Alfaisal University

Accurate yaw alignment is critical for maximizing power capture in horizontal-axis wind turbines, as even moderate yaw misalignment leads to significant aerodynamic losses, increased actuator usage, and accelerated mechanical wear. This research paper proposes a hybrid smart yaw control system for small-scale wind turbines that combines real-time measurements with short-term wind direction prediction to improve alignment accuracy, operational reliability, and energy efficiency under realistic operating conditions. The system integrates four wind direction information sources, such as physical wind vane sensing, live online weather data, forecast data, and a data-driven prediction module within a structured priority framework (VANE → LIVE → FORECAST → AI), to ensure continuous yaw control during sensor or communication unavailability. The prediction module is based on a long short-term memory (LSTM) neural network trained in MATLAB using live data from an online platform, with sine–cosine encoding employed to address the circular nature of directional data. The yaw controller incorporates a ±15° deadband, dwell-time logic, shortest-path rotation, and cable-safe constraints to reduce unnecessary actuation while maintaining effective alignment. The proposed system is validated through MATLAB/Simulink simulations and real-time microcontroller-based experiments using a stepper motor-driven nacelle. Compared with conventional vane-based yaw control, the hybrid AI-assisted approach reduces the average yaw error by approximately 35–45%, maintains a yaw error within ±15° for more than 90% of the operating time, increases average electrical power output by 3–5%, and reduces yaw motor energy consumption by 10–15%, while decreasing corrective yaw actuation events by 30–40%. These results demonstrate that integrating an LSTM-based wind direction predictor with multi-source wind data provides a robust, low-cost, and practically deployable yaw control solution that enhances energy capture and mechanical durability in small-scale wind turbines.

Background: Gene expression and cellular identity are regulated by epigenetics that occurs through chromatin modifications, RNA changes, chromatin accessibility, and three-dimensional genome organization. Although DNA methylation has been the focus of most epigenetics studies in the past, other non-methyl epigenetic processes, including histone post-translational modifications (PTMs), epitranscriptomic marks, and chromatin remodeling, are dynamic, reversible, and context-dependent, and thus are difficult to accurately interrogate using endpoint sequencing-based assays, especially in heterogeneous tissues, developing systems, and therapeutic response environments. Scope and Approach: The present review discusses epigenetic modifications other than DNA methylation regarding sensor-based technologies that can measure live, dynamic, and spatially resolved measurements. Epigenetic sensors include any genetically encoded sensors (GECs) based on resonance energy transfer, CRISPR/dCas-derived sensors, or aptamer-based sensors, and hybrid biochemical/imaging sensors that can be used in live or semi-live settings. It lays emphasis on the technologies, which have been developed recently, that allow real-time kinetic measurements, working in three-dimensional and organoid models, and being applied to disease-relevant perturbations. On these platforms, performance properties such as specificity, sensitivity, spatial and temporal resolution, ability to perform dynamic versus locus-specific interrogation, and perturbed endogenous chromatin states are compared. Key Conclusions and Outlook: Together, these sensing strategies are complementary to the traditional methods of measuring epigenomics in that they show epigenetic dynamics unobservable with static measurements. We list the important technical issues, including specificity, quantitation, multiplexing, and chromatin perturbation, and report the barriers and solutions in development and design. Lastly, we provide a conceptual map of how live epigenetic sensing and multi-omics and translational models can be integrated, and how the two methodologies can be used to develop functional epigenetics and guide disease modeling and drug development.

Programmed Death-Ligand 1 (PD-L1) promotes tumor progression through several mechanisms, including its intrinsic effect on breast cancer cell proliferation via the S-Phase Kinase-Associated Protein 2 (SKP2)-p21Cip1/p27Kip1 (SKP2-p21/p27) axis. However, the specific regulatory signaling through which PD-L1 influences the SKP2-p21/p27 axis to drive cell proliferation remains unclear. To investigate how PD-L1 mediates SKP2-dependent proliferation, proteomic analyses, gene-expression manipulation via knockdown or overexpression, Western blotting, quantitative immunofluorescence, colony-forming assays, real-time cell analysis, and Xenograft-derived cells were used. Proteomic data analysis identified several PD-L1 downstream targets as potential candidate regulators of the SKP2-p21/p27 axis and activators of the PI3K/AKT pathway. Candidate screening by gene knockdown, followed by analyses of SKP2, p21, and p27 protein expression, revealed Livin and Galectin-1 as upstream regulators of the SKP2-p21/p27 axis. Moreover, Western blotting and quantitative immunofluorescence in three breast cancer cell lines confirmed that PD-L1 is an upstream regulator of Livin, Galectin-1, and SKP2 protein expression. Mechanistically, Livin and Galectin-1 enhanced AKT phosphorylation (Ser473) to sustain PI3K/AKT pathway activation in a positive feedback loop to upregulate SKP2 expression. Functional assays, including colony-forming assays and real-time cell analyzer, demonstrated that Livin and Galectin-1 are critical for PD-L1-mediated, SKP2-dependent proliferation. These findings were corroborated in vivo using xenograft-derived cells. Overall, these findings delineate a tumor-intrinsic signaling axis in which PD-L1 upregulates Livin and Galectin-1 to sustain PI3K/AKT activity and drive SKP2-dependent cell proliferation. Targeting Livin and/or Galectin-1 may provide a rational strategy to disrupt PD-L1-associated proliferative signaling and improve combinatorial therapeutic approaches in breast cancer.

[This corrects the article DOI: 10.3389/fmed.2026.1763735.].