The increasing complexity and scale of modern power systems, combined with fluctuations in demand, modeling uncertainties, evolving network configurations, and time-varying characteristics, make load frequency control (LFC) increasingly challenging. Large frequency deviations can disrupt electric clock synchronization, alter AC motor speeds, affect magnetizing currents in transformers and induction motors, and impair the coordinated operation of systems. Conventional control methods often fail to effectively manage these uncertainties. This study evaluates LFC performance in a multi-area, multi-source interconnected power system using a novel Asymmetrical-Fuzzy-based Two-Degree-of-freedom Tilt-Integral-Derivative Controller with Low-Pass-Filter (AF-2DOF-TIDF) as a secondary control mechanism. The system comprises three unequal areas that integrate hybrid-thermal and hydropower plants, representing real-world asymmetries in capacity, inertia, and interconnections. The dynamic influence of Hydrogen-Aqua-Electrolyzer-Fuel-Cell (HAE-FC) units is analyzed relative to conventional setups. Controller parameters for TIDF, 2DOF-TIDF, and AF-2DOF-TIDF are optimized using the Skill Optimization Algorithm (SOA). Simulation results demonstrate that the proposed controller significantly enhances dynamic response, reducing overshoot, damping oscillations, and shortening settling times. The integration of a Unified Power Flow Controller (UPFC) further enhances frequency and power stability. Sensitivity analyses confirm the robustness of the proposed controller under varying loads and parameter uncertainties, with an average reduction of 68.4% in oscillation amplitude achieved.
Quantum cellular automata (QCAs) are a promising alternative to traditional CMOS technology due to their lower power consumption and ability to function at the nanoscale. However, challenges such as fault tolerance and energy efficiency remain, especially for arithmetic circuits like multipliers. The Vedic multiplier, known for its reduced computational complexity, presents a valuable opportunity to address these issues. By implementing fault-tolerant mechanisms within the QCA architecture, we aim to improve the reliability and performance of n x n multipliers in critical applications, such as cryptography, signal processing, and neural network accelerators. The proposed Vedic multiplier is designed using a hybrid of Urdhva Tiryakbhyam Sutra (vertical and crosswise technique) and error-correcting QCA gates to ensure fault tolerance. The design is implemented in a hierarchical manner, utilizing optimized QCA logic gates to form the partial product generation and summation stages. Error detection and correction techniques, such as cellular redundancy and parity-based correction, are embedded within the architecture to ensure resilience against cell misalignment and tunneling errors. Power consumption is minimized by optimizing the layout to reduce wire crossings and cell interactions. The energy efficiency and fault tolerance of the design are evaluated using QCADesigner. Simulation results demonstrate that the proposed Vedic multiplier achieves a 30
The present research aims to establish an RP-HPLC method for the simultaneous estimation of Sulopenem etzadroxil and Probenecid in a synthetic mixture and a combined dosage form by Design of Experiment and green chemistry approach. The Box-Behnken design with quadratic model and response surface methodology was adopted to ensure the effect of independent variables (Temperature, flow rate, and percentage of aqueous mobile phase) on the responses or dependent variables (RT of both drugs, resolution, and USP plate count of both drug peaks) to optimize the method confirmation of design space and robustness. The effective separation of Sulopenem etzadroxil and Probenecid was achieved with Interstil column C18 (250 × 2.1 mm,1.8 μm), 0.1
Plant-based therapeutics are increasingly studied as alternatives or add-ons to conventional antiepileptic medications. Bauhinia variegata is a medicinal plant used in traditional medicine and is reported to exhibit antioxidant and neuroprotective properties. In this study, fresh leaves of B. variegata were collected, authenticated, shade-dried, coarsely powdered, and extracted using a hydroalcoholic solvent system (ethanol:water, 6:4) via Soxhlet extraction, then dried under vacuum and lyophilized. The hydroalcoholic extract of B. variegata leaves was prepared and used for qualitative phytochemical tests and GC–MS analysis to identify major bioactive compounds. Anticonvulsant activity was tested in rats with the MES model, where animals received oral doses of the extract before electroshock-induced seizures. Preliminary phytochemical screening showed the presence of terpenoids, steroids, fatty acids, and antioxidant constituents. In the MES model, administering the hydroalcoholic extract significantly reduced seizure severity and/or prevented hind-limb tonic extension compared with vehicle-treated controls, indicating effectiveness against generalized tonic-clonic seizures. The hydroalcoholic extract of Bauhinia variegata leaves shows promising antiepileptic activity in the MES rat model, likely due to its antioxidant and neuroprotective phytoconstituents. Further research is needed to isolate active compounds, understand mechanisms (such as antioxidant activity and ion-channel modulation), and evaluate safety and dose-response relationships.
Zebrafish (Danio rerio) have proven to be a necessary model organism in the field of stress research. Their biology has been well-characterized, their genetics is amenable, and their transparent embryos allow for direct visualization of physiological and developmental events. High genetic conservation with humans and rapid development combined with lower cost make zebrafish one of the most popular models for stress studies. Stress can be induced in zebrafish through environmental factors, social stressors and pharmacological agents. This diversity makes zebrafish a versatile tool for investigating the behavioral and physiological outcomes of both acute and chronic stress. This makes zebrafish models particularly useful in studying the impact of stress on both behavioral aspects and physiological aspects such as neuroendocrine regulation by the hypothalamic-pituitary-interrenal axis, which has similarities to the mammalian HPA axis. These studies offer the basic insight of how stress works in neurodevelopment, neuroplasticity, and eventually in the pathogenesis of psychiatric disorders, including anxiety, depression, and post-traumatic stress disorder. Zebrafish are being widely applied in drug discovery and preclinical testing for identifying potential therapeutic agents against the stress-related pathways. This review would focus on the importance of the zebrafish model for stress research. It emphasizes this role in helping advance our knowledge of stress physiology and behavior while discussing some challenges, such as variability in responses and ethical issues, underpinning the call for standardized protocols for reproducible and ethical stress research.
