Blend solid polymer electrolytes (BSPEs) comprising PVA/HPMC/CuSO4 were prepared using a solution casting approach. BSPEs were synthesized with varying weight percentages of CuSO4 (0, 10, 20, and 30 wt.%). A variety of experimental methods, including X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), and linear sweep voltammetry (LSV), were used to characterize these BSPE systems. The polymer blend matrix underwent structural alterations, according to the XRD data. The standard data from JCPDS card numbers for copper sulfate matches well with the observed strong peaks of PVA/HPMC+20 wt.% of CuSO4 BSPE. The complex

This work investigates the properties of polyvinyl alcohol (PVA) nanocomposite films with varying multi-walled carbon nanotube (MWCNT) content, ranging from 2 to 8 wt.%. The films were prepared using a solution casting method and characterized using UV-visible spectroscopy, optical microscopy, X-ray diffraction, and tensile tests. The prepared PVA/MWCNT nanocomposite films exhibited optical band gap values ranging from 3.5 eV to 5.3 eV. XRD analysis confirmed the semi-crystalline nature of these nanocomposites. Mechanical properties, including hardness, yield strength, ultimate tensile strength, and Young's modulus, were enhanced by increasing MWCNT content by up to 8%. Contact angle measurements showed an increase in hydrophobicity with in

Constructing a geologically realistic reservoir model and accurately evaluating petrophysical properties are critical components for effective reservoir management. Such efforts enable reliable assessment of hydrocarbon potential and support predictive development scenarios through numerical simulations. This study aims to characterize the Yamama carbonate reservoir in the Ratawi Field, southern Iraq, and to build a static geological model as a foundation for future dynamic simulation. Comprehensive well data, including wireline logs, core analysis, and geological reports, were integrated to interpret petrophysical parameters such as shale volume, effective porosity, and water saturation. Additionally, facies classification was performed us

Accurate estimation of permeability is essential for reliable reservoir characterization and simulation. However, core data are often limited due to their high cost and operational constraints, leading to significant uncertainty in uncored intervals. This study aims to reduce the dependence on core data for permeability estimation by integrating electrofacies derived from well logs and flow zone indicator analysis in the Mishrif Formation, Nasiriyah oil field. Electrofacies were generated using dynamic clustering based on the log data from 13 wells. This led to the identification of five electrofacies units that represent intervals with similar log responses, formed by merging 75 electrofacies, where flow zone indicators analysis id

Intrusion Detection Systems (IDS) is the main defense mechanism deployed by the current networks to prevent cyber threats. Recurrent Neural Network (RNN) are also a novel IDS structure that replaces the conventional training and testing mechanism. The strategy encodes network traffic data as biological sequences using amino acid codons in such a fashion that the RNN is capable of effectively analyzing temporal and sequence data patterns. RNN architecture design adopts embedding layers to handle codon representations and Long Short-Term Memory (LSTM) layers to perform sequential data learning, which is followed by a fully connected network to perform classification functions, which preserve high feature extraction and classification

In recent years, the evolution of the community structure in social networks has gained significant attention. Due to the rapid and continuous evolution of real-world networks over time. This makes the process of identifying communities and tracking their topology changes challenging. To tackle these challenges, it is necessary to find efficient methodologies for analyzing the behavior patterns of dynamic communities. Several previous reviews have introduced algorithms and models for community detection. However, these methods have not been very accurate in identifying communities. Moreover, none of the reviewed papers made an apparent effort to link algorithms that can accurately detect dynamic communities. This review aims to present a ta

Community structures are fundamental in understanding the structure and functionality of complex networks. Different optimization algorithms, including both single-objective and multi-objective approaches, have been employed to address the challenge of community detection. Recently, multi-objective evolutionary algorithms (MOEAs) have attracted many researchers to identify communities in static networks. Many algorithms have been proposed to find a solution that achieves a trade-off between exploring new areas of the solution space and improving the quality of existing solutions. In this trade-off is crucial; whereas exploitation improves existing solutions, it may fail to find better solutions from insufficiently explored regions o

This research explored the physical form of the Iraqi sandgrouse, as well as the internal structure of its trachea histologically. To achieve this, five (5) male adult sandgrouse from Al-Ghazel market, Baghdad, were used. Appropriate approval was obtained to perform this research on animals. The birds were anesthetized with chloroform and euthanized before being dissected. The trachea was taken from each bird, and cleaned with 0.9% NaCl, for use in the morphology of the cartilaginous rings and in histology studies. The present findings indicate that the trachea is a flexible tube made of cartilage and measures approximately 4.5 ± 0.167 in length extending from the end of the cricoid cartilage to the thoracic cavity, where it separa

The work presented in this paper is a case study of the southeastern Iraqi Fauqi Oil Field to evaluate both the petrophysical properties and lithology of the Jeribe–Euphrates Formations. Reservoir characterization was performed using well log data, including Gamma Ray (GR), Density (RHOB), Neutron (NPHI), Sonic (DT), Spontaneous Potential (SP), and resistivity logs. Data processing, correction, and interpretation were conducted using Interactive Petrophysics (IP) software. The Gamma Ray method was used to estimate shale volume (Vsh), while porosity was calculated using various methods, with the neutron–density combination providing reliable results. To determine water saturation (Sw), the Archie equation was applied using common

This research explores the use of solid polymer electrolytes (SPEs) as a conductive medium for sodium ions in sodium‐ion batteries, presenting a possible alternative to traditional lithium‐ion battery technology. The researchers prepare SPEs with varying molecular weight ratios of polyacrylonitrile (PAN) and sodium tetrafluoroborate (NaBF₄) using a solution casting method with dimethyl formamide as the solvent. Through optical absorbance measurements, we identified the PAN:NaBF₄ (80:20) SPE composition as having the lowest energy band gap value (4.48 eV). This composition also exhibits high thermal stability based on thermogravimetric analysis results. Electrochemical impedance spectroscopy re

One of the challenges faced by traditional intrusion detection systems based on machine learning or deep learning is instability when dealing with unbalanced network traffic, leading to failure in detecting certain attacks (minority classifications). Additionally, they struggle with multi-stage attacks, resulting in an increase in false alarms. This paper presents a hierarchical intrusion detection system supported by a Prediction Verification Layer (PVL) and a Feature Inheritance Mechanism (FIM). Where PVL contributes to documenting the system’s final decision and increasing sensitivity to minority attacks, FIM also helps in inheriting features from previous layers and correcting errors as much as possible. Additionally, it allows for ad

Community detection is one of the most fundamental applications in understanding the structure of complicated networks. Furthermore, it is an important approach to identifying closely linked clusters of nodes that may represent underlying patterns and relationships. Networking structures are highly sensitive in social networks, requiring advanced techniques to accurately identify the structure of these communities.Most conventional algorithms for detecting communities perform inadequately with complicated networks. In addition, they miss out on accurately identifying clusters. Since single-objective optimization cannot always generate accurate and comprehensive results, as multi-objective optimization can.Therefore,we utilized two objective

Recently, detecting dynamic patterns for growing communities in social networks have attracted significant attention. The objective of dynamic community detection is to analyze and identify clusters in complex networks that change over time. Different optimization algorithms, including both single-objective and multi-objective approaches, have been employed to address the challenge of dynamic community detection. Although current evolutionary algorithms for identifying community structure can traverse extensive areas of partition space, they often become stuck in local minima. In addition, limited studies have addressed this issue by integrating local search strategies with evolutionary algorithms for community identification. This paper in

EGFR-mutant non–small cell lung cancer (NSCLC) initially responds well to EGFR tyrosine kinase inhibitors (EGFR-TKIs), yet resistance is nearly inevitable and responses to immune checkpoint inhibitors (ICIs) remain limited. In a retrospective cohort of 57 patients with advanced EGFR-mutant NSCLC treated with nivolumab or pembrolizumab, the objective response rate was 12.3%, although responses were concentrated in a small subgroup with concurrent high PD-L1 expression and dense intratumoral CD8⁺ immune-cell infiltration. Emerging evidence links these outcomes to chemokine-network dysregulation that alters immune trafficking and spatial organization. Oncogenic EGFR signaling shifts chemokine networks away from effector T-cell recruitment

The use of sugarcane molasses (SCM) as a sustainable stabilizing agent for geomaterials, particularly granular subbase soils, has recently attracted growing attention as an alternative to traditional stabilization methods employing cement, lime, or bitumen, which are often associated with high costs and environmental concerns. This study presents a mechanistic–experimental evaluation of SCM for stabilizing granular subbase materials at dosages of 2.5%, 5%, 7.5%, and 10% by weight of dry granular material. A comprehensive testing program was conducted, including compaction characteristics, California Bearing Ratio (CBR), resilient modulus (Mr), permanent deformation under repeated loading, optical microscopy, and FTIR spectroscopy.

The avian esophagus shows structural and functional differences related to feeding habits and habitat, with mucous secretions and amino acids playing key roles in protection and metabolism. The present study aimed to comparatively investigate the histological, histochemical, and amino acid profile characteristics of the cervical esophagus in the Iraqi pin-tailed sandgrouse (Pterocles alchata) and the red-wattled lapwing (Vanellus indicus). A total of eight adult individuals from each bird species (sandgrouse and lapwing) were collected from the Al-Samawah Desert, Al-Muthanna Province, and AlYusufiyah District, Baghdad Governorate, Iraq, respectively, between October 2025 and January 2026. Histological examination was performed using hematox

Arabic text classification is a challenging task because of the complex morphology of the language, the existence of different writing forms and a multitude of dialects, which can result in sparser common text representations. While transformer models such as AraBERT have obtained superior results on many Arabic NLP tasks, their high computational requirements make them difficult to deploy in environments with limited hardware resources. In some cases this can also make the model less practical for researchers working with basic computer systems. This study focuses on a more practical issue: how much accuracy a simple classifier may lose when the amount of required computation is reduced. We use a combined TF-IDF representation based on bo

This research examines the evolution of Turkey's foreign policy in dealing with international crises, especially after 2011, when Turkey shifted from a "zero problems" approach to a more active and interventionist foreign policy in regional issues, such as the Syrian crisis and the Eastern Mediterranean crises. The importance of this study lies in its focus on the experience of a regional power in a turbulent environment, reviewing Turkey's success or failure in managing these crises through various tools. This study focuses on outlining the theoretical framework of the concept of international crisis management, analyzing Turkey's tools for dealing with crises, studying the practical models of Turkey's role in regional crises, and

The rapid rise in the use of artificially generated faces has significantly increased the risk of identity theft in biometric authentication systems. Modern facial recognition technologies are now vulnerable to sophisticated attacks using printed images, replayed videos, and highly realistic 3D masks. This creates an urgent need for advanced, reliable, and mobile-compatible fake face detection systems. Research indicates that while deep learning models have demonstrated strong performance in detecting artificially generated faces, deploying these models on consumer mobile devices remains challenging due to limitations in computing power, memory, privacy, and processing speed. This paper highlights several key challenges: (1) optimiz

Background: Kocuria kristinae (earlier known as Rothia kristinae) is a relatively new opportunistic pathogen responsible for ear infections. The ability of this organism to form biofilms increases its resistance to therapy and promotes the development of antimicrobial resistance, necessitating new treatment methods. Objective: To assess the effect of 3-caffeoylquinic acid on K. kristinae isolated from patients with ear infections. Methods: Isolation of five clinical strains was done by conventional microbiological procedures. The ability of K. kristinae to form biofilms was determined by the crystal violet method (absorbance at OD₅₇₀) before and after 3-caffeoylquinic acid exposure; statistical data analysis was done using a

يتناول هذا البحث موضوع صعوبات الردع الإلكتروني في الإستراتيجية الأمنية للصين، حيث يُعَد من أبرز التغيرات في العقيدة الأمنية خلال القرن الحادي والعشرين، الهدف من الدراسة هو تحليل أدوات الردع الإلكتروني التي تستخدمها الصين، مثل القدرات التقنية، والهياكل التنظيمية، والقوانين، والدبلوماسية الرقمية، مع توضيح العلاقة بين هذا الردع والسياسة الخارجية للصين، خاصة في ظل التحديات القانونية والتقنية والمحلية