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Additional file 1: Fig. S1. Socioeconomic drivers influencing the prevalence of TB and their proxy variables. Fig. S2. Geotree of TB incidence. Note: The first branches, the second trunks and the leaves represent country types, country development stages and countries, respectively. Table S1. Countries (173 countries and regions) belong to type I to IV. Table S2. Indicators of country development stages in 173 countries and territories in 2010 and 2019. Table S3. Countries belong to development stage 1 to 5 in 2010. Table S4. Countries belong to development stage 1 to 5 in 2019.

Additional file 2: Table S1. Incidence of tuberculosis (per 10,0000 population) in 173 countries and territories in 2030. Note: A negative value represents the elimination of tuberculosis.

Spatial statistics is dominated by spatial autocorrelation (SAC) based Kriging and BHM, and spatial local heterogeneity based hotspots and geographical regression methods, appraised as the first and second laws of Geography (Tobler 1970; Goodchild 2004), respectively. Spatial stratified heterogeneity (SSH), the phenomena of a partition that within strata is more similar than between strata, examples are climate zones and landuse classes and remote sensing classification, is prevalent in geography and understood since ancient Greek, is surprisingly neglected in Spatial Statistics, probably due to the existence of hundreds of classification algorithms. In this article, we go beyond the classifications and disclose that SSH is the sources of sample bias, statistic bias, modelling confounding and misleading CI, and recommend robust solutions to overcome the negativity. In the meantime, we elaborate four benefits from SSH: creating identical PDF or equivalent to random sampling in stratum; the spatial pattern in strata, the borders between strata as a specific information for nonlinear causation; and general interaction by overlaying two spatial patterns. We developed the equation of SSH and discuss its context. The comprehensive investigation formulates the statistics for SSH, presenting a new principle and toolbox in spatial statistics.

Train travel is a common mode of public transport across the globe; however, the risk of coronavirus disease 2019 (COVID-19) transmission among individual train passengers remains unclear.We quantified the transmission risk of COVID-19 on high-speed train passengers using data from 2334 index patients and 72 093 close contacts who had co-travel times of 0-8 hours from 19 December 2019 through 6 March 2020 in China. We analyzed the spatial and temporal distribution of COVID-19 transmission among train passengers to elucidate the associations between infection, spatial distance, and co-travel time.The attack rate in train passengers on seats within a distance of 3 rows and 5 columns of the index patient varied from 0 to 10.3% (95% confidence interval [CI], 5.3%-19.0%), with a mean of 0.32% (95% CI, .29%-.37%). Passengers in seats on the same row (including the adjacent passengers to the index patient) as the index patient had an average attack rate of 1.5% (95% CI, 1.3%-1.8%), higher than that in other rows (0.14% [95% CI, .11%-.17%]), with a relative risk (RR) of 11.2 (95% CI, 8.6-14.6). Travelers adjacent to the index patient had the highest attack rate (3.5% [95% CI, 2.9%-4.3%]) of COVID-19 infection (RR, 18.0 [95% CI, 13.9-23.4]) among all seats. The attack rate decreased with increasing distance, but increased with increasing co-travel time. The attack rate increased on average by 0.15% (P = .005) per hour of co-travel; for passengers in adjacent seats, this increase was 1.3% (P = .008), the highest among all seats considered.COVID-19 has a high transmission risk among train passengers, but this risk shows significant differences with co-travel time and seat location. During disease outbreaks, when traveling on public transportation in confined spaces such as trains, measures should be taken to reduce the risk of transmission, including increasing seat distance, reducing passenger density, and use of personal hygiene protection.

Metabolites have essential roles in microbial communities, including as mediators of nutrient and energy exchange, cell-to-cell communication, and antibiosis. However, detecting and quantifying metabolites and other chemicals in samples having extremes in salt or mineral content using liquid chromatography-mass spectrometry (LC-MS)-based methods remains a significant challenge. Here we report a facile method based on in situ chemical derivatization followed by extraction for analysis of metabolites and other chemicals in hypersaline samples, enabling for the first time direct LC-MS-based exo-metabolomics analysis in sample matrices containing up to 2 molar total dissolved salts. The method, MetFish, is applicable to molecules containing amine, carboxylic acid, carbonyl, or hydroxyl functional groups, and can be integrated into either targeted or untargeted analysis pipelines. In targeted analyses, MetFish provided limits of quantification as low as 1 nM, broad linear dynamic ranges (up to 5-6 orders of magnitude) with excellent linearity, and low median inter-day reproducibility (e.g. 2.6%). MetFish was successfully applied in targeted and untargeted exo-metabolomics analyses of microbial consortia, quantifying amino acid dynamics in the exo-metabolome during community succession; in situ in a native prairie soil, whose exo-metabolome was isolated using a hypersaline extraction; and in input and produced fluids from a hydraulically fractured well, identifying dramatic changes in the exo-metabolome over time in the well.

The geographical extent, magnitude, and uncertainty of global climate change have been widely discussed and have critical policy implications at both global and local scales. In this study, a new analysis of annual mean global land surface air temperature since 1880 was generated, which has greater coverage and lower uncertainty than previous distributions. The Biased Sentinel Hospitals Areal Disease Estimation (BSHADE) method, used in this study, makes a best linear unbiased estimation (BLUE) when a sample is small and biased to a spatially heterogeneous population. For the period of 1901–2010, the warming trend was found to be 0.109 °C decade−1 with 95% confidence intervals between 0.081 °C and 0.137 °C. Additionally, warming exhibited different spatial patterns in different periods. In the early 20th century (1923–1950), warming occurred mainly in the mid-high latitudes of the Northern Hemisphere, whereas in the most recent decades (1977–2014), warming was more spatially extensive across the global land surface. Compared with other common methods, the difference in results appears in the areas with few stations and in the early years, when stations had sparse coverage and were unevenly distributed. Validation, which was performed using real data that simulated the historic situation, showed a smaller error in the BSHADE estimate than in other methods. This study produced a new database with greater coverage and less uncertainty that will improve the understanding of climate dynamics on the Earth since 1880, especially in isolated areas and early periods, and will benefit the assessment of climate-change-related issues, such as the effects of human activities.

The satellite signals are always blocked by obstructions in urban canyons, therefore multi-constellation global navigation satellite system (GNSS) performs poor. Quantitative comparison of the performance of different satellite navigation systems can provide a basis to analyze their advantages and disadvantages. This paper proposes a fuzzy comprehensive evaluation (FCE) theory to quantitatively evaluate the performance of GNSS, and systematically puts forward how to quantitatively analyze precision, availability, continuity and integrity. A simulation was conducted to emulate the environment of urban canyons. Evaluation results show the performance of BDS is neck and neck with GPS, and much better than GLONASS. A multisystem has better performance than a single system. GPS+GLONASS+BDS has the best performance and gets a high FCE result of 0.3268, while the FCE result of GPS, BDS and GLONASS are 0.1722, 0.1570 and 0.0970 respectively.

To solve the problem of the least squares estimation does not have the ability to resist the gross errors in global navigation satellite system (GNSS), the theory of robust least squares estimation is introduced, three methods (Huber, IGG, IGGIII) to construct the equivalent weight are expounded and the determination of initial parameter of the equivalent weight is discussed. The results of simulation based on GPS/BDS multi-constellation show that the robust least squares estimation can ensure the accuracy of navigation and positioning effectively, the estimator with IGGIII equivalent weight method presents optimal solutions, furthermore the performance of the robust estimation method based on median parameter estimate is better than the individual robust estimation.

To realize reasonable design task modeling and high efficiency task collaboration and allocation in complicated design process, a design task model based granular space is proposed, and cross-stage collaboration mode and task allocation method are discussed. Firstly, combining study results of Collaboration design and Cloud Manufacturing (CMfg), four dimension granular space of design task is defined and a general design task model is built. Secondly, cross-stage collaboration mode based task in distributed network environment is proposed. And then, design task allocation methods on both cross-stage synergy and single stage synergy are introduced. Finally, application prototype system is illustrated. Application results show that deign task model and task allocation in the multi-task collaboration mode are feasible. Keywords-Granular Space;Design Task Modeling;Virtual Design Unit (VDU); Cross-stage Collaboration;Task Allocation

Let the fracture event be a fuzzy event. It seems that between the fracture region and the safe region there is a fuzzy region. In the fuzzy region the structure will be either fractured or safe. Through the membership function, the fracture possibility of each point in the fuzzy region is determined. By using Monte-Carlo simulation, Edgeworth's series and the advanced first-order second-moment method, the fuzzy fracture probability of a spherical tank is determined in this paper.

Urbanization is one of the most concerned trends in the world. But until now, the impacts of urbanization on the spatial patterns of alien plants remain little known. In this paper, the impacts of urbanization on the spatial patterns of alien plants in Yunnan were investigated. The results indicated that urban population, transportation mileage and their density all significantly correlated with spatial pattern of species diversity of alien plants. There were significant correlations between proportions of alien plants among all plant species and transportation density, urban population density. Step-wised regression analysis showed that transportation density played stronger roles in the spreading of alien species. Urbanization may not only shape the spatial patterns of alien plant diversity but also that of local plant composition. With the explosive development of urbanization in the study area, we should premeditate the potential of spreading or invasion of alien plants.

The dynamic characteristics of missile vary substantially with flight conditions such as flight Mach number, altitude and angle of attack. Therefore, in order to achieve adequate levels of robustness and performance, a controller that also varies during operation has to be designed in missile control. This paper is concerned with the application of advanced mixed linear parameter-varying (LPV)/\mu techniques to global control of a missile. The techniques can produce an H \infty based LPV controller, which is automatically "gain scheduled" with respect to the flight conditions and adapts to the variation of the missil'se dynamic characteristics. The power and effectiveness of the resulting controller are demonstrated by nonlinear simulations.

A mixed linear parameter-varying (LPV)/μ technique is applied to global control of an air defense missile. The technique is a direct extension of μ-synthesis that additionally incorporates the gain-scheduling task and makes the time-varying nature of the plant be explicitly taken into account. By use of the technique, an LPV controller is designed based on a model matching control structure. The controller is automatically "gain scheduled" with respect to the flight Mach number and altitude and therefore adapts to the variation of the missile's dynamic characteristics. The power and effectiveness of the resulting controller to handle the global robustness and performance of the missile over its entire operation range are verified by nonlinear simulations. The research results appear to be sufficiently promising to warrant further study of this approach for applications to missile control.