Three strains (YZ01T, YZ02 and YZ03) of Gram-stain-positive, facultatively anaerobic rods were isolated from the forestomach contents collected from a captive male proboscis monkey (Nasalis larvatus) at Yokohama Zoo in Japan. Phylogenetic analysis of the 16S rRNA gene sequences revealed that these strains belonged to the genus Lactobacillus. Based on the sequence similarity of the 16S rRNA gene, Lactobacillus delbrueckii subsp. indicus JCM 15610T was the closest phylogenetic neighbour to YZ01T. Sequence analyses of two partial concatenated housekeeping genes, the RNA polymerase alpha subunit (rpoA) and phenylalanyl-tRNA synthase alpha subunit (pheS) also indicated that the novel strains belonged to the genus Lactobacillus. The average nucleotide identity and digital DNA-DNA hybridization (dDDH) between L. delbrueckii subsp. indicus and YZ01T were 85.9 and 31.4 %, respectively. The phylogenetic tree based on the whole genomic data of strains YZ01T, YZ02 and YZ03 suggested that these three strains formed a single monophyletic cluster in the genus Lactobacillus, indicating that it belonged to a new species. The DNA G+C content of strain YZ01T was 51.6 mol%. The major fatty acids were C16 : 0 and C18 : 1 ω9c. Therefore, based on phylogenetic, phenotypic and physiological evidence, strains YZ01T, YZ02 and YZ03 represent a novel species of the genus Lactobacillus, for which the name Lactobacillus nasalidis sp. nov. is proposed with the type strain YZ01T (=JCM 33769T=DSM 110539T).
Traditional uncoordinated traffic flows in a roundabout can lead to severe traffic congestion, travel delay, and the increased fuel consumption of vehicles. An interesting way to mitigate this would be through cooperative control of connected and automated vehicles (CAVs). In this paper, we propose a novel solution, which is a roundabout control system (RCS), for CAVs to attain smooth and safe traffic flows. The RCS is essentially a bi-level framework, consisting of higher and lower levels of control, where in the higher level, vehicles in the entry lane approaching the roundabout will be made to form clusters based on traffic flow volume, and in the lower level, the vehicles' optimal sequences and roundabout merging times are calculated by solving a combinatorial optimization problem using a receding horizon control (RHC) approach. The proposed RCS aims to minimize the total time taken for all approaching vehicles to enter the roundabout, whilst minimally affecting the movement of circulating vehicles. Our developed strategy ensures fast optimization, and can be implemented in real-time. Using microscopic simulations, we demonstrate the effectiveness of the RCS, and compare it to the current traditional roundabout system (TRS) for various traffic flow scenarios. From the results, we can conclude that the proposed RCS produces significant improvement in traffic flow performance, in particular for the average velocity, average fuel consumption, and average travel time in the roundabout.
Energy consumption and emissions of a vehicle are highly influenced by road contexts and driving behavior. Especially, driving on horizontal curves often necessitates a driver to brake and accelerate, which causes additional fuel consumption and emissions. This paper proposes a novel optimal ecological (eco) driving scheme (EDS) using nonlinear model predictive control (MPC) considering various road contexts, i.e., curvatures and surface conditions. Firstly, a nonlinear optimization problem is formulated considering a suitable prediction horizon and an objective function based on factors affecting fuel consumption, emissions, and driving safety. Secondly, the EDS dynamically computes the optimal velocity trajectory for the host vehicle considering its dynamics model, the state of the preceding vehicle, and information of road contexts that reduces fuel consumption and carbon emissions. Finally, we analyze the effect of different penetration rates of the EDS on overall traffic performance. The effectiveness of the proposed scheme is demonstrated using microscopic traffic simulations under dense and mixed traffic environment, and it is found that the proposed EDS substantially reduces the fuel consumption and carbon emissions of the host vehicle compared to the traditional (human-based) driving system (TDS), while ensuring driving safety. The proposed scheme can be employed as an advanced driver assistance system (ADAS) for semi-autonomous vehicles.
Foregut fermentation is well known to occur in a wide range of mammalian species and in a single bird species. Yet, the foregut microbial community of free-ranging, foregut-fermenting monkeys, that is, colobines, has not been investigated so far. We analysed the foregut microbiomes in four free-ranging proboscis monkeys (Nasalis larvatus) from two different tropical habitats with varying plant diversity (mangrove and riverine forests), in an individual from a semi-free-ranging setting with supplemental feeding, and in an individual from captivity, using high-throughput sequencing based on 16S ribosomal RNA genes. We found a decrease in foregut microbial diversity from a diverse natural habitat (riverine forest) to a low diverse natural habitat (mangrove forest), to human-related environments. Of a total of 2700 bacterial operational taxonomic units (OTUs) detected in all environments, only 153 OTUs were shared across all individuals, suggesting that they were not influenced by diet or habitat. These OTUs were dominated by Firmicutes and Proteobacteria. The relative abundance of the habitat-specific microbial communities showed a wide range of differences among living environments, although such bacterial communities appeared to be dominated by Firmicutes and Bacteroidetes, suggesting that those phyla are key to understanding the adaptive strategy in proboscis monkeys living in different habitats.