54 resultados para Minimal Spanning Trees


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In this single centre study of childhood acute lymphoblastic leukaemia (ALL) patients treated on the Medical Research Council UKALL 97/99 protocols, it was determined that minimal residual disease (MRD) detected by real time quantitative polymerase chain reaction (RQ-PCR) and 3-colour flow cytometry (FC) displayed high levels of qualitative concordance when evaluated at multiple time-points during treatment (93.38%), and a combined use of both approaches allowed a multi time-point evaluation of MRD kinetics for 90% (53/59) of the initial cohort. At diagnosis, MRD markers with sensitivity of at least 0.01% were identified by RQ-PCR detection of fusion gene transcripts, IGH/TRG rearrangements, and FC. Using a combined RQ-PCR and FC approach, the evaluation of 367 follow-up BM samples revealed that the detection of MRD >1% at Day 15 (P = 0.04), >0.01% at the end of induction (P = 0.02), >0.01% at the end of consolidation (P = 0.01), >0.01% prior to the first delayed intensification (P = 0.01), and >0.1% prior to the second delayed intensification and continued maintenance (P = 0.001) were all associated with relapse and, based on early time-points (end of induction and consolidation) a significant log-rank trend (P = 0.0091) was noted between survival curves for patients stratified into high, intermediate and low-risk MRD groups.

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Wilms' tumor gene 1 (WT1) is overexpressed in the majority (70-90%) of acute leukemias and has been identified as an independent adverse prognostic factor, a convenient minimal residual disease (MRD) marker and potential therapeutic target in acute leukemia. We examined WT1 expression patterns in childhood acute lymphoblastic leukemia (ALL), where its clinical implication remains unclear. Using a real-time quantitative PCR designed according to Europe Against Cancer Program recommendations, we evaluated WT1 expression in 125 consecutively enrolled patients with childhood ALL (106 BCP-ALL, 19 T-ALL) and compared it with physiologic WT1 expression in normal and regenerating bone marrow (BM). In childhood B-cell precursor (BCP)-ALL, we detected a wide range of WT1 levels (5 logs) with a median WT1 expression close to that of normal BM. WT1 expression in childhood T-ALL was significantly higher than in BCP-ALL (P<0.001). Patients with MLL-AF4 translocation showed high WT1 overexpression (P<0.01) compared to patients with other or no chromosomal aberrations. Older children (> or =10 years) expressed higher WT1 levels than children under 10 years of age (P<0.001), while there was no difference in WT1 expression in patients with peripheral blood leukocyte count (WBC) > or =50 x 10(9)/l and lower. Analysis of relapsed cases (14/125) indicated that an abnormal increase or decrease in WT1 expression was associated with a significantly increased risk of relapse (P=0.0006), and this prognostic impact of WT1 was independent of other main risk factors (P=0.0012). In summary, our study suggests that WT1 expression in childhood ALL is very variable and much lower than in AML or adult ALL. WT1, thus, will not be a useful marker for MRD detection in childhood ALL, however, it does represent a potential independent risk factor in childhood ALL. Interestingly, a proportion of childhood ALL patients express WT1 at levels below the normal physiological BM WT1 expression, and this reduced WT1 expression appears to be associated with a higher risk of relapse.

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In this paper we identify requirements for choosing a threat modelling formalisation for modelling sophisticated malware such as Duqu 2.0. We discuss the gaps in current formalisations and propose the use of Attack Trees with Sequential Conjunction when it comes to analysing complex attacks. The paper models Duqu 2.0 based on the latest information sourced from formal and informal sources. This paper provides a well structured model which can be used for future analysis of Duqu 2.0 and related attacks.

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Partially ordered preferences generally lead to choices that do not abide by standard expected utility guidelines; often such preferences are revealed by imprecision in probability values. We investigate five criteria for strategy selection in decision trees with imprecision in probabilities: “extensive” Γ-maximin and Γ-maximax, interval dominance, maximality and E-admissibility. We present algorithms that generate strategies for all these criteria; our main contribution is an algorithm for Eadmissibility that runs over admissible strategies rather than over sets of probability distributions.

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Existing compact routing schemes, e.g., Thorup and Zwick [SPAA 2001] and Chechik [PODC 2013], often have no means to tolerate failures, once the system has been setup and started. This paper presents, to our knowledge, the first self-healing compact routing scheme. Besides, our schemes are developed for low memory nodes, i.e., nodes need only O(log2 n) memory, and are thus, compact schemes.
We introduce two algorithms of independent interest: The first is CompactFT, a novel compact version (using only O(log n) local memory) of the self-healing algorithm Forgiving Tree of Hayes et al. [PODC 2008]. The second algorithm (CompactFTZ) combines CompactFT with Thorup-Zwick’s treebased compact routing scheme [SPAA 2001] to produce a fully compact self-healing routing scheme. In the self-healing model, the adversary deletes nodes one at a time with the affected nodes self-healing locally by adding few edges. CompactFT recovers from each attack in only O(1) time and ∆ messages, with only +3 degree increase and O(log∆) graph diameter increase, over any sequence of deletions (∆ is the initial maximum degree).
Additionally, CompactFTZ guarantees delivery of a packet sent from sender s as long as the receiver has not been deleted, with only an additional O(y log ∆) latency, where y is the number of nodes that have been deleted on the path between s and t. If t has been deleted, s gets informed and the packet removed from the network.