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| 1 | Climate and litter C/N ratio constrain soil organic carbon accumulation显示文摘Soil organic carbon(SOC) plays critical roles in stabilizing atmospheric CO2 concentration, but the mechanistic controls on the amount and distribution of SOC on global scales are not well understood. In turn, this has hampered the ability to model global C budgets and to find measures to mitigate climate change. Here, based on the data from a large field survey campaign with 2600 plots across China’s forest ecosystems and a global collection of published data from forested land, we find that a low litter carbon-to-nitrogen ratio(C/N) and high wetness index(P/PET, precipitation-to-potentialevapotranspiration ratio) are the two factors that promote SOC accumulation, with only minor contributions of litter quantity and soil texture. The field survey data demonstrated that high plant diversity decreased litter C/N and thus indirectly promoted SOC accumulation by increasing the litter quality. We conclude that any changes in plant-community composition, plant-species richness and environmental factors that can reduce the litter C/N ratio, or climatic changes that increase wetness index, may promote SOC accumulation. The study provides a guideline for modeling the carbon cycle of various ecosystem scales and formulates the principle for land-based actions for mitigating the rising atmospheric CO2 concentration. | Guoyi Zhou Shan Xu Philippe Ciais Stefano Manzoni Jingyun Fang Guirui Yu Xuli Tang Ping Zhou Wantong Wang Junhua Yan Gengxu Wang Keping Ma Shenggong Li Sheng Du Shijie Han Youxin Ma Deqiang Zhang Juxiu Liu Shizhong Liu Guowei Chu Qianmei Zhang Yuelin Li Wenjuan Huang Hai Ren Xiankai Lu Xiuzhi Chen | 2019 | National Science Review2019，6，4： | 21 |
| 2 | Measuring Conflict Functions in Generalized Power Space显示文摘One of the most important open issues is that the classical conflict coefficient in D-S evidence theory (DST) cannot correctly determine the conflict degree between two pieces of evidence. This drawback greatly limits the use of DST in real application systems. Early researches mainly focused on the improvement of Dempster’s rule of combination (DRC). However, the current research shows it is very important to define new conflict coefficients to determine the conflict degree between two or more pieces of evidence. The evidential sources of information are considered in this work and the definition of a conflict measure function (CMF) is proposed for selecting some useful CMFs in the next fusion work when sources are available at each instant. Firstly, the definition and theorems of CMF are put forward. Secondly, some typical CMFs are extended and then new CMFs are put forward. Finally, experiments illustrate that the CMF based on Jousselme and its similar ones are the best suited ones. | HU Lifang GUAN Xin DENG Yong HAN Deqiang HE You | 2011 | Chinese Journal of Aeronautics2011，24，1： | 11 |
| 3 | New method for measuring the degree of conflict among general basic probability assignments显示文摘There is doubt about Dempster's rule of combination because of counter-intuitive results when dealing with conflict information in intelligent reasoning.Therefore,many modified combination rules have been presented in the literature on multi-source information fusion and reasoning with uncertainty.However,the issue of identifying conflict among evidence has been ignored.A new parameter measuring conflict evidence called the conflict distance parameter is defined to determine whether there are conflicts in evidence based on the analysis of existing conflict parameters.At the same time,a decisive rule,which a reasonable conflict measure function should satisfy,is put forward.Finally,an analysis of two typical counter-intuitive situations is given,showing that the new parameter can not only satisfy the decisive rule,but can also attain the same effect as a two-dimensional measure when deciding whether to use the Dempster's rule of combination,and can exceed its effect when deciding whether to use Dezert-Smarandache theory. | HE You HU LiFang GUAN Xin DENG Yong HAN DeQiang | 2012 | Science China(Information Sciences)2012，55，2： | 7 |
| 4 | Some notes on betting commitment distance in evidence theory显示文摘The distance of evidence, which represents the degree of dissimilarity between bodies of evidence, has attracted more and more interest and has found extensive uses in many realms. In this paper some notes on a widely used distance of evidence, i.e., betting commitment distance, are provided, including the arguments on the rationality of its definition, some misuses and some counter-intuitive behaviors of betting commitment distance. Several numerical examples are also provided to support and verify our arguments. | HAN DeQiang DENG Yong HAN ChongZhao YANG Yi | 2012 | Science China(Information Sciences)2012，55，3： | 6 |
| 5 | A novel approximation of basic probability assignment based on rank-level fusion显示文摘Belief functions theory is an important tool in the field of information fusion. However, when the cardinality of the frame of discernment becomes large, the high computational cost of evidence combination will become the bottleneck of belief functions theory in real applications. The basic probability assignment (BPA) approximations, which can reduce the complexity of the BPAs, are always used to reduce the computational cost of evidence combination. In this paper, both the cardinalities and the mass assignment values of focal elements are used as the criteria of reduction. The two criteria are jointly used by using rank-level fusion. Some experiments and related analyses are provided to illustrate and justify the proposed new BPA approximation approach. | Yang Yi Han Deqiang Han Chongzhao Cao Feng | 2013 | Chinese Journal of Aeronautics2013，26，4： | 4 |
| 6 | A New Probabilistic Transformation in Generalized Power Space显示文摘The mapping from the belief to the probability domain is a controversial issue, whose original purpose is to make (hard) decision, but for contrariwise to erroneous widespread idea/claim, this is not the only interest for using such mappings nowadays. Actually the probabilistic transformations of belief mass assignments are very useful in modern multitarget multisensor tracking systems where one deals with soft decisions, especially when precise belief structures are not always available due to the existence of uncertainty in human being’s subjective judgments. Therefore, a new probabilistic transformation of interval-valued belief structure is put forward in the generalized power space, in order to build a subjective probability measure from any basic belief assignment defined on any model of the frame of discernment. Several examples are given to show how the new transformation works and we compare it to the main existing transformations proposed in the literature so far. Results are provided to illustrate the rationality and efficiency of this new proposed method making the decision problem simpler. | HU Lifang HE You GUAN Xin DENG Yong HAN Deqiang | 2011 | Chinese Journal of Aeronautics2011，24，4： | 4 |
| 7 | Visualizing DC morphology and T cell motility to characterize DC-T cell encounters in mouse lymph nodes under mTOR inhibition显示文摘Mammalian target of rapamycin(mTOR),a serine/threonine kinase orchestrating cellular metabolism,is a crucial immune system regulator.However,it remains unclear how mTOR regulates dendritic cell(DC) function in vivo,especially DC-T cell encounters,a critical step for initiating adaptive immune responses.We dynamically visualized DC-T contacts in mouse lymph node using confocal microscopy and established an encounter model to characterize the effect of mTOR inhibition on DC-T cell encounters using DC morphology.Quantitative data showed mTOR inhibition via rapamycin altered DC shape,with an increased form factor(30.17%) and decreased cellular surface area(20.36%) and perimeter(22.43%),which were associated with Cdc42 protein downregulation(52.71%).Additionally,DCs adopted a similar morphological change with Cdc42 inhibition via ZCL278 as that observed with mTOR inhibition.These morphologically altered DCs displayed low encounter rates with T cells.Time-lapse imaging data of T cell motility supported the simulated result of the encounter model,where antigen-specific T cells appeared to reduce arrest in the lymph nodes of rapamycin-pretreated mice relative to the untreated group.Therefore,mTOR inhibition altered DC morphology in vivo and decreased the DC-T cell encounter rate,as well as Cdc42 inhibition.By establishing an encounter model,our study provides an intuitive approach for the early prediction of DC function through morphological quantification of form factor and area. | Qiaoya Lin Zheng Liu Meijie Luo Hao Zheng Sha Qiao Chenlu Han Deqiang Deng Zhan Fan Yafang Lu Zhihong Zhang Qingming Luo | 2019 | Science China(Life Sciences)2019，62，9： | 2 |
| 8 | De-combination of belief function based on optimization显示文摘In the theory of belief functions,the evidence combination is a kind of decision-level information fusion.Given two or more Basic Belief Assignments(BBAs)originated from different information sources,the combination rule is used to combine them to expect a better decision result.When only a combined BBA is given and original BBAs are discarded,if one wants to analyze the difference between the information sources,evidence de-combination is needed to determine the original BBAs.Evidence de-combination can be considered as the inverse process of the information fusion.This paper focuses on such a defusion of information in the theory of belief functions.It is an under-determined problem if only the combined BBA is available.In this paper,two optimization-based approaches are proposed to de-combine a given BBA according to the criteria of divergence maximization and information maximization,respectively.The new proposed approaches can be used for two or more information sources.Some numerical examples and an example of application are provided to illustrate and validate our approaches. | Xiaojing FAN Deqiang HAN Yi YANG Jean DEZERT | 2022 | Chinese Journal of Aeronautics2022，35，5： | 2 |
| 9 | New conflict representation model in generalized power space显示文摘The study on alternative combination rules in Dempster-Shafer theory (DST) when evidences are in conflict has emerged again recently as an interesting topic, especially in data/information fusion applications. The earlier researches have mainly focused on investigating the alternative which would be appropriate for the conflicting situation, under the assumption that a conflict is identified. However, the current research shows that not only the combination rule but also the classical conflict coefficient in DST are not correct to determine the conflict degree between two pieces of evidences. Most existing methods of measuring conflict do not consider the open world situation, whose frame of discernment is incomplete. To solve this problem, a new conflict representation model to determine the conflict degree between evidences is proposed in the generalized power space, which contains two parameters: the conflict distance and the conflict coefficient of inconsistent evidences. This paper argues that only when the conflict measure value in the new representation model is high, it is safe to say the evidences are in conflict. Experiments illustrate the efficiency of the proposed conflict representation model. | You He Lifang Hu Xin Guan Deqiang Han Yong Deng | 2012 | Journal of Systems Engineering and Electronics2012，23，1： | 2 |
| 10 | New Dis- tance Measures of Evidence Based on Belief Intervals 显示文摘 | HAN Deqiang DEZERT Jean YANG Yi | 2014 | Lecture Notes in Computer Science2014，8764，1： | 1 |
| 11 | Basic belief assignment approximations using degree of non-redundancy for focal element显示文摘Dempster-Shafer evidence theory, also called the theory of belief function, is widely used for uncertainty modeling and reasoning. However, when the size and number of focal elements are large, the evidence combination will bring a high computational complexity. To address this issue,various methods have been proposed including the implementation of more efficient combination rules and the simplifications or approximations of Basic Belief Assignments(BBAs). In this paper,a novel principle for approximating a BBA into a simpler one is proposed, which is based on the degree of non-redundancy for focal elements. More non-redundant focal elements are kept in the approximation while more redundant focal elements in the original BBA are removed first. Three types of degree of non-redundancy are defined based on three different definitions of focal element distance, respectively. Two different implementations of this principle for BBA approximations are proposed including a batch and an iterative type. Examples, experiments, comparisons and related analyses are provided to validate proposed approximation approaches. | Yi YANG Deqiang HAN Jean DEZERT | 2019 | Chinese Journal of Aeronautics2019，32，11： | 1 |
| 12 | A novel classifier based on shortest feature line segment显示文摘 | HAN Deqiang HAN Chongzhao YANG Yi | 2011 | Pattern Recognition Letters2011，32，3： | 1 |
| 13 | Systematical study of the mechanistic factors regulating genome dynamics in vivo by CRISPRsie显示文摘The spatiotemporal regulation of threedimensional(3D)genome dynamics has been implicated in various genome functions including gene transcription,DNA recombination,DNA replication,and DNA repair(Bickmore,2013). | Deqiang Han Yu Hong Xueying Mai Qingtao Hu Guangqing Lu Jinzhi Duan Jingru Xu Xiaofang Si Yu Zhang | 2019 | Journal of Molecular Cell Biology2019，11，11： | 1 |
| 14 | CLASSIFIER FUSION BASED ON EVIDENCE THEORY AND ITS APPLICATION IN FACE RECOGNITION显示文摘A multiple classifier fusion approach based on evidence combination is proposed in this paper. The individual classifier is designed based on a refined Nearest Feature Line (NFL),which is called Center-based Nearest Neighbor (CNN). CNN retains the advantages of NFL while it has relatively low computational cost. Different member classifiers are trained based on different feature spaces respectively. Corresponding mass functions can be generated based on proposed mass function determination approach. The classification decision can be made based on the combined evidence and better classification performance can be expected. Experimental results on face recognition provided verify that the new approach is rational and effective. | Yang Yi Han Chongzhao Han Deqiang | 2009 | Journal of Electronics(China)2009，26，6： | 1 |
| 15 | New probabilistic transformation of imprecise belief structure显示文摘The case when the source of information provides precise belief function/mass,within the generalized power space,has been studied by many people.However,in many decision situa-tions,the precise belief structure is not always available.In this case,an interval-valued belief degree rather than a precise one may be provided.So,the probabilistic transformation of impre-cise belief function/mass in the generalized power space including Dezert-Smarandache(DSm) model from scalar transformation to sub-unitary interval transformation and,more generally,to any set of sub-unitary interval transformation is provided.Different from the existing probabilistic transformation algorithms that redistribute an ignorance mass to the singletons involved in that ignorance pro-portionally with respect to the precise belief function or probability function of singleton,the new algorithm provides an optimization idea to transform any type of imprecise belief assignment which may be represented by the union of several sub-unitary(half-) open intervals,(half-) closed intervals and/or sets of points belonging to [0,1].Numerical examples are provided to illustrate the detailed implementation process of the new probabilistic transformation approach as well as its validity and wide applicability. | Lifang Hu You He Xin Guan Deqiang Han Yong Deng | 2011 | Journal of Systems Engineering and Electronics2011，22，5： | 1 |
| 16 | A reduced-order method for estimating the stability region of power systems with saturated controls显示文摘In a modern power system, there is often large difference in the decay speeds of transients. This could lead to numerical problems such as heavy simulation burden and singularity when the traditional methods are used to estimate the stability re- gion of such a dynamic system with saturation nonlinearities. To overcome these problems, a reduced-order method, based on the singular perturbation theory, is suggested to estimate the stability region of a singular system with saturation nonlinearities. In the reduced-order method, a low-order linear dynamic system with saturation nonlinearities is constructed to estimate the stability region of the primary high-order system so that the singularity is eliminated and the estimation process is simplified. In addition, the analytical foundation of the reduction method is proven and the method is validated using a test power system with 3 buses and 5 machines. | GAN DeQiang XIN HuanHai QIU JiaJu HAN ZhenXiang | 2007 | Science China(Technological Sciences)2007，50，5： | 1 |
| 17 | Modified center-based feature line classification approach显示文摘A novel classification approach called modified center-based feature line(MCFL)is proposed to reduce the computational cost of the nearest feature line(NFL)and maintain the advantages of NFL.Unlike NFL,MCFL defines a different type of feature line and utilizes both the query point’s local information and corresponding class-global information in training set.In experiments provided,the comparisons with the nearest neighbor(NN),NFL,and other NFL-refined approaches show that the computation time of MCFL can be shortened dramatically with less accuracy decreases.MCFL proposed is probably a better choice for the classification application tasks of large-scale dataset. | Deqiang HAN Chongzhao HAN Yi YANG | 2010 | Frontiers of Electrical and Electronic Engineering in China2010，5，2： | 0 |
| 18 | Fe-doped Co3O4@C nanoparticles derived from layered double hydroxide used as efficient electrocatalyst for oxygen evolution reaction显示文摘Compared with noble metal catalyst, Co3O4-based electrocatalysts have attracted considerable interesting as low-cost alternatives for oxygen evolution reaction (OER). However, the poor electrocatalytic activity still remains a huge challenge. Herein, we demonstrate a feasible approach through oxidation of CoFe layered double hydroxide (CoFe-LDH) to synthesize Fe-doped Co3O4@C nanopmrticles with size of about 30-50 nm. As OER catalyst, the as-synthesized Fe-doped Co3O4@C nanoparticles exhibited superior OER performance with a small overpotential of 260 mV at the current density of 20 mA cm^-2, a small Tafel slope of 70 mV dec^-1 and long-term durability (there was no obviously OER current density degradation for 100 h) in alkaline solution. The present work opens a new avenue to the exploration of cost-effective and excellent electrocatalysts based on transition metal oxide materials to substitute precious metal materials for water splitting. | Caiyun He Xuzhao Han Xianggui Kong Meihong Jiang Deqiang Lei Xiaodong Lei | 2019 | Journal of Energy Chemistry2019，28，5： | 0 |
| 19 | An improved α-cut approach to transforming fuzzy membership function into basic belief assignment显示文摘In practical applications, pieces of evidence originated from different sources might be modeled by different uncertainty theories. To implement the evidence combination under the Dempster–Shafer evidence theory(DST) framework, transformations from the other type of uncertainty representation into the basic belief assignment are needed. a-Cut is an important approach to transforming a fuzzy membership function into a basic belief assignment, which provides a bridge between the fuzzy set theory and the DST. Some drawbacks of the traditional a-cut approach caused by its normalization step are pointed out in this paper. An improved a-cut approach is proposed, which can counteract the drawbacks of the traditional a-cut approach and has good properties. Illustrative examples, experiments and related analyses are provided to show the rationality of the improved a-cut approach. | Yang Yi X.Rong Li Han Deqiang | 2016 | Chinese Journal of Aeronautics2016，29，4： | 0 |
| 20 | Novel moderate transformation of fuzzy membership function into basic belief assignment显示文摘In information fusion,the uncertain information from different sources might be modeled with different theoretical frameworks.When one needs to fuse the uncertain information represented by different uncertainty theories,constructing the transformation between different frameworks is crucial.Various transformations of a Fuzzy Membership Function(FMF)into a Basic Belief Assignment(BBA)have been proposed,where the transformations based on uncertainty maximization and minimization can determine the BBA without preselecting the focal elements.However,these two transformations that based on uncertainty optimization emphasize the extreme cases of uncertainty.To avoid extreme attitudinal bias,a trade-off or moderate BBA with the uncertainty degree between the minimal and maximal ones is more preferred.In this paper,two moderate transformations of an FMF into a trade-off BBA are proposed.One is the weighted average based transformation and the other is the optimization-based transformation with weighting mechanism,where the weighting factor can be user-specified or determined with some prior information.The rationality and effectiveness of our transformations are verified through numerical examples and classification examples. | Xiaojing FAN Deqiang HAN Jean DEZERT Yi YANG | 2023 | Chinese Journal of Aeronautics2023，36，1： | 0 |
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