Assessing the CFD applicability of chemical kinetic mechanisms for pure ammonia combustion

Ammonia is a promising carbon-free fuel, but realising its potential for green energy requires combustion models that are both accurate and computationally efficient. While many reaction mechanisms have been proposed, few are designed with computational fluid dynamics (CFD) applications in mind. This study evaluates 11 mechanisms based on their predictions of laminar flame speed, peak flame temperature, NO emissions, computational cost, and minimum species timescales. One-dimensional flame simulations across equivalence ratios from 0.5 to 1.5 identified three different mechanisms as the most promising, though each showed trade-offs in computational cost, NO prediction, or laminar flame speed accuracy. Random forest regression showed that the minimum species time scale is a key factor for solution time, on par with the number of reactions. Mechanisms with OH* sub-mechanisms produced very short time scales, potentially limiting their CFD applicability. Overall, the results highlight the need to balance computational cost and accuracy in mechanism selection, and call for further development of reduced mechanisms that address CFD-relevant metrics, such as the minimum species time scale

How many samples do we need to be representative?:Grid sampling in Danish waters for assessing the distribution of microplastics and tire wear particles in seabed sediments

This study investigates the short-distance variability in microplastics (MPs) and tire wear particles (TWPs) concentrations in coastal sediment environments, aiming to refine sampling strategies for accurate environmental assessments. Grid sampling was conducted at two Danish sites, Strandby (∼0.57 km2, 16 sampling points with distance ranging from 215 to 1070 m) and Odense (∼0.95 km2, 13 sampling points, with distances ranging from 215 to 1577 m), followed by MP and TWP extraction and quantification. The results revealed significant variation in MP and TWP concentrations within and between sites, with Odense showing much higher contamination levels than Strandby likely due to the proximity to pollution sources and differences in depositional environments. No TWPs were detected at Strandby, likely due to its distance to road surfaces, as TWPs are made from the friction between tires and road surfaces. Monte Carlo simulations indicated that with 10 sampling points, the mean of the samples has a 50 % probability of being within 94-119 % of the true mean, defined here as the overall mean obtained from this study. The findings underscore the importance of collecting multiple samples to accurately represent MP pollution in the sediment compartment and provide recommendations for future monitoring efforts and sampling strategies.</p

The Impact of Graph Structure, Cluster Centroid and Text Review Embeddings on Recommendation Methods

It is generally accepted that collaborative information is important for the performance of recommender systems. It is also generally accepted that if this information is sparser, it impacts recommendation systems negatively. Various approaches have tried to lift this problem by employing side information. However, global patterns that can be provided by clusters of similar items and users or even additional information such as text are often not used together with collaborative information. We study the impact of integrating clustering embeddings, review embeddings, and their combinations with embeddings obtained by a recommender system. We study the performance of this approach across various state-of-the-art recommender system algorithms including graph-based methods. We highlight that graph structures are important with sparser datasets and both, in knowledge graphs with side information as well as in collaborative bipartite graphs. In less sparse datasets, a collaborative bipartite graph is usually sufficient. We also highlight that the improvement of recommendation performance through clustering, particularly evident when combined with review embeddings is most visible on sparser data, while on less sparse data incorporating review embeddings may be sufficient when combined with one of the graph-based methods, or otherwise when combined with clustering in other methods

Effektive retsmidler:som en menneskerettighed

Det overordnede formål med antologien er at analysere adgangen til effektive retsmidler i forskellige juridiske kontekster, hvor retsstillingen måtte være uklar eller omdiskuteret. Udover menneskeretten selv berøres således også retsområderne persondataret og digitalisering, forvaltningsret, EU -ret, strafferet, udlændingeret, politiret og sundhedsret. Undersøgelsen af disse retsområder sker med udgangspunkt i EMRK’s artikel 13 men også med inddragelse af andre retskilders og menneskerettighedssystemers tilsvarende bestemmelser (f.eks. EU’s Charter om Grundlæggende Rettigheder artikel 47), hvor dette anses for relevant. Antologien skal dermed bidrage til en forståelse af de institutionelle, proceduremæssige og indholdsmæssige krav til national sikring af effektive retsmidler indenfor forskellige retsområder og med analyse af sammenhængen til de enkelte materielle konventionsrettigheder.Effective remedies in Human Rights law

Combining enzymatic biofuel cells with supercapacitors to self-charging hybrid devices

Enzymatic biofuel cells are energy conversion devices utilizing biocatalysts to directly convert chemical energy to electricity. Due to their biocompatible, sustainable and maintenance-free properties, they hold the promise as attractive energy sources for powering next generation medical electronics for personalized healthcare. Low current and power output are main bottlenecks of enzymatic biofuel cells to hinder their practical applications. Supercapacitors are able to harness ambitious energy and deliver high-power pulses. Combining enzymatic biofuel cells with supercapacitors to establish self-charging energy-conversion/energy-storage hybrid systems are considered as an effective strategy to improve the current and power output. This design enables the hybrid electric devices to scavenge ambient energy and simultaneously store it and thus increases the efficiency and facilitates the miniaturization for practical application. In this review, we first discuss various structural configurations of these self-charging hybrid systems, and then focus on explaining their charge storage mechanisms, including electrochemical double-layer capacitance, pseudocapacitance and hybrids. Several proof-of-concept applications as implantable and wearable power sources are enumerated. Finally, we provide an overview of challenges and opportunities for research and development of self-charging hybrid devices.</p