Cost,Revenue and Profit Efficiency Models in Generalized Fuzzy Data Envelopment Analysis

One of the most important information given by data envelopment analysis models is the cost, revenue and profit efficiency of decision making units (DMUs). Cost efficiency is defined as the ratio of minimum costs to current costs, while revenue efficiency is defined as the ratio of maximum revenue to current revenue of the DMU. This paper presents a framework where data envelopment analysis (DEA) is used to measure cost, revenue and profit efficiency with fuzzy data. In such cases, the classical models cannot be used, because input and output data appear in the form of ranges. When the data are fuzzy, the cost, revenue and profit efficiency measures calculated from the data should be uncertain as well. Fuzzy DEA models emerge as another class of DEA models to account for imprecise inputs and outputs for DMUs. Although several approaches for solving fuzzy DEA models have been developed, numerous deficiencies including the $\alpha$-cut approaches and types of fuzzy numbers must still be improved. This scheme embraces evaluation method based on vector for proposed fuzzy model. This paper proposes generalized cost, revenue and profit efficiency models in fuzzy data envelopment analysis. The practical application of these models is illustrated by a numerical example.     

Phytochemical Profile,Antioxidant Capacity, α-Amylase and α-Glucosidase Inhibitory Potential of Wild Moroccan Inula viscosa (L.) Aiton Leaves

Medicinal plants offer imperative sources of innovative chemical substances with important potential therapeutic effects. Among them, the members of the genus Inula have been widely used in traditional medicine for the treatment of several diseases. The present study investigated the antioxidant (DPPH, ABTS and FRAP assays) and the in vitro anti-hyperglycemic potential of aerial parts of Inula viscosa (L.) Aiton (I. viscosa) extracts through the inhibition of digestive enzymes (α-amylase and α-glucosidase), responsible of the digestion of poly and oligosaccharides. The polyphenolic profile of the Inula viscosa (L.) Aiton EtOAc extract was also investigated using HPLC-DAD/ESI-MS analysis, whereas the volatile composition was elucidated by GC-MS. The chemical analysis resulted in the detection of twenty-one polyphenolic compounds, whereas the volatile profile highlighted the occurrence of forty-eight different compounds. Inula viscosa (L.) Aiton presented values as high as 87.2 ± 0.50 mg GAE/g and 78.6 ± 0.55mg CE/g, for gallic acid and catechin, respectively. The EtOAc extract exhibited the higher antioxidant activity compared to methanol and chloroform extracts in different tests with (IC₅₀ = 0.6 ± 0.03 µg/mL; IC₅₀ = 8.6 ± 0.08 µg/mL; 634.8 mg ± 1.45 AAE/g extract) in DPPH, ABTS and FRAP tests. Moreover, Inula viscosa (L.) Aiton leaves did show an important inhibitory effect against α-amylase and α-glucosidase. On the basis of the results achieved, such a species represents a promising traditional medicine, thanks to its remarkable content of functional bioactive compounds, thus opening new prospects for research and innovative phytopharmaceuticals developments.     

Enhancement of catalytic activity in the synthesis of 2-amino-4H-chromene derivatives using both copper- and cobalt-incorporated magnetic ferrite nanoparticles

Research on Chemical Intermediates - Cu0.5Co0.5Fe2O4 magnetic nanoparticles were prepared, characterized and employed as bench-top, highly active and magnetically separable nanocatalysts for the...     

Image quality assessment using the singular value decomposition theorem

In objective image quality metrics, one of the most important factors is the correlation of their results with the perceived quality measurements. In this paper, a new method is presented based on comparing between the structural properties of the two compared images. Based on the mathematical concept of the singular value decomposition (SVD) theorem, each matrix can be factorized to the products of three matrices, one of them related to the luminance value while the two others show the structural content information of the image. A new method to quantify the quality of images is proposed based on the projected coefficients and the left singular vector matrix of the disturbed image based on the right singular vector matrix of the original image. To evaluate this performance, many tests have been done using a widespread subjective study involving 779 images of the Live Image Quality Assessment Database, Release 2005. The objective results show a high rate of correlation with subjective quality measurements.     

A Primal-dual Interior-point Algorithm for Symmetric Cone Convex Quadratic Programming Based on the Commutative Class Directions

Acta Mathematicae Applicatae Sinica, English Series - In this paper, we present a neighborhood following primal-dual interior-point algorithm for solving symmetric cone convex quadratic programming...     

Facile synthesis of 1H-pyrazolo[1,2-a]pyridazine-5,8-dione derivatives by a one-pot, three-component reactions

Protonation of the highly reactive 1:1 intermediate produced in the reaction between alkyl or aryl isocyanides and electron-deficient acetylenic esters with 3,6-dihydroxypyridazine, leads to a vinylisonitrilium cation, which undergoes an addition reaction with the conjugate base of the 3,6-dihydroxypyridazine to produce dialkyl 3-(alkyl or arylamino)-5,8-dioxo-5,8-dihydro-1H-pyrazolo[1,2-a]pyridazine-1,2-dicarboxylates in good yields at room temperature.     

Two wide neighborhood interior-point methods for symmetric cone optimization

In this paper, we present two primal–dual interior-point algorithms for symmetric cone optimization problems. The algorithms produce a sequence of iterates in the wide neighborhood \(\mathcal {N}(\tau ,\,\beta )\) of the central path. The convergence is shown for a commutative class of search directions, which includes the Nesterov–Todd direction and the xs and sx directions. We derive that these two path-following algorithms have

$$\begin{aligned} \text{ O }\left( \sqrt{r\text{ cond }(G)}\log \varepsilon ^{-1}\right) , \text{ O }\left( \sqrt{r}\left( \text{ cond }(G)\right) ^{1/4}\log \varepsilon ^{-1}\right) \end{aligned}$$

iteration complexity bounds, respectively. The obtained complexity bounds are the best result in regard to the iteration complexity bound in the context of the path-following methods for symmetric cone optimization. Numerical results show that the algorithms are efficient for this kind of problems.