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The online core monitoring system (CMS) is a crucial system for ensuring the safe operation of nuclear power plants. Its primary function is to real-time monitor the key parameter changes within the reactor core, in order to timely detect potential abnormal conditions and provide subsequent operational recommendations. The mathematical modeling of the main functions of online CMS was conducted, and its core modeling forward problem was clearly defined as well as the inverse problems of monitoring, diagnosis, and operational control. Through analyzing the research status of typical online CMS systems, the solution approaches for the aforementioned forward and inverse problems were identified, providing references for resolving specific engineering issues of online CMS in the future. The reactor core modeling mainly involves high and low-fidelity mechanistic models, as well as various machine learning models and model order reduction techniques. Solving the detector placement, physical field reconstruction, and uncertainty quantification problems using diverse types of detectors and data assimilation algorithms is the core of the monitoring inverse problem. The diagnosis inverse problem primarily relies on in-core and ex-core neutron detector information to analyze the causes of control rod drop, self-powered neutron detector anomalies, and vibration abnormalities. Utilizing the theoretical models of core tracking, various types of reactivity or power distribution control constitute the main tasks of the operational support inverse problem. Furthermore, this paper points out the existing issues in current online CMS technology research, such as multi-source information fusion, uncertainty quantification, and operational procedures. Particularly, considering the influence of various uncertainty factors within the framework of digital twins and numerical reactors, to enhance the plant operating capability, is one of the future development directions for online CMS and its underlying technologies.

Grasslands support a variety of herbivores that profoundly impact biodiversity and ecosystem functioning at local and regional scales. Understanding how different herbivores influence plant diversity across multiple scales is crucial for effective biodiversity conservation. However, most studies have focussed on the effects of grazing intensity on plant diversity, neglecting the impacts and associated mechanisms of different herbivores across scales.Based on a 7‐year grazing experiment with 16 plots in Inner Mongolia's typical steppe, we compared the scale‐dependent effects of different herbivores (cattle, sheep and goats) on plant diversity at moderate grazing intensity. We used the species–area relationship (SAR) and linear mixed models to analyse the changes in species richness across multiple scales (1, 16, 32, 64, 128, 256, 512 and 1024 m2). To understand SAR slope changes, we examined four potential mechanisms: overall species richness, total number of individuals, species abundance distribution and species aggregation.We found that grazing had scale effects on plant diversity, as indicated by a significant decrease in the SAR slope. This decrease in slope suggests that the negative impacts of grazing were more pronounced at larger scales. Additionally, the scale effects of different herbivores on plant diversity varied. Cattle had stronger positive impacts on diversity than sheep and goats at both small (1 m2) and large (1024 m2) scales. Conversely, sheep and goats had stronger negative effects on diversity than did the control at the large scale (1024 m2).The decrease in the SAR slope was mainly caused by changes in overall species richness and species abundance distribution. This was primarily because cattle had a stronger impact on dominant species, whereas sheep and goats had a stronger impact on rare species.Synthesis: Our results demonstrate that even at the same intensity, the grazing effects on species diversity vary with the study scale, herbivore type and their interaction. This finding has important implications for the conservation of grassland biodiversity given that grazing typically occurs at larger scales than in studies with quadrats and involves various herbivores with distinct effects on plant diversity. [ABSTRACT FROM AUTHOR]

Oxygen‐ion conducting perovskite oxides are important functional materials for solid oxide fuel cells and oxygen‐permeable membranes operating at high temperatures (>500 °C). Co‐doped perovskites have recently shown their potential to boost oxygen‐related kinetics, but challenges remain in understanding the underlying mechanisms. This study unveils the local cation arrangement as a new key factor controlling oxygen kinetics in perovskite oxides. By single‐ and co‐doping Nb5+ and Ta5+ into SrCoO3‐δ, dominant factors affecting oxygen kinetics, such as lattice geometry, cobalt states, and oxygen vacancies, which are confirmed by neutron and synchrotron X‐ray diffraction as well as high‐temperature X‐ray absorption spectroscopy, are controlled. The combined experimental and theoretical study unveils that co‐doping likely leads to higher cation dispersion at the B‐site compared to single‐doping. Consequently, a high‐entropy configuration enhances oxygen ion migration in the lattice, translating to improved oxygen reduction activity. [ABSTRACT FROM AUTHOR]