Objectives This study aimed to investigate the associations between individual-level SES, area-level SES, and their interaction with dementia in China. Methods This study used data from the Second China National Sample Survey on Disability and restricted our finalized analysis to 688,507 participants aged 50 years or older. Dementia was ascertained according to the International Statistical Classification of Diseases, Tenth Revision. Multilevel logistic regression models were fitted to examine the associations between individual-level SES, area-level SES, and their interaction with dementia. Results Participants with higher individual SES were less likely to develop dementia; the risk of dementia decreased by 18% for each standard deviation increase in individual SES (OR=0.82, 95% CI=0.77, 0.88). Advantaged areas were associated with an increased risk of dementia in Chinese adults by 1.52 (95% CI=1.43, 1.62). Analysis of the combination between individual-level SES and area-level SES revealed that as the level of area SES increased, the risk of dementia in lower SES people was significantly higher than in higher SES people (OR=1.09, 95% CI=1.04,1.14). Discussion This study found that people with lower SES living in high-SES areas had a higher risk of dementia than people with lower SES living in low-SES areas. Significant socioeconomic differences in the risk of dementia exist in China, and more attention should be given to low-SES populations living in high-SES areas.
Branched glycerol dialkyl glycerol tetraethers (brGDGTs) are membrane lipids of certain soil bacteria, and their relative distributions are used as a proxy for air temperature and soil pH. While temperature is recorded by the degree of methylation, soil pH is reflected by the amount of internal cyclization and the relative abundance of 6-methyl isomers. Since the exact producers of brGDGTs remain enigmatic, the mechanisms underlying their empirical relationships with temperature and soil pH, and thus the reliability of brGDGT-based paleorecords, are not well understood, especially in arid regions where mean annual precipitation (MAP) is less than 500 mm. Here, we evaluate the influence of soil pH and aridity on brGDGT distributions in grassland soils along an aridity transect (MAP = 173–415 mm) in Inner Mongolia. While the absolute and fractional abundance of 6-methyl brGDGTs increases with increasing soil pH and aridity, following the trend in the global surface soil calibration dataset, the degree of cyclization does not. This indicates that in arid regions, soil pH reconstructions based on the relative contribution of 6-methyl brGDGTs are likely more reliable than those based on the degree of cyclization. Furthermore, 5- and 6-methyl brGDGTs respond differently to aridity, supporting prior suggestions that the distribution of brGDGTs could be the result of changes in bacterial community composition instead of the direct physiological alteration of molecular structures by the source organisms. Analysis of the bacterial community composition in the same soil transect indicates that the relative abundance of Acidobacteria, the phylum hosting potential brGDGT source-organisms, shows a poor relationship with aridity. Instead, Verrucomicrobia (r2 = 0.70, p < 0.01), and its subclass Spartobacteria (r2 = 0.70, p < 0.01) in particular, show a significant negative correlation with aridity, resembling that of 5-methyl brGDGTs. Similarly, Actinobacteria are positively correlated with aridity (r2 = 0.59, p < 0.01), following the same trend as that of 6-methyl brGDGTs. The ability of certain cultures of Verrucomicrobia and Actinobacteria to produce iso-C15:0 fatty acids that could serve as building blocks for brGDGTs hints that Verrucomicrobia and Actinobacteria could possibly produce brGDGTs in arid soils.
Studies on academic patent commercialisation are well documented. However, spatial effects are seldom considered, which could lead to potentially misleading analytical results. This study addresses this concern by applying the spatial analysis method to investigate how university-level factors and commercialising academic patents are related. Using a comprehensive dataset of university patents from 1815 Chinese universities in 2016, we find that public research funding of universities, industrial research funding, the number of scientific research personnel, the number of monographs published, and the number of awarded achievements are positively related to the commercialisation of academic patents. However, the number of teaching and research personnel and the number of academic papers published are negatively related. There are positive spatial spillover effects in commercialising academic patents among neighbouring universities, but there will be negative spatial spillover effects in funding competition.
Summary Spatially resolved in situ tagging of the cell of interest is crucial for in-depth mechanistic dissection of multicellular architectures or processes. With continuing interest in bioorthogonal photocatalytic decaging chemistry, we herein report the extracellular-targeted photocatalytic decaging system (CAT-Ex) for spatially resolved cell tagging and surface proteome profiling under living conditions. An antibody-conjugated photocatalysis system was established and extensively validated, enabling photocatalytic decaging of biotin precursors and proximal quinone methide probes on target cells. Visible-light-controlled selective cell tagging in cell mixture as well as in primary cells from tumor xenografts were demonstrated. Spatially resolved membrane proteome profiling was further achieved by coupling quinone methide decaging chemistry with CAT-Ex, revealing a potential microdomain protein cluster surrounding the endogenous HER2 receptor. Finally, we expanded our strategy to photocatalytic prodrug decaging for selective tumor cell killing, establishing CAT-Ex as a general platform for diverse photo-controlled molecular manipulations on targeted cells with spatial-temporal precision.
This quantitative study was based on data from 910 Chinese listed companies, spanning from 2002 to 2017. It finds that the geographic distribution for patent competition is spatially dispersed from China’s Southeast Coast to the Northwest. This demonstrates that companies in Western and Northern China are increasingly innovative. In terms of time, the number of patents that enterprises produce has trended upward since 2010, and patent competition among enterprises is intensifying. Moreover, there is a strategic interaction between neighbouring companies in patent competition. Invention patents have a positive spillover effect, while non-invention patents have a negative spillover effect. This study also shows that the larger the scale of the enterprise and the higher its operating income, the more patents it has. The influence of enterprise age on total patents and invention patents is inversely related. Additionally, the more concentrated the company’s equity, the fewer the patents, and the higher the industry concentration, the greater the number of patents. Further, regional economic growth has a positive effect on total patents, while the regional unemployment rate has a negative effect on invention patents.
Event camera has offered promising alternative for visual perception, especially in high speed and high dynamic range scenes. Recently, many deep learning methods have shown great success in providing model-free solutions to many event-based problems, such as optical flow estimation. However, existing deep learning methods did not address the importance of temporal information well from the perspective of architecture design and cannot effectively extract spatio-temporal features. Another line of research that utilizes Spiking Neural Network suffers from training issues for deeper architecture. To address these points, a novel input representation is proposed that captures the events temporal distribution for signal enhancement. Moreover, we introduce a spatio-temporal recurrent encoding-decoding neural network architecture for event-based optical flow estimation, which utilizes Convolutional Gated Recurrent Units to extract feature maps from a series of event images. Besides, our architecture allows some traditional frame-based core modules, such as correlation layer and iterative residual refine scheme, to be incorporated. The network is end-to-end trained with self-supervised learning on the Multi-Vehicle Stereo Event Camera dataset. We have shown that it outperforms all the existing state-of-the-art methods by a large margin.
Based on system efficient electrostatic discharge design (SEED) methodology, this paper proposes a high-order SPICE simulation methodology to predict the performance of the ESD protection circuits. The related PCB-level experiments of the selected protection circuits are fulfilled to verify this method. As a result, the consistency of the comparison results between the simulation and measurement illustrates that the method can accurately predict the performance of system-level protection circuits.
Large-scale neuromorphic dataset is costly to construct and difficult to annotate because of the unique high-speed asynchronous imaging principle of bio-inspired cameras. Lacking of large-scale annotated neuromorphic datasets has significantly hindered the applications of bio-inspired cameras in deep neural networks. Synthesizing neuromorphic data from annotated RGB images can be considered to alleviate this challenge. This paper proposes a simulator to generate simulated spiking data from images recorded by frame cameras. To minimize the deviationsbetween synthetic data and real data, the proposed simulator named SpikingSIM considers the sensing principle of spiking cameras, and generates high-quality simulated spiking data, e.g., the noises in real data are also simulated. Experimental results show that, our simulator generates more realistic spiking data than existing methods. We hence train deep neural networks with synthesized spiking data. Experiments show that, the network trained by our simulated data generalizes well on real spiking data. The source code of SpikingSIM is available at http://github.com/Evin-X/SpikingSIM.
Heteroepitaxy with large lattice mismatch remains a great challenge for high-quality epifilm growth. Although great efforts have been devoted to epifilm growth with an in-plane lattice mismatch, the epitaxy of 2D layered crystals on stepped substrates with a giant out-of-plane lattice mismatch is seldom reported. Here, taking the molecular-beam epitaxy of 2D semiconducting Bi2O2Se on 3D SrTiO3 substrates as an example, a step-climbing epitaxy growth strategy is proposed, in which the n-th (n = 1, 2, 3…) epilayer climbs the step with height difference from out-of-plane lattice mismatch and continues to grow the n+1-th epilayer. Step-climbing epitaxy can spontaneously relax and release the strain from the out-of-plane lattice mismatch, which ensures the high quality of large-area epitaxial films. Wafer-scale uniform 2D Bi2O2Se single-crystal films with controllable thickness can be obtained via step-climbing epitaxy. Most notably, one-unit-cell Bi2O2Se films (1.2 nm thick) exhibit a high Hall mobility of 180 cm2 V−1 s−1 at room temperature, which exceeds that of silicon and other 2D semiconductors with comparable thickness. As an out-of-plane lattice mismatch is generally present in the epitaxy of layered materials, the step-climbing epitaxy strategy expands the existing epitaxial growth theory and provides guidance toward the high-quality synthesis of layered materials.
Many manmade organic air pollutants are semivolatile and primarily used and exposed indoors. It remains unclear how indoor environmental parameters affect indoor air dynamics of semivolatile organic compounds (SVOCs) in real-world indoor conditions, which directly relates to human exposure. By making time-resolved SVOC measurements over multiple weeks in an office, we characterized the indoor air dynamics of six representative SVOCs which were mainly present in the gas phase and of indoor origins, and investigated the effects of the temperature and ventilation rate. The six species include di-isobutyl phthalate and di-n-butyl phthalate, as well as two n-alkanes and two siloxanes. Airborne concentrations of all six SVOCs responded strongly and quickly to changes in the indoor temperature. The temperature dependence of individual species can be well fitted in the form of the van't Hoff equation, and explained 65–86% of the observed variation in the logarithm-transformed concentrations. In contrast, increasing the ventilation rate by a factor of 3–5 for hours at a constant temperature had no discernible influence on the SVOC concentrations. Further kinetic modeling analysis suggests that the observed fast temperature response and indiscernible ventilation effect are both associated with SVOC sorption onto indoor surfaces, which dramatically slows the response of SVOC concentration to changes in the ventilation rate and speeds up the response to changes in the temperature. These results highlight the importance of sorption reservoirs on regulating indoor SVOC dynamics and also have important implications for controlling and assessing indoor air exposure to SVOCs.
Structure and properties of terrestrial magma oceans control the co-evolution of the core, mantle and atmosphere of the early Earth, but are poorly understood because discrepancies remain between experiments and theoretical calculations. Here we combine acoustic velocity measurements and ab initio simulations on pyrolite glass/melt with a silicate Earth-like composition. In the complex system, we find a gradual increase of sound velocity with increasing pressure. Through ab initio simulations, this is explicable by the transition from four- to six-fold coordinated Si occurring over the entire mantle regime. These results are at odds with recent X-ray diffraction measurements, which show an abrupt change in Si-O coordination at 35 GPa. It is however consistent with recent high-pressure data, where Ni partitioning between molten metal and silicate exhibits a similar gradual change with pressure. Unlike amorphous silica, smooth structural evolution in a multicomponent system implies progressive changes in magma ocean properties with depth, such as density, element partitioning and transport properties, which, when incorporated into magma ocean models, may improve our understanding of early history of the Earth and other rocky planets.
More than 8 million people fly on commercial aircraft each day with approximately 5% having a pre-existing respiratory disease. Thus it is necessary to provide high air quality in aircraft to protect public health. Volatile organic compounds (VOCs) present in aircraft cabins are suspected to contribute to the reported complaints. We investigated concentrations of VOCs, air temperature, relative humidity, and CO2 concentrations in a total of 46 flights, including 26 Chinese domestic flights and 20 international flights. We focused on the data from the cruising phase without meal serving in which the air supply and air recirculation were steady. A total of 284 passengers (i.e., 101 on international flights and 183 on Chinese domestic flights) were invited to participate in questionnaire surveys in this phase. We performed a linear mixed model analysis by controlling for potential confounders (age, gender, smoke habits, and history of allergy) to study associations between VOCs exposures and passengers' complaints. Xylene was significantly associated with irritations of the eyes, nose, and throat on both international and domestic flights, with antilog beta values from 1.12 to 1.28 (p < 0.05). The association of some aldehydes (i.e., nonanal, decanal, and heptanal), which are potential oxidation products with ozone, with passengers' sensory irritations was also significant, especially during international flights (antilog beta values: 1.19–1.22). It indicates that VOCs, especially xylene and aldehydes, in aircraft cabins may influence the perceived indoor air quality and complaints among passengers.