Author Correction: From countercultural ecovillages to mainstream green neighbourhoods—a view on current trends in Denmark
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Nitrospirales, including the genus Nitrospira, are environmentally widespread chemolithoautotrophic nitrite-oxidizing bacteria. These mostly uncultured microorganisms gain energy through nitrite oxidation, fix CO2, and thus play vital roles in nitrogen and carbon cycling. Over the last decade, our understanding of their physiology has advanced through several new discoveries, such as alternative energy metabolisms and complete ammonia oxidizers (comammox Nitrospira). These findings mainly resulted from studies of terrestrial species, whereas less attention has been given to marine Nitrospirales. In this study, we cultured three new marine Nitrospirales enrichments and one isolate. Three of these four NOB represent new Nitrospira species while the fourth represents a novel genus. This fourth organism, tentatively named “Ca. Nitronereus thalassa”, represents the first cultured member of a Nitrospirales lineage that encompasses both free-living and sponge-associated nitrite oxidizers, is highly abundant in the environment, and shows distinct habitat distribution patterns compared to the marine Nitrospira species. Partially explaining this, “Ca. Nitronereus thalassa” harbors a unique combination of genes involved in carbon fixation and respiration, suggesting differential adaptations to fluctuating oxygen concentrations. Furthermore, “Ca. Nitronereus thalassa” appears to have a more narrow substrate range compared to many other marine nitrite oxidizers, as it lacks the genomic potential to utilize formate, cyanate, and urea. Lastly, we show that the presumed marine Nitrospirales lineages are not restricted to oceanic and saline environments, as previously assumed.
Mobilizing power quality and reliability measurements for electricity equity and justice in Africa
In sub-Saharan Africa, urban electricity inequities manifesting as poor power quality and reliability (PQR) are prevalent. Yet, granular PQR data and frameworks for assessing PQR inequities and guiding equitable electricity interventions remain sparse. To address this gap, we present a conceptual framework that leverages energy justice, capability and multidimensional poverty theories alongside concepts relating to power systems to quantify PQR inequities in sub-Saharan Africa. To demonstrate our framework and using 1 year’s worth of remotely sensed PQR data from Accra, Ghana, we assessed the distributive scale of PQR inequities, explored how multidimensional poverty exacerbates these inequities and examined the impact of PQR on households’ domestic capabilities. We found wider patterns of PQR inequities and a link between poor PQR and neighbourhoods with higher multidimensional poverty. We conclude that using remotely sensed data combined with justice and capability frameworks offers a powerful method for revealing PQR inequities and driving sustainable energy transitions.
Adaptive link dynamics drive online hate networks and their mainstream influence
Online hate is dynamic, adaptive— and may soon surge with new AI/GPT tools. Establishing how hate operates at scale is key to overcoming it. We provide insights that challenge existing policies. Rather than large social media platforms being the key drivers, waves of adaptive links across smaller platforms connect the hate user base over time, fortifying hate networks, bypassing mitigations, and extending their direct influence into the massive neighboring mainstream. Data indicates that hundreds of thousands of people globally, including children, have been exposed. We present governing equations derived from first principles and a tipping-point condition predicting future surges in content transmission. Using the U.S. Capitol attack and a 2023 mass shooting as case studies, our findings offer actionable insights and quantitative predictions down to the hourly scale. The efficacy of proposed mitigations can now be predicted using these equations.
Operando evaluation of passivation phenomenon during ECM/Laser-ECM: direct and on-machine evidence of passivation evolution
The performance of electrochemical micromachining (ECM) is compromised when processing highly passivating materials like Ti6Al4V, which can be improved through hybrid laser-ECM (LECM) which facilitates passivation weakening. To date, passivation phenomenon has been mostly analysed through metallography and potentiometric techniques. Metallography provides oxide formation details over a limited observation area after machining, which have limited relevance for manufacturing. Whereas, potentiometric techniques cannot replicate ECM conditions to provide accurate transpassive regime conclusions. The dynamic phenomenon of passivation during ECM requires an on-machine analysis technique to provide production-oriented process history, thereby improving fundamental understanding of passivation at different processing conditions. Therefore, in this study we propose a framework based on high frequency in-process current signals which reflects the operando change in passivation for on-machine evaluation of the passivation phenomenon. We validated this framework through experiments, which demonstrated that this approach can quantitatively capture the dynamic passivation behaviour and is sensitive to different processing conditions and microstructure of the same material. The results showed that passivation weakening improved with increasing voltage up to 30 V and with LECM. In addition, the samples prepared by selective laser melting (SLM) were more resistant to EC-dissolution compared to rolled samples and the material porosity led to inhomogeneous material dissolution. Therefore, since the proposed on-machine analysis technique provides both the overall influence of passivation and its process history, it is useful for mechanistic studies and has the potential to be further developed towards process optimisation and process control.
Well-being horizons for silver and golden ages: an application of traditional and fuzzy Markov chains
European societies are currently in a process of population ageing. Although this is the general trend, it would be desirable to know whether the characteristics and intensity of this ageing process are homogeneous in all European countries. In this work, information coming from three macro-surveys (or waves) of the Survey on Health Ageing and Retirement in Europe is used for Denmark, Germany, Poland and Spain, as the basis for a longitudinal well-being and dependency indicator with the aim of studying whether the characteristics of ageing are similar in these regions. First, long-term population distributions are obtained according to the scores of the aforementioned indicator. Next, classical and fuzzy Markov chains are used to estimate steady-state distributions regarding age group, gender, country and wave. Finally, by means of a proper metric for probability distributions, steady-state distributions are clustered in different profiles, which leads us to conclude that the ageing process is not homogeneous among the studied populations.
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