Helwan University

The evaluation of photovoltaic (PV) model parameters has gained importance considering emerging new energy power systems. Because weather patterns are unpredictable, variations in PV output power are nonlinear and periodic. It is impractical to rely on a time series because traditional power forecast techniques are based on linearity. As a result, meta-heuristic algorithms have drawn significant attention for their exceptional performance in extracting characteristics from solar cell models. This study analyzes a new modification in the double-diode solar cell model (NMDDSCM) to evaluate its performance compared with the traditional double-diode solar cell model (TDDSCM). Modified Fire Hawk Optimizer (mFHO) is applied to identify the photovoltaic parameters (PV) of the TDDSCM and NMDDSCM models. The Modified Fire Hawks Optimizer (mFHO) algorithm, which incorporates two enhancement strategies to address the shortcomings of FHO. The experimental performance is evaluated by investigating the scores achieved by the method on the CEC-2022 standard test suite. The parameter extraction of the TDDSCM and NMDDSCM is an optimization problem treated with an objective function to minimize the root mean square error (RMSE) between the calculated and the measured data. Real data of the R.T.C France solar cell is used to verify the performance of NMDDSCM. The effectiveness of the mFHO algorithm is compared with other algorithms such as Teaching Learning-Based Optimization (TLBO), Grey Wolf Optimizer (GWO), Fire Hawk Optimizer (FHO), Moth Flame Optimization (MFO), Heap Based optimization (HBO), and Chimp Optimization Algorithm (ChOA). The best objective function for the TDDSCM equal to 0.000983634 and its value for NMDDSCM equal to 0.000982485 that is achieved by the mFHO algorithm. The obtained results have proved the NMDDSCM’s superiority over TDDSCM for all competitor techniques.

Fused deposition modeling (FDM) is a layered manufacturing (LM) process in which progressive 2D layers of material are kept making a 3D part. To optimize the building operation, the investigation is necessary to study the effect of process parameters. This study examines the impact of three filling patterns, “triangles,” “cross,” and “cross 3D,” with three filling densities (25%, 50%, and 75%) in three orientations (“flat,” “on long edge,” and “on short edge”) on ultimate tensile strength (UTS), hardness and the printing time of polylactic acid (PLA) material. This work built tensile specimens according to ASTM D638 on an open-source 3D printer. The UTS was collected using a WDW-2000 computer control electronic universal testing machine. The hardiness value was also measured using Shore A hardness durometers DIN 53505 and ASTM D2240. In addition, the building time was conducted by implementing the “Cura 4.6” slicer software. The results show that the filling pattern, orientation, and density at which the part is built significantly affect the strength, hardness, and building time. For light structure parts with 25% density, it is recommended to build parts with “triangles” “on long edge” to obtain the highest strength (31.02 MPa), which improved by 74.3%, with 281 HV at the minimum time (1 h:10 min), which was reduced by 46.1%. For dense structure parts, “triangles” and “on long edge” are recommended to give the highest strength (42.12 MPa), which can be improved by 69.8% (282 HV) at the minimum time (1 h:35 min), which was reduced by 36.2%. For medium construction, 50% of the parts can be built by the following parameters: “cross” and “on long edge” to obtain the highest strength (38.48 MPa) with 283 HV at the minimum possible time (1 h:55 min). The study could help with the growth of producing mechanically functional parts, such as prosthetics, using LM. In addition, the part can be built with high strength, hardness, and minimum building time, which is useful information for the best utilization of the 3DP machine. Also, the chosen parameters optimize the building process with little human intervention.

In this study, zinc oxide (ZnO) nanoparticles were prepared and modified using a wet chemical method with different concentrations of Ag and Cu nanoparticles. The objective was to improve the mechanical, optical, and antibacterial properties of the coated paper by using the prepared pigments. The long-term antimicrobial effects of the coated paper were evaluated over 25 years. The successful synthesis of a hexagonal structure of ZnO nanoparticles decorated with spherical Ag and Cu nanoparticles ranging from 20 to 50 nm was confirmed using X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), and transmission electron microscopy (TEM). By increasing the concentrations of Ag and Cu from 0.01% to 1.0%, the mechanical properties of the coated paper were enhanced. The tensile strength reached a maximum of 6.77 kN/m and 7.03 kN/m, elongation increased to 1.69% and 1.70%, tensile energy absorption improved to approximately 77 and 80 J/m², and burst strength rose to 218 and 219 kPa, respectively. The use of Ag-modified ZnO maintains the optical properties, while Cu-modified ZnO reduces brightness and whiteness without affecting opacity. The antimicrobial inhibition activity was improved with higher silver (Ag) and copper (Cu) content. The formulations containing 1% Ag/ZnO and 1%Cu/ZnO showed long-lasting antibacterial effects against gram-positive Staphylococcus aureus bacteria. Even after 25 years of aging, they maintained inhibition rates of 92.2% and 62.2%, respectively. The molecular docking and GeneMANIA analysis revealed the potential of ZnO, Ag-modified ZnO, and Cu-modified ZnO nanoparticles to disrupt the S. aureus cell wall biosynthesis pathway by targeting the MurA enzyme and associated cell wall synthesis genes.

The prediction of highly heterogeneous reservoir parameters from seismic amplitude data is a major challenge. Seismic attribute analysis can enhance the tracking of subtle stratigraphic features. It is challenging to investigate these subtle features, including channel systems, with conventional-amplitude seismic data. Over the past few years, the use of machine learning (ML) to analyze multiple seismic attributes has enhanced the facies analysis by mapping patterns in seismic data. The purpose of this research was to assess the efficiency of an unsupervised self-organizing map (SOM) approach supported by multi-attribute analysis that could improve gas channel detection and seismic facies classification in Serpent Field, offshore Nile Delta, Egypt. As well as evaluates the importance of several available seismic attributes in reservoir characterization rather than analyzing individual attribute volumes. In this study, the single attribute (spectral decomposition attribute) highlighted the gas channel spatial distribution using three distinct frequency magnitude values. Subsequently, we employ principal component analysis (PCA) as an attribute selection method, discovering that combining seismic attributes such as sweetness, envelope, spectral magnitude, and spectral voice as input for SOM reflects an effective method to determine facies. The clustering results distinguish between shale, shaly sand, wet sand, and gas-saturated sand and identify gas–water contact on a 2D topological map (SOM), where each pattern indicates certain facies. This is achieved by associating the SOM outputs with lithofacies determined from petrophysical logs. Reducing exploration and development risk and empowering the geoscientist to generate a more precise interpretation are the ultimate objectives of this multi-attribute analysis.

The continuous search for simple, noninvasive methods for assessing liver fibrosis remains very important to help risk-stratify and follow-up patients with chronic hepatitis C virus (HCV). This study aimed to evaluate the diagnostic performance and accuracy of six serological noninvasive scores for the assessment of liver fibrosis in comparison to liver histopathology. This retrospective cohort study included data from 19501 patients with chronic HCV infection who had liver biopsies as an HCV treatment prerequisite within the Egyptian national HCV treatment program. Six noninvasive scores (FIB-4, APRI, King’s score, Fibro-Q, fibrosis index, Fibro-α score) were evaluated and compared to liver histopathology data in assessing different stages of liver fibrosis. The diagnostic performance for each score was assessed using the area under the receiver-operating characteristic curve (AUROC). All six noninvasive scores were statistically significant for predicting different stages of liver fibrosis. Four scores (FIB-4, King’s score, APRI, and Fibro Q) had a better diagnostic performance for predicting different fibrosis stages. FIB-4, followed by the King’s score, performs better in identifying patients with advanced fibrosis at cutoffs of 2.01 and 16.7, respectively, with AUROC of 0.71 for both, and in predicting cirrhosis at cutoffs of 2.21 and 17.4, respectively with AUROC 0.82 for both. Using noninvasive scores for fibrosis assessment is very important, especially in limited resource settings, to rapidly stratify patients who need more specialized care.

The rapid growth of electric vehicles (EVs) demands a robust and efficient charging infrastructure. To address this, we propose a particle swarm optimization algorithm designed for optimal placement and sizing of EV charging stations. This study hypothesizes that comprehensive consideration of uncertainties in vehicle types, user behaviors, road dynamics, and environmental impacts will enhance infrastructure effectiveness. Our method integrates data from road networks, driver patterns, station owners, and EV manufacturers to meet diverse charging requirements. Results indicate that 14 fast charging stations are needed along the studied freeway, with a total installation cost of $289,820 and annual operational costs of$4,223,050, leading to annual CO2 emissions of 1,843,572.57 kg. This strategic approach balances technical, environmental, and economic criteria, providing an essential tool for policymakers and urban planners in establishing sustainable EV charging networks.

Cyclosporin A (CsA) exhibits a narrow therapeutic index and large inter-individual variation in pharmacokinetics. Two intermittent and 24-h continuous infusions (CI) are both commonly used regimens in hematopoietic stem cell transplantation (HSCT), with no universal consensus. The objective of this study was to assess whether CsA as a 2-h, twice-daily intravenous infusion (2 h/12 h) is non-inferior to 22 h CI every 24 h (22 h-CI/24 h) in terms of acute graft-versus-host disease (aGVHD) incidence and adverse events in allogeneic HSCT adult patients. An open-label randomized trial recruited 31 allogeneic HSCT patients to receive the 2 h/12 h or 22 h-CI/24 h regimen. The primary outcomes were the incidence of aGVHD and CsA-related adverse events. The secondary outcomes included the correlation between the time concentration and area under the concentration–time curve (AUC) of 2 h/12 h versus 22 h-CI/24 h regimens. Six (19.4%) patients developed aGVHD. There was no statistically significant difference between the two groups concerning the incidence of aGVHD (13.3% in 2 h/12 h vs. 25% in 22 h-CI/24 h; p = 0.359). The distribution of different aGVHD types (p = 0.20) and mortality (p = 0.9) were not significantly different between the two groups. The two groups did not differ at any time with respect to AUCs, nephrotoxicity, hepatotoxicity, or electrolyte disturbance. The study suggested that the 2 h/12 h regimen is non-inferior to the conventional regimen (22 h CI/24 h) in terms of aGVHD incidence and adverse events. Further research is necessary to validate these findings and to guide practice, considering the small sample size of this study. ClinicalTrials.gov identifier NCT04575779 with initial release on 19 September 2020-Retrospectively registered, https://clinicaltrials.gov/study/NCT04575779.

Glioblastoma (GBM) is one of the most aggressive types of brain cancer, characterized by its poor prognosis and low survival rate despite current treatment modalities. Because GBM is lethal, clarifying the pathogenesis’s underlying mechanisms is important, which are still poorly understood. Recent discoveries in the fields of molecular genetics and cancer biology have demonstrated the critical role that non-coding RNAs (ncRNAs), especially long non-coding RNAs (lncRNAs), play in the molecular pathophysiology of GBM growth. LncRNAs are transcripts longer than 200 nucleotides that do not encode proteins. They are significant epigenetic modulators that control gene e expression at several levels. Their dysregulation and interactions with important signaling pathways play a major role in the malignancy and development of GBM. The increasing role of lncRNAs in GBM pathogenesis is thoroughly examined in this review, with particular attention given to their regulation mechanisms in key signaling pathways such as PI3K/AKT, Wnt/β-catenin, and p53. It also looks into lncRNAs’ potential as new biomarkers and treatment targets for GBM. In addition, the study discusses the difficulties in delivering lncRNA-based medicines across the blood-brain barrier and identifies areas that need more research to advance lncRNA-oriented treatments for this deadly cancer. Graphical abstract

Background Microbial prodigiosin pigment has been proposed as a promising biomolecule having an antibacterial, immunosuppressive, antimalarial, antineoplastic, and anticancer activities. The good outcome originates from getting natural pigment, which has many medical applications. Results In this investigation, prodigiosin (PG) was extracted, characterized by UV-visible spectroscopy, thin-layer chromatography, mass spectroscopy, Fourier-transform infrared spectroscopy, and tested in various medical applications as an antibacterial, antioxidant, antibiofilm, anticancer, and wound healing agent at different concentrations. Antibacterial activity of PG pigment was shown against both Gram-positive and Gram-negative bacterial strains. Enterococcus faecalis was the most severely impacted, with minimum inhibitory value of 3.9 µg/mL. The formed biofilm by Pseudomonas aeruginosa was suppressed by 58–2.50% at prodigiosin doses ranging from 1000 to 31.25 µg/mL, respectively. The half-maximal inhibitory concentration (IC50) of 2,2’-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid (ABTS) free radical was 74.18 ± 23.77 µg/mL. At 100 µg/mL concentration, OK482790 prodigiosin had no harmful effect on normal skin cells and exhibited mild wound healing properties. Additionally, molecular docking simulations confirmed the prodigiosin’s interactions with target proteins, including epidermal growth factor receptor tyrosine kinase (EGFR-TK, PDB ID: 1M17), peptide deformylase from E. faecalis (PDB ID: 2OS1), acidic fibroblast growth factor (FGF-1, PDB ID: 3K1X), PA14_16140 protein from P. aeruginosa (PDB ID: 8Q8O), and human peroxiredoxin 5 (PDB ID: 1HD2) for explaining the anticancer, antibacterial, wound healing, antibiofilm, and antioxidant activities, respectively. Prodigiosin had favorable binding affinities and putative modes of action across various therapeutic domains. Conclusion This study pioneers the use of prodigiosin as a natural alternative to synthetic medicine since it fights germs, heals wounds, is antioxidant, and reduces biofilm formation. Clinical trial number Not applicable.

The current study represents a unique fabrication strategy for preparation of fluorescent hydrogels via incorporation of fluorescent quantum dots (QDs) as fluorophore entities into chitosan as a gelling matrix. QDs identified as carbon quantum dots (CQDs) & nitrogen containing carbon quantum dots (NCQDs) were preliminary synthesized from cellulose nanocrystals (CNCs) and cationic cellulose nanocrystals (CCNCs), respectively. Cationic CNCs was prepared via chemical grafting with poly-di-allyl dimethyl ammonium chloride (CNCs-g-poly-DADMAC) through free chain polymerization reaction. Additionally, both of the prepared CQDs & NCQDs were impregnated in 3D interpenetrating network of chitosan for preparation of microbicide/florescent hydrogels (CQDs@Chs hydrogel & NCQDs@Chs hydrogel). The represented data revealed that, exploitation of cationic CNCs resulted in preparation of NCQDs with more controllable size and superior photoluminescence. Moreover, the increment in concentration of CNCs reflected in nucleation of enlarged QDs, at variance of CCNCs, whereas, increment of concentration resulted in significantly smaller-sized QDs. Size distribution of CQDs ingrained from 2% CNCs was estimated to be 8.2 nm, while, NCQDs ingrained from 2% CCNCs exhibited with size distribution of 3.8 nm. The prepared florescent CQDs@Chs hydrogel & NCQDs@Chs hydrogel showed excellent antimicrobial performance and the diameter of inhibition zone was estimated to be 31 mm, 26 mm & 22 mm against E. Coli, S. Aureus & C. Albicans with CQDs@Chs, respectively. Whereas, treatment of the as-mentioned microbial strains with NCQDs@Chs resulted in detection of inhibition zone diameter to be significantly higher as 34 mm, 28 mm & 25 mm for E. Coli, S. Aureus & C. Albicans, respectively. In a conclusion, cationic CNCs showed seniority in nucleation of QDs with significantly higher photoluminescence and microbicide activities.

This study used life cycle assessment to assess carbon emissions associated with the production of three novel bio-based food punnets and to compare them with an equivalent made from polypropylene (PP). Two of the punnet formats included empty fruit bunch fibre (EFB), an abundant source waste biomass originating from the palm oil industry. Two production technologies were assessed, with one of the punnets being pulp-moulded (100% EFB fibre) and the others being thermoformed blends. Primary data for pulp-moulding was collected at factory-scale in Malaysia, while a novel fibre pretreatment step, necessary as a precursor to pulp-moulding this form of fibre, was only available at small-scale. The results showed that both the thermoformed punnets have lower GWPs than the PP equivalent, the best being that containing 18% EFB fibre, which had a 21% lower carbon footprint by weight, at the factory gate. Results for the pulp-moulded format were less clear due to the small-scale of operation during pretreatment. Results for the pre-treatment step are therefore high as presented, however analysis suggests that where efficiencies-of-scale can achieve a 57% reduction in emissions associated with this step, then pulp-moulded punnets will have lower GWPs than the thermoformed samples. The key future question from this preliminary assessment is therefore the extent to which the EFB fibre pretreatment step can be optimised in the pulp-moulded production scenario. Further development and scaling-up of the novel pretreatment process would now be beneficial, however all three punnet formats have potential to reduce emissions relative to those of fossil-based plastic equivalents.

The rapid increase in renewable energy integration and electric vehicle (EV) adoption creates significant challenges for the stability and efficiency of power distribution networks. This study addresses the need for optimized placement and sizing of Electric Vehicle Charging Stations (EVCSs), photovoltaic (PV) systems, and Distribution Static Compensators (DSTATCOMs) to enhance grid performance. The motivation for this work arises from the fluctuating nature of renewable energy generation and the unpredictable demands of EV charging, which strain existing infrastructure. To address these challenges, we propose a novel optimization framework that introduces the Renewable Distributed Generation Hosting Factor (RDG-HF) and Electric Vehicle Hosting Factor (EV-HF) as key metrics. These metrics, combined with the Hippopotamus Optimization Algorithm (HO), enable strategic planning within the IEEE 69-bus system. Simulation results demonstrate that the integrated placement of EVCSs, PVs, and DSTATCOMs reduces power losses by up to 31.5% and reactive power losses by up to 29.2%. An economic analysis further reveals payback periods ranging from 2.7 to 10.4 years and potential profits of up to $1,052,365 over 25 years. These findings highlight the importance of optimized integration in improving both technical performance and long-term economic benefits for distribution networks.

Background Prominent ears are the most common congenital anomaly of the head and neck. A complete understanding of the definition of prominent ears is necessary. The present retrospective study described guiding sutures to hold the antihelix in a temporary corrected position before placing the permanent Mustardé sutures. Methods This study was performed between January 2021 and February 2023. All patients with prominent ear deformities subjected to guiding sutures and Mustardé-based otoplasty were included. The surgical-related outcomes and surgeons’ satisfaction were evaluated. The patients’ satisfaction and health-related quality of life were reported. Results The current study included 60 patients with prominent ear deformities. There were 34 (56.66%) males and 26 (43.33%) females with a mean age of 12.2±7.8 years. The mean total operative time was 49±22 minutes. Five (8.33%) patients had suture extrusion, and no case of asymmetry, recurrence, or skin necrosis was documented. There were 55 (91.66%) patients satisfied with the final appearance of their ears, and five (8.33%) patients were not satisfied. The mean general health subscale was 57.1±6.9, and the mean physical health subscale was 8.7±1.5. Conclusions The guiding sutures allowed easy accessibility for reshaping the antihelix in patients with prominent ears. These sutures allowed a relatively shorter operative time, and stable reshaping of the antihelix allowed for a shorter recovery time. This was associated with a low complication rate with no asymmetry, recurrence, or revision surgery. Patients operated on under local anesthesia achieved shorter operative time and better pain control. Level of Evidence III This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Background Cervical cancer, though one of the most common cancers affecting women globally, holds immense potential for prevention through screening. Therefore, we conducted this meta-analysis to assess the rate of cervical cancer screening in Arab countries and identify barriers among those who did not participate. Methods A comprehensive search was conducted from January 1st to June 1st,2024, including all observational studies that reported cervical cancer screening uptake in any Arab country. A meta-analysis was performed using a random-effects model to estimate the pooled prevalence, and sensitivity analyses were conducted to test the robustness of the findings. The study followed PRISMA guidelines. Results This meta-analysis, covering 55 studies and 204,940 Arab women, found an overall cervical cancer screening uptake rate of 18.2% (95% CI: 13.9–23.6), with sensitivity analysis confirming the reliability of this estimate. Country disparities were evident, with Bahrain having the highest uptake at 44.1%, while Somalia had the lowest at 8.9%. Among women who underwent screening, the majority were ever-married (94.7%) and held positive attitudes towards screening (91.0%). Barriers to screening were common among women who did not participate, with the most frequent reasons being a lack of information (25.1%), the misconception of feeling healthy (24.5%), fear of the procedure (19.3%), and feelings of embarrassment (13.2%). Additionally, women who were screened had lower perceived barrier scores (SMD = -0.466) and higher perceived benefits scores (SMD = 0.379) than those who were not (p < 0.05). Conclusion This meta-analysis reveals a low overall cervical cancer screening uptake (18.2%) among Arab women. Key barriers such as lack of information, fear, the misconception of feeling healthy, and embarrassment hinder uptake. This alarmingly low rate underscores the urgent need for targeted interventions to address these barriers and promote awareness of early detection’s life-saving potential.