Atmospheric glyoxal(GLY) and methylglyoxal(MGLY) are key precursors of secondary organic aerosol(SOA). However, anthropogenic emissions of GLY and MGLY and their contribution to surface GLY and MGLY concentrations, as...
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Atmospheric glyoxal(GLY) and methylglyoxal(MGLY) are key precursors of secondary organic aerosol(SOA). However, anthropogenic emissions of GLY and MGLY and their contribution to surface GLY and MGLY concentrations, as well as the secondary organic aerosol(SOA) formation, are not well quantified. By developing an emission inventory of anthropogenic GLY and MGLY and improving Community Multiscale Air Quality Model(CMAQ) with SOA formation from irreversible surface uptake of GLY and MGLY, as well as a precursor-origin resolved technique, we quantified the source contributions of GLY and MGLY and their impact on wintertime SOA formation in Beijing, China. The total emissions of GLY and MGLY in Beijing in 2017 are 1.1×10～4 kmol and 7.0×10～3 kmol, respectively. Anthropogenic primary emissions are found to be the dominant contributor to GLY and MGLY concentrations(～74% for GLY and ～63% for MGLY). Anthropogenic primary emissions of GLY and MGLY contributes to 30% of GLY/MGLY SOA daily average concentration and accounts for up to 45% of nighttime GLY/MGLY SOA. The study suggests that the anthropogenic GLY and MGLY emissions, mainly from gasoline vehicles and cooking, are important for SOA formation and shall be strictly controlled in Chinese megacities.
Background: The influence of rising global temperatures on malaria dynamics and distribution remains controversial, especially in central highland regions. We aimed to address this subject by studying the spatiotempor...
Background: The influence of rising global temperatures on malaria dynamics and distribution remains controversial, especially in central highland regions. We aimed to address this subject by studying the spatiotemporal heterogeneity of malaria and the effect of climate change on malaria transmission over 27 years in Hainan, an island province in China. Methods: For this longitudinal cohort study, we used a decades-long dataset of malaria incidence reports from Hainan, China, to investigate the pattern of malaria transmission in Hainan relative to temperature and the incidence at increasing altitudes. Climatic data were obtained from the local meteorological stations in Hainan during 1984–2010 and the WorldClim dataset. A temperature-dependent R0 model and negative binomial generalised linear model were used to decipher the relationship between climate factors and malaria incidence in the tropical region. Findings: Over the past few decades, the annual peak incidence has appeared earlier in the central highland regions but later in low-altitude regions in Hainan, China. Results from the temperature-dependent model showed that these long-term changes of incidence peak timing are linked to rising temperatures (of about 1·5°C). Further, a 1°C increase corresponds to a change in cases of malaria from –5·6% (95% CI –4·5 to –6·6) to –9·2% (95% CI –7·6 to –10·9) from the northern plain regions to the central highland regions during the rainy season. In the dry season, the change in cases would be 4·6% (95% CI 3·7 to 5·5) to 11·9% (95% CI 9·8 to 14·2) from low-altitude areas to high-altitude areas. Interpretation: Our study empirically supports the idea that increasing temperatures can generate opposing effects on malaria dynamics for lowland and highland regions. This should be further investigated and incorporated into future modelling, disease burden calculations, and malaria control, with attention for central highland regions under climate change. Funding: S
Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms that are often specific to cell type. Here, to characterize the genetic contribution...
Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms that are often specific to cell type. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.
The brain requires diverse segregated and integrated processing to perform normal functions in terms of anatomical structure and self-organized dynamics with critical features, but the fundamental relationships betwee...
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The brain requires diverse segregated and integrated processing to perform normal functions in terms of anatomical structure and self-organized dynamics with critical features, but the fundamental relationships between the complex structural connectome, critical state, and functional diversity remain unknown. Herein, we extend the eigenmode analysis to investigate the joint contribution of hierarchical modular structural organization and critical state to brain functional diversity. We show that the structural modes inherent to the hierarchical modular structural connectome allow a nested functional segregation and integration across multiple spatiotemporal scales. The real brain hierarchical modular organization provides large structural capacity for diverse functional interactions, which are generated by sequentially activating and recruiting the hierarchical connectome modes, and the critical state can best explore the capacity to maximize the functional diversity. Our results reveal structural and dynamical mechanisms that jointly support a balanced segregated and integrated brain processing with diverse functional interactions, and they also shed light on dysfunctional segregation and integration in neurodegenerative diseases and neuropsychiatric disorders.
Despite a large body of literature, mechanisms contributing to low temperature jerky flow remain controversial. Here, we report a cross over from a smooth at room and liquid nitrogen temperatures to serrated plastic f...
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Chimera states in spatiotemporal dynamical systems have been investigated in physical, chemical, and biological systems, and have been shown to be robust against random perturbations. How do chimera states achieve the...
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Chimera states in spatiotemporal dynamical systems have been investigated in physical, chemical, and biological systems, and have been shown to be robust against random perturbations. How do chimera states achieve their robustness? We uncover a self-adaptation behavior by which, upon a spatially localized perturbation, the coherent component of the chimera state spontaneously drifts to an optimal location as far away from the perturbation as possible, exposing only its incoherent component to the perturbation to minimize the disturbance. A systematic numerical analysis of the evolution of the spatiotemporal pattern of the chimera state towards the optimal stable state reveals an exponential relaxation process independent of the spatial location of the perturbation, implying that its effects can be modeled as restoring and damping forces in a mechanical system and enabling the articulation of a phenomenological model. Not only is the model able to reproduce the numerical results, it can also predict the trajectory of drifting. Our finding is striking as it reveals that, inherently, chimera states possess a kind of “intelligence” in achieving robustness through self-adaptation. The behavior can be exploited for the controlled generation of chimera states with their coherent component placed in any desired spatial region of the system.
In this paper, we propose a cooperative motion planning method for a group of connected and automated vehicles (CAVs) crossing a lane-free intersection without using explicit traffic signaling. This multi-vehicle moti...
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Cancer is a term used to refer to a large set of diseases. The cancerous cells grow and divide and, as a result, they form tumours that grow in size. The immune system recognise the cancerous cells and attack them, th...
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Volatile organic compounds （VOCs） are major precursors for ozone and secondary organic aerosol （SOA）, both of which greatly harm human health and significantly affect the Earth＇s climate. We simultaneously estima...
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Volatile organic compounds （VOCs） are major precursors for ozone and secondary organic aerosol （SOA）, both of which greatly harm human health and significantly affect the Earth＇s climate. We simultaneously estimated ozone and SOA formation from anthropogenic VOCs emissions in China by employing photochemical ozone creation potential （POCP） values and SOA yields. We gave special attention to large molecular species and adopted the SOA yield curves from latest smog chamber experiments. The estimation shows that alkylbenzenes are greatest contributors to both ozone and SOA formation （36.0% and 51.6%, respectively）, while toluene and xylenes are largest contributing individual VOCs. Industry solvent use, industry process and domestic combustion are three sectors with the largest contributions to both ozone （24.7%, 23.0% and 17.8%, respectively） and SOA （22.9%, 34.6% and 19.6%, respectively） formation. In terms of the formation potential per unit VOCs emission, ozone is sensitive to open biomass burning, transportation, and domestic solvent use, and SOA is sensitive to industry process, domestic solvent use, and domestic combustion. Biomass stoves, paint application in industrial protection and buildings, adhesives application are key individual sources to ozone and SOA formation, whether measured by total contribution or contribution per unit VOCs emission. The results imply that current VOCs control policies should be extended to cover most important industrial sources, and the control measures for biomass stoves should be tightened. Finally, discrepant VOCs control policies should be implemented in different regions based on their ozone/aerosol concentration levels and dominant emission sources for ozone and SOA formation potential.
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