Variations on an ordering theme with constraints

We investigate the problem of nding a total order of a nite set that satis es various local ordering constraints. Depending on the admitted constraints, we provide an e cient algorithm or prove NP-completeness. We discuss several generalisations and systematically classify the problems4th IFIP International Conference on Theoretical Computer ScienceRed de Universidades con Carreras en Informática (RedUNCI

Randomized QuickSort and the Entropy of the Random Source

The worst-case complexity of an implementation of Quicksort depends on the random number generator that is used to select the pivot elements. In this paper we estimate the expected number of comparisons of Quicksort as a function in the entropy of the random source. We give upper and lower bounds and show that the expected number of comparisons increases from $nlog n$ to $n^2$, if the entropy of the random source is bounded. As examples we show explicit bounds for distributions with bounded min-entropy and the geometrical distribution

Variations on an ordering theme with constraints

We investigate the problem of nding a total order of a nite set that satis es various local ordering constraints. Depending on the admitted constraints, we provide an e cient algorithm or prove NP-completeness. We discuss several generalisations and systematically classify the problems4th IFIP International Conference on Theoretical Computer ScienceRed de Universidades con Carreras en Informática (RedUNCI

Multi-Objective Parameter Selection for Classifiers

Setting the free parameters of classifiers to different values can have a profound impact on their performance. For some methods, specialized tuning algorithms have been developed. These approaches mostly tune parameters according to a single criterion, such as the cross-validation error. However, it is sometimes desirable to obtain parameter values that optimize several concurrent - often conflicting - criteria. The TunePareto package provides a general and highly customizable framework to select optimal parameters for classifiers according to multiple objectives. Several strategies for sampling and optimizing parameters are supplied. The algorithm determines a set of Pareto-optimal parameter configurations and leaves the ultimate decision on the weighting of objectives to the researcher. Decision support is provided by novel visualization techniques

Siglec-6 is a novel target for CAR T-cell therapy in acute myeloid leukemia

Acute myeloid leukemia (AML) is an attractive entity for the development of chimeric antigen receptor (CAR) T-cell immunotherapy because AML blasts are susceptible to T-cell–mediated elimination. Here, we introduce sialic acid–binding immunoglobulin-like lectin 6 (Siglec-6) as a novel target for CAR T cells in AML. We designed a Siglec-6–specific CAR with a targeting domain derived from the human monoclonal antibody JML-1. We found that Siglec-6 is commonly expressed on AML cell lines and primary AML blasts, including the subpopulation of AML stem cells. Treatment with Siglec-6 CAR T cells confers specific antileukemia reactivity that correlates with Siglec-6 expression in preclinical models, including induction of complete remission in a xenograft AML model in immunodeficient mice (NSG/U937). In addition, we confirmed Siglec-6 expression on transformed B cells in chronic lymphocytic leukemia (CLL), and specific anti-CLL reactivity of Siglec-6 CAR T cells in vitro. Of particular interest, we found that Siglec-6 is not detectable on normal hematopoietic stem and progenitor cells (HSPCs) and that treatment with Siglec-6 CAR T cells does not affect their viability and lineage differentiation in colony-formation assays. These data suggest that Siglec-6 CAR T-cell therapy may be used to effectively treat AML without the need for subsequent allogeneic hematopoietic stem cell transplantation. In mature normal hematopoietic cells, we detected Siglec-6 in a proportion of memory (and naïve) B cells and basophilic granulocytes, suggesting the potential for limited on-target/off-tumor reactivity. The lack of expression of Siglec-6 on normal HSPCs is a key to differentiating it from other Siglec family members (eg, Siglec-3 [CD33]) and other CAR target antigens (eg, CD123) that are under investigation in AML, and it warrants the clinical investigation of Siglec-6 CAR T-cell therapy

Non-orographic gravity waves and turbulence caused by merging jet streams

Jet streams are important sources of non-orographic internal gravity waves and clear air turbulence (CAT). We analyze non-orographic gravity waves and CAT during a merger of the polar front jet stream (PFJ) with the subtropical jet stream (STJ) above the southern Atlantic. Thereby, we use a novel combination of airborne observations covering the meso-scale and turbulent scale in combination with high-resolution deterministic short-term forecasts. Coherent phase lines of temperature perturbations by gravity waves stretching along a highly sheared tropopause fold are simulated by the ECMWF IFS (integrated forecast system) forecasts. During the merging event, the PFJ reverses its direction from approximately antiparallel to parallel with respect to the STJ, going along with strong wind shear and horizontal deformation. Temperature perturbations in limb-imaging and lidar observations onboard the research aircraft HALO during the SouthTRAC campaign show remarkable agreement with the IFS data. Ten hours earlier, the IFS data show an “X-shaped” pattern in the temperature perturbations emanating from the sheared tropopause fold. Tendencies of the IFS wind components show that these gravity waves are excited by spontaneous emission adjusting the strongly divergent flow when the PFJ impinges the STJ. In situ observations of temperature and wind components at 100 Hz confirm upward propagation of the probed portion of the gravity waves. They furthermore reveal embedded episodes of light-to-moderate CAT, Kelvin Helmholtz waves, and indications for partial wave reflection. Patches of low Richardson numbers in the IFS data coincide with the CAT observations, suggesting that this event was accessible to turbulence forecasting

On the influence of non-perfect randomness on probabilistic algorithms

In modern computer science, many problems are solved with the help of probabilistic algorithms. This thesis concentrates on the analysis of algorithms with respect to the employment of random sources that do not provide perfect random numbers, like pseudorandom generators or biased sources. New theoretical results are presented that describe implications of using non-perfect random numbers with probabilistic algorithms. The theoretical part of this thesis considers several probabilistic algorithms: For a basic randomized algorithm for comparing polynomials, it is shown that repeating the algorithm several times does not always decrease its error probability to the same extent, depending on the pseudorandom generator. For Karger´s probabilistic algorithm for finding the minimum cut of a graph, it is shown how the algorithm can be adapted to a non-uniform source of randomness. This is shown for the basic version as well as for the more sophisticated version with two recursive calls. For the random walk algorithm for the Boolean Satisfiability Problem, it is demonstrated how a bias from the uniform distribution of the random numbers influences the error probability of the algorithm. For the Randomized Quicksort algorithm, a lower bound for the number of comparisons is given, based on the distribution on the choice of the pivot elements. The experimental part of this thesis examines the impact of various sources of randomness on the quality of the solution of probabilistic optimization heuristics, concentrating on Simulated Annealing as a representant for local search heuristics and a genetic algorithm as a representant for population based heuristics. As a reference source of randomness, bits provided with the help of a quantum theoretic experiment are used. The results of the experiments show significant differences between the influence of non-perfect randomness on the Simulated Annealing heuristic and a genetic algorithm

Constrained ordering

We investigate the problem of finding a total order of a finite set that satisfies various local ordering constraints. Depending on the admitted constraints, we provide an efficient algorithm or prove NP-completeness. To this end, we define a reduction technique and discuss its properties

On the different notions of pseudorandomness

This article explains the various notions of pseudorandomness, like Martin-L öf randomness, Kolmogorov complexity, Shannon entropy and quasi-randomness. We describe interconnections between these notions and describe how the non-computable notions among them are relaxed and used in practice, for example in statistics or cryptography. We give examples for pseudorandom generators relating to these notions and list some dependencies between the quality of pseudorandom numbers and its impact on some properties of randomized algorithms using them

Electronic Colloquium on Computational Complexity, Report No. 59 (2004) Randomized Quicksort and the Entropy of the Random Number Generator

The worst-case complexity of an implementation of Quicksort depends on the random number generator that is used to select the pivot elements. In this paper we estimate the expected number of comparisons of Quicksort as a function in the entropy of the random source. We give upper and lower bounds and show that the expected number of comparisons increases from n log n to n 2, if the entropy of the random source is bounded. As examples we show explicit bounds for distributions with bounded min-entropy, the geometrical distribution and the δ-random source.