Explore the vast range of titles available.

Introduction Healthcare systems are complex and challenging for all stakeholders, but artificial intelligence (AI) has transformed various fields, including healthcare, with the potential to improve patient care and quality of life. Rapid AI advancements can revolutionize healthcare by integrating it into clinical practice. Reporting AI’s role in clinical practice is crucial for successful implementation by equipping healthcare providers with essential knowledge and tools. Research Significance This review article provides a comprehensive and up-to-date overview of the current state of AI in clinical practice, including its potential applications in disease diagnosis, treatment recommendations, and patient engagement. It also discusses the associated challenges, covering ethical and legal considerations and the need for human expertise. By doing so, it enhances understanding of AI’s significance in healthcare and supports healthcare organizations in effectively adopting AI technologies. Materials and Methods The current investigation analyzed the use of AI in the healthcare system with a comprehensive review of relevant indexed literature, such as PubMed/Medline, Scopus, and EMBASE, with no time constraints but limited to articles published in English. The focused question explores the impact of applying AI in healthcare settings and the potential outcomes of this application. Results Integrating AI into healthcare holds excellent potential for improving disease diagnosis, treatment selection, and clinical laboratory testing. AI tools can leverage large datasets and identify patterns to surpass human performance in several healthcare aspects. AI offers increased accuracy, reduced costs, and time savings while minimizing human errors. It can revolutionize personalized medicine, optimize medication dosages, enhance population health management, establish guidelines, provide virtual health assistants, support mental health care, improve patient education, and influence patient-physician trust. Conclusion AI can be used to diagnose diseases, develop personalized treatment plans, and assist clinicians with decision-making. Rather than simply automating tasks, AI is about developing technologies that can enhance patient care across healthcare settings. However, challenges related to data privacy, bias, and the need for human expertise must be addressed for the responsible and effective implementation of AI in healthcare.

The population of the world is predicted to reach nine billion by 2050, implying that agricultural output must continue to rise. To deal with population expansion, agricultural chores must be mechanized and automated. Over the last decade, ground robots have been developed for a variety of agricultural applications, with autonomous and safe navigation being one of the most difficult hurdles in this development. When a mobile platform moves autonomously, it must perform a variety of tasks, including localization, route planning, motion control, and mapping, which is a critical stage in autonomous operations. This research examines several agricultural applications as well as the path planning approach used. The purpose of this study is to investigate the current literature on path/trajectory planning aspects of ground robots in agriculture using a systematic literature review technique, to contribute to the goal of contributing new information in the field. Coverage route planning appears to be less advanced in agriculture than point-to-point path routing, according to the finding, which is due to the fact that covering activities are usually required for agricultural applications, but precision agriculture necessitates point-to-point navigation. In the recent era, precision agriculture is getting more attention. The conclusion presented here demonstrates that both field coverage and point-to-point navigation have been applied successfully in path planning for agricultural robots.

This study examined the impact of first language (L1) on adjective ordering among Saudi English as a Foreign Language (EFL) learners. The main hypothesis posited that the presence of a common adjective ordering convention in both Arabic and English would influence the proficiency and accuracy of Saudi EFL learners in generating this specific ordering in English. To test this hypothesis, 36 Saudi EFL learners representing high and low levels of proficiency were selected. They were instructed to arrange a set of adjectives in three combinations: non-absolute + absolute (NA), absolute + absolute (AA), and non-absolute + non-absolute (NN). Statistical analyses revealed that the performance of the NA combination, which exists in both languages, was superior to the NN and AA combinations for all participants. Additionally, a significant interaction was observed between the participants' proficiency levels and the adjective combinations, with the high-proficiency group outperforming the low-proficiency group in all combinations. These findings suggest that L1 influence may have a role in learning English adjective ordering and emphasize the importance of considering L1 transfer in EFL instruction.

This study examined the impact of first language (L1) on adjective ordering among Saudi English as a Foreign Language (EFL) learners. The main hypothesis posited that the presence of a common adjective ordering convention in both Arabic and English would influence the proficiency and accuracy of Saudi EFL learners in generating this specific ordering in English. To test this hypothesis, 36 Saudi EFL learners representing high and low levels of proficiency were selected. They were instructed to arrange a set of adjectives in three combinations: non-absolute + absolute (NA), absolute + absolute (AA), and non-absolute + non-absolute (NN). Statistical analyses revealed that the performance of the NA combination, which exists in both languages, was superior to the NN and AA combinations for all participants. Additionally, a significant interaction was observed between the participants' proficiency levels and the adjective combinations, with the high-proficiency group outperforming the low-proficiency group in all combinations. These findings suggest that L1 influence may have a role in learning English adjective ordering and emphasize the importance of considering L1 transfer in EFL instruction. Index Terms--L1 transfer, English adjective ordering, absolute adjectives, non-absolute adjectives

The rapid adoption of electric vehicles (EVs) has driven the continuous evolution of traction systems, necessitating efficiency, reliability, and performance improvements. Conventional motor designs, such as single-stator permanent magnet synchronous machines (PMSMs) and induction motors, often suffer from limited torque density, inefficient thermal dissipation, high torque ripple, and reduced fault tolerance. These challenges hinder optimal EV performance, particularly under varying load conditions. Dual-stator machines (DSMs) have emerged as a promising alternative. They offer higher torque density, improved power distribution, enhanced thermal management, and increased redundancy, making them more resilient to faults. This paper presents a comprehensive mathematical modelling and operational analysis of DSMs, emphasizing their advantages over traditional motor architectures. Furthermore, the Field-Oriented Control (FOC) strategy, a widely adopted method for high-performance motor control, is explored in depth for its suitability in DSM applications. The challenge here is to designate one stator as the primary induction system, ensuring its power is effectively controlled. When the first stator reaches its maximum power capacity, the second stator compensates accordingly. The control design was specifically developed to achieve this objective. MATLAB-based simulations are conducted to assess efficiency, torque response, and fault-tolerant capability, demonstrating the superior performance of DSMs in EV traction systems. The findings highlight the potential of DSMs to redefine next-generation EV propulsion by enhancing power efficiency, reliability, and operational stability.

Numerous integrals of the fundamental frequency are known as harmonics and can be found in power systems or electrical circuitry systems. Non-linear loads occasionally drain current or contains a varying impedance with each period of the AC voltage are often responsible for power system harmonics. This can result in system overheating, system losses, and equipment or system damage. In order to achieve the IEEE 519 power quality standard, filters are routinely employed to lower harmonic levels. In this work, we designed a single tuned passive filter (STPF) to minimize harmonics of sequence 5th, 7th, 11th, 13th, 17th, and 19th in a three (3) phase power system. The measurements were taken at the point of common coupling. To test the filter performance, the system and STPF were designed in MATLAB/Simulink, and the simulated results produced without and with STPF were compared. The THD I was reduced from 14.93% down to 4.87% when STPF was connected which is within the IEEE 519-2022 standard; proving that the STPF was effective in decreasing the harmonics to the desired level.

The implementation of technology in language teaching is essential, as it can have a positive impact on the learning and teaching environment. For example, podcasts have been proven to be helpful to support learning. Therefore, the current study examines the use of podcasts to educate EFL learners about the important controversial issue of sustainability. In an exploratory stage of action research, a survey was conducted to evaluate the satisfaction of a convenience sample of 25 undergraduate EFL learners being educated about sustainability, following their use of podcasts on the topic as part of an English language listening and speaking course. The results revealed positive responses from the participants. As such, this study recommends the use of podcasts to educate EFL learners about sustainability through the medium of English and will proceed to further implementation.

One of the objectives of electrical distribution networks is to provide customers with access to high‐quality electricity. Because any disruptions in these systems result in voltage disorders, different devices are employed to offset these disruptions on consumers who are more susceptible. One of the most important and contemporary pieces of equipment that is connected in series with the network is dynamic voltage restoration (DVR), which shields delicate loads from network voltage issues by injecting the proper voltage. This article presents a DVR control scheme optimized with improved grey wolf optimization (IGWO) that uses a proportional derivative (PD) controller and adaptive notch filter (ANF). The output LC filter’s resistance has been removed, and the control system has actively engaged in oscillation damping in order to accelerate dynamic responsiveness and lower system losses. The major component of the voltage, which comprises its frequency, amplitude, and phase, is extracted using ANF. The capacitor current of the output filter in this structure is fed back to the control system and from the current mode control in the inner loop to boost stability. Owing to the occasionally complex dynamic behavior in distribution networks, particularly during a fault, the system’s frequency response has been altered and response speed has been accelerated using the PD controller. This kind of controller is distinguished by its accurate functioning in the presence of frequency deviations and its swifter dynamic reaction in the face of voltage swell and sag. In order to improve the THD and voltage sag indicators of the sensitive load, the PD coefficients were adjusted using the IGWO algorithm. As a consequence, the simulation results demonstrated that the suggested controller performed better than traditional controllers.

Vitamin C (Ascorbic acid) has evolved as an emergent co-intervention for sepsis and septic shock patients. Multiple studies discussed the pathophysiological value of vitamin C to reserve endothelial functionality and improve microcirculatory flow in these patients. Nevertheless, most randomized clinical trials failed to show the clinical impact of adding vitamin C to sepsis and septic shock. Pneumonia is the most common infection to induce sepsis and septic shock, which could be an acute respiratory distress syndrome. Preliminary in-vitro data support the role of vitamin C in mitigating the risk of acute respiratory distress syndrome (ARDS) development. This review aims to compare and contrast these trials and explore differences in their patients’ populations, methodologies, and outcomes, emphasizing pneumonia-induced sepsis and septic shock.

Background Direct oral anticoagulants (DOACs) are widely used as first-line agents in various clinical settings. However, there is very little evidence regarding their use in critically ill patients in the intensive care unit (ICU), given the gap in the literature regarding their safety in this population and the concerns of bleeding and alterations in pharmacokinetics. Therefore, this study aimed to evaluate the prescribing pattern and safety of DOAC use in critically ill patients. Methods This was a single-centre retrospective chart review study involving critically ill patients with confirmed prehospital use of DOACs who either continued their use of DOACs or switched to a therapeutic parenteral anticoagulant agent (enoxaparin or heparin) during the admission to the medical ICU and/or coronary care unit (CCU). The primary outcome was the incidence of major bleeding (MB) events. The secondary outcomes included the incidence of new thrombosis and medical ICU/CCU mortality and hospital and medical ICU/CCU lengths of stay (LOS). Results A total of 675 patients were screened for inclusion. A total of 302 patients were included in the final analysis, with 167 patients in the DOAC group and 135 patients in the parenteral anticoagulant group. There were no differences between the groups in terms of the incidence of MB (11% vs. 9%, p  = 0.61) or new thrombosis (1% vs. 3%, p  = 0.50). The overall medical ICU/CCU mortality rate was lower in the DOAC group compared to the parenteral anticoagulant group (7% vs. 15%, p  = 0.03). Additionally, the DOAC group had shorter medical ICU/CCU stays (6 days [4–11] vs. 11 days [5–24], p  < 0.001) and shorter hospital stays (7 days [5–13] vs. 13 days [7–35], p  < 0.001), respectively. Conclusion Compared with the use of parenteral anticoagulants, the use of DOACs in critically ill patients was associated with a similar incidence of MB and new thrombotic events. The observed differences in mortality and LOS between the groups may be attributed to variability in physician decision-making regarding anticoagulation strategies, potentially influenced by patient-specific factors and severity of illness. Further prospective studies to determine the optimal anticoagulation strategy in critically ill patients are warranted.