48 results on '"Funing Sun"'
Search Results
2. Origin of authigenic albite in a lacustrine mixed-deposition sequence (Lucaogou Formation, Junggar Basin) and its diagenesis implications
- Author
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Haiguang Wu, Junjun Zhou, Wenxuan Hu, Funing Sun, Xun Kang, Yunfeng Zhang, Wenjun He, and Chengcheng Feng
- Subjects
Production of electric energy or power. Powerplants. Central stations ,TK1001-1841 ,Renewable energy sources ,TJ807-830 - Abstract
Authigenic albites occur widely in clastic reservoirs with important implications for diagenesis and reservoir formation. The middle Permian Lucaogou Formation in the Jimusaer Sag (Junggar Basin, NW China), where major exploration breakthroughs in shale oil have been achieved, reveals a new phenomenon that authigenic albites are abundant in unique mixed carbonate–volcanic–clastic sequences. This has not been reported in the literatures. To fill the knowledge gap, the origin of these authigenic albites and their relationship with dissolution pores (i.e. diagenesis implications) were investigated. Results show that two types (I and II) of authigenic albite were identified within the shale oil reservoirs. Euhedral Type I authigenic albites with 3–10 μm only occur in dolarenite intraclasts and are symbiotic with amorphous dolomite minerals with a pure chemical composition of >99% albite-end-member content. Larger Type II authigenic albites with 10–50 μm are widely distributed in reservoirs, primarily in dissolution pores, and coexist with authigenic dolomite minerals or dolomite overgrowths. Their chemical composition is less pure with anorthite-end-member contents that range from undetectable to 9.77%, with an average of 1.34%. A symbiotic relationship, pure chemical composition, size, and euhedral morphology indicate that Type I authigenic albites precipitated during syngenetic hydrothermal action. However, the morphology of dissolution pores, residual symbiotic “orthoclase”, impure chemical composition and carbon–oxygen isotope indicate that Type II were the products of the dissolution and reprecipitation of “perthite” crystal pyroclasts influenced by acid organic fluids in latter diagenesis. The differential dissolution of “orthoclase” and “albite” components in “perthite” crystal pyroclasts formed enormous intergranular secondary pores in the presence of dolomite minerals in the shale oil reservoirs.
- Published
- 2022
- Full Text
- View/download PDF
3. Characteristics of dissolved pores and dissolution mechanism of zeolite-rich reservoirs in the Wuerhe Formation in Mahu area, Junggar Basin
- Author
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Ji Li, Wenjie Zhang, Baoli Xiang, Dan He, Shengchao Yang, Jian Wang, Erting Li, Ni Zhou, Funing Sun, and Wenxuan Hu
- Subjects
Production of electric energy or power. Powerplants. Central stations ,TK1001-1841 ,Renewable energy sources ,TJ807-830 - Abstract
The reservoir in the Wuerhe Formation in the Mahu Sag, northwestern Junggar Basin, China, exhibits complex dissolution and cementation related to zeolite. The source and mechanism of diagenetic fluids are crucial in studying the reservoir genesis. Thus we investigated the key reservoirs fluids related to the zeolite and discussed their significance in the zeolite-rich reservoir of the Permian Wuerhe Formation in the Mahu Sag. Based on thin sections and electron microscope observations of rock samples and analyses of physical properties, C-O isotopes, and major elements, it is found that the reservoir underwent mainly two stages of fluid-related dissolution and cementation processes, in which the hydrocarbon-bearing fluid played the primary role in forming the high-quality reservoir. Dissolution pores are the most important storage space, and zeolite cement is the most important dissolution mineral. The geochemical characteristics of zeolite and calcite cement indicate the presence of two diagenetic fluids. The iron-rich calcite and orange-red heulandite is related to early diagenetic fluids with high iron content and higher carbon isotope values, whereas the calcites, with high manganese content and lower carbon isotope values, are formed by late acidic organic diagenetic fluids related to oil and gas activities. The hydrocarbon-bearing fluids form different spatial diagenetic zones, including the dissolution zone, buffer zone, and cementation zone, and the dissolution zone near the oil source fault is the main site of zeolite dissolution. The late fluid has the characteristics of multi-stage activity, which makes the spatial zoning expand gradually, resulting in multiple superpositions of dissolution and cementation and increasing the complexity and heterogeneity of the reservoir diagenesis. This study expands the understandings of the dissolution activities of different fluids in zeolite-rich reservoirs and also has reference significance for dissolution activity of hydrocarbon fluid in other types of reservoirs.
- Published
- 2022
- Full Text
- View/download PDF
4. History-enhanced and Uncertainty-aware Trajectory Recovery via Attentive Neural Network.
- Author
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Tong Xia, Yong Li 0008, Yunhan Qi, Jie Feng 0002, Fengli Xu, Funing Sun, Diansheng Guo, and Depeng Jin
- Published
- 2024
- Full Text
- View/download PDF
5. Demand-driven Urban Facility Visit Prediction.
- Author
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Yunke Zhang, Tong Li 0013, Yuan Yuan 0032, Fengli Xu, Fan Yang, Funing Sun, and Yong Li 0008
- Published
- 2024
- Full Text
- View/download PDF
6. Deep Multi-View Channel-Wise Spatio-Temporal Network for Traffic Flow Prediction.
- Author
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Hao Miao 0001, Senzhang Wang, Meiyue Zhang, Diansheng Guo, Funing Sun, and Fan Yang
- Published
- 2024
- Full Text
- View/download PDF
7. Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution.
- Author
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Fuxian Li, Jie Feng 0002, Huan Yan, Guangyin Jin, Fan Yang, Funing Sun, Depeng Jin, and Yong Li 0008
- Published
- 2023
- Full Text
- View/download PDF
8. Context-aware Spatial-Temporal Neural Network for Citywide Crowd Flow Prediction via Modeling Long-range Spatial Dependency.
- Author
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Jie Feng 0002, Yong Li 0008, Ziqian Lin, Can Rong, Funing Sun, Diansheng Guo, and Depeng Jin
- Published
- 2022
- Full Text
- View/download PDF
9. Adaptive Spatio-Temporal Convolutional Network for Traffic Prediction.
- Author
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Mingyang Zhang 0004, Yong Li 0008, Funing Sun, Diansheng Guo, and Pan Hui 0001
- Published
- 2021
- Full Text
- View/download PDF
10. AttnMove: History Enhanced Trajectory Recovery via Attentional Network.
- Author
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Tong Xia, Yunhan Qi, Jie Feng 0002, Fengli Xu, Funing Sun, Diansheng Guo, and Yong Li 0008
- Published
- 2021
- Full Text
- View/download PDF
11. Methanogen-mediated dolomite precipitation in an early Permian lake in northwestern China.
- Author
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Funing Sun, Wenxuan Hu, Xiaolin Wang, Zhongya Hu, Haiguang Wu, and Yangrui Guo
- Subjects
- *
DOLOMITE , *LAKE sediments , *HETEROGENOUS nucleation , *SOUND recordings , *METHANOGENS , *LAKES - Abstract
Microbes are known to mediate dolomite precipitation in laboratory experiments; however, the linkage of specific microbes to ancient dolomites remains poorly constrained due to scarce diagnostic biogeochemical signatures and mineralized microbial relics in the rock record. Here, we report the occurrence of methanogen-mediated dolomite in the Lower Permian lacustrine Lucaogou Formation in northwestern China. The clumped isotope (Δ47) temperature provides direct evidence of a low-temperature origin (typically <40 °C). The extremely positive d26MgDSM3 (up to +0.44‰) and d13CVPDB (up to +19‰) values in the dolomite indicate authigenic precipitation in methanogenic lake sediments. Micron-sized spheroidal bodies and filamentous and sheetlike structures are interpreted as mineralized coccoid methanogenic archaea and extracellular polymeric substances (EPSs), respectively. Dolomite nanoglobules (primarily 40-100 nm in diameter) are interpreted as mineralized viruses attached to the archaea and EPSs and between the cells. A combination of geochemical and microscale evidence confirms the microbial origin of the dolomite induced by methanogens and their associated bacteriophages. Furthermore, dolomite nanoglobules initially nucleated on the surfaces of methanogen cells, EPSs, and viruses and then merged into larger aggregates. The formation of microbial dolomite is characterized by a metabolic incubation, heterogeneous nucleation, and aggregative growth pathway. These findings provide valuable clues to decipher the biosignatures of these particular ancient dolomites. [ABSTRACT FROM AUTHOR]
- Published
- 2024
- Full Text
- View/download PDF
12. A Sequential Convolution Network for Population Flow Prediction with Explicitly Correlation Modelling.
- Author
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Jie Feng 0002, Ziqian Lin, Tong Xia, Funing Sun, Diansheng Guo, and Yong Li 0008
- Published
- 2020
- Full Text
- View/download PDF
13. 3DGCN: 3-Dimensional Dynamic Graph Convolutional Network for Citywide Crowd Flow Prediction.
- Author
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Tong Xia, Junjie Lin, Yong Li 0008, Jie Feng 0002, Pan Hui 0001, Funing Sun, Diansheng Guo, and Depeng Jin
- Published
- 2021
- Full Text
- View/download PDF
14. No More than What I Post: Preventing Linkage Attacks on Check-in Services.
- Author
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Fengli Xu, Zhen Tu, Hongjia Huang, Shuhao Chang, Funing Sun, Diansheng Guo, and Yong Li 0008
- Published
- 2019
- Full Text
- View/download PDF
15. Understanding Urban Dynamics via State-sharing Hidden Markov Model.
- Author
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Tong Xia, Yue Yu, Fengli Xu, Funing Sun, Diansheng Guo, Depeng Jin, and Yong Li 0008
- Published
- 2019
- Full Text
- View/download PDF
16. State-Sharing Sparse Hidden Markov Models for Personalized Sequences.
- Author
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Hongzhi Shi, Chao Zhang 0014, Quanming Yao, Yong Li 0008, Funing Sun, and Depeng Jin
- Published
- 2019
- Full Text
- View/download PDF
17. DeepMM: Deep Learning Based Map Matching with Data Augmentation.
- Author
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Kai Zhao, Jie Feng 0002, Zhao Xu, Tong Xia, Lin Chen 0002, Funing Sun, Diansheng Guo, Depeng Jin, and Yong Li 0008
- Published
- 2019
- Full Text
- View/download PDF
18. Semantics-Aware Hidden Markov Model for Human Mobility.
- Author
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Hongzhi Shi, Hancheng Cao, Xiangxin Zhou, Yong Li 0008, Chao Zhang 0014, Vassilis Kostakos, Funing Sun, and Fanchao Meng
- Published
- 2019
- Full Text
- View/download PDF
19. PMF: A Privacy-preserving Human Mobility Prediction Framework via Federated Learning.
- Author
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Jie Feng 0002, Can Rong, Funing Sun, Diansheng Guo, and Yong Li 0008
- Published
- 2020
- Full Text
- View/download PDF
20. DeepMove: Predicting Human Mobility with Attentional Recurrent Networks.
- Author
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Jie Feng 0002, Yong Li 0008, Chao Zhang 0014, Funing Sun, Fanchao Meng, Ang Guo, and Depeng Jin
- Published
- 2018
- Full Text
- View/download PDF
21. Detecting Popular Temporal Modes in Population-scale Unlabelled Trajectory Data.
- Author
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Fengli Xu, Tong Xia, Hancheng Cao, Yong Li 0008, Funing Sun, and Fanchao Meng
- Published
- 2018
- Full Text
- View/download PDF
22. Origin of authigenic albite in a lacustrine mixed-deposition sequence (Lucaogou Formation, Junggar Basin) and its diagenesis implications
- Author
-
Wenjun He, Haiguang Wu, Junjun Zhou, Chengcheng Feng, Funing Sun, Yunfeng Zhang, Wenxuan Hu, and Xun Kang
- Subjects
TK1001-1841 ,Permian ,Renewable Energy, Sustainability and the Environment ,Geochemistry ,TJ807-830 ,Energy Engineering and Power Technology ,Authigenic ,Structural basin ,Renewable energy sources ,Diagenesis ,Sequence (geology) ,Albite ,Production of electric energy or power. Powerplants. Central stations ,Fuel Technology ,Nuclear Energy and Engineering ,Clastic rock ,Deposition (chemistry) ,Geology - Abstract
Authigenic albites occur widely in clastic reservoirs with important implications for diagenesis and reservoir formation. The middle Permian Lucaogou Formation in the Jimusaer Sag (Junggar Basin, NW China), where major exploration breakthroughs in shale oil have been achieved, reveals a new phenomenon that authigenic albites are abundant in unique mixed carbonate–volcanic–clastic sequences. This has not been reported in the literatures. To fill the knowledge gap, the origin of these authigenic albites and their relationship with dissolution pores (i.e. diagenesis implications) were investigated. Results show that two types (I and II) of authigenic albite were identified within the shale oil reservoirs. Euhedral Type I authigenic albites with 3–10 μm only occur in dolarenite intraclasts and are symbiotic with amorphous dolomite minerals with a pure chemical composition of >99% albite-end-member content. Larger Type II authigenic albites with 10–50 μm are widely distributed in reservoirs, primarily in dissolution pores, and coexist with authigenic dolomite minerals or dolomite overgrowths. Their chemical composition is less pure with anorthite-end-member contents that range from undetectable to 9.77%, with an average of 1.34%. A symbiotic relationship, pure chemical composition, size, and euhedral morphology indicate that Type I authigenic albites precipitated during syngenetic hydrothermal action. However, the morphology of dissolution pores, residual symbiotic “orthoclase”, impure chemical composition and carbon–oxygen isotope indicate that Type II were the products of the dissolution and reprecipitation of “perthite” crystal pyroclasts influenced by acid organic fluids in latter diagenesis. The differential dissolution of “orthoclase” and “albite” components in “perthite” crystal pyroclasts formed enormous intergranular secondary pores in the presence of dolomite minerals in the shale oil reservoirs.
- Published
- 2021
23. 3DGCN: 3-Dimensional Dynamic Graph Convolutional Network for Citywide Crowd Flow Prediction
- Author
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Pan Hui, Tong Xia, Yong Li, Junjie Lin, Depeng Jin, Funing Sun, Diansheng Guo, and Jie Feng
- Subjects
Range (mathematics) ,Theoretical computer science ,General Computer Science ,Flow (mathematics) ,Computer science ,Graph neural networks ,020204 information systems ,Urban computing ,0202 electrical engineering, electronic engineering, information engineering ,Graph (abstract data type) ,020201 artificial intelligence & image processing ,02 engineering and technology ,Task (project management) - Abstract
Crowd flow prediction is an essential task benefiting a wide range of applications for the transportation system and public safety. However, it is a challenging problem due to the complex spatio-temporal dependence and the complicated impact of urban structure on the crowd flow patterns. In this article, we propose a novel framework, 3- D imensional G raph C onvolution N etwork (3DGCN), to predict citywide crowd flow. We first model it as a dynamic spatio-temporal graph prediction problem, where each node represents a region with time-varying flows, and each edge represents the origin–destination (OD) flow between its corresponding regions. As such, OD flows among regions are treated as a proxy for the spatial interactions among regions. To tackle the complex spatio-temporal dependence, our proposed 3DGCN can model the correlation among graph spatial and temporal neighbors simultaneously. To learn and incorporate urban structures in crowd flow prediction, we design the GCN aggregator to be learned from both crowd flow prediction and region function inference at the same time. Extensive experiments with real-world datasets in two cities demonstrate that our model outperforms state-of-the-art baselines by 9.6%∼19.5% for the next-time-interval prediction.
- Published
- 2021
24. Characteristics of dissolved pores and dissolution mechanism of zeolite-rich reservoirs in the Wuerhe Formation in Mahu area, Junggar Basin
- Author
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Dan He, Baoli Xiang, Erting Li, Wenjie Zhang, Jian Wang, Shengchao Yang, Ji Li, Wenxuan Hu, Funing Sun, and Ni Zhou
- Subjects
TK1001-1841 ,Renewable Energy, Sustainability and the Environment ,0211 other engineering and technologies ,Geochemistry ,Energy Engineering and Power Technology ,TJ807-830 ,02 engineering and technology ,Structural basin ,010502 geochemistry & geophysics ,Cementation (geology) ,01 natural sciences ,Renewable energy sources ,Diagenesis ,Fuel Technology ,Production of electric energy or power. Powerplants. Central stations ,Nuclear Energy and Engineering ,021108 energy ,Zeolite ,Dissolution ,Geology ,0105 earth and related environmental sciences - Abstract
The reservoir in the Wuerhe Formation in the Mahu Sag, northwestern Junggar Basin, China, exhibits complex dissolution and cementation related to zeolite. The source and mechanism of diagenetic fluids are crucial in studying the reservoir genesis. Thus we investigated the key reservoirs fluids related to the zeolite and discussed their significance in the zeolite-rich reservoir of the Permian Wuerhe Formation in the Mahu Sag. Based on thin sections and electron microscope observations of rock samples and analyses of physical properties, C-O isotopes, and major elements, it is found that the reservoir underwent mainly two stages of fluid-related dissolution and cementation processes, in which the hydrocarbon-bearing fluid played the primary role in forming the high-quality reservoir. Dissolution pores are the most important storage space, and zeolite cement is the most important dissolution mineral. The geochemical characteristics of zeolite and calcite cement indicate the presence of two diagenetic fluids. The iron-rich calcite and orange-red heulandite is related to early diagenetic fluids with high iron content and higher carbon isotope values, whereas the calcites, with high manganese content and lower carbon isotope values, are formed by late acidic organic diagenetic fluids related to oil and gas activities. The hydrocarbon-bearing fluids form different spatial diagenetic zones, including the dissolution zone, buffer zone, and cementation zone, and the dissolution zone near the oil source fault is the main site of zeolite dissolution. The late fluid has the characteristics of multi-stage activity, which makes the spatial zoning expand gradually, resulting in multiple superpositions of dissolution and cementation and increasing the complexity and heterogeneity of the reservoir diagenesis. This study expands the understandings of the dissolution activities of different fluids in zeolite-rich reservoirs and also has reference significance for dissolution activity of hydrocarbon fluid in other types of reservoirs.
- Published
- 2022
25. Methanogen microfossils and methanogenesis in Permian lake deposits
- Author
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Jian Cao, Xiaolin Wang, Funing Sun, Haiguang Wu, Wenxuan Hu, Shengchao Yang, and Bin Fu
- Subjects
010504 meteorology & atmospheric sciences ,Permian ,biology ,Methanogenesis ,Geochemistry ,Geology ,010502 geochemistry & geophysics ,biology.organism_classification ,01 natural sciences ,Methanogen ,0105 earth and related environmental sciences - Abstract
Methanogens are methane-producing archaea (some of the most primitive organisms on Earth), which possess great phylogenetic and ecological diversity in modern ecosystems. However, cellular fossil evidence of methanogens remains extremely scarce throughout the geological record. Here, we report a new population of spheroidal microstructures composed of dolomite observed in Permian lake deposits in northwestern China. The microspheres exhibit indicators of biological affinity and are well preserved in authigenic dolomite with cellular fidelity. Based on morphological and geochemical evidence, these microspheres are interpreted as fossilized cells of methanogenic archaea, which can be divided into three size-based taxa. These microfossils are the first fossil record of spheroidal methanogens. The microfossil-bearing dolomite exhibits extremely positive δ13C values (up to +20‰ relative to Vienna Peedee belemnite) that are attributed to microbial methanogenesis. The results suggest that methanogens were a significant component of this Permian lake biosphere. As a consequence of the metabolic activity of the methanogens, a large amount of biogenic methane was produced through methanogenesis in the anoxic lake sediments. This study not only fills a gap in the fossil record of methanogenic archaea, but it also provides new insights into methane emissions from ancient lakes.
- Published
- 2020
26. PMF
- Author
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Diansheng Guo, Funing Sun, Yong Li, Can Rong, and Jie Feng
- Subjects
Mobility model ,education.field_of_study ,Ubiquitous computing ,Social network ,Computer Networks and Communications ,business.industry ,Computer science ,Deep learning ,Population ,02 engineering and technology ,Data science ,Field (computer science) ,Human-Computer Interaction ,Upload ,Hardware and Architecture ,020204 information systems ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,Artificial intelligence ,business ,education ,Mobile device - Abstract
With the popularity of mobile devices and location-based social network, understanding and modelling the human mobility becomes an important topic in the field of ubiquitous computing. With the model developing from personal models with own information to the joint models with population information, the prediction performance of proposed models become better and better. Meanwhile, the privacy issues of these models come into the view of community and the public: collecting and uploading private data to the centralized server without enough regulation. In this paper, we propose PMF, a privacy-preserving mobility prediction framework via federated learning, to solve this problem without significantly sacrificing the prediction performance. In our framework, based on the deep learning mobility model, no private data is uploaded into the centralized server and the only uploaded thing is the updated model parameters which are difficult to crack and thus more secure. Furthermore, we design a group optimization method for the training on local devices to achieve better trade-off between performance and privacy. Finally, we propose a fine-tuned personal adaptor for personal modelling to further improve the prediction performance. We conduct extensive experiments on three real-life mobility datasets to demonstrate the superiority and effectiveness of our methods in privacy protection settings.
- Published
- 2020
27. Facies-dependent early diagenesis and hydrothermal reworking in dolostones: a case study on upper Permian and lower Triassic in northeast Sichuan Basin
- Author
-
Zhongya Hu, Funing Sun, Zhiwei Liao, and Wenxuan Hu
- Subjects
Calcite ,Dolostone ,chemistry.chemical_compound ,chemistry ,Geochemistry and Petrology ,Dolomite ,Facies ,Ooid ,Geochemistry ,Carbonate ,Geology ,Hydrothermal circulation ,Diagenesis - Abstract
In this study, we systemically investigated the petrological features and geochemical compositions of dolostones in various sedimentary facies, to provide more understanding on the effects of facies-dependent diagenesis and hydrothermal reworking during the post-deposition stage. Microscopic observations and XRD analyses of carbonate were performed as well as analyses of C–O–Sr isotopic and elemental concentrations. Multiple evidence demonstrated that dolostones in the studied section underwent meteoric diagenesis and hydrothermal alterations. Effects of meteoric diagenesis were represented by meteoric dissolution, dedolomitization and calcite cementation, and varied along the downward migration of meteoric flow. Generally, meteoric dissolution mainly occurred in the exposure ooid shoal complex in the lower Triassic and accounted for the formation of mold pore, while in the underlying reef dolostones of the upper Permian, interparticle pores and cavities were mostly blocked by sparry calcite cement. Ooid dolostone layers in the lower Triassic exhibited low 87Sr/86Sr ratios and high Ba concentrations with saddle dolomite cement rimmed around the pore, demonstrating the relatively intense hydrothermal reworking. We inferred that high-permeability layers produced by early meteoric dissolution facilitated the migration of hydrothermal fluid and water–rock interaction in the burial stage. Petrologic observations indicated the hydrothermal reworking rearranged pore systems via regional transformation from dissolution to precipitation along the migration of fluid flows, and further enhanced the heterogeneity of the dolostone reservoir. Generally, the effects of early diagenesis and hydrothermal reworking in dolostones varied in dolostones of sedimentary facies, and high-quality dolostones reservoirs for oil and nature gas in this area formed as a result of the combined effects of early meteoric dissolution and hydrothermal reworking.
- Published
- 2021
28. Duration, evolution, and implications of volcanic activity across the Ordovician–Silurian transition in the Lower Yangtze region, South China
- Author
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Feng Zhu, Zhicheng Huang, Suping Yao, Shengchao Yang, Baoyu Jiang, Funing Sun, Wenxuan Hu, and Xiaolin Wang
- Subjects
Extinction event ,geography ,geography.geographical_feature_category ,010504 meteorology & atmospheric sciences ,Orogeny ,Volcanism ,010502 geochemistry & geophysics ,01 natural sciences ,Plate tectonics ,Paleontology ,Igneous rock ,Geophysics ,Volcano ,Space and Planetary Science ,Geochemistry and Petrology ,Earth and Planetary Sciences (miscellaneous) ,Ordovician ,Geology ,0105 earth and related environmental sciences ,Volcanic ash - Abstract
Volcanism provides a reliable record of local and global tectonic events and substantially influences both modern and ancient environments, climates, and the evolution of life. The Ordovician–Silurian (O–S) transition is a special period because intensive volcanism occurred globally, including in the Yangtze region of South China. Volcanic events during this period are a symptom of plate tectonic behaviour and are thought to be responsible for the remarkable changes in climate in the early Palaeozoic, though the relationships between these events remain unclear and controversial. Coeval igneous rocks and volcanic sediments (VS) are primarily used to resolve this issue. However, limited studies have been performed on VS from the O–S transition in South China. Recently, a typical VS-bearing section was found in the Lower Yangtze region, which contains ∼100 thin, interbedded volcanic ash layers across the O–S transition. Detailed petrographic and geochemical analyses of the volcanic ashes were conducted to determine their isotopic ages, magma sources, evolutionary processes, and tectonic settings. Our preliminary results suggest that volcanic eruptions in South China lasted for more than 22 Ma across the O–S boundary, from ∼449.3 ± 3.6 to 427.6 ± 4.1 Ma, where 445.14 Ma is the lowermost graptolite biozone for Metabolograptus extraordinarius, as well as the initiation of the Late Ordovician mass extinction (LOME) event in the Yangtze region. The evolutionary history of the parental magma was constructed from a depleted mantle source in the early stage and from a crustal source in the late stage, with several transitional features in the middle. The mantle source and arc-related geochemical indicators for the volcanic ashes support the disputed “subduction-collision orogeny” model. We propose that the strong volcanism in South China, accompanied by volcanism in numerous other regions worldwide, was an important trigger for the LOME and was likely responsible for oceanic 87Sr/ 86Sr fractionation and other climatic changes during the O–S transition.
- Published
- 2019
29. Conservative behavior of Mg isotopes in massive dolostones: From diagenesis to hydrothermal reworking
- Author
-
Funing Sun, Weiqiang Li, Wenxuan Hu, Yongli Liu, Chuan Liu, and Zhongya Hu
- Subjects
Dolostone ,010506 paleontology ,Carbonate platform ,Stratigraphy ,Dolomite ,Geochemistry ,Geology ,010502 geochemistry & geophysics ,01 natural sciences ,Hydrothermal circulation ,Diagenesis ,Dolomitization ,Ordovician ,Isotopes of magnesium ,0105 earth and related environmental sciences - Abstract
Mg isotopes in syndepositional dolomite have been suggested to be a potential proxy for understanding seawater chemistry. However, it is argued that the δ26Mg values of dolomite could be complicated by the effects of early diagenesis and later hydrothermal activities. Further investigations into the behaviors of Mg isotopes in dolomitization systems are needed to resolve this controversy. In the present study, we investigated early Ordovician dolostones from the Tarim Basin, including diagenetically altered dolomites, hydrothermally altered dolomites and well-preserved dolostones that precipitated in the slope, margin and interior of a carbonate platform. Different types of dolomites, bulk dolostone and limestone were sampled by microdrilling for analyses of C-O-Mg isotope compositions and REE concentrations. The dolostone δ13C values match those of coeval seawater, and the REE distribution patterns in the dolostones are comparable with those in the limestones, indicating that the dolostones originated from syndiagenetic dolomitization. The δ26Mg values of the various syndiagenetic dolomites that formed in the slope, margin and interior of the carbonate platform are similar, averaging approximately −2.06‰ ± 0.20‰. No stratigraphic variability in the dolomite Mg isotopes can be discerned, which implies that the Mg isotope compositions of the porewater were homogeneous during massive dolomitization and remained in equilibrium with seawater. Additionally, the δ26Mg values of the altered dolostone do not show correlations with diagenetic and hydrothermal signals, demonstrating that dolomite Mg isotopes are insensitive to postdepositional alteration. Given these facts, we propose that Mg isotopes in dolostones have conservative behaviors during diagenesis and late stage hydrothermal reworking.
- Published
- 2019
30. Micro/nanoscale pore structure and fractal characteristics of tight gas sandstone: A case study from the Yuanba area, northeast Sichuan Basin, China
- Author
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Feng Zhu, Jian Cao, Funing Sun, Wenxuan Hu, Yifeng Liu, and Zhenmeng Sun
- Subjects
Pore size ,020209 energy ,Stratigraphy ,Sichuan basin ,Mineralogy ,Geology ,Characterisation of pore space in soil ,02 engineering and technology ,010502 geochemistry & geophysics ,Oceanography ,01 natural sciences ,Fractal dimension ,Geophysics ,Fractal ,0202 electrical engineering, electronic engineering, information engineering ,Economic Geology ,Porosity ,Nanoscopic scale ,Tight gas ,0105 earth and related environmental sciences - Abstract
The pore size distribution (PSD) and fractal dimension are two typical parameters that are used to evaluate the heterogeneous characteristics of unconventional reservoir pores. The micro/nanoscale PSD and pore fractal-dimension characteristics of tight gas sandstones from the Upper Triassic Xujiahe formation in the Yuanba area were investigated by using nuclear magnetic resonance (NMR), nuclear magnetic resonance cryoporometry (NMRC), mercury injection capillary pressure (MICP) and scanning electronic microscopy (SEM) techniques. To date, no other attempts have been made to use NMRC with octamethylcyclotetrasiloxane (OMCTS) as a probe material to describe the pore fractal characteristics of tight gas sandstones. In this study, the fractal dimensions of tight gas sandstones were estimated by processing raw NMRC data with a fractal theoretical model, and the NMRC fractal results were compared to the calculated fractals from the MICP tube model, MICP sphere model and NMR T2 spectrum. The results consistently show that the pore fractal characteristics of tight sandstone samples from the Yuanba area exhibit multiple fractal structures at different pore-size ranges; large pores in the samples are more complex with rougher surfaces, and small pores correspond to smoother surfaces. Sandstones with greater porosity and pore space possess more heterogeneous structures. The PSD and fractal dimensions can be combined and used as an indicator for the presence of gas-bearing and dry formations in the study area. The tight sandstone samples from the dry formations have both lower porosities and smoother pore surfaces with smaller fractal dimensions; these characteristics may not be beneficial for the preservation of hydrocarbon fluids in the target area.
- Published
- 2018
31. Adaptive Spatio-Temporal Convolutional Network for Traffic Prediction
- Author
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Mingyang Zhang, Yong Li, Funing Sun, Diansheng Guo, Pan Hui, Bailey, J, Miettinen, P, Koh, YS, Tao, D, Wu, and Department of Computer Science
- Subjects
Traffic Prediction ,Graph Neural Network ,113 Computer and information sciences ,Spatio-temporal Model - Abstract
Traffic prediction is a crucial task in many real-world applications. The task is challenging due to the implicit and dynamic spatio-temporal dependencies among traffic data. On the one hand, the spatial dependencies among traffic flows are latent and fluctuate with environmental conditions. On the other hand, the temporal dependencies among traffic flows also vary significantly over time and locations. In this paper, we propose Adaptive Spatio-Temporal Convolutional Network (ASTCN) to tackle these challenges. First, we propose a spatial graph learning module that learns the dynamic spatial relations among traffic data based on multiple influential factors. Furthermore, we design an adaptive temporal convolution module that captures complex temporal traffic dependencies with environment-aware dynamic filters. We conduct extensive experiments on three real-world traffic datasets. The results demonstrate that the proposed ASTCN consistently outperforms state-of-the-arts.
- Published
- 2021
32. Isotopic evidence for the formation of 25-norhopanes via in situ biodegradation in the Permian Lucaogou shales, southern Junggar Basin
- Author
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Wenxuan Hu, Funing Sun, Zhirong Zhang, and Jian Cao
- Subjects
chemistry.chemical_compound ,δ13C ,chemistry ,Permian ,Geochemistry and Petrology ,Pristane ,Phytane ,Geochemistry ,Meteoric water ,Structural basin ,Oil shale ,Hopanoids - Abstract
Extracts of a set of the Permian Lucaogou shales collected from the southern Junggar Basin in NW China were examined for their molecular compositions and compound-specific isotopic signatures. The distribution of n-alkanes, isoprenoids, steranes, hopanes (C27 to C34) and appearance of 25-norhopanes (C26 to C33) were found to vary between samples, indicating that different degrees of biodegradation occurred in the shale strata. The non-biodegraded sample showed a complete composition of n-alkanes and isoprenoids including pristane (Pr) and phytane (Ph). Moderately biodegraded shales were characterized by near-absence of n-alkanes, but Pr and Ph still showed noticeable contents; 25-norhopanes were not detected. Heavily biodegraded shale had imperceptible content of n-alkanes, isoprenoids and steranes, but a series of abundant 25-norhopanes appeared. Compound-specific isotopic data show negative δ13C values (−44.4‰ to −55.6‰) for the regular hopanes having the same carbon number in all the examined shales, indicating a substantial contribution of methanotrophs to the sediments. Moreover, the 25-norhopanes had consistent δ13C values to the corresponding regular hopanes, which are proposed to be their parent molecules. The distributional and isotopic signatures indicate the 25-norhopanes in the heavily biodegraded Permian Lucaogou shales were genetically formed during in situ biodegradation of the extractable bitumen when the strata were uplifted from depth and may have been linked to the incursion of meteoric water.
- Published
- 2022
33. Supplemental Material: Methanogen microfossils and methanogenesis in Permian lake deposits
- Author
-
Wenxuan Hu and Funing Sun
- Subjects
biology ,Permian ,Methanogenesis ,Geochemistry ,biology.organism_classification ,Methanogen ,Geology - Abstract
Geological background, samples and methods, Figures S1–S7, and Tables S1–S3.
- Published
- 2020
34. A Sequential Convolution Network for Population Flow Prediction with Explicitly Correlation Modelling
- Author
-
Funing Sun, Ziqian Lin, Diansheng Guo, Yong Li, Jie Feng, and Tong Xia
- Subjects
Correlation ,education.field_of_study ,Flow (mathematics) ,Computer science ,Population ,Applied mathematics ,education ,Convolution - Abstract
Population flow prediction is one of the most fundamental components in many applications from urban management to transportation schedule. It is challenging due to the complicated spatial-temporal correlation.While many studies have been done in recent years, they fail to simultaneously and effectively model the spatial correlation and temporal variations among population flows. In this paper, we propose Convolution based Sequential and Cross Network (CSCNet) to solve them. On the one hand, we design a CNN based sequential structure with progressively merging the flow features from different time in different CNN layers to model the spatial-temporal information simultaneously. On the other hand, we make use of the transition flow as the proxy to efficiently and explicitly capture the dynamic correlation between different types of population flows. Extensive experiments on 4 datasets demonstrate that CSCNet outperforms the state-of-the-art baselines by reducing the prediction error around 7.7%∼10.4%.
- Published
- 2020
35. DeepMM
- Author
-
Lin Chen, Jie Feng, Tong Xia, Funing Sun, Diansheng Guo, Depeng Jin, Kai Zhao, Yong Li, and Zhao Xu
- Subjects
050210 logistics & transportation ,Schedule ,business.industry ,Computer science ,Deep learning ,05 social sciences ,Big data ,02 engineering and technology ,Map matching ,Machine learning ,computer.software_genre ,020204 information systems ,0502 economics and business ,0202 electrical engineering, electronic engineering, information engineering ,Trajectory ,Sequence learning ,Noise (video) ,Artificial intelligence ,business ,Hidden Markov model ,computer - Abstract
Map matching is important in many trajectory based applications like route optimization and traffic schedule, etc. As the widely used methods, Hidden Markov Model and its variants are well studied to provide accurate and efficient map matching service. However, HMM based methods fail to utilize the value of enormous trajectory big data, which are useful for the map matching task. Furthermore, with many following-up works, they are still easily influenced by the noisy records, which are very common in the real system. To solve these problems, we revisit the map matching task from the data perspective, and propose to utilize the great power of data to help solve these problems. We build a deep learning based model to utilize all the trajectory data for joint training and knowledge sharing. With the help of embedding techniques and sequence learning model with attention enhancement, our system does the map matching in the latent space, which is tolerant to the noise in the physical space. Extensive experiments demonstrate that our model outperforms the widely used HMM based methods more than 10% (absolute accuracy) and works robustly in the noisy settings in the meantime.
- Published
- 2019
36. Detecting Popular Temporal Modes in Population-scale Unlabelled Trajectory Data
- Author
-
Funing Sun, Tong Xia, Yong Li, Hancheng Cao, Fengli Xu, and Fanchao Meng
- Subjects
education.field_of_study ,Computer Networks and Communications ,Computer science ,business.industry ,Semantic feature ,Population ,Mode (statistics) ,Pattern recognition ,02 engineering and technology ,Pipeline (software) ,Human-Computer Interaction ,Hardware and Architecture ,020204 information systems ,0202 electrical engineering, electronic engineering, information engineering ,Trajectory ,020201 artificial intelligence & image processing ,Artificial intelligence ,Noise (video) ,education ,business ,Scale (map) ,Abstraction (linguistics) - Abstract
With the rapid process of urbanization, revealing the underlying mechanisms behind urban mobility has become a crucial research problem. The movements of urban dwellers are often constituted by their daily routines, and exhibit distinct and contextual temporal modes, i.e., the patterns of individuals allocating their time across different locations. In this paper, we investigate a novel problem of detecting popular temporal modes in population-scale unlabelled trajectory data. Our key finding is that the detected temporal modes capture the semantic feature of human's living style, and is able to unravel meaningful correlations between urban mobility and human behavior. Specifically, we represent the temporal mode of a trajectory as a partition of the time duration, where the time slices associated with same locations are partitioned into same subsets. Such abstraction decouples the temporal modes from actual physical locations, and allows individuals with similar temporal modes yet completely different physical locations to have similar representations. Based on this insight, we propose a pipeline system composed of three components: 1) noise handler that eliminates the noises in the raw mobility records, 2) representation extractor for temporal modes, and 3) popular temporal modes detector. By applying our system on three real-world mobility datasets, we demonstrate that our system effectively detects the popular temporal modes embedded in population-scale mobility datasets, which is easy to be interpreted and can be justified through the associated PoIs and mobile applications usage. More importantly, our further experiments reveal insightful correlations between the popular temporal modes and individuals' social economic status, i.e. occupation information, which sheds light on the mechanisms behind urban mobility.
- Published
- 2018
37. State-Sharing Sparse Hidden Markov Models for Personalized Sequences
- Author
-
Chao Zhang, Yong Li, Quanming Yao, Depeng Jin, Funing Sun, and Hongzhi Shi
- Subjects
Optimization problem ,business.industry ,Estimation theory ,Computer science ,Stochastic matrix ,Machine learning ,computer.software_genre ,Set (abstract data type) ,Convex optimization ,Artificial intelligence ,State (computer science) ,business ,Hidden Markov model ,computer - Abstract
Hidden Markov Model (HMM) is a powerful tool that has been widely adopted in sequence modeling tasks, such as mobility analysis, healthcare informatics, and online recommendation. However, using HMM for modeling personalized sequences remains a challenging problem: training a unified HMM with all the sequences often fails to uncover interesting personalized patterns; yet training one HMM for each individual inevitably suffers from data scarcity. We address this challenge by proposing a state-sharing sparse hidden Markov model (S3HMM) that can uncover personalized sequential patterns without suffering from data scarcity. This is achieved by two design principles: (1) all the HMMs in the ensemble share the same set of latent states; and (2) each HMM has its own transition matrix to model the personalized transitions. The result optimization problem for S3HMM becomes nontrivial, because of its two-layer hidden state design and the non-convexity in parameter estimation. We design a new Expectation-Maximization algorithm based, which treats the difference of convex programming as a sub-solver to optimize the non-convex function in the M-step with convergence guarantee. Our experimental results show that, S3HMM can successfully uncover personalized sequential patterns in various applications and outperforms baselines significantly in downstream prediction tasks.
- Published
- 2019
38. Understanding Urban Dynamics via State-sharing Hidden Markov Model
- Author
-
Fengli Xu, Funing Sun, Diansheng Guo, Depeng Jin, Tong Xia, Yue Yu, and Yong Li
- Subjects
Urban region ,education.field_of_study ,Computer science ,business.industry ,Population ,02 engineering and technology ,Machine learning ,computer.software_genre ,Task (project management) ,Dynamics (music) ,020204 information systems ,0202 electrical engineering, electronic engineering, information engineering ,020201 artificial intelligence & image processing ,Point (geometry) ,State (computer science) ,Artificial intelligence ,education ,Hidden Markov model ,business ,computer - Abstract
Modeling people's activities in the urban space is a crucial socio-economic task but extremely challenging due to the deficiency of suitable methods. To model the temporal dynamics of human activities concisely and specifically, we present State-sharing Hidden Markov Model (SSHMM). First, it extracts the urban states from the whole city, which captures the volume of population flows as well as the frequency of each type of Point of Interests (PoIs) visited. Second, it characterizes the urban dynamics of each urban region as the state transition on the shared-states, which reveals distinct daily rhythms of urban activities. We evaluate our method via a large-scale real-life mobility dataset and results demonstrate that SSHMM learns semantics-rich urban dynamics, which are highly correlated with the functions of the region. Besides, it recovers the urban dynamics in different time slots with an error of 0.0793, which outperforms the general HMM by 54.2%.
- Published
- 2019
39. No More than What I Post: Preventing Linkage Attacks on Check-in Services
- Author
-
Zhen Tu, Shuhao Chang, Yong Li, Funing Sun, Fengli Xu, Hongjia Huang, and Diansheng Guo
- Subjects
Check-in ,Computer science ,Flourishing ,020206 networking & telecommunications ,02 engineering and technology ,Linkage (mechanical) ,Computer security ,computer.software_genre ,law.invention ,law ,020204 information systems ,0202 electrical engineering, electronic engineering, information engineering ,Baseline (configuration management) ,computer - Abstract
With the flourishing of location based social networks, posting check-ins has become a common practice to document one's daily life. Users usually do not consider check-in records as violations of their privacy. However, through analyzing two real-world check-in datasets, our study shows that check-in records are vulnerable to linkage attacks. To address this problem, we design a partition-and-group framework to integrate the information of check-ins and additional mobility data to attain a novel privacy criterion - kt, l-anonymity. It ensures adversaries with arbitrary background knowledge cannot use check-ins to re-identify users in other anonymous datasets or learning unreported mobility records. The proposed framework achieves favorable performance against state-of-art baseline in terms of improving check-in utility by 24% ~ 57% while providing stronger privacy guarantee at the same time. We believe this study will open a new angle in attaining both privacy-preserving and useful check-in services.
- Published
- 2019
40. Semantics-Aware Hidden Markov Model for Human Mobility
- Author
-
Vassilis Kostakos, Fanchao Meng, Funing Sun, Hancheng Cao, Chao Zhang, Hongzhi Shi, Yong Li, and Xiangxin Zhou
- Subjects
Mobility model ,business.industry ,Computer science ,Individual mobility ,020206 networking & telecommunications ,02 engineering and technology ,Semantics ,Machine learning ,computer.software_genre ,Similarity (psychology) ,0202 electrical engineering, electronic engineering, information engineering ,Trajectory ,Embedding ,020201 artificial intelligence & image processing ,Artificial intelligence ,Hidden Markov model ,business ,Cluster analysis ,computer - Abstract
Understanding human mobility bene ts numerous applications such as urban planning, tra c control and city management. Previous work mainly focuses on modeling spatial and temporal patterns of human mobility. However, the semantics of trajectory are ignored, thus failing to model people's motivation behind mobility. In this paper, we propose a novel semantics-aware mobility model that captures human mobility motivation using large-scale semantics-rich spatialtemporal data from location-based social networks. In our system, we rst develop a multimodal embedding method to project user, location, time, and activity on the same embedding space in an unsupervised way while preserving original trajectory semantics. Then, we use hidden Markov model to learn latent states and transitions between them in the embedding space, which is the location embedding vector, to jointly consider spatial, temporal, and user motivations. In order to tackle the sparsity of individual mobility data, we further propose a von Mises-Fisher mixture clustering for user grouping so as to learn a reliable and ne-grained model for groups of users sharing mobility similarity. We evaluate our proposed method on two large-scale real-world datasets, where we validate the ability of our method to produce high-quality mobility models. We also conduct extensive experiments on the speci c task of location prediction. The results show that our model outperforms state-of-the-art mobility models with higher prediction accuracy and much higher efciency.
- Published
- 2019
41. Two-stage mineral dissolution and precipitation related to organic matter degradation: Insights from in situ C–O isotopes of zoned carbonate cements
- Author
-
Bin Fu, Haiguang Wu, Zhongya Hu, Xiaolin Wang, Funing Sun, Jian Cao, Shengchao Yang, Yong Tang, and Wenxuan Hu
- Subjects
chemistry.chemical_classification ,Calcite ,010504 meteorology & atmospheric sciences ,δ18O ,Stratigraphy ,Dolomite ,Geochemistry ,Carbonate minerals ,Geology ,010502 geochemistry & geophysics ,Oceanography ,01 natural sciences ,Diagenesis ,chemistry.chemical_compound ,Geophysics ,chemistry ,Carbonate ,Economic Geology ,Organic matter ,Ankerite ,0105 earth and related environmental sciences - Abstract
Mineral dissolution and precipitation, particularly of carbonate minerals, are ubiquitous and significant diagenetic processes in sedimentary rocks. However, the impacts of organic matter degradation on these processes in single systems remain unclear because the timing and fluid sources during progressive burial are poorly constrained. To address this issue, in situ C–O isotope analyses were conducted for zoned dolomite–ankerite/calcite cements from the Permian Lucaogou Formation in the Junggar Basin, China, using secondary ion mass spectrometry (SIMS) combined with mineralogical and elemental analyses. Carbonate minerals can be divided into early-stage and late-stage precipitations based on distinct variations in δ18O (−18.3 to −0.7‰ V-PDB), δ13C (−3.6 to +20.8‰ V-PDB), and Fe content (Fe# ranging from 0.002 to 0.373). The chemo-isotopically zoned carbonate cements record the thermal and chemical conditions of pore fluids during the burial process. The difference in δ18O values between the early and late precipitation (i.e., Δ18O [early–late]) of 11.9‰, and the difference in δ13C values (i.e., Δ13C [early–late]) of 11.7‰, reveal significant changes in precipitation temperatures and the availability of carbon sources, respectively. Early-stage precipitation occurred in association with microbial methanogenesis at lower temperatures (~25 °C) during shallow burial (~300 m), whereas late-stage precipitation was related to thermally-induced decarboxylation at higher temperatures (~90 °C or ~110 °C) during deep burial (~2500 m or ~3200 m). These two stages of dissolved pore-filling precipitation correspond to two major periods of dissolution (i.e., eogenetic and mesogenetic dissolution). Diagenetic fluids, mainly CO2 and/or organic acids, were derived from the biological and thermal degradation of organic matter, respectively. These results constrain the isotopic responses of carbonates to organic matter degradation with increasing burial depth and provide significant insights into carbonate diagenesis in organic-rich sedimentary sequences.
- Published
- 2021
42. Constraints on the accumulation of organic matter in Upper Ordovician-lower Silurian black shales from the Lower Yangtze region, South China
- Author
-
Shengchao Yang, Wenxuan Hu, Weihui He, Feng Zhu, Yin Wang, Suping Yao, Xiaolin Wang, and Funing Sun
- Subjects
chemistry.chemical_classification ,010504 meteorology & atmospheric sciences ,Stratigraphy ,Geochemistry ,Geology ,Biozone ,010502 geochemistry & geophysics ,Oceanography ,01 natural sciences ,Katian ,Geophysics ,chemistry ,Ordovician ,Period (geology) ,Upwelling ,Economic Geology ,Organic matter ,Energy source ,0105 earth and related environmental sciences ,Zircon - Abstract
The Late Ordovician to early Silurian (O/S) was an important period in which many significant geological events occurred. During the O/S transition, organic-rich black shales were widely deposited and became important unconventional energy sources. Paleoproductivity, detrital input, and redox conditions are the three major factors controlling organic matter (OM) accumulation. Although the effect of each factor is relatively clear, the complex influences of these factors remain poorly understood. Specifically, the evolution of these factors and the corresponding influence on the accumulation of OM during the O/S transition has not yet been systematically investigated. This paper investigates the constraints on OM accumulation in O/S transition black shales from the Lower Yangtze region, based on graptolite fossil identification, zircon U–Pb dating, and geochemical analyses of a well sequenced drilling profile. The results show that (i) the SY-1 core sequence was well constrained from graptolite zones WF2 (447.62 Ma) to LM5 (441.57 Ma) across the O/S boundary, with decreasing sedimentation rates (SRs) in the upper Katian (WF2 to WF3) and increasing SRs in the lower Rhuddanian; (ii) complementary volcanic inputs (Katian and Rhuddanian) and upwelling events (Hirnantian) exerted strong control over paleoproductivity; (iii) orogenic processes in South China controlled detrital inputs and redox conditions; (iv) OM accumulation in the Lower Yangtze area across the O/S transition occurred in three stages. In stage 1 (WF2–WF3), strong volcanism boosted productivity, whereas OM preservation was not favored in the oxic environment. In stage 2 (WF4–LM3), upwelling and volcanism resulted in high productivity and provided the optimal configurations for OM enrichment. In stage 3 (LM4 and later), rare OM was preserved due to terrestrial dilution and unfavorable preservation conditions. Eventually, WF4–LM3 became the prominent OM-rich biozones due to the effective coordination of the controlling factors, namely upwelling, volcanism, and redox conditions.
- Published
- 2020
43. DeepMove
- Author
-
Funing Sun, Ang Guo, Chao Zhang, Fanchao Meng, Yong Li, Jie Feng, and Depeng Jin
- Subjects
Artificial neural network ,Computer science ,business.industry ,02 engineering and technology ,Machine learning ,computer.software_genre ,Recurrent neural network ,020204 information systems ,0202 electrical engineering, electronic engineering, information engineering ,Trajectory ,Embedding ,020201 artificial intelligence & image processing ,Artificial intelligence ,business ,computer - Abstract
Human mobility prediction is of great importance for a wide spectrum of location-based applications. However, predicting mobility is not trivial because of three challenges: 1) the complex sequential transition regularities exhibited with time-dependent and high-order nature; 2) the multi-level periodicity of human mobility; and 3) the heterogeneity and sparsity of the collected trajectory data. In this paper, we propose DeepMove, an attentional recurrent network for mobility prediction from lengthy and sparse trajectories. In DeepMove, we first design a multi-modal embedding recurrent neural network to capture the complicated sequential transitions by jointly embedding the multiple factors that govern the human mobility. Then, we propose a historical attention model with two mechanisms to capture the multi-level periodicity in a principle way, which effectively utilizes the periodicity nature to augment the recurrent neural network for mobility prediction. We perform experiments on three representative real-life mobility datasets, and extensive evaluation results demonstrate that our model outperforms the state-of-the-art models by more than 10%. Moreover, compared with the state-of-the-art neural network models, DeepMove provides intuitive explanations into the prediction and sheds light on interpretable mobility prediction.
- Published
- 2018
44. Methanogen microfossils and methanogenesis in Permian lake deposits.
- Author
-
Funing Sun, Wenxuan Hu, Xiaolin Wang, Jian Cao, Bin Fu, Haiguang Wu, and Shengchao Yang
- Subjects
- *
LAKE sediments , *FOSSILS , *FOSSIL microorganisms , *BIOINDICATORS , *METHANOGENS , *DOLOMITE - Abstract
Methanogens are methane-producing archaea (some of the most primitive organisms on Earth), which possess great phylogenetic and ecological diversity in modern ecosystems. However, cellular fossil evidence of methanogens remains extremely scarce throughout the geological record. Here, we report a new population of spheroidal microstructures composed of dolomite observed in Permian lake deposits in northwestern China. The microspheres exhibit indicators of biological affinity and are well preserved in authigenic dolomite with cellular fidelity. Based on morphological and geochemical evidence, these microspheres are interpreted as fossilized cells of methanogenic archaea, which can be divided into three size-based taxa. These microfossils are the first fossil record of spheroidal methanogens. The microfossil-bearing dolomite exhibits extremely positive δ13C values (up to +20‰ relative to Vienna Peedee belemnite) that are attributed to microbial methanogenesis. The results suggest that methanogens were a significant component of this Permian lake biosphere. As a consequence of the metabolic activity of the methanogens, a large amount of biogenic methane was produced through methanogenesis in the anoxic lake sediments. This study not only fills a gap in the fossil record of methanogenic archaea, but it also provides new insights into methane emissions from ancient lakes. [ABSTRACT FROM AUTHOR]
- Published
- 2021
- Full Text
- View/download PDF
45. High-Throughput Isolation of Bacteriocin-Producing Lactic Acid Bacteria, with Potential Application in the Brewing Industry
- Author
-
Douwe van Sinderen, Susan Rouse, Funing Sun, and Anne Vaughan
- Subjects
biology ,Strain (chemistry) ,business.industry ,technology, industry, and agriculture ,food and beverages ,Pediococcus acidilactici ,biology.organism_classification ,16S ribosomal RNA ,Antimicrobial ,Lactic acid ,chemistry.chemical_compound ,Bacteriocin ,chemistry ,Brewing ,Food science ,business ,Bacteria ,Food Science - Abstract
J. Inst. Brew. 113(3), 256–262, 2007 Lactic acid bacteria (LAB) were isolated from malted cereals by means of a high-throughput screening approach and investigated for antimicrobial activity against a range of beer-spoiling bacteria. Putative bacteriocin-producing strains were identified by 16S rRNA analysis and the inhibitory compounds were partially characterized. Following determination of the inhibitory spectra of the strains, an unspeciated Lactobacillus sp. UCC128, with inhibitory activity against a range of beer-spoiling strains was subjected to further characterization. A bacteriocin was purified from this strain and analyzed by mass spectrometry to determine the weight of the protein. The result indicated that the bacteriocin was highly similar to pediocin AcH /PA-1 from Pediococcus acidilactici. The bacteriocin-producers identified in this study have the potential to be used in the brewing industry to enhance the microbiological stability of beer in conjunction with hurdles already in place in the brewing process.
- Published
- 2007
46. A Novel Prefix-Based Patching Algorithm for Streaming Media in WiBro System
- Author
-
Funing Sun, Young-Jin Kim, Wei Yang, and Changlong Xu
- Subjects
business.industry ,Computer science ,Real-time computing ,Mobile computing ,Volume (computing) ,Window (computing) ,WiBro ,IPTV ,computer.software_genre ,Proxy server ,Prefix ,Mobile IPTV ,business ,Algorithm ,computer ,Computer network - Abstract
In this paper, a novel prefix-based patching algorithm named DP2 (Dynamic Prefix-based Patching algorithm) is proposed for mobile IPTV service in the WiBro system. Proposed algorithm increase the resource utilization of wireless bandwidth and server. It uses the prefix caching in proxy server to batch those requests that demand the same video. This algorithm just requires the mobile terminal can receive two streams at the same time. The threshold is also introduced in the novel algorithm to control the frequency of regular streams initiated. Then the optimized patching window is derived. A mobile IPTV structure for this algorithm is also proposed, which uses the MBS technique. Finally simulation result show that DP2 algorithm can reduce the data volume and patching streams significantly compares to the DS2AM2PC algorithm.
- Published
- 2012
47. Comparative metagenomic analysis of plasmid encoded functions in the human gut microbiome
- Author
-
Julian R. Marchesi, Brian V. Jones, and Funing Sun
- Subjects
Adult ,DNA, Bacterial ,Male ,lcsh:QH426-470 ,Firmicutes ,lcsh:Biotechnology ,Population ,Bacterial Toxins ,Molecular Sequence Data ,Addiction module ,Biology ,Q1 ,Genome ,digestive system ,03 medical and health sciences ,Open Reading Frames ,Plasmid ,lcsh:TP248.13-248.65 ,Genetics ,Humans ,Microbiome ,Amino Acid Sequence ,education ,Phylogeny ,030304 developmental biology ,0303 health sciences ,education.field_of_study ,Comparative Genomic Hybridization ,Bacteria ,030306 microbiology ,Sequence Analysis, DNA ,biology.organism_classification ,Gastrointestinal Tract ,lcsh:Genetics ,Metagenomics ,Horizontal gene transfer ,Metagenome ,Sequence Alignment ,Genome, Bacterial ,Biotechnology ,Research Article ,Plasmids - Abstract
Background Little is known regarding the pool of mobile genetic elements associated with the human gut microbiome. In this study we employed the culture independent TRACA system to isolate novel plasmids from the human gut microbiota, and a comparative metagenomic analysis to investigate the distribution and relative abundance of functions encoded by these plasmids in the human gut microbiome. Results Novel plasmids were acquired from the human gut microbiome, and homologous nucleotide sequences with high identity (>90%) to two plasmids (pTRACA10 and pTRACA22) were identified in the multiple human gut microbiomes analysed here. However, no homologous nucleotide sequences to these plasmids were identified in the murine gut or environmental metagenomes. Functions encoded by the plasmids pTRACA10 and pTRACA22 were found to be more prevalent in the human gut microbiome when compared to microbial communities from other environments. Among the most prevalent functions identified was a putative RelBE toxin-antitoxin (TA) addiction module, and subsequent analysis revealed that this was most closely related to putative TA modules from gut associated bacteria belonging to the Firmicutes. A broad phylogenetic distribution of RelE toxin genes was observed in gut associated bacterial species (Firmicutes, Bacteroidetes, Actinobacteria and Proteobacteria), but no RelE homologues were identified in gut associated archaeal species. We also provide indirect evidence for the horizontal transfer of these genes between bacterial species belonging to disparate phylogenetic divisions, namely Gram negative Proteobacteria and Gram positive species from the Firmicutes division. Conclusions The application of a culture independent system to capture novel plasmids from the human gut mobile metagenome, coupled with subsequent comparative metagenomic analysis, highlighted the unexpected prevalence of plasmid encoded functions in the gut microbial ecosystem. In particular the increased relative abundance and broad phylogenetic distribution was identified for a putative RelBE toxin/antitoxin addiction module, a putative phosphohydrolase/phosphoesterase, and an ORF of unknown function. Our analysis also indicates that some plasmids or plasmid families are present in the gut microbiomes of geographically isolated human hosts with a broad global distribution (America, Japan and Europe), and are potentially unique to the human gut microbiome. Further investigation of the plasmid population associated with the human gut is likely to provide important insights into the development, functioning and evolution of the human gut microbiota.
- Published
- 2010
48. Comparative metagenomic analysis of plasmid encoded functions in the human gut microbiome.
- Author
-
Jones, Brian V, Funing Sun, and Marchesi, Julian R
- Subjects
- *
GENOMICS , *PLASMIDS , *CYTOPLASMIC inheritance , *MOBILE genetic elements , *BACTERIAL genomes - Abstract
Background: Little is known regarding the pool of mobile genetic elements associated with the human gut microbiome. In this study we employed the culture independent TRACA system to isolate novel plasmids from the human gut microbiota, and a comparative metagenomic analysis to investigate the distribution and relative abundance of functions encoded by these plasmids in the human gut microbiome. Results: Novel plasmids were acquired from the human gut microbiome, and homologous nucleotide sequences with high identity (>90%) to two plasmids (pTRACA10 and pTRACA22) were identified in the multiple human gut microbiomes analysed here. However, no homologous nucleotide sequences to these plasmids were identified in the murine gut or environmental metagenomes. Functions encoded by the plasmids pTRACA10 and pTRACA22 were found to be more prevalent in the human gut microbiome when compared to microbial communities from other environments. Among the most prevalent functions identified was a putative RelBE toxin-antitoxin (TA) addiction module, and subsequent analysis revealed that this was most closely related to putative TA modules from gut associated bacteria belonging to the Firmicutes. A broad phylogenetic distribution of RelE toxin genes was observed in gut associated bacterial species (Firmicutes, Bacteroidetes, Actinobacteria and Proteobacteria), but no RelE homologues were identified in gut associated archaeal species. We also provide indirect evidence for the horizontal transfer of these genes between bacterial species belonging to disparate phylogenetic divisions, namely Gram negative Proteobacteria and Gram positive species from the Firmicutes division. Conclusions: The application of a culture independent system to capture novel plasmids from the human gut mobile metagenome, coupled with subsequent comparative metagenomic analysis, highlighted the unexpected prevalence of plasmid encoded functions in the gut microbial ecosystem. In particular the increased relative abundance and broad phylogenetic distribution was identified for a putative RelBE toxin/antitoxin addiction module, a putative phosphohydrolase/phosphoesterase, and an ORF of unknown function. Our analysis also indicates that some plasmids or plasmid families are present in the gut microbiomes of geographically isolated human hosts with a broad global distribution (America, Japan and Europe), and are potentially unique to the human gut microbiome. Further investigation of the plasmid population associated with the human gut is likely to provide important insights into the development, functioning and evolution of the human gut microbiota. [ABSTRACT FROM AUTHOR]
- Published
- 2010
- Full Text
- View/download PDF
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