Wadi Alshatti University Journal of Pure and Applied Sciences
Wadi Alshatti University Journal of Pure and Applied Sciences (ISSN: 3006-0877) is a peer-reviewed, open-access academic journal dedicated to the dissemination of high-quality research in the fields of pure and applied sciences. Published biannually (two issues per year), the journal serves as a platform for researchers, scientists, and academics to share innovative findings and advancements in disciplines such as: Physical Sciences (Physics, Chemistry, Earth Sciences) Biological Sciences (Biology, Microbiology, Biochemistry) Mathematics & Statistics Environmental Sciences Computer Science & Information Technology Engineering & Technology (where applicable) Journal Mission The journal aims to promote scientific knowledge by publishing original research articles, reviews, and short communications that contribute to theoretical and practical developments in pure and applied sciences. It upholds rigorous peer-review standards to ensure the validity, significance, and originality of published work. Key Features Open Access: All articles are freely available to readers worldwide, ensuring broad dissemination of knowledge. Peer-Reviewed: Manuscripts undergo a double-blind review process by experts in the relevant fields. ISSN: Online ISSN 3006-0877 Frequency: Two issues per year (biannual). Indexing & Archiving: The journal is committed to being indexed in reputable databases to enhance visibility and impact. Article Processing Charge (Authors' Fees) This journal charges no authors' fees Article Submission Charge: 0.0 LD Article Processing Charge (APC): 0.0 LD WAUJPAS is run on a non-profit basis. Wadi Alshatti University covers 100% of the expenses of publishing Publisher The journal is published by Wadi Alshatti University, supporting the institution’s commitment to advancing scientific research and education in Libya and beyond. For inquiries, please contact the Editorial Office at [inf.wuj@wau.edu.ly].
This journal uses Creative Commons Attribution-Noncommerical 4.0 International License (CC BY-NC 4.0), which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. To view a copy of this license, visit https://creativecommons.org/licenses/by-nc/4.0/. Copyright of articles Authors retain copyright of their articles published in this journal.
A Preliminary Survey of Some Aquatic and Semi-Aquatic Insect species in Al-Jabal Al-Akhdar-Libya
The study aim to survey and identify aquatic and semi-aquatic insects from water sources located in the in Al-Jabal Al-Akhdar region of northeastern Libya, in order to understand its biodiversity and utilize it as a biological indicator of water quality, the work was completed between July 2023 and June 2024, excluding September and October when tornado Daniel blocked the road. During this study collected 20 species, 16 specimens which were completely identified to species, 4 specimens to the genus and 1 at the family, all of them belong to 16 families and 6 orders. The results indicated significant differences between the study sites, with the highest population density (42%) of aquatic and semi-aquatic insects recorded in waters Fountain of Apollo. The results showed a difference in insect population density according to the months of the study. The average number of insects increased by 91.3% in November at Ain Barghu compared to the other months of the study. Insect populations also increased significantly during March averaging 49.3 and 47.0, in April averaging 50.0 and 54.3 for Fountain of Apollo and Ain al-Hofra, respectively. The results also showed that Hydroptila sp. represent a new record for Libya. The study also included measuring water temperature, pH, and total dissolved solids at each site. The average water temperature ranged from 19 to 26, pH from 6.1 to 7.8, and total dissolved solids from 315 to 487 parts per million at Ain al-Hofra, Fountain Apollo and Ain Barghu.
Copyright (c) 2026 The authors https://creativecommons.org/licenses/by-nc/4.0
AI-Based Monitoring of Solar Panels in Desert Environments: Distinguishing Dust Accumulation for Fault Detection
Dust accumulation on photovoltaic (PV) panels in arid and desert environments poses a significant challenge by degrading conversion efficiency and reducing overall energy yield. A comparative analysis was conducted using three supervised classifiers— ogistic Regression, Support Vector Machine (SVM), and Multi-Layer Perceptron (MLP)—trained and tested on a dataset comprising 2,562 PV images (1,493 clean and 1,069 dusty) obtained from Kaggle, a widely used data science and machine learning platform. The proposed pipeline integrates robust image pre-processing steps, including resizing to 224 × 224 pixels, contrast enhancement via Contrast Limited Adaptive Histogram Equalization (CLAHE), and RGB normalization. Feature extraction yielded 28 engineered descriptors encompassing grayscale intensity statistics, RGB and HSV (Hue, Saturation, Value) color characteristics, edge-based morphology, and texture information. Experimental results indicate that the SVM classifier outperformed the other models, achieving a validation accuracy of 75.78% and a test accuracy of 74.07%, with balanced precision and recall values of 74.00% and 74.07%, respectively. Notably, the model demonstrated higher recall for clean panel detection (79%) compared to dusty panels (68%), highlighting the complexity associated with detecting varying degrees of soiling. Furthermore, the SVM achieved an area under the Receiver Operating Characteristic (ROC) curve of 0.790 while maintaining low computational complexity. The results demonstrate that the proposed SVM-based approach is a practical and efficient solution for automated solar panel monitoring in desert environments, enabling timely maintenance and reducing energy losses.
Human Papillomavirus (HPV) Awareness Among Female Students at the Higher Institute of Medical Sciences and Technologies in Al-Khums, Libya
Background: Human Papillomavirus (HPV) is a non-enveloped, double-stranded DNA virus that targets cutaneous and mucosal cells. It is primarily associated with sexually transmitted infections and is a leading cause of cervical and anogenital malignancies. Objective: To evaluate the level of knowledge regarding HPV among female students at the Higher Institute of Medical Sciences and Technology in Al-Khums. Methodology: A cross-sectional survey was conducted during October and November 2025, utilizing a convenience sampling technique and a self-administered questionnaire. The survey collected demographic data and assessed nine knowledge-based items. Data were analyzed using SPSS version 27.Results: The findings revealed that while (59.8%) of students had heard of HPV, (66.5%) exhibited a low level of overall knowledge. Although (84.3%) recognized the link between the virus and cervical cancer, only (55.5%) correctly identified its transmission routes. Misconceptions were prevalent, with (59.8%) believing that infection is rare. Awareness of the vaccine was moderate (72.4%), yet knowledge regarding the optimal timing for vaccination remained low. No statistically significant correlation was found between the students' academic specialization and their level of knowledge. Conclusion: Significant knowledge gaps persist, hindering the adoption of effective preventive measures. The lack of understanding regarding transmission mechanisms and the misconception of low infection risk remain major challenges. These results underscore the urgent need for comprehensive awareness campaigns designed to enhance correct knowledge and rectify misconceptions among students.
Designing A Protective Case to Reduce Electromagnetic Radiation Emitted from Mobile Phones Using CST Software
In this paper, a Planar Inverted-F Antenna (PIFA) is designed for mobile applications. And to study the effect of incorporating a synthetic material shell that consists of 12 split ring resonator (SRR) cells, each cell containing two overlapping rings to improve safety from electromagnetic radiation. The free-space antenna performance was analyzed before and after shell integration, based on the key performance indicators reflection coefficient (S11), return wave ratio (VSWR), radiation efficiency, radiation pattern, placement of the phone next to a human head model to study electric field distribution and surface currents, and specific absorption rate (SAR) values. Simulation results showed that incorporating the enclosure did not negatively affect the antenna matching or radiation characteristics. The value of S11 remained below -10dB at the fundamental frequencies, at an operating frequency of 0.89GHz and a power supply of 0.5w. The value of SAR-1g decreased from 3.05 kg/w to 2.91 kg/w, a decrease of 4.6%. The value of SAR-10g decreased from 2.39 kg/w to 2.25 kg/w (a decrease of 5.9%). The results confirm that the incorporation of the 12-cell SRR material shell achieves an effective balance between reducing the specific absorption rate and maintaining antenna performance, making it a practical solution for improving electromagnetic safety in mobile phones.
Bernstein Polynomials for Solving Some Classes of Abel’s Integral Equations with Weakly-Singular Kernels
Most physical phenomena are described by differential equations, such equations are frequently hard to solve in a direct way, they are commonly converted into integral equations, which can then be tackled with simpler and more efficient methods. This paper aims to numerically obtain numerical solutions of the linear main generalized Abel’s integral equations (weakly-singular kernel) of both first and second kinds using the Bernstein polynomials where the unknown function is approximated in terms of such polynomials. Then relying on some properties of the Bernstein polynomials, the considered integral equation is converted into a linear system of algebraic equations, that can be easily solved to obtain the coefficients of expansion. To evaluate its performance, some examples were presented comparing the numerical solutions with the exact ones. These comparisons showed that, even for low-degrees Bernstein polynomials, the approximate solution agrees very well with the exact one. The obtained results confirm the method's effectiveness and dependability for solving integral equations with weakly-singular kernels. Additionally, the numerical findings ensure the analytical theorems concerning existence, uniqueness, and convergence of the numerical solution.
Main generalized Abel’s integral equations
The Potential Usage of Chickpea and Flaxseed Flours in Enhancing the Nutritional Value and Functional Properties of Gluten Free Flour
This study aimed to enhance the nutritional value and functional properties of laboratory prepared gluten free flour made from rice flour fortified with flour of chickpea and flaxseed and comparing that properties with that of commercial gluten free flour. The chemical parameters measured included moisture, ash, protein, fat and total fiber. Whereas, the measured functional properties involved water and oil binding capacity, swelling capacity, foaming ability and stability. The results showed significant differences between the two samples in most of the studied chemical indicators. The commercial flour had higher moisture content (11.34%) compared to the laboratory prepared flour (9.65%). However, the laboratory flour showed a higher protein content (11.84%) compared to the commercial flour (3.61%). Ash content was also higher in the laboratory flour (1.95%) in comparison to the commercial one (0.91%). A significant higher fat content was observed in the laboratory flour (3.90%) compared to the commercial flour (2.93%). No significant difference was found in crude fiber content between the two samples. Additionally, the findings recorded significantly greater calcium and phosphorus content in the laboratory flour. The results indicated that the commercial flour demonstrated higher water and oil binding capacities (211% and 131%, respectively) compared to the laboratory flour (66% and 80%, respectively). It also exhibited better swelling capacity (297 g/g) in comparison to the laboratory made flour (50.84 g/g). The commercial flour showed a noticeable foaming ability and stability, while the laboratory flour showed no foaming ability.
Deep Learning and Bioengineered Feature Engineering for Automated Taxonomic Identification of Mediterranean and Atlantic Demospongiae
Given morphological convergence, cryptic speciation, and severe class imbalance in regional collection records, accurate taxonomic dentification of marine Demospongiae remains a major challenge in biodiversity monitoring. This study presents a novel computational framework that integrates imbalanced multi-class deep learning with biologically informed feature engineering to automate the hierarchical classification of 503 Demospongiae specimens collected from Mediterranean and Atlantic habitats. We introduce a biologically grounded feature construction pipeline that encodes morphological, ecological, and evolutionary priors derived from sponge ontology structures, generating high-dimensional representations compatible with deep neural architectures. To address strong distributional skew across 7 orders, 42 families, 114 genera, and 230 species, we implement a hybrid imbalance mitigation strategy combining topology-aware synthetic minority oversampling, adaptive class-weighted sampling, and hierarchical focal loss. The proposed architecture further employs a multi-task graph convolutional network to jointly learn taxonomic relationships while preserving hierarchical constraints. Experimental evaluation demonstrates substantial improvements over conventional machine learning baselines, achieving macro-averaged F1-scores of 0.89 at the order level and 0.76 at the species level, with notable gains in recall for underrepresented Atlantic taxa. Ablation analyses further indicate that the incorporation of bioengineered features significantly enhances model generalization.
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The Relationship Between Hepatitis C Virus (HCV) Infection and Insulin Resistance (IR)
Background: There is a well-established correlation between Hepatitis C Virus (HCV) infection and the development of diabetes mellitus, with increased prevalence observed among diabetic patients. Objective: This cross-sectional study was conducted on patients attending the Medical Reference Laboratory in Sebha-Libya. This study aimed to investigate the relationship between Hepatitis C Virus (HCV) infection and insulin resistance (IR), as one of the major metabolic complications associated with chronic infection. Method: A total of 115 participants were enrolled and divided into two groups: 90 patients with confirmed HCV infection and 25healthy controls. Clinical and laboratory assessments included fasting blood glucose, fasting insulin, glycated hemoglobin (HbA1c), liver function tests, body mass index (BMI), and calculation of HOMA-IR as an index for insulin resistance. Results: The results showed significantly higher levels of fasting blood glucose, insulin, HbA1c, and HOMA-IR in patients group compared with controls(P-value<0.05), indicating a strong association between HCV infection and insulin resistance. Notably, 52.2% of HCV patients were found to have insulin resistance (HOMA-IR > 2.4), while no significant differences were observed with respect to age or gender. Moreover, alterations in liver function parameters were observed, reflecting the interplay between viral infection and metabolic dysregulation. Conclusion: HCV infection plays a pivotal role in promoting metabolic disturbances, particularly insulin resistance, which may increase the risk of type 2 diabetes mellitus and accelerate liver-related complications.
Study and Design Multiband MPA Antenna for Smart Phones
Modern wireless communication systems require compact multiband antennas that can operate efficiently over several frequency ranges used in mobile devices. However, conventional microstrip patch antennas often suffer from narrow bandwidth and limited gain, which restrict their use in multiband applications. This work presents the design and simulation of a compact slotted microstrip patch antenna intended for Wi-Fi, WLAN, WiMAX, and IMT applications. The antenna is designed on an FR-4 substrate and improved using rectangular slots and a partially reduced ground plane to enhance bandwidth and radiation characteristics. The proposed antenna is modeled and simulated using CST Microwave Studio 2019, and its performance is evaluated in terms of return loss, gain, directivity, VSWR, and surface current distribution. Simulation results show that the antenna operates effectively within the 2.9–7.6 GHz band, achieving resonant frequencies at 2.8 GHz, 3.80 GHz, and 4.61 GHz with a maximum bandwidth of 7.40 GHz. The design also provides a gain of up to 8.7 dB and maintains a VSWR below 2 across all operating bands. These results indicate that the proposed multiband slotted microstrip antenna is a strong candidate for integration into modern mobile and wireless communication systems.
Nuclear Plants Trends for Development Planning in Egypt
Fossil fuel combustion is blamed for global climate change and associated greenhouse gases (GHG) are the main types of pollution created by GHG emissions from combustion (i.e., CO2) and as such an ever-increasing level of CO2 emissions make GHG, their pollutants and the complications of climate change awareness more significantly urgent. There is significant concern from policymakers concerning, fuel consumption, energy security and the challenges of GHG emissions created by fossil fuel consumption has created a focus on alternative, cleaner sources of energy both from public policy analysis and political perspectives. As such, clean sources of energy (i.e., nuclear and renewable sources of energy) are being promoted as alternative sources of energy and provide effective tools for mitigating the negative impacts of climate change and are being used as part of a new energy policy strategy. There has also been much discussion among various countries with regard to the need for increasing share of energy supply from nuclear energy, thereby diversifying the energy supply chain, decreasing reliance on imported fossil fuels that may be subject to significant price volatility and improving energy security. The present work will contribute to knowledge development and interface towards improving the power generation infrastructure of nuclear energy in Egypt through a study of the relationship of nuclear energy, the economy and CO2 emissions using the experience from other developed countries.
The Most Prominent Manifestations of Illness in COVID-19 Patients and Their Relationship to the Severity of Disease and Mortality in one of Isolation and Intensive Care Centers in North Western of Libya
As SARS-CoV-2 spread rapidly across continents giving rise to the COVID-19 pandemic; scientists have worked intensively to understand the virus built, behavior and Response to vaccination and treatment. This descriptive-analytical study aimed: to assess the impact of predisposing risk factors, specifically age and chronic diseases, on predicting the extent of health deterioration and increased likelihood of mortality in COVID-19 patients. Methods: In this study, data from 100 treated patients were examined at one of Isolation and Intensive Care Centers in north western of Libya “Surman “.data were extracted from medical records using a data collection form, and patients were classified according to the WHO's clinical assessment criteria, reported risk factors and laboratory indicators. Most patients were men 66% with an average age of 68 years. Common conditions included diabetes 34%, hypertension 28%, and other comorbidities 24%. 11% of cases were classified as mild, 40% as moderate, and nearly 49% as severe. Significantly, many patients 89%, required intensive care with a survival rate of 69% and a mortality rate of 31%. Results: Disease severity was significantly associated with specific biomarker profiles at admission, characterized by decreased oxygen saturation 85.47% and elevated levels of CRP (118.5 mg/L) and D-dimer (1.86 µg/mL). Moreover, CRP and D-dimer levels showed a direct positive correlation with infection severity. Recommendations: the need to strengthen community compliance with preventive measures and activate early medical intervention mechanisms as soon as clinical symptoms appear to reduce the risk of morbidity.
Hybrid Matrix-Ensemble Framework for Chronic Kidney Disease Diagnosis
This study introduces a novel Hybrid Machine Learning and Mathematical Matrix Framework (HML-MMF) for optimizing the early detection of Chronic Kidney Disease (CKD), addressing critical limitations of conventional machine learning approaches, namely, poor interpretability, overfitting, and instability in clinical settings. The proposed framework uniquely integrates matrix algebra techniques, including column-wise mean imputation, Principal Component Analysis (PCA), Fisher Discriminant Analysis (FDA), and Min-Max normalization, with an ensemble of three classifiers: Gradient Boosting Machine (GBM), Support Vector Machine (SVM), and K-Nearest Neighbors (KNN). Applied to the UCI CKD dataset (400+ patients, 24 clinical features), the HML-MMF pipeline transforms raw clinical data into a mathematically structured, low-dimensional representation that enhances class separability while preserving physiological meaning. The final diagnosis is derived through soft voting, ensuring robustness and generalizability. Experimental results demonstrate that the hybrid model achieves 96.2% accuracy, 96.0% precision, 95.5% recall, 95.7% F1-score, and an AUC-ROC of 0.973, significantly outperforming both GBM-only (AUC = 0.942) and Matrix + SVM (AUC = 0.955) baselines. The scientific novelty lies in the synergistic fusion of interpretable matrix operations with ensemble learning, not as sequential steps, but as a unified architecture where mathematical transformations actively guide model optimization. This approach not only boosts performance but also provides clinical transparency, enabling practitioners to trace predictions back to key biomarkers like serum creatinine and BUN, which eigenvalue analysis confirms as dominant contributors. In the medical domain, this work offers a reliable, explainable decision-support tool that minimizes false negatives a critical requirement in CKD screening. Via bridging rigorous linear algebra with modern ML, the HML-MMF sets a new standard for trustworthy, high- erformance diagnostic systems in resource-constrained or data-imbalanced clinical environments.
Leveraging Hydrogen for Covering Energy Shortage in an Electricity Subgrid
This study explores a sustainable solution for addressing the electricity supply-demand imbalance in Brack Ashatti by utilizing excess electricity during off-peak hours for hydrogen production through electrolysis, and subsequently employing fuel cells to generate electricity during peak periods. The research evaluates the feasibility of using a hydrogen-based system to stabilize the national grid without the need for additional power generation units. Based on the calculations, the electrolyzer can produce up to 271.8 cubic meters of hydrogen per hour, requiring approximately 9.1 MW of electricity, which is sufficient to cover the network's 6.1 MW energy deficit during off-peak hours. With a hydrogen storage capacity of 421,255 cubic meters, this system can store hydrogen for later use in fuel cells to meet the 1689 MW deficit in the national grid during peak times. The results indicate that by optimizing hydrogen production through electrolysis and utilizing fuel cells for electricity generation, the proposed system can provide 8,424 MW of power, effectively covering the network’s deficit. This method not only resolves the supply-demand gap but also proves to be a cost-effective and efficient solution for achieving grid stability, without requiring additional power plants.
The Role of Using Computer Applications in the Development of Media Work
Media work in its various fields faces challenges that hinder the optimal use of computer applications. These challenges vary between technical, human, and economic factors. Overcoming them requires a strategic vision that includes developing infrastructure, investing in training and capacity building, and establishing clear legal and ethical frameworks for the use of computer applications in the development of media work. This study highlights the role of computer applications in developing media work and their importance in improving news transmission methods, accelerating data collection and analysis, and enhancing the quality and accuracy of media content. This, in turn, increases the efficiency of media professionals and contributes to the development of media institutions. A descriptive methodology was adopted in this study. The study aims to clarify the role of using computer applications in media as one of the most influential tools in modern societies, to review the most prominent of these applications for those interested in media work—whether media professionals or officials in institutions concerned with the media sector—and to draw attention to their importance in developing media work, facilitating tasks, and accelerating processes, as well as to explain the challenges associated with employing these computer applications in the media field. The study concludes that the use of computer applications in media work represents an effective solution to the challenges facing the media sector, and that these applications can be used to improve marketing strategies, enhance content quality, and reach a wider audience. However, this requires the development of appropriate policies and tools to mitigate the challenges associated with their use.
Histological Effects of Ziziphus spina-christi Leaf Extract on Testes and Epididymides in Male Rabbits
The widespread use of medicinal plants in traditional therapy has raised concerns regarding their long-term safety, particularly with respect to reproductive function. Ziziphus spina-christi (ZSC) is commonly utilized for its antimicrobial, anti-inflammatory, and antioxidant activities; however, limited data are available concerning its possible impact on male reproductive organs. This study was conducted to investigate the histopathological effects of prolonged oral administration of ZSC leaf extract on the testes and epididymides of adult male rabbits. Animals were divided into two groups: a control group receiving distilled water and a treated group administered ZSC leaf extract at a dose of 200 mg/kg body weight daily for six weeks. At the end of the experimental period, testicular and epididymal tissues were harvested and processed for routine microscopic examination. Tissue changes were evaluated descriptively and graded using a semi-quantitative scoring method. Histological analysis revealed marked structural alterations in the reproductive tissues of treated animals compared with controls. Testicular sections demonstrated degeneration of seminiferous tubules, decreased spermatogenic cell layers, thinning of the germinal epithelium, and vascular congestion. In the epididymis, reduced sperm density, epithelial degeneration, luminal debris, and thickening of connective tissue were observed. These findings indicate that prolonged administration of ZSC leaf extract may adversely influence the histological architecture of male reproductive organs. Further studies are warranted to clarify its reproductive safety and underlying mechanisms.
Modeling A 600 MW Floating Photovoltaic System in Al-Khums city, Libya: Performance Analysis and Implementation Using PVSyst
This research presents an analysis of a 600 MW AC floating PV system to be installed in Al-Khoms, Libya. The system was simulated using PVsyst version 7.4 software with the transposition method based on the HDKR method using weather data from Meteonorm version 8.1 and Solargis weather data sources. The simulation results show that the system will have an annual AC energy production of 1,346 GWh/year, a system performance ratio of 81.7%, and a specific energy production ranging from 1,850 to 2,050 kWh/kWp/year with a capacity factor of 25.6%. The FPV system will have a bifacial rear irradiance gain of 3.0 to 4.5% and will conserve 1.25 million cubic meters of surface water per year, equivalent to a monetary value of €250,000 to €625,000 per year. Total investment required for the project falls in the range of €480 to €540 million, amounting to €0.80 to €0.90 per watt-peak (Wp) of direct current, and results in a Levelized Cost of Energy (LCOE) of €0.055 to €0.065 per kilowatt-hour (kWh) over a period of 25 years and a discount rate of 5%. This is in line with the LCOE of conventional power plants in Libya, which stands in the range of €0.07 to €0.10/kWh. Upon inclusion of the social cost of carbon (SC_CO2 ~$70/tCO2), the environmentally adjusted LCOE stands in the range of €0.028 to €0.035/kWh. The results obtained prove the feasibility of utility-scale floating photovoltaic (FPV) systems in Libya.
Comparative Analysis of Phenolic Compounds in Coffee Prepared by American and Arabic Brewing Methods
Coffee’s high antioxidant ability is attributed to its abundance of minerals and bioactive substances including caffeic acid, chlorogenic acid, and other phenolic compounds. Phenolic molecules with high nutritional value, are decomposed by the high temperatures that coffee beans are exposed to in order to produce volatile aromatic chemicals, the concentration of this active compounds are affected by the type of preparation method. The aim of this study was comparing the difference between Arabic and American coffee preparing methods in term of phenolic compounds quantity among different twelve coffee brands collected from Libyan market. Folin–Ciocalteu assay was used in quantification of phenolic compounds in all samples. The results of this study show that the preparing method have significant role in determining the phenolic content of coffee. The Arabic preparation method, which involves boiling the water with coffee, resulted in a significant reduction in Total Phenolic Compounds (TPC) compared to the American method for all samples. On average, the TPC of the all coffee samples with two different preparation methods arranged between 225.545 to 508.096 mg GAE /L. Generally, the findings show that the American preparing method is more effective in producing phenolic compounds, although the degree of this effect differs among coffee brands.
Modelling and Stability Analysis of (TIV) System Using Lyapunov Function
Tumour Immune Virus (TIV) model is theoretically analysed based on a system of five nonlinear ordinary differential equations (NODEs). The model is divided into five compartmental classes: uninfected cancer cells , virus-infected cancer cells immune effector cells dead cells and free virus particles . The aim is to investigate the stability of the deterministic TIV model both analytically and numerically, utilising the Lyapunov function and the Runge-Kutta-Fehlberg (RKF) method. For the deterministic model, five steady points are derived, and their local and global stability are investigated for the coexistence steady point; however, specific criteria were employed to confirm the existence and stability of these steady states. Also, numerical simulations were conducted to study the dynamic behaviour of the TIV system, whose findings offer more insights into the impact of oncolytic treatment on the immune response and contribute to the development of more effective strategies.
Energy and Exergy Analysis of an Al-Hussein Steam Power Plant in Jordan Using Engineering Equation Solver (EES)
This study independently reproduces the energy and exergy analysis of the Al-Hussein steam power plant in Jordan using Engineering Equation Solver (EES) under the same operating conditions and reference environment (298.15 K, 101.3 kPa) reported in the original work. The reproduced thermodynamic properties and component energy balance show close agreement with the published results, confirming the robustness of the first-law analysis. In contrast, the exergy results reveal notable deviations in specific components: the condenser exergy destruction is calculated as 18.03 MW (vs 13.74 MW reported), yielding a markedly lower condenser exergy efficiency (3.40%), while LPH5 exhibits a higher exergy efficiency (82.34% vs 67.3%). The distribution of irreversibilities indicates that the boiler remains the dominant source of exergy destruction (74.55% of the total), followed by the turbine (12.83%) and condenser (11.13%), highlighting the boiler as the primary target for performance improvement. These findings demonstrate that independent computational reproduction can confirm energy results while revealing sensitivity of component-level exergy metrics to modelling assumptions, improving the reliability of exergy-based performance assessments.
Wheat is a global dietary staple, supplying one of world’s grain production and serving as a primary source of carbohydrates, protein, as well as essential micronutrients. However, its productivity remains increasingly jeopardized via biotrophic fungal pathogens obligate parasites that severely compromise plant health and grain yield. This review critically examines four major diseases: (Puccinia graminis f. sp. tritici) stem rust, (P. striiformis f. sp. tritici) stripe rust, (P. triticina) leaf rust, and (Blumeria graminis f. sp. tritici) powdery mildew, which collectively threaten food security across diverse agroecosystems. Moreover, central to sustainable control is genetic resistance, which operates through two paradigms: race-specific (qualitative) as well as non-race-specific (quantitative or adult plant resistance). Furthermore, the novelty of this work lies in its integrative synthesis of global pathogen distribution, virulence evolution, for instance, Ug99 and TKTTF lineages), as well as the strategic deployment of resistance genes from landraces and wild relatives. In addition, this synthesis supports next-generation wheat improvement aimed at stabilizing yields under escalating disease pressure.
Techno-Economic Feasibility of Parabolic Trough Solar Steam for Thermal Enhanced Oil Recovery
This study rigorously evaluates the techno-economic feasibility of parabolic-trough collector (PTC) for thermal enhanced oil recovery (EOR) by benchmarking it against conventional diesel-fired boiler steam supply across geographically diverse thermal- OR fields. Site-specific direct normal irradiance data from NREL’s NSRDB are used to characterize the solar resource and size the collector aperture area. Techno-economic calculations and scenario evaluation are conducted using HOMER Pro, while the proposed PTC configuration includes thermal energy storage with an equivalent duration of 6 h/day and is assessed under a representative capacity factor of 0.6, reflecting partial coverage of steam-load demand. A harmonized levelized cost of energy (LCOE) framework is applied to both configurations under consistent financial assumptions to enable an apples-to-apples comparison. Results show that boiler-based LCOE is strongly driven by local diesel pricing and heat-duty requirements the Netherlands (NLD) exhibits the highest boiler LCOE, whereas Venezuela (VEN1) yields the lowest. A second Venezuelan case (VEN2) produces an anomalously high boiler LCOE around 4.5, attributable to an exceptionally large reported heat duty; it is therefore treated as an outlier with elevated uncertainty. PTC investment inputs are parameterized using NREL benchmark unit costs 24.375 SAR/kW installation, 712.5 SAR/m2 solar field, and 93.75 SAR/kWh thermal storage. Beyond cost competitiveness, solar steam substitution provides a credible pathway for fuel displacement and associated CO2 mitigation; reported solar-EOR deployments indicate annual CO2 reductions ranging from 104 to 636,720 tCO2/year, depending on plant scale.
Study of Superficial Fungal Infections among Diabetes Patients at Diabetic Center in Zliten City-Libya
This cross-sectional study examined superficial fungal infections (SFIs) among 117 diabetic patients at Dermatology Outpatient Department of Zliten Diabetes Center. Samples were collected from skin, nails, hair, Oral mucosa, and interdigital areas. Fungal identification was performed using culture methods, microscopy, Wood’s lamp examination, and potassium hydroxide (KOH) preparation. Positive fungal growth was detected in 105 samples (89.7%). Dermatophytes accounted for 53.3% of isolates, with Trichophyton violaceum (14.3%) and Trichophyton soudanense (11.4%) being the most common. Non-ermatophytes represented 46.7%, with Candida spp. (29.5%) as the predominant species, followed by Aspergillus (5.7%), Cladosporium (4.8%), Fusarium (4.8%), and Geotrichum (1.9%). The most commonly affected sites were nails (32.4%) and interdigital areas (33.3%). Statistically significant associations were observed between fungal type and age, HbA1c, Weight, diabetes type, site of infection,. No significant associations were observed with gender, diabetes duration. These findings highlight the impact of clinical and demographic factors among diabetic patients in Zliten.
Effect of Limestone Calcined Clay Cement (LC3) on Properties of Self-Compacting Concrete
Self-Compacting Concrete (SCC) offers clear advantages in constructability and enhanced durability; however, its widespread use is often limited by high cement content and reliance on imported supplementary cementitious materials, particularly in Libya. In this context, Limestone Calcined Clay Cement (LC3) has emerged as a promising alternative for regions with abundant local clay and limestone resources. This study investigates the feasibility of incorporating LC3, produced from locally available materials within the Libyan context, into SCC as a partial replacement of Portland cement at levels of 15%, 30%, and 45%. The experimental results demonstrate that LC3-based SCC satisfies the required acceptance criteria for rheological performance, despite a gradual reduction in flowability with increasing replacement levels. Mechanical testing indicates that a moderate LC3 replacement enhances early-age strength, while higher replacement levels achieve comparable or improved strength at later ages. Tensile-related properties show no adverse effect even at the highest replacement level when compared to the reference mix. Furthermore, the observed reduction in porosity and increase in ultrasonic pulse velocity confirm improved microstructural refinement, which supports the enhancement of mechanical performance. Overall, the results confirm the technical feasibility of using LC3 in self-compacting concrete (SCC) at replacement levels up to 45% with locally sourced materials, achieving performance comparable to or better than the conventional SCC reference.
Thermal Comfort of Buildings Integrated Photovoltaics (BIPV)
In today's modern world, the extensive use of glass façades in commercial buildings has an impact on the overall thermal comfort and energy consumption of these buildings, especially in regions where there is an energy shortage like Palestinian territories. The author is of the opinion that the use of BIPV systems will not only bring about the thermal comfort but also contribute to the overall energy efficiency of the commercial buildings. The work further cites the integration of photovoltaic cells in building skins and the related factors like heat transfer, thermal conductivity, and indoor thermal conditions are considered. The research signals the capabilities of double-skin and solar-integrated façades in cutting down the solar heat gain, cooling and heating load demands, and simultaneously providing on-site renewable energy. The emphasis is on Palestine, where the high solar radiation levels are in stark contrast to the political, economic, and infrastructural challenges in the energy sector. The paper integrates recent research on thermal comfort solutions, façade technologies, and photovoltaic integration, and shows that BIPV façades are a good option for energy consumption mediations and indoor environmental quality enhancement in commercial buildings. The results also clearly show that the installation of solar systems in the building envelop can be a great help in sustainable building design, energy security, and increased tenant comfort which in turn would support the transition to low and zero-energy buildings in Palestine and other similar climates.
Effectiveness of Common Washing Methods in Eliminating Ascaris lumbricoides Contamination from Fresh Vegetables Collected from Farms in Brack Alshatti
Fresh vegetables provide important nutritional value for humans; however, they can become contaminated with enteric parasitic pathogens at various stages, from cultivation to consumption. Therefore, this study aimed to investigate the contamination of Ascaris lumbricoides in fresh vegetables collected from farms in Brack Al-Shatti, Libya, and to determine the most effective method for removing Ascaris lumbricoides egg contamination from vegetables. A total of 70 fresh vegetable samples were randomly collected from vegetable farms in Brack Alshatti. The vegetables included green onion, lettuce, rocket, parsley, chard, carrot, and turnip. Different washing methods were applied, including 5% vinegar, 10% salt, and 20% lemon solutions, in addition to washing with tap water. Microscopic examination for the presence of A. lumbricoides eggs was performed using a direct wet mount technique. Overall contamination with A. lumbricoides was detected in 22.9% (16/70) of the vegetable samples. After washing with tap water, parasitic contamination was detected in 20.0% (14/70) of the samples. Washing with 10% salt reduced the contamination rate to 11.0% (8/70), while washing with 20% lemon reduced it to 4.3% (3/70). The lowest contamination rate was observed after washing with 5% vinegar, at 2.9% (2/70). The results showed persistent contamination with A. lumbricoides in turnip and lettuce when all washing methods were applied. After washing with 10% salt, no contamination was detected in green onion. Furthermore, no contamination was observed in green onion, carrot, rocket, parsley, or chard after washing with 5% vinegar or 20% lemon. These findings highlight vinegar as a superior washing agent, effectively eliminating parasitic contamination while offering a safe and broadly effective solution.
Copyright (c) 2025 Shaheerah Alshareef , Abdulkadir Bernawi, Awatif Abdulsalam https://creativecommons.org/licenses/by-nc/4.0
Impact of Dielectric Substrate Material on the Performance of Microstrip Patch Antennas (MPAs), V-Band
Microstrip Patch Antennas (MPAs) are pivotal components in modern communication systems due to their compact size and ease of fabrication; however, the shift toward the V-band necessitates designs that ensure high gain and efficiency despite challenges related to dielectric loss and narrow bandwidth. This paper analyzes the impact of substrate material properties—specifically dielectric constant and loss—on the performance of an MPA designed for a 55 GHz center frequency within the 50–60 GHz band. Using CST Microwave Studio, the antenna was simulated with uniform dimensions on three Rogers substrates of 0.127 mm thickness: RT/duroid 5880, RO3003, and RO4350B, evaluating gain, efficiency, reflection coefficient (S11), and bandwidth. Simulation results revealed distinct performance variations; the RT/duroid 5880 model (lowest permittivity) achieved the highest gain (6.16 dBi) and directivity (6.82 dBi), making it ideal for long-range applications, while the Rogers RO4350B recorded the highest radiation efficiency (89.6%). Conversely, the Rogers RO3003 model demonstrated the best impedance matching (S11 -19.8 dB) and the widest bandwidth (2.527 GHz). Consequently, the study concludes that optimal material selection depends on specific application priorities, recommending the RO3003 substrate as the premier choice for 5G applications requiring ultra-high data transfer rates due to its superior bandwidth performance.
Harmonic Distortion in Three-Phase Networks Using a 24-Pulse STATCOM: Modeling, Simulation, and Performance Evaluation
Harmonic distortion is one of the most critical challenges affecting power quality in modern industrial networks, particularly under nonlinear loading and dynamic operating conditions. This paper presents the modelling and performance evaluation of a 24-pulse STATCOM designed to reduce total harmonic distortion (THD) in three-phase power systems. The proposed STATCOM structure is developed using four 6-pulse voltage source converters (VSCs) combined with Y–Y and Y–Δ phase-shifting transformers to achieve a 15° phase displacement, enabling natural cancellation of dominant harmonics such as the 5th and 7th orders. A detailed simulation model is implemented in MATLAB/Simulink, and system performance is evaluated under nonlinear loading conditions, including the starting of a 100-HP induction motor. The results demonstrate a significant improvement in power quality, with THD reduced to 1.52% compared to values ranging between 8–12% without compensation, alongside enhanced voltage stability at the point of common coupling (PCC) and minimized voltage sag during transient events. These findings confirm that the 24-pulse STATCOM provides an effective and economical solution for harmonic mitigation, representing a practical alternative to external filters and conventional 6- or 12-pulse compensation systems.
A New Approach for Low-Latency, High-Accuracy Anomaly Detection at the Edge: Benchmarking Quantized Autoencoders, LSTMs, and Lightweight Transformers on RT-IoT2022 Time-Series Traffic
This study benchmarks edge-optimized deep learning models for real-time anomaly detection in resource-constrained IoT environments using the RT-IoT2022 dataset, which includes four benign protocols and nine cyberattack types. Three architectures a quantized autoencoder (QAE), compact LSTM, and lightweight Transformer were deployed on a Raspberry Pi 4 and evaluated on F1-score, latency, model size, and energy per inference. The QAE achieved optimal performance with 98.7% F1- core, 142 KB memory footprint, 1.8 ms latency, and 4.2 mJ energy consumption, outperforming alternatives under strict edge constraints. While the LSTM showed better recall on rare attacks and the Transformer captured long-range dependencies at higher computational cost, the QAE delivered the best overall trade-off for deployable security. The work reframes model selection around hardware- ware co-design rather than architectural complexity, demonstrating that intelligently compressed, reconstruction-based approaches surpass heavier models in efficiency and effectiveness. Findings provide a reproducible framework for low-latency, privacy-preserving intrusion detection in smart healthcare and industrial IoT, advocating a paradigm shift toward minimal sufficiency over maximal capacity in edge AI design.
Effect of Mn-Site Doping on the Magnetic Properties of the La2/3Sr1/3Mn1-xInxO3 Manganite Perovskite
The substitution of Mn with a low concentration of In (x ≤ 0.20) in the magnetoresistance compound La2/3Sr1/3Mn1-xInxO3 has been investigated. Magnetic properties were analyzed using AC magnetic susceptibility and DC electrical resistance measurements. The metal-to-insulator transition temperature (Tp)decreased from 365 K to 245K as the level of In doping increased, indicating a loss of ferromagnetic order. Similarly, the Curie temperature (Tc) of each sample shifted to lower values with higher In content. X-ray diffraction (XRD) analysis revealed a single-phase perovskite rhombohedral structure. Surface morphology and microstructural analysis using scanning electron microscopy (SEM) indicated that withan increase in Indium concentration up to x= 0.20, grain size diminished significantly, reducing from 15 µm to 2 µm, along with noticeable grain agglomeration.
Evaluation and Prediction Performance of Solar Panel and Wind Turbine Systems Using Simulation
Renewable energy is one of the important sustainable energy sources due to its low carbon emissions compared to fossil fuels; however, its performance is affected by climatic conditions. This study aims to evaluate and predict the performance of photovoltaic (PV) systems and wind turbines in Libya through two phases. In the first phase, MATLAB/Simulink was used to model and simulate three PV technologies monocrystalline, polycrystalline, and amorphous and to analyze the effects of solar irradiance and temperature on their performance. The results indicate that monocrystalline modules are more responsive to increased irradiance, while amorphous modules are less sensitive to temperature rise. Wind energy systems were analyzed by comparing two horizontal- xis wind turbines, Gamesa and Acciona, under different wind speeds, where the Gamesa turbine showed superior performance at high speeds. In the second phase, an artificial neural network trained using synthetically generated data achieved high prediction accuracy for both energy systems