Abstract
Atlantic salmon populations have declined in many regions and are affected by several natural and anthropogenic factors throughout their lives. We investigated the role of environmental drivers and the effect of dam construction on the trend in catches of spawning adults of a migratory population currently at risk. For this purpose, we examined the salmon catches from 1914 to 2020 in the Minho River (NW Portugal, SW Europe), located at the southern limit of this species' distribution. There was a decline in catches over time with an inverse and significant relationship between the trend in catches and lagged temperature. Delayed effects of this type may indicate temperature influences on survival during early life history stages. Similarly, the trend in catches decreased with the increasing number of dams. A forecast model built for the period before the construction of the first major dam in this river (before 1955), including lagged temperature, resulted in a decreasing trend in the number of catches. This demonstrates that catches would have declined due to temperature effects even without dam construction. This does not diminish the role of dams in the observed decline; rather, it reveals that temperature-driven declines would have occurred independently. Nonetheless, efficient management and conservation of this imperiled population require further detailed biological information on the number of returning spawning adults and salmons' survival throughout their life cycle.

Abstract
Background: – In the pursuit of understanding current improvements that enhance nursing care leveraging emerging technologies, this study focused on answering “How has artificial intelligence been integrated into electronic health records, with an emphasis on nursing practice?” Methods: – This scoping review was conducted after the methodology proposed by the Joanna Briggs Institute and structured according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews. The study protocol was registered on the Open Science Framework platform (DOI: 10.17605/OSF.IO/D96TY). Searches were performed across 7 databases, in addition to grey literature and manual reference screening. Results: – A total of 74 studies were included. A variety of artificial intelligence technologies were identified, particularly traditional supervised learning and natural language processing. Artificial intelligence contributed to clinical decision-making, risk anticipation, workload reduction through documentation automation, and the enhancement of documentation quality by improving its accuracy, completeness, and consistency. Discussion: – The adoption of these technologies demonstrates promising potential to optimize nursing documentation, support clinical decisions, and strengthen patient safety, thereby promoting a more efficient and evidence-based nursing practice. However, effective implementation requires attention to data quality, interoperability, and increased active engagement of nurses in the development and use of such technologies.

Abstract
Green hydrogen is expected to play an important role for decarbonizing hard-to-abate sectors but faces regulatory, economic, and operational barriers. In the EU, strict renewable energy usages requirements and temporal and geographical criteria constrain green hydrogen production and complicate integration with electricity markets. Support mechanisms (SMs), such as premiums and quotas, aim to boost hydrogen production, yet their impacts on coupled electricity-hydrogen systems remain underexplored. This paper extends a previous joint electricity-hydrogen Cournot equilibrium model to represent and analyze the impact of different green hydrogen production SMs. Different SMs lead to different equilibrium models that were solved using equivalent quadratic optimization problems and applied to real-size Iberian case studies. Results reveal how different SMs influence hydrogen and electricity prices, production and emissions, highlighting trade-offs among stakeholders. The findings provide guidance for designing balanced policies that stimulate green hydrogen while minimizing unintended consequences and offer flexible tools to assess regulatory and economic interactions in emerging hydrogen markets.

Abstract

Abstract
When shopping for perishable products, consumers typically prefer the freshest items, especially those with a short shelf life. With that in mind, retailers establish strict contractual agreements with suppliers to ensure the fulfilment of their orders for perishable products. One key condition in these agreements is the Minimum Life On Receipt (MLOR) rule, which defines the maximum product age that the retailer will accept at full price. In this study, we propose a model that facilitates the negotiation of retailer–supplier terms to increase flexibility. Specifically, we define the share of orders retailers should accept beyond the MLOR at a discounted price. We formulate the problem as a bilevel program considering the individual objectives of the retailer (leader) and the supplier (follower), while also accounting for consumer demand driven by both price and product freshness. To address the bilevel problem, we employ a reformulation-and-decomposition algorithm adapted from the literature. We then compare the supply chain benefits of solving the bilevel program with those of optimising the retailer’s and supplier’s objectives jointly in a centralised approach, as well as to standard contract terms in which products are returned if the supplier does not meet the MLOR requirement. Our results demonstrate that flexible agreements offer significant benefits, with average profit increases of up to 4% for retailers and up to 13% for suppliers. Finally, we provide suggestions for designing new clauses that account for consumer demand variability and retailer’s order frequency.

Abstract
Virtual Reality (VR) applications hold significant promise for enhancing healthcare training by providing immersive and interactive environments for skills development. This scoping review analyzed the methods, and instruments used for usability assessment in VR applications designed to support healthcare training. An electronic database search identified 19 studies meeting specific inclusion and exclusion criteria. The included studies focused on two primary objectives: (i) usability assessment, and (ii) usability and feasibility assessment, evaluating not only the usability but also the practicality and sustainability of VR applications in healthcare training settings. The findings reveal inconsistencies in the reporting of methodological details essential for robust usability assessment, particularly in terms of methods' triangulation and participants' sample sizes. This review highlights the need for more rigorous and comprehensive approaches that combine both test and inquiry methods to ensure that VR applications present good usability, which is impactful for sustainable healthcare training applications.