420 research outputs found

    c-trie++: A Dynamic Trie Tailored for Fast Prefix Searches

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    Given a dynamic set KK of kk strings of total length nn whose characters are drawn from an alphabet of size σ\sigma, a keyword dictionary is a data structure built on KK that provides locate, prefix search, and update operations on KK. Under the assumption that α=w/lgσ\alpha = w / \lg \sigma characters fit into a single machine word ww, we propose a keyword dictionary that represents KK in nlgσ+Θ(klgn)n \lg \sigma + \Theta(k \lg n) bits of space, supporting all operations in O(m/α+lgα)O(m / \alpha + \lg \alpha) expected time on an input string of length mm in the word RAM model. This data structure is underlined with an exhaustive practical evaluation, highlighting the practical usefulness of the proposed data structure, especially for prefix searches - one of the most elementary keyword dictionary operations

    Herbal medicines for the treatment of cancer chemotherapy-induced side effects

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    Accumulating evidence suggests that Japanese herbal medicines, called Kampo, have beneficial effects on cancer chemotherapy-induced side effects. Rikkunshito ameliorates cisplatin-induced anorexia through an antagonistic effect on the 5-HT receptors and by increasing the serum ghrelin levels. Hangeshashinto improves irinotecan-induced diarrhea and chemotherapy-induced mucositis by inhibiting the activity of β-glucuronidase as well as the synthesis of prostaglandin E2. Goshajinkigan prevents oxaliplatin-induced neurotoxicity, possibly through suppressing functional alterations of the transient receptor potential (TRP) channels. In this review, we will summarize the currently available literature regarding the clinical efficacy and potential mechanisms of Kampo medicines in the treatment of cancer chemotherapy-induced side effects

    Fully dynamic data structure for LCE queries in compressed space

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    A Longest Common Extension (LCE) query on a text TT of length NN asks for the length of the longest common prefix of suffixes starting at given two positions. We show that the signature encoding G\mathcal{G} of size w=O(min(zlogNlogM,N))w = O(\min(z \log N \log^* M, N)) [Mehlhorn et al., Algorithmica 17(2):183-198, 1997] of TT, which can be seen as a compressed representation of TT, has a capability to support LCE queries in O(logN+loglogM)O(\log N + \log \ell \log^* M) time, where \ell is the answer to the query, zz is the size of the Lempel-Ziv77 (LZ77) factorization of TT, and M4NM \geq 4N is an integer that can be handled in constant time under word RAM model. In compressed space, this is the fastest deterministic LCE data structure in many cases. Moreover, G\mathcal{G} can be enhanced to support efficient update operations: After processing G\mathcal{G} in O(wfA)O(w f_{\mathcal{A}}) time, we can insert/delete any (sub)string of length yy into/from an arbitrary position of TT in O((y+logNlogM)fA)O((y+ \log N\log^* M) f_{\mathcal{A}}) time, where fA=O(min{loglogMloglogwlogloglogM,logwloglogw})f_{\mathcal{A}} = O(\min \{ \frac{\log\log M \log\log w}{\log\log\log M}, \sqrt{\frac{\log w}{\log\log w}} \}). This yields the first fully dynamic LCE data structure. We also present efficient construction algorithms from various types of inputs: We can construct G\mathcal{G} in O(NfA)O(N f_{\mathcal{A}}) time from uncompressed string TT; in O(nloglognlogNlogM)O(n \log\log n \log N \log^* M) time from grammar-compressed string TT represented by a straight-line program of size nn; and in O(zfAlogNlogM)O(z f_{\mathcal{A}} \log N \log^* M) time from LZ77-compressed string TT with zz factors. On top of the above contributions, we show several applications of our data structures which improve previous best known results on grammar-compressed string processing.Comment: arXiv admin note: text overlap with arXiv:1504.0695
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