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Ubiquitin proteasome activity is suppressed in enzalutamide resistant prostate cancer cells, and the heat shock protein 70/STIP1 homology and U-box-containing protein 1 (HSP70/STUB1) machinery are involved in androgen receptor (AR) and AR variant protein stabilization. Targeting HSP70 could be a viable strategy to overcome resistance to androgen receptor signaling inhibitor (ARSI) in advanced prostate cancer. Here, we showed that a novel HSP70 allosteric inhibitor, JG98, significantly suppressed drug-resistant C4-2B MDVR and CWR22Rv1 cell growth, and enhanced enzalutamide treatment. JG98 also suppressed cell growth in conditional reprogramed cell cultures (CRCs) and organoids derived from advanced prostate cancer patient samples. Mechanistically, JG98 degraded AR/AR-V7 expression in resistant cells and promoted STUB1 nuclear translocation to bind AR-V7. Knockdown of the E3 ligase STUB1 significantly diminished the anticancer effects and partially restored AR-V7 inhibitory effects of JG98. JG231, a more potent analog developed from JG98, effectively suppressed the growth of the drug-resistant prostate cancer cells, CRCs, and organoids. Notably, the combination of JG231 and enzalutamide synergistically inhibited AR/AR-V7 expression and suppressed CWR22Rv1 xenograft tumor growth. Inhibition of HSP70 using novel small-molecule inhibitors coordinates with STUB1 to regulate AR/AR-V7 protein stabilization and ARSI resistance.

Drug-drug self-delivery systems serving as both carriers and cargos have been explored as advanced combination chemotherapy strategies to overcome the limitations of the traditional single-drug chemotherapy. However, most known drug-drug self-delivery systems may cause a rapid increase in drug concentration when the single covalent bond is broken, thus leading to high toxicity to organs and low therapeutic efficiency against tumors. To address the above problem, in this study, a novel supramolecular drug-drug complex (SDDC) simultaneously containing both covalent and noncovalent bonds was proposed to realize the sequential release of two drugs in tumor cells for enhanced combination therapy. The SDDC could self-assemble into uniform bilayer supramolecular vesicles (SVs) with a remarkable drug loading capacity and stable drug transport. Notably, the SVs with controlled sequential release ability in tumor cells exhibited a superior synergistic effect and significantly improved therapeutic efficiency with reduced toxicity in

There are extensive studies focusing on the application scenario that all the bipartite cohesive subgraphs need to be discovered in a bipartite graph. However, we observe that, for some applications, one is interested in finding bipartite cohesive subgraphs containing a specific vertex. In this paper, we study a new query dependent bipartite cohesive subgraph search problem based on $k$-wing model, named as the personalized $k$-wing search problem. We introduce a $k$-wing equivalence relationship to summarize the edges of a bipartite graph $G$ into groups. Therefore, all the edges of $G$ are segregated into different groups, i.e. $k$-wing equivalence class, forming an efficient and wing number conserving index called EquiWing. Further, we propose a more compact version of EquiWing, EquiWing-Comp, which is achieved by integrating our proposed $k$-butterfly loose approach and discovered hierarchy properties. These indices are used to expedite the personalized $k$-wing search with a non-repetitive access to $G$, which leads to linear algorithms for searching the personalized $k$-wing. Moreover, we conduct a thorough study on the maintenance of the proposed indices for evolving bipartite graphs. We discover novel properties that help us localize the scope of the maintenance at a low cost. By exploiting the discoveries, we propose novel algorithms for maintaining the two indices, which substantially reduces the cost of maintenance. We perform extensive experimental studies in real, large-scale graphs to validate the efficiency and effectiveness of EquiWing and EquiWing-Comp compared to the baseline., 13 pages, 10 figures and 4 tables

Maximal clique enumeration (MCE) is a fundamental problem in graph theory and is used in many applications, such as social network analysis, bioinformatics, intelligent agent systems, cyber security, etc. Most existing MCE algorithms focus on improving the efficiency rather than reducing the output size. The output unfortunately could consist of a large number of maximal cliques. In this paper, we study how to report a summary of less overlapping maximal cliques. The problem was studied before, however, after examining the pioneer approach, we consider it still not satisfactory. To advance the research along this line, our paper attempts to make four contributions: (a) we propose a more effective sampling strategy, which produces a much smaller summary but still ensures that the summary can somehow witness all the maximal cliques and the expectation of each maximal clique witnessed by the summary is above a predefined threshold; (b) we prove that the sampling strategy is optimal under certain optimality conditions; (c) we apply clique-size bounding and design new enumeration order to approach the optimality conditions; and (d) to verify experimentally, we test eight real benchmark datasets that have a variety of graph characteristics. The results show that our new sampling strategy consistently outperforms the state-of-the-art approach by producing smaller summaries and running faster on all the datasets., Comment: 20 pages, 80 figures

Geo-social group search aims to find a group of people proximate to a location while socially related. One of the driven applications for geo-social group search is organizing an impromptu activity. This is because the social cohesiveness of a found geo-social group ensures a good communication atmosphere and the spatial closeness of the geo-social group reduces the preparation time for the activity. Most existing works treat geo-social group search as a problem that finds a group satisfying a single social constraint while optimizing the spatial proximity. However, when an impromptu activity has additional demands on attendees, e.g., the activity requires that the attendees have certain set of skills, the existing works cannot find an effective geo-social group efficiently. In this paper, we study how to find a group that is most proximate to a query location while satisfying multiple constraints. Specifically, the multiple constraints on which we focus include social constraint, size constraint and keyword constraint. We propose a novel search framework which first effectively narrows down the search space with theoretical guarantees and then efficiently finds the optimum result. Although our model considers multiple constraints, novel techniques devised in this paper ensure that search cost is equivalent to parameterized constant times of one time social constraint checking on a vastly restricted search space. We conduct extensive experiments on both real and semi-synthetic datasets for demonstrating the efficiency of the proposed search algorithm. To evaluate the effectiveness, we conduct two case studies on real datasets, demonstrating the superiority of our proposed model., 12 Pages with 1 Page References

Background: De-regulation of Wnt signaling pathways has been shown to be associated with progression of castration-resistant prostate cancer and more recently, studies indicate that both canonical and non-canonical Wnt pathways may mediate resistance to anti-androgen therapies such as enzalutamide. However, the mechanisms by which Wnt signaling is altered in prostate cancer remain poorly understood. Wnt pathway function begins with Wnt biogenesis and secretion from Wnt signal sending cells. While previous studies have investigated downstream mechanisms of Wnt pathway alterations in prostate cancer, little is known on the role of Wnt secretion mediating proteins. Wntless (WLS) is thought to be essential for the secretion of all Wnts. In this study, we sought to understand the role of WLS in prostate cancer. Methods: RNA-seq and gene set enrichment analysis were used to understand expression profile changes in enzalutamide-resistant C4-2B-MDVR (MDVR) cells versus parental C4-2B cells. Quantitative-PCR and western blot were used to confirm RNA-seq data and to assess expression changes of gene targets of interest. Rv1 cells were used as a separate model of enzalutamide-resistant prostate cancer. RNAi was used to inhibit WLS expression. Cell viability, colony formation, and PSA ELISA assays were used to assess cell growth and survival. Results: Transcriptomic profiling revealed enriched Wnt pathway signatures in MDVR versus parental C4-2B cells. We further show that MDVR cells upregulate Wnt signaling and overexpress WLS. Inhibition of WLS decreases Wnt signaling, markedly attenuates prostate cancer cell viability, induces apoptosis, and re-sensitizes enzalutamide-resistant cells to enzalutamide treatment. Lastly, we show that inhibition of WLS reduces AR and AR-variants expression and downstream signaling. Conclusions: Our findings support a role for WLS in the progression of prostate cancer to a treatment-resistant state. Further efforts to understand Wnt signaling pathway alterations in this disease may lead to the development of novel treatments.

Advancements in research have added several new therapies for castration-resistant prostate cancer (CRPC), greatly augmenting our ability to treat patients. However, CRPC remains an incurable disease due to the development of therapeutic resistance and the existence of cross-resistance between available therapies. Understanding the interplay between different treatments will lead to improved sequencing and the creation of combinations that overcome resistance and prolong survival. Whether there exists cross-resistance between docetaxel and the next-generation taxane cabazitaxel is poorly understood. In this study, we use C4-2B and DU145 derived docetaxel-resistant cell lines to test response to cabazitaxel. Our results demonstrate that docetaxel resistance confers cross-resistance to cabazitaxel. We show that increased ABCB1 expression is responsible for cross-resistance to cabazitaxel and that inhibition of ABCB1 function through the small-molecule inhibitor elacridar resensitizes taxane-resistant cells to treatment. In addition, the antiandrogens bicalutamide and enzalutamide, previously demonstrated to be able to resensitize taxane-resistant cells to docetaxel through inhibition of ABCB1 ATPase activity, are also able to resensitize resistant cells to cabazitaxel treatment. Finally, we show that resensitization using an antiandrogen is far more effective in combination with cabazitaxel than docetaxel. Collectively, these results address key concerns in the field, including that of cross-resistance between taxanes and highlighting a mechanism of cabazitaxel resistance involving ABCB1. Furthermore, these preclinical studies suggest the potential in using combinations of antiandrogens with cabazitaxel for increased effect in treating advanced CRPC. Mol Cancer Ther; 16(10); 2257-66. ©2017 AACR.

The current first-line treatment for advanced metastatic prostate cancer, i.e. docetaxel-based therapy, is only marginally effective. The aim of the present study was to determine whether such therapy can be improved by combining docetaxel with Aneustat (OMN54), a multivalent botanical drug candidate shown to have anti-prostate cancer activity in preliminary in vitro experiments, which is currently undergoing a Phase-I Clinical Trial. Human metastatic, androgen-independent C4-2 prostate cancer cells and NOD-SCID mice bearing PTEN-deficient, metastatic and PSA-secreting, patient-derived subrenal capsule LTL-313H prostate cancer tissue xenografts were treated with docetaxel and Aneustat, alone and in combination. In vitro, Aneustat markedly inhibited C4-2 cell replication in a dose-dependent manner. When Aneustat was combined with docetaxel, the growth inhibitions of the drugs were essentially additive. In vivo, however, the combination of docetaxel and Aneustat enhanced anti-tumor activity synergistically and very markedly, without inducing major host toxicity. Complete growth inhibition and shrinkage of the xenografts could be obtained with the combined drugs as distinct from the drugs on their own. Analysis of the gene expression of the xenografts using microarray indicated that docetaxel + Aneustat led to expanded anticancer activity, in particular to targeting of cancer hallmarks that were not affected by the single drugs. Our findings, obtained with a highly clinically relevant prostate cancer model, suggest, for the first time, that docetaxel-based therapy of advanced human prostate cancer may be improved by combining docetaxel with Aneustat.

Truss was proposed to study social network data represented by graphs. A k-truss of a graph is a cohesive subgraph, in which each edge is contained in at least k-2 triangles within the subgraph. While truss has been demonstrated as superior to model the close relationship in social networks and efficient algorithms for finding trusses have been extensively studied, very little attention has been paid to truss maintenance. However, most social networks are evolving networks. It may be infeasible to recompute trusses from scratch from time to time in order to find the up-to-date $k$-trusses in the evolving networks. In this paper, we discuss how to maintain trusses in a graph with dynamic updates. We first discuss a set of properties on maintaining trusses, then propose algorithms on maintaining trusses on edge deletions and insertions, finally, we discuss truss index maintenance. We test the proposed techniques on real datasets. The experiment results show the promise of our work.

PurposeUse of enzalutamide has improved the treatment of advanced prostate cancer. However, resistance to enzalutamide can develop frequently in initial responders. This study aimed to test whether overexpression of IL-6 and constitutive activation of Stat3 in prostate cancer cells increase resistance to enzalutamide.Experimental designSensitivity of prostate cancer cells to enzalutamide was tested using cell growth assays and clonogenic assays. Quantitative reverse transcription-PCR, ELISA, and Western blotting were performed to detect expression levels of IL-6, c-Myc, survivin, and AR. Expression of Stat3 was downregulated using siRNA specific to Stat3. ChIP assay was performed to examine recruitment of AR to the PSA promoter.ResultsProstate cancer cells expressing autocrine IL-6 are resistant to enzalutamide and autocrine IL-6 leads to constitutive activation of Stat3 and its target genes. Down regulation of Stat3 led to an increase in sensitivity of prostate cancer cells to enzalutamide. Overexpression of constitutively active Stat3 in prostate cancer cells induced resistance to enzalutamide treatment. Constitutively active Stat3 also enhanced the recruitment of AR to PSA promoter which could not be disrupted by enzalutamide. The Stat3 inhibitor AG490 reversed enzalutamide resistance in prostate cancer cells, while combination treatment with enzalutamide and AG490 significantly inhibited cell growth and induced cell apoptosis.ConclusionsThis study demonstrates that the autocrine IL-6 pathway induces enzalutamide resistance in prostate cancer cells via the constitutive activation of Stat3. Co-targeting IL6-Stat3 pathway with enzalutamide may be utilized for treatment of advanced prostate cancer.

IntroductionTreatment of primary prostate cancer (CaP) is the withdrawal of androgens. However, CaP eventually progresses to grow in a castration-resistant state due to aberrant activation of androgen receptor (AR). Understanding the mechanisms leading to the aberrant activation of AR is critical to develop effective therapy. We have previously identified Rho GDP Dissociation Inhibitor alpha (GDIα) as a novel suppressor in prostate cancer. In this study, we examine the effect of GDIα on AR signaling in prostate cancer cells.MethodsGDIα was transiently or stably transfected into several prostate cancer cell lines including LNCaP, C4-2, CWR22Rv1, and DU145. The regulation of AR expression by GDIα was analyzed by qRT-PCR and Western blot. AR activity was measured by luciferase reporter assays and electrophoretic mobility shift analysis (EMSA). Immunofluorescence assay was performed to study AR nuclear translocation. The interaction between GDIα and AR was examined by co-immunoprecipitation assays.ResultsIn this study, we have identified GDIα as a negative regulator of AR signaling pathway. Overexpression of GDIα downregulates AR expression at both mRNA and protein levels. Overexpression of GDIα is able to prevent AR nuclear translocation and inhibit transactivation of AR target genes. Co-immunoprecipitation assays showed that GDIα physically interacts with the N-terminal domain of AR.ConclusionsGDIα suppresses AR signaling through inhibition of AR expression, nuclear translocation, and recruitment to androgen-responsive genes. GDIα regulatory pathway may play a critical role in regulating AR signaling and prostate cancer growth and progression.

View update is the problem of translating an update to a view to some updates to the source data of the view. In this paper, we show the factors determining XML view update translation, propose a translation procedure, and propose translated updates to the source document for different types of views. We further show that the translated updates are precise. The proposed solution makes it possible for users who do not have access privileges to the source data to update the source data via a view.

In this paper we study how to efficiently compute \textit{frequent co-occurring terms} (FCT) in the results of a keyword query in parallel using the popular MapReduce framework. Taking as input a keyword query q and an integer k, an FCT query reports the k terms that are not in q, but appear most frequently in the results of the keyword query q over multiple joined relations. The returned terms of FCT search can be used to do query expansion and query refinement for traditional keyword search. Different from the method of FCT search in a single platform, our proposed approach can efficiently answer a FCT query using the MapReduce Paradigm without pre-computing the results of the original keyword query, which is run in parallel platform. In this work, we can output the final FCT search results by two MapReduce jobs: the first is to extract the statistical information of the data; and the second is to calculate the total frequency of each term based on the output of the first job. At the two MapReduce jobs, we would guarantee the load balance of mappers and the computational balance of reducers as much as possible. Analytical and experimental evaluations demonstrate the efficiency and scalability of our proposed approach using TPC-H benchmark datasets with different sizes.

While keyword query empowers ordinary users to search vast amount of data, the ambiguity of keyword query makes it difficult to effectively answer keyword queries, especially for short and vague keyword queries. To address this challenging problem, in this paper we propose an approach that automatically diversifies XML keyword search based on its different contexts in the XML data. Given a short and vague keyword query and XML data to be searched, we firstly derive keyword search candidates of the query by a classifical feature selection model. And then, we design an effective XML keyword search diversification model to measure the quality of each candidate. After that, three efficient algorithms are proposed to evaluate the possible generated query candidates representing the diversified search intentions, from which we can find and return top-$k$ qualified query candidates that are most relevant to the given keyword query while they can cover maximal number of distinct results.At last, a comprehensive evaluation on real and synthetic datasets demonstrates the effectiveness of our proposed diversification model and the efficiency of our algorithms.

Signal transducer and activator of transcription 3 (Stat3) is an oncogenic transcriptional factor that plays a critical role in carcinogenesis and cancer progression and is a potential therapeutic target. Sanguinarine, a benzophenanthridine alkaloid derived primarily from the bloodroot plant, was identified previously as a novel inhibitor of survivin that selectively kills prostate cancer cells over "normal" prostate epithelial cells.DU145, C4-2B, and LNCaP cells were treated with sanguinarine. The phosphorylation status of Stat3 and related proteins were measured with Western blots. Activation of transcription by Stat3 was measured with luciferase reporter assay. The effect of sanguinarine on anchorage-independent growth was examined with soft agar assay, and on cell migration and invasion of DU145 cells were measured with scratch assay and invasion assay, respectively.In this study, we identified sanguinarine as a potent inhibitor of Stat3 activation which was able to suppress prostate cancer growth, migration, and invasion. Sanguinarine inhibits constitutive as well as IL6-induced phosphorylation of Stat3 at both Tyr705 and Ser727 in prostate cancer cells. The inhibition of Stat3 phosphorylation by sanguinarine correlates with reduction of Janus-activated Kinase 2 (Jak2) and Src phosphorylation. Sanguinarine downregulates the expression of Stat3-mediated genes such as c-myc and survivin and inhibits the Stat3 responsive element luciferase reporter activity. Sanguinarine inhibits the anchorage-independent growth of DU145 and LN-S17 cells expressing constitutively activated Stat3. Migration and invasion abilities of DU145 cells were also inhibited by sanguinarine in a manner similar to the dominant negative form of Stat3.These data demonstrate that sanguinarine is a potent Stat3 inhibitor and it could be developed as a therapeutic agent for prostate cancer with constitutive activation of Stat3.

In this paper, a new high precision focused word sense disambiguation (WSD) approach is proposed, which not only attempts to identify the proper sense for a word but also provides the probabilistic evaluation for the identification confidence at the same time. A novel Instance Knowledge Network (IKN) is built to generate and maintain semantic knowledge at the word, type synonym set and instance levels. Related algorithms based on graph matching are developed to train IKN with probabilistic knowledge and to use IKN for probabilistic word sense disambiguation. Based on the Senseval-3 all-words task, we run extensive experiments to show the performance enhancements in different precision ranges and the rationality of probabilistic based automatic confidence evaluation of disambiguation. We combine our WSD algorithm with five best WSD algorithms in senseval-3 all words tasks. The results show that the combined algorithms all outperform the corresponding algorithms.

Workflow-based web applications are important in workflow management systems as they interact with users of business processes. With the Model-driven approach, user interfaces (UIs) of these applications can be partially generated based on functional and data requirements obtained from underlying process models. In traditional activity-centric modelling approaches, data models and relationships between tasks and data are not clearly defined in the process model; thus, it is left to UI modellers to manually identify data requirement in generated UIs. We observed that artifact-centric approaches can be applied to address the above problems. However, it brings in challenges to automatically generate UIs due to the declarative manner of describing the processes. In this paper, we propose a model-based automatic UI generation framework with related algorithms for deriving UIs from process models.

As a tracking technology, Radio Frequency Identification (RFID) is now widely applied to enhance the context awareness of enterprise information systems. Such awareness provides great opportunities to facilitate business process automation and thereby improve operation efficiency and accuracy. With the aim to incorporate business logics into RFID-enabled applications, this book chapter addresses how RFID technologies impact current business process management and the characteristics of object-oriented business process modelling . This chapter first discusses the rationality and advantages of applying object-oriented process modelling in RFID applications, then addresses the requirements and guidelines for RFID data management and process modelling. Two typical solutions are introduced to further illustrate the modelling and incorporation of business logics/business processes into RFID edge systems. To demonstrate the applicability of these two approaches, a detailed case study is conducted within a distribution centre scenario.

Resources tend to follow certain availability patterns, due to the maintenance cycles, work shifts, etc. Such availability patterns heavily influence the efficiency and effectiveness of enterprise process scheduling. Most existing process scheduling and resource management approaches focus on process structure and resource utilisation, yet neglect the resource availability constraints. In this paper, we investigate how to plan the business process instances scheduling in accordance with resource availability patterns, so that enterprise resources can be rationally and sufficiently used. Three planning strategies are proposed to maximise the process instance throughput using different criteria.

Process view technology is catching more attentions in modern business process management, as it enables the customisation of business process representation. This capability helps improve the privacy protection, authority control, flexible display, etc., in business process modelling. One of approaches to generate process views is to allow users to construct an aggregate on their underlying processes. However, most aggregation approaches stick to a strong assumption that business processes are always well-structured, which is over strict to BPMN. Aiming to build process views for non-well-structured BPMN processes, this paper investigates the characteristics of BPMN structures, tasks, events, gateways, etc., and proposes a formal process view aggregation approach to facilitate BPMN process view creation. A set of consistency rules and construction rules are defined to regulate the aggregation and guarantee the order preservation, structural and behaviour correctness and a novel aggregation technique, called EP-Fragment, is developed to tackle non-well-structured BPMN processes.

Clustering network vertices is an enabler of various applications such as social computing and Internet of Things. However, challenges arise for clustering when networks increase in scale. This paper proposes CHIEF (Clustering with HIgher-ordEr motiFs), a solution which consists of two motif clustering techniques: standard acceleration CHIEF-ST and approximate acceleration CHIEF-AP. Both algorithms firstly find the maximal $k$-edge-connected subgraphs within the target networks to lower the network scale by optimizing the network structure with maximal $k$-edge-connected subgraphs, and then use heterogeneous four-node motifs clustering in higher-order dense networks. For CHIEF-ST, we illustrate that all target motifs will be kept after this procedure when the minimum node degree of the target motif is equal or greater than $k$. For CHIEF-AP, we prove that the eigenvalues of the adjacency matrix and the Laplacian matrix are relatively stable after this step. CHIEF offers an improved efficiency of motif clustering for big networks, and it verifies higher-order motif significance. Experiments on real and synthetic networks demonstrate that the proposed solutions outperform baseline approaches in large network analysis, and higher-order motifs outperform traditional triangle motifs in clustering Refereed/Peer-reviewed

Au/TiO2 nanocomposite particles were synthesized by a method based on intense X-ray irradiation without adding any reducing agent or stabilizer. The nanocomposite exhibits promising photocatalytic and biological properties at physiologically relevant concentration ([Au] = 0.028 mM, [TiO2] = 0.5 mM). The structure and photocatalysis were examined by X-ray diffraction, electron microscopy and ultraviolet-visible spectroscopy demonstrating that gold nanoparticles of 2-5 nm size were successfully deposited on TiO2 nanoparticle surfaces. The nanocomposite exhibited good colloidal stability within a typical cellular environment and was nontoxic to cancer cell according to evaluations under controlled conditions. The Au/TiO2 nanoparticles were also found to enhance the photocatalytic efficiency of UV radiation and even more that of X-ray radiation. In vitro studies indicated that the cell-killing effect under X-ray irradiation is more pronounced with the addition of Au/TiO2 nanoparticles than of bare TiO2 nanoparticles. (C) 2009 Elsevier B.V. All rights reserved.

Trust and reputation systems are widely adopted in the e-commerce environment to help buyers choose trustworthy sellers. It is a normal thought that the higher the reputation is, the more trustworthy its holder should be. However, our research discloses that under certain circumstances, a high-reputation seller has greater intention to cheat, which means that buyers should trust the low-reputation sellers better in those cases. We term this phenomenon Trust- Reputation Paradox. The theoretical proof, based on the game theory, is conducted to show the existence of the paradox. The root causes of this abnormality are revealed and discussed. In the end, we provide some guidelines for trust and reputation system designers to avoid this obscure pitfall. usc Refereed/Peer-reviewed

View update is the problem of translating an update to a view to some updates to the source data of the view. In this paper, we formally define the problem, show the factors determining XML view update translation, and propose a translation solution for two specific but typical settings of the view update problem. We prove that the translated source updates are precise and they generalize the solutions to the problem with similar settings in the relational database. Refereed/Peer-reviewed

Trust and reputation systems are widely adopted to help online consumers choose trustworthy suppliers. One problem is that consumers are only attracted by high-reputation holders, which disadvantages the newcomers entering the market, even they provide better goods or services. In this paper, we propose an online supplier selection model in which online consumers interact with a web institution, where online suppliers are registered in, and the web institution will recommend trustworthy suppliers according to a trust-based algorithm. This new recommendation model finds a balance point between minimizing the defective interactions as well as granting opportunities to newcomers. In addition, it saves consumers' efforts to look for trustworthy suppliers. We propose a framework to help realize the new interaction mode. We also use experiments to show its effectiveness. Refereed/Peer-reviewed

Using reputation system to help determine trust worthiness of online entities is a widely adopted method in the current web environment. Reputation bootstrapping, known as determining a default reputation value for a newcomer, is an important issue which currently is short of a proper solution. In this paper, we introduce a new concept, marginal reputation utility, based on which we discuss the relationship between trust and reputation and construct a reputation boot strapping framework that is universally applicable to different reputation models and systems. We use experiments to test the effectiveness of the proposed framework upon different reputation models, which shows satisfactory results. Refereed/Peer-reviewed

In recent years, web service composition attracts huge academic attention and is regarded as a promising area to help automatically actualize complex on-line business processes. While many composition models and frameworks are proposed, little research is conducted on the trust issues of the web service composers (WSCs). In this paper, we first discuss the necessity of the research on the trust issues of web service composers. Then we propose a trust computation framework that integrates both service-level and composer-level trust factors to calculate the trustworthiness of web service composers. Service-level and composer-level trust factors are discussed. The computational logics for each trust factor and for their integration are presented. We also use experimental environment to evaluate the effectiveness of our proposed framework. Refereed/Peer-reviewed

In this paper, we study the problem how to efficiently evaluate a set of contained rewritings on materialized views. Previous works focused on how to find a set of contained rewritings given a view and a query, but did not address how to evaluate the rewritings on materialized views. To evaluate a potential exponential number of contained rewritings, we design two algorithms, a basic algorithm and an optimized algorithm. Both algorithms are built on the observation that the exponential number of contained rewritings are actually composed by a linear number of component patterns. In the optimized algorithm, we further design four important pruning rules and several heuristic rules that can effectively reduce the number of component patterns we need to evaluate. The experiments demonstrate the efficiency of our algorithms. Refereed/Peer-reviewed

Refereed/Peer-reviewed

Data transformation from a source schema to a global schema is an important issue in data integration. For this purpose, a set of transformation operators have been defined to transform both DTDs and the conforming XML documents. In this paper we analyze the performance of individual operators both theoretically and experimentally. The performance of a sequence of operators is also investigated via experiment. Some algorithms and structures are proposed to improve the performance of operators so that linear efficiency can be achieved.The result shows thatmost of the operators can be implemented in linear time to the size of data to be transformed. The performance of sequence of operators is also close to linear. Java and XQuery language are used respectively to implement the operators and their efficiency is compared.

We present a set of primitive restructuring operators that, when combined, are sufficiently powerful to convert an XML document under a source schema into an XML document under an arbitrary target schema We initially define the operators at the schema level, and then show how each operator induces a corresponding transformation on any XML document under the schema Finally, we note that our operators can be implemented in a high level language such as XQuery, and thus our approach can be used as the basis for automating the conversion of one XML document to another XML document.

XML has become the standard for publishing and exchanging data on the Web. However, most business data is managed and will remain to be managed by relational database management systems. As such, there is an increasing need to efficiently and accurately publish relational data as XML documents for Internet-based applications. One way to publish relational data is to provide virtual XML documents for relational data via an XML schema which is transformed from the underlying relational database schema such that users can access the relational database through the XML schema. In this paper, we discuss issues in transforming a relational database schema into the corresponding XML schema. We aim to preserve all integrity constraints defined in a relational database schema, to achieve high level of nesting and to avoid introducing data redundancy in the transformed XML schema. In the paper, we first propose a basic transformation algorithm which introduces no data redundancy, then we improve the algorithm by exploring further nesting of the transformed XML schema.

Integrity constraints play a fundamental role in defining semantics in both conventional databases and in XML documents. In this paper we generalize previous approaches to defining inclusion dependencies in XML. Previous approaches have considered only the case where the paths on the l.h.s. are child attributes of the same node and the paths on the r.h.s. of the dependency are child attributes of the same node, whereas we do not apply this restriction. We then give an axiom system for XINDs and prove that the system is sound and complete. As a corollary, we also show that the implication problem for XINDs is decidable. Finally we consider the relationship between inclusion dependencies in relational databases (INDs) and XINDs in XML documents and we show that for a very general class of mappings from a relational database to a set of XML documents, and IND is satisfied in a relational database if and only if the corresponding XIND is satisfied in the XML documents.

2004

Keys and functional dependencies play a fundamental role in relational databases where they are used in integrity enforcement and in database design. Similarly, these constraints will play a fundamental role in XML and recently keys and functional dependencies in XML have been defined. In this paper we extend the previous definition of functional dependencies in XML to local functional dependencies in XML. Local functional dependencies (LFDs) are functional dependencies which hold only in a certain part of an XML document and not in the whole document. We also define, and prove correct, axioms for reasoning about the implication of LFDs in XML. Finally, we examine the relationship between LFDs and keys and show that the recently introduced concept of a relative key is a special case of a LFD.

The notion of compensation is widely used in advanced transaction models as means of recovery from a failure. Similar concepts are adopted for providing "transaction-like" behaviour for long business processes supported by workflows technology. In general, it is not trivial to design compensating tasks for tasks in the context of a workflow. Actually, a task in a workflow process does not have to be compensatable in the sense that the forcibility of "reverse" operations of the task is not always guaranteed by the application semantics. In addition, the isolation requirement on data resources may make a task difficult to compensate. In this paper, we first look into the requirements that a compensating task has to satisfy. Then we introduce a new concept called confirmation. With the help of confirmation, we are able to modify most non-compensatable tasks so that they become compensatable. This can substantially increase the availability of shared resources and greatly improve backward recovery for workflow applications in case of failures. To effectively incorporate confirmation and compensation into a workflow management environment, a three level bottom-up workflow design method is introduced. The implementation issues of this design are also discussed.

While XML is emerging as the universal format for publishing and exchanging data on the Web, most business data is still stored and maintained in relational database management systems. As a result, there is an increasing need to efficiently publish relational data as XML documents for Internet-based applications. One way to publish relational data is to provide virtual XML documents for relational data via an XML schema which is transformed from the underlying relational database schema, then users can access the relational database through the XML schema. In this paper, we discuss issues in transforming a relational database schema into corresponding schema in XML Schema. We aim to achieve high level of nesting while introducing no data redundancy for the transformed XML schema. In the paper, we first propose a basic transformation algorithm which introduces no data redundancy, then we improve the algorithm by exploring further nesting of the transformed XML schema.