Identifying the efficient extreme units in a production possibility set is a very important matter in data envelopment analysis, as these observed, real units have the best performances. In this paper, we proposed a multiple objective programming model, in which the feasible region is the production possibility set under the assumption of variable returns to scale and the objective function consists of input and output variables. As we know, by increasing the dimensions of the problem, the set of efficient points would increase as well; thus, using the multiple objective linear programming problem-solving methods in a decision set would lead to computational problems and it would be much easier to work in the outcome set instead of the decision set. In this research, we show that the efficient points in the outcome set of the suggested multiple objective linear programming problems correspond with the efficient extreme points in data envelopment analysis. An outer approximation algorithm is presented for production of all efficient extreme points in the outcome set. This algorithm provides us with the equations for all efficient surfaces. In the outcome set, this algorithm would use few calculations to produce all the extreme points. Finally, we demonstrate the presented approach through numerical examples.

‎‎‎Given a fuzzy normed space, we will introduce the notion of fuzzy near best approximation as a generalization of the notion of fuzzy best approximation. Some basic properties are characterized and also many examples for illustration are presented. Also, the hereditary properties of the fuzzy near best approximation on direct sum and tensor product of linear spaces are discussed.

Background & Objectives: Pseudomonas aeruginosa is a common cause of nosocomial infection. OprD protein is a specific protein regulating the uptake of carbapenem antibiotic. Loss of OprD is the main mechanism of Pseudomonas Aeruginosa resistance to carbapenem. In this study, the presence of OprD gene is investigated in isolated Pseudomonas Aeruginosa in burn patients of Ghotboddin hospital in Shiraz.Material & Methods: Sixtysix Pseudomonas Aeruginosa were isolated from wound specimens of 250 burn patients. Strain characteristics were confirmed by biochemical tests. Antibiogram was done via disc diffusion method. Finally, OprD gene was investigated by PCR.Results: Isolated Pseudomonas Aeruginosa showed more sensitivity to chloramphenicol and colicitin and more resistance to ciprofloxacin, gentamycin, cefotaxim, ceftazidin, imipenem, meropenem, and erythromycin. 61 percent of isolates were positive for OprD gene by PCR.Conclusion: The findings of this study revealed that Colicitin and chloramphenicol are more effective in treatment of Pseudomonas Aeruginosa infections in burn patients, and deletion and mutation in OprD gene cause bacterium resistance to carbapenem antibiotic.

For a connected graph G of order at least two, a set S of vertices in a graph G is said to be an outer connected monophonic set if S is a monophonic set of G and either S = V or the subgraph induced by V-S is connected. The minimum cardinality of an outer connected monophonic set of G is the outer connected monophonic number of G and is denoted by moc (G). The number of extreme vertices in G is its extreme order ex(G). A graph G is said to be an extreme outer connected monophonic graph if moc(G) = ex(G). Extreme outer connected monophonic graphs of order p with outer connected monophonic number p and extreme outer connected monophonic graphs of order p with outer connected monophonic number p-1 are characterized. It is shown that for every pair a,b of integers with 0 ≥,a ≥,b and b ≥,2, there exists a connected graph G with ex(G) = a and moc(G) = b. Also, it is shown that for positive integers r,d and k≥, 2 with r < d, there exists an extreme outer connected monophonic graph G with monophonic radius r, monophonic diameter d and outer connected monophonic number k.

Over the last decade or so, wavelets have had a growing impact on signal processing theory and practice, both because of their unifying role and their successes in applications. Filter banks, which lie at the heart of wavelet-based algorithms, have become standard signal processing operators, used routinely in applications ranging from compression to modems. The contributions of wavelets have often been in the subtle interplay between discrete-time and continuous-time signal processing. The purpose of this article is to look at recent wavelet advances from a signal processing perspective. In particular, approximation results are reviewed, and the implication on compression algorithms is discussed. New constructions and open problems are also addressed. Finding a good basis to solve aproblem dates at least back to Fourier and his investigation of the heat equation. The series proposed by Fourier has several distinguishing features: The series is able to represent any finite energy function on an interval. The basis functions are eigenfunctions of linear shift invariant systems or, in other words, Fourier series diagonalize linear, shift invariant operators.

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