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  • 1
    ISSN: 1432-0541
    Keywords: Key words. Approximation algorithm, Worst case ratio, Competitive analysis, On-line algorithm, Packing problem, Covering problem.
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract. This paper deals with vector covering problems in d -dimensional space. The input to a vector covering problem consists of a set X of d -dimensional vectors in [0,1] d . The goal is to partition X into a maximum number of parts, subject to the constraint that in every part the sum of all vectors is at least one in every coordinate. This problem is known to be NP-complete, and we are mainly interested in its on-line and off-line approximability. For the on-line version, we construct approximation algorithms with worst case guarantee arbitrarily close to 1/(2d) in d≥ 2 dimensions. This result contradicts a statement of Csirik and Frenk in [5] where it is claimed that, for d≥ 2 , no on-line algorithm can have a worst case ratio better than zero. Moreover, we prove that, for d≥ 2 , no on-line algorithm can have a worst case ratio better than 2/(2d+1) . For the off-line version, we derive polynomial time approximation algorithms with worst case guarantee Θ(1/ log d) . For d=2 , we present a very fast and very simple off-line approximation algorithm that has worst case ratio 1/2 . Moreover, we show that a method from the area of compact vector summation can be used to construct off-line approximation algorithms with worst case ratio 1/d for every d≥ 2 .
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Algorithmica 25 (1999), S. 22-36 
    ISSN: 1432-0541
    Keywords: Key words. On-line algorithms, Competitive ratio, On-line financial problems.
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mathematics
    Notes: Abstract. We deal with the problem of making capital investments in machines for manufacturing a product. Opportunities for investment occur over time, every such option consists of a capital cost for a new machine and a resulting productivity gain, i.e., a lower production cost for one unit of product. The goal is that of minimizing the total production costs and capital costs when future demand for the product being produced and investment opportunities are unknown. This can be viewed as a generalization of the ski-rental problem and related to the mortgage problem [3]. If all possible capital investments obey the rule that lower production costs require higher capital investments, then we present an algorithm with constant competitive ratio. If new opportunities may be strictly superior to previous ones (in terms of both capital cost and production cost), then we give an algorithm which is O (min{1+log C , 1+log log P , 1+log M }) competitive, where C is the ratio between the highest and the lowest capital costs, P is the ratio between the highest and the lowest production costs, and M is the number of investment opportunities. We also present a lower bound on the competitive ratio of any on-line algorithm for this case, which is Ω (min{log C , log log P / log log log P , log M / log log M }). This shows that the competitive ratio of our algorithm is tight (up to constant factors) as a function of C , and not far from the best achievable as a function of P and M .
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Combinatorica 11 (1991), S. 97-122 
    ISSN: 1439-6912
    Keywords: 68 E 05
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract Suppose we haven elements from a totally ordered domain, and we are allowed to performp parallel comparisons in each time unit (=round). In this paper we determine, up to a constant factor, the time complexity of several approximation problems in the common parallel comparison tree model of Valiant, for all admissible values ofn, p and ɛ, where ɛ is an accuracy parameter determining the quality of the required approximation. The problems considered include the approximate maximum problem, approximate sorting and approximate merging. Our results imply as special cases, all the known results about the time complexity for parallel sorting, parallel merging and parallel selection of the maximum (in the comparison model), up to a constant factor. We mention one very special but representative result concerning the approximate maximum problem; suppose we wish to find, among the givenn elements, one which belongs to the biggestn/2, where in each round we are allowed to askn binary comparisons. We show that log* n+O(1) rounds are both necessary and sufficient in the best algorithm for this problem.
    Type of Medium: Electronic Resource
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  • 4
    ISSN: 1573-675X
    Keywords: adenocarcinoma cells ; apoptosis ; Bcl-2 family proteins ; chimeric proteins ; GnRH-binding site ; targeting
    Source: Springer Online Journal Archives 1860-2000
    Topics: Biology , Medicine
    Notes: Abstract In recent years chimeric proteins carrying bacterial toxins as their killing moiety, have been developed to selectively recognize and kill cell populations expressing speciific receptors. The involvement of Gonadotropin releasing hormone (GnRH) has been demonstrated in several adenocarcinomas and a GnRH-bacterial toxin chimeric protein (GnRH-PE66) was thus developed and found to specifically target and kill adenocarcinoma cells both in vitro and in vivo. Because of the immunogenicity and the non-specific toxicity of the bacterial toxins, we have developed new chimeric proteins, introducing apoptosis inducing proteins of the Bcl-2 family as novel killing components. Sequences encoding the human Bik, Bak or Bax proteins were fused to the GnRH coding sequence at the DNA level and were expressed in E. coli. GnRH-Bik, GnRH-Bak and GnRH-Bax new chimeric proteins efficiently and specifically inhibited the cell growth of adenocarcinoma cell lines and eventually led to cell death. All three Bcl2-proteins-based chimeric proteins seem to induce apoptosis within the target cells, without any additional cell death stimulus. Apoptosis-inducing-proteins of the Bcl-2 family targeted by the GnRH are novel potential therapeutic reagents for adenocarcinoma treatment in humans. This novel approach could be widely applied, using any molecule that binds a specific cell type, fused to an apoptosis-inducing protein.
    Type of Medium: Electronic Resource
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