2,127 research outputs found
Throughput Maximization in the Speed-Scaling Setting
We are given a set of jobs and a single processor that can vary its speed
dynamically. Each job is characterized by its processing requirement
(work) , its release date and its deadline . We are also given
a budget of energy and we study the scheduling problem of maximizing the
throughput (i.e. the number of jobs which are completed on time). We propose a
dynamic programming algorithm that solves the preemptive case of the problem,
i.e. when the execution of the jobs may be interrupted and resumed later, in
pseudo-polynomial time. Our algorithm can be adapted for solving the weighted
version of the problem where every job is associated with a weight and
the objective is the maximization of the sum of the weights of the jobs that
are completed on time. Moreover, we provide a strongly polynomial time
algorithm to solve the non-preemptive unweighed case when the jobs have the
same processing requirements. For the weighted case, our algorithm can be
adapted for solving the non-preemptive version of the problem in
pseudo-polynomial time.Comment: submitted to SODA 201
Optimal Data Placement on Networks With Constant Number of Clients
We introduce optimal algorithms for the problems of data placement (DP) and
page placement (PP) in networks with a constant number of clients each of which
has limited storage availability and issues requests for data objects. The
objective for both problems is to efficiently utilize each client's storage
(deciding where to place replicas of objects) so that the total incurred access
and installation cost over all clients is minimized. In the PP problem an extra
constraint on the maximum number of clients served by a single client must be
satisfied. Our algorithms solve both problems optimally when all objects have
uniform lengths. When objects lengths are non-uniform we also find the optimal
solution, albeit a small, asymptotically tight violation of each client's
storage size by lmax where lmax is the maximum length of the objects
and some arbitrarily small positive constant. We make no assumption
on the underlying topology of the network (metric, ultrametric etc.), thus
obtaining the first non-trivial results for non-metric data placement problems
More than a Hundred Years in the Search for an Accurate Diagnosis for Chagas Disease: Current Panorama and Expectations
Chagas disease, or American trypanosomiasis, is a parasitic disease of the Americas. In nature, Trypanosoma cruzi is transmitted through various species of triatomine bugs. However, non-vectorial transmission can also occur, such as transmission through blood products or by transplanting infected organs, by vertical transmission, and lately by oral route. Currently, Chagas disease affects approximately 6–7 million people worldwide, and the process of urbanization in Latin America and migratory movements from endemic countries have led to Chagas disease being diagnosed in areas where the infection is not endemic. There are several methods for diagnosing Chagas disease. Some of these are mostly used for research purposes, while others are used in routine diagnostic laboratories. According to the World Health Organization (WHO), chronic Chagas disease diagnosis is based on two serological techniques. To establish a definitive diagnosis, the results must be concordant. In the case of discordances, the WHO proposes repeating serology in a new sample, and if results remain inconclusive, a confirmatory test should be performed. This chapter shows aspects of the diagnosis of Chagas disease, which varies in its sensitivity and specificity, and its use depends on the geographical location, the available resources, and the purpose of the diagnosis
Parameterized Power Vertex Cover
We study a recently introduced generalization of the Vertex Cover (VC)
problem, called Power Vertex Cover (PVC). In this problem, each edge of the
input graph is supplied with a positive integer demand. A solution is an
assignment of (power) values to the vertices, so that for each edge one of its
endpoints has value as high as the demand, and the total sum of power values
assigned is minimized. We investigate how this generalization affects the
parameterized complexity of Vertex Cover. On the positive side, when
parameterized by the value of the optimal P, we give an O*(1.274^P)-time
branching algorithm (O* is used to hide factors polynomial in the input size),
and also an O*(1.325^P)-time algorithm for the more general asymmetric case of
the problem, where the demand of each edge may differ for its two endpoints.
When the parameter is the number of vertices k that receive positive value, we
give O*(1.619^k) and O*(k^k)-time algorithms for the symmetric and asymmetric
cases respectively, as well as a simple quadratic kernel for the asymmetric
case. We also show that PVC becomes significantly harder than classical VC when
parameterized by the graph's treewidth t. More specifically, we prove that
unless the ETH is false, there is no n^o(t)-time algorithm for PVC. We give a
method to overcome this hardness by designing an FPT approximation scheme which
gives a (1+epsilon)-approximation to the optimal solution in time FPT in
parameters t and 1/epsilon.Comment: Short version presented at the conference WG 2016, Graph-Theoretic
Concepts in Computer Science, LNCS 994
Oceanographic processes shape genetic signatures of planktonic cephalopod paralarvae in two upwelling regions
The planktonic paralarval stage of cephalopods (octopus, squids and cuttlefishes) is an important dispersal phase, particularly of benthic species, that lasts from days to months. Cephalopod paralarvae modify their vertical position in the water in upwelling ecosystems and such behaviour influences their spatial distribution and genetic structure, but to what extent? In this work specific water masses were sampled with Lagrangian buoys in two contrasting upwelling systems (Iberian Peninsula and Morocco) of the Iberian-Canary current eastern boundary upwelling (ICC) in order to: (i) identify the cephalopod assemblage in the different upwelling systems (ii) define their planktonic dispersal patterns and (iii) analyse the effect of different dispersal patterns on genetic structure and connectivity. Cephalopod paralarvae were identified using the cytochrome c oxidase subunit I gene (COI), revealing 21 different species and F-st values showed no population structure between both upwelling systems. Cephalopod species richness was two times higher in the Moroccan upwelling than in the Iberian Peninsula, with an undescribed Ancistrocheiridae species identified in Moroccan waters. Three common planktonic dispersal patterns were identified in the ICC: coastal, coastal-oceanic and oceanic. Coastal and oceanic dispersal patterns favoured spatio-temporal paralarval retention or "schooling" of different cohorts over the continental shelf and continental slope in 9 and 11 species, respectively. Such spatio-temporal retention was reflected in the complex haplotype networks and high nucleotide/haplotype diversity recorded for these two groups. The only cephalopod species displaying a coastal-oceanic dispersal pattern was Octopus vulgaris, where low nucleotide and haplotype diversity was observed. The observed decline in genetic structure resulted from the dispersal of similar cohorts within upwelling currents and upwelling filaments to the oceanic realm. Seascape analysis revealed that cephalopod paralarvae from two coastal upwelling ecosystems of the ICC display three planktonic dispersal patterns with contrasting distributions and signatures at the genetic level
- …