| 1. |
- Bastos, Carlos A.P., et al.
(författare)
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Copper nanoparticles have negligible direct antibacterial impact
- 2020
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Ingår i: NanoImpact. - : Elsevier BV. - 2452-0748. ; 17
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Soluble copper that can be acquired by bacteria is toxic and therefore antimicrobial. Whether nanostructured copper materials, in either disperse or agglomerated form, have antimicrobial impact, aside from that of their dissolution products, is not clear and was herein addressed. Methods: We took five nanostructured copper materials, two metallic, and three oxo-hydroxides with one of these being silicate-substituted. Four agglomerated in the bacterial growth media whilst the silicate-substituted material remained disperse and small (6.5 nm diameter). Antibacterial activity against E. coli was assessed with copper phase distribution measured over time. Using the dose of soluble copper, and benchmark dose non-linear regression modelling, we determined how well this phase predicted antimicrobial activity. Finally, we used Time-of-Flight Secondary Ion Mass Spectrometry (ToF-SIMS) analysis to investigate whether membrane adhe- sion effects by copper were plausible or if intracellular uptake most likely explained the bacterial impact of copper. Results: Comparison over time of antimicrobial activity against particulate or soluble phases of the aquated materials clearly demonstrated that soluble copper but not particulate forms were associated with inhibition of bacterial growth. Indeed, the benchmark dose modelling showed the soluble dose required to cause a 50% reduction in E. coli growth was strongly clustered – for all particle formulations – at 14.5 mg/L (10–19 mg/L 90% confidence interval). By comparison, total copper levels associated with the same reduction in viability varied widely (45–549 mg/L). Finally, in favour of this soluble product dominance in terms of antimicrobial activity, copper had low association with bacterial membrane (something both soluble and particulate materials could do) but showed high intra-bacterial levels (something only soluble copper could do). Conclusion: Taken together our data show that it is the uptake of soluble but not particulate copper, and the intracellular loading not just contact and membrane association, that drives copper toxicity to bacteria. Therapeutic strategies for novel antimicrobial copper compounds should consider these findings.
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| 2. |
- Blackburn, Landen D., et al.
(författare)
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Dynamic machine learning-based optimization algorithm to improve boiler efficiency
- 2022
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Ingår i: Journal of Process Control. - : Elsevier BV. - 0959-1524. ; 120, s. 129-149
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Forskningsöversikt (refereegranskat)abstract
- With decreasing computational costs, improvement in algorithms, and the aggregation of large industrial and commercial datasets, machine learning is becoming a ubiquitous tool for process and business innovations. Machine learning is still lacking applications in the field of dynamic optimization for real-time control. This work presents a novel framework for performing constrained dynamic optimization using a recurrent neural network model combined with a metaheuristic optimizer. The framework is designed to augment an existing control system and is purely data-driven, like most industrial Model Predictive Control applications. Several recurrent neural network models are compared as well as several metaheuristic optimizers. Hyperparameters and optimizer parameters are tuned with parameter sweeps, and the resulting values are reported. The best parameters for each optimizer and model combination are demonstrated in closed-loop control of a dynamic simulation, and several recommendations are made for generalizing this framework to other systems. Up to 0.953% improvement is realized over the non-optimized case for a simulated coal-fired boiler. While this is not a large improvement in percentage, the total economic impact is $991,000 per year, and this study builds a foundation for future machine learning with dynamic optimization.
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| 3. |
- Bombarda, F., et al.
(författare)
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Runaway electron beam control
- 2019
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Ingår i: Plasma Physics and Controlled Fusion. - : IOP Publishing. - 1361-6587 .- 0741-3335. ; 61:1
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Tidskriftsartikel (refereegranskat)
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| 4. |
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- 2018
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Ingår i: Nuclear Fusion. - : IOP Publishing. - 1741-4326 .- 0029-5515. ; 58:1
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Forskningsöversikt (refereegranskat)
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