52 research outputs found

    Investment decision analysis of international megaprojects based on cognitive linguistic cloud models

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    The investment decision analysis of international megaprojects is a major area of interest. The choice of interna tional megaprojects usually depends on the multi-discipline knowledge from experts. Besides, experts may not be able to provide accurate or crisp evaluations such as deterministic numbers on each criterion because of the complexity of the decision problem. In this case, natural evaluation language, either single linguistic variable or multiple linguistic variables, is a good expression tool for experts to sharing their opinions freely and flexibly. To this end, this paper introduces a cognitive linguistic cloud model for the investment decision analysis of international megaprojects as a decision support system and provides a survey of the cloud model. Afterwards, the technique to tackle multi-granularity of cognitive linguistic information is proposed to capture personalized semantics. In addition, operators of the cognitive linguistic model are proposed to aggregate natural language. The proposed approach has the advantages of more accurate utilization of experts’ knowledge, reducing uncertainties, and more effective operations of cognitive clouds for decision analysis in comparing with the state of the art. Finally, a case study about the investment of international megaprojects is given to show the flexibility and understandability of the cognitive linguistic model

    Hospitality brand management by a score-based q-rung ortho pair fuzzy V.I.K.O.R. method integrated with the best worst method

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    Hospitality brand management is a primary concern in the hotel industry and the evaluation of brands can be considered as a decision-making problem with multiple criteria. The evaluation information of brands may be uncertain sometimes. The q-rung orthopair fuzzy set (q-R.O.F.S.), which represents the preference degree of a person from the positive and negative aspects, has turned out to be an efficient tool in depicting uncertainty and vagueness in the decision-making process. This article dedicates to presenting an integrated multiple criteria decision-making method with q-R.O.F.S.. Firstly, a score function of the q-R.O.F.S. is proposed to solve the deficiencies of two existing score functions. Then, a weight-determining method based on the additive consistency of the preference relation is developed. A decision-making method integrating the score function, the best worst method and the VIsekriterijumska optimizacija I KOmpromisno Resenje (V.I.K.O.R.) which means multiple criteria compromise optimisation in English) method is further proposed. Finally, a case study regarding the hospitality brand management is provided to show the applicability and validity of the proposed method

    Mesenchymal Stem Cells Promote Mammosphere Formation and Decrease E-Cadherin in Normal and Malignant Breast Cells

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    Normal and malignant breast tissue contains a rare population of multi-potent cells with the capacity to self-renew, referred to as stem cells, or tumor initiating cells (TIC). These cells can be enriched by growth as "mammospheres" in three-dimensional cultures.We tested the hypothesis that human bone-marrow derived mesenchymal stem cells (MSC), which are known to support tumor growth and metastasis, increase mammosphere formation.We found that MSC increased human mammary epithelial cell (HMEC) mammosphere formation in a dose-dependent manner. A similar increase in sphere formation was seen in human inflammatory (SUM149) and non-inflammatory breast cancer cell lines (MCF-7) but not in primary inflammatory breast cancer cells (MDA-IBC-3). We determined that increased mammosphere formation can be mediated by secreted factors as MSC conditioned media from MSC spheroids significantly increased HMEC, MCF-7 and SUM149 mammosphere formation by 6.4 to 21-fold. Mammospheres grown in MSC conditioned media had lower levels of the cell adhesion protein, E-cadherin, and increased expression of N-cadherin in SUM149 and HMEC cells, characteristic of a pro-invasive mesenchymal phenotype. Co-injection with MSC in vivo resulted in a reduced latency time to develop detectable MCF-7 and MDA-IBC-3 tumors and increased the growth of MDA-IBC-3 tumors. Furthermore, E-cadherin expression was decreased in MDA-IBC-3 xenografts with co-injection of MSC.MSC increase the efficiency of primary mammosphere formation in normal and malignant breast cells and decrease E-cadherin expression, a biologic event associated with breast cancer progression and resistance to therapy
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