534 research outputs found

    Blood microvascular organization of the nasal-associated lymphoid tissue of the guinea pig: a scanning electron microscopic study of corrosion casts.

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    It has previously been confirmed that the guinea pig has aggregations of 10-20 lymphoid follicles at the junction of the nasal cavity and the nasopharyngeal duct. The vascular architecture of this nasal-associated lymphoid tissue (NALT) was studied by the corrosion cast/scanning electron microscope method. The NALT was supplied by branches of the inferior nasal artery. These afferent arterial branches gave off arterioles to the follicles and the interfollicular regions, where the arterioles ramified into capillaries. Some of these arterioles reached the subepithelial region to form a single-layer dense capillary network. The subepithelial capillaries gathered into short collecting venules, which in turn drained into high endothelial venules (HEV) in the interfollicular region. The HEV, which also receives tributaries from the follicular and interfollicular capillary plexuses, descended in the interfollicular regions and finally flowed into the efferent veins at the bottom of the NALT. Indentations impressed by high endothelial cells (HEC) were prominent on the surface of the HEV casts, and their frequency was larger in the upper course or segments than in the lower. This suggests that the incidence of HEC in the upper segments is higher than in the lower segments, and these findings are consistent with the hypothesis that some substances which are taken up into the subepithelial capillaries and transported to the venules induce differentiation and maintain of HEVs.</p

    Consistent map building in petrochemical complexes for firefighter robots using SLAM based on GPS and LIDAR

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    The objective of this study was to achieve simultaneous localization and mapping (SLAM) of firefighter robots for petrochemical complexes. Consistency of the SLAM map is important because human operators compare the map with aerial images and identify target positions on the map. The global positioning system (GPS) enables increased consistency. Therefore, this paper describes two Rao-Blackwellized particle filters (RBPFs) based on GPS and light detection and ranging (LIDAR) as SLAM solutions. Fast-SLAM 1.0 and Fast-SLAM 2.0 were used in grid maps for RBPFs in this study. We herein propose the use of Fast-SLAM to combine GPS and LIDAR. The difference between the original Fast-SLAM and the proposed method is the use of the log-likelihood function of GPS; the proposed combination method is implemented using a probabilistic mathematics formulation. The proposed methods were evaluated using sensor data measured in a real petrochemical complex in Japan ranging in size from 550–380 m. RTK-GPS data was used for the GPS measurement and had an availability of 56%. Our results showed that Fast-SLAM 2.0 based on GPS and LIDAR in a dense grid map produced the best results. There was significant improvement in alignment to aerial data, and the mean square root error was 0.65 m. To evaluate the mapping consistency, accurate 3D point cloud data measured by Faro Focus 3D (± 3 mm) was used as the ground truth. Building sizes were compared; the minimum mean errors were 0.17 and 0.08 m for the oil refinery and management building area and the area of a sparse building layout with large oil tanks, respectively. Consequently, a consistent map, which was also consistent with an aerial map (from Google Maps), was built by Fast-SLAM 1.0 and 2.0 based on GPS and LIDAR. Our method reproduced map consistency results for ten runs with a variance of ± 0.3 m. Our method reproduced map consistency results with a global accuracy of 0.52 m in a low RTK-Fix-GPS environment, which was a factory with a building layout similar to petrochemical complexes with 20.9% of RTK-Fix-GPS data availability

    Quantifying physical insights cooperatively with exhaustive search for Bayesian spectroscopy of X-ray photoelectron spectra

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    We analyzed the X-ray photoemission spectra (XPS) of carbon 1s states in graphene and oxygen-intercalated graphene grown on SiC(0001) using Bayesian spectroscopy. To realize highly accurate spectral decomposition of the XPS spectra, we proposed a framework for discovering physical constraints from the absence of prior quantified physical knowledge, in which we designed the prior probabilities based on the found constraints and the physically required conditions. This suppresses the exchange of peak components during replica exchange Monte Carlo iterations and makes possible to decompose XPS in the case where a reliable structure model or a presumable number of components is not known. As a result, we have successfully decomposed XPS of one monolayer (1ML), two monolayers (2ML), and quasi-freestanding 2ML (qfs-2ML) graphene samples deposited on SiC substrates with the meV order precision of the binding energy, in which the posterior probability distributions of the binding energies were obtained distinguishably between the different components of buffer layer even though they are observed as hump and shoulder structures because of their overlapping

    OsDCL1a activation impairs phytoalexin biosynthesis and compromises disease resistance in rice

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    MicroRNAs (miRNAs) are small non-coding RNAs that act as post-transcriptional regulators of gene expression via sequence-specific cleavage or translational repression of target transcripts. They are transcribed as long single-stranded RNA precursors with unique stem-loop structures that are processed by a DICER-Like (DCL) ribonuclease, typically DCL1, to produce mature miRNAs. Although a plethora of miRNAs have been found to be regulated by pathogen infection in plants, the biological function of most miRNAs remains largely unknown. Here, the contribution of OsDCL1 to rice immunity was investigated. OsDCL1a activation enhances susceptibility to infection by fungal pathogens in rice. Activation of OsDCL1a represses the pathogen-inducible host defence response and negatively regulates diterpenoid phytoalexin production. These findings provide a basis to understand the molecular mechanisms through which OsDCL1a mediates rice immunity
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