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Clay minerals have great potentials in pinpointing sediment provenance for large depositional systems. However, source identification using clay minerals for small floodplain lakes is not well known. Situated in the North China Plain, the Dongping Lake receives sediments from both the Yellow River and the Dawen River, thereby representing an ideal site for testing the utility of this method. Here we use clay minerals in conjunction with the Bayesian end-member modeling analysis (BEMMA) to quantify the riverine contribution to modern sediments in the Dongping Lake. Results showed that modern sediments of the Dongping Lake are characterized by four primary clay minerals: illite, smectite, kaolinite, and chlorite, with average contents of 60.53%, 11.37%, 12.70%, and 15.40%, respectively. Clay minerals in modern sediments of the Dongping Lake are mainly delivered by the Yellow River, accounting for approximately 58.99–72.33%; whereas those originating from the Dawen River only account for 27.67–41.01%. It is also found that clay mineral from these rivers have a marked spatial variability. For example, source materials from the Yellow River are widely distributed across the lake, while those from the Dawen River only occur at the estuary of the river and slightly spread out in all directions under the action of water flow. [ABSTRACT FROM AUTHOR]

Although prior studies have proposed some smart city index systems, they primarily focus on generic indicators connected to urban development and fail to reflect the properties of intelligence. To fill this gap, we develop a new index system involving three dimensions of digital infrastructure, smart living, and digital economy. Moreover, compared with studies that use subjective weighting methods to rank the smartness of cities, we combine the Shannon entropy weighting method with three multi-criteria decision-making (MCDM) methods to show the objectiveness of the evaluation process. Through analyzing the quantitative data from nine cities in the Pearl River Delta (PRD) region in China, we find that digital infrastructure is the most important first-level indicator, accounting for 46.92%, followed by the digital economy and smart life accounting for 32.48% and 20.60% respectively. More importantly, when the nine cities in the PRD region are ranked by three MCDM methods, the correlation between the results is over 90%, thus proving robustness. We contribute to the current smart city literature by enriching the components of the smart city index system, as well as evaluation methods. Our findings also guide decision-makers in formulating more targeted smart city construction plans. • Develop a new smart city index system involving three dimensions of digital infrastructure, smart living, and digital economy • Use three multi-criteria decision-making (MCDM) methods to rank the smartness of cities • Data were gathered from online platforms in the Pearl River Delta Region, China. • The correlation between the results from different MCDM methods is >90%. • The practical implications are highlighted. [ABSTRACT FROM AUTHOR]

Lacustrine sediment played important roles in migration and transformation of its water soluble organic matter (WSOM), and the source and composition of WSOM would affect water trophic status and the fate of pollutants. However, we know little about the pathway of WSOM transformation and its driving bacterial communities in lacustrine sediment. In the present study, we investigated the spatial distribution patterns of sediment WSOM and its fluorescent fractions across Lake Chaohu using fluorescence spectroscopy, and explored WSOM compositional structure through our proposed calculated ratios. In addition, we also analyzed sediment bacterial community using Illumina sequencing technology, and probed the possible pathway of sediment WSOM transformation under the mediate of indigenous bacteria. Our results showed that the inflowing rivers affected the spatial distribution patterns of WSOM and its five fractions (including tyrosine-, tryptophan-, fulvic acid-, humic acid-like substances and soluble microbial productions), and sediment WSOM originated from fresh algae detritus or bacterial sources. In parallel, we also found that Proteobacteria (mainly γ-Proteobacteria and δ-Proteobacteria), Firmicutes (mainly Bacilli), Chloroflexi, Acidobacteria, Planctomycetes and Actinobacteria dominate sediment bacterial community. Furthermore, these dominant bacteria triggered sediment WSOM transformation, specifically, the humic acid-like substances could be converted into fulvic acid-like substances, and further degraded into aromatic protein-like and SMP substances. In addition, our proposed ratios (P-L:H-L, Ar-P:SMP and H-L ratio), as supplementary tool, were effective to reveal WSOM composition structure. These results figured out possible pathway of WSOM transformation, and revealed its microbial mechanism in lacustrine sediment. Image, graphical abstract [ABSTRACT FROM AUTHOR]

Lacustrine rift basins in Eastern China possess large amounts of petroleum, especially the shale gas and tight sand gas in deep formations, where "sweet spots" are closely related to organic-rich shale intervals. However, the OM enrichment of deep formation shale in lacustrine rift basins and the main controlling factors have not been well-researched in previous studies. The organic matter (OM) enrichment is mainly controlled by the OM input, preservation, and/or dilution. The shales deposited in deep formations of Songliao Basin, including the Jurassic Huoshiling (J 3 h), Cretaceous Shahezi (K 1 sh), and Yingcheng (K 1 yc) formations, are evaluated as fair to excellent source rocks. Taking the shales as an example, the characters and impact of input, preservation, and dilution on OM enrichment in shales are discussed by utilizing the parameters of element concentrations and biomarkers. Results show that the OM sources are mixed sources of aquatic microorganisms and higher plant materials, and the higher plant materials are dominant. The bio-productivity were moderate to high. The paleoclimate was mainly the cold and semi-humid to semi-arid. The lake salinity was fresh-to brackish-water. The redox conditions were sub-reducing to sub-oxidizing. The dilution degree in Yingcheng was the strongest, followed by the Shahezi and Huoshiling. Consequently, the OM enrichment in the J 3 h shale was called moderate bio-productivity and preservation model; the OM enrichment in the K 1 sh shale was called high bio-productivity and preservation model; the OM enrichment in the K 1 yc shale was named high dilution model. This study not only improves the model of OM enrichment but also provide some information for the research of "Deep time" in the Cretaceous of Songliao Basin, guiding the prediction of organic-rich shale distribution in lacustrine rift basin. • Fair to excellent hydrocarbon generation potential. • Organic matter origins are mainly a mixture of aquatic microorganisms and terrestrial higher plants. • Arid and cold paleoclimate and fresh- and brackish-water. • Reducing to sub-reducing, sub-reducing to oxidizing, and sub-reducing to sub-oxidizing conditions. • Moderate bio-productivity and preservation model, high bio-productivity and preservation model, high dilution model. [ABSTRACT FROM AUTHOR]

• We estimated the time to the most recent common ancestor (TMRCA) and evolutionary rate of SARS-CoV-2 to be 12 November 2019 (95% BCI: 11 October 2019 and 09 December 2019) and 9.90 × 10-4 substitutions per site per year (95% BCI: 6.29 × 10-4–1.35 × 10-3), respectively. • Our results emphasize the importance of using phylogenetic and phylodynamic analyses to provide insights into the roles of various interventions to limit the spread of SARS-CoV-2 in China and beyond. • Understanding epidemic dynamics of SARS-CoV-2 in real time is increasingly important for guiding prevention efforts. To investigate the evolutionary and epidemiological dynamics of the current COVID-19 outbreak, a total of 112 genomes of SARS-CoV-2 strains sampled from China and 12 other countries with sampling dates between 24 December 2019 and 9 February 2020 were analyzed. We performed phylogenetic, split network, likelihood-mapping, model comparison, and phylodynamic analyses of the genomes. Based on Bayesian time-scaled phylogenetic analysis with the best-fitting combination models, we estimated the time to the most recent common ancestor (TMRCA) and evolutionary rate of SARS-CoV-2 to be 12 November 2019 (95 % BCI: 11 October 2019 and 09 December 2019) and 9.90 × 10−4 substitutions per site per year (95 % BCI: 6.29 × 10−4–1.35 × 10−3), respectively. Notably, the very low R e estimates of SARS-CoV-2 during the recent sampling period may be the result of the successful control of the pandemic in China due to extreme societal lockdown efforts. Our results emphasize the importance of using phylodynamic analyses to provide insights into the roles of various interventions to limit the spread of SARS-CoV-2 in China and beyond. [ABSTRACT FROM AUTHOR]

The superimposed foreland basins mainly develop in central-western China, namely the Himalayan foreland basins superimposed on the Indo-China foreland basins. Previous research on hydrocarbon migration predominantly focused on the typical foreland basins and the fore-deep depression of superimposed foreland basins. As a result of multi-superimposition, large hydrocarbon potentials in the slope zones are evaluated, and the hydrocarbon migration shows significant differences with those in the typical foreland basins. Moreover, the hydrocarbon migration models in the slope zone of superimposed foreland basins are poor analyzed. The Chepaizi High in the South Junggar Basin, a typical slope of superimposed foreland basin, has been taken into consideration. Several points have been ascertained. 1) Multistage charging and readjustment events should be the predominant characters. 2) The combination of multi-type sand-bodies, multistage faults and unconformities have formed step- or "Z"-shaped migration pathways spatially. 3) Hydrocarbons migrated from the areas of high oil potential in the fore-deep depression to those of low oil potential in the slope. 4) The migration models of the J 1 b, K 1 q, N 1 s 1 , and N 1 s 2 have been established. Hydrocarbon reservoirs in the slope zones show the shallow accumulation from deep/distal sources with multiple reservoirs vertically and multi-charging and -readjustments chronologically. 5) The areas of (Wells SM3, C53-C90, and CF2), (Wells SM5, C80, and CF13), and (Wells K8, HG4, SM4, and CF2) can be the favorable targets for the J 1 b, K 1 q, and N 1 s, respectively. • Z-shaped and step-shaped composite hydrocarbon migration pathways. • High oil potential located in the fore-deep depression. • Hydrocarbons migrated from the fore-deep depression to the slope. • Multistage migration histories and multistage readjustments in the slope. • Hydrocarbon charged from deep sources and over long distances. [ABSTRACT FROM AUTHOR]