Parameter Identification Method for SINS Initial Alignment under Inertial Frame

The performance of a strapdown inertial navigation system (SINS) largely depends on the accuracy and rapidness of the initial alignment. The conventional alignment method with parameter identification has been already applied widely, but it needs to calculate the gyroscope drifts through two-position method; then the time of initial alignment is greatly prolonged. For this issue, a novel self-alignment algorithm by parameter identification method under inertial frame for SINS is proposed in this paper. Firstly, this coarse alignment method using the gravity in the inertial frame as a reference is discussed to overcome the limit of dynamic disturbance on a rocking base and fulfill the requirement for the fine alignment. Secondly, the fine alignment method by parameter identification under inertial frame is formulated. The theoretical analysis results show that the fine alignment model is fully self-aligned with no external reference information and the gyrodrifts can be estimated in real time. The simulation results demonstrate that the proposed method can achieve rapid and highly accurate initial alignment for SINS

Atp13a5 Marker Reveals Pericyte Specification in the Mouse Central Nervous System.

Perivascular mural cells including vascular smooth cells (VSMCs) and pericytes are integral components of the vascular system. In the central nervous system (CNS), pericytes are also indispensable for the blood-brain barrier (BBB), blood-spinal cord barrier, and blood-retinal barrier and play key roles in maintaining cerebrovascular and neuronal functions. However, the functional specifications of pericytes between CNS and peripheral organs have not been resolved at the genetic and molecular levels. Hence, the generation of reliable CNS pericyte-specific models and genetic tools remains very challenging. Here, we report a new CNS pericyte marker in mice. This putative cation-transporting ATPase 13A5 ( Atp13a5) marker was identified through single-cell transcriptomics, based on its specificity to brain pericytes. We further generated a knock-in model with both tdTomato reporter and Cre recombinase. Using this model to trace the distribution of Atp13a5-positive pericytes in mice, we found that the tdTomato reporter reliably labels the CNS pericytes, including the ones in spinal cord and retina but not peripheral organs. Interestingly, brain pericytes are likely shaped by the developing neural environment, as Atp13a5-positive pericytes start to appear around murine embryonic day 15 (E15) and expand along the cerebrovasculature. Thus, Atp13a5 is a specific marker of CNS pericyte lineage, and this Atp13a5-based model is a reliable tool to explore the heterogeneity of pericytes and BBB functions in health and diseases. </p

Association of sleep duration and sleep quality with the risk of metabolic syndrome in adults: a systematic review and meta-analysis

Introduction: The association between sleep duration and metabolic syndrome (MetS) remains controversial, and few have considered the effects of sleep quality. We performed a meta-analysis to clarify the relationship of sleep duration and sleep quality with the risk of MetS. Material and methods: We conducted a systematic and comprehensive literature search of electronic databases from inception to 17 February 2022. The effect sizes of covariates from each study were pooled using a random or fixed model, and a restricted cubic spline random-effects meta-analysis was performed to examine the dose-response relationship between sleep duration and MetS. Results: A total of 62 studies were included in this meta-analysis. Compared to normal sleep duration, short sleep duration [odds ratio (OR) = 1.14, 95% confidence interval (CI): 1.10–1.19] and long sleep duration (OR = 1.15, 95% CI: 1.09–1.23) were associated with an increased risk of MetS. The restricted cubic spline analysis indicated that sleep durations of 8.5 h (OR = 0.95, 95% CI: 0.92–0.97) and 11 h (OR = 1.58, 95% CI: 1.31–1.91) were significantly associated with the risk of MetS. The pooled results showed that poor sleep quality (OR = 1.46, 95% CI: 1.03–2.06) and sleep complaints had significant positive associations with MetS. Conclusion: Our results demonstrated that short sleep duration increased the risk of developing MetS. Long sleep duration was also associated with MetS, especially for 11 h. 8.5 h can be considered the recommended sleep duration for MetS. Poor sleep quality and sleep complaints were also associated with MetS

New perspectives on microbiome and nutrient sequestration in soil aggregates during long-term grazing exclusion

15 páginas.- 5 figuras.- referencias.-Grazing exclusion alters grassland soil aggregation, microbiome composition, and biogeochemical processes. However, the long-term effects of grazing exclusion on the microbial communities and nutrient dynamics within soil aggregates remain unclear. We conducted a 36-year exclusion experiment to investigate how grazing exclusion affects the soil microbial community and the associated soil functions within soil aggregates in a semiarid grassland. Long-term (36 years) grazing exclusion induced a shift in microbial communities, especially in the 2 mm aggregates, and reduced carbon (C) sequestration potential thus revealing a negative impact of long-term GE. In contrast, 11–26 years of grazing exclusion greatly increased C sequestration and promoted nutrient cycling in soil aggregates and associated microbial functional genes. Moreover, the environmental characteristics of microhabitats (e.g., soil pH) altered the soil microbiome and strongly contributed to C sequestration. Our findings reveal new evidence from soil microbiology for optimizing grazing exclusion duration to maintain multiple belowground ecosystem functions, providing promising suggestions for climate-smart and resource-efficient grasslands.This work was financially supported by the National Natural Science Foundation of China (32061123007, 41977031), the Strategic Priority Research Program of Chinese Academy of Sciences (XDB40020202), and the Natural Science Foundation of Hubei Province, China (2020CFA013). Manuel Delgado-Baquerizo acknowledges support from the Spanish Ministry of Science and Innovation for the I+D+i project PID2020-115813RA-I00 and TED2021-130908B-C41 funded by MCIN/AEI/10.13039/501100011033.Peer reviewe

Ecoenzymatic stoichiometry reveals widespread soil phosphorus limitation to microbial metabolism across Chinese forests

8 páginas.- 4 figuras.- 57 referencias.- Supplementary information The online version contains supplementary material available at https://doi.org/10.1038/s43247-022-00523-5Forest soils contain a large amount of organic carbon and contribute to terrestrial carbon sequestration. However, we still have a poor understanding of what nutrients limit soil microbial metabolism that drives soil carbon release across the range of boreal to tropical forests. Here we used ecoenzymatic stoichiometry methods to investigate the patterns of microbial nutrient limitations within soil profiles (organic, eluvial and parent material horizons) across 181 forest sites throughout China. Results show that, in 80% of these forests, soil microbes were limited by phosphorus availability. Microbial phosphorus limitation increased with soil depth and from boreal to tropical forests as ecosystems become wetter, warmer, more productive, and is affected by anthropogenic nitrogen deposition. We also observed an unexpected shift in the latitudinal pattern of microbial phosphorus limitation with the lowest phosphorus limitation in the warm temperate zone (41-42 degrees N). Our study highlights the importance of soil phosphorus limitation to restoring forests and predicting their carbon sinks. Phosphorus limitation of soil microbial communities in forests is widespread, increases with soil depth, and is enhanced under wetter and warmer climates and elevated anthropogenic nitrogen deposition, according to ecoenzymatic stoichiometric analyses across 181 forests in China.This study was financially supported by the Strategic Priority Research Program of Chinese Academy of Sciences (XDB40000000), Funds for International Cooperation and Exchange of National Natural Science Foundation of China (32061123007), National Natural Science Foundation of China (41977031), Program of State Key Laboratory of Loess and Quaternary Geology CAS (SKLLQGZR1803). Contributions from Dr. Chen are funded by H2020 Marie Skłodowska-Curie Actions (No. 839806). M.D.-B. acknowledges support from the Spanish Ministry of Science and Innovation for the I+D+i project PID2020-115813RA-I00 funded by CIN/AEI/10.13039/501100011033. M.D.-B. is also supported by a project of the Fondo Europeo de Desarrollo Regional (FEDER) and the Consejería de Transformación Económica, Industria, Conocimiento y Universidades of the Junta de Andalucía (FEDER Andalucía 2014-2020 Objetivo temático “01–Refuerzo de la investigación, el desarrollo tecnológico y la innovación”) associated with the research project P20_00879 (ANDABIOMA).Peer reviewe

Fatigue Damage of V-Lock Chain Ring Under Random Load

To study the influence of the random load on the V-lock chain ring for mining, the numerical simulation technology is used. The dynamic tension is obtained by using the dynamic model of the plough. The life and damage nephograms are obtained by using ANSYS Workbench. The analysis results show that the short fatigue life region of the V-lock chain ring for mining is mainly concentrated on the transition region between the medial straight edge and arc, and the fatigue damage of the link chain on the side of the motion direction of the plow head is larger than that on the other side. This link chain has strong anti-fatigue performance

A Neurocomputational Model of Figure-Ground Discrimination by Relative Motion

. A neurocomputational model is presented for figure-ground discrimination by relative motion. In the model, the correlation type of elementary motion detectors (EMDs), an oscillatory neural network for motion perception and a selective attention module are involved. It is shown that through the oscillatory amplitude and frequency encoding and selective synchronization of phase oscillators, a perfectly camouflaged textured figure can be successfully discriminated from its identically textured background by relative motion alone. KEY WORDS: figure-ground discrimination, EMDs, oscillatory neural network (ONN), multilayer network of phase oscillators. 1 Introduction An object (&quot;figure&quot;) can, at least in principle, be discriminated from a textured background on the basis of differences in structure, texture, disparity, color, luminance and contrast. However, even if figure and ground do not differ in these features, they can also be separated when they move relatively to each other. Figu..

Effect of Wetting-Drying Cycle on the Deformation and Seepage Behaviors of Rock Masses around a Tunnel

Water inrush caused by the wetting-drying cycle is a difficult problem in tunnel excavation. To investigate the effect of the wetting-drying cycle on the stability of the tunnel surrounding rock, physical experiments and numerical simulations regarding the process of tunnel excavation with different wetting-drying cycle numbers were performed in this study. The evolutions of stress, displacement, and pore water pressure were analyzed. With the increase in cycle number, the pore water pressure, vertical stress, and top-bottom approach of the tunnel surrounding rock increase gradually. And the increasing process could be divided into three stages: slightly increasing stage, slowly increasing stage, and sharply increasing stage, respectively. The failure process of the surrounding rock under the wetting-drying cycle gradually occurs from the roof to side wall, while the baseplate changes slightly. The simulation results showed that the maximum principal stress in the surrounding rock mass of the tunnel increases, while the minimum principal stress decreases. Furthermore, the displacement of the rock mass decreases gradually with the increasing distance from the tunnel surface. By comparing the simulation results with the experimental results, well consistency is shown. The results in this study can provide helpful references for the safe excavation and scientific design of a tunnel under the wetting-drying cycle

Geospatial Object Detection in High Resolution Satellite Images Based on Multi-Scale Convolutional Neural Network

Daily acquisition of large amounts of aerial and satellite images has facilitated subsequent automatic interpretations of these images. One such interpretation is object detection. Despite the great progress made in this domain, the detection of multi-scale objects, especially small objects in high resolution satellite (HRS) images, has not been adequately explored. As a result, the detection performance turns out to be poor. To address this problem, we first propose a unified multi-scale convolutional neural network (CNN) for geospatial object detection in HRS images. It consists of a multi-scale object proposal network and a multi-scale object detection network, both of which share a multi-scale base network. The base network can produce feature maps with different receptive fields to be responsible for objects with different scales. Then, we use the multi-scale object proposal network to generate high quality object proposals from the feature maps. Finally, we use these object proposals with the multi-scale object detection network to train a good object detector. Comprehensive evaluations on a publicly available remote sensing object detection dataset and comparisons with several state-of-the-art approaches demonstrate the effectiveness of the presented method. The proposed method achieves the best mean average precision (mAP) value of 89.6%, runs at 10 frames per second (FPS) on a GTX 1080Ti GPU