Fixed-parameter tractability of multicut parameterized by the size of the cutset

Given an undirected graph $G$, a collection $\{(s_1,t_1),..., (s_k,t_k)\}$ of pairs of vertices, and an integer $p$, the Edge Multicut problem ask if there is a set $S$ of at most $p$ edges such that the removal of $S$ disconnects every $s_i$ from the corresponding $t_i$. Vertex Multicut is the analogous problem where $S$ is a set of at most $p$ vertices. Our main result is that both problems can be solved in time $2^{O(p^3)}... n^{O(1)}$, i.e., fixed-parameter tractable parameterized by the size $p$ of the cutset in the solution. By contrast, it is unlikely that an algorithm with running time of the form $f(p)... n^{O(1)}$ exists for the directed version of the problem, as we show it to be W[1]-hard parameterized by the size of the cutset

ARIA 2016 : Care pathways implementing emerging technologies for predictive medicine in rhinitis and asthma across the life cycle

European Innovation Partnership on Active and Healthy Ageing Reference Site MACVIA-France, EU Structural and Development Fund Languedoc-Roussillon, ARIA.Peer reviewedPublisher PD

The hidden burden of adult allergic rhinitis : UK healthcare resource utilisation survey

Funding Funding for this survey was provided by Meda Pharma.Peer reviewedPublisher PD

Characteristics of patients receiving allergy vaccination: to which extent do socio-economic factors play a role?

Background: Little is known about characteristics of patients receiving allergen-specific immunotherapy. Identifying obstacles to appropriate treatment according to guidelines may facilitate the development of strategies aiming at improved treatment of patients with allergic respiratory diseases. The objective of this study was to investigate differences in disease severity, demographic and socioeconomic status between allergic rhinitis patients receiving allergen-specific immunotherapy and allergic rhinitis patients not receiving allergen-specific immunotherapy. Methods: A total of 366 patients were studied of whom 210 were going to receive subcutaneously administrated immunotherapy (SIT) against grass pollen and/or house dust mite allergy. The severity of rhino-conjunctivitis (hay fever) and/or asthma was classified according to international guidelines. The questionnaires included an EQ-5D visual analogue scale instrument and some socio-economic questions. Results: Severity of disease, young age, high level of education as well as greater perceived impairment of health-related quality of life due to allergic symptoms were significantly associated with use of SIT. Somewhat unexpectedly, household income was not associated with use of SIT. Conclusion: Use of SIT was associated with both disease severity measures and educational level, but not income level. These results suggest social inequality as reflected by lower use of SIT among patients with lower educational level may represent an obstacle to treatment with SIT

Identification of a regulated pathway for nuclear pre-mRNA turnover

We have identified a nuclear pathway that rapidly degrades unspliced pre-mRNAs in yeast. This involves 3′→5′ degradation by the exosome complex and 5′→3′ degradation by the exonuclease Rat1p. 3′→5′ degradation is normally the major pathway and is regulated in response to carbon source. Inhibition of pre-mRNA degradation resulted in increased levels of pre-mRNAs and spliced mRNAs. When splicing was inhibited by mutation of a splicing factor, inhibition of turnover resulted in 20- to 50-fold accumulation of pre-mRNAs, accompanied by increased mRNA production. Splicing of a reporter construct with a 3′ splice site mutation was also increased on inhibition of turnover, showing competition between degradation and splicing. We propose that nuclear pre-mRNA turnover represents a novel step in the regulation of gene expression

A Cost-based Optimizer for Gradient Descent Optimization

As the use of machine learning (ML) permeates into diverse application domains, there is an urgent need to support a declarative framework for ML. Ideally, a user will specify an ML task in a high-level and easy-to-use language and the framework will invoke the appropriate algorithms and system configurations to execute it. An important observation towards designing such a framework is that many ML tasks can be expressed as mathematical optimization problems, which take a specific form. Furthermore, these optimization problems can be efficiently solved using variations of the gradient descent (GD) algorithm. Thus, to decouple a user specification of an ML task from its execution, a key component is a GD optimizer. We propose a cost-based GD optimizer that selects the best GD plan for a given ML task. To build our optimizer, we introduce a set of abstract operators for expressing GD algorithms and propose a novel approach to estimate the number of iterations a GD algorithm requires to converge. Extensive experiments on real and synthetic datasets show that our optimizer not only chooses the best GD plan but also allows for optimizations that achieve orders of magnitude performance speed-up.Comment: Accepted at SIGMOD 201

The PseudoDojo: Training and grading a 85 element optimized norm-conserving pseudopotential table

First-principles calculations in crystalline structures are often performed with a planewave basis set. To make the number of basis functions tractable two approximations are usually introduced: core electrons are frozen and the diverging Coulomb potential near the nucleus is replaced by a smoother expression. The norm-conserving pseudopotential was the first successful method to apply these approximations in a fully ab initio way. Later on, more efficient and more exact approaches were developed based on the ultrasoft and the projector augmented wave formalisms. These formalisms are however more complex and developing new features in these frameworks is usually more difficult than in the norm-conserving framework. Most of the existing tables of norm- conserving pseudopotentials, generated long ago, do not include the latest developments, are not systematically tested or are not designed primarily for high accuracy. In this paper, we present our PseudoDojo framework for developing and testing full tables of pseudopotentials, and demonstrate it with a new table generated with the ONCVPSP approach. The PseudoDojo is an open source project, building on the AbiPy package, for developing and systematically testing pseudopotentials. At present it contains 7 different batteries of tests executed with ABINIT, which are performed as a function of the energy cutoff. The results of these tests are then used to provide hints for the energy cutoff for actual production calculations. Our final set contains 141 pseudopotentials split into a standard and a stringent accuracy table. In total around 70.000 calculations were performed to test the pseudopotentials. The process of developing the final table led to new insights into the effects of both the core-valence partitioning and the non-linear core corrections on the stability, convergence, and transferability of norm-conserving pseudopotentials. ...Comment: abstract truncated, 17 pages, 25 figures, 8 table