The widespread use of antiviral pharmaceuticals during and after the COVID-19 pandemic has raised growing concerns about their role as emerging environmental contaminants. These compounds, including favipiravir, remdesivir, molnupiravir, and oseltamivir carboxylate, are frequently detected in hospital effluents, municipal wastewater, and surface waters. Unlike many previous reviews that treat pharmaceuticals as a broad and undifferentiated class, this article focuses specifically on antiviral drugs as a distinct group of emerging contaminants and provides an integrated perspective that is still largely missing from the literature. As a review article, this work offers a critical and comprehensive synthesis that brings together environmental monitoring data, ecotoxicological and resistance-related risks, and advanced remediation strategies within a single framework. Particular emphasis is placed on recent advances in semiconductor-based photocatalytic degradation (TiO2, ZnO, g-C3N4, and their hybrids) and on mechanistic insights supported by density functional theory (DFT) and machine-learning (ML) approaches, which are used to link molecular-level properties to degradation efficiency and pathway selectivity. By systematically combining occurrence patterns, risk assessment, and DFT/ML-informed photocatalysis—specifically for antiviral pharmaceuticals—this review is among the first to delineate design principles and knowledge gaps unique to this drug class. The article highlights critical research needs and outlines future directions toward reproducible, computationally guided, and scalable treatment technologies for antiviral pollutants.
Bolted connections are being considered as an assembly method for the foundations of floating offshore wind turbines. A clear benefit of this method is the short assembly time of these foundations compared to welding. However, some concerns around corrosion, fatigue, and the ability of bolted connections to maintain preload remain. This review found that conventional ring flanges may not be suitable for the assembly of floating foundations, mainly due to the risk of bolt loosening and reduced fatigue life. However, the C1 Wedge Connection is an innovative bolted connection that has shown its ability to retain bolt preload during tests. Likewise, the Compact Flange Connection has shown its ability to retain preload without requiring maintenance during operational stages and furthermore, has a long and successful track record in offshore oil and gas applications. This review revealed several research gaps related to the use of bolted connections for the assembly of floating wind turbine foundations. These include: a lack of research on the effects of bolt loosening; dynamic loads and shear forces on bolted connections and their effect on fatigue life; structural health monitoring methods of bolted connections; and the health and safety of technicians in confined spaces with difficult accessibility. The Compact Flange Connection is perhaps the best suited bolted connection for the assembly of floating foundations. However, more research, and crucially, successful offshore demonstrations will be essential to increase confidence in the suitability of bolted connections for the floating offshore wind industry.
Understanding protein functions is essential for advancing quantitative synthetic biology, which applies quantitative and systems approaches to understand how biological functions emerge from building blocks, thereby guiding the rational design of complex living systems. Apart from a few model organisms, most species contain many proteins with unverified functions, highlighting the need for accurate, automated protein function annotation methods. Recent advances in protein bioinformatics, particularly in predicting structures and functions, have been driven by artificial intelligence (AI), especially deep learning models. Top-performing methods in the Critical Assessment of Function Annotation (CAFA) challenge have leveraged large language models to perform text mining-based protein function prediction, extracting features from scientific literature or using template proteins with similar descriptions in the literature. Despite these advances, several challenges remain. Current predictors often depend on PubMed abstracts curated by UniProt, leading to redundancy with manual annotations and to the overlooking of uncurated or full-text literature that contains richer functional evidence. Few systems automatically classify literature types or assess their relevance, limiting precision and interpretability. Benchmarking remains difficult due to the absence of unbiased gold standards, making it hard to evaluate true predictive capability. Furthermore, integrating heterogeneous evidence—from text, sequences, and structural or network data—presents additional challenges for model harmonization. This review not only summarizes current methods and limitations but also highlights strategies to improve text mining-based protein function annotation using recent AI developments. Overall, this work aims to guide the development of next-generation tools for more accurate and comprehensive protein function predictions.
Fingermarks are frequently left on metal surfaces such as kitchen utensils, door handles, or elevator buttons in crime scenes. They are crucial forensic evidence to identify individuals and link them to crimes. Fingermark development on metal surfaces targets either the fingermark residues or the substrate. This study aimed to develop a rapid fingermark development method based on displacement reactions between copper (II) sulphate and various types of metal substrates, such as brass, galvanized iron, and low-carbon steel. Immersion of the metal substrate was more effective in fingermark visualization than applying the solution using a dropper. The optimized concentrations of copper (II) sulphate solution for fingermark visualization were found to be 0.7 M for brass, 0.5 M for galvanized iron, and 0.2 M for low-carbon steel. Sebaceous-rich fingermarks were visualized after the 5th depletion on brass and galvanized iron, and even after the 7th depletion on low-carbon steel. Further improvement is required before incorporating the application of copper (II) sulphate onto metal substrates to visualize fingermarks in real crime cases, due to the destructive nature of substrate submersion.
