Journal of Insights in Basic and Applied Sciences
The Journal of Insights in Basic and Applied Sciences (JIBAS) (ISSN: 3106-1737) is a peer-reviewed, open-access journal published by Alqala Aljadida University in Libya. Located at https://jibas.com.ly/index.php/jibas/en , JIBAS is dedicated to advancing scientific knowledge by publishing high-quality research across various fields of basic and applied sciences. The journal publishes four issues per year. Vision To be a leading platform for scientific discourse and innovation, contributing to the global advancement of knowledge in basic and applied sciences. Mission To provide a high-quality, open-access platform for researchers to publish their original and impactful work, ensuring a rigorous and fair peer-review process. Aims Knowledge Dissemination: To publish cutting-edge research and make it freely accessible to the global scientific community. Scientific Integrity: To uphold the highest standards of academic integrity and promote ethical research practices. Interdisciplinary Collaboration: To foster collaboration among researchers from diverse scientific disciplines. For further inquiries, please get in touch with the editor at jibas.publishing@gmail.com or via WhatsApp at +218927648287.
Developing Low-Calorie Functional Foods Using Directed Fermentation Based on Sugar Substitutesand Natural Sweeteners
The escalating global prevalence of obesity, type 2 diabetes, and metabolic syndrome has intensified the search for effective sugar reduction strategies in food products. This study investigates the development of low-calorie functional foods through directed fermentation using sugar substitutes and natural sweeteners. A systematic formulation approach incorporating erythritol, allulose, steviol glycosides, and monk fruit extract was evaluated across three fermented food matrices: yogurt, kefir, and plant-based fermented beverage. Analytical results demonstrated that allulose-sweetened formulations achieved 92% caloric reduction compared to sucrose controls while maintaining comparable fermentation kinetics (μmax = 0.38–0.42 h⁻¹). Short-chain fatty acid (SCFA) analysis via HPLC revealed significantly enhanced propionate production (18.7 ± 1.2 mM) in isomalt-supplemented fermentations, consistent with gut microbiota modulation observed in recent multi-omics studies. Probiotic viability exceeded 8 log CFU·mL⁻¹ across all formulations, with steviol glycosides exhibiting prebiotic-like effects supporting Lactobacillus acidophilus growth. Sensory evaluation indicated that optimized sweetener blends achieved acceptable palatability scores (≥6.5/9) across all matrices. These findings establish directed fermentation as a viable platform for producing low-calorie functional foods with enhanced metabolic benefits, offering a evidence-based framework for industrial application
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"How the Living Environment Shapes Children’s Neurological Traits and Encourages Them Toward Sports" A Field Study Applied to Primary School students in Al-Maya Municipality - Libya
This study aims to investigate the impact of residential environment on the neurological characteristics of primary school pupils and its role in sports orientation and selection. The research problem stems from the lack of clear understanding of the relationship between residential environment (urban/rural) and children’s neurological and cognitive abilities, and how these factors influence their readiness to engage In sports activities. The descriptive analytical method was adopted, with a sample of 60 pupils (30 males and 20 females) distributed across urban and rural settings. Data collection tools included a residential environment questionnaire, neurological and cognitive tests (reaction speed, attention, working memory, neuromuscular coordination), a sports selection questionnaire, observation sheets, and semi-structured interviews with teachers and coaches. Statistical analyses were conducted using means, standard deviations, t-tests, ANOVA, Pearson correlation, and Chi-square tests. Results revealed significant differences between urban and rural pupils in neurological characteristics, favoring the urban environment. Strong positive correlations were found between neurological characteristics and sports selection indicators. Urban pupils showed higher participation in organized sports compared to rural pupils. Gender differences were also observed: males excelled in reaction speed, while females outperformed in attention and concentration. The study concludes that the residential environment is a key determinant in shaping children’s neurological characteristics, which in turn play a crucial role in sports orientation and selection. Recommendations include integrating neurological and cognitive assessments into sports selection programs, designing educational and sports policies that consider environmental and gender differences, and conducting broader future studies to generalize findings.
A Hybrid CNN-BiLSTM Channel Estimation Framework for DVB-T2 Systems Under Time-Varying Fading Conditions
Digital Video Broadcasting – Second Generation Terrestrial (DVB-T2) remains a cornerstone of terrestrial broadcast television, yet its performance degrades significantly in high-mobility scenarios due to rapid channel variations that violate the quasi-static assumption underlying conventional pilot-based estimation. This manuscript presents a novel hybrid deep learning framework combining convolutional neural networks (CNNs) and bidirectional long short-term memory (BiLSTM) networks for robust channel estimation in DVB-T2 systems operating under time-varying frequency-selective fading. The proposed method leverages scattered pilots to capture local time-frequency correlations while exploiting temporal dependencies across OFDM symbols. Simulation results demonstrate that the proposed approach achieves a 4.2 dB improvement in bit-error-rate performance at a signal-to-noise ratio of 20 dB compared to conventional least-squares and linear minimum mean-square error estimators under vehicular speeds of 120 km/h. The framework maintains computational feasibility for real-time implementation, requiring only 15.6 ms per frame on standard hardware. These findings suggest that integration of lightweight deep learning architectures can extend the operational envelope of existing DVB-T2 infrastructure to emerging mobile broadcast applications.
The Reality of Geopolitical Risk Disclosure in Financial Reports: An Analytical Study of the Content of Financial Reports of a Sample of Libyan Commercial Banks
This study aimed to analyze the reality of geopolitical risk disclosure in the financial reports of a sample of Libyan commercial banks, in light of the growing importance of this type of risk and Its implications for performance and continuity. The study adopted the descriptive-analytical approach by using content analysis of the published financial reports of four Libyan banks, namely: Jumhouria Bank, Sahara Bank, Bank of North Africa, and National Commercial Bank, over the last five years. The analysis was guided by relevant professional and regulatory frameworks issued by the IASB, ISSB, SEC, and GRI, while employing the unweighted dichotomous variable approach. The findings revealed that disclosure of geopolitical risks does exist; however, it remains incomplete, varies across banks, and tends to be more general and descriptive than quantitative and systematic, with limited disclosure of direct financial impacts, management mechanisms, and response measures. The results also indicated a gradual improvement in some banks, although without reaching the level of integrated institutional disclosure. The study recommended the development of more robust disclosure policies, strengthening the quantitative and analytical dimensions of disclosure, linking such disclosure to risk management and business continuity, and issuing a supportive regulatory framework at the level of the Libyan banking sector.
Design and Feasibility of a 50 MW Off-Grid Wind Energy System with Integrated Power Converters for the City of Alasaba, Libya
Off-grid renewable energy systems present a transformative solution for cities facing unreliable grid infrastructure or complete isolation from national power networks. This manuscript proposes a 50 MW standalone wind energy system (WES) with fully integrated power electronic converters to supply the city of Alasaba, Libya. Located in the Jabal al Gharbi District, Alasaba experiences moderate-to-good wind resources suitable for utility-scale generation. The proposed system incorporates Type-IV permanent magnet synchronous generators (PMSG) with back-to-back voltage source converters (VSC), battery energy storage (BESS), and a decentralized microgrid control architecture. Technical specifications, system sizing, converter topology, protection schemes, and operational strategies are detailed. Key challenges—including wind intermittency, black-start capability, frequency/voltage regulation, and desert environmental conditions are analyzed. Benefits include energy independence, diesel displacement, and long-term Levelized Cost of Energy (LCOE) reduction. Simulation results (inferred) demonstrate frequency stability within ±2% and voltage regulation within ±5% under variable wind conditions
Synthesis, Characterization, and Antibacterial activity of Cobalt (II) and Copper (II) Complexes with Urea
This study focuses on the Synthesis and Characterization of Cobalt(II) and Copper(II) complexes with Urea using FT-IR. Their antibacterial actaivity was evaluated using both of positive Gram (Staphylococcus.aureus), and Negative Gram(Escherichia.coli). The result of the findings indicated that the cobalt (II) complex showed the high inhibitory activity compared to copper (II) complex which showed poor effective. Wile, the ligand did not show any effective. This study will be benefit to grow novel possible therapeutic agents.
Effect of Mineral, Nano NPK and Chitosan on Growth Characteristics and Biomass of Two Faba Bean (Vicia faba L.) Varieties in Wadi Atba, Libya
Faba bean (Vicia faba L.) is a critical leguminous crop that plays a vital role in food security; however, it is productivity under semi-arid conditions is limited because of low nutrient use efficiency. In the 2024/2025 growing season, a field experiment was conducted in Wadi Atba, southern Libya, to evaluate the effect of mineral ,nano NPK fertilizer and chitosan on the growth and biomass production of two types of faba bean (local and imported). The experiment was arranged in a factorial randomized complete block design (RCBD) with three replications and seven fertilization treatments: control, mineral NPK(NPK min), nano NPK (NPK Nps), chitosan, 50% nano NPK + 50% mineral NPK, mineral NPK + chitosan, and nano NPK + chitosan. The results revealed that fertilization treatments and their interactions with cultivar had a significant impact on all the variables studied. The combined application of nano NPK and chitosan consistently recorded the highest values in terms of plant height, number of leaves , leaf area, fresh and dry biomass, biological yield and straw yield in both varieties with the imported cultivar showing higher performance compared to the local one. Followed by a 50% nanoNPK+ 50% mineral NPK. The findings show that nano fertilizers when used together with chitosan enhances nutrient use efficiency, vegetative growth and biomass productivity of faba bean in semi-arid conditions. This approach represents a promising and sustainable strategy for reducing reliance on the conventional mineral fertilizers and improving crop productivity.
The Impact of Using Artificial Intelligence Technologies on Improving Architectural Design
Artificial intelligence technology has been rapid development or several fields, most particularly architectural design, in terms of building design quality, increased construction efficiency, and reduced costs and working time. AI plays a significant program that able to handle unlimited amounts of data, which facilitates the design process. The designer can choose from a range of design ideas without needing to create many preliminary plans. It has been considered the technology of the future for the coming years. Through applications such as virtual reality and augmented reality, it contributes to the development of many designs, addressing design errors and delivering high-quality design work. The research concluded with several recommendations that would introduce modern software that contributes to the development of modern ideas. In addition to patterns in architectural design, meeting needs and raising the efficiency of the labor market with minimal effort and in a short time
Enabling Smart Manufacturing through Automated Quality Management Systems in the Era of the Fourth Industrial Revolution
This study aimed to enable smart manufacturing through automated quality management systems (AQMS) in the era of the Fourth Industrial Revolution. It explores this through a systematic review of contemporary literature. By analyzing key studies, this paper identifies a crucial shift from end-of-line defect detection to proactive, real-time monitoring, supported by the Internet of Things (IoT) and cyber-physical systems (CPS). The findings highlight several key pillars of this digital transformation: the application of artificial intelligence (AI) and machine learning (ML) for quality prediction; the use of digital twins for comprehensive personalization; and the application of blockchain technology for digital tracking and regulatory compliance, particularly in sensitive sectors such as medical device manufacturing. Furthermore, the study addresses the "human factor," emphasizing that the successful implementation of AQMS depends on upskilling the workforce and fostering seamless human-machine collaboration. This research proposes a comprehensive conceptual model that bridges the gap between traditional total quality management and the demands of the Fourth Industrial Revolution, providing a strategic roadmap for achieving self-regulating quality systems within a modern industrial context..
Automated Quality Management Systems (AQMS)
Exploring The Awareness and Application of Maitland's Theory Among Physiotherapists in Southern Libya: A Quantitative and Qualitative Investigation
This quantitative and qualitative cross-sectional study aims to investigate the awareness and application of Maitland's Theory among physiotherapists in Southern Libya. The research addresses a critical gap in the literature concerning the utilization of Maitland mobilization techniques in the region, given the unique healthcare challenges faced by Libya, particularly in its Southern region. Drawing on a sample size of 380 physiotherapists, data will be collected using a structured questionnaire administered electronically through platforms such as Google Forms. The questionnaire will include sections assessing socio-demographic information, levels of awareness and familiarity with Maitland's Theory, utilization of Maitland mobilization techniques in clinical practice, and perceived barriers to adoption. The study participants will consist of licensed physiotherapists actively engaged in clinical practice across various healthcare settings in Southern Libya. Data analysis will involve descriptive and inferential statistics to summarize demographic characteristics, explore relationships between variables, and identify factors associated with awareness and utilization of Maitland's Theory. The validity and reliability of the research instrument will be ensured through content validity, pilot testing, and test-retest reliability analysis. Ethical considerations will be addressed by obtaining approval from the institutional review board and ensuring participants' informed consent, confidentiality, and voluntary participation. The findings of this study are expected to provide valuable insights into the current state of physiotherapy practice in Southern Libya, potentially informing targeted interventions to enhance the knowledge and skills of physiotherapists and improve the quality of musculoskeletal care delivery in the region.
The Effect of Using (AI) Programs to Find the Increasing Production in Oil and Gas
This paper deals with the study of the oil industry have embraced digital transformation, leveraging software to further boost production efficiency. Advanced software solutions now play a crucial role in monitoring, optimizing, and managing oil production, offering real-time data insights, predictive analytics, and scenario modeling. The tools help operators make smarter decisions, reduce downtime, and maximize output. This paper delves into the intersection of traditional oil production methods and modern software solutions, with a particular focus on PIPSM (Production Integrated Planning and Scheduling Management) programs. PIPSM software is designed to streamline the entire production process, from planning, scheduling to execution, and monitoring, ensuring that artificial lift methods are deployed with maximum efficiency. Through a practical case study, the project demonstrates the real-world application of PIPSM in an oil field, illustrating how it enhances production, reduces operational costs, and optimizes the use of artificial lift techniques. The results underline the transformative potential of integrating software into oil production operations, offering a glimpse into the future of a more efficient and technologically advanced industry. In conclusion, this project highlights the critical role that software plays in modernizing oil production, ensuring that even as reservoirs age, the industry can continue to meet global energy demands with greater efficiency and sustainability.
Applications of Artificial Intelligence in Supporting Digital Transformation and Evaluating Academic Performance in Libyan Universities: An Analytical Study
An abstract is a summary of entire paper should be written in Times New Roman with font size- 10. Author can select Normal style from styles of this template. The abstract should not be more than 250 words and written in single paragraph. This electronic document is a “live” template. The abstract includes the overall purpose of the study you investigated, the basic design of the study, results of your analysis and brief summary of your interpretations and conclusion. An abstract is a summary of entire paper should be written in Times New Roman with font size- 10. Author can select Normal style from styles of this template. The abstract should not be more than 250 words and written in single paragraph. This electronic document is a “live” template. The abstract includes the overall purpose of the study you investigated, the basic design of the study, results of your analysis and brief summary of your interpretations and conclusion.
Contemporary Plastic Arts Between Artistic Thought and Aesthetic Transformations
This research examines contemporary visual arts as a visual discourse that Reflects transformations in aesthetic, cultural, and philosophical thought under modern social and technological changes. It aims to clarify the fundamental differences between modern art and contemporary art, highlighting the characteristics of the contemporary phase, such as the diversity of media, the liberation of form, and the dominance of concept over the formal structure of the artwork the study also discusses the philosophical and aesthetic roots of contemporary art and the role modernism and postmodernism in shaping the relation ship between form and content furthermore it addresses the transformation of the artwork from a purely aesthetic visual product into an open intellectual and symbolic structure subject to interpretation. The research emphasizes the importance of visual discourse and symbolism is contemporary artistic expression, as well as the role of the viewer in completing the aesthetic meaning , making the art work an interactive space that reflects the concerns and existential and cultural issues of contemporary humanity
An Integrated YOLO–OCR Architecture for Real-Time Automatic Number Plate Recognition (ANPR) in Intelligent Access Management
This project presents a real-time Automated Number Plate Recognition (ANPR) system developed to support intelligent vehicle access management in controlled and security-sensitive environments. The proposed solution combines image processing with instant decision-making to enable a secure, contactless, and autonomous gate control mechanism. It responds to the increasing demand for efficient access systems, particularly in high-security locations such as institutional facilities and residential compounds. The framework is designed to be scalable and practical for deployment in real-world scenarios through a tight integration of hardware and software components. The detection module relies on YOLOv11, which was fine-tuned to accurately localize license plates under varying conditions. For character recognition, EasyOCR was adopted to reliably read both Arabic and English plate formats. A PostgreSQL database serves as the backend layer, enabling structured storage of plate records and efficient log management. Development was carried out using Visual Studio Code for Python scripting, debugging, and project organization. The overall architecture integrates ESP32-CAM units for image acquisition, Python-based real-time processing, and a user-friendly dashboard for monitoring captured plates and reviewing logs. To validate performance, the system was evaluated across diverse operational settings, including low-light environments and high-glare scenes, to ensure robustness and stability. The results demonstrated fast response times and low latency in both detection and recognition tasks, alongside smooth communication between the user interface and the database layer. Overall, the final implementation delivers a secure, efficient, and cost-effective access control solution that can be adapted for a wide range of public and private surveillance and entry-management applications.
Automatic Number Plate Recognition (ANPR)
Strategic Integration Between Lean and Agile Manufacturing Methodologies and Resilient Supply Chains in The Context of Modern Supply Chains
The study aimed to extends the lean manufacturing technology, Agile manufacturing to modern supply chains for application in enterprises as a methodology appropriate to competitive conditions resulting from the nature of demand, product intent, level of disruption and volatility in supply, and develop a comprehensive strategic vision that helps organizations move from reactive to disruptive to proactive and adaptive and through a deeper understanding of available philosophical tools and use them in building a sustainable and competitive supply chain.
On Some Fixed Point Results in Complete 2-Metric Spaces
The present paper proves a number of related results concerning fixed points in the area of complete 2-metric spaces. These results represent versions of several fixed-point theorems in complete metric spaces that were established in the literature at a later stage. By extending classical results from metric spaces to the more general framework of 2-metric spaces, we aim to provide deeper insight into the structure and behavior of mappings defined on such spaces. In particular, we investigate conditions under which the existence and uniqueness of fixed points can be guaranteed. The obtained results not only generalize well-known theorems but also contribute to the ongoing development of fixed-point theory in generalized metric settings.
The Extent To Which Blockchain Technology Can Be Applied To The Supply Chains Of The Medical Supply Authority, Eastern Region Branch, In Benghazi
The study aimed to identify the extent to which blockchain technology can be applied to supply chains of Medical Supply Authority in the Eastern Region, Benghazi branch, the study followed the descriptive approach, and the study population consisted of employees of the medical supply Authority in Eastern Region, Benghazi branch, numbering (60) employees. A random sample was selected according to the table of Krejcie and Morgan (1970), which determined the sample size to be (52) individuals, the study data was collected using questionnaire form, and the number of forms valid for analysis was (47) questionnaire, the results of study showed that there is a high level of awareness and understanding of blockchain technology among the employees of The Medical Supply Authority, and that the availability of capabilities to apply blockchain technology was at moderate level, The result of study also showed that the most significant obstacle are organizational followed by legal, and then legislative obstacles that hinder the application of blockchain technology, the study recommended several recommendations the most important of which is enhancing employees awareness of the important of applying blockchain technology.
Genereliaed Upper and Lower Approixmations for Anti-Topology and their Structral Properties
This paper aims to study roughness in Ant-topology. In addition, we performed a comparison with approximations in classical topology. We found that the boundaries become wider as ambiguity increases, reflecting a more accurate model of uncertainty and approximation in complex. Moreover, we explain how effect of rough approximation on the result of ant-topology by creating more space for ambiguity and approximation, allowing for better modeling accuracy of phenomena characterized by high uncertainty, despite increased mathematical complexity.
Evaluation of the Level of Educational Service Quality in Intermediate Technical and Vocational Education Institutes from the Trainers’ Perspective: A Case Study of Intermediate Technical and Vocational Education Institutes – Tripoli
This study aimed to evaluate the level of educational service quality in intermediate technical and vocational education institutes from the perspective of trainers, taking the intermediate technical and vocational education institutes in Tripoli as a case study. To achieve the objectives of the study, a set of methodological steps and procedures were undertaken. The study adopted the descriptive approach, and a questionnaire was used as the primary tool for data collection. The study population consisted of 474 trainers distributed across three institutes in the Municipality of Tripoli. A stratified random sample of 212 respondents was selected, of which 180 valid questionnaires were obtained for analysis. Descriptive and analytical statistical methods were employed, including percentages, frequencies, means, standard deviations, and hypothesis testing. The primary data were analyzed using the Statistical Package for the Social Sciences (SPSS). The study reached several key findings, most notably: the limited availability of laboratories and workshops equipped with modern devices in the institutes under study; the diversity of student activities does not adequately suit all students; shortcomings in the institutes’ administration in delivering services accurately and on time; the institutes do not regularly measure student satisfaction with the services provided; and there is no continuous communication between top management and students to better understand their needs.
Analytical and Numerical Study of the Zeros of the Error Function, Local Conformality and Sectorial Asymptotic Behavior
The complex error function erf(z) plays a critical role in applied mathematics, physics and engineering; however, several of its deeper analytical properties in the complex domain remain insufficiently explored. This paper presents a comprehensive analytical and numerical study of erf(z), focusing on its zero distribution, conformal mapping behavior and sectorial asymptotic structure. By employing classical tools from complex analysis, including Rouché's Theorem, the Argument Principle and contour integration, we investigate the structure of potential zero-free regions and provide numerical evidence for the absence of zeros in certain bounded sectors. Specifically, numerical exploration suggests that no zeros occur in selected bounded angular sectors within a computational precision of 10^(-8), consistent with the analytical structure derived in this study. The conformal character of erf(z), as an entire and non-constant function, is examined through Jacobian analysis and domain-coloring visualizations, revealing its angle-preserving yet scale-distorting transformations of canonical domains. Furthermore, we analyze sectorial asymptotic expansions as |z|→∞ and demonstrate that Padé approximants reduce the relative numerical error by up to 30% compared with classical truncated series, particularly in boundary sectors where convergence deteriorates. These results provide a more robust understanding of the analytic and geometric behavior of erf(z), with practical implications for complex modeling in statistical physics, quantum theory and signal processing.
Order And multiplication Reversing In Lattice Ordered Groups
Hybridizing Particle Swarm Optimization with the Filled Function Method for Enhanced Global Optimization Performance
This research proposes a novel hybrid optimization algorithm that integrates Particle Swarm Optimization (PSO) with the Filled Function Method (FFM) to address the persistent challenges of premature convergence and local optima entrapment in high-dimensional, multimodal optimization problems. The hybrid PSO–FFM algorithm incorporates a one parameter filled function that dynamically modifies the search landscape when stagnation is detected, enabling systematic escape from deceptive basins while maintaining PSO’s exploration-exploitation balance. Experimental evaluation across eight benchmark functions (Sphere, Rosenbrock, Rastrigin, Griewank, Ackley, Schwefel, Zakharov, and Alpine1) demonstrates significant performance improvements, with the hybrid algorithm achieving up to 100% enhancement over standard PSO in several cases. The proposed method offers a robust framework for complex optimization tasks, particularly in engineering and computational applications where traditional metaheuristics struggle with complex search landscapes.
Application of Particle Swarm Optimization Algorithm to Optimal Economic Load Dispatch: A Case Study of the Western Libyan Power System
Economic Load Dispatch (ELD) is a fundamental optimization problem in power system operation that aims to minimize the total fuel cost of electricity generation while satisfying system constraints such as power balance and generator operating limits. Due to the nonlinear and nonconvex nature of practical power systems, classical optimization techniques often fail to provide optimal and reliable solutions. In this paper, the Particle Swarm Optimization (PSO) algorithm is applied to solve the optimal economic load dispatch problem of the Western Libyan Power System. The proposed approach models generator fuel cost functions as quadratic equations and incorporates essential operational constraints. Several simulation scenarios with different load levels are investigated to evaluate the performance of the PSO algorithm. The results demonstrate that PSO effectively achieves minimum fuel cost while maintaining system constraints, showing fast convergence and robust performance. The study confirms that PSO is a suitable and efficient metaheuristic technique for solving complex economic load dispatch problems in real power systems, particularly under realistic operating conditions of the Libyan power grid
A Comprehensive Review of Energy Storage Batteries for Solar Energy Systems
Solar energy intermittency necessitates efficient energy storage for grid stability and reliable power supply. This review comprehensively examines battery technologies for solar photovoltaic applications, including lead-acid, lithium-ion (LFP, NMC, LTO), flow batteries (vanadium redox, zinc-bromine), and emerging systems such as sodium-ion, solid-state, and saltwater batteries. We evaluate performance characteristics—energy density, cycle life, round-trip efficiency, depth of discharge alongside cost-effectiveness, thermal management requirements, environmental impact, and application suitability across off-grid, residential, and utility-scale installations. Lithium-ion batteries currently offer optimal balance of efficiency (90–95%) and lifespan (2000–6000 cycles), while flow batteries provide exceptional scalability for long-duration storage. Lead-acid remains cost-effective for low-budget systems despite limited cycle life. Critical challenges include degradation mechanisms, thermal runaway risks, recycling infrastructure, and upfront capital costs. Emerging trends second-life EV batteries, AI-optimized management, hybrid supercapacitor integration, and sustainable material innovation are shaping future deployment. This synthesis guides researchers, policymakers, and industry stakeholders toward techno-economically viable and environmentally sustainable solar energy storage solutions.
Impact of Hydroponic Versus Soil Cultivation on Germination, Chlorophyll Content, and productivity of Arugula plant (Eruca sativa Mill)
Plants face many stresses from soil, such as water shortage, water quality and nutrient availability, which ultimately affect the growth and productivity of the plant. This study aims to verify the effectiveness of using hydroponics compared to soil cultivation, where the seeds of (Eruca sativa Mill.) were planted in both cultivation systems, using a model of hydroponics and a model of soil. The experiment was designed according to a completely randomized design (CRD), with (24) replicates for each model treatment. The germination rate, chlorophyll content, and productivity of (Eruca sativa Mill.) grown in all models were measured. The results showed that there were very significant differences (P<0.001) between the treatments. The germination rate and chlorophyll content for hydroponics and soil cultivation were (78.7%, 48SPAD) and (26%, 30SPAD), respectively. The results of this study also showed that the average of productivity for (Eruca sativa Mill.) grown in the hydroponic system was four times higher than it was for (Eruca sativa Mill.) grown in a soil system. These results are considered motivate to research and delve into this field.
From Challenge to Transformation: AI Integration in Libyan Higher Education - An Analytical Review of Challenges and Proposed Integration Strategies
This paper examines the key role of AI and its transformative applications in the Libyan higher education environment. Despite the numerous challenges facing the Libyan educational system, AI offers innovative solutions to improve the quality of education, enhance institutional performance, and deliver personalised learning experiences. This paper reviews various applications of AI in education with particular emphasis on adaptive learning systems, intelligent tutoring platforms, the automation of administrative processes, and educational data analysis. Based on this review, this paper proposes a practical multi-stage framework for integrating AI into Libyan higher education. This comprehensive plan includes capacity development, infrastructure enhancement, pilot project implementation, and scaling of successful initiatives. Additionally, this paper examines potential barriers to integration, such as limited financial resources, community resistance to change, privacy concerns, inadequate technological infrastructure, insufficient skilled personnel, and no existing legal and regulatory structure. To address these challenges, this paper presents strategic recommendations, including fostering public-private partnerships and investing in R&D. This paper makes the case that adopting AI in Libyan higher education is a strategic imperative, not merely a technical option, essential for securing a prosperous and sustainable educational future.
Analytical Study of Some of The Active Compounds in The Clove Plant
This study aims to extract clove oil (eugenol) from different samples obtained from the local market in the city of Misrata and to determine their phenolic and flavonoid contents, in addition to verifying the oil composition using infrared (IR) spectroscopy. Three clove samples (dried buds, ground buds, and freshly ground buds) were collected and the oil was extracted by hydro distillation, then separated by adding sodium bromide and ethyl acetate, and drying the organic layer with sodium sulfate. Phenolic compounds were determined using the Folin reagent, while flavonoids were determined using aluminum chloride. Absorbance was measured using a UV-Visible spectrophotometer at wavelengths of 765 nm for phenolics and 433 nm for flavonoids. The results showed that the samples contained varying levels of phenolics and flavonoids. Sample (A) recorded the highest phenolic content before extraction, whereas the highest post-extraction phenolic content (in the organic layer) was observed in sample (B). Sample (C) showed the highest flavonoid content after extraction. Infrared spectra confirmed that the composition of the isolated oil matched that of standard eugenol, indicating its purity. The percentage of volatile oil extracted from clove ranged between 9.53% and 13.2%, which is close to reference values reported in previous studies, confirming the efficiency of the extraction method and the quality of the studied samples.
Low-Complexity Image Compression Using Semantic-Aware Block Truncation Coding
Block Truncation Coding (BTC) is a simple and computationally efficient image compression technique, but its fixed quantization strategy often leads to suboptimal perceptual quality, particularly in textured and edge-dominant regions. To address this limitation, this paper proposes a Semantic-Aware Block Truncation Coding (SA-BTC) scheme that integrates local variance as a semantic feature to adaptively control quantization at the block level. By adjusting compression strength according to texture characteristics, the proposed method preserves structural and semantically important details in high-variance regions while applying stronger compression to smooth areas. Experimental evaluations conducted on standard benchmark images demonstrate that SA-BTC achieves improved perceptual reconstruction quality compared to conventional BTC. Although the proposed method exhibits lower peak signal-to-noise ratio (PSNR) and structural similarity index (SSIM) values than classical BTC, this behavior is expected due to its semantic-aware design, which prioritizes visually significant regions such as edges and facial features over background fidelity. Visual inspection confirms that SA-BTC better preserves edge continuity, contrast, and meaningful structures, including tripod edges, clothing details, and facial components, despite mild block artifacts in homogeneous regions. These results indicate that conventional pixel-based metrics may underestimate the perceptual and semantic quality achieved by SA-BTC. Overall, the proposed approach enhances rate distortion performance from a perceptual perspective without increasing computational complexity, making it well suited for low resource image compression applications where semantic and visual fidelity are more critical than strict pixel-wise accuracy.
Design, Implementation, and Techno-Economic-Environmental Assessment of a Hybrid Solar Energy System: A Case Study of an Educational Institution in Al-Qubbah, Libya
The transition toward renewable energy sources, particularly solar energy, represents a strategic approach to addressing the environmental and economic challenges associated with dependence on conventional energy sources, achieving sustainable development requirements, and reducing carbon emissions. This study aims to design, implement, and evaluate the technical, economic, and environmental performance of a hybrid solar energy system to supply part of the electrical loads of the Electrical Engineering Department at the College of Engineering Technology in Al-Qubbah, Libya. The study adopted an integrated scientific methodology that included electrical load analysis, hybrid solar system design, and component selection based on operational efficiency and reliability criteria. This was followed by system implementation and operational testing under both no-load and actual operating conditions, in addition to a comprehensive technical and economic performance assessment. Prior to system implementation, the total electrical load of the department was 4500 W, of which 1600 W were supplied by the proposed solar system. Given that the department operates for five hours per day, the daily energy consumption of the supplied loads was estimated at approximately 8000 Wh/day. By applying a safety factor of 20%, the design energy demand was increased to 9600 Wh/day. The system consists of six photovoltaic panels with a total rated capacity of 2760 W, a 4200 W hybrid inverter operating at 24 V equipped with an integrated 120 A charge controller, four gel batteries with a total capacity of 500 Ah configured to provide a 24 V system voltage, and a comprehensive electrical protection system. The results indicate that the system was able to supply approximately 35.5% of the department’s total electrical load, demonstrating satisfactory operational efficiency and stable performance. Despite the relatively limited annual economic return of about 400 Libyan dinars, attributable to government subsidies on electricity tariffs, the findings confirm the technical and environmental feasibility of the system through reduced conventional energy consumption and lower carbon emissions.
The Positive and Negative Effects of the Oil Viscosity on Internal Combustion Engine Oils (Gasoline – Diesel) in Libya
This research aims to study and analyze the technical characteristics and practical performance of internal combustion engine oils (gasoline and diesel) and the effects of their viscosity in the Libyan context. The research focuses on analyzing the relationship between viscosity and temperature under Libya's diverse climatic conditions, while evaluating the properties of different oils and providing practical recommendations for selecting the appropriate oil. The study begins by explaining the fundamental properties of oils, specifically viscosity and its indicators (kinematic and dynamic), pour point, flash point, and total base number (TBN). It also covers the manufacturing process, starting from the vacuum distillation of crude oil, through the stages of solvent extraction and removal of asphalt and wax, and concluding with the addition of enhancing agents, detergents, dispersants, and other chemical additives that improve oil performance. The research presents a comparative analysis of major global oil classifications, such as SAE, API, and ACEA, and links them to local needs in Libya, recommending multi-grade oils (e.g., SAE 10W-40) for their ability to adapt to thermal fluctuations between winter and summer. The research also discusses the main types of oils available in the market: mineral, synthetic, semi-synthetic, and high-mileage oils, highlighting the advantages and disadvantages of each. In the practical aspect, the research provides recommendations for oil change intervals (every 3,000–6,000 km depending on the season and conditions), while emphasizing the importance of periodic maintenance and using suitable oils for both old and modern engines. The research concludes by stressing the need to raise awareness among Libyan consumers about oil selection criteria, enhance market quality control, and conduct further field studies to evaluate the actual performance of oils under Libya's specific conditions.
Osama Hamad Abd Alsalam Alasamar Alhadheeri