.
Abstract This paper presents the design and development of an adaptive online event-triggered load frequency control (LFC) framework for islanded microgrids using machine learning techniques. The proposed approach addresses the stability challenges and performance limitations of conventional LFC strategies arising from the dynamic and stochastic characteristics of modern microgrids with high renewable penetration. A Neural-PI controller, pre-trained to capture complex system dynamics, is employed to enable intelligent event-triggered switching and real-time adjustment of control gains, thereby enhancing frequency regulation and overall system stability. The framework is implemented in Python using a Jupyter Notebook environment and evaluated on the IEEE 14-bus test system, where results demonstrate its ability to dynamically adapt event thresholds under varying operating conditions, leading to improved stability and control efficiency. Accordingly, the Neural-PI controller markedly outperforms the conventional PID controller, achieving a 58% reduction in peak frequency deviations, a 33% improvement in settling time, and a 95% reduction in control actions through event-triggered switching, with particularly strong performance during periods of renewable intermittency. Its adaptive capability enabled 2.5 times more effective inertia mode changes, reduced oscillations and overshoot, and contributed to a 19% increase in renewable hosting capacity alongside a 37% reduction in load-frequency control operational costs, making it especially suitable for islanded and low-inertia grids.
This work presents a comprehensive first-principles investigation of the structural, electronic, optical, and thermoelectric properties of half-Heusler alloys HfPdX (X = Si, Ge, Sn) using density functional theory within the generalized gradient approximation, as implemented in the Quantum ESPRESSO package. Structural optimization confirms the thermodynamic stability of the compounds, with lattice parameters in good agreement with available literature. Electronic band structure calculations reveal that all three materials exhibit indirect narrow band gaps of approximately 0.69 eV (HfPdSi), 0.57 eV (HfPdGe), and 0.40 eV (HfPdSn), classifying them as narrow-gap semiconductors. Projected density of states analysis shows that the electronic states near the Fermi level are dominated by hybridized Hf-5d and Pd-4d orbitals, while the p states of the X element mainly contribute to the deeper valence bands and influence band gap narrowing along the Si → Ge → Sn trend. The calculated optical properties indicate strong interband transitions in the visible and ultraviolet regions, with HfPdSn exhibiting a well-defined absorption onset consistent with its semiconducting character, whereas HfPdSi and HfPdGe display enhanced low-energy optical response due to their narrow band gaps. Thermoelectric transport properties were evaluated using semiclassical Boltzmann transport theory within the constant relaxation time approximation. Among the studied compounds, HfPdSi shows the highest Seebeck coefficient, power factor, and overall thermoelectric performance, leading to the largest figure of merit (ZT) over the temperature range of 300–800 K. The results suggest that HfPdX alloys, particularly HfPdSi, are promising candidates for thermoelectric and optoelectronic applications, with further performance enhancement achievable through carrier concentration optimization and lattice thermal conductivity reduction.
This article argues that Nigeria has rich creative industries sectors with great potential and global footprints. Through the kaleidoscope of film, music and creative writing, it makes a critical appraisal of Nigeria's creative industries and contends that although the country is a visible player on the global landscape, it is yet to optimize the full potentiality of its creative industries sectors. The paper recommends that a clear mapping of the sector coupled with a coherent policy articulation and execution will enhance the viability of the creative industries. As the country seeks to diversify its economy away from dependency on oil revenues, the creative industries, based on their current economic value, provide a veritable incremental source of employment, revenue and growth.
The simultaneous spatiotemporal modeling of multiple related diseases strengthens inferences by borrowing information between related diseases. Numerous research contributions to spatiotemporal modeling approaches exhibit their strengths differently with increasing complexity. However, contributions that combine spatiotemporal approaches to modeling of multiple diseases simultaneously are not so common. We present a full Bayesian hierarchical spatio-temporal approach to the joint modeling of Human Immunodeficiency Virus and Tuberculosis incidences in Kenya. Using case notification data for the period 2012-2017, we estimated the model parameters and determined the joint spatial patterns and temporal variations. Our model included specific and shared spatial and temporal effects. The specific random effects allowed for departures from the shared patterns for the different diseases. The space-time interaction term characterized the underlying spatial patterns with every temporal fluctuation. We assumed the shared random effects to be the structured effects and the disease-specific random effects to be unstructured effects. We detected the spatial similarity in the distribution of Tuberculosis and Human Immunodeficiency Virus in approximately 29 counties around the western, central and southern regions of Kenya. The distribution of the shared relative risks had minimal difference with the Human Immunodeficiency Virus disease-specific relative risk whereas that of Tuberculosis presented many more counties as high-risk areas. The flexibility and informative outputs of Bayesian Hierarchical Models enabled us to identify the similarities and differences in the distribution of the relative risks associated with each disease. Estimating the Human Immunodeficiency Virus and Tuberculosis shared relative risks provide additional insights towards collaborative monitoring of the diseases and control efforts.
As the 21st Century continues to engender amazing innovations in the communication space, the influence of the media is becoming more pervasive. Thus, the media can no longer be studied separately from society; rather they must be seen as an integral part of the social structure upon which modern societies rest. Mediatization, as a theory, explains the manner in which social institutions are affected by, and seek to adapt to, the media. This paper seeks to contribute to the scholarly discussion of mediatization as a concept. It discusses its applicability within the Nigerian context and considers its implications for society. Using a mix of literature review and comments based on the authors’ observation, it discusses and interrogates the mediatization of the contemporary Nigerian society.
