against bacteria by means of the diffusion method. The Hyper Chem program was used to do theoretical calculations utilizing the MP3 approach in order to examine the stability energy of compounds and pinpoint the precise sites where they form complexes with metal elements.
Copyright (c) 2025 ahmed a alibrahimi https://creativecommons.org/licenses/by/4.0
Effect of Head Lice (Pediculus humanus capitis) on Some Haematological Variables Among Female Students in Al- Hajjaj Primary Schools
Head lice (Pediculus humanus capitis) is the most widespread external parasite worldwide, especially in developing countries, the present study involved a visual examination of 3006 female students from December 3, 2023, to May 10, 2024, across six primary schools (Hoor Al-Ain, Al-Baraa, Al-Irada Al-Iraqiya, Al-Saad, Palestine, Asmara) in the Al-Hajjaj district of Salah Al-Din Governorate, to investigate head lice prevalence. According to the findings of the current study, the overall infection rate of Pediculus humanus capitis was 25.91% throughout all of the schools that were utilized in the research. Seven hundred and seventy-nine female students out of the total number of female students who were examined were found to be contaminated. Infection cases appeared in different age groups. The highest infection rate was in the age group 9-10 years at a rate of 31.10%, while the age group 6-7 years recorded the lowest infection rate of 18.69%. The back of the head exhibited the highest lice infection rate at 43.64%, while the middle of the head recorded the lowest rate at 12.62%. The infection rate in the head region was 23.37%, but in the frontal area, it was 14.99%. The long hair category exhibited the greatest infection rate at 30.93%, followed by the very long hair category at 23.24%, while the short hair category recorded the lowest rate at 20.28%. The complete blood count (CBC) revealed significant differences in the white blood cell count at a probability level of P>0.01. However, no significant differences were observed in red blood cells and lymphocytes when compared to the control group. Conversely, significant differences were noted in HGB, HCT, MCV, MCH, and MCHC at a probability level of P>0.01 relative to the control group.
Copyright (c) 2025 Ruqaya Muzahim Khudair https://creativecommons.org/licenses/by/4.0
<a href="https://wjps.uowasit.edu.iq/index.php/wjps/A global public health concern with a substantial economic impact is antimicrobial resistance, which is the capacity of microorganisms to alter and adapt their behavior, rendering medications typically employed against them useless. The rise of drug-resistant infections, driven by the overuse and misuse of antibiotics in healthcare, agriculture, and other sectors, has led to the emergence of dangerous superbugs, such as MRSA and MDR-TB. These resistant bacteria evade traditional treatments through various mechanisms, including horizontal gene transfer, biofilm formation, and the production of resistance enzymes. Antimicrobial Resistance spreads primarily through human-to-human interaction and environmental sources, including contaminated water and food. Addressing this crisis requires a multifaceted approach, including antimicrobial stewardship, better hygiene practices, more effective infection control, and the development of new treatments. Artificial intelligence is emerging as a promising tool to identify resistance patterns and optimize treatment regimens, offering hope in the fight against AMR. Efforts to combat AMR must be collaborative, involving governments, healthcare providers, researchers, and communities to ensure sustainable solutions to this global health challenge.">A global public health concern with a substantial economic impact is antimicrobial resistance, which is the capacity of microorganisms to alter and adapt their behavior, rendering medications typically employed against them useless. The rise of drug-resistant infections, driven by the overuse and misuse of antibiotics in healthcare, agriculture, and other sectors, has led to the emergence of dangerous superbugs, such as MRSA and MDR-TB. These resistant bacteria evade traditional treatments through various mechanisms, including horizontal gene transfer, biofilm formation, and the production of resistance enzymes. Antimicrobial Resistance spreads primarily through human-to-human interaction and environmental sources, including contaminated water and food. Addressing this crisis requires a multifaceted approach, including antimicrobial stewardship, better hygiene practices, more effective infection control, and the development of new treatments. Artificial intelligence is emerging as a promising tool to identify resistance patterns and optimize treatment regimens, offering hope in the fight against AMR. Efforts to combat AMR must be collaborative, involving governments, healthcare providers, researchers, and communities to ensure sustainable solutions to this global health challenge.
Copyright (c) 2025 Rana H. Raheema https://creativecommons.org/licenses/by/4.0
Genetic and phenotypic detection of beta-lactamase isolated from Proteus mirabilis bacteria in hospitals of Anbar Province
<a href="https://wjps.uowasit.edu.iq/index.php/wjps/The study aimed to isolated Proteus mirabilis and determine the genotype and phenotype of the beta-lactamase enzymes produced by these bacteria. 242 samples were collected from various pathogenic cases during the period of August 2023 to January 2024. fifty three isolates of Proteus mirabilis were isolates Distributed as follows: 47 isolates (88.7%) were obtained from urinary tract infection, 5 isolates (9.4%) from otitis media, while one isolate (1.9%) from vaginitis . the samples were diagnosed culturally using appropriate culture media , microscopically using the Gram stain and biochemically. then the isolates were confirmed using the VITEK Compact 2 device. After confirming the isolates, a sensitivity test was conducted against some antibiotics that belong to different groups, and the results showed that the highest resistant was against the antibiotic cefotaxime with a rate of 56.6%, and Amikacin with a rate of 41.5% followed by Amoxicillin-Clavulanic acid with 35.9% , while ciprofloxacin, levofloxacin, cefepime, and azithromycin the resistant rates were moderate with percentages 30.2% , 28.3% , 26.4% , and 20.8% respectively. The lowest percentages of resistance shown by the isolates was against Azeteronam with 5.7% , and imipenem with 3.8% , while for meropenem, all isolates were sensitive to this antibiotic. The results showed that 43.4% of the isolates were Multi-Drug Resistance, as the number of isolates that have resistance to more than three of the selected antibiotics is 23 isolates . Phenotypic results according to the PST test results showed that 32 isolates (60.38%) tested positive, indicating a high probability of beta-lactamase enzyme production according to the PCT test results. PCR and gel electrophoreses revealed that , blaTEM gene were present in 32.1% of the isolates , while blaSHV gene were present in 5.7% only. Intersitingly, blaCTX-M1 was present in all the isolates that produce beta-lactamases enzymes, 41.5%. Metalobeta-lactamases genes , blaIMP and blaGIM were present in 13.2% and 64.2% , respectively.">The study aimed to isolated Proteus mirabilis and determine the genotype and phenotype of the beta-lactamase enzymes produced by these bacteria. 242 samples were collected from various pathogenic cases during the period of August 2023 to January 2024. fifty three isolates of Proteus mirabilis were isolates Distributed as follows: 47 isolates (88.7%) were obtained from urinary tract infection, 5 isolates (9.4%) from otitis media, while one isolate (1.9%) from vaginitis . the samples were diagnosed culturally using appropriate culture media , microscopically using the Gram stain and biochemically. then the isolates were confirmed using the VITEK Compact 2 device. After confirming the isolates, a sensitivity test was conducted against some antibiotics that belong to different groups, and the results showed that the highest resistant was against the antibiotic cefotaxime with a rate of 56.6%, and Amikacin with a rate of 41.5% followed by Amoxicillin-Clavulanic acid with 35.9% , while ciprofloxacin, levofloxacin, cefepime, and azithromycin the resistant rates were moderate with percentages 30.2% , 28.3% , 26.4% , and 20.8% respectively. The lowest percentages of resistance shown by the isolates was against Azeteronam with 5.7% , and imipenem with 3.8% , while for meropenem, all isolates were sensitive to this antibiotic. The results showed that 43.4% of the isolates were Multi-Drug Resistance, as the number of isolates that have resistance to more than three of the selected antibiotics is 23 isolates . Phenotypic results according to the PST test results showed that 32 isolates (60.38%) tested positive, indicating a high probability of beta-lactamase enzyme production according to the PCT test results. PCR and gel electrophoreses revealed that , blaTEM gene were present in 32.1% of the isolates , while blaSHV gene were present in 5.7% only. Intersitingly, blaCTX-M1 was present in all the isolates that produce beta-lactamases enzymes, 41.5%. Metalobeta-lactamases genes , blaIMP and blaGIM were present in 13.2% and 64.2% , respectively.
P. mirabilis, Genotypic, MDR, beta-lactamases
Copyright (c) 2025 Muthanna Hassan https://creativecommons.org/licenses/by/4.0
Effect of application of humic acid and zinc at different concentrations and their interaction on some vegetative growth characteristics of chilli pepper Capsicium annuum L
The field experiment was carried out in one of the agricultural fields in Mansouriya Al-Shatt/Diyala Governorate with the aim of studying the effect of foliar feeding with humic acid and zinc on some vegetative growth of pepper plants. A factorial experiment was designed according to a complete randomized block design with three replicates. The first factor included humic spray concentrations (0, 6, 12) g. L-1, The second factor was spraying zinc sulphate concentrations (0, 1, 2) g. L-1. The results showed that foliar fertilization with humic acid at the level of 12 g. L-1 was significantly superior in giving the highest averages for all vegetative traits, as there was a significant superiority in the trait of plant height, chlorophyll, number of branches, and leaf area, which reached 44.70 cm, 65.17 SPAD, 5.00 branches. plant-1, and 74.25 dm2, respectively. Zinc spraying at 2 gm.L-1 was superior in plant height and chlorophyll with an average of 44.31 cm and 62.70 SPAD, respectively, while the concentration of 1 gm.L-1 for zinc spraying gave the highest average in the number of branches with an average of 4.55 branches.plant-1, while the comparison treatment for zinc spraying was superior in leaf area with an average of 72.99 dm2. The interaction between the two experimental factors had a significant effect on all studied traits.
Copyright (c) 2025 Sarah Mahmood Abdullah https://creativecommons.org/licenses/by/4.0
A Novel hybridization of CG-techniques for Solving Unconstrained Optimization Problems
Conjugate gradient methods are an extremely helpful way for handling large scale non-linear optimization issues. In this paper, based on the three famous Dai-yuan (DY), Liu–Storey (LS)and Conjugate-Descent (CD) conjugate gradient methods, a new hybrid CG method is proposed. Under strong wolf line search, we prove the sufficient descent and global convergence features. The new formula is more efficient than other traditional conjugate gradient approaches, according to numerical results.
Copyright (c) 2025 Hawraz Jabbar https://creativecommons.org/licenses/by/4.0
Green Synthesis of nano calcium oxide using Olive plant extracts and studying its effect on bacteria causing dental caries in children
One hundred clinical samples were collected from children suffering from oral diseases such as tooth decay and root canal inflammation under the supervision of a specialist dentist, using sterile cotton swabs from the site of infection, for patients visiting specialized dental centers in Baiji city, Salah al-Din Governorate. Their ages ranged from 3 to 13 years, and for the period from the beginning of September 2023 until February, where 100 pathogenic bacterial isolates were isolated from clinical samples, diagnosed based on cultural and microscopic characteristics, in addition to diagnosis with the Vitek2 device for diagnosis at the species level. The genus Streptococcus mutans appeared in it at a rate of 18.18%, which is the most significant percentage among other genera. The following species were obtained: Staph. Aureus, Staph.epidermis, Staph.saprophyticus, Micro.luteus, and B.subtilius. The sensitivity of bacterial isolates to antibiotics was tested, and the results showed that they had the highest resistance to cefepime and the least resistance to Gentamycin. Olive leaves were collected and characterized, the aqueous extract was prepared, and its acidity was estimated. The antimicrobial activity was tested using the disk diffusion method. The study showed that the aqueous extract of olive leaves had inhibitory activity against Staphylococcus aureus bacteria with an inhibition diameter of 23 mm. The bio-manufacturing of nano calcium oxide from olive leaf extract was also carried out, and its inhibitory activity on some bacterial isolates was studied. The results showed that the nano solution has activity against the bacterial genus Staphylococcus aureus. In this study, the anti-oxidative activity (ROS%) of the aqueous extract of fig and olive leaves was determined, as olive plants demonstrated more muscular anti-oxidative activity compared to figs, as well as ascorbic acid, which served as a positive control in this experiment.
Copyright (c) 2025 Aya Ahmed Mohammed https://creativecommons.org/licenses/by/4.0