University of Tripoli

Objectives: The identification of novel antimicrobial agents for use in root canal treatment may provide opportunities to improve treatment outcomes. This study aimed to assess the antimicrobial efficacy of different molecular weights of chitosan (CS), and how modification with CS may impact on the antimicrobial, physico-mechanical and biological properties of Biodentine™, a calcium-silicate-based material used in endodontics. Methods:C. albicans biofilms were treated with either 3% sodium hypochlorite (NaOCl) or a 0.05% or 0.1% CS solution for 5 min. The growth medium was replenished, and cells were re-incubated for additional 72 h. Regrowth of biofilms was assessed using a colorimetric XTT assay. Additionally, multispecies biofilms were established and the regrowth of biofilms on Biodentine discs were quantified following the addition of 0.5 wt% and 1 wt% of CS powder using qPCR. The physico-mechanical and biological properties of the new composite of Biodentine and CS were also evaluated. Results: Viability readings revealed significant initial biofilm inhibitory effects of CS solutions, followed by significant regrowth after 72 h. Upon the addition of CS to Biodentine, significant reductions in multispecies biofilm regrowth were determined. Notably, the antibiofilm activity of CS was found to be increased as the molecular weight decreased. The addition of powdered CS of low molecular weight showed a reduction in the mechanical properties of Biodentine, whereas no detrimental effects on the other material properties were noted. Conclusions: Chitosan may not be useful as an alternative irrigant to NaOCl. Addition of CS to Biodentine represents a potential means of augmenting the antimicrobial activity of Biodentine against persistent microorganisms following endodontic therapy. Despite the reductions in mechanical properties of the material, the new composite still represents a viable material option when material strength and hardness are not critical.

In current study, two novel polymers derived from original Chitosan is synthetized. Polymeric blends from Chitosan and the new polymers are used to fabricate spin coated thin films. The effect of UV irradiation on the optical properties of pristine Chitosan and two novel Chitosan derived polymers blends in form of thin film structure are studied. The optical parameters of the blends thin films such as the refractive index (n), extinction coefficient (k) and dielectric constants are determined by spectrophotometric technique in the spectral range 200–2500 nm. The energy gap values (Eg), dielectric constants at infinity (ε∞), lattice permittivity (εL) and dispersion parameters are calculated. Eg is found to be 5.14 eV for Chitosan film and it is reduced to 4.25 and 4 eV for the two polymeric blends. ε∞ is calculated to be 2.96 for Chitosan film which is reduced to 2.88 upon UV irradiation. The influence of exposing thin films to UV light demonstrates interesting modifications in linear and nonlinear optical properties (third order non-linear susceptibility and the non-linear refractive index) of Chitosan and its derivatives. The emission characteristics of the blends are also investigated. The fluorescence intensity of the polymeric films is decreased upon UV exposure. The obtained results propose that Chitosan and its derivatives are possible candidates for opto-electronic applications such as optical switching, optical limiters and OLED.

Nodal Analysis, defined as a systems approach to the optimization of oil and gas wells, is used to evaluate a complete producing system thoroughly. Every component in a producing well or all wells in a producing system can be optimized to achieve the objective flow rate most economically. In our study, two wells from the Ghani oil field have been used as a case study. Three production tests and a flowing pressure survey were collected and analysed using PROSPER Software to estimate the well productivity index at different times, as well as to calculate and plot the pressure gradient and compare the results obtained by different methods with the actual one. Consequently, to find the best method that gives us the least value of error comparing with actual one used to construct IPR-VLP performance (Nodal Analysis). The measured vertical flow pressures, for most wells, matched very well with the Fancher-Brown multiphase vertical correlation pressure. This behaviour is obtained because the wells are producing under natural flow. The sensitivity analysis has been performed to predict the future reservoir performance at different reservoir pressures, water cut, and Gas Oil Ratio (GOR). In the selected wells, the total oil reserves, remaining reserves and remaining productive life were estimated using Decline Curve Analysis (DCA), furthermore and at time in future, we could predict the future oil flow rate, reservoir pressure and bottom hole flowing pressure by linking the Decline Curve Analysis with the Nodal Analysis, finally, the prediction results revealed that the wells can continue producing for only a few more years.

n this paper, metamaterial approaches are used to improve the gain, bandwidth, and radiation efficiency of microstrip patch antennas for 60GHz applications. In order to lower surface wave losses and improve the performance of proposed antennas, this work investigates a variety of techniques, including the use of metamaterials as antenna lens and as electromagnetic bandgap (EBG) structures. To overcome the narrow bandwidth (2 GHz) and low gain (1.9 dB) of a conventional GaAs-based microstrip patch antenna operating at 60GHz, several enhancements were investigated via HFSS simulations, the result were cross validated and compared using CST Microwave Studio. Integrating an Electromagnetic Band-Gap (EBG) structure improved performance to a 7.3GHz bandwidth and 3.5dB gain. The most substantial enhancement was realized by combining the EBG with a lens technique, achieving a 10GHz bandwidth and 4.8dB gain. These results confirm that metamaterial-inspired techniques are highly effective for advancing high-frequency antennas, particularly for 60GHz communication systems.

Remediating petroleum-contaminated soils from oil fields is one of the most challenging tasks for both the Libyan oil sector and the global oil industry. It is therefore necessary to isolate and identify bacteria capable of metabolically synthesising biosurfactants from oil-contaminated soil, as they can be used for bioremediation. Two bacterial strains, which degrade petroleum hydrocarbons and produce biosurfactants, were isolated from oil-contaminated soils in the southern Sirte basin in central North Libya, using an enrichment technique. Morphological, biochemical, and 16S rRNA analyses indicated that the isolates are more likely to be of the species Dietzia cinnamea and Rhodococcus pyridinivorans. The biodegradation efficiency (BE) of crude oil and diesel oil separately (1% v/v) was evaluated after 14days of incubation for both strains using the GC-FID technique. The strains effectively degraded 91.87% and 75.35% of the crude oil. Whereas for diesel oil, they displayed a lower BE of 87.61% and 70.14%, respectively. Multiple screening tests were then used to check for the production of bioemulsifiers in the bacterial isolates. The drop collapse test was positive for both bacteria tested, collapsing the culture supernatant in less than 30s. The oil spread test performed with crude oil showed a clear zone of 2.98 ± 0.02cm and 2.71 ± 0.04cm in diameter, respectively. Furthermore, the emulsification index (E24) of biosurfactant against diesel oil was measured to be 34 ± 0.17% and 30.8 ± 0.3%, respectively. It was found that biosurfactants can enhance the efficiency of oil degradation, which makes them attractive for future application in the MEOR (microbial enhanced oil recovery) process. Therefore, it has potential applications in bioremediation.

Decline curve analysis (DCA), in petroleum engineering, is a tool being used to do many calculations, for instance: to estimate original oil in place, to estimate ultimate oil reserve (EUR) at initial reservoir conditions, to estimate remaining oil reserves from certain time to the end of reservoir age (that to be at future reservoir abandonment pressure or economic production rate), to forecast future production rate at any desired time and predict the reservoir performance. The basis of decline curve analysis (DCA) is to match past production performance histories or trends (i.e., actual production rate/time data) with a “model” assuming that future production continues to follow the past trend. The decline-curve methods apply to individual wells or an entire reservoir. This project presents basic concepts and applications of decline curve analysis using OFM software. Well-testing data from ten producer-wells in the Farrud reservoir were collected and subjected to DCA calculations through OFM software. The results showed that, for the whole Farrud reservoir, the economic flow rate was about 300 STB/D of oil, the recoverable reserves at initial reservoir conditions (EUR) were 80.2 MMSTB oil, and the remaining reserves at the time of study were 19.96 MMSTB oil, with an expected abandonment date of November- 2058. The decline curve analysis for the entire field is more reliable than for the wells, and the remaining reserve for the entire reservoir is very close to the summation of the remaining reserves for the ten well producers. Finally, it is preferable to evaluate the reserves with other methods, such as the MBAL software or utilizing the Petrel software to conduct the reservoir simulation study, in order to ensure that the results that have been obtained are dependable.

The investigation examined the protective potential of aqueous extract of Morinda lucida leaf (ML) on aluminium chloride (AlCl3)-mediated testicular damage in rats (male) and determined if its secondary metabolites could modulate proteins linked with erectile dysfunction. Rats in the treatment groups were administered 30mg/kg bw AlCl3, with doses of 125mg/kg bw and 250mg/kg bw of the plant extract. Phytocompounds identified in the plant were also screened for potential phosphodiesterase-5 and arginase inhibitor molecules. After 21 days of treatment, sperm count in the animal group treated with only AlCl3 decreased significantly, though with no effect on sperm motility. Administration of ML improved sperm morphology in the extract-treated group compared to the untreated group. Moreover, the leaf extract reversed the elevated myeloperoxidase activity, IL-6, TNF-α, and nitrite concentration observed in the untreated group to near control levels in the plant treatment groups. Molecular docking analysis showed that stigmasterol (-10.2kcal/mol) and oruwacin (-8.2kcal/mol) had the best respective binding energies against the phosphodiesterase-5 and arginase proteins. The 300ns dynamics simulation further revealed the compounds' good stability at the enzymes' active sites. Further experiments will be required to determine the potential alternative therapeutic interventions of the plant in preserving male fertility.

Avian oncogenic viruses represent a major cause of neoplastic and immunosuppressive diseases in poultry, leading to substantial economic losses worldwide and providing valuable models for studying virus-induced tumorigenesis. Among these viruses, Marek's disease virus, avian leukosis virus, and reticuloendotheliosis virus induce lymphoid and hematopoietic malignancies through distinct yet convergent molecular mechanisms. Increasing evidence indicates that microRNAs and their viral homologs are central regulators linking viral infection to oncogenic transformation, immune dysregulation, and pathological outcomes. This review provides an integrated overview of microRNA's role in the pathogenesis and pathology of avian oncogenic viral diseases, emphasizing its contributions to lymphocyte proliferation, survival, immune modulation, and tumor development. We discuss the unique case of Marek's disease virus, in which a viral microRNA ortholog is indispensable for tumor induction in vivo, representing the first direct demonstration of a virus-encoded microRNA acting as a primary oncogenic factor in a natural host. In contrast, avian leukosis virus and reticuloendotheliosis virus exploit host microRNA pathways through insertional mutagenesis and NF-κB-mediated transcriptional activation, respectively, contributing to tumor progression in a context-dependent manner. The review further correlates molecular findings with gross and microscopic pathological lesions. It highlights how microRNA-driven regulatory networks shape disease severity, tissue tropism, and tumor morphology. So, these insights establish microRNA as a conserved molecular hub in avian viral oncogenesis and underscore its relevance for understanding viral tumor pathology, improving differential diagnosis, and advancing comparative oncology across species.

Accurate grading of cervical intraepithelial neoplasia (CIN1-3) from colposcopic images is clinically critical yet challenging due to subtle inter-grade morphology and substantial imaging variability. We propose an attention-guided mixture-of-experts (MoE) framework that ensembles five pretrained DenseNet-121 experts and employs an attention mechanism over pooled intermediate features to drive a gating network that adaptively weights expert outputs for each image. Operating on feature representations rather than raw pixels allows the gating network to perform input-specific expert selection and improves robustness to ambiguous cases. Using the Intel & MobileODT cervical screening dataset with a strict patient-wise 70/10/20 split, we report mean performance over five runs with 95% confidence intervals. On the independent test set, the proposed MoE achieves 74.0% ± 1.6 accuracy and 72.1% ± 1.8 F1, with per-class AUCs of 0.88 (CIN1), 0.82 (CIN2), and 0.85 (CIN3). The method yields statistically significant improvements over single-network DenseNet-121 baselines and alternative MoE backbones (MobileNet, EfficientNet, ShuffleNet) (p < 0.01). Ablation studies show that attention-guided gating contributes approximately 5-8% absolute accuracy gain over uniform weighting, and that five experts provide the optimal accuracy-efficiency balance. We further present attention visualizations and limited external validation to assess interpretability and generalizability. Although performance remains below that of recent transformer-ensemble models evaluated on smaller or less diverse test sets, the modular and interpretable MoE architecture offers a practical foundation for integrating segmentation or transformer-based experts to advance clinical utility. Code and trained models will be released to support reproducibility.