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Abstract In recent years, electricity networks across the globe have undergone rapid development, especially with the incorporation of various renewable energy sources (RES). The goal is to increase the penetration level of RES in the power grid to maximize energy efficiency. However, the optimal power flow (OPF) problem for conventional power generation with RES integration is highly complex, non‐linear, and non‐convex, and this complexity is further compounded when stochastic RES is integrated into the network. To address this problem, this article proposes an elite evolutionary strategy (EES) based on evolutionary approaches to improve the Wild Horse Optimizer (WHO), creating an enhanced hybrid technique called EESWHO. The proposed technique's effectiveness and robustness were tested on 23 numerical optimization test functions, including seven unimodal, six multimodal, and ten composite test functions. Furthermore, the EESWHO was applied to the modified IEEE‐30 bus test system to demonstrate its supremacy and efficacy in achieving the optimal solution. The simulation results show that the proposed EESWHO algorithm is highly effective and robust in achieving the optimal solution to the OPF problem with stochastic RES. This approach provides a practical solution to the challenges posed by the integration of RES into power networks, allowing for maximum energy efficiency while minimizing system complexity.

Abstract This paper presents a groundbreaking approach to enhance the performance of a vehicle cruise control system—a crucial aspect of road safety. The work offers two key contributions. Firstly, a state-of-the-art metaheuristic algorithm is proposed by augmenting the performance of the weighted mean of vectors (INFO) algorithm using pattern search and elite opposition-based learning mechanisms. The resulting boosted INFO (b-INFO) algorithm surpasses the original INFO, marine predators, and gravitational search algorithms in terms of performance on benchmark functions, including unimodal, multimodal, and fixed-dimensional multimodal functions. Secondly, a novel proportional, fractional order integral, derivative plus double derivative with filter ( $$P{I}^{\lambda }DN{D}^{2}{N}^{2}$$ P I λ D N D 2 N 2 ) controller is proposed as a more efficient control structure for vehicle cruise control systems. An objective function is utilized to determine the optimal values for the controller parameters, and the proposed method's performance is compared against a range of recent approaches. Results demonstrate that the b-INFO algorithm-based $$P{I}^{\lambda }DN{D}^{2}{N}^{2}$$ P I λ D N D 2 N 2 controller is the most efficient and superior method for controlling a vehicle cruise control system. Moreover, this work represents the first report of a $$P{I}^{\lambda }DN{D}^{2}{N}^{2}$$ P I λ D N D 2 N 2 controller’s implementation for vehicle cruise control systems, underscoring the novelty and significance of this research. The proposed method's exceptional ability is further confirmed by comparisons with the genetic algorithm, ant lion optimizer, atom search optimizer, arithmetic optimization algorithm, slime mold algorithm, Lévy flight distribution algorithm, manta ray foraging optimization, and hunger games search-based proportional–integral–derivative (PID), along with Harris hawks optimization-based PID and fractional order PID controllers. This work marks a remarkable milestone toward safer and more efficient vehicle cruise control systems.

Abstract Background The expression of vitamin D receptor in the normal endometrium and ovaries supports the role of vitamin D in local immunity and inflammatory cytokines regulation. Objective This study aimed to detect the relation between serum 25(OH)D and primary dysmenorrhea in Asian Adolescents. Methods Two hundred and five (205) adolescents complaining of primary dysmenorrhea (study group) were compared in this prospective study to matched controls (210 controls) after informed consent following the Helsinki Declaration. After thorough evaluation, including a thorough history and pelvic ultrasound examination, blood samples were collected from the studied adolescents to measure serum 25(OH)D and for vitamin D receptor TaqI (rs731236) genotyping. The studied adolescents’ data were analyzed using the Pearson’s correlation to detect the relation between serum 25(OH)D and primary dysmenorrhea (primary outcome). The secondary outcome measures the odds of primary dysmenorrhea in Asian adolescents with vitamin D receptor TaqI (rs731236) polymorphism. Results The serum 25(OH)D was significantly lower in the studied-dysmenorrhea group compared to controls (16.17 ± 7.36 versus 17.65 ± 6.36 ng/ml, respectively), (P = 0.01). The correlation analysis showed a significant negative correlation between the serum 25(OH)D and visual analogue scale of dysmenorrhea (r = -0.9003, P

Archimedes Optimization Algorithm (AOA) is a new physics-based optimizer that simulates Archimedes principles. AOA has been used in a variety of real-world applications because of potential properties such as a limited number of control parameters, adaptability, and changing the set of solutions to prevent being trapped in local optima. Despite the wide acceptance of AOA, it has some drawbacks, such as the assumption that individuals modify their locations depending on altered densities, volumes, and accelerations. This causes various shortcomings such as stagnation into local optimal regions, low diversity of the population, weakness of exploitation phase, and slow convergence curve. Thus, the exploitation of a specific local region in the conventional AOA may be examined to achieve a balance between exploitation and exploration capabilities in the AOA. The bird Swarm Algorithm (BSA) has an efficient exploitation strategy and a strong ability of search process. In this study, a hybrid optimizer called AOA-BSA is proposed to overcome the limitations of AOA by replacing its exploitation phase with a BSA exploitation one. Moreover, a transition operator is used to have a high balance between exploration and exploitation. To test and examine the AOA-BSA performance, in the first experimental series, 29 unconstrained functions from CEC2017 have been used whereas the series of the second experiments use seven constrained engineering problems to test the AOA-BSA’s ability in handling unconstrained issues. The performance of the suggested algorithm is compared with 10 optimizers. These are the original algorithms and 8 other algorithms. The first experiment’s results show the effectiveness of the AOA-BSA in optimizing the functions of the CEC2017 test suite. AOABSA outperforms the other metaheuristic algorithms compared with it across 16 functions. The results of AOABSA are statically validated using Wilcoxon Rank sum. The AOABSA shows superior convergence capability. This is due to the added power to the AOA by the integration with BSA to balance exploration and exploitation. This is not only seen in the faster convergence achieved by the AOABSA, but also in the optimal solutions found by the search process. For further validation of the AOABSA, an extensive statistical analysis is performed during the search process by recording the ratios of the exploration and exploitation. For engineering problems, AOABSA achieves competitive results compared with other algorithms. the convergence curve of the AOABSA reaches the lowest values of the problem. It also has the minimum standard deviation which indicates the robustness of the algorithm in solving these problems. Also, it obtained competitive results compared with other counterparts algorithms regarding the values of the problem variables and convergence behavior that reaches the best minimum values.

Abstract The Economic and Emission Dispatch (EED) method is widely used to optimize generator output in a power system. The goal is to reduce fuel costs and emissions, including carbon dioxide, sulphur dioxide, and nitrogen oxides, while maintaining power balance and adhering to limit constraints. EED aims to minimize emissions and operating costs while meeting power demands. To solve the multi‐objective EED problem, the supply‐demand optimization (SDO) algorithm is proposed, which employs a price penalty factor approach to convert it into a single‐objective function. The SDO algorithm uses a swarm‐based optimization strategy inspired by supply‐demand mechanisms in economics. The algorithm's performance is evaluated on seven benchmark functions before being used to simulate the EED problem on power systems with varying numbers of units and load demands. Established algorithms like the Grey Wolf Optimizer (GWO), Moth‐Flame Optimization (MFO), Transient Search Optimization (TSO), and Whale Optimization Algorithm (WOA) are compared to the SDO algorithm. The simulations are conducted on power systems with different numbers of units and load demands to optimize power generation output. The numerical analyses demonstrate that the SDO technique is more efficient and produces higher quality solutions than other recent optimization methods.

Abstract This paper proposes an improved version of the Hunter‐prey optimization (HPO) method to enhance its search capabilities for solving the Optimal Power Flow (OPF) problem, which includes FACTS devices and wind power energy integration. The new algorithm is inspired by the behavior of predator and prey animals, such as lions, wolves, leopards, stags, and gazelles. The primary contribution of this study is to address the tendency of the original HPO approach to get trapped in local optima, by proposing an enhanced Hunter‐prey optimization (EHPO) approach that improves both the exploration and exploitation phases. This is achieved through a random mutation for exploration and an adaptive process for exploitation, which balances the transition between the two phases. The performance of the EHPO algorithm is compared with other optimization algorithms, and subsequently, it is used to solve the OPF problem incorporating FACTS devices and wind power. The results demonstrate the effectiveness and superiority of the proposed algorithm. In conclusion, this study successfully enhances the EHPO algorithm to provide better accuracy and faster convergence in finding optimal solutions for complex real‐world problems.

Abstract Background In medical practice, it is common to see patients who present with physical symptoms for which no disease pathology can be found. The presence of neurological symptoms that are shown to be incompatible with neurological pathophysiology is classically known as “conversion disorder” or “Functional Neurological Symptom Disorder” (FND). While FND is common in Egypt as in the rest of the world, few scientific studies systematically evaluate the degree of knowledge, attitude, and care provided by health care professionals to FND patients. We aimed to assess Egyptian physicians’ perspectives on FND. Results A cross-sectional study has been conducted on 152 physicians dealing with FND practicing in Egypt from specialties of psychiatry, neurology, and other specialties. We found that for 45% of the participants, disordered functioning of the nervous system plus psychogenesis was the accepted etiology behind FND. Most participants were significantly not satisfied with their education about FND (p-value 0.01). Psychiatrists and neurologists significantly preferred to use the term “conversion disorder” while other specialties mainly used “psychic” and “Somatization/Somatoform Disorder” (p-value 0.001). Forty-four percent of the participants think they have a good knowledge of functional neurological disorders (FND), while the majority (86.8%) were worried about missing an organic disorder. Psychiatrists were the most confident in diagnosing FND and the most comfortable discussing it with patients (p-values 0.055 and 0.007, respectively). Conclusion Here we highlight the common theme of worry about FND patients prevailing among healthcare professionals who are mostly perplexed about the mechanisms behind FND, and how to communicate these symptoms to other professionals and patients themselves. Future directions need to be devoted to minimizing the gap between the research finding and the currently applied care. Better education and teaching about FND may improve patient care.

Abstract The Gulf of Aqaba is known for its high seismic activity in Egypt and the Middle East. An inversion technique was applied to 113 earthquakes of magnitude 2.5 to 7.2 to distinct subsets of data based on tectonic regionalization to define the stress regime in the Gulf of Aqaba involving the Eilat basin, Aragonese basin, and Dakar basin. The stress inversion revealed two active stress patterns; an active strike-slip in the Eilat basin and a dominant extensional regime in the Dakar basin, whereas both strike-slip and extensional regimes coexist in the Aragonese basin. The stress pattern in the Eilat basin is consistent with the movement along the Dead Sea Transform Fault. In contrast, the extensional regime in the Dakar basin aligns with the extensional stress field throughout the northern Red Sea. The coexistence of two dominant types of stress regimes in the Aragonese basin is likely a result of the superposition of the two main neighbouring stress regimes: the strike-slip regime along the Gulf of Aqaba Dead Sea Transform Fault and the extensional stress state across the northern Red Sea. The orientations of the minimum principal stress in the three basins are almost similar, indicating ENE trending, nearly horizontal extension.

Abstract The environmentally friendly design of analytical methods is gaining interest in pharmaceutical analysis to reduce hazardous environmental impacts and improve safety and health conditions for analysts. The adaptation and integration of chemometrics in the development of environmentally friendly analytical methods is strongly recommended in the hope of promising benefits. Favipiravir and remdesivir have been included in the COVID-19 treatment guidelines panel of several countries. The main objective of this work is to develop green, tuned spectrophotometric methods based on chemometric based models for the determination of favipiravir and remdesivir in spiked human plasma. The UV absorption spectra of favipiravir and remdesivir has shown overlap to some extent, making simultaneous determination difficult. Three advanced chemometric models, classical least squares, principal component regression, and partial least squares, have been developed to provide resolution and spectrophotometric determination of the drugs under study. A five-level, two-factor experimental design has been used to create the described models. The spectrally recorded data of favipiravir and remdesivir has been reviewed. The noise region has been neglected as it has a negative impact on the significant data. On the other hand, the other spectral data provided relevant information about the investigated drugs. A comprehensive evaluation and interpretation of the results of the described models and a statistical comparison with accepted values have been considered. The proposed models have been successfully applied to the spectrophotometric determination of favipiravir and remdesivir in pharmaceutical form spiked human plasma. In addition, the environmental friendliness of the described models was evaluated using the analytical eco-scale, the green analytical procedure index and the AGREE evaluation method. The results showed the compliance of the described models with the environmental characteristics.

Abstract In this paper, a compact two-port MIMO antenna array system is described. The antenna array spans the range from 27 to 40 GHz, whereas the impedance of the antenna element is matched at 50 Ω. The gain of the antenna element is between 5.5 and 8.5 dBi, and its radiation efficiency is between 65 and 90%. With high impedance matching for 5G MMW (Millimeter Wave), particularly at 28 GHz and 38 GHz, the 2-port antenna array operates in the frequency range of 27–40 GHz. The suggested MIMO array operates effectively with a gain of approximately 10 dBi and a radiation efficiency of approximately 95%. The antenna array's overall dimensions are a length of 55.27 mm, a width of 27.635 mm, and a depth of 1.6 mm with partial ground. A FR-4 substrate is used in the antenna's fabrication, greatly reducing the cost. In the antenna array, a decoupling surface is used between the antennas, with orthogonality being maintained between the ports to reduce mutual coupling. The results of the modelling show a reduction in the measured mutual coupling between array ports of less than − 35 dB. An envelope correlation coefficient (ECC) of less than 1 × 10–4 is preferable. Additionally, the channel loss capacity is less than 0.3 bits/s/Hz, the mean effective gain is approximately − 6 dB, and the total active reflection coefficient is upgraded to be less than − 30 dB. Moreover, a diversity gain of approximately 10 dB is achieved. The proposed construction was created using CST Microwave Studio 2019. When the antennas are constructed and tested, the experimental outcomes surpass those of the simulation. Each antenna element is 27.635 mm long, 27.635 mm wide, and 1.6 mm thick. Slots in the radiating circular patch antenna element could be used to improve the radiation characteristics across the intended bands. The parametric study specifies that the distance between the antenna elements should be 0.5 λ, where λ is the operational wavelength.

A digitizer is considered one of the fundamental components of an earthquake monitoring system. In this paper, we design and implement a high accuracy seismic digitizer. The implemented digitizer consists of several blocks, i.e., the analog-to-digital converter (ADC), GPS receiver, and microprocessor. Three finite impulse response (FIR) filters are used to decimate the sampling rate of the input seismic data according to user needs. A graphical user interface (GUI) has been designed for enabling the user to monitor the seismic waveform in real time, and process and adjust the parameters of the acquisition unit. The system casing is designed to resist harsh conditions of the environment. The prototype can represent the three component sensors data in the standard MiniSEED format. The digitizer stream seismic data from the remote station to the main center is based on TCP/IP connection. This protocol ensures data transmission without any losses as long as the data still exist in the ring buffer. The prototype was calibrated by real field testing. The prototype digitizer is integrated with the Egyptian National Seismic Network (ENSN), where a commercial instrument is already installed. Case studies shows that, for the same event, the prototype station improves the solution of the ENSN by giving accurate timing and seismic event parameters. Field test results shows that the event arrival time and the amplitude are approximately the same between the prototype digitizer and the calibrated digitizer. Furthermore, the frequency contents are similar between the two digitizers. Therefore, the prototype digitizer captures the main seismic parameters accurately, irrespective of noise existence.

The recently introduced coati optimization algorithm suffers from drawbacks such as slow search velocity and weak optimization precision. An enhanced coati optimization algorithm called CMRLCCOA is proposed. Firstly, the Sine chaotic mapping function is used to initialize the CMRLCCOA as a way to obtain better-quality coati populations and increase the diversity of the population. Secondly, the generated candidate solutions are updated again using the convex lens imaging reverse learning strategy to expand the search range. Thirdly, the Lévy flight strategy increases the search step size, expands the search range, and avoids the phenomenon of convergence too early. Finally, utilizing the crossover strategy can effectively reduce the search blind spots, making the search particles constantly close to the global optimum solution. The four strategies work together to enhance the efficiency of COA and to boost the precision and steadiness. The performance of CMRLCCOA is evaluated on CEC2017 and CEC2019. The superiority of CMRLCCOA is comprehensively demonstrated by comparing the output of CMRLCCOA with the previously submitted algorithms. Besides the results of iterative convergence curves, boxplots and a nonparametric statistical analysis illustrate that the CMRLCCOA is competitive, significantly improves the convergence accuracy, and well avoids local optimal solutions. Finally, the performance and usefulness of CMRLCCOA are proven through three engineering application problems. A mathematical model of the hypersonic vehicle cruise trajectory optimization problem is developed. The result of CMRLCCOA is less than other comparative algorithms and the shortest path length for this problem is obtained.

The construction industry faces significant challenges in measuring and assessing performance effectively. Conventional methods of measuring construction performance have become less effective, prompting a need to adopt non-financial performance measurements. This shift acknowledges the shortcomings of relying solely on financial performance measurement systems. As a result, there has been a substantial increase in research and focus on non-financial performance measurement systems in recent decades. This study focuses on analyzing performance measurement practices and key performance indicators (KPIs) in the construction industry, specifically at the project level. By examining 146 relevant articles, the study offers a thorough overview of various aspects of project performance. In addition to the traditional dimensions of the project management triangle (cost, time, and quality performance), the study emphasizes the importance of considering other dimensions. These include stakeholder performance, safety performance, technology utilization performance, value performance, environmental impact performance, and the application of maturity models. By incorporating these additional KPIs, a more comprehensive and holistic evaluation of project performance can be achieved. This study’s findings make notable contributions to the methodological framework of performance measurement in construction projects. By consolidating diverse research sources, the study offers valuable guidance for future research in the field of project performance. Moreover, it provides insights into selecting suitable performance measurement methods, empowering practitioners to effectively assess and manage project performance.

This study presents an energy regeneration model and some theory required to construct a regeneration braking system. Due to the effects of carbon dioxide (CO2) emissions, there is increasing interest in the use of electric vehicles (EVs), electric bikes, electric bicycles, electric buses and electric aircraft globally. In order to promote the use of electric transportation systems, there is a need to underscore the impact of net zero emissions. The development of EVs requires regenerating braking system. This study presents the advantages of regenerative braking. This system is globally seen in applications such as electric cars, trams, and trains. In this study, the design specification, design methodology, testing configurations, Simulink model, and recommendations will be outlined. A unique element of this work is the practical experiment that was carried out using 1.5 Amps with no load and 2.15 Amps with a load. The discharge voltage was purely from the 22 W bulb load connected to the capacitor bank as we limited this study to the use of 1.5 Amps and it took 15 min for a full discharge cycle, after which no charge was left in the capacitor bank. The results showed that the discharge rate and charging rate for the regenerative braking system were effective but could be improved. The objective of this paper is to investigate how a supercapacitor works alongside a battery in regenerative braking applications. This study demonstrates that the superconductor used can deliver maximum power when required. Also, it can also withstand elevated peaks in charging or discharging current via the supercapacitor. Combining a battery with a supercapacitor reduces the abrupt load on the battery by shifting it to the capacitor. When these two combinations are used in tandem, the battery pack’s endurance and lifespan are both boosted.

Pyruvate is situated at the intersection of oxidative phosphorylation (OXPHOS) and glycolysis, which are the primary energy-producing pathways in cells. Cancer therapies targeting these pathways have been previously documented, indicating that inhibiting one pathway may lead to functional compensation by the other, resulting in an insufficient antitumor effect. Thus, effective cancer treatment necessitates concurrent and comprehensive suppression of both. However, whether a metabolic switch between the metabolic pathways occurs in colorectal and gastric cancer cells and whether blocking it by inhibiting both pathways has an antitumor effect remain to be determined. In the present study, we used two small molecules, namely OXPHOS and glycolysis inhibitors, to target pyruvate metabolic pathways as a cancer treatment in these cancer cells. OXPHOS and glycolysis inhibition each augmented the other metabolic pathway in vitro and in vivo. OXPHOS inhibition alone enhanced glycolysis and showed antitumor effects on colorectal and gastric cancer cells in vitro and in vivo. Moreover, glycolysis inhibition in addition to OXPHOS inhibition blocked the metabolic switch from OXPHOS to glycolysis, causing an energy depletion and deterioration of the tumor microenvironment that synergistically enhanced the antitumor effect of OXPHOS inhibitors. In addition, using hyperpolarized 13C-magnetic resonance spectroscopic imaging (HP-MRSI), which enables real-time and in vivo monitoring of molecules containing 13C, we visualized how the inhibitors shifted the flux of pyruvate and how this dual inhibition in colorectal and gastric cancer mouse models altered the two pathways. Integrating dual inhibition of OXPHOS and glycolysis with HP-MRSI, this therapeutic model shows promise as a future "cancer theranostics" treatment option.

Background Reflex tachycardia that occurs during nitroglycerin-induced hypotensive anesthesia in functional endoscopic sinus surgery (FESS) increases both the risk of intraoperative bleeding and the duration of surgery. Our clinical trial aimed to compare the effect of oral ivabradine versus oral propranolol as a premedication before nitroglycerin-induced hypotensive anesthesia on the reduction of reflex tachycardia in FESS.Methods In this clinical, comparative, prospective, randomized, controlled, double-blinded study, 40 patients were divided into two equal groups (20 each); group P received oral propranolol (10 mg tablet) and group I received oral ivabradine (5 mg tablet) in the evening before the surgery and 1 hour before the induction of anesthesia.Results The reduction in heart rate (HR) was statistically significantly higher in group I than in group P. Conversely, the reduction in mean blood pressure (MAP) was statistically significantly higher in group P than in group I at baseline (pre-induction). However, after that, MAP reduction was statistically non-significant between both groups. Meanwhile, there was no statistically significant difference between both groups as regards duration of surgery, duration of deliberate hypotension, intraoperative NTG infusion doses, and the amount of bleeding.Conclusion Premedication with oral propranolol 10 mg or oral ivabradine 5 mg before FESS proved to be safe and effective in the reduction of reflex tachycardia that occurs during controlled nitroglycerin induced hypotensive anesthesia in FESS. However, ivabradine was more effective with higher safety profile than propranolol.