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The signal blockage and multipath effects of the Global Navigation Satellite System (GNSS) caused by urban canyon scenarios have brought great technical challenges to the positioning and navigation of autonomous vehicles. In this paper, an improved factor graph optimization algorithm enhanced by a resilient noise model is proposed. The measurement noise is resilient and adjusted based on an approximate Gaussian distribution-based estimation. In estimating and adjusting the noise parameters of the measurement model, the error covariance matrix of the multi-sensor fusion positioning system is dynamically optimized to improve the system accuracy. Firstly, according to the approximate Gaussian statistical property of the GNSS/odometer velocity residual sequence, the measured data are divided into an approximate Gaussian fitting region and an approximate Gaussian convergence region. Secondly, the interval is divided according to the measured data, and the corresponding variational Bayesian network and Gaussian mixture model are used to estimate the innovation online. Further, the noise covariance matrix of the adaptive factor graph-based model is dynamically optimized using the estimated noise parameters. Finally, based on low-cost inertial navigation equipment, GNSS, odometer, and vision, the algorithm is implemented and verified using a simulation platform and real-vehicle road test. The experimental results show that in a complex urban road environment, compared with the traditional factor graph fusion localization algorithm, the maximum improvement in accuracy of the proposed algorithm can reach 65.63%, 39.52%, and 42.95% for heading, position, and velocity, respectively.

Fluid flow around the sphere is widely used in industrial systems, in which the hydrodynamic and heat transfer performances play a key role in energy consumption. The flow and heat transfer characteristics around the sphere are greatly dependent on the shedding and development of vortices. In the present paper, the fluid flow and heat transfer around the smooth sphere are investigated with the LES method. The results show that along the flow direction, the leeward region of the sphere alternately produces up and down-shedding vortices. Vortex shedding causes local pressure changes, resulting in changes in flow and heat transfer performance. The Cd, CL, and Nu fluctuate around a stable value. The frequency and amplitude of the fluctuation increase significantly as the inlet flow rate increases. Especially, the maximum changes in Cd are 6.26 % and 22.79 % when Q = 1 and 6 m3/h. The frequency of vortex shedding increases by about 2.6 times when the flow rate increases from 2 m3/h to 5 m3/h. In addition, the vortex shedding from the leeward region moves downstream with more energy due to the increase in frequency, which leads to more cold fluid participating in heat transfer.

Considering that laser scan stations are expensive and heavy for the indoor environment reconstruction of unmanned systems, a low-cost and light reconstruction system is proposed in this research. The system consists of a cross-structured light visual (SLV) sensor and an inertial navigation system (INS). The cross-SLV sensor is used to scan the surroundings and to estimate the angle change between two adjacent measurements. To improve the robustness and accuracy of the angle measurement, a Kalman Filter (KF) with simple construction is designed to fuse the inertial information from the INS. The factors which influence ranging accuracy are analyzed and ranging experiments show that the SLV sensor has an accuracy of higher than 2% when the distance is less than 4 m. Then the reconstruction results of a kitchen and corridor show that the error of most points is less than 50 mm for either kitchen (94%) or corridor (85%), and the mean errors and standard deviations of kitchen and corridor are less than 20 mm and 30 mm, respectively.

The effective identification and mitigation of non-line-of-sight (NLOS) ranging errors are essential for achieving high-precision positioning and navigation with ultra-wideband (UWB) technology in harsh indoor environments. In this paper, an efficient UWB ranging-error mitigation strategy that uses novel channel impulse response parameters based on the results of a two-step NLOS identification, composed of a decision tree and feedforward neural network, is proposed to realize indoor locations. NLOS ranging errors are classified into three types, and corresponding mitigation strategies and recall mechanisms are developed, which are also extended to partial line-of-sight (LOS) errors. Extensive experiments involving three obstacles (humans, walls, and glass) and two sites show an average NLOS identification accuracy of 95.05%, with LOS/NLOS recall rates of 95.72%/94.15%. The mitigated LOS errors are reduced by 50.4%, while the average improvement in the accuracy of the three types of NLOS ranging errors is 61.8%, reaching up to 76.84%. Overall, this method achieves a reduction in LOS and NLOS ranging errors of 25.19% and 69.85%, respectively, resulting in a 54.46% enhancement in positioning accuracy. This performance surpasses that of state-of-the-art techniques, such as the convolutional neural network (CNN), long short-term memory–extended Kalman filter (LSTM-EKF), least-squares–support vector machine (LS-SVM), and k-nearest neighbor (K-NN) algorithms.

Micro-Electro-Mechanical System (MEMS) inertial sensors, characterized by their small size, low cost, and low power consumption, are commonly used in foot-mounted wearable pedestrian autonomous positioning systems. However, they also have drawbacks such as heading drift and poor repeatability. To address these issues, this paper proposes an improved pedestrian autonomous 3D positioning algorithm based on dual-foot motion characteristic constraints. Two sets of small-sized Inertial Measurement Units (IMU) are worn on the left and right feet of pedestrians to form an autonomous positioning system, each integrated with low-cost, low-power micro-inertial sensor chips. On the one hand, an improved adaptive zero-velocity detection algorithm is employed to enhance discrimination accuracy under different step-speed conditions. On the other hand, considering the dual-foot gait characteristics and the height difference feature during stair ascent and descent, horizontal position update algorithms based on dual-foot motion trajectory constraints and height update algorithms based on dual-foot height differences are, respectively, designed. These algorithms aim to re-correct the pedestrian position information updated at zero velocity in both horizontal and vertical directions. The experimental results indicate that in a laboratory environment, the 3D positioning error is reduced by 93.9% compared to unconstrained conditions. Simultaneously, the proposed approach enhances the accuracy, continuity, and repeatability of the foot-mounted IMU positioning system without the need for additional power consumption.

Abstract Background With increasing urbanization in developing countries, sanitation workers are frequently involved in road traffic collisions. Our purpose was to study specific collisions involving sanitation workers and provide decision-making suggestions and reference measures for the sanitation industry and urban managers to reduce the occurrence of collisions. Methods We obtained online news data about sanitation worker road traffic collisions in China between 2013 and 2017 and analyzed occurrence time and location, victim characteristics, and causes of collisions. Results In China, between 2013 and 2017, 511 road traffic collisions were reported, with the fewest in February and July. Most occurred around 5:00 a.m. in Eastern regions and in urban areas. Victims were mainly over 50 years old, with more females than males. Collisions usually resulted in death at the scene. The ambiguity of laws, the exploitation of workers through industry outsourcing, and the difficulty of processing claims may be the main factors preventing victims from obtaining legal compensation. Conclusions The most common cause of collisions was drivers’ speeding, but workers also regularly risk death by crossing the road in pursuit of their duties. The absence of legal controls for environmental protection, the excessive pursuit of efficiency in urban governance, and the lack of basic education of sanitation workers are underlying causes of collisions. Raising awareness about sanitation worker road traffic collisions will help protect the work safety rights of this vulnerable group.

Moving packed bed heat exchanger has been key equipment in the waste energy recovery and concentrated solar power. However, the effect of tube arrangement still deserve investigation to optimize heat transfer. In the present paper, the flow and heat transfer of gravity-driven particles flowing around the tube bank are numerically studied by the discrete element method. It was found that the stagnation zone of the staggered tubes is less than 45° and the cavity zone is in the range of 160° - 180°. The stagnation zone of the aligned tubes is in the range of 0° - 65° and 125° - 180°, and there is no cavity zone below the aligned tubes. The heat transfer performance of the staggered tubes is better than that of the aligned tubes. The best heat transfer region of the staggered tubes is at the top of the tube, and that of the aligned tubes is at the side of the tube. The bottom of the tube has the worst heat transfer in both the staggered and aligned tubes. It is necessary to improve the performance of the staggered tubes by optimizing the particle flow in the range 0° - 45° and 160° - 180°. Reducing the vertical tube spacing may be an effective option for the aligned tubes.

Abstract Background To evaluate the impact of a restricted access policy on workplace violence in a healthcare setting. Methods We surveyed healthcare workers before and after the implementation of a restricted-access policy at a tertiary hospital in north-eastern China. Data were collected in April 2017 and January 2019. Fisher’s exact test were used to compare the difference in workplace violence prevalence between responses to two surveys. Survey 1 (S1) collected data from 345 healthcare professionals who had worked in the inpatient ward for at least 12 months. Survey 2 (S2) included 338 healthcare workers from the same ward who had been employed for more than two years. The effective response rates for the two studies was 79.31 and 83.25%, respectively. All 18 female security guards were included in the investigation in S2. Results The prevalence of psychological violence was 62.03% in S1 and 34.62% in S2, the difference in prevalence showing statistical significance (P = 0.000), while the prevalence of physical violence was 3.77 and 4.73% respectively, showing no statistical significance (P = 0.573). The change in the rate of injury caused by physical violence was also statistically significant at 76.92 and 31.25% (P = 0.025), respectively. Security guards were at high risk of workplace violence under the policy. Most healthcare professionals thought this policy ameliorated treatment order, the sense of security, anxiety about workplace violence, and so forth, but one-third of the respondents thought that it caused patient dissatisfaction. Conclusion While the restricted access policy may be effective for healthcare professionals in avoiding or dealing with violence, such policy could contribute to new problems regarding the safety of security guards and the potential dissatisfaction of patients. The policy should be further developed to alleviate this phenomenon.

Abstract Purpose Physicians and Standardised Residency Training physicians (SRTPs) have relatively high exposure to psychological violence. Its adverse effects are far greater than those of physical violence. However, no previous research has paid attention to the problem of psychological violence among them. This study aims to evaluate the extent, characteristics, and risk factors of psychological violence among SRTPs in comparison to physicians, and also to highlight the psychological violence experienced by SRTPs and suggest preventive measures. Methods A cross-sectional survey was conducted in northern China. 884 physicians and 537 SRTPs completed a questionnaire which compiled by the ILO, ICN, WHO and PSI in 2003 to measure violence in the workplace. Descriptive statistics and logistic regression analysis were used to analyse results. Results The effective response rates of physicians and SRTPs were 63.1%(884/1400) and 86.3%(537/622) respectively. 73.0%(645/884) of physicians and 24.8%(133/537) of SRTPs suffered psychological violence in the past year. Compared to physicians (29/645, 4.5%), SRTPs (42/133, 31.6%) experience more internal violence. Further, after experiencing psychological violence, physicians are willing to talk to family and friends, but SRTPs generally take no action. Shift work was a risk factor for both physicians (OR 1.440, 95% CI 1.014–2.203) and SRTPs (OR 1.851, 95% CI 1.217–2.815) suffering from psychological violence. In contrast, no anxiety symptoms protected physicians (OR 0.406, 95% CI 0.209–0.789) and SRTPs (OR 0.404, 95% CI 0.170–0.959) against psychological violence. Conclusions SRTPs and physicians in northern China have a high risk of experiencing psychological violence, and physicians experience more. Meanwhile, there are obvious differences in responses to psychological violence and risk factors between them. Therefore, medical institutions should pay more attention to psychological violence, especially among SRTPs, such as supporting the reporting of psychological violence, strengthening team relationships, and providing psychological comfort and counselling. Trial registration number (Project Identification Code: HMUIRB20160014), Registered May 10, 2016.

Abstract Background The Coronavirus Disease 2019 (COVID-19) that first occurred in Wuhan, China, is currently spreading throughout China. The majority of infected patients either traveled to Wuhan or came into contact with an infected person from Wuhan. Investigating members of the public with a travel history to Wuhan became the primary focus of the Chinese government’s epidemic prevention and control measures, but several instances of withheld histories were uncovered as localized clusters of infections broke out. This study investigated the public’s willingness and beliefs associated with reporting travel history to high-risk epidemic regions, to provide effective suggestions and measures for encouraging travel reporting. Methods A cross-sectional study was conducted online between February 12 and 19, 2020. Descriptive analysis, chi-squared test, and Fisher’s exact test were used to identify socio-demographic factors and beliefs associated with reporting, as well as their impact on the willingness to report on travel history to high-risk epidemic regions. Results Of the 1344 respondents, 91 (6.77%) expressed an inclination to deliberately withhold travel history. Those who understood the benefits of reporting and the legal consequences for deliberately withholding information, showed greater willingness to report their history (P

In Wi-Fi fingerprint positioning, what we should most care about is the distance relationship between the user and the reference points (RP). However, most of the existing weighted k-nearest neighbor (WKNN) algorithms use the Euclidean distance of received signal strengths (RSS) as distance measure for fingerprint matching, and the RSS Euclidean distance is not consistent with the position distance. To address this issue, this paper analyzes the relationship between RSS similarity and position distance, propose a novel WKNN based on signal similarity and spatial position. Firstly, we obtain the weighted Euclidean distance (WED) by balancing the size between the RSS difference and the signal propagation distance difference according to the attenuation law of the spatial signal. Then, we obtain the approximate position distance (APD) by making full use of the position distances and WEDs between RPs. Finally, the nearest RPs can be selected more accurately based on the APDs between the user and different RPs, and the position of user can be estimated by the proposed WKNN based on the APD (APD-WKNN) algorithm. In order to fully evaluate the proposed algorithm, we use three fingerprint databases for comparison experiments with eight fingerprint positioning algorithms. The results show that the proposed algorithm can significantly improve the positioning accuracy of WKNN algorithm.

Aiming at the problems of the low robustness and poor reliability of a single positioning source in complex indoor environments, a multi-level fusion indoor positioning technology considering credible evaluation is proposed. A multi-dimensional electromagnetic atlas including pseudolites (PL), Wi-Fi and a geomagnetic field is constructed, and the unsupervised learning model is used to sample in the latent space to achieve a feature-level fusion positioning. A location credibility evaluation method is designed to improve the credibility of the positioning system through a multi-dimensional data quality evaluation and heterogeneous information auxiliary constraints. Finally, a large number of experiments were carried out in the laboratory environment, and, finally, about 90% of the positioning error was better than 1 m, and the average positioning error was 0.56 m. Compared with several relatively advanced positioning methods (Inter-satellite CPDM/Epoch-CPDS/Z-KPI) at present, the average positioning accuracy is improved by about 56%, 83.5% and 82.9%, respectively, which verifies the effectiveness of the algorithm. To verify the effect of the proposed method in a practical application environment, the proposed positioning system is deployed in the 2022 Winter Olympics venues. The results show that the proposed method has a significant improvement in the positioning accuracy and continuity.

ObjectivesThis study aims to investigate patient safety culture in secondary hospitals of Heilongjiang, Northeast China, and explore the implications of patient safety culture and practices through the perspectives of various healthcare workers.MethodsA cross-sectional survey using the Safety Attitude Questionnaire (SAQ) was conducted to ascertain the status of patient safety culture in nine secondary hospitals across the six dimensions of the SAQ. Among the 900 staff members who were invited to participate, 665 completed the questionnaire. Descriptive statistics were used to calculate the general means and standard deviations of the patient safety culture dimensions and other numerical variables, and F-test and a multivariate regression analysis were used to statistically analyze the differences in perceptions of safety culture considering the differences in demographic characteristics. All statistical analyses were performed using SPSS v. 22.0.ResultsThe respondents rated job satisfaction as the highest among all six dimensions of the SAQ, followed in order by teamwork climate, working conditions, and stress recognition (the lowest). There were significant differences among the dimensions of patient safety culture and other factors, such as gender, age, job position, and education. Compared with previous studies, teamwork climate and working conditions scores were quite high, while stress recognition score was very low. We also found differences in patient safety culture by demographic characteristics.ConclusionsThe findings revealed the patient safety culture attitudes of healthcare workers in secondary hospitals of Heilongjiang, and provided baseline data for related future research. This evidence may also help government health policymakers and hospital administrators understand related challenges and develop strategies to improve patient safety culture in secondary hospitals of China and perhaps also in other developing countries.

This paper presents an evaluation of real-time kinematic (RTK)/Pseudolite/landmarks assistance heuristic drift elimination (LAHDE)/inertial measurement unit-based personal dead reckoning systems (IMU-PDR) integrated pedestrian navigation system for urban and indoor environments. Real-time kinematic (RTK) technique is widely used for high-precision positioning and can provide periodic correction to inertial measurement unit (IMU)-based personal dead reckoning systems (PDR) outdoors. However, indoors, where global positioning system (GPS) signals are not available, RTK fails to achieve high-precision positioning. Pseudolite can provide satellite-like navigation signals for user receivers to achieve positioning in indoor environments. However, there are some problems in pseudolite positioning field, such as complex multipath effect in indoor environments and integer ambiguity of carrier phase. In order to avoid the limitation of these factors, a local search method based on carrier phase difference with the assistance of IMU-PDR is proposed in this paper, which can achieve higher positioning accuracy. Besides, heuristic drift elimination algorithm with the assistance of manmade landmarks (LAHDE) is introduced to eliminate the accumulated error in headings derived by IMU-PDR in indoor corridors. An algorithm verification system was developed to carry out real experiments in a cooperation scene. Results show that, although the proposed pedestrian navigation system has to use human behavior to switch the positioning algorithm according to different scenarios, it is still effective in controlling the IMU-PDR drift error in multiscenarios including outdoor, indoor corridor, and indoor room for different people.

As pedestrian dead-reckoning (PDR), based on foot-mounted inertial sensors, suffers from accumulated error in velocity and heading, an improved heuristic drift elimination (iHDE) with a zero-velocity update (ZUPT) algorithm was proposed for simultaneously reducing the error in heading and velocity in complex paths, i.e., with pathways oriented at 45°, curved corridors, and wide areas. However, the iHDE algorithm does not consider the changes in pedestrian movement modes, and it can deteriorate when a pedestrian walks along a straight path without a pre-defined dominant direction. To solve these two problems, we propose enhanced heuristic drift elimination (eHDE) with an adaptive zero-velocity update (AZUPT) algorithm and novel heading correction algorithm. The relationships between the magnitude peaks of the y-axis angular rate and the detection thresholds were established only using the readings of the three-axis accelerometer and the three-axis gyroscopic, and a mechanism for constructing temporary dominant directions in real time was introduced. Real experiments were performed and the results showed that the proposed algorithm can improve the still-phase detection accuracy of a pedestrian at different movement motions and outperforms the iHDE algorithm in complex paths with many straight features.

As an essential component of future comprehensive Positioning, Navigation, and Timing (PNT) system, indoor positioning technology has extensive application demands, making it a focal point of attention in both academia and industry. This article comprehensively reviews the research status of indoor positioning technology in China, with a focus on highlighting representative achievements and application validations from major research institutions in recent years. It addresses the challenges and issues faced in promotion and application of large-scale, high-precision indoor positioning. Furthermore, a universal and seamless indoor-outdoor positioning system architecture is proposed, along with a technical roadmap and key technologies to achieve this architecture. Finally, an analysis and outlook on future technological trends are presented. [ABSTRACT FROM AUTHOR]

Abstract After thermal treatment, quail eggs pruduce an attractive flavor that is favored by consumers. In this study, the key aroma volatiles and their lipid precursors during thermal treatment were investigated by the electronic nose, GC-MS, GC-O-MS and UPLC-Q-Exactive HF-X. The results exhibited that the raw and fresh flavor of raw egg yolks came from 1-Octen-3-ol, 2-Ethyl-1-hexanol, 1-Decene, and 1-Undecene. 2-Methyl-3-octanone, Toluene, and some aromatic compounds worked synergistically to contribute to the aroma profile of boiled eggs. (+)-2-Bornanone, Octanal, 2-Methyl-butanal, Nonanal, (.+Dihydro-3-hydroxy-4,4-dimethyl-2(3 H)-furanone, 6,7-Dihydro-2,5-dimethyl-5 H-cyclopentapyrazine, (E)-2-methyl-6-(1-propenyl)-pyrazine, 2-Ethyl-3,5-dimethyl-pyrazine, 3,5-Diethyl-2-methyl-pyrazine, 2,5-Dimethyl-pyrazine were the key flavor compounds in the fried egg and gave it the popcorn and roasted flavors. The statistical analysis of the lipid profile revealed that brief, high-temperature heating (100 or 200 °C for 10 min) in typical boiled and fried quail eggs had minor effects on the lipid nutritional value. PE-related lipids, particularly those containing 18-carbon fatty acids, contributed to the aroma formation of fried quail eggs. Graphical Abstract

Satellite Interferometric Synthetic Aperture Radar (InSAR) is widely used for topographic, geological and natural resource investigations. However, most of the existing InSAR studies of ground deformation are based on relatively short periods and single sensors. This paper introduces a new multi-sensor InSAR time series data fusion method for time-overlapping and time-interval datasets, to address cases when partial overlaps and/or temporal gaps exist. A new Power Exponential Knothe Model (PEKM) fits and fuses overlaps in the deformation curves, while a Long Short-Term Memory (LSTM) neural network predicts and fuses any temporal gaps in the series. Taking the city of Wuhan (China) as experiment area, COSMO-SkyMed (2011–2015), TerraSAR-X (2015–2019) and Sentinel-1 (2019–2021) SAR datasets were fused to map long-term surface deformation over the last decade. An independent 2011–2020 InSAR time series analysis based on 230 COSMO-SkyMed scenes was also used as reference for comparison. The correlation coefficient between the results of the fusion algorithm and the reference data is 0.87 in the time overlapping region and 0.97 in the time-interval dataset. The correlation coefficient of the overall results is 0.78, which fully demonstrates that the algorithm proposed in our paper achieves a similar trend as the reference deformation curve. The experimental results are consistent with existing studies of surface deformation at Wuhan, demonstrating the accuracy of the proposed new fusion method to provide robust time series for the analysis of long-term land subsidence mechanisms.

ABSTRACTNowadays, the rapid development of hypersonic vehicles brings great challenges to the missile defense system. As achieving successful interception depends highly on terminal guidance laws, research on guidance laws for intercepting highly maneuvering targets has aroused increasing attention. Artificial intelligence technologies, such as deep reinforcement learning (DRL), have been widely applied to improve the performance of guidance laws. However, the existing DRL guidance laws rarely consider the partial observability problem of onboard sensors, resulting in the limitations of their engineering applications. In this paper, a deep recurrent reinforcement learning (DRRL)-based guidance method is investigated to address the intercept guidance problem against maneuvering targets under partial observability. The sequence consisting of previous state observations is utilized as the input of the policy network. A recurrent layer is introduced into the networks to extract hidden information behind the temporal sequence to support policy training. The guidance problem is formulated as a partially observable Markov decision process model, and then a range-weighted reward function that considers the line-of-sight rate and energy consumption is designed to guarantee convergence of policy training. The effectiveness of the proposed DRRL guidance law is validated by extensive numerical simulations.

Optical and Synthetic Aperture Radar (SAR) remote sensing has a long history of use and reached a good level of maturity in archaeological and cultural heritage applications, yet further advances are viable through the exploitation of novel sensor data and imaging modes, big data and high-performance computing, advanced and automated analysis methods. This paper showcases the main research avenues in this field, with a focus on archaeological prospection and heritage site protection. Six demonstration use-cases with a wealth of heritage asset types (e.g. excavated and still buried archaeological features, standing monuments, natural reserves, burial mounds, paleo-channels) and respective scientific research objectives are presented: the Ostia-Portus area and the wider Province of Rome (Italy), the city of Wuhan and the Jiuzhaigou National Park (China), and the Siberian “Valley of the Kings” (Russia). Input data encompass both archive and newly tasked medium to very high-resolution imagery acquired over the last decade from satellite (e.g. Copernicus Sentinels and ESA Third Party Missions) and aerial (e.g. Unmanned Aerial Vehicles, UAV) platforms, as well as field-based evidence and ground truth, auxiliary topographic data, Digital Elevation Models (DEM), and monitoring data from geodetic campaigns and networks. The novel results achieved for the use-cases contribute to the discussion on the advantages and limitations of optical and SAR-based archaeological and heritage applications aimed to detect buried and sub-surface archaeological assets across rural and semi-vegetated landscapes, identify threats to cultural heritage assets due to ground instability and urban development in large metropolises, and monitor post-disaster impacts in natural reserves.

Background Rat models are valuable tools to study the lung microbiota in diseases. Yet the impacts of different lung parts, young and mature adult stages, and the different batches of the same conditions on the healthy rat lung microbiome have not been investigated.Methods The rat lung microbiome was analyzed to clarify the lung part-dependent and age-dependent differences and to evaluate the effects of several ‘batch environmental factors’ on normal rats, after eliminating potential contamination.Results The results showed that the contamination could be identified and excluded. The lung microbiome from left and right lung parts was very similar so one representative part could be used in the microbiome study. There were significantly different lung microbial communities between the young and mature adult groups, and also between the different feeding batches groups of the same repetitive feeding conditions, but a common lung microbiota characterized by Firmicutes, Bacteroidetes, Proteobacteria, and Actinobacteria as the most dominant phyla were present in all adult rats. It indicated that the experiment under the same condition of the same rats batch was needed to compare the difference in the lung microbiota and repeated experiments were necessary to confirm the results.Conclusion These data represented that the lung bacterial communities were dynamic and rapidly susceptible to environmental influence, clustered strongly by age or different feeding batches but similar in the different lung tissue parts. This study improved the basic understanding of the potential effects on the lung microbiome of healthy rats.

This paper considers the problem of tracking a three-dimensional target under the condition that only a single two-dimensional radar is available. Since a two-dimensional radar can only measure the slant range and azimuth information relative to the target, an unobservability issue arises in this tracking application. Therefore, we first investigate the observability issue of tracking a three-dimensional target with a single two-dimensional radar from two perspectives, including intuitive illustration and quantitative analysis. From the perspective of intuitive illustration, we demonstrate “What is the unobservability issue” and “How does the relative target-radar geometry influence the observability of the tracking system”. From the perspective of quantitative analysis, we construct a novel observability metric for this special tracking problem. Second, aiming at improving tracking performance under the unobservability of target height, we propose an observability-based Gaussian sum cubature Kalman filter. Built within the Gaussian sum framework and based on the height-parameterized strategy, this novel algorithm uses a set of independent fifth-degree cubature Kalman filters, each of which can detect the system observability variation and enhance the tracking accuracy by using a Gaussian splitting scheme under low-degree observability. Finally, the effectiveness of the presented filtering algorithm is validated through lots of simulation experiments.