Local contractors' awareness on competitiveness towards liberalisation and globalisation in the Malaysian construction industry

Globalisation gives the opportunity to contractors from a particular country to venture into various countries around the globe as the construction market is unlimitedly open. Due to this globalisation, the government has signed free trade agreements (FTA) as the result of the liberalisation process. Globalisation and liberalisation do not only provide opportunities and benefits to the local construction market, but also give challenges to local contractors in terms of competition with other local and foreign contractors. Yet, a question arises whether the local contractors in particular are aware with the competitive challenges they are facing against the foreign contractors or even amongst the local contractors themselves. This is because there are limited studies conducted which seek to identify the current levels of awareness on competitiveness among local contractors within the Malaysian construction industry. Hence, this paper emerges with the objectives of (1) identifying the current level of awareness of local contractors on competitiveness and (2) investigating the most important attributes of awareness of local contractors in the Malaysian construction industry. Questionnaire surveys were conducted on local Malaysian contractors involving 61 organisations from 112 venturing into overseas market. Data were analysed via Rasch analysis consisting of five method analysis which are the reliability and validity analysis, organisation misfit analysis, unidimensionality analysis, item misfit analysis and item measure order analysis. Findings from this paper reveal that most of the contractors have a moderate level of awareness on the competitiveness in the Malaysian construction industry. The findings of this study have been concluded as the local contractors acknowledge their competitors' strength and weaknesses when bidding for new projects and also aim to improve their competitiveness in competing with other local contractors locally. Recognition of this paper on the awareness of the importance of competitiveness by various local contractors in the Malaysian construction industry is in line with the Construction Industry Transformation Plan (CITP) 2016-2020 in addressing the Internationalisation Thrust with the aim to increase competitiveness of the domestic market, especially with the presence of foreign player

Predicting volume of distribution with decision tree-based regression methods using predicted tissue:plasma partition coefficients

Background: Volume of distribution is an important pharmacokinetic property that indicates the extent of a drug's distribution in the body tissues. This paper addresses the problem of how to estimate the apparent volume of distribution at steady state (Vss) of chemical compounds in the human body using decision tree-based regression methods from the area of data mining (or machine learning). Hence, the pros and cons of several different types of decision tree-based regression methods have been discussed. The regression methods predict Vss using, as predictive features, both the compounds' molecular descriptors and the compounds' tissue:plasma partition coefficients (Kt:p) - often used in physiologically-based pharmacokinetics. Therefore, this work has assessed whether the data mining-based prediction of Vss can be made more accurate by using as input not only the compounds' molecular descriptors but also (a subset of) their predicted Kt:p values. Results: Comparison of the models that used only molecular descriptors, in particular, the Bagging decision tree (mean fold error of 2.33), with those employing predicted Kt:p values in addition to the molecular descriptors, such as the Bagging decision tree using adipose Kt:p (mean fold error of 2.29), indicated that the use of predicted Kt:p values as descriptors may be beneficial for accurate prediction of Vss using decision trees if prior feature selection is applied. Conclusions: Decision tree based models presented in this work have an accuracy that is reasonable and similar to the accuracy of reported Vss inter-species extrapolations in the literature. The estimation of Vss for new compounds in drug discovery will benefit from methods that are able to integrate large and varied sources of data and flexible non-linear data mining methods such as decision trees, which can produce interpretable models. Figure not available: see fulltext. © 2015 Freitas et al.; licensee Springer

Fabrication of Fe3O4@CuO core-shell from MOF based materials and its antibacterial activity

Magnetic Fe3O4@CuO nanocomposite with a core/shell structure was successfully synthesized via direct calcinations of magnetic Fe3O4@HKUST-1 in air atmosphere. The morphology, structure, magnetic and porous properties of the as-synthesized nano composites were characterized by using scanning electron microscope (SEM), transmission electron microscopy (TEM), powder X-ray diffraction (PXRD), and vibration sample magnetometer (VSM). The results showed that the nanocomposite material included a Fe3O4 core and a CuO shell. The Fe3O4@CuO core-shell can be separated easily from the medium by a small magnet. The antibacterial activity of Fe3O4-CuO core-shell was investigated against gram-positive and gram-negative bacteria. A new mechanism was proposed for inactivation of bacteria over the prepared sample. It was demonstrated that the core-shell exhibit recyclable antibacterial activity, acting as an ideal long-acting antibacterial agent

Listeriosis Phytotherapy: A Review Study on the Effectiveness of Iranian Medicinal Plants in Treatment of Listeriosis

Listeria monocytogenes can be found in many processed foods, raw milk, dairy products, meat and meat products such as sausages, beef and fish products, seafoods, eggs, fruits, and vegetables such as radish and cabbage. This article is a review study on the Iranian medicinal plants applied for treatment of listeriosis. Information of this review article was obtained by searching various key words such as Listeria monocytogenes, medicinal plants, plant extracts and essential oils among scientific articles published in databases of Google scholar, ISI Web of Knowledge, PubMed, Scopus, SID and Magiran. Thyme, German chamomile, great chamomile, yarrow, onion, oregano, nutmeg, sage, sagebrush, hyssop, rosemary, St John's wort, safflower, ajowan, cumin, peppermint, shallot, anise, and parsnip are known antilisteriosis medicinal plants. Bioactive phytochemicals, antioxidants and monoterpenes, sesquiterpene, coumarin, flavonoids, tannins, saponins, alkaloids, and terpenoids are the main ingredients of antilisteriosis medicinal plants