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Nitrate-dependent anaerobic methane oxidation (Nitrate-DAMO) is a novel and sustainable process that removes both nitrogen and methane. Previously, the metabolic pathway of Nitrate-DAMO has been intensively studied with some results. However, the production and consumption of nitrous oxide (N 2 O) in the Nitrate-DAMO system were widely disregarded. In this study, a Nitrate-DAMO system was used to investigate the effect of operational parameters (C/N ratio, pH, and temperature) on N 2 O accumulation, and the optimal operating conditions were determined (C/N = 3, pH = 6.5, and temperature = 20 °C). In this study, an enzyme kinetic model was used to fit the nitrate nitrogen degradation and the nitrous oxide production and elimination under different operating conditions. The thermodynamic model of N 2 O production and elimination in the system also has been constructed. Multiple linear regression analysis found that pH was the most important factor influencing N 2 O accumulation. The Metagenomics sequencing results showed that alkaline pH promoted the abundance of Nor genes and denitrifying bacteria, which were significantly and positively correlated with N 2 O emissions. And alkaline pH also promoted the production of Mdo genes related to the N 2 O-driven AOM reaction, indicating that part of the N 2 O was consumed by denitrifying bacteria and the other part was consumed by the N 2 O-driven AOM reaction. These findings reveal the mechanism of N 2 O production and consumption in DAMO systems and provide a theoretical basis for reducing N 2 O production and greenhouse gas emissions in actual operation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Indoor localization and navigation have become an increasingly important problem in both industry and academia with the widespread use of mobile smart devices and the development of network techniques. The Wi-Fi-based technology shows great potential for applications due to the ubiquitous Wi-Fi infrastructure in public indoor environments. Most existing approaches use trilateration or machine learning methods to predict locations from a set of annotated Wi-Fi observations. However, annotated data are not always readily available. In this paper, we propose a robot-aided data collection strategy to obtain the limited but high-quality labeled data and a large amount of unlabeled data. Furthermore, we design two deep learning models based on a variational autoencoder for the localization and navigation tasks, respectively. To make full use of the collected data, a hybrid learning approach is developed to train the models by combining supervised, unsupervised and semi-supervised learning strategies. Extensive experiments suggest that our approach enables the models to learn effective knowledge from unlabeled data with incremental improvements, and it can achieve promising localization and navigation performance in a complex indoor environment with obstacles.

Acer truncatum Bunge seed oil (ASO) is rich in ω-9 (53.93%) and ω-6 (30.7%) fatty acids (FAs) and characterized by 3-7% nervonic acid (NA, C24:1ω-9). Evidence suggests that ω-9 FAs such as NA participate in processes of cognitive improvement; however, their mechanism remains ambiguous. In this study, we investigated the effect of ASO on rat memory and the change in lipid profiling and underlying metabolism. After ASO was administrated to rats for one, three and seven days, their capacity for learning and memory significantly increased via the MWM test. Lipid profiling showed alterations in a wide range of metabolic features after ASO was administrated to the rats, in which sphingolipids (SP) in the serum and glycerophospholipids (GP) in the brain were regulated significantly. The changes in the fatty acids in the serum and brain showed the synergetic effects of NA, EA, OA and DHA, where NA, EA and OA exhibited similar change trends. The enrichment analysis based on KEGG indicated that ASO supplementation evoked the pathways of neurotrophin signaling, glycerophospholipid metabolism and sphingolipid metabolism, which are related to memory and cognition improvement. Among the metabolites with different molecular forms, the biomarkers with C24:1ω-9 chains exhibited a positive correlation with others both in the serum SP and brain GP. These results suggest the synergistic effects of ω-9 FAs and that their conversion into each other may result in enhanced cognition in rats ingesting Acer truncatum Bunge seed oil.