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Now showing items 1 - 16 of 37

  • Rapid microevolution during recent range expansion to harsh environments

    Chen, Yiyong   Shenkar, Noa   Ni, Ping   Lin, Yaping   Li, Shiguo   Zhan, Aibin  

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  • A Secure and Efficient Privacy-Preserving Range Query Scheme in Location-Based Services

    Huang, Zhisheng   Yan, Xiai   Lin, Yaping   Xu, Zhou   Lin, Feng  

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  • Minority oversampling for imbalanced ordinal regression

    Zhu, Tuanfei   Lin, Yaping   Liu, Yonghe   Zhang, Wei   Zhang, Jianming  

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  • Introduction and use of non-native species for aquaculture in China: status, risks and management solutions

    Lin, Yaping   Gao, Zexia   Zhan, Aibin  

    Aquaculture is one of the fast-growing industries in the past decades. The fast expansion of aquaculture largely relies on the introduction and use of non-native species. This forms a paradox: some species significantly contribute to the fast expansion of aquaculture, while negative effects associated with unregulated introduction and irresponsible use of non-native species are increasing in number and area affected. However, lessons from reported disasters are slowly learned, and risks raised have been highly overlooked. Here, we discuss the known and potential risks derived from the introduction and use of non-native species in China to urge the necessity of incorporating sound management into sustainable aquaculture. Sound management needs to be performed based on the characteristics of each aquaculture activity or related event. We discuss risks based on aquaculture activities or related events popularly employed in the past decades in China, including (i) transfers of non-native species; (ii) fellow travellers, accidental introductions; (iii) artificial hybridization; and (iv) mass release of non-native species for ranching. For each aquaculture activity or related event, we provide general background, status of this activity, risks raised and recommendations for management. Finally, we call for the collaboration of researchers from academia, government and aquaculture industry for proper risk assessment and sound management for sustainable development of aquaculture.
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  • Population genetic structure and identification of loci under selection in the invasive tunicate, Botryllus schlosseri, using newly developed EST-SSRs

    Lin, Yaping   Zhan, Aibin  

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  • Genomewide gene-associated microsatellite markers for the model invasive ascidian,\r Ciona intestinalis\r species complex

    Lin, Yaping   Chen, Yiyong   Xiong, Wei   Zhan, Aibin  

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  • Catch You if You Misbehave:Ranked Keyword Search Results Verification in Cloud Computing

    Zhang, Wei   Lin, Yaping   Qi, Gu  

    With the advent of cloud computing, more and more people tend to outsource their data to the cloud. As a fundamental data utilization, secure keyword search over encrypted cloud data has attracted the interest of many researchers recently. However, most of existing researches are based on an ideal assumption that the cloud server is "curious but honest", where the search results are not verified. In this paper, we consider a more challenging model, where the cloud server would probably behave dishonestly. Based on this model, we explore the problem of result verification for the secure ranked keyword search. Different from previous data verification schemes, we propose a novel deterrent-based scheme. With our carefully devised verification data, the cloud server cannot know which data owners, or how many data owners exchange anchor data which will be used for verifying the cloud server's misbehavior. With our systematically designed verification construction, the cloud server cannot know which data owners' data are embedded in the verification data buffer, or how many data owners' verification data are actually used for verification. All the cloud server knows is that, once he behaves dishonestly, he would be discovered with a high probability, and punished seriously once discovered. Furthermore, we propose to optimize the value of parameters used in the construction of the secret verification data buffer. Finally, with thorough analysis and extensive experiments, we confirm the efficacy and efficiency of our proposed schemes.
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  • Dynamic Texture Recognition Using Volume Local Binary Count Patterns With an Application to 2D Face Spoofing Detection

    Zhao, Xiaochao   Lin, Yaping   Heikkila, Janne  

    In this paper, a local spatiotemporal descriptor, namely, the volume local binary count (VLBC), is proposed for the representation and recognition of dynamic texture. This descriptor, which is similar in spirit to the volume local binary pattern (VLBP), extracts histograms of thresholded local spatiotemporal volumes using both appearance and motion features to describe dynamic texture. Unlike VLBP using binary encoding, VLBC does not exploit the local structure information and only counts the number of is in the thresholded codes. Thus, VLBC can include more neighboring pixels without exponentially increasing the feature dimension as VLBP does. Furthermore, a completed version of VLBC (CVLBC) is also proposed to enhance the performance of dynamic texture recognition with additional information about local contrast and central pixel intensities. The proposed method is not only efficient to compute but also effective for dynamic texture representation. In experiments with three dynamic texture databases, namely, UCLA, DynTex, and DynTex++, the proposed method produces classification rates that are comparable to those produced by the state-of-the-art approaches. In addition to dynamic texture recognition, we propose utilizing CVLBC for 2-D face spoofing detection. As an effective spatiotemporal descriptor, CVLBC can well describe the differences between facial videos of valid users and impostors, thus achieving good performance for face spoofing detection. For comparison with other methods, the proposed method is evaluated on three face antispoofing databases: Print-Attack, Replay-Attack, and CAS Face Antispoofing. The experimental results demonstrate the effectiveness of CVLBC for 2-D face spoofing detection.
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  • Rapid microevolution during recent range expansion to harsh environments

    Chen, Yiyong   Shenkar, Noa   Ni, Ping   Lin, Yaping   Li, Shiguo   Zhan, Aibin  

    BackgroundAdaptive evolution is one of the crucial mechanisms for organisms to survive and thrive in new environments. Recent studies suggest that adaptive evolution could rapidly occur in species to respond to novel environments or environmental challenges during range expansion. However, for environmental adaptation, many studies successfully detected phenotypic features associated with local environments, but did not provide ample genetic evidence on microevolutionary dynamics. It is therefore crucial to thoroughly investigate the genetic basis of rapid microevolution in response to environmental changes, in particular on what genes and associated variation are responsible for environmental challenges. Here, we genotyped genome-wide gene-associated microsatellites to detect genetic signatures of rapid microevolution of a marine tunicate invader, Ciona robusta, during recent range expansion to the harsh environment in the Red Sea.ResultsThe Red Sea population was significantly differentiated from the other global populations. The genome-wide scan, as well as multiple analytical methods, successfully identified a set of adaptive genes. Interestingly, the allele frequency largely varied at several adaptive loci in the Red Sea population, and we found significant correlations between allele frequency and local environmental factors at these adaptive loci. Furthermore, a set of genes were annotated to get involved in local temperature and salinity adaptation, and the identified adaptive genes may largely contribute to the invasion success to harsh environments.ConclusionsAll the evidence obtained in this study clearly showed that environment-driven selection had left detectable signatures in the genome of Ciona robusta within a few generations. Such a rapid microevolutionary process is largely responsible for the harsh environmental adaptation and therefore contributes to invasion success in different aquatic ecosystems with largely varied environmental factors.
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  • Kinetics analysis of the forward extraction of cerium(III) by D2EHPA from chloride medium in the presence of two complexing agents using a constant interfacial area cell with laminar flow

    Pei, Jiannan   Zhou, Junwen   Jiang, Feng   Chen, Kaihua   Yin, Shaohua   Zhang, Libo   Peng, Jinhui   Lin, Yaping  

    The kinetic studies performed on the forward extract of cerium(III) from chloride solution with the complex agents, citric acid (H(3)Cit) and lactic acid (HLac) in the presence of di-(2-ethylhexyl)phosphoric acid (D2EHPA, H(2)A(2)) have been investigated using a constant interfacial area cell with laminar flow. The effects of stirring speed, temperature, and specific interfacial area on the extraction rate are discussed separately, and the results show that the extraction process is a diffusion-controlled kinetics process with an interfacial reaction. Studies on the effect of pH value and H(2)A(2) concentration on the extraction rate are used to obtain the rate equation. The rate-controlling step is also suggested by the predictions derived from the interfacial reaction models, and the rate equation obtained by the kinetic model is consistent with that obtained by the experimental results. The information on the extraction kinetics in this extraction system will provide some knowledge of its application.
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  • A lightweight privacy and integrity preserving range query scheme for mobile cloud computing

    Xu, Zhou   Lin, Yaping   Arthur Sandor, Voundi Koe   Huang, Zhisheng   Liu, Xinbo  

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  • Dynamic Texture Classification Using Unsupervised 3D Filter Learning and Local Binary Encoding

    Zhao, Xiaochao   Lin, Yaping   Liu, Li   Heikkila, Janne   Zheng, Wenming  

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  • Genomewide gene-associated microsatellite markers for the model invasive ascidian,Ciona intestinalis species complex

    Lin, Yaping   Chen, Yiyong   Xiong, Wei   Zhan, Aibin  

    The vase tunicate, Ciona intestinalis species complex, has become a good model for ecological and evolutionary studies, especially those focusing on microevolution associated with rapidly changing environments. However, genomewide genetic markers are still lacking. Here, we characterized a large set of genomewide gene-associated microsatellite markers for C.intestinalis spA (=3DC.robusta). Bioinformatic analysis identified 4654 microsatellites from expressed sequence tags (ESTs), 2126 of which successfully assigned to chromosomes were selected for further analysis. Based on the distribution evenness on chromosomes, function annotation and suitability for primer design, we chose 545 candidate microsatellites for further characterization. After amplification validation and variation assessment, 218 loci were polymorphic in at least one of the two populations collected from the coast of Arenys de Mar, Spain (N=3D24-48), and Cape Town, South Africa (N=3D24-33). The number of alleles, observed heterozygosity and expected heterozygosity ranged from 2 to 11, 0 to 0.833 and 0.021 to 0.818, and from 2 to 10, 0 to 0.879 and 0.031 to 0.845 for the Spanish and African populations, respectively. When all microsatellites were tested for cross-species utility, only 60 loci (25.8%) could be successfully amplified and all loci were polymorphic in C.intestinalis spB. A high level of genomewide polymorphism is likely responsible for the low transferability. The large set of microsatellite markers characterized here is expected to provide a useful genomewide resource for ecological and evolutionary studies using C.intestinalis as a model.
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  • Beware of What You Share: Inferring User Locations in Venmo

    Yao, Xin   Chen, Yimin   Zhang, Rui   Zhang, Yanchao   Lin, Yaping  

    Mobile payment apps are seeing explosive usage worldwide. This paper focuses on Venmo, a very popular mobile person-to-person payment service owned by Paypal. Venmo allows money transfers between users with a mandatory transaction note. More than half of transaction records in Venmo are public information. In this paper, we propose a multilayer location inference (MLLI) technique to infer user locations from public transaction records in Venmo. MLLI explores two observations. First, many Venmo transaction notes contain implicit location cues. Second, the types and temporal patterns of user transactions have strong ties to their location closeness. With a large dataset of 2.12M users and 20.23M Venmo transaction records, we show that MLLI can identify the top-1, top-3, and top-5 possible locations for a Venmo user with accuracy up to 50%, 80%, and 90%, respectively. Our results highlight the danger of sharing transaction notes on Venmo or similar mobile payment apps.
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  • Anonymizing popularity in online social networks with full utility

    Zhang, Shiwen   Liu, Qin   Lin, Yaping  

    With the rapid growth of social network applications, more and more people are participating in social networks. Privacy protection in online social networks becomes an important issue. The illegal disclosure or improper use of users' private information will lead to unaccepted or unexpected consequences in people's lives. In this paper, we concern on authentic popularity disclosure in online social networks. To protect users' privacy, the social networks need to be anonymized. However, existing anonymization algorithms on social networks may lead to nontrivial utility loss. The reason is that the anonymization process has changed the social network's structure. The social network's utility, such as retrieving data files, reading data files, and sharing data files among different users, has decreased. Therefore, it is a challenge to develop an effective anonymization algorithm to protect the privacy of user's authentic popularity in online social networks without decreasing their utility. In this paper, we first design a hierarchical authorization and capability delegation (HACD) model. Based on this model, we propose a novel utility-based popularity anonymization (UPA) scheme, which integrates proxy re-encryption with keyword search techniques, to tackle this issue. We demonstrate that the proposed scheme can not only protect the users' authentic popularity privacy, but also keep the full utility of the social network. Extensive experiments on large real-world online social networks confirm the efficacy and efficiency of our scheme. (C) 2016 Elsevier B.V. All rights reserved.
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  • Differential privacy-based trajectory community recommendation in social network

    Wei, Jianhao   Lin, Yaping   Yao, Xin   Sandor, Voundi Koe Arthur  

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