Modified CADF and CIPS panel unit root statistics with standard chi-squared and normal limiting distributions

In an influential paper Pesaran ('A simple panel unit root test in presence of cross-section dependence', Journal of Applied Econometrics, Vol. 22, pp. 265-312, 2007) proposes two unit root tests for panels with a common factor structure. These are the CADF and CIPS test statistics, which are amongst the most popular test statistics in the literature. One feature of these statistics is that their limiting distributions are highly non-standard, making for relatively complicated implementation. In this paper, we take this feature as our starting point to develop modified CADF and CIPS test statistics that support standard chi-squared and normal inference.

Modified AHP for gene selection and cancer classification using type-2 fuzzy logic

This paper proposes a modification to the analytic hierarchy process (AHP) to select the most informative genes that serve as inputs to an interval type-2 fuzzy logic system (IT2FLS) for cancer classification. Unlike the conventional AHP, the modified AHP allows us to process quantitative factors that are ranking outcomes of individual gene selection methods including t-test, entropy, receiver operating characteristic curve, Wilcoxon test, and signal-to-noise ratio. The IT2FLS is introduced for the classification task due to its great ability for handling nonlinear, noisy, and outlier data, which are common problems in cancer microarray gene expression profiles. An unsupervised learning strategy using the fuzzy c-means clustering is employed to initialize parameters of the IT2FLS. Other classifiers such as multilayer perceptron network, support vector machine, and fuzzy ARTMAP are also implemented for comparisons. Experiments are carried out on three well-known microarray datasets: diffuse large B-cell lymphoma, leukemia cancer, and prostate. Rather than the traditional cross validation, leave-one-out cross-validation strategy is applied for the experiments. Results demonstrate the performance dominance of the IT2FLS against the competing classifiers. More noticeably, the modified AHP improves the classification performance not only of the IT2FLS but of all other classifiers as well. Accordingly, the proposed combination between the modified AHP and IT2FLS is a powerful tool for cancer classification and can be implemented as a real clinical decision support system that is useful for medical practitioners.

A novel α-aminophosphonic acid-modified acrylamide-based hydrophobic associating copolymer with superb water solubility for enhanced oil recovery

As a non-renewable resource, the rational exploitation of oil has attracted a large amount of attention. Among many methods for enhanced oil recovery, polymer flooding is the most suitable method of chemical flooding for non-marine reservoirs and therefore various modified acrylamide-based copolymers have been studied. In this study, a novel α-aminophosphonic acid-modified hydrophobic associating copolymer was successfully synthesized by copolymerization of acrylamide, acrylic acid, N-allyldodecanamide and 1-(dimethylamino)allylphosphonic acid. The copolymer was characterized by FT-IR, 1H NMR and thermogravimetry and exhibited superior water solubility and thickening capability. Subsequently, the shear resistance, temperature resistance and salt tolerance of the copolymer solution were investigated. The value of apparent viscosity retention of a 2000 mg L-1 copolymer solution was as high as 58.55 mPa s at a shear rate of 170 s-1 and remained at 40.20 mPa s at 120 °C. The values of apparent viscosity retention of 55.41 mPa s, 59.95 mPa s and 52.97 mPa s were observed in solutions of 10000 mg L-1 NaCl, 1200 mg L-1 MgCl2, and 1200 mg L-1 CaCl2, respectively. These were better than those of partially hydrolyzed polyacrylamide under the same conditions. In addition, an increase of up to 14.52% in the oil recovery rate compared with that for water flooding could be achieved in a core flooding test using a 2000 mg L-1 copolymer solution at 65 °C.