Al-Ahliyya Amman University

With the increasing incorporation of Renewable Energy Sources (RESs) like solar Photovoltaic (PV) systems, maintaining frequency stability has turned out to be a significant challenge owing to decreased system inertia. Despite numerous developments in Load Frequency Control (LFC), existing solutions largely overlooked the issue of Under Frequency Load Shedding (UFLS) relay failure during rapid frequency decline, which led to widespread blackouts. To address this critical gap, a novel intelligent control framework integrating the Fuzzy Doubleton Parabolic Inference System (FDPIS) and the Proportional Quad-Alpine Integral Derivative (PQAID) controller for UFLS relay failure mitigation and enhanced LFC in Solar-PV systems is proposed. Primarily, the Direct Current (DC) power from the solar module is fed into the DC-DC boost converter and Maximum Power Smoothstep Point Tracking (MPSPT) algorithm. A capacitor bank failure is detected using FDPIS, and voltage stabilization is ensured through a Savitzky-Golay Dynamic Polynomial-Z Voltage Restorer (SGDP-ZVR). To predict electrical load demand accurately, a hybrid Deep Learning (DL) model, Deep Dualplus Softshrink Pan–Long Short Term Inverse Parzen Memory (2DSP-LSTIPM), is employed, delivering a high accuracy of 98.98 % with a Root Mean Squared Error (RMSE) of 0.002. When demand exceeds thresholds, transmission overload is mitigated using an Inductive Snubber Cubic Circuits–STATCOM (IS2C-STATCOM). The frequency deviation is identified via FDPIS, followed by the Rate Of Change Of Frequency (ROCOF) analysis. If a UFLS relay failure is detected, then the PQAID controller is activated to ensure stable operation. The proposed PQAID achieves a peak time of 1.91 ms, significantly outperforming traditional PID, PI, and PD controllers in transient and overshoot metrics. Simulation results on the HEDGW dataset assess the proposed approach’s robustness and low time complexity. The system demonstrates superior relay fault detection (fuzzification/defuzzification times of 452ms/463ms) and faster rule generation (597 ms) compared to conventional fuzzy systems. Overall, the proposed methodology provides a comprehensive, real-time, and scalable solution for enhancing frequency stability, relay fault mitigation, and load management in solar PV-based smart grids. • Integrates FDPIS and PQAID for real-time UFLS relay failure detection and mitigation in solar PV systems. • Proposes novel 2DSP-LSTIPM deep learning model achieving 98.98 % demand prediction accuracy with RMSE of 0.002. • Introduces SGDP-ZVR for voltage stabilization during capacitor bank faults using Savitzky-Golay filtering. • Deploys IS2C-STATCOM for efficient transmission overload control with fast reactive power regulation. • Enables seamless SCADA/EMS integration via OPC-UA protocol for smart grid compatibility and deployment.

Psychedelics have garnered significant interest for their therapeutic potential in mental health conditions such as depression, anxiety, and post-traumatic stress disorder. While research has primarily focused on well-studied psychedelics, phenethylamine derivatives have also gathered interest for their potential therapeutic applications. Thus, this study aims to investigate the pharmacological profile, safety and therapeutic potential of novel N-(2-fluorobenzyl) phenethylamine analogs (NBFs) of the 2C-X series-25C-NBF, 25B-NBF, and 25I-NBF. NBFs displayed high affinity and selectivity for the 5-HT2A receptor and demonstrated bias factors (defined in our study as the preference for Gq over β-arrestin pathways at 5-HT2A receptor) similar to that of 5-HT. Acute administration induced moderate head-twitch responses without affecting locomotion or pre-pulse inhibition. Our studies revealed no rewarding effects in mice nor reinforcing effects or changes in accumbal dopamine levels in rats after NBFs administration. Further characterization of 25C-NBF revealed psychoplastogenic effects (dendritogenesis, spinogenesis and increased Bdnf mRNA levels) both in vitro and in vivo. In addition, 25C-NBF reduced despair-like behavior in response to acute stress and exerted rapid antidepressant effects in a model of anhedonia-like behavior induced by chronic corticosterone administration. Taken together, these findings suggest that 25C-NBF, and further analogs, may hold potential as novel antidepressants with a rapid onset of action and a favorable safety profile in terms of no abuse potential or sensorimotor gating deficits.

Leukemia, characterized by the uncontrolled proliferation of abnormal white blood cells, encompasses several subtypes, including acute myeloid leukemia (AML), acute lymphoblastic leukemia (ALL), chronic lymphocytic leukemia (CLL), and chronic myeloid leukemia (CML). It presents a significant challenge in treatment due to its complex biology and the presence of drug resistance. Autophagy, a cellular process responsible for degrading and recycling cellular components, plays a dual role in leukemia. On one hand, autophagy helps cancer cells survive and adapt to stressors, including chemotherapy, promoting drug resistance. On the other hand, it can also function as a tumor suppressor by enhancing sensitivity to treatment. MicroRNAs (miRNAs), small RNA molecules that regulate gene expression, are crucial in modulating autophagy-related genes and signaling pathways in leukemia. Dysregulated miRNAs can either inhibit or enhance autophagy, influencing leukemia progression and response to therapy. Targeting the interaction between autophagy and miRNAs presents a novel therapeutic strategy to overcome drug resistance and improve leukemia treatment outcomes. By understanding the molecular mechanisms of autophagy and miRNAs, new treatment strategies could be developed that focus on restoring proper autophagic function and miRNA regulation, ultimately enhancing the effectiveness of chemotherapy and reducing side effects. This review explores the dual roles of autophagy and miRNAs in leukemia, providing a deeper insight into their interplay and their potential for improving therapeutic approaches.