Artificial intelligence (AI) has rapidly become a core enabling technology in photovoltaic (PV) power systems, supporting improvements in forecasting accuracy, operational control, fault diagnosis, and system-level energy management. Despite the rapid growth of this field, a comprehensive understanding of its intellectual structure, thematic evolution, and emerging methodological directions remains fragmented. To address this gap, this study develops an integrated bibliometric-thematic analysis framework to systematically map the knowledge structure, research trajectories, and methodological frontiers of AI applications in PV power systems. The analysis is based on 4752 peer-reviewed journal articles indexed in Scopus (2006–2025). It combines performance analysis, co-citation analysis, keyword co-occurrence analysis, and bibliographic coupling to answer five structured research questions. The results demonstrate that PV power forecasting constitutes the central intellectual backbone of AI-based PV research, with the highest citation concentration and the strongest thematic connectivity across clusters. Thematic evolution analysis reveals a clear methodological transition from conventional machine learning models toward hybrid deep learning architectures, uncertainty-aware prediction frameworks, and physics-based AI integration. Furthermore, emerging research frontiers are characterized by generative learning models, multi-source data fusion strategies, and resilience-oriented fault diagnostics, while critical gaps persist in benchmarking standardization, uncertainty quantification, system-level integration, and large-scale industrial deployment. Unlike prior reviews that focus on isolated technical applications, this study provides the first integrated performance analysis and science-mapping synthesis that connects intellectual foundations, thematic evolution, and frontier innovations across the entire AI-based PV ecosystem. The findings offer a structured research roadmap and actionable guidance for researchers, PV plant operators, and policymakers aiming to design intelligent, scalable, and resilient PV energy systems that support the global low-carbon transition.
Group 2 innate lymphoid cells (ILC2s) are tissue-resident sentinels pivotal for maintaining barrier homeostasis and orchestrating type 2 immunity. Upon acute injury, alarmins rapidly activate ILC2s, which promote tissue repair by secreting amphiregulin, IL-5, and IL-13, driving epithelial proliferation and migration, anti-inflammatory macrophage polarization, and immune regulation. Under specific conditions, such as allergen immunotherapy, a subset of ILC2s can be induced to produce IL-10, further enhancing immune regulation and tissue repair. However, in chronic inflammatory or fibrotic diseases, such as asthma, atopic dermatitis, pulmonary and liver fibrosis, and cardiovascular disorders, persistent activation skews ILC2s toward a pathogenic state. Here, excessive cytokine production drives eosinophilia, mucus hypersecretion, and fibroblast activation, while microenvironmental cues can induce plasticity toward pro-inflammatory Group 1 innate lymphoid cell (ILC1)-like phenotypes. This review systematically details the dual, context-dependent roles of ILC2s across major organs, highlighting their function as critical regulators of the repair-fibrosis axis. We critically examine the sources of functional variability, including differences in injury models, disease chronicity, species-specific effects, and ILC2 subset definitions that may explain apparent contradictions in the literature. Where appropriate, we compare ILC2 functions with those of other immune cell types such as regulatory T cells (Tregs) and macrophages, emphasizing the unique and overlapping contributions of each population. Finally, we discuss emerging therapeutic strategies that aim to precisely inhibit pathogenic ILC2 responses or harness their reparative potential, offering promising avenues for treating a spectrum of chronic inflammatory and fibrotic diseases.
The increasing demand for clean water, coupled with growing concerns over energy consumption and environmental impact, has intensified the search for sustainable materials and fabrication strategies for water treatment technologies. Polymer composites have emerged as highly promising candidates due to their tunable chemistry, lightweight nature, and compatibility with functional fillers. At the same time, additive manufacturing (AM) offers unique advantages in terms of design freedom, material efficiency, and customizable architectures. This review provides a comprehensive assessment of sustainable polymer composites fabricated via additive manufacturing for advanced water treatment applications. Major AM techniques, including material extrusion, vat photopolymerization, material jetting, powder bed fusion, binder jetting, and sheet lamination, are critically evaluated with respect to their printability, design flexibility, and environmental footprint. Emphasis is placed on sustainable polymer matrices such as polylactic acid, polyhydroxyalkanoates, cellulose-based polymers, and recycled plastics, as well as eco-friendly fillers and functional additives, including biochar, lignin, chitosan, nanocellulose, clays, zeolites, hydroxyapatite, and functional nanomaterials (e.g., AgNPs, TiO2, ZnO, and graphene). The role of composite architecture, surface modification, and hierarchical porosity enabled by AM in enhancing adsorption, catalytic activity, and antimicrobial performance is highlighted. This review demonstrates that integrating sustainable materials with additive manufacturing enables the development of multifunctional, energy-efficient, and circular water treatment systems. The findings support the advancement of purification technologies aligned with the United Nations Sustainable Development Goals, particularly SDG 6, SDG 12, and SDG 13.
The demand for sustainable, biodegradable alternatives in the food industry has increased globally due to the growing environmental impact of plastic packaging. Due to their outstanding film-forming qualities, safety, affordability, and renewability, starch-based edible coatings have become a promising solution. This article offers a thorough overview of starch-based edible coatings, including formulation strategies, coating application techniques, chemical modification methods, and sources of starch. A critical review is conducted of the functional aspects of starch coatings, such as barrier qualities, mechanical behavior, biodegradability, and compatibility with active additives like antimicrobials, antioxidants, and nanoparticles. Applications across a variety of food systems, including fruits, vegetables, meat, seafood, dairy, bakery, and confectionery products, demonstrate the ability of starch coatings to reduce moisture loss, delay oxidative and microbial spoilage, and extend shelf life. Advancements in nanocomposite films, intelligent pH-sensitive systems, and starch-polymer blends highlight emerging opportunities for next-generation active and smart packaging. Despite their potential, commercial adoption is hindered by factors like moisture sensitivity, limited mechanical strength, and scale-up barriers. The review also emphasizes the need for optimized modification methods, green processing technologies, and improved cost-effectiveness to enhance industrial applicability.
