Random walks on mutual microRNA-target gene interaction network improve the prediction of disease-associated microRNAs

Background: MicroRNAs (miRNAs) have been shown to play an important role in pathological initiation, progression and maintenance. Because identification in the laboratory of disease-related miRNAs is not straightforward, numerous network-based methods have been developed to predict novel miRNAs in silico. Homogeneous networks (in which every node is a miRNA) based on the targets shared between miRNAs have been widely used to predict their role in disease phenotypes. Although such homogeneous networks can predict potential disease-associated miRNAs, they do not consider the roles of the target genes of the miRNAs. Here, we introduce a novel method based on a heterogeneous network that not only considers miRNAs but also the corresponding target genes in the network model. Results: Instead of constructing homogeneous miRNA networks, we built heterogeneous miRNA networks consisting of both miRNAs and their target genes, using databases of known miRNA-target gene interactions. In addition, as recent studies demonstrated reciprocal regulatory relations between miRNAs and their target genes, we considered these heterogeneous miRNA networks to be undirected, assuming mutual miRNA-target interactions. Next, we introduced a novel method (RWRMTN) operating on these mutual heterogeneous miRNA networks to rank candidate disease-related miRNAs using a random walk with restart (RWR) based algorithm. Using both known disease-associated miRNAs and their target genes as seed nodes, the method can identify additional miRNAs involved in the disease phenotype. Experiments indicated that RWRMTN outperformed two existing state-of-the-art methods: RWRMDA, a network-based method that also uses a RWR on homogeneous (rather than heterogeneous) miRNA networks, and RLSMDA, a machine learning-based method. Interestingly, we could relate this performance gain to the emergence of "disease modules" in the heterogeneous miRNA networks used as input for the algorithm. Moreover, we could demonstrate that RWRMTN is stable, performing well when using both experimentally validated and predicted miRNA-target gene interaction data for network construction. Finally, using RWRMTN, we identified 76 novel miRNAs associated with 23 disease phenotypes which were present in a recent database of known disease-miRNA associations. Conclusions: Summarizing, using random walks on mutual miRNA-target networks improves the prediction of novel disease-associated miRNAs because of the existence of "disease modules" in these networks

Vietnam’s Accession to the World Trade Organization: Economic Projections to 2020

This study presents a set of assessments of the long term economic effects of Vietnam’s accession to the WTO. Generally speaking, our results indicate that Vietnam would benefit from accelerating its participation in more open multilateralism. However, it is also clear from our analysis that these benefits will remain modest in the absence of comprehensive and complementary domestic economic reforms. Passive external liberalization, even when coupled with determined domestic reform, is inferior to WTO participation combined with negotiated market access and other activist multilateral agreements. Finally, our analysis shows that capital insufficiency is a very serious constraint on Vietnamese economic growth and diversification. Capital market reform can play an essential role in dynamic and sustained economic development for the country.Vietnam, WTO, Trade

On a nonlinear heat equation associated with Dirichlet -- Robin conditions

This paper is devoted to the study of a nonlinear heat equation associated with Dirichlet-Robin conditions. At first, we use the Faedo -- Galerkin and the compactness method to prove existence and uniqueness results. Next, we consider the properties of solutions. We obtain that if the initial condition is bounded then so is the solution and we also get asymptotic behavior of solutions as. Finally, we give numerical resultsComment: 20 page

Consensus Synthesis of Robust Cooperative Control for Homogeneous Leader-Follower Multi-Agent Systems Subject to Parametric Uncertainty

This paper presents a design of robust consensus for homogeneous leader-follower multiagent systems (MAS). Each agent of MAS is described by a linear time-invariant dynamic model subject to parametric uncertainty. The agents are interconnected through a static interconnection matrix over an undirected graph to cooperate and share information with their neighbours. The consensus design of MAS can be transformed to stability analysis by using decomposition technique. We apply Lyapunov theorem to derive the sufficient condition to ensure the consensus of all independent subsystems. In addition, we design a robust distributed state feedback gain based on linear quadratic regulator (LQR) setting. Controller gain is computed via solving a linear matrix inequality. As a result, we provide a robust design procedure of a cooperative LQR control to achieve consensus objective and maximize the admissible bound of the uncertainty. Finally, we give numerical examples to illustrate the effectiveness of the proposed consensus design. The results show that the response for MAS in presence of uncertainty using robust consensus design follows the response of the leader and is better than that of the existingnominal consensus design

DEVELOPMENT AND APPLICATION OF THE ENVIRONMENTAL HYDRODYNAMIC 3D MODEL FOR COMPUTATION AND FORECASTING OF OIL POLLUTIONS IN COASTAL MARINE ENVIRONMENT

Joint Research on Environmental Science and Technology for the Eart

Supply Chain Agility and Internal and External Process Connectivity: The Impact of Supply and Product Complexity

The study attempts to analyze the impact of internal and external process connectivity on supply chain agility of manufacturing firms in Thailand. It also examines whether supply and product complexity moderates the impact of internal and external process connectivity on supply chain agility. The study relies on the questionnaire survey to collect the data. Using electronic survey, the respondents working in manager’ positions in Thailand’s manufacturing companies are targeted. Out of 250 survey questionnaires, only 173 responses were found usable with a rate of response of 57.2%. The study focuses on Thai firms because Thai manufacturing sector is one of the strongest players in the globe. The reason to select manufacturing firms is that the manufacturing firms are considered to be very crucial in global supply chains in terms of providing agility and responsiveness while delivering final products to the consumers. Supply chain agility (SCAG) is used as dependent while internal process connectivity (INPC) and external process connectivity (EXPC) are used as independent variables. Moreover, product complexity (PRCX) and supply complexity (SPCX) are used as moderating variables. Findings show that SPCX has negatively significant influence on SCAG while PRCX has insignificant effect on SCAG. INPC and EXPC have positive and significant impact on SCAG. The results state that both INPC and EXPC play vital role in attaining SCAG. The interaction effect of product term (INPC × EXPC) on SCAG is also found to be positively significant. These outcomes are in line with the process theory which states that both INPC and EXPC are significant factor that play important role in attaining SCAG. Both these processes permit companies to better respond to continuous variations