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| 1 | Ionic composition of submicron particles(PM_(1.0)) during the long-lasting haze period in January 2013 in Wuhan, central China显示文摘In January 2013, a long-lasting severe haze episode occurred in Northern and Central China; at its maximum, it covered a land area of approximately 1.4 million km2. In Wuhan, the largest city in Central China, this event was the most severe haze episode in the 21st century. Aerosol samples of submicron particles(PM1.0) were collected during the long-lasting haze episode at an urban site and a suburban site in Wuhan to investigate the ion characteristics of PM1.0 in this area. The mass concentrations of PM1.0 and its water-soluble inorganic ions(WSIIs) were almost at the same levels at two sites, which indicates that PM1.0 pollution occurs on a regional scale in Wuhan. WSIIs(Na+, NH+ 4, K+, Mg2+, Ca2+, Cl-, NO-3and SO2-4) were the dominant chemical species and constituted up to 48.4% and 47.4% of PM1.0 at WD and TH, respectively. The concentrations of PM1.0 and WSIIs on haze days were approximately two times higher than on normal days. The ion balance calculations indicate that the particles were more acidic on haze days than on normal days. The results of the back trajectory analysis imply that the high concentrations of PM1.0 and its water-soluble inorganic ions may be caused by stagnant weather conditions in Wuhan. | Hairong Cheng Wei Gong Zuwu Wang Fan Zhang Xinming Wang Xiaopu Lv Jia Liu Xiaoxin Fu Gan Zhang | 2014 | Journal of Environmental Sciences2014，26，4： | 15 |
| 2 | Geoscience knowledge graph in the big data era显示文摘Since the beginning of the 21 st century,the geoscience research has been entering a significant transitional period with the establishment of a new knowledge system as the core and with the drive of big data as the means.It is a revolutionary leap in the research of geoscience knowledge discovery from the traditional encyclopedic discipline knowledge system to the computer-understandable and operable knowledge graph.Based on adopting the graph pattern of general knowledge representation,the geoscience knowledge graph expands the unique spatiotemporal features to the Geoscience knowledge,and integrates geoscience knowledge elements,such as map,text,and number,to establish an all-domain geoscience knowledge representation model.A federated,crowd intelligence-based collaborative method of constructing the geoscience knowledge graph is developed here,which realizes the construction of high-quality professional knowledge graph in collaboration with global geo-scientists.We also develop a method for constructing a dynamic knowledge graph of multi-modal geoscience data based on in-depth text analysis,which extracts geoscience knowledge from massive geoscience literature to construct the latest and most complete dynamic geoscience knowledge graph.A comprehensive and systematic geoscience knowledge graph can not only deepen the existing geoscience big data analysis,but also advance the construction of the high-precision geological time scale driven by big data,the compilation of intelligent maps driven by rules and data,and the geoscience knowledge evolution and reasoning analysis,among others.It will further expand the new directions of geoscience research driven by both data and knowledge,break new ground where geoscience,information science,and data science converge,realize the original innovation of the geoscience research and achieve major theoretical breakthroughs in the spatiotemporal big data research. | Chenghu ZHOU Hua WANG Chengshan WANG Zengqian HOU Zhiming ZHENG Shuzhong SHEN Qiuming CHENG Zhiqiang FENG Xinbing WANG Hairong LV Junxuan FAN Xiumian HU Mingcai HOU Yunqiang ZHU | 2021 | Science China Earth Sciences2021，64，7： | 4 |
| 3 | Trace element concentrations inhair of healthy Chinese centenarians显示文摘 | LI Yonghua YANG Linsheng WANGWuyi LI Hairong LV Jinmei ZOU Xiaoyan | 2011 | Science of the TotalEnvironment2011，409，8： | 1 |
| 4 | Off-line Chinese signature verification based on support vector machines显示文摘 | Lv Hairong Wang Wenyuan Chong Wang | 2005 | Pattern Recognition Letters2005，26，： | 1 |
| 5 | A systems biology approach identifies a regulator,BplERF1,of cold tolerance in Betula platyphylla显示文摘Cold is an abiotic stress that can greatly affect the growth and survival of plants.Here,we reported that an AP2/ERF family gene,BplERF1,isolated from Betula platyphylla played a contributing role in cold stress tolerance.Overexpression of BplERF1 in B.platyphylla transgenic lines enhanced cold stress tolerance by increasing the scavenging capability and reducing H_(2)O_(2) and malondialdehyde(MDA)content in transgenic plants.Construction of BplERF-mediated multilayered hierarchical gene regulatory network(ML-hGRN),using Top-down GGM algorithm and the transcriptomic data of BplERF1 overexpression lines,led to the identification of five candidate target genes of BplERF1 which include MPK20,ERF9,WRKY53,WRKY70,and GIA1.All of them were then verified to be the true target genes of BplERF1 by chromatin-immunoprecipitation PCR(ChIP-PCR)assay.Our results indicate that BplERF1 is a positive regulator of cold tolerance and is capable of exerting regulation on the expression of cold signaling and regulatory genes,causing mitigation of reactive oxygen species. | Kaiwen Lv Wenqi Wu Hairong Wei Guifeng Liu | 2021 | Forestry Research2021，1，1： | 1 |
| 6 | Hydrogenation of dimethyl oxalate to ethylene glycol on a Cu/SiO2/cordierite monolithic catalyst: Enhanced internal mass transfer and stability显示文摘 | Hairong Yue Yujun Zhao Li Zhao Jing Lv Shengping Wang Jinlong Gong Xinbin Ma | 2011 | AIChE J2011，，9： | 1 |
| 7 | Hydrogenation of dimethyl oxalate to ethylene glycol over mesoporous Cu ‐ MCM ‐41 catalysts显示文摘 | Xinbin Ma Hanwen Chi Hairong Yue Yujun Zhao Yan Xu Jing Lv Shengping Wang Jinlong Gong | 2013 | AIChE J2013，，7： | 1 |
| 8 | NUA and ESD4 negatively regulate ABA signaling during seed germination显示文摘The phytohormone abscisic acid(ABA)plays important roles in plant growth,development and adaptative responses to abiotic stresses.SNF1-related protein kinase 2s(SnRK2)are key components that activate the ABA core signaling pathway.NUCLEAR PORE ANCHOR(NUA)is a component of the nuclear pore complex(NPC)that involves in deSU-MOylation through physically interacting with the EARLY IN SHORT DAYS 4(ESD4)SUMO protease.However,it is not clear how NUA functions with SnRK2 and ESD4 to regulate ABA signaling.In our study,we found that nua loss-of-function mutants exhibited pleiotropic ABA-hypersensitive phenotype.We also found that ABA-responsive genes remarkably up-regulated in nua by exogenous ABA.The nua snrk2.2 snrk2.3 triple mutant and nua abi5 double mutant partially rescued the ABA-hypersensitive phenotype of nua,thereby suggesting that NUA is epistatic to SnRK2s.Additionally,we observed that esd4-3 mutant was also ABA-hypersensitive.NUA and ESD4 were further demonstrated to physically interact with SnRK2s and negatively regulate ABA signaling by reducing SnRK2s stability.Taken together,our findings uncover a new regulatory mechanism that can modulate ABA signaling. | Xiaona Cui Mengyang Lv Yuanyuan Cao Ziwen Li Yan Liu Zhenzhen Ren Hairong Zhang | 2022 | Stress Biology2022，2，1： | 1 |
| 9 | Offline Chinese signature verification based on support vectormachines显示文摘 | LV HAIRONG WANG WENYUAN WANG CHONG | 2005 | Pat- tern Recognition2005，26，： | 1 |
| 10 | Chemoselective synthesis of ethanol via hydrogenation of dimethyl oxalate on Cu/SiO 2 : Enhanced stability with boron dopant显示文摘 | Shuo Zhao Hairong Yue Yujun Zhao Bo Wang Yaochen Geng Jing Lv Shengping Wang Jinlong Gong Xinbin Ma | 2013 | Journal of Catalysis2013，，： | 1 |
| 11 | The graft copolymerization of corn starch by microwave irradiation with rheological phase reaction 显示文摘 | Han Dawei Wang Jiankun Lv Hairong | 2011 | Journal of Applied Polymer Science2011，121，8： | 1 |
| 12 | An adaptive representation model for geoscience knowledge graphs considering complex spatiotemporal features and relationships显示文摘Geoscience knowledge graph(GKG)can organize various geoscience knowledge into a machine understandable and computable semantic network and is an effective way to organize geoscience knowledge and provide knowledge-related services.As a result,it has gained significant attention and become a frontier in geoscience.Geoscience knowledge is derived from many disciplines and has complex spatiotemporal features and relationships of multiple scales,granularities,and dimensions.Therefore,establishing a GKG representation model conforming to the characteristics of geoscience knowledge is the basis and premise for the construction and application of GKG.However,existing knowledge graph representation models leverage fixed tuples that are limited in fully representing complex spatiotemporal features and relationships.To address this issue,this paper first systematically analyzes the categorization and spatiotemporal features and relationships of geoscience knowledge.On this basis,an adaptive representation model for GKG is proposed by considering the complex spatiotemporal features and relationships.Under the constraint of a unified spatiotemporal ontology,this model adopts different tuples to adaptively represent different types of geoscience knowledge according to their spatiotemporal correlation.This model can efficiently represent geoscience knowledge,thereby avoiding the isolation of the spatiotemporal feature representation and improving the accuracy and efficiency of geoscience knowledge retrieval.It can further enable the alignment,transformation,computation,and reasoning of spatiotemporal information through a spatiotemporal ontology. | Yunqiang ZHU Kai SUN Shu WANG Chenghu ZHOU Feng LU Hairong LV Qinjun QIU Xinbing WANG Yanmin QI | 2023 | Science China Earth Sciences2023，66，11： | 0 |
| 13 | Toward a unified information framework for cell atlas assembly显示文摘Cells are the basic structural and functional unit of the human body.Virtually all cells of a human body possess the same genome,but they exhibit colorful heterogeneities in phenotypes and functions.The heterogeneities include rich paerns and variabilities in the transcriptomic,epigenomic and proteomic features of the cells.Building an atlas of human cells with the biomolecular properties of all cell types in all organs is essential for understanding the human body;and will provide a fundamental reference for studies on human health and diseases. | Sijie Chen Yanting Luo Haoxiang Gao Fanhong Li Jiaqi Li Yixin Chen Renke You Hairong Lv Kui Hua Rui Jiang Xuegong Zhang | 2022 | National Science Review2022，9，3： | 0 |
| 14 | Building digital life systems for future biology and medicine显示文摘The rapid development of biological technology (BT) and information technology (IT) especially of genomics and artificial intelligence (AI) is bringing great potential for revolutionizing future medicine. We propose the concept and framework of Digital Life Systems or dLife as a new paradigm to unleash this potential. It includes the multi-scale and multi-granule measure and representation of life in the digital space, the mathematical and/or computational modeling of the biology behind physiological and pathological processes, and ultimately cyber twins of healthy or diseased human body in the virtual space that can be used to simulate complex biological processes and deduce effects of medical treatments. We advocate that dLife is the route toward future AI precision medicine and should be the new paradigm for future biological and medical research. | Xuegong Zhang Lei Wei Rui Jiang Xiaowo Wang Jin Gu Zhen Xie Hairong Lv | 2023 | Quantitative Biology2023，11，3： | 0 |
| 15 | DeepCAPE: A Deep Convolutional Neural Network for the Accurate Prediction of Enhancers显示文摘The establishment of a landscape of enhancers across human cells is crucial to deciphering the mechanism of gene regulation,cell differentiation,and disease development.High-throughput experimental approaches,which contain successfully reported enhancers in typical cell lines,are still too costly and time-consuming to perform systematic identification of enhancers specific to different cell lines.Existing computational methods,capable of predicting regulatory elements purely relying on DNA sequences,lack the power of cell line-specific screening.Recent studies have suggested that chromatin accessibility of a DNA segment is closely related to its potential function in regulation,and thus may provide useful information in identifying regulatory elements.Motivated by the aforementioned understanding,we integrate DNA sequences and chromatin accessibility data to accurately predict enhancers in a cell line-specific manner.We proposed Deep CAPE,a deep convolutional neural network to predict enhancers via the integration of DNA sequences and DNase-seq data.Benefitting from the well-designed feature extraction mechanism and skip connection strategy,our model not only consistently outperforms existing methods in the imbalanced classification of cell line-specific enhancers against background sequences,but also has the ability to self-adapt to different sizes of datasets.Besides,with the adoption of autoencoder,our model is capable of making cross-cell line predictions.We further visualize kernels of the first convolutional layer and show the match of identified sequence signatures and known motifs.We finally demonstrate the potential ability of our model to explain functional implications of putative disease-associated genetic variants and discriminate diseaserelated enhancers.The source code and detailed tutorial of Deep CAPE are freely available at https://github.com/Shengquan Chen/DeepCAPE. | Shengquan Chen Mingxin Gan Hairong Lv Rui Jiang | 2021 | Genomics, Proteomics & Bioinformatics2021，19，4： | 0 |
| 16 | The geoscience knowledge system,ontology and knowledge graph for data-driven discovery:Preface显示文摘Earth science data have shown rapid growth since the 21st century with the improvement of experimental instruments and testing methods.This provides a basis for revealing the evolutionary history of life,climate,palaeogeography and economic deposits by using big data.However,it is a major challenge to integrate Earth science data for the complexity of the Earth system,the great number of terminologies in Earth science,the diversity of research methods and proxies,and the diversification of data types. | Xiumian Hu Xiaogang Ma Chao Ma Hairong Lv | 2023 | Geoscience Frontiers2023，14，5： | 0 |
| 17 | A unified framework of temporal information expression in geosciences knowledge system显示文摘Time is an essential reference system for recording objects,events,and processes in the field of geosciences.There are currently various time references,such as solar calendar,geological time,and regional calendar,to represent the knowledge in different domains and regions,which subsequently entails a time conversion process required to interpret temporal information under different time references.However,the current time conversion method is limited by the application scope of existing time ontologies(e.g.,“Jurassic”is a period in geological ontology,but a point value in calendar ontology)and the reliance on experience in conversion processes.These issues restrict accurate and efficient calculation of temporal information across different time references.To address these issues,this paper proposes a Unified Time Framework(UTF)in the geosciences knowledge system.According to a systematic time element parsing from massive time references,the proposed UTF designs an independent time root node to get rid of irrelevant nodes when accessing different time types and to adapt to the time expression of different geoscience disciplines.Furthermore,this UTF carries out several designs:to ensure the accuracy of time expressions by designing quantitative relationship definitions;to enable time calculations across different time elements by designing unified time nodes and structures,and to link to the required external ontologies by designing adequate interfaces.By comparing the time conversion methods,the experiment proves the UTF greatly supports accurate and efficient calculation of temporal information across different time references in SPARQL queries.Moreover,it shows a higher and more stable performance of temporal information queries than the time conversion method.With the advent of the Big Data era in the geosciences,the UTF can be used more widely to discover new geosciences knowledge across different time references. | Shu Wang Yunqiang Zhu Yanmin Qi Zhiwei Hou Kai Sun Weirong Li Lei Hu Jie Yang Hairong Lv | 2023 | Geoscience Frontiers2023，14，5： | 0 |
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