Load frequency stabilization of distinct hybrid conventional and renewable power systems incorporated with electrical vehicles and capacitive energy storage.

Maintaining a power balance between generation and demand is generally acknowledged as being essential to maintaining a system frequency within reasonable bounds. This is especially important for linked renewable-based hybrid power systems (HPS), where disruptions are more likely to occur. This paper suggests a prominent modified "Fractional order-proportional-integral with double derivative (FOPIDD2) controller" as an innovative HPS controller in order to navigate these obstacles. The recommended control approach has been validated in power systems including wind, reheat thermal, solar, and hydro generating, as well as capacitive energy storage and electric vehicle. The improved controller's performance is evaluated by comparing it to regular FOPID, PID, and PIDD2 controllers. Furthermore, the gains of the newly structured FOPIDD2 controller are optimized using a newly intended algorithm terms as squid game optimizer (SGO). The controller's performance is compared to benchmarks such as the grey wolf optimizer (GWO) and jellyfish search optimization. By comparing performance characteristics such as maximum frequency undershoot/overshoot, and steadying time, the SGO-FOPIDD2 controller outperforms the other techniques. The suggested SGO optimized FOPIDD2 controller was analyzed and validated for its ability to withstand the influence of power system parameter uncertainties under various loading scenarios and situations. Without any complicated design, the results show that the new controller can work steadily and regulate frequency with an appropriate controller coefficient.

Simulation Design of Novel Non-Fluorine Polymers as Electron Transport Layer for Lead-Free Perovskite Solar Cells.

Significant progress has been made in the advancement of perovskite solar cells, but their commercialization remains hindered by their lead-based toxicity. Many non-toxic perovskite-based solar cells have demonstrated potential, such as Cs2AgBi0.75Sb0.25Br6, but their power conversion efficiency is inadequate. To address this issue, some researchers are focusing on emerging acceptor-donor-acceptor'-donor-acceptor (A-DA'D-A)-type non-fullerene acceptors (NFAs) for Cs2AgBi0.75Sb0.25Br6 to find effective electron transport layers for high-performance photovoltaic responses with low voltage drops. In this comparative study, four novel A-DA'D-A-type NFAs, BT-LIC, BT-BIC, BT-L4F, and BT-BO-L4F, were used as electron transport layers (ETLs) for the proposed devices, FTO/PEDOT:PSS/Cs2AgBi0.75Sb0.25Br6/ETL/Au. Comprehensive simulations were conducted to optimize the devices. The simulations showed that all optimized devices exhibit photovoltaic responses, with the BT-BIC device having the highest power conversion efficiency (13.2%) and the BT-LIC device having the lowest (6.8%). The BT-BIC as an ETL provides fewer interfacial traps and better band alignment, enabling greater open-circuit voltage for efficient photovoltaic responses.

Lead-Free FACsSnI3 Based Perovskite Solar Cell: Designing Hole and Electron Transport Layer.

In recent years, lead-based perovskites solar cells have demonstrated excellent power-conversion efficiency. Despite their remarkable progress, the commercialization of lead-based perovskites is hampered by lead toxicity concerns. The recently discovered non-toxic FACsSnI3 perovskite has the potential to replace lead-based perovskites in solar cell applications. Since the perovskite material FACsSnI3 (FA0.85Cs0.15SnI3) is relatively new, there is a lack of information, particularly regarding the design features required for electron and hole-transport layers for efficient photovoltaic responses. The important variables, such as electron affinity, energy band gap, film thickness, and doping density of both electron and hole-transport layers, were simulated and modeled separately and iteratively in this study to achieve the most efficient photovoltaic response. Finally, the absorber layer thickness of FACsSnI3 perovskite is tuned to achieve a maximum power-conversion efficiency of slightly more than 24%. We hope that the findings of this study will serve as a strong guideline for future research and the design of lead-free perovskite solar cells for efficient photovoltaic responses.

Use, Misuse, and Complications of Contact Lens Among the General Population of the Kingdom of Saudi Arabia.

PURPOSE: This study aims to assess contact lens usage patterns, complications, knowledge levels, and the impact of psychological factors on misuse among the Saudi population. METHODS: In this study, we distributed our questionnaire through multiple social media platforms among patients who are using cosmetic or medical contact lenses regardless of the purpose of wearing them. A total of 1,708 contact lens users participated. RESULTS: Most participants were female (86.4%) and aged 21-40 years (65.7%). The purpose for usage was cosmetic (36.1%) or medical (28.7%), with some using them for both purposes (35.1%). Complications have been faced, with 26.3% experiencing issues due to lens usage, 56.8% facing visual problems, and 45.8% sometimes feeling discomfort with contact lens usage. Allergic reactions were reported by 35.2%. Higher knowledge levels were associated with participants aged 21-40 years (p = 0.009), irregular ophthalmologist visits (p = 0.032), and cosmetic use (p = 0.027). Better practice patterns were observed among urban residents (p = 0.049), higher-income earners (p = 0.002), cosmetic users (p < 0.001), and those with fewer complications (p < 0.001). Psychological factors significantly influenced misuse, with 15.4% of participants indicating its impact. Notably, a subset of these participants (16.2%) perceived prolonged wear of contact lenses as a manifestation of personal insecurity. CONCLUSIONS: Several sociodemographic factors, including place of residence, income, and difficulty, influence the use of contact lenses. It is also necessary to consider psychological issues such as low self-esteem and social acceptance while encouraging the safe use of contact lenses.

Cytological Changes and Immunocytochemistry Expression of P53 in Oral Mucosa Among Waterpipe Users in the Kingdom of Saudi Arabia.

Objective In this study, we aimed to assess cytological changes and p53 expression in oral mucosa among waterpipe users in the Kingdom of Saudi Arabia (KSA). Methodology A case-control study was conducted in KSA from January to October 2022. Two cytologic oral smear samples each were taken from 500 volunteers; 300 were waterpipe users (case) while 200 did not use a waterpipe (control). They were then stained using the Papanicolaou staining procedure and immunocytochemical method to show the expression of P53. Results The interpretation of the Papanicolaou staining outcomes showed the presence of four results with different proportions: inflammation, infection, atypia, and keratinization. Cytological inflammation was identified among 77/300 (25.6%) waterpipe smokers, which was higher than that among non-users (12/200, 6%). The reverse cytological infection and atypia were also higher in waterpipe smokers compared with controls (9% vs. 4.5% and 4.3% vs. 0.5%, respectively), and keratinization was detected only in waterpipe users (3.6%) compared with controls. Waterpipe users had higher p53 protein expression than non-users. Conclusion Using a waterpipe is an effective way to change the oral mucosa. In atypia and keratinization, there was high p53 expression. These results could indicate that p53 is involved in both the change from normal to cancerous cells and the growth of new cells, but the presence or absence of p53 staining could not be used to predict the outcome of potentially cancerous oral mucosal lesions.

Antibiotics Usage and Resistance among Patients with Severe Acute Respiratory Syndrome Coronavirus 2 in the Intensive Care Unit in Makkah, Saudi Arabia.

Antibiotic resistance is a global health and development threat, especially during the Severe Acute Respiratory Syndrome Coronavirus 2 (COVID-19) pandemic. Therefore, the current study was conducted to describe antibiotic usage and resistance among patients with COVID-19 in the intensive care unit (ICU) in Makkah, Saudi Arabia. In this cross-sectional study, only patients with positive COVID-19 status (42 patients) admitted to the ICU at the King Faisal Hospital were selected using a census sampling method. The susceptibility test of bacteria was carried out according to the standard protocol. The identified strains were tested in-vitro against several antibiotics drugs. Statistical analysis was performed using SPSS version 24. A total of 42 patients were included, with a mean age of 59.35 ± 18 years. Of them, 38.1% were males, and 61.9% were females. 35.7% have blood group O +. For age and blood groups, statistically significant associations were found between males and females, with p-values = 0.037 and 0.031, respectively. A large percentage (42.7%) of the obtained samples contained Klebsiella Pneumoniae; all bacteria were multidrug-resistance bacteria. Furthermore, 76.2% of bacteria were resistant to Ampicillin, 66.7% were resistant to Ciprofloxacin, 64.3% were resistant to Levofloxacin, 57.1% were resistant to Imipenem, and 57.1% were resistant to Moxifloxacin. On the contrary, among the 40 examined antibiotics, the effective antibiotics were Daptomycin, Linezolid, Mupirocin, Synercid, Teicoplanin, Vancomycin, and Nitrofurantoin. Our study demonstrates that antibiotic resistance is highly prevalent among ICU patients with COVID-19 at the King Faisal Hospital. Additionally, all bacteria were multidrug-resistance bacteria. Therefore, this high prevalence should be seriously discussed and urgently considered.

Electron Transport Layer Optimization for Efficient PTB7:PC70BM Bulk-Heterojunction Solar Cells.

Bulk-heterojunction (BHJ) polymer solar cells have received a great deal of attention mainly due to the possibility of higher power conversion efficiency for photovoltaic applications. Therefore, in this study, relatively novel polymer BHJ solar cells are proposed (ITO/ETL/PTB7:PC70BM/PEDOT:PSS/Au) with various electron transport layers (ETL) such as zinc oxysulfide (Zn(O,S)), zinc selenide (ZnSe), and poly[(9,9-bis(3'-((N,N-dimethyl)-N-ethylammonium)-propyl)-2,7-fluorene)-alt-2,7-(9,9-dioctylfluorene)] dibromide (PFN-Br). Here, each ETL material is selected based on the energy bandgap compatibility with ITO as well as the PTB7:PC70BM active layer and is based on other physical properties, which are generally required for efficient photovoltaic responses. Each proposed device is comprehensively optimized and then photovoltaic responses are simulated and compared using the software SCAPS-1D. It was observed that the ITO/Zn(O,S)/PTB7:PC70BM/PEDOT:PSS/Au device offered the highest power-conversion efficiency of up to 17.15% with an open-circuit voltage of 0.85 volts, a short-circuit current of 28.23 mA/cm2, and a fill factor of 70.69%.

Design of an Efficient PTB7:PC70BM-Based Polymer Solar Cell for 8% Efficiency.

Polymer semiconductors may have the potential to fully replace silicon in next-generation solar cells because of their advantages such as cheap cost, lightweight, flexibility, and the ability to be processed for very large area applications. Despite these advantages, polymer solar cells are still facing a certain lack of power-conversion efficiency (PCE), which is essentially required for commercialization. Recently, bulk heterojunction of PTB7:PC70BM as an active layer showed remarkable performance for polymer solar cells in terms of PCE. Thus, in this paper, we developed and optimized a novel design using PEDOT:PSS and PFN-Br as electron and hole transport layers (ETL and HTL) for ITO/PEDOT:PSS/PT7B:PC70BM/PFN-Br/Ag as a polymer solar cell, with the help of simulation. The optimized solar cell has a short-circuit current (Isc) of 16.434 mA.cm-2, an open-circuit voltage (Voc) of 0.731 volts, and a fill-factor of 68.055%, resulting in a maximum PCE of slightly above 8%. The findings of this work may contribute to the advancement of efficient bulk-heterojunction-based polymer solar cells.

Mathematical foundations based statistical modeling of software source code for software system evolution.

Source code is the heart of the software systems; it holds a wealth of knowledge that can be tapped for intelligent software systems and leverage the possibilities of reuse of the software. In this work, exploration revolves around making use of the pattern hidden in various software development processes and artifacts. This module is part of the smart requirements management system that is intended to be built. This system will have multiple modules to make the software requirements management phase more secure from vulnerabilities. Some of the critical challenges bothering the software development community are discussed. The background of Machine Learning approaches and their application in software development practices are explored. Some of the work done around modeling the source code and approaches used for vulnerabilities understanding in software systems are reviewed. Program representation is explored to understand some of the principles that would help in understanding the subject well. Further deeper dive into source code modeling possibilities are explored. Machine learning best practices are explored inline with the software source code modeling.

Diagnosis of Chronic Kidney Disease Using Effective Classification Algorithms and Recursive Feature Elimination Techniques.

Chronic kidney disease (CKD) is among the top 20 causes of death worldwide and affects approximately 10% of the world adult population. CKD is a disorder that disrupts normal kidney function. Due to the increasing number of people with CKD, effective prediction measures for the early diagnosis of CKD are required. The novelty of this study lies in developing the diagnosis system to detect chronic kidney diseases. This study assists experts in exploring preventive measures for CKD through early diagnosis using machine learning techniques. This study focused on evaluating a dataset collected from 400 patients containing 24 features. The mean and mode statistical analysis methods were used to replace the missing numerical and the nominal values. To choose the most important features, Recursive Feature Elimination (RFE) was applied. Four classification algorithms applied in this study were support vector machine (SVM), k-nearest neighbors (KNN), decision tree, and random forest. All the classification algorithms achieved promising performance. The random forest algorithm outperformed all other applied algorithms, reaching an accuracy, precision, recall, and F1-score of 100% for all measures. CKD is a serious life-threatening disease, with high rates of morbidity and mortality. Therefore, artificial intelligence techniques are of great importance in the early detection of CKD. These techniques are supportive of experts and doctors in early diagnosis to avoid developing kidney failure.

Design of Dopant and Lead-Free Novel Perovskite Solar Cell for 16.85% Efficiency.

Halide based perovskite offers numerous advantages such as high-efficiency, low-cost, and simple fabrication for flexible solar cells. However, long-term stability as well as environmentally green lead-free applications are the real challenges for their commercialization. Generally, the best reported perovskite solar cells are composed of toxic lead (Pb) and unstable polymer as the absorber and electron/hole-transport layer, respectively. Therefore, in this study, we proposed and simulated the photovoltaic responses of lead-free absorber such as cesium titanium (IV) bromide, Cs2TiBr6 with dopant free electron phenyl-C61-butyric acid methyl ester (PCBM), and dopant free hole transport layer N,N'-Di(1-naphthyl)-N,N'-diphenyl-(1,1'-biphenyl)-4,4'-diamine (NPB) for the Ag/BCP/PCBM/Cs2TiBr6/NPB/ITO based perovskite solar cell. After comprehensive optimization of each layer through vigorous simulations with the help of software SCAPS 1D, it is observed that the proposed solar cell can yield maximum power-conversion efficiency up to 16.85%. This efficiency is slightly better than the previously reported power-conversion efficiency of a similar type of perovskite solar cell. We believe that the outcome of this study will not only improve our knowledge, but also triggers further investigation for the dopant and lead-free perovskite solar cell.

A Novel Poly-N-Epoxy Propyl Carbazole Based Memory Device.

Generally, polymer-based memory devices store information in a manner distinct from that of silicon-based memory devices. Conventional silicon memory devices store charges as either zero or one for digital information, whereas most polymers store charges by the switching of electrical resistance. For the first time, this study reports that the novel conducting polymer Poly-N-Epoxy-Propyl Carbazole (PEPC) can offer effective memory storage behavior. In the current research, the electrical characterization of a single layer memory device (metal/polymer/metal) using PEPC, with or without doping of charge transfer complexes 7,7,8,8-tetra-cyanoquino-dimethane (TCNQ), was investigated. From the current-voltage characteristics, it was found that PEPC shows memory switching effects in both cases (with or without the TCNQ complex). However, in the presence of TCNQ, the PEPC performs faster memory switching at relatively lower voltage and, therefore, a higher ON and OFF ratio (ION/IOFF ~ 100) was observed. The outcome of this study may help to further understand the memory switching effects of conducting polymer.

The gap between ultrasonography and computed tomography in measuring the size of urinary calculi.

OBJECTIVE: Due to a lack of studies regarding the need for computed tomography (CT) in measuring the size of each urinary calculus before surgery, this study was conducted to elucidate the difference between ultrasonography (US) and CT in measuring the size of urinary stones. METHODS: A retrospective review of 100 stones from 83 patients. Each urinary stone was measured using both US and CT; both measurements were then compared. RESULTS: Of 83 patients, the mean age was 39.29 ± 23.76 years; 47 (56.62%) were male and 36 (43.37%) were female. Most of the urinary stones were <10 mm (50.0%) followed by 11-20 mm (42.0%), (P < 0.001). A cross-tabulation test revealed strong compatibility between US and CT in measuring the size of urinary stones (73.7% in stones <10 mm, 66.7% in stones 11-20 mm and 50% in stones >21 mm), (P < 0.001). Spearman's rho correlation test revealed strong compatibility between stone diameters measured by US and CT (r = 0.755), (P = 0 < 0.001). T-test for equality of means revealed no significant difference in the measured size using US and CT (mean = 11.80 ± 5.83 vs. 11.65 ± 6.59, respectively), mean difference = 0.15, and P = 0.865, 95% confidence interval: -1.584-1.884. CONCLUSION: No significant difference in measuring the size of urinary stones using US and CT. However, US may slightly overestimate small stones in some cases.

Pre-hospital delay among patients with acute myocardial infarction in Saudi Arabia. A cross-sectional study.

OBJECTIVES: To estimate the pre-hospital delay time among patients diagnosed with acute myocardial infarction and to determine factors associated with pre-hospital delay. METHODS: A cross-sectional study was conducted among 200 patients with myocardial infarction at Madinah Cardiac Center, Al Madinah Al Munawarah, Saudi Arabia between November 2019 and March 2020. Data were collected by direct physician-subject interviews. We used the validated version of the modified response to symptoms questionnaire. Chi-square test, t test, and multivariate analysis were used to examine factors associated with pre-hospital delay. RESULTS: The median pre-hospital delay time was 3.7 hours. Among all the patients, 126 patients (63%) arrived at the hospital later than 2 hours from the onset of symptoms. Factors that were significantly associated with pre-hospital delay included a previous information on acute coronary syndrome (adjusted odds ratio [adj OR]=0.35, 95% confidence interval [CI] 0.1-0.6), history of hypercholesteremia (adj OR=2.3, 95% CI 1.1-4.7), arrived by ambulance (adj OR=0.3, 95% CI 0.1-0.8), and increased pain intensity (adj OR=0.7, 95% CI 0.6-0.9). CONCLUSION: Approximately two-thirds of the patients arrived later than 2 hours from the onset of symptoms. A previous information about acute coronary syndrome, history of hypercholesteremia, arrived by ambulance, and increased pain intensity were associated with pre-hospital delay. The study recognizes the need for educational programs about acute myocardial infarction symptoms and the bene ts of availing an ambulance service.

Causality Analysis of fMRI Data Based on the Directed Information Theory Framework.

This paper aims to conduct fMRI-based causality analysis in brain connectivity by exploiting the directed information (DI) theory framework. Unlike the well-known Granger causality (GC) analysis, which relies on the linear prediction technique, the DI theory framework does not have any modeling constraints on the sequences to be evaluated and ensures estimation convergence. Moreover, it can be used to generate the GC graphs. In this paper, first, we introduce the core concepts in the DI framework. Second, we present how to conduct causality analysis using DI measures between two time series. We provide the detailed procedure on how to calculate the DI for two finite-time series. The two major steps involved here are optimal bin size selection for data digitization and probability estimation. Finally, we demonstrate the applicability of DI-based causality analysis using both the simulated data and experimental fMRI data, and compare the results with that of the GC analysis. Our analysis indicates that GC analysis is effective in detecting linear or nearly linear causal relationship, but may have difficulty in capturing nonlinear causal relationships. On the other hand, DI-based causality analysis is more effective in capturing both linear and nonlinear causal relationships. Moreover, it is observed that brain connectivity among different regions generally involves dynamic two-way information transmissions between them. Our results show that when bidirectional information flow is present, DI is more effective than GC to quantify the overall causal relationship.