adenoviruses are used extensively to deliver genes into mammalian cells, particularly where there is a requirement for high-level expression of transgene products in cultured cells, or for use as recombinant viral vaccines or in gene therapy. in spite of their usefulness, the construction of adenoviral vectors (adv) is a cumbersome and lengthy process that is not readily amenable to the generat...

introduction: neurotrophins, as a family of proteins, are responsible for induction of the survival, development, and function of neurons. also, neurotropic factors are growth factors like neurotrophins that help neurons survive. moreover, neurotrophins differentiate between progenitor cells so that neurons are formed. despite the fact that the majority of mammalian brain neurons are produced p...

The cooperative solution concept introduced here, the demand bargaining set, contains the core and is included in the Zhou bargaining set, eliminating the “dominated” coalition structures. The demand vectors belonging to the demand bargaining set are self-stable. In the class of constant-sum homogeneous weighted majority games the demand bargaining set is non-empty and predicts a unique demand ...

The cooperative solution concept introduced here, the Stable Demand Set, contains the Core and is included in the Zhou Bargaining Set, eliminating the “dominated” coalition structures. The demand vectors belonging to the Stable Demand Set are self-stable. In the class of constant-sum homogeneous weighted majority games the Stable Demand Set is non-empty and predicts a unique stable demand vecto...

In this paper, we present an approach, based on dynamic programming, for solving the 0-1 multi-objective knapsack problem. The main idea of the approach relies on the use of several complementary dominance relations to discard partial solutions that cannot lead to new non-dominated criterion vectors. This way, we obtain an efficient method that outperforms the existing methods both in terms of ...

Social image datasets have grown to dramatic size with images classified in vector spaces with high dimension (512-2048) and with potentially billions of images and corresponding classification vectors. We study the challenging problem of clustering such sets into millions of clusters using Iterative MapReduce. We introduce a new Kmeans algorithm in the Map phase which can tackle the challenge ...